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Introduction
receiving waters. In some cases, however, technology-based standards are not
enough. If water quality does not support the designated use even after every
discharger meets his technology-based standards, additional controls must be
applied. Section 301(b){l){C) of the Act requires "any more stringent
limitations," including those necessary to meet water quality standards,
whenever meeting the technology-based standards in Section 301 fail to attain
or maintain the water quality called for in the river or stream (water
quality-based limitations). Section 302(a) also authorizes the Administrator
to establish effluent limitations more stringent than those necessary to meet
quality standards in order to meet the water quality goals of the Act.
In the Water Quality Act of 1987, Congress added new Section 304(1), which
requires States to develop lists of impaired waters, lists of point sources
and amounts of pollutants causing toxic impacts and "individual control
strategies" for such point sources. These new requirements should aid in the
identification of waters that will need water quality-based standards. These
provisions direct immediate attention to establishing controls where there are
known impacts due entirely or substantially to point sources of Section 307(a)
toxic pollutants. The identification of waterbodies and point sources and the
development of control strategies is the subject of a separate Agency effort.
The statutory deadline for identification of waterbodies and development of
individual control strategies (ICSs) was February 4, 1989, and must achieve
applicable water quality standards on or before June 4, 1992. EPA approved or
disapproved the ICSs on June 4, 1989, and where EPA disapproved an ICS, the
revised ICS must achieve applicable water quality standards on or before June
4, 1993.
GENERAL APPROACH AND ASSUMPTIONS
IN THE WATER QUALITY IMPROVEMENT STUDY
The objective of this report is to identify improvements in water quality
attributable to the application of best available technology economically
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Introduction
achievable (BAT). This study is required by Section 308(g) of the Water
Quality Act of 1987. Section 308(g) also requires an evaluation of the water
quality program (including Section 302(a) site-specific water quality
determinations) and recommendations of methods for improving such program.
This study does not include an evaluation of the water quality program since
it is now the subject, of a major concurrent effort mandated under
Section 308(a) of the 1987 Water Quality Act [Section 304(1) of the Clean
Water Act].
Because of the implementation of BAT by industrial dischargers and the
subsequent reduction in pollutant loadings, it can be inferred that the water
quality in the nation has improved. As illustrated in Table 1-2, the Agency
estimates that, the result of treatment including BAT, organic priority
pollutant discharges have been reduced by 99 percent from untreated levels and
that inorganic priority pollutant discharges have been reduced by almost
98 percent. These estimates of pollutant reductions do not account for
treatment in-place prior to the implementation of BAT, and therefore, may
overestimate BAT benefits. However, the extent of these pollutant reductions
and their contribution to attaining the goals of the national water pollution
control program have not been determined. This study attempts to determine
the extent of these improvements on a national scale, through the examination
and use of currently existing data sources. However, this study does not
attempt to quantify benefits which result from improved water quality. These
include increased sport and commercial fishing, and improved recreational
opportunities.
For purposes of this study, "water quality improvement11 was defined as one
of the following:
• Compliance with EPA national water quality criteria (WQC) after BAT,
having not complied with WQC prior to BAT.
* A decrease in in-stream pollutant concentration after implementation
of BAT.
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Introduction
To determine water quality improvements, the approach used had three major
components: (1) projecting in-stream concentrations of selected pollutants by
modeling pre- and post-BAT effluent discharges of industries regulated by BAT
to determine theoretical improvements based on compliance with water quality
criteria; (2) reviewing available ambient water quality monitoring data to
determine trends in chemical water quality; and (3) providing actual case
studies on the implementation of the national effluent regulations for
industrial dischargers and a discussion of any improvements in either the
chemical or biological quality of specific waters as a result of such
implementation.
The modeling and ambient data review effort primarily focused on:
(1) facilities discharging directly to surface waters that are required, under
the BAT regulations, to control toxic pollutants; and (2) nationwide
improvements. Indirect facilities (i.e., those that discharge their
wastewater to POTUs), which are controlled by pretreatment standards, were
excluded for two reasons: (1) there was insufficient information on indirect
facilities within the EPA national data bases, and (2) these facilities are
not controlled by State or EPA-issued permits (NPDES), but rather by local
limits developed by the POTW receiving the discharge. This study also
excludes industries which are not regulated by the national categorical
(technology-based) effluent limitation guidelines, but rather by "best
professional judgment" permits. By not considering indirect facilities and
improvements in water quality resulting from pretreatment requirements or
controls on industries without additional categorical effluent limitation
regulations, this study underestimates the extent of the improvements
resulting from the national water quality program. The effectiveness of the
BAT regulations in improving water quality can be addressed on a national
level because site-specific and/or regional factors are not taken into account
in establishing these technology-based effluent limitations. The
site-specific nature of water quality-based limits prevents a theoretical
estimate of their effectiveness. Specific instances where water quality
improvements are attributable to indirect facilities will be discussed, when
applicable, in the case studies.
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The first two components (or analyses) of this study made use of existing
EPA computerized information to expedite the nationwide study. Ideally, such
information sources would have historical information available for each of
the industrial facilities affected by the BAT regulations. Ideally, this
information would include pollutant loading information prior to, and after,
implementation of BAT treatment technologies; the date when BAT treatment was
implemented; and in-stream ambient monitoring data specific to each facility.
Unfortunately, existing data bases were developed primarily for the purpose of
and tracking ambient water quality for localized pollution control purposes
and not specifically for performing a nationwide water quality improvement
study. Thus, the ideal data base described above is not available.
Other factors also need to be considered, including the long time frame
over which BAT regulations have been implemented. In addition, for a number
of years some States have been writing water quality-based permits for
industrial dischargers that are generally more stringent than the treatment
requirements of BAT. Differentiating between the time periods that represent
pre- and post-BAT and which facilities have effluent limitations based on
technology or water quality is not feasible using these sources of data.
Several assumptions were necessary in order to complete the first two
components of this study using the available EPA information:
1. All industrial facilities covered by the BAT regulations will be
evaluated assuming that technology-based limitations are the basis for
their respective discharge levels.
2. Pre-BAT effluent discharges will be represented by untreated, or raw,
levels as determined by EPA sampling programs.
3. The pre-BAT period for evaluating ambient monitoring data is from 1970
to 1980.
4. The post-BAT period is from 1985 to the present.
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Introduction
5. Ten pollutants were selected to represent toxic pollutant discharges
from BAT-regulated facilities. These selected pollutants are the most
frequently discharged and regulated priority pollutants.
6. Only stream segments receiving direct discharges for BAT facilities
were evaluated.
One limitation of this study is that it is not currently feasible to
determine which BAT industrial facilities actually have and meet permit
limitations based on the national effluent guideline (technology-based)
regulations. However, by not considering more stringent controls imposed by
water quality-based permits and assuming that all BAT industries meet the
requirement of the technology-based limitations only, the overall need for the
more stringent controls can be more accurately assessed on a national level.
This is one of the requirements of the water quality improvement study.
In evaluating the improvements resulting from the BAT regulations, the
ideal scenario would consider discharge levels prior to the implementation of
treatment requirements mandated by the Federal water quality program (i.e.,
pre-BAT), which began in 1972. Unfortunately, no accurate method exists to
determine or estimate these discharge levels, especially in the area of toxic
pollutant discharges. In some instances, facilities had treatment of their
wastewater discharges. In others, untreated wastewaters were discharged
directly to receiving waters. In addition, EPA's initial sampling of
industrial facilities in the mid-1970s to define effluent characteristics
focused on conventional pollutants and a few toxic metals. Only later, in
response to the NRDC Settlement Agreement and subsequent amendments to the
Clean Water Act, did the Agency focus its regulatory efforts on the toxic, or
priority, pollutants referenced in the Act. For this reason, and because it
is Agency policy when determining benefits of BAT guidelines, untreated
wastewater was used as the basis for determining the improvements. This
assumption will overestimate the actual benefits of the technology-based
program, but the extent of this overestimate is uncertain.
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It was difficult to select appropriate time periods for comparing pre- and
post-BAT ambient water quality monitoring data because BAT treatment levels
for some industries (such as metal finishing/electroplating, pulp and paper,
and textiles) have remained essentially the same since the mid-1970s, while
for others, BAT limitations have yet to be fully implemented or promulgated
(organic chemicals and pesticide manufacturing, respectively). Taking into
consideration, however, the fact that monitoring for toxic pollutants was not
as common prior to the mid-1970s as it is today and that detection limits for
individual chemical parameters have changed as technology has improved, the
years from 1970 to 1980 were selected to serve as the pre-BAT period. During
this period some reductions in ambient pollutant concentrations would be
reflected in the monitoring data, but the overall average for that period
should tend to be representative of levels prior to the implementation of
technology-based regulations. To reflect post-BAT levels, 1985 was selected
as the start date. A majority of the "Phase II" BAT regulations for the
industrial categories were promulgated in the early 1980s (Table 1-1), so the
period from 1981 to 1984 was considered a transition period and was not
evaluated.
By using only a select group of toxic pollutants, the overall trends in
water quality can be identified without the need for voluminous amounts of
data. However, by not considering improvements resulting from reductions of
other toxic pollutants, the full benefits of BAT are underestimated.
Only those stream segments receiving discharges from BAT-regulated
facilities were included in the first two components of this study. Because
of difficulty in modeling the fate and transport of these pollutants, no
impacts to downstream stream segments were considered, thus reducing the scope
of potential improvements.
The first two components of this study project and estimate improvements
in water quality resulting from the application of BAT. While these analyses
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provide a good picture of overall national trends, case studies best present
water quality improvements since such improvements are "real life," not
projected or estimated. Case studies reviewed for this study had to show a
direct benefit in water quality (either chemical or biological) as a result of
facilities implementing limitations set forth by BAT. The focus of such
improvements or benefits was the reduction of toxic pollutants. However,
other aspects of technology-based limitations, such as reductions in
conventional pollutant discharges for industrial sources were also considered,
as well as the beneficial results of the implementation of pretreatment
program for indirect dischargers to publicly-owned treatment works. However,
this study does not attempt to quantify benefits which result from improved
water quality. These include increased sport and commercial fishing, and
improved recreational opportunities.
REPORT ORGANIZATION
The remainder of this report consists of four chapters that address the
objective of Section 308(g) of the Water Quality Act of 1987 relevant to the
BAT regulations. Chapter 2 presents a general discussion of the data sources
and methodology used to identify water quality improvements. Chapter 3
summarizes the results of the analyses. Chapter 4 addresses the study
findings and the evaluation of the effectiveness of the BAT regulations.
Chapter 5 lists the various references used in this study. Volume II of this
report contains the technical appendices, providing the backup material and
outputs from the water quality model and ambient data evaluation. Volume II
is available under a separate cover.
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Chapter Two
METHODOLOGY
OVERVIEW
Three different components were used to Identify water quality improvements
resulting from the application of best available technology economically
achievable (BAT): (1) projection of theoretical improvements in water quality
for stream reaches with BAT industries {those industries covered by the BAT
regulations} using water quality modeling; (2) review of ambient water quality
data for pre- and post-BAT time periods; and (3) summary of specific instances
(case studies) where water quality has improved because of BAT. Specifically,
this methodology included the following:
Water quality modeling of industrial facilities with BAT effluent
limitations to control toxics. The model predicted in-stream concentrations
of ten selected pollutants at pre-BAT and post-BAT treatment levels at low and
average receiving stream flow conditions. Concentrations were then compared
to EPA water quality criteria to determine the potential/theoretical water
quality improvements.
Analysis of STORET ambient water duality monitoring data, for the same
ten selected pollutants, for stream segments receiving BAT industrial
discharges for time periods assumed to reflect pre-BAT (1970 to 1980) and
post-BAT (1985 to 1988) conditions. The average values for these two time
periods were used to determine trends in ambient pollutant levels.
Summary of case studies that associate the implementation of national
technology- based effluent limitations with improvements in the chemical and/or
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Methodology
biological quality of the receiving waters. All improvements that can be
attributable to BAT regulations are considered, primarily reductions in toxic
pollutant discharges but also including controls on conventional pollutants and
indirect dischargers. A special case study was developed by the Agency to
evaluate the benefits of BAT regulations in estuaries.
The ten pollutants selected to be evaluated were representative of toxic
pollutants regulated by BAT and could be considered "indicator" pollutants.
These pollutants are the most frequently discharged and regulated priority
pollutants found in the wastewater of the BAT facilities and include six heavy
metals (cadmium, mercury, copper, lead, nickel, and zinc), cyanide, and three
organic chemicals (phenol, toluene, and benzene). Table 2-1 lists these
pollutants and their frequency of occurrence in the BAT industries effluent.
Also shown are the industries in which these pollutants are regulated. In
addition, limiting the number of pollutants also reduced the modeling effort
to a manageable size.
The modeling and ambient data analyses are limited to only those reaches
receiving BAT industrial discharges. (Reaches are unique segments of streams
and rivers that have been delineated by EPA for the purpose of integrating
water quality and facility information.) It was beyond the scope of this study
to address the effects of the discharges on reaches downstream of the
industries, even though the downstream reaches are likely to be directly
affected.
The methodology used to identify water quality improvements is presented in
the following sections: (1) Information Sources, which presents a brief
description of all the EPA information sources used for the first two
components of the study; and (2) Description of Methods to Assess Improvements,
which presents general discussions of the components of this study - the water
quality modeling analysis, the ambient water quality data evaluation, and
site-specific case studies. The latter section also provides, for each
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Table 2-1
Frequency of Occurrence of Selected Priority Pollutants
in BAT Industrial Category Vastewater Discharges
Occurrence of
Industrial Category
Aluminum Forming
Battery Manufacturing
Coil Coating
Copper Forming
Electrical & Electronic Components
Metal Molding & Casting (Foundries)
Inorganic Chemicals
Iron i Steel
Leather Tanning & Finishing
Metal Finishing
Monferrous Metals
Nonferrous Metals Forming
Ore Mining i Dressing
Organic Chemicals, Plastics, ft
Synthetic Fibers
Petroleum Refining
Pharmaceuticals Manufacturing
Porcelain Enameling
Pulp & Paper
Textiles
Total Occurrences
Total Regulated
Cadniun
1
R
1
1
1
1
R
1
1
ft
1
R
R
1
1
1
16
5
Mercury
R
1
1
1
R
1
1
1
1
1
1
1
1
13
2
Copper
1
R
R
R
1
R
R
1
1
R
R
R
R
R
1
1
1
1
1
19
10
Lead
1
1
1
R
1
R
R
R
1
R
R
R
R
R
1
1
R
1
1
19
10
Pollutant in
Nickel
1
1
R
1
1
R
R
1
R
R
R
R
1
1
R
1
1
17
8
Zinc
ft
R
R
R
1
R
R
R
1
R
R
R
R
R
1
1
R
R
1
19
14
Industrial Catenorv
Cyanide
R
ft
R
1
1
R
R
1
R
R
R
1
R
1
R
1
1
17
10
Phenol
1
1
(R)
1
1
1
(R)
1
R
1
1
1
1
13
1(2)
Toluene
(R)
1
(R)
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1
1
(R)
1
R
1
1
1
1
13
1(3)
Benzene
1
1
R
1
(R)
R
1
1
1
1
10
2(1)
KEY
R - Regulated pollutant in industrial category.
1 - Detected, but not regulated, in wastevater of industrial category.
Values in parentheses denote when pollutant is regulated as part of "Total Toxic Organics.'
SOURCE: U.S. EPA. 1986.
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component, a summary of the approach and purpose of the analysis, assumptions
used and limitations in performing the analysis, and the actual analysis
conducted. Outputs from the water quality model and the ambient water quality
monitoring data analyses are included in the technical appendices (Volume II).
INFORMATION SOURCES
To perform the first two components of this study, readily available and
accessible information contained in the following EPA data bases were used:
Permit Compliance System (PCS), Industrial Facilities Discharge (IFD) file,
GAGE file, REACH file, and STORE! Water Quality file. A brief description of
each data base and how it was used is presented below:
• Permits Compliance System (PCS) - PCS is a computerized
management information system for tracking permit status data for the
National Pollutant Discharge Elimination System (NPDES). This system
was used to identify BAT facilities by SIC code and to determine their
discharge status (active or inactive).
• Industrial Facilities Discharge (IFO) file - The IFD file
provides a comprehensive data base of industrial and municipal point
source dischargers, including discharge flow and location information,
standard industrial classification (SIC) codes, and categorization of
discharge types. This file was used to locate the BAT facilities,
identified by PCS, on specific reaches and to provide wastewater
discharge flows for the water quality model.
• GAGE file - The GAGE file stores data from stream gaging
stations, including: station location, types and frequency of data
collected, and stream flow data (mean, annual, and low flow). The GAGE
file was used to provide stream flows (both average and low) for the
water quality model.
• REACH file - The REACH file is a digital data base of streams,
rivers, reservoirs, lakes, and estuaries in the contiguous U.S. divided
into unique segments called "reaches." The reaches allow EPA (and
other system users) to integrate data from different files and data
bases by assigning unique reach numbers to individual water body
segments. This file identified the type of reach (stream or nonstream).
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* STORE! Mater Quality file - STORET is a data base composed of
several individual, but related, files, and includes data on: stream
flow; physical and chemical characteristics of streams, fish tissue,
and sediment; municipal waste sources and disposal systems; and
pollution-caused fish kills. STORET was used to obtain ambient water
quality information for the ten selected pollutants.
All information contained in these data bases was retrieved during
December 1987, with the exception of the STORET data, which was retrieved in
July 1988.
Screening and Evaluation
Data were retrieved from the EPA data bases and subsequently compiled and
analyzed using a computerized software system. The files were then screened
to select only those facilities that would be covered by the BAT regulations
and could be evaluated by the water quality model. All currently active
facilities were also assumed to be active prior to BAT implementation,
therefore neglecting the impacts on water quality for new sources and plant
closings. The reaches identified as receiving BAT discharges in water quality
model will serve as the basis of retrieving ambient monitoring data. The
following is a brief description of the screening process:
1. The EPA data bases contain information on 120,992 industrial dischargers
and roughly 68,000 reaches. Of these dischargers, 46,467 are inactive
(e.g., closed) or their discharge status is unknown, and 53,621 reaches
do not have any assigned dischargers on them. All inactive/unknown
facilities and reaches without dischargers were excluded from this
study.
2. Of the 74,525 active dischargers, 59,338 facilities are not covered by
the BAT regulations and were not included in this study. This also
removed 8,556 reaches from consideration.
3. Five BAT industrial categories (coal mining, steam electric, plastics
molding and forming, timber products, and pesticide manufacturing) were
not evaluated in this study because their effluent regulations either:
(1) do not specify toxic pollutants; (2) control only a small volume of
the total discharge; or (3) have been rescinded. Therefore, an
additional 8,353 dischargers and 1,593 reaches were excluded from the
model/ambient analyses.
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4. Because It is necessary to correlate dischargers with stream locations
(i.e., reach numbers), those facilities in the EPA data bases without
assigned reach numbers were excluded, resulting in the removal of 1,837
facilities from the study. This step also removed all facilities in
Hawaii, Alaska, and the U.S. Territories, since streams in these areas
are not currently hydrologically linked.
5. The water quality model can evaluate only facilities located on
hydraulic transport ("stream") type reaches; therefore, all reaches
that are nonhydraulic or boundaries (e.g., coastlines, estuaries,
lakes, and shorelines) were excluded. This screening step eliminated
683 facilities and 322 reaches from consideration in the study.
6. The remainder of the facilities and reaches were then screened to
determine if flow data were available. One hundred and forty-four
reaches were excluded because they did not have both average and low
flows (which also eliminated 484 facilities) and 1,232 industrial
facilities did not have process flows (which removed 497 reaches from
consideration). The final step eliminated facilities that may have
erroneous process flows stored in the data base. If the process flow
exceeded the 95th percent!le flow for a particular industrial category,
the facility and its corresponding reach were excluded. This step
removed 108 facilities and 53 reaches because of possible erroneous
process flows.
This screening process, summarized in Table 2-2 and Figure 2-1, identified
2,490 facilities and 1,546 reaches (representing 24,289 river miles) to be
evaluated in the water quality modeling component of the Water Quality
Improvement Study (WQIS). The 1,546 reaches were also used as the basis for
retrieving ambient monitoring data for the second component of this study.
Additional Sources
Additional EPA sources of information (for the model and ambient analysis)
include (1) industry-wide effluent characteristics by industrial category and
(2) EPA ambient water quality criteria.
The industry-wide effluent characteristics were used in the water quality
modeling effort to determine the pollutant concentrations discharged by each
of the facilities evaluated. The source of these concentrations was the
Monitoring and Data Support Division (MDSD) report, Summary of Effluent
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Table 2-2
Summary of Screening Process
Used to Select BAT Facilities and Reaches
for Inclusion in the Mater Quality Improvement Study
Description of Screening Step
Total facilities/reaches in EPA data bases
No. of reaches without assigned facilities
No. of inactive facilities excluded
No. of non-BAT facilities/ reaches excluded
No. of BAT facilities/ reaches not evaluated*
No. of BAT facilities not assigned reaches
No. of BAT facilities/reaches excluded
because of non- steam reach type**
No. of BAT facilities/reaches excluded
because of unavailable reach flow
No. of BAT facilities/reaches excluded
because of unavailable process flow***
No. of BAT facilities/reaches excluded
because of "erroneous" process flow
No. of BAT facilities/reaches evaluated
No. of
Facilities
120,992
0
46,467
59,338
8,353
1,837
683
484
1,232
108
2,490
No. Of
Reaches
-68,000
-53,621
1,668
8,556
1,593
0
322
144
497
53
1,546
*Coal/steam/plastics molding and forming/timber products/pesticides
manufacturing categories.
**Lakes/coast-shoreline/estuary/artificial/etc. ^
***Includes "zero discharge" facilities (those facilities that do not
discharge process wastewater).
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Methodology
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Methodology
Characteristics and Guidelines for Selected Industrial Point Source
Categories: Industry Status Sheets (U.S. EPA, 1986). For direct dischargers,
pollutant concentrations are provided for four treatment levels: RAW
(untreated wastewater), CURRENT (the average level of discharge determined by
sampling during the second phase of the BAT rulemaking process), BPT, and BAT
(the expected BPT and BAT discharge levels based on the required treatment
technology specified in the effluent limitations). These industry-wide
effluent concentrations, developed by EPA's Industrial Technology Division,
were used to provide a consistent source of data for the selected treatment
levels and represent long-term averages. RAW and BAT levels were used in the
water quality model analysis.
The calculated in-stream pollutant concentrations from the water quality
model analysis were compared to EPA ambient water quality criteria (either
chronic freshwater aquatic life or human health ingestion of organisms only
criteria) for the ten selected pollutants. The more stringent human health
ingestion of water and organisms criteria were not used because exposures due
to drinking untreated surface waters (most surface water sources are treated)
are not as likely.
The human health criterion for benzene (a human carcinogen) represents a
risk level of 10 (1 excess cancer death per 1,000,000 people exposed over
a 70 year period). For each pollutant, the lower of the two criteria was
used. Table 2-3 shows the criteria used in this study. Four of the metals
have hardness-specific criteria. For these metals, the median hardness value
(as determined through a separate STORET analysis) for each State was used to
calculate State-specific criteria.
The study used EPA criteria rather than individual State water quality
standards because: (1) most States do not yet have numerical standards for
toxic pollutants; and (2) EPA criteria provided a consistent basis for
comparison with in-stream pollutant concentrations, even though some existing
State standards may be more or less stringent than EPA criteria.
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Nethodology
Table 2-3
EPA Ambient Mater Quality Criteria
Used 1n the Mater Quality Improvement Study
Pol1utant
Criteria (ug/1)
Type
Cadmium
Mercury
Copper
Lead
Nickel
Zinc
Cyanide
Phenol
Toluene
Benzene
Hardness-specific*
0.012
Hardness-speci f1c*
Hardness-specific*
100
Hardness-speci fi c*
5.2
750
650
40
Freshwater aquatic life-chronic
Freshwater aquatic life-chronic
Freshwater aquatic life-chronic
Freshwater aquatic life-chronic
Human health-ingesting organisms only
Freshwater aquatic life-chronic
Freshwater aquatic life-chronic
Freshwater aquatic life-chronic**
Freshwater aquatic life-chronic**
Human health-ingesting organisms only
* Hardness-specific criteria are calculated as follows:
Cadmium e(°-7852nn(hardness)]-3.49)
Copper e(°-8545[1n(hardness)]-1.465)
Lead e(1.273[ln(hardness)]-4.705)
Zinc e(0.8473[ln(hardness)J+0.7614)
** Lowest Reported Toxic Concentration:
SOURCE: EPA Ambient Water Quality Criteria Documents (various dates).
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Methodology
DESCRIPTION OF METHODS TO ASSESS IMPROVEMENTS
The following section contains brief descriptions of the three methods used
to assess water quality improvements that have resulted from the implementation
of BAT treatment technologies.
Hater Quality Nodeling Analysis
Water quality modeling was performed to identify theoretical water quality
improvements by pollutant, as well as by reach. The analysis consisted of
modeling industrial facilities with BAT effluent limitations that directly
control toxic (priority) pollutants. The model calculated theoretical
in-stream concentrations of the ten selected pollutants at pre- and post-BAT
treatment levels under low and average receiving stream flow conditions. The
in-stream concentrations were then compared to applicable water quality
criteria to identify improvements in meeting these criteria. Of the 6,834 BAT
facilities with toxic limitations (not including the 8,353 facilities in the
coal mining, steam electric, timber products, pesticides manufacturing, and
plastics molding and forming categories) identified in the EPA data bases,
2,490 were evaluated in the modeling procedure.
Assumptions and Limitations
In conducting the water quality modeling, a number of assumptions were
made. These assumptions, together with their limitations, are as follows:
1. Industry-wide pollutant concentrations for the BAT industrial
categories were used to represent individual facility discharge
levels. This approach assumes that every facility in a particular
industrial category discharges the same pollutants at the same
concentrations; the only difference between facilities in the same
category is the volume of wastewater discharged. This assumption does
not reflect "real life" conditions, since each facility is different
and effluent levels vary across categories. Since this is a national
study, however, the differences in levels (some higher, some lower)
will tend to cancel each other out.
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Methodology
2. Two treatment levels from U.S. EPA (1986) were used in the water
quality model: RAW and BAT. The RAW treatment level was used to
represent a particular industry's discharge level prior to the
promulgation of BAT. The use of RAW as the pre-BAT discharge level
overestimates the actual pre-BAT (1972) discharge levels because it
does not credit industry with treatment in place at that time. Since
it is not known how much treatment was occurring prior to BAT, RAW
levels were used. The BAT treatment level was used to represent the
levels at which an industry should be discharging after the
implementation of the BAT regulations (post-BAT).
3. Process wastewater flows contained in the IFD data base were used to
represent pre-BAT (RAW) flows. Where flow reduction was required by
the BAT limitations, this was taken into account by reducing the
pollutant concentration by a proportional amount. Flow reduction was
required for the following industrial categories: aluminum forming,
battery manufacturing, coil coating, copper forming, foundries,
inorganic chemicals, iron and steel, nonferrous metals, nonferrous
metals forming, and porcelain enameling.
4. BAT treatment levels were assumed to be the only effluent limitation
imposed on the industries. Water quality-based limitations were not
considered since the site-specific nature of such limitations prevents
a theoretical estimate of their effectiveness.
5. The model assumed the pollutant was completely mixed in the receiving
stream and that no fate-related removal (e.g., sedimentation,
biodegradation, volatilization) occurred. While fate-related removal
could be significant (especially for the organics), this assumption is
partially offset by not considering background concentrations.
6. The model assumed that all currently active BAT facilities (as
designated in PCS) were also active prior to BAT (i.e., plant closings
and new sources were not accounted for).
Analysis
The objective of the water quality modeling was to project pre- and
post-BAT in-stream pollutant concentrations for each reach in the contiguous
U.S. that received wastewater discharges from BAT industries. There are
currently 24 major industrial categories for which BAT effluent limitation
guidelines have been promulgated (as presented in Table 1-1). The effluent
discharge water quality modeling was performed for 19 of the 24 industries
using industry-wide concentrations for the ten selected pollutants. Five of
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Methodology
the 24 industries were excluded because their effluent regulations either did
not specifically regulate toxic pollutants (coal mining, timber products, and
plastic molding and forming); controlled toxics discharge only for a small
volume of the total discharge (steam electric); or have been rescinded
(pesticide manufacturing).
For each of the facilities identified as BAT facilities from the EPA data
bases, individual plant loadings were calculated (the product of industry-wide
effluent concentrations and process wastewater flows) for each of the ten
pollutants. To calculate in-stream concentrations, the individual plant
loadings were summed for each pollutant for all facilities on a particular
reach. These total loadings were then divided by the stream flow (either low
or average, depending on the analysis) and sum of the plant flows. The
following equation illustrates this procedure:
2 (Ce x Qe)
' ' Qs + s ^e)
where: C^ = In-stream pollutant concentration (ug/1)
Ce = Effluent pollutant concentration (ug/1)
Qe - Process wastewater flow (MGD)
Qs = Receiving stream flow (MGD).
This procedure was followed for each pollutant on each reach for the pre-
(RAW) and post-BAT (BAT) effluent levels and summarized on a reach-by-reach
basis (included in Volume II). The resulting in-stream pollutant
concentrations were also compared to water quality criteria (WQC) to determine
compliance.
Ambient Mater Quality Monitoring Data Analysis
An analysis of ambient water quality monitoring data for those reaches
identified as having BAT discharges was also conducted to determine water
quality improvements. Ambient water quality monitoring data (from STORET) for
the ten selected pollutants for time periods reflecting pre-BAT (1970 to 1980)
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Methodology
and post-BAT (1985 to 1988) were used to determine trends in ambient pollutant
concentrations. Corresponding monitoring data (i.e., data from both time
periods) was available for at least one pollutant for 429 of 1,546 reaches
receiving BAT discharges.
Assumptions and Limitations
The following is a brief discussion of the specific assumptions, and their
limitations, made in performing the ambient water quality monitoring analysis:
1. The monitoring period from 1970 to 1980 represents pre-BAT conditions
and the period from 1985 to 1988 represents post-BAT conditions. The
intervening years were considered a time of transition and were not
addressed. All monitoring data for the individual time periods were
averaged together. Improvement trends within each time period are not
considered as well as trends during the transition period.
2. Monitoring data reported below detectable levels were included only
where detected levels were also available. In those instances, the
monitored values were set equal to one-half the detection limit. It
can not be determined whether or not this practice overestimates or
underestimates the actual pollutant concentration.
3. The STORET water quality monitoring data should be used with some
caution, in that:
• The origins of the pollutants monitored include all upstream
sources, including facilities and sources not evaluated in this
study (e.g., POTWs, non-BAT industries, natural and nonpoint
sources);
• Information on the location of the monitoring station(s) in
relation to the BAT industrial facilities (i.e., upstream or
downstream) was not readily available; and
• The flow conditions during sampling were unknown.
Analysis
To aid in the determination of the water quality improvements attributable
to the BAT guidelines, ambient in-stream water quality monitoring data for the
ten selected pollutants were analyzed for two monitoring periods - pre-BAT and
post-BAT. The ambient pollutant data were obtained from EPA's STORET Water
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Methodology
Quality file. Monitoring data that were "unremarked" (i.e., pollutant
concentration was quantifiable) and data "remarked" (pollutant concentration
less than the detection limit) were used in this analysis. The individual
monitoring values were retrieved from STORE! and aggregated on a reach basis.
The average concentration for a particular pollutant for each of the two time
periods was calculated by using both the unremarked and the remarked data
(which was set to one-half the detection limit). This averaging procedure was
used only when there was at least one unremarked value.
In order to compare the two time periods, it was necessary to exclude
average values where data were available for only one of the two time
periods. Of the 1,546 BAT reaches, 429 had ambient water quality monitoring
data available for at least one pollutant for both time periods. The average
concentration for the two time periods were used to determine trends in
chemical water quality. Three different classifications were used to define
pollutant concentration trends: improved, deteriorated, and no change. An
"improved" trend signifies that the pollutant concentration decreased by more
than 10 percent between the two time periods. Likewise, a "deteriorated"
trend denotes an increase in the post-BAT concentration of more than 10
percent. A "no change" designation signifies that the pollutant concentration
did not change by more than 10 percent between the two periods.
Mater Quality Improvement Case Studies
The third approach to determining ambient water quality improvements was
to identify actual improvements (case studies) that can be attributed to the
implementation of BAT requirements. The focus of this effort was different
from that used for the water quality and ambient monitoring data analyses
since all types of improvements would be applicable, not just improvements
from direct dischargers of toxic pollutants. Such improvements could include
reductions in conventional (suspended solids or biochemical oxygen demand) or
nonconventional (ammonia and chlorine) pollutants and reductions in toxic
pollutants discharged from POTWs as a result of the implementation of
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Methodology
pretreatment programs. Improvements could be shown through reduced in-stream
pollutant concentrations, attainment of designated water use, or improved
biological integrity of the receiving stream.
In order to identify possible case studies, the 1988 State Water Quality
Assessment [305(b)3 Reports were reviewed. From these reports, potential case
studies were selected for further investigation. Of the thirty-six 305(b)
reports reviewed, nine States were identified as having potential case
studies. Based on contacts with these nine States, five case studies were
selected to illustrate water quality improvements attributed to the
application of BAT regulations. An additional case study was provided by EPA
Region X. The summary of these case studies are presented in Chapter 3.
A special case study was developed by the Agency to represent improvements
resulting from BAT on a typical estuary. This case study used a water quality
model to project theoretical improvements (similar to the nationwide model)
and analyzed ambient monitoring data to verify these projected improvements.
This special study is also discussed in Chapter 3.
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Chapter Three
RESULTS
The overall results of the three methods used to identify water quality
improvements that are attributable to BAT are presented in this chapter. For
the water quality model and ambient monitoring data, water quality
improvements are presented in terms of river miles that (1) complied with
water quality criteria or (2) showed a decrease in ambient pollutant
concentrations, respectively. Only nationwide summaries are presented here,
along with summaries of specific cases studies in which the implementation of
the BAT regulations have resulted in water quality improvements. The results
of the model/ambient analyses, on a reach-by-reach/State basis, are provided
in Volume II, Technical Appendices.
IMPROVEMENTS IN WATER QUALITY - WATER QUALITY MODEL
As defined in Chapter 1, a water quality improvement can mean either
(1) compliance with water quality criteria after implementation of BAT
treatment technology when criteria had been exceeded prior to BAT, or (2) a
reduction in in-stream pollutant concentrations after BAT. The water quality
model addresses improvements only in water quality criteria compliance, since
theoretically all reaches receiving discharges from BAT facilities have
improved in terms of pollutant concentration reductions (e.g., all industrial
categories evaluated in this study reduced their discharge levels from pre-BAT
to post-BAT).
The model assessed 2,490 BAT facilities on 1,546 reaches (totaling 24,289
river miles). The model calculated theoretical in-stream concentrations for
the ten selected pollutants using industry-wide effluent concentrations,
process wastewater discharge flows, and low (7-Q-10) and average receiving
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stream flows. The results of the water quality model are presented on both an
individual pollutant basis and a reach basis (to determine if all modeled
pollutants comply with their respective criteria).
Pol1utant-by-Pol1utant
Nationwide summaries of the river miles complying (instream concentration
below criteria) and not complying (instream concentration at or above
criteria) with water quality criteria (WQC) for the individual pollutants,
based on pre- and post-BAT discharge levels, using low and average receiving
stream flow are shown in Tables 3-1 and 3-2, respectively. Under low flow
conditions, pre-BAT discharges are projected to result in less than half of
the river miles complying with the WQC for copper (43 percent), lead (47
percent), and cyanide (47 percent). No pollutant had 100 percent compliance
under low flow conditions prior to BAT. After BAT, compliance ranged from
73 (mercury) to 100 percent (phenol, toluene, benzene). The average increase
in compliance was 20 percent. On a pollutant-by-pollutant basis, the
additional percentage of river miles complying with WQC after BAT is shown
below:
Pollutant
Cadmi urn
Mercury
Copper
Lead
Nickel
Zinc
Cyanide
Phenol
Toluene
Benzene
Additional Percentage
of River Miles Complying with
WQC After BAT (Low Flow)
25
7
33
28
22
30
34
8
3 *
9
* 97 percent compliance prior to BAT.
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Table 3-1
Sunaary of Water Quality Modeling Results:
Dalliance with Criteria (at Low Stream Flow)
Pre-BAT
Cadmium River Miles
Percent
Mercury River Hiles
Percent
Copper River Miles
Percent
Lead River Miles
Percent
Nickel River Miles
Percent
Zinc River Miles
Percent
Cyanide River Miles
Percent
Phenol River Miles
Percent
Toluene River Miles
Percent
Benzene River Miles
Percent
Not
Cooplying
w/WOC
9.030.2
an
8,176.4
34X
13.791.9
57X
12,864.3
53X
6,265.7
26X
9.748.1
40X
12,916.3
53X
1,836.1
8X
730.3
3X
2,283.8
9X
Conplying
•/HOC
15.258. 5
63X
16,112.3
6GX
10,496.8
43X
11,424.4
47X
18.023.0
74X
14.540. 6
60X
11,372.4
47X
22,452.6
92X
23,558.4
97X
22,004.9
91X
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Post-BAT
Not
Conplying
w/WQC
3,038.2
12X
6,523.8
27X
5.752.0
24X
6,174.2
25X
1,043.2
4X
2.469.0
10X
4,562.1
19X
0.0
OX
0.0
OX
37.5
OX
Total
Coop lying River Miles
M/UQC Assessed
21,250.5
88X
17.764.9
73X
18.536.7
76X
18,114.5
75X
23.245.5
96X
21.819.7
SOX
19,726.6
81X
24.286.7
100X
24,288.7
100X
24.251.2
100X
24,288.7
24.288.7
24.288.7
24,288.7
24.288.7
24.288.7
24.288.7
24.286.7
24,288.7
24.268.7
Results
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Table 3-2
Suonary of Water Quality Modeling Results:
Co^liance With Criteria (at Average Stream Flow)
Pre-BAT
Cadniun River Niles
Percent
Mercury River Niles
Percent
Copper River Miles
Percent
Lead River Miles
Percent
Nickel River Niles
Percent
Zinc River Miles
Percent
Cyanide River Miles
Percent
Phenol River Niles
Percent
Toluene River Niles
Percent
Benzene River Miles
Percent
Not
Complying
w/WQC
2,807.4
12X
4,704.3
19X
5.421.6
22X
5,764.3
24X
1,328.7
5X
2.915.2
12X
6,059.2
25X
115.0
OX
50.3
OX
44.5
OX
Ccoplying
v/UQC
21,481.3
8BX
19.584.4
SIX
18,867.1
78X
18,524.4
76X
22.960.0
9SX
21,373.5
88X
18,229.5
75X
24,173.7
100X
24.238.4
100X
24.244.2
100X
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Post-BAT
Not
Complying
w/WQC
332.9
IX
2.488.8
10X
923.1
4X
1,007.6
4X
2.6
OX
338.7
IX
436.2
2X
0.0
OX
0.0
OX
0.0
OX
Total
Complying River Niles
w/WQC Assessed
23.955.8
99X
21.799.9
90X
23.365.6
96X
23,281.1
96X
24,286.1
100X
23.950.0
99X
23.852.5
9BX
24,288.7
100X
24.288.7
100X
24.288.7
100X
•••^M
24.288.7
24.288.7
24.288.7
24,288.7
24.288.7
24.288.7
24.288.7
24.288.7
24.288.7
24,288.7
•^•^•va
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Results
Improvements in meeting WQC are less pronounced under average receiving
stream flow conditions. Prior to BAT, between 75 (cyanide) and 100 (phenol,
toluene, and benzene) percent of the river miles assessed complied with WQC.
After the implementation of BAT, compliance ranged from 90 (mercury) to
100 (nickel, phenol, toluene, and benzene) percent. The average increase in
compliance as a result of the implementation of BAT, at average flow, was 10
percent. Individually, the additional percentage of river miles complying
with WQC as a result of BAT for each of the pollutants, is shown below:
Pollutant
Additional Percentage
of River Miles Complying witfr
WQC After BAT (Average Flow)
Cadmium
Mercury
Copper
Lead
Nickel
Zinc
Cyanide
Phenol
Toluene
Benzene
11
9
18
20
5
. 11
23
0 *
0 *
0 *
* 100 percent compliance prior to BAT.
Overall Reach
The second method of evaluating the water quality improvements attributable
to BAT, based on the water quality model, examines the reach as a whole. If
the reach is to meet WQC, then all modeled pollutants on that reach must comply
with their respective criteria. These "overall" reach evaluations, therefore,
assess the effects of BAT on individual reaches for all the selected
pollutants. The results of assessing water quality improvements using this
methodology, under low and average flow conditions, are shown in Figure 3-1.
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Under low flow conditions, only 29 percent of the river miles were
projected to meet all WQC prior to the implementation of BAT controls. After
attaining discharge levels required under the BAT regulations, the model
predicts that 58 percent of the river miles would meet criteria, that is, an
additional 29 percent of the river miles would be in compliance. Even after
BAT, 42 percent of the river miles assessed are projected to exceed criteria
for one or more of the ten pollutants. Under this scenario, mercury and lead
are the main causes of noncompliance.
At average stream flow, only 59 percent of the river miles were projected
to comply with WQC for all the modeled pollutants prior to the implementation
of BAT. After the implementation of BAT, an additional 29 percent of river
miles would comply with WQC; 12 percent will still not comply with criteria.
The major cause of noncompliance after BAT is mercury.
IMPROVEMENTS IN WATER QUALITY - AMBIENT MONITORING DATA
Improvements in water quality, as determined through analysis of ambient
monitoring data, focus on trends in pollutant concentrations (both on an
individual and on a reach basis) as opposed to comparison with water quality
criteria. The primary reasons for this approach center on the general lack of
monitoring data for reaches evaluated using the water quality model and the
method of determining average pollutant concentrations for the pre- and
post-BAT time periods.
Of the 1,546 reaches (24,289 river miles) assessed by the water quality
model, 429 (totaling 8,434 river miles) had monitoring data for at least one
of the selected pollutants for both time periods. None of the evaluated
reaches, unfortunately, had monitoring data for both the pre-BAT and post-BAT
time periods for the selected organic chemicals (phenol, toluene, and benzene).
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Pol 1utant-by-Pol1utant
Table 3-3 presents a summary of the In-stream concentration trends for each
of the seven monitored pollutants. Between the pre-BAT (1970 to 1980) and
post-BAT (1985-1988) time periods, each of the pollutants showed a marked
decrease in in-stream concentration. On the average, each of the pollutant
concentrations decreased in 78 percent of the monitored river miles. Cadmium
and mercury showed the greatest concentration decreases (or improvement) in
monitored levels (84 and 87 percent of the river miles improved). Zinc levels
reflected the least improvement (69 percent improvement). The extent of no
significant change in monitored pollutant concentrations between the two time
periods ranged from 1 percent of the river miles (for mercury) to 11 percent
of river miles (for copper). A deterioration, or increase in concentration,
occurred along some reaches for each pollutant. The extent of deteriorations
ranged from 11 percent of the river miles (for cadmium) to 25 percent of river
miles (zinc).
Overall Reach
Using a method to show overall trends on a reach basis (similar to the
method used in presenting the results of the water quality model for overall
compliance with WQC), the ambient monitoring data were analyzed to determine
overall trends in pollutant concentrations for the monitored pollutants.
Using this method, about 76 percent of the river miles with monitoring data
available showed an overall improvement (or net decrease in pollutant
concentrations). Roughly 14 percent of the river miles showed a net increase
(deterioration) in monitored concentrations and 11 percent showed no
significant change. Figure 3-2 illustrates these overall trends based on the
ambient monitoring data analysis.
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Table 3-3
Summary of Ambient Monitoring Data Analysis:
Pollutant Trends
Improved No Change
Cadmium
Mercury
Copper
Lead
Nickel
Zinc
Cyanide
River Miles
Percent
River Miles
Percent
River Miles
Percent
River Miles
Percent
River Miles
Percent
River Miles
Percent
(
River Miles
Percent
3,822.6
MX
2.807.4
87X
4,349.9
70X
4.659.7
8zx
3.590.4
72X
5,296.2
69X
^
1,228.2
SOX
193.0
4X
31.5
IX
667.3
11X
279.3
SX
229.8
5X
498.1
6X
110.7
7X
Deteriorated
519.5
11X
375.6
12X
1.238.2
20X
766.1
13X
1.172.9
23X
1.889.7
25X
205.3
13X
Total
Monitored
4.535.1
3,214.5
6.255.4
5,705.1
4.993.1
7.684.0
1.544.2
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890
n 1*1
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TOTAL RIVER MILES ASSESSED: B434
^Jxq NO SIGNIFICANT CH
ffiffiffl DETERIORATED
[" | IMPROVED
ANGE
* River miles for reaches with BAT facilities and monitoring data
for one or more of the ten toxic pollutants.
Note: Percentages add up to more than 100 percent due to rounding.
•Figure 3—2. Summary of Ambient Monitoring Data
Analysis: Overall Trends for BAT
Reaches .
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IMPROVEMENTS IN WATER QUALITY - CASE STUDIES
Potential case studies screened for this study could represent any
improvement in water quality attributable to the implementation of BAT
regulations, including controls on conventional pollutants and regulations
applicable to indirect dischargers. However, the focus was on toxic pollutant
controls for direct discharging facilities. After a review of a number of
State 305(b) reports as well as conversations with State officials, it appears
that the focus of case studies have been on municipal discharges, where
controls on oxygen-demanding pollutants and nutrients have resulted in
improved oxygen levels in streams. The major concern with toxic chemicals, as
evidenced by the 305(b) reports, is sediment contamination, primarily because
of PCBs and pesticides. Little information is available concerning
improvements that have resulted from toxic pollutant discharges,
especially instances involving technology-based (i.e., BAT) controls.
However, six studies have been reported that indicate improvements in water
quality resulting from BAT or BAT-type controls.
In addition to the above case studies, a detailed water quality model and
ambient monitoring data analysis was performed by the Agency on an estuary
(Delaware River Estuary) to highlight the effects of BAT regulations on these
types of waterbodies.
Long Island Sound - Connecticut
In 1985, the Connecticut Department of Environmental Protection (CT DEP)
initiated a study to collect current fish tissue contaminant data for
comparison with historical data in order to show temporal trends. Of the many
sites and organisms selected for testing, oyster data obtained from Bridgeport
Harbor and the Housatonic River areas indicated that these contaminated areas
had improved over the past decade. Both Bridgeport Harbor and the Housatonic
River have a heavy concentration of metals-related industries (metal
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finishing, copper forming, and foundries). The comparison of 1972-1974 oyster
metal concentrations to the data collected in 1985-1986, shown in Figure 3-3,
indicates that the "levels of cadmium, chromium, copper, mercury and zinc were
currently lower than the lowest concentrations observed in an intensive study
from the early 1970s. Although the 1985-1986 survey was not detailed enough
to permit rigorous statistical analysis, the disparity in metals levels
strongly suggests a reduction in metals contamination of oyster tissues in the
Bridgeport and Housatonic Rivers" (NY DEC, 1988). Since Connecticut currently
does not write water quality-based permit limitations, but instead bases its
industrial discharge levels on BAT-type standards, the improvements in metals
concentrations can be at least partially attributed to reductions in discharge
levels from the metal industries located in these areas.
Naugatuck River - Connecticut
Another example of water quality improvements in Connecticut is the
Naugatuck River. According to CT DEP (1988), the Naugatuck was once
considered one of the most polluted rivers in the nation. From 1973 to 1976,
CT DEP issued abatement orders to 77 industrial dischargers along the river.
Metal finishers, the most prevalent type of industry on the river, were
required to neutralize acids, destroy cyanide water, and precipitate heavy
metals (BAT-type treatment technologies). "Monitoring data has shown a marked
reduction in heavy metals, such as copper and zinc, and improved pH levels.
While the river was virtually devoid of aquatic life in 1970, water quality
has now improved to the point where the upper 22 miles ... have been stocked
with trout on an experimental basis. The river has been identified by CT DEP
Fisheries Unit as a potentially valuable resource for cold water and anadromous
fisheries" (CT DEP, 1988). Water quality problems still exist on the lower
portions of the river, which will require more stringent (e.g., water
quality-based) permits in order to achieve water quality goals.
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COPPER
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-BV • -*-
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BRIDGEPORT HARBOR HOUSRTONIC RIVER
•Figure 3-3. Trends in Metal Concentrations
in Oysters - Long Island Sound.
• Source: NY DEC, 1388.
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South Fork Coeur d'Alene River - Idaho
The South Fork Coeur d'Alene River has had serious pollution problems for
many decades, which were the result of ore mining and related activities. At
the time of the enactment of the Federal Water Pollution Control Act of 1972,
heavy metals concentrations in the river reached 23,000 ug/1 for total zinc,
200 ug/1 for total cadmium, and more than 500 ug/1 for total lead during the
summer low flow periods. These levels are roughly two orders of magnitude
higher than EPA's acute (short-term) water quality criteria for protection of
aquatic life. As a result of the 1972 Act, effluent limits for industrial
dischargers were required. EPA's Region X Office initiated a monitoring
program in 1972 to document the improvements in the South Fork Coeur d'Alene
River and identify any remaining sources of heavy metals. Figure 3-4 shows
the trends in zinc, cadmium, and lead at the mouth of the South Fork Coeur
d'Alene River from 1972 to 1986 (USEPA, 1987). Each metal shows a decrease of
roughly 90 percent during this period. While metal concentrations still
exceed criteria levels, conditions of the South Fork are now suitable for many
of the less sensitive indigenous species of aquatic biota, and conditions of
the mainstream are enabling game fish to return downstream of the South Fork
confluence. Data now indicate that nonpoint sources are responsible for 50 to
90 percent of the metals.
Lower Fox River - HisconsIn
The Fox River Valley is heavily industrialized, especially with paper
mills, and 50 percent of all point source discharges occur in the lower
portion (from Depere to Green Bay). High pollutant loadings from the paper
mills have contributed greatly to the historically low dissolved oxygen levels
in the Lower Fox River. As a result of the Clean Water Act of 1972, improved
wastewater treatment systems, which began operation in the 1970s, have
resulted in the attainment of the 5 mg/1 dissolved oxygen standard for much of
the time period after the treatment systems became operational. Permitted
effluent levels for the paper mills have been set at the limits established by
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25,OOO —i
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the national categorical standards (BPT/BAT), however, many of the mills are
discharging at lower levels. The Wisconsin Department of Natural Resources
(WDNR) is currently revising its effluent permits to reflect water
quality-based limits for toxic pollutants; nonetheless, the national effluent
standards have had a beneficial impact on the Lower Fox River. According to
historical trends related to macroinvertebrates, there has been a recent
increase in pollution intolerant aquatic life (WDNR, 1985).
Other Case Studies
There are several other case studies in which the water quality
improvements can be at least partially attributed to the implementation of
national categorical effluent standards. The first involves the Scioto River
in Ohio. Using a macroinvertebrate index as a measure of overall water
quality, the Ohio Environmental Protection Agency (OEPA) determined that prior
to 1976, the Scioto River had marginal attainment of a warm water habitat. A
great change in the index was noted between 1977 and 1978, reflecting an index
indicative of exceptional macroinvertebrate fauna. These exceptional
conditions continued to exist through 1985. The changes in water quality "are
most attributable to improvements in wastewater treatment" at a major pulp and
paper facility on the river (OEPA, 1988).
Using the same macroinvertebrate index, OEPA has shown an improving trend
in biological conditions on the Mohican River. "These improvements may be
attributable to industrial waste pretreatment (electroplaters) requirements in
the cities of Mansfield and Ashland, as well as wastewater treatment
improvements by various industries and WWTPs" (OEPA, 1988).
Delaware River Estuary
To determine the effects of the BAT regulations on estuaries a case study
of the Delaware Estuary was performed. The general methodology for this case
study follows that used in the nationwide analyses of BAT facilities and
reaches. A modified water quality model, developed for EPA [from information
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obtained from the National Oceanic and Atmospheric Administration (NOAA)], for
use in determining 304(1) lists of waters impaired by toxics, was used to
project in-stream pollutant concentrations from pre- and post-BAT effluent
discharges from BAT industries. This model used the same industry-wide
concentrations of the ten selected pollutants as the nationwide water quality
model analysis. Ambient water quality monitoring data were also retrieved
from EPA's STORET Water Quality File to show trends in selected pollutant
levels between the pre-BAT (1970-1980) and post-BAT (1985-1988) time periods
and to verify projected compliance with WQC (no State standards available).
This analysis was based on estuary zones rather than reaches. There are
three zones in any estuary: a freshwater tidal zone, a saltwater tidal zone,
and a mixing zone located between the two. For this analysis, the in-stream
(or in-estuary) pollutant concentration was calculated using "pollutant
concentration potentials," a procedure developed by NOAA, that takes into
consideration both the flow available for dilution and the zone characteristics
(salinity). The concentration potentials do not consider pollutant fate. A
more detailed explanation of this approach can be found in U.S. EPA (1988).
The Delaware estuary water quality model evaluated 64 BAT facilities
discharging at pre- and post-BAT levels., Twenty-two discharged to the
freshwater zone (Zone 1), 39 discharged to the mixing zone (Zone 2), and
3 discharged into the saltwater zone (Zone 3). The model evaluated each zone
independently and did not account for inputs from upstream zones or other
sources. Table 3-4 presents the results of the water quality model for the
Delaware estuary. Prior to the implementation of BAT, Zone 1 was projected to
not comply with freshwater criteria for mercury, copper, lead, zinc, and
cyanide. After the facilities met the discharge requirements of BAT, all
pollutants were projected to comply with of WQC. Likewise, in Zone 2, four
pollutants (mercury, copper, lead, and cyanide) did not comply with WQC prior
to BAT and full compliance was projected after BAT. The WQC used for this
zone was the more stringent of the two freshwater and saltwater criteria. All
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pollutants in Zone 3 were projected to comply with WQC (saltwater) both before
and after the implementation of BAT.
The ambient monitoring data analysis used information obtained from
monitoring stations designated as "estuarine," as opposed to ambient "stream"
stations used in the nationwide evaluation. Values that were reported as
"less than detection limit" were handled in the same manner as the nationwide
evaluation. Data from two stations were used to represent average pollutant
concentrations in Zone 1 and seven stations were averaged for Zone 2 (see
Table 3-5). No ambient estuarine data were available for Zone 3 and limited
data (in terms of the number of pollutants) were available for Zones 1 and 2.
The results of the monitoring data analysis compare favorably to the water
quality model. In Zone 1, the average pre-BAT concentrations for copper and
lead did not comply with WQC. After BAT, only lead still did not comply with
criteria, but only by a slight margin. All monitored levels decreased by at
least 83 percent. In Zone 2, all pollutants showed a marked decrease in
average pollutant concentration. Cadmium decreased by 91 percent, mercury by
55 percent, copper and lead by over 90 percent each, and zinc by 81 percent.
The pre-BAT average concentrations for cadmium, mercury, copper, and lead were
above WQC levels. These pollutants were also above WQC after BAT, but by a
much smaller margin. One possible reason to account for the non-compliance is
that 12 of the 39 BAT facilities were in the organic chemicals category and
may not have fully implemented the requirements of the BAT regulations (the
phase II regulations were promulgated in November 1987).
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Table 3-5
Ambient Water Quality Monitoring Data Sunnary for Delaware Estuary
Average Pollutant Concentration (ug/11
Number of Cadmium Mercury
Zone Facilities 70-BO 85- 70-80 85-
Copper
Lead
70-80
85-
70-80 85-
Zinc
70-80 85-
22
39
3
29.2
2.52
1.6
0.722
49.7 *
51.5 *
2.70
2.92 *
53.2 *
53.8*
5.1 *
5.1 *
61.0
64.0
10.4
11.9
Fresh WQC
Salt WQC
1.1
9.3
0.012
0.025
11.4
2.9
3.0
5.6
102
86
* Average concentration exceeds WQC.
NOTE: Fresh WQC conpared to ill-stream concentrations in Zone 1.
Salt WQC compared to in-streaa concentrations in Zone 3.
The more stringent of the two WQC was conpared to in-stream concentrations in Zone 2.
70-80 represents the pre-BAT time period (1970-1980).
85- represents the post-BAT time period (1985-present).
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Chapter Four
CONCLUSIONS
The three components of this study indicate that water quality has improved
as a result of the implementation of the BAT effluent limitation regulations:
Hater Quality Model.
The results of the water quality modeling effort, which evaluated 2,490
BAT facilities impacting 24,289 total river miles (1,546 unique reaches), show
that under low stream flow conditions 14,169 river miles (58 percent) comply
with all the water quality criteria for the ten selected pollutants after the
implementation of BAT (an additional 29 percent improvement over pre-BAT
conditions).
Under average receiving stream flow conditions, the model predicts that
59 percent of the river miles modeled will comply with all criteria prior to
the implementation of BAT. After BAT, 88 percent of the river miles assessed
(an additional 29 percent) were projected to meet all ten criteria. The major
causes of noncompliance with criteria are discharges of mercury, lead, and
copper. All other pollutants comply with criteria in at least 81 percent of
the assessed river miles at low flow (98 percent at average flow).
The use of the water quality model does have certain limitations. The
model does not consider upstream sources of pollutants, nor does it consider
the discharge of other "nonselected" pollutants by the BAT facilities. These
sources could impact the extent of compliance with criteria. This limitation
is offset to a certain extent by the fact that pollutant fate is also not
considered. The model also assumed all facilities, within a particular
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category, discharged the same pollutants at the same concentrations. While
this is not a particularly valid assumption when dealing with an individual
facility, on a nationwide basis, the tendency to overrepresent or
underrepresent actual discharge levels is, at least partially, eliminated.
Finally, this modeling effort does not take into consideration the treatment
technologies in place prior to the Clean Water Act, and thus the actual
improvements should be somewhat less than projected.
Based on the results of the water quality model, the national categorical
effluent standards program (BAT) has been found to be an effective tool for
improving water quality up to a point. However, there may be a need for
additional water quality-based controls beyond BAT in some cases in order to
meet State water quality standards. The model predicts that 42 percent of the
assessed river miles may exceed EPA national water quality criteria under low
stream flow conditions after BAT is in place (12 percent of the river miles do
not comply at average flow conditions). This projection, however, is not a
precise measure, since it is dependent on the number of pollutants evaluated.
In many cases, water quality-based NPDES permit limits may have been already
developed in order to meet locally applicable State water quality standards,
and in other cases new water quality-based permit limits may be needed.
Ambient Water Quality Monitoring Data
Improvements in water quality, based on the ambient water quality
monitoring data analysis, are not as evident. Appropriate ambient monitoring
data were available for only 35 percent of the river miles assessed by the
model, and no comparable data (same reach for both the periods) were available
for the organic chemicals selected. This lack of ambient monitoring data is
expected, especially for the organic chemicals, since the Agency's major focus
during the early and mid-1970's was on conventional pollutants. Only after
the Clean Water Act of 1977 were toxic pollutants emphasized. It is also
important to note that ambient monitoring data is collected for many other
purposes that just to determine the effectiveness of controls placed on
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industrial discharges. Nevertheless, it is apparent that a more goal-oriented
and focused effort needs to be made to truly evaluate controls on industrial
discharges.
The monitoring data analysis, however, did show a great improvement, in
terms of pollutant reductions, between the pre- and post-BAT time periods.
About 76 percent of the river miles (assessed in this evaluation) indicated an
overall decreasing trend in in-stream concentrations of toxic pollutants.
However, about 14 percent showed an increase. Concentrations of individual
pollutants (cadmium, mercury, lead, and cyanide) improved in 80 percent or
more of the assessed river miles, while zinc, nickel, and copper showed
increases (deterioration) in 20 to 25 percent of the assessed miles.
The full benefit of the implementation of BAT is not reflected in the
ambient monitoring analysis. National categorical standards have recently
been promulgated for one major industry, organic chemicals manufacturing,
which will reduce the industry's toxic pollutant direct discharge loadings by
1.1 million pounds per year. Standards for another category (pesticides
manufacturing) are currently being prepared. While the ambient data do
reflect some of the benefits attributable to BAT, the full effect will not be
evident until the early 1990s. The second component of this study has several
other limitations. The sources of pollutants represented in the monitoring
data are not known, although these sources should include the BAT facilities
evaluated in the model. Other sources could include upstream BAT facilities,
municipal facilities, hazardous waste sites, nonpoint, and natural
(background) sources. Reductions in the monitored pollutants could possibly
be attributed to controls on these sources. Another factor that could account
for some of the decreasing pollutant concentration trends is the increase in
accuracy of the analytical techniques used to determine the pollutant
concentrations. In the past decade, increased sophistication of the
laboratory equipment has enabled the detection limits for all pollutants to be
1owered.
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The statistical significance of comparing monitoring data >frotn time
periods of different spans was not evaluated. Also, the naturally occurring
variability in monitored pollutant levels was not assessed; however, the
effect of such variability should be reduced by using average values over the
periods evaluated.
Case Studies
Actual cases where the implementation of BAT has resulted in water quality
improvements present the best illustration of the effectiveness of the
categorical standards. The few case studies that are available show that the
BAT regulations have had a positive impact on the receiving stream quality, in
terms of both chemical and biological improvements. In most instances, the
streams/rivers assessed in these case studies were highly polluted prior to
BAT. Even after the discharge levels were reduced to levels proscribed by
BAT, additional water quality-based controls may be needed in order to meet
State water quality standards. In all cases, the implementation of BAT has
resulted in considerable improvements in the biological quality (as measured
by an increase in less pollution-tolerant aquatic life) of the receiving
waters.
The special case study predicted and verified that improvements have
occurred in the chemical water quality of the Delaware estuary. All
pollutants, as projected by the water quality model, that exceeded criteria
prior to BAT complied with criteria after the implementation of these
regulations. The ambient monitoring data analysis verified these
improvements. However, in Zone 2, the area most influenced by organic
chemical manufacturing discharges, the predicted improvements are not yet
fully realized (e.g., the BAT regulations for the organic chemicals category
are not yet fully implemented by industry).
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Summary of Hater Quality Improvements
Considering the results of each component of this analysis, together with
their respective assumptions and limitations, the BAT regulations have been an
effective step toward improving the quality of our nation's waters. The
extent of this effectiveness is difficult to assess using the existing EPA
data sources and considering the fact that the full benefit of BAT has not yet
been realized. Also, by not considering improvements resulting from the
categorical pretreatment requirements, the extent of the improvements
resulting from the overall national water quality program are underestimated.
There may be a need for additional water quality-based controls beyond BAT in
some cases to meet State water quality standards. In addition, as required by
Section 304(m) of the Water Quality Act of 1987, the Agency will establish a
schedule for: (1) the annual review and revision of promulgated effluent
guidelines, and (2) the promulgation of regulations for industrial categories
identified as sources of toxic and nonconventional pollutants for which
guidelines have not previously been established.
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Chapter Five
REFERENCES
Connecticut Department of Environmental Protection, 1988. State of
Connecticut 1988 Water Quality Report to Congress. Water Compliance Unit.
New York Department of Environmental Conservation, 1988. New York State Water
Quality 1988. Division of Water, Bureau of Monitoring and Assessment.
Ohio Environmental Protection Agency, 1988. Ohio's Water Quality Inventory -
1988 305(b) Report, Volume I. Division of Water Quality Monitoring and
Assessment. Columbus, Ohio.
U.S. Environmental Protection Agency, 1988. Summary of Effluent
Characteristics and Guidelines for Selected Industrial Point Source
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