vvEiPA
             United States
             Environmental Protection
             Agency
             Office of Water
             (4303)   ;
EPA821-R-97-009
November 1997
Wafer Quality Benefits Analysis for
Proposed Pref reatmenf Standards
for Existing and New Sources for
the Industrial Laundries Point
Source Category

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     Water Quality Benefits Analysis
   for Proposed Pretreatment Standards
   for Existing and New Sources for the
Industrial Laundries Point Source Category

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                                 Executive Summary

Overview of the Industrial Laundry Industry and its Effluent Discharges

       From a detailed technical and economic survey of the industrial laundry industry, the U.S.
Environmental Protection Agency (EPA) estimates that the industry contains 1,747 facilities that
discharge water and are thus potentially subject to regulation. Of these 1,747 facilities, 1,606 would
be required to  comply with standards because they process one million pounds or more of laundry
or 255,000 pounds or more of shop towels or printer towels per year. EPA estimates that all of these
facilities are indirect dischargers (i.e., they discharge their effluent to publicly-owned treatment works
(POTWs)) and thus would be subject to Pretreatment Standards for Existing Sources (PSES).

       Currently, industrial laundry facilities nationwide discharge to POTWs 4.9 million pounds per
year of priority and nonconventional pollutants (excluding Chemical Oxygen Demand, Total Organic
Carbon, and Total Petroleum Hydrocarbons measured as Silica Gel Treated n-Hexane Extractable
Material (SGT-HEM)), and 35.9 million pounds of oil and grease measured as n-Hexane Extractable
Material (HEM).  Of the 35.9 million pounds of HEM, 13.2 million pounds are SGT-HEM (see Table
ES-1  for loadings of all pollutants).  Discharges of priority and nonconventional pollutants  into
freshwater and estuarine ecosystems may alter aquatic habitats, adversely affect aquatic biota, and
adversely impact human health  through the consumption of contaminated fish and  water.
Furthermore, these pollutants may interfere with POTW operations through contamination of sewage
sludge, thereby restricting the method of disposal, or through; inhibition of the microbes present in
activated sewage sludge.  Many of the pollutants of concern from industrial laundries have at least
one toxic effect (human health carcinogen and/or non-cancer toxicant, or aquatic toxicant). In
addition, many  of these pollutants bioaccumulate in aquatic organisms and persist in the environment.

       For this rulemaking, EPA evaluated the environmental benefits of controlling the pollutant
discharges  from industrial laundry facilities to POTWs through national analyses of four primary
treatment options:  organics  control (OC)  only,  dissolved air flotation (DAF-IL),  chemical
precipitation (CP-IL), and a combined option with either DAF or CP for all wastewater (Combo-BL).
Benefits of the Proposed Rule

       EPA estimates that the proposed standards would significantly reduce pollutant discharges
to POTWs, as shown by the loadings estimates in Table ES-1 for five categories of pollutants.
Reductions in industrial laundry pollutant discharges to POTWs i would result in a number of benefits
to society, including: improved quality of freshwater, estuarine, and marine ecosystems; increased
survivability and diversity of aquatic life and terrestrial wildlife; reduced risks to human health through
consumption of fish or water taken from affected waterways; reduced cost of disposal or use of
municipal  sewage sludge  that is affected by industrial laundry pollutant discharges; and, reduced
occurrence of biological inhibition of activated sludge at POTWs.
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Table ES-1. Summary of Estimated Pollutant tradings fedm Intfostrtaf LaundriesJo POTWis-' ',; , , ",
Regulatory
Option
Baseline
DAF-IL
CP-IL
Combo-IL
Priority and
Nonconventional
Pollutants*
(million Ib/yr)
National
Estimates
4.9
2.9
2.9
3.1
HEM
(million Ib/yr)**
National
Estimates
35.9
15.9
15.2
15.9
SGT-BEM" '
(million Ib/yr).
National
Estimates
13.2
2.6
2.4
2.6
.Other
Conventional
Pollutants (million
ib/yr)***
National
Estimates
176
137
139
139
Other r
Nonconventional
Pollutants (million
•'lb/y$****
^ ' , National
Estimates
346
252
258
258
* Excludes Total Organic Carbon (TOC), Total Petroleum Hydrocarbons measured as Silica Gel Treated n-Hexane Extractable
Material (SGT-HEM), and Chemical Oxygen Demand (COD).
** Includes the pounds of SGT-HEM.
*** Includes Biological Oxygen Demand (BOD) and Total Suspended Solids (TSS).
**** Includes Chemical Oxygen Demand (COD) and Total Organic Carbon (TOC).
Human Health Benefits

       EPA analyzed the following measures of health-related benefits from the proposed rule:
reduced cancer risk from fish consumption, measured as annual avoided cancer cases; and, reduced
occurrence of in-waterway pollutant concentrations in excess of human health-based ambient water
quality criteria (AWQC) or in excess of documented toxic effect levels for those chemicals for which
EPA has not published water quality criteria. Note that this second measure includes both cancer and
non-cancer effects.  In doing this, EPA examined industrial laundry discharges alone, not accounting
for any other discharges to receiving waters.

       For 139 industrial laundry faculties that responded to the  detailed questionnaire, EPA
predicted steady-state, in-stream pollutant concentrations by assuming complete immediate mixing
with no loss from the system. (Because of incomplete information on the POTWs to which some of
the sample facilities discharge, EPA was unable to  include in the benefits analysis 33 of the 172
facilities surveyed.)  These 139 facilities discharge to 118 POTWs that in turn discharge to 113 water
bodies (88 rivers/streams, 21 bays/estuaries, and 4 lakes).

       EPA then extrapolated the environmental assessment results for the sample facilities to the
entire population of industrial laundry facilities nationwide  (approximately 1,606 facilities discharging
to 1,178 POTWs discharging to 1,133 waterbodies).  For this extrapolation, each sample facility
received a sample weight based on the varying number of additional facilities of the same approximate
size engaged in similar activities under similar economic conditions.

       EPA then estimated the change in aggregate cancer risk through consumption of fish in
waterbodies where the identified POTWs discharge. EPA predicted pollutant concentrations in fish
by using the in-stream concentration from POTW effluent where industrial laundry discharges are
expected to pass through and pollutant-specific bioconcentration factors. EPA used data on licensed
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fishing populations by state and county, presence offish advisories, fishing activity rates, and average
household size to estimate the exposed population of recreational and subsistence anglers and their
families that would benefit from reduced pollutant concentrations in fish.  EPA used fish consumption
rates for recreational and subsistence anglers to estimate exposure levels. Based on these data, EPA
estimated the change in cancer risk among these populations.

       For combined recreational and subsistence angler household populations, EPA projects that
the treatment options would eliminate approximately 0.04 cancer cases per year from a baseline of
about 0.1 cases estimated at the current discharge level (see Table ES-2).
                          Baseline
                           CP-IL
                          DAF-IL
                         Combo-IL
0.04
0.04
0.04
       EPA also evaluated reduced occurrence of in-waterway pollutant concentrations in excess of
human-health based ambient water quality criteria (AWQC).  At current discharge levels, in-stream
concentrations of two pollutants ~bis(2-ethylhexyl)phthalate and tetrachloroethene — are projected
to exceed human health criteria (developed for consumption of water and organisms) in nine receiving
streams nationwide (see Table ES-3) for a total of 17 exceedences. The proposed PSES regulated
discharge levels would eliminate the occurrence of pollutant concentrations in excess of the human
health-based AWQCs in 7 of 9 affected streams.
Table ES-3. Discharge Reaches with Pollutant
Concentrations Exceeding AWQC Limits for Protection
of Human Health, and Redactions Achieved by
, , Regulatory Options
Regulatory
Option
Baseline
CP-IL
DAF-IL
Combo-IL
Number of Reaches with Concentrations
Exceeding Health-Based AWQCs
{National Basis)
Water and Organisms
9 ;
2
2
2 :
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Ecological Benefits Valued on the Basis of Enhanced Recreational Fishing Opportunities
       EPA analyzed one measure of ecological benefits from the proposed regulation: reduced
occurrence of in-waterway pollutant concentrations in excess of acute and chronic exposure AWQCs
that protect aquatic life. EPA used the findings from the analysis of reduced occurrence of pollutant
concentrations in excess of both EPA's ecological and human health AWQCs to assess improvements
in recreational fishing habitats and, in turn, to estimate a monetary value for the enhanced recreational
fishing opportunities.

       To assess aquatic life benefits, EPA estimated the effect of facility discharges of regulated
pollutants on  pollutant concentrations in affected waterways.   EPA compared the estimated
concentrations, on a baseline and post-compliance basis, with the Agency's AWQCs for acute and
chronic exposure impacts to aquatic life. Pollutant concentrations in excess of these values indicate
potential impacts to aquatic life. EPA's analysis found that 78 stream reaches exceed chronic AWQC
values at baseline discharge levels for a total of 93 exceedences (see Table ES-4).  Under three
options, EPA estimates that the proposed regulation would eliminate concentrations in excess of the
chronic AWQC values for aquatic life in 66 affected reaches.  EPA predicts that no pollutants under
current or proposed  discharge levels would exceed acute AWQC.

       EPA expects that society will value improvements in aquatic species habitat, resulting from
the reduction of pollutant concentrations  in excess of the chronic  AWQC values, by a number of
mechanisms. For this analysis, EPA estimated a partial monetary value of ecological improvements
based on the value of enhanced recreational fishing opportunities. Specifically, the elimination of
pollutant concentrations exceeding AWQC limits for protection of aquatic species and human health
is expected to generate benefits to recreational anglers. Such benefits are expected to manifest as
increases  in the value of the fishing experience per  day fished or the number of days anglers
subsequently choose to fish the cleaner waterways. These benefits, however, do  not include all of
the benefits that are associated with improvements in aquatic life. For example, recreational benefits
do not capture the benefit of increased assimilative capacity of a receiving waterbody, improvements
in the taste and odor of the instream flow, or improvements to other recreational  activities such as
swimming and wildlife observation that may be enhanced by improved water quality.
Table ES-4. Discharge Reaches with Pollutant Concentrations Exceeding Chronic AWQC Limits for
Protection of Aquatic Species, and Reductions Achieved by Regulatory Options
Regulatory Option
Baseline
CP-EL
DAF-BL
Combo-IL
Number of Pollutants
Estimated to Exceed
Chronic AWQC timits
3
2
2
2
Number of Reaches with
Concentrations Exceeding
Chronic AWQC Limits
78
12
12
12
Totail Exceedences of Chronic
AWQC Limits
93
19
19
19
None of the acute AWQC limits were estimated to be exceeded in the baseline.
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Benefits from Reduced Cost of Sewage Sludge Disposal and Reduced Incidence of Inhibition

       EPA expects that reduced effluent discharges from the industrial laundry industry would also
yield economic productivity benefits. For this analysis, EPA estimated productivity benefits for two
benefit categories: reduced pollutant contamination of effluent discharged by industrial laundry
facilities to sewage treatment systems and associated savings in sewage sludge use or disposal costs;
and, a reduction in biological inhibition of activated sludge. For the former category, EPA examined
the following: (1) whether industrial laundry baseline discharges would prevent POTWs from being
able to meet the metal concentration limits required for certain lower cost sewage sludge use/disposal
practices — beneficial land application and surface disposal; and (2) whether limitations on the
selection of management practices would be removed under regulatory options.

       EPA has promulgated regulations establishing standards for sewage when it is applied to the
land, disposed of at dedicated sites (surface disposal), and incinerated (40 CFR Part 503). For land
application, the regulations include three sets of pollutant concentration limits for ten metals: (1)
Pollutant Ceiling Limits, which all land-applied sewage sludge must meet with certain limitations, (2)
Cumulative Pollutant Loading Limits (which limit the cumulative amount of metal which may be
applied to the soil) and (3) more stringent Pollutant Concentration Limits,  which provide more
favorable terms for land application of sewage sludge.

       EPA estimated sewage sludge concentrations often metals for sample facilities under baseline
and post-regulatory options discharge levels. EPA compared these concentrations with the relevant
metal concentration limits for the following sewage sludge management options: Land Application-
High (Concentration Limits), Land Application-Low (Ceiling Limits), and Surface Disposal.  In the
baseline case, EPA estimated that concentrations of one pollutant (lead) at ten POTWs would fail the
Land Application-High limits while meeting the Land Application-Low limits. EPA estimated that
no POTWs would fail any of the Surface Disposal limits.  Under all three regulatory options, EPA
estimated that all ten POTWs would meet the Land Application-High limits.  EPA expects that an
estimated 6,200 dry metric tons (TDMT) of annual disposal of sewage sludge would newly qualify
for beneficial use under the Land Application-High limits as a result of the industrial laundry
regulation. By meeting the more stringent Land Application-High Criteria, EPA expects that POTWs
will benefit by reduced record-keeping costs and generally, greater flexibility in management of
sewage sludge.

       EPA estimated inhibition of POTW operations by comparing predicted POTW influent
concentrations to available inhibition levels for 45 pollutants (not including oil and grease).  At
current discharge levels, EPA estimates POTW concentrations of lead exceed biological inhibition
criteria at two POTWs. Under all treatment options, inhibition problems are eliminated.

        EPA based the POTW inhibition and sludge values upon engineering and health estimates
contained in guidance or guidelines published by EPA and other sources because the values used in
this analysis are not, in general, regulatory values. EPA did not base the proposed pretreatment
discharge standards directly on this approach.  However, the values and methodology used in this
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analysis are helpful in identifying potential benefits for POTW operations and sludge disposal that may
result from the compliance with proposed pretreatment discharge requirements.

Discussions with POTW Operators and Pre-Treatment Coordinators

       To understand the frequency and characteristics of problems to POTWs resulting from
industrial laundry discharges, EPA spoke to POTW pre-treatment coordinators in EPA's regional
offices and in states and to individual POTW operators.  Several pre-treatment coordinators and
operators recommended other sources  to call for more information on the subject.  In  these
conversations, EPA discussed 40 POTWs that receive discharges from industrial laundries. Of these
40 POTWs, 11 were described as encountering some difficulty resulting from industrial laundry
discharges while 29 reported having no problems from industrial laundry discharges.  Problems
encountered by POTWs include oil and grease, which may clog pipes and pump stations, inhibit
activated sludge, and otherwise inhibit POTW operations; metals, which may also inhibit activated
sludge; and pH fluctuations, which can injure POTW workers and deteriorate concrete pipes and
manholes.
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                                Table of Contents

Executive Summary	'.	 es-1
1. INTRODUCTION	;	1
       1.1 Description of the Industrial Laundry Industry	1
       1.2 Purpose of the Environmental Assessment Document	1
       1.3 Treatment Options Considered for the Industrial Laundry Industry	2
       1.4 Organization of the Environmental Assessment Document	2

2. CHARACTERIZATION OF POLLUTANTS IN        i
       INDUSTRIAL LAUNDRY DISCHARGES 	]	2
       2.1 Chemical Identification	2
       2.2 Compilation of Physical-Chemical and Toxicity Data	3
             2.2.1 Aquatic Life Data	j	3
             2.2.2 Human Health Data	5
       2.3 Categorization Assessment	8
             2.3.1 Acute Aquatic Toxicity	8
             2.3.2 Bioaccumulation Potential	9
       2.4 Assumptions and Limitations	13
             2.4.1 Data Compilation	13
             2.4.2 Categorization Schemes	•	13

3. METHODOLOGY	13
       3.1 Sample Set Data Analysis and National Extrapolation	13
       3.2 Estimated Water Quality Impacts	14
             3.2.1 Impact of Indirect Discharging Facilities on Waterways	14
             3.2.2 Impact of Indirect Discharging Facilities on POTW Operations	18
             3.2.3 Estimating Cancer Risk from Consumption of
                   Chemically Contaminated Fish	19
             3.2.4 Assumptions and Caveats  	;	22

4. DATA SOURCES	:	24
       4.1 Facility-Specific Data	24
       4.2 Waterbody-Specific Data	25
             4.2.1 Streams and Rivers	25
             4.2.2 Lakes	25
             4.2.3 Estuaries and Bays	26
       4.3 Information Used to Evaluate POTW Operations .:	26
       4.4 Chemical Pollutant Decay Data 	27
             4.4.1 Estimated Decay Rates  	'	27
             4.4.2 Decay Rates Calculated from Half-Life Data	28

5. RESULTS	28
       5.1 Reduced Occurrence of Pollutant Concentrations in Excess of AWQC Limits
             for Protection of Human Health	29
       5.2 Reduced Incidence of Cancer from Consumption of Fish	30
       5.3 Reduced Occurrence of Pollutant Concentrations in Excess of AWQC Limits
             for Protection of Aquatic Species	31
       5.4 Analysis of Biological Inhibition at POTWs	32

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      5.5 Analysis of Sludge Disposal Practices	
      5.6 Analysis of Baseline Closures	
      5.7 Efforts to Document POTW Problems from Industrial Laundiy Discharges
             and to Develop Case Studies of Such Problems  	
6. REFERENCES
 35
 37

 37

 41
APPENDIX A: Weighting Techniques for Extrapolating Results from Sample Facilities
              to the Population Level
      A.I Introduction  	
      A.2 Linear Weighting Technique 	
      A.3 Differential Weighting Technique  	
A-l
A-l
A-3
APPENDIX B: Chemical-Specific Data Used in Analyses

APPENDDC C: Pollutant Decay Rates

APPENDIX D: Estimated Health Benefits Based on Alternative Fish Consumption Rates

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1. INTRODUCTION

1.1 Description of the Industrial Laundry Industry

       The industrial laundry industry comprises approximately 1,747 facilities which wash light,
non-industrial items (e.g., linens from hotels, hospitals, and restaurants) and/or heavy, industrial items
(e.g., printer rags, shop towels, and mats).  For this proposed regulation, EPA is considering only
1,606 facilities with annual production greater than or equal tojone million pounds or shop and printer
towel annual production greater than or equal to 255,000 pounds. The industrial laundry facilities
are all indirect dischargers (i.e., each facility discharges to a Publicly Owned Treatment Works
(POTW) as opposed to directly discharging to a waterbody). Currently, approximately 87 percent
of the facilities do not have any wastewater treatment in place. Of the facilities with some treatment
in place, some segregate what they perceive as "heavy" items from "light" items and only treat the
wastewater generated from washing the heavy items.

       At current discharge levels, industrial laundry facilities discharge 4.9 million pounds per year
of priority and nonconventional pollutants (excluding chemical oxygen demand, total organic carbon,
and total petroleum hydrocarbons measured as Silica Gel Treated n-Hexane Extractable Material
(SGT-HEM)) and 35.9 million pounds per year of oil and grease measured as n-Hexane Extractable
Material (HEM), including 13.2 million pounds per year of SGT-HEM.

1.2 Purpose of the Environmental Assessment Document

       The purpose of this Environmental Assessment is to estimate the environmental impact of
industrial laundry  discharges on waterbodies and POTWs under both current conditions  and
conditions  corresponding  to three regulatory options.  First, EPA  established  a  baseline of
environmental effects by modeling current pollutant discharges from industrial laundries.  Then, EPA
modeled changes in pollutant loadings corresponding to the implementation of various regulatory
options to estimate how environmental effects would change with the regulation of industrial laundry
discharges.
are:
       The four types of environmental impacts quantified by EPA in this Environmental Assessment
       estimates of the occurrence of pollutant concentrations in excess of EPA Ambient Water
       Quality Criteria (AWQC) for protection of human health and aquatic species in waterways
       (streams, lakes, and bays and estuaries) receiving discharges (via POTWs) from industrial
       laundries;

       estimates of the occurrence of POTW inhibition problems resulting from industrial laundries'
       discharges;

       estimates of the inability of POTWs to use preferable sewage sludge management or disposal
       methods, i.e., beneficial land application or surface disposal, because of metals discharges
       from industrial laundries; and
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•      estimates of the number of cancer cases attributable to pollutant-tainted fish in waterways
       receiving discharges (via POTWs) from industrial laundries.

1.3 Treatment Options Considered for the Industrial Laundry Industry

       For this rulemaking, EPA evaluated the environmental benefits of controlling the pollutant
discharges from industrial laundry facilities to POTWs through national analyses of the primary
treatment options: organics control only, dissolved air flotation (DAF-EL), chemical precipitation
(CP-IL), and a combined option with either DAF or CP for all wastewater (Combo-IL).  Since EPA
determined that the organics control only option did not remove a greater amount of the organics
than the other options, EPA did not perform a separate environmental assessment for this.

1.4 Organization of the Environmental Assessment Document

       EPA organized this document into five major sections. The first section, which includes this
sub-section, provides a brief description of the industrial laundry industry and the regulatory treatment
options being considered.  The second section provides information on the pollutants found in
industrial  laundry discharges.  The third section describes  the methodology used to estimate
environmental impacts, including extrapolation of sample sets to the national level and estimates of
water quality impacts. The fourth section describes data sources for industrial laundry facilities and
for POTWs. The fifth section presents the results of the environmental assessment. Two appendices
provide further detail on statistical methods and on chemical-specific data used.

2. CHARACTERIZATION OF POLLUTANTS IN INDUSTRIAL LAUNDRY DISCHARGES

       The extent of human and ecological exposure and risk from environmental releases of toxic
chemicals depends on chemical-specific properties, the mechanism and media of release, and site-
specific environmental conditions. Chemical-specific properties include lexicological effects on living
organisms, hydrophobicity/h'pophilicity, reactivity, and persistence.

       The methodology EPA used in assessing the fate and toxicity of pollutants associated with
industrial laundry discharges consists of three steps: (1) chemical identification; (2) compilation of
physical-chemical and toxicity data; and (3) categorization assessment. These steps are described in
detail below. A summary of the major assumptions and limitations associated with this methodology
is also presented.

2.1 Chemical Identification

       From October 1992 through April  1997, EPA conducted  sampling of industrial laundry
facilities located  nationwide to determine the presence or absence of priority, conventional, and
nonconventional pollutants in the industrial laundry discharges. The Agency collected samples of raw
wastewater during eight sampling episodes. EPA used these data and applicable criteria to select 72
pollutants for regulation from the 315 pollutants initially identified as pollutants of concern. EPA was
abb to assess the potential fate and toxicity of 67 of these pollutants, including 31 priority pollutants
(18 priority organics and 13 priority metals), 35 nonconventional pollutants (24 nonconventional

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organics and 11 nonconventional metals), and one bulk nonconventional pollutant (total petroleum
hydrocarbons, measured as SGT-HEM). Exhibit 1 presents the potential fate and toxicity, based on
known characteristics of each chemical, of 67 pollutants of concern.  Although potential fate and
toxicity data are not available for the three conventional and two bulk nonconventional pollutants
(also listed in Exhibit 1), these pollutants are associated with adverse water quality impacts, as
described further below.

2.2 Compilation of Physical-Chemical and Toxicity Data

       The chemical-specific data needed to conduct the fate and toxicity evaluation for this study
include aquatic life criteria or toxic effect data for native aquatic species, human health  reference
doses (RfDs) and cancer potency slope factors (SFs), EPA maximum contaminant levels (MCLs) for
drinking water protection, and bioconcentration factors (BCFs) for native aquatic species.

       Sources of the above data include EPA ambient water quality criteria documents and updates,
EPA's Assessment Tools for the Evaluation  of  Risk (ASTER) and the  associated  AQUatic
Information REtrieval System (AQUIRE) and Environmental Research Laboratory-Duluth fathead
minnow database,,EPA's Integrated  Risk Information System (IRIS), EPA's Health Effects
Assessment Summary Tables (HEAST), EPA's 1991 and 1993 Superfund Chemical Data Matrix
(SCDM), EPA's 1989 Toxic Chemical Release Inventory Screening Guide, Syracuse  Research
Corporation's CHEMFATE and BIODEG databases, EPA and other government reports,  scientific
literature, and other  primary and secondary data sources.  To ensure that the examination is as
comprehensive as possible, EPA took alternative measures to compile data for chemicals for which
physical-chemical property and/or toxicity data are not presented in the sources listed above.  To the
extent possible, EPA estimated values for the chemicals using the quantitative structure-activity
relationship (QSAR) model  incorporated in ASTER, or for some physical-chemical properties,
utilized published linear regression correlation equations.

2.2.1 Aquatic Life Data

       EPA obtained ambient criteria or toxic effect concentration levels for the protection of aquatic
life primarily from EPA's ambient water quality criteria documents and ASTER.   For several
pollutants, EPA has published ambient water quality criteria for the protection of both freshwater and
marine aquatic life from acute and chronic effects. The acute lvalue represents a maximum  allowable
 1-hour average concentration of a pollutant at any time that protects aquatic life from lethality.  The
chronic value represents the  average allowable concentration of a toxic pollutant over a four-day
period at which a diverse genera of aquatic organisms and their uses should not be  unacceptably
affected, provided that these levels are not exceeded more than once every three years.

       For pollutants for which no water quality criteria have been developed, EPA used values from
published aquatic toxicity test data or estimated values from the ASTER QSAR model. In selecting
values from the literature, EPA preferred measured concentrations from flow-through studies under
typical pH and temperature conditions. In addition, the test organism must be a North  American
resident species offish or invertebrate.  The hierarchies used by EPA to select the appropriate acute

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 and chronic values are listed below in descending order of priority.

 Acute Aquatic Life Values
       •      National acute water quality criteria;
       •      Lowest reported acute test values (96-hour LCSO for fish and 48-hour EC50/LCSO for
              daphnids);
       •      Lowest reported LC50 test value of shorter duration, adjusted to estimate a 96-hour
              exposure period;
       •      Lowest reported LC50 test value of longer duration, up to a maximum of two weeks
              exposure; and,
       •      Estimated 96-hour LC50 from the ASTER QSAR model.

 Chronic Aquatic Life Values

       •      National chronic water quality criteria;
       •      Lowest reported maximum allowable toxic concentration (MATC), lowest observable
              effect concentration (LOEC), or no observable effect concentration (NOEC);
       •      Lowest reported chronic growth or reproductive toxicity test concentration; and,
       •      Estimated chronic toxicity concentration from a measured acute to chronic ratio for
              a less sensitive species; a quantitative structure-activity relationship (QSAR) model;
              or a default acute to chronic ratio of 10:1.

 Chronic Toxicity Values for Total Petroleum Hydrocarbons (TPH)

       Because total petroleum hydrocarbons do not constitute a definitive chemical category, but
 instead include  many organic compounds with varying  physical,  chemical, and toxicological
 properties, it is difficult for EPA to establish a numerical criterion which would be applicable to all
 types of petroleum hydrocarbons.  Given this difficulty and the chronic toxic potential of petroleum
 hydrocarbons, EPA recommends using an application factor of 0.01 and the 96-hr LC50 for a sensitive
 resident species for individual petrochemical components (U.S. EPA, 1987b). EPA compiled lethal
 toxicities of various petroleum products to aquatic organisms (U.S. EPA, 1976).  A wide range of
 toxic effect levels for a variety of petroleum products is reported for all types of organisms evaluated
 (i.e., fish, Crustacea, larvae and eggs, gastropods, bivalves,  invertebrates,  and flora). The most
 sensitive categories of organisms, the marine larvae and benthic invertebrates, appear to be intolerant
 of petroleum products, particularly the water-soluble compounds, at concentrations ranging from 0.1
ppm to 25 ppm and 1 ppm to 6,100 ppm, respectively.  Although most of the reported data are for
marine organisms, Nelson-Smith (1973) states that within a range of limits, "toxicities are much the
same in salt as in freshwater".

       In keeping with the established hierarchy of selecting the lowest reported 24 to 96-hr LC50
for a North American resident species of fish or invertebrate, EPA selected the 96-hr LC50 value of
5.6 mg/L for soluble hydrocarbons to freshwater finfish as representative of TPH toxicity in industrial
laundries. EPA then calculated the chronic aquatic life value of 56 ug/L by applying an application
factor of 0.01.

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Bioconcentration Factor Data

       Bioconcentration factor (BCF) data are available from numerous data sources, including EPA
ambient water quality criteria documents and EPA's ASTER. Because measured BCF values are not
available  for several chemicals, methods  are used to estimate  this parameter based on the
octanol/water partition coefficient or solubility of the chemical. Such methods are detailed in Lyman
et al. (1990). Multiple values are reviewed, and a representative value is selected according to the
following guidelines:

•      Resident U.S. fish species are preferred over invertebrates or estimated values.
•      Edible tissue or whole fish values are preferred over nonedible or viscera values.
•      Estimates derived from octanol/water partition coefficients are preferred over estimates based
       on solubility or other estimates, unless the estimate comes from EPA Criteria Documents.

The most conservative value (i.e., the highest BCF) is selected among comparable candidate values.

       Exhibit B-l in Appendix B provides a listing, by pollutant, of acute and chronic aquatic life
values and BCF data used in these analyses.  Freshwater chronic  and acute AWQC limits were
available for 65 and 59 pollutants, respectively, and salt water chronic and acute AWQC limits were
available for 11 and 19 pollutants, respectively.

2.2.2 Human Health Data

       Human health toxicity data include chemical-specific reference doses (RfDs) for non-cancer
effects, and potency slope factors (SFs) for carcinogenic effects. EPA obtained RfDs and SFs first
from EPA's Integrated Risk Information System (IRIS), and secondarily from EPA's Health Effects
Assessment Summary Tables (HEAST). The  RED is an estimate of a daily exposure level for the
human population, including sensitive subpopulations, that is likely to be without an appreciable risk
of deleterious non-cancer health effects over a lifetime (U.S. EPA, 1989a).  A chemical with a low
RfD is more toxic than a chemical with a high RfD. Non-cancer effects include systemic effects (e.g.,
immunological,  neurological,  circulatory,  or respiratory toxicity),  reproductive toxicity, and
developmental toxicity. EPA recommends a threshold level assessment approach for these  systemic
and other effects because several protective mechanisms must be overcome prior to the appearance
of an adverse non-cancer effect. In contrast, EPA assumes that cancer growth can be initiated from
a single cellular event, and therefore should not be subject to a threshold level assessment approach.
The SF is an upper bound estimate of the probability of cancer per unit intake of a chemical over a
lifetime (U.S. EPA, 1989a).  A chemical with a large SF has greater potential to cause cancer than
a chemical with a small SF.

       For this analysis, human health criteria values are developed for two exposure  routes: (1)
ingesting the pollutant via contaminated aquatic organisms only (carcinogens and noncarcinogens),
and (2) ingesting the pollutant via both water and contaminated aquatic organisms (noncarcinogens
only).  The equations for developing the values are presented below.

-------
 For Non-cancer Protection (ingestion of organisms only)
                                   HH   =
                                           IRf • BCF
 where:
       RfD   =
       IRf    =
       BCF   =
       CF    =
              human health value (ug/L),
              reference dose (mg/day),
              fish ingestion rate (kg/day),
              bioconcentration factor (L/kg), and
              conversion factor for units (1,000 ug/mg).
For Carcinogenic Protection (ingestion of organisms only)
                                „„     BW • RL •  CF
                                ttti   = 	
                                   00    SF • IRf • BCF
where:
       HHoa   =     human health value (ug/L),
       BW    =     body weight (kg),
       RL    =     risk level,
       SF    =     cancer slope factor (mg/kg-day)"1,
       IRf    =     fish ingestion rate (kg/day),
       BCF   =     bioconcentration factor (L/kg), and
       CF    =     conversion factor for units (1,000 ug/mg).

For Non-cancer Protection (ingestion of water and organisms)
                                           RfD - CF
                                       IRW + (IRf • BCF)
where:
HHM,  =
RfD   —
IRW    =
IRf    =
BCF   —
CF    =
                    human health value (ug/L),
                    reference dose (mg/day),
                    water ingestion rate (L/day),
                    fish ingestion rate (kg/day),
                    bioconcentration factor (L/kg), and
                    conversion factor for units (1,000 ug/mg).
       The values for ingesting water and organisms are derived by assuming an average daily
ingestion rate of 2 L of water, an average daily fish consumption rate of 6.5 g, and an average adult

-------
body weight of 70 kg (U.S. EPA, 1991).  Protective concentration levels for carcinogens are
developed in terms of non-threshold lifetime risk level. EPA chose to develop criteria at a risk level
of 10"6 for this analysis. This risk level indicates a probability of one additional case of cancer for
every 1,000,000 persons exposed.                       •'

       The hierarchy used to select the most appropriate human health criteria values is listed below
in descending order of priority:

•      Calculated human health criteria values using EPA's Integrated Risk Information System
       (IRIS) reference doses (RfDs) or slope factors (SFs) used in conjunction with adjusted three
       percent lipid BCF values derived from Ambient Water Quality Criteria Documents (U.S.
       EPA, 1980); three percent is the mean lipid content of fish tissue reported in the study from
       which the average daily fish consumption rate of 6.5 g/day was derived;

•      Calculated human health criteria values using current IRIS RfDs or SFs and representative
       BCF values for common North American species of fish or invertebrates or estimated BCF
       values;                                         '•

•      Calculated human health  criteria values using RfDs or  SFs  from EPA's Health Effects
       Assessment Summary Tables (HEAST) used in conjunction with adjusted three percent lipid
       BCF values derived from Ambient Water Quality Criteria Documents (U.S. EPA, 1980);

•      Calculated human health criteria values using current RfDs or  SFs from HEAST  and
       representative BCF values for common North American species of fish or invertebrates or
       estimated BCF values;

•      Criteria guidance from the Ambient Water Quality Criteria Documents (U.S. EPA, 1980);
       and,

•      Calculated human health values using RfDs or SFs from data sources other than IRIS or
       HEAST.

       This hierarchy is based on Section 2.4.6 of the Technical Support Document for Water
Quality-based Toxics Control  (U.S. EPA, 1991), which recommends using the most  current  risk
information from IRIS when estimating human health risks. In cases where chemicals have both RfDs
and SFs from the same level of the hierarchy, EPA calculated ihuman health values for both types of
toxicity effects. Exhibit B-2 in Appendix B provides a listing, by pollutant, of human health  risk
values used in these analyses.                            '

       For the pollutant arsenic, 30 states have adopted a less stringent human health criteria value
for arsenic ingestion via both water and contaminated aquatic ^organisms. For those states, the state
criteria values were used in this analysis. (See Exhibit B-2 for a list of the states and their criteria.)

       Other chemical designations related to potential adverse human health effects include EPA
assignment of a concentration limit for protection of drinking  water, and EPA identification as a

-------
hazardous air pollutant (HAP) in wastewater, or a pollutant  regulated under  the Resource
Conservation and Recovery Act (RCRA). EPA establishes drinking water criteria and standards,
such as the maximum contaminant level (MCL), under authority of the Safe Drinking Water Act
(SDWA).  Current MCLs are available from IRIS.  A set of 189 hazardous air  pollutants are
identified in the Clean Air Act.  The Office of Air Quality Planning and Standards  (OAQPS) has
reduced the set of 189 pollutants to produce a draft list of 111 pollutants that are considered to be
hazardous air pollutants when present in wastewater (McDonald,  1994).  OAQPS eliminated
pollutants that are inorganic, do not persist in water (short half-life),  or have a Henry's Law constant
less than 0.1 atm/mole fraction (approximately 2 x 10'6 atm-m3/mol).  RCRA pollutants are listed in
Appendix VHI to that regulation.

2.3 Categorization Assessment

       The objective of this generalized evaluation of fate and toxicity potential is to place chemicals
into groups with qualitative descriptors of potential environmental behavior and impact. EPA based
these groups on categorization schemes derived for:

•      Acute aquatic toxicity (highly, moderately, or slightly toxic);  and
•      Bioaccumulation potential (high, moderate, slight, or no significant potential).

       These  categorization schemes  identify the  relative aquatic  toxicity and bioaccumulation
potential for each chemical  associated with industrial laundry discharges.  This evaluation  also
identifies chemicals which: (1) are known or probable human carcinogens; (2) are systemic human
health toxicants; (3) have EPA human health drinking water standards; (4) are tentatively designated
as HAPs in wastewater by OAQPS; and (5) are RCRA pollutants. The results of this analysis can
provide a qualitative indication of potential risk posed by the release of these chemicals. Actual risk
depends on the magnitude, frequency, and duration of pollutant loading; site-specific environmental
conditions; proximity and number of human and ecological receptors; and relevant exposure
pathways. The following discussion outlines the categorization schemes. Ranges of parameter values
defining the categories are also presented.

2.3.1 Acute Aquatic Toxicity

Key Parameter:      Acute aquatic life criteria, LC50, or other benchmark (AT) (ug/L)

       Using acute criteria or lowest reported acute test results  (generally 96-hour and 48-hour
durations for fish and invertebrates, respectively), EPA grouped chemicals according to their relative
short-term effects on aquatic life.
Categorization Scheme:
AT < 100
100^ AT <; 1000
AT > 1000
Highly toxic
Moderately toxic
Slightly toxic

-------
       This scheme, used as a rule-of-thumb guidance by EPA's Office of Pollution Prevention and
Toxics (OPPT) for Premanufacture Notice (PMN) evaluations, is used to indicate chemicals that
could potentially cause lethality to aquatic life downstream of discharges.

2.3.2 Bioaccumulation Potential
Key Parameter:
Bioconcentration Factor (BCF) (L/kg)
               Equilibrium chemical concentration in organism (mg/kg, wet weight)
             —	—	:	:	
                          Mean chemical concentration in water (mg/L)
       BCF is a good indicator of a chemical's potential to accumulate in aquatic biota through
uptake across an external surface membrane.

Categorization Scheme:
BCF > 500           High potential
50 <; BCF <500       Moderate potential
5 < BCF 
-------
aeration due to the creation of a surface film. Oil and grease can also have detrimental effects on
waterfowl by destroying the buoyancy and insulation of their feathers.  High COD and BOD levels
can deplete oxygen concentrations, which can result in mortality or other adverse effects on fish.
                                            10

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-------
2.4 Assumptions and Limitations

       The major assumptions and limitations associated withithe data compilation and categorization
schemes are summarized in the following two sections.

2.4.1  Data Compilation

•      If data are readily available from electronic databases, other primary and secondary sources
       are not searched.

•      Many of the data  are estimated and  therefore can have a high degree of associated
       uncertainty.

•      For some chemicals,  neither measured nor estimated data are available for key categorization
       parameters. In addition, chemicals identified for this study do not represent a complete set
       of wastewater constituents. As a result, this study is an incomplete assessment of industrial
       laundry wastewater.

2.4.2  Categorization Schemes                         I

•      Receiving waterbody characteristics, magnitude of pollutant loadings, exposed populations,
       and potential exposure routes are not considered.

•      Placement into groups is based on order-of-magnitude data breaks for several categorization
       schemes.    Combined with  data  uncertainty,  this  may  lead to an overstatement or
       understatement of the characteristics of a chemical.

•      Data derived from laboratory tests may not accurately reflect conditions in the field.

•      Available aquatic toxicity and bioconcentration test data may not represent the most sensitive
       species.

3. METHODOLOGY

3.1 Sample Set Data Analysis and National Extrapolation

       EPA based the analyses in this Environmental Assessment on data from 172 industrial laundry
facilities that it surveyed as the basis for the economic, engineering, and environmental analyses being
performed in support of the industrial laundry regulation.  EPA estimates that these  172 facilities
represent 1,606 industrial laundry facilities nationwide. All sample facilities are indirect dischargers
(e.g., each facility discharges to a POTW as opposed to directly discharging to a waterbody). EPA
evaluated impacts of industrial laundry discharges on POTW operations, human health, and aquatic
life under baseline discharge conditions and under the three treatment technology options. Because
of incomplete information  on the POTWs to which some  of the sample facilities discharge, EPA
deleted 33  facilities from the analysis.  EPA  used the procedure  for addressing item level
                                            13

-------
nonresponse, outlined in Steps to Generate National Estimates of Means and Totals (SAIC, 1996),
to adjust the sample weights for the remaining facilities in each affected stratum. The sample weight
adjustment has the effect of assigning the sample mass for a lost observation(s) to the remaining
observations in the affected stratum. As a result, EPA performed analyses on 139 sample facilities
discharging to 118 POTWs.

       Appendix A provides further detail on  the simple linear weighting technique  and the
differential weighting technique used to extrapolate results estimated for the sample facilities to the
population level.

3.2 Estimated Water Quality Impacts

       EPA estimated water quality impacts of indirect dischargers on POTW operations and their
receiving waterways by using various modeling techniques. EPA quantified the releases of 72
pollutants of concern under both current (baseline) conditions and the three treatment technology
options. EPA then evaluated site-specific potential aquatic life and human health impacts resulting
from current and proposed pollutant releases. EPA compared projected water concentrations for
each pollutant to EPA water quality criteria, or to toxic effect levels (i.e., lowest reported or
estimated toxic concentration) for pollutants for which no water quality criteria have been developed.
EPA also made estimates of cancer cases attributable to the consumption of contaminated fish. The
analyses of impacts of industrial laundry discharges on POTW operations include estimates of the
occurrence of biological inhibition and estimates of limitations on the ability of POTWs to adopt most
favorable practices for use or disposal of sewage sludge.  EPA performed these  analyses for the
stratified random sample set of 139 industrial laundry facilities discharging to  118  POTWs that, in
turn, discharge to  113 waterbodies (88 rivers/streams, 21 bays/estuaries, and 4 lakes). As described
above, EPA extrapolated the  results of this analysis to the entire population of industrial laundry
facilities nationwide (approximately 1,606 facilities discharging to 1,178 POTWs, which in turn
discharge to 1,133 waterbodies)1.

3.2.1 Impact of Indirect Discharging Facilities on Waterways

       EPA used four different equations to model the impacts of indirect  industrial laundry
discharges on receiving waterways.  For POTWs that discharge into streams or rivers, EPA used a
simple stream dilution model that does not account for fate processes other than complete immediate
mixing. The facility-specific data (i.e., pollutant loading, operating days, and facility flow) used in
this equation are derived from sources described in Sections 4.1 and 4.2 of this report. One of three
receiving stream flow conditions (the lowest 1-day average flow with a recurrence interval of 10 years
(1Q10), the lowest consecutive 7-day average flow with a recurrence interval of 10 years (7Q10),
        The extrapolation results in the 92 freshwater sites representing 1,009 freshwater sites nationwide and the 21 marine sites
representing 124 marine sites nationwide.  It is important to note that the sample weights used in this extrapolation are based on
engineering and economic characteristics of the industrial laundry sample facility, not on the type of waterbody to which the receiving
POTW discharges. Therefore, although the 1,178 POTWs are discharging to 1,133 waterbodies, the actual distribution of freshwater
and marine waterbodies may vary from the numbers predicted in the extrapolation.

                                             14

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and the harmonic mean flow) is used, depending on the type of criterion or toxic effect level intended
for comparison.  The 1Q10 and 7Q10 flows are used in comparisons of instream concentrations with
acute and chronic aquatic life criteria or toxic effect levels, respectively, as recommended in the
Technical Support Document for Water Quality-based Toxics Control (U.S. EPA, 1991).  The
harmonic mean flow, defined as the inverse mean of reciprocal daily arithmetic mean flow values, is
used in comparisons of instream concentrations with human health criteria or toxic effect levels based
on lifetime exposure. EPA recommends the long-term harmonic mean flow as the design flow instead
of the arithmetic mean flow for assessing potential long-term human health impacts because instream
pollutant concentration is a function of, and inversely proportional to, the streamflow downstream
of the discharge.

       The event frequency represents  the  number of times an exposure event occurs during a
specified time period. For assessing impacts on aquatic life, EPA set the event frequency equal to
the facility operating days. The calculated instream concentration is thus the average concentration
on days the facility is discharging wastewater. For assessing long-term human health impacts, EPA
set the event frequency at 365 days.  The calculated instream concentration is thus the average
concentration on all days of the year. Although this leads to a lower calculated concentration because
of the additional dilution from days when the facility  is not operating,  it is consistent with the
conservative assumption that the target population is present to consume drinking water every day
and contaminated fish throughout an entire lifetime.       ;

                              r  _       L -(l-TMT),
 where:
       Cis
       L
       TMT
       OD
       PF
       EF
       SF
                                    (OD • PF) + (EF • SF)
instream pollutant concentration (ug/L),
facility pollutant loading (ug/yr),
POTW treatment removal efficiency (unitless),
facility operating days (days/yr),
POTW flow (L/day),
event frequency (days/yr), and
receiving stream flow (L/day).
       For POTWs that discharge into relatively small lakes, EPA used the following simple steady-
state model which takes into account pollutant degradation! and the hydraulic residence time of the
lake:
                                   'lake
                                          (1 + Tw • k)
where:
                                           15

-------
                                               V
and where:
       Qofar
       c,
       Tw
       k
       V
       Q
steady-state lake concentration of pollutant (ug/L),
steady-state inflow concentration of pollutant (ug/L),
mean hydraulic residence time (yr),
first-order pollutant decay rate (yr"1),
lake volume (m3), and
mean total inflow rate (m3/yr).
       For hydrologically complex waters such as bays and estuaries, EPA used alternative means
to predict pollutant concentrations that are suitable for comparison with ambient criteria or toxic
effect levels for facilities discharging to these types of waterbodies. The first choice is to employ site-
specific critical dilution factors (CDFs) to predict the concentration at the edge of a mixing zone. The
second choice is to use estuarine dissolved concentration potentials (DCPs).

       EPA obtained site-specific CDFs from a survey of States and Regions conducted by EPA's
Office of Pollution Prevention and Toxics (Mixing Zone Dilution Factors for  New Chemical
Exposure Assessments, U.S. EPA, 1992a). The dilution model for estimating estuary concentrations
by using a CDF is presented below.

                                  -   _   L •  (1-TMT)
where:
       L
       TMT
       EF
       PF
       CDF
                                        EF •  PF • CDF
estuary pollutant concentration (ug/L),
facility pollutant loading (ug/yr),
POTW treatment removal efficiency (unitless),
event frequency (days/yr),
POTW flow (L/day), and
critical dilution factor (unitless).
       EPA used acute CDFs to evaluate acute aquatic life effects and chronic CDFs to evaluate
chronic aquatic life or adverse human health effects. EPA assumed that the drinking water intake and
fishing location are at the edge of the chronic mixing zone.  EPA set the event frequency equal to
the facility operating days for comparison with aquatic life criteria or toxic effect levels, and equal
to 365 days for comparison with human health criteria or toxic effect levels.

       The National Oceanic and Atmospheric  Administration (NOAA) has developed DCPs to
predict pollutant concentrations in various  salinity zones for each estuary in NOAA's National
Estuarine Inventory (NEI). A DCP represents the concentration of a nonreactive dissolved substance

                                           16

-------
under well-mixed, steady-state conditions given an annual load of 10,000 tons.  DCPs account for
the effects of flushing by considering the freshwater inflow rate, and dilution by considering the total
estuarine volume.  DCPs reflect the predicted estuary-wide response, and, therefore, may not be
indicative of concentrations at the edge of much smaller mixing zones. The dilution model used for
estimating pollutant concentrations using a DCP is presented below.

                                c  =  L •  (l-TMT) • DCP
                                           BL • CF
where:
       Ces     =     estuary pollutant concentration (ug/L),
       L      =     facility pollutant loading (kg/yr),
       TMT   =     POTW treatment removal efficiency (unitless),
       DCP   =     dissolved concentration potential (ug/L),
       BL     =     benchmark load (10,000 tons/yr), and
       CF    =     conversion factor (907.2 kg/ton). ,

       EPA compared projected waterway pollutant concentrations to EPA water quality criteria or
toxic effect levels for the protection of aquatic life and human health to determine potential water
quality impacts. EPA  determined water quality  excursions by dividing the projected waterway
pollutant concentration by the EPA water quality criteria or toxic effect levels for the protection of
aquatic life and human health. A value greater than one indicates an excursion.
                                           17

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3.2.2  Impact of Indirect Discharging Facilities on POTW Operations

 Analysis of Biological Inhibition

       Inhibition of POTW operations occurs when high levels of toxics, such as metals or cyanide,
kill bacteria that are required for the wastewater treatment process.  EPA analyzed inhibition of
POTW operations by comparing calculated POTW influent concentrations with available inhibition
levels. Excursions are indicated by a value greater than one. POTW influent concentrations are
estimated as:
                                  C . =	
                                    pl    OD • PF
where:
       OD   =
       PF
POTW influent concentration (ug/L),
facility pollutant loading (ug/yr),
facility operating days (days/yr), and
POTW flow (L/day).
Analysis of Sludge Disposal Practices

       EPA also analyzed the effects of industrial laundry discharges on POTW operations by
comparing the estimated concentrations of metals in sewage sludge with the published metals
concentration limits for preferable sewage sludge disposal or use practices.  In particular, EPA
examined: (1) whether industrial laundry baseline discharges would prevent POTWs from being able
to meet the metals concentration limits required for certain more favorable and lower cost sewage
sludge use/disposal practices, i.e., beneficial land application and surface disposal; and (2) whether
limitations on the selection of management practices would be removed under regulatory options.
EPA estimated sewage sludge concentrations of ten metals for sample facilities under baseline and
post-regulatory option discharge levels. EPA compared these concentrations with the relevant metals
concentration limits for the following sewage sludge management options: Land Application-High
(Concentration Limits), Land Application-Low (Ceiling Limits), and Surface Disposal.  Metal
concentrations in sewage sludge are estimated as:
                                      L •  TMT • PART • SGF
                                             OD • PF
                                           18

-------
where:
       C5p    =     sewage sludge pollutant concentration (mg/kg),
       L     =     facility pollutant loading (ug/yr),
       TMT  =     POTW treatment removal efficiency (unitless),
       PART =     pollutant-specific sludge partition factor (unitless),
       SGF  =     sludge generation factor (mg/kg per ug/L),
       OD   =     facility operating days (days/yr), and
       PF    =     POTW flow (L/day).              :

       EPA derived the~Tacility-specific  data to evaluate POTW operations from the sources
described in Sections 4.1 and 4.2. For industrial laundry facilities that discharge to the same POTW,
EPA summed the individual loadings before the POTW influent and sewage sludge concentrations
were calculated.

       The partition factor is a chemical-specific value that represents the fraction of the load that
is expected to partition to sewage sludge during wastewater treatment. For predicting sewage sludge
generation, EPA used 1988 data on volume of sewage sludge produced (Federal Register, February
19,1993, p. 9257) and volume of wastewater treated (1988 Needs Survey, Table C-3), resulting in
a sludge generation factor of 7.4 mg/kg per  ug/L:        :
         28.736 x Kfgallday
          5,357,200  DMTIyr
365 day    1 DMT .  3.79 L m   1 mg chemical
  1 yr
 1000 kg    1  gal    1000 ug chemical
 7.4 mg chemical/kg sludge
1 ug chemicallL wastewater
       For every 1 ug/L of pollutant removed from wastewater and partitioned to sewage sludge,
the concentration in sewage sludge is 7.4 mg/kg dry weight.

Documented Impacts of Industrial Laundry Discharges on POTWs

       To understand the frequency and characteristics of problems to POTWs resulting from
industrial laundry discharges, EPA obtained information froni discussions with EPA regional staff and
POTW operators.  Of 37 POTWs that receive discharges from industrial laundries and were
contacted by EPA, 11 POTW operators described their facilities as encountering some difficulty
resulting  from industrial laundry discharges,  while the remaining 26 reported no problems from
industrial laundry discharges.

3.2.3  Estimating Cancer Risk from Consumption of Chemically Contaminated Fish

       The analysis of reduced annual occurrence of cancer in exposed populations  via the fish
consumption  pathway involves three  analytic steps: (1)  estimating,  from reduced  pollutant
contamination of fish, the reduced lifetime risk of developing cancer for an individual within the
exposed population; (2) estimating the size of the population that would be expected to benefit from

                                           19

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 reduced pollutant contamination offish; and (3) calculating the annual change in the number of cancer
 events in the exposed population.

         The estimated marginal risk to an individual of developing cancer is based on the quantity of
 carcinogenic chemicals that IL facilities discharge to waterways, the bioaccumulation of discharged
 chemicals  in fish tissue, the cancer-related effects of the discharged chemicals, and the rate of
 consumption of chemically contaminated fish. For each sample IL facility and the waterway to which
 it discharges, EPA calculated baseline and post-compliance marginal cancer risk for two population
 classes that differ based on fish consumption rates: recreational anglers and subsistence anglers.

         As described in Section 3.2.1, for  all IL chemicals for which a quantitative relationship
 between ingestion  rate and annual probability of developing cancer has  been estimated,  EPA
 calculated the pollutant concentrations for each EL facility, using a simplified waterway dilution
 model.  Then, two different risk values were estimated for subsistence fishing households and
 recreational fishing households.  The risks differ in the assumed consumption rates and exposure
 durations of the respective populations. Persons living in subsistence fishing households  were
 assumed to consume 140 grams per day (0.14 kg/day) of fish over 70 years of exposure. The risks
 to recreational fishing households were estimated based on consumption of 30 grams of fish per day
 (0.030 kg/day) over a 30-year period and 6.5 grams per day (0.0065 kg/day) over a 40-year period.
 To  estimate the annual increased risk of cancer in recreation and subsistence anglers and their
 families, the lifetime risk values were then divided by 70 years (an estimate of lifetime).  The marginal
 annual risk of developing cancer from exposure to more than one EL pollutant was assumed to be the
 sum of the marginal annual risks from all pollutants.

 Estimating the Population Expected to Benefit from Reduced Contamination of Fish

        The population exposed to chemically contaminated fish and thus expected to benefit from
 reduced EL discharges includes recreational and subsistence anglers who fish EL reaches, as well as
 members of such anglers' households.2  A "reach" is defined as a specific length of river, lake
 shoreline, or marine coastline, and an "EL reach" is a reach to which an EL facility discharges.3 The
 geographical area from which anglers would travel to fish a reach is assumed to include only those
 counties that abut a given reach.4 Estimating the number of persons fishing a reach involved the
        2
        The exposed, and thus potentially benefitting, population would also include a category of "all other individuals"
who consume freshwater and estuarine fish. Although these individuals are expected to have a much lower average daily
consumption rate, they nevertheless would likely receive some benefit from reduced exposure to pollutants through fish
consumption. This analysis omits this consumption category and the associated benefit estimate.
       3
        1 AH IL facilities considered in this analysis discharge to POTWs, which in turn discharge to waterways. The
relevant IL reach for this analysis is therefore the reach to which the receiving POTW discharges. All analyses of in-
waterway concentrations and related impacts are post-POTW and reflect the removal of pollutants at the POTW.

         This assumption is based on the finding in the 7997 National Survey of Fishing, Hunting, and Wildlife-
Associated Recreation that 65 percent of anglers travel less than 50 miles to fish (U.S. Department of the Interior,

                                             20

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following steps:

       Estimating the Licensed Fishing Population in Counties Abutting IL Reaches.  To estimate
the number of anglers fishing an IL reach, EPA first estimated the number of fishing licenses sold in
the counties abutting the reach. This number was assumed to approximate the number of anglers
residing in the abutting counties. Sample IL facilities were located in 41 states.  Due to time and
resource constraints, it was not possible to collect fishing license data at the county level for all 41
states.  Thus, EPA used the state level data to estimate the number of fishing Licenses per county.
Total state licenses were apportioned to counties based on the ratio of total population in the county
abutting a discharge reach to total state population. Where an IL reach spans more than one county,
fishing licenses were summed across all counties abutting the discharge reach.

       Estimating the Population of Subsistence Anglers in Counties Abutting IL Reaches. Although
fishing  licenses may be sold  to subsistence anglers, many such anglers do  not purchase fishing
licenses. Thus, the magnitude of subsistence fishing is not generally known. For this analysis, EPA
assumed that subsistence anglers would constitute an additional 5 percent of the licensed fishing
population.5                                              ;

       Estimating the Fraction of the Fishing Population that Fish an IL Reach. EPA assumed that
anglers residing within counties abutting a discharge reach are distributed evenly to all reach miles.
Thus, the number of anglers who fish an EL reach was estimated by computing the length of the reach
as a percentage of total reach miles within corresponding counties and multiplying the estimated ratio
by the total fishing population in counties abutting the reach. ;

        Adjusting  for Fish Advisories.  For IL reaches where fish advisories are in place, EPA
assumed that some proportion of anglers would adhere to the  advisory and not fish those reaches.
Based on the existing studies, EPA assumed that recreational fishing would be 20 percent less on
reaches subject to an advisory.6 EPA further assumed that;fish advisories  do not affect fishing
participation by subsistence anglers; thus, no adjustment was made for this population.

        Including Family Members in the Exposed Population  Estimates. For each IL reach, EPA
multiplied the estimated numbers of recreational and subsistence anglers by the corresponding size
of the  average household in each state in 1993, based on Current Population Reports (Statistical
Abstract of the US, 1993).  These calculations yielded the household populations of recreational and
1993).

        It is important to estimate recreational and subsistence populations separately because fish consumption rates for
subsistence anglers are considerably higher than those for recreational anglers.
       TFor a detailed discussion of estimation of the fraction of anglers adhering to the fish advisories, see the
Regulatory Impact Analysis of Proposed Effluent Limitations Guidelines and Standards for the Metal Products and
Machinery Industry (Phase I) (U.S. EPA, 1995).

                                             21

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subsistence anglers who are estimated to consume fish from the reach.

3.2.4 Assumptions and Caveats

       A discussion of the major assumptions and caveats in these analyses follows.

Other Source Contributions

       For the analyses described above, EPA attempted to account for "other source contributions"
of industrial  laundry  pollutants to estimate  the concentrations of these pollutants at relevant
measurement points. Accounting for the discharges from other sources is important because the
assessment of gains in these analyses — that is, from reduction of POTW inhibition, improved sewage
sludge management practices, and reduced exceedance of AWQC limits — depends on comparisons
of estimated pollutant  concentration values with applicable thresholds and identifying situations in
which threshold criteria are failed in the baseline case but met under a regulatory option. In such an
analytic framework, failure  to  account for  other source contributions is likely to lead to  an
underestimate of the  environmental problems that may be ameliorated by the regulation under
analysis.  EPA attempted to estimate other  source contributions  to sample POTWs based on
discharge information for major manufacturing facilities received by EPA in the Toxics Release
Inventory (TRT). However, data limitations prevented the completion of this analysis. For example,
only approximately one-third of the pollutants of concern for industrial laundries  are reported under
TRI.  Furthermore, EPA could not assign TRI discharge values to all of the  sample-associated
POTWs. Thus, background concentrations of each pollutant, both in the receiving stream and in the
POTW influent, are set equal to zero.

Differential Sample-Weighting Technique

       For locations where only one industrial laundry facility discharged to a POTW, the number
of reaches expected to be affected at the national level is simply the sample weight of the facility.
However, national estimates could not be extrapolated directly when more than one industrial laundry
facility discharged pollutants to a single POTW, because the unit of analysis for estimating national
impacts is a POTW, and facility sample weights differ from POTW  sample weights. Thus, for those
POTWs to which more than one facility discharges, the differential sample-weighting technique was
used to account for different sample weights in developing national estimates (see Appendix A).

Waterbody Modeling

       EPA made four major assumptions concerning all waterbody  modeling, and  two major
assumptions specific to stream modeling.  First, EPA assumed  that complete mixing of POTW
discharge flow immediately occurs in the waterbody. This mixing results in the calculation of an
"average" concentration even though the actual concentration may vary across the width and depth
of the waterbody.

       Secondly, EPA assumed the pollutant load to the receiving waterbody is continuous and
                                           22

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representative of long-term facility operations. This assumption may overestimate long-term risks
to human health and aquatic life, but may underestimate potential short-term effects.

       Thirdly, EPA did not consider pollutant fate processes such as sediment adsorption and
volatilization.  This may result in estimated waterbody concentrations that are environmentally
conservative (i.e., higher than may actually exist).

       Fourth, if data on POTW flow were missing, POTW daily flow rates were set equal to the
simple arithmetic mean flow among POTWs associated with sample industrial laundry facilities.

       For modeling streams, EPA used 1Q10 and 7Q10 receiving stream flow rates to estimate
aquatic life impacts, and harmonic mean flow rates to estimate human health impacts. EPA estimated
1Q10 low flows by using the results of a regression analysis conducted for OPPT of 1Q10 and 7Q10
flows from representative U.S. rivers and streams (Versar, 1992).  EPA estimated harmonic mean
flows from the mean and 7Q10 flows as recommended in the Technical Support Document for Water
Quality-based Toxics Control (U.S. EPA, 1991). These flows may not be the same as those used
by specific states to assess impacts.                     ;

       If data on stream flow parameters were missing, EPA set mean and 7Q10 flow values equal
to the corresponding median values associated with sample reaches.

Exposure Analyses

       AWQC for the protection of human health from consumption of organisms reflect both
freshwater and marine organism consumption and thus are used in the analyses for both aquatic and
marine discharge locations. However, EPA assumes that salt water would not be used as drinking
water,  and thus does not analyze the  exceedance  of human health-based AWQC  values for
consumption of organisms and water for marine discharge locations.

       EPA also assumes that the exposure frequency for evaluating human health impacts from
drinking water and contaminated fish ingestion is 365 days, which may overestimate long-term risks
to human health.

Extrapolation from Sample Set to National Level

       The sample set should represent a national group of facilities discharging to waterways and
POTWs.  However, effluent from an individual facility in the sample set may not have a similar
potential environmental impact as effluent from the facilities it is assumed to represent. For example,
a facility that discharges to a stream with a very small design flow may be similar to the facilities it
represents in all aspects except available dilution in the receiving stream.

Estimation of the Exposed Fishing Population

       EPA's estimation of the exposed fishing population relied on state fishing license statistics and
census data. If other factors influence the proportion of anglers in the local population, benefits may
                                           23

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be overstated or understated.  In addition, data limitations hamper the estimate of the number of
anglers who actually fish a given EL reach. Estimating the number of anglers fishing IL reaches based
on the ratio of IL reach length to the total number of IL reach miles in the county recognizes the
effect of the quantity of competing fishing opportunities on the likelihood of fishing a given IL reach,
but it does not account for the differential quality of fishing opportunities.  If water quality in
substitute sites is distinctly better or worse, the estimates of the exposed populations are likely to be
overstated or understated.

       Also, subsistence anglers were assumed to account for an additional 5 percent of the fishing
population. The magnitude of subsistence fishing in the U.S. or in individual states, however, is not
known.  As a result, this estimate may understate or overstate the actual number of subsistence
anglers.

       Finally, to account for the effect of a fish advisory on fishing activity, and therefore on the
exposed fishing population, EPA reduced the fishing population at an IL reach under a fish advisory
by 20 percent.  This could lead to either an overestimate or underestimate of the risk associated with
consumption of contaminated fish, because (1) anglers who change locations may simply be switching
to other locations where advisories are hi place and therefore maintain or increase their current risk,
and  (2) anglers who continue to fish contaminated waters may change their consumption and
preparation habits to reduce the risks from the contaminated fish they consume.

4. DATA SOURCES

       The following four sections describe the various data sources used to evaluate water quality
impacts.

4.1 Facility-Specific Data

       Within EPA's Office of Water, the Engineering and Analysis Division (BAD) provided the
Standards and Applied Science Division (SASD) with projected effluent discharge rates for sample
industrial laundry facilities, days per year wastewater is discharged by facilities, and pollutant loadings
under both current conditions and regulatory options (June, 1997).

       The names, locations, and the flow data for  the POTWs to which the industrial laundry
facilities discharge are obtained from the industrial laundry Screener Questionnaire, Regional EPA
Pretreatment Coordinators,  EPA's  1992 Needs Survey, EPA's Industrial Facilities Discharge
database (IFD), and EPA's Permit Compliance System (PCS).  If these sources did not yield
information for a facility, EPA took alternative measures to  obtain a complete set  of receiving
POTWs.

       EPA used latitude/longitude coordinates (if available) to locate those POTWs that have not
been assigned a reach number in IFD. For those facilities for which the POTW receiving the plant
discharge could not be positively identified, EPA identified the nearest POTW. The identification of
the closest linear distance was based on the latitude/longitude coordinates of the industrial laundry
facility or the city in which it was located.  EPA identified the corresponding reach  in IFD, and

                                           24

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obtained POTW flow from the Needs Survey or PCS.

4.2 Waterbody-Specific Data

4.2.1 Streams and Rivers

       For the 88 streams and rivers modeled, 1Q10, 7Q10, and mean flow data were needed. As
described in Section 3.2.1, the 1Q10 and 7Q10 flows are used to estimate instream concentrations,
which are then  compared  with acute and chronic  aquatic life criteria or toxic effect levels,
respectively.  The mean flow data are used to estimate the harmonic mean flow, defined as the inverse
mean of reciprocal daily arithmetic mean flow values. The harmonic mean flow is used to estimate
instream concentrations which are then compared with human health criteria or toxic effect levels
based on lifetime exposure.

       EPA obtained 7Q10 and mean flow data from either the W.E. Gates study data or from
measured streamflow data, both of which are contained in EPA's GAGE file. The W.E. Gates study
contains calculated average and low flow statistics based on the best available flow data and on
drainage areas for reaches throughout the United States. The GAGE file also includes average and
low flow statistics based on measured data from United States Geological Survey (USGS) gaging
stations. If data on stream flow parameters were missing, EPA set 7Q10 and mean flow values equal
to the corresponding median values associated with the sample reaches.  To estimate 1Q10 flows,
EPA used the results of a regression analysis conducted for OPPT of 1Q10 and 7Q10 flows from
representative U.S. rivers and streams (Versar, 1992). EPA estimated harmonic mean flows from
the mean and 7Q10 flows as recommended in the Technical Support Document for Water Quality-
based Toxics Control (U.S. EPA, 1991).

       For two sample facilities, the POTW outfall pipe was located near the end of the discharge
reach (i.e., within 25 percent of the discharge reach length from the downstream reach).  Therefore,
EPA  used the downstream reach flow  characteristics ' when  comparing estimated  in-stream
concentrations to AWQC protective of aquatic species.  ;

4.2.2 Lakes                                        !

       For relatively small lakes, data on hydraulic residence,time (the amount of time water remains
in a lake) were needed. For relatively large lakes, Critical Dilution Factors (CDFs), which describe
dilution in a portion of a lake, were required. The sample  industrial laundry facilities discharged
indirectly to four lake reaches: one on Lake Onondaga, one on Lake Erie, and two on Lake Michigan.
For Lake Onondaga, the average hydraulic residence time of 94 days was obtained from Russell
Nemecek (315-435-6600) in Onondaga County. For Lake Erie, CDFs were readily available. Given
the size of Lake Michigan and the use of CDFs for Lake Erie, use of a hydraulic residence time was
not appropriate; however, CDFs were not readily available for the two  sample reaches on Lake
Michigan. Therefore, the seven chronic CDFs which were available for reaches discharging to Lake
Michigan (1, 1,4, 4, 10,  10, 4) were arithmetically averaged (U.S. EPA, 1992a, p. A-4) for the two
reaches being modeled.
                                           25

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4.2.3 Estuaries and Bays

       Twenty-one (21) bays and estuaries received indirect discharges from sample industrial
laundry facilities.  To estimate the pollutant concentrations in 18 of these complex water bodies, a
dilution model that predicts pollutant concentrations in the chronic and acute mixing zones based on
site-specific critical dilution factors (CDFs) was used (U.S. EPA, 1992a and Versar,  1994). For four
of the 18 bays/estuaries, both acute and chronic CDFs were available.  For three New York
bays/estuaries, acute and chronic CDFs were estimated by arithmetically averaging available values
for nearby New Jersey sites discharging to the Arthur Kill (acute: 1.5,4.0, 5.0; chronic: 5; 20; 10)
and Upper New York Bay (acute: 8.0; chronic: 22.9).

       For the remaining 11 sample reaches, chronic CDFs could not be identified or approximated,
and thus sample weights were adjusted according to the item level nonresponse methodology (S AIC,
1996). Four of the 11 bays/estuaries had available acute CDFs. For two bays/estuaries in Florida,
acute CDFs were extrapolated from another Florida bay; for four bays/estuaries in California, acute
CDFs were extrapolated from another California bay; and for one bay in Hawaii, the acute CDF was
assumed to be ten.

       For three sample bays/estuaries, dissolved  concentration potential factors (DCPs) were
available from the National Estuarine Atlas of the Strategic Assessment Branch of NOAA's Ocean
Assessments Division. EPA then used a dilution model that predicts  pollutant concentrations in the
estuarine environment using a site-specific DCP factor.

4.3 Information Used to Evaluate POTW Operations

       When data on POTW flow rates were missing, POTW daily flow rates were calculated by
applying the following steps:

1.     Identify whether the POTW with missing information is a minor or major discharger, based
       on the PCS database.7 All POTWs associated with the sample industrial laundries which were
       missing daily flow rate data were classified as minor dischargers in the PCS database.

2.     Calculate  arithmetic mean flow among minor/major POTWs associated  with the sample
       industrial laundry facilities. The estimated arithmetic mean flow for minor POTWs associated
       with the sample industrial laundries is 2.2 million liters per day (MLD).

3.     Set POTW flow rate equal to the relevant arithmetic mean flow. Since all POTWs missing
       flow data were classifed as  minor dischargers, their flow rates were all  set equal to the
       arithmetic mean flow rate for minor POTWs, 2.2 MLD.
       To evaluate POTW operations, EPA also required removal efficiency rates, inhibition values,
       7 According to the PCS classification, municipal dischargers are considered "major" if they discharge more
than 1 million gallons per day.

                                           26

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and sewage sludge regulatory levels. EPA obtained POTW removal efficiency rates from several
sources. EPA developed rates from POTW removal data and pilot-plant studies or used the removal
rate of a similar pollutant when data were not available. Use of the selected removal rates assumes
that the evaluated POTWs are well-operated and have at least secondary treatment in place.

       EPA obtained inhibition values from Guidance Manual for Preventing Interference at POTWs
(U.S. EPA, 1987a) and from CERCLA Site Discharges to POTWs: Guidance Manual (U.S. EPA,
1990).  EPA used the most conservative values for activated  sludge. For pollutants with no specific
inhibition value, a value based on compound type (e.g., aromatics) was used.

       For the ten metals regulated in sewage sludge, EPA used the sewage sludge regulatory levels
from the Federal Register 40 CFR Part 257 et al., Standards for the Use or Disposal of Sewage
Sludge; Final Rules (February 19, 1993) and from the Federal Register 59(38):9095-9099 (February
25,1994) and 60(206):54,764-54,770 (October 25, 1995).  EPA used pollutant limits established for
the final use or disposal of sewage sludge when the sewage sludge is applied to agricultural and non-
agricultural land or is applied to a dedicated surface disposal site. EPA obtained sludge  partition
factors from  the Report to  Congress on the Discharge of Hazardous Wastes to Publicly Owned
Treatment Works (Domestic Sewage Study) (U.S. EPA, 1986).

       Exhibit B-3 in Appendix B provides a listing of POTW treatment removal efficiency rates,
inhibition values, and sewage sludge regulatory levels used  in the evaluation of POTW operations.

4.4 Chemical Pollutant Decay Data

       As presented in Section 3.2, modeling of pollutant discharges to lakes requires an estimate
of the pollutant decay rate in water. For the 24 inorganic pollutants of concern, a decay rate of zero
was conservatively assumed. Due to a lack of readily available data for ten organic pollutants and
the six conventional pollutants, a decay rate of zero was also assumed. For the remaining 32 organic
pollutants, decay rates due to abiotic hydrolysis or biodegradation were used. For six pollutants,
decay rates were readily available from the literature. For the remaining 26 organic chemicals, decay
rates were calculated from data on half-lives or were estimated.  Details of these calculations are
given below.  All of the decay rates used are summarized in Exhibit C-l in Appendix C.

4.4.1 Estimated Decay Rates

       Decay rates were  estimated for the following  four  organic chemicals:  4-chloro-3-
methylphenol, 2-methylnaphthalene, p-cymene, and pentamethylbenzene.

       According to the Hazardous Substances Data Base (1994), Tabak et al. (1981) studied settled
domestic wastewater containing ten parts per million (ppm) of 4-chloro-3-methylphenol.   The
researchers found that 100 percent of this pollutant biodegraded within 14 days. To estimate the
decay rate (£) from this information, a remaining concentration of 0.0001 ppm (one one-thousandth
                                           27

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of one percent of the initial concentration) was assumed:

                           0.0001 ppm  = 10 ppm • e~k'^ days


                               k =  0.8  day'1 = 0.03 hr~l
       For 2-methylnaphthalene, EPA assumed the same decay rate as for naphthalene, based on
structural similarity. For p-cymene, EPA assumed the same decay rate as for p-xylene, again based
on structural similarity. Likewise, for pentamethylbenzene, EPA assumed the same rate as for
benzene (Lyman et al., 1990) based on structural similarity.

4.4.2 Decay Rates Calculated from Half-Life Data

       For 22 chemicals, as noted in Exhibit C-l, the high and low estimates of half-lives presented
in Howard et al., 1991, were converted to decay rates, assuming first-order decay. They then were
arithmetically averaged to obtain an average decay rate:
                                   -In 0.5    ,   ,       -In 0.5
                         ratehigh = —	 and rateiow = —	
                                     high                    low

5. RESULTS

       At current discharge levels, industrial laundry facilities discharge 4.9 million pounds per year
of priority and nonconventional pollutants (excluding chemical oxygen demand, total organic carbon,
and total petroleum hydrocarbons measured as Silica Gel Treated n-Hexane Extractable Material
(SGT-HEM)) and 35.9 million pounds per year of oil and grease measured as n-Hexane Extractable
Material (HEM), including 13.2 million pounds per year of SGT-HEM. The three regulatory options
under analysis considerably reduce these loadings to POTWs. Exhibit 2 summarizes the estimated
industrial laundry discharges in these three pollutant categories, as well as for other conventional and
bulk nonconventional pollutants, on both sample and national level bases for the regulatory options
under analysis.
                                           28

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Regulatory
Option
Baseline
Combo-IL
DAF-IL
CP-IL

Baseline
Combo-IL
DAF-IL
CP-IL
Priority and
Nonconventional
Pollutants*(lb/yr)
Sample
Estimates
608,854
403,213
376,020
376,997
National
Estimates
4,858,790
3,130,211
2,876,415
2,918,186
HEM
(lb/yr)
Sample
Estimates
4,128,803
1,802,227
1,802,227
1,727,221
National
Estimates
35,873,675
15,880,076
15,880,076
15,180,783
SGT-HEM
(lb/yr)
Sample
Estimates
1,577,973
335,772
335,772
306,010
National
Estimates
13,242,020
2,646,313
2,646,313
2,414,526
Biological Oxygen
Demand and Total
Suspended Solids
(lb/yr)
Sample
Estimates
21,760,532
17,425,878
17,168,792
17,422,713
National
Estimates
176,053,618
139,050,357
136,600,985
139,043,890
Chemical Oxygen
Demand and Total
Organic Carbon
(lb/yr)
Sample
Estimates
43,952,456
33,358,162
32,743,837
33,329,832
National
Estimates
345,694,475
258,345,334
252,435,412
258,294,321
* Excludes Total Organic Carbon, Total Petroleum Hydrocarbons measured as Silica Gel Treated n-Hexane
Extractable Material, and Chemical Oxygen Demand.
5.1 Reduced Occurrence of Pollutant Concentrations in Excess of AWQC Limits for Protection
of Human Health

       To assess reduced human health risk from the three regulatory options, the instances in which
pollutant concentrations exceeded AWQC limits for one or more pollutants in the baseline and in
which AWQC limits for all pollutants were met in the post-regulatory option cases were identified.
At current discharge levels,  in-waterway concentrations of two industrial laundry pollutants —
tetrachloroethene and bis(2-ethylhexyl)phthalate — were estimated to exceed AWQC limits for
human health from consumption of water and organisms in two sample reaches. As shown in Exhibit
3, all three options were estimated to eliminate the occurrence of tetrachloroethene concentrations
in excess of AWQC  in all reaches.  All three options also reduced bis(2-ethylhexyl)phthalate
concentrations below AWQCs in one reach.

       In addition, pollutant concentrations  in excess of AWQC values for  human health for
consumption of organisms only were estimated. No pollutant concentrations were found to  exceed
the AWQCs  for organism consumption under baseline discharges.  Note that the AWQC limit
exceedances for organism consumption only forma subset of the AWQC limit exceedances for water
and organism consumption.

       The findings from the analysis of discharge reaches affected by sample facility discharges were
extrapolated  to national estimates using facility sample weights, as described in Section-3.1. As
                                           29

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shown in Exhibit 3, in-waterway, baseline concentrations of three industrial laundry pollutants were
estimated to exceed AWQC limits for human health for consumption of water and organisms in nine
reaches nationwide. All three regulatory options eliminated the occurrence of tetrachloroethene
concentrations in excess of AWQC limits in all reaches. All three regulatory options also eliminated
instances of bis(2-ethylhexyl)phthalate concentrations exceeding AWQC limits in seven reaches.
Exhibit 3; Discharge Reaches wttfe Pollutant Concentrations Exceeding ^WQ£-LJMSte fw^te&fen. '&,
	 :' :;'" " ;M ^ ^^ ^*^ -*
Regulatory Option
Baseline
Streams (No.) _,
Pollutants (No.)
Total Excursions
Combo-TL
Streams (No.)
Pollutants (No.)
Total Excursions
DAF-IL
Streams (No.)
Pollutants (No.)
Total Excursions
CP-IL
Streams (No.)
Pollutants (No.)
Total Excursions
Number of Reaches with Concentrations
Exceeding Health-Based AWQCs
(Sample Basis)
Water and
Organisms
2
2(BEHP,Perc)
3
1
1 (BEHP)
1
1
1 (BEHP)
1
1
1 (BEHP)
1
Organisms Only
0
0
0
0
0
0
0
0
0
0
0
0
Number of Keaches with Concentrations
,Excee4I^Hc»l^.B»s^AW^« , ,
, (National Balis) ^ '- • >
Water and
^Organisms
9
2 (BEHP, Perc)
17
2
1 (BEHP)
2
2
1 (BEHP)
2
2
1 (BEHP)
2
Organisms Only
0
0
0
0
0
0
0
0
0
0
0
0
Note: BEHP is bis(2-ethylhexyl)phthalate and Perc is tetrachloroethene (perchloroethene).

5.2 Reduced Incidence of Cancer from Consumption of Fish

       EPA calculated the cancer cases associated with the pollutant discharges from each facility
by multiplying the annual marginal cancer risk value for the two population classes (i.e., recreational
angler households and subsistence angler households) by the estimated size of each population class
living near the facility. Summing the values for the recreational and subsistence fishing,household
classes yielded the total number of cancer cases associated with the sample facility discharges.
Because these cancer event values apply to sample facilities, EPA extrapolated the sample results to
the total IL population by multiplying the result obtained for each sample facility by its sample weight
and summing the results. These values were calculated for the baseline and post-compliance cases.
The difference is the number of cancer cases estimated to be avoided annually.

       Exhibit 4 indicates the number of cancer cases associated with the IL regulation.  For
                                             30

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combined recreational and subsistence angler populations, EPA estimated that all three options would
eliminate approximately 0.04 cancer cases per year from a baseline value of approximately 0.1 cases,
representing a reduction of about 40 percent.
                Regulatory Option
                 Baseline
                 Combo-IL
                 DAF-IL
                 CP-IL
Number of Cancer Cases
             0.1
            0.06
            0.06
            0.06
                 Carcinogenic Pollutants: Arsenic, Beryllium, Bis (2-ethylhexyl)phthalate,
                 Chloroform, Isophorone, Methylene chloride, Tetrachloroethene, 1,2 -
                 Diphenylhydrazine
5.3 Reduced Occurrence of Pollutant Concentrations in Excess of AWQC Limits for Protection
of Aquatic Species

       The estimated elimination of concentrations in excess of the AWQC values for protection of
aquatic species provides a quantitative measure of ecological benefits stemming from the regulatory
options analyzed.  As shown in Exhibit 5, pollutant concentrations at baseline discharge levels were
predicted to exceed chronic exposure criteria for protection of aquatic  species on nine sample
reaches. These exceedances  are  caused by three pollutants: lead,  silver, and total petroleum
hydrocarbons (TPH). All three regulatory options reduced the concentrations of lead to values below
the chronic AWQC limit; however, on three reaches, the concentrations of silver and TPH remained
above AWQC limits under all three regulatory options.  In this analysis, none of the acute AWQC
limits were exceeded in the baseline.

       Exhibit 5 also summarizes the results extrapolated to the national level. At baseline discharge
levels, 78 reaches nationwide were estimated to exceed chronic AWQC limits for aquatic life due to
industrial laundry discharges.  The exceedances for lead were eliminated by  all three regulatory
options in all 78 reaches. Exceedances of AWQC for silver and TPH were removed in 66 streams
under all three regulatory options.
                                             31

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Exhibit §s Discharge Reaches with Fojtotejit Oojrcenfcr^ttbns
Exceeding Chronic AWQC JLkaits for Protection of -Aijiiajtie Spedc&c
and Reductions Achieved fcy Regfilafory OpMoris ''<."'
Regulatory Option
Baseline
Streams (No.)
Pollutants (No.)
Total Excursions
Combo-IL
Streams (No.)
Pollutants (No.)
Total Excursions
DAF-IL
Streams (No.)
Pollutants (No.)
Total Excursions
CP-IL
Streams (No.)
Pollutants (No.)
Total Excursions
Nnmber of Reaches with Coucetitratidtis ,
Exceeding Chrwte AWQCJfcMfeV '
Sample Basis
9
3 (Pb, Ag, TPH)
11
3
2(Ag,TPH)
4
3
2(Ag,TPH)
4
3
2 (Ag, TPH)
4
National Basis •-',
78
3 (Pb, Ag, TPH)
93
12
2 (Ag, TPH)
19
12
2(Ag,TPH)
19
12
2 (Ag, TPH)
19
None of the acute AWQC limits were estimated to be exceeded in the
baseline. Pb is lead, Ag is silver, and TPH is total petroleum hydrocarbons
          5.4 Analysis of Biological Inhibition at POTWs
                 The effects of industrial laundry discharges on POTW operations were evaluated for 45
          pollutants with inhibition criteria under baseline and post-regulatory option discharge levels. At
          current discharge levels, estimated POTW concentrations of one metal, lead, exceeded biological
          inhibition criteria at one of the 118 POTWs associated with sample industrial laundry facilities. As
          shown in Exhibits 6 and 7, these incidents  were removed under all three regulatory options.
                Sample-level results were extrapolated to the national level by summing over the weights of
          the industrial laundry facilities that discharge to the affected POTWs.  As shown in Exhibits 6 and 8,
          for the baseline  analysis, estimated POTW influent concentrations of lead  exceeded biological
          inhibition criteria at two POTWs;  inhibition criteria were not exceeded under any of the regulatory
          options.  Exhibits 7 and 8 also present the  flow rates (in million liters per day) of the POTWs with
          exceedance events.
                                                     32
,

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Basis for Biological Inhibition Analysis
Number of Facilities:     139          Number of POTWs:
118
Number of Pollutants:
45

Regulatory Option
Baseline
Combo-IL
DAF-IL
CP-IL
Number of POTWs
Estimated to be
Affected by Inhibition
Problems
1(2)
0(0)
0(0)
0(0)
Number of Pollutants
Estimated to Cause an
Inhibition Problem
KD
0(0)
0(0)
0(0)
Total Number of
Exceedance Events
Across All POTWs
and Pollutants
1(2)
0(0)
0(0)
0(0)
                                                 33

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u
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          I

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                                                             I
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5.5 Analysis of Sludge Disposal Practices
       Sewage sludge concentrations often metals were estimated for sample facilities under baseline
and post-regulatory option discharge levels.  These concentrations were compared with the relevant
metals concentration limits for the following sewage sludge management options: Land Application-
High (Concentration Limits), Land Application-Low (Ceiling Limits), and Surface Disposal. In the
baseline case, concentrations of one pollutant, lead, at two sample POTWs were estimated to fail the
Land Application-High limits while meeting the Land Application-Low limits. No POTWs were
estimated to fail any of the Surface Disposal limits. Under all three regulatory options, these two
POTWs were estimated to meet all Land Application-High limits. As a result of the metals discharge
reductions, the previously affected POTWs that would meet all Land Application-Low limits are
candidates for being able to  shift their sewage sludge management options to  the more preferable
beneficial land application methods permitted under the Land Application-High limits. The summary
of limitations on adoption of preferable sewage sludge disposal methods in the baseline case and
alternative regulatory options is presented in Exhibits 9,10, and 11.

       After extrapolating the sample results to the national level, it was estimated that baseline
concentrations of lead would fail to meet Land Application-High limits for sludge disposal at ten
POTWs.  Under all three regulatory options, these ten POTWs were estimated to meet all Land
Application-High limits for lead.  An estimated 6,200 dry metric tons (DMT) of annual disposal of
sewage sludge would be expected to newly qualify for beneficial use under the Land Application-High
limits as a result of these options (see Exhibits 9, 10, and  12).
*  * ,- sup '„ ; ;
0 ^ x *
, ° Category „ ;> „ •
•> " -c * ^* C *• < ' V,
Upgrade from Land Application-Low
limits to Land Application-High limits as a
result of the indicated regulatory option.
Regulatory" •
< Option1
Combo-IL
DAF-IL
CP-EL
Number of
x. £0TWs . \
2(10)
2(10)
2(10)
Associated Sewage
ISWgeCNantit?
k(0MT/Teat)
757 (6,200)
757 (6,200)
757 (6,200)
                                            35

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 Basis for Sludge Contamination Analysis
Number of Facilities:      139         Number of POTWs:
118
Number of Pollutants:
10
Exhibit 10: Summary of Estimated Sewage Sludge Contamination Problems on a£afnple Basis (National Basis)
Regulatory Option
1 "', ' , ":• : '„! 	 1 ,, "',:

Baseline
Combo-IL
DAF-IL
CP-IL
Numfor of POTWs
Estimated to Exceed
Land Application
Limits
2(10)
0(0)
0(0)
0(0)
Number of Pollutants
Estimated to Exceed
Land Application
Limits
l(Pb)
0
0
0
' Total Mambef of
'Exceeddhce JEveals Aej'oss'
AllfOTWisr and PolWapts
2(10)
0(0)
0(0)
OCO)
Basis for Sludge Contamination Analysis
Number of Facilities:      139          Number of POTWs:
118
Number of Pollutants:
10
Exhibit 11: Number of POTWs and Associated Sladge^odacttoHl^iniatea to Exceed La»d Application
.. , ;..-. , * Limits on a Sample Basis " ' ' "°. * -
PoUufont
	 	 	 •-• "•••
Lead
Total
number of
exceedance
events:
Baseline
No.
2
2
Weight
(metric tons)
757

Combo-IL
No,
0
0
Weight
(metric tons)
0

DAF-IL
No,
0
0
WeigKt '
(naefcicrtons)
0

,. „ °ep-iL -'
>0,'
0
0
Weighl
s) >
0

                                               36

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5.6 Analysis of Baseline Closures

       To estimate the potential impact on benefit results of baseline closures of industrial laundries,
EPA analyzed a separate case in which the baseline closures were removed from the environmental
assessment.  First, EPA removed observations corresponding to the facilities identified as potential
baseline closures from the data sets supporting the analysis. Then, EPA estimated the benefits of the
proposed regulation in the same categories as presented in Sections 5.1 through 5.5. Removing the
baseline closures from the assessment did not materially  change the  estimated benefits for the
following reasons:

1.     Human Health Benefits.  At current discharge levels, EPA estimated that in-waterway
       concentrations of IL pollutants discharged by the facilities identified as potential baseline
       closures do not exceed human health-based AWQCs.

2.     Recreational Benefits. At current discharge levels, the estimated in-waterway concentrations
       of pollutants discharged by the IL facilities identified as potential baseline closures do not
       exceed AWQC limits for protection of aquatic species.
3.     POTW benefits. At current discharge levels, EPA estimated that (1) influent concentrations
       at the  POTWs receiving discharges from the baseline closures  were below the POTW
       inhibition values for all of the IL pollutants; (2) sewage sludge generated by the POTWs
       associated with the IL facilities identified as potential baseline closures met Land Application-
       High pollutant limits.
5.7 Efforts to Document POTW Problems from Industrial Laundry Discharges and to Develop
Case Studies of Such Problems

       To  understand the frequency and characteristics of problems to POTWs resulting from
industrial laundry discharges, EPA spoke to POTW pre-treatment coordinators in EPA's regional
offices and in states and to individual POTW operators. Several pre-treatment coordinators and
operators recommended other sources to call for more information on the subject.  In  these
conversations, which occurred in early 1997, EPA discussed 40 POTWs that receive discharges from
industrial laundries. Of these 40 POTWs, 11 were described as encountering some difficulty resulting
from industrial laundry discharges either currently or in  the recent past.   This information is
summarized by EPA region in Exhibit 13.
                                           37

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Exhibit 13: Summary of POTW$ with and without Problems with todusf rial
: ' 	 " '...••, Laundries, by Region ""'_;/•," ' >
EPA
Region
m
rv
V
VI
vm
rx
x
Number of POTWs known to
encounter problems from
industrial laundry discharges
2
2
0
1
1
2
3
Number of POTWs known to
not encounter problems from
industrial laundry discharges
2
11
1
2
7
6
0
       Based on these conversations, it appears that POTWs are most interested in EPA conducting
a good study of industrial laundries that clearly describes what problems the laundries pose to
POTWs, as well as to the environment and to the health and safety of POTW workers. The POTW
operators stated that such a study and resulting regulation should provide technically-based limits for
pollutants such as oil and grease. Many POTW operators feel that the current limits for oil and
grease are not based on solid studies of the relationship between laundries' effluent and POTW
operating conditions. Some POTW operators believe EPA needs to consider that POTWs face
different situations regarding laundries' discharges; the situation presented by a large laundry
discharging to a small POTW differs considerably from a small laundry discharging to a large POTW,
and thus EPA should make regulations that are flexible enough to accommodate these different
situations.  Some  POTW operators are simply raising their limits on certain  pollutants so that
industrial laundries discharging to them will not be in violation.
       EPA also had in-depth conversations with several POTW operators to try to develop case
studies on the nature of their problems with industrial laundry discharges. The three case studies
developed did not document substantial problems from industrial laundry discharges that would be
reduced by regulation because the POTWs have already implemented new local limits, the industrial
laundry facilities have already installed pretreatment, or a combination of the two. These case studies
are summarized below.

Three Case Studies
Region VIE         South Dakota POTW

       This POTW has an annual flow of 18.1 billion liters per year, and receives 43 million liters per
year of industrial laundry discharge. The POTW has three major problems with industrial laundries'
discharges: 1) oil and grease; 2) pH fluctuations; and 3) metals.
       Excessive amounts of oil and grease do not cause problems in the treatment plant, but do clog
the collection system. Clogging does not happen often because the POTW is very aware of the issue
and is vigilant about ensuring smooth operation of the collection system. However, when there is a
                                           38

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 backup, the POTW does incur extra labor costs when someone has to conduct maintenance work on
 the system. Though estimating the cost of this maintenance is difficult, a very rough estimate would
 be that every visit would be about $200, and for every problem caused, two or three visits might be
 needed.

       For the pH of the discharge, the major problem for the POTW is the wild fluctuations: pH
 levels can vary from 1-2 to  12-14 within a few minutes.  These pH levels create problems for the
 concrete in the  manholes; the pipelines, consisting of both PVC  and concrete; and the POTW
 workers.  Highly acidic  discharges can eat away at  concrete,  and both acidic and highly basic
 discharges can injure POTW workers.  A complete manhole  rehabilitation project would cost
 approximately $2,000, half of that for labor, half for materials. If only a pipe were damaged, the total
 cost would be about $1,000, with labor and materials costing $500 each (depending on the size of
 the project).

       The  POTW  also has difficulties with metals, in particular, cadmium, lead, and zinc, in
 industrial laundries' effluent. Last year, the POTW re-defined local limits on all metals.  For zinc, the
 local limit was 1.0 mg/L, but now it is 5.3 mg/L.  The laundries are now in compliance, because even
 without pretreatment, the zinc concentration  is approximately 1.5 mg/L. Zinc comes primarily from
 inks on printers' rags; however, many printers are switching to  soy-based inks, which might help
 lower the zinc concentration. For lead, the limit was 0.2 mg/L, but now it is 0.59 mg/L; with the
 laundries installing pretreatment, they are in compliance. Lead as  well as cadmium mainly originate
 from metal filings (among other sources) left on rags from machine shops and automotive repair
 facilities.  New regulations from the  EPA concerning metals probably would not save this POTW any
 costs, because it already has all these regulations in place. The industrial laundries discharging to this
 POTW would like to see regulations from EPA because that would ensure a "level playing field"; that
 is, some nearby POTWs do not have as strict limits as this  POTW, and so the laundries believe that
 currently they are operating at a disadvantage.
Region HI
Maryland POTW
       This POTW has an annual flow of 247 billion liters per year, and receives a total of 34.8
million liters per year of discharge from five industrial laundries. This POTW was having problems
holding the industrial laundries to permitted limits of 100 ppm FOG (Fats, Oil, and Grease) and 2.13
ppm TTO (Total Toxic Organics). The laundries appealed those limits, and thus the POTW derived
new limits. The POTW took data for three years from all the industrial laundries in Baltimore City,
assumed that all laundries were using Dissolved Air Floatation (DAF), the most affordable system
of pretreatment, and calculated new limits for Total Petroleum Hydrocarbons (TPH) and TTO: 237
ppm TPH and 11.39 ppm TTO. The POTW then told the laundries that if they could not meet these
new limits, they would have to install a DAF (if they did not already have one.)

       From 1989 to 1994/5, the POTW has been concerned about volatile organics from laundries,
including: chlorobenzene,  chloroform, 1,1,1-trichloroethane, ethyl benzene, methylene chloride,
tetrachloroethane, toluene, trichloroethene, and xylene. The POTW is concerned about fumes, with
                                           39

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regard to the health and safety of sewer workers. The POTW monitors the atmosphere at all times,
and when there are unusually high levels of any pollutant, the general policy is to increase ventilation.
This POTW has had no issues with explosivity (TPH is usually around 5 ppm), and no problems to
the system caused by backups or breakdowns.
Region HI
Maryland POTWs
       This source spoke for five treatment plants operated by his agency. One plant in particular
has experienced problems with total toxic organics (TTOs) from shop towels and printer's rags
cleaned by industrial laundries. Industrial laundries have TTO values of greater than 300 ppm in their
discharges to the sanitary sewer.  The problems at the treatment plant were related to solvent odors
in the pump station and general observations of unusual colors and odors in the plant effluent.

       The source  said treatment plant workers call the pretreatment program staff when they
observe unusual colors/odors at the plant. This results in labor and laboratory costs being expended
to respond to the color/odor complaints. He mentioned that most of the laundries have some form
of pretreatment which allows them to comply with the agency's discharge limits. The laundry most
heavily involved in  the shop towel/printer's rags business installed pretreatment equipment that
significantly reduced  the number of  complaints about  unusual solvents/odors.  In the 1980s
complaints were received almost weekly. Now complaints are received four to six times per year for
one to two hours each time.  The treatment plant which received the highest TTO loadings is a
relatively small plant (an annual flow of 7.3 billion liters) receiving a discharge of 31.5 million liters
from an industrial laundry.  He also mentioned concerns regarding explosions in manholes and sewer
mains from solvent vapors from industrial laundries, although there have not been any incidents
attributable to  industrial laundries.
                                           40

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 6. REFERENCES
 Arthur D. Little. 1986. Bioaccumulation Study.            ',
 Banerjee, S. et al. 1984. Environ. Sci. Tech. 18:416-422. [As cited in HSDB, 1994.]
 Birge, WJ. et al. 1979. Aquatic Toxicity Tests on Inorganic Elements Occurring in Oil Shale. Oil
       Shale Symposium-Sampling, Analysis and Quality Assurance. March.  EPA-600/9-80-022.
 Dore, M. et al.  1975. Trib. Cebedeau 28:3-11. [As cited in HSDB, 1994.]
 Haines, J.R. and M. Alexander.  1974. Appl. Microbiol. 28:1084-1085. [As cited in HSDB, 1994.]
 Hazardous Substances Data Base (HSDB).  1994. Chemical files on-line from Toxnet.
 Holdway, D.A.,  and J.B. Spraque. 1979. Chronic Toxicity of Vanadium to Flagfish.  Water Research
       13:905-910.                                     ;
 Howard, P.H., R.S. Boethling, W.F. Jarvis, W.M. Meylan, and E.M. Michalenko. 1991. Handbook
       of Environmental Degradation Rates. Lewis Publishers, Inc. Chelsea, MI.
 ICF, Inc. 1985.  Superftmd Public Health Evaluation Manual-Draft.
 Leblanc, G.A. 1980. Acute Toxicity of Priority Pollutants to Water Flea (Daphnia magna). Bull.
       Environ. Contain. Toxicol. 24:684-691.
 Lyman, W.J., W.F. Reehl, and D.H. Rosenblatt. 1990. Handbook of Chemical Property Estimation
       Methods - Environmental Behavior of Organic Compounds. American Chemical Society.
       Washington, D.C.
 McDonald, R. 1994. Office of Air Quality Planning and Standards, U.S. EPA. Facsimile transmission
       to J. Keating, Versar Inc.                          ;
 McGaughy, R.E. 1986. Transmittal of Carcinogen Assessment Group (CAG) Carcinogenicity Data
       Base.  Memorandum to P. Preuss, OHEA.  January 7.
 Nelson-Smith, A. 1973.  Oil Pollution and Marine Ecology.  Plenum Press. New York.
 SAIC. 1996. Memo from Lisette Bergeron, SAIC, to  Jeanette Kranacs, EPA, entitled "Steps to
       Generate National Estimates of Means and Totals." June 24.
Tabak, H.H. et al. 1981. J. Water Poll. Control Fed. 53:1503-1518.  [As cited in HSDB, 1994.]
U.S. Atomic Energy Commission. 1973. Toxicity of  Power Plant  Chemicals  to Aquatic Life.
       Washington, D.C.                                :
U.S. EPA. 1976. "Red" Book (Quality Criteria for Water).  Washington, D.C.
U.S. EPA.  1980.  Ambient water quality criteria documents. Office of Water, Washington, DC.  EPA
       440/5-80 Series. Also refers to any update of criteria documents (including EPA 440/5-85 and
       EPA 440/5-87 Series) or any Federal Register notices of proposed criteria or  criteria
       corrections.                                     i
                                         41

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U.S. EPA. 1986. Report to Congress on the Discharge of Hazardous Wastes to Publicly Owned
      Treatment Works.  Office of Water, Regulations and Standards. EPA/530-SW-86-004.
      February.
U.S. EPA. 1987a. Guidance Manual for Preventing Interference at POTWs.  Washington, D.C.
U.S. EPA. 1987b. "Gold" Book (Quality Criteria for Water). Washington, D.C. USEPA 440/5-86-
      001.
U.S. EPA.  1989a. Risk Assessment Guidance for Superfund (RAGS), Volume I Human Health
      Evaluation Manual (Part A). Office of Emergency and Remedial Response. Washington,
      D.C. EPA/540/1-89/002.
U.S. EPA.  1989b.  Short-term Methods for Estimating the Chronic Toxicity of Effluent and
      Receiving Waters  to Freshwater Organisms.  Office of Research and Development,
      Cincinnati, OH. EPA/600/4-89/001.
U.S. EPA. 1989c. Computer Data Base of Physical/Chemical Properties for SARA 313 Chemicals.
      Office of Toxic Substances, Exposure Evaluation Division. (Used in the Toxic Chemical
      Release Inventory Risk Screening Guide). EPA 560/2-89-002.
U.S. EPA. 1990. CERCLA Site Discharges to POTWs: Guidance Manual.  Office of Emergency and
      Remedial Response. Washington, D.C. EPA/540/G-90/005. August.

U.S. EPA. 1991. Technical Support Document for Water Quality-based Toxics Control. Office of
      Water. EPA/505/2-90-001.
U.S. EPA. 1992a. Mixing Zone Dilution Factors for New Chemical Exposure Assessments, Draft
      Report. Contract No. 68-D9-0166, Task No. 3-35. October.

U.S. EPA. 1992b. Health Effects Assessment Summary Tables (HEAST). Office of Research and
      Development and Office of Emergency and Remedial Response. OERR 9200/6-303 (92-1).

U.S. EPA. 1993a. Integrated Risk Information System (IRIS) Retrieval. Washington, DC.

U.S. EPA. 1993b. AQUatic Information REtrieval System (AQUIRE) Data Base. Environmental
      Research Laboratory, Duluth, MN.
U.S. EPA. 1993c. QSAR. Environmental Research Laboratory, Duluth, MN.
U.S. EPA. 1993d. Assessment Tools for the Evaluation of Risk (ASTER) Data Base. Environmental
      Research Laboratory, Duluth, MN.
U.S. EPA.  1993e. Environmental Research Laboratory - Duluth Fathead  Minnow Data Base.
      Environmental Research Laboratory, Duluth, MN.
U.S. EPA.  1995. Regulatory Impact Analysis of Proposed Effluent Limitations Guidelines and
      Standards for the Metal Products and Machinery Industry (Phase 1).  EPA 821-R-95-023.
      April.
Vaishnav, D.D. and L.  Babeu.  1987.  Bull. Environ. Contam. Toxicol. 39:237-244. [As cited in
                                         42

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       HSDB, 1994.]

Versar. 1992. Upgrade of Flow Statistics Used to Estimate Surface Water Chemical Concentrations
      for Aquatic and Human Exposure Assessment.  Prepared for  the Office of Pollution
       Prevention and Toxics, U.S. EPA.                |

Versar. 1994. Development of Mixing Zone Dilution Factors. Preliminary Draft, Progress Report.
       Prepared for U.S. EPA, Office of Pollution Prevention and Toxics, Economics, Exposure and
       Technology Division. October 27. EPA Contract No. 68-D3-0013.

Walker, J.D. and R.A. Colwell.  1975. Can. J. Microbiol. 21:305-313. [As cited in HSDB, 1994.]
                                          43

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               APPENDIX A

Weighting Techniques for Extrapolating Results
 from Sample Facilities to the Population Level

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A.I Introduction

       In analyzing the benefits to society from the reduced effluent discharges that will result from
the proposed Industrial Laundry (DL) regulations, EPA used two techniques to extrapolate results
estimated for sample facilities to the population level: a simple linear weighting technique and a
differential weighting technique.  For the analysis of change in cancer risk, EPA used the linear
weighting technique. This linear weighting was possible because the marginal effects on cancer risk
of a change in pollutant exposure are assumed to be linearly additive over the facilities, chemicals,
and human populations that are affected by changes in pollutant discharges. However, EPA used a
different sample weighting technique for those analyses in which the estimated baseline and post-
compliance  POTW  influent flow concentrations,  sludge concentrations,  or  in-waterway
concentrations were compared with the corresponding threshpld values to ascertain a benefit event.
A benefit event is the change in frequency with which interference of processes and contamination
of sewage sludge would occur at the POTWs receiving effluent discharges from IL facilities or the
change in frequency with which AWQCs are exceeded by IL facility discharges. In those analyses,
the standard linear weighting method was used for POTWs (orTeaches) to which only one EL sample
facility discharges. As a result, for a benefit event on a POTW (or reach) with only one sample, the
number of POTWs (or reaches) expected to benefit in a similar fashion at the national level is  simply
the sample weight of the single facility discharging to the POTW (or reach). However, EPA found
more than one sample facility discharging to approximately  18:percent of the sample facility POTWs
and, via the POTWs, to  about 23 percent of the sample facility reaches.8  For these POTWs (or
reaches) to which more than one facility discharges, EPA used a different procedure for developing
national estimates of benefit events that accounts for the presence of more than facility with different
sample weights discharging to the reach.  This appendix first describes the simple linear weighting
technique and then the differential weighting technique used for extrapolating results estimated for
sample facilities to the population level.                    -!

A.2 Linear Weighting Technique

       EPA surveyed 172 EL facilities as the basis for the economic, engineering, and environmental
analyses being performed in support of the industrial laundries regulation. These  172 facilities are
estimated to represent 1,606 EL facilities nationwide.  All sample facilities are indirect dischargers
(e.g., each facility discharges to a POTW as opposed to directly discharging to a water body). Thus,
to evaluate the impacts of IL discharges on POTW operations, human health, and aquatic life, EPA
first associated sample IL facilities with receiving POTWs.  Because of incomplete information on
the POTWs to which some of the sample facilities discharge, 33 facilities were dropped from the
analysis.  To account for the lost observations,  EPA adjusted, the sample weights for the remaining
facilities  in each affected stratum. The sample weight adjustment has the effect  of  assigning the
 Note that, among the sample facility discharge sites, this percentage is a lower bound estimate of the frequency of multiple
facility discharge sites. While it is not possible for there to be fewer IL facilities on a POTW/reach than are seen in the
sample, it is always possible that another, or perhaps several additional, unsampled and therefore unseen facilities are
present on a POTW/reach on which only one facility was sampled.

                                           A-l        i

-------
sample mass for a lost observation(s) to the remaining observations in the affected stratum.  As a
result, the analyses encompass  139 sample facilities discharging 72 pollutants of concern to 118
POTWs.

       The following steps outline the procedure for extrapolating findings from the sample facility
analyses by the linear weighting technique:

                             Yntl =  £   Wtf x Kadj x Ysmpl
                                   F = 1
where:
       Y ml       =   national estimate of the variable of interest (for example, avoided number of
                     cancer cases or the change in frequency of AWQC exceedences in reaches to
                     which only one IL facility discharges),
       F        =   total number of facilities analyzed,
       Wtf       =   sample weight applicable to theytti facility,
       K ^      =   weight adjustment factor accounting  for a lost observation(s), and
       Y smpi     =   sample estimate of the variable of interest.

       To assign weight for the lost observations to the facilities remaining in the analyses, EPA
calculated an adjustment factor (K adj) as follows:

                                     K         N
                                     Kadj —F	
                                               Wtf x X
                                           /=!
where:
       K jjj   =     adjustment factor assigning the sample mass for a lost observation(s) to the
                     remaining observations in the affected stratum,
       N     =     total number of facilities in the EL industry (e.g., 1606),
       F     =     total number of facilities analyzed (e.g., 172),
       Wtf   =     sample weight applicable to theyth facility, and
       Xj    =     a variable that is equal to one if a facility was linked to the receiving POTW
                     and is equal to zero if information on the receiving POTW is missing.

       As discussed previously, this simple linear extrapolation method was used in the analysis of
reduced cancer cases via the fish consumption pathway. This method was also used for extrapolating
sample findings to the population in those POTW operation, AWQC comparison, and recreational
fishing benefits analyses hi which only one sample facility discharges to a POTW or reach.
                                            A-2

-------
A.3   Differential Weighting Technique

       A key issue is the fact that the EL sample is a sample of facilities, while the unit of analysis in
the POTW processes analysis, AWQC comparison analysis, and the recreational fishing benefits
analysis is a POTW or a reach. EPA can use the sample weight to estimate the nationwide number
of facilities like a sample facility. But because the facility sample weights are not POTW or reach
sample weights, those weights cannot be used directly to estimate the national occurrence of POTWs
(or reaches) associated with a specific characteristic of DL discharges. EPA developed a methodology
to account for joint occurrence of facilities on POTWs (reaches) to enable reasonable estimates of
the nationwide number of POTWs  (reaches) affected by IL facilities, based on the  concept of
"discharge events."

       "Discharge  events" are defined for each pollutant of concern discharged by one or more
facilities to a POTW (or reach) based on the loadings of the relevant sample facilities. The pollutant
loading associated with a discharge event (or discharge event loading) is the sum of the loadings
from one or more  of the facilities that discharge to the POTW (or reach).  There are as many
discharge events of each type as there are unique sample weights for the facilities discharging to the
POTW (or reach). A sample weight is calculated for each separately defined discharge event based
on the sample weights  of the facilities contributing  loadings to  the event. Discharge events are
calculated as illustrated in Exhibit A-l, and are described more fully below.

       For each regulatory option considered, each POTW (or reach) associated with more than one
IL facility, and each pollutant of concern discharged by one or more of those facilities, pollutant
loadings are ranked in ascending order of facility sample weight. The total loadings from all sample
facilities on the POTW (or reach) compose the first event, and this event is assigned the smallest
sample weight among the facilities discharging to the reach, Wt, in Exhibit A-l.  The weight of this
facility  is then considered to  be "used up,"  and that facility's loadings are not included in the
subsequent discharge events defined for the reach.  Subsequent combinations of facilities do not
include this facility  because its smaller sample weight relative to the others means that there are no
other population facilities represented by this facility that could jointly occur with the other facilities.

       Subsequent events are generated by removing the loadings of each facility in the ranking from
a running sum of loadings of all facilities in the ranking. The weight assigned to each subsequent
event is the difference between the weight of the next facility in the ranking and the previous facility
or, said another way, the remaining unused weight of the facility with the smallest weight among the
facilities in the particular discharge event.                  i

       This methodology generates a set of discharge events (loadings) for each pollutant discharged
to the POTW (or reach), along with a weight attached to each event. The event's loading is used to
calculate the resulting pollutant concentrations due to the event in the POTW influent flow, sewage
sludge, and in the receiving stream. These concentrations are then compared to the relevant threshold
values to determine whether the concentrations exceed critical values. If the concentration is greater
than a criterion, then an estimated "exceedence"  event is identified, and this exceedence event is given
                                           A-3

-------
the weight of the discharge event for the purpose of establishing national estimates of the number of
POTWs (or reaches) on which a threshold value is exceeded.
Exhibit A-l: Construction of Discharge Events for Any Pollutant Discharged to Any Reach
Event Dumber
One
Two
1
N-2
N-l
N
Loadings and Flows Assigned to
Event , " ,
N
£ Loadj
/ = i
£ Load,
i = i
1
LoadN.2 + LoadN., + LoadN
LoadN_, + LoadN
LoadN
Weight Assigned to Even!"
Wt,
Wtj-Wt,
11
WtN.2-WtN.3
WtN.,-WtN.2
WtN-WtN.,
Notes: N sample facilities discharge to the POTW (or reach), and are ranked in ascending order of sample weight and
indexed by I (1 = facility with smallest weight, N = facility with largest weight); Loadj = loading from facility I; and
Wtj = sample weight of facility I.
       EPA acknowledges that this analytic method is a relatively simplistic approach to a complex
analytic situation.  However, within the time and resource constraints for addressing this issue and
also taking into account that more sophisticated, and more expensive, approaches might not yield
significantly different aggregate findings, the Agency believes that the method represents a reasonable
approach to addressing the problem.
                                           A-4

-------
           APPENDIX B




Chemical-Specific Data Used in Analyses

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-------
         APPENDIX D

Estimated Health Benefits Based on
Alternative Fish Consumption Rates

-------

-------
       In developing  the proposed regulation, EPA  considered using alternative assumptions
regarding fish consumption rates (see Section 3.2.3). The alternative rates were derived from the
combined 1989, 1990 and 1991 USDA Continuing Survey of Food Intakes by Individuals (CSFII).
Persons living in subsistence fishing households were assumed to consume 50 grams per day (0.05
kg/day) offish over 70 years of exposure. This value corresponds to the 95th percentile consumption
value from the CSFII for fresh and estuarine fish.  The risks to recreational fishing households were
estimated based on consumption of 22 grams of fish per day (0.022 kg/day) over a 30-year period.
This value corresponds to the 90th percentile consumption value for fresh and estuarine fish from
CSFE.

       Using the methodology for calculating cancer risk discussed in Section  10.4.2.1  of the
Economic Assessment for Proposed Pretreatment Standards for Existing and New Sources for the
Industrial Laundries Point Source Category (U.S. EPA, 1997, EPA-821-R-97-008), EPA calculated
alternative cancer risk estimates using the alternative fish consumption rates. Based on the alternative
fish consumption rates, EPA estimated that the CP-EL option would eliminate approximately 0.02
cancer cases per year from a baseline value of about 0.07 cases, representing a reduction of about 30
percent. Options Combo-IL and DAF-IL would also eliminate approximately 0.02 cancer cases per
year, representing a reduction of about 28 percent. EPA estimated the value of the avoided cancer
cases at $0.041 to $0.23 million per year ($1993).
Exhibit D-l: Estimated Annual Avoided Cancer Cases and Value of Benefits for Industria
Laundry Regulatory Options Based on the Alternative Fish Consumption Rates
Regulatory Options
CP-IL
DAF-IL
Combo-EL
Fish Consumption
Avoided Cancer Cases
0.02 :
0.02 ]
0.02 !
Value of Benefit3 ($ million)
$0.043 - $0.23
$0.041 - $0.22
$0.041 - $0.22
"Estimated value of avoided cancer case ($1993): $2.1 million - $11.4 million.
                                          D-l

-------

-------