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     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

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    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

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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

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                                 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

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                                  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

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                        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

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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

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     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

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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

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                              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

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                             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

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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

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   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

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                            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

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     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

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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

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   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

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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

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  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

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          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

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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

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         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

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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

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                       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

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     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

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                                 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

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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


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                                                             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

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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.

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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

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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

-------
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.
                                     3-107

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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).
                                      3-108

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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.
                                       3-109

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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

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                                 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

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                           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"

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                        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

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   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

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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

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        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

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                       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

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                        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

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     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

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              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--

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     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

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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

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   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

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                            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

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     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

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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

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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

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     (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

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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

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     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

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                   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

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           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

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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
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
                                  2S91
                                  335*
                                  3355
                                  3357
                                  3398
                                  3*11
                                  3*63
                                  7213
                                  7218
                                  75*2
                                  3691
                                  3692
                                  UU
                                  1112
                                  1211
                                  1213
                                  3<»79
                                  3351
                                  3357
                                  3*63
                        OJ
                        c.
                        o
                        55
                       O
                        so
3*71
3*79
2392
3361
3362
3369
3321
3322
3323
332H
3325
2361
2812
2813
2316
2819
3312
3313
3315
3316
3317
3111
2511
251*
2522
2531
25*2
2591
2599
3069
3079
3293
3312
3315
3317
3321
3325
33*1
3351
335*
3356
3357
3361
10 Mii.nHf.il. A_ P.-.QtJCiS ^^
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
J6 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 a
16 MECHANICAL PRODUCTS \
16 MECHANICAL PRODUCTS .=
16 MECHANICAL PRODUCTS v
16 MECHANICAL PRODUCTS <~-
16 MECHANICAL PRODUCTS £
16 MECHANICAL PRODUCTS -
16 MECHANICAL PRODUCTS £
16 MECHANICAL PRODUCTS <-
16 MECHANICAL PRODUCTS -
16 MECHANICAL PRODUCTS -
16 MECHANICAL PRODUCTS I
16 MECHANICAL PRODUCTS £
16 MECHANICAL PRODUCTS "=
16 MECHANICAL PRODUCTS 9,
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 :
t6 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS -;
16 MECHANICAL PRODUCTS

;JCfi
i 3399
, — _• * j-
3*00
3*01
i 3*02
'' 3*03
3«0*
3*05
j«C6
3*07
3*38
3*09
3n!0
3*12
3*13
3*1*
3*15
3*16
3*17
3*18
3*19
3*20
3*21
3*22
3^23
3*24
? 3*25
f 3*26
• 3*27
3"23
1 3*29
, 3*30
' 3*32
3t33
3*3*
3 3*35
3*36
3*37
3*33
3"39
3**0
3**1
3*-2
3*^3
3«A*
3**5
3*>6
3**7
3**8
3**9
3H50
3*51
3*52
3*53
3*5*
3*55
3"56
3*57
3*58
3*59
3*.60
3*61
3*62
3*6*
•5.. £ C
                                         C-21

-------
iA3LE C3-I1.  ETCHING OF SIC  CODES WITH CATEGORICAL INDUSTRIES 'Cc- '-."
1£ MECHANICAL PRODUCTS ' — -..
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PHCDUCTS
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 g.
16 MECHANICAL PRODUCTS O
16 MECHANICAL .PRODUCTS «
16 MECHANICAL 'PRODUCTS
16 MECHANICAL PRODUCTS >
16 MECHANICAL PRODUCTS 7}
16 MECHANICAL PRODUCTS a
16 MECHANICAL PRODUCTS /3
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS g3
16 MECHANICAL PRODUCTS •*
16 MECHANICAL PRODUCTS «
16 MECHANICAL PRODUCTS ^
16 MECHANICAL PRODUCTS 5"
16 MECHANICAL PRODUCTS £
16 MECHANICAL PRODUCTS u
16 MECHANICAL PRODUCTS 3
16 MECHANICAL PRODUCTS a .
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 ;
?6 MECHANICAL PHCDUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS
16 MECHANICAL PRODUCTS '
16 MECHANICAL PHCDUCTS
16 MECHANICAL PRODUCTS
3*6o
3*67
3*68
3*69
3*70
3*72
3*73
3*7*
3*75
3*76
3*77
3*78
3*80
3*31
3*82
3*83
3*8*
3*85
3*86
3*37
3*33
3*89
3*90
3*91
3*92
3*93
3*9*
3*95
3*96
3*98
3*99
3500
3501
3502
3503
350«.
3505
3506
3507
3508
3509
3510
3511
3512
3513
351*
3515
3516
3517
3518
3519
3520
3521
3522
3523
352*
3525
3526
3527
3528
3529
3530 •
3531
3532
3533
IB MECHAMCAt
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
15 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
16 MECHANICAL
FiiCCUCIS.
PRODUCTS: ~^-~\
PSODUCTS-
PRODUCTS:
PRODUCTS;
PRODUCTS
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. ,..->•..

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^

'^ -;
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 '

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{
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i
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i
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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

-------
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

-------
     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

-------
?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

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          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

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          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

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                             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

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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

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                                                                                                                      ^1   I              I   I              I   I <»-*•. *£.'•*»   I
                                                                                                                                                   • tU*«lb*«l«Ml
                                                                                                                                                                                         to4|i>l*|k|lt«(M
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                                                              *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

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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

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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

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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.
                                     D-19

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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
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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.

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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.
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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
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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
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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

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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.
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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

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                     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

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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

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Waste Management Practices for Pharmaceutical Industry, EPA

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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

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                         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;..

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                                           •"> 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

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                        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

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                          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.

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     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.

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                                  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

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     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

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          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

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(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.

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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

-------
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

-------
 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

-------
                                                                      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)

-------
                                                                    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.

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                                                               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.

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                                                                    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.

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                                                               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

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                                                               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

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                                                         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

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                   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

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                                  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.
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                                    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
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-------
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

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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

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                                            111-8.   TYI'Efl  Or O&M "KOIil.EMS AH  A PEKCENT OK AM.

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-------
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                            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
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    60
    50
    40
<
    30
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                                                      MAJOR PROBLEM
                                               n * MI-:
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        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

-------
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-------
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

-------
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                                        A«I-.IIAI:K liAIIY llou
                                                                                                                                I'llll I III IMIHI-, IHI/M HOW
                                                    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

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                          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

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                              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

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     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

-------
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

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                                   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

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                     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

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                          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

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                         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