Document ID: EPA-HQ-OW-2002-0039-0377
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-08-12T04:00Z

United
States
EPA
Science
Advisory
EPA­
SAB­
DWC­
03­
005
Environmental
Board
(
1400A)
May
2003
Protection
Agency
Washington
DC
www.
epa.
gov/
sab
Disinfection
Byproducts
and
Surface
Water
Treatment:
A
EPA
Science
Advisory
Board
Review
of
Certain
Elements
of
the
Stage
2
Regulatory
Proposals
A
Review
by
the
Drinking
Water
Committee
of
the
EPA
Science
Advisory
Board
Executive
Committee
1
Only
partial
drafts
of
the
two
rules
were
provided;
see
Sections
3.3,
4.1
for
listing
of
review
materials.
May
21,
2003
EPA­
SAB­
DWC­
03­
005
Honorable
Christine
Todd
Whitman
Administrator
U.
S.
Environmental
Protection
Agency
1200
Pennsylvania
Avenue,
NW
Washington,
DC
20460
Subject:
Disinfection
Byproducts
and
Surface
Water
Treatment:
A
EPA
Science
Advisory
Board
Review
of
Certain
Elements
of
the
Stage
2
Regulatory
Proposals
Dear
Governor
Whitman:

This
review
was
conducted
by
a
panel
convened
in
response
to
a
request
by
the
Office
of
Ground
Water
and
Drinking
Water
(
OGWDW)
that
the
EPA
Science
Advisory
Board
(
SAB)
review
several
parts
of
two
rules1
that
are
being
proposed
together:

1.
The
Long
Term
2
Enhanced
Surface
Water
Treatment
(
LT2ESWT)
rule.
2.
The
Stage
2
Disinfectant/
Disinfection
Byproducts
(
S2DBP)
rule.

The
panel
consisted
of
the
twelve
members
of
the
SAB
Drinking
Water
Committee
(
DWC)
and
six
consultants.

During
September,
2000,
a
Federal
Stakeholder
Advisory
Committee
(
Stage
2
Microbial
Disinfectants
and
Disinfection
Byproducts
Advisory
Committee)
reached
an
Agreement
in
Principle
on
recommendations
for
both
these
"
Stage
2"
rules
after
nearly
two
years
of
fact
finding,
deliberation,
negotiation,
and
consensus
building.
The
Stage
1
rules
promulgated
in
1998,
had
also
been
developed
after
a
series
of
formal
negotiations
with
stakeholders.
This
report
presents
the
results
of
the
SAB
Drinking
Water
Committee
(
DWC)
review
of
information
provided
by
Agency
on
the
Stage
2
rules.
The
LT2ESWT
rule
is
intended
to
increase
protection
of
public
water
systems
against
microbial
pathogens,
with
specific
focus
on
Cryptosporidium.
The
S2DBP
rule
is
intended
to
increase
protection
of
public
water
systems
from
disinfection
2
Determination
of
regulatory
action
using
a
simple
classification
of
water
sources
based
on
observed
cryptosporidium
densities
("
bins").

2
byproducts
(
DBPs),
specifically
variability
in
exposure.
OGWDW
intends
to
propose
and
finalize
the
LT2ESWT
and
S2DBP
rules
simultaneously
so
that
systems
maintain
adequate
microbial
protection
while
reducing
risk
from
disinfection
byproducts.

The
Agency's
charges
with
the
Panel's
comments
follow
in
abbreviated
form:

LT2ESWT
Rule:

Charge:
The
SAB
was
asked
to
comment
on
1)
the
analysis
of
the
occurrence
(
measured,
modeled)
of
a
disease­
inducing
protozoan
(
Cryptosporidium)
in
drinking
water
systems,
2)
the
validity
of
a
risk
assessment
both
before
and
after
applying
the
proposed
treatment
methods
in
the
LT2ESWTR
to
those
drinking
water
distribution
systems
and
3)
the
proposed
treatment
credits
(
effectiveness
in
reducing
protozoan
contamination)
by
four
methods
including
offstream
water
storage,
pre­
sedimentation,
lime
softening
and
reducing
filtered
water
turbidity
(
referred
to
as
microbial
toolbox
options).

Findings:

1.
The
Panel
commends
the
Agency
on
its
groundbreaking
work
addressing
the
impact
of
the
proposed
regulation
on
endemic
disease
and
agrees
that
the
regulation
should
address
this
issue.
On
the
other
hand,
neither
the
design
of
the
regulation
nor
the
form
of
the
economic
analysis
directly
addresses
waterborne
outbreaks.
Historically
waterborne
outbreaks
are
the
primary
stimulus
for
the
regulation
and
they
are
the
arena
where
intervention
through
improved
water
treatment
has
demonstrated
its
greatest
effectiveness.
Failure
to
consider
the
impact
of
the
proposed
regulation
on
reducing
waterborne
disease
outbreaks
underestimates
the
benefit
of
this
regulation
on
public
health.
2.
There
is
a
large
amount
of
uncertainty
in
the
modeling
of
the
occurrence
of
Cryptosporidium
and
of
the
incidence
of
the
disease
cryptosporidiosis
and
the
current
benefits
analysis
does
not
give
this
uncertainty
sufficient
visibility.
3.
The
modeling
of
Cryptosporidium
occurrence
appears
to
be
plausible
and
well
done.
On
the
other
hand:
a)
The
economic
analysis
is
necessarily
complex
and
a
greater
effort
is
required
for
effective
communication.
b)
Some
statistical
issues
need
to
be
addressed,
and
c)
Understanding
the
transmission
of
cryptosporidiosis
should
be
explored
more
thoroughly.
4.
The
Panel
also
commends
the
Agency,
as
well
as
the
stakeholder
process,
for
developing
the
bin
classification
framework2
as
it
adds
great
flexibility
to
the
rule.
3
Previous
probability
assessments
of
existing
data
used
to
estimate
occurrence
under
new
conditions.

4
These
terms
refer
to
by­
products
of
the
chlorination
process.
The
Panel
believes
that
the
terminology,
TTHMs
(
total
trihalomethanes),
to
represent
the
four
regulated
bromine­
and
chlorine­
containing
THMs
is
not
adequate
since
they
do
not
represent
the
full
spectrum
of
trihalomethanes
in
drinking
water.
For
example,
for
some
time
researchers
have
also
been
reporting
iodinated
THMs
in
finished
drinking
water.
To
avoid
confusion
regulations
that
pertain
to
only
the
four
bromine­
and
chlorine­
containing
THMs
should
refer
to
these
as
THM4.
A
precedent
for
this
form
of
nomenclature
already
exists,
e.
g.
HAA5,
HAA6,
HAA9.
For
the
sake
of
clarity
this
report
has
attempted
to
employ
that
nomenclature
throughout.

3
Recommendations:

1.
Reducing
the
likelihood
of
waterborne
outbreaks
should
continue
to
be
one
of
the
most
important
goals
of
Agency
regulations
in
water
treatment.
The
Panel
recommends
the
Agency
conduct
a
systematic
review
of
the
design
of
the
LT2ESWT
Rule,
assessing
its
effectiveness
in
addressing
outbreaks.
Changes
should
be
considered
if
necessary.
2.
The
magnitude
of
the
uncertainty
in
estimating
the
occurrence
of
Cryptosporidium
oocysts
and
estimating
the
risk
of
Cryptosporidium
infection
and
the
potential
significance
of
these
uncertainties
to
the
over­
or
under­
estimation
of
benefits
should
have
high
visibility
in
any
final
documents.
3.
With
regard
to
the
modeling
of
the
occurrence
of
cryptosporidiosis,
the
Agency
should:
a)
Include
better
graphics
in
the
documentation
to
help
the
reader
understand
the
analytical
process.
b)
Conduct
and
document
sensitivity
analyses
to
the
prior
distributions3
and
demonstrate
the
absence
of
seasonal
effects
on
annual
average
Cryptosporidium
concentrations.
c)
Clarify
and
justify
the
selection
of
the
dose­
response
function,
assumptions
about
oocyst
infectivity,
assumptions
of
host
susceptibility,
and
estimates
of
water
consumption.
d)
Provide
more
information
on
evidence
of
endemic
disease;
discuss
the
significance
of
secondary
transmission;
discuss
the
role
asymptomatic
infections
play
in
disease
transmission
and
address
the
effect
of
age
on
host
susceptibility
to
the
disease.
e)
Compare
the
quantitative
microbial
risk
assessment
approach
used
by
the
Agency
to
previous
quantitative
risk
assessments
for
Cryptosporidium
described
in
the
scientific
literature.
4.
For
the
bin
Classifications
the
Agency
asked
the
Panel
to
review,
our
recommended
credits
are
as
follows:
a)
for
off­
stream
and
pre­
sedimentation
­
no
credits,
b)
for
two
stage
lime
softening
­
0.5
credits,
but
only
if
all
the
water
is
treated
in
both
stages;
and
c)
for
plants
that
meet
special
requirements
in
each
filter
­
0.5
credits.

S2DBP
Rule:

Charge:
The
Agency
asked
the
SAB
to
comment
on:
1)
whether
the
locational
running
annual
average
(
LRAA)
(
a
new
method
of
estimating
concentrations
of
DBPs)
of
total
trihalomethanes
(
TTHM)
4
and
haloacetic
acids
(
HAA5),
in
conjunction
with
the
initial
distribution
system
evaluation
(
IDSE)
(
recommendations
to
utilities
for
identifying
appropriate
monitoring
sites)
of
4
the
proposed
rule
more
effectively
achieves
public
health
protection
than
the
running
annual
average
(
RAA)
(
current
method
of
estimating
concentrations
of
DBPs)
of
the
Stage
1
DBP
rule
and
2)
if
the
IDSE
is
capable
of
identifying
new
compliance
monitoring
points
that
target
high
TTHM3
and
HAA5
levels
and
if
it
is
the
most
appropriate
tool
available
to
achieve
this
objective.

Findings:

1.
The
Panel
believes
that
the
proposed
DBP2
rules
will
result
in
a
reduction
in
the
health
risk
to
drinking
water
consumers.
a)
The
principal
outcome
of
these
rules
will
be
increased
assurance
that
each
consumer
will
be
exposed
to
regulated
DBP
levels
that
are
at
or
below
the
MCLs
specified.
b)
A
second,
important
outcome
will
be
a
reduction
in
the
average
level
of
the
regulated
DBPs
in
many
systems.
2.
The
Panel
does
not
believe
that
the
current
draft
of
the
benefits
document
does
an
adequate
job
of
reflecting
the
uncertainties
associated
with
estimating
the
reduction
in
the
health
risk
to
drinking
water
consumers:
a)
The
Source
Water
Analytical
Tool
(
SWAT)
is
used
to
estimate
DBP
concentrations
in
distribution
systems
before
and
after
the
rule,
but
the
Agency's
own
work
demonstrates
that
SWAT
does
not
do
a
good
job
of
this.
b)
The
rule
seeks
to
reduce
short
term
exposure
to
high
DBP
levels,
but
the
IDSE
is
used
to
identify
monitoring
points
with
high
DBP
levels
and
it
does
not
consider
diurnal
short­
term
variations.
c)
Benefits
are
estimated
by
assuming
that
the
incidence
of
DBP­
related
bladder
tumors
will
decrease
in
proportion
to
the
reduction
in
the
nine
regulated
DBPs,
but
it
is
not
evident
that
this
will
occur
because
it
has
not
been
adequately
demonstrated
that
bladder
cancer
is
associated
with
any
of
the
regulated
DBPs.
3.
The
Panel
believes
that
substantial
further
research
will
be
required
before
the
benefits
of
DBP
reduction
can
be
adequately
quantified.

Recommendations:

1.
The
Panel
recommends
that
the
Agency
promulgate
the
proposed
rule
without
delay,
pursuing
the
IDSE
and
LRAA
as
more
effective
means
of
controlling
exposure
to
DBPs
in
drinking
water
than
present
practice.
a)
The
Agency
should
give
high
visibility
to
the
fact
that
this
rule
will
increase
the
assurance
that
each
consumer
will
receive
water
that
meets
the
DBP
MCLs.
b)
The
Agency
should
also
give
high
visibility
to
the
fact
that
this
rule
can
be
expected
to
reduce
the
average
level
of
regulated
DBPs
in
most
systems.
5
2.
The
Panel
recommends
that
the
Agency
do
a
more
straightforward
job
of
describing
the
uncertainties
in
the
benefits
analysis:
a)
Either
the
portion
of
the
benefits
analysis
which
used
the
SWAT
should
be
abandoned
or
the
presentation
should
be
revised
to
reflect
the
true
uncertainties
associated
with
the
use
of
this
model.
b)
The
Agency
should
acknowledge
that
the
IDSE
does
not
consider
short
term
(
diurnal)
variations.
c)
The
Agency
should
be
more
candid
about
the
limitations
it
faces
in
estimating
improvements
in
health
risk
reduction
due
to
the
implementation
of
the
new
rule
rather
than
assuming
that
bladder
cancers
will
be
reduced
in
proportion
to
reductions
in
THM4
and
HAA5.
3.
For
the
future,
so
that
it
can
address
the
limitations
inherent
in
the
use
of
the
surrogates
(
THM4,
HAA5)
to
represent
the
full
spectrum
of
DBPs
present
in
drinking
water,
the
Panel
recommends
that
the
Agency:
a)
Focus
its
future
research
program
upon
identifying
causal
agents
for
bladder
cancer
and
other
adverse
health
effects
(
other
risks
of
cancer,
impairment
of
male
and
female
reproduction,
effects
on
developing
organisms)
associated
with
chlorinated
drinking
water
in
epidemiological
studies.
b)
Link
future
control
strategies
for
DBPs
more
directly
to
the
reduction
of
these
causal
agents.

Thank
you
for
the
opportunity
to
review
these
proposals
We
would
be
happy
to
continue
to
engage
with
the
Agency
as
it
pursues
this
action.
We
look
forward
to
your
response
to
this
report.

Sincerely,

/
s/
/
s/

Dr.
William
Glaze,
Chair
Dr.
R.
Rhodes
Trussell,
Chair
EPA
Science
Advisory
Board
Drinking
Water
Committee
EPA
Science
Advisory
Board
i
NOTICE
This
report
has
been
written
as
part
of
the
activities
of
the
EPA
Science
Advisory
Board,
a
Federal
advisory
committee
providing
extramural
scientific
information
and
advice
to
the
Administrator
and
other
officials
of
the
Environmental
Protection
Agency.
The
Board
is
structured
to
provide
balanced,
expert
assessment
of
scientific
matters
related
to
problems
facing
the
Agency.
This
report
has
not
been
reviewed
for
approval
by
the
Agency
and,
hence,
the
contents
of
this
report
do
not
necessarily
represent
the
views
and
policies
of
the
Environmental
Protection
Agency,
nor
of
other
agencies
in
the
Executive
Branch
of
the
Federal
government,
nor
does
mention
of
trade
names
or
commercial
products
constitute
a
recommendation
for
use.

Distribution
and
Availability:
This
EPA
Science
Advisory
Board
report
is
provided
to
the
EPA
Administrator,
senior
Agency
management,
appropriate
program
staff,
interested
members
of
the
public,
and
is
posted
on
the
SAB
website
(
www.
epa.
gov/
sab).
Information
on
its
availability
is
also
provided
in
the
SAB
monthly
newsletter
(
Happenings
at
the
Science
Advisory
Board).
Additional
copies
and
further
information
are
available
from
the
SAB
Staff
[
US
EPA
Science
Advisory
Board
(
1400A0,
1200
Pennsylvania
Avenue,
NW,
Washington,
DC
20460;
(
202)
564­
4533)].
ii
U.
S.
Environmental
Protection
Agency
Science
Advisory
Board
Executive
Committee
CHAIR
Dr.
William
H.
Glaze,
Oregon
Health
&
Science
University,
Beaverton,
OR
SAB
MEMBERS
Dr.
Henry
Anderson,
Wisconsin
Division
of
Public
Health,
Madison,
WI
Also
Member:
Environmental
Health
Committee
Dr.
Trudy
Cameron,
University
of
Oregon,
Eugene,
OR
Also
Member:
Advisory
Council
on
Clean
Air
Compliance
Analysis
Dr.
Maureen
L.
Cropper,
The
World
Bank,
Washington,
DC
Also
Member:
Environmental
Economics
Advisory
Committee
Dr.
Kenneth
Cummins,
Humboldt
State
University,
Arcata,
CA
Dr.
Virginia
Dale,
Oak
Ridge
National
Laboratory,
Oak
Ridge,
TN
Also
Member:
Ecological
Processes
and
Effects
Committee
Dr.
Domenico
Grasso,
Smith
College,
Northampton,
MA
Also
Member:
Environmental
Engineering
Committee
Dr.
Linda
Greer,
Natural
Resources
Defense
Council,
Washington,
DC
Also
Member:
Research
Strategies
Advisory
Committee
Dr.
Philip
Hopke,
Clarkson
University,
Potsdam,
NY
Also
Member:
Research
Strategies
Advisory
Committee
Clean
Air
Scientific
Advisory
Committee
Dr.
Janet
A.
Johnson,
MFG,
Inc.,
Fort
Collins,
CO
Also
Member:
Radiation
Advisory
Committee
Dr.
Roger
E.
Kasperson,
Stockholm
Environment
Institute,
Stockholm,
,
Sweden
Also
Member:
Research
Strategies
Advisory
Committee
Dr.
Raymond
C.
Loehr,
University
of
Texas
,
Austin,
TX
Dr.
Genevieve
Matanoski,
Johns
Hopkins
University,
Baltimore,
MD
Also
Member:
Research
Strategies
Advisory
Committee
Dr.
M.
Granger
Morgan,
Carnegie
Mellon
University,
Pittsburgh,
PA
iii
Dr.
Rebecca
Parkin,
The
George
Washington
University,
Washington,
DC
Also
Member:
Integrated
Human
Exposure
Committee
Dr.
William
H.
Smith,
Yale
University,
Center
Harbor,
NH
Dr.
R.
Rhodes
Trussell,
MWH­
Montgomery
Watson
Harza,
Pasadena,
CA
Also
Member:
Drinking
Water
Committee
SCIENCE
ADVISORY
BOARD
STAFF
Mr.
A.
Robert
Flaak,
Washington,
DC
Ms
Betty
Fortune,
Washington,
DC
Ms.
Diana
Pozun,
Washington,
DC
iv
U.
S.
Environmental
Protection
Agency
Science
Advisory
Board
Drinking
Water
Committee
Stage
2
DBP/
Surface
Water
Treatment
Rule
Review
Panel*

CHAIR
Dr.
R.
Rhodes
Trussell,
MWH­
Montgomery
Watson
Harza,
Pasadena,
CA.

DWC
MEMBERS**
Dr.
David
B.
Baker,
Heidelberg
College,
Tiffin,
OH
Dr.
Mary
Davis,
West
Virginia
University
Health
Sciences
Center,
Morgantown,
WV
Dr.
Ricardo
De
Leon,
Metropolitan
Water
District,
La
Verne,
CA
Dr.
Sidney
Green,
Howard
University,
Department
of
Medicine,
Washington,
DC
Member:
Environmental
Health
Committee
Dr.
Barbara
Harper,
Yakima
Indian
Nation,
West
Richland,
WA
Dr.
Lee
D.
(
L.
D.)
McMullen,
Des
Moines
Water
Works,
Des
Moines,
IA
Dr.
Christine
Moe,
Emory
University,
Atlanta,
GA
Dr.
Philip
Singer,
University
of
North
Carolina,
Chapel
Hill,
NC
Dr.
Gary
A.
Toranzos,
University
of
Puerto
Rico,
San
Juan,
PR
OTHER
SAB
MEMBERS
Dr.
Richard
Bull,
MoBull
Consulting,
Inc.,
Kennewick,
WA
Member:
Research
Strategies
Advisory
Committee
Dr.
Lauren
Zeise,
California
Environmental
Protection
Agency,
Oakland,
CA
Member:
Research
Strategies
Advisory
Committee
CONSULTANTS
Dr.
Mark
Benjamin,
University
of
Washington,
Seattle,
WA
Dr.
L.
Mark
Berliner,
Ohio
State
University,
Columbus,
OH
Dr.
Paul
Boulos,
MWH
Soft,
Inc.,
Broomfield,
CO
Dr.
Michael
J.
Daniels,
University
of
Florida,
Gainesville,
FL
v
Dr.
Gregory
Harrington,
University
of
Wisconsin,
Madison,
WI
Dr.
Charles
O'Melia,
The
Johns
Hopkins
University,
Baltimore,
MD
LIAISONS
Dr.
David
P.
Spath,
California
Department
of
Health
Services,
Sacramento,
CA
SCIENCE
ADVISORY
BOARD
STAFF
Mr.
Thomas
O.
Miller,
Washington,
DC
Dr.
James
N.
Rowe,
Washington,
DC
*
Members
of
this
SAB
Panel
consist
of:

a.
SAB
Members:
Experts
appointed
by
the
Administrator
to
serve
on
one
of
the
SAB
Standing
Committees.
b.
SAB
Consultants:
Experts
appointed
by
the
SAB
Staff
Director
to
a
one­
year
term
to
serve
on
ad
hoc
Panels
formed
to
address
a
particular
issue.
c.
Liaisons:
Members
of
other
Federal
Advisory
Committee
who
are
not
Members
of
Consultants
of
the
Board.
d.
Federal
Experts:
"
Federal
Experts"
are
federal
employees
who
have
technical
knowledge
and
expertise
relevant
to
the
subject
matter
under
review
or
study
by
a
particular
panel.

**
Current
Members
or
Members
at
the
time
of
the
Panel
review
vi
TABLE
OF
CONTENTS
1.
EXECUTIVE
SUMMARY
......................................................................................................
1
2.
INTRODUCTION
AND
CHARGE
.........................................................................................
5
2.1
Introduction
..................................................................................................................
5
2.2
The
Charge
...................................................................................................................
6
3.
LONG
TERM
2
ENHANCED
SURFACE
WATER
TREATMENT
RULE
........................................................................................................
7
3.1
Introduction
..................................................................................................................
7
3.2
Charge
Question
1:
Analysis
of
Cryptosporidium
occurrence
...................................
7
3.2.1
Panel
Response
to
LT2ESWTR
Charge
Question
1­­
Analysis
of
Cryptosporidium
occurrence
......................................................................
7
3.2.1.1
Background
....................................................................................
7
3.2.1.2
Panel
Conclusions
........................................................................
12
3.3
Charge
Question
2:
Pre­
and
post­
LT2ESWTR
Cryptosporidium
risk
assessment
............................................................................................................
14
3.3.1.1
Hazard
Identification
..................................................................
15
3.2.1.2
Dose­
Response
Assessment
........................................................
16
3.3.1.3
Exposure
Assessment
(
pgs
5­
14
­
5­
24)
.....................................
19
3.4
Charge
3:
Treatment
credits
for
four
microbial
toolbox
options
............................
21
3.4.1
Panel
Response
to
LT2ESWTR
Charge
Question
3
...................................
21
4.
STAGE
2
DISINFECTION
BYPRODUCTS
RULE
.............................................................
24
4.1
Charge
1:
Initial
Distribution
System
Evaluation
(
IDSE):
........................................
24
4.1.1
Panel
Response
to
S2DBP
rule
Charge
Question
1.
...................................
24
4.1.1.1
Initial
Distribution
System
Evaluation
(
IDSE)
Effectiveness
....
24
4.1.1.2
IDSE
Appropriateness
.................................................................
25
4.2
Charge
2:
Public
Health
Protection
of
S2DBPR.
....................................................
28
4.2.1
Panel
Response
to
S2DBPR
Charge
Question
2.
.......................................
28
REFERENCES
..........................................................................................................................
R­
1
ATTACHMENT
A
­
ACRONYMS
AND
ABBREVIATIONS
..............................................
A­
1
ATTACHMENT
B
­
SELECTED
GLOSSARY
OF
TERMS
...................................................
B­
1
ATTACHMENT
C
­
BIOSKETCHES
OF
THE
DRINKING
WATER
COMMITTEE
MEMBERS
....................................................................................................................
C­
1
1
1.
EXECUTIVE
SUMMARY
The
Drinking
Water
Committee
(
DWC)
of
EPA's
Science
Advisory
Board
(
SAB)
met
to
consider
several
support
documents
that
are
a
part
of
the
Agency's
Long
Term
2
Enhanced
Surface
Water
Treatment
(
LT2ESWT)
rule
and
the
Stage
2
Disinfectant/
Disinfection
Byproducts
(
S2DBP)
rule,
both
of
which
are
under
development
by
the
Agency.
During
September,
2000,
a
Federal
Stakeholder
Advisory
Committee
reached
an
Agreement
in
Principle
on
recommendations
for
both
these
Stage
2
rules
after
nearly
two
years
of
fact
finding,
deliberation,
negotiation,
and
consensus
building.
The
Stage
1
rule
promulgated
in
1998,
had
also
been
developed
after
a
series
of
formal
negotiations
with
stakeholders.
This
report
presents
the
results
of
the
SAB
Drinking
Water
Committee
(
DWC)
review
of
information
provided
by
the
Agency
on
the
Stage
2
rules.

The
1996
Amendments
to
the
Safe
Drinking
Water
Act
(
SDWA)
require
the
Agency
to
develop
National
Primary
Drinking
Water
Regulations
(
NPDWRs)
for
contaminants
which
have
an
adverse
effect
on
the
health
of
persons
and
where
regulation
provides
a
meaningful
opportunity
for
public
health
protection.
The
Agency
is
developing
a
LT2ESWT
rule
to
provide
increased
protection
for
public
water
systems
against
microbial
pathogens,
with
a
specific
focus
on
Cryptosporidium.
The
proposed
rule
is
intended
to
supplement
existing
surface
water
treatment
rules
by
establishing
targeted
treatment
requirements
for
systems
with
greater
vulnerability
to
Cryptosporidium.
Such
systems
include
those
with
high
concentrations
of
Cryptosporidium
in
their
source
water
and
those
that
do
not
provide
filtration.
In
addition,
the
1996
SDWA
Amendments
require
the
Agency
to
develop
a
S2DBP
rule.
The
intent
of
the
proposed
S2DBP
rule
is
to
reduce
the
variability
of
exposure
to
disinfection
byproducts
(
DBPs)
for
people
served
at
different
points
in
the
distribution
systems
of
public
water
supplies.
The
Agency
has
suggested
that
this
decreased
exposure
will
result
in
reduced
risks
from
potential
reproductive
and
developmental
health
effects
and
cancer.
To
be
consistent
with
the
SDWA
requirements
for
risk
balancing,
the
Agency
intends
to
propose
and
finalize
the
LT2ESWT
and
the
S2DBP
rules
simultaneously.
This
coordinated
approach
is
designed
to
ensure
that
systems
maintain
adequate
microbial
protection
while
reducing
risk
from
disinfection
byproducts.

The
Panel
believes
that
the
terminology,
TTHMs
(
total
trihalomethanes),
to
represent
the
four
regulated
bromine­
and
chlorine­
containing
THMs
is
not
adequate
since
they
do
not
represent
the
full
spectrum
of
trihalomethanes
present
in
drinking
water.
For
example,
for
some
time
researchers
have
also
been
reporting
iodinated
THMs
in
finished
drinking
water.
To
avoid
confusion,
regulations
that
pertain
to
only
the
four
bromine­
and
chlorine­
containing
THMs
should
refer
to
these
as
THM4.
A
precedent
for
this
form
of
nomenclature
already
exists,
e.
g.
HAA5,
HAA6,
HAA9.
For
the
sake
of
clarity
this
report
has
attempted
to
employ
that
nomenclature
throughout.

This
report
has
two
major
parts
reflecting
the
structure
of
the
Agency
Charge.
The
charge
to
the
SAB
Panel
for
the
Long
Term­
2
Enhanced
Surface
Water
Treatment
rule
asked
the
SAB
to
comment
on:
a)
the
analysis
of
Cryptosporidium
occurrence;
b)
the
pre­
and
post­
LT2ESWTR
Cryptosporidium
risk
assessment;
and
c)
the
proposed
treatment
credits
for
four
2
microbial
toolbox
options.
For
the
S2DBP
rule,
the
Agency
asked
the
SAB
to
comment
on:
a)
whether
the
locational
running
annual
average
(
LRAA)
for
total
trihalomethanes
(
TTHM)
and
haloacetic
acids
(
HAA5),
in
conjunction
with
the
initial
distribution
system
evaluation
(
IDSE),
of
the
proposed
rule
more
effectively
achieves
public
health
protection
than
the
running
annual
average
(
RAA)
of
the
Stage
1
DBP
rule
and
b)
if
the
IDSE
is
capable
of
identifying
new
compliance
monitoring
points
that
target
high
TTHM
and
HAA5
levels
and
if
it
is
the
most
appropriate
tool
available
to
achieve
this
objective.

For
the
LT2ESWTR,
because
the
risk
assessment
is
quite
complex,
the
Panel
recommends
that
the
document
include
graphics
that
show
how
the
different
elements
were
derived
and
how
they
relate
to
each
other.
For
clarity,
comments
and
recommendations
are
presented
separately
for
the
three
charge
questions
related
to
the
risk
assessment.

First,
the
Panel
concludes
that
the
occurrence
modeling
appears
to
be
both
plausible
and
well­
done.
However,
the
Panel
believes
that
a
number
of
issues
need
to
be
addressed,
either
by
supplementing
the
current
documents
and/
or
modifying
the
model.

The
Panel
recommends
that
the
Agency:

a)
Conduct
and
document
sensitivity
analyses
to
the
prior
distributions
and,
b)
Demonstrate
the
absence
of
seasonal
effects
on
the
annual
average
Cryptosporidium
concentration.

Secondly,
for
the
microbiological
risk
assessment
review,
each
of
the
basic
elements
was
examined
in
order:
hazard
identification,
dose­
response
assessment,
and
exposure
assessment.
Then
the
outcome
of
the
risk
assessment
was
evaluated.
Two
criteria
were
considered
in
the
Panel
evaluation:
a)
whether
the
Agency
assumptions
were
transparent,
and
b)
whether
scientific
evidence
exists
to
support
the
assumptions.
Cryptosporidium
parvum
has
been
responsible
for
significant
waterborne
disease
outbreaks,
and
it
is
likely
that
the
organism
is
responsible
for
reports
of
significant
endemic
disease
as
well.
Both
of
these
outcomes
are
important.
The
current
Agency
analysis
(
The
Cadmus
Group,
Inc.,
2001b)
for
the
LT2ESWTR
does
an
excellent
job
of
addressing
the
impact
of
drinking
water
quality
on
the
incidence
of
non­
reportable
endemic
disease
and
the
health
risk
reduction
that
will
result
from
the
reduction
of
endemic
disease
as
a
result
of
the
proposed
regulation.
The
Agency
is
to
be
congratulated
for
this
ground­
breaking
work.
On
the
other
hand,
in
the
present
draft,
neither
the
design
of
the
regulation
nor
the
contents
of
the
Agency
analysis
directly
address
reportable
waterborne
outbreaks.
These
outbreaks
are
the
primary
stimulus
for
the
regulation
and
reducing
their
occurrence
should
be
one
of
the
most
important
potential
outcomes
from
the
regulation
as
well.
The
Panel
recommends
that
the
Agency
conduct
a
systematic
review
of
the
design
of
the
LT2ESWTR
regulation
keeping
its
effectiveness
in
addressing
waterborne
outbreaks
in
mind.

a)
The
Panel
agrees
with
the
basic
information
on
Cryptosporidium
health
effects
in
the
Hazard
Identification
section
but
recommends
that
the
following
be
included
in
the
analysis:
a)
evidence
of
current
prevalence
of
endemic
disease;
b)
information
on
secondary
transmission
of
cryptosporidiosis;
and
c)
host
age
and
frequency
of
asymptomatic
infections.
3
b)
For
the
Dose­
Response
Assessment,
the
Panel
recommends
clarification
and
justification
of:
a)
the
basis
for
the
selection
of
the
dose
response
function
that
was
used
and
whether
other
models
were
considered;
b)
the
term
"
infectivity"
as
it
is
used
in
the
Agency
analyses;
c)
the
assumptions
about
infectivity
of
oocysts
used
in
human
dosing
experiments,
infectivity
of
oocysts
found
in
environmental
samples
and
of
the
significance
of
Cryptosporidium
genotype
when
evaluating
infectivity
for
humans;
and,
d)
assumptions
about
variability
in
host
susceptibility,
both
due
to
possible
immunity
resulting
from
previous
infections
and
due
to
other
susceptibility
factors
such
as
age
and
health.

c)
For
Exposure
Assessment,
the
estimates
of
consumption
require
clarification.

d)
For
the
Risk
Assessment,
the
Panel
notes
that
quantitative
microbial
risk
assessment
is
a
rapidly
developing
field.
The
Agency
should
a)
identify
other
approaches
to
microbial
risk
assessment,
especially
risk
assessments
for
Cryptosporidium,
that
are
reported
in
the
literature
and
consider
how
they
compare
to
their
own
assessment;
b)
include
a
discussion
of
uncertainties
and
variability;
and
c)
discuss
assumptions
which
may
lead
to
underestimates
or
overestimates
of
risk
and
benefits.

Finally,
for
the
treatment
credits
for
the
four
microbial
toolbox
options,
the
Panel
commends
the
Agency,
as
well
as
the
stakeholder
process
used,
for
developing
the
bin
classification
framework
for
identifying
the
treatment
requirements
for
drinking
water
and
the
microbial
toolbox
containing
possible
treatment
options
to
guide
systems
having
treatment
needs.
These
alternatives
add
great
flexibility
for
meeting
varying
water
quality
and
treatment
options
and
should
result
in
safe
drinking
water
for
the
people
of
the
United
States.
The
Agency
charged
the
Panel
with
evaluating
Agency
information
on
four
of
the
toolbox
options:
a)
off
stream
raw
water
storage;
b)
pre­
sedimentation,
c)
lime
softening
and
d)
lower
finished
water
turbidity.
Specifically,
the
Agency
asked
the
Panel
to
comment
on
the
credits
that
have
been
proposed
for
specific
toolbox
options
for
Cryptosporidium
removal.
In
summary,
the
Panel
recommends
that
no
presumptive
credits
be
given
for
off­
stream
storage
and
pre­
sedimentation.
It
does
agree
with
giving
0.5
log
credit
for
two­
stage
lime
softening
if
all
the
water
is
treated
with
both
stages,
and
0.5
log
credit
for
plants
that
demonstrate
a
turbidity
level
in
each
individual
filter
effluent
less
than
or
equal
to
0.15
NTU
in
at
least
95
percent
of
the
measurements
taken
each
month.
Details
about
these
recommendations
are
found
in
the
report.

For
the
Stage
2
DBP
rule,
the
Panel
believes
that
the
proposed
Initial
Distribution
System
Evaluation
is
capable
of
identifying
new
compliance
monitoring
points
that
target
higher
THM
and
HAA
levels
than
are
currently
measured
in
the
existing
THM
Rule
and
Stage
1
DBP
Rule
compliance
monitoring
programs.
However,
the
IDSE
does
not
consider
short­
term,
temporal
variations
that
occur
at
different
sites
in
the
distribution
system
due
to
varying
water
demands
and
distribution
system
architecture
and
operation.
This
temporal
variability
needs
to
be
acknowledged
in
the
IDSE
documentation.
The
Panel
further
believes
that
the
proposed
standard
monitoring
program
(
SMP)
for
sub­
part
H
systems
serving
more
than
10,
000
people
is
reasonable.
The
Panel,
however,
does
make
some
recommendations
concerning
the
proposed
4
sampling
requirements.
The
switch
from
the
running
annual
average
(
RAA)
approach
to
the
locational
running
annual
average
(
LRAA)
approach
provides
a
measure
of
equity
not
previously
reflected
in
the
standards
for
disinfection
by­
products.
The
LRAA
allows
one
to
state
that
a
larger
segment
of
the
consumers
will
be
provided
with
drinking
water
within
a
particular
water
system
which
will
meet
the
MCL
than
would
be
the
case
using
the
RAA
approach.
The
Panel
also
agrees
that
these
changes
are
likely
to
result
in
a
reduction
in
health
risk
due
to
DBP
exposure,
but
the
Agency
has
not
demonstrated
that
this
reduction
in
health
risk
will
be
in
direct
proportion
to
the
reduction
in
the
THM
and
HAA5
concentrations.

The
Committee
recommends
that
in
proposing
its
Stage
2
DBP
rule,
the
Agency:

a)
Continue
to
pursue
the
concept
of
locational
running
annual
averages
(
LRAAs)
as
a
more
effective
means
of
controlling
exposure
to
harmful
compounds
in
the
drinking
water
than
system­
wide
running
annual
averages
(
RAAs).
b)
Identify
temporal
limitations
in
the
IDSE
documentation
and
require
periodic
reevaluation
of
selected
sites;
c)
Reallocate
sampling
locations
so
that,
for
both
free
chlorine
and
chloramines,
sampling
takes
into
account
potential
high
THM
and
HAA
sites;
d)
Require
the
measurement
and
reporting
of
residual
chlorine
and
individual
THM
and
HAA
species;
e)
Provide
more
guidance
to
utilities
to
identify
sampling
sites
with
highest
HAA
concentrations;
f)
Improve
the
proposed
system
specific
studies
(
SSS)
approach
(
Chapter
6);
g)
Reconsider
the
use
of
the
SWAT
(
Surface
Water
Analytical
Tool)
model
and
ICR
(
Information
Collection
Rule)
data
in
economic
analyses
or
risk
reduction
calculations;
h)
Focus
their
research
program
upon
identifying
causal
agents
for
bladder
cancer
and
other
potential
adverse
health
effects
associated
with
chlorinated
drinking
water;
and,
i)
Link
control
strategies
for
DBPs
to
reduction
of
causal
factors
of
health
effects.
5
2.
INTRODUCTION
AND
CHARGE
2.1
Introduction
The
1996
Amendments
to
the
Safe
Drinking
Water
Act
(
SDWA)
require
the
Agency
to
develop
National
Primary
Drinking
Water
Regulations
(
NPDWRs)
for
contaminants
which
have
an
adverse
effect
on
the
health
of
persons
and
where
regulation
provides
a
meaningful
opportunity
for
public
health
protection.
The
Agency
is
developing
a
Long
Term
2
Enhanced
Surface
Water
Treatment
(
LT2ESWT)
rule
to
provide
increased
protection
for
public
water
systems
against
microbial
pathogens,
with
a
specific
focus
on
Cryptosporidium.
The
proposed
rule
is
intended
to
supplement
existing
surface
water
treatment
rules
by
establishing
targeted
treatment
requirements
for
systems
with
greater
vulnerability
to
Cryptosporidium.
Such
systems
include
those
with
high
concentrations
of
Cryptosporidium
in
their
source
water
and
those
that
do
not
provide
filtration.

In
addition,
the
1996
SDWA
Amendments
require
the
Agency
to
develop
a
Stage
2
Disinfectant/
Disinfection
Byproducts
(
S2DBP)
rule.
The
intent
of
the
proposed
S2DBP
rule
is
to
reduce
the
variability
of
exposure
to
disinfection
byproducts
for
people
served
at
different
points
in
the
distribution
systems
of
public
water
supplies.
The
Agency
has
suggested
that
this
decreased
exposure
will
result
in
reduced
risks
from
potential
reproductive
and
developmental
health
effects
and
cancer.

To
be
consistent
with
the
SDWA
requirements
for
risk
balancing,
the
Agency
intends
to
propose
and
finalize
the
LT2ESWT
and
the
S2DBP
rules
simultaneously.
This
coordinated
approach
is
designed
to
ensure
that
systems
maintain
adequate
microbial
protection
while
reducing
risk
from
disinfection
byproducts.
During
September,
2000,
a
Federal
Stakeholder
Advisory
Committee
reached
an
Agreement
in
Principle
on
recommendations
for
both
these
rules
after
nearly
two
years
of
fact
finding,
deliberation,
negotiation,
and
consensus
building.
Prior
to
that,
the
Stage
1
rules
for
DBPs
and
surface
water
treatment
also
reflected
periods
of
formal
regulatory
negotiations
and
stakeholder
discussions
over
a
period
of
years
stretching
from
the
early
to
mid­
1990s.

The
Panel
believes
that
the
terminology,
TTHMs
(
total
trihalomethanes),
to
represent
the
four
bromine­
and
chlorine­
containing
THMs
is
not
adequate
since
they
do
not
represent
the
full
spectrum
of
trihalomethanes
in
drinking
water.
For
example,
for
some
time
researchers
have
also
been
reporting
iodinated
THMs
in
finished
drinking
water.
To
avoid
confusion
regulations
that
pertain
to
only
the
four
bromine­
and
chlorine­
containing
THMs
should
refer
to
these
as
THM4.
A
precedent
for
this
form
of
nomenclature
already
exists,
e.
g.
HAA5,
HAA6,
HAA9.
For
the
sake
of
clarity
this
report
has
attempted
to
employ
that
nomenclature
throughout
The
EPA
Office
of
Ground
Water
and
Drinking
Water
(
OGWDW)
representatives
requested
that
the
EPA
Science
Advisory
Board
(
SAB)
review
several
parts
of
the
LT2ESWT
and
the
S2DBP
rule
proposals
and
certain
support
documents
and
provide
advice
in
response
to
a
6
number
of
charge
questions.
This
report
presents
the
results
of
the
SAB
Drinking
Water
Committee
(
DWC)
review
of
these
issues.

2.2
The
Charge
The
Agency
charge
to
the
SAB
Panel
for
the
Long
Term­
2
Enhanced
Surface
Water
Treatment
rule
asked
the
SAB
to
comment
on:
a)
the
analysis
of
Cryptosporidium
occurrence;
b)
the
preand
post­
LT2ESWTR
Cryptosporidium
risk
assessment;
and
c)
the
proposed
treatment
credits
for
four
microbial
toolbox
options.

For
the
Stage
2
DBP
rule,
the
Agency
asked
the
SAB
to
comment
on:
a)
whether
the
locational
running
annual
average
(
LRAA)
for
total
trihalomethanes
(
TTHM)
and
haloacetic
acids
(
HAA5),
in
conjunction
with
the
initial
distribution
system
evaluation
(
IDSE),
of
the
proposed
rule
more
effectively
achieves
public
health
protection
than
the
running
annual
average
(
RAA)
of
the
Stage
1
DBP
rule
and
b)
if
the
IDSE
is
capable
of
identifying
new
compliance
monitoring
points
that
target
high
TTHM
and
HAA5
levels
and
if
it
is
the
most
appropriate
tool
available
to
achieve
this
objective.
7
3.
LONG
TERM
2
ENHANCED
SURFACE
WATER
TREATMENT
RULE
3.1
Introduction
The
Agency
convened
a
group
of
stakeholders,
including
EPA
itself,
to
hold
formal
negotiations
on
issues
related
to
the
LT2ESWT
and
Stage
2
DBP
rules
from
1999
to
2000.
Their
Agreement
in
Principle,
which
contains
recommendations
for
the
proposed
LT2ESWT
and
Stage
2
DBP
rules,
was
published
in
the
Federal
Register
on
December
29,
2000
(
US
EPA,
2000).

In
general,
because
the
risk
assessment
is
quite
complex,
the
Panel
recommends
that
the
document
include
more
graphics
to
illustrate
how
the
different
elements
of
the
model
were
derived
and
how
they
relate
to
each
other.
Exhibit
5.2
(
The
Cadmus
Group,
Inc.,
2001b)
is
helpful
but
does
not
provide
sufficient
detail.
Additional
figures
are
needed
to
show
what
elements
were
in
the
pre­
regulation
risk
assessment
versus
the
post­
regulation
risk
assessment
and
how
the
reduction
in
risk
from
the
proposed
regulation
was
calculated.
Figures
3.1
through
3.4
of
this
report
are
examples
displaying
the
Panel's
understanding
based
on
its
reading
of
the
documents
provided
by
the
Agency
and
its
discussions
with
EPA
personnel
and
discussed
below.

3.2
Charge
Question
1:
Analysis
of
Cryptosporidium
occurrence
The
Agency
requested
SAB
comments
on
the
EPA
analysis
of
Cryptosporidium
occurrence.

The
Agency
provided
the
Panel
with
a
draft
document
entitled
Occurrence
and
Exposure
Assessment
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule.
(
The
Cadmus
Group,
2001a)
that
discusses
how
the
Agency
estimated
the
occurrence
distribution
of
Cryptosporidium
in
the
source
and
finished
water
of
public
water
systems
prior
to
implementation
of
a
new
LT2ESWT
rule.
Sections
of
the
document
considered
to
be
of
particular
importance
discussed
the
data
sources
used
to
estimate
Cryptosporidium
occurrence
in
source
water,
along
with
analytical
methods,
data
quality
issues,
and
the
statistical
techniques
used
to
model
occurrence
distributions;
information
on
observed
and
modeled
results
from
the
source
water
occurrence
surveys;
information
from
studies
of
the
physical
removal
of
Cryptosporidium
by
treatment
processes;
finished
water
occurrence
data
resulting
from
the
Information
Collection
Rule
(
ICR);
a
description
of
how
the
Agency
estimated
finished
water
Cryptosporidium
levels
prior
to
implementation
of
the
LT2ESWTR;
and
technical
information
on
the
statistical
models
used
to
analyze
source
water
occurrence
data.

3.2.1
Panel
Response
to
LT2ESWTR
Charge
Question
1­­
Analysis
of
Cryptosporidium
occurrence
3.2.1.1
Background.
The
model
developed
by
the
Agency
can
be
thought
of
in
three
parts
(
Figure
3­
1).
The
first
part
is
designed
to
address
an
important
limitation
of
the
data
collected
in
the
ICR
and
ICR
Supplemental
Survey
(
ICRSS),
namely
information
on
the
national
occurrence
of
Cryptosporidium
parvum
oocysts
at
levels
below
the
detection
limits
(
DLs)
of
the
4
Responses
are
modeled
above
the
detection
limit
as
a
function
of
turbidity,
location,
etc.,
and
the
model
uses
this
in
addition
to
information
about
the
number
below
the
detection
limit
to
`
impute'
values
below
the
limit.
The
MCMC
approach
also
integrates
over
the
uncertainty
of
the
values
below
the
detection
limit
(
as
opposed
to
`
imputing'
a
single
value).
In
terms
of
validation,
there
is
no
way
to
validate
`
values'
below
the
DL
as
they
were
not
observed,
but
we
can
determine
how
well
the
model
fits
for
values
above
the
limit
and
determine
whether
the
proportion
predicted
by
the
model
for
the
number
below
the
limit
is
consistent
with
the
observed
data.

8
methods
used
in
those
surveys.
Thus,
the
first
part
simulates
national
distributions
of
the
concentration
of
C.
parvum
oocysts
in
the
source
water.
Using
ICR
and
ICRSS
data,
the
model
is
designed
to
produce
an
estimate
of
the
national
occurrence
of
oocysts
in
untreated
surface
waters,
above
and
below
the
ICR
and
ICRSS
DL4s.
Bayesian
hierarchical
models
and
Markov
chain
Monte
Carlo
(
MCMC)
methods
are
used
to
accomplish
this
(
Figure
3­
2).
These
models
accommodate
the
many
complex
features
seen
in
the
data
used
by
the
Agency
to
develop
its
national
occurrence
estimates,
including
low
recovery
probabilities,
the
presence
of
false
positives,
and
the
presence
of
true
Cryptosporidium­
free
source
waters.

Figure
3­
1.
The
model
developed
by
the
EPA
contains
three
components.
The
first
uses
data
from
the
ICR
and
ICRSS
to
produce
a
national
distribution
of
C.
parvum
oocysts
in
untreated
surface
water.
The
second
uses
that
national
distribution
and
a
model
of
treatment
performance
to
produce
a
simulation
of
the
national
distribution
of
C.
parvum
oocysts
in
finished
water.
The
third
component
uses
a
dose­
response
model
calibrated
via
human
exposure
studies,
data
on
water
consumption,
and
finished
water
oocyst
levels
to
predict
the
level
of
endemic
disease.

Model
1
­
Occurrence
of
oocysts
in
raw
water
­
Model
uses
data
from
ICR
and
ICRSS
to
estimate
the
national
occurrence
of
C.
parvum
oocysts
in
raw
water
supplies
across
the
nation
Model
1
­
Occurrence
of
oocysts
in
raw
water
­
Model
uses
data
from
ICR
and
ICRSS
to
estimate
the
national
occurrence
of
C.
parvum
oocysts
in
raw
water
supplies
across
the
nation
Model
2
­
Occurrence
of
oocysts
in
Finished
water
­
Model
starts
with
data
from
Model
1
and
then
uses
estimates
of
removal
in
treatment
to
produce
an
estimate
of
the
national
occurrence
of
C.
parvum
oocysts
in
finished
water.
Treatment
performance
is
assumed
to
have
a
triangular
distribution
about
the
nominal
performance
specified.
To
estimate
occurrence
before
regulation,
existing
treatment
is
used.
To
estimate
occurrence
after
regulation,
a
decision
tree
is
employed
where
the
treatment
selected
depends
on
the
level
of
influent
oocysts
Model
2
­
Occurrence
of
oocysts
in
Finished
water
­
Model
starts
with
data
from
Model
1
and
then
uses
estimates
of
removal
in
treatment
to
produce
an
estimate
of
the
national
occurrence
of
C.
parvum
oocysts
in
finished
water.
Treatment
performance
is
assumed
to
have
a
triangular
distribution
about
the
nominal
performance
specified.
To
estimate
occurrence
before
regulation,
existing
treatment
is
used.
To
estimate
occurrence
after
regulation,
a
decision
tree
is
employed
where
the
treatment
selected
depends
on
the
level
of
influent
oocysts
Model
3
­
Occurrence
of
endemic
disease
­
Model
starts
with
data
from
Model
2
and
then
uses
a
dose­
response
model
to
estimate
the
occurrence
of
disease.
The
doseresponse
model
is
calibrated
using
data
from
three
available
human
feeding
studies.
Model
3
­
Occurrence
of
endemic
disease
­
Model
starts
with
data
from
Model
2
and
then
uses
a
dose­
response
model
to
estimate
the
occurrence
of
disease.
The
doseresponse
model
is
calibrated
using
data
from
three
available
human
feeding
studies.
9
Figure
3­
2.
Model
1:
Occurrence
of
oocysts
in
raw
water
­
Bayesian
hierarchical
models
and
MCMC
Methods
were
used
to
estimate
the
national
occurrence
of
C.
parvum
oocysts
in
raw
water.

1.
Conduct
ICR
and
ICRSS
1.
Conduct
1.
Conduct
ICR
and
ICR
and
ICRSS
ICRSS
MCMC
MCMC
(
)
(
)
(
)
0
turb
ij
MSW
ij
Loci
Monj
ij
Log
turb
MSW
ij
C
e
 
 
 
 
 
 
+
+
+
+
+
=
3.
Analyze
data
from
survey
and
propose
structure
for
model
that
can
be
used
to
predict
oocyst
concentrations
both
above
and
below
detection
limit
3.
Analyze
data
from
survey
and
propose
structure
for
3.
Analyze
data
from
survey
and
propose
structure
for
model
that
can
be
used
to
predict
model
that
can
be
used
to
predict
oocyst
oocyst
concentrations
both
above
concentrations
both
above
and
and
below
detection
limit
below
detection
limit
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
2.
Observed
oocyst
occurrence
only
shows
data
above
method
detection
limit
(
D.
L.)
2.
Observed
oocyst
occurrence
only
shows
data
above
method
detection
limit
(
D.
L.)
D.
L.

4.
Use
model
and
Markov
Chain
Monte
Carlo
(
MCMC)
methods
to
produce
a
new
"
simulated"
national
frequency
distribution
of
oocysts.
4.
Use
model
and
Markov
Chain
Monte
Carlo
(
MCMC)
methods
to
produce
a
new
"
simulated"
national
frequency
distribution
of
oocysts.
Fraction
of
samples
<

Log[
oocyst/
L]

Log[
oocyst/
L]
Fraction
of
samples
<

Corrected
Estimate
The
second
part
of
the
model
takes
the
national
occurrence
in
untreated
water
from
the
first
part
and
uses
treatment
assumptions
to
produce
an
estimate
of
the
national
occurrence
of
C.
parvum
oocysts
in
treated
water
(
Figure
3­
3).
To
estimate
occurrence
before
regulation,
treatment
credits
in
the
existing
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IEWSTR)
are
used.
The
proposed
regulation
assigns
water
systems
into
various
bins
depending
on
the
level
of
oocysts
in
their
untreated
water.
A
higher
degree
of
removal
is
required
for
systems
with
untreated
water
falling
into
bins
that
correspond
to
higher
oocyst
concentrations.
To
estimate
occurrence
after
regulation,
treatment
is
assumed
to
meet
the
requirements
that
correspond
to
the
bin
selected
for
each
supply.
For
the
analysis
in
this
second
part,
the
Agency
assumed
that
treatment
effectiveness
is
independent
of
concentration
and,
based
on
expert
opinion,
treatment
effectiveness
across
the
nation
is
assumed
to
follow
a
simple
triangular
distribution
with
the
mode
at
the
performance
specified
by
the
rule.
10
Figure
3­
3.
Model
2
­
Occurrence
of
oocysts
in
Finished
water
­
Treatment
performance
is
assumed
to
have
a
triangular
distribution.
Before
regulation,
existing
treatment
is
assumed
to
meet
the
IESWTR.
After
regulation,
a
decision
tree
is
employed
where
the
treatment
selected
depends
on
the
level
of
influent
oocysts
(
the
bin).

0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
Fraction
of
samples
<

Log[
oocyst/
L]

MCMC
MCMC
5.
Make
treatment
assumptions:
Before
rule,
assume
nominal
removal
equals
credit
in
IESWTR.
After
rule,
based
on
raw
water
"
bin"
choose
treatment
from
toolbox
and
give
credit
accordingly
5.
Make
treatment
assumptions:
Before
rule,
assume
nominal
removal
equals
credit
in
IESWTR.
After
rule,
based
on
raw
water
"
bin"
choose
treatment
from
toolbox
and
give
credit
accordingly
6.
Characterize
treatment
performance:
Assume
treatment
performance
follows
a
triangular
distribution
and
that
mode
of
distribution
varies
from
site
to
site
±
0.5
logs.
6.
Characterize
treatment
performance:
Assume
treatment
performance
follows
a
triangular
distribution
and
that
mode
of
distribution
varies
from
site
to
site
±
0.5
logs.

7.
Simulate
treatment
performance:
Use
MCMC
to
sample
raw
water
and
make
removal
estimate
while
varying
the
mode
of
triangular
treatment
distribution
±
0.5
logs.
To
produce
an
estimate
of
the
national
distribution
of
oocysts
in
finished
water.
7.
Simulate
treatment
performance:
Use
MCMC
to
sample
raw
water
and
make
removal
estimate
while
varying
the
mode
of
triangular
treatment
distribution
±
0.5
logs.
To
produce
an
estimate
of
the
national
distribution
of
oocysts
in
finished
water.
0%
25%
50%
75%
100%

0
2
4
Fraction
of
samples
<

Log[
oocyst/
L]
LogRemoval
Fraction
of
treatment
plants
The
third
part
of
the
model
estimates
the
national
occurrence
of
disease.
The
model
uses
the
national
occurrence
of
C.
parvum
oocysts
in
finished
water
and
combines
it
with
data
on
water
consumption
and
on
dose­
response
to
produce
an
estimate
of
disease.
The
model
considers
the
distribution
of
infection
(
and
disease)
conditional
on
the
concentration
of
viable
oocysts
in
the
drinking
water
through
the
use
of
an
exponential
dose­
response
model.
The
parameters
of
the
dose­
response
model
were
estimated
using
data
from
three
human
dosing
studies.
A
Bayesian
hierarchical
model
is
also
used
here
to
model
the
distribution
of
infectivity
across
Cryptosporidium
strains.
To
predict
the
occurrence
of
disease,
Monte
Carlo
methods
are
used
to
sample
oocyst
concentrations
in
finished
water
and
volumes
of
water
consumed
and
estimate
disease
using
the
dose­
response
model
(
Figure
3­
4).
11
Figure
3­
4.
Model
3
­
Occurrence
of
endemic
disease
­
Human
feeding
studies
are
used
to
calibrate
the
dose­
response
model
and
then
MCMC
methods
are
used
to
sample
from
finished
water,
determine
the
liters
consumed
and
estimate
the
national
incidence
of
endemic
disease.

0%
25%
50%
75%
100%

0
20
40
60
80
100
Oocyst
Dose
Fraction
Infected
0%
25%
50%
75%
100%

­
4
­
2
0
2
0%
25%
50%
75%
100%

­
4
­
2
0
2
8.
Dose
Response
is
calibrated
to
human
studies.
The
exponential
dose­
response
model
is
calibrated
using
data
from
human
studies
with
UCP,
Iowa
and
Tamu
isolates
of
C.
parvum.
8.
Dose
Response
is
calibrated
to
human
studies.
The
exponential
dose­
response
model
is
calibrated
using
data
from
human
studies
with
UCP,
Iowa
and
Tamu
isolates
of
C.
parvum.

National
Disease
incidence
National
Disease
incidence
9.
National
Incidence
of
Endemic
Disease
is
Simulated:
MCMC
is
used
to
sample
finished
water,
determine
volume
of
water
consumed,
and
then
predict
incidence
of
disease
using
dose
response
model
9.
National
Incidence
of
Endemic
Disease
is
Simulated:
MCMC
is
used
to
sample
finished
water,
determine
volume
of
water
consumed,
and
then
predict
incidence
of
disease
using
dose
response
model
Fraction
of
samples
<
0%
25%
50%
75%
100%

0
20
40
60
80
100
Oocyst
Dose
Fraction
Infected
Log[
oocyst/
L]

MCMC
MCMC
0%
25%
50%
75%
100%

0.5
1
1.5
2
2.5
Liters
Consumed
Fraction
0%
25%
50%
75%
100%

0.5
1
1.5
2
2.5
Liters
Consumed
Fraction
Monte
Carlo
integration
is
used
throughout
the
model,
and,
for
the
first
and
third
parts
of
the
model,
MCMC
methods
were
used
to
sample
from
posterior
distributions
which
are
used
to
both
estimate
parameters
in
the
model
and
to
address
the
uncertainty
associated
with
these
parameters.
In
complex
Bayesian
models,
MCMC
is
the
appropriate
way
to
do
this.
Both
parts
two
and
three
of
the
model
must
be
re­
run
each
time
different
regulations
or
different
treatment
conditions
must
be
considered.
5
Averaging
is
desired
for
12
months
for
an
annual
average
so
the
data
are
averaged
by
month
first
(
6
months
of
averaging
two
values
and
six
months
of
just
one
value)
and
then
averaging
across
months.
12
Immediately
below,
is
a
discussion
of
some
specific
issues
regarding
the
first
piece
of
the
model,
the
national
occurrence
distribution
of
Cryptosporidium.

3.2.1.2
Panel
Conclusions.
First,
the
Panel
concludes
that
the
occurrence
modeling
appears
to
be
both
plausible
and
well­
done.
However,
the
Panel
believes
that
a
number
of
issues
need
to
be
addressed,
either
by
supplementing
the
current
documents
and/
or
modifying
the
model.

The
Panel
recommends
that
sensitivity
analyses
of
the
modeling
effort
(
specifications
of
prior
distributions)
be
conducted
and
documented.
A
key
component
in
Bayesian
hierarchical
models
is
the
specification
of
prior
distributions,
which
a
priori,
characterize
the
state
of
knowledge
about
the
parameters
at
the
higher
levels
of
the
model.
Little
information
is
contained
about
such
priors
in
the
current
documentation
and
it
is
not
evident
that
the
sensitivity
of
the
occurrence
distribution
and
the
infectivity
parameter,
k,
to
these
priors
has
been
assessed.
Sensitivity
analyses
should
be
conducted
and
documented.
Particular
concerns
arise
when
the
data
are
used
to
assess
the
model
and
direct
the
selection
of
prior
distributions.
While
such
practices
are
sometimes
needed
in
difficult
problems,
they
can
result
in
underestimation
of
uncertainty
due
to
the
double
use
of
the
data.
The
analysts
need
to
be
clear
about
whether
or
not
such
methods
were
used,
and
if
so,
how
the
final
uncertainties
may
be
impacted.
Much
of
the
concern
can
be
ameliorated
through
complete
sensitivity
analysis.

The
Panel
also
recommends
that
seasonal
effects
be
more
carefully
addressed.
In
the
Panel's
opinion,
the
absence
of
seasonal
effects
on
the
annual
average
Cryptosporidium
concentration
has
not
been
demonstrated.
The
Agency
should
address
and
clarify
its
computation
of
the
average
Cryptosporidium
concentration
for
plants
in
a
system
over
the
18­
month
period
for
which
the
data
were
collected
in
the
Information
Collection
Rule
(
ICR).
Averaging
concentrations
equally
over
the
18
months
to
obtain
an
annual
average
will
only
give
an
unbiased
estimate
of
the
true
annual
average
if
there
are
no
seasonal
effects.
But
the
absence
of
seasonal
effects
has
not
been
demonstrated.
The
current
approach
effectively
counts
six
months
twice
in
the
averaging5.
During
discussions
at
the
DWC
meeting
in
December
2001,
Agency
representatives
stated
that
parameters
characterizing
seasonality
were
included
in
the
model
(
in
the
form
of
the
turbidity
term).
This
problem
might
be
solved
by
averaging
the
data
by
month,
and
then
to
using
the
mean
of
the
resulting
twelve
monthly
averages
as
the
annual
average.

The
Panel
believes
that
a
number
of
other
improvements
would
also
strengthen
the
Agency's
LT2ESWTR
documentation.
Additional
model
checking
should
be
conducted.
The
current
Agency
report
includes
some
model­
checking
using
the
estimated
distributions
of
true
concentrations,
but
the
Panel
recommends
additional
model
checking,
specifically,
an
additional
internal
check
and
an
external
check.
The
internal
check
could
use
the
current
output
from
the
MCMC
sampler
to
sample
from
the
distribution
of
predicted
oocyst
counts
("
Y")
(
from
the
posterior
predictive
distribution
of
"
Y")
.
To
assess
how
consistent
predictions
from
the
model
13
are
with
the
observed
data,
about
twenty
sample
distributions
can
be
plotted
versus
the
observed
distribution
of
counts.
The
observed
distribution
ideally
should
lie
within
these
20
and
should
look
similar.
For
an
external
check,
the
current
model
could
be
fit
to
the
first
12
months
of
the
18
month
ICR
data,
then
months
13­
18
could
be
predicted
by
the
model
and
finally
these
predictions
could
be
compared
to
the
observed
data.

There
are
some
additional
features
that
could
be
included
in
the
documentation
to
improve
the
clarity
of
the
Agency's
analyses.
A
map
of
the
sites
for
both
the
ICR
and
Information
Rule
Supplemental
Survey
(
ICRSS)
data
would
be
helpful
to
see
how
similar
the
spatial
distribution
of
sites
was
across
the
surveys
and
to
also
look
for
spatial
similarity
in
concentrations
for
sites
close
together
and/
or
in
the
same
regions
of
the
country.
In
addition,
the
Panel
recommends
that
a
short
paragraph
be
added
documenting
the
convergence
and
mixing
checks
on
the
MCMC
sampler.
An
additional
issue
of
moderate
importance
is
that
several
parameters
that
were
included
in
the
modeling
of
oocyst
levels
in
filtered
water
are
excluded
in
the
discussion
of
the
model
for
the
unfiltered
plants
(
e.
g.,
turbidity).
Justification
for
this
would
improve
the
clarity
of
the
Agency's
analysis.

The
Panel
notes
that
the
Agency
approach
to
concisely
summarize
the
occurrence
distribution
functions
using
parametric
models,
in
particular
the
log
normal
function,
was
done
to
simplify
computations
for
the
individuals
conducting
the
risk
analysis.
Documentation
could
be
made
available
to
confirm
that
the
realizations
of
the
cumulative
distribution
functions
(
CDFs)
from
the
MCMC
sampler
were
well
approximated
by
log­
normal
cumulative
distribution
functions
(
CDFs).
Second,
several
ad
hoc
simplifications
were
done
to
sample
the
CDF
for
the
risk
analysis
(
see
bottom
of
p.
5­
15
of
the
economic
analysis
document,
The
Cadmus
Group,
Inc.
2001b).
The
Panel
recommends
that
these
be
examined
carefully
for
their
plausibility
and
the
conclusions
documented.

The
Panel
concluded
that
there
is
a
large
amount
of
uncertainty
in
the
modeling
of
the
occurrence
of
Cryptosporidium.
For
example,
the
occurrence
distributions
are
estimated
based
on
only
one
year
of
data.
This
will
be
fine
if
these
distributions
are
stable
over
years.
However,
the
current
data
does
not
allow
determination
if
the
particular
year
in
which
the
data
were
collected
were
aberrant
(
for
example,
due
to
weather
patterns)
or
if
there
is
some
sort
of
trend
in
occurrence
over
time.
In
addition,
for
the
infectivity
modeling,
the
distribution
of
infectivity
across
strains
is
estimated
based
on
only
three
Cryptosporidium
strains
which
may
or
may
not
be
a
random
sample
of
strains.
The
only
way
this
distribution
can
be
estimated
is
to
make
a
strong
assumption
about
its
form
(
here
it
is
assumed
to
be
log­
normal).
The
ultimate
accuracy
of
the
predicted
decrease
in
disease
from
these
stochastic
models
relies
on
both
the
representativeness
and
applicability
of
the
observed
data
and
the
numerous
modeling
assumptions
that
were
made
in
the
course
of
the
three
pieces
of
the
model
discussed
at
the
beginning
of
this
section.
This
qualification
should
be
noted
in
the
document.
14
3.3
Charge
Question
2:
Pre­
and
post­
LT2ESWTR
Cryptosporidium
risk
assessment
Agency
requested
SAB
comments
on
the
pre­
and
post­
LT2ESWTR
Cryptosporidium
risk
assessment.

The
Agency
provided
the
Panel
with
partial
drafts
of
documents
entitled:
1)
Economic
Analysis
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
The
Cadmus
Group,
Inc.,
2001b)
and
2)
Appendices
to
the
Economic
Analysis
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
The
Cadmus
Group,
Inc.,
2001c).
These
documents
show
how
the
Agency
estimated
the
incidence
of
endemic
cryptosporidiosis
attributable
to
drinking
water
both
prior
to
and
following
implementation
of
the
LT2ESWTR.
Information
in
the
documents
considered
by
the
Agency
to
be
of
particular
relevance
included:

a)
a
summary
of
the
LT2ESWTR
to
be
proposed,
based
on
the
Stage
2
 
DBP
Advisory
Committee
Agreement
in
Principle;
b)
baseline
information
used
to
conduct
the
risk
assessment;
c)
descriptions
of
how
the
Agency
modeled
pre­
and
post­
LT2ESWTR
risk
of
cryptosporidiosis;
d)
a
summary
of
how
the
Agency
predicted
the
technologies
that
filtered
and
unfiltered
systems
would
select
to
comply
with
the
LT2ESWTR;
e)
descriptions
of
how
the
Agency
estimated
the
percentage
of
plants
expected
to
receive
0.5
and
1.0
log
additional
Cryptosporidium
treatment
credit
under
the
LT2ESWTR;
f)
details
on
estimates
of
the
percent
of
systems
that
would
be
assigned
to
different
bins
as
a
result
of
source
water
monitoring
under
the
LT2ESWTR;
g)
distributions
of
risk
of
illness;
h)
unit
costs
for
treatment
technologies;
i)
descriptions
of
the
methodology
used
to
forecast
the
percentage
of
plants
assigned
to
a
given
bin
that
would
select
a
particular
technology;
j)
results
of
the
technology
selection
forecast;
k)
total
treatment
costs
for
different
system
categories
associated
with
different
regulatory
alternatives
and
assumptions
about
technology
availability.

3.3.1
Panel
Response
to
LT2ESWTR
Charge
Question
2.
This
SAB
review
panel
included
experts
in
statistical
modeling,
in
public
health
microbiology
and
engineering,
but
it
did
not
include
specialists
in
quantitative
microbiological
risk
analysis,
a
relatively
new
field.
For
the
review,
each
of
the
basic
elements
of
microbial
risk
assessment
was
examined
in
order:
hazard
identification,
dose­
response
assessment,
and
exposure
assessment.
Then
the
outcome
of
the
risk
assessment
was
evaluated.
Two
criteria
were
considered
in
the
Panel
evaluation:
a)
whether
the
Agency
assumptions
were
transparent,
and
b)
whether
scientific
evidence
exists
to
support
the
conclusions.

Cryptosporidium
parvum
has
been
responsible
for
significant
waterborne
disease
outbreaks,
and
it
is
likely
that
the
organism
is
responsible
for
significant
endemic
disease
as
well.
Both
of
these
outcomes
are
important.
The
current
form
of
the
Agency's
analysis
(
The
15
Cadmus
Group,
Inc.,
2001b)
for
the
LT2ESWTR
does
an
excellent
job
of
addressing
the
impact
of
drinking
water
quality
on
the
incidence
of
endemic
disease
and
the
health
risk
reduction
that
will
result
from
the
reduction
of
endemic
disease
as
a
result
of
the
proposed
regulation.
The
Agency
is
to
be
congratulated
for
this
ground­
breaking
work.

On
the
other
hand,
in
the
present
draft,
neither
the
design
of
the
regulation
nor
the
contents
of
the
Agency
analysis
directly
address
waterborne
outbreaks.
These
outbreaks
are
the
primary
stimulus
for
the
regulation
and
reducing
their
occurrence
should
be
one
of
the
most
important
potential
outcomes
from
the
regulation
as
well.

The
Panel
recommends
that
the
Agency
conduct
a
systematic
review
of
the
design
of
the
LT2ESWTR
regulation
and
evaluate
its
effectiveness
in
addressing
waterborne
outbreaks.
This
review
should
include
an
examination
of
the
causes
of
past
outbreaks
and
how
the
proposed
regulatory
framework
will
address
those
causes.
The
Agency
should
then
consider
if
any
changes
in
the
framework
must
be
made.
Additional
consultation
with
specialists
in
quantitative
microbial
risk
assessment
could
be
of
benefit
to
the
Agency
as
it
completes
its
consideration
of
Cryptosporidium
risks.

3.3.1.1
Hazard
Identification.
The
Panel
agreed
with
the
basic
information
on
Cryptosporidium
health
effects
that
were
presented
in
this
section.
See
pages
5­
7
­
5­
8
of
the
Economic
Analysis
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
US
EPA
2001b).
There
are
a
few
additional
areas
that
should
also
be
included
in
the
analysis:

a)
Evidence
of
current
prevalence
of
endemic
disease.
The
Agency's
analysis
is
based
on
reduction
of
endemic
disease.
Some
direct
evidence
of
endemic
disease
levels
would
greatly
strengthen
the
case.
Perhaps
the
results
of
serological
studies
could
be
used
to
indicate
about
the
prevalence
of
Cryptosporidium
exposure/
infection
in
the
US.

b)
Information
on
secondary
transmission
of
cryptosporidiosis.
The
current
analysis
does
not
consider
secondary
transmission
of
the
disease.
This
decision
should
have
stronger
support
in
the
documentation
or
should
be
reconsidered.
Haas
et
al.
(
1999)
present
data
on
prevalence
of
secondary
cases
of
cryptosporidiosis
from
two
outbreak
investigations
that
range
from
4
­
33%.
Other
data
in
the
published
research
literature,
and
perhaps
data
from
the
Centers
for
Disease
Control
may
provide
the
basis
for
estimating
the
magnitude
of
secondary
transmission
[
e.
g.,
household
via
child
(
e.
g.,
Newman
et
al.,
1994),
household
via
adult
(
MacKenzie
et
al.,
1995),
child
care
centers,
swimming
pools
(
Puech
et
al.,
2001;
Sorvillo
et
al.,
2001);
Millard,
et
al.,
1994].
Asymptomatic
infections
may
play
an
important
role
in
secondary
transmission
of
infection.
Failure
to
consider
secondary
transmission
will
likely
underestimate
the
impact
of
the
LT2ESWTR
on
reducing
the
risks
of
cryptosporidiosis.

c)
Age
Effects.
Information
on
the
prevalence
of
asymptomatic
Cryptosporidium
infections
by
age
should
be
included
in
the
hazard
identification.
The
rationale
16
for
including
age
effects
is
that,
in
general,
different
age
groups
are
more
or
less
prone
to
asymptomatic
infections.
Thus
there
may
be
a
high
prevalence
of
Cryptosporidiosis
in
some
age
groups
that
may
not
be
detected
if
only
symptomatic
cases
are
evaluated.

3.2.1.2
Dose­
Response
Assessment.
For
the
dose­
response
component
of
the
risk
assessment,
the
Panel
comments
on
four
areas
of
the
assessment:
a)
selection
of
a
dose­
response
function,
b)
use
of
the
term
infectivity,
c)
the
morbidity
rate,
and
d)
the
mortality
rate.

a)
Clarify
the
Basis
for
Selection
of
a
Dose
Response
Function.
The
general
exponential
model
was
used
to
characterize
the
dose­
response
relationship
based
on
the
data
from
three
human
challenge
studies.
Modeling
this
relationship
is
important
for
estimating
the
risk
of
infection
at
low
doses
because
it
is
not
economical
to
conduct
large
human
challenge
studies
to
directly
measure
infection
rates.
The
choice
of
the
exponential
dose­
response
model
is
reasonable
and
has
been
used
in
previous
cryptosporidiosis
risk
assessments
(
Haas
et
al.,
1996,
1999).
But
it
is
not
clear
if
other
models
were
considered
and
fit
to
the
data
from
the
human
challenge
studies.
The
Panel
recommends
that
the
Agency
document
the
models
that
were
considered
and
the
reasons
for
selecting
this
particular
one.

b)
Clarify
the
Use
of
the
Term
Infectivity
in
the
Agency
Analysis.
A
number
of
aspects
of
infectivity
that
are
described
in
the
Agency's
analysis
(
pages
5­
10)
deserve
further
discussion.
Among
these
things
are:
I)
the
use
of
the
proportion
of
the
total
oocysts
from
the
occurrence
estimates
that
have
internal
structures
to
determine
the
fraction
of
oocysts
considered
infectious,
ii)
the
fraction
of
the
oocysts
from
the
three
strains
of
C.
parvum
used
in
the
human
challenge
studies
(
IOWA,
TAMU
and
UCP)
which
were
considered
infectious
and
iii)
the
relationship
between
the
two,
namely
the
fraction
of
oocysts
that
were
infectious
in
the
human
studies
versus
the
fraction
of
the
oocysts
that
were
infectious
in
environmental
samples
(
i.
e.,
the
parameter
"
v"
in
the
equation
below).

Infectivity
of
oocysts
in
the
environment:
The
assumptions
about
the
proportion
of
infectious
oocysts
in
the
environment
determine
the
variable
"
v"
used
in
the
Agency
equation
for
estimating
morbidity:

PM
=
M{
1­[
e
(­
CvI
/
k)]
n}

Where:
M
=
fraction
of
infections
resulting
in
morbidity
C
=
concentration
of
oocysts
in
water
(
oocysts/
L)
v
=
fraction
of
oocysts
that
are
infectious
I
=
volume
of
water
ingested
each
day
(
L)
k
=
infectivity
parameter
n
=
number
of
days
of
exposure
PM
=
probability
of
disease
17
In
the
occurrence
data,
the
Agency
assumed
that
only
a
proportion
of
oocysts
detected
in
the
environment
are
infectious
and
that
proportion
was
determined
by
use
of
data
from
microscopic
examination
of
the
oocysts.
The
proportion
of
Cryptosporidium
oocysts
in
the
environment
that
are
infectious
was
estimated
from
the
ICR
and
ICRSS
data
based
on
morphological
appearance
of
oocysts
and
the
proportion
of
oocysts
with
internal
structures.
These
measures
are
more
frequently
used
as
a
measure
of
viability
than
infectivity.
Viability,
usually
evaluated
by
evidence
of
dye
uptake,
excystation
or
the
presence
of
RNA,
is
a
measure
of
the
organism's
ability
to
continue
to
survive
as
a
living
organism.
Infectivity
is
usually
defined
as
invasion
and
replication
in
a
host
cell,
mouse
model
or
human
volunteers
(
analogous
to
infection).
The
set
of
organisms
that
are
infectious
is
a
subset
of
the
set
of
organisms
that
are
viable.
Infectivity,
not
viability,
is
the
relevant
issue
where
the
parameter
is
concerned.

The
Agency
analysis
also
used
data
on
infectivity
from
a
study
by
LeChevallier
(
2000).
The
data
were
expressed
as
a
distribution
with
a
range
of
30
­
50%,
mode
=
40%
(
page
5­
17).
There
is
some
evidence
that
polymerase
chain
reaction
(
PCR)
detection
of
Cryptosporidium
DNA
in
cell
culture
will
give
false
positives
because
some
oocysts
may
not
be
infectious
but
it
is
still
possible
to
detect
their
DNA.
Thus,
direct
detection
of
DNA
by
PCR
may
also
pick
up
noninfectious
oocysts
that
stick
to
the
cell
monolayer
even
if
they
have
not
infected
the
cells
(
Rochelle
et
al.,
2001;
De
Leon
and
Rochelle,
2000).
The
Panel
recommends
that
a
careful
analysis
of
these
issues
be
conducted
and
their
impact
on
the
risk
reduction
estimates
be
evaluated.

Infectivity
of
oocysts
in
the
dose
in
the
human
challenge
studies:
The
analysis
of
the
human
dose­
response
data
assumes
that
100%
of
the
oocysts
in
the
dose
were
infectious.
However,
it
is
likely
that
not
all
of
the
oocysts
in
the
dose
are
"
infectious".
During
its
deliberations,
the
Panel
discussed
new
data
on
cell
culture
infectivity
and
mouse
infectivity
that
shows
that
approximately
5%
of
freshly
excreted
oocysts
from
a
cow
are
"
infectious"
(
see
Upton
et
al.
1994;
Rochelle
et
al.
2001;
Rochelle
et
al.
2002).
It
is
important
to
clarify
how
the
viability
and/
or
infectivity
of
the
oocysts
used
in
the
dose
was
evaluated.
Was
this
based
on
excystation
rate
or
on
the
morphological
appearance
of
intact
oocysts?
It
would
also
be
helpful
to
verify
the
time
between
oocyst
excretion
and
dosing
volunteers
(<
2
weeks?)
because
this
may
affect
the
proportion
of
infectious
oocysts
in
the
various
doses.
The
Panel
recommends
that
the
Agency
clarify
these
details
on
the
conduct
of
the
original
study
and
include
this
clarification
in
its
own
documentation.

Use
of
human
infectivity
and
cell
infectivity
data
for
the
analysis:
The
Agency
risk
analysis
incorporates
viability
determinations
(
a
much
weaker
technique)
and
direct
PCR­
cell
culture
technique
(
which
gives
false
positives).
It
is
important
that
the
Agency
clearly
indicate
that
human
challenge
data
are
currently
limited
to
three
strains
necessitating
the
use
of
several
major
assumptions
in
the
analysis.
However,
several
strains
have
been
studied
in
cell
culture
and
in
mouse
infectivity
assays.
Since
it
is
unclear
whether
these
strains
will
ever
be
tested
in
human
volunteers,
it
would
be
of
value
to
compare
the
data
between
human,
animal
and
cell
culture
lines.
It
would
be
useful
for
the
Agency
to
consult
with
a
number
of
researchers
who
have
conducted
infectivity
studies
on
Cryptosporidium
to
gain
a
deeper
understanding
of
how
animal
and
cell
infectivity
data
might
supplement
the
data
on
infectivity
from
human
challenge
18
studies.
Further,
it
will
be
important
to
make
broader
use
of
statistical
analysis
as
the
Agency
seeks
to
compare
these
differing
types
of
infectivity
data.
The
Panel
recommends
using
the
PCR­
cell
culture
data
as
a
supplement
to
the
human
infectivity
data
and
clarify
with
the
investigators
the
strengths,
limitations
and
use
of
these
data.

Proper
statistical
treatment
of
human
challenge
data
from
multiple
isolates:
As
discussed
above,
there
are
some
major
concerns
with
the
models
for
infectivity
across
strains.
There
are
data
from
only
three
strains
available
to
estimate
the
distribution
of
infectivity
across
strains.
As
a
result,
the
distribution
of
infectivity
derived
from
fitting
the
model
relies
heavily
on
both
the
assumed
class
of
distributions
(
log
normal)
used
and
the
assumed
prior
distribution
for
the
standard
deviation
parameter
F,
which
characterizes
the
variability
of
infectivity
across
strains.
The
Panel
believes
that
the
Agency
could
use
a
mixture
of
two
distributions
for
infectivity
to
help
characterize
this
uncertainty.
The
first
component
of
the
mixture
will
be
a
log
normal
distribution
(
with
probability
=
8)
and
the
second
component
will
be
a
log­
t
distribution
with
three
degrees
of
freedom
(
with
probability
=
1
­
lambda).
The
latter
provides
heavier
tails
and
considers
more
extreme
values
for
k
to
be
more
likely.
Sensitivity
analyses
regarding
the
impact
of
the
prior
on
sigma
should
also
be
performed.

The
importance
of
genotype:
It
is
correctly
recognized
that
there
are
anthroponotic
and
zoonotic
strains
of
Cryptosporidium
parvum.
One
limitation
of
the
infectivity
data
from
human
challenge
studies
is
that
currently
only
zoonotic
strains
(
genotype
2)
have
been
tested
to
date.
However,
most
of
the
recognized
Cryptosporidium
outbreaks
(
foodborne
and
waterborne)
have
involved
human
genotypes.
A
human
challenge
study
with
a
human
genotype
strain
(
genotype
1)
is
currently
in
progress
and
will
provide
valuable
data
for
future
risk
assessments.
The
Panel
recommends
that
when
this
data
becomes
available,
the
Agency
reevaluate
this
risk
assessment
and
the
dose
response
model.

Variability
in
host
susceptibility
and
the
effect
of
previous
infections:
Variability
in
host
susceptibility
was
not
considered
in
the
analyses
of
infectivity
and
morbidity.
For
example,
the
Agency
dose­
response
model
takes
the
number
of
oocysts
as
the
dose
surrogate.
Thus
the
same
approach
is
used
to
evaluate
risk
for
infants
and
adults
.
The
Panel
recommends
that
the
risk
assessment
consider
explicitly
the
risk
to
susceptible
populations
(
e.
g.,
elderly,
young,
immunocompromised,
etc.).
These
groups
may
be
at
greater
risk
of
infection
and/
or
disease
due
to
greater
water
consumption
per
unit
body
weight,
less
effective
immune
systems,
etc.
Data
from
outbreak
investigations
may
provide
evidence
of
the
consequences
of
infection
for
these
populations.

Also,
the
analysis
assumed
that
the
exposed
population
had
no
previous
immunity
to
Cryptosporidium.
It
is
likely
that
the
volunteers
in
the
human
challenge
study
are
a
mix
of
naive
and
previously
exposed
individuals,
and
that
differences
in
host
susceptibility
and
previous
immunity
had
an
effect
on
the
estimates
of
the
dose­
response
parameter.
The
Panel
recommends
that
the
Agency
compare
its
approach
to
this
issue
with
the
approach
taken
in
other
studies.
Differences
in
host
susceptibility
and
previous
immunity
will
have
an
effect
on
the
estimates
of
the
infectivity
parameter
"
k".
19
c
)
Morbidity
Rate
(
pg
5­
13).
The
morbidity
rate
was
defined
as
the
probability
of
illness
given
infection
and
was
estimated
using
a
triangular
distribution
based
on
a
range
from
Haas
et
al
1996.
This
rate
may
not
be
accurately
estimated
if
asymptomatic
infections
were
not
detected
in
the
human
challenge
studies.
The
greater
the
rate
of
asymptomatic
infections,
the
more
the
probability
of
illness
given
infection
will
be
underestimated.

In
addition,
the
probability
of
illness
given
infection
may
be
underestimated
because
these
data
are
based
on
challenge
studies
in
healthy
adult
volunteers.
In
the
general
population,
there
may
be
a
greater
probability
of
developing
illness
given
infection
because
the
whole
population
includes
sensitive
sub­
populations
that
are
more
likely
to
develop
symptomatic
illness
given
infection.

Individuals
with
existing
antibodies
to
Cryptosporidium
may
have
a
lower
morbidity
rate,
although,
data
from
Okhuysen
et
al.,
(
1998)
does
not
seem
to
support
this.
The
Okhuysen,
et
al.,
experiment
was
conducted
at
relatively
high
doses,
and
there
are
no
data
on
the
morbidity
rate
at
low
doses
in
a
population
with
previous
Cryptosporidium
infection.
The
high
doses
employed
may
have
overwhelmed
any
immune
response
in
a
way
that
low
doses
would
not.
If
a
significant
fraction
of
the
population
carries
antibodies,
the
incidence
of
disease
might
be
significantly
reduced.

The
mortality
rate
in
AIDS
patients
that
was
used
in
the
economic
analysis
is
based
on
old
data
from
the
1993
Milwaukee
outbreak.
Current
therapy
has
markedly
reduced
cryptosporidiosis
mortality
in
AIDS
cases.
As
a
result,
the
mortality
rate
in
this
analysis
is
probably
overestimated.
At
the
same
time,
the
mortality
rate
derived
from
Milwaukee
may
be
too
low
for
populations
with
a
greater
proportion
of
immunocompromised
individuals.

The
Panel
recommends
that
these
questions
of
morbidity
rate,
and
their
potential
impact
on
the
analysis
of
risk
reduction,
be
more
thoroughly
analyzed
and
discussed
in
the
document.

3.3.1.3
Exposure
Assessment
(
pgs
5­
14
­
5­
24).
Exposure
assessment
in
the
Agency's
analysis
included
estimation
of:
a)
the
distribution
of
total
and
infectious
Cryptosporidium
oocysts
in
finished
water
­
derived
from
source
water
levels
and
estimated
removal/
inactivation
from
treatment;
b)
the
population
served
by
systems
potentially
affected
by
the
LT2ESWTR,
and
c)
the
distribution
of
individual
daily
average
drinking
water
consumption.
The
Panel
has
a
number
of
comments
on
this
assessment.

a)
Estimates
of
Consumption
(
pg
5­
22)
require
clarification.
There
are
a
number
of
questions
that
arise
in
a
review
of
the
water
consumption
estimates
used
in
the
analysis.
These
questions
should
be
more
effectively
addressed
in
the
documentation.
They
include:

1)
Why
were
two
distributions
of
consumption
used?
What
is
the
difference
between
them?
2)
Why
are
the
median
values
(
1.045,
0.71)
lower
than
previous
estimates
of
daily
water
consumption?
20
3)
Why
was
Distribution
1
used
for
the
main
analysis
and
Distribution
2
used
in
the
analysis
in
the
appendix?

Finally,
it
is
not
clear
how
the
daily
estimated
consumption
was
extrapolated
to
annual
exposure
in
Exhibit
5.8
(
pg
5­
23).
Is
individual
consumption
split
between
Community
Water
Systems
and
Non­
Transient
Non­
Community
Water
Systems
based
on
the
estimated
proportion
of
their
time
spent
at
home
and
at
work
or
school
or
are
individuals
counted
in
both
categories
­
i.
e.,
total
consumption
counted
twice.
This
estimate
could
be
refined
by
age
group.
The
Agency
should
examine
water
consumption
patterns
of
the
very
young
and
very
old
because
these
are
the
most
vulnerable
age
groups.

3.3.1.4
Results
of
the
Risk
Assessment.

The
estimates
of
risk
require
clarification
as
to
the
general
approach
to
quantitative
microbial
risk
assessment,
discussions
of
uncertainty
and
significance
of
assumptions
made..

Quantitative
microbial
risk
assessment
is
a
rapidly
developing
field.
Previous
work
includes
risk
assessments
by
Casman
et
al.,
(
2000),
Haas
et
al.,
(
1999)(
see
in
NRC
2000),
Perz,
et
al.,
(
1998),
and
Teunis,
et
al.,
(
1999)
and
an
outbreak
model
done
by
Eisenberg,
et
al.,
(
1998).
The
Panel
recommends
that
a
review
of
these
and
other
preceding
studies
(
including
the
sources
of
data,
assumptions
and
statistical
methods)
be
added
to
the
document
preamble.
To
the
extent
the
approaches
by
these
predecessors
differ
from
the
approach
used
by
the
Agency,
the
significance
of
the
differences
should
be
discussed
and
the
reasoning
behind
the
choices
provided.

In
regard
to
discussions
of
uncertainty,
the
document
should
include
a
summary
discussion
of
uncertainty
and
variability
that
is
more
detailed
than
that
currently
presented
on
pg
5­
26.
This
discussion
should
include
the
following:

a)
Identifying
sources
of
uncertainty
(
already
included
on
pg
5­
26)
b)
Magnitude
of
uncertainty
c)
Effect
of
uncertainty
on
the
estimate
of
risk
d)
Sensitivity
analysis
of
which
sources
of
uncertainty
have
the
greatest
impact
on
the
estimate
and
the
implications
of
this
for
future
research
efforts.
It
appears
that
uncertainty
in
estimates
of
risk
and
uncertainty
in
costs
have
different
drivers.
Uncertainty
in
estimates
of
risk
was
driven
by
dose­
response
data.
Uncertainty
in
cost
was
driven
by
occurrence
data
(
how
the
systems
are
classified
into
bins
where
action
is
necessary).
Hence,
it
may
turn
out
that
uncertainty
is
much
greater
in
cost
than
in
estimates
of
risk
or
vice
versa.
v)
Identifying
sources
of
variability
(
already
included
on
pg
5­
26).
Sources
of
oocysts
may
be
different
for
different
communities
(
watersheds)
animal
sources
vs
human
sources
1)
Magnitude
of
variability
2)
Effect
of
variability
on
the
estimate
of
risk
21
3)
Sensitivity
analysis
of
what
sources
of
variability
have
the
greatest
impact
on
the
estimate
In
regard
to
the
significance
of
assumptions,
the
document
should
also
include
a
discussion
of
which
assumptions
may
lead
to
an
underestimate
or
overestimate
of
the
risk
and
the
benefits
of
the
proposed
regulation.
For
example,
because
the
analysis
only
considered
morbidity
and
mortality
as
outcomes,
it
is
possible
that
the
benefit
is
underestimated
because
the
benefit
of
avoided
infection
was
not
considered.
Avoiding
infection
in
the
community
will
reduce
the
potential
for
secondary
transmission
and
additional
cases
and
deaths.
From
a
public
health
perspective,
infection
is
the
key
outcome.

3.4
Charge
3:
Treatment
credits
for
four
microbial
toolbox
options
The
Agency
requested
SAB
comments
on
the
treatment
credits
for
four
specific
technologies
included
among
its
microbial
toolbox
options.

The
Agency
provided
the
Panel
with
drafts
of
portions
of
the
preamble
to
the
LT2ESWTR,
including:
a)
a
Microbial
toolbox
overview
(
US
EPA
2001a),
b)
Off­
stream
raw
water
storage
(
US
EPA,
2001b),
c)
Pre­
sedimentation
(
US
EPA
2001c),
d)
Lime
softening
(
US
EPA,
2001d),
and
e)
Lower
finished
water
turbidity
(
US
EPA
2001e).

These
draft
documents
were
intended
to
provide
the
Panel
with
an
understanding
of
the
role
and
context
of
toolbox
options
in
the
LT2ESWTR
and
specific
information
on
each
of
the
four
toolbox
options
that
the
Agency
asked
the
Panel
to
comment
upon.

3.4.1
Panel
Response
to
LT2ESWTR
Charge
Question
3
a)
Comments
on
the
Four
Options.
The
Panel
commends
the
Agency,
as
well
as
the
stakeholder
process
used,
for
developing
the
bin
classification
framework
for
identifying
the
treatment
requirements
for
drinking
water
and
the
microbial
toolbox
containing
possible
treatment
options
to
guide
systems
having
treatment
needs.
These
alternatives
add
great
flexibility
for
meeting
varying
water
quality
and
treatment
options
and
should
result
in
safer
drinking
water
for
the
people
of
the
United
States.

The
Agency
charged
the
Panel
with
evaluating
Agency
information
on
four
of
the
toolbox
options:
1)
off
stream
raw
water
storage;
2)
pre­
sedimentation,
3)
lime
softening
and
4)
lower
finished
water
turbidity.
Specifically,
the
Agency
asked
the
Panel
to
comment
on
the
credits
that
have
been
proposed
for
specific
toolbox
options
for
Cryptosporidium
removal.
The
proposal
requires
that
utilities
monitor
the
oocyst
densities
in
their
raw
water
supplies.
It
then
classifies
each
supply
into
one
of
several
bins
depending
on
the
oocyst
densities
observed,
each
bin
having
different
treatment
removal
requirements.
The
proposal
then
identifies
a
"
toolbox"
of
several
actions
that
utilities
can
take
in
order
to
get
credit
for
removal.
Removal
credits
are
generally
expressed
as
the
logarithm
of
the
reduction
required.
For
example,
a
1
log
credit
would
correspond
to
90%
removal.
22
In
summary,
the
Panel
recommends
that
no
presumptive
credits
be
given
for
off­
stream
storage
and
pre­
sedimentation.
It
does
agree
with
giving
0.5
log
credit
for
two­
stage
lime
softening
if
all
the
water
is
treated
with
both
stages,
and
0.5
log
credit
for
plants
that
demonstrate
a
turbidity
level
in
each
individual
filter
effluent
less
than
or
equal
to
0.15
NTU
in
at
least
95
percent
of
the
measurements
taken
each
month.
Details
about
these
recommendations
follow.

Off­
Stream
Storage:
The
data
utilized
by
the
Agency
in
determining
the
appropriate
credit
for
off­
stream
storage
were
derived
from
experiences
in
the
United
States
as
well
as
peerreviewed
literature
from
elsewhere
in
the
world.
The
data
show
that
there
is
variability
in
the
removal
of
active
oocysts
in
different
reservoirs,
due
primarily
to
sedimentation,
but
also
due
to
inactivation
within
the
environment,
both
of
which
are
governed
to
some
degree
by
temperature
and
by
residence
time
in
the
facility.
After
reviewing
the
supporting
documentation,
the
Panel
does
not
feel
there
are
adequate
data
to
demonstrate
the
proposed
credits
for
off­
stream
storage
and
therefore
recommends
that
no
presumptive
credits
be
given
for
this
toolbox
option.
However,
the
Panel
agrees
that
a
particular
utility
should
be
able
to
take
advantage
of
any
removal
achieved
by
this
option
by
sampling
after
the
off­
stream
storage
facility
for
appropriate
bin
placement.

Pre­
sedimentation:
With
regard
to
pre­
sedimentation,
many
water
treatment
plants
located
on
surface
waters
having
large
variations
in
water
quality
utilize
pre­
sedimentation
as
a
treatment
technique
to
remove
large
quantities
of
suspended
material
prior
to
input
to
an
existing
conventional
treatment
plant
or
lime
softening
operation.
The
real
purpose
of
pre­
sedimentation
is
to
provide
for
more
consistent
water
quality
prior
to
the
conventional
or
lime
softening
treatment.
In
reviewing
the
literature
provided
by
the
Agency,
not
only
on
Cryptosporidium,
but
also
on
spore
removal
with
both
pilot
as
well
as
full­
scale
plants,
it
seems
that
the
data
are
insufficient
to
support
a
0.5
log
presumptive
credit
for
pre­
sedimentation.
As
a
result,
the
Panel
feels
that
no
credit
should
be
given
for
pre­
sedimentation.
Additionally,
the
Panel
feels
performance
criteria
other
than
overflow
rate
need
to
be
included
if
credit
is
to
be
given
for
presedimentation
As
with
off­
stream
storage,
the
Panel
does
agree
that
a
utility
should
be
able
to
take
advantage
of
this
removal
by
sampling
after
the
pre­
sedimentation
treatment
process
for
appropriate
bin
placement.

Lime­
softening:
The
Agency
proposes
a
0.5
log
credit
toward
Cryptosporidium
treatment
with
lime
softening
plants
that
utilize
two­
stage
softening.
Based
on
the
data
provided,
it
appears
that
a
0.5
log
of
additional
Cryptosporidium
removal
is
an
average
number
for
a
twostage
lime
softening
plant.
Based
on
the
data,
single
stage
as
well
as
two­
stage
lime
softening
generally
outperforms
conventional
treatment
due
primarily
to
the
heavy
precipitation
that
occurs
in
lime
softening
reactors
particularly
when
magnesium
precipitation
occurs.
By
treating
water
through
a
second
precipitation
reactor,
additional
removal
should
occur.
However,
depending
on
how
the
second
reactor
is
utilized
and
the
chemical
feeds
to
the
second
reactor,
the
removal
efficiencies
vary
significantly
as
presented
in
the
literature.
Therefore,
the
Panel
supports
an
additional
0.5
log
removal
for
two
stage
lime
softening
only
if
all
the
water
passes
through
both
stages.
If
a
portion
of
the
water
bypasses
the
first
stage,
the
Panel
feels
there
should
be
no
additional
removal
credit
given.
23
Lower
Finished­
Water
Turbidity:
Finally,
the
additional
credits
for
lower
finished
water
turbidity
seem
to
be
consistent
with
what
is
known
in
both
pilot
and
full­
scale
operational
experiences
for
Cryptosporidium
removal.
As
was
contained
in
the
Enhanced
Surface
Water
Treatment
Rule,
lowering
effluent
turbidity
in
the
treated
water
results
in
lower
concentrations
of
Cryptosporidium.
Therefore,
it
would
be
consistent
to
assume
that
even
further
lowering
of
turbidity
would
result
in
further
reductions
in
Cryptosporidium
in
the
effluent
from
filtration
processes.
It
is
also
logical
to
assume
that
individual
filter
effluent
turbidity
meeting
a
specific
criterion
will
provide
for
better
water
quality
than
for
combined
filter
effluent
meeting
the
same
requirement.
However,
limited
data
were
presented
to
show
the
exact
removal
that
can
be
achieved
using
these
two
operational
benchmarks.
Based
on
the
data
provided,
the
Panel
recommends
that
a
0.5
log
credit
be
given
to
plants
that
demonstrate
a
turbidity
level
in
each
individual
filter
effluent
less
than
or
equal
to
0.15
NTU
in
at
least
95
percent
of
the
measurements
taken
each
month.
No
additional
credit
should
be
given
to
plants
that
demonstrate
a
combined
filter
effluent
turbidity
of
0.15
NTU
or
less.

b)
Other
Issues.
The
Panel's
understanding
of
the
approach
used
in
developing
the
microbial
toolbox
is
as
follows.
The
additional
log
removals
in
the
table
of
bin
requirements
are
based
in
part
on
the
assumption
that
conventional
filtration
plants
in
compliance
with
the
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IESWTR)
achieve
an
average
of
3
logs
removal
of
Cryptosporidium.
The
Panel
also
understands
that
this
assumption
indicates
that
all
conventional
treatment
plants
can
be
expected
to
remove
a
minimum
of
2
logs
of
Cryptosporidium.
Furthermore,
it
is
the
Panel's
understanding
that
an
objective
of
the
rule
is
to
achieve
an
average
oocyst
concentration
in
treated
surface
waters
of
10­
4
oocysts/
l
or
lower.
Given
the
oocyst
concentrations
in
bins
2,
3,
and
4,
and
considering
an
average
removal
of
3
logs
for
conventional
treatment,
the
additional
removal
requirements
in
bins
2,
3,
and
4
are
expected
to
provide
an
average
treated
water
oocyst
concentration
of
10­
4
oocyst/
l
or
lower.

This
approach
differs
from
past
regulatory
approaches
to
Giardia
and
Cryptosporidium
treatment
credits
and
from
present
regulatory
approaches
to
Giardia
control.
Current
regulations
for
Giardia
control
provide
2.5
logs
of
removal
credit
when
conventional
treatment
is
used.
It
is
the
understanding
of
the
Panel
that
this
removal
credit
for
Giardia
is
based
on
the
minimum
removal
(
not
the
average
removal)
achieved
by
these
plants.

These
differences
between
the
IESWTR
and
LT2ESWTR
regulations
in
the
bases
for
assuming
removal
credits
for
Giardia
and
Crypotosporidium
are
not
readily
apparent
and
should
be
clarified
and
supported
in
the
new
regulations.
Appropriate
guidance
will
be
needed
for
consistent
implementation
of
these
two
regulations.
24
4.
STAGE
2
DISINFECTION
BYPRODUCTS
RULE
4.1
Charge
1:
Initial
Distribution
System
Evaluation
(
IDSE):

The
Agency
requests
SAB
comment
on
whether
the
IDSE
is
capable
of
identifying
new
compliance
monitoring
points
that
target
high
TTHM
and
HAA5
levels
and
whether
it
is
the
most
appropriate
tool
available
to
achieve
this
objective.

The
Agency
provided
the
Panel
with
two
draft
documents
on
the
Initial
Distribution
System
Evaluation
that
is
to
be
proposed
in
the
S2DBP
rule.
Information
provided
in
support
of
Charge
question
2
below
in
this
section
also
bears
some
relevance
to
this
question.
The
documents
provided
by
the
Agency
include:

a)
"
E.
Initial
distribution
system
evaluation
(
IDSE)"
(
US
EPA,
2001f)
a
draft
overview
of
the
IDSE
intended
for
the
preamble
of
the
rule;
and
b)
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
Initial
Distribution
System
Evaluation
Guidance
Manual
(
The
Cadmus
Group,
Inc.,
2001d)
which
provides
recommendations
for
how
utilities
should
proceed
to
determine
monitoring
sites
to
reflect
the
highest
levels
of
TTHM
and
HAA5
occurrence
within
the
distribution
system.

4.1.1
Panel
Response
to
S2DBP
rule
Charge
Question
1.

4.1.1.1
Initial
Distribution
System
Evaluation
(
IDSE)
Effectiveness.
The
Panel
believes
that
the
proposed
IDSE
is
capable
of
identifying
new
compliance
monitoring
points
that
target
higher
DBP
levels
than
are
currently
monitored
in
the
existing
compliance
monitoring
programs
for
the
THM
Rule
and
Stage
1
DBP
Rule.
However,
the
IDSE
may
not
identify
the
highest
levels
to
which
consumers
in
a
given
distribution
system
are
exposed.
The
basis
for
the
latter
statement
is
that
the
IDSE
does
not
consider
short­
term,
temporal
variations
that
occur
at
different
sites
in
the
distribution
system
due
to
varying
(
e.
g.
diurnal)
water
demands
and
distribution
system
architecture
and
operation.
Distribution
systems
are,
by
their
nature,
highly
dynamic.
Varying
water
demand
patterns
(
e.
g.
low
density
and
high
density
residential
water
use,
industrial
and
commercial
water
use,
irrigation)
and
operating
conditions
(
e.
g.
pumping
patterns
and
storage
tank
operations)
normally
lead
to
appreciable
temporal
and
spatial
variations
in
hydraulic
residence
times
(
water
age)
and
water
quality
throughout
the
system
that
are
not
captured
by
the
proposed
IDSE.
Hence,
it
is
unlikely
that
a
single
grab
sample
taken
at
any
site
at
any
time
will
yield
a
representative
DBP
concentration
for
that
site,
and
that
grab
samples
taken
at
a
number
of
sites
will
identify
sampling
sites
with
the
highest
DBP
concentrations.

Further,
rates
of
disinfection
byproduct
formation
and
degradation
are
temperaturedependent
and
may
change
on
a
seasonal
basis.
Coupling
this
with
the
fact
that
water
demand
patterns,
and
therefore
hydraulic
residence
times,
also
may
change
with
season
may
mean
that
peak
DBP
levels
migrate
from
the
remote
parts
of
the
system
during
colder
months
to
interior
25
portions
of
the
system
during
warmer
months.
Furthermore,
this
behavior
will
probably
not
be
consistent
for
all.

Therefore,
the
Panel
believes
that
it
is
important
that
site
selection
be
re­
evaluated
periodically.
In
rapidly
growing
utilities
changes
in
the
distribution
system
architecture
and
flow
patterns
are
common.
As
a
result,
the
sites
with
high
DBP
levels
often
change.
Significant
changes
also
occur
in
systems
that
are
not
rapidly
growing
as
components
fail
and/
or
improvements
are
made.
If
sample
locations
are
not
updated
with
time
to
reflect
these
changes
in
distribution
system
behavior,
then
the
sample
locations
may
lose
their
relevance
over
time.
Further,
the
IDSE
is
only
a
12­
month
program,
and
utilities
and
primacy
agencies
have
no
assurances
that
the
12­
month
period
over
which
the
IDSE
is
performed
will
indeed
be
typical
of
normal
system
operations.
The
Panel
recommends
that
temporal
limitations
be
identified
in
the
documentation
and
that
periodic
re­
evaluation
of
selected
sites
be
required
so
that
changes
in
the
system
and/
or
its
use
will
be
addressed.

4.1.1.2
IDSE
Appropriateness.
The
Agency
also
asked
if
the
IDSE
is
the
most
appropriate
tool
to
reach
the
objective
of
identifying
new
compliance
monitoring
points
that
target
higher
THM4
and
HAA5
levels.
The
Panel
believes
that
the
proposed
standard
monitoring
program
(
SMP)
for
sub­
part
H
systems
serving
more
than
10,000
people,
in
which
8
samples
are
collected
at
2­
month
intervals,
is
reasonable.
The
Panel
does
recommend,
however,
that
the
8
samples
be
re­
allocated
so
that,
for
both
free
chlorine
and
chloramines,
3
samples
be
taken
at
potential
high
THM4
sites,
3
samples
be
taken
at
potential
high
HAA5
sites,
and
only
1
sample
each
be
taken
at
an
average
site
and
at
the
point
of
entry
to
the
system.
If
indeed
the
objective
is
to
locate
and
monitor
the
sites
with
high
THM4
and
high
HAA5
concentrations,
more
samples
need
to
be
allocated
to
this
objective.
One
point
of
entry
site
is
sufficient
to
gauge
the
initial
concentration
of
DBPs
entering
the
system,
and
only
one
"
average"
site
should
be
sufficient
to
maintain
connectivity
to
the
existing
compliance
monitoring
program.
The
Panel
also
believes
that
the
"
average"
site
for
the
IDSE
should
be
one
of
the
average
locations
in
the
existing
Stage
1
DBP
compliance
monitoring
program.
This
would
mean
that
every
6
months
(
twice
during
the
IDSE),
utilities
would
only
have
to
take
7
samples
as
part
of
the
IDSE,
with
the
eighth
sample
being
one
of
the
compliance
monitoring
samples.

The
Panel
also
recommends
that
the
IDSE
should
require
the
measurement
and
reporting
of
residual
chlorine
(
free
or
combined)
concentrations
at
the
time
of
DBP
sample
collection,
and
that
individual
THM
and
HAA
species
be
reported
in
addition
to
the
aggregate
concentrations.
The
Panel
also
suggests
that
the
IDSE
recommend
that
complementary
pH,
temperature,
and
heterotrophic
plate
count
be
measured
and
recorded
concurrently
with
DBP
measurements.
Such
information
will
prove
to
be
valuable
to
the
utilities,
the
primacy
agencies,
and
the
Agency
in
the
future.

With
respect
to
time
of
sample
collection,
there
is
no
reason
to
believe
that
THM4
or
HAA5
levels
will
be
highest
in
the
morning.
In
view
of
the
dynamic
and
highly
complex
nature
of
water
distribution
systems,
it
is
equally
likely
that
THM4
or
HAA5
levels
at
some
locations
will
be
highest
in
the
evening.
The
Committee
recommends
that
the
reference
to
time
of
sample
26
collection
be
omitted
from
the
Guidance
Manual
(
e.
g.
p.
2.9
of
Guidance
Manual)
and
be
left
to
the
discretion
of
the
utilities
and
their
respective
primacy
agency.

The
Panel
also
recommends
that
the
Agency
provide
more
guidance
to
the
utilities
with
respect
to
identifying
potential
sampling
sites
with
the
highest
HAA5
concentrations.
The
only
reference
in
which
some
guidance
is
provided
is
on
page
5­
18,
line
39
of
the
Guidance
Manual,
although
that
guidance
is
not
especially
clear.
It
might
be
expected
that,
at
least
in
waters
with
temperatures
supporting
microbial
activity,
HAA5
levels
may
decrease
when
free
chlorine
residuals
decrease
below
0.2­
0.3
mg/
l
or
combined
chlorine
residuals
decrease
below
0.5
mg/
l.
This
may
not
be
the
case
in
cold
waters
in
which
microbial
activity
is
minimal;
in
such
cases,
high
HAA5
sites
may
coincide
with
high
THM4
sites.
Distribution
system
dynamics,
water
age,
chlorine
residual
data,
and
heterotrophic
plate
count
data
should
be
examined
in
selecting
sample
sites.

The
Panel
also
recommends
that
the
Agency
require
that
the
selection
of
monitoring
sites
be
justified
rather
than
simply
recommending
that
they
be
justified
(
p.
1­
4,
line
14),
and
that
the
IDSE
report
provide
justification
for
the
selection
of
sites
(
p.
5­
24,
line
16)
(
The
Cadmus
Group,
Inc.,
2001d).

The
Panel
believes
that
the
proposed
system
specific
studies
(
SSS)
approach
described
in
Chapter
6
of
the
Guidance
Manual
needs
improvement
if
sound
guidance
is
to
be
provided
to
the
utilities.
Water
consumption
(
demands)
should
be
more
accurately
simulated
in
the
network
model,
given
the
availability
of
such
information.
It
is
important
to
realize
that
different
types
of
water
users
will
consume
water
at
different
times
and
rates
during
the
day.
Water
demands
should
be
classified
and
allocated
based
on
their
water
use
type
(
domestic,
industrial,
commercial,
etc.)
and
each
type
of
water
user
should
be
assigned
an
individual
water
use
pattern
over
a
24­
hour
(
or
other)
period.
Estimates
of
demand
distributions
could
be
obtained
by
using
land
use
information
or
by
using
a
water
meter
or
assessor's
parcel
number
location
methodology
(
geocoded
meter
location).
For
example,
the
land
use
computation
method
consists
of
intersecting
demand
area
polygons
with
land
use
polygons
using
water
duty
factors
to
create
water
demands
for
selected
analysis
nodes.
The
geocoded
meter
location
method
consists
of
grouping
water
billing
data
into
demand
areas
around
analysis
nodes
by
using
a
spatial
reference
of
water
meters,
yielding
a
credible
demand
distribution
as
demands
are
allocated
per
customer
billing
accounts
(
and
automatically
taking
into
account
vacant
parcels
and
large
water
users).
Other
spatial
demand
allocation
methods
include
assigning
geocoded
customer
meters
to
the
nearest
analysis
node
or
to
the
nearest
pipe
and
then
split
the
demand
among
the
bounding
analysis
nodes.
Some
care
will
be
required
to
ensure
that
demands
are
accurately
allocated
according
to
actual
spatial
consumption.

4.1.1.3
Other
Considerations.
The
Panel
has
a
number
of
concerns
that
it
considers
to
be
of
significance
but
which
do
not
easily
fit
into
the
other
two
charge
questions
on
the
S2DBP
Rule.
These
are
discussed
in
the
following
paragraphs.
27
Clarification
of
Assumptions:
A
number
of
assumptions
and
policy
decisions
were
made
in
the
development
of
the
form
of
the
Stage
2
DBP
Rule
and
the
IDSE.
These
need
to
be
stated
at
the
outset
and
made
clear
throughout
the
documentation
in
support
of
the
rule.
These
include:

a)
the
decision
to
continue
to
regulate
THM4s
and
HAA5s
collectively
as
group
parameters
rather
than
as
individual
species;
b)
the
decision
to
continue
to
regulate
only
five
of
the
HAAs
(
HAA5)
rather
than
all
nine
bromine­
and
chlorine­
containing
HAAs
(
HAA9);
c)
recognition
of
the
fact
that,
for
purposes
of
simplicity,
the
IDSE
overlooks
shortterm
temporal
variability
in
the
selection
of
sites
for
locating
and
monitoring
maximum
levels
of
THM4s
and
HAA5s;
d)
recognition
of
the
fact
that
sampling
and
monitoring
costs
were
key
considerations
in
designing
the
requirements
for
the
standard
monitoring
program
for
the
IDSE;
e)
recognition
of
the
fact
that,
although
the
Source
Water
Analytical
Tool
(
SWAT)
model
was
developed
for
modeling
the
effects
of
treatment
on
DBP
formation
and
was
not
developed
to
model
changes
in
individual
or
aggregate
DBP
concentrations
in
distribution
systems,
it
was
the
only
tool
that
the
Agency
had
for
purposes
of
the
benefits
analysis
in
support
of
the
Stage
2
Rule.

Use
of
the
SWAT
Model:
In
the
risk
reduction
analysis,
the
SWAT
model
is
used
to
predict
monthly
DBP
concentrations
both
under
current
conditions
and
under
conditions
where
plant
modifications
have
been
made
to
meet
the
requirements
of
Stages
1
and
2
(
sections
3.7.2
and
5.4.1.1)
(
The
Cadmus
Group,
Inc.,
2001e).
This
use
of
the
SWAT
model
would
be
appropriate
if
it
could
be
relied
upon
for
valid
predictions
in
such
applications.
Unfortunately,
the
Agency
has
not
demonstrated
that
this
is
the
case.
Large
discrepancies
exist
between
SWAT
predictions
and
ICR
data,
and
these
discrepancies
raise
serious
questions
regarding
both
the
accuracy
of
the
SWAT
model
and
the
adequacy
of
attempts
to
characterize
DBP
concentrations
of
dynamic
systems
with
such
a
limited
number
of
samples
(
four
sites
with
four
samples
per
year).

Two
aspects
of
data
presentation
in
the
Stage
2
DBPR
Economic
Analysis
serve
to
illustrate
how
the
discrepancies
are
under­
represented:
a)
the
use
of
cumulative
frequency
distributions
(
pages
3­
31
and
A­
18
through
A20)(
The
Cadmus
Group,
Inc.,
2001e),
and
b)
miscalculation
of
"
mean
predicted
errors"
(
page
A­
34
and
Exhibit
A.
21).
The
problem
with
the
use
of
cumulative
frequency
diagrams
is
that
such
plots
have
the
same
shape
even
when
paired
values
have
little
agreement.
Plants
with
low
THM4
or
HAA5
from
the
SWAT
model
are
not
necessarily
the
same
plants
with
low
THM4
or
HAA5
plants
from
the
ICR
data.
This
discrepancy
is
totally
lost
when
the
data
are
presented
as
cumulative
frequency
curves.
In
the
calculation
of
the
"
mean
predicted
error,"
"
the
absolute
value
of
the
difference
between
"
SWAT
annual
plant
mean"
and
"
ICR
annual
plant
mean"
should
have
been
used
instead
of
signed
values,
or
an
R2
value
should
have
been
calculated.
The
way
the
calculation
was
done,
positive
deviations
canceled
out
negative
deviations
thereby
grossly
underestimating
"
mean
predicted
errors."
The
graphical
results
of
pages
A­
23
to
A33
convey
a
much
greater
sense
of
the
discrepancies
between
the
SWAT
predictions
and
the
ICR
data.
The
magnitude
of
these
28
discrepancies
diminishes
the
value
of
the
subsequent
use
of
either
SWAT
or
ICR
data
in
Economic
Analyses
or
risk
reduction
calculations.

The
limitations
to
the
model's
accuracy
arise
from
the
inherent
limitations
of
the
existing
state
of
the
art
for
predicting
DBP
concentrations
from
water
quality
data
and/
or
the
inherent
limitations
in
the
available
database,
and
hence
cannot
be
easily
fixed.
Under
the
circumstances,
the
contribution
that
the
model
can
make
to
an
evaluation
of
the
risk
reduction
from
the
Stage
2
rule
is
marginal
at
best.
The
Panel
recommends
that
either
this
portion
of
the
analysis
of
the
risk
reduction
be
eliminated
or
that
the
presentation
be
altered
to
reflect
the
uncertainties
associated
with
use
of
the
model.

Monitoring
Frequency
Under
the
IDSE:
Though
this
is
a
relatively
minor
point,
it
should
be
made
clear,
in
all
documents
relevant
to
the
Stage
2
Rule,
that
quarterly
monitoring
of
DBPs
means
every
3
months.
For
example,
Table
5.4
and
page
192
(
US
EPA,
2001h)
do
not
unequivocally
indicate
that
the
basis
for
the
LRAA
calculation
is
sampling
at
3­
month
intervals
rather
than
once
each
quarter
as
in
the
current
THM
Rule
and
Stage
1
Rule.

4.2
Charge
2:
Public
Health
Protection
of
S2DBPR.

4.2.1
Panel
Response
to
S2DBPR
Charge
Question
2.

The
Agency
requests
SAB
comment
on
whether
the
locational
running
annual
average
(
LRAA)
standards
for
total
trihalomethanes
(
TTHMs)
and
haloacetic
acids
(
HAA5),
in
conjunction
with
the
Initial
Distribution
System
Evaluation
of
the
proposed
S2DBP
rule,
more
effectively
achieves
public
health
protection
than
the
current
running
annual
average
(
RAA)
standards,
given
the
existing
knowledge
of
DBP
occurrence
and
the
available
health
effects
data.

The
Agency
is
concerned
with
reproductive,
developmental,
and
carcinogenic
effects
which
are
associated
with
TTHMs
and
HAAs.
The
Agency
intends
to
reduce
the
variability
of
exposure
to
DBPs
for
people
at
different
points
in
the
distribution
system,
and
therefore
reduce
risks.

The
Agency
provided
the
Panel
with
documents
that
gives
the
Agency's
case
for
why
it
believes
there
is
a
health
concern
for
disinfection
byproducts.
Documents
provided
to
the
Panel
in
support
of
the
Health
concerns
determination
include:

a)
A
draft
of
preamble
section
"
III.
Public
Health
Risk"
(
US
EPA,
2001g)
that
briefly
discusses
reproductive
and
developmental
epidemiology
information
received
after
the
Stage
1
DBP
rule;
b)
Quantification
of
Bladder
Cancer
Risk
from
Exposure
to
Chlorinated
Surface
Water
(
US
EPA,
1998)
which
provides
details
on
the
population
attributable
risk
concept
used
to
quantify
the
estimated
number
of
cancer
cases
that
would
be
attributable
to
the
consumption
of
chlorinated
drinking
water;
29
c)
Reproductive
and
Developmental
Effects
of
Disinfection
By­
Products
(
Reif
et
al.,
2000)
which
provides
a
critical
review
of
the
epidemiologic
literature
pertaining
to
reproductive
and
developmental
effects
of
exposure
to
disinfection
byproducts
in
drinking
water;
d)
Review
of
Animal
Studies
for
Reproductive
and
Developmental
Toxicity
Assessment
of
Drinking
Water
Contaminants:
Disinfection
By­
Products
(
DBPs)
(
Tyl,
2000),
which
provides
a
review
of
the
animal
reproductive
and
developmental
toxicity
data
on
disinfection
byproducts;
and
e)
"
V.
Discussion
of
Proposed
Stage
2
DBPR
Requirements"
(
US
EPA,
2001h)
which
explains
how
the
chloroform
MCLG
was
developed.

One
document
was
provided
to
support
evaluation
of
charge
question
2
in
the
area
of
"
Occurrence/
Reduction
of
Peaks":

a)
Excerpts
from
the
Economic
Analysis
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
The
Cadmus
Group,
Inc.,
2001e)
which
indicates
the
extent
to
which
the
Agency
estimates
that
DBP
peaks
might
be
reduced
by
the
proposed
S2DBPR.

One
document
was
provided
to
support
evaluation
of
charge
question
2
in
the
area
of
"
Monitoring
Requirements
and
Compliance
Determination:":

a)
G.
Monitoring
requirements
and
compliance
determination.
(
US
EPA,
2001i).

The
Agency
issued
a
Stage
1
DBP
regulation
that
requires
regulated
water
systems
to
meet
a
standard
of
80
ug/
l
Total
Trihalomethanes
(
THM4)
and
60
ug/
l
for
five
Haloacetic
Acids
(
HAA5)
as
well
as
other
DBPs
during
1998.
Consistent
with
the
original
THM
rule,
the
regulation
requires
that
systems
implement
a
Running
Annual
Average
(
RAA)
approach
to
monitoring
for
these
contaminants
and
that
they
be
kept
at
or
below
these
levels.
In
arriving
at
these
standards,
the
Agency
recognized,
as
does
this
Panel,
that
the
regulated
THM4
and
HAA5,
which
are
prominently
identified
in
the
rule,
are
not
the
only
DBPs
in
these
classes
that
could
be
in
drinking
water,
nor
are
these
classes
the
only
possible
DBPs
in
chlorinated
or
other
drinking
water
systems.
However,
the
Agency
and
a
large
group
of
stakeholders
who
were
involved
in
an
extensive
series
of
negotiations,
agreed
that
it
was
appropriate
to
focus
on
these
DBPs
in
the
policy
embodied
in
the
Stage
I
standard.
They
further
agreed
that
it
was
reasonable
to
assume
that
the
controls
that
would
be
implemented
for
reducing
levels,
and
therefore
risks,
of
those
regulated
DBPs,
would
also
reduce
risks
from
other
DBPs
that
are,
as
yet,
to
be
identified
and/
or
studied
for
health
effects.

The
panel
is
generally
supportive
of
the
THM4
and
HAA5
actions
under
consideration.
Although
the
epidemiology
data
associating
cancer
with
chlorinated
drinking
water
has
resulted
in
relatively
small
odds
ratios,
the
observations
have
now
been
consistent
across
a
broad
number
of
studies
with
varying
degrees
of
increasing
sophistication,
especially
for
bladder
cancer.
While
the
odds
ratios
are
small,
the
numbers
of
attributable
cases
are
large
relative
to
other
environmental
issues
of
concern
(
Morris
et
al.,
1992;
Poole,
1997).
Therefore,
the
epidemiology
30
data
can
be
taken
to
indicate
that
there
is
a
problem
that
needs
to
be
taken
seriously.
The
THM4
and
HAA5
standards
reviewed
by
the
Panel
are
a
constructive
interim
step
towards
addressing
this
problem.

The
Panel
also
agrees
that
establishing
an
LRAA
would
be
expected
to
reduce
exposure
to
the
nine
compounds
that
are
regulated.
As
detailed
in
section
4.1.1.1
of
this
document,
which
discusses
the
dynamics
of
water
movement
through
the
distribution
system
and
on­
going
production
and
degradation
of
disinfection
by­
products,
it
is
uncertain
that
the
requirements
of
the
IDSE
will
result
in
a
sufficiently
complete
distribution
system
characterization
to
be
confident
that
the
locations
with
the
highest
exposure
will
be
identified
and
therefore
that
all
the
households
will
gain
the
protection
of
the
new
standards.
Nevertheless,
the
variability
in
exposure
to
regulated
DBPs,
from
one
point
in
the
system
to
another,
will
be
reduced,
particularly
at
the
extreme
locations
that
the
IDSE
does
identify,
and
the
consumers
at
those
locations
will
have
lower
levels
of
exposure
to
the
measured
DBPs.

The
principle
outcome
of
the
LRAA/
IDSE
proposal
will
be
increased
assurance
that
each
consumer
will
be
exposed
to
THM4/
HAA5
levels
that
are
at
or
below
the
MCLs
specified.
The
existing
RAA
allows
locations
with
THM4/
HAA5
levels
above
the
MCL
to
be
averaged
with
other
locations
in
the
system
that
do
not.
The
LRAA
identifies
locations
in
the
system
with
consistently
high
concentrations
of
the
regulated
DBPs
and
requires
that
they
meet
the
MCL.
Thus
the
new
proposal
substantially
reduces
the
probability
that
a
given
consumer
will
be
exposed
to
THM4/
HAA5
levels
above
those
specified
in
the
regulation.
The
Panel
recommends
that
the
Agency
give
greater
visibility
to
this
benefit.

A
second,
but
important
outcome
of
the
LRAA/
RAA
proposal
will
be
reduced
overall
average
level
of
the
regulated
DBPs
in
many
systems.
This
will
occur
because,
when
systems
use
precursor
removal
as
their
strategy,
THM4/
HAA5
levels
must
be
reduced
throughout
the
system
in
order
to
bring
sampling
points
with
high
THM4/
HAA5
levels
into
compliance.

Assessments
of
health
risk
reduction
from
this
rule
have
emphasized
reductions
in
bladder
cancer
risk.
It
is
important
to
address
bladder
cancer
because
epidemiological
data
consistently
indicate
that
lifetime
consumption
of
chlorinated
surface
water
poses
a
bladder
cancer
risk
(
Cantor
et
al.,
1998;
Doyle
et
al.,
1997;
King
and
Marrett,
1996;
McGeehin
et
al.,
1993;
Morris
et
al.,
1992;
Poole,
1997;
Vilanueva
et
al.,
2001;
Vena
et
al.,
1993).
There
are
other
serious
putative
health
effects
that
have
been
identified
from
epidemiology
studies
or
toxicological
studies
of
individual
disinfection
byproducts
(
Cantor
et
al.,
1999;
Hildesheim
et
al.,
1998;
King
et
al.,
2000;
Reif
et
al.,
2000;
Tyl,
2000).
These
include
risks
of
other
cancers
(
brain,
colon,
rectal),
impairment
of
male
and
female
reproduction,
and
effects
on
developing
organisms.
Additionally,
it
should
be
noted
that
the
brominated
THM
and
HAAs
might
account
for
some
of
the
colon
cancer
as
they
can
produce
colon
cancer
in
rats.
Collectively,
the
risks
calculated
from
these
toxicological
studies
are
1­
2
orders
of
magnitude
less
than
the
bladder
cancer
risks
indicated
by
the
epidemiology
studies.
The
bladder
cancer
may
well
be
due
to
agents
other
than
the
THM4
and
HAA5
species
(
Bull
et
al.,
2001)
While
based
on
more
limited
evidence,
reductions
in
reproductive
health
risks
are
considered
to
be
a
benefit
of
the
rule;
however
the
lack
of
data
preclude
quantification
of
this
benefit.
6For
example,
the
target
DBPs
being
regulated
may
not
be
good
surrogates
for
the
compounds
that
produce
the
reproductive
toxicities.
The
risks
identified
in
the
epidemiology
studies
are
much
greater
than
those
suggested
by
the
studies
of
these
individual
by­
products
in
animals.
It
is
important
to
note,
that
the
target
DBPs
do
not
include
the
most
potent
reproductive
toxicant
among
the
DBPs
examined
to
date,
bromochloroacetic
acid..

7The
recent
identification
of
N­
nitroso­
N­
dimethylamine
(
NDMA)
as
a
by­
product
of
chloramination
is
an
example.
NDMA
belongs
to
a
class
of
chemical
carcinogens
which
contains
some
members
that
are
known
to
produce
bladder
cancer
in
rats.
NDMA
is
between
3
and
4
orders
of
magnitude
more
potent
as
a
carcinogen
than
the
THM4
and
HAA5
(
U.
S.
EPA,
1997).
Perhaps
the
most
common
method
used
for
controlling
THM4
and
HAA5
formation
is
to
use
chlorine
combined
with
ammonia
for
residual
control.
Recent
work
has
shown
that
this
combined
chlorine
can
result
in
increased
NDMA
formation
(
Najm
and
Trussell,
2002,
Choi
and
Valentine,
2002,
Mitch
and
Sedlak,
2002).

31
On
the
other
hand,
the
panel
cautions
that
the
Agency
has
not
satisfactorily
demonstrated
that
promulgating
the
S2DBP
rule
will
result
in
the
reduction
in
bladder
cancer
risk
which
has
been
projected.
The
following
are
the
reasons
for
this
statement:

a)
The
disinfectant
by­
product
mixture
produced
when
water
is
chlorinated
is
extremely
complex,
and
within
a
given
system,
varies
considerably.
b)
The
specific
by­
products
resulting
in
increased
bladder
cancer
have
not
been
identified,
but
are
unlikely
to
be
accounted
for
by
the
aggregate
THM4
or
HAA56
concentrations.
c)
It
has
not
been
demonstrated
that
actions
taken
to
control
the
collective
THM4
and
HAA5
concentrations
will
also
control
other
known
and
unknown
by­
products.
d).
Treatment
technologies
may
emerge
that
target
only
the
regulated
by­
products,
without
addressing
the
rest
of
the
DBP
mixture.
e)
Some
technologies
aimed
at
reducing
the
target
DBPs
might
result
in
new
DBPs
of
unknown
significance7.

In
summary,
it
is
the
Panel's
opinion
that
cancer
and
reproductive
health
risks
are
likely
to
result
from
water
chlorination.
However,
the
Agency
has
not
demonstrated
that
the
health
risk
reductions
that
accrue
from
the
proposed
rule
will
be
proportional
to
the
reductions
in
the
THM4
and
HAA5
concentrations.
Some
health
benefits
in
addition
to
those
specifically
attributable
to
these
classes
of
DBPs
could
accrue,
but
only
to
the
extent
that
the
measures
that
water
systems
take
to
reduce
these
byproducts
also
reduce
the
concentrations
of
other
byproducts.
It
should
be
remembered
that
changing
treatment
has
some
potential
to
change
the
by­
product
mixture
produced
and
some
of
the
new
compounds
generated
could
be
more
harmful.
Nevertheless,
the
Panel
believes
that
some
risk
reduction
will
occur
and
that
speculation
such
as
that
discussed
above
should
not
delay
the
promulgation
of
the
present
rule.
R­
1
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State
University,
Dept.
of
Environmental
Health,
Fort
Collins,
CO,
October
31,
2000.

Rochelle,
PA,
DM
Ferguson,
DM
Johnson,
and
R.
DeLeon
(
2001).
Quantitation
of
Cryptosporidium
parvum
infection
in
cell
culture
using
a
colorimetric
in
situ
hybridization
assay.
J.
Eukaryot.
Microbial.
48:
565­
574.

Rochelle,
PA,
MM
Marshall,
JR
Mead,
AM
Johnson,
DG
Carrick,
JS
Rosen
and
R.
DeLeon.
(
2002).
Measurement
of
Cryptosporidium
parvum
infectivity:
in
vitro
cell
culture
compared
to
a
mouse
assay.
Applied
and
Environmental
Microbial.
submitted.

Sorvillo,
JF,
MPH,
K
Fagaceae,
PhD,
M
Torrey,
MPH,
R
Kebabjian,
RS,
W
Tokushige,
L
Mascola,
MD,
S
Schweid,
M
Hillario,
SH
Waterman,
MD
(
2001).
Epidemiologic
Notes
and
Reports
Swimming­
Associated
Cryptosporidiosis
­­
Los
Angeles
County.
MMWR
39(
20);
343­
345
Teunis,
PFM
and
AH
Havelaar
(
1999).
Cryptosporidium
in
drinking
water:
Evaluation
of
the
ILSI/
RSI
quantitative
risk
assessment
framework.
Rijksinstituut
voor
Volksgezondheid
en
Lilieu,
RIVM
report
number
284550006.

The
Cadmus
Group,
Inc.
(
2001a).
Occurrence
and
Exposure
Assessment
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule.
Report
under
Contract
68­
C­
00­
113,
August
27,
2001,
Fifth
Draft.
R­
4
The
Cadmus
Group,
Inc.
(
2001b).
Economic
Analysis
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
9.
Report
under
Contract
68­
C­
00­
113,
August
27,
2001,
Fifth
Draft.

The
Cadmus
Group,
Inc.
(
2001c).
Appendices
to
the
Economic
Analysis
for
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule.
Report
under
Contract
68­
C­
00­
113,
August
27,
2001,
Fifth
Draft.

The
Cadmus
Group,
Inc.
(
2001d).
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
Initial
Distribution
System
Evaluation
Guidance
Manual.
Report
under
Contract
68­
C­
99­
206,
August
22,
2001,
Fourth
Draft.

The
Cadmus
Group,
Inc.
(
2001e).
Excerpts
from
the
Economic
Analysis
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule.
Report
under
Contract
68­
C­
99­
206,
August
24,
2001,
Seventh
Draft
revised.

Tyl,
RW
(
2000).
Review
of
Animal
Studies
for
Reproductive
and
Developmental
Toxicity
Assessment
of
Drinking
Water
Contaminants:
Disinfection
By­
Products
(
DBPs).
Research
Triangle
Institute.
October
12,
2000.

Upton,
SJ,
M
Tilley
and
DB
Brillhart
(
1994).
Comparative
development
of
Cryptosporidium
parvum
in
11
continuous
cell
lines.
FEMS
Microbial.
Letters.
118:
233­
236.

USEPA
(
1997).
Integrated
Risk
Information
System.
N
 
Nitrosodimethylamine;
CASRN
62­
75­
9.

US
EPA
(
1998).
Quantification
of
Bladder
Cancer
Risk
from
Exposure
to
Chlorinated
Surface
Water.
US
EPA,
Office
of
Water,
Office
of
Science
and
Technology.
August
26,
1998.

US
EPA
(
2000).
Stage
2
Microbial
and
Disinfection
Byproducts
Federal
Advisory
Committee
Agreement
in
Principle.
FR
65,
No.
251:
pp83015­
83024,
December
29,
2000.

US
EPA.
(
2001a).
Microbial
toolbox
overview.
Draft
document
prepared
by
the
US
EPA
Office
of
Ground
Water
and
Drinking
Water
and
transmitted
to
the
SAB
via
an
email
from
Dr.
D.
Schmelling,
September
4,
2001.

US
EPA.
(
2001b).
Off­
stream
raw
water
storage.
Draft
document
prepared
by
the
US
EPA
Office
of
Ground
Water
and
Drinking
Water
and
transmitted
to
the
SAB
via
an
email
from
Dr.
D.
Schmelling,
September
4,
2001.

US
EPA
(
2001c).
Pre­
sedimentation.
Draft
document
prepared
by
the
US
EPA
Office
of
Ground
Water
and
Drinking
Water
and
transmitted
to
the
SAB
via
an
email
from
Dr.
D.
Schmelling,
September
4,
2001.
R­
5
US
EPA
(
2001d).
Lime
softening.
Draft
document
prepared
by
the
US
EPA
Office
of
Ground
Water
and
Drinking
Water
and
transmitted
to
the
SAB
via
an
email
from
Dr.
D.
Schmelling,
September
4,
2001.

US
EPA
(
2001e).
Lower
finished
water
turbidity.
Draft
document
prepared
by
the
US
EPA
Office
of
Ground
Water
and
Drinking
Water
and
transmitted
to
the
SAB
via
an
email
from
Dr.
D.
Schmelling,
September
4,
2001.

US
EPA
(
2001f).
Draft
of
preamble
section
.
Initial
distribution
system
evaluation
(
IDSE)
Undated.

US
EPA
(
2001g).
Draft
of
preamble
section
II.
Public
Health
Risk
Undated.
Pages
77­
116.

US
EPA
(
2001h).
Draft
of
preamble
section
.
Discussion
of
Proposed
Stage
2
DBPR
Requirements.
Undated.
Pages
155­
202.

US
EPA
(
2001i).
Draft
of
preamble
section
.
Monitoring
requirements
and
compliance
determination.
Undated.

Venu,
J.
E.,
Graham,
S.,
Freudenheim,
J.,
Marshall,
J.,
Zielezyny,
M.,
Swanson,
M.
and
Sufrin,
G.
(
1993).
Drinking
water,
fluid
intake,
and
bladder
cancer
in
Western
New
York.
Arch.
of
Environ.
Health,
48:
191­
198.

Vilanueva,
C.,
Kogevinas,
M.
and
Grimalt,
J.
(
2001).
Chlorination
of
drinking
water
in
Spain
and
bladder
cancer.
Gac.
Sanit.
15:
48­
53.
A­
1
ATTACHMENT
A
ACRONYMS
AND
ABBREVIATIONS
BAT
Best
Available
Treatment
cdf
Cumulative
Distribution
Frequency
CWS
Community
Water
System
DBP
Disinfection
Byproducts
DWC
Drinking
Water
Committee
EPA
U.
S.
Environmental
Protection
Agency
HAA5
Haloacetic
Acids
HAN
Haloacetonitriles
ICR
Information
Collection
Rule
ICRSS
Information
Collection
Rule
Supplemental
Survey
IDSE
Initial
Distribution
System
Evaluation
IESWTR
Interim
Enhanced
Surface
Water
Treatment
Rule
LRAA
Locational
Running
Annual
Average
LS
Lime
Softening
LT2ESWTR
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
MCL
Maximum
Contaminant
Level
MCLG
Maximum
Contaminant
Level
Goal
NTNCWS
Non­
transient
Non­
community
Water
Systems
PCR
Polymerase
Chain
Reaction
POTW
Publically
Owned
Treatment
Works
RAA
Running
Annual
Average
SAB
U.
S.
EPA
Science
Advisory
Board
SDWA
Safe
Drinking
Water
Act
Amendments
of
1996
SWAT
Surface
Water
Analytical
Tool
S2DBPR
Stage
2
Disinfection/
Disinfectant
Byproduct
Rule
THM
Trihalomethanes
TTHM
Total
Trihalomethanes
B­
1
ATTACHMENT
B
SELECTED
GLOSSARY
OF
TERMS
Bayesian
hierarchical
models
­
Statistical
hierarchical
models
with
Bayesian
parameter
estimation
techniques
which
fit
probability
models
to
a
set
of
data
and
summarizes
the
results
with
a
probability
distribution,
to
determine
parameters
of
a
hierarchical
model
to
predict
the
occurrence
distribution.

Bin
classification
framework
­
The
LT2ESWTR
incorporates
specific
treatment
requirements
for
protection
against
Cryptosporidium
involving
assignment
of
systems
into
different
categories
(
bins)
based
on
the
results
of
source
water
Cryptosporidium
monitoring.
Additional
treatment
requirements
depend
on
the
bin
to
which
the
system
is
assigned
(
see
Microbial
Toolbox
Options).

Cryptosporidium
­
Microbial
pathogen,
Cryptosporidium
parvum,
associated
with
waterborne
disease
(
i.
e.,
cryptosporidiosis)
and
known
to
infect
immunocompetent
and
immunocompromised
humans.

Endemic
disease
­
Disease
levels
that
are
natural
or
"
on­
going"
in
the
"
normal"
population
and
do
not
usually
reach
the
attention
of
medical
observers
as
would
an
epidemic.

Information
Collection
Rule
(
ICR)
­
EPA
rule
promulgated
in
1996
pursuant
to
SDWA
requirements
which
required
approximately
300
large
public
water
systems
to
conduct
18
months
of
sampling
for
water
quality
and
treatment
related
to
DBP
formation
and
the
occurrence
of
microbial
pathogens.
Data
on
DBP
formation
in
small
systems
was
obtained
through
1)
a
survey
of
approximately
120
treatment
plants
in
systems
serving
fewer
than
10,000
people
and
2)
information
received
from
seven
states
on
small
systems.

ICR
Supplemental
Surveys
(
ICRSS)
­
EPA
obtained
additional
pathogen
occurrence
data
through
ICRSS
which
involved
127
water
treatment
plants,
including
40
small
systems,
and
comprised
one­
year
of
bi­
monthly
sampling
for
Cryptosporidium,
Giardia,
and
other
water
quality
parameters
(
small
systems
did
not
measure
protozoa).

Initial
distribution
system
evaluation
­
Studies
conducted
by
Community
Water
Systems
which
are
intended
to
select
new
compliance
monitoring
sites
that
more
accurately
reflect
sites
representing
high
TTHM
and
HAA5
levels.
The
studies
are
based
on
either
on
system
specific
monitoring
or
other
system
specific
data
that
provides
equivalent
or
better
information
on
site
selection.

Locational
running
annual
average
(
LRAA)
­
RAAs
(
see
below)
calculated
for
each
sample
location
in
the
distribution
system
which
must
be
below
the
compliance
levels
(
MCLs)
in
each
quarter
of
the
year.
B­
2
Log
credits
­
The
logarithmic
range
of
credit
given
for
water
system
treatment
and
management
options
employed,
e.
g.,
reducing
pathogen
loading
into
the
plant,
pretreatment
processes,
additional
pathogen
barriers,
etc.

Log
removal
­
The
logarithm
of
the
reduction
in
microbial
density
due
to
an
action.
For
example
90%
removal
corresponds
to
1
log
removal.

Markov
Chain
Monte
Carlo
­
A
method
to
obtain
a
sample
from
the
posterior
distribution
of
the
parameters
in
a
Bayesian
hierarchical
model
that
involves
both
Monte
Carlo
integration,
to
handle
high­
dimensional,
intractable
integrals
and
construction
of
Markov
chains
to
draw
these
samples.
The
posterior
distribution
is
used
to
make
inferences
about
parameters
in
the
model
and
to
do
predictions.

Microbial
tool
box
options
­
Water
systems
will
choose
technologies
to
comply
with
additional
treatment
requirements
from
a
`
toolbox'
of
options,
e.
g.,
pretreatment
of
water
or
improved
disinfection.

PCR
(
Polymerase
chain
reaction)
­
The
process
of
rapidly
amplifying
a
defined
region
of
DNA
by
sequential
steps
of
denaturation
and
replication.

Priors
or
Prior
Distributions
­
Previous
probability
assessments
of
existing
data
used
to
estimate
occurrence
under
new
conditions.

Posterior
Probabilities
­
Estimates
of
occurrence
under
new
conditions
produced
using
prior
distributions.

Running
annual
average
(
RAA)
­
Quarterly
measurements
of
various
sampling
points
in
a
water
distribution
which
are
averaged
over
the
year
to
provide
a
average
which
is
compared
against
the
Maximum
Contaminant
Levels
(
MCLs)
for
TTHM
and
HAA5.

Surface
Water
Analytical
Tool
­
Model
used
in
conjunction
with
the
ICR
data
to
predict
the
impact
of
potential
new
standards
for
DBPs
and/
or
pathogens
on
shifts
in
treatment
technologies
among
water
systems
and
resulting
DBP
exposure
profiles.

Waterborne
Disease
Outbreak­
A
waterborne
disease
outbreak
occurs
when
two
or
more
persons
experience
a
similar
illness
after
consumption
or
use
of
water
intended
for
drinking
and
epidemiologic
evidence
implicates
the
water
as
the
source
of
illness.
This
outbreak
is
reported
by
the
authorities.
Also,
a
single
case
of
chemical
poisoning
constitutes
an
outbreak
if
laboratory
studies
indicate
that
the
water
has
been
contaminated
by
the
chemical.
Only
outbreaks
associated
with
water
intended
for
drinking
are
included.
C­
1
ATTACHMENT
C
BIOSKETCHES
OF
THE
DRINKING
WATER
COMMITTEE
MEMBERS
Science
Advisory
Board
(
SAB)
U.
S.
Environmental
Protection
Agency
Dr.
Mary
E.
Davis:
Dr.
Mary
E.
Davis
is
a
Professor
of
Toxicology
in
the
Department
of
Physiology
and
Pharmacology
at
West
Virginia
University
Health
Sciences
Center.
Her
research
interests
are
in
the
mechanisms
of
toxicity,
focusing
on
renal
and
cardiovascular
systems
and
liver
and
emphasizing
agents
of
environmental
and
occupational
interest,
including
halomethanes
and
disinfection
by­
products.
She
earned
a
doctorate
in
Pharmacology
from
Michigan
State
University
in
1977.

Dr.
Davis
is
a
member
of
the
Editorial
Board
of
Toxicology
and
Applied
Pharmacology,
and
has
served
on
the
Editorial
Board
of
Toxicology.
She
served
as
Treasurer
for
the
Society
of
Toxicology.
Dr.
Davis
previously
served
on
two
NRC
Subcommittees
on
the
health
effects
of
disinfectants
and
their
by­
products
and
use
of
physiologically­
based
pharmacokinetics
in
risk
assessment.
She
served
as
an
external
reviewer
of
EPA's
risk
assessment
of
the
WTI
hazardous
waste
incinerator
and
of
EPA's
proposed
guidelines
for
human
health
risk
assessment
protocol
for
hazardous
waste
incinerators.
In
addition
to
serving
on
the
DWC,
Dr.
Davis
has
been
the
SAB
Liaison
to
the
National
Drinking
Water
Advisory
Council
(
NDWAC)
and
was
a
member
of
the
SAB's
Chloroform
Review
Panel.

Dr.
Ricardo
DeLeon:
Dr.
De
Leon
is
the
Laboratory
Manager
for
the
Microbiology
Unit
of
the
Water
Quality
Laboratory
of
Metropolitan
Water
District
of
Southern
California.
The
Microbiology
Unit
consists
of
the
Compliance,
Development
and
Reservoir
Management
Teams.
His
area
of
expertise
is
water
microbiology,
methods
development
for
detection
of
microorganisms
in
water,
inactivation
of
pathogens
by
disinfection
and
removal
by
treatment
technology.
He
is
currently
working
primarily
on
drinking
water
but
his
expertise
also
includes
water
reuse
and
public
health
issues
associated
with
water.
He
has
been
working
in
the
area
of
water
microbiology
since
1983.

Dr.
De
Leon
holds
a
Bachelor's
of
Science
in
Microbiology
and
a
Ph.
D.
in
Microbiology
and
Immunology
from
the
University
of
Arizona
and
did
post­
doctoral
training
in
the
Department
of
Environmental
Sciences
and
Engineering
of
the
University
of
North
Carolina.
He
was
also
a
faculty
member
at
the
University
of
California,
Irvine
Campus
prior
to
joining
Metropolitan
Water
District.
He
has
been
the
principal
or
co­
principal
investigator
on
22
research
grants
on
methods
development,
disinfection
of
microorganisms
and
microbial
aspects
of
water
treatment
technology.
He
has
published
more
than
29
journal
articles
and
book
chapters
on
pathogen
detection
in
environmental
samples.
He
is
currently
serving
in
the
Drinking
Water
Committee
of
the
Science
Advisory
Board
to
the
U.
S.
Environmental
Protection
Agency
and
on
the
National
Research
Council
Committee
on
Indicators
of
Pathogens
in
Water.
C­
2
Dr.
Barbara
Harper:
Dr.
Harper
is
an
independent
consultant
in
the
areas
of
toxicology,
risk
assessment,
CERCLA
oversight,
tribal
water
quality,
and
environmental
management.
She
is
affiliated
with
AESE,
Inc
(
www.
aeseinc.
com).
AESE's
clientele
consists
entirely
of
Tribes/
Alaska
Natives.
She
is
also
an
adjunct
faculty
member
of
Oregon
State
University's
Public
Health
Department.
Dr.
Harper
is
a
board­
certified
toxicologist
(
Diplomate
of
the
American
Board
of
Toxicology,
1989).
She
received
her
B.
A.
degree
cum
laude
with
departmental
honors
in
biology
from
Occidental
College
in
1970.
She
received
her
PhD
in
genetics
from
the
University
of
Texas
at
Austin
in
1974.
She
was
on
the
faculty
of
the
University
of
Texas
Medical
Branch
(
UTMB)
at
Galveston
in
the
Department
of
Preventive
Medicine
and
Community
Health;
Division
of
Genetic
and
Environmental
Toxicology.
She
then
took
a
position
with
the
Commonwealth
of
Pennsylvania'
s
Department
of
Environmental
Resources,
and
developed
and
managed
the
Special
Science
and
Resources
Program.
She
taught
risk
assessment
as
an
adjunct
faculty
member
at
Penn
State
Harrisburg
during
this
time
period
as
well.
She
was
recruited
by
Battelle's
Pacific
Northwest
National
Lab
as
a
program
manager
in
risk
assessment
in
1993
(
Hanford),
where
she
started
working
on
tribal
risk
issues.
She
joined
the
Yakama
Nation
ERWM
Program
in
1997
and
developed
methods
for
tribal
risk
assessment
methods
now
in
use
at
DOE
and
EPA,
and
continues
to
develop
tribally­
relevant
methods
for
evaluating
cumulative
risks
and
impacts
to
tribal
health
and
culture.
Her
research
interests
include
contamination
of
fish
and
other
tribal
subsistence
foods,
the
associated
health
effects,
eco­
cultural
and
human
health
risk
method
development,
nutrition,
anthro­
toxicology,
and
tribal
parameters
for
subsistence
exposure
assessment.

Dr.
Irva
Hertz­
Picciotto:
Irva
Hertz­
Picciotto,
Ph.
D.,
Professor.
Dr.
Hertz­
Picciotto
received
her
Master's
of
Arts
in
Biostatistics,
a
Ph.
D.
in
Epidemiology
and
a
Master's
of
Public
Health
from
the
University
of
California,
Berkeley.
She
has
held
positions
as
Assistant,
Associate
and
Full
Professor
at
the
University
of
North
Carolina,
Chapel
Hill,
and
most
recently
joined
the
Department
of
Epidemiology
and
Preventive
Medicine
at
the
University
of
California,
Davis.
Dr.
Hertz­
Picciotto
receives
funding
for
research
from
the
National
Institutes
of
Health,
the
U.
S.
Environmental
Protection
Agency,
the
Medical
Investigations
of
Neurodevelopmental
Disorders
(
M.
I.
N.
D.)
Institute,
State
of
California
Office
of
Environmental
Health
Hazard
Assessment,
the
Health
Effects
Institute,
the
Hawaii
Heptachlor
Research
and
Education
Foundation,
the
International
Life
Sciences
Institute,
and
the
University
of
California,
Berkeley.

Dr.
Hertz­
Picciotto
serves
on
editorial
boards
for
the
two
major
journals
in
her
field,
namely
Epidemiology
and
the
American
Journal
of
Epidemiology,
as
well
as
for
Human
and
Ecological
Risk
Assessment.
She
served
as
Chair
of
the
Institute
of
Medicine/
National
Academy
of
Science's
Veterans
and
Agent
Orange:
Update
2000
committee,
and
is
currently
Chair
of
the
IOM/
NAS
Update
2002
committee.
Dr.
Hertz­
Picciotto
is
also
a
member
of
the
Board
of
Scientific
Counselors
of
the
U.
S.
National
Toxicology
Program,
the
Food
Safety
in
Europe
Working
Group
sponsored
by
the
International
Life
Sciences
Institute,
and
the
Carcinogen
Identification
Committee
of
the
California
Governor's
Scientific
Advisory
Board.
She
is
currently
President
of
the
International
Society
for
Environmental
Epidemiology,
and
was
recently
a
delegate
to
the
NIEHS­
sponsored
U.
S.­
Vietnam
Scientific
Conference
on
the
C­
3
Environmental
and
Health
Effects
of
the
Vietnam
War.
She
founded
the
Center
on
Environmental
Health
and
Susceptibility
at
the
University
of
North
Carolina,
Chapel
Hill.
For
over
ten
years,
she
has
taught
methods
for
epidemiologic
data
analysis
in
Chapel
Hill,
and
has
taught
courses
on
four
continents.
Dr.
Hertz­
Picciotto
has
published
seminal
papers
on
the
use
of
epidemiology
in
quantitative
risk
assessment
and
is
internationally
renowned
for
her
work
in
this
field,
as
well
as
occupationally
related
cancer,
environmental
exposures,
reproductive
outcomes,
and
methods
for
epidemiologic
research.

Dr.
Joseph
R.
Landolph:
Dr.
Joseph
R.
Landolph
is
currently
Associate
Professor
of
Molecular
Microbiology
and
Immunology
and
Pathology
and
a
Member
of
the
USC/
Norris
Comprehensive
Cancer
Center,
in
the
Keck
School
of
Medicine
and
Associate
Professor
of
Molecular
Pharmacology
and
Toxicology,
in
the
School
of
Pharmacy,
with
tenure,
at
the
University
of
Southern
California
(
USC)
in
Los
Angeles,
California.
Dr.
Landolph
received
a
B.
S.
degree
in
Chemistry
from
Drexel
University
in
l971
and
a
Ph.
D.
in
Chemistry
from
the
University
of
California
at
Berkeley
in
l976,
under
the
guidance
of
the
late
Professor
Melvin
Calvin,
where
he
studied
the
metabolism
of
the
chemical
carcinogen,
benzo(
a)
pyrene,
and
its
ability
to
induce
cytotoxicity
in
cultured
mouse
liver
epithelial
cells
and
morphological
transformation
in
Balb/
c
3T3
mouse
fibroblasts.
Dr.
Landolph
performed
postdoctoral
study
in
chemical
carcinogenesis
and
chemically
induced
morphological
and
neoplastic
cell
transformation
and
mutagenesis
at
the
USC/
Norris
Comprehensive
Cancer
Center
at
the
University
of
Southern
California
under
the
late
Professor
Charles
Heidelberger
from
l977­
l980.
Dr.
Landolph
was
appointed
Assistant
Professor
of
Pathology
in
l980,
and
Associate
Professor
of
Microbiology,
Pathology,
and
Toxicology
at
USC
in
l987.
Dr.
Landolph
has
served
as
a
grant
reviewer
for
the
U.
S.
E.
P.
A.
Health
Effects
Panel,
for
special
RFAs
for
the
N.
I..
E.
H.
S.,
and
as
an
ad
hoc
member
for
the
Chemical
Pathology
Study
Section
and
the
Al­
Tox­
4
Study
Section
of
the
N.
I.
H.
Dr.
Landolph
has
also
been
a
member
of
the
Carcinogen
Identification
Committee
reporting
to
the
Scientific
Advisory
Committee
of
the
Office
of
Environmental
Health
Hazard
Assessment
of
the
California
Environmental
Protection
Agency
from
1994­
2002.
He
is
the
recipient
of
numerous
awards,
including
the
Merck
Award
in
Chemistry
and
the
Superior
Cadet
Award
in
ROTC
from
Drexel
University
in
l971,
the
Edmundson
Teaching
Award
in
the
Dept.
of
Pathology
at
USC
in
l985,
a
Traveling
Lectureship
Award
from
the
U.
S.
Society
of
Toxicology
in
l990,
and
a
competitive
American
Cancer
Society
Postdoctoral
Fellowship
from
l977­
l979.
Dr.
Landolph
receives
funding
from
the
Nickel
Producers
Environmental
Research
Association
(
NiPERA),
from
the
National
Cancer
Institute,
National
Institutes
of
Health,
from
the
National
Institute
of
Allergy
and
Infectious
Diseases,
National
Institutes
of
Health,
and
from
the
Office
of
Environmental
Health
Hazard
Assessment
of
the
Environmental
Protection
Agency
of
the
State
of
California.

Dr.
Landolph's
research
interests
and
activities
include
studies
of
the
genetic
toxicology
and
carcinogenicity
of
carcinogenic
insoluble
nickel
compounds,
carcinogenic
chromium
compounds,
carcinogenic
arsenic
compounds,
and
carcinogenic
polycyclic
aromatic
hydrocarbons.
His
laboratory
is
focused
on
studying
the
ability
of
these
carcinogens
to
induce
morphological
and
neoplastic
transformation
of
C3H/
10T1/
2
mouse
embryo
cells
and
the
cellular
and
molecular
biology
of
the
transformation
process.
His
laboratory
is
currently
studying
the
ability
of
carcinogenic
nickel
compounds
to
induce
activation
of
expression
of
C­
4
oncogenes
and
inactivation
of
expression
of
tumor
suppressor
genes
in
cells
transformed
by
insoluble
carcinogenic
nickel
compounds,
such
as
nickel
subsulfide,
crystalline
nickel
monosulfide,
and
green
(
high
temperature)
and
black
(
low
temperature)
nickel
oxides.
His
laboratory
is
also
studying
the
molecular
biology
of
chromium
compound­
induced
cell
transformation
and
the
role
of
valence
in
cell
transformation
by
various
chromium­
containing
compounds.
Dr.
Landolph
is
an
expert
in
chemically
induced
morphological
and
neoplastic
transformation
and
chemically
induced
mutation
in
murine
and
human
fibroblasts.
He
is
the
author
of
32
peer­
reviewed
scientific
publications,
21
book
chapters/
review
articles,
and
has
held
peer­
reviewed
research
grant
support
from
the
U.
S.
E.
P.
A.,
the
U.
S.
National
Cancer
Institute,
and
the
U.
S.
Institute
of
Environmental
Health
Sciences.

Dr.
David
L.
Sedlak:
Dr.
David
L.
Sedlak
is
Associate
Professor
of
Civil
and
Environmental
Engineering
at
the
University
of
California,
Berkeley.
Dr.
Sedlak
received
has
B.
S.
degree
in
Environmental
Science
from
Cornell
University
in
1986.
He
received
his
Ph.
D.
degree
in
Water
Chemistry
from
the
University
of
Wisconsin
in
Madison
in
1992
and
served
as
a
postdoctoral
researcher
at
the
Swiss
Federal
Institute
for
Environmental
Science
and
Technology
(
EAWAG)
from
1992
to
1994.
He
has
received
several
notable
awards
including
the
NSF
CAREER
Award
in
1997,
the
Hellman
Family
Faculty
Award
in
1996
and
the
American
Chemical
Society
Graduate
Student
Award
in
1991.
His
areas
of
research
interest
include
analytical
methods
for
measuring
organic
compounds
in
water,
fate
of
chemical
contaminants
in
water
recycling
systems,
metal
speciation
and
its
effect
on
metal
uptake
and
reaction,
environmental
photochemistry
and
ecological
engineering.
David
Sedlak
receives
research
funding
from
federal
(
i.
e.,
National
Science
Foundation)
and
state
(
i.
e.,
University
of
California
Water
Resources
Program,
University
of
California
Toxic
Substances
Research
and
Teaching
Program)
programs.
He
also
receives
funding
from
a
private
foundation
(
i.
e.,
National
Water
Research
Institute)
and
several
water
industry
sponsored
foundations
(
i.
e.,
American
Water
Works
Association
Research
Foundation,
Water
Environment
Research
Foundation
and
WateReuse
Foundation)

Dr.
Philip
C.
Singer:
Dr.
Philip
C.
Singer
is
the
Dan
Okun
Professor
of
Environmental
Engineering
in
the
Department
of
Environmental
Sciences
and
Engineering
in
the
School
of
Public
Health
at
the
University
of
North
Carolina
at
Chapel
Hill.
He
directed
the
Water
Resources
Engineering
Program
at
UNC
for
19
years
and
currently
directs
UNC's
Drinking
Water
Research
Center.
He
has
conducted
research
on
chemical
aspects
of
water
and
wastewater
treatment
and
on
aquatic
chemistry
for
the
past
35
years,
and
has
published
more
than
160
papers
and
reports
in
these
areas.
For
the
past
27
years,
Dr.
Singer's
research
has
focused
on
the
formation
and
control
of
disinfection
by­
products
in
drinking
water.
In
1993,
Dr
Singer
was
selected
for
the
Freese
Lecture
by
the
American
Society
of
Civil
Engineers,
in
1995
he
was
given
the
A.
P.
Black
Research
Award
by
the
American
Water
Works
Association,
and
in
1999
he
received
the
Fuller
Award
from
the
North
Carolina
section
of
the
American
Water
Works
Association.

Dr.
Singer
has
been
active
in
the
American
Water
Works
Association,
serving
as
a
past
Chair
and
Trustee
of
the
Research
Division,
and
has
served
on
the
Research
Advisory
Council
of
the
American
Water
Works
Association
Research
Foundation.
He
was
on
the
editorial
board
of
C­
5
Ozone
Science
and
Engineering
and
is
a
past
associate
editor
of
Environmental
Science
and
Technology.
He
was
a
member
of
the
Water
Science
and
Technology
Board
of
the
National
Research
Council,
and
served
on
the
National
Research
Council's
Committee
on
Drinking
Water
Contaminants.
He
is
currently
on
the
Board
of
Directors
of
the
Water
Environment
Research
Foundation
and
the
U.
S.
Environmental
Protection
Agency
Science
Advisory
Board's
Drinking
Water
Committee.
In
1995,
Dr.
Singer
was
inducted
into
the
National
Academy
of
Engineering.

Dr.
Laura
Steinberg:
Dr.
Steinberg
is
Associate
Professor
in
the
Civil
and
Environmental
Engineering
Department
of
Tulane
University.
She
holds
a
B.
S.
E.
in
Civil
and
Urban
Engineering
from
the
University
of
Pennsylvania
and
an
M.
S.
and
Ph.
D.
in
Environmental
Engineering
from
Duke
University.
Her
research
currently
focuses
on
water
quality
modeling
and
natural
hazards
management.
She
has
recently
completed
modeling
studies
of
arsenic
concentrations
in
water
distribution
systems
and
transport
processes
in
contaminated
sediments,
and
is
working
on
spatial
statistical
modeling
of
heavy
metals
and
PCB's
in
contaminated
sediments.
During
the
last
two
years,
she
has
spent
several
months
in
Turkey,
investigating
the
impacts
of
the
devastating
earthquake
of
1999
on
industrial
infrastructure
and
the
environment,
and
evaluating
the
effectiveness
of
chemical
risk
management
procedures.
Dr.
Steinberg
is
the
incoming
chair
of
the
American
Society
of
Civil
Engineer's
National
Environmental
Policy
Committee,
and
a
past
member
of
the
ASCE's
National
Water
Policy
Committee.
She
serves
on
the
Water
Environment
Federation's
Disinfection
Committee,
and
is
a
fellow
of
the
Institute
of
Civil
Infrastructure
Systems
and
a
former
member
of
the
Chapel
Hill,
NC
Planning
Board.
She
has
consulted
to
the
USEPA's
Science
Advisory
Board
on
technology
diffusion,
and
the
Department
of
Energy
on
risk
assessment.
Prior
to
her
work
in
academia,
Dr.
Steinberg
was
Environmental
Engineering
Department
Head
at
the
planning
and
engineering
firm
of
Louis
Berger
International,
and
Business
Development
Manager
at
Geraghty
and
Miller,
an
environmental
engineering
firm.
She
also
had
the
distinct
honor
of
serving
as
a
US
Congressional
Page
while
attending
high
school.

Ms.
Susan
Teefy:
Susan
Teefy
currently
serves
on
the
staff
of
the
Water
Quality
and
Treatment
Solutions,
Inc.
Susan
formerly
served
as
the
Operations
Engineer
for
the
Alameda
County
Water
District
in
Fremont
California.
Since
1992,
she
has
worked
with
this
public
water
agency
to
ensure
compliance
with
drinking
water
regulations,
and
analyze
and
optimize
plant
operations.
She
has
held
positions
of
increasing
authority
with
the
District,
including
Manager
of
the
Water
Production
Division,
which
is
responsible
for
the
operation
and
maintenance
of
three
water
treatment
plants
and
the
distribution
system.
Ms.
Teefy
has
also
supervised
ACWD's
Environmental
Engineering
section,
where
she
developed
and
implemented
water
quality
monitoring
programs
and
conducted
plant
optimization
studies.
Her
particular
interest
is
surface
water
treatment
(
particulate
removal
processes)
and
ozone
disinfection.
Prior
to
working
with
the
Alameda
County
Water
District,
she
worked
at
the
East
Bay
Municipal
Utility
District
in
Oakland
California,
providing
technical
support
for
surface
water
treatment
plant
operations.
Ms.
Teefy
also
worked
for
the
U.
S.
Environmental
Protection
Agency,
Region
9,
in
San
Francisco
where
she
managed
the
drinking
water
program
on
Indian
Lands
in
California.

Ms.
Teefy
has
a
bachelor's
degree
in
civil
engineering
from
the
University
of
California
at
Berkeley,
and
a
master's
degree
in
environmental
engineering
from
the
University
of
North
C­
6
Carolina
at
Chapel
Hill.
She
is
a
registered
civil
engineer
in
the
state
of
California,
and
a
licensed
water
treatment
plant
operator
(
Grade
5,
highest
level).
In
1985
she
was
awarded
USEPA's
Bronze
Medal
for
outstanding
service
for
significantly
improving
compliance
with
drinking
water
regulations
on
California
Indian
Lands.
In
1989
she
was
the
first
recipient
of
the
AWWA
Larson
Aquatic
Research
Support
(
LARS)
Scholarship.
In
1991
she
received
AWWA's
Academic
Achievement
award
for
her
Master's
thesis.
She
has
chaired
AWWA's
California
Nevada
Section
Research
Committee,
and
currently
is
a
member
of
AWWA's
national
coagulation
and
filtration
committee.
Ms.
Teefy
has
been
a
Project
Advisory
Committee
member
on
several
projects
funded
by
the
AWWA
Research
Foundation,
and
a
peer­
reviewer
for
the
Journal
of
AWWA.
She
has
served
on
AWWARF's
Unsolicited
Proposal
Review
Committee,
as
well
as
AWWARF
and
EPA­
convened
Expert
Panels
regarding
water
treatment
issues.
She
has
given
numerous
presentations
at
international
AWWA
and
International
Ozone
Association
conferences
Dr.
Gary
A.
Toranzos:
Gary
A.
Toranzos
is
a
professor
of
microbiology
in
the
Department
of
Biology,
University
of
Puerto
Rico,
Rio
Piedras
Campus.
He
got
his
Ph.
D.
in
1985
at
the
University
of
Arizona
in
Tucson.
His
research
interests
are
varied
and
include
water
microbiology,
the
ecology
of
enteric
pathogens
and
the
development
of
indicators
of
risk.
He
has
published
extensively
on
all
the
above
subjects
and
is
currently
working
on
projects
dealing
with
bacterial
nitrification
and
denitrification
in
soils,
as
well
as
development
of
new
indicators
of
biological
contamination
in
waters.
Dr.
Gary
A.
Toranzos
receives
funding
from
NASA
to
study
nitrifying
and
denitrifying
microbial
communities
in
tropical
soils.
He
also
has
funding
from
the
USGS
(
Water
Resources
Center,
University
of
the
U.
S.
Virgin
Islands)
to
study
the
microbial
water
quality
of
bathing
beaches
in
Puerto
Rico
and
St.
Thomas,
U.
S.
V.
I.

He
is
currently
working
at
the
National
Science
Foundation
as
a
Program
Director
in
the
Division
of
Molecular
and
Cellular
Biosciences.

He
is
an
elected
member
of
the
American
Academy
of
Microbiology,
a
Fellow
of
the
American
Association
for
the
Advancement
of
Science
and
is
serving
a
term
as
member
of
the
Technical
Advisory
Board
of
the
Water
Environment
Research
Foundation
Dr.
Rhodes
Trussell:
Dr.
R.
Rhodes
Trussell
is
Director
of
the
Water
Knowledge
Center
and
Senior
Vice
President
at
MWH,
Inc.
He
has
served
in
that
Role
since
September
2001.
For
several
years
prior
to
that
he
served
as
the
firm's
Director
of
Corporate
Development
and
as
a
member
of
the
firm's
Board
of
Directors.
The
bulk
of
Dr.
Trussell's
technical
career
has
been
spent
advising
municipal
utilities,
both
in
the
US
and
abroad,
concerning
problems
of
drinking
water
quality
and
treatment.
Dr.
Trussell
is
active
in
American
Water
Works
Association
and
in
the
International
Water
Association
where
he
serves
on
the
program
committee,
the
Strategic
Council
and
the
editorial
board
for
North
America.
He
also
serves
on
the
Water
Science
and
Technology
Board
for
the
National
Resource
Council
where
he
has
served
on
several
specific
Committees,
most
recently
those
on
potable
reuse,
the
CCL,
and
indicators
for
pathogens
in
water.
Dr.
Trussell
serves
on
the
Magazine
Board
for
Environmental
Science
and
Technology,
as
a
member
of
the
Industrial
Advisory
Board
for
Engineering
program
at
UC
Riverside
and
as
Chair
of
the
Industrial
Advisory
Board
for
the
Department
of
Civil
Engineering
at
UCLA.
Dr.
C­
7
Trussell
received
his
B.
S.(
1966),
M.
S.(
1967),
and
Ph.
D.(
1972)
in
Environmental
Engineering
from
the
University
of
California
at
Berkeley.
He
was
elected
to
the
National
Academy
of
Engineering
in
1995
and
serves
on
the
Peer
Committee
for
Civil
Engineering.
He
is
currently
the
Chair
of
the
SAB's
Drinking
Water
Committee.

For
the
past
30+
years,
Dr.
Trussell
has
worked
for
MWH,
Inc.
and
is
solely
funded
by
the
corporation.
During
the
past
year
he
as
worked
directly
on
projects
for
the
city
of
Portland
Oregon,
for
the
East
Bay
Municipal
Water
District,
for
Hong
Kong,
the
City
of
San
Diego,
the
City
of
Long
Beach,
the
Metropolitan
Water
district
of
Southern
California,
and
the
Los
Angeles
Department
of
Water
and
Power.