Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Appendix
A
EXAMPLE
NAICS
AND
SIC
CODES
FOR
THE
METAL
PRODUCTS
&
MACHINERY
FINAL
EFFLUENT
LIMITATIONS
GUIDELINES
AND
STANDARDS
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Appendix
A
Example
NAICS
and
SIC
codes
for
the
Metal
Products
&
Machinery
Final
Effluent
Limitations
Guidelines
and
Standards
The
scope
of
the
MP&
M
regulation
includes
facilities
that
discharge
process
wastewater
from
oily
operations
and
manufacture,
maintain,
or
rebuild
metal
parts,
products,
or
machines
used
in
the
following
sectors:
Aerospace,
Aircraft,
Bus
&
Truck,
Electronic
Equipment,
Hardware,
Household
Equipment,
Instruments,
Mobile
Industrial
Equipment,
Motor
Vehicles,
Office
Machines,
Ordnance,
Precious
Metals
and
Jewelry,
Railroad,
Ships
and
Boats,
Stationary
Industrial
Equipment,
and
Miscellaneous
Metal
Products.
In
addition,
state,
local
and
federal
government
facilities
that
discharge
wastewater
from
oily
operations
and
manufacture,
maintain,
or
rebuild
metal
parts,
products
or
machines
(
e.
g.,
a
town
that
operates
its
own
bus,
truck,
and/
or
snow
removal
equipment
maintenance
facility)
are
also
covered
by
the
MP&
M
rule.

EPA
also
evaluated
job
shops
and
printed
wiring
board
facilities
for
the
final
rule
(
see
Section
6.0).
As
described
in
Section
9.0,
these
facilities
are
not
regulated
by
the
MP&
M
effluent
guidelines.

Table
A­
1
lists
of
example
Standard
Industrial
Classification
(
SIC)
codes
and
North
American
Industrial
Classification
System
(
NAICS)
codes
associated
with
the
various
MP&
M
industrial
sectors
and
the
two
industrial
sectors
also
reviewed
for
the
final
rule.
Please
note
that
this
list
is
not
intended
to
be
exhaustive,
but
rather
it
provides
a
guide
regarding
entities
that
may
be
within
the
scope
of
the
MP&
M
industry.

Table
A­
1
Example
SIC
and
NAICS
Codes
Associated
with
MP&
M
Industrial
Sectors
Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Aerospace
33641400
3761
Guided
Missiles
and
Space
Vehicles
33641500
3764
Guided
Missile
and
Space
Vehicle
Propulsion
33641900
3769
Other
Space
Vehicle
and
Missile
Parts
A­
1
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Aircraft
33641100
3721
Aircraft
33641200
3724
Aircraft
Engines
and
Engine
Parts
33641300
33291220
33399520
33399620
3728
Aircraft
Parts
and
Auxiliary
Equipment
48811110
48811910
48819000
56172020
4581
Airports,
Flying
Fields,
Airport
Terminal
Services
Bus
And
Truck
33621120
3713
Truck
and
Bus
Bodies
33621200
3715
Truck
Trailers
48511100
48511200
48511300
48511900
4111
Local
and
Suburban
Transit
48532000
48541020
48599100
48599920
62191090
4119
Local
Passenger
Transit,
N.
E.
C.

48521000
4131
Intercity
and
Rural
Bus
Transportation
48551010
4141
Local
Bus
Charter
Service
48551020
4142
Bus
Charter
Service,
Except
Local
48849010
4173
Bus
Terminal
and
Service
Facilities
48411010
48411020
4212
Local
Trucking
without
Storage
48412100
48412200
48421020
4213
Trucking,
Except
Local
48411030
48411040
4214
Local
Trucking
with
Storage
A­
2
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Bus
and
Truck
(
Continued)

49211010
49221000
4215
Courier
Services,
Except
by
Air
48849020
4231
Trucking
Terminal
Facilities
Electronic
Equipment
33421000
3661
Telephone
and
Telegraph
Apparatus
33422010
3663
Radio
and
Television
Broadcast
and
Communications
Equipment
33429000
3669
Communications
Equipment,
N.
E.
C.

33441100
3671
Electron
Tubes
33441400
3675
Electronic
Capacitors
33441610
33441620
3677
Electronic
Coils
and
Transformers
33441700
3678
Connectors
for
Electronic
Applications
33422020
33441820
33441900
33632210
3679
Electronic
Components,
N.
E.
C.

33451010
33451110
33451610
33451910
33512920
33599920
33911410
3699
Electrical
Machinery,
Equipment,
and
Supplies,
N.
E.
C.

Hardware
32312220
2796
Platemaking
and
Related
Services
33281100
3398
Metal
Heat
Treating
33243910
3412
Metal
Shipping
Barrels,
Drums,
Kegs,
Pails
33221110
3421
Cutlery
33221210
33221240
3423
Hand
and
Edge
Tools,
Except
Machine
Tools
and
Handsaws
33221300
3425
Hand
Saws
and
Saw
Blades
33243920
3429
Hardware,
N.
E.
C.

A­
3
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Hardware
(
Continued)

33341410
3433
Heating
Equipment,
Except
Electric
and
Warm
Air
Furnace
33231210
3441
Fabricated
Structural
Metal
33231300
3443
Fabricated
Plate
Work
(
Boiler
Shops)

33243930
3444
Sheet
Metal
Work
33232310
3446
Architectural
and
Ornamental
Metal
Work
33231100
3448
Prefabricated
Metal
Buildings
and
Components
33231220
3449
Miscellaneous
Metal
Work
33272100
3451
Screw
Machine
Products
33272200
3452
Bolts,
Nuts,
Screws,
Rivets,
and
Washers
33211100
3462
Iron
and
Steel
Forgings
33211500
3466
Crowns
and
Closures
33221400
3469
Metal
Stamping,
N.
E.
C.

33291210
3492
Fluid
Power
Valves
and
Hose
Fittings
33261100
3493
Steel
Springs
33291920
3494
Valves
and
Pipe
Fittings,
Except
Brass
33451810
3495
Wire
Springs
33261830
3496
Miscellaneous
Fabricated
Wire
Products
33299620
3498
Fabricated
Pipe
and
Fabricated
Pipe
Fitting
33243940
33251020
33211700
33721540
33991420
3499
Fabricated
Metal
Products,
N.
E.
C.

33351210
3541
Machine
Tools,
Metal
Cutting
Types
33351300
3542
Machine
Tools,
Metal
Forming
Types
33351400
3544
Special
Dies
and
Tools,
Die
Sets,
Jigs
and
Fixtures,
and
Industrial
Molds
33351500
3545
Machine
Tool
Access
and
Measuring
Devices
33399100
3546
Power
Driven
Hand
Tools
33999320
3965
Fasteners,
Buttons,
Needles,
Pins
A­
4
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Household
Equipment
33712400
2514
Metal
Household
Furniture
33721400
2522
Office
Furniture,
Except
Wood
33712710
2531
Public
Building
and
Related
Furniture
33721530
2542
Partitions
and
Fixtures,
Except
Wood
33792000
2591
Drapery
Hardware
and
Window
Blinds/
shades
33712720
33911310
2599
Furniture
and
Fixtures,
N.
E.
C.

33299800
3431
Metal
Sanitary
Ware
33291300
3432
Plumbing
Fittings
and
Brass
Goods
33232120
3442
Metal
Doors,
Sash,
and
Trim
33522100
3631
Household
Cooking
Equipment
33522200
3632
Household
Refrigerators
and
Home
and
Farm
and
Freezers
33522400
3633
Household
Laundry
Equipment
33521100
33341420
3634
Electric
Housewares
and
Fans
33521210
3635
Household
Vacuum
Cleaners
33521220
33522800
3639
Household
Appliances,
N.
E.
C.

33511000
3641
Electric
Lamps
33593100
3643
Current­
Carrying
Wiring
Devices
33593200
3644
Noncurrent­
Carrying
Wiring
Devices
33512120
3645
Residential
Electrical
Lighting
Fixtures
33512200
3646
Commercial,
Industrial,
and
Institutional
33512910
3648
Lighting
Equipment,
NEC
33431000
3651
Radio/
Television
Sets
Except
Communication
Types
81131030
81141220
7623
Refrigeration
and
Air­
conditioning
Service
and
Repair
Shops
A­
5
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Instruments
33451120
3812
Search,
Detection,
Navigation,
Guidance,
Aeronautical,
Nautical
Systems
and
Instruments
33911100
3821
Laboratory
Apparatus
and
Furniture
33451200
3822
Automatic
Environmental
Controls
33451300
3823
Process
Control
Instruments
33451400
3824
Fluid
Meters
and
Counting
Devices
33451500
3825
Instruments
to
Measure
Electricity
33451620
3826
Laboratory
Analytical
Instruments
33331420
3827
Optical
Instruments
and
Lenses
33451920
3829
Measuring
and
Controlling
Devices,
N.
E.
C.

33911210
33911220
3841
Surgical
and
Medical
Instruments
and
Apparatus
32229120
33451020
33911320
3842
Orthopedic,
Prosthetic
and
Surgical
Supplies
33911420
3843
Dental
Equipment
and
Supplies
33451700
3844
X­
ray
Apparatus
and
Tubes
33451030
3845
Electromedical
Equipment
33911500
3851
Ophthalmic
Goods
81121210
81121310
81121910
81141120
81141210
7629
Electric
Repair
Shop
Job
Shopsa
33281300
3471
Plating
and
Polishing
33281200
33991210
33991410
3479
Metal
Coating
and
Allied
Services
A­
6
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Mobile
Industrial
Equipment
33221220
33311100
33392210
3523
Farm
Machinery
and
Equipment
33221230
33311200
3524
Garden
Tractors
and
Lawn
and
Garden
Equipment
33312000
33392310
33651010
3531
Construction
Machinery
and
Equipment
33313100
3532
Mining
Machinery
and
Equipment,
Except
Oil
Field
33392320
3536
Hoists,
Industrial
Cranes
and
Monorails
33243950
33299960
33392400
3537
Industrial
Trucks,
Tractors,
Trailers
33699220
3795
Tanks
and
Tank
Components
Motor
Vehicle
33637000
3465
Automotive
Stampings
33631100
3592
Carburetors,
Piston
Rings,
Valves
33632100
3647
Vehicular
Lighting
Equipment
33632220
3694
Electrical
Equipment
for
Motor
Vehicles
33611100
33611200
33612000
33621110
33621130
33699210
3711
Motor
Vehicle
and
Automobile
Bodies
33621130
3714
Motor
Vehicle
Parts
and
Accessories
33621300
3716
Mobile
Homes
33699110
3751
Motorcycles
33621410
3792
Travel
Trailers
and
Campers
33699900
3799
Miscellaneous
Transportation
Equipment
48531000
4121
Taxicabs
44131030
5013
Motor
Vehicle
Supplies
and
New
Parts
A­
7
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Motor
Vehicle
(
Continued)

44111000
5511
Motor
Vehicle
Dealers
(
New
and
Used)

44112000
5521
Motor
Vehicle
Dealers
(
Used
Only)

44121000
5561
Recreational
Vehicle
Dealers
44122100
5571
Motorcycle
Dealers
44122900
5599
Automotive
Dealers,
N.
E.
C.

53211200
7515
Passenger
Car
Lease
81112110
81112120
81112130
7532
Top,
Body,
and
Upholstery
Repair
and
Paint
Shops
81111200
7533
Auto
Exhaust
Systems
81111300
7537
Auto
Transmission
Repair
81111100
7538
General
Automotive
Repair
81111810
81111820
81111830
81111840
81111890
7539
Auto
Repair
Shop,
N.
E.
C.

81119100
81119820
7549
Auto
Services,
Except
Repair
and
Carwashes
Office
Machines
33411100
3571
Electronic
Computers
33411200
3572
Typewriters
33411300
3575
Computer
Terminals
33411910
3577
Computer
Peripheral
Equipment,
N.
E.
C.

33411920
3578
Calculating,
Accounting
Machines
Except
Computers
33451820
3579
Office
Machines,
N.
E.
C.

81121230
7378
Computer
Maintenance
and
Repairs
54151220
54151910
33451820
7379
Computer
Related
Services,
N.
E.
C.

A­
8
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Ordnance
33299200
3482
Small
Arms
Ammunition
33299300
3483
Ammunition,
Except
for
Small
Arms
33299400
3484
Small
Arms
33299500
3489
Ordnance
and
Accessories,
N.
E.
C.

Precious
Metals
and
Jewelry
33451830
3873
Watches,
Clocks,
and
Watchcases
33991120
3911
Jewelry,
Precious
Metal
33991220
3914
Silverware,
Plated
Ware
and
Stainless
33991300
3915
Jewelers'
Materials
and
Lapidary
Work
33991430
3961
Costume
Jewelry
81149010
7631
Watch,
Clock,
Jewelry
Repair
Printed
Circuit
Boardsa
33441200
3672
Printed
Circuit
Boards
Railroad
33391120
33651020
3743
Railcars,
Railway
Systems
48211100
4011
Railroad
Transportation
48211200
4013
Railroad
Transportation
Ships
and
Boats
33661100
3731
Ship
Building
and
Repairing
33661200
81149020
3732
Boat
Building
and
Repairing
48311100
4412
Deep
Sea
Foreign
Transportation
48311310
4424
Deep
Sea
Domestic
Transportation
48311320
4432
Freight
Transportation
Great
Lakes
48321110
4449
Water
Transportation
of
Freight,
N.
E.
C.

48311410
4481
Deep
Sea
Passenger
Transportation
48311420
4482
Ferries
A­
9
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Ships
and
Boats
(
Continued)

48321220
48721010
4489
Water
Passenger
Transportation,
N.
E.
C.

48831010
4491
Marine
Cargo
Handling
48321120
4492
Towing
and
Tugboat
Service
71393000
4493
Marinas
48831020
48833020
48833030
48839010
53241110
4499
Water
Transportation
Services,
N.
E.
C.

Stationary
Industrial
Equipment
33361100
3511
Steam,
Gas,
Hydraulic
Turbines,
Generating
Units
33639910
3519
Internal
Combustion
Engines,
N.
E.
C.

33313200
3533
Oil
Field
Machinery
and
Equipment
33392100
3534
Elevators
and
Moving
Stairways
33392220
3535
Conveyors
and
Conveying
Equipment
33299700
3543
Industrial
Patterns
33351600
3547
Rolling
Mill
Machinery
and
Equipment
33399210
3548
Electric
and
Gas
Welding
and
Soldering
33351800
3549
Metal
Working
Machinery,
N.
E.
C.

33329210
3552
Textile
Machinery
33321000
3553
Woodworking
Machinery
33329100
3554
Paper
Industries
Machinery
33329310
3555
Printing
Trades
Machinery
and
Equipment
33329400
3556
Food
Products
Machinery
33329810
3559
Special
Industry
Machinery,
N.
E.
C.

33391110
3561
Pumps
and
Pumping
Equipment
33299100
3562
Ball
and
Roller
Bearings
33391200
3563
Air
and
Gas
Compressors
A­
10
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Stationary
Industrial
Equipment
(
Continued)

33341200
33341100
3564
Blowers
and
Exhaust
and
Ventilation
Fans
33399300
3565
Industrial
Patterns
33361200
3566
Speed
Changers,
High
Speed
Drivers
and
Gears
33399400
3567
Industrial
Process
Furnaces
and
Ovens
33361300
3568
Mechanical
Power
Transmission
Equipment,
N.
E.
C.

33399910
3569
General
Industrial
Machinery,
N.
E.
C.

33331100
3581
Automatic
Merchandising
Machines
33331200
3582
Commercial
Laundry
Equipment
33639100
3585
Refrigeration
and
Air
and
Heating
Equipment
33391300
3586
Measuring
and
Dispensing
Pumps
33331920
3589
Service
Industry
Machines,
N.
E.
C.

33399510
3593
Fluid
Power
Cylinders
and
Actuators
33399610
3594
Fluid
Power
Pumps
and
Motors
33399700
3596
Scales
and
Balances,
Except
Laboratory
33399920
3599
Machinery,
Except
Electrical,
N.
E.
C.

33531120
3612
Transformers
33531300
3613
Switchgear
and
Switchboard
Apparatus
33531210
3621
Motors
and
Generators
33599910
3629
Electric
Industrial
Apparatus,
N.
E.
C.

53241210
7353
Heavy
Construction
Equipment
Rental,
Leasing
53221000
53229990
53231000
53241190
53241290
53242010
53249020
56299120
7359
Equipment
Rental,
Leasing,
N.
E.
C.

A­
11
Appendix
A
­
Example
NAICS
&
SIC
codes
for
MP&
M
Sectors
Table
A­
1
(
Continued)

Example
NAICS
and
SIC
Codes
for
the
MP&
M
Industrial
Sectors
NAICS
Code
SIC
Code
Standard
Industrial
Classification
Groups
Miscellaneous
Metal
Products
33299940
3497
Metal
Foil
and
Leaf
33331520
3861
Photographic
Equipment
and
Supplies
33999200
3931
Musical
Instruments
33699120
3944
Games,
Toys,
Children's
Vehicles
33992000
3949
Sporting
and
Athletic
Goods,
N.
E.
C.

33994100
3951
Pens
and
Mechanical
Pencils
33994300
3953
Marking
Devices
33995000
3993
Signs
and
Advertising
Displays
33999500
3995
Burial
Caskets
33221270
33299980
33512130
3999
Manufacturing
Industries,
N.
E.
C.

81149030
7692
Welding
Repair
48839030
81149090
56162200
56179010
81121220
81121990
81131010
81141110
81141290
7699
Repair
Shop,
Related
Service
Continuous
Electroplaters
33281300
3399
Electroplating,
Plating,
Polishing,
Anodizing,
and
Coloring
Source:
U.
S.
Census
Bureau,
North
American
Industrial
Classification
System,
http://
www.
census.
gov/
epcd/
www/
naics.
html.
N.
E.
C.
­
Not
elsewhere
classified.
a
Industrial
sector
considered,
but
not
included,
in
Part
438.

A­
12
Appendix
B
­
Analytical
Methods
and
Baseline
Values
Appendix
B
ANALYTICAL
METHODS
AND
BASELINE
VALUES
FOR
THE
METAL
PRODUCTS
AND
MACHINERY
INDUSTRY
Appendix
B
­
Analytical
Methods
and
Baseline
Values
APPENDIX
B
ANALYTICAL
METHODS
AND
BASELINE
VALUES
B.
1
Nominal
Quantitation
Limits
B.
2
Baseline
Values
B.
3
Analytical
Results
Reporting
Conventions
B.
4
Analytical
Methods
B.
4.1
EPA
Methods
1624,
1625,
1664,
and
OIA­
1677
(
Volatile
Organics,
Semivolatile
Organics,
SGT­
HEM,
HEM,
and
Available
Cyanide)
B.
4.2
EPA
Methods
1620
and
200.7
(
Metals)
B.
4.3
EPA
Method
335.1
(
Amenable
Cyanide)
B.
4.4
EPA
Methods
350.2
and
350.3
(
Ammonia
as
Nitrogen)
B.
4.5
EPA
Method
405.1
and
SM
5210B
(
BOD5
and
Carbonaceous
BOD)
B.
4.6
EPA
Methods
410.1,
410.2,
and
410.4
(
Chemical
Oxygen
Demand)
B.
4.7
EPA
Method
325.3
(
Chloride)
B.
4.8
EPA
Method
340.2
(
Fluoride)
B.
4.9
EPA
Method
218.4,
SM
3111A,
and
SM
3500D
(
Hexavalent
Chromium)
B.
4.10
EPA
Method
150.1
and
SM
4500H
(
pH)
B.
4.11
EPA
Methods
375.2
and
375.4
(
Sulfate)
B.
4.12
EPA
Methods
335.2
and
335.3
(
Total
Cyanide)
B.
4.13
EPA
Method
160.1
and
SM
2540C
(
Total
Dissolved
Solids)
B.
4.14
EPA
Method
351.3
(
Total
Kjeldahl
Nitrogen)
B.
4.15
EPA
Method
415.1
(
Total
Organic
Carbon)
B.
4.16
EPA
Methods
420.1
and
420.2
(
Total
Phenols)
B.
4.17
EPA
Methods
365.2
and
365.3
(
Total
Phosphorus)
B.
4.18
EPA
Methods
376.1
and
376.2,
SM
4500D
and
SM
4500E,
and
D4658
(
Total
Sulfide)
B.
4.19
EPA
Method
160.2
and
SM
2540D
(
Total
Suspended
Solids)
B.
4.20
EPA
Methods
204.1
and
7041
(
Antimony)
B.
4.21
EPA
Methods
206.2
and
7060A
(
Arsenic)
B.
4.22
EPA
Method
231.2
(
Gold)
B.
4.23
EPA
Method
239.1
(
Lead)
B.
4.24
EPA
Methods
245.1
and
245.2
(
Mercury)
B.
4.25
EPA
Method
265.2
(
Rhodium)
B.
4.26
EPA
Methods
270.2
and
7740
(
Selenium)
B.
4.27
EPA
Method
272.1
(
Silver)
B.
4.28
EPA
Methods
279.1
and
7841
(
Thallium)
B.
4.29
EPA
Methods
624
and
625
(
Volatile
Organics
and
Semivolatile
Organics)
B.
4.30
EPA
Method
630.1
(
Ziram)
B.
5
Analytical
Method
Development
Efforts
i
Appendix
B
­
Analytical
Methods
and
Baseline
Values
The
analytical
methods
described
in
this
appendix
were
used
to
determine
pollutant
levels
in
wastewater
samples
collected
by
EPA
and
industry
at
a
number
of
metal
products
and
machinery
facilities.
(
Sampling
efforts
are
described
in
Section
3.0)
In
developing
the
rule,
EPA
used
data
from
samples
collected
by
EPA
and
industry
to
determine
the
levels
of
amenable
cyanide,
ammonia
as
nitrogen,
available
cyanide,
biochemical
oxygen
demand
(
BOD),
carbonaceous
biochemical
oxygen
demand,
chemical
oxygen
demand
(
COD),
chloride,
fluoride,
hexavalent
chromium,
metals,
oil
and
grease
(
measured
as
hexane
extractable
material
(
HEM)),
pH,
semivolatile
organics,
silica
gel­
treated
hexane
extractable
material
(
SGT­
HEM),
sulfate,
total
cyanide,
total
dissolved
solids
(
TDS),
total
Kjeldahl
nitrogen
(
TKN),
total
organic
carbon
(
TOC),
total
phenols,
total
phosphorus,
total
sulfide,
total
suspended
solids
(
TSS),
volatile
organics,
and
ziram.
As
explained
in
Section
7.0,
EPA
is
regulating
a
subset
of
these
pollutants.

Sections
B.
1
and
B.
2
of
this
appendix
provide
explanations
of
nominal
quantitation
limits
and
baseline
values.
Section
B.
3
describes
the
reporting
conventions
used
by
laboratories
in
expressing
the
results
of
the
analyses.
Section
B.
4
describes
each
analytical
method
and
the
corresponding
baseline
values
that
EPA
used
in
determining
the
pollutants
of
concern.
Section
B.
5
discusses
analytical
method
development
efforts.
Table
B­
1
identifies
the
analytical
methods
and
baseline
values
for
each
pollutant,
identifies
each
pollutant
by
Chemical
Abstract
Service
Registry
Number,
indicates
whether
the
samples
were
collected
by
EPA
and/
or
by
industry,
and
lists
the
nominal
quantitation
value
for
the
method
used.

Nominal
Quantitation
Limits
The
nominal
quantitation
limit
is
the
smallest
quantity
of
an
analyte
that
can
be
reliably
measured
with
a
particular
method,
using
the
typical
(
nominal)
sample
size.
The
protocols
used
for
determination
of
nominal
quantitation
limits
in
a
particular
method
depend
on
the
definitions
and
conventions
that
EPA
used
at
the
time
the
method
was
developed.
The
nominal
quantitation
limits
associated
with
the
methods
addressed
in
this
section
fall
into
three
categories.

1)
The
first
category
pertains
to
EPA
Methods
1624,
1625,
1664,
and
OIA­
1677,
which
define
the
minimum
level
(
ML)
as
the
lowest
level
at
which
the
entire
analytical
system
must
give
a
recognizable
signal
and
an
acceptable
calibration
point
for
the
analyte.
These
methods
are
described
in
Section
B.
4.1.

2)
The
second
category
pertains
specifically
to
EPA
Method
1620,
and
is
explained
in
detail
in
Section
B.
4.2.

3)
The
third
category
pertains
to
the
remainder
of
the
chemical
methods
in
which
a
variety
of
terms
are
used
to
describe
the
lowest
level
at
which
measurement
results
are
quantitated.
In
some
cases
(
especially
with
the
classical
wet
chemistry
analytes)
the
methods
date
to
the
1970s
and
1980s
when
different
concepts
of
quantitation
were
employed
by
EPA.
These
methods
typically
list
a
measurement
range
or
lower
limit
of
B­
1
B.
1
Appendix
B
­
Analytical
Methods
and
Baseline
Values
measurement.
The
terms
differ
by
method
and,
as
discussed
in
subsequent
sections,
the
levels
presented
are
not
always
representative
of
the
lowest
levels
laboratories
currently
can
achieve.

For
those
methods
associated
with
a
calibration
procedure,
the
laboratories
demonstrated
through
a
low­
point
calibration
standard
that
they
were
capable
of
reliable
quantitation
at
method­
specified
(
or
lower)
levels.
In
such
cases
these
nominal
quantitation
limits
are
operationally
equivalent
to
the
ML
(
though
not
specifically
identified
as
such
in
the
methods).

In
the
case
of
titrimetric
or
gravimetric
methods,
the
laboratory
adhered
to
the
established
lower
limit
of
the
measurement
range
published
in
the
methods.
Details
of
the
specific
methods
are
presented
in
Sections
B.
4.3
through
B.
4.30.

Baseline
Values
As
described
further
in
Section
7.0,
in
determining
the
pollutants
of
concern,
EPA
compared
the
reported
concentrations
for
each
pollutant
to
a
multiple
of
the
baseline
value.
As
described
in
Section
B.
3
and
shown
in
Table
B­
1,
for
most
pollutants,
the
baseline
value
was
set
equal
to
the
nominal
quantitation
limit
for
the
analytical
method.
EPA
made
two
general
types
of
exceptions
which
are
briefly
described
below.
Section
B.
4
provides
additional
details
about
these
exceptions
in
the
context
of
the
analytical
methods.

The
first
type
of
exception
was
for
baseline
values
that
were
different
than
the
nominal
quantitation
limits
in
the
analytical
methods.
When
the
baseline
values
were
lower,
EPA
made
these
exceptions
because
the
laboratory
submitted
data
that
demonstrated
that
reliable
measurements
could
be
obtained
at
lower
levels
for
those
pollutants.
When
the
baseline
values
were
higher,
EPA
concluded
that
the
nominal
quantitation
limit
for
a
specified
method
was
less
than
the
level
that
laboratories
could
reliably
achieve
and
adjusted
the
baseline
value
upward.

The
second
type
of
exception
was
for
baseline
values
set
at
a
common
value
for
multiple
analytical
methods
for
the
same
pollutant.
For
some
analytes,
EPA
permitted
the
laboratories
to
choose
between
methods
to
accommodate
sample
characteristics
and/
or
industry
used
a
different
analytical
method
than
EPA.
When
these
methods
had
different
nominal
quantitation
limits,
EPA
generally
used
the
one
with
the
lowest
value
or
the
one
associated
with
the
method
used
for
most
samples.

B­
2
B.
2
Appendix
B
­
Analytical
Methods
and
Baseline
Values
B.
3
Analytical
Results
Reporting
Conventions
The
laboratories
reported
each
analytical
result
either
as
a
numeric
value
or
as
not
quantitated1
.
A
numeric
result
indicates
that
the
pollutant
was
quantitated2
in
the
sample.
Most
analytical
results
were
reported
as
liquid
concentrations
in
weight/
volume
units
(
e.
g.,
micrograms
per
liter
(
µ
g/
L)),
except
for
the
pH
data,
which
were
reported
in
"
standard
units"
(
SU).
For
solid
samples,
the
results
were
provided
in
weight/
weight
units
(
e.
g.,
milligrams
per
kilogram
(
mg/
kg)).
In
those
instances,
EPA
converted
the
solids
results
into
weight/
volume
units
by
using
a
conversion
factor
based
on
the
percentage
of
solids
in
the
samples.

For
example,
the
result
for
a
hypothetical
pollutant
X
would
be
reported
as
"
15
g/
L"
when
the
laboratory
cannot
quantitated
the
amount
of
pollutant
X
in
the
sample
as
being
15
g/
L.
When
the
laboratory
cannot
quantitate
the
amount
of
pollutant
X
in
the
sample,
the
laboratory
would
report
that
the
analytical
result
indicated
a
value
less
than
the
sample­
specific
quantitation
limit
of
10
g/
L
(
i.
e.,
"<
10
g/
L").
The
actual
amount
of
pollutant
X
in
that
sample
is
between
zero
(
i.
e.,
the
pollutant
is
not
present)
and
10
g/
L.
The
sample­
specific
quantitation
limit
for
a
particular
pollutant
is
generally
the
smallest
quantity
in
the
calibration
range
that
can
be
measured
reliably
in
any
given
sample.
Reporting
a
pollutant
as
nonquantitated
does
not
mean
that
the
pollutant
is
not
present
in
the
wastewater;
it
merely
indicates
that
analytical
techniques
(
whether
because
of
instrument
limitations,
pollutant
interactions,
or
other
reasons)
do
not
permit
its
measurement
at
levels
below
the
sample­
specific
quantitation
limit.

In
its
calculations,
EPA
generally
substituted
the
reported
sample­
specific
quantitation
limit
for
each
nonquantitated
result.
As
described
in
Section
B.
4.1,
EPA
substituted
the
baseline
value
for
the
nonquantitated
result
when
the
sample­
specific
quantitation
limit
was
less
than
the
baseline
value.
In
addition,
when
the
detected
quantitated
value
was
below
the
baseline
value,
EPA
substituted
the
baseline
value
for
the
measured
value
and
considered
these
values
to
be
nonquantitated
in
the
statistical
analyses.

B.
4
Analytical
Methods
EPA
and
industry
analyzed
all
metal
products
and
machinery
facility
wastewater
samples
using
methods
identified
in
Table
B­
1.
(
As
explained
in
Section
7.0,
EPA
is
regulating
only
a
subset
of
these
analytes.)
In
analyzing
samples,
EPA
generally
used
analytical
methods
approved
at
40
CFR
136
or
methods
that
EPA
has
used
for
decades
in
support
of
effluent
guidelines
development.
Exceptions
for
use
of
nonapproved
methods
are
explained
in
the
method­
specific
subsections
that
1Elsewhere
in
this
document
and
in
the
preamble
to
the
rule,
EPA
may
refer
to
pollutants
as
 
not
detected 
or
 
nondetected. 
This
appendix
uses
the
terms
 
not
quantitated 
or
 
nonquantitated 
rather
than
not
detected
or
nondetected.

2Elsewhere
in
this
document
and
in
the
preamble
to
the
rule,
EPA
may
refer
to
pollutants
as
 
detected. 
This
appendix
uses
the
term
 
quantitated 
rather
than
detected.

B­
3
Appendix
B
­
Analytical
Methods
and
Baseline
Values
follow.
EPA
proposed
limitations
or
standards
based
only
upon
data
generated
by
methods
approved
in
40
CFR
136.
Table
B­
1
provides
a
summary
of
the
analytical
methods,
the
associated
pollutants
measured
by
the
method,
the
nominal
quantitation
levels,
and
the
baseline
levels.
The
following
sections
provide
additional
information
supporting
the
summary
in
Table
B­
1.

The
following
sections
describe
the
methods
used
to
determine
pollutant
levels
in
wastewater
samples
collected
at
metal
products
and
machinery
facilities.
Each
section
states
whether
the
method
is
approved
at
40
CFR
136
(
even
if
the
pollutant
was
not
proposed
to
be
regulated),
provides
a
short
description
of
the
method,
identifies
the
nominal
quantitation
limit,
and
explains
EPA's
choice
for
the
baseline
value.

B.
4.1
EPA
Methods
1624,
1625,
1664,
and
OIA­
1677
(
Volatile
Organics,
Semivolatile
Organics,
HEM,
SGT­
HEM,
and
Available
Cyanide)

EPA
used
Methods
1624,
1625,
1664,
and
OIA­
1677
to
measure
volatile
organics,
semivolatile
organics,
n­
hexane
extractable
material
(
HEM)/
silica
gel
treated
n­
hexane
extractable
material
(
SGT­
HEM)
and
available
cyanide,
respectively.
Industry
used
Method
1664
to
measure
HEM
and
SGT­
HEM.
Methods
1624,
1625,
1664,
and
OIA­
1677
are
approved
at
40
CFR
136.

These
methods
use
the
minimum
level
(
ML)
of
quantitation.
The
ML
is
defined
as
the
lowest
level
at
which
the
entire
analytical
system
must
give
a
recognizable
signal
and
an
acceptable
calibration
point
for
the
analyte.
When
an
ML
is
published
in
a
method,
the
Agency
has
demonstrated
that
the
ML
can
be
achieved
in
at
least
one
well­
operated
laboratory.
When
that
laboratory
or
another
laboratory
uses
that
method,
the
laboratory
is
required
to
demonstrate,
through
calibration
of
the
instrument
or
analytical
system,
that
it
can
achieve
pollutant
measurements
at
the
ML.

For
volatile
organics,
semivolatile
organics,
HEM/
SGT­
HEM,
and
available
cyanide,
EPA
used
the
method­
specified
MLs
as
the
baseline
values.
In
determining
the
pollutants
of
concern
and
in
calculating
the
HEM/
SGT­
HEM
standards,
EPA
substituted
the
value
of
the
ML
and
assumed
that
the
measurement
was
not
quantitated
when
a
quantitated
value
or
sample­
specific
quantitation
limit
was
reported
with
a
value
less
than
the
ML
specified
in
the
method.
For
example,
if
the
ML
was
10
g/
L
and
the
laboratory
reported
a
quantitated
value
of
5
g/
L,
EPA
assumed
that
the
concentration
was
nonquantitated
with
a
sample­
specific
quantitation
limit
of
10
g/
L.
The
objective
of
this
comparison
was
to
identify
any
results
for
the
pollutants
reported
below
the
method­
defined
ML.
Results
reported
below
the
ML
were
changed
to
the
ML
to
ensure
that
all
results
used
by
EPA
were
reliable.
In
most
cases,
the
quantitated
values
and
sample­
specific
quantitation
limits
were
equal
to
or
greater
than
the
baseline
values.

B.
4.2
EPA
Methods
1620
and
200.7
(
Metals)

EPA
used
Method
1620
to
measure
the
concentrations
of
metals.
While
Method
1620
is
not
listed
at
40
CFR
136
as
an
approved
method,
it
represents
a
consolidation
of
the
analytical
B­
4
Appendix
B
­
Analytical
Methods
and
Baseline
Values
techniques
in
several
40
CFR
136­
approved
methods,
such
as
Method
200.7
(
inductively
coupled
plasma
atomic
emission
(
ICP)
spectroscopy
of
trace
elements)
and
Method
245.1
(
mercury
cold
vapor
atomic
absorption
(
CVAA)
spectroscopy).
This
method
was
developed
specifically
for
the
effluent
guidelines
program.
Method
1620
includes
more
metal
analytes
than
are
listed
in
the
approved
methods
and
contains
quality
control
requirements
at
least
as
stringent
as
the
40
CFR
136­
approved
methods.
Some
industry­
supplied
results
for
aluminum,
barium,
beryllium,
cadmium,
calcium,
chromium,
cobalt,
copper,
iron,
magnesium,
manganese,
molybdenum,
nickel,
sodium,
vanadium,
and
zinc
were
determined
by
Method
200.7.
Other
industry­
supplied
results
for
metals
were
determined
by
EPA
Methods
204.1,
206.2,
231.2,
239.1,
245.1,
245.2,
265.2,
270.2,
272.1,
279.1,
7041,
7060A,
7740,
and
7841.

Method
1620
employs
the
concept
of
an
instrument
detection
limit
(
IDL).
The
IDL
is
defined
as
"
the
smallest
signal
above
background
noise
that
an
instrument
can
detect
reliably."
3
Data
reporting
practices
for
Method
1620
analyses
follow
conventional
metals
reporting
practices
used
in
other
EPA
programs,
in
which
values
are
required
to
be
reported
at
or
above
the
IDL.
In
applying
Method
1620,
IDLs
are
determined
on
a
quarterly
basis
by
each
analytical
laboratory
and
are,
therefore,
laboratory­
specific
and
time­
specific.
Although
Method
1620
contains
MLs,
these
MLs
pre­
date
EPA's
recent
refinements
of
the
ML
concept
described
earlier.
The
MLs
associated
with
Method
1620
are
based
on
a
consensus
opinion
reached
between
EPA
and
laboratories
during
the
1980s
regarding
levels
that
could
be
considered
reliable
quantitation
limits
when
using
Method
1620.
These
limits
do
not
reflect
advances
in
technology
and
instrumentation
since
the
1980s.
Consequently,
the
IDLs,
which
are
more
reflective
of
current
analytical
capabilities,
were
used
as
the
lowest
values
for
reporting
purposes,
with
the
general
understanding
that
reliable
results
can
be
produced
at
or
above
the
IDL.
Although
the
baseline
values
were
derived
from
the
MLs
(
or
adjusted
MLs)
in
Method
1620,
EPA
used
the
laboratory­
reported
quantitated
values
and
sample­
specific
quantitation
limits,
which
captured
concentrations
down
to
the
IDLs,
in
its
data
analyses.

In
general,
EPA
used
the
MLs
specified
in
Method
1620
as
the
baseline
values.
However,
EPA
adjusted
the
baseline
value
for
lead
to
50
:
g/
L
and
boron
to
100
:
g/
L.
In
Method
1620,
lead
has
an
ML
of
5
:
g/
L
for
graphite
furnace
atomic
absorption
(
GFAA)
spectroscopy
analysis;
EPA
determined,
however,
that
it
was
not
necessary
for
the
laboratories
to
measure
down
to
such
low
levels,
and
that
lead
could
be
analyzed
by
inductively
coupled
plasma
atomic
emission
(
ICP)
spectroscopy.
Consequently,
the
ML
requirement
was
adjusted
to
50
:
g/
L,
the
ML
for
the
ICP
method.
In
Method
1620,
boron
has
an
ML
of
10
:
g/
L,
but
laboratory
feedback
years
ago
indicated
that
laboratories
could
not
reliably
achieve
this
low
level.
As
a
result,
EPA
only
required
laboratories
to
measure
values
at
100
:
g/
L
and
above.
Thus,
EPA
adjusted
the
baseline
value
to
100
:
g/
L.

3Keith,
L.
H.,
W.
Crummett,
J.
Deegan,
R.
A.
Libby,
J.
K.
Taylor,
G.
Wentler
(
1983).
 
Principles
of
Environmental
Analysis, 
Analytical
Chemistry,
Volume
55,
Page
2217.

B­
5
Appendix
B
­
Analytical
Methods
and
Baseline
Values
B.
4.3
EPA
Method
335.1
(
Amenable
Cyanide)

Amenable
cyanide
was
measured
using
Method
335.1,
which
is
approved
at
40
CFR
136.
Industry
also
supplied
data
determined
by
Method
335.1.
Method
335.1
utilizes
either
a
titrimetric
or
colorimetric
procedure
to
measure
amenable
cyanide.

Method
335.1
has
a
lower
measurement
range
limit
of
0.02
milligrams
per
liter
(
mg/
L)
for
the
colorimetric
procedure
and
a
lower
measurement
range
limit
of
1
mg/
L
for
the
titrimetric
procedure.
The
nominal
quantitation
limit
of
0.02
mg/
L
was
used
as
the
baseline
for
all
amenable
cyanide
results,
since
it
is
the
lower
value
of
the
two.

B.
4.4
EPA
Methods
350.2
and
350.3
(
Ammonia
as
Nitrogen)

Ammonia,
as
nitrogen,
was
measured
using
Methods
350.2
and
350.3,
both
of
which
are
approved
at
40
CFR
136.
Method
350.2
utilizes
colorimetric,
titrimetric,
or
electrode
procedures
to
measure
ammonia.
Method
350.3
uses
a
potentiometric
procedure
to
measure
ammonia.

Method
350.2
has
a
lower
measurement
range
limit
of
0.20
mg/
L
for
the
colorimetric
and
electrode
procedures,
and
a
lower
measurement
range
limit
of
1.0
mg/
L
for
the
titrimetric
procedure.
Method
350.3
has
a
lower
measurement
range
limit
of
0.03
mg/
L
for
the
potentiometric
procedure.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
0.03
mg/
L
as
the
baseline
value
from
Method
350.3
because
it
represents
the
lowest
value
at
which
ammonia
as
nitrogen
can
be
measured
reliably.

B.
4.5
EPA
Method
405.1
and
SM
5210B
(
BOD5
and
Carbonaceous
BOD5
)

Biochemical
oxygen
demand
(
BOD5
)
and
carbonaceous
BOD5
(
cBOD5
)
were
measured
using
Method
405.1
and
Standard
Method
(
SM)
5210B,
both
of
which
are
approved
at
40
CFR
136.
BOD5
and
cBOD5
are
determined
by
the
same
method,
except
that
an
organic
compound
is
added
to
the
cBOD5
test
to
inhibit
nitrogenous
oxygen
demand.
If
the
sample
does
not
include
any
nitrogenous
demand
to
inhibit,
the
results
should
be
comparable
for
BOD5
and
cBOD5
.

Method
405.1
and
SM
5210B
are
identical
and
the
nominal
quantitation
limit,
which
is
expressed
in
the
methods
as
the
lower
limit
of
the
measurement
range
at
2
mg/
L,
is
the
same
for
both
forms
of
BOD5
.
EPA
used
this
nominal
quantitation
limit
of
2
mg/
L
as
the
baseline
value
in
determining
the
pollutants
of
concern.

B.
4.6
EPA
Methods
410.1,
410.2,
and
410.4
(
Chemical
Oxygen
Demand)

Chemical
Oxygen
Demand
(
COD)
was
measured
using
Methods
410.1,
410.2,
and
410.4,
all
of
which
are
approved
at
40
CFR
136.
Method
410.4
is
a
colorimetric
procedure.
Methods
410.1
and
410.2
are
titrimetric
procedures
that
follow
identical
analytical
protocols;
they
B­
6
Appendix
B
­
Analytical
Methods
and
Baseline
Values
differ
only
in
the
range
of
COD
concentration
that
they
are
designed
to
measure.
Reagent
concentrations
and
sample
volumes
are
adjusted
to
accommodate
a
wide
range
of
sample
concentrations,
since
the
dynamic
range
of
the
chemistry
used
to
detect
COD
is
somewhat
limited.
Data
from
all
three
of
these
methods
are
directly
comparable.

Method
410.1
is
designed
to
measure
mid­
level
concentrations
(
greater
than
50
mg/
L)
of
COD
and
is
associated
with
a
nominal
quantitation
limit
of
50
mg/
L.
Method
410.2
is
designed
to
measure
low­
level
concentrations
in
the
range
of
5­
50
mg/
L.
Method
410.4
has
a
measurement
range
of
3­
900
mg/
L
for
automated
procedures
and
measurement
range
of
20­
900
mg/
L
for
manual
procedures.
EPA
contracts
required
that
laboratories
measure
down
to
the
lowest
quantitation
limit
possible
for
whatever
method
is
used.
Therefore,
if
the
laboratory
analyzes
a
sample
using
Method
410.1
and
obtains
a
nonquantitated
result,
it
must
reanalyze
the
sample
using
Method
410.2.
Thus,
the
quantitation
limit
reported
for
nonquantitated
was
5
mg/
L,
unless
sample
dilutions
were
required
for
complex
matrices.

For
all
COD
data,
EPA
used
the
baseline
value
of
5
mg/
L
that
is
associated
with
the
lower
quantitation
limit
for
the
titrimetric
procedures
because
most
of
the
data
used
to
determine
COD
were
obtained
by
the
titrimetric
procedures
(
i.
e.,
Methods
410.1
and
410.2).

B.
4.7
EPA
Method
325.3
(
Chloride)

Chloride
was
measured
using
Method
325.3,
which
is
approved
at
40
CFR
136.
Method
325.3
is
a
titrimetric
procedure
and
measures
concentrations
greater
than
1
mg/
L;
therefore,
EPA
used
the
baseline
value
of
1
mg/
L.

B.
4.8
EPA
Method
340.2
(
Fluoride)

Fluoride
was
determined
by
Method
340.2,
which
is
approved
at
40
CFR
136.
Method
340.2
is
a
potentiometric
procedure
that
uses
a
fluoride
electrode.
The
nominal
quantitation
limit
of
0.1
mg/
L
is
expressed
in
the
method
as
the
lower
limit
of
the
measurement
range.
This
nominal
quantitation
limit
was
used
as
the
baseline
value
for
fluoride.

B.
4.9
EPA
Method
218.4,
SM
3111A,
and
SM
3500D
(
Hexavalent
Chromium)

For
EPA
sampling
episodes,
hexavalent
chromium
was
determined
by
Method
218.4
and
SM
3500D,
which
are
approved
at
40
CFR
136.
Industry
supplied
data
generated
by
SM
3111A
which
is
not
approved
at
40
CFR
136.
Method
218.4
utilizes
atomic
absorption
for
the
determination
of
hexavalent
chromium
after
chelation
and
extraction.
SM
3500D
is
a
colorimetric
procedure
using
reaction
with
diphenylcarbazide
to
produce
a
color
proportional
to
Cr6+
concentration.
SM
3111A
utilizes
flame
atomic
absorption
spectrometry
to
measure
Cr6+
or
total
Cr.

B­
7
Appendix
B
­
Analytical
Methods
and
Baseline
Values
In
Method
218.4,
SM
3111A,
and
SM
3500D,
the
nominal
quantitation
limit
or
lower
limit
of
the
measurement
range
is
0.01
mg/
L.
Because
EPA
used
Methods
218.4
and
SM
3500D
for
analysis,
the
nominal
quantitation
limit
of
0.01
mg/
L
was
used
as
the
baseline
value
for
all
hexavalent
chromium
results.

B.
4.10
EPA
Method
150.1
and
SM
4500H
(
pH)

For
EPA
sampling
episodes,
pH
was
determined
by
Method
150.1.
For
industry­
supplied
data,
pH
was
determined
by
SM
4500H.
Both
methods
are
approved
at
40
CFR
136.
For
Method
150.1
and
SM
4500H,
the
pH
of
a
sample
is
determined
electrometrically
using
either
a
glass
electrode
in
combination
with
a
reference
potential
or
a
combination
electrode.
There
are
no
nominal
quantitation
limits
for
either
Method
150.1
or
SM
4500H.

B.
4.11
EPA
Methods
375.2
and
375.4
(
Sulfate)

For
EPA
sampling
episodes,
sulfate
was
measured
by
Methods
375.2
and
375.4.
For
industry­
supplied
data,
sulfate
was
measured
by
Method
375.4.
Both
of
these
methods
are
approved
at
40
CFR
136.
Method
375.2
is
a
colorimetric
procedure
that
uses
the
decrease
in
color
caused
by
the
formation
of
barium
sulfate
to
measure
the
sulfate
concentration.
Method
375.4
measures
the
turbidity
created
by
the
insoluble
barium
sulfate
in
solution.
A
dispersant/
buffer
is
added
to
the
solution
to
aid
in
creating
uniform
suspension
of
the
barium
sulfate.

The
nominal
quantitation
limit
(
also
the
lower
limit
of
the
measurement
range)
for
Method
375.2
is
0.50
mg/
L.
The
nominal
quantitation
limit
(
also
the
lower
limit
of
the
measurement
range)
for
Method
375.4
is
1
mg/
L.
EPA
used
the
baseline
value
of
1
mg/
L
that
is
associated
with
the
higher
quantitation
limit
for
all
the
sulfate
data,
rather
than
having
multiple
baseline
values,
because
most
of
the
sulfate
data
was
determined
by
Method
375.4.

B.
4.12
EPA
Methods
335.2
and
335.3
(
Total
Cyanide)

EPA
determined
total
cyanide
using
Method
335.2.
Industry
determined
total
cyanide
by
Methods
335.2
and
335.3.
Both
methods
are
approved
at
40
CFR
136.
Method
335.2
uses
either
titration
with
silver
nitrate,
or
colorimetry
with
an
organic
dye,
to
measure
total
cyanide.
Method
335.3
uses
an
automated
distillation­
colorimetry
procedure
for
continuous
flow
analytical
systems
that
utilizes
UV
oxidation
to
measure
total
cyanide.

The
nominal
quantitation
limit
for
Method
335.2,
expressed
in
the
method
as
the
lower
limit
of
the
measurement
range,
is
0.02
mg/
L.
The
nominal
quantitation
limit
for
Method
335.3,
also
expressed
as
the
lower
limit
of
the
measurement
range,
is
0.005
mg/
L.
Because
EPA
used
Method
335.2,
the
Agency
used
the
nominal
quantitation
limit
of
0.02
mg/
L
as
the
baseline
value
for
all
total
cyanide
results.

B­
8
Appendix
B
­
Analytical
Methods
and
Baseline
Values
B.
4.13
EPA
Method
160.1
and
SM
2540C
(
Total
Dissolved
Solids)

EPA
determined
total
dissolved
solids
(
TDS)
by
Method
160.1.
Industry
determined
TDS
by
SM
2540C.
Both
methods
are
approved
at
40
CFR
136
under
"
residue­
filterable."
Method
160.1
and
SM
2540C
are
gravimetric
methods
with
a
lower
limit
of
the
measurement
range
of
10
mg/
L;
this
value
is
the
nominal
quantitation
limit.
The
nominal
quantitation
limit
of
10
mg/
L
is
also
the
baseline
value.

B.
4.14
EPA
Method
351.3
(
Total
Kjeldahl
Nitrogen)

EPA
determined
total
Kjeldahl
nitrogen
(
TKN)
by
Method
351.3,
which
is
approved
at
40
CFR
136.
Method
351.3
is
a
manual
colorimetric
analysis
that
has
a
lower
measurement
range
limit,
which
is
also
the
nominal
quantitation
limit,
of
1.0
mg/
L.
The
nominal
quantitation
limit
of
1.0
mg/
L
is
also
the
baseline
value.

B.
4.15
EPA
Method
415.1
(
Total
Organic
Carbon)

EPA
determined
total
organic
carbon
(
TOC)
by
Method
415.1,
which
is
approved
at
40
CFR
136.
Method
415.1
is
a
combustion
(
or
oxidation)
method
with
a
lower
measurement
range
limit
of
1
mg/
L.
EPA
used
this
nominal
quantitation
limit
of
1
mg/
L
as
the
baseline
value.

B.
4.16
EPA
Methods
420.1
and
420.2
(
Total
Phenols)

In
EPA's
database,
the
terms
"
total
phenols"
and
"
total
recoverable
phenolics"
are
used
synonymously.
The
term
"
total
recoverable
phenolics"
is
used
in
the
titles
of
Methods
420.1
to
420.4.
While
"
total
recoverable
phenolics"
could
be
considered
a
more
accurate
term
for
what
is
measured
in
any
of
these
related
methods,
both
terms
refer
to
an
aggregate
measure
of
compounds
with
a
phenol­
like
or
"
phenolic"
structure.
The
use
of
the
adjective
"
recoverable"
simply
recognizes
that
there
are
some
compounds
that
are
not
measured,
as
well
as
other
related
compounds
in
this
class.
Thus,
the
method
reports
what
can
be
recovered
from
the
sample
under
the
conditions
of
the
analysis.

The
methods
for
the
analysis
of
total
phenols
employ
the
reagent
4­
aminoantipyrine
(
4AAP),
which
reacts
with
phenolic
compounds
to
produce
a
dark
red
product,
an
antipyrine
dye.
The
concentration
of
the
phenolic
compounds
is
determined
by
measuring
the
absorbance
of
the
sample
at
a
wavelength
of
460
to
520
nm,
depending
on
the
method.
The
methods
are
calibrated
using
a
series
of
standards
containing
the
single
compound
phenol.
Methods
420.1
and
420.2,
the
two
methods
approved
at
40
CFR
136,
provide
several
options
for
sample
preparation
and
analysis,
including
a
preliminary
distillation
designed
to
remove
interferences,
and
a
chloroform
extraction
procedure
in
Method
420.1
that
is
designed
to
improve
the
sensitivity
of
the
method.
Both
methods
also
provide
information
on
the
concentrations
of
the
calibration
standards
that
may
be
prepared
for
a
given
set
of
procedural
options.

B­
9
Appendix
B
­
Analytical
Methods
and
Baseline
Values
The
methods
themselves
do
not
contain
a
required
calibration
range.
Each
laboratory
can,
and
does,
establish
a
calibration
range
based
on
its
use
of
the
method.
EPA
used
a
baseline
value
of
0.05
mg/
L
because
this
was
the
most
commonly
reported
sample­
specific
detection
limit
in
EPA's
sampling
episode
data
(
these
data
included
more
concentrated
samples
than
effluent).

B.
4.17
EPA
Methods
365.2
and
365.3
(
Total
Phosphorus)

EPA
determined
total
phosphorus
by
Methods
365.2
and
365.3.
Both
methods
are
approved
at
40
CFR
136.
Total
phosphorus
represents
all
of
the
phosphorus
present
in
the
sample,
regardless
of
form,
as
measured
by
the
persulfate
digestion
procedure.

The
two
methods
differ
only
in
the
preparation
of
one
of
the
reagents.
Method
365.2
specifies
the
separation
of
the
ammonium
molybdate
and
the
antimony
potassium
tartrate
from
the
ascorbic
acid
reagent.
Method
365.3
allows
for
combining
these
reagents
into
a
single
solution.
Because
the
chemistry
is
unaffected,
the
data
are
directly
comparable.

These
methods
have
the
same
nominal
quantitation
limit
of
0.01
mg/
L.
EPA
used
this
value
as
the
baseline
value
for
total
phosphorus.

B.
4.18
EPA
Methods
376.1
and
376.2,
SM
4500D
and
SM
4500E,
and
D4658
(
Total
Sulfide)

EPA
determined
total
sulfide
by
Methods
376.1,
376.2,
and
SM
4500E,
all
of
which
are
approved
at
40
CFR
136.
Industry
determined
sulfide
by
SM
4500D
and
ASTM
Method
D4658.
SM
4500D
is
approved
at
40
CFR
136,
while
ASTM
Method
D4658
is
not
approved
at
40
CFR
136.
Method
376.1
and
SM
4500E
utilize
an
iodine
solution
to
oxidize
any
sulfide
present
in
the
sample.
The
remaining
iodine
is
then
titrated
with
sodium
thiosulfate
in
the
presence
of
a
starch
solution.
The
quantity
of
iodine
added
to
the
sample
and
the
titrant
required
to
neutralize
the
remaining
iodine
give
the
sulfide
concentration
by
calculation.
Method
376.2
and
SM
4500D
use
the
reaction
of
the
sulfide
ion
with
ferric
chloride
and
dimethyl­
P­
phenylenediamine
to
produce
deeply
colored
methylene
blue.
The
color
is
proportional
to
the
sulfide
concentration.
ASTM
Method
D4658
utilizes
an
ion­
selective
electrode
to
determine
sulfide
ion
in
water.

EPA
collected
sulfide
data
for
236
samples
in
seven
post­
proposal
sampling
episodes
using
Methods
376.1,
376.2,
and
SM
4500E
(
EPA
Episode
numbers
6455,
6456,
6457,
6458,
6461,
6462,
and
6463).
These
samples
were
collected
from
both
process
wastewaters
prior
to
treatment
and
effluent
wastewater
after
treatment.
EPA
reviewed
the
analytical
data
from
these
236
samples
and
compared
the
three
different
methods.
The
study
is
included
in
the
rulemaking
record
(
see
Section
16.2
of
the
rulemaking
record,
DCN
16941)
and
a
summary
of
the
findings
are
in
the
notice
of
data
availability
(
67
FR
38754;
June
5,
2002).

B­
10
Appendix
B
­
Analytical
Methods
and
Baseline
Values
The
nominal
quantitation
limit
for
Method
376.1
and
SM
4500E,
which
is
also
the
lower
limit
of
the
measurement
range,
is
1.0
mg/
L.
The
nominal
quantitation
limit
for
Method
376.2
and
SM
4500D
is
0.5
mg/
L.
The
nominal
quantitation
limit
for
D4658,
which
is
also
the
lower
limit
of
the
measurement
range,
is
0.04
mg/
L.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
1.0
mg/
L
as
the
baseline
value
from
Method
376.1
because
the
majority
of
the
data
were
determined
by
this
method.

B.
4.19
EPA
Method
160.2
and
SM
2540D
(
Total
Suspended
Solids)

EPA
determined
total
suspended
solids
(
TSS)
by
Method
160.2.
Industry
determined
TSS
by
SM
2540D.
Both
methods
are
approved
at
40
CFR
136
under
"
residue­
non­
filterable."
Method
160.2
and
SM
2540D
are
gravimetric
methods
with
a
lower
limit
of
the
measurement
range
of
4
mg/
L;
this
value
is
also
the
nominal
quantitation
limit.
The
nominal
quantitation
limit
of
4
mg/
L
is
the
baseline
value.

B.
4.20
EPA
Method
204.1
and
7041
(
Antimony)

Industry
determined
antimony
by
Methods
204.1
and
7041.
Method
204.1
is
approved
at
40
CFR
136.
Method
7041
is
from
Test
Methods
for
Evaluating
Solid
Waste,
Physical/
Chemical
Methods
(
SW­
846).
Although
Method
7041
is
not
listed
at
40
CFR
136,
it
is
approved
for
analyses
of
samples
under
the
RCRA
regulations
at
40
CFR
261.
Method
204.1
utilizes
direct­
aspiration
atomic
absorption
as
the
determinative
technique
to
measure
antimony.
Method
7041
utilizes
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.

The
nominal
quantitation
limit
(
also
the
lower
limit
of
the
measurement
range)
for
Method
204.1
is
1.0
mg/
L.
The
nominal
quantitation
limit
(
also
the
lower
limit
of
the
measurement
range)
for
Method
7041
is
20
:
g/
L.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
20
:
g/
L
for
antimony
from
Method
1620
as
the
baseline
value,
because
this
was
the
method
that
EPA
used
for
the
determination
of
antimony.

B.
4.21
EPA
Method
206.2
and
7060A
(
Arsenic)

Industry
determined
arsenic
by
Methods
206.2
and
7060A.
Method
206.2
is
approved
at
40
CFR
136.
Method
7060A
is
from
Test
Methods
for
Evaluating
Solid
Waste,
Physical/
Chemical
Methods
(
SW­
846).
Although
Method
7060A
is
not
listed
at
40
CFR
136,
it
is
approved
for
analyses
of
samples
under
the
RCRA
regulations
at
40
CFR
261.
Methods
206.2
and
7060A
utilize
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.

The
nominal
quantitation
limit
(
also
the
lower
limit
of
the
measurement
range)
for
Method
206.2
and
Method
7060A
is
5.0
:
g/
L.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
10
:
g/
L
for
arsenic
from
Method
1620
as
the
baseline
value,
because
this
was
the
method
that
EPA
used
for
the
determination
of
arsenic.

B­
11
Appendix
B
­
Analytical
Methods
and
Baseline
Values
B.
4.22
EPA
Method
231.2
(
Gold)

EPA
determined
gold
by
Method
231.2,
since
this
parameter
is
only
semiquantitatively
analyzed
by
Method
1620.
Method
231.2
is
approved
at
40
CFR
136.
Method
231.2
utilizes
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.
The
nominal
quantitation
limit
for
gold,
which
is
also
the
lower
limit
of
the
measurement
range,
is
5
:
g/
L.
The
nominal
quantitation
limit
is
also
the
baseline
value.

B.
4.23
EPA
Method
239.1
(
Lead)

Industry
determined
lead
by
Method
239.1,
which
is
approved
at
40
CFR
136.
Method
239.1
utilizes
direct­
aspiration
atomic
absorption
as
the
determinative
technique
to
measure
lead.
The
nominal
quantitation
limit
of
0.1
mg/
L
is
expressed
in
the
method
as
the
lower
limit
of
the
measurement
range.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
50
:
g/
L
for
lead
from
Method
1620
from
the
ICP
technique,
as
the
baseline
value
since
this
was
the
method
that
EPA
used
for
the
determination
of
lead.

B.
4.24
EPA
Methods
245.1
and
245.2
(
Mercury)

Industry
determined
mercury
by
Methods
245.1
and
245.2,
both
of
which
are
approved
at
40
CFR
136.
The
methods
utilize
cold
vapor
atomic
absorption
as
the
determinative
technique
to
measure
mercury.
The
nominal
quantitation
limit
for
both
methods
is
0.2
:
g/
L,
which
is
also
expressed
as
the
lower
limit
of
the
measurement
range.
The
nominal
quantitation
limit
matches
the
nominal
quantitation
limit
from
Method
1620,
which
EPA
used
to
determine
mercury.
The
nominal
quantitation
limit
is
the
same
as
the
baseline
value
of
0.2
:
g/
L.

B.
4.25
EPA
Method
265.2
(
Rhodium)

EPA
determined
rhodium
by
Method
265.2,
since
this
parameter
is
only
semiquantitatively
analyzed
by
Method
1620.
Method
265.2
is
approved
at
40
CFR
136.
Method
265.2
utilizes
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.
The
nominal
quantitation
limit
for
rhodium,
which
is
also
the
lower
limit
of
the
measurement
range,
is
20
:
g/
L.
The
nominal
quantitation
limit
is
also
the
baseline
value.

B.
4.26
EPA
Methods
270.2
and
7740
(
Selenium)

Industry
determined
selenium
by
Methods
270.2
and
7740.
Method
270.2
is
approved
at
40
CFR
136.
Method
7740
is
from
Test
Methods
for
Evaluating
Solid
Waste,
Physical/
Chemical
Methods
(
SW­
846).
Although
Method
7740
is
not
listed
at
40
CFR
136,
it
is
approved
for
analyses
of
samples
under
the
RCRA
regulations
at
40
CFR
261.
Methods
270.2
and
7740
utilize
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.

B­
12
Appendix
B
­
Analytical
Methods
and
Baseline
Values
The
nominal
quantitation
limit
for
Method
270.2
and
Method
7740,
which
is
also
lower
limit
of
the
measurement
range,
is
5.0
:
g/
L.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
5
:
g/
L
for
selenium
from
Method
1620
as
the
baseline
value,
since
this
was
the
method
that
EPA
used
for
the
determination
of
selenium.

B.
4.27
EPA
Method
272.1
(
Silver)

Industry
determined
silver
by
Method
272.1,
which
is
approved
at
40
CFR
136.
Method
272.1
utilizes
direct­
aspiration
atomic
absorption
as
the
determinative
technique
to
measure
silver.
The
nominal
quantitation
limit
of
0.1
mg/
L
is
expressed
in
the
method
as
the
lower
limit
of
the
measurement
range.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
10
:
g/
L
for
silver
from
Method
1620
as
the
baseline
value,
since
this
was
the
method
that
EPA
used
for
the
determination
of
silver.

B.
4.28
EPA
Methods
279.1
and
7841
(
Thallium)

Industry
determined
thallium
by
Methods
279.1
and
7841.
Method
279.1
is
approved
at
40
CFR
136.
Method
7841
is
from
Test
Methods
for
Evaluating
Solid
Waste,
Physical/
Chemical
Methods
(
SW­
846).
Although
Method
7841
is
not
listed
at
40
CFR
136,
it
is
approved
for
analyses
of
samples
under
the
RCRA
regulations
at
40
CFR
261.
Method
279.1
utilizes
direct­
aspiration
atomic
absorption
as
the
determinative
technique
to
measure
thallium.
Method
7841
utilizes
the
furnace
technique
in
conjunction
with
an
atomic
absorption
spectrophotometer.

The
nominal
quantitation
limit
for
Method
279.1,
which
is
also
the
lower
limit
of
the
measurement
range,
is
1.0
mg/
L.
The
nominal
quantitation
limit
for
Method
7841,
which
is
also
the
lower
limit
of
the
measurement
range,
is
5
:
g/
L.
Rather
than
use
different
baseline
values
for
the
same
pollutant,
EPA
used
the
minimum
level
of
10
:
g/
L
for
thallium
from
Method
1620
as
the
baseline
value,
since
this
was
the
method
that
EPA
used
for
the
determination
of
thallium.

B.
4.29
EPA
Methods
624
and
625
(
Volatile
Organics
and
Semivolatile
Organics)

EPA
included
industry­
supplied
data
from
Methods
624
and
625,
both
of
which
are
approved
at
40
CFR
136.
Methods
624
and
625
are
GC/
MS
methods,
similar
to
Methods
1624
and
1625,
except
that
Methods
624
and
625
do
not
utilize
isotope
dilution.
The
nominal
quantitation
limits
are
expressed
as
the
lower
limit
of
the
measurement
range,
typically
the
concentration
of
the
lowest
calibration
standard.
However,
rather
than
use
different
baseline
values
for
the
same
pollutants
(
Methods
624
and
625
have
many
of
the
same
analytes
as
Methods
1624
and
1625),
EPA
used
the
minimum
levels
that
are
listed
in
Methods
1624
and
1625
as
the
baseline
values,
since
these
methods
were
used
by
EPA
for
the
determination
of
volatile
and
semivolatile
organic
analytes.

B­
13
Appendix
B
­
Analytical
Methods
and
Baseline
Values
B.
4.30
EPA
Method
630.1
(
Ziram)

Ziram
was
determined
by
Method
630.1.
There
are
no
methods
approved
at
40
CFR
136
for
ziram.
In
this
method,
the
sample
is
digested
with
acid
to
yield
CS2
by
hydrolysis
of
the
dithiocarbamate
moiety.
The
evolved
CS2
is
extracted
from
the
water
with
hexane
and
the
extract
is
injected
into
a
GC.
The
nominal
quantitation
limit
was
determined
by
a
low­
point
calibration
standard.
The
nominal
quantitation
limit
for
ziram
is
10
:
g/
L
and
was
used
as
the
baseline
value.

Analytical
Method
Development
Efforts
Section
304(
h)
of
the
Clean
Water
Act
directs
EPA
to
promulgate
guidelines
establishing
test
procedures
for
the
analysis
of
pollutants.
These
methods
allow
the
analyst
to
determine
the
presence
and
concentration
of
pollutants
in
wastewater.
The
methods
are
used
for
compliance
monitoring,
for
filing
applications
for
the
NPDES
program
under
40
CFR
122.21,
122.41,
122.44
and
123.25,
and
for
the
implementation
of
the
pretreatment
standards
under
40
CFR
403.10
and
403.12.
To
date,
EPA
has
promulgated
methods
for
all
conventional
and
toxic
pollutants,
and
for
some
nonconventional
pollutants.

Currently
approved
methods
for
metals
and
wet
chemistry
parameters
are
included
in
the
table
of
approved
inorganic
test
procedures
at
40
CFR
136.3,
Table
I­
B.
Table
I­
C
at
40
CFR
136.3
lists
approved
methods
for
measurement
of
nonpesticide
organic
pollutants,
and
Table
I­
D
lists
approved
methods
for
the
toxic
pesticide
pollutants
and
for
other
pesticide
pollutants.
Dischargers
must
use
the
test
methods
promulgated
at
40
CFR
136.3
or
incorporated
by
reference
in
the
tables,
when
available,
to
monitor
pollutant
discharges
from
the
metal
products
and
machinery
(
MP&
M)
industry,
unless
specified
otherwise
in
40
CFR
413,
433,
438,
463,
464,
467,
and
471,
or
by
the
permitting
authority.

Table
I­
C
does
not
include
six
of
the
MP&
M
semivolatile
organic
pollutants
and
one
of
the
MP&
M
volatile
organic
pollutant
that
EPA
is
regulating
in
the
rule.
Although
these
pollutants
are
missing
from
Table
I­
C,
the
analyte
list
for
Method
1624
contains
the
volatile
organic
pollutant
and
the
analyte
list
for
Method
1625
contains
the
six
semivolatile
organic
pollutants.
EPA
promulgated
both
of
these
methods
for
use
in
Clean
Water
Act
measurement
programs
at
40
CFR
136,
Appendix
A.

As
a
part
of
the
rule,
EPA
will
allow
the
use
of
modified
versions
of
Methods
624
and
1624
for
the
determination
of
the
additional
volatile
organic
pollutant
and
modified
versions
of
Methods
625
and
1625
for
the
determination
of
the
additional
six
semivolatile
organic
pollutants.

The
modifications
to
Methods
624,
625,
1624,
and
1625
have
been
included
in
the
Docket
for
the
rule.
The
modifications
to
Methods
624,
625,
1624,
and
1625
consist
of
text,
performance
data,
and
quality
control
(
QC)
acceptance
criteria
for
the
additional
analytes.
This
information
will
allow
a
laboratory
to
practice
the
methods
with
the
additional
analytes
as
an
integral
part.
EPA
conducted
an
interlaboratory
validation
study
on
the
modifications
to
these
methods.
The
B­
14
B.
5
Appendix
B
­
Analytical
Methods
and
Baseline
Values
data
from
the
interlaboratory
study
and
the
proposed
modifications
to
the
method
were
made
available
for
public
comment
in
a
notice
of
data
availability
(
see
Section
B.
4.18).
EPA
is
promulgating
these
method
modifications
for
monitoring
MP&
M
industry
wastewaters
at
40
CFR
136
in
the
rule.

As
part
of
the
rule,
the
following
pollutants
will
be
added
to
their
respective
analyte
lists
for
the
MP&
M
industry
only:

Methods
Pollutant
CAS
Number
EPA
Methods
624/
1624
carbon
disulfide
75­
15­
0
EPA
Methods
625/
1625
aniline
62­
53­
3
EPA
Methods
625/
1625
3,6­
dimethylphenanthrene
1576­
67­
6
EPA
Methods
625/
1625
2­
isopropylnaphthalene
2027­
17­
0
EPA
Methods
625/
1625
1­
methylfluorene
1730­
37­
6
EPA
Methods
625/
1625
2­
methylnaphthalene
91­
57­
6
EPA
Methods
625/
1625
1­
methylphenanthrene
832­
69­
9
B­
15
Appendix
B
­
Analytical
Methods
and
Baseline
Values
Table
B­
1
Analytical
Methods
and
Baseline
Values
Analyte
Method
CAS
Number
Samples
Collected
and
Analyzed
by
Nominal
Quantitation
Value
(
mg/
L)
Baseline
Value
(
mg/
L)

Amenable
Cyanide
335.1
C025
EPA,
Industry
0.02
0.02
Ammonia
as
Nitrogen
350.2
766417
EPA
0.05
0.05
350.3
0.03
Available
Cyanide
OIA­
1677
C054
EPA
0.002
0.002
BOD
Carbonaceous
BOD
405.1
C003
EPA
2.00
2.00
5210B
C002
2.00
Chemical
Oxygen
Demand
410.1
C004
EPA
50.00
5.00a
410.2
5.00
410.4(
automated)
b
3.00
410.4(
manual)
b
20.00
Chloride
325.3
16887006
EPA
1.00
1.00
Fluoride
340.2
16984488
EPA
0.10
0.10
HEM,
SGT­
HEM
1664
C036,
C037
EPA,
Industry
5.00
5.00
Hexavalent
Chromium
218.4
18540299
EPA
0.01
0.01
3111A
Industry
0.01
3500D
EPA
0.01
Metals
1620
c
EPA
c
c
200.7
c
Industry
c
c
pH
150.1
C006
EPA
N/
A
4500H
Industry
N/
A
Semivolatile
Organics
1625
c
EPA
c
c
625
Industry
Sulfate
375.2
14808798
EPA
3.00
1.00
375.4
EPA,
Industry
1.00
Total
Cyanide
335.2
57125
EPA,
Industry
0.02
0.02
335.3
Industry
0.005
TDS
160.1
C010
EPA
10.00
10.00
2540C
Industry
10.00
TKN
351.3
C021
EPA
1.00
1.00
TOC
415.1
C012
EPA
1.00
1.00
Total
Phenols
420.1
C020
EPA
d
0.05
420.2
d
Total
Phosphorus
365.2
14265442
EPA
0.01
0.01
365.3
0.01
B­
16
Appendix
B
­
Analytical
Methods
and
Baseline
Values
Table
B­
1
(
Continued)

Analyte
Method
CAS
Number
Samples
Collected
and
Analyzed
by
Nominal
Quantitation
Value
(
mg/
L)
Baseline
Value
(
mg/
L)

Total
Sulfide
376.1
18496258
EPA
1.00
1.00
376.2
0.10
4500D
Industry
0.50
4500E
EPA
1.00
D4568
Industry
0.04
TSS
160.2
C009
EPA
4.00
4.00
2540D
Industry
4.00
Volatile
Organics
1624
c
EPA
c
c
624
Industry
Ziram
630.1
137304
EPA
0.01
0.01
aThe
baseline
value
was
adjusted
to
reflect
the
lowest
nominal
quantitation
limit
of
the
titrimetric
procedures
(
i.
e.,
410.1,
410.2,
and
5220B).
See
Section
B.
4.6
for
a
detailed
explanation.
bMethod
410.4
lists
two
different
quantitation
limits
that
are
dependent
upon
whether
the
automated
or
manual
protocols
were
followed.
The
automated
method
limit
=
3
mg/
L
and
the
manual
method
limit
=
20
mg/
L.
cThe
method
analyzed
a
number
of
pollutants
each
with
its
own
CAS
number,
baseline
value,
and
nominal
quantitation
limit.
dThe
method
does
not
have
a
required
calibration
range.
The
baseline
value
is
based
upon
the
most
frequently
reported
sample­
specific
detection
limit.

B­
17
Appendix
C
­
Wastewater
Characteristics
Appendix
C
WASTEWATER
CHARACTERISTICS
Appendix
C
­
Wastewater
Characteristics
Appendix
C
WASTEWATER
CHARACTERISTICS
This
appendix
summarizes
the
characteristics
of
wastewater
generated
by
unit
operations
evaluated
for
the
final
rule
and
discharged
to
wastewater
treatment
systems.
The
wastewaters
characterized
in
this
appendix
can
be
grouped
into
the
following
types
of
wastewaters:

C
Hexavalent
chromium­
bearing
wastewater;
C
Cyanide­
bearing
wastewater;
C
Oil­
bearing
and
organic
pollutant­
bearing
wastewaters;
C
Chelated
metal­
bearing
wastewater;
and
C
Metal­
bearing
wastewater.

EPA
evaluated
a
number
of
unit
operations
for
the
May
1995
proposal,
January
2001
proposal,
and
June
2002
NODA
(
see
Tables
4­
3
and
4­
4).
However,
EPA
selected
a
subset
of
these
unit
operations
for
regulation
in
the
final
rule
(
see
Section
1.0).
For
this
appendix,
the
term
"
proposed
MP&
M
operations"
means
those
operations
evaluated
for
the
two
proposals,
NODA,
and
final
rule.
The
term
"
final
MP&
M
operations"
means
those
operations
defined
as
"
oily
operations"
(
see
Section
1.0,
40
CFR
438.2(
f),
and
Appendix
B
to
Part
438)
and
regulated
by
the
final
rule.

Sections
C.
1
through
C.
5
summarize,
for
each
type
of
wastewater,
analytical
data
obtained
during
the
MP&
M
regulatory
development
process
for
unit
operations
and
influents
to
the
wastewater
treatment
systems.
These
subsections
present
the
number
of
samples
analyzed,
the
number
of
times
each
pollutant
was
detected,
and
the
minimum,
maximum,
mean,
and
median
pollutant
concentrations.
Oil­
bearing
and
organic
pollutant­
bearing
wastewaters
are
characterized
in
Section
5.0.

Analytical
data
from
the
MP&
M
sampling
program,
including
data
obtained
from
sanitation
districts,
facilities
performing
proposed
MP&
M
operations,
and
MP&
M
industry
trade
associations,
are
in
the
sampling
episode
reports
located
in
Sections
5.2
and
15.3
of
the
rulemaking
record.

C.
1
Hexavalent
Chromium­
Bearing
Wastewater
Hexavalent
chromium­
bearing
wastewater
exhibits
high
concentrations
of
hexavalent
chromium
and
may
contain
other
metals,
and
generally
has
a
low
pH
of
approximately
2.
Sections
C.
1.1
and
C.
1.2
present
chromium
data
for
process
water
and
associated
rinse
water
and
for
the
influent
to
the
chromium
reduction
process,
respectively.

C­
1
Appendix
C
­
Wastewater
Characteristics
C.
1.1
Process
Water
and
Rinse
Water
Hexavalent
chromium
is
present
in
process
bath
wastewater
from
various
unit
operations
(
e.
g.,
chromic
acid
anodizing,
chromate
conversion
coating,
and
chromium
electroplating).
Table
C­
1
presents
the
number
of
samples
collected
and
analyzed
during
EPA s
sampling
program
for
unit
operations
and
associated
rinses
that
generate
hexavalent
chromium­
bearing
wastewater.

Table
C­
1
Number
of
Process
and
Rinse
Water
Samples
for
Unit
Operations
That
Generate
Hexavalent
Chromium­
Bearing
Wastewater
Unit
Operation
No.
of
Process
Water
Samples
No.
of
Rinse
Water
Samples
Acid
Treatment
with
Chromium
Anodizing
with
Chromium
Chromate
Conversion
Coating
(
Or
Chromating)

Electroplating
with
Chromium
Wet
Air
Pollution
Control
1
2
16
4
6
3
7
23
10
NA
Source:
MP&
M
Sampling
Program.
NA
­
Not
applicable.
No
associated
rinse.

The
mean
total
and
hexavalent
chromium
concentrations
in
process
bath
water
from
these
operations
are
24,120
milligrams
per
liter
(
mg/
L)
and
10.0
mg/
L,
respectively.
In
the
associated
rinses,
the
mean
concentrations
for
total
and
hexavalent
chromium
are
156
mg/
L
and
10.3
mg/
L,
respectively.
Table
C­
2
summarizes
total
and
hexavalent
chromium
concentration
data
for
the
process
bath
water
and
rinse
water
samples
with
detected
concentrations
for
the
unit
operations
listed
in
Table
C­
1.

Table
C­
2
Chromium
Concentration
Data
for
Process
Water
and
Rinse
Water
Source
Chromium
Form
No.
of
Samples
Analyzed
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Process
Water
Total
29
29
0.045
139,000
24,120
2,990
Hexavalent
2
1
10.0
10.0
10.0
10.0
Rinse
Water
Total
43
43
0.22
1,762
156
12.8
Hexavalent
6
6
2.1
21.2
10.3
8.0
Source:
MP&
M
Sampling
Program.

C­
2
Appendix
C
­
Wastewater
Characteristics
C.
1.2
Influent
to
Chromium
Reduction
Process
Facilities
performing
proposed
MP&
M
operations
usually
segregate
hexavalent
chromium­
bearing
wastewater
and
treat
it
in
a
chromium
reduction
unit
before
commingling
it
with
other
process
wastewater
for
further
treatment.
This
segregated
wastewater
requires
preliminary
treatment
to
reduce
hexavalent
chromium
to
trivalent
chromium
because
the
chemical
precipitation
systems
typically
used
to
treat
the
commingled
wastewater
do
not
effectively
treat
hexavalent
chromium.
Typical
chrome
treatment
involves
chromium
reduction
using
sulfur
dioxide,
sodium
bisulfite,
sodium
metabisulfite,
peroxide,
or
ferrous
sulfate
(
see
Section
8.4.1).
Table
C­
3
presents
the
total
and
hexavalent
chromium
concentration
data
for
samples
of
the
influent
to
the
chromium
reduction
process
collected
during
EPA s
sampling
program.
The
treatment
influent
typically
represents
several
commingled
wastestreams,
most
of
which
are
rinses.
The
influent­
to­
treatment
concentrations
are
typically
lower
than
the
concentrations
of
process
and
rinse
water
due
to
the
number
of
high­
flow,
low­
concentration
rinses
that
are
commingled
prior
to
treatment.

Table
C­
3
Chromium
Concentration
Data
for
the
Influent
to
the
Chromium
Reduction
Process
Form
of
Chromium
No.
of
Samples
Analyzed
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Total
Chromium
54
54
0.2
432
54.8
18.2
Hexavalent
Chromium
21
18
0.027
20
6.7
4.0
Source:
MP&
M
Sampling
Program.

Cyanide­
Bearing
Wastewater
Cyanide­
bearing
wastewater
exhibits
high
concentrations
of
cyanide
and
metals
such
as
copper,
cadmium,
and
zinc,
and
generally
has
a
high
pH
of
approximately
12.
Electroplating
baths
usually
are
the
source
of
the
high
concentrations
of
cyanide.
Cyanide
may
be
analyzed
as
total
cyanide
(
i.
e.,
all
forms
included),
amenable
cyanide
(
i.
e.,
cyanide
present
in
forms
amenable
to
treatment
using
alkaline
chlorination),
or
weak­
acid­
dissociable
cyanide
(
i.
e.,
cyanide
that
dissociates
in
a
weak
acid).
Sections
C.
2.1
and
C.
2.2
present
cyanide
concentration
data
for
cyanide­
bearing
wastewater
generated
in
proposed
MP&
M
operations
and
in
the
influent
to
the
cyanide
treatment
processes,
respectively.

C­
3
C.
2
Appendix
C
­
Wastewater
Characteristics
C.
2.1
Process
Water
and
Rinse
Water
Table
C­
4
presents
the
number
of
process
and
rinse
water
samples
collected
and
analyzed
during
EPA s
sampling
program
for
proposed
MP&
M
operations
that
generate
cyanide­
bearing
wastewater.

Table
C­
4
Number
of
Process
and
Rinse
Water
Samples
for
Unit
Operations
That
Generate
Cyanide­
Bearing
Wastewater
Unit
Operation
No.
of
Process
Water
Samples
No.
of
Rinse
Water
Samples
Alkaline
Treatment
with
Cyanide
Electroplating
with
Cyanide
Wet
Air
Pollution
Control
2
11a
3
4
13
NA
Source:
MP&
M
Surveys
and
MP&
M
Site
Visits.
a
Does
not
include
one
sample
from
a
gold­
cyanide
electroplating
bath
that
was
analyzed
only
for
metals.
NA
­
Not
applicable.
No
associated
rinse.

Cyanide
is
used
as
a
complexing
agent
in
electroplating
and
cleaning
baths
and
is
present
in
wastewater
generated
in
the
wet
air
pollution
control
systems.
Table
C­
5
summarizes
the
total
and
amendable
cyanide
concentration
data
for
the
process
water
and
rinse
water
samples
with
detected
concentrations
for
the
unit
operations
listed
in
Table
C­
4.

Table
C­
5
Cyanide
Concentration
Data
for
Process
Water
and
Rinse
Water
Source
Cyanide
Form
No.
of
Samples
Analyzed
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Process
Water
Total
15
15
2.6
100,000
16,521
5,200
Amenable
1
0
NA
NA
NA
NA
Rinse
Water
Total
17
17
0.054
135
38
12.7
Amenable
3
3
61.5
135
100
104
Source:
MP&
M
Sampling
Program.
NA
­
Not
applicable.
No
samples
were
analyzed
for
amenable
cyanide.

C­
4
Appendix
C
­
Wastewater
Characteristics
C.
2.1
Influent
to
Cyanide
Treatment
Process
Facilities
performing
proposed
MP&
M
operations
usually
segregate
cyanide­
bearing
wastewater
generated
and
treat
it
in
a
cyanide
reduction
process
before
commingling
it
with
other
process
wastewater
for
further
treatment.
This
preliminary
treatment
prevents
cyanide
complexes
from
forming
in
the
commingled
wastewater.
Typical
cyanide
treatment
methods
include
alkaline
chlorination
with
sodium
hypochlorite
or
chlorine
gas
or
ozone
oxidation
(
see
Section
8.4.3).
These
complexes
decrease
the
effectiveness
of
chemical
precipitation,
the
technology
typically
used
to
treat
the
commingled
wastewater.
Table
C­
6
summarizes
the
cyanide
concentration
data
for
the
influent
to
cyanide
treatment
process.
The
treatment
influent
typically
represents
several
commingled
wastestreams,
most
of
which
are
rinses.
The
influent­
to­
treatment
concentrations
are
typically
lower
than
the
concentrations
of
process
and
rinse
water
due
to
the
number
of
high­
flow,
low­
concentration
rinses
that
are
commingled
prior
to
treatment.

Table
C­
6
Cyanide
Concentration
Data
for
Influent
to
the
Cyanide
Treatment
Process
Form
of
Cyanide
No.
of
Samples
Analyzed
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Total
Cyanide
101
98
0.024
1,110
50.7
6.1
Amenable
Cyanide
70
65
0.01
394
34.4
3.15
Source:
MP&
M
Sampling
Program.

C.
3
Oil­
Bearing
and
Organic
Pollutant­
Bearing
Wastewaters
Oil­
bearing
wastewater
exhibits
high
concentrations
of
oil
and
concentrations
of
organic
pollutants.
Oil­
bearing
wastewater
is
classified
as
containing
either
free
(
floating)
oils
or
oil/
water
emulsions.
As
previously
discussed
above,
 
oily
operations 
are
defined
and
regulated
in
the
final
rule
and
described
in
Section
4.0.
The
wastewater
from
oily
operations
is
characterized
in
Section
5.0.
In
addition,
EPA
collected
data
on
two
proposed
MP&
M
operations
(
Bilge
Water
and
Dry
Dock)
that
also
generate
oil­
bearing
and
organic
pollutant­
bearing
wastewaters.
EPA
is
not
regulating
these
two
operations
as
EPA
excluded
the
proposed
Shipbuilding
Dry
Dock
Subcategory
from
the
final
rule
(
see
Section
9.0).
Sampling
episode
reports
for
the
proposed
Shipbuilding
Dry
Dock
Subcategory
are
located
in
Sections
5.2
and
15.2
of
the
rulemaking
record.

C.
4
Chelated
Metal­
Bearing
Wastewater
Chelated
metal­
bearing
wastewater
exhibits
high
concentrations
of
metals,
usually
copper
or
nickel.
Section
C.
4.1
discusses
the
various
unit
processes
that
generate
chelated
metal­

C­
5
Appendix
C
­
Wastewater
Characteristics
bearing
wastewater
and
presents
process
water
and
rinse
water
pollutant
concentration
data
for
those
processes
collected
during
EPA s
sampling
program.
Section
C.
4.2
discusses
the
pollutant
concentration
data
for
the
influent
to
chelation­
breaking
preliminary
treatment
systems.

C.
4.1
Process
Water
and
Rinse
Water
Facilities
performing
proposed
MP&
M
operations
use
chelating
agents
in
unit
operations
to
prevent
metals
from
being
precipitated
in
the
process
bath.
Electroless
plating
processes
and
associated
rinses
are
the
most
common
proposed
MP&
M
operations
that
generate
chelated
metal­
bearing
wastewater.
Some
cleaning
operations
also
generate
chelated
metal­
bearing
wastewater.

To
characterize
process
waters
and
associated
rinse
waters
for
proposed
MP&
M
operations
that
use
chelating
agents,
EPA
collected
37
samples
of
electroless
plating
solutions
and
rinses
from
electroless
nickel
plating,
or
from
electroless
copper.
The
maximum
concentration
of
nickel
in
the
process
water
and
the
rinses
was
7,530
mg/
L
and
378
mg/
L,
respectively.
The
maximum
concentration
of
copper
in
the
process
water
and
the
rinses
was
14,200
mg/
L
and
138
mg/
L,
respectively.
Only
one
sample
of
tin
was
taken
from
process
water,
which
had
a
concentration
of
3.8
mg/
L.
Other
metals
typically
plated
using
electroless
plating
include
gold,
palladium,
and
cobalt.

C.
4.2
Influent
to
Chelate­
Breaking
Preliminary
Treatment
System
Typical
chemical
precipitation
and
sedimentation
treatment
processes
do
not
remove
chelated
metals;
therefore,
facilities
performing
proposed
MP&
M
operations
usually
segregate
and
pretreat
chelated
metal­
bearing
wastewater
to
break
down
the
metal
chelates
before
commingling
it
with
other
metal­
bearing
wastewaters.
Preliminary
treatment
may
consist
of
chemical
reduction
using
reducing
agents
such
as
sodium
borohydride,
hydrazine,
dithiocarbamate
(
measured
analytically
as
ziram)
or
sodium
hydrosulfite;
high
pH
precipitation
using
calcium
hydroxide
or
ferrous
sulfate;
or
filtering
the
chelated
metals
out
of
solution
(
see
Section
8.4.4).

EPA
measured
copper
in
concentrations
ranging
from
570
to
700
mg/
L
in
the
influent
to
the
preliminary
treatment
systems
for
electroless
copper
processes.
EPA
measured
nickel
in
concentrations
ranging
from
0.149
to
480
mg/
L
in
the
influent
to
the
preliminary
treatment
systems
for
electroless
nickel
processes.
Copper
and
nickel
electroless
plating
are
the
most
prevalent
electroless
plating
operations
seen
at
facilities
performing
proposed
MP&
M
operations.

C.
5
Metal­
Bearing
Wastewater
All
of
the
wastewaters
generated
in
proposed
MP&
M
operations
can
contain
metals,
including
the
wastewaters
described
in
the
previous
subsections.
Section
C.
5.1
discusses
proposed
MP&
M
operations
not
presented
in
the
previous
subsections
that
generate
metal­
bearing
wastewater
and
presents
pollutant
concentration
data
for
the
process
water
and
rinse
water
for
those
operations.

C­
6
Appendix
C
­
Wastewater
Characteristics
Section
C.
5.2
presents
pollutant
concentration
data
for
the
influent
to
chemical
precipitation
systems
used
to
treat
metal­
bearing
wastewater.

C.
5.1
Process
Water
and
Rinse
Water
Table
C­
7
lists
the
proposed
MP&
M
operations
that
generate
metal­
bearing
wastewater
and
presents
the
number
of
samples
of
process
water
and
rinse
water
collected
and
analyzed
in
EPA s
sampling
program
for
each
unit
operation.

Facilities
performing
proposed
MP&
M
operations
typically
use
metals
in
the
process
baths
for
unit
operations
such
as
electroplating
and
stripping.
Tables
C­
8
and
C­
9
summarize
the
pollutant
concentration
data
for
process
water
and
rinse
water,
respectively,
collected
during
the
MP&
M
sampling
program
for
unit
operations
generating
metal­
bearing
wastewater.
As
shown
in
the
tables,
the
metal
priority
pollutants
most
frequently
detected
in
samples
of
process
water
were
copper,
zinc,
chromium,
nickel,
and
lead.
Nonconventional
metal
pollutants
frequently
detected
include
iron,
magnesium,
boron,
barium,
manganese,
and
aluminum.
The
process
water
and
rinses
also
typically
contained
oil
and
grease,
total
suspended
solids,
and
low
concentrations
of
organic
pollutants.

C.
5.2
Influent
to
the
Chemical
Precipitation
Treatment
Systems
Typically,
facilities
performing
proposed
MP&
M
operations
segregate
their
wastewaters
by
type
and
treat
them
in
preliminary
treatment
systems.
After
preliminary
treatment,
facilities
performing
proposed
MP&
M
operations
usually
commingle
the
wastewater
with
other
process
wastewater
and
treat
the
commingled
wastewater
in
an
end­
of­
pipe
treatment
system.
Generally,
the
end­
of­
pipe
treatment
consists
of
chemical
precipitation
and
sedimentation
(
see
Section
8.5.1).
When
high
concentrations
of
metals
are
present
in
the
wastewater,
sites
may
use
preliminary
batch
chemical
precipitation
and
sedimentation
to
ensure
that
the
high
concentrations
do
not
cause
an
upset
in
the
end­
of­
pipe
treatment
system.
Facilities
performing
proposed
MP&
M
operations
may
also
contract
haul
concentrated
baths
to
centralized
waste
treatment
facilities.
Table
C­
10
summarizes
the
pollutant
concentration
data
obtained
from
sampling
the
influent
to
end­
of­
pipe
chemical
precipitation
with
sedimentation
and
chemical
precipitation
with
membrane
filtration
systems
for
metal­
bearing
wastewater.

C­
7
Appendix
C
­
Wastewater
Characteristics
Table
C­
7
Number
of
Process
Water
and
Rinse
Water
Samples
Collected
and
Analyzed
for
Unit
Operations
That
Generate
Metal­
Bearing
Wastewater
Unit
Operation
No.
of
Process
Water
Samples
a
No.
of
Rinse
Water
Samples
a
Abrasive
Jet
Machining
Acid
Treatment
without
Chromium
Anodizing
without
Chromium
Carbon
Black
Deposition
Chemical
Milling
Chemical
Conversion
Coating
without
Chromium
Electrochemical
Machining
Electroless
Plating
Electrolytic
Cleaning
Electroplating
without
Chromium
or
Cyanide
Electropolishing
Painting­
immersion
(
Including
Electrophoretic,
"
E­
coat")

Photo
Image
Developing
Photoresist
Applications
Plasma
Arc
Machining
Salt
Bath
Descaling
Solder
Flux
Cleaning
Solder
Fusing
Stripping
(
paint)

Stripping
(
metallic
coating)
3
27
4
2
4
24
1
9
9
24
1
1
5
0
1
0
1
0
6
9
3
65
3
3
9
59
2
28
17
48
1
6
11
0
0
4
4
3
4
12
Source:
MP&
M
Sampling
Program.
a
Unit
operations
for
which
no
samples
were
collected
are
rarely
performed
or
were
not
observed
at
facilities
performing
proposed
MP&
M
operations.

C­
8
Appendix
C
­
Wastewater
Characteristics
Table
C­
8
Process
Water
Pollutant
Concentration
Data
for
Unit
Operations
That
Generate
Metal­
Bearing
Wastewater
Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
1,1­
Dichloroethane
41
0
NA
NA
NA
NA
1,1­
Dichloroethene
41
0
NA
NA
NA
NA
1,1,1­
Trichloroethane
41
0
NA
NA
NA
NA
2­
Nitrophenol
40
1
2.15
2.15
2.15
2.15
2,4­
Dinitrophenol
36
1
335
335
335
335
2,4­
Dimethylphenol
40
1
0.167
0.167
0.167
0.167
2,6­
Dinitrotoluene
41
2
0.605
6.98
3.79
3.79
4­
Chloro­
3­
Methylphenol
39
0
NA
NA
NA
NA
4­
Nitrophenol
39
1
14.1
14.1
14.1
14.1
Acenaphthene
41
0
NA
NA
NA
NA
Acrolein
40
1
0.591
0.591
0.591
0.591
Anthracene
41
0
NA
NA
NA
NA
Bis(
2­
ethylhexyl)
Phthalate
41
12
0.012
18.2
3.10
0.291
Butyl
Benzyl
Phthalate
41
0
NA
NA
NA
NA
Chlorobenzene
41
4
0.011
1.56
0.414
0.041
Chloroethane
41
0
NA
NA
NA
NA
Chloroform
41
3
0.012
0.218
0.080
0.012
Di­
n­
octyl
Phthalate
41
2
0.639
1.42
1.03
1.03
Di­
n­
butyl
Phthalate
41
0
NA
NA
NA
NA
Dimethyl
Phthalate
41
0
NA
NA
NA
NA
Ethylbenzene
41
2
0.020
2.91
1.46
1.46
Fluoranthene
41
0
NA
NA
NA
NA
Fluorene
41
0
NA
NA
NA
NA
Isophorone
41
0
NA
NA
NA
NA
Methylene
Chloride
41
3
0.011
0.173
0.080
0.056
N­
Nitrosodimethylamine
41
1
6.67
6.67
6.67
6.67
N­
Nitrosodiphenylamine
41
0
NA
NA
NA
NA
C­
9
Appendix
C
­
Wastewater
Characteristics
Table
C­
8
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
(
continued)

Naphthalene
41
2
0.024
0.208
0.116
0.116
Phenanthrene
41
0
NA
NA
NA
NA
Phenol
41
5
0.024
1,044
216
2.00
Pyrene
41
0
NA
NA
NA
NA
Tetrachloroethene
41
0
NA
NA
NA
NA
Toluene
41
2
0.014
0.032
0.023
0.023
Trichloroethene
41
6
0.010
0.058
0.026
0.023
Metal
Priority
Pollutants
Antimony
129
50
0.002
3.56
0.359
0.090
Arsenic
129
62
0.001
16.4
0.655
0.080
Beryllium
129
39
0.001
3.87
0.270
0.030
Cadmium
132
74
0.002
57,100
791
0.203
Chromium
132
115
0.007
108,000
1,952
1.87
Copper
132
124
0.009
141,000
2,885
7.24
Lead
132
83
0.002
4,880
120
2.62
Mercury
129
25
0.0003
0.032
0.003
0.0009
Nickel
131
109
0.007
84,623
3,091
5.89
Selenium
129
30
0.001
8.00
0.659
0.051
Silver
132
57
0.001
14.4
0.503
0.075
Thallium
129
18
0.001
3.48
0.411
0.019
Zinc
131
118
0.005
53,200
2,750
15.7
Conventional
Pollutants
BOD
5­
Day
(
Carbonaceous)
33
22
4.29
18,600
4,537
1,600
Oil
and
Grease
(
as
HEM)
53
27
1.08
2,400
271
68.9
Total
Suspended
Solids
127
119
5.00
110,000
2,338
154
Nonconventional
Organic
Pollutants
1­
Bromo­
2­
Chlorobenzene
41
4
0.012
0.978
0.382
0.268
1­
Bromo­
3­
Chlorobenzene
41
4
0.031
0.490
0.193
0.126
1­
Methylfluorene
41
0
NA
NA
NA
NA
1­
Methylphenanthrene
41
0
NA
NA
NA
NA
1,4­
Dioxane
41
3
0.365
2.80
1.36
0.920
C­
10
Appendix
C
­
Wastewater
Characteristics
Table
C­
8
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

2­
Butanone
40
12
0.070
26.1
4.61
1.43
2­
Hexanone
41
1
5.02
5.02
5.02
5.02
2­
Isopropylnaphthalene
41
0
NA
NA
NA
NA
2­
Methylnaphthalene
41
1
0.220
0.220
0.220
0.220
2­
Propanone
41
27
0.052
250
11.3
0.485
3,6­
Dimethylphenanthrene
41
0
NA
NA
NA
NA
4­
Methyl­
2­
Pentanone
41
5
0.052
159
32.0
0.187
Acetophenone
41
0
NA
NA
NA
NA
Alpha­
terpineol
41
0
NA
NA
NA
NA
Aniline
41
4
0.015
0.335
0.145
0.115
Benzoic
Acid
41
8
0.051
8,098
1,037
27.2
Benzyl
Alcohol
41
4
0.012
0.278
0.103
0.061
Biphenyl
41
0
NA
NA
NA
NA
Carbon
Disulfide
41
1
0.053
0.053
0.053
0.053
Dibenzofuran
41
1
0.140
0.140
0.140
0.140
Dibenzothiophene
41
0
NA
NA
NA
NA
Diphenyl
Ether
41
0
NA
NA
NA
NA
Diphenylamine
41
0
NA
NA
NA
NA
Hexanoic
Acid
41
5
0.012
31.5
9.12
0.763
Isobutyl
Alcohol
41
0
NA
NA
NA
NA
m­
Xylene
14
2
0.020
5.06
2.54
2.54
m+
p
Xylene
27
0
NA
NA
NA
NA
Methyl
Methacrylate
41
4
0.181
0.797
0.586
0.682
n­
Decane
41
1
3.51
3.51
3.51
3.51
n­
Docosane
41
1
0.142
0.142
0.142
0.142
n­
Dodecane
41
1
1.27
1.27
1.27
1.27
n­
Eicosane
41
1
0.030
0.030
0.030
0.030
n­
Hexacosane
41
1
0.106
0.106
0.106
0.106
n­
Hexadecane
41
0
NA
NA
NA
NA
n­
Nitrosopiperidine
41
0
NA
NA
NA
NA
n­
Octacosane
41
1
0.071
0.071
0.071
0.071
C­
11
Appendix
C
­
Wastewater
Characteristics
Table
C­
8
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

n­
Octadecane
41
0
NA
NA
NA
NA
n­
Tetracosane
41
1
0.097
0.097
0.097
0.097
n­
Tetradecane
41
0
NA
NA
NA
NA
n­
Triacontane
41
1
0.082
0.082
0.082
0.082
n,
n­
Dimethylformamide
41
3
0.032
0.123
0.064
0.036
o­
cresol
41
2
0.023
0.195
0.109
0.109
o­
xylene
27
0
NA
NA
NA
NA
o+
p
Xylene
14
2
0.910
2.01
1.46
1.46
p­
Cymene
41
0
NA
NA
NA
NA
p­
Cresol
41
3
0.011
0.513
0.192
0.054
Pyridine
41
0
NA
NA
NA
NA
Styrene
41
0
NA
NA
NA
NA
Trichlorofluoromethane
41
0
NA
NA
NA
NA
Tripropyleneglycol
Methyl
Ether
41
2
0.245
1.45
0.848
0.848
Nonconventional
Metal
Pollutants
Aluminum
131
107
0.042
34,900
1,112
3.39
Barium
129
102
0.001
259
4.24
0.096
Boron
130
106
0.022
17,800
659
1.32
Calcium
129
125
0.054
2,250
130
23.4
Cobalt
129
81
0.003
4,700
73.5
0.660
Gold
1
1
0.392
0.392
0.392
0.392
Iron
131
122
0.011
374,000
7,051
13.4
Magnesium
129
106
0.085
960
73.8
15.2
Manganese
132
110
0.001
4,790
106
0.767
Molybdenum
130
87
0.001
197
5.40
0.237
Sodium
129
125
1.25
383,000
17,905
1,164
Tin
132
82
0.004
22,670
930
0.984
Titanium
129
84
0.002
13,250
180
0.303
Vanadium
129
68
0.001
1,495
23.5
0.066
Yttrium
129
24
0.001
0.900
0.115
0.038
C­
12
Appendix
C
­
Wastewater
Characteristics
Table
C­
8
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Other
Nonconventional
Pollutants
Ammonia
as
Nitrogen
66
53
0.060
44,800
2,922
10.0
Chemical
Oxygen
Demand
(
COD)
60
56
83.0
600,000
32,426
7,400
Chloride
69
53
1.00
328,300
20,901
240
Cyanide
10
7
0.027
0.510
0.153
0.120
Fluoride
69
58
0.140
55,500
1,034
5.10
Hexavalent
Chromium
36
5
0.008
0.430
0.104
0.025
Sulfate
105
89
1.56
755,000
36,919
808
Total
Dissolved
Solids
125
123
87.0
1,000,000
135,033
64,100
Total
Kjeldahl
Nitrogen
49
42
0.480
40,000
2,584
42.0
Total
Organic
Carbon
(
TOC)
49
48
4.71
54,000
7,492
1,245
Total
Petroleum
Hydrocarbons
(
as
SGT­
HEM)
51
9
6.00
352
88.2
14.1
Total
Phosphorus
30
21
0.020
11,000
945
11.0
Total
Recoverable
Phenolics
52
35
0.006
135
7.78
0.330
Total
Sulfide
17
0
NA
NA
NA
NA
Source:
MP&
M
Sampling
Program.
a
Due
to
budgetary
constraints,
EPA
did
not
analyze
all
samples
for
all
pollutants.
NA
­
Not
applicable.

C­
13
Appendix
C
­
Wastewater
Characteristics
Table
C­
9
Rinse
Water
Pollutant
Concentration
Data
for
Unit
Operations
That
Generate
Metal­
Bearing
Wastewater
Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
1,1­
Dichloroethane
91
0
NA
NA
NA
NA
1,1­
Dichloroethene
91
0
NA
NA
NA
NA
1,1,1­
Trichloroethane
91
0
NA
NA
NA
NA
2­
Nitrophenol
89
0
NA
NA
NA
NA
2,4­
Dimethylphenol
91
0
NA
NA
NA
NA
2,4­
Dinitrophenol
85
0
NA
NA
NA
NA
2,6­
Dinitrotoluene
91
0
NA
NA
NA
NA
4­
Chloro­
3­
Methylphenol
91
0
NA
NA
NA
NA
4­
Nitrophenol
88
0
NA
NA
NA
NA
Acenaphthene
91
0
NA
NA
NA
NA
Acrolein
87
0
NA
NA
NA
NA
Anthracene
91
0
NA
NA
NA
NA
Bis(
2­
ethylhexyl)
Phthalate
91
10
0.011
0.281
0.064
0.019
Butyl
Benzyl
Phthalate
91
0
NA
NA
NA
NA
Chlorobenzene
91
0
NA
NA
NA
NA
Chloroethane
91
0
NA
NA
NA
NA
Chloroform
91
49
0.010
0.063
0.025
0.022
Di­
n­
octyl
Phthalate
91
1
0.013
0.013
0.013
0.088
Di­
n­
butyl
Phthalate
91
6
0.014
0.190
0.098
0.013
Dimethyl
Phthalate
91
1
0.021
0.021
0.021
0.021
Ethylbenzene
91
2
0.021
0.028
0.024
0.024
Fluoranthene
91
0
NA
NA
NA
NA
Fluorene
91
0
NA
NA
NA
NA
Isophorone
91
0
NA
NA
NA
NA
Methylene
Chloride
91
1
0.011
0.011
0.011
0.011
n­
Nitrosodiphenylamine
91
0
NA
NA
NA
NA
n­
Nitrosodimethylamine
91
0
NA
NA
NA
NA
Naphthalene
91
1
0.021
0.021
0.021
0.021
C­
14
Appendix
C
­
Wastewater
Characteristics
Table
C­
9
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
(
continued)

Phenanthrene
91
0
NA
NA
NA
NA
Phenol
90
5
0.011
2.00
0.417
0.024
Pyrene
91
0
NA
NA
NA
NA
Tetrachloroethene
91
0
NA
NA
NA
NA
Toluene
91
0
NA
NA
NA
NA
Trichloroethene
91
3
0.010
0.018
0.015
0.015
Metal
Priority
Pollutants
Antimony
261
42
0.002
0.158
0.026
0.011
Arsenic
261
63
0.001
0.308
0.018
0.006
Beryllium
261
13
0.001
0.059
0.010
0.001
Cadmium
265
62
0.002
6.93
0.310
0.011
Chromium
265
155
0.002
21.6
0.761
0.052
Copper
265
235
0.003
507
14.0
0.154
Lead
265
90
0.002
81.0
3.52
0.066
Mercury
261
25
0.0002
0.004
0.001
0.0004
Nickel
263
172
0.002
437
20.0
0.115
Selenium
261
39
0.001
0.412
0.019
0.003
Silver
265
55
0.001
0.962
0.047
0.010
Thallium
261
19
0.001
0.039
0.006
0.001
Zinc
265
187
0.002
13,700
168
0.019
Conventional
Pollutants
BOD
5­
Day
(
Carbonaceous)
86
39
1.07
11,400
505
40.0
Oil
and
Grease
(
as
HEM)
130
34
1.12
114
17.2
10.4
Total
Suspended
Solids
260
174
2.00
6,920
132
20.0
Nonconventional
Organic
Pollutants
1­
Bromo­
2­
Chlorobenzene
91
0
NA
NA
NA
NA
1­
Bromo­
3­
Chlorobenzene
91
0
NA
NA
NA
NA
1­
Methylfluorene
91
0
NA
NA
NA
NA
1­
Methylphenanthrene
91
0
NA
NA
NA
NA
1,4­
Dioxane
91
1
0.196
0.196
0.196
0.196
2­
Butanone
89
10
0.066
0.550
0.214
0.133
C­
15
Appendix
C
­
Wastewater
Characteristics
Table
C­
9
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

2­
Hexanone
91
0
NA
NA
NA
NA
2­
Isopropylnaphthalene
91
0
NA
NA
NA
NA
2­
Methylnaphthalene
91
0
NA
NA
NA
NA
2­
Propanone
91
13
0.052
11.5
1.51
0.097
3,6­
Dimethylphenanthrene
91
0
NA
NA
NA
NA
4­
Methyl­
2­
Pentanone
91
2
0.190
17.4
8.80
8.80
Acetophenone
91
0
NA
NA
NA
NA
Alpha­
Terpineol
91
0
NA
NA
NA
NA
Aniline
91
0
NA
NA
NA
NA
Benzoic
Acid
91
6
0.108
4.31
1.21
0.659
Benzyl
Alcohol
91
2
0.014
0.014
0.014
0.014
Biphenyl
91
0
NA
NA
NA
NA
Carbon
Disulfide
91
0
NA
NA
NA
NA
Dibenzofuran
91
0
NA
NA
NA
NA
Dibenzothiophene
91
0
NA
NA
NA
NA
Diphenyl
Ether
91
1
0.013
0.013
0.013
0.013
Diphenylamine
91
0
NA
NA
NA
NA
Hexanoic
Acid
91
1
0.015
0.015
0.015
0.015
Isobutyl
Alcohol
91
0
NA
NA
NA
NA
m­
Xylene
20
2
0.036
0.076
0.056
0.056
m+
p
Xylene
71
0
NA
NA
NA
NA
Methyl
Methacrylate
91
0
NA
NA
NA
NA
n­
Decane
91
0
NA
NA
NA
NA
n­
Docosane
91
1
0.012
0.012
0.012
0.012
n­
Dodecane
91
0
NA
NA
NA
NA
n­
Eicosane
91
0
NA
NA
NA
NA
n­
Hexacosane
91
2
0.037
0.434
0.236
0.236
n­
Hexadecane
91
1
0.057
0.057
0.057
0.057
n­
Nitrosopiperidine
91
0
NA
NA
NA
NA
n­
Octacosane
91
1
0.041
0.041
0.041
0.041
n­
Octadecane
91
0
NA
NA
NA
NA
C­
16
Appendix
C
­
Wastewater
Characteristics
Table
C­
9
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

n­
Tetracosane
91
1
0.018
0.018
0.018
0.018
n­
Tetradecane
91
1
0.221
0.221
0.221
0.221
n­
Triacontane
91
2
0.030
0.477
0.253
0.253
n,
n­
dimethylformamide
91
2
0.026
0.115
0.071
0.071
o­
Cresol
91
0
NA
NA
NA
NA
o­
Xylene
71
0
NA
NA
NA
NA
o+
p
Xylene
20
2
0.042
0.113
0.077
0.077
p­
Cymene
91
0
NA
NA
NA
NA
p­
Cresol
91
0
NA
NA
NA
NA
Pyridine
91
0
NA
NA
NA
NA
Styrene
91
0
NA
NA
NA
NA
Trichlorofluoromethane
91
0
NA
NA
NA
NA
Tripropyleneglycol
Methyl
Ether
91
1
8.48
8.48
8.48
8.48
Nonconventional
Metal
Pollutants
Aluminum
263
161
0.022
76.9
1.61
0.192
Barium
261
207
0.001
2.90
0.064
0.028
Boron
263
179
0.016
363
4.38
0.180
Calcium
261
255
0.033
361
30.7
23.0
Cobalt
261
58
0.001
12.4
0.945
0.014
Gold
2
1
6.88
6.88
6.88
6.88
Iron
263
196
0.003
2,810
58.8
0.334
Magnesium
261
240
0.067
130
9.22
7.56
Manganese
265
171
0.001
68.3
1.52
0.024
Molybdenum
263
80
0.002
13.4
0.341
0.017
Sodium
261
257
0.277
55,800
710
60.0
Tin
265
105
0.002
828
11.6
0.052
Titanium
261
80
0.001
18.1
0.762
0.015
Vanadium
261
35
0.001
1.10
0.108
0.010
Yttrium
261
8
0.001
0.004
0.002
0.001
C­
17
Appendix
C
­
Wastewater
Characteristics
Table
C­
9
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Other
Nonconventional
Pollutants
Amenable
Cyanide
3
3
0.340
1.97
1.05
0.830
Ammonia
as
Nitrogen
114
68
0.050
1,190
91.2
1.58
Chemical
Oxygen
Demand
(
COD)
107
84
5.20
20,400
614
44.0
Chloride
77
76
1.20
5,000
219
26.0
Cyanide
12
9
0.028
87.0
10.7
0.830
Fluoride
77
68
0.110
60.0
3.65
0.990
Hexavalent
Chromium
90
17
0.011
0.063
0.023
0.019
Sulfate
163
158
1.64
7,120
306
54.0
Total
Dissolved
Solids
258
258
10.0
132,000
2,469
550
Total
Kjeldahl
Nitrogen
79
44
0.100
395
28.0
8.69
Total
Organic
Carbon
(
TOC)
129
114
1.16
6,110
230
12.0
Total
Petroleum
Hydrocarbons
(
as
SGT­
HEM)
129
7
5.25
13.0
7.86
7.75
Total
Phosphorus
28
21
0.026
290
30.9
1.40
Total
Recoverable
Phenolics
100
42
0.005
2.85
0.192
0.013
Total
Sulfide
45
0
NA
NA
NA
NA
Source:
MP&
M
Sampling
Data.
a
Due
to
budgetary
constraints,
EPA
did
not
analyze
all
samples
for
all
pollutants.
NA
­
Not
applicable.

C­
18
Appendix
C
­
Wastewater
Characteristics
Table
C­
10
Pollutant
Concentration
Data
for
the
Influent
to
Chemical
Precipitation
Systems
Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
1,1­
Dichloroethane
171
0
NA
NA
NA
NA
1,1­
Dichloroethylene
171
2
0.011
0.748
0.379
0.379
1,1,1­
Trichloroethane
171
6
0.019
0.084
0.053
0.053
2,4­
Dimethylphenol
162
0
NA
NA
NA
NA
2,4­
Dinitrophenol
167
2
0.111
1.66
0.885
0.885
2,6­
Dinitrotoluene
178
0
NA
NA
NA
NA
2­
Nitrophenol
177
0
NA
NA
NA
NA
4­
Chloro­
m­
Cresol
176
9
0.011
1.14
0.183
0.076
4­
Nitrophenol
172
0
NA
NA
NA
NA
Acenaphthene
178
0
NA
NA
NA
NA
Acrolein
141
0
NA
NA
NA
NA
Anthracene
178
1
0.104
0.104
0.104
0.104
Benzyl
Butyl
Phthalate
178
2
0.009
0.010
0.009
0.009
Bis(
2­
ethylhexyl)
Phthalate
178
43
0.008
0.298
0.052
0.030
Chlorobenzene
171
0
NA
NA
NA
NA
Chloroethane
171
0
NA
NA
NA
NA
Chloroform
171
68
0.010
0.824
0.097
0.031
Di­
n­
butyl
Phthalate
178
6
0.007
0.066
0.030
0.018
Di­
n­
octyl
Phthalate
178
1
0.012
0.012
0.012
0.012
Dimethyl
Phthalate
175
1
0.0004
0.0004
0.0004
0.0004
Ethylbenzene
171
5
0.006
0.335
0.074
0.010
Fluoranthene
178
0
NA
NA
NA
NA
Fluorene
178
1
0.045
0.045
0.045
0.045
Isophorone
175
0
NA
NA
NA
NA
Methylene
Chloride
171
10
0.008
0.172
0.043
0.023
n­
Nitrosodimethylamine
175
2
0.065
0.070
0.067
0.067
n­
Nitrosodiphenylamine
174
0
NA
NA
NA
NA
C­
19
Appendix
C
­
Wastewater
Characteristics
Table
C­
10
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Organic
Priority
Pollutants
(
continued)

Naphthalene
178
3
0.012
0.054
0.035
0.038
Phenanthrene
178
3
0.041
0.112
0.071
0.060
Phenol
179
34
0.010
0.634
0.070
0.030
Pyrene
178
0
NA
NA
NA
NA
Tetrachloroethene
171
8
0.015
1.11
0.306
0.081
Toluene
171
6
0.009
2.77
0.534
0.019
Trichloroethylene
171
3
0.019
0.023
0.021
0.021
Metal
Priority
Pollutants
Antimony
261
86
0.002
1.13
0.058
0.018
Arsenic
268
109
0.001
0.530
0.025
0.009
Beryllium
268
64
0.0002
3.23
0.228
0.004
Cadmium
457
170
0.0003
323
4.25
0.039
Chromium
469
444
0.001
1,350
9.92
0.676
Copper
472
467
0.010
665
13.9
0.480
Lead
465
376
0.002
159
3.44
0.416
Mercury
266
52
0.00003
0.012
0.001
0.0003
Nickel
467
457
0.012
2,101
18.3
1.47
Selenium
265
42
0.001
0.090
0.018
0.006
Silver
460
222
0.001
4.94
0.406
0.036
Thallium
265
26
0.001
0.112
0.011
0.002
Zinc
472
459
0.009
636
33.6
3.65
Conventional
Pollutants
BOD
5­
Day
(
Carbonaceous)
133
86
2.40
609
64.4
26.0
Oil
and
Grease
(
as
HEM)
236
159
0.570
32,000
428
12.1
Total
Suspended
Solids
334
314
4.00
11,400
803
120
Nonconventional
Organic
Pollutants
1,4­
Dioxane
166
6
0.033
2.41
0.788
0.584
1­
Bromo­
2­
Chlorobenzene
169
2
0.011
0.012
0.012
0.012
1­
Bromo­
3­
Chlorobenzene
169
5
0.026
0.067
0.045
0.038
1­
Methylfluorene
169
2
0.111
0.189
0.150
0.150
1­
Methylphenanthrene
169
2
0.092
0.181
0.136
0.136
C­
20
Appendix
C
­
Wastewater
Characteristics
Table
C­
10
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

2­
Butanone
166
13
0.056
2.45
0.668
0.151
2­
Hexanone
166
0
NA
NA
NA
NA
2­
Isopropylnaphthalene
169
0
NA
NA
NA
NA
2­
Methylnaphthalene
173
2
0.076
0.205
0.140
0.140
2­
Propanone
166
87
0.051
16.7
0.822
0.137
3,6­
Dimethylphenanthrene
169
2
0.019
0.062
0.041
0.041
4­
Methyl­
2­
Pentanone
166
10
0.120
1.36
0.308
0.181
Acetophenone
169
2
0.010
0.011
0.011
0.011
Alpha­
terpineol
162
5
0.013
0.087
0.051
0.054
Aniline
173
6
0.013
0.052
0.023
0.017
Benzoic
Acid
173
69
0.011
34.8
3.27
0.229
Benzyl
Alcohol
173
9
0.005
0.080
0.028
0.013
Biphenyl
169
1
0.011
0.011
0.011
0.011
Carbon
Disulfide
166
10
0.016
3.92
0.505
0.058
Dibenzofuran
173
0
NA
NA
NA
NA
Dibenzothiophene
169
2
0.015
0.025
0.020
0.020
Diphenyl
Ether
169
0
NA
NA
NA
NA
Diphenylamine
165
1
0.033
0.033
0.033
0.033
Hexanoic
Acid
169
23
0.010
0.461
0.053
0.017
Isobutyl
Alcohol
166
0
NA
NA
NA
NA
m+
p
Xylene
96
0
NA
NA
NA
NA
m­
Xylene
70
1
0.016
0.016
0.016
0.016
Methyl
Methacrylate
166
3
0.019
0.039
0.030
0.032
n­
Decane
166
3
0.029
0.031
0.031
0.031
n­
Docosane
169
6
0.011
0.026
0.016
0.013
n­
Dodecane
168
6
0.044
0.772
0.269
0.101
n­
Eicosane
169
17
0.010
0.181
0.034
0.020
n­
Hexacosane
169
12
0.012
0.041
0.027
0.028
n­
Hexadecane
169
22
0.010
0.631
0.085
0.026
n­
Nitrosopiperidine
169
0
NA
NA
NA
NA
n­
octacosane
169
3
0.018
0.036
0.030
0.035
C­
21
Appendix
C
­
Wastewater
Characteristics
Table
C­
10
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Nonconventional
Organic
Pollutants
(
continued)

n­
Octadecane
169
25
0.011
0.493
0.072
0.024
n­
Tetracosane
169
7
0.012
0.032
0.019
0.017
n­
Tetradecane
169
14
0.016
1.01
0.174
0.058
n­
Triacontane
169
4
0.011
0.031
0.019
0.017
n,
n­
Dimethylformamide
169
22
0.011
0.581
0.094
0.044
o+
p
Xylene
70
3
0.013
0.023
0.017
0.014
o­
Cresol
169
0
NA
NA
NA
NA
o­
Xylene
96
0
NA
NA
NA
NA
p­
Cresol
169
10
0.013
0.030
0.019
0.017
p­
Cymene
169
3
0.015
0.054
0.030
0.02
Pyridine
169
0
NA
NA
NA
NA
Styrene
173
8
0.010
0.188
0.041
0.022
Trichlorofluoromethane
171
6
0.029
0.109
0.045
0.033
Tripropyleneglycol
Methyl
Ether
169
23
0.064
5.21
1.83
1.05
Nonconventional
Metal
Pollutants
Aluminum
268
246
0.055
132
8.68
2.38
Barium
266
241
0.003
9.91
0.251
0.058
Boron
253
232
0.057
81.3
3.53
0.787
Calcium
268
268
3.40
1,220
83.0
34.9
Cobalt
264
121
0.001
25.8
0.757
0.019
Gold
20
10
0.013
0.150
0.056
0.038
Iron
268
268
0.022
3,880
111
5.38
Magnesium
268
263
0.349
3,360
74.5
8.88
Manganese
453
452
0.001
109
4.04
0.870
Molybdenum
453
347
0.001
3.06
0.175
0.037
Sodium
268
268
17.7
9,600
460
211
Tin
442
341
0.004
1,440
14.2
0.199
Titanium
253
189
0.002
76.4
1.53
0.048
Vanadium
264
87
0.002
1.19
0.052
0.014
Yttrium
253
60
0.001
0.085
0.010
0.004
C­
22
Appendix
C
­
Wastewater
Characteristics
Table
C­
10
(
Continued)

Pollutant
No.
of
Samples
Analyzeda
No.
of
Detects
Concentration
(
mg/
L)

Minimum
Maximum
Mean
Median
Other
Nonconventional
Pollutants
Ammonia
as
Nitrogen
113
110
0.040
320
25.9
5.61
Chemical
Oxygen
Demand
(
COD)
203
194
1.50
13,000
532
122
Chloride
78
75
4.50
9,500
338
140
Cyanide
32
12
0.008
0.096
0.022
0.012
Fluoride
78
77
0.130
100
4.54
1.50
Hexavalent
Chromium
133
50
0.010
21.0
0.771
0.060
Sulfate
177
170
18.0
6,125
469
318
Total
Dissolved
Solids
263
263
19.0
34,000
2,325
1,103
Total
Kjeldahl
Nitrogen
83
80
0.110
160
14.9
6.66
Total
Organic
Carbon
(
TOC)
175
146
3.57
400
73.5
46.9
Total
Petroleum
Hydrocarbons
(
as
SGT­
HEM)
143
52
5.00
93.0
20.4
10.0
Total
Phosphorus
84
82
0.020
525
28.1
5.20
Total
Recoverable
Phenolics
188
110
0.006
13.0
0.387
0.047
Total
Sulfide
95
31
0.150
28.0
5.20
1.03
Ziram
5
3
0.177
0.448
0.291
0.247
Source:
MP&
M
Sampling
Program.
a
Due
to
budgetary
constraints,
EPA
did
not
analyze
all
samples
for
all
pollutants.
NA
­
Not
applicable.

C­
23
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Appendix
D
POLLUTION
PREVENTION
AND
WATER
CONSERVATION
PRACTICES
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Appendix
D
POLLUTION
PREVENTION
AND
WATER
CONSERVATION
PRACTICES
EPA
observed
a
number
of
pollution
prevention
and
water
conservation
practices
during
site
visits
and
sampling
episodes,
and
MP&
M
surveys
provided
additional
information
on
these
practices
(
see
Sections
3.0
and
8.0).
Some
common
pollution
prevention
and
water
conservation
methods
for
surface
treatment
include
drag­
out
tanks,
countercurrent
cascade
rinsing,
manual
and
automatic
rinse
water
shut­
off,
timed
rinses,
flow
restrictors,
conductivity
meters,
and
in­
process
ion
exchange
and
water
recycle.
In
this
appendix,
EPA
describes
some
of
these
common
pollution
prevention
and
water
conservation
methods
used
by
facilities
evaluated
for
the
final
rule
( 
MP&
M
facilities )
as
a
measure
to
assist
a
broader
audience
to
achieve
improved
environmental
performance
and
compliance,
pollution
prevention
through
source
reduction,
and
continual
improvement.
EPA
is
not
promulgating
or
requiring
any
of
these
methods
or
mass­
based
limitations
and
standards
in
the
MP&
M
effluent
guidelines
(
see
Section
15.0).
The
final
limitations
and
standards
in
the
MP&
M
effluent
guidelines
are
concentration
based
and
may
be
achieved
using
any
method
compliant
with
EPA
regulations.

Pollution
Prevention
and
Water
Conservation
Practices
for
Surface
Treatment
The
Agency
identified
four
categories
of
pollution
prevention
and
water
conservation
practices
and
technologies
that
can
be
applied
to
reduce
rinse­
water
use:
drag­
out
reduction
and/
or
drag­
out
recovery
methods;
improved
rinse
tank
design
and
rinsing
configurations;
rinse­
water
use
control
devices;
and,
metal
recovery
and
rinse­
water
reuse
technologies.
Surface
treatment
rinses
include
those
following
acid
and
alkaline
treatment,
anodizing,
electroplating,
electroless
plating,
and
chemical
conversion
coating.
Rinsing
dilutes
and
removes
the
chemical
film
of
drag­
out
remaining
on
parts
and
racks
after
processing
in
a
chemical
bath.
In
addition
to
conserving
water
use,
some
of
these
methods
(
especially
those
that
affect
drag­
out
and
recover
chemicals)
also
conserve
raw
materials,
reduce
pollutant
loadings
to
wastewater
treatment
systems,
and
reduce
treatment
reagent
requirements
and
sludge
production.
Within
each
of
these
categories
are
several
specific
practices
and
technologies.
Table
D­
1
presents
examples
of
these
practices
and
technologies,
as
well
as
their
applicability
to
the
MP&
M
operations.
1
Table
D­
2
provides
descriptions
of
these
practices.

1EPA
evaluated
a
number
of
unit
operations
for
the
May
1995
proposal,
January
2001
proposal,
and
June
2002
NODA
(
see
Tables
4­
3
and
4­
4).
However,
EPA
selected
a
subset
of
these
unit
operations
for
regulation
in
the
final
rule
(
see
Section
1.0).
For
this
Section,
the
term
 
proposed
MP&
M
operations 
means
those
operations
evaluated
for
the
two
proposals,
NODA,
and
final
rule.
The
term
 
final
MP&
M
operations 
means
those
operations
defined
as
 
oily
operations 
(
see
Section
1.0,
40
CFR
438.2(
f),
and
Appendix
B
to
Part
438)
and
regulated
by
the
final
rule.

D­
1
D.
1
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D­
2
Table
D­
1
Potential
Water
Conservation
Methods
for
Surface
Treatment
Rinses
Practice
Alkaline
Clean
Acid
Clean
Hexavalent
Chromium
Trivalent
Chromium
Cadmium
Zinc
Cyanide
Cadmium
Zinc
Non­

Cyanide
Acid
Copper
Copper
Cyanide
Watts,
Woods,

Other
Nickels
Electro
less
Nickel
Silver
Cyanide
Gold
Cyanide
Lead,
Lead­

Tin
Tin
Chrom
ate
Phos
phate
Chromic­
AcidAnodize
Sulfuric
Anodize
Drag­
out
Reduction
and
Recovery
Fog
or
spray
rinsing
over
tank
(
110
°
F
or
higher)
 
 
 
 
 
 
 
 
a
 
 
Controlled
slow
withdrawal
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Addition
of
wetting
agent
(
when
compatible)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Positioning
work
piece
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Long
drip
time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Drip
shield
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Air
knife
 
 
 
 
 
 
 
 
 
 
 
Drag­
out
tank
(
heated)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Drag­
in/
out
tank
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lowest
concentration
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Highest
temperature
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Rinse
Tank
Design
and
Innovative
Configuration
Countercurrent
rinse
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Cascading
rinse
(
cleaning)
 
 
Spray
rinse
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Good
tank
designb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Rinse
Water
Use
Control
Flow
restrictors
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Timer
controls
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Conductivity
controls
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
1
(
Continued)

Practice
Alkaline
Clean
Acid
Clean
Hexavalent
Chromium
Trivalent
Chromium
Cadmium
Zinc
Cyanide
Cadmium
Zinc
Non­

Cyanide
Acid
Copper
Copper
Cyanide
Watts,
Woods,

Other
Nickels
Electro
less
Nickel
Silver
Cyanide
Gold
Cyanide
Lead,
Lead­

Tin
Tin
Chrom
ate
Phos
phate
Chromic­
AcidAnodize
Sulfuric
Anodize
Metal
Recovery
and
Rinse
Water
Reuse
Technologies
Evaporatorc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Ion
exchangec
 
 
 
 
 
 
 
 
 
 
Electrolytic
Recovery
 
 
 
 
 
 
 
 
Electrodialysisc
 
 
 
 
Reverse
osmosisc
 
 
 
 
 
 
 
 
Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.

a
Alkaline
tin
only.

b
For
example,
air
or
other
agitation,
minimum
size,
and
inlet,
outlet
location
opposite
ends.

c
Only
common
applications
of
this
technology
are
checked.

D­
3
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
2
Descriptions
of
Pollution
Prevention
and
Water
Conservation
Practices
and
Technologies
Practice
or
Technology
Description
Air
Knife
Air
knives
are
usually
installed
over
a
process
tank
or
drip
shield
and
are
designed
to
remove
drag­
out
by
blowing
it
off
the
surface
of
parts
and
racks.
Drag­
out
is
routed
back
to
the
process
tank.
Air
knives
are
more
effective
with
flat
parts.
They
cannot
be
used
to
dry
surfaces
that
passivate
or
stain
due
to
oxidation.

Cascade
Rinsing
Cascade
rinsing
is
a
method
of
reusing
rinse
water.
Water
from
one
rinsing
operation
is
plumbed
to
another,
less
critical
one
before
being
discharged
to
treatment.
Some
rinse
waters
acquire
chemical
properties,
such
as
low
pH,
that
make
them
desirable
for
reuse
in
specific
rinse
systems.
This
is
generally
referred
to
as
reactive
rinsing.

Conductivity
Controller
Conductivity
probes
measure
the
conductivity
of
water
in
a
rinse
tank
to
regulate
the
flow
of
fresh
water
into
the
rinse
system.
Conductivity
controllers
consist
of
a
controller,
a
meter
with
adjustable
set
points,
a
probe
that
is
placed
in
the
rinse
tank,
and
a
solenoid
valve.
As
parts
are
rinsed,
dissolved
solids
are
added
to
the
water
in
the
rinse
tank,
raising
the
conductivity
of
the
water.
When
conductivity
reaches
the
set
point,
the
solenoid
valve
opens
to
allow
make­
up
water
to
enter
the
tank.
When
the
conductivity
falls
below
the
set
point,
the
valve
shuts
to
discontinue
the
make­
up
water.

In
theory,
conductivity
control
of
rinse
flow
is
a
precise
method
of
maintaining
optimum
rinsing
conditions
in
intermittently
used
rinse
operations.
In
practice,
conductivity
controllers
work
best
with
deionized
rinse
water.
Incoming
water
conductivity
may
vary
day
to
day
and
season
to
season,
which
forces
frequent
set­
point
adjustments.
Suspended
solids
and
nonionic
contaminants
(
e.
g.,
oil)
are
not
detected
by
the
conductivity
probe
and
can
cause
inadequate
rinsing.

Countercurrent
Cascade
Rinsing
Countercurrent
cascade
rinsing
refers
to
a
series
of
consecutive
rinse
tanks
that
are
plumbed
to
cause
water
to
flow
from
one
tank
to
another
in
the
direction
opposite
of
the
work
flow.
Countercurrent
cascade
rinsing
is
widely
used
to
reduce
the
discharge
rate
of
rinse
water.
Fresh
water
flows
into
the
rinse
tank
located
farthest
from
the
process
tank
and
overflows,
in
turn,
to
the
rinse
tanks
closer
to
the
process
tank.
This
technique
is
termed
countercurrent
rinsing,
because
the
part
and
the
rinse
water
move
in
opposite
directions.
Over
time,
the
first
rinse
becomes
contaminated
with
drag­
out
and
reaches
a
stable
concentration
that
is
lower
than
the
process
solution.
The
second
rinse
stabilizes
at
a
lower
concentration,
which
enables
less
rinse
water
to
be
used
than
if
only
one
rinse
tank
were
in
place.
The
more
countercurrent
cascade
rinse
tanks
(
three­
stage,
four­
stage,
etc.),
the
less
water
is
needed
to
adequately
remove
the
process
solution.

Drag­
in/
Drag­
out
Rinsing
A
drag­
in/
drag­
out
rinse
system
may
be
a
single
tank
or
two
tanks
plumbed
together.
Parts
enter
the
rinse
system
before
and
after
processing
in
the
bath.
As
parts
enter
the
process
bath,
they
drag
in
process
chemicals
present
in
the
drag­
in/
drag­
out
rinse
rather
than
plain
rinse
water.
This
rinsing
configuration
is
an
effective
recovery
method
for
process
baths
that
have
low
evaporation
rates.

D­
4
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
2
(
Continued)

Practice
or
Technology
Description
Drag­
out
Tank
Drag­
out
tanks
are
rinse
tanks
that
are
initially
filled
with
water
and
remain
stagnant.
Parts
are
rinsed
in
drag­
out
tanks
directly
after
exiting
the
process
bath.
Gradually,
the
concentration
of
process
chemicals
in
the
drag­
out
tank
rises.
In
the
most
efficient
configuration,
a
drag­
out
tank
is
used
after
a
heated
process
tank
that
has
a
moderate
to
high
evaporation
rate.
Part
of
the
fluid
in
the
drag­
out
tank
is
returned
to
the
process
tank
to
replace
the
evaporative
loss.
The
level
of
fluid
in
the
drag­
out
tank
is
maintained
by
adding
fresh
water.

Drip
Shields
Drip
shields
are
installed
between
process
tanks
and
rinse
tanks
to
recover
process
fluid
dripping
off
racks
and
barrels
that
would
otherwise
fall
into
rinse
tanks
or
onto
the
floor.
Often,
drip
shields
are
an
inclined
piece
of
polypropylene
or
other
material
that
is
inert
to
the
process.

Drip
Tanks
Drip
tanks
are
similar
to
drag­
out
tanks
except
they
are
not
filled
with
water.
Parts
exiting
a
process
bath
are
held
over
the
drip
tank
and
the
process
fluid
that
drips
from
the
parts
is
collected
in
the
tank.
When
enough
fluid
is
collected
in
the
drip
tank,
it
is
returned
to
the
process
tank.
Drip
tanks
are
generally
considered
to
be
a
less
effective
drag­
out
recovery
practice
than
using
drag­
out
tanks.

Electrodialysis
Electrodialysis
is
a
membrane
technology
used
to
remove
impurities
from
and
recover
process
solutions.
With
this
technology,
a
direct
current
is
applied
across
a
series
of
alternating
anion
and
cation
exchange
membranes
to
remove
dissolved
metal
salts
and
other
ionic
constituents
from
solutions.

An
electrodialysis
unit
consists
of
a
rectifier
and
a
membrane
stack.
The
stack
consists
of
alternating
anion­
and
cation­
specific
membranes
that
form
compartments.
As
the
feed
stream
enters
the
unit,
each
alternating
membrane
compartment
becomes
filled
with
either
dilute
or
concentrate.
When
the
compartments
are
filled,
a
direct
current
is
applied
across
the
membrane.
Cations
in
a
dilute
compartment
traverse
one
cation­
specific
membrane
in
the
direction
of
the
cathode,
and
are
trapped
in
that
compartment
by
the
next
membrane,
which
is
anion­
specific.
Anions
from
the
neighboring
dilute
compartment
traverse
the
anion­
specific
membrane
in
the
direction
of
the
anode,
joining
the
cations,
and
are
likewise
trapped
in
the
concentrate
compartment
by
the
next
cation­
specific
membrane.
In
this
way,
the
feed
stream
is
depleted
of
ions,
and
anions
and
cations
are
trapped
in
each
concentrate
compartment.

The
feed
stream
is
often
from
the
first
rinse
tank
in
a
countercurrent
series,
with
a
concentration
of
5
gallons
per
liter
(
g/
L)
or
more
of
total
dissolved
solids
(
TDS).
The
concentrate,
with
a
TDS
concentration
of
50
g/
L
or
more
and
a
volume
of
less
than
10%
of
the
feed
stream,
is
returned
to
the
process.
The
dilute,
representing
more
than
90%
of
the
feed
stream
at
a
TDS
concentration
of
typically
1
g/
L
or
less,
is
recycled
as
rinse
water
or
discharged
to
treatment.

D­
5
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
2
(
Continued)

Practice
or
Technology
Description
Electrolytic
Recovery
(
Electrowinning)
Electrolytic
recovery
is
an
electrochemical
process
used
to
recover
metals
from
many
types
of
process
solutions,
such
as
electroplating
rinse
waters
and
baths.
Electrolytic
recovery
removes
metal
ions
from
a
wastestream
by
processing
the
stream
in
an
electrolytic
cell,
which
consists
of
a
closely
spaced
anode
and
cathode.
Commercial
equipment
consists
of
several
cells,
a
transfer
pump,
and
a
rectifier.
Current
is
applied
across
the
cell
and
metal
cations
are
deposited
on
the
cathodes.
The
wastestream
is
usually
recirculated
through
the
cell
from
a
separate
tank,
such
as
a
drag­
out
recovery
rinse.

Electrolytic
recovery
is
typically
applied
to
solutions
containing
nickel,
copper,
precious
metals,
and
cadmium.
Chromium
and
aluminum
are
poor
candidates
for
electrolytic
recovery.
Drag­
out
recovery
rinses
and
ion­
exchange
regenerant
are
common
solutions
that
are
processed
using
electrolytic
recovery.
Some
solutions
require
pH
adjustment
prior
to
electrolytic
recovery.
Acidic,
metal­
rich,
cation
regenerant
is
an
excellent
candidate
stream
for
electrolytic
recovery,
and
is
often
electrolytically
recovered
without
adjustment.
In
some
cases,
when
the
target
concentration
is
reached,
the
wastestream
is
reused
as
cation
regenerant.

Evaporation
Evaporation
is
a
common
chemical
recovery
technology.
There
are
two
basic
types
of
evaporators:
atmospheric
and
vacuum.
Atmospheric
evaporators,
the
more
prevalent
type,
are
relatively
inexpensive
to
purchase
and
easy
to
operate.
Vacuum
evaporators
are
mechanically
more
sophisticated
and
are
more
energy­
efficient.
Vacuum
evaporators
are
typically
used
when
evaporation
rates
greater
than
50
to
70
gallons/
hour
are
required.
Additionally,
with
vacuum
evaporators,
evaporated
water
can
be
recovered
as
a
condensate
and
reused
on
site.

A
disadvantage
of
evaporation­
based
recovery
is
that
all
drag­
out,
including
unwanted
components,
are
returned
and
accumulate
in
the
process
bath.
For
this
reason,
deionized
water
is
preferred
as
rinse
water
to
prevent
the
introduction
of
water
contaminants
in
the
process
bath.

Flow
Restrictor
Flow
restrictors
prevent
the
flow
in
a
pipe
from
exceeding
a
predetermined
volume.
They
are
commonly
installed
on
a
rinse
tank s
water
inlet.
These
devices
contain
an
elastomer
washer
that
flexes
under
pressure
to
maintain
a
constant
water
flow
regardless
of
pressure.
Flow
restrictors
can
maintain
a
wide
range
of
flow
rates,
from
less
than
0.1
gal/
min
to
more
than
10
gal/
min.

As
a
stand­
alone
device,
a
flow
restrictor
provides
a
constant
water
flow.
As
such,
for
intermittent
rinsing
operations,
a
flow
restrictor
does
not
coordinate
the
rinse
flow
with
drag­
out
introduction.
Precise
control
with
intermittent
operations
typically
requires
a
combination
of
flow
restrictors
and
rinse
timers.
However,
for
continuous
rinsing
(
e.
g.,
continuous
electroplating
machines),
flow
restrictors
may
be
adequate
for
good
water
control.

Fog
or
Spray
Rinse
Over
Tank
Fog
or
spray
rinsing
is
performed
over
a
process
bath
to
recover
drag­
out.
Draining
over
a
process
bath
can
be
greatly
enhanced
by
spray
or
fog
rinsing,
which
dilutes
and
lowers
the
viscosity
of
the
film
of
process
fluid
clinging
to
the
parts.
This
method
of
drag­
out
recovery
is
only
possible
if
the
evaporation
rate
of
the
process
fluid
is
moderate
to
high.

D­
6
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
2
(
Continued)

Practice
or
Technology
Description
Good
Tank
Design
Rinse
tanks
should
be
designed
to
remove
the
drag­
out
layer
from
the
part
and
cause
it
to
rapidly
and
thoroughly
mix
with
the
rinse
water.
Common
elements
of
good
tank
design
are
positioning
the
inlet
and
outlet
at
opposite
ends
of
the
tank,
using
air
or
other
agitation,
using
a
flow
distributor,
and
using
the
minimum
size
tank
possible.

Ion
Exchange
Ion
exchange
is
a
reversible
chemical
reaction
that
exchanges
ions
in
a
feed
stream
for
ions
of
like
charge
on
the
surface
of
an
ion­
exchange
resin.
Resins
are
broadly
divided
into
cationic
or
anionic
types.
Typical
cation
resins
exchange
H+
for
other
cations,
while
anion
resins
exchange
OH
­
for
other
anions.

In
practice,
a
feed
stream
is
passed
through
a
vessel,
referred
to
as
a
column,
which
holds
the
resin.
The
feed
stream
is
typically
dilute
rinse
water.
The
exchange
process
proceeds
until
the
capacity
of
the
resin
is
reached
(
i.
e.,
an
exchange
has
occurred
at
all
the
resin
facilities).
A
regenerant
solution
is
then
passed
through
the
column.
For
cation
resins,
the
regenerant
is
an
acid,
and
the
H+
ions
replace
the
cations
captured
from
the
feed
stream.
For
anion
resins,
the
regenerant
is
a
base,
and
OH
­
ions
replace
the
anions
captured
from
the
feed
stream.
The
concentration
of
feed
stream
ions
is
much
higher
in
the
regenerant
than
in
the
feed
stream;
therefore,
the
ion­
exchange
process
accomplishes
both
separation
and
concentration.

Ion
exchange
is
used
for
water
recycling
and/
or
metal
recovery.
For
water
recycling,
cation
and
anion
columns
are
placed
in
series.
The
feed
stream
is
deionized
and
the
product
water
is
reused
for
rinsing.
Often,
closed­
loop
rinsing
is
achieved.
The
regenerant
from
the
cation
column
typically
contains
the
metal
species,
which
can
be
recovered
in
elemental
form
via
recovery.
The
anion
regenerant
is
typically
discharged
to
wastewater
treatment.
When
metal
recovery
is
the
only
objective,
a
single
or
double
cation
column
unit
containing
selective
resin
is
used.
These
resins
attract
divalent
cations
while
allowing
monovalent
cations
to
pass,
a
process
usually
referred
to
as
metal
scavenging.
Water
cannot
be
recycled
because
contaminants
other
than
the
target
cations
remain
in
the
stream
exiting
the
column.

Long
Drip
Time
Long
drip
times
over
the
process
tank
reduce
the
volume
of
drag­
out
reaching
the
rinsing
system.
Automatic
lines
can
be
easily
programmed
to
include
optimum
drip
times.
On
manual
lines,
racks
are
commonly
hung
on
bars
over
process
baths
and
allowed
to
drip.
Barrels
can
be
rotated
over
the
process
bath
to
enhance
drainage.
Some
surfaces
cannot
tolerate
long
exposure
to
air
due
to
oxidation
or
staining,
and
would
therefore
be
unsuitable
for
extended
drip
times.

Raising
Bath
Temperature
Bath
temperature
and
viscosity
are
inversely
related.
Operating
at
the
highest
possible
bath
temperature
lowers
viscosity
and
reduces
drag­
out.
Higher
bath
temperatures
also
increase
evaporation,
which
facilitates
efficient
recovery
rinsing.

Lowering
Bath
Concentration
Operating
at
the
lowest
possible
concentration
reduces
the
mass
of
chemicals
in
a
given
volume
of
drag­
out.
Also,
viscosity
and
concentration
are
directly
related
and
lower
process
bath
concentration
lowers
viscosity
and
reduces
drag­
out
volume.
Contaminants
and
other
substances
that
build
in
concentration
over
the
life
of
a
process
bath
should
be
controlled
at
a
low
level,
if
possible.

Part
Position
on
Rack
Positioning
parts
on
racks
to
promote
rapid
draining
includes
minimizing
the
profile
of
the
parts
emerging
from
the
bath,
tilting
and
inverting
cup­
shaped
parts,
and
avoiding
placement
of
parts
directly
atop
one
another.

D­
7
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
2
(
Continued)

Practice
or
Technology
Description
Slow
Part
Withdrawal
The
faster
a
part
is
removed
from
a
process
bath,
the
thicker
the
layer
of
fluid
clinging
to
the
part
will
be.
A
slower
withdrawal
rate
reduces
the
thickness
of
the
fluid
layer
and
reduces
drag­
out.
Generally,
this
method
of
drag­
out
reduction
can
only
be
practiced
on
automatic
lines
where
the
withdrawal
velocity
can
be
programmed.

Reverse
Osmosis
Reverse
osmosis
is
a
membrane
separation
technology
used
for
chemical
recovery.
The
feed
stream,
usually
relatively
dilute
rinse
water
or
wastewater,
is
pumped
to
the
surface
of
the
reverse
osmosis
membrane
at
pressures
of
400
to
1,000
psig.
The
membrane
separates
the
feed
stream
into
a
reject
stream
and
a
permeate.
The
reject
stream,
containing
most
of
the
dissolved
solids
in
the
feed
stream,
is
deflected
from
the
membrane
while
the
permeate
passes
through.
Reverse
osmosis
membranes
reject
more
than
99%
of
multivalent
ions
and
90%
to
96%
of
monovalent
ions,
in
addition
to
organic
pollutants
and
nonionic
dissolved
solids.
The
permeate
stream
is
usually
of
sufficient
quality
to
be
recycled
as
rinse
water,
despite
the
small
percentage
of
monovalent
ions
(
commonly
potassium,
sodium
and
chloride)
that
pass
through
the
membrane.

A
sufficiently
concentrated
reject
stream
can
be
returned
directly
to
the
process
bath.
The
reject
stream
concentration
can
be
increased
by
recycling
the
stream
through
the
unit
more
than
once
or
by
increasing
the
feed
pressure.
In
multiple­
stage
units
containing
more
than
one
membrane
chamber,
the
reject
stream
from
the
first
chamber
is
routed
to
the
second,
and
so
on.
The
combined
reject
streams
from
multistage
units
may,
in
some
cases,
have
high
enough
concentrations
to
be
returned
directly
to
the
bath.

Timer
Rinse
Controller
Rinse
timers
are
electronic
devices
that
control
a
solenoid
valve.
The
timer
usually
consists
of
a
button
that,
when
pressed,
opens
the
valve
for
a
predetermined
length
of
time,
usually
from
1
to
99
minutes.
When
the
valve
is
open,
make­
up
water
is
allowed
to
flow
into
a
given
tank.
After
the
time
period
has
expired,
the
valve
is
automatically
shut.
The
timer
may
be
activated
either
manually
by
the
operator
or
automatically
by
the
action
of
racks
or
hoists.

Most
rinse
systems
that
are
used
intermittently
benefit
from
the
installation
of
a
rinse
timer,
as
operator
error
is
eliminated.
Rinse
timers
installed
in
conjunction
with
flow
restrictors
can
provide
precise
control
when
the
incoming
water
pressure
may
rise
and
fall.
Rinse
timers
are
less
effective
in
continuous
or
nearly
continuous
rinse
operations
(
e.
g.,
continuous
electroplating
machines).

Wetting
Agents
Wetting
agents
or
surfactants
may
be
added
to
some
process
baths
to
reduce
viscosity
and
surface
tension,
thereby
significantly
reducing
drag­
out.

Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.

D­
8
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
1.1
Drag­
Out
Reduction
and
Drag­
Out
Recovery
The
quantity
of
water
needed
for
good
rinsing
for
a
given
system
is
proportional
to
the
quantity
of
drag­
out
from
a
process
bath.
Facilities
can
implement
various
methods
that
minimize
the
rate
of
drag­
out
(
measured
as
gallons
per
square
foot
of
part
surface
area)
and/
or
they
can
implement
direct
drag­
out
recovery.
The
drag­
out
rate
for
an
individual
process
operation
(
e.
g.,
cleaning
or
plating)
depends
on
numerous
factors,
including
process
type,
shape
of
parts
processed,
production
equipment,
and
processing
procedures,
which
include
human
factors.
Of
these
factors,
the
shape
of
the
parts
and
the
type
of
device
used
to
move
the
parts
(
e.
g.,
racks,
baskets,
barrels)
usually
have
the
greatest
influence
on
drag­
out
rates.
Tables
D­
3
and
D­
4
present
drag­
out
rate
estimates
from
two
sources
in
the
literature
for
various
shaped
parts.

Table
D­
3
Average
Drag­
Out
Losses
­
from
Soderberg s
Work
Nature
of
Work
Drainage
Drag­
Out
Rate
(
gal/
1,000
ft2)

Vertical
Well
drained
0.4
Poorly
drained
2
Very
poorly
drained
4
Horizontal
Well
drained
0.8
Very
poorly
drained
10
Cup
Shapes
Well
drained
8
Very
poorly
drained
24
Source:
Reference
4.

D­
9
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
4
Average
Drag­
Out
Losses
­
from
Hogaboom s
Work
Electroplating
Solution
Type
Drag­
Out
Rate
(
gal/
1,000
ft2)

Flat
Surfaces
Contoured
Surfaces
Brass
0.95
3.3
Cadmium
1
3.1
Chromium
(
33
oz/
gal)
1.18
3
Chromium
(
53
oz/
gal)
a
4.53
11.9
Copper
cyanide
0.91
3.2
Watts
nickel
1
3.8
Silver
1.2
3.2
Stannate
tin
0.83
1.6
Acid
zinc
1.3
3.5
Cyanide
zinc
1.2
3.8
Source:
Reference
4.
a
Increased
viscosity,
caused
by
an
increase
in
concentration,
can
increase
the
drag­
out
volume
approximately
three
times
with
less
than
double
the
concentration
increase.

Several
factors
other
than
shape,
some
of
which
are
interrelated,
influence
the
drag­
out
rate
for
a
given
process
and
part.
Table
D­
5
lists
these
and
other
key
factors
and
describes
their
impact
on
drag­
out
rates.
Also
listed
are
examples
of
water
conservation
practices
that
reduce
the
generation
of
drag­
out,
and
the
major
restrictions
that
are
associated
with
these
practices.
Table
D­
6
shows
the
effect
of
altering
the
withdrawal
rate
and
drain
time.

Soderberg s
data
indicate
that
the
shape
of
the
part
has
a
significant
influence
on
drag­
out
rate.
Cup­
shaped
parts,
including
intricately
designed
parts
with
internal
surfaces,
can
generate
five
or
more
times
the
drag­
out
than
flat
surfaced
parts
with
the
same
surface
area.
Hogaboom s
data
show
a
similar
trend
for
flat
versus
contoured
surfaces.
These
data
also
show
that
the
type
and
concentration
of
the
electroplating
solution
influence
the
drag­
out
rate.
For
example,
some
solutions,
such
as
stannate
tin,
drain
effectively,
while
others,
such
as
concentrated
chromium
electroplating
solutions
(
53
ounces
per
gallon
(
oz/
gal)
drain
poorly.
As
to
the
type
of
device
used
to
move
parts,
barrels
(
used
to
hold
fasteners
or
other
small
parts
that
cannot
be
practically
held
by
racks)
generate
more
drag­
out
than
racks,
because
of
the
surface
area
of
the
barrel
and
its
tendency
to
hold
the
solution.

D­
10
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D­
11
Table
D­
5
Factors
Affecting
Drag­
Out
Factor
Affecting
Drag­
Out
Impact
on
Drag­
out
Potential
Pollution
Prevention
and
Water
Conservation
Practices
Restrictions
Bath
Concentration
Concentration
and
drag­
out
are
directly
related.
Operate
at
lowest
concentration
possible.
Remove
all
contaminants
promptly.
Concentration
range
limited
by
process.

Bath
Temperature
Higher
temperatures
lower
drag­
out
by
lowering
viscosity.
Operate
at
highest
possible
temperature.
Temperature
range
limited
by
process.

Bath
Viscosity
High
viscosity
raises
drag­
out
by
increasing
the
thickness
of
the
fluid
layer
clinging
to
the
part.
Operate
at
highest
temperature
and
lowest
concentration
possible.
Add
wetting
agent.
Concentration
and
temperature
ranges
limited
by
process.
Wetting
agent
must
be
compatible.

Part
Configuration
Cup
shapes
result
in
8­
20
times
the
drag­
out
volume
of
flat
shapes.
Drain
holes
can
be
added
to
many
cup­
shaped
parts
to
improve
drainage
of
drag­
out.
Functionality
of
parts
may
restrict
use
of
drain
holes
or
other
changes
to
part
configuration.

Part
Orientation
Orientation
on
rack
can
be
optimized
to
minimized
drag­
out.
Keep
records
of
optimal
orientations.
Train
operators.
None.

Withdrawal
Rate
Doubling
speed
of
withdrawal
results
in
a
fourfold
increase
in
drag­
out
volume.
Program
automatic
equipment
for
slow
withdrawal.
Impossible
to
consistently
practice
without
automation.

Drain
Time
Long
drain
times
and
barrel
rotations
greatly
reduce
drag­
out.
Program
automatic
equipment
for
long
drain
times.
Impossible
or
difficult
to
consistently
practice
without
automation.
Drain
time
limited
by
staining
or
passivation
of
some
coatings.

Rack
versus
Barrel
Barrels
produce
greater
drag­
out
than
racks.
(
See
 
Rack/
Barrel
Design)
Part
transport
device
is
dictated
by
part
size.

Rack/
Barrel
Design
Drag­
out
volume
is
related
to
barrel
design.
Redesign
barrels
with
largest
holes
possible.
Barrel
design
limited
by
part
sizes
and
configurations.

Rack/
Barrel
Condition
Loose
rack
coating
cause
reservoirs
of
fluid
to
be
transported
with
rack.
Maintain
a
schedule
of
maintenance
and
recoating.
None.

Operator
Awareness
Poor
operator
awareness
greatly
increases
drag­
out
or
offsets
other
practices.
Require
training
programs
for
operators.
None.

Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
6
Effect
of
Withdrawal
Rate
and
Drain
Time
on
Drag­
out
Ratea
Micro­
Etch
Results
Withdrawal
Rate
(
ft/
min)
Time
of
Withdrawal
(
seconds)
Drain
Time
(
seconds)
Total
Time
(
seconds)
Drag­
out
(
gal/
1,000
ft2)

Baseline
100
1.7
3.4
5.1
3.13
Slower
rate
of
withdrawal
11
14.9
2.5
17.4
1.73
Intermediate
withdrawal
rate
and
longer
drain
time
40
4.3
12.1
16.4
1.83
Electroless
Copper
Results
Withdrawal
Rate
(
ft/
min)
Time
of
Withdrawal
(
seconds)
Drain
Time
(
seconds)
Total
Time
(
seconds)
Drag­
out
(
gal/
1,000
ft2)

Baseline
94
1.8
5.2
7
1.55
Slower
Rate
of
Withdrawal
12
13.9
3.2
17
0.78
Intermediate
Withdrawal
Rate
and
Longer
Drain
Time
40
4.3
11.9
16.3
0.75
Source:
Reference
4.
a
The
effects
of
changing
the
withdrawal
rate
and
drain
time
were
measured
at
a
printed
circuit
board
manufacturing
facility.

The
following
is
a
list
of
drag­
out
reduction
practices
that
facilities
can
implement
on
electroplating
or
surface
finishing
lines:

 
Lower
process
solution
viscosity
and/
or
surface
tension
by
decreasing
chemical
concentration,
increasing
bath
temperature,
or
using
wetting
agents;

 
Reduce
drag­
out
volume
by
modifying
rack/
barrel
design
and
perform
rack
maintenance
to
avoid
solution
trapping;

 
Position
parts
on
racks
in
a
manner
that
avoids
trapping
solution;

 
Reduce
speed
of
rack/
barrel
withdrawal
from
process
solution
an/
or
increase
dwell
time
over
process
tank;

 
Rotate
barrels
over
the
process
tank
to
improve
drainage;

 
Use
spray/
fog
rinsing
over
the
process
tank
(
limited
applicability);

 
Use
drip
boards
and
return
process
solution
to
the
process
tank;

D­
12
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
 
Use
drag­
out
tanks,
where
applicable,
and
return
solution
to
the
process
tank;
and
 
Work
with
customers
to
ensure
that
part
design
maximizes
drainage.

D.
1.2
Improved
Rinse
Tank
Design
and
Rinsing
Configurations
Rinse
tank
design
and
rinsing
configuration
greatly
influence
water
usage.
The
key
objectives
for
optimal
rinse
tank
design
are
to
quickly
remove
drag­
out
from
the
part
and
completely
disperse
the
drag­
out
throughout
the
rinse
tank.
Achieving
these
objectives
reduces
the
time
necessary
for
rinsing
and
minimizes
the
concentration
of
contaminants
on
the
part
when
it
leaves
the
rinse
tank.
Examples
of
good
design
include
locating
water
inlet
and
discharge
points
of
the
tank
at
opposite
positions
in
the
tank
to
avoid
short­
circuiting,
and
using
air
agitation
for
better
mixing
(
5).

Various
rinsing
configurations
are
used
by
MP&
M
facilities.
Having
single­
rinse
tanks
following
each
process
tank
is
the
most
inefficient
use
of
rinse
water.
Multiple­
rinse
tanks
connected
in
series
(
i.
e.,
countercurrent
cascade
rinsing)
reduces
the
water
needs
of
a
given
rinsing
operation
by
one
or
more
orders
of
magnitude.
Spray
rinsing
can
also
reduce
water
use
requirements,
but
the
achievable
percent
reduction
is
usually
less
than
for
countercurrent
cascade
rinsing.
Other
configurations
that
reduce
water
use
include
cascade,
reactive,
and
dual
purpose
rinses.

D.
1.3
Rinse
Water
Use
Control
Devices
Regardless
of
the
type
of
rinsing
configuration
used,
facilities
can
reduce
their
water
use
by
coordinating
water
use
and
water
use
requirements.
Matching
water
use
to
water
use
requirements
can
optimize
the
quantity
of
rinse
water
used
for
a
given
work
load
and
tank
arrangement
(
5).
Not
controlling
water
use
negates
the
benefits
of
using
multiple
rinse
tanks
or
other
water
conservation
practices
and
increases
water
usage.

Facilities
may
wish
to
implement
at
least
one
effective
method
of
water
use
control
on
all
electroplating
or
surface
finishing
lines.
Effective
water
use
controls
include,
but
are
not
limited
to:

 
Use
of
softened
or
deionized
water
for
rinsing.

 
Flow
restrictors
(
flow
restrictors
as
a
stand­
alone
method
of
rinse
water
control
are
only
effective
with
plating
lines
that
have
constant
production
rates,
such
as
automatic
plating
machines.
For
other
operations,
there
must
also
be
a
mechanism
or
procedure
for
stopping
water
flow
during
idle
periods.).

 
Conductivity
controls.

D­
13
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
 
Timer
rinse
controls.

 
Production­
activated
controls
(
e.
g.,
spray
systems
activated
when
a
rack
or
barrel
enters/
exits
a
rinse
station).

D.
1.4
Metal
Recovery
and
Rinse
Water
Reuse
Technologies
MP&
M
facilities
use
various
technologies
to
recover
metals
drag­
out
and
rinses
and
reuse
the
rinse
water.
The
technologies
most
commonly
used
are
evaporation,
ion
exchange,
electrolytic
recovery
(
also
referred
to
as
electrowinning),
reverse
osmosis,
and
electrodialysis.
Table
D­
7
presents
examples
of
metal
recovery
technologies
and
the
drag­
out/
rinses
to
which
they
are
primarily
applied.

Table
D­
7
Examples
of
Metal
Recovery
Methods
Chemistry
or
Process
with
Which
Rinse
is
Associated
Recovery
Technology
Brass
electroplating
Electrolytic
recovery,
evaporation
Cadmium
(
cyanide)
electroplating
Electrodialysis,
electrolytic
recovery,
evaporation,
ion
exchange,
reverse
osmosis
Cadmium
(
noncyanide)
electroplating
Electrodialysis,
electrolytic
recovery,
evaporation,
ion
exchange,
reverse
osmosis
Chromate
conversion
coating
of
aluminum
Evaporation
Chromium
(
hard)
anodizing
Evaporation,
mist
eliminator
Chromium
electroplating
­
decorative
(
Cr+
6)
Evaporation
Chromium
electroplating
­
decorative
(
Cr+
3)
Evaporation
Copper
(
cyanide
and
sulfate)
electroplating
Electrolytic
recovery,
evaporation,
ion
exchange,
reverse
osmosis
Gold
electroplating
Electrolytic
recovery,
ion
exchange
Lead­
tin
electroplating
Evaporation,
ion
exchange
Nickel
electroplating
Electrodialysis,
electrolytic
recovery,
evaporation,
ion
exchange,
reverse
osmosis
Nickel
electroless
plating
Evaporation,
ion
exchange
Nickel
sealant
Reverse
osmosis
Silver
electroplating
Electrolytic
recovery,
evaporation,
ion
exchange
Zinc
(
cyanide)
electroplating
Electrolytic
recovery,
evaporation,
reverse
osmosis
Zinc
(
noncyanide)
electroplating
Electrolytic
recovery,
evaporation,
ion
exchange,
reverse
osmosis
Zincate
Evaporation
Source:
Reference
5.

D­
14
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D­
15
Hand
Valve
Fresh
Water
Work
Flow
5
sec.
withdraw
rate
5
sec.
dwell
time
Plating
Tank
Rinse
Tank
Figure
D­
1(
a).

Hand
Valve
Fresh
Water
Work
Flow
15sec.
withdraw
rate
15sec.
dwell
time
Plating
Tank
Rinse
Tank
Flow
Restrictor
Figure
D­
1(
b).
Rinse
Tank
with
Flow
Reduction
D.
1.5Summary
of
Water
Conservation
Methods
Figures
D­
1(
a)
through
(
f)
present
six
examples
of
rinsing
configurations
with
increasingly
good
levels
of
water
use
practices.
nse
systems
is
described
below.
These
configurations
can
be
operated
to
provide
adequate
rinsing
and
are
common
at
MP&
M
facilities.
ver,
the
quantity
of
water
needed
for
the
same
rinse
quality
may
vary
by
as
much
as
two
orders
of
magnitude
from
the
lowest
level
to
the
best
level
of
water
use.

Single
Rinse
Tank
Single
Each
of
these
ri
Howe
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D­
16
Fresh
Water
Work
Flow
15
sec.
withdraw
rate
15
sec.
dwell
time
Plating
Tank
Rinse
Tank
Hand
Valve
Fresh
Water
Rinse
Tank
Flow
Restrictor
Figure
D­
1(
c).
e
Tanks
with
Flow
Reduction
Work
Flow15
sec.
withdraw
rate
15
sec.
dwell
time
Plating
Tank
Rinse
Tank
Fresh
Water
Rinse
Tank
Conductivity
Controller
Drag­
Out
Tank
Recovered
Rinse
Figure
D­
1(
e).
ltiple
Rinse
Tanks
with
Flow
Reduction
and
Drag­
Out
Recovery
Work
Flow
15
sec.
withdraw
rate
15
sec.
dwell
time
Plating
Tank
Rinse
Tank
Hand
Valve
Fresh
Water
Rinse
Tank
Flow
Restrictor
Figure
D­
1(
d).
ntercurrent
Rinsing
with
Flow
Reduction
Multiple
Rins
Mu
Cou
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Work
Flow15
s
e
c
.
w
ithdraw
ra
te
15
s
e
c
.
dw
ell
tim
e
Pla
tin
g
Tank
R
e
cycle
Rin
s
e
Tank
D
rag
­
O
ut
Tank
R
e
c
o
v
e
red
R
ins
e
Cation
Colmn
Anion
column
To
tre
a
tm
e
n
t
E
lectro
w
inning
Un
it
M
e
ta
l
d
epleted
elec
troly
te
reus
e
d
fo
r
re
g
eneratio
n
R
egen
erants
Scrap
metal
to
recycle
Figure
D­
1(
f).
Multiple
Rinse
Tanks
with
Water
Recycle,
Drag­
Out
Recovery,
and
Metal
Recovery
Figure
D­
1(
a)
is
an
example
of
inefficient
water
use.
This
configuration
uses
a
single­
rinse
tank
with
either
continuous
water
flow
or
manual
use
control.
To
coordinate
rinse
water
needs
and
use,
the
operator
manually
turns
on
the
water
valve
to
give
the
correct
flow
rate
and
then
turns
it
off
when
the
flow
is
no
longer
needed.
The
flow­
rate
setting
will
usually
vary
by
operator
and
the
water
valve
may
be
left
open
during
idle
production
periods.
The
single
rinse
tank
configuration
uses
rinse
water
at
a
very
high
rate,
even
if
water
use
is
coordinated
with
the
introduction
of
drag­
out.
In
the
example
shown,
with
a
1­
gallon­
per­
hour
(
gph)
drag­
out
rate,
the
rinse
water
requirement
is
30
gallons
per
minute
(
gpm),
based
on
rinsing
of
Watts
nickel
plating
solution
and
a
rinsing
criterion
of
50
milligrams
per
liter
(
mg/
L)
nickel.
If
water
use
and
drag­
out
introduction
are
not
coordinated,
an
even
higher
rinse
water
use
rate
would
be
needed
to
meet
a
given
rinse
criterion.

Figure
D­
1(
b)
shows
a
rinsing
configuration
where
simple
rinse
water
reduction
methods
have
been
implemented.
The
water
use
is
still
inefficient
because
a
single
rinse
tank
is
used
versus
multiple
rinse
tanks.
However,
with
this
configuration,
the
drag­
out
rate
is
reduced
by
controlling
the
withdrawal
rate
of
the
part
(
increasing
the
withdrawal
rate
from
5
to
15
seconds)
and
by
holding
the
part
over
the
process
tank
(
increasing
dwell
time
from
5
to
15
D­
17
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
seconds)
to
permit
the
drag­
out
to
drip
into
the
tank.
The
rinse
water
flow
rate
is
controlled
at
a
constant
flow
by
a
flow
restrictor.
The
flow
restrictor
is
usually
sized
to
provide
adequate
rinsing
at
all
times,
and
is
more
acceptable
for
constant
production
rates,
such
as
those
often
found
with
automated
plating
machines.
However,
this
configuration
is
inefficient
when
the
work
is
intermittent
because
the
rinse
water
flow
rate
must
be
set
high
enough
to
provide
adequate
rinsing
during
peak
production
periods.
In
addition,
a
large
quantity
of
rinse
water
is
wasted
during
low
or
idle
production
periods,
unless
the
water
flow
is
manually
stopped.

Figure
D­
1(
c)
shows
a
rinsing
configuration
using
multiple
rinse
tanks,
which
provides
a
moderately
efficient
use
of
water.
This
configuration
is
referred
to
as
parallel
rinsing,
where
each
of
the
two
rinse
tanks
are
fed
with
fresh
water
and
they
each
discharge
to
treatment.
This
arrangement
can
reduce
water
use
to
less
than
50
percent
of
that
used
in
Figure
D­
1(
a).

Figure
D­
1(
d)
shows
a
more
efficient
rinsing
configuration.
This
configuration
is
similar
to
that
shown
in
Figure
D­
1(
c),
except
that
wastewater
from
the
second
rinse
tank
flows
back
into
the
first
rinse
tank
to
provide
more
efficient
rinsing
with
less
water
use.
Wastewater
from
the
first
rinse
tank
is
then
discharged
to
treatment.
In
this
configuration,
known
as
countercurrent
cascade
rinsing,
the
rinse
water
flows
in
a
direction
opposite
to
the
part
flow.
This
arrangement
can
reduce
water
use
by
more
than
90
percent
over
the
rinse
configuration
in
Figure
D­
1(
a).

Figure
D­
1(
e)
shows
a
very
efficient
rinsing
configuration.
There
are
three
key
elements
to
this
rinse
system:
drag­
out
reduction/
recovery,
countercurrent
cascade
rinsing,
and
water­
use
control.
This
configuration
reduces/
recovers
drag­
out
by
controlling
the
withdrawal
rate
and
dwell
time
and
by
installing
a
drag­
out
recovery
tank.
This
tank
can
reduce
the
drag­
out
entering
the
countercurrent
cascade
rinses
by
up
to
90
percent,
depending
on
the
surface
evaporation
rate
of
the
process
tank.
A
conductivity
controller
controls
the
feed
to
the
countercurrent
cascade
rinses.
This
type
of
device
coordinates
water
use
with
drag­
out
introduction
and
reduces
the
influence
of
human
error
found
with
manually
controlled
rinses.
An
alternative
device
is
a
timer
rinse
control,
which
is
as
effective
as
a
conductivity
controller
when
there
is
no
variability
in
drag­
out
volume
between
rinsing
events.

Figure
D­
1(
f)
shows
a
rinse
system
that
uses
an
ion
exchange/
electrolytic
recovery
unit
as
a
chemical
recovery
and
water
recycling
technology.
This
rinsing
configuration
can
reduce
water
use
by
more
than
99
percent
compared
to
the
rinse
configuration
in
Figure
D­
1(
a),
since
wastewater
is
discharged
only
from
the
regeneration
cycle
of
the
ion­
exchange
unit.

Table
D­
1
presents
examples
of
additional
practices
and
technologies
that
could
be
components
of
a
well­
designed
rinse
system.

D.
1.6
Influences
on
Flow
Rates
Available
data
show
that
rinse
water
use
rates
are
related
to
production
when
measured
in
terms
of
the
surface
area
of
parts
processed.
Other
factors
that
influence
rinse
water
D­
18
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
use
rates
include
the
drag­
out
rate
(
gallons
per
1,000
square
feet
of
workload),
the
rinse
water
purity
criteria
(
mg/
L
metal),
the
concentration
of
TDS
in
the
bath
(
mg/
L
TDS),
rinse
tank
design
and
configuration
(
e.
g.,
single
overflow
rinse
versus
countercurrent
cascade
rinse),
and
the
type
of
rinse
water
flow
control
(
e.
g.,
manual
versus
conductivity
controlled).
Section
D.
1.5
discusses
drag­
out
rinse
tank
design
and
configuration
and
rinse
water
flow
control.
The
other
factors
are
discussed
below.

D.
1.6.1
Rinse
Water
Purity
Criteria
Rinse
water
purity
criteria
are
the
levels
of
tolerable
contamination
in
the
rinse
water.
These
levels
vary
for
different
processes
and
types
of
products.
For
example,
rinse
water
used
after
cleaning
typically
does
not
have
to
be
as
pure
as
rinse
water
used
following
plating,
since
rinse
water
that
remains
on
the
plated
part
(
essentially
the
drag­
out
from
the
rinse
tank)
will
leave
spots
after
it
evaporates
if
the
concentration
of
dissolved
solids
in
the
rinse
water
is
too
high.
Although
preliminary
and
intermediate
processing
steps
such
as
cleaning
and
etching
usually
do
not
require
as
pure
a
rinse
water
as
final
rinsing,
the
rinse
water
needs
to
be
pure
enough
to
stop
chemical
reactions
(
e.
g.,
etching)
and
prevent
the
contamination
of
subsequent
process
solutions.
Among
plating
processes,
differences
also
exist
in
rinse
water
quality
requirements.
Parts
plated
for
engineering
or
functional
purposes
(
e.
g.,
corrosion
resistance)
can
often
be
rinsed
in
water
that
is
significantly
less
pure
than
decoratively
plated
parts
rinses.

High­
purity
water
is
needed
for
various
rinsing
operations.
In
some
cases
(
e.
g.,
electronics
parts
rinsing),
tap
water
is
not
pure
enough
to
serve
as
rinse
water.
Before
use
as
rinse
water
for
this
type
of
operation,
the
source
water
is
purified
by
reverse
osmosis
and/
or
ion
exchange
to
remove
dissolved
solids
and
other
constituents.
Source
water
is
sometimes
treated
even
for
common
rinsing
operations,
especially
when
the
water
supply
is
high
in
dissolved
solids.

The
metal
finishing
industry
has
had
rinse
water
quality
requirements
for
decades.
They
are
typically
expressed
in
mg/
L
of
TDS
or
in
conductivity
or
resistivity
units
(
resistivity
is
the
inverse
of
conductivity).
Table
D­
8
summarizes
some
generalized
rinse
criteria
found
in
the
literature
(
4).

D­
19
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
8
Generalized
Rinse
Criteria
Type
of
Rinse
Normal
Range
for
Adequate
Rinsing
(
mg/
L
TDS)

Alkaline
Treatment/
Acid
Treatment
Rinse
400
to
1,000
Functional
or
Engineering
Plating
Rinse
100
to
700
Decorative
or
Bright
Plating
Rinse
5
to
40
Source:
Reference
4.

D.
1.6.2
Bath
Concentration
The
concentration
of
a
bath
(
which
can
be
expressed
in
g/
L
TDS)
will
affect
the
quantity
of
water
needed
for
good
rinsing.
Baths
that
are
more
concentrated
(
i.
e.,
higher
TDS)
will
require
more
rinse
water
to
meet
the
same
rinse
water
purity
criteria
as
a
less
concentrated
bath.
The
bath
concentration
depends
on
the
type
of
bath.
For
example,
a
typical
acid
zinc
electroplating
bath
will
have
a
TDS
concentration
of
166
g/
L
and
a
typical
copper
cyanide
electroplating
bath
will
have
a
TDS
concentration
of
250
g/
L
(
6,7).
For
equal
volumes
of
drag­
out
from
these
two
baths,
the
copper
cyanide
rinse
flow
must
be
1.5
times
greater
to
achieve
the
same
rinse
quality
criteria
(
i.
e.,
250/
166
=
1.5).
This
calculation
does
not
account
for
the
differences
in
viscosity
that
will
also
affect
the
volume
of
drag­
out.
For
example,
for
flat
surfaces,
the
drag­
out
rate
for
a
396­
g/
L
chromic
acid
bath
is
3.8
times
greater
than
that
of
a
247­
g/
L
bath
(
6,7).
In
some
cases,
the
TDS
concentration
of
the
bath
inadvertently
increases
due
to
a
buildup
of
bath
contaminants
(
e.
g.,
iron
may
accumulate
in
a
chromic
acid
bath
due
to
the
attack
of
the
base
metal).
The
TDS
added
by
the
contaminants
may
affect
the
drag­
out
rate
in
the
same
manner
as
its
intended
bath
constituents
(
e.
g.,
chromic
acid).
Therefore,
operating
a
bath
at
the
lowest
concentration
necessary
to
perform
the
job
properly
and
maintaining
bath
contaminants
at
low
levels
is
a
significant
pollution
prevention
measure.

D.
1.7
Technical
Literature
Table
D­
9
presents,
for
several
types
of
rinses,
calculated
flow
rates
for
a
single­
stage
overflow
rinsing
configuration
and
a
two­
stage
countercurrent
cascade
rinsing
configuration.
Both
rinsing
configurations
are
assumed
to
have
flow
control
(
i.
e.,
water
use
is
coordinated
with
drag­
out
introduction
using
a
conductivity
control
or
other
device).
This
table
presents
the
TDS
concentration
in
the
associated
bath
(
from
literature),
the
target
TDS
in
the
rinse
(
based
on
the
rinsing
criteria),
the
part
type,
the
assumed
drag­
out
rate,
and
two
production
normalized
flow
(
PNF)
values.

The
first
value,
PNF
100%
Control,
is
a
calculated
value
based
on
the
assumption
that
a
facility
perfectly
coordinates
work
flow
and
rinse
water
use
(
e.
g.,
using
a
conductivity
controller).
In
actual
operations,
perfect
coordination
is
nearly
impossible
to
achieve
because
the
quantity
of
rinse
D­
20
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D­
21
Table
D­
9
Rinse
Water
Required
for
Various
Plating
Processes
Based
on
Literature
Values
Process
Rinse
Configuration
TDS
Concentrationa
Target
TDS
Concentration
in
Rinsea
Part
Type
Drag­
out
Ratea
PNF
100%
Control
(
gal/
ft2)
PNF
100%
Excess
(
gal/
ft2)

Acid
Zinc
Single
overflow
166
g/
L
Functional:
100­
700
mg/
L
(
used
400
mg/
L)
Flat
1.3
gal/
1,000
ft2
0.54
1.1
Contoured
3.5
gal/
1,000
ft2
1.5
2.9
2­
stage
countercurrent
cascade
166
g/
L
Functional:
100­
700
mg/
L
(
used
400
mg/
L)
Flat
1.3
gal/
1,000
ft2
0.024
0.048
Contoured
3.5
gal/
1,000
ft2
0.072
0.14
Silver
Cyanide
Single
overflow
370
g/
L
Bright:
5­
40
mg/
L
(
used
20
mg/
L)
Flat
1.2
gal/
1,000
ft2
22
44
Contoured
3.2
gal/
1,000
ft2
58
120
2­
stage
countercurrent
cascade
370
g/
L
Bright:
5­
40
mg/
L
(
used
20
mg/
L)
Flat
1.2
gal/
1,000
ft2
0.16
0.32
Contoured
3.2
gal/
1,000
ft2
0.43
0.87
Copper
Cyanide
Single
overflow
250
g/
L
Functional:
100­
700
mg/
L
(
used
400
mg/
L)
Flat
0.91
gal/
1,000
ft2
0.57
1.1
Contoured
3.2
gal/
1,000
ft2
2
4
2­
stage
countercurrent
cascade
250
g/
L
Functional:
100­
700
mg/
L
(
used
400
mg/
L)
Flat
0.91
gal/
1,000
ft2
0.023
0.046
Contoured
3.2
gal/
1,000
ft2
0.081
0.16
Acid
Descale
Single
Overflow
248
g/
L
Clean:
400­
1000
mg/
L
(
used
700
mg/
L)
Flat
1
gal/
1,000
ft2
(
estimated)
3.5
7.1
Contoured
3
gal/
1,000
ft2
(
estimated)
11
21
2­
stage
countercurrent
cascade
248
g/
L
Clean:
400­
1000
mg/
L
(
used
700
mg/
L)
Flat
1
gal/
1,000
ft2
(
estimated)
0.019
0.038
Contoured
3
gal/
1,000
ft2
(
estimated)
0.056
0.11
Alkaline
Clean
(
Proprietary
Chemistry)
Single
overflow
90
g/
L
Clean:
400­
1000
mg/
L
(
used
700
mg/
L)
Flat
1
gal/
1,000
ft2
(
estimated)
0.13
0.26
Contoured
3
gal/
1,000
ft2
(
estimated)
0.39
0.77
2­
stage
countercurrent
cascade
90
g/
L
Clean:
400­
1000
mg/
L
(
used
700
mg/
L)
Flat
1
gal/
1,000
ft2
(
estimated)
0.011
0.022
Contoured
3
gal/
1,000
ft2
(
estimated)
0.033
0.066
Sources:
References
4,
6,
and
7.

a
TDS
concentrations
are
from
References
6
and
7,
based
on
bath
formulations.
Target
TDS
concentrations
are
based
on
criteria
presented
in
Section
3.2.1
(
Reference
4).
Drag­
out
rates
are
from
References
4
and
5
unless
data
were
not
available,
in
which
case
rates
were
assumed
based
on
technical
knowledge
of
the
operations.
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
9
(
Continued)

1.
Acid
zinc
formulation:

ZnSO4
(
7H2
O)
240
g/
L
NH4
Cl
15
g/
L
Al2
(
SO4
)
3
(
18H2
O)
30
g/
L
Licorice
1
g/
L
2.
Equation
used
to
calculate
rinse
flow
and
flow
per
square
foot
for
single
overflow
rinse:
Solving
for
Q:
Where:

D
=
Drag­
out
per
ft2
(
gal)
Ce
=
Target
concentration
of
rinse
(
oz/
gal)
Co
=
Concentration
of
process
bath
(
oz/
gal)
Cr
=
Target
concentration
of
final
rinse
(
oz/
gal)
M
=
Interval
between
drag­
out
events
(
minutes)
Q
=
Flow
(
gal/
min)

Note:
Any
interval
M
can
be
chosen.
Q,
when
divided
by
the
work
rate,
ft2
/
M,
yields
the
gal/
ft2
in
the
table
and
the
gal/
ft2
number
remains
the
same
for
any
M.

3.
Equation
used
to
calculate
100
percent
controlled
flow
and
gallons
per
square
foot
for
countercurrent
cascade
rinse:

xWhere
n
=
number
of
rinse
stages
For
50
percent
controlled
flow,
Q
was
multiplied
by
a
factor
of
2.

With
100
percent
controlled
flow,
the
introduction
of
drag­
out
and
rinse
water
into
the
rinse
tank
are
perfectly
coordinated
and,
therefore,
the
rinse
water
required
to
meet
the
target
concentration
of
the
final
rinse
is
equal
to
Q.
With
100
percent
excess
flow,
the
introduction
of
drag­
out
and
rinse
water
are
not
perfectly
coordinated
and
an
excess
of
100
percent
of
Q
(
or
2Q)
is
used
to
meet
the
target
concentration
of
the
final
rinse.

4.
Silver
cyanide
formulation
(
middle
of
high­
speed
bath
range):

AgCN
97.5
g/
L
KCN
152.5
g/
L
K2
CO3
52.5
g/
L
KNO3
50
g/
L
KOH
17
g/
L
5.
High­
efficiency
copper
cyanide
formulation:

CuCN
75
g/
L
KCN
133
g/
L
KOH
42
g/
L
6.
Acid
descale
formulation:

20%
H2
NO3
(
by
volume)
1.5%
HF
(
by
volume)

All
bath
formulations
and
equations
are
from
References
4,
6,
and
7.

D­
22
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
water
needed
to
meet
a
given
rinse
criterion
usually
cannot
be
added
exactly
at
the
time
that
drag­
out
enters
and
is
dispersed
in
the
rinse
tank.
For
example,
when
a
barrel
of
parts
is
rinsed,
it
is
usually
placed
in
a
rinse
tank
for
1
to
3
minutes.
The
rinse
water
volume
needed
to
meet
the
rinse
criterion
may
be
50
gallons
or
more.
The
flow
rate
of
water
into
the
rinse
tank
is
typically
less
than
10
gpm
(
flow
rates
into
rinse
tanks
vary
depending
on
the
pipe
size
and
water
pressure
and
may
be
reduced
by
a
flow
restrictor).
Therefore,
it
may
take
5
minutes
to
add
the
50
gallons
of
rinse
water.
Because
of
this,
actual
water
use
rates
will
be
higher
than
those
presented
in
the
column,
PNF
100%
Control.
A
reasonable
assumption
is
that
good
water
flow
control
will
result
in
a
PNF
twice
that
of
the
calculated
values
that
assume
100
percent
control.
These
flows
are
shown
as
PNF
100%
Excess.

Machining
Operations
Many
machining
operations
use
metal­
working
fluids
to
cool
and
lubricate
parts
and
machining
tools
during
cutting,
drilling,
milling,
and
other
machining
operations.
These
fluids
become
contaminated
and
begin
to
lose
their
working
characteristics.
If
neglected,
the
fluids
become
unusable
and
require
treatment
and
disposal.
Through
proper
care,
the
life
span
of
the
fluids
can
be
extended
indefinitely.
For
most
machining
operations,
prolonging
metal­
working
fluid
life
reduces
the
cost
of
treatment
and
disposal,
as
well
as
the
cost
of
fresh
coolant.

Many
MP&
M
facilities
use
some
type
of
pollution
prevention
and
water
conservation
practices
for
machining
wastewaters.
Some
facilities
have
implemented
numerous
pollution
prevention
and
water
conservation
methods
and
technologies
that
result
in
very
low
machining
wastewater
discharge
rates
and
in
some
cases
eliminate
the
discharge
of
machining
fluids.
Pollution
prevention
and
water
conservation
practices
are
applicable
to
all
machining
operations;
however,
process­
related
factors
and
site­
specific
conditions
may
restrict
the
utility
of
certain
methods.

D.
2.1
Wastewater
Generation
from
Machining
Operations
Various
types
of
metal­
working
fluids,
also
termed
cutting
fluids
and
coolants,
are
used
in
machining
operations
to
improve
the
life
and
function
of
machine
tools.
During
machining,
these
fluids
are
circulated
over
working
surfaces,
reducing
friction,
cooling
the
tool
and
part,
and
removing
metal
chips
from
the
work
face.
The
type
of
fluid
used
depends
on
the
type
of
machining
being
performed
and
the
preference
of
the
site.
The
fluids
are
broadly
divided
into
four
groups:
straight
oil
(
neat
oils),
synthetic
oils,
semisynthetic,
and
soluble
oil.
The
most
commonly
used
fluids
are
soluble
oils,
synthetics,
and
semisynthetics.

Water­
soluble
coolants
are
prepared
by
mixing
a
concentrated
coolant
with
water
in
a
1:
15
to
1:
30
ratio
to
produce
a
fluid
with
a
90­
to
98­
percent
water
content.
Most
water­
soluble
coolants
are
suitable
for
light­
and
medium­
duty
operations.
Synthetic
coolants
are
designed
for
high
cooling
capacity,
lubricity,
and
corrosion
prevention.
Common
chemical
agents
in
synthetics
include:
amines
and
nitrites
for
rust
prevention;
nitrates
for
nitrite
stabilization;
phosphates
and
borates
for
water
softening;
soaps
and
wetting
agents
for
D­
23
D.
2
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
lubrication;
phosphorus,
chlorine,
and
sulfur
compounds
for
chemical
lubrication;
glycols
to
act
as
blending
agents;
and
biocides
to
control
bacteria
growth.
Semisynthetics
contain
small
dispersions
of
oil
in
an
almost
otherwise
organic
water­
dilutable
system.
Straight
oils
are
good
lubricants,
but
are
less
effective
for
cooling,
and
therefore
are
limited
mostly
to
use
in
low­
speed
operations
(
8).

Metal­
working
fluids
are
periodically
discarded
because
of
reduced
performance
or
development
of
a
rancid
odor.
The
fluids
that
contain
a
large
percentage
of
oil
typically
are
contract
hauled
as
solid
waste
for
disposal
or
recovery.
Fluids
with
lower
oil
content
typically
are
sent
to
a
site s
wastewater
treatment
system
for
treatment
and
subsequent
discharge.

Metal­
working
fluids
degrade
mainly
because
of
contamination
with
tramp
oil
and
dirt
and
by
bacterial
growth,
which
can
be
accelerated
by
tramp
oil
contamination.
Tramp
oil
contamination
is
caused
mostly
by
oil
from
the
part s
surface
during
machining
and
by
leaks
of
lubricating
and
hydraulic
oils
from
the
machine.
Airborne
dust
or
poor
housekeeping
practices
can
cause
dirt
to
accumulate.
Bacteria
are
initially
contributed
from
the
surfaces
of
the
machine
and
parts
and
from
the
air.
More
than
2,000
known
species
of
bacteria
have
been
reported
to
affect
and
eventually
destroy
the
stability
of
machining
fluids
(
9).
Bacteria
feed
on
the
fluids 
chemicals,
causing
the
fluids
to
lose
lubricity
and
corrosion
inhibition.
Under
anaerobic
conditions,
sometimes
caused
by
floating
tramp
oil
in
coolant
sumps,
bacteria
generate
a
hydrogen
sulfide
odor.

In
addition
to
spent
fluid,
machining
operations
may
generate
wastewater
from
rinsing.
Machined
parts
may
be
rinsed
to
remove
fluid,
chips
and
other
foreign
materials.
However,
parts
typically
are
not
rinsed
following
machining.
More
frequently,
the
fluid
is
permitted
to
remain
on
the
part
to
inhibit
corrosion,
is
wiped
off
using
shop
towels,
or
is
cleaned
in
an
alkaline
cleaning
or
degreasing
operation.

The
quantity
of
wastewater
generated
by
a
machining
operation
depends
primarily
on
the
volume
of
work
performed.
Production
volume
can
be
roughly
measured
by
the
quantity
of
metal
stock
removed
by
turning,
milling,
boring,
broaching,
cutting
and
other
machining
operations.
For
most
machining
operations,
the
removed
metal
consists
of
small
fragments
called
chips
or
fines.
Most
chips
carry
a
thin
film
of
fluid
on
their
surfaces,
which,
when
it
drains,
is
another
source
of
wastewater.

D.
2.2
Pollution
Prevention
and
Water
Conservation
Practices
for
Machining
Operations
The
Agency
has
identified
two
categories
of
pollution
prevention
and
water
conservation
practices
and
technologies
that
can
be
used
to
reduce
metal­
working
fluid
discharge:
those
used
to
prevent
metal­
working
fluid
contamination
and
those
used
to
extend
the
life
of
machining
fluids,
including
recovering
and
recycling
metal­
working
fluids.
Within
each
of
these
categories
are
several
specific
practices
and
technologies.
Table
D­
10
presents
several
examples
of
these
practices,
which
are
discussed
below.
There
may
be
other
practices
and
D­
24
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
technologies
not
identified
here
that
can
reduce
metal­
working
fluid
discharge.
Therefore,
the
list
provided
below
is
not
exhaustive.

Table
D­
10
Potential
Pollution
Prevention
and
Water
Conservation
Methods
Applicable
to
Machining
Operations
Pollution
Prevention/
Water
Conservation
Method
Examples
Applicability
Prevention
of
Metal­
Working
Fluid
Contamination
Reduce
contamination
from
tramp
oil
Use
coolant
in
hydraulic
and
other
oil
systems.
Applicable
to
most
machines.
In
most
cases,
requires
use
of
special
fluid.

Replace
hydraulics
with
electrical
systems.
Limited
applicability.
Practical
only
during
major
equipment
overhaul.

Machine
maintenance.
Applicable
to
all
machines.
Should
be
performed
at
regularly
scheduled
intervals.

Reduce
contamination
from
make­
up
water
Use
deionized
water
for
initial
make­
up
of
working
fluid
and
to
account
for
evaporative
losses.
Applicable
to
all
machining
operations
using
a
water­
soluble
fluid.
Especially
important
in
areas
where
the
water
supply
is
high
in
TDS.

Reduce
contamination
from
sumps
Sterilize
sumps
during
clean­
out
using
steam.
Applicable
to
all
machining
operations.
Especially
important
with
large
concrete
sumps.

Use
metal
inserts
or
coat
walls
of
concrete
sumps.
Applicable
to
in­
ground
concrete
sumps.

Extension
of
Metal­
Working
Fluid
Life
Raw
material
substitution
Use
high
quality
fluids
with
needed
 
additive
package. 
Most
machining
operations
can
benefit
from
the
use
of
high­
quality
fluids
that
can
extend
fluid
life,
while
reducing
bacterial
growth,
improving
lubricity,
reducing
friction,
and
providing
corrosion
protection.

Equipment
modification
Replace
sump s
air
agitation
with
mechanical
agitation.
Applicable
to
central
sumps
with
air
agitation.

Install
tramp
oil
removal
device.
Limited
mainly
to
external
sumps.

Fluid
Monitoring
Measure
pH,
coolant
concentration,
tramp
oil
concentration,
and
bacterial
count
weekly
or
more
frequently.
Applicable
to
all
machining
operations.
Larger
operations
can
use
data
for
statistical
process
control.

D­
25
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
10
(
Continued)

Pollution
Prevention/
Water
Conservation
Method
Examples
Applicability
Extension
of
Metal­
Working
Fluid
Life
(
continued)

Metal­
working
fluid
recycling
Use
methods
and
technologies
for
removing
fluid
contaminants
(
e.
g.,
filtration,
centrifuge,
pasteurization).
Simple
filtration
methods
can
be
used
by
all
machining
operations.
More
sophisticated
equipment
is
limited
to
larger
operations.

Recycle
chip
drainage.
Applicable
to
all
machining
operations.
Requires
clean
handling
and
storage
methods
to
prevent
contamination.

Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.

D.
2.2.1
Prevention
of
Metal­
Working
Fluid
Contamination
Facilities
can
implement
various
methods
to
reduce
the
amount
of
fluid
contamination.
Several
of
these
methods
are
discussed
below.

Reduction
of
Contamination
From
Tramp
Oil.
Tramp
oil
is
a
primary
contaminant
in
machining
fluids
and
for
many
facilities
the
major
cause
of
metal­
working
fluid
degradation.
EPA
has
identified
the
following
methods
to
reduce
contamination
of
metal­
working
fluid
with
tramp
oil.

 
Use
of
Coolant
in
Hydraulic
and
Other
Oil
Systems
.
Some
metal­
working
coolants
are
formulated
to
be
used
as
hydraulic
fluid
and/
or
lubricant
in
concentrated
form
and
as
a
coolant
in
its
dilute
form
(
i.
e.,
diluted
with
water).
When
used
as
a
hydraulic
fluid
or
lubricant,
leaks
of
the
fluid
will
assimilate
into
the
coolant
without
causing
contamination.

 
Replacement
of
Hydraulics
with
Electrical
Systems
.
Hydraulic
systems
on
some
machines
can
be
replaced
by
newer
electrical
systems
that
do
not
contain
hydraulic
fluid.
This
replacement
could
be
economically
performed
during
major
equipment
overhauls.

 
Machine
Maintenance
.
Machine
design
and
age
may
affect
the
quantity
of
hydraulic
oil
that
leaks
to
the
metal­
working
fluid
during
machining
operations.
There
are
numerous
hydraulic
systems
used
with
machines,
depending
on
the
type
of
machine.
These
systems
will
leak
variable
quantities
of
oil
depending
on
design,
sealing
mechanisms,
operating
pressures,
and
other
factors.
Older
machines,
especially
those
that
are
not
properly
maintained,
can
leak
excessively
from
hydraulic
seals.
Facilities
D­
26
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
should
implement
scheduled
maintenance
of
machines
to
check
and
repair
sealing
mechanisms.

Reduction
of
Contamination
from
Make­
Up
Water.
Make­
up
water
contributes
to
the
dissolved
solids
content
of
the
metal­
working
fluid,
reducing
fluid
life.
This
problem
occurs
more
rapidly
when
water
with
high
TDS
is
used
for
evaporative
make­
up.
Certain
dissolved
solids
or
minerals
cause
more
problems
for
metal­
working
fluids
than
others.
For
example,
chloride
salts
and
sulfates
corrode
at
levels
of
greater
than
100
parts
per
million.
Sulfates
also
promote
the
growth
of
sulfate­
reducing
bacteria
that
cause
fluids
to
become
rancid.
When
minerals
become
concentrated
in
the
fluid,
they
can
cause
increased
corrosion,
gumming,
and
machine
wear
(
6).
Consequently,
using
hard
water
can
reduce
the
fluid
life.
Deionized
(
DI)
water
can
be
used
in
place
of
hard
water
(
DI
units
can
be
either
purchased
or
rented).

Reduction
of
Contamination
from
Sumps.
EPA
has
identified
the
following
examples
of
methods
to
reduce
contamination
from
metal­
working
fluid
sumps:

 
Steam
Cleaning
of
Sumps
.
Machine
coolant
sumps
harbor
bacteria
that
degrade
the
fluids.
If
coolant
sumps
are
not
sterilized
during
cleanouts,
residual
bacteria
may
degrade
the
fresh
coolant
added
to
cleaned
sumps.
Steam
cleaning
the
sumps
during
cleanout
can
eliminate
bacteria.

 
Sump
Modification
.
Many
coolant
sumps
are
designed
as
in­
ground
concrete
tanks,
whose
porous
concrete
surfaces
absorb
oil
and
promote
bacterial
growth.
Improving
the
design
of
the
sumps
can
extend
fluid
life.
Potential
design
changes
include
inserting
metal
tanks
and
coating
sump
walls
with
fiberglass
or
other
nonporous
material.

Reduce
Miscellaneous
Contamination.
Good
housekeeping
practices
can
extend
metal­
working
fluid
life
by
reducing
contamination.
Facilities
can
implement
housekeeping
procedures
to
keep
floor
sweepings,
solvents,
paint
chips,
soil,
rags,
paper,
and
other
debris
out
of
the
coolant
sumps.

D.
2.2.2
Extension
of
Metal­
Working
Fluid
Life
Facilities
can
implement
several
methods
to
extend
the
life
of
metal­
working
fluids.
These
include
raw
material
substitution,
equipment
modification,
and
fluid
monitoring,
as
discussed
below.

Raw
Material
Substitution.
As
discussed
above,
four
general
types
of
metal­
working
fluids
are
used
in
machining
operations.
Within
a
given
group
of
fluids,
such
as
soluble
oil,
various
formulations
are
used.
Within
each
group,
the
major
difference
from
one
fluid
to
another
is
the
 
additive
package. 
Additives
are
included
in
most
metal­
working
fluid
formulations
to
improve
fluid
performance
(
e.
g.,
improve
lubricity,
reduce
friction,
or
increase
corrosion
protection)
and
increase
life
span
(
e.
g.,
reduce
bacterial
growth).
Costs
of
different
D­
27
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
metal­
working
fluids
can
vary
by
100
percent
or
more.
Fluids
with
additive
packages
that
do
not
meet
the
lubrication
and
cooling
requirements
of
the
specific
machining
operation
may
degrade
faster
than
other
metal­
working
fluids.
These
fluids
will
need
to
be
replaced
more
often
and
increase
overall
operating
costs.
These
fluids
may
also
affect
tool
life,
further
increasing
operating
costs.
Therefore,
using
the
proper
grade
metal­
working
fluids
can
increase
the
life
span
of
the
fluid,
reducing
the
generation
of
waste
machining
fluids
and
decreasing
the
overall
operating
costs.

Equipment
Modification.
EPA
has
identified
the
following
examples
of
equipment
modifications
that
can
extend
the
life
of
machining
fluids.

 
Replacement
of
Air
Agitation
With
Mechanical
Agitation
.
Some
facilities
use
air
agitation
in
central
coolant
sumps
to
constantly
mix
the
fluid
and
prevent
phase
separation
and
pooling
of
tramp
oil.
However,
air
agitation
increases
the
activity
of
aerobic
bacteria
by
adding
oxygen,
which
causes
the
bacteria
to
consume
fluid
additives.
An
alternative
method
of
mixing
is
mechanical
agitation
(
i.
e.,
pumping).
Mechanical
agitation
mixes
without
increasing
the
oxygen
concentration
of
the
coolant.

 
Removal
of
Tramp
Oil
.
Machining
fluid
life
can
be
extended
by
continuous,
in­
sump
removal
of
tramp
oil.
Facilities
can
install
continuous
oil­
skimming
devices
directly
in
the
machine
sump
to
remove
tramp
oil.
Absorbent
blankets,
fabrics,
or
pillows
can
also
remove
tramp
oil.

Fluid
Monitoring.
During
use,
the
metal­
working
fluid
undergoes
various
physical,
chemical,
and
biological
changes.
If
the
properties
of
the
fluid
are
monitored
on
a
regular
basis,
the
fluid
can
be
adjusted
before
it
is
degraded.
Parameters
measured
to
monitor
the
fluid
include:
pH,
coolant
concentration
(
using
a
refractometer
or
titration
kit),
TDS,
tramp
oil
(
visual)
and
biological
activity
(
using
dip
slides
available
from
coolant
suppliers
and
laboratories
(
6)
or
other
methods).
Facilities
can
use
these
data
to
guide
periodic
fluid
adjustments
and/
or
develop
statistical
process
control
(
SPC)
procedures.
Facilities
may
wish
to
monitor
fluid
concentration
at
least
weekly,
if
not
daily,
to
identify
contamination.
The
correct
pH
operating
range
of
most
coolants
is
8.5
to
9.5.
If
the
pH
drops
below
the
operating
range,
coolants
may
cause
rusting
and
be
prone
to
increased
biological
activity.
Dilute
concentrations
can
shorten
tool
life,
increase
biological
activity,
and
cause
rust.
Rich
concentrations
can
lead
to
foaming
and
tramp
oil
contributes
to
biological
growth.

D.
2.2.3
Metal­
Working
Fluid
Recycling
Most
metal­
working
fluids
can
be
recycled
on­
site
by
removing
contaminants
accumulated
during
use
and
storage.
Recycling
methods
include
settling,
straining,
skimming,
simple
filtration,
membrane
filtration,
coalescing,
centrifugation,
cyclone
separation,
magnetic
separation,
and
pasteurization.
Some
of
these
methods
can
be
used
in
combination
to
recover
D­
28
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
nearly
100
percent
of
the
metal­
working
fluid.
Facilities
can
purchase
recycling
equipment
or
hire
commercial
services
that
perform
on­
site
processing
(
10,11,12).
A
self­
contained
recycling
unit
can
be
purchased
that
is
specifically
designed
for
smaller
machine
shops
and
is
a
complete
sump
maintenance
and
fluid
recycling
system
in
one
unit
(
8).
In
most
cases,
facilities
can
facilitate
metal­
working
fluid
recycling
by
consolidating
the
types
of
machining
fluids
they
use
to
one
or
two
types
of
fluid.

Additional
metal­
working
fluid
can
be
recycled
by
chip
drainage.
Chip
drainage
can
account
for
up
to
50
percent
of
annual
fluid
use
(
11).
During
machining,
the
metal
chips
(
scraps)
become
coated
with
fluid.
Part
of
the
fluid
drains
from
the
chips
and
part
remains
on
the
chips.
In
many
cases,
the
chips
and
associated
fluid
drop
to
the
floor
and
are
manually
collected
in
storage
containers.
Some
machines
send
the
chips
and
fluid
to
a
storage
container
using
automated
equipment
(
e.
g.,
belt
or
pneumatic
conveyor).
Fluid
that
drains
from
chips
can
be
recycled
rather
than
discharged,
which
may
require
design
changes
of
chip
handling
and
storage
equipment.

D.
2.2.4
Design
of
the
Machine
Fluid
System
Fluids
used
in
machining
are
stored
either
in
sumps
dedicated
to
individual
machines
(
either
internal
or
external
to
the
machine),
or
in
central
sumps
that
serve
multiple
machines.
Large
machining
operations
typically
use
central
sumps,
whereas
small
machine
shops
tend
to
have
individual
sumps
for
each
machine.
Central
systems
usually
contain
three
to
five
times
greater
volume
of
fluid
per
machine
from
individual
sumps.
The
reservoir
volumes
of
most
machines
with
internal
sumps
are
typically
10
to
50
gallons.
External
sumps
serving
a
single
machine
typically
have
a
volume
of
1,000
to
2,500
gallons.
Central
sumps
may
have
volumes
that
exceed
50,000
gallons.

The
amount
of
make­
up
fluid
in
a
central
system
amounts
to
a
smaller
percentage
of
total
fluid
than
in
a
single
machine
operation.
Consequently,
the
potential
for
bacterial
degeneration
is
greater
in
central
systems
as
the
bacteria
have
a
longer
time
in
which
to
degrade
the
fluid
(
9).
Further,
central
sumps
are
often
unlined
concrete
basins,
whose
porous
walls
harbor
bacteria
and
prevent
complete
disinfecting
during
cleanouts.
This
reduces
the
time
needed
for
the
bacteria
to
become
reestablished
(
11).
Additionally,
the
larger
pumps
used
in
central
systems
keep
the
tramp
oils
suspended
in
the
fluid
so
they
do
not
readily
 
float
out, 
adding
to
further
bacterial
attack.
Central
systems
may
require
more
maintenance
than
dedicated
sumps
to
prevent
bacterial
growth.

D.
2.2.5
Machining
Operations
Performed
The
ratio
of
scrap
metal
(
e.
g.,
chips)
generated
to
fluid
used
varies
among
machining
operations.
For
example,
metal
cutting
may
generate
large
pieces
of
scrap
metal
using
a
small
volume
of
fluid,
whereas
a
milling
operation
usually
produces
a
much
smaller
mass
of
chips
for
the
same
volume
of
fluid.

D­
29
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
2.2.6
Base
Material
Being
Machined
The
type
of
base
material
being
machined
affects
the
quantity
of
metal­
working
fluid
used.
The
hardness
of
base
materials
varies,
which
in
turn
affects
the
speed
at
which
the
base
metal
can
be
removed.
Harder
metals
require
more
fluid
than
softer
metals
for
the
same
operation.

D.
2.2.7
Climatic
Conditions
The
temperature
of
the
shop
can
affect
the
life
span
of
metal­
working
fluid
in
that
warmer
temperatures
may
foster
the
growth
of
certain
bacteria.

D.
2.2.8
Design
and
Age
of
Machines
The
design
and
age
of
machines
may
affect
the
quantity
of
hydraulic
oil
that
is
leaked
to
the
metal­
working
fluid
during
machining
operations.
Numerous
hydraulic
systems
are
used
with
machines.
These
systems
will
leak
variable
amounts
of
oil
depending
on
design,
sealing
mechanisms,
operating
pressures,
and
other
factors.
Older
machines,
especially
those
that
are
not
properly
maintained,
can
have
hydraulic
seals
that
excessively
leak.

D.
2.2.9
Uniform
Coolant
Use
Minimizing
the
number
of
different
machine
coolants
used
at
a
facility
reduces
the
chance
of
formulation
errors.
When
employees
are
familiar
with
fluid
properties
and
coolant
formulation
chemistry,
it
is
less
likely
that
coolant
batches
will
be
prepared
incorrectly,
which
many
times
requires
the
entire
batch
to
be
discharged
to
the
on­
site
wastewater
treatment
facility.
Facilities
may
also
save
money
by
purchasing
larger
volumes
of
coolant
(
i.
e.,
economies
of
scale).

Painting
Operations
Paint
is
applied
to
a
base
material
for
protective
and
decorative
reasons
in
various
forms,
including
dry
powder,
solvent­
diluted
formulations,
and
water­
borne
formulations.
There
are
various
methods
of
application,
the
most
common
being
immersion
and
spraying.
Water
is
used
in
painting
operations
in
paint
booth
water­
wash
systems
(
water
curtains),
in
water­
borne
formulations,
in
electrophoretic
painting
solutions
and
rinses,
and
in
clean­
up
operations.
This
discussion
is
directed
at
water
use
in
spray
painting
booths;
however,
this
subsection
also
provides
some
information
on
rinsing
following
electrophoretic
painting
and
water
clean­
up.

D.
3.1
Wastewater
Generation
from
Painting
Operations
In
spray
painting,
an
organic
coating
is
applied
to
a
product.
During
manufacturing
operations,
spray
painting
is
usually
performed
in
a
booth
to
control
the
introduction
of
contaminants
and
the
release
of
solvent
and
paint
to
the
work
place
and
D­
30
D.
3
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
environment,
and
to
reduce
the
likelihood
of
explosions
and
fires.
Paint
booths
are
categorized
into
two
types
(
dry
filter
or
water
wash)
and
by
the
method
of
collecting
the
overspray
(
i.
e.,
the
paint
that
misses
the
product
during
application).
The
type
of
booth
design
selected
depends
mainly
on
production
requirements,
including
part
size
and
configuration,
production
rate
and
transfer
efficiency,
the
material
being
sprayed,
and
finish
quality
requirements.

Dry­
filter
booths
use
filters
to
screen
out
the
paint
solids,
by
pulling
prefiltered
air
through
the
booth,
past
the
spraying
operation,
and
through
the
filter.
The
air
entrains
the
overspray
and
is
pulled
through
the
filter,
which
collects
the
paint.
Solvent
evaporates
from
the
paint,
leaving
the
paint
solids
on
the
filter.
Filters
are
periodically
replaced
when
they
become
laden
with
paint
solids
and
the
air
flow
through
them
is
restricted.
Dry­
filter
booths
are
most
often
used
when
paint
usage
does
not
exceed
20
gallons/
8­
hour
shift/
10
feet
of
chamber
width
(
13).
At
higher
usage
rates,
the
frequency
of
filter
changes
greatly
increases
operating
costs
(
i.
e.,
filter,
filter
disposal,
cost,
and
labor).

The
only
water
used
with
dry
filter
units
is
to
clean
painting
equipment
(
e.
g.,
guns
and
lines)
when
water­
borne
paints
are
used.
The
operation
of
dry­
filter
units
is
essentially
dry
when
solvent­
based
paints
are
used.

Water­
wash
booths
use
a
 
water
curtain 
to
capture
paint
overspray.
Air
containing
entrained
paint
overspray
is
pulled
through
a
circulating
water
stream,
which
 
scrubs 
the
overspray
from
the
air.
There
are
two
primary
types
of
water­
wash
booths,
side­
draft
and
downward­
draft.
The
basic
difference
between
the
two
types
is
the
way
the
air
moves
through
the
system
to
draw
the
paint
overspray
in
for
capture
(
14,15).
Small
operations
typically
use
side­
draft
units
and
large
and/
or
continuous
operations
use
downward­
draft
units.

Water­
wash
booths
use
a
water
stream
that
recirculates
from
a
sump
or
tank
with
a
typical
capacity
of
200
to
5,000
gallons
or
more.
Downward­
draft
systems
normally
contain
much
larger
volumes
of
water
than
side­
draft
systems.
Water
is
periodically
added
to
the
system
as
make­
up
for
evaporative
losses.
The
sump
water
is
periodically
discharged,
usually
during
general
system
cleaning
or
maintenance.
The
discharge
rate
depends
on
various
factors,
including
booth
design,
paint
type,
overspray
rate,
and
the
water
treatment
methods
used.
Water
is
also
used
to
clean
the
painting
equipment
and
the
paint
booth.
Booth
cleanup
may
involve
using
paint
stripper
to
remove
dried
paint
from
the
walls
of
the
booth
and
the
piping
system.

A
common
practice
in
water­
wash
booth
operation
is
to
immediately
detacify
suspended
paint
solids
to
reduce
maintenance
problems
and
to
subsequently
separate
and
remove
the
solids
from
the
water.
The
organic
resins
that
make
up
the
bulk
of
the
paint
coating
are
insoluble
in
water
and
tend
to
stay
tacky
if
not
treated
with
some
other
material
added
to
the
water
(
14,15).
If
left
untreated,
the
tacky
solids
can
plug
recirculation
pipes
and
pumps
and
adhere
to
wetted
surfaces
of
the
booth.
Dissolved
solids
are
either
immediately
precipitated
and
flocculated,
removed
by
water
treatment,
or
discarded
when
the
sump
is
discharged.

D­
31
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Solids
can
be
detacified
and
removed
in
various
ways,
depending
on
the
type
of
paint
used
and
the
booth
design.
Detacification
chemicals
include
sodium
hydroxide
(
caustic),
metal
salts,
clay,
and
polymers.
Depending
on
the
type
of
paint
and
the
detacification
chemical,
the
paint
solids
may
either
disperse
or
agglomerate.
Agglomerated
solids
may
either
sink
or
float.
In
solids
dispersal,
the
suspended
solids
increase
in
concentration
as
overspray
enters
the
water.
Subsequently,
another
chemical
is
added
to
the
water
that
causes
the
dispersed
solids
to
agglomerate
into
a
dense
floc,
which
is
then
removed.

There
are
various
ways
to
remove
paint
solids
from
the
booth
water­
wash
system.
These
removal
technologies
vary
in
sophistication,
automation,
efficiency
(
removal
and
separation),
and
capital
and
operating
costs.
The
most
common
methods
include
passive
settling,
skimming,
screening,
filtration
(
bag,
roll
bed,
press),
and
centrifugal
methods
(
hydrocyclone,
centrifuge).

Besides
spray
painting,
another
common
method
of
painting
is
electrophoretic
painting
(
also
known
as
electrocoating
or
electrodeposition),
which
is
the
process
of
coating
a
work
piece
by
making
it
either
anodic
or
cathodic
in
a
bath
that
is
generally
an
aqueous
emulsion
of
the
coating
material.
The
electrophoretic
painting
bath
contains
stabilized
resin,
pigment,
surfactants,
and
sometimes
organic
solvents
in
water.
Electrophoretic
painting
is
used
primarily
for
primer
coats
(
e.
g.,
bodies
for
motor
vehicles
or
mobile
industrial
equipment)
because
it
gives
a
fairly
thick,
highly
uniform,
corrosion­
resistant
coating
in
relatively
little
time.
During
this
process,
precleaned
parts
carrying
an
electrical
charge
are
immersed
into
the
coating
tank
(
paint)
and
then
through
a
rinsing
system.
Rinsing
removes
excess
paint
(
drag­
out)
from
the
parts.
The
typical
rinsing
procedure
is
a
three­
stage
countercurrent
cascade
rinse,
and
may
include
both
dip
and
spray
rinsing.
Typically,
the
final
rinse
is
performed
with
deionized
water.

Ultrafiltration
is
commonly
used
to
separate
and
recover
paint
solids
and
recycle
rinse
water,
by
counter
flowing
the
rinse
water
into
the
painting
bath
and
running
the
bath
through
the
ultrafilter.
The
ultrafilter
removes
excess
water
from
the
bath,
recycles
the
paint
solids
to
the
bath,
and
recycles
the
water
(
permeate)
to
the
rinse
system.
Occasional
blowdown
of
rinse
water
is
needed
to
purge
the
system
of
contaminants.
Processing
the
rinse
water
through
a
reverse
osmosis
unit
can
reduce
the
volume
of
wastewater
discharged
(
16).

D.
3.2
Pollution
Prevention
and
Water
Conservation
Practices
for
Painting
Operations
EPA
has
identified
three
categories
of
pollution
prevention
and
water
conservation
practices
that,
if
implemented,
can
reduce
or
eliminate
wastewater
discharges
from
painting
operations:
practices
to
reduce
the
quantity
of
paint
entering
the
water
system;
recycling
technologies
for
paint
booth
water;
and
conversion
of
water­
wash
booths
to
dry­
filter
booths.
These
are
discussed
in
this
subsection
and
summarized
in
Table
D­
11.
It
is
possible,
however,
that
facilities
can
reduce
or
eliminate
wastewater
discharges
using
different
practices
than
those
described
here.

D­
32
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
Table
D­
11
Potential
Pollution
Prevention
and
Water
Conservation
Methods
Applicable
to
Painting
Operations
Pollution
Prevention/
Water
Conservation
Method
Examples
Applicability
Reduce
the
Quantity
of
Paint
Entering
the
Water
System
Improve
spray
painting
operating
practices
Provide
operator
training
to
improve
racking
and
positioning
of
parts
to
reduce
overspray,
assure
proper
selection
of
nozzle
for
efficient
spray
pattern,
improve
work
scheduling
and
reduce
clean­
outs,
improve
housekeeping.
Applicable
to
all
spray
painting
operations.

Improve
paint
transfer
efficiency
Replace
inefficient
conventional
compressed
air
spray
equipment
with
high­
velocity/
low­
pressure
equipment.
Applicable
to
most
existing
spray
painting
operations
using
conventional
equipment.
Will
require
some
retraining
of
operators.

Install
gun
cleaning
station
Use
gun­
cleaning
station
to
clean
guns
and
lines.
Can
prevent
spraying
of
cleaning
fluid/
paint
into
booth.
Applicable
to
most
solvent­
based
painting
operations.

Recycle
Paint
Booth
Water
Recycle
paint
booth
water
through
solids
removal
Use
booth
water
maintenance
system
that
removes
paint
solids.
Applicable
technologies
include
weirs,
filters,
and
centrifuges.
Applicable
to
most
water­
wash
booths.
Usually
requires
treatment
of
booth
water
with
chemicals
to
produce
solids
that
can
be
separated
from
water.

Use
Dry­
Filter
Booths
Use
dry­
filter
booths
instead
of
water­
wash
booths
Convert
existing
water­
wash
booth
to
a
dry­
filter
booth.
Applicable
to
booths
with
low
to
moderate
paint
usage.
In
cases
of
high
paint
usage,
dry
filters
clog
too
quickly.

Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.

D­
33
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
3.2.1
Reducing
the
Quantity
of
Paint
Entering
the
Water
System
Facilities
can
implement
various
methods
to
reduce
the
quantity
of
paint
entering
the
water
system.
Three
of
these
methods
are
discussed
below.

Improving
Spray
Painting
Operating
Practices.
Facilities
can
implement
various
practices
that
reduce
the
quantity
of
paint
and
other
material
entering
the
water
system
of
a
paint
booth
and
thereby
reduce
the
need
to
discharge
wastewater.
Generally,
implementing
these
practices
requires
only
operator
training.
These
practices
include:
racking
and
positioning
parts
to
minimize
overspray;
selecting
the
proper
nozzle
for
an
efficient
spray
pattern;
scheduling
work
to
reduce
color
changes
and
associated
clean­
outs
of
guns,
lines,
and
pots;
and
housekeeping
to
prevent
painting
wastes
and
foreign
materials
from
entering
the
booth s
water
system.

Improving
Transfer
Efficiency.
The
transfer
efficiency
(
i.
e.,
spray
efficiency)
is
the
amount
of
coating
that
is
applied
to
the
part
divided
by
the
amount
of
coating
that
is
sprayed
from
the
gun.
It
is
reported
as
a
percentage.
The
transfer
efficiency
depends
on
several
factors,
including
the
spraying
equipment,
part
size
and
configuration,
paint
type,
and
operating
methods.
Improving
the
transfer
efficiency
can
reduce
booth
water
processing
requirements.

During
the
past
15
to
20
years,
spraying
equipment
has
improved,
primarily
in
response
to
more
stringent
air
pollution
regulations
and
rising
paint
costs.
One
of
the
key
improvements
has
been
replacement
of
conventional
compressed
air
spray
equipment
by
more
efficient
equipment.
In
terms
of
transfer
efficiency,
the
common
types
of
spray
equipment
are
ranked
as
follows
(
shown
in
order
of
increasing
efficiency
with
relative
transfer
efficiencies
shown
in
parenthesis):
conventional
compressed
air
(
25
percent),
airless
(
35
percent),
air
assisted
airless
(
45
percent),
electrostatic,
(
65
percent),
and
high­
volume/
low­
pressure
(
HVLP)
(
80
percent)
(
17).
The
HVLP
equipment
has
been
widely
implemented
due
to
the
high
transfer
efficiency,
as
well
as
the
low
cost
of
converting
from
conventional
compressed
air
equipment.
The
cost
is
primarily
for
the
spray
guns,
since
the
compressors
and
other
equipment
are
the
same
as
for
conventional
compressed
air
painting
equipment.

Installing
Gun
Cleaning
Station.
After
use,
spray­
painting
equipment
must
be
cleaned
to
prevent
a
buildup
of
paint
solids.
Spray
guns
are
often
cleaned
by
spraying
solvent
through
the
lines
and
guns
and
into
the
booth.
However,
this
practice
increases
the
amount
of
paint
entering
the
booth s
water
system
and
increases
emissions
of
volatile
organic
compounds
(
VOCs).
An
alternative
practice
is
to
install
gun­
cleaning
stations.
A
commercial
gun­
cleaning
unit
is
designed
to
sit
on
top
of
a
55­
gallon
drum.
The
gun
is
connected
to
the
solvent
tank
and
the
drum.
Solvent
is
drawn
through
the
gun
and
exits
into
the
drum,
where
it
can
be
recovered
by
distillation
(
18).

D.
3.2.2
Booth
Water
Recycle
Various
methods
and
equipment
can
reduce
or
eliminate
the
discharge
of
the
water
used
in
water­
wash
booths.
These
methods
and
equipment
prevent
the
continuous
D­
34
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
discharge
of
booth
waters
by
conditioning
(
i.
e.,
adding
detacifiers
and
paint­
dispersing
polymers)
and
removing
paint
solids.
The
least
efficient
paint
booth
water­
wash
system,
in
terms
of
water
use,
is
one
where
the
paint
solids
are
not
conditioned
and
accumulate
until
booth
water
must
be
replaced.
Cleaning
such
systems
typically
involves
draining
or
pumping
the
water
from
the
booth
reservoir
and
contract
hauling
the
entire
waste
product.
Due
to
high
operating
costs
and
downtime,
this
procedure
is
usually
used
only
by
low­
production
operations.
Moderate­
and
high­
production
operations
need
daily,
if
not
continuous,
booth
water
maintenance
to
conserve
water.
The
most
basic
form
of
booth
water
maintenance
is
removing
paint
solids
by
manual
skimming
and/
or
raking.
These
solids
can
be
removed
without
water
conditioning
since
some
portion
of
solvent­
based
paints
usually
floats
and/
or
sinks.
With
the
use
of
detacifiers
and
paint­
dispersing
polymer
treatments,
facilities
can
implement
more
advanced
methods
of
solids
removal.
Some
common
methods
are
discussed
below.

Wet­
Vacuum
Filtration.
Wet­
vacuum
filtration
units
consist
of
an
industrial
wet­
vacuum
head
on
a
steel
drum
containing
a
filter
bag.
The
unit
vacuums
paint
sludge
from
the
booth.
The
solids
are
filtered
by
the
bag
and
the
water
is
returned
to
the
booth.
Large
vacuum
units
are
also
commercially
available
that
can
be
moved
from
booth
to
booth
by
forklift
or
permanently
installed
near
a
large
booth.

Tank­
Side
Weir.
A
weir
attached
to
the
side
of
a
side­
draft
booth
tank
allows
floating
material
to
overflow
from
the
booth
and
be
pumped
to
a
filtering
tank
for
dewatering
(
14,15).

Consolidator.
A
consolidator
is
a
separate
tank
into
which
booth
water
is
pumped.
The
water
is
then
conditioned
by
adding
chemicals.
Detacified
paint
floats
to
the
surface
of
the
tank,
where
it
is
skimmed
by
a
continuously
moving
blade.
The
clean
water
is
recycled
to
the
booth
(
14,15).

Filtration.
Various
types
of
filtration
units
are
used
to
remove
paint
solids
from
booth
water.
The
booth
water
is
pumped
to
the
unit
where
the
solids
are
separated,
and
the
water
is
returned
to
the
booth.
The
simplest
filtration
unit
consists
of
a
gravity
filter
bed
with
paper
or
cloth
media.
Vacuum
filters
are
also
used,
some
of
which
require
precoating
with
diatomaceous
earth
(
14,15).

Centrifuge
Methods.
Two
common
types
of
centrifugal
separators
are
the
hydrocyclone
and
the
centrifuge.
The
hydrocyclone
is
used
to
concentrate
solids.
The
paint
booth
water
enters
a
cone­
shaped
unit
under
pressure
and
spins
around
the
inside
surface.
The
spinning
increases
the
gravity,
which
causes
most
of
the
solid
particles
to
be
pulled
outward
to
the
walls
of
the
cone.
Treated
water
exits
the
top
of
the
unit
and
the
solids
exit
the
bottom.
Some
systems
have
secondary
filtration
devices
to
further
process
the
solids.
The
centrifuge
works
in
a
similar
manner,
except
that
the
booth
water
enters
a
spinning
drum,
which
imparts
the
centrifugal
force
needed
to
separate
the
water
and
solids.
Efficient
centrifugation
requires
close
control
of
the
booth
water
chemistry
to
assure
a
uniform
feed.
Also,
auxiliary
equipment
such
as
booth
water
agitation
equipment
may
be
needed.

D­
35
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
3.2.3
Conversion
of
Water­
Wash
Booths
to
Dry­
Filter
Booths
Water­
wash
booths
can
be
converted
to
or
replaced
by
dry­
filter
booths.
The
dry­
filter
booths
have
the
potential
to
eliminate
the
wastewater
discharge,
but
they
create
a
solid
wastestream.
The
choice
between
using
a
water­
wash
booth
or
a
dry­
filter
booth
is
primarily
based
on
the
amount
of
overspray.
It
is
usually
cost­
effective
to
use
a
dry­
filter
booth
when
paint
usage
does
not
exceed
20
gallons/
8­
hour
shift/
10
feet
of
chamber
width
(
13).

A
1989
U.
S.
Navy
study
concluded
that
conversion
from
wet
to
dry
booths
can
be
cost­
effective
for
a
range
of
operations.
This
study
included
a
survey
of
military
and
industrial
facilities
that
have
successfully
converted
and
an
economic
analysis
based
on
typical
Navy
painting
operational
parameters
(
1).

D.
3.3
Solvent,
Paint
Solids,
and
Other
Components
of
Paint
The
chemical
make­
up
of
the
paint
can
impact
wastewater
generation.
The
recirculated
water
in
a
water­
wash
booth
contains
the
various
constituents
of
the
paint(
s)
being
applied.
With
most
solvent
formulations,
the
solvents
(
e.
g.,
xylene,
toluene,
methylene
chloride)
are
not
water­
soluble,
but
can
be
water­
miscible.
Some
exceptions,
such
as
acetone
and
methyl
ethyl
ketone
(
MEK),
are
water­
soluble.
However,
in
most
cases,
the
solvents
are
volatile
and
evaporate
over
time
and
exit
the
booth
through
the
air
exhaust
system.
The
organic
resins
that
make
up
the
bulk
of
the
paint
coating
are
insoluble
in
water
and
tend
to
stay
tacky
if
not
treated
with
some
additional
material
introduced
to
the
water
(
14,15).
If
left
untreated,
the
tacky
solids
can
plug
recirculation
pipes
and
pumps
and
adhere
to
wetted
surfaces
of
the
booth.
Other
paint
additives,
such
as
wetting
agents,
pigments,
and
heavy
metals
(
e.
g.,
zinc
and
chromium
salts)
may
be
soluble
in
water.
These
constituents
can
be
made
partly
insoluble
and
removed
by
adjusting
the
chemistry
of
the
water.

Water­
based
paints
present
two
problems
with
regard
to
water
use.
First,
these
paints
disperse
in
water
rather
than
agglomerate
like
solvent­
based
paints,
making
the
maintenance
of
paint
booth
waters
more
difficult
(
14,15).
Second,
water
is
used
to
clean
spraying
equipment
when
water­
based
paints
are
applied,
which
may
generate
wastewater.
A
typical
equipment­
cleaning
procedure
is
to
flush
with
water,
then
solvent,
then
water
(
2).

D.
3.4
Paint
Booth
Maintenance
Requirements
Water­
wash
paint
booths
are
periodically
shut
down
for
maintenance,
which
usually
involves
removing
the
water
in
the
booth.
Various
conditions
can
exist
that
may
necessitate
discharging
the
water,
including
odor,
bacterial
growth,
foaming,
TDS
buildup,
and
the
presence
of
corrosion
and
scale
constituents.

Booth
maintenance
typically
involves
incidental
repairs
and
cleaning
the
booth
surfaces
and
piping
system.
Often
facilities
do
maintenance
according
to
a
schedule,
but
periodic
repairs
may
also
necessitate
an
unplanned
shut­
down
and
clean­
out.
A
common
clean­
out
D­
36
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
procedure
is
to
remove
the
accumulated
paint
solids
from
the
water,
transfer
the
water
to
a
holding
tank,
and
return
the
water
after
the
maintenance
is
completed.
Alternate
methods
are
draining
the
booth
water
to
a
sewer
or
wastewater
treatment
system
or
having
it
hauled
to
a
disposal
site.
Systems
with
accumulated
paint
solids
on
the
wetted
surfaces
of
the
booth
and
in
the
piping
system
can
be
cleaned
by
circulating
an
alkaline
cleaner
or
other
chemical
for
dissolving
paint.
Since
the
amount
of
water
discharged
from
water­
wash
paint
booths
is
a
function
of
the
system s
maintenance
requirements,
newer
systems
that
require
less
maintenance
will
discharge
less
water.
Therefore,
one
pollution
prevention
option
for
water­
wash
paint
booths
is
to
install
new
systems
or
upgrade
existing
systems
to
limit
maintenance
requirements.

Cleaning
Operations
Cleaning
operations
include
aqueous
degreasing,
acid
treatment,
alkaline
treatment,
and
electrolytic
cleaning.
Depending
on
the
chemicals,
equipment,
and
procedures
used,
these
processes
are
commonly
referred
to
as
immersion,
spray,
or
electrolytic
alkaline
cleaning;
immersion,
spray,
or
electrolytic
acid
cleaning
or
pickling;
ultrasonic
cleaning;
and
emulsion
cleaning
and
parts
washing.

Many
MP&
M
facilities
implement
pollution
prevention
and
water
conservation
methods
and
technologies
that
result
in
low
cleaning
wastewater
discharge
rates,
and
in
some
cases,
eliminate
the
discharge
of
cleaning
solutions.
Pollution
prevention
and
water
conservation
practices
are
applicable
to
all
cleaning
operations;
however,
process­
related
factors
and
site­
specific
conditions
may
restrict
the
utility
of
certain
methods.
This
subsection
identifies
pollution
prevention
and
water
conservation
practices
and
technologies
applicable
to
cleaning
operations.

D.
4.1
Wastewater
Generation
From
Cleaning
Operations
MP&
M
facilities
commonly
perform
cleaning
as
a
stand­
alone
operation
or
in
combination
with
other
proposed
MP&
M
operations
such
as
anodizing,
electroplating,
conversion
coating,
and
painting.
Cleaning
removes
surface
contaminants
that
affect
the
appearance
of
parts
or
the
ability
to
further
process
the
parts.
Various
types
of
acidic
and
alkaline
solutions
are
used
for
cleaning.

Alkaline
cleaners
are
usually
impacted
by
organic
pollutants
such
as
oil
and
grease.
The
effectiveness
of
most
alkaline
cleaners
is
reduced
when
the
oil
concentration
of
the
bath
is
in
the
range
of
1
to
5
g/
L
or
more.
Oil
and
grease
enters
the
alkaline
cleaning
bath
on
the
parts
being
processed.
The
rate
of
oil
buildup
depends
on
the
production
rate
(
measured
in
square
feet
per
day)
and
the
quantity
and
characteristics
of
the
contamination
on
the
parts.
Acid
treatment
solutions
and,
to
a
lesser
extent,
alkaline
treatment
solutions
accumulate
dissolved
metals
from
corrosion
of
the
base
metals
being
processed.
The
dissolved
metal
reduces
the
strength
of
the
cleaning
bath.
As
dissolved
metal
increases,
additional
acid
or
alkaline
solution
is
added;
however,
at
certain
metal
concentrations,
the
bath
is
no
longer
usable.
The
tolerable
concentration
of
dissolved
metals
depends
mostly
on
the
type
of
acid
or
alkaline
solution
and
the
D­
37
D.
4
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
function
of
the
bath.
The
buildup
rate
of
dissolved
metal
depends
primarily
on
the
production
rate,
type
and
concentration
of
acid
or
alkaline
solution,
type
of
base
metal,
duration
of
cleaning
cycle,
and
bath
temperature.

D.
4.2
Pollution
Prevention
and
Water
Conservation
Practices
for
Cleaning
Operations
EPA
identified
three
categories
of
pollution
prevention
and
water
conservation
practices
that,
if
implemented,
can
reduce
or
eliminate
wastewater
discharges
from
cleaning
operations:
housekeeping
and
maintenance,
oil
and
suspended
solids
removal,
and
dissolved
solids
removal.
These
are
discussed
in
this
subsection
and
summarized
in
Table
D­
12.
It
is
possible,
however,
that
facilities
can
reduce
or
eliminate
wastewater
discharges
using
different
practices
than
those
described
here.

Table
D­
12
Potential
Pollution
Prevention
and
Water
Conservation
Methods
Applicable
to
Cleaning
Operations
Pollution
Prevention/
Water
Conservation
Method
Examples
Applicability
Housekeeping
and
maintenance
Check
the
accuracy
of
temperature
controls;
remove
sludge
build­
up
from
tanks,
heat
coils
and
temperature
regulators;
retrieve
parts,
racks,
etc.
dropped
into
the
tanks;
and
check
the
integrity
of
tanks
and
tank
liners.
Applicable
to
all
cleaning
operations.

Oil
and
suspended
solids
removal
Technologies
used
to
remove
oil
and
suspended
solids
from
cleaning
solutions,
thereby
extending
the
useful
life
span
of
the
solutions
(
e.
g.,
skimmers,
coalescers,
cartridge
and
membrane
filters).
Suspended
solids
removal
equipment
(
e.
g.,
cartridge
filters)
are
applicable
to
nearly
all
baths.
The
other
types
of
equipment
are
applicable
to
most
or
all
alkaline
cleaning
baths.

Dissolved
solids
removal
Various
technologies
and
processes
that
remove
dissolved
metals
from
baths,
including
acid
sorption,
diffusion
dialysis,
and
membrane
electrolysis.
Applicable
to
acid
and
alkaline
solutions
that
become
contaminated
with
dissolved
metal,
usually
due
to
etching
of
the
basis
metal.

Source:
MP&
M
Site
Visits,
MP&
M
Surveys,
Technical
Literature.

D­
38
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
4.2.1
Housekeeping
and
Maintenance
Facilities
can
implement
various
housekeeping
and
maintenance
practices
to
reduce
the
quantity
of
cleaning
solution
discharge.
Several
of
these
practices
are
discussed
below.

Solution
Testing.
The
chemical
make­
up
of
cleaning
solutions
changes
over
time
due
to
evaporative
losses,
water
additions,
cleaning
chemical
drag­
out,
chemical
reactions,
and
drag­
in
of
impurities.
Because
of
these
factors,
cleaning
baths
lose
strength,
performance
declines,
and
solutions
require
disposal.
Many
facilities
operate
cleaning
baths
on
a
three­
step
schedule:
formulate,
use,
and
discard.
This
procedure
can
be
expensive
and
inefficient
from
a
production
standpoint,
and
generates
large
volumes
of
wastewater.
For
this
reason,
facilities
should
frequently
test
the
strength
of
the
cleaning
solution
and
appropriate
chemical
additions
needed
to
continue
using
the
solution.
By
implementing
testing
and
recordkeeping,
facilities
can
reduce
the
disposal
frequency
of
cleaning
baths.

Most
alkaline
cleaning
solutions
are
proprietary
formulations,
and
the
vendors
of
these
solutions
provide
test
methods
for
determining
the
condition
of
a
bath.
Also,
commercial
test
kits
are
available
that
include
generic
test
methods.
For
example,
the
strength
of
an
alkaline
cleaning
solution
can
be
tested
using
acid­
base
titration,
which
measures
alkalinity.
Also,
there
is
a
dual
test
method
that
indirectly
measures
the
level
of
contamination
in
the
cleaner.
This
process
consists
of
titrating
a
measured
sample
of
cleaner
(
e.
g.,
5
milliliters
(
ml)
and
then
adding
a
color
indicator
(
phenolphthalein
or
methyl
orange)
with
an
acid
of
precise
concentration
(
e.
g.,
1N
solution
of
sulfuric
acid).
Phenolphthalein
is
used
as
the
indicator
to
measure
free
alkalinity
and
methyl
orange
is
used
to
measure
total
alkalinity.
By
performing
both
tests,
the
ratio
of
total
alkalinity
to
free
alkalinity
can
be
calculated.
A
ratio
close
to
1
indicates
that
the
cleaner
is
relatively
free
of
contamination,
while
a
higher
ratio
indicates
that
contamination
exists.
Facilities
sometime
use
this
ratio
to
determine
if
they
should
discharge
a
cleaning
solution.
For
example,
a
common
guideline
used
is
that
the
solution
is
discarded
when
the
ratio
exceeds
2.0.
The
total
alkalinity/
free
alkalinity
test
method
does
not
work
for
all
cleaners.
Because
of
additives
used,
some
alkaline
cleaners
do
not
have
any
free
alkalinity.
In
such
cases,
the
facility
may
want
to
perform
more
detailed
tests
to
accurately
determine
the
contaminant
concentration
(
e.
g.,
oil
and
grease
measurement).

Similar
test
methods
exist
for
acid
cleaners.
The
most
common
parameters
in
acid
cleaner
test
programs
are
acid
concentration
and
dissolved
metal
concentration.
The
concentration
of
sulfuric
acid
or
hydrochloric
acid
in
pickling
solutions
is
usually
measured
by
titrating
a
sample
of
the
solution
with
sodium
carbonate
and
using
a
methyl
orange
indicator.
Iron
and
other
dissolved
metals
can
also
be
measured
by
titration
or
by
using
laboratory
analytical
equipment
such
as
an
atomic
adsorption
spectrophotometer.

Recordkeeping.
Maintaining
accurate
records
of
bath
additive
rates
and
bath
lives
can
help
facilities
identify
trends
in
solution
use
and
focus
on
extending
the
lives
of
those
that
are
D­
39
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
frequently
discarded.
Important
records
to
keep
are
occurrences
of
chemical
additions
and
solution
dumps,
production
throughput,
and
chemical
concentration
data.

Miscellaneous
Housekeeping
and
Maintenance.
To
obtain
consistently
good
cleaning
results
and
reduce
their
solution
discharge,
facilities
should
implement
a
regular
schedule
of
housekeeping
and
maintenance.
Tasks
should
include:
checking
the
accuracy
of
temperature
controls;
removing
sludge
buildup
from
tanks,
heating
coils,
and
temperature
regulators;
retrieving
parts,
racks,
and
other
foreign
materials
dropped
into
the
tanks;
and
checking
the
integrity
of
tanks
and
tank
liners.

D.
4.2.2
Oil
and
Suspended
Solids
Removal
Cleaning
baths
accumulate
oil
and
suspended
solids
during
use.
These
contaminants
eventually
reach
a
concentration
that
interferes
with
the
effectiveness
of
the
cleaning
process,
despite
the
fact
that
most
bath
constituents
remain
usable.
Also,
contaminated
cleaning
baths
may
carry
over
contaminants
to
subsequent
process
solutions.
As
a
result,
cleaning
baths
are
often
discarded
when
they
reach
a
certain
concentration
of
contaminants.
There
are
several
technologies
used
to
remove
oil
and
suspended
solids
from
cleaning
solutions,
thereby
extending
the
useful
life
of
the
solutions.
These
technologies
are
primarily
applicable
to
alkaline
cleaning
baths
and
are
discussed
below.

Free/
Floating
Oil
Separation
Devices.
Separation
devices
for
oil/
water
mixtures
use
the
difference
in
specific
gravity
between
oils
and
water
to
remove
free
or
floating
oil
from
wastewater.
Common
separation
devices
for
cleaning
solutions
include
skimming
devices
(
disks,
belts,
and
rotating
drum
oil
skimmers)
and
coalescers.
These
devices
are
not
suited
for
emulsified
oil
removal,
which
typically
is
addressed
through
chemical
treatment
or
membrane
filtration.

Skimming
is
a
simple
method
of
separating
floating
oil
from
cleaning
solutions.
Skimming
devices
are
typically
mounted
onto
the
side
of
a
tank
and
operate
on
a
continuous
basis.
The
disk
skimmer
is
a
vertically
rotating
disk
(
typically
12
to
24
inches
in
diameter)
that
is
partially
submerged
into
the
liquid
of
a
tank
(
typically
4
to
12
inches
below
the
surface).
The
disk
continuously
revolves
between
spring­
loaded
wiper
blades
that
are
located
above
the
surface.
The
adhesive
characteristics
of
the
floating
oil
cause
it
to
adhere
to
the
disk.
As
the
disk
surface
passes
through
the
wiper
blades,
the
oil
is
removed
and
diverted
to
a
run­
off
spout
for
collection.
Maximum
skimming
rates
typically
range
from
2
to
10
gallons
per
hour
of
oil.
Belt
and
drum
skimmers
operate
similarly,
with
either
a
continuous
belt
or
drum
rotating
partially
submerged
in
a
tank.
As
the
surface
of
the
belt
or
drum
emerges
from
the
liquid,
the
oil
that
adheres
to
its
surface
is
scraped
(
drum)
or
squeezed
off
(
belt)
and
diverted
to
a
collection
vessel.

Coalescers
separate
liquids
with
specific
gravity
differences
of
0.09
and
greater.
Coalescers
are
typically
tanks
containing
a
coalescing
media
that
accelerates
phase
separation
(
3).
A
suction
skimmer
removes
cleaning
solution
and
oil
from
the
process
tank
and
pumps
it
to
the
coalescer.
The
media
in
the
coalescers
is
a
material
such
as
polypropylene,
ceramic,
or
glass
D­
40
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
that
attracts
oil
in
preference
to
water
(
i.
e.,
oleophilic).
The
oil/
cleaner
mixture
passes
through
the
unit
and
the
oil
adheres
to
the
coalescing
media.
The
oil
forms
droplets
that
conglomerate
and
rise
to
the
surface
of
the
tank,
where
a
skimming
device
or
weir
removes
them.
According
to
Stoke s
Law,
the
rise/
fall
velocity
of
a
dispersed­
phase
droplet
is
exponentially
increased
with
the
droplet
size.
Therefore,
the
coalescing
media
separates
the
phases
more
rapidly
than
a
common
gravity
settling
device.

Media
Filtration
Methods.
Filtration
removes
suspended
solids
from
cleaning
solutions.
Common
types
of
filters
include
cartridge
filters,
precoat
diatomaceous
earth
filters,
and
sand
or
multimedia
filters.
Cartridge
filters
are
available
with
either
in­
tank
or
external
configurations;
the
in­
tank
filters
typically
are
used
for
small
tanks
and
the
external
filters
for
larger
tanks.
Most
cartridges
are
disposable;
however,
washable
and
reusable
filters
are
available,
which
further
reduce
waste
generation.
Precoat,
sand,
and
multimedia
filters
are
used
mostly
for
large
tank
applications.
The
type
of
filter
media
used
is
based
on
the
chemical
composition
of
the
bath.
All
filtration
systems
are
sized
based
on
solids
loading
and
the
required
flow
rate.
Typical
flow
rates
for
cleaning
solution
applications
are
two
to
three
bath
turnovers
per
hour.

Membrane
Filtration.
Microfiltration
and
ultrafiltration
are
membrane­
based
technologies
used
primarily
to
remove
emulsified
oil
and
other
colloids
from
cleaning
solutions.
The
solution
entering
a
microfiltration
or
ultrafiltration
unit
typically
is
prefiltered
using
media
filters
to
remove
large
particulates.
Various
devices
then
trap
or
skim
floating
oils
and
allow
heavier
solids
to
settle.
The
solution
is
pumped
into
the
membrane
compartment,
where
the
membrane
traps
remaining
oil
and
grease
while
water,
solvent
and
other
cleaning
bath
constituents
pass
through.
The
fluid
flows
parallel
to
the
membrane
with
enough
velocity
to
remove
the
reject
from
the
membrane
surface.
Ceramic
membranes
are
available
in
various
pore
sizes
ranging
from
several
hundred
angstroms
to
over
0.2
microns.
The
appropriate
pore
size
is
determined
by
the
specific
cleaner
to
be
filtered.
The
capacity
of
a
unit
is
based
on
the
total
area
and
flux
rate
of
the
membrane.
Commercially
available
units
range
in
capacity
from
less
than
260
to
more
than
1,300
gallons
per
day.

D.
4.2.3
Dissolved
Metals
Removal
Metals
become
dissolved
in
acid
and
alkaline
cleaning
solutions
as
a
result
of
corrosion
of
the
base
metal.
The
dissolved
metal
forms
salts
or
other
compounds
that
reduce
the
strength
of
the
cleaning
bath.
Technologies
used
to
remove
dissolved
metals
include
acid
sorption,
diffusion
dialysis,
and
membrane
electrolysis,
discussed
below.

Acid
Sorption.
Acid
sorption
is
an
acid
purification
technology
that
is
applicable
to
various
acid
treatment
solutions,
as
well
as
other
acidic
baths
(
e.
g.,
anodizing
baths).
The
acid
sorption
unit
resembles
an
ion­
exchange
column.
The
column
contains
a
bed
of
alkaline
anion
exchange
resin
that
separates
the
acid
from
the
metal
ions.

D­
41
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
First,
spent
acid
is
pumped
upward
through
the
resin;
the
acid
is
absorbed
by
the
resin
while
the
metal
ions
pass
through
it.
The
resulting
metal­
rich,
mildly
acidic
solution
is
collected
at
the
top
of
the
bed.
Water
is
then
pumped
downward
through
the
bed
and
desorbs
the
acid
from
the
resin.
The
purified
acid
solution
is
collected
at
the
bottom
of
the
bed.
This
technology
can
recover
approximately
80
percent
of
the
free
acid
remaining
in
a
spent
acid
treatment
solution.
Purification
can
be
performed
in
a
batch
mode,
but
is
most
effective
in
a
continuous
flow
mode
(
usually
expressed
in
terms
of
the
mass
of
metal
removed
from
the
acid
solution
per
unit
of
time).
Equipment
capacity
ranges
from
100
grams/
hour
to
several
thousand
grams/
hour.
Units
are
sized
to
remove
metal
near
or
above
the
rate
at
which
the
metal
is
being
introduced.
Typically,
a
facility
determines
a
target
level
of
metal
concentration
and
sizes
the
unit
to
maintain
that
level.

Diffusion
Dialysis.
Diffusion
dialysis
is
a
membrane
process
that
separates
metal
contaminants
from
the
acid
solution
using
an
acid
concentration
gradient
between
solution
compartments.
Anion
exchange
membranes
makeup
the
compartments.
The
membranes
are
usually
assembled
in
a
membrane
stack,
like
that
used
with
electrodialysis.
The
contaminated
acid
passes
through
one
set
of
compartments
and
deionized
water
through
the
adjacent
compartments.
Acid
is
diffused
across
the
membrane
into
the
deionized
water
whereas
metals
are
blocked
due
to
their
charge
and
the
selectivity
of
the
membrane.
Unlike
electrodialysis,
this
process
uses
no
electrical
potential.
The
acid
diffuses
because
of
the
difference
in
acid
concentration
on
either
side
of
the
membrane
(
i.
e.,
material
in
high
concentration
moves
to
an
area
of
low
concentration).

Membrane
Electrolysis.
Membrane
electrolysis
is
a
bath
maintenance
technology
that
lowers
or
maintains
the
concentration
of
metallic
impurities
in
cleaning
solutions.
This
technology
is
also
applicable
to
other
metal­
bearing
solutions
(
e.
g.,
electroplating,
anodizing,
and
stripping
solutions).
This
technology
uses
an
ion­
exchange
membrane(
s)
and
an
electrical
potential
applied
across
the
membrane(
s).
The
membrane
is
ion­
permeable
and
selective,
permitting
ions
of
a
given
electrical
charge
to
pass
through.
Cation
membranes
allow
only
cations
(
e.
g.,
copper,
nickel,
aluminum)
to
pass
from
one
electrolyte
to
another,
while
anion
membranes
allow
only
anions
(
e.
g.,
sulfates,
chromates,
chlorides,
cyanide)
to
pass
through.
Bath
maintenance
units
can
be
configured
with
cation
or
anion
membranes,
or
both.

A
typical
application
of
membrane
electrolysis
is
maintenance
of
an
acid
cleaning
solution.
The
cleaning
solution
is
placed
in
an
anode
compartment
that
is
separated
from
a
second
electrolyte
by
a
cation
membrane.
The
solution
in
the
cathode
compartment
(
i.
e.,
catholyte)
is
typically
a
dilute
acidic
or
alkaline
solution.
When
an
electrical
potential
is
applied,
the
dissolved
metals
in
the
cleaning
solution
migrate
through
the
cation
membrane
into
the
catholyte.
The
catholyte
is
periodically
discarded
when
it
becomes
saturated
with
metals.

D­
42
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
D.
4.3
Condition
of
the
Surfaces
Being
Cleaned
The
condition
of
the
parts
being
cleaned
varies
widely,
both
in
terms
of
the
types
and
quantities
of
contaminants
present
and
the
quantity
of
oil.
For
example,
some
parts
may
have
been
wiped
clean
and
have
only
a
light
deposit
of
metal­
working
fluids,
while
other
parts
may
be
heavily
coated.
Since
metal­
working
fluids
(
oils)
present
on
the
parts
are
removed
during
the
cleaning
process
(
aqueous
degreasing),
the
rate
of
oil
that
is
entering
into
the
cleaning
solution
per
square
foot
of
part
cleaned
will
vary.
The
type
of
oil
entering
the
cleaning
solution
will
also
affect
the
cleaning
fluid s
life­
span.

D.
4.4
Cleaning
Requirements
Some
processes,
such
as
electroplating,
require
a
high
degree
of
cleanliness
while
others,
such
as
phosphate
conversion
coating,
may
have
less
stringent
requirements.
The
cleaning
requirements
will
therefore
vary
within
a
facility,
as
well
as
from
facility
to
facility,
as
will
the
type
of
cleaning
process
selected.

Some
cleaning
processes
are
more
amenable
to
pollution
prevention
practices
than
others,
based
on
the
purpose
of
the
cleaning
process.
For
example,
many
electroplating
processes
require
etching
of
the
part s
surface
to
enhance
adhesion
of
the
electroplated
metal
deposit.
Surface
etching
introduces
dissolved
metal
into
the
cleaning
solution
and
will
reduce
its
life­
span.

D.
4.5
Type
of
Cleaning
Process
and
Equipment
The
life­
span
of
cleaning
solutions
depends
on
the
type
of
cleaning
process
(
i.
e.,
process
chemistry
and
cleaning
equipment).
Numerous
factors
affect
the
selection
of
a
cleaning
process,
including:
type
and
characteristics
of
contaminants
to
be
removed;
type
and
condition
of
base
metal;
size
and
configuration
of
parts;
degree
of
cleanliness
required;
processing
capabilities
at
the
site;
subsequent
operations
to
be
performed;
and
financial
considerations.

The
factors
that
most
affect
the
selection
of
process
chemistry
and
equipment
are
the
type
of
contaminants
present
on
the
parts,
type
of
base
metal,
and
the
subsequent
finishing
operation,
which
in
turn
dictate
the
cleaning
requirements.
Contaminants
present
on
parts
can
include
both
organic
and
inorganic
contaminants.
Examples
of
organic
contaminants
are
machining
fluids,
miscellaneous
oils,
waxes,
and
buffing
compounds,
which
are
typically
removed
by
solvents,
detergents,
and
alkaline
solutions.
Examples
of
inorganic
contaminants
are
scale,
smut,
and
grinding
residue,
which
are
typically
removed
by
acidic
solutions.
Various
methods
are
used
to
apply
the
cleaning
solution.
For
example,
solutions
can
be
applied
by
spraying
or
immersing,
and
can
be
applied
electrolytically
(
including
both
anodic
and
cathodic
cleaning).
Application
method
is
primarily
based
on
the
concentration
and
condition
of
the
contaminant
and
the
configuration
of
the
parts.

D­
43
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
The
base
material
of
the
parts
is
also
a
consideration
in
selecting
a
cleaning
process.
Some
base
materials
are
chemically
or
physically
altered
by
certain
cleaning
steps
because
of
oxidation,
etching,
activation,
and
hydrogen
embrittlement.
Such
changes
may
be
either
desirable
or
damaging.
The
base
material
is
also
important
in
considering
the
operating
conditions
of
the
cleaning
process
(
e.
g.,
concentration,
temperature,
current).
Further,
the
base
material
contaminates
the
cleaning
solution
(
e.
g.,
etching
during
acid
treatment)
and
therefore
affects
the
life
span
of
the
solution.

References
1.
Ayer,
Jacqueline
and
McElligott,
Anthony.
 
Navy
Paint
Booth
Conversion
Feasibility
Study
(
CR
89.004). 
Naval
Civil
Engineering
Laboratory,
January
1989.

2.
Joseph,
Ron.
 
Low­
VOC
Waterborne
Coatings, 
Metal
Finishing
Organic
Finishing
Guidebook
and
Directory
Issue
for
 
94
.
Metal
Finishing
.
Hackensack,
NJ,
May
1994.

3.
Batutis,
Edward,
F.
 
Keep
Your
Cleaners
Clean, 
Products
Finishing
.
October
1989.

4.
Kushner,
Joseph
B.
Water
and
Waste
Control
for
the
Plating
Shop
.
Gardner
Publications,
Inc.,
1976.

5.
Cushnie,
George
C.
Pollution
Prevention
and
Control
Technology
for
Plating
Operations
.
National
Center
for
Manufacturing
Sciences,
1994.

6.
Lownheim,
Frederick
A.
Electroplating
Fundamentals
of
Surface
Finishing
.
McGraw­
Hill
Book
Co.,
New
York,
NY,
1978.

7.
Murphy,
Michael,
Ed.
Metal
Finishing
Guidebook
and
Directory
Issue
for
1994
.
Metal
Finishing
.
Hackensack,
NJ,
1994.

8.
University
of
Northern
Iowa.
Cutting
Fluid
Management
in
Small
Machine
Shop
Operations
.
Iowa
Waste
Reduction
Center,
Cedar
Falls,
Iowa,
undated.

9.
Master
Chemical
Corporation.
A
Guide
to
Coolant
Management
.

10.
Higgins,
Thomas.
Hazardous
Waste
Minimization
Handbook
.
Lewis
Publishers,
Chelsa,
MI,
1989.

11.
Ebasco
Environmental.
Hazardous
Waste
Minimization
Study,
Air
Force
Plant
No.
6
.
Final
Report,
Norcross,
GA,
1992.

D­
44
D.
5
Appendix
D
­
Pollution
Prevention
and
Water
Conservation
Practices
12.
Freeman,
H.
M.
Standard
Handbook
of
Hazardous
Waste
Treatment
and
Disposal
.
McGraw­
Hill,
New
York,
NY,
1989.

13.
Thomas,
Barry,
 
Spray
Booths, 
Metal
Finishing
Organic
Finishing
Guidebook
and
Directory
Issue
for
 
94
.
Metal
Finishing
.
Hackensack,
NJ,
May
1994.

14.
Monken,
Alan.
 
Wastewater
Treatment
Systems
for
Finishing
Operations, 
Metal
Finishing
Organic
Finishing
Guidebook
and
Directory
Issue
for
 
94
.
Metal
Finishing
.
Hackensack,
NJ,
May
1994.

15.
Monken,
Alan.
 
Water
Pollution
Control
for
Paint
Booths, 
Metal
Finishing
Organic
Finishing
Guidebook
and
Directory
Issue
for
 
94
.
Metal
Finishing
.
Hackensack,
NJ,
May
1994.

16.
Brewer,
George.
 
Electrodeposition
of
Organic
Coatings, 
Metal
Finishing
Organic
Finishing
Guidebook
and
Directory
Issue
for
 
94
.
Metal
Finishing
.
Hackensack,
NJ,
May
1994.

17.
Marg,
Ken.
 
HVLP
Spray
Puts
You
into
Compliance. 
Metal
Finishing
.
March
1989.

18.
Lighthall
Industries,
LighthallTM
SC
70
Gun
Cleaner,
Lighthall
Industries,
Santa
Cruz,
CA.

D­
45
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
Appendix
E
MODIFIED
DELTA­
LOGNORMAL
DISTRIBUTION
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
Appendix
E
MODIFIED
DELTA­
LOGNORMAL
DISTRIBUTION
This
appendix
describes
the
use
of
the
modified
delta­
lognormal
distribution
to
model
treated
effluent
data
and
the
estimation
of
the
episode
long­
term
averages
and
variability
factors
used
to
calculate
the
limitations
and
standards.
1
This
appendix
describes
the
statistical
methodology
that
was
used
to
obtain
the
results
presented
in
Section
10.0.

The
modified
delta­
lognormal
distribution
is
a
generalization
of
the
familiar
two
parameter
lognormal
distribution.
This
generalized
model
can
be
used
to
model
data
sets
that
are
a
mixture
of
lognormally
distributed
values
and
values
that
are
censored
and/
or
assigned
a
constant
value
such
as
zero
or
a
sample­
specific
detection
limit.
When
only
measured
(
i.
e.,
noncensored)
values
are
present
in
the
data,
such
as
all
the
data
sets
used
to
determine
the
limitations,
the
modified
delta­
lognormal
distribution
is
equivalent
to
the
familiar
two
parameter
lognormal
distribution.
Researchers
have
concluded
that
the
lognormal
distribution
is
often
useful
for
environmental
data.
2,3
Furthermore,
EPA
has
found
that
the
lognormal
consistently
provides
a
reasonably
good
fit
to
observed
effluent
data
distributions.
4
In
this
appendix,
EPA
has
described
the
full
model,
that
is,
the
modified
delta­
lognormal
distribution,
because
it
was
used
to
calculate
some
of
the
loadings
used
in
other
analyses
supporting
this
rule.
This
model
has
been
used
to
develop
effluent
limitations
for
currently
regulated
industries
including
the
Iron
and
Steel
industry
and
the
Centralized
Waste
Treatment
industry.

Basic
Overview
of
the
Modified
Delta­
Lognormal
Distribution
EPA
selected
the
modified
delta­
lognormal
distribution
to
model
pollutant
effluent
concentrations
from
the
MP&
M
industry
in
developing
the
long­
term
averages
and
variability
factors.
A
typical
effluent
data
set
from
a
sampling
episode
or
self­
monitoring
episode
(
see
Section
3.0
for
a
discussion
of
the
data
associated
with
these
episodes)
consists
of
a
mixture
of
measured
(
detected)
and
nondetected
values.
The
modified
delta­
lognormal
distribution
is
appropriate
for
such
data
sets
because
it
models
the
data
as
a
mixture
of
measurements
that
follow
a
lognormal
distribution
and
nondetect
measurements
that
occur
with
a
certain
probability.
The
model
also
allows
for
the
possibility
that
nondetect
measurements
occur
at
multiple
sample­
specific
detection
limits.
Because
the
data
appeared
1In
the
remainder
of
this
appendix,
references
to
 
limitations 
includes
 
standards. 

2e.
g.,
see
Richard
O.
Gilbert,
Statistical
Methods
for
Environmental
Pollution
Monitoring,
Van
Nostrand
Reinhold,
New
York,
1987.

3W.
J.
Owen
and
T.
A.
DeRouen,
 
Estimation
of
the
Mean
for
Lognormal
Data
Containing
Zeroes
and
Left­
Censored
Values,
with
Applications
to
the
Measurement
of
Worker
Exposure
to
Air
Contaminants, 
Biometrics
36:
707­
719,
1980.

4See
H.
D.
Kahn
and
M.
B.
Rubin,
 
Use
of
Statistical
Methods
in
Industrial
Water
Pollution
Control
Regulations
in
the
United
States, 
Environmental
Monitoring
and
Assessment,
12:
129­
148,
1989.

E­
1
E.
1
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
to
fit
the
modified
delta­
lognormal
model
reasonably
well,
EPA
has
determined
that
this
model
is
appropriate
for
these
data.

The
modified
delta­
lognormal
distribution
is
a
modification
of
the
 
delta
distribution'
originally
developed
by
Aitchison
and
Brown.
5
While
this
distribution
was
originally
developed
to
model
economic
data,
other
researchers
have
shown
the
application
to
environmental
data.
6
The
resulting
mixed
distributional
model,
which
combines
a
continuous
density
portion
with
a
discrete­
valued
spike
at
zero,
is
also
known
as
the
delta­
lognormal
distribution.
The
delta
in
the
name
refers
to
the
proportion
of
the
overall
distribution
contained
in
the
discrete
distributional
spike
at
zero;
that
is,
the
proportion
of
zero
amounts.
The
remaining
nonzero,
noncensored
(
NC)
amounts
are
grouped
together
and
fit
to
a
lognormal
distribution.

EPA
modified
this
delta­
lognormal
distribution
to
incorporate
multiple
detection
limits.
In
the
modification
of
the
delta
portion,
the
single
spike
located
at
zero
is
replaced
by
a
discrete
distribution
made
up
of
multiple
spikes.
Each
spike
in
this
modification
is
associated
with
a
distinct
sample­
specific
detection
limit
associated
with
nondetected
(
ND)
measurements
in
the
database.
7
A
lognormal
density
is
used
to
represent
the
set
of
measured
values.
This
modification
of
the
delta­
lognormal
distribution
is
illustrated
in
Figure
1.

5Aitchison,
J.
and
Brown,
J.
A.
C.
(
1963)
The
Lognormal
Distribution.
Cambridge
University
Press,
pages
87­
99.

6Owen,
W.
J.
and
T.
A.
DeRouen.
1980.
 
Estimation
of
the
Mean
for
Lognormal
Data
Containing
Zeroes
and
Left­
Censored
Values,
with
Applications
to
the
Measurement
of
Worker
Exposure
to
Air
Contaminants. 
Biometrics,
36:
707­
719.

7Previously,
EPA
had
modified
the
delta­
lognormal
model
to
account
for
nondetected
measurements
by
placing
the
distributional
 
spike 
at
a
single
positive
value,
usually
equal
to
the
nominal
quantitation
limit,
rather
than
at
zero.
For
further
details,
see
Kahn
and
Rubin,
1989.
This
adaptation
was
used
in
developing
limitations
and
standards
for
the
organic
chemicals,
plastics,
and
synthetic
fibers
(
OCPSF)
and
pesticides
manufacturing
rulemakings.
EPA
has
used
the
current
modification
in
several,
more
recent,
rulemakings.

E­
2
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
Figure
1
The
following
two
subsections
describe
the
delta
and
lognormal
portions
of
the
modified
delta­
lognormal
distribution
in
further
detail.

Continuous
and
Discrete
Portions
of
the
Modified
Delta­
Lognormal
Distribution
The
discrete
portion
of
the
modified
delta­
lognormal
distribution
models
the
nondetected
values
corresponding
to
the
k
reported
sample­
specific
detection
limits.
In
the
model,
*
represents
the
proportion
of
nondetected
values
in
the
dataset
and
is
the
sum
of
smaller
fractions,
*
i
,
each
representing
the
proportion
of
nondetected
values
associated
with
each
distinct
detection
limit
value.
By
letting
Di
equal
the
value
of
the
ith
smallest
distinct
detection
limit
in
the
data
set
and
the
random
variable
XD
represents
a
randomly
chosen
nondetected
measurement,
the
cumulative
distribution
function
of
the
discrete
portion
of
the
modified
delta­
lognormal
model
can
be
mathematically
expressed
as:

1
Pr
(
XD
£
c)
=
d
 
d
i
0
<
c
(
E­
1)
i:
Di
£
c
The
mean
and
variance
of
this
discrete
distribution
can
be
calculated
using
the
following
formulas:

1
k
E
(
XD
)
=
 
di
Di
(
E­
2)
d
i
=
1
k
2
Var
(
XD
)
=
1
 
di(
Di
­
E
(
XD
))
(
E­
3)
d
i
=
1
E­
3
E.
2
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
The
continuous,
lognormal
portion
of
the
modified
delta­
lognormal
distribution
was
used
to
model
the
detected
measurements
from
the
MP&
M
industry
database.
The
cumulative
probability
distribution
of
the
continuous
portion
of
the
modified
delta­
lognormal
distribution
can
be
mathematically
expressed
as:

Pr[
XC
£
c]
=
F
Ø
 
ln(
c)
­
m
ø
 
(
E­
4)
º
s
ß
where
the
random
variable
XC
represents
a
randomly
chosen
detected
measurement,
M
is
the
standard
normal
distribution,
and
:
and
F
are
parameters
of
the
distribution.

The
expected
value,
E(
XC
),
and
the
variance,
Var(
XC
),
of
the
lognormal
distribution
can
be
calculated
as:

 
2
 
E
(
XC
)
=
exp
 
m
+
s
2
 
 
(
E­
5)
 
Var
(
XC
)
=[
E
(
XC
)]
2
(
exp(
s
2
)
­
1)
(
E­
6)

Combining
the
Continuous
and
Discrete
Portions
The
continuous
portion
of
the
modified
delta­
lognormal
distribution
is
combined
with
the
discrete
portion
to
model
data
sets
that
contain
a
mixture
of
nondetected
and
detected
measurements.
It
is
possible
to
fit
a
wide
variety
of
observed
effluent
data
sets
to
the
modified
delta­
lognormal
distribution.
Multiple
detection
limits
for
nondetect
measurements
are
incorporated,
as
are
measured
("
detected")
values.
The
same
basic
framework
can
be
used
even
if
there
are
no
nondetected
values
in
the
data
set
(
in
this
case,
it
is
the
same
as
the
lognormal
distribution).
Thus,
the
modified
delta­
lognormal
distribution
offers
a
large
degree
of
flexibility
in
modeling
effluent
data.

The
modified
delta­
lognormal
random
variable
U
can
be
expressed
as
a
combination
of
three
other
independent
variables,
that
is,

U
=
Iu
XD
+(
1
­
Iu
)
XC
(
E­
7)

where
XD
represents
a
random
nondetect
from
the
discrete
portion
of
the
distribution,
XC
represents
a
random
detected
measurement
from
the
continuous
lognormal
portion,
and
Iu
is
an
indicator
variable
signaling
whether
any
particular
random
measurement,
u,
is
nondetected
or
noncensored
(
that
is,
Iu
=
1
if
u
is
nondetected;
Iu
=
0
if
u
is
noncensored).
Using
a
weighted
sum,
the
cumulative
distribution
function
from
the
discrete
portion
of
the
distribution
(
equation
1)
can
be
combined
with
the
function
from
the
E­
4
E.
3
 
 
 
 
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
continuous
portion
(
equation
4)
to
obtain
the
overall
cumulative
probability
distribution
of
the
modified
delta­
lognormal
distribution
as
follows,

Pr
(
U
£
c)
=
 
d
i
+(
1­
d
)
F 
Ø
ln(
c)
­
m
ø
 
(
E­
8)
i:
Di
£
c
º
s
ß
where
Di
is
the
value
of
the
ith
sample­
specific
detection
limit.

The
expected
value
of
the
random
variable
U
can
be
derived
as
a
weighted
sum
of
the
expected
values
of
the
discrete
and
continuous
portions
of
the
distribution
(
equations
2
and
5,
respectively)
as
follows
E
(
U
)
=
d
E
(
XD
)
+(
1
­
d
)
E
(
XC
)
(
E­
9)

In
a
similar
manner,
the
expected
value
of
the
random
variable
squared
can
be
written
as
a
weighted
sum
of
the
expected
values
of
the
squares
of
the
discrete
and
continuous
portions
of
the
distribution
as
follows
22
E
(
U
2
)
=
d
E
(
XD
)
+(
1­
d
)
E
(
XC
)
(
E­
10)

Although
written
in
terms
of
U,
the
following
relationship
holds
for
all
random
variables,
U,
XD
,
and
XC
.

E
(
U
2
)
=
Var
(
U
)
+[
E
(
U
)]
2
(
E­
11)

So
using
equation
11
to
solve
for
Var(
U),
and
applying
the
relationships
in
equations
9
and
10,
the
variance
of
U
can
be
obtained
as
2
22
Var(
U
)
=
d
 
 
Var(
XD
)
+[
E(
XD
)]

 
 
+
(
1­
d
)
 
 
Var(
XC
)
+[
E(
XC
)]

 
 
­
[
E(
U)]
(
E­
12)

Episode­
specific
Estimates
Under
the
Modified
Delta­
Lognormal
Distribution
In
order
to
use
the
modified
delta­
lognormal
model
to
calculate
the
limitations,
the
parameters
of
the
distribution
are
estimated
from
the
data.
These
estimates
are
then
used
to
calculate
the
limitations.

The
parameters
d$
i
and
d$
are
estimated
from
the
data
using
the
following
formulas:

E­
5
E.
4
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
nd
d$
i
=
1
 
I(
dj
=
Di
)
nj=
1
(
E­
13)

d$
=
nd
n
where
nd
is
the
number
of
nondetected
measurements,
dj
,
j
=
1
to
nd
,
are
the
detection
limits
for
the
nondetected
measurements,
n
is
the
number
of
measurements
(
both
detected
and
nondetected)
and
I( )
is
an
indicator
function
equal
to
one
if
the
expression
within
the
parentheses
is
true
and
zero
otherwise.
The
"
hat"
over
the
parameters
indicates
that
they
are
estimated
from
the
data.
When
all
of
the
data
are
noncensored,
d$
is
equal
to
zero
and
the
modified
delta­
lognormal
distribution
is
equivalent
to
the
lognormal
distribution.

The
expected
value
and
the
variance
of
the
delta
portion
of
the
modified
delta­
lognormal
distribution
can
be
calculated
from
the
data
as:

k
E$

(
XD
)
=
1
$
 
d$
i
Di
(
E­
14)
d
i=
1
k
2
V$
ar(
XD
)
=
1
$
 
d$
i
(
Di
­
E$
(
XD
))
(
E­
15)
d
i
=
1
The
parameters
of
the
continuous
portion
of
the
modified
delta­
lognormal
distribution,

m$
and
s$
2
,
are
estimated
by
nc
ln(
xi
)
m$
=
 
i=
1
nc
nc
(
ln(
xi
)­
m$
)
2
(
E­
16)

s$
2
=
 
i=
1
nc
­
1
where
xi
is
the
ith
detected
measurement
value
and
nc
is
the
number
of
detected
measurements.
Note
that
n
=
nd
+
nc
.

The
expected
value
and
the
variance
of
the
lognormal
portion
of
the
modified
delta­
lognormal
distribution
can
be
calculated
from
the
data
as:

E$
(
XC
)
=
exp
 
 
m$
+
s$
2
 
 
(
E­
17)
 
2
 
E­
6
1
2
3
4
5
6
7
8
9
10
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
V$
ar(
XC
)
=[
E$

(
XC
)]
2
(
exp(
s$
2
)
­
1)
(
E­
18)

Finally,
the
expected
value
and
variance
of
the
modified
delta­
lognormal
distribution
can
be
estimated
using
the
following
formulas:

E$
(
U
)
=
d$
E$
(
XD
)
+(
1­
d$)
E$
(
XC
)
(
E­
19)

V$
ar(
U
)
=
d$

 
 
 
V$
ar(
XD
)
+[
E$

(
XD
)]
2
 
 
 
+(
1­
d$)

 
 
 
V$
ar(
XC
)
+[
E$
(
XC
)]
2
 
 
 
­[
E$
(
U
)]
2
(
E­
20)

Equations
17
through
20
are
particularly
important
in
the
estimation
of
episode
long­
term
averages
and
variability
factors
as
described
in
the
following
sections.
These
sections
are
preceded
by
a
section
that
identifies
the
episode
data
set
requirements.

Example:

Consider
a
facility
that
has
10
samples
with
the
following
concentrations:

The
ND
components
of
the
variance
equation
are:
Sample
number
Measurement
Type
Concentration
(
mg/
L)

ND
10
ND
15
ND
15
ND
20
NC
25
NC
25
NC
30
NC
35
NC
35
NC
40
D1
=
10,
d$
1
=
1/
10
D2
=
15,
d$
2
=
1/
5
D3
=
20,
d$
3
=
1/
10.

E­
7
$
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
Since
d$
=
2/
5,
the
expected
value
and
the
variance
of
the
discrete
portion
of
the
modified
delta­

lognormal
distribution
are
1
 
111
 
E$
(
XD
)=
2/
5
 
 
10
·
10
+
5
·
15
+
10
·
20
 
 
=
15,

1
 
111
V$
ar(
XD
)=
2/
5
 
 
10
·
(
10
­
15)
2
+
5
·
(
15
­
15)
2
+
10
·
(
20
­
15)
2
 
 
 
=
12.5.

The
mean
and
variance
of
the
log
NC
values
are
calculated
as
follows:
n
c
 
ln(
xi
)(
2
·
ln(
25)+
ln(
30)+
2
·
ln(
35)+
ln(
40))$
=
i=
1
==
3.44
n
6
c
n
c
2
 
(
ln(
xi
)­
m
)(
2
·
(
ln(
25)­
3.44)
2
)+(
ln(
30)­
3.44)
2
+(
2
·
(
ln(
35)­
3.44)
2
)
+(
ln(
40)­
3.44)
2
i
=
1s$
==
=
0.0376
nc
­
15
Then,
the
expected
value
and
the
variance
of
the
lognormal
portion
of
the
modified
delta­
lognormal
distribution
are
E$

(
XC
)=
exp
 
 
 
3.44
+
0.0376
 
 
 
=
31.779
2
V$
ar(
XC
)=[
31.779]
2
(
exp(
0.0376)
­
1)=
38.695.

The
expected
value
and
variance
of
the
modified
delta­
lognormal
distribution
are
E$
(
U)
=
2
5
·
15
+

 
 
 
1­
2
5
 
 
 
·
31.779
=
25.067
V$
ar(
U
)=
2
·
(
12.5
+
152
)
+

 
 
 
1­
2
 
·
(
38.695+
31.7792
)
­
25.0672
=
95.781.
55 
 
E­
8
2
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
E.
4.1
Episode
Data
Set
Requirements
Estimates
of
the
necessary
parameters
for
the
lognormal
portion
of
the
distribution
can
be
calculated
with
as
few
as
two
distinct
detected
values
in
a
data
set.
(
In
order
to
calculate
the
variance
of
the
modified
delta­
lognormal
distribution,
two
distinct
detected
values
are
the
minimum
number
that
can
be
used
and
still
obtain
an
estimate
of
the
variance
for
the
distribution.)

If
an
episode
data
set
for
a
pollutant
contained
three
or
more
observations
with
two
or
more
distinct
detected
concentration
values,
then
EPA
used
the
modified
delta­
lognormal
distribution
to
calculate
long­
term
averages
and
variability
factors.
If
the
episode
data
set
for
a
pollutant
did
not
meet
these
requirements,
EPA
used
an
arithmetic
average
to
calculate
the
episode
long­
term
average
and
excluded
the
dataset
from
the
variability
factor
calculations
(
because
the
variability
could
not
be
calculated).

In
statistical
terms,
each
measurement
was
assumed
to
be
independently
and
identically
distributed
from
the
other
measurements
of
that
pollutant
in
the
episode
data
set.

The
next
two
sections
apply
the
modified
delta­
lognormal
distribution
to
the
data
for
estimating
episode
long­
term
averages
and
variability
factors
for
the
MP&
M
industry.

E.
4.2
Estimation
of
Episode
Long­
Term
Averages
If
an
episode
dataset
for
a
pollutant
meets
the
requirements
described
in
the
last
section,
then
EPA
calculated
the
long­
term
average
using
equation
19.
Otherwise,
EPA
calculated
the
long­
term
average
as
the
arithmetic
average
of
the
daily
values
where
the
sample­
specific
detection
limit
was
used
for
each
nondetected
measurement.

E.
4.3
Estimation
of
Episode
Daily
Variability
Factors
For
each
episode,
EPA
estimated
the
daily
variability
factors
by
fitting
a
modified
delta­
lognormal
distribution
to
the
daily
measurements
for
each
pollutant.
The
episode
daily
variability
factor
is
a
function
of
the
expected
value,
and
the
99th
percentile
of
the
modified
delta­
lognormal
distribution
fit
to
the
daily
concentration
values
of
the
pollutant
in
the
wastewater
from
the
episode.
The
expected
value,
was
estimated
using
equation
19
(
the
expected
value
is
the
same
as
the
episode
long­
term
average).

The
99th
percentile
of
the
modified
delta­
lognormal
distribution
fit
to
each
data
set
was
estimated
by
using
an
iterative
approach.
First,
the
pollutant­
specific
detection
limits
were
ordered
from
smallest
to
largest.
Next,
the
cumulative
distribution
function,
p,
for
each
detection
limit
was
computed.
The
general
form,
for
a
given
value
c,
was:

E­
9
º
ß
º
ß
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
p
=
 
d$
i
+(
1­
d$)
F
 
Ø
 
ln(
c
s
)
$
­
m$

 
ø
 
(
E­
21)
i:
Di
£
c
where
M
is
the
standard
normal
cumulative
distribution
function.
Next,
the
interval
containing
the
99th
percentile
was
identified.
Finally,
the
99th
percentile
of
the
modified
delta­
lognormal
distribution
was
calculated.
The
following
steps
were
completed
to
compute
the
estimated
99th
percentile
of
each
data
subset:

Step
1
Using
equation
21,
k
values
of
p
at
c=
Dm
,
m=
1,...,
k
were
computed
and
labeled
pm
.

Step
2
 
The
smallest
value
of
m
(
m=
1,...,
k),
such
that
pm
$
0.99,
was
determined
and
labeled
as
pj
.
If
no
such
m
existed,
steps
3
and
4
were
skipped
and
step
5
was
computed
instead.

Step
3
Computed
p*
=
pj
­
d$
j
.

Step
4
If
p*
<
0.99,
then
P$
99
=
Dj
else
if
p*
>
0.99,
then
 
Ø
j
­
1
ø
 
 
 0.99
­
 
d$
i
 
 
P$
99
=
exp
 
 
m$
+
s$
F­
1 
 
i
=
1
  
 
 
(
E­
22)
 
 1­
d$
 
 
 
 
º
 
 ß
 
 
where
M­
1
is
the
inverse
normal
distribution
function.

Step
5
If
no
such
m
exists
such
that
pm
>
0.99
(
m=
1,...,
k),
then
 
P$
99
=
exp
 
m$
+
s$
F
­
1
Ø
 
0.99
­
d$
 ø
 
 
(
E­
23)
 
 
 1­
d$
  
 
The
episode
daily
variability
factor,
VF1,
was
then
calculated
as:

P$
99
VF1
=
E$(
U
)
(
E­
24)

Example:
 
Since
no
such
m
exists
such
that
pm
>
0.99
(
m=
1,...,
k),
 
E­
10
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
P$
99
=
exp
 
 
 
3.44
+
0.194
·
F
­
1
Ø 
0.99
­
0.4
ø 
 
 
=
47.126.
º
1­
0.4
ß 
The
episode
daily
variability
factor,
VF1,
was
then
calculated
as:

47.126
VF1
==
1.880.
25.067
To
identify
situations
producing
unexpected
results,
EPA
reviewed
all
of
the
variability
factors.
EPA
used
several
criteria
to
determine
if
the
episode
daily
variability
factors
should
be
included
in
calculating
the
option
variability
factors.
One
criteria
that
EPA
used
was
that
the
daily
variability
factors
should
be
greater
than
1.0.
A
variability
factor
less
than
1.0
would
result
in
a
unexpected
result
where
the
estimated
99th
percentile
would
be
less
than
the
long­
term
average.
This
would
be
an
indication
that
the
estimate
of
s$
(
the
log
standard
deviation)
was
unstable.
A
second
criteria
was
that
not
all
of
the
sample­
specific
detection
limits
could
exceed
the
values
of
the
noncensored
values.
All
the
episode
variability
factors
used
for
the
limitations
and
standards
met
these
criteria.

References
1.
 
Aitchison,
J.
and
J.
A.
C.
Brown.
1963.
The
Lognormal
Distribution.
Cambridge
University
Press,
New
York.

2.
 
Barakat,
R.
1976.
 
Sums
of
Independent
Lognormally
Distributed
Random
Variables. 
Journal
of
the
Optical
Society
of
America,
66:
211­
216.

3.
 
Cohen,
A.
Clifford.
1976.
Progressively
Censored
Sampling
in
the
Three
Parameter
Log­
Normal
Distribution.
Technometrics,
18:
99­
103.

4.
 
Crow,
E.
L.
and
K.
Shimizu.
1988.
Lognormal
Distributions:
Theory
and
Applications.
Marcel
Dekker,
Inc.,
New
York.

5.
 
Kahn,
H.
D.,
and
M.
B.
Rubin.
1989.
"
Use
of
Statistical
Methods
in
Industrial
Water
Pollution
Control
Regulations
in
the
United
States."
Environmental
Monitoring
and
Assessment.
Vol.
12:
129­
148.

6.
 
Owen,
W.
J.
and
T.
A.
DeRouen.
1980.
Estimation
of
the
Mean
for
Lognormal
Data
Containing
Zeroes
and
Left­
Censored
Values,
with
Applications
to
the
Measurement
of
Worker
Exposure
to
Air
Contaminants.
Biometrics,
36:
707­
719.

E­
11
E.
5
Appendix
E
­
Modified
Delta­
Lognormal
Distribution
7.
U.
S.
Environmental
Protection
Agency.
2000.
Development
Document
for
Effluent
Limitations
Guidelines
and
Standards
for
the
Centralized
Waste
Treatment
Point
Source
Category
.
Volume
I,
Volume
II.
EPA
440/
1­
87/
009.

8.
 
U.
S.
Environmental
Protection
Agency.
2002.
Development
Document
for
Effluent
Limitations
Guidelines
and
Standards
for
the
Iron
and
Steel
Manufacturing
Point
Source
Category
.
EPA­
821­
R­
02­
004.

E­
12
