-------
In all case study municipalities, one of two types of pollutant Imita-
tions has been established in industrial wastewater permits: concentration
limits or mass emission limits. Because selection of limitation criteria is
based upon local situations and POTW operational parameters, the use of either
type of limitation is fully addressed in the discussion of each municipal
program.
Municipalities gave one of three generic reasons for adopting local
programs: 43% cited the improvement of water quality; 43% cited the reduction
of POTW treatment costs; and 14% cited the improvement of sludge treatment,
hauling, and disposal practices.
SPECIFIC POTW INDUSTRIAL PRETREATMENT PROGRAMS
Muncie, Indiana
Muncie's POTW recieves a fairly large industrial input; wastewater
from about 80 industries contributes about one-third of its 18 MGD flew.
Industries such as foundries, metal platers, and manufacturers of batteries,
wire and transformers, and automotive parts produce most of the metal, oil,
and acid wastes that were once major problems for the city. In recent years,
the industrial discharges have been brought almost fully under control as a
result of pretreatment limitations and industrial investment in pretreatment
equipment.
Muncie established local ordinances for pretreatment limits on industrial
wastes in 1972. Industries that discharge organic wastes to the POTW must pay
a user charge for BOD loading greater than 250 mg/liter. The system in Muncie
now generates about $125,000 in revenue per year from nine industrial users.
Although no charges are assessed for toxic discharges, industries must meet
the required pretreatment limits under reasonable time schedules. Figure B5-2
illustrates the success that the pretreatment program has had in limiting
pollutant concentrations entering the POTW (USEPA, 1980a).
B-67
-------
70
60
50
40
9
JH 30
a
sa
20
10
Influent
-• — ••»» Effluent
1972 1973 1974 1975 1976 1977 1973
Figure B5-2. Industrial Loading of Lead into rhe Huncie, Indiana ?OT«. 1972-1978
3-68
-------
Los Angeles County, California
The county sanitation districts of Los Angeles receive in flow of about
469 MGD, and about 85 MGD is from industrial sources. Table B5-III provides a
breakdown of the principal industrial wastewater sources to the municipal
plants. In 1980 the plants received a total of 30,925 million gallons of
industrial waste.
Institution of the district's industrial wastewater control program
brought significant improvements to effluent quality. Table 35-IV provides
before and after influent pollutant values for the sanitation districts of Los
Angeles County. Over the 5-years during which this industrial pretreattaent
program was implemented, heavy metals and toxic organics pollutants to the
treatment plant were reduced by 44% and 98% respectively (Kremer, 1981).
Grand Rapids, Michigan
During the late fifties and early sixties, excessive industrial dis-
charges of cyanide and heavy metals from metal platers were causing severe
water quality deterioration of the Grand River. Grand Rapids has one of the
largest concentrations of electroplating firms in the country, and fish kills
in the Grand River were attributed to the effluents from these firms. Public
attention was focused on the deterioration of the once healthy Grand River,
and in 1969 the city adopted a sewer use ordinance establishing effluent
limits for heavy metals and cyanide. Effluent limits were also established
for BOD (300 mg/liter), suspended solids (350 mg/liter), fats, oil, and grease
(50 mg/liter), and phenols (0.02 mg/liter). A cost recovery system requiring
industrial users to pay proportionate shares of the cost for effluents in
excess of the limits for BOD and suspended solids was a part of the ordinance.
Table B5-V and Figures B5-3 and B5-4 illustrate the effectiveness of the
Grand Rapids industrial waste pretreatment program for heavy metals and
cyanide, respectively. Most significantly are the reduction in influent con-
centrations shown on Table 5-V. For the heavy metals as a group, the reduc-
tions for influent and effluent concentrations are 37% and 927, respectively.
The results shown on Figures 35-3 and B5-4 suggest that higher removal
efficiencies can be obtained at lower influent concentrations, with a greater
3-69
-------
TABLE B5-1II
PRINCIPAL INDUSTRIAL SOURCES OF WASTEWATER
RECEIVED 3Y LOS ANGELES COUNTY SANITATION DISTRICTS
Industry
Average
Flow (MGD)
Percent of
Industrial Flow
Percent of
District Flow
Nuaber of
Companies
Petroleum
Refining &
Related
Industries
Fabricated
Metal
Products
14.0
9.7
16.5
11.4
3.0
2.1
27
419
Paper and
Allied
Products
9.4
11.1
2.0
46
Food and
Kindred
Products
Chemicals
and Allied
Products
9.2
5.1
10.9
6.0
2.0
1.1
208
172
Source: Kremer, 1981
3-70
-------
TABLE B5-IV
INFLUENT POLLUTANT VALUES BEFORE AND AFTER INDUSTRIAL
PRETREATMENT PROGRAM, LOS ANGELES COUNTY, CALIFORNIA
Pollutant
Influent (kg/day)
Before (1975) After (1980) Percent Reduction
Phenols
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Cyanide
PC3
DDT & Metabolic •
Products
4626
34
50
952
680
1.36
408
454
2494
590
29
295
3200
6.8
36.3
635
408
0.91
295
227
1224
194
0.91
0.91
30
80
27
33
40
33
28
50
51
73
97
>99
1__ . , u • U • • 1 1 J •
This pollutant, which is essentially discharged only by industrial sources,
was a candidate for source control limits. However, a reduction in the 4,626
kg/day discharge was not required to meet effluent discharge requirements, so
no limits were adopted. Phenols are discharged nainly by petroleum refining
and allied companies. The decrease in phenol discharges is related to
decrease in gasoline production.
2
It is estimated that only abut 1.6kg/day of the decrease is attributable to
the district's source control program. Most of the decrease has been due to
changes in formulations of household pesticides and action by State of
California and OSHA.
While the districts instituted a source control limit for mercury, all avail-
able information shows there are no significant industrial discharges of
mercury to district sewer systems. The observed decrease is similar in
percentage magnitude to that observed at the district's residential treatment
plant. Therefore, factors other than the district's source control program
account for the apparent 33% reduction.
Source: Kramer, 1981
3-71
-------
TABLE B-5-V.
EFFECT OF SEWER USE ORDINANCE ON
INFLUENT AND EFFFLUENT CONCENTRATION, 1968 to 1977,
GRAND RAPIDS, MICHIGAN
Pollutant
Chromium
Copper
Nickel
Zinc
Cyanide
Influent
Z Reduction
90
89
87
79
93
Effluent
% Reduction
96
93
89
85
96
Source: Bieaer & Bouma, 1978b
B-72
-------
ea
a
u
3
Influent:
Effluent
1968 1970 1972 1974 1976 1978
Figure B5-3. Total Metals Influent and
Effluent Concentrations, 1963-1977
3-73
-------
3.0
2.5
C 2.0
s
1.5
1.0
0.5
Influent
Effluent
1968 1970 1972 1974 1976 1978
Figure B5-A. Cyanide Influent and Effluent
Concentrations, 1J68-1977
-------
percentage of the heavy metals adsorbed onto the sludges. Neufald (1975)
confirms these findings in tests with zinc and particularly cadmium using
biological sludges. The 40 POTW Study (Feiler 1980 and Southworth 1931)
indicates percent removal to be independent of concentration found in POTW
influents.
The most significant direct benefit from the sewer use ordinance has been
the improvement in water quality of the Grand River. By 1974 steelhead trout
and Coho and Chinook salmon were sprawning in the river. The city has
purchased parkland along the river for recreational activities, and has now
constructed and improved boat ramps for canoe and other boating enthusiasts
(Biener & Bouaa, 1978a & b).
Oakland, California
In the late sixties, the East Bay Municipal Utility District, head-
quartered in Oakland, California, determined that a wastewater control program
was needed for POTW effluents to achieve Federal and State standards.
Industrial discharges received in the District are primarily from pigment
manufacturing, organic chemical refining, petroleum products processing, metal
plating, and food processing. In December of 1972, a wastewater control
ordinance was adopted that created the District's pretreatment program.
The results of this new pretreatment program are shown on Table 35-VI.
As indicated, much lower influent concentrations of arsenic, chromium, copper,
lead, mercury and zinc were noted and accordingly lower discharge concentra-
tions, see Table B5-VII. Removal percentages are good but not direct In-
comparable before and after because in addition to the pretreatment program,
secondary treatment was implemented during this period (Damas, 1981).
Chicago, Illinois
The Metropolitan Sanitary District of Greater Chicago operates and
maintains six plants that treat a flow of approximately 1,500 MGD.
Metropolitan Chicago has the nation's largest industrial concentration. There
B-75
-------
TABLE B5-VI
HEAVY METAL INFLUENTS BEFORE AND AFTER
PRETREATMSNT PROGRAM OAKLAND, CALIFORNIA
Pollutants
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Zinc
Past
Values (kg/day)
<3
7
209
318
106
95
35
495
Recent
Values (kg/ day)
<1
6
45
54
51
.5
35
263
Percent
Reduction
67
14
78
83
52
>99
0
71
Source: Danas, 1981
3-76
-------
TABLE B5-VII
POTW EFFLUENT PAST AND RECENT QUALITY VALUES FOR HEAVY METALS,
OAKLAND, CALIFORNIA
Pollutants
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Zinc
Past
Values (kg/day)
<3.0
4.0
175.0
129.0
60.0
4.0
37.0
385.0
Recent
Values (kg/day)
<1.0
0.6
7.4
30.0
4.6
<0.1
30.0
46
Percent
Reduction
67
85
96
77
92
>98
19
88
Source: Damas, 1981
3-77
-------
are about 11,000 industries in the 865 square mile district, over 500 metals
platers are included in this total.
In September of 1969, a Sewage and Waste Control Ordinance was adopted.
The purpose of the ordinance was to
o Ensure that the effluents from the six POTWs would meet new discharge
standards imposed by the state
o Protect the treatment plants from upsets
o To allow industry ample latitude regarding the type of pretreatment
systems needed to control discharges to the sewer system.
The ordinance sets specific concentration limits for pollutants and
limits conditions for the discharge of wastes to the sewage system. The
controlled discharge of these pollutants is considered necessary to ensure
occupational safety; to protect the physical, chemical, and biological inte-
grity of the system; and to allow the sludge produced by the plants to be used
as a fertilizer for land reclamation.
The effectiveness of the program is evidenced by the reductions in metal
loadings Co the District's plants. Figure B5-5 provides a 7-year profile of
heavy metal loadings. A 702 reduction in these metals was reported for 1977
compared to 1971. Table 35-VIII provides the percent reductions of specific
metal influents to the plants from 1971 to 1977 (Lue-Hing, 1981).
Greensboro, North Carolina
Greensboro operates one POTW that receives 8 MGD and one that receives 18
MGD; 173 of the flow, 28Z of the suspended solids, and 49% of the BOD volume
of industrial waste water. Textile manufacturers account for the largest
volume of industrial waste water. Other local industries include cigarette
manufacturers, meat packers, dairies, food processors, metal platers, and
chemical manufacturers.
The waste ordinance adopted in Greensboro established limits for copper,
zinc, chromium, and cyanide. No limits for BOD or suspended solids were
adopted, but these pollutants are subject to a surcharge.
B-78
-------
Klgure B5-5. Heavy Metal Loading to Six POTWs, Chicago. Tlliiiolu
20 -
1 O
J y
18 -
17 -
16 -
15 -
14 -
13 -
12 -
11 -
10 -
9 -
a -
7 -
It -
5 -
19,181 Kg
13,340 Kg
9,982 Kg
7,523 Kg
5.580 Kg s 5,723 Kg
r"-i J
1971
1972
1973
1974
1975
1976
1977
-------
TABLE B5-VIII
METAL REDUCTION IN PLANT INFLUENT,
CHICAGO, ILLINOIS
Pollutants
Cadmium
Chromium
Copper
Lead
Nickel
Zinc
Past
Values (kg/day)
397
5,185
2,161
2,044
2,437
6,956
Recent
Values (kg/day)
168
1,419
586
535
434
2,581
Percent
Reduction
58
73
73
74
82
63
Source: Lue-Hing, 1981
3-80
-------
Two specific improvements in industrial effluent pollutant concentrations
are noteworthy. A local poultry processing plant reduced both BOD and
suspended solids by 66% by installing a blood trench to prevent waste from
entering the sewer system. A slaughterhouse reduced BOD by 68% and suspended
solids by 59% by improving process operations.
Greensboro has found its pretreatment program to be financially self-
sustaining. Surcharges imposed upon industry add considerable income to the
general revenue of the local water and sewer department. Industry is kept
aware of the problems associated with the treatment of industrial waste and
the related POTW costs. Waste loads to the POTW are lower than, they would be
without a control program, and information on both current and long-term waste
strength and volume have permitted extended predictions of treatment plant
life (Shaw, 1970)
Champaign, Illinois
In the late sixties, a major food processor in Champaign, Illinois,
decided to expand plant size to increase production of margarine, salad
dressings, and cheeses. Before accepting the additional load from the
expanded plant, the municipality required the processor to meet the following
limits contained in a proposed city ordinance:
o 200 mg/liter of BOD
o 200 mg/liter of suspended solids
o 100 mg/liter of fats, oils, and grease
In order to achieve the required effluent concentrations, the processor
installed pretreatment equipment designed to handle a flow of 500,000 G?D.
The effectiveness of the pretreatnent equipment was evident in the percent
removal of the three pollutants regulated by the municipality. Figure 35-6
provides this information for the first 7 months of operation. Values
exceeding the limits prescribed by the municipality were noted during the
first 3 months, but the concentrations fell to an acceptable level by the
beginning of the fourth month. The high initial values were attributed to the
startup problems associated with dewatering digested sludge. These problems
3-81
-------
to
00
100
95
90
85
80
/5
70
"
60
a -
„
40
\
m .
I
\
\
\
4
\
\
\
f
J 4 '
Mimlhtt
Removal KtfIclenctea f»r Hrnl
..il|;n. 11 HIM.la
- BUI)
- Suspended Sol Ma
l.O «f
-------
were corrected, and the equipment has operated well since that time, with all
pollutant removal efficiencies equal to or greater than 97%.
Figures 35-7, B5-8, B5-9 provide comparisons between raw waste and final
effluent for 300; suspended solids; and fats, oils, and grease, respectively.
Orange County, California
As early as 1954, the Orange County Sanitation District recognized the
need to control the quantity and quality of wastewaters discharged to their
sewerage systems. In subsequent years, the District adopted ordinances that
established industrial waste discharge permits, provided for monitoring of
discharges, and set limits for certain conventional and toxic wastes. The
toxics ordinance was in response to the clean water legislation of the early
1970's and sought to meet stated environmental goals of the 1972 Amendments.
The ordinance represented a cooperative effort between the District,
local industry representatives, and consulting engineers. While many local
waste ordinances specify toxic concentration limits, the District and the
industrial community decided that this approach was inappropriate. Concen-
tration limits were not adopted because these criteria would not address the
value of water conservation and the limitation of the total quantity of
pollutants entering the treatment facilities. To respond to these considera-
tions, industrial waste discharge limits were specified by average daily
quantities.
Once the mass emission limits for specific pollutants and specific firms
were established, industry was encouraged to implement water conservation
measures. Because of the criteria adopted by the District, industry was not
penalized for the changes in pollutant concentrations that resulted from
conservation initiatives. Similarly, industry could not introduce large
quantities of water to the sewerage system in an attempt to reduce concentra-
tion limits.
3-83
-------
5000
4000
3000
2000
51
u
3 1000
o
u
a
<:
300
200
100
0
Discharge Lisic
i i
j i
Jan ?eb Mar Aor May June July Aug
Figure 35-7. 30D Seaoval ac Pracreatnenc Facility, Chaapaign. Illinois
3-34
-------
2500
2400
2300
2200
2100
2000
1900
1300
1700
1600
1500
1400
1300
1200
1100
1000
900
BOO
700
MO
300
400
300
200
100
0
Raw Wate
Effluent
Discharge Liait
Jan
reo
Mar
Aor
May
June
July
Aug
Figure B5-8. Suspended Solids ?-s=oval at Precreataese Facility, Champaign, Illinois
3-85
-------
2000
1500
u
I
u
o
1000
4
161
150
140
130
120
110
100
90
SO
70
60
50
40
30
20
10
0
Discharge Unit
Jan
Feb
Har
Apr
v
lay
June
July
Aug
Figure 35-9. Reaoval of Fats, Oils, and Greases at ?recreat=enc "acil
Champaign, Illinois
3-36'
-------
The results of the control program have included reduced wastewatar
discharge volumes and pollutant quantities. Industry reduced water discharge
to the sewerage system by 2.5 million and 3 million gallons per day during
1973 and 1979, respectively. In addition, a 46% reduction in influent metal
loadings (cadmium, chromium, copper, lead, nickel, and zinc) to the treatment
facilities was achieved over a 5-year period. Figure 35-10 provides the
specific quantity reductions in metal influents to the treatment facilities
over this 5-year period. Chromium and zinc have been reduced by the largest
percentage; each is 55% less than levels before the program was implemented
(Lewis, undated).
MOTIVATION FOR INDUSTRIAL PRETREATMENT PROGRAMS
A total of 14 municipalities in the case studies adopted industrial waste
pretreatment programs before the publication of the General Pretreatment
Regulations of 1978. Thus, their motivation for adopting programs is derived
from reasons other than Federal requirements. Three generic reasons for
adopting pretreatment programs are cited in the literature and reports:
o To improve sludge handling and disposal practices
o To improve water quality
o To protect POTW systems and operations.
Sludge Handling and Disposal
Two municipalities (14%) cited the improvement of sludge handling and
disposal practices as their motivation in adopting pretreatment programs. One
of these municipalities adopted the program because of the limited number of
disposal sites in the state for sludge containing high metal and toxic
pollutant concentrations. The other adopted a pretreatment program because
its ocean sludge disposal permit required industrial pretreataent. Sludge
concentrations of metals and toxics have now been reduced, and land applica-
tion is employed as the preferred disposal technique.
3-37
-------
Figure 35-10. Influent Pollutant Values,
Before and After Industrial Pretreatment Program,
Los Angeles County, California
Influent (Xg/d)
Pollutant Before (1975) After (1980) Percent Seduction
Phenols1 4626 3220 30
Arsenic2 34 6.3 80
Cadmium 50 36.3 27
Chromium 952 635 33
Copper3 680 408 40
Mercury 1.36 0.91 33
Nickel 408 295 28
Lead 454 227 50
Zinc 2494 1224 51
Cyanide 590 194 73
PCS 29 0.91 97
DDT & Metabolic 295 0.91 > 99
• Products
1. This pollutant, which is essentially discharged only by industrial
sources, was a candidate for source control liaits. However,
the 4,626 Kg/day discharge was not required to be reduced to
meet effluent discharge requirements, so no liaits were adopted.
Phenols are discharged aainly by petroleum refining and allied
companies. The observed decrease in phenol discharges is related
to decreases in gasoline production.
2. It is estimated that only about 1.6 Kg/day of che decrease is
attributable to the districts' source control program. Most
of the decrease has been due to changes in formulations of
household pest poisons and action by State of California CAL/OSKA.
3. While the districts instituted a source control limit for mercury,
all available information shows there are r.o significant industrial
dischargers of mercury to districts' sewer system. The observed
decrease shown is similar is percentage magnitude =o chat observed
at the districts' residential treatment plant. Therefore, factors
other than the"districts' source control program account for che
apparent thirty-three percent redaction.
3-33
-------
Water Quality
Six municipalities (43%) cited the need to improve water quality as their
motivation in adopting pretreatnent programs. Several of these municipalities
required industrial pretreatment in response to state plans for specific
receiving waters. Three of the municipalities adopted programs in response to
public reaction against fish kills, malodorous water in drainage canals, and
general water quality deterioration.
?OTV Protection
Six municipalities (43%) cited the need to protect the POTW operations
and equipment from periodic, highly concentrated slugs from industrial
sources.
3-89
-------
3-6. SUMMARY - WORKER HEALTH AND SAFETY, AIR AND GROUNDWATER
A review of Che potential impacts of industrial wastes in areas other
than surface water quality was conducted. The three areas of concern covered
in Section B-6 of this Appendix focus on Worker Health and Safety, Air, and
Groundwater. The following conclusions are drawn from the studies presented
in Section 3-6:
WORKER HEALTH AND SAFETY
o Documented instances in which industrial wastes entering POTWs have
caused health and safety hazards to wastewater treatment workers are
found in the literature. Potential health and safety problems include
exposure to toxic aerosols and fumes, and the danger of explosive
gases and materials.
o The problems described in the case studies reviewed in this section
were due to shock loads of toxic chemicals into the POTW, but evidence
the potential problems that can exist under normal operation.
o The types of pollutants that can cause health and safety problems are
present in POTW influent and are subject to pretreatment regulations.
The potential for problems could be reduced with industrial pretreat-
ment control.
AIR
o 1,067,432 tons of sludge are incinerated annually in the United
States. This number is expected to increase in the next decade as
landfill space becomes restricted.
o The possible sources of air pollution from incineration of sludge
include particulate emissions containing heavy metals and organics,
odorous compounds, gaseous and volatile organics, and biological
aerosols. Particulate emissions and heavy metals are of greatest
concern.
o Reduction in concentration of pollutants in sludge, which can be
accomplished through pretreatment, reduces the extent o£ air pollution
caused by incineration of municipal sludge. However, pretreatment can
result in the generation of additional industrial sludge which is
likely to contain toxic pollutants. Therefore, air pollution caused
by incineration of industrial sludge may increase.
B-90
-------
GROUND WATER
o Approximately 1.3 billion gallons/year of POTW influent exfiltrates
from the POTT'/, much of it is believed to reach grcundwater sources.
o A few case studies conclusively show ground water contamination frot?.
POTW exfiltration caused by broken pipes and migration/leakage from
holding ponds.
B-91
-------
B-6-1. WORKER HEALTH AND SAJETY
Approximately 53,000 sewer workers aay be exposed to toxic substances
from industrial effluents. Many of these substances can cause acute and
chronic health effects. Chemical substances that are discharged frcra indus-
trial sources to POTWs can become airborne in the collection and treatment
systems. Contaminants that are a concern in wastewater treatment facilities
include volatile organic chemicals, heavy metals, asphyxiants, and explosive
materials. Approximately 2,000 wastewater treatment systems are affected by
pretreataent regulations. In an annual survey of wastewater treatment workers
conducted by the Water Pollution Control Federation, the mean number of
employees at each of 1,299 wastewater treatment plants and collection systems
surveyed was 21 (WPCF, 1981).
POTW workers can be exposed to airborne chemical hazards in several
activities, including
o Sampling of wastewater
o Manning the control room of the treatment system (often Che puaps that
feed the waste treatment system are located in the basement of the
control house)
o Inspecting the system on regular rounds
o Inspecting the piping and lift stations in the sewage collection
system
•
o Perforating general maintenance activities.
Additionally, there may be secondary health hazards from the following
sources:
o Accumulation of sewer gases from blockages caused by industrial
discharges
o Skin contact with chemicals carried by foam
o Handling of strong acids and bases used as pH control reagents for
waste streams with variable pH.
B-92
-------
Volatile organic compounds may be discharged to the public sewer from
numerous commercial and industrial establishments. Although such compounds
may be in solution in the discharged water, the compounds may volatilize in
the sewer or in the treatment unit because the unit generally operates at a
slightly elevated temperature. The concentrations of these compounds in
industrial effluents can be lowered by pretreatment. If pretreatment regula-
tions are instituted, the concentrations of these substances in the water and
subsequently in the air should be reduced.
In a recent study of 40 POTW facilities, volatile organic compounds were
measured in the influent. Table 36-1-1 shows the average concentrations and
detection frequencies of 11 compounds that are conmonly found in POTW influent.
Table B6-1-II lists the airborne concentrations of several of these volatile
organic compounds measured either at the treatment plant or in the collection
system. These concentrations were reported in the case studies described in
the following sections. Table B6-1-II also shows the applicable exposure
criteria, toxicologic characteristics, phsyical properties, and industrial
sources of volatile organics commonly found in the influent of POTWs. The
health effects described in the case studies can be expected to occur if
workers are exposed to concentrations of chemicals greater than the threshold
limit value (TLV). As shown in Table B6-1-II, the values actually measured
did not exceed the TLV. However, it is important to note that greater
concentrations of volatile organics than those measured must have been present
to have caused the health effects observed and reported in the case studies.
Heavy metals such as lead, mercury, cadmium, chromium, and nickel from
industrial sources, including electroplating and battery manufacture, are also
contained in the wastewater that reaches the POTW. In the aeration basin of a
typical sewage treatment plant, the heavy metals may be adsorbed onto parti-
culate matter and emitted to the air as aerosols. These metal-containing
aerosols can be inhaled by workers during POTW operations. However, the metal
concentrations that have been measured near aeration basins of POTWs are much
lower than the established TLVs or permissible exposure limits (PELs).
Therefore, based on limited data, concentrations of heavy metals in the POTW
B-93
-------
TABLE B6-1-I
VOLATILES WITH HIGHEST INFLUENT CONCENTRATIONS
Organic Compound Average Percent of Tinie
(in g/1) Detected
Benzene 21 59.3
Chloroform 17 90.3
1,2-Dichloroethane 585 14.4
Methylchloride 21 13.1
Methylene Chloride 516 94.1
Perchloroethylene 127 94.9
Toluene 218 97.9
1,1,1-Trichloroethane 223 87.3
Trichloroethylene 77 92.4
Vinyl Chloride 46 7.2
Source: U.S. EPA 1980
B-94
-------
TABLE B6-I-1I
Volatile Organic (Concentrations
Compound (in p|Kn))
Acutually . -
KeuH.ireJ TLV PEL
benzene — 10 1
chloroforu — 10 SO
l-2,dicliloroethane — 10 5
tn
1 «
^ ethyl beniene -- 100 100
methyl chloride — 100 100
inuthlcne chloride 50 500
pt:i chloroethylene 5 100 100
toluene 37 100 200
1.1,1-trichloro- 180 350 150
e i!i une
trichloroethylene 20 50 100
Local Acute
Skin Irritant
Eye and reupira-
tory irritant
Eyci, noae,
throat, and akin
irritant
—
--
Hild eye, none,
and throat
irritant
Eye, respiratory.
and akin irritant
Eye and denial
irritant
Eye, noae, and
throat irritant
Health Effect.
Systemic Acute Chronic
CHS d«pre»*ant carcinogen of
blood-forming
t iaaue
Liver damage liaa cauaed can-
CN3 effecta cer in humana
when adminis-
tered at high
doaea
Narcotic effecta
_- —
CHS depreiaant CHS effecta
Narcotic —
CNS depreaaant;
nay cause hepa-
tic injury
CHS depreaaant —
Narcotic
CNS depreaaant
Phyaical Propertied
VP BP Induatria) llaa
75 BUB 176*1' Solvent, const iluent of
uotor fuula
160 mm 142"F Solvent in pharmaceutical
manufacture
62 uux 183*F Solvent, antiknock
compound
7.1 ma 277*F Solvent, antiknock
compound
A. 8 atm -12*K Extractant, anlvent
tiaed in organic chemical
manufacture
350 mm I04*K Solvent
IA ma 250*F Solvent, dry cleaning
22 lira 231 'K Feed for chemical
production, aolventa
fuel count fluent
100 mm 165*F Induutrial solvent
58 nun 18U*F Degruuaing uolvent
-------
TABLE B6-I-1I (Continued)
Valat lie Organic
Con pound
vinyl chloride
(Concentration!
(in ppa)
Acutually . ,
Meaaured* TI.V PEL Local Acute
56 1 Skin irritant
Health Effect*
Syateuic Acute Chronic
CMS depre*»ant itrong correla-
tion with CMS,
respiratory,
hepat ic , and
lyapliatic can-
cer in human*
Phyaicat Properties
VP* HP Industrial U«e
2,600 BUI 6.9U*K U«ed in the manufacture
of polyviny Iclilor iile,
uolvunt, and clieuical
•anufacturing
iiiterucdiate
'source: NIOSII, Interin Report. I & 2, Health Hazard* Report*, 1981, Unpubliiilied
Tlirenliold Limit Value* (TI.V) "refer to airborn concentration* of *ub«tance* and represent condition* under which it i* believed that nearly all
worker* may be repeatedly expoied day after day without adverae effect. Theae value* are 8-hour tine-weighted expu*ure leveln."
3Pertnia»ible Expoaure l.init* (PEL*) are the OSIIA atandard for theie compound* the value* are 8-hour tioie-ueifthted average*.
4«t 20 C mm llg
100-800 ppb concentration* were meaourcd above the aeration baain of a WWTI'. Source: Per*onal conver*at ion, Haul Wagner - KI'A/HLHI.
6Propoued TI.V
7at 23 C i»n llg
-------
workplace air do not appear to be a major occupational health hazard. The
toxicologic properties and exposure criteria for heavy metals commonly found
in POTW influent are shown in Table B6-1-III.
Explosive gases are of concern because they may collect in pockets in the
waste collection system and be ignited by static electricity, sparks from
electrical utilities, and high temperature. As a recent example, the cata-
lytic converter of an automobile ignited explosive gases in a manhole causing
significant damage to the sewer system in Louisville, Kentucky.
The types of problems discussed above have been documented in the follow-
ing four case studies. In each case, workers exposed to industrial chemicals
suffered a variety of acute symptoms. The long-term chronic effects of these
exposures are not known. As knowledge of chronic effects such as carcino-
genesis, reproductive abnormalities, and chronic organ damage increases, a
more comprehensive picture of the risks faced by POTW workers may develop.
CASE STUDY I
Elia, et al. (1980), conducted an epidemiology study of diseases among
wastewater treatment plant workers at the North Wastewater Treatment Plant in
Memphis, Tennessee. The investigators measured concentrations of chemical
substances in the workplace air. The plant, which uses secondary treatment,
receives the effluent from a plant that uses and produces several chlorinated
intermediates in manufacturing flame retardants and pesticides.
While investigating disease caused by microorganisms, the researchers
noted an irritating odor characteristic of chemical waste. Employees at the
wastewater treatment plant who were exposed to these odors complained of a
variety of acute symptoms, including the following:
o respiratory distress
o dizziness
o headache
o irritation of the eyes and upper respiratory tract
o skin irritation.
3-97 -
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TABLE 116-1-1II
Concentrations (in
Metals Actually
Measured TLV
Cadmium 1 .57 x 10- 0.05
Chromium 3 x 10~ 0.5
w
rag/m )
PEL
dust: 0.2
fume: 0.1
O.I
Health
Local Acute
Respiratory
irritant
Tracheo-
bronchial
irritant
Effects
Systemic Acute
Respiratory
injury, lung
damage
__
Chronic
Suspected
care inogen,
kidney damage
Carcinogen of
lungs and nasal
cavity (llexa-
valent chromium
form only)
In dust r i n 1
Use
Protect ive
coating applied
by electroplating
Protective
coating applied
by electroplating
00 Copper 2.1 x 10
Lead
Si Iver
-A
O.I fume: 0.1
dust: 1.0
Skin irritant Respiratory
irritant
6.1 x 10 H 0.15 0.05
Nickel 1 x 10
-5
1.0 1.0
Skin sensitizer —
Kidney damage,
CMS damage
Carcinogen of
nasal cavity,
lungs, paranasal
s inns
0.01 0.01
Grayish pig-
mentat ion of
skin and
membranes
Electrical
industry, pesti-
c ides
Battery manufac-
ture ant iknock
compound
Electroplat ing,
metal working
Photograph ic
films, jewulry,
catalynts
NOTK: These measurements wen: taken at an activated sludge plant.
-------
Subsequently, air, water, and urine samples were taken for the following
substances.
o hexachlorocyclopentadiene (HEX)
o hexachloronorbornadiene (HEX-BCH)
o heptachlorobicycloheptene (HEX-VCL)
o chlorodene.
A urine sampling program for these chemicals was performed at the Maxscn Sewage
Treatment Plant in Memphis to act as a control for the study. The Maxson plant
does not receive the effluent from the pesticide plant.
As shown in Table B6-1-IV, the results of the study indicate that the above
chemical substances were present in the influent to the North Treatment Plant.
This contamination was also detected in appreciable quantities in the air in the
wet well of the facility, indicating that the chemicals had volatilized from the
water into the air.
In response to a questionnaire distributed by the NIOSH study team to
determine the effects of exposures, the affected employees reported the
following symptoms:
o Eye irritation—110 of 200 employees complained of this symptom, and
44 reported that the symptom lasted more than 1 week.
o Headache—97 employees complained of this symptom, and 50 reported
that the headache lasted more than 1 week.
o Chest discomfort—60 employees reported this effect, and 41 stated
that the symptom lasted more than 1 week.
o Fatigue—60 employees suffered from fatigue and the majority (46)
reported that the fatigue lasted more than 1 week.
o Sore throat—53 reported this symptom, and 20 stated that the symptom
lasted more than 1 week.
Other symptoms reported during the employee survey were coughing, nausea,
vomiting, and skin irritation. Several employees noted that these symptoms
continued for more than 6 weeks after exposure. The reported symptoms were
3-99
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TABLE 36-1-IV
A STUDY OF THE NORTH WASTEWATES. TREATMENT PLANT IN MEMPHIS
Air
Concentration Urine Influent
Conpound TLV at Wet Well Concentration Concentration
Hexachlorocyclo- 100 g/M3 0.03-39 (ttg/M3 0.8-2.5^/1 0.8-3ug/l
pentadiene
Hexachloronor- NA 2.4-2 73^ g/M3 0.3-15.2 ug/i 11-334
bornadiene
Hepcachlorobi- NA 1-200 ug/M NA 17-68 ag/1
cycloheptene
Chlorodene NA 0.5-65»g/M3 NA 32-216 ag/1
NA - not available
Source: Elia et al. (1980)
_I nn
-------
consistent with the known acute toxicology of hexachlorocyclopentadiene.
Little is known about the chronic toxicology of this compound; however, the
chronic effects could be significant if they include tumorogenesis and repro-
ductive abnormalities similar to the effects of other chlorinated
hydrocarbons.
Air samples were taken only during the cleanup operations that followed
the contamination of the treatment system. Samples were taken from the area
and personal samples were taken from the 97 individuals that were involved.
The air sampling results are listed in Table B6-1-IV. Concentrations of
hexachlorocyclopentadiene in the personal samples exceeded the TLV of 10 ?pb
that has been established for the compound. No TLV has been established for
octachlorocyclopentene. It is clear in this case that employees of the waste-
water treatment plant were adversely affected by discharge of the industrial
waste and that the cleanup crew would have also been significantly affected if
the problem had not been fully recognized prior to the cleanup effort
(Koniinsky 1930).
Although there was no attempt to determine S-hour worker exposure levels
to these chemicals, urine sampling confirmed that the worker had been exposed.
Of the urine samples of 31 employees, 25% had measurable quantities of hexa-
chlorocyclopentadiene (HEX) and 90% contained HEX-5CH.
A TLV has been established for only one of the compounds, HEX. The TLV
for this compound is 100 in/M , which represents the concentration to which
workers can be exposed for an 8-hour day without adverse health effects. The
author of the study points out that "Hypothetically, if it is assumed that the
TLV for HEX-3CH would be equal to the TLV for HEX (110 g/M of 10 ppb), air
concentrations in the wet well during May and June 1978 would be about two
tines this TLV level." The authors also noted that the large number of com-
pounds that may be present in a waste treatment unit may result in additive
health effects that are not adequately represented by a single TLV for one of
the compounds of concern (Elia et al., 1980).
3-101
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TABLE 36-1-V
AIR MEASUREMENT DURING CLEANUP OPERATIONS
Concencration
Chemical
Hexachloro-
cyclopencadiene
Occachloro-
cyclopentene
Type of Sample
Personal
Work area
Personal
Work area
No. of Samples
19
41
19
41
Mean
1,518
1,446
142
185
Median
960
1,286
91
189
- DD'D
Range
21-3,833
131-4,286
3-472
17-416
Adapted froa J.R. Kominsky et. al. (1980)
3-102
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CASE STUDY II
The National Institute for Occupational Safety and Health (NIOSH)
conducted a study of chemical contamination at the Morris Foreman Wastewater
Treatment Plant in Louisville, Kentucky, in 1977 (Kominsky, et al., I960).
There were two incidents at the treatment unit in which a blue haze was
generated at the grit chamber. The first incident occurred while workers were
attempting to remove a viscous, foul-smelling substance from a screen using a
steam jet. Twenty workers sought medical attention for respiratory irritation
following this incident. The blue haze was observed a second time over the
grit chamber and the primary treatment areas following a heavy rain.
Two chlorinated hydrocarbon constituents, hexachlorocyclopentadiene and
octachlorocyclopentene, which are commonly associated with pesticide manu-
facturing were identified in samples of the blue haze. Contamination of the
treatment system resulted from an unauthorized discharge of a chemical waste
stream into the domestic sewer system.
CASE STUDY III
In February 1981 a large section of an underground sewer in Cincinnati,
Ohio, collapsed. The collapse occurred following concrete pipe deterioration
that was caused by a highly acidic waste stream from a pigment manufacturer.
During tha repair operation a number of workers were overcome by nausea,
vomiting, dizziness, headache, and eye and nose irritation. The workers also
complained of solvent-like odors in the sewer. A study team from NIOSH took
air samples to determine whether exposure to chemicals, could be causing these
symptoms. Samples were taken at the collapsed sewer repair site; at sewer
hubs, life stations, and manholes; and in the sewer both upstream and down-
stream from the discharge point of the pigment plant. Initial monitoring
showed that the concentration of Stoddard solvent below the discharge point
was 780 ppm, while above the outfall the concentration was only 20 ppra. Air
concentrations of several other common organic solvents were also measured.
It is clear from the data gathered by NIOSH that the concentrations of
several of the organic solvents including naphtha, trichlorcbenzene ana
Stoddard solvent were above the TLV and therefore could be hazardous to
3-103
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workers who nay be required to eater manholes and lift stations for routine
maintenance (Center for Disease Control, 1980).
CASE STUDY IV
Two sewer workers in Newark, New Jersey, were overcome by a gas consisting
of various toxic chetnicals, including tetrachloroeth?.ne, ethylbenzene, trichlo-
roethylene, tetrachloroethylene, and methylisobutylketone. Exposure to the
chemicals in the manhole is believed to have caused the death of one man and a
severe health condition in another worker. It was suggested chat the toxic
chemicals ware contributed from an industrial source (Bergen Record, 1981).
IMPACT OF PRETREATMENT
The limited data available provide evidence of exposure of POTW workers
Co industrial chemicals. Appreciable concentrations of chemicals from indus-
trial sources have been identified in both influent water and in ambient work-
place air at POTW facilities. Exposures to volatile organic compounds have
caused adverse health effects among POTW workers. Pretreatisent programs
should reduce influent concentrations of toxic chemicals, and thus should
reduce the exposure and the risk of subsequent health problems for POTW
workers.
B-104
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3-6-2. AIR POLLUTION IMPACTS RELATED TO POTWS
AIR POLLUTION CHARACTERIZATION
There are four types of air pollutant emissions that can be expected from
the operation of POTWs. These are odorous compounds, gaseous and volatile
organics, biological aerosols, and particulars. The nature and magnitude of
the emission problems are a function of the processes involved and the manner
in which these processes are operated. No single process is likely to
encompass all the problems, although more than one problem can occur in any
specific process. 3y far, particulate emissions, including heavy metals, are
the most serious concern. In fact, particulate emissions from incinerators
are subject to the Mew Source Performance Standards established by I?A (EPA,
1974). On the other hand, odor problems are not necessarily serious health
concerns, but they often create very difficult techcnical and public relation
problems. The following is a discussion of the problems associated with the
four types of air pollution.
Emission of Odorous Compounds
Odorous compounds are produced in sewers and in treatment plants from
organic compounds formed by hydrolysis of materials such as cystine and
nethionine, and by reduction of sulfates. In descending order of magnitude,
methyl inercaptans, methyl sulfides, amines, indoles, skatoles, and hydrogen
sulfides have been identified as the main causes of odor (Post, 1956). The
processes that may evolve these compounds can be grouped ino several different
categories: gases from aerobic biological processes, gases originating from
certain types of algae, flow-off gases from high temperature pressure cooking
processes, gases from the incomplete or improper oxidation or combustion of
sludges in incinerators, gases that evaporate from exposed screenings, and
gases resulting from poor housekeeping or poor plant operations (Sutton,
1971).
A treatment plant will always generate some odorous compounds, but a
properly designed, operated, and maintained facility should not generate
enough of these compounds to cause complaints from immediate neighbors.
Occasional malfunctions in the treatment process, overloading (from industrial
3-105
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or domestic sources) of the treatment capacity, sudden excessive discharge of
industrial wastes, and land spreading sludge are examples of concidtions
likely to result in odor complaints.
Emission of Other Gaseous and Volatile Compounds
Sewage treatment plants also generate other gases and hydrocarbons that
nay be health and environmental concerns. Other than methane gas, most
organic compounds ara emitted from treatment and handling in the liquid phase.
The specific species of hydrocarbons and the rate of emission will depend on
the type of plant process, the condition and composition of the influent, and
the size of the plant. Glaser and Ledbetcer in (1969) found organic vapor
concentrations of 35,2 mg/m at the bar screen area, 20 ng/m at the aeration
tank, and 6.7 mg/m at the clarifier in one activated sludge treatment plant.
Various EPA priority compounds have been identified in the influents of
sewage treatment plants (EPA, 1980). Those that are volatile at ambient
temperatures may evaporate in the collection or treatment systems. The 10
volatiles with the highest influent concentrations ranged from an average of
17 to 585 g/liter. Assuming that total volatile organics in the influent at
a concentration of 1,000 g/liter are all evaporated, which is unlikely, a
1-MGD treatment plant will release 3.34 Ib. of organics per day into the air.
This loading of hydrocarbons is very low when compared to the amounts of
photochemically reactive hydrocarbons permitted by air pollution control
agencies. However, hydrocarbons are typically regulated by these agencies to
prevent photochemical oxidation rather than to prevent toxic effects.
Many gaseous pollutants are emitted from sludge incineration operations.
Hydrogen chloride, sulfur dioxide, oxides of nitrogen, and carbon monoxide
have been identified in the stack gas of sludge incinerators. A study (SPA,
1975) of two fluidized beds and three multiple hearth sludge incinerators with
a capacity of 500 Ib./hr. to 2,500 Ib./hr. found the following concentration
for these gases:
Hydrogen chloride 1-10 ppm
Sulfur dioxide 0-14 ppm
3-106
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Oxides of nitrogen 5-165 ppm
Carbon monoxide 0
The concentrations of these gases at ground level will be substantially
lower than these values as a result of atmospheric dispersion. It is
improbable that sludge incinerator emissions would cause violations of
National Ambient Air Quality Standards for sulfur dioxide, oxides of nitrogen,
or carbon monoxide. Although a national ambient standard for hydrogen
chloride has not been set, OSHA has established an occupational exposure limit
of 5 ppm. Taking into account atmospheric dispersion, ground level concentra-
tion of hydrogen chloride would be several tines lower than the OSHA limit and
should not cause a significant ambient impact. The sulfur dioxide concentra-
tion is well below the emission limit specified in most air pollution codas
(300 ppa). As for oxides of nitrogen, the concentration is such less than
that contributed by other sources. For example, Jacknow (1978) postulated
that per capita enission of oxides of nitrogen from sludge incineration are
equivalent to those resulting from driving an automobile for less than a tenth
of a mile.
Because of the high temperature (1450°F average) required for incinera-
tion, almost all organic compounds entering the incinerator are destroyed.
Localized volatization in the entrance zone of a inultiple hearth incinerator
could cause a small percentage of the incoming organics to be released
unchanged (Jacknow, 1978). However, unless the incoming sludge has a high
concentration of toxic compounds, the emission of toxic organic compounds from
sludge incinerators should not result in significant environmental impacts.
Emission of Biological Aerosols
Biological aerosols can vary in size from virus units of less than 0.1
to fungal spores of 100 or larger. They may occur as single, unattached
organisms or aggregates of organisms. They may adhere to a dust particle or
be surrounded by a film of dried organic or inorganic material. Not all
biological aerosols are harmful to humans, but airborne pathogenic micro-
organisms have been isolated in the vicinity of sewage treatment facilities.
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Randall and Ledbetter (1966) found that 6% of all bacteria emitted from
an activated sludge unit were of the Klebsiella species, a potential respir-
atory tract pathogen. Furthermore, approximately 40% of the viable airborne
bacteria in the vicinity of the treatment unit were in the respirable size
range (Sjjor less). In another study (Napolitano and Rowe, 1966), the
aeration tank of the activated sludge process facility and the trickling
filter bed of the trickling filter process were identified as the main sources
of bacteria emission.
Obviously, the spread of biological aerosols from the sewage treatment
plant will be affected by wind direction and wind speed. Although biological
aerosols may travel a long distance, they may not remain viable for a long
time in air. For this reason, health hazards arising from pathogens in the
treatment plant are only of likely concern to the plant operators. Even so,
an investigation of incidence of infections among sewage plant workers (Dixon
and McCabe, 1964) did not result in conclusive evidence of worker health
effects.
Emission of Particulates
Particulate emission is a problem associated only with incineration of
sludge. The New Source Performance Standard (EPA, 1974) sets a particulate
emission limit of 0.08 grain/sdcf, or on the basis of dry sludge feed rate,
1,3 Ib/ton. It also limits the plume capacity to 20%. These limits can be
met with the use of high efficiency particulate emission control devices such
as the high energy venturi scrubber.
Wastewater sludges contain metals that could be hazardous if discharged
into the atmosphere. The forms in which the metals are found in the sludge
and the operating parameters of the incinerator will affect the type of metal
emission. Higher temperatures will increase the volatization of metals such
as lead, mercury, and cadmium. However, it is believed that most of the
metals, with the exception of mercury, are converted into oxides and appear in
the particulates removed by scrubbers or other control devices, and in the ash
(Dixon and McCabe, 1964).
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In a study supporting the EPA mercury emission standard (IPA, 1974),
63-96% of the mercury was found to be removed by the scrubbers. Another study
(Versar, 1974) showed that only 9.7% of the mercury entering a multiple-hearch
furnace escaped through the scrubber and into the air. However, other studies
(Dewling et al, 1980; Olexsey, 1974) have indicated that all of the mercury
contained in the incoming sludge msy be released into the air. These dis-
crepancies may be attributed to the different methods used in various studies,
(e.g., theoretical calculation, partial mass balance, and total mass balance).
Regardless of these different findings, none of the studies have indicated any
instances of the EPA mercury emission standard of 3200g per day being exceeded.
In fact, tests in five incinerators (Dixon and McCabe, 1964) showed an average
emission factor of 1.65g/raetric ton, which would mean the operation of a 1939
metric tons/day incinerator to reach the EPA emission standard. In addition,
the total mass of mercury released from a sludge incinerator is much less than
that from other large point sources such as power plants or municipal inciner-
ators. A plume dispersion modeling study (Greenberg, 1981), based on a 50g/
day emission, predicted maximum ground concentrations of mercury of 27 and 29
ng/m under the two most unfavorable conditions, compared to typical ambient
mercury concentrations of 1-10 ng/m .
Aside from mercury, atmospheric emissions of other metals such as
cadmium, chromium, copper, nickel, lead, and zinc from fluidized bed sludge
incinerators are relatively insignificant when compared to other sources of
these pollutants (Dewling et al, 1980; Greenberg et al, 1981). Most of the
metals end up in the ash, with less than 1% of the metal content in the
incoming sludge released into thet air. Except for lead at 2g/day and zinc at
1.5g/day, emission rates measured for other heavy metals are less than Ig/day
(Greenberg et al, 1981).
It appeals that heavy metal emissions from the incineration of "typical"
sewage sludge present minimal environmental hazards to the public. Mercury
emissions have the greatest potential for exposing local residents, but
aercury releases from sludge incinerators are small when compared to other
large sources. Because of a lack of available data, conclusions can not be
made about impacts resulting from the incineration of municipal sludges highly
concentrated with metals.
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IMPACT OF PRETREATMENT
POTW operations, especially treatment plants, wastewater collection
systems, and sludge disposal methods generate air pollutants which contribute
to the total atmospheric loading. However, the magnitude of these emissions
is small when compared to other air pollution sources. A well designed and
operated POTW whose facilities (e.g., incinerators) incorporate efficient air
pollution control equipment can substantially reduce air pollutant emissions,
and associated problems can be virtually eliminated.
Particulate emissions from the incineration of sludge, which include
toxic heavy metals, have the potential for causing the most significant POTW-
related air pollution problems. Of the heavy metals, mercury may be released
from sludge incinerations in concentrations that could gave significant
impacts. Other metals may also result in air pollution problems when the
incinerated sludge is highly concentrated with heavy metals. However, studies
have shown that incinerators, equipped with well-designed scrubbers, remove
significant amounts of air pollutants.
Although POTWs are not themselves likely to create serious air pollution
problems, POTW air emissions in conjunction with other sources may contribute
to a total atmospheric loading which could result in violations of national or
state ambient air quality standards. Pretreatment of industrial water which
reduces the amount of heavy metals and organic materials introduced into
POTW systems would indirectly result in lower atmospheric emissions from the
POTW. In the case of odor problems where the odor results from industrial
related emissions, pretreatment has the potential to completely eliminate this
air pollution problem.
However, pretreatment will often result in the generation of new or addi-
tional amounts of industrial sludges. These sludges are likely to be highly
contaminated with toxic pollutants and will frequently be disposed of by
industrial sludge incineration. Data does not exist to quantify POTW vs.
industrial pretreatiaent related air pollution, and such a study is beyond the
scope of this report. However, it is likely that the net result would not
change air pollution problems on a national scope. Considering the current
3-110
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state-of-the-art for pretreatment technology, it is very possible that
prereatment may reduce air pollution problems for one localized area and
contribute to probleas in another.
3-111
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B-6-3 EFFECTS OF INDUSTRIAL DISCHARGE ON GROUNDWATER
INTRODUCTION
Groundwater contamination is rapidly becoming an issue of national con-
cern. Nearly half of the U.S. population relies directly on groundwater as a
source of drinking water. Many government agencies have attempted to assess
changes in the quality of the Nation's groundwater, but the magnitude of
groundwater contamination is still unknown. Qualitative assessments are often
the only means available for evaluating existing groundwater quality.
This section deals with only one component of the problem: can pretreat-
nent of industrial waste appreciably minimize the degradation of groundwater
quality? Like other components of the groundwater contamination problem, very
little is known about the extent of the impact of untreated industrial waste
on groundwater. Documented studies and case histories of these impacts
provide information only on the nature of the problem, not the extent. The
only means of making even a qualitative estimate of the extent of the problem
is to assess current trends in the quantity and distribution of wastewater
discharges.
The importance of industrial waste pretreatment in preserving the quality
of groundwater resources depends on two key factors:
o The quantity of wastewater discharged by industry that can be upgraded
through pretreatraent activities.
o The extent to which industrial discharges can enter groundwater
systems.
Trends in Industrial Discharge Practices
The point of discharge is important in evaluating industrial discharges.
Table B6-3-I shows the distribution of industrial wastewater discharges for
indirect discharges, from raw discharge to discharge today through anticipated
discharges at full 403 (PSES). This table shows the distribution by cate-
gorical industry of the total metals and total organics in pounds discharged.
B-112
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TABLE B6-3-I
VOLUMES OF WATER USE AND DISPOSAL FOR MAJOR INDUSTRIAL GROUPS
(Billions of Gallons in 1972)
I
M
U>
Industrial Croup
Pr imary Metals
Chemicals and Allied Products
Paper and Allied Products
Petroleum and Coal Products
Food and Kindred Products
Transportation Equipment
Stone, Clay, and Glass Products
Textile Mill Products
Non-electrical Machinery
Lumber and Wood Products
Rubber and Plastic Products
Fabricated Metal Products
Electrical Equipment and Supplies
Instruments and Related Products
Leather and Leather Products
Furniture and Fixtures
Tobacco
Miscellaneous Manufacturing Industries
TOTALS
Total
Intake
4,941
4,176
2,415
1,282
803
242
219
177
171
159
153
107
104
37
8
6
5
12
15,017
Percent
of Total
Intake
33
28
16
9
5
2
1
1
I
1
1
1
1
<1
<1
<1
<1
-------
Table 36-3-2 shows the major pollutants which comprise the discharge for some
of the industries.
The pretreatment program has focused on the reduction in toxics released
to the environment. However, in analyzing a need for a national program for
control of toxics, or asssessment must be made of contamination to the
environment from "unconventional" sources, such as leakage from sewer pi per.
This leakage of wastewater from sewers is a source of groundwater contami-
nation that has received fairly little attention. However, the 1977 Report to
Congress on Waste Disposal Practices and Their Effects on Groundwater esti-
mated that "sewer leakage on the average is probably around 5% of the total
[flow]." In terms of the POTWs which are subject to pretreatment; 750 million
gallons per year are released by leakage. The report attributes leakage to
several factors:
o Poor workmanship, especially in the past when mortar was applied by
hand as a joining material.
o Cracked or defective pipe sections.
o Breakage by tree roots penetrating or heaving the sewer lines.
o Pipeline rupture by superimposed loads, heavy equipment, or earthfill
on pipe laid on a poor foundation.
o Rupture of downhill creep of soil in hilly terrain.
o Fracture and displacement of pipe by seismic activity, e.g., a
sewerage system in California still suffers for fractures caused by an
earthquake in 1909.
o Loss of foundation support due to underground washout.
o Poorly constructed manholes, or shearing of pipe at manholes due to
differential settlement.
While cases of groundwater contamination from leaky sewers are rare, they
do exist. For instance, groundwater degradation discovered in July of 1966 in
Marshall County, Illinois, was traced to a leaky sewer line from an industrial
plant, Walker W.H. (1969). The rareness of this type of case history is
probably due to the scarcity of groundwater wells in areas served by public
water supplies.
B-114
-------
TABLE B6-3-II
INDUSTRIAL WASTEWATER PARAMETERS HAVING
SIGNIFICANT GROUNDWATER CONTAMINATION POTENTIAL
PAPER AND ALLIED PRODUCTS
Pulp and Paper jLndustry
COD Phenols Nutrients (nitrogen
TOC Sulfite and phosphorus)
pH Color Total Dissolved Solids
Ammonia Heavy metals
PETROLEUM AND COAL PRODUCTS
Petroleum Refining Industry
Ammonia Chloride Nitrogen
Chromium Color Odor
COD Copper Total Phosphorus
pH Cyanide Sulfate
Phenols Iron TOC
Sulfide Lead Turbidity
Total Dissolved Solids Mercaptans Zinc
PRIMARY METALS
pH Cyanide Tin
Chloride Phenols Chromium
Sulfate Iron Zinc
Ammonia Cadmium
CHEMICALS AND ALLIED PRODUCTS
Organic Chemicals Industry
COD TOC Phenols
pH Total Phosphorus Cyanide
Total Dissolved Solids Heavy metals Total Nitrogen
B-115
-------
TABLE B6-3-II (Continued)
INDUSTRIAL WASTEWATER PARAMETERS HAVING
SIGNIFICANT GROUNDWATER CONTAMINATION POTENTIAL
CHEMICALS AND ALLIED PRODUCTS (Continued)
Inorganic Chemicals, Alkalies and Chlorine Industry
Acidity/Alkalinity
Total Dissolved Solids
Chloride
Sulfate
COD
TOC
Chlorinated Benzenoids and Chromium
Polynuclear Aroinatics Lead
Phenols Titanium
Fluoride Iron
Total Phosphorus Aluminum
Cyanide Boron
Mercury Arsenic
Plastic Materials and Synthetics Industrv
COD
pH
Phenols
Total Dissolved Solids
Sulfate
Ammonia
Chloride
Chromium
Total Dissolved Solids
Nitrate
Calcium
Dissolved Solids
Fluoride
pH
Phosphorus
Phosphorus
Nitrate
Organic Nitrogen
Chlorinated Benzenoids
Polynuclear Aromatics
Nitrogen Fertilizer Industry
Sulfate
Organic Nitrogen
Compounds
Zinc
Calcium
Phosphate Fertilizer Industry
Acidity
Aluminum
Arsenic
Iron
Ammonia
Cyanide
Zinc
Mercaptans
COD
Iron, Total
pH
Phosphate
Sodium
Mercury
Nitrogen
Sulfate
Uranium
Source: EGD, 1981.
3-116
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THE ROLE OF PRETREATMENT IN GROUNDWATER CONTAMINATION
In addition to the hydrologic, climatic, and environmental conditions
that exacerbate groundwater quality problems, it is important to consider
background water quality and the distribution of industrial facilities across
the Nation. Industries tend to concentrate in favorable localities, making,
by their numbers, the groundwater basins in those areas much more susceptible
to pollution than others with few industries. Pretreating wastewaters in
these areas could have favorable impact in minimizing the potential for
groundwater contamination.
Once an aquifer becomes polluted, recovery from that pollution usually is
slow because of the generally slow rate of groundwater movement through the
aquifer. Hence, groundwater pollution, may be considered a semipermanent
condition, perhaps lasting for decades after the source of the pollution has
been determined and the pollution has been stopped. Thus, the strategy for
minimizing the impacts of industrial discharges 'on groundwater should stress
prevention rather than correction. Pretreatraent would be a step toward
implementing such a strategy.
Potential and existing groundwater pollution is of significant concern,
not only from the standpoint of public health but also from an economic stand-
point. The cost of treating water to attain an acceptable level of quality
continues to increase, both because of the larger quantities of material
needed to treat the water and the increasing cost of the material. It will
always be less difficult and less expensive to renovate wastewater before it
is discharged rather than after it has entered the groundwater system.
3-11"
-------
3-7. SUMMARY OF POTW PROBLEMS
INTRODUCTION
A number of problems exist within POTWs throughout the United States. As
part of the RIA of EPA's pretraatment program, the types of POTW problens and
potential causes were analyzed and evaluated. Several data bases were used in
order to evaluate the scope and significance of the problems and to identify
those that are common to POTWs and that can be addressed by local
pretreatment. The data bases that were analyzed are presented in Appendix 3
to this RIA report and include:
Section
Data Base
B-l O&M Data Base
B-2 132 POTW Local IU Control Assessment
B-3 77 POTW Visits
B-4 40 POTW Study
B-5 Pretreatment Case Studies
3-6 Worker Health and Safety, Air, and Groundwatar
In each data base, potential impacts and effects on the following problems
were analyzed, as appropriate:
o passthroughs
o bypasses
o process upsets
o sludge contamination
o NPDES permit violation
o problem distribution
o environmental/health concerns
This appendix and the associated sections were not developed solely to
conclude a strong need for pretreatment and/or a Federal involvement, but were
developed in order to quantify and depict the level of industry-related
problems at POTWs and to present needs to be addressed.
POTW PROBLEMS
An analysis of these data bases indicates and verifies that there are
conanon problems found in POTWs. These problems are national in scope anci
3-U8
-------
cover the full range of plant sizes and industrial mixes. The following
matrix presents generic problems common to POTWs based on the data bases
analyzsd. Each generic problem is summarized in Table B7-I below.
leu
Und Trocess Ipsets
lass than 5 MO
• laeiive I'-' flswa and resort probieaa
• hserting hydraulic overloada
• assorting organic overloads
Unit Problems
• iisociated wits 19 and reporting
QIR problem
• Halation and less than 5 MG9
• laca baae MTV« controlling;:
i conventional pollutants
1 setlls
I toxics
- Tlolations
• lined prior to 1977
Belte Problems
• Slaag' contaainarion
• bforted to be unsatisfactory
•lacking sludge quality data
hmhrou^h . Bypa a s ,
atCSO Prob'ieai
• assort i"ag ta receive ID flows
aid 9y-p*jses aootSly
• ana of concern
• Spotting p*sa-chroufb
lad/or interference
• ttO system shows aetala
iactuse in we condition
total
• IDCTs in soae pnaae of precreatment
tragrxm developaent
•132/77/40 3ata bale POTVa srovidisg
sacondary treatment
04M Data Ease
79Z
721
771
421
801
70Z
100Z (of ?OTWe
eveluated for
sludge)
35Z
Regions II and '
report highest
instances
97«Z
TABLS B7-I
DATA USES
132 Study
—
•OW5MKXPOTV
82S-85Z
13Z-2SZ
16Z-29Z
78Z-42Z
241-401
43Z-49Z*
43Z-69I
36Z-78Z
73Z-49Z
77 P07VS 40 POTWS Case Studies
Five ?OTVs developed local
at98I — 40 C7H, 403 due ta high :=sts of
34! — operation and for POT*' protection.
58Z —
Six developed local pretreataeat
av66Z — due to vater quality (permit)
problems .
38Z —
101 —
4Z —
ieZ —
tOZ — Two POTVs cited sludge hacdlin;
— — aa reason for developing local
precreacment program.
30Z —
— Yes —
Champaign, Illinois, developed a
IOOZ — local precreatment program due to
to nev induatrial growth.
132/77/iO Data baae POT-'s less than
5 BE)
1 U2/7T/40 3ata baeed fOT-t reporting
ta receive IS flow
1 haitar and enforce ordinance
*> a rtgultr baa it
' WTB haa conducted, or ia
Deducting, or plana ta
eoaduct industrial vaste
78Z
21Z
(inaccurate
reporting; may
be hither)
981
32!
None
' Control all ICs by soae legal
techaniaa.
1JZ-28I
522
3-119
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O&M and Process Upsets
A high percentage of O&M and process upset problems at POTWs are associated
with nondomestic (industrial) flows entering the POTW. From a review of the
O&M data base and the 77 POTW visits, it can be concluded that industrial
waste control will reduce O&M and process upsets and improve POTW operation.
o In the range of 5 to 100 MGD 48 to 68% of the POTWs report major and
minor O&M problems associated with industrial waste.
o The percentage of industrial waste flow to a POTW is not an important
parameter for determining O&M problems and violations of NPDES
permits.
o Over 70% of POTWs that report receiving industrial wastes report O&M
problems associated with the industrial flow.
o Of POTWs with overloads 772 report hydraulic problems and 42% report
organic problems.
o O&M and sludge problems associated with industrial waste are the most
often reported reasons for performance problems other than plant
obsolescence.
o The most commonly listed problem industries are: food, electro-
plating, mechanical products, and textiles.
Permit Problems
An large percentage of POTWs violate their current NPDES permits. In
addition, these permits will be updated to provide control on priority
pollutants. The data presented in these analyses and summarized below
indicate that there will probably be POTW permit problems associated with
industrial flows.
o More than 802 of the POTWs in the O&M data base that report O&M
problems associated with industrial wastes violate their NPDES permit.
o Of the POTWs in the 77 POTW data base with permit violations, 65%
reported nondomestic flows as contributors.
o Almost 702 of all POTWs violate their NPDES permit, with approximately
502 of them in violation 102 or more of the time.
o Approximately 802 of all permits address only conventional pollutants
with 30-402 of current permits having been issued prior to 1977.
B-120
-------
o Approximately 50% of POTWs have some level of control (ordinance,
permit, etc.) on all industrial users in their system, but approximately
70% do not monitor on a regular basis.
Sludge Problems
As summarized below, the analyses indicate that sludge contamination is
primarily associated with the concentration of metals in the POTW sludge. As
more POTWs opt for land-based disposal options, the metal concentrations could
become critical.
o Heavy metals removed at POTWs are incorporated into the sludge of the
POTWs.
o POTWs in the O&M data base that were evaluated for sludge problems
reported that their sludge disposal practices and/or costs are about
100% dissatisfactory.
o Of the POTWs in the 77 POTW data base, 87% report sludge contamination
contributed by industrial wastes.
o The 77 POTW data base indicates that 30% of the POTWs are not aware of
their sludge quality.
Passthrough, Bypass, and CSO Problems
The data available are insufficient to analyze pass through of toxics
organics. In bypass situations all pollutants are discharged into the
receiving waters and there is a'potential for toxic pollutants to enter the
environment. The O&M data base yields the following:
o Approximately 35% of the POTWs bypass monthly for varying time periods
of up to 24 hours per month.
o The highest reported instances of bypass occur in Regions II and V.
The states in SPA Region V are heavily industrialized and the
potential exists for industrial pollution due to bypassing.
o The 40 POTW study found increased heavy metal concentrations in (CSO)
systems due to wet conditions. This may be due to flushing of netals
that settle during dry conditions.
B-121
-------
General
POTWs have operational problems chat are influenced by the industrial
flows entering their systems. A number of POTWs do not report industrial
flows because they do not know the volume, but they report industrial wastes
as contributors to their O&M, sludge, and permit problems.
o In the 40 POTW Study, industry was found to be the major contributor
of priority pollutants to POTWs. Variations in priority pollutant
concentrations can be attributed to the types and sizes of industries
discharging into the POTW.
o Approximately 25 organics, 8 heavy metals, and cyanide are normally
found in POTW influent.
o A number of POTWs report O&M problems due to industrial wastes but do
not report industrial flow quantities into their facility.
o Approximately 70+% of POTWs reporting industrial waste flows provide
secondary treatment, and are less than 5 M60.
o POTWs meeting secondary treatment requirements provide good removal of
priority pollutants. Generally, these POTWs remove 802-75% or more of
the heavy metals, 80% of the total volatile organics, and 702 of the
total acid-base-neutral organic pollutants.
o High concentrations of priority pollutants in the POTW influent
encourage high removal efficiency across the POTW.
o 68% of the POTWs do not monitor or enforce their industrial users on a
regular basis (at least once per year), and of the remaining 32% that
monitor for conventional pollutants, 12* monitor metals and 1.3%
monitor for toxics.
o POTWs that have existing pretreatment programs have lower concentrations
of priority pollutants in the POTW influent and effluent. For example,
total metals were 28% higher in the influents of POTWs and 34" higher
in effluents without pretreatment. These trends carried through for
acid-base-neutrals—76% and 59% for influent and effluent
respectively, and volatiles—315% and 299%, respectively.
B-122
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APPENDIX C
INTRODUCTION
To assess the environmental, health, and cost impacts and benefits of
pretreatment program alternatives, JR3 developed a mathematical model of the
2,000 POTWs required to adopt a program. The POTW model reviews each of the
2,000 POTWs requiring pretreatment, determines and quantifies the pretreatment
options for each, and then aggregates the results in order to estimate the
national impact, and to serve as a decision-making tool.
Appendix C is divid-ed into the following four sections:
o C-l Overview of the POTW Model
o C-2 Data Sources
o C-3 POTW Model Methodology, Assumptions and Documentation
o C-4 POTW Model Results and Analysis
Appendix C-l discusses the POTW model selection and conceptualization of
the model, approach of the model, and aggregation of the modeling
calculations.
Appendix C-2 provides a description of the data sources used by.the
Model. The model relies heavily on existing, centralized data bases such as
the Needs Survey, Dun and Bradstreet, and the Permit Compliance System. In
general, the data collected from these sources is specific to the 2,000 munic-
ipalities required to adopt a program.
Appendix C-3 describes the details of the computer model. the computer
model calculates the following:
o Impacts Related to Industrial Users - including environmental effects
such as sludge quality and quantity, and effluent quality; and
financial effects such as pretreatment-related costs and sludge
disposal costs.
C-l
-------
Impacts Related to POTWs - including environmental effects such as
influent and effluent concentrations, receiving stream flow, water
quality impacts, sludge quality and air emissions of volatile toxic
pollutants, and cost factors such as municipal pretreatment program
costs.
Appendix C-4 includes a discussion of the model's outputs and compares
these results to other EPA measures. The sensitivity of the model to various
factors is also addressed.
C-2
-------
C-l. OVERVIEW OF THE POTW MODEL
POTW MODEL SELECTION
During the early stages of this task JRB studied and reviewed several
analytical methods for quantifying the regulatory impact of various pretreat-
ment strategies. The models evaluated include: a nationwide combined model,
a POTW model and a case study model.
The nationwide combined method would have involved compilation of all the
2,000 POTWs requiring pretreatment and consideration of them as one large
national POTW. In this manner, a gross analysis of each of the options could
have been made. However, after the data collection task was completed, a
preliminary analysis of the data indicated that POTW characteristics and
problems are largely localized and unique to the individual POTW. The nation-
wide combined method would be too precise, as it would ignore the individual
characteristics of the POTWs and make comparisons between the options meaning-
less or unclear.
The POTW model method examined each of the 2,000 POTWs requiring pre-
treatment, for a variety of pretreatment options, and then aggregated the
results for estimating the national impact of each option. This method
collected data for POTWs from the Needs Data base, the 40 POTW Study, Effluent
Guidelines Data (EGD), Dun & Bradstreet (D&B) and Pollution Control System
(PCS) data for industry, and Office of Solid Waste data. In developing the
analytical model to perform this method, the Environmental Protection Agency
(EPA) made the following assumptions:
o Conventional pollutants would not be treated in the model except for
their effect on sludge quantities.
o POTW sludge was assumed to be rion-hazardous, regardless of the
concentration of priority pollutants.
o Industrial sludge was assumed to be hazardous and had one disposal
cost, independent of the disposal method used.
o Industrial raw wasteloads and discharge volumes from EGD data
accounted for current pretreatment in place.
C-3
-------
The POTW model developed used a. mass balance approach to determine the
quality and quantity of POTW effluent, sludge contamination, quantity of water
quality violations, and industrial and municipal pretreatiaent program costs.
Individual variables which compare each option are inserted into the model and
applied to each POTW. Although POTW results were aggregated, each POTV could
be analyzed individually or in subgroups to determine the effects on individ-
ual POTW types.
The use of case study model exclusively would have involved considerable
field visits and primary data collection with the further commitment of time
and resources. However, rather than expand the information base, it was
decided to review the existing published data, (see Appendices B-l through
B-7). Attention was directed toward specific POTW problems such as upsets,
intereferences and bypass not treated in the POTW-computer model. Information
on approximately 1,750 POTWs is documented through these studies. In addition
to POTW operational data, pretreatment program motivation, effluent quality,
worker health and safety, air quality, and estimates of the amount of
"grandfathering" in place were other issues analyzed.
C-4
-------
CONCEPTUALIZATION OF THE XODEL
One of the principal purposes of the Regulatory Impact analysis (RIA) is
to obtain quantitative information on the costs and the benefits associated
with industrial pretreatinent of wastewater. The data presented in Appendix 3
summarized the qualitative data, previous data compilations, and case studies
that pertain to pretreatment, and drew appropriate conclusions from each.
However, a natural extension of these results would be to prepare a precise
model that could quantify some of the known pretreatment-related costs and
benefits and that would serve as a valuable decisioniaaking tool. Addition-
ally, the model could predict some of the parameters that could not be
qualitatively discussed in Appendix B. The model is basically organized into
three modules:
(1) A regulatory alternative, which influences both the data selected
from appropriate data bases and the major baseline assumptions.
(2) Effects of that alternative on industry, including environmental
effects (sludge quality and quantity, effluent quality, etc.) and
cost effects (pretreatment technology cost, hazardous sludge
disposal, etc.).
(3) Effects of that alternative on POTWs, including operational effects,
(POTW sludge quality and quantity, effluent quality, etc.) cost
effects (pretreatment program implementation and development costs),
and environmental effects (water quality changes resulting from POTW
effluent and stream flow, volatilization of toxic organic pollu-
tants, etc.).
The following sections detail how the above factors were modeled, and what the
overall modeling approach involved.
APPROACH OF THE MODEL
It was first decided to computerize the entire modeling effort.
Computerization would:
o Facilitate data input from sources that were already computerized
(e.g., STORET, the NEEDS Survey, Dun and Bradstreet, Permit Compliance
system, etc.) and quickly handle the magnitude of the input data
required to accurately simulate the interactions of industry, the
POTW, and the environment.
05
-------
o Allow a microanalysis for a large number of POTW systems, and easily
make the nusaber of simulation runs, with slightly modified assump-
tions, to analyze the sensitivity of the assumption.
o Permit a precise analysis that includes as much of the nation as
possible.
o Facilitate modifications and changes in assumptions or data elements
in order to test additional alternatives quickly in the late stages of
the analysis.
o Be available for subsequent use in other EPA programs that could
benefit from a precise simulation of a POTW.
o Be more cost-effective than other methods of achieving the sane
results.
Next, a flow chart of the major modeling steps was developed. A simplified
chart is presented in Figure C2-1. The first major step was to read the input
data. The data sources are described in detail in Section C-2, but the major
iteas and their sources are:
o Number of industrial users (Dun and Bradstreet)
o Number of directly discharging industrial users (Permit Compliance
System)
o Average flow per industrial user in each category (EPA EGD)
o Average effluent quality per industrial user in each category (EPA
EGD)
o Removal required per industrial user in each category (EPA EGD)
o Cost of pretreatment technology per industrial user (EPA EGD)
o POTW statistics, i.e., flow, level of treatment (EPA NEEDS Survey)
o POTW removal efficiency (EPA 40 POTW Study)
o POTW nonindustrial contributions EPA 40 POTW and 4-City Study
o Sludge disposal costs (EPA estimates)
o Stream flows for each POTW, STORET, USGS.
C-6
-------
TABLE C2-I. MAJOR DATA SOURCES USED BY THE COMPUTER MODEL
DATA GROUT
POTW Data
BATA IM7UT ELEMENT
3
E
3
S
POTW ID & Location
POTW Flow
POTW Level of TreataenC
Methods of Sludge Disposal Used by POTW
POTW Seaoval Efficiency of Priority Pollutants
Data On
Industrial
Users
Industrial Flow to POTW
Nuaber of ID's per Category
Total Nueber of Direct lU's per Category
Total Number of Industrial Planes per Category in U.S.
Total Number of Direct Industrial Dischargers Per Category in US
Average Model Industrial Plant Flow per Category
Raw Waste Concentrations
Raw Waste Concent. Assuaing No Pretreataent In Place (Saseliae)
Sludge
Generation
Data
Industrial Sludge Generation Rates
Municipal Sludge Generation Rates
Average Receiving Streaa Flows
Low Receiving Streaa Flows
Receiving Streaa Water Quality Criteria for Aquatic Life
Receiving Streaa Water Quality Criteria for Public Health
Volatilization Rate of Volatile Toxic Organics
Cose Data
Unit Cost for Prtcreataenc Technology
Cost Estiaace for Development of Local Pretreacaent Prograas
Cost Sstiraate for lapleaeatacion of Local Pretreatsenc Prcgrsos
Uait Industrial Sludge Disposal Cost
Vnit Municipal Sludge Disposal Cost Per Method
Miscellaneous
Data
Pollutant Coneen. Contrib. by Non-Indus. Sources to Model POTV
Matching between SIC Codes and Category Codes
C--
-------
After the input of all data, the model was used to calculate the appro-
priate outputs The key computations performed were:
o Identification of all industrial users served by a POTw. Tnis
involved correlating Dun and Bradstreet/Permit Compliance files to the
proper categorical industry and determining how many indirect dis-
chargers exist.
o Prediction of the average effluent flow and characteristics, and the
pretreatment cost for industrial users. These data primarily related
data from EGD to the actual industrial user count and flow at each
POTW.
o Addition of a baseline concentration of toxic pollutants to account
for domestic and commercial contributions. These data were calculated
from two EPA studies: the 40 POTW study and the 4-City study.
o Adjustment of each industrial user flow to reflect the actual indus-
trial flow at that POTW (called "normalization"). The actual POTW
flow and industrial flow were based on the NEEDS Survey.
o Calculation of a POTW influent based on the previous three steps.
o Application of an average POTW removal efficiency for each toxic
pollutant depending on the POTW level of treatment, and subsequent
calculation of the POTW effluent and sludge concentrations of toxic
pollutants.
o Determination of the effects of the POTW effluent on stream quality
and its contribution to potential water quality violations. The POTW
effluent was divided by the actual stream dilution ratio (based on
stream flow) to determine these impacts.
•
o Calculation of the industry-related costs (pretreatment technology and
hazardous sludge disposal) based on industrial user count and indus-
trial flow.
o Calculation of POTW pretreatment program development and implementa-
tion costs based on the POTW flow, industrial flow, and number and
variety of industrial user's present.
AGGREGATION OF THE MODELING CALCULATIONS
The last step in the modeling effort was to prepare an aggregate summary
table presenting the national costs and the net improvement in water, air, and
sludge quality. The aggregation output can be used to compare the results of
C-8
-------
various pretreatment options. Items that appeared in the aggregation summary
include:
o Industrial sludge quantity and quality for significant toxic
pollutants, and disposal costs
o POTW sludge quantity and concentration of toxic pollutants
o POTW influent and effluent quality
o Applicable water quality and health criteria
o Ambient stream concentration (POTW effluent concentration/dilution
ratio)
o Average incremental percent of water quality criteria consumed by the
POTW discharged
o Number of POTWs exceeding water quality criteria as well as human
health standards.
In general, the model appears to be a credible simulation of a POTW
system. The model does have a number of specified and implied assumptions,
and some weaknesses was designed primarily to indicate specific differences
between various pretreatment options. Accordingly, the results calculated for
any particular POTW are often inaccurate because of the generalizations ar.d
normalization assumptions needed to design the model and because of certain
data deficiencies. Nonetheless, the aggregate results closely represent the'
actual cost and environmental effects expected from pretreatment. The major
omissions and assumptions of the modeling exercise that affect the conclusions
are:
POTW Model Weaknesses
o Conventional pollutants are not addressed, except as they affect
sludge production. EPA data for each of the categorical industries
does not always have sufficient data on treatability of conventionals
and removal by pretreatment technologies to be incorporated into the
model. This deficiency could be remedied in future analyses.
o The POTW removal efficiency for each pollutant in the model is
identical for all POTWs within a given level of treatment. Tha most
representative data on priority pollutant removal by a POTW is the EPA
C-9
-------
40 POTW study which only includes well operating plants, the median
removals from this study are usad in the model. As a result, the
estimates of possible water quality violations are probably a minimum.
The averaging effect of this assumption tends to further minimize the
water quality impacts calculated by the model.
Municipal sludge is defined by EPA to be non-hazardous. The cost of
municipal sludge disposal is, therefore, not a function of level of
contamination with toxic pollutants from industry — no matter how
severe the contamination. Consequently, improved sludge quality will
not have quantifiable economic effect in the model. If EPA issued new
sludge criteria, then certain sludge disposal options utilized by
POTWs might need to be replaced by more costly options. This result:
could greatly increase the cost effectiveness of some pretreatment
options.
Ambient water quality data for toxic pollutants is not available for
most water bodies. Therefore, the model could not calculate the
increaencal degradation caused by the POTW discharge. As a result the
actual number of violations are likely to be substantially higher than
those calculated by the model. Especially when several POTWs are on
one stretch of a stream. The model can be made to take into account
other discharges so that the marginal water quality impacts of each
PCTW can be calculated.
Industrial Model Weaknesses
o The only common denominator between the NEEDS Survey information of
POTWs and D&B identification of lUs is the city name. Consequently,
ITJs within a POTW service area but in a suburb or different city will
not be counted in this method. This affects the distribution of
industry in each POTW simulation. This error can greatly affect an
individual POTW, but has an overall minimal effect on the aggregate
results.
o Within cities with multiple POTWs, D&B cannot distinguish which POTW
services each IU discharges. This error is minimized by the flow
normalization procedure described in Appendix C-3.
o Each IU is assumed to have the characteristics of the EGD model plant.
As a result, the characteristics of an individual POTW will contain
errors related to the degree to which actual lUs in that system vary
from the national composite. Again, this assumption leads to an
understatement of water quality impacts.
o EGD has not entirely verified all organic priority pollutant discharge
data from industry categories. Consequently total toxic organics had
to be treated as a group in the model rather than individually.
Therefore, the model does not now estimate water quality criteria
exceedences for toxic organic pollutants.
C-10
-------
Overall Data Weaknesses
o At the time of this report D&3 could supply data for 1,600 of the
2,000 cities. The remaining data will be delivered shortly. The
400 POTWs outstanding appear to be larger on average than 1,600
cities, accounting for 6.5 bgd out of 21 bgd for the 2,000 POTWs.
However, we don't expect that the results and trends indicated by the
model will be significantly altered when the model is run with the
complete data base.
o The bench mark for water quality impacts of POTW discharges on the
model is the Federal Water Criteria, and Drinking Water Standards.
State standards were evaluated but were not found to be better for use
in the model.
o Stream flow data is only available for 703 streams (only 592 that
matched the 1,600 POTWs) from computerized data bases and other
readily accessible information.
Aggregate results are more representative of national cost and environ-
mental impacts than is the result for a particular POTW. Inaccuracies in
individual POTWs could be minimized by improving the quality of the input
data. For example, by contacting the POTW to determine its actual service
area, the accuracy of local industrial pretreatment costs and industry
discharge calculations could be improved. Thus the model could become a more
useful predictive tool for local POTWs or regional areas than it is using
nationwide data bases. Using local site-specific water quality and local
sludge would enable the model to be used to optimize the development of such
advance limits on their industrial discharge control measures at specific
POTWs.
C-2. DATA SOURCES
A broad approach ws applied to data collection efforts for the 5.IA. In
an attempt to be as thorough and all-inclusive as possible and to ensure that
modeling results were accurate. The following pages present the major data
sources used in the model and a description of how each was applied to it.
These sources are:
o Dun and Bradstreet Marketing Services (Dun and Bradstreet 1981)
Oil
-------
o Permit Compliance System (U.S. EPA 1981)
o SPA Supplied Data (DENIT 1981, O'Farrall 1981)
o NEEDS Survey (U.S. EPA 1980)
o 40 POTW Study (Feiler 1980, Southworth 1981)
o 4-City Study (Adams 1981)
o STORET/USGS (U.S. EPA 1981)
o Pretreatnent Program Costs.
The overall limitations of the data are also summarized.
DUN AND BRADSTREST MARKETING SERVICES
Dun and Bradstreet Marketing Services (D&B) has compiled a list of many
industrial, commercial, and service firms in the United States as a credit
service to its clients. Categorized by Standard Industrial Classification
(SIC) code and city, this data base represents the most complete centralized
listing of manufacturing facilities that was available for the RIA. The D&3
computer tapes were requested for those cities containing the 2,000 POTWs
required to implement the General Pretreatment Regulations. 3y the deadline
for this report, information was supplied for 1,607 of these. Several
problems with the D&3 data as applied to RIA were recognized:
o D&B listings could only be obtained for industrial users in. the same
city as the POTW. Data could not be obtained for industrial users
that discharged to regional POTWs, but were located in nearby cities
or suburbs.
o Where cities had multiple POTWs, D&B data could not identify where any
particular industrial user discharged.
o D&B listings icluded direct, indirect, and zero discharges.
JR3 checked at random several POTWs that had completed industrial waste
surveys and compared those data with D&B listings. Overall, the data were
consistent; consequently, subject to the above constraints and the adjustments
that were made, D&B counts were used as the basis for identifying the indus-
tries present in a POTW system.
C-12
-------
PERMIT COMPLIANCE SYSTEM
The Permit Compliance System (PCS) is a data management system designed
to track the conditions detailed in SPDES permits. For purposes of the RIA,
the only data extracted from PCS were counts of direct discharging facilities
in each city by SIC code. These counts were subtracted from the D&3 counts to
approximate the number of industrial users indirectly discharging to the POTW.
EPA-SUPPLIED DATA
For each categorical industry, and for several noncategorical industries,
the Effluent Guidelines Division (EGD) of EPA provided estimates of the number
of facilities nationwide that discharge to POTVs, their total flow, quantity
of several toxic pollutants, best estimates of removals that would be required
under Pretreatment Standards for Existing Sources (PSES) and the resulting
pretreatment technology costs (O'Farrell 1981). By necessity, these estimates
were used to predict what characteristics each individual plant in each
category would contain. The EGD also supplied estimates of the total number
of plants in each category (direct, indirect, and zero dischargers). These
estimates were used to adjust D&3 national counts to ensure consistency
between the two data bases.
The EGD raw waste load data, which was used to profile existing POTW
conditions, accounted for the amount of pretreatment already in place. A
separate set of raw waste load data with no pretreatment was also provided by
EGD, as a measure of the mangitude of toxic pollutant control achieved to
date.
The pretreatment technology cost data from EGD were provided as a
national total for each categorical industry. This total was converted to a
cost per unit of flow, which varied between categories, and was applied to the
flow from facilities in each SIC code category. The required removals by PSES
were EGD estimates, since few regulations have yet been issued.
EPA has also supplied other assumptions and data throughout the develop-
ment of the model, on such items as sludge disposal costs and adjustments to
industrial user totals.
C-13
-------
EPA NEEDS SURVEY
The NEEDS Survey is designed to determine the cost of needed treatment
work and sewer system construction. The survey is performed every 2 years,
and the summarized results are reported to Congress. The costs predicted by
the Survey are used by the states and EPA as a basis for allocating these
funds. Surveys of construction needs have been conducted since 1969; the
first to include a prediction of the costs to meet future goals (1983) was
performed in 1972, the year that major changes were made in the Federal Water
Pollution Control Act. The most current completed survey (1980) was used in
the RIA model to obtain information for each of the 1,607 POTW s where D&3
data were available. The principal data items extracted from the NEEDS Survey
include:
o POTW identification
o POTW flow
o POTW industrial flow
o City, state, and region
o Level of treatment
o Sludge disposal method(s) used.
The POTW city name provided the common denominator for D&B counts of various
industries. The POTW flow and industrial flow determined the flow normal-
ization procedure used in the model.
40 POTW STUDY
From 1978 to 1980, the EGD conducted an intensive sampling program at
40 POTWs to characterize the fate and occurrence of toxic pollutants in POTWs.
This study was fully described in Section B-4. Basically it consisted of
week-long sampling of 40 POTWs1 influent, effluent, and sludge streams for
conventional and priority pollutants. The data from this study had three
basic uses in this model:
(1) It was the primary source for data on the removal of toxic
pollutants by POTWs.
C-14
-------
(2) It,^along with the 4-City Study, was the basis for estimating the
nonindustrial contribution of toxic pollutants to POTWs.
(3) It was used to verify many of the outputs for the social.
The 40 POTW Study compiled data on influent and secondary effluent at
40 reasonably well-operated POTWs that net at least secondary if not
30/30 treatment requirements. These data formed the basis of secondary
removal levels for each toxic pollutant that were required for the model. Of
the 40 POTWs, 7 also had tertiary treatment in place and operating at the time
of sampling, and data from these POTWs constituted the POTW tertiary removal
data. Although primary effluent samples were collected at approximately one-
third of the 40 POTWs, it was judged that primary effluent at secondary POTWs
did not reflect that of primary plants for a variety of reasons, including
interferences from recycle lines. Consequently, primary removal of toxic
pollutants was estimated from one of the 40 POTWs that had no recycle lines,
and from literature sources.
Two of the 40 POTWs sampled received virtually no industrial wastewater.
These POTWs were used as one benchmark of the nonindustrial priority pollutant
loading expected from domestic and commercial sources. A second studv used to
determine nonindustrial contribution is described in the following section.
EPA 4-CITY STUDY "
During 1978 and 1979 the Monitoring and Data Support Division of EPA
conducted a source sampling survey of 4 POTW collection systems. Sampling in
all 4 cities was conducted in interceptors from domestic, commercial, and
industrial users, and at the POTW influent. The industrial component of this
study was not used in the RLA because the four collection systems did not
include a sufficient variety of EPA's categorical industries. However, the
domestic and commercial results were used in the model as a second measure of
nonindustrial contribution. It is important to note that two of the four
cities in this study were the two plants from the 40 POTW study that had
little industry. All four cities were included in the 40 POTW sampling.
C-15
-------
STORST/USGS
Where available, stream flow data for each POTW was collected fron the
STORST and U.S. Geological Survey (USGS) data bases, supplemented by EPA's
Basin Characteristics File. At this time, data are only available for
703 streaas matching the 2,000 cities that require pretreataent programs and
for 592 of the streams corresponding to the 1,600 POTWs for which D&B data are
available.
PRETREATMENT PROGRAM DEVELOPMENT AND IMPLEMENTATION COSTS
JRB prepared two independent cost estimates of pretreatment program
costs: the first based on engineering estimates by individuals who were
experienced in developing these programs for municipalities, and the second a
statistical analysis of data supplied by cities that had completed such
programs, with coses drawn from their 201 Grant applications. Both cost
estimates are displayed in the computer model.
DATA 3ASE LIMITATIONS
Overall, the many data sources provide excellent information on the
2,000 POTWs. However, some of the data are being used for purposes other than
those intended at the time of data collection and may have some inaccuracies.
The generalized limitations of the data are described in the following
paragraphs.
The number and type of industrial users serving a POTW can not be
properly approximated by using D&B counts for industrial users in the city
where the POTW is located, because regional plants that serve two or more
communities will undercount the industrial users, while cities with more than
one POTW will count the same industrial users twice or core. Adjustments were
made betveen the national total of plants counted by D&B and by EPA to some-
what normalize the total counts. However, any single POTW may be signif-
icantly misrepresented. The major limitation of the data, therefore, is not
whether the absolute D&B count for each SIC code is accurate, but whether the
ratio of plants in each category reflects the actual distribution in that POTW
system.
C-16
-------
The industrial users in each category at each POTW were all assur.ed to
have the model plant flow and effluent quality predicted by EPA. On an
aggregate basis this will result in a total similar to EPA's estimated total,
but again an individual POTW's influent may have far different characteristics
than those predicted by the model, depending on how closely their industrial
users match EPA's model plants.
The majority of the environmental quality calculations performed in the
model are based on the computed influent quality and the individual industrial
wastestreams. On the PQTW level, these outputs are affected by the factors
discussed above. There are also other assumptions in the model relating to
treatment efficiency and sludge production, which treat all POTWs as "average"
plants. However, these assumptions have less impact on the results than the
above factors.
C-17
-------
C.3 MODEL METHODOLOGIES AND ASSUMPTIONS
The computer modeling effort has been described in general cernis in
previous sections of the RIA. Tnis Appendix provides the specific methodology
employed by the model, relates the data sources to the model's algorithms, and
details the explicit and implicit assumptions made. Appendix C-3 is divided
into subsections which correspond to the major tasks within the model, and
which are based on the general design described in Appendix C-l.
A simplified flow chart of the model is presented in Figure C3-1. It
represents the data inputs received and the major outputs prepared. Table
C2-I, previously presented in Appendix C-2, is repeated here as Table C3-I.
This table indicates the relationship of the data sources to the needed inputs
of the model.
INDUSTRIAL MODULE OF THE MODEL
Identification of all Industrial Users (lU's) Served by a POTW and Calculation
of the Total Industrial Flow and Pollutant Loading to the ?OTW
The industrial component of POTW flow was determined by the following
steps:
1. The number of Industrial Users (lUs) was first computed by counting
the D&B responses for each SIC code in the city matching the POTW
location city from the Needs Survey. The SIC code responses were
then assigned to appropriate categorical industries according to
definitions supplied by EGD. A listing of these definitions is
presented in Table C3-II.
2. Because D&B site descriptions and counts are often more broadly
defined than EGD estimates of actual manufacturing sites, the D&B
counts were adjusted according to the following ratio (calculated for
each categorical industry):
Adjustment Factor = Total Nupper of Plants Estimated by EGD Nationwide
Total Number of Plants Counted by D4B Nationwide
The adjustment factors derived are listed in Table C3-III.
3. A count of direct dischargers in each city was obtained from the PCS
database. These counts were assigned to the proper categorical
industry according to the same definitions described is Table C3-II.
C-18
-------
Figure C3-1. Simplified Flew Chare of the Ccir.nucer Model
D & 3
PCS
Needs Survey
Scream Flews
EGD CAtegorical Data
Cose Data
PTOW Efficiency Data
Water Quality Criteria
Select an
Oocicn
J Read Data
i Sources
Compute IUs
and Industrial;
Flow oer ?0'
131 i 3|
rw I
N"orr.alize
necessar
Calculate Industrial
Sludge Quality/Quantit
Calculate ?CTW
Influent
Quantify Environmental
Effects
• Water Quality Violations
• Emission to Air
• POTV Sludge Quality
• POTW Effluent Cualitv
Output Suroaary
of Results
Quantify Option
Costs
• Industrial Sludge Disposal
• Industrial Precr&atr.enc Techology
• Pretreatnent Program Costs
• POTW Sludge Disposal Costs
_^ Aggregate
1 Results
End
-------
TABLE CJ-1.
MAJOR DATA SOURCES USED BY THE COMPUTER MODEL
DATA GROUP
POTV Data
Data On
Industrial
Csers
Sludge
Generation
Data
Cost Cata
Miscellaneous
Data
DATA IJt?UT ELS^Errr
POTW ID & Location
?OW Flow
?OTW Level of Treatment
Methods of Sludge Disposal Used by POTW
POTW Senoval Efficiency of Priority Pollutants
Industrial Flow so POT*
N'unber of lU'j per Category
Total Sraber of Direec lU's per Category
Total Suabcr of Industrial Plants per Category in O.S.
Total Number of Direct industrial Dischargers Per Category 'in US
Average Model Industrial Plane Flow per Category
Rav Waste Concentrations
Raw Waste Concent. Assuming No Pretreataent In Place (3aselir.e)
Industrial Sludge Generation Rates
Municipal Sludge Generation Satss
Average Receiving SCrean Flows
Lav Receiving Streaa Flows
Receiving. Strean Water Quality Criteria for Aquatic Life
Receiving Stream Water Quality Criteria for Public Health
Volatilization Rate of Volatile Toxic Organics
Unit Cost for Pretreatsent Technology
Cost Estiaate for Development of Local Pretrearsent Programs
Cast Estiaate tor Implementation of Local ?retreat=ent Prsgraas
Unit Industrial Sludge Disposal Cast
"nit Municipal Sludge Disposal Cast ?sr Method
Pollutant Coccen. Contrib. by Non-Indus. Sources to Medal ?07V
Matching between SIC Codes and Category Cedes
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C-20
-------
TABLE C3-II. MATCHING OF SIC CODES WIT?. CATEGORICAL I*TBU^
1 ACHESIVES
2 ALUMINUM FORMING
2 ALUMINUM FORMING
2 ALUMINUM FORMING
2 ALUMIHUM FORMING
2 ALUMIHUM FORMING
2 ALUMINUM FORMING
3 AUTO 4 OTHER LAUNDRIES
3 AUTO 4 OTHEH LAUNDRIES
3 AUTO 4 OTHER LAUNDRIES
H BATTERY MANUFACTURING
* BATTERY MANUFACTURING
5 COAL MINING
5 COAL MINING
5 COAL MINING
5 COAL MINING
6 COIL COATING
7 COPPER FORMING
7 COPPER FORMING
7 COPPER FORMING
8 ELECTRICAL PRODUCTS
9 ELECTROPLATING (Job Shops)
9 ELECTROPLATING (.Job Shoes)
10 EXPLOSIVES MANUFACTURING *
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
11 FOUNDRIES
12 GUM 4 WOOD CHEMICALS
13 INORGANIC CHEMICALS
13 INORGANIC CHEMICALS
13 INORGANIC CHEMICALS
13 INORGANIC CHEMICALS
U IRON 4 STEEL
It IRON 4 STEEL
1M IRON 4 STEEL
1H IRON 4 STEEL
U IRON 4 STEEL
15 LEATHER TANNING 4 FINISHING
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C-21
-------
iA3LE C3-I1. ETCHING OF SIC CODES WITH CATEGORICAL INDUSTRIES 'Cc- '-."
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PSODUCtS
PHCDUCTS
PRODUCTS
PRODUCTS
PRODUCTS'
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS :
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS • •
PRODUCTS
PRODUCTS
PRODUCTS I
PRODUCTS ;
PRODUCTS; :
PRODUCTS ' 5
PRODUCTS - :
PRODUCTS*
PRODUCTS?.
PSCDUCTSt
PRODUCTS *
PRODUCTS .-
PRODUCTS
PRODUCTS.'
PRODUCTS
PRODUCTS
PRODUCTS
PHCDUCTS
PRODUCTS
PRODUCTS '
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS
PRODUCTS "• .
PRODUCTS
PHCPUCTS
PHCDUCTS ^^
PRODUCTS -""""^
: •- : '
• -. ' *i
3537
3533
3539
35*0
35*1
35*2
35*3
35**
35*5
35*6
35*7
35*3
55*9
3550
3551
3552
3553
355*
' 3555
3556
3557
3558
2 3559
E* 3560
= 3561
3562
> 3563
-i 356-«
1 3565
3 3566
3567
•? 3563
5 3569
1 3570
4 3571
r 3572
- 3573
j 357*
J 3575
' 3576
3577
3573
3579
3vSC
35 ,;1
3582
3533
353*
35S5
3536
3567
353S
3539
3590
35?i
3592
3593
359*
3595
3596
3597
3593
3559
C-22
-------
TABLE C3-II.MATCHING 0? SIC CODES WITH CATEGORICAL INDUSTRIES (Con'd)
lb H£CHANICA_ PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHAHICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHAHICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
3602
3603
3605
3606
3607
3608
3609
3610
JW I W
361 1
351*
3615
Jw ' J
3616
3617
3618
J W 1 W
3619
3620
3622
3623
- 3625
3 3626
J" 3627
; 3628
J "" *
> 363*
* • 36'5
j JO-3
— 3636
3 3637
) J*"' J I
3638
? ^,M
5 3£*3
3 36*5
4
5* 36*7
*
3 36*9
j • J v *
; 3650
3 3651
J W ^ '
3652
3653
-*w •* J
365*
3655
•- 3657
JUJ 1
3653
3659
3650
3661
3662
3663
366*
'665
_f!JW J
3666
3667
3668
3569
3670
3675
3673
3680
^631
j 3682
3533
'*
1i "-CHANICAL PRODUCTS
15 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSCDUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSCDUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS „
.< ..—.,. .IT- .. nn~.n. ,..->•..
\
,
i
1
i
w
e.
~
^
.-.
^_
~
^
•~
.Z
C3
—i
5"
S-4
^J
o
a
r-l
i
!
^
'^ -;
3 '- .J 6
3637
3688
3689
3590
3695
3696
3697
3693
3700
3701
3702
3703
370*
3705
3706
3707
3708
3709
' 3710
3711
3712
3713
37 1*4
3715
37-6
3717
3718
3719
3720
3721
3722
3723
3724
3725
3726
3727
3728
3729
3730
3731
3732
3733
373"
3735
3735
3737
3733
3739
37*0
37*1
37*2
37l*3
371,4
37*5
37*7
37*3
37*9
3750
3751
3752
3753
375*
rrs
C-23
-------
TABLE C3-II.
MATCHING OF SIC CODES WITH CATEGORICAL INDUSTRIES (Coat'd)
16 MECHANICAL PHODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRCDUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSOCUCTS '
~ -.
i
i
j
i
i
!
in
c.
o
53
>
7J
c.
5
•5
S3
f-i
o"
J-i
o
1— I
a
\
I
j
i
I
I
j
I
i
|
I
;
{
!
i
'
i
i
X
375o
3757
3753
3759
3760
3761
3762
3763
376*
3765
3766
3767
3763
3769
3770
3771
3772
3773
377H
3775
• 3776
3777
3778
3779
3780
3781
3782
3783
378*
3785
3786
3787
3788
3789
3790
3791
3792
3793
379*
3795
3796
3797
3798
3799
3800
3801
•3802
3803
380*
3805
3806
3807
3808
3809
3810
3811
3812
3813
381*
3815
3816
3817
3818
3819
3820
3821
10 MECnANI'JAw Kl^lXlC.'S ~^
16 MECHANICAL PSCDUCT3
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PSODUCTS ',
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS ',
16 MECHANICAL PSODUCTS i
16 MECHANICAL PRODUCTS ;
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS
16 MECHANICAL PRCOUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRCCUCTS i
16 MECHANICAL PSODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS j
16 MECHANICAL PRODUCTS '.
16 MECHANICAL PRODUCTS |
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS a.
16 MECHANICAL PRODUCTS 9
16 MECHANICAL PRODUCTS 35
16 MECHANICAL PRODUCTS
16 MECHANICAL PHODUCTS >
16 MECHANICAL PRCDUCTS ^
16 MECHANICAL PRODUCTS C.
16 MECHANICAL PRODUCTS y
16 MECHANICAL PHODUCTS
16 MECHANICAL PRODUCTS "
16 MECHANICAL PRODUCTS ^
16 MECHANICAL PSODUCTS 3
16 MECHANICAL PRODUCTS T
16 MECHANICAL PRODUCTS c"
16 MECHANICAL PRODUCTS £
16 MECHANICAL PRODUCTS y
16 MECHANICAL PRODUCTS .2
16 MECHANICAL PSODUCTS —
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PHODUCTS
16 MECHANICAL PSODUCTS ;
16 MECHANICAL PRCDUCTS ;
16 MECHANICAL PRCDUCTS '
16 MECHANICAL PSODUCTS 1
16 MECHANICAL PRODUCTS !
16 MECHANICAL PRODUCTS
16 MECHANICAL PSODUCTS '
16 MECHANICAL PRODUCTS i
16 MECHANICAL PRCDUCTS :
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL P30CUCTS .'
16 MECHANICAL PRODUCTS I
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRCDUCTS
16 MECHANICAL PRODUCTS i
16 MECHANICAL PRODUCTS ^^
<*<• '
»ro 5
3S2-
3825
3826
3327
3323
3329
3330
3831
3832
3333
383*
3935
3336
3837
3833
3839
33*0
38*1
38*3
38*5
38*6
38*7
38*6
33*9
3350
3351
3352
3853
335*
3355
38C6
JV * «
3857
3858
3859
3860
3862
3862
386*
3865
33*6
3667
3863
8869
3870
3371
jfj I i
3372
3373
337*
3375
3876
3877
3378
3379
3SOO
3881
3S82
3383
388*
3365
3366
3537
C-24
-------
TABLE C3-II. MATCHING OF SIC CODES WITH CATEGORICAL INDUSTRIES (Cont'd)
15 MECHANICAL Pi-C DUCTS
15 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS t
16 MECHANICAL PRODUCTS ,
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS °
16 MECHANICAL PRODUCTS <
16 MECHANICAL PRODUCTS J.
16 MECHANICAL PRODUCTS ^
16 MECHANICAL PRODUCTS c
16 MECHANICAL PRODUCTS ^
16 MECHANICAL PRODUCTS :
16 MECHANICAL PRODUCTS 4
16 MECHANICAL PRODUCTS -
16 MECHANICAL PRODUCTS i
16 MECHANICAL PRODUCTS '•
16 MECHANICAL PRODUCTS j
16 MECHANICAL PRODUCTS •
16 MECHANICAL PRODUCTS <
16 MECHANICAL PRODUCTS ~
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS •
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS ^~
-5
^£^9
,1 2 J \J
' 3c9l
: 3392
3893
389*
3895
3896
3397
3893
3899
3900
3901
3902
3903
390*
3905
3906
3907
3908
' 3909
a 3910
§• 3911
= 3912
~ 3913
J 391*
5 3915
i 3916
7 3917
J 3918
x 3919
5 3920
-> 3921
2 3922
^ 3923
2 392*
j 3925
J 3926
•J 3927
3928
3929
3930
3931
3932
3933
393*
3935
3S36
3937
3938
3939
39*0
39*1
39*2
39*3
39**
39*5
39*6
39*7
39*3
39*9
3950
3951
3952
3953
~--'T
16 HiCHAHICAL FHCDUC15
15 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
15 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS •-"
17 NON-FERROUS METALS
17 NON-FERROUS METALS
17 NON-FERROUS METALS
17 .NON-FERROUS METALS
17 NON-FEHSOUS METALS
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 CRE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
18 ORE MINING 4 DRESSING
19 ORGANIC CHEMICALS
19 ORGANIC CHEMICALS
20 PAINT 4 INK
20 PAINT 4 INK
21 PESTICIDES
22 PETROLEUM REFINING
•31 putPuirriiTTni 3
en
c.
o
CJ
c"
-U
<3
£
o
2955
2556
3957
3958
3959
3960
3961
3962
3963
396*
3965
3966
396?
3968
3969
3970
3971
3972
3973
397*
397;
3976
3977
3978
3979
3980
3961
3982
3933
398,
3935
3986
3987
3983
3939
3990
3991
3992
3993
399*
3995
3997
3995
3999
3331
3332
333*
3339
33m
1011
1021
1037
10*1
10**
1051
1061
1092
109*
1099
2365
2869
2851
2893
2379
2911
C-25
-------
TABLE C3-II. MATCHING OF SIC CODES WITH CATEGORICAL INDUSTRIES (Conc'd)
«!i
23 PHARMACEUTICALS
2t PHOTOGHAPHIC SUPPLIES
25 ?LAST:CS i SYNTHETICS
25 PLASTICS 4 SYNTHETICS
25 PLASTICS 4 SYNTHETICS
26 PLASTICS PROCESSING
27 PORCELAIN ENAMELING
27 PORCELAIN ENAMELING
27 PORCELAIN ENAMELING
27 PORCELAIN ENAMELING
27 PORCELAIN ENAMELING
27 PORCELAIN ENAMELING
23 PSINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 P3IHTIMG 4
28 PRINTING 4
28 P3INTING 4
28 PRINTING 4
28 PRINTING 4
28 PSINTING 4
28 PRINTING 4
28 PRINTING 4
28 PSINTING 4
28 PRINTING 4
28 PRINTING
?fl PSINTING
28 PRINTING 4 PUBLISHING
28 PRINTING PUBLISHING
28 PS1NTINO 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PSINTING 4
28 PSINTING 4
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
4 PUBLISHING
4 PUBLISHING
28 PRINTING
28 PRINTING
28 PRINTING 4
28 PRINTING 4
28 PRINTING 4
28 PRINTING
PUBLISHING
PUBLISHING
4 PUBLISHING
4 PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRITING 4 PUBLISHING
23 PSINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PSIKTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PSJWTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
23 PRINTING 4 PUBLISHING
28 PSINTING 4 PUBLISHING
-S3i
2S3»
3361
2521
2323
282-.
3079
3*29
3*31
3631
3632
3633
3639
2711
2712
2713
271*
2715
2716
2717
2718
2719
2720
2721
2722
2723
272*
2725
2726
2727
2728
2729
2730
2731
2732
2733
273*
2735
2736
2737
2738
2739
27*0
27*1
27*2
27*3
2?t*
27*5
27*6
27*7
27«8
27*9
2750
2751
2752
2753
275-.
2755
2756
2757
2758
2759
2760
2761
2762
£3 f^lMliNU 4 fJUuiirtiNti
28 PSINTING 4 PU3LI3HING
23 PRINTING 4 PUBLISHING
23 PRINTING i PUBLISHING
28 P3INTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
23 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PalNTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PSINTIMG 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PRINTING 4 PUBLISHING
28 PULP. PAPER 4 FIStSBOARO
29 ?ULP, PAPSR 4 FIBESBOA8D
29 PULP, RAPES 4 FI3ESSOASD
29 PULP. PAPEH 4 FI3E3BOARD
29 PULP. PAPSS 4 FI3ES30ASD
30 NON -CATEGORICAL INC.
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
2763
2769
2770
2771
2772
2773
2?7"
2775
2776
2778
2779
2730
2751
2732
2561
2611
2621
2631
2661
2032
2033
203*
2035
2037
203S
2099
2021
2022
2023
202*
2026
2091
2C92
51*6
5-23
2016
2017
20»1
20*5
20*6
20*8
2011
2013
2017
203*
2038
20*7
2051
2C52
2265
2066
206?
207t
2075
2076
2079
2032
2083
C-26
-------
TABLE C3-II. MATCHING OF SIC CODES WITH CATEGORICAL INDUSTRIES (Cont'd)
20
;o
30
30
30
30
30
30
31 SOAPS 4 DETERGENTS
31 SCAPS & DETESGSNTS
31 SOAPS 4 D£TE?,G£NTS
32 STEAM ELECTS1C
32 STEAM ELECTHIC
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE HILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE HILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE HILLS
33 TEXTILE MILLS
33 TEXTILE HILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE HILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
53 -rYTTi r «T: i <;
2086
2037
2095
2097
2098
2099
51 «^
5182
28m
28*2
28*3
j3 it.ti:,.t
*931
2210
2211
2212
2213
221H
2215
2216
2217
2218
2219
2220
2221
2222
2223
222*.
2225
2226
2227
2228
2229
2230
2231
2232
2233
223*
2235
2236
2237
2238
2239
22*0
22*1
22*2
22*3
22*-.
22*5
22>»6
22*7
22*8
22*9
2250
2251
2252
2253
225*
2255
2256
2257
2258
2259
2260
2261
i 3 TT YT *- ~ M r^ i s
33 TiXTILt HILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TtXTILi MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TSXTILS MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
B3 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
33 TEXTILE MILLS
3* TIMSE3 PSODUCTS
3* TIMBEH PSCDUCTS
3* TIMBES P300UCTS
PROCESSING
PROCESSING
PROCESSING
2265
2266
2267
2268
2269
2270
2271
2272
2273
227 x
2275
2275
2277
2273
2279
2280
2281
2222
2233
223-
2285
2286
2257
22 33
2289
2291
2292
2295
2296
2297
229*
2299
2*91
2651
2*99
C-27
-------
TABLE C3-III
SIC ADJUSTMENT FACTORS
INDUSTRY ADJUSTMENT FACTOR
1. Adhesives /Sealants
2. Aluminum Forming
3. Auto & Other Laundries
4. Battery Manufacturing
5. Coal Mining
6. Coil Coating
7. Copper Forming
8. Electrical Products
9. Electroplating Job Shops
10. Explosives Manufacturing
11. Foundries
12. Gum & Wood Chemicals
13. Inorganic Chemicals
14. Iron & Steel
15. Leather Tanning & Finishing
16. Electroplating Captive Shops
17. Non-Ferrous Metals
18. Ore Mining & Dressing
19. Organic Chemicals
20. Paint & Ink Formulation
21. Pesticides Manufacturing
22. Petroleum Refining
23. Pharmaceuticals Manufacturing
24. Photographic Supplies
25. Plastics & Synthetics
26. Plastics Processing
27. Porcelain Enameling
28. Printing & Publishing
29. Pulp, Paper & Fiberboard
30. Non-Categorical Industries
31. Soaps & Detergents
32. Steam Electric Power Generation
33. Textile Mills
34. Timber Products •& Processing
0.658
0.199
1.0
0.69
1.691
0.036
0.385
0.322
0.83
1.521
0.417
0.14
0.058
0.358
0.291
1.0
0.322
1.0
1.223
0.837
0.215
0.042
0.173
0.082
1.0
1.0
0.045
0.949
0.444
0.2
0.596
0.189
0.199
0.103
C-28
-------
This PCS count was subtracted from the adjusted D&3 count (Step 2) to
result in the estimated number of indirect discharges to a POTW. In
the few instances where PCS was greater than adjusted Da3 were set
equal to 0.
4. For two categorical industries (metal finishers - job shops and metal
finishers - captive shops) a different approach was used, based on a
telephone survey by EPA. For captives the number of indirect dis-
chargers was defined as 3 tines the nunber of direct dischargers
(from PCS). For job shops, the number of indirect dischargers was
defined as 9 times the number of direct dischargers. This approach
was necessitated by the larger number of sites that are defined as
metal finishers according to the SIC code definition but generate no
wastewater. EPA consequently decided that the above approach would
result in the best approximation of nietal finisher distribution.
Implicitly however, this approach assumes that indirect dischargers
are geographically distributed among cities proportionally to direct
dischargers.
5. One categorical industry, rubber manufacturing, was not addressed by
the model because industry was excluded from regulation and data from
EGD was not available. Since there are almost no indirectly
discharging rubber plants the error of this assumption is small.
6. EGD supplied an assumed model plant flow as well as effluent
characteristics for each of the categorical industries. The effluent
description included specific concentrations for the priority
pollutant metals, but only a total concentration of the organic
priority pollutants. This flow and effluent characteristic was used
for each categorical industry to determine the industrial component
of the POTW flow and toxic loading as follows:
-r , • ! -, indirect n , .
Industrial Flow = ^ count ^ model
i=l i i
Industrial Priority Pollutant Loading = (Indirect I'J count).
i-1
(C model)^
The information supplied by SGD is detailed in the Tables C3-IV and C3-V to
this section. The user of one model plant flow and one assumed effluent
concentration has the effect of minimizing the variability of industrial flow
and wasteload to the POTW. However, the following section will indicate how
the model attempted to negate these limitations by relying only on the
distribution of industry and not the actual IU count.
C-29
-------
TABLE C3-IV
Average Flow (CQ model) of Model Industrial Use:
Category
Average Flow (tngd)
1.
2.
3.
4.
5.
6.
7.
8.
9a.
9b.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
Adhesives & Sealants
Aluminum Forming
Auto & Other Laundries
Battery Manufacturing
Coal Mining
Coil Coating
Copper Forming
Electrical & Electronic Products
Electroplating & Job Shops
Electroplating & Captive Shops
Explosives Manufacturing
Foundries
Gum & Wood Chemicals
Inorganic Chemical Mfg.
Iron & Steel
Leather Tanning
Mechanical Products
Non-Ferms Metals
Ore Mining & Dressing
Organic Chemical Mfg.
Paint & Ink Formulating
Pesticides
Petroleum Refining
Phsmaceutical Mfg.
Photographic Equip. & Supplies
Plastic & Synthetics
Plastic Dressing
Porcelain Enameling
Printing & Publishing
Pulp, Paper & Fiberboard
Rubber
Soap & Detergent Mfg.
Steam Electric Power Generation
Textile
Timber
0.0106
0.0822
0.0062
0.0254
0.0
0.065
0.112
0.088
0,019
0.069
0.008
0.061
0.233
0.664
0.017
0.221
0.0
0.041
0.0
0.802
0.0007
0.0937
0.0936
0.1561
0.0117
0.802
0.01
0.0067
0.0028
0.878
0.0
0.0553
0.1414
0.2187
0.14457
35. Non-Cacegorical Industries
0.113
030
-------
Table C3-V
Industrial Waste-water Characteristics
n
Auto
Adhesives Aluminum other Mattery Coal coil
Pollutant & Sealants Forming Laundries Manufacturing Mining Coating
Silver (A(|)
Arsenic (As)
Beryllium (Be)
Cadmium (Cd)
To t ;« I Ch r om i urn ( C r )
Copper (Cu)
Mercury (llg)
Nickel (Mi)
Lead (Pb)
Antimony (Sn)
Selenium (Se)
Thai limn (Th)
Zinc (Zn)
Cyanide (Cn)
Toxic Organic s
Pest ie idea
BOD
TSS
Ainiiioii i a
? 't ? ? V ? 9 9 9 9
Pre treatment Tech.
Cor.t/SlOOO gal.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
8
0
0
0
0.016
44.631
125.9
0
0.221
0.174
0
0
0
114.75
0.085
0.014
0
0
62.617
0
28. 644
$22.00
0.028
0.0012
0.
0.644
0.494
0,261
0.130
1.164
3.764
0
0
0
5.959
0.008
0.008
0
0
1165.936
0
55. 326
8.20
0
0
0
0
21.32
0
0
0.147
0
0
0
0
0.6
0.147
0.253
0
0
67.95
0
119.9
2.80
Copper
Forming
0
0
0
0
0.041
36.749
0
1.185
0.215
0
0
0
8.641
0
0
0
0
4.602
0
42.235
1.40
Electrical &
Electronic
Products
0
0.28
0
0.003
0.284
0.872
0.009
1 .051
0.117
0
0
0
0.125
0 . 006
3.581
0
0
0
0
0
25.00
-------
n
Table C3-V (Continued)
Industrial Wastewater Characteristics
Mechanical
Products:
Metal Finishing Captive
Pollutant
Silver (Aq)
Araenic (As)
Beryllium (Be)
Cadmium (Cd)
Total Chromium (Cr)
Copper (Cu)
Mercury (Hg)
Nickel (Ni)
Load (l»b)
Antimony (Sn)
Selenium (Se)
Thallium (Th)
Zinc
Un)
Cyanide (Cn)
Toxic Organ ica
1'est ic idea
HOD
TSS
Ainmon i a
???????? '{ '!
t'retreiitment Tech.
Job Shops
0.02
0
0
0.24
23.4
11
0
13
0.28
0
0
0
10
8.3
0
0
0
667
0
0
1.96
Shops
0.019
0
0
0.059
5.5
2.8
0
3.4
0.093
0
0
0
2.6
2.0
0
0
0
667
0
0
3.17
Inorganic
Explosive
Manufacturing Found ires
10.791 0.455
0
0
0
3.036
0
0.911
0
41.97 0
26.38 415.87
0
24.284
1.80
Cum
Wood Chemicals
0.0002
0.006
0
0.00003
0.079
0.310
0
0.045
0.021
0
0
0
0.521
0.004
1.053
0
981.18
153.6
0
376.17
—
Chemical
Mfg.
0.0001
0.0022
0
0.016
1.459
0.002
0.0002
0.0002
0.024
0
0
0
1.319
0.001
0
0
0
0
0
0
0
Iron &
Steel
0.6676
1.736
0
1.736
58.48
28.31
0
108.82
47.26
0
0
0
235.66
62.75
150.87
0
0
35782.3
0
17624.12
M.A.
Leather
Tanning
0
0
0
0.002
59.634
0.128
0
0.077
0.922
0
0
0
0.483
0.073
0
0.176
1439.91
2228.31
0
350.162
5.30
Cos t/$ 1000 gal
-------
o
Table C3-V (Continued)
Industrial Wastewater Characteristics
Pollutant
Silver (Aq)
Arsenic (As)
lleryllium (lie)
Cadmium (Cd)
Total
Chromium (Cr)
Copper (Cu)
Mercury (llg)
Nickel (Ni.)
Lead (Pb)
Antimony (Sn)
Selenium (Se)
Thallium (Th)
Zinc (Zn)
Cyanide (Cn)
Toxic Orgnnics
Pesticides
1101)
TSS
Ammonia
? ? V ???????
Pro treat me nt
Organic
Non-Porous Ore Mining Chem.
Metal & Dressing Mfg.
0.702
3.026
0
0.382
0.36
1.038
0.008
1.042
2.345
0
0
0
10.314
0.017
0.081
0
0
130.758
0
2.477
7.90
0.0007
0.001
0
0.017
0.054
0.280
0.001
0.011
0.036
0
0
0
0.201
0.096
1347.83
0
39.385
55.138
0
0
1.30
Paint &
Ink
Formulat ing
0
0.03
0
0.316
0.536
1.956
0. 139
0.133
0.757
0
0
0
75.729
0.631
25.243
0
5301.022
631.741
0
1454.704
34 . 00
Pesticides
0.0005
0.0042
0
0.0008
0.0101
0.6641
0.0002
0.1199
0.008
0
0
0
0.6641
0.7563
22.1361
0
0
0
0
0
1 2 . 00
Pe t r o 1 e um Pli nvma c eu t i c a 1
Refining Mfg.
0
0.0179
0
0
1.0597
0.0199
0.009
0.0019
0.0179
0
0
0
0.5298
2.517
13.345
0
100.67
90.736
0
84.770
—
0
0
0
0
0.0147
0.0184
0.0005
0.0262
0.0110
0
0
0
0.0918
0.0314
0
0
203.45
124.46
0
0
—
Photographic
Equip. & Supplies
1,0569
0.0476
0
0.6961
0. 1679
0.1894
0.0178
0.0021
0.2055
0
0
0
1.267
0.3522
0. 1744
0
969.51
356.29
0
14.099
—
Tech. Cost/
1000 n.-il
-------
Table C3-V (Continued)
Industrial Wastewater Characteristics
Pollutant
Silver (Aq)
Arsenic (Aa)
Beryllium (Be)
Cudmium (Cd)
Total Chromium (Cr
Copper (Cu)
Mercury (llg)
Nickel (Ni)
0 Lead (Pb)
£j Antimony (Sn)
*" {Selenium (Se)
Tl id Ilium (Tit)
?.lnc (Zn)
Cyanide (Cn)
Toxic Organics
I'tiat ic ides
BOD
TSS
Ammo n in
??????????
Prutrentment Tech.
Plastic &
Synthetics
0.0007
0.001
0
0.017
) 0.054
0.280
0.001
0.011
0.036
0
0
0
0.201
0.096
134.783
0
39.385
55.138
0
0
$1.30
Plastic Procelain
Processing Enameling
0 '
2.659
0
4.987
2.581
265.961
0
60.944
77.572
0
0
0
169.55
0
0
0
0
20501.16
0
199.471
$59.00
Pulp
Printing
Publ ishing
0.2616
0
0
0 . 2834
0.5014
0.4578
0.0087
0.02
0.2115
0
0
0
0.3270
0.2398
1 . 548
0
0
0
0
0
—
Paper &
Fiberboard Kubber
0
0
0
0
0.0444
0.0444
0
0.0134
0.0987
0
0
0
2.539
0.0233
0.705
0
359.712
543.095
0
0
$0.034
Soaps
Detergents
0.0297
0.0015
0
0
0.0063
0.0073
0.0011
0.00284
0.02359
0
0
0
0.3571
0.0050
0.1999
0
0
0
0
0
—
Steam
1! lee trie
Power Generation
0.0274
0.0899
0
0.0115
0.0205
0.0399
0
0.0475
0.0525
0
0
0
0.2048
0.0227
0
0
0
32.47
0
0
—
COM t$/ 1000 gal.
-------
Table C3-V (Continued)
Industrial Waatewater Characteristics
Pollutant
Silver (Aq)
Arsenic (As)
lk:ry Ilium (Be)
Cadmium (Cd)
Total Chromium (Cr)
Copper (Cu)
Mercury (lly)
Nickel (Ni)
Lead (I'b)
o Antimony (Hn)
^ Selenium (Se)
01 Thallium (Th)
Zinc ('in)
Cyanide (Cn)
Toxic Organics
Peal; ic ideu
1501)
TSS
Ammonia
??????????
Pre treatment Tech.
Textile
0.0154
0.0136
0
0.0016
0.1231
0.3079
0.00019
0.0502
0.0308
0
0
0
0.4051
0.0123
17.013
0
307.862
108.562
0
68.054
$2.60
Non-categorical.
Timber Industries
0
0.0014
0
0
0.0384
0.0041
0
0.0007
0.0004
0
0
0
0.2542
0
2.1583
_
110.312 1644
767.386 650
0 0
1.0551 0 .
—
Coat/$lOO
-------
7. Data for non-categorical industries wera included in the model, and
were treated exactly as any other categorical industry. Industrial flow data
and effluent characteristics were taken from a composite of various food
industry subcategories studied by EPA, and account for much of the
noncategorical industry flow. Hereafter, noncategorical industries will be
used in place of rubber manufacturing, and will be considered one of the 34
groups. This adjustment is necessary to account for the significant amount of
industrial flow that does not contribute a substantial amount of priority
pollutants.
8. The most accurate measure of an individual POTW's industrial flow was
judged to be the flow reported in the Needs Survey. Therefore, the calculated
industrial flow from Step 7 was adjusted or "normalized" to the reported flow
by the following ratio:
where
IF = Industrial flow
RI? = Reported industrial flow (Needs Survey)
GIF = Calculated industrial flow
i * Categorical industry i
Where no industrial flow was reported on the Needs Survey, no adjustment was
made unless the calculated industrial flow exceeded 50% of tha total POTW
flow. In that case, the reported total industrial flow was set equal to 25%
of the POTW total flow (the median industrial flow of all plants reporting
some industrial flow) and the individual categorical flows were adjusted
accordingly).
C-36
-------
The following is a measure of how the normalization procedure actually
worked (based on 1607 POTWs):
o At 300 FOTWs the calculated industrial flow was lower than the
reported flow; and subsequently the categorical industrial flows were
adjusted upwards.
o At 300 POTWs the calculated industrial flow was higher than the
reported industrial flow; the categorical industrial flows were
adjusted downwards.
0 At 200 POTWs that did not report industrial flow, the calculated
industrial flow was below 50% of the POTW flow and was unadjusted.
o At 100 POTWs that did not report industrial flow, the calculated
industrial flow exceed 50% of the POTW flow and consequently was
normalized to 25% of the POTW flow.
o At 200 POTWs that did not report industrial flow, the calculated
industrial flow was also 0, and was not further adjusted.
Overall, these figures imply that the adjusted D&3 counts and the EGD
data resulted in slightly lower industrial flow projections than those
actually reported by POTWs. This may have occurred because the reported
industrial flows or the Needs Survey for some POTWs include commercial flows
or industrial flows not covered by the SIC definitions for the 34 industries.
However, the flow normalization schemes should account for these
discrepancies.
9. A baseline concentration of toxic pollutants to account for domestic
and commercial contribution was added to the industrial concentration from
Step 8. The baseline concentration was calculated from two sources (the EPA
LQ POTW Study and EPA 4 City Study). Thase data sources were described in
Appendix C.2. A summary of these concentrations is presented in Table C3-VI.
10. The total mass of toxic pollutants was calculated from the industrial
component (normalized industrial flow and EGD concentration) and domestic
component (nonindustrial flow and baseline concentration). Where pretreatment
options were in effect only the industrial component was considered
controllable.
C-37
-------
TASLE C3-VI
Priorty Pollutant Baseline Concentrations
Pollutant Concentration (ms/1)
Silver (Ag) 0.005
Arsenic (As) 0.003
Beryllium (Be) 0.0
Cadmium (Cd) 0.003
Total Chromium (Cr) 0.05
Copper (Cu) 0.061
Mercury (Hg) 0.0003
Nickel (Ni) 0.021
Lead (?b) 0.049
Antimony (Sn) 0.001
Selenium (Se) 0.0
Thallium (Th) 0.0
Zinc (Zn) 0.175
Cyanide (Cn) 0.041
Total Metals 0.3683
C-3S
-------
11. The removals chat would be achieved by the pretreatment option to
complete categorical standards were developed by EPA for each categorical
industry, and were reported for all metal priority pollutants and the total
organic priority pollutants. Since not every industry has developed guide-
lines or effluent limitations, sons of these removals were estimates of what
technology similar to "BAT" would achieve. The removals used in the model for
each industry for each pollutant are listed in the Table C3-VII.
12. The projected POTW influent was calculated by summing the total
pollutant loading (Step 10) under the appropriate industrial pretreatnent
option and allocating this load to the total POTW flow. This projected
influent concentration was displayed for each POTW on its suicaary sheet, and
the average of all POTWs was displayed on the Model aggregate summary sheet.
A discussion of these results and their meaning appears in Appendix C-4.
Calculation of Industrial Sludge Quantity and Quality
The pretreatment of industrial wastes has a wide variety of technologies
available with highly variable costs and sludge generation rates. Because the
actual technologies assumed were not available from the EGD data, some
assumptions were necessary for this component of the model. Pretreatment
technology costs were provided only as the national total cost. To be able to
relate this figure to the "normalized" industrial flow (which adjusts the flow
from each categorical industry but not the count of plants) the total
national cost was divided by the total flow for that industry to arrive at a
cost per gallon. This cost was used by the model to compute the cost for each
category at each POTW. In reality, small lUs are likely to have a higher cost
per gallon treated than large Ills. However, for POTWs that have a number of
lUs in each category, the cost per gallon should be correct within a
reasonable limit of error. The aggregated cost for pretreatment from the
model will be compared to EGD predictions in Appendix C-4.
Sludge disposal rates for industrial pretreatment technologies also vary
signficantly. Seme neutralization and chemical treatment methods will
generate several pounds of sludge for each pound of suspended solids removed
>39
-------
Table C3-VII
Level of Removal 3y Modal POTW
Removal in Percentage
Pollutant
BOD
TSS
Silver (Ag)
Arsenic (As)
Beryllium (Be)
Cadmium (Cd)
Total Chromium (Cr)
Copper (Cu)
Mercury (Hg)
Hickel (Ni)
Lead (?b)
Antimony (Sn)
Selenium (Se)
Thallium (Th)
Zinc
Cyanide (Cn)
Toxic Organic s
Pesticides
Primary
Treatment
35
msg.
20
0
0
27
34
19
12
17
48
0
0
0
31
14
35
0
Secondary
Treatment
70
0
0
50
71
82
51
32
57
60
0
0
76
59
79
0
Tertiary
Treatment
70
0
0
50
79
S2
63
39
57
60
0
0
79
59
86
0
C-40
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while other technologies will generate substantially less. Since the
pretreatment technologies used were unknown, we assumed that two pounds of
sludge would be generated for each pound of toxic r?.eca.l removed, while TGS
removed would generate sludge on a pound for pound basis. All industrial
sludges from the categorical industries vere assumed to be hazardous, with a
disposal cost of $400 per con of dry solids (including transportation).
The concentration of toxic pollutants in industrial sludges was also
displayed by the model. These concentrations were computed by allocating the
toxic pollutants removed by pretreatment to the total quantity of industrial
sludge. The removals were the sane as those described in C3-VII Step 11.
POTW MODULE
The majority of the POTW effluent quality, sludge quality, and receiving
stream impacts are all based on the influent to the POTW. The influent for
each POTW is a calculated average, as has been detailed. The remaining
calculations in the POTW nodule include:
- POTW effluent quality
- Impact of POTW effluent on Stream Quality
- POTW sludge quantity/quality
- Emission of volatile toxic pollutants to the atmosphere
- Pretreataent program development and implementation costs.
POTW Effluent Quality
The POTW effluent quality was computed by applying an assumed removal for
each pollutant to the influent concentration. This removal was developed from
the EGD 40 POTW study, and was the median removal from all plants. Removals
for tertiary plants were developed from 9 of the 40 POTWs where a variety of
advanced waste treatment processes were sampled. Although the 40 POTW study
collected samples of primary effluent at a number of secondary POTWs, this
data was judged to be nonrepresentative of primary plants due to the influence
of recycle lines. Primary effluent data was consequently based on one of the
40 POTWs in which the primary system was unaffected by recycle lines. For
Ci ^
-*i
-------
most pollutants primary treatment was estimated to achieve approximately 35%
removal. Secondary effluent generally removed 70-80% of most toxic pollutants
while tertiary effluent removed 70-90%. The actual removal rates used in the
model are indicated on Table C3-VII. The POTW effluent is displayed on each
POTW's summary sheet, and is averaged for display on the aggregate output.
The changes in effluent quality under various pretreatment options is one of
the primary purposes of the modal, and is discussed in the following section
and in Appendix C-4.
Impact of POTW Effluent on Stream Quality
One of the measurements of pretreatment effectiveness is the net change
in stream quality that would be achieved by a pretreatment strategy. The
computer model developed data to assess these impacts by two methods:
1. The calculated incremental concentration change in the receiving
stream contributed by the POTW.
2. The comparison of that incremental concentration to national water
quality criteria.
The incremental concentration was computed by dividing the POTW effluent
concentration by the dilution ratio for the receiving stream. The dilution
ratio was defined as the upstream receiving water flow plus the POTW flow
divided by the POTT'? flow. The stream flows used were the average flows
obtained for STORET and USGS records. However, flows from only 703 streams
identified from the 2000 POTWs were available at this writing. Therefore,
data related to water quality were calculated on this reduced database and
scaled up to represent the universe of POTWs. The number of PQTWs with stream
flows was further reduced because some of the 2000 POTWs were reported (by the
Needs Survey) to have no flow and consequently were not used in the model.
The final number of POTWs for which we identified both the POTW flow and the
corresponding stream flow was 665. These POTWs formed the basis for
calculating water quality impacts.
C-42
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The most precise neasure of how pratreatment will impact water quality is
the net change in toxic pollutant concentration (and mass) in the receiving
stream under various pretreatment options. The computer model indicates these
figures on a plant-by-plant basis and as an average of all plants on the
aggregation nodal. Thesa results are evaluated in Appendix C-4, and have been
presented in the following section.
Although the above net changes are fairly accurate measures of water
quality impacts, they require interpretation to determine whether the
concentrations of any one toxic pollutant are signficant. JR3 approached this
task by comparing these concentrations to:
o The national water quality criteria for aquatic life (chronic toxicity)
o recommended criteria for human health.
Tb.e values and references for these criteria are listed in Table C3-VIII.
The results of the comparison are presented in Appendix C-4. Two limitations
should be noted, however, on use of Federal water quality criteria. One is
that these criteria are not standards, and only serve as a measurement tool.
Secondly, many of these criteria values are sufficiently low that any assumed
concentration of that pollutant will trigger exceedenca in any POTW with a lew
or, moderate dilution ratio. The term exceedence is used throughout this
report to indicate a predicted water quality concentration in excess of the
national water quality criteria. Specifically, the aquatic standard for
cadmium is 25 ng/1. Cadmium cannot be measured at levels below 1 ug/1 by
conventional atomic absorption (AA) or inductively coupled arc plasma (ICAP)
procedures. Therefore, the number of cadmium exceedences is not very
sensitive to the level of pretreatment in place. This insensitivity to
pretreatinent extends to the human health criteria for arsenic and to the
aquatic criteria for arsenic. Other pollutants which have higher (and
measurable) criteria values are more sensitive to industrial pretreatment
levels, although the overall number of exceedences is smaller. These results
are discussed in Appendix C-4.
-------
Table C3-VIII
Receiving Stream Water Quality Criteria
Freshwater Human Health
Pollutant Aquatic Life (ug/1) Criteria (ug/1)
Silver Uq) OTTZ515
Arsenic (As) 440 0.0022
Beryllium (Be) 5.3 0.037
Gadaiua (Cd) 0.025 10
Total Chromium (Cr) 44 1700
Copper (Ca) 5.6 1000
Mercury (Hq) 0.2 0.144
Nickel (Ni) 96 13.4
Lead (Pb) 3.8 50
Antimony (Sn) 1600 146
Selenium (Se) 35 10
Thallium (Th) 40 13
Zinc (Zn) 47 5000
Cyanide (Cn) 3.5 200
C-44
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?OTW Sludge Qualitv/Quantitv
Another major benefit of industrial pretreatment is the improvement in
sludge quality that will result .ron such a program. TVie model assessed
sludge quality improvement by predicting ?OTW sludge quality for each
pretreatment option. POTW sludge quantity from domestic and cotnmerical
sources was predicted from literature sources as follows (1):
Primary Plants: Dry tons/day = 0.625 x POTW flow in MGD
Secondary Plants: Dry tons/day = 1.17 x POTW flow in MGD
Tertiary Plants: Dry tons/day = 1.39 x POTW flow in MGD
Sludge solids were then increased by the total solids contributed by
industrial flow under the option in effect. Sludge quality was computed by
distributing the toxic pollutants removed by the POTW into the total POTW
sludge, on a dry weight basis. Tha removal rates used were the same as those
presented in Table C3-VII. (Metcalf and Eddy, 1972.)
POTW sludge was assumed to always be non-hazardous and sludge disposal
costs were based solely on the sludge disposal methods used by the POTW (from
the Needs Survey). The following costs were applied to all municipal sludge:
Disposal Method . Assumed Cost
Ocean Dumping $30/ton of dry solids
Land Spreading $60/ton of dry solids
Landfill S80/ton of dry solids
Incineration $150/ton of dry solids
The costs include transportation, and were supplied by EPA's Office of
Solid Waste. One important assumption implied in this data is that POTW
sludge disposal costs are not affected by the level of toxic pollutants
prasent. In actuality, some POTWs that have chosen an expensive disposal
option, such as incineration, nay have been driven inpart by sludge quality
problems that prohibited less costly options such as application to cropland,
(O'rarrell, 1931), The magnitude of this assumption will be discussed in
Aopendix C-4.
C-45
-------
The sludga disposal method used by each POTW was obtained from the Needs
Survey (Question 32). If a POTV did net indicate any disposal method, we
assumad that land fill ing was employed. The Needs Survey cid not require ?07~v?
that used multiple disposal methods to report the amount of sludge related to
each method. Consequently, JR3 assumed that POTWs using multiple disposal
methods divided their sludge equally among them.
The assumption that POTW sludge disposal costs are not affected by toxic
pollutant concentration has a serious impact on the entire cost benefit
structure of the RIA. Throughout the RIAj POTW sludges have been assumed to be
non-hazardous while industrial pretreatment sludges have been assumed to be
hazardous. The non-hazardous disposal costs are 3 to 11 time less expensive
than hazardous costs, according to EPA estimates. Consequently, a unit of
toxic pollutant removed by pretreatment at an industrial site incurs both the
cost of removal by the treatment system and the cost of disposal as a
hazardous waste. Under the option of no pretreatment, where the tonic
pollutant is discharged to the POTW, no cost of industrial pretreatment is
incurred, and dilution with domestic sludge permits its disposal as a
non-hazardous waste and at much lower unit cost. There is no corresponding
cost reported for the contamination of the POTW sludge. This assumption has s.
strong effect of skewing the cost benefit analysis towards the option of nor.
pretreatment, in essence using the dilution effects of domestic sewage. Data
from primary plants was not readily available, and was taken from a
combination of the 40 POTW study, where applicable, and literature sources.
For most pollutants primary treatment achieved approximately 25% removal,
secondary 70-80%, and tertiary 70-90%. The actual values used are indicated
on Table C3-VII.
C-46
-------
Enission of Volatile Priority Pollutants to the Atmosphere
One effect of the discharge of volatile priority pollutants to POTWs by
industry is their volatilization and subsequent discharge to the atmosphare.
The modal does not assess the enviror.aer.tal effect of this, but reports the
total mass discharge under each option. The assumptions for this calculation
are:
o 90% of the toxic organics received by the POTW are volatile
o 80% of the volatile pollutants are removed by the POTW with 20«
passing through)
o 90% of the volatiles removed by POTW are released to the atmosphere.
Pretreatment Program Development and Implementation Costs
JRB developed two estimates of pretreatment program costs. The first
based on engineering estimates by individuals experienced in developing
pretreatment programs and the second based on a statistical analysis of costs
reported by cities who have implemented programs. These two estimates are
presented below:
1. Engineering Estimates of POTW Pretreatment Development and
Implementation Cost
The following cost estimates have been developed based on an approach
option for a POTW to control nondomestic discharges to the POTW system. This
option meets the requirements of 40 CFR 403 and is also reasonable and
functional at the local level. In developing these estimates, actual program
experience was used and a number of assumptions have been made and will be
presented below.
The POTW pretreatment program cost estimates developed cover two inter-
related activities: Figure C3-2 - development of a local program; and Figure
C3-3 - implementation of the local program. In both estimates, the size of
the POTW was broken into 4 general size ranges. These size ranges were
compared to 3 relative ranges of nondomestic dischargers to the POTW. Each
nondomestic discharger range is comprised of a combination of categorical and
noncategorical users.
C-47
-------
FTfillHR C.'\~2.
ESTIHArt'O POTU PUCHttAIHrNT PROGRAM OFVELOPHCNf COSTS
o
I
Co
"•" -.UIIMIICH
sm * ---,.„,
(II ~---Hls
I.'OIM I".
PO m !> mil)
; S III < 10 Catoiiorlcal Imlustrlos
III fhHicAteqorlcal Inilustrtes
Item l.ilmr lion -labor Costs
1 1,429 100 1,52<>
2 l,fl«l 200 2.ini
3 3,601 100 3,701
4 2,744 400 3.144
5 - 4.000 4.000
6 r4,!iS5
Hem l.dlior llon-l dlmr Costs
1 l,7l!i ?00 1.915
2 2,1109 300 3,109
3 3,601 200 3./IOI
4 6,064 miO 6,1)64
0 - 4,000 4,000
6 19.6'n9
Hum Idlior Non-1 .ilmr Costs
1 2,l)')ll 300 3,1511
2 4.321 000 5,121
3 3,601 200 3,ft01
4 15,216 1,000 16,216
D - 26,000 26,000
6 M.J'lC
Item lalnit Nun-l.iilior Costs
1 3.573 400 3,9/3
2 3.000 1, 600 5.21)0
3 2,900 200 3,100
4 11.760 1,200 12,960
!i - 2 ft. 000 26,000
6 51,? It
III1 10 Catoiiorlcal Industries
IM ' IS Mnncat.R'iorlcal Industries
II em Idlior tlou-I.Almr Costs
114.556
i
Item 1 alior Non-1 ahor Costs
1 1,715 200 1,915
2 4,141 1,200 VM1
3 7.202 200 7,40?
4 6,064 000 6.1164
5 - tt.ooo ii.nno
6 ?')', !l22"
Item Idlior Non-1 .ilior Costs
1 2.H5H 3011 3,1 Ml
2 !i.!.H2 1,600 7. 1112
3 7.202 200 ;,4II2
4 15,216 1.0(10 Hi. 216
5 - 30,000 30,000
6 61, 'Milt
Hem l.ilior llon-l iilxir Cost s
1 3,573 400 3,973
2 4,300 3,200 /.SOU
3 4.000 200 4,200
4 11,760 1,200 12, %0
i> - 30,0(10 10,000
6 '•!.,;''•'
tuui
3 - I nijinterim)
4 - AiliiilrilstrAtloii/IYo
-------
B C3-3.
I'OTW ItiErRF/UMFNI ('HOOKAH IMPLLMF.HfATION COSTS
•\NIIMIH;K " '
sur\QF
or ^MUS
I'OIM
•01U < 5 ICil)
• 5 iic.i) i-oivi -25 MOO
•25 »GI» I'OfU <6UMCI
I'D IU .-? 50 lir,l)
IM/.5 Caleflorlral Inrlnstrlos
III! 10 Noiicat.cijoHcril Industries
>
Itom labor Non-labor Hosts
1 300 100 100
2 4.000 5,500 10.300
3 620 100 720
4 7,6110 100 7,7(1(1
5 li),200
Kent Labor Hon-labor Costs
1 ISO 100 550
2 4.IMO 5,500 10,300
3 3,41.6 100 3,556
1 7,6(10 100 7.700
5 22YIW
Item Labor Han-labor Costs
1 f>00 100 700
2 1,800 5.500 10,300
3 6,912 100 7,012
4 7,6HO 100 7,7(10
5 21,79*
Item Labor Hon -Labor Costs
1 750 100 «50
2 2,560 5,500 8,060
3 7,6(10 200 7, MOO
4 4.000 100 4,«JOO
5 21,690
> 5 III <10 Catniiorlcal Industries
III i 15 Hunt: dteanr leal Industrlns
Itnin Lnbor Non-Labor Costs
1 300 - 300
2 10,000 10,300 20.300
3 1.I4J 100 1.243
4 14.01C. 200 11,216
5 1?;i.lQ
Item tabor Non-Labor Costs
1 450 100 550
2 10,000 10,300 20,3(10
3 3.156 100 3.556
4 14,016 200 14,216
5 1fi,?0?
Itom Labor Hon-Labor Costs
1 600 JOO 700
2 10,000 10,300 20.3(10
3 10.3611 100 10.46(1
4 14.016 200 M.2I6
5 WJM
Item Labor Nun-LaUor Costs
1 750 100 «!iO
2 5.3/6 10,300 15,6/6
3 0,600 300 O.OOO
4 10, OHO 200 10,200
5 367706
Ill> 10 C,itn(|orlci]| Iii'liislries
|ll> 15 Miiiii:,il"i|<>ric,il Indus t.rli:s
$36.1:)')
Item Labor Mon-l.ahnr Custs
1 450 100 500
2 12,000 I?, 500 Zl.liOO
3 6,01? 100 7,012
4 14,400 400 14, ftOO
5 Jltf.ititf
Item Labor Non-Labor Costs
1 600 100 700
2 12,000 IP. 500 24.500
3 13.824 100 13,021
4 1 4. 400 4
-------
Major cost items include labor and nonlabor line items. Labor costs
include: legal, engineering, field and laboratory, and arrangement and
administration. Nonlabor costs include: equipment purchase, postage,
duplicating, notices, etc. The assumptions used to develop these cost
estimates are as follows.
General Assumptions:
These general assumptions are applicable to the development of both cost
estimates.
• Every POTW and their respective consultant has available for their use
and review all of the pretreatment program guidance documents prepared
under the OWE contract, (i.e., 304 (g) Guidance Docunent, Industrial
Residuals Manual, Procedures Manual, etc.)
• The Cost Estimates were developed for the normal type of POTW/IU
situation and are not intended to be directly applicable to the very
large or special POTWs (i.e., Chicago - MSD, Detroit, Los Angeles,
Passiac Valley (NJ), Chattanooga, etc.)
• Development costs are based on getting a reasonable program started
and during implementation the program can be fine tuned and expanded
as required. This trend is indicated by the deflated development
costs with somewhat higher than expected operating costs.
» 95% of all the POTWs in the U.S. are 10 MGD or less.
• Approximately 90-95% of all POTW programs will fall "within the first
two POTW ranges and the first two IU ranges.
» Labor Costs are estimated assuming that POTWs up to 50 MGD will use
consultants and POTWs greater than 50 MGD will use in-house
capabilities. The following rates were used and include overhead,
fringe benefits, etc.:
• Legal - Applies to all POTWs
- §42,000 per year » approx. $20/hour
• Consultants (Overhead 1.5)
• Engineering - $75,000/year « approx. $36/hour
• Field Crews - $34,000/year » approx. $30/hour
« Laboratory - $62,500/year " approx. S30/hour
• Admin/Mgmt - $75,000/year » approx. $36/hour
• POTW (Overhead 0.33)
• Engineering - $40,000/year = approx. 520/hour
• Field Crews - $34,000/year = approx. $15/hour
C-50
-------
o Laboratory - $34,000/year = approx. $15/hour
o Admin/Mgmt - $40,000/year = approx. S20/hour
o For POTWs < 5 MGD and within IU > 10 category, use previously
developed costs in row.
Development Assumptions:
These assumptions are applicable to the cost estimates for developing local
POTW pretreatment programs.
1. Legal Costs. Items here include: ordinance review, comparison with
the EPA Model Ordinance, drafting of modified POTW legal authority,
attending City Council meetings, etc. Tne costs presented are based
on the assumption that a single jurisdiction is involved. If
inter-jurisdictional questions have to be resolved, then legal costs
could be multiplied by a factor of 2.0 to 2.5.
2. Industrial (Nondomestic) Waste Surveys (IWS). IWS are assumed to be
updated by using as much of the existing data as possible and
performing a paper survey with none or limited sampling and
analytical efforts. The idea is to frane the program in and then
fine tune it as the monitoring and surveillance activities are
implemented.
The development costs included looking at potentially significant
noncategorical industries as well as the categorical industries. A
limited number of users will be looked .at via a waste questionnaire
with a fewer number actually being involved in the monitoring and
surveillance program to be implemented.
The cost estimate includes hours based on POTW size to create the
general user list and 3 hours per IU for the questionnaire.
The cost estimates are based on single service areas and if
jurisdictional conditions exist, the costs could be multiplied by a
factor of 1.5 to 2.0.
3. Engineering. This item is to include: technical input into the
ordinance review, standard setting, reviewing industrial compliance
schedules, etc. The cost estimate assumes that engineering is
primarily a function of the number of significant nondomestic
dischargers into the POTW with less impact due to size of the POTW.
Estimates were based on 3 hours per average number of lUs.
4. Administration/Program Submission. This item was assumed to be a
function of POTW size and complexity rather than number of users.
The activities include: treatment plant overview, development of
procedures, public participating, legal coordination, funding
procedures, and assembly of the submission packet. Nonlabor costs
include: printing, public notices, etc. In addition, POTW rates were
used to develoo contract services.
051
-------
5. Equipment. It is assumed that justified field and laboratory
equipment is included as a development cost. The laboratory cost
only includes the purchase of an AA ($22,000) for POTWs between 25-50
MGD with more than 5 categorical industries and all POTWs greater
than 50 MGD. Field equipment (including safety) was estimated to be
54,000 for all POTWs up to 10 categorical industries and $8,000 for
all POTWs with more than 10 categorical industries. It is also
assumed that organic analysis is not required.
Implementation Assumptions:
These assumptions apply to the cost estimate for implementing a local
POTW pretreatraent program.
1. Legal costs. Minimal legal costs are assumed as the normal operating
needs of a local program. Enforcement costs are assumed to be picked
up by fines and penalties levied on the IU in noncompliance.
2. Monitoring/Surveillance. It is assumed that smaller PQTWs use
in-house efforts to collect samples and use contract or regional
laboratories to perform'analysis. Demand monitoring and additional
sampling/analytical costs are to be recovered from the IU in
noncompliance and not assumed to be normal operating costs.
Laboratory costs for categorical industries are assumed to be related
to assuring validity of self-monitoring reports. Costs are based on
$400 per sample and approximately 2 random samplings per industry per
year. Laboratory costs for noncategorical industries are based on
$150 per sample with approximately 2 samples taken per year. Field
crew costs are based on 2 men per sampling event, spending 4 hours
per industrial user, twice a year. lUs were averaged to represent a
reasonable spread across industrial user ranges.
3. Engineering. Nominal engineering costs were assumed for the norm.
Review of new industry coming into town is hard to predict and is
considered as an add-on. Engineering efforts are used to update and
fine tune the local program. A range of effort from 1 day per
quarter for the small POTWs up to 6 days per month for the large POTW
with a heavy IU base was used.
4. Administration/Reports. These activities are assumed to include
review and quality assurance that the POTW program complies with the
resonsibilities detailed in the program submission. Approximately 3
hours per IU per sample per year was used as an estimate where
consultant efforts were used and 12 hours per IU per sample per year
was used as an estimate for POTWs 50 MGD. In addition, where
consultants were used, an additional 8 hours per month of POTW
administrative effort was included to cover contract management.
Nonlabor costs include: filing, duplicating, postage, etc.
C-52
-------
Statistical Analysis of Reported Local Pretreatment Program Costs
Regression analysis is one method of developing a quantitative model to
aid in predicting the cost associated with local pretreatment programs. For
the purposes of this analysis, the quantitive model generated relates changes
in the development and operating costs of a pretreatment program to the size
and level of industrial activity at the treatment facility.
Equations of the following form were estimated and tested for statistical
significance:
03X3 •*• e
where
c = dependent variable, pretreatment program development and
operating cost
b,, b- + b3 » the parameters of the relationship to be estimated
x. , x +• x = explanatory variables, i.e., size, and industrial activity
a = constant term
e • error term.
The explanatory variable size is defined in this analysis as the actual
flow of wastewater entering the treatment facility in millions of gallons per
day (aigd). The measure of industrial activity at the treatment facility
includes such variables as the percent of actual wastewater flow from
industrial sources, the number of industrial users serviced by a given POTW,
and the number of electroplaters and metal finishers discharging to a
treatment facility.
These explanatory variables were selected because they relate to the most
costly elements of development and operating a pretreatment program, i.e.,
industrial user survey, sampling and analysis, and manpower requirements.
These elements appear to be heavily influenced by the facility size and the
level of industrial activity at the facility. As the size/flow of a POTW
increases, it is likely to require additional manpower to maintain a workable
C-53
-------
pretreatment program. Similarly, higher levels of industrial activity are
liable to necessitate an increased level of effort in the the industrial
survey, and additional sampling and analysis requirements.
The regression analysis tests the strength of these relationships. If a
signficant portion of the fluctuation in the dependent variable can be
accounted for by the explanatory variables, then the resulting equation can be
used to predict pretreataent program costs to a given POTW.
Data Collection and Limitations
The basic sources of data for estimating the above variables are:
• phone contacts with POTW Industrial Waste Coordinators
• pretreatment programs submitted to EPA Headquarters for review and
approval
• 201 Construction Grant requests to fund the development cose of
pretreatment programs
• Needs Survey containing information on total and industrial flow at
various POTWs
• Dun i Bradstreet tapes listing the number of industrial users by SIC
code serviced at various POTWs.
Separate regression analyses are performed for the development and operating
costs. Only 14 observations are included in the operating cost analysis
due to the limited number of POTWs currently operating pretreatment programs.
Although this number is small, the wide range provided by the individual data
points strengthens the analysis.
Of the 14 POTWs in the operating cost analysis, eleven are currently
operating pretreatment programs. Of these eleven POTWs, two have received EPA
approval, four are currently awaiting EPA approval, and five are at various
stages of the review process. The operating cost figures were obtained
primarily from phone contacts with the POTW Industrial Waste Division, while
data on the explanatory variables were taken from the Needs Survey and Dun &
Bradstreet tapes.
C-54
-------
The pretreatiaent program development cost analysis is based on a total of
54 observations. The development cost information was extracted from various
POTW construction grant applications provided by EPA regional pretreatment
coordinators. The data for the explanatory variables were derived from the
Needs Survey and Dun & Bradstreet tapes and then matched with the POTW grant
requests.
Only POTWs with an actual flow of less than 150 mgd are included in the
development cost analysis. This cutoff point was chosen because the costs
observed for large (> 150 tngd) POTW pretreatment programs were considered to
be heavily dependent on specific site factors. Inclusion of these outliers
would exert upward pressure on the regression results and therefore introduce
a distinct bias on the smaller plants in the model. The development cost for
large POTWs (> 150 aigd) is estimated on a case-by-case basis and is presented
in Section III of the report. In an attempt to identify a spectrum for
development costs, individual regressions were performed for the states of New
Jersey and California.
Results
A number of regression analyses were performed in an attempt to account
for the fluctuation in the development and operating cost data in the sample
POTW population. These regression results are presented in Tables C3-IX
through C3-XI. The separate analyses conducted for the development and
operating costs are discussed in the following two sections.
Develooment Cost Model
After testing several functional forms and different explanatory vari-
ables, Equation 8 in Table C3-IX was selected for use as the pretreatment
development cost predictor. In this equation, both the actual flow in mgd and
the constant term are statistically signficant. The explanatory variable
measuring the percent flow from industrial sources is of questionable
significance. This equation was selected as a predictor of development cost
to avoid data inconsistencies. All of the other equations required a mix of
data bases and therefore lowered confidence in those equations as predictors.
The logarithmic functional form was selected under the assumption that the
size of POTWs is logarithmically distributed.
C-55
-------
TABLE C3-IX DEVELOPMENT COST REGRESSION EQUATIONS
Equation Dependent Functional
Number Variable Ford
Development
1 J'y (000) linear
Development
2 $'« (000) log
Development
3 $'« (000) linear
Ul
cr- Development
4 $'« (000) log
Development
5 $'a (000) linear
Duvelo|iaiunt
6 $'B (000) log
Development
7 $'a (000) linear
Dewe 1 opine nt
8 $'s (000) log
Actual
Flou
2.51
(2.39 )
.54
(4.71 )
2.61
(2.43 )
.51
(4.25 )
2.55
(2.32 )
.54
(4.79 )
3.75
(5.02 )
.489
(6.02 )
Z Induatrlal Z Electroplatera
Flou 1 Hetal Flnlshora
\
\
1 1
.976 -2.29
(1.13 ) (- .58 )
.097 .104
(1.08 ) ( .61 )
.66
( .82 )
.083
(1.05 )
Number of
Induatrlal
User*
- .51
(-1.77 )
- .064
(- .38 )
- .59
(-1.82 )
- .003
( .02 )
.158
( 1.41.)
- .062
(- .54 )
Huuber of
Electroplatera 6
Metal Plnlahera
9.23
( 2.49
.003
( .02 )
10.39
( 2.50 )
- .009
(- .44 )
Degrees of
Conatant Freedom
49.84
( 2.46) 53
3.18
( 6.65) 53
41.03
( 1.21) 53
2.75
( 4.47) 53
41.75
( 1.99) 53
3.18
( 8.77) 53
34.9
( 1.37) 57
2.91
(12.43) 57
Coefficient of
Deturnlnatlon
R2
.41
.41
.43
.43
.34
.42
.31
.42
Standard
Error
121.5
.87
121.6
.87
127.5
.86
127.99
.85
-------
£<|tiat Ion
Hunlier
1
(C.llf.)
(Calif.)
(H.J.)
4
(N.J.)
5
(Calif.)
6
(Calif.)
7
0 (M.J.)
Ul
8
(H.J.)
9
(C.llf.)
10
(C.llf.)
11
(M.J.)
12
(M.J.)
13
(C.llf.)
14
(C.llf.)
15
(H-J.)
16
(M.J.)
Dependent Functional
Variable For*
Development
$'a (000) linear
Development
$'. (000) log
Dcvaloiment
J'e (000) linear
Development
J'e (000) log
Development
J'e (000) linear
Develop* tint
J'e (000) log
Development
J'e (000) linear
Development
J'e (000) lug
Development
S'a (000) linear
Development
$'. (000) Ing
Development
J'a (000) linear
Development
$'i> (000) log
Development
$'a (000) linear
Development
J'a (000) log
Development
$'a (000) linear
Deve lopwent
S'a (000) log
A««».l Mu.b.r .r
(aig
-------
o
Ul
03
TABLE C3-XI ANNUAL OPERATING COST REGRESSION EQUATIONS
Actual . Number of Hunker of Coefficient of
F.<|iintlnn Dependent FunctInnnl Flou X Industrial { Electroplatera Intlustrlal Electrnplatera I Degree* of Determination Standard
NumliiT Vurlnlile
FnrM
Flow
• Metal Flnloliera Uaurs
Metal Flnlaliera Conatnnt Freedom
Error
Operating 2.04 2.3B
$'a (000) llnrnr (3.99 ) ( .49 )
-53.12
(- .27)
13
.60
295.9
Operating
$'s (000)
loll
.499
($.19 )
.126
( .56 )
2.87
II
.71
.535
Operating log- .005 .007
1 $'a (000) linear (5.37 ) ( .83 )
4.44
( 12.62)
13
.70
.521
-------
Entering the actual flow (mgd) and the percent of that flow from
industrial sources for a given POTW into Equation 8, will yield an estimate of
the cost of developing a pretreatinent program at that POTW. Figure C3-4
presents the estimated cost for a sleeted portion of the sample POTWs plotted
against plant size. For example, a POTW receiving 45.2 mgd, 44 percent of
which is from industrial users, will incur an estimated $162,000 in
pretreataient development costs.
In addition to estimating a development cost equation for all 58 sample
POTWs, similar regressions were performed separately far those POTWs located
in New Jersey and California. The resulting equations are presented in Table
C3-X. For the reasons noted above, and in order to maintain consistency
between models, Equations 14 and 16 were selected as development cost
predictors. These States were singled out under the assumption that the State
of California is currently under more stringent State requirements and will
yield more conservative cost estimates than the more loosely controlled state
of New Jersey. The result of this regional analysis is presented in Figure
C3-5. These State regression lines appear to confirm this assumption and
provide an upper and lower bounding estimate of pretreatinent development costs
based on actual flow and percent of industrial flow.
Operating Costs
The fluctuation observed in annual POTW pretreatment program operating
cost was regressed against actual flow and percent industrial flow. The
results of these equations are presented in Table C3-XI. Equation 2 was
selected as a predictor of POTW operating costs based on the strength of the
coefficient of determination (R2). This coefficient shows 71 percent of the
observed fluctuation in operating cost explained by Equation 2. Both the
constant term and the explanatory variable size (actual flow, mgd) are
statistically significant.
Figure C3-6 presents these operating cost estimates plotted against plant
size. For example, a POTW with an actual flow rate of 156 ngd, with 11
percent flow from industrial sources, will incur $301,000 annually in
pretreatment operating expenses.
C-59
-------
500
c *
(Qt s
440 •
430
400
3*0
xo
340
330
300
290
260
240
230
20O
1*3
160
140
120
100
80
M
FIGITRK C3-4.
DEVELOPMENT COST ESTIMATES
« 13 IS 34 »
43 « S4 SO « 73 7« 84 90 9« M2 ia« U4
piant size (mgd)
C-60
-------
FIGURE C3-5.
REGIONAL DEVELOPMENT COST ESTIMATES
•
9
0°
6 13 1M 24 30 X 43 «« S« 60 « 72 7« M SO 96 102 108
« - NJ. POTWs plant size (mgd)
• « CALJF POTWs
C-61
-------
FIGURE C3-6.
ANNUAL OPERATING COST ESTIMATES
Or '**)
.•1 •
in 200 225 ISO 275 300 US 3SO 175 40O US 450
>> SO 75 100 US ISO — _
C-62
-------
To provide an upper and lower bound estimate of annual operating costs, a
95 percent confidence interval analysis was conducted for Equation 2. The
results of this confidence interval are presented in Figure C3-7. The black
line represents the annual operating cost estimates obtained from Equation 2,
the green line indicates the 95 percent upper bound limit, and the red line
shows the 95 percent lower bound limits.
C-63
-------
250- •
a- •
200- •
ISO- •
M- •
(• a'.tt
FIGURE C3-7.
ANNUAL OPERATING COST ESTIMATES
95 PERCENT CONFIDENCE INTERVAL
"-S--
MO- •
If -
550- -
5- •
300- •
15- -
~~0- •
4ZS- •
,0- .
ITS- •
;a- -
325- -
•
e
M » " WO 125 130 ITS 2OO 225 250 275 »0 MS 3SO ITS 400 425 450 475
• ^ plant size (mgoO
0<5>" C-64
-------
C-4. MODEL OUTPUTS AND ANALYSIS
Some of the results of the computer model have been presented throughout
the RIA Report. This section presents the model outputs in detail and com-
pares them to other data obtained by EPA. This section follows the model
methodology as it is outlined in Appendix C-2 and discusses relative sensi-
tivity of model output to various input conditions.
COVERAGE OF THE MODEL
EPA has identified approximately 2,000 POTWs that are required to imple-
ment the General Pretreatment Regulations. The model outputs were based on
1,839 POTWs. The remaining POTWs did not report their flow on the NEEDS
Survey, and descriptive data was insufficient for inclusion in the modeling
runs. These 1,839 POTWs accounted for 19 billion gallons per day (BCD), out
of a total national POTW flow of 26 BCD. The 1,839 POTWs accounted for 38 BCD
of industrial flow, out of a projected total of 44 BCD for the nation.
Stream flow data was only available for the two primary data sources
(USGS and STORET) for 703 POTWs. Of these 703 streams, 665 matched the 1,839
POTWs. Therefore, the modeling runs reflect water quality data for 665 POTWs
and all other outputs for 1,839 POTWs.
.FLOW NORMALIZATION
As detailed in Section C-3, the model calculates the industrial flow for
each POTW based on the number of industrial users and model plant flows, and
normalizes to the reported POTW industrial flow. The initial pre-nonnalized
industrial flow calculated by the model was 3.4 BDG, subsequently normalized
to 3,8 BCD. Normalization, however adjusted some POTW's upwards and some
downwards. A measure of how the normalization worked:
o Approximately 50% of the POTW's were normalized upwards
o Approximately 20% of the POTW's were normalized downwards
o Approximately 12,52 of the POTW's, did not report industrial flow and
had a pre-normalized indusrial flow below 50% of the total POTW flow,
which was used unadjusted
C-65
-------
o Approximately 52 of the POTW's did not report industrial flow and had
pre-normalized industrial flow above 502 of the total POTW flow, which
was adjusted downward to 252 of the total flow
o Approximately 12.52 of the POTW's did not report industrial flow and
also had no calculated industrial flow. These POTW's were left
unadjusted.
This final group of POTW's represents on measure of the magnitude of
error either in the model or the selection of the POTW's required to install
pretreatment programs. In theory, virtually all of the POTW's covered by the
General Pretreatment Regulations should have some industrial flow.
INDUSTRIAL SLUDGE QUANTITY/QUALITY
The model projects that under full categorical standards, industries
would remove approximately 25,000 meric tons per year of toxic metals and
70,000 metric tons per year of toxic organic pollutants, which would accumu-
late in their sludge. The SGD (Effluent Guidelines Division) of EPA has
calculated that categorical industries generate 28,000 and 85,000 metric tons
per year of toxic metals and toxic organics per year respectively.
•
These numbers should compare well, because the EGD data was the basis for
the model plant characteristics which formed the basis for the model's
projections. Differences occur because the total EGD numbers were broken into
pounds per IU, which were adjusted, and flow normalized at the POTW level
prior to aggregation back to the total.
Industrial Sludge Quality is simply the total pounds of toxic materials
applied to an assumed total sludge quantity. There are no meaningful measure-
ments for comparison of these outputs.
POTW SLUDGE QUANTITY/QUALITY
The model predicts the POTW sludge quality under the options of no pre-
treatment in effect and under full categorical standards. These measurements
can be compared to a variety of independently measured results, such as the
40 POTW study and various case studies. For example, a comparison between
partial data from the 40 POTW Study (Table 3-5) and the model output, under
066
-------
the option of no pretreattnent beyond what is in place today compares as
follows:
40 POTW Study
Parameter Average Median Model Average
Cadmium 157 14 26
Chromium 730 422 831
Copper 894 553 563
Nickel 240 121 181
Zinc 2874 2167 923
Overall, the comparison between the two methods is good. The data from Table
3-5, however is based on only the first nine POTW's. When the average data
for all 40 POTW's is available a nore definitive comparison should be
available.
Another comparison between the model's projections and another
independent measurement is Che net change in sludge quality between the
options of no additional pretreatment and full categorical standards. The raw
data for this comparison has been prsented in Table 3-7, which is repeated on
the following page. The model's projections are compared against those case
studies where sludge measurements were available. Overall, the model is
extremely close to the actual measurements for every parameter except lead.
The model probably predicts a higher nonindustrial baseline concentration of
lead. The model probably predicts a higher non-industrial baseline concen-
tration of lead than was experienced in those cities used as case-studies.
POTW INFLUENT QUALITY
The calculation of a POTW influent may be the single most important model
output, because it forms the basis for prdicting the POTW effluent concen-
tration (and water quality effects), the amount of organic priority pollutants
volatilized (and air pollution effects) and the POTW sludge quality. The
influent is calculated by the model according to the procedure in Appendix
C-2, but is primarily based on the count of industries present in each POTW
city, the EGD characteristics for that industry mix and the flow normalization
C-67
-------
according to the Needs Survey. The model predicts the following as the
average influent for all 1839 POTW'S under the current in-place pretreataent
scenario.
Average
Parameter Concentration ( g/1)
Silver 15
Arsenic 6
Cadmium 16
Chromium 468
Copper 252
Mercury 0.9
Nickel 203
Lead 75
Antimony 1
Zinc 410
Total Metals 1450
Total Organics 1820
Consistent with previous EGD data on metal finisher and other industries,
chromium, copper, lead, nickel and zinc account for almost all of the total
metals.
Several EPA studies in recent years have collected information on toxic
pollutant concentrations in POTW influents. The most exhaustive study was the
40 POTW study, described in Appendix B-4 and C-2. On average the model
compares well with that study. The 40 POTW study measured an average total
metal concentration of approximately 1.5 mg/1 (compared to 1.4 mg/1) for the
model and a total toxic organic pollutant concentration of approximately 2
ug/1 (compared to 1.8 for the model).
C-68
-------
Under the option of full categorical standards the POTW influent toxic
pollutant concentration drops substantially. The following table presents
this data.
Average
Parameter Concentration (ug/1)
Silver 14
Arsenic 4
Cadmium 12
Chromium 89
Copper 103
Mercury 0.6
Nickel 52
Lead 60
Antimony 1.0
Zinc 210
Total Metals 546
Toxic Organics 550
One very significant coincident can be noted between the model outputs
and without pretreatment. Several of the parameters that are least controlled
by categorical standards have the lowest water quality criteria, and cause the
majority of violations. As an example, cadmium is projected by the model to
decrease 252 (from 16 g/1 to 12 g/1) in the POTW influent by the imposition
of categorical standards. This is a fairly small decrease, considering the
criteria value of 25 mg/1. Copper, which has a smaller number of initial
exceedences, is projected to decrease in POTW influent by 59% (from 252 g/1
to 103 g/1) under categorical standards, compared to its criteria value of
5.6 g/1. Arsenic and silver, which also have a high number of initial
exceedences are also not as sensitive (33Z and 62 reductions, respectively) to
pretreatraents as other parameters. Chromium (812), Nickel (752), and toxic
organics (702) are the pollutants most effectively reduced by categorical
standards. However, chromium and nickel have fairly high criteria values,
while no criteria exist for toxic organics as a group. These data anamolies
have an important effect on the failure of exceedences to show a significant
impact on the effects of categorical standards.
C-69
-------
POTW REMOVAL EFFICIENCY
The use of median POTW removal efficiencies from the 40 POTW study was
discussed in Appendix C-3, and the removal efficiencies used were indicatd in
Table C3-VII. The use of median removals based on well operated POTW's may
understate the number of exceedences by POTW's. Median removals will also
have an equalizing effect on all POTW streams, and remove the normal degree of
variation expected. Consequently, the number of initial exceedences by POTW's
is slightly sensitive to the removal levels used, but the difference in
exceedences between different pretreatnent options is not particularly
sensitive to the removal efficiency chosen.
POTW EFFLUENT RESULTS
The computation of the POTW effluent is straightforward calculation of
reducing the POTW influent by the appropriate removal efficiency (depending on
POTW level of treatment). The two previous tables listing influent concentra-
tion were reduced by the removal efficiencies as found in Appendix C-2 (see
also Feiler, 1980 and Southworth 1980). The results are indicated below:
Effluent Concentration Effluent Concentration
Parameter Current Conditions ( g/1) Categorical Standards ( g/1)
Silver
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Antimony
Zinc
Total Metals
Toxic Organics
Clearly since removal efficiencies are constant, influent and effluent
concentration change proportionately.
5.6
5.6
8.8
170
66
0.5
141
33
0.5
123
554
507
5.3
3.8
6.5
32
28
0.3
36
27
0.5
65
204
154
C-70
-------
EMISSION OF VOLATILE PRIORITY POLLUTANTS TO THE ATMOSPHERE
As indicated in Appendix C-3, a rough estimate of emissions of volatile
pollutants was made based on assumptions derived from the 40 POTW study. The
model projects that approximately 50,000 tons/year of organic pollutants
volatilize from the 1839 POTW's included. The model does not account for any
volatilization in the POTW collection system, and to our knowledge no large
scale study of this phenomenon has been completed by EPA.
WATER QUALITY EFFECTS
A significant objective of the model is to detail the water quality
impacts of categorical standards. The first measure used was comparing the
average incremental concenration from POTW's to the water quality criteria.
These results are presented below:
Parameter
Silver
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Cyanide
Aquatic ' Average Incremental
Criteria g/1 Concentration in Stream (
.12
440
.025
44
5.6
0.2
96
3.8
47
3.5
.15
.16
3.2
1.4
0.01
4.3
1.0
3.2
2.0
Percent of
2/1) Criteria
127
0.04
7
26
5
5
25
7
58
Cadmium, silver, and cyanide all consume a significant portion of the
allowable criteria.
Another measure used by the model to assess water quality criteria was
exceedences, which was defined to be an incremental stream concentration for
any pollutant contributed by a POTW that exceeded the National Water Quality
criteria. This measure, although useful, is limited in that the number of
exceedences is primarily driven by the dilution ratio of stream flow to POTW
C-71
-------
flow. Combined with the very low criteria for some pollutants, this caused
exceedences to be fairly insensitive to industrial flow characteristics. The
example below serves to illustrate the problems.
Cadmium has an adequate life chronic toxicity of 25 ng/1 (0.025 g/l).
The model projects predict cadmium contribution of 3 ug/1 from non-industrial
sources, of which 50% (1.5 g/l) will pass through a secondary POTW.
Consequently, any POTW with a dilution ratio of 60 to 1 or less will exceed
the cadmium limit, even if no industries are present. Pretreatment in any
cities in this dilution range will have no effect on causing the plant to
exceed the criteria.
Conversely, at POTW'S with very large stream dilution ratios even a large
industrial flow with no pretreatment may not cause a violation. Using
cadmium, a POTW with 102 of their flow from metal finishing operations would
expect their influent cadmium level to increase by 24 g/l, with 12 g/l
passing through the plant. Added to the 1.5 g/l effluent concentration from
non-industrial sources, an exceedence would be caused only if the dilution
ratio for that POTW was less than 540 to 1. Consequently for a significant
number of POTW's with small or large dilution ratios, the level of "pretreat-
ment has no effect on the number of exceedences. It has also been shown least
sensitive to catgorical standards.
To increase the sensitivity somewhat, the model also indicates POTW's
that exceed 50% and 25% of the water quality criteria. These numbers
implicitly assume that the POTW is not the only discharge on a stream, and set
the other sources of pollutant equal to the POTW concentrations or three times
the POTW concentrations arbitrarily. These results are presented in Section
3 of the main body of the report.
The model is much more sensitive to pretreatment options where it
predicts absolute values, such as POTW influent concentration, effluent con-
centration or sludge concentrations. These values are directly calculatd from
the input conditions and can be used to indicate the absolute and percentage
differences between pretreatment options.
C-72
-------
PRETREATMEJiT PROGRAM COSTS
The costs for developing and implementing a pretreatment program is
displayed by the model for both methdologies described in Appendix C-3. These
costs are presented below for the 1839 aggregated.
Method 1 Method 2
1) Development Costs $35,000,000 $ 91,000,000
2) Implementatoin Costs $51,000,000 $101,000,000
These figures are probably higher than would actually be incurred (in 1981
dollars) because
o They do not allow credit for programs already in place
o They do not account for programs partially complete
o These figures compute and add a cost for each POTW in cities with
multiple POTW's. The city in actuality would incur a cost lower than
the sum of all POTW's.
This pretreatment program cost is largely unaffected by the pretreatment
option chosen. Even where a POTW can waive certain groups of indusries or
only regulate a small number of industrial categories they would have to
complete most aspects of a pretreatment program.
INDUSTRIAL PRETREATMENT COSTS
The model prepares two industrial pretreatment related costs:
o the cost of pretreatment technology
o the cost of hazardous sludge disposal.
These costs are both shown to be zero today, which only shows the incremental
costs of categorical standards. The costs of complete categorical standards
are:
Pretreatment Technology - $1.3 billion
Industrial Sludge Disposal - 0.5 billion.
C-73
-------
These costs are based on EGD supplied data, and consequently approximate their
estimates of total compliance costs. The actual costs of pretreatment in
place today will be addressed in the following section.
BASELINE CONDITIONS
One key assumption of the modelling effort is that pretreatment in place
today would remain so under all options considered, so only the incremental
costs of additional industrial pretreatment was calculated. The rationale for
this assumption is that most pretreatment in place has been motivated for
other reasons than Federal intervention, and these motivations would continue
to exist regardless of the EPA regulatory option chosen. However, without
enforceable standards the potential for "backsliding" exists. Consequently
the model was used to indicate the net change that has occurred between
industrial raw waste loads (from EGD) with no pretreatment and th estimate of
.current industrial wasteloads used to simulate conditions today. The major
model outputs are summarized on Table C.4-I to C.4-IV.
Referring to Table C.4-I, the raw waste loads are estimated (by model)
average influent concentrations assuming that no industrial pretreatment were
being conducted at the present time. Conditions today are average influent
concentrations as they exist today based on an estimate of the current
pretreatment level. Categorical standards are estimates averaged from the
model assuming complete pretreatment and anticipated categorical standards.
The model was used subsequently to generate average effluent, sludge, and
stream concentrations as summarized in Tables C.4-II, III, and IV.
C-74
-------
C4-I
Summary of Model Outputs
POTW Influent Projections
( g/1)
Parameter
Silver
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Total Metals
Toxic Organics
Raw Waste
Loads
15
36
28
1250
693
1.0
638
361
853
3880
4100
Conditions
Today
15
6
16
468
252
0.9
203
75
410
1450
1820
Categorical
Standards
14
4
12
89
103
0.6
52
60
211
546
550
C-75
-------
C4-II
Summary of Model Outputs
POTW Effluent Projections
( g/D
Parameter
Silver
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Total Metals
Toxic Organics
Raw Waste
Loads
6
36
15
427
180
0.6
443
160
253
1520
1091
Conditions
Today
6
6
9
170
66
0.5
141
33
123
554
507
Categorical
Standards
5
4
6
32
28
0.3
36
26
65
204
154
C-76
-------
C4-III
Summary of Model Outputs
POTW Sludge Projections
(ng/kg)
Parameter
Silver
Arsenic
Cadmium.
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Total Metals
Toxic Organic
Raw Waste
Loads
31
0
41
2360
1470
1.5
571
538
1810
6880
s 1920
Conditions
Today
32
0
26
831
563
1.3
181
147
923
2700
913
Categorical
Standards
32
0
21
222
274
1.0
60
132
547
1290
300
077
-------
C4-IV
Summary of Model Outputs
POTW Incremental Stream Concentration Projections
Parameter
Silver
Arsenic
Cadmium
Chromium
Copper
Mercury
Nickel
Lead
Zinc
Raw Waste
Loads
0.2
0.3
0.4
11
4.3
0.02
14
2.8
6.3
Conditions
Today
0.2
0.2
0.2
3.2
1.5
0.01
4.3
1.0
3.2
Categorical
Standards
0,1
0.1
0.2
0.7
0.7
0.01
1.1
0.7
1.6
C-78
-------
D. BENEFITS APPENDIX
INTRODUCTION
The literature on assessing and measuring benefits associated with
improved water quality is diverse and theoretical. This appendix outlines a
general approach to estimating water resource benefits, and an overview of the
practicality of benefit estimation based on the existing state-of-the-art.
Methodologically, we assume an aggregation approach, estimating benefits
associated with diverse water quality uses for case study areas. Numerous
case studies of the benefit uses of water quality improvements throughout the
United States have been undertaken, thereby providing benchmarks for
estimating alternative benefit measures for diverse water uses associated with
water pollution control. Individual study area results are generalized for
broader regional applications. Similarly, results across all regions are
aggregated to yield national benefits.
STAGES IN BENEFITS ESTIMATION
Five stages to benefits analysis are generally applied:
1. Establishing the foundation of the study (defining assumptions);
2. Determining the relationship between physical attributes and
environmental quality, with and without improvement;
3. Collecting data to estimate recreation, nonuser, household,
municipal, industrial, and commercial fishing benefits; and
generalizing benefit results using multivariate techniques;
4. Deriving regional benefits from study area estimates; and,
5. Estimating national benefits.
Each stage is discussed in detail below. Where necessary, appropriate
exhibits are presented to facilitate the discussion of particular stages of
the analysis.
D-l
-------
ESTABLISHING THE FOUNDATIONS OF THE STUDY: STAGE 1
Establishing the foundations of the study requires specification of the
study objectives, determining the geographic area of analysis, identification
of secondary data sources, defining benefits, specifying assumptions of the
analysis and study limitations.
Study Area Boundaries
The initial task is to define the study area boundaries, given the
specificity of the study objective(s), to ensure that benefit measures can be
attributable to specific uses arising from water pllution control within those
study areas. The diversity of area types to be studied and benefits to be
analyzed facilitates generalizations. Therefore, the study area(s) might be
defined by political boundaries, hydrological basins defined by the Corps of
Engineers, functional economic area, or by other means consistent with study
objectives. The overall approach is presented in Figure D-l and details
concerning specific elements are discussed below. Individual stages of the
analysis are presented sequentially in following sections.
Define Benefits
Examples of benefits stemming from improvements in water quality include
improvment in recreational opportunities (swimming, fishing, boating, water
fowl hunting); reductions in water treatments costs for industrial users;
improvements in human health; reductions in household costs associated with
water hardness; increases in aesthetic values of water-based odor, taste and
appearance; and increased yields of commercial fisheries with potential lower
costs to consumers.
Benefits are classified into six categories as illustrated in Figure D-l:
o Primary
o Secondary
o Tangible (possess a market price)
o Intangible
o Measurable
o Unmeasurable.
D-2
-------
u^'i-'j'i'-r I T||^^
O
Cd
t**f i I I •••••*• Ul* I I MM*** I I |*MUr •**•••• •! I
i • MI.I^MI I *• **• *••!•« I I ••'•• I I )f*~iM »«T*«M* I
^1 I I I I I <»-*•. *£.'•*» I
• tU*«lb*«l«Ml
to4|i>l*|k|lt«(M
UpfovM*«i«. TV* MikU«u *fr)»kl*« u i« i«i*iBiM Mki«*«i w««*iu« wt Kki* M««ri« win *n\9 *t»tnit*\\r
*c»» all r*|i«M »lll yUM MI|«M| baMfii*.
-------
1>-I (continued)
O
Idtntltfy Types of
Ustsr Quality
Parana tars
1
«
Quality i»provu»*iu
Utliute Water
*^}uallty Pataoeler*
Reglnnlng in 1972
Mteretln* Antlclpa-
•*- ted Water Quality
without pollution
tat train* how saticipatvd l«v«U of w«i«r quality
lf«cts physical parasMtcr* for users and non us*
f wstsr sssu-minf no quality lsiprov«swnt «ft«r 19
*••<•»« lc» **rl«*ltMia|
l**>4> *>| tU««- 4kM* 4>f •wtf)^
Ml** •*•!• •••) tWIMM I*
r*M**iUl fUl- MMMHM
•*tt 1* I** C«f>ll»|
lll«>*
*-»»• MM || It
|U«.li*M»
lu«. !•«• k.e>u,
• *« 1
r-
»
ItCll Latt* «|
"
Property Value*
(tosses duo to
Water Quality)*
i
«a» tM aVil*«J aUt..|l. (nit** t.i*.
1 . . 1
CosMwrcUl g t|i|||
Fishing w*..i u..
Mus)b«r of ti*il"ii*l|*
W ISn LOSt tWM f>%iff|«W «M|a>|
1 . I
•«M4fl«l *"*^f*'
MM4MM »"»lll(»«l««
CMI* *|M<
1
Recreat Ion
(Water Contact)
Lou of Recree-
tlon daya tiy
1
**•••• ••«!•
With U.iter
Qua 1 1 1 y l*)pr uv«M«nt
CttlBat* Water Quality
luprovemnt a *eginnln|
In 1172
1
1
ra i Oete
J2 , t -
1
k«l«»f
UM •! riMi.
telxl 11 1«. .
•••MtT. loll**
1
S*Mf»llM
C«(>lla| <•«
WMAM.M
1
Recreation
(Non Water
font act )
Loa* of Potent lei
Vliltora to Site2
1 1
•>«a t.iuiti. til M4
••*. *^.«. !!*• I14K*. .«, 4*. 4C. 4NI
1 Char
| I—I,
1
1
1
1
1
i
l
i
t
i
I
i
i
1
t
i
i
I j
Aeathetlc*'
f
ttuaun
Health
(Ingeatlon)
f
Power
Generation
mine llou laprnved Level* of Water Quality
cla Uiara and Hon-Uaer> In Teroa of Phyilcal
acterlatlc*
1
Agriculture
1
Huaun
Healtli
'water con-
tact)!
1 , I ,.\
CitBimarcial Ooe>uatlc Ecology
Finding Water U*e
1" 1 I
Industrial Municipal Navigation
Jaier Safety later Supply
1 I 1
Property Recreation Rucreation
Value* [Uatet Contact) (Non-Water
Contact)'
««•••• Ik« HMfllMt fkfVlMl
•«*U|4I *MOl4«4 *>f M«M«t >>MMfl|
!*.>«•••••••• !• tawti •«••
•••iMlN* •• Itfl
CategoriM
•" Uaeri, Hei
clal Flah
i Oaauige Avoided: Rucrnat ion. Non-Water
illh. Industry, Municipal H In. . Comiucr-
m . Other
|
I Co to Stage 1
-------
Ul
I'11 MIRK IJ-
StjUje }. CoMect lug Survey Data to^ Eat l»ute Kc c real Inn' , Nuii-ustir', llouHebold3, Hun I c I |i,i t \
Industr 1 pi BeiitffIits* anil Tluine Accj-ulii(i to Coiniierrlal Fisheries*
Dele rmlne
Sample
1 raiue lly
Siiclo-ICcoiiomlc
Crimp/Loral Inn
Select Method
of Samp) Ing
and Means I.e.
Interview/Mall
Select Appropriate
Sample Size
Design
()ueutlonalre
Conduct Pilot
Survey
Analyse Survey
•(espouses
He v I HI; (Juuutloiiulre
and Suinple Size
Compute Ul
On Hue led
fiurveyH at
llxliuil Dal
Ail) UN I Ui
the l'o|>nl
tit Data
In I'revluua
nl wild Pub-
a
»i|>le to
ul Ion
As genii Bias
Due ID Non-
KeHponBe
*»•
As
Establish the Net Present
Value of Marginal bencf Us
••- Hue Data In Stage It
Asness Bias of
Keaponsun
Compare Survey
Kesponnea with Nutlonal
and State Surveyu
Analyse
Survey Keapimaea
Conduct
Survey
lliu objective IK to auk Individuals to state their "willingness to pay" for changes In water quality or how mich water quality they would demand at a
Klven price in under specified conditions of taxation. Tliere are two problems: tin- way qucutloiia are utiked can he iiiiud to create Incentives for
strategic lu'liavlor on the part of respondents I.e., respondenta may provide distorted or biased Information to tnfliiunce the final outcome; there may
lie no Incentive to provide accurate reBponaes. Both problems ran be overcome by precise questions.
The i|neiitloim In the surveys conducted to dale determine phynlcal damages for each type of household appllcance and w.ilcr dlstrIbulloii facility to
tin! quality of water. These Impacts are translated Into ranges of economic losses from operating proll 1 ems and equipment depreciation In a typical
houMuliold.
(jnestloiiH will determine- the cost savings due to Improved water quality.
Tin* ol> |t»ct I v*? IH to determine polenc lal cost Havings accruing to t'lrmu who currently, or In the future, une water as pan of Lhelr production prnri'su
e.g., for cool I UK.
the survey will a.sseus potential losses of flub and revenue due to specific types tif pollutants.
-------
FICIIKK l>-l (n.nl limed)
St age AA. Eii 11 mat Inn the Recreational Benefits of Water Quality Improvements
Verify
Socln-UcnnomIc Da In
mid Project limn From
Stage I
Define A Series of
Traffic Zones
Determine all R«c-
reatlonal Sites in
the Area and Their
Characteristics, In-
cluding Water Qual-
ity, (1972 and 1980
If PoaBlblu)
Sample Visitors to
Each Site to Deter-
mine Their Soclo-
Economlc Character-
istics and Zones of
Origin*
Calculate Visitor
Days Per Capita at
Each Site by Zone
of Origin1
Estimate Travel Cost
From Origin to Kuch
Situ and Return In-
cluding Tin* Costs
Develop ModeI(a) of
Hccrent tonal Demand
(1972 and 1980 If
PoHslhle) Accounting
for SubHt Hulublllty
of Sites. Test for
Weak Complementarity
Ke-KHt Imute
Tul nl Bf nef Us
for Site J
•«-
Hruject Explanatory
Varlulileu lo I9B5 and
Beyond (l.v. to the
Tine Limit of the Life
of the Project Deter-
mined In Stage 1)
Re-Estimate
Total Benefits
for Site J
Csliauite Marginal Changes
In Benefits Due to Uater
Quality Improvements
For Bach Uatar Qual-
ity Level In 1972,
1980, 198) and 19A5
Compute the Nut
Present Value of
Benefits
Project Explanatory
Variables In Model
to 1983
-*
Estimate the Secondary
Bcnef Us and Exter-
nalities From Improved
Water Quality
Assess the Net Present
Value of Secondary Huneflts
From Recreation (Net of the
Hunt-line) for 1980. I9B'J
and 1985 levels of Water
Ouulltv
-
Estimate Benefits Pur
Capita1 and Total
Benefits for the Stud
Area
Compute the Net Pre-
sent Value of Recre-
ational Benefits
Co To
Stage 5
1 I'rom Survey Data.
' Derived from regrusnlon equations.
-------
i: l>-l(.:,>nl liimul.)
Stage >in. Estimating Health Benefit*
Verily the physical
effects uf water quality
improvement eat inn ted
in stuge 2
Determine marginal
changes in mortality
between 1972 and I960
due to water quality
2
improvement
Estimate the net present
value of tlie expected
• stream of earning* for
• avoiding eacli
individual's death
Sum net prcucnt values
for all individuals
Sum benefits over all
individuala
Compare estimated bene-
fito with those given by
aha lysis baui'd on re-
sponses given in the
survey (in net present
value I.Tnia)
Estimate the reduced
net present value of
costs of friends and
relative! due to water
quality Improvement
Co
to Stage 5
Estimate the net preuuet
value of health care
costs due to morbidity
avoided from water
quality improvements
Verify estimated change in
the number of days lost
from work by occupation
for individuals in the
study area due
to water
quality improvements be-
tween 1972 and
19UO
Estimate net present
value of the loan nf
earnings due to reduced
morbidity in I9BO as com-
pared to 1972 due to
water quality improvement
I. It it is desirable to obtain national benefits it would he belter to collect and analyse U.S. data rather than that for specific regions. The
analysis is the same for the nation as for a region.
2.
Consider: pollutants which enter through the public water supply; pollutants which enter through the food supplies; effects'ol polluted water
DII the transmission of coniiniinicuhle disease; pollutants which enter the body through direct bodily contact with water; pollutants uhich lead to
emliigicnl changes which affect physical and/or psychological health.
-------
K1CIIHK ll-
U Imuul)
Stage Ac. Estimating the Property Value Component of Hon-llaer Benefits
Collect data for the
vtuily area
•••
Apply hedonic price
technique
**
Impiita net present
value of economic rent
due to water quality
Improvement*
-
Aggregate acroaa
neighborhood* to
study area
-
Compare reunite with
thoae prevented in
other studies
••»•
Determine marginal
benefit* by nut tr act-
ing the net present
value of economic
rent* without improve-
ment* in water quality
with tliat applying (or
estimated) in 1980,
198) and l«85.
Co to Stage
5
Aggregate marginal
benefit* (or each
year to obtain total
benefit*
I. Ideally, tlie ideal itiidy area for such a atuily might contain a number of lake* that are popular for retort cottage and a ecu ml home u*e. If
Ihi.1 lakes liave different degree* of water quality ft 1* possible to ihed light on the water quality-property value relationship. Another possible
uiluutiiin would be a river along which water quality varied considerably because of the locational pattern of Uincli.iigers. Eximlng utudieu have
found benefit* to be rero beyond 1 mile from a given body of water.
2. Dominiuli (1966) emimaled that the effect of water quality improvement on property value i* limited to an area 4,000 feet from the water: this m/iy
ritiliict! dula requirement a.
). I'roperty value*, characteriatic* i>f itructure and lot, locational characteristic* i.e. diitance from ahopping center*, park*, other recreational
IIM iIil Irn, downtown area*, etc., appropriate measures of water quality, neighborhood character ill leu and microeconomic itruclure, tlanuportiitinn
coutu to varioim location*, etc.
-------
KfiaiKK l)-l(cimt Iniiud)
Estimating I lie Bencf ita From Comnercial Fishing
O
Verify potential marginal
loHttCu in different types
of find du« to different
typi-H of (ml lut ant u.
(Stage 2)
Develop a Market
Analyst* fur different
types of fish
Project prices for
different typos of fish
(in real terns)
Estimate potential
tosses in reviMinea if
water had not been
Co to Stage
5
Compute the net
preuenl value of poten
tial fish louses
Compute the net present wuluo
of any secondary effects (i.e.
losses of hoar building income
etc.
I.
2.
I.e. Compare losses in fish at 1972 water quality levels with losses at 1980, 1981 and 19B5 water quality levels.
If there were no fish «t 1972 water quality levels, benefits might lie expense* at the potential revenues from a commercial fishery
if one were estalil islio'l.
-------
KlCIIKK ll-l(i:nnlliuiud)
Stagu i. Derivation of National Benefit*
Determine the marginal
benefit* of water
quality improvement to
1980 in HVP terms
Specify all benefit*
value could be estimated
Develop utiitly
uoncluvion* anil
limitat ion*
Repeat the analy*i*
in the next region
Conduct *en*itivity anal-
y*i* under «ltcrnativ«
growth (cenuriui and price
level*, discount ratea,
etc.
A**e*» the integralional
benefit* of water, with
and without improvement
Aggregate benefit*
aero** all region* to
derive nat ional
e*timale*
Adjuit eilinute* to
the regional level
A**e*« the validity/
applicability of the
analy*i« to other
area*
Repeat the andlybin for
water quality lovi'lu
projected for 1'IHI
and I9B5
-------
Primary benefits may be tangible or intangible, measurable or immeasurable;
similarly, secondary benefits fall within tangible, intangible, measurable and
immeasurable classifications.
Primary and secondary benefits that are directly measurable pose few
problems in economic analysis; less tangible and generally unmeasurable
benefits have been the focus of intense controversy in the past. However, a
general concensus has emerged—particularly in the broader applications of
welfare analysis—that specific techniques, grounded in established theory,
are applicable to measuring intangible/unmeasurable benefits. Revealed
preference theory offers one such approach giving rise to willingness-to-pay
survey techniques which, properly developed and implemented, are used to
determine and quantify benefit preferences of direct and indirect
beneficiaries of water quality improvements.
Collect Secondary Data
Estimating benefits of water quality improvements through the use of
economic models (Stage 4) requires collection of secondary data for estab-
lishing the functional relationships, scope, and time frame of anticipated
analyses. Required data include ecologic, engineering, and economic data to
project economic and demographic activity. Identifying and estimating exist-
ing and future land uses and faciilties affected by water quality improvements
must also be determined and included in the analytical framework for assessing
and measuring water quality benefits.
Specific Assumptions
In quantifying benefits over time, it is necessary to make assumptions
regarding the general level of prices, the economic life of the project, the
discount rate to translate future benefits to net present value terms, and
various market imperfections governing the estimation of shadow prices;
namely, imperfect competition, unemployment, indivisibilities, collective
goods, import quotas and tariffs, externalities and nonmarginal changes which
may also affect relative prices. It is also necessary to account for possible
sources of double counting. For example, aesthetic benefits may be included
in recreational or nonuser benefits. If boating is possible at water quality
D-ll
-------
level, improved water quality should not result in additional benefits to
boaters. Many of those issues are well documented in the literature and need
no further elaboration.
Limitations of the Research
The previous steps—*establishing study area boundaries, defining
benefits, indentifying secondary data sources, and explicitly specifying
assumptions that must be taken into account—define the study scope. Within
this context, it is possible to identify study objectives which might not be
possible to achieve.
DETERMINING THE RELATIONSHIP BETWEEN PHYSICAL ATTRIBUTES AND ENVIRONMENTAL
QUALITY: STACS 2
Figure D-l, Stage 2 provides a schematic presentation for determining the
relationship between physical attributes of water (pollution levels) and
benefits associated with environmental quality, with and without water quality
improvement scenarios. Three areas of inquiry are important: identifying
types of water quality parameters, estimating water quality parameters, and
determining how anticipated levels of water quality impact on physical
parameters.
Identifying Types of Water Quality Parameters
The first decision is whether changes in water quality will be indicated
by a general index or whether specific parameters are necessary. Studies have
used acidity, BOD, coliform bacteria, color, flotation solids, hardness,
nutrients, odor, oil, pesticides, radionuclides, sediment, taste, temperature,
TDS and salinity, TSS and turbidity, and toxic metals as particular indicators
of water quality. On the other hand, individual parameters can be combined
and weighted into one or more indices depending on identifiable relationships
between water quality parameters and associated impacts/changes in the physi-
cal characteristics of water and resultant effects (benefits) on users and
nonusers of water.
D-12
-------
Estimating Water Quality Parameters
The objective is to determine the ambient concentration of pollutants
with and without public policies to improve water quality (Figure D-l, Stage
2). Of importance is the quantitative relationship between residual dis-
charges and ambient concentrations of pollutants, thus making it possible to
attribute changes in the output of a particular industry to changes in the
ambient concentration of pollutants. Estimates of water quality parameters
are known to vary—depending on volume, flow, sampling procedures, and the
extent of pollution from natural sources. Quasi-experimental treatment con-
trol comparisons (control laboratory experimentation) should contribute to
understanding changes in water quality parameters under alternative residual
discharge/ambient concentration scenarios.
Determine How Anticipated Levels of Water Quality Affect Physical
Parameters
Given levels of ambient water quality, physical effects can be
determined; i.e., potential fish loss, increase in morbidity and mortality,
damage to bridges, piers, or shipping for various levels of water quality.
The link between water quality and its. impact on physical parameters is
causal, one that accounts for the physical damage avoided by water quality
improvements versus the situation without public policy maintaining or
improving water quality.
ESTIMATING BENEFITS FROM SURVEY DATA: STAGE 3
Data used to determine the economic benefits of water quality improve-
ments are largely derived from surveys. Figure D-l, Stage 3 outlines a
general methodology for survey design and implementation for estimating
recreation, nonuser, household, municipal, and industrial benefits as well as
those accruing to commercial fisheries.
Data are collected using either a stratified random sample or sampling of
the entire population, depending on the objectives of the study and the level
of accuracy sought. Pilot surveys provide a ready means of evaluating the
adequacy of the questionnaire by reducing incentives for biased responses and
providing indications as to the accuracy of specific responses. Based on
D-13
-------
results of pilot surveys, survey instruments can be revised and sample sizes
adjusted. Estimates of benefits can be derived for the population of
households, municipalities, and industry.
Willingness-To-Pay Survey Techniques
One approach to estimating benefits through survey techniques is to have
individuals state their "willingness-to-pay" for a given stream of benefits
associated with water quality improvements. Questions used to derive
willingness-to-pay responses must place the individual in a situation where
he/she can understand the objectives of water quality improvement such that
he/she can imagine the consequences of his/her response; i.e., questions
should include concrete data and accurate descriptions of alternatives. The
objective is to create as real a situation as possible rather than to present
hypothetical scenarios.
Willingness-to-pay surveys must be directed toward discerning particular
water level uses and their relative worth to respondents, an approach that
permits investigating trade-offs among differing use levels and their pro-
spective values to respondents. Such an approach has been used extensively
for estimating recreational benefits, both for users and nonusers.
ESTIMATING BENEFITS OF WATER QUALITY IMPROVEMENT FROM ECONOMIC MODELS:
STAGS 4 " .
Economic models have generally focused on assessing the benefits and
costs associated with particular water level uses—recreation, health, the
property value components of nonuser benefits, and commercial fishing are
examples that have received extensive treatment in the literature and are
discussed below. However, other use benefit aspects covering navigation,
municipal water supply, agriculture and domestic water users should also be
considered in a more comprehensive treatment of the subject.
Recreational Benefits
Figure 0-1, Stage 4A provides a detailed schematic chart for estimating
the recreational benefits from water quality improvements. Inputs into the
estimation procedure follow directly from Figure D-l, Stage 1, which provides
the socio-economic data base for undertaking the analysis.
D-14
-------
As the demand for outdoor recreation grows due to population growth and
increased leisure time, benefits of water pollution abatement will also rise.
Particular benefits will derive from each type of recreational use of water
resources: fishing, boating, swimming, sightseeing, camping, water fowl
hunting, fish and animal preservation, and skiing are examples. Benefits can
be defined by the amount an individual is willing to pay (in license fees,
travel costs, etc.) to enjoy the different types of water recreation; i.e.,
the amount that could be collected from users of recreation areas (in the form
of licenses, sales of hunting rights, etc.) if it were possible to charge for
service and amenities.
A number of studies have used travel costs as a means of estimating the
demand for recreation where frequency of visits to a site is a decreasing
function of distance from the site. The cost of travel increases with
distance from the site because of monetary and intellectual considerations.
Hence, a demand curve for recreation may be derived by plotting frequency of
visits against distance. This method computes , the consumer surplus or
economic benefit of the site to an individual as the amount saved over the
traveling costs of the user coining from the longest distance. It easily lends
itself to estimates of recreational benefits except in the case of unique
wildlife or scenic facilities.
A typical demand function is described by Freeman, (1979) and may be of
the form
vijb-vj(pxj>
where
V. . : Number of visits of individual i to site j for purpose of boating
P •: Vector of prices of entry to various sites
XJ
Di: Vector of distances from the residence of individual
ti: Vector of travel times to the various sites
hi: Cost of travel time to the various sites
D-15
-------
Q.: Indicators of water quality at the various sites (this may be
specified as the concentrations of different types of pollutants)
R, , : Indicators of recreational facilities and amenities at each site
• * iC
M.: Vector of individual socio-economic characteristics including
income.
The dependent variable can be adjusted to account for other types of
recreation besides boating.
Health Benefits
Figure D-l, Stage 4B provides a diagrammatic procedure for estimating
health benefits and follows directly from the preceding discussion of Stage 2.
For people in the labor force, the human capital approach can be used to
derive the expected net present value of future earnings which an individual
might have earned had death been avoided. The benefit of preventing a death
of an individual in any year, H., can be derived from:
t
H. = I PtEt/(l + i)t
1 t-1
where
Pt * probability of the individual surviving to year t
Et " earnings of an individual in year t
i * discount rate.
These benefits, H., therefore represent the potential loss of output to
society, and will obviously depend on the socio-economic characteristics of
the individual. The estimate of H. often expresses the net of the
individual's worth to society, relecting the individual's consumption.
In addition to the valuation of reduced mortality due to water quality
improvement, account should also be taken of the reduced costs of health care,
and the indirect costs of morbidity due to lost earnings. An essential part
of the analysis is to determine the number of days of lost activity or
D-l 6
-------
restricted activity due specifically to adverse water quality. This part of
the study may thus involve defining specific relationships between levels of
water quality and various types of illness or disease.
Property Value Component of Nonuser Benefits
Figure D-l, Stage 4C outlines the general approach for estimating the
property value component of nonuser benefits associated with improved water
quality. It is assumed that as the quality of water in a stream or lake
improves, people are willing to pay to locate nearer to that water if they
consider it an amenity. Hence, property and land values near the amenity will
increase. Benefits of water improvement will be greatest at the water's edge
and will decline with distance from it.
Typically, a hedonic price approach is used to isolate the change in
property or land values due to changes in water quality from that due to
structural or neighborhood characteristics. The hedonic equation may be used
to estimate the implicit price of water quality and may be of the form
where
R.: Value of property (expressed as a rent using assessed values,
sometimes adjusted for taxation)
P.: Vector or property characteristics
N.; Vector of neighborhood characteristics (including zoning,
public services and taxes, density, racial composition)
Q.: Level of water quality
D..: Distance to water body
D., : Distance to other social amenities (local schools, parks,
il...k"
stores, hospitals, place to work, cultural centers, highways).
This method can be used to determine how rapidly water quality improve-
ment effects decrease with distance from the water body. Selection of the
study area is particularly important: an ideal area would include as much
variation as possible along water body types and geographic locations so that
D-17
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the influence of water quality can be identified. If water quality improve-
ments are to change individuals' valuation of a water resource, a considera-
tion is that people are aware of changes that have taken place.
Benefits from Commercial Fishing
As in preceeding sections, the procedural approach for estimating bene-
fits from commercial fishing is presented in Figure D-l, Stage 4D. Benefits
of water quality improvement are estimated as the net increase in income which
results from improvement—the net value of production less marginal cost.
Improved water quality also leads to benefits in the form of reduced costs of
maintaining vessels, bait and other operating capital.
Consideration must be given to an analysis of the abundance of fish
resources and the potential increases in catch with varying levels of water
quality improvements. Secondary considerations are increased commercial
yields on fish packing plants, and the indirect effects of increased expendi-
tures of the additional income earned in local areas.
ESTIMATING NATIONAL BENEFITS: STAGE 5
Emphasis in preceding discussions has been on the explicit identification
and measurement of benefits that, in the general context of contemporary
literature, are area specific. Intangible and unmeasurable benefits can be
proxied, albeit crudely, through "willingness-to-pay" surveys premised on a
revealed preference theory approach. Initial ordinal values can be inter-
preted in terms of monetized values. Less difficulty is encountered with
physically observable changes that directly impact on land values, commercial
fishing, recreational uses of water, and health effects—all of which can be
observed on-site and directly measured through survey techniques/economic
models.
National benefits—quantifiable changes in water uses due to improved
water quality—are approximated by a bottoms-up approach. Area specific case
studies can be generalized to other comparable areas and/or modified to
account for different types of areas experiencing similar water quality/use
changes. Estimates are adjusted to a regional basis and aggregated across all
D-18
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regions to derive national estimates making allowance for externalities in the
cases where one regions's gain may be another's loss. The general procedure
is outlined in Figure D-l, Stage 5.
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APPENDIX E
MONETIZING BENEFITS
In this report the benefits of pretreatment are described in both qualita-
tive and quantitative terms. The quantitative measures of benefits for all of
the 2000 POTWs studied are: the change in pollution loadings as a result of
the pretreatment options and the improvements in water quality as indicated by
the elimination of exceedances. However, for those cases where exceedances
are eliminated, this report goes further by attempting to measure some of
the benefits of cleaner water. Specifically, this report measures the dollar
value of achieving designated recreation uses (such as swimming, fishing, and
boating). This section describes the methods used to make these recreation
use value estimates. Other benefits of cleaner water were not addressed.
E.I INTRODUCTION
Initially, several estimation techniques were considered for this analysis.
These included (1) apportioning existing national benefits estimates and as-
signing a portion to pretreatment measures and (2) extrapolating total pretreat-
ment benefits from detailed case studies. But apportionment approaches are
hampered by the lack of adequate data for assigning benefits to water bodies.
And for case studies, sophisticated benefits analysis techniques could not be
applied to a sufficient number of cases to provide representative results due
to time and resource constraints. Therefore, a hybrid technique was developed.
This hybrid approach combines readily available local information on stream
capacity and affected population with recreation value factors estimated from
several national and site-specific studies. It proved to be feasible and
performed well when tested against other techniques recently used by EPA.
The approach used here provides an interesting indication of the actual
and potential benefits of pretreatment options. However, the approach does not
E-l
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provide an adequate basis for making cost-benefit tradeoffs in program design
and application. This is because of several important limitations. The ap-
proach measures only the benefits of recreational uses of water, neglecting
POTW upsets, effects on sludge toxicity, industrial and municipal costs to
treat water prior to use, and health effects. Because it was not possible to
relate recreation uses of water to particular levels of various toxic pollu-
tants, the analysis assumes that no recreation takes place if there are any
toxic exceedances. Finally, this analysis neglects the presence of pollutant
sources other than POTWs; this lends to an over-estimation of likely water
quality (before and after controls) and an under-estimation of potential control
costs to achieve water quality levels. Other limitations also exist and are
discussed later in this section.
In the next subsection (E.2), basic approaches to benefits analysis are
briefly described and compared, to put the approach used here in perspective.
In subsection E.3, the methodology employed is described In detail. In sub-
section E.4, the limitations of the methodology are discussed. In subsection
E.5, this benefits estimation approach is tested by comparing the results
to recent and available EPA case studies.
E.2 APPROACHES TO BENEFITS ESTIMATAION
This section attempts to place the benefits estimation approach used here
in perspective by describing its relationship to approaches used in the past.
The discussion is brief, and does not describe alternative benefits estimation
techniques in great detail. A more general and complete discussion of benefits
analysis for water pollution control is provided in Appendix D.
E.2.1 Previous Studies
In general, past studies have either examined improvements for particular
bodies of water (case studies), or attempted to estimate the nationwide benefits
of improving all water quality to a uniformly high level.
E-2
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Case studies can include relatively sophisticated water quality modelling
to estimate actual changes in water quality. Local information on use levels
and stream capacities can be collected. Surveys can be used to relate travel
distances or costs to water quality, or to collect reports on subjective willing-
ness to pay for improved water quality. All of this information can be combined
to estimate the value that affected individuals place on the change in their
recreational opportunities. (Past studies show that enhanced recreation value
is usually the largest component of total benefits from an improvement in
water quality.) Good case studies provide the best available estimates of the
value of improved water quality. However, these studies require a great deal
of data and are typically expensive and time consuming.
National benefits studies use generalized estimates of the value of recre-
ation activities, based on the estimates of values at particular times and
places derived in case studies. These estimates are then extrapolated to the
national level using aggregations of such factors as surface area of affected
water bodies or population affected. Water quality modelling is typically not
undertaken; the studies measure the benefits of improvements in water quality,
and assume that the regulations will produce such improvements. Recreation is
assigned similar values in all locations, without regard for local tastes or
available alternatives. (We will call these assigned values "national benefits
factors.") Extrapolations are necessarily crude, and subjective judgments
about the weight to be accorded particular case studies is inevitably important.
E.2.2 This Study
The pretreatment program will affect a large number of locations and will
have different effects on water quality in different places. As a result,
local detail is important but many cases must be examined. The methodology
used in this study is designed to make local detail manageable within time and
resource constraints. This methodology can be viewed either as a simplified
case study approach, or as an exercise in extrapolation of national benefits
factors that is somewhat more case specific than existing national benefits
studies.
E-3
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The approach is like a case study because it uses case specific predictions
of changes in water quality, and uses local information about affected popula-
tions and the recreation potential of the affected water body (based on its
size). The approach simplifies the case study approach considerably (and
moves in the direction of national benefits studies) by using national benefits
factors, and by not measuring actual changes in use. While this approach
allows many cases to be examined quickly and economically, the results in any
particular case may over- or under-estimate actual benefits. Case-by-case
benefits estimates are aggregated here to average sources of error that are
not systematic, before benefits are compared to costs.
E.3 DETAILED METHODOLOGY
The methodology used here measures recreation use benefits in two ways:
I) as the value of use multiplied by the level of use, and 2) as the value
of proximity to clean water multiplied by affected population. Both approaches
rely on the use of appropriate national benefit factors, which are taken from
earlier studies (primarily national benefits studies). In the first approach,
boating and fishing benefit factors are combined with an estimate of actual
fishing and boating participation levels based on stream reach area and recrea-
tion planning standards. (The estimation method assumes recreation capacity
will be fully utilized.) In the second case, a different benefits factor is
combined with affected population, estimated as the population of contiguous
counties. Benefits other than recureation use are cot estimated.
E.3.1 Sample Selection
The benefits factor approach can be applied in any case where basic data
on stream area are available. It is used here to measure actual benefits in
cases where a POTW control option leads to elimination of all water quality
exceedances for the designated stream segment. To the extent that stream area
and affected population in these cases are typical, the benefits measured are
E-4
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indicative of the benefits that could be achieved by eliminating exceedances
in other cases.
Data sufficient to calculate the effects of regulation on exceedances were
available for 650 POTWs from a population of 2000. This sample is believed
to be representative of the general population. In 325 of these 650 cases,
some exceedances occurred in the absence of control. In 22 of the 325 cases
with exceedances, the exceedances were eliminated by the control options. Bene-
fits were analyzed for 17 of these cases. The cases analyzed are representative
of about 60 cases in the total population of 2,000 for which controls
could be expected to eliminate all exceedances.
E.3.2 Benefits Factors
Case study estimates of benefits provide a series of examples of the value
of recreation. The examples involve different individuals in various places
and times, and different activities that are more or less affected by improve-
ments in water quality. Existing national benefits studies have relied on
these case study results to estimate general values for boating, fishing, and
swimming. These values are expressed in terms of dollars per user or household
over a given time period. In conjunction with EPA, this analysis reviewed
existing national benefits studies to select the most reasonable and well
founded benefits factors that are available. The benefits factors used for
this analysis, and their sources, are given in Table E-l. Other typical factors
that were not used are also presented for comparison purposes.
One set of factors used in this analysis measures the use value of boating
and fishing; these factors are given in dollars per individual user per day of
use. Boating benefits were estimated to be about $17 to $30 per user per day,
and fishing benefits to be about $15 to $30 per user per day. These benefits
factors are properly used in conjunction with estimates of the change in actual
use of a stream segment that results from an improvement in water quality.
E-5
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Table E-l
ESTIMATED PER CAPITA BENEFITS
IN 1981 DOLLARS
Type of Benefit
RECREATION
Boating*
Fishing
Swimmable, fishable
and beatable water
(includes non-user benefits as well)
Amount
$16.76 - 29.73 /person/day
$15-30 /person/day
(catfish-trout)
$35-45 /household/year
Source
NCWQ (1978)
Russell and Vaughan
(RFF/EPA 1981)
Charbonneau and Hay (1978)
Gramlich (1977)
NON-USER**
Fishable waters
OTHER
Drinking Water
Health
$111 /household/year
Mitchell and Carson
(forthcoming)
402 of local treatment costs Barker & Kraner (1973)
Bramen (1960)
$300,000-3 million
per fatality avoided
Thaler and Rosen (1975)
Bailey (1979)
* Boating benefits do not include canoeing, water skiing, or sailing
** Non-user benefits are for all U.S. waters, and includes aesthetics,
preservation (future generations) value, and option value.
E-6
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Another factor measures the benefits of attaining waters of "swimmable"
quality; this factor is given as $35 to $45 dollars per "local" household per
year. This last factor is for improvement from water that is not useable for
recreation to water that is beatable, fishable and swinmable; therefore it
incorporates the use value of all of these activities. Clean water also creates
new recreation opportunities that are valuable even if they are not used; the
benefits factor used here includes such non-user benefits as preservation and
option values; after application of this factor, results were adjusted to
include only user benefits. This benefits factor is properly used in conjunc-
tion with estimates of the number of households within range of the stream
segment experiencing the water quality improvement.
Z.3.3 Estimation of Stream Size, Use Levels, and Household Affected
This study does not measure actual use levels (if any) now occuring for
the stream segaents of interest, nor does it estimate the change in use levels
that can be expected to occur on a particular body of water experiencing an
improvement in water quality. Instead, the study assumes that attaining water
quality thresholds trigger full capacity use. It is assumed that use is
achieved only when exceedances are eliminated.
Where water can support boating or fishing, this study assumes that the
water is fully utilized. The estimates of "full use" capacities for fishing
and boating activity used for this analysis are based on the characteristics
of the affected stream segment — e.g. stream length (miles), surface area
(acres), and number of available recreation days.
For this analysis, each POTW was assumed to be affecting one stream reach
(the section of a stream between two confluents). For the cases in which a
POTW was located in the upper half of a stream reach, that reach was used.
Where a POTW was located in the lower half of a stream reach, the next reach
was used. (This reach would begin at the first major confluent downstream of
the POTW, and extends to the next major confluent.) The total surface area of
E-7
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the affected segment was determined by multiplying the average width of each
reach by the length of the reach.
Boating and fishing capacity and recreation days are based on recreation
planning standards adopted by the state of Ohio in its State Comprehensive
Recreation Plan. (The boating capacity estimate is based on canoeing, while
boating benefits factors used in this study specifically exclude canoeing.
However, this capacity figure is the best that could be located for this
purpose.) One hundred ten (110) use-days were assumed, based on 90 weekend
days in a nine-month season, plus 20 vacation days, with zero use at other
times. This approach provides only a rough notion of capacity, and may not
accurately represent potential use levels for any particular stream reach.
However, the fishing capacity and use days estimates are supported by an Army
Corps of Engineers study showing 87 fisherman days per acre per year for
Mosquito Creek, Pennsylvania.
Estimates of the number of households affected by an improvement in water
quality were derived by examining Census Bureau 1980 Advanced Reports data for
counties bordering or containing the stream segments of interest.
E.3.4 Estimating Benefits
As indicated in Section E.3, two slightly different methods were used
here to estimate benefits. The first derives user benefits from boating and
fishing by multiplying stream use capacities by the values per person-day of
those uses. The second approach estimates total user benefits by multiplying
the number of "local" households by a separate benefits factor intended to
capture annual household benefits for fishable/swimmable waters. With both of
these approaches, it is assumed that water quality is improved from a level
that does not permit any recreation to a level that permits boating, fishing
and swimming.
These two methods of estimating benefits are independent of one another
(except that both are affected by stream length) and therefore provide checks
E-8
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on each other. In general, the "households affected" measure should give higher
values for benefits, because it captures swimming benefits. However, estimates
of user benefits using either technique can be overstated. The "households
affected" measure can overstate benefits when a large population center is
located near a stream reach of limited capacity. The capacity estimation
technique can overstate benefits when population levels are low relative to
stream capacity. This approach does not use population as an input; it asks
how many users can be supported rather than asking how many users will actually
be added. These capacity estimates should be matched with benefits factors
that measure the benefits of potential use, but instead they are matched with
factors for boating and swimming that are based on actual rather than potential
use. Where benefits estimates based on one approach are much greater than
benefits estimates based on the other, it is likely that the higher estimate
is unreliable.
Table E-2 provides an example of the amount of activity that would be
required for boating and fishing user benefits to each equal $1 million. The
table also shows the number of affected households that would be required for
the aggregate user benefits of swimnable waters to equal $1 million. This
substantial level of benefits can be achieved with fewer than 100 boaters or
fishers per pay, or as few as 25,000 local households.
E.4 ASSUMPTIONS AND LIMITATIONS
Strong assumptions and significant simplifications were needed to apply
this approach to estimating benefits. Therefore, it is important to under-
stand the major limitations of the approach in considering the reliability
of its results. Judgements about reliability should also consider the evidence
in section E.6 on the good performance of this approach in comparison to more
sophisticated benefits estimation approaches recently applied by EPA in three
case studies. The limitations of this approach do not appear to have introduced
any major or systematic bias in the estimates of benefits that result for
these cases.
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Table E-2
RECREATION BENEFITS MATRIX
Level of Attained Designated Use Number of Users User Benefits
0 Boating*
($17-30 /person/day 91 - 161t $1,000,000
" Fishing
($15-30 /person/day) 91 - 183§ $1,000,000
0 Swimmable
($35-45 /household/year) 33,333 - 42,8571 $1,000,000
(includes non-user benefits)**
* Boating benefits do not include water skiing or sailing.
** Non-user benefits are assumed to be 50Z of user fishing benefits, and include
aesthetics, preservation (future) generation value and option value.
NOTES;
t The Ohio State Comprehensive Recreation Plan (SCRP) adopts a standard of 40
persons/aile/day maximum canoeing capacity. The number of user days per year
is estimated by multiplying this standard times the number of recreation
days available (weekends and holidays in a nine month season plus 20 days of
vacation time) times the number of navigable miles on the particular body of
water.
For example, using an average (user) boating benefit of $23.50/person/
day, a body of water having 9.67 navigable miles and located where 9 months
out of the year provide suitable weather (90 days of weekends and holidays,
and 20 days of vacation time), would yield $1 million per year in user bene-
fits (40*110*9.67*23.5).
§ According to the Ohio SCRP, potential use of a fishery is 1 fisherman per
acre of surface water per day. With 110 recreation days of full use per
year, maximum use would be 110 fisherman per acre per year. This use estimate
is supported by an Army Corps of Engineers study at Mosquito Creek which
estimates potential use of a fishery at 87 fisherman per acre per year. Thus,
for a particular body of water, an upper bound estimate of users per year
can be made by multiplying 110 times the number of surface acres available.
For example, using an average (user) fishing benefit of S22.50/person/day,
a body of water with 404.04 acres of surface area would yield user benefits of
$1 million per year (110*404.04*22.50).
E-10
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Table E-2 continued
Recreation Benefits Matrix
NOTES continued;
This estimate of fishing benefits does not account for bank fishing, but
only for boat fishing. For bank fishing, a standard of 20 fisherman per day
per river mile would be used to estimate benefits.
*, Estimating user benefits using this benefits factor for swimiaable, fishable,
and beatable vater, would involve estimating the population of counties or
towns in an area adjoining the body of water on either side. To arrive at
total user benefits from this aggregate measure, non-user benefits amounting
to 50Z of user fishing benefits would be subtracted out after fishing benefits
are calculated as above. For example, suppose that the body of water used
in the fishing example above runs through one or more counties having a total
of 37,500 households. Then, using an average aggregate benefit of $40 per
household per year, total user benefits for swimming, fishing, boating plus
non-user benefits would be $1,500,000 (40*37,500). Subtract out the $.5
million in non-user benefits would yield total user benefits of $1 million.
E-ll
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Assumptions and limitations are discussed here roughly in order of impor-
tance. In each case an attempt is made to indicate whether the assumption intro-
duces a bias for which the direction can be predicted or controlled, and to
indicate the likely direction of bias if possible. A summary section discusses
the implications of all these limitations for uses of the analysis results.
E.4.1 Use of Thresholds
This analysis treats benefits as a threshold phenomena, and assumes that
there is only one threshold of importance. These assumptions introduce
different biases in different cases. The use of any threshold will lead to
underestimates of benefits in cases where thresholds are not reached, because
no benefits will be found if those cases are examined using this approach.
The use of thresholds will lead to overestimates of benefits in most cases
where thresholds are crossed, because benefits attributable to a large change
in water quality may all be assigned to the small change that crosses the
chosen threshold. Even if the threshold phenomena existed in practice or
was officially established for toxics at the state level, it Is unlikely
that a single threshold would be appropriate for boating, fishing and swim-
ming. The use of a single threshold exacerbates the problems inherent in the
threshold approach. With one threshold rather than several there will be
more cases in which thresholds are not crossed, and a greater overestimate of
benefits in cases where thresholds are crossed.
E.4.2 Other Dischargers
Due to data limitations, this approach treats POTWs as the only source of
pollutant discharges. As a result, exceedances probably appear less frequently
and are eliminated more easily in the model than in practice. In addition,
all benefits of cleaner water are attributed to controls on POTWs, when elimi-
nating exceedances may typically require the control of other sources (such as
direct industrial dischargers). This limitation probably contributes to an
overestimate of benefits in the cases examined.
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E.4.3 Estimation of Use Levels
The analysis makes no adjustments for prior use of stream reaches, and
does not account for factors (other than limited population) that may prevent
"full use" of a stream reach as defined by recreation planning standards.
These assumptions may introduce a bias toward overstated benefits.
E.4.4 Single Stream Reaches
The analysis looks at only one stream reach for each POTW. Confining
the analysis to a single stream reach will lead to underestimates of benefits,
because improving the water quality in the given reach will make it more likely
that uses and benefits can be achieved downstream. This source of under-esti-
mation tends to offset any over-estimation resulting from the "full use" assump-
tion described above.
S.4.5 Local Value of Uses
The national benefits factors used in this analysis do not reflect the
local value of particular uses, and so are unlikely to be appropriate in specific
instances. It is not known whether this results in over or underestimation
of benefits for the particular cases examined. The aggregation of case results
probably smooths out much of the error from this source.
E.4.6 Recreation Days
This analysis assumes 110 recreation days for all parts of the country (9
months of weekends plus 20 vacation days), on the basis of estimates intended
for use in the Ohio/Pennsylvania region. In areas with a less harsh climate,
or a harsh climate but a greater propensity toward water quality sensitive
winter recreation (e.g., ice fishing), this will lead to an underestimate of
benefits. Benefits may also be underestimated if a stream reach is more heavily
used by vactationers than is assumed here. In other regions benefits may be
overestimated.
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E.4.7 Other Data Limitations
This analysis ties benefits estimation to estimates of affected population
and to estimates of the area of water affected controls on the POTW. These
estimates are quite crude, and errors will introduce biases in the estimated
level of benefits.
2.5 LIMITS ON THE USE OF RESULTS
The results of this analysis of 17 cases could be used only to assess the
cases actually examined, or could be extrapolated to all other cases where
exceedances are eliminated, or to the entire population of POTWs. However,
the limitations of this analysis make it unreliable for some purposes, so
results must be used with caution.
For the cases examined, many factors that could not be controlled or
evaluated can introduce errors in the estimates of benefits. Therefore for
single POTWs small differences (i.e., less than a factor of two) between costs
and benefits should not be considered significant. The direction of bias
resulting from all of these factors in a particular case cannot be determined;
however, when cases are aggregated a systematic bias toward overestimation
of recreation use benefits is likely to prevail, allowing a more informed
use of results. Even after averaging, however, results should not be used
to make cost/benefit tradeoffs in program design. This is because of the
remaining systematic bias, and because too few cases were examined here to
prevent attaching undue significance to potentially unreliable results in one
or a few cases.
The results for the 17 cases examined here can easily be extrapolated to
the 60 or so cases in the entire population of POTWs for which exceedances
could be expected to be eliminated. However, substantial uncertainty exists
about the representativeness of the sampled cases. POTW flows, stream flows,
stream reach and width, and affected populations are all relevant here, and no
E-14
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attempt has been made to compare these factors for sampled and unsampled cases.
Therefore, extrapolated results would be of unknown reliability.
Finally, there is a major question as to whether the benefits measured
here should be compared to all pretreatment costs, or only to the costs of the
cases examined. Cost-benefit ratios will differ radically in the two cases,
and reasonable people can differ on which approach is most appropriate. Thus,
the results of using either approach cannot be conclusive in determining whether
costs exceed benefits for the pretreatment program as a whole.
This issue turns on particular biases in the estimating techniques used
here. On the one hand, this analysis probably overestimates benefits for the
stream segments that were examined (those where thresholds were crossed); on
the other hand, benefits exist in many cases where this approach was not applied
because it would not capture benefits. The factors that contribute to an
overestimation of benefits in the cases where thresholds are crossed also
contribute to an underestimation of benefits in other cases. If cases were
properly divided into these two groups, attribution of measured benefits to
more cases might result in a more accurate picture of benefits in an average
case. But if too few cases are identified as involving elimination of all
exceedances, benefits would be seriously underestimated for the population of
POTWs as a whole.
This kind of misclassification is likely to exist in this case. The
model used to predict exceedances assumes that POTWs are the only dischargers,
and that they discharge into pristine water; partly because of these assumptions
half of all cases examined involved water so clean that no control was needed
to avoid exceedances. In actual practice receiving waters would not be so
clean, and exceedances that could be eliminated through control would probably
be more common.
The decision made here is to exclude the costs in the latter set of cases
from cost/benefit comparisons. However, some readers may wish to take the
other approach, assume that substantially all benefits have been captured in
E-15
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the cases examined, and compare these benefits to total costs for all the
POTWs. These costs are reported in this study, so that the reader can generate
any desired comparisions.
The benefits found in the cases examined here are indicative of potential
benefits from eliminating exceedances in other cases. Comparing potential
benefits to the costs incurred for control in cases where exceedances were not
eliminated provides some indication of whether additional expenditures on
pretreataent might be worthwhile.
E.6 TESTS OF RELIABILITT OF RESULTS
This section compares the results of the benefits estimates made using
the benefits factors techniques described above to results of using three
other and more sophisticated techniques. These comparison cases were chosen
because they are the most recent case studies that were available. The benefits
factors approaches described above were applied to the same stream segments
examined in these recent case studies.
Comparison of results indicates that simple benefits factor approaches
can produce benefits estimates in the same range as more sophisticated ap-
proaches. However, these comparisons are not conclusive because significant
biases are possible using benefits factors techniques as they are applied
here, and only a small sample of cases is being examined. There cannot be a
high level of confidence that the performance of the benefits factor approaches
In these cases is representative of their performance in general.
The case studies examined three rivers (the Mahoning, Black, and Monong-
ahela rivers, in Ohio and Pennsylvania) and applied three different approaches
to estimate benefits. There approaches were Participation Models (PIE-C/1),
Planning Standards (PIE-C/2) and Willingness to Pay (PIE-C/3). (Some of the
results of the case studies used here are preliminary, and subject to change.)
E-16
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The participation model predicted changes in levels of participation,
given changes in the supply of beatable and fishable water, changes in type of
fish caught and average size of catch, and socioeconomic factors.
The planning standards approach is conceptually very similar to the "capa-
city times value" approach used here to measure boating and fishing benefits.
In addition, common data were used for affected area of water, population in
the vicinity, and recreation days, and similar data were used for benefits
factors. The major differences in the results of using the planning standards
approach and the benefits factor approach are probably the result of adjustments
for previous use and sensitivity to kinds of boating and fishing in the planning
standards approach.
The willingness to pay approach was based on a survey
that addressed the value of improving all U.S. waters to swimmable quality.
A comparison of the results using the three alternative estimation tech-
niques and a benefits factor technique is shown in Table E-3. The table gives
total user benefits by river, total user benefits aggregated for all three
rivers, and a breakdown of fishing and boating estimates by river. The benefits
factor method produces benefits estimates that are comparable to those produced
by these other techniques. When results for all three rivers are aggregated,
the benefits factor technique compares even more favorably.
For each of the three rivers analyzed in the study, the benefits factor
method estimates for fishing and boating user benefits estimates are closer to
estimates made with the very similar planning standards technique than with
the less similar participation model technique. When fishing and boating
estimates for the three rivers are aggregated, the ranges calculated by dif-
ferent methods become closer. Before totalling, the benefits factor and plan-
ning standards fishing aggregate estimates differ by 38 percent on the low end
and by 13 percent on the high end, and the boating aggregate estimates are
nearly identical on both ends. After totalling, aggregate (fishing and boating)
estimates differ by 20 percent on the low end and by less than nine percent on
E-17
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Table E-3
TOTAL USER BENEFITS FOR ALL METHODS (IN S MILLIONS)
Case Study PIE-C ESTIMATE* SCI ESTIMATE
Mahoning River
(fishing and boating) 1.19 - 1.86
4.47 - 6.43 4.71 - 8.64*
(fishing, boating, swimming) 7.74 - 9.64 6.41 - 8.54**
Black River
(fishing and boating) 2.89 - 3.74
1.79 - 2.82 1.73 - 3.16*
(fishing, boating, swimming) 3.57 - 6.56 2.81 - 3.72**
Monongahela
(fishing and boating) 9.00 - 12.53
12.66 - 17.99 9.30 - 17.82*
(fishing, boating, swimming) 27.31 - 28.54 21.39 - 28.79**
* All PIE-C estimates are preliminary. Some revisions may be made.
AGGREGATE ESTIMATES FOR ALL THREE RIVERS
(in million dollars)
PIErC/1 PIE-C/2 SCI
Fishing 8.2 - 9.9 10.9 - 14.0 7.9 - 15.8
Boating 4.9 - 8.2 8.0 - 13.3 7.8 - 13.8
Total 13.1 - 18.1 18.9 - 27.2 15.7 - 29.6
PIE-C/3 SCI
Fishing,
Boating, 38.6 - 44.7 30.6 - 41.1
Swimming
NOTES OH PIE-C DATA USED FOR SCI ESTIMATES
* For Fishing: used PIE-C estimates for surface acres:
839, 318.6, and 3640 respectively.
For Boating: used PIE-C estimates for river miles (length):
44.5, 16, and 44 respectively; and recreation
days (110).
** For Fishing, Boating, Swimming: used PIE-C estimates for population:
638,500 274,909 2,219,848 individuals
respectively; and then assumed that there
are 3 individuals per household.
E-18
-------
Table E-3 (continued)
BREAKDOWN OF FISHING AND BOATING ESTIMATES
Fishing
Boating
Total
Fishing
Boating
Total
PIE-C/ 1
.25 - .39
.94 - 1.47
1.19 - 1.86
PIE-C/ 1
2.35 - 2.83
.54 - .91
2.89 - 3.74
Mahoning River
PIE-C/ 2
1.91 - 2.42
2.56 - 4.01
4.47 - 6.43
Black River
PIE-C/ 2
.73 - 1.02
1.06 - 1.80
1.79 - 2.82
Monongahela River
SCI
1.38 -
3.33 -
4.71 -
SCI
.53 -
1.20 -
1.73 -
2.77
5.87
8.64
1.05
2.11
3.16
Fishing
Boating
Total
PIE-C/1
5.60 - 6.72
3.40 - 5.81
9.00 - 12.53
PIE-C/2
8.29 - 10.52
4.37 - 7.47
12.66 - 17.99
SCI
6.01 - 12.01
3.29 - 5.81
9.30 - 17.82
E-19
-------
the high end. Thus, when taken as a total, the individually aggregated fishing
and boating estimates are quite close to one another.
The situation with respect to the swimming, fishing, and boating estimates
is similar. Whereas the individual case study estimates differ on the low
and high ends by 21 and 13 percent, 27 and 75 percent, and 28 and one percent,
respectively, the aggregate estimates differ by .only 25 percent on the low
end and by only nine percent on the high end.
E-20
-------
CITED REFERENCES
Adams, J. et al., 1981: "Source of Toxic Pollutants Found in Influents to
Sewage Treatment Plants, Volume 7, Model Evaluation", U.S. EPA Contract No.
68-01-3857 (4 City Study).
Association of Metropolitan Sewerage Agencies, undated. "The East Bay M.U.D.
Experience", Pretreatment Resource Reader. Oakland, California
Association of Metropolitan Sewerage Agencies, undated. "The Rockford
Experience", Pretreatment Resource Reader. Rockford, Illinois
Biener, James A., and Wm. H. Bouma, November 1978b. "An Industrial Waste
Pretreatment Success Story", Public Works, Vol. 109. Grand Rapids, Michigan
Biener, James A., and Wm. H. Bouma, 1978a. "City of Grand Rapids, Michigan!
Program of Industrial Waste Control". Pretreatment of Industrial Wastes,
Joint Municipal and Industrial Seminar.
Boyle, J.D., and P.G. Hall, January 1972. "Small City Solves Seasonal
Industrial Waste Problem", Public Works, Vol. 103. Chehalis, Washington
Bureau of the Census, 1979: Statistical Abstract of the United States, 100th
Edition, (Prepared under the direction of William Lerner), Washington, D.C.
Bureau of National Affairs 1981: BNA Environment Reporter - State Air Lavs.
Bureau of National Affairs 1981: BNA Environment Reporter - State Solid Waste
and Land Use Laws.
Bureau of Naional Affairs 1981: BNA Environmen Reporter - State Water Laws.
Census of Manufacturers, 1972: Water Use in Manufacturing, Special Report
Servies.
Census of Manufacturers, 1977: Water Use in Manufacturing, Special Report
Servies.
Centers for Disease Control 1981: "Sewer Collapse and Toxic Illness in Sewer
Repairmen - Ohio", Morbidity and Mortality Weekly Report, Vol. 3, No. 8,
Atlanta, Georgia.
Comptroller General, 1980: Costly Wastewater Treatment Plants Fail to Perform
as Expected, Report.
Denit, J. 1981: Effluent Guidelines Division, U.S. EPA, Personal
Communications.
Department of Commerce 1977: Annual Survey of Manufacturers.
Department of Environmental Protection, City of Grand Rapids, Michigan,
1979-1980. Fiftieth Annual Reporrt, Wastewater Treatmen Plant.
-------
Derieux 1980: "Operation and Maintenance Data Base", U.S. EPA DWPO-MCD.
Devling, R.T. 1980: "Sewage-Sludge Incineration Raises Air Pollution
Concerns", Water and Sewage Works, Volume 127, No. 10, pp. 26-43.
Dewling, R.T., et al., 1980: "Fate and Behavior of Selected Heavy Metals in
Incinerated Sludge", J. WPCF, Vol. 52, No. 10, p. 2552.
Diamond, W. 1981: "March 1981 Listing of POTWs Requiring Pretreatment",
Personal Conmunications.
Diamond, W., 1981: personal communications (B6-3).
Dixon, F.R. and McCabe, L.J. 1964: "Health Aspects of Wastewater Treatment",
J. Water Pollution Control Federation, 36:984.
Dryden, F.D., 1977. "An Assessment of the Pretreatment Strategy Option Review
Based on Los Angeles County's Operational Experience", paper presented a the
50th Annual Conference of the Water Pollution Control Federation. Los
Angeles, California
Dun and Bradstreet 1981: "Dun's Marketing Service" (Data File).
East Bay Municipal Utility District, 1973 Annual Report Supplement, Special
District One.
East Bay Municipal Utility District, 1979-1980, Special District No. 1
Operating Report.
Elias, E.S., et al 1980: "Worker Exposure to Organic Chemicals at an
Activated Sludge Plant", Wastewater Aerosols and Disease.
EPA 1975: Air Pollution Aspects of Sludge Incineraion, EPA, Cincinnati, Ohio.
PB 259457.
EPA 1981 EPA Permits Division and Reg. PT Coordination (A-4).
EPA R&D Bulletin, January, 1980. Muncie, Indiana
EPA 1978: Sludge Treatment and Disposal, EPA-Cincinnati, Ohio. EPA
625/4-78-012.
EPA 1980: Wastewater Aerosols and Disease, Environmental Research Laboratory.
EPA-600/9-80-028.
Feiler, H., 1980: Fate of Priority Pollutants in Publicly-Owner Treatment
Works: Interim Report, Office of Water and Waste Management, U.S.
Environmental Protection Agency, Washington, D.C.
Forrestell, William L., July 1973. "City-Industry Teamwork Solves Critical
Wastewater Problem", The American City, Vol. 88, No. 7. South Charleston,
West Virginia
-------
Glaser, J.R., and Ledbetter, J.O. 1969. "Air Pollution from Sewage
Treatment", Paper 69-44, presented at the 62nd Air Pollution Control
Association Meeting, New York, June 22-26.
Greenberg, R.R., et al. 1981: "Atmospheric Emissions of Elements on Particles
from the Parkway Sewage - Sludge Incineration". EST 15(1):64-70.
Industrial Permits, Monitoring, and Pretreatment Program, Draft Submission to
EPA, May 1930. Manchester, New Hampshire
Jacknow, J. 1978: "Environmental Aspects of Municipal Sludge Incineration",
Fifth Conference on Acceptable Sludge Disposal Techniques.
"Joint Treatment in the Kalamazoo, Michigan Metropolitan Area", April 1978.
Third Annual Conference on Treatment and Disposal of Industrial Wastewtears
and Residues. Kalamazoo, Michigan
Key, Marcus, M., M.D. et al, eds. 1977: Occupational Diseases; A Guide to
Their Recognition, Revised ed., NIOSH, U.S. Department of Health, Education,
and Welfare, Washington, D.C.
Kominsky 1980: "Nonviable Contaminants From Wastewater; Hexachlorocyclo-
pentadiene Contamination of a Municipal Wastewater Treatment Plant",
Wastewater Aerosols and Disease.
Kulesza, T.J., August 22-24, 1979. "Industrial Pretreatment and Municipal
Wastewater Treatment Plant Sludge Disposal in Philadelphia," paper presented
at the National Pretreatment Symposium. Philadelphia, Pennsylvania
Lanyon, Richard, et al., August 8-9, 1977. "Reduction of Wastes Discharged
from Steel Mills in Metropolitan Chicago Through Local Ordinance
Enforcement", paper presented at the 9th Mid-Atlantic Industrial Waste
Conference.
Larson, R.L., November 1971. "Wastewater Treatment Lures Industry," The
American City, Vol. 86, No. 11. Plant City, Florida
Leith, R. 1981: "Worker's Death in Manhole Probed" Bergen Record, April 5, 6,
7, Bergen .
Letter and attachments from Jay G. Kremer, Head, Industrial Waste Section,
County Sanitation Districts of Los Angeles County, September 3, 1981.
Letter and attachments from Joseph G. Dumas, Senior Environmental Engineer,
East Bay Municipal Utility District, August, 1981.
Letter and enclosures from Richard W. Eick, Plant Operations Manager, Sanitary
District of Rockford, July 31, 1981.
Letter from Cecil Lue-Hing, D. Sc., P.E. Director, Research and Development,
The Metropolitan Sanitary District of Greater Chicago, August 26, 1981.
-------
Lewis, Bay E., "Industrial-Municipal Pretreatment Program Implementation: Can
It Really Be Done?" Paper presented June 19-20, Anaheim, La.?? Orange
County, California
Lue-Hing, Cecil, et al., "Industrial Waste Pretreataent and EPA Cadmium
Limitation", Journal of the Water Pollution Control Federation, Vol. 52
No. 10, October 1980. Chicago, Illinois
Metcalf & Eddy, Inc. 1972: Wastevater Engineering; Collection, Treatment,
Disposal, McGraw-Hill Book Co., N.Y., New York, p. 581.
Metcalf, R.R. 1981: "Incineration is a Waste-Management Alternative", Water
and Sewage Works, Volume 127, No. 10, p. 30.
Metropolitan Sanitary District of Greater Chicago, July 1978. "Development
and Enforcement of the Industrial Waste Control Ordinance at the
Metropolitan Sanitary District of Greater Chicago", Report No. 78-11.
Morbidity and Morbidity Weekly 1981: "Sewer collapse and toxic Illness in
Sewer Repairmen - Ohio", Morbidiy and Mortality Weekly, Volume 20, No. 8, p.
89.
Napolitano,' P.J. and Rowe, D.R., 1966: "Microbial Content of Air Near Sewage
Treatment Planes", Water and Sewage Works, 113:480.
Neufeld, Ronald D., 1975: "Utilization of Biological Sludges for the Removal
and Possible Reclamation of Heavy Metals From Wastewaters," Management and
Disposal of Residues From the Treatment of Industrial Wastevaters,
Proceedings of the National Conference, February 3-5, 1975, Informaiton
Transfer Inc., Washington, D.C.
NIOSH/OSHA 1978: Pocket Guide to Chemical Hazards. Department of Health,
Education, and Welfare, Cincinnati, Ohio, Pub. No. 78-210.
NIOSH 1981: "Interim Reports 1 and 2, Health Hazard Reports", Department of
Health, Education and Welfare, unpublished.
Northrop, R., ett al. 1980: "Health Effects of Aerosols Emitted From an
Activated Sludge Plant", Wastewater Aerosols and Disease.
O'Farrell, T., 1981: personal communication (C-3).
O'Farrell, T. 1981, Office of Water Regulations and Standards, U.S. EPA,
Personal Communications.
Olexsey, R.A. 1974: "Thermal Degradation of Sludges, Proc.", Symposium on
Pretreatment and Ultimate Disposal of Wastewater Solids, EPA and Rutgers
Univ.
Post, N. 1956. "Counteractions of Sewage Odors", Sewage Ind. Wastes, Volume
28, No. 2, p. 221.
-------
Pahren, H. and Jakubowski, W., eds. 1979: Wastewater Aerosols and Disease,
Proceedings of a Symposium, Health Efects Research Laboratory, Cincinnati,
Ohio.
Pollard, F., 1979. "The Detroit Experience", paper presented at the 52nd
Annual Conference of the Water Pollution Control Federation. Detroit,
Michigan
Ongerth, J., and F.B. Dewalle, August 1980. "Pretreatment of Industrial
Discharges to Publicly Owned Treatment Works," Journal of the Water
Pollution Control Federation, Vol. 52, No. 8.
Randall, C.W. and Ledbetter, J.O. 1966: "Bacterial Air Pollution from
Activated Sludge Units", Am. Indust. Hygiene J. 27-506.
Report to Congress, 1977: Waste Disposal Practices and Their Effects on
Groundwater, U.S. EPA Office of Water Supply and Office of Solid Waste
Management Programs.
Saltzberg, E. 1981: "Statistical Assessment of Local Industrial Wastewater
Control Programs" U.S. EPA Contract No. 68-01-5052 (132 POTW Survey), JRB
Associates, McLean, VA.
Shaw, Ray E., Jr., January 1970. "Experience with Waste Ordinance and
Surcharges at Greensboro, N.C.", Journal of the Water Polluion Control
Federation, Vol. 42, No. 1. Greensboro, North Carolina
Shilesky, D.M., Wyatt, J.M. 1976: "Combustion Processing of Sludge Potential
Health and Nuisance Considerations", Third National Conference on Sludge
Management Disposal and Utilization, Miami Beach, Fl. Dec, 14-16.
Southworth, R.M., 1981: "Fate of Priority Pollutants in Publicly Owned
Treatment Works"; Final Report to be published, Office of Water and Waste
Management, U.S.Environmenal Protection Agency, Washington, D.C.
State Program Submissions.
Sutton, G.P. 1971. "Odors and Air Pollution from the Treatment of Municipal
Wastewater", Reprint, Air Pollution Control Assoc. presented at the 64th
Annual APCA Meeting, Atlantic City, NJ, June 27-July 2. Pages 71-103.
"The Enforcement of An Industrial Waste Ordinance in a Large Metropolitan
Area", April, 1978. Third Annual Conference on Treatment and Disposal of
Industrial Wastewaters and Residues.
U.S. EPA 1975: "Air Pollution Aspecs of Sludge Incineration", EPA PB-259,
457.
U.S. EPA 1974: "Background Information on National Emission Standards for
Hazardous Air Pollutants - Proposed Amendments to Standards for Asbestos and
Mercury", EPA 450/2-74-009a.
-------
U.S. EPA 1970: "Fate of Priority Pollutants in Publicly Owned Treatment
Works", EAP 440/1-80-301.
U.S. EPA 1974: Federal Register, Vol. 39, p. 9319, March 8, 1974.
O.S. EPA 1980: "1980 Seeds Survey", Office of Water Program Operations Data
File.
U.S. EPA 1981: "Permit Compliance System", Construction Grants Data File.
U.S. EPA 1981: "Pretreatment Program Status; Permits Division". U.S. EPA
Office of Water Enforcement and Permits, Memo, August 1, 1981.
U.S. EPA 1979: Sludge Management: A Comparison Between State and Proposed
Federal Guidelines, EPA Contract No. 09075-068-003.
U.S. EPA 1981: "STOHET", Office of Water Regulations and Standards Data File.
U.S. EPA 1977: U.S. EPA Contract No. 68-01-5052 (77 POTW Study).
Versar, Inc., 1974: "A Study of Pesticide Disposal in a Sewage Sludge
Incinerator", Monthly Progress Report, EPA Contract No. 68-01-1587, Sept. 9.
Walker, W.H., 1968.
WPCF 1981: 15th Annual Safety Survey; Deeds and Data,, Vol. 17, No. 12, pp.
1-3, Water Pollution Control Federation, Washington, D.C.
Wright, Eugene G., et al., 1978. "The Industrial-Municipal Pretreatment
Program for the City of Chattanooga", paper presented at the 51st Annual
Conference of the Water Pollution Control Federation.
Yost, K.J., et al., undated. "Heavy Metal Sources and Flows in a Municipal
Sewage System", Purdue University. Kokomo, Indiana
-------
OTHER SOURCES
American Paper Institute, Inc., 1981: Letter of Comment on Clean Water Act -
General Pretreatment Guidelines.
API/NFPA (American Paper Institute/National Forest Products Institute), March
13, 1981: Letter of Comment on General Pretreatment Regulations for
Existing and New Sources.
AMSA (Association of Metropolitan Sewerage Agencies), March 17, 1981 and May
19, 1981: Comments on General Pretreatment Regulations.
MVMA (Motor Vehicle Manufacturers Association of the United States, Inc., May
15, 1981: Comments on General Pretreatment Regulations for Existing and New
Sources.
Burlington Industries, Inc., May 1, 1981: Comments on General Pretreatment
Regulations.
ATMI (American Textile Manufacturers Institute, Inc.), April 30, 1981:
Comments on General Pretreatment Regulations.
CACI (Chicago Association of Commerce and Industry), April 30, 1981: Comments
on General Pretreatment Regulations for Existing and New Sources.
ACS (American Chemical Society), May 19, 1981: Comments on General
Pretreatment Regulations for Existing and New Sources.
DuPont de Nemours and co., April 30, 1981: Comments on General Pretreatment
Regulations for Existing and New Sources.
Peanut Butter and Nut Processors Association, April 30, 1981: Comments on
General Pretreatment Regulations for Existing and New Sources.
National League of Cities, May 14, 1981: Comments on General Pretreatment
Regulations for Existing and New Sources.
National Cotton Council of America, April 29, 1981: Comments on General
Pretreatment Regulations for Existing and New Sources.
United States Steel Corporation, June 3, 1981: Comments on General
Pretreatment Regulations for Existing and New Sources.
Atlantic Richfield Co., April 30, 1981: Comments on General Pretreatment
Regulations for Existing and New Sources.
Interlak, Inc., May 8, 1981: Comments on General Pretreatment Regulations for
Existing and New Sources.
FMC Corporation, May 7, 1981: Comments on General Pretreatment Regulations
for Existing and New Sources.
-------
NAMF (National Association of Metal Finishers, April 30, 1981: Comments on
General Pretreatment Regulations for New and Existing Sources.
American Institute of Chemical Engineers, May 8, 1981: Comments on General
Pretreatment Regulations for Existing and New Sources.
Association of State and Interstate Water Pollution Control Administrators,
May, 1981: Comments on General Pretreatment Regulations for Existing and
New Sources.
Industrial Facilities Database
40 POTW Study
ADL Study - Arthur D. Little, 15 POTW Study
Effluent Guidelines Data on Categorical information
ECD - Development Documents
JSB - 65 POTW Study
Environmental Regulations and Acts
John Pai - Construction Grants Estimates
State Pretreatment and Regional Pretreatment Coordinators
Association Metropolitan Sewer Authorities - Resource Reader
D.S.G.S. Water Quality Database
RCRA - Regulatory Background Documents
Elements of an Industrial Waste Control Program, Burns & Roe, 5/1978
Analysis of PL 92-500, David Gushee
Pretreatment Issues and Public Response - EPA, 9/77
Application of Sludge to Land Used for Production of Food Chain Crops for EPA
1/70
Municipal Pretreatment Guidance Program - USEPA, 9/80
Industrial-Municipal Pretreatment Program Implantation, 3/80 MSD-Chicago
Legislative History of the CWA of 1977. 10/78
Options for an EPA Policy on Centralized Wastewater Treatment for EPA, 2/81
Sludge Management: Compairson Between State and Proposed Federal Guidelines -
for EPA, 10/79
Information on: Proposed General Pretreatment Regulation, EPA Document, 3/77
Local Pretreatment Program: Requirements Funding Cost, Case Studies, for EPA,
8/79
Toxic Survey for POTW Plants - for EPA, 6/78
Codisposal for EPA 11/79
Social and Economic Benefits and Costs of the Implementation of the
Pennslyvania Water Quality Standards on the Mahonig Riber - EPA Document,
5/77
Powers of the State of Kentucky in Implementing an Effluent Tax as a Part of
an Interstate Ohio River Basin Water Pollution Control Program - for DOT
1974
OAE - Economic Development Documents
Municipal Sludge Management for EPA, 10/78
Water Quality Analyses for EPA, 2/80
Hazardous Waste Generation and Commercial Hazardous Waste Management Capacity
- EPA, 12/80
Comprehensive Sludge Study Relevant to Section 8002(g) RCRA - SCS Engineers
Waste Management Practices for Pharmaceutical Industry, EPA
-------
Environmental Impact Statement - Criteria for Classification of Solid Waste
Disposal Facilities and Practices, 12/79
State and Naitonal Water Use Trends to the Year 2000, Congressional Report
5/80
Pollutants Threaten Drinking Water from Underground, National Journal, 8/80
Surface Impoundments and their Effects on Groundwater Quality in the United
States, SPA document, 6/78
Environmental Assessment of Subsurface Disposal of Municipal Wastewater
Treatment Sludge - EPA, 9/77
Guidance for Panning the Localtion of Water Supply Intake
Groundwater Contamination - US, U.S.G.S. DOI, 1973
Effects of Septic Tank Systems on Groundwater Quality - National Center for
Ground Water Research, 1980
Effects of Wastewater Ponds on Groundwater Quality - National Center for
Ground Water Research, 1980
Effects of Land Disposal of Sewage Sludge on Groundwater Quality - National
Center for Ground Water Research, 1979
Report to Congress - Waste Disposal Practices and their Effects on
Groundwater, EPA, 1/77
Overview: Costs, Benefits and Problems of Utilization of Sludge, John Walter,
EPA
Federal Register: Water Quality Criteria, 12/80
State Water Quality Criteria
-------
ASSESSl-EST OF THE IMPACTS
OF i:~"37?.I---l DISCHARGES
PUBLICLY C-V^EJ T-.ZAiyi:" WORKS
APPEND1CIIS
FINAL
Submitted to the Environmental Protection Agency
_D) ASSOCIATES. INC.
Subsidiary of Science Applications, Inc.
'V"X;..
-------
•"> f~ r o c
t o bob
ASSESSMENT OF THE IMPACTS
OF INTUSTRIAL DISCHARGES
ON PUBLICLY OWNED TREATMENT WORKS
APPEND1CIES
FINAL
November 16, 1981
Prepared by:
JRB Associates
Assisted by:
AEPCO, Inc.
Sobotka and' Company, Inc.
and
SCS Engineers
ETC, Inc.
Burns and Roe
-------
TABLE OF CONTENTS - APPENDICIES
Page
APPENDIX A - RATIONALE FOR PRETREATMENT PROGRAM. A-l
APPENDIX 3 - DOCUMENTATION OF PROBLEMS AT POTWs 3-1
APPENDIX C - POTW MODEL C-l
APPENDIX D - BENEFITS ANALYSIS D-l
APPENDIX E - MONETIZING BENEFITS E-l
BIBLIOGRAPHY
-------
INTRODUCTION TO APPENDICES
The appendices provide the details of the many analyses that were
performed for the Regulatory Impact Analysis (RIA). Each appendix includes a
discussion of its data source, assumptions, and analytical methods, and is a
support document for the RLA report.
Appendix A includes background information and thought processes which
have resulted in the initiation and development of nationwide pretreatment
programs. Consideration is given to the impact of industrial effluents on
POTWs' performance, an assessment of Federal laws and regulations, the
characteristics of POTWs subject to a pretreatment program, progress made to
date by Federal, State and municipal governments toward implementation, and a
summary assessment of State regulations affecting industrial waste control at
POTWs.
Appendix B contains an in-depth study of technical problems associated
with the operation of POTWs. This pretreatment program was developed
initially to prevent upset problems caused by industrial waste at a POTW. The
appendix reviews studies on POTWs performance, operation and maintenance,
presence of toxics, air pollution, and worker health and safety. Funded
primarily by U.S.EPA, this review provides a sound basis for evaluating the
qualitative impact of the various pretreatment strategies in the main report.
Theanalyses and results from Appendix B also provide background information
and a quantitative basis for several key POTW computer model assumptions (see
Appendix C).
Appendix C includes the overview, development, program documentation and
complete results from a computerized mathematical model constructed to assess
the environmental, cost impacts, and benefits of pretreatment program alter-
natives. The POTW model reviews each of the 2,000 POTWs requiring
pretreatment, determines and quantifies the pretreatment options for each, and
then aggregates the results to estimate national impacts.
-------
Appendix D assesses the benefits associated with improved water quality.
The object is to provide theoretical benchmarks for estimating alternate
benefit measures for diverse water uses.
-------
APPENDIX A
RATIONALE FOR PRETREATMENT PROGRAM:
BACKGROUND ON POTW PERFORMANCE, LEGAL ASSESSMENT
AND STATE AND FEDERAL PROGRAMS SUMMARY
INTRODUCTION
The purpose of Appendix A is to provide background and rationale for the
pretreatment program. The appendix is divided into five sections:
o A-l, Impact of Industrial Effluents on POTWs Performance
o A-2, Federal Legal Assessment
o A-3, POT/? Demographics
o A-4, Progress Made in the Federal 403 Program
o A-5, Summary Assessment of State Environmental Regulations Affecting
Industrial Waste Control at POTWs
The Federal 403 Pretreatment Program was developed in response to the
upset, interference, and bypass problems that were associated with industries
discharging into POTWs. The Technical Problems Section, A-l, summarises the
typical problems associated with industrial pollutants.
POTW operation and industrial wastewater discharge are primarily regu-
lated under the Clean Water Act (CWA); however, many of the other major
environmental acts have authority to regulate various aspects of POTW oper-
ations. The Federal Legal section, A-2, provides a brief summary of each of
the major environmental acts and highlights their relation to the pretreatment
program. The purpose of Section A-2 is to provide a basis for understanding
the reasons Congress directed EPA to develop pretreatment regulations and to
lay the groundwork for assessing whether other environmental acts have the
regulatory authority to carry out the intent of the pretreatment regulations.
A-l
-------
Of the 15,000 POTWs in the country, 2,000 are required to have pretreat-
ment programs under the General Pretreatment Regulations. These POTWs ara
distributed more or less uniformly throughout the U.S. Section A-3 discusses
geographic distribution, size, and other characteristics of the 2,000 POTWs.
The Federal 403 Program has been in effect since February 1978. Since
then, funds have been spent by governnent and industry to comply with these
regulations. Section A-4 compiles data on the costs of program development
x
and implementation at the municipal, State and Federal level. In addition, it
estimates the number of pretreattnent programs currently in effect as well as
the status of pretreatment program implementation at the 2,000 POTWs.
Section A-5 characterizes the role of the States in instituting environ-
mental controls. It also provides data for assessing likely State initiatives
and actions in the absence of a Federal pretreatment program.
A-2
-------
A-l. IMFACT OF INDUSTRIAL EFFLUENTS ON POTW'S PERFORMANCE
BACKGROUND
Currently, 26 billion gallons of sewage are generated each day in the
United States and discharged to POTWs for treatment and disposal. Of this
total flow, 83% consists primarily of biodegradable human waste products from
residential and commercial discharges. The remaining 17% (approximately 4.4
billion gallons) of the total flow is attributable to industrial discharges.
The POTWs that receive and treat these wastewaters are designed to remove
biodegradable organics, suspended solids, and pathogens, normally using
primary and/or secondary treatment to achieve specified performance standards.
These performance standards, more commonly referred to as secondary treatment
standards, limit the quantity of 5-day biochemical oxygen demand (BOD^),
suspended solids (SS), and pH allowed in the discharge to surface waterways
and are enforced through POTW National Pollutant Discharge Elimination System
(NPDES) permits.
The unit operations most commonly used to meet secondary treatment
standards at POTWs are activated sludge and trickling filter operations.
Primary treatment to remove suspended and floating solids is achieved in both
operations by gravity settling and/or by chemically aided coagulation/
precipitation. Additional BOD. and suspended solids (SS) removal is achieved
by allowing acclimated microorganisms to convert much of the remaining organic
material to food and energy. These organisms are either present in a liquid
phase, as in activated sludge, or attached to a growth medium such as rocks or
plastics, as in the trickling filter operation.
The constituents including screenings, grit, scum and sludge removed by
these operations are important waste products of the treatment process. The
resulting sludge is usually in the form of a liquid or a semisolid liquid,
which typically contains 0.25 to 12% solids. The sludge is usually thickened,
and it is then stabilized to (1) reduce pathogens, (2) eliminate offensive
odors, and (3) inhibit, reduce, or eliminate the potential for putrefaction
A-3
-------
(Metcalf and Eddy 1972). The technologies currently available for sludge
stabilization include (1) chlorine oxidation, (2) lime stabilization, (3) heat
treatment, (4) anaerobic digestion, and (5) aerobic digestion. The latter two
are the roost conznon stabilization processes used at POTWs. Byproducts of
these two stabilization processes include water, carbon dioxide, acaaonia,
methane, and a solid material suitable for disposal. The liquid byproducts
can be recycled in a POTW for treatment and the gaseous byproducts can be
vented and used for fuel. The solid material is most commonly disposed of in
a sanitary landfill or by land spreading.
When properly designed, operated, and maintained, activated sludge and
trickling filter unit operations, coupled with aerobic and anaerobic digestion
processes, are capable of removing 55% or more of the influent 30D- and S3.
This is an important consideration to POTWs, which must consistently meet the
requirements of its NPDES permit.
However, a recent study has shown that a significant percentage of POTWs
designed to meet secondary treatment -standards are not consistently meeting
their NPDES permit limitations for conventional pollutants and pH (Comptroller
General 1980). GAO'a random sample of 242 plants in 10 states showed that
87% of the plants were in violation of their permit; 311 were, in GAO's
opinion, in serious violation. Additionally, because of water quality
considerations, toxic pollutants and nutrients (e.g., heavy metals and
phosphate anion) are being regulated through the NPDES permit, and these
limitations are also being violated.
One reason given for noncompliance is industrial waste discharges.
Industrial waste discharges, although contributing a small percentage of the
total flow to POTWs contain significantly higher concentrations of toxic and
conventional pollutants than do residential and commercial discharges.
When industrial wastewater is discharged to a POTW, it can contribute to
four technical problems: (1) POTW operational problems, (2) POTW sludge dis-
posal problems, (3) POTW effluent water quality problems and (4) POTW worker
safety and health. These problems are discussed briefly in the following
A-4
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SLUDGE MANAGEMENT PROBLEMS
The removal of some toxic industrial pollutants is incidental to the
basic POTW treatment operation. Toxic pollutants, particularly heavy metals,
enter POTW sludge and can contribute significantly to sludge management
problems.
The two primary methods for disposing of POTW sludges are landfilling and
landspreading. They are the most widely used methods primarily because they
are the easiest and most cost-effective means of disposal. However, if the
POTW sludge contains high quantities of toxic pollutants, these methods of
disposal may be precluded in order to avoid leaching of toxic pollutants to
groundwater or surface water and uptake of heavy metals into crops and the
food chain. In turn, this could lead to increased disposal costs because of
the need to use alternative disposal methods such as incineration or
pyrolysis.
Conversely, toxic pollutants can adversely affect the sludge digestion
process. Concentrations of heavy metals in the sludges can increase from
2,000 to 10,000 times higher than the surrounding liquid heavy metal
concentration (Feiler 1980, Southworth 1981). If not acclimated to such high
concentrations of particular pollutants, the bacterial strain used for sludge
digestion can be inhibited or destroyed.
WATER QUALITY PROBLEMS
Many toxic industrial pollutants are inadequately treated at POTWs and
consequently pass through the treatment process into the receiving water body.
This pass through of toxic pollutants could jeopardize the attainment of water
quality goals and increase the cost of treating drinking water downstream.
Toxic pollutants entering POTWs can also be transformed to another, more
toxic pollutant by a particular treatment process. For example, according to
Glaze et al. (1975) many new chlorinated organics including chloroform can be
formed during the final effluent chlorination.
A-5
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sections. Specific documentation of these problems can be found in Appendix
B.
OPERATIONAL PROBLEMS
Two primary operational problems at POTWs that are caused by industrial
waste discharges POTW process upsets or interferences leading to a loss of
BOD,, SS, and pH treatment efficiency and hydraulic and/or organic overloading
resulting in reduced treatment efficiency. Each can be controlled by an
effective industrial waste pretreatment program.
POTW process upsets or interferences can be caused by continuous or slug
discharges of a toxic pollutant that is incompatible with the biological
treatment process. Toxic pollutants can retard the normal growth patterns of
the microbes that perform the treatment process if the microbes are not
acclimated to the pollutants. Additionally, toxic pollutants can destroy the
microbial population so that no treatment is provided.
Hydraulic overloads can be caused by one of three conditions: (1) storm
events in combined sanitary/stormwater sewer systems, (2) excessive infiltra-
tion/inflow, or (3) industrial slug discharges. Hydraulic overloads reduce
the detention time within a POTW, thereby reducing removal efficency.
Separating combined sewers and relining sewer pipes, although expensive, can
solve the first two overload conditions. Slug discharges can be corrected by
providing equalisation facilities at the source of discharge to more evenly
distibute over time the volume and concentration of the industrial discharge.
Organic overloads are normally associated with industries discharging
compatible pollutants that are of such strength and volume that the POTW
design capacity is exceeded. Pretreatment at the source of the discharge to
levels that protect the design loading capacity of the POTW will prevent
organic overloads. Industrial pretreatment will also protect any existing
unused reserve capacity at the POTW, thereby allowing future growth.
A-6
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For other toxic pollutants, such as cadmium and zinc, removal efficien-
cies are low. In both cases, toxic pollutant treatment at a POTW does not
attain the level of removal efficiency achieved by the systems typically
employed by direct industrial discharges. This passthrough of toxic pollu-
tants may lead to an NPDES permit violation (where toxic effluent limits have
been imposed), may result in water quality standard violations, and may
jeopardize designated uses of the receiving stream.
POTW Operator Safety and Health
Two additional concerns may be attributed to industrial discharges to
POTWs. Some instances of sewage treatment personnel suffering illness and
death as a result of exposure to toxic pollutants have been reported. For the
most part, personnel affected have been exposed to concentrated toxic
chemicals in the anaerobic environment of sewage collection systems. However,
industrial slug loads of volatile toxic organic chemicals have also caused
worker health and safety problems within POTWs. Finally, the air pollution
resulting from the volatilization and aerosolization of toxic pollutants
discharged by industry may pose health and environmental risks.
SUMMARY
Industrial discharges of toxic and conventional pollutants have been
documented as the important cause of the following problems at POTWs:
'o Process interference and upset
o Organic overloading, loss of treatment efficiency, and violation of
NPDES permit limitations
o Heavy metal contamination of sludge, limiting available disposal
options
o Passthrough of untreated pollutants into receiving streams.
Industrial discharges contribute to these problems because POTWs are
primarily designed to remove conventional, not toxic pollutants. Most removal
of toxics that occurs is incidental to the treatment process.
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A-2 FEDERAL LEGAL ASSESSMENT
The preceeding discussion in Appendix A-l introduced Che kinds of environ-
mental and operational problems that POTWs may experience in conjunction with
their treatment of industrial wastes. The following section outlines the
legislative and regulatory remedies developed by Congress and EPA to minimize
these problems. The principal Federal strategy for prevention of pass-
through, sludge contamination, and interference is embodied in the National
Pretreatment Program. The history, scope, and workings of its components, the
General Pretreatment Regulations and Categorical Pretreatment Standards for
New and Existing Sources, are presented to provide a framework for estimating
the impacts of this program on States, municipalities, industries and the
public.
In addition, other provisions of the Clean Water Act and several other
environmental laws affect industrial waste control at POTWs. The procedures,
rationales, and interrelationships of the Clean Water Act; the Resource
Conservation and Recovery Act; the Safe Drinking Water Act; the Toxic
Substances Control Act; the Marine Protection, Research, and Sanctuaries Act;
and the Clean Air Act are analyzed to establish the current regulatory
environment affecting the National Pretreatment Program. Table A2-I, a
summary overview of key statutory and regulatory provisions, is presented at
the end of this discussion.
BRIEF LEGISLATIVE AND REGULATORY HISTORY OF THE PRETREATMENT PROGRAM
Because the U.S. Congress was concerned with possible problems associated
with indirect dischargers, they included a mechanism, Section 307(b) and
307(c) of the Federal Water Pollution Control Act of 1972, that required the
EPA administrator to establish pretreatment standards
"...to prevent the discharge of any pollutant through
treatment works... which pollutant interferes with,
passes through or otherwise is incompatible with such
works."
A-3
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The original regulations (40 CFR 128) promulgated under this authority in
1973 required major indirect industrial dischargers to comply with effluent
guidelines that define the best practicable treatment for removal of incompa-
tible pollutants. (The regulations anticipated that specific provisions in
effluent guidelines would be applicable to pretreatment.) However, tech-
nological uncertainties and administrative delays hindered the promulgation of
effluent guidelines and pretreatraent standards and were one of the bases for
the National Resources Defense Council (NRDC) lawsuit against EPA in 1976.
As a result of this suit, the toxics Settlement Agreement obligated EPA to
develop distinct performance-based pretreatment standards for the same
21 industries and 129 industries and 129 priority pollutants for which "Best
Available Technology" (BAT) Standards were to be developed for indirect
dischargers. The designation of categorical industries has now been expanded
to cover 34 industries. This parallel regulatory approach was incorporated in
the Clean Water Act (CWA) Amendments of 1977. To date, two categorical pre-
treatment standards have been developed, one for the electroplating industry
and one for the timber products processing industry. The electroplating
standards (40 CFR 413) were first issued on September 7, 1979, have gone
through three corrections, and were amended on January 28, 1981. (Certain
portions of the electroplating regulations pertaining to integrated facilities
as opposed to the smaller job shops are not yet in effect.) The timber
products processing pretreatment standards (40 CFR 429) were issued on
January 26, 1981 and are currently in effect.
To provide the administrative context and procedures for the enforcement
of these categorical pretreatment standards and to otherwise protect POTWs
from interference, passthrough, and sludge contamination, the General Pre-
treatment Regulations (40 CFR 403) were issued on June 26, 1978. Simplifying
amendments were issued on January 28, 1981, but their effective date was
postponed indefinitely pending submission of a RIA on the National Pretreat-
ment Program to the Office of Management and Budget, as required under
Executive. Order 12291. Until the outcome of this regulatory review, expected
in April of 1982, the 1978 regulations will remain in effect. In the interim,
several trade associations, industries, and the NRDC have filed suit, either
for review of the amendment package or to challenge its suspension.
A-9
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SCOPE OF THE PRETREATMENT PROGRAM UNDER 40 CFR 403
The National Pretreatinent Program represents an integrated and inter-
governmental approach to the control of the environmental and operational
problems discussed above. POTWs that have disorders related to industrial
waste are afforded regulatory tools and cross-media planning mechanism to
develop local solutions. The core of the program requires industries to
pretreat wastewater so that discharges to POTWs have a minimal impact on
operations and the environment. The General Pretreatment Regulations set
forth prohibited discharge standards intended to protect POTWs from non-
domestic pollutants causing interference, passthrough, and sludge con-
tamination. General guidance is given for parameters such as acidity,
flammability, corrosivity, and heat. Localities are authorized to develop and
enforce specific effluent limits for prohibited discharges from industrial
users, and additionally to impose limits which ensure compliance by priority
pollutant discharges with categorical pretreatment standards.
Enforcement of both prohibited and categorical pretreatment standards is
accomplished by a three-tiered administrative scheme. First-line responsi-
bility rests at the local level. POTWs with total flows greater than 5 MGD
and that receive wastes from industries subject to national pretreatment
standards are required to develop and operate pretreatment programs. Compli-
ance schedules have been written into NPDES permits to ensure that these major
POTWs will have pretreatment programs by July 1, 1983. POTWs with total flows
less than 5 MGD may also be required to establish pretreatment programs were
warranted when special problems associated with industrial influent exist. In
either case, NPDES states may relieve localities of program development
responsibilities if they choose to operate pretreatment programs at the state
level in lieu of operation by municipalities. Connecticut and Vermont have
exercised this option. All NPDES states that develop approvable state
pretreatment programs will receive full EPA program delegation. EPA Regional
Offices will implement pretreatment programs for NPDES states that do not
submit state pretreatment program plans and for non-NPDES states. All
pretreatment standards including those developed by localities are ultimately
enforceable by the Federal Government against industrial users pursuant to
Section 309(f) of the Clean Water Act.
A-10
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In developing pretreatment programs, municipalities survey industrial
users and identify the types and magnitudes or industrial pollution in POTW
influents. To set prohibited discharge standards interference, passthrough,
and sludge contamination problems are analyzed, and effluent limitations are
developed to control these problems. All categorical industries discharging
to POTWs must be required to comply with effluent limitations set in the
applicable Pretreatment Standards for New and Existing Standards. Permitting,
monitoring, and enforcement mechanisms are developed to implement these
limitations. POTWs then work with existing industrial users to secure the
installation of pretreatment technologies or process changes to control
excessive discharges. New industrial contributors will be required to
incorporate pretreatment technologies into facility design before being
allowed to connect to the POTW system. POTWs with high removal efficiencies
for regulated pollutants may also pass on removal credits to industrial users,
after EPA/State approval. Variances from categorical standards may also be
granted by EPA for firms with fundamentally different factors and adjustments
approved where toxics are present in industrial user intake water.
In addition to the above standards and mechanisms for regulating
industrial pollutants in wastewater discharged to POTWs, the General Pre-
treatment Regulations encourage localities and states to consider impacts on
other environmental media in their pretreatment strategies. In making sludge
management decisions, POTWs must comply with the Resource Conservation and
Recovery Act (RCRA) and the Clean Air Act (CAA), and a violation of either
statute resulting from an industrial discharge constitutes interference under
the regulations. Given the profound effects that pretreatment programs have
on industrial and municipal sludge generation, POTWs and states are in a
position to coordinate water pollution control with local and statewide
residual waste planning activities. POTW pretreatment programs must also be
consistent with Section 208 water quality management plans.
-------
OTHER CWA PROVISIONS AFFECTING POTWS
Section 301
While the National Pretreatnent Program is the focal point for con-
trolling industry-related problems at POTWs, several other CWA provisions
affect the posture that POTWs assume in exercising pretreatraent authority. As
mentioned earlier, existing and new indirect dischargers are subject to
pretreatraent standards covering 129 toxic pollutants and 34 categorical
industries. Toxic linits for the same industries and pollutants are also to
be set for direct dischargers to U.S. waters. Pursuant to Sections 301 and
304 of the CWA industries must meet Best Available Technology Sconoaically
Achievable (BATSA or BAT) for toxic pollutants by July 1, 1984. An approx-
imate parity must be established between pretreatment standards and BAT
standards in terms of ultimate effluent discharged to navigable waters: an
indirect discharger's pollutant removal efficiency required by pretreatment
standards combined with the subsequent treatment by the POTW should result in
approximately the same removal efficiency as that of a direct discharger. If
there is an imbalance in the strictness of either control, a shift in dis-
charge status may occur; i.e., if pretreatraent requirements are less stringent
than direct discharger BAT requirements, direct dischargers might connect to a
POTW system or vice versa. The interaction of these two toxic control mech-
anisms may have a significant impact on POTW wasteloads, operating costs, and
races.
Direct dischargers (industries and POTWs, among others) to the nation's
waters must acquire an NPDES permit pursuant to Section 402 of the CWA. These
permits, written either by approved NPDES states (33) or the EPA Regions,
contain specific effluent limits for point sources to ensure compliance with
applicable technology-based performance standards. According to Section 301
of the CWA, standards for industry include meeting Best Practicable Technology
(BPT) by 1977 and BCT for conventionals and BAT for toxics by July 1, 1984.
Section 301 also mandates performance standards for POTWs: implementation of
secondary treatment by 1977 as established by Section 304(d) and Best
Practicable Waste Treatment Technology (BPWTT) by 1983. Where effluent
guidelines have yet to be developed, as is the case for most toxic pollutants
A-12
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and categorical industries, NPDES permit writers must use Best Engineering
Judgement (BEJ) to set permit effluent limits.
Sections 302 and 303
In addition, the NPDES system imposes more stringent water quality-based
standards for point sources. Unlike the technology-based standards discussed
above, which focus on removal technologies, vater quality standards are
related to the ambient water quality of receiving streams. Standards are set
to protect water quality so that the designated uses of stream segments can be
maintained. Pursuant to Section 302 of the CWA, EPA may establish effluent
limits for a point source (or sources) to protect public water supplies,
agricultural and industrial uses, fish and wildlife, and recreational
activities. EPA has published water quality criteria for 64 toxic pollutants
(45 FR 79318, November 28, 1980). Under Section 303 of the CWA, states are
required to develop water quality standards to protect intrastate water uses.
If a state fails to submit water quality standards, EPA will set the
standards. In addition to technology-based standards, any applicable water
quality standard will determine the extent of pollutant reduction required for
a point source in the NPDES permit, if more stringent than the
technology-based standard.
Sections 402 and 201
An interdependent relationship exists between the National Pretreatment
Program and the NPDES permitting system (Section 402 of the CWA). On the one
hand, local pretreatment programs are implemented to enable POTWs to meet
technology based standards or water quality standards. On the other hand,
NPDES permits may be used to compel municipalities to develop pretreatment
programs by making pretreatment programs an NPDES permit condition for munici-
palities needing pretreatment. The NPDES permitting system is a pollution-
reduction-forcing process, and local pretreatment programs are an integrated
tool for achieving this reduction. Ideally, applying and enforcing conven-
tional and toxic limits in POTW NPDES permits should prevent the passthrough
of industrial effluents into national waters. However, the National
Pretreatment Program also provides municipalities with a sophisticated
-------
regulatory tool and a national mandate to control industrial waste
passthrough. Additionally, protection is provided from interference, sludge
contamination, and worker injuries, which might not constitute violations of
POTW NPDES permits.
Two other provisions of the CWA influence POTW pretreatment programs.
Section 403 regulations require the development of pretreatraent programs. The
construction grants program under Section 201 of the CWA makes the costs
incurred in developing such pretreatment programs eligible for 75% Federal
funding, thus lessening state and local financial burdens. In fact,
recognizing that POTW pretreatment programs protect POTWs, thereby protecting
Federal investment in wastewater facilities made under the construction grants
program, EPA made the development of a pretreatment program a condition for
the award of any grant or modification for sewage treatment plant construc-
tion. This requirement was recently eliminated as part of the overall EPA
effort to simplify grant processing.
The National Pretraatment Program may also reduce Federal expenditures
for the entire construction grants program. Without the Program's standards
and procedures for controlling industrial waste problems, POTWs may eventually
choose or be forced to install advanced wastewater treatment technologies to
meet NPDES effluent limits. Given the dilution of industrial wastes that
occurs at POTWs, such systems may be inefficient, in addition to being
extremely costly. Current Congressional concern over the return on the
Federal investment in Advanced Wastewater Treatment (AWT) plants under the
construction grants program suggests that reliance on and enhancement of POTW
performance beyond secondary treatment to control industrial wastes may be
politically and economically unrealistic.
POTW costs associated with operating POTW pretreatment programs are not
eligible for Federal funding, and Section 403 regulations encourage municipa-
lities to recover costs by imposing industrial use charges. States receive
grants under Section 106 of the CWA to administer pollution control programs.
These funds may also be used to administer state pretreatment programs.
Section 205(g) funds may also be used for these purposes.
A-14
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Section 405
One final section of Che CWA Section 405, has a significant impact on
state and POTW pretreatment programs and operations. Section 405 requires EPA
to establish regulations that provide guidelines for the disposal and utiliza-
tion of sewage sludges. Section 405 calls on states and/or EPA to regulate
this activity in the POTW NPDES permit. In amending the Federal Water
Pollution Control Act, Congress tied pretreatment standard removal credits in
Section 307 with an ability to comply with the sludge disposal requirements of
Section 405. Section 405 in turn invokes the requirements of other statutes
and regulations Chat protect the numerous environmental media affected by the
various sludge disposal methods. Under the joint authority of 4004 of RCRA
and Section 405 of the CWA, limits have been set for cadmium and polychlori-
nated byphenyls (PCB's) in solid waste that is intended for application on
lands used for producing food-chain crops (40 CFR 257). Entitled "Criteria
for the Classification of Solid Waste Disposal Facilities and Practices,"
these regulations also provide guidelines for the disposal of sludge inciner-
ator ash, sludge in landfills, sludge in surface impoundments, and sludge that
is landspread for nonfood-chain application. They also contain guidelines for
protecting groundwater, endangered species, flood plains, and surface waters,
and for reducing the transport of pathogens. Under Section 405 EPA has also
issued a preproposal draft to regulate the distribution and marketing of
sludge and sludge products. This consolidated regulation will set standards
for the sale of sludge intended for use as fetilizer, or as a soil
conditioner. Because pretreatment standards are designed to prevent sludge
contamination, they are an integral part of the strategy to assist POTWs in
meeting sludge disposal requirements under RCRA and Section 405 of the CWA.
OTHER STATUTES AFFECTING INDUSTRIAL WASTE CONTROL AT POTWS
Other environmental statutes and regulations require POTWs to control the
industrial wastes they receive, thereby enhancing the strategic importance of
the National Pretreatment Program. The CAA requires POTWs that choose to
incinerate or dry their sludge to meet National Ambient Air Quality Standards
(NAAQS) and New Source Performance Standards (NSPS) for sulfur dioxides,
particulate matter, carbon monoxide, hydrocarbons, nitrogen dioxide, ozone,
A-15
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and lead, and National Emission Standards for Hazardous Air Pollutants
(NESHAPS) for mercury. Further, the Toxic Substances Control Act (TSCA)
specifies incineration practices for sludges containing certain levels of
?C3's. As sludge quality is improved as the result of pretreattaent programs,
the efforts required to meet air standards should decrease. The absence of
controls placed on emissions resulting from the volatization of pollutants
within the treatment facility is a noticeable omission from current air
regulations.
The ban on ocean dumping of municipal sludges which do not meet stringent
disposal criteria, scheduled to take effect in December 1981 under the Marine
Protection Research and Sanctuaries Act, has forced municipalities to find
alternate sludge disposal methods. The improvement of sludge quality afforded
by pretreatment has eased this transition for cities such as Philadelphia.
The Safe Drinking Water Act establishes maximum contaminant levels for
substances such as heavy metals in drinking water. POTWs may affect drinking
water sources in a number of ways. A considerable portion of the nation's
drinking water sources are surface waters into which POTWs discharge.
Reducing the toxic chemicals discharged to these waters should ease the water
treatment obligations of municipalities. Leaching of toxic pollutants from
municipal sludges to groundwater will also be reduced as sludge quality is
improved. . .
A final area lacking any regulatory protection outside the pretreatment
program is worker health and safety at the POTW. The Occupational Safety and
Health Act specifically exempts national, state, and local governments from
its definition of an employer. Thus, POTW workers are not protected from
occupationally related health or safety hazards under the Act. Similarly,
most state laws do not provide any means for protecting sewage treatment
workers from industrial slug loads of toxic chemicals. Thus, in the absence
of other worker health and safety protection, the pretreatment program may
play an important role in protecting their workers.
A-16
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STATUTE
REGULATION
SIIMMAKy
miMKHICAl. LIMITS
Clean Walur Act
Suction 402
Suction 303
Section 301
Section 30A
Sad ion 31)1 (b)
Section 304(d)
AO CFK 125--t4l'l>KH
Kugulat ion*
AO CFH I20--Feder«l
Water Quality
Standard*
ItAt Standard! (See
Effluent Guideline*
Document)
40 <.TII I )J
Secondary Treatment
l(e|>ulut iuna
iiiui 20I<£>(2)urmit. Permits written, either by approved HPDES
otatea or El'A Region* contain specific effluent Units fur
point sources that ensure compliance with applicable
technology-baaed performance utandarda and water quality
atandarda.
Under Section 303, disposal facilitiea must meet Federal/
state ambient water quality utandarda, which are baaed on
federal guideline! and criteria for maximum perutisstl>le
otruum loading of deaignuted polIiitantH. Aquatic limit
i«'|J g/liter bated on 2A-hr average chronic toxtcity
with an assumed average lurJiiuuu of 100 ing/liter viheru
required.
Standard* are let for toxic and non-conventional pollu-
tant*. Compliance for priority toxic pollutant* to lie
obtained by 7/1/HA. for other toxic pollutant a
identified, compliance required within 3 yeara of
effluent limit promulgation; for non-conventional
pollutants, by 7/1/U7.
I'OTIVa are required tn meet effluent I iiuitat ion* bated
on secondary treatment by 1977 and Bent Practicable Ud
Trualment Technology (Ul'UTT) by I'J83.
Cuneral prohibitiona applicable to all non-Jomeutic
uuera of a POTW iiru set forth to prevent interference
with rOTU ofioral: iona, pollutant (iiiaullirun^h in
violdlion of I'OTW ltl'0£i> permit, and municipal aludge
cout umi itat ion .
iste
Pol lut ant
Ant imony
Arsenic
Beryl 1 iuu
Cadmium
Chromium
Copper
Cyanide
I efld
Mercury
Nickel
Selenium
Silver
Thai I iiini
Zinc
t'revhwuter
Aquatic Limit
1.600
AAO
5.3
0.025
4.700
5.6
3.5
3.8
0.00057
96
35
A.I
AO
A7
Unman
Health Limit
1A6
0.0022
0 . 6A 1
10
1 , 700
1,000
WO
50
O.IAA
13. A
10
50
13
5,000
Secondary Treatment
Pol lut an t 1.1 mil ii t i on
BOI) ~ " 30 rag/liter (30-day mean)
TSS 30 mg/liter (JO-d.iy IIH.-JII)
pll 6.0 < x <».0
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TAUI.K AV-1 (Continued)
STATUTE
REGULATION
6UMMAIIY
NUMERICAL LIMITS
Clean Mater Act
(cuntM)
Section 307
(cunt 'l, 5/fc/BO,
on I)tutribut ion and
Market ing of Slu.lge
Product* (/|0 CKH 25B)
Adminiatrative mechaulan 1* eatabl ialied to ensure
application and enforcement of di*charge prohibitiona and
categorical pretreatment atandarda.
Regulation provide* for iaatiance of conatruction grant*
for major POTUa required to eatabliah local pretreat-
inunt program*.
Meclinniaiaa are provided for tailoring the effluent Halt*
in categorical pretretitment alandarda lu unique circnm-
atancea of a particulur indimtrial iinei'.
Tlie concentration or naia of certain pollutant! that
uuj', be introduced into POTWa by operationa in tlie
electroplating point aource category ia limited.
Standarda contain apecific numerical limit* baaed on
evaluation of available teclmologlea in each industrial
aubcategory.
Diachargc of pollutant* into navigable water* and POTWa
from exiating and potential new aource* in tlie timber
product* induNtry ia limited.
Regulationa eatablial) KPT, BCT, NSI'S. and I'SHS atandarda
for some *ubcategoriea of the timber pruducta proceaaing
point-aource category.
Sludge diapoaal facllltie* must meet criteria for safety,
aurface water protection, groundwater protection, flood
plaina, endangered and threatened apeci««, and *ir
(futility protection.
Facilitie* comply with maxiuum conlaminaiit level* in
Appendix I of criteria to protect giounduatur quality
promulgated under thr Safe Drinking Water Act (SDUA).
If berma or dikea are uaed to meet flood plain criteria,
dredge and fill peimita mtiat be obtained if facility i*
located in a wetland.
The following are being conuidered for incorporation
into rc.'tiulul ion* on dial ribnl ion and marketing (40 CFR
258), buaed on propoual druft:
o Manufacturer (firm or I'OTW that producea, puck-
agea, liibela finiuheil aludge product) ia likely
to be regulated.
-------
STATUTE
KKCIIJ.ATKUJ
SUMMARY
NUMERICAL LIMITS
Clean Water Act
(cnat'a)
Section '.05
(cunt'it)
I
[-~»
VO
Regulations are likely to deal with Kludge
fertilizer products and sludge noil conditioner*
separately, baaed on nitrogen, moisture content*,
end tine.
o Sludge constituent of the fertilizer product or
soil conditioner may require treatment by •
process to further reduce pathogen* aa described
in Criteria for the Claseification of Solid Waste
Disposal Facilities and Practice*, Appendix 11,
Part H.
o Sludge fertilizer products uay be lesa
stringently legulsted than aludge soil
conditioner*, but nay have nitrogen/contaminant
linit «»d label* apecifying use instructions.
o Control* on aludge soil conditioner* and
fertilizers nay recognize the concept of a "good
aludge"; minimum requirement* for good aludge and
unrestricted use might include
- Specific limiting concentration* for
contaminant* auch a* cadmium, I'CH, lead
- Requirement for minimum line- content to protect
against heavy metal availability
- Adequate stabilization to prevent pathogens,
odor
- Controlling cadmium/zinc ratio a* protection
against problem* with cadmium in the diet.
o Sludges not neeting "good" aludge requirement*
may be classified into two separate categoric* by
end use
- Products for restricted general use—may
require sludge producer to include labels or
invoices Lit at give user application rates, use
instructions. Label may contain warnings which
restrict certain image based on specific
contaminant content.
- Product* for governmental uue—to be uaed under
governmental or POTW supervision on
publicly-owned land. Product would have
maximum concentration limits for specific
contaminants.
o Sludge producers may be required to analyze
sludge for keeping records on levels uf
- Cadmium - Nitrogen - Lime
- Lead - Phosphorus - Other metals
- I'Cil - I'olutiuiiiiii (/n, lJu, Hi)
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TABLE A2-1 (Continued)
STATUTE
KEIIIII.ATIOH
SUMMARY
NUHKKICAI, LIMITS
Clean Water Act
(cont'd)
They may have to maintain record* on method uaed to reduce
pathogen*.
Section 106 40 CFR 35.1500 Regulation give* Federal matching granta to atate* for
(Subpart C) pollution control programa.
Sect Ian 201 40 CFH 35.900 Regulation givea Federal granta for deaign and
(Subpart K) conatruction of municipal treatment worka.
Section 205(g) 40 CFH 35.1000 Regulation provide* for the uae of portion of atate'a
(Subpart F) conatruction granta allotment for non-coitat ruction
40 CFR IS.1500 purpoiea auch a* adminiatration of approved permit
(Subpart C) programa under Sectlona 402 and 404, and administration of
Section 206 atatewide waatewater management programa.
Sat a Drinking
Water Act
V
Ki
O
40 CFK 143—tUtion-
al Secondary Drink-
ing Water Hegula-
t iona
40 CFK 257~-Criter-
ia for Clarifica-
tion of Solid Unate
niapoaal Facilitiea
and Practice*
(derived from
40 CFH 141, Nation-
al Interiai Primary
Drinking Water
Uugulation»)
Regulationa provide guideline* for contaminanta that may
adveraely affect an eathetic quality of drinking water,
i.e., taate, odor, color, appearance, and liait* copper
and line levela in drinking water.
Regulation aeta forth Baximun contaminant In Appendix I
if aludge diupoaal facilitiea comply with groundwater
criteria.
SDUA copper levela!
1.0 lag/liter
8DWA sine levelat
S.O
o Maximum contaminant levela to deter-
mine whether facilitiea comply with
groundwater criteria (Appendix 1).
- Inorganic chemical*:
Contaminant Level dug/liter)
Araenic
Barium
Cadmium
Chromium
Lead
Mercury
Nitrate (aa N)
Selenium
Silver
0.05
1.0
0.010
0.05
0.05
O.U02
10.0
0.01
0.05
- Fluoride:
Temp. CF)* Temp. CO* Level Pig/liter)
53
53
58
70
79
.7
.8
.4
.9
.7
.3
and below
- 58.3
- 63.8
- 70.6
- 79.2
- 90.5
12
12
14
17
21
26
and
. 1 •
.7 -
.7 -
.5 -
.3 -
below
14.6
17.6
21.4
26.2
12.5
2
2
2
1
1
1
.4
.2
.0
.1)
.6
.4
*Aiumal average <>f max. duily teuipuriidue.
-------
TABLE A2-I IConl limed)
STATUTE
KEGUI.ATION
SiUHMAkY
MIMKHICAL
Safe Drinking
Water Act (cont'it)
40 CKK 257
(cunt'J)
- Organic Cheraicala;
Contaminant Level (aig/liter)
Chlorinated bydrocurbona:
o Endrin 0.0002
o Lindane 0.004
o Methoxyclor 0.1
o Toxaphene 0.005
Chlorophyoxya:
o 2,4-Dichlorophenoxy-
acetic acid 0.1
o 2,4,5-TP lie 1 vex 0.01
o Maximum Microbiological Contaminant
Level* (coliforn bacteria)
- Doing membrane (liter technique:
o 4 coliforin bacteria per 100
millilitera if one aample taken
o 4 coliforn bactera per 100
nilliliter* in more than one
a ample of all aauiplea analyzed
in one muntli.
- Da ing 5 tube moat probable number
technique (fermentation tube
technique);
o If standard portion in 10
mi 11 ilitera coliform in any
five connective oamplea from
well not to be pi count in 3 or
more of the 25 portiona.
o If ulandard portion in 100
uilliliter* coliform in any
five conaucutive uamplea from a
well not to be picaent in 5
portion of 5 aamplua or in more
than 15 of the 25 portiona.
o Maximum contaminant I eve I a of
radioactive onbatuncea:
- Combined Kadium-226 and
Hadiiim-22H - 5 pC/liter.
-------
TABU A2-I (Continued)
STATUTE
MECUUTION
SUMMARY
NUMERICAL LIMITS
Safe Drinking
Water Act (cont'd)
40 cm 257
(cont'd)
- Cross alpha particle activity
(including rsdium-226 but
excluding radon and uranium - 15
[>C/liter).
Marine Protect-
ion Research
«nd Sanctuaries
Ace
40 CFK 220 through
229--Ocean Duaiptng
Regulations
Regulates Introduction of toxic pollutants Into the
marine environment, with •pacific prohibitions on ocean
dumping of any material containing cadmium or mercury
as other than trace, contaminants.
Ocean disposal of sewage sludge will be prohibited by
12/31/81 for POTWs not meeting disposal criteria.
Clean Air Act
Section 109
AO CrR SO—National
Ambient Air Quality
Standards (HAAQ8)
MAAQS define lavela of air quality neceaaary to protect
public health and welfare, aetting primary and secondary
standards for sulfur oxide*, particulatea, carbon
monoxide, ozone, hydrocarbons, nitrogen dioxide, lead.
10
IJ
Primary NAAQS - Sulfur oxides:
a) 80 Ug'm (0.03 ppm) - annual
arithmetic mean.
b) 365 Mg/m1 (0.14 ppm) - max
24-hour concentration not to be
exceeded more than once/year.
Secondary IIAAQS - Sulfur oxides:
1300 gg/rn3 (0.5 ppm) - max
3-hour concentration not to be
exceeded more than once/year.
Primary NAAQS - Particulatea:
a) 75 Mg/*> ~ annual geometric
mean.
b) 260 Mg/m - max 24-hour
concentration not to be exceeded
more than once/year.
Secondary IIAAQS - Particulatca:
a) 601 pg/m - annual geometric mean
utt guide to auuemiiiig
implementation piano for
achieving 24-liour atandurd.
b) 150 |lg/u - max 24 lioiir
concentration not to be exceuiled
more than once/year.
-------
TAB1.K A2-t (Continued)
STATUTE
RKGIILATION
SUMMARY
NUMERICAL LIMITS
Clean Air Act
(cant'd)
Section 109
(cout'd)
Section 112
Section III
40 CHI 61—National
Emission Standards
for Hazardous Air
Pol Iutant a
(NKSIIAP)
40 CFH 60—Hew
Source Vetformance
Standards (N.SP1J)
NtiSllAP restrict emissions of mercury into the atmosphere
trom sludge incineration, sludge drying, or combined
incineration/drying plants.
NSPS prescribe performance standards for incinerators,
including minimum Federal requirements tor particulates
discharge, opacity, and monitoring. They apply to
incinerators with charging rate ^ 43 metric tons/day
(50 tons/day). Owner/operator is required to
record daily charging rates, hours of operation.
Primary and secondary NAAQS - Caibon
monoxide:
a) 10 mg/m (9 ppm) - uax 8-hour
concentration not to be exceeded
more than once/year.
b) 40 mg/m OS ppm) - max I-hour
concentration not be exceeded
more than once/year.
Primary and Secondary NAAQS - Ozone:
235-J2
-------
TABU A3-1 (Continued)
STATUTE
Clean Air Act
(cont'il)
REGULATION
SUMMARY
NUMERICAL LIMITS
Section 109
40 CKU 51—New HSR rul« under regulation for State Impliiseittation
Source Review Plans (SIP) sets forth procaduree for ruview end
(HSR) approval of new air pollution sourcee prior to
construction. Al«o act forth requirement! for
preventing algnificant deterioration of air quality.
Toxic Substances
Control Act
Section IS
Sect! tin 16
Section 17
40 CPU 761-PCB EPA impoace requirements on facilitiea disposing of
Regulations sludge that contain* PCB*!
Incinerator*—recommendations are provided for
incinerating sludges containing more than 25 ppm
PCB, and incineration disposal practice* are specified:
o Facilities must comply with combustion criteria.
o Rate, quantity of PCBs fed Into incinerator
must be measured, recorded every IS minute*.
o Automatic stop of PCB flow to incinerstor ia
required if incinerator temperature drops below
specified level.
o Monitoring requirements are imposed for oxygen,
carbon monoxide, carbon dioxide, nitrogen oxidea,
hydrogen chloride, total chlorinated organic*,
PChs, part iciilstes, and for the following
cowbuation products: Oxygen, carbon monoxide,
carbon dioxide.
Incineration:
Sludge containing > 25 ppm PCB on
dry weight Uasis (recommended):
o Increaae incinerator
temperature and residence
tine to destroy at least
951 pen.
Sludge containing 2. 50 ppm PCB on
dry weight basis (required):
1200'C * 100'C for 2-scc,
dwell time with at leant 31
exceaa oxygen in atack gaa;
or_
I600'C » 100'C for I.S-*ec,
dwell time with at least 21
excess oxygen in atack gaa.
o EPA Regional Administrator nuat approve of
incinerator uaed to diiipoae of PCB-containing
aludge.
o Facilitiea must meet requirements for record-
keeping, reporting, trial .run.
Ha nil air uniasiona from
incinerator - no more than
0.001 gm I'CII/kg (1 ppm) of
PCU introduced into
incinerator.
Comlxiat inn efficiency to be
at leant 99.91. calculated as:
cniubuvt ion
frequency
C „ • Concentration of CO
(• - Conceiilral ion of O)
-------
TAUI.B A2-I (Continued)
STATUTK
UKCIILATION
Toxic Substances
Coiitrul Act
(conl'd)
Section I)
Suction 16
Suction 17
(cont'd)
SUMMARY
Lundspreading—Limit! are imposed on araoiint of PCBa
that can be ad.led to noil uaed for
food-chain crops. Limit i; are baaed on
level a imposed by FDA for FCba in
aninal feed and milk fat.
Chemical landfilla uaed for PCB disposal— EPA
Regional Administrator approval ia required, and
hydrologic condition requirements; locution
requirement*; aanpling, gronndwoter u«ll monitoring,
water analyiiia, leachate collection requirement*;
and operation and atipport facility requirement a
roust be net.
NUMKKICAI. LIMITS
Landapreading:
Surface application of sludgea
allowed if aludgea contain 10 ing/kg
PCB (10 ppm) or leaa.
If aludge containa more than 10 ppra
PClls, must be incorporated into
aoil rather than apreud.
If PCS level* are above SO ppni,
l»0 CKK 761 regulations apply for
diupounl procedurea.
Chemical Landfilla uaed for I'CB
disposal:
Soil parametera - inplace uoil A ft.
thick or compacted aoil linttr 3 ft.
thick.
PerueahiIity equal to or leua than
1 x 10 cn/uec.
Mare than 30Z aoil passing through
1200 sieve.
Liquid limit > 30.
Planticity index > 30.
Heuourcu Cmiucr-
vatiuu and Keco-
vury Act
Suction 300/<
Suction 4U04
l»0 CPU 260 through
265—Hazardous
Waatu and Conaoli-
datud Permit
Kugtilat iona
Incineration requirement a:
o Incinerator must he brought to ateady-atate
operating condition before hazardous waste ia added.
o Haute nut previously burned in incinerator muat
be analyzed for heating value, halogen and sulfur
content, lead and mercury content unless written
evidence shows their absence. Analyaia ruaulta muat
be kept on file.
o Followup monitoring/inupticriona are required for
incineration of huzardoua wastes:
- Instrument monitoring every 15 minutes.
- Immediate corrections when required to maintain
iltirudy stale.
-------
TABLE AJ-I (Continued)
8TATIITB
REGULATION
SUMMARY
NUMERICAL LIMITS
Kc source Comer-
vat ion and Keco-
vury Act
Section 1004
Section 4004
(cont'd)
40 CFB 260 through
265 (cont'd)
- Hourly vlnual observation ot euivilon* for color,
opacity.
- All equipment to be inspected daily,
including emergency and alarm systems.
o All waste* to be removed from incinerator it closure.
Surface Impoundment requirementa:
o At lea«t 2 feet of freeboard muat IKI maintained to
prevent overtopping dyke. Earth dykea to have
protective cover to minimize erosion.
o Uaate analyaea, trial teat* are required.
o Daily freeboard and weekly impoundment
inspection* are required.
o Closure, pout-demure requirement* must
be followed.
Landfill requirement*!
o For general operation, run-on, run-off, and
wind dlaparaal of waatu mu«t be controlled.
o Enact location msp and record* of cell con-
tent* and waste type* must be maintained.
o Closure, post-closure requirement*:
- Closure plan muat specify cover function and
design and post-closure care.
- Flan muat address how pollution migration
and surface water infiltration will be con-
trolled and erosion prevented..
- Plan must be baaed on type, amount, constituenta
of waste; wsste mobility and expected rate of
migration; site location, topography, surrounding
land use; climate; cover characteristics; geology,
hydrology, (oil profile*.
o I.eachnte collection, removal, treatment must be
maintained and monitoring.
o Can collection and control to be Maintained and
monitored.
-------
TABLE A2-I (Continued)
STATUTE
HKCW.ATIOH
SUMMARY
NIIHEHICAL LIMITS
Keaource Conservation
and Recovery Act
(conl'd)
40 CFR 260 through
265 (cont'd)
o Access aunt J»* restricted.
Section 3004
Section 4004
(cont'd)
't
10
a Ignitable, reactive uante must be controlled
•o th«t it not hazardous.
o Incowpatible waate must to be diapoied of
separately unless special precautions are taken.
o Special precaution* for leachate control and
treatment must be taken and approved containers
nust be uaed far liquid wastes.
Landapreading requirements:
o Waste Bust be made nonhazardoua before use in land
treatment.
o Uaste Must be analyzed for concentrations of tonic
and other hazardous substances so that maximum
concentration limits are not exceeded.
o Before food-chain crops can be grown at hazardous
wuste land treatment facility, it must be
demonstrated that arsenic, cadmium, lead, and
mercury will not be uptakeii by plants or otherwise
ingested by food-chain animals; and that concentra-
tions of these substances are not greater than in
crops grown on untreated aoil in the saute region
under the same conditions.
o Waste containig cadmium must be treated according
to cadmium level guide)inea.
o Unaaturated zone monitoring plan required.
o Records of application dates, rates,
quantities must be kept, along with record of
location of each hazardous waste placed in the
facility.
o Clouitre, post-closure plans were required;
contents should be the aume as for landfills.
Cadmium Levels;
a) pll of sludge and aoil mixture
at time of each sludge
com a ins calmium at con-
centration of 2 nig/kg dry
weight or less.
b) Annual application of cadmium
from aludge does not exceed
0.5 kg/l.ectare on land uaed
to produce tobacco, lealy
vegetables, rout crops lur
huiuun consumption. For other
food chain crops, uniiuul
cadmium rate not to exceed:
Time Period
9/13/79-6/30/84
7/I/84-I2/3I/U6
1/1/B7 —
Annual Cadmium
Applicat ion Hate
2.0
1.25
0.5
c) Cumulative application uf
cadmium (ram sludge nut to
exceed levels in l(a) or l(b)
above or in Il(d) or ll(ti)
below.
-------
TABLE A2-1 (Continued)
STATUTE
REGULATION
SUMMARY
NUMERICAL LIMITS
Reaourue Congervation 40 CfK 260 through
and Recovery Act 265 (conc'd)
(tont'd)
Suction 3004
Section 4004
(cnnt'd)
o Special requirement* muat be followed for
ignitlable, reactive, or incompatible waatea.
II.
•) Soil Cation Max. Cumulative
A|tpl lotion
kg/ha
Exchange
Capacity
(•eq/IOOg)
Back-
ground
Soil
pll<6.5
Back-
ground
Sail
iill<6.5
J-1S
5
10
20
ro
oo
b) For aoila with background (ill
lea* thin 6.5, cumulative
cadmium application rate daea
not exceed level* below,
provided pll of aludge «nd
•oil mixture ia aJjuuteJ to
and naintaiued at leant 6.S
whenever food-chain cropa are
Crown.
Soil Cation
Exchange Capacity
(•eg/IOOg)
Max. Cumulative
Application Rate
(kg/ha)
< 5 5
5-15 10
> 15 20
III. a) Only food-chain crop produced
ia aniiaal feud.
b) pll of aludge and aoil mixture
ia at leant 6.5 at time crop
ia planted or at time ttludgt)
ia applied, whichever ia
later, and pll lev«l ia main-
tained whenever food chain
cropa are grown.
c) Hun for facility doiann-
atratea linw animal fc-ed ia
diatributt*ii Lo preclutlii human
conatiMpt ion.
d) Future property ounera to be
notified in record or deep
thtit aludge waa high in
cadrniuui and tood-thiiiu
-------
TAHI.E A2-I (Continued)
8TATIJTK
REGULATION
SUMMARY
NUMERICAL LIMITS
Resource Conservation
and Recovery Act
(cont'd)
Section 1008
Section 4004
40 CKK 257—Criteria
for Clarification
of Solid Waste
Disposal Facilities
and Practice*
Landfills, aurfaca inpoundnenta. 1 and*preailing facilitiea
are to comply with Criteria in Appendix II for Procesaea
to Significantly Reduce Pathogen* (PSHP) and Processes
to Further Reduce Puthogena (PKHP), where applicable.
10
Appendix HA - Processes to Signifi-
cantly Reduce Pathogens:
o Aerobic digeation - sludge ia
agitated with air or oxygen to
usinla in aerobic conditions lor
residence tines from 60 days at
IS'C to 40 daya at 20*C. Hin. of
3 months uecenuary, 2 months of
which temperatures average above
O'C on daily basis.
o Air drying - liquid sludge
allowed to drain, dry in drain
basina at depth of 9 inches for
at least 3 months, 2 months of
which teuiepraturea average above
O'C on daily baaia.
o An aerobic digestion - absence of
air at residence time tiom 60
daya at 20*C to 20 daya at 35'C
to 55*C; volatile solid reduction
at least 381.
o Composting - all net hod a; in illinium
40*C for 5 daya, with temperature
>5S*C for at least 4 hours.
o Line stabilisation - sufficient
line added to produce pll of 12
after 2 hours.
o Other methods acceptable if
piithogen reduction » to aliove.
Appendiit lilt - Processes to further
Reduce Pathogen*:
o Compuating 5*C or
grester fur 3 days. Coiiipoui-ing
(windrow) - at 53*C or greater
fur at lesst IS days with ul
least 5 tuininga uf windrow.
-------
TABLE AJ-l (Continued)
STATUTE
REGULATION
SIIMHARV
NUMERICAL LIMITS
Resource Caniarvtit ion
•nil Recovery Act
(coiit'il)
Section 1(108
Saction 4004
(coiit'd)
40 CFR 57
(cont'd)
I"
OJ
o
Heat drying - aioiature to be
reduced to IOZ or leu*;
temperature to reach at luaat
80'C.
llaat treatment - liquid Kludge
lieatcd to IBO'C for 10 win.
Themopliillc ajrobic digeatioii -
liquid aludga agitated with
oxygen or air; aerobic
conditiona maintained for 10
daya at SS-60*C, volatile nulida
reduced at leait 3BZ.
Other nethoda nay acceptable if
pithogen reduction " above
Method*.
-------
A-3. POTW DEMOGRAPHICS
In performing an analysis of the impact of the pretreataent regulations,
it is important to understand the characteristics of the POTWs that will be
affected by the regulations. To assess how these POTWs are or will be
affected by various regulatory options (both technical and procedural), the
difference between the POTWs must be understood. This section details how
POTWs are characterized according to total and industrial wastewater flow,
level of treatment provided, and liquid and sludge disposal techniques.
EPA has identified 2089 individual facilities (2003 POTWs) that are
required to develop a pretreatraent program under the current regulations.
Using EPA's NEEDS Survey (U.S. EPA 1980), all POTWs with a total design flow
>5 MGD were identified as needing to develop a program. In March 1981, EPA
identified the POTWs with <5 MGD total design flow which will require a
pretreatment program bringing the total to 2003 POTWs (Diamond, 1981). Of
these 2003 POTWs, 36% have design flows _>. MGD and 64% have design flows <5
MGD. While there are currently 15,250 POTWs in the country, the 2003 POTWs
represent systems that treat 81% of the total flow and 91% of the total
indusrial flow in the nation. EPA also regards these 2003 POTWs as receiving
a majority of the wastewater flow from those categorical industries chat have
indirect discharges. These 2003 POTWs are geographically distributed across
all of EPA's ten regions.
The following tables present the general characteristics of the POTWs in
terms of their individual demographics. Table A3-! provides an overview of
total and industrial wastewater flows for these POTWs, according to average
daily flow. Table A3-II provides similar data, according to the level of
treatment provided.
TOTAL FLOW
An analysis of these tables indicate that of the 2003 POTWs, 721 POTWs
(36 percent) receive total flows greater than 5 MGD, while 1232 POTWs (64
percent) receive total flows less than 5 MGD. It is important to note that
the. 1282 POTWs with flows less than 5 MGD only account for about 10 percent oi
A-31
-------
TABLE A3-I. DISTRIBUTION OF POTWS 3Y AVERAGE DAILY FLOW
AVER.
DAILY
FLOW
0-1
MGD
1-5
MGD
5-20
MGD
20-50
MGD
50-100
MGD
> 100
MGD
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
TOTAL FLOW
INDUSTRIAL FLOW
NO. OF PLANTS
PER
0-15
158
3
378
1,070
41
422
2,717
123
292
1,690
116
57
1,609
108
22
2,966
192
18
CENT
15-20
16
3
32
134
23
59
439
79
43
249
43
10
313
56
5
1,436
235
4
I N D U
20-30
19
4
37
130
45
73
683
174
67
628
157
19
289
63
4
1,752
404
7
S I R I
30-40
15
5
30
116
41
47
567
200
53
306
111
11
352
119
5
1,153
394
6
A L
40-50
6
3
16
113
51
42
268
120
25
- 279
126
9
293
123
4
122
49
1
FLO W
50-100
17
12
34
213
148
86
321
225
36
526
355
17
82
52
1
—
»
0
A-32
-------
TABLE A3-1I
DISTRIBUTION OF 1'OTWS BY LEVEL OF TREATMENT
I
U)
i l
PERCENT I NO. OF
INDUSTRIAL 1 PLANTS
FLOW j
1
0-15 228
15-20 26
i
20-30 ! 25
1
30-40 ! 16
!
l
40-50 j 16
> 50 ! 32
j
j
i
!
U 1 M A R Y
TOTAL FLOW
(MCD)
2960
784
761
187
388
184
i
i
INDUSTRIAL
FLOW
(MGD)
198
in
201
64
i
167
135
|
i
l
1
i
S E
NO. OF
PLANTS
914
119
166
131
i 78
l
| 133
l
1
!
1
C 0 N D A R
TOTAL FLOW
(MGD)
6831
1720
i 2597
!
j 2201
1
j 667
l
! 879
i
l
!
1
Y
INDUSTRIAL
FLOW
(MGD)
360
292
628
765
297
597
T 1
NO. OF
PLANTS
47
8
16
5
i
3
9
I R T I A R Y
TOTAL FLOW
(MCD)
418
84
93
119
26
96
i
INDUSTRIAL
FLOW
(MGD)
25
16
! 23
41
12
i
i "
i
-------
the total flow in all 2003 POTWs. Conversely, the 36 POTWs (less than 2 per-
cent) that receive flows greater than 100 MGD account for about 35 percent of
the total flow in all 2003 POTWS. 519 POTWs (26 percent) receive flows in the
5-20 MGD range and these account for the majority of the renaining total flow
in all of the POTWs. While all of these plants are subject tc the pretreat-
ment regulations, a major portion of the total flow is received by a
relatively small number of large capacity POTWs.
INDUSTRIAL FLOW
The 2003 POTWs receive a design industrial flow of 4,013 MGD and 60 per-
cent of the POTWs receive 0-15 percent industrial flow. The remaining indus-
trial flow is dispersed fairly equally among the POTWs, with 25 percent of the
industrial flow entering those POTWs that each receive less than 20 percent
industrial flow. Of the plants with 0-15 percent industrial flow, 41 percent
receive less than 5 MGD total flow.
LEVEL OF TREATMENT
Of the 2003 POTWs, 17 percent provide primary treatment, 78 percent
provide secondary treatment, and 5 percent provide tertiary treatment. Of the
total flow in all POTWs, 25 percent received primary treatment. These primary
plants treat 22 percent of the industrial flow.
DISPOSAL OF LIQUID EFFLUENTS
Of the 2003 POTWs, 1,764 discharge liquid effluents to surface waters.
This represents 84 percent of the total volume discharged by POTWs. Ocean
discharges, account for 12 percent of the total effluent discharged while all
other POTW discharge methods combined account for the remaining 4 percent.
None of the other other discharge methods account individually for more than
12 of the total.
DISPOSAL OF SLUDGE
Table A3-III shows the annual tonnage of sludge disposed by five differ-
ent techniques. Annually, 3.7 million tons are disposed by the 2003 POTWs;
44 percent of that which is disposed cooes from secondary and tertiary plants
that send sludge to landfils. Because these plants have the capability? to
A-34
-------
TABLE A3-III
POTW SLUDGE DISPOSAL METHODS
Incineration
Landfill
Land Spread
Trenching
Ocean Duaping
Total
Tons/Year
Primary Secondary Tertiary Total
193,791 772,915 100,726 1,067,432
250,849 1,463,593 164,607 1,379,049
15,445 254,638 30,221 300,304
794
18,386
133,567 266,884
594,446 2,776,366 295,554
19,630
400,451
A-35
-------
remove toxic pollutants in significant quantities, the possibility exists that
the toxics could accumulate in the sludge in concentration that may make the
sludge hazardous and/or difficult to dispose of in a cost/effective manner.
Sludge from pirmary treatment facilities can also become significantly con-
taminated by toxic pollutants if the influent concentration of toxics entering
the POTW treatment plant is not controlled. Thus, sludge disposed of in
conventional landfills or by land spreading can pose a significant envrion-
mental problem if the concentration of toxics allowed to accumulate in the
sludge is not controlled. Of primary concern are contamination of agricul-
tural land and groundvater.
A-36
-------
A-4. PROGRESS OF THE FEDERAL 403 PROGRAM
INTRODUCTION
•»
Pretreatinent is the control of pollutants in nondomestic wastewaters
prior to their discharge into POTWs. Pretreatinent minimizes or eliminates
interference with POTW operations, contamination of POTW sludge, and pass-
through of industrial pollutants to the receiving water body. Sections of the
Clean Water Act (CWA) of 1977 (Public Law 95-217) specify Federal pretreatment
regulations governing existing and new sources discharging to POTWs. The
General Pretreatment Regulations promulgated under the authority of the CWA
require states and municipalities to develop their own pretreatment programs.
The three authorities responsible for developing and implementing the
Pretreatment Program are EPA, State water pollution control agencies, and
local POTW management authorities. Appendix A-4 has been broken into three
sections which describe the role of each of these authorities and the progress
that has been made by each, towards implementing the National Pretreatment
Program. Together they provide an overview of the current status of the
Federal 403 program.
FEDERAL PROGRAM
EPA Headquarters and Regional Offices are responsible for the Federal
portion of the program. The EPA Headquarters conducts program activities,
sets policy, develops guidelines, and coordinates those in the regions.
Within the Office of Water Enforcement, the Permits Division has ongoing
responsibility for developing and promulgating the General Pretreataent
Regulations and is also responsible (in conjunction with the Office of the
General Counsel) for the final review and approval of state programs. The
Permits Division also develops guidance materials for the national program.
Examples of EPA guidance materials are as follows:
o Local Program Development — "Procedures Manual for Preparing a POTW
Pretreatment Program Submission"
A-37
-------
o Local Program Review — "Guidelines for the Review of POTW
Pretreatment Program Submissions"
o State Program Development — "Guidance to State on Implementation of
the General Pretreatment Regulations"
o Technology Transfer — "Industrial Residuals Manual, Vols. I, II, III"
o Public Information — "Protecting Our Nation's Waters: The National
Pretreataent Program"
This Division also provides direct program development assistance to states
and POTWs, and enforcement support to the states and regions.
Within the General Pretreatment Regulations developed by the Permits
Division, EPA has elected to develop 34 Categorical Pretreataent Standards.
The responsibility for developing these 34 effluent standards rests with the
Effluent Guidelines Division of EPA. To date, EPA has promulgated two
Categorical Standards, and in addition, 32 sets of standards are under
development.
All Federal funding to state and local governments for pretreatment
purposes is managed by EPA's Office of Water Program Operations, the Municipal
Construction Division administers the dissemination of 201 funds, which are
used for matching grants to POTW authorities. Pretreatment program develop-
ment is one item eligible for funding under this program and may be financed
up to 75Z through a Section 201 grant. Also within this office is the Water
Planning Division, which administers Section 106 funds. These monies are used
for matching grants to the states for water pollution control program activ-
ities. Pretreatment program development is an eligible cost under the 106
program. The CWA also enables leftover Section 205g monies to be used for
state pretreatment program development. Efforts have been made to quantify
the amount of Section 106 and 205g funds that have been used for pretreataent,
but this information is not available from EPA at this time.
The EPA Regions also offer assistance to states and POTWs for program
development. In addition, the Regional Offices review state pretreataent
program submissions and make approval recommendations to Headquarters. In
A-38
-------
non-NPDES states and NPDES states that have not received pretreatment program
approval, the Region is responsible for identifying POTWs that need programs,
the incorporation of pretreatment program compliance schedules into NPDES
permits and the approval of POTW program submissions. In the absence of a
local program where one is required, the Region is also responsible for
program development and implementation. The region administers funds avail-
able to states and municipalities for water programs including pretreatment
under Sections 201, 106, and 205g of the CWA and is responsible for enforce-
ment actions against states and POTWs that do not meet their responsibilities
under 40 CFR 403.
Federal Pretreatment Program costs are presented in Table A4-I. A
man-year of effort for EPA, including fringe and overhead, was estinaed at
$39,000. Personnel costs presented in Table A4-I are based on man-years of
effort as estimated by each SPA Headquarters Division: Permits, Effluent
Guidelines, and Municipal Construction. Regional personnel costs are based on
estimates from the Headquarters Permits Division. The contract totals were
obtained from the Permits Division based on specific contract awards. The
Effluent Guidelines Division estimated the amount of contract money associated
with pretreatment as a percentage of their total contract monies. Section 201
grant monies were estimated based on contacts with Headquarters and their
respective Regions. In all cases the numbers presented are based on the
information available at this time, and should be considered as estimates
only.
STATE PROGRAMS
EPA's General Pretreatment Regulations require those states that have
been delegated NPDES responsibilities and authority to develop and implement
statewide pretreatment programs. Upon approval from EPA, each state assumes
responsibility for the following:
o Identification of POTWs that will be required to develop programs.
o Review and approval of POTW program submission.
o Compliance monitoring.
o Enforcement actions.
A-39
-------
TABLE A4-I.
FEDERAL PRETREATMENT PROGRAM RESOURCE EXPENDITURES
($ Tliouauiula)
110
IIQ
Permits Division
Personnel
Contracts
Effluent Guidelines Division
Personnel
Contracts
1977
317
273
2,340
F T
1978
317
100
273
2,340
S C A 1.
1979
200
1,706
273
2,340
YEAR
1980
200
1,862
273
2,340
1981
200
1,419
273
2 , 340
1
5
1
11
TOTAL
,234
,087
,365
,700
IIQ Municipal Construction Division
Personnel
Grants
Regional Personnel
(Including all Pretreutment
related personnel)
40
390
40
390
40 120
38,952
390
59,628
CONSTRUCTION GRANTS FUNDS OBLIGATED TO POTUs AND STATES FOR PRETREATMENT ($ Thousands)
Hug l.on
Grunt Total
1 IT III
2,500 11,221 4,874
IV V VI VII VIII
1,245 9,240 3,352 2,041 331
IX X
2,348 1,800
Total for
ail Regions
38,952
Note: These figures have not been adjusted to 1981 dollars. Also included In the personnel figures la a
$5,000 per fiscal year total travel cost estimate; no other costs were included.
A-
Totals for each area arc: Personnel 3,889
Contracts 16,787
Grants _!<)>?5J.
Total 59~628 '
-------
Where there is no POTW program in place, States with approved programs are
responsible for compliance monitoring and enforcement actions with respect to
the industrial users.
There are currently 32 NPDES states. Of these, the Virgin Islands,
although treated like a state, will not be required to develop a pretreatrnent
program and is therefore not included in the summaries presented in this
appendix. Currently, eight states have received EPA's approval to implement a
statewide pretreatment program. Seven other states have completed all major
elements of their program development and are likely to be approved in
calendar year 1981. These 15 states with advanced pretreatment programs are
identified in Table A4-II.
State pretreatment program status and development costs are presented in
Table A4-II. The columns marked "Actual Cost" contain figures obtained from
state program development documents or from conversations with state pretreat-
ment personnel. The estimates or development and operational costs were
generated using a predictive mathematical equation, which was derived using
actual costs. A detailed discussion of this methodology is included as
Attachment A4-a. For the purpose of this section development costs were
defined as those costs incurred up to the time of official program approval.
The estimates of current program development status were obtained in conjunc-
tion with the Headquarters Permits Division, which tracks state pretreatment
program development. The estimate of development monies spent to date was
computed from Permits Division information on state program development
status, and the development costs were predicted by the mathematical equation.
However, when actual information was available directly from the state, this
was used rather than the predicted values.
The estimates show approximately $5.9 million must be spent to develop
programs for those states required to do so, and approximately $3.4 million
of this projected total has been spent in State program development to date.
It should be noted that these figures include Federal grants as well as state
monies, as record keeping practices do not allow for a break down to be made.
Therefore this figure, when added to the Federal total, exhibits a "double"
count of funds.
A-41
-------
TABLE A4-11.
STATE PRETUEATMKN'I' PROGRAMS
($ Thousands)
AMOUNT
EXPENDED TO DATE
ESTIMATED ACTUAL ON DEVELOPMENT
S'BATE DEVELOPMENT COST DEVELOPMENT COST (Estimate)
AL*
CA
CO
CT*
m
C.A*
III
II.
IN
IA*
KA
Ml)
Ml
MN*
MS
MO*
NT
m
NV
NY
NC
Nl)
Oil
OK*
PA
112.6
649.3
51.9
106.3
23.5
176.6
7.6
A 98. 3
278.4
128
83.3
83.4
503
122.6
70
176.0
13.2
44.9
2.7
464.5
220.5
2.5
515.7
77.8
430.7
60 60
162
0
270 270
9
263.9 263.9
13.5
299
139
147.7 147.7
25
25
500
62.1 62.1
36
245.7 245.7
0
22
2
232
110
0
232
10 10
108
PERCENT
DEVELOPMENT
(Estimate)
100
25
0
too
40
100
80
60
50
100
30
30
75
100
90
100
0
50
UO
50
50
0
45
100
25
ESTIMATED
OPERATIONAL
Coat ($/year)
193.5
721
84
158.7
15.3
246.0
12
539
336.6
98
85.5
89.8
642.0
312.0
55
210
21.7
27
4.5
421
227.9
11.4
625.2
76.4
600
ACTUAL
OPERATIONAL
Cost ($/year)
273.2
297
271.1
19.7
222.3
124.2
Note: All i:osts are In $ Thousands and include Federal contributions
* Approved PT Program.
I Will aoon he NPDES approved.
Source: State program development documents, State Water,Pollution Control A gencies, EPA Headquarters.
-------
TAIVLE A 4-11.
STATE PRETREATMENT PROGRAMS (Continued)
($ Thousands)
STATE
Sfi
TN
VT
VI
VA
WA
t Wl*
OJ
WY
N.J**
PR**
WV**
TOTAL
ESTIMATED ACTUAL
DEVELOPMENT COST DEVELOPMENT COST
105.4
153.8
10.7
No program
required
128
115.4
208 209.9
2.2
267
45
45.3
5,924.1
EXPENDED TO DATE
ON DEVELOPMENT
(ESTIMATE)
90
77
10
—
26
11
209
0
189
27
27
3,408.8
PERCENT
DEVELOPMENT
(ESTIMATE)
85
50
95
—
20
10
100
0
85
50
60
ACTUAL
EST. OPERATIONAL OPERATIONAL
COST ($/year) COST ($/year)
129.9
173.3
36.2
181.4
106.5
468.9 325.6
2.3
304
120
43.4
7,379.4
Note: All coats include Federal contributions.
* Approved Pre treatment Program.
** Will soon lie NPDES approved.
Source: State program development documents, State Water Pollution Control Agencies, EPA Headquarters
-------
POTW PROGRAMS
EPA's General Pretreatment Regulations require POTWs greater than 5 MGD
to have pretreatment programs. SPA or states with approved programs nay
require POTWs to develop a pretreataent program following an evaluation of the
POTW's system, problems, and nondomestic discharges. Where a program is
required, it is administered by the POTW authority and is comprised of three
general elements. These elements are the legal, procedural, and resource
aspects of the program.
For the first element, the POTW authority must document its legal
authority to effectively run the program. The procedural aspect of a program
involve industrial user identification, compliance monitoring, enforcement
actions, reporting, and recordkeeping. The resource analysis must demonstrate
the ability of an authority to support its program with the necessary person-
nel, equipment, financing, and other resources.
Estimate of the status and costs associated with the development of
programs by the 2,000 municipalities EPA has identified as requiring programs
are presented in Table A4-III. These estimates are derived from a sample
survey of 132 POTWs conducted by JRB. This survey represents a statistically
valid subset of the total population of POTWs nationaly that will be required
to develop pretreatment programs. (Section 3-2 describes the survey).
Cost and status data reported by the 132 survey respondents was extra-
polated to provide estimates on a national scale. Those sample POTWs reported
to be at various stages in the development process (i.e., no action, planning,
developing, implementing, and having applied for approval) were assigned a
percentage of expenditure to date based on how close they were to having an
A-44
-------
TABLE A/i-111.
POTW PKCTREATHENT PROGRAM STATUS
1
u<
Design Flow
(MCI))
0 + 5
> 5
Total.
Percentage
Total No.
of POTWs
1,261
735
1,996
100
No. of POTWs
No Action
714
143
857
43
No. of POTWa
Planning
301
245
546
27
No. of POTWa
Developing
76
216
292
15
No. of POTWs
Applied
for Approval
38
79
117
6
No. of POTWs No Response
Implementing
38 94
33 19
71 113
3 6
Estimated
Development Costs
to Date ($ millions)
5.696
29.204
34 . 900
Source: Statistical extrapolation of 132 POTW assessment.
-------
approval prograa. These percentages were chosen based on professional judge-
ment. This schedule was assigned as follows:
Status 2 Expended to Date
No action 0
Planning 20
Developing 60
Implementing 90
Applied for Approval 100
By matching these percentages to development cost figures derived in Appendix
03.2.5 for each of the sample POTWs, an estimate of dollars spent on develop-
ment to date was obtained. These figures were then simply scaled up to the
2,000 POTWs to .yield the total cost expended to date to develop local pre-
treataent prograas. It should be noted that this estimate includes Federal
monies also. The results are illustrated in Table A4-III. From the inforna-
tion in the table the following conclusions can be drawn:
o 792 of POTWs greater than 5 MGD have made soae programs toward
obtaining an approved pretreataent prograa.
o 452 of the POTWs less than 5 MGD have made some progress toward
obtaining an approved pretreataient prograa.
o 152 of POTWs greater than 5 MGD have applied for approval of or are
actually implementing pretreataent programs.
o 62 of POTWs less than 5 MGD have applied for approval of or are
actually implementing pretreataent programs.
These results imply that the size classification imposed by the Federal
Pretreataent Regulations has had a noticeable effect. EPA's decision to make
a pretreatment program mandatory for POTWs with flow greater than 5 MGD has
resulted in more progress for this group of POTWs. It should be noted that
larger POTWs are also more likely to have the fiscal and technical resources
to more readily develop and implement a pretreataent prograa.
A-46
-------
The figures in Table A4-III represent monie spent by POTWs to comply with
Federal Pretreatment Regulations since their promulgation in June 1978. They
aer based on the current status of local programs. For those programs that
are only partially developed a portion of the cost for full program develop-
ment is shown. It should also be noted that these expenditures include monies
obtained through Federal grants as well as local funding.
Table A4-III does not include operational cost information. Detailed
information on operational costs for pretreatment programs on the local level
is sparse, primarily because of the lack of operating programs. Efforts were
made through the EFA Regions to obtain more data, but not enough information
was obtained to estimate current or projected operational costs for local
programs in this baseline report. POTW operational costs are addressed in
Appendix C.
SUMMARY
Compiling the available data for this appendix was complicated by two
factors: (1) the data had to be obtained from numerous government agencies
who do not keep consistent data records, and (2) in many instances,
pretreatment information and costs are not tracked as separate line items.
Therefore, extrapolations from existing data and calculated estimates had to
be used to complete the necessary data base.. A detailed description of the
estimating methodology for state program costs appears in the attachment to
this appendix while the methodology for local program cost estimates appear in
appendix C.3.2.E of this report. It should be noted that because estimates
were used, the data are much more reliable when viewed on a national scale
than when analyzed on a smaller categorical scale.
Federal
Close to $60 million has been spent at the Federal level for the develop-
ment and implementation of the Pretreatment Program since FY 1977. This
includes personnel, contracts, and grants.
-------
ATTACHMENT A4-a
STATE PRETREATMSNT PROGRAM COST
The purpose of this section is to derive individual state pretreataent
program cost estimate which can be totalled to yield an estinate of the total
cost of pretreatment at the state level. For the purpose of this analysis,
this total has been limited to the 35 states that have alrady received or will
soon receive NPDES program delegation. These 35 states are those required by
EPA to have pretreatment programs in the immediate or near future.
Methodology
Regresssion analysis is one tool that can be used to estimate the costs
of developing and implementing a state pretreament program. In this type of
analysis, a statistical relationship between a dependent or cost variable and
some number of explanatory variables is derived in the form of an equation for
predicting a state's program cost. This equation is represented by the
following general form:
y « a + bj x, + b2 *2 * e
where:
y " the cost to develop and implement a state pretreatment program
x,, %2 * explanatory variables testsd (i.e., population, total flow,
value of shipments, and number of POTW s)
b., b- * coefficients to be estimated
a » constant term
e * error term
Using the cost data available, this equation can generate an estimate for
the cost of pretreataent to states for which no cost figures are currently
available.
A-48
-------
Data Collection and Limitations
The basic source of data used in this analysis are:
o State pretreatment program subraittals
o Phone contacts with State Pretreatment Coordinators
o Statistical Abstract of the United States 1980 (U.S. Bureau of Census
1980)
o NEEDS Survey containing information on flow and the number of POTW
(U.S. SPA 1980).
o 1977 Census of Manufacturers (U.S. Bureau of Census 1977).
Separate regression analyses are performed for the development and
implementation costs of state pretreatment programs. (Of the 15 states with
advanced programs, Vermont and Connecticut were excluded from this statistical
analysis because their state agencies will directly administer all stace pra-
treatment activities. Since no local POTW programs will be developed in these
states, they are considered atypical). The development cost analysis is based
on observations of 13 states. Of these 13 states, 8 have received EPA
approval while the other 5 are in the final stages of the review process. The
development cost figures for the 8 approved states were obtained from their
pretreatment program submittals, and the remainder were compiled from phone
contacts with state pretreatment coordinators.
For the implementation cost analysis, 12 individual state pretreatment
programs were reviewed. Of these 12 programs, 8 have received EPA approval,
while the remainder are currently awaiting approval. The 12 operating cost
figures were extracted from program submittals. Since most of these programs
provided only mn-year estimates over a 5-year period, they were converted into
dollar amounts by multiplying by $27,000. This number was used to represent
an average, fully loaded salary for a state employee involved in pretreatment.
The 5-year cost projections were then evaluated statistically (i.e., mean,
median) to arrive at a single estimate of the state's annual pretraatment
cost.
A-49
-------
Data on the explanatory variables used in both analyses were derived fron
three sources. Value of shipments was obtained from the 1977 Census of
Manufacturers; number of POTWs requiring pretreataent, actual flow, and total
number of POTVs were obtained from the NEEDS Survey; and population was
obtained from the U.S. Bureauof Census (1980).
Results
Several regression analyses were performed to test the strength of the
relationship between the dependent or cost variable and alternative explan-
atory variables. The results of these analyses of state implementation and
development costs are presented in Tables a-1 and a-2.
Based on these results, equation 8 in Table a-1 was selected as a
predictor of the state's implementation cost. The rationale behind this
selection is straightforward from both statistical and common sense perspec-
tives. Statistically, equation 8 is the best predictor because it accounts
2
for the greatest fluctuation in the dependent variable (R * .93). From a
common sense standpoint, the explanatory variables in equation 3 are key state
pretreataent cost determinants. Value of shipments provides a measure of
industrial activity within the state, and the number of POTKs within the state
requiring pretratment is a good indication of the amount of supervision
required at the state level. Both of these variables prove to be statis-
tically significant in equation 8.
Equation 5 in Table a-2 was selected to predict the cost incurred to
develop a pretreatment program at the state level. This selection is based on
2
the strength of the coefficient of determination (R 3 .90). This coefficient
shows that 90* of the observed fluctuation in development cost can be
explained by equation 5. The same explanatory variables are used as in the
implementation cost analysis but only the value of shipments is statistically
significant.
A-50
-------
.'-I
Kutia-
lion
Niimliur
1
2
3
4
5
6
7
8
9
10
II
12
13
"'
Dependent
Variable
Slale
Cum
Slale
Coat
Slate
Com
Stale
Cou I
Slale
Com
Slale
Com
iitale
Coll
Slutu
Com
Sliilc
Cou I
Slale
Cou I
Slate
Cuul
SI ill 4:
Cou l
Slate
Cou I
iituli:
Cum
Functional
ram
linear
log
1 inear
log
linear
log
Linear
log
1 incut
log
linear
log
1 incur
log
State Implement at ion Com Kegreution Ki|uat ioni
Value of
Shipment a
$ Million
(6.58)
.885
(768)
7.133
(4.9)
.535
(3.58)
Re-
quiring
Prctruat
menC
1.369
(2.20)
1.279
(703)
2.158
(2.31)
1.283
(6.69)
.483
(.71)
.615
(2.89)
.472
(.75)
.78
(4.54)
Aetna
Flow
(MOD)
1.843
(.25)
.247
(1.29
Popu-
lation
aandg)
.078
(7.16)
1.377
.072
(5.41)
.7)7
( 1 . 69
.O;H
(«. .84)
1 . t.l\
(B. VI
Total
of
POTS»
1 .29
(.34)
-.56
(-3.29)
Conatan
58.72
(.48)
-.574
(-.64)
77.37
(.84)
.089
(.12)
21.19
(.47)
2.462
(6.68)
2.487
(.05)
1.014
(1 .77)
-79.9
(-1.50)
-6.16
(-3.09)
-91 .4
(-1.62)
-4. 10
(-3.3)
-12.1.
(-1 .19)
-ft. 91
(4. 82)
Degreev
of
Freedom
11
11
11
II
11
11
11
II
11
II
11
II
II
Coeffic-
ient of
Deter-
lainat ion
I.'
.35
.84
.35
.82
.81
.86
.82
.93
.83
.76
.92
.81
.89
Stanilan
Error
186.2
.60
177.2
.62
95.1
.55
97.52
.42
88.6
.71
.41
92. B
.50
-------
TABLE a-2
STATE DEVELOPMENT COST REGRESSION EQUATIONS
Equation Dependent
Number Variable
State
1 Coat
State
2 Cost
State
3 Coat
State
4 Cout
State
5 Coot
State
6 Cob t
Value of
Functional Shipments
Form ($ million)
linear
log
linear 5.42
(9.67 )
log .732
(4.45 )
linear 5.32
(5.89 )
log .403
0.23 )
No. of
Requiring
Pretreatinent
1.96
(3.53 )
.827
(4.40 )
.058
( -14 )
.428
U.15.)
Degrees of
Constant Freedom
40.8 12
( 1.00)
1.57 12
( 2.32)
-2.88 12
(-0.14)
2.37 12
( 4.69)
-3.41 12
(-0.16)
1.81 12
( 2.62)
Coefficient of
Determination Standard
R2 Error
.53 101.3
.64 .80
.89 47.9
.64 .79
. 90 50 . 3
.6!! .78
-------
By entering data on the explanatory variables for each state into
equation 8 for implementation and equation 5 for development, an estimate of
the cost of each state's pretreattnent program can be derived. For the
purposes of the baseline analysis, the estimates for each of the 35 NPDES
states were summed to yield an estimate of the total cost of pretreatment at
the state level. The estimated operating cost for these 35 states is $7.4
million, and the estimated development cost is $5.9 million.
A-53
-------
A-5. SUMMARY ASSESSMENT OF STATS ENVIRONMENTAL REGULATIONS
AFFECTING INDUSRIAL WASTE CONTROL AT POTWS
Several regulatory options being considered in this analysis of the
National Pretreatment Program would result in state assumption of greater
responsibility for standard setting for administration and oversight of indus-
trial waste control programs at POTWs. The following cursory assessment of
state environmental regulations was performed to measure how far along states
are in acquiring the basic environmental regulatory tools which would enable
them to control industrial (and particularly toxic) waste impacts at POTWs.
The extent to which state environmental programs and regulations are lacking
or present may have implications on the feasibility and effectiveness of state
primacy in controlling industry-related problems at POTWs. Moreover, the
availability of existing state controls will determine the magnitude of the
state's administrative burden in implementing pretreatment programs for each
of the options. For instance, option 4 of the analysis of pretreatment
options (water quality standards for POTWs) calls on pretreatment programs to
be instituted at POTWs exceeding toxic water quality standards. In states
where these standards have not been promulgatd, a substantial administrative
burden and program delay may be encountered.
This assessment focuses on state legislation, rules, and programs for
water protection, hazardous and solid waste management, and air pollution
control. The existence of environmental programs, and, where applicable, the
date of authority delegation, are given. To highlight those concerns most
relevant to pretreatment, key regulations were examined. These included water
quality standards for toxic organics and heavy metals, solid waste regulations
affecting municipal sludge disposal options, and air rules affecting
incineration.
Table A5-I presents the findings of this assessment. A measure of
relative industrialization and value of manufacturing shipments is included to
allow a quick correlation between the magnitude of possible industrial waste
problems in a state and the extent of environmental regulation within that
state.
A-54
-------
TABLE A5-I
WATER PROTECTION
!'KO-
n.C.TJON
STA1>E
Manufacturers
Shipments
(? Million)
Alahaina
Alaska
Ari zona
Arkansas
Cali fornia
Colorado
Connect i cut
Del aware
1'lori.da
Ceoryia
llawai 1
Idaho
1 11 inoi:;
I ml iana
Iowa
Kaiusas
Kentucky
l.ou is tana
Maine
Mary 1 and
Ma:;i;adm:ii:U..s
Miclii (>an
Mi nneyoLa
Miiiii i us i ppi
Missouri
21
1
7
12
121
10
20
3
22
33
2
4
93
52
24
16
23
30
5
16
31
94
22
13
33
SOLID WASTE MANAGEMENT
'79
73
75
73
74
74
74
77
75
78
74
74
73
74
74
'81 '77+
73
68 xx
75
68 x x
74 x x
81 77
75 x x
74 xx
81 74
73
73 x x
72 x x
77+ x x
81 77-1 x x
74
71 x x
77
77 x
73
67
73
81 64 x x
81* 74 + x x
ttl. 73 x x
'72
72
76
73
?
72
75
74
74
72
74
73
73
74
71
72
75
68
74
—
71
54
70
78
73
'80
x
80
74
x
x
X
80
x
X
X
X
X
X
80
79
(*)
80
73
x
80
78
x
x
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X X**
XX X
X X
X
X*
X* X
X* X
X X
X X
XX X
X* X
X X*
XX* X
XX X
X X
X X
X X* X
X* X
X
X* X
X X* X
X X*
X X* X
'71
71
62
65
73
71
73
71
78
67
68
79
69
79
67
65
67
42
65
x
x
X
X
X
X
X
X
X
72 x
72 x
70 x
61 x
77 x
x
X
X
X
X
X
-------
TABLE A5-1 (Continued)
WATER PROTECTION
page two
SOLID WASTE MANAGEMENT
AIK PHO-
TO T I ON
Manufacturers ff
Shipments //
STATE ($ Million) // £
//* J
Montana
Nebraska
Nevada
New Hampshire
New Je rsey
New Mexico
New York
North Carolina
North Dakota
Ohio
Ok lahoiua
Oregon
Pennsylvania
Khode Island
South Carol Ina
South Dakota
Temteiiuce
Texaii
III ah
Vermont
Virginia
Wash ington
We fit Virginia
Wiijcoiu; in
Wyoming
3
9
0.9
4
50
2
87
1
96
13
13
80
5
20
2
29
93
'->
2
24
22
9
39
1
74
75
75
75
75
74
73
78
75
77
74
75
73
74
75
I
•//'/S/S/
W/ // //
73
76
IJlfl 67-1-
73
64
73
8U 66
74
73
75
73+
81 73+
67
77
810 72
77
73
75
65
81 // 67
70
73
74
81 73
73
x
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
//£
//<$
f /
72
77
(*)
y/i
7*i
77
79
76
76
n
72
71
75
71
73
75.
75
74
78
71
(*)
74
73
75
/-?
/ ^/
$/
x
X
X
X
(*)
X
X
X
80
79
7.6
x
79
72
x
X
79
80
x
X
X
X
X
X
X
X
X
X
X X
X
X
X X
X
X X
X
X
X
X
X
X
X
X
X X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x
X
X
X
X
X*A
X* X
X
X X
X* X
x
X* X
X* X
X*
x
X X
X
X*
X X
X X
x
X*
67 x
71 x
71 x
70 x
67
72 x
51 x
69 x
67 x
67 x
69 x
60 x
66 x
71 x
67 x
67 x
67 x
67 x
68 x
70 x
67 x
'! x
67 x
73
-------
EXPLANATION OF CATEGORIES AND NOTES FOR TABLE A5-I
Manufacturers Shipments - Total value oE manufacturers' shipments in 1977,
SIC codes 20-39 excluding 23 are represented in the survey
(Source: Annual Survey of Manufacturers, Dept. of Commerce, 1977)
NPDES Program -
Pretreatment -
Water Standards -
Toxic Organlcs/Metala -
Solid Waste Rules "1
Hazardous Waste Rules J
Landf ill
Impoundment
IDC i ncrat ion
Landupreading
Other
Date of EPA Program approval
(Source: UNA, Env I r o ninent a 1 Reporter)
Date of EPA approval of Industrial Pretreatment Program
// = pending HQ review
(Source: EPA memo)
Initial date of state adoption of Federally approved standards of water quality
(Source: UNA, Environmental Reporter)
Standards include numerical criteria for toxic substances organlcs or metals
(Source: EPA survey)
Date of initial adoption of rules by the states
(*) indicates that legislation has been unacted but rules have not been adopted
x in the IIW column indicates that SW rules also cover III/
Source: RMA, Envlronmental Reporter)
Guidance for disposal options is included in the SW and IIU ruJes
* criteria for Cd, Pb and/or PCIJs are specified
** disposal option is prohibited
"other" includes utilization for non-food chain landspreadlng, composting,
fuel utilization, marketing aa fertilizer
(S ou re e : E PA , Sludge Management: A Comparison Between Statg_ and Proposed
Federal On I delines. 1979)
-------
The following general trends and characteristics were observed:
o Water Protection Requirements and Guidance
- NPDES Programs:
Thirty-three states now have established EPA-approved programs. The
earliest approvals were obtained by California, Connecticut,
Michigan, Oregon and Washington in 1973. Most of the NPDES states'
programs were obtained in 1975.
- State Industrial Pretreatment Programs:
Programs in eight states (Alabama, Connecticut, Georgia, Iowa,
Minnesota, Missouri, Oregon and Wisconsin) have been approved.
Programs for four states are currently being reviewed by EPA
Headquarters.
- Water Standards:
Federally-approved water standards were adopted by ten states prior
to 1970. Nine of those ten states have also established contami-
nation criteria for toxic organics and metals. To date, 30 states
have established criteria for organics; twenty-nine have criteria
for metals. Coverage does vary significantly among the states. For
example, Maine rules specify acceptable levels for chromium while
Colorado rules cover total metals, CN, PCBs, and 17 pesticides.
o Solid Waste Management Requirements
- Solid Wastes:
Prior to 1976, 38 states had adopted rules governing the disposal of
solid wastes. By 1979, the remaining states had followed suit.
State rules in general treat landfill disposal of wastes. Sixty to
70 percent of the states also offer guidance for landspreading and
incineration methods. Less than half of the states have adopted
rules to specifically address "ether" options such as fuel utiliza-
tion or marketed fertilizer products. Many states do include, how-
ever, provisions for operation of "experimental" facilities on a
case-by-case basis.
- Hazardous Wastes:
Over 80 percent of the states have amended solid waste rules or
adopted a separate body of rules to specifically treat hazardous
wastes. However, state rules for hazardous waste management vary
dramatically. For example, Virginia has established a single rule:
"Hazardous wastes will be disposed of in a manner approved of by the
Health Commissioner." In contrast, the Utah rules consist of nearly
100 pages of regulations derived largely from the EPA rules.
A-58
-------
o Air Pollution Controls
Over 50% of the states had enacted legislation to protect air quality
prior to 1970. The regaining states have since adopted lavs for air.
Nearly 90% of the states have specifically addressed incineration as a
potential source of pollutants, although the extent of control varies
from state to state.
As evidenced above, there is substantial variation in the coverage and
vigorousness of the state regulations governing water and air protection and
solid waste management. Given this inherent tendency toward diversity, it is
probable that, without a uniform National Pretreattnent Program, State efforts
to regulate industrial wastes at POTWs would vary considerably. Moreover, the
above assessment shows that several states were motivated to take regulatory
action to comply with federal environmental laws. Although some states had
other motivations, it is conceivable that, in the absence of a mandatory
National Pretreatment Program, fewer states would take steps to control
industrial waste problems at POTWs.
A-59
-------
APPENDIX B
DOCUMENTATION OF PROBLEMS AT POTWS
INTRODUCTION
Appendix B provides documentation and review of technical problems at
POTWs. The objective of this search and in-depth analysis of the literature
and unpublished sources is to review POTW operational and maintenance data,
effluent quality, worker health and safety, and pretreataient program motiva-
tion. The pretreatment regulations were initially developed to prevent upset
problems caused by industrial waste at POTWs. This appendix is directed
toward specfic POTW problems not treated subsequently in the POTW computer
model. The case study analyses and results from Appendix 3 also provide
information and a basis for assumptions from which the POTW computer model has
been developed; see Appendix C.
Appendix B is divided into the following seven sections:
o B-l, Operation and Maintenance Data Base
o B-2, 132 POTW Local IU Control Assessment
o B-3, 77 POTW Visits
o 3-4, 40 PQTW Study
o B-5, Case Studies
o B-6, Worker Health and Safety, Air, and Groundwater
o B-7, Summary.
The O&M data file (Section 3-1) was developed by the Municipal
Construction Division of The Environmental Protection Agency (EPA) and
includes the investigation and findings of approximately 1,500 POTW site
inspections made annually by EPA and state personnel. The results of their
investigations are entered in a standard formatted computer file. This data
file covers a multitude of O&M problems that are readily quantifiable.
3-1
-------
The Assessment of 132 Local Industrial Wastewacar Control Programs
(Section B-2) vas a study conducted by JRB Associates, focussing on the
administrative issues surrounding the Pretreatment Program. Estimates of
pretreatnent in place, program motivation, monitoring and enforcement,
National Pollutant Discharge Elimination System (NPDES) violations, and other
administrative functions can be made from this study.
JRB has made site visits to 77 small « 5 MGD) POTWs (Section 3-3) to
assess their needs and compliance with the Preteatment Program. This data
source provides a firsthand report of the problems POTWs experience as a
result of industrial discharges. Section B-3 addresses specific industrial
discharge problems such as reported NPDES violations and sludge contamination.
The 40 POTW Study, Feiler and Southworth (1980), (Section B-4) was an
in-depth look at POTW toxicity levels and included continuous monitoring of
the plant influent, effluent, and sludge. This is one of the few studies that
has detailed analytical data on priority pollutants in POTW wastevacer
streams. The 40 POTW Study also provides a useful comparison to the 77 POTW
Study because the 40 POTW Study includes only plants that had a total flow
> 5 MGD.
Numerous published articles exist on case studies of POTWs with
Pretreataient Programs (Section B-5). These case studies provide data on POTW
operation before and after implementation of a Pretreatment Program.
Furthermore, some of these studies report the difference in influent and
effluent quality before and after pretreacment and discuss the benefits
derived from the program.
The potential environmental problems associated with industrial effluent
treatment are numerous. They include worker health and safety, air pollution,
and groundwater contamination. Section B-6 discusses these problems and
reports incidences where industrial effluent has caused environmental
problems.
Section B-7 is a generic summary of POTW operational problems.
3-2
-------
APPENDIX B-l
OPERATION AND MAINTENANCE DATA BASE SUMMARY
Publicly owned treatment works (POTWs) are inspected annually to
determine compliance with National Pollutant Discharge Elimination System
(NPDES) permits and to develop an operation and maintenance (O&M) data base
(Derieux 1980). The 1980 O&M data base includes information from 1,547 POTWs
located in 24 states with 78% treating less than 5 MGD.
The analysis of the O&M data base compares several key variables for
POTWs that receive industrial waste to POTWs that receive no industrial waste.
Information is not available in the database regarding POTWs that have or have
not instituted pretreatment. Approximately 21% of the POTWs report that they
receive some quantity of industrial waste. In reality, the percentage may be
much higher. Of the POTWs that report O&M problems associated with industrial
waste, 31% do not report the quantity of industrial flow into their facili-
ties; a possible explanaion is that these POTWs have not conducted an indus-
trial waste survey.
POTWs that receive industrial waste cite O&M problems associated with
that waste as the most frequent O&M problem (30% of all O&M problems). Of
these POTWs, 42% also report a problem with organic overloads, while 28% of
ail POTWs in the data base report an organic overload problem.
The percentage of POTWs having secondary treatment reporting major or
minor O&M problem associated with industrial wastes generally increases with
the average daily flow up to 100 MGD. In the range of 5 to 100 MGD 48 to 68%
of the POTW report major and minor O&M problems associated with industrial
waste.
An indicator of the significance of this problem is the violation of
NPDES permit requirements. More than 60% of the POTWs reporting O&M problems
associated wih industrial waste violate at least one of their permit require-
ments. The percentage violations by POWs increases only slightly with the
percentage industrial flow.
3-3
-------
Sewage bypasses occur when untreated or incompletely treated waste loads
are discharged to receiving waters. Of the POTWs receiving industrial waste,
about 35% report monthly sewage bypasses. On the average, these bypass events
occur 3 tines per month, each lasting close to 6 hours in duration. The
*
percentage of POTWs reporting bypasses is highest in the industrialized North
Central and Northeastern United States.
O&M DATA BASE
The O&M data base is compiled form reports of POTW inspections conducted
by EPA and the States. The purpose of these inspections is to ensure compli-
ance with the requirements of NPDES permits and of construction grants, and to
assess personnel and equipment performance. These inspections are required by
Section 210 of the Clean Water Act and the results are summarized and reported
to Congress annuually. Inspection frequency is determined by the requirements
of the State and the degree and type of problems encountered at each facility.
Some facilities are monitored more than once a year, while others are moni-
tored less frequently.
The data elements addressed by the inspections and contained in the O&M
data base are shown in Table Bl-I. Four generic categories of data are
represented:
o Identification information
o Facility datta
o Pollution load data
o Facility assessments.
Identification Information
Identification data include name, location of plant, the State permit
number, the type of receiving body, and the owner of the facility.
B-4
-------
TABLE 31-1.
Data Elements Contained in the
Operation and Maintenance Data Base
Sacsisa
• facility :tas«
• .-idaTMa
• £lac« ? trail 3usa«:
• 0«n«r sf raciiicy
• ~r?« ai Sacsiviaj 3ody
• Avarazm its 152 !l:w (=^e)
Facility lasa
• ?>•?• of S«v«r Sy»ean
(Caaaiaad/Saparasa)
• T«ar ?iaac is Oparaeian
• Stae* t££lu«at Scaaiiris
• Aabiaas Vacir Qualisy Seaadarsa ar
3»«* af Uc*lvia« Sody
• ** !y?ais«4 5::ua Cilarlaaead?
(diactsaeiaa)
• Ocsumoc* a£ S«w«r Cw«rii»w« ia
?laae ar Cp«er«4a
• Japerta of Creuadvacar CjnMaisAtiaa
?rsisi«aa
Caaeiaucm, I
• icr.«satlc if ?Uac
• ?t»K flew, drr inii -«c v«acr.*r '=?;;
• Aosuai iv«ragt 3CD« lead is i^il^ar.i
• Annua 1 «v*ra;« S3 lJ«c i2 Is^iucc:
:T-?«S af liiaac-riil uaaets
t: jyscea
• Japulacisn teuv/alcnt (3CD) si '^laustr
• ?opvLUei3n *Qtiiv»l«nc (SS) si tr.duatrlii
uaacaa
• Voi^aa sf ineujcrtal vaji«3
Car* =on:.-.i ;.- , tad ;*«« fl:w, (sga) , aad *r»
sootiiv isiluant iaa ti;ij«cc, S3 (r?/i},
SODj (=?/':) , 00 (35/1) r««liual thisrla.
(a«/l). csiijars Cscal tnd .'tcai p«r ICO =t)
• ?«re«nt rtaovii af «ach :*eerdad pollusaac
• ?r*qu«ac? a: iaaiyju far taes ;eU.u£aac
• racaivlcj i:riaa
stm of wn«c*ar •tlia.z saccs M?9£5 ;er=i:
Faciiirr Aas«s»s«ai taisrsacisa
• ;ouar
• ?«rsooati iaca - =aaa«r, =as
• .•usaanMae if :.w.a 5=«rat-.-a o
vaica trtaezaae j:
B-5
-------
Facility Data
Facility data include descriptive information on the P07W:
o Type of sewer system
o Year in which the POTW became operational
o Problems associated witth infiltration, overflow, and industrial
discharges
o State water quality standards for receiving waters
o State effluent standards
o Schematic of the POTW showing each treatment process component.
Pollution Load Data
Pollution load data include total and industrial flow rates, influent and
effluent BOD and TSS loading, NPDES permit requirements, pollution reduction
efficiency, and frequency of sampling and analysis.
Plant Assessments
Data in this category include an overall facility rating; individual
ratings of equipment and waste treatment component operation; a compilation of
personnel classification, certification, and training data; and specific
problems or deficiencies associated with POTW operations.
CHARACTERISTICS OF POTWS INCLUDED IN THE O&M DATA BASE
The sample size for 1980 in he O&M data base includes 1,547 POTWs
distributed across 24 States. The sample included states from 7 of the 10
EPA regions; region III (Maryland, Pennsylvania, Virginia, and West Virginia),
region VII (Iowa, Kansas, Missouri, and Nebraska), and region IX (Arizona,
California, and Nevada) are not included in the data base. More than 97% of
thes POTWs provide secondary treatment, and 78% receive an average daily flow
of less than 5 MGD. Figure 31-1 provides the distribution of POTWs in the O&M
3-6
-------
n KCi-idAi.i.
ill- I'lllflAKY
Ul
imi
•Ml
mi
411
10
211
in
AVEKAUt IIAII.Y FUN
20-Jtl HUI
i-20 HUB
l-i Will
li-1 HU>
IIMI
10
10
t'KltCI'.NTACE
UK SliCONIIAKY
Itt
*°
40
10
20
in
AVKKACE UAII.Y KIJIU
> 20 HCI)
1-20 MOD
l-i HCII
0-1 HCD
IIP TI'K'I'IAKY
I'l.ANTS
III
6(1
ill
10
III
AVIIIAU IIAII.V I'l.OU
ill - IIMI Mlill
i-2ll HUH
i-i
UISTUIIIIIIIOM
UK
16 I'HIHAKY
IIY
Avi:iiAi:t
UAII.Y
ri.iiu
(IK
t.<<'ii st
bY
AVKHACK.
IIAII.Y
KIJHJ
111
•> TIHTIAHY I'OIVs
BV
AVI luM.I'
DA IIY
II «U
FHJURK 111-1. DlstrlhuL ion Of POTWa.Tn The O&M Ifcitu Uase By Level Of Troiitmcnt
Anil Average Dally FJ.ow
-------
data base, presented by level of treatment and average daily flow. The total
daily flow of the POTWs in the O&M data base is 10,970 MGD; the mean flow for
these POTWs is 7.1 MGD, however this figure is positively skewed by several
extremely large POTWs.
At least 21 percent of the POTWs in the O&M data base receive some
quantity of industrial waste; the actual number is probably much higher. Due
to incomplete responses of the survey questions, the precise number of POTWs
that actually receive industrial waste cannot be determined. More than
70 percent of the POTWs that report receiving industrial waste provide secon-
dary treatment and have an average daily flow less than 5 MGD. The total
volume of industrial wastes received by POTWs included in the O&M data base is
6,061 MGD; the mean volume is 3.9 MGD.
SUMMARIES OF CONCLUSIONS AND FINDINGS FROM THE O&M DATA BASE
The conclusions that can be drawn from the O&M data base are explained in.
the following sections and are summarized below:
o The percentage of POTWs reporting occurrences of sewage bypasses is
highest in the industrialized North Central and Northeastern United,
Sates.
o Of the 330 POTWs that report receiving industrial waste, about 35 per-
cent report monthly sewage bypasses.
o Of the 139 POTWs that were evaluated for the operation of their sludge
disposal processes, not one received a totally satisfactory rating.
o Of the 330 POTWs which receive industrial waste, 42 percent report a
problem with organic overloads; of all the POTWs in the data base,
28 percent report a similar problem.
o Other than plant obsolescence, major O&M problems associated with
industrial waste and with sludge handling and processing rank highest
for all POTWs. Plant obsolescence was reported as a major problem by
355 plants; industrial waste, and sludge handling and processing, were
reported as major problems by 195 plants and 194 plants, respectively.
Of the plants that receive industrial waste, O&M problems associated
with that waste rank highest.
o Of the 476 POTWs that report O&M problems associated with industrial
waste, 79 percent receive less than 5 MGD average daily flow.
B-8
-------
o Of the 330 POTWs that report receiving industrial waste, 72% report an
O&M problem associated with the waste.
o The percentage of POTWs having secondary treatment reporting major or
minor O&M problems associated with industrial wastes generally
increases with the average daily flow up to 100 MGD. In the range of
5 to 100 MGD 48 to 68% of the POTW report major and minor O&M problems
associated with industrial waste
o More than 60% of the POTWs that report an O&M problem associated with
industrial waste are in violation of at least one of their NPDES
permit requirements.
Bypass Data
The O&M data base includes information on the monthly occurrence of
sewage bypasses at POTWs. Of all the reported sewage bypasses, 79% occur in
POTWs that receive less than 5 MGD average daily flow. While POTWs of this
size account for most of the monthly bypasses, larger POTWs also report the
occurrence of bypass events. Figure Bl-2 presents the percentage of POTWs
within average daily flow categories that report monthly sewage bypasses. The
figure indicates, for example, that about 35% of all of the secondary treat-
ment POTWs that receive 1-5 MGD average daily flow report monthly sewage
bypasses, and that about 89% of all the secondary treatment POTWs that receive
100-200 MGD report monthly sewage bypasses.
Bypass durations reported by POTWs and contained in the O&M data base
range from 1 hour per month to more than 24 hours per month. Of the 227 POTWs
that reported the duration of monthly sewage bypasses, 59% stated that the
average bypass lasts less than 10 hours, and 122 reported that the average
bypass lasts more than 24 hours. The mean duration of sewage bypasses is
5.9 hours; the mean frequency is about 3 occurrences per month.
The percentage of POTWs reporting instances of bypasses is highest in the
North Central and Northeastern United States; these geographic areas corre-
spond to EPA Regions II and V. Industrialization is very high in these
regions. Figure Bl-3 provides the percentage of POTWs within EPA's 10 regions
that report monthly sewage bypasses. Of the POTWs in EPA regions II and V,
47% and 55%, respectively, report monthly bypasses.
3-9
-------
100
90
ao
70
so
10
1
^
'l,^
•j-20 ?0-r>0 50-100
AVKKACL MAI I.Y FLOW (MCI>)
X
X
A
A
X
X
100-200
l-'ICUKK IU-2. I'r.KCKN'I'ACK <)!•' I'CVrWs Klll'OU'l'IIU; MONTHLY
SKWACK liYi-ASSi':;; KY AVKIJACK DAILY KI.HW CATKCOIMKS
D
- I'ltlHAKY
- BECONItAKY
Q
-------
FIGURE 31-3.
PERCENTAGE OF POTWs 3Y EPA REGION
WHICH REPORT BYPASSES.
3-11
-------
Of the POTWs that report monthly bypasses, 18% discharge into water
classified for body contact (swimming, etc.); 442 discharge into waters
classified for all uses except body contact, 332 discharge into waters classi-
fied for special use by the State; and 5% report no data on receiving waters.
The O&M data base does not contain a subcategory for drinking water usage.
Figure Bl-4 provides information on monthly sewage bypasses for POTWs
that report industrial waste as an influent to the plant. Of these POTWs,
about 352 report monthly bypasses.
Sludge Disposal
The O&M data base includes information on how sludge is disposed of by
the POTWs. Figure Bl-5 shows the percentage distribution of sludge disposal
techniques for the POTWs that reported this information. Sanitary landfill
and agricultural fertilizer appear to be the most common disposal techniques.
The third most common technique, long distance transport, is not really an end
disposal in itself. Presumably, a high percentage of the sludge reportedly
disposed of in this manner is actually landfilled or land spread.
Of the 139 POTWs evaluated for operational effectiveness of the sludge
dissposal processes, not one POTW was given a totally satisfactory rating.
All of these POTWs provide secondary treatment. Approximately 67* of these
POTWs were given a marginal ratingg for the operartion of sludge disposal
processes, and an additional 312 were given an unsatisfactory rating. More
than 702 of all of the marginal ratings were given to POTWs receiving less
than 5 MGD average daily flow.
Overloads
Overloads, whether hydraulic or organic, create an O&M problem for POTWs.
The O&M data base includes information on the relative length or overloads
(continuous or periodic), the type of overloads, and the causes of overloads.
Table 31-11 provides information on the types of overloads at POTWs, and
whether they are considered to have a major or minor effect on plant perfor-
mance. Of all the FOTWs in the O&M data base, 342 have a problem associated
B-12
-------
100
80
70
(.0
30
20
10
0-10 10-20 20-30 30-40
I'liKCKNT INWJSTKIAI. I-'I.OW
40-50
Ii li.l-4. I'KUCENTACIJ 01-' I'OTHti BY INDIISTIMAI, FLOW CATKCOIUES
Klil'OUTINC MONTHLY SKWA^K BYPASSES
tw
I
-------
KTCUKE Bl-5. 1'EKCENTAfiE OF AU- I'OTWu HEI'ORTINfJ
VAIUOUS TYPES OK Sl.HDOE DTf'OSAI. METHODS
-------
with hydraulic overloads, and 28% a problem associated with organic overloads.
Table Bl-III lists similar information for POTWs that receive industrial
waste. Of these POTWs, 77% have a problem associated with hydraulic over-
loads. Significantly, 42% report a problem with organic overloads, as
compared to only 28% of all of the POTWs in the O&M data base.
The distribution of the overload causes for all POTWs is shown in Figure
31-6. While infiltration accounts for two-thirds of the overloads for all
POTWs, industrial growth, increased service area, and rapid population growth
each account for about 9% of the overloads. For the 330 POTWs that receive
industrial waste, infiltration accounts for only 35% of the overloads, and
industrial growth accounts for 25%. Figure Bl-7 provides the distribution of
overload causes for POTWs that receive industrial waste.
O&M Problems and Deficiencies Reported by POTWs
O&M problems at POTWs have an adverse effect on the performance of the
plant. These problems include laboratory control, lack of personnel training,
and inadequate spare parts inventories, as well as problems caused by indus-
trial discharges. Figure Bl-8 shows that distribution of the types of major
O&M problems for all of the POTWs in the O&M data base. While plant obso-
lescence is rated as the most frequent O&M problem, problems associated with
industrial waste and with the sludge handling and processing equipment rank
second and third. For the 330 POTWs reporting that they receive industrial
waste, O&M problems associated with industrial waste rank highest, accounting
for 30% of all O&M problems. In these POTWs, plant obsolescence is cited as a
major O&M problem in only 12 percent of the reports.
Most of the POTWs that report an O&M problem associated with industrial
waste receive less than 5 MGD average daily flow. Figure Bl-9 provides the
distribution of POTWs in the data base which report an O&M problem associated
with industrial waste. Of these plants, 79% receive less than 5 MGD average
daily flow.
3-15
-------
TABLE Bl-II
Percentage of All POTWS Reporting Various
Types of Overloads
Overload Type
Periodic Hydraulic
Continuous Hydraulic
Periodic Organic
Continuous Organic
Major Problem
382
72
82
62
Minor Problem Total
242
52
92
52
622
122
172
112
842
282
TABLE 31-111
Percentage of All POTWs Which Receive Industrial
Waste Reporting Various Types of Overloads
Overload Type
Periodic Hydraulic
Continuous Hydraulic
Periodic Organic
Continuous Organic
Major Problem
422
52
182
122
Minor Problem
252
52
92
32
672
102
272
152
Total
772
422
3-16
-------
OVERLOAD CAUSE
100
90
80
70
60
to
§ 50
£
u
0 40
w &
M W
^ 30
B
u
Pi OA
Id ^u
P.
10
(I
7%
9X
9 %
9%
66%
x
-
COMHINED SEWERS 100
90
KAPII) POPULATION CKOWT1I
80
1 NCKIiASIil) SI'UVICIi AKKA
§70
__ „
S 60
o
* 50
w
o
<:
w /'°
«
W -„
ilNI'ILTKATION ^
20
10
0
13%
13%
14%
25%
35%
OVERLOAD CAUSli
INCREASED SERVICE AUFA
POPULATION CHOWTII
COMBINED SEWEKS
INDUSTRIAL GROWTH
SlNFILTRATION
I-MCURE HI-6. DISTR1IUITTON OF THE CAUSES OF
HYDRAULIC AND ORGANIC OVERLOADS
FOR ALL POTWS.
FIGURE Bl-7. DISTRIBUTION OF THE CAUSES
OF HYDRAULIC AND ORGANIC
OVERLOADS FOR POTWS WHICH
RECEIVE INDUSTRIAL WASTE.
-------
ta
H1
OO
111-8. TYI'Efl Or O&M "KOIil.EMS AH A PEKCENT OK AM.
06.M PKOHI.EMS KEI'OKTEI) BY I'OTWS
-------
AVERAGE DAILY KI.OW
ui
I
100
90
80
y
$ 70
3
p.
6 <•»
B
A.
S 5"
1
2 30
d
a 20
i 10
M
P.
/\
6%
15%
35%
>• 20 MCI)
5-20 MCO
1-5 MOD
0-1 MCI)
FIGURE IJl~'J. DI9.TRUJUTTON OF POTW9 REPORTING
AN O&M PROBLEM ASSOCIATE!) WITH
r.NUUSTI(lAL WASTE
-------
Figure 31-10 provides the percentage distribution of POTWs receiving
industrial waste which report an O&M problem associated with an industrial
waste. Of the 330 POTWs that receive industrial waste, 72% report an O&M
problem associated with that waste.
Figure Bl-11 provides information on secondary POTWs reporting this
problem as a percent of all POTWs in the seven categories of average daily
flow. While the percent of the smallest size POTWs reporting the problem is
low, the percentage increases up to POTWs receiving not more than 100 MGD.
This suggests that the industrial waste O&M problems are common to most POTWs,
NPDES Permit Compliance
The inspections of POTWs are made to ensure compliance with the require-
ments of NPDES permits and construction grants. The factors used to assess
plant performance and NPDES permit or construction grant compliance are:
o Monthly average flow (MGD)
o Maximum daily peak flow (MGD)
o Settleable solids
- influent (nig/1)
- effluent (mg/1)
- percent removal
o Suspended solids
- influent (mg/1)
- effluent (mg/1)
- percent removal
o BOD
- influent (mg/1)
- effluent (mg/1)
- percent removal
o Dissolved oxygen effluent (mg/1)
o Chlorine residual effluent (mg/1)
o Coliform per 100 ml
3-20
-------
100
80
70
to
60
50
20
10
0-5 5-10 10-15 15-20 20-25 25-3030-35 35-40 40-45 45-50'50-55 55-60 60-65 65-70 70-7575-8080-8585-90 90-95 95-100
PliKCIiNT INDUSTRIAL I'LOW
1'TCIMU 111-10. rKKCKNTACIJ or I'OTWs ItKCKl V INfl INDUSTRIAL WASTE KKl'OUTfNC
AM 0 t, M I'UOULKM AiJSOt'IATI'I) WITH INDIJSTIUAI. WASTK
-------
100
90
3C
> 70
60
50
40
<
30
20
10
MAJOR PROBLEM
n * MI-:
OR PROBLEM
0-1 1-5 5-20 20-50 50-100100-200 >200
AVERAGE DAILY FLOW (>!CD)
F'GURZ 31-11. PERCENTAGE OF SECONDARY ?OT«3 REPORTING MAJOR
AND MINOR 0&.M PROBLEMS ASSOCIATED VITH
INDUSTRIAL WASTE
3-22
-------
o pH range effluent
o Total phosphorous
- influent (mg/1)
- effluent (mg/1)
- percent removal
o Total nitrogen
- influent (mg/1)
- effluent (mg/1)
- percent removal.
Plants that reported an O&M problem associated with industrial waste were
examined for their compliance status their IR permits and construction grants.
More than 60% of the POTWs that report an O&M problem associated with
industrial waste also did not meet at least one of their permit requirements.
Of the 189 POTWs that reported an O&M problem with industrial waste and that
did not meet at least one of their permit requirements, 70% receive less than
5 MGD average daily flow. Using categories of percent industrial flow, POTWs
that reported the industrial waste O&M problem and that did not meet at least
one of the permit requirements were examined. Figure Bl-12 presents the
results of this examination. The point is that the percentage of industrial
wastes to a POTW is not an important parameter for determining O&M problems
and violations of NPDES permits.
Sources of Industrial Charges to POTWs
The O&M data base contains information on the principal types of indus-
trial waste discharged to the municipal systems. Not all POTWs that report an
O&M problem associated with industrial waste are able to specify either the
source or the volume of the waste; a possible explanaion is that these POTWs
have not yet conducted an industrial waste survey. Other POTWs responded with
snore than one source of industrial discharges. The narrative responses of the
POTWs have been entered into the data base using four digit SIC codes. A
total of 383 industries discharge waste to POTWs that report the O&M problem.
Because the POTW may receive industrial waste from more than one source, the
frequency distribution of industrial sources includes double counting. The
3-23
-------
101)
•JO
no
60
3
60
50
40
o
p.
30
M
-------
most frequent sources of industrial waste to POTWs that report an O&M problem
associated with industrial waste are, in descending frequency of occurrence:
o Textile goods, not elsewhere classified
o Electroplating, plating, polishing, anodizing, and coloring
o Chemicals and allied products
o Industrial machinery and equipment
o General contractors - industrial buildings and warehouses
o Scrap and waste materials
o Power laundries, family and commercial
o Restaurants
o Meat packing plants
o Poultry and egg processing.
These industrial sources reflect the four-digit SIC codes contained in
the O&M data base. If a more general accounting of industrial waste
discharges into POTWs with the O&M problem is desired, the three-digit SIC
industrial groupings can be used. This ranking is, of course, less specific;
it does however, tend to validate the four-digit rankings. There is some
reordering of the frequency distribution and there are several new industrial
waste sources. The most frequent three-digit groups of industrial waste
sources discharging to POTWs that have an O&M problem associated with that
waste are, in descending frequency of occurrence:
o Miscellaneous textile goods
o Coating, engraving, and allied services
o Meat products
o Groceries and related products
o Machinery, equipment, and supplies
o Chemicals and allied products
o Miscellaneous durable goods
o General building contractors—nonresidential buildings
o Laundry, cleaning, and garment services
o Dairy products
o Miscellaneous nondurable goods.
B-25
-------
B-2. ASSESSMENT OF 132 LOCAL INDUSTRIAL
WASTEWATER CONTROL PROGRAMS
DESCRIPTION
JRB performed a statistical assessment of industrial wastewater control
programs in selected municipalities to assess the local progress made in
controlling industrial discharges to POTWs (Saltzberg, 1981). The assessment
consisted of studying 132 municipal authorities that operated 294 plants. The
POTWs included in the assessment were a statistically significant sample of
the approximately 2,000 POTWs that are required to develop local pretreatment
programs. The results of the study sample yielded results about the universe
of POTWs with an error of +_ 302.
The data sought in the study were
o General facility data
o Industrial waste survey information
o Information on industrial users and industries regulated
o Legal authority for local programs
o Formal pretreatment programs and motivations for programs
o Industrial controls
o NPDES permit information.
CHARACTERISTICS OF POTWS IN THE ASSESSMENT
Of the 132 POTWs in the assessment, 512 received average flows equal to
or less than 5 MGD, and 492 received flows greater than 5 MGD. Close Co
three-quarters of the municipalities reported secondary treatment as the
highest level of treatment provided. Of the remaining municipalities,
172 percent provided tertiary treatment and 102 provided only primary
treatment. Approximately 172 of the POTWs indicated that operations are most
frequently carried out at or above design capacity.
Industrial flows to these POTWs varied with the size of the plant. For
POTWs that received average flows equal to or less than 5 MGD, 49% received
B-26
-------
less than 10% industrial flow. For che larger POTWs, 41% received less than
10% industrial flow. A profile of the percentage of industrial flows for all
POTWs in the assessment is provided in Table B2-I.
TABLE B2-I. DISTRIBUTION OF INDUSTRIAL FLOWS TO POTWS
Percent of
Industrial Flow
Received
0-10
11-25
26-50
51-75
76-100
No response
Percent
of POTWs
44
23
14
9
2
8
SUMMARY OF CONCLUSIONS AND FINDINGS FROM THE ASSESSMENT
The conclusions and findings from the assessment are summarized below,
and are discussed fully in the following sections:
o Of the 132 municipalities, 36% have not yet conducted an industrial
waste survey.
o Of the municipalities that have conducted industrial waste surveys,
73% have taken some action toward establishing a local pretreatment
program.
o Of the 120 municipalities that reported the total number of industries
connected to the sewerage system, 41% receive waste from 26 or more
industries.
3-27
-------
o The industry-related problems reported by the all municipalities in
the assessment are, in descending frequency of occurrence:
- Interference (38% of total problems)
- Passthrough (28% of total problems)
- Sludge contamination (18% of total problems)
- Other (16% of total problems; overloads and coloration problems were
most frequently cited).
o Of the municipalities with POTWs greater than 5 MGD and that reported
at least one industry related problem, only 112 have taken no action
toward establishing a pretreatment program; of the municipalities with
smaller POTWs, 59% have taken no action.
o Of the 63 municipalities with no industry-related problems, 64% had
local permits or ordinances that restricted industrial discharges; of
these municipalities, 63% regulated all local industry.
o Of the 127 municipalities reporting the status of formal pretreatment
programs, only 12% had implemented a program or applied for approval;
however, when asked whether limits against industry were enforced, 65%
of the municipalities indicated some enforcement activity.
o The motivations cited for developing a local control or a formal
pretreatment program are:
- Protection of POTW Operations (27%)
- POTW Cost Recovery (8%)
- Water Quality Improvement (8%)
- Sludge Quality Improvement (6%)
- POTW Worker Health & Safety (1%)
- State or Federal Requirement (38%)
- No Response (12%)
o Of all the municipalities, 94% had NPDES permits that controlled
conventional pollutants; 87% of the permits did not address metals and
85% did not address toxic organics.
Industrial Waste Surveys
Of the 132 municipalities in the assessment, 36% have not yet conducted
an industrial waste survey. Municipalities with POTWs that receive average
flows equal to or less than 5 MGD accounted for 70% of the municipalities that
have not conducted industrial waste surveys. Of those that have conducted
surveys, 86% conducted them after the passage of the Clean Water Act of 1977.
3-28
-------
In general, municipalities that conducted industrial waste surveys, or
that were in the actual process of conducting surveys at the time of this
study, had taken some action toward establishing a pretreatznent program. Of
the municipalities with plants larger than 5 MGD that conducted surveys, 89%
were in the pretreatment program planning, development, implementation, or
approval stage. Only 55% of the municipalities with smaller plants that
conducted surveys had taken action toward establishing a local program.
Overall, 73% of the municipalities that conducted industrial waste surveys
reported some action toward establishing a local pretreatment program.
Industrial Users
Of the 120 municipalities that reported the total number of industries
connected to the sewerage system, 41% received waste from 26 or more
industries. The distribution of the number of industries connected to the
sewerage systems of the municipalities is provided in Table B2-II.
TABLE B2-II. DISTRIBUTION OF THE NUMBER OF INDUSTRIES
SERVED BY INDIVIDUAL POTWS
Number of
Industries
0-10
11-25
26-50
51-75
76-100
MOO
Percent of
Municipalities
46
13
13
1
6
21
3-29
-------
Of the municipalities that reported no problems related to industrial
discharges, the mean number of industries connected to the sewerage system is
91; the range was between 0 and 2,250 industries. Of the municipalities that
reported at least one industry-related problem, the mean number of industries
connected was 220; the range was between 1 and 4,000 industries.
Industrv-Relaced Problems
At least one industry-related problem was reported by 43% of the
municipalities with POTWs receiving average flows equal to or less than 5 MGD
Of the municipalities with larger POTWs, 57% reported at least one industry-
related problem. Of all the POTWs assessed, 662 of the POTWs that received
between 11 and 50% industrial flow reported at least one problem.
The distribution of the types of problems reported is provided in
Table B2-III.
TABLE B2-III.
DISTRIBUTION OF THE TYPES OF PROBLEMS RELATED TO INDUSTRY
Problem Percent of
Total Problems
Interference 33%
Passthrough 28%
Sludge Contamination 18%
Other 16%
Seventeen percent of the municipalities reported that they experienced
two or more problems. Of those that reported other problems, overloads and
coloration were most frequently cited. Corrosion in pumps, foaming, oil anc
grease, and plating wastes accumulating in the anaerobic digester were also
B-30
-------
cited. When asked specifically whether these problems caused a NPDES permit
violation, 42% said no, 36% said yes, 19% did not know, and 3% prefsred not to
respond.
There are apparent differences in the way municipalities have responded
to identified problems related to industrial discharges. Of municipalities
with POTWs that receive average flows greater than 5 MGD, only 11% have taken
no action toward establishing a pretreatment program. However, of the
municipalities with small POTWs and with at least one problem, 59% have taken
no action toward controlling industrial discharges.
Of the municipalities that have large POTWs and that have no reported
problems related to industrial discharges, 74% have permits or ordinances
restricting waste. For the smaller POTWs with no problems, 56% use permits or
ordinances to regulate discharges to the sewerage system. Overall, 64% of the
municipalities with no identified problems have permits or ordinances to
restrict industrial discharges. Of this number of municipalities, 63%
regulate all the local industry.
Local Control and Formal Pretreatment Programs
POTWs were requested to answer several specific questions regarding their
initiations in controlling industrial waste. First, POTWs were asked whether
they enforced limits against industry. Of the POTWs in the assessment, 65%
indicated that they do enforce limits. The most frequently cited enforcement
activities were POTW monitoring, severe use ordinances, surcharges,
self-monitoring by industry, and face-to-face negotiations with industry.
The second question addressed the status of formal pretreatment programs,
developed in accordance with the General Pretreatment Regulations.
Of the municipalities that reported the status of their formal pretreatment
program, only 12% had applied for approval or were in the implementation
stage. Table B2-IV provides the status of formal pretreatment programs for
the municipalities in the assessment. Only 21% of the 65 municipalities that
had plants with flows above 5 MGD had taken no action, but 57% of the
67 municipalities with smaller plants had taken no action.
3-31
-------
TABLE B2-IV.
FORMAL PRETREATMENT PROGRAM STATUS
Level of Effort
Percentage of
Municipalities with
POTWs >5 MGD
Percentage of
Municipalities
with POTWs
<5 MGD
Percentage
of all
Municipalities
Planning
Developing
Implementing
Applied for Approval
No action
No response
34
28
5
12
21
0
24
6
3
3
57
7
29
17
4
8
39
3
In addition, municipalities were asked to cite their motivation for
developing either a local control program or a formal pretreatment program.
Table B2-V provides the distribution of the responses on motivation for
developing programs. Because several responses to the question of motivation
were received from some POTWs, the percentages in Table B2-V represent the
percent of all responses received, not a percent of all POTWs.
B-32
-------
Motivation
TABLE B2-V.
MOTIVATION FOR DEVELOPING PRETREATMENT PROGRAMS
Percentage of Percentage of
Responses from Responses from Percentage of
Municipalities Municipalities Responses
with POTWs with POTWs from all
>5 mgd <5 mgd Municipalities
Protection of POTW Operations
POTW Cost Recovery
Water Quality Improvement
Sludge Quality Improvement
POTW Worker Health & Safety
State or Federal Requirement
No Response
24%
13%
9%
9%
1%
38%
6%
30%
0
7%
2%
0
37%
24%
27%
3%
8%
6%
1%
38%
12%
Industrial Controls
Municipalities were requested to provide information on specific
industrial limits that exist set by local ordinance and permit mechanisms, and
on monitoring performed by the POTWs and by industry. Figure B2-1 shows the
pollutants restricted at the POTWs in the assessment. For evaluation
purposes, municipalities that had adopted an ordinance, issued permits, and
monitored industrial users were considered to have an operational pretreatment
program. Figure 32-2 provides the percentage of POTWs r-egulating specific
pollutant types, which were aggregated by average daily flow and percent
industrial flow.
A total of 31 municipalities, or 23%, reported that their POTWs conduct
no industrial compliance monitoring. For conventional pollutants, metals, and
toxics, 41%, 36%, and 32%, respectively, of the municipalities conduct
compliance monitoring. Twenty eight percent of the municipalities report that
their local industries do not self-monitor their discharges to the sewerage
system.
B-33
-------
B2-1.
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T.SS
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I'lflUKK H2-2. I'KKCIvNT (>!• I'OTWS Itl'ClU.ATI NC SI'KC I !• 1C I'OI.I.IITAMI1
TYI'KS IIY AVKUACI-: DAILY I'l.OU AMI) I'KKCKMT
IUD1ISI Kl AI, H OW
-------
NPDES Permit Information
Only 3% of the municipalities have no NPDES permit limits specified for
conventional, metal, and toxic pollutants. For individual pollutant types, 6%
of the municipalities had no conventional limits, 87% had no netal limits, and
85% had no toxic limits. A profile of the NPDES permit parameters for the
municipalities assessed is provided in Table B2-VI.
Five municipalities reported violations of at least one parameter in the
NPDES permits Co occur as frequently as 100% of the time. For conventional
pollutants, 31% of che municipalities with permit limitations reported that no
violations occurred. For metal pollutants, 25% of the municipalities with
permit limitations reported that no violations occurred. For toxic
pollutants, 14% of the municipalities with permit limitations reported that no
violations occurred.
TABLE B2-VI.
PARAMETERS LISTED IN NPDES PERMITS
Pollutant
Number of Limits
in Permit
Percent of Municipalities
with Specified Limits
Conventional
Metal
Toxic
None
More than 1
None
1-3
4-6
More than 6
None
1-3
4-6
More than 6
5
96
87
2
0
8
85
8
1
3
No Pollutants
No limits
B-36
-------
Receiving Waters
POTWs in the asssessment were asked the type of receiving water to which
they discharge and the use of that receiving body. In general, POTWs
responded with multiple answers to the use question. Rivers and creeks were
cited as the receiving body by 82% of the POTWs; of the plants receiving less
than 5 MGD average flow, 95% discharge effluent to rivers and creeks. Table
B2-VII presents the distribution of the types of receiving waters to which the
POTWs discharge.
Table B2-VIII presents the distribution of the uses of the receiving
water.
TABLE B2-VII
DISTRIBUTION OF RECEIVING BODIES
TYPE OF RECEIVING WATER
Rivers & Creeks
Oceans, Bays, & Estuaries
Lakes
Channels & Bayous
Settling Ponds
No Response
% OF POTWS
£ 5MGD
95%
0
0
0
1%
4%
% OF POTWS
>5MGD
71%
15%
9%
4%
0
2%
% OF
ALL POTWS
82%
8%
4%
2%
1%
3%
Because raany of these waters are typified by general uses, the responses
shown in the table are the percentages of the total responses. The most
frequently occurring response, fron both large & small POTWs, was recreational
water use.
3-37
-------
TABLE B2-VIII
DISTRIBUTION OF RECEIVING WATER USES
2 OF RESPONSES % OF RESPONSES
USE FROM POTWS <_ 5MGD FROM POTWS > 5MGD
Recreation
Water Supply
Commercial Shipping
Agriculture
Fish and/or Wildlife Refuge or
Preserve
Drainage
Industrial
Commercial Fishing and/or
Shell Fishing
Negligible Use*
No Response
29%
16
3
6
6
6
2
0
16
16
382
22
11
4
4
2
2
4
2
11
% OF
TOTAL
34Z
19
7
5
5
4
2
2
9
13
*The most common response categorized as "negligible use" was that the
receiving body "is not used for much." Further questions indicated that
stream flow is minimal, or too intermitent in nature to sustain a qualifiable
use.
B-38
-------
B-3. 77 POTW VISITS' SUMMARY
JRB Associates and several subcontractors provided technical assistance
to 77 POTWs from 1979 to 1980 (U.S. EPA 1979). Candidate POTWs were selected,
after screening, from a list identified by EPA Regional Offices and NPDES
States. Assistance involved evaluating and recommending, as appropriate, the
need for local pretreatment program development. The POTWs covered in this
assistance program were distributed over 22 States and all of the EPA Regions,
except Region X. A report was prepared on each POTW which included a review
of the plant operations, performance data, and discussions with POTW personnel
on operating conditions and problems. Major nondomestic users of each POTW
were visited to determine the quantity and origin of pollutants entering the
POTW. Each report reviews the sewer-use ordinance of each POTW in terms of
specific legal authority requirements under 40 CFR 403.
This data base was analyzed and is presented in this section of
Appendix B. The analysis included POTW operational problems, distribution of
categorical and noncategorical industries discharging to the POTWs, the
specific impact of electroplating and food processing discharges, and
industrial discharge limit setting and monitoring/enforcement practices.
Pertinent conclusions drawn from this analysis are presented below.
o Operational Problems
- 84% of process upsets are reported to be caused by industrial
discharges.
- 662 of the POTWs periodically violate their NPDES permit limits.
- 65% of these violations are reported to be caused by industrial
discharges.
- 19% of the POTWs have had heavy metal sludge contamination
problems.
- 87% of the POTWs reporting a known sludge contamination condition
attribute it to industrial discharges.
3-39
-------
o Industrial Distribution
- The food processing (51% of the POTWs have at least one such
discharge) electroplating (40%), mechanical products (35%), and
textiles (16%) industries were the most prevalent industrial
discharges found.
- 46% of the food processors, 50-64% of the electroplaters, 34% of
the mechanical products firms, and 7% of the textile industries
that discharge to POTWs provide some form of pratreatment.
o Impact of Electroplaters and Food Processors
- POTWs receiving electroplating discharges indicated four times the
known sludge contamination incidence as those POTWs that do not
receive electroplating discharges.
- POTWs receiving electroplating discharges indicated two times che
process upsets as those POTWs that do not receive electroplating
discharges.
- POTWs receiving food processing discharges indicated over twice as
many NPDES violations for residual chlorine and/or fecal coliform
as those POTWs not receiving food processing discharges.
- POTWs receiving food processing discharges indicated twice as many
biological and sedimentation process upsets.
o Limit Setting and Monitoring/Enforcement
- 19% of the POTWs have no limits on conventional pollutants,
47% have no limits on metals, and 57% have no limits on toxics.
- 68% of the POTWs do not monitor or enforce their industrial users
on a regular basis (at least once a year).
- 12% of the POTWs monitor for metals and 1.3% monitor for toxics.
- Approximately 30% of the POTWs have never performed a sludge
analysis.
BACKGROUND
Technical assistance in developing local pretreatment programs was pro-
vided to 77 POTWs from 1979 through 1980. JRB Associates and several sub-
contractors provided this assistance through a contract with Environmental
Protection Agency Office of Water Enforcement (EPA-OWE, EPA contract No.
68-01-5052). Candidate POTWs were identified by EPA Regional Offices and the
NPDES states. JRB contacted the candidate POTWs by phone and screened out
those POTWs that were not interested in assistance, that received little or no
B-40
-------
industrial wastewater flows, and/or that were in the process of developing
their local pretreatment with 201 Grant assistance. The POTWs selected were
distributed over 22 states and all EPA Regions, with the exception of Region
X.
An engineering team visited each POTW selected, reviewed plant operations
and performance data, and discussed operating conditions and problems with
POTW personnel. Major nondomestic dischargers to each POTW were also con-
tacted to determine the quantity and origin of pollutants that may interfere
with or pass through the POTW. Copies of pertinent data including monitoring
reports, financial reports, and POTW sewer-use ordinances were provided to the
team so that it could evaluate the POTW and determine local pretreatment
program needs.
A technical report was prepared for each POTW visited, describing the
POTW, the major nondomestic users, and any existing problems. Each report
included recommended pollutant discharge limits, suggested solutions to
operating problems, evaluation of the local sewer use ordinance with respect
to pretreatment legal authority requirements, a summary of the local
situation, and where warranted, a recommended a local pretreatment program.
The following data and conclusions have been developed from an overall review
and analysis of the 77 POTW reports comprising this data base.
This analysis was conducted to gain insight into the following questions.
o To what extent are the 77 small POTWs experiencing operating problems?
o Do industrial discharges appear to be contributing to POTW operating
problems?
o How are the industries that are considered to be possible sources of
problem pollutants distributed among the 77 POTWs?
o How many of the these industries are presently pretreating their
wastewater?
o Do certain POTW operating problems appear to be related to the
presence of specific types of industrial wastes?
o How many of the 77 POTWs have established specific pollutant limits?
3-41
-------
o How many of the 77 POTWs are presently monitoring their industrial
users?
The data base was analyzed by observing operational problems (including
NPDES permit violations, industrial user problems, sludge contamination, and
process upsets) distribution of industries using POTWs, impact of specific
users (electroplaters, food processors), discharge limits, and monitoring/
enforcement practices. The results of this analysis are presented below.
OPERATIONAL PROBLEMS
The 77 reports were reviewed to determine the extent to which the POTWs
were experiencing operating problems. Problems were classified into three
types: NPDES violations, sludge contamination, and plant upsets. The NPDES
violations category was subdivided into three additional subcategories: bio-
chemical oxygen demand (BOO) and/or suspended solids, residual chlorine and/or
fecal coliforms, and "other" (pH, NH3, P, metals, etc.). All of the POTWs
that reported sludge contamination problems listed metals contaminants, with
one POTW also reporting sludge containing a significant quantity of poly-
chlorinated biphenyls (PCBs).
Because many POTWs have not yet analyzed their sludge for contaminants,
the reports were also reviewed to determine which POTWs suspected sludge
contamination and which POTWs needed to analyze their sludge. POTWs that used
land application for final sludge disposal and those that had to change their
final sludge disposal method due to contamination were also noted. Three
major types of plant upsets were observed: sedimentation process upsets,
biological process upsets, and sludge handling process upsets.
The number of POTWs that reported industrial discharges contributing to
the three types of operating problems were recorded. To simplify the
analysis, frequency of occurrence was not addressed, and only those problems
that recurred at least yearly were recorded.
-------
Table B3-I summarizes the operational problems discussed above. From
this table the following conclusions were drawn:
o Two-thirds of the 77 POTWs experienced periodic NPDES violations for
one or more pollutants.
o Most of these NPDES violations were for BOD and/or suspended solids.
o Nearly two-thirds of the POTWs experiencing NPDES violations reported
that industrial waste contributed to the violations.
o Nearly one-fifth of the 77 POTWs have heavy metal concentrations in
their sludge that are high enough for the sludge to be considered
contaminated (i.e., not suitable for cropland or pasture application
and that could create leachate problems in landfills).
o Over one-fifth of the 77 POTWs have not analyzed for contaminants in
their sludge and probably should.
o Nearly one-fourth of those POTWs that should analyze their sludge are
suspected to have sludge contamination as a result of the discharge of
industrial wastewater containing heavy metals into their system.
\j Of the POTWs with known sludge contamination 87% reported that
industrial wastewater contributed to the contamination.
o Two-thirds of the POTWs with contaminated sludge have changed or will
need to change their methods of final sludge disposal because of the
contaminat ion.
o Over one-third of the 77 POTWs practice land spreading as a method of
final sludge disposal. ,
o One-fourth of the 77 POTWs are experiencing one or more types of
process upsets.
o Of the POTWs experiencing process upsets, 84% reported that industrial
wastewater contributed to the uspets.
o Biological process upsets were twice as prevalent as reports of sedi-
mentation process upsets, and four times as prevalent reports of
sludge-handling process upsets.
DISTRIBUTION AND PRETREATMENT OF INDUSTRIAL USERS
The food processing, electroplating, and mechanical products industries
were the most prevalent industries listed in the 77 POTW reports as possible
sources of problem pollutants. Generally, food processing wastewater has been
considered to be compatible with POTW treatment processes. However, in many
B-43
-------
UJ
TA1JLE 113-1
INCIDCNCE Of COIW Oft MI IN- PHO.UMS
1 i*f row*
I at lut.l
(III
1 -1 tantm
trubl-- LUI«4
HTOES Violation*
lua ••!/•• «.. -1 •• -«i»i
._j/_i ». c.u- tow. U4.-u>
«> it it .1 ii
>» ill in t» tit
tti
•i rone
vim HrMt
• UUll_i»
Sludge Con.anlnaUon
"••OM* CMIIka. _«Ml.ft_.
11 » (1 1) III II
HI >l IW HI III 111
111 -- III ill
mi ran. „, riml_ ^ ,--„.
* 1 *i* *«!••» h«->_* vl«- fc-AMi
Plant Uotcti
r._«.. -l.l.|- 1..-
1 U 1
II III II
______
tx.l «r r-.i.j
ffOTU. •• c.uc.4 by
"«k l-.u.lil.l
It It
111 111
— 141
_< tmv«
.lib UP..|.
-------
instances the quantity and strength of this wastewater has contributed to
shock loadings and overloading of BOD, suspended solids, and oil and grease.
Less than half of the food processors examined provide any form of pretreat-
ment, indicating that a number of the 77 POTWs in this study may be receiving
untreated wastewater from food processors. Some POTW operating problems could
be attributable to these dischargers.
The electroplating industry is a known source of wastewater containing
heavy metals, cyanide, and extreme pH values. At the time that the reports
were written, only 50-64% of the electroplaters were pretreating their dis-
charges to the POTWs. With the promulgation of the Electroplating Categorical
Pretreatment Standards, the percent of electroplaters that pretreat their
wastewaters should increase dramatically as the compliance date approaches.
Until they begin to pretreat, electroplating wastewaters will continue to be a
source of POTW operating problems.
The mechanical products industry consists of a wide variety of industrial
processes and products. The fact that a large variety of industries fall into
this category may be the main reason that so many POTWs reported that mechani-
cal products industries may be a possible source of problem pollutants. Due
to the variety of processes used, the pollutants discharged by these indus-
tries contain many different priority pollutants, including toxic organics and
metals, suspended solids, extreme pH values and shock loads. Approximately
two-thirds of the mechanical products industries listed in the 77 POTW reports
do not pretreat their discharges. This indicates that a large number of the
mechanical products industries discharging to the 77 POTWs do nothing to
control pollutants in their discharges.
Distribution of Industries
Each report described the major nondomestic dischargers that the engi-
neering team and the POTW staff considered to be possible sources of pollu-
tants that might interfere with or pass through the POTW. Table B3-II shows
the number of industries reported in each category and noncategorical group
and the percent of industries in each group that provide some form of pre-
treatment prior to discharge to the POTW. Only the industries considered to
3-45
-------
TABLE B3-II
DISTRIBUTION AND PRETREATMENT OF INDUSTRIAL USERS
CATSGORICAL/NON-CATEGORICAL INDUSTRIES
POTWs with
Categorical/
Non-categorical
Categorical Industry
Adhesives
Aluminum Forming
Automatic and Other Laundries
Electrical Products
Electroplating
Foundries
Inorganic Chemicals
Iron and Steel
Leather Tanning and Finishing
Mechanical Products
Organic Chemicals
Paint and Ink
Pesticides
Petroleum Refining
Pharmaceuticals
Photographic Supplies
Plastics and Synthetics
Plastics Processing
Printing and Publishing
Pulp, Paper, and Fiberboard
Rubber
Soaps and Detergents
Textile Mills
Timber Products Processing
Food Processors
Hospitals
Total
^Jf *«*)}% A V f\ f"
11 Ufflls G t w i.
Industries
1
2
16
5
50
6
3
3
4
38
8
4
1
1
2
1
2
2
3
7
4
2
14
1
52
9
Indirect
Number
1
2
11
5
31
5
3
3
4
27
7
3
1
1
2
1
2
2
3
6
4
2
12
1
39
S
Discharges
Percent
of 77 POTWs
1.3
2.6
14
3.9
40
6.5
3.9
3.9
5.2
35
9.1
3.9
1.3
1.3
2.6
1.3
2.6
2.6
3.9
7.8
5.2
2.6
16
1.3
51
10
Industries that
Pretreat
Number
0
1
6
4
25-K7)**
r\
t.
2
0
3
13
3
2
1
0
1
1
1
0
0
4
2
0
1
0
24
1
Percent
0
50
38*
80*
50-64*
23*
67
0
75
34*
38*
50
100
C
50
IOC
50
0
0
57*
50
C
7*
0
46*
11*
3-46
-------
TABLE 33-11 (Continued)
DISTRIBUTION AND PRETREATMENT OF INDUSTRIAL USERS
CATEGORICAL/NON-CATEGORICAL INDUSTRIES
POTWs with
Categorical/
Non-categorical
Categorical Industry
Septage Haulers
Photo Finishers
Waste Processor
Bottling
Glass Manufacturing
- Total
Number of
Industries
4
5
1
3
3
Indirect
Number
3
5
1
2
2
Discharges
Percent
3.9
6.5
1.3
2.6
2.6
Industries that
Pretreat
Number
1
4
0
0
0
Percent
25
80*
(mostly
for
Ag)
0
0
0
*Indicates percent of analysis included five or more industries.
**In one POTW, no pretreatment information was available for seven
electroplaters.
3-47
-------
be possible sources of problem pollutants are listed, not all of the indus-
tries that discharge to the POTWs. Therefore, the information in Table B3-11
cannot be used to determine the extent to which these industries are distrib-
uted throughout the 77 POTWs. However, the table can be used to assess the
percentage of the reported industries that are pretreating.
The number of POTWs that reported one or more industries in each category
or groups as possible sources of problem pollutants are listed below in
descending order. Only those industrial categories or groups listed by five
or more POTWs are presented.
Industrial Category or Group No. of POTWs
Food Processing 39
Electroplating 31
Mechanical Products 27
Textile Mills 12
Automatic and Other Laundries 11
Hospitals 8
Organic Chemicals . 7
Pump, Paper, and Fiberboard 6
Foundries 5
Photo Finishing 5
Pretreataent of Industrial Wastewater
The percentage of industries in each category or group that pretreat
their wastewater before discharging to POTWs is presented below in descending
B-48
-------
order. Only those categories or groups with five or sore industries are
presented.
Industrial Category or Grouo Percent of Industries That Pretreat
Photo Finishing 80
Electrical Products ' SO
Electroplating 50-64
Pulp, Paper, and Fiberbcard 57
Food Processing -6
Organic Chemicals 38
Automatic and Other Laundries 38
Mechanical Products 34
Foundries 33
Hospitals 11
Textile Mills . 7
IMPACT OF ELiCTRCPLATIRS AND FOOD PROCESSORS
EPA has promulgated discharge limits for electroplaters that discharge to
PQTWs. Slectroplaters have long been suspected as a major nondocestic source
of metals entering ?OT«s. Another nondoaestic discharger of major concern is
the food processing industry. This industry group is not a primary industry,
but its wastes enter a majority of U.S. POTVs and are a reported source of
continuous and slug loads of high strength 300, suspended solids, and grease
entering POTWs. For these reasons, the 77 POTW data base was analysed with
respect to JTPDES violations, plant upsets, and sludge contamination across
POTWs with and without electroplating discharges and with and without food
processing discharges. Table 33-111 presents these two analyses. It should
be noted th.it the data between industries cannot be compared directly.
Results indicate the following trends:
o POTW SPDES violations do not seen to be directly associated with
discharges froa electroplaters.
o POTWs receiving electroplating discharges showed four tiaes the known
sludge contamination incidence as those POTWs not receiving .electro-
plating discharges.
-------
TABLE 113-111
PERCENT OF POTHS RECEIVING GIVEN INDUSTRIAL WASTEWATERS
EXPERIENCING VARIOUS OPERATING PROBLEMS
POTUu Receiving
Electroplating
Uuutuwater
I'OTUs Hucalvlng
(l.i Klectruplatlng
Uuuleuutor
I'OTWu Receiving
food I'roceuuor
Uuul uwutur
I'OTWu Receiving
Uatiluwutur
Number
of
POTU
31
46
40
37
NPDES Violations
BOO Chlorine Other:
and/or and/or pll. Nil.
as focal Col. P. Metola
4SZ 13Z 26X
6/X 22Z 20Z
60Z 25Z IttZ
5« IIZ 241
Sludge
Contamination
Suupuctud Known
32Z 15Z
24Z 91
SZ IOZ
SX 24Z
Plant Upsets
Sedlaen- Blulog- Sludge Total
tat Ion leal Handling Proceuu
Procevuea Proceuucs Proreuueu Upuetu
IOZ 26Z 6Z 42X
7X IIX ?t 20Z
10Z 23Z 3t 3SX
SZ IIZ SZ 22Z
Ui
O
-------
o POTWs receiving electroplacing discharges had two times the number of
process upsets as those POTWs not receiving electroplating discharges.
o Although the proportion of POTWs reporting sludge handling problems
was snail, POTWs receiving electroplating discharges indicated over
twice as many sludge handling process upsets.
o POTWs receiving food processing discharges indicated only a slightly
higher incidence of NPDES violations for BOD and/or suspended solids
than those POTWs receiving no food processing wastewater.
o POTWs receiving food processing discharges reported over twice as many
NPDES violations for residual chlorine and/or fecal coliforms as those
POTWs not receiving food processing discharges.
o POTWs receiving food processing discharges had twice as many
biological and sedimentation process upsets.
SPECIFIC LIMITS AND MONITORING/ENFORCEMENT
The 77 reports were reviewed to determine whether the POTWs have specific
limits for conventional pollutants (i.e., BOD suspended solids, NH,, oil, and
grease), metals, and toxic organics. Many POTWs that do limit pollutants do
not set specific limits. Instead their requirements limit a given pollutant
in sufficient quantity to interfere with POTW operations. The results of this
review are presented in Table B3-IV.
The 77 reports were also reviewed to determine how many POTWs conduct
compliance monitoring of industrial discharges and/or have taken enforcement
actions against indusyrial dischargers. Any POTW that monitors industrial
dischargers at least once a year was considered to be conducting compliance
monitoring. The results of this review are presented in Table 33-V.
3-51
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TABLE B3-IV.
DISTRIBUTION OF POTW LIMITS FOR CONVENTIONAL POLLUTANTS
Percent of Pollutants
Conventional Metals Toxic Organics
Have Specific Limits 38 10 4
Have General or Specific
Limits 82 53 43
Have No Limits 18 47 57
TABLE B3-V.
PERCENT OF 77 POTWS EXHIBITING COMPLIANCE MONITORING
AND/OR ENFORCEMENT
Extant of Monitoring Percentage
None 68
Conventional 32
Metals 12
Toxic Organics 1.3 (1 POTW)
From these two tables the following conclusions can be made:
o Over two-thirds of the 77 POTWs do not routinely monitor their
industrial contributors
o Monitoring for toxic organic compounds is almost nonexistent (only one
of the 77 POTWs), while 4>3% of the POTWs have at least general limits
on one or more of these compounds.
o Only 12Z of the 77 POTW's monitor industrial contributors for metals,
while 532 have at least general limits for one or more metals.
o Roughly one-third of the 77 POTWs routinely monitor their industrial
contributors for conventional pollutants, while four-fifths have at
least general pollutant limits.
B-52
-------
B-4. 40 POTW STUDY SUMMARY
This study was conducted by the EPA Office of Water Regulations and
Standards, Effluent Guidelines Division, and focused on 40 POTWs providing at
least secondary treatment. Data collection for the 40 POTW Toxic Study
(1978-1980) has been completed. An intensive week-long sampling program was
conducted at each POTW to determine the occurrence and fate of priority
pollutants. This section presents a detailed analysis of the data (Feiler
1980, Southworth 1981). Conclusions that can be drawn from this analysis are
summarized below:
o Among the 40 POTWs studied, industry was found to be a significant
contributor of priority pollutants to POTWs. Variations in priority
pollutant concentrations can be attributed to the type and size of
industry discharging into the POTW.
o Approximately 15 organics, 8 heavy metals, and cyanide were found
consistently in POTW influents.
o POTWs that meet secondary treatment requirements provide good removal
of priority pollutants. Generally, these POTWs remove approximately
75% of the heavy metals, 80% of the total volatile organics, and 70%
of the total acid-base-neutral organic pollutants. Removals vary for
individual pollutants.
o POTW removal efficiency was found to be independent of the influent
pollutant concentration.
o POTWs that have pretreatment programs have lower concentrations of
priority pollutants in the POTW influent and effluent. For example,
total metals were 28% higher in influent that had no pretreatment and
24% higher in effluents. These trends carried through for acid-base
neutrals—76% and 59%, and for volatiles—315% and 299% for influent
and effluent, respectively.
o Priority pollutant metals removed at POTWs are incorporated into the
waste sludge.
o A significant portion of the volatile priority pollutants are
air-stripped during the treatment process, and consequently do not
appear in the sludge.
B-53
-------
B-4. 40 POTW STUDY
DESCRIPTION
From 1978 to 1980 Che Effluent Guidelines Division embarked on a study at
40 POTWs that operated with at least secondary treatment to determine the fate
and occurrence of the 129 priority pollutants. At each POTW an intensive
week-long sampling progran was conducted at appropriate sampling points,
including at a minimum the POTW influent, secondary effluent, primary sludge,
and secondary sludge (unless combined). The 40 POTWs were distributed
according to size, location, treatment process(es) utilized, and percent
industrial flow, to profile all POTWs with flows over 5 mgd that would be
required to implement pretreatment programs. All but 1 of the 40 plants
received over 5 mgd; the exception was a POTW that employed rotating
biological contactors. It was chosen to include that unit operation. Two
POTWs with virtually no industrial flow were included to observe baseline
conditions, while the other 38 POTWs had industrial flows ranging from
approximately 4 to 50% of total flow. Normally, samples were collected for
six 24-hour periods at each POTW. The results of the full study have not yet
been published by EPA but some preliminary results pertinent to the RIA are
presented in the following pages (Feiler 1980, Southworth 1981).
OCCURRENCE OF TOXIC POLLUTANTS
Over 100 of the 129 priority pollutants were detected once or more in
POTW influents during the 40 POTW Study, although most were present in only a
small percentage of the samples. The pollutants that were detected in core
than 502 of influent samples (and their average concentration) are listed
below.
Metals Organics
Zinc (717 g/liter) Toluene (214 g/liter)
Copper (224 g/liter) Benzene (20 g/liter)
Lead (98 g/liter) Tetrachloroethylene (125 g/liter)
Chromium (174 g/liter) Trichloroethylene (76 g/liter)
B-54
-------
Cyanide (544 g/Liter) Chloroform (16 g/liter)
Nickel (118 g/liter) Methylene (515 g/liter
Cadmium (38 g/liter) Bis(2-ethylhexyl)phathalate (45 g/liter)
Silver (9 g/liter) 1,1,1-Trichloroethane (223 g/liter)
Mercury (550 g/liter) Phenol (53 g/liter)
Ethylbenzene (18 g/liter) Butyl Benzyl Phthalate (11 g/liter)
1,2-Trans-Dichloroethylene Diethyl Phthalate (4 g/liter)
(7 g/liter)
Di-N-Butyl Phthalate Naphthalene (7 g/liter)
(9 g/liter)
In general, the pollutants in the influent were the same as those
detected in the effluent. However, some of the common volatile organic
pollutants were detected less frequently in sludges than in POTW influents.
PASSTHROUGH OF TOXIC POLLUTANTS .
POTWs were found to remove a varying degree of priority and conventional
pollutants. Table B4-I presents the median removal and passthrough for
individual metal priority pollutants and for the other major classes of
compounds. No data were available for beryllium, selenium, thallium, and
pesticides because all were detected too infrequently in POTW influents. The
following were the major trends observed in an analysis of these data.
o Of the metals, nickel had the greatest passthrough in terms of
percentage (68% pass through).
o Copper and zinc were the metals best removed by POTWs (82% and 75%
removal respectively).
o Toxic organics were also removed by POTWs. Volatile organics (which
predominate among the total organics) were reduced by 81% at the
median plant, with 19% subsequently passing through to the secondary
effluent.
ACCUMULATION OF TOXIC POLLUTANTS IN POTW SLUDGE
Virtually all of the metal priority pollutants removed by the POTW
accumulated in the resulting sludge streams. The concentration factors
(defined as sludge concentration divided by influent concentration) in both
3-55
-------
TABLE B4-I
MEDIAN REMOVALS AND PASSTHROUGH OF PRIORITY POLLUTANT IN POTWs
Pollutant
Metals
Antimony
Arsenic
Cadmium
Chromium
Copper
Cyanide
Lead
Mercury
Nickel
Silver
Zinc
Volatiles
Acid Extracts
Base-Neutral
Convent iona Is
BOD
TSS
COD
Oil & Grease
Total Phenols
Secondary
Median Percent
Removal
56%
50
50
70
82
59
57
51
32
70
75
81
97
64
90
91
81
84
73
Treatment
Median
Pass through
442
50
50
30
18
41
43
49
63
30
25
19
3
36
10
9
19
16
27
Advanced Wastewater Treatment*
Median Percent
Removal from
Secondary Effluent
ID
ID
ID
26
0
0
0
25
11
ID
14
33
25
0
62
41
17
15
63
Median
Passthrough
—
—
74
100
100
100
75
89
—
86
67
75
100
38
59
83
85
37
ID * insufficient data
*Based on seven plants with a variety of treatment
B-56
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primary, secondary, and combined sludges varied greatly. Depending on the
solids content and other factors, but usually ranged from 10 to 1,000.
Volatile priority pollutants that were present frequently and that were
sufficiently above their detection limits generally had concentration factors
between <1 and 10. The nonvolatile organic priority pollutants had
concentration factors between the two other groups.
Several priority pollutants that were found to be below their detection
limits in most POTW influents regularly were quantified in sludge streams.
Pollutants with this tendency included antimony, arsenic, silver, selenium,
phenanthracene/anthracene, and pyrene. For example, arsenic was measured
above its detection limit in only 15% of all influent samples, but in 94% of
all sludge streams.
Effect of Industrial Contribution on Priority Pollutant Occurrence
Table B4-II presents data showing the effect of industrial flow to POTWs
influent concentrations for specific priority pollutants. Two sources of data
were used as baseline priority pollutant concentrations:
o The average of two plants from the POTW data base that had little
industrial flow (plants No. 2 and 9).
o The average of the projected residential and commercial loading from
the EPA study of four cities. These represent samples from specific
interceptors that contained no industrial flow.
The comparative data used are the overall influent averages from the
40 POTW study, which included most of the categorical industries within
contributors to the POTWs. For many of the volatile organic pollutants the
baseline data were an order of magnitude or more lower than the 40 plant
average. The trend extended to the metals and nonvolatile organic pollutants,
although the percentage differences were smaller. Most of the toxic metals
were 2 to 6 times higher on the average for POTWs that received industrial
influent than in the cases where there were no industrial contributors.
B-57
-------
TABLE B4-II
EFFECT OF INDUSTRIAL FLOW ON SPECIFIC PRIORITY POLLUTANTS
Pollutant
Cadmium
Chromium
Copper
Cyanide
Lead
Nickel
Silver
Zinc
1 , 2-Dich loroethane
Methylene Chloride
1,1, 1-Trichloroe thane
Toluene
Te traca loroe thy lene
Tr ich loroe thy lene
Vinyl Chloride
Ethylbenzene
Methyl Chloride
Benzene
Chloroform
1 , 2-Dich loroproprane
Phenol
Bis(2-Ethylhexyl)
Fhthalate
Pentachlorophenol
Butyl Benzyl Phthalate
40 POTW Study
Avg. 2 Plants with
Low Industrial Flow
4
63
62
80
54
34
6
219
1
7
<5
7
5
18
<5
2
1
6
5
<5
3
8
1
<20
EPA 4 City Study
Avg. Residential
and Commercial*
1
37
59
1
43
8
3
130
0.1
NR
3
6
14
7
NR
2
NR
1
5
NR
5
5
4
8
40 POTW Study
Avg. All Plants
39
175
225
574
99
119
9
718
585
516
223
218
127
77
46
22
21
21
17
11
55
45
13
12
NR • not reported
All units are ug/1
*Adams et al 1981
B-58
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Effect of a Pretreatnent Program on POTW Influent and Effluent Quality
The data front Che 40 POTW study were examined to determine whether there
were any differences in influent and effluent quality between cities that had
exemplary pretreatment programs at the time of sampling and cities that had
not yet developed their pretreatment programs. The classification of the
pretreatment programs were largely subjective and judgmental, based on factors
such as completion of detailed industrial waste survey, sampling, analysis,
flow measurement and regulation of industrial discharges, publication of a
comprehensive ordinance, maintenance of facilities, and personnel exclusively
devoted to industrial waste. Nine of the 40 POTWs were judged to have such a
program. These nine POTWs had between 7 and 44% industrial flows with a
median of 16%. For comparison, the remaining 31 plants had a median
industrial flow of 18% and a range of 1-50%.
Table B4-III shows the average concentration for each priority pollutant
fraction. The influent from plants with pretreatment programs is lower than
plants without pretreatment for all classes of priority pollutants although
the trend does not extend to each pollutant. For example, total priority
pollutant metals were 28% higher in the influents of POTWs without
pretreatment programs than in POTWs with programs; acid base neutrals were 76%
higher and volatiles were 315% higher in the POTWs without pretreatment.
Effect of Toxic Pollutant Concentration in Influent on Removal of
Toxic Pollutants
Preliminary data from the 40 POTW study indicate that removal of any
particular toxic pollutant is not affected to any degree by the influent con-
centration of that pollutant. At this time, regression analysis has been
performed for only the most commonly occurring metal and volatile priority
pollutants, and the data indicate that removal for each is almost completely
independent of influent concentration. The significance of this analysis is
that added concentrations of toxic pollutants contributed by industry will
only be removed by the POTW at its normal removal rates. Removal efficency
will not increase or decrease as influent concentration increases. However,
at very high concentrations of priority pollutants (higher than those
encountered in the 40 POTW study) interference with the POTW can occur,
reducing both conventional and toxic removal efficiency.
3-59
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TASIS 34-111
OF PSZT8EATJ2JIT PSOC2AM OH CIFLUEST COHC23TJIATIOS OF SPECIFIC PXIORIT? POU.UTA.NTS
Pollutant
Cadaita
Caroedtaa
Copper
Cyanide
Lead
Hickel
Silver
Zinc
Total of all Metals
1,2 Dichloroethane
Methylene Chloride
1.1,1 Trichloroethane
Toluene
Tecrachloroethylene
Trichloroechylene
Vinyl Qloride
Eehyl 5«ni«a«
Xcchyl Chloride
Senses*
Chlorofora
1,2 Dichloropropane
Total of all Volatile*
Phenol
Si* (2-SthylaexTUPhthalate
?encachloropheno 1
Butyl Senzyl ?hthalate
Total of all Acid Sue Heutral*
Influent
Plant* with
Prograa*
22
147
237
563
33
82
10
470
1607
S-0
148
43
132
31
74
2
20
3
23
9
5-0
334
42
47
I
5
107
Cug/liter)
? lints witiiout
?rograa*
40
179
222
379
112
129
8
786
2037
718
597
264
236
147
73
36
21
24
18
17
13
::i6
36
43
15
12
188
Effluent
Plant* with
"rogruas
2
24
41
142
7
68
1
92
383
3
36
10
6
12
3
0
1
44
0
6
0
178
0
21
0
0
22
(ug/liter)
Planes vitaout
Program*
3
36
38
169
17
62
1
186
514
194
&30
32
12
21
6
3
0
5
1
6
0
711
1
^ 1
* A
3
0
35
3-60
-------
B-5. CASE STUDIES OF POTW OPERATIONS
SUMMARY
A limited number of POTWs were examined to determine and assess
differences in POTW operating parameters before and after industrial waste
pretreatment processes were initiated. The POTWs were analyzed to determine
the effect of pretreatment programs on elminating or reducing environmental
problems, and to determine the motivation involved in addressing industrial
waste control. The municipalities were selected because descriptions of thai:
industrial waste control programs have been published in the available
literature. The municipalities represent a variety of population sizes,
service areas, waste flows, and types and quantities of industrial flows.
Some of the POTWs that were evaluated intiated control programs as early as
1961, but most programs were started in 1969-1970. Two of the POTWs started
their programs in 1978. The types of industrial .users covered in this
analysis include:
o Chemical Manufacturers
o Commercial Laundries
o Dairies
o Electroplaters
o Fabricated metal Manufacturers
o Food Processors
o Petroleum Refineries
o Steel Mills
o Textile Manufacturers
The general conclusion drawn from this analysis is that percentage reductions
of pollutants improve with pretreatment program implementation.
Most of the POTWs adopted their local pretreatment programs prior to the
publication of the General Pretreatment Regulations of 1978. The generic
B-61
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reasons these POTWs gave for controlling industrial flows into their treatment
plants are:
o To improve sludge treatment, handling, and disposal practices
o To improve water quality
o To protect POTW systems and operations.
Of the POTWs that stated reasons, 14% cited sludge disposal problems, 43%
cited water quality problems, and 43% cited POTW protection. In addition, one
POTW developed its local program in order to accommodate a new industry that
planned to locate in the area.
DESCRIPTION
The available information for several POTWs was examined and analyzed to
assess differences in POTW operating parameters before and after industrial
waste pretreatment programs. Information sources included academic and trade
literature, published reports by POTWs and EPA, and JRB's telephone survey of
nine POTWs. Responses to the telephone survey are provided at the end of this
Appendix. In all, 19 municipalities were examined in detail as case studies;
of these, 8 were found to have sufficient documentation on pretreatment to be
included in this Appendix. Table B5-I provides an overview of the charac-
teristics of the municipal treatment facilities included herein.
The purpose of this analysis was to determine the effect of industrial
pretreatment on POTW pollutant removal efficiencies. While some of the
literature and published reports provide data specifically suited to this
purpose, many only provide descriptive information on how the local pretreat-
ment program was established, and what lessons were learned. As a result, the
sample size for the removal efficiences of some pollutants is quite small.
Telephone surveys of nine POTWs were used to improve the sample size. A
followup form was sent to the POTWs (see Figure 35-1).
3-62
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TABLE 85-1
OVCHVU'U Of I'OTWS EXAHINKO AS CASE STUDIES
IIHC ipality
Mime ie, Indiana
l.iia Angeles Country,
Cal i foriiia
Grand Kupida
Michigan
Oakland. Cali furhi a
Chicago, IIIinois
<2r eenubnro,
llurtli Carolina
Average Daily
Flow (MCi>)
18
Percentage
niliiut rial Flow
It')
1.500
26
Major
Iniluatries
31Z Foundries, Metal Platers,
Manufacturers of Automative
Parti
IBZ Petroleum defining, Fahricated
Metals, Pa |ior. Food Clii-inical s
Nl) Electroplates
HZ Pigment Manufacturing,
Organic Clirmirsl Kefining,
Pelioliu-m Piotlucts 1'iouc-au ing ,
Net a I Plating, Food
Processing
HI) Metal Platers, Steel Hills
I7X Textile M.inuf actnrers ,
Cigarette Miintif ac t in ers ,
Heat Pakrers, (fairies, [ooil
Processors, Metal I'l alt-is,
Clieuical Manuiuctiirerd
L'liain|>ai|;n, Illinuia Nl)
Orangi- Count ry , 71 1
Cnl i fornin
IZ Fu<»i I'roceasora
201 fleet n>|.| alt MI; , l'rint<:.l
Circuit Mnnu lac t eres ,
Biiltery Manufacl nrvr ' s
Paper Printing In.lusl i i i-s
till - No Dill a
-------
Pollutant
BOD
TSS
Influents
Effluenti
Slmlge
Units
B«fore(V«ar)
A(ter(¥<"r)
Before(Y"r)
*rt.r(Ye")
„ ,
Bafoio
I
F«t, Oil, «n
-------
CHARACTERISTICS OF POTWS SELECTED AS CASE STUDIES
POTWs selected for case studies were chosen because the municipalities
were representative of a variety of population sizes and service areas,
average daily flows, types of industries, and quantities of industrial flow.
Several POTWs initiated industrial pretreatment programs for conventional
pollutants as early as 1961, but most initiated programs for conventional,
toxic, and/or heavy metal pollutants in 1969 and 1970. Two POTWs started
their programs as late as 1978. The sources of industrial waste discharged to
the POTWs in the case studies include:
o Chemical manufacturers o Food processors
o Commerical laundries o Petroleum refineries
o Dairies o Steel mills
o Electroplaters o Textile manufacturers
o Fabricated metal manufacturers
SUMMARY OF FINDINGS FROM THE CASE STUDIES
To determine the effectiveness of industrial pretreatment programs in
terms of removal efficiencies of specific pollutants, influent, effluent, and
sludge concentrations were analyzed before and after program implementation.
The results of this analysis are presented in Table 35-11. The general trend
for the group of pollutants is toward improved removal efficiences after pra-
treatment program implementation. The most consistent percent reduction
appears to be for influent metal values; for the group of eight metals, the
case studiees indicate a 43% reduction has been achieved. Table 35-11 sug-
gests that higher removal efficiencies can be obtained at lower influent
concentrations; presumably, a greater percentage of the metals are adsorbed
onto the sludges. However, at least one POTW in the case studies implemented
new and additional treatment operations at the same time as industrial control
programs were implemented. Therefore, it is sufficient to say that the
general trend is toward improved removal efficiencies when past influent
values are compared to recent values.
3-65
-------
TABLE 85-11
PERCENT REDUCTION IN POLLUTANT VALUES AKTER IMPLEMENTATION OF
PRETHEATMENT PROGRAM FOR VARIOUS POTWS FROM CASE STUDIES
Parcent Reduction in
Parcent Rmluction in
Influent Value*
Pollutant*
BOD
TSS
Plieno 1 a
Fat*, Oil* anil Crease
He-till »:
Arsenic
CadwiiM
Ctifumiiiw
Cu|ip |
|