United States

Environmental Protection

Agency

Office of Water

(4303)

EPA

EPA 821-R-00-004

March 2000

Economic Assessment for the Final

Action Regarding Pretreatment

Standards for the Industrial Laundries

Point Source Category

(Revised March 2000)
ECONOMIC ASSESSMENT FOR THE FINAL ACTION

REGARDING PRETREATMENT STANDARDS FOR THE 

INDUSTRIAL LAUNDRIES POINT SOURCE CATEGORY

(REVISED MARCH 2000)

FINAL REPORT

Carol M. Browner

Administrator

J. Charles Fox

Assistant Administrator, Office of Water

Sheila Frace

Director, Engineering and Analysis Division

Marvin B. Rubin

Chief, Energy Branch

George Denning

Work Assignment Manager

Engineering and Analysis Division

Office of Science and Technology

U.S. Environmental Protection Agency

Washington, D.C. 20460
FOREWORD

This document delineates the economic assessment of the final action regarding pretreatment

standards for the Industrial Laundries Point Source Category. Based on revised analytical data for

semivolatile organic compounds for two sampling episodes conducted in 1996 and 1998, EPA revised

the document entitled Technical Development Document for the Final Action Regarding

Pretreatment Standards for the Industrial Laundries Categorical Point Source Category in March

2000. Section One, Executive Summary, Table 1-1 and Section 1.10, have been revised to reflect the

changes in benefits calculated as a result of the change in pollution reduction. Footnote 1 in Section One

and Section Two, Data Sources, have been revised to reflect the change in the reference title and EPA

document number. Section 10.2, as well as Tables 10-2 and 10-3, have been revised to reflect a

change in the benefits calculated as a result of the change in pollution reduction, and to provide Docket

Numbers for some references. Minor editorial changes also were made on pages 6-4 and 6-5.
ACKNOWLEDGMENT

This report has been reviewed and approved for publication by the Engineering and

Analysis Division, Office of Science and Technology. This report was prepared with the support

of Eastern Research Group, Inc. (Contract No. 68-C6-0022), under the direction and review of

the Office of Science and Technology.
i

CONTENTS

Page

SECTION ONE EXECUTIVE SUMMARY .................................. 1-1

1.1 Introduction ...................................................... 1-1

1.2 Sources of Data ................................................... 1-3

1.3 Profile of the Industry ............................................... 1-3

1.4 Annualized Costs of Compliance ....................................... 1-5

1.5 Facility-Level Analysis .............................................. 1-6

1.6 Firm Failure Analysis ............................................... 1-8

1.7 Industry, National and Regional Impacts on Employment and Impacts on 

National-Level Output ............................................... 1-9

1.8 Other Secondary Impacts ........................................... 1-11

1.9 Small Business Impacts ............................................. 1-12

1.10 Cost-Benefit Analysis .............................................. 1-13

SECTION TWO DATA SOURCES ......................................... 2-1

2.1 The 1994 Industrial Laundries Industry Detailed Questionnaire ................ 2-1

2.2 Government Data Sources ............................................ 2-3

2.3 Other Sources ..................................................... 2-4

SECTION THREE INDUSTRY PROFILE ..................................... 3-1

3.1 Introduction ...................................................... 3-1

3.2 Overview of the Industrial Laundries Industry ............................. 3-2
Page

ii

3.2.1 Services Provided .......................................... 3-2

3.2.2 Industry Processes ......................................... 3-11

3.2.3 Classification of Facilities Performing Industrial Laundering ......... 3-13

3.3 The Structure of the Industrial Laundries Industry ......................... 3-17

3.3.1 Numbers and Types of Facilities and Firms ...................... 3-17

3.3.2 The Market for Industrial Laundering Services ................... 3-20

3.3.3 Growth and the Industry’s Trajectory .......................... 3-27

3.4 Industry Demographics ............................................. 3-31

3.4.1 All Industrial Laundry Facilities .............................. 3-31

3.4.2 Industrial Laundry Facilities that Meet Cutoffs Considered by EPA 

for an Exclusion from a Rule ................................. 3-43

3.4.3 Financial Conditions at the Firm Level .......................... 3-45

SECTION FOUR ECONOMIC IMPACT ANALYSIS METHODOLOGY 

OVERVIEW AND COMPLIANCE COST ANALYSIS ........... 4-1

4.1 Methodology Overview .............................................. 4-1

4.2 Cost Annualization Model ............................................ 4-3

4.2.1 Purpose of Cost Annualization ................................. 4-3

4.2.2 Inputs, Assumptions, and Model Outputs ......................... 4-4

4.3 Total Annualized Compliance Costs ................................... 4-11

SECTION FIVE ANALYSIS OF FACILITY-LEVEL IMPACTS ................. 5-1

5.1 Facility Impact Model ............................................... 5-3

5.1.1 Estimating the Present Value of Forecasted Cash Flow ............... 5-4
Page

iii

5.1.2 Evaluating Impacts ......................................... 5-7

5.2 Results ....................................................... 5-10

5.2.1 Baseline Closures ......................................... 5-10

5.2.2 Postcompliance Closures .................................... 5-12

5.3 Impacts on New Sources ............................................ 5-15

SECTION SIX ANALYSIS OF FIRM-LEVEL IMPACTS ..................... 6-1

6.1 Ratio Analysis Methodology .......................................... 6-3

6.2 Evaluating Baseline and Postcompliance Ratios ............................ 6-7

6.2.1 Baseline Analysis .......................................... 6-7

6.2.2 Postcompliance Analysis ..................................... 6-8

6.3 Baseline and Postcompliance Altman Z”-Score Results ..................... 6-11

6.3.1 Baseline Altman Z”-Score Results ............................. 6-11

6.3.2 Postcompliance Altman Z”-Score Results — “Bankruptcy Likely” ..... 6-13

6.3.3 Postcompliance Altman Z”-Score Results — Change from 

Healthy to Indeterminate Status ............................... 6-13

SECTION SEVEN INDUSTRY, NATIONAL, AND REGIONAL EMPLOYMENT

IMPACTS AND TOTAL NATIONAL OUTPUT LOSSES ........ 7-1

7.1 Industry-Level Employment Losses from Facility Closures and Firm Failures ..... 7-4

7.2 National-Level Output and Employment Impacts ........................... 7-7

7.2.1 Introduction ............................................... 7-7

7.2.2 Methodology for Estimating National-Level Output 

and Employment Impacts ..................................... 7-7

7.2.3 National-Level Output and Employment Impacts .................. 7-10
Page

iv

7.3 Direct Longer-Term Employment Impacts in the Industrial 

Laundries Industry ............................................... . 7-18

7.3.1 Methodology for Estimating Longer-Term Impacts

on Employment .......................................... . 7-18

7.3.2 Longer-Term Employment Impacts ........................... . 7-20

7.4 Regional Employment Impacts ...................................... . 7-24

7.4.1 Introduction ............................................. . 7-24

7.4.2 Regional-Level Impacts Methodology ......................... . 7-24

7.4.3 Results of the Regional-Level Community Impact Analysis ......... . 7-26

SECTION EIGHT OTHER IMPACTS ....................................... . 8-1

8.1 Introduction ..................................................... . 8-1

8.2 Impacts on Markets ................................................ . 8-1

8.2.1 Impacts on Foreign Markets/Trade ............................ . 8-1

8.2.2 Impacts on Domestic Markets ................................ . 8-2

8.3 Impacts on Industrial Laundries Customers .............................. . 8-3

8.3.1 Financial Profile of the Customer Base ......................... . 8-3

8.3.2 Impacts of Price Increases on Customers ........................ . 8-5

8.4 Impacts of a Decision not to Regulate the Industrial Laundries Industry Under

Pretreatment Standards on the Market for Disposables ..................... . 8-10

8.5 Impacts on Consolidation in the Industrial Laundries Industry ............... . 8-11

8.6 Impacts on Other Establishments that Might Launder Industrial Textile Items ... . 8-12

8.7 Impacts on Inflation .............................................. . 8-12

8.8 Distributional Impacts and Environmental Justice ........................ . 8-13
Page

v

SECTION NINE SMALL BUSINESS ANALYSIS ............................ . 9-1

9.1 Introduction ..................................................... . 9-1

9.2 Small Business Analysis Components .................................. . 9-1

9.2.1 Need for and Objectives of the Rule ............................ . 9-2

9.2.2 Significant Issues Raised by Public Comment .................... . 9-2

9.2.3 Steps Used to Minimize Impacts .............................. . 9-4

9.2.4 Estimated Number of Small Business Entities to Which the 

Regulation Would Have Applied .............................. . 9-5

9.2.5 Description of Reporting, Recordkeeping, and Other Compliance

Requirements ............................................ . 9-7

SECTION TEN COSTS AND BENEFITS OF EPA’S DECISION .............. . 10-1

10.1 Requirements of Executive Order 12866 and the Unfunded Mandates 

Reform Act (UMRA) ............................................. . 10-1

10.2 Costs and Benefits of Regulatory Options .............................. . 10-3

10.2.1 Total Social Costs ........................................ . 10-3

10.2.2 Benefits ................................................ . 10-3

10.2.3 Comparison of Costs and Benefits ............................ . 10-6

APPENDIX A MARKET MODEL METHODOLOGY AND RESULTS ....... . A-1

A.1 Overview of the Industrial Laundries Market Model ...................... . A-1

A.2 Preregulatory Market Conditions ..................................... . A-4

A.2.1 Market Supply and Demand Equations and Market 

Equilibrium Conditions .................................... . A-5

A.2.2 Supply and Demand Variables ............................... . A-7
Page

vi

A.3 Postregulatory Market Conditions ..................................... A-15

A.3.1 Estimating Incremental Pollution Control Costs ................... A-15

A.3.2 Estimating Postregulatory Price and Quantity .................... A-17

A.3.3 Estimating the Percentage CPT and Applying it to the 

Closure Model ............................................ A-18

A.4 Market Model Results .............................................. A-19

A.4.1 Preregulatory Market Results ................................ A-19

A.4.2 Postregulatory Market Results ............................... A-23

A.5 Results of the Impact Analysis using the Market Model Results ............... A-25

A.5.1 Results of the Facility Closure Analysis Assuming Costs Can Be 

Passed Through ........................................... A-26

A.5.2 Results of the Firm Failure Analysis Assuming Costs Can Be 

Passed Through ........................................... A-26

APPENDIX B ADDITIONAL DISCUSSION OF ASSUMPTIONS USED OR

CONSIDERED FOR USE IN THE COST ANNUALIZATION 

MODEL ................................................ . B-1

B.1 Financial Assumptions ............................................. . B-1

B.1.1 Depreciation Method ....................................... . B-1

B.1.2 Timing Between Initial Investment and Operation ................. . B-6

B.1.3 Depreciable Lifetime for the Equipment ......................... . B-6

B.1.4 Tax Shields on Interest Payments .............................. . B-7

B.1.5 Discount Rates ........................................... . B-7

B.2 Average State Tax Rate ............................................ . B-9

B.3 Cost Annualization Model and Total Cost Assessment ..................... . B-10
Page

vii

APPENDIX C RESULTS OF THE FACILITY CLOSURE ANALYSIS AND 

FIRM FAILURE ANALYSIS UNDER THE DAF-IL OPTION .... C-1

APPENDIX D RESULTS OF THE BASELINE AND POSTCOMPLIANCE 

CLOSURE ANALYSIS ASSUMING SALVAGE VALUE PLAYS 

A ROLE IN CLOSURE DECISIONS ........................ D-1

D.1 Closure Analysis Assuming Salvage Value Plays a Role in 

the Decision ............................................. D-2

D.2 Results of a Baseline Analysis Assuming that Salvage Value 

Equals Market Value ....................................... D-3
viii

TABLES

Table Page

1-1 Summary of Costs, Impacts, and Benefits for the CP-IL Option, by Cutoff ............ 1-2

2-1 Conversion From SIC to NAICs Code ....................................... 2-4

3-1 The Top 15 Customer Industries for Industrial Launderers, for All Products ........... 3-5

3-2 Percentage of Total Customer Base Renting Each Type of Product .................. 3-7

3-3 Textiles Laundered by Industrial Laundries ................................... 3-8

3-4 Primary and Secondary SIC Codes Reported by Industrial Laundries ............... 3-15

3-5 Number of Firms and Facilities, by Chain of Ownership ......................... 3-21

3-6 Actual 1994 Employment and Projected 2005 Employment in the Top Customer 

Industries for Industrial Launderers in 1995 .................................. 3-30

3-7 Number of Facilities by Annual Production .................................. 3-32

3-8 Volume of Textiles Laundered by Industrial Laundries, by Type of Textile and 

Production Group ...................................................... 3-33

3-9 Number of Facilities by Annual Flow ....................................... 3-35

3-10 Number of Facilities by Employment Group .................................. 3-36

3-11 Average and Total Number of Employees for Facilities In Each Production Group ..... 3-38

3-12 Number of Nonindependent and Single Facilities, Average Revenues, and 

Average Operating Costs for Each Revenue Group ............................. 3-39

3-13 Average and Total Revenues and Operating Costs for Facilities in each 

Production Group ...................................................... 3-40

3-14 Number of Multifacility Firms and Average Revenues for Each Revenue Group ....... 3-41

3-15 Comparison of Facilities Meeting Cutoffs Considered Compared to the 

No-Cutoff Scenario .................................................... 3-44

3-16 Number of Firms and Average Financial Measures for Each Revenue Group ......... 3-47
Table Page

ix

4-1 The Regulatory Options ................................................. . 4-6

4-2 Sample Spreadsheet for Annualizing Costs ................................... . 4-7

4-3 Compliance Costs for the Regulatory Options ................................ . 4-12

5-1 Baseline Closure Analysis - All Facilities ................................... . 5-11

5-2 Facility Closure Analysis - Single-Facility Firms ............................. . 5-13

5-3 Facility Closure Analysis - Nonindependent Facilities .......................... . 5-14

5-4 Facility Closure Analysis - All Facilities .................................... . 5-16

6-1 Baseline Firm Failure Analysis - All Firms .................................. . 6-12

6-2 Firm Failure Analysis - Single-Facility Firms ................................ . 6-14

6-3 Firm Failure Analysis - Multifacility Firms .................................. . 6-15

6-4 Firm Failure Analysis - All Firms ......................................... . 6-16

6-5 Indeterminate Analysis - All Firms ........................................ . 6-17

7-1 Net Employment Losses in the U.S. Economy Based on Closures and Failures

in the Industrial Laundries Industry ........................................ . 7-6

7-2 Annual National-Level Output Losses ..................................... . 7-12

7-3 Annual National-Level Output Gains ...................................... . 7-13

7-4 Net Annual National-Level Output Losses .................................. . 7-14

7-5 National-Level Employment Losses ....................................... . 7-15

7-6 National-Level Employment Gains ........................................ . 7-16

7-7 Net Annual National-Level Employment Losses Based on Output ................. . 7-17

7-8 Direct Employment Losses in the Industrial Laundries Industry Based on 

Output Losses Assuming Zero Cost Passthrough ............................. . 7-21

7-9 Direct Employment Losses in the Industrial Laundries Industry Based on 

Market Model Predictions of Production Losses .............................. . 7-23
Table Page

x

7-10 Facility-by Facility Employment Loss ...................................... . 7-27

8-1 Average Financial Statistics for Active Corporations in 14 Industrial 

Laundries Customer Industries ............................................ . 8-4

9-1 Number of Firms and Average Financial Measures, by Firm Size .................. . 9-8

10-1 Approximate Total Annual Social Costs of the CP-IL Regulatory Option 

and Cutoffs ......................................................... . 10-4

10-2 Monetized Benefits by Category .......................................... . 10-7

10-3 A Comparison of Annual Cost and Monetized Benefits of the CP-IL Option ......... . 10-8

A-1 Data Used to Estimate the Industrial Laundry Supply and Demand Curves .......... . A-8

A-2 Preregulatory Supply and Demand Curve Regression Results ..................... A-20

A-3 Calculation of Postcompliance Price and Quantity ............................. A-24

A-4 Cost-Passthrough Analysis: Facility Closure Analysis - All Facilities ............... A-27

A-5 Cost-Passthrough Analysis: Firm Failure Analysis - All Firms .................... A-28

B-1 Depreciation Methods: Comparison of Straight Line vs. Modified 

Accelerated Cost Recovery System ......................................... . B-3

B-2 Spreadsheet for Annualizing Costs ......................................... . B-4

B-3 Spreadsheet for Annualizing Costs Using Section 169 Provision ................... . B-5

B-4 Spreadsheet for Annualizing Costs with Interest Payments ....................... . B-8

B-5 State Income Tax Rates ................................................ . B-11

C-1 Facility Closure Analysis for the DAF-IL Option - All Facilities .................... C-2

C-2 Firm Failure Analysis for the DAF-IL Option - All Firms ......................... C-3

D-1 Baseline Closure Analysis - Nonindependent Facilities ......................... . D-4

D-2 Salvage Value Approach: Facility Closure Analysis - Nonindependent Facilities ...... . D-5

D-3 Salvage Value = Revenues: Baseline Closure Analysis - All Facilities .............. . D-7
xi

FIGURES

Figure Page

4-1 Relationships of the four principal models used in this economic analysis ............. 4-2

A-1 Pre- and postregulatory supply and demand for the industrial laundries industry ....... A-3

A-2 Industrial laundries industry preregulatory supply and demand curves ............... A-22
1-1

SECTION ONE

EXECUTIVE SUMMARY

1.1 INTRODUCTION

This Economic Assessment (EA) report evaluates the economic impacts of various regulatory

options that the U.S. Environmental Protection Agency (EPA) considered for pretreatment standards for the

industrial laundries point source category. The EA is organized into ten sections: 

# Section Two presents the major sources of data used in analyzing the regulatory options

# Section Three presents a profile of the industry

# Section Four presents an estimate of the annual aggregate cost for industrial laundry facilities

to comply with the rule using facility-level capital and operating and maintenance (O&M)

costs

# Section Five evaluates, using a financial model, compliance cost impacts on facilities’ cash

flow (closure analysis)

# Section Six evaluates, using a financial model, compliance cost impacts on the financial health

of firms in the industry (firm failure analysis) and also presents an assessment of the potential

for impact on new sources (barrier to entry)

# Section Seven presents an assessment of impacts from the regulatory options considered on

output and employment, both nationally and regionally

# Section Eight discusses impacts on employment, markets, customers, establishments other than

industrial laundries that might provide some industrial laundry services, consolidation,

inflation, distribution, and environmental justice

# Section Nine presents an analysis of the effects of compliance costs on small businesses

# Section Ten presents a brief comparison of costs and benefits of the regulatory options

Summaries of each of these sections are presented below in Sections 1.2 through 1.10. Table 1-1 presents a

summary of all costs, impacts, and benefits, by option.
1-2

Table 1-1 

Summary of Costs, Impacts, and Benefits for the CP-IL Option, by Cutoff (1993$)

Option

Annualized

Posttax

Cost 

($ million,

1993)

No. of

Facility

Closures

No. of 

Firm 

Failures

Direct

Employment 

Losses (Closures +

Failures)

Other

Secondary

Impacts

Total Social

Costs 

($ million,

1993)

Total 

Benefits 

($ million,

1993)

CP-IL 

no cutoff $128.4 106 72 5,039 Negligible $179.7 $0.07 - $0.35

CP-IL

1MM/255K $120.9 61 72 4,405 Negligible $171.3 $0.07 - $0.35

CP-IL

3MM/120K $90.8 44 0 2,261 Negligible $131.2 $0.07 - $0.35

CP-IL

5MM/255K $53.9 2 0 235 Negligible $77.4 $0.07 - $0.35

 Note: See Table 4-1 in Section Four of the EA for a detailed description of these options.
1U.S. EPA, 2000. Technical Development Document for the Final Action Regarding

Pretreatment Standards for the Industrial Point Source Category (Revised March 2000). EPA 821-R-00-

006. March.

1-3

1.2 SOURCES OF DATA

This EA presents all costs in 1993 dollars. Any costs not originally in the base year (1993) dollars

have been inflated or deflated to 1993 dollars using the Engineering News Record Construction Cost Index,

unless otherwise noted in that report (see the EA for details). The primary source of data for the economic

analysis is the 1994 Industrial Laundries Industry Detailed Questionnaire (Section 308 Survey). Other

sources include government data from the Bureau of the Census, industry trade journals, and several

preliminary surveys of the industry, including the 1989 Preliminary Data Summary for Industrial

Laundries, the 1993 Industrial Laundries Industry Screener Questionnaire, the 1994 Industrial

Laundries Supplemental Screener Questionnaire, and EPA’s Final Development Document.1

1.3 PROFILE OF THE INDUSTRY

The industrial laundries industry supplies clean uniforms and textiles to industrial, commercial,

and government customers. Industrially laundered items enhance workplace cleanliness and promote

safety, corporate identity, and company image. For the most part, industrial laundries own the goods they

process and supply them to customers on a rental basis; however, some facilities also launder customerowned uniforms and textiles, which the industry refers to as “Not Our Goods” (NOGs). Direct sales of

products can also account for a small portion of industrial laundries’ business. Uniform rentals account for

the largest portion of industrial laundries’ customer base and revenues. Other products rented include

mats, mops, shop and print towels/rags, continuous roller towels, and linen. 

In general, industrial laundries operate in local or regional markets, although there are some

“niche” laundries that specialize in handling particular items and that service customers over a relatively

wide geographic area. Furthermore, while some localities are dominated by a single firm or handful of

firms, the typical market for industrial laundering services appears to be quite competitive. 
2

 See the preamble to the Final Action. EPA also found the 5MM/255K cutoff economically

achievable.

1-4

Based on Section 308 Survey data, EPA estimates that 1,742 facilities in the United States meet its

definition of an industrial laundry. These facilities vary significantly with respect to the types and volume

of items they clean, the amount of wastewater they generate, the number of people they employ, and the

revenues they earn, among other characteristics. As a result, it is not possible to describe a “typical”

industrial laundry. In general, however, facilities that handle less than 3 million pounds of textiles per year

receive smaller profits and generate less wastewater than facilities that handle larger quantities of textiles. 

EPA investigated three cutoffs (and used a no-cutoff scenario for comparison purposes):

# A cutoff excluding all facilities laundering less than 1 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year (this

cutoff is identical to that proposed). This cutoff is called the 1MM/255K cutoff for the

purposes of this EA.

# A cutoff excluding all facilities that launder between 1 and 3 million pounds of incoming

laundry (total) and less than 120,000 pounds of shop and/or printer towels per calender

year, in addition to those facilities laundering less than 1 million pounds of incoming

laundry (total) and less than 255,000 pounds of shop and/or printer towels per calender

year. This cutoff is called the 3MM/120K cutoff for the purposes of this EA.

# A cutoff excluding all facilities laundering less than 5 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year. This

cutoff is called the 5MM/255K cutoff for the purposes of this EA.

All the facilities investigated for exclusion from a rule are small entities under the Small Business

Administration (SBA) definition of “small.” EPA has selected the 3MM/120K cutoff under the CP-IL

option as economically achievable.2 Had EPA promulgated a rule, it is this cutoff and option that would

have been implemented.

The 1,742 industrial laundry facilities are owned by an estimated 903 firms. A total of 830 of

these firms (92 percent) are single-facility firms (i.e., firms associated with a single facility). The

remaining 73 firms are multifacility firms (i.e., firms that own more than one facility). In general,

multifacility firms are larger than single-facility firms and might service multiple localities. A total of 837
1-5

of the 903 firms (93 percent) earn less than $10.5 million in revenues per year and therefore are small firms

according to SBA Guidelines. Most of these small businesses (812) are single-facility firms.

1.4 ANNUALIZED COSTS OF COMPLIANCE

Central to the EA is the cost annualization model, which uses facility-specific cost data and other

inputs to determine the annualized capital and O&M costs of improved wastewater treatment. This model

uses these costs (along with an annual compliance monitoring cost) with the industry-specific real cost of

capital (discount rate) over a 16-year analytic time frame to generate the annual cost of compliance for the

options considered. EPA chose the 16-year time frame for analysis based on the depreciable life for

equipment of this type, 15 years according to Internal Revenue Service (IRS) rules, plus time for

purchasing and installing the equipment. As an alternative to installing wastewater treatment, facilities

may choose, within the technology options considered, to have wastewater hauled offsite (a decision

handled within the model, as discussed below). The model generates the annualized cost for each option

(including the annual cost of hauling wastewater) for each facility in the survey, which is then used in the

facility closure and firm failure analyses, discussed below in Sections 1.5 and 1.6. The cost estimates

include zero costs for any facility meeting the definitions of the cutoffs described above.

EPA investigated two options under the three cutoffs in this EA: Chemical Precipitation (CP-IL)

and Dissolved Air Flotation (DAF-IL). EPA estimates that pretreatment standards would have cost

industry from $60.0 million to $148.6 million per year posttax ($1993) under the DAF-IL option,

depending on cutoff and from $53.9 million to $128.4 million per year posttax under the CP-IL option. CPIL under the 3MM/120K cutoff would have cost $90.8 million per year posttax. Most of the results in

Section One, as well as in the remainder of this EA are reported for the CP-IL option only. Results for

DAF-IL are similar and are reported in Appendix C.
3

 At proposal, EPA’s primary analysis assumed costs could be passed through to consumers and

accounted for this cost passthrough in these analyses. As discussed in the Notice of Data Availability (63

FR 71054, December 23, 1998), EPA no longer uses this assumption in the primary analyses in this EA. 

A cost passthrough analysis is undertaken, however, in Appendix A of this EA.

1-6

1.5 FACILITY-LEVEL ANALYSIS

In the facility closure analysis, EPA models the economic impacts of regulatory costs on individual

industrial laundry facilities, irrespective of ownership. In this part of the analysis, the model uses the

annualized costs of each option, compares them to the alternative annual wastewater hauling costs (where

this alternative is available), and selects the lowest of the two. 

EPA then converts the annual cost for each facility3 into a present value change in cash flow,

which is subtracted from the estimated baseline present value of facility cash flow. Estimated baseline

present value of facility cash flow is based on the average of three years of financial data from each facility

in the Section 308 survey under an assumed no-growth scenario (i.e., the annual cash flow, calculated as

the 3-year average is expected to remain the same over the 16-year period of analysis). If the change in

present value of cash flow (which is derived from the adjusted annualized costs of compliance) causes a

facility’s estimated cash flow to change from positive in the baseline to zero or negative after implementing

the requirements of the regulatory options over the 16-year period of analysis, EPA considers the facility

likely to close (i.e., liquidate) as a result of the regulation. This approach is somewhat different from

methodologies used in other EAs and economic impact analysis for manufacturing industries, since salvage

value is not considered in the closure analysis here. For a number of reasons, outlined in the EA (see

Appendix D), EPA found that using salvage value in a closure analysis for this industry is not the best way

for determining whether a facility would be liquidated. Single-facility firms do not typically take salvage

value into account in deciding whether to liquidate. EPA did perform a sensitivity analysis on facilities

owned by multifacility firms, which showed that the results with and without using salvage value are

approximately the same (see Appendix D).

Note that facilities that reported negative cash flow over the 3-year period of the survey are

considered baseline closures and are not considered affected by the rule for several reasons. First, many of

these facilities are nonindependent facilities owned by multifacility firms. These facilities might be
4EPA also considers the 5MM/255K cutoff economically achievable.

1-7

transferring production (laundering services at or near cost) from other facilities owned by the same parent

company, or otherwise not expected to be self-supporting by the parent. EPA analyzes the owner firms of

these facilities in the firm-level analysis and as long as the owner firm can afford to install and operate

compliance equipment in these non-self-supporting facilities, EPA assumes these facilities will close neither

in the baseline nor postcompliance. Second, OMB guidance suggests that agencies develop a baseline that

is “the best assessment of the way the world would look absent from the proposed regulation. That

assessment may consider a wide range of factors, including the likely evolution of the market...” EPA’s

best assessment is that some facilities currently operating might not be around to install and operate the

pollution control equipment. It is possible that a facility estimated to be a baseline closure might remain

open, but the converse is also true—a facility projected to remain open until it is subject to the rule might

actually close independently of the effects of the rule (both results might be equally possible). Thus,

consistent with OMB guidance, EPA estimated postcompliance closures by counting closures that are

projected to close solely due to the effect of regulatory options.

EPA estimates that the CP-IL option (DAF-IL impact results are identical and are presented in

Appendix C) would have resulted in from 2 to 106 facilities closing, depending on cutoff, or 0.2 percent to

6.7 percent of all facilities in the postcompliance analysis. Under the 3MM/120K cutoff, 44 facilities (2.7

percent of facilities not closing in the baseline), would have closed.

Another key analysis EPA performs is an analysis to determine impacts on new sources, which is

primarily a “barrier-to-entry analysis” to determine whether the costs of PSNS would prevent a new source

from entering the market. This analysis looks at whether new industrial laundries would be at a

competitive disadvantage compared with existing sources. Market effects and barriers to entry associated

with cutoffs also are qualitatively investigated. 

EPA is not regulating new sources under pretreatment standards, but has selected the same cutoff

for new sources (the 3MM/120K cutoff) under the CP-IL option as for existing sources as an economically

achievable option as discussed in the preamble to the Final Action.4 EPA determined that costs to new

facilities should be similar to costs for existing facilities. EPA has determined that no barriers to entry
1-8

would have occurred as long as the same cutoff was selected for new sources as for existing sources. In this

circumstance, all sources, regardless of whether they are new or existing, would have faced similar costs

and the same market factors as existing sources. EPA found that no sources identified as new in the

Section 308 survey (that is, the firm identified them as beginning production during the 3-year survey

period) would have closed under the CP-IL option at the 3MM/120K cutoff. Thus this regulatory option

would have been economically achievable for new sources.

1.6 FIRM FAILURE ANALYSIS

In the firm failure analysis, EPA uses the compliance costs to compute a change in earnings,

assets, liabilities, and working capital at the firm level (accounting for costs for multiple facilities, where

applicable). These postcompliance financial figures are used in a computerized model of financial health

on a firm-by-firm basis. The model uses an equation known as Altman’s Z", which was developed based

on empirical data to characterize the financial health of firms. This equation calculates one number, based

on the financial data, that can be compared to index numbers that define “good” financial health,

“indeterminate” financial health, and “poor” financial health. All firms whose Altman’s Z" number

changes such that the firm goes from a “good” or “indeterminate” baseline category to a “poor”

postcompliance category are classified as likely to have significant difficulties raising the capital needed to

comply with a regulatory option, which can indicate the likelihood of firm bankruptcy, or loss of financial

independence.

EPA estimates that the CP-IL option would have resulted in 72 firms under no cutoff or the

1MM/255K cutoff failing or losing their financial independence. Under the 3MM/120K cutoff and the

5MM/255K cutoff, no firms are projected to fail. As discussed below, firm failures in this industry can

have effects on employment, and these effects can approach those associated with closures, since firms that

are acquired are often converted to depots with a subsequent loss of as much as three-quarters of existing

employment.
1-9

1.7 INDUSTRY, NATIONAL, AND REGIONAL IMPACTS ON EMPLOYMENT AND

IMPACTS ON NATIONAL-LEVEL OUTPUT

EPA undertook several different types of analyses to estimate impacts on employment in the

industrial laundries industry, on the national-level economy, and on communities. EPA also estimated

impacts on national-level output. 

The primary analysis of employment impacts focuses on the job losses associated with facility

closures and firm failures. EPA assumes that all employment is lost at facilities projected to close as a

result of the regulatory options, and as noted above, EPA also assumes that 75 percent of employment is

lost at firms projected to fail as a result of the regulatory options. Based on the numbers of facilities

estimated to close and firms estimated to fail, EPA estimates that employment losses within the industrial

laundries industry might range from 235 jobs under the 5MM/255K cutoff to 5,039 jobs under a no cutoff

scenario. The selected 3MM/120K cutoff is associated with 2,261 job losses.

According to economic theory, these losses can have further repercussions throughout the

economy, as industries that provide inputs to the industrial laundries industry react to the contraction in

that industry and as laid off workers curb their expenditures. Using a type of analysis called input-output

analysis, EPA estimates the total losses to the U.S. economy (which incorporates the losses within the

industrial laundries industry). These losses, based on the closure- and failure-induced losses estimated

above, range from 404 to 8,667 jobs throughout the U.S. economy, depending on cutoff. The selected

3MM/120K cutoff is associated with 3,889 jobs lost throughout the U.S. economy, based on closures and

failures.

These losses do not account for gains in employment due to the need to manufacture, install, and

operate pollution control equipment. Furthermore, closures and failures are not the only possible

employment impacts driving national-level employment losses. Output losses (which are production-driven

losses) can be different from the losses associated with closures and failures. That is, closures and failures

can reduce production to levels that are greater than or less than the level of production that is the market

equilibrium solution of that amount of production demanded. Production-driven losses can be seen as

longer-term losses that can occur as the market reaches equilibrium, compared to the more immediate
1-10

losses associated with closures and failures. The production-driven impacts on employment can be

determined at the national level and the industry level.

At the national level, input-output analysis uses the total output loss measured as the cost of

compliance to estimate the total losses to the national-level economy. These same compliance costs are

also used to estimate employment gains (most of which occur in industries other than the industrial

laundries industry). Under the assumptions of this analysis, net losses to the national-level economy are

estimated to total 3,389 to 7,900 jobs, depending on cutoff. Net output losses to the U.S. economy in

dollar value are estimated to total $55.1 million to $131.9 million, depending on cutoff. The selected

3MM/120K cutoff is associated with net employment losses of 5,795 jobs and $98.04 million in net output

losses. These net losses in employment and output would have had a negligible impact on the U.S.

economy.

Direct losses to the industrial laundries industry can also be calculated using the gross nationallevel employment losses (which are based on the output losses represented by compliance costs) and a

portion of employment gains. The losses thus computed would be a reasonable upper bound estimate of

production-driven losses (as discussed above). The net losses estimated incorporate assumptions that no

costs can be passed through to customers and some employment is gained in the industrial laundries

industry to operate pollution control equipment. EPA estimates that these longer-term net losses in the

industrial laundries industry might have ranged from 2,284 to 6,792 jobs lost, depending on cutoff, or

somewhat greater than the losses to the industry predicted from closures and failures alone. The selected

3MM/120K cutoff is associated with losses of 4,897 jobs within the industrial laundries industry in the

worst case.

EPA also undertook an alternative analysis to compute a reasonable lower-bound estimate of

production-driven net employment losses using the estimate of production losses from EPA’s market

model. Implicit in this estimate is the assumption that some compliance costs can bef passed through to

customers. Using this approach, EPA estimated that the lower-bound loss would be almost exactly offset

by gains. Thus EPA believes that the longer-term net employment impacts in the industrial laundries

industry would have ranged from offsetting losses and gains to a loss of 2,284 to 6,692 jobs, depending on

cutoff. The selected 3MM/120K cutoff is associated with losses ranging from roughly none to 4,897 jobs. 
1-11

The employment losses from closures and failures estimated for the industrial laundries industry would

have fallen roughly between these two bounding estimates of longer-term losses.

EPA also determined the impacts on regional-level employment, which is estimated using facility

closures and employment at those closing facilities to determine the change in unemployment rates in a

county. EPA conducted a regional analysis because even if net employment effects (losses minus gains) are

relatively small on a national level, an employment loss might still have a substantial negative effect on an

individual community. EPA determined that closures and failures would have resulted in a change in a

community unemployment rates of less than 1 percent. 

1.8 OTHER SECONDARY IMPACTS

EPA investigated additional secondary impacts qualitatively and quantitatively. These impacts

include impacts on domestic and international markets, impacts on substitutes for industrial laundry

services, impacts on industries that might offer some industrial laundering services, impacts on

consolidation, impacts on inflation, distributional impacts, and impacts on environmental justice. EPA also

investigates the impact of the rule on domestic markets. The rule would have affected domestic markets to

the extent that excluded facilities could have affected market share. EPA makes an assessment of the

potential for effect on domestic market on the basis of pounds of laundry processed by excluded facilities to

the total pounds processed by the industry.

EPA expects the regulatory options would have had a minimal impact on international markets due

to the limited number of facilities near international boundaries, the relatively high transaction costs

associated with border crossings, and the ability of most facilities to absorb, if necessary, the full cost of

regulatory options without threat of closing or failing. Domestic markets might have been affected by the

3MM/120K cutoff since many larger firms would have faced increased costs, while many smaller firms

would not; however, the need to protect small, vulnerable firms outweighs the need to minimize market

effects.
1-12

EPA also investigated impacts on customers. EPA determined that even if most of the cost of CPIL under the no cutoff scenario was passed through on only shop towels, highly affected customers, such as

printers, should only experience typical cost increases of about $3,000 per year, and under a more realistic

scenario, this typical cost increase would be only about $200 per year. Therefore, EPA does not expect

price increases to have a major impact on customers. 

EPA also investigated the likelihood that customers might substitute disposable items for laundered

items or begin operating onsite laundries. Both the substitution of disposable items for laundered items and

the installation and operation of onsite laundries are associated with potential negative impacts on

customers that might deter them from choosing these potential substitutes. Disposable items can be more

expensive to use than laundered items, might not meet quality requirements (e.g., disposable printer towels

tend to be linty, and the printing industry trade organization indicated in comments that disposables are

considered inferior to reusables in this business) and are, in certain circumstances, regulated under other

environmental statutes. Meanwhile because of the high initial costs to install equipment on-site and the

small increase in price of industrial laundry services discussed earlier, onsite laundries could require years

before any cost savings might be realized. Given the disincentives towards those substitutes indicated

above, EPA does not expect the regulatory options to have caused customers to substitute disposable items

for laundered items or commence industrial laundering on site for industrial laundries services in any major

way. The small reduction in production is more likely to have occurred due to customers delaying cleaning

(rather than weekly pickups of mats, for example, some might substitute biweekly pickups) or dropping

certain rental items, such as uniforms used only for image purposes. This decline in production is

negligible compared to the approximate 6 percent per year growth in current years.

EPA also expects that regulatory options would have had a minimal impact on consolidation,

inflation, other providers of industrial laundry services, and environmental justice.

1.9 SMALL BUSINESS IMPACTS

Had EPA promulgated a rule, no small firms (as defined by SBA, i.e., firms with revenues less

than $10.5 million per year) would have closed or failed under the 5MM/255 cutoff; 39 small, single-
1-13

facility firms would have closed or failed under the 3MM/120K cutoff (39 closures out of the 44 closures

predicted for all facilities and no failures, or 5.7 percent of all small firms in the postcompliance analyses),

and 126 small, single-facility firms would have closed or failed under the 1MM/255K cutoff (54 closures

out of the 61 closures predicted for all facilities and 72 failures, or 18.4 percent of all small firms in the

postcompliance analysis). EPA believes the 3MM/120K cutoff would have provided sufficient mitigation

of small business impacts, had EPA promulgated a rule. Because EPA has decided not to promulgate

pretreatment standards for the industrial laundries industry, all impacts (regardless of whether significant

or not) on all small firms have been mitigated.

1.10 COST-BENEFIT ANALYSIS

Because EPA had decided not to promulgate pretreatment standards for the industrial laundries

industry, a cost benefit analysis pursuant to Executive Order 12866 and Section 202 of the Unfunded

Mandates Reform Act (UMRA) is not required, since regulatory costs and regulatory benefits are zero.

However, EPA provides a social cost and benefits comparison (see also Table 1-1 above). 

EPA approximates social cost using the pretax costs of compliance (which comprise the vast

majority of the social costs). Pretax costs of compliance range from $77.4 million to $179.7 million per

year, depending on cutoff. Benefits, which comprise the monetized benefits of avoiding 0.03 cancer cases,

and improvements in the quality of biosolids (sewage sludge) at 8 publicly owned treatment works, range

from $0.07 million to $0.35 million per year. EPA’s selected option, CP-IL under the 3MM/120K cutoff

would have been associated with social costs of approximately $131.2 million per year and benefits of

approximately $0.07 million to $0.35 million per year.
2-1

SECTION TWO

DATA SOURCES

EPA relied on several data sources to develop the industry profile and the economic and financial

analyses of the technical options evaluated during EPA’s consideration of pretreatment standards for the

industrial laundries industry prior to the Agency’s decision not to promulgate pretreatment standards for

the industrial laundries point source category. The following subsections discuss the principal data sources

used. Additional data sources are described in Sections Three through Ten as they are referenced. All

documents and databases cited in this report, except where noted (e.g., publicly available documents), are

available in EPA’s decisionmaking record.

2.1 THE 1994 INDUSTRIAL LAUNDRIES INDUSTRY DETAILED QUESTIONNAIRE

EPA used the 1994 Industrial Laundries Industry Detailed Questionnaire (hereinafter referred to

as the Section 308 Survey) to obtain detailed technical and financial information from a sample of 255

establishments engaged in industrial laundering that could potentially be affected by the regulatory options.

Data provided by the surveyed facilities included technical information on the quantity and types of items

laundered; water use and waste characteristics; waste/wastewater treatment operations and waste

minimization practices; cost of industrial laundry operations; and treatment capacity. The Survey also

collected economic and financial data, such as the number of employees; industrial laundering revenues and

costs; assets; liabilities; net income; ownership structure; discount rate; and market value of land,

buildings, and equipment. The questionnaire collected economic and financial data at the facility, ownercompany, and parent-company levels. EPA used these data extensively to develop the proposed rule for this

industry. 

EPA based the Survey sampling frame on two sources of population information: (1) the trade

association listings, which were used to develop the population for the 1993 Industrial Laundries Industry

Screener Questionnaire (Screener Questionnaire) and (2) information from Dun and Bradstreet, which was

used to develop the population for the Industrial Laundries Industry Supplemental Screener

Questionnaire issued in 1994 (Supplemental Screener Questionnaire). See EPA’s Statistical Support
1 The sampling frame stratified facilities into four categories based on types of items laundered,

three categories based on types of wastewater treatment, and four categories based on revenues.

2-2

Document for Proposed Pretreatment Standards for Existing and New Sources for the Industrial

Laundries Point Source Category (Statistical Support Document) for more information on how EPA

developed the survey sampling frame. EPA also sent out another screener questionnaire in 1995, the

Hotels, Hospitals, and Prisons Screener Questionnaire (HHPs Screener Questionnaire). EPA used the

information from the HHPs Screener Questionnaire to further clarify the regulatory scope of this rule.

EPA stratified the affected population according to the types of items laundered, types of

wastewater treatment in place, and annual revenues.1 Based on these strata, EPA developed “cells,” which

are the intersection of two sampling strata. For example, a survey could be stratified on the basis of

revenue and treatment technology, which would each be considered a stratum. A cell in this example would

correspond to a particular range of revenues and a treatment technology type. To select facilities to receive

the detailed questionnaire, EPA took a census of all facilities that at the time of the survey had in-place

treatment technologies such as air strippers, centrifuge, dissolved-air flotation, membrane filtration,

pressure filtration, media filtration, and/or chemical precipitation, because these treatment technologies

were considered likely options for the proposed regulation. EPA also took a census of all facilities with

annual revenues less than $1 million that used dissolved-air flotation, oil/water separation, and/or chemical

precipitation wastewater treatment technologies to learn more about how facilities in these sampling cells,

despite their low revenues, were able to install advanced treatment systems as might be required by the

regulation. In addition, EPA took a census of cells with fewer than five facilities to ensure that the most

information possible on these more unusual types of facilities was collected. EPA’s Statistical Support

Document, provides more information on the stratification and development of survey weights for the

Section 308 Survey.

2.2 GOVERNMENT DATA SOURCES

Facilities in the affected population are predominantly classified into one of four primary Standard

Industrial Classifications (SICs):
2-3

# SIC 7218: Industrial Launderers. Establishments primarily engaged in supplying

laundered or dry-cleaned industrial work uniforms and related work clothing, such as

protective apparel (flame and heat resistant) and clean room apparel; laundered mats and

rugs; dust control items, such as treated mops, rugs, mats, dust tool covers, and cloths;

laundered wiping towels; and other selected items to industrial, commercial, and

government users. These items may belong to the industrial launderer and be supplied to

users on a rental basis, or they may be the customers’ own goods. Establishments included

in this industry may or may not operate their own laundry or dry-cleaning facilities.

# SIC 7213: Linen Supply. Establishments primarily engaged in supplying to commercial

establishments or household users, on a rental basis, such laundered items as uniforms,

gowns, and coats of the type used by doctors, nurses, barbers, beauticians, and waitresses;

and table linens, bed linens, towels and toweling, and similar items. Establishments

included in this industry may or may not operate their own laundry facilities.

Establishments primarily engaged in providing diaper service are classified in Industry

7219.

# SIC 7211: Power Laundries, Family and Commercial. Establishments primarily

engaged in operating mechanical laundries with steam or other power. Establishments

primarily engaged in supplying laundered work clothing on a contract or fee basis are

classified in Industry 7218.

# SIC 7216: Dry-cleaning Plants, Except Rug Cleaning. Establishments primarily

engaged in dry-cleaning or dyeing apparel and household fabrics other than rugs. Press

shops and agents for dry-cleaners are classified in Industry 7212; establishments primarily

engaged in cleaning rugs are classified in Industry 7217; and establishments primarily

engaged in dyeing fabrics for trade are classified in Manufacturing, Major Group 22.

The SIC codes listed above translate to a new numbering system called the North American

Industry Classification System (NAICS). A translation chart for these codes is provided in Table 2-1.

EPA used U.S. Department of Commerce data for these SICs in developing the market model

discussed in Appendix A. The Department of Commerce collects a wide range of industry data, including

number of establishments, number of employees, annual payroll, and annual receipts, at the 4-digit SIC

level. These data are reported in U.S. Census Bureau publications such as County Business Patterns and

the Service Annual Survey (exact citations appear where data are used in the EA). 

EPA also used other government data, such as the Bureau of Labor Statistics’ producer and

consumer price indexes, in developing the market model. EPA further used the indexes to inflate and deflate

Section 308 Survey financial data, as reported in Sections Five and Six. 
2U.S. EPA, 2000. Technical Development Document for the Final Action Regarding

Pretreatment Standards for the Industrial Laundries Categorical Point Source Category (Revised March

2000). EPA 821-R-00-006. March.

2-4

Table 2-1

Conversion From SIC to NAICS Codes

SIC NAICS

7218: Industrial Launderers 812332

7213: Linen Supply 812331

7211: Power Laundries, Family and Commercial 812321

7216: Dry Cleaning Plants, Except Rug Cleaning 812322

2.3 OTHER SOURCES

EPA’s Final Technical Development Document for the Final Action Regarding Pretreatment

Standards for the Industrial Laundries Categorical Point Source Category (hereinafter, the Final

Development Document),2 is the major source of technical information about the industry presented in

Section Three; it is also the source of capital and operating and maintenance cost estimates for the

regulatory options evaluated in this EA.

EPA further supplemented questionnaire and government data with information from a number of

other sources: the industry trade journals Industrial Launderer, published by the Uniform & Textile

Service Association, and Textile Rental, published by the Textile Rental Services Association of America,

provided details on changing laundering processes, new technologies, and industry perceptions of the

industrial laundries market. In addition, EPA referenced several studies sponsored by the Uniform &

Textile Service Association (formerly the Institute of Industrial Launderers) that examined the customer

base for industrial laundries and the markets for wipers and mats, as well as the industry as a whole. EPA’s

1989 Preliminary Data Summary for Industrial Laundries provided information about the overall

industry. Lastly, information from investment sources, such as the equity research division of Barrington

Research Associates, aided EPA in producing its financial profile of the industry. Finally, EPA obtained
3U.S. EPA. Comment Response Document for the Final Action Regarding Pretreatment

Standards for the Industrial Laundries Point Source Category. Docket No. L08312.

2-5

some data from comments submitted to the record for both the proposal and the Notice of Data

Availability. These comments and their responses can be seen in EPA’s Comment Response Document.3
1

 Based on data from the 1993 Screener Questionnaire and 1993 Supplemental Screener

Questionnaire.

3-1

SECTION THREE

INDUSTRY PROFILE

3.1 INTRODUCTION

The industrial laundries industry comprises establishments engaged in supplying laundered or drycleaned industrial work uniforms and related textiles, such as shop towels, mats, and dust mops, to

industrial, commercial, and government users. EPA would have established pretreatment standards for

those industrial laundry facilities discharging wastewater to publicly owned treatment works (POTWs);

there are no known industrial laundries discharging directly into receiving waters.1 Compliance with

pretreatment standards might have required industrial launderers to purchase and install wastewater

pretreatment systems, send certain items offsite for laundering, or contract for offsite wastewater treatment,

and would have required them to monitor pollutant concentrations in wastewater. EPA, however, has

decided not to promulgate pretreatment standards for the industrial laundries point source category. This

EA presents the information EPA needed to make this decision. 

This section presents a profile of the industrial laundries industry as defined by EPA for the

purposes of the decisionmaking process. Only facilities with laundering discharges would have been

regulated; administrative offices and depots established for the purposes of marketing, retailing, and/or

distributing laundered items would have been out of the scope of the regulation and were not included in the

Section 308 Survey. Laundries engaged in onsite laundering at industrial facilities also would not have been

covered by pretreatment standards. The rationale for omitting these facilities was discussed in detail in the

preamble to the proposed rule. Some of these laundries are already covered by effluent guidelines for other

industry categories (e.g., pesticides). Moreover, data from the 1995 HHPs Screener Questionnaire indicate

that facilities engaged in onsite laundering at hospitals, hotels, and prisons generally do not launder items
2

 Anne Jones, ERG, 1997. “Analysis of hospitals, hotels, and prisons (HHPs) database.”

Memorandum to the Rulemaking Record. February 21.

3

 Although some of the information (i.e., Section 308 Survey data) presented here is now dated, the

survey data are still the most complete and most representative data available on the industry. Here, EPA

did not resurvey industries between proposing and finalizing the rule in order to minimize reporting burdens

on the industry. Where appropriate, EPA indicates the potential for change in conditions in intervening

years.

3-2

for offsite customers. Further follow-up work indicates that those onsite laundries that do launder items

from off site generally do not handle “industrial” items.2

The purpose of this profile is to provide a baseline description of the current activities, structure,

and performance of the industrial laundries industry.3 The industry’s characteristics and market structure

serve as foundations for developing the methodology used elsewhere in this EA to analyze the potential

impacts associated with the regulatory options considered by EPA during the decisionmaking process.

Information presented in this section is drawn, for the most part, from industry and government literature

on industrial laundries and from the Section 308 Survey.

Section 3.2 provides an overview of the industrial laundries industry and the processes involved in

industrial laundering. Section 3.3 summarizes the structure of the industrial laundries market, and Section

3.4 gives a more detailed breakdown of industry demographics and the facilities affected by the regulation.

It also provides baseline descriptive and financial information related to the industry’s ability to absorb

potential regulatory costs.

3.2 OVERVIEW OF THE INDUSTRIAL LAUNDRIES INDUSTRY

3.2.1 Services Provided

The industrial laundries industry was established in the period during and immediately after World

War II, when the growth of the industrial sector resulted in increasing interest in services geared toward

providing clean work apparel, clean work materials, and a clean work environment. Over time, as the

service sector of the economy expanded, industrial laundries also became involved in providing customers
4

 U.S. EPA, 1989. Preliminary Data Summary for Industrial Laundries. Washington, DC: Office

of Water Regulations and Standards. September.

5

 Establishments engaged in dry cleaning only or oil treatment only are not covered by the Final IL

Standards.

3-3

with uniforms and textile goods designed to promote safety, corporate identity, and company image. As a

result, industrial laundry services are currently used by a variety of industrial, commercial, and government

organizations.

Industrial laundries can be found throughout the United States because of the diversity of

customers they service. Facilities tend, however, to be concentrated in metropolitan areas and the more

populated states (California, Texas, New York, and Florida), where the service sector is relatively large,

and in the heavily industrialized states (Ohio, Illinois, Michigan, Pennsylvania, and Indiana).4

Industrial laundries supply customers with water-washed uniforms and related work items through

a complex distribution system. (Note that some items may be water washed in series with other processes

such as dry cleaning or oil treatment.5) The launderer gathers items from customers for cleaning and

returns these items after they have been laundered and, if necessary, repaired and/or pressed. The launderer

might also personalize items for some customers. For the most part, industrial laundries own the goods they

process and supply them to customers on a rental basis; however, some facilities also launder customerowned uniforms and textiles, which the industry refers to as “Not Our Goods” (NOGs). Direct sales of

products also can account for a small portion of industrial laundries’ business. Thus, industrial laundries

might be engaged in a variety of activities in addition to the actual cleaning of work garments and

associated goods.
6

 1996. “The super SICs.” Industrial Launderer. October, pp. 53-54, 56.

7

 UTSA, 1996. Customer Profile Analysis. Arlington, VA: UTSA. The survey database included

information on 3,739 randomly selected customer accounts from 22 UTSA member companies.

8

Ibid.

9

Ibid.

10 Institute of Industrial Launderers (IIL), 1993, Customer Profile Analysis: Identification of

Sources of Uniform and Textile Service Industry Customers by Product by SIC Code. Washington, DC:

IIL. (Prior to November 1993, the UTSA was known as the IIL.

3-4

3.2.1.1 The Needs of Different Customers: Functional Cleaning and Cleaning for

Convenience

Industrial laundries have a wide variety of customers. From the industry’s perspective, “just about

any type of business is a potential customer.”6 Consistent with this, data from the most recent customer

profile survey conducted by the Uniform and Textile Service Association (UTSA) indicates that no single

industry sector dominates the industrial laundries customer base.7 When customers are grouped according

to SIC category, only automotive dealers and service stations (SIC 55) and companies involved in

automotive repair, services, and parking (SIC 75) account for more than 10 percent of industrial laundries’

customers (10.1 percent each).8 Furthermore, the 15 largest segments of the industrial laundries customer

base in 1995 (listed in Table 3-1) account for less than two-thirds of all industrial laundries’ customers.9

This pattern is similar to that observed in the 1993 customer profile report: automotive services, dealers,

and service stations represented the largest customer groups, but, in general, businesses in customer

category constituted only a small portion of the industry’s overall customer base.10

Blue-collar businesses at which petroleum- and carbon-based substances are used (e.g., automobile

repair shops, dealers, and gas stations) are the traditional purchasers of industrial laundry services.

Uniforms and textiles (especially shop towels and mats) in such environments can become heavily soiled

with oil, gasoline, and grease. Printers and publishers also represent a significant portion of the customer

base for industrial laundries; towels used in the print shop can become contaminated with hazardous

compounds, including paint, ink, and solvents. Other businesses using industrial laundries services include

the metal fabrication and chemical industries. For all these customers, industrial laundries can offer an
Table 3-1

The Top 15 Customer Industries for Industrial Launderers,

for All Products, 1995

Major % of

SIC Group Title Customer Base

55 Automotive Dealers & Service Stations 10.1%

75 Auto Repair, Services, and Parking 10.1%

58 Eating and Drinking Places 7.5%

54 Food Stores 5.3%

17 Special Trade Contractors 3.6%

50 Wholesale Trade -- Durable Goods 3.6%

35 Industrial Machinery and Equipment 3.3%

27 Printing and Publishing 3.1%

73 Business Services 2.7%

20 Food and Kindred Products 2.4%

80 Health Services 2.3%

34 Fabricated Metal Products 2.2%

82 Educational Services 2.1%

51 Wholesale Trade -- Nondurable Goods 2.1%

59 Miscellaneous Retail 2.0%

 Total, Top 15 Customer Categories 62.4%

Source: UTSA, 1996. Customer Profile Analysis,

 Table 2. Washington, DC: UTSA.

3-5
11 UTSA, 1996. Op. cit. 

12 UTSA, 1996. Op. cit. (Table 1). 

13 IIL, 1993. Op. cit.

3-6

effective means of cleaning highly soiled items for reuse. The traditional blue-collar market still accounts

for approximately 50 percent of garments rented.11

As the industrial laundries customer base broadened from purchasers desiring simple functionality

to include purchasers concerned with appearance and corporate identity, the volume of moderately to

lightly soiled items laundered by the industry also grew. Eating and drinking establishments, wholesale and

retail trade businesses, and food stores use industrial laundries in part because uniforms serve as a means

of cultivating a more distinct public image and encouraging employee identification with the larger

organization. In addition, industrial laundry services offer a convenient means of handling garments without

requiring either direct garment purchase programs in the workplace or worker maintenance of clothing.

3.2.1.2 Products

Uniform rentals account for the largest portion of industrial laundries’ customer base and revenues;

according to UTSA’s 1996 customer profile analysis, nearly 60 percent of industrial laundries’ customers

rent uniforms (see Table 3-2).12 Other products rented include mats, mops, shop and print towels,

continuous roller towels, and linen. These products are often “add-ons” to uniform rentals, although many

customers renting mops and linen do not rent uniforms.13

Table 3-3 indicates the percentage of industrial laundries laundering each category of rental

textiles, based on responses to the Section 308 Survey. A detailed description of the major items rented and

how they are used follows:

# Uniforms. Traditionally, uniform rentals were geared toward meeting the need for clean

work clothes in blue-collar industries. As noted above, however, once the garment rental

market expanded to include customers interested in improving corporate identity and

image, in addition to maintaining the cleanliness of work apparel, the number of businesses
Table 3-2

Percentage of Total Customer Base

Renting Each Type of Product, 1995

Percentage of

Product Customer Base*

 Uniforms 58.6%

 Mats 48.3%

 Mops 18.6%

 Shop Towels 33.2%

 Continuous Roll Towels (CRTs) 11.2%

 Table and Bed Linen 4.4%

 Aprons and Bath Towels 12.9%

 Not Our Goods (NOG) Items 2.5%

 Other Products 17.5%

* Percentages do not sum to 100 because customers 

may rent more than one type of product.

Source: UTSA, 1996.

 Customer Profile Analysis, Table 1. 

 Washington, DC: UTSA.

3-7
Table 3-3

Textiles Laundered by Industrial Laundries

% of Laundries

 Textile Type Handling Textile Type

 Industrial Garments 82%

 Shop Towels and Printer Towels 78%

 Floor Mats 94%

 Mops, Dust Cloths, and Tool Covers 80%

 Linen Supply Garments 54%

 Flatwork/Fulldry 78%

 Health Care Items 37%

 Fender Covers 39%

 Continuous Roll Towels 53%

 Clean Room Garments 2%

 Other 17%

Source: Section 308 Survey (based only on facilities for which 

 there is sufficient information).

3-8
14 Ibid.

15 See EPA’s Final Development Document.

16 Millunzi, Carolyn, 1997. “Mat stats reveal product potential.” Industrial Launderer. September,

p. 91.

17 See EPA’s Final Development Document.

18 Ibid.

3-9

renting uniforms more for convenience than function increased. In 1993, the uniform rental

market was nearly evenly split between industrial and nonindustrial customers.14 The

automotive sales and services industries account for a significant proportion of the

industrial customer base, and, as such, some of the main contaminants found in uniform

laundry wastewater are oil and grease (measured as n-hexane extractable material [HEM])

and total organic carbon (TOC).15 Uniforms rented primarily for identity and image

purposes tend to be less soiled and require less intensive laundering than those rented for

functional purposes.

# Mats. Mats are used particularly in high soil areas, such as manufacturing plants or

automobile repair shops, to prevent the spread of dirt. Mat rental is thus typically geared

toward providing a clean work environment. The mat rental market has been expanding in

low-soil areas. Mats are increasingly used for dust control and in special applications such

as scrapers, wet area/anti-slip, antifatigue, and inclines. Reflecting this expansion, the mat

rental market is growing eight percent a year.16 In low-soil situations, however, mat rental

from industrial launderers might not offer customers significant advantages over purchase.

The type and quantity of soils found in mats vary based on the settings in which they are

used; contaminants that can be found in mat wastewater include oil and grease (as HEM),

biochemical oxygen demand (BOD5), total suspended solids (TSS), metals such as

aluminum and iron, and salt and sand.17

# Mops. Mops are designed to meet the need for a clean working environment by removing

soils and controlling dust. Unlike other rental items, mops are generally not “add-ons”

associated with uniform rentals; customers using industrial laundry services to obtain clean

mops might not rent any other products. The soils in mops handled by industrial launderers

reflect the soils present at the various customer sites. Pollutants found in relatively high

concentrations in mop wastewater include TSS, oil and grease (measured as HEM), and

metals such as aluminum and iron.18

# Shop towels and printer towels/rags. Industrial launderers process shop towels and printer

towels/rags, also known as industrial wipers, to provide customers with clean work

materials. Shop towels are used primarily by the industries that comprise the traditional

industrial laundries customer base (i.e., auto repair shops, machine shops, printers, etc).

The towels are highly absorbent and are designed to wipe oil, grease, paint and ink, and

solvents off equipment. Because of the way in which shop and printer towels are used,
19 See EPA’s Final Development Document, Chapter 5.

20 See EPA’s Final Development Document.

21 1995. “Printer’s use of friendlier solvents pays off for all.” Industrial Launderer. September,

pp. 51-52.

22 1997. “Tackling the toughest textiles.” Industrial Launderer. January, pp. 27-28, 71.

23 Site Visit Report, DCN L03977; confidential business information (CBI) material in the

Rulemaking Record. 

3-10

wastewaters from the towels have generally been found to contain higher pollutant loads

than the wastewaters from all other items cleaned by industrial laundries.19 Shop and

printer towel wastewater generally has been found to contain high concentrations of BOD5,

oil and grease (measured as HEM), total petroleum hydrocarbons (TPH, measured as

SGT-HEM), TOC, and TSS. Shop towels are also the primary source of hazardous

pollutants found in industrial laundries’ effluent; they often contain small amounts of

volatile organic compounds (VOCs), semivolatile organics such as tetrachlorethene,

ethylbenzene, 1,1,1-trichloroethane, and toluene, and toxic metals such as copper, lead,

chromium, and zinc, among other pollutants.20 Industrial launderers therefore generally

require more water and chemicals to clean shop towels than to clean other items. As a

result, and in anticipation of future environmental regulation, some laundries refuse to rent

or clean shop towels, while others charge by weight for shop towel cleaning to encourage

customers to perform some cleaning before the towels are picked up. In one case study, a

print shop using a centrifuge to extract excess solvents from shop towels found that this

not only reduced compliance problems for its launderer, but it also resulted in net savings

for the shop by allowing for more reuse and recycling of solvents.21 Section 308 Survey

data indicates that only 1.4 percent of industrial laundries are exclusively devoted to shop

towel cleaning. There may, however, be an opportunity for industrial launderers to

establish a market niche with little competition by cleaning shop towels. For example,

Brent Industries, which devotes about 30 percent of its business to dry cleaning followed

by water washing of shop and printer towels, has grown in the last 5 years from a single

facility to three facilities and three depots, with plans for additional expansion.22 EPA also

found facilities laundering primarily shop and printer towels during site visits to industrial

laundries conducted as part of the regulatory process.23
24 See EPA’s Final Development Document.

25 See EPA’s Final Development Document, Table 4-5.

3-11

3.2.2 Industry Processes

3.2.2.1 Laundering Techniques

The three primary cleaning techniques employed by industrial launderers are water washing, dry

cleaning, and dual-phase laundering. Water washing is the most commonly used process; approximately 97

percent of industrially laundered items are water washed.24 Dry cleaning, which uses solvents to dissolve

soils at low temperatures, accounts for less than 1 percent of items laundered, as does dual-phase cleaning,

which uses solvents and water in series on items with both water-soluble and organic solvent-soluble

soils.25 Other processes, such as oil treatment of dust mops, represent a very small portion of industrial

laundries’ business as well.

Water washing and dual-phase laundering are the most relevant processes of concern for a

pretreatment standard, because both produce wastewater. Launderers exclusively engaged in oil treatment

of mops (which generates no wastewater) or dry cleaning (which generates no wastewater) would not have

been covered by pretreatment standards as defined during EPA’s decisionmaking process.

EPA’s Final Development Document provides a detailed description of industrial laundering

processes. In general, when items to be cleaned arrive at the industrial laundering facility, they are first

sorted on the basis of fabric type, color, type of garment, and soil constituents. Stains that could be set by

washing are pretreated, which may involve soaking and/or application of acids, bleaches, or solvents

directly to the stains. There are a variety of industrial washing machines, but regardless of the type of

washer used, all water washing by industrial laundries involves the following basic steps:

# Flush. Soiled items are subjected to an initial rinsing, or flush, which removes loosely

attached soils.

# Break. Alkaline chemicals are added to wash waters to swell the fibers in the cloth and

facilitate soil removal. Detergents can also be added at this time.
26 Hutterly, John, 1997. “Why automated sorting is ready for your plant today.” Industrial

Launderer. January, p. 31.

27 1997. “The escort/carrier debate.” Industrial Launderer. April, p. 71.

3-12

# Wash cycle(s). During the wash cycle, chemicals and detergents are added to wash waters,

and the items are agitated. The amounts and types of chemicals or detergents added depend

on the soils being treated. Wash cycles can be followed by the addition of bleaching,

blueing, or brightening chemicals.

# Rinse. Between wash cycles and following the last wash cycle, items are rinsed. Chemicals

can be added during this process to neutralize any remaining bleach (anti-chlor) and to

reduce water pH to prevent yellowing of garments (sour). Other additives that might be

applied at this time are starch, oil treatment chemicals, water conditioners, dyes, stain

treatment chemicals, and bactericides.

# Extraction. During the extraction process, excess rinse water is removed from the items

laundered. This water typically contains dissolved and suspended soils.

Cleaned items are then dried, pressed, inspected for wear, folded, and delivered back to customers.

3.2.2.2 Labor Intensity

Although much of the actual cleaning process is mechanized, industrial laundering is still relatively

labor intensive. Industrial laundries require large numbers of comparatively unskilled in-plant production

workers, in addition to managers, sales representatives, and delivery truck drivers. These in-plant workers

maintain and operate equipment controls for washers and dryers. Additional labor is required for sorting

and routing items to the appropriate customers. However, many in the industry are adopting automated

sorting systems. Such systems are now installed in all stages of garment handling, from hang-up to load-out

on route vehicles, including database management software.26 At the same time, efficient garment

identification for such systems is available with “on the fly” scanning using code information extraction

(CIX) software.27

Because labor is relatively inexpensive in this industry, however, automation may make sense

mainly for facilities operated by large firms that need to, for example, coordinate routing between

processing facilities and depots. In addition, automation may work for certain small- to medium-sized
28 Murphy, Ed, 1997. “How to avoid the high cost of plant expansion.” Industrial Launderer. 

February, pp. 47-48, 50.

29 1996. “Association poised to meet industry’s operational challenges.” Industrial Launderer.

December, pp. 13-14, 16.

30 Hobson, David F., 1997. “Industry trend watch.” Industrial Launderer. January, p. 72.

31 SIC codes translate now to a new numbering system called the North American Industry

Classification System (NAICS). See Section Two of this EA for the NAICS codes relevant for the

industrial laundries industry.

3-13

facilities that are able to eliminate a second- or third-shift crew by upgrading their equipment; other larger

facilities or facilities operating only a single-shift crew generally might achieve significant savings simply

by utilizing existing resources more efficiently.28 Thus, historically, equipment manufacturers have had few

incentives to fund research and development in the area of laundries automation, and industrial laundries

have been slow to adopt technological advancements relative to more “high tech” industries. In recent

years, however, industrial launderers have shown more interest in purchasing new technology to improve

quality control and increase capacity for growth, particularly as older machinery wears out.29,30 It is,

nevertheless, likely that labor will continue to be a significant input in the industrial laundering process for

the foreseeable future.

3.2.3 Classification of Facilities Performing Industrial Laundering

3.2.3.1 Census Classifications

The U.S. Department of Commerce divides the laundering industry into several subcategories, each

corresponding to a different four-digit SIC code. These classifications can be useful in interpreting

Department of Commerce data on industry performance, employment, consumption, etc.

Although there are facilities meeting EPA’s definition of an industrial laundry in almost all the SIC

subcategories of the laundering industry, four SIC codes are particularly relevant for the purposes of

discussion here.31 These are SIC 7218, Industrial Launderers; SIC 7213, Linen Supply; SIC 7211, Power
3-14

Launderers, Family and Commercial; and SIC 7216, Dry-cleaning Plants, Except Rug Cleaning (see

Section Two for definitions).

Facilities engaged in industrial laundering tend to be classified into one of these groups. SIC codes,

however, do not provide an exact means of distinguishing between industrial and nonindustrial laundries.

Many firms assigned a primary SIC code of 7211, 7213, or 7216 have a secondary (or even tertiary) code

of 7218, and vice versa. Consequently, it would be too limiting to consider only laundries with a primary

SIC code of 7218 to be industrial laundries. Furthermore, each SIC category can include independent sales,

administrative, and distribution centers, as well as facilities actually involved in laundering; not all the

facilities in SIC 7218 are actually laundering textiles. SIC groupings therefore are not used in this EA as a

baseline for assessing possible impacts of regulatory options. Pretreatment standards would have

specifically covered launderers involved in water washing of industrial textile items (although these same

launderers might also have in-house sales, administrative, and distribution capabilities) and would thus

have pertained to a subset of the facilities classified in several SIC subcategories, primarily SICs 7211,

7213, 7216, and 7218.

3.2.3.2 Classification of Industrial Laundries for Regulatory Purposes

Given that facilities engaged in industrial laundering can be found in all of the various SIC

subcategories of the laundering industry, EPA also does not use SIC codes to determine which laundries

would have been covered by pretreatment standards. The breakdown of primary and secondary SIC codes

for the facilities meeting EPA’s definition of an industrial laundry for purposes of the regulatory decision

making process is given in Table 3-4. Data in the table are based on the Section 308 Survey. As the table

indicates, although many of the facilities in this analysis are classified by the U.S. Department of

Commerce as primarily industrial laundries (SIC 7218), the number of facilities that are classified

primarily as linen suppliers (SIC 7213), power launderers (SIC 7211), or dry-cleaning plants (SIC 7216),

but that also perform water-washing of industrial textiles, is also substantial.

As noted in the preamble to the proposed rule, industrial laundries facilities are facilities that

launder industrial textile items from offsite as a business activity (i.e., that launder industrial textile items
Table 3-4

Primary and Secondary SIC Codes Reported by Industrial Laundries

SECONDARY SIC CODES*

Number 2269 5047 5085 5136 72 7211 7213 7215 7216 7218 7389

of Finishers of Medical, Dental, Industrial Men's & Boys' Personal Power Linen Coin-Operated Drycleaning Industrial Business

 PRIMARY SIC CODES Facilities Textiles** and Hospital Supplies Clothing and Services Laundries, Supply Laundries & Plants, Except Laundries Services**

Equipment Furnishings Family and Drycleaning Rug Cleaning

and Supplies Commercial

 72-Personal Services 1 0 0 0 0 N.A. 0 0 0 0 1 0

 721-Laundry, Cleaning, and Garment Services 1 0 0 0 0 0 0 0 0 0 0 0

 7211-Power Laundries, Family and Commercial 138 0 0 0 0 0 N.A. 61 0 6 61 0

 7213-Linen Supply 615 0 0 0 0 0 119 N.A. 2 0 177 0

 7216-Drycleaning Plants, Except Rug Cleaning 42 0 0 0 0 0 22 0 0 N.A. 20 0

 7218-Industrial Launderers 926 1 7 1 1 13 11 295 0 1 N.A. 11

 7219-Laundry and Garment Service** 1 0 0 0 0 0 0 0 0 0 0 0

 7359-Equipment Rental and Leasing** 22 0 0 0 0 0 0 22 0 0 0 0

 8980*** 1 0 0 0 0 0 0 1 0 0 0 0

 Totals 1,747 1 7 1 1 13 151 379 2 7 259 11

* Secondary SIC code included only for those facilities reporting this information. Number of facilities reporting secondary SIC codes does not equal number of facilities reporting primary SIC codes.

** Not elsewhere classified.

*** SIC code as reported by the surveyed facility. Not an actual SIC code.

Source: Section 308 Survey.

3-15
32 EPA defines linen items as: sheets, pillowcases, blankets, bath towels, washcloths, hospital

gowns and robes, tablecloths, napkins, tableskirts, kitchen textile items, continuous roll towels, laboratory

coats, household laundry (such as clothes, but not industrial uniforms), executive wear, mattress pads,

incontinence pads, and diapers. This list is meant to be inclusive. See the preamble to the proposed rule for

additional discussion of regulated entities.

33 EPA added clean room items to this list later in the decisionmaking process.

3-16

for other business entities for a fee or through a cooperative arrangement). This definition includes textile

rental companies that perform laundering operations; the industrial-laundered textile items may be owned

by either the industrial laundry facility or the offsite customer. Laundering means washing with water,

including water washing following dry cleaning (dual-phase laundering). (The rule would not have applied

to laundering exclusively through dry cleaning.) For facilities covered under the industrial laundry

definition, wastewater from all water washing operations would have been covered, including the washing

of linen items as long as these items do not constitute 100 percent of the items washed. Industrial textile

items include, but are not limited to, shop towels, printer towels/rags, furniture towels, mops, mats, rugs,

tool covers, fender covers, dust-control items, gloves, buffing pads, absorbents, uniforms, filters, and clean

room garments.

3.2.3.3 Launderers Not Covered by the Effluent Guideline

Certain launderers specifically do not meet the definition of an industrial laundry for the purposes

of EPA’s regulatory decisionmaking process. As discussed in the preamble to the proposed rule, discharges

from onsite laundering at industrial facilities; laundering of industrial textile items originating from the

same business entity; and facilities that exclusively launder linen items,32 denim prewash items, new items

(i.e., items directly from textile manufacturers, not yet used for their intended purpose), any other items that

come from hospitals hotels or restaurants, or any combination of these items were not to be covered by the

rule.33 In addition, the rule would not have applied to the discharges from oil-only treatment of mops.
34 The number of in-scope facilities at proposal was 1,747. The difference results from EPA’s

decision to exclude clean room items from the scope of a rule following proposal. 

35 1997. “Tackling the toughest textiles.” Industrial Launderer. January, pp. 27-28, 71.

3-17

3.3 THE STRUCTURE OF THE INDUSTRIAL LAUNDRIES INDUSTRY

3.3.1 Numbers and Types of Facilities and Firms

Based on Section 308 Survey data, EPA estimates that 1,74234 facilities in the United States meet

its definition of an industrial laundry. These facilities all engage in laundering of some industrial uniforms

or textiles, although this is not necessarily their only or primary activity. As discussed above, the Section

308 Survey is the main source of industry information used in this EA; data based on SIC classifications

generally do not coincide with the firms and facilities involved in industrial laundering activities as defined

by EPA.

Given the nature of the work performed by industrial launderers, many industrial laundries are

small, independently owned, single-facility firms that rent and launder textiles for customers in a specific

locality or region. The local to regional focus of the industry stems, in part, from the fact that, to provide a

service that involves delivering and retrieving items directly to and from the customer, the distribution area

serviced by the typical industrial laundry is not very large. On average, according to Section 308 Survey

data, industrial laundries service customers within 125 miles. Some “niche” laundries, which handle very

specific types of items or soils (e.g., highly contaminated gloves or shop towels), have larger service areas.

For example, Brent Industries, a company that rents and launders gloves and shop towels both to laundries

and directly to industrial customers, provides services in 24 states.35

In recent years, the number of larger, multifacility industrial laundry firms has increased, in part

due to changes in tax regulations. Much of this growth has occurred through industry consolidation, or

expansion by acquisition, rather than through independent development of multiple plants by a single owner
36 Paris, Alexander, Jr., 1994. Equity Research: Uniform Services. Barrington, IL: Barrington

Research Associates. November 22.

37 IIL, 1989. Op. cit.

38 1996. “Investment analyst sees healthy ‘96 for uniform rental with internal growth and

acquisitions.” Industrial Launderer. January, p. 12.

39 http://www.utsa.com/ceocenter/cintas-unitogrelease.htm

40 Paris, Alexander, Jr. 1994. Op. cit.

41 1996. “Association poised to meet industry’s operational challenges.” Industrial Launderer.

Op. cit.

42 The relative rarity of facilities processing less than 1 million pounds of laundry suggest some

economy of scale among smaller facility sizes, but the lack of many very large facilities indicates any

facility-level economies of scale tend not to continue beyond a certain point. Thus in the range of 3 million

to 7 million pounds of total laundry processed, laundries might achieve the greatest facility-level efficiency.

3-18

or parent firm.36,37 After the economy rebounded from the recession of the early 1990s and the business

environment improved, the rate of consolidation slowed somewhat, reflecting an apparent decline in the

number of small facility owners interested in selling their companies38 but not necessarily a decline in large

firm owners’ interest in expansion. Consolidation is still a factor in the current healthy economy, and it is

not just large facilities acquiring small ones, as evidenced by the recent announcement that Cintas is

acquiring Unitog, a $275 million firm.39 This merger trend is in line with consolidation trends throughout

the U.S. and global economies in the 1990s.

Larger, multifacility firms typically resemble their smaller, single-facility counterparts in that they

operate in local or regional markets, although a few may have national accounts as well.40,41 In competing

for customers, it is generally an advantage for an industrial launderer to have a local presence and

knowledge of the local business environment. As mentioned above, industrial laundries are also

geographically limited because customers must, for the most part, be within easy driving distance. Larger

firms may, however, have larger service areas than smaller firms because they are often more able to make

use of depots for delivery purposes.

On the facility level, few significant economies of scale in industrial laundering are apparent;42

production efficiency is more closely related to the age of a facility’s technology than to size. According to
43 Knight, Lynn, ERG, 1993. “Interview and site visit with Brian Keegan, Unifirst.” June 10. CBI

material in the Rulemaking Record.

44 Comment Response Document, PECON-2D, Tracking Nos. 1491, 1494, and 1495.

45 See the Section 308 Survey for more information on firm level classification.

3-19

some industry sources, efforts at consolidation are aimed more at purchasing customer accounts than

achieving cost savings. Generally, according to these same sources, there is no reduction in labor needs at

consolidated facilities,43 although others have noted that acquired facilities are sometimes converted to

depots with up to three-quarters of employment lost under such circumstances.44 Nevertheless, greater

operating efficiencies are likely to be present at the firm level since larger firms might experience some

advantages with their greater access to capital markets and from being able to invest more heavily in

marketing, technological improvements, and the development of professional management staff.

Reflecting the fact that individual industrial laundry facilities can have very different ownership

structures, the Section 308 Survey classified facilities into five categories:

# A—Facilities having an owner company that is subsumed under another company or legal

entity that, in turn, is owned by an ultimate parent company.

# B—Facilities having an owner company that is subsumed under an ultimate parent

company.

# C—Facilities that are also owner companies (and maintain their own financial records),

but that are subsumed under an ultimate parent company.

# D—Facilities having an owner company.

# E—Independent facilities (where the facility maintains its own financial records and is also

the owner company).

For purposes of some of the analyses discussed in this EA, facilities are examined in two groups (A, B, and

D combined, and C and E combined). Generally, ABD firms are analyzed at the owner-company level, as

multifacility firms, and CE firms are analyzed as single-facility firms.45
46 1996. “Association poised to meet industry’s operational challenges.” Industrial Launderer. 

Op. cit.

47 IIL, 1989. Op. cit.

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Table 3-5 provides a breakdown of facilities and firms by chain of ownership. The estimated 1,742

facilities correspond to 903 firms. The 912 ABD facilities are associated with 73 multifacility firms. The

830 CE facilities are single-facility firms (Section 308 Survey results).

3.3.2 The Market for Industrial Laundering Services

The industrial laundries industry operates in many small to medium-size markets, not one national

market, reflecting the local to regional focus of the businesses discussed above. Although some localities

are dominated by a single firm or a handful of firms, the typical market for industrial laundering services

appears to be quite competitive. The general characteristics of the industry also are consistent with what

might be expected in a competitive situation. Nothing suggests that individual laundries are engaging in

monopolistic or oligopolistic pricing strategies (except, possibly, in certain isolated markets); furthermore,

industry sources describe competition for customers as strong, particularly with regard to price.46 Most of

this competition centers around existing accounts, although the industry trade associations are encouraging

industrial launderers to expand into new markets.

3.3.2.1 Competitiveness in the Industrial Laundries Market

The large number of firms engaged in industrial laundering and the relative ease with which new

industrial laundries can be established makes it difficult for any one firm to dominate the market in which it

operates. Thus, firms tend to be price takers, rather than price setters. This is particularly true in more

densely populated urban and suburban areas, although even in more rural markets it is likely that new

industrial laundries will be established to compete with existing facilities if there are profits to be made.

The fact that there are generally several facilities owned by several firms in any market47 seems to support

this conclusion.
Table 3-5

Number of Firms and Facilities

by Chain of Ownership

Chain of Ownership Total Number*

Facilities

Type A 92

Type B 335

Type D 485

Total A\B\D\ 912

Type C 129

Type E 701

Total C\E 830

Total Facilities 1,742

Firms

Multifacility firms 73

Single-Facility Firms 830

Total Firms 903

* Weighted

Source: Section 308 Survey.

3-21
48 According to Section 308 Survey data, single-facility firms that began operation during the

survey timeframe (1991, 1992, and 1993) were estimated to have started up with a median capital

investment of approximately $81,000 (measured as total assets). The range of capital investments reported

by these facilities was $58,000 to $1.8 million per facility. Thus it appears that most laundry facilities can

be established with a capital investment of substantially less than $1 million.

49 IIL, 1989. Op. cit.

50 1997. “Don’t count out more public company acquisitions.” Industrial Launderer. August, 

p. 29.

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The initial capital investments required to establish a new industrial laundry are relatively low, and

there are no natural barriers to entering the industrial laundries market. A typical small, single-facility firm

can currently be established with a relatively small capital investment and relatively unskilled labor.48

Furthermore, facilities in related industries (i.e., engaged in other types of laundering) can be readily

converted to industrial laundries because they possess some (if not all) of the necessary equipment, as well

as general knowledge of the necessary skills. As their customer base and revenues have declined, for

example, linen suppliers (SIC 7213) have begun offering industrial laundry products and supplies.49

The increase in the number of large, multifacility firms in the industry (described in Section 3.3.1)

does not appear to have had a significant impact on the overall competitive structure of the industry,

although some local markets are more affected than others. Concentration in the industry is not extreme,

but some concentration is evident. The top five firms control about 55 percent of the market,50 and this

percentage might have grown with recent acquisitions (e.g., Cintas’ acquisition of Unitog). In theory, large

multifacility operations have the potential to gain a competitive edge over independent launderers because

they have more resources and greater access to capital markets and thus might be able to use price pressure

to increase market share. In addition, they could employ full-time professional marketing experts to try to

attract customers, and they might be more able to withstand the shocks of changing market conditions and

increased costs of adding environmental treatment technology. Multifacility firms still have to operate in

local or regional markets, however, and typically have no advantages over small, single-facility firms with

respect to knowing and being recognized in these markets. (In fact, a multifacility firm establishing a

laundry in a new locality can even be at a slight disadvantage, particularly if it is building a customer base

from scratch, rather than acquiring an existing facility with current accounts.) Thus, at this time, no

evidence supports the conclusion that multifacility firms enjoy sufficient advantages or are large enough
51 Levite, Caryn Adair, 1996. “Getting there first is half the sale.” Industrial Launderer. August, 

p. 30.

52 Johnson, Mark W., and Lintereur, Jacob J., 1998. “The Uniform Rental Industry.” Cleary Gull

Reiland & McDevitt Inc. Winter, p. 6.

53 Koepper, Ken, 1997. “1997: The year of the add-ons? Part 1.” Industrial Launderer. January,

pp. 21-22, 24. Also, Koepper, Ken, 1997. “1997: The year of the add-ons? Part 2.” Industrial Launderer.

February, pp. 16-18.

3-23

and few enough to dominate the industrial laundries market, on the aggregate level, through oligopolistic

behavior.

Evidence of the lack of differentiation among industrial launderers can be found in the attitudes and

behaviors of customers in selecting a rental uniform supplier. According to a 1996 UTSA study of how

customers choose a uniform rental company, customers “do not regard the selection of a supplier as a highrisk decision,” apparently because they perceive no significant differences among suppliers, particularly in

terms of price.51 Such attitudes are characteristic for customers in a competitive market. Increasingly,

individual firms and facilities are working to improve quality and customer service as a means of

differentiating themselves from their competitors. Strong customer service is key to remaining competitive.

Success in a service industry like the uniform rental industry is largely a function of fulfilling the

customer’s needs; therefore, intense attention to customer service is necessary to retain customers.52 In

addition, some industrial laundries have actively begun marketing add-on items such as continuous roll

towels, air fresheners, and direct-sale mats to attract customers because they believe customers want the

convenience of buying as much as possible from a single source.53

The observed behavior of individual firms in the industrial laundries industry also seems to confirm

that industrial laundries markets are, on the whole, competitive. Profit margins are generally small (see

Section 3.4.3), and there seem to be few opportunities for firms to earn and sustain large economic profits.

This pattern is consistent with theories of perfect competition, which predict that excessive profits in an

industry entice new firms to enter the market and therefore will be quickly competed away. In most of the

markets serviced by industrial laundries, profits are sufficient to keep firms from exiting, but are not

attractive enough to encourage many new firms to enter. Small profit margins could also be a reflection of

“predatory pricing” strategies, but, in this instance, profits are relatively small at nearly all firms and, as
54 1996. “Association poised to meet industry’s operational challenges.” Industrial Launderer. Op.

cit.

55 1995. “Strategic analysis of the textile rental industry: 1995.” Textile Rental. Op. cit.

56 U.S. EPA. 1989. Preliminary Data Summary for Industrial Laundries. Op. cit.

57 1997. “Wiper market watch: The view from EPA.” Industrial Launderer. February, pp. 61-63.

58Comment Response Document, PECON-7, Tracking No. 1552.

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noted above, few opportunities exist for even multifacility firms to substantially or quickly reduce costs per

unit laundered relative to others in the industry. Industry experts note that the primary means by which

firms can increase profits and remain competitive is to focus on improving productivity, service, and

quality.54,55

3.3.2.2 Substitutes for Industrial Laundering

Although there are services and products that can be substituted for industrial laundering, and

substitutes are of significant concern to the industry, substitutes might not currently pose the level of

competitive threat to the industrial laundries industry that the industry perceives. For example, customers

who rent uniforms could purchase garments outright and either establish onsite laundries or require

employees to maintain their own garments. Onsite laundries often are not as efficient as industrial

laundries, however, and individual workers, particularly those exposed to heavy-soil environments, might

not have the equipment and chemicals needed to clean many stains at home.56 Similarly, customers could

purchase disposable shop towels and mops, but industrial laundries’ products tend to be less costly, more

durable, and more absorbent. In fact, for the printing industry, there are currently no real disposable

alternatives to the reusable wiper towel; no disposables meet the industry’s need for wipers that are both

lint-free and highly absorbent.57,58

It is possible that disposables, particularly disposable shop towels (also known as “wipers”), might

prove to be a competitive threat in the future, and, as such, they are regarded with concern by many
59 Dunlap, David D., and Mary Anne Dolbeare, 1996. “Wiper marketing challenges mount.” 

Industrial Launderer. December, pp. 25-26, 30.

60 Comment Response Document, PECON-7, Tracking No. 1555 and PECON-7, Tracking No.

1531.

61 Comment Response Document, PECON-7, Tracking No.1531.

62 EPA’s Office of Solid Waste, is still investigating the possibility of regulating both disposable

and reusable shop towels under one rule.

63 Comment Response Document, PECON-7, Tracking No. 1552.

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industrial launderers.59 To date, however, disposable shop towels have not been able to gain a significant

foothold in key markets because some states require that disposable textiles contaminated with hazardous

soils be treated as hazardous wastes. The disposable industry argues that it is they who face a competitive

disadvantage and who are struggling to gain market share, not the industrial laundries, although the

industrial laundry industry argues otherwise.60 However, the disposables industry does not believe a rule

would have significantly affected demand for disposables.61 As of the date of this report, EPA’s current

RCRA policy relies on EPA regions and states to determine how best to regulate solvent-contaminated

reusable shop towels.62 Environmental regulations regarding solid waste reduction also increase the cost of

using disposables because this cost includes not only the cost of the textile itself but also the cost of getting

rid of it once it is soiled. At this time, therefore, few good substitutes for industrial laundering of shop

towels exist for many applications. In fact, the printers’ trade association expressed dismay that printers

would be “forced” to rely on disposables, clearly reflecting their opinion that reusable shop towels are not a

suitable substitute.63 (See Section Eight of this EA for a discussion of the potential for impacts of

regulatory options considered by EPA on price and thus on substitutability.)

EPA also has examined whether increased costs as a result of environmental regulation would

create incentives for customers to establish onsite laundries. To establish onsite laundries, customers would

have to purchase the equipment needed for processes such as textile cleaning, drying, sorting, and pressing.

Companies would typically make such capital investments only if faced with large incremental increases in

the cost (price) of industrial laundering. See Section Eight for a more detailed discussion of this subject.
64 Hobson, David F, 1996. “Wipers continue to be UTSA focus.” Industrial Launderer. October,

p. 114.

65 Mullen, Jocelyn, and Carl Lehrburger, 1991. A Solid Waste And Laundering Assessment of

Selected Reusable and Disposable Products. Report to the Textile Rental Services Association of

America, Hallendale, FL, and the Institute of Industrial Launderers, Washington, DC.

66 Koepper, Ken, 1997. “Blue ridge shop towels American style.” Industrial Launderer.

November, p. 12.

3-26

Nevertheless, major changes in laundering costs or in regulations regarding the treatment and

handling of hazardous substances on cloth and disposable wipers might have implications for whether

disposable products will be competitive substitutes for industrial laundering services in the future.64 An

industry study of the industrial wiper market65 found that cloth shop towels are more economical than paper

wipers, except for extremely dirty tasks requiring only one paper wiper. For cleaner tasks, quality cloth

towels can be used multiple times before laundering and can be laundered up to 30 times before being

disposed of.66 Thus, changes in the price of industrial laundering could reduce the economic advantages of

using cloth shop towels instead of paper in high-soil situations, but only if the price of using reusable shop

towels increases substantially.

3.3.2.3 Customers and the Demand for Industrial Laundering Services

As discussed earlier, industrial laundries meet customers’ needs for clean work apparel, clean work

materials, and clean work environments. In other words, industrial laundering services are intermediate

goods, or inputs in the production of final goods or services. Although there certainly is variation among

industrial laundries’ customers, the cost of laundering is most likely small relative to the cost of other

inputs. See Section Eight of this EA for a detailed discussion of operating costs for major industrial laundry

customers.

The industry demand curve for industrial laundering is downward sloping even though individual

firms perceive an elastic demand curve (in a competitive industry each firm acts as a price taker). The

industry demand curve is downward sloping as indicated by evidence provided by industry in comments.

According to industry, prices for industrial laundry services have been falling. Prices are falling, at least in
67 1994. “Strategic analysis of the textile rental industry: 1995.” Textile Rental. October, pp. 26-

28, 30, 32, 34, 36, 40, 42, 44, 46-47.

68 IIL, 1989. Op. cit.

69 Hobson, David F., 1996. “Wipers continue to be UTSA focus.” Industrial Launderer. Op. cit.

70 Paris, Alexander, Jr, 1994. Op. cit.

71 1996. “Investment analyst sees healthy ‘96 for uniform rental with internal growth and

acquisitions.” Industrial Launderer. Op. cit.

72 Hobson, David F., 1996. “Wipers continue to be UTSA focus.” Industrial Launderer. Op. cit.

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part, due to falling costs of production driven by increased productivity. Despite these declines in price,

revenues have been increasing at greater than the increase in gross domestic product (GDP). This scenario

(i.e., falling costs and falling prices with rising revenues) cannot occur without a downward sloping

demand curve. If industry can pass through cost savings, then it can pass through cost increases. Appendix

A provides a more detailed description of the demand for industrial laundering, as well as calculations of

elasticity based on Section 308 Survey data and historical output and price data. As Appendix A shows,

demand, with an elasticity of -0.593, is estimated to be somewhat inelastic.

3.3.3 Growth and the Industry’s Trajectory

 Since the 1970s and through the early 1990s, revenue growth in the industry has been

comfortable, but not outstanding, slightly outpacing GNP.67,68 Industry sources and investment analysts

generally have described the industrial laundries industry as “healthy.”69,70,71 On average, industry revenue

growth has exceeded inflation through the mid-1990s, and most launderers have received a small but

“comfortable” profit level in this timeframe.72 Between 1982 and 1992, for example, revenues for SIC 721

(Laundry, Cleaning, and Shoe Repair), which encompasses almost all industrial laundering facilities as well

as linen suppliers and dry cleaners increased at an average rate of 4.1 percent per year (adjusted for

inflation). Revenue data from the Section 308 Survey is consistent with this pattern; revenue for the

estimated 1,742 facilities engaged in industrial laundering activities grew an average real rate of 4.2 percent

per year between 1991 and 1993. Such growth reflects the influence of a variety of factors, including the

expansion of existing customer accounts, increased efforts at marketing and the broadening of the customer

base in nontraditional markets, gains in productivity, and the adoption of new technology. At the same time,
73 Comment Response Document, PECON-9B, Tracking Nos. 1584 and 1585.

74 1998. “The Uniform Rental Industry.” Cleary Gull Reiland & McDevitt, Inc. Winter, p.2

75 1996. “Regional trend analysis shows pockets of potential.” Industrial Launderer. Op. cit.

76 IIL, 1989. Op. cit.

77 Millunzi, Carolyn. 1998. “Trends and markets for your maximum growth.” Industrial

Launderer. May, p. 61.

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industrial laundries have reduced production costs by adopting techniques for enhanced labor productivity,

improving the efficiency of water and energy use, and extending the life of rental uniforms and linens.73

More recently, growth is expected to substantially outpace GDP. According to an October 1997

survey by TRSA, textile rental sales increased a robust 12.7% in 1996. Industry analysts estimate that the

uniform rental market is growing twice as fast as GDP, implying sustainable growth of 6-8 percent

annually over the next 3 to 5 years.74 Given this information and given the overall strength of the economy

over the intervening years since the Section 308 Survey was undertaken, EPA believes that the financial

health of the industry has improved since 1993. 

Since the size of the customer base and the resulting amount of textiles processed factor heavily

into the profitability of industrial laundries, the future growth of the industrial laundries industry depends

largely on the growth of current and potential customer industries. Because of the wide variety of

customers serviced by industrial launderers, no one class of customers serves as the bellwether for the

industrial laundries industry. There were some earlier signs that suggested that the rate of growth in the

industry might be slowing somewhat in the mid- to late 1990s. The rate of job growth among all industries

nationwide slowed to approximately 1.5 percent in the early to mid-1990s (in comparison to the 2.0 to 2.5

percent growth seen during the “boom years” of the previous decade75), and garment rental in the heavy soil

industries had declined by 1996.76 More recent trends, however, point to growth potential even in the heavy

soil industries in the coming years. One industry analyst points to one of the industrial laundries’ important

customer bases—automobile dealers and service stations. This industry is projected to grow substantially

during the next 5 years, leading to a growing market for industrial laundries services. This source further

hints at other customer industries that are growing even faster.77
78 Paris, Alexander, Jr., 1994. Op. cit.

79 1996. “Association poised to meet industry’s operational challenge.” Industrial Launderer. Op.

cit.

80 1996. “IL interview: Bob Vieno.” Industrial Launderer. September, pp. 41-42, 46.

81 Ibid.

82 Paris, Alexander, Jr., 1994. Op. cit.

83 1999. “First Aid: Step one in rebuilding your business.” Industrial Laundries, January, pp. 15-

21.

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Furthermore, aggressive marketing to the light-soil service and retail businesses have offset some

of the declines in the heavy-soil market to date. Data from the Department of Commerce, moreover, suggest

that job growth in many of the primary customer industries for industrial laundering — particularly the

services industries — is likely to exceed average job growth nationwide (see Table 3-6). Job growth serves

as an indicator of the health of the customer industry and represents a possible opportunity for increased

sales of uniforms and other products.

In general, industry analysts note that the potential market for industrial laundries’ services is

several times greater than the current market.78,79,80 The growth of the service economy, for example, offers

opportunities for industrial launderers to further develop the image- and identity-oriented side of their

businesses. In fact, laundries that adopt formal door-to-door sales strategies, as opposed to relying on an ad

hoc sales and marketing staff, find their expansion limited more by internal resource constraints than by an

inability to attract customers.81 Industrial launderers also can expand their businesses by pursuing rental

contracts with the large number of employers who currently maintain onsite laundries or who require

employees to clean their own work uniforms.82 Additional market areas beyond the traditional laundry

services are being pursued as well. For example, first aid supplies are now being offered by some industrial

laundries83 in addition to add-on products such as jeans, continuous roll towels, liquid hand soap, and air

fresheners.
Table 3-6

Actual 1994 Employment and Projected 2005 Employment in the Top Customer Industries

For Industrial Landerers in 1995*

(in thousands)

Major Employment (000) Percent

SIC Group Title 1994** 2005*** Change

55 Automotive Dealers & Service Stations 2,153 2,252 5%

75 Auto Repair, Services, and Parking 971 1,345 39%

58 Eating and Drinking Places 7,069 8,089 14%

54 Food Stores 3,289 3,930 19%

17 Special Trade Contractors 3,073 3,437 12%

50, 51 Wholesale Trade -- Durable and Nondurable Goods 6,140 6,559 7%

35 Industrial Machinery and Equipment 1,985 1,769 -11%

27 Printing and Publishing 1,542 1,627 6%

73 Business Services 6,239 10,032 61%

20 Food and Kindred Products 1,680 1,696 1%

80 Health Services 10,082 13,165 31%

34 Fabricated Metal Products 1,387 1,181 -15%

82 Educational Services 10,187 12,400 22%

59 Miscellaneous Retail 2,560 3,012 18%

* Data reflects all employees.

** Employment data from 1994 presented because 1994 data was used to project 2005 employment.

*** Projected employment in 2005 based on moderate growth assumptions.

Source: U.S. Department of Labor, 1997. "Employment by industry and occupation, 1994 and projected 2005 

 alternatives. Total, all occupations." Bureau of Labor Statistics (BLS), Office of Employment Projections.

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3-31

3.4 INDUSTRY DEMOGRAPHICS

3.4.1 All Industrial Laundry Facilities

The 1,742 facilities engaged in industrial laundering in the United States vary significantly with

respect to the types and amount of items they clean, the amount of wastewater they generate, the number of

people they employ, and the revenues they earn, among other characteristics. As a result, it is not possible

to describe a “typical” industrial laundry. This section therefore discusses the range of industrial laundry

facilities found in the Section 308 Survey database.

3.4.1.1 Types and Volume of Items Laundered

According to Section 308 Survey data, the total amount of textiles laundered annually by all

industrial laundries is approximately 9.4 billion pounds, with the average industrial laundry facility

processing 5.4 million pounds annually. However, volumes processed range widely from facility to facility,

as illustrated by Table 3-7. Approximately 2 percent of industrial laundry facilities are quite small and

wash less than 300,000 pounds of textiles per year. An additional 7 percent launder between 300,000 and

1,000,000 pounds per year. On the other extreme, 36 percent of facilities launder more than 5 million

pounds per year.

Approximately 51 percent of the total volume of items washed by the 1,742 industrial laundry

facilities are industrial textiles. Nonindustrial textiles such as linens, flatwork, and health care items

account for the remaining 49 percent. These data reflect the fact that linen supply firms cross over into

industrial laundering activities and vice versa, as well as the fact that facilities primarily engaged in linen

supply activities are considered industrial laundries under the regulation if they launder even small

quantities of industrial items. As Table 3-8 indicates, facilities handling 1 million pounds of textiles or

more per year account for almost all (99 percent) of total annual industry production.
Table 3-7

Number of Facilities by Annual Production

Number of Percent of Total lbs Laundered

 Annual Production Facilities Facilities Annually by Group

 Less than l,000,000 lbs 167 10% 76,386,023

 >=1,000,000 lbs and <2,000,000 lbs 264 15% 376,713,085

 >=2,000,000 lbs and <3,000,000 lbs 211 12% 508,879,534

 >=3,000,000 lbs and <4,000,000 lbs 231 13% 806,697,157

 >=4,000,000 lbs and <5,000,000 lbs 254 15% 1,152,448,718

 >=5,000,000 lbs and <6,000,000 lbs 144 8% 784,269,443

 >=6,000,000 lbs and <7,000,000 lbs 116 7% 754,574,370

 >=7,000,000 lbs and <10,000,000 lbs 116 7% 937,639,671

 10,000,000 lbs or greater 245 14% 3,960,935,763

 Total Number of Facilities 1,747 100% 9,358,543,764

Source: Section 308 Survey.

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Table 3-8

Volume of Textiles Laundered by Industrial Laundries,

by Type of Textile and Production Group

Annual Production at the Facility Level Total Annual

Less than 1 million lbs 1 million lbs or greater Industry

 Textile Type lbs laundered % of total vol. lbs laundered % of total vol. Production

 Industrial Garments 6,911,593 0.30% 2,282,802,624 99.70% 2,289,714,217

 Shop Towels and Printer Towels 24,186,721 5.02% 457,258,414 94.98% 481,445,135

 Floor Mats 7,029,910 0.39% 1,796,974,890 99.61% 1,804,004,800

 Mops, Dust Cloths, and Tool Covers 1,622,980 1.30% 122,998,088 98.70% 124,621,068

 Fender Covers 14,784 0.04% 36,044,709 99.96% 36,059,493

 Clean Room Garments 4,929,126 29.59% 11,729,595 70.41% 16,658,721

 Other Industrial Textiles* 37,255 0.85% 4,355,905 99.15% 4,393,160

 Total Industrial Textiles 44,732,370 0.94% 4,712,164,226 99.06% 4,756,896,595

 Linen Supply Garments 441,930 0.16% 273,996,866 99.84% 274,438,796

 Flatwork/Fulldry 21,474,561 0.65% 3,277,523,870 99.35% 3,298,998,431

 Health Care Items 5,986,931 0.81% 731,770,997 99.19% 737,757,928

 Continuous Roll Towels 117,978 0.10% 117,707,097 99.90% 117,825,075

 Other Non-Industrial Textiles** 3,632,253 2.10% 168,994,683 97.90% 172,626,936

 Total Non-Industrial Textiles 31,653,654 0.69% 4,569,993,514 99.31% 4,601,647,167

 Total lbs. Laundered 76,386,023 0.82% 9,282,157,739 99.18% 9,358,543,763

* Includes laundry bags, filters, buffing pads, and other industrial items.

** Includes family laundry, absorbents, new items, and executive wear.

Source: Section 308 Survey (based only on facilities for which there is sufficient information).

3-33
84 The Small Business Administration (SBA) defines “small” on the basis of revenues. This

breakdown between small and large will be discussed in detail in Section Nine.

3-34

3.4.1.2 Wastewater Generated

The quantity, or flow, of wastewater generated by industrial laundering activities is related to the

amount and types of items laundered, the soils contained in these items, and the water conservation

measures employed by each individual facility. As such, flow, like textile production volume, also ranges

from facility to facility. Table 3-9 presents a breakdown of industrial laundering facilities by flow. The

average flow volume for industrial laundries is 13.9 million gallons per year of wastewater. Flow rates

from facilities range from 148,000 gallons per year to 204,500,000 gallons per year. Note that flow should

not be interpreted as a complete description of the industrial laundries effluent stream because it is

calculated simply on the basis of the volume of water produced and not the concentration of pollutants.

3.4.1.3 Employment

An estimated 128,000 people are employed in industrial laundry facilities in the United States,

according to Section 308 Survey data. Although nearly 20,000 of these people (15 percent) are engaged

primarily in management and administration, most are production employees. Production employees, as

discussed earlier in Section 3.2.2.2, are typically unskilled or semiskilled laborers.

Approximately 20 percent of all industrial laundry facilities have 30 employees or fewer; as

indicated in Table 3-10, almost all of these small facilities (85 percent) are single-facility firms.84 At the

other end of the scale, only 1 percent of industrial laundries employ more than 200 workers. The average

number of employees per facility is 73; of these, 62 are production employees and 11 are in management

and administration.

Facilities with 30 employees or fewer, on average, handle fewer pounds of textiles per employee, at

higher costs per pound, than facilities with more than 30 employees. This difference suggests that there

might be slight economies of scale in industrial laundering. Production amounts and costs vary widely,

however, particularly at facilities with more than 30 employees. Thus, any economies of scale that exist do
Table 3-9

Number of Facilities by Annual Flow

Number of Percent of Total Annual Flow Percent of Total

 Annual Flow Facilities Facilities by Group (gals/yr) Flow by Group

 Less than 1,000,000 gallons/year 32 2% 8,196,303 0.03%

 >=1,000,000 and <5,000,000 gallons/year 318 18% 1,068,764,447 4.41%

 >=5,000,000 and <10,000,000 gallons/year 471 27% 3,353,564,121 13.84%

 >=10,000,000 and <20,000,000 gallons/year 502 29% 6,890,983,819 28.44%

 >=20,000,000 and <30,000,000 gallons/year 244 14% 5,558,530,911 22.94%

 >=30,000,000 gallons/year 181 10% 7,351,249,874 30.34%

 Total Number of Facilities 1,747 24,231,289,475

Source: Section 308 Survey.

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Table 3-10

Number of Facilities by Employment Group

Nonindependent Facilities Single Facilities All Facilities

 Number of Employees Number Percent Number Percent Number Percent

 Less than 10 0 0% 39 5% 39 2%

 >=10 and <30 53 6% 263 32% 316 18%

 >=30 and <65 242 26% 249 30% 491 28%

 >=65 and <100 374 41% 209 25% 583 33%

 >=100 and <200 232 25% 63 8% 296 17%

 200 or more 16 2% 6 1% 23 1%

 Total Number of Facilities 917 830 1,747

Source: Section 308 Survey.

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3-37

not appear to be substantial, although the statistical significance of the variation in costs by facility size has

not been tested.

Consistent with there being no substantial economies of scale at the facility level and with the

labor-intensity of industrial laundering, the average number of workers employed at the facility level

increases with production volume (i.e., facilities processing more textiles require more employees) (see

Table 3-11).

3.4.1.4 Operating Costs and Revenues

Given the production and size variations discussed above, it is not surprising that industrial

laundries’ operating costs and revenues also span a wide range. Table 3-12 provides a breakdown of

nonindependent facilities (those belonging to multifacility firms) and single facilities (those belonging to

single-facility firms) by revenue group. To calculate the median operating costs and revenues for each

group, EPA used Section 308 Survey data on individual facilities’ and firms’ operating costs and revenues.

For each individual facility and firm, EPA estimated operating costs and revenues by averaging 3 years of

survey data (1991, 1992, and 1993) in 1993 dollars. (Financial data in this EA are reported in 1993 dollars

unless otherwise noted.)

The average industrial laundry facility has revenues of $4.3 million in 1993 dollars. On the whole,

nonindependent facilities, which are part of larger multifacility firms, are slightly larger than single-facility

firms in terms of both operating costs and revenues; average revenues for nonindependent facilities were

$5.0 million, while average revenues for single-facility firms were $3.4 million. This reflects the fact that,

on average, nonindependent facilities handle higher production volumes than single-facility firms.

Moreover, the facilities that handle very small volumes of textiles (under 500,000 pounds annually) are all

single-facility firms. Nevertheless, average costs and revenues for facilities handling approximately the

same volume of textiles are relatively similar (see Table 3-13).

Multifacility firms also provided EPA with information on receipts at the owner-company level.

Table 3-14 provides a breakdown of these firms by revenue group. Mean revenues are calculated using
Table 3-11

Average and Total Number of Employees for Facilities

In Each Production Group

Annual Production at the Facility Level

Less than >=1 million lbs 5 million lbs All

1 million lbs but <5 million lbs or more Facilities

 Production Employees

 Average number of employees per facility 14 44 103 62

 Total number of employees 2,394 42,040 63,848 108,282

 Management and Administration Employees

 Average number of employees per facility 6 9 16 11

 Total number of employees 1,037 8,797 9,932 19,766

 All Employees

 Average number of employees per facility 21 53 119 73

 Total number of employees 3,431 50,838 73,780 128,048

Source: Section 308 Survey.

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Table 3-12

Nunber of Nonindependent and Single Facilities, Average Revenues,

and Average Operating Costs for Each Revenue Group (1993 $)

Number of Average Annual Average Annual Operating Avg. Operating Costs

 Revenue Group Facilities Revenues per Facility* Costs per Facility* as a % of Revenue**

Nonindependent Facilities

 <$1 Million 47 $713,473 $740,604 107%

 >=$1 Million and <$3.5 Million 257 $2,165,290 $1,750,122 81%

 >=$3.5 Million and <$7 Million 405 $4,854,545 $4,386,794 90%

 >=$7 Million and <$10.5 Million 156 $9,179,807 $8,039,859 88%

 >=$10.5 Million 47 $12,909,232 $11,269,148 87%

 All Nonindependent Facilities 912 $5,042,254 $4,438,798 88%

Single Facilities

 <$1 Million 182 $636,258 $601,073 97%

 >=$1 Million and <$3.5 Million 292 $2,036,557 $1,777,440 90%

 >=$3.5 Million and <$7 Million 258 $4,719,935 $4,305,133 92%

 >=$7 Million and <$10.5 Million 81 $8,171,814 $7,211,935 88%

 >=$10.5 Million 18 $15,416,262 $13,416,214 87%

 All Single Facilities 830 $3,443,624 $3,080,149 92%

All Facilities

 <$1 Million 228 $651,987 $629,496 99%

 >=$1 Million and <$3.5 Million 549 $2,096,840 $1,764,648 86%

 >=$3.5 Million and <$7 Million 663 $4,802,161 $4,355,015 91%

 >=$7 Million and <$10.5 Million 237 $8,836,064 $7,757,522 88%

 >=$10.5 Million 65 $13,589,341 $11,851,605 87%

 All facilities 1,742 $4,280,409 $3,791,319 90%

* Figures in 1993 $ based on average revenues and average costs over the three years from 1991 to 1993.

** Average of ratios calculated on a per-facility basis. Does not reflect relationship between average revenues and costs as reported in this table

 because these figures may not be based on the same average facility. Figures above 100% reflect the fact that facility costs and revenues

 are calculated based on a 3-year average. For some facilities, revenues exceeded costs in each of the 3 years covered by the Survey,

 but costs exceeded revenues on average.

3-39
Table 3-13

Average and Total Revenues and Operating Costs for Facilities

in Each Production Group (1993 $)

Annual Production at the Facility Level

Less than >=1 million lbs 5 million lbs All

1 million lbs but <5 million lbs or more Facilities

 Nonindependent Facilities

 Average revenue per facility* $758,936 $3,281,432 $6,909,441 $5,042,254

 Average operating costs per facility* $823,940 $2,829,663 $6,125,213 $4,438,798

 Number of nonindependent facilities 31 417 464 912

 Single Facilities

 Average revenue per facility* $999,020 $3,029,328 $6,915,453 $3,443,624

 Average operating costs per facility* $977,181 $2,635,831 $6,371,593 $3,080,149

 Number of nonindependent facilities 130 543 157 830

* Figures in 1993 $ based on average revenues and average costs over the 3 years from 1991 to 1993.

Source: Section 308 Survey.

3-40
Table 3-14

Number of Multifacility Firms and Average Revenues

for Each Revenue Group (1993 $)

Number of Average Annual

 Revenue Group Firms Revenues per Firm

 <$3.5 Million** 7 $1,038,204

 >=$3.5 Million and <$7 Million 8 $4,644,041

 >=$7 Million and <$10.5 Million 10 $8,501,095

 >=$10.5 Million 48 $319,648,406

 All Multifacility Firms 73 $212,458,713

* Figures in 1993 $ based on average revenues and average costs over the 3 years from 1991 to 1993.

** Firms in the <$1 million revenue group were combined with firms in the >+$1 million and <$3.5 million

 group to protect confidentiality.

Source: Section 308 Survey.

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85 According to the SBA, firms in SIC 7211, 7213, and 7218 are “small” if they have under $10.0

million (SIC 7218) or $10.5 million (SIC 7213 and 7211) in annual revenues. EPA uses the $10.5 million

cutoff for the purposes of this analysis.

86 Antonelli, Joe, 1996. “Getting to know your uniform costs.” Industrial Launderer. July, pp.

47-48, 50, 52.

3-42

each firm’s 3-year average in the same manner as that described above. For the single-facility firms, firmlevel numbers are the same as the facility-level numbers in Table 3-12.

Based on firm-level revenues, 812 single-facility firms (97.8 percent of all single-facility firms) and

25 multifacility firms (34 percent of all multifacility firms) meet the definition of “small” used by EPA and

SBA to classify small businesses under the Small Business Regulatory Flexibility Act (SBREFA),85 for a

total of 837 small businesses, or 92.7 percent of all firms.

Although the Section 308 Survey gathered information on revenues earned at the facility- and firmlevel from the laundering of industrial and nonindustrial textiles, as well as the percentage of total revenues

earned from laundering the various types of textile items, EPA found that responses to these questions were

not always reliable nor consistent with the definitions of “industrial” and “nonindustrial” EPA used in its

decisionmaking process. The data on revenues by types of textiles laundered therefore are not presented in

this EA.

3.4.1.5 Price

Revenues in the industrial laundries industry really cannot be calculated with reference to a single

per-unit price. Instead, in developing a pricing strategy, a laundry generally takes into consideration a

variety of factors, including the original cost of the textile rented or sold, the lifetime of the textile (if

rented), and the cost and frequency of required maintenance.86 Uniforms, for example, often are priced on a

“per wearer” basis, which incorporates specific assumptions about the number of changes required per

week. The average weekly revenue per uniform wearer for industrial laundries in 1992 was approximately
87 IIL, 1993. Op. cit. In the absence of price data, revenue is assumed to be a proxy for price.

88 IIL, 1988. An Analysis Of The Industrial Wiper Market. Op. cit.

89 Ibid.

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$6.14.87 For shop towels, prices per shop towel in the late 1980s range from under 21⁄2 cents to over 8

cents, again reflecting the absence of any standard industry pricing pattern.88

Customers that purchase laundering services in large quantities (e.g. uniforms for an entire

company) may be offered bulk discount prices or add-on services (such as laundering of rented mats) at no

additional charge. About half of the users of rental shop towels, for example, also receive uniforms from

their suppliers. For such customers, shop towels and other peripheral items may be priced to undercut

competitors as part of a strategy to attract and retain uniform rental accounts because the uniform rental

business tends to be extremely competitive and price sensitive.89

3.4.2 Industrial Laundry Facilities that Meet Cutoffs Considered by EPA for an Exclusion

from a Rule

Table 3-15 highlights the fact that, as a group, facilities that were considered for exclusion from a

rule have a rather different profile from the laundries industry as a whole (shown in the No Cutoff column).

Small facilities generate smaller profits and substantially less wastewater on an individual facility basis.

Baseline pollutant loadings from these facilities, moreover, account for a small percentage of the overall

industry loadings.

In recognition of the differences between small and large facilities, EPA investigated three cutoffs

(in comparison to a no cutoff scenario).

# No cutoff for the exclusion: all facilities would have been regulated. This is called No

Cutoff for the purposes of this EA and is used for comparative purposes only.

# A cutoff excluding all facilities laundering less than 1 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year (this

cutoff is identical to that proposed). This cutoff is called the 1MM/255K cutoff for the

purposes of this EA.
Table 3-15

Comparison of Facilities Meeting Cutoffs Considered Compared to

the No-Cutoff Scenario

Cutoff

No Cutoff 1MM/255K 3MM/120K 5MM/255K

Single-Facility Firms

Number of Facilities 830 128 363 556

Average Revenues $3,443,624 $833,789 $1,337,635 $2,106,280

Average Operating Costs $2,175,648 $472,755 $827,776 $1,288,068

Average Flow Rate 6,591 5,239 15,056 23,724

Average Number of Employees 54 19 26 38

Average Total Production 3,542,459 369,967 1,109,865 1,898,181

Nonindependent Facilities

Number of Facilities 912 8 155 396

Average Revenues $5,042,254 $1,312,507 $1,683,637 $3,210,769

Average Operating Costs $4,438,798 $1,255,711 $1,223,306 $2,784,947

Average Flow Rate 17,359,857 1,750,168 5,245,592 9,141,006

Average Number of Employees 91 27 37 56

Average Total Production 7,032,389 836,690 2,073,478 3,167,721

All Facilities

Number of Facilities 1,742 136 518 953

Average Revenues $4,280,409 $863,523 $1,440,898 $2,565,767

Average Operating Costs $3,360,269 $521,386 $945,821 $1,910,797

Average Flow Rate 9,105,353 113,619 1,576,098 3,816,680

Average Number of Employees 73 19 29 45

Average Total Production 5,369,225 398,956 1,397,453 2,426,333

Source: Section 308 Survey data.

3-44
90 S corporations are firms that have elected to be taxed at the shareholder level, rather than at the

corporate level, under Subchapter S of the Internal Revenue Code.

3-45

# A cutoff excluding all facilities that launder between 1 and 3 million pounds of incoming

laundry (total) and less than 120,000 pounds of shop and/or printer towels per calender

year, in addition to those facilities laundering less than 1 million pounds of incoming

laundry (total) and less than 255,000 pounds of shop and/or printer towels per calender

year. This cutoff is called the 3MM/120K cutoff for the purposes of this EA.

# A cutoff excluding all facilities laundering less than 5 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year. This

cutoff is called the 5MM/255K cutoff for the purposes of this EA.

Existing facilities laundering less than the cutoffs listed above would have been excluded from regulation. 

Approximately 8 to 55 percent of the facilities that otherwise meet EPA’s definition of an industrial

laundry (136 to 953 out of 1,742 facilities) might have been eligible for exclusion. All the excluded

facilities are small entities under the Small Business Administration (SBA) definition of small entity. New

facilities would also have been entitled to these exclusions.

3.4.3 Financial Conditions at the Firm Level

As mentioned earlier, there are 903 industrial laundry firms associated with 1,742 industrial

laundry facilities through five general chains of ownership (identified as A, B, C, D and E in the Section

308 Survey) in the United States. Seventy-three of these firms (those linked to A, B, and D facilities)

maintain financial records for multiple laundering facilities. The remaining 830 firms (those linked to C and

E facilities) are associated with single facilities. Firms with A, B, and C facility ownership patterns also are

associated with an ultimate parent company.

A variety of organizational structures can be found in each ownership grouping. Although most

industrial laundries are structured as standard corporations, which results in the corporation paying

corporate income tax, approximately 382 of the 903 industrial laundry firms (42 percent) are S

corporations,90 limited partnerships, and sole proprietorships, which are taxed at the owner-level (at rates

for individual taxpayers), rather than at the firm-level. With the exception of an estimated 10 owner firms
91 Note, however, despite slim profit margins, returns on investment in small firms are reasonable,

due to the small investment required to start up and operate a laundry (see discussion in Section Nine of

this EA and Table 9-1).

3-46

of type-D facilities, most of the S corporations are single-facility (CE) firms. Most industrial laundries are

privately held, but some of the larger multifacility firms are publicly held.

As noted earlier, to examine the firm-level impacts of the proposed standards, EPA grouped

industrial laundries into two categories on the basis of ownership category; ABD multifacility firms are

analyzed separately from CE single-facility firms. Data for these analyses were taken from the Section 308

Survey database.

Table 3-16 presents average baseline summary financial data on the firms in the industrial laundry

industry. Since financial conditions at multifacility firms reflect the aggregate conditions at several

facilities, multifacility firms typically earn more revenue and have greater assets and financial resources

than single-facility firms. This is not always true of multifacility and single-facility firms within each

revenue group; earnings at single-facility firms are higher than those at multifacility firms in the $3.5

million to $7 million and the $7 million to $10.5 million revenue groups, for example. However, the

average ratio of earnings before interest and taxes (EBIT) to revenues (which is used as a proxy for profit

margin) is higher at multifacility firms than at single-facility firms in all revenue groups.91

Possible differences between the two types of firms with respect to financing capital investments

are reflected in the fact that, in some revenue groups, single-facility firms have higher average total assets

and owner equity, while multifacility firms have higher average total liabilities.

The baseline and postcompliance financial health of firms in the industrial laundries industry is

discussed in greater detail in Section Six. Postcompliance impacts are calculated relative to baseline

financial conditions.
Table 3-16

Number of Firms and Average Financial Measures

for Each Revenue Group (1993 $)

Number of Earnings Before Working Total Total Owner Ratio of Earnings to

 Revenue Group Firms Interest and Taxes Capital Assets Liabilities Equity* Revenues**

Multifacility Firms

 <$3.5 Million*** 7 $338,244 $546,696 $1,135,711 $714,855 $420,857 0.1353

 >=$3.5 Million and <$7 Million 8 $200,027 $1,028,953 $2,317,731 $1,050,920 $1,265,441 0.0258

 >=$7 Million and <$10.5 Million 10 $669,794 $1,795,676 $5,717,464 $2,430,647 $3,286,817 0.0470

 >=$10.5 Million  48 $11,365,961 $17,697,501 $81,211,283 $26,800,090 $54,411,216 0.0464

 All Multifacility Firms** ** 73 $7,549,274 $11,945,014 $54,054,702 $17,979,079 $36,075,479 0.0524

Single-Facility Firms

 <$1 Million 182 $2,462 $8,680 $246,720 $198,887 $32,079 0.0008

 >=$1 Million and <$3.5 Million 292 $91,310 $189,454 $827,992 $429,221 $403,588 0.0034

 >=$3.5 Million and <$7 Million 258 $268,154 $560,027 $3,161,855 $903,575 $2,275,879 0.0032

 >=$7 Million and <$10.5 Million 81 $1,032,098 $1,316,423 $13,077,679 $1,246,974 $11,887,875 0.0111

 >=$10.5 Million 18 $2,129,316 $2,010,339 $20,246,504 $3,636,866 $16,609,638 0.0274

 All Single-Facility Firms 830 $261,473 $413,148 $3,028,406 $673,667 $2,364,007 0.0040

* Owner equity is being used as a proxy for retained earnings in Altman Z" analyses of firm-level impacts.

** The ratio of earnings to revenues is a proxy for profit margin (or the ratio of earnings to sales), for comparison of multifacility and single-facility firms.

*** For multifacility firms, firms in the <$1 million revenue group were combined with firms in the >=$1 million and <$3.5 million group to protect confidentiality.

**** Two weighted firms that are statistical outliers were not included in the calculation of financial measures.

Source: Section 308 Survey.

3-47
1Most market model results are provided in Appendix A. Results in the main text of this EA

generally reflect an assumption that regulatory costs could not have been passed through to customers.

4-1

SECTION FOUR

ECONOMIC IMPACT ANALYSIS METHODOLOGY

OVERVIEW AND COMPLIANCE COST ANALYSIS

This section covers several components necessary for identifying and characterizing the potential

impacts of regulatory compliance costs at the facility and owner-company levels and other potential

secondary impacts for all regulatory options that were considered at the time of EPA’s decision not to

promulgate pretreatment standards for the industrial laundries point source category. Section 4.1 provides

an overview of the methodology used in analyzing the economic impact of the regulatory compliance costs.

Section 4.2 discusses the cost annualization model, which is the fundamental component of this

methodology. Section 4.3 summarizes the results calculated using this model (i.e., the total annualized cost

of compliance for the industrial laundries industry as a whole for each of the regulatory options

considered).

4.1 METHODOLOGY OVERVIEW

Together, the regulatory analyses presented in this EA offer a comprehensive assessment of

potential economic impacts of regulatory options at all relevant levels of activity. Figure 4-1 shows how the

four principal models used in the EA (the cost annualization model, the facility closure model, the owner

company model, and the market model)1 relate to one another, the inputs required for these models, and the

outputs they generate. At the heart of the EA is the cost annualization model, which uses facility-specific

cost data and other inputs (from EPA’s Final Development Document) to determine the annualized capital

and operating and maintenance (O&M) costs of improved wastewater treatment. Annualized cost data feed

into the facility analysis, which models the economic impacts of regulatory costs on individual industrial

laundry facilities, irrespective of ownership. The firm-level analysis assesses the ability of all firms to raise

the capital necessary to purchase and install pollution control equipment. This is a different analysis from

that determining whether a facility’s cash flow can meet the expenses associated with meeting regulatory
4-2

Employment Impacts

(SECTION 7)

Regulatory Flexibility

(SECTION 9)

Number

of Facility

Closures (Baseline

and Postcompliance

(SECTION 5)

Likely OwnerCompany Failures

and Other

Significant Impacts

(SECTION 6)

Total Annual 

Cost of

Compliance

(SECTION 4)

Firm-Level

Analysis

(SECTION 6)

Market

Model

APPENDIX A

Cost Annualization

Model

(SECTION 4)

Facility Impact

Analysis

(SECTION 5)

Annual Cost of Compliance

Per Facility

Market

Impacts

MODELS

MODEL

OUTPUTS

Figure 4-1. Relationships of the four principal models used in this economic analysis.
2

 Cost data are from EPA’s Final Development Document.

4-3

requirements. A firm or its facilities (if a multifacility firm) might be able to afford the costs of pollution

control, but the firm itself might be too weak financially to attract the capital to make the purchase. The

market model estimates changes in market price and quantity due to increased facility regulatory costs (see

Appendix A). The EA then explores impacts on employment and other measures of community welfare.

Additional analyses examine whether increased compliance costs would have affected domestic or

international markets, customers, consolidation, inflation, new sources, or small businesses.

4.2 COST ANNUALIZATION MODEL

4.2.1 Purpose of Cost Annualization

The cost annualization model estimates each facility’s annual compliance cost on the basis of the

costs required to purchase and operate new pollution control equipment for each technology option that was

considered for the industrial laundries point source category. Cost annualization calculations consider the

changes in annual cash outflow for each facility due to pollution control expenditures, once the tax effects

of these expenditures (e.g., depreciation tax shields) are taken into account. Pollution control expenditures

can be divided between two components: the initial capital investment to purchase and install the equipment

and the annual cost of operating and maintaining such equipment (O&M costs). Capital costs are a onetime expense incurred only with the acquisition of the equipment, while O&M costs are incurred every year

of the equipment’s operation. The engineering cost model used to estimate facility compliance costs defines

both capital and O&M costs.2

To determine the economic feasibility of upgrading a facility, the costs of compliance must be

compared to each facility’s precompliance cash flow. Pollution control costs cannot be directly compared

to first-year facility cash flow, however; the capital costs must be annualized, reflecting the fact that capital

equipment costs are incurred only once and can be financed (i.e., spread out over the equipment’s lifetime).
3

 The annualized cost is analogous to a mortgage payment, which spreads the one-time investment

in a home into a series of continual monthly payments. An annualized cost approach also more closely

reflects how companies report expenditures on pollution control equipment. This equipment must be

capitalized, not expensed according to IRS requirements: The equipment can be depreciated, but the total

cost of the equipment cannot be subtracted from income in the first year (Commerce Clearinghouse, Inc.,

1995. U.S. Master Tax Guide, 1995; and Research Institute of America, Inc., 1995. The Complete

Internal Revenue Code [Section 169]. New York, NY: Research Institute of American, Inc., January).

4-4

In the model, EPA calculates total annualized costs by allocating the capital investment over the

lifetime of the equipment, using a cost-of-capital factor to address the costs associated with raising or

borrowing money for this investment, and adding in annual O&M costs. The resulting annualized cost

represents the average annual payment a given company will need to make to upgrade its facility.3 EPA

investigates whether a firm can raise the capital to make the investment in the firm-level analysis.

4.2.2 Inputs, Assumptions, and Model Outputs

4.2.2.1 Regulatory Options

The engineering cost estimates that feed into the cost annualization model are based on a set of two

regulatory options, each with three exclusions for small facilities considered. The two regulatory options

included chemical precipitation (known as the CP-IL option) and dissolved air flotation (known as the

DAF-IL option). The three exclusions (plus a no-exclusion scenario used for comparison) that were

considered for both regulatory options included:

# A cutoff excluding all facilities laundering less than 1 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year (this

cutoff is identical to that proposed). This cutoff is called the 1MM/255K cutoff for the

purposes of this EA.

# A cutoff excluding all facilities that launder between 1 and 3 million pounds of incoming

laundry (total) and less than 120,000 pounds of shop and/or printer towels per calender

year, in addition to those facilities laundering less than 1 million pounds of incoming

laundry (total) and less than 255,000 pounds of shop and/or printer towels per calender

year. This cutoff is called the 3MM/120K cutoff for the purposes of this EA.
4U.S. EPA, 1997. Economic Assessment for Proposed Pretreatment Standards for Existing and

New Sources for the Industrial Laundries Point Source Category. EPA 821-R-97-008, Office of Water,

November.

5

63 FR 71054 (December 23, 1998).

6See the preamble to the Final Action for EPA’s rationale. EPA also found the CP-IL option at the

5MM/255K cutoff to be economically achievable.

7

 The terms “option” and “alternative” are used interchangeably in this section.

4-5

# A cutoff excluding all facilities laundering less than 5 million pounds of incoming laundry

(total) and less than 255,000 pounds of shop and/or printer towels per calender year. This

cutoff is called the 5MM/255K cutoff for the purposes of this EA.

Other options that were analyzed at proposal, including the organics control option (OC) and

various “COMBO” options, were not considered in this EA, as they played little or no role in EPA’s final

decisionmaking process. A description of these options can be seen in the EA for the proposal.

4

 Also

rejected was the DAF-TWL option and its various cutoffs, discussed in EPA’s Notice of Information

Availability (NODA),5 for reasons discussed in EPA’s preamble to the Final Action. EPA developed

compliance costs for each facility in the Section 308 Survey database for each of the two regulatory

options. EPA’s Final Development Document presents the derivation of the engineering cost estimates,

including capital and O&M costs, under each option. Table 4-1 presents the regulatory options addressed

in this analysis and defines the technologies associated with each option. EPA has determined that the CPIL option at the 3MM/120K cutoff is economically achievable and had the Agency promulgated a rule,

would have selected this option and cutoff.6

4.2.2.2 The Cost Annualization Model Parameters

Table 4-2 presents the cost annualization model using assumed data for illustrative purposes. The

inputs and assumptions for the analysis are listed above the spreadsheet. The first input is the facility code

for the facility analyzed. The second line is the type of corporate entity (e.g., incorporated or other). The

third line presents the regulatory option or alternative for which the annualized costs are calculated.7 The

fourth and fifth lines are the option's capital and O&M costs (from EPA’s Final Development Document).

For comparison purposes, costs are provided in terms of 1993 dollars.
4-6

Table 4-1

The Regulatory Options

Option Description

CP-IL Chemical precipitation treatment of wastewater from industrial laundry

items; linen wastewater does not require treatment. If untreated, the

treated and untreated streams are combined prior to discharge.

DAF-IL Dissolved air flotation treatment of wastewater from industrial laundry

items; linen wastewater does not require treatment. If untreated, streams

are combined prior to discharge.

Source: Final Development Document.
Table 4-2

Sample Spreadsheet for Annualizing Costs

Inputs

Survey ID: XXXX

Option Number:

1994 Engineering Inputs Economic Analysis

Initial Capital Cost ($) (Line A): $303,055 Year Dollars 1994 1994

Annual O&M Cost ($) (Line B): $68,256 $68,256 ENR CCI 5439 5439

Facility-Specific Nominal Discount/Interest Rate: 10.0%

Expected Inflation Rate: 2.9%

Real Discount Rate: 7.1% Federal Corp.Tax Table: Federal Personal Tax Table:

Corporate Tax Structure: 1

Taxable Income ($): $65,887,133

Marginal Income Tax Rates: $50,000 16.7% $22,750 18.8%

 Federal: 34.00% $75,000 20.4% $55,100 24.8%

 State: 6.60% $100,000 28.3% $115,000 29.5%

 Combined (Line C): 40.60% $335,000 34.0% $250,000 37.8%

1 2 3 4 5 6 7 8

Tax Shield Cash Outflow

Depreciation From O&M Cash Outflow After

Depreciation For Year Depreciation O&M Cost Tax Shield (Line A in Yr 1; Tax Shields

Year Rate (Line A*Col 2) (Line C*Col 3) (Line B) (Line C*Col 5) Line B in Yrs 2-15)* (Col 7*(Col 4+Col 6))

1 5.00% $15,153 $6,152 $34,128 $13,856 $337,183 $317,175

2 9.50% $28,790 $11,689 $68,256 $27,712 $68,256 $28,855

3 8.55% $25,911 $10,520 $68,256 $27,712 $68,256 $30,024

4 7.70% $23,335 $9,474 $68,256 $27,712 $68,256 $31,070

5 6.93% $21,002 $8,527 $68,256 $27,712 $68,256 $32,017

6 6.23% $18,880 $7,665 $68,256 $27,712 $68,256 $32,879

7 5.90% $17,880 $7,259 $68,256 $27,712 $68,256 $33,285

8 5.90% $17,880 $7,259 $68,256 $27,712 $68,256 $33,285

9 5.91% $17,911 $7,272 $68,256 $27,712 $68,256 $33,272

10 5.90% $17,880 $7,259 $68,256 $27,712 $68,256 $33,285

11 5.91% $17,911 $7,272 $68,256 $27,712 $68,256 $33,272

12 5.90% $17,880 $7,259 $68,256 $27,712 $68,256 $33,285

13 5.91% $17,911 $7,272 $68,256 $27,712 $68,256 $33,272

14 5.90% $17,880 $7,259 $68,256 $27,712 $68,256 $33,285

15 5.91% $17,911 $7,272 $68,256 $27,712 $68,256 $33,272

16 2.95% $8,940 $3,630 $34,128 $13,856 $34,128 $16,642

Sum 100.00% $303,055 $123,040 $1,023,840 $415,679 $1,326,895 $788,176

Present Value $198,702 $80,673 $640,232 $259,934 $943,287 $602,680

_________________________

Before Tax Shield After Tax Shield

Present Value of Incremental Costs: $943,287 $602,680

Annualized Cost: $100,421 $64,160

Notes:This spreadsheet assumes that MACRS is used to depreciate capital expenditures.

Depreciation rates are from 1995 U.S. Master Tax Guide for 15-year property and mid-year convention.

Corporate Tax Structure: 1= corporate tax rate 2= individual tax rate.

If the company-specific discount rate is <3% or >19%, then an industry median figure of 10.0% is used.

First year is not discounted.

*Plus 1/2 of Line B in years 1 and 16.

4-7
8

 Commerce Clearinghouse, Inc., 1995. U.S. Master Tax Guide. p. 322.

9

 EPA investigated the sensitivity of the analysis to changes in depreciation schedules and life of

property. Only changes in life of property have any measurable impact on annual costs, but life of

property is unlikely to be less than 15 years; see Jeff Cotter and Anne Jones, ERG, 1997. “Sensitivity

analysis of annualized cost estimates to changes in depreciation and project lifetime.” Memorandum to Sue

Burris, EPA. October 25.

10 EPA assigned a discount rate of 6 percent, the Federal Reserve prime rate for 1993, to facilities

that reported a discount rate of “prime.” EPA considered reported discount rates of less than 3 percent and

more than 19 percent to be suspect. Discount rates in these ranges were dropped and replaced by the

average of all other reported discount rates. Discount rates of less than 3 percent were thought to be too

low because banks were charging a prime rate of nearly 6 percent and the Federal Reserve Bank of New

York had instituted a discount rate of nearly 3 percent during the time of the Section 308 Survey effort.

Prime and discount rate data are from Federal Reserve Statistics, 1994. Public Statistical Release H-15.

Public Services, Board of Governors, Federal Reserve System, January 3. Similarly, discount rates of more

than 19 percent were considered to represent a hurdle rate (the rate of return desired for a project before it

will be undertaken), rather than a true discount rate. Only a few discount rates were considered suspect.

Generally, these ranged from 25 to 100 percent.

11 The inflation rate is based on changes in the Consumer Price Index between 1992 and 1994. U.S.

Government Printing Office, 1996. Economic Report of the President, 1996. Washington, DC: U.S.

Government Printing Office. February. Note that this discount rate is approximately the same as that

recommended by OMB, 1996. “Memorandum for members of the regulatory working group regarding

economic analysis of federal regulations under Executive Order 12866.” Sally Katzen.

4-8

The life of the asset is determined according to the Internal Revenue Code's classes of depreciable

property. Fifteen-year property is assumed to have a class life of 20 to 25 years—a typical life span for the

equipment considered in the costing analysis. According to the U.S. Master Tax Guide, 15-year property

includes such assets as municipal wastewater treatment plants.8 Thus, for the purposes of calculating

depreciation, most components of the capital cost for a pollution control option would be considered 15-

year property.9

The discount rate reflects the costs of capital for industrial laundry facilities and is used to

calculate the present value of the cash flows. The discount rate used in the EA is based either on the actual

cost of capital reported by each facility in the Section 308 Survey or, if these data are missing or suspect,

on the mean and median discount rate (which both equal 10 percent) reported by the industrial laundry

facilities in the Section 308 Survey.10 All rates were adjusted for an inflation rate of approximately 3

percent, providing an average real discount rate of approximately 7 percent.11
12 Commerce Clearinghouse, Inc., 1995. U.S. Master Tax Guide, p. 314.

13 The cost annualization model uses the relevant marginal federal income tax rate based on the

amount of taxable earnings at each facility’s owner firm and applies either a corporate marginal rate or an

individual marginal rate (if the firm is an S corporation or organized as another noncorporate structure). If

a firm had no earnings, a marginal rate of 0 percent was used (i.e., no tax shield would be calculated).

14 An asset’s depreciable life can differ from its actual life. The pollution control equipment

considered in this analysis is in the 15-year property class; however, the actual life could extend to 25

years. EPA’s estimate of annualized costs is conservatively high as long as the equipment does not have to

be replaced in its entirety (costs for replacement pumps and other equipment needed for maintenance have

been included in O&M) in less than 16 years (see Appendix B). 

4-9

The final model parameters are the federal and average state tax rates, which are used in

determining each facility’s tax benefit or tax shield. A facility is allowed to reduce its taxable income by the

amount spent on incremental O&M costs and by the depreciable portion of its capital equipment.12 The tax

rates used in the model represent the marginal federal tax rate appropriate to the owner firm13 and the

average state corporate income tax rate (see Appendix B). The average state tax rate is used in the cost

annualization model because it can be unclear which state tax rates apply to a given facility’s revenues. For

example, a facility located in one state might be owned by a firm whose corporate headquarters is located

in a second state and whose corporate holding company is located in a third.

4.2.2.3 The Cost Annualization Model Structure and Outputs

Two assumptions were made in annualizing compliance costs. The first assumption is that the

facility owners will be using the Modified Accelerated Cost Recovery System (MACRS) to depreciate

capital investments, which reduces the effective cost to the facility of purchasing and operating the

pollution control equipment. The second is that a 6-month delay occurs between the purchase of pollution

control equipment and its operation. The details of these assumptions and their impact on the results of the

MACRS cost annualization model are presented in Appendix B.

In Table 4-2, the spreadsheet contains numbered columns in which the costs of the investment to

the facility are calculated. The first column lists each year of the equipment's life span, from its installation

through its 15-year depreciable lifetime.14 Column 2 represents the portion of capital costs that can be
15 The tax shield amount shown is limited later in the macro programming when the present value

of the tax shield is compared to the present value of baseline taxes paid by the firm. The model assigns a

tax shield value equal to the lower of the two.

16 The 6-month delay between purchase and operation plus the 15-year life is actually 16 years

because a mid-year convention is used to compute the annualized cost. A 6-month delay plus the mid-year

convention means that the annualization formula does not begin discounting until the end of the first year.

17 See previous footnote on timing.

4-10

written off or depreciated each year; these rates are based on MACRS, as shown in Appendix B. By

multiplying these rates by the total capital cost, EPA calculates the annual amount the facility can

depreciate (Column 3). These depreciable amounts are used by the firm to offset annual taxable income.

Column 4 shows the tax benefit provided by the depreciation expense, (i.e., the overall tax rate times the

depreciation amount for the year).15

Column 5 of Table 4-2 shows the annual O&M expense. These costs are constant, except in Year

1 when only half the O&M costs are incurred because the equipment is not in service through half the

year.16 Column 6 shows the tax shield or benefit provided from expensing the O&M costs. Column 7 lists

the facility’s total expenses associated with the additional pollution control equipment: EPA assumes that

capital costs are incurred during the first year when the equipment is installed. The O&M expense is added

to capital costs for all years except Year 1, in which one half of O&M costs is added. Column 8 lists the

annual cash outflow minus the tax shields from the O&M expenses and depreciation because the facility

will recoup these costs as a result of reduced income taxes.

Once the yearly cost to the facility has been determined, the yearly cost is transformed into a

constant cost stream. The bottom line in Column 8 represents the present value of the costs over the

equipment's life span. The annualized cost is calculated as the 16-year annuity (15 years plus one year)17

that has the same present value as the bottom line in Column 8 of Table 4-2. The annualized cost

represents the annual payment required to finance the capital outlay and pay for O&M after tax shields. In

essence, paying the annualized cost every year and paying the amounts listed in Column 8 for each year are

equivalent. In this example, the capital investment of $303 thousand and annual O&M cost of $68
18 Note that the annualized cost can be determined in two ways. The first way is to calculate the

annualized cost as the difference between the annuity value of the cash flows (Column 7) and the tax

shields (Columns 4 and 6). The second way is to calculate the annuity value of the cash flows after tax

shields (Column 8). Both methods yield the same value.

4-11

thousand (1993 dollars) result in an annualized posttax cost of $64 thousand.18 Figure 4-2 presents the

equations used to calculate present value and annual cost.

The present value of the cost for incremental pollution control is used in the facility analysis

(Section Five). Results of the calculation of aggregate compliance costs are presented below in Section 4.2.

4.3 TOTAL ANNUALIZED COMPLIANCE COSTS

EPA calculates total annualized compliance costs by aggregating the annualized compliance costs

for all affected facilities, based on the output of the cost annualization model. Table 4-3 presents the results

of this cost aggregation by regulatory option and cutoff. Both pretax and posttax costs are shown, but only

posttax costs are used to represent impacts on industry facilities, which are calculated on the basis of these

posttax costs (i.e., the costs as perceived by the affected facilities after taxes are paid). These impacts are

summarized in Section Five. Note that Table 4-3 reflects the zero compliance costs assigned to facilities

excluded from the rule as discussed above in Section 4.2.2.1.

As Table 4-3 shows, CP-IL is associated with an annual posttax cost of $53.9 million to $128.4

million, depending on cutoff. DAF-IL is associated with a cost of $60.0 million to $136.6 million,

depending on cutoff. The selected option and cutoff, CP-IL at the 3MM/120K cutoff, is associated with a

posttax cost of $90.8 million per year.
Table 4-3

Compliance Costs for the Regulatory Options (1993 dollars)*

Total Total Total Pretax Total Posttax

 Option Capital Costs O&M Costs Annualized Costs Annualized Costs

 No Regulation ** $0 $0 $0 $0

 CP-IL No cutoff $528,827,868 $123,057,702 $179,687,660 $128,354,241

 CP-IL 1MM/255K $507,469,980 $116,835,047 $171,291,344 $120,884,335

 CP-IL 3MM/120K $387,491,478 $89,155,808 $131,248,498 $90,812,547

 CP-IL 5MM/255K $234,139,808 $52,866,169 $77,401,631 $53,905,645

 DAF-IL No cutoff $435,352,966 $148,560,743 $195,250,102 $136,637,259

 DAF-IL 1MM/255K $417,313,882 $142,276,538 $187,131,063 $129,428,733

 DAF-IL 3MM/120K $313,173,435 $111,909,892 $146,043,663 $98,835,405

 DAF-IL 5MM/255K $180,570,477 $69,533,822 $88,427,117 $59,963,207

Source: U.S. EPA, 1999. Facility and Firm Financial Model, and Section 308 Survey data. Capital and O&M costs from the Final Technical

 Report. Models and data are included in the Decisionmaking Record.

* Includes lesser hauling cost, if appropriate, thus capital costs may appear slightly lower and O&M costs may be slightly different than

 those shown in the Final Technical Report.

** EPA did not estimate the cost of industry's voluntary program.

4-12
1

 Section 308 Survey data.

2

 Discrepancies between the sum of single-facility firms and nonindependent facilities and the total

number of affected facilities are caused by rounding of the survey weights assigned to each facility.

Fractional facilities are created using the survey weights, but, for clarity, only integers are used to describe

numbers of facilities in the text and tables of this report.

3

 As independent entities, these facilities operate as both facilities and firms. To capture both

(continued...)

5-1

SECTION FIVE

ANALYSIS OF FACILITY-LEVEL IMPACTS

This section presents the facility-level economic impact methodology and reports the results of the

facility economic impact analysis (closure analysis) of regulatory options EPA investigated before making

its decision not to promulgate pretreatment standards for the industrial laundries point source category.

This analysis, described in Section 5.1, uses output from the cost annualization model (discussed in Section

Four) to predict facility closures. Section 5.2 summarizes the results of the analysis in terms of the number

of facility closures that would have occurred prior to regulatory compliance (baseline closures) and the

number of facility closures that would have resulted from regulatory compliance (incremental closures).

Section 5.3 discusses impacts on new sources.

EPA determined that 1,742 facilities would have been potentially affected by pretreatment

standards.1 To evaluate preregulatory (baseline) conditions at and postcompliance impacts on these

facilities, EPA divided the facilities into two groups: facilities that are independently owned and operated

(“single-facility firms”) and nonindependent facilities, owned by firms that own multiple facilities. EPA

classified facilities in these groups on the basis of each facility’s response to Question 27 in Part B of the

Section 308 Survey, which asked about the organizational structure of each facility. 

A total of 830 of the 1,742 potentially affected facilities are classified as single-facility firms.2

These facilities responded with a C or E to Question 27 in Part B of the Section 308 Survey. Single-facility

firms are independently owned; in some cases, they may have an ultimate parent company, but for all

intents and purposes, they act as independent entities.3 In addition, these firm-facilities generally maintain
3

(...continued)

facility- and firm-level impacts for these single-facility firms, EPA evaluates them as facilities in Section

Five and as firms in Section Six. Results in Section Six are incremental to the closures reported in Section

Five, that is, single-facility firms reported as financially vulnerable as a result of regulatory options in

Section Six are those that do not close in Section Five. EPA used this approach in reporting results because

the impacts associated with closure for a single-facility firm are considered greater than those associated

with a weakened financial position. In the industrial laundries industry, closures have a greater impact

because those facilities that do not close can be sold to financially stronger firms (or in the case of singlefacility firms owned by parent firms, might be able to rely on the parent for financial backing). Thus singlefacility firms that do not close but become financially vulnerable might lose their status as independent

entities, but other impacts at financially vulnerable firms, such as employment impacts, are likely to be

somewhat less severe. (See Section Six for more details on impacts of firm failures in this industry.)

5-2

their own balance sheets and income statements and pay taxes at the facility level. Of the 830 single-facility

firms, from 128 to 556 firms would have been excluded from the rule (see discussion in Section Four about

the various ways EPA defined cutoffs for exemptions for small facilities and Table 3-15 in Section Three)

and thus would have incurred no compliance costs. All 830 of the single-facility firms are analyzed in this

section of the EA.

A total of 912 of the 1,742 facilities are classified as nonindependent facilities. These facilities

responded with A, B, or D to Question 27 in Part B of the Section 308 Survey. Nonindependent facilities

are subordinate to multifacility owner companies and, in some cases, parent companies. Such facilities

might maintain their own balance sheets or income statements, but financial statements are generally kept

at the owner-company level. In addition, any corporate taxes associated with these facilities are typically

paid by the owner company. Of the 912 nonindependent facilities, from 8 to 396 would have been excluded

from the rule, depending on cutoff and would not have incurred compliance costs (see Table 3-15 in

Section Three). All 912 of the nonindependent facilities are analyzed in this section of the EA.

Because of the very different nature of the financial reporting at single-facility firms and

nonindependent facilities, the following sections discuss the analysis and results of the two types of

facilities separately, then together, for the 1,742 facilities in the analysis.
4Comment Response Document, PECON-2C, Tracking No. 1481.

5-3

5.1 FACILITY IMPACT MODEL

In this study, EPA estimates facility impacts by evaluating the impact of compliance costs on a

facility’s cash flow. To do this, EPA compares each facility’s average annual precompliance cash flow

with its annualized pollution control costs. The present value of cash flow represents the value in current

dollars of the expected cash flow that the facility can generate over a specified period (in this case 16 years;

see below). If the present value of future cash flow is expected to be less than or equal to zero, EPA

assumes that the facility would cease operation, as it would no longer be a profitable venture. Cash flow

analysis is one of the most commonly used tools for financial analysis and in many instances is considered

a more accurate measure of financial health than net income analysis, since net income includes

depreciation as a cost even though depreciation is not a cash outlay (see, e.g., Brigham, E.F., and L.C.

Gapenski, 1997. Financial Management Theory and Practice, pp. 40-41). 

As in the EA for the proposed pretreatment standards, EPA does not use salvage value in the cash

flow analysis. Salvage value is the residual value of the facility at liquidation, which can be considered to

play a role in an assessment of the financial viability of a facility (i.e., the decision to liquidate would be

based on whether the estimated salvage value exceeded the estimated present value of cash flow). For

numerous reasons, EPA considers salvage value analysis an unreliable measure for identifying closures

among single- facility firms in this industry (see Appendix D). Furthermore, it is very difficult to estimate

salvage value, even where it might play a role in decision making, such as at multifacility firms. EPA did

perform a sensitivity analysis using salvage value for nonindependent facilities and determined that results

are nearly identical for these facilities (see Appendix D). Nevertheless, because of additional uncertainties

introduced by a salvage value analysis, EPA believes that a cash flow approach, without considering

salvage value, is a more realistic approach for the majority of facilities, since it will not overstate baseline

closures. A salvage value approach could identify baseline closures among facilities that are not expected

to be self supporting. Also note (as discussed in Appendix D) that setting salvage value equal to the market

value of a facility, as suggested by commenters on the proposal, is analytically incorrect.4 A sale at market

value is not a liquidation and, as such, is not a closure as EPA defines closure. Furthermore, this approach

results in a baseline closure rate of approximately 70 percent (see Appendix D). This approach is a better
5-4

indicator of why consolidation is occurring so rapidly in this industry. In fact, if one accepts the premise

that market value depends on revenue, not cash flow, it is likely that no facilities would have truly

liquidated post compliance (where liquidation is seen as a forced sale of assets at well below market value).

Section 5.1.1 describes the calculations used to determine the present value of future cash flow for

a facility, and Section 5.1.2 discusses how closure results are evaluated using the facility impact model. 

Figure 5-1 provides a schematic diagram of the methodology and components used in the facility impact

analysis. 

5.1.1 Estimating the Present Value of Forecasted Cash Flow 

As stated previously, the present value of each facility’s cash flow is equal to its future stream of

cash flow in current dollars. The impact methodology uses recent cash flow and other relevant data to

estimate future earnings and then applies a discount rate to derive the present value of future cash flow.

The components of this analysis include: 1) estimating current cash flow; 2) estimating the present value of

future cash flow, which involves establishing a time frame for the analysis, projecting cash flow during this

time frame, and discounting cash flow to the present; and 3) evaluating impacts (adjusting the regulatory

baseline for baseline closures and incorporating the incremental costs of the regulatory options). 

5.1.1.1 Estimating Current Cash Flow

Before the present value of future cash flow can be estimated, EPA must estimate current cash

flow. This figure is used, in turn, to project future cash flow. Estimating cash flow (current or future)

involves two steps. 

1. Determining net income, which is calculated as facility receipts minus operating costs, 

depreciation, interest, and taxes.

2. Reconciling net income to cash flow by adding back in depreciation. 
5

 EPA adjusted net income for all firms to account for any reported extraordinary expenses or

revenue. In addition, EPA used the appropriate marginal tax rate, given the firms’ taxable earnings, to

further adjust net income in each year in which extraordinary expenses or revenues were reported. These

adjustments were made to ensure that the financial “snapshot” developed reflects typical years, not unusual

ones. Very few firms reported unusual income or expenditures.

6

 Shipments may or may not generate revenues; transfers typically are shipments in which revenues

are set equal to operating costs.

7

 EPA evaluated baseline closure facilities to determine whether transfers at cost play a role in the

closure analysis, but the available information was insufficient to draw any conclusions.

5-5

In the closure model for the industrial laundries industry, cash flow at the 830 single-facility firms

can be calculated using Section 308 Survey data on facility-level net income and depreciation.5 At facilities

that do not operate independently from an owner company (i.e., the 912 nonindependent facilities),

however, neither cash flow nor net income can be determined using Survey data because taxes and interest

are typically recorded only at the firm level, not the facility level, and firm-level Survey data were not

sufficiently detailed to be applied to individual facilities. Thus, for nonindependent facilities, the closure

model uses operating earnings (e.g., receipts minus total operating costs, including depreciation and costs

unrelated to laundering; that is, depreciation is not subtracted from earnings) as an approximation of

posttax facility cash flow. The remainder of this report refers to nonindependent facility “cash flow” to

mean operating earnings. EPA did not attempt to determine the nonindependent facilities’ share of total

firm interest and taxes because the analysis would require data that even firms themselves might have

difficulty estimating (since often this type of accounting is not undertaken) and, as such, may not even play

a role in a firm’s liquidation decision. 

One factor that could affect cash flow at nonindependent facilities is the interfacility transfer of

laundry among facilities owned by the same firm. Because this practice occurs in multifacility firms, the

Section 308 Survey asked nonindependent facilities to report the value of shipments (including transfers)6

to other facilities owned by the same firm. This figure was used to evaluate whether transfers might play a

role in potentially overestimating baseline closures.7 In some cases, respondents might have underestimated

the value of transfers because transfers typically are valued at the cost of production (i.e., the cost of

laundering the items), rather than at the market value of that service. Cash flow, therefore, could be

understated at facilities that value transfers at the cost of production. This, in turn, could lead the facility

impact model to overstate total facility closures. EPA’s avoidance of a salvage value approach minimizes
8

 The cash flow period and the cost annualization period are the same to keep the annualized costs

comparable to cash flow. Otherwise either cash flow or annualized costs might be overstated relative to the

other.

9Cleary Hull Reiland & McDevitt, Inc., 1998. The Uniform Rental Industry. Winter, p. 2.

5-6

the likelihood that facilities that launder transferred items will be classified as baseline closures.

Furthermore, EPA evaluates nonindependent facilities shown to close in the baseline at the firm level to

determine if the firm can afford to continue to support a facility postcompliance, under the assumption that

the facility might not close in the baseline because it is not expected to be self-supporting. If the firm can

afford to install and operate pollution control equipment in all of its facilities (closing or not), EPA assumes

that facilities appearing to close in the baseline would have closed neither in the baseline nor

postcompliance.

5.1.1.2 Estimating the Present Value of Future Cash Flow

Current annual cash flow (or its proxy, operating earnings) can be used to estimate the present

value of future cash flow by setting a time frame for the analysis (16 years, as discussed in Section Four),

defining any trends or cycles that the affected industry’s cash flow might follow, and discounting the cash

flow projected over the time frame to the present time.8

EPA has determined that a slightly rising cash flow forecast over the defined 16-year period (see

Section Four) best fits the data provided in the Section 308 Survey, as well as that from other sources

(Section Three shows that net income rises slightly in real terms between 1991 and 1993 in the surveyed

facilities, and data submitted by commenters indicate that revenues have been rising rapidly in the later

years of the 1990s).9 To be conservative, however, EPA models growth in the industry as flat (thus

avoiding the assumption that the industry can “grow” its way out of financial impacts). Because general

industry information indicates that this industry is neither cyclical nor declining (see Section Three), EPA

expects the flat cash flow growth projection to yield a reasonable estimate of the present value of future

cash flow. 
10 OMB, 1996. “Memorandum for members of the regulatory working group regarding economic

analysis of federal regulations under Executive Order 12886.” Sally Katzen.

5-7

To represent this flat cash flow growth, EPA inflated 1991 and 1992 Section 308 Survey data to

1993 dollars using the change in the CPI for SIC 7218 and then took an average of the data for these 3

years. Constant 1993 dollars are used throughout the 16-year period of analysis, so a real (not a nominal)

discount rate is used. The same cost of capital factor (discount rate) used in the cost annualization model is

used to discount cash flow. All firms and facilities had at least 1 year’s data on which to base the

projection.

5.1.2 Evaluating Impacts

Establishing the Regulatory Baseline

OMB directs agencies to develop a regulatory baseline against which to judge impacts. OMB’s

guidance states:

The benefits and costs of each alternative must be measured against a baseline. The baseline

should be the best assessment of the way the world would look absent the proposed regulation.

That assessment may consider a wide range of factors, including the likely evolution of the

market...10

EPA must assess the impacts of regulatory options against a baseline that is the Agency’s best

assessment of the way the world would look without the regulation. If a facility’s present value of cash

flow is less than or equal to zero over the 16-year timeframe, EPA’s best estimate is that this facility is a

baseline closure independent of the impact of a regulatory option. Although it is possible that a facility

estimated to be a baseline closure might remain open, the converse also might be true—a facility projected

to remain open until it is subject to a rule might actually close independently of a rule. Both results might

be equally likely. If EPA were to assume that all facilities that are estimated to close in the baseline were

actually postcompliance closures, this would seriously overstate impacts. To avoid either seriously

overstating or understating impacts, EPA has chosen to estimate postcompliance closures by counting

facilities that are projected to close solely due to the effects of the regulatory options.
5-8

Furthermore, as noted earlier in Section 5.1.1.1, EPA does assess impacts on nonindependent

facilities that are estimated to close in the baseline by investigating whether the firm can continue to

support the facility in the firm failure analysis. The nonindependent facilities with negative or zero

operating earnings as reported in the Section 308 survey are assumed likely to be subsidized by their

owners, since they are not supporting themselves currently. If they are being subsidized in the baseline, then

EPA can assume they will continue to be subsidized postcompliance, as long as the firm can afford to

continue to support all of its facilities postcompliance (which is analyzed in Section Six). Thus only a few

single-facility firms are assumed to close regardless of any regulatory action and even fewer would have

been subject to a pretreatment standard, regardless of their baseline status, under the cutoffs investigated by

EPA. The number of single-facility firms classified as baseline closures thus is very small and certainly

within the expected number that might close over a period of a few years. Just in the time between when the

screener survey was sent out and when the Section 308 Survey was issued, some survey facilities were

reported to have closed or otherwise ceased to operate.

For all of these reasons, EPA creates a regulatory baseline by evaluating the current baseline

(represented by the data collected in the Section 308 Survey) and determining which facilities are likely to

close regardless of regulatory requirements, as directed by OMB Guidance. The facilities that are not

expected to close are then used to establish the regulatory (as opposed to the current) baseline. This

regulatory baseline is the one against which incremental impacts in the postcompliance closure analysis are

measured. In analysis of the current baseline, EPA uses the model as described above to calculate the

present value of the cash flow stream over the 16-year time frame. If a facility’s present value of cash flow

(current baseline cash flow) is less than or equal to zero, EPA classifies that facility as a “baseline

closure.” These “closure” facilities are eliminated from the regulatory baseline used in the subsequent,

postcompliance closure analysis either because such closures are expected to occur regardless of any

regulatory action and therefore cannot be attributed to increased regulatory costs, or because the closure

analysis is irrelevant, and the appropriate level of analysis is at the firm level (for nonindependent facilities

that are not self-supporting). 
11Comment Response Document, PECON-9B, Tracking Nos. 1584 and 1585.

5-9

Incorporating Compliance Costs

For the postcompliance closure analysis, EPA calculates the impacts of regulatory option costs on

cash flow using the facility-specific posttax annualized costs for each regulatory option and an estimate of

the depreciation allowed on the compliance investment calculated by EPA’s cost annualization model (see

Section Four). This figure is then subtracted from baseline cash flow to compute each facility’s

postcompliance cash flow. EPA assumes that no costs of compliance can be passed through to customers in

computing the post compliance cash flow. After computing the postcompliance cash flow, the model notes

for which facilities postcompliance cash flow is less than or equal to zero and classifies these facilities as

closures. The model actually annualizes these costs and compares them to the baseline annual estimate of

cash flow for simplicity and speed of model calculations, since in a zero-growth scenario, results are

identical (in terms of whether precompliance cash flow is less than or equal to zero) whether annualized

values or present values are used. The number of estimated closures under each cutoff is recorded by

revenue size, and cutoff for all facilities. Only the CP-IL option results are presented here. Results for

DAF-IL are identical and are shown in Appendix C.

Although EPA assumes no costs can be passed through, it is likely that at least some costs could

have been passed through. The cost passthrough percentage is calculated in Appendix A. In this appendix,

EPA conducted a market analysis of the industrial laundry industry and concluded that a portion of

compliance costs (approximately 32 percent of costs) could have been passed through to industrial laundry

customers as a price increase (see Appendix A). EPA believes that some costs would have been passed

through to customers for the following reasons. First, although commenters insisted that the industrial

laundries industry is highly competitive, this does not mean the industry faces a perfectly elastic demand

curve, although in a perfectly competitive industry, each firm faces a perfectly elastic demand curve (each

firm acts as a price taker). If an increase in production costs affects many to most firms in an industry, the

relevant demand curve is the industry demand curve, which is almost always downward sloping. Data

submitted by commenters support the assumption of a downward sloping demand curve. Commenters

noted that production costs have been declining, as have prices, while revenues have been rising over the

last couple of decades.11 This means that the industrial laundry industry has been passing through
5-10

productivity improvements and production costs savings through to customers in the form of price

reductions. The only way this can happen (other than with downward shifts in the demand curve, which

could not be happening with rising revenues) is with a downward sloping demand curve. Furthermore, if

industry passes through cost savings, industry would have passed through cost increases in the same way. 

Despite the likelihood that costs can be passed through, however, EPA recognizes that those facilities

processing few pounds of laundry might only have passed through a very small part of their costs, while

larger facilities might have been able to pass through most of their costs, even though overall, some average

cost passthrough would have applied. Additionally, EPA recognizes that in certain markets and with

certain customers, individual facilities might have been more constrained than in more typical markets if

more extreme competition with substitutes is perceived. Furthermore, at higher cutoffs (e.g., the

5MM/255K cutoff), the model would most likely overstate impacts on the industry supply curve leading to

overestimates of cost passthrough and price increases. For these reasons, EPA assumes that costs cannot

be passed through to customers, to ensure that impacts on any one facility would not be underestimated. 

Appendix A presents (as a sensitivity analysis) facility closure results under the assumption that 32

percent of costs can be passed through at each facility. Under most cutoffs, impacts are substantially

reduced.

5.2 RESULTS

5.2.1 Baseline Closures

Table 5-1 presents the results of the baseline analysis by type of facility and by revenue categories

within each facility type. The results of the analysis indicate that 51 nonindependent facilities (about 6

percent) close in the baseline, (one is an excluded facility under all cutoffs considered) and about 96 singlefacility firms (or 11.6 percent) close in the baseline. However, 39 to 74 of these single-facility firms would

have been excluded facilities, depending on the cutoff examined (not including the no cutoff scenario, which

is used only for comparison purposes), so a rule would have had no effect on them anyway. A total of 22 to

57 nonexcluded, single-facility firms close in the baseline, depending on cutoff, which is only about 8

percent (regardless of cutoff) of all nonexcluded, single-facility firms. 
Table 5-1

Baseline Closure Analysis - All Facilities

Closures Nonclosures

Percentage of Percentage of

Revenue Groups ($000) Number Revenue Group Number Revenue Group Total

Nonindependent Facilities

Total 51 5.6% 861 94.4% 912

< $1 Million 25 52.8% 22 47.2% 47

>= $1 and < $3.5 Million 4 1.5% 253 98.5% 257

>= $3.5 and < $7 Million 21 5.3% 383 94.7% 405

>= $7 and < $10.5 Million 1 0.9% 155 99.1% 156

>= $10.5 Million 0 0.0% 47 100.0% 47

Single-Facility Firms

Total 96 11.6% 734 88.4% 830

< $1 Million 72 39.7% 110 60.3% 182

>= $1 and < $3.5 Million 2 0.6% 290 99.4% 292

>= $3.5 and < $7 Million 22 8.7% 236 91.3% 258

>= $7 and < $10.5 Million 0 0.0% 81 100.0% 81

>= $10.5 Million 0 0.0% 18 100.0% 18

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are included in the 

 Decisionmaking Record.

5-11
12 Note that some nonexcluded single-facility firms that are shown to close in the baseline have

ultimate parent companies that might be supporting these firms and could continue to support them

postcompliance. To be conservative, however, EPA does not extend this closure analysis to parent

companies, but measures baseline conditions and impacts against the most vulnerable corporate levels.

13 As will be shown in Section Six, all multifacility firms that are not baseline firm failures can

afford to install and operate pollution control equipment at all of their facilities, thus the 50 nonindependent

facilities shown to close in the baseline might not close in either the baseline nor the postcompliance for the

reasons outlined above in Section 5.1.1.1.

5-12

It is likely that many of the nonindependent facilities shown to close in this analysis are transfer

facilities, or are facilities otherwise supported by their firms, and therefore probably would have closed

neither in the baseline nor postcompliance as discussed above in Section 5.1.1.1. The ability of firms to

afford to continue to support nonindependent facilities postcompliance is assessed in Section Six.

Therefore, the number of baseline closures estimated at this stage of the analysis is 96 facilities, of which

only 22 to 57 would not have been excluded anyway under the cutoffs investigated. These 22 to 57 singlefacility firms amount to only 1.3 to 3.3 percent of all in-scope facilities (1,742 facilities).12

As discussed earlier in Section 5.1.2, none of the 147 baseline closure facilities (both excluded and

nonexcluded) is analyzed in the postcompliance closure analysis. The total number of potentially affected

facilities is adjusted downward to exclude facilities predicted to be baseline closures (single-facility firms)

or estimated to be not self-supporting (nonindependent facilities that must be analyzed at the firm level); 

therefore, only facilities that are self-supporting (nonindependent facilities) and/or financially viable in the

baseline (single-facility firms) are analyzed in the postcompliance analysis.13 These facilities include

734 single-facility firms and 861 nonindependent facilities for a total of 1,595 facilities.

5.2.2 Postcompliance Closures

Tables 5-2 and 5-3 present the results of postcompliance analysis for the CP-IL regulatory option

under the four cutoffs discussed in Section Four for single-facility firms and nonindependent facilities,

respectively. As noted earlier, only CP-IL option impact results are analyzed in the main report. Impact

results for DAF-IL are identical and are presented in Appendix C. As with the baseline results, the

postcompliance results are presented by revenue categories. The results presented in these two tables
Table 5-2

Facility Closure Analysis - Single-Facility Firms*

CP_IL CP-IL CP_IL CP-IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=734)

 Closures 94 54 39 0

 Percentage of all facilities 12.8% 7.4% 5.3% 0.0%

Facilities with revenues less than $1 million (N=110)

 Closures 51 14 0 0

 Percentage of all facilities 6.9% 1.9% 0.0% 0.0%

 Percentage of revenue group 46.3% 12.8% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=290)

 Closures 43 40 39 0

 Percentage of all facilities 5.9% 5.5% 5.3% 0.0%

 Percentage of revenue group 15.0% 13.8% 13.3% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=236)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$7 million and <$10.5 million (N=81)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=18)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline closures. Note that results have changed from those seen in briefings based on a

refinement to the model that more conservatively computes tax shield.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

5-13
Table 5-3

Facility Closure Analysis - Nonindependent Facilities*

CP_IL CP-IL CP_IL CP-IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=861)

 Closures 12 6 5 2

 Percentage of all facilities 1.4% 0.8% 0.6% 0.3%

Facilities with revenues less than $1 million (N=22)

 Closures 7 1 0 0

 Percentage of all facilities 0.8% 0.2% 0.0% 0.0%

 Percentage of revenue group 32.4% 6.3% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=253)

 Closures 3 3 3 0

 Percentage of all facilities 0.3% 0.3% 0.3% 0.0%

 Percentage of revenue group 1.1% 1.1% 1.1% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=383)

 Closures 2 2 2 2

 Percentage of all facilities 0.3% 0.3% 0.3% 0.3%

 Percentage of revenue group 0.6% 0.6% 0.6% 0.6%

Facilities with revenues >=$7 million and <$10.5 million (N=155)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=47)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline closures.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

5-14
5-15

indicate that single-facility firms and facilities in the revenue category of $1 to $3.5 million would the most

affected group under all but the no cutoff and 5MM/255K cutoff scenarios. 

As Tables 5-2 through 5-4 show, the option presented here, CP-IL is associated with 2 to 106

closures, depending on cutoff. Note that impacts drop off rapidly when the cutoff is increased to the 

5MM/255K group of facilities. Under this cutoff, only 0.2 percent of the facilities would have been

affected by a rule. Under the no cutoff scenario, 44 percent of the facilities with revenues less than $1

million would have closed. EPA, however, used this scenario for comparison purposes only. Under EPA’s

selected cutoff (3MM/120K), 44 facilities would have closed, 39 of which are single-facility firms.

5.3 IMPACTS ON NEW SOURCES

EPA’s decision not to promulgate pretreatment standards applies to new sources as well. This

section presents EPA’s assessment of what impacts on new sources might have been had EPA decided to

promulgate pretreatment standards for new sources under the same option and exclusion selected for

existing sources (CP-IL under the 3MM/120K cutoff). EPA assessed impacts on new sources by

determining whether the regulatory options would have resulted in a barrier to entry into the market. 

EPA has found that overall impacts from the either the CP-IL or DAF-IL options would not have

been any more severe on new sources than those on existing sources as long as both are subject to the same

cutoff, since the costs faced by new sources generally will be similar to those faced by existing sources.

Because most new sources and existing sources would have faced similar costs, EPA has determined that

the CP-IL option under the 3MM/120K cutoff for new sources would not have posed a barrier to entry on

the basis of competitiveness. 

EPA also examined whether there would be a barrier to entry for small new sources based on

disproportionate impacts measured as closures or failures. EPA investigated facilities in the Section 308

Survey that indicated they were new or relatively new at the time of the survey. Using the Section 308

Survey data, EPA expects that new sources would generally have exceeded most of the threshold size

cutoffs that EPA considered for existing sources. Sixty percent of facilities identified as new exceed the

5MM/255K cutoff. The number of new source facilities coming on line each year is extremely small. Over
Table 5-4

Facility Closure Analysis - All Facilities*

CP_IL CP-IL CP_IL CP-IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=1595)

 Closures 106 61 44 2

 Percentage of all facilities 6.7% 3.8% 2.7% 0.2%

Facilities with revenues less than $1 million (N=132)

 Closures 58 15 0 0

 Percentage of all facilities 3.6% 1.0% 0.0% 0.0%

 Percentage of revenue group 44.0% 11.7% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=544)

 Closures 46 43 41 0

 Percentage of all facilities 2.9% 2.7% 2.6% 0.0%

 Percentage of revenue group 8.5% 7.9% 7.6% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=619)

 Closures 2 2 2 2

 Percentage of all facilities 0.2% 0.2% 0.2% 0.2%

 Percentage of revenue group 0.4% 0.4% 0.4% 0.4%

Facilities with revenues >=$7 million and <$10.5 million (N=235)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=65)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline closures. Note that results have changed from those seen in briefings based on a

refinement to the model that more conservatively computes tax shield.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

5-16
5-17

a three year period (1991, 1992, and 1993), according to Section 308 Survey data, laundry operations

began at about only 80 facilities (and it is not absolutely clear from the data whether these facilities were

actually new dischargers or were existing dischargers acquired in that year by a different firm). Over the

3-year period, this amounts to 27 new sources a year at most, or only 1.5 percent of existing facilities.

Given the small level of growth in the industrial laundries industry, EPA believes that new sources are

primarily replacing production from closing facilities that exit the market.

Of these facilities identified as new or relatively new facilities, EPA determined that the average

revenues of this group exceeded $4 million per year, and the amount of laundry processed averaged over 5

million pounds per year. Only 24 to 32 facilities out of 80 total newer facilities (weighted), or 30 to 40

percent, would meet the size threshold for the exclusions EPA investigated for existing sources. On a yearly

basis (given that these facilities started up over the 3 years of the survey) EPA estimates that 8 to 11

facilities of the size, on average, that would meet an exclusion similar to those investigated for existing

sources might be started up each year. Under the 3MM/120K cutoff, 30 facilities total, or 10 per year, on

average, would meet this exclusion. Overall, in the group of 80 facilities, 6 facilities (weighted), or 7.5

percent, were identified as postcompliance closures (based on a closure by one surveyed nonindependent

facility). These facilities would have been exempted under all cutoffs considered. Given the above results,

EPA finds that had new sources been regulated under the 3MM/120K cutoff, the rule for new sources

would have been economically achievable and no barriers to entry would have occurred.

Furthermore, because both new sources and existing sources would have been provided the same

exclusion, EPA avoids a situation where a level playing field would not be provided for new sources

relative to existing sources. This could occur when a new smaller facility that was not excluded from the

rule must complete with an existing smaller facility that was excluded under the production threshold for

the rule. This competitive disadvantage could be a barrier to entry if the production threshold for new and

existing sources were not the same.
1Again, in this section, the CP-IL option is discussed. Impacts associated with the DAF-IL option

are identical and are reported in Appendix C.

2As noted in Section Five, single-facility firms are both firms and facilities. To fully capture both

facility- and firm-level impacts for these firms, EPA evaluates them as facilities in Section Five and as

firms in Section Six.

6-1

SECTION SIX

ANALYSIS OF FIRM-LEVEL IMPACTS

The firm-level analysis evaluates the effects on firms of regulatory options1 that were considered at

the time EPA made its decision not to promulgate pretreatment standards for the industrial laundries point

source category. It also serves to identify impacts not captured in the facility analysis. For example, some

firms might have been be too weak financially to undertake the investment in the technology options

considered, even though the investment might have seemed financially feasible at the facility level. Such

circumstances can exist, in particular, at firms owning more than one potentially affected facility. Given the

range of possible firm-level impacts, the firm-level analysis is an important component of this EA.

EPA determined that 903 firms might have been affected by a pretreatment standard. To evaluate

precompliance conditions at and postcompliance impacts on these firms, EPA divided the firms into two

categories—single-facility firms (described in Section Five) and multifacility firms. As with facility

groupings in Section Five, EPA based firm groupings on responses to Question 27 in Part B of the Section

308 questionnaire, which asked about organizational structure. Because of the differences in organizational

structure and size between two categories of firms (discussed below), results are presented separately for

each type of firm. 

A total of 830 firms classified themselves as single-facility firms by responding with C or E to

Question 27 in Part B of the Section 308 Survey.2 These firms operate as independent entities, although, in

some cases, single-facility firms can have an ultimate parent company. As independent entities, these firms

maintain balance sheets and income statements and pay corporate taxes on their own earnings. Singlefacility firms also are generally smaller than multifacility firms in terms of revenues, production, and

employment. Of these firms, 128 to 556 would have met a definition of a small industrial laundries
3

 Because the Section 308 Survey was issued only to a subset of all industrial laundry facilities, not

all firms owning industrial laundry facilities were identified in the survey. To estimate the total number of

multifacility firms (not just those surveyed), EPA compared the survey-weighted number of nonindependent

facilities (those responding with A, B, or D to Question 27) to the total number of industrial laundry

facilities reported owned by the surveyed firms with nonindependent facilities. (Most surveyed multifacility

firms reported owning more than one industrial laundry facility). EPA assumed that the difference between

these two numbers of facilities reflects the number of facilities owned by nonsurveyed firms. In order for

the two facility numbers to match, EPA would have to multiply the number of firms captured in the survey

by 1.7. EPA therefore used this ratio (1.7) as if it were a statistical weight to estimate the total number of

multifacility firms, multiplying each surveyed multifacility firm by 1.7. Results of the firm-level analyses

for multifacility firms were likewise multiplied by 1.7. Basically, this approach embodies the assumption

that the nonsurveyed firms own the same average number of industrial laundry facilities as the surveyed

firms. This assumption could bias impact results, allowing impacts to be understated if smaller or more

vulnerable multifacility firms are underrepresented in the survey. However, EPA believes any bias that

might have been introduced is largely irrelevant given the results of the analysis, which shows that

multifacility firms do not fail under any option or cutoff, so the “weight” used does not effect the results.

4

 For example, a firm owning a number of hotels and laundries might own only one laundry that

meets the definition of an industrial laundry, with its remaining facilities being either hotels or linen supply

laundries.

5

 Impacts on parent companies (i.e., owners of the owner companies) are not analyzed in this EA

because the impacts of a given facility closure or major facility-level capital investment become more dilute

as assets increase at higher levels in the corporate hierarchy. Thus EPA’s analysis assumes that the

impacts fall on the most vulnerable firms. Had EPA assumed that the firms in the analysis could be “bailed

out” by their parent companies, impacts would most likely have appeared less. For most of the 830 singlefacility firms, however, analysis at the facility level, firm level, and corporate parent level coincide.

6-2

exclusion under the various cutoffs and thus would have incurred no compliance costs. Note that 2 to 106

single-facility firms were estimated to close in the postcompliance analysis in Section Five. To avoid double

counting impacts, these firms are removed from the results of the firm-level analysis. Section Nine

discusses the combined impacts of closures and failures on small firms in the industrial laundries industry. 

In addition to the 830 single-facility firms, EPA estimated that there are 73 multifacility firms.

Multifacility firms are those whose facility representatives responded with A, B, or D to Question 27 in

Part B of the Section 308 Survey;3 these firms own and operate more than one facility and have at least one

industrial laundry facility.4 In addition, they maintain financial records for all their facilities at the firm

level and typically pay corporate taxes at the firm level for all owned facilities. As noted above (and as

shown in Section Three), multifacility firms tend to be substantially larger than single-facility firms.5
6-3

The basic core of the firm-level analysis, both for single-facility and multifacility firms, is the

Altman ZO-score analysis, a ratio analysis that employs several indicators of financial viability to assess

firm-level precompliance conditions and postcompliance impacts. Section 6.1 presents an overview of this

ratio analysis methodology. Section 6.2 discusses the Altman ZO-score model as it applies to the industrial

laundries industry. Section 6.3 summarizes the results of the firm-level analysis in terms of the number of

firms that face bankruptcy prior to regulatory compliance (baseline bankruptcies) and the number of firms

that experience bankruptcy as a result of additional regulatory compliance costs (incremental

bankruptcies). It also discusses the number of firms that, while considered financially healthy in the

baseline, slip from the financially healthy category into an indeterminate category in the postcompliance

analysis (this is considered an impact short of bankruptcy). Results are presented under an assumption that

compliance costs could not have been passed through to customers. Appendix A presents an alternative

analysis assuming that compliance costs could have been passed through to the industry’s customers.

6.1 RATIO ANALYSIS METHODOLOGY

Ratio analyses are conducted from the perspective of creditors and equity investors who would

finance a company’s treatment system investment. To attract financing for a treatment system, a company

must demonstrate financial strength both before and, on a projected basis, after the treatment system has

been purchased and installed. The ratio analysis undertaken in this section simulates the analysis an

investor and/or creditor would be likely to employ in deciding whether to finance a treatment system or

make any other investment in the firm.

The baseline ratio analysis evaluates the company’s financial viability before the investment, and

the postcompliance analysis predicts the company’s financial condition subsequent to the investment. The

baseline analysis identifies companies in extremely weak financial condition, independent of pending

regulatory actions. Such companies are at risk of financial failure even without the additional cost of the

regulation. Firms that are projected to fail in the baseline analysis are excluded from the postcompliance
6

 OMB, 1996. “Memorandum for members of the regulatory working group regarding economic

analysis of federal regulations under Executive Order 12866.” Sally Katzen.

7

 Multidiscriminant analysis is a statistical procedure similar to regression analysis. It is used

primarily to classify or make predictions in cases where the dependent variable is qualitative. In this case,

the dependent variable would be “financially stable” or “financially unstable.”

8Altman, Edward, 1993. Corporate Financial Distress and Bankruptcy. New York: John Wiley

and Sons.

9

 See for example, Altman, 1993, Ibid.; Brealy, Richard A., and Stewart C. Meyers, 1996. 

Principles of Corporate Finance, McGraw Hill Companies, Inc.; and Brigham, E.F., and L.C. Gapenski,

1997. Financial Management Theory and Practice. Chicago: The Dryden Press, 8th edition, pp. 1064-

1066.

10 Eastern Research Group, Inc. (ERG), 1999. Review of recent bankruptcy prediction literature.

Memorandum from Maureen Kaplan, ERG, to William Wheeler, U.S. EPA. February 12.

6-4

analysis. This development of a regulatory baseline is consistent with OMB guidance, as discussed in

Section Five.6

The postcompliance analysis identifies companies for which regulatory compliance poses a threat

to financial viability, although they are otherwise financially sound. Such companies could be weakened by

the costs of the regulatory options. These companies are characterized as experiencing a larger impact from

the regulatory options than the majority of industrial laundry firms.

For the industrial laundries industry, a ratio analysis based on the Altman ZO-score is used to

characterize the baseline and postregulatory financial conditions of potentially affected firms. This method

is described in more detail below.

The Altman Z-score, originally developed in the late 1960s for manufacturing firms, is a

multidiscriminant analysis (MDA) used to assess bankruptcy potential.7,8 Over the years, the Altman Zscore model has gained acceptance among financial institutions9

 and, more recently, has been used by EPA

in the regulatory impact analyses for centralized waste treaters, the pharmaceutical industry, and the pulp

and paper industry. A review of numerous measure of financial health concluded that the Altman’s Z

approach, while not perfect, is superior to other such measurement reviewed.10 Altman’s Z-score model

analyzes a number of financial ratios simultaneously to arrive at a single number to predict the overall
11 Brigham, Eugene F., and Louis C. Gapenski, 1997. Ibid.

12 Altman, Edward. 1993. Op. cit.

6-5

Z ' 1.2X1% 1.4X2% 0.33X3% 0.06X4% 0.999X5 (1)

Z ' Overall Index

X1'

Working Capital

Total Assets

X2'

Retained Earnings

Total Assets

X3'

Earnings Before Interest and Taxes

Total Assets

X4'

Market Value of Equity

Book Value of Total Liabilities

X5'

Sales

Total Assets

financial health of a particular firm. The advantage of the Altman Z-score model over traditional ratio

analysis is its simultaneous financial consideration of liquidity, asset management, debt management,

profitability, and market value. It addresses the problem of how to interpret a series of financial ratios when

some financial ratios look “good” while other ratios look “bad.”11 The Altman Z-function is given in

Equation 1:

where,

In a later work, Altman developed two modified versions of this original model for use in

evaluating privately held firms (ZN-score) and firms within a service industry (ZO-score).12 In the original

model, the market value component (X4) uses stock price data; consequently, the Altman Z-score is only

applicable to firms with publicly traded stock. The Z’-score model substitutes the book value of equity

(owner equity) for the market value in X4 and thus can be used to evaluate privately and publicly held firms

on an equal basis. 
13 Ibid.

14 Working capital is current assets minus current liabilities and is a measure of available cash on

(continued...)

6-6

ZO ' 6.56X1% 3.26X2% 6.72X3% 1.05X4 (2)

ZO ' Overall Index

X1'

Working Capital

Total Assets

X2'

Retained Earnings

Total Assets

X3'

Earnings Before Interest and Taxes (EBIT)

Total Assets

X4'

Owner Equity

Total Liabilities

Altman developed the ZO function to extend the analysis to nonmanufacturing industrial firms.

This revision removes the sales/asset component (X5) to minimize the industry-sensitive aspect of asset

turnover. Altman further notes that, “This particular model is also useful within an industry where the type

of financing of assets differs greatly among firms and important adjustments, like lease capitalization, are

not made.”13

Because the industrial laundries industry is a nonmanufacturing industry, the Altman ZO-score is

the most appropriate model to use to evaluate the financial conditions of firms in this industry. The

equation for the Altman ZO-score model is shown in Equation 2:

where, 

Each of the above ratios is further defined below.

# Working Capital to Total Assets is a liquidity ratio which measures a firm’s net liquid

assets relative to total capitalization.14
14(...continued)

hand.

15 For this analysis, owner equity (which is total assets minus total liabilities) is used as a proxy for

retained earnings. Owner equity includes retained earnings; it also includes paid-in capital, which is the

dollar amount over par in stock value. Many industrial laundries are believed to be privately held

(according to the Section 308 Survey, 42 percent are S corporations or other noncorporate entities, which

are typically privately held) thus owner equity will equal retained earnings in these cases.

16Altman, 1993. Op. cit. 

6-7

# Retained Earnings to Total Assets indicates the total amount of reinvested earnings

and/or losses associated with a firm over its entire life, relative to total capitalization. 15

# EBIT to Total Assets measures the productivity of a firm’s assets. Earnings are total firm

revenues minus total firm costs (including general and administrative costs and

depreciation). 

# Owner Equity to Total Liabilities is a solvency ratio that measures the firm’s total

indebtedness to the venture capital invested by the owners. High debt levels can indicate

high levels of risk.

Taken individually, each of the ratios given above (X1 through X4) is higher for firms in good

financial condition and lower for firms in poor financial condition. Consequently, the greater a firm’s

bankruptcy potential, the lower its discriminant score. An Altman ZO-score below 1.1 indicates that

bankruptcy is likely; a score above 2.6 indicates that bankruptcy is unlikely. ZO-scores between 1.1 and 2.6

are indeterminate.16 EPA treats firms with indeterminate scores as financially viable but nevertheless

undertakes a separate postcompliance analysis of firms that have baseline scores in the range indicating

that bankruptcy is unlikely and postcompliance scores in the indeterminate range. These firms are

considered to experience some financial distress short of bankruptcy.

6.2 EVALUATING BASELINE AND POSTCOMPLIANCE RATIOS

6.2.1 Baseline Analysis

As discussed in Section Five, OMB requires EPA to establish a regulatory baseline. There are a

number of firms in this analysis that are likely to fail before the rule is promulgated. As in Section Five,
17 Data on assets, liabilities, owner equity, and EBIT from the Section 308 Survey were inflated by

the CPI for SIC 2718 and averaged over the available years of data (which ranged from 1 to 3 years).

18 The terms “failure” and “bankruptcy” are used interchangeably in this EA.

19 In the rare instance when single-facility firms were shown to close in the baseline in Section Five

but to remain open in Section Six, these closures are also considered baseline failures because EPA

assumes that single-facility firms that close in the baseline are not financially viable as firms and assigns

them an Altman ZO score of 1.00. The facilities in this group are generally firms with very strong equity

positions that closed in the baseline facility-level analysis because they reported a small negative cash flow. 

These firms were found to have baseline Altman ZO-scores in the “bankruptcy unlikely” or “indeterminate”

range, so would not have been shown to fail in the baseline without this additional consideration. This

approach was taken for consistency with the baseline closure analysis, which also characterized singlefacility firms that closed in the baseline as baseline firm failures.

6-8

EPA divides vulnerable firms into those likeliest to fail in the baseline vs. those likeliest to fail

postcompliance as a way to avoid either overcounting or undercounting impacts.

 The baseline analysis uses the Altman ZO-score model to separate financially healthy firms from

those likely to fail regardless of whether the regulation is promulgated. To evaluate the baseline viability of

the companies analyzed, the baseline Altman ZO-score values were calculated for each firm using Section

308 Survey data. Where sufficient data were available, 3-year average (1990-1993) financial ratios were

calculated and used as the baseline ratios.17 At a minimum, 1 year of data was available for all firms. 

Those firms with baseline scores below 1.1 are considered baseline failures18 and are removed from

the analysis.19 All other firms (including those with scores in the indeterminate range) are included in the

postcompliance analysis.

6.2.2 Postcompliance Analysis

EPA undertakes postcompliance analysis for those firms found to be financially viable in the

baseline analysis (i.e., those firms for which the baseline results are “bankruptcy unlikely” or
20 As noted above, EPA considers firms with ZO-scores that fall in the “indeterminate” range to be

viable operations, although the financial stability of these firms might be somewhat uncertain.

21 The pollution control costs for each option were calculated using the cost annualization model

described in Section Four.

22 To estimate firm-level impacts at multifacility firms owning nonsurveyed industrial laundry

facilities, EPA assumes that the capital costs and change in EBIT associated with compliance costs for

nonsurveyed facilities are equal to the capital costs and change in EBIT at the surveyed nonindependent

facility with the median and mean annual compliance costs, whichever was higher, depending on regulatory

option. Because EPA used all nonindependent facilities to compute the mean or median, costs are likely

overstated at the smaller more vulnerable firms, although they could be somewhat understated at the largest

firms, which tend to own the largest facilities. Multifacility firms are, however, not very sensitive to this

assumption (ERG, 1999. Multifacility firm failure analysis using maximum costs. Memordandum from

Anne Jones and Andrea Desilets, to George Denning, U.S. EPA, May 11). For each multifacility firm,

costs and change in EBIT for surveyed facilities are summed with estimated costs and change in EBIT for

nonsurveyed facilities to develop firm-level figures. The number of nonsurveyed industrial laundry

facilities owned by each multifacility firm is calculated based on responses to the Section 308 Survey,

which asks for the total number of industrial laundry facilities owned by the firm.

23 These calculations assume 100 percent financing of compliance equipment through long-term

debt, although tax shield on interest payments are not included (see Appendix B). Firms can choose to use

working capital or debt. If choosing working capital over debt puts them in precarious financial position,

(continued...)

6-9

“indeterminate”).20 The total number of potentially affected firms in the postcompliance analysis is adjusted

downward to exclude the baseline bankruptcies. 

Postcompliance bankruptcy predictions are based on changes in the financial status of a firm as a

result of incremental pollution control costs.21 The change in a firm’s bankruptcy potential as a result of

incremental pollution control costs, as predicted by the Altman ZO-score, is determined using firm-specific

capital and annual O&M costs associated with each regulatory option. For the postcompliance analysis, the

relevant survey data (total assets, total liabilities, and EBIT) are adjusted to reflect facility compliance

costs for all facilities owned by a particular company.22 Compliance costs for each facility owned by each

company are incorporated into the analysis as follows:

# Postcompliance Total Assets = Total Assets + Capital Cost (3)

# Postcompliance Total Liabilities = Total Liabilities + Capital Cost (4)

# Postcompliance EBIT = EBIT – (Postcompliance Change in EBIT)23 (5)
(...continued)

then that is a poor business decision. EPA must assume firms make reasonable business decisions. Firms

are assumed to incur all compliance costs for all facilities regardless of whether the facilities close in the

baseline or postcompliance facility-level analyses, since liquidation and other costs associated with a

facility closure will not exceed the compliance costs associated with a closing facility. Note that the

postcompliance change in assets and liabilities are set to capital expenditures for modeling simplicity, thus

also providing a conservative estimate of ratios (assets and liabilities are used in the denominators of

Altman’s ZO ratios, so larger numbers reduce those ratios). EBIT is calculated using one year’s O&M plus

the third year depreciation to adjust baseline EBIT. This year’s depreciation was selected, since Altman’s

ZO is likeliest to identify bankruptcies over a 2- to 5-year period.

24 Although some industry sources indicated that the acquisition of a firm or facility does not result

in employment losses and that the facilities or firms are usually operated intact, others indicated that many

facilities or firms might be acquired and transformed into depots with a subsequent loss of up to 75 percent

of the employees (see discussion in Section Three).

6-10

The postcompliance analysis is performed under the assumption that the industry could not have

passed through compliance costs to its customers (an alternative analysis assuming cost passthrough is

presented in Appendix A). The change in EBIT presented in Equation (5) reflects no cost passthrough.

Note that even if a firm is considered likely to fail, its facilities (as determined in the facilityclosure analysis) might not close. In the cases where a firm is considered likely to fail, its viable facilities

could be sold as part of the company liquidation process and operated successfully under different

ownership. Also note that some facilities could be sold (and continue to operate) to raise the necessary

capital to finance the installation of pollution control equipment at a firm’s remaining facilities. Thus

multifacility firms that are estimated to fail but that do not have facilities that are estimated to close (as

discussed in Section Five) are not considered as severely affected as firms that are estimated to fail and to

have to close some or all of their facilities. Single-facility firms that fail but do not close are assumed to be

sold, so the primary impact to these firms is their loss of independent status. This impact is considered to

be a lesser impact than closure, but is assumed to have some impact on employment in the industry (see

Section Seven).24 Single-facility firms that fail and close would not be counted here because the significant

impacts to these entities are already captured in the closure analysis in Section Five.
25 Note that of the 830 single-facility firms, 96 single-facility firms fail in the baseline because their

facilities are predicted to close in the baseline facility-level analysis in Section Five. (As discussed above,

single-facility firms that close in the baseline are assumed also to fail. Even if this assumption is not made,

however, most of these 96 firms would fail based on the Altman ZO analysis.) Thus only 59 firms fail in the

baseline additional to those closing in the baseline. This totals 155 facilities, leaving 675 single-facility

firms in the analysis. Additionally, 0 to 94 single-facility firms are estimated to close in the postcompliance

analysis presented in Section Five, depending on cutoff. These 0 to 94 firms have been removed from the

postcompliance analyses, as discussed earlier, to avoid double counting of impacts. Thus the actual number

of single-facility firms analyzed ranges from 581 to 675, depending on cutoff.

6-11

6.3 BASELINE AND POSTCOMPLIANCE ALTMAN ZO-SCORE RESULTS

6.3.1 Baseline Altman ZO-Score Results

Table 6-1 presents the baseline results of the Altman ZO-score analysis, grouped according to firm

type (single-facility and multifacility). The table presents the total number of firms in each of the ZO-score

categories (i.e., “bankruptcy likely,” “indeterminate,” and “bankruptcy unlikely”), as well as the total

number of firms in each ZO-score category broken down by revenue groups. As stated previously, an

Altman ZO-score below 1.1 indicates that bankruptcy is likely; a score above 2.6 indicates that bankruptcy

is unlikely. ZO-scores between 1.1 and 2.6 are indeterminate. 

The results in Table 6-1 indicate that single-facility firms have the greatest likelihood of

bankruptcy in the baseline, with nearly 19 percent of single-facility firms facing potential bankruptcy prior

to the imposition of any regulatory costs. Additionally, among single-facility firms, EPA predicts that firms

with less than $1 million in revenues will experience the largest number of bankruptcies in the baseline.

Based on these results, note that multifacility firms appear less likely to fail in the baseline analysis than

single-facility firms.

EPA analyzed an initial total of 745 firms (675 single-facility firms and 70 multifacility firms)25 in

the postcompliance analysis, the results of which are discussed in Section 6.3.2. These numbers include

firms in a small industrial laundries exclusion as defined by the cutoffs, but do not include any that close or

fail in the baseline. Of the firms considered in the postcompliance analysis, a number of firms fall in the

“indeterminate” category postcompliance. EPA considers these firms to be viable operations in marginal

financial health; as such, these firms are discussed separately in Section 6.3.3.
Table 6-1

Baseline Firm Failure Analysis- All Firms

Bankruptcy Likely Indeterminate Bankruptcy Unlikely

Z''<1.1 1.1<Z''<2.6 Z''>2.6

Firm Size Percentage of Percentage of Percentage of 

or Type Number Revenue Group Number Revenue group Number Revenue Group

Multifacility Firms

 All Multifacility Firms 3 4.5% 8 11.4% 61 84.1%

 By Revenue Group ($000)

< $1 Million 0 0.0% 0 0.0% 2 100.0%

>= $1 and < $3.5 Million 0 0.0% 0 0.0% 5 100.0%

>= $3.5 and < $7 Million 0 0.0% 0 0.0% 8 100.0%

>= $7 and < $10.5 Million 0 0.0% 2 16.7% 8 83.3%

>= $10.5 Million 3 6.9% 7 13.8% 38 79.3%

Single-Facility Firms

 All Single-Facility Firms 155 18.6% 65 7.9% 610 73.5%

 By Revenue Group ($000)

< $1 Million 84 46.0% 34 18.5% 64 35.4%

>= $1 and < $3.5 Million 28 9.5% 11 3.7% 254 86.8%

>= $3.5 and < $7 Million 42 11.4% 18 7.6% 198 81.1%

>= $7 and < $10.5 Million 0 0.0% 0 0.0% 81 100.0%

>= $10.5 Million 1 0.0% 3 15.4% 14 84.6%

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are included in

 the Decisionmaking Record.

6-12
6-13

6.3.2 Postcompliance Altman ZO-Score Results — “Bankruptcy Likely”

Table 6-2 presents the results of the postcompliance Altman ZO analysis for single-facility firms

under the CP-IL option (the results for the DAF-IL option are identical and are discussed in Appendix C).

As the table shows, most bankruptcies would have occurred among firms with revenues under $1 million

per year with no cutoff or under the 1MM/255K cutoff. Numbers of firms potentially facing bankruptcy

(or loss of independent status) total 72 under these two scenarios. Under the higher 3MM/120K and

5MM/255K cutoffs, no firm failures would have occurred. 

Table 6-3 presents the results of the postcompliance Altman ZO analysis for multifacility firms: no

failures are expected under any cutoffs.

Table 6-4 combines the results for the two types of firms. As the table shows, impacts range from

no to 72 failures, or 0 percent to 9.7 percent of all firms depending on cutoff. The selected 3MM/120K

cutoff is associated with no firm failures.

6.3.3 Postcompliance Altman ZO-Score Results — Change From Healthy to Indeterminate

Status 

Table 6-5 presents the results of an analysis looking at the numbers of facilities that change from

Altman ZO-scores of greater than 2.6 (bankruptcy unlikely) to less than 2.6 but greater than 1.1 (status

“indeterminate”). As the table shows, 0 to 54 firms change financial status in this manner, depending on

cutoff. This result is considered a potential impact of the regulatory options, but is considered a lesser

impact than bankruptcy, because these firms might not have been on track to failure if a pretreatment

standard had been implemented and probably would have had more time and flexibility to improve their

financial condition than those firms whose scores fell in the “bankruptcy likely” category. The 3MM/120K

cutoff is associated with no firms changing status from healthy to indeterminate.
Table 6-2

Firm Failure Analysis - Single-Facility Firms*

CP_IL CP_IL CP_IL CP_IL

Bankruptcies no cutoff 1MM/255K 3MM/120K 5MM/255K

All single-facility firms (N=675)**

Incremental bankruptcies 72 72 0 0

Percentage of all single-facility firms 12.1% 12.1% 0.0% 0.0%

Single-facility firms with revenues < $1 million (N=98)**

Incremental bankruptcies 53 53 0 0

Percentage of all single-facility firms 9.0% 9.0% 0.0% 0.0%

Percentage of revenue group 90.6% 90.6% 0.0% 0.0%

Single-facility firms with revenues >= $1 million and < $3.5 million (N=264)**

Incremental bankruptcies 0 0 0 0

Percentage of all single-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Single-facility firms with revenues >=$3.5 million and < $7 million (N=216)**

Incremental bankruptcies 18 18 0 0

Percentage of all single-facility firms 3.1% 3.1% 0.0% 0.0%

Percentage of revenue group 8.5% 8.5% 0.0% 0.0%

Single-facility firms with revenues >=$7 million and <$10.5 million (N=81)** 

Incremental bankruptcies 0 0 0 0

Percentage of all single-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Single-facility firms with revenues >=$10.5 million (N=16)**

Incremental bankruptcies 0 0 0 0

Percentage of all single-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline bankruptcies and baseline and postcompliance closures among single-facility firms.

** Number of facilities in each revenue group varies by the difference in postcompliance closures among

 options.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

6-14
Table 6-3

Firm Failure Analysis - Multifacility Firms*

CP_IL CP_IL CP_IL CP_IL

Bankruptcies no cutoff 1MM/255K 3MM/120K 5MM/255K

All multifacility firms (N=70)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Multifacility firms with revenues < $1 million (N=2)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Multifacility firms with revenues >= $1 million and < $3.5 million (N=5)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Multifacility firms with revenues >=$3.5 million and < $7 million (N=8)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Multifacility firms with revenues >=$7 million and <$10.5 million (N=10)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Multifacility firms with revenues >=$10.5 million (N=45)

Incremental bankruptcies 0 0 0 0

Percentage of all multi-facility firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline bankruptcies and baseline and postcompliance closures among single-facility firms.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

6-15
Table 6-4

Firm Failure Analysis - All Firms*

CP_IL CP_IL CP_IL CP_IL

Bankruptcies no cutoff 1MM/255K 3MM/120K 5MM/255K

All firms (N=745)**

Incremental bankruptcies 72 72 0 0

Percentage of all firms 9.6% 9.6% 0.0% 0.0%

Firms with revenues < $1 million (N=100)** 

Incremental bankruptcies 53 53 0 0

Percentage of all firms 7.2% 7.2% 0.0% 0.0%

Percentage of revenue group 53.5% 53.5% 0.0% 0.0%

Firms with revenues >= $1 million and < $3.5 million (N=269)**

Incremental bankruptcies 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$3.5 million and < $7 million (N=224)**

Incremental bankruptcies 18 18 0 0

Percentage of all firms 2.5% 2.5% 0.0% 0.0%

Percentage of revenue group 8.2% 8.2% 0.0% 0.0%

Firms with revenues >=$7 million and <$10.5 million (N=91)**

Incremental bankruptcies 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$10.5 million (N=61)**

Incremental bankruptcies 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline bankruptcies and baseline and postcompliance closures among single-facility firms.

** Number of facilities in each revenue group varies by the difference in postcompliance closures among

 options.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

6-16
Table 6-5

Indeterminate Analysis - All Firms

CP CP CP CP

Indeterminates no cutoff 1MM/255K 3MM/120K 5MM/255K

All firms (N=651)

Incremental indeterminates 54 7 0 0

Percentage of all firms 7.3% 0.9% 0.0% 0.0%

Firms with revenues < $1 million (N=49)

Incremental indeterminates 2 2 0 0

Percentage of all firms 0.2% 0.2% 0.0% 0.0%

Percentage of revenue group 1.7% 1.7% 0.0% 0.0%

Firms with revenues >= $1 million and < $3.5 million (N=226)

Incremental indeterminates 33 2 0 0

Percentage of all firms 4.5% 0.2% 0.0% 0.0%

Percentage of revenue group 12.3% 0.6% 0.0% 0.0%

Firms with revenues >=$3.5 million and < $7 million (N=224)

Incremental indeterminates 17 2 0 0

Percentage of all firms 2.2% 0.2% 0.0% 0.0%

Percentage of revenue group 7.4% 0.7% 0.0% 0.0%

Firms with revenues >=$7 million and <$10.5 million (N=91)

Incremental indeterminates 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$10.5 million (N=61)

Incremental indeterminates 3 2 0 0

Percentage of all firms 0.4% 0.2% 0.0% 0.0%

Percentage of revenue group 4.5% 2.7% 0.0% 0.0%

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are

 included in the Decisionmaking Record.

6-17
1Note that many of these operators may be transferred at least in part from production jobs at

industrial laundry facilities (Knight, Lynn, ERG, 1993. “Interview and site visit with Brian Keegan,

Unifirst,” June 10. CBI material in the Decisionmaking Record.)

7-1

SECTION SEVEN

INDUSTRY, NATIONAL, AND REGIONAL EMPLOYMENT

IMPACTS AND TOTAL NATIONAL OUTPUT LOSSES

This section of the EA assesses the employment impacts of the regulatory options EPA considered

during the pretreatment standards decisionmaking process on the industrial laundries industry, the national

economy, and communities in which highly affected industrial laundries are located. It also discusses

output losses to the national economy that would have been induced by revenue losses in the industrial

laundries industry. Only impacts on existing sources are discussed here; Section Five discusses impacts on

new sources. 

EPA first examines the losses of employment in the industrial laundries industry and U.S. economy

driven by the facility closures and failures that were estimated in Sections Five and Six to have occurred

under the CP-IL option and the various cutoffs examined. Next EPA examines national-level employment

losses and gains that would have occurred throughout the economy in response to the reallocation of

expenditures had pretreatment standards been promulgated. Additionally, because closures can overstate or

understate total employment losses over time (since nonclosing facilities might have expanded production to

take over some of the lost production of closing facilities, if not capacity constrained, or production losses

at market equilibrium might be greater than those associated with closing facilities), EPA also estimates

longer-term employment losses that might have occurred in the industrial laundries industry alone. These

losses are tempered by gains within that industry (due to direct hiring of pollution control equipment

operators within the industry),1 so EPA calculates a net direct loss of employment in this analysis. Finally,

EPA examines regional-level losses to determine impacts on communities.

To understand the methods for estimating national- and regional-level impacts, whether driven by

closures and failures or by output losses, an understanding of input-output (I-O) analysis is required. 

Pollution control expenditures divert investment away from production by industrial laundries (production
2When the demand curve is perfectly elastic, the output loss, which is a function of the unit cost of

compliance (cost of compliance per pound of laundry processed), simplifies to Output = (Total Cost of

Compliance/Initial Quantity of Production) * Initial Quantity of Production. Thus output loss further

simplifies to the total cost of compliance. Appendix A discusses some of these equations in more detail. 

This assumption will hold as long as the supply curve is roughly unitary (neither very elastic nor very

inelastic). The loss of output occurs because the industry supply curve shifts up over all points in the

curve. The industry supply curve is the aggregation of all facilities’ marginal cost curves, which increase

at every point when pollution control costs are added to production costs (see Figure A-1 in Appendix A).

7-2

in this context is economic terminology meaning “production” of industrial laundering services), which

leads to direct employment losses and to a reduction in industrial laundry production. These losses are

offset by gains in employment and production in the firms that manufacture the pollution control equipment

and by gains in employment related to installing and operating the equipment. Some of these gains might

have even occurred in the industrial laundries industry itself. These gains and losses can be measured using

I-O analysis.

To compute either regional- or national-level employment changes, output effects or direct

employment losses such as facility closures must be considered. Output loss, as defined for the purposes of

I-O analysis, is measured as the total production loss multiplied by the unit price of that production (price

per pound of laundry), or the gross revenue loss to the industry. Industrial laundry investments in

compliance equipment and the operation of the equipment translate directly into output losses in the

industrial laundries industry (assuming none of these costs is passed through to customers); that is, the

costs of compliance equal the output losses, which is consistent with economic theory under a zero cost

passthrough scenario (perfectly elastic demand curve—see Appendix A).2 Declines in production at

industrial laundries affect the revenues of input industries (industries that supply goods and services to the

industrial laundries industry). These shifts in turn eventually result in a reduction of household

consumption by workers in both industrial laundries and input industries, decreasing demand for consumer

products at the national level. Direct employment effects such as employment losses from postcompliance

facility closures or firm failures also can be used to derive national- and regional-level impacts using directeffect multipliers. Impacts on the industrial laundries industry are known as direct effects, impacts that

continue to resonate through the economy are known as indirect effects (effects on input industries), and

effects on consumer demand are known as induced effects. Such effects are tracked both nationally and

regionally in massive I-O tables prepared by the U.S. Department of Commerce’s Bureau of Economic

Analysis (BEA). For every dollar spent in a “spending industry” (or for every employment change in the
3

 One FTE = 2,080 labor hours = 1 person-year of employment.

7-3

directly affected industry), these tables identify the portion spent (or every employment change) in

contributing or vendor industries and the portion spent by consumers (or employment change as a result of

a change in consumption). 

For example, as a result of the implementation of the CP-IL option (results of only the CP-IL

option are discussed here, since the DAF results are nearly identical), an industrial laundry might have had

to purchase equipment to meet the standards equivalent to chemical precipitation. One piece of this

equipment could be a tank to hold wastewater. To make the tanks, the manufacturer would purchase

stainless steel. The steel manufacturer would purchase iron ore, coke, energy sources, and other

commodities. Thus a portion of a dollar spent by the industrial laundries industry becomes a smaller

portion of a dollar spent by the tank manufacturer, and a smaller portion of a dollar spent by the steel

manufacturer, and so on. These iterations are captured in BEA’s I-O tables and summarized as regional

and national multipliers for output (revenues). BEA also has determined average wages and the proportion

of output in each industry that goes to employee earnings and, as a result, the number of employees or fulltime equivalents (FTEs)3

 associated with each $1 million change in output. I-O analysis provides a

straightforward framework as long as the direct effects to the industry are small and certain limiting

assumptions about technology are valid (e.g., constant returns to scale and fixed input ratios). 

As noted above, I-O analysis uses the multipliers derived by BEA to determine both output and

employment effects. There are national-level multipliers and regional-level multipliers. National-level

multipliers used here include final-demand output multipliers (which are used to estimate total U.S.

economy effects when output changes in a specific industry), final-demand employment multipliers (which

are used to estimate the change in total U.S. employment when output changes in a specific industry), and

direct-effect employment multipliers (which are used to estimate the change in U.S. employment given a

change in employment in a specific industry, for example changes in employment due to closures or

failures). The regional multipliers used here are direct-effect employment multipliers (which are used to

estimate a state-wide change in employment given a change in employment in a specific industry in a

specific state). These multipliers will be discussed in more detail below. 
7-4

The analysis of employment and output losses (as well as related impacts) is divided into four

parts. Section 7.1 presents the methodology and results for estimating the direct employment losses in the

industrial laundries industry based on the facility closures and firm failures estimated in Sections Five and

Six to have occurred as a result of compliance with the CP-IL option under the various cutoffs considered. 

This section also discusses the impacts such losses would have on the national-level economy. 

Section 7.2 analyzes the national-level impacts of the CP-IL option on both labor and output using

direct output effects, which produce a different estimate of employment effects than that derived using

closures and failures, since output effects and economic impacts are never exactly correlated. 

Section 7.3 discusses two analyses that calculate the net, direct impacts on the industrial laundries

industry based on reductions in output or production (which in turn affect employment) These analyses are

considered the longer-term impacts of the rule, with the impacts from closures and failures being the more

immediate impacts of the rule. The first analysis uses the standard I-O analysis assumption that compliance

costs equal direct output losses to compute employment losses within the industrial laundries industry. 

This estimate is considered a reasonable worst-case estimate. The second analysis uses production losses

estimated by EPA’s market model (assuming costs can be passed through) and current price to estimate the

output losses in the industry, which is then used to compute direct employment losses. This analysis is

considered to produce a reasonable best-case estimate of employment losses, and the two analyses together

are considered reasonable bounding estimates of net, production-driven, longer-term impact. 

Finally, Section 7.4 examines the regional impacts associated with employment losses and presents

the methodology and results of the employment loss and community-level impact analyses. Note that the net

change in employment at the national level includes the regional-level losses (i.e., national and regional

losses are not additive).

7.1 INDUSTRY-LEVEL EMPLOYMENT LOSSES FROM FACILITY CLOSURES AND

FIRM FAILURES

This section assesses the employment losses that might have occurred based on estimates of facility

closures and firm failures presented in Sections Five and Six. According to these estimates, from 2 to 106
4

 Based on comments from industry (see Comment Response Document, PECON-2D, Tracking

No. 1494), EPA has revised its methodology for calculating the short-term employment effects by

assuming that failures can also contribute to employment losses. Comments received indicated that as

much as 75 percent of employment might be lost if a failing firm is acquired and turned into a depot instead

of continuing to operate. 

5

 U.S. Department of Commerce, 1992. Table A-2.4—Total Multipliers, by Industry Aggregation,

for Output, Earnings, and Employment. Regional Input-Output Modeling System (RIMS II). Washington,

DC: BEA, Regional Analysis Division, (RIMS II National Multipliers).

7-5

facilities would have been expected to close and from 0 to 72 firms would have been expected to fail,

depending on cutoff. Closing facilities are associated with 235 to 3,318 FTEs, depending on cutoff, based

on the analysis in Section Five and on Section 308 Survey data on employment at closing facilities (see

Table 7-1). The number of FTEs associated with failing firms range from 0 to 2,294, of which EPA

estimates as many as 75 percent might be lost in the process of firm acquisitions.4 Thus from 0 to 1,721

FTEs might have been lost as a result of firm failures. Therefore, total losses might have ranged from 235

to 5,039 FTEs. 

As noted above in the introduction, these direct effects are associated with indirect and induced

employment effects, which can be estimated using BEA’s national-level direct-effect employment multiplier

for the industrial laundries industry (1.7201)5

. Total employment losses to the U.S. economy associated

with the employment losses occurring in the industrial laundries industry due to closures and failures are

estimated to have been 404 to 8,667 FTEs, depending on cutoff (see Table 7-1). The 3MM/120K cutoff is

associated with direct losses of 2,261 FTEs and direct, indirect, and induced losses of 3,889 FTEs. This

latter number, while a national-level figure, does not account for output-based losses (which can be

different from losses calculated on the basis of facility closures and firm failures, as discussed above), nor

does it account for possible employment gains due to the need for operating pollution control equipment. 

Output-based employment losses and gains in the national-level economy are discussed in Section 7.2.
Table 7-1

Employment Losses in the U.S. Economy Based on Closures and Failures in the

Industrial Laundries Industry

Employment Total Closure

Employment Losses Based on Percent of Direct Effect Total Closure- Plus FailureLosses Based on Facility Closures Industry Employment Based Based

Option Facility Closures Plus Failures Employment Multiplier FTE Loss FTE Loss

 No Cutoff 3,318 5,039 3.9% 1.7201 5,707 8,667

 1MM/255K 2,684 4,405 3.4% 1.7201 4,617 7,576

 3MM/120K 2,261 2,261 1.8% 1.7201 3,889 3,889

 5MM/255K 235 235 0.2% 1.7201 404 404

Source: EPA, 1999, Firm and Facility Financial Model and Section 308 Survey Data. Multiplier is from Department of

Commerce, 1992, op. cit.

7-6
7-7

7.2 NATIONAL-LEVEL OUTPUT AND EMPLOYMENT IMPACTS

7.2.1 Introduction

To comply with the CP-IL option, facilities might have needed to install and operate pollution

control systems. The costs for these systems would have reduced output and employment in the industrial

laundries industry and increased output and employment in the sectors that manufacture, install, and

operate pollution control equipment.

Despite the fact that employment losses and gains associated with pollution control expenditures

tend to act as counterbalances, there are differences in the national-level economy under baseline and

postcompliance scenarios. Baseline and postcompliance labor effects differ primarily because the industrial

laundries industry is substantially more labor-intensive than the various pollution control industries.

Furthermore, the output multiplier for the industrial laundries industry is greater than those for the

pollution control industries, so output losses might exceed output gains.

7.2.2 Methodology for Estimating National-Level Output and Employment Impacts

EPA estimates two categories of national-level impacts associated with the CP-IL option: impacts

on output in the economy as a whole (in dollars) and impacts on national employment (in FTEs).

7.2.2.1 National-Level Output Losses and Gains

The loss in national-level output associated with output loss in the industrial laundries industry is

estimated using the pretax capital and O&M costs of compliance (not adjusted for cost passthrough), which

were presented in Section Four, Table 4-3, for each of the regulatory options. The pretax costs are used

because I-O multipliers are based on changes in revenues, which are pretax numbers. 
6

 Department of Commerce, 1992. Op cit.

7

Ibid.

8

 Includes tanks.

9

 The weighted multiplier is developed assuming that 20 percent of capitol costs is piping, 10

percent is pumps, and 70 percent is tanks. These breakdowns, as well as those discussed in the following

bullets, are developed on the basis of discussions with EPA’s technical contractor (telephone conversation

between Anne Jones, Eastern Research Group, Lexington, MA, and Wendy Grome, Eastern Research

Group, Herndon, VA, June 3, 1997). These same assumptions are applied to the development of the

employment multiplier breakdown discussed later.

7-8

BEA industry 72.0201, which corresponds to SIC 721 and 725 (laundry, cleaning, garment

services, and shoe repair), is the detailed industry category that most closely matches the industrial

laundries industry. The national-level output multiplier estimated by BEA for this industry grouping is

3.7134 (RIMS II National Multipliers).6 This multiplier represents the total dollar change in national

output for all industries for each dollar change in the output of the industrial laundries industry. Using the

BEA multiplier and the output loss to the industry (equivalent to the pretax compliance costs to the

industry, as discussed above), EPA estimates losses throughout the national economy in the following way: 

Option Compliance Cost x 3.7134 = National-Level Output Loss

EPA also estimates the output gains in the economy using the following output multipliers7

 for the

pollution control industries: 

# For capital material costs: BEA Industry 42.0800 (pipes, valves, and pipe fittings); BEA

Industry 40.0600 (fabricated plate work);8 and BEA Industry 49.0100 (pumps and

compressors), with a weighted output multiplier of 3.0516.9 Capital material costs are

assumed to be 85 percent of the total capital costs estimated for each option.

# For installation costs: BEA Industry 11.0000 (construction — new and maintenance and

repair), with a multiplier of 3.1957. Installation costs are assumed to be 15 percent of total

capital costs estimated for each option.

# For operating costs: (1) Labor: BEA Industry 72.0201 (laundries), with a multiplier of

3.7134 (assumes that operators for pollution control equipment will be hired by the

affected industry); (2) Materials: BEA Industry 27.0406 (chemical and chemical

preparations, not elsewhere classified) with a multiplier of 2.9083; (3) Energy: BEA
10Employment impacts calculated using a final-demand multiplier include direct, indirect, and

induced effects.

11 Losses are deflated to 1992 dollars because BEA’s national multipliers are based on 1992 data. 

EPA uses Engineering News Record, 1997. “Construction Cost Index,” March 31, for deflating.

12 The difference in output multipliers between the industrial laundries and its customer industries

is not so extreme, thus the overestimate of the national-level employment loss may be proportionately

(continued...)

7-9

Industry 68.0100 (electric services [utilities]), with a multiplier of 2.2370. Labor,

materials, and energy costs are assumed to make up one-third each of operating costs.

Gains are calculated using the cost share assigned to an industry (e.g., O&M cost/3 x 2.9083 =

national-level output gain associated with the materials portion of O&M cost). When all the gains

associated with pollution control industries are aggregated, EPA can estimate the total output gains

attributable to the CP-IL option. To determine a net loss or gain, EPA then compares the losses and gains

in the economy.

7.2.2.2 National-Level Employment Losses and Gains

In calculating national-level employment impacts, the Agency uses a similar approach to that used

to calculate output effects. Based on industrial laundries industry output, BEA (RIMS II National

Multipliers) has estimated a final-demand multiplier for national-level employment of 83.3. This number

represents the total change in the number of jobs in all industries nationally for each $1 million change in

output delivered to final demand by the industrial laundries industry.10 Therefore, to calculate employment

impacts, EPA divides the output loss of the industrial laundries industry, measured as the annual pretax

compliance cost, by $1 million and multiplies this figure by BEA’s employment multiplier.11

EPA believes that this approach will yield a possible worst-case estimate of employment losses

nationwide because the Agency is assuming costs are not passed through to customers. Customer industries

generally have much lower multipliers (on the basis of number of employees per $1 million output).

Customer multipliers are easily half of the 83.3 employees per $1 million output of the industrial laundries

industry.12
12(...continued)

greater than the overestimate of the national-level output loss.

13Weighting is the same as that used for the output gains analysis.

7-10

Employment gains are estimated using the final-demand multipliers for each of the pollution

control industries listed above. These multipliers are:

# For capital material costs: BEA Industry 42.0800 (pipes, valves, and pipe fittings); BEA

Industry 40.0600 (fabricated plate work); and BEA Industry 49.0100 (pumps and

compressors), with a weighted average final-demand employment multiplier of 31.4.13

# For installation costs: BEA Industry 11.0000 (construction — new and maintenance and

repair), with a multiplier of 21.5.

# For operating costs: (1) Labor: BEA Industry 72.0201 (laundries), with a multiplier of

83.3 (assumes that operators for pollution control equipment will be hired by the affected

industry); (2) Materials: BEA Industry 27.0406 (chemicals and chemical preparations, not

elsewhere classified) with a multiplier of 23.7; and (3) Energy: BEA Industry 68.0100

(electric services [utilities]), with a multiplier of 15.8.

EPA computes employment gains by multiplying the appropriate industry shares of the pollution

control costs times the appropriate multiplier. After aggregating all gains, EPA compares national-level

losses and gains to compute the net employment change resulting from the CP-IL option. This net change

can then be compared to national-level employment to gauge the magnitude of employment impacts on the

national economy.

7.2.3 National-Level Output and Employment Impacts

The sections that follow present the national-level output losses and employment losses calculated

on the basis that direct output losses equal compliance costs in Sections 7.2.3.1 and 7.2.3.2.
14 U.S. Government Printing Office, 1997. Economic Report of the President, February, 1997.

Washington, DC: U.S. Government Printing Office.

15 BEA's RIMS II National Multipliers are based on 1992 data.

16 U.S. Government Printing Office, 1997. Op. cit.

7-11

7.2.3.1 National-Level Output Losses

Table 7-2 shows the total gross, national-level output losses associated with the CP-IL option.

Using the output multiplier of 3.7134, EPA estimates national-level output losses would have ranged from

$287.4 million to $667.3 million per year, depending on cutoff.

Table 7-3 shows the total gross national-level output gains associated with purchasing, installing,

and operating pollution control equipment. The national-level output gains are estimated to total $232.3

million to $535.4 million per year with a net annual loss of national-level output of $55.1 million to $131.9

million per year, depending on cutoff (see Table 7-4). At most, this is 0.001 percent of 1993 gross

domestic product ($6.6 trillion),14 thus EPA believes this loss would have had a negligible effect on the

national-level economy.

7.2.3.2 National-Level Employment Losses

Table 7-5 presents the national-level employment losses associated with potential lost industrial

laundries industry output. EPA converts the industry output losses into millions of 1992 dollars15 and

multiplies these losses by the employment multipliers to determine total annual employment losses of 6,169

to 14,322 FTEs, depending on cutoff. Note that the losses estimated here for national-level employment

losses exceed those estimated using facility closures and failures in Section 7.1. At most, this is only 0.01

percent of total U.S. employment of 120.3 million persons in 1993.16

Table 7-6 presents the national-level employment gains associated with the output gains in the

pollution control industries. These gains total 2,780 to 6,422 FTEs, depending on cutoff. The CP-IL option

therefore is associated with a net loss of 3,389 to 7,900 FTEs, depending on cutoff (see Table 7-7).
Table 7-2 

Annual National-Level Output Losses (millions, 1993 dollars)

Total Estimated Output Loss 

in the Industrial Laundries Output National-Level

Option Industry Multiplier Output Losses

 No Cutoff $179.70 3.7134 $667.30

 1MM/255K $171.29 3.7134 $636.07

 3MM/120K $131.25 3.7134 $487.38

 5MM/255K $77.40 3.7134 $287.42

Source: Output loss is from U.S. EPA, 1999. IL Facility and Firm Financial Model (included in Decisionmaking

Record). Output multiplier is from U.S. Department of Commerce, 1992. Table A-2.4--Total Multipliers, by 

Industry Aggregation, for Output,Earnings and Employment. Regional Input-Output Modeling System 

(RIMS II). BEA, Regional Analysis Division.

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7-13

Table 7-3

Annual National-Level Output Gains (millions, 1993 dollars)

Item No Cutoff 1MM/255K 3MM/120K 5MM/255K

Total Capital Cost (Annualized Over 16 Years at 7%) $55.98 $53.72 $41.02 $24.78

Capital Materials Cost (85% of Total Cost) $47.58 $45.66 $34.87 $21.06

Capital Materials Multiplier 3.0516 3.0516 3.0516 3.0516

Output Gain (Capital Materials) $145.20 $139.35 $106.40 $64.28

Installation Cost (15% of Total Cost) $8.40 $8.06 $6.15 $3.72

Installation Cost Multiplier 3.1957 3.1957 3.1957 3.1957

Output Gain (Installation) $26.83 $25.75 $19.66 $11.88

Total O&M Cost $123.06 $116.84 $89.16 $52.87

Labor Share (33.3%) $41.02 $38.95 $29.72 $17.62

Labor Multiplier 3.7134 3.7134 3.7134 3.7134

Output Gain (Labor) $152.32 $144.62 $110.36 $65.44

Materials Share (33.3%) $41.02 $38.95 $29.72 $17.62

Materials Multiplier 2.9083 2.9083 2.9083 2.9083

Output Gain (Materials) $119.30 $113.27 $86.43 $51.25

Energy Share (33.3%) $41.02 $38.95 $29.72 $17.62

Energy Multiplier 2.237 2.237 2.237 2.237

Output Gain (Energy) $91.76 $87.12 $66.48 $39.42

Total Output Gain $535.41 $510.12 $389.34 $232.28

Source: Capital and O&M costs are from EPA's Final Technical Report. Multipliers are derived as discussed in the EA.
Table 7-4

Net Annual National-Level Output Losses (millions, 1993 dollars)

Net Loss in

Total Annual Total Annual National-Level

Option Loss Gain Output

No Cutoff $667.30 $535.41 $131.88

1MM/255K $636.07 $510.12 $125.95

3MM/120K $487.38 $389.34 $98.04

5MM/255K $287.42 $232.28 $55.14

Source: Tables 7-1 and 7-2.

7-14
Table 7-5

National-Level Employment Losses (FTEs)

Total Annual Output Output Total OutputLoss in the IL Loss in 1992 Employment Based FTE

Option Industry ($ MM 1993) Dollars ($ MM 1992) Multiplier Loss

No Cutoff $179.70 $171.94 83.3 14,322

1MM/255K $171.29 $163.89 83.3 13,652

3MM/120K $131.25 $125.58 83.3 10,461

5MM/255K $77.40 $74.06 83.3 6,169

Note: Employment losses for firm failures are assumed to be 75% of total employment.

Source: Output loss is from Table 7-1. Employment multiplier is from U.S. Department of Commerce, 1992. 

Table A-2.4--Total Multipliers, by Industry Aggregation, for Output, Earnings and Employment. 

Regional Input-Output Modeling System (RIMS II). BEA, Regional Analysis Division.

1993 dollars are deflated to 1992 dollars using the Engineering News Record's Construction Cost Index (0.9568).

7-15
Table 7-6

National-Level Employment Gains (FTEs) (Millions, 1992 Dollars)

Item No Cutoff 1MM/255K 3MM/120K 5MM/255K

Total Capital Cost (Annualized over 16 years at 7%) $53.56 $51.40 $39.25 $23.71

Capital Materials Cost (85% of total cost) $45.53 $43.69 $33.36 $20.15

Capital Materials Employment Multiplier 31.4 31.4 31.4 31.4

Employment Gain (Capital Materials) 1,429 1,372 1,048 633

Installation Cost (15% of total cost) $8.03 $7.71 $5.89 $3.56

Installation Cost Employment Multiplier 21.5 21.5 21.5 21.5

Employment Gain (Installation) 173 166 127 76

Total O&M Cost $117.74 $111.79 $85.31 $50.59

Labor Share (33.3%) $39.25 $37.26 $28.44 $16.86

Labor Employment Multiplier 83.3 83.3 83.3 83.3

Employment Gain (Labor) 3,269 3,104 2,369 1,405

Materials Share (33.3%) $39.25 $37.26 $28.44 $16.86

Materials Employment Multiplier 23.7 23.7 23.7 23.7

Employment Gain (Materials) 930 883 674 400

Energy Share (33.3%) $39.25 $37.26 $28.44 $16.86

Energy Employment Multiplier 15.8 15.8 15.8 15.8

Employment Gain (Energy) 620 589 449 266

Total Employment Gain 6,422 6,114 4,666 2,780

Source: Capital and O&M costs are from Final Technical Report; multipliers are from U.S. Dept. of Commerce, op cit.

7-16
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Table 7-7

Net Annual National-Level Employment Losses (FTEs) Based on Output

Total Annual Net Loss (Gain) in NationalLosses Based on Total Annual Level Employment Based

Option Output Gain on Output

No Cutoff 14,322 6,422 7,900

1MM/255K 13,652 6,114 7,538

3MM/120K 10,461 4,666 5,795

5MM/255K 6,169 2,780 3,389

Source: From Table 7-5, Section 308 Survey data, and closure and failure results from EPA, 1999, Facility and

firm financial model.
17Ibid.

18 Output is revenues; production loss is equated with output using price (price times production

equals revenues). Output and production are used interchangeably here since they can be equated with

each other.

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National-level (civilian) employment in 1993 was 120.3 million persons.17 This loss is thus at most 0.01

percent of total national employment. EPA therefore believes that the options considered would have had a

negligible impact on national-level employment.

7.3 DIRECT LONGER-TERM EMPLOYMENT IMPACTS IN THE INDUSTRIAL

LAUNDRIES INDUSTRY

7.3.1 Methodology for Estimating Longer-Term Impacts on Employment

There are two ways to compute net direct employment losses in the industrial laundries industry. 

The first way is to calculate employment losses based on closures and failures, which was discussed in

Section 7.1 and the second way is to compute losses based on production losses. 

As noted above, employment losses associated with postcompliance facility closures or failures

could overstate or understate production- or output-driven losses18 in the industrial laundries industry, since

closures and failures are different measures than output. Although impacts such as closures or failures are

somewhat correlated with output losses, since higher compliance costs tend to increase such impacts, they

are not exactly correlated and will not produce the same estimate of employment impacts (other than by

chance). Furthermore, the analysis in Section 7.1 did not account for employment gains. 

EPA thus conducts two analyses that both incorporate employment gains, but which define

reasonable upper and lower bounds of output-driven employment losses within the industrial laundries

industry. The first analysis is based on output effects estimated assuming that direct output losses equal

compliance costs, as was done above in the national-level analysis. This output loss was used to generate

the national-level employment loss in Section 7.2, which includes indirect and induced losses. In this

section, the indirect and induced losses are removed from the estimate to derive the direct losses to the
19 EPA assumed previously in the national-level analysis that all operating labor is industrial

laundries employment because on a national level, it matters very little which industry is picking up the

gains in employment associated with operating pollution control equipment, since any of the industries that

might experience these gains have similar multipliers. It makes a substantial difference, however, in this

analysis whether the industrial laundries industry or another industry is credited with these gains.

20 This approach is consistent with how the I-O tables are created; price is held constant, and

(continued...)

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industry, and the analysis also uses gains in labor associated with operating pollution control equipment to

calculate net losses (or gains) in employment

To estimate direct losses only (losses only in the industrial laundries industry), EPA multiplies total

national-level employment losses (which are shown in Table 7-5) by the inverse of the national-level directeffect employment multiplier (1.7201). The direct-effect multiplier represents the change in total (direct,

indirect, and induced) employment for each unit change in direct employment; its inverse, therefore,

represents the direct employment change portion of total employment impacts. Direct losses can be

compared to total industry baseline employment to gauge the magnitude of employment impacts within the

industry.

As with the national-level analysis described above, employment losses in the industry might be

offset by employment gains, because it is likely industrial laundries will hire workers (or transfer workers

from productive operations) to operate the pollution control equipment installed. However, since industrial

laundries might opt to contract out the operation of pollution control equipment (and thus another industry

might be credited with some of the employment gains), EPA makes the conservative assumption that 50

percent of the labor component of the operating costs of compliance does not contribute to employment

gains within the industrial laundries industry.19 These gains can then be subtracted from the losses

estimated above to calculate a reasonable worst-case estimate of longer-term, production-driven, net

employment losses (or gains).

EPA’s second analysis is identical except that instead of assuming that the output loss equals the

compliance cost, the analysis uses the estimated production losses calculated using the market model valued

at the current price to reflect the reduction in output that would have affected employment in the industrial

laundries industry alone.20 To do this, EPA first calculates output loss using the loss of production
20(...continued)

output is allowed to vary.

7-20

calculated using the market model (see Appendix A, Table A-3) valued at current price. EPA then

calculates the output-driven employment loss at the national level (which includes direct, indirect, and

induced losses) in the same manner as was done above. Then, using the inverse of the national-level direct

effect employment multiplier, EPA calculates the direct employment component. The Agency then adjusts

for gains (as above) and calculates the reasonable best-case estimate of longer-term, production-driven, net

employment losses (or gains). The results of these two analyses can be considered reasonable bounding

estimates of production-driven employment impacts in the industry. 

7.3.2 Longer-Term Employment Impacts

To determine output-driven losses, EPA’s first analysis takes the national-level employment losses

(computed assuming direct output losses equal compliance costs) and calculates the direct employment

losses that would be experienced by the industrial laundries industry. As shown in Table 7-8, the direct

component of the losses calculated is estimated to range from 3,586 to 8,326 FTEs. The 3MM/120K

cutoff is associated with losses totaling 6,082 FTEs.

The losses computed do not account for gains in employment in the industrial laundries industry. 

Employment gains that would have been expected due to the need to operate the pollution control

equipment, as shown in Table 7-6, are estimated to be 1,405 to 3,269 FTEs. If 50 percent of these gains

are assumed to be employment gains in the industrial laundries industry itself, gains are estimated to range

from 702 to 1,635 FTEs, depending on cutoff (see Table 7-8). Thus the total net losses associated with

industrial laundries range from 2,884 to 6,692 FTEs, which is 2.2 percent to 5.2 percent of the estimated

128,000 FTEs employed in the industrial laundries industry (see Table 7-8). These net losses are greater

than the total losses associated with facility closures and firm failures. The 3MM/120K cutoff is

associated with a net loss of 4,897 FTEs. Thus over the longer term (under the assumptions of direct

output losses equaling compliance costs) EPA estimates that employment losses would not have been offset

substantially by gains and that some additional employment losses at nonclosing/nonfailing facilities and
Table 7-8

Direct Employment Losses in the Industrial Laundries Industry (FTEs) Based on Output Losses Assuming Zero Cost Passthrough

(Reasonable Worst-Case Analysis)

Total Percent of

Output-based Total Direct Total Direct Net Direct IL Industry

Option FTE Loss FTE Loss FTE Gain FTE Loss Employment

No Cutoff 14,322 8,326 1,635 6,692 5.15%

1MM/255K 13,652 7,937 1,552 6,385 4.91%

3MM/120K 10,461 6,082 1,184 4,897 3.77%

5MM/255K 6,169 3,586 702 2,884 2.22%

Source: Output-based FTE loss is from Table 7-4. The final-demand employment multiplier is from U.S. Dept. of Commerce, op cit.

Total FTE Gain is from Table 7-5 assuming that 50 percent of labor gains occur within the industrial laundries industry. Net Direct FTE Loss

uses the direct-effect employment multiplier, 1.7201, from U.S. Dept. of Commerce, op cit.

7-21
7-22

firms might have occurred (production-driven losses include losses from closures and failures). This is

considered a reasonable worst-case estimate of production-driven losses. 

EPA’s second analysis, considered a reasonable best-case analysis uses an alternative estimate of

direct output loss, which is calculated for the industrial laundries industry using production losses

estimated in Appendix A using the market model and assuming costs can be passed through to customers. 

This output loss is estimated to be $13.9 million to $32.0 million annually (1992 dollars) or 0.2 percent to

0.4 percent of the $7.5 billion in 1993 industrial laundries revenues (see Section Three). This output loss

would result in a nationwide employment loss of 1,157 to 2,663 FTEs, depending on cutoff (see Table 7-9).

These numbers, however, include the direct, indirect, and induced employment losses, as well as losses that

might be offset by gains within the industrial laundries industry. Given the total national-level loss of

employment calculated using this direct output loss estimate, the inverse of the direct-effect multiplier can

be used to calculate the direct employment losses, as was done above. Thus the direct component of the

losses calculated is estimated to range from 672 to 1,548 FTEs. The 3MM/120K cutoff is associated with

an estimated 1,135 FTEs lost.

As above, employment gains (assuming 50 percent of operating labor accrues to the industrial

laundries industry) are also used to calculate the net effect on employment. Gains are estimated to range

from 702 to 1,635 FTEs, depending on cutoff (see Table 7-9). Thus the total net gains associated with

industrial laundries range from 30 to 87 FTEs, which is 0.02 to 0.07 percent of the estimated 128,000

FTEs employed in the industrial laundries industry (see Table 7-9). Given the assumptions of EPA’s

market model and the uncertainties associated with these assumptions (see Appendix A), these results can

be interpreted as employment losses and gains possibly offsetting each other over time. Because gains

would not necessarily have occurred in the same geographic location nor at the same time as losses, these

gains might not prevent employment disruptions, even though over time, under the assumptions of this

analysis, no net loss of employment might occur. Furthermore, because employment losses would have

been expected from closures or closures plus failures, EPA concludes that some nonclosing facilities might

have experienced employment gains under the assumptions of this analysis. As discussed, this estimate is

considered to be a reasonable, longer-term, best-case estimate, and the two estimates combined are

considered reasonable bounding estimates of the longer-term, production-driven, net employment impacts

on the industrial laundries industry. The 3MM/120K cutoff can be considered to result in as few as no
Table 7-9

Direct Employment Losses in the Industrial Laundries Industry (FTEs) Based on Market Model Predictions of Production Losses

(Reasonable Best-Case Analysis)

Output Loss

Total Based on Final-Demand Percent of

Estimated Production Loss Output Loss Employment Total Total Direct Total Direct Net Direct IL Industry

Option Production Loss ($ million 1993) ($ million 1992) Multiplier FTE Loss FTE Loss FTE Gain FTE Loss Employment

No Cutoff 41,305,874.12 $33.41 $31.96 83.3 2,663 1,548 1,635 (87) -0.07%

1MM/255K 39,402,880.46 $31.87 $30.49 83.3 2,540 1,477 1,552 (75) -0.06%

3MM/120K 30,291,231.68 $24.50 $23.44 83.3 1,953 1,135 1,184 (49) -0.04%

5MM/255K 17,943,475.25 $14.51 $13.88 83.3 1,157 672 702 (30) -0.02%

Source: Output Loss in 1992 dollars is from Appendix A. The final-demand employment multiplier is from U.S. Dept. of Commerce, op cit. Total FTE Gain is from

Table 7-5 assuming that 50 percent of labor gains occur within the industrial laundries industry. Net Direct FTE Loss uses the direct-effect employment multiplier,

1.7201, from U.S. Dept. of Commerce, op cit.

7-23
21 The only employment gains assumed to offset losses at the regional level are those associated

with the labor required to operate pollution control systems. All other gains are assumed to be unlikely to

occur either in the same locations as losses or at the same time as losses (e.g., immediate hiring of laid-off

workers by other industrial laundry facilities in the area might not occur).

7-24

employment losses to as many as 4,897 jobs lost over the longer term, with the more immediate losses

totaling 2,261 jobs as a result of facility closures and firm failures.

7.4 REGIONAL EMPLOYMENT IMPACTS

7.4.1 Introduction

In the previous section, EPA estimated the employment impacts associated strictly with the

industrial laundries industry, subtracting out employment losses that were expected to be offset by gains for

operating pollution control equipment within the industry and calculating the net direct-effect only.21 These

market based effects would have been spread out throughout the economy and thus would have little to no

regional effect. 

The losses that might have some measurable effect at the community level are those associated

with closures and failures, because these losses tend to be larger and possibly could have been concentrated

in one location. EPA is concerned with the impacts of dislocation, even if other laundries in the region hire

the displaced workers from closing facilities (most likely after some delay); thus the analysis discussed

below uses the full loss of employment at closing and facilities to assess community-level impacts.

7.4.2 Regional-Level Impacts Methodology

The employment losses of concern in the regional-level analysis consist of employee layoffs

associated with the facility closures estimated in the facility closure analysis. Section 308 Survey data on

annual employment hours is used to calculate direct employment losses associated with facility closures

and failures that might have occurred under the options considered (the CP-IL option is discussed here) on

an FTE basis.
22 Http://www.census.gov/statab/USA96.

7-25

These losses are those direct employment losses associated with the CP-IL option that might have

had a significant impact on a region’s economy. The direct employment losses, however, are only a fraction

of the employment losses that might affect a region’s economy; as discussed earlier, there are indirect and

induced losses of employment also to consider. These indirect and induced losses can be estimated on a

regional basis using BEA multipliers for the affected state. Note, however, that because these multipliers

are derived for an entire state, they will most likely overstate the impacts within a smaller region (e.g.,

county or metropolitan statistical area [MSA]). The specific multiplier used is the direct-effect multiplier

for the state in which the surveyed closure occurs. 

The direct-effect multiplier shows the number of total jobs lost in all industries given one job lost in

the subject industry. For example, BEA tables show that one job lost in the industrial laundries industry in

the state of California will result in a total of 1.5119 jobs lost in all industries throughout the state. Thus

the calculation is:

Direct Employment Loss x Direct-Effect Multiplier = Total Direct, Indirect, and Induced Losses

The significance to the community of employment losses is measured by their impact on the

community’s overall level of employment. Data necessary to determine the community impact include the

community’s total labor force and employment rate. The community employment information used in this

analysis is from the Census Bureau’s web page,22 as estimated by the Bureau of Labor Statistics. For the

purposes of this analysis, the community is defined as the MSA (if urban) or county (if rural) in which the

facility is located and is assumed to represent the labor market area within which residents could

reasonably commute to work. An increase in the unemployment rate equal to or greater than 1 percent (e.g.,

from a 5 percent to a 6 percent unemployment rate) is considered significant. The change in the

unemployment rate is computed as:

Current Unemployment Rate-[(Current Unemployment + Postcompliance Employment Losses)/Labor

Force]
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Statistical weights complicate the analysis. Many closing facilities or failing firms that were

surveyed have fairly high weights. Because the sampling strata are not geographically based, it is highly

unlikely that any more than a few facilities represented by the closing facility would be located in the

survey facility’s county or be grouped in any way geographically. EPA assumes no more than three

facilities (where the facility weight exceeds 3) would close in the same county.

7.4.3 Results of the Regional-Level Community Impact Analysis

Table 7-10 presents the total number of closing facilities surveyed in the Section 308 Survey, their

weighted employment losses, and the state in which they are located, along with the appropriate directeffect multiplier for the state. The total number of direct and other losses are also presented. The change in

the unemployment rates ranges from less than 0.01 percent to 4.4 percent, depending on which facilities

close or fail and assuming that no more than 3 closing facilities represented by the facilities in this table are

located in the same county. The greatest change in the unemployment rate, 4.4 percent, is associated with

Facility 3, which closes only if no cutoff is considered. Under the 3MM/120K cutoff, the greatest change

in unemployment rate is estimated to be 0.5 percent. Thus EPA believes community-level employment

impacts under the 3MM/120K cutoff or above would have been negligible.
Table 7-10

Facility-by-Facility Employment Loss

Cutoffs Change in

Number of Facility Closes Survey Direct Regional Total Unemployment

Facility Employees Under Weight Losses State Multiplier Losses Rate*

Facility 1 24 No 6 138 DE 1.2856 177 0.14%

Facility 2 8 No 22 179 MI 1.3903 249 0.01%

Facility 3 20 No 6 115 TX 1.5361 177 4.40%

Facility 4 15 No 1 21 VA 1.4516 30 0.03%

Facility 5 14 No 6 81 NM 1.3731 111 1.73%

Facility 6 20 No 2 43 MA 1.4476 62 0.02%

Facility 7 32 No 1 42 KY 1.5031 63 0.73%

Facility 8 11 No 1 15 MN 1.4533 22 0.08%

Facility 9 16 No, 1MM 1 22 AR 1.4530 32 0.15%

Facility 10 29 No, 1MM 1 40 WI 1.3909 56 0.03%

Facility 11 (f) 75 No, 1MM 18 1,380 IN 1.4743 2,035 0.25%

Facility 12 (f) 20 No, 1MM 22 448 CA 1.5119 678 0.00%

Facility 13 (f) 15 No, 1MM 31 465 OH 1.4593 679 0.30%

Facility 14 28 No, 1MM 11 316 IN 1.4743 466 0.59%

Facility 15 14 No, 1MM 1 18 CT 1.4313 26 0.01%

Facility 16 18 No, 1MM 1 25 CO 1.4405 36 0.02%

Facility 17 34 No, 1MM, 3MM 1 44 IN 1.4743 65 0.18%

Facility 18 30 No, 1MM, 3MM 13 390 NY 1.3224 516 0.49%

Facility 19 60 No, 1MM, 3MM 26 1,540 TX 1.5361 2,366 0.04%

Facility 20 37 No, 1MM, 3MM 1 51 KS 1.4557 74 0.03%

Facility 21 116 All 1 131 MD 1.4092 185 0.04%

Facility 22 81 All 1 104 CA 1.5119 158 0.04%

(f) = facility that fails but does not close.

* Assuming a maximum of three facilities represented by the surveyed facility close or fail in the same county.

Source: Section 308 Survey data on numbers of FTEs at closing and failing facilities and firms. Closing facilities and failing firms are

identified using EPA, 1998. IL Facility and Firm Financial Model, Notice Version. Multiplier is from U.S. Department of Commerce, 1992.

Table A-2.4--Total Multipliers, by Industry Aggregation, for Output, Earnings and Employment. Regional Input-Output Modeling

System (RIMS II). Bureau of Economic Analysis, Regional Analysis Division.

7-27
8-1

SECTION EIGHT

OTHER IMPACTS

8.1 INTRODUCTION

In this section of the EA, EPA investigates other potential impacts associated with the regulatory

options considered for pretreatment standards, including impacts on markets, both foreign and domestic,

impacts on the customers of industrial laundries services (including the potential for customers to substitute

other products for industrial laundries services), impacts on the market for disposables of EPA’s decision

not to promulgate pretreatment standards, impacts on consolidation in the industrial laundries industry,

impacts on establishments other than industrial laundries that might launder industrial textile items from

offsite sources, impacts on inflation, and distributional impacts and environmental justice (which addresses

who would ultimately bear the costs and reap the benefits of a regulation). 

8.2 IMPACTS ON MARKETS

8.2.1 Impacts on Foreign Markets/Trade

Unlike a manufacturing industry, the industrial laundries market, with a few exceptions, is made up

of numerous small, local to regional market areas, with facilities each having a distinct radius of service,

limited by the cost of transportation. Thus impacts on foreign markets and trade are limited to areas of the

United States that are near foreign borders. Most industrial laundries are located in small urban to large

urban areas. This further limits the numbers of border localities likely to be served by industrial laundries,

since most border areas in the United States are not associated with major urban centers, with a few

exceptions such as the Seattle area, Southern California, the Detroit area, and El Paso, Texas. EPA thus

believes that the number of industrial laundries facing foreign competition is very small.

A requirement to meet pretreatment standards could have put some industrial laundry facilities at a

slight disadvantage relative to foreign facilities in certain border areas, but there are a number of factors
8-2

that likely would have mitigated this disadvantage. It is likely that the U.S. and non-U.S. markets do not

strongly overlap in border areas because the transaction costs of clearing customs can be high. Even in

areas, such as in, say, Southern California (San Diego/Tijuana), where border crossings are frequent,

pickup and delivery of items across international boundaries could involve substantial paperwork, searches,

and other delays. 

Additionally, EPA considered certain options (i.e., CP-IL under the 3MM/120K or 5MM/255K

cutoff) that were economically achievable and limited impacts on small firms. In so doing, these options

would have had acceptable impact on facilities and firms, even if they had not been able to pass costs

through to customers. Thus facilities near borders, had they been competing with foreign facilities, would

have been able to continue to price their services competitively with little risk of facing closure or failure as

a result. Thus EPA would not expect pretreatment standards to have resulted in major impacts on foreign

markets, given the limited involvement of this industry in foreign markets, given the relatively high

transaction costs of doing business in international markets, and given that EPA would have considered a

rule that would allow nearly all facilities and firms to absorb the cost of a rule, if necessary to maintain

competitiveness in a foreign market, without facing severe impacts.

8.2.2 Impacts on Domestic Markets

Had EPA promulgated pretreatment standards for the industrial laundries industry, it would have

included a cutoff excluding a large portion of small facilities. Had a rule been promulgated with the

selected 3MM/120K cutoff, a large portion of small firms might have gained a competitive advantage over

larger firms. At this cutoff, however, only a few major impacts were estimated to have occurred, thus most

larger firms would have been able to absorb all costs of compliance and remained price competitive with

smaller firms, without risking severe impacts. EPA views the need to mitigate impacts on small firms to be

greater than the need to prevent a competitive advantage to some (larger) firms. Furthermore, smaller firms

generally tend to be at somewhat of a disadvantage in comparison with larger firms even before any

regulatory impacts are considered (see for example the discussion in Section Three, where EPA identifies

various cost efficiencies that large, multifacility firms can achieve and that small firms often cannot). 
1

 1996. “Regional trend analysis shows pockets of potential.” Industrial Launderer. October, 

p. 85-86, 88-89.

2

 1996. “Job growth trends show industry’s pockets of potential.” Industrial Launderer.

November, p. 53-54, 56, 58.

3

 The industrial laundries customers discussed in Section Three were grouped according to SIC

code. The industry groupings used by the Internal Revenue Service in the Corporation Source Book of

8-3

Thus, an exclusion would have slightly reduced the relative competitive advantage of larger firms relative

to smaller ones.

8.3 IMPACTS ON INDUSTRIAL LAUNDRIES CUSTOMERS

8.3.1 Financial Profile of the Customer Base

As discussed in Section Three, a variety of customers purchase industrial laundries’ services for a

number of reasons. For some customers, particularly those in the manufacturing and automotive service

industries and print shops, industrially laundered textiles facilitate workplace cleanliness; industrial

laundries provide and launder protective clothing and employee uniforms, work materials (e.g., shop and

print towels), and items geared towards soil minimization and removal (e.g., mats and mops). In addition,

customers purchase industrial laundering services in the interest of enhancing employee appearance and

corporate image and identity; especially in the service industries, uniform and mat rental programs promote

company cohesion and brand recognition.

Because of the many different types of companies that use industrial laundries, it is not possible to

develop a single financial profile of the industrial laundries customer base. Overall, the health of industrial

laundries’ customers is good. The service sector, in particular, has experienced a fair amount of growth in

recent years. Despite some regional manufacturing job losses, moreover, the industrial laundries industry

remains optimistic about prospects for future business from traditional, blue-collar customers.1,2

Table 8-1 contains average financial statistics for the 14 industry groups that correspond roughly

to 14 of the 15 major industrial laundries customer groups discussed in Section Three.3 The figures in the
Table 8-1

Average Financial Statistics for Active Corportions in 14 Industrial Laundries Customer Industries (1993 $)*

(in thousands)

Receipts Deductions Average

ESIC Average Avg. Total Avg. Business Avg. Total Avg. "Other" Pct. "Other" Receipts minus

Group** Industry Title Assets Receipts Receipts Deductions Deductions*** Deductions*** Deductions

39 Automotive Dealers & Service Stations $1,350 $5,687 $5,593 $5,631 $172 3.06% $56

7500 Auto Repair & Services $540 $798 $760 $783 $101 12.86% $15

42 Eating and Drinking Places $472 $869 $836 $850 $128 15.10% $19

38 Food Stores $1,439 $5,057 $4,971 $4,983 $240 4.82% $74

08 Special Trade Contractors $314 $976 $967 $955 $77 8.05% $21

5089 Wholesale Trade: Other Durable Goods $1,331 $3,039 $2,994 $2,990 $200 6.69% $50

24 Machinery, except Electrical $9,769 $11,513 $10,574 $11,174 $1,197 10.71% $338

16 Printing and Publishing $3,478 $3,346 $3,181 $3,128 $457 14.59% $218

54 Business Services $703 $985 $930 $949 $173 18.19% $36

09 Food and Kindred Products $25,822 $26,926 $25,723 $25,765 $2,476 9.61% $1,161

23 Fabricated Metal Products $3,101 $4,541 $4,436 $4,309 $304 7.06% $232

8200 Educational Services $321 $643 $625 $625 $145 23.15% $18

5190 Wholesale Trade: Misc. Nondurable Goods $1,065 $2,963 $2,922 $2,910 $179 6.16% $53

43 Miscellaneous Retail Stores $625 $1,481 $1,452 $1,454 $114 7.86% $27

* Numbers from 1994 tax year, deflated to 1993 dollars using the Producer Price Index for Finished Goods.

** The Internal Revenue Services groups industries according to their primary Enterprise Standard Industrial Classification (ESIC) code. ESIC codes correspond closely with, but do 

 not match, SIC codes.

*** Does not include cost of goods, compensation of officers, salaries, repairs, bad debts, rent, taxes, interest, contributions or gifts, amortization, depreciation, depletion, advertising,

 pension, employee benefits, and net loss (noncapital assets). Expenses for industrial laundering services would be in this "other" category.

Source: U.S. Internal Revenue Service, 1994. "Balance sheet, income statement, tax and selected items by major and minor industries, size of total assets." Tax Year 1994 Source Book, 

 Statistics of Income: Active Corporation Income Tax Returns, July 1994-June 1995. Washington, DC: U. S. Internal Revenue Sevice.

8-4
Statistics of Income are based on the Enterprise Standard Industrial Classification (ESIC), which

corresponds closely with, but does not match, the SIC. An ESIC group corresponding to SIC 80 (Health

Services) could not be found, so only 14 industry groups are mentioned in this section.

4

 “Other deductions” are expenses other than the cost of goods, compensation of officers, salaries

and wages, repairs, bad debts, rent paid on business property, taxes paid, interest paid, contributions or

gifts, amortization, depreciation, depletion, advertising, pension and profit sharing, employee benefit

programs, and the net loss associated with noncapital assets.

8-5

table are estimated based on corporate income tax return data provided by the Internal Revenue Service

(IRS). Since such data does not reflect the financial situation at S corporations and sole proprietorships, the

average costs and revenues calculated herein may be overstated, and total costs and revenues are

understated.

8.3.2 Impacts of Price Increases on Customers

The costs of industrial laundering, like the costs of employee wages and benefits, raw materials,

telephone and utilities, legal and accounting services, etc., are expenses incurred in the production of goods

and services at customer companies. For the most part, however, industrial laundering does not appear to

represent a substantial portion of overall operating costs, relative to other costs. The IRS data cost category

in which costs for industrial laundering is captured is the “other deductions” category.4 According to IRS

data, “other deductions” constitute between 3 and 23 percent of total annual expenses at 14 of the major

customer industries for industrial laundries (see Table 8-1). Given that “other deductions” includes a

number of other miscellaneous costs aside from those for industrial laundering, the actual percentage of

total annual costs devoted to textile cleaning and rental is estimated to be quite small on average.

EPA does not expect the cost of pretreatment standards would have substantially affected

industrial laundries’ customer industries. Relative to other operating costs, the cost of industrial laundering

services is quite small. As such, an increase in costs is not likely to have a major impact on the bottom line

at customer industries. The following analysis in Section 8.3.2.1 provides a worst-case estimate and a

reasonable estimate of impacts among customers, and Section 8.3.2.2 discusses the potential for impacts on

competition with substitutes had EPA promulgated pretreatment standards.
5

EPA is unsure of how the trade association calculated increases of $13,000 per year based on a

0.4 percent increase in price predicted in the EA for the proposal (see PECON-6, Tracking No. 1516 in the

Comment Response Document). EPA suspects that the commenter calculated the impact by setting 0.4

percent to 0.4 and multiplying typical current costs, rather than setting 0.4 percent to 0.004. A cost

increase of $13,000 per year triggered by a price increase of 0.4 percent would lead to an estimated

baseline cost of shop towel cleaning at a medium-size firm of $3.25 million per year. A price increase of

40 percent would result in a cost increase of $13,000 per year based on a baseline laundering cost of

$32,500, or approximately the baseline laundering cost that EPA has estimated above.

8-6

8.3.2.1 Increases in Production Costs

The potential for increased production costs among customer industries appears to be of the most

concern to the printing industry, based on comments received (see Comment Response Document, PECON6 Tracking Nos. 1514-1521). According to the printing industry’s trade association, a typical medium-size

printing firm would use 100,000 towels per year. If it is assumed that a large majority of the cost of

pretreatment standards would have been passed through to users of shop towels/rags, a price increase of 10

percent might reflect this assumption. This 10 percent price increase would mean that the average cost of

shop towels would rise from $1.60 per pound (cited in the Comment Response Document, PECON-9A,

Tracking No. 1576, which was submitted by the industrial laundries trade associations) to $1.76 per

pound. Under this assumption, $76.8 million of compliance costs (or 85 percent of the entire cost of the

CP-IL option under the 3MM/120K cutoff) would have been passed through on 480 million pounds of shop

towels (480 million pounds of shop towels were processed by the industry in 1993 according to the Section

308 Survey). If there are 5 shop towels per pound (a higher ratio would lead to lower estimates of impact),

a medium-size firm would be using 20,000 pounds per year of shop towels (based on a usage rate of

100,000 shop towels per year). The baseline cost of this item is estimated at $32,000 per year per year at

$1.60 per pound. Postcompliance, this cost (at $1.76 per pound) would be $35,200, or an increase of

$3,200.5

 If the average “other deduction” shown in Table 8-1 for the printing and publishing industry

corresponds reasonably well to the “other deduction” amounts typical for a medium-size firm, this increase

of $3,200 per year would amount to 0.7 percent of this category of deductions ($457,000 on average for

the industry), or 0.1 percent of total deductions ($3.128 million on average). 

EPA believes that a more realistic cost increase, however, likely would have been in hundreds of

dollars rather than in thousands of dollars. The market model, discussed in Appendix A, is not sufficiently

detailed to predict cost increases on individual product lines, so the precise cost passthrough on shop towels
6

1997. “Wiper market watch: The view from EPA.” Industrial Launderer. February, p. 61-63.

8-7

cannot be calculated. However, if it is assumed that costs can be passed through only on 5 billion pounds

of laundry (excluding linens and other items not considered for regulation) and that the 32 percent cost

passthrough applies (as calculated in Appendix A), $41 million would be passed through under the CP-IL

option with no cutoff, and the price per pound increase would be about $0.01. At a facility using 20,000

pounds of shop towels per year, the cost increase at this medium-size printer would amount to $200 (a 0.6

percent increase over baseline laundry costs).

EPA believes the estimated worst-case impact on a medium-size firm (in terms of the percent

increase in “other deductions”) is also a worst-case scenario for small firms (since numbers of towels

would drop proportionately with size of firm and costs of production) and would also be a worst-case

scenario for other customers of industrial laundries. This result would be a worst-case result for other

customers, since industrial laundries probably could not have passed through such a large portion of costs,

and price increases would probably have been spread over more pounds of industrial laundry. Thus price

increases on any one type of laundry probably would have been much less than that estimated for this

analysis and impacts on customers would more likely resemble those estimated in the second analysis

discussed above.

8.3.2.2 Potentials for Substitution

EPA believes pretreatment standards also would have been unlikely to cause customer industries to

switch from industrially laundered textiles to substitute products. As discussed in Section 3.2.2.2 and here,

among current customers of industrial laundries, few perfect (or, in some cases, even close) substitutes to

the products and services provided by industrial laundries currently exist. Reusable textiles are typically

more durable than disposables, so customers for industrially laundered items such as industrial uniforms,

mats, and mops, which are subject to heavy use, do not have many disposable alternatives. With respect to

wipers and shop towels, moreover, the quality of the single-use shop towels now on the market might not be

high enough for use by the printing industry because printers require towels that are both durable and

generate little lint.6

 As the printing industry trade association notes in comments on the proposal (PECON-
7

 Mullen, Jocelyn, and Carl Lehrburger, 1991. A Solid Waste and Laundering Assessment of

Selected Reusable and Disposable Products. Washington, DC: Textile Rental Services Association of

America and IIL.

8

TRSA, 1999. 1999 Strategic Analysis of the Textile Rental Industry. http://www.trsa.org

/public/trsa_mag/sapub.htm.

9

 TRSA, 1999. Op cit.

8-8

7, Tracking No. 1552 see the Comment Response Document), if reusables are no longer available in certain

market areas “the printer will be forced to either use disposable towels or launder on-site, neither of which

is an attractive or cost effective option.” Customers in the automotive industry might place more emphasis

on price than quality in the selection of towels, but in industrial settings it has been found to be more

economical to use cloth towels than paper wipers for all but a dirty task that would require only one paper

wiper.7

 Furthermore, the possibility that a disposable wiper might be considered hazardous waste under

RCRA could further deter the substitution of disposables for industrial laundry services. 

Another possible substitute for industrial laundry services is onsite laundries, which EPA would

have excluded from coverage by pretreatment standards for industrial laundries. However, a number of

major disincentives would exist. As the industry itself notes, industrial laundries currently are encountering

substantial success converting OPLs to rental customers.8

 “These converts are being won with the

argument that professional laundering in a textile rental plant meets their needs in a cost-effective and

environmentally responsible manner with an additional advantage of worker safety.”9

 Many of these

converts are likely to have fully depreciated their laundry equipment, but, apparently, the industrial

laundries industry has been proving that their current operations are more efficient than many OPLs, even

if O&M costs alone are considered. As EPA noted in its response to PECON-13, Tracking No. 1598, in

the Comment Response Document, economies of scale at a facility level are not great, except that it is

likely that very small facilities (particularly those processing under about 1 million pounds of laundry per

year) are not prevalent, and are probably not very cost-effective relative to larger facilities (in the range of

3 million to 7 million pounds per year of laundry processed). Because OPLs are likely to be smaller than

many of the smallest industrial laundries, it is not a surprise that the industrial laundries industry is making

substantial inroads into this market area.
10 TRSA, 1999. Op cit.

8-9

Furthermore, establishing an onsite laundry would involve capital investment, and given that EPA

believes that for most types of laundry, the estimated average postcompliance price increase would most

likely not be large, it is likely that the “payback” period for an onsite laundry might be too long to interest

most customers. Furthermore, an increase in pollutant loads at a facility that installs an onsite laundry may

necessitate additional changes in the facility’s NPDES permit if it is a direct discharger or its pretreatment

permit issued by the local POTW if it is an indirect discharger. A POTW might even initiate local limits

(where none were previously required to be met) or might impose a surcharge. Thus EPA believes,

although a rule might have slowed conversions of OPLs to rental customers at the margin, a rule would

have probably not have encouraged current customers to switch to OPLs.

Other possible substitutes for industrial laundry services would be for customers to drop industrial

laundry services and, for example, require employees to purchase and launder their own clothing, or to

reduce the frequency of pickup and laundering of certain items. Customers who use uniform rentals and

related services for image reasons rather than strictly for cleanliness might be the likeliest to choose the

former route if faced by higher prices, since image reasons for using industrial laundering services might

not be as compelling and might more likely to be targeted for cost-cutting measures than a need to remove

stains that cannot be easily cleaned. However, home laundered items, even though sufficiently cleaned

might suffer variability in the quality of the final appearance of the article (e.g., poorly ironed), making this

route unacceptable to a firm looking for a proper image. Thus home laundering is also not a perfect

substitute for industrial laundry services. Items such as mats might be targeted for reduction in frequency

of pickup and laundering. Even this substitution is not likely to result in much of a move away from

industrial laundries services as is reflected in EPA’s results from the market model, presented in Appendix

A, which indicate that production in the industrial laundries industry might be reduced about 0.2 to 0.5

percent. These reductions are associated with the lower demand for laundry services at the higher,

postcompliance price and would represent the move by some customers towards some of the substitutes

discussed above. This small percentage reduction in industrial laundries production might be unobservable,

however, in the overall growth of the industry, which is currently averaging better than 6 percent per year.10
8-10

Industry has argued that customers would be very sensitive to a change in price, but there really

are two price sensitivities being discussed. EPA agrees that customers are very price sensitive in

comparing industrial laundries services among industrial laundries firms, but in many cases (such as the

printing industry), are less price sensitive when comparing industrial laundries services to substitutes. 

Because the industrial laundries industry is very competitive, customers would be generally indifferent to a

choice between industrial laundries services provided by one firm and those provided by any other firm. 

However, substitutes for industrial laundries services such as OPLs, home laundering, and disposables are

not perfect substitutes for industrial laundries services, as discussed above. The fact that substitutes are

not perfect for some key customers is clearly stated by the printing industry trade association in the quote

cited above. Thus EPA still believes that many customers would not have been very sensitive to small

price increases, particularly where substitutes are least likely to be perceived as equivalent to industrial

laundries services (e.g., the printing industry and heavy soil industries for whom OPLs or home laundering

do not provide adequate soil removal) or where the industrial laundries service makes up a very small

percentage of operating costs (such as at a business that uses only a personalized mat rental service). 

EPA does concede that some customers would have been more sensitive to small price increases,

but the ability of the market to be disaggregated among various product lines, services, and perhaps even

groups of customers makes it likely that price increases would have fallen on those items whose demand is

the most inelastic. As noted in the Comment Response Document, PECON-9A, Tracking Nos. 1579 and

1584, the industry recognizes a vast array of products and services as distinct markets, thus the industry

would have been able to maximize cost passthrough while minimizing impacts on production (and thus

substitution) by the ability to distinguish these different markets.

8.4 IMPACTS OF A DECISION NOT TO REGULATE THE INDUSTRIAL LAUNDRIES

INDUSTRY UNDER PRETREATMENT STANDARDS ON THE MARKET FOR

DISPOSABLES

EPA’s decision not to promulgate pretreatment standards for the industrial laundries industry will

not adversely affect the disposables industry. First, this decision merely perpetuates the status quo. The

disposables industry will be no worse off than at present. Second, even if the effect of this decision is

compared to what might have been had EPA promulgated pretreatment standards, EPA’s analyses show
8-11

that no major changes in the market for reusables vs. disposables would have occurred. The industrial

laundries industry has indicated, in comments to the rule, that it is able distinguish a wide variety markets

based on regions, products, and customers (Comment Response Document, PECON-9A, Tracking Nos.

1579 and 1584) and thus would have been able to practice finely tuned price discrimination. Thus the

industry would have gauged the sensitivity of customers to changes in prices that might lead to customers

converting to disposables and would have avoided raising prices for particular products or customers or in

certain regions to a level that might encourage this conversion. Third, the disposables industry itself

concurs that had EPA promulgated a rule, there would have been no marked changes in the market for

disposables vs. reusables: “we do not expect [pretreatment standards] to significantly impact demand for

our members’ products” (Comment Response Document, PECON-7, Tracking No. 1531).

8.5 IMPACTS ON CONSOLIDATION IN THE INDUSTRIAL LAUNDRIES INDUSTRY

The industrial laundries industry, by all accounts, has been and is in a moderately to rapidly

consolidating phase, as have many firms in other industries in the U.S. and global economies of the 1990s. 

EPA believes that pretreatment standards for the industrial laundries industry would not have had a major

effect on consolidation on the industry, primarily because of impacts on demand for facilities. Although a

rule might have had an effect on the “supply” of firms and facilities offered for sale, it would also have had

an effect on demand for those firms and facilities, since multifacility firms would be engaged in purchasing

and installing pollution control equipment and generally would, at least for a while, have less capital

available for acquisitions. Appendix D addresses the issue of consolidation in more detail, showing that at

current market prices for facilities in this industry (which, according to comments from industry--see the

Comment Response Document, PECON-2C, Tracking No. 1481--is set on the basis of revenues, not cash

flow), over 70 percent of facilities in the industry might currently consider selling to maximize return on

investment.
11U.S. Government Printing Office, 1997. Economic Report of the President, February 1997. 

Washington, DC: U.S. Government Printing Office.

8-12

8.6 IMPACTS ON OTHER ESTABLISHMENTS THAT MIGHT LAUNDER INDUSTRIAL

TEXTILE ITEMS

It is possible that pretreatment standards, in theory, could have had an impact on hotels, hospitals,

prisons, and other establishments (e.g., manufacturing facilities) that could potentially launder industrial

textile items from offsite sources. As developed by EPA, any such standards would have required that any

wastewater generated from the laundering of industrial textile items from offsite sources by such

establishments might be required to be treated before discharge. EPA believes that any impacts to such

establishments from pretreatment standards would have been minimal. For more details, see the discussion

in the EA for the proposal.

8.7 IMPACTS ON INFLATION

If all costs under a 3MM/120K cutoff scenario were to have been passed through to the ultimate

consumer (including costs passed through by customers of industrial laundries), the entire $90.8 million per

year cost of pretreatment standards (CP-IL option costs) would fall directly on consumers. This cost as a

portion of GDP is, however, minuscule: 0.001 percent of 1993 GDP.11 Therefore, even under an

 assumption of a 100 percent cost passthrough to ultimate consumers, pretreatment standards would have

been highly unlikely to have had any noticeable effect on inflation. 
8-13

8.8 DISTRIBUTIONAL IMPACTS AND ENVIRONMENTAL JUSTICE

Because any potential price increases in the services offered by the industrial laundries industry

might have affected a wide segment of the manufacturing, service, and trade industries (see Section Three),

the impacts on ultimate consumers will be felt primarily to the extent that these potential price increases

affect inflation. The groups most affected by the potential distributional impacts of pretreatment standards 

therefore would have been those most affected by general inflation: the elderly and others on fixed income

and those in the lowest socioeconomic strata, including children. As noted above, however, the effect on

inflation would have been negligible. Thus the impacts to these more vulnerable groups would also be

negligible.

The benefits of pretreatment standards, had EPA promulgated a rule, would have been very small,

and thus little to no measurable benefits would have accrued to any disadvantaged groups. Although EPA

has decided not to promulgate pretreatment standards for the industrial laundries industry, the Agency

believes that any environmental inequities that currently exist due to discharge of pollutants by industrial

laundries are very small. Additionally, the Agency expects that many of the pollutants that remain

uncontrolled because of EPA’s decision not to promulgate pretreatment standards will be reduced through

industry’s voluntary program and through a possible rule governing reusable and disposable shop towels

that is expected to be proposed by the Office of Solid Waste under the Resource Conservation and

Recovery Act (RCRA). EPA believes industry’s voluntary program and a potential shop towel rule would

eliminate any possible very small inequities that might remain.
1

 See U.S. EPA, 1997. Interim Guidance for Implementing the Small Business Regulatory

Enforcement Fairness Act and Related Provisions of the Regulatory Flexibility Act. February 5.

9-1

SECTION NINE

SMALL BUSINESS ANALYSIS

9.1 INTRODUCTION

This section examines the projected effects of the costs from incremental pollution control on small

entities. EPA acknowledges that small entities have limited resources and is aware of its responsibility for

avoiding burdening such entities unnecessarily. Although EPA has decided not to promulgate pretreatment

standards for the industrial laundries point source category, EPA presents information that could have been

used to prepare a final regulatory flexibility analysis (FRFA).1 Despite the fact that EPA’s decision not to

promulgate the rule means that a formal regulatory flexibility analysis performed in accordance with the

Regulatory Flexibility Act (RFA), as amended by the Small Business Regulatory Enforcement Fairness Act

of 1996 (SBREFA), is not required, this section generally includes much of the content typical of a

regulatory flexibility analysis to ensure that all aspects of a small business analysis are addressed in

Section 9.2, below.

9.2 SMALL BUSINESS ANALYSIS COMPONENTS

To analyze small business impacts, EPA has undertaken all components of an analysis typically

performed to meet Section 603 of the RFA, which requires that a FRFA must contain the following:

# State the need for and objectives of the rule.

# Summarize the significant issues raised by public comments on the initial regulatory

flexibility analysis (IRFA) and the Agency’s assessment of those issues and describe any

changes in the rule resulting from public comment.

# Describe the steps the Agency has used to minimize the significant economic impact on

small entities consistent with the stated objectives of the applicable statutes, including a
9-2

statement of the factual, policy, and legal reasons for selecting the alternative adopted in

the final rule and why each one of the other significant regulatory alternatives to the rule

considered by the Agency which affect the impact on small entities was rejected.

# Describe/estimate the number of small entities to which the rule will apply or explain why

no such estimate is available.

# Describe the projected reporting, recordkeeping, and other compliance requirements of the

rule, including an estimate of the classes of small entities that will be subject to the

requirements of the rule.

9.2.1 Need for and Objectives of the Rule

The rule was proposed under the authority of Sections 301, 304, 306, 307, 308, and 501 of the

Clean Water Act, 33 U.S.C. Sections 1311, 1314, 1316, 1317, 1318, and 1361. Under these sections, EPA

sets standards for the control of discharge of pollutants for the Industrial Laundries Industry Point Source

Category. The decision to regulate or not to regulate was considered pursuant to a Consent Decree entered

in NRDC et al. v. Reilly (D.D.C. No. 89-2980, January 31, 1992), and the decision is consistent with

EPA’s latest Effluent Guidelines Plan under Section 304(m) of the CWA (see 61 FR 52582, October 7,

1996). 

The objective of the CWA is to “restore and maintain the chemical, physical, and biological

integrity of the Nation’s waters.” To assist in achieving this objective, EPA issues effluent limitations

guidelines, pretreatment standards, and new source performance standards for industrial dischargers.

Sections 304(g) and 307(b) authorize EPA to issue PSES and PSNS for all pollutants. In this case,

however, for a variety of reasons, which are discussed in the preamble to the Final Action, EPA has

decided not to promulgate pretreatment standards for the industrial laundries point source category.

9.2.2 Significant Issues Raised by Public Comment

The significant issues raised by public comment that specifically address small business concerns

are as follows: 
9-3

# EPA ignored SBA’s definition of small business. EPA adhered to SBA’s definition of

small in evaluating the industry. The commenter is confusing SBA’s requirements to

evaluate small entities based on its definition (or a definition it agrees to) of small business

and the RFA’s requirements to consider how to mitigate impacts on small entities if such

impacts can be mitigated under the constraints imposed by the Clean Water Act. EPA is

not required to craft an exclusion from a rule based on entities defined as small under SBA

definitions; that is, EPA is not required to exclude all firms defined as small by SBA from

regulation. EPA’s development of an exclusion at proposal took into account what firms

and facilities would be the most highly affected by a rule, all of which were small, but

these were only a fraction of all small business. EPA continued to investigate cutoffs for

small business, but even though the Agency believed it could construct an economically

achievable rule that would mitigate impacts on some small firms, the Agency chose not to

promulgate a pretreatment standard for the industrial laundries point source category (for

reasons other than economic achievability and impacts on small business).

# Economic indicators other than closures and failures are better indicators of impact. 

EPA disagrees. First, EPA used the standard measure of impact defined in its guidance on

undertaking analyses under SBREFA. This impact measure is the revenue test, the results

of which can be seen in the EA for the proposal. This guidance and EPA’s guidance for

performing regulatory flexibility analyses state that other measures might be used in a

regulatory flexibility analysis, including closures and bankruptcies. The comment fails to

provide EPA with the other measures believed to be better indicators. EPA has continued

to use facility closures and firm failures as impact measures for small business analysis

purposes.

# A 10 percent bankruptcy rate is not acceptable. EPA has been concerned with the

number of bankruptcies estimated to occur as a result of the options considered. Both

closures and bankruptcies were considered when EPA crafted its small production cutoffs

for an exclusion to a pretreatment standard during the final decisionmaking process as

presented in Section Six of this report. EPA’s selection of the 3MM/120K cutoff would

have resulted in a rule that would have eliminated the likelihood of firm failures among all

firms.

# The impact of a rule would be more severe than EPA has predicted (analyses are in

error), and impacts will disproportionately affect small businesses. EPA, as described

in detail in the Comment Response document, believes that the analyses as now undertaken

do not underestimate impacts. EPA’s selection of the 3MM/120K cutoff would have

resulted in a rule that would have been economically achievable and that would have

minimized impacts on small firms, but decided instead not to promulgate pretreatment

standards for the industrial laundries point source category.

# Impacts on consolidation need to be addressed. EPA evaluated the effects of the rule on

consolidation and found that a rule would not have had much impact on consolidation. 

First, the pressures to consolidate in this industry are already very strong. Second, a rule

would have affected both supply and demand of laundry facilities. More facilities might

have been interested in being purchased, but fewer multifacility firms would have been

interested in acquiring facilities, at least for a while, since capital for acquisitions most
9-4

likely would have been tied up in purchasing and installing pollution control equipment. 

The net effect on consolidation might have even been to reduce consolidations temporarily.

The effect of a rule on consolidation is discussed in more detail in Section Eight and

Appendix D of this report.

# Higher cutoffs for an exclusion are needed. EPA investigated higher cutoffs than that

selected for proposal, as shown in Sections Five, Six, and Seven of this report. As these

analyses show, EPA’s selected cutoff, which was higher than the cutoff selected at

proposal, resulted in impacts that are less than those which would have occurred under the

lower cutoff selected at proposal (measured as closures plus failures) EPA also examined

the pollutant load reductions, or lack of reductions, that would have occurred at these

cutoffs. 

# EPA should not use the results of its impact analyses to devise cutoffs. EPA did

exactly what it should have done as regulatory flexibility guidance suggests for

determining ways to mitigate impacts--identify the impacts, then use those impacts, if

falling on small businesses, to define a highly affected group to assess mitigation

measures. EPA used the best tools it had available to define this highly affected group. If

the Agency could not use the method it did use to define cutoffs (both at proposal and in

the final decisionmaking process), EPA might not have had any method at all by which to

define cutoffs that could mitigate impacts. EPA continued to use closures and failures to

identify impacts and define cutoffs in its final decisionmaking process.

# Impacts due to shifts to substitutes need to be addressed. EPA determined that shifts to

substitutes would have been small had EPA promulgated a rule and did discuss this in

Section Eight of the EA for the proposal. The issue is again discussed in Section Eight of

this report.

# EPA did not meet the requirements of an IRFA. EPA disagrees. All IRFA

requirements were discussed in the EA for the proposal.

9.2.3 Steps Used To Minimize Impacts

EPA investigated two methods for minimizing impacts. The first method was to define an

exclusion based on size (amount of laundry processed each year), which is presented in detail in earlier

sections of this report. The second method was to consider a no-regulation option. The primary purpose of

EPA’s decision not to regulate was not associated with mitigating impacts on small entities, because EPA

believed the Agency could have constructed a rule, using either the 3MM/120K or 5MM/255K cutoff, that

mitigated impacts on small firms. EPA’s decision not to regulate, however, clearly avoids any impacts on

small entities from pretreatment standards. The complete rationale for EPA’s decision to reject the
9-5

regulatory options and to decide not to promulgate pretreatment standards for the industrial laundries point

source category is presented in the preamble to the Final Action.

9.2.4 Estimated Number of Small Business Entities to Which the Regulation Would Have

Applied

The section begins with a discussion of the definition of “small business” for the purpose of

undertaking a small business analysis, then summarizes the data available for the estimated number of

small business entities and the methodology used in calculating that estimate. 

9.2.4.1 Definition

The RFA and SBREFA both define “small business” as having the same meaning as the term

“small business concern” under Section 3 of the Small Business Act (unless an alternative definition has

been approved). The latter defines a small business at the business entity or company level, not the facility

level. The analysis, then, needs to determine whether an industrial laundry facility is owned by a small

business entity, not whether the facility itself may be considered “small.”

The definition of “small” generally is defined by standards for each SIC code as set by the Small

Business Administration (SBA). As discussed in the industry profile (see Section Three), the industrial

laundries industry is covered by a number of SIC codes. The predominant SIC codes also are discussed in

Section Three. In SIC code 7218, SBA defines “small” as firms with revenues of less than $10 million per

year; for SIC 7211 and 7213, “small” is defined as less than $10.5 million per year. Less than $10.5

million per year in revenues is the definition EPA is using for this analysis.

9.2.4.2 Estimated Number of Small Business Entities

EPA sent the Section 308 Survey questionnaire to a sample of industrial laundry facilities. The

sampling frame for the questionnaire was stratified on the basis of facility characteristics, including facility
9-6

revenues (see Section Two and EPA’s Final Development Document). Therefore, it is possible to estimate

statistically the number of facilities, but the same statistical approach cannot be used to estimate the

number of companies or business entities, other than single-facility firms. For single-facility firms, the

number of business entities is the statistically weighted total number of single-facility firms. For

multifacility firms, EPA used a different approach, which was described in detail in Section Six. Using

both sets of estimates, EPA calculates that there are 837 total small industrial laundry firms out of 903

firms (92.7 percent). These 837 firms are estimated to own 900 facilities.

When baseline failures/closures are removed from the analysis (see Section 5.1.2 of this EA for a

discussion of how EPA establishes the baseline against which to measure impacts), EPA estimates that

there are 675 single-facility firms, of which 659 (97.6 percent) are defined as small (see EPA’s rationale on

removing baseline closure and failures from the analyses in Sections Five and Six of this EA). EPA also

estimates that there are 70 multifacility firms, only 25 of which (35.7 percent) are defined as small. Thus,

EPA estimates that out of the 745 total in-scope industrial laundry firms in the postcompliance analysis,

684 (91.8 percent) are defined as small. 

Not all of these firms would have been affected by pretreatment standards, however, had EPA

promulgated a rule. EPA investigated several size cutoffs for excluding groups of small facilities for

excluding from coverage by a rule. The three cutoffs that EPA investigated included industrial laundry

facilities that process fewer than 1 million water-washed pounds of laundry per year and fewer than

255,000 pounds of shop towels and printer towels/rags per year (the 1MM/255K cutoff group), a group

that included the 1MM/255K cutoff group and added facilities that process fewer than 3 million waterwashed pounds of laundry per year and fewer than 120,000 pounds of shop towels and printer towels/rags

per year (the 3MM/120K cutoff), and a group of facilities that process fewer than 5 million water-washed

pounds of laundry per year and fewer than 255,000 pounds of shop towels and printer towels/rags per year

(the 5MM/255K cutoff). EPA investigated excluding these groups because these facilities are associated

with small to very small pollutant loads, yet, financially, are somewhat vulnerable to very vulnerable to

potential impacts from pretreatment standards. Under the 1MM/255K cutoff, 128 facilities (16 percent of

all small, single-facility firms, regardless of baseline status) would have been excluded single-facility firms,

under the 3MM/120K cutoff, 363 (45 percent of small, single facility firms) would have been excluded
2

 Pretax returns are based on earnings before interest and taxes. Pretax returns are used here for

comparative purposes because many small firms do not pay corporate taxes.

9-7

single-facility firms, and under the 5MM/255K cutoff, 556 (69 percent of all small single-facility firms)

would have been excluded single-facility firms.

Had EPA promulgated a rule, no small firms would have closed or failed under the 5MM/255

cutoff; 39 small, single-facility firms would have closed or failed under the 3MM/120K cutoff (39 closures

and no failures, or 5.7 percent of all small firms in the postcompliance analyses), and 126 small, singlefacility firms would have closed or failed under the 1MM/255K cutoff (54 closures and 72 failures, or 18.4

percent of all small firms in the postcompliance analysis). At the 3MM/120K cutoff, the 518 facilities

excluded would have been associated with 62 closures or 12 percent of all excluded facilities, and 72

failures out of 363 excluded firms, or 20 percent of all excluded firms.

Small firms were profiled in detail in Section Three, which presents the number of firms and the

financial profile of all firms broken down into detailed revenue categories. Table 9-1 summarizes these

financial characteristics, showing the differences between those classified as small (including those in the

excluded group) and those classified as large and provides some additional comparative measures of

financial health: a pretax return on assets ratio and a pretax return on equity ratio for both small and large

firms.2 As the table shows, the typical small firm generally has smaller earnings, working capital, total

assets and liabilities and owner equity than the typical large firm, but the small size does not necessarily

mean less healthy financially. Both small and large firms, on average, show strong returns on assets and

equity, pretax. Furthermore, small firms might even have slightly better ratios than the larger firms,

although the differences seen might not be statistically significant. (Additional detailed information on

comparative financial health between small and large firms was presented in Section Three.)

9.2.5 Description of Reporting, Recordkeeping, and Other Compliance Requirements

Because EPA has decided not to promulgate pretreatment standards for the industrial laundries

point source category, incremental compliance requirements will not apply.
Table 9-1

Number of Firms and Average Financial Measures,

by Firm Size (1993 $)*

Number of Earnings Before Working Total Total Owner Ratio of Earnings to Ratio of Earnings to

 Revenue Group Firms* Interest and Taxes Capital Assets Liabilities Equity** Owner Equity** Total Assets

 Less than $10.5 million 741 $276,075 $464,271 $2,951,787 $639,930 $2,312,024 0.2874 0.1327

 $10.5 million or greater*** 66 $8,825,605 $13,383,059 $64,444,134 $20,429,506 $44,014,645 0.2845 0.1064

 All firms*** 807 $956,214 $1,491,997 $7,843,677 $2,214,247 $5,635,852 0.2872 0.1306

* The 96 single-facility firms estimated to be baseline closures in Section 5 have been excluded from this analysis.

** Owner equity is being used as a proxy for retained earnings in Altman Z" analyses of firm-level impacts.

*** Two weighted firms that are statistical outliers were not included in the calculation of financial measures.

Source: Section 308 Survey.

9-8
10-1

SECTION TEN

COST AND BENEFITS OF EPA’S DECISION

10.1 REQUIREMENTS OF EXECUTIVE ORDER 12866 AND THE UNFUNDED

MANDATES REFORM ACT (UMRA)

This section has been prepared to comply with Executive Order 12866, which requires federal

agencies to assess the costs and benefits of each significant rule they propose or promulgate. Although

EPA has decided not to promulgate pretreatment standards for the industrial laundries point source

category, this section reviews the major requirements associated with cost-benefit analyses and discusses

EPA’s decision in relationship to these requirements. It also presents a brief comparison of costs and

benefits of regulatory options considered. The methodologies for calculating costs and benefits are the

same as those presented in the EA for the proposal. For the most part, this section discusses only results,

which change slightly due to changes in inputs such as costs of compliance and number of surface water

reaches improved.

The principal requirements of the Executive Order are that the Agency perform an analysis

comparing the benefits of the regulation to the costs that the regulation imposes, that the Agency analyze

alternative approaches to the rule, and that the need for the rule be identified. Wherever possible, the

costs and benefits of the rule are to be expressed in monetary terms.

This section also has been prepared to comply with UMRA. Title II of the Unfunded Mandates

Reform Act of 1995 (UMRA), P.L. 104-4, establishes requirements for federal agencies to assess the

effects of their regulatory actions on state, local and tribal governments and the private sector. Under

section 202 of the UMRA, EPA generally must prepare a written statement, including a cost-benefits

analysis, for proposed and final rules with “federal mandates” that may result in expenditures to state,

local and tribal governments, in the aggregate, or the private sectors, of $100 million or more in any one

year.
1UTSA, TRSA, 1999. Joint Comments of the Uniform and Textile Service Association and the

Textile Rental Services Association in Response to Notice of Data Availability. Written Memorialization

of Oral Comments Provided to EPA Prior to February 8, 1999. Docket No. W-97-14.

10-2

Before promulgating an EPA rule for which a written statement is needed, section 205 of UMRA

generally requires EPA to identify and consider a reasonable number of regulatory alternatives and adopt

the least costly, most cost-effective, or least burdensome alternative that achieves the objectives of the

rule. The provisions of section 205 do not apply when they are inconsistent with applicable law.

Moreover, section 205 allows EPA to adopt an alternative other than the least costly, most cost-effective

or least burdensome alternative if the Administrator publishes with the final rule an explanation why that

alternative was not adopted.

Before EPA establishes any regulatory requirements that might significantly or uniquely affect

small governments, including tribal governments, it must have developed under section 203 of the UMRA

a small government agency plan. The plan must provide for notifying potentially affected small

governments, enabling officials of affected small governments to have meaningful and timely input in the

development of EPA regulatory proposals with significant federal intergovernmental mandates, and

informing, educating, and advising small governments on compliance with the regulatory requirements.

Up through the final decision, EPA complied with requirements of both EO 12866 and UMRA. 

The Agency presented the costs and benefits of the proposed rule in the EA for the proposal and detailed

how the proposal met the requirements of both EO 12866 and UMRA. Now that EPA has decided not to

promulgate pretreatment standards for the industrial laundries point source category, the calculation of

costs and benefits is substantially simplified. Because no regulation is promulgated, EPA’s decision will

result in no regulatory costs and no regulatory benefits as calculated under either EO 12866 or UMRA. 

The industry’s voluntary program will result in some costs and benefits, but as they are not driven by any

regulation, the Agency is not required to measure these costs and benefits. Industry believes their

voluntary program will be significantly more cost-effective than any rule EPA might have devised.1

Thus the decision does not result in a federal mandate that might result in expenditures of $100

million or more for either the public or the private sector in any one year, and there will be no
10-3

disproportionate budgetary effects on any particular areas of the country, particular types of communities,

or particular industry segments. Furthermore, EPA has selected the “least costly, most cost-effective,

and least burdensome alternative.” This satisfies section 203 of the UMRA. EPA’s selection of a noregulation option from among various options is consistent with the requirements of the UMRA in terms

of costs, cost-effectiveness, and burden.

10.2 COSTS AND BENEFITS OF REGULATORY OPTIONS

In this section, EPA presents the costs and benefits of the CP-IL option under the three cutoffs

considered--1MM/255K, 3MM/120K, and 5MM/255K. Costs for DAF-IL are higher (see Table 4-3 in

Section Four) and benefits of DAF-IL are the same as those for CP-IL, ranging from $0.07 to $0.35

million ($1993).

10.2.1 Total Social Costs

As discussed in the EA for the proposal, total social costs that can be monetized include primarily

the pretax costs of compliance. EPA estimated two additional very small cost categories in the EA for

the proposal. These two cost categories included the costs to administer a permitting program (costs to

governments only, since costs of permitting from industry’s perspective are included in the costs of

compliance) and costs of administering unemployment benefits (the benefits themselves are a transfer

payment and are therefore not a social cost). EPA has not precisely estimated these last two costs, but

estimates that they would sum to less than $3 million per year at the 1MM/255K cutoff, and less than that

for the other two cutoffs. For the purposes of this approximate comparison of costs and benefits, EPA

uses the pretax costs of compliance as a reasonable proxy for total social costs.

Table 10-1 presents the total social costs of the rule approximated for the 1MM/255K,

3MM/120K, and 5MM/255K cutoffs. The social costs range from $77.4 million to $171.2 million per

year. The 3MM/120K cutoff is associated with a cost of $131.2 million per year.
10-4

Table 10-1

Approximate Total Annual Social Costs of the CP-IL Regulatory Option and Cutoffs

Cutoff Total Social Costs (million $1993)

1MM/255K $171.3

3MM/120K $131.2

5MM/255K $77.4

Source: Table 4-3 in Section Four.
2

 U.S. EPA. Water Quality Benefits Analysis for the Final Action Regarding the

Pretreatment Standards for the Industrial Laundries Point Source Category. Docket No. L15050.

3

 In fact, EPA looked at the one reach used to model baseline exceedences and found that, in

fact, it was used by a POTW that treats over 5 million gallons a day and thus has authority to issue local

limits.

10-5

10.2.2 Benefits

As in the EA for the proposal, EPA measured the human health, recreational, nonuse, and POTW

benefits. See the EA for the proposal for a detailed discussion of these benefit categories and

methodologies; also see the Water Quality Benefits Analysis for the Final Action Regarding the

Pretreatment Standards for the Industrial Laundries Point Source Category (WQBA)2 for more

information on how the results were derived.

Monetized human health benefits would be nominal under all CP-IL cutoffs. Cancer cases

would be reduced from far less than one cancer case per year in the baseline (0.03 cancer cases would

be avoided, measured from a baseline of 0.10 cancer cases). EPA’s use of a hazard ranking score to

evaluate noncancer effects found no noncancer effects would occur. Based on an estimated monetary

value of cancer cases avoided ($2.1 million to $11.4 million per cancer case avoided; see the EA for the

proposal), cancer cases avoided under all cutoffs would be valued at $0.06 million to $0.34 million per

year.

For recreational benefits, EPA estimates that out of 30 exceedences of ambient water quality

criteria (AWQC) for protection of human health and/or aquatic life on 12 reaches, the regulatory options

under consideration would have eliminated 16 exceedences on these reaches, but would not have

eliminated all the exceedences on any one of the 12 reaches adversely affected by industrial laundry

discharges under the baseline scenario. However, EPA does not consider industrial laundry discharges to

be a nationwide problem. Further, EPA expects that the benefits realized from a rule could be realized

under the existing pretreatment program, where EPA will work with any POTW that is not meeting its

water quality-based permit limit to impose controls as necessary to meet that permit limit.3 EPA also
4

 U.S. EPA. Water Quality Benefits Analysis for the Final Action Regarding the

Pretreatment Standards for the Industrial Laundries Point Source Category. Docket No. L15050.

10-6

notes that the voluntary program, if successful, or the efforts of the OSW to regulate shop towels under

RCRA might also realize these same benefits.

EPA also estimates biosolids quality at 8 POTWs would be improved. EPA estimates this benefit

to be valued at $0.005 million to $0.009 million.4

Table 10-2 presents a summary of these benefits. As the table shows, the total benefits

associated with the CP-IL option under all cutoffs is $0.07 million to $0.35 million, which is primarily the

value of human health benefits.

10.2.3 Comparison of Costs and Benefits

Table 10-3 compares the cost of the CP-IL option under the three cutoffs considered to the

monetized benefits of this regulatory option. As the table shows, the 3MM/120K cutoff is associated with

costs totaling $131.2 million compared with benefits totaling $0.07 to $0.35 million per year.
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Table 10-2

Monetized Benefits by Category

Category Monetized Benefit

Reduced Cancer Cases $0.06 - $0.34 million

Improved Recreational Fishing -

Nonuse -

Sewage Sludge Improvement $0.005 - $0.009 million

Total $0.07 - $0.35 million

 Source: EA for the proposal and the WQBA.
10-8

Table 10-3

A Comparison of Annual Cost and Monetized Benefits of the CP-IL Option

Cutoff Total Social Cost (million $ 1993) Monetized Benefits ($1993)

1MM/255K $171.3 $0.07 - $0.35 million

3MM/120K $131.2 $0..07 - $0.35 million

5MM/255K $77.4 $0.07 - $0.35 million

Source: Table 10-1, EA for the proposal, and the WQBA.
A-1

APPENDIX A

MARKET MODEL METHODOLOGY AND RESULTS

In this Appendix the economic impact analysis of potential pretreatment standards considers the

possible changes in market price and industry output that could result from increased pollution control

costs. EPA uses a market model comprising an industry supply and demand curve to estimate changes in

market price and quantity due to potential standards using the CP-IL option under all cutoffs. This

appendix describes EPA’s market model methodology for the industrial laundries industry. Section A.1

presents an overview of the model used to estimate the economic impacts of the regulation. Section A.2

provides a description of the methodology used for estimating preregulatory market conditions (i.e., the

market supply and demand equations, the methodology used to construct the variables in the model, and the

methodology for estimating preregulatory price and quantity). Section A.3 presents the methodology used

to estimate the postregulatory market conditions. Section A.4 presents the results of the pre- and

postregulatory analyses. Section A.5 presents the results of impact analyses (facility-level and firm-level

analyses) assuming costs can be passed through to customers.

A.1 OVERVIEW OF THE INDUSTRIAL LAUNDRIES MARKET MODEL

A market demand curve shows the relationship between market price and the quantity demanded,

while a market supply curve shows the relationship between market price and the quantity supplied. The

market is in equilibrium when the market price is such that the quantity demanded by industrial laundering

customers is equal to the quantity that industrial launderers are willing to supply. Quantity, in this case,

refers to pounds laundered. EPA assumes that the industrial laundries market is in equilibrium with the

supply and demand curves that determine preregulatory market price and quantity prior to the

implementation of pretreatment standards. The postregulatory scenario will show a shift in the market

equilibrium due to a shift in the supply curve resulting from industry cost increases associated with the
1 The industry supply curve is the aggregate of all facilities’ marginal cost curves. Pollution control costs

add to each facilities’ marginal cost, so the marginal cost curves of all facilities shifts upward (see Figure A–1). 

This shift is very small. The difference between baseline production (Q1) and post compliance production (Q2)

under the CP-IL option is only about 18 to 41 million pounds out of a total baseline production of nearly 9 billion

pounds or 0.2 to 0.5 percent of current production, depending on cutoff.

2 Note, however, that this does not mean that the demand curve faced by the industry is horizontal. If all

firms in the industry face increased costs price can rise along the downward sloping industry demand curve.

3

Pollution control costs are the costs incurred by all facilities in the industry to reduce or minimize the

amount of pollutants that are contained in the effluent from industrial laundries. This cost causes a very small shift

in the supply curve (see footnote above).

A-2

potential standards.1 Figure A-1 illustrates industry demand and supply curves under preregulatory and

postregulatory conditions, showing these shifts.

Although the discussion in this section focuses on market supply and demand, it is important to

consider firm-level conditions, because these conditions influence market conditions. As shown in the

industry profile, the industrial laundries industry is, in most markets, considered a competitive industry. As

such, firms in this industry can be viewed as price takers, in that each firm takes the market price as given

and has no ability to influence that price. In effect, each firm in this industry faces a horizontal demand

curve: at any level of output the firm faces the same market price.2 Given the market price, each

(competitive) firm maximizes its profits by producing at a level where marginal cost is equal to price. Thus,

the marginal cost curve also represents the supply curve for the individual firm under most circumstances. 

Increased pollution control costs cause each firm’s marginal cost curve (i.e., its supply curve) to

shift upward because the cost of production has increased at each point on the marginal cost curve. When

the marginal cost curve shifts up, the competitive firm responds with a lower level of production at each

price level to maximize its profits.3 The market supply curve, which is the sum of the individual firm

supply curves, also shifts upward and to the left, from S1 to S2 (see Figure A-1), resulting in an increase in

the equilibrium market price for industrial laundering services. Ultimately, when the market adjusts to the

impact of increased pollution control costs due to a regulatory option, market equilibrium will reflect a

higher price and lower quantity than the preregulatory price and quantity. The industry now faces a new

market price of P2 and supplies Q2 of industrial laundering services. 
A-3

D, S1 = preregulatory market demand and supply

D, S2 = postregulatory market demand and supply

P1, Q1 = preregulatory equilibrium price and quantity

P2, Q2 = postregulatory equilibrium price and quantity

s

 = supply shift = weighted average increase in marginal cost due to regulation

Figure A-1. Pre-and postregulatory supply and demand for the industrial laundries industry.

s
A-4

The market model assumes that the demand curve does not shift as a result of a regulatory option

of the IL Standards. This assumption is appropriate because, although changes in pollution control costs

affect the production costs of industrial launderers, production costs are supply-side variables and do not

shift the market demand curve. However, at the new, higher price, consumers purchase less, which is

represented as a movement along the demand curve as a result of the change in market price.

 Market impacts depend on the extent to which increases in production costs due to the regulation

cause a decrease in the market supply for industrial laundering services and the extent to which higher costs

can be passed on to customers through higher prices. The final results of the market model include:

# An estimate of preregulatory market supply and demand curves.

# An estimate of postregulatory market price and quantity.

# Price elasticities of supply and demand that will be used to estimate the postregulatory

price, which is used in turn to estimate an industry percentage cost passthrough (CPT).

The percentage CPT can be used to revise facility estimates of total posttax annualized

costs, which then can be input into the facility and firm financial impact analysis models.

A.2 PREREGULATORY MARKET CONDITIONS

This section provides a detailed discussion of the methodology for modeling the preregulatory

market conditions. Section A.2.1 lays the groundwork for the preregulatory market analysis by introducing

the preregulatory market supply and demand equations. Section A.2.2 defines the market model variables

used in the supply and demand equations, provides a discussion of the sources of data for each of the

variables and the methodologies used to construct the variables, and presents the data used in the market

model analysis. Section A.2.3 outlines the steps used to solve for (estimate) the preregulatory market

equations that pass through the 1993 market equilibrium point and presents the elasticities of supply and

demand for the industrial laundries industry. 
4 Although a term for pollution control costs does appear in the preregulatory model, some facilities that

were surveyed in the Section 308 Survey reported having some level of pollution control equipment in place. For

the purposes of this model, EPA assumes that existing unit pollution control costs (costs per pound of laundry

processed) for all facilities have remained constant in the years prior to the regulation, enabling EPA to consider

the marginal effect of incremental pollution control costs that result from regulatory options. As a constant value

in the preregulatory market, preregulatory pollution control costs appear as part of the constant term for the supply

equation, "s, and not as a separate term. A term for incremental, or marginal, pollution control costs appears in the

postregulatory market model.

 

5

PPI is a proxy for input costs and Pop is a proxy for shifts in demand.

A-5

lnQs' ln"s% ,lnPt% 21lnPPIt (1)

lnQd' ln"d% 0lnPt% 22lnPopt (2)

A.2.1 Market Supply and Demand Equations and Market Equilibrium Conditions

The supply and demand relationships represent a system of interdependent equations in which price

and quantity are determined simultaneously to reach a common solution that satisfies both equations. In

theory, these equations mimic the market interactions of industrial launderers and their customers and the

resulting price and quantity are those that would be faced in the market. 

 For this model, market supply is assumed to be a function of market price and the Producer Price

Index (PPI).4 Market demand is assumed to be a function of market price and the U.S. population.5 In

addition, the demand and supply relationships are assumed to be log-linear in form. Given these

relationships, the market supply and demand equations (which are used to estimate the elasticities of supply

and demand [, and 0]) can be written as follows:

Preregulatory Supply

Preregulatory Demand

where,
A-6

Qs' market supply

"s' supply constant

Pt' market price

, ' coefficient for Ptin the supply equation (supply elasticity)

PPIt' Producer Price Index

21' coefficient for PPIt

Qd' market demand

"d' demand constant

0 ' coefficient for Ptin the demand equation (demand elasticity)

Popt' United States population

22' coefficient for Popt

To identify the supply and demand relationships econometrically, each equation must contain at

least one exogenous variable that does not influence the other equation. This is a prerequisite for obtaining

intersecting supply and demand curves and thus a prerequisite for obtaining a solution to the system of

simultaneous equations. For the supply equation, PPI is an exogenous variable and is expected to influence

market supply but not market demand. For the demand equation, U.S. population is an exogenous variable,

expected to affect market demand but not market supply. Because market supply and demand curves show

the relationship between industry output, (i.e., quantity supplied or quantity demanded) and market price,

these variables (quantity and price) are common to both the supply and demand equations. Each of the

variables used in the market model equations are defined and discussed in Section A.2.2. 
6 EPA obtained historical employment data for 1978-1993 from County Business Patterns, U.S.

Department of Commerce, Bureau of the Census.

A-7

A.2.2 Supply and Demand Variables

To measure the impacts of the regulation, actual data for the four market model variables (i.e.,

industry output, market price, PPI, and population) must be input into the model. After an extensive search,

EPA found that industry output and market price data for the industrial laundries industry are not available

through government sources, trade associations, other organizations, or databases that monitor industry

information. For this reason, EPA estimated historical values of output and price from information

provided in the industrial laundries detailed questionnaire database and data available through the U.S.

Census Bureau and the U.S. Bureau of Labor Statistics, and obtained information for the PPI and

population variables from various published sources (see Sections A.2.2.1-A.2.2.4 for exact references).

Each of the variables in the market model are discussed below in detail. The variables for both the market

supply and demand equations are based on historical data for the years 1978 through 1993, which

incorporate a sufficient span to account for industry behavior and trends. Table A-1 presents the data used

to estimate the industrial laundries industry market supply and demand curves. Because this analysis is

based on annual data, the results derived from this data can be considered “intermediate run results,” that is

most, but perhaps not all, factors of production can be varied. As is usually the case, EPA assumes that the

market is in equilibrium each year.

A.2.2.1 Industry Output (Q)

Industry output is defined as the total pounds laundered by all industrial laundry facilities. EPA

constructed estimates of historical industry output data using 1993 industry output data, calculated from

survey data contained in the Section 308 Survey database and historical employment data.6

 Industry

employment was used to construct pre-1993 industry output because employment is an input into the

industrial laundries’ production process and directly affects the level of output. 

To estimate industry output, EPA assumed that no significant changes in worker productivity

occurred over the period analyzed. To explore the effect of this assumption on the model results, EPA used
A-8

Table A-1

Data Used To Estimate The Industrial Laundries Industry

Supply And Demand Curves

Year

Production 

(million pounds)

Price

(1993 dollars) PPI

U.S. Population 

(millions) 

1978 7779.31 $0.39 58.79 222.59

1979 8196.14 $0.42 66.19 225.06

1980 7917.85 $0.47 75.53 227.73

1981 7743.09 $0.52 82.42 229.97

1982 7644.65 $0.56 84.10 232.19

1983 8048.45 $0.54 85.20 234.31

1984 7971.83 $0.60 87.22 236.35

1985 8022.24 $0.62 86.80 238.47

1986 8024.72 $0.68 84.27 240.65

1087 8143.82 $0.72 86.46 242.80

1988 8538.13 $0.75 89.91 245.02

1989 8563.08 $0.76 94.37 247.34

1990 8582.26 $0.77 97.81 249.91

1991 9136.66 $0.74 97.98 252.65

1992 8534.47 $0.83 98.57 255.46

1993 8776.27 $0.81 100.00 258.25

Source: EPA sources and estimates as described in text of Sections A.2.2.1 through A.2.2.4.
7 EPA obtained historical employment data for 1978-1993 from County Business Patterns, U.S.

Department of Commerce, Bureau of the Census.

A-9

Q1993 ' Ei(qiwi) (3)

a productivity factor constructed by the Bureau of Labor Statistics to conduct a sensitivity analysis for

worker productivity. The productivity factor did not improve the regression results and therefore was not

included in the final model. One possible explanation for poor results using the productivity factor is that

this factor is based partly on industry revenues and not at all on actual production data. Due to the lack of

an effective alternative proxy for changes in worker productivity, EPA has assumed a constant 1993 level

of worker productivity in the industrial laundries industry between 1978 and 1993. If, as is generally

expected, worker productivity improved over those 15 fifteen years, the estimates for historical output

could be somewhat high, particularly for the earlier years of the study period. Because productivity

measures are calculated as residuals, they capture changes in nonsupply-side factors as well as

improvements in worker utilization. Thus, a decrease in product demand one year can cause a measured

decrease in productivity if laundries do not lay off a proportionate number of workers. Economically, a

decrease in demand is not equivalent to a decrease in supply even though the impact on measured

productivity may be equivalent. Thus, productivity measures are more reliable in the long-run, rather than

as year-to-year measures of shifts in supply. 

Industry output for 1978 to 1992 was constructed by scaling 1993 industry output estimates based

on industry employment. EPA derived estimates of historical industry output data using 1) 1993 output

estimates from the Section 308 Survey database, 2) 1993 employment estimates from the detailed

questionnaire database, and 3) historical employment figures by SIC codes (note new classification scheme

presented in Table 2-1 in Section Two of this EA).7

Industry output for 1993 was estimated by calculating total output for the population of industrial

laundry facilities contained in the detailed questionnaire database. Because the survey was not a census,

EPA weighted output data for each facility by a facility-specific sample weight to scale the data to the

affected population of industrial laundering facilities. EPA used the following equation to estimate total

output for all industrial laundry facilities for 1993:
8

See Table 2-1 in Section Two of this EA for the new designations for these industries under the NAICS

codes.

A-10

qi' output for sampled facility i in 1993

wi' facility&specific weight factor for facility i

Q1993 ' output for all facilities in 1993

EweightedSIC' ESIC (e

iwi

)

(4)

EweightedSIC' weighted 1993 employment by SIC

ei' employment for facility i in 1993

wi' facility&specific weight factor for facility i

where, 

EPA estimated industry employment ratios using several steps, the first of which involved

calculating population estimates for 1993 employment for the three most prevalent SICs in the database:

7211, 7213, and 7218.8 (The SICs are used in the next step to tailor census employment data to the

facilities represented in the detailed questionnaire database.) These three SICs were chosen because their

employment represents over 96 percent of total employment for facilities in the database. The mathematical

expression for this can be written as follows:

where,

Because only 1993 output and employment data were collected in the detailed questionnaire, EPA

used Census Bureau data to construct historical data for these variables. EPA compared total 1993

employment for the three selected SICs to 1993 total Census Bureau employment figures for those same

SICs. The ratios resulting from this comparison were multiplied by the Census Bureau employment data

for each SIC for each of the years between 1978 and 1993, then summed across SICs, to estimate total

employment in the population for each of these years. Mathematically, this can be written as follows:
A-11

Et' ESIC

eweighted1993SIC

ecensus1993SIC

(ecensustSIC

) (5)

Et' total employment in weighted population in year t

eweighted1993SIC

' employment in weighted population in 1993 by SIC

ecensus1993SIC' census employment in 1993 by SIC

ecensustSIC' census employment in year t

Qt'

Et

E1993

(Q1993) (6)

Qt' total output for weighted facilities in year t

Et' total employment for the weighted population in year t

E1993 ' total employment for the weighted population in 1993

Q1993 ' total output for all facilities in 1993

where, 

EPA scaled total employment for each year by total employment for 1993, so that 1993 became the

base year, then multiplied by 1993 output to obtain output figures for each year between 1978 and 1993.

This can be expressed using the following equation:

where, 
9 EPA obtained historical revenue data from Service Annual Surveys for 1978-1993 published by the U.S.

Department of Commerce, Bureau of the Census. Consumer Price Index data were obtained from the U.S.

Department of Labor, Bureau of Labor Statistics.

A-12

Rev1993 ' Ei(r

iwi

) (7)

r

i

' receipts for sampled facility i in 1993 revenues

wi' facility&specific sample weight factor for facility i

Rev1993 ' total revenues for weighted industrial laundering facilities in 1993

rweighted1993SIC

' ESIC (r

iwi

)

(8)

A.2.2.2 Market Price (P)

Market price is defined as the average receipts per pound that industrial launderers receive for the

services they provide. EPA constructed market prices for 1978 to 1992 by scaling 1993 industry revenue

estimates obtained from the Section 308 Survey using industry revenues and CPI data. EPA derived

estimates of historical market price from information provided by 1) industrial laundering facilities in the

Section 308 Survey database, 2) historical revenue figures by SIC, and 3) CPI data.9

EPA calculated market prices by first estimating total 1993 receipts for the population of industrial

laundry facilities contained in the detailed questionnaire database. EPA based total population receipts on

facility revenue data and facility-specific weights and estimated them using the following equation:

where, 

EPA then calculated revenue ratios and estimated total population receipts for 1993 for the three

most significant SICs (7211, 7213, 7218), which represent over 96 percent of revenues for facilities in the

database. These SICs are used to tailor Census Bureau revenue data to the facilities represented in the

Section 308 Survey database. EPA derived these estimates as follows:
A-13

rweighted1993SIC

' weighted 1993 revenues by SIC

r

i

' revenues for facility i in 1993

wi' facility&specific weight factor for facility i

Revt' ESIC

rweighted1993SIC

r

census1993SIC

(r

censustSIC

) (9)

Revt' total revenues in weighted population in year t

rweighted1993SIC

' revenues in weighted population in 1993 by SIC

r

census1993SIC

' census revenues for 1993 by SIC

r

censustSIC

' census revenues for year t

where, 

Because only 1993 revenue data were collected in the detailed questionnaire, EPA used Census

Bureau data to construct historical revenue figures. EPA compared total 1993 revenues for each of the

three SICs to 1993 Census Bureau revenue figures for the same SICs, then multiplied these ratios by the

Census Bureau revenues for each SIC for each of the years between 1978 and 1993. Summing across

SICs, the Agency estimated total revenues in the population for each of these years. Mathematically, this

approach can be written as follows:

where, 

EPA scaled total revenues for each year by total revenues for 1993, so that 1993 became the base

year, then multiplied by 1993 revenues to obtain revenue figures for each year between 1978 and 1993.

EPA also multiplied the revenue figures by the ratio of two price indexes: 1) the Consumer Price Index for

Laundry and Drycleaning Services Other Than Coin-Operated and 2) the overall CPI. This ratio provides
A-14

Rt'

Revt

Rev1993

(Ct) (Rev1993) (10)

Rt' total revenues for all facilities in year t

Revt' total revenues for the weighted population in year t

Rev1993 ' total revenues for the weighted population in 1993

Ct' Consumer Price Index Ratio (CPI for industrial laundries / CPI for all industries)

for 1978 to 1993

Pt'

Rt

Qt

(11)

an indication of how market prices for laundering services have changed relative to market prices for all

goods and services. The equation used to estimate historical market prices is as follows:

where, 

EPA estimated market price for 1978 to 1993 by dividing the aggregate revenue estimate for each

year by the aggregate output estimate for each year (derived previously) to construct a price per pound for

industrial items for each year between 1978 and 1993:

Changes in product mix can affect price estimated in this manner. Consider a laundry that provides

one higher-priced service and one lower-priced service. In year one, it cleans 500,000 pounds of the higherpriced product at a price of $2 per pound and 500,000 pounds of the lower-priced product at $1 per pound.

Its average revenue is equal to $1.50 per pound:

(500,000 x $2) + (500,000 x $1)/1,000,000 lbs)
A-15

Due to a shift in consumer preferences in year 2, it cleans 100,000 pounds more of the higher-priced

product and 100,000 pounds less of the lower-priced product. Then its average revenue will increase:

(600,000 x $2) + (400,000 x $1)/1,000,000 = $1.60 per pound

even though the product price is unchanged. Changes in product mix ideally should be controlled for

calculating price indices. However, EPA had absolutely no reliable data for the 15-year period with which

to make such adjustments.

A.2.2.3 PPI

The PPI is a proxy for industrial laundering unit production costs and serves as an indicator of

changes or trends in industrial laundering production costs. As stated above, changes in production costs

directly influence the level of services that industrial launderers are willing to supply to the market at any 

A.3 POSTREGULATORY MARKET CONDITIONS

This section describes the changes in the postregulatory market that result from increases in

regulatory compliance costs. Section A.3.1 discusses the methodology for estimating incremental pollution

control costs. Section A.2.3 describes the methodologies used to estimate postregulatory price and quantity.

Section A.3.3 describes the methodology for estimating the percentage CPT that is applied to the facility

and firm closure models.

A.3.1 Estimating Incremental Pollution Control Costs

Industrial launderers that would have incurred compliance costs as a result of pretreatment

standards would have faced increased production costs. When production costs increase, industrial

launderers would decrease the amount of services they provide at any given price. As noted above, an 
11 Pollution control costs include capital costs and operating and maintenance expenses for each facility in

the detailed questionnaire database. The pollution control costs have been weighted by a facility-specific sample

weight to scale the costs associated with the survey sample to the population of industrial laundering facilities. In

addition, the costs have been annualized over a 16-year period so that they remain constant over the lifetime of the

pollution control equipment.

A-16

8 '

Eicciwi

Eiqiwi

(12)

8 ' weighted average incremental pollution control cost per unit of output

cci' incremental pollution control costs for facility i

wi' facility&specific weighting factor

qi' annual quantity for facility i

 EPA assumes that the market supply curve will shift such that the elasticity of supply remains

unchanged, and solely because of the change in unit pollution control costs (compliance costs per pound or

laundry processed). This assumption implies that unit pollution control costs vary with the level of output

in the same way current operating costs do. This is a reasonable assumption that enables the change in the

industry’s average pollution control costs per unit of output to be used to determine the magnitude of the

supply curve shift, as long as shifts in the curve are not large (which they are not).

Unit pollution control costs will be different for each firm and generally are not correlated with

firm size. Therefore, EPA uses the weighted average incremental pollution control cost per unit of output to

estimate the supply shift.11 To calculate the weighted average pollution control costs, the incremental

control costs for each facility are summed to yield total pollution control costs for the industry and then

divided by total weighted output for the industry. This calculation is shown in the following equation: 

where,

The numerator is the total cost of compliance for each option (presented in Table 4-3 in Section Four of

this EA) and the denominator is the total pounds of laundry processed by the industry in 1993 (8.8 billion

pounds—see Table A-1).
A-17

Postregulatory change in unit cost of production '

P1

(1%

8

P1

)

(13)

Postregulatory supply: lnQs' ln"s% ,lnPs& ,ln(1%k) % 21lnPPI (14)

Demand: lnQd' ln"d% 0lnPd& 22lnPop (15)

A.3.2 Estimating Postregulatory Price and Quantity

Postregulatory equilibrium price and quantity depend on the preregulatory supply and demand

equations and the change in unit pollution control costs that result from a regulatory option. The unit

pollution control cost, 8, is used in the postregulatory supply equation as a function of initial price. Using a

constant price elasticity model, the shift in supply caused by compliance costs enters the supply equation

as:

This configuration allows EPA to model the shift in the supply curve assuming a constant elasticity of

supply. EPA could also have specified a parallel shift in the curve, but this approach leads to small

inconsistencies in computing postregulatory price and quantity. When evaluating small changes in unit

costs, however, either assumption (a parallel shift or a constant-elasticity shift) leads to approximately the

same change in price.

We can now solve for (estimate) postregulatory price (P2) using the postregulatory supply and

demand equations (in this case the demand equation is the same both pre- and postcompliance, since no

shifts in demand are assumed): 

Note that the only change in the postregulatory supply and demand equations compared to preregulatory

supply and demand is the addition of the term ,ln (1+k), where k = 8/P1, to the supply equation. This term

represents the unit cost of compliance under constant elasticity assumptions. Under equilibrium conditions,

Qs

 = Qd, we can set the two equations equal to each other and rearrange terms:
A-18

ln"d% 0lnP2% 22lnPop ' ln"s% ,lnP2& ,ln(1%k) % 21lnPPI (16)

(0&,)lnP2' ln"s& ln"d% 21lnPPI & 22lnPop & ,ln(1%k) (17)

lnP2' (0&,)

&1

[ln"s& ln"d% 21lnPPI & 22lnPop & ,ln(1%k)] (18)

lnQ2' lnQ1&

,0

0&,

ln(1%k) (19)

CPT '

P2& P1

8

(20)

This equation can be then written algebraically as:

which further can be written as:

where P2 is the new equilibrium market price. EPA uses this equation to calculate P2.

To determine postregulatory supply, the same equations are used, but are solved for Q2. Solving

for Q2 using the above equations leads to:

A.3.3 Estimating the Percentage CPT and Applying it to the Closure Model

CPT is the percentage of the incremental pollution control cost incurred by an industrial laundries

facility that it can pass on to its customers in the form of higher prices. CPT is calculated as the difference

between the pre- and postregulatory prices relative to the weighted average pollution control cost per unit

of output. The equation is as follows:
A-19

where P2 is calculated using the elasticities of supply and demand.

The percentage of the incremental pollution control costs incurred by each facility is calculated by

multiplying the facility pollution control costs by the complement of CPT, (1 - CPT). This modified

estimate of the control costs for each facility is used in the facility and firm closure models to predict the

number of facilities and firms that will close as a result of an option. EPA recognizes that cost passthrough

may vary by firm. As such this approach defines a lower bound estimate of impact. 

A.4 MARKET MODEL RESULTS

This section presents the results of both the pre- and postregulatory market model analyses. Section

A.4.1 discusses the preregulatory results, including the estimated preregulatory supply and demand

equations and the supply and demand elasticities for the industrial laundries industry. Section A.4.2

presents the postregulatory market model results. These include the estimated shift in the supply curve due

to the incremental pollution control costs, the postregulatory price and quantity, and the percentage CPT

that is subsequently used in the facility and firm closure models.

A.4.1 Preregulatory Market Results 

The preregulatory supply and demand equations were econometrically estimated using the

procedures described above. The parameter estimates and regression statistics for both equations are

reported in Table A-2. 

EPA’s contention that the supply and demand equations used are a good approximation of the

actual market is supported by a variety of statistics. Of particular note are the probablities, which indicate

the estimate for price is just barely outside the 90th percent confidence interval. The low standard errors for

both parameter estimates and the overall model indicate that each variable used in this model (i.e.,

industrial laundering output, market prices, PPI, and U.S. population levels) are significant in estimating

the relationship between supply and demand in the industrial laundries market. Durbin-Watson statistics of
A-20

Table A-2

Preregulatory Supply And Demand Curve Regression Results

SUPPLY CURVE

Parameter Value Std. Error t-stat Probability

Intercept 27.81 0.345 80.64 0.000

Price 0.277 0.067 4.12 0.001

PPI -0.280 0.131 2.14 0.052

Model Statistics

Sum of Squared Residuals 0.010

Standard Error 0.027

Adjusted R-Squared 0.707

F-Statistic (p = 0.0001) 19.104

Durbin-Watson Statistic 1.938

DEMAND CURVE

Parameter Value Std. Error t-stat Probability

Intercept -58.38 40.028 1.459 0.168

Price -0.593 0.346 1.715 0.110

Pop 4.585 2.147 2.136 0.052

Model Statistics

Sum of Squared Residuals 0.010

Standard Error 0.027

Adjusted R-Squared 0.707

F-Statistic (p = 0.0001) 19.104

Durbin-Watson Statistic 1.938

Source: U.S. EPA, 1997. Industrial Laundries Market Model. Model and data are included in the

Rulemaking Record for this proposed rule.
A-21

lnQs' 24.243 % 0.277 lnPt& 0.280 lnPPIt (21)

lnQd' &66.04 & 0.593 lnPt% 4.585 lnPopt (22)

1.938 for both the supply and demand equations indicate that no serial correlation exists in the error terms,

that is, these equations provide unbiased estimates of supply and demand. An F-statistic of 19.104 indicates

that the independent variables as a group contribute significantly to the prediction of quantity supplied and

quantity demanded. An adjusted R-squared statistic of 0.707 indicates that 71 percent of the variance in

quantity supplied and quantity demanded is explained by the variance in the independent variables used in

the equations.

Using the equations for preregulatory supply and demand presented as Equations 1 and 2 in this

Appendix, the parameter estimates presented in Table A-2, and the 1993 values for market price, quantity

demanded, PPI, and U.S. population presented in Table A-1, the estimated supply and demand equation

can be written as:

Preregulatory Supply

Preregulatory Demand

The constants shown in both equations are not those shown in the regression results; instead, EPA

calculated these constants based on the parameter estimates and the 1993 values for the model variables.

This modification enables the estimated supply and demand curves to pass through the 1993 market

equilibrium point. Figure A-2 plots the preregulatory supply and demand equations and the preregulatory

equilibrium price and quantity. The regression equations shown above provide estimates of the elasticities

of supply and demand for the industrial laundries market. The price elasticity of supply is the first partial

derivative of the log-linear supply equation with respect to price, or 0.277. The interpretation of this

estimate is that the quantity supplied of industrial laundering services will increase by 0.277 percent in
A-22

0.00

0.50

1.00

1.50

2.00

2.50

3.00

5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000

Quantity Demanded (millions of pounds)

Price ($ per pound)

Supply

Demand

 

 Figure A-2. Industrial laundries industry preregulatory supply and demand curves.
A-23

lnP2' (0&,)

&1

[ln"s& ln"d% 21lnPPI & 22lnPop & ,ln(1%k)] (23)

lnP2' (&0.0593 & 0.277)

&1 x [(24.243 % 66.04) & (0.28 x ln 100)

& (4.585 x ln 258,250,000) & (0.277 x ln[1 % (0.0150/0.81)])]

lnP2' &0.206438

P2' 0.813

(24)

CPT '

P2&P1

8

(25)

response to a 1 percent increase in price. Similarly, the price elasticity of demand is the first partial

derivative of the log-linear demand equation with respect to price, or -0.593. The interpretation of this

estimate is that the quantity demanded for industrial laundering services will decrease by -0.593 percent in

response to a 1 percent increase in price. 

A.4.2 Postregulatory Market Results

Using the equation derived in Section A.3, EPA can estimate the postregulatory price:

where k is 8/P1 and 8 is the unit cost of pollution control. The unit cost of pollution control (pretax) for the

CP-IL option ranges from $0.009 to $0.021 per pound. As shown in Table A-1, P1 = $0.81 and, from

Table A-2, , = 0.277 and 0 = -0.593. Substituting the cost of the CP-IL option at the 3MM/255K cutoff

($0.0150) into the equation (it does not matter which cost is used to compute CPT since constant elasticity

is assumed) reveals: 

Then, using the CPT equation:

the percentage CPT for all options is found to be approximately 32 percent (see Table A-3). This

percentage is applied to all options. Therefore, the factor applied to compliance costs to determine the

proportion of these costs that will affect the industrial laundries firms and facilities is 68 percent (1 - CPT).
Table A-3

Calculation of Postcompliance Price and Quantity

Pretax Compliance Pretax Compliance Postcompliance Postcompliance Production

Cutoff Cost Cost/lb. Price Cost Passthrough Quantity Loss (lbs.)

 CP-IL: no cutoff $179,687,660 $0.0205 0.815208581 31.57% 8,730,014,495 41,305,874

 CP-IL: 1MM/255K $171,291,344 $0.0195 0.814909003 31.58% 8,731,917,488 39,402,880

 CP-IL: 3MM/255K $131,248,498 $0.0150 0.813477035 31.64% 8,741,029,137 30,291,232

 CP-IL: 5MM/255K $77,401,631 $0.0088 0.811542874 31.72% 8,753,376,894 17,943,475

Source: U.S. EPA, 1999, IL Facility and Firm Financial Model; U.S. EPA, 1999, Industrial Laundries Market Model component. 

Models and data are included in the Decisionmaking Record for the Notice.

A-24
12 Note that if no costs can be passed through (i.e., a perfectly elastic demand curve), -,0/0-, in the

equation solving for quantity approaches –1 and the equation becomes lnQ2 = lnQ1!ln(1+K). Through

additional substitutions, one can prove under these circumstances that the output loss becomes 8Q1, or the

total cost of the regulatory option under consideration, since 8 is the unit cost, (i.e., total cost/Q1.) These

equations are not reproduced here. This fact is used to develop output losses under a zero-cost passthrough

assumption in Section Seven.

A-25

Note that prices will rise $0.003 per pound (from $0.81 to $0.813 per pound; see equation 24)

under the 3MM/255K cutoff, which is an increase of only 0.4 percent. With this rise in prices, EPA

predicts using the equation solving for quantity that the reductions in laundry services provided (Q1 - Q2)

range from 17.9 million pounds (0.2 percent of Q1) to 41.3 million pounds (0.5 percent of Q1),12 depending

on cutoff. This lost production represents a move towards substitutes for individual laundries services (see

Section Eight). 

Price increases and production decreases of these magnitudes would only slow the growth trend in

revenues occurring in the industry, which averaged 4.2 percent per year over the 1991-1993 timeframe

according to the Section 308 survey and which, in 1996 reached 12.7 percent (see Section Three), and has

been averaging greater than 6 percent in recent years. Given the fact that prices have remained constant or

have dropped slightly in recent years, according to comments received by EPA on its proposal (see

Comment Response Document), production has been increasing at a similar or greater rate.

A.5 RESULTS OF THE IMPACT ANALYSIS USING THE MARKET MODEL RESULTS

This section discusses the results of analyses undertaken in Sections Five (Facility-Level Analysis)

and Six (Firm-Level Analysis) should industrial laundry facilities pass through the costs of compliance. 

Because EPA uses an average cost passthrough percentage at each facility, this analysis can be considered

a lower bound estimate of impact, with the estimates shown in Sections Five and Six being the upper bound

estimates. EPA believes that the actual impacts would be bounded by these two sets of estimates.

The baseline analyses do not change when a cost passthrough assumption is used, so the faciltiies

and firms that are analyzed in the postcompliance analysis (for the CP-IL option) are the same as those
A-26

analyzed in Sections Five and Six (see Tables 5-1 and 6-1 for the results of baseline closure and failure

analyses).

A.5.1 Results of the Facility Closure Analysis Assuming Costs Can Be Passed Through

In this analysis, EPA assumes that each facility can pass through 32 percent of compliance costs to

customers (EPA acknowledges that actual cost passthrough will vary by facility, thus this analysis is a

lower bound estimate of impacts on industrial laundry facilities). As Table A-4 shows, facility closures

under all cutoffs are much fewer when costs are assumed to be passed through. For the 1MM/255K and

3MM/120K cutoffs, results differ by approximately one order of magnitude (with no costs passed through

results are 61 and 44 closures, respectively). Results for the 5MM/255K cutoff, however, are not much

different regardless of what assumption regarding cost passthrough is used.

A.5.2 Results of the Firm Failure Analysis Assuming Costs Can Be Passed Through

Assuming that all facilities in the analysis can pass through 32 percent of the costs of compliance,

the firm failure analysis estimates slightly fewer failures under the no cutoff and 1MM/255K cutoff (both

of which were associated with 72 failures assuming no costs can be passed through). No failures would

occur under either assumption regarding cost passthrough at the 3MM/120K and 5MM/225K cutoffs. See

Table A-5 for more detailed results.
Table A-4

Cost-Passthrough Analysis

Facility Closure Analysis - All Facilities*

CP_IL CP-IL CP_IL CP-IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=1595)

 Closures 50 7 4 1

 Percentage of all facilities 3.2% 0.4% 0.3% 0.1%

Facilities with revenues less than $1 million (N=132)

 Closures 44 1 0 0

 Percentage of all facilities 2.7% 0.1% 0.0% 0.0%

 Percentage of revenue group 33.3% 1.0% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=544)

 Closures 5 4 3 0

 Percentage of all facilities 0.3% 0.3% 0.2% 0.0%

 Percentage of revenue group 1.0% 0.7% 0.5% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=619)

 Closures 1 1 1 1

 Percentage of all facilities 0.1% 0.1% 0.1% 0.1%

 Percentage of revenue group 0.2% 0.2% 0.2% 0.2%

Facilities with revenues >=$7 million and <$10.5 million (N=235)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=65)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline closures.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record for the proposed rule.

A-27
Table A-5

Cost-Passthrough Analysis

Firm Failure Analysis - All Firms*

CP_IL CP_IL CP_IL CP_IL

Bankruptcies no cutoff 1MM/255K 3MM/120K 5MM/255K

All firms**

Incremental bankruptcies 56 54 0 0

Percentage of all firms 7.9% 7.6% 0.0% 0.0%

Firms with revenues < $1 million** 

Incremental bankruptcies 35 35 0 0

Percentage of all firms 5.0% 5.0% 0.0% 0.0%

Percentage of revenue group 56.8% 56.8% 0.0% 0.0%

Firms with revenues >= $1 million and < $3.5 million**

Incremental bankruptcies 2 0 0 0

Percentage of all firms 0.3% 0.0% 0.0% 0.0%

Percentage of revenue group 0.8% 0.0% 0.0% 0.0%

Firms with revenues >=$3.5 million and < $7 million**

Incremental bankruptcies 18 18 0 0

Percentage of all firms 2.6% 2.6% 0.0% 0.0%

Percentage of revenue group 8.2% 8.2% 0.0% 0.0%

Firms with revenues >=$7 million and <$10.5 million**

Incremental bankruptcies 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$10.5 million**

Incremental bankruptcies 0 0 0 0

Percentage of all firms 0.0% 0.0% 0.0% 0.0%

Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline bankruptcies and baseline and postcompliance closures among single-facility firms.

** Number of facilities in each revenue group varies by the difference in postcompliance closures among

 options.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record for the proposed rule.

A-28
B-1

APPENDIX B

ADDITIONAL DISCUSSION OF ASSUMPTIONS USED OR

CONSIDERED FOR USE IN THE COST ANNUALIZATION MODEL

B.1 FINANCIAL ASSUMPTIONS

The cost annualization model incorporates several financial assumptions:

# Depreciation method

# Timing between initial investment and operation

# Depreciable lifetime for equipment

# Tax shields on interest payments

# Discount rates

Each assumption, and the alternatives examined in making the assumption, is discussed in detail below.

B.1.1 Depreciation Method

The Agency examined four alternatives for depreciating capital investments:

# Modified Accelerated Cost Recovery System (MACRS)

# Straight-line depreciation

# Section 169 of the Internal Revenue Code

# Section 179 of the Internal Revenue Code

Modified Accelerated Cost Recovery System (MACRS) applies to assets put into service after

December 31, 1986. MACRS involves the ability to write off greater portions of the investment in the
1

 Research Institute of America, Inc., 1995. The Complete Internal Revenue Code. New York,

NY: Research Institute of America, Inc. January.

2

 This assumes that the investment costs do not exceed $200,000 (The Complete Internal Revenue

Code, Section 179(b)(2); ibid.).

B-2

early years. In contrast, the straight-line depreciation writes off a constant amount of the investment each

year. MACRS offers companies an advantage over the straight-line method because a company's income

can be reduced under MACRS by a greater amount in the early years when the time value of money is

greater. Table B-1 illustrates the effects of the difference in timing in writing off a $100,000 capital

investment. The absolute amount depreciated over the 16-year period is the same—$100,000 for both

depreciation methods. The sum of the tax shields is also the same for both methods—$100,000 x 38.46

percent or $38,460. The difference in timing, however, means that MACRS provides a $1,664 benefit over

straight-line depreciation (i.e., the difference between the present values of the tax shields). The benefit of

using MACRS is clear; MACRS is the depreciation used in the cost annualization model.

Section 169 of the Internal Revenue Code provides an option to amortize pollution control facilities

over a 5-year period.1 Under this provision, 75 percent of the investment could be rapidly amortized in a 5-

year period using a straight line method. The 75 percent figure is based on the ratio of allowable lifetime

(15 years) to the estimated usable lifetime (20 years) as specified in the Internal Revenue Code Section

169, Subsection (f). Although the tax provision enables the facility to expense the investment over a

shorter time period, the advantage is substantially reduced because only 75 percent of the capital

investment can be recovered. Tables B-2 and B-3 illustrate the differences between using the Section 169

tax provision and MACRS using hypothetical costs. The present value of the tax shield from depreciation

(Column 4) increases slightly, from $23,756 (Table B-2) to $24,546 (Table B-3). Because the benefit of

the provision is slight, and the facilities might not get the required certification to take advantage of it, the

provision was not included in the cost annualization model. Its exclusion results in a more conservative

(i.e., higher) estimate of the after-tax annualized compliance cost for the facility.

The Agency also considered the Internal Revenue Code Section 179 provision to elect to expense

up to $17,500 the year the investment is placed into service.2 The Agency assumes that this provision is

applied to other investments for the business entity. Its absence in the cost annualization model may result

in a slightly more conservative (i.e., higher) estimate of the after-tax annualized cost for the facility.
Table B-1

Depreciation Methods

Comparison of Straight Line vs. Modified Accelerated Cost Recovery System (MACRS)

Inputs:

Capital Cost ($): $100,000

Discount Rate : 7.0%

Depreciable Lifetime (yrs): 15

Starting Convention: mid-year

Marignal Tax Rates:

Federal 34.00%

State 6.75%

Overall 38.46%

Straight-Line MACRS

Depreciation Depreciation Depreciation Depreciation

Year Rate For Year Tax-Shield Rate For Year Tax-Shield

1 3.33% $3,330 $1,281 5.00% $5,000 $1,923

2 6.67% $6,670 $2,565 9.50% $9,500 $3,653

3 6.67% $6,670 $2,565 8.55% $8,550 $3,288

4 6.67% $6,670 $2,565 7.70% $7,700 $2,961

5 6.67% $6,670 $2,565 6.93% $6,930 $2,665

6 6.67% $6,670 $2,565 6.23% $6,230 $2,396

7 6.67% $6,670 $2,565 5.90% $5,900 $2,269

8 6.66% $6,660 $2,561 5.90% $5,900 $2,269

9 6.67% $6,670 $2,565 5.91% $5,910 $2,273

10 6.66% $6,660 $2,561 5.90% $5,900 $2,269

11 6.67% $6,670 $2,565 5.91% $5,910 $2,273

12 6.66% $6,660 $2,561 5.90% $5,900 $2,269

13 6.67% $6,670 $2,565 5.91% $5,910 $2,273

14 6.66% $6,660 $2,561 5.90% $5,900 $2,269

15 6.67% $6,670 $2,565 5.91% $5,910 $2,273

16 3.33% $3,330 $1,281 2.95% $2,950 $1,134

Sum 100.00% $100,000 $38,455 100.00% $100,000 $38,455

Present Value $62,849 $24,168 $65,856 $25,325

Net Benefit of Using MACRS over Straight-Line Method (Year 1 dollars) $1,157

Source: See text.

B-3
Table B-2

Spreadsheet for Annualizing Costs

INPUTS

 Survey ID #: 1234

 Option Number:

1994 Engineering Inputs Economic Analysis

Initial Capital Cost ($): $100,000 $100,000 Year Dollars 1994 1994

 Annual Operation & Maintenance Cost ($): $10,000 $10,000 ENR CCI 5439 5439

 Facility-Specific Nominal Discount/Interest Rate: 13.0% Federal Corp.Tax Table: Federal Personal Tax Table:

 Expected Inflation Rate: 3.6% Taxable Average Taxable Average

 Real Discount Rate: 9.1% Income Effective Income Effective

 Corporate Tax Structure 1 ($) Tax Rate ($) Tax Rate

 Taxable Income ($) $400,000 $0 15.0% $0 15.0%

 Marginal Income Tax Rates: $50,000 16.7% $22,750 18.8%

 Federal 34.0% $75,000 20.4% $55,100 24.8%

 State 6.60% $100,000 28.3% $115,000 29.5%

 Combined 40.60% $335,000 34.0% $250,000 37.8%

Column 1 2 3 4 5 6 7 8

Tax Shield Cash Outflow

Year Depreciation Depreciation From O&M After

Rate For Year Depreciation O&M Cost Tax Shield Cash Outflow Tax Shields

1 5.00% $5,000 $2,030 $5,000 $2,030 $105,000 $100,940

2 9.50% $9,500 $3,857 $10,000 $4,060 $10,000 $2,083

3 8.55% $8,550 $3,471 $10,000 $4,060 $10,000 $2,469

4 7.70% $7,700 $3,126 $10,000 $4,060 $10,000 $2,814

5 6.93% $6,930 $2,814 $10,000 $4,060 $10,000 $3,126

6 6.23% $6,230 $2,529 $10,000 $4,060 $10,000 $3,411

7 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545

8 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545

9 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541

10 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545

11 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541

12 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545

13 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541

14 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545

15 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541

16 2.95% $2,950 $1,198 $5,000 $2,030 $5,000 $1,772

Sum 100.00% $100,000 $40,600 $150,000 $60,900 $250,000 $148,500

Present Value $59,423 $24,126 $83,900 $34,063 $183,900 $125,711

_________________________

After Tax Shield Before Tax Shield

Present Value of Incremental Costs: $125,711 $183,900

Annualized Cost: $15,192 $22,223

Notes: This spreadsheet assumes that a modified accelerated cost recovery system (MACRS) is used to depreciate capital expenditures.

 Depreciation rates are from 1995 U.S. Master Tax Guide for 15-year property and mid-year convention.

 Corporate Tax Structure: 1= corporate tax rate 2 = individual tax rate.

 If the company-specific discount rate is <3% or >19%, then the industry average figure of 10.0% is used.

 First Year is not discounted.

Source: See text.

B-4
Table B-3

Spreadsheet for Annualizing Costs Using Section 169 Provision

INPUTS

 Survey ID #: XXXX

 Option Number:

1994 Engineering Inputs Economic Analysis

 Initial Capital Cost ($): $100,000 $100,000 Year Dollars 1994 1994

 Annual Operation & Maintenance Cost ($): $10,000 $10,000 ENR CCI 5439 5439

 Facility-Specific Nominal Discount/Interest Rate: 13.0% Federal Corp.Tax Table: Federal Personal Tax Table:

 Expected Inflation Rate: 3.6% Taxable Average Taxable Average

 Real Discount Rate: 9.1% Income Effective Income Effective

 Corporate Tax Structure 1 ($) Tax Rate ($) Tax Rate

 Taxable Income ($) $400,000 $0 15.0% $0 15.0%

 Marginal Income Tax Rates: $50,000 16.7% $22,750 18.8%

 Federal 34.0% $75,000 20.4% $55,100 24.8%

 State 6.60% $100,000 28.3% $115,000 29.5%

 Combined 40.60% $335,000 34.0% $250,000 37.8%

Column 1 2 3 4 5 6 7 8

Tax Shield Cash Outflow

Year Depreciation Depreciation From O&M After

Rate For Year Depreciation O&M Cost Tax Shield Cash Outflow Tax Shields

1 10.00% $7,500 $3,045 $5,000 $2,030 $105,000 $99,925

2 20.00% $15,000 $6,090 $10,000 $4,060 $10,000 ($150)

3 20.00% $15,000 $6,090 $10,000 $4,060 $10,000 ($150)

4 20.00% $15,000 $6,090 $10,000 $4,060 $10,000 ($150)

5 20.00% $15,000 $6,090 $10,000 $4,060 $10,000 ($150)

6 10.00% $7,500 $3,045 $10,000 $4,060 $10,000 $2,895

7 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

8 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

9 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

10 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

11 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

12 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

13 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

14 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

15 0.00% $0 $0 $10,000 $4,060 $10,000 $5,940

16 0.00% $0 $0 $5,000 $2,030 $5,000 $2,970

Sum 100.00% $75,000 $30,450 $150,000 $60,900 $250,000 $158,650

Present Value $60,876 $24,716 $83,900 $34,063 $183,900 $125,121

___________________________

After Tax Shield Before Tax Shield

Present Value of Incremental Costs: $125,121 $183,900

Annualized Cost: $15,120 $22,223

Notes: This spreadsheet assumes that Internal Revenue Code Section 169 is used to depreciate capital expenditures.

 Corporate Tax Structure: 1= corporate tax rate 2 = individual tax rate.

 If the company-specific discount rate is <3% or >19%, then the industry average figure of 10.0% is used.

 First Year is not discounted.

Source: See text.

B-5
3Assuming the equipment goes into service midway through the first year, the annualized cost

would decrease slightly because a 5-percent depreciation of the capital investment would more than exceed

a half year of O&M expenses.

4

 Research Institute of America, 1995. Op. cit.

5

Jeff Cotter and Anne Jones, ERG, 1997. “Sensitivity analysis of annualized cost estimates to

changes in depreciation and project lifetime.” Memorandum to Sue Burris, EPA, October 27.

B-6

B.1.2 Timing Between Initial Investment and Operation

A business cannot begin to depreciate a capital investment before it goes into operation. Although

the midyear convention is frequently used when calculating depreciation, it is not appropriate for the

analysis in Section Four. Several months would be required to build and install most of the equipment

considered in the regulatory alternatives. Additional time might be required for design, permitting, and site

preparation. The cost annualization model, therefore, assumes a 6-month delay from the capital expenditure

to the beginning of operation. As shown in Table B-2, the capital expenditure, depreciation, and one-half of

O&M is listed in Year 1, but depreciation and annual O&M costs are not listed until Year 2 (assumed to be

the first full year of operation).3

B.1.3 Depreciable Lifetime for the Equipment

An asset’s depreciable life can differ from its actual service lifetime. The Internal Revenue Code

Section 168 classifies an investment as 15-year property if it has a class life of 20 years or more but less

than 25 years. Section 168(e)(3)(E) lists a municipal wastewater treatment plant as an example of 15-year

property.4 Fifteen years is also the most commonly listed depreciable lifetime for wastewater treatment

equipment in the 1994 Questionnaire. The cost annualization model, therefore, incorporates a 15-year

lifetime. EPA investigated the use of a 7-year depreciable life, as well as a 7-year actual life.5 Only a

change in the assumption of actual life has any noticeable effect on annual cost. It is unlikely, however,

that the actual life of pollution control equipment is less than 15 years.
6CCH, 1994, op. cit.

B-7

B.1.4 Tax Shields on Interest Payments

The cost annualization model does not consider tax shields on interest paid to finance new pollution

control equipment. A facility could finance the investment through a bank loan (debt), money from

working capital, issuance of a corporate bond, or selling additional stock (equity shares). In any case, the

cost annualization model assumes a cost to the facility to use the money (the discount/interest rate),

whether the money is paid as interest or is the opportunity cost of internal funding. According to current

tax law, if a facility finances the investment using debt, the associated interest expenses can be deducted,

thereby reducing taxable income.6 The tax shield on the interest payments, therefore, would reduce the

after-tax annualized cost. It is not known what mix of debt and capital a facility will use to finance the cost

of pollution control equipment. According to Table B-4, which illustrates the effects of 100-percent debt

financing, the after-tax annualized cost would drop by approximately 3 percent due to tax shields on the

interest payments. If the facility financed the entire investment out of working capital, there would be no

associated tax benefit and the after-tax cost should be calculated without interest tax shields. To maintain

a conservative estimate of the after-tax annualized cost, tax shields on interest payments are not included in

the cost annualization model.

B.1.5 Discount Rates

A company can use internal financing, external financing, or some combination to raise the capital

for upgrading its wastewater treatment system. Retained earnings and working capital are examples of

internal funding sources. Debt and external equity (stock issuance) are examples of external funding

sources. The respondents supplied their discount rate (defined as the weighted average marginal cost of

capital given their mix of debt and equity) in the Section 308 Survey. 
Table B-4

Spreadsheet for Annualizing Costs with Interest Payments

INPUTS

 Survey ID #: XXXX

 Option Number:

1994 Engineering Inputs Economic Analysis

 Initial Capital Cost ($): $100,000 $100,000 Year Dollars 1994 1994

 Annual Operation & Maintenance Cost ($): $10,000 $10,000 ENR CCI 5439 5439

 Facility-Specific Nominal Discount/Interest Rate: 13.0% Federal Corp.Tax Table: Federal Personal Tax Table:

 Expected Inflation Rate: 3.6% Taxable Average Taxable Average

 Real Discount Rate: 9.1% Income Effective Income Effective

 Corporate Tax Structure 1 ($) Tax Rate ($) Tax Rate

 Taxable Income ($) $400,000 $0 15.0% $0 15.0%

 Marginal Income Tax Rates: $50,000 16.7% $22,750 18.8% Financing:

 Federal 34.0% $75,000 20.4% $55,100 24.8% Amount Financed: $100,000

 State 6.60% $100,000 28.3% $115,000 29.5% Annualized: $12,084

 Combined 40.60% $335,000 34.0% $250,000 37.8%

Column 1 2 3 4 5 6 7 8 9 10

Tax Shield Cash Outflow Interest

Year Depreciation Depreciation From O&M After Interest Payment

Rate For Year Depreciation O&M Cost Tax Shield Cash Outflow Tax Shields Payments Tax Shield

1 5.00% $5,000 $2,030 $5,000 $2,030 $105,000 $100,940 $1,096 $445

2 9.50% $9,500 $3,857 $10,000 $4,060 $10,000 $2,083 $1,096 $445

3 8.55% $8,550 $3,471 $10,000 $4,060 $10,000 $2,469 $1,096 $445

4 7.70% $7,700 $3,126 $10,000 $4,060 $10,000 $2,814 $1,096 $445

5 6.93% $6,930 $2,814 $10,000 $4,060 $10,000 $3,126 $1,096 $445

6 6.23% $6,230 $2,529 $10,000 $4,060 $10,000 $3,411 $1,096 $445

7 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545 $1,096 $445

8 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545 $1,096 $445

9 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541 $1,096 $445

10 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545 $1,096 $445

11 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541 $1,096 $445

12 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545 $1,096 $445

13 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541 $1,096 $445

14 5.90% $5,900 $2,395 $10,000 $4,060 $10,000 $3,545 $1,096 $445

15 5.91% $5,910 $2,399 $10,000 $4,060 $10,000 $3,541 $1,096 $445

16 2.95% $2,950 $1,198 $5,000 $2,030 $5,000 $1,772 $1,096 $445

Sum 100.00% $100,000 $40,600 $150,000 $60,900 $250,000 $148,500 $17,544 $7,123

Present Value $59,423 $24,126 $83,900 $34,063 $183,900 $125,711 $9,897 $4,018

___________________________

After Tax Shield Before Tax Shield

Present Value of Incremental Costs: $125,711 $183,900

Annualized Cost: $15,192 $22,223

Annualized Interest Tax Shield: $486

Annualized Cost After Interest Tax Shield: $14,706

Notes: This spreadsheet assumes that a modified accelerated cost recovery system (MACRS) is used to depreciate capital expenditures.

 Depreciation rates are from 1995 U.S. Master Tax Guide for 15-year property and mid-year convention.

 Corporate Tax Structure: 1= corporate tax rate 2 = individual tax rate.

 If the company-specific discount rate is <3% or >19%, then the industry average figure of 10.0% is used.

 First Year is not discounted.

Source: See text.

B-8
7

 Brigham, E.F., and L.C. Gapenski, 1997. Financial Management Theory and Practice. Chicago:

The Dryden Press, 8th edition.

B-9

In theory, a company can raise capital up to its retained earnings breakpoint—the point at which

its capital structure changes. The break occurs when new stock must be issued. Flotation costs associated

with the new issue lead to a higher component cost which, in turn, leads to a higher discount rate.7 

In practice, however, issuing new stock is an option restricted to publicly traded companies. The

Section 308 Survey did not ask the respondent to identify whether it is publicly or privately held. However,

given the number of S corps and other noncorporate structure arrangements (approximately 42 percent of

surveyed firms), given the tendency of these types of firms to be privately held, and given that standard

corporations also often are privately held, a substantial proportion of the industry might be privately held. 

In other words, determining whether the cost of the regulation results in higher discount rates does not seem

to be appropriate for a likely majority of the regulated community.

The Agency uses the discount rate provided by the facility, where possible (see Section Four for a

discussion of how all facilities were assigned a discount rate), in the cost annualization model. This

approach generates the appropriate annualized cost if the capital needed for the pollution control upgrades

is raised by:

# internal funding only.

# a mix of internal funding, debt, and equity as long as the mix reflects the capital structure

used to calculate the discount rate.

# a mix of debt and equity as long as the mix reflects the capital structure used to calculate

the discount rate.

This approach should not underestimate industry compliance costs or impacts.
8

 CCH, 1994. State Tax Handbook. Chicago, IL: CCH.

9

 U.S. EPA, 1992. Total Cost Assessment: Accelerating Industrial Pollution Prevention Through

Innovative Project Financial Analysis. Washington, D.C.: U.S. EPA, Office of Pollution Prevention and

Toxics.

B-10

B.2 AVERAGE STATE TAX RATE

Table B-5 lists each state’s top corporate and individual tax rates and calculates national average

state tax rates.8 The cost annualization model uses the average state tax rate because of the complexities in

the industry; for example, a facility could be located in one state, while its corporate headquarters are

located in a second state. Given the uncertainty over which state tax rate applies to a given facility’s

revenues the average state tax rate is used in the cost annualization model for all facilities.

B.3 COST ANNUALIZATION MODEL AND TOTAL COST ASSESSMENT

The Total Cost Assessment (TCA) approach for evaluating pollution prevention alternatives is

comprehensive financial analysis of the life-cycle costs and savings of a pollution prevention project.9 A

TCA approach includes:

# Internal allocation of environmental costs to product lines or processes through full cost

accounting.

# Financial analysis of direct and indirect costs, short- and long-term costs, liability costs,

and less tangible benefits of an investment.

# Evaluation of project costs and savings over a long-time horizon, e.g., 10 to 15 years.

# Measures of profitability that capture the long-term profitability of the project, e.g., net

present value and internal rate of return.

TCA approaches are being developed as alternatives to traditional financial analysis methods to capture

and properly evaluate the long-term costs and savings inherent in pollution prevention activities.
Table B-5

State Income Tax Rates

Basis for States Basis for States

Corporate Income With Graduated Personal Income Tax With Graduated

State Tax Rate Tax Tables Upper Rate Tax Tables

Alabama 5.00% 5.00% $3,000+

Alaska 9.40% $90,000+ 0.00%

Arizona 9.00% 6.90% $150,000+

Arkansas 6.50% $100,000+ 7.00% $25,000+

California 9.30% 11.00% $215,000+

Colorado 5.00% 5.00%

Connecticut 11.50% 4.50%

Delaware 8.70% 7.70% $40,000+

Florida 5.50% 0.00%

Georgia 6.00% 6.00% $7,000+

Hawaii 6.40% $100,000+ 10.00% $21,000+

Idaho 8.00% 8.20% $20,000+

Illinois 4.80% 3.00%

Indiana 3.40% 3.40%

Iowa 12.00% $250,000+ 9.98% $47,000+

Kansas 4.00% $50,000+ 7.75% $30,000+

Kentucky 8.25% $250,000+ 6.00% $8,000+

Louisiana 8.00% $200,000+ 6.00% $50,000+

Maine 8.93% $250,000+ 8.50% $33,000+

Maryland 7.00% 6.00% $100,000+

Massachusetts 9.50% 5.95%

Michigan 2.30% 4.40%

Minnesota 9.80% 8.50% $50,000+

Mississippi 5.00% $10,000+ 5.00% $10,000+

Missouri 6.25% 6.00% $9,000+

Montana 6.75% 11.00% $63,000+

Nebraska 7.81% $50,000+ 6.99% $27,000+

Nevada 0.00% 0.00%

New Hampshire 7.00% 0.00%

New Jersey 7.25% 6.65% $75,000+

New Mexico 7.60% $1Million+ 8.50% $42,000+

New York 9.00% 7.88% $13,000+

North Carolina 7.75% 7.75% $60,000+

North Dakota 10.50% $50,000+ 12.00% $50,000+

Ohio 8.90% Based on Stock Value 7.50% $200,000+

Oklahoma 6.00% 7.00% $10,000+

Oregon 6.60% 9.00% $5,000+

Pennsylvania 9.90% 1997 and thereafter 2.80%

Rhode Island * 9.00% 10.40% $250,000+

South Carolina 5.00% 7.00% $11,000+

South Dakota 0.00% 0.00%

Tennesee 6.00% 0.00%

Texas 0.00% 0.00%

Utah 5.00% 7.20% $4,000+

Vermont * 8.25% $250,000+ 9.45% $250,000+

Virginia 6.00% 5.75% $17,000+

Washington 0.00% 0.00%

West Virginia 9.00% 6.50% $60,000+

Wisconsin 7.90% 6.93% $20,000+

Wyoming 0.00% 0.00%

 Average: 6.61% 5.84%

Notes: Basis for rates is reported to nearest $1,000.

Personal income tax rates for Rhode Island and Vermont based on federal tax (not taxable income).

Tax rates given here are equivalents for highest personal federal tax rate.

Source: Personal communication, Maureen Kaplan, ERG, and Commerce Clearinghouse (CCH) Inc., to resolve

discrepancies on tax rate for Missouri and Rhode Island, March 30, 1995

CCH, 1994. State Tax Handbook. Chicago, IL: CCH.

B-11
B-12

The cost annualization model incorporates several features of a total cost assessment analysis,

including:

# Long-time horizon (the annualization model uses a 15-year time frame).

# Short- and long-term costs.

# Cost savings due to reduced chemical usage, etc., which are included in the cost estimates

prepared by the EPA engineers (see Development Document).

# Depreciation, taxes, inflation, and discount rate. 

# The associated closure analysis (Section Five), which uses the net present value of the

investment calculated in the cost annualization model to evaluate the long-term impacts on

profitability.

The economic analysis differs from the TCA approach in that it does not include a “liability avoided”

component or an evaluation of the less tangible benefits of the regulation. There are insufficient data to

estimate potential future liability costs for each facility. The exclusion of this parameter results in a more

conservative analysis where potential impacts are not offset by avoiding future liability costs. A separate

analysis and report compare the costs and benefits of the regulation. 
C-1

APPENDIX C

RESULTS OF THE FACILITY CLOSURE ANALYSIS

AND FIRM FAILURE ANALYSIS UNDER THE DAF-IL OPTION

This appendix presents the results of analyses of the DAF-IL option. These analyses are identical

to those performed for the CP-IL option in Sections Five and Six of this report. Table C-1 presents the

results of the facility closure analysis under the same four cutoffs investigated in Section Five. As the table

shows, the results are identical to those for the CP-IL option under the same cutoffs (see Table 5-4).

Table C-2 presents the results of the firm failure analysis under the cutoffs considered. As the

table shows, the results are identical to those for the CP-IL option under the same cutoffs (see Table 6-4). 

All other impacts from the DAF-IL option would be expected to be approximately the same as

those for the CP-IL option.
Table C-1

Facility Closure Analysis for the DAF-IL Option - All Facilities*

DAF-IL DAF-IL DAF-IL DAF-IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=1595)

 Closures 106 61 44 2

 Percentage of all facilities 6.7% 3.8% 2.7% 0.2%

Facilities with revenues less than $1 million (N=132)

 Closures 58 15 0 0

 Percentage of all facilities 3.6% 1.0% 0.0% 0.0%

 Percentage of revenue group 44.0% 11.7% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=544)

 Closures 46 43 41 0

 Percentage of all facilities 2.9% 2.7% 2.6% 0.0%

 Percentage of revenue group 8.5% 7.9% 7.6% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=619)

 Closures 2 2 2 2

 Percentage of all facilities 0.2% 0.2% 0.2% 0.2%

 Percentage of revenue group 0.4% 0.4% 0.4% 0.4%

Facilities with revenues >=$7 million and <$10.5 million (N=235)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=65)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline closures.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

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Table C-2

Firm Failure Analysis for the DAF-IL Option - All Firms*

DAF-IL DAF-IL DAF-IL DAF-IL

Bankruptcies no cutoff 1MM/255K 3MM/120K 5MM/255K

All firms**

 Incremental bankruptcies 72 72 0 0

 Percentage of all firms 9.6% 9.6% 0.0% 0.0%

Firms with revenues < $1 million** 

 Incremental bankruptcies 53 53 0 0

 Percentage of all firms 7.2% 7.2% 0.0% 0.0%

 Percentage of revenue group 53.5% 53.5% 0.0% 0.0%

Firms with revenues >= $1 million and < $3.5 million**

 Incremental bankruptcies 0 0 0 0

 Percentage of all firms 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$3.5 million and < $7 million**

 Incremental bankruptcies 18 18 0 0

 Percentage of all firms 2.5% 2.5% 0.0% 0.0%

 Percentage of revenue group 8.2% 8.2% 0.0% 0.0%

Firms with revenues >=$7 million and <$10.5 million**

 Incremental bankruptcies 0 0 0 0

 Percentage of all firms 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Firms with revenues >=$10.5 million**

 Incremental bankruptcies 0 0 0 0

 Percentage of all firms 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

* Excluding baseline bankruptcies and baseline and postcompliance closures among single-facility firms.

** Number of facilities in each revenue group varies by the difference in postcompliance closures among

 options.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models

 and data are included in the Decisionmaking Record.

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D-1

APPENDIX D

RESULTS OF THE BASELINE AND POSTCOMPLIANCE

CLOSURE ANALYSIS ASSUMING SALVAGE VALUE

PLAYS A ROLE IN CLOSURE DECISIONS

This appendix presents the results of two analyses. The first analysis is a sensitivity analysis that

assumes that salvage value would play a role on decisions to close at facilities owned by multifacility firms. 

As discussed in Section Five, EPA, as supported by industry comments (see Comment Response

Document), does not believe salvage value is used by single-facility firms in making decisions about

whether to stay open. These firms have many other reasons besides returns on investments to stay in

business, and EPA believes, for the most part, these firms would try to stay in business under nearly all

adversities unless forced to close under circumstances of persistent negative cash flows. EPA, for a variety

of reasons, which are discussed briefly in Section Five and more thoroughly in the Comment Response

Document in its response to PECON-2C, Tracking No. 1482, believes that although salvage value might be

used by multifacility firms in considering whether to close a facility, the way in which cash flow estimates

were made might make a salvage value analysis too conservative. Nevertheless, EPA performed a

sensitivity analysis to determine if its decision to model closures without considering salvage value would

have had any impact on a decisionmaking process, had EPA decided to promulgate a rule.

The second analysis responds to several public comments submitted to EPA that suggested that a

market value for facilities should be used as a salvage value. As is made clear in EPA’s response to

PECON-2C, Tracking No. 1481, in the Comment Response Document, believes this approach is

inappropriate for a closure analysis, primarily because a market value (the value of a business at a market

rate) does not reflect a salvage value (the value upon liquidation, that is, well below the market rate of

viable facilities), nor does a voluntary sale at a market rate reflect the impact of a forced sale at much

below market rate, which is the definition of a regulation-induced closure. The analysis of a market rate

baseline “closure” analysis, however, provides an interesting view of the forces that are driving

consolidation. This information is summarized in Section Eight in a discussion of impacts of a rule on

consolidation in the industry.
1

 U.S. EPA, 1997. Economic Analysis for the National Emission Standards for Hazardous Air

Pollutants for Source Category: Pulp and Paper Production; Effluent Limitations, Guidelines,

Pretreatment Standards, and New Source Performance Standards: Pulp, Paper, and Paperboard

Category—Phase I. p. 3-11.

D-2

D.1 CLOSURE ANALYSIS ASSUMING SALVAGE VALUE PLAYS A ROLE IN THE

DECISION

Facility impacts under the salvage value scenario are estimated by comparing each facility’s

salvage value to the present value of its future earnings. The salvage value represents the expected amount

of cash the owner would receive if the facility were closed and liquidated. In the baseline salvage value

scenario analysis, the basic model calculates the present value of the earnings stream over a 16-year time

frame and subtracts that present value from the calculated salvage value. If salvage value exceeds the

present value of cash flow, the model classifies the facility as a “closure” in the baseline. 

EPA assumed that if firms go out of business or close a facility under “forced” circumstances (as

would happen if the facility must comply with a regulation or close), they will move quickly to liquidate

their fixed assets and that, as a result, they will receive only a small fraction of the market value for their

fixed assets. In the original model specifications, a 20-percent recovery factor is applied to facilities’

actual or estimated value for fixed assets. Like fixed assets, the valuation of current assets when estimating

salvage value is based on their probable value during an auction/liquidation process. However, unlike fixed

assets, current assets are assumed to be relatively easy to liquidate. Given this, it is assumed that a firm

could recover close to the full value of its current assets and, as a result, in the original model, a 100

percent recovery factor is used for current assets. In EPA’s sensitivity analysis in the EA for the proposal,

inventories were assumed to be liquidated at a 100 percent of cost or fair market value, whichever was

lower. EPA subsequently determined that inventories, because they are not nearly as liquid as other current

assets also would be liquidated at far less than their actual market value, given the nature of those

inventories. The 20 percent fixed asset recovery factor was therefore applied to inventories. This provided

a much more realistic baseline closure result than had the previous analysis in the EA for proposal, which

used the 100 percent liquidation value for inventories. The 20 percent fixed asset recovery factor and the

100 percent current asset recovery factor (with lower recovery rates for inventories) have been used in

previous Office of Water EIAs.1
D-3

Table D-1 presents the results of the baseline closure analysis using salvage value as a determinant

in the closure of facilities owned by multifacility firms. This table indicates that there are a somewhat

larger number of baseline closures under the salvage value analysis than under the cash flow-only scenario

shown in Section Five, Table 5-1, particularly among facilities in the $1 million to $3.5 million revenue

range, but substantially fewer than those estimated using a 100 percent liquidation value of inventories

(36.6 percent of all nonindependent facilities were estimated to close in the baseline under this assumption,

as reported in Appendix C in the EA for the proposal as compared to 9.3 percent using the current

methodology). A total of 85 nonindependent facilities are estimated to close in the baseline using the

current methodology, compared to 51 facilities assuming salvage value does not play a role in the decision

to close.

Table D-2 presents the results of a postcompliance closure analysis on those nonindependent

facilities that do not close in the baseline. As the table shows, 15 nonindependent facilities would close

with no cutoff (3 more than that estimated without using salvage value—see Table 5-3), 9 would close

under the 1MM/255K cutoff (3 more than that estimated without using salvage value), 3 would close under

the 3MM/120K cutoff (2 fewer than that estimated without using salvage value), and 1 would close under

the 5MM/255K cutoff (1 fewer than that estimated without using salvage value).

Thus, had the Agency used a salvage value approach, results would have changed very little, and

certainly not enough to have had any impact on any decisionmaking process. EPA considers the estimates

derived in this sensitivity analysis to be no more accurate than the ones derived without the use of salvage

value.

D.2 RESULTS OF A BASELINE ANALYSIS ASSUMING THAT SALVAGE VALUE

EQUALS MARKET VALUE

In this analysis, EPA assumed that the market value of a facility was equal to 1 times annual

revenues, which is approximately the midpoint of the range suggested in the Comment Response Document

PECON-2C,Tracking No. 1481 and the lower end of the range suggested in PECON-2D, Tracking No.

1486. EPA then set this value to the salvage value of each facility (both single-facility firms and
Table D-1

Baseline Closure Analysis - Nonindependent Facilities

Closures Nonclosures

Percentage of Percentage of

Revenue Groups ($000) Number Revenue Group Number Revenue Group Total

Nonindependent Facilities

Total 85 9.3% 827 90.7% 912

< $1 Million 26 63.6% 15 36.4% 41

>= $1 and < $3.5 Million 28 10.8% 228 89.2% 256

>= $3.5 and < $7 Million 23 5.6% 382 94.4% 405

>= $7 and < $10.5 Million 1 0.9% 155 99.1% 156

>= $10.5 Million 0 0.0% 47 100.0% 47

Note: Discrepancies in the number of facilities are due to rounding errors.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are included in the 

 Decisionmaking Record.

D-4
Table D-2

Salvage Value Approach

Facility Closure Analysis - Nonindependent Facilities*

CP_IL CP_IL CP_IL CP_IL

Closures no cutoff 1MM/255K 3MM/120K 5MM/255K

All facilities (N=827)

 Closures 15 9 3 1

 Percentage of all facilities 1.8% 1.1% 0.3% 0.1%

Facilities with revenues less than $1 million (N=15)

 Closures 7 1 0 0

 Percentage of all facilities 0.9% 0.2% 0.0% 0.0%

 Percentage of revenue group 48.0% 9.3% 0.0% 0.0%

Facilities with revenues >= $1 million and < $3.5 million (N=228)

 Closures 3 3 1 0

 Percentage of all facilities 0.3% 0.3% 0.2% 0.0%

 Percentage of revenue group 1.2% 1.2% 0.6% 0.0%

Facilities with revenues >=$3.5 million and < $7 million (N=382)

 Closures** 2 2 1 1

 Percentage of all facilities 0.3% 0.3% 0.1% 0.1%

 Percentage of revenue group 0.6% 0.6% 0.3% 0.3%

Facilities with revenues >=$7 million and <$10.5 million (N=155)

 Closures 0 0 0 0

 Percentage of all facilities 0.0% 0.0% 0.0% 0.0%

 Percentage of revenue group 0.0% 0.0% 0.0% 0.0%

Facilities with revenues >=$10.5 million (N=47)

 Closures 3 3 0 0

 Percentage of all facilities 0.3% 0.3% 0.0% 0.0%

 Percentage of revenue group 5.3% 5.3% 0.0% 0.0%

* Excluding baseline closures.

Note: Discrepancies in the number of facilities are due to rounding.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are

 included in the Decisionmaking Record.

D-5
D-6

nonindependent facilities) and used the same methodology outlined above in Section D.1 to compare

salvage value with the present value of discounted cash flow.

As Table D-3 indicates, over 70 percent of all facilities (both nonindependent and single-facility

firms) would fit into a “sell now” classification based on this approach. Thus this approach is considered

more a measure of the consolidation pressures currently in force in the industry rather than a measure of

baseline financial health. Furthermore, it is clear from this analysis that a rule would not have had a

substantial impact on consolidation. Even if the percentage of the firms that would fit into a “sell now”

category grew, demand for industrial laundry facilities might actually have dropped postcompliance (that

is, the demand curve for industrial laundry facility acquisitions could have shifted downwards) as

multifacility firms would not have had as many funds available to make acquisitions after purchasing and

installing pollution control equipment. If demand dropped, the increase in supply of facilities available for

acquisition might have had minimal impact on the rate of consolidation, since the decrease in demand

would have had the opposite effect on quantity as the increase in supply (note, however, that the average

sales price would have inevitably dropped, driven both by an shift downward and outward in the supply

curve and by the downward shift in demand).
Table D-3

Salvage Value = Revenues

Baseline Closure Analysis - All Facilities

Closures Nonclosures

Percentage of Percentage of

Revenue Groups ($000) Number Revenue Group Number Revenue Group Total

Nonindependent Facilities

Total 646 70.9% 266 29.1% 912

< $1 Million 47 100.0% 0 0.0% 47

>= $1 and < $3.5 Million 140 54.4% 117 45.6% 257

>= $3.5 and < $7 Million 337 83.1% 68 16.9% 405

>= $7 and < $10.5 Million 109 70.0% 47 30.0% 156

>= $10.5 Million 14 29.8% 33 70.2% 47

Single-Facility Firms

Total 587 70.7% 243 29.3% 830

< $1 Million 124 68.4% 58 31.6% 182

>= $1 and < $3.5 Million 248 84.8% 44 15.2% 292

>= $3.5 and < $7 Million 186 72.3% 71 27.7% 258

>= $7 and < $10.5 Million 20 24.2% 61 75.8% 81

>= $10.5 Million 9 69.3% 9 30.7% 28

Note: Discrepancies in the number of facilities are due to rounding errors.

Source: U.S. EPA, 1999. IL Facility and Firm Financial Model, and Section 308 Survey data. Models and data are included in the 

 Decisionmaking Record.

D-7