Document ID: EPA-HQ-OW-2002-0033-0229
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-05-13T04:00Z

MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
INTRODUCTION
Part
III
of
the
EEBA
assesses
the
benefits
to
society
from
the
reduced
effluent
discharges
that
will
result
from
the
MP&
M
industry
regulations.
EPA
expects
that
benefits
will
accrue
to
society
in
several
broad
categories,
including
reduced
health
risks,
enhanced
environmental
quality,
and
increased
productivity
in
economic
activities
that
are
adversely
affected
by
MP&
M
industry
discharges.

This
chapter
provides
a
discussion
of
the
pollutants
of
concern
(
POCs)
,
their
effect
on
human
health,
their
environmental
effects,
a
framework
for
understanding
the
benefits
likely
to
be
achieved
by
the
MP
&
M
regulation,
and
a
qualitative
discussion
of
those
benefits.
The
following
chapters
quantify
and
estimate
the
economic
value
of
these
benefit
categories.
Appendices
I
and
H
provide
further
information
on
environmental
effects
of
MP&
M
pollutants
and
water
quality
models
used
to
assess
these
effects.
Chapter
12:
Benefit
Overview
CHAPTER
CONTENTS
12.1
.................
........
12­
2
12.1.1
teristics
of
MP&
M
Pollutants
.....
12­
2
12.1.2
ects
of
MP&
M
Pollutants
on
Human
Health
.................
..............
12­
3
12.1.3
ental
Effects
of
MP&
M
Pollutants
.................
...........
12­
7
12.1.4
ects
of
MP&
M
Pollutants
on
Economic
Productivity
.................
.........
12­
8
12.2
to
Beneficial
Outcomes
.
.
12­
9
12.3
ive
and
Quantitative
Benefits
Assessment
12­
11
12.3.1
........
12­
11
12.3.2
n
Health
Benefits
..............
12­
13
12.3.3
.................
12­
13
12.3.4
c
Productivity
Benefits
........
12­
14
12.3.5
or
Valuing
Benefit
Events
....
12­
14
Glossary
.................
.................
..
12­
16
Acronyms
.................
.................
.
12­
19
References
.................
.................
12­
20
MP&
M
Pollutants
Charac
Eff
Environm
Eff
Linking
the
Regulation
Qualitat
Overview
of
Benefit
Categories
Huma
Ecological
Benefits
Economi
Methods
f
EPA
estimated
national
benefits
expected
to
accrue
from
the
regulation
on
the
basis
of
sample
facility
data.
The
Agency
extrapolated
findings
from
the
sample
facility
analyses
to
the
national
level
using
two
alternative
extrapolation
methods:
(
1)

traditional
extrapolation
and
(
2)
post­
stratification
extrapolation.
The
traditional
extrapolation
approach
relies
on
sample
facility
weights
that
were
developed
based
on
information
about
the
economic
and
technical
characteristics
of
the
regulated
community.
This
extrapolation
approach
does
not
incorporate
information
that
could
significantly
affect
the
occurrence
and
distribution
of
regulatory
benefits,
such
as
characteristics
of
the
receiving
water
body
and
the
size
of
the
population
that
may
benefit
from
reduced
pollutant
discharges.
EPA
recognizes
that
using
a
traditional
extrapolation
method
to
estimate
national
level
benefits
may
lead
to
a
large
degree
of
uncertainty
in
benefits
estimates.
Thus,
EPA
also
used
an
alternative
set
of
sampling
weights,
based
on
a
post­
sampling
stratification
method,
to
calculate
alternative
national
estimates
of
benefits.
EPA
adjusted
the
original
sample
weights
using
two
variables
that
are
likely
to
affect
the
occurrence
and
size
of
benefits
associated
with
reduced
discharges
from
sample
MP&
M
facilities:
receiving
water
body
type
and
size,
and
the
size
of
the
population
residing
in
the
vicinity
of
the
sample
facility.
The
following
chapters
present
two
sets
of
estimates
of
benefits
expected
to
accrue
from
the
MP&
M
regulation
based
on
both
traditional
and
post­
stratification
extrapolation
approaches.
Appendix
G
of
this
report
provides
detailed
information
on
extrapolation
methods.

In
addition,
the
Agency
used
the
Ohio
case
study
results
to
develop
a
third
estimate
of
the
monetary
value
of
national
benefits.
1
EPA
extrapolated
the
Ohio
case
study
results
to
the
national
level
based
on
three
key
factors
that
affect
the
occurrence
and
magnitude
of
benefits:
(
1)
the
estimated
change
in
the
MP&
M
pollutant
loadings,
(
2)
the
level
of
recreational
activities
on
the
reaches
affected
by
MP&
M
discharges,
and
(
3)
state
level
income.
The
Agency
recognizes
that
this
method
is
not
rigorous
for
extrapolation
to
the
national
level.
Therefore,
EPA
used
this
method
only
as
a
sensitivity
analysis
(
see
Appendix
G
of
this
report
for
detail).

EPA
notes
that
effluent
limitations
guidelines
for
the
MP&
M
industry
are
technology­
based.
EPA
is
not
required
to
demonstrate
environmental
benefits
of
its
technology­
based
rules.
It
is
well
established
that
EPA
is
not
required
to
consider
receiving
water
quality
in
setting
technology­
based
effluent
limitations
guidelines
and
standards.
Weyerhaeuser
v.
Costle,

590
F.
2nd
1011,
1043
(
D.
C.
Cir.
1978)
("
The
Senate
Committee
declared
that
'[
t]
he
use
of
any
river,
lake,
stream
or
ocean
as
a
waste
treatment
system
is
unacceptable'
regardless
of
the
measurable
impact
of
the
waste
on
the
body
of
water
in
question.

Legislative
History
at
1425
(
Senate
Report).
The
Conference
Report
states
that
the
Act
'
specifically
bans
pollution
dilution
as
1
See
Chapter
21
for
a
detailed
discussion
the
Ohio
case
study.

12­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
an
alternative
to
treatment.'
"
Id.
at
284).
In
establishing
effluent
limitations
and
standards,
EPA
considers
benefits
as
one
of
the
factors
that
the
Agency
evaluates.

12.1
MP&
M
POLLUTANTS
EPA
defines
three
general
categories
of
pollutants:
priority
or
toxic
pollutants;
nonconventional
pollutants;
and
conventional
pollutants.
Priority
pollutants
(
PPs)
are
defined
as
any
of
126
named
pollutants.
2
Conventional
pollutants
include
biological
oxygen
demand
(
BOD)
,
total
suspended
solids
(
TSS)
,
oil
and
grease
(
O&
G)
,
pH,
and
anything
else
the
Administrator
defines
as
a
conventional
pollutant.
Nonconventionals
are
a
catch­
all
category
that
includes
everything
that
is
not
in
the
two
previously
described
categories.
The
naming
system
is
somewhat
confusing
in
that
some
nonconventional
pollutants
may
be
as
"
toxic"
as,
or
more
"
toxic"
than
some
of
the
PPs.

MP&
M
effluents
contain
a
variety
of
priority,
nonconventional,
and
conventional
pollutants.
The
release
of
these
pollutants
to
our
nation's
surface
water
degrades
aquatic
environments,
alters
aquatic
habitats,
and
affects
the
diversity
and
abundance
of
aquatic
life.
It
also
increases
the
health
risks
to
humans
who
ingest
contaminated
surface
waters
or
eat
contaminated
fish
and
shellfish
(
U.
S.
EPA,
1997).
A
number
of
the
pollutants
commonly
found
in
MP&
M
effluents
also
inhibit
biological
wastewater
treatment
systems
or
accumulate
in
sewage
sludge
or
sediment.

Metals
are
a
particular
concern
because
of
their
prevalence
in
MP&
M
effluents.
Metals
are
inorganic
compounds,
generally
non­
volatile
(
with
the
notable
exception
of
mercury),
and
cannot
be
broken
down
by
biodegradation
processes.
Metals
can
accumulate
in
biological
tissues,
sequester
into
sewage
sludge
in
publicly­
owned
treatment
works
(
POTWs),
and
contaminate
soils
and
sediments
when
released
to
the
environment.
Sediments
contaminated
with
metals
become
resuspended
by
dredging,
boat
propellers,
water
currents
or
wave
action,
and
storm
events,
releasing
metals
back
into
the
water
column.

Metals
can
also
become
biologically
available
and
enter
terrestrial
food
chains
once
the
sludge
is
applied
on
land.
Sludges
with
high
concentrations
of
metals
are
therefore
unsuitable
for
land
application.
Some
metals
are
quite
toxic
even
when
present
at
relatively
low
levels.

Some
of
the
inorganic
POCs
found
in
MP&
M
effluents
are
also
natural
constituents
of
water,
including
potassium,
calcium,

magnesium,
iron,
chlorine,
fluoride,
sulfate,
phosphates,
silica,
and
a
number
of
trace
metals
such
as
copper
and
zinc.

Human
and
ecological
exposure
and
risk
from
environmental
releases
of
MP&
M
pollutants
depend
on
chemical­
specific
properties,
the
mechanism
and
medium
of
release,
and
site­
specific
environmental
conditions.
Chemical­
specific
properties
include
toxicological
effects
on
living
organisms,
hydrophobicity/
lipophilicity,
reactivity
and
persisistence.
These
properties
are
described
in
sections
12.1.1
through
12.1.4.

12.1.1
Characteristics
of
MP&
M
Pollutants
EPA
sampled
MP&
M
facilities
nationwide
to
assess
the
concentrations
of
pollutants
in
MP&
M
effluents.
The
Agency
collected
samples
of
raw
wastewater
from
MP&
M
facilities
and
applied
standard
water
analysis
protocols
to
identify
and
quantify
the
pollutant
levels
in
each
sample.
EPA
used
these
analytical
data,
along
with
selection
criteria,
to
identify
132
contaminants
of
potential
concern.
3
EPA
then
evaluated
the
potential
environmental
fate
and
transport
of
these
pollutants
and
their
toxicity
to
humans
and
aquatic
receptors.
Fate
of
the
MP&
M
pollutants
was
estimated
based
on
the
propensity
of
those
pollutants
to
volatilize,
adsorb
onto
sediments,
bioconcentrate,
and
biodegrade.
Table
I.
1
in
Appendix
I
lists
MP&
M
pollutants
and
provides
data
on
human
health
concerns,
and
fate
and
effects.

EPA
used
various
data
sources
to
evaluate
pollutant­
specific
fate
and
toxicity.
To
evaluate
potential
human
health
effects,
the
Agency
relied
on
reference
doses
(
RfDs)
and
cancer
potency
slope
factors
(
SFs),
human
health­
based
water
2
The
Agency
originally
had
129
PPs,
but
3
have
been
dropped
from
the
list
bringing
the
number
of
PPs
to
126.

3
EPA
originally
identified
150
MP&
M
POCs.
Of
these
150
POCs,
the
Agency
estimated
loadings
for
132
pollutants
for
the
phase
2
proposal
and
NODA.
The
benefits
analysis
presented
in
this
chapter
and
the
following
chapters
was
based
on
132
pollutants
for
which
loadings
are
available.
The
final
regulation
covers
only
the
Oily
Wastes
subcategory
and
benefit
reductions
were
estimated
for
122
pollutants.

12­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
quality
criteria
(
WQC)
,
maximum
contaminant
levels
(
MCLs)
for
drinking
water
protection
and
other
drinking
water
related
criteria,
and
hazardous
air
pollutant
(
HAP)
and
PP
lists.
Appendix
I.
1.2
provides
short
descriptions
and
definitions
for
each
of
these
measures
of
human
health
effects.

To
evaluate
potential
fate
and
effects
in
aquatic
environments,
the
Agency
relied
on
measures
of
acute
and
chronic
toxicity
to
aquatic
species,
bioconcentration
factors
for
aquatic
species,
Henry's
Law
constants
(
to
estimate
volatility),

adsorption
coefficients
(
Koc)
(
to
estimate
association
with
bottom
sediments),
and
biodegradation
half­
lives
(
to
estimate
the
removal
of
chemicals
via
microbial
metabolism).

The
data
sources
used
in
the
assessment
include
EPA
ambient
water
quality
criteria
(
AWQC)
documents
and
updates,

EPA's
ASsessment
Tools
for
the
Evaluation
of
Risk
(
ASTER)
,
the
AQUatic
Information
REtrieval
System
(
AQUIRE)
,
and
the
Environmental
Research
Laboratory­
Duluth
fathead
minnow
database,
EPA's
Integrated
Risk
Information
System
(
IRIS
),
EPA's
Health
Effects
Assessment
Summary
Tables
(
HEAST)
,
EPA's
1991
and
1993
Superfund
Chemical
Data
Matrix
(
SCDM)
,
Syracuse
Research
Corporation's
CHEMFATE
and
BIODEG
databases,
EPA
and
other
government
reports,
scientific
literature,
and
other
primary
and
secondary
data
sources.

To
ensure
that
the
assessment
is
as
comprehensive
as
possible,
EPA
also
obtained
data
on
chemicals
for
which
physical­
chemical
properties
and/
or
toxicity
data
were
not
available
from
the
sources
listed
above.
To
the
extent
possible,

EPA
estimated
values
for
the
chemicals
using
the
quantitative
structure­
activity
relationship
(
QSAR)
model
incorporated
in
ASTER,
and
for
some
physical­
chemical
properties,
used
published
linear
regression
correlation
equations.

12.1.2
Effects
of
MP&
M
Pollutants
on
Human
Health
Individuals
are
potentially
exposed
to
MP&
M
pollutants
released
to
the
aquatic
environment
via
consumption
of
contaminated
fish.
Populations
served
by
drinking
water
utilities
located
downstream
of
effluent
discharges
from
MP&
M
facilities
are
also
exposed
to
M
P&
M
pollutants
via
contaminated
drinking
water.
Many
of
these
pollutants
may
increase
risks
to
human
health.

Based
on
the
available
human
health
toxicity
data
for
the
132
POCs
presented
in
Table
I.
1
(
Appendix
I),
EPA
found
that:
4
 
76
pollutants
are
human
system
ic
toxicants;

 
13
pollutants
with
published
SFs
are
classified
as
known,
probable,
or
possible
human
carcinogens
when
ingested
via
drinking
water
or
food.
Lead
is
also
classified
as
a
possible
human
carcinogen
in
IRIS
but
EPA
has
not
developed
a
SF
for
it
(
U.
S.
EPA,
1998/
99d);

 
36
pollutants
have
drinking
water
criteria
(
27
with
enforceable
health­
based
MCLs,
7
with
secondary
MCLs
for
taste
or
aesthetics,
and
2
with
action
levels
for
treatment);

 
35
pollutants
are
designated
as
HAP
s
in
wastewater;

 
43
pollutants
are
identified
as
PPs;
and
 
76
pollutants
have
human
health­
based
water
quality
criteria
(
WQC)
to
protect
against
the
ingestion
of
water
and
organisms
or
organisms
only
(
see
Chapter
13,
Table
13.3).

The
carcinogens
identified
by
EPA
in
MP&
M
effluent
samples
include
known
(
A),
probable
(
B1
and
B2)
and
possible
(
C)

human
carcinogens.
These
pollutants
are
associated
with
the
development
of
cancers
in
the
spleen,
liver,
kidney,
lung,

bladder,
and
skin,
among
others.
These
pollutants
and
target
organs
are
shown
in
Table
12.1.

4
Facilities
in
the
Oily
Wastes
subcategory
discharge:
75
of
the
76
systemic
toxicants;
all
13
human
carcinogens;
all
36
pollutants
with
drinking
water
criteria;
all
35
pollutants
designated
as
HAPs;
41
of
the
43
priority
pollutants;
and
75
of
the
76
pollutants
that
have
human
health­
based
water
quality
criteria.
Of
the
132
POCs
evaluated,
facilities
in
the
Oily
Wastes
subcategory
do
not
discharge
the
following
10
pollutants:
amenable
cyanide,
boron,
cadmium,
cyanide,
phosphate,
sodium,
sulfide,
total
dissolved
solids,
weak­
acid
dissociable
cyanide,

and
ziram/
cymate.

12­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
Table
12.1:
Human
Carcinogens
Evaluated,
Weight­
of­
Evidence
Classifications,
and
Target
Organs
CAS
Number
Carcinogen
Weight­
of­
Evidence
Classification
Target
Organs
62533
Aniline
B2
Spleen
7440382
Arsenic
A
Liver,
kidneys,
lungs,
bladder,

117817
Bis(
2­
ethylhexyl)
phthalate
B2
Liver
75003
Chloroethane
a
75092
Dichloromethane
B2
Liver,
lungs
75354
Dichloroethene,
1,1­
C
Inconclusive
b
123911
Dioxane,
1,4­
B2
Liver,
nasal
cavity,
gall
bladder
78591
Isophorone
C
Preputial
gland
62759
Nitrosodimethylamine,
N­
B2
Liver,
lungs,
skin,
seminal
vesicle,

lymphatic/
hematopoetic
system
86306
Nitrosodiphenylamine,
N­
B2
Bladder
tumors,
reticulum
cell
sarcomas
127184
Tetrachloroethene
B2
Liver
79016
Trichloroethene
a
67663
Trichloromethane
B2
Kidneys
skin
A
=
Human
Carcinogen
B1
=
Probable
Human
Carcinogen
(
limited
human
data)

B2
=
Probable
Human
Carcinogen
(
animal
data
only)

C
=
Possible
Human
Carcinogen
a
Pollutant
has
been
withdrawn
from
the
IRIS
database
for
additional
study.

b
There
is
equivocal
evidence
for
the
oral
route
of
exposure.
This
chemical
is
likely
a
systemic
carcinogen
via
inhalation.

Target
organs
include:
kidney,
pancreas,
skin,
mammary
gland,
and
blood
forming
elements
(
lymphoma
and
leukemia).

Source:
U.
S.
Environmental
Protection
Agency
verified
(
IRIS)
or
provisional
(
HEAST)
(
U.
S.
EPA
(
1998/
99d),
U.
S.
EPA
(
1997)).

Non­
carcinogenic
hazards
associated
with
pollutants
in
MP&
M
effluent
include
systemic
effects
(
e.
g.,
impairment
or
loss
of
neurological,
respiratory,
reproductive,
circulatory,
or
immunological
functions),
organ­
specific
toxicity
(
e.
g.,
kidney,
small
intestines,
blood,
testes,
liver,
stomach,
thyroid),
fetal
effects
(
e.
g.,
increased
fetal
mortality,
decreased
birth
weight),
other
effects
(
e.
g.,
lethargy,
cataracts,
weight
loss,
hyperactivity),
and
mortality.
These
effects
are
listed
by
pollutant
in
Table
12.2.

12­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
Table
12.2:
MP&
M
Pollutants
Exhibiting
Systemic
and
Other
Non­
Cancer
Human
Health
Effectsa
CAS
Number
Toxicant
RfD
Target
Organ
and
Effects
83329
Acenaphthene
Liver,
hepatotoxicity
67641
Acetone
Increased
liver
and
kidney
weights,
nephrotoxicity
98862
Acetophenone
General
toxicity
107028
Acrolein
Cardiovascular
toxicityc
7429905
Aluminum
Renal
failure,
intestinal
contraction
interference,
adverse
neurological
effectsd
120127
Anthracene
General
toxicity
7440360
Antimony
Longevity,
blood
glucose,
cholesterol
7440382
Arsenic
Hyperpigmentation,
keratosis
and
possible
vascular
complications
7440393
Barium
Increased
kidney
weight
65850
Benzoic
acid
General
toxicity
100516
Benzyl
alcohol
Forestomach,
epithelial
hyperplasia
7440417
Beryllium
Small
intestinal
lesions
92524
Biphenyl
Kidney
damage
117817
Bis(
2­
et
hylhexy
l
)

phthalate
Increased
relative
liver
weight
7440428
Boron
Testicular
atrophy,
spermatogenic
arrest
85687
Butyl
benzyl
phthalate
Significantly
increased
liver­
to­
body
and
liver­
to­
brain
weight
7440439
Cadmium
Significant
proteinuria
(
protein
in
urine)

75150
Carbon
disulfide
Fetal
toxicity,
malformations
108907
Chlorobenzene
Histopathologic
changes
in
liver
75003
Chloroethane
General
toxicity
7440473
Chromium
Renal
tubular
necrosis
(
kidney
tissue
decay)
d
18540299
Chromium­
hexavalent
Reduced
water
consumption
7440484
Cobalt
Heart
effectsd
7440508
Copper
Gastrointestinal
effects,
liver
necrosisd
95487
Cresol,
o­
Decreased
body
weight
and
neurotoxicity
106445
Cresol,
p­
Central
nervous
system
hypoactivity
and
respiratory
system
distress
57125
Cyanide
Weight
loss,
thyroid
effects
and
myelin
degeneration
75354
Dichloroethene,
1,1­
Toxic
effects
on
kidneys,
spleen,
lungsd;
hepatic
lesions
75092
Dichloromethane
Liver
toxicity
68122
Dimethylformamide,

N,
N­
Liver
and
gastrointestinal
system
effects
105679
Dimethylphenol,
2,4­
Clinical
signs
(
lethargy,
prostration,
and
ataxia)
and
hematological
changes
84742
Di­
n­
butyl
phthalate
Increased
mortality
51285
Dinitrophenol,
2,4­
Cataract
formation
606202
Dinitrotoluene,
2,6­
Mortality,
central
nervous
system
neurotoxicity,
blood
heinz
bodies
and
methemoglobinemia,
bile
duct
hyperplasia,
kidney
histopathology
117840
Di­
n­
octyl
phthalate
Kidney
and
liver
increased
weights,
increased
liver
enzymes
122394
Diphenylamine
Decreased
body
weight,
and
increased
liver
and
kidney
weights
100414
Ethylbenzene
Liver
and
kidney
toxicity
206440
Fluoranthene
Nephropathy,
increased
liver
weights,
hematological
alterations,
clinical
effects
86737
Fluorene
Decreased
red
blood
cell
count,
packed
cell
volume
and
hemoglobin
16984488
Fluoride
Objectionable
dental
fluorosis
(
soft,
mottled
teeth)

591786
Hexanone,
2­
Hepatotoxicity
and
nephrotoxcity
c
12­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
Table
12.2:
MP&
M
Pollutants
Exhibiting
Systemic
and
Other
Non­
Cancer
Human
Health
Effectsa
CAS
Number
Toxicant
RfD
Target
Organ
and
Effects
7439896
Iron
Liver
pathology,
diabetes
mellitus,
endocrine
disturbance,
and
cardiovascular
effects
c
78831
Isobutyl
alcohol
Hypoactivity
and
ataxia
78591
Isophorone
Kidney
pathology
7439965
Manganese
Central
nervous
system
effects
78933
Methyl
ethyl
ketone
Decreased
fetal
birth
weight
108101
Methyl
isobutyl
ketone
Lethargy,
increased
liver
and
kidney
weights
and
urinary
protein
80626
Methyl
methacrylate
Increased
kidney
to
body
weight
ratio
91576
Methylnaphthalene,
2­

7439987
Molybdenum
Increased
uric
acid
91203
Naphthalene
Decreased
body
weight
7440020
Nickel
Decreased
body
and
organ
weights
100027
Nitrophenol,
4­

59507
Parachlorometacresol
108952
Phenol
Reduced
fetal
body
weight
129000
Pyrene
Kidney
effects
(
renal
tubular
pathology,
decreased
kidney
weights)

110861
Pyridine
Increased
liver
weight
7782492
Selenium
Clinical
selenosis
(
hair
or
nail
loss)

7440224
Silver
Argyria
(
skin
discoloration)

100425
Styrene
Red
blood
cell
and
liver
effects
127184
Tetrachloroethene
Liver
toxicity,
weight
gain
7440280
Thallium
Liver
toxicity,
gastroenteritis,
degeneration
of
peripheral
and
central
nervous
systemc
7440315
Tin
Kidney
and
liver
lesions
7440326
Titanium
Considered
to
be
physiologically
inertc
108883
Toluene
Changes
in
liver
and
kidney
weights
79016
Trichloroethene
Bone
marrow,
central
nervous
system,
liver,
kidneys
4
75694
Trichlorofluoromethane
Histopathology
and
mortality
67663
Trichloromethane
Fatty
cyst
formation
in
liver
7440622
Vanadium
Kidney
and
central
nervous
system
effectsb
108383
Xylene,
m­
Central
nervous
system
hyperactivity,
decreased
body
weight
179601231
Xylene,
m­
&
p­
(
c)

95476
Xylene,
o­
Central
nervous
system
hyperactivity,
decreased
body
weight
136777612
Xylene,
o­
&
p­
(
c)

7440666
Zinc
47%
decrease
in
erythrocyte
superoxide
dismutase
(
ESOD)
concentration
in
adult
human
females
after
10
weeks
of
zinc
exposure
137304
Ziram
\
Cymate
a
Chemicals
with
EPA
verified
(
IRIS)
or
provisional
(
HEAST,
or
other
Agency
document))
human
health­
based
RfDs,
referred
to
as
 
systemic
toxicants 
(
U.
S.
EPA
(
1998/
99d),
U.
S.
EPA
(
1997)).

b
RfD
based
on
a
no­
observed­
adverse­
effect
level
(
NOAEL).
Health
effects
summarized
from
Amdur,
M.
O.,
Doul,
J.,
and
Klaassen,
C.
D.,

eds.
Cassarett
and
Doul s
Toxicology,
4th
edition,
1991.

c
Target
organ
and
effects
summarized
from
Amdur,
M.
O.,
Doul,
J.,
and
Klaassen,
C.
D.,
eds.
Cassarett
and
Doul s
Toxicology,
5th
edition,

1996.

d
Target
organ
and
effects
summarized
from
Wexler,
P.,
ed.
Encyclopedia
of
Toxicology,
Volumes
1­
3,
1998.

Source:
U.
S.
EPA
analysis.

12­
6
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
12.1.3
Environmental
Effects
of
MP&
M
Pollutants
Ecological
impacts
of
MP&
M
pollutants
include
acute
and
chronic
toxicity
to
aquatic
receptors
by
dozens
of
pollutants
present
in
MP&
M
effluents,
uptake
of
certain
pollutants
into
aquatic
food
webs,
sub­
lethal
effects
on
metabolic
and
reproductive
functions,
habitat
degradation
from
turbidity,
eutrophication,
dissolved
oxygen
depletion,
and
loss
of
prey
organisms.
Metals
are
of
particular
concern
to
this
regulation
because
they
(
1)
do
not
volatilize,
(
2)
do
not
biodegrade,
(
3)

can
be
toxic
to
plants,
invertebrates
and
fish,
(
4)
adsorb
to
sediments
and
(
5)
bioconcentrate
in
biological
tissues.

EPA
obtained
the
environmental
fate
and
toxicity
information
for
the
132
MP&
M
POCs.
Table
I.
1
in
Appendix
I
shows
the
environmental
fate
and
toxicity
of
each
MP&
M
pollutant.
5
EPA
found
that:

 
56
pollutants
are
not
volatile
or
are
only
slightly
volatile
(
all
metals
were
assumed
to
be
non­
volatile
except
for
mercury);

 
57
pollutants
have
moderate
to
high
adsorption
potentials
(
all
metals
were
assumed
to
have
high
adsorption
potential
except
for
nickel);

 
42
pollutants
have
moderate
to
high
bioconcentration
factors;

 
62
pollutants
biodegrade
slowly
or
are
resistant
to
biodegradation
altogether
(
all
metals
were
assumed
to
be
resistant
to
biodegradation);

 
For
freshwater
environments,
32
pollutants
have
acute
toxicities
to
aquatic
life
that
range
from
moderate
to
high,
and
33
pollutants
have
chronic
toxicities
that
range
from
moderate
to
high;

 
For
saltwater
environments,
20
pollutants
have
acute
toxicities
to
aquatic
life
that
range
from
moderate
to
high,
and
23
pollutants
have
chronic
toxicities
that
range
from
moderate
to
high.

The
available
information
shows
that
dozens
of
the
MP&
M
POCs
have
the
potential
to
pose
significant
hazards
to
the
aquatic
environment
when
released
to
receiving
waters.
A
number
of
pollutants
are
of
particular
concern
because
of
their
combined
toxicity
and
fate.
These
include
several
polyaromatic
hydrocarbons
(
acenaphthene,
anthracene,
3,6­
dimethyl­
phenanthrene,

fluoranthene,
phenanthrene,
and
pyrene),
several
metals
(
aluminum,
cadmium,
copper,
mercury,
and
selenium)
and
several
phthalates
(
di­
n­
octyl
phthalate,
butyl
benzyl
phthalate,
and
di­
n­
butyl
phthalate).
Other
pollutants
are
of
concern
chiefly
because
of
their
toxicity
(
arsenic,
cyanide,
chromium,
lead,
nickel,
silver,
and
zinc)
or
their
fate
(
bis(
2­
ethylhexyl)
phthalate,

bromo­
2­
chlorobenzene,
bromo­
3­
chlorobenzene,
dibenzofuran,
dibenzothiophene,
diphenylamine,
long­
chained
petroleum
hydrocarbons,
1­
methylfluorene,
N­
nitrosodiphenylamine,
and
several
metals).

The
available
fate
and
toxicity
data
indicate
that
many
MP&
M
pollutants
tend
(
1)
to
be
"
toxic",
(
2)
to
not
readily
volatilize
from
the
water
column,
(
3)
to
adsorb
to
sediments,
(
4)
to
bioconcentrate
in
aquatic
organisms,
and
(
5)
do
not
biodegrade.

Such
pollutants
accumulate
in
sediments
and
reach
concentrations
which
can
impair
benthic
communities.
Pollutants
that
have
accumulated
in
sediments
can
be
released
back
into
the
water
column
because
sediments
act
as
long­
term
sinks.
The
pollutants
can
also
enter
soils
and
reach
high
levels
over
time
if
present
in
sewage
sludge
that
is
applied
to
land.
The
tendency
of
these
pollutants
to
resist
biodegradation
and
to
bioconcentrate
in
biological
tissue
also
causes
them
to
be
taken
up
into
aquatic
food
chains
where
they
can
affect
predators
or
humans
who
consume
fish
and
shellfish
(
U.
S.
EPA,
1998).

The
toxicity
data
also
indicate
that
a
sizable
number
of
the
POCs
in
MP&
M
effluents
have
toxicities
that
result
in
lethal
or
sub­
lethal
responses
in
aquatic
receptors,
including
algae,
vascular
plants,
invertebrates,
fish,
and
amphibians.
Responses
include
death,
which
may
occur
within
a
matter
of
hours
to
days,
or
longer­
term
sub­
lethal
responses
(
such
as
reproductive
failure
or
growth
impairment)
that
manifest
themselves
over
weeks,
months,
or
even
years.
The
effects
of
toxic
chemicals
are
not
shared
equally
among
exposed
species:
sensitive
species
are
typically
more
affected
than
species
that
are
more
resistant.

Hence,
toxic
conditions
could
selectively
remove
sensitive
species
from
receiving
waters.
Such
a
pattern
is
of
particular
concern
to
threatened
and
endangered
(
T&
E)
species,
which
may
already
be
close
to
extinction.
Aquatic
receptors
are
exposed
to
many
different
toxicants
at
the
same
time,
which
may
have
additive
effects.
The
EPA
assessment
is
based
on
a
5
Note
that
EPA
was
unable
to
obtain
fate
or
toxicity
data
for
a
substantial
number
of
POCs.

12­
7
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
chemical­
by­
chemical
approach
and
therefore
does
not
consider
additive
effects.
This
approach
may
understate
the
benefits
of
the
rule.

EPA
also
did
not
evaluate
the
potential
fate
and
effects
of
the
four
conventional
pollutants
(
BOD,
pH,
O&
G,
TSS)
and
several
other
pollutants,
including
Total
Petroleum
Hydrocarbon
(
TPH),
Total
Kjeldahl
Nitrogen
(
TKN),
phosphorus,
and
chemical
oxygen
demand
(
COD)
,
which
may
nonetheless
adversely
affect
aquatic
environments.
6,7
Effluents
with
high
levels
of
BOD
or
COD
consume
large
amounts
of
dissolved
oxygen
in
a
short
time,
causing
surface
waters
to
become
oxygen­
depleted,
thereby
killing
or
excluding
aquatic
life
(
U.
S.
EPA,
1986).
At
current
discharge
levels,
MP&
M
facilities
discharge
1.1
million
pounds
of
BOD
per
year.

Low
pH
(
high
acidity)
water
can
be
lethal
to
aquatic
organisms;
sensitive
species
of
fish
and
invertebrates
are
eliminated
from
surface
waters
at
pH's
between
6.0
and
6.5
(
U.
S.
EPA,
1999).

O&
G
and
TPH
can
have
lethal
effects
on
fish
by
coating
gill
surfaces
and
causing
asphyxia,
depleting
dissolved
oxygen
levels
due
to
excessive
BOD,
and
impairing
stream
re­
aeration
due
to
the
presence
of
surface
films.
Compounds
present
in
O&
G
or
TPH
can
also
be
detrimental
to
waterfowl
by
affecting
the
buoyancy
and
insulating
capacity
of
their
feathers
(
U.
S.
EPA,

1998).
At
current
discharge
levels,
MP&
M
facilities
discharge
553,481
pounds
per
year
of
O&
G,
including
67,427
pounds
a
year
of
TPH.

TSS
increases
the
turbidity
of
surface
water
and
impairs
underwater
visibility
and
transparency,
thereby
inhibiting
photosynthesis
by
diminishing
the
amount
of
sunlight
that
reaches
algae
or
submerged
aquatic
plants.
TSS
also
causes
a
general
degradation
of
aquatic
habitats
by
increasing
the
rate
of
sedimentation,
which
smothers
eggs,
covers
aquatic
plants,

and
affects
benthic
invertebrates
(
U.
S.
EPA,
1998).

High
input
of
nitrogen
in
estuarine
and
marine
systems
or
phosphorus
in
freshwater
systems
can
increase
primary
productivity
and
result
in
eutrophication.
Such
a
process
overloads
surface
waters
with
algae
and
reduces
the
transparency
of
the
water
column.
The
excess
algae
sink
to
the
bottom
and
decompose
at
the
end
of
their
life
cycle.
This
process
consumes
large
amounts
of
dissolved
oxygen
and
can
turn
surface
waters
anoxic
(
U.
S.
EPA,
1998;
U.
S.
EPA,
1995).

12.1.4
Effects
of
MP&
M
Pollutants
on
Economic
Productivity
Most
MP&
M
pollutants
associated
with
adverse
health
effects
are
subject
to
drinking
water
criteria.
Thus,
MP&
M
discharges
to
surface
water
can
increase
the
cost
of
municipal
water
treatment
by
requiring
investment
in
chemical
treatment
and
filtration.
Public
water
treatment
systems
must
comply
with
drinking
water
criteria
MCLs
and
secondary
standards.

Compliance
may
require
treatment
to
reduce
the
levels
of
regulated
pollutants
below
their
MCLs.
Capital
investment
and
operating
and
maintenance
(
O&
M
)
costs
associated
with
treatment
technologies
can
be
substantial.
To
the
extent
that
the
MP&
M
regulation
reduces
the
concentration
of
MP&
M
pollutants
in
source
waters
to
values
that
are
below
pollutant­
specific
drinking
water
criteria,
public
drinking
water
systems
will
accrue
benefits
in
the
form
of
reduced
water
treatment
costs.

Releases
of
MP&
M
pollutants
to
surface
waters
may
also
increase
treatment
costs
of
irrigation
water
and
industrial
water.

Releases
of
large
quantities
or
high
concentrations
of
toxic
pollutants
in
MP&
M
effluents
may
interfere
with
POTW
processes
(
e.
g.,
inhibiting
microbial
degradation),
reduce
the
treatment
efficiency
or
capacity
of
POTW
s,
and
reduce
disposal
options
for
the
sludge.
In
addition,
toxic
pollutants
present
in
the
effluent
discharges
may
pass
through
a
POTW
and
adversely
affect
receiving
water
quality,
or
may
contaminate
sludges
generated
during
primary
or
secondary
wastewater
treatment.
EPA
expects
no
changes
in
the
current
status
of
POTW
processes
or
disposal
options
for
the
sludge
at
POTWs
receiving
effluent
discharges
from
MP&
M
facilities
associated
with
the
MP&
M
rule
since
all
indirect
dischargers
have
been
excluded
from
the
final
option.
EPA,
however,
analyzed
changes
in
interferences
of
POTW
operations
and
contamination
of
sewage
sludge
at
6
TKN
is
defined
as
the
total
of
organic
and
ammonia
nitrogen.
It
is
determined
in
the
same
manner
as
organic
nitrogen,
except
that
the
ammonia
is
not
driven
off
before
the
digestion
step.

7
EPA,
however,
considered
environmental
effects
of
TKN
in
the
Ohio
case
study.
EPA
evaluated
the
impact
of
in­
stream
TKN
concentrations
on
recreational
value
of
fishing,
boating,
swimming,
and
wildlife
viewing
sites.
For
detail
see
Chapter
21
of
this
report.

12­
8
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
POTWs
receiving
effluent
discharges
from
MP&
M
facilities
for
the
alternative
regulatory
options
which
include
indirect
dischargers.

12.2
LINKING
THE
REGULATION
TO
BENEFICIAL
OUTCOMES
This
section
describes
the
linkages
between
promulgation
of
a
regulation
and
the
expected
benefits
to
society.
As
indicated
in
Figure
12.1,
the
benefits
of
the
MP&
M
regulation
occur
from
a
chain
of
events.
These
events
include:
(
1)
Agency
publication
of
the
regulation,
(
2)
industry
changes
in
production
processes
and/
or
treatment
systems,
(
3)
reductions
in
pollutant
discharges,
(
4)
changes
in
water
quality,
(
5)
changes
in
ecosystem
attributes
and
sewage
sludge
quality,
(
6)
changes
in
human
responses,
and
(
7)
changes
in
human
health
and
ecological
risk.
The
first
two
events
reflect
the
institutional
and
technical
aspects
of
the
regulation.
The
benefit
analysis
begins
with
the
third
event,
the
changes
in
the
pollutant
content
of
effluent
discharges.

12­
9
 
 
 
 
 
 
 
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
Figure
12.1:
Chain
of
Events
in
a
Benefits
Analysis
1.
EPA
Publication
of
Regulation
2.
ges
in
Production
Processes
and/
or
Treatment
Chan
3.
ctions
in
Pollutant
Discharges
Redu
4.
ges
in
Ambient
Water
Quality
(
Pollutant
Concentrations
&

Aquatic
Habitat)
Chan
5.
ge
in
Aquatic
Ecosystem
(
e.
g.,
Increased
Fish
Populations
&

Diversity
&
Reduced
Bioaccumulation)
Chan
6.

Demand
&
Value
of
Fishery
(
e.
g.,
Recreational
&

Other
Benefit
Categories)
Change
in
Level
of
7.
tial
Change
in
Health
Risk
(
e.
g.,
from
Consumption
of
Fish
Caught)
Poten
Source:
U.
S.
EPA
analysis.

In
event
four,
changes
in
pollutant
discharges
translate
into
improvements
in
water
and
sludge
quality.
In
event
five,
these
improvements
in
turn
affect
in­
stream
and
near­
stream
biota
(
e.
g.,
increased
diversity
of
aquatic
species
and
size
of
species
populations)
and
sludge
disposal
options.
Finally,
human
effects
and
the
related
valuation
of
benefits
occur
in
events
six
and
seven.
For
example,
improvements
to
recreational
fisheries
and
enhanced
enjoyment
by
recreational
anglers
is
connected
to
12­
10
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
improved
water
quality
and
the
value
of
reduced
risk
to
human
health.
These
linkages
are
the
basis
of
the
benefits
analysis
presented
in
this
and
the
following
chapters.

12.3
QUALITATIVE
AND
QUANTITATIVE
BENEFITS
ASSESSMENT
A
benefit
assessment
defines
and
quantifies
the
types
of
improvements
to
human
health
and
ecological
receptors
that
can
be
expected
from
reducing
the
amount
of
MP&
M
pollutants
released
to
the
environment.
The
following
sections
provide
an
overview
of
the
concepts
and
analytic
approaches
involved
in
the
benefits
assessment.
The
first
section
describes
the
general
categories
of
benefits
expected
to
result
from
the
regulation
and
the
level
of
analysis
undertaken
for
them.
The
following
three
sections
review,
within
the
broad
categories
of
benefits
likely
to
be
achieved
by
the
MP&
M
regulation,
the
specific
benefits
that
are
evaluated
in
this
analysis.
Finally,
Section
12.3.5
summarizes
methods
for
attaching
values
to
some
of
the
benefit
measures.
Chapters
13
through
16
present
the
quantitative
assessment
of
benefits.

12.3.1
Overview
of
Benefit
Categories
The
benefits
of
reduced
MP
&
M
discharges
may
be
classified
in
three
broad
categories:
human
health,
ecological,
and
economic
productivity
benefits.
Table
12.3
summarizes
the
different
types
of
benefits
that
fall
in
each
of
these
categories.

Each
category
is
comprised
of
a
number
of
more
narrowly
defined
benefit
categories.
EPA
expects
that
the
MP&
M
regulation
will
provide
benefits
to
society
in
all
of
these
categories.
EPA
was
not
able
to
bring
the
same
depth
of
analysis
to
all
of
these
categories,
however,
because
of
imperfect
understanding
of
the
link
between
discharge
reductions
and
benefit
categories,
and
how
society
values
some
of
the
benefit
events.
EPA
was
able
to
quantify
and
monetize
some
benefits,

quantify
but
not
monetize
other
benefits,
and
assess
still
other
benefits
only
qualitatively.

In
addition
to
the
national­
level
benefits
analysis,
the
Agency
conducted
a
case
study
in
the
state
of
Ohio
to
provide
in­
depth
analysis
of
the
regulation's
expected
benefits.
The
Ohio
case
study
improves
on
the
national
analysis
in
two
ways.
First,
the
analysis
uses
improved
data
and
methods
to
address
co­
occurrence
of
M
P&
M
facility
benefits
and
other­
source
contributions
of
MP&
M
pollutants
in
the
same
locations.
Second,
the
analysis
of
recreational
benefits
is
based
on
original
travel
cost
models
of
resource
valuation
in
a
random
utility
framework.
The
analysis
values
changes
in
the
value
of
water
resources
for
four
recreational
activities
­­
fishing,
boating,
swimming,
and
near­
water
recreation.
Due
to
data
limitations,
only
three
of
these
four
activities
were
valued
at
the
national­
level
benefits
analysis.

To
provide
perspective
on
the
extent
to
which
this
regulatory
impact
assessment
was
able
to
comprehensively
analyze
the
benefits,
Table
12.3
summarizes
the
specific
benefits
within
each
of
the
three
broad
benefit
categories
that
are
expected
to
accrue
from
the
MP&
M
regulation
and
the
level
of
analysis
applied
to
each
category.
As
shown
in
Table
12.3,
only
a
few
of
the
relevant
benefit
categories
can
be
both
quantified
and
monetized.

12­
11
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
Table
12.3:
Level
of
Analysis
Performed
for
Specific
Benefit
Categories
Benefit
Category
Quantified
and
Monetized
Quantified
but
Not
Monetized
Qualitative
Human
Health
Benefits
Reduced
cancer
risk
due
to
ingestion
of
chemically­
contaminated
fish
and
unregulated
pollutants
in
drinking
water
X
Reduced
non­
cancer
adverse
health
effects
(
e.
g.

immunological,
neurological,
circulatory,
or
respiratory
toxicity)

due
to
ingestion
of
chemically­
contaminated
fish
and
unregulated
pollutants
in
drinking
water
X
Reduced
non­
cancer
adverse
health
effects
from
exposure
to
lead
from
consumption
of
chemically­
contaminated
fish
X
Reduced
cancer
risk
and
non­
cancer
adverse
health
effects
from
exposure
to
unregulated
pollutants
in
chemically­
contaminated
sewage
sludgea
X
Reduced
health
hazards
from
exposure
to
contaminants
in
waters
used
recreationally
(
e.
g.,
swimming)
X
Ecological
Benefits
Reduced
risk
to
aquatic
life
X
Enhanced
water­
based
recreation
including
fishing,
boating,
and
near­
water
(
wildlife
viewing)
activities
X
Other
enhanced
water­
based
recreation
such
as
swimming,

waterskiing,
and
white
water
rafting
X
Increased
aesthetic
benefits
such
as
enhancement
of
adjoining
site
amenities
(
e.
g.
,
working,
traveling,
and
owning
property
near
the
water)
X
Nonuser
value
(
i.
e.,
existence,
option,
and
bequest
value)
X
Reduced
contamination
of
sediments
X
Reduced
non­
point
source
nitrogen
contamination
of
water
if
sewage
sludge
is
used
as
a
substitute
for
chemical
fertilizer
on
agricultural
landa
X
Satisfaction
of
a
public
preference
for
beneficial
use
of
sewage
sludgea
X
Economic
Productivity
Benefits
Reduced
sewage
sludge
disposal
costsa
X
Reduced
management
practice
and
record­
keeping
costs
of
sewage
sludge
that
meets
exceptional
quality
criteriaa
X
Reduced
interference
with
POTW
operations
a
X
Benefits
to
tourism
industries
from
increased
participation
in
water­

based
recreation
X
Improved
commercial
fisheries
yields
X
Improved
crop
yield
(
the
organic
matter
in
land­
applied
sewage
sludge
increases
soil s
water
retention)
a
X
Avoidance
of
costly
siting
processes
for
more
controversial
sewage
sludge
disposal
methods
(
e.
g.,
incinerators)
because
of
greater
use
of
land
applicationa
X
Reduced
water
treatment
costs
for
municipal
drinking
water,

irrigation
water,
and
industrial
process
and
cooling
water
X
reproductive,

residing
a
These
benefit
categories
are
not
applicable
to
the
final
rule
since
all
indirect
dischargers
have
been
excluded
from
the
selected
option.
EPA,
however,
analyzed
these
benefit
categories
for
the
alternative
regulatory
options
which
include
indirect
dischargers.

Source:
U.
S.
EPA
analysis.

Each
category
of
benefits
and
the
level
of
analysis
applied
to
this
category
are
discussed
in
greater
detail
below.

12­
12
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
12.3.2
Human
Health
Benefits
Reduced
pollutant
discharges
to
the
nation s
waterways
will
generate
human
health
benefits
by
several
mechanisms.
The
most
important
and
readily
analyzed
benefits
stem
from
reduced
risk
of
illness
associated
with
the
consumption
of
water,
fish,

shellfish,
and
other
aquatic
organisms
that
is
taken
from
waterways
affected
by
MP&
M
discharges.
Human
health
benefits
are
typically
analyzed
by
estimating
the
change
in
the
expected
number
of
adverse
human
health
events
in
the
exposed
population
resulting
from
a
reduction
in
effluent
discharges.
While
some
health
effects
such
as
cancer
are
relatively
well
understood
and
thus
may
be
quantified
in
a
benefits
analysis,
others
are
less
well
characterized
and
cannot
be
assessed
with
the
same
rigor
or
at
all.

EPA
analyzed
the
following
direct
measures
of
change
in
risk
to
human
health:
incidence
of
cancer
from
fish
and
water
consumption;
reduced
risk
of
non­
cancer
toxic
effects
from
fish
and
water
consumption;
and
lead­
related
health
effects
to
children
and
adults.
EPA
was
able
to
monetize
only
two
of
the
three
measures
(
cancer­
related
and
lead­
related
health
risks).

Incidence
of
cancer
was
translated
into
an
expected
number
of
avoided
mortality
events
and,
on
that
basis,
monetized.
Lead
impacts
to
children
were
evaluated
in
terms
of
potential
intellectual
impairment
as
measured
by
estimated
changes
in
IQ.

Changes
in
adverse
health
effects
to
adults
from
lead
exposure
were
measured
in
terms
of
reduced
risk
of
hypertension,
non­

fatal
coronary
heart
disease,
non­
fatal
strokes,
and
mortality.

EPA
also
quantified
but
did
not
monetize
the
expected
reduction
of
pollutant
concentrations
in
excess
of
health­
based
AWQC
limits.
This
benefit
measure
was
obtained
by
comparing
in­
waterway
pollutant
concentrations
to
toxic
effect
levels.

In
concept,
the
value
of
these
health
effects
to
society
is
the
monetary
value
that
society
is
willing
to
pay
to
avoid
the
health
effects,
or
the
amount
that
society
would
need
to
be
compensated
to
accept
increases
in
the
number
of
adverse
health
events.

 
Willingness­
to­
pay 
(
WTP)
values
are
generally
considered
to
provide
a
fairly
comprehensive
measure
of
society s
valuation
of
the
human
and
financial
costs
of
illness
associated
with
the
costs
of
health
care,
losses
in
income,
and
pain
and
suffering
of
affected
individuals
and
of
their
family
and
friends.

In
some
cases,
available
economic
research
provides
little
empirical
data
for
society's
WTP
to
avoid
certain
health
effects.

One
component
of
the
cost
of
an
illness
estimates
the
direct
medical
costs
of
treating
a
health
condition
(
e.
g.,
hypertension),

and
can
be
used
to
value
changes
in
health
risk
from
reduced
exposure
to
toxic
pollutants
such
as
lead.
These
estimates
represent
only
one
component
of
society's
WT
P
to
avoid
adverse
health
effects
and
therefore
produce
a
partial
measure
of
the
value
of
reduced
exposure
to
MP&
M
pollutants.
Employed
alone,
these
monetized
effects
will
significantly
underestimate
society's
WTP.

12.3.3
Ecological
Benefits
EPA
expects
that
the
ecological
benefits
from
the
regulation
will
include
protection
of
fresh­
and
saltwater
plants,

invertebrates,
fish,
and
amphibians,
as
well
as
terrestrial
wildlife
and
birds
that
prey
on
aquatic
organisms
exposed
to
MP&
M
pollutants.
The
regulation
will
reduce
the
presence
and
discharge
of
various
pollutants
and
will
enhance
or
protect
aquatic
ecosystems
currently
under
stress.
The
drop
in
pollutant
loading
is
expected
to
reestablish
productive
ecosystems
in
damaged
waterways
and
to
protect
resident
species,
including
T&
E
species.
EPA
also
expects
that
the
regulation
will
enhance
the
general
health
of
fish
and
invertebrate
populations,
increase
their
propagation
to
waters
currently
impaired,
and
expand
fisheries
for
both
commercial
and
recreational
purposes.
Improvements
in
water
quality
will
also
favor
increased
recreational
activities
such
as
swimming,
boating,
fishing,
and
water
skiing.
Finally,
the
Agency
expects
that
the
regulation
will
augment
nonuse
values
(
e.
g.,
option,
existence,
and
bequest
values)
of
the
affected
water
resources.

It
is
frequently
difficult
to
quantify
and
attach
economic
values
to
ecological
benefits.
The
difficulty
results
from
imperfect
understanding
of
the
relationship
between
changes
in
effluent
discharges
and
the
specific
ecological
changes,
lack
of
water
quality
monitoring
data
for
most
locations,
and
time
lags
between
water
quality
changes
and
changes
in
species
population
and
composition.
In
addition,
it
is
difficult
to
attach
monetary
values
to
these
ecological
changes
because
they
often
do
not
occur
in
markets
in
which
prices
or
costs
are
readily
observed.
As
such,
ecological
benefits
may
be
loosely
classified
as
nonmarket
benefits.
This
classification
can
be
further
divided
into
nonmarket
use
benefits
and
nonmarket
nonuse
benefits.

Nonmarket
use
benefits
stem
from
improvements
in
ecosystems
and
habitats,
which
in
turn
lead
to
enhanced
human
use
and
enjoyment
of
these
areas.
For
example,
reduced
discharges
may
lead
to
increased
recreational
use
and
enjoyment
of
affected
waterways
in
such
activities
as
fishing,
swimming,
boating,
hunting
or
near­
water
activities
such
as
bird
watching.
In
some
12­
13
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
cases,
it
may
be
possible
to
quantify
and
attach
partial
economic
values
to
ecological
benefits
using
market
values
(
e.
g.,
an
increase
in
tourism
or
boat
rentals
associated
with
improved
recreational
fishing
opportunities);
in
this
case,
these
benefit
events
might
better
be
classified
as
economic
productivity
related
events,
which
are
discussed
below.
Economic
markets,

however,
do
not
provide
enough
information
to
fully
capture
the
value
of
these
benefits.
Such
markets
capture
only
related
expenditures
made
by
recreationists
(
e.
g.,
food
and
lodging)
and
do
not
capture
the
value
placed
on
the
experience
itself.
A
variety
of
nonmarket
valuation
techniques
can
be
used
to
capture
the
value
placed
on
the
resource
in
question.
These
techniques
include
hedonic
valuation
(
wage­
risk
studies)
and
travel
cost
methods
(
TCM),
stated
preferences
methods
(
i.
e.,

contingent
valuation
(
CV)
,
contingent
rating
(
CR)
,
contingent
activity
(
CA)
,
benefits
transfer,
and
averting
behavior
models.

Nonmarket
nonuse
benefits
are
not
associated
with
current
use
of
the
affected
ecosystem
or
habitat,
but
rather
arise
from
(
1)

the
realization
of
the
improvement
in
the
affected
ecosystem
or
habitat
resulting
from
reduced
effluent
discharges
and
(
2)
the
value
that
individuals
place
on
the
potential
for
use
sometime
in
the
future.
Nonmarket
nonuse
benefits
may
also
be
manifested
by
other
valuation
mechanisms,
such
as
cultural
valuation,
philanthropy,
and
bequest
valuation.
It
is
often
extremely
difficult
to
quantify
the
relationship
between
changes
in
discharges
and
the
improvements
in
societal
well­
being
associated
with
such
valuation
mechanisms.
That
these
valuation
mechanisms
exist,
however,
is
indisputable,
as
evidenced,

for
example,
by
society s
willingness
to
contribute
to
organizations
whose
mission
is
to
purchase
and
preserve
lands
or
habitats
to
avert
development.

12.3.4
Economic
Productivity
Benefits
Reduced
pollutant
discharges
may
also
benefit
economic
productivity.
First,
economic
productivity
benefits
may
accrue
from
reduced
treatment
costs
of
drinking
water,
irrigation
water,
and
industrial
use
water.
Reduced
pollutant
concentrations
in
public
water
systems
source
water
to
levels
at
or
below
MCLs
or
secondary
standards
could
reduce
ongoing
treatment
costs
and
avoid
the
need
to
invest
in
treatment
technologies
in
the
future.
Reduced
pollutant
discharges
may
also
reduce
sediment
dredging
costs.
Contaminated
sediments
may
contribute
substantially
to
contamination
of
aquatic
biota
and
to
human
exposure
of
human
health
toxicants.
Controlling
point
source
discharges
of
toxic
pollutants
can
prevent
sediment
contamination
and
eliminate
the
need
for
future
remediation
(
i.
e.,
dredging)
of
contaminated
sediments.

Other
economic
productivity
gains
may
result
from
improved
tourism
opportunities
in
areas
affected
by
MP&
M
discharges.

Improved
aquatic
species
survival
may
contribute
to
increased
commercial
fishing
yield.
When
such
economic
productivity
effects
can
be
identified
and
quantified,
they
are
generally
straightforward
to
value
because
they
involve
market
commodities
for
which
prices
or
unit
costs
are
readily
available.

Economic
productivity
gains
may
also
occur
through
reduced
costs
to
public
sewage
systems
(
POTWs)
for
managing
and
disposing
of
the
sludge
(
i.
e.,
biosolids)
from
treating
effluent
discharges.
For
example,
higher
quality
sludge
may
be
applied
to
agricultural
land
or
otherwise
beneficially
used
rather
than
being
incinerated
or
disposed
of
in
landfills.
POTWs
may
also
incur
lower
costs
because
of
lower
record
keeping
requirements.
Under
the
final
regulatory
option,
EPA
expects
no
POTW
productivity
gains
since
all
indirect
dischargers
have
been
excluded
from
the
final
regulatory
option.

12.3.5
Methods
for
Valuing
Benefit
Events
Some
of
the
benefits
expected
from
the
MP&
M
regulation
will
manifest
themselves
in
economic
markets
through
changes
in
price,
cost,
or
quantity
of
market­
valued
activities.
For
benefits
endpoints
traded
in
markets,
such
as
increased
yields
from
commercial
fisheries,
benefits
can
be
measured
by
market
prices
or
market­
based
factor
pricing.
Competitive
prices
can
be
used
also
to
measure
avoided
cost
type
of
benefits.
For
example,
reduced
pollutant
loadings
to
public
water
supplies
may
lower
costs
of
drinking
treatment.
Market
prices
can
be
used
also
to
value
direct
medical
costs
of
illnesses
associated
with
exposure
to
pollutants.
For
this
analysis,
EPA
used
medical
costs
associated
with
treating
hypertension,
coronary
heart
disease,
and
stroke
to
estimate
benefits
from
reduced
exposure
to
lead
(
see
Chapter
14).
The
estimated
values
can
be
used
as
minimum
measures
of
the
benefits
associated
with
reduced
cases
of
these
illnesses.

In
other
cases,
benefits
involve
activities
or
sources
of
value
that
either
do
not
involve
economic
markets
or
involve
them
only
indirectly.
Methods
used
to
value
such
benefits
are
described
briefly
below:

12­
14
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
a.
Wage­
risk
approach.

The
wage­
risk
approach
uses
regression
estimates
of
the
wage
premium
associated
with
greater
risks
of
death
on
the
job
to
estimate
the
amount
that
persons
are
willing
to
pay
to
avoid
death.
Benefit
values
based
on
this
approach
are
used
as
part
of
the
basis
for
valuing
reduced
cancer
cases
due
to
fish
consumption
in
Chapter
13.

b.
Travel
cost
method
The
T
CM
uses
information
on
costs
incurred
by
people
in
traveling
to
a
site
and
in
using
the
site
to
estimate
a
demand
curve
for
that
site.
The
demand
curve
is
then
used
to
estimate
the
 
consumer
surplus 
associated
with
the
use
of
the
site,
that
is,
the
value
that
consumers
receive
from
the
site
over
and
above
the
costs
that
they
incur
in
using
it.
Consumer
surplus
is
an
estimate
of
the
net
benefits
of
the
resource
to
the
people
using
that
resource.
For
example,
if
the
resource
is
a
recreational
fishing
site,
the
TCM
can
be
used
to
value
the
recreational
fishing
experience.
The
Agency
used
an
original
travel
cost
study
to
value
benefits
from
enhanced
water­
based
recreation
in
Ohio
(
see
Part
V:
Chapter
21).
The
analysis
of
recreational
benefits
in
Chapter
15
uses
a
meta­
analysis
of
water­
based
recreation
studies
(
including
TCM
studies)
to
derive
the
baseline
and
post­
compliance
values
of
water­
based
recreation
activities
(
including
fishing,
boating,
and
wildlife
viewing)
and
to
estimate
benefits
to
consumers
of
water­
based
recreation
from
improved
water
quality
resulting
from
reduced
MP&
M
dischargers.

c.
Contingent
valuation
In
the
CV
method,
surveys
are
conducted
to
elicit
individuals 
WTP
for
a
particular
good,
such
as
a
fishery,
or
clean
water.

CV
is
more
broadly
applicable
than
TCM.
Like
TCM,
CV
can
be
used
to
estimate
the
consumer
surplus
associated
with
recreational
fisheries.
CV
can
also
be
used
to
estimate
less
tangible
values,
such
as
how
much
people
care
about
a
clean
environment.
Values
from
both
the
CV
approach
and
the
wage­
risk
approach
support
the
estimated
value
of
avoided
death
that
is
used
to
monetize
reduced
cancer
cases
from
consumption
of
contaminated
fish
(
Chapter
13).
Similarly
to
the
TCM
studies,
CV
studies
are
used
in
a
meta­
analysis
to
derive
the
baseline
and
post­
compliance
values
of
water­
based
recreation
activities
(
including
fishing,
boating,
and
wildlife
viewing)
and
to
estimate
benefits
from
improved
opportunities
for
water­

based
recreation
from
reduced
MP&
M
dischargers
(
Chapter
15).

d.
Benefits
transfer
When
time
and
resource
constraints
preclude
primary
research,
benefit
assessment
based
on
benefits
transfer
from
existing
studies
is
used.
This
approach
involves
extrapolating
benefit
findings
for
one
analytic
situation
to
another.
The
relevant
study
situations
are
defined
by
type
of
environmental
resource
(
e.
g.,
fishery),
policy
variable(
s),
and
the
characteristics
of
user
populations.
The
benefits
transfer
approach
is
used
to
monetize
several
benefit
categories,
including
changes
in
the
incidence
of
cancer
cases
(
Chapter
13)
and
the
national­
level
benefits
from
enhanced
water­
based
recreation
(
Chapter
15).

The
techniques
described
above
form
the
basis
of
the
benefits
methodologies
described
in
Chapters
13,14,
and
15.

12­
15
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
GLOSSARY
acute
toxicity:
the
ability
of
a
substance
to
cause
severe
biological
harm
or
death
soon
after
a
single
exposure
or
dose.

Also,
any
poisonous
effect
resulting
from
a
single
short­
term
exposure
to
a
toxic
substance.
(
See:
chronic
toxicity,
toxicity.)

(
http://
www.
epa.
gov/
OCEPAterms/
aterms.
html)

adsorption
coefficients
(
Koc):
represents
the
ratio
of
the
target
chemical
absorbed
per
unit
weight
of
organic
carbon
in
the
soil
or
sediment
to
the
concentration
of
that
same
chemical
in
solution
at
equilibrium.

ambient
water
quality
criteria
(
AWQC):
AWQC
present
scientific
data
and
guidance
of
the
environmental
effects
of
pollutants
which
can
be
useful
to
derive
regulatory
requirements
based
on
considerations
of
water
quality
impacts;
these
criteria
are
not
rules
and
do
not
have
regulatory
impact
(
U.
S.
EPA.
1986.
Quality
Criteria
for
Water
1986.
U.
S.

Environmental
Protection
Agency,
Office
of
Water
Regulations
and
Standards,
Washington,
DC.
EPA
440/
5­
86­
001).

AQUatic
Information
REtrieval
System
(
AQUIRE):
a
web­
based
ecotoxicity
database
maintained
by
EPA's
Mid­
Continent
Ecology
Division
(
MED)
which
summarizes
ecotoxicity
data
retrieved
from
the
literature.

(
http://
www.
epa.
gov/
med/
databases/
databases.
html#
aquire)
(
U.
S.
EPA,
1998/
99b)

ASsessment
Tools
for
the
Evaluation
of
Risk
(
ASTER):
an
ecological
risk
assessment
tool
developed
by
EPA's
Mid­
Continent
Ecology
Division
(
MED);
ASTER
integrates
information
from
the
AQUIRE
toxic
effects
database
and
the
QSAR
system
(
a
structure
activity­
based
expert
system)
to
estimate
ecotoxicity,
chemical
properties,
biodegradation
and
environmental
partitioning.
(
http://
www.
epa.
gov/
med/
databases/
aster.
html)
(
U.
S.
EPA,
1998/
99c)

avoided
cost:
costs
that
are
likely
to
be
incurred
in
the
future
if
current
conditions
still
prevail
at
the
time,
but
which
will
be
avoided
if
particular
actions
are
taken
now
to
change
the
status
quo.

benthic:
relating
to
the
bottom
of
a
body
of
water;
living
on,
or
near,
the
bottom
of
a
water
body.

BIODEG:
a
web­
based
biodegradation
database
developed
by
Syracuse
Research
Corporation.

(
http://
esc.
syrres.
com/
efdb/
BIODGSUM
.
HTM)
(
Syracuse
Research
Corporation,
1999)

biodegradation
half­
lives:
represents
the
number
of
days
a
compound
takes
to
be
degraded
to
half
of
its
starting
concentration
under
prescribed
laboratory
conditions.

biological
oxygen
demand
(
BOD):
the
amount
of
dissolved
oxygen
consumed
by
microorganisms
as
they
decompose
organic
material
in
an
aquatic
environment.

cancer
potency
slope
factor
(
SF):
a
plausible
upper­
bound
estimate
of
the
probability
of
a
response
per
unit
intake
of
a
chemical
over
a
lifetime.
The
slope
factor
is
used
to
estimate
an
upper­
bound
probability
of
an
individual
developing
cancer
as
a
result
of
a
lifetime
of
exposure
to
a
particular
level
of
a
potential
carcinogen.

CHEMFATE:
a
web­
based
chemical
fate
database
developed
by
Syracuse
Research
Corporation.

(
http://
esc.
syrres.
com/
efdb/
Chemfate.
htm)
(
Syracuse
Research
Corporation,
1999)

chemical
oxygen
demand
(
COD):
a
measure
of
the
oxygen
required
to
oxidize
all
compounds,
both
organic
and
inorganic,
in
water.
(
http://
www.
epa.
gov/
OCEPAterms/
cterms.
html)

chronic
toxicity:
the
capacity
of
a
substance
to
cause
long­
term
poisonous
health
effects
in
humans,
animals,
fish,
and
other
organisms.
(
http://
www.
epa.
gov/
OCEPAterms/
cterms.
html)

contingent
activity:
one
of
the
stated
preference
methods
(
see:
contingent
valuation
and
contingent
activity).
Survey
respondents
are
asked
how
their
behavior
would
change
in
response
to
a
proposed
change
in
one
or
more
attributes
of
an
activity
(
e.
g.,
cost
of
the
activity,
site
accessibility,
or
site
attractiveness).
Given
responses
to
this
type
of
question,
and
given
information
about
incremental
travel
costs
and
value
of
time,
a
revealed
preference
method
can
be
used
to
estimate
the
value
of
change.

12­
16
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
contingent
rating:
one
of
the
stated
preference
methods
(
see:
contingent
valuation
and
contingent
activity).
Survey
respondents
are
asked
to
rate
several
alternatives
on
an
ad
hoc
utility
scale
(
e.
g.,
1
to
10).
The
choice
set
of
alternatives
usually
includes
the
environmental
effect
to
be
valued,
substitutes
for
the
effect,
and
a
good
with
a
monetary
price
to
act
as
a
threshold.
Based
on
the
respondent's
rating
of
the
environmental
effect
and
the
threshold
good,
and
the
monetary
price
of
the
threshold
good,
the
value
of
the
environmental
effect
can
be
determined.

contingent
valuation
(
CV):
a
method
used
to
determine
a
value
for
a
particular
event,
where
people
are
asked
what
they
are
willing
to
pay
for
a
benefit
and/
or
are
willing
to
receive
in
compensation
for
tolerating
a
cost.
Personal
valuations
for
increases
or
decreases
in
the
quantity
of
some
good
are
obtained
contingent
upon
a
hypothetical
market.
The
aim
is
to
elicit
valuations
or
bids
that
are
close
to
what
would
be
revealed
if
an
actual
market
existed.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

Environmental
Research
Laboratory­
Duluth
fathead
minnow
database:
a
database
developed
by
EPA's
Mid­
Continent
Ecology
Division
(
MED)
which
provides
data
on
the
acute
toxicity
of
hundreds
of
industrial
organic
compounds
to
the
fathead
minnow.
(
http://
www.
eoa.
gov/
med/
databases/
fathead_
minnow.
html)
(
U.
S.
EPA,
1998/
99a)

hazardous
air
pollutant
(
HAP):
compounds
that
EPA
believes
may
represent
an
unacceptable
risk
to
human
health
if
present
in
the
air.

Health
Effects
Assessment
Summary
Tables
(
HEAST):
a
comprehensive
listing
of
provisional
human
health
risk
assessment
data
relative
to
oral
and
inhalation
routes
for
chemicals
of
interest
to
EPA.
Unlike
data
in
IRIS,
HEAST
entries
have
received
insufficient
review
to
be
recognized
as
high
quality,
Agency­
wide
consensus
information.
(
U.
S.
EPA.
1997.

Health
Effects
Assessment
Table;
FY
1997
Update.
EPA­
540­
R­
97­
036)

Henry's
Law
constant:
a
numeric
value
which
relates
the
equilibrium
partial
pressure
of
a
gaseous
substance
in
the
atmosphere
above
a
liquid
solution
to
the
concentration
of
the
same
substance
in
the
liquid
solution.

human
health­
based
water
quality
criteria
(
WQC):
human
health­
based
criteria
are
based
on
specific
levels
of
pollutants
that
would
make
the
water
harmful
if
used
for
drinking,
swimming,
farming,
fish
production,
or
industrial
processes
(
see
ambient
water
quality
criteria
(
AWQC)).
(
http://
www.
epa.
gov/
OCEPAterms/
wterms.
html).

hydrophobicity:
having
a
strong
aversion
to
water.
(
http://
www.
epa.
gov/
OCEPAterms/
hterms.
html)

Integrated
Risk
Information
System
(
IRIS):
IRIS
is
an
electronic
database
with
information
on
human
health
effects
of
various
chemicals.
IRIS
provides
consistent
information
on
chemical
substances
for
use
in
risk
assessments,
decision­
making
and
regulatory
activities.

lipophilicity:
having
a
strong
attraction
to
oils
maximum
contaminant
levels
(
MCLs):
the
maximum
permissible
level
of
a
contaminant
in
water
delivered
to
any
user
of
a
public
system.
MCLs
are
enforceable
standards.

(
http://
www.
epa.
gov/
OCEPAterms/
mterms.
html)

metals:
inorganic
compounds,
generally
non­
volatile,
and
which
cannot
be
broken
down
by
biodegradation
processes.
They
are
a
particular
concern
because
of
their
prevalence
in
MP&
M
effluents.
Metals
can
accumulate
in
biological
tissues,

sequester
into
sewage
sludge
in
POTWs,
and
contaminate
soils
and
sediments
when
released
to
the
environment.
Some
metals
are
quite
toxic
even
when
present
at
relatively
low
levels.

microbial
metabolism:
biochemical
reactions
occurring
in
living
microorganisms
such
as
bacteria,
algae,
diatoms,

plankton,
and
fungi.
POTWs
make
use
of
bacterial
metabolism
for
wastewater
treatment
purposes.
This
process
is
inhibited
by
the
presence
of
toxins
such
as
metals
and
cyanide
because
these
pollutants
kill
bacteria.

oil
and
grease
(
O&
G):
organic
substances
that
may
include
hydrocarbons,
fats,
oils,
waxes,
and
high­
molecular
fatty
acids.
Oil
and
grease
may
produce
sludge
solids
that
are
difficult
to
process.
(
http://
www.
epa.
gov/
owmitnet/
reg.
htm)

pH:
an
expression
of
the
intensity
of
the
basic
or
acid
condition
of
a
liquid;
natural
waters
usually
have
a
pH
between
6.5
and
8.5.
(
http://
www.
epa.
gov/
OCEPAterms/
pterms.
html)

12­
17
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
pollutants
of
concern
(
POCs):
are
the
150
contaminants
identified
by
EPA
as
being
of
potential
concern
for
this
rule
and
which
are
currently
being
discharged
by
MP&
M
facilities.

priority
pollutant
(
PP):
126
individual
chemicals
that
EPA
routinely
analyzes
when
assessing
contaminated
surface
water,

sediment,
groundwater,
or
soil
samples.

publicly­
owned
treatment
works
(
POTWs):
a
treatment
works,
as
defined
by
section
212
of
the
Act,
that
is
owned
by
a
State
or
municipality.
This
definition
includes
any
devices
or
systems
used
in
the
storage,
treatment,
recycling,
and
reclamation
of
municipal
sewage
or
industrial
wastes
of
a
liquid
nature.
It
also
includes
sewers,
pipes,
or
other
conveyances
only
if
they
convey
wastewater
to
a
POTW
Treatment
Plant.
(
http://
www.
epa.
gov/
owm/
permits/
pretreat/
final99.
pdf)

quantitative
structure­
activity
relationship
(
QSAR)
model:
an
expert
system
which
uses
a
large
database
of
measured
physicochemical
properties
such
as
melting
point,
vapor
pressure,
and
water
solubility
to
estimate
the
fate
and
effect
of
a
specific
chemical
based
on
its
molecular
structure.
(
http://
www.
epa.
gov/
med/
databases/
aster.
html)
(
U.
S.
EPA,

1998/
99)

reference
doses
(
RfDs):
chemical
concentrations
expressed
in
mg
of
pollutant/
kg
body
weight/
day,
that,
if
not
exceeded,

are
expected
to
protect
an
exposed
population,
including
sensitive
groups
such
as
young
children
or
pregnant
women.

secondary
MCLs:
human
health­
based
drinking
water
criteria
to
assess
the
health
hazards
associated
with
the
presence
of
certain
toxic
chemicals
in
drinking
water.
SMCLs
are
established
for
taste
or
aesthetic
effects.

Superfund
Chemical
Data
Matrix
(
SCDM):
a
source
for
factor
values
and
benchmark
values
applied
when
evaluating
potential
National
Priorities
List
(
NPL)
sites
using
the
Hazard
Ranking
System
(
HRS).

(
http://
www.
epa.
gov/
superfund/
resources/
scdm/
index.
htm).

suspended
solids:
small
particles
of
solid
pollutants
that
float
on
the
surface
of,
or
are
suspended
in,
water
bodies.

(
http://
www.
epa.
gov/
OCEPAterms/
sterms.
html)

systemic
toxicants:
chemicals
that
EPA
believes
can
cause
significant
non­
carcinogenic
health
effects
when
present
in
the
human
body
above
chemical­
specific
toxicity
thresholds.

threatened
and
endangered
(
T&
E):
animals,
birds,
fish,
plants,
or
other
living
organisms
threatened
with
extinction
by
anthropogenic
(
man­
caused)
or
other
natural
changes
in
their
environment.
Requirements
for
declaring
a
species
endangered
are
contained
in
the
Endangered
Species
Act.

Total
Petroleum
Hydrocarbon
(
TPH):
a
general
measure
of
the
amount
of
crude
oil
or
petroleum
product
present
in
an
environmental
media
(
e.
g.,
soil,
water,
or
sediments).
While
it
provides
a
measure
of
the
overall
concentration
of
petroleum
hydrocarbons
present,
TPH
does
not
distinguish
between
different
types
of
petroleum
hydrocarbons.

Total
Kjeldahl
Nitrogen
(
TKN):
the
total
of
organic
and
ammonia
nitrogen.
TKN
is
determined
in
the
same
manner
as
organic
nitrogen,
except
that
the
ammonia
is
not
driven
off
before
the
digestion
step.

total
suspended
solids
(
TSS):
a
measure
of
the
suspended
solids
in
wastewater,
effluent,
or
water
bodies,
determined
by
tests
for
"
total
suspended
non­
filterable
solids."
(
See:
suspended
solids.)

(
http://
www.
epa.
gov/
OCEPAterms/
tterms.
html)

travel
cost
method
(
TCM):
method
to
determine
the
value
of
an
event
by
evaluating
expenditures
of
recreators.
Travel
costs
are
used
as
a
proxy
for
price
in
deriving
demand
curves
for
the
recreation
site.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

uptake:
the
movement
of
one
or
more
chemicals
into
an
organism
via
ingestion,
inhalation,
and/
or
through
the
skin.

vascular
plants:
plants
that
are
composed
of,
or
provided
with,
vessels
or
ducts
that
convey
fluids.
(
www.
infoplease.
com)

willingness­
to­
pay
(
WTP):
maximum
amount
of
money
one
would
give
up
to
buy
some
good.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

12­
18
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
ACRONYMS
AQUIRE:
AQUatic
Information
REtrieval
System
ASTER:
ASsessment
Tools
for
the
Evaluation
of
Risk
AWQC:
ambient
water
quality
criteria
BIODEG:
biodegradation
BOD:
biological
oxygen
demand
CA:
contingent
activity
CHEMFATE:
chemical
fate
CR:
contingent
rating
CV:
contingent
valuation
COD:
chemical
oxygen
demand
HAP:
hazardous
air
pollutant
HEAST:
Health
Effects
Assessment
Summary
Tables
IRIS:
Integrated
Risk
Information
System
Koc:
adsorption
coefficient
MCL:
maximum
contaminant
level
O&
G:
oil
and
grease
POC:
pollutant
of
concern
POTW:
publicly­
owned
treatment
work
PP:
priority
pollutant
QSAR:
quantitative
structure­
activity
relationship
RfD:
reference
dose
SCDM:
Superfund
Chemical
Data
Matrix
SF:
cancer
potency
slope
factor
T&
E:
threatened
and
endangered
TCM:
travel
cost
method
TKN:
Total
Kjeldahl
Nitrogen
TPH:
Total
Petroleum
Hydrocarbon
TSS:
total
suspended
solids
WQC:
human
health­
based
water
quality
criteria
WTP:
willingness­
to­
pay
12­
19
MP&
M
EEBA
Part
III:
Benefits
Chapter
12:
Benefit
Overview
REFERENCES
Amdur,
M.
O.,
J.
Doul,
and
C.
D.
Klaassen,
eds.
1991.
Cassarett
and
Doul's:
Toxicology,
the
Basic
Science
of
Poisons.
4th
ed.
New
York,
NY:
McGraw­
Hill
Inc.

Amdur,
M.
O.,
J.
Doul,
and
C.
D.
Klaassen,
eds.
1996.
Cassarett
and
Doul's:
Toxicology,
the
Basic
Science
of
Poisons.
5th
ed.
New
York,
NY:
McGraw­
Hill
Inc.

Syracuse
Research
Corporation
(
BIODEG,
CHEMFATE).
1999.
Syracuse
Research
Corporation's
Environmental
Fate
Databases.
Syracuse,
NY:
Syracuse
Research
Corporation.
http://
esc.
syrres.
com/
efdb/
BIODGSUM.
HTM
and
http://
esc.
syrres.
com/
efdb/
Chemfate.
htm.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1980.
Ambient
water
quality
criteria
documents.
Washington,
DC:

Office
of
Water,
U.
S.
EPA.
EPA
440/
5­
80
Series.
Also
refers
to
any
update
of
criteria
documents
(
EPA
440/
5­
85
and
EPA
440/
5­
87
Series)
or
any
Federal
Register
notices
of
proposed
criteria
or
criteria
corrections,
and
EPA
822­
Z­
99­
001.
The
most
recent
National
Recommended
Water
Quality
Criteria
used
in
this
report
were
published
in
the
Federal
Register
on
December
10,
1998.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1986.
Ambient
Water
Quality
Criteria
for
Dissolved
Oxygen.
EPA
440/
5­
86­
003.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1995.
Proceedings
of
the
First
Gulf
of
Mexico
Hypoxia
Management
Conference.
EPA­
55­
R­
97­
001.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1997.
Health
Effects
Assessment
Summary
Tables
(
HEAST).

Washington,
DC:
Office
of
Research
and
Development
and
Office
of
Emergency
and
Remedial
Response,
U.
S.
EPA.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998.
National
Water
Quality
Inventory.
1996
Report
to
Congress.

EPA
841­
R­
97­
008.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998/
99a.
QSAR.
Duluth,
MN:
Environmental
Research
Laboratory,

U.
S.
EPA.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998/
99b.
Aquatic
Toxicity
Information
Retrieval
(
AQUIRE)

Database.
Mid­
Continent
Ecology
Division
(
MED),
Duluth,
MN.
U.
S.
Environmental
Protection
Agency.
Database
retrieval
@
http://
www.
epa.
gov/
ecotox/.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998/
99c.
Assessment
Tools
for
Evaluation
of
Risk
(
ASTER)

Database.
Duluth,
MN:
Environmental
Research
Laboratory,
U.
S.
EPA.
1998
Database
retrieval.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998/
99d.
Integrated
Risk
Information
System
(
IRIS).
Washington,

DC:
U.
S.
EPA.
1998
Database
retrieval
@
http://
www.
epa.
gov/
iris/.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1999.
Progress
Report
on
the
EPA
Acid
Rain
Program.
U.
S.
EPA
Office
of
Air
and
Radiation.
EPA
430­
R­
99­
011.

Wexler,
P.,
ed.
1998.
Encyclopedia
of
Toxicology,
Volumes
1­
3.

12­
20
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
INTRODUCTION
EPA
expects
that
the
final
MP&
M
regulation
will
yield
a
range
of
human
health
benefits
by
reducing
effluent
discharges
to
waterways
used
for
fishing
or
drinking
water.

This
chapter
analyzes
four
categories
of
expected
human
health
benefits.
The
first
two
categories
involve
reductions
in
cancer
cases
from
two
exposure
pathways:
consumption
of
contaminated
fish
tissue
and
ingestion
of
contaminated
drinking
water
for
the
exposed
population.
EPA
evaluated
the
expected
annual
reduction
in
cancer
cases
in
the
exposed
population
and
the
associated
monetary
value
of
avoiding
those
cancer
cases.

EPA
quantified,
but
did
not
monetize,
two
additional
measures
of
human
health­
related
benefits.
The
first
is
the
changes
in
fish
consumption
and
drinking
water
exposures
to
non­
cancer
causing
pollutants
measured
against
non­
cancer
health
effect
reference
doses
(
RfDs),
an
indicator
of
non­

cancer
health
risk.
The
second
benefit
measure
is
the
change
in
occurrence
of
pollutant
concentrations
that
are
estimated
to
exceed
human
health­
based
ambient
water
quality
criteria
(
AWQC).

EPA
also
quantified
and
monetized
changes
in
health
risk
to
adults
and
children
from
reduced
exposure
to
lead.
This
analysis
is
presented
in
Chapter
14.

The
health­
related
measures
were
estimated
for
the
baseline
and
for
the
final
option
for
all
of
the
benefit
categories
analyzed.
In
addition,
EPA
estimated
health
benefits
for
alternative
options
which
EPA
considered
for
the
MP&
M
regulation.

The
reduction
in
the
health­
related
measures
(
i.
e.,
number
of
annual
cancer
cases)
from
baseline
to
the
post­
compliance
case
is
the
estimated
benefit
of
the
MP&
M
regulation.
As
discussed
in
Chapter
12,
EPA
estimated
national
benefits
for
the
regulation
based
on
sample
facility
data.
The
Agency
extrapolated
findings
from
the
sample
facility
analyses
to
the
national
level
using
two
alternative
extrapolation
methods:
(
1)
traditional
extrapolation
and
(
2)
post­
stratification
extrapolation.

Appendix
G
provides
detailed
information
on
the
extrapolation
approaches
used
in
this
analysis.
Chapter
13:
Human
Health
Benefits
CHAPTER
CONTENTS
13.1
...............
13­
2
13.1.1
from
Fish
Consumption
........
13­
2
13.1.2
from
Drinking
Water
Consumption
13­
8
13.1.3
s
above
Non­
cancer
Health
Thresholds
.................
........
13­
10
13.1.4
..............
13­
14
13.2
.................
...............
13­
17
13.2.1
ption
Cancer
Results
.....
13­
17
13.2.2
Water
Consumption
Cancer
Results
.................
...........
13­
19
13.2.3
er
Health
Threshold
Results
.
.
13­
19
13.2.4
n
Health
AWQC
Results
........
13­
21
13.3
..............
13­
22
13.3.1
e
Design
&
Analysis
of
Benefits
by
Location
of
Occurrence
...............
13­
22
13.3.2
Pollutants
.................
.........
13­
23
13.3.3
fects
of
Pollutants
............
13­
23
13.3.4
s
of
MP&
M
Pollutants
.................
.........
13­
23
13.3.5
ream
Effects
................
13­
24
13.3.6
ishing
Population
..........
13­
24
13.3.7
Treatment
of
Cancer
Latency
..........
13­
25
13.3.8
Treatment
of
Cessation
Lag
...........
13­
25
13.3.9
Use
of
Mean
Individual
Exposure
Parameters
.................
........
13­
26
13.3.10
Cancer
Potency
Factors
.............
13­
26
Glossary
.................
.................
.
13­
27
Acronyms
.................
.................
13­
28
References
.................
................
13­
29
Methodology
&
Data
Sources
Cancer
Cancer
Exposure
Human
Health
AWQC
Results
Fish
Consum
Drinking
Non­
canc
Huma
Limitations
and
Uncertainties
Sampl
In­
Waterway
Concentrations
of
MP&
M
Joint
Ef
Background
Concentration
Downst
Exposed
F
EPA
estimated
that,
for
combined
recreational
and
subsistence
angler
populations,
the
final
option
would
lead
to
a
marginal
reduction
in
cancer
cases.
The
total
monetized
human
health
benefits
from
reduced
cancer
cases
from
both
the
fish
consumption
and
drinking
water
pathways
are
essentially
negligible
(
i.
e.,
$
90
per
year
based
on
the
traditional
extrapolation
and
$
134
per
year
based
on
the
post­
stratification
extrapolation
(
2001$)).

Benefits
will
also
be
realized
in
the
form
of
reductions
in
non­
cancer
human
health
effects
(
e.
g.,
systemic
effects,
reproductive
toxicity,
and
developmental
toxicity)
from
reduced
contamination
of
fish
tissue
and
drinking
water
sources.
For
this
analysis,

EPA
estimates
the
numbers
of
individuals
in
the
exposed
populations
who
might
be
expected
to
realize
reduced
risk
of
non­
cancer
health
effects
in
the
post­
compliance
scenario.
To
evaluate
the
potential
benefits
of
reducing
the
in­
stream
concentrations
of
76
pollutants
that
cause
non­
cancer
health
effects,
EPA
estimated
target
organ­
specific
hazard
indices
(
HI)

for
drinking
water
and
fish
ingestion
exposures
in
both
the
baseline
and
post­
compliance
scenarios.
HI
values
below
one
are
generally
considered
to
suggest
that
exposures
are
not
likely
to
result
in
appreciable
risk
of
adverse
health
effects
during
a
lifetime,
and
values
above
one
are
generally
cause
for
concern,
although
an
HI
greater
than
one
does
not
necessarily
suggest
a
likelihood
of
adverse
effects.

13­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
The
results
of
EPA's
analysis
suggest
that
the
incremental
risk
of
non­
cancer
effects
from
pollutants
discharged
by
MP&
M
facilities
alone
is
quite
low.
This
analysis
found
that
HIs
for
the
entire
population
associated
with
sample
facilities
is
less
than
one
in
the
baseline.
The
results
of
EPA s
analysis
of
the
post­
compliance
scenario
indicate
that
hazard
indices
for
individuals
in
the
exposed
population
may
decrease
after
facilities
comply
with
the
MP&
M
regulation.
Increases
in
the
percentage
of
exposed
populations
that
would
be
exposed
to
no
risk
of
non­
cancer
adverse
human
health
effects
due
to
the
MP&
M
discharges
occur
in
both
the
fish
and
drinking
water
analyses.
Whether
the
incremental
shifts
in
HIs
are
significant
in
reducing
absolute
risks
of
non­
cancer
adverse
human
health
effects
is
uncertain
and
will
depend
on
the
magnitude
of
contaminant
exposures
for
a
given
population
from
risk
sources
not
accounted
for
in
this
analysis.

Finally,
EPA
analyzed
the
effect
of
the
final
regulation
on
occurrence
of
pollutant
concentrations
resulting
from
MP&
M
discharges
that
exceed
human
health­
based
AWQC.
EPA
estimated
that,
as
the
result
of
baseline
MP&
M
pollutant
discharges,
in­
stream
concentrations
exceed
human
health­
based
AWQC
in
78
and
112
receiving
reaches
nationwide
based
on
the
traditional
extrapolation
and
post­
stratification
extrapolation,
respectively.
EPA
estimated
that
none
of
these
exceedances
will
be
eliminated
under
the
final
option.

13.1
METHODOLOGY
&
DATA
SOURCES
Individuals
are
potentially
exposed
to
pollutants
from
MP&
M
facilities
via
consumption
of
contaminated
fish
tissue
and
drinking
water.
Potential
human
health
effects
include
cancer
and
non­
cancer
health
effects.
Risks
such
as
skin,
lung,
liver,

kidney,
and
bladder
cancer
and
leukemia
are
associated
with
exposure
to
13
MP&
M
pollutants
(
see
Table
13.1).
Non­
cancer
health
effects
are
associated
with
exposure
to
76
MP&
M
pollutants.
These
effects
include
increased
blood
pressure,

gastrointestinal
effects,
liver
and
kidney
toxicity,
cardiovascular
and
central
nervous
system
effects,
and
decreased
birth
weight
(
see
Table
13.2).

This
section
summarizes
the
methodology
for
estimating
national
benefits
for
three
benefit
categories:

1.
reduced
incidence
of
cancer
from
consumption
of
fish
taken
from
waterways
affected
by
MP&
M
industry
discharges,

2.
reduced
incidence
of
cancer
from
ingestion
of
water
taken
from
waterways
affected
by
MP&
M
industry
discharges,

and
3.
reduced
occurrence
of
pollutant
concentrations
resulting
from
MP&
M
discharges
that
exceed
human
health­
based
AWQC.

This
analysis
does
not
include
all
possible
human
health
benefits
and
does
not
provide
a
comprehensive
estimate
of
the
total
human
health
benefits
associated
with
the
final
MP&
M
rule.
Analyses
of
health
benefits
are
not
possible
for
a
significant
number
of
the
pollutants
whose
discharges
will
be
reduced
under
the
post­
compliance
scenario
due
to
the
lack
of
data
on
a
quantitative
relationship
between
ingestion
rate
and
the
potential
health
effects
associated
with
these
chemicals.

Beyond
these
important
limitations,
the
methodologies
used
to
assess
the
human
health
benefits
involve
significant
simplifications
and
uncertainties.
Elements
of
the
analysis
involving
significant
simplifications
and
uncertainties
include
the
following:
sample
design
and
analysis
of
benefits
by
location
of
occurrence;
estimation
of
in­
waterway
concentrations
of
MP&
M
pollutants;
consideration
of
the
joint
effects
of
pollutants;
consideration
of
background
concentrations
of
MP&
M
pollutants;
consideration
of
downstream
effects;
and
estimation
of
the
exposed
fishing
population.
Section
13.3
provides
more
detail
on
limitations
and
uncertainties
associated
with
the
human
health
benefits
analyses.
Whether
these
simplifications
and
uncertainties,
taken
together,
are
likely
to
lead
to
an
understatement
or
overstatement
of
the
estimated
economic
values
for
the
human
health
benefits
that
were
analyzed
is
not
known.

13.1.1
Cancer
from
Fish
Consumption
The
analysis
of
reduced
annual
occurrence
of
cancer
in
exposed
populations
via
the
fish
consumption
pathway
involves
three
analytic
steps:

 
estimating
the
reduced
annual
risk
of
incurring
cancer
per
exposed
individual;

 
estimating
the
population
that
would
be
expected
to
benefit
from
reduced
contamination
of
fish;
and
13­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
 
calculating
the
c
hange
in
the
nu
mbe
r
of
can
cer
ev
ents
in
the
expo
sed
p
opu
lation.

Each
step
is
discussed
in
detail
below.

a.
g
change
in
individual
cancer
risk
The
estimated
increm
ental
risk
to
an
individual
of
de
veloping
ca
ncer
is
based
on
four
factors:
1
 
the
quantity
of
carcinoge
nic
chemica
ls
that
MP
&
M
facilities
discharge
to
waterways,

 
the
rate
at
which
the
discharged
chemicals
accumulate
in
fish
tissue,

 
the
cancer
effect
of
the
chemicals,
and
 
the
rate
of
personal
consumption
of
contaminated
fish.

For
each
sample
M
P&
M
facility
and
the
waterway
to
which
it
discharges,
EPA
calculated
the
incremental
cancer
risk
to
four
population
classes
with
different
fish
consumption
rates:
children
in
families
that
participate
in
recreational
angling,
children
in
families
tha
t
particip
ate
in
sub
sistence
angling,
adults
in
families
that
particip
ate
in
rec
reational
ang
ling,
and
adults
in
families
that
participate
in
subsistence
angling.
sk
values
for
baseline
(
i.
e.,
before
regula
tion)
p
ollutant
d
ischarg
es
and
for
po
st­
com
plianc
e
disch
arges
base
d
on
the
po
licy
options
co
nsidered
in
th
e
final
rule
analysis.
iscussion
summ
arizes
the
increme
ntal
cancer
risk
calculations.

EPA
calculated
the
in­
waterway
pollutant
concentrations
for
each
reach
receiving
discharges
from
an
M
P&
M
facility
using
a
simplified
dilution
model
for
all
chemicals
for
which
a
quantitative
relationship
between
ingestion
rate
and
the
annual
probability
of
developing
cancer
has
been
estimated.
reach 
is
a
specific
length
of
river,
lake
shoreline,
or
marine
coastline,
and
an
 
MP&
M
reach 
is
one
to
which
a
n
M
P&
M
facility
discharges.
2
This
analysis
considered
only
the
discharge
reach
and
did
not
estimate
concentrations
below
the
initial
MP&
M
reach.
T
he
water
quality
model
used
for
calculating
in­

waterway
po
llutant
concentrations
acc
ounts
for
the
dilution
chara
cteristics
of
different
water
body
types
(
i.
e.,
streams,

estuaries,
and
lakes).
It
does
not
account
for
other
fate
processes,
such
as
chemical
degradation
or
photolysis.
The
estimated
pollutant
concentrations
reflect
the
average
pollutant
concentrations
in
the
reach
to
which
a
facility
discharges.
For
additional
details
on
the
calculation
of
waterway
concentrations,
see
Appendix
I.

The
incremental
cancer
risk
associated
with
each
pollutant
was
calculated
based
on
the
estimated
concentration
of
the
pollutant
in
the
affected
waterway,
the
assumed
uptake
of
the
pollutant
into
fish
flesh,
the
daily
rate
of
fish
ingestion,
and
the
cancer
risk
factor
for
each
pollutant.
a
for
calculating
the
risk
to
an
individual
from
consumption
of
a
given
chemical
is
as
follows:

(
13.1)

where:

Risk
=
incremental
risk
of
incurring
cancer
from
fish
consumption
(
change
in
probability);

C
=
pollutant
concentrations
in
surface
water
(
 
g/
l);

CF1
=
conversion
factor,
micrograms
to
milligrams
(
0.001
mg/
 
g);

BCF
=
bioconcentration
factor
of
pollutant
in
fish
(
l/
kg);

CR
=
human
consumption
rate
of
fish
(
kg/
day);

EF
=
exposure
frequency
(
365
days/
year);

ED
=
exposure
duration
(
years);

BW
=
human
body
weight
(
70
kg
for
adults
and
30
kg
for
children
under
18);
Estimatin
EPA
calculated
the
incremental
cancer
ri
The
following
d
A
 

The
formul
1
The
risk
value
is
referred
to
as
the
incremental
risk
because
it
is
the
incremental
lifetime
probability
that
an
individual
will
develop
cancer
above
and
beyond
the
baseline
probability
posed
by
all
other
extant
factors
that
contribute
to
a
risk
of
developing
cancer.

2
A
reach
is
a
length
of
river,
shoreline,
or
coastline
with
relatively
uniform
water
flow
characteristics.
Thus,
it
is
reasonable
to
assume
that
pollutant
dischargers
have
a
relatively
uniform
effect
on
concentrations
within
a
reach.

13­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
LT
=
human
lifetime
(
years);

CF2
=
conversion
factor,
years
to
days
(
365
days/
year);
and
SF
=
pollutant
cancer
potency
factor
(
mg/
kg/
day)­
1
.

The
pollutants
analyzed
and
their
cancer
potency
factors
are
presented
in
Table
13.1.
EPA
used
the
relationship
outlined
above
to
estimate
lifetime
risk
values
for
individuals
in
subsistence
and
recreational
fishing
households.
The
risks
to
recreational
and
subsistence
households
are
estimated
over
two
lifetime
segments.
Specifically,
children
living
in
recreational
fishing
households
are
assumed
to
consume
7.27
grams
per
day
(
0.007
kg/
day)
of
freshwater/
estuarine
fish
over
an
18­
year
period
(
ages
0
to
18).
Adults
are
assumed
to
consume
17.5
grams
per
day
(
0.018
kg/
day)
of
freshwater/
estuarine
fish
over
a
52­
year
period
(
ages
18
to
70).
Risks
for
individuals
living
in
recreational
and
subsistence
fishing
households
differ
in
the
assumed
consumption
rates.
Children
living
in
subsistence
fishing
households
are
assumed
to
consume
60.58
grams
per
day
(
0.061
kg/
day)
of
freshwater/
estuarine
fish
over
an
18­
year
period
(
ages
0­
18).
Adults
in
subsistence
households
are
assumed
to
consume
142.4
grams
per
day
(
0.142
kg/
day)
of
freshwater/
estuarine
fish
over
a
52­
year
period
(
ages
18
to
70).
The
total
lifetime
incremental
risk
for
these
households
is
calculated
by
summing
the
risks
for
both
lifetime
segments.

Fish
consumption
rates
for
adults
are
taken
from
the
Methodology
for
Deriving
Ambient
Water
Quality
Criteria
for
the
Protection
of
Human
Health
(
EPA,
2000a).
Both
these
rates,
142.4
g/
day
for
adult
subsistence
anglers
and
17.5g/
day
for
adult
recreational
anglers,
are
used
for
the
specific
sub­
population
that
they
represent.
EPA
was
not
able
to
break
the
data
supporting
these
rates
down
by
gender
or
age
group
for
use
in
this
analysis.

EPA
has
determined
that
the
fish
consumption
rate
of
142.4
g/
day
for
adult
subsistence
anglers
falls
within
the
range
of
the
arithmetic
mean
of
adult
subsistence
angler
studies
representative
of
the
United
States
(
EPA,
1998).
The
value
represents
the
average
consumption
rate
for
this
population
of
anglers.
It
represents
uncooked,
fresh
and
estuarine
finfish
and
shellfish.

This
rate
is
reported
on
an
uncooked
basis
because
pollutant
concentration
data
is
reported
on
an
uncooked
weight
basis.

Similarly,
the
fish
consumption
rate
of
17.5
g/
day
falls
within
the
average
consumption
rate
for
adult
recreational
anglers.

This
rate
also
represents
uncooked,
fresh
and
estuarine
finfish
and
shellfish.
3
Fish
consumption
rates
for
children
in
recreational
angling
households
are
based
on
W
est
et
al.
(
1989)
in
the
Exposure
Factors
Handbook
(
EPA
1997c).
This
study
has
the
most
specific
data
for
this
population
group
and
cites
an
intake
of
7.27
grams/
day
of
freshwater
and
estuarine
fish
for
children
in
recreational
angling
households.
For
children
in
subsistence
angling
households,
the
consumption
rate
was
extrapolated
from
the
7.27
grams/
day
rate
for
children
in
recreational
angling
households
using
the
proportional
relationship
between
consumption
rates
for
adult
subsistence
and
recreational
anglers
(
142.4
grams/
day
divided
by
17.5
grams/
day).
The
consumption
rate
for
children
in
subsistence
angling
households
is
calculated
to
be
60.58
grams/
day.

Currently,
data
on
marine
fish
consumption
rates
for
recreational
anglers
and
subsistence
anglers
are
not
readily
available.

Given
that
there
are
few
marine
reaches
affected
by
the
MP&
M
effluent
guideline,
EPA
decided
to
use
the
fresh
and
estuarine
fish
consumption
rates
in
lieu
of
marine
fish
consumption
rates.
This
may
result
in
underestimation
of
benefits,

however,
it
may
also
be
argued
that
few
subsistence
fishers
eat
fresh/
estuarine
fish
and
marine
fish
at
the
same
rate.

3
For
detail
see
memorandum
Fish
Consumption
Rates
by
Lynn
Zipf
(
EPA,
2002).

13­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.1:
Cancer
Potency
Factors
for
MP&
M
Pollutants
CAS
Number
Regulated
Pollutant
Cancer
Potency
Factor
(
mg/
kg/
day)
a
Drinking
Water
Criterion?

62533
Aniline
0.0057
62759
Nitrosodimethylamine,
N­
51
67663
Trichloromethane
0.0061
Yes
75003
Chloroethane
0.0029
75092
Dichloromethane
0.0075
Yes
75354
Dichloroethene,
1,1­
0.6
Yes
78591
Isophorone
0.00095
79016
Trichloroethene
0.011
Yes
86306
Nitrosodiphenylamine,
N­
0.0049
117817
Bis(
2­
ethylhexyl)
phthalate
0.014
Yes
123911
Dioxane,
1,4­
0.011
127184
Tetrachloroethene
0.052
Yes
7440382
Arsenic
1.5
Yes
a
The
cancer
potency
factor
is
the
incremental
probability
of
developing
cancer
over
a
lifetime
resulting
from
ingestion
of
the
indicated
chemical
at
the
rate
of
one
milligram
per
day
per
kilogram
of
body
mass.
For
the
incremental
rates
of
exposure
in
this
analysis
and
assuming
reasonable
background
chemical
exposures,
the
potency
factor
may
be
reasonably
assumed
to
be
a
linear
constant.

Source:
U.
S.
EPA
(
1998/
99);
U.
S.
EPA
(
1997a).

The
pollutant­
specific
risks
to
recreational
and
subsistence
anglers
from
MP&
M
facility
discharges
were
then
summed
across
pollutants
for
each
type
of
angler,
to
obtain
incremental
risks
for
each
population
group
from
each
facility s
discharge.
EPA
developed
separate
estimates
of
cancer
risk
for
each
combination
of
angler
type
and
facility
discharging
at
least
one
pollutant
with
a
cancer
risk
factor.
The
total
change
in
probability
of
developing
cancer
from
exposure
to
more
than
one
MP&
M
pollutant
is
assumed
to
be
the
sum
of
the
incremental
risk
effects
from
each
pollutant:
that
is,
the
effects
of
the
individual
pollutants
are
assumed
to
be
linearly
additive.
4
The
annual
increased
risk
of
cancer
was
estimated
by
dividing
the
increased
lifetime
risk
values
by
70
(
an
estimate
of
lifetime).

b.
Estimating
the
affected
population
The
population
exposed
to
contaminated
fish
and
thus
expected
to
benefit
from
reduced
discharges
includes
recreational
and
subsistence
anglers
who
fish
the
affected
reaches,
as
well
as
members
of
such
anglers'
households.
The
geographic
area
from
which
anglers
would
travel
to
fish
a
reach
is
assumed
to
include
only
those
counties
that
abut
a
given
reach.
5
This
assumption
is
based
on
the
finding
in
the
1991
National
Survey
of
Fishing,
Hunting,
and
Wildlife­
Associated
Recreation
that
65
percent
of
anglers
travel
less
than
50
miles
to
fish
(
U.
S.
Department
of
the
Interior,
1993).
The
average
diameter
of
the
counties
abutting
the
reaches
receiving
discharges
from
the
sample
MP&
M
facilities
is
approximately
20
miles.
Given
that
counties
may
have
different
shapes
and
that
the
road
distance
to
the
fishing
site
is
likely
to
be
greater
than
a
straight
line,
the
MP&
M
approach
is
likely
to
account
for
the
majority
of
anglers
that
are
likely
to
fish
the
affected
reach.
It
is,
however,
likely
to
4
Note
that
the
assumption
of
linear
additivity
of
cancer
risk
effects
applies
not
only
to
the
combination
of
pollutants
from
a
single
facility
but
also
to
the
combined
effects
of
multiple
facility
discharges.
When
more
than
one
MP&
M
facility
discharges
to
the
same
affected
waterway
a
circumstance
found
to
occur
with
some
frequency
in
the
sample
facility
data
the
combination
of
the
multiple
facility
discharges
may
be
accounted
for
by
simply
analyzing
the
effects
of
each
facility
independently.
The
cancer
effects
from
multiple
facilities
can
be
aggregated
to
estimate
cancer
cases
in
the
exposed
population.

5
The
exposed,
and
thus
potentially
benefiting,
population
would
also
include
a
category
of
 
all
other
individuals 
who
consume
freshwater
and
estuarine
fish.
Although
these
individuals
are
expected
to
have
a
much
lower
average
daily
consumption
rate
than
anglers
in
the
adjacent
counties,
they
nevertheless
would
likely
receive
some
benefit
from
reduced
exposure
to
pollutants
through
fish
consumption.
This
analysis
omits
this
consumption
category
and
the
associated
benefit
estimate.

13­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
introduce
a
downward
bias
into
the
estimate
of
the
affected
population.
Given
that
anglers
tend
to
travel
farther
to
visit
sites
of
very
good
or
exceptional
quality,
the
magnitude
of
this
bias
will
depend
on
the
fishing
quality
of
the
affected
sites.

Estimating
the
number
of
persons
fishing
a
reach
involved
the
following
steps:

 
estimating
the
licensed
fishing
population
in
counties
abutting
MP&
M
reaches;

 
estimating
the
population
of
subsistence
fishermen
in
counties
abutting
MP&
M
reaches;

 
estimating
the
fraction
of
the
total
fishing
population
in
counties
abutting
an
MP&
M
reach
that
fish
the
MP&
M
reach
and,
from
that
fraction,
the
size
of
population
expected
to
fish
each
MP&
M
reach;

 
adjusting
the
calculated
fishing
populations
for
the
presence
of
fish
advisories;
and
 
including
family
members
in
the
exposed
population
estimates.

 
Estimating
the
licensed
fishing
population
in
counties
abutting
MP&
M
reaches
The
number
of
fishing
licenses
sold
in
counties
abutting
MP&
M
reaches
is
assumed
to
approximate
the
number
of
anglers
residing
in
the
abutting
counties.
EPA
excluded
the
nonresident,
one­
day,
and
three­
day
license
categories
from
the
total
number
of
licenses
used
in
this
analysis.
Data
on
fishing
licenses
are
not
available
for
every
state
in
which
MP&
M
facilities
are
located.
EPA
used
state­
level
data
to
estimate
the
number
of
fishing
licenses
per
county
for
those
states
for
which
county­

level
data
were
not
assembled.
Total
state
licenses
were
apportioned
to
counties
based
on
the
ratio
of
total
population
in
the
county
abutting
a
discharge
reach
to
total
state
population.
Where
an
M
P&
M
reach
spans
more
than
one
county,
fishing
licenses
were
summed
across
all
counties
abutting
the
discharge
reach.
Where
a
reach
lies
in
more
than
one
state,
EPA
separately
calculated
the
number
of
licenses
for
the
abutting
county(
ies)
based
on
the
fishing
license
and
county
population
data
for
the
respective
states.

EPA s
analysis
does
not
account
for
recreational
anglers
who
do
not
purchase
licenses
as
required
by
law.
This
may
result
in
a
significant
underestimate
of
the
fishing
population
at
risk
from
exposure
to
MP&
M
pollutants.
For
example,
the
1996
National
Survey
of
Fishing,
Hunting,
and
Wildlife­
Associated
Recreation
found
that
34
percent
of
the
anglers
(
16
years
of
age
and
older)
did
not
have
licenses
(
U.
S.
Department
of
the
Interior,
1996).

 
Estimating
the
population
of
subsistence
fishermen
in
counties
abutting
MP&
M
reaches
Although
fishing
licenses
may
be
sold
to
subsistence
fishermen,
many
of
these
individuals
do
not
purchase
fishing
licenses.

The
extent
of
subsistence
fishing
in
the
U.
S.
or
in
individual
states
is
not
generally
known.
For
this
analysis,
EPA
assumed
that
the
number
of
subsistence
fishermen
would
be
an
additional
5
percent
of
the
licensed
fishing
population.
6
That
is,
after
estimating
the
licensed
fishing
population
in
counties
abutting
MP&
M
reaches,
EPA
added
5
percent
to
this
value
as
the
estimated
number
of
subsistence
fishermen.
7
 
Estimating
the
population
fishing
an
MP&
M
reach
EPA
assumed
that
fishing
activity
among
anglers
residing
within
counties
abutting
a
discharge
reach
is
distributed
evenly
among
all
reach
miles
within
those
counties.
Thus,
the
number
of
anglers
who
fish
an
MP&
M
reach
was
estimated
by
computing
the
length
of
the
reach
as
a
percentage
of
total
reach
miles
within
corresponding
counties
and
multiplying
the
estimated
ratio
by
the
total
fishing
population
in
counties
abutting
the
reach.

 
Adjusting
for
fish
advisories
For
MP&
M
reaches
where
fish
advisories
are
in
place
(
typically
due
to
non­
MP&
M
regulated
pollutants
such
as
dioxin
and
mercury),
EPA
assumed
that
some
proportion
of
anglers
would
adhere
to
the
advisory
and
not
fish
those
reaches
(
U.
S.
EPA,

1999a).
Past
studies
suggest
that
anglers
have
a
high,
although
not
complete,
level
of
awareness
of
fish
advisories.
These
studies
further
suggest
that
while
anglers
may
change
their
behavior
in
response
to
fish
consumption
advisories,
they
do
not
necessarily
refrain
from
fishing
in
these
reaches
or
consuming
fish
taken
from
reaches
under
an
advisory.
For
example,

6
It
is
important
to
estimate
recreational
and
subsistence
populations
separately
because
fish
consumption
rates
for
subsistence
anglers
are
considerably
higher
than
those
for
recreational
anglers.

7
The
environmental
justice
analysis
presented
in
Chapter
17
of
this
report
shows
that
the
percent
of
residents
living
below
the
poverty
level
in
the
counties
affected
by
MP&
M
discharges
ranges
from
7.4
to
25.2.
Thus,
the
assumption
that
subsistence
anglers
are
an
additional
5%
of
the
licensed
fishing
population
is
likely
to
provide
a
reasonable
estimate
of
the
subsistence
anglers
population.

13­
6
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
studies
conducted
by
Belton
et
al
(
1986),
Knuth
and
Velicer
(
1990),
Silverman
(
1990),
W
est
et
al.
(
1989),
Connelly,
Knuth,

and
Biso
gni
(
19
92),
and
C
onne
lly
and
K
nuth
(
1
993
)
indica
te
that
50
to
87
percent
of
an
glers
surveyed
were
a
ware
of
state
fish
advisories
on
water
bodies
where
they
fish.

These
studies
also
indicate
that
only
10
to
34
percent
of
anglers
who
were
aware
of
advisories
modified
their
fishing
behavior
in
response
by
no
longe
r
fishing
a
p
articular
locatio
n,
chan
ging
the
locatio
n
in
whic
h
they
fish,
o
r
taking
fe
wer
fishing
trips.

Ho
wever,
13
to
68
p
ercen
t
of
anglers
who
were
a
ware
of
advisories
changed
their
consumption
or
preparation
h
abits
in
response
to
advisories.
udy
by
Knuth
and
Velicer
(
1990)
also
found
some
confusion
among
anglers
regarding
which
waters
were
under
advisory:
37
percent
of
fishermen
actually
fishing
in
waters
under
advisory
reported
that
they
were
fishing
in
uncontam
inated
waters.

On
the
basis
of
these
data,
EPA
assumed
that
recreational
fishing
activity
would
be
20
percent
less
on
reaches
subject
to
an
advisory
than
wo
uld
otherwise
b
e
estimated.
A
also
assum
ed
that
fish
advisories
do
not
affect
fishing
participation
by
subsistence
anglers;
thus,
no
adjustment
was
made
to
the
estimates
of
the
subsistence
fishing
population
based
on
the
presence
of
fish
advisories.

The
assumed
20
pe
rcent
decrease
in
recreationa
l
fishing
could
lead
to
either
an
o
verestimate
or
un
derestimate
o
f
the
risk
assoc
iated
with
consump
tion
of
contam
inated
fish.
ne
thing,
anglers
who
c
hange
loca
tions
may
simp
ly
be
switching
to
other
locatio
ns
where
advisories
are
in
p
lace
and
therefore
maintain
or
increase
their
current
risk.
lso,
those
who
continue
to
fish
contaminated
w
aters
may
chang
e
their
consum
ption
and
prepa
ration
habits
to
minimize
the
risks.
Data
on
the
sp
ecific
fish
advisories
was
pulled
from
EP
A s
on­
line
Listing
of
Fish
and
Wildlife
Advisories
(
U.
S.
EPA
,
1999a).

 
Including
family
mem
bers
in
the
exposed
population
estimates
EPA
assumed
that,
in
addition
to
anglers
themselves,
families
of
anglers
would
also
consume
fish
taken
from
waters
affected
by
MP
&
M
facility
discharges.
Therefore,
for
each
MP&
M
reach,
EP
A
multiplied
the
estimated
numbers
of
recreational
and
subsistence
anglers
fishing
the
affected
reaches
by
2.65,
the
size
of
the
average
U.
S.
household
in
1996
based
on
C
urrent
Population
Reports,
(
U.
S.
Bureau
of
the
Census,
1997).
These
calculations
yielded
the
household
populations
of
recreational
and
subsistence
anglers
who
are
estimated
to
consume
fish
from
the
reach
to
which
the
MP&
M
facility
discharges,
either
directly
or
indirectly
through
a
POT
W
.
EPA
expe
cts
that
family
members
will
benefit
from
reduced
M
P&
M
industry
discharges
by
consuming
fish
that
has
lower
levels
of
pollutant
contamination.

c.

EPA
calculated
the
number
of
cancer
cases
associated
with
the
pollutant
discharges
(
baseline
and
post­
compliance)
from
each
facility
by
multiplying
the
incremental
cancer
risk
value
for
the
two
population
classes
times
the
estimated
sizes
of
the
population
classes
living
near
the
facility.
of
the
incremental
risk
value
and
the
population
size
yields
the
number
of
annual
can
cer
ev
ents
in
the
given
p
opu
lation
cla
ss
estima
ted
to
result
from
consump
tion
of
fish
ta
ken
fro
m
wa
terways
affected
by
MP&
M
pollutant
discharges.
the
values
for
the
recreational
and
subsistence
fishing
household
classes
yields
the
total
number
of
cancer
cases
associated
with
the
sample
facility
discharges.
Because
the
number
of
cancer
cases
apply
to
sample
facilities,
EP
A
extrapo
lated
the
samp
le
results
to
the
total
M
P&
M
pop
ulation
b
y
multiplying
the
resu
lt
obta
ined
fo
r
each
samp
le
facility
by
its
sam
ple
we
ight
and
summ
ing
the
sa
mple
­
weighte
d
facility
resu
lts.
formu
la
follows:

(
13.2)

where:

TCCf
c
=
total
national
estimate
of
annual
cancer
cases
associated
with
consumption
of
contaminated
fish
tissue
(
baseline
or
post­
compliance);

Wti
=
facility
samp
le
weigh
t
i
(
i
=
1
to
N
facilities,
where
N
is
the
number
of
facilities
in
the
sample);

POPi,
sprt
=
exposed
pop
ulation
in
recreational
fishing
househo
lds
for
the
reac
h
to
which
facility
i
discha
rges
(
with
adjustments
as
indicated
for
the
presence
of
fish
consumption
advisories);

POPi,
sbst
=
exposed
pop
ulation
in
subsistence
fishing
households
for
the
reac
h
to
which
facility
i
discharges;
The
st
EP
For
o
A
Calculating
the
change
in
the
number
of
cancer
events
in
the
exposed
population
The
product
Summing
The
13­
7
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Riski,
sprt
=
incremental
cancer
risk
from
fish
consumption
in
the
recreational
fishing
household
population
assoc
iated
with
MP&
M
pollutant
discharges
from
facility
i;
and
Riski
sbst
=
incremental
cancer
risk
from
fish
consumption
in
the
subsistence
fishing
household
population
assoc
iated
with
MP&
M
pollutant
discharges
from
facility
i.

These
values
were
calculated
for
the
baseline
and
post­
compliance
discharge
cases.
difference
is
the
number
of
cancer
cases
estimated
to
be
avoided
annually
through
the
fish
consumption
pathway
as
a
result
of
the
final
regulation.

13.1.2
Cancer
from
Drinking
Water
Consumption
Th
e
analysis
of
red
uced
cancer
incid
ence
via
the
d
rinking
w
ater
pathway
involve
s
three
analytical
step
s
that
are
largely
parallel
to
those
performed
for
the
fish
co
nsumption
pathw
ay:

 
estimating
cancer
risk
to
an
exposed
individual
from
consumption
of
contaminated
drinking
water,

 
estimating
the
population
that
would
benefit,
and
 
calculating
the
change
in
the
number
of
cancer
events
in
the
exposed
population.

The
majo
r
differences
in
the
analysis
for
the
drinking
water
pathway
involve
the
identification
of
the
exposed
po
pulation
and
the
analysis
of
pollutant
discharge
effects
in
both
the
reach
to
which
a
facility
discharges
and
reaches
downstream
of
the
discharge
p
oint.

a.
water
consumption
Estimating
cancer
risk
from
consumption
of
drinking
water
affected
by
MP&
M
discharges
requires
calculating
in­
waterway
pollutant
concentrations
in
locatio
ns
whe
re
drin
king
wa
ter
treatm
ent
system
s
draw
water
fo
r
pub
lic
con
sump
tion.
his
analysis
involves
three
eleme
nts:

 
estimating
in­
waterway
pollutant
concentrations
for
each
pollutant
in
the
reach
to
which
a
facility
directly
or
indirec
tly
discharges.
he
me
thod
and
fo
rmulas
for
this
calculation
are
ide
ntical
to
tho
se
describe
d
for
the
analysis
of
cancer
effec
ts
for
the
fish
consumptio
n
pathway.

 
estimating
the
pollutant
concentrations
over
a
distance
of
500
kilometers
downstream
from
each
facility s
discharge
reach,
using
an
exponential
decay
model
in
which
pollution
concentrations
diminish
below
the
initial
point
of
discharge
(
e.
g.,
dilution,
adso
rption,
partitioning,
vola
tilization,
an
d
hydrolysis).
ethod
s
used
to
calculate
downstream
pollutant
concentrations
are
described
in
more
detail
in
Appendix
H.

 
identifying
the
location
of
any
drinking
water
intakes
in
the
initial
and
downstream
reaches
where
pollutant
concentrations
were
calculated
and
assigning
pollutant
concentration
values
to
each
relevant
intake
point.
The
EPA's
Safe
Drinking
Water
Information
System
(
SDWIS)
file
in
the
Risk
Screening
Environmental
Indicator
(
RS
EI)
model
provided
information
on
drinking
water
intakes
(
U.
S.
EPA
,
1999b).

Estimated
pollutant
concentrations
at
each
drinking
water
intake
determines
cancer
risk.
nking
water
treatment
systems
will
reduce
concentrations
to
below
adverse
effect
thresholds
for
all
chemicals
for
which
EPA
has
pub
lished
a
drinking
water
criterion
.
refore
,
pollutants
exam
ined
in
the
M
P&
M
drinkin
g
water
analysis
inc
lude
o
nly
six
carcinogens
for
which
current
drinking
water
criteria
are
not
available.
See
Table
13.1
for
a
list
of
the
pollutants,
their
cancer
potency
factors,
and
drinking
water
criteria.

The
formula
for
calculating
the
incremental
risk
to
an
individual
resulting
from
the
discharge
of
a
given
pollutant
from
a
given
facility
at
reaches
with
a
known
pu
blic
drinking
water
intake
is
as
follows:

(
13.3)

where:

Risk
=
incremental
risk
of
incurring
cancer
from
drinking
water
consumption
(
change
in
probability),
calculated
at
each
drinkin
g
water
intake
w
ithin
50
0
km
of
the
initial
d
ischarg
e
po
int;
The
Estimating
cancer
risk
from
drinking
T
T
M
EPA
assumed
dri
The
13­
8
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
C
=
pollutant
concentration
in
surface
water
in
the
reach
with
an
intake
(
 
g/
l);

CF1
=
conversion
factor,
micrograms
to
milligrams
(
0.001
mg/
 
g);

CR
=
human
consumption
rate
of
water
(
1.24
l/
day);

EF
=
exposure
frequency
(
350
days/
year);

ED
=
exposure
duration
(
70
years);

BW
=
human
body
weight
(
70
kg);

LT
=
human
lifetime
(
70
years);

CF2
=
conversion
factor
(
365
days/
year);
and
SF
=
pollutant
can
cer
p
otenc
y
factor
(
m
g/
kg/
day)­
1
.

The
consumption
rate
of
1.24
liters
per
day
used
in
this
analysis
to
represent
the
average
daily
consumption
of
drinking
water
by
a
person
in
the
United
States
is
taken
from
Estimated
Per
Capita
Water
Ingestion
in
the
United
States
(
EPA,
2000b).

reco
mmended
in
the
Exp
osure
Facto
rs
Ha
ndb
ook
(
1997c
),
EP
A
use
s
an
exposure
freq
uenc
y
of
35
0
da
ys
per
ye
ar
to
es
timate
the
increased
risk
of
cancer
from
consuming
drinking
water
supplied
by
drinking
water
systems
with
intakes
on
local
surface
water
b
odie
s.

The
incremental
individual
risk
from
each
facility s
pollutants
are
then
summed
over
pollutants
at
each
drinking
water
intake
to
calculate
the
incremental
risk
at
each
intake
resulting
from
pollutant
discharges
by
each
upstream
facility.
The
findings
carried
forward
to
the
next
step
include
the
incremental
cancer
risk
for
each
combination
of
facility
and
associated
drinking
water
intake(
s).

To
estimate
the
annual
increa
sed
risk
of
cance
r
in
consume
rs
served
by
d
rinking
water
intakes
affected
b
y
MP
&
M
discharges,

the
lifetime
risk
values
were
then
divided
by
70
years
(
an
estimate
of
lifetime).
These
values
were
calculated
for
both
the
baseline
and
post­
com
pliance
discha
rge
cases.

b.

The
exposed
population
for
each
combination
of
discharging
facility
and
drinking
water
intake
is
the
general
population
served
by
the
drinking
water
system
for
which
the
drinking
water
intake
was
identified.
fe
Drinking
Water
Information
System
(
SDW
IS)
file
in
the
Risk
Screening
Environmental
Indicator
(
RSEI)
model
provided
information
on
drinking
water
intakes.

c.

EPA
calculated
the
number
of
cancer
cases
for
baseline
and
post­
compliance
pollutant
discharges
for
each
combination
of
facility
and
affected
drinking
water
intake
by
multiplying
the
incremental
cancer
risk
value
times
the
population
served
by
the
water
system
drawing
water
at
the
drinking
water
intake.

The
total
number
of
cancer
cases
associated
with
the
facility
discharges
is
the
sum
of
cancer
cases
over
all
drinking
water
intakes.
PA
extrap
olated
the
sam
ple
results
to
the
to
tal
M
P&
M
pop
ulation
b
y
multiplying
the
resu
lt
for
eac
h
sam
ple
fac
ility
by
its
sample
weight
and
summing
the
sample­
weighted
facility
results.
Because
incremental
cancer
effects
are
assumed
to
be
linearly
ad
ditive,
ca
ncer­
risk
effects
are
aggre
gated
over
facilities
and
drinkin
g
water
intakes
b
y
simple
add
ition
of
the
effects
calculated
sep
arately
for
each
co
mbination
o
f
facility
and
drinking
wa
ter
intake.
ula
follows:

(
13.4)

where:

TCCdw
=
total
national
estimate
of
cancer
cases
associated
with
consumption
of
chemically­
contaminated
drinking
water
(
baseline
or
post­
compliance);

Wti
=
facility
samp
le
weigh
t
i
(
i
=
1
to
N
facilities);

POPi,
j
=
population
exposed
to
discharges
by
facility
i
at
drinking
water
intake
j
(
j
=
1
to
M
water
supply
intakes);
and
Riski,
j
=
increm
ental
ca
ncer
risk
for
d
ischarg
es
by
fac
ility
i
at
drinking
water
intake
j.

EPA
calculated
these
values
for
the
baseline
and
post­
compliance
discharge
cases.
ference
in
the
values
is
the
number
of
drinking
water
asso
ciated
canc
er
cases
estimated
to
be
avo
ided
ann
ually
by
reduced
MP
&
M
industry
discharges.
As
Estimating
the
benefiting
population
Sa
Calculating
the
changes
in
the
number
of
cancer
events
E
The
form
The
dif
13­
9
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
13.1.3
Exposures
above
Non­
cancer
Health
Thresholds
Exposed
populations
are
also
at
risk
of
developing
non­
cancer
health
problems
(
including
systemic,
reproductive,

immunological,
neurological,
or
circulatory
problems)
from
fish
ingestion
and
water
consumption.
The
common
approach
for
assessing
the
risk
of
non­
cancer
health
effects
from
the
ingestion
of
a
pollutant
is
to
calculate
a
hazard
quotient
by
dividing
an
individual's
oral
exposure
to
the
pollutant,
expressed
as
a
pollutant
dose
in
milligrams
per
kilogram
body
weight
per
day
(
mg/
kg/
day),
by
the
pollutant's
oral
reference
dose
(
RfD).
An
RfD
is
defined
as
an
estimate
(
with
uncertainty
spanning
perhaps
an
order
of
magnitude)
of
a
daily
oral
exposure
that
likely
would
not
result
in
the
occurrence
of
adverse
health
effects
in
humans,
including
sensitive
individuals,
during
a
lifetime.
Toxicologists
typically
establish
an
RfD
by
applying
uncertainty
factors
to
the
lowest­
or
no
observed
adverse
effect
level
(
NOAEL)
for
the
critical
toxic
effect
of
a
pollutant.
A
hazard
quotient
less
than
one
means
that
the
pollutant
dose
to
which
an
individual
is
exposed
is
less
than
the
RfD,
and,
therefore,

presumed
to
be
without
appreciable
risk
of
adverse
human
health
effects.
A
hazard
quotient
greater
than
one
means
that
the
pollutant
dose
is
greater
than
the
RfD.
RfDs
are
available
for
77
of
the
132
MP&
M
pollutants
of
concern.
The
pollutants
analyzed
and
their
RfDs
are
listed
in
Table
13.2.

Table
13.2:
RfDs
for
MP&
M
Pollutants
CAS
Number
Regulated
Pollutant
RfD
(
mg/
kg/
day)
Drinking
Water
Criterion?
a
Target
Organ
and
Effects
83329
Acenaphthene
0.060
No
Liver
toxicity
67641
Acetone
0.100
No
Increased
liver
and
kidney
weights;
nephrotoxicity
98862
Acetophenone
0.100
No
General
toxicity
107028
Acrolein
0.020
No
Cardiovascular
toxicityb
7429905
Aluminum
1.000
Yes
Renal
failure,
intestinal
contraction
interference,
adverse
neurological
effectsc
120127
Anthracene
0.300
No
7440360
Antimony
0.000
Yes
Longevity,
blood
glucose,
cholesterol
7440382
Arsenic
0.000
Yes
Hyperpigmentation,
keratosis
and
possible
vascular
complications
7440393
Barium
0.070
Yes
Increased
kidney
weight
65850
Benzoic
acid
4.000
No
100516
Benzyl
alcohol
0.300
No
Forestomach,
epithelial
hyperplasia
7440417
Beryllium
0.002
Yes
Small
intestinal
lesions
92524
Biphenyl
0.050
No
Kidney
damage
117817
Bis(
2­
ethylhexyl)

phthalate
0.020
Yes
Increased
relative
liver
weight
7440428
Boron
0.090
No
Testicular
atrophy,
spermatogenic
arrest
85687
Butyl
benzyl
phthalate
0.200
No
Significantly
increased
liver­
to­
body
weight
and
liver­
to­
brain
weight
ratios
7440439
Cadmium
0.001
Yes
Significant
proteinuria
(
protein
in
urine)

75150
Carbon
disulfide
0.100
No
Fetal
toxicity,
malformations
108907
Chlorobenzene
0.020
No
Histopathologic
changes
in
liver
75003
Chloroethane
0.400
No
7440473
Chromium
1.500
Yes
Renal
tubular
necrosis
(
kidney
tissue
decay)
c
18540299
Chromium
hexavalent
0.003
Yes
Reduced
water
consumption
7440484
Cobalt
0.060
No
Heart
effectsc
7440508
Copper
0.040
Yes
Gastrointestinal
effects,
liver
necrosisc
95487
Cresol,
o­
0.050
No
Decreased
body
weights
and
neurotoxicity.

13­
10
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.2:
RfDs
for
MP&
M
Pollutants
CAS
Number
Regulated
Pollutant
RfD
(
mg/
kg/
day)
Drinking
Water
Criterion?
a
Target
Organ
and
Effects
106445
Cresol,
p­
0.005
No
Central
nervous
system
hypoactivity
and
respiratory
system
distress
57125
Cyanide
0.020
Yes
Weight
loss,
thyroid
effects
and
myelin
degeneration
75354
Dichloroethene,
1,1­
0.009
Yes
Toxic
effects
on
kidneys,
spleen,
lungsc;
hepatic
lesions
75092
Dichloromethane
0.060
Yes
Liver
toxicity
60297
Diethyl
ether
0.200
No
Depressed
body
weights
68122
Dimethylformamide,
N,
N­
0.100
No
Liver
and
gastrointestinal
system
effects
105679
Dimethylphenol,
2,4­
0.020
No
Clinical
signs
(
lethargy,
prostration,
and
ataxia)
and
hematological
changes
84742
Di­
n­
butyl
phthalate
0.100
No
Increased
mortality
51285
Dinitrophenol,
2,4­
0.002
No
Cataract
formation
606202
Dinitrotoluene,
2,6­
0.001
No
Mortality,
central
nervous
system
neurotoxicity,
blood
heinz
bodies
and
methemoglobinemia,
bile
duct
hyperplasia,
kidney
histopathology
117840
Di­
n­
octyl
phthalate
0.020
No
Kidney
and
liver
increased
weights,
liver
increased
SGOT
and
SGPT
activity
122394
Diphenylamine
0.025
No
Decreased
body
weight,
and
increased
liver
and
kidney
weights
100414
Ethylbenzene
0.100
Yes
Liver
and
kidney
toxicity
206440
Fluoranthene
0.040
No
Nephropathy,
increased
liver
weights,
hematological
alterations,
clinical
effects
86737
Fluorene
0.040
No
Decreased
red
blood
cell
count,
packed
cell
volume
and
hemoglobin
16984488
Fluoride
0.060
Yes
Objectionable
dental
fluorosis
(
soft,
mottled
teeth)

591786
Hexanone,
2­
0.040
No
Hypatotoxicity
and
nephrotoxcity
d
7439896
Iron
0.300
Yes
Liver,
diabetes
mellitus,
endocrine
disturbance,
and
cardiovascular
effectsd
78831
Isobutyl
alcohol
0.300
No
Hypoactivity
and
ataxia
78591
Isophorone
0.200
No
Kidney
pathology
7439965
Manganese
0.140
Yes
Central
nervous
system
effects
78933
Methyl
ethyl
ketone
0.600
No
Decreased
fetal
birth
weight
108101
Methyl
isobutyl
ketone
0.080
No
Lethargy,
increased
liver
and
kidney
weights
and
urinary
protein
80626
Methyl
methacrylate
1.400
No
Increased
kidney
to
body
weight
ratio
91576
Methylnaphthalene,
2­
0.020
No
7439987
Molybdenum
0.005
No
Increased
uric
acid
91203
Naphthalene
0.020
No
Decreased
body
weight
7440020
Nickel
0.020
Yes
Decreased
body
and
organ
weights
100027
Nitrophenol,
4­
0.008
No
59507
Parachlorometacresol
2.000
No
108952
Phenol
0.600
No
Reduced
fetal
body
weight
in
rats
7723140
Phosphorus
(
elemental)
0.000
No
Parturition
mortality;
forelimb
hair
loss
13­
11
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.2:
RfDs
for
MP&
M
Pollutants
CAS
Number
Regulated
Pollutant
RfD
(
mg/
kg/
day)
Drinking
Water
Criterion?
a
Target
Organ
and
Effects
129000
Pyrene
0.030
No
Kidney
effects
(
renal
tubular
pathology,
decreased
kidney
weights)

110861
Pyridine
0.001
No
Increased
liver
weight
7782492
Selenium
0.005
Yes
Clinical
selenosis
(
hair
or
nail
loss)

7440224
Silver
0.005
Yes
Argyria
(
skin
discoloration)

100425
Styrene
0.200
Yes
Red
blood
cell
and
liver
effects
127184
Tetrachloroethene
0.010
Yes
Liver
toxicity,
weight
gain
7440280
Thallium
0.000
Yes
Liver
toxicity,
gastroenteritis,
degeneration
of
peripheral
and
central
nervous
systemb
7440315
Tin
0.600
No
Kidney
and
liver
lesions
7440326
Titanium
4.000
No
108883
Toluene
0.200
Yes
Changes
in
liver
and
kidney
weights
79016
Trichloroethene
0.006
Yes
Bone
marrow,
central
nervous
system,
liver,
kidneys
d
75694
Trichlorofluoromethane
0.300
No
Survival
and
histopathology
67663
Trichloromethane
0.010
Yes
Fatty
cyst
formation
in
liver
7440622
Vanadium
0.007
No
Kidney
and
central
nervous
system
effects
b
108383
Xylene,
m­
2.000
Yes
Central
nervous
system
hyperactivity,
decreased
body
weight
179601231
Xylene,
m­&
p­*
2.000
Yes
95476
Xylene,
o­
2.000
Yes
Central
nervous
system
hyperactivity,
decreased
body
weight
136777612
Xylene,
o­&
p­*
2.000
Yes
7440666
Zinc
0.300
Yes
47%
decrease
in
erythrocyte
superoxide
dismutase
(
ESOD)

concentration
in
adult
human
females
after
10
weeks
of
zinc
exposure
137304
Ziram
\
Cymate
0.020
No
a
 
Yes =
there
is
a
published
drinking
water
criterion
for
a
given
chemical.

b
Reference
dose
based
on
a
no
observed
adverse
effect
level
(
NOAEL).
Health
effects
summarized
from
Amdur,
M.
O.;
Doul,
J.;
and
Klaassen,
C.
D.,
eds.
1991.
Cassarett
and
Doul s
Toxicology,
4th
edition.
Target
organ
and
effects
summarized
from
Wexler,
P.,
ed.
1998.
Encyclopedia
of
Toxicology,
Volumes
1­
3.

d
Target
organ
and
effects
summarized
from
Amdur,
M.
O.;
Doul,
J.;
and
Klaassen,
C.
D.,
eds.
1996.
Cassarett
and
Doul s
Toxicology,

5th
edition.

Source:
U.
S.
EPA
(
1998/
99);
U.
S.
EPA
(
1997a).

EPA
guidance
for
assessing
exposures
to
mixtures
of
pollutants
recommends
calculating
a
hazard
index
(
HI)
by
summing
the
individual
hazard
quotients
for
those
pollutants
in
the
mixture
that
affect
the
same
target
organ
or
system
(
e.
g.,
the
kidneys,

the
respiratory
system).
For
example,
for
three
liver
toxicants
discharged
from
an
MP
&
M
facility
(
pollutant
A
with
a
hazard
index
of
0.10,
pollutant
B
with
a
hazard
index
of
0.05,
and
pollutant
C
with
a
hazard
index
of
0.15),
the
combined
hazard
index
is
0.30.
HI
values
are
interpreted
similarly
to
hazard
quotients;
values
below
one
are
generally
considered
to
suggest
that
exposures
are
not
likely
to
result
in
appreciable
risk
of
adverse
health
effects
during
a
lifetime,
and
values
above
one
are
generally
cause
for
concern,
although
an
HI
greater
than
one
does
not
necessarily
suggest
a
likelihood
of
adverse
effects.

To
evaluate
the
potential
benefits
of
reducing
the
in­
stream
concentrations
of
76
pollutants
that
cause
non­
cancer
health
effects,
EPA
estimated
target
organ­
specific
HIs
for
drinking
water
and
fish
ingestion
exposures
in
both
the
baseline
and
post­
compliance
scenarios.
HI
is
calculated
for
each
discharge
reach
associated
with
one
or
more
MP&
M
sample
facilities
by
dividing
the
estimated
ingestion
rate
of
each
pollutant
by
the
RfD
value
for
the
pollutant.
The
formula
follows:

13­
12
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
(
13.5)

where:

HI
=
haza
rd
ind
ex
for
the
po
llutants
disc
harge
d
from
a
facility
and
ingested
by
a
specific
co
nsumption
pathw
ay;

DCRk
=
estimated
d
aily
consump
tion
rate
per
kilogram
of
bo
dy
ma
ss
for
pollutant
k
via
a
specific
consumption
pathway
(
mg/
kg/
day);

RfD
k
=
reference
d
ose
fo
r
pollutant
k
(
mg/
kg/
day);
and
K
=
number
of
pollutants
affecting
a
given
organ
or
system.

Daily
consumption
rate
(
DCR)
per
kilogram
of
body
mass
for
pollutant
k
is
estimated
as
follows:

(
13.6)

where:

DCRk
=
estimated
daily
consump
tion
rate
per
kilogram
of
bo
dy
ma
ss
for
pollutant
k
via
a
specific
consumption
pathway
(
mg/
kg/
day);

C
=
pollutant
concentration
in
surface
water
in
the
MP&
M
reach
(
 
g/
l);

CF1
=
conversion
factor,
micrograms
to
milligrams
(
0.001
mg/
 
g);

CR
=
human
consumption
rate
of
water
(
mg/
day);

BCF
=
bioc
oncentratio
n
factor
for
po
llutant
k;

B
W
=
human
body
weight
(
kg).

These
HIs
are
calculated
separately
for
the
fish
and
water
consumption
pathways.
The
fish
consumption
pathway
was
further
divided
into
recreational
and
subsistence
fish
consumption
rates.
s
and
formulas
for
estimating
the
in­
waterway
concentrations
and
ingestion
of
pollutants
by
exposed
pop
ulations
are
the
same
as
those
used
for
the
fish
consumption
and
drinking
water
cancer
analyses.
s
that
the
analysis
of
non­
cancer
health
pathways
was
performed
for
the
discharge
reach
only
and
not
for
reac
hes
downstream
,
due
to
time
and
reso
urce
c
onstraints.
sult,
this
analysis
unde
restimates
populatio
ns
exp
osed
to
non
­
cance
r
risks
via
d
rinking
w
ater
pathways
EP
A
then
com
bined
estimate
s
of
the
nu
mbe
rs
of
ind
ividua
ls
in
the
exp
osed
pop
ulations
with
the
H
Is
for
the
pop
ulations
to
determine
how
many
individuals
might
be
expected
to
realize
reduced
risk
of
non­
cancer
health
effects
in
the
post­
compliance
scenario.
The
basis
for
identifying
exposed
populations
is
the
same
as
that
described
for
the
analysis
of
reduced
incidence
of
cancer
via
the
fish
con
sumption
a
nd
drinking
w
ater
consum
ption
pathw
ays.
8
The
shift
in
populations
from
a
higher
to
a
lower
HI
value
fro
m
the
b
aseline
to
po
st­
com
plianc
e
case
s
is
the
qu
antitative
m
easure
of
benefits
fro
m
this
an
alysis.
T
his
analysis
was
limited
in
two
primary
w
ays:

 
First,
haz
ard
ind
ices
estim
ated
in
this
analysis
m
ay
und
erstate
the
actual
p
otentia
l
for
ad
verse
health
e
ffects
be
cause
this
analysis
consid
ers
co
ntributio
ns
to
no
n­
canc
er
risk
resulting
on
ly
from
M
P&
M
facility
discharges,
and
d
oes
not
take
into
account
other
sources
of
exposure
to
MP&
M
p
ollutants
or
other
chemicals
that
may
contribute
to
an
aggregate
non­

cancer
risk.
result
is
that
the
analysis
understates
the
numerical
value
estimated
for
HIs,
but
the
incremental
change
in
HIs
between
the
baseline
and
the
final
option
would
remain
the
same.
EPA
therefore
evaluated
potential
incremental
changes
in
non­
cancer
health
risks
over
the
entire
range
of
hazard
indices,
including
hazard
indices
below
one.

 
Sec
ond
,
EPA
used
me
an
individual
expo
sure
param
eters
and
not
the
distribution
o
f
expo
sure
param
eters
to
estimate
hazard
ind
ices
for
the
pop
ulations
affected
by
M
P&
M
discharges.

Th
e
results
fro
m
the
non­
cancer
health
risk
analysis
ap
ply
to
sample
discha
rge
loc
ations
o
nly.
Analytic
tractability
issues
prevented
this
analysis
from
being
cond
ucted
on
a
sample­
we
ighted
national
ba
sis.
EPA
d
id
not
mo
netize
these
bene
fits.
The
procedure
The
only
exception
i
As
a
re
The
net
8
The
exposed
populations
for
the
drinking
water
consumption
pathway
are
those
associated
with
drinking
water
intakes
only
in
a
facility s
discharge
reach.

13­
13
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
13.1.4
Human
Health
AWQC
EPA
used
another
approach
to
quantify
reductions
in
health
risk
from
the
final
MP&
M
regulation,
based
on
the
extent
to
which
reduced
MP&
M
discharges
would
decrease
the
occurrence
of
pollutant
concentrations
in
affected
waterways
that
exceed
human
health­
based
AWQC.
This
analysis
provides
a
measure
of
the
change
in
cancer
and
non­
cancer
health
risk
by
comparing
the
number
of
discharge
reaches
exceeding
health­
based
AWQC
for
regulated
pollutants
due
to
MP&
M
activities
in
the
baseline
to
the
number
exceeding
AWQC
under
the
final
option.

AWQC
are
set
at
levels
to
protect
human
health
through
ingestion
of
aquatic
organisms
and
ingestion
of
water
and
aquatic
organisms.
Accordingly,
reducing
the
frequency
at
which
human
health­
based
AWQC
are
exceeded
should
translate
into
reduced
risk
to
human
health.
This
measure
should
be
viewed
as
an
indirect
indicator
of
reduced
risk
to
human
health,

9
because
it
does
not
reflect
the
size
of
the
exposed
population
and
is
not
tied
to
changes
in
human
health
risk
per
se.

EPA
estimated
the
baseline
concentrations
of
all
MP&
M
pollutants
for
each
reach
to
which
one
or
more
MP&
M
facilities
discharge.
The
calculation
of
concentrations
used
the
same
in­
waterway
dilution
and
mixing
model
described
in
the
analysis
of
cancer
risk
for
the
fish
consumption
pathway.
The
baseline
concentrations
were
compared
with
human
health­
based
AWQC
values.
(
See
Table
13.3
for
a
list
of
MP&
M
pollutants
with
AWQC
values.)
Reaches
in
which
concentrations
of
one
or
more
pollutants
were
estimated
to
exceed
an
AWQC
value
were
identified
as
exceeding
AWQC
limits
in
the
baseline.

This
analysis
was
repeated
using
the
post­
compliance
discharge
values
for
the
final
option.
Reaches
estimated
to
have
concentrations
in
excess
of
AWQC
in
the
baseline
but
not
in
the
post­
compliance
case
were
assessed
as
having
substantial
water
quality
improvements
relative
to
human
health­
based
criteria
as
a
result
of
regulation.
EPA
deems
such
water
quality
improvements
to
be
indicative
of
reduced
risk
to
human
health.
Although
not
explicitly
accounted
for
in
this
analysis,
human
health
risk
reductions
are
also
likely
to
occur
wherever
in­
waterway
concentrations
are
reduced,
regardless
of
whether
or
not
they
are
reduced
to
levels
below
AWQC.

Table
13.3:
MP&
M
Pollutants
with
Human
Health­
Based
AWQC
CAS
Number
Pollutant
Human
Health­
Based
AWQC
(
ug/
l)
Target
Organ
and
Effectsa
Organisms
Only
Water
&

Organisms
83329
Acenaphthene
2700
1200
Liver,
hepatotoxicity
67641
Acetone
2800000
3500
Increased
liver
and
kidney
weights;
nephrotoxicity
98862
Acetophenone
98000
3400
General
toxicity
107028
Acrolein
1000
410
Cardiovascular
toxicityc
7429905
Aluminum
47000
20000
Renal
failure,
intestinal
contraction
interference,
adverse
neurological
effectsd
62533
Aniline
95
5.8
Spleen
and
body
cavity
120127
Anthracene
6800
4100
No
observed
effects
7440360
Antimony
4300
14
Longevity,
blood
glucose,
cholesterol
7440382
Arsenic
0.16
0.02
Liver,
kidneys,
lungs,
bladder,
and
skin
7440393
Barium
1000
Increased
kidney
weight
65850
Benzoic
acid
2900000
130000
No
observed
adverse
effects
100516
Benzyl
alcohol
810000
10000
Forestomach,
epithelial
hyperplasia
7440417
Beryllium
1100
66
Small
intestinal
lesions
92524
Biphenyl
1200
720
Kidney
damage
9
The
following
chapter
uses
this
same
information
in
part
as
a
direct
indicator
of
improved
water
quality.

13­
14
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.3:
MP&
M
Pollutants
with
Human
Health­
Based
AWQC
CAS
Number
Pollutant
Human
Health­
Based
AWQC
(
ug/
l)
Target
Organ
and
Effectsa
Organisms
Only
Water
&

Organisms
117817
Bis(
2­
ethylhexyl)

phthalate
5.9
1.8
Liver
85687
Butyl
benzyl
phthalate
5200
3000
Significantly
increased
liver­
to­
body
weight
and
liver­
to­
brain
weight
ratios
7440439
Cadmium
84
14
Significant
proteinuria
(
protein
in
urine)

75150
Carbon
disulfide
94000
3400
Fetal
toxicity,
malformations
108907
Chlorobenzene
21000
680
Histopathologic
changes
in
liver
75003
Chloroethane
520
12
1854029
9
Chromium
hexavalent
2000
100
Reduced
water
consumption
7440473
Chromium
1000000
50000
Renal
tubular
necrosis
(
kidney
tissue
decay)
d
7440508
Copper
1200
650
Gastrointestinal
effects,
liver
necrosisd
106445
Cresol,
p­
3100
170
Central
nervous
system
hypoactivity
and
respiratory
system
distress
95487
Cresol,
o­
30000
1700
Decreased
body
weights
and
neurotoxicity.

57125
Cyanide
220000
700
Weight
loss,
thyroid
effects
and
myelin
degeneration
117840
Di­
n­
octyl
phthalate
39
37
Kidney
and
liver
increased
weights,
liver
increased
SGOT
and
SGPT
activity
84742
Di­
n­
butyl
phthalate
12000
2700
Increased
mortality
75354
Dichloroethene,
1,1­
3.2
0.057
Inconclusive
75092
Dichloromethane
1600
4.7
Liver,
lungs
60297
Diethyl
ether
770000
6900
Depressed
body
weights
131113
Dimethyl
phthalate
2900000
310000
68122
Dimethylformamide,
N,
N­
220000000
3500
Liver
and
gastrointestinal
system
effects
105679
Dimethylphenol,
2,4­
2300
540
Clinical
signs
(
lethargy,
prostration,
and
ataxia)
and
hematological
changes
51285
Dinitrophenol,
2,4­
14000
70
Cataract
formation
606202
Dinitrotoluene,
2,6­
900
34
Mortality,
central
nervous
system
neurotoxicity,
blood
heinz
bodies
and
methemoglobinemia,
bile
duct
hyperplasia,
kidney
histopathology
123911
Dioxane,
1,4­
2400
3.2
Liver,
nasal
cavity,
gall
bladder
122394
Diphenylamine
1000
470
Decreased
body
weight
gain,
and
increased
liver
and
kidney
weights
100414
Ethylbenzene
29000
3100
Liver
and
kidney
toxicity
206440
Fluoranthene
370
300
Nephropathy,
increased
liver
weights,
hematological
alterations,
clinical
effects
86737
Fluorene
14000
1300
Decreased
red
blood
cell
count,
packed
cell
volume
and
hemoglobin
591786
Hexanone,
2­
65000
1400
Hypatotoxicity
and
nephrotoxcity
b
7439896
Iron
300
Liver,
diabetes
mellitus,
endocrine
disturbance,
and
cardiovascular
effectsc
13­
15
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.3:
MP&
M
Pollutants
with
Human
Health­
Based
AWQC
CAS
Number
Pollutant
Human
Health­
Based
AWQC
(
ug/
l)
Target
Organ
and
Effectsa
Organisms
Only
Water
&

Organisms
78831
Isobutyl
alcohol
1500000
10000
Hypoactivity
and
ataxia
78591
Isophorone
2600
36
Preputial
gland
7439965
Manganese
100
50
Central
nervous
system
effects
7439976
Mercury
0.051
0.05
80626
Methyl
methacrylate
2300000
48000
Increased
kidney
to
body
weight
ratio
78933
Methyl
ethyl
ketone
6500000
21000
Decreased
fetal
birth
weight
108101
Methyl
isobutyl
ketone
360000
2800
Lethargy,
increased
liver
and
kidney
weights
and
urinary
protein
91576
Methylnaphthalene,
2­
84
75
91203
Naphthalene
21000
680
Decreased
body
weight
7440020
Nickel
4600
610
Decreased
body
and
organ
weights
100027
Nitrophenol,
4­
1100
220
62759
Nitrosodimethylamine,

N­
8.1
0.00069
Tumors
observed
at
multiple
sites
86306
Nitrosodiphenylamine,

N­
16
5
Bladder
tumors,
reticulum
cell
sarcomas
59507
Parachlorometacresol
270000
56000
108952
Phenol
4600000
21000
Reduced
fetal
body
weight
in
rats
7723140
Phosphorus
(
elemental)
2.2
0.53
Parturition
mortality;
forelimb
hair
loss
129000
Pyrene
290
230
Kidney
effects
(
renal
tubular
pathology,
decreased
kidney
weights)

110861
Pyridine
5400
35
Increased
liver
weight
7782492
Selenium
11000
170
Clinical
selenosis
(
hair
or
nail
loss)

7440224
Silver
110000
170
Argyria
(
skin
discoloration)

100425
Styrene
160000
6700
Red
blood
cell
and
liver
effects
127184
Tetrachloroethene
3500
320
Liver
toxicity,
weight
gain
7440280
Thallium
6.5
1.8
Liver
toxicity,
gastroenteritis,
degeneration
of
peripheral
and
central
nervous
system
108883
Toluene
200000
6800
Changes
in
liver
and
kidney
weights
79016
Trichloroethene
92
3.1
75694
Trichlorofluoromethane
66000
9100
Survival
and
histopathology
67663
Trichloromethane
470
5.7
Kidneys
108383
Xylene,
m­
100000
42000
Central
nervous
system
hyperactivity,
decreased
body
weight
1367776
12
Xylene,
o­
&
p­(
c)
100000
42000
95476
Xylene,
o­
100000
42000
Central
nervous
system
hyperactivity,
decreased
body
weight
1796012
31
Xylene,
m­
&
p­(
c)
100000
42000
7440666
Zinc
69000
9100
47%
decrease
in
erythrocyte
superoxide
dismutase
(
ESOD)
concentration
in
adult
human
females
after
10
weeks
of
zinc
exposure
13­
16
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.3:
MP&
M
Pollutants
with
Human
Health­
Based
AWQC
CAS
Number
Pollutant
Human
Health­
Based
AWQC
(
ug/
l)
Target
Organ
and
Effectsa
Organisms
Only
Water
&

Organisms
137304
Ziram
\
Cymate
220000000
700
a
Information
on
target
organs
are
not
available
for
some
pollutants.

b
Reference
dose
based
on
a
NOAEL.
Health
effects
summarized
from
Amdur,
M.
O.;
Doul,
J.;
and
Klaassen,
C.
D.,
eds.
1991.

Cassarett
and
Doul s
Toxicology,
4th
edition/

c
Target
organ
and
effects
summarized
from
Amdur,
M.
O.;
Doul,
J.;
and
Klaassen,
C.
D.,
eds.,
C.
D.,
ed.
1996.
Cassarett
and
Doul s
Toxicology,
5th
edition.

d
Target
organ
and
effects
summarized
from
Wexler,
P.,
ed.
1998.
Encyclopedia
of
Toxicology,
Volumes
1­
3.

Source:
U.
S.
EPA
(
1980);
U.
S.
EPA
(
1997a);
U.
S.
EPA
(
1998/
99).

13.2
RESULTS
EPA
estimated
the
monetary
value
to
society
associated
with
reduced
cancer
risk
from
consumption
of
fish
and
drinking
water
affected
by
MP&
M
pollutant
discharges.
Little
information
is
available
about
dose­
response
relationships
for
non­
cancer
health
outcomes
or
about
the
monetary
value
of
avoiding
such
health
outcomes.
As
a
result,
EPA
was
unable
to
assign
monetary
values
to
the
estimated
reductions
in
non­
cancer
health
risks.
Such
non­
cancer
health
risks
include
systemic,

reproductive,
immunological,
neurological,
and
circulatory
problems.
Although
EPA
was
unable
to
assign
monetary
values
to
the
latter
two
benefit
measures
for
this
regulation,
the
quantitative
analyses
of
these
events
provide
additional
insight
into
the
human
health­
related
benefits
likely
to
result
from
the
final
regulation.

The
following
sections
present
the
findings
from
the
analysis
of
each
of
the
benefit
measures.

13.2.1
Fish
Consumption
Cancer
Results
Table
13.4
shows
the
estimated
changes
in
incidence
of
cancer
cases
from
consumption
of
MP&
M
pollutants
in
fish
tissue
and
drinking
water
from
regulatory
compliance
by
option.
The
national­
level
analysis
finds
that
the
final
regulation
and
the
433
Upgrade
Options
would
lead
to
a
marginal
reduction
in
cancer
cases
resulting
from
consumption
of
contaminated
fish
tissue;
correspondingly,
monetary
benefits
estimated
from
reduced
consumption
of
contaminated
fish
are
negligible
under
all
of
these
three
regulatory
alternatives.
In
contrast,
the
estimated
reductions
in
carcinogen
loadings
under
the
Proposed/
NODA
Option
would
result
in
$
3.68
million
(
2001$)
in
benefits
to
recreational
and
subsistence
anglers.

13­
17
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.4:
Estimated
Avoided
Cancer
Cases
and
Value
of
Annual
Benefits
for
the
Final
Option
and
Regulatory
Alternativesa,
b
Option
Fish
Consumption
Drinking
Waterc
Avoided
Cancer
Cases
per
Year
Mean
Value
of
Benefit
(
2001$)
c
Avoided
Cancer
Cases
per
Year
Mean
Value
of
Benefit
(
2001$)
d
Final
Option:
Traditional
Extrapolation
1.38E­
05
$
90
0
$
0
Final
Option:
Post­
Stratification
Extrapolation
2.05E­
05
$
134
0
$
0
Proposed/
NODA
Optione
0.57
$
3,684,973
0.001
$
6,536
Directs
+
413
to
433
Upgrade
Option
1.38E­
05
$
90
0
$
0
Directs
+
All
to
433
Upgrade
Option
2.6E­
05
$
169
0
$
0
a
In
this
analysis,
EPA
did
not
consider
reductions
in
discharges
of
one
carcinogen
n­
nitrosodimethylanine
(
NDMA)
due
to
the
low
number
of
detected
values
for
that
pollutant.

b
Regulatory
alternatives
are
based
on
the
Traditional
Extrapolation.

c
Avoided
cancer
cases
via
the
drinking
water
consumption
pathway
were
not
included
for
pollutants
with
drinking
water
criteria.
EPA
has
published
a
drinking
water
criterion
for
seven
of
the
13
carcinogens
and
it
is
assumed
that
drinking
water
treatment
systems
will
reduce
concentrations
of
these
chemicals
to
below
adverse
effect
thresholds.

d
Estimated
value
of
one
avoided
cancer
case
(
2001$):
$
6.5
million.

e
The
estimated
benefits
of
the
Proposed/
NODA
Option
are
not
directly
comparable
to
the
final
option
alternatives.
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
two
upgrade
options.
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
performed
no
more
analysis
on
the
NODA
option,
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

Source:
U.
S.
EPA
analysis.

The
valuation
of
benefits
is
based
on
estimates
of
society s
willingness­
to­
pay
to
avoid
the
risk
of
cancer­
related
premature
mortality.
Although
it
is
not
certain
that
all
cancer
cases
will
result
in
death,
avoided
cancer
cases
are
valued
on
the
basis
of
avoided
mortality
to
provide
a
conservative
estimate
of
benefits.

In
this
analysis,
EPA
used
the
$
6.5
million
estimate
of
the
value
of
a
statistical
life
saved
(
VSL)
recommended
in
the
Guidelines
for
Preparing
Economic
Analysis
(
EPA,
2000c).
EPA
based
this
value
on
its
review
and
analysis
of
26
policy­

relevant
value
of
life
studies
(
EPA,
1997b).
The
reviewed
studies
used
hedonic
wage
and
contingent
valuation
analyses
in
labor
markets
to
estimate
the
amounts
that
individuals
would
either
be
willing
to
pay
to
avoid
slight
increases
in
the
risk
of
mortality,
or
would
need
to
be
compensated
to
accept
a
slight
increase
in
risk
of
mortality.
10
EPA
associated
the
willingness­
to­
pay
(
WTP)
values
estimated
in
these
studies
with
small
changes
in
the
probability
of
mortality.
To
estimate
a
WTP
value
for
avoiding
certain
or
high
probability
mortality
events,
EPA
extrapolated
the
smaller
value
to
that
for
a
100
percent
probability
event.
11
The
Agency
used
the
resulting
estimates
of
the
value
of
a
 
statistical
life
saved 
in
regulatory
analyses
to
value
regulatory
effects
that
are
expected
to
reduce
the
incidence
of
mortality.

The
monetary
value
of
a
statistical
life
saved
used
in
this
analysis
corresponds
to
the
value
of
unforeseen
instant
death
with
no
significant
period
of
morbidity.
Because
a
long
period
of
morbidity
usually
precedes
death
from
cancer,
the
value
of
an
avoided
cancer
case
may
be
underestimated.
Therefore,
the
estimated
value
of
the
human
health
benefit
of
the
final
regulation
may
be
understated.

10
The
question
analyzed
in
these
studies
is:
How
much
more
must
a
worker
be
paid
to
accept
an
occupation
with
a
slightly
higher
risk
of
mortality?

11
These
estimates,
however,
do
not
represent
the
willingness­
to­
pay
to
avoid
the
certainty
of
death.

13­
18
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
13.2.2
Drinking
Water
Consumption
Cancer
Results
Table
13.4
also
shows
the
number
of
cancer
cases
estimated
to
be
avoided
for
each
pollutant
analyzed
for
drinking
water
populations.
The
national­
level
analysis
finds
that
the
final
regulation
and
the
433
Upgrade
Options
would
lead
to
a
marginal
reduction
in
cancer
cases
resulting
from
consumption
of
contaminated
drinking
water;
correspondingly,
monetary
benefits
estimated
from
reduced
consumption
of
contaminated
drinking
water
are
essentially
zero
under
all
of
these
three
regulatory
alternatives.
As
shown
in
Table
13.4,
the
Proposed/
NODA
Option
would
eliminate
approximately
0.001
cancer
cases
per
year.
Annual
monetary
benefits
from
reduced
cancer
risk
for
the
Proposed/
NODA
Option
are
estimated
at
$
6,536
(
2001$).

As
noted
in
the
preceding
sections,
EPA
has
established
drinking
water
criteria
for
seven
carcinogens.
EPA
assumes
that
public
drinking
water
treatment
systems
will
reduce
these
seven
pollutants
in
the
public
water
supply
to
levels
that
are
protective
of
human
health.
To
the
extent
that
the
final
regulation
reduces
the
concentration
of
MP&
M
pollutants
to
values
that
are
below
pollutant­
specific
drinking
water
criteria,
public
drinking
water
systems
will
accrue
benefits
in
the
form
of
reduced
water
treatment
costs.
EPA
was
not
able
to
quantify
such
cost
savings
at
the
national
level,
however.

Public
drinking
water
supply
systems
that
currently
employ
various
treatment
technologies
may
also
reduce
concentrations
of
the
six
unregulated
pollutants
to
the
levels
that
are
protective
of
human
health.
However,
the
Agency
does
not
have
information
on
specific
treatment
technologies
used
by
the
drinking
water
systems
affected
by
MP&
M
discharges.
It
is
not
feasible
to
assess
whether
the
technologies
employed
by
the
affected
drinking
water
systems
reduce
concentrations
of
MP&
M
pollutants
that
don t
have
the
published
drinking
water
criteria
without
collecting
detailed
information
on
the
affected
drinking
water
systems.
Thus,
this
analysis
conservatively
assumes
that
public
water
supply
systems
do
not
monitor
pollutants
that
don t
have
published
drinking
water
criteria
and,
as
result,
these
pollutants
may
be
passed
through
the
affected
drinking
water
supply
systems.

13.2.3
Non­
cancer
Health
Threshold
Results
Table
13.5
summarizes
baseline
and
post­
compliance
distributions
of
non­
cancer
health
hazard
indices
and
associated
population
estimates
for
each
exposed
population
group
for
the
final
option.
The
shift
in
populations
from
higher
to
lower
hazard
score
values
between
the
baseline
and
post­
compliance
cases
is
the
measure
of
benefit
from
reduced
non­
cancer
health
hazards.

13­
19
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.5:
Change
in
Risk
of
Non­
cancer
Health
Hazards
from
Reduced
Exposure
to
MP&
M
Pollutants:

Distribution
of
Hazard
Indicesa
Range
of
Ratios
Fish
Consumption
Drinking
Water
Consumption
Baseline
Post­
Compliance
Baseline
Post­
Compliance
Population
Percent
Population
Percent
Population
Percent
Population
Percent
Final
Option
Ratio
=
0.00
0
0%
122,865
12.05%
39,822,464
97.48%
40,723,280
99.69%

0.00
­
10­
6
121,814
11.95%
103,103
10.12%
1,029,333
2.52%
128,517
0.31%

10­
6
­
10­
3
680,301
66.73%
578,122
56.72%
0
0%
0
0%

10­
3
­
1.00
217,201
21.31%
215,226
21.11%
0
0%
0
0%

Score
>
1.00
0
0%
0
0%
0
0%
0
0%

Totals
1,019,316
100%
1,019,316
100%
40,851,797
100
40,851,797
100%

Proposed/
NODA
Optionb
Ratio
=
0.00
0
0%
342,040
8.17%
0
0%
4,308,352
10.95%

0.00
­
10­
6
872,003
20.82%
796,003
19.01%
36,552,343
92.93%
33,667,164
85.59%

10­
6
­
10­
3
2,221,724
53.04%
2,310,376
55.16%
2,783,100
7.07%
1,359,927
3.46%

10­
3
­
1.00
1,054,627
25.18%
737,312
17.60%
0
0%
0
0%

Score
>
1.00
40,630
0.97%
3,253
0.08%
0
0%
0
0%

Totals
4,188,984
100%
4,188,984
100%
39,335,442
100%
39,335,442
100%

Directs
+
413
to
433
Upgrade
Option
Ratio
=
0.00
0
0.0%
169,106
16.59%
39,822,464
97.48%
40,723,280
99.69%

0.00
­
10­
6
121,814
11.95%
91,255
8.96%
1,029,333
2.52%
128,517
0.31%

10­
6
­
10­
3
680,301
66.73%
559,690
54.91%
0
0%
0
0%

10­
3
­
1.00
217,201
21.31%
199,265
19.54%
0
0%
0
0%

Score
>
1.00
0
0%
0
0%
0
0%
0
0%

Totals
1,019,316
100%
1,019,316
100%
40,851,797
100%
40,851,797
100%

Directs
+
All
to
433
Upgrade
Option
Ratio
=
0.00
0
0.0%
169,106
16.59%
39,822,464
97.48%
40,723,280
99.69%

0.00
­
10­
6
121,814
11.95%
91,255
8.96%
1,029,333
2.52%
128,517
0.31%

10­
6
­
10­
3
680,301
66.73%
563,526
55.28%
0
0%
0
0%

10­
3
­
1.00
217,201
21.31%
195,429
19.17%
0
0%
0
0%

Score
>
1.00
0
0%
0
0%
0
0%
0
0%

Totals
1,019,316
100%
1,019,316
100%
40,851,797
100%
40,851,797
100%

a
This
analysis
addresses
only
76
of
132
chemicals
of
concern,
excludes
background
exposures,
and
is
based
only
on
sample
facility
discharges
and
associated
populations.
The
exposed
population
values
are
not
national
estimates
of
the
populations
that
would
benefit
by
reduced
risk
of
non­
cancer
health
hazards.

b
The
estimated
benefits
of
the
Proposed/
NODA
Option
are
not
directly
comparable
to
the
final
option
alternatives.
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
two
upgrade
options.
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
performed
no
more
analysis
on
the
NODA
option,
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

Source:
U.
S.
EPA
analysis.

For
each
discharge
reach,
EPA
selected
the
maximum
of
the
target
organ­
specific
hazard
index
values
calculated
for
a
given
13­
20
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
discharge
reach
to
characterize
the
potential
for
adverse
non­
cancer
health
affects
from
exposure
to
MP&
M
pollutants
among
exposed
individuals.
The
results
of
EPA's
analysis
suggest
that
HIs
for
individuals
in
the
exposed
populations
may
decrease
after
facilities
comply
with
the
final
rule
(
see
Table
13.5
for
detail).
Increases
in
the
percentage
of
exposed
populations
that
would
be
exposed
to
no
risk
of
non­
cancer
adverse
human
health
effects
due
to
the
MP&
M
discharges
occur
in
both
the
fish
and
drinking
water
analyses.
The
shift
to
lower
hazard
indices
should
be
considered
in
conjunction
with
the
finding
that
the
hazard
indices
for
incremental
exposures
to
pollutants
discharged
by
MP&
M
facilities
(
for
which
reference
doses
are
available)
are
less
than
one
in
the
baseline
analysis
for
the
entire
population
associated
with
sample
facilities.
Whether
the
incremental
shifts
in
hazard
indices
are
significant
in
reducing
absolute
risks
of
non­
cancer
adverse
human
health
effects
is
uncertain
and
will
depend
on
the
magnitude
of
contaminant
exposures
for
a
given
population
from
risk
sources
not
accounted
for
in
this
analysis.

Table
13.5
shows
that
the
Proposed/
NODA
Option
and
the
433
Upgrade
Options
would
result
in
similar
shifts
in
the
exposed
populations
from
higher
to
low
hazard
index
values.
All
of
these
three
alternative
regulatory
options
would
increase
the
population
with
a
zero
incremental
risk
of
non­
cancer
health
effects
from
exposure
to
MP&
M
pollutants.

Although
EPA
was
unable
to
associate
an
economic
value
with
changes
in
the
number
of
individuals
exposed
to
pollutant
levels
likely
to
result
in
non­
cancer
health
effects,
the
reductions
in
health
risk
indicated
by
this
benefit
measure
further
indicate
that
the
final
regulation
can
be
expected
to
yield
human
health
benefits.

13.2.4
Human
Health
AWQC
Results
The
final
human
health
benefit
category
is
the
reduced
occurrence
of
pollutant
concentrations
that
are
estimated
to
exceed
human
health­
based
AWQC.
This
analysis
provides
an
alternative
measure
of
the
expected
reduction
in
risk
to
human
health.

EPA
estimates
that
in­
stream
concentrations
of
4
pollutants
(
i.
e.,
arsenic,
iron,
manganese,
and
n­
nitrosodimethylamine)
will
exceed
human
health
criteria
for
consumption
of
water
and
organisms
in
78
receiving
reaches
nationwide
as
the
result
of
baseline
MP&
M
pollutant
discharges.
EPA
estimates
that
there
are
human
health
AWQC
exceedances
caused
by
n­
nitrosodimethylamine
(
NDMA).
EPA
did
not
consider
NDMA
pollutant
reductions
in
its
benefits
analyses
because
of
low
number
of
detected
values
for
that
pollutant.
EPA
estimates
that
the
final
rule
will
not
eliminate
the
occurrence
of
concentrations
in
excess
of
human
health
criteria
for
consumption
of
water
and
organisms
and
for
consumption
of
organisms
on
any
of
the
reaches
on
which
baseline
discharges
are
estimated
to
cause
concentrations
in
excess
of
AWQC
values.

EPA s
analysis
of
the
433
Upgrade
Options
yields
similar
results.
However,
the
Directs
+
All
to
433
option
would
reduce
the
number
of
pollutants
causing
in­
stream
concentrations
to
exceed
the
human
health­
based
AWQC
values
from
4
to
2
(
i.
e.,

exceedances
from
iron
and
manganese
are
eliminated).
As
shown
in
Table
13.6,
the
Proposed/
NODA
Option
would
not
result
in
a
significant
reduction
in
the
number
of
reaches
that
are
estimated
to
exceed
human
health­
based
AWQC
for
consumption
of
water
and
organisms
under
the
baseline
discharge
level.
The
Proposed/
NODA
option,
however,
eliminates
human
health­

based
AWQC
for
consumption
of
organisms
only
on
69
(
35
percent)
of
the
197
reaches,
in
which
in­
stream
pollutant
concentrations
exceeded
the
relevant
criteria
in
the
baseline.
The
Agency
points
out
that
analytic
results
corresponding
to
the
Proposed/
NODA
Option
are
not
directly
comparable
to
the
analytic
results
corresponding
to
the
final
rule
alternatives
due
to
the
inconsistent
baseline
conditions
(
see
Chapter
5
of
this
report
for
detail).

13­
21
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
Table
13.6:
MP&
M
Discharge
Reaches
with
Pollutant
Concentrations
Exceeding
Human
Health­
Based
AWQC
Limits
and
Reductions
Achieveda
Category
Human
Health
Water
and
Organisms
Human
Health
Organisms
Only
Number
of
Reaches
Number
of
Pollutants
Number
of
Reaches
Number
of
Pollutants
Final
Option:
Traditional
Extrapolation
Baseline
78
4
21
1
Post­
Compliance
78
4
21
1
Percent
Reduction
0.0%
0.0%

Final
Option:
Post­
Stratification
Extrapolation
Baseline
112
4
21
1
Post­
Compliance
112
4
21
1
Percent
Reduction
0.0%
0.0%

Proposed/
NODA
Optionb
Baseline
5,852
26
197
12
Post­
Compliance
5,789
21
128
9
Percent
Reduction
1.1%
34.6%

413
to
433
Upgrade
Option
Baseline
78
4
21
1
Post­
Compliance
78
4
21
1
Percent
Reduction
0.0%
0.0%

Directs
+
All
to
433
Upgrade
Option
Baseline
78
4
21
1
Post­
Compliance
78
2
0
Percent
Reduction
0.0%
100.0%
0
a
Regulatory
alternatives
are
based
on
the
Traditional
Extrapolation.

b
The
estimated
benefits
of
the
Proposed/
NODA
Option
are
not
directly
comparable
to
the
final
option
alternatives.
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
two
upgrade
options.
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
performed
no
more
analysis
on
the
NODA
option,
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

Source:
U.
S.
EPA
analysis.

13.3
LIMITATIONS
AND
UNCERTAINTIES
This
section
discusses
limitations
and
uncertainties
in
the
human
health
benefits
analysis.
The
analysis
does
not
include
all
possible
human
health
benefits,
and
therefore
does
not
provide
a
comprehensive
estimate
of
the
total
human
health
benefits
associated
with
the
final
rule.
Quantification
of
changes
in
human
health
risk
described
in
this
chapter
are
not
possible
for
all
pollutants
whose
discharges
will
be
reduced
by
the
final
regulation.
Due
to
current
research
limitations,
cancer
potency
factors,
reference
doses,
and
AWQC
are
not
available
for
6
metals,
27
organics,
8
nonconventional
pollutants,
and
3
conventional
pollutants.
The
methodologies
used
also
involve
significant
simplifications
and
uncertainties,
as
described
below.
Whether
these
simplifications
and
uncertainties,
taken
together,
are
likely
to
lead
to
an
understatement
or
overstatement
of
the
estimated
economic
values
for
the
human
health
benefits
that
were
analyzed
is
not
known.

13.3.1
Sample
Design
&
Analysis
of
Benefits
by
Location
of
Occurrence
The
M
P&
M
industries
are
estimated
to
include
over
43,867
facilities
nationwide
that
generate
wastewater
while
processing
metal
parts,
metal
products,
and
machinery.
Many
of
these
facilities
are
quite
small
and,
individually,
discharge
relatively
small
quantities
of
pollutants.
Most
individual
facilities
are
not
likely
to
have
a
significant
adverse
impact
on
human
health
at
13­
22
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
any
one
MP
&
M
reach.
The
industry
discharges
a
significant
quantity
of
pollutants
in
the
aggregate,
however,
because
of
the
large
number
of
facilities.
Thus,
the
combined
effect
of
discharges
from
several
facilities
at
a
given
reach
may
well
result
in
appreciable
risks
to
human
health.
Multiple
dischargers
affecting
a
single
reach
were
found
to
be
common,
based
on
the
sample
facility
data.

The
sample
of
MP&
M
facilities
on
which
this
analysis
is
based
(
910
facilities)
represents
only
approximately
2
percent
of
MP&
M
facilities
nationwide.
This
sample
was
based
on
basic
industry
characteristics
rather
than
geographic
location.
As
a
result,
the
sample
does
not
accurately
reflect
the
likelihood
of
co­
occurrence
of
MP&
M
facilities
on
a
reach
and,
therefore,

the
contribution
to
in­
waterway
pollutant
concentrations
made
by
multiple
facilities.
For
example,
the
sample
may
include
three
MP&
M
facilities,
all
discharging
to
the
same
reach.
In
reality,
however,
five
MP&
M
facilities
might
discharge
to
this
reach.

The
omission
of
co­
occurrence
of
discharges
from
additional
facilities
does
not
create
a
problem
in
the
analysis
of
incremental
cancer
risk,
because
each
facility s
contribution
to
total
risk
can
be
estimated
separately
and
is
assumed
be
linearly
additive.
The
cancer
effects
associated
with
individual
facility
discharges
can
be
summed
over
facilities
to
estimate
occurrence
of
cancer
events
in
the
total
population.
Therefore,
the
application
of
sample
weights
in
the
cancer
analysis
accounts
for
pollutant
contributions
from
facilities
co­
occurring
on
MP&
M
reaches
that
are
not
present
in
the
sample
of
facilities.

This
omission
does
present
a
problem,
however,
when
analyzing
changes
in
hazard
indices
and
changes
in
in­
waterway
pollutant
concentrations
relative
to
human
health­
based
AWQC
for
reaches
to
which
more
than
one
facility
discharge.
For
these
reaches,
changes
in
hazard
indices
and
in­
waterway
pollutant
concentrations
from
reduced
pollutant
discharges
should
account
for
the
total
discharge
of
pollutants
over
the
several
facilities
whose
discharges
may
affect
the
reach.
When
facilities
whose
discharges
to
the
reach
have
unequal
sample
weights,
however,
results
from
the
sample
facility
analysis
cannot
be
extrapolated
to
the
population
simply
by
multiplying
estimated
benefit
values
by
the
sum
of
the
sample
weights
of
the
individual
facilities.
See
Appendix
G
for
an
explanation
of
the
sample
weighting
methodology
devised
to
partially
address
this
problem.

While
this
weighting
methodology
does
recognize
the
contributions
of
facilities
with
different
sample
facility
weights
to
aggregate
results,
it
still
does
not
account
for
the
contributions
made
by
co­
occurring
facilities
not
included
in
the
sample.

The
omission
of
the
frequency
of
true
multiple
discharger
effects
on
aggregate
instream
concentrations
and
pollutant
exposures
understate
the
benefits.

13.3.2
In­
Waterway
Concentrations
of
MP&
M
Pollutants
Human
health
benefits
are
based
on
the
estimated
changes
in
in­
waterway
concentrations
of
MP&
M
pollutants.
A
variety
of
factors
affect
in­
waterway
concentrations,
including
flow
rates
under
average
and
low
flow
conditions,
flow
depth,
chemistry
of
the
waterway,
mixing
processes,
longitudinal
dispersion,
flow
geometry,
suspension
of
solids,
and
reaction
rates.
This
analysis
takes
into
account
only
site­
specific
variations
in
flow
rates
and
flow
depth.
Standard
values
are
used
for
other
inputs
to
the
water
quality
model,
due
to
lack
of
data
on
the
reaches
affected
by
sample
facility
discharges.
These
standard
values
may
not
be
accurate
for
all
the
sample
facility
reaches.
In
addition,
the
flow
characteristics
of
the
sample
facility
reaches
may
not
be
representative
of
the
national
distribution
of
those
characteristics.
Extrapolating
the
sample
facility
benefits
to
national
results
based
on
sample
facility
weights
may
therefore
introduce
distortions.
The
net
effect
of
these
assumptions
and
extrapolations
on
the
aggregate
benefits
estimates
is
uncertain.

13.3.3
Joint
Effects
of
Pollutants
The
analyses
of
human
health
benefits
ignore
the
potential
for
joint
effects
of
more
than
one
pollutant.
Each
pollutant
is
dealt
with
in
isolation;
the
individually
estimated
effects
are
then
added
together.
As
such,
the
analyses
do
not
account
for
the
possibility
that
several
pollutants
may
combine
to
yield
more
or
less
adverse
effects
to
human
health
than
indicated
by
the
simple
sum
of
the
individual
effects.
The
impact
of
this
limitation
on
the
results
of
this
analysis
is
unknown.

13.3.4
Background
Concentrations
of
MP&
M
Pollutants
Background
concentrations
of
MP&
M
pollutants
are
not
considered
in
the
benefits
analysis.
Rather,
the
analysis
assumes
that
MP&
M
facilities
are
the
only
source
of
each
of
the
regulated
pollutants
in
the
waterway.
Background
contributions,
either
from
other
upstream
sources
or
contaminated
sediments
from
previous
discharges,
are
not
considered.
Even
if
discharges
of
13­
23
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
these
contaminants
are
reduced
or
eliminated,
sediment
contamination
and
subsequent
accumulation
of
the
regulated
pollutants
in
aquatic
organisms
may
continue
for
years.

Excluding
background
contributions
to
in­
waterway
pollutant
concentrations
affects
the
results
for
non­
cancer
risk
and
changes
in
human
health­
based
AWQC
exceedances.
In
the
non­
cancer
risk
analysis,
hazard
indices
are
likely
to
be
systematically
biased
downwards
by
the
omission
of
exposures
to
these
chemicals
from
other
water­
related
and
non­
water­

12
related
sources.
The
net
result
is
understated
absolute
risks
of
non­
cancer
health
hazards.
Similarly,
reductions
in
human
health­
based
AWQ
C
exceedances
calculated
for
a
given
MP&
M
reach
are
likely
to
be
systematically
biased
downwards.
The
analysis
is
therefore
likely
to
understate
the
frequency
with
which
in­
waterway
pollutant
concentrations
move
from
values
exceeding
pollutant
specific
AWQC
to
values
less
than
pollutant
specific
AWQC
as
a
result
of
the
regulation.

13.3.5
Downstream
Effects
The
analysis
of
cancer
effects
from
drinking
water
consumption
considered
exposures
from
intakes
downstream
of
the
MP&
M
discharges.
EPA,
however,
did
not
evaluate
cancer
risk
to
recreational
and
subsistence
fishermen
fishing
downstream
reaches,
because
of
resource
constraints.
In
addition,
due
to
differential
weighting
of
sample
facility
results,
it
was
not
possible
to
evaluate
hazard
indices
indicating
non­
cancer
health
hazards
or
human
health­
based
AWQC
excursions
in
downstream
reaches.
By
omitting
these
downstream
effects,
this
analysis
potentially
understates
baseline
risks
that
would
be
reduced
by
the
final
option:

 
cancer
cases
(
from
fish
consumption),

 
populations
exposed
to
non­
cancer
risks,
and
 
waterways
with
pollutant
concentrations
exceeding
human
health­
based
AWQC.

13.3.6
Exposed
Fishing
Population
Estimating
the
exposed
fishing
populations
for
specific
MP&
M
reaches
requires
statistics
on
county
fishing
licences.
EPA
collects
these
data
for
every
state
where
the
MP&
M
facilities
are
located
where
the
state
collects
these
data
at
the
county
level.
Where
fishing
license
data
were
not
available
at
the
county
level,
EPA
estimated
the
exposed
fishing
population
based
on
state
fishing
license
statistics
and
census
data.
This
approach
is
likely
to
understate
actual
fishing
populations.
As
noted
in
Section
13.1.1,
the
1996
National
Survey
of
Fishing,
Hunting,
and
Wildlife­
Associated
Recreation
found
that
34
percent
of
the
anglers
(
16
years
of
age
and
older)
did
not
have
licenses
(
U.
S.
Department
of
the
Interior,
1996).
In
addition,
data
limitations
hamper
the
estimate
of
the
number
of
anglers
who
actually
fish
a
given
MP&
M
reach.
Estimating
the
number
of
anglers
fishing
MP&
M
reaches
based
on
the
ratio
of
MP&
M
reach
length
to
the
total
number
of
MP&
M
reach
miles
in
the
county
recognizes
the
effect
of
the
quantity
of
competing
fishing
opportunities
on
the
likelihood
of
fishing
a
given
reach,
but
it
does
not
account
for
the
differential
quality
of
fishing
opportunities.
If
water
quality
in
substitute
sites
is
distinctly
worse
or
better,
the
estimates
of
the
exposed
populations
are
likely
to
be
overstated
or
understated.

In
addition,
the
number
of
subsistence
anglers
was
assumed
to
equal
5
percent
of
the
recreational
fishing
population.
The
magnitude
of
subsistence
fishing
in
the
United
States
or
in
individual
states
is
not
known.
As
a
result,
this
estimate
may
understate
or
overstate
the
actual
number
of
subsistence
anglers.

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

12
Ideally,
the
analysis
would
include
not
only
background
concentration
and
exposure
effects
from
water­
related
exposures
but
would
also
account
for
exposures
to
chemicals
by
other
routes
including,
air
exposures
including
dust
inhalation,
and
food
contamination.

13­
24
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
13.3.7
Treatment
of
Cancer
Latency
Cancer
latency
refers
to
the
time
between
the
initial
event
that
leads
to
cancer
(
e.
g.,
chemical
damage
to
DNA)
and
the
onset
of
cancer.
Ideally,
cancer
would
be
detected
at
a
very
early
stage,
when
very
few
cells
are
involved.
In
reality,
cancer
latency
is
a
very
complex
issue,
and
the
time
to
detection
varies
considerably.

 
Latency
is
related
to
health,
age,
immune
status,
genetics
and
other
characteristics
of
the
individual.

 
Latency
is
also
related
to
the
specific
carcinogen,
the
route
of
exposure,
the
type
of
cancer,
the
technology
used
for
cancer
detection,
and
numerous
other
factors.

 
Environmentally
induced
cancers
may
not
follow
a
typical
progression
pattern;
their
latency
may
be
unusually
shortened.

 
Cancers
may
begin
long
before
they
are
detected.
The
exact
progress
and
time
of
recognition/
detection
of
cancer
cannot
be
predicted,
because
of
the
numerous
factors
involved.

 
Variations
in
timing
of
cancer
detection
are
partially
attributable
to
the
type
of
cancer
involved,
the
individuals
affected,
and
differences
in
the
medical
technology
used.

 
The
fundamental
issue
is
when
the
damage
related
to
cancer
actually
begins
in
an
individual
and
when
the
continued
cell
damage
stops.
Damage
to
the
individual
begins
when
cancer
is
induced.
Once
cellular
changes
begin,
the
immune
system
and
other
body
resources
are
diverted
to
limiting
the
carcinogenic
process
and
organ
system
damage
is
occurring.

EPA
assumed
that
benefits
of
avoiding
cancer
begin
to
accrue
when
the
initial
events
leading
to
cancer
cease,
even
though
the
benefits
may
not
be
clinically
measurable
until
some
point
in
the
future.
In
making
this
assumption,
the
Agency
considered
two
factors:

 
uncertainty
as
to
how
and
when
exposure
changes
translate
into
reduced
cancer
risk,
and
 
economic
uncertainty
associated
with
the
value
of
avoiding
cancer
and
the
timing
at
which
a
value
of
cancer
avoidance
is
recognized.

The
monetary
valuation
of
mortality
risk
from
cancer
in
EPA
benefit­
cost
analyses
is
based
on
the
VSL.
This
is
derived
from
a
number
of
revealed­
preference
studies
that
estimate
the
value
of
avoided
premature
mortality.
The
estimates
correspond
to
the
value
of
unforeseen
instant
death
with
no
significant
period
of
morbidity.
The
value
of
an
avoided
cancer
case
used
in
this
analysis
may
therefore
be
understated,
and
ultimately
the
estimated
value
of
the
human
health
benefit
of
the
final
regulation
may
be
understated.

13.3.8
Treatment
of
Cessation
Lag
In
August
2001,
EPA's
Science
Advisory
Board
(
SAB)
recommended
that
EPA
should
not
assume
that
a
reduction
in
cancer
cases
immediately
follows
a
reduction
in
exposure
(
U.
S.
EPA,
2001).
The
SAB
explained
that,
in
fact,
there
is
a
lag
between
the
time
when
exposures
are
reduced
and
the
time
when
a
reduction
in
risk
occurs,
and
that
"...
if
the
lag
between
reduction
in
exposure
and
reduction
in
risk
is
long,
there
will
be
fewer
cancer
fatalities
avoided
in
years
immediately
following
the
policy
than
if
the
lag
were
shorter."
However,
the
Agency
points
out
the
published
studies
that
attempted
to
address
cessation
lag
found
that
after
cessation
of
exposure,
cancer
risk
begins
to
decline
quickly
(
U.
S.
EPA,
2001).

The
analysis
of
cancer
benefits
presented
did
not
account
for
a
cessation
lag
because
the
relevant
information
was
not
available
for
all
but
one
(
arsenic)
MP&
M
pollutants.
Not
accounting
for
cessation
lag
results
in
an
upper
bound
estimate
of
cancer­
related
benefits
(
U.
S.
EPA,
2001).

13­
25
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
13.3.9
Use
of
Mean
Individual
Exposure
Parameters
EPA
used
mean
individual
exposure
parameters
and
not
the
distribution
of
exposure
parameters
to
estimate
hazard
indices,

cancer
risk,
and
adverse
human
health
effects
associated
with
exposure
to
lead
for
the
populations
affected
by
MP&
M
discharges.
Because
individuals
associated
with
high­
end
exposure
parameter
estimates
would
have
higher
health
risks,
EPA's
approach
is
likely
to
result
in
underestimation
of
human
health
risk
reduction
from
the
final
MP&
M
regulation.

13.3.10
Cancer
Potency
Factors
EPA's
estimates
of
cancer
cases
were
calculated
using
cancer
potency
factors
that
are
upper
bound
estimates
of
cancer
potency,
potentially
leading
to
overestimation
of
cancer
risk.

13­
26
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
GLOSSARY
ambient
water
quality
criteria
(
AWQC):
AWQC
present
scientific
data
and
guidance
of
the
environmental
effects
of
pollutants
which
can
be
useful
to
derive
regulatory
requirements
based
on
considerations
of
water
quality
impacts;
these
criteria
are
not
rules
and
do
not
have
regulatory
impact
(
U.
S.
EPA.
1986.
Quality
Criteria
for
Water
1986.
U.
S.

Environmental
Protection
Agency,
Office
of
Water
Regulations
and
Standards,
Washington,
DC.
EPA
440/
5­
86­
001).

marine
reach:
a
specific
length
of
marine
coastline.

MP&
M
reach:
a
reach
to
which
an
MP&
M
facility
discharges.

no
observed
adverse
effect
level
(
NOAEL):
exposure
level
at
which
there
are
no
statistically
or
biologically
significant
differences
in
the
frequency
or
severity
of
any
effect
in
the
exposed
or
control
populations.

reach:
a
specific
length
of
river,
lake
shoreline,
or
marine
coastline.

reference
dose
(
RfD):
an
estimate
of
the
maximum
daily
ingestion
in
that
is
likely
to
be
without
an
appreciable
risk
of
deleterious
effects
during
a
lifetime.

value
of
a
statistical
life
saved
(
VSL):
a
monetary
value
of
fatalities.
A
statistical
life
is
saved
when
the
mortality
rate
of
a
group
of
people
is
reduced
sufficiently
that
one
less
person
will
die
than
would
otherwise
be
the
case.
One
must
distinguish
between
statistical
and
actual
lives.
An
actual
life
is
saved
when
the
identity
of
the
beneficiary
is
known
before
the
lifesaving
expenditure
is
made.

waterway:
streams,
lakes,
bays,
and
estuaries.

willingness­
to­
pay
(
WTP):
maximum
amount
of
money
one
would
give
up
to
buy
some
good.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

13­
27
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
ACRONYMS
AWQC:
ambient
water
quality
criteria
NOAEL:
no
observed
adverse
effect
level
RfD:
reference
dose
RSEI:
Risk
Screening
Environmental
Indicator
Model
SDWIS:
Safe
Drinking
Water
Information
System
VSL:
value
of
a
statistical
life
saved
WTP:
willingness­
to­
pay
13­
28
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
REFERENCES
Amdur,
M.
O.,
J.
Doul,
and
C.
D.
Klaassen,
eds.
1991.
Cassarett
and
Doul's:
Toxicology,
the
Basic
Science
of
Poisons.
4th
ed.
New
York,
NY:
McGraw­
Hill
Inc.

Amdur,
M.
O.,
J.
Doul,
and
C.
D.
Klaassen,
eds.
1996.
Cassarett
and
Doul's:
Toxicology,
the
Basic
Science
of
Poisons.
5th
ed.
New
York,
NY:
McGraw­
Hill
Inc.

Belton,
T.,
R.
Roundy,
and
N.
Weinstein.
1986.
 
Urban
Fishermen:
Managing
the
Risks
of
Toxic
Exposure. 
Environment
Vol.
28.
No.
9,
November.

Connelly,
N.
and
B.
Knuth.
1993.
Great
Lakes
Fish
Consumption
Health
Advisories:
Angler
Response
to
Advisories
and
Evaluation
of
Communication
Techniques,
Human
Dimensions
Research
Unit,
Dept.
of
Natural
Resources,
NY
State
College
of
Agriculture
and
Life
Sciences,
Cornell
University,
HDRU
Series
No
93­
3,
February.

Connelly,
N.,
B.
Knuth,
and
C.
Bisogni.
1992.
Effects
of
the
Health
Advisory
and
Advisory
Changes
on
Fishing
Habits
and
Fish
Consumption
in
New
York
Sport
Fisheries,
Human
Dimensions
Research
Unit,
Dept.
of
Natural
Resources,
NY
State
College
of
Agriculture
and
Life
Sciences,
Cornell
University,
HDRU
Series
No
92­
9,
September.

Knuth,
B.
and
C.
Velicer.
1990.
Receiver­
Centered
Risk
Communication
for
Sportfisheries:
Lessons
from
New
York
Licensed
Anglers.
Paper
presented
at
the
American
Fisheries
Society
Annual
Meeting,
Pittsburgh,
Penn,
August.

Silverman,
W.
1990.
Michigan s
Sport
Fish
Consumption
Advisory:
A
Study
in
Risk
Communication.
Thesis
submitted
in
partial
fulfillment
of
the
requirements
for
the
degree
of
Master
of
Science
(
Natural
Resources)
at
the
University
of
Michigan,

May.

U.
S.
Department
of
Commerce,
Bureau
of
the
Census.
1997.
http://
www.
census.
gov.

U.
S.
Department
of
the
Interior.
1993.
1991
National
Survey
of
Fishing,
Hunting,
and
Wildlife­
Associated
Recreation,
DOI,

March.

U.
S.
Department
of
the
Interior,
U.
S.
Fish
and
Wildlife
Service
and
U.
S.
Department
of
Commerce,
Bureau
of
the
Census.

1996.
1996
National
Survey
of
Fishing,
Hunting,
and
Wildlife­
Associated
Recreation,
DOI.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1980.
Ambient
water
quality
criteria
documents.
Washington,
DC:

Office
of
Water,
U.
S.
EPA.
EPA
440/
5­
80
Series.
Also
refers
to
any
update
of
criteria
documents
(
EPA
440/
85
and
EPA
440/
5­
87
Series)
or
any
Federal
Register
notices
of
proposed
criteria
or
criteria
corrections.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1997a.
Health
Effects
Assessment
Summary
Tables
(
HEAST).
Office
of
Research
and
Development
and
Office
of
Emergency
and
Remedial
Response,
Washington,
DC:
U.
S.
EPA.
OERR
9200/
6­

303
(
92­
1).

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1997b.
The
Benefits
and
Costs
of
the
Clean
Air
Act,
1970
to
1990.

Washington,
DC:
Office
of
Air
and
Radiation,
U.
S.
EPA.
EPA
410­
R­
97­
002,
October.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1997c.
Exposure
Factors
Handbook.
Volumes
I,
II,
and
III.

Washington,
DC:
National
Center
for
Environmental
Assessment,
Office
of
Research
and
Development.
EPA­
600­
P­
95­

002Fa,
b,
c.
August.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998.
Ambient
Water
Quality
Criteria
Derivation
Methodology:

Human
Health.
Technical
Support
Document.
EPA­
822­
B­
98­
005.
July.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1998/
99.
Integrated
Risk
Information
System
(
IRIS)
Retrieval.

Washington,
DC:
U.
S.
EPA.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1999a.
National
Listing
of
Fish
and
Wildlife
Consumption
Advisories.

Washington,
DC:
Office
of
Water,
U.
S.
EPA.

13­
29
MP&
M
EEBA
Part
III:
Benefits
Chapter
13:
Human
Health
Benefits
U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
1999b.
Risk­
Screening
Environmental
Indicators
Model:
Version
1.0.

Washington,
DC:
Office
of
Pollution
Prevention
and
Toxics,
U.
S.
EPA.
July
6.

http://
www.
epa.
gov/
opptintr/
env_
ind/
index.
html.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
2000a.
Methodology
for
Deriving
Ambient
Water
Quality
Criteria
for
the
Protection
of
Human
Health
.
EPA
822­
B­
00­
004.
October.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
2000b.
Estimated
Per
Capita
Water
Ingestion
in
the
United
States.

EPA­
822­
R­
00­
008.
April.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
2000c.
Guidelines
for
Preparing
Economic
Analyses.
Washington,

DC:
EPA
240­
R­
00­
003.
September.

U.
S.
Environmental
Protection
Agency.
(
U.
S.
EPA).
2001.
Arsenic
Rule
Benefits
Analysis:
An
SAB
Review
.
Washington,

DC:
EPA­
SAB­
EC­
01­
008.
August.

West,
P.,
R.
Marans,
F.
Larkin,
and
M.
Fly.
1989.
Michigan
Sport
Anglers
Fish
Consumption
Survey:
A
Report
to
the
Michigan
Toxic
Substances
Control
Commission,
University
of
Michigan
School
of
Natural
Resources,
Natural
Resources
Sociology
Research
Lab,
Technical
Report
#
1,
May.

Wexler,
P.,
ed.
1998.
Encyclopedia
of
Toxicology,
Vol.
1­
3.

13­
30
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
INTRODUCTION
The
human
health
benefits
analysis
presented
in
the
previous
chapter
examined
both
cancer
and
non­
cancer
health
risks
from
exposure
to
MP&
M
pollutants.
EPA
performed
a
separate
analysis
of
benefits
from
reduced
exposure
to
lead.

The
analysis
of
health
effects
from
exposure
to
lead
is
based
on
dose­
response
functions
tied
to
specific
health
endpoints
to
which
monetary
values
can
be
applied.
In
this
way
it
differs
from
the
analysis
of
non­
cancer
health
risk
from
exposure
to
other
MP&
M
pollutants.
This
analysis
assessed
benefits
of
reduced
lead
exposure
from
consumption
of
contaminated
fish
tissue
to
three
population
groups:
(
1)

preschool
age
children,
(
2)
pregnant
women,
and
(
3)
adult
men
and
women.
These
lead­
related
benefits
were
estimated
for
the
final
MP&
M
regulation,
the
433
Upgrade
Options,
and
the
Proposed/
NODA
option.

EPA
estimated
benefits
to
preschool
children
based
on
a
dose­
response
relationship
for
intelligence
quotient
(
IQ)

decrements.
The
Agency
calculated
monetary
values
for
avoided
neurological
and
cognitive
damages
based
on
the
impact
of
an
additional
IQ
point
on
an
individual s
future
earnings
and
the
cost
of
compensatory
education
for
children
with
learning
disabilities.
EPA
also
assessed
the
incidence
of
neonatal
mortality
due
to
changes
in
maternal
blood
lead
(
PbB)
levels
during
pregnancy
based
on
willingness­
to­

pay
(
WTP)
values
for
avoiding
death.
EPA
estimated
that
the
final
regulation
will
not
yield
any
benefits
to
children
from
reduced
exposure
to
lead.

The
health
effects
in
adults
that
EPA
was
able
to
quantify
all
relate
to
lead s
effect
on
blood
pressure
(
BP).
Quantified
health
effects
include
incidence
of
hypertension
in
adult
men,
initial
non­
fatal
coronary
heart
disease
(
CHD),
non­
fatal
strokes
(
cerebrovascular
accidents
(
CBA)
and
atherothrombotic
brain
infarctions
(
BI)),
and
premature
mortality.

EPA
used
cost
of
illness
(
COI)
estimates
(
i.
e.,
medical
costs
and
lost
work
time)
to
estimate
monetary
values
of
reduced
incidence
of
hypertension,
initial
CHD,
and
strokes.
EPA
used
COI
estimates
to
estimate
monetary
values
for
reduced
incidence
of
hypertension,
initial
CHD,
and
strokes.
This
analysis
uses
the
$
6.5
million
estimate
of
the
value
of
a
statistical
life
saved
recommended
in
the
Guidelines
for
Preparing
Economic
Analysis
(
EPA,
2000a)
to
estimate
monetary
value
of
reduced
incidence
of
premature
mortality.
EPA
estimated
that
the
final
rule
will
achieve
no
lead­
related
health
benefits
among
adults.
Chapter
14:
Lead­
Related
Benefits
CHAPTER
CONTENTS
14.1
iew
of
Lead­
Related
Health
Effects
......
14­
2
14.1.1
nder
Age
One
..............
14­
3
14.1.2
etween
the
Ages
of
One
and
Seven
.................
..............
14­
3
14.1.3
.................
............
14­
4
14.2
.................
.
14­
4
14.2.1
ution
of
Exposed
Children
....
14­
5
14.2.2
and
IQ
.................
.............
14­
12
14.2.3
........
14­
12
14.2.4
Additional
Educational
Resources
.................
..........
14­
14
14.2.5
in
Neonatal
Mortality
.........
14­
17
14.3
alth
Benefits
.................
....
14­
17
14.3.1
Distribution
Levels
.................
...
14­
20
14.3.2
alth
Benefits
................
14­
22
14.3.3
le
Health
Benefits
..............
14­
26
14.4
elated
Benefit
Results
...............
14­
28
14.4.1
ge
Children
Lead­
Related
Benefit
Results
.................
......
14­
28
14.4.2
ead­
Related
Benefit
Results
.....
14­
29
14.5
...............
14­
31
14.5.1
............
14­
31
14.5.2
nsatory
Education
Costs
........
14­
32
14.5.3
sponse
Relationships
.........
14­
32
14.5.4
on
Function
for
Ingested
Lead
in
Fish
Tissue
.................
...
14­
32
14.5.5
c
Valuation
.................
14­
33
Glossary
.................
.................
..
14­
35
Acronyms
.................
.................
.
14­
38
References
.................
.................
14­
39
Overv
Children
U
Children
B
Adults
Health
Benefits
to
Children
PbB
Distrib
Relationship
Between
PbB
Levels
Value
of
Children's
Intelligence
Value
of
Changes
Adult
He
Estimating
Changes
in
Adult
PbB
Male
He
Fema
Lead­
R
Preschool
A
Adult
L
Limitations
and
Uncertainties
Excluding
Older
Children
Compe
Dose­
Re
Absorpti
Economi
14­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
14.1
OVERVIEW
OF
LEAD­
RELATED
HEALTH
EFFECTS
The
MP&
M
regulation
will
reduce
lead
exposure
by
reducing
the
amount
of
lead
discharged
to
water
bodies
from
MP&
M
facilities,
thereby
reducing
health
and
ecological
risks.
This
section
provides
a
brief
summary
of
the
human
health
effects
from
exposure
to
lead.
Data
for
this
analysis
are
taken
from
the
Agency
for
Toxic
Substance
and
Disease
Registry s
(
ATSDR)
Draft
Toxicological
Profile
for
Lead
(
1997)
unless
otherwise
noted.
The
discussion
provided
in
this
section
is
qualitative
and
was
not
used
to
generate
risk
estimates.

Lead
and
lead
compounds
are
toxic
and
pose
threats
to
human
health
and
well
being.
The
health
effects
of
very
high
levels
of
PbB
include
convulsions,
coma,
and
death
from
lead
toxicity.
These
effects
have
been
understood
for
many
years.
The
effects
of
lower
doses
of
lead
are
not
fully
understood,
however,
and
continue
to
be
the
subject
of
intensive
scientific
investigation
(
CDC,
1991b).

Lead
accumulates
in
the
body
and
is
stored
in
various
organ
systems.
While
high
level
exposures
are
of
immediate
concern
due
to
acute
toxicity,
exposure
to
small
amounts
can
accumulate
over
time
to
harmful
levels.
Accumulated
lead
is
very
persistent,
with
a
half­
life
in
bone
of
approximately
27
years.
1
Known
or
strongly
suspected
health
effects
include
kidney,

stomach,
and
respiratory
cancer,
nervous
system
disorders,
hypertension,
anemia
and
blood
disorders,
gastrointestinal
disorders,
renal
damage,
and
other
effects
(
ATSDR,
1997;
CARB,
1996).
Increased
mortality
from
these
effects
has
been
observed
in
studies
(
ATSDR
,
1997).

Many
lead­
associated
adverse
health
effects
are
both
chronic
in
nature
and
relatively
common.
These
effects
include
but
are
not
limited
to
hypertension,
coronary
artery
disease,
and
impaired
cognitive
function.
Specific
cases
of
these
conditions
are
difficult
to
link
to
lead
exposure
because
the
same
adverse
health
effects
or
endpoints
can
arise
from
a
variety
of
causes.

Despite
numerous
studies
conducted
by
EPA
and
other
institutions,
dose­
response
functions
are
available
only
for
a
handful
of
health
endpoints
associated
with
elevated
PbB
levels.
2
The
available
research
does
not
always
allow
complete
economic
evaluation,
even
for
quantifiable
health
effects.

Lead
is
harmful
to
any
exposed
individual,
and
the
effects
of
lead
on
children
are
of
particular
concern.
Children s
rapid
development
rate
makes
them
more
susceptible
to
neurobehavioral
deficits
resulting
from
lead
exposure.
U.
S.
EPA
identifies
three
sensitive
populations:
children
under
age
one,
children
between
the
ages
one
and
seven,
and
adult
men
and
women
(
U.
S.
EPA,
1990).
New
research
suggests
that
children
older
than
seven
may
also
be
a
hypersensitive
population.

Recent
research
on
brain
development
among
10­
to
18­
year­
old
children
shows
unanticipated
and
substantial
growth
in
brain
development,
mainly
in
the
early
teenage
years
(
Giedd
et
al.,
1999).
This
analysis
does
not,
however,
include
this
group
due
to
data
limitations.
Table
14.1
summarizes
the
quantifiable
health
effects
on
children
under
seven
and
adult
men
and
women,

along
with
other
important,
non­
quantified,
known
health
effects
on
these
populations.

1
A
half­
life
of
27
years
means
that
it
takes
27
years
for
the
levels
measured
in
bone
to
decrease
by
50
percent.

2
In
a
pioneering
study,
Schwartz
et
al.
quantified
a
number
of
health
benefits
that
would
result
from
reducing
the
lead
content
of
gasoline
(
U.
S.
EPA,
1985).
EPA
extended
this
work
by
analyzing
lead
in
drinking
water
(
U.
S.
EPA,
1986a)
and
by
funding
the
study
of
lead
in
the
air
(
U.
S.
EPA,
1987).

14­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.1:
Quantified
and
Unquantified
Health
Effects
of
Lead
Population
Group
Quantified
Health
Effect
Unquantified
Health
Effect
Children
ages
0­
7
Neonatal
mortality
due
to
decreased
gestational
age
and
low
birth
weight
caused
by
maternal
exposure
to
lead
Nervous
system
effects
in
children
younger
than
7
years
­
IQ
decrements,
cases
of
IQ
less
than
70,
PbB
levels
greater
than
20
 
g/
dL
Fetal
effects
from
maternal
exposure
(
including
diminished
IQ
and
reduced
birth
weight)

Low
IQ
(
70
<
IQ<
84)
Permanent
brain
structure
changes
Slowed/
delayed
growth
Delinquent
and
anti­
social
behavior
Metabolic
effects,
impaired
heme
synthesis,

anemia
Impaired
hearing
Possible
cancer
­
stomach,
kidney,
respiratory
tract
Lead
effects
in
children
over
7
years
Adult
Female
ages
45­
74
Ages
45­
74
Non­
fatal
CHD
Non­
fatal
stroke
Mortality
Non­
fatal
CHD,
non­
fatal
strokes
and
mortality
for
women
in
other
age
ranges
Other
cardiovascular
diseases
Hypertension
Hypertension
in
pregnant
women
Reproductive
effects
­
reduced
fertility
Neurobehavioral
function
Gastrointestinal
effects
­
nausea,
constipation,
loss
of
appetite
Renal
effects
­
chronic
nephropathy,
gout
Possible
cancer
­
stomach,
kidney,
respiratory
tract
Adult
Male
ages
20
­
74
For
men
in
specified
age
ranges:

Ages
20­
74
Hypertension
Ages
40­
75
Non­
fatal
CHD
Mortality
Ages
45­
74
Non­
fatal
stroke
Non­
fatal
CHD,
non­
fatal
strokes
and
mortality
for
men
in
other
age
ranges
Other
cardiovascular
diseases
Reproductive
­
men:
sperm
abnormalities
Neurobehavioral
function
Gastrointestinal
effects
­
nausea,
constipation,
loss
of
appetite
Renal
effects
­
chronic
nephropathy,
gout
Possible
cancer
­
stomach,
kidney,
respiratory
tract
Source:
U.
S.
EPA
analysis.

14.1.1
Children
Under
Age
One
Fetal
exposure
to
lead
in
utero
from
maternal
lead
intake
may
result
in
several
adverse
health
effects,
including
decreased
gestational
age,
body
weight,
head
circumference,
body
length,
late
fetal
death,
and
increased
infant
mortality
(
Moore
et
al.,

1982;
McMichael
et
al.,
1986;
Ward
et
al.,
1987;
Dietrich
et
al.,
1987;
Bornschein
et
al.,
1989;
Bellinger
et
al.,
1991).
The
Centers
for
Disease
Control
(
CDC)
estimated
that
the
risk
of
infant
mortality
increases
by
10­
4
for
each
1
 
g/
dL
increase
in
maternal
PbB
level
during
pregnancy
(
CDC,
1991b).
Neurobehavioral
deficits
in
infants
can
result
from
both
pre­
natal
and
early
post­
natal
exposure.
The
metabolic
effects
described
for
children
in
the
section
below
have
also
been
identified
in
infants.
These
effects
can
be
quantified
based
on
the
dose­
response
relationship
between
PbB
levels
and
intelligence
quotient
(
IQ)
decrements
(
Schwartz,
1994).

14.1.2
Children
Between
the
Ages
of
One
and
Seven
Elevated
PbB
levels
in
children
may
result
in
metabolic
effects
such
as
impaired
heme
synthesis,
anemia,
slowed
growth,
and
cancer
(
U.
S.
EPA,
1990).
Severe
lead
poisoning
may
result
in
seizures,
impaired
coordination,
recurrent
vomiting,
coma,
and
acute
lead
encephalopathy,
a
potentially
fatal
condition
(
Piomelli
et
al.,
1984).
Elevated
lead
exposure
may
also
induce
a
number
of
effects
on
the
human
nervous
system.
These
effects
include
hyperactivity,
behavioral
and
attentional
difficulties,

delayed
mental
development,
and
motor
and
perceptual
skill
deficits.
The
neurobehavioral
effects
on
children
can
be
quantified
based
on
the
dose­
response
relationship
for
IQ
decrements
(
Shwartz,
1993).

14­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
14.1.3
Adults
EPA
has
classified
lead
as
a
probable
human
carcinogen
(
Group
2b)
based
on
animal
toxicological
evidence
(
IRIS,
2002a;

see
file
titled
Lead
and
Compounds
(
inorganic)).
Lead
also
has
been
strongly
suggested
as
the
causative
agent
in
numerous
studies
of
kidney,
stomach,
and
respiratory
cancer
in
humans.
The
cancers
observed
in
human
studies
are
usually
lethal.
A
cancer
potency
factor
for
lead
has
not
been
published
by
U.
S.
EPA,
however,
due
to
uncertainties
associated
with
human
studies.
The
California
Environmental
Protection
Agency
(
CEPA)
has
also
classified
lead
as
a
carcinogen
and
estimated
a
cancer
potency
factor
of
8.5
×
10­
3
per
mg/
kg/
day
for
exposure
to
lead
and
lead
compounds
(
California
Air
Resource
Board
[
CARB],
1996).
3
Reduced
cancer
risk
associated
with
reduced
exposure
to
lead
can
be
estimated
based
on
cancer
cases
avoided
(
see
Section
13.2.1).
The
Agency
did
not
incorporate
cancer
effects
from
exposure
to
lead
in
the
final
rule
analysis
because
these
effects
appeared
very
small
compared
to
other
adverse
health
effects
from
exposure
to
lead
(
e.
g.,
neurological
damages
to
children).

Elevated
PbB
has
been
linked
to
elevated
BP
in
adults,
especially
in
men
aged
40
to
59
(
Pirkle
et
al.,
1985).
Elevated
BP,

itself
a
health
hazard,
is
also
a
risk
factor
for
heart
attack,
stroke
(
Shurtleff,
1974;
McGee
and
Gordon,
1976;
Pooling
Project
Research
Group
[
PPRG],
1978),
and
premature
death.
Since
heart
disease
and
its
related
diseases
are
the
primary
cause
of
death
in
the
United
States,
avoiding
their
exacerbation
by
minimizing
lead
exposure
can
be
assumed
to
have
considerable
benefits
for
the
affected
population.
Although
elevated
BP
in
women
results
in
the
same
effects
as
for
men,
the
general
relationships
between
BP
and
these
health
effects
differ
somewhat
across
gender
(
Shurtleff,
1974).

Other
known
or
strongly
suspected
health
endpoints
include
nervous
system
disorders
in
adults,
anemia
and
blood
disorders,

gastrointestinal
disorders,
and
renal
damage
(
Roels
et
al.,
1976;
Factor­
Litvak
et
al.,
1993;
1998;
and
1999).
Finally,
data
suggest
that
lead
is
genotoxic
and
may
cause
chromosomal
damage
in
humans
leading
to
birth
defects
(
Anwar,
1994;

Apostoli
et
al.,
2000;
Sallmen
et
al,
2000).
Lead
may
also
cause
other
adverse
reproductive
effects
in
women,
including
increased
miscarriage
and
stillbirth
(
U.
S.
EPA
1990).
A
study
of
National
Health
and
Nutrition
Examination
Surveys
(
NHANES)
II
data
by
Silbergeld
et
al.
suggests
that
accumulated
lead
is
stored
in
women s
bone
tissues
and
is
mobilized
back
into
the
blood
during
the
bone
demineralization
associated
with
pregnancy,
lactation,
and
osteoporosis
(
Silbergeld
et
al.,

1988).
Many
of
these
effects
cannot
be
quantified
due
to
a
lack
of
information
on
the
dose­
effect
relationship.

14.2
HEALTH
BENEFITS
TO
CHILDREN
The
following
analysis
assesses
benefits
to
children
from
reduced
lead
exposure,
via
reduced
consumption
of
contaminated
4
fish
tissue.
This
analysis
uses
PbB
concentrations
as
a
biomarker
of
lead
exposure.
5
EPA
estimated
PbB
levels
in
the
population
of
exposed
children
to
obtain
both
baseline
and
post­
compliance
readings.
Changes
in
those
readings
yielded
estimated
benefits
from
reduced
lead
exposure
in
the
form
of
avoided
damages.
Avoided
neurological
and
cognitive
damages
are
expressed
as
changes
in
overall
IQ
levels,
including
reduced
incidence
of
extremely
low
IQ
scores
(<
70,
or
two
standard
deviations
below
the
mean),
and
reduced
incidence
of
PbB
levels
above
20
 
g/
dL.
The
neurological
and
cognitive
damages
avoided
are
then
quantified
using
the
value
of
compensatory
education
that
an
individual
would
otherwise
need,
and
the
impact
on
that
individual s
future
earnings.
This
analysis
does
not
quantify
additional
benefit
categories,
such
as
the
costs
of
PbB
screening
and
medical
treatment.
The
reduced
loss
in
IQ
points,
reduced
cases
of
IQ
levels
below
70
points,
and
reduced
special
education
costs
associated
with
various
PbB
levels
are
likely
to
be
the
largest
benefit
categories.
This
analysis
does
not
estimate
the
cost
of
group
homes
and
other
special
care
facilities.

The
analysis
of
health
benefits
to
children
involves
the
following
steps:

 
estimate
the
baseline
and
post­
compliance
lead
discharges
from
MP&
M
facilities;

3
The
cancer
potency
factors
for
lead
acetate
and
lead
subacetate
are
28
×
10­
1
and
3.8
×
10­
2
,
respectively.

4
This
analysis
does
not
consider
the
beneficial
effects
due
to
reduced
drinking
water
exposure.
EPA
has
issued
drinking
water
criteria
for
lead.
This
analysis
assumes
drinking
water
treatment
has
already
reduced
lead
content
below
threshold
levels.

5
PbB
concentration
is
the
most
common
measure
of
body­
lead
burden.
Other
measures
of
body­
lead
burden
include
lead
in
bones,

teeth,
and
hair.

14­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
 
estimate
lead
concentrations
in
receiving
water
bodies
before
and
after
final
effluent
guidelines
based
on
lead
discharge
estimates,
effluent
flow,
characteristics
of
the
receiving
POTW
s,
and
characteristics
of
receiving
water
bodies;

 
estimate
the
baseline
and
post­
compliance
dietary
lead
intake
of
children
via
fish
consumption;

 
estimate
PbB
levels
of
exposed
children
before
and
after
the
final
regulation,
based
on
in­
stream
lead
concentrations,

bioconcentration
factors,
and
fish
consumption
rates
for
children;

 
assess
changes
in
health
impacts
to
children
from
reduced
lead
exposure,
including
changes
in
IQ
loss,
changes
in
incidence
of
IQ<
70,
and
changes
in
neonatal
mortality;

 
estimate
monetary
benefits
resulting
from
reduced
adverse
health
impacts
to
children;
and
 
estimate
benefits
from
changes
in
neonatal
mortality
from
reduced
maternal
exposure
to
lead.

Figure
14.1
depicts
the
above
steps.

The
following
sections
summarize
the
relevant
dose­
response
relationships
for
children,
and
discuss
data
sources
used
for
the
dose­
response
relationships.
Each
section
also
includes
the
methods
used
to
value
the
changes
in
health
effects
based
upon
dose­
response
relationships.

14.2.1
PbB
Distribution
of
Exposed
Children
This
section
describes
the
estimation
of
changes
in
PbB
distribution
of
exposed
children.

a.
Estimating
lead
concentrations
in
the
receiving
water
bodies
Estimating
health
risks
associated
with
lead
exposure
from
fish
consumption
requires
calculating
in­
waterway
lead
concentrations.
The
method
and
formulas
for
this
calculation
were
identical
to
those
described
for
the
analysis
of
cancer
effects
for
the
fish
consumption
pathway
(
see
Chapter
13
on
Human
Health
Benefits
and
the
Environmental
Assessment
in
Appendix
I
for
details.)
6
b.
Estimating
PbB
levels
in
exposed
children
This
analysis
considers
children
that
are
born
today
and
live
in
recreational
and
subsistence
fishermen
households.
The
analysis
considers
a
continuous
exposure
pattern
for
children
from
birth
through
the
seventh
birthday.
Exposure,
health
effects,
and
benefits
are
calculated
separately
for
children
living
in
recreational
and
subsistence
fishing
households.
This
analysis
relies
on
EPA s
Integrated
Exposure,
Uptake,
and
Biokinetics
(
IEUBK)
Model
for
Lead
in
Children
(
IEUBK
version
0.99d,
March
8,
1994).

 
Description
of
the
IEUBK
model
The
IEU
BK
model
uses
exposure,
uptake,
and
biokinetic
response
information
to
estimate
the
PbB
level
distribution
for
a
population
of
children
receiving
similar
exposures.
The
estimated
distribution
may
be
used
to
predict
the
probability
of
elevated
PbB
levels
in
children
exposed
to
a
specific
combination
of
environmental­
lead
levels.
The
model
addresses
four
components
of
environmental
risk
assessment:

 
the
multimedia
nature
of
exposure
to
lead;

 
the
differential
bioavailability
of
various
sources
of
lead;

 
the
pharmacokinetics
of
internal
distribution
of
lead
to
bone,
blood,
and
other
tissues;
and
 
inter­
individual
variability
in
PbB
levels.

6
The
water
quality
model
used
for
the
Ohio
case
study
is
discussed
in
Appendix
H.

14­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Figure
14.1
Assessing
Benefits
to
Children
from
Reduced
Lead
Discharges
from
MP&
M
Facilities
Source:
U.
S.
EPA
analysis.

14­
6
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
The
model
uses
estimated
or
measured
lead
concentrations
in
fish
tissues
and
other
media,
such
as
soil,
dust,
air,
and
water
to
estimate
a
continuous
exposure
pattern
for
children
from
birth
through
the
seventh
birthday
(
U.
S.
EPA,
1995).
The
model
then
estimates
a
distribution
of
PbB
levels
for
a
population
of
children
receiving
similar
exposures
by
predicting
its
geometric
mean
(
GM)
.
The
inter­
individual
and
biological
variability
in
PbB
levels
of
children
exposed
to
similar
environmental
lead
levels
is
represented
by
the
geometric
standard
deviation
(
GSD).
This
analysis
uses
an
empirical
estimate
of
the
variability
in
PbB
concentrations,
a
GSD
of
1.6,
estimated
from
residential
community
PbB
studies
(
U.
S.
EPA,

1995).
This
estimate
is
applied
for
predictions
of
the
national
distribution
of
PbB
concentrations.

The
model
has
three
distinct
functional
components
that
work
together
in
a
series:

 
exposure,

 
uptake,
and
 
biokinetics
response.

Each
model
component
is
a
set
of
complex
equations
and
parameters.
The
Technical
Support
Document
(
U.
S.
EPA,
1995)

provides
the
scientific
basis
of
the
parameters
and
equations
used
in
the
model,
while
the
Guidance
Manual
(
U.
S.
EPA,
1994)

includes
a
detailed
description
of
the
exposure
pathways,
absorption
mechanism,
biokinetic
compartments,
and
associated
comparted
transfers
of
lead.

 
 
Inputs
to
the
IEUBK
model
The
IEUBK
model
uses
three
sets
of
parameters:

 
exposure
parameters
estimate
the
amount
of
environmental
lead
taken
into
the
body,
through
breathing
or
ingestion;

 
uptake
parameters
estimate
the
amount
of
lead
absorbed
from
environmental
sources;

 
biokinetic
parameters
characterize
the
transfer
of
lead
between
compartments
of
the
body
(
e.
g.,
between
blood
and
bone)
and
elimination
of
lead
from
the
body.

The
IEUBK
model
allows
the
user
to
input
values
for
most
exposure
and
uptake
parameters.
The
biokinetic
parameter
values
cannot
be
altered.
When
exposure
and
uptake
values
are
not
specified,
the
IEUBK
model
provides
default
values.
Table
14.2
summarizes
the
key
parameter
values
used
in
this
analysis
and
indicates
whether
a
value
is
an
IEUBK
default
value
or
has
7
been
specified
by
EPA.

1.
Exposure
parameters
include
exposure
rates
and
exposure
concentrations:

 
Exposure
rates:
Children
in
recreational
fishing
households
are
assumed
to
consume
6.03
grams
of
fish
per
day.

Children
living
in
subsistence
households
are
assumed
to
consume
30.33
grams
of
fish
per
day.
These
fish
consumption
rates
are
based
on
uncooked
fish
weights.
The
fish
consumption
rate
for
children
in
recreational
fishing
households
is
calculated
as
a
weighted
average
based
on
West
et
al.
(
U.
S.
EPA,
1997a)
for
children
ages
1­
5
(
5.63
grams
of
fish
per
day)
and
children
ages
6­
10
(
7.94
grams
of
fish
per
day).
For
children
of
subsistence
fishing
households,
the
fish
consumption
rate
is
calculated
as
a
weighted
average
based
on
Columbia
River
Intertribal
Fish
Commission
(
CRITFC,
1994)
estimates
for
children
under
age
5
(
19.6
grams
of
fish
per
day)
and
the
Continuing
Survey
of
Foods
by
Individuals
(
U.
S.
EPA,
2002b)
for
children
ages
3­
5
(
40.31
grams
of
fish
per
day)
and
ages
6­
10
(
61.49
grams
of
fish
per
day).

 
Exposure
concentrations:
EPA
used
estimated
in­
stream
concentrations
of
lead
to
calculate
lead
concentration
of
the
fish
consumption
exposure
pathway.
The
Agency
used
1996
monitoring
data
(
U.
S.
EPA,
1996b)
on
lead
concentrations
in
air
and
the
Housing
and
Urban
Development
National
Survey
(
HUD
,
1995)
for
data
on
lead
8
concentrations
in
dust
and
soil
to
characterize
lead
exposure
concentrations
for
these
exposure
pathways.
This
7
A
complete
list
of
IEUBK
default
parameters
is
presented
in
Appendix
L.

8
EPA
found
that
the
typical
PbB
level
distribution
predicted
in
the
IEUBK
Model
for
Lead
in
Children
based
on
the
default
values
for
air,
dust,
soil,
and
drinking
water
lead
concentrations
did
not
correspond
to
the
most
recent
national
population
PbB
distribution
(
NHANES
III,
Phase
2,
1994).
Therefore,
the
Agency
used
more
recent
data
to
characterize
the
background
exposure
to
environmental
14­
7
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
analysis
uses
median
concentration
values
for
these
three
pathways
as
inputs
to
the
IEUBK
to
characterize
background
exposure
to
environmental
lead.
EPA
used
the
IEUBK
default
value
for
lead
concentration
in
drinking
water
that
takes
into
account
contributions
of
lead
from
plumbing.
Because
of
past
use
of
lead
in
plumbing,
lead
concentrations
in
tap
water
are
likely
to
be
above
the
current
water
quality
standard
for
lead
in
drinking
water.

2.
Uptake
of
ingested
lead:
Lead
bioavailability
varies
across
the
chemical
forms
in
which
lead
can
exist.
Many
factors
complicate
the
estimation
of
bioavailability,
including
nutritional
status
and
timing
of
meals
relative
to
lead
intake.
The
Agency
used
the
default
media­
specific
bioavailabilities
in
the
IEUBK
model
for
this
analysis.

3.
Biokinetic
parameters:
The
data
on
which
these
parameter
values
are
based
originate
from
a
variety
of
sources,
including
available
clinical
data
(
U.
S.
EPA,
1995).
These
parameters
cannot
be
changed
by
the
user.

lead.
Median
values
from
recent
monitoring
data
allowed
the
Agency
to
match
the
IEUBK­
predicted
PbB
distribution
to
the
NHANES­

derived
distribution.

14­
8
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.2:
Selected
List
of
Parameters
Used
in
the
IEUBK
Model
Variable
Value
IEUBK
Default
Data
Source
Exposure
Rates
Fish:
Recreational
6.03
g/
day
No
The
fish
consumption
rate
for
children
in
recreational
fishing
households
is
calculated
as
a
weighted
average
based
on
West
et
al.
(
U.
S.
EPA,
1997a)
for
children
ages
1­
5
(
5.63
g/
day)
and
children
ages
6­
10
(
7.94
g/
day).
ish
consumption
rate
for
children
in
subsistence
fishing
households
is
calculated
as
a
weighted
average
based
on
Columbia
River
Intertribal
Fish
Commission
(
CRITFC,
1994)
estimates
for
children
under
age
5
(
19.6
g/
day)
and
the
Continuing
Survey
of
Foods
by
Individuals
(
U.
S.
EPA,
2002b)
for
children
ages
3­
5
(
40.31
g/
day)
and
ages
6­
10
(
61.49
g/
day).

Fish:
Subsistence
30.33
g/
day
No
Fresh
Fruit
38.481
g/
day
0­
11
months
169.000
g/
day
12­
23
months
63.166
g/
day
24­
35
months
61.672
g/
day
36­
47
months
61.848
g/
day
48­
59
months
67.907
g/
day
60­
71
months
80.024
g/
day
72­
84
months
Yes
Values
taken
from
Pennington,
J.
A.
T.
(
1983)
Revision
of
the
total
diet
study
food
list
and
diets.
Journal
of
American
Dietetic
Association
82(
2):
166­
173
Fresh
Vegetables
56.84
g/
day
0­
11
months
106.50
g/
day
12­
23
months
155.75
g/
day
24­
35
months
157.34
g/
day
36­
47
months
158.93
g/
day
48­
59
months
172.50
g/
day
60­
71
months
199.65
g/
day
72­
84
months
Yes
Values
taken
from
Pennington,
J.
A.
T.
(
1983)
Revision
of
the
total
diet
study
food
list
and
diets.
Journal
of
American
Dietetic
Association
82(
2):
166­
173
Meat
(
Including
fish
and
game)
29.551
g/
day
0­
11
months
87.477
g/
day
12­
23
months
95.700
g/
day
24­
35
months
101.570
g/
day
36­
47
months
107.441
g/
day
48­
59
months
111.948
g/
day
60­
71
months
120.961
g/
day
72­
84
months
Yes
Values
taken
from
Pennington,
J.
A.
T.
(
1983)
Revision
of
the
total
diet
study
food
list
and
diets.
Journal
of
American
Dietetic
Association
82(
2):
166­
173
Air
(
Time
spent
outdoors)
1
hrs/
day
0­
11
months
2
hrs/
day
12­
23
months
3
hrs/
day
24­
35
months
4
hrs/
day
36­
47
months
4
hrs/
day
48­
59
months
4
hrs/
day
60­
71
months
4
hrs/
day
72­
84
months
Yes
Based
on
values
reported
in
(
1)
U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA),

Review
of
the
National
Ambient
Air
Quality
Standards
for
Lead:
Assessment
of
Scientific
and
Technical
Information.
OAQPS
Staff
Paper,
Air
Quality
Management
Division,

Research
Triangle
Park,
NC
(
EPA
1989c),
and
(
2)
Report
of
the
Clean
Air
Scientific
Advisory
Committee
on
Its
Review
of
the
OAQPS
Lead
Staff
Paper.

EPA­
SAB­
CASAC­
90­
002
(
EPA
1990a)
The
f
14­
9
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.2:
Selected
List
of
Parameters
Used
in
the
IEUBK
Model
Variable
Value
IEUBK
Default
Data
Source
Water
(
Daily
amount
of
water
consumed)
0.20
L/
day
0­
11
months
0.50
L/
day
12­
23
months
0.52
L/
day
24­
35
months
0.53
L/
day
36­
47
months
0.55
L/
day
48­
59
months
0.58
L/
day
60­
71
months
0.59
L/
day
72­
84
months
Yes
Exposure
Factors
Handbook.
U.
S.
EPA
Office
of
Health
and
Environmental
Assessment,

Washington,
DC.
EPA/
600/
8­
89/
043
(
1989b)

Soil
(
Combined
soil
and
dust
consumption)
0.085
g/
day
0­
11months
0.135
g/
day
12­
23
months
0.135
g/
day
24­
35
months
0.135
g/
day
36­
47
months
0.100
g/
day
48­
59
months
0.090
g/
day
60­
71
months
0.085
g/
day
72­
84
months
Yes
Based
on
value
reported
in
Review
of
the
National
Ambient
Air
Quality
Standards
for
Lead:
Assessment
of
Scientific
and
Technical
Information.
OAQPS
Staff
Paper,
Air
Quality
Management
Division,
Research
Triangle
Park,
NC
(
1989c)

Exposure
Concentrations
Fish
Tissue
site­
specific
No
Estimated
based
on
predicted
lead
concentration
in
receiving
reaches
and
bioconcentration
factor
for
lead
(
49
L/
Kg)

Outdoor
Air
0.03
 
g/
m3
No
Median
value
for
1996
from
EPA s
AIRS
(
Aerometric
Information
Retrieval
System)
air
monitoring
data
(
U.
S.
EPA,
1996b)

Indoor
Air
30%
of
Outdoor
Air
Yes
Based
on
value
reported
in
Review
of
the
National
Ambient
Air
Quality
Standards
for
Lead:
Assessment
of
Scientific
and
Technical
Information.
OAQPS
Staff
Paper,
Air
Quality
Management
Division,
Research
Triangle
Park,
NC
(
1989c)

Water
4.0
 
g/
L
Yes
Analysis
of
data
from
American
Water
Works
Service
Co.
in
Marcus,
A.
H.
(
1989)

Distribution
of
lead
in
tap
water.
Parts
I
and
II.
Report
to
the
U.
S.
EPA
Office
of
Drinking
Water/
Office
of
Toxic
Substances,
from
Battelle
Memorial
Institute
under
Contract
68­
D8­

0115.

Soil
61.78
 
g/
g
No
Median
values
from
the
Housing
and
Urban
Development
National
Survey
(
U.
S.

Department
of
Housing
and
Urban
Development,
1995)

Dust
187.11
 
g/
g
No
Food
Lead
Intake
Fresh
Fruit
0.039
 
g/
day
0­
11
months
0.196
 
g/
day
12­
23
months
0.175
 
g/
day
24­
35
months
0.175
 
g/
day
36­
47
months
0.179
 
g/
day
48­
59
months
0.203
 
g/
day
60­
71
months
0.251
 
g/
day
72­
84
months
Yes
Based
on
data
provided
by
FDA
in
Air
Quality
Criteria
for
Lead
Vol
I­
IV.
U.
S.
EPA
Environmental
Criteria
and
Assessment
Office,
Research
Triangle
Park,
NC.
EPA
600/
8­
83­
028a­
d
(
1986b)

14­
10
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.2:
Selected
List
of
Parameters
Used
in
the
IEUBK
Model
Variable
Value
IEUBK
Default
Data
Source
Fresh
Vegetables
0.148
 
g/
day
0­
11
months
0.269
 
g/
day
12­
23
months
0.475
 
g/
day
24­
35
months
0.466
 
g/
day
36­
47
months
0.456
 
g/
day
48­
59
months
0.492
 
g/
day
60­
71
months
0.563
 
g/
day
72­
84
months
Yes
Based
on
data
provided
by
FDA
in
Air
Quality
Criteria
for
Lead
Vol
I­
IV.
U.
S.
EPA
Environmental
Criteria
and
Assessment
Office,
Research
Triangle
Park,
NC.
EPA
600/
8­
83­
028a­
d
(
1986b)

Meat
(
No
fish
or
game
meat)
0.226
 
g/
day
0­
11
months
0.630
 
g/
day
12­
23
months
0.811
 
g/
day
24­
35
months
0.871
 
g/
day
36­
47
months
0.931
 
g/
day
48­
59
months
1.008
 
g/
day
60­
71
months
1.161
 
g/
day
72­
84
months
Yes
Based
on
data
provided
by
FDA
in
Air
Quality
Criteria
for
Lead
Vol
I­
IV.
U.
S.
EPA
Environmental
Criteria
and
Assessment
Office,
Research
Triangle
Park,
NC.
EPA
600/
8­
83­
028a­
d
(
1986b)

Other
Foods
(
No
fish
or
game
meat)
3.578
 
g/
day
0­
11
months
3.506
 
g/
day
12­
23
months
3.990
 
g/
day
24­
35
months
3.765
 
g/
day
36­
47
months
3.545
 
g/
day
48­
59
months
3.784
 
g/
day
60­
71
months
4.215
 
g/
day
72­
84
months
Yes
Based
on
data
provided
by
FDA
in
Air
Quality
Criteria
for
Lead
Vol
I­
IV.
U.
S.
EPA
Environmental
Criteria
and
Assessment
Office,
Research
Triangle
Park,
NC.
EPA
600/
8­
83­
028a­
d
(
1986b)

Lead
Absorption
Factor
Food
0.5
Yes
Based
on
values
reported
in
the
Review
of
the
National
Ambient
Air
Quality
Standards
for
Lead:
Exposure
Analysis
Methodology
and
Validation;
Report
No.
EPA­
450/
2­
89/
011;

U.
S.
EPA
Office
of
Air
Quality
Planning
and
Standards,
Research
Triangle
Park,
NC
(
1989d)

Air
32%
Yes
Water
0.5
Yes
Soil
0.3
Yes
Dust
0.3
Yes
Biokinetic
Parameters
IEUBK
default
values
and
equations
were
used
for
all
biokinetic
parameters
(
these
cannot
be
changed
by
the
user).
The
complete
list
of
IEUBK
biokinetic
parameters
is
listed
in
Appendix
L
and
in
the
Technical
Support
Document:
Parameters
and
Equations
Used
in
the
IEUBK
Model
for
Lead
in
Children.
U.
S.
EPA,
EPA
540­
R­
94­
040,
(
1995)

Age
Fish
Introduced
in
Infant
Diet
9
months
N/
A
Literature
on
dietary
guidelines
for
children
from
various
childcare
organizations,

including
the
National
Network
for
Child
Care
Source:
U.
S.
EPA
analysis.
14­
11
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
c.
&
M
discharges
EPA
used
the
IEUBK
model
in
this
analysis
to
estimate
the
effect
of
lead­
contaminated
fish
consumption
on
children s
PbB
concentrations.
The
Agency
first
calculated
lead
concentration
in
fish
tissue
corresponding
to
each
reach
affected
by
MP&
M
discharges
to
pro
vide
inputs
to
the
IEUB
K
m
ode
l.
mod
el
uses
the
specified
fish
tissue
conc
entratio
ns
in
conjunc
tion
with
fish
ingestion
rates
and
bioava
ilability
factors
to
de
termine
the
dose
o
f
lead
absorbed
by
the
b
ody.
his
do
se
is
then
u
sed
to
predict
the
GM
PbB
concentration
for
children
associated
with
each
reach
affected
by
lead
discharges
from
the
MP&
M
facilities.

EP
A
used
the
IEU
BK
mod
el
to
predict
the
ba
seline
and
po
st­
compliance
PbB
distributions
for
children
that
con
sume
fish
from
reach
es
affecte
d
by
lead
discharges
from
MP&
M
facilities.
he
difference
betwe
en
the
estimated
baseline
and
postcom
plianc
e
Pb
B
d
istribution
is
the
basis
for
the
analysis
of
b
enefits
to
c
hildren
from
the
M
P&
M
regulation.

14.2.2
Relationship
Between
PbB
Levels
and
IQ
A
dose­
response
relationship
between
PbB
and
IQ
decrements
determined
by
Schwartz
(
1994)
suggests
that
a
decrease
of
0.25
IQ
points
can
be
expected
for
every
1
 
g/
dL
increase
in
PbB
(
Schwartz,
1994).
p­
value
(<
0.0001)
indicates
that
this
relationship
is
highly
significant.

EPA
multiplied
the
0.25
IQ
po
ints
lost
per
 
g/
dL
increase
in
PbB
by
the
average
increase
in
PbB
level
for
children
and
by
the
number
of
exposed
children
to
obtain
the
total
change
in
number
of
IQ
points
for
the
population.
PbB
level
modeled
in
this
analysis
is
a
GM,
not
the
arithmetic
mean
used
by
Schwartz
(
1993).
To
adjust
for
this
difference,
equation
14.1
uses
a
ratio
between
the
arithmetic
mean
and
the
GM
of
a
logno
rm
ally­
d
istributed
random
variable.
ratio
between
the
expe
cted
v
alue
(
m
ean)
o
f
the
distribution
and
the
GM
is
1.11
7
for
the
assum
ed
G
SD
of
children's
Pb
B
lev
els
(
1.6).

The
total
avoided
loss
of
IQ
p
oints
for
each
gro
up
is
estimated
as:

(
14.1)

where:

(
Pop)
k
=
the
number
of
children
(
up
to
age
seven)
in
anglers 
families
in
the
vicinity
of
a
given
MP
&
M
reach;
and
GM
k
=
the
GM
of
the
PbB
distribution
in
the
population
of
children.

As
shown
in
equation
14.1,
the
population
of
children
up
to
age
seven
is
divided
by
seven
to
avoid
doub
le­
counting.
The
IEUB
K
mo
del
calculates
the
GM
of
the
PbB
distribution
in
the
population
of
children
born
today,
assuming
a
continuous
exposure
pattern
for
children
from
birth
through
the
seventh
birthday.
suming
that
children
are
evenly
distributed
by
age,

this
division
adjusts
this
equation
to
apply
only
to
children
age
0­
1.
ng
by
seven
undercounts
overall
benefits.
dren
from
age
1
to
7
are
not
accounted
for
in
the
base
year
of
the
analysis,
although
they
are
presumably
affected
by
the
lead
exp
osure
,
beca
use
the
IEU
BK
mod
el
assum
es
a
co
ntinuous
exp
osure
pattern
for
child
ren
from
birth
throug
h
the
sev
enth
birthd
ay.

14.2.3
e
Available
economic
research
provid
es
little
emp
irical
data
on
so
ciety's
overall
W
TP
to
avo
id
a
decrea
se
in
an
infant's
IQ.

This
analysis
uses
research
that
monetizes
a
subset
of
effects
associated
with
decreased
IQ.
These
effects
represent
only
some
compo
nents
of
society's
W
TP
to
avoid
IQ
decreases,
and
underestimate
society s
WT
P
when
emp
loyed
alone.

purpo
se
of
this
analysis,
these
effects
are
the
only
ones
available
at
this
time
to
app
roximate
the
W
TP
to
avoid
IQ
decrem
ents.

Rec
ent
stud
ies
pro
vide
c
oncrete
ev
idenc
e
of
lon
g­
term
e
ffects
from
childhood
lead
e
xpo
sure
(
S
chwa
rtz,
19
94)
.
nalysis
assumes
a
permanent
loss
of
IQ
points
based
on
PbB
levels
estimated
for
children
up
to
age
seven,
and
considers
two
con
sequ
ence
s
of
this
IQ
decr
eme
nt:
Estimating
changes
in
the
PbB
level
in
exposed
children
from
reduced
MP
Value
of
Children's
Intelligenc
 
the
decreased
present
value
of
the
infant s
expected
lifetime
earnings,
and
 
the
increased
educational
resources
expended
for
an
infant
who
becomes
mentally
handicapped
or
needs
compensatory
education
as
a
consequence
of
lead
exposure.
The
T
T
The
The
average
The
As
DividiChil
For
the
This
a
14­
12
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
a.
Estimating
the
effect
of
IQ
on
earnings
Reduced
IQ
has
direct
and
indirect
effects
on
earnings.
This
analysis
models
the
overall
impact
from
a
one­
point
reduction
in
IQ
as
the
sum
of
these
direct
and
indirect
effects
on
lifetime
earnings.
EPA
used
the
most
recent
estimates
of
the
effects
of
IQ
9
on
earnings
based
on
Salkever
(
1995).
Salkever
provided
updated
estimates
of
the
direct
and
indirect
effects
of
IQ
loss
on
earnings,
using
the
most
recent
available
data
set,
the
National
Longitudinal
Survey
of
Youth
(
NLSY).
Salkever
used
regression
analysis
techniques
to
estimate
direct
and
indirect
effects
of
IQ
on
earnings.
Three
different
relationships
are
estimated
separately
for
male
and
female
respondents:

 
a
least­
squares
regression
of
highest
grade
on
IQ
test
scores;

 
a
probit
regression
of
a
0­
1
indicator
of
positive
earnings
on
highest
grade
and
IQ
test
scores;

 
a
least­
squares
regression,
for
persons
with
positive
earnings,
of
the
logarithm
of
earnings
on
highest
grade
and
IQ
test
scores.

Other
variables
were
included
in
each
regression
to
control
for
effects
of
family
background
(
parents 
education
and
income),

the
age
of
the
respondent,
ethnic
group,
and
residence
location
(
urban
U.
S.,
non­
urban
U.
S.,
south
versus
non­
south).

Based
on
the
regression
results,
Salkever
estimated
the
effects
of
IQ
on
earnings
as
the
sum
of
direct
and
indirect
effects:

 
The
direct
effect
is
the
sum
of
effects
of
IQ
test
scores
on
employment
and
earnings
for
employed
persons,
holding
the
years
of
schooling
constant.

 
The
indirect
effect
is
the
sum
of
effects
of
IQ
test
scores
on
years
of
schooling
attained,
and
the
subsequent
effect
of
years
of
schooling
on
the
probability
of
employment
and
on
earnings
for
employed
persons.

The
analysis
found
that
percentage
effects
of
lead
exposure
are
greater
for
females
than
for
males.
The
total
estimated
effect
of
the
loss
of
an
IQ
point
on
earnings,
based
on
the
Salkever
study,
is
an
earnings
reduction
of
1.93
percent
for
men
and
3.22
percent
for
women.
The
total
effect
of
the
loss
of
an
IQ
point
on
earnings
also
includes
non­
IQ
effects
on
schooling
(
e.
g.,

behavioral
problems).

b.
Valuing
foregone
earnings
EPA
monetized
IQ
loss
effects
by
combining
the
percent
earnings
loss
estimate
with
an
estimate
of
the
present
value
of
expected
lifetime
earnings.
EPA
used
the
1992
data
on
money
income
for
the
U.
S.
population
(
U.
S.
Department
of
Commerce,
1993)
to
calculate
the
mean
present
value
of
lifetime
earnings
of
a
person
born
today.
The
data
included
earnings
for
employed
persons
and
employment
rates
as
a
function
of
educational
attainment,
age,
and
gender.
The
following
assumptions
were
used
to
calculate
the
mean
present
value
of
lifetime
earnings
of
a
person
born
today:

 
The
distribution
of
earnings
for
employed
persons
and
labor
force
participation
rates
remains
constant
over
time.

 
A
person
earns
income
from
age
18
through
age
67.

 
Real
wages
grow
one
percent
per
year.

 
Future
earnings
are
discounted
at
a
three
percent
annual
rate.

The
money
income
data
(
U.
S.
Department
of
Commerce,
1993)
form
the
best
available
basis
for
projecting
lifetime
earnings,

but
involve
some
uncertainties.
Labor
force
participation
rates
of
women,
the
elderly,
and
other
groups
will
likely
continue
to
change.
Currently,
men
tend
to
earn
more
than
women
due
to
higher
wage
rates
and
higher
labor
force
participation.

Expected
lifetime
earnings
increase
with
education
for
both
men
and
women.
Real
earnings
of
women
will
probably
continue
to
rise
relative
to
real
earnings
of
men.
Educational
attainment
has
risen
over
time
and
may
continue
to
rise.
Unpredictable
9
EPA
did
not
incorporate
earlier
studies
of
the
effects
of
IQ
on
earnings
in
this
analysis
because
the
Salkever
study
is
more
complete
in
capturing
the
various
pathways
through
which
IQ
affects
earnings,
such
as
the
indirect
effect
of
IQ
on
earnings
via
its
effect
on
educational
attainment.
Also,
other
studies
are
much
older.
The
IQ/
earning
effect
is
likely
to
be
higher
during
the
high
tech
boom
in
the
last
decade.

14­
13
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
fluctuations
in
the
economy's
growth
rate
will
probably
affect
labor
force
participation
rates
and
real
wage
growth
for
all
groups.
Medical
advances
that
increase
life
expectancy
will
probably
increase
lifetime
earnings.

Although
earnings
data
alone
form
an
incomplete
measure
of
an
individual's
value
to
society,
this
analysis
does
not
account
for
those
individuals
who
do
not
participate
in
the
labor
force
at
all
throughout
their
working
years
and
whose
productive
services
are
not
measured
by
wage
rates.
The
largest
group
in
this
population
are
those
who
remain
at
home
doing
housework
and
child
rearing.
Volunteer
work
also
contributes
significantly
to
social
welfare,
and
volunteerism
rates
tend
to
increase
with
educational
attainment
and
income.
Assuming
that
the
opportunity
cost
of
non­
wage­
compensated
work
equals
the
average
wage
earned
by
persons
of
the
same
sex,
age,
and
education,
the
average
lifetime
earnings
estimates
would
be
significantly
higher.
Recalculating
the
tables
using
full
employment
rates
for
all
age,
sex,
and
education
groups
would
provide
higher
lifetime
earnings
estimates.
To
be
conservative,
this
analysis
considered
only
the
value
of
lost
wages
and
does
not
include
the
opportunity
cost
of
non­
wage­
compensated
work.

The
adjusted
value
of
expected
lifetime
earnings
equals
the
present
value
for
an
individual
entering
the
labor
force
at
age
18
and
working
until
age
67.
Given
a
three
percent
social
discount
rate,
the
other
assumptions
mentioned,
and
current
survival
10
probabilities,
the
present
value
of
lifetime
earnings
of
a
person
born
today
in
the
U.
S.
would
be
$
448,957
(
2001$).

c.
Valuing
costs
of
education
The
increase
in
lifetime
earnings
from
additional
education
equals
the
gross
return
on
education.
The
cost
of
education
is
subtracted
from
the
gross
return
to
obtain
the
net
increase
in
earnings
from
additional
education.
The
cost
of
education
has
two
components:
the
direct
cost
of
the
education,
and
the
opportunity
cost
of
lost
income
during
the
education.
The
marginal
cost
of
education
used
in
this
analysis
was
assumed
to
be
$
8,898
(
2001$)
per
year.
This
figure
was
derived
from
the
U.
S.
Department
of
Education's
reported
($
6,961)
average
per­
student
annual
expenditure
(
current
plus
capital
11
expenditures)
in
public
primary
and
secondary
schools
in
1995­
96
(
U.
S.
Department
of
Education,
1998).
EPA
adjusted
this
value
to
2001
dollars
based
on
CPI
for
education.

Salkever s
study
found
the
estimated
effect
of
IQ
on
educational
attainment
to
be
0.1007
years
per
IQ
point.
The
estimated
cost
of
an
additional
0.1007
years
of
education
per
IQ
point
is
$
896
(
i.
e.,
0.1007
×
$
8,898).
This
marginal
cost
was
discounted
to
the
time
the
exposure
and
damage
is
modeled
to
occur
(
age
zero)
because
this
cost
is
incurred
after
the
completion
of
formal
education.
The
average
level
of
educational
attainment
in
the
population
over
age
25
is
12.9
years
(
U.
S.

Department
of
Education,
1993).
The
marginal
educational
cost
was
therefore
assumed
to
occur
at
age
19,
resulting
in
a
discounted
present
value
cost
of
$
511
(
2001$).

The
other
component
of
the
cost
of
education
is
the
opportunity
cost
of
lost
income
while
in
school.
Income
loss
is
frequently
cited
as
a
major
factor
in
the
decision
to
terminate
education,
and
must
be
subtracted
from
the
gross
returns
to
education.
An
estimate
of
the
lost
income
was
derived
assuming
that
people
in
school
are
employed
part­
time
but
that
people
out
of
school
are
employed
full­
time.
The
opportunity
cost
of
lost
income
is
the
difference
between
full­
time
and
part­
time
earnings.
The
value
of
lost
income
associated
with
being
in
school
an
additional
0.1007
years
is
$
746
(
2001$)
discounted
to
age
zero.

d.
Estimating
the
total
effect
of
IQ
on
earnings
Combining
the
value
of
lifetime
earnings
($
448,957)
with
the
estimate
of
percent
wage
loss
per
IQ
point
yielded
$
10,675
per
IQ
point.
Subtracting
the
education
and
opportunity
costs
reduced
this
value
to
$
9,419
per
IQ
point
(
2001$).

14.2.4
Value
of
Additional
Educational
Resources
Children
with
IQs
less
than
70
and
whose
PbB
is
greater
than
20
 
g/
dL
will
require
additional
educational
resources
including
an
educational
program
tailored
to
the
mentally
handicapped.
Some
children
whose
PbB
is
greater
than
20
 
g/
dL
will
need
additional
instruction
while
attending
school
later
in
life.
The
following
sections
describe
approaches
used
to
quantify
the
number
of
children
with
IQs
less
than
70
and
to
estimate
increased
educational
costs
resulting
from
lead
exposure.

10
Assuming
a
seven
percent
social
discount
rate,
the
present
value
of
lifetime
earnings
of
a
person
born
today
in
the
U.
S.
would
be
$
101,247
(
2001$).
Appendix
M
presents
a
sensitivity
analysis
with
respect
to
the
value
of
an
IQ
point.

11
In
comparison,
the
average
annual
cost
of
tuition,
fees,
room,
and
board
for
a
four­
year
public
undergraduate
institution
was
$
8,655
(
2001$)
for
the
year
2000­
2001
(
U.
S.
Department
of
Education,
2001).

14­
14
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
a.
Children
with
IQs
less
than
70
 
Quantifying
the
number
of
children
with
IQs
less
than
70
Increases
in
the
mean
PbB
levels
of
children
results
in
an
increased
incidence
of
children
with
very
low
IQ
scores.

are
normalized
to
have
a
mean
of
100
and
a
standard
d
eviation
of
15.
andard
deviations
below
the
mean,
and
is
generally
regarded
as
the
point
below
which
children
require
significant
special
compensatory
education
tailored
to
the
mentally
handicapped.

The
relationship
presented
here
for
estimating
changes
in
the
incidence
of
IQs
less
than
70
used
the
most
current
IQ
point
decrement
function
provided
by
Schwartz
(
1993).
It
assumed
that,
for
a
baseline
children s
PbB
distribution
(
defined
by
GM
and
GSD
),
the
population
also
has
a
normalized
IQ
point
distribution
with
a
mean
of
100
and
a
standard
deviation
of
15.

proportion
of
the
population
expected
to
have
IQs
less
than
70
was
determined
from
the
standard
normal
distribution
function
for
this
baseline
condition:

(
14.2)

where:

P(
IQ
<
70)
=
probability
of
IQ
scores
less
than
70
z
=
stand
ard
normal
variate
(
i.
e.,
the
numbe
r
of
stand
ard
d
eviations);
compu
ted
for
an
IQ
score
of
70
,
with
mean
IQ
score
of
10
0
and
stand
ard
de
viation
of
15
as:

(
14.3)

 
(
z)
=
standard
normal
distribution
function:

(
14.4)

The
integral
in
the
standard
normal
distribution
function
does
not
have
a
closed
form
solution.
 
(
z)
are
usually
obtained
using
software
with
basic
statistical
functions
or
from
tables
typically
provided
in
statistics
texts.
olution
for
 
(
z)
where
z
=
­
2
is
0.02275.
is,
for
the
normalized
IQ
score
distribution
with
a
mean
of
100
and
standard
deviation
of
15,
approximately
2.3
percent
of
children
are
expected
to
have
IQ
scores
below
70.

EP
A
made
two
ke
y
assum
ptions
to
relate
chang
es
in
the
p
roportion
of
child
ren
with
I
Q
sc
ores
b
elow
70
to
chang
es
in
pop
ulation
mean
P
bB
levels:

1.
The
mean
IQ
score
will
change
a
s
a
result
of
changes
in
the
me
an
Pb
B
level
as:

 
Mea
n
IQ
=
­
0.25
x
 
Mean
PbB
(
14.5)

where:

 
Mea
n
IQ
=
the
change
in
the
mean
IQ
score
between
the
baseline
and
post­
compliance
scenarios,
and
 
Mean
PbB
=
the
change
in
the
m
ean
Pb
B
level
b
etween
the
two
sc
enarios.

This
relationship
relies
on
Schwartz 
estimate
(
1993)
of
a
decrease
of
0.25
IQ
po
ints
for
each
 
g/
dL
increase
in
PbB
.

The
mean
PbB
level
referred
to
here
is
the
arithmetic
mean
(
or
expected
value)
for
the
distribution,
obtained
as
described
previously
from
the
GM
and
GSD.
IQ
scores
An
IQ
score
of
70
is
two
st
The
Values
for
The
s
That
2.
The
standard
deviation
for
the
IQ
distribution
is
15
for
both
the
baseline
and
the
post­
compliance
scenario.

14­
15
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Using
these
assumptions,
EPA
determined
the
change
in
the
probability
of
children
having
IQ
less
than
70
for
a
given
change
in
mean
PbB
from:

(
14.6)

where:

 
(
zBl)
=
baseline
standard
normal
distribution
function,
and
 
(
zPc)
=
post­
compliance
standard
normal
distribution
function.

(
14.7)

EPA
then
converted
a
given
change
in
the
mean
PbB
level
between
the
baseline
and
post­
compliance
scenarios
into
a
measure
of
IQ
.
procedure
ab
ove
yielded
an
estim
ate
of
the
perc
ent
of
the
pop
ulation
w
ith
IQs
less
than
7
0.
A
m
ultiplied
this
percent
by
the
population
of
exposed
children
to
estimate
the
increased
incidence
of
children
with
low
IQs.
he
IQ
point
loss
eq
uation
,
EP
A
ap
plied
the
results
of
this
functio
n
to
ch
ildren
a
ge
0­
7
and
d
ivided
by
seve
n
to
av
oid
d
oub
le
cou
nting.

(
See
discussion
un
der
e
quation
14
.1.)

This
procedure
quantified
only
the
change
in
the
number
of
children
who
pass
below
the
70
point
IQ
threshold.
EPA
quantified
other
changes
in
children's
IQ
using
the
IQ
point
loss
function
(
Equation
14.1)
described
previously.

these
two
endpoints
additively
does
not
result
in
double
counting,
because
the
value
associated
with
the
IQ
point
loss
function
is
the
change
in
individual
lifetime
earnings,
while
the
value
associated
with
IQs
less
than
70
is
the
increased
educational
costs
for
the
individual,
as
discussed
below.

 
Valuing
educational
costs
EPA
estimated
the
number
of
avoided
cases
of
children
with
IQs
less
than
70.
ensatory
education
expenses
will
no
lo
ng
er
be
incu
rr
ed
fo
r
th
es
e
c
as
es
.
K
ak
alik
et
al.
(
1
98
1)
,
usin
g
d
ata
fro
m
a
stu
dy
pr
ep
ar
ed
fo
r
th
e
D
ep
ar
tm
en
t
o
f
E
du
ca
tio
n's
Office
of
Special
Education
Programs,
estimated
part­
time
special
education
costs
for
children
who
remained
in
regular
classrooms
at
$
3,064
extra
per
child
per
year
in
1978.
Adjusting
for
changes
in
the
GDP
price
deflator
yielded
an
estimate
of
$
6
,959
per
child
in
2001
dollars.
A
used
the
inc
reme
ntal
estimate
of
the
cost
of
part­
time
special
education
to
estima
te
the
annual
cost
per
child
needing
special
education
as
a
result
of
lead
impacts
on
mental
development.
EPA
assumed
that
com
pensatory
education
b
egins
at
age
seven
and
continues
thro
ugh
ag
e
18
(
grad
es
one
throu
gh
twelv
e).
Discounting
future
expenses
a
t
a
rate
o
f
three
p
ercen
t
yielded
an
exp
ected
prese
nt
value
cost
o
f
app
roxim
ately
$
5
8,01
2
pe
r
child
(
2
001
$).
his
discounting
underestimates
the
cost
because
Kakalik
et
al.
measured
the
increased
cost
to
educate
children
attending
regular
school
rather
than
a
special
education
program.
The
costs
of
attending
a
special
education
program
are
likely
to
be
much
higher
than
those
associated
with
regular
schooling.
ddition,
some
compensatory
education
programs
begin
earlier
than
at
age
seven.
For
example,
some
states,
such
as
Connecticut
and
Rhode
Island,
offer
Head
Start
programs
to
disadvantaged
children
beginning
at
age
three.

b.
Children
with
PbB
levels
greater
than
20
 
g/
dL
 
Quantifying
the
number
of
children
with
PbB
levels
greater
than
20
 
g/
dL
EPA
obtained
the
percentage
of
children
with
PbB
levels
greater
than
20
 
g/
dL
directly
from
the
estimated
distribution
of
PbB
levels
for
a
given
location
(
IEUBK
).
s
percentage
by
the
number
of
exposed
children
in
the
vicinity
of
a
given
MP&
M
reach
to
estimate
the
number
of
children
with
PbB
levels
greater
than
20
 
g/
dL.
12
 
Estimating
and
valuing
compensatory
education
for
children
with
PbB
levels
greater
than
20
 
g/
dL
EPA
assumed
that
20
percent
of
the
children
with
PbB
levels
greater
than
20
 
g/
dL
would
require
and
receive
compensatory
education
for
three
years.
tional
expend
itures
are
incurred
b
y
those
children.
hese
TheEP
As
in
t
Treating
Comp
EP
T
In
a
EPA
then
multiplied
thi
After
this
time,
no
further
educa
T
12
See
Section
13.1.1
for
detail
on
estimating
the
affected
population.
The
percentage
of
children
in
the
affected
population
is
estimated
based
on
the
Census
data.

14­
16
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
assumptions
are
conservative.
Many
studies
show
adverse
cognitive
effects
of
PbB
levels
at
15
 
g/
dL
(
CDC,
1991b).
Some
studies
of
the
persistence
of
cognitive
effects
indicate
that
the
effects
often
last
longer
than
three
years.

The
Kakalik
et
al.
(
1981)
estimate
of
part­
time
special
education
costs
for
children
who
remained
in
regular
classrooms
can
be
used
to
estimate
the
cost
of
compensatory
education
for
children
suffering
low­
level
cognitive
damage.
As
indicated
above,
the
part­
time
special
education
cost
per
child
is
$
6,959
per
year
in
2001
dollars.
The
Agency
assumes
that
compensatory
education
starts
at
age
7
and
continues
for
3
years.
Discounting
future
costs
at
a
rate
of
3
percent
annually
to
account
for
the
age
at
which
costs
are
incurred
(
i.
e.,
age
7
through
9)
yields
a
present
value
estimate
of
$
16,485
in
2001
dollars.

14.2.5
Changes
in
Neonatal
Mortality
a.
Quantifying
the
relationship
between
maternal
PbB
levels
and
neonatal
mortality
U.
S.
EPA
(
1990)
cites
a
number
of
studies
linking
fetal
exposure
to
lead
(
via
in
utero
exposure
from
maternal
lead
intake)
to
several
adverse
health
effects.
These
effects
include
decreased
gestational
age
(
i.
e.,
premature
birth),
reduced
birth
weight,

late
fetal
death,
and
increases
in
infant
mortality.

The
CDC
(
CDC,
1991a)
developed
a
method
to
estimate
changes
in
infant
mortality
due
to
changes
in
maternal
PbB
levels
during
pregnancy.
The
analysis
linked
the
following
two
relationships:

 
gestational
age
as
a
function
of
maternal
PbB
(
Dietrich
et
al.,
1987),
and
 
infant
mortality
as
a
function
of
gestational
age.
This
is
performed
using
data
from
the
Linked
Birth
and
Infant
Death
Record
Project
from
the
National
Center
for
Health
Statistics
(
CDC,
1991a).

Combining
the
two
relationships
provided
a
decreased
risk
of
infant
mortality
of
10­
4
(
or
0.0001)
for
each
1
 
g/
dL
decrease
in
maternal
PbB
level
during
pregnancy.
EPA
used
this
relationship
for
its
analysis
of
maternal
PbB
levels
and
neonatal
mortality.

b.
Valuing
changes
in
neonatal
mortality
This
analysis
used
the
estimated
WTP
for
avoiding
a
mortality
event
to
estimate
the
monetary
benefit
associated
with
reducing
risks
of
neonatal
mortality.
This
analysis
uses
the
$
6.5
million
(
2001$)
estimate
of
the
value
of
a
statistical
life
saved
recommended
in
the
Guidelines
for
Preparing
Economic
Analysis
(
EPA,
2000a).
For
detail
on
valuing
reduced
mortality
risks
see
Section
13.2.1.

14.3
ADULT
HEALTH
BENEFITS
Lead
exposure
has
been
shown
to
have
adverse
effects
on
the
health
of
adults
as
well
as
children.
The
quantified
adult
health
effects
included
in
the
benefits
analysis
all
relate
to
lead s
effects
on
BP.
13
The
estimated
relationships
between
these
health
effects
and
lead
exposure
differ
between
men
and
women.
Quantified
health
effects
include
increased
incidence
of
hypertension
(
estimated
for
males
only),
initial
CHD,
strokes
(
initial
CBA
and
BI),
and
premature
mortality.
This
analysis
does
not
include
other
health
effects
associated
with
elevated
BP,
and
other
adult
health
effects
of
lead
including
neurobehavioral
and
possible
cancer
effects.

13
Citing
laboratory
studies
with
rodents,
U.
S.
EPA
(
1990)
also
presents
evidence
of
the
genotoxicity
and/
or
carcinogenicity
of
lead
compounds.
The
animal
toxicological
evidence
suggests
that
human
cancer
effects
are
possible,
but
dose­
response
relationships
are
not
currently
available.

14­
17
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Estimating
adult
health
benefits
from
reduced
exposure
to
lead
requires
analytic
steps
similar
to
those
used
in
estimating
children s
health
benefits.
These
steps
are:

 
estimate
in­
stream
lead
concentrations
in
the
reaches
affected
by
MP&
M
discharges;

 
estimate
baseline
and
post­
compliance
adult
dietary
lead
intake
via
fish
consumption.
The
analysis
of
adult
health
benefits
from
reduced
exposure
to
lead
via
contaminated
fish
uses
the
results
from
water
quality
modeling
efforts
described
in
Appendix
I;

 
estimate
changes
in
the
PbB
level
distribution
in
the
affected
adult
population;

 
estimate
changes
in
health
status
in
the
affected
population
of
adult
men,
and
the
monetary
value
of
health
benefits
from
reduced
lead
discharges
from
MP
&
M
facilities;
and
 
estimate
changes
in
health
status
in
the
affected
population
of
adult
women,
and
the
monetary
value
of
health
benefits
from
reduced
lead
discharges
from
MP&
M
facilities.

Figure
14.2
depicts
the
above
steps.
Table
14.3
summarizes
per­
case
costs
of
lead­
related
illnesses.

Table
14.3:
Per­
Case
Costs
of
Lead­
Related
Illnesses
Illness
Gender
Cost
per
Case
(
2001$)
Cost
Description
Hypertensiona
Male
$
1,141
The
cost
estimates
were
derived
by
taking
Krupnick
et
al. 
s
(
1989)
average
annual
per­
person
costs
of
hypertension.
$
using
the
CPI
for
Medical
Care.
Female
$
1,141
CHDa,
b
Male
$
76,347
The
costs
were
estimated
(
Wittels
et
al.,
1990)
for
three
CHDs
(
acute
myocardial
infarction,
uncomplicated
angina
pectoris,
and
unstable
angina
pectoris)
for
5
years
post­
diagnosis
using
a
three
percent
discount
rate.

service
was
multiplied
by
the
estimated
price
of
the
service
and
the
average
cost
for
the
three
CHD
types.
he
effect
of
elevated
PbB
on
CHD
incidence
rates
is
beyond
the
scope
of
this
analysis,
weighting
factors
were
not
used
to
account
for
the
different
probabilities
of
contracting
the
three
types
of
CHD.
adjusted
to
2001$
using
the
CPI
for
Medical
Care.
Female
$
76,347
Strokea
Male
$
335,135
The
cost
estimates
(
Taylor
et
al.,
1996)
represent
the
expected
lifetime
cost
of
a
stroke
for
males
and
females
age
45­
74,
including
the
present
discounted
value
of
the
stream
of
medical
expenditures
and
the
stream
of
lost
earnings.
t
the
study
used
a
five
percent
discount
rate.
did
not
adjust
this
value
to
reflect
a
3
percent
discount
rate
used
elsewhere
in
this
analysis.
lues
adjusted
to
2001$
using
the
CPI
for
Medical
Care.
Female
$
251,351
Low
Birth
Weightc
Female
$
89,503
The
cost
estimate
was
extrapolated
from
direct
costs
for
LBW
taken
from
Lewitt
et
al.,

using
a
three
percent
discount
rate
(
Lewitt
et
al.,
1995).
alue
includes
medical,
special
education,
and
grade
repetition
costs.
Value
adjusted
to
2001$
using
the
CPI
for
Medical
Care.

Death
­­
Any
Illnessd
Male
$
6.5
Value
taken
from
U.
S.
EPA s
Guidelines
for
Preparing
Economic
Analysis
(
2000a).
The
value
is
the
central
estimate
recommended
in
the
document
based
on
a
range
of
estimates
available
from
studies
measuring
the
value
of
a
statistical
life.

adjusted
to
2001$
using
the
CPI
for
All
Items.
Female
$
6.5
Value
adjusted
to
2001
The
probability
of
medical
Since
t
Value
Note
tha
EPA
Va
The
v
Million
Value
Million
a
Costs
were
taken
from
U.
S.
EPA,
1997b.

b
Extends
methodology
in
U.
S.
EPA,
1997b
to
discount
medical
costs
over
a
5
year
period.

c
Note
that
this
analysis
does
not
estimate
occurrence
of
low
birth
weight
cases,
due
to
data
limitations.
Cost
was
taken
from
U.
S.

EPA,
1999.

d
Value
taken
from
U.
S.
EPA,
2000a.

Source:
U.
S.
EPA
analysis.;
U.
S.
EPA
1997b;
U.
S.
EPA
1999,
U.
S.
EPA
2000a.

14­
18
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Figure
14.2
Assessing
Benefits
to
Adults
from
Reduced
Lead
Discharges
from
MP&
M
Facilities
Source:
U.
S.
EPA
analysis.

14­
19
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
14.3.1
Estimating
Changes
in
Adult
PbB
Distribution
Levels
a.
Estimating
values
of
PbB
concentrations
in
exposed
adults
EPA
adapted
the
methodology
described
in
the
Interim
Approach
to
Assessing
Risks
Associated
with
Adult
Exposure
to
Lead
in
Soil
(
hereafter,
Interim
Guidance)
to
estimate
changes
in
the
distribution
of
PbB
levels
in
exposed
adults
from
reduced
MP&
M
discharges
(
U.
S.
EPA,
1996a).
The
methodology
presented
in
the
Interim
Guidance
used
a
simplified
representation
of
lead
biokinetics
to
predict
quasi­
steady
state
PbB
concentrations
among
adults
who
have
relatively
steady
patterns
of
exposures
to
lead.
This
methodology
is
recommended
by
the
Technical
Review
Workgroup
(
TRW)
to
assess
the
effects
of
ingesting
lead­
contaminated
soil
on
PbB
levels
of
women
of
childbearing
age,
to
derive
risk­
based
remediation
goals
(
RBRG)
protective
of
the
developing
fetus
in
exposed
adult
women.
14
The
Interim
Guidance
describes
the
basic
algorithms
to
be
used
in
the
analysis
and
provides
a
set
of
default
parameters
that
can
be
used
in
cases
where
site­
specific
data
are
not
available.
The
TRW
points
out
that
this
methodology
is
an
interim
approach
recommended
for
use
pending
further
development
and
evaluation
of
integrated
exposure
biokinetic
models
for
adults.

The
dose­
response
relationship
recommended
in
the
Interim
Guidance
for
exposures
to
lead­
contaminated
soil
can
be
modified
to
analyze
PbB
levels
in
recreational
and
subsistence
anglers
exposed
to
lead­
contaminated
fish
tissue.
In
both
cases,
the
exposure
pathways
involve
ingestion.
The
Interim
Guidance
differs
from
this
analysis
mainly
in
the
medium
containing
lead
(
soil
versus
fish
tissue).
Substituting
ingestion
of
lead
in
fish
for
ingestion
of
lead
in
soil
yields
the
following
equation:

(
14.8)

where:

PbB
adult,
central
=
central
tendency
estimate
of
PbB
concentrations
(
 
g/
dL)
in
adults
exposed
to
lead
in
fish
at
a
concentration
of
PbW;

PbB
adult,
0
=
typical
PbB
concentration
(
 
g/
dL)
in
adults
in
the
absence
of
exposures
via
fish
consumption;

PbW
=
in­
stream
lead
co
ncentrations
(
 
g/
L);

BCF
=
bioconcentration
factor
of
lead
in
fish
tissue
(
L/
kg);

INF
=
average
daily
fish
consumption
(
g/
day);

AFF
=
absolute
gastrointestinal
absorption
fraction
for
ingested
lead
in
fish
tissue
(
dimensionless);

BKSF
=
biok
inetic
slop
e
facto
r
relating
(
quasi­
steady
sta
te)
incre
ases
in
typ
ical
ad
ult
Pb
B
c
oncentratio
ns
to
average
daily
lead
uptake
(
 
g/
dL
PbB
increase
per
mg/
day
lead
uptake);

EF
=
exposure
frequency
for
ingestion
of
contaminated
fish
(
days
of
exposure
during
the
averaging
period);

may
be
taken
as
days
per
year
for
continuing,
long­
term
exposure;

CF
=
conversion
factor
(
10
 
3
kg/
g);
and
AT
=
averaging
time,
the
total
period
during
which
fish
consumption
may
occur;
365
days/
year
for
continuing
long­
term
exposure.

Equation
14.8
is
recommended
for
females
aged
17
to
45
(
U.
S.
EPA,
1996a).
Studies
of
adult
males,
however,
provided
many
of
the
parameters
used
in
the
Interim
Guidance.
For
example,
the
biokinetic
slope
factor
(
BKSF)
relating
increase
in
typical
adult
blood
concentrations
to
average
daily
lead
uptake
was
developed
on
data
reported
by
Pocock
et
al
(
1983).
These
data
characterize
the
relationship
between
tap
water
lead
concentrations
and
blood
lead
concentrations
for
a
sample
of
adult
males.
15
Thus,
EPA
judged
that
this
model
can
be
applicable
to
all
adults.
Table
14.4
summarizes
values
for
the
model
parameters.

14
EPA s
TRW
for
lead
began
considering
methodologies
to
evaluate
nonresidential
adult
exposure
to
lead
in
1994.
A
TRW
committee
on
adult
lead
risk
assessment
formed
in
January
1996
to
develop
a
generic
methodology
that
could
be
adapted
for
use
in
site­
specific
assessments
of
adult
health
risks.

15
For
detail,
see
p.
A­
10,
Recommendations
of
the
Technical
Review
Workgroup
for
Lead
to
Assessing
Risks
Associated
with
Adult
Exposure
to
Lead
in
Soil
(
U.
S.
EPA,
1996a).

14­
20
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.4:
Summary
of
Parameter
Values
for
Estimating
PbB
Levels
in
Adults
Parameter
Unit
Value
Comment
a
PbBadult,
0
 
g/
dL
4.55­
3.45
Male
adult
PbB
levels
based
on
NHANES
III
Phase
2
(
U.
S.
EPA,
1991­

1994).
le
adult
PbB
levels
based
on
NHANES
III
Phase
2
(
U.
S.
EPA,
1996a).

BKSF
 
g/
dL
per
 
g/
day
0.4
Based
on
analysis
of
Pocock
et
al.
(
1983)
and
Sherlock
et
al.
(
1984)
data.

INF
g/
day
17.5
142
.4
Daily
fish
consumption;
lower
value
(
on
left)
for
recreational
anglers
and
higher
value
(
on
right)
for
subsistence
anglers.
Fish
consumption
rates
for
adults
are
taken
from
the
Methodology
for
Deriving
Ambient
Water
Quality
Criteria
for
the
Protection
of
Human
Health
(
EPA,
2000b).
Both
these
rates,
142.4
g/
day
for
adult
subsistence
anglers
and
17.5g/
day
for
adult
recreational
anglers,
are
used
for
the
specific
sub­
population
that
they
represent.
EPA
was
not
able
to
break
these
rates
down
by
gender
or
age
group
for
use
in
this
analysis.

EF
day/
yr
365
Days
per
year
for
continual
long­
term
exposure.

BCF
L/
kg
49
Bioconcentration
factor
of
lead
in
fish
tissue.

AFF
dimensionless
0.03
Absolute
gastrointestinal
absorption
fraction
for
ingested
lead
in
fish
tissue.
sed
on
Maddaloni
(
1998).
Fema
Ba
a
For
detailed
information
on
the
sources
of
the
parameters
and
uncertainties
associated
with
their
use,
see
U.
S.
EPA,
1996a.

Source:
U.
S.
EPA
analysis.

 
Typical
adult
PbB
concentrations
at
baseline
Previous
research
suggests
males
have
a
higher
background
PbB
level
(
U.
S.
EPA,
1996a).
This
analysis
uses
population­

specific
typical
concentrations
to
account
for
differences
in
background
lead
exposure
between
genders
and
between
two
socioeconomic
subgroups
considered
in
the
analysis
(
i.
e.,
recreational
and
subsistence
fishermen).
EPA
used
data
for
adult
males
and
females
from
NHANES
III
to
characterize
the
baseline
distribution
of
PbB
concentrations
in
the
relevant
sub­

populations
for
each
MP&
M
reach
and
affected
population
(
NHANESIII,
1991­
1994).
The
baseline
PbB
distribution
scenario
reflects
site­
specific
population
characteristics
because
baseline
PbB
levels
differ
across
ethnic,
income,
and
urban
status
groups.

 
Bioavailability
of
lead
from
fish
tissue
To
identify
lead
bioavailability
in
fish
tissue,
EPA
reviewed
lead
absorption
data
from
various
materials
reported
in
the
lead
toxicity
summary
document:
Draft
Toxicological
Profile
for
Lead
(
ATSDR,
1997).
EPA
also
reviewed
Measurement
of
Soil­
Borne
Lead
Bioavailability
in
Human
Adults,
and
Its
Application
to
Biokinetic
Modeling
(
Maddaloni,
1998)
and
consulted
with
the
study
author
(
March,
2000).
Numerous
studies
have
found
that
lead
ingested
with
food
is
absorbed
at
a
significantly
lower
rate
than
lead
ingested
after
fasting.
The
Interim
Approach
reports
this
dynamic
and
notes
that
"
the
bioavailability
of
ingested
soluble
lead
in
adults
varies
from
less
than
10
percent
when
ingested
with
a
meal
to
between
60
and
80
percent
when
ingested
after
a
fast"
(
U.
S.
EPA,
1996a).
TRW
uses
a
20
percent
lead
bioavailability
factor
for
soil.
This
factor
is
based
on
lead
consumption
interspersed
with
and
between
meals
throughout
the
day,
and
is
therefore
likely
to
overestimate
PbB
levels
in
adults
exposed
to
lead­
contaminated
fish.
In
the
absence
of
data
on
lead
incorporated
into
food,

however,
EPA
considered
this
to
be
the
most
appropriate
data
to
use
in
estimating
absorption.

In
the
most
recent
study
reviewed
for
this
analysis
(
Maddaloni,
1998),
non­
fasted
subjects
showed
a
mean
percent
absorption
of
2.52
with
a
range
of
0.2
to
5.2
percent
and
a
confidence
value
of
0.66.
The
male
and
female
study
subjects
had
normal
clinical
chemistry
parameters
and
were
between
21
and
40
years
of
age.
The
study
used
soil
as
the
dosing
vehicle.
Other
studies
have
used
water
as
the
dosing
vehicle,
but
soil
is
considered
to
be
more
similar
to
fish
consumption.

EPA
selected
an
absorption
value
of
3
percent
for
lead
ingested
in
fish
tissue,
based
on
Maddaloni s
results.
The
value
of
3
percent
provides
a
reasonable
estimate
for
most
adults.
This
analysis
does
not
address
individuals
who
may
have
higher
lead
absorption,
or
are
at
elevated
risk
due
to
lead
exposure.
These
individuals
include
pregnant
women,
who
have
higher
calcium
requirements
(
and
are
therefore
more
likely
to
be
calcium­
deficient),
people
with
poor
nutritional
status
(
including
iron
and
calcium
deficiencies),
and
individuals
with
other
metabolic
disorders.
By
evaluating
subsistence
and
recreational
anglers
at
proposal
and
for
final
rule
options
with
lead
benefits,
the
analysis
is
already
focusing
on
sub­
populations
at
higher
risk
than
14­
21
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
the
average
population.
To
maintain
an
approach
that
represents
likely
exposures,
intakes,
and
risks,
EPA
chose
not
to
consider
individuals
at
unusually
high
risk
within
an
already­
high
risk
sub­
population.

14.3.2
Male
Health
Benefits
This
section
describes
the
health
effects
of
reduced
lead
exposure
that
this
analysis
has
quantified
for
men;
the
next
section
prese
nts
a
similar
discussion
for
wom
en.

a.
Hypertension
 
Quantifying
the
relationship
between
PbB
levels
and
hypertension
Studies
have
linked
elevated
PbB
to
elevated
BP
in
adult
males,
especially
men
aged
40
to
59
(
Pirkle
et
al.,
1985).
Further
studies
have
d
emo
nstrated
a
do
se­
resp
onse
relation
ship
for
hype
rtensio
n
(
de
fined
a
s
diasto
lic
BP
abo
ve
90
mm
H
g
for
this
mod
el)
in
males
aged
20
to
7
4
(
Schw
artz,
1988
).

(
14.9)

where:

 
Pr(
HYP)
=
the
change
in
the
probability
of
hypertension,

e
=
base
of
the
natural
logarithm
(
2.76)

PbB1
=
PbB
level
in
the
baseline
scenario,
and
PbB2
=
PbB
level
in
the
post­
compliance
scenario.

 
Valuing
reductions
in
hypertension
Th
e
best
measure
o
f
the
social
costs
o
f
hyperte
nsion,
so
ciety's
W
TP
to
avo
id
the
cond
ition,
can
not
b
e
qua
ntified
witho
ut
basic
research
that
is
well
beyo
nd
the
scop
e
of
this
p
roject.
lly,
the
mea
sure
wo
uld
include
a
ll
the
med
ical
co
sts
assoc
iated
w
ith
treating
hypertension,
the
individual's
WT
P
to
avoid
the
worry
that
hypertension
could
lead
to
a
stroke
or
CH
D,
and
the
individual's
WTP
to
avoid
the
behavioral
changes
required
to
reduce
the
probability
that
hypertension
leads
to
a
stroke
or
CHD.

Th
is
analysis
use
d
recent
research
results
to
q
uantify
two
bene
fit
catego
ry
com
pon
ents:
me
dical
costs
and
lost
work
tim
e.

Krupnick
and
Cro
pper
(
1989
)
estimated
the
medical
costs
of
hypertension,
using
data
from
the
National
Medical
Care
Expenditure
Survey.
or
physician
care,
drugs,
and
hospitalization.
ion,

hypertensives
have
more
bed
disability
days
and
work­
loss
days
than
non­
hypertensives
of
comparable
age
and
sex.

and
Cropp
er
estimated
the
increase
in
work­
loss
days
at
0.8
per
year.
Valuing
this
estimate
at
the
estimated
mean
daily
wage
rate
and
adjusting
the
costs
to
2001
dollars
yields
an
estimate
of
the
annual
cost
of
each
case
of
hypertension
of
$
1,141.

The
benefits
estimate
in
this
analysis
likely
underestimates
the
true
social
benefit
of
avoiding
a
case
of
hypertension
for
several
reaso
ns:

 
It
doe
s
not
include
a
measure
of
the
value
of
pain,
suffering,
and
stress
associated
with
hype
rtension.

 
It
does
no
t
value
the
direct
costs
(
out­
of­
po
cket
expe
nses)
of
diet
and
b
ehavior
m
odification
(
e.
g.,
salt­
free
diets,

etc.).
hese
costs,
whic
h
are
typ
ical
for
severe
m
odifica
tions,
are
likely
to
be
significant.

 
This
ana
lysis
does
not
add
ress
the
loss
of
satisfaction
associated
with
the
d
iet
and
beha
vior
mod
ifications.

 
This
analysis
does
not
include
the
value
of
avoiding
side
effects
associated
with
the
medication
for
hypertension,

which
include
drowsiness,
nausea,
vomiting,
anemia,
impotence,
cancer,
and
depression.

 
The
analysis
does
not
includ
e
the
effects
of
the
disease
on
fam
ily
members.
This
relationship
is:

Idea
Medical
costs
include
expenditures
fIn
addit
Krupnick
T
14­
22
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
b.
Changes
in
CHD
 
Quantifying
the
relationship
between
PbB
and
BP
EPA
quantified
the
effect
of
changes
in
PbB
levels
on
changes
in
BP
to
predict
the
probability
of
both
hypertension
and
other
cardiova
scular
illnesses,
such
as
CH
D,
strokes,
and
prema
ture
mortality.
iovascular
illnesses
include
P
bB
as
a
risk
factor
(
Shurtleff,
1974;
McGee
and
Gordon,
1976;
PPR
G,
1978).
esults
of
a
meta­
analysis
of
several
studies,
Schwartz
(
1992)
estimated
a
relationship
between
a
change
in
BP
associated
with
a
decrease
in
PbB
from
10
 
g/
dL
to
5
 
g/
dL.
the
coefficient
reported
by
Schwartz
to
relate
BP
to
Pb
B
for
men:

(
14.10)

where:

 
DBPmen
=
the
change
in
men's
diastolic
BP
expected
from
a
change
in
PbB;

PbB1
=
PbB
level
in
the
baseline
scenario
(
in
 
g/
dL);
and
PbB2
=
PbB
level
in
the
post­
compliance
scenario
(
in
 
g/
dL).

EPA
used
this
PbB
to
BP
relationship
to
estimate
the
incidence
of
initial
CHD,
strokes
(
BI
and
initial
CBA),
and
prem
ature
mortality
in
men.

 
Quantif
ying
th
e
re
la
tionsh
ip
be
tw
ee
n
BP
and
CH
D
This
analysis
used
estimated
BP
changes
to
predict
the
increased
probability
of
initial
CHD
and
stroke
occurrence
(
U.
S.
EPA,

198
7).
BP
also
increases
the
pr
obab
ility
of
CHD
a
nd
stroke
rec
urrence,
but
E
PA
d
id
not
quan
tify
these
relationships
in
this
analysis.
An
equation
with
different
coefficients
for
each
of
three
age
groups
can
predict
first­
time
CHD
events
in
men.
A
1978
study
by
the
PPRG
supplied
information
for
men
between
ages
40
and
59.
d
a
mu
ltivariate
model
(
controlling
for
smoking
and
serum
cholesterol)
relating
the
probability
of
CHD
to
BP.

data
from
five
different
epidemiological
studies.
The
equation
for
the
change
in
10­
year
probability
of
a
first­
time
occurrence
of
CH
D
related
to
an
increase
in
B
P
is:

(
14.11)

where:

 
Pr(
CH
D40­
59)
=
the
change
in
10­
year
probability
of
an
occurrence
of
a
CHD
event
for
men
between
ages
40
and
59;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
40
to
59
is
81.8
and
80.0,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

Inform
ation
p
resented
in
Shurtleff
(
1974
)
helpe
d
de
fine
the
relationship
between
BP
and
first­
time
CH
D
in
o
lder
m
en.
his
study
used
data
from
the
Framingham
Study
(
McGee
and
Gordo
n,
1976)
to
estimate
univariate
relationships
between
BP
and
a
variety
of
health
effects,
by
se
x
and
for
three
age
ranges:
4
5
to
5
4,
55
to
64
,
and
6
5
to
7
4
years.
e
study
p
erform
ed
sing
le
compo
site
analyses
for
ages
45
to
74
for
each
sex.
For
every
equation,
t­
statistics
on
the
BP
variable
are
significant
at
the
99th
percent
confidence
interval.
icted
first­
time
CHD
related
to
an
increase
in
BP
for
men
aged
60
to
64
from
the
following
equation:

(
14.12)

where:

 
Pr(
CHD60­
64)
=
the
change
in
2­
year
probability
of
occurrence
of
a
CHD
event
for
men
aged
60
to
64;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
60
to
64
is
79.5
and
77.8,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.
Several
card
Based
on
the
r
The
following
equation
uses
Increased
PPRG
use
The
model
used
T
Th
EPA
pred
14­
23
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
The
following
equation
uses
data
from
Shurtleff
(
1974)
to
predict
the
probability
of
first­
time
CHD
related
to
an
increase
in
BP
for
men
aged
65
to
74:

(
14.13)

where:

 
Pr(
CHD65­
74)
=
the
change
in
2­
year
probability
of
occurrence
of
a
CHD
event
for
men
aged
65
to
74;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
65
to
74
is
79.5
and
76.4,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

EPA
used
the
above
equations
to
estimate
the
number
of
CHD
events
avoided
in
a
given
year
due
to
water
quality
improvements
from
reduced
MP&
M
lead
discharges.
The
resulting
CHD
incidence
estimates
include
both
fatal
and
non­
fatal
events.
Only
the
non­
fatal
CHD
events
are
considered
here
because
mortality
benefits
are
estimated
independently
in
this
analysis
(
see
Section
14.3.2.
d,
below).
Shurtleff
(
1974)
reported
that
two­
thirds
of
all
CHD
events
were
non­
fatal.
This
factor
was
therefore
applied
to
the
estimate
of
avoided
CHD
events
due
to
reductions
in
PbB
and
BP
for
each
age
category.

 
Valuing
reductions
in
CHD
events
EPA
first
estimated
the
number
of
CHD
events
avoided
each
year
by
multiplying
the
number
of
exposed
recreational
and
subsistence
anglers
in
the
relevant
age
group
by
the
change
in
annual
probability
of
a
CHD
event.
Changes
in
annual
probability
of
CHD
events
for
different
age
groups
are
calculated
by
dividing
the
change
in
probability
over
ten­
and
two­
year
periods
by
the
relevant
number
of
years.

EPA
then
used
the
central
tendency
estimate
of
the
COI
associated
with
pollution­
related
CHD
to
estimate
the
benefits
of
avoiding
an
initial
CHD
event.
The
cost
estimates
(
Wittels
et
al.,
1990)
represent
the
weighted
medical
costs
of
three
separate
CHD
s
(
acute
myocardial
infarction,
uncomplicated
angina
pectoris,
unstable
angina
pectoris),
experienced
within
five
years
of
diagnosis.
EPA
estimated
the
costs
by
multiplying
the
probability
of
a
medical
test
or
treatment
(
within
five
years
of
the
initial
CHD
event)
by
the
estimated
price
of
the
test
or
treatment.
16
The
estimated
cost
for
acute
myocardial
infarction
was
then
reduced
by
23%,
which
represents
the
proportion
of
cases
that
go
unrecognized
by
the
patient
and
therefore
do
not
result
in
any
medical
costs
(
based
on
Hartunian
et
al.,
1981).
EPA
used
a
three
percent
discount
rate
to
calculate
the
present
value
of
these
costs.
EPA
then
calculated
the
final
cost
estimate
by
taking
the
simple
average
of
the
three
CHD
types.
The
central
tendency
estimate
of
the
COI
associated
with
a
case
of
pollution­
related
CHD
is
about
$
76,347
(
2001$).

This
estimate
likely
underestimates
the
full
COI
because
it
does
not
include
lost
earnings.
It
likely
underestimates
total
WTP
to
avoid
CHD
to
an
even
greater
extent
because
it
does
not
include
WTP
to
avoid
the
pain
and
suffering
associated
with
the
CHD
event.

This
analysis
combined
the
value
of
reducing
CHD
events
with
the
value
of
reducing
hypertension,
even
though
these
conditions
often
occur
together.
The
two
values
represent
different
costs
associated
with
the
conditions.
The
valuation
for
hypertension
includes
hypertension­
associated
work
day
loss
and
medical
costs.
CHD
valuation
is
based
on
the
medical
costs
for
treatment
associated
with
the
CHD
itself.
EPA
estimated
these
two
values
separately
and
added
them
together.

c.
Changes
in
initial
CBA
and
initial
BI
 
Quantifying
the
relationship
between
BP
and
first­
time
stroke
Strokes
include
two
types
of
health
events:
initial
CBA
and
initial
BI.
The
risk
of
CBA
has
been
quantified
for
the
male
population
between
45
and
74
years
old
(
Shurtleff,
1974).
For
initial
CBA,
the
equation
is:

16
EPA
obtained
costs
from
Appendix
G
of
the
Benefits
and
Costs
of
the
Clean
Air
Act:
1970
to
1990,
prepared
for
U.
S.
Congress
by
U.
S.
EPA,
Office
of
Air
and
Radiation
and
Office
of
Policy,
Planning,
and
Evaluation,
1997b.

14­
24
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
(
14.14)

where:

 
Pr(
CBAmen)
=
the
change
in
2­
year
probability
of
CBA
in
men;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
45
to
74
is
81.1
and
78.8,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

For
initial
BI,
the
equation
is
(
Pirkle
et
al.,
1985):

(
14.15)

where:

 
Pr(
BImen)
=
the
change
in
2­
year
probability
of
brain
infarction
in
men;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
45
to
74
is
81.1
and
78.8,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

Similar
ly
to
CH
D
events,
this
analysis
estim
ates
on
ly
non­
fata
l
strokes
to
avo
id
do
uble­
c
ountin
g
with
pr
ema
ture
m
ortality.

Shurtleff
repo
rted
tha
t
70
percen
t
of
strokes
were
non
­
fatal.
A
ap
plied
this
factor
to
the
estimates
o
f
both
C
BA
and
B
I
to
ensure
that
the
estimate
of
avoided
CBA
and
B
I
events
included
only
non­
fatal
events
(
Shurtleff,
1974).

 
Valuing
reductions
in
strokes
Similarly
to
CH
D
eve
nts,
EPA
first
calculates
the
number
of
avo
ided
stroke
s
per
year
and
then
uses
the
estimated
lifetime
cost
of
a
stroke
to
value
reductions
in
stro
kes.
aylor
et
al.
estimated
the
lifetim
e
cost
of
stroke,
includ
ing
the
p
resent
value
(
in
1990
d
ollars)
of
the
stream
of
medical
expenditures
and
the
present
discounted
value
of
the
stream
of
lost
earnings,
using
a
five
percent
discount
rate
(
Taylor
et
al.,
1996).
The
estimated
expected
lifetime
cost
of
a
non­
fatal
stroke
for
males
aged
45
to
74
is
335,135
(
20
01$).
17
d.
Changes
in
premature
mortality
 
Qu
antifying
the
relatio
nship
betw
een
BP
and
prem
ature
m
ortality
It
is
well
established
that
elevated
BP
increases
the
probability
of
premature
death.
There
are,
however,
several
underlying
conditions
that
cause
elevated
BP
(
e.
g.,
cholesterol
level).
U.
S.
EPA
(
1987)
used
po
pulation
mean
values
for
serum
cholesterol
and
smoking
to
reduce
results
from
a
12­
year
follow­
up
of
men
aged
40
to
54
in
the
Framingham
Study
(
McGee
and
Go
rdon,
1976)
to
an
equation
with
one
explanatory
variable
(
DBP):

(
14.16)

where:

 
Pr(
MORT40­
54)
=
the
change
in
12­
year
probability
of
death
for
men
aged
40
to
54;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
40
to
54
is
81.9
and
79.9,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.
EP
T
17
EPA
obtained
cost
from
Appendix
G
of
the
Benefits
and
Costs
of
the
Clean
Air
Act:
1970
to
1990,
prepared
for
U.
S.
Congress
by
U.
S.
EPA,
Office
of
Air
and
Radiation
and
Office
of
Policy,
Planning,
and
Evaluation,
1997b.

14­
25
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
This
analysis
used
information
from
Shurtleff
(
1974)
to
estimate
the
probability
of
premature
death
in
men
older
than
54
years.
The
present
analysis
estimates
a
two­
year
probability
based
on
the
Shurtleff
study s
two­
year
follow­
up
period.
EPA
predicted
mortality
for
men
aged
55
to
64
years
old
using
the
following
equation:

(
14.17)

where:

 
Pr(
MORT55­
64)
=
the
change
in
two­
year
probability
of
death
in
men
aged
55
to
64;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
55
to
64
is
80.6
and
79.0,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

Using
data
from
Shurtleff
(
1974),
EP
A
predicted
premature
mortality
for
men
aged
65
to
74
using
the
following
equation:

(
14.18)

where:

 
Pr(
MORT65­
74)
=
the
change
in
two­
year
probability
of
death
in
men
aged
65
to
74;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
subsistence
and
recreational
fishermen
aged
65
to
74
is
79.5
and
76.4,
respectively;
and
DBP2
=
mea
n
diasto
lic
BP
in
the
po
st­
com
plianc
e
scen
ario.

 
Valuing
redu
ctions
in
prem
ature
mortality
Similarly
to
health
outcomes
discussed
in
the
preceding
sections,
EPA
first
estimated
changes
in
annual
probability
of
premature
mortality
for
men
in
different
age
groups.
The
Agency
then
calculated
avoided
premature
death
cases
by
multiplying
the
estimated
change
in
annual
probability
of
premature
mortality
by
the
relevant
population.
s
analysis
uses
the
$
6.5
million
(
2001$)
estimate
of
the
value
of
a
statistical
life
saved
recommended
in
the
Guidelines
for
Preparing
Eco
nom
ic
An
alysis
(
EPA,
20
00a).
P
to
avoid
the
risk
of
death.

The
values
of
avoiding
CHD,
BA,
and
BI
events
are
all
based
on
COI
estimates
associated
with
a
non­
fatal
health
event.
On
the
other
hand,
the
va
lue
of
the
chang
e
in
pre
mature
mo
rtality
is
based
on
the
value
of
avoiding
a
hea
lth
event
that
does
end
in
death.
Thus,
these
two
endpoints
are
additive.

14.3.3
Female
Health
Benefits
Rec
ently
exp
anded
an
alysis
of
data
from
NH
AN
ES
II
by
Sc
hwartz
indicates
a
significa
nt
association
betwe
en
P
bB
and
B
P
in
women
(
Schwartz,
1990).
her
study,
by
Rabinowitz
et
al.
(
1987),
found
a
small
but
demonstrable
association
between
maternal
PbB
,
pregnancy
hyper
tension
,
and
B
P
at
tim
e
of
delivery.

a.
Relationship
between
BP
and
PbB
Altho
ugh
wo
men
are
at
risk
for
lead
­
induced
hyp
ertensio
n,
no
d
ose­
re
sponse
func
tion
for
h
yperte
nsion
in
wom
en
is
ava
ilable
at
this
time.
gency
did
no
t
quantify
changes
in
risk
for
lead­
induc
ed
hyper
tension
in
wom
en
for
this
analysis.

This
analysis
used
an
adjusted
dose­
response
function
for
a
change
in
BP
associated
with
a
decrease
in
PbB
in
men
(
Equation
14.10)
to
estimate
lead­
induced
changes
in
blood
pressure
in
women.
is
used
to
provide
input
values
for
the
analyse
s
discussed
in
the
following
sections.

A
review
of
ten
published
studies
examined
the
effect
of
lead
exposure
on
the
BP
of
women,
relative
to
the
effect
on
men
(
Schwartz,
1992).
All
of
the
reviewed
studies
included
data
for
men;
some
included
data
for
women.
Schwartz
used
a
conco
rdance
p
roced
ure
that
comb
ined
data
from
each
study
to
p
redict
the
decre
ase
in
diastolic
BP
associated
with
a
d
ecrease
Thi
This
value
is
based
on
WT
Anot
Therefore,
the
A
Equation
14.19
14­
26
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
from
10
 
g/
dL
to
5
 
g/
dL
PbB
(
Schwartz,
1992).
The
results
suggest
that
when
PbB
is
decreased,
women
experience
a
BP
change
that
is
60
percent
of
the
change
seen
in
men.
Equation
(
14.10)
can
be
rewritten
for
women
as:

(
14.19)

where:

 
DBPwomen
=
the
change
in
women's
diastolic
BP
expected
from
a
change
in
PbB;

PbB1
=
PbB
level
in
the
baseline
scenario;
and
PbB2
=
PbB
level
in
the
post­
compliance
scenario.

b.
Changes
in
CHD
 
Quantif
ying
th
e
re
la
tionsh
ip
be
tw
ee
n
BP
and
CH
D
Elevated
BP
in
women
results
in
the
same
effects
as
for
men
(
CHD,
two
types
of
stroke,
and
premature
death).
However,
the
general
relatio
nships
betwe
en
B
P
an
d
these
health
e
ffects
are
n
ot
identical
to
the
dose
­
respo
nse
func
tions
estim
ated
fo
r
men
.

All
relatio
nships
prese
nted
h
ere
ha
ve
be
en
estim
ated
fo
r
wom
en
age
d
45
to
74
years
o
ld
using
inform
ation
fro
m
Sh
urtleff
(
1974).
A
estimated
first­
time
CHD
related
to
an
increase
in
BP
in
women
using
the
following
equation:

(
14.20)

where:

 
Pr(
CHDwomen)
=
change
in
2­
year
probability
of
occurrence
of
CHD
event
for
women
aged
45­
74;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
wo
men
in
subsiste
nce
and
re
creatio
nal
ho
useho
lds
age
d
45
to
74
is
76.5
and
7
4.8,
re
spec
tively;

and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

EPA
estimated
non­
fatal
CHD
events
by
assuming
that
two­
thirds
of
all
estimated
CH
D
events
are
not
fatal
(
Shurtleff,
1974).

 
Valuing
redu
ctions
in
CH
D
events
The
Agency
first
calculated
the
number
of
avoided
CHD
events
for
women
using
Equation
14.20.
EPA
assumed
that
values
of
red
ucing
C
HD
events
fo
r
wom
en
eq
ual
those
calc
ulated
for
me
n
(
ab
ove):
$
76
,347
(
2001$
)
per
C
HD
event.

c.
Changes
in
BI
and
initial
CBA
 
Quantifying
the
relationship
between
BP
and
first­
time
stroke
EPA
predicted
the
relationship
between
BP
and
initial
CBA
for
women
using
the
following
equation:

(
14.21)

where:

 
Pr(
CBAwomen)
=
change
in
two­
year
probability
of
cerebrovascular
accident
in
women
aged
45
to
74;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

The
following
equation
illustrates
the
relationship
between
BI
and
initial
BI
in
women:

(
14.22)
EP
14­
27
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
where:

 
Pr(
BIwomen)
=
change
in
2­
year
probability
of
brain
infarction
in
women
aged
45
to
74;

DBP1
=
mean
diastolic
BP
in
the
baseline
scenario;
based
on
the
Phase
2
NHANES
III,
mean
diastolic
BP
for
women
in
subsistence
and
recreational
households
aged
45
to
74
is
76.5
and
74.8,
respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

EP
A
multiplied
the
pre
dicted
incidences
o
f
avoid
ed
B
I
and
CB
A
by
7
0
pe
rcent
to
estimate
only
no
n­
fatal
strok
es
(
Shurtleff,

1974).

 
Valuing
reductions
in
strokes
EPA
calculated
the
value
of
avoiding
an
initial
CBA
or
an
initial
BI
for
women
in
the
same
way
as
for
men
(
see
above).
EPA
predicted
lead­
related
stroke
for
women
in
the
United
States
between
the
ages
of
45
and
74,
of
whom
38.2
percent
are
aged
45
to
54
and
the
remaining
61.8
percent
are
aged
55
­
74.
ic
values
in
Taylor
et
al.
(
1996),

EPA
estimated
the
average
value
of
avoiding
a
stroke
among
women
aged
45
to
74
to
be
about
$
25
1,351
(
200
1$).

d.
Changes
in
premature
mortality
 
Qu
antify
ing
th
e
relatio
nship
betw
een
BP
and
prem
ature
m
ortality
The
following
equation
estimates
the
risk
of
premature
mortality
in
women
(
Shurtleff,
1974):

(
14.23)

where:

 
Pr(
MORTwomen)
=
the
change
in
two­
year
probability
of
death
for
women
aged
45
to
74;

DBP1
=
mea
n
diasto
lic
BP
in
the
ba
seline
scenario
;
based
on
the
Pha
se
2
N
HA
NE
S
III,
m
ean
d
iastolic
BP
for
women
in
subsistence
and
recreational
households
aged
45
to
74
is
76.5
and
74.8,

respectively;
and
DBP2
=
mean
diastolic
BP
in
the
post­
compliance
scenario.

 
Valuing
redu
ctions
in
pre
m
ature
m
ortality
EPA
predicted
changes
in
lead­
related
premature
mortality
for
women
in
the
same
way
as
for
men
(
see
above).

the
value
of
reducing
premature
mortality
in
women
to
be
equal
to
that
estimated
for
all
premature
mortality,
$
6.5
million
(
2001$
)
per
incident
(
see
Section
13.2.1).

14.4
LEAD­
RELATED
BENEFIT
RESULTS
This
section
describes
the
estimated
benefits
of
reduced
lead
exposure
from
consumption
of
fish
in
three
populations:
(
1)

preschool
age
children,
(
2)
pregnant
women,
and
(
3)
adult
men
and
women.
Benefit
estimates
for
pregnant
women
appear
with
those
for
preschool
age
children,
because
the
beneficiaries
in
this
category
are
children
under
the
age
of
one
who
suffer
in
utero
fetal
lead
exposure
from
maternal
lead
intake
during
pregnancy.
inal
regulation
will
yield
no
benefits
to
children
or
adults
from
reduced
exp
osure
to
lead.
ive
regulatory
options
considered
by
EPA
w
ere
estimated
to
yield
be
nefits
from
reduce
d
expo
sure
to
lead.
he
following
discussion
reviews
the
estimated
b
enefits
from
these
alternative
op
tions.

14.4.1
Preschool
Age
Children
Lead­
Related
Benefit
Results
EP
A
analyzed
the
mone
tary
value
of
health
bene
fits
to
children
from
reduc
ed
lead
e
xposure
in
four
categories:

 
redu
ced
neo­
n
atal
mo
rtality,

 
avoided
IQ
lo
ss,

 
reduced
incidence
of
IQ
below
70,
and
 
reduced
incidence
of
PbB
levels
above
20
 
g/
dL.
Using
the
gender­
and
age­
specif
EPA
assumed
EPA
estimated
that
the
f
Alternat
T
14­
28
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
From
this
analysis,
EPA
estimated
that
the
final
rule
will
yield
no
lead­
related
benefits
to
children.

Other
regulatory
options
considered
by
EPA
were
found
to
yield
lead­
related
benefits
to
children.
Table
14.5
summarizes
lead­
related
benefits
estimated
for
the
433
Upgrade
Options.
EPA
estimated
that
the
Directs
+
413
to
433
Upgrade
Option
and
the
Directs
+
All
to
433
Upgrade
Option
would
reduce
0.15
and
0.17
cases
of
neonatal
mortality,
and
avoid
the
loss
of
32
and
36
IQ
points,
respectively.
The
Directs
+
413
to
433
Upgrade
Option
and
the
Directs
+
All
to
433
Upgrade
Option
would
result
in
$
1.3
and
$
1.5
million
(
2001$)
in
annual
lead­
related
benefits
for
children,
respectively.

Table
14.5:
National
Annual
Benefits
from
Reduced
Lead
in
Children
(
2001$)
 
433
Upgrade
Options
a
Category
Directs
+
413
to
433
Upgrade
Directs
+
All
to
433
Upgrade
Reduced
Cases
or
IQ
Points
Benefit
Value
(
2001$)
Reduced
Cases
or
IQ
Points
Benefit
Value
(
2001$)

Neonatal
mortality
0.15
$
995,630
0.17
$
1,109,294
Avoided
IQ
Loss
31.99
$
301,323
36.19
$
340,845
Reduced
IQ
<
70
0.11
$
6,637
0.13
$
7,501
Reduced
PbB
>
20
 
g/
L
0.00
$
0
0.00
$
0
Total
Benefits
$
1,303,590
$
1,457,640
a
Based
on
the
Traditional
Extrapolation.

Source:
U.
S.
EPA
analysis.

Table
14.6
summarizes
lead­
related
benefits
estimated
for
the
Proposed/
NODA
Option.
EPA
estimated
that
the
Proposed/
NODA
Option
would
reduce
1.60
cases
of
neonatal
mortality
and
avoid
the
loss
of
1,078
IQ
points.
Annual
lead­

related
benefits
for
children
equal
$
20.8
million
(
2001$)
under
the
Proposed/
NODA
Option,
which
substantially
exceeds
estimated
lead­
related
benefits
for
children
under
the
two
433
Upgrade
Options.

Table
14.6:
National
Annual
Benefits
from
Reduced
Lead
in
Children
(
2001$)
 
Proposed/
NODA
Option
a
Category
Reduced
Cases
or
IQ
Points
Benefit
Value
(
2001$)

Neonatal
mortality
1.60
$
10,417,781
Avoided
IQ
Loss
1,078.38
$
10,157,286
Reduced
IQ
<
70
3.72
$
216,007
Reduced
PbB
>
20
 
g/
L
0.00
$
0
Total
Benefits
$
20,791,073
a
Based
on
the
Traditional
Extrapolation.

Source:
U.
S.
EPA
analysis.

The
results
from
the
estimated
lead­
related
benefits
for
children
are
conservative,
because
this
analysis
omits
other
lead­

related
impacts,
such
as
the
cost
of
group
homes
and
other
special
care
facilities.
Table
14.1
presents
other
omitted
benefits
categories.
Section
14.5
discusses
uncertainty
and
limitations
inherent
in
this
analysis.

14.4.2
Adult
Lead­
Related
Benefit
Results
As
discussed
previously,
EPA
quantified
only
the
lead­
related
health
effects
in
adults
that
relate
to
lead s
effect
on
BP.
These
health
effects
include
increased
incidence
of
hypertension,
initial
non­
fatal
CHD,
non­
fatal
stokes
(
CBA
and
BI),
and
premature
mortality.
EPA
used
COI
estimates
(
i.
e.,
medical
costs
and
lost
work
time)
to
estimate
monetary
values
for
14­
29
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
reduced
incidence
of
hypertension,
initial
CHD
,
and
strokes.
EPA
based
monetary
values
for
changes
in
risk
of
premature
mortality
on
estimates
of
the
value
of
a
statistical
life
saved.
The
results
are
conservative
estimates,
because
this
analysis
does
not
include
other
health
effects
associated
with
elevated
BP
or
with
lead.
Other
effects
of
lead
in
adults
can
include
nervous
system
disorders,
anemia,
and
possible
cancer
effects.

From
this
analysis,
EPA
estimated
that
the
final
rule
will
yield
no
lead­
related
health
benefits
to
adults.

Other
regulatory
options
considered
by
EPA
were
found
to
yield
lead­
related
benefits
to
adults.
Table
14.7
summarizes
lead­

related
benefits
estimated
for
the
433
Upgrade
Options.
EPA
estimated
that
the
Directs
+
413
to
433
Upgrade
Option
and
the
Directs
+
All
to
433
Upgrade
Option
respectively
would
reduce
hypertension
among
males
by
53
and
60
cases
annually.
Both
the
433
Upgrade
Options
would
also
reduce
the
annual
incidence
of
premature
mortality
among
men
and
women
by
approximately
0.1
cases.
EPA
estimated
annual
lead­
related
benefits
for
adults
under
the
Directs
+
413
to
433
Upgrade
Option
at
$
0.70
million
(
2001$)
and
under
the
Directs
+
All
to
433
Upgrade
Option
at
$
0.79
million
(
2001$).

Table
14.7:
National
Adult
Lead
Annual
Benefits
(
2001$)
 
433
Upgrade
Options
a,
b
Category
Directs
+
413
to
433
Upgrade
Directs
+
All
to
433
Upgrade
Reduced
Cases
Mean
Value
of
Benefits
Reduced
Cases
Mean
Value
of
Benefits
Men
Hypertension
53.47
$
61,004
59.58
$
67,982
CHD
0.05
$
4,155
0.06
$
4,631
CBA
0.02
$
5,698
0.02
$
6,350
BI
0.01
$
3,226
0.01
$
3,596
Mortality
0.07
$
474,735
0.08
$
529,125
Women
CHD
0.02
$
1,662
0.02
$
1,853
CBA
0.01
$
2,417
0.01
$
2,694
BI
0.01
$
1,487
0.01
$
1,658
Mortality
0.02
$
150,190
0.03
$
167,417
Total
Benefits
$
704,574
$
785,304
a
Based
on
the
Traditional
Extrapolation.

b
National
Level
Exposed
Population:

(
1)
Directs
+
413
to
433
Upgrade
Hypertension:
139,745
men
ages
20
to
74;

CHD,
CBA,
BI,
and
mortality:
56,564
men
and
62,666
women
ages
45­
74.

(
2)
Directs
+
413
+
50%
LL
Upgrade
Hypertension:
139,745
men
ages
20
to
74;

CHD,
CBA,
BI,
and
mortality:
56,564
men
and
62,666
women
ages
45­
74.

Source:
U.
S.
EPA
analysis.

Table
14­
8
summarizes
lead­
related
benefits
estimated
for
the
Proposed/
NODA
Option.
EPA
estimated
that
this
option
would
reduce
hypertension
among
males
by
approximately
545
cases
and
the
incidence
of
premature
mortality
among
men
and
women
by
0.96
cases
annually.
Lead­
related
benefits
for
adults
under
the
Proposed/
NODA
Option
would
be
$
7.05
million
annually,
which
substantially
exceeds
estimated
benefits
under
the
two
433
Upgrade
Options.

14­
30
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.8:
National
Adult
Lead
Annual
Benefits
(
2001$)
 
Proposed/
NODA
Option
a,
b
Category
Reduced
Cases
Mean
Value
of
Benefits
Men
Hypertension
545.25
$
622,126
CHD
0.54
$
41,564
CBA
0.17
$
56,907
BI
0.10
$
32,197
Mortality
0.73
$
4,750,132
Women
CHD
0.22
$
16,472
CBA
0.10
$
23,928
BI
0.06
$
14,714
Mortality
0.23
$
1,489,984
Total
Benefits
$
7,048,025
a
Based
on
the
Traditional
Extrapolation.

b
National
Level
Exposed
Population:

Hypertension:
539,142
men
ages
20
to
74;

CHD,
CBA,
BI,
and
mortality:
218,226
men
and
241,768
women
ages
45­
74.

Source:
U.
S.
EPA
analysis.

14.5
LIMITATIONS
AND
UNCERTAINTIES
This
section
discusses
limitations
and
uncertainties
in
the
lead­
related
benefits
analysis.
Developing
dose­
response
functions
depends
on
relating
lead
exposure
to
PbB
levels,
then
evaluating
PbB
levels
in
relation
to
specific
health
outcomes.

Quantitative
dose­
response
functions
for
most
health
effects
associated
with
lead
exposure
currently
do
not
exist.
For
this
reason,
the
analysis
does
not
provide
a
comprehensive
estimate
of
health
benefits
from
reduced
lead
discharges
from
MP&
M
facilities.

Table
14.1
summarizes
quantified
and
non­
quantified
health
effects.
Economic
research
does
not
always
yield
a
complete
evaluation,
even
for
those
effects
that
can
be
quantified.
This
uncertainly
is
likely
to
bias
the
estimate
of
lead­
related
benefits
of
the
MP&
M
regulation
downward.
The
analysis
methodologies
used
here
also
involve
significant
simplifications
and
uncertainties.
Section
13.3
discusses
similar
limitations
and
uncertainties
associated
with
the
assessment
of
risk
associated
with
non­
lead­
related
human
health
hazards
and
the
possible
direction
of
bias
associated
with
sample
design
and
benefits
analysis
by:

 
occurrence
location,

 
estimated
in­
waterway
concentrations
of
MP&
M
pollutants,
and
 
estimated
exposed
fishing
population.

The
next
five
sections
discuss
other
omissions,
biases,
and
uncertainties
in
the
lead­
benefit
analysis.
Table
14.9
provides
a
summary
of
this
discussion.

14.5.1
Excluding
Older
Children
Recent
research
on
brain
development
among
10­
to
18­
year­
old
children
shows
unanticipated
and
substantial
growth
in
brain
development,
mainly
in
the
early
teenage
years
(
Giedd
et
al.,
1999).
This
growth
appears
to
be
a
second
 
burst 
of
cell
development
in
some
brain
areas,
in
addition
to
the
previously
recognized
period
of
rapid
growth
during
early
childhood.

One
of
lead s
fundamental
effects
is
to
disrupt
the
protective
coating
(
myelin)
on
nerve
cells.
This
disruption
can
lead
to
permanent
impairment
if
it
occurs
during
development.
New
research
suggests
that
older
children
may
be
a
hypersensitive
14­
31
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
sub­
population,
along
with
children
aged
0
to
7.
Excluding
this
sub­
population
from
the
analysis
may
significantly
underestimate
benefits
from
reduced
lead
discharges.

14.5.2
Compensatory
Education
Costs
This
analysis
assumes
that
compensatory
education
is
required
only
for
children
with
IQs
less
than
70,
and
that
part­
time
special
education
costs
are
assumed
to
be
incurred
only
from
grades
1
through
12
(
Section
14.2.4).
This
assumption
underestimates
compensatory
education
costs
for
the
following
reasons:

 
Children
with
IQ
scores
between
70
and
85
will
likely
be
assigned
to
special
education
or
 
slow 
classes
that
will
likely
be
smaller
than
regular
classes
and
require
more
teacher
attention.
Children
in
this
IQ
range
may
frequently
require
more
than
12
years
to
graduate
and
are
more
likely
to
drop
out
of
school.
Such
children
therefore
require
additional
education
costs.

 
Compensatory
education
may
begin
before
grade
one.
Some
states
(
e.
g.,
Connecticut)
offer
compensatory
education
programs
for
disadvantaged
children
beginning
at
age
three.

This
analysis
is
based
on
a
study
that
measured
the
increased
cost
to
educate
children
with
low
IQs
attending
a
regular
school,

not
a
special
education
program
(
Kakalik
et
al.,
1981).
The
cost
to
attend
a
special
education
program
is
generally
much
higher
than
that
for
regular
schooling.

Some
overlap
may
exist
between
estimates
of
the
avoided
costs
of
compensatory
education
due
to
reduced
incidence
of
children
with
IQ
below
70
and
PbB
levels
above
20
 
g/
dL
because
children
with
PbB
levels
may
also
have
low
IQ
scores.

Estimating
the
magnitude
of
this
overlap
is,
however,
not
feasible
due
to
data
paucity.
In
addition,
the
estimated
avoided
cost
of
compensatory
education
due
to
reduced
incidence
of
children
with
PbB
levels
above
20
 
g/
dL
is
negligible
compared
to
other
benefits
from
reduced
exposure
to
lead.
Thus,
this
overlap
does
not
introduce
a
significant
bias
in
the
estimate
of
total
benefits
from
reduced
exposure
to
lead
to
children.

14.5.3
Dose­
Response
Relationships
The
dose­
response
functions
described
for
each
health
outcome
considered
above
generally
quantify
the
adverse
health
effects
expected
from
increased
lead
exposure.
For
children,
these
effects
are
defined
in
terms
of
changes
in
PbB.
For
adults,
these
effects
are
estimated
in
terms
of
changes
in
BP,
which
are
in
turn
related
to
changes
in
PbB
levels.
Uncertainty
is
inherent
in
the
dose­
response
functions,
which
are
typically
expressed
in
terms
of
the
standard
deviations
of
the
dose­
response
coefficients
used
in
the
analysis.
Any
uncertainty
affecting
the
dose­
response
coefficients
will
also
indirectly
affect
the
accuracy
of
this
analysis.

14.5.4
Absorption
Function
for
Ingested
Lead
in
Fish
Tissue
Numerous
research
groups
have
evaluated
lead
absorption
under
a
variety
of
conditions.
ATSDR
reports
a
range
of
three
percent
to
45
percent
in
the
studies
they
present,
which
consider
lead
intake
with
and
without
food
(
ATSDR,
1997).

Absorption
appears
to
be
affected
by
total
lead
intake,
with
some
studies
showing
a
higher
absorption
proportion
with
higher
doses.
Animal
studies
show
a
saturation
effect,
which
modifies
absorption.

Lead s
chemical
form
also
determines
its
absorption
rate.
For
example,
lead
sulfide
has
approximately
10
percent
of
the
bioavailability
of
lead
acetate
(
ATSDR,
1997).
Particle
size
and
solubility
are
also
important
absorption
factors.
EPA
could
not
obtain
data
to
describe
lead s
precise
chemical
form,
particle
size,
and
other
physical
parameters
in
fish
tissue,
which
would
allow
more
refined
absorption
estimates.
These
characteristics
vary
because
MP&
M
facilities
produce
lead
using
different
processes
and
release
it
in
different
forms.

An
individual s
nutritional
status
also
affects
lead
absorption
rates.
People
who
are
malnourished,
particularly
with
respect
to
calcium
and
iron,
have
high
absorption
rates
(
ATSDR,
1997).
EPA
assumed
that
anglers
were
not
malnourished,
and
made
no
adjustment
for
their
nutritional
status.
See
the
section
on
lead
absorption
in
Maddaloni
(
1998)
for
a
discussion
of
factors
influencing
absorption.
In
the
absence
of
data
on
lead
incorporated
into
food,
EPA
considered
data
from
studies
of
lead
absorption
during
meals
to
be
the
most
appropriate
data
to
use
in
estimating
absorption.

14­
32
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
14.5.5
Economic
Valuation
This
analysis
used
IQ
differentials
to
represent
cognitive
damage
to
children
resulting
from
lead
exposure.
The
economic
analysis
relates
IQ
level
to
annual
earnings,
which
serve
as
the
basis
for
valuing
benefits
from
reduced
lead
exposure.
IQ
differentials
are
used
rather
than
WTP,
the
preferred
measure
to
use,
because
WTP
values
to
avoid
cognitive
damage
are
not
available.
This
analysis
likely
underestimates
the
value
of
an
IQ
point
because
special
education
and
lost
wages
form
only
a
portion
of
the
costs
associated
with
lost
cognitive
functioning.
A
simple
IQ
change
analysis
does
not
capture
all
the
ways
in
which
a
child,
family,
and
society
are
affected
by
the
effects
of
lead­
induced
cognitive
damage.

Dollar
values
associated
with
most
of
the
adult
health
and
welfare
endpoints
represent
only
some
components
of
society s
WTP
to
avoid
these
health
effects.
EPA
used
COI
estimates
to
value
reductions
in
CHD
events,
strokes,
and
hypertension.

These
values
are
likely
to
be
downward­
biased
because
the
value
of
pain
and
suffering
avoided
is
not
included.
Employed
alone,
these
monetized
effects
will
underestimate
society's
WTP.

14­
33
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Table
14.9:
Key
Omissions,
Biases,
and
Uncertainties
in
the
Lead­
Benefit
Analysis
Omissions/
Biases/

Uncertainties
Directional
Impact
on
Benefits
Estimates
Comments
Excluding
older
children
downward
New
research
suggests
that
older
children
may
be
a
hypersensitive
sub­

population,
as
children
aged
0
to
7
are
now
considered.
Excluding
this
sub­
population
from
the
analysis
may
significantly
underestimate
benefits
from
reduced
lead
discharges.

Compensatory
education
costs
uncertain
Assuming
that
compensatory
education
is
required
only
for
children
with
IQs
less
than
70
and
that
part­
time
special
education
costs
are
incurred
from
grades
1
through
12
underestimates
the
special
education
costs
because:

 
Children
with
IQ
scores
between
70
and
85
will
likely
be
assigned
to
special
education
or
 
slow 
classes,
requiring
more
teacher
attention,
and
taking
longer
to
graduate
or
dropping
out
altogether.

 
Compensatory
education
may
begin
before
grade
one.

 
The
cost
to
attend
a
special
education
program
is
generally
much
higher
than
that
for
regular
schooling.

A
potential
overlap
exists
between
estimates
of
the
avoided
costs
of
compensatory
education
due
to
reduced
incidence
of
children
with
IQ
below
70
and
PbB
levels
above
20
g/
dL
because
children
with
PbB
levels
may
also
have
low
IQ
scores.
This
overlap
may
introduce
an
upward
bias
in
the
estimate
of
the
lead­
related
benefits
to
children.
This
bias
is,
however,
negligible
due
to
the
magnitude
of
the
avoided
compensatory
education
cost
estimates.

Dose­
response
relationship
uncertain
Uncertainty
is
inherent
in
the
dose­
response
functions
(
expressed
in
changes
in
PbB
for
children,
changes
in
BP
for
adults).
response
coefficients
will
also
indirectly
affect
the
accuracy
of
this
analysis.

Absorption
factor
for
lead
in
fish
tissue
uncertain
Absorption
rate
appears
to
be
affected
by:

 
total
lead
intake,
with
some
studies
showing
a
higher
absorption
proportion
with
higher
doses;

 
lead s
chemical
form.
Because
MP&
M
facilities
produce
lead
using
different
processes
and
release
it
in
different
forms,
EPA
could
not
obtain
data
to
describe
lead s
precise
chemical
form,
particle
size,
and
other
physical
parameters
in
fish
tissue,
which
would
allow
more
refined
absorption
estimates;

 
an
individual s
nutritional
status;
and
 
time
of
lead
ingestion.
absence
of
data
on
lead
incorporated
into
food,
EPA
considered
data
from
studies
of
lead
absorption
during
meals
to
be
the
most
appropriate
data
to
use
in
estimating
absorption.

Economic
valuation
downward
The
values
associated
with
cognitive
damage
to
children
and
adult
health
effects
are
likely
to
be
downward­
biased.
children,
a
simple
IQ
change
analysis
does
not
capture
all
effects
of
lead­
induced
IQ
loss
on
a
child,
family,
and
society.
luation
of
adults 
health
effects
from
lead
exposure
do
not
include
the
value
of
avoided
pain
and
suffering.

monetized
effects
will
underestimate
society's
WTP.

Overall
impact
downward
Any
uncertainty
affecting
the
dose­

In
the
For
The
va
Employed
alone,
these
Source:
U.
S.
EPA
analysis.

14­
34
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
GLOSSARY
absolute
gastrointestinal
absorption
fraction:
the
fraction
of
lead
in
food
ingested
daily
that
is
absorbed
from
the
gastrointestinal
tract.

acute
toxicity:
the
ability
of
a
substance
to
cause
severe
biological
harm
or
death
soon
after
a
single
exposure
or
dose.

Also,
any
poisonous
effect
resulting
from
a
single
short­
term
exposure
to
a
toxic
substance.

(
http://
www.
epa.
gov/
OCEPAterms/
aterms.
html)

angina
pectoris:
a
syndrome
characterized
by
paroxysmal,
constricting
pain
below
the
sternum,
most
easily
precipitated
by
exertion
or
excitement
and
caused
by
ischemia
of
the
heart
muscle,
usually
due
to
a
coronary
artery
disease,
as
arteriosclerosis.
(
www.
infoplease.
com)

arithmetic
mean:
the
mean
obtained
by
adding
several
quantities
together
and
dividing
the
sum
by
the
number
of
quantities.
(
www.
infoplease.
com)

atherothrombotic
brain
infarctions
(
BI):
scientific
name
for
a
stroke.

bioavailability:
degree
of
ability
to
be
absorbed
and
ready
to
interact
in
organism
metabolism.

(
http://
www.
epa.
gov/
OCEPAterms/
bterms.
html)

biokinetics:
the
study
of
movements
of
or
within
organisms.
(
www.
infoplease.
com)

biomarker:
a
physical,
functional,
or
biochemical
indicator
of
a
certain
process
or
event.
It
is
commonly
used
to
measure
the
progress
of
a
disease,
the
effects
of
treatment,
or
the
status
of
a
condition.

blood
lead
(
PbB):
concentration
level
of
lead
in
blood
stream;
usually
expressed
in
 
g/
dL.

blood
pressure:
the
pressure
of
the
blood
against
the
inner
walls
of
the
blood
vessels,
varying
in
different
parts
of
the
body
during
different
phases
of
contraction
of
the
heart
and
under
different
conditions
of
health,
exertion,
etc.

(
www.
infoplease.
com)

central
tendency
estimate:
major
trend
in
group
of
data.

cerebrovascular
accident
(
CBA):
stroke.

coronary
heart
disease
(
CHD):
disorder
that
restricts
blood
supply
to
the
heart;
occurs
when
coronary
arteries
become
narrowed
or
clogged
due
to
the
build
up
of
cholesterol
and
fat
on
the
inside
walls
and
are
unable
supply
enough
blood
to
the
heart.

diastolic:
pertaining
to
or
produced
by
diastole,
or
(
of
blood
pressure)
indicating
the
arterial
pressure
during
the
interval
between
heartbeats.
(
www.
infoplease.
com)

discounting:
degree
to
which
future
dollars
are
discounted
relative
to
current
dollars.
Economic
analysis
generally
assumes
that
a
given
unit
of
benefit
or
cost
matters
more
if
it
is
experienced
now
than
if
it
occurs
in
the
future.
The
present
is
more
important
due
to
impatience,
uncertainty,
and
the
productivity
of
capital.
This
analysis
uses
a
three
percent
discount
rate
to
discount
future
benefits.
(
http://
www.
damagevaluation.
com/
glossary)

dose
response:
shifts
in
toxicological
responses
of
an
individual
(
such
as
alterations
in
severity)
or
populations
(
such
as
alterations
in
incidence)
that
are
related
to
changes
in
the
dose
of
any
given
substance.

dose­
response
assessment:
1.
Estimating
the
potency
of
a
chemical.
2.
In
exposure
assessment,
the
process
of
determining
the
relationship
between
the
dose
of
a
stressor
and
a
specific
biological
response.
3.
Evaluating
the
quantitative
relationship
between
dose
and
toxicological
responses.

14­
35
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
dose­
response
curve:
graphical
representation
of
the
relationship
between
the
dose
of
a
stressor
and
the
biological
response
thereto.

dose­
response
functions:
see
dose­
response
relationship.

dose­
response
relationship:
the
quantitative
relationship
between
the
amount
of
exposure
to
a
substance
and
the
extent
of
toxic
injury
or
disease
produced.
(
http://
www.
epa.
gov/
OCEPAterms/
dterms.
html)

encephalopathy:
any
brain
disease.
(
www.
infoplease.
com)

GDP
price
deflator:
measure
of
the
percentage
increase
in
the
average
price
of
products
in
GDP
over
a
certain
base
year
published
by
the
Commerce
Department.
(
http://
www.
damagevaluation.
com/
glossary.
htm)

genotoxic:
may
cause
chromosomal
damage
in
humans
leading
to
birth
defects.

geometric
mean
(
GM):
for
a
set
of
n
numbers
{
x1,
x2,
x3,
...,
xn}
it
is
the
n­
th
root
of
their
product:
(
x1
*
x2*
x3
...
xn)
1/
n.

geometric
standard
deviation
(
GSD):
a
measure
of
the
inter­
individual
variability
in
blood
lead
concentrations
in
a
population
whose
members
are
exposed
to
the
same
environmental
lead
levels.
For
a
lognormal
distribution,
GSD
is
the
exponential
of
the
standard
deviation
of
the
associated
normal
distribution.

half­
life:
time
required
for
a
living
tissue,
organ,
or
organism
to
eliminate
one­
half
of
a
substance
which
has
been
introduced
into
it.

health
endpoints:
an
observable
or
measurable
biological
event
or
chemical
concentration
(
e.
g.,
metabolite
concentration
in
a
target
tissue)
used
as
an
index
of
an
effect
of
a
chemical
exposure.

heme
synthesis:
creation
of
heme;
an
iron
compound
of
protoporphyrin
which
constitutes
the
pigment
portion
or
protein­

free
part
of
the
hemoglobin
molecule
and
is
responsible
for
its
oxygen­
carrying
properties.

Integrated
Exposure,
Uptake,
and
Biokinetics
(
IEUBK):
the
IEUBK
model
is
an
exposure­
response
model
that
uses
children s
environmental
lead
exposure
to
estimate
risk
of
elevated
blood
lead
(
typically>
10
 
g/
dL)
through
estimation
of
lead
body
burdens
in
mass
balance
framework.

least­
squares
regression:
a
tool
of
regression
analysis
that
computes
a
best­
fit
line
to
represent
the
relationship
between
two
(
or
more)
variables
based
on
the
principle
that
the
squared
deviations
of
the
observed
points
from
that
line
are
minimized
(
see
also:
regression
analysis).

lognormal
distribution:
a
distribution
of
a
random
variable
for
which
the
logarithm
of
the
variable
has
a
normal
distribution.
(
www.
infoplease.
com)

lognormally­
distributed
random
variable:
same
as
lognormal
distribution.

marginal
cost:
the
increase
in
total
costs
as
one
more
unit
is
produced.
(
http://
www.
damagevaluation.
com/
glossary.
htm)

multivariate:
(
of
a
combined
distribution)
having
more
than
one
variate
or
variable.
(
www.
infoplease.
com)

nephropathy:
any
kidney
disease.
(
www.
infoplease.
com)

neurobehavioral
deficits:
neurologic
effects
as
assessed
by
observation
of
behavior.
These
effects
may
include
behavioral
and
attentional
difficulties,
delayed
mental
development,
lack
of
motor
and
perceptual
skills,
and
hyperactivity.

neurobehavioral
function:
see
neurobehavioral
deficits.

non­
cancer
health
risks:
include
systemic
effects,
reproductive
toxicity,
and
developmental
toxicity.

normal
distribution:
a
random
variable
X
is
normally
distributed
if
its
density
is
given
by
f
x
(
x)
=
f(
x;
 
,
 
)
,
where
 
and
 
are
the
mean
and
the
variance
of
the
distribution.

14­
36
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
opportunity
cost:
the
highest­
valued
sacrifice
needed
to
get
a
good
or
service.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

p­
value:
the
probability
of
obtaining
a
given
outcome
due
to
chance
alone.
For
example,
a
study
result
with
a
significance
level
of
p<
0.05
implies
that
5
times
out
of
100
the
result
could
have
occurred
by
chance.

(
http://
www.
teleport.
com/~
celinec/
glossary.
htm)

pharmacokinetics:
the
study
of
the
way
drugs
move
through
the
body
after
they
are
swallowed
or
injected.

(
http://
www.
epa.
gov/
OCEPAterms/
pterms.
html)

probability
distribution:
a
distribution
of
all
possible
values
of
a
random
variable
together
with
an
indication
of
their
probabilities.
(
www.
infoplease.
com)

probit
regression:
a
regression
model,
where
the
dependent
variable
is
set
up
as
a
0­
1
dummy
variable
and
regressed
on
the
explanatory
variables.
The
predicted
value
of
the
dependent
variable
could
be
interpreted
as
the
probability
that
a
certain
event
will
take
place
(
e.
g.,
an
individual
will
buy
a
car,
visit
a
particular
location,
or
get
a
specific
disease).

quasi­
steady
state:
almost
not
changing
state.

regression
analysis:
a
procedure
for
determining
a
relationship
between
a
dependent
variable,
such
as
predicted
success
in
college,
and
an
independent
variable,
such
as
a
score
on
a
scholastic
aptitude
test,
for
a
given
population.
The
relationship
is
expressed
as
an
equation
for
a
line.
(
www.
infoplease.
com)

risk­
based
remediation
goals
(
RBRG):
target
human
health
and
environmental
risk
levels
to
be
achieved
via
remedial
actions
at
Superfund
sites.

Technical
Review
Workgroup
(
TRW):
a
workgroup
formed
in
1994
to
evaluate
methodologies
for
adult
lead
risk
assessment.

 
g/
L:
microgram
per
liter
 
g/
dL:
microgram
per
decaliter
willingness­
to­
pay
(
WTP):
maximum
amount
of
money
one
would
give
up
to
buy
some
good.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

14­
37
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
ACRONYMS
ATSDR:
Agency
for
Toxic
Substances
and
Disease
Registry
BI:
atherothrombotic
brain
infarction
BP:
blood
pressure
CARB:
California
Air
Resources
Board
CBA:
cerebrovascular
accidents
CDC:
Centers
for
Disease
Control
CEPA:
California
Environmental
Protection
Agency
CHD:
coronary
heart
disease
COI:
cost
of
illness
GM:
geometric
mean
GSD:
geometric
standard
deviation
IEUBK:
Integrated
Exposure,
Uptake,
and
Biokinetics
NHANES:
National
Health
and
Nutrition
Examination
Surveys
NLSY:
National
Longitudinal
Survey
of
Youth
PbB:
blood
lead
PPRG:
Pooling
Project
Research
Group
RBRG:
risk­
based
remediation
goals
TRW:
Technical
Review
Workgroup
WTP:
willingness­
to­
pay
14­
38
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
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and
Development.
Washington,
DC:
EPA­
600­
P­
95­
002Fa,
b,
c.
August.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1997b.
The
Benefits
and
Costs
of
the
Clean
Air
Act:
1970
to
1990.

Office
of
Air
and
Radiation
and
Office
of
Policy,
Planning
and
Evaluation,
Appendix
G:
Lead
Benefits
Analysis.
EPA
410­
R­
97­
002.
October.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1998a.
Economic
Analysis
of
Toxic
Substances
Control
Act
Section
403:
Hazard
Standards.
Prepared
for
EPA
by
Abt
Associates
Inc.,
May.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1998b.
Risk
Analysis
to
Support
Standards
for
Lead
in
Paint,
Dust
and
Soil.
Washington,
D.
C.:
EPA/
OPPT
747­
R­
97­
006.
June.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1998c.
Lead;
Identification
of
Dangerous
Levels
of
Lead;
Proposed
Rule.
Federal
Register
June
3:
30302­
30355.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1999.
Cost
of
Illness
Handbook
(
Draft).
Washington,
D.
C.:
OPPT.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
2000a.
Guidelines
for
Preparing
Economic
Analyses.
Washington,

D.
C.:
EPA
240­
R­
00­
003.
September.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
2000b.
Methodology
for
Deriving
Ambient
Water
Quality
Criteria
for
the
Protection
of
Human
Health
.
EPA
822­
B­
00­
004.
October.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
2002a.
Integrated
Risk
Information
System
(
IRIS)
Retrieval.

Washington,
DC:
U.
S.
EPA.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
2002b.
Estimated
Per
Capita
Fish
Consumption
in
the
United
States.

EPA­
821­
C­
02­
003.
August.

14­
42
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
Ward
N.,
R.
Watson,
and
D.
Bryce­
Smith.
1987.
"
Placental
Element
Levels
in
Relation
to
Fetal
Development
for
Obstetrically
Normal
Births:
A
Study
of
37
Elements:
Evidence
for
the
Effects
of
Cadmium,
Lead,
and
Zinc
on
Fetal
Growth
and
for
Smoking
as
a
Source
of
Cadmium. 
Int
J
Biosoc
Res
9:
63­
81.

Wittels,
E.
H.,
J.
W.
Hay,
and
A.
M.
Gotto,
Jr.
1990.
 
Medical
Costs
of
Coronary
Artery
Disease
in
the
United
States. 
The
American
Journal
of
Cardiology
65:
432­
440.

14­
43
MP&
M
EEBA
Part
III:
Benefits
Chapter
14:
Lead­
Related
Benefits
THIS
PAGE
INTENTIONALLY
LEFT
BLANK
14­
44
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
INTRODUCTION
The
final
Metal
Product
and
Machinery
(
MP&
M)

regulation
is
expected
to
provide
ecological
benefits
through
improvements
in
the
habitats
or
ecosystems
(
aquatic
and
terrestrial)
that
are
affected
by
the
MP&
M
industry
discharges.
Society
is
expected
to
value
such
ecological
improvements
by
a
number
of
mechanisms,
including
increased
frequency
and
value
of
use
of
the
improved
habitat
for
recreational
activities.
In
addition,
individuals
may
also
value
the
protection
of
habitats
and
species
that
are
adversely
affected
by
effluent
dischargers
even
when
they
do
not
use
or
anticipate
future
use
of
the
affected
waterways
for
recreational
or
other
purposes.

This
chapter
presents
EPA s
analysis
of
ecological
benefits
from
reduced
effluent
discharges
to
the
nation s
waterways
as
a
result
of
the
final
MP&
M
regulation,
the
433
Upgrade
Options,
and
the
Proposed/
NODA
option.
EPA
assessed
ecological
benefits
in
terms
of
reduced
occurrence
of
pollutant
concentrations
in
excess
of
AWQC
protective
of
aquatic
life
and
human
health.
For
this
analysis,
EPA
estimated
the
in­
waterway
pollutant
concentrations
of
MP&
M
facility
discharges
for
the
baseline
and
the
final
rule
and
identified
those
reaches
in
which
MP&
M
facility
discharges
would
cause
one
or
more
pollutant
concentrations
to
exceed
ambient
water
quality
criteria
(
AWQC)
for
aquatic
species
and
human
health.
1,
2
The
change
in
the
number
of
reaches
with
concentrations
in
excess
of
AWQC
from
the
baseline
to
post­
compliance
scenarios
provides
a
quantitative
measure
of
the
improvement
in
aquatic
species
habitat
expected
to
result
from
the
final
regulation.
Chapter
15:
Recreational
Benefits
CHAPTER
CONTENTS
15.1
al
Improvements
from
the
MP&
M
Regulation
.................
.....
15­
3
15.1.1
iew
of
Ecological
Improvements
.....
15­
3
15.1.2
ication
of
Ecological
Improvements
.
.
15­
3
15.1.3
.................
...
15­
4
15.1.4
of
MP&
M
Reaches15­
6
15.2
onomic
Recreational
Benefits
........
15­
6
15.2.1
ferring
Values
from
Surface
Water
Valuation
Studies
.................
......
15­
6
15.2.2
ational
Fishing
.................
..
15­
9
15.2.3
e
Viewing
.................
....
15­
13
15.2.4
ational
Boating
.................
.
15­
17
15.2.5
nefits
.................
.....
15­
20
15.3
ary
of
Recreational
Benefits
............
15­
20
15.4
itations
and
Uncertainties
Associated
with
Estimating
Recreational
Benefits
..........
15­
22
Glossary
.................
.................
...
15­
26
Acronyms
.................
.................
..
15­
28
References
.................
.................
.
15­
29
Ecologic
Overv
Quantif
Benefiting
Reaches
Geographic
Characteristics
Valuing
Ec
Trans
Recre
Wildlif
Recre
Nonuse
Be
Summ
Lim
As
discussed
in
Chapter
12,
EPA
performed
all
benefits
analysis
on
a
basis
of
the
sample
facility
data.
The
Agency
then
extrapolated
findings
from
the
sample
facility
analyses
to
the
national
level
using
two
alternative
extrapolation
methods:
(
1)

traditional
extrapolation
and
(
2)
post­
stratification
extrapolation.
EPA
also
used
the
differential
extrapolation
technique
in
addition
to
both
traditional
and
post­
stratification
approaches
when
a
sample
reach
was
estimated
to
receive
discharges
from
multiple
facilities.
Appendix
G
provides
detailed
information
on
the
extrapolation
approaches
used
in
this
analysis.

Reducing
concentrations
of
MP&
M
pollutants
to
below
AWQC
limits
for
protection
of
aquatic
species
and
human
health
will
generate
benefits
to
users
of
water
resources
for
recreation,
including
anglers,
boaters,
and
viewers.
These
benefits
include:

 
increased
value
of
the
recreational
trip
or
day,
and
 
increased
number
of
days
that
consumers
of
water­
based
recreation
choose
to
visit
the
cleaner
waterways.

1
For
this
analysis,
a
reach
is
a
length
of
river,
shoreline,
or
coastline
on
which
a
pollutant
discharge
may
be
expected
to
have
a
relatively
uniform
effect
on
concentrations.
The
typical
length
of
a
reach
in
this
analysis
was
five
to
ten
kilometers,
although
some
were
considerably
longer.

2
AWQC
set
limits
on
pollutant
concentrations
that
are
assumed
to
be
protective
of
aquatic
life.
Pollutant
concentrations
that
exceed
AWQC
can
harm
organisms
that
live
in
or
consume
water.
MP&
M
pollutants
can
also
harm
other
organisms
that
consume
these
organisms.
These
organisms
at
risk
include
humans
who
may
recreate
in
contaminated
waters
or
consume
aquatic
organisms
living
in
them.

15­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
EPA
estimated
national
annual
recreational
use
benefits
for
three
water­
based
recreation
activities
(
i.
e.,
recreational
fishing,

boating,
and
viewing)
and
nonuse
benefits,
but
did
not
estimate
national
swimming
benefits
due
to
data
limitations.
3
EPA
estimated
the
following
recreational
use
benefits
of
the
final
MP&
M
rule
(
2001$):

 
recreational
fishing
benefits
range
from
$
287,220
to
$
923,988
and
from
$
187,123
to
$
601,976,
based
on
the
traditional
and
post­
stratification
extrapolation,
respectively;

 
near­
water
recreation
(
viewing)
benefits
range
from
$
185,172
to
$
334,315
and
from
$
120,639
to
$
217,805,
based
on
the
traditional
and
post­
stratification
extrapolation,
respectively;
and
 
boating
benefits
range
from
$
114,111
to
$
316,078
and
from
$
74,343
to
$
205,924,
based
on
the
traditional
and
post­

stratification
extrapolation,
respectively.

EPA
also
estimated
nonuse
benefits
from
improved
water
quality
in
the
nation s
surface
water
resulting
from
the
final
rule.

Empirical
estimates
from
surface
water
valuation
studies
indicate
that
nonuse
values
for
water
resources
may
be
substantial
because
people
who
do
not
use
or
expect
to
use
affected
waterways
for
recreational
or
other
purposes
may
still
value
protecting
habitats
and
species
impacted
by
effluent
discharges
(
Harpman,
et
al.,
1993;
Fisher
and
Raucher,
1984;
Brown,

1993).
The
Agency
estimated
that
nonuse
benefits
will
range
from
$
293,252
to
$
787,190
and
from
$
191,053
to
$
512,852,

based
on
the
traditional
and
post­
stratification
extrapolation,
respectively.

EPA
calculated
the
total
value
of
enhanced
water­
based
recreation
opportunities
by
summing
over
the
three
recreation
categories
and
nonuser
value.
Since
recreational
trips
corresponding
to
fishing,
boating,
and
wildlife
viewing
considered
in
this
analysis
are
stochastically
independent
(
i.
e.,
only
the
primary
activity
is
counted
on
each
trip
occasion),
benefits
from
improved
recreational
opportunities
corresponding
to
these
activities
are
additive.
The
total
annual
recreational
benefit
based
on
the
traditional
extrapolation
is
estimated
at
$
879,755
to
$
2,361,570
(
2001$),
with
a
midpoint
estimate
of
$
1,499,756
(
2001$).
Likewise,
total
annual
recreational
benefit
based
on
the
post­
stratification
extrapolation
is
estimated
at
$
573,158
to
$
1,538,557
(
2001$),
with
a
midpoint
estimate
of
$
977,087
(
2001$).

The
analysis
of
recreational
benefits
presented
in
this
chapter
uses
the
National
Demand
Study
(
NDS)
data
to
estimate
the
number
of
participants
in
wildlife
viewing
and
boating
in
the
counties
affected
by
MP&
M
discharges.
4
To
estimate
the
number
of
recreational
fishermen,
EPA
used
fishing
license
data.
The
NDS
survey
asked
respondents
to
report
the
number
of
recreational
trips
taken
annually
for
the
primary
purpose
of
boating
and
wildlife
viewing.
The
Agency
used
these
data
to
estimate
the
number
of
participants
and
the
number
of
recreational
trips
taken
annually
by
state
and
activity
type.

Appendix
N
summarizes
this
information.

EPA
chose
to
use
fish
license
data
rather
than
the
NDS
data
to
estimate
the
number
of
recreational
anglers
fishing
the
MP&
M
reaches
because
these
data
are
often
available
at
the
county
level
and
therefore
provide
location­
specific
information.

Although
the
use
of
the
NDS
and
fish
license
data
yields
similar
estimates
of
the
number
of
recreational
anglers
at
the
state
level
(
see
Chapter
21)
fish
license
data
are
likely
to
be
more
accurate
at
the
county
level.
The
use
of
the
fish
license
data
in
the
recreational
fishing
benefit
analysis
also
provides
consistency
with
other
parts
of
the
benefits
analysis
(
see
Chapters
13
and
14
for
detail).

Benefit
categories
examined
in
this
chapter
are
different
from
and
generally
do
not
overlap
with
benefits
associated
with
reduced
risk
to
human
health
discussed
in
Chapter
13.
Nevertheless,
there
is
some
likelihood
that
the
valuation
of
ecological
benefits
based
on
enhanced
recreational
fishing
overlaps
to
a
degree
with
the
valuation
of
human
health
benefits
from
reduced
cancer
risk
via
fish
consumption.

3
Fewer
water
bodies
are
designated
for
primary
contact
recreation,
such
as
swimming,
than
for
secondary
contact
recreation,
such
as
boating
and
fishing.
Assessing
recreational
swimming
benefits
requires
first
obtaining
information
on
designated
uses
of
the
sample
MP&
M
reaches
from
the
305(
b)
database.
This
analysis
was
not
feasible
due
to
resource
and
time
constraints.

4
Additional
information
on
the
NDS
survey
can
be
found
in
Chapter
21.

15­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
15.1
ECOLOGICAL
IMPROVEMENTS
FROM
THE
MP&
M
REGULATION
15.1.1
Overview
of
Ecological
Improvements
Many
M
P&
M
pollutants
can
adversely
affect
the
survival,
growth,
and
reproduction
of
aquatic
organisms.
Such
effects
are
ecologically
significant
when
they
affect
the
size,
structure,
or
function
of
populations:

 
MP&
M
pollutants
can
affect
population
size
by
reducing
prey,
and
by
affecting
development
or
reproduction
in
sensitive
life
stages
of
target
species;

 
MP
&
M
pollutants
can
alter
population
structure
by
impairing
sensitive
age
groups
or
affecting
the
development
or
maturation
rates
of
target
species;
and
 
MP&
M
pollutants
can
impact
population
function
by
decreasing
genetic
diversity
and
changing
interactions
among
different
populations
in
the
affected
areas.

MP&
M
pollutants
may
also
contaminate
fish
tissue
and
therefore
decrease
the
value
of
fishery
resources.
Thus,
the
final
MP&
M
regulation
may
generate
a
broad
range
of
ecological
effects
by
reducing
MP&
M
pollutant
discharges.
Ecological
effects
associated
with
reductions
in
MP&
M
discharges
may
include:

 
recovery
of
populations
of
aquatic
species
that
are
particularly
sensitive
to
MP&
M
pollutants;

 
decreases
in
noxious
algae,
which
affect
the
taste
and
odor
of
the
receiving
waters;

 
increases
in
the
concentrations
of
dissolved
oxygen
(
DO)
in
the
water
column;

 
improvements
in
the
natural
assimilative
capacity
of
the
affected
waterways;

 
decreases
in
fish
tissue
contamination;
and
 
terrestrial
life
benefits.

Improvements
in
aquatic
species
habitat
are
expected
to
improve
the
quality
and
value
of
water­
based
recreation
and
nonuse
values
of
the
affected
resources.
Recent
studies
valuing
recreational
fishing
showed
that
the
value
of
water
resources
for
recreational
fishing
increases
as
the
level
of
toxic
contamination
in
fish
tissue
decreases
(
Lyke,
1993;
Phaneuf
et
al.,
1998;

and
Jakus
et
al.,
1997).
Thus,
knowing
that
the
water
is
cleaner
and
does
not
contain
any
or
contains
fewer
pollutants
that
harm
humans
and
aquatic
life,
increases
individuals 
enjoyment
of
their
recreational
experience.
The
value
of
a
recreational
fishery
also
increases
from
increased
number,
size,
diversity,
and
health
of
recreational
fish
species.

Participants
in
other
water­
based
recreation,
such
as
boating
and
wildlife
viewing,
will
also
benefit
from
improved
abundance
and
diversity
of
aquatic
and
terrestrial
species.
For
example,
wildlife
viewers
may
benefit
from
improved
abundance
of
piscivorous
birds
(
e.
g.,
osprey
and
cormorants)
whose
population
is
likely
to
increase
due
to
an
increase
in
the
forage
fish
populations.
Boaters
may
benefit
from
enhanced
opportunities
for
companion
activities,
such
as
fishing
and
wildlife
viewing
(
e.
g.,
piscivorous
birds)
and
from
improved
water
clarity
and
smell.
Reducing
conventional
pollutant
loadings
will
also
improve
visual
aesthetics,
thereby
enhancing
all
water­
based
recreation
experiences.

15.1.2
Quantification
of
Ecological
Improvements
EPA
evaluated
potential
impacts
to
aquatic
life
from
the
final
MP&
M
regulation
by
estimating
in­
waterway
concentrations
of
pollutants
discharged
by
MP&
M
facilities
and
comparing
those
concentrations
within
AWQC
limits
for
protection
of
aquatic
species.
Pollutant
concentrations
in
excess
of
AWQC
limits
indicate
a
significant
detriment
to
the
aquatic
species
habitat.

EPA
expects
that
eliminating
these
exceedances
as
the
result
of
the
MP&
M
regulation
will
significantly
improve
aquatic
species
habitat
and
thus
provide
a
quantitative
measure
of
ecological
benefit
for
this
regulatory
analysis.

15­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
For
this
analysis,
EPA
estimated
in­
waterway
concentrations
for
all
MP&
M
pollutants
for
which
AWQC
limits
are
available.

Of
the
132
MP&
M
pollutants
of
concern,
AWQC
values
are
available
for
114
pollutants.
5
Table
I.
3
in
Appendix
I
lists
the
pollutants
evaluated
in
this
analysis
and
their
acute
and
chronic
aquatic
life
AWQC.
The
acute
value
is
the
maximum
allowable
one­
hour
average
concentration
at
any
time
at
which
aquatic
life
can
survive.
The
chronic
value
is
the
average
concentration
of
a
toxic
pollutant
over
a
four­
day
period
at
which
aquatic
life
is
not
unacceptably
affected.
The
endpoints
of
concern
are
one
or
more
sub­
lethal
responses,
such
as
changes
in
reproduction
or
growth
in
the
affected
organisms.
The
chronic
levels
should
not
be
exceeded
more
than
once
every
three
years.

EPA
used
the
mixing
and
dilution
methods
outlined
in
Appendix
I
to
estimate
the
in­
waterway
concentrations
resulting
from
MP&
M
facility
discharges.
Acute
and
chronic
exposure
concentrations
for
each
pollutant
are
calculated
on
the
basis
of
7Q10
and
1Q10
stream
flow
rates,
where
7Q10
is
the
lowest
consecutive
seven­
day
average
flow
with
a
recurrence
interval
of
ten
years,
and
1Q10
is
the
lowest
one­
day
average
flow
with
a
recurrence
interval
of
ten
years.
For
reaches
to
which
more
than
one
sample
MP&
M
facility
discharge,
EPA
summed
the
discharge
values
by
pollutant
for
all
known
sample
facilities
discharging
to
the
reach.

EPA
first
identified
the
MP&
M
discharge
reaches
in
which
MP&
M
discharges
alone
caused
one
or
more
pollutant
concentrations
to
exceed
AWQC
limits
for
aquatic
species
under
the
baseline
discharge
level.
If
concentrations
of
all
MP&
M
pollutants
exceeding
the
limits
in
the
baseline
fell
below
AWQC
limits
as
a
result
of
the
final
rule,
then
aquatic
species
habitat
conditions
on
that
discharge
reach
would
likely
improve
significantly
as
a
result
of
the
final
regulation.
The
final
regulation
would
result
in
partial
aquatic
habitat
improvements
if
concentrations
of
some,
but
not
all,
MP&
M
pollutants
fell
below
their
AW
QC
limits.
Although
not
explicitly
accounted
for
in
this
analysis,
species
habitat
conditions
are
likely
to
improve
whenever
in­
waterway
concentrations
are
reduced,
regardless
of
whether
or
not
they
fall
to
levels
below
aquatic
AWQC.

EPA s
analysis
based
on
the
traditional
extrapolation
method
indicates
that
pollutant
concentrations
at
current
industry
discharge
levels
exceed
acute
exposure
criteria
for
protection
of
aquatic
species
on
18
receiving
reaches,
and
exceed
chronic
exposure
criteria
for
protection
of
aquatic
species
on
353
receiving
reaches.
6
EPA
estimates
that
the
final
rule
would
eliminate
concentrations
in
excess
of
the
acute
aquatic
life
exposure
criteria
on
nine
reaches,
and
would
eliminate
concentrations
in
excess
of
the
chronic
aquatic
life
exposure
criteria
on
nine
reaches.

Similarly,
EPA s
analysis
based
on
the
post­
stratification
extrapolation
method
indicates
that
baseline
pollutant
concentrations
at
current
industry
discharge
levels
exceed
acute
exposure
criteria
for
protection
of
aquatic
species
on
15
reaches,
and
exceed
chronic
exposure
criteria
for
protection
of
aquatic
species
on
350
reaches.
EPA
estimates
that
the
final
rule
would
eliminate
concentrations
in
excess
of
the
acute
aquatic
life
exposure
criteria
on
six
reaches,
and
would
eliminate
concentrations
in
excess
of
the
chronic
aquatic
life
exposure
criteria
on
six
reaches.
Table
15.1
summarizes
these
results.

15.1.3
Benefiting
Reaches
As
a
first
step
in
estimating
the
monetary
value
of
improvements
in
the
aquatic
habitats
affected
by
MP&
M
discharges
from
the
final
MP&
M
rule,
EPA
identified
reaches
that
are
likely
to
experience
significant
water
quality
improvements
from
reduced
MP&
M
discharges
due
to
the
final
MP&
M
rule
(
hereafter,
benefiting
reaches).
A
reach
is
considered
to
benefit
from
the
MP&
M
rule
if
at
least
one
AWQC
exceedance
is
eliminated
due
to
reduced
MP&
M
discharges.
This
approach
differs
from
some
past
approaches
where
EPA
took
credit
for
pollution
reductions
only
in
cases
where
all
AWQC
exceedances
are
eliminated.
EPA
believes
that
the
latter
approach
significantly
underestimates
benefits
from
reduced
pollutant
discharges.

This
analysis
combines
two
AWQC
calculation
procedures:

 
analysis
of
in­
waterway
concentrations
relative
to
human
health
AWQC
limits
described
in
Chapter
13,7
and
5
Facilities
in
the
Oily
Wastes
subcategory
discharge
122
of
the
132
POCs
evaluated.
See
Chapter
12
for
detail.

6
This
analysis
used
baseline
pollutant
loads
for
direct
and
indirect
dischargers
belonging
to
all
subcategories
considered
for
regulation.

7
Although
EPA
estimated
the
value
of
reduced
cancer
risk
from
consumption
of
contaminated
fish
tissue,
the
Agency
was
unable
to
estimate
the
value
of
reduced
systemic
risk
from
consumption
of
fish
caught
in
the
reaches
affected
by
MP&
M
discharges
(
see
Chapter
13).

The
recreational
benefits
analysis
presented
in
the
following
sections
assumes
that
some
of
the
value
of
reduced
systemic
health
risk
is
implicitly
captured
in
the
increased
value
of
water
resources
from
reduced
occurrence
of
human
health­
based
AWQC
exceedances.
For
15­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
 
analysis
of
in­
waterway
concentrations
relative
to
aquatic
life
AWQC
limits
described
in
the
preceding
section
of
this
chapter.

Table
15.1
summarizes
the
number
of
reaches
with
estimated
baseline
concentrations
that
exceed
AWQC
limits
for
either
human
health
or
aquatic
species,
and
the
number
of
those
reaches
where
the
regulation
is
estimated
to
eliminate
or
reduce
exceedances.
Based
on
the
traditional
extrapolation,
the
combined
analysis
over
all
AWQC
limit
categories
(
i.
e.,
acute
and
chronic
aquatic
life
and
human
health)
indicates
that
MP&
M
pollutant
concentrations
would
exceed
at
least
one
AWQC
limit
on
395
reaches
as
the
result
of
baseline
MP&
M
discharges.
The
expected
discharge
reductions
from
the
final
rule
eliminate
exceedances
on
nine
of
these
discharge
reaches,
leaving
386
reaches
with
concentrations
of
one
or
more
pollutants
that
exceed
AW
QC
limits.

Likewise,
based
on
the
post­
stratification
extrapolation,
the
combined
analysis
indicates
that
MP&
M
pollutant
concentrations
would
exceed
at
least
one
AWQC
limit
on
426
reaches
as
the
result
of
baseline
MP&
M
discharges.
The
expected
discharge
reductions
from
the
final
rule
eliminate
exceedances
on
six
of
these
discharge
reaches,
leaving
420
reaches
with
concentrations
of
one
or
more
pollutants
that
exceed
AWQC
limits.

EPA
assigned
full
benefits
in
situations
where
the
rule
eliminates
all
AWQC
exceedances
and
partial
benefits
where
the
rule
eliminates
one
or
more,
but
not
all,
AWQC
exceedances.
EPA
calculates
partial
benefits
as
the
ratio
of
the
AWQC
exceedances
removed
by
reducing
MP&
M
discharges
to
the
total
number
of
AWQC
exceedances
caused
by
MP&
M
facilities
in
the
baseline.
For
example,
if
the
MP&
M
rule
removes
seven
out
of
a
total
ten
baseline
AWQC
exceedances
on
a
benefiting
reach,
the
Agency
attributes
a
70
percent
benefit
to
the
MP&
M
regulation,
where
100
percent
would
represent
an
 
AWQC
exceedance­
free 
level.

Table
15.1:
Estimated
MP&
M
Discharge
Reaches
with
MP&
M
Pollutant
Concentrations
in
Excess
of
AWQC
Limits
for
Protection
of
Aquatic
Species
or
Human
Health
Regulatory
Status
Number
of
Reaches
with
Concentrations
Exceeding
AWQC
Limits
Total
Number
of
Reaches
with
Concentrations
Exceeding
AWQC
Limits
Number
of
Benefiting
Reaches
AWQC
Limits
for
Aquatic
Species
AWQC
Limits
for
Human
Health
All
AWQC
Exceedances
Eliminated
Reaches
with
Some
Exceedances
EliminatedAcute
Chronic
H20
and
Organisms
Organisms
Only
Selected
Option:
Traditional
Extrapolation
Baseline
18
353
78
21
395
N/
A
N/
A
Final
Option
9
344
78
21
386
9
0
Selected
Option:
Post­
Stratification
Extrapolation
Baseline
15
350
112
21
426
N/
A
N/
A
Final
Option
9
344
112
21
420
6
0
Note:
In
the
baseline,
the
total
number
of
reaches
with
concentrations
exceeding
AWQC
limits
does
not
equal
the
sum
of
the
numbers
in
the
separate
analysis
categories
because
some
reaches
were
estimated
to
have
concentrations
in
excess
of
AWQC
limits
for
more
than
one
analysis
category.

Source:
U.
S.
EPA
analysis
Surface
water
valuation
studies
show
that
benefits
from
partial
improvements
are
likely
to
be
considerable.
For
example,

Carson
and
M
itchell
(
1993)
found
that
almost
nine
out
of
ten
individuals
indicated
that
 
halfway 
improvements
are
worth
the
same
as
a
complete
improvement
in
water
quality.
The
remaining
one
out
of
ten
individuals
were
willing
to
pay
a
reduced
amount
for
partial
improvements
in
water
quality.

example,
some
studies
showed
that
anglers
place
a
much
higher
value
on
fishery
resources
that
are
safe
for
consumption
(
Lyke,
1993
and
Phaneuf,
1997).

15­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
The
effects
of
partially
removing
AWQC
exceedances,
however,
are
difficult
to
generalize.
The
overall
improvement
in
surface
water
quality
from
reduced
toxic
loadings
will
depend
on
the
amount
and
duration
of
exceedances,
together
with
the
kinds
of
chemical(
s)
that
are
removed
from
the
mixture
by
regulatory
action.
AWQC
are
developed
on
a
chemical­
by­
chemical
basis;
they
are
not
designed
to
assess
the
toxicity
of
multiple
chemicals.
In
most
cases,
the
toxicities
of
chemicals
in
a
mixture
are
considered
additive
(
i.
e.,
the
total
toxicity
is
the
sum
of
the
toxicities
of
the
individual
chemicals).

Total
toxicity
decreases
by
the
amount
of
a
chemical
removed
from
the
mixture.
Benefits
to
sensitive
aquatic
species
(
i.
e.,

amphibians,
fish,
benthic
invertebrates,
zooplankton)
could
occur
if
the
concentration
of
one
chemical
fell
below
its
AWQC
even
when
two
or
more
other
chemicals
still
were
at
or
exceeding
their
respective
AWQC.
The
reason
is
that
the
total
toxic
pressure
in
the
receiving
water
decreases
so
that
a
smaller
fraction
of
the
most
sensitive
species
remain
affected.
For
example,
consider
a
case
in
which
three
chemicals
exceeding
their
chronic
AWQC
adversely
affect
7
percent
of
all
aquatic
species
in
a
receiving
water.
If
certain
species
are
particularly
sensitive
to
one
of
the
three
chemicals,
then
eliminating
the
AWQC
exceedance
for
this
chemical
would
lower
the
percentage
of
sensitive
species
being
adversely
affected.

15.1.4
Geographic
Characteristics
of
MP&
M
Reaches
EPA
cannot
identify
all
of
the
specific
reaches
affected
by
MP&
M
facilities
that
reduce
discharges
under
the
final
rule
because
location
is
known
only
for
the
facilities
included
in
the
random
stratified
sample.
EPA
assumes
that
facilities
represented
by
the
sample
facility
have
the
same
environmental
and
geographic
characteristics
that
affect
benefits
from
the
final
rule.
These
characteristics
include
water
body
type
and
physical
characteristics
(
e.
g.,
stream
flow
conditions),

populations
residing
near
the
water
body,
and
the
number
of
potential
recreational
users
affected.

The
analysis
of
the
sample
reach
locations
indicates
that
sample
MP&
M
reaches
tend
to
be
located
in
heavily
populated
areas.

For
example,
approximately
35
percent
of
sample
reaches
receiving
discharges
from
sample
MP&
M
direct
dischargers
are
located
adjacent
to
counties
with
populations
of
at
least
500
thousand
residents.
These
reaches
have
a
greater
number
of
potential
recreational
users
than
do
reaches
in
less
populated
areas.

15.2
VALUING
ECONOMIC
RECREATIONAL
BENEFITS
The
final
MP&
M
rule
will
improve
aquatic
habitats
by
reducing
concentrations
of
priority
(
i.
e.,
toxic),
nonconventional,

and
conventional
pollutants
in
water.
In
turn,
these
improvements
will
enhance
the
quality
and
value
of
water­
based
recreation,
such
as
fishing,
wildlife
viewing,
camping,
waterfowl
hunting,
and
boating.
The
Agency
used
the
estimated
increase
in
the
monetary
value
of
recreational
opportunities
for
fishing,
boating,
and
wildlife
viewing
as
a
partial
measure
of
the
economic
benefit
to
society
from
the
improvements
to
aquatic
species
habitat
expected
to
result
from
the
final
MP&
M
regulation.
The
Agency
also
estimated
nonuse
benefits
from
improvements
in
aquatic
habitats
and
ecosystems
that
are
affected
by
the
MP&
M
industry
discharges.

This
analysis
uses
a
benefits
transfer
approach
to
monetize
changes
in
water
resource
recreational
values
for
reaches
affected
by
MP&
M
discharges.
8
This
approach
builds
upon
an
analysis
of
applicable
surface
water
valuation
literature
to
estimate
the
total
WTP
value
(
including
both
use
and
nonuse
values)
for
improvements
in
surface
water
quality.

15.2.1
Transferring
Values
from
Surface
Water
Valuation
Studies
EPA
identified
several
surface
water
evaluation
studies
that
quantified
the
effects
of
water
quality
improvements
on
various
water­
based
recreational
activities.
The
Agency
used
the
following
technical
criteria
for
evaluating
study
transferability
(
Boyle
and
Bergstrom,
1990):

 
The
environmental
change
valued
at
the
study
site
must
be
the
same
as
the
environmental
quality
change
caused
by
the
rule
(
e.
g.,
changes
in
toxic
contamination
vs
changes
in
turbidity);

 
The
populations
affected
at
the
study
site
and
at
the
policy
site
must
be
the
same
(
e.
g.,
recreational
users
vs
nonusers);

8
Benefits
transfer
involves
the
application
of
value
estimates,
functions,
and/
or
models
developed
in
one
context
to
address
a
similar
resource
valuation
question
in
another
context.

15­
6
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
 
The
assignment
of
property
rights
at
both
sites
must
lead
to
the
same
theoretically
appropriate
welfare
measure
(
e.
g.,

willingness­
to­
pay
vs
willingness
to
accept
compensation).

In
addition
to
the
above
criteria,
the
Agency
considered
authors'
recommendations
regarding
robustness
and
theoretical
soundness
of
various
estimates.

Existing
studies
are
unlikely
to
meet
all
of
the
above
criteria.
Boyle
and
Bergstrom
(
1990)
reported
that
most
researchers
will
likely
encounter
problems
with
at
least
one
criterion.
This
analysis
is
no
exception.
The
major
limitation
in
performing
the
national
analysis
is
the
comparability
of
the
water
quality
changes
considered
in
the
original
studies
with
the
water
quality
changes
considered
in
this
analysis.
These
comparisons
are
discussed
below.

The
Agency
used
eight
of
the
most
comparable
studies
and
calculated
the
changes
in
recreation
values
resulting
from
water
quality
improvements
(
as
a
percentage
of
the
baseline
value)
implied
by
those
studies.
EPA
took
a
simple
mean
of
upper­
and
lower­
bound
estimates
from
these
studies
to
derive
a
range
of
percentage
changes
in
the
water
resource
values
due
to
water
quality
improvements.
The
studies
used
for
benefits
transfer
in
the
MP&
M
regulatory
analysis
included
Lyke
(
1993),
Jakus
et
al.
(
1997),
Montgomery
and
Needelman
(
1997),
Phaneuf
et
al.
(
1998),
Desvousges
et
al.
(
1987),
Lant
and
Roberts
(
1990),

Farber
and
Griner
(
2000),
and
Tudor
et
al.
(
2002).
Appendix
K
presents
WTP
values
for
various
water
quality
improvements
and
summarizes
EPA s
reasoning
for
selecting
specific
WTP
estimates
for
benefits
transfer.
Each
of
the
eight
studies
and
the
WTP
values
selected
for
benefits
transfer
are
discussed
briefly
below.

Lyke s
(
1993)
study
of
the
Wisconsin
Great
Lakes
open
water
sport
fishery
showed
that
anglers
may
place
a
significantly
higher
value
on
a
contaminant­
free
fishery
than
on
one
with
some
level
of
contamination.
Lyke
estimated
the
value
of
the
fishery
to
Great
Lakes
trout
and
salmon
anglers
if
it
were
improved
enough
to
be
"
completely
free
of
contaminants
that
may
threaten
human
health,"
and
found
that
this
value
would
add
between
11
and
31
percent
of
the
fishery s
current
value.

Jakus
et
al.
(
1997)
used
a
repeated
discrete
choice
travel
cost
(
TC)
model
to
examine
the
impacts
of
sport­
fishing
consumption
advisories
in
eastern
Tennessee.
The
model
controlled
for
anglers 
knowledge
of
advisories,
the
type
of
angler
(
i.
e.,
fish
consumption
vs.
catch
and
release),
and
catch
rate.
The
estimated
welfare
gain
(
as
a
percentage
of
baseline)
from
cleaning
up
six
reservoirs
and
removing
these
advisories
ranges
from
six
to
8
percent.
These
estimates
are
below
Lyke s
estimated
11
to
31
percent
range,
due
to
the
difference
in
methodology
used.
The
TC
method
captures
use
values
only,
while
the
combined
TC
and
stated
preferences
method
used
in
Lyke
captures
both
the
use
and
nonuse
components
of
the
resource
value
to
users.
Differences
in
the
fisheries
and
user
populations
may
also
affect
the
estimated
percentage
changes
in
the
resource
value.

Montgomery
and
Needelman
(
1997)
estimated
benefits
from
removing
 
toxic 
contamination
from
lakes
and
ponds
in
New
York
State.
They
used
a
binary
variable
as
their
primary
water
quality
measure,
which
indicates
whether
the
New
York
Department
of
Environmental
Conservation
considers
water
quality
in
a
given
lake
to
be
impaired
by
toxic
pollutants.
The
model
controls
for
major
causes
of
impairments
other
than
 
toxic 
pollutants
to
separate
the
effects
of
various
pollution
problems
that
affect
the
fishing
experience.
The
estimates
from
Montgomery
and
Needelman
imply
that
removing
 
toxic 

impairments
in
all
New
York
lakes
and
ponds
would
increase
recreational
fishing
value
by
13.7
percent.

Phaneuf
et
al.
(
1998)
studied
angling
in
the
Wisconsin
Great
Lakes.
They
estimated
changes
in
recreational
fishing
values
resulting
from
a
20
percent
reduction
of
toxin
levels
in
lake
trout
flesh.
The
study
uses
a
TC
model
to
value
water
quality
improvements
when
corner
solutions
are
present
in
the
data.
Corner
solutions
arise
when
consumers
visit
only
a
subset
of
the
available
recreation
sites,
setting
their
demand
to
zero
for
the
remaining
sites.
Phaneuf
et
al.
found
that
improved
industrial
and
municipal
waste
management
results
in
general
water
quality
improvement.
This
improvement
leads
in
turn
to
a
20
percent
decrease
in
fish
tissue
toxin
levels,
yielding
a
welfare
gain
of
$
166.21
(
2001$)
per
angler
per
year.
9
This
estimate
implies
that
recreational
fishing
values
would
increase
by
approximately
27.5
to
34.3
percent
from
reduced
toxin
levels.
This
analysis
estimates
use
values
only.

Desvousges
et
al.
(
1987)
used
findings
from
a
contingent
valuation
(
CV)
survey
to
estimate
WTP
for
improved
recreational
fishing
from
enhanced
water
quality
in
the
Pennsylvania
portion
of
the
Monongahela
River.
In
a
hypothetical
market,
each
survey
respondent
was
asked
to
provide
an
option
price
for
different
water
quality
changes,
including
 
raising
9
The
study
used
the
1989
survey
data
on
recreational
angling
in
Wisconsin s
Great
Lakes.
Therefore,
this
analysis
assumes
that
all
estimates
in
the
original
study
are
in
1989
dollars.

15­
7
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
the
water
quality
from
suitable
for
boating
(
hereafter,
 
boatable 
water)
to
a
level
where
gamefish
would
survive
(
hereafter,

 
fishable 
water). 

In
applying
Desvousges
et
al.
for
the
MP&
M
analysis,
EPA
assumed
that
reaches
with
AWQC
exceedences
under
the
baseline
conditions
are
likely
to
support
rough
fishing
but
may
not
be
clean
enough
to
support
gamefishing.
Removing
AWQC
exceedences
is
therefore
comparable
to
shifting
water
quality
from
"
boatable"
to
"
fishable."
This
is
a
relatively
conservative
assumption.
Desvousges
et
al.
found
that
improving
water
quality
from
 
boatable 
to
 
fishable 
would
yield
a
5.9
to
7.9
percent
increase
in
water
resource
value
to
recreational
anglers.

Lant
and
Roberts
(
1990)
used
a
CV
study
to
estimate
the
recreational
and
nonuse
benefits
of
improved
water
quality
in
selected
Iowa
and
Illinois
river
basins.
River
quality
was
defined
by
means
of
an
interval
scale
of
 
poor, 
 
fair, 
 
good, 
and
 
excellent. 
The
authors
defined
 
fair 
water
quality
as
adequate
for
boating
and
rough
fishing
and
 
good 
water
quality
as
adequate
for
gamefishing.

For
the
MP&
M
analysis,
EPA
assumes
that
eliminating
AWQC
exceedences
is
roughly
equivalent
to
shifting
water
quality
from
"
fair"
to
"
good."
The
estimates
from
this
study
imply
an
increase
of
9.7
to
13.1
percent
in
recreational
fishing
value
from
improving
water
quality
from
 
fair 
to
 
good. 

Farber
and
Griner
(
2000)
used
a
CV
study
to
estimate
changes
in
water
resource
values
to
users
from
various
improvements
in
water
quality
in
Pennsylvania.
The
study
defines
water
quality
as
 
polluted, 
 
moderately
polluted, 
and
 
unpolluted 

based
on
a
water
quality
scale
developed
by
EPA
Region
III:
 
Polluted 
streams
are
unable
to
support
aquatic
life;

 
moderately
polluted 
streams
are
somewhat
unable
to
support
aquatic
life;
and
 
unpolluted 
streams
adequately
support
aquatic
life.
Streams
unable
to
support
aquatic
life
(
i.
e.,
"
polluted")
are
likely
to
be
affected
by
environmental
stressors
unrelated
to
MP&
M
discharges,
such
as
acidity
or
severe
oxygen
depletion.

The
MP&
M
analysis
assumes
that
most
streams
affected
by
MP&
M
facility
discharges
are
moderately
polluted;
i.
e.,
these
streams
support
aquatic
life,
but
sensitive
species
may
be
adversely
affected
by
MP&
M
pollutants
that
exceed
AWQC
values
protective
of
aquatic
life.
Removing
all
AWQC
exceedences
would
make
such
streams
unpolluted.
The
estimates
from
this
study
imply
that
improving
water
quality
from
 
moderately
polluted 
to
 
unpolluted 
would
yield
an
increase
in
recreation
fishery
value
ranging
from
3.9
to
9
percent.

Tudor
et
al.
(
2002)
used
a
TC
model
to
estimate
changes
in
water
resource
recreation
values
resulting
from
eliminating
10
MP&
M
pollutant
concentrations
in
excess
of
AWQC
limits
at
recreation
sites
in
Ohio.
The
study
involves
four
recreation
activities
­­
fishing,
boating,
near­
water
recreation,
and
swimming
­­
and
covers
most
recreationally­
important
water
bodies
in
all
Ohio
counties.
The
study
considers
two
types
of
water
quality
effects
from
MP&
M
pollutants
on
consumers 
decisions
to
visit
a
particular
water
body:

(
1)
visible
or
otherwise
perceivable
effects
(
e.
g.,
turbidity
and
odor);
and
(
2)
"
toxic"
effects
that
are
not
directly
perceivable
by
consumers.

Because
priority
and
nonconventional
pollutants
at
high
enough
concentrations
may
adversely
affect
aquatic
species,
 
toxic 

effects
may
be
indirectly
observable
via
species
abundance
and
diversity.
The
study
uses
a
dummy
variable
to
account
for
effects
of
"
toxic"
MP&
M
pollutants,
identifying
recreation
sites
at
which
estimated
concentrations
of
one
or
more
MP&
M
pollutants
exceed
AWQC
for
protection
of
aquatic
life.
The
study
estimated
that
eliminating
AWQC
exceedances
and
reducing
TKN
concentrations
would
yield
per
trip
benefits
of
$
1.34,
$
1.78,
$.
60,
and
$
0.33
(
2001$)
from
improved
fishing,

boating,
wildlife
viewing,
and
swimming
opportunities,
respectively.
The
estimated
changes
in
the
recreational
use
value
of
Ohio
water
resources,
are
0.77,
1.67,
and
0.77
percent
for
fishing,
boating,
and
wildlife
viewing,
respectively.
This
analysis
estimates
use
values
only.

With
the
exception
of
the
Tudor
et
al.
(
2002)
study,
the
types
of
water
quality
changes
assessed
in
these
studies
are
only
roughly
comparable
to
those
studied
in
the
MP&
M
analysis.
Whereas
the
analysis
of
the
final
MP&
M
regulation
and
Tudor
et
al.
(
2002)
assessed
the
impact
of
eliminating
AWQC
exceedances,
the
other
studies
used
other
measures
of
water
quality
improvement.
EPA
addressed
the
differences
in
measurement
between
the
other
studies
and
the
MP&
M
analysis
by
linking
10
Preliminary
results
of
this
study
were
presented
at
the
annual
American
Agricultural
Economic
Association
meeting
(
Tudor
et
al.,
1999a)
and
at
the
annual
Northeastern
Agricultural
and
Resource
Economic
Association
Meeting
(
Tudor
et
al.,
1999b).
EPA
subjected
this
study
to
a
formal
peer
review
by
experts
in
the
natural
resource
valuation
field.
The
peer
review
concluded
that
EPA
had
done
a
competent
job,
especially
given
the
available
data.
This
study
can
be
found
in
Chapter
21.
The
peer
review
report
is
in
the
docket
for
the
rule.

15­
8
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
water
quality
changes
expected
from
the
MP&
M
regulation
to
the
type
of
water
quality
changes
assessed
in
the
other
studies.

EPA
assumed
that
eliminating
AWQC
exceedances
is
roughly
comparable
to
the
following
discrete
water
quality
changes:
11
 
 
achieving
a
contaminant
free
fishery; 

 
reducing
the
level
of
toxins
in
fish
tissue;

 
removing
fish
consumption
advisories
(
FCA);
and
 
improving
water
quality
from
 
boatable 
to
 
fishable, 
from
 
fair 
to
 
good, 
and
from
 
moderately
polluted 
to
 
unpolluted. 

The
MP&
M
analysis
uses
the
estimates
derived
from
the
eight
surface
water
evaluation
studies
described
above
to
calculate
a
range
of
national
WTP
values.
The
following
sections
present
the
methodology
and
relevant
values
used
to
estimate
the
value
of
improved
fishing,
wildlife
viewing,
and
boating
opportunities
resulting
from
the
MP&
M
regulation.

15.2.2
Recreational
Fishing
The
MP&
M
rule
will
improve
the
recreational
angling
experience
by
reducing
concentrations
of
priority,
nonconventional,

and
conventional
contaminants
in
water.
EPA
estimated
the
benefits
of
these
reductions
by
estimating:

 
the
number
of
recreational
fishing
days
on
benefiting
reaches;

 
the
baseline
fishery
value
of
each
benefiting
reach;
and
 
changes
in
recreational
fishery
value,
using
values
from
the
available
surface
water
valuation
studies.

a.
Number
of
recreational
fishing
days
EPA
calculated
the
annual
number
of
person­
days
of
recreational
fishing
for
each
benefiting
reach
using
a
two­
step
approach:

 
Participating
population
The
geographic
area
from
which
anglers
would
travel
to
fish
a
reach
is
assumed
to
include
only
those
counties
that
abut
a
given
reach.
As
noted
in
Chapter
13,
this
assumption
is
based
on
the
finding
in
the
1991
N
ational
Survey
of
Fishing,
Hunting,

and
W
ildlife­
Associated
Recreation
that
65
percent
of
anglers
travel
less
than
50
miles
to
fish
(
U.
S.
Department
of
the
Interior,
1993).
ND
S
data
showed
that
recreational
anglers
travel
from
20
to
66
miles
to
their
destination,
with
an
average
one­
way
travel
distance
of
30
miles.
12,13
EPA
estimated
the
population
participating
in
recreational
fishing
using
the
number
of
licensed
fishermen
in
counties
bordering
MP&
M
discharge
reaches
using
the
following
steps:

 
assume
that
fishing
activity
among
these
anglers
is
distributed
evenly
among
all
reach
miles
within
those
counties;

 
compute
the
length
of
the
MP&
M
reach
as
a
percentage
of
total
reach
miles
within
corresponding
counties;

 
multiply
the
estimated
ratio
by
the
total
fishing
population
in
counties
abutting
the
reach
to
estimate
the
number
of
anglers
who
may
fish
an
MP
&
M
reach;
and
11
Section
15.1.3
discusses
a
method
used
for
estimating
partial
water
quality
improvements.

12
See
Chapter
21
for
detail
on
the
NDS
data.

13
These
estimates
exclude
outliers.

15­
9
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
 
reduce
the
number
of
anglers
by
20
percent
in
reaches
where
MP&
M
and
other
pollutants
have
required
a
fish
consumption
advisory.
This
reduction
is
an
estimate
of
angler
response
to
the
presence
of
a
fish
consumption
advisory.
14
 
Average
number
of
fishing
days
Anglers
generally
participate
in
recreational
fishing
several
times
a
year.
The
U.
S.
Fish
and
Wildlife
Service
(
FWS)

provides
estimates
of
the
average
number
of
fishing
days
per
angler
in
each
state.
The
FWS
estimates
range
from
10.5
days
per
angler
in
Arizona
to
21.1
days
per
angler
in
Alabama
for
freshwater
fishing,
and
7.3
days
per
angler
in
Louisiana
to
18.7
days
per
angler
in
Virginia
for
saltwater
fishing.
15
EPA
calculated
the
total
number
of
angler
days
by
multiplying
the
number
of
recreational
anglers
for
each
benefiting
reach
by
the
average
number
of
fishing
days
for
the
reach
(
based
on
the
state
in
which
the
reach
is
located).

b.
Baseline
fishery
value
The
net
value
of
a
recreational
fishing
day
is
the
total
value
of
the
fishing
day
exclusive
of
any
fishing­
related
costs
(
e.
g.,

license
fees,
travel
costs,
bait,
tackle,
charter
boats,
etc.)
incurred
by
the
angler.

EPA
used
two
recreational
fishing
valuation
studies
(
Bergstrom
and
Cordell
(
1991)
and
Walsh
et
al.
(
1992))
to
calculate
the
net
economic
value
per
recreational
fishing
day
under
the
baseline
conditions.
Both
studies
used
a
meta­
analysis
of
recreational
fishery
valuation
studies
to
estimate
per­
day
values
of
the
three
types
of
recreational
fishing:
warmwater,

coldwater,
and
anadromous.
Based
on
the
two
studies,
EPA
developed
an
average
per­
day
value
for
each
type
of
recreational
fishing.
This
analysis
uses
low
and
high
average
benefit
values
for
fishing
days
of
$
28.11
and
$
60.43
(
2001$)
to
estimate
a
range
of
the
baseline
fishery
values.

Table
15.2:
Baseline
Values
of
Fishing
Fishery
Type
Per­
day
Value
(
2001$)
a
Average
Per­
day
Value
(
2001$)
Bergstrom
and
Cordell
(
1991)
b
Walsh
et
al.

(
1992)
c
Warmwater
$
19.52
$
36.70
$
28.11
Coldwater
$
27.77
$
47.71
$
37.74
Anadromous
$
36.73
$
84.15
$
60.43
Range
of
above
$
28.11
­
$
60.43
a
Original
study
values
were
adjusted
to
2001
dollars
based
on
the
relative
change
in
CPI
from
1987
to
2001.

b
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
TC
studies.
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
CV
and
TC
studies.

Source:
U.
S.
EPA
analysis
EPA
calculated
the
total
baseline
value
for
each
fishery
located
on
a
benefiting
reach
by
multiplying
the
estimated
net
value
of
a
recreational
fishing
day
by
the
total
number
of
fishing
days
calculated
in
subsection
(
a)
above.
Applying
facility
weights
and
summing
over
all
benefiting
reaches
provides
a
total
baseline
recreational
fishing
value
for
MP&
M
reaches
expected
to
benefit
from
the
elimination
of
pollutant
concentrations
in
excess
of
AWQC
limits.

14
See
Belton
et
al.
(
1986),
Knuth
and
Velicer
(
1990),
Silverman
(
1990),
West
(
1989),
Connelly
et
al.
(
1992),
and
Connelly
and
Knuth
(
1993)
for
more
information
on
angler
response
to
fish
advisories.

15
These
averages
reflect
participation
levels
in
the
48
contiguous
states.
No
sample
facility
is
located
in
Hawaii
or
Alaska.

15­
10
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
c.
Changes
in
recreational
fishery
value
Expected
benefits
from
the
final
MP&
M
regulation
include
an
increase
in
the
quality
of
an
angler s
recreational
opportunities
and/
or
the
number
of
days
an
angler
chooses
to
fish
each
season.

EPA
assumes
that
the
expected
welfare
gain
for
recreational
anglers
is
a
function
of
changes
in
the
overall
quality
of
all
recreational
opportunities
available
to
each
angler.
Recreational
anglers
residing
in
the
counties
abutting
MP&
M
reaches
will
therefore
benefit
from
improved
recreational
opportunities
whether
or
not
they
actually
visit
an
MP&
M
reach.

EPA
used
the
eight
studies
discussed
above
to
calculate
the
changes
in
recreation
values
from
water
quality
improvements
(
as
a
percentage
of
baseline)
implied
by
those
studies.
Table
15.3
compiles
information
on
the
baseline
values,
values
of
changes
in
water
quality,
and
percentage
changes
in
values
reported
or
implied
by
these
studies.

15­
11
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.3:
Studies
Estimating
Changes
in
Value
of
a
Recreational
Fishery
Study
Type
of
Water
Quality
Change
Valued
Baseline
Value
of
Recreational
Angling
(
2001$)
Value
of
Water
Quality
Change
(
2001$)
Value
of
Change
as
%
of
Baseline
Type
of
Benefits
Included
Lyke
(
1993)
Fish
tissue
is
completely
free
of
toxic
contaminants
that
may
threaten
human
health
$
95.0­$
119.0
million
per
year
a
$
10.5­$
37.1
million
per
year
a
11%
­
31%
a
Use
and
nonuse
values
for
recreational
anglers
Jakus
et
al.

(
1997)
Lifting
FCAs
$
26.0­$
52.6
per
trip
$
2.0­$
3.2
per
trip
6.0%
­
8.0%
Use
values
for
recreational
anglers
Montgomery
and
Needelman
(
1997)
Elimination
of
toxic
impairment
$
656.6
per
angler
per
year
b
$
90.3
per
angler
per
year
13.7%
Use
values
for
recreational
anglers
Phaneuf
at
al.

(
1998)
20%
reduction
of
toxic
contamination
in
trout
flesh
$
484.5
­
$
605.8
per
angler
per
year
a
$
166.2
per
angler
per
year
27.5%
­
34.3%
Use
values
for
recreational
anglers
Desvousges
et
al.
(
1987)
Improvement
from
 
boatable 
to
 
fishable 
$
28.11­
$
37.73
per
trip
c
$
2.21
per
trip
d
5.9%
­
7.9%
Recreational
and
nonuse
values
to
users
Lant
and
Roberts
(
1990)
Improvement
from
 
fair 
to
 
good 
$
28.11­
$
37.73
per
trip
c
$
3.67
per
trip
e
9.7%
­
13.1%
Recreational
and
nonuse
values
to
users
Farber
and
Griner
(
2000)
Improvement
from
 
moderately
polluted 

to
 
unpolluted 
$
28.11­
$
37.73
per
trip
c
$
1.49­$
2.55
per
trip
f
3.9%
­
9.0%
Recreational
use
values
to
users
and
nonusers
Tudor
et
al.
(
2002)
g
Elimination
of
AWQC
exceedances
$
173.34
per
trip
$
1.34
per
trip
0.77%
Use
values
for
recreational
anglers
Average
percentage
change
in
recreational
fishery
value
(
based
on
above
studies)
h
9.8%
­
14.7
%
Recreational
and
nonuse
values
to
users
a
The
baseline
fishery
value
for
the
study
site
location
is
based
on
the
baseline
fishery
value
reported
in
Lyke
(
1993).
The
study
used
data
from
two
mail
surveys
conducted
in
1989
at
the
University
of
Wisconsin­
Madison.
These
surveys
were
originally
used
by
Lyke
(
1993).

b
Based
on
the
average
value
for
a
coldwater
fishing
day
of
$
37.74
(
see
Table
15.2),
multiplied
by
the
average
number
of
freshwater
(
non­
Great
Lakes)
angling
days
per
year
in
New
York
State
(
17.4
days,
USFWS,
1996).

Range
based
on
the
range
of
values
for
a
fishing
day
used
in
this
analysis
(
see
Table
15.2);

d
Based
on
the
value
of
water
quality
improvement
of
$
36.79
per
year
(
updated
from
1987
dollars
reported
in
Desvousges
et
al.,
1987).

divided
by
the
average
number
of
freshwater
angling
days
per
year
in
Pennsylvania
(
16.6
days,
USFWS,
1996).

e
Based
on
the
value
of
water
quality
improvement
of
$
57.81
per
year
(
updated
from
1990
dollars
reported
in
Lant
and
Roberts)
divided
by
the
average
number
of
freshwater
angling
days
per
year
in
Iowa
and
Illinois
(
16.6
and
15.5
days,
USFWS,
1996).

f
Based
on
the
values
of
water
quality
improvements
ranging
from
$
24.55
to
$
41.93
per
year
reported
in
Farber
and
Griner
(
2000),

divided
by
the
average
number
of
freshwater
angling
days
per
year
in
Pennsylvania
(
16.6
days,
USFWS,
1996).

g
See
Chapter
21
of
this
report
for
detail.
The
baseline
value
of
recreational
fishery
is
based
on
the
estimated
mean
value
of
water
resources
for
recreational
anglers
reported
by
Tudor
et
al.
(
2002).
The
estimated
median
value
of
recreational
fishing
is
$
175.48.
These
values
were
derived
from
a
September
23,
2002
analysis.

h
EPA
took
a
simple
mean
of
lower­
and
upper­
bound
estimates
from
the
eight
studies
to
calculate
a
range
of
percentage
changes
in
the
recreational
fishery
value
from
improved
water
quality
conditions.
When
only
one
value
is
available
from
the
study
(
i.
e.,
Tudor
et
al.,

2002),
EPA
used
this
value
in
calculating
both
the
lower­
and
upper­
bound
estimates.

Source:
U.
S.
EPA
analysis
EPA
used
the
percentage
change
in
the
fishery
value
implied
by
the
eight
studies
to
estimate
increased
recreational
fishing
values
for
all
MP&
M
reaches
in
which
the
regulation
eliminates
AWQC
exceedances
of
one
or
more
MP&
M
pollutants.
That
is,
the
Agency
estimated
benefits
for
all
MP&
M
discharge
reaches
where
at
least
one
AWQC
exceedance
is
eliminated
due
to
reduced
MP&
M
discharges.
As
noted
above,
EPA
took
a
simple
mean
of
lower­
and
upper­
bound
estimates
from
the
eight
studies
described
above
to
calculate
a
range
of
percentage
changes
in
the
recreational
fishery
value
from
reduced
MP&
M
discharges.
These
studies
yielded
estimates
of
increased
value
ranging
from
9.8
to
14.7
percent.
Multiplying
these
15­
12
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
percentages
by
the
baseline
value
of
fisheries
located
on
benefiting
reaches
yielded
a
range
of
benefits
from
eliminating
pollutant
concentrations
in
excess
of
AWQC
limits.

Table
15.4
below
summarizes
the
results
of
EPA s
recreational
fishing
benefits
analysis.

Table
15.4:
Summary
of
Recreational
Fishing
Benefits
(
2001$)

Number
of
Benefiting
Reaches
Participating
Population
(
millions)
Average
Number
of
Fishing
Days
Total
Angler
Days
(
millions)
Baseline
Fishery
Value/
Rec.

Day
Baseline
Fishery
Value
($
millions)
%
Change
in
Fishery
Value
MP&
M
Benefits
Selected
Option:
Traditional
Extrapolation
Low
Estimate
9
0.98
17.3
16.98
$
28.11
$
477
9.8%
$
287,220
High
Estimate
9
0.98
17.3
16.98
$
60.43
$
1,026
14.7%
$
923,988
Selected
Option:
Post­
Stratification
Extrapolation
Low
Estimate
6
1.08
17.2
18.61
$
28.11
$
523
9.8%
$
187,123
High
Estimate
6
1.08
17.2
18.61
$
60.43
$
1,125
14.7%
$
601,976
Source:
U.
S.
EPA
analysis
15.2.3
Wildlife
Viewing
EPA
expects
that
water
quality
improvements
from
the
MP&
M
regulation
will
decrease
the
uptake
of
pollutants
through
aquatic
food
chains.
These
changes
are
expected
to
increase
the
health
and
reproductive
success
of
sensitive
wildlife
species
that
feed
on
fish
and
other
aquatic
organisms.
In
particular,
Piscivorous
(
i.
e.,
fish­
eating)
bird
species
such
as
the
osprey
(
Pandion
haliaetus),
bald
eagle
(
Haliaeetus
leucocephalus),
great
blue
heron
(
Ardeidae
herodias),
mergansers
(
Merginae
sp.),
and
cormorants
(
Phalacrocorax
sp.)
will
benefit
from
increased
numbers,
size,
and
health
of
forage
fish.
Increased
food
and
lower
pollutant
levels
in
fish
flesh
will
improve
reproduction
in
these
birds,
leading
to
healthier
and
larger
bird
populations.
Reducing
conventional
pollutant
loadings
will
also
improve
visual
aesthetics,
thereby
enhancing
wildlife
viewing
and
other
near­
water­
based
recreation
experiences,
such
as
photography,
camping,
picnicking,
and
waterfowl
hunting
(
hereafter,
this
discussion
refers
to
all
of
these
activities
as
 
wildlife
viewing ).

As
with
the
recreational
fishing
analysis,
EPA
assumes
that
the
expected
welfare
gain
for
consumers
of
viewing
activities
is
a
function
of
changes
in
the
overall
quality
of
all
recreational
opportunities
available
to
each
consumer.
Consumers
of
water­

based
recreation
residing
in
the
counties
abutting
MP&
M
reaches
are
therefore
likely
to
benefit
from
improved
recreational
opportunities
whether
or
not
they
actually
visit
an
MP&
M
reach.

EPA
estimated
wildlife
viewing
benefits
using
an
approach
similar
to
that
used
in
estimating
recreational
fishing
benefits.

EPA
estimated:

 
the
number
of
wildlife
viewing
days
on
benefiting
reaches;

 
the
baseline
value
of
wildlife
viewing
for
each
benefiting
reach;
and
 
changes
in
wildlife
viewing
value,
using
values
from
the
available
surface
water
valuation
studies.

15­
13
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
a.
Number
of
wildlife
viewing
days
EPA
calculated
the
annual
number
of
person­
days
of
wildlife
viewing
for
each
benefiting
reach
using
a
two­
step
approach:

 
Participating
population
The
analysis
of
the
NDS
data
showed
that
participants
in
viewing
activities
travel
from
16
to
117
miles
to
their
destination,

with
an
average
one­
way
travel
distance
of
34
miles.
16
EPA
therefore
assumes
that
improvements
in
recreational
opportunities
will
benefit
only
recreational
users
residing
within
the
counties
abutting
MP&
M
reaches.
EPA
estimated
the
population
participating
in
viewing
activities
using
the
number
of
water­
based
recreation
consumers
residing
in
the
counties
traversed
by
benefiting
reaches
using
the
following
steps:

 
estimate
resident
populations
in
the
counties
traversed
by
the
benefiting
reaches
using
Census
data;

 
calculate
the
number
of
wildlife
viewing
participants
based
on
the
percent
of
the
population
engaged
in
wildlife
viewing
activities;

 
estimate
the
percentage
of
individuals
that
participate
in
wildlife
viewing
in
each
state
using
NDS
data.
The
total
state
population
participating
in
wildlife
viewing
ranges
from
8.6
percent
in
New
Mexico
to
44.4
percent
in
Maine;

and
 
adjust
the
number
of
wildlife
viewing
participants
within
the
affected
county
based
on
the
ratio
of
the
affected
reach
length
to
the
number
of
total
reach
miles
in
the
affected
county
to
calculate
the
population
potentially
benefiting
from
the
rule.
17,18
 
Average
number
of
viewing
days
Recreators
generally
participate
in
wildlife
viewing
several
times
a
year.
The
Agency
used
NDS
data
on
the
number
of
wildlife
viewing
trips
to
estimate
the
average
number
of
user
days
in
each
state.
The
NDS
data
show
that
the
number
of
wildlife
viewing
trips
in
the
48
states
range
from
1.8
days
per
user
in
South
Dakota
to
24.2
days
per
user
in
Mississippi.
19
EPA
multiplied
the
number
of
wildlife
viewing
consumers
by
estimates
of
the
average
number
of
days
per
user
in
each
state
to
estimate
the
annual
number
of
user
days
for
each
benefiting
MP&
M
reach.

b.
Baseline
value
of
wildlife
viewing
EPA
estimated
the
baseline
value
of
wildlife
viewing
for
the
benefiting
reaches
based
on
the
estimated
annual
person­
days
calculated
in
subsection
(
a)
above
and
the
estimated
value
per
person­
day
of
wildlife
viewing.

EPA
used
two
recreational
activity
valuation
studies
(
Bergstrom
and
Cordell
(
1991)
and
Walsh
et
al.
(
1992))
to
calculate
the
net
economic
values
per
wildlife
viewing
day.
These
studies
estimate
net
benefit
values
for
four
recreational
activities:

wildlife
viewing,
waterfowl
hunting,
camping,
and
picnicking.
Based
on
the
two
studies,
EPA
developed
an
average
per­
day
value
for
three
of
the
four
activities.
20
EPA s
MP&
M
benefits
analysis
uses
the
lowest
average
benefit
value,
$
22.73,
for
the
low
estimate
of
wildlife
viewing
benefits
and
the
highest
average
value,
$
28.73,
for
the
high
estimate.
Table
15.5
presents
information
on
the
relevant
values
reported
in
these
studies.

Using
facility
sample
weights
and
summing
over
all
benefiting
reaches
provides
the
total
baseline
value
of
wildlife
viewing
for
MP&
M
reaches
that
EPA
expects
to
benefit
by
eliminating
pollutant
concentrations
in
excess
of
AWQC
limits.

16
These
estimates
exclude
outliers.

17
Information
in
EPA's
Reach
File
1
indicates
that
the
ratio
of
affected
reach
length
to
the
total
number
of
reach
miles
within
a
county
ranges
from
0.02
to
0.39.

18
This
analysis
assumes
that
recreation
activities
among
residents
of
the
counties
affected
by
MP&
M
discharges
are
distributed
evenly
across
all
reach
miles
within
those
counties.

19
See
Chapter
21
for
details
on
the
NDS
data.

20
EPA
excluded
the
per­
day
value
of
waterfowl
hunting
($
55.53)
from
the
activities
included
in
this
analysis,
because
this
activity
is
limited
to
designated
hunting
areas
only.

15­
14
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.5:
Baseline
Values
of
Wildlife
Viewing
Recreational
Activity
Per­
day
Value
(
2001$)
a
Average
Per­
day
Value
(
2001$)
Bergstrom
and
Cordell
(
1991)
b
Walsh
et
al.

(
1992)
c
Camping
$
27.10
$
30.38
$
28.73
Picnicking
$
18.46
$
27.00
$
22.73
Near­
water
Activities
$
20.07
$
34.59
$
27.33
Range
of
above
$
22.73
­
$
28.73
a
Original
study
values
were
adjusted
to
2001
dollars
based
on
the
relative
change
in
CPI
from
1987
to
2001.

b
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
TC
studies.
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
contingent
valuation
(
CV)
and
TC
studies.

Source:
U.
S.
EPA
analysis
c.
Changes
in
wildlife
viewing
value
EPA
selected
a
subset
of
the
candidate
benefits
transfer
studies
discussed
in
Section
15.2.1
to
estimate
changes
in
water
resource
value
to
wildlife
viewers
due
to
the
MP&
M
rule.
The
four
selected
studies
include
Tudor
et
al.
(
2002),
Desvousges
et
al.
(
1987),
Lant
and
Roberts
(
1990),
and
Farber
and
Griner
(
2000)
21
.
Table
15.6
compiles
information
on
the
baseline
values
of
wildlife
viewing,
values
of
changes
in
water
quality,
and
percentage
change
in
values
reported
or
implied
by
these
studies.

21
The
remaining
four
studies
value
changes
in
the
value
recreational
fishing
only.

15­
15
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.6:
Studies
Estimating
Changes
in
Value
of
Wildlife
Viewing
Study
Water
Quality
Change
Valued
Baseline
Value
of
Wildlife
Viewing
(
2001$)
Value
of
Water
Quality
Change
(
2001$)
Value
of
Change
as
%
of
Baseline
Type
of
Benefits
Included
Desvousges
et
al.
(
1987)
Improvement
from
 
boatable 
to
 
fishable 
$
22.8
­
$
28.7
per
trip
a
$
5.00
per
trip
b
17.4%
­
22.0%
Recreational
and
nonuse
values
to
users
Lant
and
Roberts
(
1990)
Improvement
from
 
fair 
to
 
good 
$
22.8
­
$
28.7
per
trip
a
$
8.60
per
trip
c
29.9%
­
37.8%
Recreational
and
nonuse
values
to
users
Farber
and
Griner
(
2000)
Improvement
from
 
moderately
polluted 

to
 
unpolluted 
$
22.8
­
$
28.7
per
trip
a
$
3.33
­
$
5.69
per
trip
d
11.6%
­
25.0%
Recreational
and
nonuse
values
to
users
Tudor
et
al.
(
2002)
Elimination
of
AWQC
exceedances
$
77.99
per
trip
e
$
0.60
per
trip
0.77%
Recreational
use
values
to
users
Average
percentage
change
(
based
on
the
above
studies)
f
14.9%
­
21.3%

a
Based
on
the
range
of
median
values
for
a
near­
water
recreation
day
(
updated
to
2001
dollars)
reported
in
Walsh
et
al.
(
1992)
and
Bergstrom
and
Cordell
(
1991)
(
see
Table15.5).

b
Based
on
the
value
of
water
quality
improvement
of
$
36.79
per
person
per
year
(
updated
from
1987
dollars
reported
in
Desvousges
et
al.)
divided
by
the
average
number
of
near­
water
recreation
days
per
year
in
Pennsylvania
(
7.37
days,
NDS,
1993).
Based
on
the
value
of
water
quality
improvement
of
$
57.79
per
year
(
updated
from
1990
dollars)
reported
in
Lant
and
Roberts
divided
by
the
average
number
of
near­
water
recreation
days
per
year
in
Iowa
and
Illinois
(
9.58
and
5.04
days,
NDS,
1993).

d
Based
on
the
value
of
water
quality
improvements
ranging
from
$
24.55
to
$
41.93
per
person
per
year
reported
in
Farber
and
Griner
(
2000)
divided
by
the
average
number
of
near­
water
recreation
days
per
year
in
Pennsylvania
(
7.37
days,
NDS,
1993).

e
The
baseline
value
of
viewing
is
based
on
the
estimated
mean
value
of
water
resources
for
wildlife
viewers
reported
by
Tudor
et
al.
(
2002).
The
estimated
median
value
of
recreational
fishing
is
$
82.77.
These
values
were
derived
from
a
September
23,
2002
analysis.

f
EPA
took
a
simple
mean
of
lower­
and
upper­
bound
estimates
from
the
four
studies
to
calculate
a
range
of
percentage
changes
in
the
wildlife
viewing
value
from
improved
water
quality
conditions.
When
only
one
value
is
available
from
the
study
(
i.
e.,
Tudor
et
al.,

2002),
EPA
used
this
value
in
calculating
both
the
lower­
and
upper­
bound
estimates.

Source:
U.
S.
EPA
analysis
This
analysis
uses
the
change
of
14.9
percent
for
the
low
benefits
estimate
and
21.3
percent
for
the
high
benefits
estimate
to
calculate
benefits
from
reduced
M
P&
M
facility
discharges
to
users
of
water­
based
recreation.
These
values
represent
the
average
of
the
low
and
high
values,
respectively,
estimated
in
the
four
studies.

Table
15.7
below
summarizes
the
results
of
EPA s
wildlife
viewing
benefits
analysis.

15­
16
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.7:
Summary
of
Wildlife
Viewing
Benefits
(
2001$)

Number
of
Benefiting
Reaches
Participating
Population
(
millions)
Ave.

Number
of
Viewing
Days
Total
Viewing
Days
(
millions)
Baseline
Value/
Rec.

Day
Total
Baseline
Value
($
millions)
%
Change
in
Value
Benefit
from
MP&
M
Selected
Option:
Traditional
Extrapolation
Low
Estimate
9
3.12
7.5
23.52
$
22.73
$
535
14.9%
$
185,172
High
Estimate
9
3.12
7.5
23.52
$
28.73
$
676
21.3%
$
334,315
Selected
Option:
Post­
Stratification
Extrapolation
Low
Estimate
6
3.17
7.5
23.91
$
22.73
$
544
14.9%
$
120,639
High
Estimate
6
3.17
7.5
23.91
$
28.73
$
687
21.3%
$
217,805
Source:
U.
S.
EPA
analysis.

15.2.4
Recreational
Boating
Improvements
in
water
quality
from
the
final
MP&
M
rule
may
enhance
recreational
boating
by
(
1)
providing
more
opportunities
for
companion
activities
(
e.
g.,
fishing
and
wildlife
viewing)
and
(
2)
improving
visual
aesthetics.
EPA
assumes
that
the
expected
welfare
gain
for
boaters
is
a
function
of
changes
in
the
overall
quality
of
all
recreational
opportunities
available
to
each
boater
on
a
given
day.

This
analysis
estimates
recreational
boating
benefits
the
same
way
as
recreational
fishing
and
wildlife
viewing
benefits.
The
analysis
estimates:

 
the
number
of
recreational
boating
days
on
benefiting
reaches,

 
the
baseline
value
of
boating
for
each
benefiting
reach,
and
 
changes
in
recreational
boating
value.

a.
Number
of
recreational
boating
days
EPA
calculated
the
annual
number
of
recreational
boating
days
for
each
benefiting
reach
using
two
steps:

 
Participating
population
The
analysis
of
the
NDS
data
showed
that
boaters
travel
from
10
to
108
miles
to
their
destination,
with
an
average
one­
way
travel
distance
of
32
miles.
22
This
analysis
therefore
considers
only
boaters
residing
in
the
counties
abutting
MP&
M
reaches.

EPA
estimated
the
number
of
boaters
residing
in
the
counties
traversed
by
benefiting
reaches
by
combining
information
from
Census
data
and
NDS
data
on
the
proportion
of
individuals
participating
in
boating
in
each
state.
The
percent
of
the
total
state
population
in
the
48
states
participating
in
boating
ranges
from
8.0
percent
in
Colorado
to
28.7
percent
in
Washington.

EPA
further
adjusted
the
number
of
boaters
likely
to
use
MP&
M
reaches
within
the
affected
county
based
on
the
ratio
of
the
affected
reach
length
to
the
number
of
total
reach
miles
in
the
affected
county.
23
22
These
estimates
exclude
outliers.

23
See
section
13.1.1
for
detail.

15­
17
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
 
Average
number
of
boating
days
People
using
benefiting
reaches
for
boating
generally
participate
in
this
activity
several
times
per
year.
The
NDS
data
show
the
number
of
boating
trips
in
the
48
states
ranging
from
3.2
days
per
user
in
New
Hampshire
to
14.6
days
per
user
in
Colorado.

EPA
estimated
the
annual
number
of
user
days
for
recreational
boating
activities
by
multiplying
the
number
of
boaters
by
the
average
number
of
boating
days
per
user
in
each
state.

b.
Baseline
value
of
boating
EPA
estimated
the
baseline
value
of
boating
on
benefiting
reaches
using
the
estimated
annual
person­
days
of
boating
per
reach
and
estimated
values
per
person­
day
of
various
types
of
boating.
EPA
calculated
a
range
of
net
economic
values
per
recreation
day
of
boating
based
on
studies
by
Bergstrom
and
Cordell
(
1991)
and
Walsh
et
al.
(
1992).
Mean
net
benefit
values
for
motorized
and
non­
motorized
boating
are
$
37.30
to
$
59.26
in
2001
dollars.
Table
15.8
compiles
information
on
the
relevant
values
reported
in
these
studies.

Table
15.8:
Baseline
Values
of
a
Boating
Day
Recreational
Activity
Per­
day
Value
(
2001$)
a
Average
Per­
day
Value
(
2001$)
Bergstrom
and
Cordell
(
1991)
b
Walsh
et
al.
(
1992)
c
Motorized
$
25.43
$
49.18
$
37.30
Non­
motorized
$
42.67
$
75.85
$
59.26
Boating
(
any
type)
$
37.30
­
$
59.26
a
Original
study
values
were
adjusted
to
2001
dollars
based
on
the
relative
change
in
CPI
from
1987
to
2001.

b
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
TC
studies.
Study
location:
various
U.
S.
locations.
Estimating
approach:
meta­
analysis
of
CV
and
TC
studies.

Source:
U.
S.
EPA
analysis
Weighting
by
facility
sample
weights
and
summing
over
all
benefiting
reaches
provides
a
total
baseline
value
of
boating
for
MP&
M
reaches
expected
to
benefit
by
eliminating
pollutant
concentrations
in
excess
of
AWQC
limits.

c.
Changes
in
recreational
boating
values
The
Agency
used
the
same
four
studies
discussed
in
Section
15.2.3
to
calculate
the
change
in
per­
day
boating
value
as
a
result
of
water
quality
improvements.
EPA
expressed
this
change
as
a
percentage
of
the
baseline
value.
Table
15.9
compiles
information
on
the
baseline
values
of
boating,
values
of
changes
in
water
quality,
and
percentage
change
in
boating
values
reported
or
implied
by
these
studies.

15­
18
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.9:
Studies
Estimating
Changes
in
Value
of
Recreational
Boating
Study
Water
Quality
Change
Valued
Baseline
Value
of
Boating
(
2001$)
Value
of
Water
Quality
Change
(
2001$)
Value
of
Change
as
%
of
Baseline
Type
of
Benefits
Included
Desvousges
et
al.
(
1987)
Improvement
from
 
boatable 
to
 
fishable 
$
37.30
­
$
59.26
per
trip
a
$
3.92
per
trip
b
6.6%
­
10.5%
Recreational
and
nonuse
values
to
users
Lant
and
Roberts
(
1990)
Improvement
from
 
fair 
to
 
good 
$
37.30
­
$
59.26
per
trip
a
$
7.91
per
trip
c
13.3%
­
21.2%
Recreational
use
values
to
users
and
nonusers
Farber
and
Griner
(
2000)
Improvement
from
 
moderately
polluted 
to
 
unpolluted 
$
37.30
­
$
59.26
per
trip
a
$
2.62
­
$
4.48
per
trip
d
4.4%­
12.0%
Recreational
and
nonuse
values
to
users
Tudor
et
al.

(
2002)
Elimination
of
AWQC
exceedances
$
106.60
per
trip
e
$
1.78
pr
trip
1.67%
Recreational
values
for
users
Average
percentage
change
(
based
on
the
above
studies)
f
6.5%
­
11.4%

a
Based
on
the
average
value
for
a
boating
day
(
updated
to
2001
dollars)
reported
in
Walsh
et
al.
(
1992)
and
Bergstrom
and
Cordell
(
1991).

b
Based
on
the
value
of
water
quality
improvement
of
$
36.79
per
person
per
year
(
updated
from
1987
dollars)
reported
in
Desvousges
et
al.
divided
by
the
average
number
of
boating
days
per
year
in
Pennsylvania
(
9.37
days,
NDS,
1993).
Based
on
the
value
of
water
quality
improvement
of
$
57.79
per
person
per
year
(
updated
from
1990
dollars)
reported
in
Lant
and
Roberts
divided
by
the
average
number
of
boating
days
per
year
in
Iowa
and
Illinois
(
9.58
and
5.04
days,
NDS,
1993).

d
Based
on
the
value
of
water
quality
improvements
ranging
from
$
24.55
to
$
41.93
per
person
per
year
reported
in
Farber
and
Griner
(
2000)
divided
by
the
average
number
of
boating
days
per
year
in
Pennsylvania
(
9.37
days,
NDS,
1993).

e
The
baseline
value
of
boating
is
based
on
the
estimated
mean
value
of
water
resources
for
boaters
reported
by
Tudor
et
al.
(
2002).
The
estimated
median
value
of
recreational
boating
is
$
112.55.
These
values
were
derived
from
a
September
23,
2002
analysis.

f
EPA
took
a
simple
mean
of
lower­
and
upper­
bound
estimates
from
the
four
studies
described
to
calculate
a
range
of
percentage
changes
in
the
recreational
boating
value
from
improved
water
quality.
When
only
one
value
is
available
from
the
study
(
i.
e.,
Tudor
et
al.,
2002),
EPA
used
this
value
in
calculating
both
the
lower­
and
upper­
bound
estimates.

Source:
U.
S.
EPA
analysis
This
analysis
uses
the
change
of
6.5
percent
for
the
low
benefits
estimate
and
11.4
percent
for
the
high
benefits
estimate
to
calculate
benefits
to
boaters
from
reduced
M
P&
M
facility
discharges.
These
values
represent
the
average
of
the
low
and
high
values,
respectively,
estimated
in
the
four
studies.

Table
15.10
summarizes
the
results
of
EPA s
recreational
boating
benefits
analysis.

15­
19
c
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.10:
Summary
of
Recreational
Boating
Benefits
(
2001$)

Number
of
Benefiting
Reaches
Participating
Population
(
millions)
Ave.

Number
of
Boating
Days
Total
Boating
Days
(
millions)
Baseline
Value/
Rec.

Day
Total
Baseline
Value
($
millions)
%
Change
in
Value
MP&
M
Benefits
Selected
Option:
Traditional
Extrapolation
Low
Estimate
9
2.53
8.3
21.06
$
37.30
$
786
6.5%
$
114,111
High
Estimate
9
2.53
8.3
21.06
$
59.26
$
1,249
11.4%
$
316,078
Selected
Option:
Post­
Stratification
Extrapolation
Low
Estimate
6
2.57
8.4
21.47
$
37.30
$
801
6.5%
$
74,343
High
Estimate
6
2.57
8.4
21.47
$
59.26
$
1,272
11.4%
$
205,924
Source:
U.
S.
EPA
analysis.

15.2.5
Nonuse
Benefits
EPA
estimated
changes
in
nonuse
values
for
this
analysis
because
nonuse
value
is
a
sizeable
portion
of
the
total
value
of
water
resources.
Individuals
who
never
visit
or
otherwise
use
a
natural
resource
may
still
be
affected
by
changes
in
its
status
or
quality.
Empirical
estimates
indicate
that
such
"
nonuse
values"
may
be
substantial
for
some
resources
(
Harpman
et
al.,
1993;

Fisher
and
Raucher,
1984;
Brown,
1993).
Most
studies
have
found
that
nonuse
values
exceed
use
values.
Brown
reviewed
31
CV
studies
in
which
both
use
and
nonuse
values
were
estimated,
and
calculated
the
ratio
of
nonuse
values
to
use
values
(
Brown,
1993).
The
goal
of
Brown s
study
was
to
assess
consistency
of
ratios
of
use
to
nonuse
value
and
to
develop
a
basis
for
obtaining
a
rough
estimate
of
nonuse
value,
and
therefore
total
values,
for
the
many
studies
that
measured
only
use
values.

His
31
estimated
ratios
range
from
0.1
to
10,
with
the
median
ratio
of
1.92.
The
ratios
of
nonuse
to
use
values
reported
by
Brown
for
the
studies
that
valued
environmental
improvements
in
water
resources
range
for
users
of
those
resources
from
0.85
to
2.56.
The
estimated
average
ratio
is
1.57.
That
is,
for
every
dollar
of
annual
use­
benefit
value
to
users
of
the
subject
environmental
resource,
the
annual
nonuse
value
to
resource
users
for
the
subject
environmental
resource
is
$
1.57.

Carson
and
Mitchell
suggested
that
nonuse
benefits
account
for
19
to
39
percent
of
total
WTP
values
for
water
quality
improvements
depending
on
the
definition
of
nonuse
values
(
Carson
and
Mitchell,
1993).
The
ratio
of
nonuse
to
use
value
ranges
from
one­
fourth
to
two­
thirds
based
on
the
Carson
and
Mitchell
study
(
1993).
Fisher
and
Raucher
(
1984)
found
that
nonuse
benefits
comprise
one­
half
of
recreational
use
benefits.

EPA
used
findings
from
the
Fisher
and
Raucher
(
1984)
study
in
which
nonuse
values
are
estimated
to
be
equal
to
50
percent
of
use
values
to
estimate
nonuse
benefits
from
the
final
MP&
M
regulation.
The
method
has
long
been
used
by
EPA
as
a
pragmatic
alternative
to
omitting
nonuse
values
entirely.
EPA
acknowledges
that
this
method
is
crude
and
nonuse
values
estimated
by
the
50
percent
of
use
value
approach
are
quite
low
given
the
applicable
literature
discussed
above.

The
Agency
estimates
that
nonuse
benefits
from
the
final
MP&
M
rule
will
range
from
$
293,252
to
$
787,190
and
from
$
191,053
to
$
512,852,
based
on
the
traditional
and
post­
stratification
extrapolation,
respectively.

15.3
SUMMARY
OF
RECREATIONAL
BENEFITS
EPA
assumes
that
eliminating
concentrations
of
MP&
M
pollutants
in
excess
of
AWQC
limits
will
achieve
water
quality
protective
of
aquatic
life
and
human
health.
This
improved
water
quality
then
generates
benefits
for
both
users
and
nonusers
of
water­
based
recreation.
These
benefits
can
be
seen
as
an
increase
in
the
value
of
each
day
spent
on
or
near
the
waterway,

as
well
as
an
increase
in
the
number
of
days
spent
on
or
near
the
waterway.
EPA
estimated
the
monetary
value
of
improved
water­
based
recreational
opportunity
for
the
9
discharge
reaches
based
on
the
traditional
extrapolation
(
6
reaches
based
on
the
post­
stratification
extrapolation)
for
which
concentrations
in
excess
of
AWQC
limits
would
be
eliminated.

15­
20
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
EPA
first
estimated
the
number
of
recreational
days
on
benefiting
reaches
for
each
water­
based
activity.
The
Agency
then
calculated
the
baseline
value
of
these
activities
and
then
calculated
the
percentage
changes
in
this
value
stemming
from
water
quality
improvements.

EPA
calculated
partial
benefits
for
reaches
with
reduced
numbers
of
AWQC
exceedances
by
adjusting
the
percentage
increase
in
the
recreational
value
of
these
reaches.
EPA
made
these
adjustments
based
on
the
ratio
of
the
number
of
AWQC
exceedances
eliminated
post­
compliance
to
the
number
of
AWQC
exceedances
occurring
at
baseline.

Table
15.11
summarizes
benefit
estimates
by
recreational
category
for
the
final
rule
based
on
the
traditional
and
post­

stratification
extrapolation
methods.
The
activities
considered
in
this
analysis
are
stochastically
independent;
EPA
calculated
the
total
value
of
enhanced
water­
based
recreation
opportunities
by
summing
over
the
three
recreation
categories.
EPA
also
estimated
the
changes
in
nonuse
value
resulting
from
reduced
MP&
M
discharges
based
on
the
ratio
of
use
to
nonuse
values
implied
by
the
Fisher
and
Raucher
study
(
Fisher
and
Raucher,
1984).
Based
on
the
traditional
extrapolation,
the
estimated
increase
in
nonuse
value
ranges
from
$
0.29
to
$
0.79
million
(
2001$),
with
a
midpoint
value
of
$
0.50
million
(
2001$).
The
resulting
increased
value
of
recreational
activities
to
consumers
(
users
and
nonusers)
of
water­
based
recreation
ranges
from
an
estimated
$
0.59
to
$
1.57
million
(
2001$)
annually.
The
estimated
mean
value
of
recreational
benefits
is
$
1.00
million
(
2001$)
annually.
Likewise,
based
on
the
post­
stratification
extrapolation,
the
estimated
increase
in
nonuse
value
ranges
from
$
0.19
to
$
0.51
million
(
2001$),
with
a
midpoint
value
of
$
0.33
million
(
2001$).
The
resulting
increased
value
of
recreational
activities
to
consumers
(
users
and
nonusers)
of
water­
based
recreation
ranges
from
an
estimated
$
0.38
to
$
1.03
million
(
2001$)
annually.
The
estimated
mean
value
of
recreational
benefits
is
$
0.65
million
(
2001$)
annually.

Tables
15.12
and
15.13
summarize
benefit
estimates
for
the
433
Upgrade
Options
and
Proposed/
NODA
Option,
respectively.

Recreational
use
and
nonuse
benefits
are
almost
200
times
higher
under
the
two
433
Upgrade
Options,
and
over
430
times
higher
under
the
Proposed/
NO
DA
O
ption.

Table
15.11:
Estimated
Recreational
Benefits
from
Reduced
MP&
M
Discharges
(
Thousands,
2001$)

Recreational
Activity
Traditional
Extrapolation
Post­
Stratification
Extrapolation
Low
Value
Midpoint
Value
High
Value
Low
Value
Midpoint
Value
High
Value
Fishing
$
287
$
537
$
924
$
187
$
350
$
602
Boating
$
114
$
203
$
316
$
74
$
132
$
206
Viewing
and
near­
water
activities
$
185
$
260
$
334
$
121
$
169
$
218
Total
Recreational
Use
Benefits
$
587
$
1,000
$
1,574
$
382
$
651
$
1,026
Nonuse
Benefits
(
½
of
the
Recreational
Use
Benefits)
$
293
$
500
$
787
$
191
$
326
$
513
Total
Recreational
Benefits
$
880
$
1,500
$
2,362
$
573
$
977
$
1,539
Source:
U.
S.
EPA
analysis.

15­
21
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.12:
Estimated
Recreational
Benefits
from
Reduced
MP&
M
Discharges
(
Thousands,
2001$)
a
Recreational
Activity
Directs
+
413
to
433
Upgrade
Directs
+
All
to
433
Upgrade
Low
Value
Midpoint
Value
High
Value
Low
Value
Midpoint
Value
High
Value
Fishing
$
28,713
$
53,703
$
92,369
$
29,052
$
54,337
$
93,460
Boating
$
36,511
$
64,854
$
101,134
$
36,652
$
65,103
$
101,523
Viewing
and
near­
water
activities
$
56,584
$
79,434
$
102,158
$
56,657
$
79,536
$
102,290
Total
Recreational
Use
Benefits
$
121,808
$
197,990
$
295,661
$
122,360
$
198,976
$
297,272
Nonuse
Benefits
(
½
of
the
Recreational
Use
Benefits)
$
60,904
$
98,995
$
147,831
$
61,180
$
99,488
$
148,636
Total
Recreational
Benefits
$
182,712
$
296,986
$
443,492
$
183,541
$
298,464
$
445,908
a
Based
on
the
Traditional
Extrapolation.

Source:
U.
S.
EPA
analysis.

Table
15.13:
Estimated
Recreational
Benefits
from
Reduced
MP&
M
Discharges
(
Thousands,
2001$)
a
Recreational
Activity
Proposed/
NOD
A
Optionb
Low
Value
Midpoint
Value
High
Value
Fishing
$
53,897
$
100,805
$
173,386
Boating
$
75,847
$
134,724
$
210,089
Viewing
and
near­
water
activities
$
140,623
$
197,410
$
253,884
Total
Recreational
Use
Benefits
$
270,366
$
432,939
$
637,360
Nonuse
Benefits
(
½
of
the
Recreational
Use
Benefits)
$
135,183
$
216,469
$
318,680
Total
Recreational
Benefits
$
405,550
$
649,408
$
956,040
a
Based
on
the
Traditional
Extrapolation.

b
The
estimated
recreational
benefits
of
the
Proposed/
NODA
Option
are
not
directly
comparable
to
the
final
option
alternatives.
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
two
upgrade
options.
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
performed
no
more
analysis
on
the
NODA
option,
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

Source:
U.
S.
EPA
analysis.

15.4
LIMITATIONS
AND
UNCERTAINTIES
ASSOCIATED
WITH
ESTIMATING
RECREATIONAL
BENEFITS
EPA
assessed
recreational
benefits
in
terms
of
reduced
occurrence
of
pollutant
concentrations
exceeding
acute
and
chronic
toxic
effect
levels
for
aquatic
species.
EPA
also
attached
a
monetary
value
to
ecological
improvements
expected
to
result
from
the
MP&
M
regulation,
in
the
form
of
the
increased
value
of
three
water­
based
recreation
activities
recreational
fishing,

wildlife
viewing,
and
boating
plus
the
increase
in
nonuse
value.
The
estimated
increase
in
value
detailed
in
this
chapter
constitutes
only
a
partial
measure
of
the
value
to
society
of
improving
aquatic
habitats
and
aquatic
life.
This
benefits
analysis
is
limited
because
it
ignores
improvements
to
recreational
activities
other
than
fishing,
boating,
and
wildlife
viewing
(
e.
g.,

swimming),
as
well
as
non­
recreational
benefits,
such
as
increased
assimilative
capacity
and
improvements
in
the
taste
and
odor
of
the
affected
waters.

15­
22
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
The
methodologies
used
to
assess
ecological
benefits
also
involved
significant
simplifications
and
uncertainties,
whose
combined
effect
on
the
estimated
benefits
is
not
known.
Estimated
economic
values
may
be
under­
or
overestimated.
Some
of
these
simplifications
and
uncertainties
also
apply
to
the
human
health
benefits
analysis,
and
have
been
discussed
at
length
in
the
previous
chapter,
including
those
associated
with:

 
developing
the
sample
of
MP&
M
facilities
analyzed
in
the
EEBA,

 
estimating
in­
waterway
concentrations
of
MP&
M
pollutants,

 
considering
background
concentrations
of
MP&
M
pollutants,
and
 
considering
downstream
effects.

Table
15.14
summarizes
the
additional
elements
of
uncertainty
that
are
specific
to
the
recreational
benefits
analysis.

Table
15.14:
Key
Omissions,
Biases,
and
Uncertainties
in
the
Analysis
for
Improved
Recreational
and
Nonuse
Benefits
Assumption/
Limitation
Direction
of
Impact
on
Benefit
Estimates
Scope
of
Recreational
Benefits
Analysis
Only
the
receiving
reach
itself
is
estimated
to
provide
benefits.
(­)

Water
quality
in
reaches
downstream
of
the
reaches
affected
by
MP&
M
discharges
may
also
improve,
generating
additional
benefits
to
society.
luding
these
benefits
from
the
analysis
biases
benefits
estimates
downward.

Only
recreational
users
living
in
the
counties
abutting
MP&
M
reaches
are
assumed
to
benefit
from
water
quality
improvements
due
to
the
MP&
M
rule.
(­)

The
analysis
underestimates
the
total
value
of
benefits
from
the
MP&
M
regulation
because
it
does
not
account
for
people s
WTP
for
water
quality
improvements
to
distant
water
bodies.

For
example,
economic
values
for
improving
nationally­
significant
water
bodies
(
e.
g.,
Great
Lakes,
Chesapeake
Bay,
Long
Island
Sound)
are
likely
to
be
substantial
at
a
regional
level
or
even
nationwide.

The
analysis
of
recreational
fishing
ignores
effects
that
occur
in
secondary
industries.
(­)

The
analysis
of
recreational
benefits
ignores
potential
economic
effects
on
tourism
industries
stemming
from
improved
recreational
opportunities.
a
positive
effect
on
industries
supplying
bait,
tackle,
charter
boats,
etc.
r
demand
for
boating
may
have
positive
effects
on
industries
such
as
boat
construction,
sales,
rentals,
boating
equipment,
marinas,
racing
activities,
etc.
ovements
in
wildlife
viewing
and
near­
water
recreation
opportunities
may
benefit
industries
involved
in
providing
other
recreational
opportunities,
such
as
tours,
books,
binoculars,
etc.

The
analysis
of
recreational
benefits
ignores
changes
in
the
value
of
water­
based
recreational
activities
other
than
fishing,
wildlife
viewing,

and
boating
(
e.
g.,
swimming
or
waterskiing).
(­)
The
estimate
of
recreational
benefits
is
incomplete
because
it
includes
only
a
subset
of
recreational
activities
(
i.
e.,
fishing,
wildlife
viewing,
and
boating)
which
society
may
value
improved
aquatic
habitat.

activities,
such
as
swimming
or
waterskiing.

changes
in
the
affected
reaches,
such
as
improved
taste
and
odor.
Exc
Improved
recreational
fishing
may
have
An
increase
in
consume
Impr
for
It
ignores
changes
in
value
for
other
water­
based
recreational
In
addition,
the
analysis
did
not
consider
other
15­
23
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.14:
Key
Omissions,
Biases,
and
Uncertainties
in
the
Analysis
for
Improved
Recreational
and
Nonuse
Benefits
Assumption/
Limitation
Direction
of
Impact
on
Benefit
Estimates
Extrapolating
from
sample
facility
results
to
national
results
is
based
on
the
sample
facility
weights
(?)

This
extrapolation
technique
is
not
ideal
and
introduces
uncertainty
into
the
analysis.
ility
sample
weights
are
based
on
facility
size
and
type
of
industry.
se
weights
do
not
necessarily
account
for
the
frequency
benefit
pathway
characteristics
in
the
MP&
M
facility
universe.
Therefore
benefit
estimates
may
suffer
from
uncertainties
associated
with
the
extrapolation
method.
For
example,
a
sample
facility
may
have
a
significant
impact
on
benefit
estimates
if
it
is
more
likely
to
be
located
in
a
densely
populated
area,
such
as
a
facility
located
in
Cleveland,
Ohio,
or
a
facility
discharging
in
Long
Island
Sound,
than
the
facilities
it
represents.

To
improve
accuracy
of
the
national
benefit
estimates,
EPA
used
an
alternative
extrapolation
method
(
i.
e.,
post­
stratification
extrapolation).

weights
that
account
for
the
distribution
of
benefit
pathway
characteristics,
including
water
body
type
and
population
size,
in
the
MP&
M
facility
universe.
ppendix
G
summarizes
this
extrapolation
approach.

Congestion
Externalities
(+)

Recreational
benefits
associated
with
water
quality
improvements
can
be
eroded
by
congestion
if
policies
greatly
increase
the
number
of
participants.
can
be
particularly
problematic
when
policies
affect
geographically
scattered
sites,
so
that
there
is
considerable
switching
to
the
improved
site
from
substitute
sites.
be
a
lesser
problem
for
national
regulations
that
might
affect
the
total
number
of
recreation
days
and
the
overall
value
of
recreational
opportunities,
but
are
less
likely
to
have
a
large
effect
on
industrial
sites
relative
to
its
substitutes.

Benefits
Transfer
The
waters
assessed
by
local­
level
studies
are
not
necessarily
nationally
representative.
(?)
The
studies
selected
came
from
the
Midwest
and
the
Northeast.
valued,
as
well
as
respondent
preferences,
may
not
be
representative
of
the
rest
of
the
country.

Types
of
water
quality
changes
expected
from
the
MP&
M
rule
may
differ
from
the
water
quality
changes
considered
in
the
original
studies.
(?)

The
types
of
water
quality
changes
expected
from
the
MP&
M
regulation
are
only
roughly
comparable
with
the
majority
of
water
quality
changes
considered
in
the
original
studies
(
Tudor
et
al.
is
the
only
exception).
paucity
of
available
studies,
the
Agency
made
simplifying
assumptions
to
 
map 
the
water
quality
changes
valued
in
the
original
studies
onto
those
expected
from
the
rule.
lthough
these
assumptions
are
likely
to
increase
uncertainty
associated
with
recreational
benefits
estimates,
the
direction
of
bias
is
not
known.

Compatibility
of
time
periods
considered
in
the
original
studies
and
in
the
analysis
of
MP&
M
costs
and
benefits.
(+)

Most
studies
considered
in
the
benefits
transfer
analysis
did
not
specify
payment
periods.
The
scenario
in
the
Farber
and
Griner
(
2000)
paper
asked
for
payments
for
the
next
five
years.

This
scenario
implies
that
five
years
of
pollution
control
will
result
in
permanent
water
quality
changes.
the
MP&
M
regulation
assumes
that
pollution
control
continues
over
15
years
and
that
water
quality
improvements
depend
on
continued
operation
of
the
water
pollution
controls.

opposed
to
the
total
value
paid
over
five
years,
annualized
over
the
15
years
considered
in
the
cost
analysis.
assumption
may
result
in
an
overestimation
of
the
regulation s
benefit.

The
magnitude
of
this
error
is
unlikely
to
be
significant
because
this
study
is
used
in
combination
with
other
surface
water
valuation
studies.

Baseline
Value
of
Fishery
Converting
annual
WTP
values
to
per­
trip
values
(+)
EPA
converted
annual
WTP
values
reported
in
the
three
CV
studies
used
in
this
analysis
to
per­
trip
values
by
dividing
seasonal
welfare
gain
per
user
reported
in
each
CV
study
by
the
average
number
of
fishing,
boating,
or
viewing
days
in
a
given
state.
his
calculation
implies
that
every
individual
participates
in
only
one
activity,
which
may
not
be
the
case.
This
implication
may
result
in
an
overestimation
of
the
per­
trip
welfare
gain,
and,
consequently,
an
overestimation
of
total
recreational
benefits
from
the
final
rule.
Fac
The
The
opposite
may
also
be
true.

This
method
relies
on
adjusted
sample
facilities
A
This
Congestion
may
As
a
result,
the
resources
Due
to
the
A
The
analysis
of
EPA
therefore
chose
the
annual
WTP
values
presented
in
the
paper,
as
This
T
15­
24
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
Table
15.14:
Key
Omissions,
Biases,
and
Uncertainties
in
the
Analysis
for
Improved
Recreational
and
Nonuse
Benefits
Assumption/
Limitation
Direction
of
Impact
on
Benefit
Estimates
This
analysis
estimates
the
baseline
value
of
the
fisheries
at
locations
across
the
country
using
a
range
of
values
for
all
types
of
fisheries.
(?)

Site­
specific
fisheries
may
have
higher
or
lower
baseline
values,
and
thus,
higher
or
lower
benefits
from
reduced
MP&
M
discharges.

The
total
number
of
recreational
person­
days
in
the
counties
abutting
MP&
M
reaches
is
evenly
distributed
across
all
reach
miles
in
these
counties.
(+)
This
method
for
estimating
the
number
of
recreational
users
potentially
affected
by
water
quality
improvements
from
the
final
regulation
accounts
for
the
quantity
but
not
quality
of
potential
recreational
opportunities
available
to
recreational
users.
re
may
be
important
substitute
sites
in
or
outside
the
counties
abutting
MP&
M
reaches.
recreationally
important
substitute
sites
may
result
in
overestimation
of
benefits
from
the
final
regulation.

Ideally
the
analysis
would
consider
recreational
importance
of
both
sites
affected
by
MP&
M
discharges
and
substitute
sites.

Nonuse
Values
Nonuse
values
are
estimated
as
one­

half
of
recreational
use
benefits.
(?)

It
is
unknown
what
bias
estimating
nonuse
values
based
on
recreational
use
values
has
on
benefits.

Overall
Impact
on
Benefits
Estimates
(?)
The
Ignoring
+
Potential
overestimate.
?
Uncertain
impact.
­
Potential
underestimate.

Source:
U.
S.
EPA
analysis.

15­
25
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
GLOSSARY
1Q10:
the
lowest
one­
day
average
flow
with
a
recurrence
interval
of
ten
years.

7Q10:
the
lowest
consecutive
seven­
day
average
flow
with
a
recurrence
interval
of
ten
years.

ambient
water
quality
criteria
(
AWQC):
published
and
periodically
updated
by
the
EPA
under
the
Clean
Water
Act.

The
criteria
reflect
the
latest
scientific
knowledge
on
the
effects
of
specific
pollutants
on
public
health
and
welfare,
aquatic
life,
and
recreation.
The
criteria
do
not
reflect
consideration
of
economic
impacts
or
the
technological
feasibility
of
reducing
chemical
concentrations
in
ambient
water.
The
criteria
serve
as
guides
to
states,
territories,
and
authorized
tribes
in
developing
water
quality
standards
and
ultimately
provide
a
basis
for
controlling
discharges
or
releases
of
pollutants
into
our
nation s
waterways.
AWQC
are
developed
for
two
exposure
pathways:
ingestion
of
the
pollutant
via
contaminated
aquatic
organisms
only,
and
ingestion
of
the
pollutant
via
both
water
and
contaminated
aquatic
organisms.

benefiting
reaches:
reaches
where
the
MP&
M
rule
is
expected
to
eliminate
existing
AWQC
exceedences.
These
receiving
waters
are
likely
to
experience
significant
water
quality
improvements
as
a
result
of
the
reduced
MP&
M
discharges.

A
reach
is
considered
to
benefit
if
at
least
one
AWQC
exceedance
is
eliminated
due
to
reduced
MP&
M
discharges.

benefits
transfer:
involves
the
application
of
value
estimates,
functions,
and/
or
models
developed
in
one
context
to
address
a
similar
resource
valuation
question
in
another
context.
Often
a
meta­
analysis
is
undertaken
where
benefits
estimates
based
on
existing
studies
are
used
to
develop
new
estimates
which
are
applicable
to
the
scenario
under
consideration.
This
process
accounts
for
relevant
differences
in
study
characteristics,
such
as
the
quality
of
environmental
resource,
the
environmental
change
considered,
and
the
user
population
being
investigated.

contingent
valuation
(
CV):
directly
asks
people
what
they
are
willing
to
pay
for
a
benefit
and/
or
willing
to
receive
in
compensation
for
tolerating
a
cost
through
a
survey
or
questionnaire.
Personal
valuations
for
increases
or
decreases
in
the
quantity
of
some
good
are
obtained
contingent
upon
a
hypothetical
market.
The
aim
is
to
elicit
valuations
or
bids
that
are
close
to
what
would
be
revealed
if
an
actual
market
existed.

conventional
pollutants:
biological
oxygen
demand
(
BOD),
total
suspended
solids
(
TSS),
oil
and
grease
(
O&
G),
pH,
and
anything
else
the
Administrator
defines
as
a
conventional
pollutant.

dissolved
oxygen
(
DO):
oxygen
freely
available
in
water,
vital
to
fish
and
other
aquatic
life
and
for
the
prevention
of
odors.
DO
levels
are
considered
a
most
important
indicator
of
a
water
body's
ability
to
support
desirable
aquatic
life.

Secondary
and
advanced
waste
treatment
are
generally
designed
to
ensure
adequate
DO
in
waste­
receiving
waters.

(
http://
www.
epa.
gov/
OCEPAterms/
dterms.
html)

Metal
Products
and
Machinery
(
MP&
M):
industry
includes
facilities
that
manufacture,
rebuild,
and
maintain
metal
parts,

products,
or
machines.

National
Demand
Study
(
NDS):
U.
S.
EPA
and
the
National
Forest
Service
conducted
the
National
Demand
Survey
for
Water­
Based
Recreation
in
1993.
The
survey
collected
data
on
demographic
characteristics
and
water­
based
recreation
behavior
using
a
nationwide
stratified
random
sample
of
13,059
individuals
aged
16
and
over.

nonconventional
pollutant:
catch­
all
category
that
includes
everything
that
is
not
classified
as
a
priority
pollutant
or
a
conventional
pollutant.

piscivorous:
feeding
preferably
on
fish.

priority
pollutant
(
PP):
126
individual
chemicals
that
EPA
routinely
analyzes
when
assessing
contaminated
surface
water,

sediment,
groundwater,
or
soil
samples.

toxic
pollutants:
EPA s
Office
of
Water
narrowly
defines
a
toxic
pollutant
as
one
of
126
priority
pollutants.
This
definition
is
not
completely
synonymous
with
pollutants
that
have
a
 
toxic 
effect.
Many
nonconventional
pollutants
may
also
be
hazardous
to
aquatic
life
and
human
health.

 
toxic 
pollutant:
any
pollutant
that
has
an
adverse
effect
on
aquatic
life
or
human
health.

15­
26
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
travel
cost
(
TC)
model:
derives
values
by
evaluating
expenditures
of
recreators.
Travel
costs
are
used
as
a
proxy
for
price
in
deriving
demand
curves
for
the
recreation
site.
(
http://
www.
damagevaluation.
com/
glossary.
htm)

U.
S.
Fish
and
Wildlife
Service
(
FWS):
the
principal
federal
agency
responsible
for
conserving,
protecting,
and
enhancing
fish,
wildlife,
and
plants
and
their
habitats
for
the
continuing
benefit
of
the
American
people.

(
http://
www.
fws.
gov/
r9extaff/
pafaq/
fwsfaq.
html)

willingness­
to­
pay
(
WTP):
maximum
amount
of
money
one
would
give
to
buy
some
good.

(
http://
www.
damagevaluation.
com/
glossary.
htm)

15­
27
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
ACRONYMS
1Q10:
the
lowest
1­
day
average
flow
with
a
recurrence
interval
of
10
years
7Q10:
the
lowest
7­
day
average
flow
with
a
recurrence
interval
of
10
years
AWQC:
ambient
water
quality
criteria
CV:
contingent
valuation
DO:
dissolved
oxygen
FWS:
U.
S.
Fish
and
Wildlife
Service
MP&
M:
Metal
Products
and
Machinery
NDS:
National
Demand
Study
TC:
travel
cost
WTP:
willingness­
to­
pay
15­
28
MP&
M
EEBA
Part
III:
Benefits
Chapter
15:
Recreational
Benefits
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Harpman,
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Silverman,
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Tudor,
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15­
30
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
INTRODUCTION
The
final
rule
only
regulates
direct
dischargers.
Therefore,

the
selected
option
does
not
affect
POTW
operations.
For
the
alternative
policy
options
that
consider
both
direct
and
indirect
dischargers,
EPA
evaluated
two
categories
of
productivity
benefits
for
publicly­
owned
treatment
works
(
POTWs):

 
reduced
interference
with
the
operations
of
POTW
s,
and
 
reduced
contamination
of
sewage
sludge
(
i.
e.,

biosolids)
at
POTWs
that
receive
discharges
from
MP&
M
facilities.

Interference
with
POTW
processes
occurs
when
high
levels
of
toxics,
such
as
metals
or
cyanide,
kill
bacteria
required
for
wastewater
treatment
processes.
The
removal
of
these
pollutants
would
eliminate
the
need
for
extra
labor
and
materials
to
maintain
POTW
operations.
Chapter
16:
POTW
Benefits
CHAPTER
CONTENTS
16.1
nterference
with
POTW
Operations
.
.
.
16­
2
16.2
ng
Benefits
from
Reduced
Sludge
Contamination
.................
.......
16­
2
16.2.1
.................
.......
16­
2
16.2.2
Practices
.................
............
16­
4
16.2.3
Quality
Benefits
.................
......
16­
7
16.2.4
and
Practices
.
.
16­
8
16.2.5
ying
Sludge
Benefits
...........
16­
10
16.3
ated
Savings
in
Sludge
Use/
Disposal
Costs
16­
15
16.4
Limitations
.................
.
16­
16
Glossary
.................
.................
..
16­
18
Acronyms
.................
.................
.
16­
19
References
.................
.................
16­
20
Reduced
I
Assessi
Data
Sources
Sludge
Generation,
Treatment,
and
Disposal
Overview
of
Improved
Sludge
Sludge
Use/
Disposal
Costs
Quantif
Estim
Methodology
Toxic
priority
and
nonconventional
pollutants
may
also
pass
through
a
POTW
and
contaminate
sludge
generated
during
primary
and
secondary
wastewater
treatment.
1
POTW
treatment
of
wastewater
with
reduced
pollutant
concentrations
translates
into
cleaner
sludge,
which
can
be
disposed
of
using
less
expensive
and
more
environmentally
benign
methods.
In
some
cases,
cleaner
sludge
may
have
agricultural
applications,
which
would
generate
additional
resource
conservation
benefits.

Some
MP&
M
pollutants
that
pass
through
a
POTW
and
contaminate
sludge
are
not
currently
subject
to
sewage
sludge
pollutant
concentration
limits.
The
alternative
policy
options
would
reduce
concentrations
of
these
pollutants
in
sewage
sludge
as
well,
which
may
translate
into
reduced
environmental
and
human
health
risks.
EPA
did
not
estimate
the
reduced
risk
attributable
to
the
reduction
of
these
pollutants.

Wastewater
from
MP&
M
facilities
also
contains
hazardous
air
pollutants
(
HAPs).
These
pollutants
may
represent
unacceptable
health
risks
to
POTW
workers
if
released
into
the
air
at
high
enough
concentrations
during
the
wastewater
treatment
cycle.
This
reduction
in
pollutants
may
translate
into
health
benefits
to
POTW
workers
and
those
living
near
POTWs.

The
remaining
sections
of
this
chapter
present
methodology
for
estimating
benefits
to
the
receiving
POTW
s
from
reducing
pollutants
in
the
wastewater
of
indirect
MP&
M
dischargers.
As
noted
above,
the
final
option
does
not
affect
POTW
operations
since
it
regulates
direct
dischargers
only.
For
the
alternative
options
that
consider
both
direct
and
indirect
dischargers,
EPA
evaluated
two
benefits
measures
associated
with
MP&
M
pollutants:
(
1)
the
reduction
in
pollutant
interference
at
POTWs;
and
(
2)
pass­
through
of
pollutants
into
the
sludge,
which
limits
options
for
POTW
disposal
of
sewage
sludge.

1
The
term
sewage
sludge,
also
called
biosolids,
is
often
shortened
to
sludge
throughout
this
chapter
for
simplicity.

16­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
16.1
REDUCED
INTERFERENCE
WITH
POTW
OPERATIONS
High
levels
of
some
MP&
M
pollutants
(
such
as
metals,
chlorobenzene,
polyaromatic
hydrocarbons,
and
oil
and
grease)
can
kill
bacteria
that
are
required
for
the
wastewater
treatment
process
(
U.
S.
EPA,
1987).
POTWs
affected
by
such
"
inhibition
problems"
may
incur
extra
labor
and
materials
costs
to
maintain
system
operations.
As
a
partial
measure
of
the
economic
benefits
resulting
from
the
alternative
regulatory
options,
EPA
estimated
the
extent
to
which
reduced
MP&
M
discharges
would
decrease
pollutant
concentrations
to
below
POTW
pollutant
inhibition
values,
using
the
following
steps:

 
estimate
the
baseline
and
post­
compliance
influent
concentrations
for
each
POTW
receiving
discharges
from
MP&
M
facilities,
based
on
annual
pollutant
loadings
from
the
MP&
M
facility,
the
number
of
POTW
operating
days
per
year,
and
the
gross
volume
of
influent;

 
compare
baseline
and
post­
compliance
influent
concentrations
with
available
inhibition
levels
(
see
Table
I.
5
in
Appendix
I);
and
 
estimate
the
change
in
the
number
of
POTWs
in
which
influent
concentrations
of
MP&
M
pollutants
exceed
POTW
inhibition
values.

Adverse
effects
on
POTW
operations,
including
inhibition
of
microbial
degradation,
are
likely
when
influent
concentrations
of
one
or
more
pollutants
exceed
an
inhibition
value.
EPA
estimated
influent
concentrations
in
excess
of
POTW
inhibition
values
for
the
sample
facilities
for
the
baseline
and
the
alternative
regulatory
options.
Results
of
this
analysis
are
presented
in
Appendix
I
of
this
report.
Eliminating
the
exceedances
will
result
in
operating
cost
savings
to
POTWs.
EPA
has
not
estimated
a
monetary
value
for
this
benefit,
however,
due
to
data
limitations.

The
final
rule
only
regulates
direct
dischargers.
Therefore,
the
selected
option
does
not
affect
POTW
operation.
For
the
alternative
policy
options
that
consider
both
direct
and
indirect
dischargers,
EPA
estimated
that
51
PO
TW
s
had
influent
concentrations
in
excess
of
biological
inhibition
values
for
one
or
more
pollutants
under
the
baseline
conditions
corresponding
to
the
433
Upgrade
Options.
This
represents
0.3%
of
the
over
16,000
POTWs
operating
nationwide.
(
Table
I.
12
in
Appendix
I
provides
detailed
information
on
pollutants
exceeding
POTW
inhibition
criteria.)
Both
upgrade
options
would
eliminate
exceedances
of
POTW
inhibition
criteria
in
21
POTWs.

EPA s
analysis
finds
that
influent
concentrations
in
293
POTWs
exceed
biological
inhibition
values
for
one
or
more
pollutants
under
the
Proposed/
NODA
Option.
The
Proposed/
NODA
Option
would
eliminate
inhibition
criteria
exceedances
in
156
of
the
affected
POTW.
2
POTWs
may
impose
local
limits
to
prevent
inhibitions.
If
local
limits
are
in
place,
the
estimated
reduction
in
potential
inhibition
problems
at
the
affected
POTWs
may
be
overstated.
In
this
case,
however,
the
estimated
social
cost
of
the
MP&
M
regulation
is
also
overstated.

16.2
ASSESSING
BENEFITS
FROM
REDUCED
SLUDGE
CONTAMINATION
16.2.1
Data
Sources
The
analysis
of
POTW
benefits
from
improved
sludge
quality
draws
on
several
data
sources.
The
§
308
POTW
Surveys
provide
most
of
the
required
information.
EPA
collected
information
from
147
POTWs
representing
a
98
percent
response
rate
to
the
150
surveys
that
were
mailed.
EPA
also
used
the
§
308
survey
of
MP&
M
facilities.
The
two
data
collection
efforts
were
not
designed
to
provide
a
match
between
the
MP&
M
sample
facilities
and
the
POTWs
to
which
they
discharge.
EPA
obtained
a
significant
amount
of
information
from
the
POTW
Surveys,
but
had
substantially
less
information
on
the
POTWs
that
receive
discharges
from
the
MP&
M
facilities.
To
address
this
data
limitation,
EPA
used
the
POTW
Survey
data
to
infer
2
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
upgrade
options
(
Directs
+
413
to
433
Upgrade
Option,
Directs
+
All
to
433
Upgrade
Option).
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
did
not
perform
any
more
analyses
on
the
NODA
option
­­
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

16­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
information
on
the
key
factors
that
are
likely
to
influence
choice
of
sewage
sludge
use
and
disposal
practices
for
the
POTWs
receiving
discharges
from
the
MP&
M
facilities.

The
POTW
Survey
contains
three
sections.
Section
1
provides
general
information
on
POTW
location
and
size.
Section
2
provides
data
on
the
cost
of
administering
pre­
treatment
programs
(
see
Appendix
F).
Section
3
contains
data
on
the
cost
of
treating
and
disposing
of
sewage
sludge
and
provides
new
and
more
consistent
data
for
analyzing
the
effect
of
reduced
pollutant
loadings
on
sewage
sludge
management
costs.

The
POTW
Survey
asked
for
the
following
information:

 
current
sludge
disposal
practices;

 
sludge
disposal
costs
for
one
or
more
disposal
methods;

 
reasons
for
not
using
a
less
expensive
disposal
method;

 
number
of
MP&
M
facilities
discharging
to
the
POTW,
by
flow
size
(
less
than
1
million
gal/
year;
1­
6.25
million
gal/
year;
greater
than
6.25
million
gal/
year);

 
total
metal
loadings
discharged
to
the
POTW
from
all
sources;
and
 
percentage
of
total
metal
loadings
attributable
to
MP&
M
facilities.

The
POTW
Survey
was
intended
to
address
data
limitations
encountered
in
the
Phase
1
analysis,
particularly
the
inadequacy
of
information
about
POTWs
that
receive
discharges
from
the
MP&
M
sample
facilities.
The
only
information
available
for
the
Phase
I
analysis
was
POTW
geographic
location,
influent
volume,
and
the
metals
content
of
the
discharge
received
from
the
sampled
MP&
M
facilities.
Discharges
to
the
POTW
by
non­
sampled
MP&
M
facilities
and
by
non­
MP&
M
facilities
were
not
known.
These
discharges
may
significantly
affect
sewage
sludge
quality,
however,
resulting
in
a
discrepancy
between
predicted
and
actual
pollutant
concentrations
in
sewage
sludge
and
the
corresponding
disposal
practices.
In
addition,
lack
of
information
on
the
factors
that
may
influence
a
POTW's
decisions
about
sludge
management
practices
introduced
additional
uncertainty
in
the
analysis.

EPA
used
the
POTW
Survey
to
calculate
the
following
parameters:

 
baseline
percentage
of
the
total
metal
loadings
to
POTWs
by
POTW
flow
category
attributable
to
MP&
M
facilities;

 
post­
compliance
loading
reductions
for
non­
sampled
MP&
M
facilities
discharging
to
the
receiving
POTWs;

 
costs
of
sewage
sludge
disposal
practices;
and
 
percentage
of
qualifying
sludge
that
is
not
beneficially
used
for
any
of
the
following
reasons:
lack
of
land;
lower
cost
alternative;
inability
to
meet
vector
or
pathogen
requirements;
poor
weather;
stricter
state
standards;
and
other
reasons.

EPA
also
used
the
data
provided
by
the
Association
of
Metropolitan
Sewerage
Agencies
(
AMSA)
to
refine
its
analysis
of
POTW
benefits
for
the
final
rule.
AMSA
provided
EPA
with
comments
on
the
proposed
MP&
M
rule
and
supplemented
these
comments
with
a
spreadsheet
database
(
AMSA,
2000).
The
database
contains
data
from
an
AMSA
formulated
survey
and
covers
responses
from
176
POTWs,
representing
66
pretreatment
programs.
The
AMSA
survey
was
conducted
to
verify
data
from
EPA's
survey
of
POTWs
and
therefore
included
similar,
although
fewer,
variables
compared
to
EPA's
survey.

EPA
used
the
results
of
the
AMSA
survey
to
supplement
information
from
the
MP&
M
POTW
Survey
on
percentage
of
metal
loadings
contributed
by
MP&
M
facilities
and
the
number
of
MP&
M
facilities
served
by
POTWs.
Based
on
the
results
of
the
joint
analysis
of
the
EPA
and
AMSA
surveys,
EPA
revised
the
following
elements
of
the
POTW
benefits
methodology:
(
1)

the
number
of
MP&
M
facilities
served
by
small,
medium,
and
large
POTW
s,
(
2)
percentage
of
metal
loadings
contributed
by
MP&
M
facilities,
and
(
3)
percentage
of
qualifying
sludge
that
is
not
land­
applied.

Finally,
EPA
used
other
data
sources
in
this
analysis,
including
Handbook
for
Estimating
Sludge
Management
Costs
(
EPA,

1985)
and
Regulatory
Impact
Analysis
of
the
Part
503
Sludge
Regulation
(
EPA,
1993b).

16­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
16.2.2
Sludge
Generation,
Treatment,
and
Disposal
Practices
a.
Sludge
generation
POTW
s
generally
treat
wastewater
from
industrial
indirect
dischargers
along
with
domestic
wastewater.
Sludge
results
from
primary,
secondary,
and
advanced
wastewater
treatment.
The
extent
and
type
of
wastewater
treatment
determine
the
chemical
and
physical
character
of
the
sludge.
Sludge
may
be
conditioned,
thickened,
stabilized,
and
dewatered
to
reduce
its
volume.

Sludge
contains
five
classes
of
components:
organic
matter,
pathogens,
nutrients,
inorganic
chemicals,
and
organic
chemicals.

The
mix
and
levels
of
these
components
ultimately
determine
the
human
health
and
environmental
impact
of
sludge
use/
disposal,
and
so
may
also
dictate
the
most
appropriate
uses
and
disposal
practices
(
EPA,
1993b).

Organic
matter
(
the
primary
constituent
of
sludge)
comes
from
human
waste,
kitchen
waste,
and
stormwater
runoff.
Organic
and
inorganic
chemicals
in
sludge
come
from
industrial
processes
that
discharge
to
municipal
sewers.
The
concentration
of
inorganic
pollutants
in
sludge,
including
metals,
depends
upon
the
volume
and
type
of
industrial
wastes
discharged
to
the
POTW,
as
well
as
the
extent
and
character
of
stormwater
runoff.

b.
Sludge
use/
disposal
practices
After
treatment,
sludge
can
be
used
in
the
following
ways:

 
Land
Application:
Spraying
or
spreading
on
the
land
surface,
injection
below
the
surface,
or
incorporation
into
the
soil,
for
soil
conditioning
or
fertilization
of
crops
or
vegetation.
Agricultural
lands
(
pasture,
range
land,
crops),

forest
lands
(
silviculture),
and
drastically
disturbed
lands
(
land
reclamation
sites)
may
all
receive
sludge;

 
Bagged
Application:
Collection
of
sludge
in
containers
for
application
to
land
(
i.
e.,
distribution
and
marketing);

 
Surface
Disposal:
Disposal
on
land
specifically
set
aside
for
this
use,
including
surface
impoundments
(
also
called
lagoons),
sludge
monofills
(
i.
e.,
sludge­
only
landfills),
and
dedicated
sites
(
i.
e.,
land
on
which
sludge
is
spread
solely
for
final
disposal);

 
Co­
disposal:
Disposal
in
a
municipal
solid
waste
landfill
(
MSWL)
or
hazardous
waste
landfill;
and
 
Incineration:
Combustion
of
organic
and
inorganic
matter
at
high
temperatures
in
an
enclosed
device.

Land
application
and
bagged
application
are
beneficial
uses
of
sludge.
Both
methods
can
be
categorized
as
being
"
high"
or
"
low,"
depending
on
pollutant
concentrations
in
sewage
sludge.
"
High"
applications
meet
stringent
limits
on
the
total
concentration
of
a
given
pollutant
at
a
given
application
site.
"
High"
sludge
is
exempt
from
meeting
pollutant
loading
rate
limits
and
certain
record­
keeping
requirements.
"
Low"
applications
meet
less
stringent
"
ceiling"
limits
for
pollutants.
Ceiling
limits
govern
whether
a
sewage
sludge
can
be
applied
to
land
at
all.
"
Low"
applications
require
more
record­
keeping
because
POTWs
must
track
total
(
cumulative)
loadings
applied
to
each
given
site,
in
addition
to
tracking
the
concentration
of
sludge
applied
at
any
given
time.

Many
POTWs
use
more
than
one
use/
disposal
practice,
which
helps
to
maintain
flexibility
and
avoid
the
capacity
limitations
of
a
single
practice.
The
practice
chosen
depends
on
several
factors,
including:

 
cost
to
prepare
sludge
for
use/
disposal;

 
pollutant
concentrations;

 
market
demand
for
sludge;

 
cost
to
transport
sludge
to
use/
disposal
sites;

 
availability
of
suitable
sites
for
land
application,
landfilling,
or
surface
disposal;

 
weather
and
other
local
conditions;

 
allowance
of
a
safety
factor
to
account
for
unplanned
or
unforseen
conditions;

16­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
 
state
environmental
regulations;
and
 
public
acceptance
(
EPA,
1993b).

The
choice
of
use/
disposal
method
is
restricted
by
the
quality
of
the
sludge
generated
by
the
POTW
.
Sludge
for
beneficial
uses
must
meet
more
stringent
standards
for
pollutant
concentrations
than
sludge
used
or
disposed
of
in
other
ways.
Similarly,

sludge
that
is
surface­
disposed
in
an
unlined
unit
generally
must
meet
more
stringent
standards
than
sludge
surface­
disposed
in
a
lined
unit,
disposed
in
an
MSWL,
or
incinerated.
Sludge
disposed
in
a
MSWL
must
meet
more
stringent
standards
than
incinerated
sludge.

Table
16.1
summarizes
sludge
use/
disposal
methods
according
to
the
number
and
percent
of
dry
metric
tons
(
DMT),
based
on
information
provided
in
Section
3
of
the
§
308
POTW
Survey.
The
information
presented
in
this
table
takes
into
account
data
provided
by
AMSA
on
POTW
characteristics
such
as
POTW
flow
and
the
total
amount
of
sludge
generated
by
each
POTW.

Because
the
AM
SA
data
was
collected
five
years
after
the
EPA
POT
W
Survey
was
administered
and
it
does
not
correspond
to
the
base
year
of
the
analysis
(
1996),
EPA
did
not
use
AMSA
data
to
adjust
the
allocation
of
sludge
to
each
use/
disposal
method
category.

Table
16.1:
Sludge
Use/
Disposal
(
1996)
by
POTWs
Discharging
>
2
Million
Gallons/
Day
a
Use/
Disposal
Sub­
Class
Thousand
DMT
Percent
of
DMT
Total
Beneficial
Use
2,641.2
39.9%

Land
Application­
High
1,017.4
15.4%

Bag
Application­
High
339.9
5.1%

Land
Application­
Low
1,283.9
19.4%

Bagged
Application­
Low
0
0%

Total
Surface
Disposal
528.2
8.0%

Surface
Disposal:
Unlined
Unit
347.2
5.3%

Surface
Disposal:
Lined
Unit
181.0
2.7%

Co­
Disposal:
Municipal
Landfill
1,768.8
26.8%

Incineration
1,129.9
17.1%

Unknown:
Other
543.2
8.2%

All
6,611.2
100.0%

a
The
§
308
POTW
Survey
did
not
collect
information
from
POTWs
discharging
<
2
million
gallons
per
day.

Source:
U.
S.
EPA,
POTW
Survey
and
AMSA
Survey
(
2000)
on
Proposed
MP&
M
Effluent
Guidelines.

As
Table
16.1
shows,
39.9
percent
of
total
sludge
tons
reported
by
respondents
is
used
beneficially
(
land
application
and
bagged
application).
Co­
disposal
in
a
municipal
landfill
is
the
second
most
frequently
used
disposal
method,
accounting
for
26.8
percent
of
all
sludge
disposed
in
the
U.
S.
Surface
disposal
in
unlined
and
lined
units,
incineration,
and
"
other"
disposal
methods
account
for
5.3
percent,
2.7
percent,
17.1
percent,
and
8.2
percent
of
all
sludge
tons,
respectively.
No
sludge
was
sent
to
a
hazardous
waste
landfill
by
the
POTW
Survey
respondents.

c.
Pollutant
limits
and
disposal
options
Section
405(
d)
of
the
Clean
Water
Act,
as
amended,
requires
EPA
to
specify
acceptable
management
practices
and
numerical
limits
for
certain
pollutants
in
sludge.
The
Agency
published
Standards
for
the
Use/
Disposal
of
Sludge
(
40
CFR
Part
503,

February
1993)
to
protect
public
health
and
the
environment
from
reasonably
anticipated
adverse
effects
of
pollutants
in
sludge
(
U.
S.
EPA,
1993a).
The
standards
include
general
requirements,
pollutant
limits,
management
practices,
operational
standards,
monitoring
frequency,
record­
keeping,
and
reporting
for
the
final
use
and
disposal
of
sludge
in
four
circumstances:

 
sludge
co­
disposed
with
household
waste
in
a
MSWL;

16­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
 
sludge
land­
applied
for
beneficial
purposes
(
including
bagged
sludge);

 
sludge
disposed
on
land
or
on
surface
disposal
sites;
and
 
incinerated
sludge.

With
the
exception
of
MSWLs,
the
standards
for
each
practice
include
numerical
limits
on
sludge
pollutant
concentrations.

Part
503
sets
limits
on
pollutant
concentrations
for
land
application
at
two
levels:

 
Land
Application­
Low
limits,
which
govern
whether
sludge
can
be
applied
to
land
at
all;
and
 
more
stringent
Land
Application­
High
limits
which
define,
in
part,
sludge
that
is
exempt
from
meeting
certain
record­
keeping
requirements.

For
sludge
meeting
only
the
Land
Application­
Low
limits,
Part
503
contains
pollutant
loading
rate
limits.
These
determine
the
amount
of
sludge
and
associated
pollutant
content
that
may
be
applied
to
a
particular
site.

EPA
did
not
establish
pollutant­
specific,
numerical
criteria
for
toxic
pollutants
of
concern
in
the
sludge
disposed
in
MSWLs,

because
the
design
standards
applicable
to
MSWLs
are
considered
adequate
to
protect
human
health
and
the
environment.

Also,
MSWL
sludge
is
co­
disposed
with
household
waste,
making
precise
numerical
criteria
infeasible.
The
Solid
Waste
Disposal
Facility
Criteria
(
40
CFR
Part
258,
Federal
Register
50978,
October
9,
1991)
specify
that
POTW
s
using
an
MSWL
must
ensure
that
their
sewage
is
non­
hazardous
and
passes
the
Paint
Filter
Liquid
Test.

The
pollutant
limits
for
sludge
land
application,
surface
disposal,
and
incineration
constrain
a
POTW's
choice
of
sludge
use/
disposal
practice.
Table
16.2
presents
numerical
limits
for
the
three
sludge
use/
disposal
practices
for
eight
MP&
M
pollutants.
The
land
application
pollutant
limits
place
restrictions
on
concentrations
of
metals
in
sludge;
the
surface
disposal
criteria
cover
a
subset
of
the
metals
regulated
for
land
application.
The
MP&
M
effluent
limitations
guideline
covers
five
metals
and
causes
incidental
removal
of
the
remaining
three
metals
regulated
under
the
Part
503
sludge
regulation.
The
alternative
policy
options
would
improve
the
quality
of
sewage
sludge
generated
by
POTWs
receiving
discharges
from
MP&
M
facilities
and,
as
a
result,
would
increase
sludge
use/
disposal
options
for
the
affected
POTWs.

Table
16.2:
Sludge
Use/
Disposal
Pollutant
Limits
Pollutant
Application
Limits
Surface
Disposal
Limits
(
mg/
kg
dry
weight)
a
MP&
M
Pollutants
of
ConcernLow
Limits
(
Low)

(
mg/
kg
dry
weight)
High
Limits
(
High)

(
mg/
kg
dry
weight)

Arsenic
75
41
73
 
Cadmium
85
39
 
Copper
4,300
1,500
 
Lead
840
300
 
Mercury
57
17
 
Nickel
420
420
420
 
Selenium
100
100
 
Zinc
7,500
2,800
 
a
Pollutant
limits
for
active
sludge
unit
whose
boundary
is
greater
than
150
meters
from
the
surface
disposal
site
property
line.

Source:
Standards
for
the
Use
or
Disposal
of
Sludge;
Final
Rules.
40
CFR
Part
257
et
al.
Federal
Register
February
19,

1993a.

16­
6
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
d.
Reasons
for
not
land­
applying
qualifying
sludge
POTW
characteristics
including
location,
state
regulations,
and
community
concerns
also
affect
use/
disposal
methods
for
sludge.
The
POTW
Survey
provided
information
on
the
percentage
of
sludge
that
qualified
for
beneficial
use
but
was
not
beneficially
used.
Survey
data
indicate
that
57
percent
of
qualifying
sludge
was
not
land­
applied,
for
the
following
reasons:

 
land
application
is
more
expensive
than
another
method;

 
land
is
not
available
for
sludge
application;

 
the
cumulative
pollutant
loads
at
the
land
application
site
used
had
been
exceeded;

 
the
vector
or
pathogen
requirements
to
land
apply
could
not
be
met
at
an
acceptable
cost;
and
 
inclement
weather,
concern
over
liability,
stakeholder
complaints,
stricter
state
standards,
desire
to
diversify
practices,
or
technical
problems.

Of
the
57
percent
of
sludge
that
was
not
land­
applied,
only
11
percent
of
qualifying
sludge
was
otherwise
beneficially
used
(
i.
e.,
sold
in
bags).
Therefore,
only
50
percent
of
the
total
qualifying
sludge
is
beneficially
used.
3
In
addition,
POTW
Survey
data
indicate
that,
on
average,
7.5
percent
of
all
sludge
that
qualifies
for
surface
disposal
is
not
surface
disposed.

16.2.3
Overview
of
Improved
Sludge
Quality
Benefits
This
section
discusses
potential
economic
productivity
benefits
resulting
from
cleaner
sludge,
describes
the
methodology
used
to
estimate
benefits
to
POTWs
directly
affected
by
the
regulation,
and
presents
the
results
of
the
analysis.

EPA
expected
that
the
alternative
regulatory
options
would
reduce
MP&
M
facility
discharges
of
eight
metals
with
Part
503
limits.
The
influent
pollutant
reductions
to
the
receiving
POTWs
translate
into
sludge
with
reduced
pollutant
concentrations,

allowing
the
sludge
to
meet
the
criteria
for
lower­
cost
use/
disposal
methods.
The
reduction
in
pollutants
will
then
provide
many
POTWs
with
greater
flexibility
in
the
disposal
of
their
sludge,
and
for
some
the
opportunity
to
use
less
expensive
methods
of
sludge
use/
disposal.
In
some
cases,
wastewater
treatment
systems
may
be
able
to
use
the
cleaner
sludge
in
agricultural
applications,
generating
additional
agricultural
productivity
benefits.
Numerous
benefits
will
result
from
reduced
contamination
of
sludge,
including
the
following:

 
POTWs
may
have
less
expensive
options
for
use/
disposal
of
sludge.
Methods
involving
stricter
criteria
are
generally
less
expensive
than
the
alternatives.
In
particular,
land
application
usually
costs
substantially
less
than
incineration
or
landfilling.
As
a
result,
under
the
alternative
policy
options
sludge
from
some
PO
TW
s
may
meet
more
stringent
criteria
for
less
expensive
use/
disposal
methods.

 
Some
sludge
currently
meeting
only
Land
Application­
Low
concentration
limits
and
pollutant
loading
rate
limits
would
meet
the
more
stringent
Land
Application­
High
concentration
limits.
Users
applying
sludge
meeting
Land
Application­
High
pollutant
limits
would
be
exempt
from
meeting
pollutant
loading
rate
limits.
They
would
have
fewer
record­
keeping
requirements
than
users
of
sludge
meeting
only
Land
Application­
Low
concentration
and
loading
rate
limits.

 
By
land­
applying
sludge,
POTW
s
may
avoid
costly
siting
negotiations
for
more
contentious
sewage
sludge
use
or
disposal
practices,
such
as
incineration.

 
POTW
sludge
provides
supplemental
nitrogen,
which
enhances
soil
productivity
when
land­
applied.
Sludge
applied
to
agricultural
land,
golf
courses,
sod
farms,
forests,
or
residential
gardens
is
a
valuable
source
of
nitrogen
fertilizer.

 
Non­
point
source
nitrogen
contamination
of
water
may
be
reduced
if
sludge
is
used
as
a
substitute
for
chemical
fertilizers
on
agricultural
land.
Compared
to
nitrogen
in
most
chemical
fertilizers,
nitrogen
in
sludge
is
relatively
insoluble
in
water.
The
release
of
nitrogen
from
sludge
occurs
largely
through
continuous
microbial
activity,

resulting
in
greater
plant
uptake
and
less
nitrogen
runoff
than
from
conventional
chemical
fertilizers.

3
Percent
of
Qualifying
Sludge
Beneficially
Used
=
(
100%
 
57%)
+[(
57%
×
11%)/
100%]=
50%

16­
7
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
 
The
organic
matter
in
land­
applied
sludge
can
improve
crop
yields
by
increasing
the
ability
of
soil
to
retain
water.

 
Reduced
concentrations
of
sludge
pollutants
not
currently
regulated
may
reduce
human
health
and
environmental
risks.
Human
health
risks
from
exposure
to
these
unregulated
sludge
pollutants
may
occur
from
particulate
inhalation,
dermal
exposure,
ingestion
of
food
grown
in
sludge­
amended
soils,
ingestion
of
surface
water
containing
sludge
runoff,
ingestion
of
fish
from
surface
water
containing
sludge
runoff,
or
ingestion
of
contaminated
ground
water.

 
Land
application
of
sludge
satisfies
an
apparent
public
preference
for
this
practice
of
sludge
disposal,
apart
from
considerations
of
costs
and
risk.

This
analysis
assumes
that
POTWs
will
choose
the
least
expensive
sludge
use/
disposal
practice
for
which
their
sludge
meets
pollutant
limits.
POTW
s
with
sludge
pollutant
concentrations
exceeding
the
Land
Application­
High,
Land
Application­
Low,

or
surface
disposal
pollutant
limits
in
the
baseline
may
be
able
to
reduce
sludge
use/
disposal
costs
after
MP&
M
facilities
have
complied
with
the
effluent
limitations
considered
under
alternative
regulatory
options.

As
public
entities,
POTW
s
are
not
forced
by
the
market
to
act
as
profit­
maximizing
or
cost­
minimizing
agents,
but
rather
are
assumed
to
optimize
their
jurisdictional
welfare
function.
POTW
s
take
factors
other
than
cost
into
consideration
when
determining
their
sludge
use/
disposal
methods.
These
factors
may
include
the
desire
to
be
perceived
by
the
public
as
using
sludge
in
an
environmentally
friendly
way,
or
the
desire
to
enhance
relationships
with
clients
by
providing
no­
cost
or
low­
cost
fertilizer.
Greater
flexibility
in
disposal
practices
may
therefore
provide
benefits
beyond
cost
savings.

16.2.4
Sludge
Use/
Disposal
Costs
and
Practices
This
section
summarizes
the
estimated
cost
differences
of
various
use
and
disposal
methods,
based
on
the
POTW
Survey.

Alternative
sludge
use/
disposal
practices
costs
vary
considerably
among
POTWs,
based
on
several
factors,
the
most
important
being
the
availability
of
local
agricultural
land
or
land
suitable
for
surface
disposal
of
sludge.
Table
16.3
lists
and
ranks
the
use/
disposal
methods
from
least
expensive
to
most
expensive,
according
to
the
average
qualitative
ranking
of
each
method
in
the
POTW
Survey.

Table
16.3:
National
Estimate
of
Qualitative
Ranking
of
Use/
Disposal
Methods
Mean
Rankings
Least
Expensive
Land
Application­
High
 
Land
Application­
Low
MSWL
 
Bagged
Application­
High
Surface
Disposal
in
Unlined
Unit
 
Bagged
Application­
Low
Surface
Disposal
in
Lined
Unit
 
Incineration
Most
Expensive
Hazardous
Waste
Landfill
Source:
U.
S.
EPA,
§
308
POTW
Survey.

Land
Application­
Low
and
Land
Application­
High
were
ranked
as
the
two
cheapest
sewage
sludge
disposal
options,

supporting
the
assumption
that
beneficial
use
of
sludge
offers
cost
savings.
The
third
least
expensive
option
co­
disposal
in
an
MSWL
costs
less
on
average
than
either
bagging
sludge
or
surface
disposing
in
an
unlined
unit.

16­
8
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
EPA
used
the
POTW
Survey
data
as
the
primary
source
for
estimating
an
average
difference
in
costs
among
certain
combinations
of
use/
disposal
practices
(
e.
g.,
the
cost
savings
achieved
by
switching
from
incineration
to
land
application).

Table
16.4
compares
the
cost
savings
realized
by
switching
to
sludge
land
application
and
surface
disposal
practices
from
less
stringently
regulated
sludge
use/
disposal
practices.
While
on
average
the
estimates
provided
in
Table
16.4
are
expected
to
hold,
the
cost
savings
will
vary
for
individual
POTWs.
POTWs
whose
sludge
qualifies
for
beneficial
use
post­
compliance
but
did
not
qualify
for
such
use
in
the
baseline
may
achieve
cost
savings
in
some,
but
not
all,
circumstances.
For
example,
a
POTW
may
not
achieve
cost
savings
from
agricultural
application
due
to
sludge
transportation
costs
or
because
there
are
less
expensive
alternatives
for
that
particular
facility.
Switching
from
sewage
sludge
co­
disposal
in
a
MSW
L
to
surface
disposal
offers
no
savings
to
a
POTW.

Table
16.4:
Cost
Savings
for
Shifts
in
Sludge
Use/
Disposal
Practices
(
2001$/
DMT)

Switch
From
Switch
To:

Land
Applicationa
(
High)
Land
Applicationa
(
Low)
Sold
in
a
Bag
for
Land
Application
Surface
Disposal
on
Unlined
Unit
Surface
Disposal
on
Lined
Unit
Incineration
$
103.82
$
103.82
$
95.91
$
103.08
No
Saving
Surface
Disposal
on
Lined
Unit
$
126.39
$
126.39
$
71.89
Surface
Disposal
on
Unlined
Unit
$
6.44
$
6.44
$
0.59
Co­
disposal:
MSWL
$
100.44
$
100.44
$
69.96
No
Saving
No
Saving
Land
Application­
Low
$
0.54­
1.09
a
EPA
assumes
that
the
costs
of
land
application
to
forests,
public
contact
sites,
and
reclaimed
land
are
similar
to
the
costs
of
agricultural
application.

Source:
U.
S.
EPA
analysis
of
the
§
308
POTW
Survey
data.

The
cost
section
of
the
POTW
Survey
did
not
distinguish
between
low
and
high
land
application
or
low
and
high
bagged
application.
Therefore,
costs
provided
in
the
survey
reflect
the
cost
of
both
methods.
To
estimate
the
cost
savings
of
avoiding
these
requirements
by
meeting
Land
Application­
High
limits,
EPA
used
the
compliance
requirements
for
meeting
Land
Application­
Low
limits
for
bulk
sludge
(
U.
S.
EPA,
1997).
These
cost
savings
provide
a
partial
measure
of
the
monetary
benefit
of
improved
sludge
quality.

EPA
estimates
that
the
incremental
record­
keeping
associated
with
the
cumulative
Land
Application­
Low
limits
requires
two
to
four
hours
per
application.
Materials
costs
for
meeting
these
requirements
should
be
negligible.
EPA
estimated
the
record­

keeping
costs
avoided
from
upgrading
sludge
quality
from
Land
Application­
Low
to
Land
Application­
High
standards,
using
the
following
assumptions:

 
a
40­
acre
site
is
a
typical
site
size
for
land
application
(
approximately
16
hectares)
(
US
EPA,
1997);

 
the
typical
application
rate
for
land
application
is
7
DMT
per
hectare
per
application
(
US
EPA,
1997);
and
4
 
labor
at
POTWs
costs
an
average
of
$
30.42
per
hour
(
2001$),
based
on
the
§
308
POTW
Survey.

Based
on
these
assumptions,
EPA
estimated
that
$
0.54
to
$
1.09
would
be
saved
per
DMT
of
sludge
upgraded
from
Land
Application­
Low
to
Land
Application­
High.
5
4
See
Appendix
F
for
detail.

5
Savings
per
DMT
are
calculated
by
dividing
the
estimated
labor
cost
per
application
($
30.42
per
Hour
*
Hours
per
Application)
by
the
total
amount
of
sludge
disposed
of
per
one
application
(
16
Hectares
*
7
DMT
per
hectare).

16­
9
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
16.2.5
Quantifying
Sludge
Benefits
EPA
estimated
the
number
of
POTWs
receiving
MP&
M
discharges
and
the
associated
quantity
of
sludge
that
would
not
meet
Land
Application­
High
pollutant
limits,
Land
Application­
Low
pollutant
limits,
or
surface
disposal
pollutant
limits
under
both
the
baseline
and
regulatory
options.
EPA
then
assumed
that,
as
a
result
of
compliance
with
the
MP&
M
effluent
limitations
guideline,
a
POTW
meeting
all
pollutant
limits
for
a
less
costly
sludge
use/
disposal
method
would
benefit
from
the
reduced
cost
of
that
particular
method.
EPA
estimated
the
reduction
in
sludge
use/
disposal
costs
using
the
steps
described
below:

1.
Estimate
total
industrial
baseline
and
post­
compliance
loadings
of
Part
503
regulated
metals
for
each
POTW
with
MP&
M
sample
facility
discharges;

2.
Calculate
the
baseline
and
post­
compliance
sludge
pollutant
concentrations
for
all
MP&
M
wastewater
discharged
to
the
POTW;

3.
Compare
POTW
sludge
pollutant
concentrations
with
sludge
pollutant
limits
for
surface
disposal
and
land
application;

4.
Estimate
baseline
and
post­
compliance
sludge
use/
disposal
practices
based
on
the
estimated
pollutant
concentrations
in
sewage
sludge;

5.
Identify
POTWs
that
upgrade
their
sewage
sludge
disposal
practices
under
the
alternative
policy
options;
calculate
the
economic
POTW
benefits
by
multiplying
the
cost
savings
for
the
shift
in
practices
by
the
quantity
of
newly
qualified
sludge;
adjust
the
estimate
of
benefits
for
the
percentage
of
POTWs
that
cannot
land
apply
sewage
sludge
due
to
transportation
costs
or
other
reasons,
such
as
cold
temperature;
and
6.
Estimate
national
benefits
using
MP&
M
sample
facility
weights.

a.
Step
1:
Estimate
total
industrial
baseline
and
post­
compliance
loadings
of
Part
503
regulated
metals
EPA
estimated
the
quantities
of
Part
503
metals
discharged
to
POTWs
receiving
wastewater
from
MP&
M
sample
facilities
and
facilities
operating
in
other
metal
discharging
industries.
6
EPA
used
POTW
Survey
data
to
estimate
the
total
metal
loadings
and
percent
of
total
loadings
discharged
to
POTWs
by
MP&
M
facilities.

The
POTW
Survey
provides
the
following
information:

 
number
of
known
MP&
M
facilities
discharging
to
the
POTW,

 
total
loadings
of
each
regulated
metal
received
by
the
POTW,
and
 
percent
of
the
total
metal
loadings
attributable
to
MP&
M
industries.

6
EPA
did
not
include
metals
from
residential
wastewater
due
to
lack
of
data.
The
effect
on
the
analysis
of
omitting
residential
metal
loadings
is
not
known.

16­
10
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
Table
16.5
summarizes
this
information
by
POTW
flow
volume.

Table
16.5:
MP&
M
Contribution
to
Total
Industrial
Loadings
Received
by
POTWs
MP&
M
Contribution
POTW
size
(
million
gallons
per
day)

2­
10
11­
50
>
50
MP&
M
facilities
Average
number
of
MP&
M
facilities
per
POTW
small
(<
1
MG/
year)
32.8
72.1
147.7
medium
(
1­
6.25
MG/
year)
2.5
8.0
24.5
large
(>
6.25
MG/
year)
1.2
2.7
10.4
Chemicals
MP&
M
percentage
of
total
loadings
by
weight
Arsenic
7.4
14.0
7.0
Cadmium
16.1
23.4
12.8
Copper
18.9
21.6
10.9
Lead
13.8
19.8
10.3
Mercury
7.9
20.8
6.0
Nickel
25.1
24.4
15.8
Selenium
7.2
8.5
3.3
Zinc
20.2
16.0
8.2
Source:
U.
S.
EPA,
§
308
POTW
Survey.

EP
A
estimated
to
tal
baseline
metal
load
ings
from
all
M
P&
M
sources,
as
follows:

(
16.1)

where:

PLM
k,
i
=
base
line
load
ings
of
p
ollutant
k
to
PO
TW
;
from
all
MP
&
M
sources
(
 
g/
year);

LMPsmall,
k,
i
=
loadings
of
p
ollutant
k
from
sm
all
(<
1
MG/
y
ear)
sample
MP&
M
f
ac
ilitie
s,
dis
ch
argin
g
to
POTW
i
(
 
g/
year);

AvgNumSm
=
the
average
number
of
small
MP&
M
fa
cilitie
s
dis
charging
to
P
OTW
i;
EPA
estimated
the
average
numb
er
of
M
P&
M
facilities
of
a
g
iven
size
(
small,
medium
,
large)
tha
t
discharge
to
P
OT
W
s
in
given
flow
categories,
based
on
the
§
308
PO
TW
Survey
(
see
Table
16.5);
7,8
SampleSm
=
number
of
MP&
M
sm
all
(<
1
MG/
year)
sa
mp
le
fa
cilitie
s
dis
charging
to
P
OTW;

LMPmedium,
k,
i
=
loadings
of
p
ollutant
k
from
m
edium
(
1­
6.2
5
M
G/
year)
sam
ple
M
P&
M
facilities,
disch
arging
to
PO
TW
s
(
 
g/
year);

AvgNumM
ed
=
the
a
verage
nu
mb
er
of
med
iu
m
MP&
M
fa
cilities
d
ischarging
to
PO
TW
i
(
based
on
th
e
POTW
flow
category
(
see
Table
16
.5));

7
EPA
classified
MP&
M
facilities
as
small,
medium,
and
large
flow
in
the
POTW
Survey,
based
on
their
discharge
volume.

8
This
analysis
considers
the
following
POTW
flow
categories:
(
1)
from
2
MG/
day
to10
MG/
day;
(
2)
from
11
to
50
MG/
day;
and
(
3)
greater
than
50
MG/
day.

16­
11
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
SampleMed
=
n
um
b
er
of
MP&
M
medium
(
1­
6
.2
5
MG/
year)
sa
mp
le
fa
cilities
d
ischar
ging
to
PO
TW
i;

LMPlarge,
k,
i
=
load
ings
of
p
ollutant
k
fr
om
large
(>
6.25
M
G/
year)
samp
le
MP&
M
f
acilities
d
isch
argin
g
to
PO
TW
i
(
 
g/
year);

AvgNumLg
=
the
average
number
of
large
MP&
M
fa
cilitie
s
dis
charging
to
P
OTW
i
(
based
on
the
POTW
flow
category
(
see
Table
16.5));
and
SampleLg
=
number
of
MP&
M
la
rg
e
(>
6.25
MG/
year)
sa
mp
le
fa
cilitie
s
dis
charging
to
P
OTW
i.

EP
A
estimated
to
tal
baseline
metal
load
ings
from
all
industrial
sources
using
d
ata
from
the
P
OT
W
Survey,
as
follows:

(
16.2)

where:

PLk,
i
=
total
ba
seline
loading
s
of
po
llutant
k
fr
om
all
in
du
strial
sources
to
POTW
i
(
 
g/
year),

PLM
k,
i
=
base
line
load
ings
of
p
ollutant
k
to
POTW
i
from
all
M
P&
M
sources
(
 
g/
year),

100%
=
the
total
re
ported
P
OT
W
transfers
o
f
pollutant
k
from
all
industrial
sources,
and
%
MPk
=
the
percentage
of
total
repo
rted
P
OT
W
transfers
o
f
pollutant
k
fr
om
MP&
M
fa
cilities
in
a
g
iv
en
POT
W
flow
category
(
see
Table
16
.5).

Post­
compliance
pollutant
loadings
to
POT
W
s
are
calculated
by
subtracting
the
reduction
in
MP&
M
load
ings
due
to
the
regulation
from
the
e
stimated
total
baseline
loa
dings.

b.
ge
quality
First,
for
each
metal
with
limits
under
the
Part
503
regulation,
EPA
calculated
POT
W
influent
concentrations
based
on
the
pollutant
loading
a
nd
PO
TW
flow
rates,
as
follows:

(
16.3)

where
:

ICk,
i
=
PO
TW
influent
co
ncentration
o
f
polluta
nt
k
(
 
g/
liter)
for
POTW
i;

PLk,
i
=
total
lo
ad
in
g
of
pollu
ta
nt
k
to
POTW
i
(
 
g/
year)
;

Fli
=
OT
W
i
flow
(
liters/
day);
and
ODi
=
OT
W
i
operation
days
(
365
days/
year).

Second
,
EP
A
ca
lculated
sludge
polluta
nt
con
centra
tions
for
each
polluta
nt:

(
16.4)

where
:

PCk,
i
=
concentra
tion
of
p
ollutant
k
in
POTW
i
sludge
(
mg/
kg
or
ppm),

ICk,
i
=
OT
W
i
influent
co
ncentration
o
f
polluta
nt
k
(
 
g/
liter
or
ppb),

TREk
=
treatment
rem
oval
efficiency
fo
r
pollutant
k
(
unitless),

PFk
=
sludge
partition
factor
fo
r
pollutant
k
(
unitless),
and
SG
=
sludge
gener
ation
fac
tor
((
L
­
mg)/(
 
g­
kg)
or
ppm/
ppb).

Th
e
par
tition
facto
r
represents
the
fraction
of
the
pollutant
lo
ad
ex
pected
to
partition
to
sludg
e
during
wastewater
treatment.

This
factor
is
chemical­
specific.
EPA
uses
a
sludge
generation
factor
of
5.96
(
mg
of
chemical/
kg
sludge)/(
g
chemical/
L
of
wastewater).
The
value
of
5.96
is
based
on
the
"
normal
quantity
of
sludge
produced
"
by
a
PO
TW
with
primary
sedimentation/
activated
sludge/
digestion/
dewatering
as
reported
in
Wastewater
Engineering
(
Metcalf
&
Eddy,
197
2).
The
estimated
sludge
generation
factor
indicates
that
concentration
in
sludge
is
5.96
ppb
dry
weight
for
every
1
ppb
of
pollutant
removed
and
partitioned
to
sludge.
Step
2:
Calculate
baseline
and
post­
compliance
slud
P
P
P
16­
12
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
c.
Step
3:
Compare
sludge
pollutant
concentrations
at
each
POTW
with
limits
for
surface
disposal
and
land
application
EPA
next
compared
sludge
baseline
and
post­
compliance
pollutant
concentrations
to
pollutant
limits
for
land
application
and
surface
disposal
using
the
following
formula:

(
16.5)

where
:

SE
p
=
sludge
exceeds
c
oncentratio
n
limits
for
d
isposal
or
use
pra
ctice,
p;

PCk
=
sludge
polluta
nt,
k,
concentration;
and
CRk,
p
=
sludge
polluta
nt,
k,
criterion
for
disp
osal
o
r
use
p
ractice
,
p.

If
any
sludge
pollutant
concentration
at
a
POTW
exceeds
the
pollutant
limit
for
a
sludge
use/
disposal
practice
in
the
baseline
(
i.
e.,
PC/
CR
>
1),
then
EPA
assumed
that
the
POTW
cannot
use
that
sludge
use/
disposal
practice.
,
as
a
result
of
compliance
with
the
MP&
M
regulation,
a
POTW
meets
all
pollutant
limits
for
a
sludge
use/
disposal
practice
(
i.
e.,
PC/
CR
 
1),
that
PO
TW
is
assumed
to
b
enefit
from
an
increase
in
sludge
use/
dispo
sal
options.

d.
imate
baseline
sludge
use/
disposal
practices
at
POTWs
that
can
meet
land
application
or
surface
disposal
pollutant
limits
post­
compliance
Benefits
from
changes
in
sludge
use/
disposal
practices
depend
on
the
baseline
practices
employed.
hat
PO
TW
s
choose
the
least
exp
ensive
sludge
use/
disp
osal
p
ractice
for
whic
h
their
slud
ge
me
ets
po
llutant
limits.
OT
W
s
with
sludge
qualifying
for
land
application
in
the
baseline
are
assumed
to
dispose
of
their
sludge
by
land
application;
likewise,

PO
TW
s
with
sludge
me
eting
surfa
ce
disp
osal
p
ollutant
lim
its
(
but
no
t
land
applic
ation
p
ollutant
lim
its)
are
ass
ume
d
to
dispose
o
f
their
sludge
on
surface
d
isposal
sites.

EPA
assumed
that
the
mix
of
surface
disposal
practices
employed
by
POT
W
s
in
the
baseline
(
e.
g.,
surface
disposal
in
a
lined
unit
and
su
rface
disposal
in
an
un
lined
un
it)
ma
tc
he
s
th
at
of
natio
na
l
surface
disposal
practic
es
as
ca
lc
ulated
fr
om
th
e
POTW
Survey
(
see
Table
16.1).

POTW
Survey
data
indicate
that
25
percent
of
total
sludge
meeting
Land
Application­
High
standards
is
sold
in
bags
and
75
percent
is
land­
applied.
sold
in
bags.
W
meeting
Land
App
lication­
H
igh
stand
ards
in
the
po
st­
com
plianc
e
scen
ario
is
assumed
to
sell
25
p
ercen
t
of
its
sludge
in
bags
and
to
land­
apply
the
remainder.

Th
e
PO
TW
Surve
y
shows
that
34
percent
of
total
surface
dispo
sed
sludge
is
dispo
sed
o
f
in
lined
un
its
and
6
6
pe
rcent
in
unlined
units.
face
disposal
practices
may
not
match
the
actual
sludge
disposal
surface
practices
of
any
individual
POTW
.
however,
the
assumed
surface
disposal
practices
are
consistent
with
actual
POT
W
sludge
surface
disposal
practices.
rvey
data
also
showed
that,
on
average,
7.5
percent
of
all
sludge
that
qualifies
for
surface
disposal
was
not
surface
disposed.

PO
TW
s
generating
slud
ge
exc
eeding
land
app
lication
a
nd
surface
d
isposal
pollutant
limits
in
the
baseline
are
assum
ed
to
either
incinerate
sludge
or
place
sludge
in
a
MSWL.
ey
indicates
that
39
percent
of
sludge
not
land­
applied
or
deposited
in
surface
disposal
sites
is
incinerated
and
61
percent
is
placed
in
MW
SLs.
exceeding
surface
disposal
and
land
application
limits
in
the
baseline
is
assumed
to
incinerate
39
percent
of
its
sludge
and
co­
dispose
of
the
rema
inder.
,
this
mix
of
sludge
use/
disp
osal
p
ractice
s
may
not
ma
tch
the
a
ctual
slud
ge
disp
osal
p
ractice
s
of
any
sin
gle
PO
TW
;
in
aggregate,
howe
ver,
the
assumed
distribution
corresp
onds
to
a
ctual
practices.

Using
the
sludge
disposal
cost
differentials
from
Ta
ble
16.4,
EPA
estimated
savings
for
shifts
into
land
application
and
surface
disposal
from
the
assumed
mix
of
baseline
use/
disposal
practices
(
see
Table
16.6).
As
previously
discussed,
EPA
assum
ed
that
50
p
ercen
t
of
sludge
cou
ld
not
be
use
d
be
neficially
(
lan
d­
ap
plied
or
so
ld
in
ba
gs)
and
dispo
sed
les
s
exp
ensive
ly
through
agricultural
application
of
sludge
due
to
transportation
costs,
land
availability,
or
weather
constraints.

did
not
estimate
benefits
for
this
percentage
of
the
sludge
newly
qualified
for
land
application.
If
Step
4:
Est
EPA
assumes
t
P
None
of
the
sludge
meeting
Land
Application­
Low
standards
is
Each
POT
This
mix
of
sur
In
aggregate,

Su
The
surv
Each
POTW
Again
The
Agency
16­
13
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
e.
Step
5:
Calculate
economic
benefits
for
POTWs
receiving
wastewater
from
sample
MP&
M
facilities
Table
16.6
shows
the
cost
savings
for
shifts
from
composite
baseline
sludge
use/
disposal
practices
to
land
application
or
surface
disposal.
Reductions
in
sludge
use/
disposal
costs
are
calculated
for
each
POTW
receiving
wastewater
from
an
MP&
M
facility,
using
the
following
formula:

(
16.6)

where
:

SCRi
=
e
stim
ated
sludge
use/
disposal
cost
reductio
ns
re
su
ltin
g
fr
om
th
e
regula
tion
fo
r
POTW
i
(
2001$
);

FLi
=
OT
W
i
wastewater
flow
(
million
gallons/
year);

S
=
sludge
to
wastewater
ratio,
assumed
to
be
1,127
lbs.
(
dry
weight)
per
million
gallons
of
water
(
lbs./
million
gallons)
and
divided
by
2,200
to
convert
pounds
to
metric
tons;
and
CDi
=
e
stim
ated
cost
diffe
re
ntia
l
betw
ee
n
le
as
t
costly
composite
ba
se
line
use/
disposal
meth
od
fo
r
whic
h
POTW
i
qualifie
s
and
le
as
t
costly
use/
disposal
meth
od
fo
r
whic
h
POTW
i
qualifies
post­
compliance
(
2001$/
D
MT
).
P
Table
16.6:
Cost
Savings
from
Shifts
in
Sludge
Use/
Disposal
Practices
from
Composite
Baseline
Disposal
Practices
(
2001$/
DMT)

Baseline
POTW
Mix
of
Sludge
Use/
Disposal
Practices
Post­
Compliance
POTW
Sludge
Use/
disposal
Practice
Agricultural
Application­
High
(
75%

of
sludge
meeting
Land
Application­
High
pollutant
limits)
Bagged
Sludge
(
25%
of
sludge
meeting
Land
Application­
High
pollutant
limits)
Agricultural
Application­

Low
Surface
Disposala
(
Meet
surface
pollutant
limits;
do
not
meet
land
application
pollutant
limits)

Meets
Land
Application­
Low
pollutant
limits,
but
not
Land
Application­
High
limits
$
0.54­
1.09
N/
Ab
N/
A
N/
A
Meets
surface
disposal
pollutant
limits,
but
not
Land
Application­

Low
limits
Assumed
disposal
mix:

34%
lined
unit
66%
unlined
unit
$
126.39
$
6.44
$
71.89
$
0.59
$
126.39
$
6.44
N.
A.

Does
not
meet
land
application
pollutant
limits
or
surface
disposal
pollutant
limits
Assumed
disposal
mix:

39%
incineration,
61%
co­
disposal
$
103.82
$
100.44
$
95.91
$
69.96
$
103.82
$
100.44
$
0­$
103.08
N/
A
a
Surface
disposal
includes
monofills,
surface
impoundments,
and
dedicated
sites.

b
Not
applicable
(
i.
e.,
there
is
no
cost
savings).

Source:
U.
S.
EPA,
§
308
POTW
Survey.

EPA
assumed
that
only
50
percent
of
the
sludge
qualified
for
land
application
is
beneficially
used
(
i.
e.,
land­
applied
or
sold
in
bags).
The
remaining
50
percent
of
the
sludge
newly
qualified
for
land
application
will
be
disposed
of
by
other
methods;

therefore,
EPA
assumed
that
no
cost
savings
will
be
associated
with
50
percent
of
the
sludge
qualified
for
land
application.

To
ensure
that
these
benefits
are
not
overstated,
this
analysis
includes
an
adjustment
to
the
estimate
of
national
sludge
use/
disposal
cost
benefits
for
POTWs
that
may
be
located
at
some
distance
from
agricultural
sites.
This
adjustment
does
not
apply
to
benefits
from
shifts
into
surface
disposal.

16­
14
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
f.
Step
6:
Estimate
national
sludge
benefits
EPA
scaled
the
sludge
use/
disposal
cost
reductions
to
the
national
level
as
follows:

(
16.7)

where:

NSCR
=
national
estimated
sludge
use/
disposal
cost
reductions
resulting
from
the
regulation
(
2001$);

n
=
numbe
r
of
PO
TW
s
estimated
to
shift
into
meeting
surface
d
isposal
or
land
application
p
ollutant
limits
as
a
result
of
MP
&
M
effluent
limitations;

FWi
=
facility
sample
weights
for
facility
or
fa
cilities
d
isch
arging
to
PO
TW
i;
and
SCRi
=
e
stim
ated
sludge
use/
disposal
cost
reductio
ns
re
su
ltin
g
fr
om
th
e
regula
tion
fo
r
POTW
i
(
2001$
).

16.3
ESTIMATED
SAVINGS
IN
SLUDGE
USE/
DISPOSAL
COSTS
Of
the
POTWs
receiving
discharge
wastewater
from
MP&
M
facilities,
1,020
POTWs
exceed
the
Land
Application­
High
pollutant
limits
and
856
exceed
the
Land
Application­
Low
pollutant
limits
at
baseline
discharge
levels
under
the
alternative
options
considered
for
the
final
rule.
This
represents
approximately
6
percent
of
the
over
16,000
operating
POTWs
nationwide.
The
number
of
POTWs
exceeding
Land
Application­
High
and
Land
Application­
Low
pollutant
limits
under
the
Proposed/
NODA
Option
at
baseline
conditions
is
equal
to
5,328
and
3,728,
respectively.
9
The
final
rule
only
regulates
direct
dischargers
and,
as
a
result,
sewage
sludge
quality
will
not
be
affected
by
the
selected
option.
EPA,
however,
did
estimate
savings
in
sludge
disposal
costs
for
the
alternative
options
which
consider
both
direct
and
indirect
dischargers.
EPA
used
the
estimated
sludge
use/
disposal
cost
differentials
presented
in
Table
16.6
to
calculate
cost
savings
for
the
POTWs
expected
to
upgrade
their
sludge
disposal
practices
under
alternative
policy
options.
These
results
are
presented
in
Table
16.7
below.
The
benefits
are
estimated
at
$
11,319
to
$
22,539
(
2001$)
annually
for
both
upgrade
options.

The
Proposed/
NODA
Option
would
result
in
more
substantial
cost
savings
(
i.
e.,
$
22.8
million
(
2001$))
to
POTWs.
However,

the
Proposed/
NODA
Option
is
not
directly
comparable
to
the
two
upgrade
options
due
to
inconsistent
baselines.

9
The
total
number
of
facilities
reported
for
the
Proposed/
NODA
Option
analysis
differs
from
the
facility
count
reported
for
the
final
rule
and
the
upgrade
options
(
Directs
+
413
to
433
Upgrade
Option,
Directs
+
All
to
433
Upgrade
Option).
After
deciding
in
July
2002
not
to
consider
the
NODA
option
as
the
basis
for
the
final
rule,
EPA
did
not
perform
any
more
analyses
on
the
NODA
option
­­
including
not
updating
facility
counts
and
related
analyses
for
the
change
in
subcategory
and
discharge
status
classifications.

16­
15
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
Table
16.7:
ional
Estimate
of
Cost
Savings
from
Shifts
in
Sludge
Use/
Disposal
Under
the
Alternative
Policy
Optionsa
Shift
Category/
Number
of
POTWs
Associated
Sludge
Quantity
(
DMT/
Year)
Estimated
Benefits
(
2001$)

Directs
+
413
to
433
Upgrade
Upgrade
from
minimum
Land
Application­
Low
limits
to
Land
Application­
High
pollutant
limits
15
16,548
$
11,319
to
$
22,539
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
High
pollutant
limits
0
$
0
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
Low
pollutant
limits
0
$
0
Total
15
16,548
$
11,319
to
$
22,539
Directs
+
All
to
433
Upgrade
Upgrade
from
minimum
Land
Application­
Low
limits
to
Land
Application­
High
pollutant
limits
15
16,548
$
11,319
to
$
22,539
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
High
pollutant
limits
0
$
0
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
Low
pollutant
limits
0
$
0
Total
15
16,548
$
11,319
to
$
22,539
Proposed/
NODA
Option
Upgrade
from
minimum
Land
Application­
Low
limits
to
Land
Application­
High
pollutant
limits
45
88,389
$
60,458
to
$
120,386
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
High
pollutant
limits
24
140,460
$
6,725,273
Upgrade
from
not
meeting
land
application
or
surface
disposal
limits
to
Land
Application­
Low
pollutant
limits
25
316,565
$
16,009,889
Total
93
545,414
$
22,795,620
to
$
22,855,548
Nat
0
0
0
0
a
Based
on
the
Traditional
Extrapolation.

Source:
U.
S.
EPA
analysis.

16.4
Methodology
Limitations
EPA
used
the
POTW
Survey
to
develop
estimates
of
the
cost­
saving
differentials
for
the
various
sludge
use/
disposal
practices.
Sludge
use/
disposal
costs
vary
by
POTW.
The
POTWs
affected
by
the
MP&
M
regulation
may
face
costs
that
differ
from
those
estimated.
As
a
result,
the
analysis
may
over­
or
under­
estimate
the
cost
differentials.

POTW
Survey
data
were
also
used
to
estimate
metal
loadings
to
POTW
s
in
the
baseline
analysis.
There
are
two
major
limitations
associated
with
this
approach:

 
The
baseline
metal
loadings
from
individual
MP&
M
facilities
of
interest
may
differ
from
this
estimate.
The
effect
of
using
the
§
308
survey
data
to
characterize
the
POTWs
that
receive
MP&
M
discharges
is
therefore
not
known.

 
The
total
share
of
metals
coming
from
MP&
M
facilities
is
likely
to
be
underestimated
because
lower
flow
MP&
M
facilities
are
not
always
known
by
the
POTW.
During
the
pretest
of
the
MP&
M
POTW
questionnaire,
POTWs
told
EPA
that
they
were
not
aware
of
many
of
the
lower
flow
facilities
that
were
discharging
to
them.
The
POTW
would
have
to
use
the
phone
book
in
order
to
find
and
permit
these
facilities.
EPA
consequently
considered
exempting
low
flow
facilities
in
the
general
metals
and
only
oily
wastes
indirect
discharge
categories
under
some
of
the
alternative
regulatory
options.

16­
16
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
This
analysis
assumes
that
the
mix
of
disposal
practices
estimated
for
a
specific
POTW
may
not
match
the
actual
sludge
disposal
practices
used
by
that
POTW.
We
know
that
the
mix
in
the
aggregate,
as
confirmed
by
the
POTW
Survey,
is
correct.

The
practices
used
in
this
analysis
are
therefore
consistent
with
actual
POTW
sludge
surface
disposal
practices.
Because
accurate
assumptions
for
specific
POTWs
could
not
be
made,
the
analysis
may
over­
or
underestimate
the
cost
differentials.

EPA
quantified,
but
did
not
monetize
economic
benefits
from
reducing
interference
with
POTW
operations
for
the
alternative
regulatory
options.
EPA
did
not
estimate
cost
reductions
that
occur
at
POTW
s
with
sludge
inhibition
problems
caused
by
MP
&
M
discharges.
These
omissions
thereby
underestimate
the
benefits
of
the
regulation.

16­
17
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
GLOSSARY
hazardous
air
pollutants
(
HAPs):
air
pollutants
that
are
not
covered
by
ambient
air
quality
standards
but
which,
as
defined
in
the
Clean
Air
Act,
may
present
a
threat
of
adverse
human
health
effects
or
adverse
environmental
effects.
Such
pollutants
include
asbestos,
beryllium,
mercury,
benzene,
coke
oven
emissions,
radionuclides,
and
vinyl
chloride.
MP&
M
pollutants
include
but
are
not
limited
to:
chlorobenzene,
dioxin,
1,4­
isophorone,
and
pyrene.

(
http://
www.
epa.
gov/
OCEPAterms/
hterms.
html)

hazardous
waste
landfill:
an
excavated
or
engineered
site
where
hazardous
waste
is
deposited
and
covered.

(
http://
www.
epa.
gov/
OCEPAterms/
hterms.
html)

influent
concentrations:
measure
of
a
pollutant's
concentration
in
wastewater
being
received
by
a
POTW
for
treatment
(
see
also:
pollutant
inhibition
values).

interference:
the
obstruction
of
a
routine
treatment
process
of
POTWs
that
is
caused
by
the
presence
of
high
levels
of
toxics,
such
as
metals
and
cyanide
in
wastewater
discharges.
These
toxic
pollutants
kill
bacteria
used
for
microbial
degradation
during
wastewater
treatment
(
see:
microbial
degradation).

microbial
degradation:
the
breakdown
of
organic
molecules
via
biochemical
reactions
occurring
in
living
microorganisms
such
as
bacteria,
algae,
diatoms,
plankton,
and
fungi.
POTWs
make
use
of
microbial
degradation
for
wastewater
treatment
purposes.
This
process
is
inhibited
by
the
presence
of
toxics
such
as
metals
and
cyanide
because
these
pollutants
kill
microorganisms.

municipal
solid
waste
landfill
(
MSWL):
common
garbage
or
trash
generated
by
industries,
businesses,
institutions,
and
homes.
Also
known
as
municipal
solid
waste.
(
http://
www.
epa.
gov/
OCEPAterms/
mterms.
html)

pathogens:
microorganisms
(
e.
g.,
bacteria,
viruses,
or
parasites)
that
can
cause
disease
in
humans,
animals
and
plants.

(
http://
www.
epa.
gov/
OCEPAterms/
pterms.
html)

pollutant
inhibition
values:
determined
threshold
concentration
for
a
pollutant,
which
when
exceeded
by
the
pollutant's
influent
concentration
in
wastewater
received
for
treatment
will
have
adverse
effects
on
POTW
operations,
such
as
inhibition
of
microbial
degradation
(
see:
microbial
degradation).

publicly­
owned
treatment
works
(
POTWs):
a
treatment
works
as
defined
by
Section
212
of
the
Act,
which
is
owned
by
a
state
or
municipality.
This
definition
includes
any
devices
or
systems
used
in
the
storage,
treatment,
recycling,
and
reclamation
of
municipal
sewage
or
industrial
wastes
of
a
liquid
nature.

(
http://
www.
epa.
gov/
owm/
permits/
pretreat/
final99
.
pdf)

silviculture:
management
of
forest
land
for
timber.
(
http://
www.
epa.
gov/
OCEPAterms/
sterms.
html)

vector:
1.
An
organism,
often
an
insect
or
rodent,
that
carries
disease.
2.
Plasmids,
viruses,
or
bacteria
used
to
transport
genes
into
a
host
cell.
A
gene
is
placed
in
the
vector;
the
vector
then
"
infects"
the
bacterium.

(
http://
www.
epa.
gov/
OCEPAterms/
vterms.
html)

16­
18
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
ACRONYMS
DMT:
dry
metric
tons
HAPs:
hazardous
air
pollutants
MSWL:
municipal
solid
waste
landfill
POTWs:
publicly­
owned
treatment
works
16­
19
MP&
M
EEBA
Part
III:
Benefits
Chapter
16:
POTW
Benefits
REFERENCES
Association
of
Metropolitan
Sewage
Agencies
(
AMSA).
2000.
Survey
on
Proposed
MP&
M
Effluent
Guidelines.

Metcalf
and
Eddy.
1972.
Wastewater
Engineering.
New
York,
NY:
McGraw­
Hill,
Inc.

Solid
Waste
Disposal
Facility
Criteria.
40
CFR
Part
258,
Federal
Register
50978,
October
9,
1991)

Standards
for
the
Use/
Disposal
of
Sludge.
40
CFR
Part
503,
February
1993.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1985.
Handbook
for
Estimating
Sludge
Management
Costs
U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1987.
Guidance
for
Preventing
Interference
with
POTW
Operations.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1993a.
Standards
for
the
Use
and
Disposal
of
Sludge;
Final
Rules.
40
CFR
Part
257
et
al.,
Federal
Register,
February
19.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1993b.
Regulatory
Impact
Analysis
of
the
Part
503
Sludge
Regulation.

Final.
Office
of
Water.
EPA
821­
12­
93­
006.
March.

U.
S.
Environmental
Protection
Agency
(
U.
S.
EPA).
1997.
Economic
Assessment
for
Proposed
Pretreatment
Standards
for
Existing
and
New
Sources
for
the
Industrial
Laundry
Point
Source
Category.
Office
of
Water.
EPA
821­
R­
97­
008
(
pp
10­
51
­
10­
54).

16­
20
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
Chapter
17:
Environmental
Justice
&

Protection
of
Children
INTRODUCTION
Executive
Order
12898
requires
that,
to
the
greatest
extent
practicable
and
permitted
by
law,
each
federal
agency
must
make
achieving
environmental
justice
part
of
its
mission.

Therefore,
EPA
examined
whether
the
final
regulation
will
promote
environmental
justice
in
areas
affected
by
MP&
M
discharges.
CHAPTER
CONTENTS
17.1
raphic
Characteristics
of
Populations
Living
in
the
Counties
Near
MP&
M
Facilities
.....
17­
1
17.2
Children
from
Environmental
Health
and
Safety
Risks
.................
......
17­
3
Glossary
.................
.................
...
17­
4
Reference
.................
.................
..
17­
5
Demog
Protection
of
EPA
concludes
that
discharges
from
MP&
M
facilities
regulated
under
the
final
rule
do
not
have
a
disproportional
environmental
impact
on
minority
populations,
based
on
the
demographic
characteristics
of
the
populations
residing
in
the
counties
affected
by
MP&
M
discharges.

The
final
rule
is
not
subject
to
Executive
Order
13045,
 
Protection
of
Children
from
Environmental
Health
Risks
and
Safety
Risks"
(
62
FR
19885,
April
23,
1997),
because
it
is
based
on
technology
performance
and
not
on
health
or
safety
risks.

However,
EPA
analyzed
the
reduction
of
children's
health
impacts
associated
with
the
MP&
M
regulation,
and
determined
that
reductions
in
the
baseline
lead
exposure
are
minimal.

The
following
section
assesses
whether
MP&
M
discharges
have
a
disproportionally
high
impact
on
minority
populations.

17.1
DEMOGRAPHIC
CHARACTERISTICS
OF
POPULATIONS
LIVING
IN
THE
COUNTIES
NEAR
MP&
M
FACILITIES
EPA
assessed
whether
adverse
environmental,
human
health,
or
economic
effects
associated
with
MP&
M
facility
discharges
are
more
likely
to
affect
minorities
and
low­
income
populations.
This
analysis
uses
data
on
the
race,
national
origin,
and
income
level
of
populations
residing
in
counties
traversed
by
reaches
receiving
discharges
from
the
32
sample
MP&
M
facilities
considered
in
the
final
rule
analysis.
The
32
sample
facilities
are
located
in
46
counties
in
12
states.
The
MP&
M
survey
was
designed
to
provide
a
representative
coverage
of
various
types
of
MP&
M
facilities,
but
not
of
their
geographical
location.
EPA
is
therefore
able
to
analyze
only
the
location
characteristics
of
the
sample
facilities,
and
not
all
43,901
MP&
M
dischargers.
1
EPA
compared
demographic
data
from
the
1990
Population
Census
for
the
counties
traversed
by
sample
MP&
M
reaches
with
the
corresponding
state
level
indicators
(
U.
S.
Census
Bureau,
1990).
EPA
considered
several
demographic
characteristics
to
assess
the
environmental
justice
of
the
final
regulation,
including
the
relative
proportions
of
African
Americans,
Native
Americans,
and
Asian
or
Pacific
Islanders,
median
income,
the
proportion
of
the
population
below
the
poverty
level,
unemployment
percentage,
and
the
proportion
of
the
population
that
are
children.
Table
17.1
presents
the
results
of
this
analysis,
which
show
that
the
demographic
characteristics
of
MP&
M
counties
generally
reflect
state
averages.

EPA
calculated
median
income
for
the
group
of
counties
in
each
state
receiving
MP&
M
discharges
as
a
weighted
average
of
2
each
county's
median
household
income.
County s
populations
are
used
as
weights
in
this
analysis.
EPA
calculated
this
summary
variable
in
place
of
the
true
median
household
income
for
MP&
M
counties
because
appropriate
census
data
are
not
1
This
estimate
of
MP&
M
facilities
includes
baseline
closures.

2
Average
median
income
in
MP&
M
counties
=

 
i
Median
Income
(
i)
×
Number
of
Households
(
i)/
 
Number
of
Households
(
i),
where
(
i)
is
a
sample
MP&
M
county.

17­
1
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
available.
The
Agency
notes
that
comparing
this
weighted
average
median
income
to
the
state­
level
median
income
may
introduce
uncertainty
in
the
analysis.

Income
data,
as
well
as
other
characteristics
examined
to
determine
whether
minority
and/
or
low­
income
populations
are
subject
to
disproportionally
high
environmental
impacts,
show
that
the
socioeconomic
characteristics
of
populations
residing
in
counties
affected
by
MP&
M
discharges
reflect
corresponding
state
averages.
Based
on
these
findings,
EPA
expects
that
environmental
benefits
resulting
from
the
MP&
M
rule
will
not
accrue
to
populations
disproportionally
based
on
race
or
national
origin
and
therefore
will
promote
environmental
justice.

Table
17.1:
County
Level
Comparison
of
Demographic
Data:
Counties
with
Sample
MP&
M
Facilities
Versus
Entire
State
State
Counties
%

White
%

African­

American
%
Native
Am.,

Eskimo,

or
Aleut
%
Asian
or
Pacific
Islander
Median
Income
%

Below
Poverty
Level
%

Unemployed
%

Children
California
MP&
M
Only
3
58.64%
11.82%
0.53%
11.20%
$
36,100
13.98%
7.04%
25.83%

Entire
State
58
69.07%
7.39%
0.84%
9.57%
$
35,798
12.51%
6.65%
26.01%

Indiana
MP&
M
Only
3
95.38%
3.76%
0.23%
0.41%
$
24,785
14.31%
7.42%
23.38%

Entire
State
93
90.59%
7.75%
0.26%
0.66%
$
28,797
10.68%
5.74%
26.29%

Kentucky
MP&
M
Only
1
98.44%
0.54%
0.12%
0.74%
$
34,485
7.40%
3.64%
29.38%

Entire
State
120
92.06%
7.11%
0.19%
0.47%
$
22,534
19.03%
7.37%
25.93%

Maryland
MP&
M
Only
1
94.61%
4.47%
0.35%
0.34%
$
36,019
7.50%
4.56%
26.86%

Entire
State
24
71.03%
24.87%
0.30%
2.88%
$
39,386
8.27%
4.30%
24.31%

Mississippi
MP&
M
Only
3
56.88%
42.46%
0.09%
0.47%
$
26,342
19.31%
6.93%
28.00%

Entire
State
82
63.46%
35.59%
0.34%
0.49%
$
20,136
25.21%
8.43%
29.04%

Missouri
MP&
M
Only
1
99.45%
0.04%
0.44%
0.04%
$
17,594
18.87%
4.00%
24.21%

Entire
State
115
87.68%
10.69%
0.44%
0.77%
$
26,362
13.34%
6.16%
25.71%

New
York
MP&
M
Only
2
92.64%
4.90%
0.34%
0.78%
$
25,864
12.13%
10.57%
28.09%

Entire
State
63
74.47%
15.90%
0.33%
3.83%
$
32,965
13.03%
6.88%
23.66%

North
Carolina
MP&
M
Only
3
88.47%
10.71%
0.23%
0.33%
$
26,189
10.75%
3.94%
24.10%

Entire
State
100
75.60%
21.96%
1.25%
0.76%
$
26,647
12.97%
4.79%
24.27%

Ohio
MP&
M
Only
2
89.17%
9.69%
0.24%
0.74%
$
28,527
11.70%
6.82%
24.76%

Entire
State
89
87.81%
10.62%
0.21%
0.82%
$
28,706
12.54%
6.60%
25.85%

Oklahoma
MP&
M
Only
4
82.68%
8.48%
6.99%
1.06%
$
26,456
13.63%
5.86%
26.20%

Entire
State
77
82.26%
7.38%
8.03%
1.04%
$
23,577
16.71%
6.87%
26.60%

17­
2
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
Table
17.1:
County
Level
Comparison
of
Demographic
Data:
Counties
with
Sample
MP&
M
Facilities
Versus
Entire
State
State
Counties
%

White
%

African­

American
%
Native
Am.,

Eskimo,

or
Aleut
%
Asian
or
Pacific
Islander
Median
Income
%

Below
Poverty
Level
%

Unemployed
%

Children
Pennsylvania
MP&
M
Only
22
92.89%
6.12%
0.12%
0.64%
$
27,851
11.56%
6.46%
22.88%

Entire
State
68
88.57%
9.15%
0.13%
1.14%
$
29,069
11.13%
5.97%
23.54%

Washington
MP&
M
Only
1
84.94%
4.97%
1.18%
7.90%
$
36,179
7.96%
4.15%
22.56%

Entire
State
40
88.64%
3.03%
1.71%
4.34%
$
31,183
10.92%
5.72%
25.86%

Source:
U.
S.
EPA
analysis
of
1990
Census
Data
(
U.
S.
Bureau
of
Census
1990).

17.2
PROTECTION
OF
CHILDREN
FROM
ENVIRONMENTAL
HEALTH
AND
SAFETY
RISKS
EPA
assessed
whether
the
final
regulation
will
benefit
children,
including
reducing
health
risk
from
exposure
to
MP&
M
pollutants
from
consumption
of
contaminated
fish
tissue
and
drinking
water
and
improving
recreational
opportunities.
EPA
was
able
to
quantify
only
one
category
of
benefits
specific
to
children:
avoided
health
damages
to
pre­
school
age
children
from
reduced
exposure
to
lead.
This
analysis
considered
several
measures
of
children s
health
benefits
associated
with
lead
exposure
for
children
up
to
age
six.
Avoided
neurological
and
cognitive
damages
were
expressed
as
changes
in
three
metrics:

(
1)
overall
IQ
levels;
(
2)
the
incidence
of
low
IQ
scores
(<
70);
and
(
3)
the
incidence
of
blood
lead
levels
above
20
mg/
dL.

EPA
also
assessed
changes
in
the
incidence
of
neonatal
mortality
from
reduced
maternal
exposure
to
lead.
EPA s
methodology
for
assessing
lead­
related
benefits
to
children
is
presented
in
Chapter
14
of
this
report.

The
Ohio
case
study
analysis
showed
that
the
final
rule
is
expected
to
yield
$
422,000
(
2001$)
in
annual
benefits
to
children
in
the
state
of
Ohio
from
reduced
neurological
and
cognitive
damages
and
reduced
incidence
of
neonatal
mortality.
On
the
other
hand,
the
national­
level
analysis
shows
that
benefits
to
children
from
reduced
lead
discharges
are
negligible
nationwide.
As
noted
in
Chapter
18,
different
findings
from
these
two
analyses
are
likely
to
be
due
to
insufficient
data
and
a
more
simplistic
approach
used
in
the
national­
level
analysis.

Children
over
age
seven
are
also
likely
to
benefit
from
reduced
neurological
and
cognitive
damages
from
reduced
exposure
to
lead.
Giedd
et
al.
(
1999)
studied
brain
development
among
10
to
18
year­
old
children
and
found
substantial
growth
in
brain
development,
mainly
in
the
early
teenage
years.
This
research
suggests
that
older
children
may
be
hypersensitive
to
lead
exposure,
as
are
children
aged
0
to
7.

Additional
benefits
to
children
from
reduced
exposure
to
lead
not
quantified
in
this
analysis
may
include
prevention
of
the
following
adverse
health
effects:
slowed
or
delayed
growth,
delinquent
and
anti­
social
behavior,
metabolic
effects,
impaired
heme
synthesis,
anemia,
impaired
hearing,
and
cancer
(
see
Chapter
14
of
this
report
for
details).

17­
3
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
GLOSSARY
MP&
M
reach:
a
reach
to
which
an
MP&
M
facility
discharges.

17­
4
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
REFERENCES
U.
S
Bureau
of
Census.
1990.
1990
Census
of
Population
Data.
http://
www.
census.
gov/.

Giedd,
J.
N.,
L.
Blumenthal,
N.
O.
Jeffries,
F.
X.
Castellanes,
Hong
Liu,
A.
Zijdenbos,
Tomas
Paus,
Alan
C.
Evans,
and
J.

Rapoport.
1999.
 
Brain
Development
During
Childhood
and
Adolescence:
A
Longitudinal
MRI
Study. 
Nature
Neuroscience,
Vol.
2,
No.
10.
October:
861­
863.

17­
5
MP&
M
EEBA
Part
III:
Benefits
Chapter
17:
Environmental
Justice
&
Protection
of
Children
THIS
PAGE
INTENTIONALLY
LEFT
BLANK
17­
6