Document ID: EPA-HQ-OW-2002-0043-0210
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-08-11T04:00Z

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
i
Contents
List
of
Appendices
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vi
List
of
Exhibits
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vii
List
of
Acronyms
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xii
Health
Risk
Reduction
and
Cost
Analysis
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xvi
Executive
Summary
ES.
1
Need
for
the
Rule
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ES­
1
ES.
2
Consideration
of
Regulatory
Alternatives
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ES­
2
ES.
3
Summary
of
the
Proposed
Stage
2
DBPR
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ES­
2
ES.
4
Systems
Subject
to
the
Stage
2
DBPR
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ES­
6
ES.
5
National
Benefits
and
Costs
of
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
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ES­
8
ES.
5.1
Plants
Making
Treatment
Changes
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ES­
10
ES.
5.2
Derivation
of
Benefits
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ES­
12
ES.
5.3
Derivation
of
Costs
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ES­
14
ES.
6
Estimated
Impacts
on
Household
Costs
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ES­
15
ES.
7
Comparison
of
Costs
and
Benefits
for
Four
Regulatory
Alternatives
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ES­
16
ES.
8
Conclusions
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ES­
18
Chapter
1.
Introduction
1.1
Summary
of
the
Stage
2
DBPR
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1­
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1.2
Document
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1­
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1.3
Calculations
and
Citations
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1­
9
Chapter
2.
Need
for
the
Proposal
2.1
Introduction
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2­
1
2.1.1
Description
of
the
Issue
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2­
1
2.2
Public
Health
Concerns
to
Be
Addressed
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2­
1
2.3
Regulatory
History
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2­
2
2.3.1
Statutory
Authority
for
Promulgating
the
Rule
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2­
2
2.3.2
1979
Total
Trihalomethane
Rule
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2­
3
2.3.3
1989
Total
Coliform
Rule
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2­
3
2.3.4
1989
Surface
Water
Treatment
Rule
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2­
4
2.3.5
1996
Information
Collection
Rule
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2­
4
2.3.6
1998
Interim
Enhanced
Surface
Water
Treatment
Rule
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2­
5
2.3.7
1998
Stage
1
Disinfectants
and
Disinfection
Byproducts
Rule
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2­
5
2.3.8
2000
Proposed
Ground
Water
Rule
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2­
6
2.3.9
2001
Arsenic
Rule
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2­
6
2.3.10
2001
Filter
Backwash
Recycling
Rule
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2­
6
2.3.11
2002
Long
Term
1
Enhanced
Surface
Water
Treatment
Rule
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2­
7
2.3.12
2002
Proposed
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
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2­
7
2.4
Economic
Rationale
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2­
7
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
ii
Chapter
3.
Baseline
Conditions
3.1
Introduction
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3­
1
3.2
Data
Sources
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3­
2
3.3
Predictive
Tools
for
Analysis
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3­
3
3.3.1
The
Surface
Water
Analytical
Tool
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3­
4
3.3.2
The
Small
Surface
Water
Expert
Review
Process
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3­
6
3.3.3
The
ICR
Ground
Water
Delphi
Poll
Process
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3­
9
3.3.4
The
Small
Ground
Water
Expert
Review
Process
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3­
9
3.4
Industry
Profile
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3­
10
3.4.1
Public
Water
System
Categorization
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3­
10
3.4.2
Systems,
Plants,
and
Population
Subject
to
the
Stage
2
DBPR
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3­
12
3.4.2.1
System
Baseline
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3­
13
3.4.2.2
Plant
Baseline
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3­
15
3.4.2.3
Population
Baseline
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3­
21
3.4.3
Water
Treatment
Plant
Design
and
Average
Daily
Flows
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3­
24
3.4.4
Number
of
Households
Served
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3­
26
3.4.5
Uncertainty
in
Baseline
Input
Data
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3­
27
3.5
Influent
Water
Quality
Characterization
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3­
28
3.5.1
Summary
of
Available
Influent
Water
Quality
Data
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3­
28
3.5.2
Regional
Differences
in
Water
Quality
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3­
30
3.6
Treatment
Characterization
for
the
Pre­
Stage
1
and
Pre­
Stage
2
DBPRs
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3­
35
3.6.1
Treatment
Technologies
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3­
35
3.6.2
Treatment
Characterization
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3­
39
3.7
DBP
Occurrence
for
the
Pre­
Stage
1
and
Pre­
Stage
2
DBPR
Baselines
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3­
44
3.7.1
Description
of
ICR
and
SWAT
DBP
Data
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3­
45
3.7.1.1
ICR
DBP
Data
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3­
45
3.7.1.2
SWAT
DBP
Data
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.
3­
46
3.7.2
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Large
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
46
3.7.3
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
in
Large
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
52
3.7.4
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Medium
Surface
and
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
53
3.7.5
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrences
for
Small
Surface
and
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3­
53
3.8
Summary
of
Uncertainties
in
Development
of
Stage
2
DBPR
Baselines
.
.
.
.
.
.
.
.
.
.
.
.
3­
55
Chapter
4.
Consideration
of
Regulatory
Alternatives
4.1
Introduction
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
4­
1
4.2
Process
for
Development
of
Regulatory
Alternatives
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4­
1
4.3
Regulatory
Alternatives
Considered
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
4­
3
Chapter
5.
Benefits
Analysis
5.1
Introduction
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
1
5.1.1
Overview
of
Methodology
for
Quantifying
Stage
2
DBPR
Benefits
.
.
.
.
.
.
.
.
.
5­
2
5.1.2
Summary
of
National
Benefits
of
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
4
5.2
Problem
Identification
and
Assessment
of
Potential
Hazard
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
5
5.2.1
Reproductive
and
Developmental
Health
Effects
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
5
5.2.1.1
Epidemiological
Evidence
of
Adverse
Reproductive
and
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
iii
Developmental
Health
Effects
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
6
5.2.1.2
Toxicological
Evidence
of
Adverse
Reproductive
and
Developmental
Health
Effects
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
15
5.2.1.3
Conclusions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
19
5.2.2
Cancer
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
20
5.2.2.1
Epidemiological
Evidence
of
DBP
Carcinogenicity
.
.
.
.
.
.
.
.
5­
20
5.2.2.2
Toxicological
Evidence
of
DBP
Carcinogenicity
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
24
5.2.2.3
Conclusions
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
.
.
.
.
.
.
5­
28
5.3
Exposure
Assessment
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
.
.
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.
.
.
.
.
.
.
.
.
5­
29
5.3.1
Population
Exposed
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
29
5.3.2
Routes
of
Exposure
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
30
5.3.3
Special
Exposure
Issues
for
Pregnant
Women
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
31
5.4
Occurrence
and
Exposure
Reduction
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
31
5.4.1
Occurrence
and
Exposure
Reduction:
Peak
DBPs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
32
5.4.1.1
Methodology
for
Evaluating
ICR
Data
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
33
5.4.1.2
Discussion
of
Changes
in
Peak
DBP
Occurrence
.
.
.
.
.
.
.
.
.
5­
35
5.4.1.3
Estimated
Reduction
in
Peak
DBP
Exposure
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
41
5.4.2
Exposure
Reduction:
Average
DBPs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
43
5.5
Benefits
of
the
Stage
2
DBPR:
Reduced
Incidence
of
Adverse
Effects
.
.
.
.
.
.
.
.
.
.
.
.
5­
49
5.5.1
Reduced
Incidence
of
Reproductive
and
Developmental
Effects
.
.
.
.
.
.
.
.
.
.
5­
49
5.5.2
Reduced
Incidence
of
Bladder
Cancer
Cases
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
49
5.5.2.1
Annual
Cancer
Cases
Avoided
(
Steady­
State)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
50
5.5.5.2
Annual
Cancer
Cases
Avoided
Accounting
for
Cessation
Lag
.
.
.
.
.
.
5­
52
5.5.2.3
Adjustments
in
Annual
Cancer
Cases
Avoided
to
Account
for
the
Rule
Implementation
Schedule
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
56
5.5.3
Other
Health­
Related
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
60
5.5.4
Non­
Health­
Related
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
60
5.5.5
Potential
Increases
in
Health
Risks
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
60
5.6
Valuation
of
Health
Benefits
for
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
64
5.6.1
Value
of
Reductions
in
Potential
Adverse
Reproductive
and
Developmental
Health
Effects
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
64
5.6.2
Value
of
Reductions
in
Bladder
Cancer
Cases
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
65
5.6.3
Value
of
Benefits
Resulting
from
the
Stage
2
DBPR
for
the
Preferred
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
70
5.6.4
Comparison
of
the
Value
of
Benefits
for
Regulatory
Alternatives
.
.
.
.
.
.
.
.
.
.
5­
76
5.7
Uncertainties
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
78
5.8
Sensitivity
Analyses
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
78
5.9
Potential
Fetal
Losses
Avoided
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
81
5.9.1
Reproductive
Effects
Illustrative
Calculation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
81
5.9.2
Value
of
Reductions
in
Fetal
Losses
Avoided
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
83
Chapter
6.
Cost
Analysis
6.1
Introduction
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
1
6.1.1
Overview
of
Methodology
for
Quantifying
Stage
2
DBPR
Costs
.
.
.
.
.
.
.
.
.
.
.
6­
2
6.1.1.1
Baseline
Data
Inputs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
2
6.1.1.2
Technology
Unit
Costs
and
Technology
Selection
Forecasts
.
.
.
.
.
.
.
.
6­
4
6.1.1.3
Projections
and
Discounting
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
4
6.1.1.4
Household
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
6
6.1.1.5
Modeled
Uncertainty
in
National
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
7
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
iv
6.2
Summary
of
the
National
Costs
of
the
Stage
2
DBPR
(
Preferred
Alternative)
.
.
.
.
.
.
.
.
6­
7
6.2.1
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
8
6.2.2
Plants
Adding
Treatment
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
10
6.2.3
Summary
of
One­
Time
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
10
6.2.4
Summary
of
Total
Annualized
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
13
6.3
Non­
Treatment
Costs
for
Systems
and
States/
Primacy
Agencies
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
13
6.3.1
Rule
Implementation
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
16
6.3.2
Initial
Distribution
System
Evaluations
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
17
6.3.3
Additional
Routine
Monitoring
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
17
6.3.4
Significant
Excursion
Evaluations
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
18
6.3.5
Results
(
One­
Time
and
Annual
Steady­
State
Costs)
.
.
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.
6­
19
6.4
Treatment
Costs
.
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6­
19
6.4.1
Technologies
and
Unit
Costs
.
.
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6­
19
6.4.1.1
Technologies
Used
to
Estimate
Treatment
Costs
.
.
.
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.
6­
21
6.4.1.2
Alternatives
to
Treatment
.
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6­
30
6.4.2
Compliance
Forecasts
.
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6­
30
6.4.2.1
Overview
of
Compliance
Forecast
Methodology
.
.
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.
6­
31
6.4.2.2
Surface
Water
Compliance
Forecasts
.
.
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.
6­
33
6.4.2.3
Ground
Water
Compliance
Forecasts
.
.
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6­
37
6.4.2.4
Uncertainties
in
Compliance
Forecast
.
.
.
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.
6­
37
6.4.3
Results
(
Initial
Capital
and
Steady­
State
O&
M
Costs)
.
.
.
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.
6­
37
6.5
Projecting
and
Discounting
Costs
.
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6­
41
6.6
Household
Costs
.
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6­
44
6.7
Unquantifiable
Costs
.
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6­
51
6.8
Uncertainty
Analysis
.
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6­
51
6.9
Comparison
of
Regulatory
Alternatives
.
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6­
53
Chapter
7.
Compliance
Forecast
Sensitivity
Analyses
7.1
Introduction
.
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.
7­
1
7.2
IDSE
Sensitivity
Analysis
.
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.
7­
2
7.3
Minimal
Impact
Sensitivity
Analysis
.
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7­
8
Chapter
8.
Economic
Impact
Analysis
8.1
Introduction
.
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.
8­
1
8.2
Regulatory
Flexibility
Act
and
Small
Business
Regulatory
Enforcement
Fairness
Act
.
.
.
8­
1
8.3
Small
System
Affordability
.
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8­
8
8.3.1
Affordability
Threshold
.
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8­
9
8.3.2
Affordable
Compliance
Technologies
.
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8­
11
8.3.3
Funding
Options
for
Disadvantaged
Systems
.
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8­
14
8.4
Feasible
Treatment
Technologies
for
All
Systems
.
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8­
14
8.4.1
ICR
Treatment
Studies
.
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8­
15
8.4.2
BAT
Evaluation
Using
SWAT
.
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8­
16
8.4.3
BATs
for
Consecutive
Systems
.
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8­
17
8.5
Effect
of
Compliance
with
the
Stage
2
DBPR
on
the
Technical,
Managerial,
and
Financial
Capacity
of
Public
Water
Systems
.
.
.
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.
8­
18
8.5.1
Requirements
of
the
Preferred
Regulatory
Alternative
.
.
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.
8­
19
8.5.2
Systems
Subject
to
the
Stage
2
DBPR
.
.
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.
8­
20
8.5.3
Impact
of
the
Stage
2
DBPR
on
System
Capacity
.
.
.
.
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.
8­
20
8.5.4
Final
Analysis
of
Impact
of
the
Stage
2
DBPR
on
Small
System
Capacity
.
.
.
.
8­
20
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
v
8.5.5
Derivation
of
Stage
2
DBPR
Scores
.
.
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.
8­
23
8.5.5.1
Familiarization
with
the
Stage
2
DBPR
.
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8­
24
8.5.5.2
Conducting
an
Initial
Distribution
System
Evaluation
.
.
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.
8­
25
8.5.5.3
Compliance
with
MCLs
for
TTHM
and
HAA5
.
.
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.
8­
25
8.5.5.4
Additional
Routine
Monitoring
.
.
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8­
27
8.5.5.5
Significant
Excursion
.
.
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.
8­
27
8.5.6
Rationale
for
Scores
.
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.
8­
28
8.6
Paperwork
Reduction
Act
.
.
.
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.
.
8­
28
8.7
Unfunded
Mandates
Reform
Act
Analysis
.
.
.
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.
8­
30
8.8
Indian
Tribal
Governments
.
.
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.
8­
33
8.9
Impacts
on
Sensitive
Subpopulations
.
.
.
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.
.
.
.
8­
35
8.9.1
Protecting
Children
from
Environmental
Health
Risks
and
Safety
Risks
.
.
.
.
.
8­
36
8.10
Environmental
Justice
.
.
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.
8­
37
8.11
Federalism
.
.
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.
8­
38
8.12
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use
.
.
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.
8­
39
Chapter
9.
Comparison
of
Benefits
and
Costs
of
the
Stage
2
DBPR
9.1
Evaluation
of
National
Benefits
and
Costs
of
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
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.
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.
.
.
.
.
.
9­
1
9.1.1
National
Benefits
Summary
.
.
.
.
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.
.
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.
.
9­
1
9.1.2
National
Cost
Summary
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
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.
.
.
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.
.
.
.
.
.
.
.
9­
3
9.1.3
Comparison
of
National
Benefits
and
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
3
9.2
Effects
of
Uncertainties
on
the
Estimation
of
Net
National
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
4
9.3
Breakeven
Analysis
.
.
.
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.
.
.
.
.
9­
7
9.4
Comparison
of
Regulatory
Alternatives
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
8
9.4.1
Comparison
of
Reductions
in
DBP
Occurrence
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
8
9.4.2
Comparison
of
Benefits
and
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
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.
.
.
.
9­
9
9.4.3
Cost­
Effectiveness
.
.
.
.
.
.
.
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.
9­
11
9.5
Summary
of
Conclusions
.
.
.
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.
.
9­
15
References
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
vi
Appendices
Appendix
A:
Surface
Water
Compliance
Forecasts
Using
SWAT
Appendix
B:
Ground
Water
Plant
Compliance
Forecasts
Appendix
C:
Supplemental
Compliance
Forecasts
Appendix
D:
Rule
Activity
Schedule
Appendix
E:
Annual
Cancer
Cases
Avoided
as
a
Result
of
the
Stage
2
DBPR
Appendix
F:
Valuation
of
Stage
2
DBPR
Benefits
Appendix
G:
Illustrative
Calculation
for
Quantifying
Reproductive
and
Developmental
Benefits
of
the
Stage
2
DBPR
Appendix
H:
National
Costs
for
Non­
Treatment
Related
Rule
Activities
Appendix
I:
Cost
Implications
for
Alternative
Monitoring
Requirements
and
Alternative
Approaches
to
Implementing
the
IDSE
Appendix
J:
Unit
Costs
for
Technologies
Considered
in
the
Stage
2
DBPR
Appendix
K:
Stage
2
DBPR
Cost
Projections
Appendix
L:
Benefit
and
Cost
Models
Appendix
M:
Quality
Assurance
Supplemental
Information
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
vii
Exhibits
Exhibit
ES.
1
Summary
of
Stage
2
DBPR
Requirements
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ES­
4
Exhibit
ES.
2
Implementation
Timeline
for
the
Stage
2
DBPR
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ES­
5
Exhibit
ES.
3
Number
of
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
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ES­
7
Exhibit
ES.
4
Summary
of
Estimated
National
Benefits
and
Costs
of
the
Stage
2
DBPR
.
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ES­
9
Exhibit
ES.
5
Comparison
of
Annualized
National
Costs
and
Benefits
($
Millions)
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ES­
10
Exhibit
ES.
6
Plants
Making
Treatment
Changes
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ES­
11
Exhibit
ES.
7
Methods
Used
to
Predict
Treatment
Changes
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ES­
11
Exhibit
ES.
8
Summary
of
Annual
Household
Cost
Increases
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ES­
16
Exhibit
ES.
9a
Comparison
of
Costs
and
Benefits
for
the
Stage
2
DBPR
Regulatory
Alternatives
(
3%
Discount
Rate,
$
Million)
.
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ES­
17
Exhibit
ES.
9b
Comparison
of
Costs
and
Benefits
for
the
Stage
2
DBPR
Regulatory
Alternatives
(
7%
Discount
Rate,
$
Million)
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ES­
18
Exhibit
1.1
Summary
of
IDSE
SMP
Requirements
for
100
Percent
Purchasing
Systems1,
Population­
Based
Approach
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1­
3
Exhibit
1.2
Summary
of
IDSE
SMP
Requirements
for
Producing
Systems1,
Plant­
Based
Approach
.
.
.
.
1­
4
Exhibit
1.3
Comparison
of
Stage
1
and
Stage
2B
DBPR
Compliance
Calculations
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1­
5
Exhibit
1.4
Summary
of
Stage
2B
Monitoring
Requirements
for
100
Percent
Purchasing
Systems1,
Population­
Based
Approach
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1­
7
Exhibit
1.5
Comparison
of
Stage
1
and
Stage
2B
DBPR
Monitoring
Requirements
for
Producing
Systems1,
Plant­
Based
Approach
.
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1­
8
Exhibit
3.1
Tools
Used
to
Predict
Treatment
Changes
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3­
4
Exhibit
3.2a
SWAT
Components
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3­
5
Exhibit
3.2b
SWAT
Inputs
and
Outputs
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3­
7
Exhibit
3.3
Derivation
of
the
Stage
2
DBPR
System
Baseline
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3­
14
Exhibit
3.4
Derivation
of
the
Stage
2
DBPR
Plant
Baseline
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3­
18
Exhibit
3.5
Derivation
of
the
Stage
2
DBPR
Population
Baseline
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3­
22
Exhibit
3.6
Design
Flows
and
Average
Daily
Flows
per
Plant
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3­
25
Exhibit
3.7
Number
of
Households
Subject
to
the
Stage
2
DBPR
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3­
27
Exhibit
3.8
ICR
Large
System
Influent
Water
Quality
Parameters
 
Summary
of
Pre­
Stage
1
Plant­
Mean
Data
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3­
29
Exhibit
3.9
Cumulative
Distribution
of
TOC
in
Influent
Water
ICR
Plant­
Mean
Data
.
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3­
31
Exhibit
3.10
Cumulative
Distribution
of
Bromide
in
Influent
Water
ICR
Plant­
Mean
Data
.
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.
3­
32
Exhibit
3.11
Medium
and
Small
System
Influent
Water
Quality
Parameters
 
Summary
of
Pre­
Stage
1
Plant­
Mean
Data
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3­
33
Exhibit
3.12a
Influent
Water
TOC
Distribution
for
ICR
Surface
Water
Systems
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3­
34
Exhibit
3.12b
Influent
Water
TOC
Distribution
for
ICR
Ground
Water
Systems
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3­
34
Exhibit
3.12c
Influent
Water
TOC
Distribution
for
Ground
Water
Systems
Derived
from
the
Ground
Water
Supply
Survey
(
GWSS)
.
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3­
35
Exhibit
3.13
Comparison
of
Technologies
Considered
for
the
Stage
1
DBPR
in
the
Stage
1
DBPR
RIA
and
the
Stage
2
DBPR
EA
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3­
37
Exhibit
3.14
Aggregated
Treatment
Technology
Categories
for
Stage
1
DBPR
Used
for
the
Stage
2
DBPR
EA
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3­
38
Exhibit
3.15a
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
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3­
40
Exhibit
3.15b
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants
.
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.
3­
40
Exhibit
3.16a
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
CWS
Ground
Water
Plants
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.
3­
41
Exhibit
3.16b
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
NTNCWS
Ground
Water
Plants
.
.
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.
3­
41
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
viii
Exhibit
3.17a
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
Plants
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3­
42
Exhibit
3.17b
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants
.
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.
3­
42
Exhibit
3.18a
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Ground
Water
Plants
.
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3­
43
Exhibit
3.18b
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Ground
Water
Plants
.
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3­
43
Exhibit
3.19
Summary
of
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Large
Surface
Water
Plants,
DS
Average
Data
.
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3­
47
Exhibit
3.20a
Cumulative
Distributions
of
TTHM
Monthly
Data
Predicted
by
SWAT
(
DS
Average)
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3­
48
Exhibit
3.20b
Cumulative
Distributions
of
TTHM
Plant­
Mean
Data
Predicted
by
SWAT
(
DS
Average)
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3­
48
Exhibit
3.21a
Cumulative
Distributions
of
HAA5
Monthly
Data
Predicted
by
SWAT
(
DS
Average)
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3­
49
Exhibit
3.21b
Cumulative
Distributions
of
HAA5
Plant­
Mean
Data
Predicted
by
SWAT
(
DS
Average)
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3­
49
Exhibit
3.22a
Cumulative
Distributions
of
Bromate
Monthly
Data
Predicted
by
SWAT
(
Finished
Water)
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3­
50
Exhibit
3.22b
Cumulative
Distributions
of
Bromate
Plant­
Mean
Data
Predicted
by
SWAT
(
Finished
Water)
.
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3­
50
Exhibit
3.23a
Cumulative
Distributions
of
Chlorite
Monthly
Data
Predicted
by
SWAT
(
Finished
Water)
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3­
51
Exhibit
3.23b
Cumulative
Distributions
of
Chlorite
Plant­
Mean
Data
Predicted
by
SWAT
(
Finished
Water)
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3­
51
Exhibit
3.24
Summary
of
Pre­
Stage
1
DBP
Occurrence
for
Large
Ground
Water
Plants,
ICR
Data
.
.
.
3­
52
Exhibit
3.25
Summary
of
Pre­
Stage
1
DBP
Occurrence
Data
for
Small
Systems,
DS
Average
Data
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3­
54
Exhibit
3.26
Summary
of
Uncertainties
Affecting
Stage
2
DBPR
Baseline
Estimates
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3­
55
Exhibit
4.1
Comparison
of
Compliance
Calculations
for
Regulatory
Alternatives
.
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4­
6
Exhibit
5.1
Summary
of
Quantified
Benefits
for
the
Stage
2
DBPR
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5­
5
Exhibit
5.2
Odds
Ratios
(
and
95%
Confidence
Intervals
1)
Calculated
by
Reif
et
al.
(
2000)
for
Reproductive
and
Developmental
Health
Endpoints
at
TTHM
Levels
of
>
80
µ
g/
L
versus
<
80
µ
g/
L
and
>
60
µ
g/
L
versus
<
60
µ
g/
L
.
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5­
12
Exhibit
5.3
PAR
Values
(
and
95%
Confidence
Intervals
1
)
Calculated
by
Reif
et
al.
(
2000)
for
Reproductive
and
Developmental
Health
Endpoints
at
TTHM
Levels
of
>
80
µ
g/
L
versus
<
80
µ
g/
L
and
>
60
µ
g/
L
versus
<
60
µ
g/
L
(
Values
are
Percentages)
.
.
.
.
.
.
.
5­
13
Exhibit
5.4
Availability
of
Reproductive
and
Developmental
Toxicology
Studies
for
Specific
DBPs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
16
Exhibit
5.5
Reproductive
and
Developmental
Health
Effects
Associated
with
DBPs
in
Toxicological
Studies
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
17
Exhibit
5.6
Summary
of
Epidemiology
Studies
for
Bladder
Cancer
Associated
with
Chlorinated
Drinking
Water
and
EPA
Calculated
PAR
Values
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
22
Exhibit
5.7
Summary
of
EPA's
Cancer
Risk
Assessments
for
Specific
DBPs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
26
Exhibit
5.8
Quantification
of
Cancer
Risk,
Pre­
Stage
2
Baseline
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
27
Exhibit
5.9
Estimated
Population
Exposed
to
DBPs
in
Drinking
Water
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
30
Exhibit
5.10
Number
of
Plants,
Locations,
and
TTHM/
HAA5
Observations
In
Each
Data
Set
.
.
.
.
.
.
.
5­
34
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
ix
Exhibit
5.11
Comparison
of
TTHM
and
HAA5
Concentrations
Calculated
as
RAAs
and
Maximum
LRAAs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
37
Exhibit
5.12a
Distribution
of
TTHM
Observations
for
Different
Subsets
of
ICR
Plants
.
.
.
.
.
.
.
.
.
.
.
.
5­
39
Exhibit
5.12b
Distribution
of
HAA5
Observations
for
Different
Subsets
of
ICR
Plants
.
.
.
.
.
.
.
.
.
.
.
.
5­
40
Exhibit
5.13
Percent
Reduction
in
Locations
with
Peaks
from
the
Stage
1
to
the
Stage
2
DBPR
.
.
.
.
.
.
5­
43
Exhibit
5.14
Operational
Changes
Predicted
by
SWAT
for
the
Stage
1
DBPR
and
Stage
2
DBPR,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
45
Exhibit
5.15a
TTHM
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
46
Exhibit
5.15b
TTHM
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
46
Exhibit
5.16a
HAA5
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
47
Exhibit
5.16b
HAA5
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
47
Exhibit
5.17a
Reduction
in
Average
TTHM
and
HAA5
Concentrations
from
Pre­
Stage
1
to
Pre­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
48
Exhibit
5.17b
Reduction
in
Average
TTHM
and
HAA5
Concentrations
from
Pre­
Stage
2
to
Post­
Stage
2,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
48
Exhibit
5.18
Steady­
State
Cancer
Cases
Remaining
after
Stage
1
and
Avoided
by
Stage
2
(
Total
Estimated
Cases)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
52
Exhibit
5.19
Cases
Avoided
Under
2
Percent
PAR:
Steady­
State
and
with
Cessation
Lag
(
TTHM
as
Indicator)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
57
Exhibit
5.20
Cases
Avoided
Under
17
Percent
PAR:
Steady­
State
and
with
Cessation
Lag
(
TTHM
as
Indicator)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
58
Exhibit
5.21
Estimated
Cancer
Cases
Avoided
by
Year
All
Water
Systems,
TTHM
as
Indicator
.
.
.
.
.
.
5­
59
Exhibit
5.22a
Chlorite
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
62
Exhibit
5.22b
Chlorite
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
62
Exhibit
5.23a
Bromate
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
63
Exhibit
5.23b
Bromate
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
63
Exhibit
5.24
VSL,
WTP,
and
Morbidity
Increment
Price
Level
Updates
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
67
Exhibit
5.25
Value
of
Morbidity
Increment,
VSL,
and
WTP
by
Year
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
69
Exhibit
5.26
Non­
discounted
Stream
of
Benefits
from
the
Stage
2
DBPR
Preferred
Regulatory
Alternative,
All
Systems,
TTHM
as
Indicator
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
71
Exhibit
5.27
Benefits
Summary
for
the
Stage
2
DBPR,
Preferred
Regulatory
Alternative
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
75
Exhibit
5.28
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
All
Stage
2
DBPR
Regulatory
Alternatives
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
77
Exhibit
5.29
Uncertainties
and
Possible
Effect
on
Estimate
of
Benefits
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
79
Exhibit
5.30
Comparison
of
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
Stage
2
DBPR
Sensitivity
Analysis
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
.
5­
80
Exhibit
5.31
Summary
of
the
Fetal
Loss
Human
Epidemiology
Studies
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
5­
82
Exhibit
6.1
Stage
2
DBPR
Cost
Model
Components
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
3
Exhibit
6.2
Household
Cost
Inputs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
7
Exhibit
6.3
Number
of
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
9
Exhibit
6.4
Number
and
Percent
of
Plants
Adding
Treatment
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
11
Exhibit
6.5
Initial
Capital
and
One­
Time
Costs
for
the
Stage
2
DBPR
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
12
Exhibit
6.6a
Total
Annualized
Costs
for
Stage
2
DBPR
Rule
Activities
($
Millions/
Year,
3
Percent
Discount
Rate)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
14
Exhibit
6.6b
Total
Annualized
Costs
for
Stage
2
DBPR
Rule
Activities
($
Millions/
Year,
7
Percent
Discount
Rate)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
15
Exhibit
6.7
Summary
of
System
Costs
for
Non­
Treatment
Related
Stage
2
DBPR
Rule
Activities
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
x
(
One­
Time
and
Steady­
State)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
20
Exhibit
6.8a
Treatment
Technologies
for
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
24
Exhibit
6.8b
Treatment
Technologies
for
Disinfecting
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
25
Exhibit
6.9a
Capital
Costs
($/
Plant)
for
CWS
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
26
Exhibit
6.9b
Annual
O&
M
Costs
($/
Plant/
Year)
for
CWS
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
26
Exhibit
6.9c
Household
Unit
Costs
($/
Household/
Year)
for
CWS
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
6­
27
Exhibit
6.10a
Capital
Cost
($/
Plant/
Year)
forCWS
Disinfecting
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
28
Exhibit
6.10b
Annual
O&
M
Costs
($/
Plant/
Year)
for
CWS
Disinfecting
Ground
Water
Plants
.
.
.
.
.
.
.
6­
28
Exhibit
6.10c
Household
Unit
Costs
($/
Household/
Year)
for
CWS
Disinfecting
Ground
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
29
Exhibit
6.11
Tools
Used
to
Develop
the
Stage
2
DBPR
Compliance
Forecasts
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
31
Exhibit
6.12
Stage
2
DBPR
Compliance
Forecast
Summary
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
32
Exhibit
6.13
Interpretation
of
Technology
Selection
Forecasts
for
Surface
Water
Plants
.
.
.
.
.
.
.
.
.
.
.
6­
34
Exhibit
6.14a
Technology
Selection
Deltas
for
CWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
35
Exhibit
6.14b
Technology
Selection
Deltas
for
NTNCWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
35
Exhibit
6.15a
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
36
Exhibit
6.15b
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
6­
36
Exhibit
6.16a
Technology
Selection
Deltas
for
CWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
6­
38
Exhibit
6.16b
Technology
Selection
Deltas
for
NTNCWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
38
Exhibit
6.17a
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
39
Exhibit
6.17b
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
39
Exhibit
6.18
Total
Initial
Capital
Costs
($
Millions)
and
Steady­
State
O&
M
Costs
($
Millions/
Year)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
40
Exhibit
6.19a
Total
Annualized
Costs
at
3
Percent
Social
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
42
Exhibit
6.19b
Total
Annualized
Costs
at
7
Percent
Social
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
43
Exhibit
6.20
Annual
Household
Cost
Increases
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
45
Exhibit
6.21a
Household
Cost
Distributions,
All
Surface
Water
Systems
Subject
to
the
Rule
.
.
.
.
.
.
.
.
6­
46
Exhibit
6.21b
Household
Cost
Distributions,
All
Ground
Water
Systems
Subject
to
the
Rule
.
.
.
.
.
.
.
.
6­
47
Exhibit
6.22a
Household
Cost
Distributions,
Surface
Water
Systems
Adding
Treatment
.
.
.
.
.
.
.
.
.
.
.
6­
48
Exhibit
6.22b
Household
Cost
Distributions,
Ground
Water
Systems
Adding
Treatment
.
.
.
.
.
.
.
.
.
.
.
6­
49
Exhibit
6.22c
Household
Cost
Distributions,
Small
Systems
Adding
Treatment
(
Surface
and
Ground)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
50
Exhibit
6.23
Cost
Uncertainty
Summary
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
6­
52
Exhibit
6.24
Total
Annualized
Cost
for
the
Stage
2
DBPR
Regulatory
Alternatives
($
Millions)
.
.
.
.
.
.
.
6­
53
Exhibit
7.1
Total
Percent
Adding
Treatment
from
Stage
1
to
Stage
2
for
IDSE
No.
1
and
IDSE
No.
2
(
CWSs)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
3
Exhibit
7.2
Comparison
of
Estimated
Annual
Cases
and
Annualized
Benefits
for
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
7­
4
Exhibit
7.3
Comparison
of
the
Total
Initial
Capital
Costs
for
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
5
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xi
Exhibit
7.4a
Comparison
of
Annualized
Costs
for
the
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative,
3
Percent
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
6
Exhibit
7.4b
Comparison
of
Annualized
Costs
for
the
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative,
7
Percent
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
7
Exhibit
7.5
Comparison
of
Estimated
Annual
Cases
and
Annualized
Benefits
for
Minimal
Impact
Sensitivity
Analysis
and
the
Preferred
Alternative
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
7­
9
Exhibit
7.6
Comparison
of
Initial
Capital
Costs
for
the
Minimal
Impact
Sensitivity
Analysis
and
the
Preferred
Alternative
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
10
Exhibit
7.7a
Comparison
of
Annualized
Costs
for
the
Minimal
Impact
Sensitivity
Analyses
and
the
Preferred
Alternative,
3
Percent
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
11
Exhibit
7.7b
Comparison
of
Annualized
Costs
for
the
Minimal
Impact
Sensitivity
Analyses
and
the
Preferred
Alternative,
7
Percent
Discount
Rate
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
7­
12
Exhibit
8.1a
Annualized
Compliance
Cost
as
a
Percentage
of
Revenues
for
All
Small
Entities
Using
Surface
Water
and
GWUDI
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
4
Exhibit
8.1b
Annualized
Compliance
Cost
as
a
Percentage
of
Revenues
for
All
Small
Entities
Using
Ground
Water
Only
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
5
Exhibit
8.2
Derivation
of
Available
Expenditure
Margin
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
10
Exhibit
8.3
Affordability
Analysis
Inputs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
11
Exhibit
8.4a
Affordable
Compliance
Technologies
and
Household
Unit
Treatment
Costs
($/
HH/
Year)
for
Surface
Water
Systems
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
13
Exhibit
8.4b
Affordable
Compliance
Technologies
and
Household
Unit
Treatment
Costs
($/
HH/
Year)
for
Ground
Water
Systems
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
13
Exhibit
8.5
SWAT
Model
Predictions
of
Percent
of
Large
Plants
in
Compliance
with
TTHM
and
HAA5
Stage
2B
MCLs
after
Application
of
Specified
Treatment
Technologies
.
.
.
.
8­
17
Exhibit
8.6
Estimated
Impact
of
the
Stage
2
DBPR
on
Small
System
Capacity
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
21
Exhibit
8.7
Estimated
Impact
of
the
Stage
2
DBPR
on
Large
System
Capacity
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
22
Exhibit
8.8
Impact
of
the
Stage
2
DBPR
on
CWS
and
NTNCWS
Capacity
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
23
Exhibit
8.9
Summary
of
Average
Annual
Burden
Hours
and
Labor
Costs
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
29
Exhibit
8.10
Public
and
Private
Costs
for
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
30
Exhibit
8.11a
Annualized
Cost
of
Compliance
for
CWSs
(
3
and
7
Percent
Discount
Rates)
.
.
.
.
.
.
.
.
.
8­
33
Exhibit
8.11b
Annualized
Cost
of
Compliance
for
NTNCWSs
(
3
and
7
Percent
Discount
Rates)
.
.
.
.
.
8­
33
Exhibit
8.12
Annual
Cost
of
Compliance
for
Tribal
Systems
by
System
Type
and
Size
(
Annualized
at
3
Percent)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
35
Exhibit
8.13
Increase
in
Energy
Usage
as
a
Result
of
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
8­
41
Exhibit
8.14
Sample
Calculation
for
Determining
Increase
in
Energy
Usage:
Chloramines
.
.
.
.
.
.
.
.
.
.
8­
42
Exhibit
9.1
Summary
of
Estimated
National
Benefits
of
the
Stage
2
DBPR
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
2
Exhibit
9.2
Summary
of
Nominal
Benefit
and
Cost
Estimates
by
Year
Incurred,
Preferred
Alternative
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
3
Exhibit
9.3
Estimated
Annualized
National
Costs
and
Benefits
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
4
Exhibit
9.4
Effects
of
Uncertainties
on
National
Estimates
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
5
Exhibit
9.5
IDSE
Sensitivity
Cost
Range
Comparison
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
6
Exhibit
9.6
IDSE
Sensitivity
Benefit
Range
Comparison
($
Millions)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
6
Exhibit
9.7
Estimated
Breakeven
Points
(
Number
of
Bladder
Cancer
Cases
Avoided)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
7
Exhibit
9.8
Comparison
of
DBP
Reduction
(
of
Annual
Plant
Mean
TTHM
Data)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
9
Exhibit
9.9
Comparison
of
Annualized
Costs
for
Regulatory
Alternatives
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
9
Exhibit
9.10
Comparison
of
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
Regulatory
Alternatives
(
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
10
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xii
Exhibit
9.11
Comparison
of
Annualized
Costs
and
Benefits
for
the
Stage
2
Regulatory
Alternatives
(
3
%
Discount
Rate)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
12
Exhibit
9.12
Comparison
of
Estimated
Cost
Per
Case
Avoided
for
the
Regulatory
Alternatives
($
Millions,
2000$)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9­
14
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xii
Acronyms
and
Notations
AAM
Annual
Average
of
the
Maximum
AIPC
All
Indian
Pueblo
Council
AMWA
Association
of
Metropolitan
Water
Agencies
ARBRP
Arsenic
Rule
Benefits
Review
Panel
ASDWA
Association
of
State
Drinking
Water
Administrators
AD
Advanced
Disinfectants
AO
Advanced
Oxidants
AUX1
Auxiliary
Database
1
AUX8
Auxiliary
Database
8
AVG
1
Average
sample
point
number
1
AVG
2
Average
sample
point
number
2
AWWA
American
Water
Works
Association
BAT
Best
Available
Technology
BCAA
Bromochloroacetic
Acid
BCAN
Bromochloroacetonitrile
BDCAA
Bromodichloroacetic
Acid
BDCM
Bromodichloromethane
BLS
Bureau
of
Labor
Statistics
CCR
Consumer
Confidence
Report
Rule
(
1998)
CDC
Centers
for
Disease
Control
and
Prevention
CDHS
California
Department
of
Health
Services
CI
Confidence
Interval
CKA
Chernoff­
Kavlock
Assay
CL2
Chlorine
CLM
Chloramines
CLO2
Chlorine
Dioxide
COI
Cost
of
Illness
CPI
Consumer
Price
Index
CWS
Community
Water
System
CWSS
Community
Water
Systems
Survey
DBAA
Dibromoacetic
Acid
DBAN
Dibromoacetonitrile
DBCM
Dibromochloromethane
DBPR
Disinfectants
and
Disinfection
Byproducts
Rule
DBP
Disinfection
Byproduct
DCAA
Dichloroacetic
Acid
DCAN
Dichloroacetonitrile
DNA
Deoxyribonucleic
Acid
DS
Average
Distribution
System
Average
Sample
Point
DSE
Distribution
System
Equivalent
Sample
Point
DS
Maximum
Distribution
System
Maximum
Sample
Point
DWSRF
Drinking
Water
State
Revolving
Fund
EA
Economic
Analysis
EBCT
Empty
Bed
Contact
Time
EC
Enhanced
Coagulation
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xiii
ECI
Employment
Cost
Index
Information
ED
10
Effective
Dose
for
10%
response
EPA
Environmental
Protection
Agency
FACA
Federal
Advisory
Committees
Act
FBRR
Filter
Backwash
Recycling
Rule
(
2001)
FLR
Full
Liter
Resorption
FR
Federal
Register
FRFA
Final
Regulatory
Flexibility
Analysis
FTE
Full­
Time
Equivalent
GAC
Granular
Activated
Carbon
GAC10
Granular
Activated
Carbon
 
10­
Minute
Contact
Time
GAC20
Granular
Activated
Carbon
 
20­
Minute
Contact
Time
GDP
Gross
Domestic
Product
GIS
Geographical
Information
System
GW
Ground
Water
GWSS
Ground
Water
Supply
Survey
GWUDI
Ground
Water
Under
the
Direct
Influence
of
Surface
Water
HAA5
Haloacetic
Acids
[
total
of
five]
HAA6
Haloacetic
Acids
[
total
of
six]
HAA9
Haloacetic
Acids
[
total
of
nine]
HAN
Haloacetonitrile
ICMA
International
City/
County
Management
Association
ICR
Information
Collection
Rule
(
1996)
ILSI
International
Life
Sciences
Institute
IDSE
Initial
Distribution
System
Evaluation
IDSE
SMP
Initial
Distribution
System
Evaluation
Standard
Monitoring
Program
IESWTR
Interim
Enhanced
Surface
Water
Treatment
Rule
(
1998)
IPCS
International
Programme
on
Chemical
Safety
IRFA
Initial
Regulatory
Flexibility
Analysis
IRIS
Integrated
Risk
Information
System
LED
10
Lower
Bound
on
the
Effective
Dose
for
10%
response
LH
Luteinizing
Hormone
LOAEL
Lowest­
Observed­
Adverse­
Effect­
Level
LRAA
Locational
Running
Annual
Average
LT1ESWTR
Long
Term
1
Enhanced
Surface
Water
Treatment
Rule
(
2002)
LT2ESWTR
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
under
development)
MBAA
Monobromoacetic
Acid
MCAA
Monochloroacetic
Acid
MCAN
Monochloroacetonitrile
MCL
Maximum
Contaminant
Level
MCLG
Maximum
Contaminant
Level
Goal
M­
DBP
Microbial­
Disinfectants/
Disinfection
Byproducts
[
Advisory
Committee]
MF
Microfiltration
MGD
Million
Gallons
per
Day
:
g/
L
Micrograms
per
Liter
mg/
L
Milligrams
per
Liter
MHI
Median
Household
Income
mJ/
cm2
Millijoules
per
centimeter
square
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xiv
MLE
Maximum
Likelihood
Estimation
MRDL
Maximum
Residual
Disinfectant
Level
MRDLG
Maximum
Residual
Disinfectant
Level
Goal
mWh
Megawatt
Hours
MX
3­
Chloro­
4­(
dichloromethyl)­
5­
hydroxy­
2(
5H)­
furanone
NCSL
National
Conference
of
State
Legislatures
NCWS
Noncommunity
Water
System
NDMA
N­
nitrosodimethylamine
NDWAC
National
Drinking
Water
Advisory
Council
NF
Nanofiltration
ng
Nanograms
NGA
National
Governors'
Association
NHEERL
National
Health
and
Environmental
Effects
Research
Laboratory
(
EPA)
NLC
National
League
of
Cities
NOAEL
No­
Observed­
Adverse­
Effect­
Level
NODA
Notice
of
Data
Availability
NPDWR
National
Primary
Drinking
Water
Regulations
NRWA
National
Rural
Water
Association
NTNCWS
Nontransient
Noncommunity
Water
System
NTU
Nephelometric
Turbidity
Unit
O
3
Ozone
OR
Odds
Ratio
OMB
Office
of
Management
and
Budget
O&
M
Operations
and
Maintenance
PAR
Population
Attributable
Risk
POE
Point­
of­
Entry
POU
Point­
of­
Use
ppb
Parts
per
Billion
ppm
Parts
per
Million
PUC
Public
Utilities
Commission
PSC
Public
Services
Commission
PV
Present
Value
PWS
Public
Water
System
PWSID
Public
Water
System
Identification
RAA
Running
Annual
Average
RFA
Regulatory
Flexibility
Act
RfD
Reference
Dose
RIA
Regulatory
Impact
Analysis
RR
Relative
Risk
RSI
Risk
Sciences
Institute
SAB
Science
Advisory
Board
SBA
Small
Business
Administration
SBAR
Small
Business
Advocacy
Review
SBREFA
Small
Business
Regulatory
Enforcement
Fairness
Act
SCADA
Supervisory
Control
and
Data
Acquisition
SD
Sprague­
Dawley
SDS
Simulated
Distribution
System
SDWA
Safe
Drinking
Water
Act
(
1974)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
xv
SDWIS
Safe
Drinking
Water
Information
System
SER
Small
Entity
Representatives
SH
Single
Highest
SIC
Standard
Industrial
Codes
SMP
Standard
Monitoring
Program
SSS
System­
Specific
Study
SW
Surface
Water
SWAT
Surface
Water
Analytical
Tool
Stage
1
DBPR
Stage
1
Disinfectants
and
Disinfection
Byproducts
Rule
(
1998)
Stage
2
DBPR
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
under
development)
SWTR
Surface
Water
Treatment
Rule
(
1989)
TBAA
Tribromoacetic
Acid
TCAA
Trichloroacetic
Acid
TCAN
Trichloroacetonitrile
TCR
Total
Coliform
Rule
(
1989)
THM
Trihalomethane
TMF
Technical,
Managerial,
and
Financial
TNCWS
Transient
Noncommunity
Water
System
TOC
Total
Organic
Carbon
TOX
Total
Organic
Halides
TTHM
Total
Trihalomethanes
TWG
Technical
Workgroup
T&
C
Technology
and
Cost
UF
Ultrafiltration
UMRA
Unfunded
Mandates
Reform
Act
USC
United
States
Code
USDA
United
States
Department
of
Agriculture
USEPA
United
States
Environmental
Protection
Agency
UV
Ultraviolet
[
Light
Disinfection]
µ
g/
L
Micrograms
per
Liter
VSL
Value
of
a
Statistical
Life
WEC
Whole
embryo
culture
WHO
World
Health
Organization
w(
t)
cessation
lag
weighting
factor
WTP
Willingness
to
Pay
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
xvi
July
2003
Health
Risk
Reduction
and
Cost
Analysis
(
HRRCA)

Under
the
Safe
Drinking
Water
Act
(
SDWA)
Amendments
of
1996,
when
proposing
a
national
primary
drinking
water
regulation
that
includes
an
maximum
contaminant
level
(
MCL),
the
Environmental
Protection
Agency
(
EPA)
must
conduct
a
health
risk
reduction
and
cost
analysis
(
HRRCA).
A
HRRCA
contains
seven
requirements,
all
of
which
are
addressed
in
this
Economic
Analysis
(
EA)
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
The
table
below
shows
where
the
HRRCA
requirements
are
discussed
in
this
document.

HRRCA
Crosswalk
to
the
Economic
Analysis
for
the
Stage
2
DBPR
HRRCA
Requirement
Addressed
in
Economic
Analysis
Quantifiable
and
nonquantifiable
health
risk
reduction
benefits
Chapter
5
(
Sections
5.5
and
5.6;
Exhibits
5.18­
5.28)
Chapter
9
(
Sections
9.1.1,
9.1.3,
and
9.4.2;
Exhibits
9.1­
9.3,
9.10,
and
9.12)

Quantifiable
and
nonquantifiable
health
risk
reduction
benefits
from
co­
occurring
contaminants
Chapter
5
(
Section
5.5.3)

Quantifiable
and
nonquantifiable
costs
Chapter
6
(
All
sections
and
exhibits)
Chapter
8
(
Sections
8.2,
8.3,
and
8.6­
8.8;
Exhibits
8.1,
8.2,
8.4,
and
8.9­
8.12)
Chapter
9
(
Sections
9.1.2
and
9.1.3,
9.4.2;
Exhibits
9.2­
9.3
and
9.9)

Incremental
costs
and
benefits
associated
with
MCL
alternatives
Chapter
5
(
Section
5.6.4;
Exhibit
5.28)
Chapter
6
(
Section
6.9;
Exhibit
6.24)
Chapter
9
(
Section
9.4;
Exhibits
9.9­
9.11)

Effects
of
the
contaminants
on
the
general
population
and
sensitive
subpopulations
Chapter
5
(
Sections
5.2
and
5.3.3;
Exhibits
5.2­
5.8)
Chapter
8
(
Sections
8.8,
8.9,
and
8.10)

Increased
health
risk
that
may
occur
as
a
result
of
compliance
Chapter
5
(
Section
5.5.5)

Other
relevant
factors
(
quality
and
uncertainty
of
information)
Chapter
3
(
Section
3.8;
Exhibit
3.26)
Chapter
5
(
Section
5.7;
Exhibit
5.29)
Chapter
6
(
Section
6.8;
Exhibit
6.23)
Chapter
7
(
All
sections
and
exhibits)
Chapter
9
(
Section
9.2;
Exhibits
9.4­
9.6)
1The
key
outcomes
of
this
regulatory
negotiation
effort
were
recommendations
to
proceed
with
rules
addressing
DBPs
and
microbial
pathogens
in
two
stages
and
to
collect
relevant
information
from
public
water
supplies
for
use
in
the
development
of
these
rules
and
the
analysis
of
their
impacts.
This
two­
stage
approach
was
subsequently
incorporated
into
the
1996
Safe
Drinking
Water
Act
(
SDWA)
Amendments.
The
first
stage
of
the
M­
DBP
rulemaking
process
culminated
with
the
joint
promulgation
of
the
Stage
1
DBPR
and
the
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IESWTR)
by
EPA
in
December
1998.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
1
July
2003
Executive
Summary
This
document
presents
the
Economic
Analysis
(
EA),
prepared
by
the
Environmental
Protection
Agency
(
EPA),
of
the
benefits
and
costs
of
the
proposed
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
Executive
Order
12866
requires
federal
agencies
to
conduct
an
analysis
of
the
benefits
and
costs
of
proposed
and
final
rules
that
cost
over
$
100
million
annually.
Although
EPA's
analysis
of
the
Stage
2
DBPR
has
determined
that
its
annual
costs
are
less
than
this
threshold,
EPA
has
chosen
to
publish
a
complete
EA
for
this
rule.

ES.
1
Need
for
the
Rule
Over
51,600
public
water
systems
(
PWSs),
serving
nearly
260
million
people
in
the
United
States,
chemically
disinfect
their
water
to
kill
or
inactivate
microbial
contaminants
(
USEPA
2001h).
Chemical
disinfection,
however,
may
pose
health
risks
of
its
own.
Disinfection
byproducts
(
DBPs)
result
from
reactions
between
chemical
disinfectants
and
naturally
occurring
compounds
in
source
waters.
Research
has
shown
that
some
of
the
DBPs,
including
total
trihalomethanes
(
TTHM)
and
haloacetic
acids
(
HAA5),
which
are
the
subject
of
this
rule,
are
associated
with
increased
risk
of
bladder
and
other
cancers.
While
there
are
uncertainties
in
the
quantitative
relationship
between
the
incidence
of
these
cancers
and
the
occurrence
of
DBPs
in
drinking
water,
EPA
believes
that
the
weight
of
evidence
supports
concern
for
these
potential
hazards
and
that
additional
reductions
in
DBP
levels
in
drinking
water
will
reduce
the
incidence
of
bladder
cancer
and,
possibly,
other
cancers.

In
addition,
results
from
toxicology
and,
particularly,
epidemiology
studies
published
in
the
last
several
years
suggest
an
increased
risk
for
pregnant
women
and
their
fetuses
who
are
exposed
to
DBPs
in
drinking
water.
The
studies
have
shown
that
early­
term
miscarriage,
stillbirth,
low
birth
weight,
and
some
birth
defects
may
be
associated
with
drinking
water
containing
DBPs.
(
These
studies
are
discussed
in
detail
in
Chapter
5.)
There
are
still
uncertainties
regarding
which
DBPs
are
of
greatest
concern,
what
levels
of
DBPs
pose
a
risk,
and
at
what
period
of
development
fetuses
may
be
at
the
greatest
risk.
While
the
levels
of
DBPs
associated
with
specific
potential
adverse
reproductive
and
developmental
effects
are
not
known,
EPA
believes
the
evidence
supports
concern
for
these
potential
hazards
and
warrants
regulatory
action.

In
a
separate
but
concurrent
action,
EPA
is
proposing
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR)
to
improve
control
of
microbial
contaminants,
particularly
Cryptosporidium,
in
surface
water
and
to
ensure
that
microbial
protection
is
not
compromised
by
efforts
to
reduce
exposure
to
DBPs.
The
Stage
2
DBPR
and
LT2ESWTR
represent
the
final
stage
of
a
twostage
strategy
that
was
developed
in
a
regulatory
negotiation
effort
in
1992
and
19931
and
reflect
recommendations
presented
by
the
Stage
2
Microbial
and
Disinfection
Byproducts
(
M­
DBP)
Federal
Advisory
Committee
Agreement
in
Principle,
signed
in
September
2000
(
USEPA
2000n).
2
For
the
purposes
of
this
EA,
"
surface
water"
is
equivalent
to
the
definition
of
subpart
H
systems
used
in
the
Stage
2
DBPR
rule
language
and
includes
systems
that
provide
ground
water
under
the
direct
influence
of
surface
water
(
GWUDI).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
2
July
2003
ES.
2
Consideration
of
Regulatory
Alternatives
The
M­
DBP
Advisory
Committee
met
from
March
1999
to
December
2000
to
evaluate
whether
and
to
what
degree
EPA
should
promulgate
revised
or
additional
DBP
standards
to
protect
public
health.
The
committee
focused
on
developing
a
regulatory
framework
that
would
reduce
peak
DBP
concentrations
in
the
distribution
systems
without
exorbitant
costs,
and
thus,
evaluated
regulatory
options
that
either
lowered
DBP
maximum
contaminant
levels
(
MCLs),
revised
the
method
for
compliance
determination,
or
both.
After
extensive
deliberations,
the
committee
recommended
revising
the
compliance
monitoring
scheme
from
that
established
in
the
Stage
1
DBPR,
while
maintaining
the
same
numerical
DBP
MCL
values
to
determine
compliance.
The
Stage
1
DBPR
uses
the
running
annual
average
(
RAA)
of
distribution
system
samples
for
compliance
determination,
consistent
with
the
1979
TTHM
standards.
While
this
approach
reduces
average
exposure
to
DBPs,
samples
from
some
locations
in
the
distribution
system
could
have
considerably
higher
DBPs
than
the
system­
wide
average
used
for
compliance
determination.
The
Stage
2
DBPR
focuses
on
reducing
the
occurrence
of
peak
DBP
levels
whenever
they
occur
in
the
system,
by
requiring
compliance
to
be
determined
using
a
locational
running
annual
average
(
LRAA)
calculation.
The
M­
DBP
Agreement
in
Principle
(
available
on
the
web
at
http://
www.
epa.
gov/
safewater/
mdbp/
st2fr29.
html)
summarizes
the
recommendations
from
the
advisory
committee
(
USEPA
2000p).

This
EA
considers
four
regulatory
alternatives
derived
from
a
larger
number
discussed
by
the
MDBP
Advisory
Committee,
including
the
Preferred
Alternative
that
EPA
is
proposing
in
the
Stage
2
DBPR:

°
Preferred
Alternative:
MCLs
of
80
micrograms
per
liter
(
:
g/
L)
for
TTHM
and
60
:
g/
L
for
HAA5,
measured
as
an
LRAA.
MCL
of
10
:
g/
L
for
bromate.

°
Alternative
1:
MCLs
of
80
:
g/
L
for
TTHM
and
60
:
g/
L
for
HAA5,
measured
as
an
LRAA.
MCL
of
5
:
g/
L
for
bromate.

°
Alternative
2:
MCLs
of
80
:
g/
L
for
TTHM
and
60
:
g/
L
for
HAA5,
measured
as
a
single
highest
(
SH)
value.
MCL
of
10
:
g/
L
for
bromate.

°
Alternative
3:
MCLs
of
40
:
g/
L
for
TTHM
and
30
:
g/
L
for
HAA5,
measured
as
an
RAA.
MCL
of
10
:
g/
L
for
bromate.

For
comparison
with
the
Preferred
Alternative,
EPA
carried
Alternatives
1,
2,
and
3
through
the
full
analytical
process
in
this
document.

ES.
3
Summary
of
the
Proposed
Stage
2
DBPR
The
requirements
of
the
Stage
2
DBPR
apply
to
all
community
water
systems
(
CWSs)
and
nontransient
noncommunity
water
systems
(
NTNCWSs)
 
both
ground
and
surface
water
systems2
 
that
add
a
disinfectant
other
than
ultraviolet
light
(
UV),
or
that
deliver
water
that
has
been
treated
with
a
disinfectant
other
than
UV.
Each
Stage
2
DBPR
rule
activity
for
the
Preferred
Regulatory
Alternative
is
described
below
and
illustrated
in
the
flow
chart
in
Exhibit
ES.
1.
3
EPA
is
considering
an
alternative
schedule
for
IDSE
(
starting
2
years
later
for
all
systems)
and
an
alternative
to
the
IDSE
whereby
it
is
replaced
with
increased
monitoring
during
the
first
year
to
reduce
the
burden
on
systems
and
EPA
regions
and
increase
the
technical
involvement
of
the
States.
A
more
detailed
description
of
these
alternatives
and
estimated
costs
implications
are
in
Appendix
I.

4
A
"
consecutive
system"
is
a
PWS
that
buys
or
otherwise
receives
some
or
all
of
its
finished
water
from
one
or
more
wholesale
systems,
for
at
least
60
days
per
year.
For
the
purposes
of
this
EA,
"
100
percent
purchasing
systems"
are
consecutive
systems
that
buy
(
or
otherwise
receive)
all
of
their
finished
water
from
one
or
more
systems
year
round.
"
Producing
systems"
are
those
that
do
not
purchase
100
percent
of
their
water
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
3
July
2003
Initial
Distribution
System
Evaluations
The
Stage
2
DBPR
is
designed
to
reduce
DBP
occurrence
peaks
in
the
distribution
system
by
changing
compliance
monitoring
requirements.
Compliance
monitoring
will
be
preceded
by
an
initial
distribution
system
evaluation
(
IDSE)
to
identify
compliance
monitoring
locations
that
represent
high
TTHM
and
HAA5
levels.
The
IDSE
consists
of
either
a
standard
monitoring
program
(
SMP)
or
a
system­
specific
study
(
SSS).
NTNCWSs
serving
fewer
than
10,000
people
are
not
required
to
perform
an
IDSE,
and
other
systems
may
receive
waivers
from
the
IDSE
requirement.

Compliance
with
Stage
2
DBPR
MCLs
The
Stage
2
DBPR
changes
the
way
sampling
results
are
averaged
to
determine
compliance.
The
determination
for
the
Stage
2
DBPR
is
based
on
an
LRAA
(
i.
e.,
compliance
must
be
met
at
each
monitoring
location)
instead
of
the
system­
wide
RAA
used
under
the
Stage
1
DBPR.

The
Stage
2
DBPR
will
be
implemented
in
two
phases,
Stage
2A
and
Stage
2B.
Under
Stage
2A,
all
systems
must
comply
with
TTHM/
HAA5
MCLs
of
120/
100
:
g/
L
measured
as
LRAAs
at
each
Stage
1
DBPR
monitoring
site,
while
continuing
to
comply
with
the
Stage
1
DBPR
MCLs
of
80/
60
:
g/
L
measured
as
RAAs.
Under
Stage
2B,
systems
must
comply
with
TTHM/
HAA5
MCLs
of
80/
60
:
g/
L
at
locations
identified
under
the
IDSE.
Exhibit
ES.
2
shows
the
compliance
schedule
for
Stage
2A
and
2B
for
different
types
of
systems3.

Routine
Monitoring
Requirements
Systems
will
continue
to
monitor
at
their
Stage
1
DBPR
compliance
monitoring
locations
for
the
Stage
2A
DBPR.
Stage
2B
compliance
monitoring
requirements
will
be
similar
to
the
Stage
1
DBPR
requirements
for
most,
but
not
all,
systems.
Some
small
systems
will
have
to
add
a
monitoring
location
if
their
highest
TTHM
and
highest
HAA5
sites
do
not
occur
at
the
same
location.
For
consecutive
systems
that
buy
all
of
their
water4,
monitoring
requirements
will
be
based
on
population
served
rather
than
on
the
number
of
plants;
therefore,
the
number
of
sampling
sites
for
routine
monitoring
could
either
increase
or
decrease
from
the
Stage
1
to
the
Stage
2
DBPR.

Significant
Excursion
Evaluations
Because
Stage
2
DBPR
MCL
compliance
is
based
on
an
annual
average
of
DBP
measurements,
a
system
could
from
time
to
time
have
DBP
levels
significantly
higher
than
the
MCL
(
referred
to
as
a
significant
excursion)
while
still
being
in
compliance.
This
is
because
the
high
concentration
could
be
averaged
with
lower
concentrations
at
a
given
location.
If
a
significant
excursion
occurs,
a
system
must
conduct
a
significant
excursion
evaluation
and
discuss
the
evaluation
with
the
State
no
later
than
the
next
sanitary
survey.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
4
July
2003
Systems
Subject
to
the
Stage
2
DBPR
(
All
surface
water
and
ground
water
CWSs
and
NTNCWSs
that
apply
a
chemical
disinfectant
to
their
water,
or
deliver
such
water.)

Rule
Implementation
(
All
systems
subject
to
the
rule
must
perform
rule
implementation
activities
such
as
reading
the
rule,
training,
etc.)

Initial
Distribution
System
Evaluation
(
IDSE)
(
All
systems
subject
to
the
rule
must
perform
an
IDSE,
or
meet
the
criteria
not
to
perform
an
IDSE.)

Systems
not
performing
an
IDSE
Systems
perfomring
an
IDSE
Systems
qualifying
for
the
40/
30
certification
Systems
conducting
a
Standard
Monitoring
Program
Systems
may
or
may
not
have
to
select
new
Stage
2B
DBPR
monitoring
sites
and
submit
report
Systems
submit
an
IDSE
report
identifying
Stage
2B
site
selection
Systems
conducting
a
System­
Specific
Study
Systems
receiving
a
very
small
system
waiver
NTNCWSs
serving
<
10,000
people
Compliance
with
Stage
2
DBPR
MCLs
(
All
systems
subject
to
the
rule
must
meet
Stage
2
DBPR
MCLs
 
applicable
for
Stage
2A
MCLs
at
Stage
1
DBPR
locations
and
Stage
2B
MCLs
at
revised
locations.
Systems
may
or
may
not
have
to
make
treatment
changes.)

Routine
Monitoring
Requirements
(
Some
systems
subject
to
the
Stage
2
DBPR
may
have
additional
routine
monitoring
requirements
beyond
those
already
required
by
the
Stage
1
DBPR.)

Producing
surface
water
systems
serving
fewer
than
10,000
people
and
all
producing
ground
water
systems
must
add
one
sampling
site
if
they
determine
that
high
TTHMs
and
HAA5s
do
not
occur
at
the
same
location.

Significant
Excursion
Evaluations
(
All
systems
subject
to
the
rule
must
perform
significant
excursion
evaluations
if
they
exceed
threshold
DBP
levels,
and
review
results
with
the
state
no
later
than
the
next
sanitary
survey.)
Producing
surface
water
systems
serving
at
least
10,000
people
will
not
have
to
add
a
sampling
site.
All
100
percent
purchasing
systems
may
have
additional
routine
monitoring
sites,
depending
on
their
population
served,
source
water
type,
and
Stage
1
DBPR
monitoring
plan.
Exhibit
ES.
1
Summary
of
Stage
2
DBPR
Requirements
5
Small
systems
that
either
buy
from
or
sell
to
a
large
system
must
follow
the
large
system
schedule
for
the
IDSE.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
5
July
2003
Final
Stage
2
DBPR
Large
and
Medium
Systems
(
Serving
>
10,000
People)

Small
Systems
(
Serving
<
10,000
People)
5
Systems
Not
Conducting
Crypto
Monitoring
Under
the
LT2ESWTR
State
Process
Submit
sites
to
state
IDSE
Comply
with
Stage
2A
2
Year
Extension
Begin
Stage
2B
0.080/
0.060
LRAA
Compliance
Primacy
Review
Stage
2
DBPR
sample
sites
Comply
with
Stage
2A
2
Year
Extension
IDSE
Submit
sites
to
state
Comply
with
Stage
2A
2
Year
Extension
Systems
Conducting
Crypto
Monitoring
Under
the
LT2ESWTR
Review
Stage
2
DBPR
sample
sites
Year
1
Year
2
Year
3
Year
4
Year
5
Year
6
Year
7
Year
8
Year
9
Year
10
Year
11
Year
1
Year
2
Year
3
Year
4
Year
5
Year
6
Year
7
Year
8
Year
9
Year
10
Year
11
Begin
Stage
2B
0.080/
0.060
LRAA
Compliance
Exhibit
ES.
2
Implementation
Timeline
for
the
Stage
2
DBPR5
6
The
baseline
number
of
plants
 
as
opposed
to
systems
 
that
may
have
to
add
treatment
to
meet
rule
requirements
is
different
and
discussed
in
section
ES.
5.1.

7
SDWIS­
Federal
Version
(
SDWIS/
FED)
is
a
database
created
by
EPA
containing
data
submitted
by
States
and
Regions
regarding
compliance
with
SDWA.
The
system
and
population
baselines
in
this
EA
reflect
the
SDWIS
4th
quarter
frozen
data
with
adjustments
to
account
for
reporting
discrepancies
in
Massachusetts
and
Montana.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
6
July
2003
ES.
4
Systems
Subject
to
the
Stage
2
DBPR
Exhibit
ES.
3
shows
the
baseline
number
of
systems
subject
to
the
rule6
and
the
estimated
number
that
will
perform
various
rule
activities
(
implementation,
IDSE
monitoring,
additional
routine
monitoring,
and
significant
excursion
evaluations).
This
baseline
is
derived
from
EPA's
Safe
Drinking
Water
Information
System
(
SDWIS)
inventory,
4th
quarter
2000
data.
7
The
systems
are
subdivided
by
type
(
CWS
or
NTNCWS),
source
water
type
(
either
disinfecting
ground
water
only
or
surface
water
and
mixed­
source)
and
size
(
small
and
large,
based
on
population
served).
The
number
of
ground
water
systems
in
column
A
represents
the
subset
of
all
ground
water
systems
that
disinfect.

As
shown
in
column
B,
EPA
estimates
that
all
disinfecting
CWSs
and
NTNCWSs
will
have
to
perform
at
least
minimal
implementation
activities
(
reading
and
understanding
the
rule,
training,
and
others).
The
number
of
systems
performing
IDSE
monitoring
(
shown
in
column
D),
however,
is
only
a
fraction
of
all
systems
because
some
will
choose
to
perform
studies
or
will
qualify
for
waivers
from
IDSE
requirements.
Results
in
column
F
indicate
that
less
than
20
percent
of
systems
will
need
to
conduct
additional
routine
monitoring
for
the
Stage
2
DBPR
beyond
the
Stage
1
DBPR
requirements.
This
small
percentage
reflects
the
fact
that
sampling
requirements
for
many
systems
(
particularly
large,
nonpurchased
systems)
will
not
change
from
Stage
1
DBPR
requirements
under
the
Stage
2
DBPR.
Systems
with
increased
requirements
include
small
systems
that
have
to
add
a
sample
site
because
their
high
TTHM
and
high
HAA5
concentrations
occur
at
different
locations.
For
some
consecutive
systems,
monitoring
requirements
will
be
based
on
population
served
rather
than
on
the
number
of
plants;
therefore,
the
number
of
sampling
sites
for
routine
monitoring
could
either
increase
or
decrease
from
the
Stage
1
to
Stage
2
DBPR.

Because
Stage
2
DBPR
compliance
is
based
on
an
annual
average
of
samples
collected
at
each
site,
EPA
expects
that
some
number
of
Stage
2­
compliant
systems
will
observe
DBP
concentrations
high
enough
to
trigger
the
requirement
for
a
significant
excursion
evaluation.
Column
H
shows
the
estimated
number
of
systems
that
may
require
significant
excursion
evaluations.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
7
July
2003
A
B
C=
B/
A*
100
D
E=
D/
A*
100
F
G=
F/
A*
100
H
I=
H/
A*
100
£
10,000
9,111
9,111
100%
5,954
65%
2,700
30%
120
1%
>
10,000
2,292
2,292
100%
1,932
84%
0
0%
218
10%
National
Totals
11,403
11,403
100%
7,886
69%
2,700
24%
338
3%

£
10,000
30,683
30,683
100%
1,955
6%
4,772
16%
0
0%
>
10,000
1,423
1,423
100%
258
18%
569
40%
0
0%
National
Totals
32,105
32,105
100%
2,213
7%
5,341
17%
0
0%

£
10,000
810
810
100%
0
0%
6
1%
0
0%
>
10,000
11
11
100%
10
91%
6
55%
0
0%
National
Totals
821
821
100%
10
1%
12
1%
0
0%

£
10,000
7,298
7,298
100%
0
0%
8
0%
0
0%
>
10,000
6
6
100%
1
17%
1
17%
0
0%
National
Totals
7,303
7,303
100%
1
0%
9
0%
0
0%

£
10,000
47,901
47,901
100%
7,909
17%
7,486
16%
120
0%
>
10,000
3,731
3,731
100%
2,201
59%
576
15%
218
6%
GRAND
TOTAL
ALL
SYSTEMS
51,632
51,632
100%
10,110
20%
8,062
16%
338
1%

Sources:
(
A)
Exhibit
3.3,
column
K.
(
B),
(
D),
(
F),
(
H)
Exhibit
6.3.
Surface
Water
and
Mixed
NTNCWSs
Disinfecting
Ground
Water
Only
NTNCWSs
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.
Column
D
does
not
include
the
number
of
systems
performing
SSS's.
Refer
to
Appendix
H,
Exhibits
H.
4a
and
H.
4b
for
this
estimate.
ALL
SYSTEMS
Surface
Water
and
Mixed
CWSs
Disinfecting
Ground
Water
Only
CWSs
IDSE
Monitoring
Additional
Routine
Monitoring
System
Size
(
Population
Served)
Stage
2
DBPR
System
Baseline
Number
and
Percent
of
Systems
Performing
Various
Rule
Activities
Implementation
Significant
Excursion
Evaluations
Exhibit
ES.
3
Number
of
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
8
There
is
much
discussion
among
economists
of
the
proper
social
discount
rate
to
use
for
policy
analysis.
Therefore,
for
Stage
2
DBPR
cost
analyses,
calculations
are
made
using
two
social
discount
rates
thought
to
best
represent
current
policy
evaluation
methodologies,
3
and
7
percent.
Historically,
the
use
of
3
percent
is
based
on
rates
of
return
on
relatively
risk­
free
investments,
as
described
in
the
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j).
The
rate
of
7
percent
is
a
recommendation
of
the
Office
of
Management
and
Budget
(
OMB)
as
an
estimate
of
"
before­
tax
rate
of
return
to
incremental
private
investment"
(
USEPA
1996b).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
8
July
2003
ES.
5
National
Benefits
and
Costs
of
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
EPA
has
determined
from
its
analysis
of
the
available
animal
toxicological
studies
and
human
epidemiological
studies
that
the
Stage
2
DBPR
could
provide
benefits
resulting
from
reduced
incidence
of
adverse
reproductive
and
developmental
effects
and
reduced
incidence
of
cancer,
particularly
bladder
cancer.

The
main
category
of
benefits
that
EPA
has
quantified
is
the
expected
range
of
avoided
new
cases
of
bladder
cancer
each
year,
including
both
fatal
and
non­
fatal
cases.
In
addition,
EPA
has
estimated
the
monetized
value
of
avoiding
these
fatal
and
non­
fatal
bladder
cancer
cases.
Exhibit
ES.
4
summarizes
the
estimated
total
number
of
bladder
cases
avoided
and
the
monetized
benefits
resulting
from
those
cases
avoided
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative.
The
cases
and
monetized
benefits
are
based
on
reductions
in
average
DBP
concentrations
that
result
from
treatment
technology
changes.

Because
of
limitations
in
the
available
data,
it
is
not
possible
to
quantify
all
of
the
health
benefits
of
the
Stage
2
DBPR.
In
particular,
the
science
is
not
strong
enough
to
quantify
risk
of
reproductive
and
developmental
health
effects
resulting
from
DBP
exposure.
To
help
inform
the
assessment
of
the
Stage
2
DBPR
benefits,
EPA
has
prepared
an
illustrative
calculation
for
one
specific
reproductive
effect's
endpoint
(
fetal
loss).
Results
from
this
analysis
show
that
1,100
to
4,700
fetal
losses
could
potentially
be
avoided
annually
as
a
result
of
the
Stage
2
DBPR.
Other
unquantified
health
and
non­
health
benefits
derived
from
rule
implementation
also
could
contribute
to
the
overall
value
of
benefits.
Unquantified
benefits
are
discussed
in
detail
in
Chapter
5
and
are
summarized
in
Exhibit
9.1.

EPA's
national
cost
estimate
includes
costs
incurred
by
CWSs
and
NTNCWSs
for
rule
implementation,
the
IDSE,
additional
routine
monitoring,
significant
excursion
evaluations,
and
treatment
changes
(
treatment
changes
account
for
the
majority
of
the
national
costs)
as
well
as
estimated
State/
Primacy
Agency
costs.
Exhibit
ES.
4
summarizes
the
total
national
cost
estimate
(
both
one­
time
and
annualized)
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative.
Note
that
the
exhibit
presents
two
estimates
for
national
costs
and
monetized
benefits,
depending
upon
the
discount
rate
used
for
present
value
calculations
and
annualizing
one­
time
costs.
8
Exhibit
ES.
5
compares
the
benefits
and
costs
graphically.

Sections
ES.
5.1
through
ES.
5.3
summarize
the
methods
used
to
estimate
the
number
of
plants
making
treatment
changes
to
comply
with
the
rule,
and
the
benefits
and
costs
resulting
from
these
treatment
changes.
Chapters
3,
5,
and
6
and
the
appendices
provide
a
more
complete
discussion
of
all
data
and
calculations
used
to
derive
the
results
in
Exhibits
ES.
4
and
ES.
5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
9
July
2003
Surface
Water
Disinfecting
Ground
Water
£
10,000
>
10,000
£
10,000
>
10,000
0.9
­
7.7
18.1
­
157.8
0.7
­
5.8
1.2
­
10.9
20.9
­
182.2
Annualized
Monetized
Benefits
of
Bladder
Cancer
Cases
Avoided
Range
shown
reflects
2
and
17
percent
estimates
of
PAR
$
4.8
­
$
41.5
$
97.9
­
$
854.3
$
3.6
­
$
31.3
$
6.8
­
$
59.1
$
113.0
­
$
986.2
and
WTP
for
Lymphoma
as
the
basis
for
non­
fatal
cases
Range
shown
reflects
2
and
17
percent
estimates
of
PAR
$
2.3
­
$
20.2
$
47.6
­
$
415.2
$
1.7
­
$
15.2
$
3.3
­
$
28.7
$
54.9
­
$
479.3
and
WTP
for
Chronic
Bronchitis
as
the
basis
for
non­
fatal
cases
Annualized
Total
Costs
$
8.9
$
21.5
$
13.3
$
14.2
$
1.1
$
59.1
Expected
value
and
90
percent
confidence
bounds
(
)
($
8.3
­
$
9.6)
($
19.6
­
$
23.4)
($
12.0
­
$
14.6)
($
13.3
­
$
15.2)
($
54.3
­
$
63.9)

Annualized
Monetized
Benefits
of
Bladder
Cancer
Cases
Avoided
Range
shown
reflects
2
and
17
percent
estimates
of
PAR
$
4.0
­
$
35.1
$
85.0
­
$
741.6
$
3.0
­
$
26.5
$
5.9
­
$
51.3
$
97.9
­
$
854.4
and
WTP
for
Lymphoma
as
the
basis
for
non­
fatal
cases
Range
shown
reflects
2
and
17
percent
estimates
of
PAR
$
2.0
­
$
17.1
$
41.3
­
$
360.6
$
1.5
­
$
12.9
$
2.9
­
$
24.9
$
47.6
­
$
415.5
and
WTP
for
Chronic
Bronchitis
as
the
basis
for
non­
fatal
cases
Annualized
Total
Costs
$
9.2
$
25.2
$
13.7
$
14.9
$
1.5
$
64.6
Expected
value
and
90
percent
confidence
bounds
(
)
($
8.5
­
$
9.9)
($
23.0
­
$
27.4)
($
12.3
­
$
15.1)
($
13.9
­
$
16.0)
($
59.2
­
$
70.0)

Notes:

Sources:
Totals
for
bladder
cancer
cases
avoided
and
monetized
benefits
from
Exhibit
5.27.
Detail
for
source
and
size
provided
in
Appendix
F.
Total
initial
capital
costs
provided
in
Exhibit
6.5;
annualized
total
costs
and
state/
primacy
agency
costs
derived
from
Exhibits
6.6a
and
6.6b.
Cases
avoided
and
monetized
benefits
are
derived
using
TTHM
as
an
indicator
for
all
DBPs.
These
benefits
could
be
zero
(
see
PAR
note
below).

PAR
=
Population
Attributable
Risk.
A
range
of
"
best
estimates"
of
2
to
17
percent
derived
from
five
epidemiological
studies.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
(
see
section
ES5.2
and
Chapter
5
for
a
discussion
of
PAR
values).
Total
State/
Primacy
Agencies
Estimated
Number
of
Bladder
Cancer
Cases
Avoided
per
Year
Includes
both
fatal
and
non­
fatal
cases.
Range
corresponds
to
low
and
high
"
best
estimates"
of
PAR
Type
of
Cost
or
Benefit
Unquantified
Benefits
Causality
has
not
been
established
between
adverse
developmental
and
reproductive
health
effects
and
exposure
to
chlorinated
water.
Thus,
numbers
and
types
of
cases
avoided,
as
well
as
the
value
of
such
cases,
were
not
quantified
in
the
primary
benefits
Qualitative
assessment
indicates
that
the
value
of
other
health
benefits
and
non­
health
benefits
could
be
positive
and
significant.

Monetized
benefits
and
costs
represent
present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
Costs
are
for
CWSs
and
NTNCWSs
and
include
treatment
and
nontreatment
costs.
90
percent
confidence
bounds
around
cost
estimates
reflec
Detail
may
not
add
due
to
independent
rounding.
Benefits
and
Costs
Based
on
Annualization
Discount
Rate
of
7
%
Benefits
and
Costs
Based
on
Annualization
Discount
Rate
of
3
%
Exhibit
ES.
4
Summary
of
Estimated
National
Benefits
and
Costs
of
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
($
Million)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
10
July
2003
Unquantified
Benefits
Estimated
Annualized
Value
of
Quantified
National
Benefits
0
800
900
400
500
600
Estimated
Annualized
National
Costs
700
100
200
300
Exhibit
ES.
5
Comparison
of
Annualized
National
Costs
and
Benefits
($
Millions)

Source:
Exhibit
9.3
ES.
5.1
Plants
Making
Treatment
Changes
A
key
input
to
estimating
the
national
benefits
and
costs
is
the
number
of
plants
making
treatment
changes
to
comply
with
the
rule.
Exhibit
ES.
6
(
column
A)
shows
the
baseline
number
of
plants
subject
to
the
Stage
2
DBPR.
Like
the
system
baseline
in
Exhibit
ES.
3,
the
plant
baseline
is
derived
from
the
4th
quarter
2000
SDWIS
data
and
includes
only
the
subset
of
ground
water
plants
that
disinfect.
The
system
baseline
from
SDWIS
is
converted
to
the
plant
baseline
through
three
steps:
(
1)
link
purchased
systems
to
their
respective
seller(
s),
(
2)
categorize
systems
by
primary
source
water
type,
and
(
3)
multiply
the
adjusted
system
inventory
from
steps
1
and
2
by
the
mean
estimated
number
of
plants
per
system.
Refer
to
section
3.4
of
this
EA
for
a
detailed
description
of
the
derivation
of
the
Stage
2
DBPR
plant
baseline.

Columns
B
and
C
in
Exhibit
ES.
6
show
the
number
and
percent
of
plants
in
the
baseline
expected
to
add
advanced
technologies
or
chloramines
to
meet
the
requirements
of
the
Stage
2
DBPR.
Advanced
technologies
include
alternative
disinfectants
such
as
ozone,
UV,
and
chlorine
dioxide,
and
DBP
precursor
removal
technologies
such
as
microfiltration
or
ultrafiltration.

The
methods
used
by
EPA
to
predict
the
number
of
plants
changing
treatment
to
meet
the
rule
and
the
technologies
used
by
these
plants
are
summarized
in
Exhibit
ES.
7.
These
methods
are
complex
and
are
different
for
different
source
water
types
and
system
sizes.
The
primary
tool
used
to
predict
changes
in
treatment
and
reductions
in
DBP
levels
was
the
Surface
Water
Analytical
Tool
(
SWAT).
SWAT
was
developed
by
EPA
using
results
from
the
1996
Information
Collection
Rule
(
ICR)
for
large
surface
water
plants.
The
SWAT
results
were
also
used
directly
for
the
medium
surface
water
systems;
adjustments
were
made
to
the
forecasts
for
small
surface
water
systems
to
account
for
differences
in
water
quality
and
operational
constraints
that
exist
in
small
systems.

For
large
ground
water
plants,
ICR
data
were
used
to
determine
which
plants
would
add
treatment
for
the
Stage
2
DBPR,
and
a
Delphi
poll
process
(
a
group
of
drinking
water
experts
who
provided
best
professional
judgment
in
a
structured
format)
was
used
to
identify
the
most
likely
technologies
selected
by
these
plants.
Like
the
medium
and
small
surface
water
systems,
the
technology
forecasts
for
the
medium
and
small
ground
water
systems
were
derived
from
the
large­
system
forecasts,
adjusting
for
differences
in
water
quality,
operational
constraints,
and
other
factors.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
11
July
2003
System
Size
(
Population
Served)
Stage
2
DBPR
Plant
Baseline
A
B
C=
B/
A*
100
£
10,000
4,089
149
3.7%
>
10,000
2,471
143
5.8%
National
Totals
6,560
293
4.5%

£
10,000
42,496
1,151
2.7%
>
10,000
6,999
145
2.1%
National
Totals
49,495
1,296
2.6%

£
10,000
802
30
3.8%
>
10,000
11
1
5.8%
National
Totals
813
31
3.8%

£
10,000
7,298
204
2.8%
>
10,000
6
0.1
2.1%
National
Totals
7,303
204
2.8%
ALL
PLANTS
£
10,000
54,685
1,535
2.81%
>
10,000
9,486
289
3.05%
GRAND
TOTAL
ALL
PLANTS
64,171
1,824
2.84%
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.
Sources:
(
A)
Exhibit
3.4,
column
Q.
Number
and
Percent
of
Plants
Adding
Treatment
(
B)
Number
of
plants
adding
treatment
based
on
technology
selection
delta
forecast
for
surface
water
and
ground
water
systems
in
section
6.4.
Primarily
Surface
Water
CWSs
Primarily
Ground
Water
CWSs
Primarily
Suface
Water
NTNCWSs
Primarily
Ground
Water
NTNCWSs
Exhibit
ES.
6
Plants
Making
Treatment
Changes
Exhibit
ES.
7
Methods
Used
to
Predict
Treatment
Changes
System
Size
(
Population
Served)
Source
Water
Category
Surface
Water
Disinfecting
Ground
Water
Large
(>
100,000
people)
SWAT
Ground
Water
Delphi
Poll
Medium
(
10,000
to
100,000
people)
Extrapolation
from
SWAT
Extrapolation
from
large
ground
water
system
results
Small
(
#
10,000
people)
Extrapolation
from
SWAT,
through
small
surface
water
system
expert
review
process
Extrapolation
from
large
ground
water
system
results,
through
small
ground
water
system
expert
review
process
9
See
Chapter
5
for
a
complete
discussion.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
12
July
2003
There
are
uncertainties
associated
with
the
estimates
of
plants
making
treatment
changes
shown
in
Exhibit
ES.
6.
One
is
the
effect
of
the
IDSE
on
predictions
of
non­
compliance.
The
number
of
plants
adding
chloramines
or
advanced
technology
could
be
understated
because
plants
may
find
higher
TTHM
or
HAA5
concentrations
at
new
sites
identified
during
the
IDSE.
The
number
of
plants
adding
chloramines
or
advanced
technology,
however,
may
be
overstated
because
of
conservative
assumptions
used
in
the
analysis.
For
example,
compliance
determination
for
plants
is
made
assuming
a
20
percent
margin
of
safety
under
the
MCLs.
Systems
complying
by
switching
to
chloramines
may
choose
to
meet
the
Stage
2
MCLs
with
a
much
smaller
margin
of
safety
since
chloramines
dampen
the
variability
of
DBP
concentrations
on
distribution
systems.
Also,
EPA
believes
that
the
estimated
number
of
ground
water
and
small
surface
water
plants
changing
technology
may
be
biased
upward
because
their
monitoring
requirements
and,
thus,
compliance
calculation,
are
expected
to
be
very
similar
from
the
Stage
1
to
Stage
2
DBPR.
Chapter
7
provides
a
more
complete
discussion
of
these
uncertainties
and
includes
a
quantitative
analysis
to
assess
their
effects.
It
is
not
known
in
which
direction
the
net
impact
of
these
uncertainties
influences
the
estimates
in
Exhibit
ES.
6.

ES.
5.2
Derivation
of
Benefits
The
quantified
benefits
estimates
for
the
Stage
2
DBPR
are
based
on
reductions
in
fatal
and
nonfatal
bladder
cancer
cases.
Only
an
illustrative
example
of
reduction
in
one
potential
reproductive
and
developmental
health
endpoint
(
fetal
loss)
is
given
because
of
the
much
greater
uncertainties
in
quantifying
this
risk
than
for
bladder
cancer.

All
benefit
calculations
were
performed
using
the
Stage
2
DBPR
Benefits
Model
(
USEPA
2003i).
EPA
used
similar
approaches
to
estimate
the
number
of
bladder
cancer
cases
avoided
and
the
avoided
incidence
of
fetal
loss
the
illustrative
calculation.
The
major
steps
in
deriving
and
characterizing
cases
avoided
are:

°
Estimate
the
current
cases
of
annual
bladder
cancer
and
fetal
loss.

°
Estimate
how
many
of
these
cases
are
attributable
to
DBP
exposure.

°
Estimate
the
reduction
in
current
cases
corresponding
to
anticipated
reductions
in
DBP
occurrence
and
exposure
due
to
the
Stage
2
DBPR
(
i.
e.,
cases
avoided).

For
bladder
cancer,
EPA
computed
the
total
national
annual
monetized
benefits
of
the
Stage
2
DBPR
by
multiplying
the
estimated
number
of
bladder
cancer
cases
avoided
by
an
estimated
monetary
value
associated
with
the
avoided
cases
of
fatal
and
non­
fatal
bladder
cancer.
EPA
has
not
valued
fetal
losses
at
this
time.

To
quantify
the
benefits
due
to
reduction
in
bladder
cancer,
EPA
begins
with
an
estimated
number
of
new
cases
per
year
from
all
causes
of
56,500
(
based
on
published
2002
American
Cancer
Society
data,
available
on
the
web
at
http://
www.
cancer.
org/).
The
estimated
percent
of
those
cases
attributable
to
DBPs
is
based
on
several
epidemiological
studies
conducted
in
the
1980s
and
1990s.
9
Results
from
five
studies
were
used
to
estimate
the
population
attributable
risk
(
PAR)
of
bladder
cancer
due
to
DBPs.
PAR
represents
the
fraction
of
occurrence
of
a
particular
disease
that
is
attributable
to
some
specified
risk
factor.
Analysis
of
data
from
the
five
studies
showed
that
best
estimates
of
PAR
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
13
July
2003
range
from
2
to
17
percent.
The
total
cases
of
bladder
cancer
from
all
causes
multiplied
by
the
range
of
best
estimate
PAR
values
results
in
approximately
1,100
to
9,600
new
bladder
cancer
cases
per
year
that
can
be
attributed
to
DBPs
in
chlorinated
drinking
water.
EPA
recognizes
that
the
causality
has
not
yet
been
established
between
chlorinated
water
and
bladder
cancer
and
that
the
actual
cases
attributable
to
DBPs
could
be
zero.

The
baseline
cancer
incidence
and
the
PAR
estimates
described
above
reflect
conditions
prior
to
the
implementation
of
not
only
the
Stage
2
DBPR
but
also
the
Stage
1
DBPR.
To
estimate
the
benefits
of
the
Stage
2
DBPR,
EPA
first
estimated
the
portion
of
the
56,500
annual
cases
expected
to
be
avoided
by
DBP
reductions
resulting
from
the
Stage
1
DBPR
and
then
estimated
the
additional
cases
avoided
due
to
the
additional
reductions
in
DBP
levels
predicted
for
the
Stage
2
DBPR.
EPA
has
assumed
that
reductions
in
bladder
cancer
cases
attributable
to
DBP
exposure
are
directly
proportional
to
reductions
in
the
national
average
DBP
levels.
SWAT
was
the
primary
tool
used
to
predict
these
reductions
in
national
average
TTHM
and
HAA5
levels.
The
resulting
reductions
in
new
bladder
cancer
cases
are
calculated
annually
for
a
25­
year
time
period
based
on
the
rule
implementation
schedule,
and
include
an
adjustment
to
account
for
an
anticipated
transition
time
for
individual
risk
to
be
reduced
from
pre­
Stage
2
levels
to
post­
Stage
2
levels
(
referred
to
as
the
cessation
lag).
Also,
EPA
has
estimated
that
26
percent
of
bladder
cancer
cases
are
fatal,
while
74
percent
are
non­
fatal
(
USEPA,
1999a)

The
final
step
in
the
benefit
calculation
is
to
monetize
the
estimated
reduction
in
bladder
cancer
cases
by
applying
economic
values
for
avoided
illness
and
deaths.
The
value
of
avoiding
non­
fatal
bladder
cancer
cases
is
based
on
people's
willingness
to
pay
(
WTP)
for
incremental
reductions
in
the
risk
of
contracting
cancer.
The
reduced
risk
represented
by
willingness
to
pay
accounts
for
the
desire
to
avoid
treatment
costs,
pain
and
discomfort,
productivity
losses,
and
any
other
adverse
consequences
related
to
contraction
of
a
non­
fatal
case
of
bladder
cancer.

Because
specific
estimates
of
WTP
for
avoiding
non­
fatal
bladder
cancer
are
not
available,
EPA
estimated
WTP
values
from
two
other
non­
fatal
illnesses:
chronic
bronchitis
and
curable
lymphoma.
Both
are
considered
equally
valid
estimates
of
WTP
for
non­
fatal
bladder
cancer.

For
fatal
bladder
cancer
cases,
the
Value
of
a
Statistical
Life
(
VSL)
is
used
to
capture
the
value
of
benefits.
The
VSL
represents
an
estimate
of
the
monetary
value
of
reducing
risks
of
premature
death
from
cancer.
The
VSL,
therefore,
is
not
an
estimate
of
the
value
of
saving
a
particular
individual's
life.
Rather,
the
value
of
a
"
statistical"
life
represents
the
sum
of
the
values
placed
on
small
individual
risk
reductions
across
an
exposed
population.
Other
economic
factors
are
taken
into
consideration
when
calculating
benefits
over
time,
such
as
income
growth
and
social
discount
rates.

There
are
several
areas
of
uncertainty
with
respect
to
quantified
benefits
for
bladder
cancer.
Many
are
incorporated
into
the
analyses,
such
as
the
uncertainty
in
PAR
values
reflected
by
the
use
of
a
wide
range
of
"
best
estimates"
of
2
to
17
percent
derived
from
several
credible
epidemiological
studies.
Uncertainties
in
these
best­
estimates
of
PAR
suggest
95
percent
confidence
interval
ranges
truncated
at
0
percent
on
the
low
end
and
up
to
33
percent
on
the
high
end
(
see
Appendix
E
for
details).
There
is
also
uncertainty
in
the
valuation
of
the
estimated
bladder
cancer
cases
avoided,
including
the
use
of
two
alternatives
for
valuing
non­
fatal
bladder
cancer.

As
noted
previously,
EPA
expects
that
a
large
portion
of
the
total
benefits
from
this
rule
could
come
from
reduction
in
developmental
and
reproductive
health
effects,
although
the
science
on
these
effects
as
a
result
of
DBP
exposure
is
not
strong
enough
to
fully
quantify
risk.
EPA
completed
a
preliminary
quantification
of
the
fetal
loss
risk
and
rule
benefits
in
an
illustrative
calculation.
Fetal
loss
was
used
in
the
analysis
because,
while
some
epidemiological
data
exist
for
other
reproductive
and
10
System
size
categories
are
based
on
population
served
and
are
as
follows:
<
100;
101­
500;
501­
1,000;
1,001­
3,300;
3,301­
10,000;
10,001­
50,000;
50,001­
100,000;
100,001­
1
million;
>
1
million.
These
categories
are
consistent
with
data
in
the
Drinking
Water
Baseline
Handbook
(
USEPA
2001h).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
14
July
2003
developmental
effects
potentially
associated
with
DBP
exposure,
more
data
are
available
on
this
particular
end­
point.
Because
approximately
one
million
of
the
six
million
pregnancies
each
year
in
the
United
States
end
in
a
miscarriage
or
stillbirth
(
Ventura
et
al.
2000a),
even
a
small
risk
attributable
to
DBP
exposure
that
can
be
avoided
by
reducing
DBP
levels
may
result
in
a
significant
number
of
avoided
fetal
losses.

EPA
estimated
the
reduction
in
fetal
losses
in
a
similar
manner
to
bladder
cancer
cases.
A
range
of
possible
PAR
values
for
relating
annual
fetal
losses
to
DBP
exposure
was
obtained
from
available
epidemiological
studies.
Reductions
in
occurrence
of
peak
DBPs
due
to
the
Stage
1
DBPR
and
the
Stage
2
DBPR
were
estimated.
Reductions
in
exposure
to
peak
DBPs
were
assumed
to
be
proportional
to
reductions
in
peak
DBP
occurrence.

The
estimate
of
potential
fetal
losses
avoided
as
a
result
of
the
Stage
2
DBPR
ranges
from
1,100
to
4,700.
Like
the
analysis
of
bladder
cancer,
there
is
large
uncertainty
in
fetal
loss
PAR
values,
reflected
in
the
large
range
of
values
used
in
the
analysis.
There
are
other
important
uncertainties
in
this
illustrative
calculation,
including
the
assumed
proportional
relationship
between
reduction
in
fetal
losses
and
reduction
in
exposure
to
peak
levels
due
to
the
Stage
2
DBPR.

ES.
5.3
Derivation
of
Costs
To
estimate
the
total
national
costs
of
the
Stage
2
DBPR,
EPA
calculated
the
incremental
costs
to
be
incurred
by
PWSs
and
States
from
the
Stage
1
DBPR
to
the
Stage
2
DBPR.
Cost
analyses
for
PWSs
include
identifying
treatment
process
improvements
that
systems
may
make,
as
well
as
estimating
the
costs
to
implement
the
rule,
conduct
IDSEs,
perform
additional
routine
monitoring,
and
evaluate
significant
DBP
excursion
events
(
referred
to
as
"
non­
treatment"
activities
in
this
document).
State
cost
analyses
include
estimates
of
the
labor
burdens
that
States
would
face,
such
as
training
employees
on
the
requirements
of
the
Stage
2
DBPR,
responding
to
PWS
reports,
and
record
keeping.
Cost
calculations
are
performed
using
the
Stage
2
DBPR
Cost
Model
(
USEPA
2003j).
The
methodology
for
estimating
treatment
and
non­
treatment
related
costs
for
systems
is
discussed
in
the
next
several
paragraphs,
followed
by
a
discussion
of
uncertainties.
(
A
complete
discussion
of
the
cost
analysis
is
provided
in
Chapter
6.)

All
treatment
costs
are
based
on
mean
unit
cost
estimates
for
advanced
technologies
and
chloramines.
Technology
unit
cost
estimates
are
in
the
form
of
"
dollars
per
plant"
for
initial
capital
and
yearly
operations
and
maintenance
(
O&
M)
activities.
Derivation
of
unit
costs
for
a
wide
range
of
plant
sizes,
represented
by
different
design
and
average
daily
flow
rates,
are
described
in
detail
in
the
document,
Technologies
and
Costs
for
Control
of
Microbial
Contaminants
and
Disinfection
Byproducts
(
USEPA
2003o).
EPA
uses
mean
population
per
system
for
each
of
nine
system
size
categories
(
derived
from
SDWIS)
combined
with
regression
equations
to
estimate
mean
design
and
average
daily
flows
as
a
function
of
population
served,
for
ground
and
surface
water
plants.
10
Unit
costs
(
capital
and
O&
M)
for
each
of
the
nine
system
size
categories
can
be
calculated
using
these
mean
flow
values.
The
unit
costs
are
then
combined
with
the
predicted
number
of
plants
selecting
each
technology
to
produce
national
treatment
cost
estimates.
11
A
population­
based
monitoring
approach
(
i.
e.,
the
number
of
samples
is
based
solely
on
system
size
and
source
water
type)
is
used
for
100
percent
purchasing
systems.
A
plant­
based
approach
(
i.
e.,
the
number
of
samples
depends
not
only
on
system
size
and
source
water
type,
but
also
on
the
number
of
plants
in
a
system)
is
used
for
producing
systems.
EPA
is
considering
a
population­
based
approach
for
all
systems
for
IDSE
and
routine
monitoring
requirements.
Appendix
I
of
this
EA
provides
the
rationale
for
using
a
population­
based
approach
for
all
systems
and
compares
costs
and
burdens
of
the
two
approaches.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
15
July
2003
Non­
treatment
costs
for
implementation,
the
IDSE,
additional
routine
monitoring,
and
significant
excursion
evaluations
are
based
on
estimates
of
labor
hours
for
performing
these
activities
and
on
additional
laboratory
costs.
For
all
non­
treatment
cost
calculations,
EPA
used
the
Stage
2
DBPR
system
baseline
shown
in
Exhibit
ES.
3.
For
the
IDSE
and
additional
routine
monitoring,
costs
are
estimated
separately
for
100
percent
purchasing
systems
(
those
that
buy
or
otherwise
receive
all
of
their
finished
water
from
another
system)
and
producing
systems
that
do
not
buy
or
otherwise
receive
all
of
their
finished
water
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water)
because
the
Stage
2
DBPR
set
forth
different
requirements
for
these
two
groups
of
systems.
11
EPA
recognizes
that
systems
vary
with
respect
to
many
of
the
input
parameters
to
the
Stage
2
DBPR
cost
model
(
e.
g.,
plants
per
system,
population
served,
flow
per
population,
labor
rates).
In
most
cases,
there
is
insufficient
information
to
characterize
fully
the
variability
on
a
national
scale.
EPA
believes
that
mean
values
for
the
various
input
parameters
are
adequate
to
generate
EPA's
best
estimate
of
national
costs
for
the
rule.

EPA
also
recognizes
that
there
is
uncertainty
in
the
national
cost
estimates
in
addition
to
those
elements
of
uncertainty
discussed
in
Section
ES.
5.1
related
to
the
number
of
plants
implementing
various
treatment
technologies.
There
is
uncertainty
in
the
national
average
unit
capital
and
O&
M
costs
for
the
various
technologies
expected
to
be
implemented
in
response
to
the
Stage
2
DBPR.
This
uncertainty
has
been
incorporated
into
the
cost
model
(
using
Monte
Carlo
simulation
procedures).
The
national
costs
of
the
Stage
2
DBPR
summarized
in
Exhibit
ES.
4
show
both
the
expected
values
and
the
90
percent
confidence
bounds
on
the
national
cost
estimates
obtained
from
the
cost
model.

ES.
6
Estimated
Impacts
on
Household
Costs
EPA
assumes
that
systems
will,
to
the
extent
possible,
pass
cost
increases
on
to
their
customers
through
increases
in
water
rates.
Exhibit
ES.
8
presents
estimated
annual
household
cost
increases
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative.
The
top
half
of
the
exhibit
shows
summary
statistics
for
all
households
served
by
systems
subject
to
the
rule,
including
those
that
will
not
change
or
add
treatment
but
will
incur
other
minimal
costs,
such
as
for
rule
implementation
or
additional
routine
monitoring.
The
bottom
half
shows
statistics
just
for
those
households
served
by
systems
actually
changing
treatment
technologies
to
comply
with
the
rule
(
see
Exhibit
ES.
6
for
estimates
of
the
percent
of
plants
adding
treatment).
Because
treatment
changes
represent
the
majority
of
rule
costs,
this
provides
insight
into
how
the
rule
will
affect
that
segment
of
the
population
most
impacted
by
the
rule.

As
shown
in
Exhibit
ES.
8,
the
mean,
median,
and
90th
percentile
household
cost
increases
for
all
systems
are
$
0.51,
$
0.02,
and
$
0.47,
respectively.
The
mean,
median,
and
90th
percentile
household
cost
increases
for
those
served
by
plants
adding
treatment
are
$
8.52,
$
1.22,
and
$
20.57,
respectively.
Households
in
small
systems
served
by
plants
adding
treatment
will
experience
the
highest
household
cost
increases
because
they
must
spread
technology
costs
over
a
smaller
customer
base.
12
Section
1415(
e)(
1)
of
SDWA
allows
States
to
grant
variances
to
small
water
systems
in
lieu
of
complying
with
an
MCL
if
EPA
determines
that
no
nationally
affordable
compliance
technologies
exist
for
that
system
size/
water
quality
combination.
These
variances
also
may
be
granted
only
where
EPA
has
identified
a
variance
technology
under
Section
1412(
b)(
15)
for
the
contaminant,
system
size,
and
source
water
quality
in
question.
EPA
is
conducting
a
rigorous
review
of
the
methodology
for
the
small
system
affordability
analysis.

13
The
only
technology
that
was
selected
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
that
is
slightly
above
the
affordability
threshold
for
systems
serving
25
to
500
people
is
GAC20
(
90­
day
reactivation
frequency)
with
advanced
oxidants.
EPA
believes,
however,
that
the
number
of
plants
in
small
systems
predicted
to
add
advanced
technologies
(
including
GAC20)
is
overstated
for
two
reasons:
1)
Stage
2
DBPR
requirements
for
small
systems
are
similar
to
Stage
1
DBPR
requirements
and
may
not
trigger
compliance
violations,
as
explained
in
the
minimal
impacts
sensitivity
analysis
in
Chapter
7,
and
2)
distribution
system
modifications
are
not
considered
in
the
compliance
forecast.
A
more
detailed
discussion
of
this
rationale
is
provided
in
Chapter
8.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
16
July
2003
All
Households
Subject
to
the
Stage
2
DBPR
Total
Number
of
Households
Served
(
Percent
of
Total)
Mean
Annual
Household
Cost
Increase
Median
Annual
Household
Cost
Increase
90th
Percentile
Annual
Household
Cost
Increase
95th
Percentile
Annual
Household
Cost
Increase
Percentage
of
Annual
Household
Cost
Increase
<
$
12
Percentage
of
Annual
Household
Cost
Increase
<
$
120
All
Systems
98,254,000
(
100.0)
$
0.51
$
0.02
$
0.47
$
0.79
99.24%
99.96%
All
Small
Systems
14,522,000
(
100.0)
$
1.66
$
0.18
$
0.90
$
2.96
98.23%
99.74%
SW
£
10,000
3,165,000
(
3.2%)
$
3.72
$
0.90
$
2.96
$
5.51
97.89%
99.09%
SW
>
10,000
58,876,000
(
59.9%)
$
0.34
$
0.003
$
0.32
$
0.33
99.35%
100.00%
GW
£
10,000
11,357,000
(
11.6%)
$
1.08
$
0.11
$
0.53
$
1.37
98.37%
99.92%
GW
>
10,000
24,857,000
(
25.3%)
$
0.23
$
0.01
$
0.47
$
0.47
99.57%
100.00%
Households
Served
by
Plants
Adding
Treatment
Number
of
Households
Served
(
Percent
of
Total)
Mean
Annual
Household
Cost
Increase
Median
Annual
Household
Cost
Increase
90th
Percentile
Annual
Household
Cost
Increase
95th
Percentile
Annual
Household
Cost
Increase
Percentage
of
Household
Cost
Increase
<
$
12
Percentage
of
Household
Cost
Increase
<
$
120
All
Systems
4,793,000
(
4.9%)
$
8.52
$
1.22
$
20.57
$
33.98
84.47%
99.18%
All
Small
Systems
422,000
(
2.9%)
$
43.78
$
19.05
$
117.68
$
166.67
39.38%
91.12%
SW
£
10,000
142,000
(
4.5%)
$
60.64
$
9.08
$
166.67
$
270.04
54.36%
79.78%
SW
>
10,000
3,868,000
(
6.6%)
$
5.02
$
1.02
$
11.58
$
23.56
90.16%
99.96%
GW
£
10,000
279,000
(
2.5%)
$
35.18
$
19.22
$
72.07
$
117.68
33.71%
96.94%
GW
>
10,000
504,000
(
2.0%)
$
5.90
$
1.33
$
26.33
$
33.24
78.73%
100.00%

Source:
Results
represent
the
sum
of
treatment
and
non­
treatment
costs.
Household
costs
for
treatment
are
derived
from
household
unit
costs
in
Exhibits
6.9c
and
6.10c
combined
with
technology
selection
deltas
in
Exhibits
6.14
and
6.16.
Household
costs
for
non­
treatment­
related
rule
activities
are
derived
from
mean
costs
for
each
system
size
category
for
implementation,
IDSE,
additional
routine
monitoring,
and
significant
excursion
evaluations
(
as
derived
in
Appendix
H).
See
section
6.1.1
for
additional
information
on
the
derivation
of
household
costs.
Notes:
Detail
may
not
to
total
add
due
to
independent
rounding.
Number
of
households
served
by
systems
adding
treatment
will
be
higher
than
households
served
by
plants
adding
treatment
because
an
entire
system
will
incur
costs
even
if
less
than
the
total
number
of
plants
for
that
system
add
treatment
(
this
would
result
in
lower
household
costs,
however).
EPA
analyzed
the
affordability
of
the
Stage
2
DBPR
to
determine
if
variance
technologies
are
needed
for
small
systems.
12
The
analysis
was
performed
by
comparing
median
household
cost
increases
to
an
"
affordability
threshold"
(
i.
e.,
the
total
annual
household
water
bill
that
would
be
considered
affordable).
The
results
of
EPA's
analysis
show
that,
with
very
few
exceptions,
the
household
costs
for
all
technologies
predicted
to
be
selected
by
small
systems
are
less
than
the
available
expenditure
margin
and
that
variance
technologies
are
not
required.
13
Exhibit
ES.
8
Summary
of
Annual
Household
Cost
Increases
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
17
July
2003
WTP
for
lymphoma
used
to
value
nonfatal
cases
WTP
for
chronic
bronchitis
used
to
value
non­
fatal
cases
A
B
C
D
E
Preferred
(
80/
60
LRAA,
Br
10)
21
­
182
$
113
­
$
986
$
55
­
$
479
$
59
(
$
54
­
64
)

Alternative
1
(
80/
60
LRAA,
Br
5)
22
­
189
$
117
­
$
1,024
$
57
­
$
498
$
182
(
$
165
­
200
)

Alternative
2
(
80/
60
SH,
Br
10)
135
­
1,182
$
733
­
$
6,398
$
356
­
$
3,109
$
410
(
$
384
­
436
)

Alternative
3
(
40/
30
RAA,
Br
10)
161
­
1,408
$
873
­
$
7,621
$
424
­
$
3,704
$
594
(
$
556
­
632
)

Notes:

A.
See
section
ES.
2
for
a
full
description
of
the
regulatory
alternatives
considered
in
this
EA.

E.
90
percent
confidence
bounds
around
cost
estimate
reflect
uncertainty
in
unit
treatment
costs.
Source:
Exhibit
6.24
B.
Based
on
TTHM
as
an
indicator.
EPA
recognizes
that
the
number
of
cases
avoided
could
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
Source:
Exhibit
5.28
C.
and
D.
Source:
Exhibit
5.28
Monetized
benefits
and
costs
represent
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
Costs
are
for
CWSs
and
NTNCWSs
and
include
treatment
and
non­
treatment
costs.
Rule
Alternative
Estimated
Number
of
Cases
Avoided
(
2
and
17%
PAR)
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
Total
Annualized
Costs
(
90
%
Confidence
Bounds)
ES.
7
Comparison
of
Costs
and
Benefits
for
Four
Regulatory
Alternatives
Section
ES.
2
described
the
four
regulatory
alternatives
considered
in
this
economic
analysis.
Costs
and
benefits
for
these
four
alternatives
are
summarized
in
Exhibit
ES.
9a
for
a
3­
percent
discount
rate
and
ES.
9b
for
a
7­
percent
discount
rate.
EPA
recognizes
that
the
quantified
benefits
based
on
reduced
cases
of
bladder
cancer,
as
shown
in
Exhibits
ES.
9a
and
b,
could
be
zero
for
all
alternatives
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
It
is
important
to
note,
however,
that
the
non­
quantified
benefits
(
e.
g.,
reduction
in
developmental
and
reproductive
risk)
are
not
included
in
the
primary
benefits
analysis,
but
could
be
substantial
(
see
the
illustrative
calculation
of
fetal
losses
avoided
in
Chapter
5).

As
shown
in
Exhibits
ES.
9a
and
b,
estimated
costs
for
Alternative
1
are
more
than
twice
those
for
the
preferred
alternative,
though
quantified
benefits
based
on
bladder
cancer
cases
avoided
are
nearly
the
same.
The
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
they
were
concerned
that
lowering
the
bromate
level
to
5
µ
g/
L
could
have
adverse
effects
on
microbial
protection.
(
see
Chapter
4
for
a
full
discussion).

Exhibit
ES.
9a
Comparison
of
Costs
and
Benefits
for
the
Stage
2
DBPR
Regulatory
Alternatives
(
3%
Discount
Rate,
$
Million)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
ES­
18
July
2003
WTP
for
Lymphoma
used
to
value
non­
fatal
cases
WTP
for
Chronic
Bronchitis
used
to
value
non­
fatal
cases
A
B
C
D
E
Preferred
(
80/
60
LRAA,
Br
10)
21
­
182
$
98
­
$
854
$
48
­
$
415
$
65
(
$
59
­
70
)

Alternative
1
(
80/
60
LRAA,
Br
5)
22
­
189
$
102
­
$
887
$
49
­
$
431
$
195
(
$
176
­
214
)

Alternative
2
(
80/
60
SH,
Br
10)
135
­
1,182
$
635
­
$
5,546
$
309
­
$
2,697
$
443
(
$
413
­
472
)

Alternative
3
(
40/
30
RAA,
Br
10)
161
­
1,408
$
757
­
$
6,607
$
368
­
$
3,213
$
644
(
$
601
­
687
)

Notes:

A.
See
section
ES.
2
for
a
full
description
of
the
regulatory
alternatives
considered
in
this
EA.

E.
90
percent
confidence
bounds
around
cost
estimate
reflect
uncertainty
in
unit
treatment
costs.
Source:
Exhibit
6.24
B.
Based
on
TTHM
as
an
indicator.
EPA
recognizes
that
the
number
of
cases
avoided
could
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
Source:
Exhibit
5.28
C.
and
D.
Source:
Exhibit
5.28
Monetized
benefits
and
costs
represent
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
Costs
are
for
CWSs
and
NTNCWSs
and
include
treatment
and
non­
treatment
costs.
Rule
Alternative
Estimated
Number
of
Cases
Avoided
(
2
and
17%
PAR)
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
Total
Annualized
Costs
(
90
%
Confidence
Bounds)
Exhibit
ES.
9b
Comparison
of
Costs
and
Benefits
for
the
Stage
2
DBPR
Regulatory
Alternatives
(
7%
Discount
Rate,
$
Million)

The
range
of
quantified
benefits
increases
significantly
with
Alternatives
2
and
3.
However,
the
associated
costs
also
increase
significantly
 
cost
figures
in
Exhibit
ES.
9
show
estimated
values
between
$
384
and
$
682
million
per
year.
Although
the
benefits
for
Alternatives
2
and
3
are
potentially
significant,
the
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
it
believed
that
the
health
effects
data
are
not
certain
enough
to
warrant
such
a
potentially
expensive
regulation
at
this
time.

ES.
8
Conclusions
Pursuing
its
mandate
to
protect
public
health,
EPA
has
proposed
the
Stage
2
DBPR
to
reduce
the
risks
that
byproducts
of
chemical
disinfection
pose
to
consumers
of
drinking
water.
Disinfection
itself
is
important
for
protecting
the
public
against
waterborne
microbes,
and
is
practiced
by
over
51,600
PWSs
in
the
United
States.
The
chemicals
commonly
used,
however,
can
react
with
substances
in
the
source
water
to
create
harmful
disinfection
byproducts.
These
disinfection
byproducts
include
trihalomethanes
and
haloacetic
acids,
which
are
associated
with
increased
incidence
of
bladder
cancer
and,
possibly,
of
other
cancers.
They
may
also
cause
adverse
reproductive
and
developmental
effects
such
as
early­
term
miscarriage,
stillbirth,
low
birth
weight,
and
some
birth
defects.
There
is
uncertainty
in
the
scientific
literature
regarding
the
extent
to
which
DBPs
contribute
to
the
incidence
of
these
adverse
effects
in
the
exposed
population.
Nevertheless,
EPA
believes
that
the
evidence
provided
in
the
toxicological
and
epidemiological
studies
relating
DBPs
to
cancer
and
to
reproductive
and
developmental
effects
supports
concern
for
these
potential
hazards
and
justifies
the
proposed
regulatory
action.
1
Chapter
6
shows
that
the
costs
of
the
Stage
2
DBPR
are
estimated
to
be
less
than
$
100
million
per
year.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
1
July
2003
1.
Introduction
This
document
presents
an
analysis
of
the
costs
and
benefits
of
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
The
analysis
is
performed
in
compliance
with
Executive
Order
12866,
Regulatory
Planning
and
Review
(
USEPA
1993),
which
requires
that
the
Environmental
Protection
Agency
(
EPA)
estimate
the
economic
impact
of
rules
costing
over
$
100
million
annually1
in
an
Economic
Analysis
(
EA)
and
to
submit
the
analysis
in
conjunction
with
publishing
the
rule.

This
chapter
provides
a
summary
of
the
Stage
2
DBPR
in
Section
1.1.
Section
1.2
outlines
the
organization
of
this
EA
and
section
1.3
provides
information
regarding
supporting
calculations
and
citations
in
this
EA.

1.1
Summary
of
the
Stage
2
DBPR
The
requirements
of
the
Stage
2
DBPR
apply
to
all
community
water
systems
(
CWSs)
and
nontransient
noncommunity
water
systems
(
NTNCWSs)
that
add
a
disinfectant
other
than
ultraviolet
light
(
UV)
or
that
deliver
water
that
has
been
treated
with
a
disinfectant
other
than
UV.
The
Stage
2
DBPR
builds
on
the
1979
Total
Trihalomethane
Rule
and
the
1998
Stage
1
DBPR
by
requiring
reduced
levels
of
disinfection
byproducts
(
DBPs)
in
distribution
systems.
Each
rule
activity
for
the
Preferred
Regulatory
Alternative
and
the
associated
rule
schedule
are
described
below.

The
Stage
2
DBPR
is
designed
to
reduce
DBP
occurrence
peaks
in
the
distribution
system
by
changing
compliance
monitoring
requirements.
Compliance
monitoring
will
be
preceded
by
an
initial
distribution
system
evaluation
(
IDSE)
to
identify
distribution
system
locations
that
represent
high
total
trihalomethane
(
TTHM)
and
haloacetic
acids
(
HAA5)
levels.
Systems
may
perform
an
IDSE
either
by
completing
a
system­
specific
study
(
SSS)
or
a
standard
monitoring
program
(
SMP).
NTNCWSs
serving
fewer
than
10,000
people
are
not
required
to
conduct
an
IDSE.
In
addition,
some
systems
may
not
need
to
perform
the
IDSE
if
(
1)
they
demonstrate
low
historic
DBP
distribution
system
concentrations
(
all
samples
less
than
or
equal
to
0.040
mg/
L
and
0.030
mg/
L
for
TTHM
and
HAA5,
respectively),
or
if
(
2)
they
serve
fewer
than
500
people
and
the
State/
Primacy
Agency
determines
that
the
Stage
1
DBPR
monitoring
site
represents
both
their
highest
TTHM
and
HAA5
concentrations.

The
IDSE
SMP
requirements
depend
on
a
system's
source
water
type,
population
served,
number
of
plants,
residual
disinfectant,
and
whether
or
not
they
purchase
100
percent
of
their
finished
water.
For
the
purposes
of
this
EA,
systems
are
classified
into
one
of
two
categories
according
to
their
buying
and
selling
relationships
with
other
systems:
(
1)
100
percent
purchasing
systems
buy
or
otherwise
receive
all
of
their
finished
water
from
another
system,
(
2)
Producing
systems
do
not
buy
or
otherwise
receive
all
of
their
water
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).
Temporary
or
emergency
sources
are
not
considered
when
determining
if
a
system
is
100
percent
purchasing.
2
EPA
has
identified
several
potential
issues
with
the
plant
based
approach
(
e.
g.,
the
number
of
required
sample
sites
may
be
either
excessive
or
insufficient
in
representing
DBP
occurrence
in
cases
where
a
small
system
has
multiple
plants,
or
where
a
very
large
systems
has
very
few
plants)
and
is
considering
a
population­
based
approach
for
the
IDSE
and
Stage
2B
compliance
monitoring
for
all
systems.
EPA
has
requested
comment
on
this
alternative
monitoring
scheme
in
the
preamble
to
this
rule
proposal.
Appendix
I
summarizes
the
rationale
for
considering
the
population­
based
approach
for
all
systems
and
evaluates
cost
implications.

3
EPA
is
considering
delaying
implementation
deadlines
for
the
IDSE
to
reduce
the
burden
on
systems
and
EPA
regions
and
increase
technical
involvement
of
the
States.
See
Appendix
I
for
further
discussion.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
2
July
2003
EPA
has
developed
two
monitoring
schemes
for
the
SMP
for
100
percent
purchasing
and
producing
systems:

(
1)
A
population­
based
approach
(
with
the
number
of
samples
based
solely
on
system
size
and
source
water
type)
for
100
percent
purchasing
systems.

(
2)
A
plant­
based
approach
(
in
which
the
numbers
of
samples
are
dependent
on
the
number
of
plants
in
the
system
as
well
as
on
system
size
and
source
water
type)
for
producing
systems.

Appendix
I
discusses
the
rationale
for
using
the
population­
based
approach
in
detail.
2
Exhibits
1.1
and
1.2
present
the
IDSE
SMP
requirements
for
100
percent
purchasing
systems
and
producing
systems,
respectively.

The
Stage
2
DBPR
changes
the
way
sampling
results
are
averaged
to
determine
compliance.
The
compliance
determination
for
the
Stage
2
DBPR
is
based
on
a
locational
running
annual
average
(
LRAA)
instead
of
the
system­
wide
running
annual
average
(
RAA)
used
under
the
Stage
1
DBPR.
LRAAs
are
essentially
RAAs
calculated
separately
for
each
sample
location
in
the
distribution
system.
With
the
Stage
2
LRAA
requirement,
the
TTHM
and
HAA5
maximum
contaminant
levels
(
MCLs)
must
be
met
at
each
monitoring
location,
while
the
Stage
1
RAA
requires
a
system
to
average
results
over
all
monitoring
locations.
Exhibit
1.3
provides
a
comparison
of
Stage
1
and
Stage
2
DBPR
compliance
calculations.

The
Stage
2
DBPR,
which
is
being
promulgated
simultaneously
with
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR)
to
address
complex
risk
trade­
offs
between
DBPs
and
microbial
pathogens,
will
be
implemented
in
two
stages.

Stage
2A:
Starting
[
3
years
after
rule
promulgation],
all
systems
must
comply
with
TTHM/
HAA5
MCLs
of
120/
100
µ
g/
L
measured
as
LRAAs
at
each
Stage
1
DBPR
monitoring
site
and
must
continue
to
comply
with
the
Stage
1
DBPR
TTHM/
HAA5
MCLs
of
80/
60
µ
g/
L,
measured
as
RAAs.

Stage
2B:
Starting
[
6
years
after
rule
promulgation],
systems
serving
at
least
10,000
people
must
comply
with
TTHM/
HAA5
MCLs
of
80/
60
µ
g/
L
measured
as
LRAAs
at
the
monitoring
sites
identified
during
an
IDSE3.
For
small
systems
required
to
perform
Cryptosporidium
monitoring
under
the
LT2ESWTR,
compliance
with
the
80/
60
µ
g/
L
MCLs,
measured
as
LRAAs,
will
begin
[
8.5
years
after
rule
promulgation].
For
all
other
small
systems,
compliance
with
the
80/
60
µ
g/
L
MCLs,
measured
as
LRAAs,
will
begin
[
7.5
years
after
rule
promulgation].
If
a
system
requires
capital
improvements,
the
State/
Primacy
Agency
may
grant
up
to
an
additional
24
months
for
compliance.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
3
July
2003
Exhibit
1.1
Summary
of
IDSE
SMP
Requirements
for
100
Percent
Purchasing
Systems1,
Population­
Based
Approach
System
Size
(
Population
Served)
Number
of
Distribution
System
Sites2
(
by
location
type)
per
System
Total
Number
of
Sites
per
System
Monitoring
Frequency
for
the
1­
year
IDSE
period3
Near
Entry
Point
Average
Residence
Time
High
TTHM
High
HAA5
Systems
Using
Surface
Water
in
Whole
or
in
Part4
<
500
­
­
1
1
2
Every
180
days
500
­
4,999
­
­
1
1
2
Every
90
days
5,000
­
9,999
­
1
2
1
4
Every
90
days
10,000
­
24,999
1
2
3
2
8
Every
60
days
25,000
­
49,999
2
3
4
3
12
Every
60
days
50,000
­
99,999
3
4
5
4
16
Every
60
days
100,000
­
499,999
4
6
8
6
24
Every
60
days
500,000
­
<
1.5
million
6
8
10
8
32
Every
60
days
1.5
million
­
<
5
million
8
10
12
10
40
Every
60
days
>
5
million
10
12
14
12
48
Every
60
days
Systems
Using
Only
Ground
Water
<
500
­
­
1
1
2
Every
180
days
500
­
9,999
­
­
1
1
2
Every
90
days
10,000
­
99,999
1
1
2
2
6
Every
90
days
100,000
­
499,999
1
1
3
3
8
Every
90
days
>
500,000
2
2
4
4
12
Every
90
days
1
100
percent
purchasing
systems
buy
or
otherwise
receive
all
of
their
finished
water
from
one
or
more
wholesale
systems
year­
round.
2
A
dual
sample
set
must
be
collected
at
each
location.
A
dual
sample
set
is
one
TTHM
and
one
HAA5
sample
that
is
taken
at
the
same
time
and
location.
3
Monitoring
frequency
is
the
approximate
number
of
days
between
monitoring
events.

4
For
the
purposes
of
this
EA,
"
surface
water"
systems
are
equivalent
to
"
subpart
H"
systems
and
include
systems
that
provide
ground
water
under
the
direct
influence
of
surface
water
(
GWUDI).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
4
July
2003
Exhibit
1.2
Summary
of
IDSE
SMP
Requirements
for
Producing
Systems1,
Plant­
Based
Approach
System
Size
(
Population
Served)
Residual
Disinfectant
Number
of
Distribution
System
Sites2
(
by
location
type)
per
Plant
Total
Number
of
Sites
per
Plant
Monitoring
Frequency3
Near
Entry
Point
Average
Residence
Time
High
TTHM
High
HAA5
Systems
Using
Surface
Water
in
Whole
or
in
Part4
<
500
Chlorine
or
Chloramines
­
­
1
1
2
Every
180
days
500
­
9,999
Chlorine
or
Chloramines
­
­
1
1
2
Every
90
days
>
10,000
Chlorine
1
2
3
2
8
Every
60
days
Chloramines
2
2
2
2
8
Systems
Using
Ground
Water
Only
<
10,000
Chlorine
or
Chloramines
­
­
1
1
2
Every
180
days
>
10,000
Chlorine
or
Chloramines
­
­
1
1
2
Every
90
days
1
Producing
systems
do
not
buy
100
percent
of
their
water
year­
round
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).
2
A
dual
sample
set
must
be
collected
at
each
location.
A
dual
sample
set
is
one
TTHM
and
one
HAA5
sample
that
is
taken
at
the
same
time
and
location.
3
Monitoring
frequency
is
the
approximate
number
of
days
between
monitoring
events.
4
For
the
purposes
of
this
EA,
"
surface
water"
systems
are
equivalent
to
"
subpart
H"
systems
and
include
systems
that
provide
GWUDI.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
5
July
2003
Stage
2B
DBPR
(
Note
that
some
sampling
locations
may
change
as
a
result
of
the
IDSE.)
Stage
1
DBPR
Distribution
System
Sampling
Location
First
Quarter
Average
of
All
Samples
Second
Quarter
Third
Quarter
Fourth
Quarter
Average
of
All
Samples
Average
of
All
Samples
Average
of
All
Samples
Running
Annual
Average
(
RAA)
of
Quarterly
Averages
MUST
BE
AT
OR
BELOW
COMPLIANCE
LEVELS
First
Quarter
Second
Quarter
Third
Quarter
Fourth
Quarter
First
Quarter
Second
Quarter
Third
Quarter
Fourth
Quarter
Locational
Running
Annual
Average
MUST
BE
AT
OR
BELOW
COMPLIANCE
LEVELS
First
Quarter
Second
Quarter
Third
Quarter
Fourth
Quarter
Locational
Running
Annual
Average
MUST
BE
AT
OR
BELOW
COMPLIANCE
LEVELS
First
Quarter
Second
Quarter
Third
Quarter
Fourth
Quarter
Locational
Running
Annual
Average
MUST
BE
AT
OR
BELOW
COMPLIANCE
LEVELS
First
Quarter
Second
Quarter
Third
Quarter
Fourth
Quarter
Locational
Running
Annual
Average
MUST
BE
AT
OR
BELOW
COMPLIANCE
LEVELS
Exhibit
1.3
Comparison
of
Stage
1
and
Stage
2B
DBPR
Compliance
Calculations
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
6
July
2003
Systems
will
continue
to
monitor
at
their
Stage
1
DBPR
compliance
monitoring
locations
for
the
Stage
2A
DBPR;
however,
monitoring
location
requirements
for
Stage
2B
may
change.
Exhibit
1.4
shows
the
Stage
2B
compliance
monitoring
requirements
for
100
percent
purchasing
surface
and
ground
water
systems.
For
these
systems,
monitoring
requirements
are
no
longer
based
on
the
number
of
plants,
as
was
the
case
under
the
Stage
1
DBPR;
therefore,
the
number
of
sampling
sites
may
increase
or
decrease
from
Stage
1
to
Stage
2
DBPR.
Stage
2B
compliance
monitoring
requirements
will
be
similar
to
the
Stage
1
DBPR
requirements
for
most
producing
systems.
Exhibit
1.5
shows
a
comparison
of
Stage
1
and
Stage
2B
compliance
monitoring
requirements
for
these
systems.

Because
Stage
2
DBPR
MCL
compliance
is
based
on
an
annual
average
of
DBP
measurements,
a
system
could
from
time
to
time
experience
DBP
levels
significantly
higher
than
the
MCL
(
referred
to
as
a
significant
excursion)
while
maintaining
compliance
because
the
high
concentration
levels
could
be
averaged
with
lower
concentrations.
For
this
reason,
the
Stage
2
DBPR
includes
a
provision
for
"
significant
excursions"
as
follows:

°
Systems
are
required
to
conduct
a
significant
excursion
evaluation
and
review/
discuss
the
evaluation
with
the
State/
Primacy
Agency
no
later
than
the
next
sanitary
survey.
A
significant
excursion
evaluation
must
include
an
examination
of
distribution
system
operational
practices
and
how
these
practices
may
be
modified
to
reduce
TTHM
and
HAA5
levels.

Appendix
H
provides
further
detail
on
significant
excursion
requirements.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
7
July
2003
Exhibit
1.4
Summary
of
Stage
2B
Monitoring
Requirements
for
100
Percent
Purchasing
Systems1,
Population­
Based
Approach
System
Size
(
Population
Served)
Number
of
Distribution
System
Sites2
(
by
location
type)
per
System
Total
Number
of
Sites
per
System
Monitoring
Frequency3
Existing
Stage
1
Compliance
Sites
Highest
TTHM
Highest
HAA5
Systems
Using
Surface
Water
in
Whole
or
in
Part4
<
500
­
1
1
25
Every
365
days
500
­
4,999
­
1
1
25
Every
90
days
5,000
­
9,999
­
1
1
2
Every
90
days
10,000
­
24,999
1
2
1
4
Every
90
days
25,000
­
49,999
1
3
2
6
Every
90
days
50,000
­
99,999
2
4
2
8
Every
90
days
100,000
­
499,999
3
6
3
12
Every
90
days
500,000
­
1,499,999
4
8
4
16
Every
90
days
1.5
million
­
<
5
million
5
10
5
20
Every
90
days
>
5
million
6
12
6
24
Every
90
days
Systems
Using
Only
Ground
Water
<
500
­
1
1
25
Every
365
days
500
­
9,999
­
1
1
2
Every
365
days
10,000
­
99,999
1
2
1
4
Every
90
days
100,000
­
499,999
1
3
2
6
Every
90
days
>
500,000
2
4
2
8
Every
90
days
1
100
percent
purchasing
systems
buy
or
otherwise
receive
all
of
their
finished
water
from
one
or
more
wholesale
systems
year­
round.
2
A
dual
sample
set
must
be
collected
at
each
location.
A
dual
sample
set
is
one
TTHM
and
one
HAA5
sample
that
is
taken
at
the
same
time
and
location.
3
Monitoring
frequency
is
the
approximate
number
of
days
between
monitoring
events.

4
For
the
purposes
of
this
EA,
"
surface
water"
systems
are
equivalent
to
"
subpart
H"
systems
and
include
systems
that
provide
GWUDI.
5
Only
one
location
per
system
is
required
if
the
highest
TTHM
and
HAA5
levels
occur
at
a
same
location.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
8
July
2003
Exhibit
1.5
Comparison
of
Stage
1
and
Stage
2B
DBPR
Monitoring
Requirements
for
Producing
Systems1,
Plant­
Based
Approach
System
Description
Stage
1
DBPR
Stage
2B
DBPR
Delivering
surface
water,
in
whole
or
in
part
(>
10,000)
2
°
4
sites
per
plant
(
dual
samples)
3
°
25
percent
(
1
per
plant)
at
maximum
residence
time
°
Samples
collected
quarterly
°
4
sites
per
plant
(
dual
samples)
3
!
1
representative
of
average
residence
time
from
Stage
1
DBPR
sites
!
1
representative
of
highest
HAA5
!
2
representative
of
highest
TTHM
°
Samples
collected
approximately
every
90
days
4
Delivering
surface
water,
in
whole
or
in
part
(
500
­
9,999)
2
°
1
site
per
plant
(
dual
samples)
3
°
At
maximum
residence
time
°
Samples
collected
quarterly
°
2
sites
per
plant
(
dual
samples)
3
!
1
representative
of
highest
HAA5
!
1
representative
of
highest
TTHM
If
State
determines
these
are
at
the
same
location,
monitor
at
1
site
only.
°
Samples
collected
approximately
every
90
days
4
Delivering
surface
water,
in
whole
or
in
part
(<
500)
2
°
1
site
per
plant
(
dual
samples)
3
°
At
maximum
residence
time
°
Samples
collected
annually
°
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
°
2
sites
per
plant
!
1
representative
of
highest
HAA5
!
1
representative
of
highest
TTHM
If
State
determines
these
are
at
the
same
location,
monitor
at
1
site
only.
°
Samples
collected
annually4
!
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
Delivering
only
ground
water
(>
10,000)
2
°
1
site
per
plant
(
dual
samples)
3
°
At
maximum
residence
time
°
Samples
collected
quarterly
°
2
sites
per
plant
(
dual
samples)
3
!
1
representative
of
highest
HAA5
!
1
representative
of
highest
TTHM
If
State
determines
these
are
at
the
same
location,
monitor
at
1
site
only.
°
Samples
collected
approximately
every
90
days
4
Delivering
only
ground
water
(
500
­
9,999)
2
°
1
site
per
plant
(
dual
samples)
3
°
At
maximum
residence
time
°
Sample
collected
annually
!
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
°
2
sites
per
plant
(
dual
samples)
3
!
1
representative
of
highest
HAA5
!
1
representative
of
highest
TTHM
If
State
determines
these
are
at
the
same
location,
monitor
at
1
site
only.
°
Samples
collected
annually4
!
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
Delivering
only
ground
water
(<
500)
2
°
1
site
per
plant
(
dual
samples)
3
°
At
maximum
residence
time
°
Sample
collected
annually
!
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
°
2
sites
per
plant
!
1
representative
of
highest
HAA5
!
1
representative
of
highest
TTHM
If
State
determines
these
are
at
the
same
location,
monitor
at
1
site
only.
°
Samples
collected
annually4
!
If
annual
result
exceeds
MCL,
then
must
sample
quarterly
1
Producing
systems
are
those
that
do
not
buy
100
percent
of
their
water
year­
round
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).
2
Numbers
denote
population
served.

3
A
dual
sample
set
must
be
collected
at
each
location.
A
dual
sample
set
is
one
TTHM
and
one
HAA5
sample
that
is
taken
at
the
same
time
and
location.
4
One
set
must
be
taken
during
the
peak
historical
month
for
DBP
concentrations.
4
The
compliance
deadline
for
the
Stage
1
DBPR
occurred
very
recently
(
January
2002)
for
large
and
medium
surface
water
systems
and
is
January
2004
for
small
surface
water
systems
and
all
ground
water
systems.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
9
July
2003
1.2
Document
Organization
The
rest
of
this
EA
is
organized
into
the
following
chapters:

°
Chapter
2
identifies
public
health
concerns
addressed
by
the
rule
and
provides
a
20­
year
regulatory
history
that
includes
a
description
of
relevant
National
Primary
Drinking
Water
Regulations
(
NPDWRs).
It
also
explains
the
statutory
authority
for
promulgating
the
Stage
2
DBPR
and
economic
rationale
for
choosing
a
regulatory
approach.

°
Chapter
3
characterizes
conditions
that
exist
(
including
system
inventory,
treatment,
and
water
quality
data)
before
systems
make
changes
to
meet
the
Stage
2
DBPR
requirements.
Because
of
the
timing
of
the
Stage
1
DBPR4,
EPA
had
to
predict
the
changes
in
treatment
and
water
quality
made
by
systems
as
a
result
of
the
Stage
1
DBPR
to
characterize
pre­
Stage
2
DBPR
conditions.

°
Chapter
4
reviews
alternative
regulatory
approaches
EPA
considered
during
the
development
of
the
rule
and
presents
the
rationale
for
selecting
the
Preferred
Regulatory
Alternative.

°
Chapter
5
reviews
available
epidemiological
and
toxicological
data
related
to
DBPs.
The
public
health
and
economic
benefits
of
this
rule,
as
well
as
several
sensitivity
analyses,
are
provided
in
this
chapter.

°
Chapter
6
presents
an
estimate
of
the
costs
of
implementing
the
rule
to
industry,
households,
and
States/
Primacy
Agencies.
It
also
compares
the
costs
of
the
four
regulatory
alternatives.

°
Chapter
7
presents
the
rationale
and
results
from
sensitivity
analyses
to
evaluate
uncertainties
associated
with
cost
and
benefit
estimates.

°
Chapter
8
discusses
analyses
performed
to
evaluate
the
effects
of
the
rule
on
different
segments
of
the
population,
and
considers
various
executive
orders
and
requirements,
including
the
Regulatory
Flexibility
Act
(
RFA)
and
Unfunded
Mandates
Reform
Act
(
UMRA).

°
Chapter
9
compares
the
rule's
benefits
and
costs
to
evaluate
whether
projected
benefits
exceed
costs.
The
results
for
the
Preferred
Regulatory
Alternative
are
discussed
and
compared
to
the
regulatory
alternatives
considered.

1.3
Calculations
and
Citations
This
EA
presents
results
from
detailed
and
complex
analyses.
To
help
the
reader
track
the
various
calculations
and
analyses,
the
following
are
provided:

°
A
detailed
reference
section.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
1­
10
July
2003
°
A
row
on
most
tabular
exhibits
that
gives
the
formulas
used
to
compute
the
contents
of
each
column.

°
Sources
for
elements
of
exhibits
that
are
not
calculated
in
the
exhibits
themselves.

°
Supporting
electronic
files
(
Stage
2
DBPR
cost
model;
Stage
2
DBPR
benefits
model;
Stage
2
DBPR
Surface
Water
Analytical
Tool
(
SWAT)
supporting
files).
1
For
the
purposes
of
this
document,
"
surface
water"
systems
include
subpart
H
systems
using
surface
water
or
ground
water
under
the
direct
influence
of
surface
water
(
GWUDI)
as
a
source.

Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
1
2.
Need
for
the
Proposal
2.1
Introduction
This
chapter
first
identifies
the
issue
to
be
addressed
by
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR)
(
section
2.1.1)
and
then
summarizes
in
section
2.2
the
public
health
concerns
addressed
by
the
rule.
Section
2.3
provides
the
regulatory
history
leading
up
to
the
Stage
2
DBPR,
and
section
2.4
addresses
the
economic
rationale
for
choosing
this
regulatory
approach.

2.1.1
Description
of
the
Issue
Over
51,600
community
water
systems
(
CWSs)
and
nontransient
noncommunity
water
systems
(
NTNCWS)
in
the
United
States
disinfect
their
water
(
USEPA
2001h).
These
systems
receive
water
from
either
ground
water
sources
(
wells)
or
surface
water1
sources
(
lakes,
reservoirs,
and
rivers).
Although
ground
water
systems
greatly
outnumber
surface
water
systems,
large
surface
water
systems
serve
most
people's
water
needs.
Most
water
is
not
pure
enough
to
be
safely
ingested
directly
from
the
source.
For
this
reason,
water
systems
usually
apply
some
form
of
contaminant
control.
Disinfection
is
one
important
and
widespread
(
but
not
universal)
practice
used
to
meet
the
public
health
goal
of
providing
safe
drinking
water.
Systems
often
disinfect
their
drinking
water
supplies
by
adding
chemicals
to
kill
or
inactivate
microbial
contaminants.

Chemical
disinfection,
however,
poses
health
risks
of
its
own.
Disinfection
byproducts
(
DBPs)
result
from
reactions
between
chemical
disinfectants
and
organic
and
inorganic
compounds
in
source
waters.
Some
of
these
byproducts,
including
those
that
are
the
subject
of
this
rule
(
total
trihalomethanes
(
TTHM)
and
haloacetic
acids
(
HAA5)),
are
associated
with
adverse
reproductive
and
developmental
health
effects
and
cancer.
Research
on
DBP
formation
and
DBP­
associated
health
effects
is
ongoing;
results
of
recent
research
on
the
health
risks
associated
with
DBPs
were
used
in
the
development
of
the
Stage
2
DBPR
and
are
discussed
in
Chapter
5.

Because
disinfection
reduces
risks
from
microbial
contamination,
reducing
DBPs
by
decreasing
the
concentration
of
disinfectant
or
its
contact
time
could
increase
the
risk
from
microbial
contamination.
The
Environmental
Protection
Agency's
(
EPA's)
Science
Advisory
Board
(
SAB),
an
independent
panel
established
by
Congress,
has
reported
that
microbiological
contaminants
(
e.
g.,
bacteria,
protozoa,
and
viruses)
are
likely
the
greatest
remaining
risk­
management
challenge
for
drinking
water
suppliers.
The
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR)
is
being
proposed
concurrently
with
the
Stage
2
DBPR
to
ensure
that
microbial
protection
is
not
compromised
by
efforts
to
reduce
exposure
to
DBPs.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
2
2.2
Public
Health
Concerns
to
Be
Addressed
EPA's
primary
mission
is
to
protect
human
health
and
the
environment.
In
carrying
out
this
mission,
EPA
must
often
make
regulatory
decisions
based
on
incomplete
or
uncertain
information.
The
Agency
believes
it
is
appropriate
and
prudent
to
take
action
to
protect
public
health
when
evidence
indicates
that
exposure
to
a
contaminant
could
present
significant
risks
to
the
public,
rather
than
take
no
action
until
risks
are
unequivocally
proven.
Additionally,
the
1996
Amendments
to
the
Safe
Drinking
Water
Act
(
SDWA)
require
EPA
to
address
DBP
and
microbial
risks
by
certain
statutory
deadlines.

An
important
consideration
in
assessing
public
health
risks
is
the
number
of
people
who
may
be
exposed
to
a
particular
contaminant.
Nearly
260
million
people
in
the
United
States
potentially
are
exposed
to
DBPs
via
drinking
water
because
they
are
served
by
PWSs
that
add
chemical
disinfectants
(
see
Exhibit
3.5
for
the
Stage
2
population
baseline).
While
effective
in
controlling
many
harmful
microorganisms,
chemical
disinfectants
also
form
DBPs,
some
of
which
may
pose
health
risks.
Because
of
the
large
number
of
people
potentially
exposed
to
DBPs,
EPA
is
concerned
about
any
health
risks
that
may
be
associated
with
DBPs.
Information
on
these
risks
can
come
from
two
types
of
studies
 
epidemiological
and
toxicological.

Epidemiological
studies
indicate
a
link
between
DBP
exposure
and
adverse
reproductive
and
developmental
health
effects,
particularly
early­
term
miscarriage
(
see
Chapter
5
for
discussion).
In
addition,
toxicological
studies
have
shown
that
several
DBPs
cause
adverse
reproductive
and
developmental
health
effects
in
laboratory
animals.
EPA
believes
that
these
studies
together
provide
evidence
that
DBPs
present
potential
public
health
risks
to
pregnant
women
and
their
fetuses.

Other
epidemiological
studies
have
investigated
the
relationship
between
exposure
to
chlorinated
drinking
water
and
cancer.
These
studies
suggest
an
association
between
bladder,
rectal,
and
colon
cancers
and
exposure
to
chlorinated
drinking
water.
Numerous
toxicology
studies
have
shown
several
DBPs
(
such
as
bromodichloromethane,
bromoform,
dichloroacetic
acid,
and
bromate)
to
be
carcinogenic
in
laboratory
animals
(
see
Chapter
5
for
details).

Research,
therefore,
supports
EPA's
conclusion
that
disinfected
drinking
water
may
be
a
significant
source
of
health
risk
to
the
general
public.
While
EPA
recognizes
the
uncertainties
in
the
available
data
on
health
effects
from
DBPs
and
on
the
exposure
levels
at
which
adverse
health
effects
occur,
the
Agency
believes
the
weight
of
evidence
supports
concern
for
these
potential
hazards
and
warrants
regulatory
action.

2.3
Regulatory
History
2.3.1
Statutory
Authority
for
Promulgating
the
Rule
The
primary
responsibility
for
regulating
the
quality
of
drinking
water
lies
with
EPA.
The
SDWA
establishes
this
responsibility
and
defines
the
mechanisms
at
the
Agency's
disposal
to
protect
public
health.
EPA
sets
standards
by
identifying
which
contaminants
should
be
regulated
and
by
establishing
the
maximum
levels
of
the
contaminants
allowed
in
drinking
water.

Section
1412(
b)(
1)
of
the
1996
SDWA
reauthorization
mandated
new
drinking
water
requirements.
EPA's
general
authority
to
set
Maximum
Contaminant
Level
Goals
(
MCLGs)
and
develop
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
3
the
National
Primary
Drinking
Water
Regulations
(
NPDWRs)
was
modified
to
apply
to
contaminants
that
"
may
have
an
adverse
effect
on
the
health
of
persons,"
are
"
known
to
occur
or
there
is
a
substantial
likelihood
that
the
contaminant
will
occur
in
public
water
systems
with
a
frequency
and
at
levels
of
public
health
concern,"
and
for
which,
"
in
the
sole
judgment
of
the
Administrator,
regulation
of
such
contaminant
presents
a
meaningful
opportunity
for
health
risk
reductions
for
persons
served
by
public
water
systems"
(
SDWA
1412(
b)(
1)(
A)).

To
regulate
a
contaminant,
EPA
sets
an
MCLG
at
a
level
at
which
no
known
or
anticipated
adverse
health
effects
occur.
MCLGs
are
established
solely
on
the
basis
of
protecting
public
health
and
are
not
enforceable.
EPA
simultaneously
sets
an
enforceable
Maximum
Contaminant
Level
(
MCL)
as
close
as
technologically
feasible
to
the
MCLG,
while
taking
costs
into
consideration.
If
it
is
not
feasible
to
measure
the
contaminant
at
levels
presumed
to
have
impacts
on
health,
a
treatment
technique
can
be
specified
in
place
of
an
MCL.
For
water
systems,
compliance
with
a
drinking
water
regulation
means
either
not
exceeding
the
MCL
or
meeting
treatment
technology
requirements.

Additionally,
EPA
identifies
maximum
concentrations
of
residual
disinfectants
that
can
occur
in
water
without
harming
human
health
and
sets
maximum
residual
disinfectant
level
goals
(
MRDLGs)
and
maximum
residual
disinfectant
levels
(
MRDLs).
PWSs
maintain
residual
levels
of
disinfectants
in
the
distribution
system,
following
treatment,
to
ensure
consumer
protection
from
microbial
contaminants.
Like
MCLGs,
MRDLGs
are
not
enforceable,
while
MRDLs
are.

In
addition
to
the
general
authorities
cited
above,
SDWA
1412(
b)(
2)(
C)
requires
specifically
that
EPA
promulgate
the
Stage
2
DBPR.

The
Administrator
shall
promulgate
an
Interim
Enhanced
Surface
Water
Treatment
Rule,
a
Final
Enhanced
Surface
Water
Treatment
Rule,
a
Stage
1
Disinfectants
and
Disinfection
Byproducts
Rule,
and
a
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
in
accordance
with
the
schedule
published
in
Volume
29,
Federal
Register,
Page
6361
(
February
10,
1994),
in
Table
III.
13
of
the
proposed
Information
Collection
Rule.
(
SDWA
1412(
b)(
2)(
C))

The
following
sections
summarize
the
development
of
relevant
NPDWRs
over
the
past
20
years.

2.3.2
1979
Total
Trihalomethane
Rule
Under
the
Total
Trihalomethane
Rule
(
44
Federal
Register
(
FR)
68624
November
1979),
EPA
set
an
MCL
for
TTHM,
the
sum
of
the
concentrations
of
chloroform,
bromoform,
bromodichloromethane
and
dibromochloromethane,
of
0.10
mg/
L
as
a
running
annual
average
(
RAA)
of
quarterly
measurements.
This
standard
applied
to
CWSs
using
surface
or
ground
water
that
served
at
least
10,000
people
and
that
added
a
disinfectant
to
the
drinking
water
during
any
part
of
the
treatment
process.
This
1979
rule
was
superseded
by
the
1998
Stage
1
DBPR
(
section
2.3.7)
with
which
CWSs
and
NTNCWSs
must
have
complied
by
January
2002.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
4
2.3.3
1989
Total
Coliform
Rule
The
Total
Coliform
Rule
(
TCR)
(
54
FR
27544
June
1989)
applies
to
all
public
water
systems
(
PWSs).
Because
monitoring
PWSs
for
every
possible
pathogenic
organism
is
not
feasible,
coliform
organisms
are
used
as
indicators
of
possible
contamination.
Coliforms
are
easily
detected
in
water
and
are
used
to
indicate
a
system's
vulnerability
to
pathogens.
In
the
TCR,
EPA
set
an
MCLG
of
zero
for
total
coliforms.
EPA
also
set
a
monthly
MCL
for
total
coliforms
and
required
testing
of
total­
coliformpositive
cultures
for
the
presence
of
E.
coli
or
fecal
coliforms.
E.
coli
and
fecal
coliforms
indicate
more
immediate
health
risks
from
sewage
or
fecal
contamination
and
are
used
as
the
indicator
of
an
acute
MCL
violation.
Coliform
monitoring
frequency
is
determined
by
population
served,
the
type
of
system
(
community
or
noncommunity)
and
the
type
of
source
water
(
GWUDI
or
ground
water).
In
addition,
the
TCR
required
sanitary
surveys
every
5
years
(
or
10
years
for
noncommunity
systems
using
disinfected
ground
water)
for
systems
that
collect
fewer
than
5
routine
total
coliform
samples
per
month
(
typically
systems
serving
fewer
than
4,100
people).

2.3.4
1989
Surface
Water
Treatment
Rule
Under
the
Surface
Water
Treatment
Rule
(
SWTR)
(
54
FR
27486
June
1989),
EPA
set
MCLGs
of
0
for
Giardia
lamblia,
viruses,
and
Legionella
and
established
requirements
for
all
PWSs
using
surface
water
or
GWUDI
as
a
source.
The
SWTR
includes
treatment
technique
requirements
for
filtered
and
unfiltered
systems
that
are
intended
to
protect
against
the
adverse
health
effects
associated
with
Giardia
lamblia,
viruses,
and
Legionella,
as
well
as
many
other
pathogenic
organisms.
These
requirements
include:

°
Maintenance
of
a
disinfectant
residual
in
water
entering
and
within
the
distribution
system.

°
Removal
or
inactivation
of
at
least
99.9
percent
(
3
logs)
of
Giardia
and
99.99
percent
(
4
logs)
of
viruses.

°
For
filtered
systems,
meeting
a
turbidity
performance
standard
for
the
combined
filter
effluent
of
5
nephelometric
turbidity
units
(
NTUs)
as
a
maximum
and
0.5
NTU
in
95
percent
of
monthly
measurements,
based
on
4­
hour
monitoring
for
treatment
plants
using
conventional
treatment
or
direct
filtration
(
with
separate
standards
for
other
filtration
technologies).
These
requirements
were
enhanced
by
the
1998
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IESWTR)
and
the
2002
Long
Term
1
Enhanced
Surface
Water
Treatment
Rule
(
LT1ESWTR).

°
Watershed
control
programs
and
other
requirements
for
unfiltered
systems.

2.3.5
1996
Information
Collection
Rule
The
Information
Collection
Rule
(
ICR)
(
61
FR
24354
May
1996)
applied
to
PWSs
serving
more
than
100,000
people.
A
more
limited
set
of
ICR
requirements
covered
ground
water
systems
serving
50,000
to
100,000
people.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
5
The
ICR
authorized
EPA
to
collect
occurrence
and
treatment
information
from
water
treatment
plants
to
help
evaluate
the
possible
need
for
changes
to
microbial
requirements
and
microbial
treatment
practices
and
to
help
evaluate
the
need
for
future
regulation
of
disinfectants
and
DBPs.
The
ICR
provided
EPA
with
information
on
the
national
occurrence
of
(
1)
chemical
byproducts
that
form
when
disinfectants
used
for
microbial
control
react
with
naturally
occurring
compounds
and
ions
present
in
source
water;
and
(
2)
disease­
causing
microorganisms
including
Cryptosporidium,
Giardia,
viruses,
and
coliform
bacteria.
The
ICR
also
mandated
the
collection
of
data
on
how
water
systems
currently
treat
for
contaminants.
The
ICR
monthly
sampling
data
provided
18
months
of
information
on
the
quality
of
the
influent
and
treated
water,
including
pH,
alkalinity,
turbidity,
temperature,
calcium,
total
hardness,
total
organic
carbon,
ultraviolet
254
(
UV)
absorbency,
bromide,
ammonia,
and
disinfectant
residual.
These
data
provide
some
indication
of
the
"
treatability"
of
the
water,
the
occurrence
of
contaminants,
and
the
potential
for
DBP
formation.
The
data
collected
under
the
ICR
are
being
analyzed
to
help
develop
the
LT2ESWTR
and
Stage
2
DBPR.

2.3.6
1998
Interim
Enhanced
Surface
Water
Treatment
Rule
The
IESWTR
(
63
FR
69478
December
1998)
enhances
the
1989
SWTR.
It
applies
to
PWSs
serving
at
least
10,000
people
and
using
surface
water
or
GWUDI
as
a
source.
These
systems
began
compliance
with
the
IESWTR
in
January
2002.
The
purpose
of
the
IESWTR
is
to
improve
control
of
the
protozoan
Cryptosporidium
and
to
address
tradeoffs
between
the
risks
of
microbial
pathogens
and
those
of
DBPs.
The
requirements
and
guidelines
include:

°
An
MCLG
of
zero
for
Cryptosporidium.

°
Removal
of
99
percent
(
2
logs)
of
Cryptosporidium
for
systems
that
use
filters.

°
For
filtered
systems,
a
turbidity
performance
standard
for
the
combined
filter
effluent
of
1
NTU
as
a
maximum
and
0.3
NTU
as
a
minimum
in
95
percent
of
monthly
measurements,
based
on
4­
hour
monitoring
for
treatment
plants
using
conventional
treatment
or
direct
filtration.

°
Continuous
monitoring
of
individual
filter
effluent
in
conventional
and
direct
filtration
plants
and
recording
turbidity
readings
every
15
minutes
when
these
filters
are
on­
line.

°
A
disinfection
benchmark
to
assess
the
level
of
microbial
protection
provided
before
facilities
change
their
disinfection
practices
to
meet
the
requirements
of
the
Stage
1
DBPR.

°
Inclusion
of
Cryptosporidium
in
the
definition
of
GWUDI
and
in
the
watershed
control
requirements
for
unfiltered
PWSs.

°
Covers
for
all
new
finished
water
storage
facilities.

°
A
primacy
provision
that
requires
States
to
conduct
sanitary
surveys
for
all
surface
water
systems,
including
those
serving
fewer
than
10,000
people.

The
IESWTR
was
promulgated
concurrently
with
the
Stage
1
DBPR
so
that
systems
could
coordinate
their
response
to
the
risks
posed
by
DBPs
and
microbial
pathogens.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
6
2.3.7
1998
Stage
1
Disinfectants
and
Disinfection
Byproducts
Rule
The
Stage
1
DBPR
(
63
FR
69390
December
1998)
applies
to
all
CWSs
and
NTNCWSs
that
add
a
chemical
disinfectant
to
their
water.
Certain
requirements
designed
to
provide
protection
against
acute
health
effects
from
chlorine
dioxide
also
apply
to
transient
noncommunity
water
systems
(
TNCWSs).
Compliance
for
surface
water
and
GWUDI
systems
serving
at
least
10,000
people
began
in
January
2002.
Surface
water
and
GWUDI
systems
serving
fewer
than
10,000
people
and
all
ground
water
systems
must
comply
by
January
2004.

The
Stage
1
DBPR
sets
MRDLGs
for
chlorine
(
4
mg/
L
as
chlorine
(
Cl
2)),
chloramines
(
4
mg/
L
as
Cl
2),
and
chlorine
dioxide
(
0.8
mg/
L
as
ClO
2);
and
MCLGs
for
bromodichloromethane
(
0
mg/
L),
bromoform
(
0
mg/
L),
dibromochloromethane
(
0.06
mg/
L),
dichloroacetic
acid
(
0
mg/
L),
trichloroacetic
acid
(
0.3
mg/
L),
bromate
(
0
mg/
L),
and
chlorite
(
0.8
mg/
L).
The
rule
sets
MRDLs
for
chlorine
(
4
mg/
L
as
Cl
2),
chloramines
(
4
mg/
L
as
Cl
2),
and
chlorine
dioxide
(
0.8
mg/
L
as
ClO
2);
and
MCLs
for
TTHM
(
0.080
mg/
L),
HAA5
(
0.060
mg/
L),
bromate
(
0.010
mg/
L),
and
chlorite
(
1.0
mg/
L).
The
MRDLs
and
MCLs,
except
those
for
chlorite
and
chlorine
dioxide,
are
calculated
as
RAAs.
For
conventional
surface
water
and
GWUDI
systems,
a
treatment
technique
 
enhanced
coagulation/
softening
 
is
specified
for
the
removal
of
DBP
precursors.

As
noted
in
section
2.3.6,
the
Stage
1
DBPR
was
promulgated
concurrently
with
the
IESWTR
to
coordinate
the
control
of
DBPs
and
microbial
contaminants.

2.3.8
2000
Proposed
Ground
Water
Rule
The
proposed
Ground
Water
Rule
(
65
FR
30194
May
2000)
addresses
fecal
contamination
in
ground
water
systems.
It
also
builds
on
the
TCR
through
provisions
based
on
further
evaluation
of
E.
coli
monitoring
results
measured
under
the
TCR.
Key
components
of
the
approach
for
protection
of
ground
water
included
in
the
proposed
rule
are:

°
Sanitary
surveys
for
all
ground
water
systems.

°
Hydrogeologic
sensitivity
assessments
to
identify
ground
water
sources
that
are
susceptible
to
fecal
contamination.

°
Source
water
monitoring
for
an
indicator
of
fecal
contamination
for
systems
drawing
from
sensitive
ground
water
sources.

°
Correction
of
significant
deficiencies
and
fecal
contamination
by
eliminating
the
source
of
contamination,
correcting
the
deficiency,
providing
an
alternative
source
of
water,
or
providing
inactivation
and/
or
removal
of
99.99
percent
(
4
logs)
of
viruses.

°
Compliance
monitoring
to
ensure
that
disinfection
treatment
is
reliably
operated
when
it
is
used.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
7
2.3.9
2001
Arsenic
Rule
The
Arsenic
Rule
(
66
FR
6976
January
2001)
increases
the
level
of
public
health
protection
against
exposure
to
arsenic
in
drinking
water.
The
rule
revises
the
MCL
for
arsenic
in
drinking
water
from
0.05
mg/
L
to
0.01
mg/
L
and
sets
an
MCLG
of
0
mg/
L
for
all
CWSs
and
NTNCWSs.
Clarification
on
how
compliance
is
demonstrated
for
many
inorganic
and
organic
contaminants
in
drinking
water
is
also
given.
All
existing
CWSs
and
NTNCWSs
must
comply
with
the
Arsenic
Rule
by
January
23,
2006.

2.3.10
2001
Filter
Backwash
Recycling
Rule
The
Filter
Backwash
Recycling
Rule
(
FBRR)
(
66
FR
31086
June
2001)
regulates
systems
that
return
filter
backwash
to
the
treatment
process.
The
rule
applies
to
surface
water
and
GWUDI
systems
that
use
direct
or
conventional
filtration
and
recycle
spent
filter
backwash
water,
sludge
thickener
supernatant,
or
liquids
from
dewatering
processes.
The
rule
requires
that
these
recycled
liquids
be
returned
to
a
location
such
that
all
steps
of
a
system's
conventional
or
direct
filtration
are
employed.
The
rule
also
requires
systems
to
notify
the
State
that
they
practice
recycling.
Finally,
systems
must
collect
and
maintain
information
for
review
by
the
State.

2.3.11
2002
Long
Term
1
Enhanced
Surface
Water
Treatment
Rule
The
LT1ESWTR
(
67
FR
1812
January
2002)
enhances
the
1989
SWTR
requirements
for
small
systems.
LT1ESWTR
enhances
control
of
Cryptosporidium
and
other
disease­
causing
microbes
for
surface
water
and
GWUDI
systems
that
serve
fewer
than
10,000
people.
Key
provisions
in
the
LT1ESWTR
are
very
similar
to
those
for
the
IESWTR,
but
provide
additional
flexibility
for
small
systems.

2.3.12
2002
Proposed
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
To
be
made
final
in
concert
with
the
Stage
2
DBPR,
the
LT2ESWTR
strengthens
control
of
Cryptosporidium,
and
applies
to
all
PWSs
that
use
surface
water
or
GWUDI
as
a
source.
It
incorporates
system­
specific
treatment
requirements
based
on
a
"
Microbial
Framework"
approach
that
targets
high­
risk
systems.
This
approach
involves
assigning
systems
to
different
categories
(
or
"
bins")
based
on
the
levels
of
Cryptosporidium
found
in
the
source
water.
Additional
treatment
requirements,
if
any,
are
linked
to
the
level
of
Cryptosporidium.
A
system
will
choose
technologies
and
management
practices
from
a
"
toolbox"
of
options
appropriate
to
its
bin.

Medium
and
large
systems
(
serving
at
least
10,000
people)
that
filter
will
be
required
to
conduct
Cryptosporidium
source
water
monitoring
for
24
months
(
beginning
on
the
date
of
rule
promulgation)
to
determine
their
bin
classification.
Source
water
monitoring
for
small
systems
(
serving
fewer
than
10,000
people)
that
filter
will
begin
2
years
after
the
large
and
medium
systems
initiate
source
water
Cryptosporidium
monitoring.

In
addition
to
requirements
for
filtered
systems,
the
LT2ESWTR
will
require
unfiltered
systems
to
continue
to
meet
the
filtration
avoidance
criteria
under
the
1989
SWTR
and
provide
inactivation
at
4
logs
(
99.99
percent)
for
virus,
3
logs
(
99.9
percent)
for
Giardia,
and
2
to
3
logs
(
99
to
99.9
percent)
for
Cryptosporidium.
Building
on
the
SWTR
requirements,
inactivation
requirements
for
unfiltered
systems
subject
to
the
LT2ESWTR
must
be
met
using
a
minimum
of
two
disinfectants.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
8
Also,
the
LT2ESWTR
will
require
systems
with
uncovered
finished
water
reservoirs
to
cover
the
reservoirs
or
treat
reservoir
discharge
to
the
distribution
system
to
achieve
4­
log
virus
inactivation,
unless
the
Primacy
Agency
determines
that
existing
risk
mitigation
is
adequate.

2.4
Economic
Rationale
This
section
addresses
the
economic
rationale
for
choosing
a
regulatory
approach.
Such
a
rationale
is
required
by
Executive
Order
Number
12866,
Regulatory
Planning
and
Review
(
USEPA
1993),
which
states:

[
E]
ach
agency
shall
identify
the
problem
that
it
intends
to
address
(
including,
where
applicable,
the
failures
of
the
private
markets
or
public
institutions
that
warrant
new
agency
action)
as
well
as
assess
the
significance
of
that
problem.
(
Section
1,
b(
1))

In
addition,
Office
of
Management
and
Budget
(
OMB)
guidance
dated
January
11,
1996,
states
that
"
in
order
to
establish
the
need
for
the
proposed
action,
the
analysis
should
discuss
whether
the
problem
constitutes
a
significant
market
failure"
(
USEPA
1996b).

In
a
perfectly
competitive
market,
prices
and
quantities
are
determined
solely
by
the
aggregated
decisions
of
buyers
and
sellers.
Such
a
market
occurs
when
many
producers
of
a
product
are
selling
to
many
buyers,
and
both
producers
and
consumers
have
perfect
information
on
the
characteristics
and
prices
of
each
firm's
products.
Barriers
to
entry
in
the
industry
cannot
exist,
and
individual
buyers
and
sellers
must
be
"
price
takers";
i.
e.,
their
individual
decisions
cannot
affect
the
price.
Several
properties
of
the
public
water
supply
do
not
satisfy
the
conditions
for
a
perfectly
competitive
market
and,
thus,
lead
to
market
failures
that
require
regulation.

First,
many
water
systems
are
natural
monopolies.
A
natural
monopoly
exists
when
it
is
impossible
for
more
than
one
firm
in
each
area
to
recover
the
costs
of
production
and
survive.
There
are
high
fixed
costs
associated
with
reservoirs
and
wells,
transmission
and
distribution
systems,
treatment
plants,
and
other
facilities.
For
other
potential
suppliers
to
enter
the
market,
they
would
have
to
provide
the
same
extensive
infrastructure
to
realize
similar
economies
of
scale
and
be
competitive.
A
splitting
of
the
market
with
increased
fixed
costs
(
for
example,
two
supplier
networks
in
a
single
market)
usually
makes
this
situation
unprofitable
for
one
or
both
suppliers.
The
result
is
a
market
suitable
for
a
single
supplier
and
one
that
is
hostile
to
alternative
suppliers.
In
such
natural
monopolies,
suppliers
have
fewer
incentives
for
providing
high­
quality
services
or
maintaining
competitive
prices.
In
these
situations,
governments
often
intervene
to
help
protect
the
public
interest.

Because
PWSs
are
legal,
as
well
as
natural,
monopolies,
they
often
are
subject
to
price
controls,
if
not
outright
public
ownership.
While
customers
may
demand
improvements
in
water
quality,
the
regulatory
regime
may
not
transmit
that
demand
to
the
water
supplier
or
allow
the
supplier
to
raise
its
price
to
recover
the
cost
of
the
improvements.
If
consumers
do
not
believe
that
their
drinking
water
is
safe
enough,
they
cannot
simply
switch
to
another
water
utility.
Other
options
for
obtaining
safe
drinking
water
(
e.
g.,
buying
bottled
water
or
installing
point­
of­
use
filtration)
most
often
cost
consumers
more
than
the
purchase
from
public
water
supplies.
Therefore,
the
water
supplier
may
have
little
incentive
to
improve
water
quality.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
2­
9
Second,
the
public
may
not
understand
the
health
and
safety
issues
associated
with
drinking
water
quality.
Understanding
the
health
risks
potentially
posed
by
trace
quantities
of
drinking
water
contaminants
involves
analysis
and
synthesis
of
complex
toxicological
and
health
sciences
data.
Therefore,
the
public
may
not
be
aware
of
the
risks
it
faces.
EPA
has
implemented
a
Consumer
Confidence
Report
Rule
(
CCR)
(
63
FR
44512
August
1998)
that
makes
water
quality
information
more
easily
available
to
consumers.
This
rule
requires
CWSs
to
publish
an
annual
report
on
local
drinking
water
quality.
Consumers,
however,
still
have
to
analyze
this
information
for
its
health
risk
implications.
Even
if
informed
consumers
are
able
to
engage
water
systems
in
a
dialogue
about
health
issues,
the
transaction
costs
of
such
interaction
(
measured
in
personal
time
and
monetary
outlays)
present
another
significant
impediment
to
consumer
expression
of
risk
reduction
preferences.

SDWA
regulations
are
intended
to
provide
a
level
of
protection
from
exposure
to
drinking
water
contaminants.
The
regulations
set
minimum
performance
requirements
to
protect
consumers
from
exposure
to
contaminants.
They
are
not
intended
to
restructure
market
mechanisms
or
to
establish
competition
in
supply;
rather,
they
establish
the
level
of
service
to
be
provided
that
best
reflects
public
preference
for
safety.
The
federal
regulations
reduce
the
high
information
and
transaction
costs
by
acting
on
behalf
of
consumers
in
balancing
risk
reduction
and
the
social
costs
of
achieving
this
risk
reduction.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
1
July
2003
3.
Baseline
Conditions
3.1
Introduction
To
quantify
the
effects
of
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR),
it
is
necessary
to
have
a
baseline
against
which
to
compare
the
set
of
regulatory
alternatives.
The
baseline
is
a
characterization
of
the
industry
and
its
operations
under
the
conditions
expected
to
exist
before
systems
make
changes
to
meet
requirements
of
the
Stage
2
DBPR.
The
baseline
allows
a
consistent
comparison
of
public
health
impacts
(
developed
in
Chapter
5)
and
the
economic
and
financial
impacts
(
developed
in
Chapters
6
and
8)
of
each
regulatory
alternative.

The
appropriate
baseline
for
assessing
the
impacts
of
Stage
2
would
be
conditions
following
implementation
of
Stage
1.
However,
the
compliance
deadline
for
the
Stage
1
DBPR
occurred
only
very
recently
(
January
2002)
for
large
and
medium
surface
water
systems
and
will
not
arrive
until
January
2004
for
small
surface
water
systems
and
all
ground
water
systems.
Therefore,
the
Environmental
Protection
Agency
(
EPA)
had
to
predict
treatment
and
disinfection
byproduct
(
DBP)
occurrence
conditions
resulting
from
the
Stage
1
DBPR
rather
than
use
observed
conditons.
These
predictions
are
not
necessarily
the
same
as
those
made
in
the
Regulatory
Impact
Analysis
for
the
Stage
1
Disinfectants/
Disinfection
Byproducts
Rule
(
USEPA
1998a)
because
new
data
and
a
new
model,
the
Surface
Water
Analytical
Tool
(
SWAT)
(
USEPA
2000a),
are
now
available
to
make
better
estimates.
Making
new
predictions
for
the
Stage
1
DBPR
in
this
Economic
Analysis
(
EA)
is
consistent
with
the
overall
purpose
of
the
two­
staged
rulemaking
process
 
to
develop
an
initial
rule
(
Stage
1
DBPR)
while
gathering
more
information
on
treatment
processes
and
DBP
and
microbial
occurrences
and
assessing
the
need
for
further
rules.

Development
of
the
pre­
Stage
2
baseline
(
i.
e.,
conditions
following
the
Stage
1
DBPR)
consists
of
the
following
processes:

°
Compiling
an
industry
profile
 
identifying
and
collecting
information
on
the
segment(
s)
of
the
water
supply
industry
subject
to
the
Stage
2
DBPR.

°
Characterizing
influent
water
quality
 
summarizing
the
relevant
characteristics
of
the
raw
water
treated
by
the
industry.

°
Characterizing
treatment
for
the
Stage
1
DBPR
 
predicting
what
the
industry
will
do
to
comply
with
the
provisions
of
the
Stage
1
DBPR.

°
Predicting
finished
water
DBP
occurrence
following
the
Stage
1
DBPR
 
estimating
what
the
water
quality
will
be
after
the
Stage
1
DBPR
is
implemented.

Sections
3.2
and
3.3
describe
the
data
sources
used
to
characterize
the
baseline
and
the
predictive
tools
used
to
evaluate
changes
in
treatment
technologies
and
water
quality
for
different
regulatory
alternatives.
Section
3.4
characterizes
the
water
industry,
including
the
baseline
estimates
of
systems,
treatment
plants,
and
population
subject
to
the
Stage
2
DBPR.
Influent
water
quality
is
summarized
in
section
3.5,
and
section
3.6
describes
the
types
of
treatment
technologies
used
by
systems.
Treated
water
quality,
as
it
relates
to
both
the
pre­
Stage
1
baseline
(
observed
data)
and
the
pre­
Stage
2
1
Throughout
this
document,
the
acronym
"
SDWIS/
FED"
is
shortened
to
"
SDWIS."

2
All
industry
baseline
data
reflects
revisions
to
SDWIS
4th
Quarter
Year
2000
Freeze
to
account
for
reporting
errors
in
Massachusetts
and
Montana.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
2
July
2003
baseline
(
modeled
data),
is
presented
in
section
3.7.
Lastly,
section
3.8
itemizes
and
estimates
the
effects
of
uncertainties
in
the
baseline
analysis.

This
chapter
presents
an
analysis
at
a
level
of
detail
and
precision
appropriate
to
support
subsequent
analyses
and
regulatory
decisions
for
the
Stage
2
DBPR.
Therefore,
it
does
not
give
an
exhaustive
review
of
the
water
supply
industry,
source
waters,
or
industry
practices.

3.2
Data
Sources
Several
data
sources
were
used
to
characterize
the
baseline
and
to
predict
changes
in
treatment
technologies
and
water
quality
for
different
regulatory
alternatives.
The
Safe
Drinking
Water
Information
System­
Federal
Version
(
SDWIS/
FED1)
data
(
4th
Quarter
Freeze
Year
2000
data2)
is
used
to
create
system
and
population
baselines
(
USEPA
2000d).
SDWIS
is
EPA's
national
regulatory
compliance
database
for
the
drinking
water
program.
It
includes
information
on
the
nation's
170,000
public
water
systems
(
PWSs)
and
on
violations
of
drinking
water
regulations.
Refer
to
EPA's
website
for
more
information
on
SDWIS
(
http://
www.
epa.
gov/
safewater/
sdwisfed/
sdwis.
htm).
A
second
key
source
of
data
used
to
develop
the
industry
profile
is
the
Third
Edition
of
the
Water
Industry
Baseline
Handbook
(
Baseline
Handbook)
(
USEPA
2001h)
published
in
May
2001,
which
compiles
data
derived
from
the
1995
Community
Water
System
Survey
(
CWSS)
and
SDWIS.
The
1995
CWSS
was
a
mail
survey
that
covered
ground
and
surface
water
systems
of
all
sizes
(
based
on
population
served).
The
survey
was
based
on
a
two­
phase,
stratified
sample
design.
Phase
1
was
a
telephone
screening
survey
that
provided
a
sampling
frame
for
the
main
data
collection
in
Phase
2.
The
survey
sample
in
Phase
2
was
stratified
according
to
water
system
size
(
residential
population
served),
ownership
(
public,
private,
or
ancillary),
and
primary
water
source
(
ground
or
surface).
A
total
of
3,681
systems
covering
a
range
of
source
water
types
and
system
sizes
were
randomly
selected
to
receive
the
main
survey
questionnaire.
Of
these,
1,980
systems
responded.
See
the
EPA
Report,
"
Community
Water
System
Survey,
Volume
2"
(
USEPA
1997),
for
more
information
on
the
1995
CWSS
sample
design
and
data
evaluation.

EPA
also
used
the
December
2000
document,
"
Geometries
and
Characteristics
of
Water
Systems
Report"
(
Model
Systems
Report)
(
USEPA
2000c).
In
this
document,
EPA
analyzed
1995
CWSS
data
to
develop
equations
relating
flow
and
population,
among
other
things.

The
data
source
providing
the
most
comprehensive
information
on
influent
water
quality,
treatment
processes,
and
finished
water
quality
came
from
the
1996
Information
Collection
Rule
(
ICR),
which
applied
to
all
PWSs
serving
at
least
100,000
people,
with
a
more
limited
set
of
ICR
requirements
pertaining
to
ground
water
systems
serving
50,000
to
100,000.
The
purpose
of
the
ICR
was
to
collect
DBP
and
microbial
occurrence
and
treatment
information
to
help
evaluate
the
need
for
microbial
and
DBP
rules.
The
ICR
gathered
plant­
level
sets
of
data
from
approximately
300
water
systems
over
18
months
(
July
1997
 
December
1998).
These
data
characterize
the
source
waters
and
the
water
quality
at
each
step
in
the
treatment
process
and
at
points
in
the
distribution
system.
The
water
quality
data
include
information
about
the
DBPs
formed
when
chemical
disinfectants
react
with
naturally
occurring
3
Although
the
language
in
EPA
rules
generally
does
not
include
systems
serving
exactly
10,000
people
in
the
"
small"
category,
this
document
places
them
in
the
small
category
to
be
consistent
with
the
system
and
population
data
categories
from
the
Baseline
Handbook.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
3
July
2003
compounds
present
in
source
water.
In
addition,
the
ICR
collected
treatment
and
process
train
data
that
were
used
in
the
predictive
analyses
described
in
this
chapter.

The
American
Water
Works
Association
(
AWWA)
submitted
several
comments
in
response
to
the
proposed
Stage
1
DBPR
that
underscore
the
necessity
of
the
ICR
in
developing
the
Stage
2
DBPR.
AWWA
stated,
"
Promulgation
of
the
Stage
2
D/
DBPR
and
LT2ESWTR
[
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule]
is
contingent
upon
completion
of
necessary
health
effects
research
and
analysis
of
the
ICR
data"
(
USEPA
1998m)
and
"
AWWA
believes
that
the
data
from
both
the
ICR
and
complimentary
research
will
ensure
that
a
scientific
database
will
be
created
to
make
important
and
cost
effective
decisions
on
the
direction
of
both
the
final
ESWTR
and
Stage
2
of
the
D/
DBPR"
(
USEPA
1997e).
In
addition,
AWWA
concurred
with
the
appropriateness
of
the
phased
approach
to
allow
for
analysis
of
ICR
data
in
its
comments
on
the
1994
rule
versions.
Comments
on
the
1994
rule
from
AWWA
explain
that
data
collected
through
the
ICR
would
be
used
to
determine
the
occurrence
of
DBPs
and
DBP
precursors
as
well
as
treatment
capabilities
associated
with
DBP
control
in
developing
the
Stage
2
DBPR
(
USEPA
1994a).

For
medium
systems
(
serving
10,001
to
100,000
people)
and
small
systems
(
serving
10,000
or
fewer
people),
several
additional
data
sources
were
used
to
characterize
the
source
water
and
finished
water
quality:
3
°
ICR
Supplemental
Surveys
°
The
National
Rural
Water
Association
(
NRWA)
Survey
°
The
Ground
Water
Supply
Survey
°
Small
surface
and
ground
water
plant
data
collected
by
various
States
(
several
States
provided
DBP
data
to
EPA)

°
The
Water
Utility
Database
(
WATER:\
STATS,
AWWA
2000)

Data
from
these
sources
were
also
used
to
help
predict
changes
in
treatment
technologies
to
comply
with
regulatory
alternatives.
These
data
are
presented
in
detail
in
the
Stage
2
Occurrence
Assessment
for
Disinfectants
and
Disinfection
Byproducts
(
D/
DBPs)
(
Occurrence
Assessment)
(
USEPA
2003l).

3.3
Predictive
Tools
for
Analysis
To
develop
the
pre­
Stage
2
baseline,
EPA
must
predict
what
treatment
changes
will
be
made
by
systems
to
comply
with
the
Stage
1
DBPR
and
the
resulting
changes
in
DBP
concentrations
from
observed,
pre­
Stage
1
data
sets.
EPA
developed
a
model
(
SWAT)
that
served
as
the
primary
tool
for
predicting
treatment
changes
and
DBP
occurrence
resulting
from
both
the
Stage
1
DBPR
and
Stage
2
DBPR
regulatory
alternatives.
SWAT
uses
a
series
of
algorithms
and
decision
rules
to
predict
the
type
of
treatment
a
large
surface
water
plant
will
use
and
the
resulting
DBP
occurrence,
given
a
specific
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
4
July
2003
regulatory
alternative
and
source
water
quality
based
on
ICR
data.
An
additional
description
of
SWAT
is
provided
in
section
3.3.1,
Appendix
A,
and
the
SWAT
Operations
Manual
(
USEPA
2000a).

Because
of
limitations
in
observed
data,
the
SWAT
model
could
not
be
used
directly
for
large
ground
water
systems
or
any
medium
and
small
systems.
For
large
ground
water
systems,
a
Delphi
Poll
Process
(
a
method
based
on
expert
opinion)
was
used
to
determine
ground
water
system
impacts
(
Appendix
B
provides
additional
description
of
this
process).
This
process
consisted
of
a
group
of
industry
experts
who
provided
their
best
professional
judgement
to
identify
likely
technologies
for
affected
plants.
The
expert
opinions
were
consolidated
for
a
best
estimate
of
the
technology
selection
response
of
compliance
impacted
systems.
This
provided
a
compliance
forecast
for
a
given
regulatory
option.

The
results
of
the
analyses
from
SWAT
and
the
Delphi
processes
were
extrapolated
to
the
medium
surface
and
ground
water
systems
based
on
analysis
of
source
water
treatment
characteristics
and
treatment
decision
trees
(
described
in
more
detail
in
Appendices
A
and
B).
For
the
small
surface
and
ground
water
systems
analyses,
predicted
treatment
changes
were
extrapolated
from
large­
system
results
by
a
group
of
experts.
Exhibit
3.1
summarizes
which
tools
were
used
to
predict
treatment
changes
for
various
systems
sizes.

Exhibit
3.1
Tools
Used
to
Predict
Treatment
Changes
System
Size
(
Population
Served)
Source
Water
Category
Surface
Water
Disinfecting
Ground
Water
Large
(>
100,000
people)
SWAT
Ground
Water
Delphi
Poll
Medium
(
10,001
to
100,000
people)
Extrapolation
from
SWAT
Extrapolation
from
large
ground
water
system
results
Small
(<
10,000
people)
Extrapolation
from
SWAT,
through
small
surface
water
system
review
process
Extrapolation
from
large
ground
water
system
results,
through
small
ground
water
system
expert
review
process
3.3.1
The
Surface
Water
Analytical
Tool
SWAT
was
designed
to
provide
answers
to
two
broad
questions:

°
What
technologies
will
large
surface
water
treatment
plants
implement
(
given
a
predetermined
least­
cost
decision
tree)
to
comply
with
a
defined
set
of
disinfection
and
DBP
compliance
criteria?

°
What
is
the
predicted
finished
and
delivered
water
quality
(
particularly
DBP
levels)
produced
by
large
surface
water
treatment
plants
after
implementation
of
a
range
of
technologies
for
a
given
set
of
disinfection
criteria?
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
5
July
2003
Inputs
(
e.
g.,
MCL
Criteria)

Treatment
Plants
and
Water
Quality
(
ICR
Data)

Modified
Plants
and
Selected
Outputs
(
e.
g.,
DBP
Levels)
User
Interface
ICR
Auxiliary
Database
8
Water
Treatment
Plant
Model
Decision
Tree
Program
SWAT
has
four
major
components
(
Exhibit
3.2a),
including:

°
ICR
Auxiliary
Database
8
(
AUX8)
­
It
is
a
Microsoft
Access
 
database
that
contains
both
inputs
and
outputs
of
the
SWAT
program.
Inputs
include
ICR
influent
water
quality
and
plant
process
train
data.
Outputs
consist
of
technologies
predicted
for
compliance,
treated
water
quality,
and
modified
process
train
data.

°
Decision
Tree
Program
 
This
part
of
SWAT
determines
how
a
treatment
plant
is
modified
to
comply
with
defined
regulatory
alternatives.
First,
the
program
determines
if
an
individual
plant
can
be
modified
using
the
least
expensive
(
and
typically
least
effective)
technology
to
comply
with
the
regulatory
alternative.
If
not,
the
program
moves
to
the
next
lowest­
cost
technology.
This
process
continues
until
the
plant
achieves
compliance.
The
program
receives
inputs
from
the
database
(
AUX8),
and
uses
the
Water
Treatment
Plant
Model
(
described
in
the
next
bullet)
to
estimate
treated
water
quality
before
and
after
predicted
treatment
changes,
and
sends
results
back
to
the
database.

°
Water
Treatment
Plant
Model
 
This
model
is
the
main
predictive
component
of
SWAT.
It
generates
predictions
of
treated
water
quality
(
e.
g.,
DBP
levels)
for
the
water
treatment
process
trains
defined
by
the
Decision
Tree
Program.
Predictive
modules
of
the
model
were
calibrated
using
the
central
tendency
of
the
ICR
data.

°
User
Interface
 
A
Windows
 
interface
enables
the
user
to
specify
the
disinfection
and
DBP
criteria,
as
well
as
numerous
other
assumptions
for
a
SWAT
run.

Exhibit
3.2a
SWAT
Components
4
Empirical
equations
are
used
to
estimate
DBP
formation
based
on
residence
time
(
see
Appendix
A
for
discussion
of
these
equations).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
6
July
2003
The
Water
Treatment
Plant
Model
and
the
Decision
Tree
Program
work
together
to
predict
DBP
occurrence
levels
and
treatment
plant
modifications.
The
Water
Treatment
Plant
Model
computes
DBP
concentrations
that
reflect
the
treatment
process
train
for
a
plant,
influent
water
quality
characteristics,
and
specific
treatment
constraints.
The
DBP
concentrations
are
predicted
for
two
distribution
system
conditions
 
maximum
water
residence
time
and
average
water
residence
time.
4
If
the
DBP
concentrations
do
not
meet
regulatory
constraints
at
the
average
residence
time
(
for
Stage
1)
or
at
maximum
residence
time
(
for
Stage
2),
the
Decision
Tree
Program
modifies
the
process
train
to
meet
the
specified
water
quality
objectives
using
a
least­
cost
decision
sequence.
For
the
pre­
Stage
2
DBPR
baseline
runs
(
conditions
following
implementation
of
the
Stage
1
DBPR)
and
Stage
2
DBPR
regulatory
alternative
runs,
these
criteria
are
based
on
specified
maximum
contaminant
levels
(
MCLs)
for
DBPs.
If
a
plant's
predicted
DBP
occurrence
exceeds
an
MCL,
the
Decision
Tree
Program
chooses
a
more
effective
technology
(
i.
e.,
the
next
higher­
cost
option)
in
the
decision
tree,
and
the
Water
Treatment
Plant
Model
generates
a
new
DBP
prediction.
This
selection
process
continues
until
a
selected
technology
results
in
the
plant
meeting
the
regulatory
alternative.

SWAT
was
run
using
actual
data
from
the
ICR
on
influent
water
quality,
treatment
trains,
and
related
characteristics
of
273
ICR
surface
water
plants.
All
SWAT
results
are
based
on
a
12­
month
period
using
input
data
from
months
7
 
18
(
January
1998
 
December
1998).
The
number
of
months
with
valid
data
input
varied
among
plants;
therefore,
the
output
of
SWAT
does
not
contain
12
months
of
data
for
every
plant.

Exhibit
3.2b
summarizes
the
inputs
and
outputs
used
in
the
SWAT
modeling
process.
Appendix
A
describes
the
technology
selection
process
of
the
decision
tree,
the
assumptions
contained
within
SWAT,
and
the
analysis
of
uncertainty.
For
further
programming
details,
refer
to
The
Surface
Water
Analytical
Tool
(
SWAT)
Version
1.1
 
Program
Design
and
Assumptions
(
USEPA
2000a).

3.3.2
The
Small
Surface
Water
Expert
Review
Process
Small
systems
differ
from
larger
systems
in
important
ways.
The
source
water
quality
in
small
systems
is
generally
somewhat
better
than
that
in
larger
systems,
as
shown
by
lower
TOC
levels
(
see
Appendix
A).
Unit
costs
per
volume
treated
for
new
technologies
in
small
systems
are
relatively
higher
than
those
for
larger
systems
and
may
drive
systems
to
take
different
treatment
approaches.
Finally,
small
surface
water
systems
were
exempt
from
the
1979
Total
Trihalomethane
Rule,
which
set
the
total
trihalomethane
(
TTHM)
MCL
for
all
systems
serving
at
least
10,000
people
at
100
µ
g/
L.
Because
of
these
considerations,
SWAT
predictions
based
exclusively
on
large
system
data
were
unlikely
to
characterize
smaller
systems
well.
Therefore,
EPA
developed
an
expert
review
process
to
estimate
the
impact
of
the
Stage
1
DBPR
(
for
the
pre­
Stage
2
DBPR
baseline)
and
the
Stage
2
DBPR
regulatory
alternatives
on
small
systems.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
7
July
2003
Exhibit
3.2b
SWAT
Inputs
and
Outputs
Input
data
Source
water
quality
°
pH
°
Temperature
(
average
and
annual
minimum)
°
Total
organic
carbon
(
TOC)
°
Ultraviolet254
(
UV)
absorbance
°
Bromide
°
Alkalinity
°
Hardness
(
total
and
calcium)
°
Ammonia
°
Turbidity
Treatment
plant
characteristics
°
Flow
(
average
and
peak
hourly)
°
Presence
of,
sequence
of,
and
parameters
(
e.
g.,
volumes
and
retention
times)
for
unit
processes,
including
rapid
mix,
flocculation,
settling
basin,
filtration,
contact
tank,
reservoir,
granulated
activated
carbon,
membranes,
and
ozone
chambers
°
Dosages
and
chemical
feeds
(
e.
g.,
alum,
ammonium
sulfate,
ammonia,
CO2,
NaOH,
Cl2
(
gas),
ClO2,
ferric
chloride,
lime,
ozone,
potassium
permanganate,
soda
ash,
SO2,
and
H2SO4)
°
Average
and
maximum
distribution
system
residence
times
Compliance
measures
(
DBPs)

Finished
water
concentration
°
For
each
plant,
and
for
each
month
for
which
data
are
available
for
that
plant,
the
DBP
concentration
at
the
entry
point
to
the
distribution
system
is
calculated,
reflecting
a
residence
time
of
0.
These
monthly
values
can
then
be
used
in
compliance
calculations.

Distribution
system
average
concentration
°
For
each
plant,
and
for
each
month
for
which
data
are
available
for
that
plant,
the
DBP
concentration
in
the
distribution
system
is
calculated
based
on
the
average
distribution
system
residence
time
reported
by
the
system.
These
monthly
values
can
then
be
used
in
different
compliance
calculations.

Distribution
system
maximum
concentration
°
For
each
plant,
and
for
each
month
for
which
data
are
available
for
that
plant,
the
DBP
concentration
in
the
distribution
system
is
calculated
based
on
the
maximum
distribution
system
residence
time
reported
by
the
system.
These
monthly
values
can
then
be
used
in
different
compliance
calculations.

Source:
Appendix
A.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
8
July
2003
The
process
for
estimating
the
impacts
of
the
proposed
Stage
2
DBPR
on
small
surface
water
systems
included
integrated
technical
analyses
and
predictions
from
small­
system
experts
on
anticipated
changes
in
technologies
and
the
formation
of
DBPs.
The
review
process
assembled
technical
experts
in
drinking
water,
posed
questions
and
rule
option
scenarios
to
them,
had
them
analyze
available
data,
and
then
aggregated
their
responses
for
further
analysis.
The
participating
experts
included
members
of
the
NRWA
(
a
federation
of
45
State
rural
water
associations,
representing
more
than
19,000
water
and
wastewater
utilities),
EPA
staff,
and
consulting
engineers
with
many
years
of
experience
in
small
surface
water
systems.
Before
the
review
meetings
began,
several
descriptive
analyses
were
performed
with
available
data
to
provide
information
on
source
water
characteristics
and
key
relationships
between
water
quality
and
treatment.
The
Microbial­
Disinfectants/
Disinfection
Byproducts
(
M­
DBP)
Meeting
Summaries
(
USEPA
2000p)
include
information
on
issues
discussed
by
this
group.

The
technical
experts
considered
several
constraints
on
treatment
and
disinfection
technologies
that
are
common
for
small
systems.
For
the
purposes
of
developing
compliance
forecasts
for
the
Stage
1
DBPR
and
the
Stage
2
DBPR
regulatory
alternatives,
they
applied
the
following
decision
rules:

°
Chloramines
 
It
was
assumed
that
not
all
systems
can
use
chloramines
due
to
their
operational
complexities
and
the
availability
of
staff.
Therefore,
although
100
percent
of
systems
serving
1,001
to
10,000
people
are
expected
to
be
able
to
implement
a
chloramine
addition
system,
only
75
percent
of
systems
serving
100
or
fewer
people
and
90
percent
of
those
serving
101
to
1,000
people
are
expected
to
reduce
DBP
levels
by
this
method.

°
Ozone
 
Based
on
existing
information,
this
technology
is
not
expected
to
be
used
by
very
small
systems
serving
fewer
than
100
people
because
of
its
operational
complexities.

°
Chlorine
dioxide
 
Based
on
existing
information,
this
technology
is
not
expected
to
be
used
by
very
small
systems
serving
fewer
than
100
people
because
of
its
operational
complexities.
Its
use
is
restricted
to
50
percent
of
the
SWAT­
predicted
technology
selection
for
large
systems
(
with
the
balance
going
to
UV,
ozone,
microfiltration/
ultrafiltration
(
MF/
UF)
in
proportion
for
the
101
to
1,000
category).

°
GAC
 
Small
systems
converting
to
Granular
Activated
Carbon
(
GAC)
are
more
likely
to
choose
GAC20
(
GAC
with
a
20­
minute
empty
bed
contact
time)
or
GAC20
with
advanced
disinfectants
(
ozone
with
chloramines
as
residual
disinfectant)
and
GAC
media
replacement
rather
than
on­
site
reactivation
as
compared
to
GAC10
(
GAC
with
a
10­
minute
empty
bed
contact
time)
or
GAC10
with
advanced
disinfectants
and
on­
site
reactivation,
based
on
technical
feasability
and
a
unit­
cost
analysis.

°
Microfiltration/
Ultrafiltration
(
MF/
UF)
 
A
larger
proportion
of
small
surface
water
systems
are
currently
using
MF/
UF,
as
compared
with
medium
and
large
systems.
Hence,
in
the
initial
set
of
adjustments,
the
existing
percentage
of
systems
using
MF/
UF
was
added
to
the
SWAT­
predicted
values
for
large
systems
(
in
proportion
to
the
number
of
systems
using
chlorine
or
chloramines)
(
see
Appendix
A
for
details).

For
more
details
on
assumptions
made
for
DBP
occurrence
and
treatment
technologies
for
small
surface
water
systems,
see
Appendix
A.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
9
July
2003
3.3.3
The
ICR
Ground
Water
Delphi
Poll
Process
Because
SWAT
does
not
apply
to
ground
water
systems,
the
Technical
Working
Group
(
TWG)
convened
the
ICR
Ground
Water
Delphi
Poll
Process,
composed
of
ground
water
experts.
The
mission
of
the
Delphi
Group
was
to
characterize
the
pre­
Stage
2
DBPR
baseline
and
the
Stage
2
DBPR
regulatory
alternatives
for
ground
water
systems
serving
more
than
100,000
people.
The
group
did
not
predict
DBP
occurrence.
Rather,
using
the
ICR
data,
Delphi
Group
members
estimated
the
number
of
ground
water
plants
unable
to
meet
the
MCL
standards
for
the
Stage
1
DBPR
and
each
Stage
2
DBPR
regulatory
alternative.
For
those
plants
not
complying,
each
member
selected
an
appropriate
final
technology
and
residual
disinfectant,
taking
into
account
constraints
on
technology
choice,
such
as
water
quality,
design
issues,
and
chloramine
use.
They
also
considered
the
effects
of
the
Arsenic
Rule
and
the
proposed
Ground
Water
and
Radon
Rules.
ICR
ground
water
plants
thought
to
be
blending
with
surface
water
in
the
distribution
system
were
excluded
from
the
analysis.

The
Delphi
Group
concluded
that
ground
water
systems
changing
their
treatment
would
choose
to
implement
one
or
two
of
four
technologies:
chloramines,
advanced
disinfectants,
GAC20,
or
nanofiltration
(
NF).
For
more
detail
on
the
assumptions
and
results
of
the
ground
water
Delphi
process,
see
Appendix
B.

3.3.4
The
Small
Ground
Water
Expert
Review
Process
The
DBP
occurrence
ICR
data
for
large
systems
were
inappropriate
for
use
directly
with
small
ground
water
systems
because
of
significant
differences
in
water
quality,
geography,
and
technology
use.
Therefore,
EPA
and
water
system
experts
estimated
the
Stage
2
DBPR
compliance
forecasts
for
small
ground
water
systems
by
beginning
with
compliance
forecasts
for
large
systems
and
making
adjustments
based
on
expert
knowledge
and
data
evaluation.
For
information
on
issues
discussed
by
this
group,
see
the
M­
DBP
Meeting
Summaries
(
USEPA
2000p).

The
following
key
differences
were
identified
and
used
as
the
basis
for
estimating
the
percentage
of
small
ground
water
systems
needing
to
make
changes:

°
Application
of
the
1979
TTHM
standard
(
applied
to
large,
but
not
small,
ground
water
systems)

°
Softening
use
°
TOC
concentration
in
influent
water
°
Proportion
of
systems
in
Florida
Of
these
four
factors,
one
of
the
most
significant
is
whether
a
plant
was
located
in
Florida.
The
ground
water
experts
assumed
that,
overall,
more
small
ground
water
systems
would
be
able
to
meet
the
Stage
2
DBPR
standards
than
large
ground
water
systems,
because
small
systems
have
lower
DBP
precursor
levels
(
e.
g.,
TOC,
bromide)
in
their
source
water
than
medium
or
large
systems
do.
This
is
largely
due
to
the
"
Florida
effect."
Florida
has
a
larger
proportion
of
the
nation's
large
and
medium
ground
water
supplies
than
of
the
nation's
small
ground
water
supplies.
TOC
levels
in
Florida's
ground
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
10
July
2003
water
supplies
are
much
higher
than
most
of
the
nation's
other
ground
water
supplies.
See
section
3.8
(
Regional
Differences
in
Water
Quality)
for
further
discussion
of
Florida
TOC
levels.
In
addition
to
adjustments
to
the
number
of
systems
making
treatment
changes,
adjustments
were
made
to
the
large
system
technology
selection
forecast.
As
with
large
ground
water
systems,
small
systems
had
four
technology
choices:
switching
to
chloramines
for
secondary
disinfection,
advanced
disinfection,
GAC20,
or
nanofiltration.
As
with
small
surface
water
systems,
chloramine
and
ozone
use
were
assumed
to
be
less
feasible
for
small
ground
water
systems
than
for
large
systems.
The
use
of
these
disinfectants
was
adjusted
for
each
small
system
size
category.

For
more
detail
on
the
methodology
and
results
of
the
small
ground
water
expert
review
process,
see
Appendix
B.

3.4
Industry
Profile
This
section
provides
the
water
industry
characterization
used
to
derive
costs
and
benefits
for
the
Stage
2
DBPR.
It
is
organized
as
follows:

°
Section
3.4.1
is
a
background
section
with
terminology
and
definitions
used
to
characterize
the
water
industry
baseline.
It
also
identifies
distinctions
that
are
important
for
regulatory
analysis.

°
Section
3.4.2
presents
the
baseline
numbers
of
systems,
plants,
and
population
subject
to
the
Stage
2
DBPR.

°
Section
3.4.3
presents
mean
plant
design
and
average
daily
flows.

°
Section
3.4.4
estimates
the
total
number
of
households
subject
to
the
Stage
2
DBPR.

°
Section
3.4.5
describes
uncertainties
in
the
industry
baseline
data.

3.4.1
Public
Water
System
Categorization
Categorization
of
water
systems
is
important
because
system
size,
ownership,
and
retail/
wholesale
relationships
dictate
the
way
in
which
costs
and
benefits
are
estimated.
This
section
explains
the
water
system
categories
as
defined
by
EPA's
National
Primary
Drinking
Water
Regulations
(
NPDWRs)
and
describes
further
subdivisions
according
to
water
source,
size
(
population
served),
and
ownership
for
regulatory
analysis
purposes.

PWS
Type
NPDWRs
apply
to
all
PWSs.
A
PWS
is
a
system
that
provides
water
for
human
consumption
through
pipes
or
other
constructed
conveyances
and
that
has
at
least
15
service
connections
or
regularly
serves
an
average
of
at
least
25
individuals
per
day
for
at
least
60
days
per
year.
PWSs
are
categorized
as
follows:
5
EPA
also
refers
to
the
grouping
of
surface
water
and
GWUDI
systems
as
"
subpart
H"
systems
in
the
Stage
2
DBPR
rule
language.
Surface
water
and
GWUDI
systems
are
grouped
together
because
they
fall
under
the
same
requirements
in
the
SDWA
regulations.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
11
July
2003
°
A
Community
Water
System
(
CWS)
is
a
PWS
that
has
at
least
15
service
connections
used
by
year­
round
residents
or
regularly
serves
at
least
25
year­
round
residents.

°
A
Noncommunity
Water
System
(
NCWS)
is
a
PWS
that
is
not
a
CWS.
NCWSs
are
subdivided
into
two
categories:

°
A
Nontransient
Noncommunity
Water
System
(
NTNCWS)
is
a
NCWS
that
regularly
serves
at
least
25
of
the
same
people
more
than
6
months
per
year.

°
A
Transient
Noncommunity
Water
System
(
TNCWS)
is
a
NCWS
that
does
not
regularly
serve
at
least
25
of
the
same
people
more
than
6
months
per
year.

Source
Water
Type
For
the
purposes
of
regulatory
analysis,
systems
are
typically
categorized
according
to
the
source
of
their
water.
Types
of
sources
include
surface
water
(
reservoirs,
lakes,
or
flowing
streams),
ground
water
under
the
direct
influence
of
surface
water
(
GWUDI),
ground
water
(
aquifers
not
under
the
influence
of
surface
water),
and
treated
water
that
is
purchased
from
other
systems.
For
the
purposes
of
this
document,
"
surface
water"
includes
GWUDI
sources.
5
In
SDWIS
and
the
Baseline
Handbook
(
USEPA
2001h),
systems
are
assigned
a
source
type
using
the
following
hierarchy,
in
descending
order:
Surface
Water,
Purchased
Surface
Water,
Ground
Water,
and
Purchased
Ground
Water.
The
presence
of
the
first
source
in
this
list
determines
the
source
assignment
for
that
system.
As
a
result,
all
"
mixed
systems"
(
systems
with
both
a
ground
and
surface
water
source)
are
placed
in
the
surface
water
system
category.
Based
on
an
analysis
in
the
Model
Systems
Report
(
USEPA
2000c),
it
is
estimated
that
21
percent
of
surface
water
systems
obtain
some
of
their
water
from
ground
water
sources.
Approximately
one­
third
of
these,
or
8
percent
of
all
surface
water
systems
in
SDWIS
and
the
Baseline
Handbook,
receive
the
majority
of
their
flow
from
ground
water.

Other
data
sets
classify
systems
differently.
For
example,
the
ICR
Auxiliary
Database
1
(
AUX1)
classifies
systems
that
receive
more
than
80
percent
of
their
source
water
from
surface
water
as
surface
water
systems.
Systems
that
rely
on
ground
water
for
more
than
80
percent
of
their
supply
are
considered
ground
water
systems.
Systems
that
receive
more
than
80
percent
of
their
supply
from
another
system
are
considered
purchased
water
systems.
All
other
systems
are
considered
mixed.
(
The
ICR
data
analysis,
however,
grouped
purchased
and
mixed
systems
with
surface
water
systems
[
USEPA,
2001i]).
The
1995
CWSS
data
are
classified
by
primary
source
(
the
source
that
provides
more
than
50
percent
of
average
flow
to
the
distribution
system).
In
cases
where
there
are
three
different
sources
(
e.
g.,
surface,
ground,
and
purchased),
systems
in
the
1995
CWSS
are
classified
by
the
largest
source.
6
In
this
document,
the
terms
"
consecutive"
and
"
purchased
water"
are
used
interchangeably.

7
For
the
purposes
of
this
EA,
systems
are
classified
into
one
of
two
categories
according
to
their
buying
and
selling
relationships
with
other
systems:
(
1)
100
percent
purchasing
systems
buy
or
otherwise
receive
all
of
their
finished
water
from
another
system,
(
2)
Producing
systems
do
not
buy
or
otherwise
receive
all
of
their
water
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).
These
distinctions
are
important
for
the
derivation
of
initial
distribution
system
evaluations
(
IDSE)
and
monitoring
costs
estimated
in
Appendix
G.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
12
July
2003
Ownership
Systems
are
categorized
in
SDWIS
and
in
the
Baseline
Handbook
according
to
three
ownership
types:
"
private,"
"
public,"
and
"
other."
Private
systems
are
owned
by
private
corporations
or
individuals.
Public
systems
are
owned
by
public
entities
such
as
municipalities,
counties,
or
special
districts
and
have
access
to
capital
and
means
of
financing
that
are
not
available
to
private
systems.
The
"
other"
category
contains
systems
where
ownership
is
not
reported
in
SDWIS.
These
distinctions
become
important
in
calculating
household
costs
(
see
Chapter
6)
and
in
assessing
Unfunded
Mandates
Reform
Act
(
UMRA)
requirements
(
see
Chapter
8).

Consecutive
(
or
Purchased
Water)
6
and
Wholesale
System
Types
Systems
are
typically
categorized
according
to
whether
they
treat
water
themselves
or
purchase
treated
water
from
other
systems.
The
Stage
2
DBPR
defines
a
consecutive
system
as
a
PWS
that
buys
or
otherwise
receives
some
or
all
of
its
finished
water
from
one
or
more
wholesale
systems
for
at
least
60
days
per
year.
7
A
wholesale
system
is
defined
as
a
PWS
that
treats
and
then
sells
or
otherwise
delivers
finished
water
to
another
PWS
at
least
60
days
per
year.
Treatment
modifications
are
generally
not
made
by
consecutive
water
systems,
but
are
instead
made
by
the
associated
wholesale
systems.
Costs
of
these
treatment
modifications
are
typically
passed
on
to
the
consecutive
systems
in
the
form
of
water
rate
increases.

Population
Served
The
number
of
people
served
by
systems
(
indicating
system
size)
is
a
key
parameter
used
to
calculate
benefits
and
costs
of
drinking
water
regulations.
This
EA
defines
to
two
types
of
system
populations:
the
retail
customers
of
a
system
who
buy
water
directly
from
the
system,
and
the
wholesale
customers
of
a
system
who
are
served
by
a
second
system
that
purchases
treated
water
from
the
first.
Systems
are
categorized
in
SDWIS
and
the
Baseline
Handbook
by
retail
population
served.
Systems
in
the
1995
CWSS
database
are
classified
by
total
population
(
wholesale
and
retail).

3.4.2
Systems,
Plants,
and
Population
Subject
to
the
Stage
2
DBPR
To
estimate
costs
and
benefits
attributable
to
the
Stage
2
DBPR,
EPA
has
developed
the
following
industry
baselines:

°
The
System
Baseline
(
Exhibit
3.3)
is
used
to
estimate
non­
treatment
costs
(
implementation,
IDSEs,
additional
routine
monitoring,
and
significant
excursion
evaluations).

°
The
Plant
Baseline
(
Exhibit
3.4)
is
used
to
estimate
treatment
costs
(
based
on
predictions
of
plants
changing
to
various
advanced
technologies).
8
SDWIS
federal
data
are
updated
continuously
by
States.
Each
quarter,
data
is
"
frozen"
as
of
a
certain
date.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
13
July
2003
°
The
Population
Baseline
(
Exhibit
3.5)
is
used
to
estimate
cancer
cases
avoided
as
a
result
of
the
Stage
2
DBPR
and
subsequent
monetized
benefits.

The
purpose
of
this
section
is
to
define
these
baselines
and
describe
how
they
were
derived.

3.4.2.1
System
Baseline
The
Stage
2
DBPR
applies
to
all
CWSs
and
NTNCWSs
that
add
a
primary
or
residual
disinfectant
other
than
UV
or
that
deliver
water
that
has
been
treated
with
a
primary
residual
disinfectant
other
than
UV.
The
derivation
of
the
Stage
2
DBPR
system
baseline
(
i.
e.,
the
number
of
PWSs
subject
to
the
Stage
2
DBPR)
is
presented
in
Exhibit
3.3.
Note
that
systems
in
this
exhibit
are
classified
in
one
of
two
source
water
categories:
(
1)
systems
that
provide
only
ground
water,
and
(
2)
systems
that
provide
either
all
surface
water
or
a
mix
of
surface
and
ground
water.

The
system
inventory
data
in
columns
A
through
E
represent
SDWIS
4th
Quarter
Year
2000
Freeze
data8
adjusted
for
reporting
errors
in
Massachusetts
and
Montana
(
USEPA
2000d).
This
inventory
is
reduced
by
the
percent
disinfecting
(
shown
in
column
F)
to
produce
the
Stage
2
system
baseline
shown
in
columns
G
through
K.

The
estimate
of
percent
disinfecting
in
column
F
comes
from
several
sources.
The
percent
of
ground
water
CWSs
providing
disinfection
is
derived
from
1995
CWSS
results,
as
summarized
in
Table
B1.3.3
of
the
Baseline
Handbook.
The
data
in
Table
B1.3.3
have
been
adjusted
upward
by
2
to
6
percent
to
account
for
ground
water
systems
adding
disinfection
as
a
result
of
the
proposed
Ground
Water
Rule
(
the
exact
increase
was
derived
from
data
in
Appendix
C
of
the
2000
document,
Regulatory
Impact
Analysis
for
the
Proposed
Ground
Water
Rule
[
USEPA
2000g]).
The
percent
of
ground
water
NTNCWSs
that
disinfect
was
derived
from
Ground
Water
Disinfection
and
Protective
Practices
in
the
United
States
(
USEPA
1996a),
updated
to
account
for
potential
impacts
of
the
Ground
Water
Rule
(
USEPA
2000g,
Appendix
C),
and
averaged
across
all
size
categories.
All
surface
water
systems
are
required
to
disinfect
their
water;
thus,
the
percent
disinfecting
for
surface
CWSs
and
NTNCWSs
is
100.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
14
July
2003
Public
Private
Public
Private
Public
Private
Public
Private
A
B
C
D
E=
A+
B+
C+
D
F
G=
A*
F
H=
B*
F
I=
C*
F
J=
D*
F
K=
G+
H+
I+
J
£
1
0
0
445
308
222
308
1,283
100%
445
308
222
308
1,283
101­
500
850
513
426
331
2,120
100%
850
513
426
331
2,120
501­
1,000
614
243
372
84
1,313
100%
614
243
372
84
1,313
1,001­
3,300
1,199
181
977
110
2,467
100%
1,199
181
977
110
2,467
3,301­
10,000
831
80
961
56
1,928
100%
831
80
961
56
1,928
10,001­
50,000
672
59
880
79
1,690
100%
672
59
880
79
1,690
50,001­
100,000
106
14
165
28
313
100%
106
14
165
28
313
100,001­
1
Million
60
11
176
29
276
100%
60
11
176
29
276
>
1
Million
0
0
13
0
13
100%
0
0
13
0
13
Total
4,776
1,410
4,192
1,025
11,403
­
4,776
1,410
4,192
1,025
11,403
£
1
0
0
177
130
1,227
12,162
13,696
55.5%
98
72
681
6,750
7,601
101­
500
594
225
4,471
9,322
14,612
81.0%
481
183
3,622
7,551
11,836
501­
1,000
301
86
2,904
1,382
4,673
87.5%
263
75
2,541
1,210
4,089
1,001­
3,300
324
47
4,346
984
5,701
85.4%
277
40
3,712
840
4,869
3,301­
10,000
91
13
2,125
302
2,531
90.4%
82
12
1,921
273
2,288
10,001­
50,000
36
4
1,037
171
1,248
98.7%
35
4
1,023
169
1,232
50,001­
100,000
1
0
115
21
137
94.0%
1
0
108
20
129
100,001­
1
Million
4
0
48
9
61
98.9%
4
0
47
9
60
>
1
Million
0
0
2
0
2
100.0%
0
0
2
0
2
Total
1,527
506
16,274
24,354
42,661
­
1,241
387
13,656
16,822
32,105
£
1
0
0
21
80
76
126
303
100%
21
80
76
126
303
101­
500
28
38
60
176
302
100%
28
38
60
176
302
501­
1,000
11
14
19
65
109
100%
11
14
19
65
109
1,001­
3,300
11
8
15
40
74
100%
11
8
15
40
74
3,301­
10,000
5
4
4
9
22
100%
5
4
4
9
22
10,001­
50,000
3
3
2
1
9
100%
3
3
2
1
9
50,001­
100,000
1
0
0
0
1
100%
1
0
0
0
1
100,001­
1
Million
1
0
0
0
1
100%
1
0
0
0
1
>
1
Million
0
0
0
0
0
100%
0
0
0
0
0
Total
81
147
177
416
821
­
81
147
177
416
821
£
1
0
0
11
26
1,731
8,130
9,898
37%
4
10
640
3,008
3,662
101­
500
15
19
3,179
3,880
7,093
37%
5
7
1,176
1,436
2,624
501­
1,000
5
6
1,209
717
1,937
37%
2
2
447
265
717
1,001­
3,300
4
0
365
352
721
37%
1
0
135
130
267
3,301­
10,000
4
0
21
49
74
37%
1
0
8
18
27
10,001­
50,000
2
0
9
1
12
37%
1
0
3
0
4
50,001­
100,000
0
0
1
0
1
37%
0
0
0
0
0
100,001­
1
Million
1
0
0
1
2
37%
0
0
0
0
1
>
1
Million
0
0
0
0
0
37%
0
0
0
0
0
Total
42
51
6,514
13,131
19,738
­
16
19
2,410
4,858
7,303
Grand
Total,
All
Systems
6,425
2,115
27,156
38,927
74,623
­
6,113
1,963
20,435
23,122
51,632
Sources:
(
A­
D)
System
and
population
data
are
the
inventory
derived
directly
from
SDWIS
4th
Quarter
Year
2000
Freeze
data,
adjusted
for
reporting
errors
in
Massachusetts
and
Montana
(
USEPA
2000d).
"
Other"
systems
have
been
allocated
to
the
4
categories
according
to
the
proportion
of
systems
in
those
categories.
(
F)
Percentage
of
ground
water
CWSs
that
disinfect
is
estimated
using
percentage
of
treatment
in
place
from
the
Third
Edition
of
the
Baseline
Handbook
(
Table
B1.3.3),
originally
derived
from
the
1995
CWSS.
These
percentages
were
increased
to
account
for
potential
impacts
of
the
Ground
Water
Rule
(
derived
from
Appendix
C
of
the
Ground
Water
Rule
Regulatory
Impact
Analysis
[
USEPA
2000g]).
Disinfecting
Ground
Water
Only
NTNCWSs
%
Disinfecting
System
Size
(
population
served)

Surface
Water
and
All
Mixed
NTNCWSs
Surface
Water
and
All
Mixed
CWSs
Disinfecting
Ground
Water
Only
CWSs
Purchased
Non­
Purchased
Total
No.
of
Systems
Baseline
Number
of
Systems
Subject
to
the
Stage
2
DBPR
Disinfecting,
Purchased
Disinfecting,
Non­
Purchased
Total
No.
of
Disinfecting
Systems
Exhibit
3.3
Derivation
of
the
Stage
2
DBPR
System
Baseline
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
15
July
2003
3.4.2.2
Plant
Baseline
Exhibit
3.4,
presented
at
the
end
of
this
subsection,
shows
the
derivation
of
the
baseline
number
of
treatment
plants
subject
to
the
Stage
2
DBPR
(
i.
e.,
the
plant
baseline).
The
derivation
is
described
below
in
three
steps.
Step
1
involves
modifying
the
surface
water
system
inventory
to
better
represent
the
size
and
number
of
plants
that
exist
by
"
linking"
purchasing
surface
water
systems
to
their
respective
sellers.
Only
surface
water
systems
were
modified
in
this
step
(
the
number
of
purchasing
ground
water
systems
is
such
a
small
proportion
of
all
ground
water
systems
that
linking
them
to
sellers
was
not
expected
to
change
the
characterization
of
the
ground
water
plant
baseline).
In
step
2,
the
system
inventory
was
reclassified
according
to
the
primary
source
water
type
(
i.
e.,
the
source
type
that
provides
more
than
50
percent
of
the
water
to
a
system).
The
final
step,
step
3,
involves
converting
the
system
inventory
to
a
treatment
plant
inventory
based
on
estimates
of
average
treatment
plants
per
system.

Step
1:
Modify
the
Surface
Water
System
Inventory
by
Linking
Buyers
and
Sellers
Because
population
served
is
used
directly
to
estimate
the
volume
of
water
treated,
the
type
of
system
population
reported
is
key
to
defining
an
accurate
treatment
plant
baseline.
As
noted
in
section
3.4.1,
system
populations
in
SDWIS
represent
retail
populations
only.
In
other
words,
system
populations
reported
in
SDWIS
do
not
include
the
populations
of
those
consecutive
systems
to
whom
they
sell
water
(
purchased
water
systems
are
considered
separate,
stand­
alone
systems).
More
than
half
of
the
surface
water
systems
are
consecutive,
stand­
alone
systems.
Purchased­
water
systems
comprise
a
much
lower
proportion
of
ground
water
systems
(
approximately
five
percent).

The
advantage
of
classifying
systems
by
retail
population
as
done
in
SDWIS
is
that
it
appropriately
accounts
for
both
the
total
number
of
individual
PWSs
in
the
United
States
and
the
total
population
served
by
all
of
those
systems.
However,
a
disadvantage
(
especially
for
surface
water
CWSs)
when
estimating
national
costs
of
regulations
is
that
it
does
not
directly
account
for
the
fact
that
the
water
delivered
by
the
consecutive
systems
to
their
retail
customers
is
actually
treated
by
other
systems.
It
is
important
to
recognize
that
the
total
flow
of
surface
water
is
actually
treated
by
fewer
than
half
of
the
surface
water
systems
accounted
for
in
SDWIS.
Because
of
economies
of
scale,
the
cost
of
treatment
(
in
cents
per
gallon)
is
less
for
systems
treating
larger
flows
than
it
is
for
systems
treating
smaller
flows.
For
example,
it
is
typically
more
expensive
to
build
and
operate
two
treatment
plants
serving
5,000
people
than
one
treatment
plant
serving
10,000
people.
Failing
to
account
for
the
fact
that
surface
water
is
actually
treated
in
larger
quantities
at
a
smaller
number
of
systems
than
SDWIS
suggests
could
result
in
an
upward
bias
in
national
cost
estimates
of
rules
that
affect
a
substantial
portion
of
surface
water
systems.

To
rectify
this
bias,
an
analysis
was
performed
to
"
link"
consecutive
surface
water
systems
to
their
respective
wholesale
system
using
data
from
SDWIS
(
each
purchased
system
lists
the
PWS
identification
number(
s)
for
systems
that
sell
water
to
it)
.
If
a
consecutive
system
could
be
linked
to
a
wholesaler,
that
system
was
removed
from
the
system
count
and
its
population
was
added
to
the
population
of
the
wholesale
system.

The
methodology
used
to
link
the
SDWIS
2000
system
inventory
is
described
in
detail
below:

°
If
a
system
has
multiple
sources,
(
e.
g.,
a
system
has
a
primary
source
of
surface
water
in
addition
to
a
purchased
surface
water
source),
it
was
assumed
to
be
adequately
represented
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
16
July
2003
as
a
non­
purchased
surface
water
system,
and
was
not
linked
to
its
seller
(
i.
e.,
only
100
percent
purchased
surface
water
systems
were
linked).
°
For
systems
that
purchase
water,
all
sellers
were
identified
using
SDWIS
data
(
SDWIS
has
a
data
field
that
lists
the
PWS
identification
number
(
PWSID)
for
each
seller).

°
If
a
purchased
surface
water
system
(
System
P)
purchases
all
of
its
water
from
one
nonpurchased
surface
water
system
(
System
S),
its
population
was
added
to
that
of
System
S,
and
it
was
removed
from
the
inventory
of
purchased
systems.

°
If
the
purchased
surface
water
system
buys
water
from
multiple
non­
purchased
systems,
it
was
assigned
to
the
most
directly
related
non­
purchased
seller
with
the
largest
population.
For
example,
a
purchased
system
(
System
C)
purchases
from
a
non­
purchased
system
(
System
B1)
and
a
purchased
system
(
System
B2),
which
in
turn
purchases
from
a
nonpurchased
system
(
System
A).
In
this
case,
System
C
was
linked
to
System
B1;
in
other
words,
the
population
of
System
C
was
added
to
that
of
System
B1.

°
Some
purchased
systems
have
what
is
referred
to
as
"
cascading
provider
relationships."
For
instance,
a
purchased
system,
System
C,
may
purchase
water
from
another
system,
System
B.
System
B
does
not
treat
its
own
water
but,
instead
purchases
waters
from
a
nonpurchased
system,
System
A.
For
this
analysis,
the
populations
of
both
Systems
B
and
C
were
added
to
the
population
of
System
A,
and
Systems
B
and
C
were
removed
from
the
inventory
of
purchased
systems.

°
When
the
purchased
system
and
its
seller
are
not
of
the
same
type
(
e.
g.,
a
CWS
purchasing
from
a
NTNCWS),
they
were
not
linked
and
are
counted
as
separate,
unlinked
purchased
systems.
Systems
purchasing
from
systems
of
different
ownership
type
(
e.
g.,
a
public
water
system
purchasing
from
a
private
water
system),
however,
were
linked.

°
If
the
ID
number
of
the
seller
did
not
correspond
to
an
active
water
system,
the
purchased
system
was
counted
as
a
separate,
unlinked,
purchased
system.

°
In
a
few
cases,
the
seller
could
not
be
found,
i.
e.,
a
purchased
system
(
e.
g.,
System
C)
cannot
be
linked
to
a
non­
purchased
system.
These
purchased
systems
were
counted
as
separate,
unlinked,
purchased
systems.

Results
of
the
linking
exercise
for
surface
water
CWSs
and
NTNCWSs
are
shown
in
Exhibit
3.4,
columns
A
through
E.
Note
that
the
total
number
of
disinfecting,
non­
purchased
systems
in
columns
C
and
D
is
the
same
as
the
total
number
of
non­
purchased
systems
before
linking
in
Exhibit
3.3,
columns
I
and
J.
The
inventory
has
shifted,
however,
to
higher
system
size
categories.
Also,
note
that
the
relative
numbers
of
public
and
private
systems
have
changed
slightly
because
of
how
the
systems
with
"
other"
ownership
types
are
allocated
(
they
are
allocated
proportionally
according
to
the
number
of
systems
in
the
public
and
private
categories).

As
shown
in
Exhibit
3.4,
columns
A
and
B,
there
are
approximately
2,200
purchased,
remaining
unlinked
systems
in
the
inventory.
These
include
surface
water
systems
that
could
not
be
linked
(
e.
g.,
many
surface
water
NTNCWSs
purchase
water
from
CWSs
and
were
not
be
linked),
purchased
surface
water
systems
with
a
non­
purchased
ground
water
source,
and
the
unlinked
purchased
ground
water
systems.
For
the
purposes
of
estimating
treatment
costs
in
this
EA,
EPA
includes
the
remaining
unlinked
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
17
July
2003
purchased
water
systems
in
the
system
inventory
and
evaluates
them
as
if
they
are
treating
water
themselves.
As
described
previously,
evaluating
purchased
systems
as
if
they
are
stand­
alone,
treating
systems
could
result
in
an
upward
bias
in
national
cost
estimates.
This
bias
is
greatly
reduced,
however,
by
the
linking
effort
described
in
this
step.

While
EPA
believes
that
linking
consecutive
systems
with
their
wholesalers
will
improve
the
accuracy
of
cost
estimates,
it
is
possible
that
purchased
systems
may
be
out
of
compliance
even
when
the
wholesaler
is
in
compliance,
thereby
incurring
treatment
costs
that
are
not
being
captured
by
this
approach.
EPA
believes
that
the
number
of
these
systems,
however,
is
small
and
will
not
have
a
measurable
effect
on
the
costs
or
benefits
of
the
Stage
2
DBPR.

Step
2:
Re­
classify
Systems
by
Primary
Source
Water
Type
The
characterization
of
distribution
system
DBP
levels
and
predictions
of
treatment
changes
are
very
different
for
ground
and
surface
water
plants.
This
is
mainly
because
ground
water
sources
generally
have
lower
DBP
precursor
(
e.
g.,
TOC)
concentrations
than
surface
water;
thus,
DBP
levels
and
predicted
changes
to
meet
Stage
2
DBPR
requirements
are
generally
less
for
plants
treating
ground
water
than
for
plants
treating
surface
water.

As
noted
in
section
3.4.1,
all
mixed
systems
(
even
those
that
are
primarily
ground
water)
are
grouped
with
the
100
percent
surface
water
systems
in
SDWIS.
If
EPA
applied
the
compliance
forecasts
for
surface
water
plants
to
systems
that
are
primarily
served
by
ground
water
sources,
costs
could
be
overstated.
Therefore,
systems
were
reclassified
by
primary
source.
This
is
consistent
with
recommendations
in
the
Arsenic
NDWAC
Final
Report
(
National
Drinking
Water
Advisory
Council
2001).

SDWIS
does
not
contain
information
on
whether
or
not
a
system
is
mixed
or
the
relative
proportions
of
surface
and
ground
water
flow
used,
indicating
only
whether
it
is
served
by
all
ground
water
or
by
at
least
some
proportion
of
surface
water.
Therefore,
to
reclassify
by
primary
source,
EPA
used
flow
data
from
the
1995
CWSS
to
estimate
the
proportion
of
surface
water
and
mixed
CWSs
that
received
more
than
50
percent
of
their
flow
from
a
ground
water
source
(
percentages
are
shown
in
Exhibit
3.4,
column
F).
These
systems,
originally
classified
as
surface
water
CWSs
in
SDWIS,
were
reassigned
to
the
ground
water
CWS
category.
Note
that
this
adjustment
was
not
made
for
NTNCWSs
because
these
systems
are
most
often
a
single
building
or
in
a
small
area,
and
are
less
likely
to
be
served
by
more
than
one
source
type.

Step
3:
Convert
System
Inventory
to
Plant
Inventory
The
1995
CWSS
data
(
question
18
from
the
CWSS
questionnaire)
were
used
to
estimate
the
number
of
treatment
plants
per
system
for
both
surface
and
ground
water
CWSs
for
all
system
sizes.
The
analysis
produced
a
distribution
of
plants
per
system
within
each
system
size
category.
For
analyses
in
this
EA,
EPA
uses
the
mean
plant
per
system
estimate
(
presented
in
column
I
of
Exhibit
3.4).
For
NTNCWSs,
EPA
assumed
a
1:
1
plant
per
system
ratio
for
all
sizes
and
source
water
types
because
these
systems
are
most
often
a
single
building
or
located
in
a
small
area.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
18
July
2003
Public
Private
Public
Private
A
B
C
D
E=
A+
B+
C+
D
 
 
 
 
 
 
£
100
18
14
135
321
488
101­
500
47
22
396
338
803
501­
1,000
20
9
344
86
459
1,001­
3,300
51
5
904
106
1,066
3,301­
10,000
45
1
951
63
1,060
10,001­
50,000
32
6
984
78
1,100
50,001­
100,000
6
0
210
30
246
100,001­
1
Million
8
0
215
33
256
>
1
Million
0
0
20
3
23
Total
227
57
4,160
1,057
5,501
 
 
 
 
 
 
£
100
98
72
681
6,750
7,601
101­
500
481
183
3,622
7,551
11,836
501­
1,000
263
75
2,541
1,210
4,089
1,001­
3,300
277
40
3,712
840
4,869
3,301­
10,000
82
12
1,921
273
2,288
10,001­
50,000
35
4
1,023
169
1,232
50,001­
100,000
1
0
108
20
129
100,001­
1
Million
4
0
47
9
60
>
1
Million
0
0
2
0
2
Total
1,241
387
13,656
16,822
32,105
 
 
 
 
 
 
£
100
21
75
76
126
298
101­
500
28
38
61
174
301
501­
1,000
12
12
19
66
108
1,001­
3,300
10
8
14
40
72
3,301­
10,000
5
4
6
8
23
10,001­
50,000
3
3
2
1
9
50,001­
100,000
1
0
0
0
1
100,001­
1
Million
1
0
0
0
1
>
1
Million
0
0
0
0
0
Total
80
140
177
416
813
 
 
 
 
 
 
£
100
4
10
640
3,008
3,662
101­
500
5
7
1,176
1,436
2,624
501­
1,000
2
2
447
265
717
1,001­
3,300
1
0
135
130
267
3,301­
10,000
1
0
8
18
27
10,001­
50,000
1
0
3
0
4
50,001­
100,000
0
0
0
0
0
100,001­
1
Million
0
0
0
0
1
>
1
Million
0
0
0
0
0
Total
16
19
2,410
4,858
7,303
Grand
Total,
All
Sys.
1,563
603
20,403
23,154
45,722
LINKED
Surface
Water
and
All
Mixed
CWSs
LINKED
Surface
Water
and
All
Mixed
NTNCWSs
Disinfecting,
Non­
Purchased
Systems
Total
No.
of
Disinfecting
Systems
Disinfecting,
Purchased
Systems
Ground
Water­
Only
CWSs
(
A­
D)
for
Surface
Water
CWSs
&
NTNCWSs:
"
Linked"
system
inventory
derived
from
SDWIS
4th
Quarter
Year
2000
Freeze
data,
adjusted
for
reporting
errors
in
Massachusetts
and
Montana
(
USEPA
2000d).
"
Other"
systems
have
been
allocated
to
the
4
categories
according
to
the
proportion
of
systems
in
those
categories.
See
section
3.4.2.2
for
a
description
of
linking
methodology.
(
A­
D)
for
Ground
Water
CWSs
&
NTNCWSs:
Taken
from
Exhibit
3.3,
columns
G­
J.
Step
1:
Use
modified
inventory
for
surface
water
systems
System
Size
(
population
served)

Sources:
Ground
Water­
Only
NTNCWSs
Exhibit
3.4
Derivation
of
the
Stage
2
DBPR
Plant
Baseline
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
19
July
2003
Public
Private
Public
Private
F
G
H
I
J
K=
G+
H+
I+
J
 
 
 
 
 
 
£
100
3.7%
18
13
130
309
470
101­
500
9.6%
43
20
358
306
726
501­
1,000
0.0%
20
9
344
86
459
1,001­
3,300
5.9%
48
5
851
100
1,003
3,301­
10,000
12.0%
40
1
837
55
933
10,001­
50,000
10.0%
29
6
885
70
990
50,001­
100,000
8.9%
5
0
191
27
224
100,001­
1
Million
14.0%
7
0
185
28
220
>
1
Million
0.0%
0
0
20
3
23
Total
8.2%
208
54
3,802
984
5,048
 
 
 
 
 
 
£
100
N/
A
99
73
686
6,762
7,619
101­
500
N/
A
485
185
3,660
7,583
11,913
501­
1,000
N/
A
263
75
2,541
1,210
4,089
1,001­
3,300
N/
A
280
40
3,765
846
4,932
3,301­
10,000
N/
A
87
12
2,035
281
2,415
10,001­
50,000
N/
A
39
5
1,122
177
1,342
50,001­
100,000
N/
A
1
0
127
22
151
100,001­
1
Million
N/
A
5
0
77
14
96
>
1
Million
N/
A
0
0
2
0
2
Total
­
1,259
390
14,014
16,895
32,558
 
 
 
 
 
 
£
100
0.0%
21
75
76
126
298
101­
500
0.0%
28
38
61
174
301
501­
1,000
0.0%
12
12
19
66
108
1,001­
3,300
0.0%
10
8
14
40
72
3,301­
10,000
0.0%
5
4
6
8
23
10,001­
50,000
0.0%
3
3
2
1
9
50,001­
100,000
0.0%
1
0
0
0
1
100,001­
1
Million
0.0%
1
0
0
0
1
>
1
Million
0.0%
0
0
0
0
0
Total
0.0%
80
140
177
416
813
 
 
 
 
 
 
£
100
N/
A
4
10
640
3,008
3,662
101­
500
N/
A
5
7
1,176
1,436
2,624
501­
1,000
N/
A
2
2
447
265
717
1,001­
3,300
N/
A
1
0
135
130
267
3,301­
10,000
N/
A
1
0
8
18
27
10,001­
50,000
N/
A
1
0
3
0
4
50,001­
100,000
N/
A
0
0
0
0
0
100,001­
1
Million
N/
A
0
0
0
0
1
>
1
Million
N/
A
0
0
0
0
0
Total
­
16
19
2,410
4,858
7,303
Grand
Total,
All
Sys.
­
1,563
603
20,403
23,154
45,722
Disinfecting,
Purchased
Systems
Disinfecting,
Non­
Purchased
Systems
(
I)
For
surface
water,
I=
C*(
1­
F);
for
ground
water,
I=
C+((
C
for
SW)*(
F
for
SW)).
(
J)
For
surface
water,
J=
D*(
1­
F);
for
ground
water,
J=
D+((
D
for
SW)*(
F
for
SW)).
(
F)
Percentage
of
SW
systems
that
are
primarily
GW
from
"
Geometries
and
Characteristics
of
Public
Water
Supplies"
(
USEPA
2000c),
Exhibit
2.9.
(
G)
For
surface
water,
G=
A*(
1­
F);
for
ground
water,
G=
A+((
A
for
SW)*(
F
for
SW)).
(
H)
For
surface
water,
H=
B*(
1­
F);
for
ground
water,
H=
B+((
B
for
SW)*(
F
for
SW)).
System
Size
(
population
served)
%
SW
that
are
Primarily
GW
Step
2:
Re­
allocate
such
that
systems
are
categorized
by
primary
source
water
type
LINKED
Primarily
Surface
Water
CWSs
Primarily
Ground
Water
CWSs
Total
No.
of
Disinfecting
Systems
Sources:
LINKED
Primarily
Surface
Water
NTNCWSs
LINKED
Primarily
Ground
Water
NTNCWSs
Exhibit
3.4
Derivation
of
the
Stage
2
DBPR
Plant
Baseline
(
Continued)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
20
July
2003
Public
Private
Public
Private
L
M=
G*
L
N=
H*
L
O=
I*
L
P=
J*
L
Q=
M+
N+
O+
P
 
 
 
 
 
 
£
100
1.0
18
13
130
309
470
101­
500
1.1
47
22
394
336
799
501­
1,000
1.1
22
10
378
95
505
1,001­
3,300
1.1
52
6
936
110
1,103
3,301­
10,000
1.3
51
1
1,088
72
1,213
10,001­
50,000
1.3
37
7
1,151
91
1,287
50,001­
100,000
2.4
13
0
459
66
538
100,001­
1
Million
2.6
18
0
482
73
572
>
1
Million
3.2
0
0
64
10
74
Total
­
258
59
5,082
1,161
6,560
 
 
 
 
 
 
£
100
1.0
101
74
699
6,897
7,772
101­
500
1.3
641
244
4,831
10,010
15,725
501­
1,000
1.5
395
113
3,811
1,814
6,133
1,001­
3,300
1.6
447
65
6,024
1,354
7,890
3,301­
10,000
2.1
180
25
4,192
579
4,975
10,001­
50,000
4.0
154
19
4,487
707
5,367
50,001­
100,000
4.9
7
0
622
109
738
100,001­
1
Million
9.1
46
0
703
125
875
>
1
Million
9.1
0
0
18
0
18
Total
­
1,971
540
25,387
21,596
49,495
 
 
 
 
 
 
£
100
1.0
21
75
76
126
298
101­
500
1.0
28
38
61
174
301
501­
1,000
1.0
12
12
19
66
108
1,001­
3,300
1.0
10
8
14
40
72
3,301­
10,000
1.0
5
4
6
8
23
10,001­
50,000
1.0
3
3
2
1
9
50,001­
100,000
1.0
1
0
0
0
1
100,001­
1
Million
1.0
1
0
0
0
1
>
1
Million
1.0
0
0
0
0
0
Total
­
80
140
177
416
813
 
 
 
 
 
 
£
100
1.0
4
10
640
3,008
3,662
101­
500
1.0
5
7
1,176
1,436
2,624
501­
1,000
1.0
2
2
447
265
717
1,001­
3,300
1.0
1
0
135
130
267
3,301­
10,000
1.0
1
0
8
18
27
10,001­
50,000
1.0
1
0
3
0
4
50,001­
100,000
1.0
0
0
0
0
0
100,001­
1
Million
1.0
0
0
0
0
1
>
1
Million
1.0
0
0
0
0
0
Total
­
16
19
2,410
4,858
7,303
Grand
Total,
All
Sys.
­
2,325
758
33,056
28,032
64,171
LINKED
Primarily
Surface
Water
NTNCWSs
(
L)
Derived
from
Question
18
of
the
1995
CWSS,
calculations
based
on
classification
of
systems
by
primary
source.
Methodology
to
be
included
in
subsequent
drafts
of
the
Geometries
Document
(
USEPA
2000c).
Step
3:
Convert
system
inventory
to
plant
inventory
System
Size
(
population
served)
Disinfecting,
Purchased
Plants
Disinfecting,
Non­
Purchased
Plants
Baseline
Number
of
Plants
Subject
to
the
Stage
2
DBPR
Total
No.
of
Disinfecting
Plants
Plants
per
System
LINKED
Primarily
Surface
Water
CWSs
Disinfecting
Primarily
Ground
Water
CWSs
Sources:
LINKED
Disinfecting
Primarily
Ground
Water
NTNCWSs
Exhibit
3.4
Derivation
of
the
Stage
2
DBPR
Plant
Baseline
(
Continued)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
21
July
2003
3.4.2.3
Population
Baseline
The
population
baseline
is
used
in
the
Stage
2
DBPR
benefits
analysis
to
help
derive
the
cases
of
bladder
cancer
avoided
as
a
result
of
treatment
changes
resulting
from
the
Stage
2
DBPR
(
see
chapter
5).
Because
the
benefits
of
the
rule
are
a
function
of
treatment
changes
and
subsequent
DBP
reductions,
the
population
baseline
must
be
consistent
with
the
plant
baseline.
Thus,
the
derivation
of
the
Stage
2
DBPR
population
baseline
is
similar
to
that
of
the
Stage
2
DBPR
plant
baseline
(
with
the
exception
of
Step
3
 
convert
system
inventory
to
plant
inventory.
This
is
not
needed
given
the
population
served
by
all
plants
in
a
size
category
and
all
systems
in
a
size
category
are
the
same).

Note
that
because
NTNCWs
are
most
often
businesses
such
as
restaurants,
schools,
campgrounds,
etc.,
their
population
generally
duplicates
population
served
by
CWSs.
Total
population
served
by
disinfecting
systems
as
derived
in
this
section
is
just
the
total
of
CWS
population
served,
or
254,478,588
(
160,685,640
+
93,792,948)
from
Exhibit
3.5,
column
K.

Step
1:
Modify
the
Surface
Water
System
Inventory
by
Linking
Buyers
and
Sellers
As
with
the
plant
baseline,
EPA
has
modified
the
system­
level
population
data
in
SDWIS
to
add
populations
served
by
purchasing
systems
to
the
population
served
of
their
wholesale
seller
for
surface
water
systems.
The
overall
effect
of
this
step
shifts
population
into
higher
system
size
categories;
however,
it
does
not
alter
the
total
population
served
by
all
surface
water
systems
as
reported
in
SDWIS.
Section
3.4.2.2
provides
the
rationale
and
detailed
methodology
used
to
modify
the
surface
water
inventory.

For
disinfecting
ground
water
systems,
the
population
is
derived
directly
from
SDWIS
4th
Quarter
Year
2000
data,
multiplied
by
the
percent
disinfecting
as
presented
in
Exhibit
3.3,
Column
F.

Step
2:
Re­
classify
Population
by
Primary
Source
Water
Type
As
with
the
plant
baseline,
EPA
modified
population
data
from
SDWIS
to
represent
populations
served
either
by
primarily
ground
or
primarily
surface
water
systems.
Given
that
SDWIS
does
not
contain
information
on
whether
or
not
a
system
is
mixed
or
the
relative
proportions
of
surface
and
ground
water
flow
used,
EPA
used
flow
data
from
the
1995
CWSS
to
estimate
the
proportion
of
surface
water
and
mixed
CWSs
that
received
more
than
50
percent
of
their
flow
from
a
ground
water
source
(
percentages
are
shown
in
Exhibit
3.4,
column
F).
This
population,
originally
classified
as
served
by
surface
water
CWSs
in
SDWIS,
was
re­
assigned
to
the
ground
water
CWS
category.
This
adjustment
was
not
made
for
NTNCWSs
because
these
systems
are
most
often
a
single
building
or
in
a
small
area,
and
are
less
likely
to
be
served
by
more
than
one
source
type.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
22
July
2003
Purchased
Nonpurchased
Purchased
Nonpurchased
A
B
C
D
E=
A+
B+
C+
D
 
 
 
 
 
 
£
100
1,008
8,212
764
19,015
28,999
101­
500
15,172
118,580
5,084
85,941
224,777
501­
1,000
14,807
265,379
6,254
66,673
353,113
1,001­
3,300
96,868
1,843,253
10,197
207,704
2,158,022
3,301­
10,000
259,849
5,704,051
7,547
372,535
6,343,982
10,001­
50,000
733,778
22,828,170
132,629
2,027,840
25,722,417
50,001­
100,000
444,600
14,497,753
0
2,034,557
16,976,910
100,001­
1
Million
1,953,583
58,562,443
0
10,285,575
70,801,601
>
1
Million
0
48,827,897
0
4,154,586
52,982,483
Total
3,519,665
152,655,737
162,475
19,254,427
175,592,304
 
 
 
 
 
 
£
100
6,318
4,660
43,610
406,244
460,833
101­
500
135,204
49,126
1,060,560
1,713,310
2,958,199
501­
1,000
197,809
55,389
1,891,777
866,957
3,011,931
1,001­
3,300
503,076
69,746
7,011,909
1,500,710
9,085,441
3,301­
10,000
436,864
69,717
10,958,860
1,520,877
12,986,318
10,001­
50,000
660,144
52,502
21,116,243
3,435,931
25,264,820
50,001­
100,000
90,240
0
7,123,365
1,425,111
8,638,716
100,001­
1
Million
509,754
0
11,015,578
2,051,107
13,576,439
>
1
Million
0
0
2,903,587
0
2,903,587
Total
2,539,409
301,140
63,125,489
12,920,246
78,886,284
 
 
 
 
 
 
£
100
1,241
4,107
3,250
6,849
15,447
101­
500
8,002
15,605
11,425
47,126
82,158
501­
1,000
8,815
13,591
9,571
51,565
83,542
1,001­
3,300
17,179
25,905
14,343
68,747
126,174
3,301­
10,000
34,500
24,162
21,353
41,013
121,028
10,001­
50,000
105,000
62,180
60,766
13,000
240,946
50,001­
100,000
93,204
0
0
0
93,204
100,001­
1
Million
169,846
0
0
0
169,846
>
1
Million
0
0
0
0
0
Total
437,787
145,550
120,708
228,300
932,345
 
 
 
 
 
 
£
100
252
440
35,739
160,604
197,035
101­
500
1,480
1,599
328,088
337,928
669,094
501­
1,000
1,349
1,646
314,798
199,348
517,141
1,001­
3,300
3,068
0
208,587
227,170
438,825
3,301­
10,000
8,066
0
33,247
93,092
134,405
10,001­
50,000
15,096
0
64,565
6,472
86,133
50,001­
100,000
0
0
19,898
0
19,898
100,001­
1
Million
111,034
0
0
40,700
151,734
>
1
Million
0
0
0
0
0
Total
140,344
3,684
1,004,921
1,065,315
2,214,265
Grand
Total,
All
Systems
6,637,206
153,106,111
64,413,593
33,468,288
257,625,198
System
Size
(
population
served)
Population
Served
by
Public,
Disinfecting
Systems
Population
Served
by
Private,
Disinfecting
Systems
Total
Population
Served
by
Disinfecting
Systems
Step
1:
Use
linked
inventory
for
SW
systems
(
A­
D)
for
Surface
Water
CWSs
&
NTNCWSs:
"
Linked"
system
inventory
derived
from
SDWIS
4th
Quarter
Year
2000
Freeze
data,
adjusted
for
reporting
errors
in
Massachusetts
and
Montana
(
USEPA
2000d).
See
section
3.4.2.2
for
a
description
of
linking
methodology.
(
A­
D)
for
Ground
Water
CWSs
and
NTNCWSs
directly
from
SDWIS
4th
Quarter
Year
2000
Freeze
data,
adjusted
for
reporting
errors
in
Massachusetts
and
Montana
(
USEPA
2000d),
reduced
by
%
disinfecting
from
Exhibit
3.3,
column
F.
Disinfecting
Ground
Water­
Only
NTNCWSs
LINKED
Surface
Water
and
All
Mixed
CWSs
Sources:
LINKED
Surface
Water
and
All
Mixed
NTNCWSs
Disinfecting
Ground
Water­
Only
CWSs
Exhibit
3.5
Derivation
of
the
Stage
2
DBPR
Population
Baseline
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
23
July
2003
Purchased
Nonpurchased
Purchased
Nonpurchased
F
G
H
I
J
K=
G+
H+
I+
J
 
 
 
 
 
 
 
£
100
3.7%
971
7,908
736
18,312
27,926
101­
500
9.6%
13,716
107,196
4,596
77,691
203,198
501­
1,000
0.0%
14,807
265,379
6,254
66,673
353,113
1,001­
3,300
5.9%
91,152
1,734,501
9,596
195,449
2,030,699
3,301­
10,000
12.0%
228,668
5,019,565
6,641
327,831
5,582,704
10,001­
50,000
10.0%
660,400
20,545,353
119,366
1,825,056
23,150,175
50,001­
100,000
8.9%
405,031
13,207,453
0
1,853,481
15,465,965
100,001­
1
Million
14.0%
1,680,081
50,363,701
0
8,845,594
60,889,377
>
1
Million
0.0%
0
48,827,897
0
4,154,586
52,982,483
Total
8.2%
3,094,826
140,078,952
147,188
17,364,674
160,685,640
 
 
 
 
 
 
 
£
100
N/
A
6,355
4,964
43,638
406,948
461,906
101­
500
N/
A
136,660
60,509
1,061,048
1,721,561
2,979,778
501­
1,000
N/
A
197,809
55,389
1,891,777
866,957
3,011,931
1,001­
3,300
N/
A
508,791
178,498
7,012,511
1,512,965
9,212,765
3,301­
10,000
N/
A
468,046
754,203
10,959,766
1,565,581
13,747,596
10,001­
50,000
N/
A
733,522
2,335,319
21,129,506
3,638,715
27,837,062
50,001­
100,000
N/
A
129,809
1,290,300
7,123,365
1,606,186
10,149,661
100,001­
1
Million
N/
A
783,256
8,198,742
11,015,578
3,491,087
23,488,663
>
1
Million
N/
A
0
0
2,903,587
0
2,903,587
Total
­
2,964,249
12,877,925
63,140,775
14,809,999
93,792,948
 
 
 
 
 
 
 
£
100
0.0%
1,241
4,107
3,250
6,849
15,447
101­
500
0.0%
8,002
15,605
11,425
47,126
82,158
501­
1,000
0.0%
8,815
13,591
9,571
51,565
83,542
1,001­
3,300
0.0%
17,179
25,905
14,343
68,747
126,174
3,301­
10,000
0.0%
34,500
24,162
21,353
41,013
121,028
10,001­
50,000
0.0%
105,000
62,180
60,766
13,000
240,946
50,001­
100,000
0.0%
93,204
0
0
0
93,204
100,001­
1
Million
0.0%
169,846
0
0
0
169,846
>
1
Million
0.0%
0
0
0
0
0
Total
0.0%
437,787
145,550
120,708
228,300
932,345
 
 
 
 
 
 
 
£
100
N/
A
252
440
35,739
160,604
197,035
101­
500
N/
A
1,480
1,599
328,088
337,928
669,094
501­
1,000
N/
A
1,349
1,646
314,798
199,348
517,141
1,001­
3,300
N/
A
3,068
0
208,587
227,170
438,825
3,301­
10,000
N/
A
8,066
0
33,247
93,092
134,405
10,001­
50,000
N/
A
15,096
0
64,565
6,472
86,133
50,001­
100,000
N/
A
0
0
19,898
0
19,898
100,001­
1
Million
N/
A
111,034
0
0
40,700
151,734
>
1
Million
N/
A
0
0
0
0
0
Total
­
140,344
3,684
1,004,921
1,065,315
2,214,265
Grand
Total,
All
Systems
­
6,637,206
153,106,111
64,413,593
33,468,288
257,625,198
Step
2:
Re­
allocate
such
that
systems
are
categorized
by
primary
source
water
type
LINKED
Primarily
Surface
Water
NTNCWSs
LINKED
Disinfecting
Primarily
Ground
Water
NTNCWSs
Total
Population
Served
by
Disinfecting
Systems
Baseline
Number
of
People
Subject
to
the
Stage
2
DBPR
%
SW
that
are
Primarily
GW
Population
Served
by
Public,
Disinfecting
Systems
Population
Served
by
Private,
Disinfecting
Systems
System
Size
(
population
served)

(
J)
For
surface
water,
J=
D*(
1­
F);
For
ground
water,
J=
D+((
D
for
SW)*(
F
for
SW)).
(
F)
Percentage
of
SW
systems
that
are
primarily
GW
from
"
Geometries
and
Characteristics
of
Public
Water
Supplies"
(
USEPA
2000c),
Exhibit
2.9.
(
G)
For
surface
water,
G=
A*(
1­
F);
For
ground
water,
G=
A+((
A
for
SW)*(
F
for
SW)).
(
I)
For
surface
water,
I=
C*(
1­
F);
For
ground
water,
I=
C+((
C
for
SW)*(
F
for
SW)).
Sources:
LINKED
Primarily
Surface
Water
CWSs
Disinfecting
Primarily
Ground
Water
CWSs
Note:
Detail
may
not
add
due
to
independent
rounding.
Exhibit
3.5
Derivation
of
the
Stage
2
DBPR
Population
Baseline
(
Continued)
9
Equations
are
from
the
3nd
Edition
of
the
Baseline
Handbook
as
derived
in
December
2000
Model
Systems
Report
(
USEPA
2000c).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
24
July
2003
3.4.3
Water
Treatment
Plant
Design
and
Average
Daily
Flows
Treatment
technology
costs
depend
on
the
volume
of
water
treated
per
day.
The
cost
analysis
described
in
Chapter
6
uses
two
types
of
treatment
plant
flow:
(
1)
design
flow,
which
is
the
maximum
capacity
at
which
the
plant
was
intended
to
operate,
expressed
in
millions
of
gallons
per
day
(
MGD),
and
(
2)
average
daily
flow,
which
is
the
flow
produced
by
a
treatment
plant
in
one
day,
an
average
derived
from
365
days
of
flow
measurements,
expressed
in
MGD.
Design
flows
are
used
to
estimate
the
capital
costs
of
the
technology
that
will
be
installed
to
meet
the
requirements
of
the
Stage
2
DBPR.
Average
daily
flows
are
used
to
estimate
the
annual
cost
of
ongoing
operations
and
maintenance
(
O&
M).

To
estimate
flows
for
different
sized
systems,
EPA
developed
the
following
regression
equations:

Surface
Water:
Design
Flow
(
MGD)
=
0.36971
X0.97757
/
1,000
Average
Daily
Flow
(
MGD)
=
0.10540
X1.02058
/
1,000
Ground
Water:
Design
Flow
(
MGD)
=
0.39639
X0.97708
/
1,000
Average
Daily
Flow
(
MGD)
=
0.06428
X1.07652
/
1,000
Where
X
=
mean
population
served
per
system.
9
These
equations
are
based
on
1995
CWSS
data.
Their
derivation
is
presented
in
detail
in
the
Model
Systems
Report
(
USEPA
2000c)
and
summarized
in
the
Baseline
Handbook
(
USEPA
2001h).
The
equations
are
used
in
this
EA
to
estimate
mean
flows
per
plant
for
each
size
category,
using
the
mean
population
served
per
plant.
(
The
mean
population
served
per
plant
can
be
calculated
by
dividing
the
total
population
for
a
given
size
category
presented
in
Exhibit
3.5,
column
K,
by
the
baseline
number
of
systems
in
that
size
category
as
presented
in
Exhibit
3.4,
column
Q.)
Flows
per
system
are
divided
by
the
number
of
plants
per
system
to
obtain
the
flow
per
plant.
Exhibit
3.6
shows
the
population
per
system,
the
number
of
plants
per
system,
and
the
design
and
average
flows
per
plant.

This
EA
uses
a
single
regression
equation
to
estimate
flows
for
either
public
or
privately
owned
systems.
There
is,
however,
a
slight
difference
in
the
flow
characteristics
for
these
two
ownership
types,
as
discussed
in
the
Model
Systems
Report
(
USEPA
2000c).
The
use
of
different
flow
equations
for
public
and
private
systems
would
not
affect
total
national
costs,
although
per­
household
costs
may
be
slightly
affected.
EPA
has
evaluated
the
equations
and
believes
that
the
differences
are
small
and
would
have
a
negligible
effect
on
household
costs.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
25
July
2003
Plants
per
System
X
Y
Z
=
0.36971
X
0.97757/
1000Y
AA
=
0.10540
X
1.02058/
1000Y
£
100
59.4
1.0
0.020
0.007
101­
500
279.9
1.1
0.083
0.030
501­
1,000
769.3
1.1
0.223
0.085
1,001­
3,300
2,024.4
1.1
0.574
0.227
3,301­
10,000
5,984.9
1.3
1.400
0.580
10,001­
50,000
23,384.0
1.3
5.307
2.332
50,001­
100,000
69,011.8
2.4
8.280
3.812
100,001­
1
Million
276,568.8
2.6
29.691
14.510
>
1
Million
2,303,586.2
3.2
191.605
102.574
X
Y
Z
=
0.36971
X
0.97757/
1000Y
AA
=
0.10540
X
1.02058/
1000Y
£
100
60.6
1.0
0.021
0.005
101­
500
250.1
1.3
0.066
0.019
501­
1,000
736.6
1.5
0.167
0.052
1,001­
3,300
1,868.1
1.6
0.389
0.134
3,301­
10,000
5,692.1
2.1
0.898
0.344
10,001­
50,000
20,746.4
4.0
1.637
0.713
50,001­
100,000
67,361.7
4.9
4.223
2.069
100,001­
1
Million
244,243.6
9.1
8.006
4.458
>
1
Million
1,451,793.5
9.1
45.683
30.372
X
Y
Z
=
0.36971
X
0.97757/
1000Y
AA
=
0.10540
X
1.02058/
1000Y
£
100
51.8
1.0
0.018
0.006
101­
500
273.0
1.0
0.089
0.032
501­
1,000
773.5
1.0
0.246
0.093
1,001­
3,300
1,752.4
1.0
0.548
0.215
3,301­
10,000
5,262.1
1.0
1.605
0.662
10,001­
50,000
26,771.8
1.0
7.875
3.481
50,001­
100,000
93,204.0
1.0
26.658
12.432
100,001­
1
Million
169,846.0
1.0
47.930
22.937
>
1
Million
NA
NA
NA
NA
X
Y
Z
=
0.36971
X
0.97757/
1000Y
AA
=
0.10540
X
1.02058/
1000Y
£
100
53.8
1.0
0.019
0.005
101­
500
255.0
1.0
0.089
0.025
501­
1,000
721.6
1.0
0.246
0.077
1,001­
3,300
1,645.0
1.0
0.550
0.186
3,301­
10,000
4,908.9
1.0
1.601
0.605
10,001­
50,000
19,399.3
1.0
6.132
2.655
50,001­
100,000
53,778.0
1.0
16.607
7.956
100,001­
1
Million
205,045.5
1.0
61.408
33.606
>
1
Million
NA
NA
NA
NA
Source:
Equations
relating
mean
population
to
flow
are
from
the
Baseline
Handbook
(
USEPA
2001h).
For
surface
water,
X
is
the
total
population
for
the
size
category
(
Exhibit
3.5,
column
K)
divided
by
the
total
number
of
systems
for
the
size
category
(
Exhibit
3.4,
column
Q).
For
ground
water,
X
is
derived
directly
from
SDWIS
4th
Quarter
Year
2000
Freeze
Data
(
USEPA
2000d).
Note:
Formulas
may
not
produce
exact
results
due
to
independent
rounding
(
average
people
per
plant
includes
fractions).
System
Size
(
population
served)

Disinfecting
Primarily
Ground
Water
NTNCWSs
LINKED,
Primarily
Surface
Water
NTNCWSs
Average
No.
of
Population
Served
per
Plant
Design
Flows
(
MGD)
Per
Plant
Average
Daily
Flow
(
MGD)
Per
Plant
LINKED,
Primarily
Surface
Water
CWSs
Disinfecting
Primarily
Ground
Water
CWSs
Exhibit
3.6
Design
Flows
and
Average
Daily
Flows
per
Plant
(
MGD)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
26
July
2003
Comparable
analyses
relating
average
daily
and
design
flow
to
population
was
not
performed
for
the
NTNCWSs.
Other
drinking
water
rules
have
evaluated
flows
for
NTNCWSs
according
to
service
categories
(
e.
g.,
schools,
restaurants,
hotels,
industry)
instead
of
size.
EPA
considered
using
this
method
for
evaluating
NTNCWSs
for
the
Stage
2
DBPR,
but
decided
against
it
for
the
following
reasons:

°
Service
category
flows
are
based
on
mean
population
served
for
all
systems
in
that
category,
regardless
of
source
water
type.
EPA
expects
that
surface
water
and
GWUDI
sources
would
be
more
prevalent
in
larger
NTNCWSs,
but
has
no
basis
for
developing
revised
population
estimates
for
each
service
category
by
source.

°
The
prediction
of
technology
selection
in
Chapter
6
is
a
function
of
population
served
and
does
not
directly
apply
to
service
categories
that
may
include
a
wide
range
of
water
system
sizes
and
flows
(
e.
g.,
schools
can
be
very
small
local
buildings
or
metropolitan
high
schools).

EPA,
therefore,
applied
the
CWS
regression
equations
to
NTNCWSs,
recognizing
that
this
may
over­
estimate
flows
and,
therefore,
costs.
This
over­
estimation
is
addressed
as
part
of
the
uncertainties
summarized
in
section
3.9.
Note
that
because
the
ratio
of
plants
per
system
was
assumed
to
be
1:
1
for
all
NTNCWSs,
plant
flows
equal
to
system
flows.
Mean
plant
flows
for
CWSs
and
NTNCWSs
may
differ
from
each
other
because
of
the
difference
in
mean
population
per
plant
within
each
size
category.

3.4.4
Number
of
Households
Served
The
number
of
households
served
by
CWSs
expected
to
be
subject
to
the
Stage
2
DBPR
is
estimated
by
dividing
the
population
for
each
system
size
category
by
the
average
number
of
people
per
household
(
2.59)
(
U.
S.
Census
Bureau
2001).
As
shown
in
Exhibit
3.7,
PWSs
serve
nearly
99
million
households.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
27
July
2003
Number
of
Households
Served
Linked,
Primarily
Surface
Water
Primarily
Disinfecting
Ground
Water
£
100
10,782
178,216
101­
500
78,455
1,150,017
501­
1,000
136,337
1,162,952
1,001­
3,300
784,054
3,555,183
3,301­
10,000
2,155,484
5,307,952
10,001­
50,000
8,938,292
10,812,015
50,001­
100,000
5,971,415
4,412,524
100,001­
1
Million
23,509,412
9,068,982
>
1
Million
20,456,557
1,121,076
Total
62,040,788
36,768,917
National
Total
98,809,705
System
Size
(
population
served)
Exhibit
3.7
Number
of
Households
Subject
to
the
Stage
2
DBPR
Note:
Detail
may
not
add
due
to
independent
rounding.

Source:
Calculated
by
dividing
the
total
population
served
(
Exhibit
3.5,
column
K)
by
2.59,
the
average
number
of
people
per
household
(
U.
S.
Census
Bureau
2001).

3.4.5
Uncertainty
in
Baseline
Input
Data
EPA
recognizes
that
there
is
uncertainty
related
to
the
various
data
sources
used
to
define
the
system
inventory
for
the
Stage
2
DBPR.
The
uncertainty
in
the
system
inventory
data
inputs
is
not
quantified
in
this
EA;
however,
a
qualitative
discussion
of
the
identified
uncertainties
is
provided
below.

As
noted
above,
SDWIS
and
the
1995
CWSS
are
the
primary
sources
of
system
inventory
data.
SDWIS
is
EPA's
primary
drinking
water
database,
containing
data
for
over
170,000
PWSs.
SDWIS
stores
State­
reported
information
on
each
water
system,
including
name,
ID
number,
number
of
people
served,
type
of
system
(
year­
round
or
seasonal),
and
source
of
water
(
ground
water
or
surface
water),
along
with
monitoring
and
violation
information.
In
1998,
EPA
began
a
major
effort
to
assess
the
quality
of
its
drinking
water
data
in
SDWIS.
The
results,
published
in
Data
Reliability
Analysis
of
the
EPA
Safe
Drinking
Water
Information
System/
Federal
Version,
found
that
the
quality
of
the
required
inventory
data
was
high
(
USEPA
2000e).
Thus,
EPA
believes
that
uncertainty
in
the
system
inventory
data
from
SDWIS
with
respect
to
numbers
of
systems,
source
information,
and
size
classification
is
low.

The
1995
CWSS
was
developed
to
gather
data
on
water
systems
in
the
United
States.
A
total
of
3,681
systems
covering
a
range
of
source
water
types
and
system
sizes
were
statistically
selected
to
receive
the
main
survey
questionnaire.
Of
these,
1,980
systems
responded.
These
responses
were
weighted
to
maintain
statistical
representation
of
the
total
universe
of
CWSs.
The
EPA
report
Community
Water
System
Survey
(
USEPA
1997c)
provides
information
on
the
1995
CWSS
survey
design
and
data
evaluation.

The
1995
CWSS
was
the
primary
data
source
used
to
develop
the
following
baseline
characteristics:
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
28
July
2003
°
Percent
of
ground
water
systems
that
disinfect
°
Percent
of
SDWIS
surface
water
systems
that
use
primarily
ground
water
°
Treatment
plants
per
system
°
Average
and
design
flow
based
on
population
served
(
presented
in
section
3.4.3)

Because
the
CWSS
is
a
survey
of
CWSs,
estimates
based
on
the
data
will
contain
uncertainty
because
of
sampling
errors.
To
help
define
these
uncertainties,
the
CWSS
report
provides
the
confidence
intervals
on
certain
parameters.
The
report
does
not,
however,
contain
data
for
percent
disinfecting,
percent
of
SDWIS
surface
water
systems
providing
ground
water,
and
treatment
plants
per
system
that
are
used
in
this
EA.
The
confidence
intervals
for
similar
parameters
can
provide
some
information
on
uncertainty.
For
example,
an
analysis
of
the
percent
of
ground
water
systems
with
no
treatment
(
which
uses
similar
data
to
the
analysis
of
percent
disinfecting),
yielded
95
percent
confidence
intervals
of
less
than
+/­
10
percent.

For
average
and
design
flow
regression
equations,
one
measure
of
uncertainty
is
the
R­
value
for
the
regressions.
The
regressions
both
for
average
daily
flow
and
for
design
flow
had
very
high
R­
values
(
0.97
and
0.90,
respectively),
indicating
a
low
level
of
uncertainty.

3.5
Influent
Water
Quality
Characterization
3.5.1
Summary
of
Available
Influent
Water
Quality
Data
Predictions
of
compliance
forecasts
(
as
summarized
in
section
3.3)
assume
that
a
system
will
choose
a
treatment
technology
for
the
Stage
2
DBPR
that
best
addresses
its
water
quality
improvement
needs.
The
quality
of
the
source
water
plays
a
key
role
in
evaluating
treatment
alternatives
to
meet
regulatory
requirements.
This
section
provides
an
overview
of
influent
water
quality
on
a
national
level.

Exhibit
3.8
summarizes
the
influent
water
quality
data
that
were
collected
under
the
ICR
for
large
surface
and
ground
water
systems.
Monthly
plant
data
collected
during
the
last
12
months
of
the
ICR
collection
period
(
January
1998
 
December
1998)
for
each
plant
were
averaged
to
estimate
a
"
plantmean
value
for
each
plant.
Only
plants
that
had
data
for
at
least
9
of
the
last
12
months
of
the
ICR
period
were
included
in
Exhibit
3.8.
The
results
in
Exhibit
3.8
represent
the
characteristics
of
the
distribution
of
those
plant­
means.

The
median,
90th
percentile,
and
range
provide
some
insight
to
the
variability
in
plant­
means
among
all
large
surface
and
ground
water
plants.
Data
for
these
influent
water
quality
parameters
were
part
of
the
input
data
for
SWAT.
They
were
also
used
by
the
Delphi
Group
and
the
small
system
experts
(
both
for
surface
water
and
ground
water)
to
assess
treatment
alternatives.
For
a
complete
characterization
and
discussion
of
these
parameters,
see
Chapter
3
of
the
Occurrence
Assessment
(
USEPA
2003l).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
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July
2003
Exhibit
3.8
ICR
Large
System
Influent
Water
Quality
Parameters
 
Summary
of
Pre­
Stage
1
Plant­
Mean
Data
Parameter
Source
Type
Number
of
Plants
Mean
of
Plant
Mean
s
Median
of
Plant
Means
90th
Percentile
of
Plant
Means
Range
of
Plant
Means
Alkalinity
(
mg/
L
as
CaCO
3)
Surface
325
81
79
161
2.75
 
272
Ground
119
160
157
265
1.58
 
415
Bromide
(
mg/
L)
Surface
320
0.055
0.027
0.115
<
0.02
 
1.325
Ground
118
0.103
0.066
0.190
<
0.02
 
1.325
pH
Surface
323
7.6
7.7
8.2
6.0
 
8.5
Ground
118
7.3
7.4
8.0
4.1
 
8.8
Temperature
(
°
C)
Surface
334
16.0
16.1
20.7
3.7
 
27.7
Ground
121
19.9
20.1
26.3
9.5
 
30.5
Total
Hardness
(
mg/
L
as
CaCO
3)
Surface
315
118
110
251
3.1
 
501
Ground
115
194
197
352
3.6
 
778
Total
Organic
Carbon
(
mg/
L
as
C)
Surface
307
3.14
2.71
5.29
<
0.7
 
21.4
Ground
103
1.46
0.18
3.36
<
0.7
 
16.1
Turbidity
(
Nephelometric
Turbidity
Units)
Surface
316
18.6
6.7
34.1
0.06
 
529
Ground
115
1.3
0.2
2.6
0.03
 
38.7
UV
254
Absorbance
(
cm­
1)
Surface
306
0.098
0.079
0.176
<
0.009
 
0.880
Ground
104
0.062
0.009
0.266
<
0.009
 
0.606
Note:
The
maximum
surface
water
bromide
mean
value,
3.13
mg/
L,
is
not
shown.
This
value
was
calculated
based
on
a
one­
month
reported
bromide
concentration
of
28
mg/
L,
which
EPA
assumes
to
be
a
reporting
error.
(
Laboratories
often
report
bromide
values
in
µ
g/
L,
rather
than
mg/
L;
this
value
may
not
have
been
converted
to
mg/
L.)
All
the
other
values
for
that
plant
in
the
last
12
months
of
the
ICR
were
below
0.1
mg/
L.

Source:
ICR
AUX1
database
(
USEPA
2000h).
Represents
distribution
of
plant­
mean
data
as
calculated
using
ICR
monthly
data
from
the
last
12
months
of
the
ICR
(
January
1998
­
December
1998).
Only
plants
with
reported
data
for
at
least
9
of
the
12
months
are
included
in
this
summary
table.
Does
not
include
blended,
mixed,
or
purchased
plants.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
30
July
2003
A
key
influent
water
quality
parameter
related
to
Stage
2
DBPR
compliance
is
Total
Organic
Carbon
(
TOC).
TOC
is
a
measure
of
organic
content
in
the
water
and
is
generally
a
good
indicator
of
the
concentrations
of
TTHM
and
haloacetic
acid
(
HAA5)
precursors.
The
distribution
of
plant­
mean
TOC
concentrations
for
plants
with
surface
water
sources
covers
a
large
range
(
from
0
to
21.4
mg/
L
(
Exhibit
3.8));
however,
90
percent
of
the
plants
had
mean
TOC
concentrations
below
5.3
mg/
L.
Exhibit
3.9
shows
the
distribution
of
plant­
mean
TOC
concentrations
for
surface
water
and
ground
water
plants
for
the
subset
of
plants
shown
in
Exhibit
3.8.
For
ground
water
plants,
70
percent
had
mean
TOC
concentrations
below
1
mg/
L;
the
highest
values
were
close
to
those
for
surface
water
plants.
A
large
percentage
of
ICR
ground
water
plants
(
approximately
25
percent)
are
located
in
Florida,
where
high
levels
of
TOC
occur
in
ground
water.

Bromide
in
source
water
can
affect
the
amount
and
type
of
DBPs
formed,
shifting
the
distribution
of
DBPs
more
to
the
brominated
species.
Also,
bromide
can
react
with
ozone
and
chlorine
dioxide
to
form
bromate,
another
byproduct
of
concern.
As
shown
in
Exhibit
3.8,
most
of
the
plant­
mean
bromide
levels
are
relatively
low
(
the
90th
percentiles
were
0.122
and
0.190
mg/
L
for
surface
water
and
ground
water
sources,
respectively).
Exhibit
3.10
shows
the
distribution
of
mean
bromide
concentrations
for
large
surface
water
and
ground
water
plants.

There
is
no
extensive
data
set
similar
to
the
ICR
that
provides
comparable
influent
water
quality
data
for
medium
and
small
systems.
Therefore,
as
noted
in
section
3.2,
several
alternative
data
sources
were
used
to
characterize
these
systems
and
compare
their
water
quality
to
the
large
systems.
The
Occurrence
Document
(
USEPA
2003l)
provides
an
overview
of
each
alternative
data
set
and
compares
source
water
quality
for
medium
and
small
systems.
Exhibit
3.11
provides
a
summary
of
influent
water
quality
data
from
these
sources
for
medium
and
small
surface
and
ground
water
systems.
Appendices
A
and
B
provide
additional
detail
regarding
influent
water
quality
data
that
are
relevant
to
compliance
forecast
analyses
for
surface
and
ground
water
systems,
respectively.

3.5.2
Regional
Differences
in
Water
Quality
EPA
evaluated
ICR
data
for
surface
and
ground
water
systems
to
determine
if
there
were
differences
in
influent
water
quality
among
regions.
Exhibits
3.12a
and
3.12b
show
average
TOC
concentrations
by
State
for
surface
and
ground
water
systems,
respectively,
using
ICR
data.
Exhibit
3.12c
shows
average
TOC
concentrations
by
State
for
ground
water
systems
using
Ground
Water
Supply
Survey
(
GWSS)
data.
Surface
water
systems
did
not
exhibit
any
notable
regional
trends;
however,
ICR
data
and
GWSS
data
show
that
Florida
has
very
high
TOC
concentrations
compared
to
other
States.
Florida
also
has
the
largest
proportion
of
large
ground
water
systems
of
all
the
States.
The
ICR
Ground
Water
Delphi
Group
estimated
that,
of
the
large
and
medium
ground
water
plants
that
will
need
to
make
changes
to
comply
with
the
Stage
2
DBPR
Preferred
Alternative,
more
than
80
percent
are
in
Florida
(
see
Appendix
B,
Exhibit
B.
4
for
compliance
forecast
data
on
ground
water
systems).
Economic
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July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
2
4
6
8
10
12
14
16
18
20
22
24
Plant­
Mean
TOC
(
mg/
L
as
C)
Percentile
SW
ICR
TOC
Plant­
Means
(
N=
307)

GW
ICR
TOC
Plant­
Means
(
N=
103)
Exhibit
3.9
Cumulative
Distribution
of
TOC
in
Influent
Water
ICR
Plant­
Mean
Data
Source:
ICR
AUX1
database
(
USEPA
2000d).
Economic
Analysis
for
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July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
0.2
0.4
0.6
0.8
1
1.2
1.4
Plant­
Mean
Bromide
(
mg/
L)
Percentile
SW
ICR
Bromide
Plant­
Means
(
N=
320)

GW
ICR
Bromide
Plant­
Means
(
N=
118)
Exhibit
3.10
Cumulative
Distribution
of
Bromide
in
Influent
Water
ICR
Plant­
Mean
Data
Source:
Each
data
point
in
the
distribution
represents
the
mean
value
of
monthly
data
collected
at
a
single
plant
over
a
12­
month
period
(
January
1998
 
December
1998).
Only
plants
with
reported
data
for
at
least
9
of
the
12
months
are
included
in
this
summary
table
(
USEPA
2000h).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
33
July
2003
Exhibit
3.11
Medium
and
Small
System
Influent
Water
Quality
Parameters
 
Summary
of
Pre­
Stage
1
Plant­
Mean
Data
Data
Source/
Size
Category
N
Mean
of
Plant­
Means
Median
of
Plant­
Means
90th
Percentile
of
Plant­
Means
Range
of
Plant­
Means
Source
Water
Alkalinity
(
mg/
L
as
CaCO3)

NRWA
Small
Surface
Water
(
SW)
Plants
95
81
74
146
0
­
281
ICR
Supplemental
Survey
(
ICR
SS)
Medium
SW
Plants
40
82
74
159
4.8
­
240
ICR
SS
Small
SW
Plants
38
66
55
123
4.4
­
249
Source
Water
Bromide
(
mg/
L)

NRWA
Small
SW
Plants
95
0.063
0.021
0.107
0­
1.72
ICR
SS
Medium
SW
Plants
40
0.050
0.016
0.092
0
­
0.53
ICR
SS
Small
SW
Plants
38
0.02
0
0.044
0
­
0.27
Source
Water
pH
NRWA
Small
SW
Plants
78
7.3
7.4
8.1
3.8
­
8.8
ICR
SS
Medium
SW
Plants
40
7.6
7.6
8.2
5.9
­
8.4
ICR
SS
Small
SW
Plants
36
7.3
7.4
8.0
5.8
­
8.3
Source
Water
TOC
(
mg/
L
as
C)

NRWA
Small
SW
Plants
96
3.0
2.6
5.3
0.3
­
9.0
ICR
SS
Medium
SW
Plants
40
3.6
3.7
5.5
0.2
­
7.9
ICR
SS
Small
SW
Plants
38
2.4
2.1
4.5
0.1
­
7.1
WATER:\
STATS
Medium
SW
Plants
102
5.6
3.2
6.4
0
­
200
WATER:\
STATS
Medium
GW
Plants
51
2.3
0.79
7.0
0
­
25
Source
Water
Turbidity
(
NTU)

NRWA
Small
SW
Plants
76
7.8
4.1
18
0.1
­
65
ICR
SS
Medium
SW
Plants
40
13
5.9
33
1
­
103
ICR
SS
Small
SW
Plants
36
6.2
3.5
13
0.3
­
43
Source
Water
UV­
254
(
cm­
1)

NRWA
Small
SW
Plants
96
0.082
0.075
0.127
0.01
­
0.23
ICR
SS
Medium
SW
Plants
40
0.093
0.083
0.171
0.03
­
0.21
ICR
SS
Small
SW
Plants
38
0.074
0.051
0.113
0.02
­
0.44
Note:
ICR
SS
data
are
the
plant­
means
for
plants
that
took
at
least
three­
fourths
of
the
total
possible
samples
for
each
parameter.
Only
plants
that
had
both
a
Winter
and
Summer
sample
are
included
in
the
NRWA
data
for
this
analysis.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
34
July
2003
TOC
³
2
or
<
3
mg/
L
TOC
³
3
or
<
4
mg/
L
No
Data
TOC
<
1
mg/
L
TOC
³
1
or
<
2
mg/
L
TOC
³
4
mg/
L
TOC
³
2
or
<
3
mg/
L
TOC
³
3
or
<
4
mg/
L
No
Data
TOC
<
1
mg/
L
TOC
³
1
or
<
2
mg/
L
TOC
³
4
mg/
L
Exhibit
3.12a
Influent
Water
TOC
Distribution
for
ICR
Surface
Water
Systems
Source:
ICR
AUX1
Database
(
USEPA
2000h);
mean
of
all
plant­
means
for
each
State.

Exhibit
3.12b
Influent
Water
TOC
Distribution
for
ICR
Ground
Water
Systems
Source:
ICR
AUX1
Database
(
USEPA
2000h);
mean
of
all
plant­
means
for
each
State.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
35
July
2003
TOC
³
2
or
<
3
mg/
L
TOC
³
3
or
<
4
mg/
L
No
Data
TOC
<
1
mg/
L
TOC
³
1
or
<
2
mg/
L
TOC
³
4
mg/
L
Exhibit
3.12c
Influent
Water
TOC
Distribution
for
Ground
Water
Systems
Derived
from
the
Ground
Water
Supply
Survey
(
GWSS)

Source:
GWSS
(
USEPA
1981),
mean
of
all
finished
water
TOC
samples
in
the
State.

3.6
Treatment
Characterization
for
the
Pre­
Stage
1
and
Pre­
Stage
2
DBPRs
This
section
summarizes
treatment
conditions
for
the
pre­
Stage
1
and
pre­
Stage
2
DBPR
baselines.
A
summary
of
technologies
is
provided
first,
followed
by
the
estimate
of
technologies­
in­
place
for
each
baseline.
Chapter
6
provides
further
detail
on
treatment
technologies
and
compliance
forecast
methodology
used
in
this
EA.

3.6.1
Treatment
Technologies
In
the
Stage
1
DBPR
Regulatory
Impact
Analysis
(
RIA),
EPA
predicted
the
changes
in
technologies
that
systems
would
make
to
comply
with
the
Stage
1
DBPR.
From
this
compliance
forecast,
national
cost
estimates
and
reductions
in
DBP
levels
were
estimated
for
the
Stage
1
DBPR.
This
earlier
estimation
of
the
Stage
1
DBPR
compliance
forecast
and
subsequent
costs
and
DBP
reductions,
however,
is
not
the
same
as
the
pre­
Stage
2
DBPR
(
post­
Stage
1
DBPR)
baseline
derived
in
this
chapter.
For
the
Stage
2
DBPR
analyses,
new
tools
and
processes
were
used
to
forecast
the
costs
of
complying
with
the
Stage
1
DBPR.
These
tools
and
processes,
summarized
in
section
3.3,
included:
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
36
July
2003
°
SWAT
°
ICR
Ground
Water
Delphi
process
°
Expert
opinion
process
for
small
systems
(
both
surface
and
ground
water)

These
tools
and
processes
provided
a
larger
and
more
detailed
set
of
technology
choices
than
those
used
in
the
Stage
1
DBPR
RIA.
Consequently,
the
forecast
results
of
the
Stage
1
DBPR
used
as
a
baseline
in
this
EA
(
the
pre­
Stage
2
DBPR
baseline),
while
different
from
those
in
the
Stage
1
DBPR
RIA,
are
based
on
a
more
complete
set
of
compliance
options
and
a
more
rigorous
analysis.
Exhibit
3.13
compares
the
technology
choices
used
in
the
Stage
1
DBPR
RIA
to
those
used
in
the
Stage
2
DBPR
EA.

The
detailed
technology
choices
evaluated
for
the
Stage
2
DBPR
EA
were
aggregated
into
more
general
categories
for
the
purposes
of
estimating
national
costs.
The
final
12
major
treatment
technology
categories
evaluated
in
this
EA
are
summarized
in
Exhibit
3.14.
They
are
generally
ordered
according
to
cost,
with
the
most
expensive
at
the
bottom
of
the
exhibit.
With
each
technology,
systems
are
expected
to
use
either
free
chlorine
or
combined
chlorine
(
chloramines)
as
the
residual
disinfectant.
Conversion
from
free
chlorine
to
chloramine
residual
disinfection
is
a
relatively
inexpensive
way
for
systems
to
reduce
DBP
levels.

The
first
four
technologies
(
in
italic
font
in
Exhibit
3.14)
represent
operational
changes
to
existing
treatment
configurations.
Although
these
changes
may
result
in
small
increases
in
chemical
costs
or
minor
capital
improvements,
EPA
assumes
their
costs
to
be
negligible
when
compared
to
the
costs
of
the
advanced
technologies
(
e.
g.,
UV,
ozone,
granulated
activated
carbon,
microfiltration/
ultra­
filtration)
shown
in
Exhibit
3.14
(
refer
to
Technologies
and
Costs
for
Control
of
Microbial
Contaminants
and
Disinfection
Byproducts
[
USEPA
2003o]
for
comparison).
Also,
most
systems
that
are
able
to
use
these
technologies
are
predicted
to
do
so
to
meet
the
Stage
1
DBPR.
For
these
reasons,
the
predicted
costs
for
the
Stage
2
DBPR
do
not
include
costs
for
operational
changes.
(
This
is
noted
in
section
6.8
as
an
uncertainty
that
may
lead
to
an
underestimate
in
national
costs.)

Because
UV
is
an
emerging
technology,
it
was
not
considered
an
option
for
most
systems
for
the
Stage
1
DBPR.
For
the
Stage
2
DBPR,
UV
is
an
advanced
disinfection
option
for
all
surface
water
systems
and
small
ground
water
systems.
Adjustments
to
the
compliance
forecast
to
account
for
use
of
UV
are
discussed
in
Chapter
6
and
Appendices
A
and
B.

As
indicated
in
Exhibit
3.14,
fewer
technologies
are
listed
for
ground
water
plants
than
for
surface
water
plants.
As
summarized
in
Appendix
B,
section
B.
2.2,
the
ICR
Ground
Water
Delphi
Group
concluded
that
large
ground
water
systems
would
choose
primarily
from
four
treatment
technologies:
conversion
to
chloramines,
ozone,
GAC20,
or
nanofiltration;
small
ground
water
systems
would
also
consider
UV.
The
selection
of
technologies
as
a
function
of
source
water
types
and
small
systems'
constraints
are
summarized
in
Chapter
6
and
discussed
in
detail
in
the
compliance
forecasts
for
surface
and
ground
water
plants,
as
described
in
Appendices
A
and
B,
respectively.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
37
July
2003
Exhibit
3.13
Comparison
of
Technologies
Considered
for
the
Stage
1
DBPR
in
the
Stage
1
DBPR
RIA
and
the
Stage
2
DBPR
EA
Stage
1
DBPR
RIA
Technologies
Stage
2
DBPR
EA
Technologies
Chlorine/
Chloramine
Adjust
Primary
Disinfection
Move
Points
of
Disinfection
with
Chloramines
Enhanced
Coagulation
Enhanced
Coagulation
with
Chlorine
Turbo
Coagulation
with
Chlorine
Enhanced
Coagulation
with
Chloramines
Enhanced
Coagulation
with
Chloramines
Turbo
Coagulation
with
Chloramines
Chlorine
Dioxide
Chlorine
Dioxide
with
Chlorine
Chlorine
Dioxide
with
Chloramines
Ozone
with
Chloramines
Ozone
with
Chlorine
Ozone
with
Chloramines
GAC10
GAC10
with
Chlorine
GAC10
with
Chloramines
GAC10
+
Chlorine
Dioxide
with
Chlorine
GAC10
+
Chlorine
Dioxide
with
Chloramines
GAC10
+
UV
(
Small
Systems)

GAC20
GAC20
with
Chlorine
GAC20
with
Chloramines
GAC20
+
Chlorine
Dioxide
with
Chlorine
(
Large
and
Medium
Systems)

GAC20
+
Chlorine
Dioxide
with
Chloramines
(
Large
and
Medium
Systems)

GAC20
+
Ozone
with
Chlorine
(
Small
Systems)

GAC20
+
Ozone
with
Chloramines
(
Small
Systems)

GAC20
+
UV
(
Small
Systems)

Membranes
Microfiltration/
Ultrafiltration
with
Chlorine
Microfiltration/
Ultrafiltration
with
Chloramines
Integrated
Membranes
with
Chlorine
(
Surface
Water
Systems)

Integrated
Membranes
with
Chloramines
(
Surface
Water
Systems)

Nanofiltration
with
Chlorine
(
Ground
Water
Systems)

Nanofiltration
with
Chloramines
(
Ground
Water
Systems)
Source:
Stage
1
DBPR
RIA
(
USEPA
1998a)
for
Stage
1
technologies;
Federal
Advisory
Committees
Act
(
FACA)
deliberations
for
Stage
2
technologies
(
USEPA
2000p).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
38
July
2003
Exhibit
3.14
Aggregated
Treatment
Technology
Categories
for
Stage
1
DBPR
Used
for
the
Stage
2
DBPR
EA
Treatment
Technology
Category
Explanation
of
Technology
for
Surface
Water
Plants
Explanation
of
Technology
for
Ground
Water
Plants
Adjust
Primary
Disinfectant
Dose
Reduce
primary
disinfectant
dose
(
usually
chlorine)
NA
Enhanced
Coagulation/
Enhanced
Softening
Increased
TOC
removal
through
increased
coagulant
addition
to
meet
Stage
1
DBPR
requirements
NA
Turbo
Coagulation
Increased
TOC
removal
through
increased
coagulant
addition,
but
higher
than
that
required
by
enhanced
coagulation
NA
Moving
Point
of
Disinfection
Move
point
of
disinfection
downstream
to
minimize
formation
of
DBPs
NA
Chlorine
Dioxide
Chlorine
dioxide
instead
of
chlorine
for
primary
disinfection
NA
Ozone
Ozone
instead
of
chlorine
for
primary
disinfection,
applied
to
raw
or
settled
water
Ozone
instead
of
chlorine
for
primary
disinfection,
applied
to
raw
or
settled
water
MF/
UF
Microfiltration
or
ultrafiltration
as
the
particle
removal
process
NA
GAC10
Granular
activated
carbon
with
a
10­
minute
Empty
Bed
Contact
Time
(
EBCT)
NA
GAC10
+
Advanced
Disinfectants
GAC10
+
chlorine
dioxide
(
large
and
medium
systems)
GAC10
+
UV
(
small
systems)
NA
GAC20
Granular
activated
carbon
with
a
20­
minute
EBCT
Granular
activated
carbon
with
a
20­
minute
EBCT
GAC20
+
Advanced
Disinfectants
GAC20
+
UV
or
ozone
NA
Membranes
Integrated
membranes
as
the
particle
removal
process
(
MF/
UF
and
nanofiltration)
Nanofiltration
alone
as
the
particle
removal
process
Notes:
NA
=
Not
applicable
to
plant
type.
Italic
font
indicates
that
technology
was
not
considered
in
estimating
costs
of
rule
alternatives.

Source:
Technology
and
Cost
Document
(
USEPA
2003o);
applicability
to
ground
water
systems
discussed
in
Chapter
6
and
Appendix
B
of
this
EA.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
39
July
2003
3.6.2
Treatment
Characterization
Although
cost
analyses
in
Chapter
6
are
performed
for
each
of
the
nine
system
size
categories
separately,
treatment
characterizations
are
predicted
according
to
the
following
aggregated
categories
by
population
served:

°
Small
systems
°
Serving
fewer
than
100
people
°
Serving
101
to
1,000
people
°
Serving
1,001
to
10,000
people
°
Medium
systems
 
serving
10,001
to
100,000
people
°
Large
systems
 
serving
more
than
100,000
people
Small
systems
were
stratified
by
the
three
population
categories
shown
above
to
reflect
differences
in
the
number
of
systems
needing
to
change
technologies
and
the
technology
options
available
to
each
category.
The
treatment
characterizations
presented
here
and
in
Chapter
6
show
the
nine
population
size
categories
used
for
costing,
but
present
one
compliance
forecast
(
as
a
percentage
of
the
total
baseline
number
of
plants)
for
each
of
the
population
size
categories
listed
above.

Exhibits
3.15
and
3.16
summarize
the
pre­
Stage
1
DBPR
baseline
technologies­
in­
place
for
surface
and
ground
water
treatment
plants,
respectively.
For
plants
in
large
and
medium
ground
water
systems,
ICR
treatment
data
were
used
to
derive
the
estimated
percent
of
plants
using
each
technology.
For
plants
in
large
and
medium
surface
water
systems,
SWAT­
predicted
results
from
the
"
initial
plant
run"
(
USEPA
2001e)
are
used
to
characterize
the
percent
of
plants
using
each
technology
in
Exhibit
3.15.
SWAT­
predicted
results
were
used
instead
of
available
ICR­
observed
data
to
allow
for
consistent
comparison
of
pre­
Stage
1
data
to
modeled
pre­
Stage
2
and
post­
Stage
2
data
(
if
observed
data
were
used
for
pre­
Stage
1
technology­
in­
place
estimates,
differences
between
pre­
Stage
1
and
pre­
Stage
2
results
would
reflect
potential
inconsistencies
in
observed
vs.
predicted
data,
not
just
the
expected
change
from
pre­
Stage
1
to
pre­
Stage
2).

For
all
small
systems,
the
only
significant
use
of
advanced
technologies
was
reported
in
the
NRWA
database
for
small
surface
water
systems
(
approximately
3.6
percent
are
estimated
to
be
using
MF/
UF,
as
shown
in
Exhibit
3.16).
The
percent
using
each
technology
is
based
on
evaluation
of
CWS
data;
EPA
assumed
that
NTNCWSs
use
similar
technologies
for
the
size
categories
shown.

Exhibits
3.17
and
3.18
show
the
predicted
technologies­
in­
place
following
the
Stage
1
DBPR
(
pre­
Stage
2
DBPR
baseline).
In
most
cases,
the
technologies­
in­
place
for
the
pre­
Stage
2
baseline
can
be
derived
by
adding
the
technology
selection
for
the
Stage
1
DBPR
(
shown
in
Appendix
C)
to
the
technologies­
in­
place
for
the
pre­
Stage
1
baseline
(
Exhibits
3.15
and
3.16).
This
is
not
true,
however,
for
plants
in
large
and
medium
surface
water
systems.
SWAT
outputs
for
"
technology
selection"
only
reflect
those
technologies
selected
for
compliance
rule
and
do
not
account
for
the
corresponding
decrease
in
technologies
out
of
which
plants
are
moving.
The
SWAT
program
produces
a
different
type
of
result
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
40
July
2003
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGY
CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
=
A
+
B
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
96.4%
453
0.0%
0
96.4%
453
0
0
3.6%
17
0.0%
0
0.0%
0
0.0%
0
3.6%
17
0%
0
101­
500
96.4%
770
0.0%
0
96.4%
770
0.0%
0
0.0%
0
3.6%
29
0.0%
0
0.0%
0
0.0%
0
3.6%
29
0%
0
501­
1,000
96.4%
487
0.0%
0
96.4%
487
0.0%
0
0.0%
0
3.6%
18
0.0%
0
0.0%
0
0.0%
0
3.6%
18
0
1,001
­
3,300
96.4%
1,064
0.0%
0
96.4%
1,064
0.0%
0
0.0%
0
3.6%
40
0.0%
0
0.0%
0
0.0%
0
3.6%
40
0%
0
3,301­
10,000
96.4%
1,169
0.0%
0
96.4%
1,169
0.0%
0
0.0%
0
3.6%
44
0.0%
0
0.0%
0
0.0%
0
3.6%
44
0
10,001­
50,000
54.0%
695
31.0%
399
85.0%
1,094
8.1%
104
5.1%
66
0.4%
5
1.5%
19
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
193
35.9%
462
50,001­
100,000
54.0%
290
31.0%
167
85.0%
457
8.1%
43
5.1%
28
0.4%
2
1.5%
8
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
81
35.9%
193
100,001­
1
Million
54.0%
309
31.0%
177
85.0%
486
8.1%
46
5.1%
29
0.4%
2
1.5%
8
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
86
35.9%
206
>
1
Million
54.0%
40
31.0%
23
85.0%
63
8.1%
6
5.1%
4
0.4%
0
1.5%
1
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
11
35.9%
26
Total
%,
Plants
80.4%
5,276
11.7%
766
92.1%
6,042
3.0%
199
1.9%
127
2.4%
156
0.6%
36
0.0%
0
0.0%
0
0.0%
0
0.0%
0
7.9%
518
13.5%
887
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.
1"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Surface
water
systems
serving
10,000
people
or
fewer:
National
Rural
Water
Survey
(
USEPA,
2001c).
Surface
water
systems
serving
more
than
10,000
people:
SWAT
initial
plant
run
(
USEPA,
2001e).
Percentage
using
chloramine
is
taken
from
the
Occurrence
Document.
TOTAL
USING
CLM
System
Size
(
Population
Served)

NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGY
CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
=
A
+
B
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
96.4%
287
0.0%
0
96.4%
287
0
0
3.6%
11
0.0%
0
0.0%
0
0.0%
0
3.6%
11
0%
0
101­
500
96.4%
290
0.0%
0
96.4%
290
0.0%
0
0.0%
0
3.6%
11
0.0%
0
0.0%
0
0.0%
0
3.6%
11
0%
0
501­
1,000
96.4%
104
0.0%
0
96.4%
104
0.0%
0
0.0%
0
3.6%
4
0.0%
0
0.0%
0
0.0%
0
3.6%
4
0
1,001
­
3,300
96.4%
69
0.0%
0
96.4%
69
0.0%
0
0.0%
0
3.6%
3
0.0%
0
0.0%
0
0.0%
0
3.6%
3
0%
0
3,301­
10,000
96.4%
22
0.0%
0
96.4%
22
0.0%
0
0.0%
0
3.6%
1
0.0%
0
0.0%
0
0.0%
0
3.6%
1
0
10,001­
50,000
54.0%
5
31.0%
3
85.0%
8
8.1%
1
5.1%
0
0.4%
0
1.5%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
1
35.9%
3
50,001­
100,000
54.0%
1
31.0%
0
85.0%
1
8.1%
0
5.1%
0
0.4%
0
1.5%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
0
35.9%
0
100,001­
1
Million
54.0%
1
31.0%
0
85.0%
1
8.1%
0
5.1%
0
0.4%
0
1.5%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
0
35.9%
0
>
1
Million
54.0%
0
31.0%
0
85.0%
0
8.1%
0
5.1%
0
0.4%
0
1.5%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
15.0%
0
35.9%
0
Total
%,
Plants
95.8%
779
0.4%
3
96.2%
782
0.1%
1
0.1%
1
3.6%
29
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
3.8%
31
0.5%
4
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.
1"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Surface
water
systems
serving
10,000
people
or
fewer:
National
Rural
Water
Survey
(
USEPA,
2001c).
Surface
water
systems
serving
more
than
10,000
people:
SWAT
initial
plant
run
(
USEPA,
2001e).
Percentage
using
chloramine
is
taken
from
the
Occurrence
Document.
TOTAL
USING
CLM
System
Size
(
Population
Served)
directly,
called
"
ending
technologies"
that
accounts
for
those
plants
that
already
have
an
advanced
technology
but
must
select
another
to
meet
the
rule
alternative.

Exhibit
3.15a
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
Plants
Exhibit
3.15b
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
41
July
2003
System
Size
(
Population
Served)
No
Adv
1
CL2
No
Adv
1
CLM
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
USING
CLM
TOTAL
A
B
C
D
E
F
G
H
I
J
K
=
B
+
D
+
F
+
H
+
J
L
=
SUM(
A:
J)
£
100
100.0%
7,772
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
7,772
101­
500
100.0%
15,725
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
15,725
501­
1,000
100.0%
6,133
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
6,133
1,001
­
3,300
100.0%
7,890
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
7,890
3,301­
10,000
100.0%
4,975
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
4,975
10,001­
50,000
92.3%
4,954
5.4%
289
0.8%
41
0.0%
0
0.0%
0
0.0%
0
1.5%
83
0.0%
0
5.4%
289
100.0%
5,367
50,001­
100,000
92.3%
682
5.4%
40
0.8%
6
0.0%
0
0.0%
0
0.0%
0
1.5%
11
0.0%
0
5.4%
40
100.0%
738
100,001­
1
Million
92.3%
808
5.4%
47
0.8%
7
0.0%
0
0.0%
0
0.0%
0
1.5%
13
0.0%
0
5.4%
47
100.0%
875
>
1
Million
92.3%
17
5.4%
1
0.8%
0
0.0%
0
0.0%
0
0.0%
0
1.5%
0
0.0%
0
5.4%
1
100.0%
18
Total
%,
Plants
98.9%
48,956
0.8%
377
0.0%
0
0.0%
0
0.1%
54
0.0%
0
0.0%
0
0.0%
0
0.2%
108
0.0%
0
0.8%
377
100.0%
49,495
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.
Membranes
CLM
Membranes
CL2
Source:
Ground
water
systems
serving
10,000
people
or
fewer
­
limited
data
available.
Assumed
only
cholrine
usage
and
no
advanced
technologies;
Ground
water
systems
serving
more
than
10,000
people
­
based
on
ICR
data
for
130
large
GW
plants.

System
Size
(
Population
Served)
No
Adv
1
CL2
No
Adv
1
CLM
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
USING
CLM
TOTAL
A
B
C
D
E
F
G
H
I
J
K
=
B
+
D
+
F
+
H
+
J
L
=
SUM(
A:
J)
£
100
100.0%
3,662
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
3,662
101­
500
100.0%
2,624
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
2,624
501­
1,000
100.0%
717
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
717
1,001
­
3,300
100.0%
267
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
267
3,301­
10,000
100.0%
27
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
27
10,001­
50,000
92.3%
4
5.4%
0
0.8%
0
0.0%
0
0.0%
0
0.0%
0
1.5%
0
0.0%
0
5.4%
0
100.0%
4
50,001­
100,000
92.3%
0
5.4%
0
0.8%
0
0.0%
0
0.0%
0
0.0%
0
1.5%
0
0.0%
0
5.4%
0
100.0%
0
100,001­
1
Million
92.3%
1
5.4%
0
0.8%
0
0.0%
0
0.0%
0
0.0%
0
1.5%
0
0.0%
0
5.4%
0
100.0%
1
>
1
Million
92.3%
0
5.4%
0
0.8%
0
0.0%
0
0.0%
0
0.0%
0
1.5%
0
0.0%
0
5.4%
0
100.0%
0
Total
%,
Plants
100.0%
7,303
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
100.0%
7,303
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.
Membranes
CLM
Membranes
CL2
Source:
Ground
water
systems
serving
10,000
people
or
fewer
­
limited
data
available.
Assumed
only
cholrine
usage
and
no
advanced
technologies;
Ground
water
systems
serving
more
than
10,000
people
­
based
on
ICR
data
for
130
large
GW
plants.
Exhibit
3.16a
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
CWS
Ground
Water
Plants
Exhibit
3.16b
Pre­
Stage
1
DBPR
Technologies­
in­
Place
for
NTNCWS
Ground
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
42
July
2003
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGY
CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
=
A
+
B
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
43.0%
202
30.5%
143
73.4%
345
18.6%
88
3.8%
18
0.0%
0
4.1%
19
26.6%
125
39.6%
186
101­
500
35.7%
285
35.6%
284
71.3%
569
2.3%
19
11.9%
95
9.9%
79
2.3%
19
0.9%
7
1.3%
10
28.7%
229
47.5%
379
501­
1,000
35.7%
180
35.6%
180
71.3%
360
2.3%
12
11.9%
60
9.9%
50
2.3%
12
0.9%
5
1.3%
6
28.7%
145
47.5%
240
1,001
­
3,300
33.5%
370
41.5%
457
75.0%
827
5.1%
56
10.1%
111
5.4%
60
2.6%
28
1.1%
12
0.7%
8
25.0%
276
52.8%
582
3,301­
10,000
33.5%
406
41.5%
503
75.0%
909
5.1%
62
10.1%
122
5.4%
66
2.6%
31
1.1%
13
0.7%
9
25.0%
303
52.8%
640
10,001­
50,000
37.7%
486
36.3%
467
74.0%
952
7.0%
90
12.8%
165
1.8%
24
2.2%
28
1.1%
14
0.4%
5
0.0%
0
0.7%
9
26.0%
335
52.7%
679
50,001­
100,000
37.7%
203
36.3%
195
74.0%
398
7.0%
37
12.8%
69
1.8%
10
2.2%
12
1.1%
6
0.4%
2
0.0%
0
0.7%
4
26.0%
140
52.7%
284
100,001­
1
Million
37.7%
216
36.3%
208
74.0%
424
7.0%
40
12.8%
73
1.8%
10
2.2%
13
1.1%
6
0.4%
2
0.0%
0
0.7%
4
26.0%
149
52.7%
302
>
1
Million
37.7%
28
36.3%
27
74.0%
54
7.0%
5
12.8%
9
1.8%
1
2.2%
2
1.1%
1
0.4%
0
0.0%
0
0.7%
1
26.0%
19
52.7%
39
Total
%,
Plants
36.2%
2,376
37.5%
2,463
73.8%
4,839
4.9%
321
10.7%
705
5.9%
388
0.8%
54
0.4%
27
1.8%
117
0.6%
38
1.1%
71
26.2%
1,721
50.8%
3,330
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.

Source:
Surface
water
systems
serving
10,000
people
or
less:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
1
DBPR
Baseline
(
Exhibit
3.15)
to
Stage
1
Technology
Selection
(
Exhibit
C.
1.
Surface
water
systems
serving
10,000
people
or
more:
Use
ending
technologies.
System
Size
(
Population
Served)
TOTAL
USING
CLM
NO
ADVANCED
TECHNOLOGIES1
WITH
ADVANCED
TECHNOLOGY
CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
=
A
+
B
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
43.0%
128
30.5%
91
73.4%
219
18.6%
56
3.8%
11
0.0%
0
4.1%
12
26.6%
79
39.6%
118
101­
500
35.7%
108
35.6%
107
71.3%
215
2.3%
7
11.9%
36
9.9%
30
2.3%
7
0.9%
3
1.3%
4
28.7%
86
47.5%
143
501­
1,000
35.7%
39
35.6%
38
71.3%
77
2.3%
3
11.9%
13
9.9%
11
2.3%
3
0.9%
1
1.3%
1
28.7%
31
47.5%
51
1,001
­
3,300
33.5%
24
41.5%
30
75.0%
54
5.1%
4
10.1%
7
5.4%
4
2.6%
2
1.1%
1
0.7%
1
25.0%
18
52.8%
38
3,301­
10,000
33.5%
8
41.5%
10
75.0%
17
5.1%
1
10.1%
2
5.4%
1
2.6%
1
1.1%
0
0.7%
0
25.0%
6
52.8%
12
10,001­
50,000
37.7%
3
36.3%
3
74.0%
7
7.0%
1
12.8%
1
1.8%
0
2.2%
0
1.1%
0
0.4%
0
0.0%
0
0.7%
0
26.0%
2
52.7%
5
50,001­
100,000
37.7%
0
36.3%
0
74.0%
1
7.0%
0
12.8%
0
1.8%
0
2.2%
0
1.1%
0
0.4%
0
0.0%
0
0.7%
0
26.0%
0
52.7%
1
100,001­
1
Million
37.7%
0
36.3%
0
74.0%
1
7.0%
0
12.8%
0
1.8%
0
2.2%
0
1.1%
0
0.4%
0
0.0%
0
0.7%
0
26.0%
0
52.7%
1
>
1
Million
37.7%
0
36.3%
0
74.0%
0
7.0%
0
12.8%
0
1.8%
0
2.2%
0
1.1%
0
0.4%
0
0.0%
0
0.7%
0
26.0%
0
52.7%
0
Total
%,
Plants
38.2%
310
34.4%
280
72.6%
590
1.9%
15
7.3%
60
12.5%
101
0.0%
0
0.0%
0
2.9%
23
0.6%
5
2.3%
18
27.4%
223
45.3%
368
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1"
No
Adv"
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Surface
water
systems
serving
10,000
people
or
less:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
1
DBPR
Baseline
(
Exhibit
3.15)
to
Stage
1
Technology
Selection
(
Exhibit
C.
1.
Surface
water
systems
serving
10,000
people
or
more:
Use
ending
technologies.
System
Size
(
Population
Served)
TOTAL
USING
CLM
Exhibit
3.17a
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
Plants
Exhibit
3.17b
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
43
July
2003
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGIES
CL2
CLM
TOTAL
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
A
B
C
=
A+
B
D
E
F
G
H
I
J
K
L
=
SUM(
D:
K)
M
=
B+
E+
G+
I+
K
£
100
95.2%
7,397
2.9%
222
98.0%
7,619
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
1.0%
80
0.4%
31
0.5%
41
2.0%
153
4.4%
343
101­
500
95.8%
15,068
2.5%
389
98.3%
15,457
0.0%
0
0.0%
0
0.1%
22
0.4%
67
0.0%
0
0.6%
88
0.1%
18
0.5%
73
1.7%
268
3.9%
617
501­
1,000
95.8%
5,877
2.5%
152
98.3%
6,029
0.0%
0
0.0%
0
0.1%
9
0.4%
26
0.0%
0
0.6%
34
0.1%
7
0.5%
28
1.7%
105
3.9%
240
1,001
­
3,300
96.6%
7,620
2.0%
160
98.6%
7,780
0.0%
0
0.0%
0
0.2%
18
0.7%
55
0.0%
0
0.0%
4
0.0%
3
0.4%
30
1.4%
110
3.1%
248
3,301­
10,000
96.6%
4,805
2.0%
101
98.6%
4,906
0.0%
0
0.0%
0
0.2%
12
0.7%
35
0.0%
0
0.0%
2
0.0%
2
0.4%
19
1.4%
70
3.1%
157
10,001­
50,000
89.1%
4,783
7.3%
390
96.4%
5,173
0.8%
45
0.8%
42
0.0%
0
0.0%
2
1.7%
89
0.3%
14
3.6%
194
8.4%
449
50,001­
100,000
89.1%
658
7.3%
54
96.4%
712
0.8%
6
0.8%
6
0.0%
0
0.0%
0
1.7%
12
0.3%
2
3.6%
27
8.4%
62
100,001­
1
Million
89.6%
784
7.0%
61
96.6%
845
0.8%
7
0.7%
6
0.0%
0
0.0%
0
1.6%
14
0.2%
2
3.4%
30
7.9%
69
>
1
Million
89.6%
16
7.0%
1
96.6%
18
0.8%
0
0.7%
0
0.0%
0
0.0%
0
1.6%
0
0.2%
0
3.4%
1
7.9%
1
Total
%,
Plants
95.0%
47,009
3.1%
1,529
98.1%
48,539
0.0%
0
0.0%
0
0.2%
120
0.5%
238
0.0%
0
0.4%
211
0.4%
178
0.4%
209
1.9%
956
4.4%
2,187
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
No
advanced
technologies
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
1
DBPR
Baseline
(
Exhibit
3.16)
to
Stage
1
Technology
Selection
(
Exhibit
C.
2)
Membranes
CL2
Membranes
CLM
TOTAL
USING
CLM
System
Size
(
Population
Served)

NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGIES
CL2
CLM
TOTAL
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
A
B
C
=
A+
B
D
E
F
G
H
I
J
K
L
=
SUM(
D:
K)
M
=
B+
E+
G+
I+
K
£
100
95.2%
3,486
2.9%
104
98.0%
3,590
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
1.0%
38
0.4%
15
0.5%
19
2.0%
72
4.4%
162
101­
500
95.8%
2,515
2.5%
65
98.3%
2,580
0.0%
0
0.0%
0
0.1%
4
0.4%
11
0.0%
0
0.6%
15
0.1%
3
0.5%
12
1.7%
45
3.9%
103
501­
1,000
95.8%
687
2.5%
18
98.3%
704
0.0%
0
0.0%
0
0.1%
1
0.4%
3
0.0%
0
0.6%
4
0.1%
1
0.5%
3
1.7%
12
3.9%
28
1,001
­
3,300
96.6%
258
2.0%
5
98.6%
263
0.0%
0
0.0%
0
0.2%
1
0.7%
2
0.0%
0
0.0%
0
0.0%
0
0.4%
1
1.4%
4
3.1%
8
3,301­
10,000
96.6%
26
2.0%
1
98.6%
27
0.0%
0
0.0%
0
0.2%
0
0.7%
0
0.0%
0
0.0%
0
0.0%
0
0.4%
0
1.4%
0
3.1%
1
10,001­
50,000
89.1%
4
7.3%
0
96.4%
4
0.8%
0
0.8%
0
0.0%
0
0.0%
0
1.7%
0
0.3%
0
3.6%
0
8.4%
0
50,001­
100,000
89.1%
0
7.3%
0
96.4%
0
0.8%
0
0.8%
0
0.0%
0
0.0%
0
1.7%
0
0.3%
0
3.6%
0
8.4%
0
100,001­
1
Million
89.6%
1
7.0%
0
96.6%
1
0.8%
0
0.7%
0
0.0%
0
0.0%
0
1.6%
0
0.2%
0
3.4%
0
7.9%
0
>
1
Million
89.6%
0
7.0%
0
96.6%
0
0.8%
0
0.7%
0
0.0%
0
0.0%
0
1.6%
0
0.2%
0
3.4%
0
7.9%
0
Total
%,
Plants
95.5%
6,976
2.6%
193
98.2%
7,170
0.0%
0
0.0%
0
0.1%
5
0.2%
16
0.0%
0
0.8%
57
0.3%
19
0.5%
36
1.8%
133
4.1%
302
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
No
advanced
technologies
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
1
DBPR
Baseline
(
Exhibit
3.16)
to
Stage
1
Technology
Selection
(
Exhibit
C.
2)
Membranes
CL2
Membranes
CLM
TOTAL
USING
CLM
System
Size
(
Population
Served)
Exhibit
3.18a
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Ground
Water
Plants
Exhibit
3.18b
Pre­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Ground
Water
Plants
10
SWAT
results
are
used
for
both
cost
and
quantified
benefits
analysis
in
this
EA.
SWAT
results
are
used
to
predict
treatment
changes
and
resulting
treatment
costs
(
see
Chapter
6)
and
to
predict
reductions
in
average
DBP
levels.
Changes
in
average
DBP
levels
are
the
basis
for
quantifying
the
reduction
in
bladder
cancer
cases
attributable
to
the
Stage
2
DBPR
(
see
Chapter
5).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
44
July
2003
3.7
DBP
Occurrence
for
the
Pre­
Stage
1
and
Pre­
Stage
2
DBPR
Baselines
For
pre­
Stage
1
DBPR
conditions,
observed
DBP
data
is
available
from
the
ICR
for
large
systems
and
from
the
NRWA
survey,
WATER:\
STATS,
and
other
data
sources
for
medium
and
small
systems
(
see
section
3.2
for
a
summary
of
data
sources).
Because
the
Stage
1
DBPR
compliance
deadline
recently
occurred
(
January
2002)
for
large
and
medium
surface
water
systems
and
will
not
occur
until
January
2004
for
all
other
systems,
observed
DBP
data
for
pre­
Stage
2,
or
post­
Stage
1
conditions
are
not
available
and
must
be
predicted
for
this
EA.

As
stated
in
section
3.3,
SWAT
was
the
primary
tool
used
during
the
M­
DBP
FACA
process
and
in
this
EA
to
predict
changes
in
treatment
and
related
reductions
in
national
DBP
levels
as
a
result
of
the
Stage
1
and
Stage
2
DBPRs.
10
Comparisons
of
SWAT
to
ICR
data,
however,
showed
large
differences
between
observations
and
modeled
data
in
some
cases
(
see
Appendix
A
for
plant­
by­
plant
comparisons
of
SWAT
and
ICR
data).
This
is
to
be
expected
to
some
extent
 
the
SWAT­
predicted
DBP
concentration
is
a
function
of
influent
water
quality,
treatment
conditions,
flows,
residence
times,
and
other
factors
that
are
incorporated
into
the
model
algorithms.
In
essence,
SWAT
models
a
particular
"
slug"
of
water
from
the
source
through
the
distribution
system.
Non­
uniform
flow,
mixing,
sampling
time,
and
other
factors
in
the
field
do
not
allow
a
perfect
correlation
between
the
influent
water
sample
and
finished
water
sample.
Also,
the
distribution
system
sampling
locations
for
the
ICR
are
similar,
but
not
equivalent
to,
the
conditions
modeled
by
SWAT.
For
example,
the
ICR
data
set
uses
the
average
value
of
the
concentrations
at
four
sampling
locations:
two
thought
to
represent
the
average
residence
time
in
the
distribution
system,
one
thought
to
represent
the
maximum
residence
time,
and
another
located
elsewhere
in
the
distribution
system.
The
modeled
distribution
system
data
are
computed
using
the
average
residence
time
in
the
distribution
system,
based
on
the
average
of
the
residence
times
at
the
four
ICR
distribution
system
locations.
Appendix
A
provides
the
rationale
for
why
SWAT
was
selected
as
the
primary
tool
for
estimating
benefits
and
costs
of
the
Stage
2
DBPR,
along
with
a
summary
of
uncertainties
and
biases
introduced
by
its
use.

Because
of
uncertainties
in
the
modeled
data,
changes
in
occurrence
of
peak
DBP
concentrations
are
predicted
using
ICR
rather
than
SWAT
data.
Section
5.4.1
summarizes
the
methodology
for
predicting
changes
in
single
peak
DBP
occurrences
using
ICR
data.

Section
3.7.1
provides
background
information
describing
ICR
and
SWAT
DBP
data
evaluated
in
this
EA.
Section
3.7.2
summarizes
pre­
Stage
1
and
pre­
Stage
2
DBP
occurrence
data
for
large
surface
water
systems.
Pre­
Stage
1
and
pre­
Stage
2
DBPR
occurrence
levels
for
large
ground
water
systems
are
provided
in
section
3.7.3.
DBP
occurrence
for
medium
systems
is
discussed
in
section
3.7.4,
followed
by
presentation
of
small
system
data
in
section
3.7.5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
45
July
2003
3.7.1
Description
of
ICR
and
SWAT
DBP
Data
3.7.1.1
ICR
DBP
Data
Analysis
of
ICR
DBP
data
in
this
EA
is
consistent
with
the
methodology
used
in
the
Occurrence
Document
(
USEPA
2003l)
and
in
Chapter
5.
A
brief
description
of
the
data
and
assumptions
used
for
data
analyses
are
provided
below.

Distribution
System
Sampling
Locations
Quarterly
TTHM
and
HAA5
data
were
collected
at
the
following
distribution
system
sampling
locations
(
note
that
these
locations
are
each
associated
with
one
ICR
plant):

°
Average
1
(
AVG
1)
and
Average
2
(
AVG
2)
 
two
sample
locations
in
the
distribution
system,
each
representing
an
approximate
average
residence
time,
as
designated
by
the
water
system.

°
Distribution
System
Maximum
(
DS
Maximum)
 
the
sample
location
in
the
distribution
system
that
has
the
longest
residence
time,
as
designated
by
the
water
system.

°
Distribution
System
Equivalent
Location
(
DSE)
 
a
sample
location
in
the
distribution
system
that
has
a
known
residence
time,
where
no
additional
disinfectant
has
been
added
between
the
plant
and
sample
location,
and
where
there
has
been
no
blending
with
water
from
other
plants.

Sample
Collection
Period
TTHM
and
HAA5
data
were
collected
quarterly
from
the
period
of
July
1997
to
December
1998
(
6
quarters).
Analyses
of
TTHM
and
HAA5
data
in
this
EA
were
limited
to
the
last
4
quarters
of
the
ICR
collection
period
(
January
to
December
1998).
Only
the
last
4
quarters
were
evaluated
because
they
appear
to
be
of
higher
quality
than
data
collected
during
the
first
6
months
of
the
survey.
In
addition,
using
all
18
months
of
data
could
skew
results
(
data
from
the
last
2
quarters
of
the
year
would
be
counted
twice).

Plant
Source
Water
Types
Plants
were
required
to
report
source
water
type
for
each
month
from
July
1997
to
December
1998.
The
types
of
sources
recorded
were
surface
water,
ground
water,
mixed,
or
purchased.
Most
plants
reported
on
one
source
type
for
all
months,
but
some
plants
reported
surface
water
for
some
months
and
mixed
for
others.
These
plants
were
considered
surface
water
plants.
One
ground
water
plant
reported
ground
water
for
some
months
and
mixed
for
others
 
this
plant
was
considered
a
ground
water.
Analyses
of
all
plants
includes
"
blended,"
"
mixed,"
and
"
purchased"
plant­
types
from
the
ICR
database.
These
plant
types
make
up
a
small
portion
(
less
than
10
percent)
of
the
total
 
most
ICR
plants
are
categorized
as
either
surface
or
ground
water
plants.

Initial
Plant
Screening
All
ICR
plants
(
there
are
approximately
500
plants
in
the
ICR
database)
were
screened
to
ensure
that
at
least
3
of
4
quarters
have
TTHM
and
HAA5
data
for
at
least
3
of
4
distribution
system
locations.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
46
July
2003
Results
of
the
screening
process
are
detailed
in
Chapter
5
and
summarized
in
Exhibit
5.10.
Note
that
the
total
number
of
plants
that
meet
the
minimum
screening
criteria
(
311
plants,
of
which
213
are
surface
water
plants,
83
are
ground
water
plants,
and
15
are
either
blended,
mixed,
or
purchase
plants)
represents
more
than
60
percent
of
all
large
plants
that
participated
in
the
ICR
data
collection
effort.

3.7.1.2
SWAT
DBP
Data
SWAT
produces
monthly
estimates
of
DBP
occurrence
for
surface
water
plants
at
only
two
distribution
system
locations:

°
Distribution
System
Average
(
DS
Average)
 
theoretical
location
with
average
residence
time
(
calculated
by
averaging
the
residence
times
reported
by
the
water
system
for
the
four
locations
listed
above).

°
Distribution
System
Maximum
(
DS
Maximum)
 
theoretical
location
with
the
maximum
residence
time
(
highest
residence
time
reported
for
the
four
locations
above).

Data
from
these
locations
are
compared
and
summarized
in
subsequent
sections.

3.7.2
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Large
Surface
Water
Plants
Exhibit
3.19
summarizes
the
TTHM,
HAA5,
bromate,
and
chlorite
occurrence
for
pre­
Stage
1
and
pre­
Stage
2
baseline
conditions.
Pre­
Stage
1
occurrence
is
shown
for
both
observed
ICR
data
and
SWAT­
predicted
data.
Pre­
Stage
2
data
shown
in
Exhibit
3.19
are
predicted
by
SWAT
only.
Exhibits
3.20
through
3.23
show
the
cumulative
distributions
of
the
same
plant­
mean
and
individual
observations
(
monthly
DBP
concentrations)
for
SWAT
data.
SWAT
plant­
mean
data
represent
plant­
mean
concentrations
at
the
DS
Average
(
average
residence
time)
location.
ICR
plant­
mean
data
represent
the
average
of
four
distribution
system
locations
(
AVG1,
AVG2,
DSE,
and
DS
Maximum).
Bromate
and
chlorite
data
represent
finished
water
concentrations
from
both
ICR
and
SWAT
data
sets,
although
ICR
chlorite
data
show
the
maximum
finished
water
concentration
at
each
plant,
rather
than
the
plant­
mean.
Statistical
calculations
of
individual
observations
are
for
SWAT
monthly
data
and
ICR
quarterly
data.

Pre­
Stage
1
conditions
are
modeled
by
SWAT
because,
in
Chapter
5,
predicted
pre­
Stage
2
and
post­
Stage
2
DBP
levels
are
subtracted
from
pre­
Stage
1
levels
to
assess
the
overall
changes
in
DBP
concentrations
as
a
result
of
the
regulations.
Pre­
Stage
1
modeled
data
were
used
instead
of
pre­
Stage
1
observed
(
ICR)
data
to
ensure
that
the
results
of
the
analyses
would
represent
only
changes
in
exposure
resulting
from
different
rule
requirements
and
would
not
reflect
inherent
differences
between
observed
and
modeled
data.

As
summarized
in
Exhibit
3.19,
SWAT
predicts
that
TTHM
plant­
means
will
decrease
from
an
average
of
49
µ
g/
L
at
pre­
Stage
1
conditions
to
35
µ
g/
L
at
pre­
Stage
2
conditions.
Looking
at
the
average
of
plant­
mean
data,
the
HAA5
occurrence
decreases
by
approximately
30
percent,
from
36
µ
g/
L
at
pre­
Stage
1
to
25
µ
g/
L
at
pre­
Stage
2
conditions.
Bromate
and
chlorite
concentrations
are
predicted
to
decrease
slightly
under
the
Stage
1
DBPR
because
of
the
MCLs
established
for
these
contaminants.
Note,
however,
that
the
bromate
and
chlorite
distributions
apply
only
to
plants
that
use
ozone
and
chlorine
dioxide,
respectively,
and
that
the
universe
of
plants
using
those
technologies
may
vary
from
pre­
Stage
1
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
47
July
2003
to
pre­
Stage
2
(
SWAT
predicts
that
the
number
of
plants
using
ozone
will
increase
from
15
to
39
from
pre­
Stage
1
to
pre­
Stage
2,
while
the
number
using
chlorine
dioxide
will
stay
constant
at
22).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
48
July
2003
Exhibit
3.19
Summary
of
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Large
Surface
Water
Plants,
DS
Average
Data
Parameter
Plant­
Mean
Data
Individual
Observations
N
Mean
Median
90th
%
ile
Range
N
Mean
Median
90th
%
ile
Range
TTHM
(
µ
g/
L)

Pre­
Stage
1
(
ICR)
213
42
40
70
0­
117
3083
42
37
78
0­
177
Pre­
Stage
1
(
SWAT)
273
49
44
90
3­
207
2784
49
39
100
0­
356
Pre­
Stage
2
(
SWAT)
273
35
36
57
3­
64
2784
36
33
62
0­
206
HAA5
(
µ
g/
L)

Pre­
Stage
1
(
ICR)
213
29
24
53
0­
116
3083
29
23
55
0­
188
Pre­
Stage
1
(
SWAT)
273
36
29
70
1­
146
2784
36
27
77
0­
294
Pre­
Stage
2
(
SWAT)
273
25
25
41
1­
48
2784
25
23
44
0­
138
Bromate
(
µ
g/
L)
(
Ozone
plants
only)

Pre­
Stage
1
(
ICR)
14
2.6
2.2
5.4
0.02­
7.2
157
2.6
1.9
6.7
<
0.2­
14.6
Pre­
Stage
1
(
SWAT)
15
6.3
1.8
19.6
0.2­
28
156
6.1
1.9
18
0.1­
62
Pre­
Stage
2
(
SWAT)
39
2.2
1.8
4.1
0.04­
7.4
409
2.3
1.7
4.7
0.01­
17
Chlorite
(
µ
g/
L)
(
Chlorine
dioxide
plants
only)

Pre­
Stage
1
(
ICR)
18
429
465
701
2.2­
1105
192
435
435
830
<
20­
1719
Pre­
Stage
1
(
SWAT)
22
663
708
861
10­
1483
177
636
700
1309
42­
1680
Pre­
Stage
2
(
SWAT)
22
417
404
628
140­
715
200
402
383
656
14­
784
Note:
For
TTHM
and
HAA5
data,
SWAT
data
are
from
the
DS
Average
location
and
ICR
data
are
the
average
of
four
distribution
system
locations
for
the
last
12
months
of
the
ICR
collection
period
(
January
1998­
December
1998).
For
bromate
and
chlorite
data,
finished
water
data
from
both
SWAT
and
ICR
are
used.
All
SWAT
data
are
based
on
monthly
predicted
observations,
ICR
TTHM
and
HAA5
data
are
based
on
quarterly
observations,
and
ICR
chlorite
and
bromate
data
are
based
on
monthly
observations.
For
ICR
data,
only
individual
observations
used
to
calculate
plant
means
are
shown.
For
ICR
data,
only
plants
that
have
data
for
3
of
the
last
4
quarters
were
included,
and,
for
ICR
TTHM
and
HAA5
data,
only
plants
with
at
least
3
of
the
4
required
distribution
system
samples
each
quarter
were
included.

Sources:
SWAT
Initial
Plant
Run
and
Run
300
(
USEPA
2001e);
ICR
AUX1
Database
(
USEPA
2000h).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
49
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
50
100
150
200
250
TTHM
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
50
100
150
200
250
TTHM
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
Exhibit
3.20a
Cumulative
Distributions
of
TTHM
Monthly
Data
Predicted
by
SWAT
(
DS
Average)

Exhibit
3.20b
Cumulative
Distributions
of
TTHM
Plant­
Mean
Data
Predicted
by
SWAT
(
DS
Average)

Note:
DS
Average
data
from
SWAT;
for
pre­
Stage
2,
SWAT
requires
all
plants
to
use
a
technology
that
results
in
an
annual
average
less
than
64
µ
g/
L
(
based
on
the
Stage
1
DBPR
TTHM
MCL
of
80
µ
g/
L
with
a
20
percent
safety
factor).

Source:
SWAT
Initial
Plant
Run
and
Run
300
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
50
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
50
100
150
200
HAA5
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
50
100
150
200
HAA5
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
Exhibit
3.21a
Cumulative
Distributions
of
HAA5
Monthly
Data
Predicted
by
SWAT
(
DS
Average)

Exhibit
3.21b
Cumulative
Distributions
of
HAA5
Plant­
Mean
Data
Predicted
by
SWAT
(
DS
Average)

Note:
DS
Average
data
from
SWAT;
for
pre­
Stage
2,
SWAT
requires
all
plants
to
use
a
technology
that
results
in
an
annual
average
less
than
48
µ
g/
L
(
based
on
the
Stage
I
DBPR
HAA5
MCL
of
60
µ
g/
L
with
a
20
percent
safety
factor).

Source:
SWAT
Initial
Plant
Run
and
Run
300
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
51
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
5
10
15
20
25
30
35
40
Bromate
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
5
10
15
20
25
30
35
40
Bromate
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
Exhibit
3.22a
Cumulative
Distributions
of
Bromate
Monthly
Data
Predicted
by
SWAT
(
Finished
Water)

Exhibit
3.22b
Cumulative
Distributions
of
Bromate
Plant­
Mean
Data
Predicted
by
SWAT
(
Finished
Water)

Note:
Finished
water
data
from
SWAT
for
ozone
plants
only.
Because
some
plants
change
technology
from
pre­
Stage
1
to
pre­
Stage
2,
the
number
of
ozone
plants
is
different
for
the
two
data
sets
(
15
plants
in
the
pre­
Stage
1
distribution,
and
39
plants
in
the
pre­
Stage
2
distribution).

Source:
SWAT
Initial
Plant
Run
and
Run
300
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
52
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
200
400
600
800
1000
1200
1400
1600
1800
Chlorite
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
200
400
600
800
1000
1200
1400
1600
1800
Chlorite
(
m
g/
L)
Cumulative
Percent
Pre­
Stage
1
Pre­
Stage
2
Exhibit
3.23a
Cumulative
Distributions
of
Chlorite
Monthly
Data
Predicted
by
SWAT
(
Finished
Water)

Exhibit
3.23b
Cumulative
Distributions
of
Chlorite
Plant­
Mean
Data
Predicted
by
SWAT
(
Finished
Water)

Note:
Finished
water
data
from
SWAT.
Includes
chlorine
dioxide
plants
only.
Both
distributions
represent
22
plants;
however,
the
plants
are
not
the
same
because
some
systems
added
chlorine
dioxide
for
Stage
1
and
some
systems
changed
form
chlorine
dioxide
to
a
more
advance
technology
for
Stage
1
(
resulting
a
net
change
of
zero
in
the
number
of
plants).

Source:
SWAT
Initial
Plant
Run
and
Run
300
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
53
July
2003
3.7.3
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
in
Large
Ground
Water
Plants
ICR
data
were
the
only
source
of
pre­
Stage
1
DBP
data
for
large
ground
water
systems.
There
are
limited
or
no
data
on
bromate
and
chlorite,
since
these
DBPs
were
monitored
only
by
plants
using
ozone
or
chlorine
dioxide,
and
only
one
ground
water
plant
in
the
ICR
used
these
disinfectants
(
USEPA
2001i).
TTHM
and
HAA5
data
for
these
plants
are
summarized
in
Exhibit
3.24.
DBP
levels
in
ground
water
are
significantly
less
than
in
large
surface
water
plants
(
see
Exhibit
3.19);
mean
TTHM
levels
in
ground
water
plants
are
less
than
half
those
in
large
surface
water
plants,
compared
to
observed
or
modeled
surface
water
data.
Ground
water
data
are
more
skewed
than
surface
water
data;
there
is
a
much
bigger
difference
between
the
median
and
the
mean
values
for
ground
water.

Because
a
modeling
tool
similar
to
SWAT
could
not
be
used
for
large
ground
water
plants,
predictions
of
DBP
occurrence
for
pre­
Stage
2
DBPR
(
post­
Stage
1)
are
unavailable.
Therefore,
average
reductions
in
DBP
occurrence
were
extrapolated
from
SWAT
data,
taking
into
account
the
percentage
of
large
ground
water
plants
that
are
predicted
to
change
technologies
relative
to
the
percentage
of
large
surface
water
plants
that
change.
Exhibit
3.24
presents
results
of
the
predicted
DBP
reduction
for
mean
TTHM
and
HAA5
concentrations.
Appendix
E
(
section
E.
3)
provides
detailed
methodology,
calculations,
and
results
for
predicted
pre­
Stage
2
DBP
occurrence
for
large
ground
water
plants.

Exhibit
3.24
Summary
of
Pre­
Stage
1
DBP
Occurrence
for
Large
Ground
Water
Plants,
ICR
Data
Parameter
Plant­
Mean
Data
Individual
Observations
N
Mean
Median
90th
%
ile
Range
N
Mean
Median
90th
%
ile
Range
TTHM
(
µ
g/
L)

Pre­
Stage
1
96
16.7
7.8
48
0­
123
360
16
6.5
47
0­
156
Pre­
Stage
2
­
16.2
­
­
­
­
­
­
­

HAA5
(
µ
g/
L)

Pre­
Stage
1
99
8.9
2.7
25
0­
71
373
8.8
2.0
28
0­
96
Pre­
Stage
2
­
8.6
­
­
­
­
­
­
­
­

Source:
Pre­
Stage
1
data:
AUX1
database
(
USEPA
2000h),
based
on
data
from
January
1998­
December
1998.
Only
plants
that
had
at
least
3
distribution
system
samples
in
each
of
at
least
3
of
the
last
4
quarters
were
included.
Pre­
Stage
2
data:
mean
DBP
concentration
derived
from
percent
DBP
reduction
for
surface
water
plants,
adjusted
to
account
for
relative
change
in
technologies
(
see
Appendix
E,
section
E.
3
for
derivation).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
54
July
2003
3.7.4
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrence
for
Medium
Surface
and
Ground
Water
Plants
DBP
occurrence
data
for
medium
ground
water
and
surface
water
plants
are
limited.
Plantmean
data
on
TTHM
are
available
from
WATER:\
STATS,
a
database
compiled
by
the
American
Water
Works
Association
(
AWWA
2000).
Graphs
of
WATER:\
STATS
data
in
Appendix
A
show
that
DBP
levels
and
water
quality
parameter
levels
are
similar
in
medium
and
large
surface
water
plants.
Graphs
for
ground
water
in
the
Occurrence
Document
(
USEPA
2003l)
also
show
similarities
between
medium
and
large
ground
water
plants.
Therefore,
EPA
assumed
that
DBP
occurrence
for
medium
surface
water
and
ground
water
plants
is
roughly
equivalent
to
DBP
occurrence
for
large
surface
water
and
ground
water
plants,
respectively.

3.7.5
Pre­
Stage
1
and
Pre­
Stage
2
DBP
Occurrences
for
Small
Surface
and
Ground
Water
Plants
The
small
system
experts
used
NRWA
survey
data
and
TTHM
data
submitted
to
EPA
from
eight
States
to
assess
pre­
Stage
1
DBP
occurrence
levels
for
small
surface
and
ground
water
plants.
Exhibit
3.25
summarizes
the
TTHM
and
HAA5
data
from
these
two
data
sets.

Although
Exhibit
3.25
shows
that
TTHM
levels
from
the
State
data
set
are
higher
than
the
levels
from
the
NRWA
data
set,
NRWA
data
are
considered
more
reliable
and
representative
of
national
pre­
Stage
1
DBP
occurrence
than
the
State
surface
water
data.
For
further
characterization
of
small
surface
and
ground
water
plant
data
sets,
refer
to
Chapter
3
of
the
Occurrence
Document
(
USEPA
2003l).
Therefore,
NRWA
observed
data
were
used
to
describe
occurrence
for
small
surface
water
plants.

A
modeling
tool
similar
to
SWAT
used
for
large
surface
water
plants
was
not
available
to
predict
pre­
Stage
2
(
post­
Stage
1)
DBP
occurrence
for
small
surface
and
ground
water
plants.
Reductions
in
DBP
occurrence
from
pre­
Stage
1
to
pre­
Stage
2
were
extrapolated
from
SWAT
data,
taking
into
account
the
relative
percent
of
plants
that
change
technologies
relative
to
large
surface
water
plants.
Appendix
E
(
section
E.
3)
provides
detailed
methodology,
calculations,
and
results
for
predicted
pre­
Stage
2
DBP
occurrence
for
small
surface
and
ground
water
plants.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
55
July
2003
Exhibit
3.25
Summary
of
Pre­
Stage
1
DBP
Occurrence
Data
for
Small
Systems,
DS
Average
Data
Parameter
(
source)
Plant­
Mean
Data
Individual
Observations
N
Mean
Median
90th
%
ile
Range
N
Mean
Median
90th
%
ile
Range
TTHM
(
µ
g/
L)

Pre­
Stage
1
(
NRWA
survey,
SW
systems)
96
83
62
168
0­
328
192
83
63
162
0­
446
Pre­
Stage
1
(
State
data,
SW
systems)
562
99
66
215
0­
687
N/
A
N/
A
N/
A
N/
A
N/
A
Pre­
Stage
1
(
State
data,
GW
systems)
233
6
17
3
46
0­
655
N/
A
N/
A
N/
A
N/
A
N/
A
Pre­
Stage
2
(
SW
systems)
­
35
­
­
­
­
­
­
­
­

Pre­
Stage
2
(
GW
systems)
­
16
­
­
­
­
­
­
­
­

HAA5
(
µ
g/
L)

Pre­
Stage
1
(
NRWA
survey,
SW
only)
96
45
35
83
0­
262
192
45
34
88
0­
381
Pre­
Stage
2
(
SW
systems)
­
25
­
­
­
­
­
­
­
­

Pre­
Stage
2
(
GW
systems)
­
8
­
­
­
­
­
­
­
­

Source:
Pre­
Stage
1
data:
NRWA
data
(
USEPA
2001c)
are
weighted
averages
of
data
at
locations
with
average
and
maximum
residence
time
in
the
distribution
system.
Average
residence
time
data
are
weighted
three
times
more
than
maximum
residence
time
data
to
make
data
equivalent
to
DS
Averages
calculated
for
ICR
TTHM
and
HAA5.
NRWA
plant­
mean
data
include
only
those
plants
that
had
data
for
both
sampling
periods
and
for
both
distribution
system
locations.
Only
those
individual
observations
that
were
used
to
calculate
plant­
mean
data
are
shown
here.
State
data
(
USEPA
2001i)
are
a
mixed
data
set
from
eight
States
for
surface
water
and
seven
States
for
ground
water;
N/
A
indicates
no
individual
observations
were
available
for
this
data
set.
Pre­
Stage
2
data:
mean
DBP
concentration
derived
from
percent
DBP
reduction
for
surface
water
plants,
adjusted
to
account
for
relative
change
in
technologies
(
see
Appendix
E
for
derivation).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
3­
56
July
2003
3.8
Summary
of
Uncertainties
in
Development
of
Stage
2
DBPR
Baselines
There
is
uncertainty
in
this
baseline
analysis
due
to
measurement
error
or
incomplete
information
that
could
result
in
either
an
over­
estimate
or
under­
estimate
of
the
costs
and/
or
benefits
as
presented
in
Chapters
5
and
6.
Exhibit
3.26
below
presents
a
summary
of
these
issues
and
an
estimate
of
the
effects
that
each
may
have
on
subsequent
analyses.
Note
the
effects
on
benefits
and
costs
is
unknown
for
most
of
the
uncertainties
listed
in
Exhibit
3.26.

Exhibit
3.26
Summary
of
Uncertainties
Affecting
Stage
2
DBPR
Baseline
Estimates
Uncertainty
Section
with
Full
Discussion
of
Uncertainty
Effect
on
Benefit
Estimate
Effect
on
Cost
Estimates
Underestimate
Overestimate
Unknown
Impact
Underestimate
Overestimate
Unknown
Impact
Uncertainty
in
baseline
data
inputs
(
SDWIS
and
1995
CWSS
data)
3.4.2
X
X
Mean
value
instead
of
distribution
for
plants
per
system
and
flow
per
system
3.4.2
3.4.3
X
X
CWS
flow
equations
for
NTNCWSs
3.4.3
X
X
SWAT
prediction
of
Pre­
Stage
1
and
Pre­
Stage
2
DBP
occurrence
3.7.1
X
X
Extrapolation
of
large
systems
predicted
DBP
occurrence
to
medium
and
small
systems
for
Pre­
Stage
2
Appendix
E
X
X
Uncertainties
in
NRWA
and
State
data
for
small
systems
3.7.6
X
X
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
1
4.
Consideration
of
Regulatory
Alternatives
4.1
Introduction
To
address
the
public
health
concerns
presented
in
Chapter
2
and
discussed
in
more
detail
in
Chapter
5,
the
Environmental
Protection
Agency
(
EPA)
convened
the
Microbial­
Disinfectants/
Disinfection
Byproducts
(
M­
DBP)
Advisory
Committee
under
the
Federal
Advisory
Committees
Act
(
FACA)
to
explore
a
number
of
regulatory
alternatives
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
The
M­
DBP
Advisory
Committee
was
composed
of
representatives
from
the
following
groups:

All
Indian
Pueblo
Council,
Pueblo
Office
of
Environmental
Protection
American
Water
Works
Association
Association
of
Metropolitan
Water
Agencies
Association
of
State
Drinking
Water
Administrators
Chlorine
Chemistry
Council
Clean
Water
Action
Conservation
Law
Foundation
Environmental
Council
of
the
States
International
Ozone
Association
National
Association
of
County
and
City
Health
Officials
National
Association
of
People
with
AIDS
National
Association
of
Regulatory
Utility
Commissioners
National
Association
of
State
Utility
Consumer
Advocates
National
Association
of
Water
Companies
National
Environmental
Health
Association
National
League
of
Cities
National
Resources
Defense
Council
National
Rural
Water
Association
Physicians
for
Social
Responsibility
Unfiltered
Systems
U.
S.
Environmental
Protection
Agency
Water
and
Wastewater
Equipment
Manufacturers
Association
M­
DBP
deliberations
began
the
Spring
of
1999
and
culminated
in
December
2000
and
are
documented
on
EPA's
website
in
the
form
of
meeting
summaries
(
USEPA
2000p).

This
chapter
describes
the
process
for
developing
regulatory
alternatives,
then
summarizes
the
four
Stage
2
DBPR
regulatory
alternatives
considered
in
this
Economic
Analysis
(
EA).
Among
the
four
alternatives
is
the
Preferred
Alternative,
which
reflects
the
recommendation
of
the
M­
DBP
Advisory
Committee.

4.2
Process
for
Development
of
Regulatory
Alternatives
The
process
that
led
to
the
development
of
the
Stage
2
DBPR
now
being
proposed
began
with
the
initiation
of
a
negotiated
rulemaking
by
EPA
in
1992
to
address
public
health
concerns
related
to
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
2
disinfectants,
disinfection
byproducts
(
DBPs),
and
microbial
pathogens.
The
Regulatory
Negotiation
Committee
met
from
November
1992
through
June
1993.
The
Committee
included
representatives
of
State
and
local
public
health
and
regulatory
agencies,
public
water
systems,
elected
officials,
consumer
groups,
and
environmental
groups.
As
a
result
of
its
deliberations,
the
Committee
recommended
the
development
of
three
sets
of
rules:

°
A
two­
stage
approach
for
regulations
to
control
risks
from
DBPs.

°
A
two­
stage
approach
for
regulations
to
control
risks
from
microbial
contaminants
(
the
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IESWTR)
and
the
Long
Term
Enhanced
Surface
Water
Treatment
Rule).

°
An
information
collection
rule
to
support
the
above.

The
Information
Collection
Rule
(
ICR)
was
promulgated
in
May
1996.
The
DBP
and
microbial
regulatory
process
recommendations
of
the
Committee
were
subsequently
incorporated
into
the
1996
SDWA
Amendments
as
statutory
requirements.
The
Stage
1
DBPR
and
the
IESWTR
were
both
promulgated
by
EPA
in
December
1998.

Results
from
the
1996
ICR,
which
were
gathered
between
July
1997
and
December
1998,
provided
the
M­
DBP
Advisory
Committee
and
EPA
with
a
wealth
of
information
on
large
water
systems,
their
treatment
processes,
and
the
quality
of
their
source
and
finished
waters.
This
information
was
used
to
develop
and
run
Surface
Water
Analytical
Tool
(
SWAT)
(
a
model
that
uses
a
series
of
algorithms
and
decision
rules
to
predict
treatment
changes
and
DBP
occurrence
for
regulatory
alternatives;
see
Appendix
A).
The
output
from
SWAT
formed
much
of
the
basis
for
estimates
of
national
cost
and
DBP
exposure
for
the
regulatory
alternatives
under
consideration.
Additional
data
were
obtained
from
a
survey
conducted
by
the
National
Rural
Water
Association
(
NRWA)
of
120
smaller
systems
 
serving
fewer
than
10,000
people
 
as
well
as
from
a
variety
of
State
data
sources.

The
M­
DBP
Advisory
Committee
considered
several
key
questions
during
the
negotiation
process,
including:

°
What
health
effects
will
the
Stage
2
DBPR
address?

°
Should
disinfectants
and
DBPs
not
regulated
under
the
Stage
1
DBPR
now
be
regulated?

°
Should
standards
for
disinfectants
and
DBPs
set
under
the
Stage
1
DBPR
be
amended?

°
Should
monitoring
requirements
under
the
Stage
1
DBPR
be
amended?

°
Should
compliance
standards
be
calculated
differently
than
those
in
the
Stage
1
DBPR?

°
What
are
the
risk
tradeoffs
that
need
to
be
considered?

EPA
used
SWAT
to
develop
rough
estimates
of
costs
and
DBP
exposure
reductions
for
over
a
hundred
possible
rule
alternatives.
Of
these,
the
M­
DBP
Advisory
Committee
focused
its
attention
on
those
alternatives
that
would
reduce
peaks
in
DBP
exposure
that
may
occur
throughout
the
distribution
system.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
3
4.3
Regulatory
Alternatives
Considered
There
are
four
Stage
2
DBPR
regulatory
options
considered
in
this
EA.
They
include
what
is
referred
to
as
the
Preferred
Alternative,
reflecting
the
recommendation
of
the
M­
DBP
Advisory
Committee,
and
three
other
alternatives
studied
by
the
Committee,
but
not
selected
for
reasons
noted
below.
Though
not
selected
as
a
preferred
option,
the
Committee
considered
each
of
those
other
three
options
as
alternatives
worth
careful
consideration;
EPA
carried
them
through
the
full
cost
and
benefit
analysis
process
for
comparison
with
the
Preferred
Alternative.

The
goal
of
the
M­
DBP
Advisory
Committee
was
to
increase
the
stringency
of
the
total
trihalomethanes
(
TTHM)
and
haloacetic
acids
(
HAA5)
compliance
standards
by
reducing
peak
concentrations
of
DBPs
in
distribution
systems.
The
Advisory
Committee
debated
three
different
compliance
determination
approaches.
The
first,
a
running
annual
average
(
RAA),
bases
compliance
on
the
average
of
all
samples
taken
over
a
12­
month
period,
and
allows
certain
monitoring
locations
to
be
exposed
to
DBP
levels
higher
than
the
maximum
contaminant
level
(
MCL)
as
long
as
the
average
does
not
exceed
the
MCL.
The
second
approach,
a
locational
running
annual
average
(
LRAA),
bases
compliance
on
the
average
of
all
samples
taken
at
each
specific
monitoring
location
over
a
12­
month
period,
and
requires
all
monitoring
locations
to
be
exposed
to
average
DBP
levels
lower
than
the
MCL.
The
third,
a
single
highest
(
SH)
value,
bases
compliance
on
each
individual
sample
meeting
the
MCL,
and
requires
all
monitoring
locations
never
to
be
exposed
to
DBP
levels
higher
than
the
MCL.
Compared
to
RAA
compliance
options,
the
options
involving
LRAA
and
SH
compliance
measures
focus
on
reducing
peak
exposures
 
and
the
potential
inequalities
in
exposure
resulting
from
them
 
to
customers
served
in
some
parts
of
distribution
systems.

The
following
discussion
provides
details
of
the
four
main
regulatory
alternatives
considered.

Preferred
Alternative
The
Stage
1
DBPR
set
MCLs
for
total
TTHM
at
80
µ
g/
L
and
HAA5
at
60
µ
g/
L,
each
measured
as
a
RAA
based
on
quarterly
averages
of
all
samples
taken.
The
Stage
2
Preferred
Alternative
retains
these
MCL
values,
but
modifies
how
compliance
is
determined
for
TTHM
and
HAA5
under
the
Stage
1
DBPR.
Its
components
include:

°
MCL
of
80
µ
g/
L
TTHM
measured
as
an
LRAA
°
MCL
of
60
µ
g/
L
HAA5
measured
as
an
LRAA
°
MCL
of
10
µ
g/
L
bromate
measured
as
an
RAA,
based
on
monthly
samples
taken
at
the
finished
water
point
(
no
change
from
the
Stage
1
DBPR)

Under
the
Preferred
Alternative
for
the
Stage
2
DBPR,
systems
are
required
to
identify
the
compliance
monitoring
sites
that
most
accurately
reflect
high
TTHM
and
HAA5
levels
(
the
Initial
Distribution
System
Evaluation
(
IDSE))
and
to
monitor
at
these
locations.
The
purpose
of
this
alternative
is
to
control
the
levels
of
TTHM
and
HAA5
at
locations
in
the
distribution
system
with
the
highest
levels
of
these
DBPs
so
that
systems
are
assured
of
meeting
the
MCLs
throughout
the
entire
distribution
system.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
4
Alternative
1
This
alternative
has
the
same
TTHM
and
HAA5
requirements
as
the
Preferred
Alternative,
but
has
a
lower
MCL
for
bromate.
Its
components
include:

°
MCL
of
80
µ
g/
L
TTHM
measured
as
an
LRAA
°
MCL
of
60
µ
g/
L
HAA5
measured
as
an
LRAA
°
MCL
of
5
µ
g/
L
bromate
measured
as
an
RAA,
based
on
monthly
samples
taken
at
the
finished
water
point
Members
of
the
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
they
were
concerned
that
lowering
the
bromate
level
to
5
µ
g/
L
could
have
adverse
effects
on
microbial
protection.
This
alternative
would
probably
cause
some
systems
to
stop
using
ozone
or
not
consider
ozone
for
microbial
protection
 
developments
that
the
M­
DBP
Advisory
Committee
and
EPA
did
not
want
to
encourage
because
ozone
is
more
effective
than
chlorine
against
Cryptosporidium.

Alternative
2
This
alternative
measures
TTHM
and
HAA5
concentrations
as
a
SH
value
for
the
MCL
and
maintains
the
MCL
for
bromate.
Its
components
include:

°
MCL
of
80
µ
g/
L
TTHM
measured
as
the
SH
value
for
any
sample
taken
°
MCL
of
60
µ
g/
L
HAA5
measured
as
the
SH
value
for
any
sample
taken
°
MCL
of
10
µ
g/
L
bromate
measured
as
an
RAA
(
no
change
from
the
Stage
1
DBPR)

This
alternative
is
more
stringent
than
the
Preferred
Alternative
and
Alternative
1.
Under
Alternative
2,
no
TTHM
or
HAA5
sample
can
exceed
the
MCL.
It
is
expected
that
a
large
portion
of
the
surface
water
systems
covered
by
the
rule
would
have
to
switch
from
their
current
treatment
practice
to
more
expensive
advanced
technologies
to
comply
with
this
alternative.
The
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
it
believed
that
the
health
effects
data
are
not
certain
enough
to
warrant
such
a
potentially
expensive
regulation.

Alternative
3
This
alternative
reduces
MCLs
for
TTHM
and
HAA5
and
maintains
the
MCL
for
bromate,
but
does
not
modify
how
compliance
is
measured
under
the
Stage
1
DBPR.
Its
components
include:

°
MCL
of
40
µ
g/
L
TTHM
measured
as
an
RAA
°
MCL
of
30
µ
g/
L
HAA5
measured
as
an
RAA
°
MCL
of
10
µ
g/
L
bromate
measured
as
an
RAA
(
no
change
from
Stage
1
DBPR
MCL)
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
5
This
alternative
reduces
the
average
level
of
TTHM
and
HAA5
in
the
distribution
system,
but
does
not
necessarily
reduce
peaks
in
the
distribution
system
as
an
LRAA
compliance
strategy
is
expected
to
do.
As
with
Alternative
2,
a
large
portion
of
the
surface
water
systems
covered
by
the
rule
would
have
to
switch
from
their
current
treatment
practices
to
expensive
advanced
technologies
to
comply
with
this
alternative.
Similarly,
the
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
it
believed
that
the
health
effects
data
are
not
certain
enough
to
warrant
such
a
potentially
expensive
regulation.

Exhibit
4.1
shows
how
compliance
would
be
determined
for
the
Stage
1
DBPR
and
under
each
of
the
regulatory
alternatives
described
above
when
applied
to
a
hypothetical
large
surface
water
system.
This
hypothetical
system
has
one
treatment
plant
and
measures
TTHM
in
the
distribution
system
in
four
locations
per
quarter
(
the
calculations
shown
would
be
the
same
for
HAA5).
In
this
example,
the
system
is
in
compliance
with
the
Stage
1
DBPR,
but
would
be
in
violation
of
all
four
Stage
2
DBPR
regulatory
options.

In
addition
to
the
four
regulatory
options
addressed
above,
the
M­
DBP
Advisory
Committee
considered
other
changes
in
the
approach
to
regulating
DBPs
worth
noting.
Both
the
current
Stage
1
DBPR
and
the
Stage
2
DBPR
alternatives
considered
in
this
analysis
use
TTHM
and
HAA5
as
the
specific
DBPs
measured
for
compliance.
The
M­
DBP
Advisory
Committee
determined
that
TTHM
and
HAA5
are
reliable
indicators
for
all
halogenated
DBPs
that
exist
in
chlorinated
drinking
water,
including
known
DBPs
that
are
unmeasurable
and
others
that
have
yet
to
be
identified.
The
Committee
considered
having
EPA
modify
the
group
of
indicators
to
include
a
total
of
six
haloacetic
acids
(
HAA6),
a
total
of
nine
haloacetic
acids
(
HAA9),
or
other
DBPs.
They
did
not,
however,
recommend
this.

The
Stage
1
DBPR
also
set
a
bromate
MCL
at
10
µ
g/
L
measured
as
an
RAA,
based
on
monthly
measurements
for
ozone
systems
and
a
chlorite
MCL
at
100
µ
g/
L
based
on
measurements
required
for
chlorine
dioxide
systems.
The
M­
DBP
Advisory
Committee
debated
whether
the
bromate
MCL
should
be
lowered
(
Regulatory
Alternative
1).
The
Stage
1
DBPR
set
the
MCL
for
bromate
at
10
µ
g/
L
partly
because
that
was
the
limit
of
EPA's
measuring
capability
at
that
time.
New
methods
now
exist
to
measure
lower
concentrations
of
bromate,
which
would
allow
a
lower
limit
to
be
set.
However,
the
Committee
was
concerned
that
a
lower
bromate
MCL
might
discourage
systems
from
switching
to
(
or
continuing
to
use)
ozone
to
increase
microbial
protection.
Unlike
chlorine,
ozone
is
effective
in
the
disinfection
of
Cryptosporidium
 
a
focus
of
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR).
Therefore,
the
M­
DBP
Advisory
Committee
recommended
that
EPA
not
change
the
bromate
MCL.
The
M­
DBP
Advisory
Committee
did
not
discuss
the
chlorite
standard,
and
EPA
does
not
believe
it
needs
to
be
revised.

Last,
it
should
be
noted
that
reductions
in
exposure
to
DBPs
could
also
be
achieved
through
treatment
techniques
in
lieu
of
or
in
addition
to
setting
MCLs.
For
example,
reducing
organic
precursor
compounds,
measured
as
Total
Organic
Carbon
(
TOC),
by
such
means
as
enhanced
coagulation
has
been
shown
to
lower
DBP
formation.
The
M­
DBP
Advisory
Committee
considered
regulatory
alternatives
for
reducing
precursors
and
determined
that
the
Stage
1
DBPR
reduced
TOC
to
a
sufficient
degree.
Further,
removing
ever­
smaller
quantities
of
these
compounds
will
be
more
difficult,
less
efficient,
and
increasingly
costly.
While
analysis
of
ICR
data
shows
that
some
systems
could
improve
performance
in
this
way
(
and
SWAT
incorporated
that
into
its
decision
tree),
a
regulatory
requirement
for
reducing
TOC
levels
was
deemed
unnecessary.
Economic
Analysis
for
Stage
2
DBPR
Proposal
July
2003
4­
6
Basis
of
Compliance
Violation
of
MCL
Stage
1
DBPR
TTHM
MCL
=
80
µ
g/
L
measured
as
an
RAA
No
exceedance
of
MCL
Loc.
1
Loc.
2
Loc.
3
Loc.
4
Qtrly
Avg.
Q1
100
40
50
50
60
Q2
75
50
40
100
66
Q3
55
45
55
110
66
Q4
60
55
40
75
58
RAA
63
Preferred
Stage
2
DBPR
Alternative
and
Alternative
1*
TTHM
MCL
=
80
µ
g/
L
measured
as
an
LRAA
LRAA
at
Location
4
exceeds
MCL
Loc.
1
Loc.
2
Loc.
3
Loc.
4
Q1
100
40
50
50
Q2
75
50
40
100
Q3
55
45
55
110
Q4
60
55
40
75
LRAA
73
48
46
84
*
The
Preferred
Alternative
and
Alternative
1
have
the
same
TTHM
MCL;
they
differ
only
in
regard
to
the
bromate
MCL.

Alternative
2
TTHM
MCL
=
80
µ
g/
L
measured
as
a
single
highest
value
Three
samples
at
Locations
1
and
4
exceed
MCL
Loc.
1
Loc.
2
Loc.
3
Loc.
4
Q1
100
40
50
50
Q2
75
50
40
100
Q3
55
45
55
110
Q4
60
55
40
75
Alternative
3
TTHM
MCL
=
40
µ
g/
L
measured
as
an
RAA
RAA
exceeds
MCL
Loc.
1
Loc.
2
Loc.
3
Loc.
4
Qtrly
Avg.
Q1
100
40
50
50
60
Q2
75
50
40
100
66
Q3
55
45
55
110
66
Q4
60
55
40
75
58
RAA
63
Exhibit
4.1
Comparison
of
Compliance
Calculations
for
Regulatory
Alternatives
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
1
July
2003
5.
Benefits
Analysis
5.1
Introduction
The
mission
of
the
Environmental
Protection
Agency
(
EPA)
is
to
protect
human
health
and
to
safeguard
the
natural
environment
(
USEPA
2000m).
The
specific
mandate
in
the
Safe
Drinking
Water
Act
(
SDWA)
for
regulating
contaminants
provides
that
the
"
Administrator
shall...
publish
a
maximum
contaminant
level
goal
and
promulgate
a
national
primary
drinking
water
regulation
for
a
contaminant...
if
the
Administrator
determines
that
­
(
i)
the
contaminant
may
have
an
adverse
effect
on
the
health
of
persons;
(
ii)
the
contaminant
is
known
to
occur
or
there
is
a
substantial
likelihood
that
the
contaminant
will
occur
in
public
water
systems
with
a
frequency
and
at
levels
of
public
health
concern;
and
(
iii)
in
the
sole
judgment
of
the
Administrator,
regulation
of
such
contaminant
presents
a
meaningful
opportunity
for
health
risk
reduction
for
persons
served
by
public
water
systems."
(
42
USC
§
300g­
1(
b)(
1)(
A))

When
carrying
out
its
statutory
mandate,
EPA
must
often
make
regulatory
decisions
using
incomplete
or
uncertain
information.
EPA
believes
it
is
appropriate
and
prudent
to
act
to
protect
public
health
when
there
are
indications
that
exposure
to
a
contaminant
could
present
significant
risks
to
the
public,
rather
than
take
no
action
until
risks
are
unequivocally
proven.
Evidence
from
both
human
epidemiology
and
animal
toxicology
studies
indicate
that
the
consumption
of
drinking
water
containing
disinfection
byproducts
(
DBPs)
may
result
in
adverse
health
effects.
The
two
main
categories
of
adverse
health
effects
that
have
been
associated
with
DBPs
are
reproductive
and
developmental
effects
and
cancer
(
particularly
bladder
cancer).
EPA
has
concluded
that
DBPs
occur
at
levels
that
are
of
a
public
health
concern
in
some
public
water
systems
(
PWSs)
that
apply
a
chemical
disinfectant,
and
that
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR)
presents
a
meaningful
opportunity
for
a
reduction
in
the
risk
of
adverse
health
effects.

Under
Executive
Order
12866,
EPA
must
conduct
an
Economic
Analysis
(
EA)
for
rules
costing
over
$
100
million
annually.
The
benefit
analyses
presented
in
this
chapter
follow
the
requirements
of
the
executive
order
and
related
Office
of
Management
and
Budget
(
OMB)
and
EPA
guidance,
and
provide
a
reasonable
basis
for
estimating
potential
health
benefits
using
the
best
available
science.

EPA
has
quantified
the
benefits
associated
with
expected
reductions
in
the
incidence
of
bladder
cancer.
The
science
on
the
association
of
reproductive
and
developmental
health
effects
with
DBP
exposure,
however,
is
not
strong
enough
to
fully
quantify
these
risks
of
the
benefits
of
reduced
DBP
exposure.
Nevertheless,
EPA
believes
that
the
reproductive
and
developmental
effects
benefits
resulting
from
the
Stage
2
DBPR
may
be
substantial.
To
help
inform
the
assessment
of
the
Stage
2
DBPR
benefits,
EPA
completed
an
illustrative
calculation
of
potential
benefits
for
one
specific
reproductive
effects
endpoint
(
fetal
loss).

Section
5.1.1
provides
an
overview
of
the
methodology
and
key
assumptions
used
to
estimate
the
benefits
that
may
be
attributed
to
the
Stage
2
DBPR
(
including
the
illustrative
calculations
for
developmental
and
reproductive
health
endpoints).
Section
5.1.2
summarizes
results.

Section
5.2
presents
the
problem
identification
and
assessment
of
potential
hazard.
Carcinogenic
and
non­
carcinogenic
(
e.
g.,
reproductive
and
developmental)
risks
are
presented
with
both
toxicological
and
epidemiological
supporting
evidence.
Section
5.3
follows
with
an
assessment
of
exposure.
The
rule's
benefits,
including
cancer
cases
avoided
and
the
associated
value
of
those
benefits,
are
addressed
in
Sections
5.4
through
5.6.
Section
5.7
summarizes
uncertainties
of
national
benefits
estimates.
Section
5.8
is
a
sensitivity
analysis
looking
at
the
impacts
of
not
considering
cessation
lag
when
estimating
quantified
benefits.
Potential
benefits
from
reductions
in
one
reproductive
and
developmental
endpoint
 
fetal
loss
 
are
evaluated
through
an
illustrative
calculation
in
Section
5.9.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
2
July
2003
The
following
appendices
provide
additional
details
in
support
of
this
chapter:

°
Appendix
D
shows
the
schedule
for
all
rule
activities
(
this
information
is
used
as
input
for
the
quantified
benefits
calculation).

°
Appendix
E
provides
general
background
information
on
population
attributable
risk
(
PAR)
and
a
detailed
description
of
the
derivation
of
PAR
values
used
to
quantify
benefits
associated
with
reduction
in
cancer
cases.
In
addition,
it
supports
the
discussion
of
average
exposure
reduction
presented
in
this
chapter.
Lastly,
Appendix
E
shows
detailed
calculations
for
estimating
the
number
of
bladder
cancer
cases
avoided
as
a
result
of
the
Stage
2
DBPR.

°
Appendix
F
describes
the
valuation
of
Stage
2
DBPR
benefits
and
presents
results
for
all
regulatory
alternatives
and
sensitivity
analyses.

°
Appendix
G
provides
detailed
calculations
for
the
illustrative
calculation
of
reproductive
and
developmental
health
impacts.

5.1.1
Overview
of
Methodology
for
Quantifying
Stage
2
DBPR
Benefits
There
are
two
categories
of
benefits
that
are
addressed
in
this
chapter:
estimated
benefits
associated
with
reductions
in
the
incidence
of
bladder
cancer
and
estimated
benefits
associated
with
reductions
in
the
incidence
of
adverse
reproductive
and
developmental
health
effects.
The
primary
benefits
analysis
in
this
EA
is
based
on
reductions
in
cancer
cases,
while
potential
benefits
associated
with
decreasing
adverse
developmental
and
reproductive
health
effects
(
specifically,
fetal
losses)
are
presented
as
an
illustrative
calculation.

EPA
used
similar
approaches
to
estimate
the
number
of
bladder
cancer
cases
avoided
(
the
primary
benefits
analysis)
and
the
avoided
incidence
of
fetal
loss
(
the
illustrative
calculation).
The
major
steps
in
deriving
and
characterizing
cases
avoided
are:

°
Estimate
the
current
and
future
cases
of
annual
bladder
cancer
and
fetal
loss
°
Estimate
how
many
cases
can
be
attributed
to
DBP
exposure
°
Estimate
the
reduction
in
future
cases
corresponding
to
anticipated
reductions
in
DBP
occurrence
and
exposure
due
to
the
Stage
2
DBPR
(
i.
e.,
cases
avoided)

For
bladder
cancer,
EPA
computed
the
total
national
annual
monetized
benefits
of
the
Stage
2
DBPR
by
multiplying
the
estimated
number
of
bladder
cases
avoided
by
an
estimated
monetary
value
associated
with
avoiding
both
fatal
and
non­
fatal
cases
of
bladder
cancer.
The
value
of
statistical
life
(
VSL)
was
used
for
fatal
bladder
cancers,
while
two
equally
valid
estimates
of
willingness­
to­
pay
to
avoid
non­
fatal
bladder
cancer
are
used
(
one
based
on
avoiding
a
case
of
curable
lymphoma
and
the
other
based
on
avoiding
a
case
of
chronic
bronchitis).
EPA
recognizes
that
there
could
be
a
significant
value
associated
with
reducing
the
number
of
avoided
fetal
losses
estimated
in
the
illustrative
calculation.
However,
the
Agency
is
unable
at
this
time
to
develop
a
specific
estimate
of
the
value
of
avoiding
fetal
loss
or
to
use
a
benefit
transfer
methodology
to
estimate
the
value
of
avoiding
fetal
loss
from
existing
valuation
studies
on
other
endpoints
(
see
section
5.9
for
a
full
discussion
of
this
issue).

All
benefit
calculations
were
performed
using
the
Stage
2
DBPR
Benefits
Model
(
USEPA
2003i).
See
Appendix
L
for
model
documentation
and
a
CD
containing
benefits
model
and
data
files.
1
PAR
represents
the
fraction
of
occurrence
of
a
particular
disease
that
is
attributable
to
some
specified
risk
factor.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
3
July
2003
To
quantify
the
benefits
due
to
reduction
in
bladder
cancer,
EPA
begins
with
an
estimated
number
of
new
cases
per
year
from
all
causes
of
56,500
(
based
on
published
2002
American
Cancer
Society
data,
available
on
the
web
at
http://
www.
cancer.
org/).
The
estimated
percent
of
bladder
cancer
cases
attributable
to
DBPs
is
based
on
five
epidemiological
studies
conducted
in
the
1980'
s
and
1990'
s.
Analysis
of
the
data
from
these
five
studies
was
used
to
estimate
the
PAR
of
bladder
cancer
due
to
DBPs.
1
Results
showed
that
best
estimates
range
from
2
to
17
percent.
The
total
cases
of
bladder
cancer
from
all
causes
multiplied
by
the
range
of
best
estimate
PAR
values
results
in
approximately
1,100
to
9,600
new
bladder
cancer
cases
per
year
that
may
be
attributed
to
DBPs
in
chlorinated
drinking
water.
EPA
recognizes
that
the
because
causality
has
not
yet
been
established
between
chlorinated
water
and
bladder
cancer,
the
actual
cases
attributable
to
DBPs
could
be
zero.

The
baseline
cancer
incidence
and
the
PAR
estimates
described
above
reflect
conditions
prior
to
the
implementation
of
not
only
the
Stage
2
DBPR
but
also
the
Stage
1
DBPR.
To
estimate
the
benefits
of
the
Stage
2
DBPR,
EPA
first
estimated
the
portion
of
the
56,500
annual
cases
expected
to
be
avoided
by
DBP
reductions
resulting
from
the
Stage
1
DBPR,
and
then
the
additional
cases
avoided
due
to
the
additional
reductions
in
DBP
levels
predicted
for
the
Stage
2
DBPR.
EPA
has
assumed
that
reductions
in
bladder
cancer
cases
avoided
is
estimated
by
assuming
that
reductions
in
bladder
cancer
cases
attributable
to
DBP
exposure
are
directly
proportional
to
reductions
in
the
national
average
DBP
levels.
Predicted
reductions
in
national
average
total
trihalomethanes
(
TTHM)
and
haloacetic
acid
(
HAA5)
levels
obtained
from
the
Surface
Water
Analytical
Tool
(
SWAT)
models
runs
were
used
as
indicators
of
overall
DBP
reductions.
The
resulting
reductions
new
in
bladder
cancer
cases
are
calculated
separately
for
each
year
over
a
25­
year
time
period
based
on
the
rule
implementation
schedule.
Adjustments
were
made
to
account
for
the
anticipated
transition
time
for
individual
lifetime
risks
among
those
in
the
exposed
population
to
become
more
reflective
of
the
post­
Stage
2
DBP
levels
rather
than
pre­
Stage
2
DBP
levels
(
referred
to
as
the
cessation
lag).
Also,
EPA
has
estimated
that
26%
of
bladder
cancer
cases
are
fatal,
while
74%
are
non­
fatal
(
USEPA,
1999a).

The
final
step
in
the
benefit
calculation
is
to
monetize
the
estimated
reduction
in
bladder
cancer
cases
by
applying
economic
values
for
avoided
illnesses
and
deaths.
The
value
of
avoiding
non­
fatal
bladder
cancer
cases
is
based
on
people's
Willingness
to
Pay
(
WTP)
for
incremental
reductions
in
the
risk
they
face
of
contracting
cancer.
The
metric
of
WTP
to
avoid
an
increased
risk
accounts
for
the
desire
to
avoid
treatment
costs,
pain
and
discomfort,
productivity
losses,
and
any
other
adverse
consequences
related
to
contraction
of
a
non­
fatal
case
of
bladder
cancer.

Because
specific
estimates
of
WTP
for
avoiding
non­
fatal
bladder
cancer
are
not
available,
EPA
estimated
WTP
values
from
two
other
non­
fatal
illnesses:
chronic
bronchitis
and
curable
lymphoma.
Both
are
considered
equally
valid
estimtates
of
WTP
for
non­
fatal
cancer.

For
fatal
bladder
cancer
cases,
the
VSL
is
used
to
capture
the
value
of
benefits.
The
VSL
represents
an
estimate
of
the
monetary
value
of
reducing
risks
of
premature
death
from
cancer.
The
VSL,
therefore,
is
not
an
estimate
of
the
value
of
saving
a
particular
individual's
life.
Rather,
the
value
of
a
"
statistical"
life
represents
the
sum
of
the
values
placed
on
small
individual
risk
reductions
across
an
exposed
population.
Other
economic
factors
are
taken
into
consideration
when
calculating
benefits
over
time,
such
as
income
growth
and
social
discount
rates.

There
are
several
areas
of
uncertainty
with
respect
to
quantified
benefits
for
bladder
cancer.
Many
are
incorporated
into
the
analyses,
such
as
the
uncertainty
in
PAR
values
reflected
by
the
use
of
a
wide
range
of
"
best
estimates"
of
2
to
17
percent
derived
from
several
credible
epidemiological
studies.
Uncertainties
in
these
best­
estimates
of
PAR
suggest
95
percent
confidence
interval
ranges
truncated
at
0
percent
on
the
low
end
and
up
to
33
percent
on
the
high
end
(
see
Appendix
E
for
details).
There
is
also
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
4
July
2003
uncertainty
in
the
valuation
of
the
estimated
bladder
cancer
cases
avoided,
including
the
use
of
two
alternatives
for
valuing
non­
fatal
bladder
cancer.

As
noted
previously,
EPA
expects
that
a
large
portion
of
the
total
benefits
from
this
rule
could
come
from
reduction
in
developmental
and
reproductive
health
effects,
although
the
science
on
these
effects
as
a
result
of
DBP
exposure
is
not
strong
enough
to
fully
quantify
risk.
EPA
completed
a
preliminary
quantification
of
fetal
loss
risk
and
rule
benefits
in
an
illustrative
calculation.
Fetal
loss
was
used
in
the
analysis
because,
while
some
epidemiology
data
exist
for
other
reproductive
and
developmental
effects
potentially
associated
with
DBP
exposure,
more
data
are
available
on
this
particular
end­
point.
Because
approximately
one
million
of
the
six
million
pregnancies
each
year
in
the
United
States
end
in
a
miscarriage
or
stillbirth
(
Ventura
et
al.
2000a),
even
a
small
risk
attributable
to
DBP
exposure
that
can
be
avoided
by
reducing
DBP
levels
may
result
in
a
significant
number
of
avoided
fetal
losses.

EPA
estimated
the
reduction
in
fetal
losses
in
a
similar
manner
to
bladder
cancer
cases.
A
range
of
possible
PAR
values
for
relating
annual
fetal
losses
to
DBP
exposure
was
obtained
from
available
epidemiological
studies.
Reductions
in
occurrence
of
peak
DBPs
due
to
the
Stage
1
DBPR
and
the
Stage
2
DBPR
were
estimated.
Reductions
in
exposure
to
peak
DBPs
were
assumed
to
be
proportional
to
reductions
in
peak
DBP
occurrence.
Like
the
analysis
of
bladder
cancer,
there
is
uncertainty
in
fetal
loss
PAR
values,
reflected
in
the
range
of
values
used
in
the
analysis.
There
are
other
important
uncertainties
in
this
illustrative
calculation,
including
the
assumed
proportional
relationship
between
reduction
in
fetal
losses
and
reduction
in
exposure
to
peak
levels
due
to
the
Stage
2
DBPR.

5.1.2
Summary
of
National
Benefits
of
the
Stage
2
DBPR
Exhibit
5.1
summarizes
the
estimated
number
of
bladder
cancer
cases
avoided
as
a
result
of
the
Stage
2
DBPR
and
the
monetized
value
of
those
cases.
While
causality
has
not
been
established,
the
weight
of
evidence
supports
PAR
estimates
of
potential
benefits.
Although
zero
is
within
the
range
of
potential
benefits,
the
evidence
indicates
that
both
the
number
of
cases
and
the
value
of
preventing
those
cases
could
be
significant.
The
wide
range
of
total
monetized
benefits
in
Exhibit
5.1
primarily
reflects
the
large
uncertainty
in
PAR
values
for
related
DBP
exposure
to
bladder
cancer.
The
benefits
in
Exhibit
5.1
are
for
the
Preferred
Regulatory
Alternative
for
the
Stage
2
DBPR.
Benefits
estimates
for
the
other
regulatory
alternatives
were
derived
using
the
same
methods
as
for
the
Preferred
Regulatory
Alternative
and
are
presented
in
section
5.6.4.

It
is
important
to
note
that
26
percent
of
bladder
cancer
cases
in
the
US
are
fatal,
and
74
percent
are
non­
fatal.
The
monetized
benefits
therefore
reflect
the
estimate
of
avoiding
both
fatal
and
non­
fatal
cancers
in
those
proportions.

In
addition
to
bladder
cancer
cases
avoided,
EPA
provides
an
illustrative
calculation
on
the
potential
number
of
fetal
losses
that
might
be
avoided
per
year,
ranging
from
1,100
to
4,700.
Only
an
illustrative
example
of
potential
fetal
loss
avoided
is
given
because
of
the
much
greater
uncertainties
in
quantifying
this
risk
than
for
bladder
cancer.
The
value
of
other
health
benefits,
including
the
potential
reduction
in
other
types
of
cancer
such
as
colon
or
rectal,
could
be
significant.
Also,
the
value
of
nonhealth
benefits,
such
as
improved
taste
and
odor
of
water,
are
expected
to
be
positive.
These
are
discussed
further
in
section
5.5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
5
July
2003
Exhibit
5.1
Summary
of
Quantified
Benefits
for
the
Stage
2
DBPR
PAR
Value
1
Average
Annual
Estimate
of
Bladder
Cancer
Cases
Avoided
Annualized
Total
Estimated
Value
of
Cases
Avoided
(
Millions,
2000$)
(
90%
Confidence
Bounds
2)

Discount
Rate
WTP
for
Curable
Lymphoma
as
the
Basis
for
Non­
Fatal
Cases
WTP
for
Chronic
Bronchitis
as
the
Basis
for
Non­
Fatal
Cases
2%
20.9
3
%
$
113.0
($
17.9
­
258.2)
$
54.9
($
12.5
­
119.6)

7
%
$
97.9
($
15.6
­
223.7)
$
47.6
($
10.9
­
103.7)

17
%
182.3
3
%
$
986.2
($
156.6
­
2,252.5)
$
479.3
($
109.3
­
1,043.7)

7
%
$
854.4
($
135.8
­
1,952.3)
$
415.6
($
94.9
­
904.6)
Notes:
Results
are
based
on
analysis
of
reduction
in
average
TTHM
concentrations
due
to
the
Stage
2
DBPR.
1.
The
2
and
17
percent
PAR
values
used
in
the
bladder
cancer
risk
and
benefits
analyses
reflect
the
range
of
best
estimates
derived
from
the
relevant
epidemiological
data.
EPA
recognizes
that
the
lower
bound
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
%
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
Exhibit
5.27.

5.2
Problem
Identification
and
Assessment
of
Potential
Hazard
This
section
provides
detailed
information
from
the
toxicological
and
epidemiological
literature
regarding
the
key
adverse
health
effects
that
have
been
associated
with
exposure
to
DBPs.
In
addition
to
the
specific
studies
and
key
reviews
presented
here,
EPA
has
also
addressed
reproductive
and
developmental
effects,
carcinogenicity,
and
other
adverse
health
effects
at
length
in
several
Health
Criteria
Documents.
Specifically,
EPA
is
currently
developing
external
review
drafts
of
Drinking
Water
Criteria
Documents
for
the
following
DBPs:
brominated
trihalomethanes
(
USEPA
2003c),
brominated
haloacetic
acids
(
USEPA
2003d),
cyanogen
chloride
(
USEPA
2003e),
glyoxal
and
methylglyoxal
(
USEPA
2003f),
and
haloacetonitriles
(
USEPA
2003g).
EPA
is
also
writing
addendums
to
the
Criteria
Document
for
bromate
(
IRIS
2001a),
chloroform
(
IRIS
2001b),
chlorine
dioxide
and
chlorite
(
IRIS
2001c),
and
dichloroacetic
acid
(
IRIS
2002).
Similar
documents
exist
for
MX
(
USEPA
2000r)
and
chlorohydroxyfurfanones
(
USEPA
1999c).

5.2.1
Reproductive
and
Developmental
Health
Effects
Adverse
impacts
on
reproduction
and
development
that
have
been
hypothesized
to
be
associated
with
maternal
exposure
to
disinfection
byproducts
include
early
term
miscarriage
(
Waller
et
al.,
1998),
stillbirth
(
Dodds
et
al.,
1999),
low
birth
weight
(
Gallagher
et
al.,
1998),
premature
birth
(
Kallen
and
Robert,
1999),
and
some
congenital
birth
defects
(
Magnus
et
al.,
1999).

CDC
reports
that,
for
the
10
year
period
between
1986
and
1996,
spontaneous
fetal
losses
were
estimated
to
be
between
0.8
million
and
1.0
million
per
year.
Approximately
15
percent
of
births
are
considered
very
low
birth
weight
(
defined
by
CDC
as
below
1.0kg
and
2.2kg).
Congenital
abnormalities
are
reported
to
occur
in
just
over
1
percent
of
all
live
births
per
year
in
the
United
States.
Although
research
has
identified
some
risk
factors
for
these
adverse
birth
outcomes,
including
nutritional
deficits
2
"
Term
low
birth
weight"
refers
to
low
weight
of
infants
carried
to
a
full
term
(
i.
e.,
nine
months),
as
opposed
to
low
birth
weight
as
a
general
category
that
includes
infants
born
prematurely.

3
Epidemiology
studies
often
report
results
as
an
odds
ratio
(
OR)
or
as
a
relative
risk
(
RR),
usually
adjusted
to
account
for
confounders,
as
measures
of
the
strength
of
the
association
between
a
risk
factor
(
e.
g.,
exposure
to
some
substance)
and
an
adverse
health
effect.
Appendix
E
provides
a
detailed
discussion
of
the
meaning
and
derivation
of
OR
and
RR
values.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
6
July
2003
(
e.
g.,
inadequate
folic
acid)
and
fetal
exposure
to
tobacco
smoke
and
alcohol,
the
causes
of
many
outcomes
are
unknown.

A
variety
of
research
is
underway
to
examine
the
potential
role
that
maternal
exposure
to
specific
air
and
water
pollutants
might
play
in
these
adverse
outcomes.
The
following
sections
provide
a
review
of
the
literature
addressing
the
potential
relationship
between
DBPs
and
adverse
reproductive
and
developmental
outcomes.

5.2.1.1
Epidemiological
Evidence
of
Adverse
Reproductive
and
Developmental
Health
Effects
All
published
reproductive
and
developmental
epidemiology
studies
concerning
drinking
water
have
been
evaluated,
including
recently
published
studies
of
the
relationship
between
exposure
to
contaminants
in
chlorinated
surface
water
and
potential
adverse
reproductive
and
developmental
health
effects.
EPA
also
considered
critical
reviews
of
the
epidemiological
literature
by
Reif
et
al.
(
2000);
Bove
et
al.
(
2002);
and
Nieuwenhuijsen
et
al.
(
2000).
Dr.
John
Reif
and
colleagues
at
the
University
of
Colorado
(
Reif
et
al.
2000)
prepared
a
report
for
Health
Canada
that
analyzed
and
summarized
these
studies.
Similarly,
Frank
Bove
from
the
Agency
for
Toxic
Substances
and
Disease
Registry
(
ATSDR)
conducted
a
qualitative
review
of
14
reproductive
and
developmental
epidemiology
studies
on
exposure
to
chlorinated
byproducts
in
the
report,
"
Drinking
Water
Contaminants
and
Adverse
Pregnancy
Outcomes:
A
Review"
(
2002).
In
addition,
Mark
Nieuwenhuijsen
and
colleagues
reviewed
toxicological
and
epidemiological
data
and
evaluated
the
potential
risk
of
chlorination
DBPs
on
human
reproductive
health
(
2000).

New
epidemiology
reports
since
the
Stage
1
DBPR
The
1997
Notice
of
Data
Ability
(
NODA)
(
USEPA
1997f),
the
1998
NODA
(
USEPA
1998f),
the
Stage
1
DBPR,
and
the
Stage
1
DBPR
companion
Regulatory
Impact
Analysis
(
RIA)
(
USEPA
1998a)
presented
EPA's
reviews
of
the
reproductive
and
developmental
epidemiological
literature
published
prior
to
the
Stage
1
DBPR
concerning
DBPs.
Eight
new
epidemiology
reports
have
been
published
since
the
1998
Stage
1
DBPR.

1)
Gallagher
et
al.
(
1998)
conducted
a
retrospective
cohort
study
in
Colorado
to
examine
the
relationship
between
TTHM
exposure
during
the
third
trimester
of
pregnancy
and
low
birth
weight,
term
low
birth
weight2,
and
preterm
delivery.
Estimates
of
TTHM
concentration
at
maternal
residence
were
based
on
routinely
collected
TTHM
data
that
were
adjusted,
using
a
Geographical
Information
System
(
GIS)­
based
modeling
technique,
to
account
for
spatial
variability.

Compared
to
the
reference
category
used
in
the
study
(
#
20
µ
g/
L
estimated
TTHM
exposure),
women
exposed
to
water
containing
$
61
µ
g/
L
of
TTHM
had
an
increased
risk
for
low
birth
weight
(
odds
ratio
(
OR)
=
2.1,
95
percent
confidence
interval
of
1.0­
4.8)
and
for
term
low
birth
weight
(
OR
=
5.9,
95
percent
confidence
interval
2.0­
17.0).
3
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
7
July
2003
The
wide
confidence
intervals
for
term
low
birth
weight
reflect
the
small
sample
size
(
n=
6
births)
in
the
exposed
category.

2)
Dodds
et
al.
(
1999)
conducted
a
retrospective
cohort
study
in
Nova
Scotia
to
examine
the
relationship
between
the
level
of
TTHMs
and
low
birth
weight,
term
low
birth
weight,
very
low
birth
weight,
preterm
delivery,
small
size
for
gestational
age,
stillbirth,
and
congenital
anomalies.
The
study
population
included
50,755
women
residing
in
an
area
with
municipal
surface
water
who
had
singleton
births
(
i.
e.,
birth
of
one
offspring)
or
pregnancy
terminations
for
major
fetal
anomalies
in
Nova
Scotia
between
1988
and
1995.
The
authors
used
linear
regression
to
estimate
the
concentration
of
TTHM
by
month
from
quarterly
sampling
data
within
the
distribution
system
of
each
public
water
facility.

The
investigators
found
little
association
between
TTHM
level
and
outcomes
related
to
fetal
weight,
gestational
age,
preterm
delivery,
or
congenital
defects.
They
did
find
an
elevated
risk
for
stillbirth
among
women
who
experienced
average
TTHM
levels
of
100
µ
g/
L
or
greater
during
pregnancy
(
adjusted
RR
=
1.66;
95
percent
confidence
interval
1.09­
2.52)
relative
to
the
referent
group
of
women
exposed
to
levels
of
0­
49
µ
g/
L.
(
Because
of
relatively
high
TTHM
levels
in
Nova
Scotia,
the
referent
group
contained
women
exposed
to
higher
concentrations
than
were
typically
used
in
other
studies.)
The
authors
observed
an
elevated
prevalence
of
chromosomal
abnormalities
(
adjusted
RR
=
1.38;
95
percent
confidence
interval
0.73­
2.59
for
women
exposed
to
TTHM
levels
of
100
µ
g/
L
or
greater),
but
there
was
no
evidence
of
a
dose­
response
relationship.

3)
King
et
al.
(
2000a)
used
the
Dodds
et
al.
(
1999)
Nova
Scotia
study
data
to
evaluate
the
relationship
between
the
level
of
TTHM,
as
well
as
specific
trihalomethanes
(
THMs)
in
public
water
supplies,
and
risk
of
stillbirth.
Individual
exposures
were
assigned
by
linking
mothers'
residence
location
at
the
time
of
delivery
to
the
levels
of
specific
THMs
observed
in
public
water
supplies.

King
et
al.
(
2000a)
found
an
association
between
BDCM
and
stillbirth,
comparing
exposures
$
20
µ
g/
L
with
exposures
<
5
:
g/
L
(
RR
=
1.98;
95
percent
confidence
interval
1.23­
3.49).
When
analyzed
as
a
continuous
variable,
BDCM
was
associated
with
a
29
percent
increase
in
risk
for
stillbirth
for
each
10
:
g/
L
increase
in
concentration.
King
et
al.
also
noted
an
association
between
chloroform
and
an
increased
risk
for
stillbirth
(
RR
=
1.56;
95
percent
confidence
interval
1.04­
2.34).

4)
Magnus
et
al.
(
1999)
conducted
a
"
semi­
individual"
ecological
study
in
Norway
to
examine
the
relation
of
water
chlorination
practice
and
color
(
used
as
an
indicator
for
the
presence
of
natural
organic
matter
and
DBPs)
to
birth
defects.
An
exposure
assessment
was
performed
by
linking
the
national
waterworks
registry
with
the
national
birth
registry
(
1993­
1995;
141,077
children).
The
authors
reported
that
DBP
concentrations
in
Norway
were
generally
low
(
mean
of
9.4
µ
g/
L
for
TTHM
and
14.6
µ
g/
L
for
HAAs).
In
a
comparison
between
exposed
(
high
color;
chlorination)
and
reference
groups
(
low
color;
no
chlorination),
the
adjusted
OR
was
1.14
(
95
percent
confidence
interval
0.99­
1.31)
for
any
malformation,
1.26
(
95
percent
confidence
interval
0.61­
2.62)
for
neural
tube
defects
and
1.99
(
95
percent
confidence
interval
1.10­
3.57)
for
urinary
tract
defects.
Elevated
risks
were
not
observed
for
major
cardiac
defects,
respiratory
defects,
or
oral
cleft
defects.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
8
July
2003
5)
Källén
and
Robert
(
1999)
conducted
a
cross­
sectional,
population­
based
ecological
study
in
Sweden
to
examine
associations
between
water
disinfection
practices
and
birth
defects.
The
authors
compared
birth
outcomes
recorded
in
the
Swedish
national
registry
for
women
living
in
municipalities
where
the
water
supply
was
disinfected
with
chlorine
(
sodium
hypochlorite)
or
chlorine
dioxide,
or
was
left
untreated.
Three
years
of
data
were
analyzed,
encompassing
approximately
74,300
births
in
referent
areas,
15,400
in
areas
using
chlorine
dioxide
and
24,700
in
areas
using
sodium
hypochlorite.
Statistically
significant
associations
with
pre­
term
delivery,
low
birth
weight,
short
body
length,
and
small
head
circumference
were
found
for
chlorination.
These
associations
were
not
observed
in
communities
which
treated
water
with
chlorine
dioxide.
No
data
on
concentrations
of
DBPs
in
Swedish
water
supplies
were
provided.

6)
Yang
et
al.
(
2000)
conducted
a
cross­
sectional,
population­
based
ecological
study
in
Taiwan
to
examine
water
disinfection
practices
and
birth
outcomes.
The
authors
compared
birth
outcomes
in
14
municipalities
in
which
chlorinated
water
was
supplied
to
over
90
percent
of
the
residents
to
birth
outcomes
in
14
non­
chlorinating
municipalities.
Two
years
of
singleton
data
on
18,025
women
were
analyzed
(
1994­
1996).
Pre­
term
delivery
(<
37
weeks)
occurred
more
often
in
municipalities
that
treated
water
with
chlorine
(
OR=
1.34;
95
percent
confidence
interval
1.15­
1.56).
No
statistically
significant
associations
were
found
for
birth
weight
or
the
percent
term
low
birth
weight.
No
THM
concentration
data
were
provided.

7)
Waller
et
al.
(
2001)
published
a
study
that
evaluated
different
exposure
assessment
methods
used
to
estimate
relationships
between
exposure
to
chlorinated
tap
water
and
the
risk
of
spontaneous
abortion
by
recalculating
the
total
trihalomethane
exposures
from
their
original
publication
(
Waller
et
al.,
1998).
The
study
was
co­
funded
by
EPA's
National
Health
and
Environmental
Effects
Research
Laboratory
(
NHEERL)
and
the
California
Department
of
Health
Services
(
CDHS).
The
investigators
conducted
this
methods
development
study
as
a
follow­
up
to
a
1998
CDHS
study
of
THMs
and
miscarriage.
The
primary
purpose
was
to
evaluate
improved
methods
for
assessing
exposures
to
DBPs,
and
to
develop
and
evaluate
statistical
techniques
that
might
reduce
the
effects
of
misclassification.
Two
methods
were
compared,
the
"
utility­
wide"
approach
and
the
"
closest
site"
approach,
the
latter
using
TTHM
levels
from
the
monitoring
site
closest
to
the
individual's
residence.
Unweighted,
weighted,
and
subset
analyses
were
performed
for
both
approaches.
The
researchers
concluded
that
two
of
the
analyses
(
called
"
weighted"
and
"
subset"
analyses),
when
used
with
the
utility­
wide
approach,
are
relatively
simple
techniques
that
may
increase
the
usefulness
of
utility
monitoring
records.
However,
these
techniques
result
in
a
loss
of
sample
size,
which
may
limit
their
value
in
small
studies
or
in
areas
where
TTHM
levels
vary
widely.
In
conclusion,
the
results
neither
strengthen
nor
weaken
the
previously
reported
association
between
THMs
and
spontaneous
abortions.

8)
Hwang
et
al.
(
2002)
conducted
a
nationwide
cross­
sectional
study
of
birth
defects
in
Norway.
The
authors
reviewed
records
for
184,676
infants
born
between
1993
and
1998
to
assess
the
association
between
chlorination
byproducts
and
specific
birth
defects.
The
authors
did
not
measure
chlorination
by­
products
directly,
but
rather
used
six
exposure
categories
based
on
the
presence/
absence
of
chlorination
in
combination
with
low,
medium,
or
high
color
in
raw
water
as
an
indicator
of
natural
organic
matter
(
chlorination
by­
product
precursors).
To
measure
risk,
the
authors
used
logistic
regression
to
compute
odds
ratios
adjusted
for
maternal
age,
previous
deliveries,
and
locality
measures.
The
category
of
no
chlorination
and
low
color
was
used
as
the
reference
category
(
adjusted
OR
=
1.0
for
all
birth
defects).
The
authors
reported
that
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
9
July
2003
overall,
chlorination
increases
the
risk
of
all
birth
defects
(
adjusted
OR=
1.13,
95
percent
confidence
interval
1.01­
1.25
for
combined
groups
of
chlorination
with
medium
or
high
water
color).
Significant
associations
were
found
between
chlorination
(
medium
and
high
color
groups
combined)
and
cardiac
defects
(
adjusted
OR=
1.37,
95
percent
confidence
interval
1.00­
1.89),
respiratory
system
defects
(
adjusted
OR=
1.89,
95
percent
confidence
interval
1.00­
3.58),
and
urinary
tract
birth
defects
(
adjusted
OR=
1.46,
95
percent
confidence
interval
1.00­
2.13).
Of
the
various
specific
birth
defects
examined
in
the
study,
the
risk
of
ventricular
septal
defects
increased
with
chlorinated
drinking
water
(
adjusted
OR
for
medium
color
=
1.63,
95
percent
confidence
interval
1.02­
2.58;
adjusted
OR
for
high
color
=
1.81,
95
percent
confidence
interval
1.05­
3.09).
The
author's
reported
that
no
significant
association
was
observed
between
chlorination
and
neural
tube
defects
or
oral
cleft
defects,
but
did
observe
that
the
risk
of
spina
bifida
was
related
to
high
amounts
of
organic
matter
(
i.
e.,
high
color)
in
non­
chlorinated
water.

9)
Windham
et
al.,
2003,
assessed
the
relationship
between
exposure
to
THMs
in
drinking
water
and
characteristics
of
the
menstrual
cycle
among
403
women
who
provided
daily
urine
samples
for
an
average
of
5.6
cycles.
Women
whose
tap
water
had
TTHM
levels
greater
than
0.060
mg/
l
had
statistically
significantly
shorter
menstrual
cycles
than
women
whose
tap
water
had
lower
TTHMs.
On
average,
the
menstrual
cycles
of
women
with
the
higher
levels
of
TTHMs
were
one
day
shorter
than
cycles
of
women
with
the
lower
levels
(
adjusted
difference:
­
1.1
days,
95%
confidence
interval:
­
1.8
days
to
­
0.4
days).
This
shortening
occurred
during
the
first
half
of
the
cycle,
before
ovulation
(
adjusted
difference:
­
0.9
days;
95%
confidence
interval:
­
1.6
days
to
­
0.2
days).
There
were
no
changes
in
bleed
length
or
in
the
regularity
of
the
cycles.
Based
on
their
study,
Windham
et
al.
suggested
that
THM
exposure
may
affect
ovarian
function,
but
since
this
is
the
first
study
to
examine
human
menstrual
cycle
variation
in
relation
to
THM
exposure,
more
research
is
needed
to
confirm
the
relationship.
The
public
health
implication
of
a
small
reduction
in
menstrual
cycle
length
is
not
clear,
but
if
THMs
are
related
to
disturbances
in
ovarian
function,
that
might
provide
insight
into
the
observed
associations
between
THMs
and
a
variety
of
adverse
reproductive
outcomes.

Critical
review
of
epidemiology
literature
by
Reif
et
al.
(
2000)

Reif
et
al.
(
2000)
conducted
a
critical
review
of
the
epidemiology
literature
pertaining
to
potential
reproductive
and
developmental
effects
of
exposure
to
DBPs
in
drinking
water.
The
review
included
16
peer­
reviewed
scientific
manuscripts
and
published
reports
of
which
10
were
previously
discussed
in
the
Stage
1
DBPR.
The
authors
evaluated
associations
between
DBPs
and
outcomes
grouped
as
effects
on
(
1)
fetal
growth
(
birth
weight
[
as
a
continuous
variable];
low
birth
weight
[
defined
as
<
2,500
grams];
term
low
birth
weight
[
defined
as
<
2,500
grams];
very
low
birth
weight
[
defined
as
<
1,500
grams];
preterm
delivery
[
defined
as
<
37
weeks
of
gestation]
and
intrauterine
growth
retardation
[
or
decreased
rate
of
growth
of
the
fetus]);
(
2)
fetal
viability
(
spontaneous
abortion
and
stillbirth);
and,
(
3)
risk
of
fetal
malformations
(
all
malformations,
oral
cleft
defects,
major
cardiac
defects,
neural
tube
defects,
and
chromosomal
abnormalities).

Reif
et
al.
(
2000)
found
mixed
evidence
in
the
epidemiological
literature
they
reviewed
for
associations
between
DBPs
and
effects
on
fetal
growth.
Studies
using
TTHM
concentrations
reached
differing
conclusions.
Some
studies
found
weak
but
statistically
significant
associations
(
Gallagher
et
al.
1998;
Bove
et
al.
1992b;
Bove
et
al.
1995),
but
two
found
none
(
Dodds
et
al.
1999;
and
Savitz
et
al.
1995).
Studies
with
qualitative
exposure
assessment
designs
are
similarly
variable
in
their
findings
(
Kanitz
et
al.
1996;
Källén
and
Robert
1999;
and
Yang
et
al.
2000).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
10
July
2003
For
effects
on
fetal
viability,
the
authors
reported
that
some
evidence
exists
for
an
increased
risk
of
spontaneous
abortion
and
stillbirth.
Increased
rates
of
spontaneous
abortion
associated
with
TTHM
levels
of
75
µ
g/
L
or
more
were
reported
by
Waller
et
al.
(
1998).
Aschengrau
et
al.
(
1989)
reported
a
doubling
of
risk
of
spontaneous
abortion
for
exposure
to
surface
water
compared
to
ground
and
mixed
water.
Although
Savitz
et
al.
(
1995)
found
an
association
between
high
levels
of
THMs
and
spontaneous
abortion,
no
relationship
with
dose
or
water
source
was
discovered.
As
discussed
previously,
an
increased
risk
of
stillbirth
was
found
to
be
associated
with
THM
and
BDCM
exposure
(
Dodds
et
al.
1999;
King
et
al.
2000a).
Aschengrau
et
al.
(
1993)
found
an
association
between
stillbirth
and
the
use
of
chlorinated
versus
chloraminated
water
systems.
A
weak
association
was
found
for
the
use
of
surface
water
systems
and
risk
of
stillbirth,
but
these
authors
found
little
evidence
for
an
association
between
TTHM
and
risk
of
stillbirth
(
Bove
et
al.
1992a;
Bove
et
al.
1995).

For
congenital
abnormalities
related
to
DBP
exposure,
Reif
et
al.
(
2000)
reported
that
the
relatively
few
studies
available
in
the
technical
literature
provide
an
inconsistent
pattern
both
in
terms
of
associating
exposure
with
the
occurrence
of
anomalies
in
general,
and
with
respect
to
identifying
specific
anomalies
that
result
from
exposure.
The
authors
conceded
that
an
assessment
of
congenital
anomalies
is
difficult
due
to
the
small
number
of
cases
available
for
evaluation
and
possible
selection
bias
due
to
elective
terminations
of
pregnancy.
In
addition,
the
authors
stated
that
(
1)
categorizing
defects
may
yield
etiologically
dissimilar
aggregations
and
may
dilute
the
estimated
risk,
(
2)
at
higher
DBP
concentrations,
multiple
or
lethal
defects
may
be
induced
and
the
outcomes
may
be
expressed
as
spontaneous
abortion
or
stillbirth,
or
cause
unrecognized
fetal
loss,
and
(
3)
cases
with
recognized,
single
anomalies
may
represent
only
a
portion
of
the
full
range
of
the
potential
effects.

Reif
et
al.
provide
several
possible
explanations
for
the
discrepancies
and
inconsistencies
between
the
epidemiologic
studies:
(
1)
substantial
differences
existed
between
methods
of
exposure
assessment
and,
in
some
cases,
definition
of
the
outcome,
(
2)
referent
groups
varied
across
studies,
(
3)
the
composition
of
DBP
mixtures
may
have
varied
across
locales
and
studies,
and
(
4)
other
classes
of
DBPs
may
be
the
causal
agents
and
THMs
may
or
may
not
be
an
appropriate
exposure
indicator
for
those
DBPs.
Exposure
misclassification
in
the
studies
may
either
hide
a
true
effect
or,
in
rare
circumstances,
create
an
artificial
effect.

Reif
et
al.
also
reviewed
the
epidemiology
literature
for
dose­
response
relationships.
The
researchers
did
not
find
a
dose­
response
pattern
of
increasing
risk
with
increasing
concentration
of
TTHM,
but
they
did
observe
a
general
trend
of
small
increases
in
risk
for
concentrations
of
TTHM
greater
than
100
:
g/
L.

Based
on
information
provided
in
the
literature,
Reif
et
al.
(
2000)
estimated
PAR
for
each
outcome
in
each
study.
A
PAR
value
represents
the
fraction
of
disease
incidence
in
a
population
that
is
attributable
to
a
specific
risk
factor.
The
PAR
value,
therefore,
also
reflects
the
portion
of
disease
in
the
population
that
would
be
eliminated
by
eliminating
the
associated
risk
factor
while
distributions
of
other
risk
factors
in
the
population
remain
unchanged.
Appendix
E
provides
a
detailed
discussion
of
the
derivation
of
PAR
values
from
epidemiological
studies
and
their
use
in
risk
and
benefits
assessments.

Reif
et
al.
(
2000)
explored
the
differential
in
potential
health
risk
across
TTHM
thresholds
of
80
and
60
µ
g/
L.
Odds
ratios
with
95
percent
confidence
intervals
from
various
studies
are
compared
in
Exhibit
5.2
and
PAR
values
with
95
percent
confidence
intervals
(
truncated
at
zero
to
reflect
biological
relevance)
from
various
studies
are
compared
in
Exhibit
5.3.
The
distribution
of
exposure
levels
differed
among
the
studies,
but
when
normalized
in
this
way
the
studies
appear
to
provide
some
support
for
establishing
a
threshold
level
for
TTHM.
The
PAR
value
point
estimates
in
Exhibit
5.3
are
generally
higher
when
60
:
g/
L
is
used
as
the
cut­
point
rather
than
80
:
g/
L.
This
seems
to
indicate
that
an
important
reduction
in
disease
occurrence
may
be
obtained
by
eliminating
not
only
TTHM
exposure
levels
above
80
:
g/
L,
but
also
levels
between
60
:
g/
L
and
80
:
g/
L.
The
authors
note
that
this
conclusion
is
tentative
because
many
of
the
95
percent
confidence
intervals
on
the
Odds
Ratios
were
very
wide
and
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
11
July
2003
extended
to
values
of
one
and
lower.
Moreover,
Reif
et
al.
(
2000)
suggest
caution
when
interpreting
the
PAR
values
and
note
that
"[
s]
ince
a
number
of
assumptions
regarding
attributable
fraction
do
not
appear
to
hold,
population
attributable
risks
are
unlikely
to
be
useful
with
the
current
data
set."

The
findings
for
low
birth
weight
are
varied
and
do
not
strongly
support
a
threshold
of
80
or
60
µ
g/
L.
Reif
et
al.
noted
that
the
higher
outcomes
in
the
Gallagher
et
al.
(
1998)
study
may
result
from
decreased
non­
differential
misclassification
by
taking
spatial
variability
into
account.
Also,
the
DBP
mixture
may
have
been
different
from
the
mixtures
used
in
other
studies.
There
does
not
appear
to
be
an
increased
association
between
TTHM
and
intrauterine
growth
retardation
or
preterm
birth
above
the
thresholds
in
question,
based
on
the
findings
presented
in
Exhibit
5.2.
The
Waller
et
al.
(
1998)
study
presents
higher
odds
ratios
for
spontaneous
abortions
than
Savitz
et
al.
(
1995).
The
odds
ratios
for
spontaneous
abortion
varied
from
region
to
region,
possibly
due
to
a
difference
in
concentrations
of
BDCM
and
other
byproducts
(
Waller
et
al.
1998).
The
odds
ratios
for
neural
tube
defects
were
generally
higher
than
for
other
defects
above
both
thresholds.
There
was
not
strong
evidence
of
increased
risk,
however,
for
oral
cleft
defects
or
major
cardiac
defects
(
the
odds
ratios
for
both
defects
based
on
Bove
et
al.
(
1995)
were
high).
Overall,
the
odds
ratios
across
60
and
80
µ
g/
L
thresholds
were
similar,
but
tended
to
be
slightly
higher
for
80
µ
g/
L.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
12
July
2003
Exhibit
5.2
Odds
Ratios
(
and
95%
Confidence
Intervals
1)
Calculated
by
Reif
et
al.
(
2000)
for
Reproductive
and
Developmental
Health
Endpoints
at
TTHM
Levels
of
>
80
µ
g/
L
versus
<
80
µ
g/
L
and
>
60
µ
g/
L
versus
<
60
µ
g/
L
Health
Endpoint
Dodds
et
al.
(
1999)
Bove
et
al.
(
1995)
Klotz
and
Pyrch
(
1998)
Savitz
et
al.
(
1995)
Waller
et
al.
(
1998)
Gallagher
et
al.
(
1998)

>
80
µ
g/
L
versus
<
80
µ
g/
L
TTHM
Low
Birth
Weight
1.09
(
0.99,1.19)
1.20
(
1.02,1.41)
N/
A
1.01
(
0.69,1.50)
N/
A
N/
A
Intrauterine
Growth
Retardation
1.05
(
0.98,1.12)
1.12
(
1.03,1.22)
N/
A
N/
A
N/
A
N/
A
Preterm
Birth
1.01
(
0.92,1.10)
1.09
(
0.99,1.19)
N/
A
0.74
(
0.51,1.07)
N/
A
N/
A
Spontaneous
Abortion
N/
A
N/
A
N/
A
1.06
(
0.63,1.78)
1.29
(
0.98,1.69)
N/
A
Stillbirths
1.59
(
1.21,2.10)
0.65
(
0.45,0.95)
N/
A
N/
A
N/
A
N/
A
Neural
Tube
Defects
1.37
(
0.88,2.15)
2.12
(
1.00,4.49)
1.35
(
0.65,2.79)
N/
A
N/
A
N/
A
Oral
Cleft
Defects
1.01
(
0.63,1.63)
1.95
(
0.87,2.90)
N/
A
N/
A
N/
A
N/
A
Major
Cardiac
Defects
0.87
(
0.70,1.08)
1.59
(
0.87,2.90)
N/
A
N/
A
N/
A
N/
A
>
60
µ
g/
L
versus
<
60
µ
g/
L
TTHM
Low
Birth
Weight
1.06
(
0.98,1.16)
1.07
(
0.96,1.18)
N/
A
1.35
(
0.90,2.01)
N/
A
2.24
(
1.03,4.88)

Intrauterine
Growth
Retardation
1.05
(
0.99,1.12)
1.04
(
0.99,1.09)
N/
A
N/
A
N/
A
N/
A
Preterm
Birth
0.98
(
0.91,1.06)
0.96
(
0.91,1.02)
N/
A
1.01
(
0.71,1.44)
N/
A
N/
A
Spontaneous
Abortion
N/
A
N/
A
N/
A
0.97
(
0.56,1.67)
1.22
(
0.98,1.53)
N/
A
Stillbirths
1.56
(
1.18,2.06)
0.80
(
0.65,0.97)
N/
A
N/
A
N/
A
N/
A
Neural
Tube
Defects
1.01
(
0.66,1.56)
1.34
(
0.76,2.38)
1.79
(
1.08,2.95)
N/
A
N/
A
N/
A
Oral
Cleft
Defects
0.91
(
0.59,1.40)
1.25
(
0.78,2.02)
N/
A
N/
A
N/
A
N/
A
Major
Cardiac
Defects
0.94
(
0.78,1.14)
0.93
(
0.59,1.45)
N/
A
N/
A
N/
A
N/
A
Notes:
N/
A
indicates
that
data
for
that
health
endpoint
was
not
presented
in
the
study.

Source:
Adapted
from
Reif
et
al.
(
2000).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
13
July
2003
Exhibit
5.3
PAR
Values
(
and
95%
Confidence
Intervals
1
)
Calculated
by
Reif
et
al.
(
2000)
for
Reproductive
and
Developmental
Health
Endpoints
at
TTHM
Levels
of
>
80
µ
g/
L
versus
<
80
µ
g/
L
and
>
60
µ
g/
L
versus
<
60
µ
g/
L
(
Values
are
Percentages)

Health
Endpoint
Dodds
et
al.
(
1999)
Bove
et
al.
(
1995)
Klotz
and
Pyrch
(
1998)
Savitz
et
al.
(
1995)
Waller
et
al.
(
1998)
Gallagher
et
al.
(
1998)

>
80
µ
g/
L
versus
<
80
µ
g/
L
TTHM
Low
Birth
Weight
2.4
(
0,4.9)
1.5
(
0.1,2.9)
N/
A
0.5
(
0,13.1)
N/
A
N/
A
Intrauterine
Growth
Retardation
1.3
(
0,3.1)
0.9
(
0.2,1.6)
N/
A
N/
A
N/
A
N/
A
Preterm
Birth
0.2
(
0,2.2)
0.7
(
0,1.5)
N/
A
N/
A
N/
A
N/
A
Spontaneous
Abortion
N/
A
N/
A
N/
A
1.9
(
0,18.2)
4.5
(
0,9.5)
N/
A
Stillbirths
14.1
(
4.6,22.7)
N/
A
N/
A
N/
A
N/
A
N/
A
Neural
Tube
Defects
9.8
(
0,23.3)
7.6
(
0,17.0)
3.0
(
0,10.2)
N/
A
N/
A
N/
A
Oral
Cleft
Defects
0.4
(
0,13.1)
6.4
(
0,13.9)
N/
A
N/
A
N/
A
N/
A
Major
Cardiac
Defects
N/
A
4.1
(
0,10.2)
N/
A
N/
A
N/
A
N/
A
>
60
µ
g/
L
versus
<
60
µ
g/
L
TTHM
Low
Birth
Weight
3.2
(
0,7.3)
1.8
(
0,4.6)
N/
A
18.8
(
0,39.0)
N/
A
6.4
(
0,14.1)

Intrauterine
Growth
Retardation
2.7
(
0,5.8)
1.0
(
0,2.4)
N/
A
N/
A
N/
A
N/
A
Preterm
Birth
N/
A
N/
A
N/
A
0.7
(
0,20.4)
N/
A
N/
A
Spontaneous
Abortion
N/
A
N/
A
N/
A
N/
A
6.5
(
0,13.6)
N/
A
Stillbirths
22.5
(
7.7,34.9)
N/
A
N/
A
N/
A
N/
A
N/
A
Neural
Tube
Defects
0.5
(
0,20.0)
7.8
(
0,22.5)
14.1
(
1,25.5)
N/
A
N/
A
N/
A
Oral
Cleft
Defects
N/
A
5.9
(
0,18.0)
N/
A
N/
A
N/
A
N/
A
Major
Cardiac
Defects
N/
A
N/
A
N/
A
N/
A
N/
A
N/
A
Notes:
1.
Lower
confidence
limit
is
truncated
at
zero
N/
A
indicates
that
data
for
that
health
endpoint
were
not
presented
in
the
study.
Note
that
Reif
et
al.
(
2000)
did
not
present
PAR
values
for
effects
where
the
OR
as
shown
in
Exhibit
5.2
was
<
1
(
PAR
considered
by
the
authors
in
those
cases
as
undefined).

Source:
Adapted
from
Reif
et
al.
(
2000).

Critical
review
of
epidemiology
literature
by
Bove
et
al.
(
2002)

Bove
et
al.
(
2002)
conducted
a
qualitative
review
of
14
reproductive
and
developmental
epidemiology
studies
on
exposure
to
chlorination
byproducts
in
drinking
water
(
many
studies
are
the
same
as
those
reviewed
by
Reif
et
al.
[
2000]).
Endpoints
reviewed
include
small
size
for
gestational
age,
birth
defects
(
e.
g.,
neural
tube
defects,
cleft
defects,
and
cardiac
effects),
and
spontaneous
abortions.
Studies
that
evaluated
the
end
point
of
"
small
for
gestational
age"
were
limited
due
to
lack
of
adequate
exposure
information
and
low
study
participation
rate.
Studies
conducted
in
Denver
(
Gallagher
et
al.
1998),
northern
New
Jersey
(
Bove
et
al.
1995),
central
North
Carolina
(
Savitz
et
al.
1995),
and
Nova
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
14
July
2003
Scotia
(
Dodds
et
al.
1999)
based
their
exposure
estimates
on
tap
water
samples
of
THMs
taken
concurrently
with
the
pregnancy
period.
However,
only
one
study
(
Gallagher
et
al.
1998)
involved
modeling
the
distribution
system
characteristics
and
matching
the
residence
with
the
appropriate
sample
location;
this
likely
minimized
exposure
misclassification,
and
further
strengthened
the
relationship
found
in
the
Denver
study
between
TTHM
and
small
for
gestational
age
(
OR
=
5.9;
no
confidence
intervals
reported).

Bove
et
al.
(
2002)
believed
that
there
was
some
consistency
in
the
findings
for
neural
tube
defects
and
oral
cleft
defects,
but
not
for
cardiac
defects.
In
the
two
studies
that
evaluated
neural
tube
defects
and
individual
THMs,
one
obtained
similar
findings
for
both
chloroform
and
BDCM
(
Klotz
and
Pyrch
1998),
while
the
other
study
found
a
much
stronger
association
with
BDCM
(
Dodds
and
King
2001).
Of
the
two
studies
that
evaluated
oral
cleft
defects
and
levels
of
THMs,
one
found
an
association
with
TTHM
(
Bove
et
al.
1995)
and
the
other
found
an
association
with
chloroform,
but
not
TTHM
(
Dodds
and
King
2001).

The
California
prospective
cohort
study
(
Waller
et
al.
1998)
found
a
correlation
between
spontaneous
abortion
and
THMs,
especially
for
BDCM.
An
association
was
also
reported
for
spontaneous
abortion
when
TTHM
levels
were
evaluated,
but
this
relationship
disappeared
when
water
consumption
habits
were
taken
into
account.
Bove
et
al.
(
1995)
noted
that
this
study's
low
participation
rate
was
a
notable
weakness.
In
addition,
because
the
maternal
interviews
were
conducted
after
the
loss
had
occurred,
the
potential
for
recall
bias
in
water
consumption
habits
during
pregnancy
was
introduced.
A
Massachusetts
study
(
Aschengrau
et
al.
1993)
found
no
excess
spontaneous
abortion
correlating
with
treatment
type
(
i.
e.,
chlorination
vs.
chloramination),
but
an
effect
was
reported
correlating
with
water
source
(
i.
e.,
surface
water
vs.
ground
water).

Bove
et
al.
(
2002)
evaluated
three
studies
on
the
incidence
of
fetal
deaths
and
THM
levels,
that
had
very
different
results.
The
Nova
Scotia
study
(
Dodds
and
King
2001)
found
a
strong
association,
especially
with
BDCM
levels.
In
contrast,
the
northern
New
Jersey
study
(
Bove
et
al.
1995)
could
not
evaluate
the
individual
THM
levels
or
information
on
the
cause
of
death.
Therefore,
its
finding
of
no
excess
could
be
the
result
of
misclassification
biases
due
to
the
failure
to
evaluate
individual
THMs
and
specific
causes
of
death.
The
Massachusetts
study
(
Ascehngrau
et
al.
1993)
found
an
association
between
stillbirths
and
chlorinated
surface
water
when
compared
with
chloraminated
surface
water.

Critical
review
of
epidemiology
literature
by
Nieuwenhuijsen
et
al.
(
2000)

Nieuwenhuijsen
et
al.
(
2000)
reviewed
the
toxicological
and
epidemiological
literature
and
evaluated
the
potential
risk
of
chlorinated
DBPs
on
human
reproductive
health.
The
authors
reviewed
10
epidemiological
studies
according
to
the
type
of
assessment
of
exposure
used:
water
source
and
water
treatment
as
an
exposure
index,
routinely
collected
measurements
of
THMs
as
an
index
of
exposure,
and
routinely
collected
THM
measurements
and
estimation
of
individual
THM
ingestion
as
an
exposure
index.
The
authors
commented
that
assessment
of
exposure
is
one
of
the
weakest
aspects
of
the
available
epidemiological
studies.

The
authors
concluded
that
the
evidence
from
a
small
number
of
studies
suggests
a
weak
association
for
spontaneous
abortions,
stillbirths,
and
birth
defects,
and
the
weight­
of­
evidence
is
increasing
as
more
quality
studies
are
completed.
Nieuwenhuijsen
et
al.
concluded
that,
"
although
studies
report
small
risks
that
are
difficult
to
interpret,
the
large
number
of
people
exposed
to
chlorinated
water
supplies
constitutes
a
public
health
concern."

EPA's
epidemiology
research
program
EPA's
epidemiology
research
program
continues
to
examine
the
relationship
between
exposure
to
DBPs
and
adverse
developmental
and
reproductive
effects.
The
Agency
is
supporting
several
studies
using
improved
study
designs
to
provide
better
information
for
characterizing
potential
risks.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
15
July
2003
5.2.1.2
Toxicological
Evidence
of
Adverse
Reproductive
and
Developmental
Health
Effects
EPA
has
evaluated
all
published
studies
of
the
potential
adverse
effects
of
DBPs
on
the
reproductive
and
developmental
health
of
laboratory
animals.
Especially
pertinent
information
comes
from
reviews
of
the
toxicology
literature
by
Dr.
Rochelle
Tyl
(
2000):
"
Review
of
Animal
Studies
for
Reproductive
and
Developmental
Toxicity
Assessment
of
Drinking
Water
Contaminants:
DBPs"
and
by
the
World
Health
Organization
(
2000):
"
Environmental
Health
Criteria
216:
Disinfectants
and
Disinfection
Byproducts."

Review
of
Tyl
(
2000)

Tyl
evaluated
the
literature
using
the
EPA
developmental
(
USEPA
1991b)
and
reproductive
(
USEPA
1996d)
toxicity
risk
assessment
guidelines.
Tyl
focused
her
analysis
on
making
determinations
regarding
hazard
identification
(
that
is,
identifying
the
specific
types
of
adverse
effects
caused
by
these
substances)
and
the
adequacy
of
data
from
the
available
studies
to
support
the
development
of
doseresponse
assessments.

Exhibit
5.4,
adapted
and
updated
from
Tyl
(
2000),
lists
the
types
of
reproductive
and
developmental
toxicology
studies
that
have
been
performed
for
various
disinfectants
and
specific
DBPs.
In
Exhibit
5.4,
the
study
types
are
classified
as
either
screening
studies
or
as
dose­
response
studies.

Tyl
concluded,
based
upon
a
weight
of
evidence
approach
to
the
analysis
of
the
available,
relevant
literature,
that
"
some
of
the
DBPs
have
the
intrinsic
capacity
to
do
harm,
specifically
to
the
developing
conceptus
and
the
male
(
and
possibly
the
female)
reproductive
system."
Specific
reproductive
and
developmental
hazards
that
have
been
identified
and
associated
with
exposure
to
various
DBPs
are
summarized
in
Exhibit
5.5.

Notwithstanding
the
evidence
supporting
the
identification
of
specific
developmental
and
reproductive
effects
from
DBP
exposure,
Tyl
also
concluded
that
the
weight
of
evidence
assessment
does
not
support
a
dose­
response
evaluation
based
on
existing
studies.
(
Tyl
notes
as
"
one
possible
exception"
the
1996
Chemical
Manufacturers
Association's
two­
generation
rat
study
on
chlorite.)

Tyl
also
noted
in
her
overall
summary
and
conclusions
that
in
a
review
of
animal
literature
for
the
purpose
of
risk
assessment,
"
biological
plausibility"
is
a
major
concern.
Tyl
pointed
to
several
aspects
of
both
the
in
vitro
and
in
vivo
studies
that
support
the
biological
plausibility
that
DBPs
can
cause
adverse
reproductive
and
developmental
effects.
In
particular,
there
was
an
observed
temporal
relationship
between
the
exposures
in
toxicological
studies
and
the
occurrence
of
the
developmental
(
e.
g.,
embryonic
neural
tube,
embryonic
heart)
or
reproductive
process
(
e.
g.,
spermatogenesis).
The
observed
effects
were
reproducible
in
the
same
or
similar
study
designs.
The
effects
were
consistent
across
study
designs.
The
effects
observed
in
animal
toxicological
studies
were
comparable
to
those
observed
in
some
human
epidemiological
studies
(
e.
g.,
embryonic
heart
and
neural
tube
defects,
full
litter
resorption/
miscarriage,
spontaneous
abortion,
or
stillbirth).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
16
July
2003
Exhibit
5.4
Availability
of
Reproductive
and
Developmental
Toxicology
Studies
for
Specific
DBPs
Disinfectant
or
DBP
Screens
­
Hazard
Identification
Dose
Response
WEC
NTP
35
Day
CKA
CKA++
Male
Repro
Seg
II
Multi­
GEN
DISINFECTANTS
Chlorine
X
Chlorine
Dioxide
X
X
Chloramine
X
TRIHALOMETHANES
Chloroform
X
X
X
X
Bromoform
X
X
X
Bromodichloromethane
X
X
X
X
X
Dibromochloromethane
X
X
HALOACETIC
ACIDS
Monochloroacetic
acid
X
X
Dichloroacetic
acid
X
X
X
Trichloroacetic
acid
X
X
X
Monobromoacetic
acid
X
X
X
Dibromoacetic
acid
X
X
X
X
X
X
Tribromoacetic
acid
X
X
Bromochloroacetic
acid
X
X
X
P
Bromodichloroacetic
acid
X
Dibromochloroacetic
acid
X
X
HALOACETONITRILES
Chloroacetonitrile
X
Dichloroacetonitrile
X
X
Trichloroacetonitrile
X
X
Bromoacetonitrile
X
X
Dibromoacetonitrile
X
X
Tribromoacetonitrile
Bromochloroacetonitrile
X
X
ALDEHYDES
Formaldehyde
X
X
X
X
Acetaldehyde
X
X
Propanal
X
X
MISCELLANEOUS
1,1­
Dichloropropanone
X
Hexachloropropanone
X
Dichloromethane
X
Dibromomethane
X
MX
X
X
Bromate
X
Chlorite
X
X
X
Notes:
X
=
Completed
and
published
in
the
literature;
P
=
In
planning
stage;
WEC
=
Whole
embryo
culture;
NTP
35
Day
=
NTP
35­
day
reproductive/
developmental
toxicity
screen;
CKA
=
Chernoff­
Kavlock
Assay;
CKA
(++)
=
Chernoff­
Kavlock
Assay
(
modified);
Male
Repro.
=
Short­
term
adult
male
reproductive
toxicity
screen;
Seg
II
=
Segment
II
developmental
toxicity
study;
Multi­
GEN
=
Multigeneration
reproductive
toxicity
study.

Source:
Adapted
and
updated
from
Tyl
(
2000).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
17
July
2003
Exhibit
5.5
Reproductive
and
Developmental
Health
Effects
Associated
with
DBPs
in
Toxicological
Studies
Type
of
Effect
DBP
Developmental
defects
Trichloroacetic
acid
(
TCAA),
dichloroacetic
acid
(
DCAA),
and
monochloroacetic
acid
(
MCAA)

Whole
litter
resorption
Chloroform,
bromoform,
bromodichloromethane
(
BDCM),
dibromochloromethane
(
DBCM),
DCAA,
TCAA,
dichloroacetonitrile
(
DCAN),
and
trichloroacetonitrile
(
TCAN)

Fetotoxicity
(
reduced
fetal
body
weights,
increased
anomalies
like
chromosomal
defects)
Chloroform,
BDCM,
DBCM,
DCAA,
TCAA,
DCAN,
TCAN,
dibromoacetonitrile
(
DBAN),
bromochloroacetonitrile
(
BCAN),
monochloroacetonitrile
(
MCAN)
acetaldehyde,
formaldehyde
Male
reproductive
defects
DCAA,
dibromoacetic
acid
(
DBAA),
BDCM,
formaldehyde
Source:
Adapted
from
Tyl
(
2000).

Review
of
WHO
(
2000)

The
International
Programme
on
Chemical
Safety
(
IPCS)
published
an
evaluation
of
Disinfectants
and
DBPs
in
its
Environmental
Health
Criteria
monograph
series
(
WHO
2000).
In
this
review
of
the
toxicology
data
on
reproductive
and
developmental
effects
from
DBP
exposure,
the
World
Health
Organization
(
WHO)
concludes
that
although
the
data
on
these
effects
are
not
as
robust
as
the
cancer
database,
these
effects
are
of
potential
health
concern.
The
WHO
concludes
that
reproductive
effects
in
females
have
been
principally
embryolethality
and
fetal
resorptions
associated
with
the
haloacetonitriles
(
HANs)
and
the
dihaloacetates,
while
DCAA
and
DBAA
have
both
been
associated
with
adverse
effects
on
male
reproduction.

New
Toxicology
Data
Since
promulgating
the
Stage
1
DBPR,
EPA
has
continued
to
support
reproductive
and
developmental
toxicological
research
on
various
DBPs
through
extramural
and
intramural
research
programs.
Information
on
EPA's
toxicology
programs
can
be
found
at
http://
www.
epa.
gov/
nheerl/.
This
research,
along
with
the
new
published
data
on
several
DBPs
since
the
1998
Stage
1
DBPR,
are
summarized
in
the
draft
updated
children's
health
document
"
Health
Risks
to
Fetuses,
Infants,
and
Children:
A
Review"
(
USEPA
2002h).
Summaries
of
new
studies
are
provided
below.

Christian
et
al.
(
2001a)
conducted
a
developmental
toxicity
study
with
pregnant
New
Zealand
White
rabbits
exposed
to
BDCM
in
drinking
water
at
concentrations
of
0,
15,
150,
450,
and
900
ppm
in
drinking
water
on
gestation
days
6­
29.
The
NOAEL
and
LOAEL
identified
for
maternal
toxicity
in
this
study
were
13.4
mg/
kg­
day
(
150
ppm)
and
35.6
mg/
kg­
day
(
450
ppm),
respectively,
based
on
decreased
body
weight
gain.
The
developmental
NOAEL
was
55.3
mg/
kg­
day
(
900
ppm)
based
on
absence
of
statistically
significant,
dose­
related
effects
at
any
tested
concentration.
Christian
et
al.
(
2001a)
also
conducted
a
developmental
study
of
BDCM
in
a
second
species,
Sprague­
Dawley
rats.
Rats
were
exposed
to
BDCM
in
the
drinking
water
at
concentrations
of
0,
50,
150,
450,
and
900
ppm
on
gestation
days
6
to
21.
The
concentration­
based
maternal
NOAEL
and
LOAEL
for
this
study
were
150
ppm
and
450
ppm,
respectively,
based
on
statistically
significant,
persistent
reductions
in
maternal
body
weight
and
body
weight
gains.
Based
on
the
mean
consumed
dosage
of
bromodichloromethane,
these
concentrations
correspond
to
doses
of
18.4
mg/
kg­
day
and
45.0
mg/
kg­
day,
respectively.
The
concentration­
based
developmental
NOAEL
and
LOAEL
were
450
ppm
and
900
ppm,
respectively,
based
on
a
significantly
decreased
number
of
ossification
sites
per
fetus
for
the
forelimb
phalanges
(
bones
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
18
July
2003
of
the
hand
or
the
foot)
and
the
hindlimb
metatarsals
and
phalanges.
These
concentrations
correspond
to
mean
consumed
doses
of
45.0
mg/
kg­
day
and
82.0
mg/
kg­
day,
respectively.

Christian
et
al.
(
2002b)
summarized
the
results
of
a
two­
generation
reproductive
toxicity
study
on
bromodichloromethane
conducted
in
Sprague­
Dawley
(
SD)
rats.
Bromodichloromethane
was
continuously
provided
to
test
animals
in
the
drinking
water
at
concentrations
of
0,
50,
150,
or
450
ppm.
Average
daily
doses
estimated
for
the
50,
150
and
450
ppm
concentrations
were
reportedly
4.1
to
12.6,
11.6
to
40.2,
and
29.5
to
109
mg/
kg­
day,
respectively.
The
parental
NOAEL
and
LOAEL
were
50
and
150
ppm,
respectively,
based
on
statistically
significant
reduced
body
weight
and
body
weight
gain;
F1
and
F2
generation
pup
body
weights
were
reduced
in
the
150
and
450
ppm
groups
during
the
lactation
period
after
the
pups
began
to
drink
the
water
provided
to
the
dams.
Body
weight
and
body
weight
gain
were
also
reduced
in
the
150
and
450
ppm
F1
generation
males
and
females.
A
marginal
effect
on
estrous
cyclicity
was
observed
in
F1
females
in
the
450
ppm
exposure
group.
Small
(
#
6%),
but
statistically
significant,
delays
in
F1
generation
sexual
maturation
occurred
at
150
ppm
(
males)
and
450
ppm
(
males
and
females)
as
determined
by
timing
of
vaginal
patency
or
preputial
separation.
The
study
authors
considered
these
effects
to
be
a
secondary
response
associated
with
reduced
body
weights
cause
appears
to
be
dehydration
brought
about
by
taste
aversion
to
the
compound.
The
results
of
this
study
identify
NOAEL
and
LOAEL
values
for
reproductive
effects
of
50
ppm
(
4.1
to
12.6
mg/
kg­
day)
and
150
ppm
(
11.6
to
40.2
mg/
kg­
day),
respectively,
based
on
delayed
sexual
maturation.

Bielmeier
et
al.
(
2001)
conducted
a
series
of
experiments
to
investigate
the
mode
of
action
in
bromodichloromethane­
induced
full
litter
resorption
(
FLR).
The
study
included
a
strain
comparison
of
F344
and
Sprague­
Dawley
(
SD)
rats.
In
the
strain
comparison
experiment,
female
SD
rats
(
13
to
14/
dose
group)
were
dosed
with
0,
75,
or
100
mg/
kg­
day
by
aqueous
gavage
in
10%
Emulphor
®
on
GD
6
to
10.
F344
rats
(
12
to
14/
dose
group)
were
dosed
with
0
or
75
mg/
kg­
day
administered
in
the
same
vehicle.
The
incidence
of
FLR
in
the
bromodichloromethane­
treated
F344
rats
was
62%,
while
the
incidence
of
FLR
in
SD
rats
treated
with
75
or
100
mg/
kg­
day
of
bromodichloromethane
was
0%.
Both
strains
of
rats
showed
similar
signs
of
maternal
toxicity,
and
the
percent
body
weight
loss
after
the
first
day
of
dosing
was
comparable
for
SD
rats
and
the
F344
rats
that
resorbed
their
litters.
The
rats
were
allowed
to
deliver
and
pups
were
examined
on
postnatal
days
1
and
6.
Surviving
litters
appeared
normal
and
no
effect
on
post­
natal
survival,
litter
size,
or
pup
weight
was
observed.
The
series
of
experiments
conducted
by
Bielmeier
et
al.
(
2001)
identified
a
LOAEL
of
75
mg/
kg­
day
(
the
lowest
dose
tested)
based
on
FLR
in
F344
rats.
A
NOAEL
was
not
identified.
Mechanistic
studies
indicate
that
BDCM­
induced
pregnancy
loss
is
likely
to
be
luteinizing
hormone
(
LH)­
mediated
(
Bielmeier
et
al.,
2001).
It
is
possible
that
BDCM
alters
LH
levels
by
disrupting
the
hypothalamic­
pituitary­
gonadal
axis
or
by
altering
the
responsiveness
of
the
corpora
lutea
to
LH.
Since
these
possible
mechanisms
are
potentially
relevant
to
pregnancy
maintenance
in
humans,
EPA
believes
the
finding
of
BDCM­
induced
pregnancy
loss
in
F344
rats
is
relevant
to
risk
assessment,
and
may
provide
insight
into
the
epidemiological
finding
of
increased
risk
of
spontaneous
abortion
associated
with
consumption
of
BDCM
(
Waller
et
al.
1998,
2001).

Christian
et
al.
(
2002a)
recently
completed
a
two­
generation
drinking
water
study
of
DBAA
in
rats.
Male
and
female
Sprague­
Dawley
rats
(
30/
sex/
exposure
group)
were
administered
DBAA
in
drinking
water
at
concentrations
of
0,
50,
250,
or
650
ppm
continuously
from
initiation
of
exposure
of
the
parental
(
P)
generation
male
and
female
rats
through
weaning
of
the
F
2
offspring.
Based
on
testicular
histomorphology
indicative
of
abnormal
spermatogenesis
in
P
and
F
1
males,
the
parental
and
reproductive/
developmental
toxicity
LOAEL
and
NOAEL
are
250
and
50
ppm,
respectively.

Previous
studies
by
EPA
have
reported
adverse
effects
of
DBAA,
administered
via
oral
gavage,
on
spermatogenesis
that
impacted
male
fertility
(
Linder
et
al.
1994a,
1995,
1997a)
at
doses­
comparable
to
those
achieved
in
the
Christian
et
al.
(
2002a)
study.
Based
on
these
studies
collectively,
DBAA
is
spermatotoxic.
Moreover,
Veeramachaneni
et
al.
(
2000)
reported
in
an
abstract
that
sperm
from
male
rabbits
exposed
to
DBA
in
utero
from
gestation
days
15
and
throughout
life
reduced
the
fertility
of
artificially
inseminated
females
as
evidenced
by
reduced
conceptions.
When
published,
this
study
may
support
the
evidence
that
DBA
is
a
male
reproductive
system
toxicant.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
19
July
2003
In
addition,
research
on
DBAA
by
Klinefelter
et
al.
(
2001)
has
demonstrated
statistically
significant
delays
in
both
vaginal
opening
and
preputial
separation
using
the
body
weight
on
the
day
of
acquisition
(
at
postnatal
day
45)
as
the
co­
variant.
This
was
not
found
by
Christian
et
al
(
2002a)
using
the
body
weight
at
weaning
as
the
statistical
covariant.
However,
the
authors
analyzed
the
data
for
preputial
separation
and
vaginal
opening
with
body
weight
on
the
day
of
weaning
as
a
co­
variant
rather
than
body
weight
on
the
day
of
acquisition,
i.
e.
the
day
that
the
prepuce
separates
or
the
day
the
vagina
opens.
It
is
likely
that
there
was
an
increase
in
body
weight
from
postnatal
day
21
(
weaning)
until
preputial
separation
(
day
45)
that
was
independent
of
the
delay
in
sexual
maturation.

Although
the
Christian
et
al
(
2002a)
study
was
conducted
in
accordance
with
EPA's
1998
testing
guidelines,
EPA
has
incorporated
newer,
more
sophisticated
measures
into
recent
intramural
and
extramural
studies
that
have
not
yet
been
incorporated
into
the
testing
guidelines.
Such
measures
include
measuring
changes
in
specific
proteins
in
the
sperm
membrane
proteome
and
fertility
assessments
via
in
utero
insemination.
EPA
believes
that
additional
research
is
needed,
utilizing
these
newer
toxicological
measures,
to
clarify
the
extent
to
which
DBAA
poses
human
reproductive
or
developmental
risk.
The
database
on
male
reproductive
effects
from
exposure
to
DBAA
is
incomplete
and
is
not
suitable
for
quantitative
risk
assessment
at
this
time.
It
does
identify
reproductive
effects
as
an
area
of
concern.

In
addition
data
compiled
in
the
children's
health
document,
EPA
has
prepared
individual
health
criteria
documents
that
provide
detailed
summaries
of
the
relevant
new
information,
as
well
as
an
overall
characterization
of
the
human
health
risks
from
exposure
to
these
DBPs
(
USEPA
2003c­
g).
From
these
new
evaluations,
EPA
has
concluded
that
several
new
studies
on
individual
byproducts
contribute
to
the
weight
of
evidence
for
an
association
between
DBP
exposure
and
adverse
effects
on
the
developing
fetus
and
reproduction.
These
effects
include
fetal
loss,
cardiovascular
effects,
and
male
reproductive
effects
and
are
associated
with
BDCM,
DCAA,
TCAA,
BCAA,
and
DBAA.
The
new
data
from
these
studies
do
not
change
the
MCLGs
and
MRDLGs
that
were
established
as
a
part
of
the
Stage
1
DBPR.

5.2.1.3
Conclusions
EPA
believes
that
toxicology
and
epidemiology
data
suggests
that
exposure
to
chlorinated
drinking
water
has
the
potential
to
cause
adverse
reproductive
and
developmental
effects.
Although
the
science
on
reproductive
and
developmental
health
effects
as
a
result
of
DBP
exposure
is
not
strong
enough
to
include
them
in
the
primary
Stage
2
DBPR
benefits
analysis
at
this
time,
EPA
concludes
that
the
data
are
sufficient
to
determine
that
a
concern
exists
warranting
additional
regulatory
action.
The
following
are
the
specific
key
factors
used
to
support
EPA's
weight­
of­
evidence
conclusion
regarding
this
conclusion:

°
The
results
of
several
studies
performed
by
different
researchers
with
different
methods
at
different
research
sites
show
similar
trends.

°
Some
health
effects
observed
in
animal
toxicological
studies
are
comparable
to
those
observed
in
some
human
epidemiological
studies
(
e.
g.,
embryonic
heart
and
neural
tube
defects,
full
litter
resorption/
miscarriage,
spontaneous
abortion,
or
stillbirth)
showing
similarity
of
effects
between
animal
toxicity
and
human
epidemiology
studies.

°
Difficulties
in
assessing
exposure
to
DBPs,
resulting
in
exposure
misclassification,
may
underestimate
reproductive
and
developmental
risks
associated
with
DBPs.
It
is
possible
that
some
of
the
inconsistencies
reported
in
epidemiological
and
toxicological
study
results
are
due
to
these
misclassifications,
and
the
true
effects
may
be
greater
than
demonstrated.
A
spurious
effect
would
be
produced
only
in
rare
cases,
and
is
unlikely
as
described
in
Reif
et
al.
(
2000)
and
Bove
et
al.
(
2002).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
20
July
2003
EPA
has
epidemiology
and
toxicology
research
programs
that
continue
to
examine
the
relationship
between
exposure
to
DBPs
and
potential
adverse
reproductive
and
developmental
health
effects.
EPA
is
also
supporting
several
studies
using
improved
study
design
to
provide
better
information
for
characterizing
potential
risks.
This
research
is
intended
to
yield
more
precise
dose­
response
relationships
to
support
a
quantitative
risk
assessment.

5.2.2
Cancer
Several
DBPs
have
been
identified
by
EPA
as
probable
or
possible
human
carcinogens.
The
following
sections
provide
an
overview
of
the
epidemiological
and
toxicological
evidence
for
the
carcinogenicity
of
key
DBPs.

5.2.2.1
Epidemiological
Evidence
of
DBP
Carcinogenicity
New
studies
published
since
the
Stage
1
DBPR
continue
to
support
an
association
between
bladder,
colon
and
rectal
cancers
and
exposure
to
chlorinated
surface
water
(
Yang
et
al.
1998;
Koivusalo
et
al.
1998;
King
et
al.
2000b).
EPA
believes
that
the
available
epidemiological
studies
along
with
the
review
of
the
cancer
epidemiology
literature
in
the
International
Programme
on
Chemical
Safety
report
on
disinfectants
and
disinfection
byproducts
(
WHO
2000)
provide
important
information
on
the
potential
human
health
hazards
from
exposure
to
chlorinated
drinking
water.

Bladder
Cancer
­
Studies
Supporting
EPA's
PAR
Analysis
Bladder
cancer
and
chlorinated
DBP
exposure
has
historically
been
the
most
strongly
supported
association
of
all
the
possible
cancers,
based
on
human
evidence.
The
Stage
1
DBPR
RIA
(
USEPA
1998a)
presents
EPA's
review
of
the
large
body
of
epidemiology
literature
for
bladder
cancer
and
its
association
with
DBPs
in
drinking
water.
From
this
review,
EPA
concluded
that
although
causality
has
not
been
established,
the
data
support
a
weak
association,
which
may
be
a
concern.
Particular
gaps
in
EPA's
understanding
include
the
reason
for
inconsistent
results
across
subpopulations
in
the
different
studies,
especially
for
males
versus
females
and
smokers
versus
nonsmokers.

Consistent
with
the
approach
used
for
the
Stage
1
DBPR,
EPA
calculated
PAR
values
for
bladder
cancer
associated
with
exposure
to
chlorinated
drinking
water
from
data
provided
in
five
epidemiological
studies
(
note
that
Cantor
et
al.
1985
and
Cantor
et
al.
1987
use
the
same
epidemiological
data):

°
Cantor
et
al.
(
1985;
1987)

°
McGeehin
et
al.
(
1993)

°
King
and
Marrett
(
1996)

°
Freedman
et
al.
(
1997)

°
Cantor
et
al.
(
1998)

Exhibit
5.6
provides
relevant
summary
information
for
each
of
these
studies
and
the
PAR
values
calculated
from
them
by
EPA.
Appendix
E
provides
additional
information
on
the
derivation
and
use
of
PAR
values
in
general,
as
well
as
additional
details
on
the
PAR
values
derived
from
these
studies
by
EPA.

All
of
these
studies
include
adjustments
in
their
analyses
to
account
for
possible
confounding
by
other
factors
that
may
contribute
to
bladder
cancer,
notably
sex,
age,
and
smoking.
Cantor
et
al.
and
McGeehin
et
al.
also
included
adjustments
for
occupational
exposure,
which
other
studies
have
estimated
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
21
July
2003
may
be
the
attributable
factor
in
20
percent
of
bladder
cancer
cases
(
Silverman
et
al.
1989a,
Silverman
et
al.
1989b,
and
Silverman
et
al.
1990)

As
shown
in
Exhibit
5.6,
the
estimated
PAR
percentages
from
the
studies
range
from
2
percent
to
17
percent.
Those
values
are
"
best
estimates"
derived
from
the
study
data
as
described
in
Appendix
E,
and
are
the
values
used
in
the
quantitative
benefits
analysis
for
the
Stage
2
DBPR
(
presented
later
in
this
chapter).
EPA
has
also
estimated
95
percent
confidence
intervals
for
those
PAR
values
using
a
Monte
Carlo
simulation
procedure,
which
is
also
described
in
Appendix
E.
In
most
cases,
the
lower
confidence
bound
has
been
truncated
at
0
percent
based
on
biological
plausibility
considerations.
That
is,
notwithstanding
statistical
indications
of
PAR
values
<
0
percent
implied
by
odds
ratios
<
1.0,
there
is
no
toxicological
or
epidemiological
data
to
support
a
conclusion
that
increased
DBP
exposure
would
reduce
bladder
cancer.

It
is
estimated
that
currently
56,500
new
cases
of
bladder
cancer
occur
annually
(
American
Cancer
Society
2002).
Using
the
PAR
estimates
of
2
to
17
percent,
the
number
of
bladder
cancer
cases
per
year
potentially
associated
with
exposure
to
DBPs
in
chlorinated
drinking
water
is
estimated
to
range
from
1,100
(
0.02
×
56,500)
to
9,600
(
0.17
×
56,500)
cases.
EPA
believes
that
the
central
tendencies
(
i.
e.,
the
means
of
individual
studies,
which
in
this
case
range
from
2
to
17
percent)
are
a
reasonable
estimate
of
the
potential
range
of
risk
in
the
entire
population.
However,
this
range
is
not
absolute
and
the
actual
PAR
value
may
be
higher
or
lower
than
this
estimated
range,
including
zero
as
a
possible
value.
Appendix
E
provides
additional
discussion
of
the
estimation
of
the
95
percent
confidence
bounds
on
the
PAR
values
as
shown
in
Exhibit
5.6.

Given
the
studies
used
in
the
PAR
analysis
were
conducted
prior
to
the
implementation
of
Stage
1
DBPR,
the
potential
risk
estimates
derived
from
these
studies
are
considered
pre­
Stage
1
risk
estimates.
The
analysis
in
this
EA
takes
this
into
account
when
estimating
potential
risk
reductions
from
Stage
1
DBPR
and
Stage
2
DBPR
(
see
section
5.4.2).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
22
July
2003
Exhibit
5.6
Summary
of
Epidemiology
Studies
for
Bladder
Cancer
Associated
with
Chlorinated
Drinking
Water
and
EPA
Calculated
PAR
Values
Study
Description
Summary
of
Results
Comments
PAR
(
95%
CI)
1
Cantor
et
al.
(
1985)
Case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
surface
water
­
Odds
ratio
for
all
whites
with
over
59
years
of
exposure
is
1.1
(
95%
Confidence
Interval:
0.8­
1.5)
­
Odds
ratio
for
nonsmokers
is
2.3
(
95%
Confidence
Interval:
1.3­
4.2)
­
Odds
ratio
for
current
smokers
is
0.6
(
95%
Confidence
Interval:
0.3­
1.2)
Majority
of
water
systems
contained
less
than
20
µ
g/
L
THMs.
2%
(
0%
­
15%)

Cantor
et
al.
(
1987)
2
Case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
surface
water
­
Odds
ratio
for
both
sexes
with
over
59
years
of
exposure
to
tap
water
is
1.4
(
95%
Confidence
Interval:
0.9­
2.3)
­
Odds
ratio
for
nonsmokers
with
over
59
years
of
exposure
to
tap
water
is
3.1
(
95%
Confidence
Interval:
1.3­
7.3)
Long­
term
bladder
cancer
risks
are
more
prominent
in
nonsmokers.
15%
(
0%
­
31%)

McGeehin
et
al.
(
1993)
Case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
surface
water
­
Odds
ratio
for
bladder
cancer
with
over
30
years
of
exposure
is
1.8
(
95%
Confidence
Interval:
1.1­
2.9)
­
Odds
ratio
for
cases
consuming
over
5
glasses
of
tap
water
per
day
is
2.0
(
95%
Confidence
Interval:
1.1­
2.8)
Level
of
total
THMs,
residual
chlorine,
or
nitrates
not
associated
with
bladder
cancer
risk
controlling
for
years
of
exposure.
17%
(
0%
­
33%)

King
and
Marrett
(
1996)
Case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
surface
water
­
Odds
ratio
for
bladder
cancer
for
35
years
of
exposure
compared
to
10
years
is
1.42
(
95%
Confidence
Interval:
1.10­
1.81)
­
Bladder
cancer
risk
increased
with
years
of
exposure
­
Risk
increases
by
11
percent
with
each
1,000
µ
g/
L
THM­
year3
Statistically
significant
only
for
lengthy
exposures.
Results
provide
no
support
for
an
interaction
between
volume
of
water
consumed
and
years
of
exposure
to
THMs
level
>
49
µ
g/
L.
17%
(
1%
­
28%)

Freedman
et
al.
(
1997)
Nested
case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
drinking
water
­
Odds
ratio
for
bladder
cancer
using
1975
measure
of
exposure
is
1.2
(
95%
Confidence
Interval:
0.9­
1.6)
­
Slight
gradient
of
increasing
risk
with
increasing
duration
noted
only
among
smokers
Further
stratification
by
gender
showed
elevated
odds
ratios
to
be
restricted
to
male
smokers.
3%
(
0%
­
22%)

Cantor
et
al.
(
1998)
Case­
control
study
of
association
between
bladder
cancer
and
consumption
of
chlorinated
surface
water
­
Little
overall
association
between
bladder
cancer
risk
and
exposure
to
chlorination
byproducts
­
Bladder
cancer
risk
increased
with
exposure
duration
Opposite
trends
were
found
in
males
and
females.
Total
lifetime
and
average
lifetime
TTHM
levels
show
all
risk
increases
are
apparently
restricted
to
male
smokers.
3%
(
0%
­
8%)

Notes:
1.
Confidence
intervals
truncated
at
zero
to
reflect
biological
plausibility.
The
actual
lower
confidence
level
is
often
negative.
2.
The
Cantor
et
al.
1987
study
is
based
upon
the
same
data
set
as
the
Cantor
et
al.
1985
study.
OR
and
PAR
values
for
Cantor
1987
reflect
modifications
to
the
inclusion
criteria
and
adjustments
for
confounders
relative
to
the
analysis
performed
in
the
1985
study.
3.
THM­
years
are
the
product
of
the
continuous
estimate
of
a
given
THM
level
(
1,000
µ
g/
L)
and
years
at
that
level,
analogous
to
pack­
years
of
cigarette
smoking.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
23
July
2003
New
Bladder
Cancer
Studies
Two
new
studies
(
Yang
et
al.
1998
and
Koivusalo
et
al.
1998)
also
suggest
an
association
of
DBP
exposure
with
bladder
cancer.
Yang
et
al.
1998
found
a
positive
association
between
consumption
of
chlorinated
drinking
water
and
bladder
cancer.
Koivusalo
et
al.(
1998)
found
evidence
of
increased
risk
as
a
function
of
increasing
DBP
exposure
duration.
Long
exposure
durations
(>
45
years
for
Koivusalo
et
al.
1998)
were
associated
with
about
a
two­
fold
increase
in
risk.
The
new
bladder
cancer
studies
continue
to
support
an
association
and
potential
for
a
causal
relationship
between
exposure
to
chlorination
byproducts
and
risk
for
bladder
cancer.

A
new
publication
by
Villanueva
et
al.
(
2003)
reports
on
their
meta­
analysis
of
case­
control
and
cohort
studies.
This
meta­
analysis
may
be
useful
for
improving
the
estimate
of
national
population
attributable
risk
(
fraction
of
bladder
cancer
cases
in
the
US
that
may
be
attributed
to
chlorinated
drinking
water).
Compared
to
EPA's
current
approach
(
i.
e.,
providing
a
range
of
population
attributable
risks
(
PAR)),
use
of
the
meta­
estimate
would
provide
a
more
stable
result
because:

°
It
provides
a
single
(
meta)
estimate
of
the
odds
ratio
from
which
to
calculate
the
PAR,
thereby
summarizing
the
results
across
studies,
thus
reducing
the
influence
of
geographic
and
temporal
differences.

°
It
uses
three
additional
high­
quality
studies
not
included
in
the
PAR
range
analysis
conducted
by
EPA
(
i.
e.,
studies
by
Koivusalo
et
al.
1998,
Doyle
et
al.
1997,
and
Vena
et
al.
1993).

°
It
weights
the
individual
studies
according
to
their
precision,
so
more
precise
estimates
(
due
principally
to
greater
numbers
of
cases)
carry
greater
statistical
weight
and
therefore
have
greater
influence
on
the
meta­
estimate.

°
In
addition
to
the
primary
analysis,
the
authors
conducted
an
evaluation
of
the
robustness
of
their
conclusions.
They
examined
the
sensitivity
of
estimates
to
decisions
made
with
respect
to
exposure
definitions,
cut
points
defining
exposure
groups,
inclusion/
exclusion
of
individual
studies,
and
potential
publication
bias.

The
meta­
analysis
provided
at
least
two
meta­
estimates
that
may
be
useful
for
estimating
national
population
attributable
risk:

°
A
combined
odds
ratio
for
ever­
exposure,
with
confidence
intervals
and
°
A
combined
dose­
response
regression
slope
coefficient,
relating
increasing
odds
ratios
to
additional
years
of
chlorinated
drinking
water
consumption.

EPA
conducted
an
estimate
of
the
impact
of
using
the
meta­
analysis
to
provide
a
perspective
on
the
national
population
attributable
risk.
This
estimate
is
based
on
the
author's
correction
of
a
minor
transcription
error
in
their
published
manuscript
(
the
appropriate
estimate
for
the
King
study
yields
corrected
over­
all
odds
ratio
for
ever­
consumers
of
1.2
with
95%
confidence
interval
of
1.091
to
1.320,
personal
communication
from
M.
Kogevinas
to
M.
Messner,
5/
19/
2003).
Assuming
70%
of
the
US
population
is
in
the
ever­
consumed
category
(
based
on
the
chlorinated
surface
water
exposed
population),
a
point
estimate
of
the
population
attributable
risk
using
the
odds
ratio
from
the
meta­
analysis
is
12%
(
95%
interval
6%
to
18%).
Although
EPA's
population
attributable
risk
range
(
2%
to
17%)
was
not
intended
to
convey
a
quantified
level
of
confidence,
it
is
not
vastly
different
from
the
meta­
analysis'
95%
confidence
range
of
6%
to
18%.
EPA
regards
the
meta­
range
as
additional
support
for
EPA's
population
attributable
risk
range.
The
meta­
analysis
provides
continued
support
for
an
association
between
exposure
to
chlorinated
surface
water
and
bladder
cancer.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
24
July
2003
Other
Cancers
Colorectal
cancer
is
the
third
most
common
site
of
new
cases
and
deaths
in
both
men
and
women
in
the
U.
S.
It
is
estimated
that
148,300
new
colorectal
cancer
cases
will
be
diagnosed
in
2002,
with
56,600
resulting
in
deaths
(
American
Cancer
Society
2002).
Human
epidemiology
studies
on
chlorinated
surface
water
have
reported
associations
with
colorectal
cancer.
Since
the
Stage
1
DBPR,
three
new
human
epidemiology
studies
(
King
et
al.
2000b;
Yang
et
al.
1998
and
Hildesheim
et
al.
1998)
have
been
conducted
to
investigate
the
relationship
between
colorectal
cancers
and
exposure
to
chlorinated
surface
water.
King
et
al.
(
2000b),
a
population­
based
case­
control
study,
found
evidence
of
an
increased
colon
cancer
risk
for
males
with
cumulative
exposure
to
THMs
and
duration
of
exposure
to
chlorinated
surface
water.
Yang
et
al.
(
1998),
an
ecologic
epidemiological
study,
and
Hildesheim
et
al.
(
1998),
a
populationbased
case­
control
study,
both
found
associations
between
chlorinated
drinking
water
exposure
and
rectal
cancer,
and
the
associations
had
a
similar
magnitude
in
both
sexes.
Hildesheim
et
al.
also
found
an
association
in
both
sexes
with
lifetime
average
THM
concentration.
The
consistency
of
the
dose­
response
trends,
the
consistency
between
sexes,
and
the
apparent
control
of
important
potential
confounders
in
this
study
suggest
that
the
observed
associations
between
the
exposures
and
rectal
cancer
are
real.

Two
new
human
epidemiology
studies
support
the
possibility
of
an
association
between
DBPs
and
kidney
cancer.
The
previously
mentioned
Yang
et
al.
(
1998)
study
found
fairly
high
odds
ratios
(
ORs).
Koivusalo
et
al.
(
1998)
demonstrated
a
dose­
response
association
when
the
exposure
was
represented
by
an
estimation
of
the
level
of
mutagenicity
of
the
drinking
water.
This
mutagenicity
estimation
was
based
on
raw
water
quality
and
water
treatment
practices
information.
The
current
database
for
this
endpoint
of
cancer,
however,
is
insufficient
to
conclude
an
association.

Cantor
et
al.
(
1999)
studied
brain
cancer,
focusing
on
gliomas.
None
of
the
exposure
variables
were
related
to
brain
cancer
among
females,
but
males
showed
a
statistically
significant,
monotonically
increasing
risk
associated
with
duration
of
exposure
to
chlorinated
surface
water.
This
study
suggests
a
possible
association
between
chlorination
byproducts
and
gliomas;
however,
the
evidence
from
this
study
is
not
strong
enough
to
support
or
discount
a
conclusion
of
a
causal
association.

Infante­
Rivard
et
al.
(
2001)
conducted
a
population­
based
case­
control
study
in
Quebec
Province,
Canada,
to
examine
possible
associations
between
childhood
acute
lymphoblastic
leukemia
and
THMs.
There
were
no
associations
with
leukemia
for
any
of
the
exposure
indices
for
total
THM,
or
specific
THMs.
Therefore
the
study
does
not
provide
evidence
of
an
association
between
any
of
the
exposure
variables
and
childhood
leukemia.

Review
of
the
cancer
epidemiology
literature
(
WHO
2000)

The
International
Programme
on
Chemical
Safety
(
IPCS)
report
on
disinfectants
and
disinfection
byproducts
(
WHO
2000)
concludes
that
results
of
the
analytical
epidemiological
cancer
studies
are
insufficient
to
support
a
causal
relationship
for
bladder,
colon,
rectal,
or
any
other
cancer
and
chlorinated
drinking
water
or
THMs.

5.2.2.2
Toxicological
Evidence
of
DBP
Carcinogenicity
EPA
believes
that
the
available
toxicological
studies
provide
important
information
on
the
potential
carcinogenicity
of
DBPs
in
humans.
EPA's
Integrated
Risk
Information
System
(
IRIS),
which
is
accessible
at
http://
www.
epa.
gov/
iris,
provides
detailed
descriptions
of
cancer
risk
assessments
that
EPA
has
performed
for
seven
DBPs.
Included
on
IRIS
are
weight­
of­
evidence
characterizations
of
the
carcinogenic
potential
of
those
seven
DBPs
and
lifetime
unit
cancer
risk
factors
for
four
of
those
seven
DBPs,
based
primarily
on
animal
toxicological
data.
As
with
all
risk
evaluations
based
on
animal
toxicological
studies,
several
extrapolations
were
required
to
establish
lifetime
unit
cancer
risks
for
4A
more
recent
draft
final
version
of
the
EPA
Guidelines
for
Carcinogen
Risk
Assessment
was
made
available
for
public
review
and
comment
on
March
3,
2003
(
68
FR
10012)
(
USEPA
2003q).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
25
July
2003
humans
(
e.
g.,
from
high
to
low
doses,
from
nonhuman
species
to
humans,
and
for
DBPs,
from
gavage
to
ingestion
of
water).
Exhibit
5.7
provides
a
summary
of
the
cancer
risk
assessments
for
those
seven
DBPs
as
presented
on
the
IRIS
database.

The
lifetime
unit
risk
factors
shown
in
Exhibit
5.7
for
bromoform,
bromodichloromethane,
and
dibromochloromethane
were
included
in
the
cancer
risk
assessment
and
benefit
analyses
performed
by
EPA
in
support
of
the
Stage
1
DBPR
promulgated
in
1998.
Since
the
Stage
1
DBPR,
EPA
has
updated
the
quantitative
risk
assessments
for
these
three
DBPs
in
order
to
reflect
the
methodology
proposed
in
the
1996/
1999
draft
cancer
guidelines
(
USEPA
1996e
and
1999d)
resulting
in
revisions
to
the
unit
risk
factors4.
Also,
a
new
study
of
dichloroacetic
acid
tumorigenicity
in
mice
by
DeAngelo
et
al.
(
1999)
examined
doses
lower
than
those
used
in
previously
published
studies
and
has
been
judged
by
EPA
to
be
suitable
for
quantification
of
risk,
also
using
the
newer
methodology.

Although
these
updated
cancer
risk
assessments
do
not
yet
appear
on
the
IRIS
database,
EPA
is
completing
new
Criteria
Documents
for
bromoform,
bromodichloromethane,
dibromochloromethane,
and
dichloroacetic
acid
that
support
the
Stage
2
proposal,
and
those
documents
provide
details
on
the
animal
toxicological
data
used
to
derive
the
new
cancer
unit
risk
factors
for
these
DBPs.

The
updated
cancer
risk
factors
for
these
four
DBPs
are
presented
in
Exhibit
5.8,
and
these
factors
have
been
used
to
estimate
the
pre­
Stage
2
baseline
cancer
cases
implied
by
these
values,
the
pre­
Stage
1
concentrations
of
these
compounds,
the
changes
in
those
concentrations
following
Stage
1,
and
the
estimated
number
of
people
exposed.
As
described
in
the
Criteria
Documents,
cancer
risk
values
were
developed
by
fitting
the
key
animal
toxicological
data
to
linearized
multistage
models
using
a
Maximum
Likelihood
Estimation
(
MLE)
methods.
The
MLE
method
provides
parameter
estimates
for
the
model
that
fit
the
underlying
data.
Two
risk
factors
are
then
derived
from
the
dose­
response
curve
that
is
fit
to
the
data.

The
first
risk
factor
is
based
on
the
estimated
dose
that
the
model
predicts
will
result
in
a
carcinogenic
response
in
10
percent
of
the
subjects
(
referred
to
as
the
Effective
Dose
for
10%
response,
or
ED
10).
(
Note:
This
unit
risk
factor
is
also
sometime
referred
to
as
the
MLE
estimate
since
it
reflects
the
dose
taken
directly
from
the
curve
fit
by
the
MLE
method.)

The
second
risk
factor,
which
reflects
a
more
conservative
estimate
of
the
risk
(
and
which
corresponds
more
directly
to
the
lifetime
unit
risks
shown
in
Exhibit
5.7
from
the
IRIS
database),
are
based
on
the
lower
95%
confidence
bound
on
the
dose
that
the
model
predicts
will
result
in
a
carcinogenic
response
in
10
percent
of
the
subjects
(
referred
to
as
the
Lower
Bound
on
the
Effective
Dose
for
10%
response,
or
LED
10).

In
both
cases,
EPA
derives
a
slope
factor
from
those
unit
risk
values
assuming
low­
dose
linearity
and
no
threshold
to
estimate
risk.
As
shown
in
Exhibit
5.8,
the
baseline
number
of
annual
Pre­
Stage
cancer
cases
calculated
from
the
risk
factors
for
these
four
DBPs
are
37
cases
for
the
ED
10
risk
factors
and
87
cases
for
the
ED
10
risk
factors.
Assuming
that
DBP
risk
reductions
for
Stage
2
for
the
entire
population
average
4.2%
corresponding
to
the
reduction
in
average
TTHM
levels
(
see
Section
5.4.2),
Stage
2
cancer
cases
avoided
based
on
the
toxicological
data
range
from
1.7
to
4.0
cases
per
year.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
26
July
2003
Exhibit
5.7
Summary
of
EPA's
Cancer
Risk
Assessments
for
Specific
DBPs
Chemical
EPA's
Human
Carcinogen
Assessment
Lifetime
Unit
Cancer
Risk
Factor
Date
and
Source
Bromoform
Probable1
2.30
X
10­
7
(
:
g/
L)­
1
1993
(
IRIS)

Bromodichloromethane
Probable1
1.8
X
10­
6
(
:
g/
L)­
1
1993
(
IRIS)

Chloroform
Probable1
Likely
human
carcinogen
under
high­
exposure
conditions
that
lead
to
cytotoxicity
and
regenerative
hyperplasia
in
susceptible
tissues.
Not
likely
without
cytotoxicity
and
cell
regeneration.
2
Not
Available
2001
(
IRIS)

Dibromochloromethane
Possible1
2.4
X
10­
6
(
:
g/
L)­
1
1992
(
IRIS)

Dichloroacetic
Acid
Probable1
Not
Available
1996
(
IRIS)

Trichloroacetic
Acid
Possible1
Not
Available
1996
(
IRIS)

Bromate
Probable1
Likely
to
be
carcinogenic
via
oral
route
of
exposure2
2
X
10­
5
(
:
g/
L)­
1
2001
(
IRIS)

1
EPA's
Human
Carcinogen
Assessment
reported,
as
classified
under
EPA
1986
Cancer
Risk
Assessment
Guidelines
(
USEPA
1986).
2
EPA's
Human
Carcinogen
Assessment
reported,
as
classified
under
EPA
1996
and
1999
Proposed
Cancer
Risk
Assessment
Guidelines
(
USEPA
1996e
and
1999d).

There
are
several
limitations
that
must
be
considered
in
conjunction
with
the
interpretation
and
use
of
these
cancer
risk
estimates.
There
are
only
seven
DBPs
(
those
shown
in
Exhibit
5.7)
for
which
EPA
has
determined
that
there
are
adequate
toxicology
studies
available
to
support
an
assessment
of
their
potential
for
carcinogenicity
in
humans.
As
discussed
elsewhere
in
this
document,
there
is
a
large
number
of
DBPs
present
in
drinking
water
that
has
been
disinfected,
including
many
substances
that
have
not
yet
been
specifically
identified.
It
must
also
be
recognized
that
these
highly
controlled
toxicology
studies
involve
exposure
to
each
respective
DBP
separately,
while
actual
exposure
to
humans
is
to
a
mixture
that
includes
many
other
DBPs
in
a
wide
array
of
relative
proportions.
Lastly,
it
must
be
recognized
that
these
toxicology
studies
limit
exposure
to
the
oral
route
only,
whereas
humans
are
generally
exposed
to
DBPs
in
drinking
water
not
only
by
the
oral
route
but
by
dermal
exposure
and
inhalation
as
well.

There
have
been
other
studies
since
the
promulgation
of
the
Stage
1
DBPR
that
assess
the
cancer
risks
of
DBPs.
Also,
EPA
has
several
ongoing
studies
in
addition
to
a
collaboration
with
the
National
Toxicology
Program
of
the
National
Institute
of
Environmental
Health
Sciences.
More
information
on
EPA's
toxicology
research
program
can
be
found
at
http://
www.
epa.
gov/
nheerl.

Another
significant
advancement
beyond
the
Stage
1
DBPR
was
the
evaluation
of
the
chloroform
tumorigenicity
data
on
the
basis
of
its
nonlinear
mode
of
action
following
the
draft
1999
proposed
Guidelines
for
Carcinogen
Risk
Assessment
(
USEPA
1999d).
The
new
chloroform
assessment
became
available
on
IRIS
in
October,
2001.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
27
July
2003
Lifetime
unit
risk
(
cases/
person)/
(
mg/
kg­
day)
Lifetime
unit
risk
conc.
(
cases/
person)/
(
ug/
L)
Annual
unit
risk
conc.
(
cases/
person)/
(
ug/
L)
Baseline
Cases
Lifetime
unit
risk
(
cases/
person)/
(
mg/
kg­
day)
Lifetime
unit
risk
conc.
(
cases/
person)/
(
ug/
L)
Annual
unit
risk
conc.
(
cases/
person)/
(
ug/
L)
Baseline
Cases
A
B
C
D=
C*(
1/
1000)*
(
2L/
day)*(
1/
70
kD)
E=
D/
70
years
F=
A*
B*
E
G
H=
G*(
1/
1000)*
(
2L/
day)*(
1/
70
kD)
I=
H/
70
years
J=
A*
B*
I
BDCM
SW
8.20
160,685,640
2.2E­
02
6.29E­
07
8.98E­
09
11.8
3.4E­
02
9.71E­
07
1.39E­
08
18.3
GW
2.92
93,792,948
2.2E­
02
6.29E­
07
8.98E­
09
2.5
3.4E­
02
9.71E­
07
1.39E­
08
3.8
Total
254,478,588
14.3
22.1
Bromoform
SW
2.69
160,685,640
3.4E­
03
9.71E­
08
1.39E­
09
0.6
4.5E­
03
1.29E­
07
1.84E­
09
0.8
GW
1.94
93,792,948
3.4E­
03
9.71E­
08
1.39E­
09
0.3
4.5E­
03
1.29E­
07
1.84E­
09
0.3
Total
254,478,588
0.9
1.1
DBCM
SW
5.50
160,685,640
1.7E­
02
4.86E­
07
6.94E­
09
6.1
4.0E­
02
1.14E­
06
1.63E­
08
14.4
GW
2.81
93,792,948
1.7E­
02
4.86E­
07
6.94E­
09
1.8
4.0E­
02
1.14E­
06
1.63E­
08
4.3
Total
254,478,588
8.0
18.7
DCAA
SW
11.98
160,685,640
1.4E­
02
4.14E­
07
5.92E­
09
11.4
4.8E­
02
1.36E­
06
1.94E­
08
37.4
GW
4.28
93,792,948
1.4E­
02
4.14E­
07
5.92E­
09
2.4
4.8E­
02
1.36E­
06
1.94E­
08
7.8
Total
254,478,588
13.8
45.2
Grand
Total
36.9
87.2
A)
SW:
SWAT
DBP
Summary
Statistics,
Run
300
(
Pre­
Stage
2)

B)
Stage
2
Population
Baseline:
Column
K
from
Exhibit
3.5,
CWS
population
only
C)
The
slope
based
on
the
ED10
(
effective
dose
for
10%
response)
based
on
the
Maximum
Likelihood
Estimation
(
MLE)
method
G)
The
slope
based
on
the
LED10
(
lower
95%
confidence
bound
on
effective
dose
for
10%
response)
based
on
the
Maximum
Likelihood
Estimation
(
MLE)
method
Exhibit
5.8
Cancer
Risk
Factors
and
Pre­
Stage
2
Baseline
Cancer
Case
Estimates
for
Bromoform,
BDCM,
DBCM
and
DCAA
Derivation
of
cases
using
ED10
Derivation
of
cases
using
LED10
GW:
Pre­
Stage
1
data
from
ICR.
Pre­
Stage
2
value
estimated
by
applying
%
reduction
in
SW
values
from
SWAT
(
see
sheet
"
SWAT
DBP
summary")
to
Pre­
Stage
1
value,
adjusting
by
the
ratio
of
%
GW
plants
changing
technology
to
%
surface
water
plants
changing
technology
(
Pre­
S2
GW
=
Pre­
S1
GW
*
SW
reduction
(%
GW
changers/%
SW
changers).
Source
Water
Type
Sources:
Population
Pre­
Stage
2
Conc
(
ug/
L),
Mean
of
Plant
Means,
DS
Average
Exhibit
5.8
Quantification
of
Cancer
Risk,
Pre­
Stage
2
Baseline
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
28
July
2003
Other
byproducts
with
carcinogenic
potential
3­
Chloro­
4­(
dichloromethyl)­
5­
hydroxy­
2(
5H)­
furanone
(
MX)
is
a
byproduct
of
chlorination
that
is
typically
found
at
very
low
concentrations
(
approximately
<
0.000067
mg/
L)
in
drinking
water.
The
information
available
on
MX
was
recently
compiled
in
the
Quantitative
Cancer
Assessment
for
MX
and
chlorohydroxyfuranones
(
USEPA
2000r).
Overall,
the
weight­
of­
evidence
indicates
that
MX
is
a
directacting
genotoxicant
in
mammals,
with
the
ability
to
induce
tumors
in
multiple
sites.
The
primary
sites
for
tumor
formation
are
the
thyroid
and
liver.

N­
nitrosodimethylamine
(
NDMA),
as
described
on
IRIS
(
1991),
is
a
probable
human
carcinogen
based
on
health
effects
data.
Risk
assessments
have
estimated
that
the
10­
6
lifetime
cancer
risk
level
is
0.000007
mg/
L
based
on
induction
of
tumors
at
multiple
sites.
Recent
studies
have
produced
new
information
on
the
occurrence
and
mechanism
of
formation
of
NDMA
but
there
is
not
enough
information
at
this
time
to
draw
conclusions.
More
research
is
underway
to
determine
the
mechanism
by
which
NDMA
is
formed
in
drinking
water,
and
the
extent
of
its
occurrence
in
chloraminated
systems.

Other
toxicological
effects
The
Agency
has
modified
the
reference
dose
(
RfD)
values
of
the
chlorinated
acetic
acids
since
the
Stage
1
DBPR.
Under
the
Stage
1
DBPR
there
was
no
established
RfD
for
monochloroacetic
acid
(
MCAA).
Data
from
a
drinking
water
exposure
study
of
MCAA
in
rats
by
DeAngelo
et
al.
(
1997)
were
used
to
establish
an
RfD
of
0.004
mg/
kg/
day
based
on
observed
increases
in
spleen
weights.
Data
from
DeAngelo
et
al.
(
1997)
were
also
used
to
calculate
a
new
RfD
of
0.03
mg/
kg/
day
for
trichloroacetic
acid
based
on
observed
effects
on
body
weight
and
liver
effects.

WHO
review
of
toxicology
literature
(
2000)

The
IPCS
report
on
Disinfectants
and
Disinfection
Byproducts
(
WHO
2000)
emphasizes
that
the
bulk
of
the
toxicology
data
focuses
primarily
on
carcinogenesis.
The
Task
Group
found
BDCM
to
be
of
particular
interest
because
it
produces
tumors
in
both
rats
and
mice
at
several
sites.
Although
the
HAAs
appear
to
be
without
significant
genotoxic
activity,
the
brominated
HAAs
appear
to
induce
oxidative
damage
to
DNA,
leading
to
tumor
formation.

5.2.2.3
Conclusions
EPA
concludes
that
the
epidemiological
and
toxicological
studies
support
a
weight
of
evidence
conclusion
that
there
may
be
a
weak
association
between
DBPs
and
cancer.
The
following
are
the
key
factors
used
to
support
EPA's
weight­
of­
evidence
conclusion:

°
There
is
some
evidence
from
animal
studies
for
the
carcinogenicity
of
individual
DBPs
included
in
this
rule.
Exhibit
5.7
summarizes
the
Agency
findings
on
the
carcinogenicity
of
7
DBPs.
They
have
all
been
characterized
on
IRIS
as
either
"
possible"
or
"
probable"
carcinogens
under
EPA's
1986
guidelines,
and
in
some
cases
also
as
"
likely"
carcinogens
under
EPA's
1996/
1999
guidelines.
One
of
these
(
chloroform)
has
been
evaluated
based
on
its
mode
of
action,
with
the
finding
that
it
is
likely
to
be
carcinogenic
only
under
highexposure
conditions
that
lead
to
cytotoxicity
and
regenerative
hyperplasia.

°
PAR
analysis
of
the
epidemiological
data
from
five
well­
designed
studies
link
exposure
to
chlorinated
water
with
an
increased
risk
for
bladder
cancer
in
some
population
subgroups.
Associations
of
chlorinated
water
to
cancer
of
the
colon,
rectum,
and
kidney
were
found
in
some
cases
but
the
data
are
less
robust
than
the
data
for
bladder
cancer.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
29
July
2003
°
The
epidemiological
data
cannot
link
specific
DBPs
with
cancer
risk
because
of
difficulties
in
characterizing
the
exposure.
Exposure
is
some
studies
was
monitored
purely
in
terms
of
chlorinated
water
which
contains
a
mixture
of
DBPs,
some
of
which
have
not
yet
been
identified,
as
well
as
a
variety
of
other
drinking
water
contaminants.
In
other
studies
the
DBP
exposure
was
monitored
in
terms
of
trihalomethane
concentrations
(
a
variable
mixture
of
four
individual
DBPs).
Thus,
the
Agency
must
rely
on
both
the
bioassays
for
individual
chemicals
as
well
as
the
epidemiology
data
in
making
a
weight­
of­
evidence
determination.

An
ILSI
Expert
Panel
Recommendations
for
Toxicological
Testing
(
ILSI
and
RSI
1998)
recommended
that
DBP
risk
cannot
be
assessed
by
single­
chemical
testing
approaches
alone.
The
report
suggested
the
use
of
modern
approaches
(
e.
g.,
studies
relating
chemical
structure
to
toxicity,
application
of
molecular
biology
techniques,
studies
of
mechanism
of
action),
the
use
of
a
3­
tiered
testing
approach
(
i.
e.,
in­
vitro
tests;
short­
term
screening
tests
or
90
day
animal
studies;
long­
term
chronic
bioassays),
and
a
focus
on
three
scenarios:
(
1)
defined
(
simple)
mixtures
of
less
than
10
DBPs;
(
2)
whole
mixtures
produced
by
simulating
disinfection
scenarios;
and
(
3)
real
drinking
water
samples
or
their
extracts.

EPA
is
devoting
significant
resources
to
DBP
research
in
the
coming
years.
The
Agency
has
a
research
program
that
continues
to
examine
the
relationship
between
exposure
to
DBPs
and
carcinogenicity.
EPA
is
also
supporting
several
studies
using
improved
study
design
to
provide
better
information
for
characterizing
potential
risks.
This
research
is
intended
to
yield
more
precise
doseresponse
relationships
to
support
a
quantitative
risk
assessment.

Additional
data
needs
include
information
on
modes
of
action,
the
reasons
for
inconsistencies
in
findings
between
men
and
women
and
inconsistencies
across
studies
in
the
role
of
smoking,
and
carcinogenicity
testing
for
selected
brominated
and
chlorinated
DBPs
administered
in
drinking
water.
New
studies
are
under
way
or
planned
that
would
provide
screening­
level
data
on
the
carcinogenicity,
neurotoxicity,
and
immunotoxicity
of
several
DBPs
(
reproductive
toxicity
research
is
discussed
elsewhere).

5.3
Exposure
Assessment
5.3.1
Population
Exposed
Because
DBPs
are
formed
when
disinfectants
combine
with
organic
compounds,
the
population
at
risk
is
identified
as
the
population
served
by
drinking
water
systems
that
disinfect.
A
very
large
portion
of
the
United
States
population
 
approximately
90
percent
 
is
potentially
exposed
to
DBPs
in
disinfected
drinking
water.
Exhibit
5.9
contains
EPA's
estimates
of
the
population
potentially
exposed
to
DBPs.
Nearly
255
million
people
in
the
United
States
are
served
by
community
water
systems
(
CWSs)
that
apply
a
disinfectant
to
water
to
protect
against
microbial
contaminants.
In
addition
to
those
served
by
CWSs,
just
over
3
million
individuals
are
served
regularly
by
nontransient
noncommunity
water
systems
(
NTNCWSs).
(
See
exhibit
3.5
for
population
served
by
different
system
types.)

In
general,
the
total
population
exposed
to
disinfected
water
can
potentially
benefit
from
reduction
in
average
DBP
concentration
as
a
result
of
the
Stage
2
DBPR.
The
number
of
people
who
may
potentially
benefit
from
the
reduction
in
peak
DBP
exposures,
however,
is
less
than
the
total
and
is
very
difficult
to
estimate.
Two
obvious
population
subgroups
of
concern
are
women
of
child­
bearing
age
and
developing
fetuses.
Women
of
child­
bearing
age
are
generally
considered
to
be
those
in
the
age
range
of
15
to
45.
The
estimated
United
States
population
for
the
year
2000
is
281
million,
of
which
approximately
64
million
(
23
percent)
are
females
between
the
ages
of
15
and
45.
As
noted
earlier,
it
is
estimated
that
approximately
90
percent
of
the
population
is
served
by
PWSs
that
disinfect,
so
it
can
be
estimated
that
about
58
million
women
of
child­
bearing
age
are
served
by
these
water
supplies.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
30
July
2003
Exhibit
5.9
Estimated
Population
Exposed
to
DBPs
in
Drinking
Water
System
Size
(
Population
Served)
Population
Served
by
Disinfecting
Systems
Percent
of
Total
Population
Served
by
Disinfecting
System
<
100
489,832
0.19%

101­
500
3,182,976
1.25%

501­
1,000
3,365,004
1.32%

1,001­
3,300
11,243,463
4.42%

3,301­
10,000
19,330,300
7.60%

10,001­
50,000
50,987,237
20.04%

50,001­
100,000
25,615,626
10.07%

100,001­
1,000,000
84,378,040
33.16%

>
1,000,000
55,886,070
21.96%

Total
254,478,588
100.00%
Source:
Derived
from
the
Stage
2
DBPR
population
baseline
for
surface
and
disinfecting
ground
water
CWSs
in
Exhibit
3.5.

Currently,
there
are
approximately
4
million
live
births
each
year.
Again,
using
the
factors
above,
it
can
roughly
be
estimated
that
more
than
3.5
million
infants
are
born
each
year
to
a
mother
served
by
a
disinfecting
water
supply.

5.3.2
Routes
of
Exposure
The
predominant
route
of
exposure
to
DBPs
is
from
the
direct
ingestion
of
drinking
water
and
from
the
consumption
of
food
that
has
been
cleaned,
processed
and/
or
prepared
with
drinking
water.
EPA
has
recently
examined
drinking
water
consumption
data
from
the
1994
 
1996
USDA
Continuing
Survey
of
Food
Intakes
by
Individuals
(
USDA
1997)
and
determined
that
mean
daily
drinking
water
consumption
across
all
ages,
sexes,
and
regions
in
the
US
ranges
from
0.9
to
1.2
liters
per
day,
with
an
upper
95th
percentile
range
of
2.5
to
2.9
liters
per
day
(
USEPA
2000s).

People
also
can
be
exposed
to
some
contaminants
in
drinking
water
by
routes
of
exposure
other
than
ingestion,
particularly
by
inhalation
and
dermal
contact
from
showering,
bathing,
washing
dishes,
washing
clothes,
or
swimming.
The
remainder
of
this
section
focuses
on
routes
of
exposure
other
than
direct
ingestion.

Some
studies
have
found
that
exposure
due
to
inhalation
and
skin
absorption
during
showering
may
actually
be
higher
than
ingestion­
related
exposure
(
Kuo
et
al.
1998;
Backer
et
al.
2000).
Kuo
et
al.
did
not
determine
actual
exposure,
but
modeled
exposure
based
on
chloroform
concentrations
in
three
cities
in
Taiwan.
In
Taipei,
where
chloroform
concentrations
are
19
µ
g/
L,
exposure
resulting
from
a
10­
minute
shower
was
14
nanograms
(
ng)
for
ingestion,
15
ng
for
inhalation,
and
9
ng
for
skin
absorption.
In
Kaohsiung,
which
had
chloroform
concentrations
of
60
µ
g/
L,
the
total
exposure
was
103
ng.
For
a
20­
minute
shower,
inhalation
exposure
was
expected
to
more
than
double
due
to
changes
in
the
diffusion
of
volatile
substances
through
air
and
water
over
time.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
31
July
2003
The
route
of
exposure
may
depend
on
the
volatility
of
the
DBP
in
question
(
Weisel
et
al.
1999);
THMs
are
more
volatile
than
HAAs
and
exist
in
the
air
at
background
levels.
Weisel
et
al.
(
1999)
found
a
significant
correlation
between
breath
concentrations
of
chloroform
after
showering
and
water
concentration.
They
were
unable
to
show
a
relationship
between
breath
concentration
and
overall
exposure
due
to
variability
in
when
breath
samples
were
taken
and
the
fast
rate
of
THM
metabolization.
However,
almost
all
breath
concentrations,
except
for
chloroform,
were
below
the
detection
limit,
most
likely
due
to
low
water
concentrations.
Weisel
et
al.
also
found
a
link
between
urinary
trichloroacetic
acid
(
TCAA)
excretion
rates
and
TCAA
exposure,
calculated
as
the
water's
TCAA
concentration
multiplied
by
the
volume
of
water
consumed
by
volunteers
over
a
48
hour
period,
adjusted
for
home
filters
and
boiling.
TCAA
exposure
generally
fell
below
10
ng
over
48
hours,
but
ranged
up
to
50
ng.

Exposure
appears
to
differ
between
males
and
females,
with
males
absorbing
more
chloroform
than
females
(
Corley
et
al.
2000).
Most
significantly,
dermal
absorption,
especially
in
women,
is
significantly
affected
by
water
temperature,
since
at
higher
temperatures
blood
flow
to
the
skin
is
higher,
allowing
the
blood
to
take
in
more
DBPs
(
Corley
et
al.
2000;
Gordon
et
al.
1998).
Measuring
the
chloroform
breath
concentrations
of
test
subjects
immersed
in
bath
water
at
concentrations
of
~
90
µ
g/
L
at
35
°
C
for
30
minutes,
Corley
et
al.
calculated
that
men
would
absorb
42
µ
g
and
women
would
absorb
12
µ
g
of
chloroform.
These
exposures
were
based
on
models
taking
blood
flow
to
the
skin
and
skin
permeability
into
consideration.
At
40
°
C,
this
increased
to
44
µ
g
for
men
and
40
µ
g/
L
for
women.
(
This
includes
chloroform
exhaled,
metabolized,
and
maintained
in
the
body.)
At
30
°
C,
on
the
other
hand,
most
subjects
had
chloroform
breath
levels
below
detection
limits.
For
comparison,
if
2
liters
of
water
with
the
same
chloroform
concentration
were
ingested,
the
exposure
from
ingestion
would
range
from
79
to
194
µ
g.

5.3.3
Special
Exposure
Issues
for
Pregnant
Women
Because
of
the
potential
reproductive
and
developmental
effects
of
DBPs,
pregnant
women
represent
a
subset
of
the
population
of
special
concern
with
respect
to
the
ingestion
of
DBPs
in
drinking
water.
Because
the
kidneys
work
harder
in
pregnancy
to
expel
waste
material
from
the
body,
drinking
an
adequate
volume
of
water
is
extremely
important.
Pregnant
women
can
become
dehydrated
easily,
which
can
lead
to
fetotoxicity.
Thus,
women
who
are
pregnant
are
encouraged
to
drink
a
minimum
of
eight
8­
ounce
glasses
of
water
a
day
to
ensure
proper
hydration
(
March
of
Dimes
1999).

Pregnant
women
cannot
avoid
tap
water
completely.
As
discussed
in
the
previous
section,
DBP
exposure
can
occur
through
inhalation
and
dermal
contact
from
a
variety
of
activities,
including
showering
and
bathing.
Reducing
exposure
by
switching
to
bottled
water
is
not
necessarily
safer
than
tap
water
and
is
comparatively
more
expensive.
Purchasing
bottled
water,
even
if
safer,
may
not
be
an
option
for
economically
disadvantaged
pregnant
women.
Because
pregnant
women
cannot
avoid
exposure
to
tap
water,
the
expected
reduction
in
DBP
exposure
that
is
estimated
for
the
proposed
Stage
2
DBPR
is
especially
important
in
providing
public
health
protection
to
pregnant
women
and
their
developing
children.

5.4
Occurrence
and
Exposure
Reduction
It
is
well
recognized
that
DBP
concentrations
can
be
highly
variable
throughout
a
distribution
system
and
over
time
at
the
same
location
in
a
distribution
system.
The
Stage
1
DBPR
requires
systems
to
meet
the
MCL
standards
and
associated
compliance
monitoring
requirements
as
running
annual
averages
(
RAAs)
of
80
:
g/
L
for
TTHM
and
60
:
g/
L
for
HAA5.
It
is
possible
that
some
systems
can
achieve
the
average
concentration
targeted
by
the
Stage
1
DBPR,
and
yet
still
have
some
locations
in
the
distribution
system
where
average
DBP
levels
are
far
in
excess
of
the
system­
wide
target
at
some,
or
even
5
These
MCL
requirements
are
for
Stage
2B,
which
requires
that
compliance
be
met
at
revised
sampling
locations
identified
during
the
Initial
Distribution
System
Evaluation
(
IDSE).
Systems
must
also
meet
transitional
MCLs
of
120
:
g/
L
for
TTHM
and
100
:
g/
L
for
HAA5
calculated
as
the
LRAA
based
on
Stage
1
DBPR
monitoring
sites
under
Stage
2A
(
See
Chapter
1
for
a
complete
description
of
the
Stage
2A
and
2B
requirements).
The
exposure
reduction,
as
a
result
of
treatment
changes
to
meet
Stage
2B,
is
expected
to
be
much
larger
than
the
reduction
under
Stage
2A;
therefore,
exposure
reduction
resulting
from
Stage
2A
transitional
MCL
requirements
is
not
evaluated
in
this
section.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
32
July
2003
at
all,
times.
The
peak
exposures
resulting
from
these
high
concentrations
are
of
particular
concern
in
regard
to
potential
adverse
reproductive
and
developmental
health
effects.
Exposure
at
locations
having
repeatedly
high
sample
concentrations
are
of
particular
concern
for
pregnant
women,
who
are
encouraged
to
drink
more
water
than
the
average
person
and
who
may
be
especially
sensitive
to
the
potential
effects
of
DBPs,
as
explained
in
section
5.3.3.

Under
the
Stage
2
DBPR
preferred
regulatory
alternative,
TTHM
and
HAA5
MCLs
will
remain
at
80
µ
g/
L
and
60
µ
g/
L,
respectively,
but
compliance
will
be
based
on
the
locational
running
annual
average
(
LRAA)
5.
Exhibits
1.3
and
4.1
illustrate
how
the
LRAA
and
RAA
are
calculated.
This
revised
compliance
calculation
requirement
will
reduce
average
DBP
levels
in
the
entire
distribution
system
as
well
as
avoid
having
average
DBP
levels
at
any
sampling
location
exceed
80
and
60
:
g/
L
for
TTHM
and
HAA5,
respectively.
Systems
are
required
to
meet
the
Stage
2
DBPR
MCLs
at
revised
sampling
locations
that
will
be
identified
through
the
IDSE
to
further
ensure
that
peak
occurrence
events
are
captured
and
controlled.

The
Stage
2
DBPR
Preferred
Regulatory
Alternative
is
expected
to
yield
health
benefits
by
achieving
the
following
in
those
systems
subject
to
the
rule:

1)
Reducing
exposures
to
single
peak
occurrences
exceeding
80/
60
:
g/
L.

2)
Reducing
exposures
at
individual
distribution
system
locations
that
consistently
exceed
80/
60
:
g/
L.

Both
types
of
peak
exposure
reductions,
based
on
analysis
of
ICR
data,
are
discussed
in
section
5.4.1.
Analysis
of
exposure
reduction
due
to
reductions
in
average
DBP
levels
is
presented
in
section
5.4.2.
As
discussed
in
Section
3.7,
changes
in
average
DBP
levels
(
as
a
result
of
technology
changes
for
the
Stage
1
and
Stage
2
DBPRs)
are
characterized
using
SWAT.
The
ICR
data
were
considered
more
reliable
than
the
SWAT
data
for
predicting
peak
DBP
concentrations
and,
therefore,
were
used
for
estimating
reductions
in
peaks
resulting
from
the
Stage
2
DBPR.

5.4.1
Occurrence
and
Exposure
Reduction:
Peak
DBPs
For
the
purposes
of
this
section,
a
"
peak"
DBP
occurrence
is
defined
as
any
individual
occurrence
of
a
measured
DBP
level
greater
than
a
specified
threshold
concentration.
The
level
does
not
have
to
be
sustained
over
any
period
of
time
to
be
considered
a
peak
occurrence,
and
it
can
be
a
measurement
taken
at
any
time
in
the
year.
Since
the
developmental
and
reproductive
health
data
described
in
section
5.2
does
not
conclusively
identify
the
peak
level
of
concern,
analyses
in
this
section
focus
on
several
possible
peak
TTHM
and
HAA5
concentrations
(
or
TTHM/
HAA5
study
levels).

This
section
uses
ICR
data
to
show
how
peak
DBP
concentrations
are
reduced
by
the
Stage
2
DBPR.
Section
5.4.1.1
describes
the
methodology
for
evaluating
ICR
data
and
generating
subsets
of
Stage
1­
and
Stage
2­
compliant
plants.
ICR
TTHM
and
HAA5
data
for
Stage
1­
and
Stage
2­
compliant
plants
are
used
in
sections
5.4.1.2
and
5.4.1.3
to
characterize
changes
in
peak
DBP
occurrence.
6
Blended
plants
have
only
3
distribution
system
sampling
locations
 
DSE,
AVG,
and
DS
Maximum.

7
Blended,
mixed,
and
purchased
plants
are
not
included
in
the
separate
analyses
of
surface
and
ground
water
plants
performed
to
estimate
the
occurrence
of
significant
excursions
in
Appendix
G,
section
G.
5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
33
July
2003
Results
in
this
section
will
show
that
the
Stage
2
DBPR
is
predicted
to
be
very
effective
at
reducing
occurrence
of
DBP
peaks.
For
example,
as
shown
in
Exhibit
5.13
at
the
end
of
this
section,
the
percent
of
sampling
locations
with
peaks
is
expected
to
drop
from
17.5
to
7.1
as
a
results
of
the
Stage
1
DBPR
and
from
7.1
to
2.2
as
a
results
of
the
Stage
2
DBPR
for
a
TTHM
study
level
of
80
:
g/
L.
As
noted
previously,
EPA
believes
that
through
the
IDSE,
the
Stage
2
DBPR
will
better
identify
distribution
system
locations
having
these
high
peaks.
Therefore,
the
reduction
in
peak
occurrence
will
be
greater
than
described
in
this
section
if
the
IDSE
identifies
sampling
locations
with
higher
peak
observations
than
those
seen
under
the
ICR
(
this
factor
is
included
in
the
consideration
of
uncertainties
discussed
in
section
5.7).

5.4.1.1
Methodology
for
Evaluating
ICR
Data
Evaluation
of
ICR
TTHM
and
HAA5
data
in
this
section
is
consistent
with
the
methodology
used
in
section
3.7
and
in
the
Stage
2
DBPR
Occurrence
Document
(
USEPA
2003l).
An
initial
plant
screening
was
performed
to
ensure
that
the
plants
evaluated
had
adequate
distribution
system
data.
The
screened
plants
were
then
evaluated
for
compliance
with
the
Stage
1
and
Stage
2
DBPRs.
The
Stage
2
DBPR
Occurrence
Document
provides
additional
description
of
the
ICR
data
set,
additional
details
regarding
the
plant
screening
and
compliance
assessment,
and
the
Access
®
query
language
used
to
extract
the
data
from
the
ICR
Aux
1
database
(
USEPA
2000f).

Description
of
ICR
Data
The
analysis
of
ICR
data
was
limited
to
the
last
four
quarters
of
the
ICR
collection
period
(
January
to
December
1998).
Data
for
a
full
year
(
four
quarters)
were
evaluated
so
that
the
analysis
captured
seasonal
variations
in
TTHM
and
HAA5
levels.
The
last
four
quarters
were
evaluated
because
using
all
6
quarters
of
data
could
skew
results
(
data
from
the
last
6
months
of
the
calender
year
would
be
included
twice).

Four
distribution
system
sampling
locations
were
evaluated:
DSE,
AVG1,
AVG2,
and
DS
Maximum6.
See
Chapter
3,
section
3.7.1,
for
a
description
of
these
sampling
locations.

In
this
section,
analyses
of
all
plants
includes
"
blended,"
"
mixed,"
and
"
purchased"
plant­
types
from
the
ICR
database7.
These
plant
types
make
up
a
small
portion
(
less
than
10
percent)
of
the
total
 
most
ICR
plants
are
categorized
as
either
surface
or
ground
water
plants.

Initial
Plant
Screening
All
ICR
plants
(
there
are
approximately
500
plants
in
the
ICR
database)
were
screened
to
ensure
that
at
least
3
of
4
quarters
have
TTHM
and
HAA5
data
for
at
least
3
of
4
distribution
system
locations.
This
screening
was
done
to
minimize
biases
in
RAA
and
LRAA
calculations
(
e.
g.,
LRAAs
could
be
skewed
if
data
from
multiple
quarters
is
missing).
The
results
of
the
screening
analysis
are
presented
in
column
2
of
Exhibit
5.10.
Note
that
the
total
number
of
plants
that
meet
the
minimum
screening
criteria
(
311
plants)
represents
more
than
60
percent
of
all
large
plants
that
participated
in
the
ICR
data
collection
effort.
Exhibit
5.10
also
shows
the
number
of
plant
locations
and
paired
TTHM/
HAA5
observations
that
are
included
in
the
screened
data
set.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
34
July
2003
While
the
screening
process
is
intended
to
reduce
biases
in
data
analysis,
EPA
recognizes
that
biases
in
the
RAA
and
LRAA
calculations
may
still
exist.
First,
missing
data
points
from
locations
may
skew
the
quarterly
average.
For
example,
a
plant
with
less
than
3
of
4
quarters
of
data
for
the
maximum
residence
time
location
(
but
having
at
least
3
of
4
quarters
of
data
for
all
other
locations,
allowing
it
to
be
included
in
the
analysis)
would
probably
have
an
RAA
that
is
skewed
low.
Second,
missing
quarterly
data
could
skew
the
yearly
average.
For
example,
because
higher
DBP
levels
are
typically
seen
during
the
warmest
months,
missing
data
in
the
warmest
quarter
may
lower
the
annual
average
at
that
location.
The
screening
criteria
described
above
were
selected
to
strike
a
balance
between
minimizing
biases
in
RAA
and
LRAA
calculations
and
maximizing
the
number
of
plants
evaluated
(
60
percent
of
all
ICR
plants).

Evaluation
of
Stage
1
and
Stage
2
DBPR
Compliance
The
ICR
data
set
represents
pre­
Stage
1
conditions;
that
is,
before
plants
have
made
changes
to
meet
Stage
1
or
Stage
2
DBPR
requirements.
In
order
to
assess
changes
in
peak
DBP
occurrence
as
a
result
of
the
Stage
2
DBPR,
the
analysis
in
this
section
uses
the
subsets
of
ICR
plants
that
are
already
in
compliance
with
Stage
1
to
characterize
pre­
Stage
2
peak
occurrence,
and
those
already
in
compliance
with
both
Stage
1
and
2
to
characterize
post­
Stage
2
peak
occurrence.
This
assumes
that
the
DBP
occurrence
for
these
plant
subsets
represents
DBP
occurrence
once
all
plants
meet
the
rule
requirements.

Compliance
with
the
Stage
1
DBPR
(
80/
60
RAA)
was
determined
by
calculating
the
annual
average
of
the
last
four
quarters
of
ICR
data
(
January
to
December
1998)
at
the
four
distribution
system
locations
(
DSE,
AVG1,
AVG2,
and
DS
Maximum).
Compliance
with
the
Stage
2
DBPR
(
80/
60
LRAA)
was
determined
by
calculating
the
annual
average
of
the
last
four
quarters
of
data
for
each
of
the
four
locations
and
taking
the
maximum.
A
20
percent
safety
factor
was
applied
when
assessing
compliance
to
be
consistent
with
evaluation
of
compliance
by
SWAT.
Results
are
summarized
in
Exhibit
5.10.

Exhibit
5.10
Number
of
Plants,
Locations,
and
TTHM/
HAA5
Observations
In
Each
Data
Set
Data
Type
No.
That
Meet
the
Screening
Criteria
(
Pre­
Stage
1
data
set)
No.
that
are
Stage
1­
Compliant
(
Pre­
Stage
2
data
set)
No.
that
are
Stage
2­
Compliant
(
Post­
Stage
2
data
set)

Plants
311
262
223
Locations
1
1,230
1,035
880
Paired
TTHM/
HAA5
Observations
2
4,482
3,767
3,212
1
Number
of
locations
with
at
least
one
data
point
for
all
plants
in
the
data
set
(
pre­
stage
1,
pre­
stage
2,
or
post­
stage
2).
There
is
a
maximum
of
4
locations
(
DSE,
AVG1,
AVG2,
and
DS
Maximum)
for
each
plant.
2
Number
of
paired
TTHM/
HAA5
observations
for
all
screened
plants
in
the
data
set.
There
is
a
maximum
of
16
observations
for
each
plant.

Source:
Occurrence
Document
(
USEPA
2003l).
See
section
5.4.1.1
for
summary
of
methodology
used
to
derive
data
in
this
exhibit.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
35
July
2003
5.4.1.2
Discussion
of
Changes
in
Peak
DBP
Occurrence
This
section
provides
evidence
of
the
effectiveness
of
the
Stage
2
DBPR
in
reducing
peaks
by
answering
two
questions
related
to
peak
DBP
occurrence.
Analysis
of
ICR
data
are
used
to
derive
conclusions
for
each
question.

Question
1
 
What
do
current
LRAA
and
RAA
measurements
at
plants
indicate
about
compliance
with
the
Stage
1
and
Stage
2
DBPRs?

Exhibit
5.11
compares
the
RAA
and
maximum
LRAA
compliance
calculations
for
the
same
plants
from
ICR
data.
The
maximum
LRAA
values
shown
reflect
the
highest
of
the
individual
LRAA
values
observed
at
the
different
locations
included
in
the
ICR
data
(
the
locational
average
was
calculated
at
each
of
the
four
ICR
distribution
system
locations,
and
the
maximum
was
identified
as
the
LRAA).
As
would
be
expected
from
the
structure
of
the
LRAA
and
RAA
measurement
approaches,
there
will
typically
be
one
or
more
LRAA
values
that
exceeds
the
RAA
(
with
one
or
more
falling
below
the
RAA).
The
values
used
in
these
comparisons
are
simply
the
highest
among
those
LRAA
values
that
exceed
the
RAA,
indicating
the
highest
of
the
peak
values
in
those
plants.

The
upper
graph
depicts
results
using
TTHM
data,
and
the
lower
graph
shows
HAA5
results.
Each
point
on
the
graph
represents
one
plant.
The
x­
axis
value
represents
the
RAA
value
for
that
plant,
based
on
data
from
all
distribution
system
locations.
The
y­
axis
value
represents
the
maximum
LRAA
from
a
specific
distribution
system
location
for
the
same
plant.
The
diagonal
(
dotted)
line
indicates
where
the
RAA
and
maximum
LRAA
are
equal.
The
data
points
consistently
fall
to
the
left
and
above
that
diagonal,
consistent
with
the
expectation
that
maximum
LRAA
measurement
at
any
plant
will
typically
be
greater
than
the
RAA
value
at
that
plant.

The
thick
vertical
and
horizontal
dashed
lines
depict
the
MCL
values
for
Stage
1
and
Stage
2
with
a
20
percent
safety
factor.
The
four
quadrants
created
by
these
crossing
lines
are
useful
for
interpreting
the
incremental
impact
of
the
Stage
2
maximum
LRAA
relative
to
the
Stage
1
RAA.
Quadrant
I
captures
those
plants
that,
based
on
the
ICR
data,
currently
meet
both
the
Stage
1
80/
60
RAA
and
the
Stage
2
80/
60
LRAA
regulations.
Quadrant
II
captures
those
plants
that
currently
meet
the
Stage
1
RAA,
but
not
the
Stage
2
LRAA.
Quadrant
III
captures
those
plants
that
do
not
meet
either
the
Stage
1
or
Stage
2
regulations.
The
lower
right
quadrant
(
quadrant
IV)
corresponds
with
plants
that
would
meet
Stage
2,
but
not
Stage
1,
which
is
not
possible
under
these
regulatory
options
and
is
therefore
an
empty
set.
It
is
useful
to
note
that
among
those
systems
that
currently
meet
both
the
Stage
1
and
Stage
2
requirements
(
quadrant
I),
the
maximum
LRAA
values
typically
exceed
the
RAA
for
those
plants
by
only
5
to
10
µ
g/
L.

The
impact
of
the
Stage
1
rule
alone
would
mainly
be
seen
in
plants
in
quadrant
III.
These
plants
do
not
meet
the
Stage
1
MCL
of
80/
60
RAA
and
would
most
likely
change
technology
to
reduce
DBP
concentrations.
With
those
technology
changes,
plants
in
quadrant
III
would
be
redistributed
into
quadrants
I
and
II.
It
is
not
possible
to
know
precisely
how
that
redistribution
would
occur,
but
it
is
reasonable
to
assume
that
the
DBP
levels
at
these
plants
would
roughly
reflect
the
current
distribution
in
those
two
quadrants.
This
suggests
that
those
plants
implementing
treatment
to
reduce
the
RAA
values
(
and
therefore
move
to
the
left
on
the
x­
axis),
will
also
move
down
the
y­
axis
to
more
closely
match
those
plants
in
both
quandrants
I
and
II
already
in
compliance
with
Stage
1.
This
indicates
that
Stage
1
will
result
not
only
in
reductions
in
the
RAA,
but
also
reductions
in
the
highest
LRAA
value
at
those
plants.
This
makes
sense
if
one
considers
that
if
the
maximum
LRAA
values
did
not
change,
it
would
imply
that
the
plant
was
achieving
the
RAA
value
by
reducing
already
low
LRAA
values
at
other
sites
even
further
while
not
affecting
the
levels
at
the
peak
locations,
which
is
an
unlikely
scenario.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
36
July
2003
The
potential
reductions
in
DBP
occurrence
resulting
from
the
Stage
2
LRAA
relative
to
the
Stage
1
RAA
are
reflected
by
expected
treatment
changes
in
the
plants
in
quadrant
II.
(
These
would
include
both
those
already
in
quadrant
II
as
shown
in
Exhibit
5.11
and
those
that
would
be
added
by
virtue
of
the
redistribution
of
plants
from
quadrant
III
following
implementation
of
Stage
1.)
Plants
in
quadrant
II
meet
the
80/
60
RAA
for
the
distribution
system
as
a
whole,
but
would
have
one
or
more
locations
where
the
80/
60
LRAA(
s)
are
not
being
met.
These,
then,
are
plants
having
peak
events
that
the
Stage
1
RAA
does
not
capture,
but
which
would
be
addressed
under
the
Stage
2
LRAA.
Following
Stage
2,
these
plants
would
be
redistributed
into
quadrant
I
of
the
graphs.

Consideration
of
the
data
in
these
two
quandrants
suggests
that
plants
reducing
DBP
levels
to
meet
the
Stage
2
LRAA
requirements
will
likely
also
reduce
their
RAA
values
as
they
become
more
similar
to
those
plants
already
in
quandrant
I,
which
are
now
meeting
both
rules.
While
it
is
conceivable
that
plants
could
move
down
the
y­
axis
to
comply
with
the
LRAA
without
changing
their
current
RAA
values,
this
would
imply
that
there
would
have
to
be
increases
in
the
LRAA
values
at
other
locations
in
order
maintain
that
same
RAA
value.
This
is
an
unlikely
scenario
based
on
the
expected
treatment
techniques
that
will
be
used
to
achieve
compliance
with
the
Stage
2
LRAA
values,
and
therefore
it
is
expected
that
reductions
in
the
LRAA
values
will
result
in
a
concomitant
reduction
in
the
RAA
at
those
systems
making
changes
to
comply
with
the
Stage
2
DBPR.

Conclusion:
Estimates
derived
from
the
ICR
data
of
the
LRAA
and
RAA
at
individual
plants
indicate
that
the
highest
LRAA
values
exceed
the
RAA
(
as
would
be
expected),
but
that
the
LRAA
values
at
plants
already
complying
with
Stage
1
and
2
DBPR
typically
do
not
exceed
the
RAA
by
more
than
5
to
10
µ
g/
L.
These
data
indicate
that,
when
those
plants
currently
out
of
compliance
with
Stage
1
reduce
DBP
levels
to
meet
the
RAA,
there
will
likely
be
a
concurrent
reduction
in
the
highest
LRAA
values
at
those
plants.
Similarly,
when
plants
out
of
compliance
with
Stage
2
reduce
DBP
levels
to
meet
the
LRAA,
there
will
be
a
concurrent
reduction
in
RAA
values.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
37
July
2003
0
20
40
60
80
100
120
0
20
40
60
80
100
120
HAA5
RAA,
ug/
L
Maximum
HAA5
LRAA,
ug/
L
II
IV
III
I
48
48
Note:
Each
point
on
the
graph
represents
one
plant
MCL
(
with
20%
Safety
Factor)
RAA
=
LRAA
representation
Plants
under
the
Stage
1
DBPR,
but
above
the
Stage
2
DBPR
compliance
targets
Source:
Derived
from
ICR
Aux
1
database
(
US
EPA,
2000h)
Exhibit
5.11
Comparison
of
TTHM
and
HAA5
Concentrations
Calculated
as
RAAs
and
Maximum
LRAAs
0
20
40
60
80
100
120
140
160
0
20
40
60
80
100
120
140
160
TTHM
RAA,
ug/
L
Maximum
TTHM
LRAA,
ug/
L
II
IV
III
I
64
64
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
38
July
2003
Question
2
 
Will
compliance
with
the
LRAA
reduce
the
incidence
of
peak
occurrence
events?

ICR
data
were
evaluated
by
comparing
the
distributions
of
TTHM
and
HAA5
data
for
all
plants
against
the
subset
of
Stage
1­
and
Stage
2­
compliant
plants.
EPA
assumed
that
the
distribution
of
the
subset
of
Stage
1­
and
Stage
2­
compliant
plants
from
the
ICR
will
generally
reflect
the
distribution
of
all
plants
after
non­
compliant
plants
change
technologies
to
meet
rule
requirements.

The
results
of
this
analysis
are
presented
in
Exhibit
5.12a
for
TTHM,
and
5.12b
for
HAA5.
The
darkest
line
represents
all
plants
evaluated,
the
dashed
line
represents
the
subset
of
Stage
1­
compliant
plants,
and
the
thin
line
represents
Stage
2­
compliant
plants.
Note
that
the
data
for
the
Stage
1­
compliant
plants
shown
in
Exhibits
5.12a
and
5.12b
are
equivalent
to
those
included
in
quadrants
I
and
II
of
Exhibit
5.11;
data
for
the
Stage
2­
compliant
plants
in
Exhibits
5.12a
and
5.12b
are
included
in
quadrant
I
of
Exhibit
5.11.

Exhibits
5.12a
and
5.12b
consistently
show
a
right­
to­
left
shift
in
the
cumulative
distributions
of
individual
observations,
indicating
a
reduction
in
peak
events
as
the
MCL
becomes
more
stringent.
In
addition,
the
percent
of
all
plants
with
at
least
one
observation
above
various
TTHM
and
HAA5
peak
levels
drops
significantly.
For
example,
the
percent
of
observations
greater
than
a
TTHM
peak
of
80
µ
g/
L
in
Exhibit
5.12a
decreases
from
7.4
percent
for
all
plants
to
2.3
percent
for
Stage
1­
compliant
plants
to
0.7
percent
for
Stage
2­
compliant
plants.
A
similar
trend
can
be
seen
for
the
percent
of
observations
greater
than
a
HAA5
peak
of
60
µ
g/
L
(
as
indicated
in
Exhibit
5.12b),
which
decreases
from
5.9
percent
for
all
plants
to
1.3
percent
for
Stage
1­
compliant
plants
to
0.4
percent
for
Stage
2­
compliant
plants.
These
data
support
the
conclusion
that
the
LRAA
will
reduce
the
occurrence
of
peak
events
as
the
MCL
becomes
more
stringent.

Conclusion:
Compliance
with
the
MCL
on
the
basis
of
LRAA
measurements
will
reduce
the
incidence
of
peak
occurrence.
There
will
be
a
higher
percentage
of
plants
with
zero
peaks
for
those
plants
that
are
in
compliance
with
Stage
2
compared
to
all
plants
in
compliance
with
the
Stage
1
DBPR.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
39
July
2003
70%
75%
80%
85%
90%
95%
100%

0
50
100
150
200
250
300
350
TTHM
Plant­
Observation
Cumulative
Percentile
All
Plants
Stage
1
Compliant
Plants
Stage
2
Compliant
Plants
Observations
>
80
ug/
L
Observations
>
100
ug/
L
Observations
>
120
ug/
L
Number
Percent
Number
Percent
Number
Percent
All
Plants
4,482
333
7.4%
140
3.1%
55
1.2%
Stage
1­
Compliant
Plants
3,767
88
2.3%
21
0.6%
5
0.1%
Stage
2­
Compliant
Plants
3,212
21
0.7%
4
0.1%
0
0.0%
All
Observations
Exhibit
5.12a
Distribution
of
TTHM
Observations
for
Different
Subsets
of
ICR
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
40
July
2003
70%
75%
80%
85%
90%
95%
100%

0
40
80
120
160
200
HAA5
Plant­
Observation
Cumulative
Percentile
All
Plants
Stage
1
Compliant
Plants
Stage
2
Compliant
Plants
Observations
>
60
ug/
L
Observations
>
75
ug/
L
Observations
>
90
ug/
L
Number
Percent
Number
Percent
Number
Percent
All
Plants
4,482
263
5.9%
138
3.1%
93
2.1%
Stage
1­
Compliant
Plants
3,767
50
1.3%
12
0.3%
5
0.1%
Stage
2­
Compliant
Plants
3,212
13
0.4%
3
0.1%
0
0.0%
All
Observations
Exhibit
5.12b
Distribution
of
HAA5
Observations
for
Different
Subsets
of
ICR
Plants
Source:
Derived
from
ICR
Aux
1
database
(
USEPA
2000h)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
41
July
2003
5.4.1.3
Estimated
Reduction
in
Peak
DBP
Exposure
This
section
contains
estimates
of
the
reduction
in
exposure
to
peak
DBPs
as
a
result
of
the
Stage
2
DBPR.
Results
are
based
on
evaluation
of
the
ICR
plants
that
met
the
screening
criteria
as
described
in
section
5.4.1.1
and
shown
in
Exhibit
5.10.
This
analysis
focuses
on
TTHM
occurrence
events,
and
includes
evaluation
of
several
peak
study
levels
(
60,
75,
80,
and
100
:
g/
L).

TTHM
occurrence
was
evaluated
for
the
four
different
distribution
system
sampling
locations
(
DSE,
AVG1,
AVG2,
and
DS
Maximum).
Exhibit
5.13
at
the
end
of
this
section
shows
the
number
and
percent
of
sampling
locations
with
at
least
one
TTHM
measurement
above
each
of
the
four
study
levels
for
all
plants
evaluated
(
columns
B
and
C),
the
subset
of
Stage
1­
compliant
plants
(
columns
E
and
F),
and
the
subset
of
Stage
2­
compliant
plants
(
columns
H
and
I).
The
results
show
that,
at
a
TTHM
study
level
of
75
:
g/
L,
the
percent
of
locations
with
at
least
one
peak
observation
declines
from
20.1
percent
for
pre­
Stage
1
to
9.3
percent
for
pre­
Stage
2
to
3.5
percent
for
post­
Stage
2
DBPR
conditions.

To
translate
estimated
changes
in
peak
DBP
occurrence
as
a
result
of
the
Stage
2
DBPR
(
as
presented
in
Exhibit
5.13)
to
changes
in
peak
DBP
exposure,
the
following
assumptions
are
used:

1)
Each
plant­
location
(
DSE,
AVG1,
AVG2,
and
DS
Maximum)
represents
an
equal
portion
(
25
percent)
of
the
total
population
served
by
the
plant.

2)
Peak
DBP
occurrence
for
311
large
ICR
plants
evaluated
is
representative
of
the
peak
DBP
occurrence
for
all
plants
(
large
and
small).

The
first
assumption
may
overestimate
the
population
represented
by
the
DS
Maximum
location
(
i.
e.,
25
percent
may
be
too
high)
and
thus,
may
overestimate
the
population
exposed
to
peaks.
This
potential
overestimate,
however,
is
minimized
because
ICR
data
showed
that
the
peak
TTHM
level
occurred
somewhere
other
than
the
DS
maximum
location
approximately
52
percent
of
the
time
(
see
Chapter
3
of
the
Stage
2
DBPR
Occurrence
Document
(
USEPA
2003l)).
The
rationale
for
the
second
assumption
is
provided
in
the
next
two
paragraphs.

ICR
data
pertains
to
all
systems
serving
more
than
100,000
people.
As
stated
previously,
the
311
plants
evaluated
represent
62
percent
(
311/
500)
of
all
plants
in
the
ICR.
Systems
serving
more
than
100,000
people
serve
approximately
140
million
people,
or
55
percent
(
140
million/
254
million)
of
total
population
served
by
disinfecting
systems
(
see
Exhibit
5.9
for
a
summary
of
population
served
by
each
disinfecting
system
size
category).
Thus,
analysis
of
311
plants
reflects
approximately
34
percent
(
55%
x
62%)
of
the
total
population
served
by
disinfecting
systems.

Because
medium­
sized
systems
serving
10,001
to
100,000
people
are
expected
to
have
technologies
and
source
water
quality
very
similar
to
large
systems
serving
100,000
or
more
people,
EPA
believes
that
ICR
large
system
data
is
adequate
for
characterizing
peak
DBP
occurrence
for
medium
systems
(
see
Appendices
A
and
B
for
comparisons
of
source
water
quality
data
and
treatment
technologies
in
place
for
medium
and
large
systems).

For
small
systems
serving
10,000
or
fewer
people,
using
ICR
data
to
characterize
pre­
Stage
1
peak
occurrence
may
bias
results
of
this
analysis
for
two
reasons.
First,
small
systems
serving
fewer
than
10,000
people
did
not
have
to
comply
with
the
1979
TTHM
standard
of
100
:
g/
L
and
may
have
higher
DBP
levels
than
indicated
by
ICR
data.
However,
small
systems
may
have
lower
DBP
levels
than
indicated
by
ICR
data
since
they
are
made
up
of
a
higher
proportion
(
more
than
75
percent)
of
ground
water­
only
systems
compared
to
large
systems,
which
are
made
up
of
less
than
20
percent
of
ground
water­
only
systems
(
source:
Exhibit
3.3).
It
is
expected
that
these
two
biases
offset
each
other
to
some
extent
in
the
analysis
of
pre­
Stage
1
data.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
42
July
2003
For
pre­
Stage
2
and
post­
Stage
2
analyses,
the
upward
bias
of
the
1979
TTHM
standard
is
eliminated
since
the
analysis
considers
only
those
plants
that
meet
the
Stage
2
DBPR
MCLs
of
80/
60
µ
g/
L
(
with
a
20
percent
safety
factor)
for
TTHM/
HAA5.
The
second
bias,
introduced
by
the
higher
proportion
of
ground
water­
only
systems
in
the
small
system
universe
as
compared
to
the
large
system
universe,
is
minimized
by
the
comparison
of
post­
Stage
2
peak
occurrence
to
pre­
Stage
2
peak
occurrence.
Lastly,
it
is
important
to
note
that
biases
in
characterization
of
DBP
peaks
nationally
that
are
caused
by
differences
in
small
system
occurrence
are
minimized
because
systems
serving
10,000
or
fewer
people
represent
only
14.8
percent
of
the
total
population
served.

DBP
concentrations
are
highly
variable
in
distribution
systems;
it
is
probable
that
this
analysis
does
not
capture
true
variability
in
exposure
to
peaks.
Uncertainties
with
interpretation
of
ICR
data
for
the
purposes
of
this
exposure
assessment
include:

°
The
extent
to
which
small
system
occurrence
is
represented
°
Year
to
year
variability
of
DBP
occurrence
data
that
might
be
affected
by
changes
in
source
water
quality
(
e.
g.,
drought
years
versus
non­
drought
years)

°
The
extent
to
which
each
ICR
sampling
point
represents
an
equal
fraction
of
the
population
served
°
The
extent
to
which
ICR
sampling
locations
represent
compliance
monitoring
locations
when
trying
to
estimate
reductions
in
exposure
resulting
from
compliance
with
Stage
1
and
Stage
2
DBPRs.

The
assumptions
in
this
section
are
necessary,
however,
for
predicting
exposure
changes
given
the
limited
data
on
DBP
occurrence
in
small
systems
and
in
distribution
systems
in
general.
Using
the
two
assumptions
listed
above,
the
reduction
in
plant­
locations
with
peaks
as
a
result
of
the
Stage
2
DBPR
(
shown
in
Exhibit
5.13)
can
be
taken
to
represent
the
reduction
in
exposure
to
peaks
nationally
as
a
result
of
the
Stage
2
DBPR.
For
example,
for
a
TTHM
study
level
of
75
:
g/
L,
the
percent
of
the
population
exposed
to
peak
DBPs
declined
from
9.3
to
3.5
percent
(
a
62%
reduction
 
5.8%
divided
by
9.3%)
as
a
result
of
the
Stage
2
DBPR.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
43
July
2003
No.
of
Locations
Evaluated
No.
of
Locations
with
Peaks
Percent
of
Locations
with
Peaks
No.
of
Locations
Evaluated
No.
of
Locations
with
Peaks
Percent
of
Locations
with
Peaks
No.
of
Locations
Evaluated
No.
of
Locations
with
Peaks
Percent
of
Locations
with
Peaks
A
B
C
=
B/
A
D
E
F
=
E/
D
G
H
I
=
H/
G
60
m
g/
L
1,230
391
31.8%
1,035
218
21.1%
880
122
13.9%
75
m
g/
L
1,230
247
20.1%
1,035
96
9.3%
880
31
3.5%
80
m
g/
L
1,230
215
17.5%
1,035
73
7.1%
880
19
2.2%
100
m
g/
L
1,230
104
8.5%
1,035
21
2.0%
880
4
0.5%
Sources:
(
A),
(
D),
and
(
G)
are
from
Exhibit
5.10.
(
B),
(
E),
and
(
H)
are
number
of
locations
with
at
least
one
TTHM
observation
over
the
TTHM
study
level
for
each
data
set
(
pre­
Stage
1,
pre­
Stage
2,
and
post­
Stage
2).
TTHM
Study
Level
Evaluated
Pre­
Stage
1
Conditions
Pre­
Stage
2
Conditions
Post­
Stage
2
Conditions
Exhibit
5.13
Percent
Reduction
in
Locations
with
Peaks
from
the
Stage
1
to
the
Stage
2
DBPR
5.4.2
Exposure
Reduction:
Average
DBPs
This
section
presents
the
predicted
reductions
in
average
distribution
system
DBP
levels
as
a
result
of
the
Stage
2
DBPR.
Appendix
E
provides
detailed
calculations
for
all
regulatory
alternatives
and
sensitivity
analyses.
The
reductions
in
average
DBP
levels
are
used
to
estimate
reduction
in
bladder
cancer
cases
in
section
5.5.2.

The
average
reduction
in
plant­
mean
TTHM
and
HAA5
concentrations
is
assumed
to
reflect
the
range
of
reductions
for
all
DBPs.
Using
these
two
DBP
classes
as
"
indicators"
for
all
chlorinated
DBPs
may
overestimate
or
underestimate
the
true
concentration
reduction
(
see
section
5.7
for
a
summary
of
uncertainties).
However,
because
measurable
halogen­
substituted
DBP
concentrations,
comprised
primarily
of
TTHM
and
HAA5,
are
estimated
to
make
up
30
to
60
percent
of
the
measured
total
organic
halide
(
TOX)
concentration
(
Singer
1999),
TTHM
and
HAA5
reductions
are
assumed
to
be
reasonable
indicators
of
the
overall
DBP
reductions.
Separate
evaluations
for
TTHM
and
HAA5
are
carried
throughout
the
analyses.

Methodology
The
methodology
used
to
estimate
the
percent
reduction
in
average
DBP
levels
draws
upon
SWAT
model
results
that
describe
changes
occurring
from
pre­
Stage
1
levels
to
pre­
Stage
2
and
post­
Stage
2
levels
(
see
Chapter
3
and
Appendix
A
for
a
detailed
description
of
SWAT).
For
each
model
run,
SWAT
generates
monthly
TTHM
and
HAA5
occurrence
data
for
each
of
273
plants
evaluated.
Monthly
data
were
averaged
for
each
plant
to
produce
plant­
mean
data.
The
mean
of
all
plant­
means
was
then
estimated,
and
the
results
for
pre­
Stage
2
and
post­
Stage
2
were
compared
to
pre­
Stage
1
DBP
occurrence
to
compute
percent
DBP
reduction.
As
discussed
further
below,
the
SWAT
model
results
were
used
directly
for
predicting
changes
in
large
and
medium
surface
water
systems
but
required
additional
assumptions
in
their
application
to
estimate
changes
in
small
surface
water
and
in
all
ground
water
systems.

Because
pre­
Stage
1
occurrence
is
used
as
a
baseline
to
compute
DBP
reduction,
SWAT
predicted
data
were
used
to
characterize
pre­
Stage
1
occurrence
for
large
surface
water
plants
instead
of
ICR
data.
Pre­
Stage
1
average
levels
for
other
categories
of
systems
were
obtained
from
observed
data.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
44
July
2003
Specifically,
results
of
an
National
Rural
Water
Association
(
NRWA)
survey
were
the
basis
for
estimating
baseline
TTHM
and
HAA5
levels
in
small
surface
water
systems
(
USEPA
2000c);
data
from
seven
States
were
used
to
characterize
TTHM
and
HAA5
occurrence
for
small
ground
water
systems
(
USEPA
2003l);
and
data
from
the
ICR
were
used
for
large
ground
water
plants
(
USEPA
2000h).
See
section
3.7
for
pre­
Stage
1
DBP
occurrence.

For
large
and
medium
surface
water
systems,
SWAT
data
was
used
directly
to
predict
pre­
Stage
2
(
post­
Stage
1)
and
post­
Stage
2
occurrence
of
TTHM's
and
HAA5'
s.
For
small
surface
water
systems,
EPA
assumes
that
pre­
Stage
2
and
post­
Stage
2
DBP
occurrence
levels
will
be
the
same
as
those
of
large
surface
water
systems.
Therefore,
the
percent
reductions
in
average
TTHM
and
HAA5
levels
in
small
systems
from
pre­
Stage
2
to
post­
Stage
2
are
identical
to
the
percent
reductions
predicted
for
large
surface
water
systems
from
the
SWAT
model.

To
estimate
reductions
in
average
DBP
concentrations
for
ground
water
systems,
EPA
assumed
that
the
percent
reduction
in
DBP
concentrations
is
related
to
the
percent
of
plants
changing
technology.
These
estimated
percentages
(
based
on
the
technology
selection
forecasts
for
ground
and
surface
water
systems
in
Chapter
3,
Chapter
6,
and
Appendix
C)
are
used
in
combination
with
the
large
surface
water
system
TTHM/
HAA5
reduction
rates
to
generate
reduction
estimates
for
ground
water
systems.
Appendix
E,
section
E.
3,
provides
detailed
calculations
for
reductions
in
average
TTHM
and
HAA5
levels
for
each
system
size
grouping
and
type.

Uncertainties
Uncertainty
in
the
SWAT­
generated
TTHM
and
HAA5
occurrence
predictions
is
evaluated
in
detail
in
Appendix
A.
Another
area
of
uncertainty
in
this
analysis
is
the
effect
of
plants
that
selected
an
advanced
technology
for
Stage
1
but
were
able
to
meet
requirements
using
ultraviolet
light
(
UV)
for
Stage
2
(
or
plants
that
"
drop
to
UV")
on
predicted
DBP
occurrence.
Because
of
the
high
level
of
uncertainty
in
SWAT
DBP
data
for
individual
plants
or
subsets
of
plants
(
summarized
in
Appendix
A),
adjustments
to
DBP
occurrence
data
were
not
made
for
those
plants
dropping
to
UV
for
Stage
2.
EPA
believes
that
this
may
underestimate
the
percent
reduction
in
DBP
concentrations
nationally,
but
does
not
believe
that
the
effects
are
great.

The
methodology
for
estimating
percent
DBP
reductions
for
small
surface
water
and
for
ground
water
systems
also
has
inherent
uncertainties.
Technologies
for
ground
water
and
small
surface
water
systems
are
not
exactly
the
same
as
those
available
to
large
surface
water
systems.
In
cases
where
the
technology
type
is
similar,
the
design
assumptions
and
operating
parameters
can
be
different,
resulting
in
a
different
predicted
reduction
in
DBP
concentration.
Also,
SWAT
allows
plants
to
make
operational
changes
to
existing
treatment
configurations
to
meet
the
Stage
1
and
Stage
2
MCLs.
These
changes
are
not
included
in
the
compliance
forecast
and
their
costs
are
not
estimated
in
this
document,
but
they
do
produce
some
reduction
in
DBPs.
Exhibit
5.14
summarizes
the
percent
of
plants
making
operational
changes
from
Stage
1
to
Stage
2
DBPR.
The
results
include
negative
values
because
some
plants
selecting
an
operational
change
for
Stage
1
will
move
to
a
higher
operational
change
or
to
an
advanced
technology
for
Stage
2.
The
technology
selection
forecasts
for
ground
water
systems
does
not
include
similar
minimal­
cost
techniques
to
reduce
DBP
concentrations.

Another
area
of
uncertainty
is
the
effect
of
the
IDSE
on
the
compliance
forecast
and
resultant
reduction
in
average
TTHM
and
HAA5
levels.
This
uncertainty
is
addressed
in
a
sensitivity
analysis
in
Chapter
7.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
45
July
2003
Condition
Adjust
Disinfectant
Dose
Enhanced
Coagulation
Enhanced
Softening
Moving
Point
of
Chlorination
Total
for
All
Operational
Changes
Technology
Selection
­
Stage
1
22.7%
6.6%
2.6%
9.2%
41.0%
Technology
Selection
­
Stage
2
19.0%
8.4%
3.7%
9.5%
40.7%

Delta
(
Stage
2
minus
Stage
1)
­
3.7%
1.8%
1.1%
0.4%
­
0.4%

Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.

Source:
SWAT
run
summaries
(
USEPA
2001e).
Exhibit
5.14
Operational
Changes
Predicted
by
SWAT
for
the
Stage
1
DBPR
and
Stage
2
DBPR,
Preferred
Regulatory
Alternative
Results
Exhibits
5.15
and
5.16
show
the
cumulative
distributions
of
SWAT­
predicted
concentrations
of
TTHM
and
HAA5,
respectively,
for
pre­
Stage
2
and
post­
Stage
2
conditions
(
cumulative
distributions
comparing
pre­
Stage
1
and
pre­
Stage
2
occurrence
are
presented
in
Chapter
3).
Although
only
plantmean
data
are
used
in
the
exposure
calculations,
both
individual
monthly
observations
and
calculated
plant­
means
are
depicted
in
the
exhibits
to
show
the
full
distributions
of
the
predicted
data.

Exhibit
5.17a
presents
estimated
pre­
Stage
1
and
pre­
Stage
2
TTHM
and
HAA5
mean
distribution
system
concentrations
for
surface
and
ground
water
plants.
This
analysis
shows
that
the
largest
percent
reduction
in
DBP
concentrations
is
for
surface
water
plants
from
pre­
Stage
1
to
pre­
Stage
2
conditions
(
reductions
range
from
approximately
27
to
57
percent
for
all
plants).
The
reduction
in
DBP
occurrence
for
ground
water
plants
is
much
less,
ranging
from
3
to
4
percent.
The
percent
reduction
for
small
surface
water
plants
is
greater
than
the
percent
reduction
for
large
surface
water
plants
because
plants
in
small
systems
did
not
have
to
meet
the
TTHM
rule
MCL
of
100
:
g/
L
prior
to
the
Stage
1
DPBR.

Exhibit
5.17b
shows
the
estimated
percent
reduction
in
TTHM/
HAA5
concentrations
from
pre­
Stage
2
to
post­
Stage
2
DBPR
conditions
for
the
preferred
regulatory
alternative.
The
estimated
average
reduction
in
plant­
mean
TTHM
and
HAA5
concentrations
as
a
result
of
the
Stage
2
DPBR
is
much
smaller
than
the
reduction
for
Stage
1;
approximately
4.7
percent
for
all
surface
water
plants
and
between
1.7
and
2.2
percent
for
all
ground
water
plants.
Results
for
the
other
regulatory
alternatives
are
in
Appendix
E.

The
calculation
of
the
percent
reduction
in
all
plant­
mean
DBP
levels
(
summarized
in
Exhibits
5.17a
and
5.17b
above)
includes
plants
that
make
minor
process
changes
at
the
plant
as
well
as
those
that
do
not
make
any
technology
changes
to
meet
the
Stage
2
DBPR.
The
estimated
percent
reduction
for
the
subset
of
plants
that
add
advanced
technologies
or
chloramines,
therefore,
is
much
higher.
Among
those
plants
reducing
DBP
levels
from
Stage
1
to
Stage
2,
it
is
estimated
that
the
average
reductions
in
DBP
levels
will
be
approximately
30%,
and
may
range
from
less
than
5%
up
to
60%.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
46
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
10
20
30
40
50
60
70
Plant
Mean
TTHM
(
ug/
L)
Cumulative
Percentile
TTHM
DSAVG
­
Post
S2
TTHM
DSAVG
­
Pre
S2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
50
100
150
200
250
TTHM
(
ug/
L)
Cumulative
Percentile
TTHM
DSAVG
­
Post
S2
TTHM
DSAVG
­
Pre
S2
Exhibit
5.15a
TTHM
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Exhibit
5.15b
TTHM
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Source:
DS
average
data
from
SWAT
runs
300
and
303
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
47
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
20
40
60
80
100
120
140
160
HAA5
(
ug/
L)
Cumulative
Percentile
HAA5
DSAVG
­
Post
S2
HAA5
DSAVG
­
Pre
S2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
10
20
30
40
50
60
Plant
Mean
HAA5
(
ug/
L)
Cumulative
Percentile
HAA5
DSAVG
­
Post
S2
HAA5
DSAVG
­
Pre
S2
Exhibit
5.16a
HAA5
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Exhibit
5.16b
HAA5
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Source:
DS
average
data
from
SWAT
runs
300
and
303
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
48
July
2003
Exhibit
5.17a
Reduction
in
Average
TTHM
and
HAA5
Concentrations
from
Pre­
Stage
1
to
Pre­
Stage
2
Source
Water
System
Size
(
Population
Served)
Mean
of
Plant­
Mean
TTHM
Concentrations
(
:
g/
L)
Mean
of
Plant­
Mean
HAA5
Concentrations
(
:
g/
L)

Pre­
Stage
1
Pre­
Stage
2
Percent
Reduction
Pre­
Stage
1
Pre­
Stage
2
Percent
Reduction
SW
#
10,000
82.8
35.5
57.2
%
45.3
25.0
44.8
%

>
10,000
48.7
35.5
27.2
%
35.5
25.0
29.5
%

GW
#
10,000
16.5
16.0
3.4
%
8.8
8.5
3.7
%

>
10,000
16.7
16.3
2.6
%
8.9
8.6
2.8
%

Exhibit
5.17b
Reduction
in
Average
TTHM
and
HAA5
Concentrations
from
Pre­
Stage
2
to
Post­
Stage
2,
Preferred
Regulatory
Alternative
Source
Water
System
Size
(
Population
Served)
Mean
of
Plant­
Mean
TTHM
Concentrations
(
:
g/
L)
Mean
of
Plant­
Mean
HAA5
Concentrations
(
:
g/
L)

Pre­
Stage
2
Post­
Stage
2
Percent
Reduction
Pre­
Stage
2
Post­
Stage
2
Percent
Reduction
SW
#
10,000
35.5
33.8
4.7
%
25.0
23.8
4.7
%

>
10,000
35.5
33.8
4.7
%
25.0
23.8
4.7
%

GW
#
10,000
16.0
15.6
2.2
%
8.5
8.3
2.2
%

>
10,000
16.3
16.0
1.7
%
8.6
8.5
1.7
%

Note:
Due
to
rounding,
percent
reductions
calculated
from
data
in
the
tables
may
differ
from
the
actual
values
presented
here.

Source:
Derived
in
Appendix
E.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
49
July
2003
5.5
Benefits
of
the
Stage
2
DBPR:
Reduced
Incidence
of
Adverse
Effects
5.5.1
Reduced
Incidence
of
Reproductive
and
Developmental
Effects
As
discussed
earlier,
both
epidemiological
and
toxicological
evidence
suggest
the
potential
for
increased
adverse
health
risk
for
pregnant
women
and
their
fetuses
exposed
to
DBPs
in
drinking
water.
While
the
levels
of
DBPs
associated
with
specific
potential
adverse
reproductive
and
developmental
effects
is
not
known,
EPA
believes
that
lowering
the
overall
levels
of
DBPs
in
distribution
systems
and
in
particular
by
reducing
the
incidence
of
peak
levels
is
important
from
a
public
health
perspective.

EPA
believes
that
the
current
scientific
knowledge
on
reproductive
and
developmental
health
effects
is
not
strong
enough
to
quantify
risk
in
the
primary
benefits
analysis.
However,
an
illustrative
calculation
considering
the
range
of
possible
benefits
for
one
specific
effect
in
this
category
 
avoided
cases
of
fetal
loss
 
is
presented
in
Section
5.9.
The
discussion
in
Section
5.2
and
the
illustrative
calculation
in
Section
5.9
suggest
that
the
benefits
from
reduced
DBP
exposure
in
terms
of
both
avoided
incidence
of
reproductive
and
developmental
effects
and
in
terms
of
the
potential
monetized
value
of
those
avoided
cases
could
be
significant.

5.5.2
Reduced
Incidence
of
Bladder
Cancer
Cases
This
section
presents
EPA's
estimates
of
the
expected
reduction
in
the
incidence
of
new
bladder
cancer
cases
annually
as
result
of
the
Stage
2
DBPR.
The
methodology
used
to
obtain
these
estimates
is
also
discussed
in
this
section.
Additional
details
on
the
methodology
are
provided
in
Appendix
E
and
related
information
on
the
baseline
cases
of
bladder
cancer
attributable
to
DBPs
is
provided
in
Section
5.2.2.

Several
key
assumptions
underlie
the
calculation
of
bladder
cancer
cases
avoided
by
the
Stage
2
DBPR.
The
most
important
assumption
is
that
a
causal
relationship
exists
between
exposure
to
chlorinated
surface
water
and
bladder
cancer.
However,
EPA
and
the
international
bodies
that
classify
risk
recognize
that
such
causality
has
not
yet
been
established.
Other
important
assumptions
are
that
the
assumed
attributable
risk
of
bladder
cancer
from
drinking
water
increases
linearly
with
increasing
average
concentrations
of
TTHMs
and
HAA5
in
drinking
water
and
that
the
number
of
cases
occurring
each
year
in
the
population
served
by
disinfecting
water
supplies
is
directly
proportional
to
the
average
DBP
levels
in
those
systems.
For
example,
if
some
specified
number
of
cancer
cases
per
year
were
known
to
be
attributable
to
consumption
of
disinfected
water
where
the
current
DBP
levels
are
of
some
known
average,
this
assumption
implies
that
only
half
that
number
of
cases
would
have
occurred
if
the
average
DBP
levels
were
only
half
the
current
average.
Therefore,
the
number
of
cancer
cases
avoided
from
the
Stage
2
DBPR
can
be
estimated
from
expected
changes
in
average
DBP
levels
in
disinfecting
public
water
systems.

An
important
assumption
that
is
directly
related
to
the
above
is
that
the
reduction
in
the
incidence
of
new
cancer
cases
assumed
to
be
due
to
DBPs
can
be
estimated
from
modeled
reductions
in
average
levels
of
TTHM
and
HAA5
resulting
from
the
Stage
2
DBPR
where
TTHM
and
HAA5
serve
as
indicators
of
overall
DBP
levels
in
drinking
water.
The
number
of
cases
avoided
(
and
the
resulting
monetized
benefits
discussed
in
subsequent
sections)
were
calculated
using
both
TTHM
and
HAA5
as
indicators
for
exposure
to
all
DBPs
(
see
section
5.4.2
for
discussion
of
the
use
of
TTHM
and
HAA5
as
indicators).
However,
for
analyses
presented
in
the
rest
of
the
chapter,
only
the
results
of
calculations
using
TTHM
as
the
indicator
of
DBPs
are
presented,
to
simplify
the
presentation.
Benefits
calculated
using
TTHM
as
an
indicator
are
less
than
1
percent
lower
for
the
preferred
regulatory
alternative
than
those
calculated
using
HAA5
as
an
indicator.
Thus,
evaluation
of
TTHM­
based
figures
presents
a
very
similar,
yet
conservative,
estimate
of
benefits
throughout
the
analysis.
Detailed
results
for
all
analyses
using
both
TTHM
and
HAA5
as
indicators
are
presented
in
Appendices
E
and
F.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
50
July
2003
Another
key
set
of
assumptions
used
to
estimate
the
reduction
of
bladder
cancer
incidence
relates
to
the
timing
of
when
the
expected
reduction
in
new
cancer
cases
each
year
begins
to
occur.
It
is
assumed
that
the
reductions
in
average
DBP
levels
expected
to
occur
when
the
Stage
2
DBPR
is
implemented
will
not
produce
immediate
reductions
in
annual
cancer
cases.
Individual
cancer
risks
generally
reflect
lifetime
exposure
levels
and
not
just
recent
or
current
exposure
levels.
Therefore,
it
would
not
be
appropriate
to
assume
that
individuals
exposed
to
some
level
of
DBPs
for
a
substantial
portion
of
their
lifetime
would
immediately
attain
a
reduced
risk
of
bladder
cancer
when
DBP
levels
in
their
water
system
are
reduced
as
a
result
of
compliance
with
the
Stage
2
DBPR.
A
transition
between
the
pre­
Stage
2
risks
and
the
post­
Stage
2
risks
 
referred
to
here
as
the
"
cessation
lag"
 
has
been
included
in
the
calculation
of
cancer
cases
avoided
each
year
to
account
for
this
factor.

Three
subsections
describing
the
estimation
of
cancer
cases
avoided
follow.
In
the
first
subsection,
the
annual
cancer
cases
avoided
due
to
the
Stage
2
DBPR
are
calculated
without
taking
the
cessation
lag
transition
into
account.
This
establishes
the
"
steady­
state"
number
of
cases
avoided
that
will
be
achieved
once
the
full
effect
of
the
reduced
DBP
exposure
is
realized.
The
second
subsection
takes
into
account
the
effect
of
the
cessation
lag
transition
period
between
current
and
post­
regulatory
risk
levels.
A
final
subsection
accounts
for
the
timing
of
the
avoided
cancer
cases
by
considering
the
implementation
schedule
of
the
rule
(
that
is,
not
all
affected
systems
will
implement
the
rule
simultaneously).

5.5.2.1
Annual
Cancer
Cases
Avoided
(
Steady­
State)

Once
the
Stage
2
DBPR
has
been
fully
implemented,
the
incidence
of
bladder
cancer
cases
annually
are
anticipated
to
decline
to
some
new,
lower
value
reflecting
the
lower
average
DBP
exposure
levels.
That
new,
lower
value
will
be
achieved
over
time
as
lifetime
risks
for
individuals
currently
consuming
water
with
DBPs
at
the
high,
pre­
Stage
2
levels
become
more
influenced
by
the
lower,
post­
Stage
2
levels.
(
Over
the
long­
term,
the
lower
incidence
of
new
bladder
cancer
cases
reflect
the
difference
in
the
risk
of
new
generations
of
individuals
who
are
exposed
largely
or
solely
to
the
post­
Stage
2
levels
for
their
lifetimes
instead
of
the
pre­
Stage
2
levels.)

The
new,
lower
level
of
annual
cancer
incidence
that
is
assumed
to
be
achieved,
and
the
implied
cases
avoided
relative
to
current
cancer
incidence,
are
referred
to
here
as
the
"
steady­
state"
values
and
reflect
the
maximum
number
of
cases
avoided
per
year
that
could
be
achieved
from
these
rules.
The
first
step
in
estimating
the
expected
number
of
cases
avoided
per
year
is
to
calculate
this
steady­
state
or
maximum
value.

To
calculate
the
post­
Stage
2
steady­
state
incidence
of
DBP
cancer
cases,
it
is
necessary
to
begin
with
a
calculation
of
the
pre­
Stage
1
cancer
incidence,
determine
the
expected
effects
of
Stage
1
to
estimate
a
pre­
Stage
2
(
post­
Stage
1)
steady­
state
cancer
incidence,
and
then
determine
the
expected
effects
of
the
Stage
2
DBPR
on
steady­
state
cancer
incidence.
This
is
done
by
relating
steady­
state
cancer
cases
to
DBP
occurrence
before
and
after
these
rules
are
implemented,
as
follows:

°
Apportion
pre­
Stage
1
baseline
estimates
of
bladder
cases
(
as
derived
in
Section
5.2.2)
to
populations
served
by
ground
and
surface
water
systems
according
to
the
proportion
of
total
population
served
and
relative
TTHM
and
HAA5
occurrence.

°
Calculate
the
number
of
pre­
Stage
2
cases
remaining
by
applying
the
percent
reduction
in
TTHM
and
HAA5
occurrence
attributable
to
the
Stage
1
DBPR
(
percent
reduction
from
pre­
Stage
1
to
pre­
Stage
2
in
Exhibit
5.18,
values
for
large
and
large
ground
and
surface
water
systems)
to
the
pre­
Stage
1
DBPR
estimate
of
bladder
cancer.
8Although
the
2
and
17
percent
PAR
values
are
used
throughout
this
section,
EPA
recognizes
that
the
lower
bound
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
51
July
2003
°
Calculate
post­
Stage
2
cases
remaining
(
steady­
state)
by
applying
the
percent
reduction
in
TTHM
and
HAA5
occurrence
attributable
to
the
Stage
2
regulatory
alternatives
to
the
pre­
Stage
2
cases
remaining.

As
discussed
in
Section
5.2.2,
the
low
and
high
estimates
of
pre­
Stage
1
cases
(
1,100
and
9,600
cases)
are
based
on
2
and
17
percent
PAR
estimates8.
Detailed
methodology
and
results
for
the
derivation
of
PAR
and
the
resulting
cases
avoided
by
the
Stage
2
regulatory
alternatives
and
sensitivity
analyses
are
provided
in
Appendix
E.

Exhibit
5.18
summarizes
the
predicted
number
of
steady­
state
cancer
cases
remaining
after
implementation
of
the
Stage
1
DBPR
and
the
estimated
steady­
state
reduction
in
the
number
of
cases
attributable
to
the
Stage
2
DBPR
preferred
regulatory
alternative.
The
estimated
787
"
steady­
state"
post­
Stage
2
cancer
cases
presented
in
Exhibit
5.18
indicate
what
the
annual
cancer
incidence
assumed
to
be
attributable
to
DBPs
would
be
currently
if
the
lower
average
DBP
levels
anticipated
from
this
regulation
were
the
status
quo.
Similarly,
the
estimated
821
"
steady­
state"
pre­
Stage
2
cancer
cases
presented
in
Exhibit
5.18
indicate
what
the
annual
cancer
incidence
assumed
to
be
attributable
to
DBPs
would
be
currently
if
average
DBP
levels
reflecting
those
regulations
were
the
status
quo.
The
difference
between
these
 
34
cases
avoided
annually
 
describes
the
difference
between
these
alternative
conditions
and,
therefore,
the
potential
benefits
of
the
stage
2
DBPR
(
using
the
2
percent
PAR
value).

The
estimates
in
Exhibit
5.18
do
not
take
into
account
the
time
between
changes
in
exposure
to
a
carcinogen
and
changes
in
lifetime
risk
for
individuals
who
have
already
been
exposed
at
the
higher
levels
for
some
portion
of
their
lifetime,
nor
to
the
phase­
in
over
time
of
reductions
in
DBP
concentrations
due
to
the
Stage
2
DBPR
implementation
schedule.
The
next
two
sections
show
how
the
steady­
state
results
in
Exhibit
5.18
are
modified
to
account
for
the
cessation
lag
in
risk
reductions
and
the
rule
implementation
schedule.
9
SAB
included
the
following
statement
in
its
report
on
arsenic
to
emphasize
this
difference:
"
An
important
point
is
that
the
time
to
benefits
from
reducing
arsenic
in
drinking
water
may
not
equal
the
estimated
time
since
first
exposure
to
an
adverse
effect.
A
good
example
is
cigarette
smoking:
the
latency
between
initiation
of
exposure
and
an
increase
in
lung
cancer
risk
is
approximately
20
years.
However,
after
cessation
of
exposure,
risk
for
lung
cancer
begins
to
decline
rather
quickly.
A
benefits
analysis
of
smoking
cessation
programs
based
on
the
observed
latency
would
greatly
underestimate
the
actual
benefits."
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
52
July
2003
Exhibit
5.18
Steady­
State
Cancer
Cases
Remaining
after
Stage
1
and
Avoided
by
Stage
2
(
Total
Estimated
Cases)

TTHM
as
an
Indicator
For
DBP
Exposure
2%
PAR
17%
PAR
Annual
Steady­
State
Number
of
Bladder
Cancer
Cases
Attributed
to
DBPs,
Pre­
Stage
2
conditions
821
7,166
Annual
Steady­
State
Number
of
Bladder
Cancer
Cases
Attributed
to
DBPs,
Post­
Stage
2
conditions
787
6,871
Annual
Steady­
State
Cases
of
Bladder
Cancer
Avoided
with
Stage
2
DBPR
Compliance,
Preferred
Alternative
(%
of
Pre­
Stage
2
Cases)
34
(
4.1%)
295
(
4.1%)

Notes:
Detail
may
not
add
due
to
independent
rounding.
EPA
recognizes
that
the
actual
cases
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
Source:
Derived
by
multiplying
estimated
pre­
Stage
2
bladder
cancer
cases
remaining
in
surface
and
ground
water
systems
by
the
percent
reduction
in
TTHM
concentration
in
surface
and
ground
water
systems
(
from
Exhibit
5.22b).
Detailed
calculations
presented
in
Appendix
E
(
see
Exhibit
E.
17a
for
results).

5.5.5.2
Annual
Cancer
Cases
Avoided
Accounting
for
Cessation
Lag
The
development
of
cancer
due
to
exposure
to
environmental
carcinogens
involves
a
complex
set
of
processes
that
are
not
well
understood
for
most
substances.
In
general,
however,
the
development
of
cancer
involves
some
time
period,
usually
referred
to
as
the
latency
period,
between
the
initiation
of
exposure
and
the
onset
of
cancer.
However,
the
lengths
of
cancer
latency
periods
are
poorly
understood
by
health
scientists.
Latency
periods
in
humans
often
involve
many
years,
even
decades.

EPA
recognizes
that
despite
uncertainties
in
the
latency
period
associated
with
different
types
of
carcinogens,
it
is
unlikely
that
all
cancer
reduction
benefits
would
be
realized
immediately
upon
exposure
reduction.
If
it
is
assumed
that
the
full
reduction
in
risk
is
attained
immediately
upon
reduction
in
exposure,
this
would
tend
to
overestimate
the
benefits.
On
the
other
hand,
assuming
that
no
risk
reduction
occurs
for
some
extended
period
of
time
following
exposure
reduction
may
lead
to
an
underestimation
of
the
benefits.
There
will
likely
be
some
transition
period
as
individual
risks
become
more
reflective
of
the
new
lower
exposures
than
the
past
higher
exposures.

Recently,
the
Arsenic
Rule
Benefits
Review
Panel
(
ARBRP)
of
EPA's
Science
Advisory
Board
(
SAB)
addressed
this
issue
in
detail
and
provided
guidance
for
computing
benefits
to
account
for
this
transition
period
between
higher
and
lower
steady­
state
risks
(
USEPA
2001k).
The
ARBRP
coined
the
term
"
cessation­
lag"
to
emphasize
the
focus
on
the
timing
of
the
attenuation
of
risk
after
reduction
in
exposures
to
avoid
confusion
with
the
more
traditional
term
of
"
latency"
to
reflect
the
increased
risk9
from
time
of
initial
exposure.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
53
July
2003
Although
the
focus
of
the
cessation
lag
discussion
in
the
SAB
review
was
on
reducing
levels
of
arsenic
in
drinking
water,
much
of
their
consideration
of
this
issue
had
more
general
applications
beyond
the
arsenic
issue
at
hand.
In
particular,
SAB
noted
that:

°
The
same
model
should
be
used
to
estimate
the
time
pattern
of
exposure
and
response
as
is
used
to
estimate
the
potency
of
the
carcinogen.

°
If
possible,
information
about
the
mechanism
by
which
cancer
occurs
should
be
used
in
estimating
the
cessation
lag
(
noting
that
late­
stage
mechanisms
in
cancer
formation
imply
a
shorter
cessation
lag
than
early­
stage
mechanisms).

°
If
specific
data
are
not
available
for
characterizing
the
cessation
lag,
an
upper
bound
for
benefits
can
be
provided
based
on
the
assumption
of
immediately
attaining
steady­
state
results.

°
In
the
absence
of
specific
cessation
lag
data,
other
models
should
be
considered
to
examine
the
influence
of
the
lag
(
e.
g.,
the
particulate
matter
lag
model
used
for
the
Clean
Air
Act).

Following
the
release
of
the
SAB
report
on
arsenic,
EPA
initiated
an
effort
to
explore
approaches
to
including
the
cessation
lag
in
modeling
risk
reduction
and
calculating
benefits
for
the
arsenic
regulation.
EPA
recognized,
however,
that
the
concept
of
cessation
lag
may
not
only
be
applicable
to
arsenic,
but
to
other
drinking
water
contaminants
having
a
cancer
end­
point
as
well.

In
response
to
the
SAB
cessation
lag
recommendations,
EPA
has:

°
Conducted
a
study
that
resulted
in
the
2003
final
report
Arsenic
in
Drinking
Water:
Cessation
Lag
Model
(
USEPA
2003r).

°
Conducted
an
expert
scientific
peer
review
of
the
draft
report.

°
Initiated
development
of
general
criteria
for
incorporating
cessation
lag
modeling
in
benefits
analyses
for
other
drinking
water
regulations.

In
the
effort
to
develop
a
cessation
lag
model
specific
to
DBPs,
EPA
reviewed
the
available
epidemiological
literature
for
information
relating
to
the
timing
of
exposure
and
response,
but
could
not
identify
any
studies
that
were
adequate,
alone
or
in
combination,
to
support
a
specific
cessation
lag
model
for
DBPs
in
drinking
water.
Thus,
in
keeping
with
the
SAB
recommendation
to
consider
other
models
in
the
absence
of
specific
cessation
lag
information,
EPA
explored
the
use
of
information
on
other
carcinogens
that
could
be
used
as
an
indicator
to
characterize
the
influence
of
cessation
lag
in
calculating
benefits.
The
carcinogen
for
which
the
most
extensive
database
was
available
for
characterizing
cessation
lag
was
for
cigarette
smoking.
EPA
examined
several
extensive
epidemiological
studies
on
the
comparison
of
the
risks
of
adverse
health
effects,
including
lung
cancer,
for
smokers
and
former
smokers.
EPA
selected
the
Hrubek
and
McLaughlin
(
1997)
study
as
the
most
appropriate
study
for
development
of
a
statistical
model
of
disease
response
to
smoking
cessation.
This
was
a
comprehensive
study
involving
a
26­
year
follow­
up
of
almost
300,000
U.
S.
male
veterans.

In
evaluating
the
Hrubek
and
McLaughlin
data,
EPA
determined
that
the
RR
for
lung
cancer
declined
very
rapidly
after
smoking
cessation
and
derived
the
following
model
from
that
data:

RR
=
34.5
*
(
t)­
0.77
Where
"
t"
is
the
number
of
years
following
cessation
of
smoking
(
where
t
>
1).
(
USEPA
2003r)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
54
July
2003
The
34.5
factor
reflects
the
relative
risk
of
lung
cancer
for
smokers
as
a
group
in
comparison
with
the
group
of
individuals
who
have
never
smoked.
The
second
portion
of
this
model,
(
t)­
0.77,
describes
the
decline
in
relative
risk
each
year
following
the
change
in
exposure.

Although
the
model
does
not
explicitly
include
a
component
that
describes
latency,
it
does
substantially
account
for
latency.
The
reason
is
that
a
person
accumulates
risk
over
time
during
periods
of
exposure.
As
the
duration
of
exposure
increases,
total
lifetime
risk
of
disease
also
increases.
Also,
if
exposure
ceases
or
is
reduced
to
a
substantially
lower
level,
risk
does
not
go
to
zero
or
some
much
lower
level
immediately
but
transitions
over
time
to
a
level
that
initially
reflects
mainly
the
risk
from
the
previous
higher
exposure
but
ultimately
approaches
the
risk
from
the
newer,
lower
exposures.

In
the
case
of
DBPs,
it
was
determined
that
the
available
epidemiology
data
used
to
derive
the
PAR
values
did
not
provide
adequate
information
on
the
changes
in
risk
following
changes
in
exposure,
and,
therefore,
were
judged
not
suitable
for
developing
a
cessation
lag
model
specific
to
exposure
to
chlorinated
drinking
water
or
to
specific
DBPs.
On
the
other
hand,
there
is
no
available
information
on
mode
of
action
for
chlorinated
water
and
DBPs.
Thus,
EPA
assumes
that
the
mode
of
action
is
not
markedly
different
from
the
mixed
initiator
and
promoter
aspects
of
the
cigarette
smoking
model.
EPA
has
therefore
judged
that
this
smoking
cessation
model
may
be
the
best
available
for
characterizing
cessation
lag
for
estimating
benefits
attributable
to
DBP
reduction.

The
application
of
the
smoking
cessation
lag
model
to
the
calculation
of
annual
cases
of
bladder
cancer
assumed
to
be
avoided
from
reduced
DBP
levels
in
drinking
water
uses
the
following
equation
based
on
the
cessation
lag
model
presented
in
the
draft
report
Arsenic
in
Drinking
Water:
Cessation
Lag
Model
(
USEPA
2003r):

R(
t)
net
=
R
Pre­
Stage
2
­
[
w(
t)*
R
Pre­
Stage
2
+
(
1­
w(
t))*
R
Post­
Stage
2
]

where:
R(
t)
net
=
annual
cancer
cases
avoided
at
a
time
(
t)
after
implementation
of
the
Stage
2
DBPR
R
Pre­
Stage
2
=
steady­
state
annual
cancer
cases
prior
to
implementation
of
Stage
2
DBPR
R
Post­
Stage
2
=
steady­
state
annual
cancer
cases
after
implementation
of
the
Stage
2
DBPR
w(
t)
=
(
t)
­
0.77;
the
weighting
factor
for
pre­
Stage
2
cancer
cases
at
a
time
(
t)
after
implementation
of
the
Stage
2
DBPR
1­
w(
t)
=
weighting
factor
for
post­
Stage
2
cancer
cases
at
a
time
(
t)
after
implementation
of
the
Stage
2
DBPR
The
cessation
lag
weighting
factors
that
result
from
this
model
are
presented
in
Appendix
E
(
Exhibit
E.
14).

Exhibits
5.19
and
5.20,
presented
at
the
end
of
this
subsection,
compare
the
post­
Stage
2
cancer
cases
(
and
cases
avoided)
calculated
with
and
without
the
cessation
lag
model
using
TTHM
as
an
indicator
for
reduction
of
all
DBPs
and
2
percent
and
17
percent
PAR
values,
respectively.
For
both
the
2
percent
and
17
percent
PAR
values,
the
cessation
lag
model
shows
that
the
majority
of
the
potential
steady­
state
cases
avoided
occur
within
the
first
several
years,
but
with
diminishing
incremental
increases
in
later
years.
For
example,
the
cessation
lag
model
indicates
that
approximately
40
percent
of
the
steadystate
cases
avoided
are
achieved
by
the
end
of
the
second
year,
with
almost
70
percent
achieved
by
the
end
of
the
fifth
year,
and
approximately
80
percent
by
the
tenth
year.
However,
it
then
takes
until
beyond
the
twentieth
year
to
reach
90
percent
of
the
steady­
state
cases
avoided.

EPA
recognizes
that
there
are
several
factors
that
contribute
to
the
uncertainty
in
the
application
of
the
specific
cessation
lag
model
used
in
the
estimation
of
the
benefits
of
the
proposed
Stage
2
regulation.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
55
July
2003
A
key
factor
to
consider
in
assessing
this
impact
is
the
likely
mode
of
action
of
DBPs
in
eliciting
bladder
cancer
versus
the
mode
of
action
of
tobacco
smoke
in
producing
lung
cancer,
and
in
particular
whether
they
behave
as
initiators
or
promoters
of
the
carcinogenic
process.
As
discussed
in
the
SAB
report
and
the
EPA
Cessation
Lag
report
(
USEPA
2003r),
carcinogens
that
act
solely
or
primarily
as
initiators
would
tend
to
show
a
longer
cessation
lag
(
lower
rate
of
risk
reduction
following
reductions
in
exposure)
than
carcinogens
that
act
solely
or
primarily
as
promoters.
The
available
information
on
tobacco
smoke
and
lung
cancer
suggests
that
it
involves
a
mixture
of
both
initiators
and
promoters,
and
therefore
the
cessation
lag
derived
from
smoking
data
is
expected
to
reflect
the
combined
influence
of
these
divergent
mechanisms.
There
are
no
data
available
on
the
mechanism
of
action
for
DBPs
and
bladder
cancer;
indeed
the
specific
carcinogenic
agent(
s)
present
in
disinfected
water
responsible
for
the
observed
effect
have
not
been
identified.
The
use
of
the
tobacco
smoke
cessation
lag
model
reflecting
a
mixture
of
initiators
and
promoters
would
be
expected
to
attenuate
a
possible
bias
in
either
direction
if
the
DBPs
responsible
for
bladder
cancer
are
acting
predominately
as
either
initiators
or
promoters.

Another
factor
to
consider
is
that
the
cessation
lag
model
used
is
based
upon
exposure
to
tobacco
smoke
where
lung
cancer
is
the
end­
point
but
is
being
applied
to
exposure
to
disinfection
by­
products
where
the
end­
point
is
bladder
cancer.
Of
concern
here
is
that
there
is
a
more
direct
correlation
between
inhalation
and
the
site
of
cancer
for
smoking
than
there
is
for
ingestion
and
inhalation
of
drinking
water
and
the
sites
of
cancer
for
DBP
exposure.
Unfortunately,
EPA
does
not
have
data
on
which
to
develop
a
cessation
lag
model
using
data
specific
to
how
changes
in
DBP
exposures
affect
the
risks
of
developing
bladder
cancer.

Another
divergence,
and
perhaps
the
most
important,
between
the
smoking
model
and
the
DBP
application
is
that
the
smoking
model
is
based
on
complete
cessation
of
exposure,
whereas
in
the
case
of
DBP
exposure
is
only
being
reduced.
In
some
water
systems
the
reduction
is
only
10
percent,
whereas
in
others
it
may
be
as
high
as
60
percent,
with
an
average
of
approximately
30%.
This
moderate
reduction
in
exposure
may
prevent
full
DNA
repair,
which
some
scientists
interpret
as
the
basis
for
the
short
cessation
lag
associated
with
smoking.

Currently,
tobacco
smoke
is
the
only
substance
for
which
enough
data
exist
to
estimate
a
cessation
lag.
In
the
absence
of
a
reliable
cessation
lag
model
based
specifically
on
DBPs
and
bladder
cancer,
EPA
used
the
cessation
lag
model
based
on
smoking
to
provide
a
means
of
estimating
the
rate
at
which
bladder
cancer
risk
in
the
exposed
population
falls
from
the
pre­
Stage
2
levels
to
the
post­
Stage
2
levels.
However,
this
model
is
derived
from
data
involving
notable
differences
from
DBPs
in
drinking
water,
including
different
cancer
sites
(
lung
v.
bladder),
different
exposure
pathways
(
inhalation
v.
a
combination
of
ingestion,
inhalation
and
dermal),
different
risk
levels,
and,
perhaps
most
importantly,
complete
cessation
for
smoking
v.
small
exposure
decreases
for
DBPs.
For
these
reasons,
the
extent
to
which
the
smoking
/
lung
cancer
model
is
directly
transferable
to
DBP
/
bladder
cancer
is
uncertain.
It
is
not
possible
to
know,
however,
whether
and
to
what
degree
the
tobacco
smoke
cessation
lag
model
either
over­
states
or
under­
states
the
rate
at
which
population
risk
reduction
for
bladder
cancer
occurs
following
DBP
exposure
reductions.

As
discussed
above,
the
smoking
cessation
lag
model
based
on
data
from
the
Hrubek
and
McLaughlin
(
1997)
study
has
a
key
parameter
of
­
0.77
to
characterize
the
rate
of
risk
change
following
exposure
reduction.
In
the
estimation
of
that
key
parameter,
using
a
random
effects
model
as
described
in
EPA
2003a,
a
standard
error
on
that
value
of
0.052
was
also
obtained.
EPA
has
examined
the
potential
impact
of
uncertainty
in
the
­
0.77
value
of
this
key
model
parameter
by
running
alternative
models
where
parameters
values
of
­
0.68
and
­
0.86
were
used,
reflecting
approximately
90
percent
confidence
bounds
on
the
­
0.77
value.
It
was
determined
that
the
impact
of
this
quantifiable
component
of
uncertainty
is
relatively
small
and
changed
the
cases
avoided
with
cessation
lag
values
for
the
2
percent
PAR
shown
in
Exhibit
5.19
by
±
approximately
1
case
per
year,
and
for
the
7
percent
PAR
shown
in
Exhibit
5.20
by
+/­
approximately
6
cases
per
year
(
approximately
±
3
to
4
percent
on
cases
avoided
for
both
PAR
values).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
56
July
2003
EPA
is
currently
examining
the
recently
published
meta­
analysis
by
Villanueva
et
al
(
2003)
to
determine
if
the
information
provided
there
on
increases
in
risk
as
a
function
of
duration
of
exposure
can
provide
any
insight
on
how
reductions
in
risk
over
time
might
occur
following
reductions
in
exposure.
Villanueva
et
al
(
2003)
demonstrated
that
the
risk
associated
with
chlorinated
drinking
water
and
bladder
cancer
are
related
to
exposure
duration.
Specifically,
they
estimated
a
unit
increase
in
the
OR
of
1.006
per
year
(
95%
CI
of
1.004
to
1.009).
The
model
suggests
a
cumulative
OR
of
1.13
after
20
years
of
exposure
(
95%
CI
of
1.08
to
1.20),
and
1.27
(
95%
CI
of
1.17
to
1.43)
after
40
years.
This
result
is
consistent
with
most
of
the
individual
studies
which
do
not
show
statistically
significant
risk
increases
until
at
least
30­
40
years
of
exposure.
However,
these
studies
provide
indirect
evidence
only
about
the
latency
of
potential
effects.
For
perspective,
it
is
important
to
note
that
the
latency
between
initiation
of
exposure
and
an
increase
in
lung
cancer
risk
is
approximately
20
years.
As
noted
above,
latency
is
not
the
same
as
the
cessation
lag.
In
the
proposed
rule,
EPA
is
requesting
comment
on
a)
the
potential
application
of
the
Villanueva
et
al.
(
2003)
model
to
estimate
reductions
in
bladder
cancer
risk
that
might
accompany
decreased
exposure
to
DBPs
as
a
result
of
the
Stage
2
Rule;
b)
the
advantages
and
disadvantages
of
using
the
current
approach
­
i.
e.,
application
of
the
smoking
cessation
lag
model;
and
c)
suggestions
for
alternative
data
sets
or
approaches
to
characterize
cessation
lag.

5.5.2.3
Adjustments
in
Annual
Cancer
Cases
Avoided
to
Account
for
the
Rule
Implementation
Schedule
In
addition
to
the
delay
in
reaching
a
new
steady­
state
level
of
risk
reduction
as
a
result
of
cessation
lag
effects,
there
is
a
delay
in
attaining
maximum
exposure
reduction
across
the
entire
affected
population
resulting
from
the
Stage
2
DBPR
implementation
schedule.
For
example,
large
surface
water
PWSs
have
3
years
from
rule
promulgation
to
meet
the
new
Stage
2
MCLs,
with
an
additional
2­
year
extension
possible
for
capital
improvements.
For
the
benefits
(
and
costs)
analysis,
EPA
estimates
that
some
percentage
will
make
treatment
changes
in
year
1,
some
percentage
will
make
treatment
changes
in
year
2,
and
so
on.
Appendix
D
shows
the
assumptions
regarding
the
schedule
for
installation
of
treatment
technologies
to
meet
Stage
2
DBPR
requirements.
In
general,
EPA
assumes
that
a
fairly
uniform
increment
of
systems
will
complete
installation
of
new
treatment
technologies
each
year,
with
the
last
systems
installing
treatment
by
2013.

The
delay
in
exposure
reduction
resulting
from
the
rule
implementation
schedule
is
incorporated
into
the
benefits
model
by
adjusting
the
cessation
lag
weighting
factor
[
w(
t)].
For
example,
if
10
percent
of
systems
install
treatment
equipment
(
and
start
realizing
reductions
in
cancer
cases)
in
year
1,
only
that
portion
of
the
cases
will
begin
the
cessation
lag
equilibrium
process
in
that
year.
Thus,
the
resulting
"
weighted
weighting
factor"
is
higher
relative
to
the
base
factor.
Appendix
E
(
Exhibits
E.
14
through
E.
25)
presents
detailed
breakdowns
of
all
weighting
factor
adjustments
and
resulting
cancer
cases
avoided,
by
year,
for
each
rule
alternative
based
on
the
application
of
the
cessation
lag
methodology
described
above.

EPA
analyses
of
available
data
indicate
that
26
percent
of
bladder
cancers
are
fatal
and
74
percent
are
non­
fatal
(
USEPA
1999a)
and
annual
cases
avoided
were
apportioned
to
each
category
accordingly.
The
resulting
yearly
numbers
of
cases
avoided
using
TTHM
as
an
indicator
for
all
DBP
exposure
are
presented
in
Exhibit
5.21
for
both
fatal
and
non­
fatal
cases
at
both
2
and
17
percent
PAR
values.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
57
July
2003
Steady­
State
Post­
Stage
1
Cases
Steady­
State
Post­
Stage
2
Cases
Steady­
State
Cases
Avoided
Post­
Stage
2
Cases
with
Cessation
Lag
Cases
Avoided
with
Cessation
Lag
Percent
of
Steady­
State
Cases
Avoided
a
b
c=
a­
b
d
e=
a­
d
f=
e/
c*
100
1
821
787
34
821.0
0.0
0.0%
2
821
787
34
806.9
14.1
41.4%
3
821
787
34
801.6
19.4
57.1%
4
821
787
34
798.7
22.3
65.6%
5
821
787
34
796.8
24.2
71.0%
6
821
787
34
795.6
25.4
74.8%
7
821
787
34
794.6
26.4
77.7%
8
821
787
34
793.9
27.1
79.8%
9
821
787
34
793.3
27.7
81.6%
10
821
787
34
792.8
28.2
83.0%
11
821
787
34
792.4
28.6
84.2%
12
821
787
34
792.0
29.0
85.2%
13
821
787
34
791.7
29.3
86.1%
14
821
787
34
791.5
29.5
86.9%
15
821
787
34
791.2
29.8
87.6%
16
821
787
34
791.0
30.0
88.2%
17
821
787
34
790.8
30.2
88.7%
18
821
787
34
790.7
30.3
89.2%
19
821
787
34
790.5
30.5
89.6%
20
821
787
34
790.4
30.6
90.0%
21
821
787
34
790.3
30.7
90.4%
22
821
787
34
790.1
30.9
90.7%
23
821
787
34
790.0
31.0
91.1%
24
821
787
34
789.9
31.1
91.3%
25
821
787
34
789.9
31.1
91.6%
Source:
(
a)
and
(
b):
Exhibit
5.18.

(
d):
Calculated
as
(
t^­
0.77)*(
a)
+
(
1­
t^­
0.77)*(
b).
Number
of
Years
(
t)
Exhibit
5.19
Cases
Avoided
Under
2
Percent
PAR:
Steady­
State
and
with
Cessation
Lag
(
TTHM
as
Indicator)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
58
July
2003
Steady­
State
Post­
Stage
1
Cases
Steady­
State
Post­
Stage
2
Cases
Steady­
State
Cases
Avoided
Post­
Stage
2
Cases
with
Cessation
Lag
Cases
Avoided
with
Cessation
Lag
Percent
of
Steady­
State
Cases
Avoided
a
b
c=
a­
b
d
e=
a­
d
f=
e/
c*
100
1
7166
6871
295
7166.0
0.0
0.0%
2
7166
6871
295
7044.0
122.0
41.4%
3
7166
6871
295
6997.6
168.4
57.1%
4
7166
6871
295
6972.4
193.6
65.6%
5
7166
6871
295
6956.4
209.6
71.0%
6
7166
6871
295
6945.2
220.8
74.8%
7
7166
6871
295
6936.9
229.1
77.7%
8
7166
6871
295
6930.5
235.5
79.8%
9
7166
6871
295
6925.3
240.7
81.6%
10
7166
6871
295
6921.1
244.9
83.0%
11
7166
6871
295
6917.6
248.4
84.2%
12
7166
6871
295
6914.5
251.5
85.2%
13
7166
6871
295
6911.9
254.1
86.1%
14
7166
6871
295
6909.7
256.3
86.9%
15
7166
6871
295
6907.7
258.3
87.6%
16
7166
6871
295
6905.9
260.1
88.2%
17
7166
6871
295
6904.3
261.7
88.7%
18
7166
6871
295
6902.9
263.1
89.2%
19
7166
6871
295
6901.6
264.4
89.6%
20
7166
6871
295
6900.4
265.6
90.0%
21
7166
6871
295
6899.3
266.7
90.4%
22
7166
6871
295
6898.3
267.7
90.7%
23
7166
6871
295
6897.4
268.6
91.1%
24
7166
6871
295
6896.5
269.5
91.3%
25
7166
6871
295
6895.7
270.3
91.6%
Source:
(
a)
and
(
b):
Exhibit
5.18.
(
d):
Calculated
as
(
t^­
0.77)*(
a)
+
(
1­
t^­
0.77)*(
b).
Number
of
Years
(
t)
Exhibit
5.20
Cases
Avoided
Under
17
Percent
PAR:
Steady­
State
and
with
Cessation
Lag
(
TTHM
as
Indicator)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
59
July
2003
Fatal
Non­
Fatal
Total
Fatal
Non­
Fatal
Total
2003
­
­
­
­
­
­

2004
­
­
­
­
­
­

2005
­
­
­
­
­
­

2006
0.59
1.68
2.27
5.15
14.66
19.80
2007
1.40
4.00
5.40
12.26
34.88
47.14
2008
2.34
6.66
9.00
20.43
58.13
78.56
2009
3.35
9.55
12.90
29.27
83.31
112.58
2010
4.42
12.58
17.01
38.59
109.82
148.41
2011
5.53
15.74
21.27
48.25
137.34
185.59
2012
6.11
17.39
23.50
53.33
151.78
205.11
2013
6.51
18.51
25.02
56.77
161.58
218.35
2014
6.81
19.37
26.17
59.39
169.03
228.43
2015
7.02
19.97
26.99
61.24
174.29
235.52
2016
7.18
20.43
27.61
62.65
178.32
240.98
2017
7.31
20.80
28.11
63.79
181.56
245.35
2018
7.42
21.11
28.53
64.73
184.23
248.97
2019
7.51
21.37
28.88
65.52
186.49
252.01
2020
7.59
21.59
29.18
66.20
188.42
254.62
2021
7.65
21.78
29.44
66.79
190.10
256.89
2022
7.71
21.95
29.66
67.31
191.57
258.88
2023
7.77
22.10
29.87
67.77
192.88
260.65
2024
7.81
22.23
30.05
68.18
194.05
262.23
2025
7.85
22.36
30.21
68.55
195.10
263.65
2026
7.89
22.46
30.36
68.88
196.05
264.93
2027
7.93
22.56
30.49
69.19
196.92
266.10
Total
135.69
386.21
521.90
1,184.24
3,370.53
4,554.76
Avg.
5.43
15.45
20.88
47.37
134.82
182.19
Year
2%
PAR
17%
Exhibit
5.21
Estimated
Cancer
Cases
Avoided
by
Year
All
Water
Systems,
TTHM
as
Indicator
Notes:
Details
may
not
add
to
totals
due
to
independent
rounding.
EPA
recognizes
that
the
actual
cases
avoided
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
Source:
Exhibit
E.
17d
and
E.
17g
(
sum
for
all
system
sizes)
Economic
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for
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Stage
2
DBPR
Proposal
5­
60
July
2003
5.5.3
Other
Health­
Related
Benefits
The
scientific
literature
indicates
that
exposure
to
DBPs
may
be
related
to
health
effects
other
than
reproductive,
developmental,
and
bladder
cancer
effects.
Some
studies
have
indicated
an
association
between
consumption
of
chlorinated
drinking
water
and
colon
and
rectal
cancer,
while
other
studies
have
shown
no
association.
Since
1998,
several
new
studies
have
been
published
that
contribute
to
the
weight
of
evidence
relating
DBP
exposure
with
colon
and
rectal
cancer.
However,
EPA
continues
to
believe
that
the
association
between
exposure
to
DBPs
and
colon
and
rectal
cancer,
while
possibly
significant,
cannot
be
adequately
quantified
at
this
time
due
to
data
limitations.

As
TTHM
and
HAA5
levels
are
reduced
under
the
proposed
Stage
2
DBPR,
other
potentially
carcinogenic
DBPs
(
both
known
and
unknown)
will
be
reduced
as
well.
These
collateral
effects
may
further
reduce
the
number
of
colon
and
rectal
cancer
cases.
Both
toxicology
and
epidemiology
studies
indicate
that
the
other
cancers
are
associated
with
DBP
exposure
but
currently
there
is
not
enough
data
to
quantify
or
monetize
these
risks.

5.5.4
Non­
Health­
Related
Benefits
The
Stage
2
DBPR
may
increase
consumer
confidence
in
the
quality
of
drinking
water.
Drinking
water
consumers
may
be
willing
to
pay
a
premium
for
regulatory
action
if
it
reduces
their
risk
of
becoming
ill.
Consumers'
WTP
depends
on
several
factors,
including
their
degree
of
risk
aversion,
their
perceptions
about
drinking
water
quality,
and
the
expected
probability
and
severity
of
potential
human
health
effects
associated
with
DBPs.

Most
people
who
switch
to
bottled
water
or
use
filtration
devices
do
so
because
of
taste
and
odor
problems
and
health­
related
issues.
Chlorine
dioxide
and
chloramines
have
historically
been
used
to
address
taste
and
odor
problems.
To
the
extent
that
the
Stage
2
DBPR
changes
perceptions
of
the
health
risks
associated
with
drinking
water
and
improves
taste
and
odor,
it
may
reduce
actions
such
as
buying
bottled
water
or
installing
filtration
devices.
Any
resulting
cost
savings
would
be
a
regulatory
benefit.

As
PWSs
move
away
from
conventional
treatment
to
more
advanced
technologies,
other
nonhealth
benefits
are
anticipated
besides
better
tasting
and
smelling
water.
For
example,
chlorine
dioxide
is
effective
in
controlling
the
spread
of
zebra
mussels,
an
invasive
species
that
has
caused
significant
ecological
damage
in
some
U.
S.
waterways.
In
addition,
installation
of
certain
advanced
technologies
can
remove
many
contaminants
in
addition
to
those
specifically
targeted
by
the
Stage
2
DBPR,
including
those
that
EPA
may
regulate
in
the
future.
For
example,
membrane
technology
(
depending
on
pore
size),
can
be
used
to
lower
DBP
formation,
but
it
can
also
remove
many
other
contaminants
that
EPA
is
in
the
process
of
regulating.
Removal
of
any
contaminants
that
may
face
regulation
could
result
in
future
cost
savings
to
a
water
system.

5.5.5
Potential
Increases
in
Health
Risks
It
is
important
to
maintain
a
balance
between
the
risks
from
DBPs
and
those
from
microbial
pathogens
in
drinking
water.
The
Stage
2
Advisory
Committee
considered
the
impact
of
DBP
control
on
microbial
protection
when
they
recommended
the
MCLs
in
the
Stage
2
DBPR.
For
example,
as
described
in
Chapter
4
of
this
EA,
the
Microbial­
Disinfectants/
Disinfection
Byproducts
(
M­
DBP)
Advisory
Committee
debated
whether
the
bromate
MCL
should
be
lowered.
The
Stage
1
DBPR
set
the
MCL
for
bromate
at
10
µ
g/
L,
partly
because
that
was
the
limit
of
EPA's
measuring
capability
at
that
time.
New
methods
now
exist
to
measure
lower
concentrations
of
bromate,
which
would
allow
a
lower
limit
to
be
Economic
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for
the
Stage
2
DBPR
Proposal
5­
61
July
2003
set.
However,
the
committee
was
concerned
that
a
lower
bromate
MCL
might
discourage
systems
from
switching
to
(
or
continuing
to
use)
ozone
to
increase
microbial
protection.
Unlike
chlorine,
ozone
can
inactivate
Cryptosporidium,
a
focus
of
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR).
Therefore,
to
encourage
the
use
of
ozone,
M­
DBP
Advisory
Committee
recommended
that
EPA
not
change
the
bromate
MCL.

Along
with
the
reduction
in
chlorinated
DBPs
such
as
TTHM
and
HAA5,
there
may
be
increases
in
other
DBPs
as
systems
change
from
chlorine
to
more
advanced
disinfectants.
Exhibits
5.22
and
5.23
compare
the
SWAT­
predicted
monthly
average
and
plant­
mean
average
concentrations
for
chlorite
(
a
potential
byproduct
of
chlorine
dioxide
disinfection)
and
bromate
(
a
potential
byproduct
of
ozone
disinfection)
for
pre­
Stage
2
and
post­
Stage
2
conditions.
These
exhibits
show
that
the
predicted
changes
in
bromate
and
chlorite
concentration
as
a
result
of
the
Stage
2
DBPR
are
expected
to
be
minimal.

Another
potential
increase
in
health
risks
is
due
to
increases
in
N­
nitrosodimethylamine
(
NDMA),
a
probable
human
carcinogen
(
IRIS
1991),
formed
during
the
chloramination
process.
Chapter
6
shows
that
a
large
portion
of
systems
that
do
not
currently
meet
the
Stage
2
requirements
will
do
so
by
switching
to
chloramines.
Graham
et
al.
(
1995)
reported
its
formation
at
drinking
water
treatment
plants
and
Najm
and
Trussell
(
2000)
found
that
water
disinfected
with
chloramines
resulted
in
NDMA
formation.
The
concern
over
the
formation
of
NDMA
in
the
treatment
process
is
based
on
the
compound's
ability
to
persist
for
a
long
period
of
time
in
the
distribution
system.
The
mechanism
of
formation,
however,
is
still
under
examination.
A
number
of
ongoing
studies
will
also
evaluate
occurrence,
factors
that
affect
NDMA
formation,
mechanisms,
treatment
effectiveness
and
improved
analytical
methods
for
measuring
NDMA.
NDMA
is
also
found
in
a
variety
of
food
products,
beverages
and
drugs.
Economic
Analysis
for
the
Stage
2
DBPR
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5­
62
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
100
200
300
400
500
600
700
800
900
Chlorite
(
ug/
L)
Cumulative
Percentile
Post­
Stage
2
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
100
200
300
400
500
600
700
800
Plant
Mean
Chlorite
(
ug/
L)
Cumulative
Percentile
Pre­
Stage
2
Post­
Stage
2
Exhibit
5.22a
Chlorite
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Exhibit
5.22b
Chlorite
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Source:
DS
average
data
from
SWAT
runs
300
and
303
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
63
July
2003
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
1
2
3
4
5
6
7
8
Plant
Mean
Bromate
(
ug/
L)
Cumulative
Percentile
Post­
Stage
2
Pre­
Stage
2
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

0
5
10
15
20
25
Bromate
(
ug/
L)
Cumulative
Percentile
Post­
Stage
2
Pre­
Stage
2
Exhibit
5.23a
Bromate
Plant­
Mean
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Exhibit
5.23b
Bromate
Monthly
Data
for
Pre­
Stage
2
and
Post­
Stage
2
Source:
DS
average
data
from
SWAT
runs
300
and
303
(
USEPA
2001e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
64
July
2003
5.6
Valuation
of
Health
Benefits
for
the
Stage
2
DBPR
Once
the
benefits
of
implementing
the
Stage
2
DBPR
have
been
identified,
a
monetary
value
must
be
assigned
to
those
benefits
to
allow
comparison
with
the
costs
of
the
regulation
in
a
cost­
benefit
framework.
The
following
sections
draw
on
existing
valuation
literature
to
attribute
the
most
appropriate
monetary
values
to
specific
benefits
derived
from
the
rule.
Where
the
available
information
is
not
sufficient
to
quantify
monetary
benefits,
a
qualitative
discussion
of
potential
monetary
value
is
presented.

To
augment
the
valuation
data
from
existing
literature,
EPA
incorporated
into
Stage
2
DBPR
analyses
recommendations
stemming
from
reviews
of
previous
regulations.
In
particular,
recommendations
made
by
EPA's
SAB
with
regard
to
the
benefits
analysis
of
the
recently
promulgated
Arsenic
Rule
(
66
FR
6976
January
2001)
were
incorporated
into
the
Stage
2
DBPR
analyses
as
appropriate.
Even
though
the
recommendations
made
by
the
SAB
and
presented
in
Arsenic
Rule
Benefits
Analysis:
An
SAB
Review
(
USEPA
2001k)
were
made
in
the
context
of
the
arsenic
regulation,
certain
recommendations
regarding
methodology
(
e.
g.,
incorporation
of
cessation
lag,
calculation
and
presentation
of
uncertainties,
etc.)
are
applicable
to
other
impact
analyses,
including
the
Stage
2
DBPR.
This
section
is
organized
as
follows
below:

Section
5.6.1
Presents
a
qualitative
discussion
of
the
value
of
reductions
in
potential
adverse
reproductive
developmental
health
effects
derived
from
the
Stage
2
DBPR.

Section
5.6.2
Explains
the
methodology
used
for
quantitative
valuation
of
reductions
in
bladder
cancer
cases
attributable
to
the
Stage
2
DBPR.

Section
5.6.3
Summarizes
the
total
potential
benefits
attributable
to
the
Stage
2
DBPR
from
implementation
of
the
preferred
regulatory
alternative.

Section
5.6.4
Compares
estimated
benefits
attributable
to
the
preferred
regulatory
alternative
to
those
estimated
for
alternative
approaches.

5.6.1
Value
of
Reductions
in
Potential
Adverse
Reproductive
and
Developmental
Health
Effects
Potential
adverse
reproductive
and
developmental
effects
may
impose
a
large
economic
cost
on
the
nation.
Although
many
miscarriages
do
not
have
associated
medical
costs,
some
do,
with
costs
ranging
from
$
5,000
to
$
11,000
depending
on
the
conditions
of
the
miscarriage
and
the
length
of
stay
in
the
hospital
(
HCUPnet
2000).
The
full
economic
benefit
of
avoiding
a
miscarriage
would
also
include
the
monetary
value
of
forgoing
the
associated
pain,
suffering,
and
loss.
Another
potential
benefit
of
avoiding
a
miscarriage
is
that
the
life
of
the
fetus
is
saved.
Avoiding
these
costs
represents
one
potential
economic
benefit
of
the
rule.

Low
birth
weight
also
imposes
costs
on
society.
A
report
from
The
Future
of
Children
(
Lewit
et
al.
1995)
estimates
that
approximately
40,000
infants
die
each
year
as
a
result
of
low
birth
weight
and
that
$
5.4
billion
is
spent
each
year
on
the
additional
services
that
low­
birth­
weight
children
require
for
health
care
and,
eventually,
special
education
and
child
care.
The
Lewit
et
al.
(
1995)
study
also
estimates
that
$
5.5
to
$
6
billion
are
spent
each
year
caring
for
low­
birth­
weight
infants
and
children.
It
estimates
that
low­
birth­
weight
children
are
almost
50
percent
more
likely
than
normal­
birth­
weight
children
to
require
special
education.
Additionally,
the
costs
of
caring
for
low­
birth­
weight
infants
is
increasing
as
their
chances
for
survival
increase.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
65
July
2003
The
cost
for
treating
and
caring
for
those
with
birth
defects
is
high.
For
example,
the
lifetime
cost
for
a
case
of
spina
bifida,
is
estimated
at
$
0.3
million.
Estimates
for
the
lifetime
cost
for
a
heart
defect
range
from
$
0.1
to
$
0.4
million
(
CDC
1995).
These
costs
account
only
for
the
estimated
medical,
developmental,
and
special
education
services
attributed
to
each
case.
They
do
not
account
for
the
pain
and
suffering
of
the
children
with
these
conditions
or
the
emotional
strain
on
their
parents
and
other
family
members.

If
a
small
proportion
of
fetal
losses,
low
birth
weights,
premature
births,
congenital
anomalies,
and
infertility
problems
are
attributable
to
DBPs,
the
associated
monetary
value
of
benefits
from
the
Stage
2
DBPR
would
be
great.
Given
the
high
costs
of
medical
care,
the
many
ways
to
value
a
pregnancy
saved,
the
unknown
pain
and
suffering
as
a
result
of
potential
adverse
reproductive
and
developmental
effects,
the
high
percentage
of
the
U.
S.
population
exposed
to
DBPs,
and
the
large
number
of
women
pregnant,
the
Stage
2
DBPR
presents
a
potential
for
substantial
savings
to
society.
Although
uncertainties
in
the
estimation
of
potentially
avoided
adverse
reproductive
and
developmental
health
effects
preclude
a
definitive
quantitative
evaluation
of
associated
benefits
in
the
primary
analysis,
EPA
has
conducted
a
illustrative
calculation
to
estimate
a
range
of
possible
benefits
associated
with
fetal
losses
(
see
section
5.9).

5.6.2
Value
of
Reductions
in
Bladder
Cancer
Cases
Valuation
input
data
for
fatal
and
non­
fatal
bladder
cancer
cases
are
summarized
below.
This
is
followed
by
an
explanation
of
how
these
data
are
adjusted
to
current
price
levels
and
for
income
elasticity
effects,
allowing
proper
incorporation
into
the
Stage
2
DBPR
benefits
model.
The
next
section
(
5.6.3)
describes
how
these
values
are
combined
with
the
estimates
of
bladder
cancer
case
reductions
to
estimate
the
total
estimated
benefits
resulting
from
the
Stage
2
DBPR.

Value
of
Avoiding
a
Fatal
Case
of
Bladder
Cancer
For
fatal
bladder
cancer
cases,
the
Value
of
a
Statistical
Life
(
VSL)
is
used
to
capture
the
value
of
benefits.
The
VSL
represents
an
estimate
of
the
monetary
value
of
reducing
risks
of
premature
death
from
cancer.
The
VSL,
therefore,
is
not
an
estimate
of
the
value
of
saving
a
particular
individual's
life.
The
value
of
a
"
statistical"
life
represents
the
sum
of
the
values
placed
on
small
individual
risk
reductions
across
an
exposed
population.
For
example,
if
a
regulation
were
to
reduce
the
risk
of
premature
death
from
cancer
by
1/
1,000,000
for
1
million
exposed
individuals,
the
regulation
would
"
save"
one
statistical
life
(
1,000,000
X
1/
1,000,000).
If
each
of
the
1,000,000
people
were
willing
to
pay
$
5
to
achieve
the
risk
reduction
anticipated
from
the
regulation,
the
VSL
would
be
$
5
million
($
5
X
1,000,000).

An
EPA
study
characterized
the
range
of
possible
VSL
values
as
a
Weibull
distribution
with
a
mean
of
$
4.8
million
(
1990
price
level),
based
on
26
individual
study
estimates
(
USEPA
1997b).
This
is
the
value
recommended
for
use
in
benefits
analyses
in
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j)
and
endorsed
by
the
SAB
Arsenic
review
panel
(
USEPA
2001k).
For
purposes
of
the
Stage
2
DBPR
benefits
analysis,
the
VSL
Weibull
distribution
(
with
parameters
of
location
=
0,
scale
=
5.32,
shape
=
1.51)
was
incorporated
into
the
benefits
model
using
a
Monte
Carlo
simulation.
This
allows
quantification
of
the
uncertainty
surrounding
benefits
estimates.

Value
of
Avoiding
the
Morbidity
Increment
of
a
Fatal
Case
of
Bladder
Cancer
The
VSL
represents
the
value
of
avoiding
a
premature
death.
This
valuation,
however,
does
not
take
into
account
the
medical
costs
associated
with
the
period
of
illness
(
morbidity
increment)
leading
up
to
death.
In
its
review
of
the
Arsenic
Rule,
the
SAB
suggested
that
the
appropriate
measure
to
use
in
valuing
the
avoidance
of
the
morbidity
increment
is
the
medical
cost
attributable
to
a
cancer
case
(
USEPA
10
Previous
EPA
analyses
(
Stage
1
DBPR
and
Arsenic
Rule)
used
the
WTP
value
for
avoiding
a
case
of
chronic
bronchitis
for
benefits
transfer
calculations.
The
SAB
review
of
the
Arsenic
benefits
analysis
identified
the
curable
lymphoma
WTP
value
as
another
metric
that
could
be
used
in
benefits
valuation
because
"...
the
endpoint
being
valued
more
nearly
corresponds
to
nonfatal
bladder
cancer..."
(
USEPA
2001k).
The
SAB
suggested,
however,
that
calculations
using
the
WTP
for
chronic
bronchitis
also
be
presented.
Based
on
this
recommendation,
values
derived
using
both
the
WTP
for
curable
lymphoma
and
chronic
bronchitis
are
presented
throughout
the
analysis.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
66
July
2003
2001k).
Based
on
available
medical
data,
EPA
estimates
the
medical
costs
for
a
fatal
bladder
cancer
case
to
be
$
93,927
at
1996
price
levels
(
USEPA
1999a).
This
medical
cost
value
(
updated
to
2000
price
levels)
is
applied
as
a
point
estimate
to
each
fatal
case
of
bladder
cancer
in
the
benefits
model.

Value
of
Avoiding
a
Non­
fatal
Case
of
Bladder
Cancer
For
a
case
of
non­
fatal
bladder
cancer,
a
Willingness
to
Pay
(
WTP)
measure
is
used
to
estimate
what
a
person
would
be
willing
to
pay
to
reduce
the
risk
of
developing
a
case
of
cancer.
The
reduced
risk
that
the
WTP
represents
accounts
for
the
desire
to
avoid
treatment
costs,
pain
and
discomfort,
productivity
losses,
and
any
other
adverse
consequences
related
to
contraction
of
a
non­
fatal
case
of
bladder
cancer.
As
is
the
case
with
VSL
valuation,
the
cumulative
WTP
for
this
risk
reduction
across
an
exposed
population
can
be
used
to
represent
the
statistical
value
of
avoiding
the
illness
itself.
This
WTP
value
is
a
more
comprehensive
measure
of
the
total
value
that
a
person
would
place
on
avoiding
a
cancer
case
than
the
much
simpler
cost
of
illness
(
COI)
measure.

A
review
of
the
available
literature
did
not
reveal
any
studies
that
specifically
measured
the
WTP
to
avoid
risks
of
contracting
non­
fatal
cases
of
bladder
cancer.
Instead,
two
estimates
of
WTP
to
avoid
non­
fatal
bladder
cancer
are
used:
one
based
on
avoiding
a
case
of
curable
lymph
cancer
(
lymphoma)
and
the
other
based
on
avoiding
a
case
of
for
chronic
bronchitis10.
Results
using
both
WTP
estimates
are
presented
throughout
the
remainder
of
the
analyses.

The
WTP
to
avoid
the
risk
of
contracting
curable
lymphoma
is
derived
from
a
survey
by
Magat
et
al.
(
1996)
that
evaluates
the
risk­
risk
trade­
off
between
curable
lymphoma
and
death
using
a
reference
lottery
metric.
A
reference
lottery
metric
is
a
methodology
that
educates
survey
respondents
of
the
health
consequences
of
a
particular
disease
(
in
this
case
curable
lymphoma)
and,
based
on
this
information,
presents
them
with
choices
related
to
health
outcomes.
The
choices
in
health
outcomes
made
by
the
respondents
can
be
further
evaluated
to
derive
quantitative
measures
of
relative
risk
aversion.
Based
on
the
outcomes
of
the
Magat
et
al.
study,
it
was
determined
that
the
median
risk­
risk
trade­
off
(
relative
risk
aversion)
for
contracting
a
curable
case
of
lymphoma
was
equivalent
to
58.3
percent
of
the
risk
attributed
to
reducing
the
chances
of
facing
a
sudden
death
(
i.
e.,
the
average
person
would
pay
58.3
percent
of
what
they
would
pay
to
reduce
the
risk
of
sudden
death
to
achieve
an
equal
risk
reduction
for
contracting
curable
lymphoma).
Based
on
the
Magat
et
al.
study
results,
EPA
calculated
a
WTP
distribution
for
nonfatal
bladder
cancer
as
a
percentage
of
the
VSL
distribution,
resulting
in
a
mean
WTP
value
of
$
2.8
million
($
4.8
million
*
58.3
percent)
at
1990
price
levels
(
see
Appendix
F,
section
F.
1
for
additional
information
on
the
derivation
of
this
WTP
estimate).

The
distribution
of
WTP
values
for
avoiding
the
risk
of
chronic
bronchitis
are
consistent
with
those
defined
for
the
Stage
1
DBPR.
This
distribution
is
best
represented
by
a
lognormal
distribution
with
a
mean
of
$
587,500,
standard
deviation
of
$
264,826,
and
a
maximum
value
of
$
1.5
million
at
1998
price
values
(
USEPA
1998a;
Viscusi
et
al.
1991).

Although
the
WTP
to
avoid
curable
lymphoma
or
chronic
bronchitis
is
not
a
perfect
substitute
for
the
WTP
to
avoid
a
case
of
non­
fatal
bladder
cancer,
it
is
a
very
reasonable
value
to
use
in
a
benefits
transfer
methodology.
Non­
fatal
internal
cancers,
regardless
of
type,
generally
present
patients
with
very
similar
treatment,
health,
and
long­
term
quality
of
life
implications,
including
surgery,
radiation
or
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
67
July
2003
Mean
Median
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

Morbidity
Increment
1996
0.1
$
1.14
0.1
$
N/
A
N/
A
N/
A
VSL
1990
4.8
$
1.32
6.3
$
5.5
$
1.0
$
14.5
$

WTP
­
Non­
Fatal
Lymphoma
1990
2.8
$
1.32
3.7
$
3.2
$
0.6
$
8.5
$

WTP
­
Chronic
Bronchitis
1998
0.6
$
1.06
0.6
$
0.6
$
0.3
$
1.1
$
CPI
Update
Factor
Values
at
Year
2000
Price
Level
(
Millions)

Valuation
Parameter
Base
Year
Mean
Value
in
Base
Year
(
Millions)
chemotherapy
treatments
(
with
attendant
side
effects),
and
generally
diminished
vitality
over
the
duration
of
the
illness.
In
the
absence
of
more
specific
WTP
studies,
the
WTP
values
for
avoiding
a
case
of
curable
lymphoma
or
a
case
of
chronic
bronchitis
provides
a
reasonable,
though
not
definitive,
substitute
for
the
value
of
avoiding
non­
fatal
bladder
cancer.

Updating
Price
Levels
All
valuation
parameters
must
be
updated
to
the
same
price
level
so
comparisons
can
be
made
in
real
terms.
Values
for
VSL,
WTP,
and
the
morbidity
increment
used
in
the
model
are
updated
based
on
adjustment
factors
derived
from
Bureau
of
Labor
Statistics
(
BLS)
consumer
price
index
(
CPI)
data
so
that
each
represents
a
year
2000
price
level.
Exhibit
5.24
presents
these
updates.

Exhibit
5.24
VSL,
WTP,
and
Morbidity
Increment
Price
Level
Updates
Notes:
Morbidity
increment
value
is
presented
as
a
point
estimate.

Source:
Derived
from
Appendix
F
(
Exhibits
F.
1a
and
F.
1b).

Adjustments
for
Real
Income
Growth
and
Elasticity
Although
the
price
level
(
year
2000)
is
held
constant
throughout
the
benefits
model,
projections
of
benefits
in
future
years
are
subject
to
income
elasticity
adjustments.
Income
elasticity
adjustments
represent
changes
in
valuation
in
relation
to
changes
in
real
income.
For
example,
if,
for
every
1
percent
increase
in
real
income,
a
particular
consumer's
WTP
for
a
particular
item
increases
by
1
percent,
this
would
be
represented
by
an
income
elasticity
of
1.
For
most
items,
income
elasticity
values
are
actually
less
than
1,
indicating
that
valuation
of
most
items
does
not
increase
as
fast
as
real
income
levels.

Based
on
an
evaluation
of
the
income
elasticity
literature,
Kleckner
and
Neuman
(
2000)
identified
published
studies
from
which
elasticity
values
could
be
derived
for
both
fatal
and
non­
fatal
potential
health
effects.
For
fatal
cancers,
they
identified
a
triangular
distribution
with
a
central
estimate
of
0.40
(
low
end:
0.08;
high
end:
1.00)
to
best
represent
the
uncertainty
of
that
income
elasticity
value.
For
nonfatal
cancers,
a
triangular
distribution
with
a
central
estimate
of
0.45
(
low
end:
0.25;
high
end:
0.60)
best
represents
the
value.
These
distributions
are
used
as
assumptions
in
the
Monte
Carlo
simulation
to
further
characterize
uncertainty
in
benefits
estimates.

In
order
to
apply
the
income
elasticity
values
in
the
model,
they
must
be
combined
with
projections
of
real
income
growth
over
the
time
frame
for
analysis.
Population
and
real
gross
domestic
11
Ideally,
income
elasticity
measurements
would
be
calculated
using
real
per
capita
personal
income
growth.
However,
real
per
capita
GDP
is
used
as
a
proxy
for
real
per
capita
personal
income
growth
due
to
lack
of
appropriate
data
projections
for
real
personal
income
growth.
Historical
data
suggests
that
GDP
and
personal
income
grow
at
similar
rates
(
i.
e.,
Table
B­
31
of
the
2002
Economic
Report
of
the
President
shows
that
both
real
per
capita
GDP
and
disposable
personal
income
grew
at
an
average
annual
rate
of
2.3
percent
between
1959
and
2000).

12
See
Appendix
A
of
Kleckner
and
Neuman
(
2000)
for
additional
information
on
the
derivation
and
application
of
income
elasticity
adjustments.

13
The
distribution
of
VSL
values
used
in
this
EA
is
derived
based
on
a
meta­
analysis
of
26
different
VSL
studies,
all
representing
different
year
price
levels.
These
price
levels
were
updated
to
a
common
1990
price
level
as
part
of
the
analysis
in
"
The
Benefits
and
Costs
of
the
Clean
Air
Act,
1970­
1990"
(
USEPA
1997b),
from
which
the
distribution
used
in
this
EA
is
taken.

14
Because
the
morbidity
increment
reflects
a
point
estimate
of
direct
medical
costs
and
income
elasticity
figures
used
in
this
analysis
are
based
on
WTP
values,
income
elasticity
adjustments
were
not
applied
to
the
projected
morbidity
increment
values
(
only
the
CPI
update
factor
is
applied).

15
A
25­
year
analysis
time
frame
was
chosen
to
reflect
the
period
before
which
most
systems
would
need
to
reinvest
in
capital
equipment
replacement
(
a
20­
year
useful
life
is
assumed
for
the
analysis).
Since
the
benefits,
as
derived
in
this
analysis,
are
a
result
of
installing
treatment
equipment,
this
time
frame
was
also
applied
to
benefits
projections.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
68
July
2003
product
(
GDP)
projections
are
combined
to
calculate
per­
capita
real
GDP
values.
11
Percent
changes
in
these
values
over
time
can
then
be
combined
with
income
elasticity
figures
to
derive
a
single
adjustment
factor.
12
Given
any
two
time
periods,
this
factor
can
be
calculated
as
follows:

Income
elasticity
adjustment
factor
=
(
eI
1
­
eI
2
­
I
2
­
I
1)
/
(
eI
2
­
eI
1
­
I
2
­
I
1)

where:
e
=
income
elasticity
I
1
=
real
income
(
per­
capita
GDP)
in
the
base
year
I
2
=
real
income
(
per­
capita
GDP)
in
the
year
of
analysis
Income
elasticity
adjustment
factors
are
calculated
from
the
same
base
year
as
the
values
subject
to
adjustment.
For
example,
income
elasticity
factors
for
fatal
cancers
are
calculated
from
a
1990
base
year
because
that
is
the
base
year
used
in
the
study
from
which
VSL
estimates
are
derived.
13
The
mean
values
of
the
income
adjustment
factors
calculated
for
the
Stage
2
benefits
model
range
from
1.131
to
1.460
for
fatal
cancer
valuation
and
1.114
to
1.393
for
non­
fatal
valuation
over
the
25­
year
analysis
time
frame
(
Appendix
F
presents
detailed
spreadsheets
of
these
calculations).
The
adjusted
yearly
values
for
the
VSL
and
WTP
(
at
a
2000
price
level)
are
then
calculated
by
multiplying
the
base
value
of
each
by
the
appropriate
income
elasticity
adjustment
factor.
14
Exhibit
5.25
presents
the
results
of
the
income
elasticity
adjustments
for
the
25
year
analysis
time
frame.
15
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
69
July
2003
Morbidity
Increment
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
0.1
$
7.2
$
6.2
$
1.1
$
16.4
$
4.2
$
3.6
$
0.6
$
9.6
$
0.7
$
0.7
$
0.3
$
1.3
$

2004
0.1
$
7.2
$
6.3
$
1.1
$
16.6
$
4.2
$
3.7
$
0.7
$
9.7
$
0.7
$
0.7
$
0.3
$
1.4
$

2005
0.1
$
7.3
$
6.4
$
1.1
$
16.8
$
4.3
$
3.7
$
0.7
$
9.8
$
0.8
$
0.7
$
0.3
$
1.4
$

2006
0.1
$
7.4
$
6.4
$
1.1
$
17.0
$
4.3
$
3.8
$
0.7
$
9.9
$
0.8
$
0.7
$
0.3
$
1.4
$

2007
0.1
$
7.5
$
6.5
$
1.2
$
17.2
$
4.4
$
3.8
$
0.7
$
10.0
$
0.8
$
0.7
$
0.3
$
1.4
$

2008
0.1
$
7.6
$
6.6
$
1.2
$
17.4
$
4.4
$
3.8
$
0.7
$
10.1
$
0.8
$
0.7
$
0.4
$
1.4
$

2009
0.1
$
7.7
$
6.7
$
1.2
$
17.6
$
4.5
$
3.9
$
0.7
$
10.3
$
0.8
$
0.7
$
0.4
$
1.4
$

2010
0.1
$
7.8
$
6.7
$
1.2
$
17.8
$
4.5
$
3.9
$
0.7
$
10.4
$
0.8
$
0.7
$
0.4
$
1.4
$

2011
0.1
$
7.8
$
6.8
$
1.2
$
18.0
$
4.6
$
4.0
$
0.7
$
10.5
$
0.8
$
0.7
$
0.4
$
1.5
$

2012
0.1
$
7.9
$
6.9
$
1.2
$
18.2
$
4.6
$
4.0
$
0.7
$
10.6
$
0.8
$
0.7
$
0.4
$
1.5
$

2013
0.1
$
8.0
$
7.0
$
1.2
$
18.4
$
4.7
$
4.1
$
0.7
$
10.7
$
0.8
$
0.7
$
0.4
$
1.5
$

2014
0.1
$
8.1
$
7.1
$
1.3
$
18.6
$
4.7
$
4.1
$
0.7
$
10.8
$
0.8
$
0.8
$
0.4
$
1.5
$

2015
0.1
$
8.2
$
7.1
$
1.3
$
18.8
$
4.8
$
4.2
$
0.7
$
11.0
$
0.8
$
0.8
$
0.4
$
1.5
$

2016
0.1
$
8.3
$
7.2
$
1.3
$
19.0
$
4.8
$
4.2
$
0.7
$
11.1
$
0.8
$
0.8
$
0.4
$
1.5
$

2017
0.1
$
8.4
$
7.3
$
1.3
$
19.2
$
4.9
$
4.3
$
0.8
$
11.2
$
0.8
$
0.8
$
0.4
$
1.5
$

2018
0.1
$
8.5
$
7.4
$
1.3
$
19.4
$
4.9
$
4.3
$
0.8
$
11.3
$
0.9
$
0.8
$
0.4
$
1.6
$

2019
0.1
$
8.6
$
7.5
$
1.3
$
19.6
$
5.0
$
4.3
$
0.8
$
11.5
$
0.9
$
0.8
$
0.4
$
1.6
$

2020
0.1
$
8.7
$
7.5
$
1.3
$
19.9
$
5.1
$
4.4
$
0.8
$
11.6
$
0.9
$
0.8
$
0.4
$
1.6
$

2021
0.1
$
8.8
$
7.6
$
1.4
$
20.1
$
5.1
$
4.4
$
0.8
$
11.7
$
0.9
$
0.8
$
0.4
$
1.6
$

2022
0.1
$
8.9
$
7.7
$
1.4
$
20.3
$
5.2
$
4.5
$
0.8
$
11.8
$
0.9
$
0.8
$
0.4
$
1.6
$

2023
0.1
$
9.0
$
7.8
$
1.4
$
20.5
$
5.2
$
4.5
$
0.8
$
12.0
$
0.9
$
0.8
$
0.4
$
1.6
$

2024
0.1
$
9.1
$
7.9
$
1.4
$
20.8
$
5.3
$
4.6
$
0.8
$
12.1
$
0.9
$
0.8
$
0.4
$
1.7
$

2025
0.1
$
9.2
$
8.0
$
1.4
$
21.0
$
5.3
$
4.6
$
0.8
$
12.2
$
0.9
$
0.8
$
0.4
$
1.7
$

2026
0.1
$
9.3
$
8.0
$
1.4
$
21.2
$
5.4
$
4.7
$
0.8
$
12.4
$
0.9
$
0.8
$
0.4
$
1.7
$

2027
0.1
$
9.4
$
8.1
$
1.4
$
21.4
$
5.5
$
4.7
$
0.8
$
12.5
$
0.9
$
0.9
$
0.4
$
1.7
$

Notes:

Source:
All
values
in
millions
of
year
2000
dollars.
VSL
Fatal
Cancer
Cases
WTP
­
Chronic
Bronchitis
WTP
­
Non­
Fatal
Lymphoma
Year
Point
Estimate
Mean
Value
90
Percent
Confidence
Bound
Non­
Fatal
Cancer
Cases
Values
derived
based
on
valuation
distributions
and
inflation
(
CPI)
and
income
elasticity
factors
from
Exhibits
F.
1a,
F.
1b,
and
F.
1e.
Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.
Mean
Value
Mean
Value
Median
Value
90
Percent
Confidence
Bound
Median
Value
Median
Value
90
Percent
Confidence
Bound
Exhibit
5.25
Value
of
Morbidity
Increment,
VSL,
and
WTP
by
Year
16
Although
the
2
and
17
percent
PAR
values
are
used
throughout
this
section,
EPA
recognizes
that
the
lower
bound
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

17
See
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j)
for
a
full
discussion
of
the
use
of
social
discount
rates
in
the
evaluation
of
policy
decisions.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
70
July
2003
5.6.3
Value
of
Benefits
Resulting
from
the
Stage
2
DBPR
for
the
Preferred
Alternative
To
assess
the
total
value
of
benefits
resulting
from
the
Stage
2
DBPR,
both
the
qualitative
and
quantitative
benefits
must
be
considered.
Although
information
is
not
sufficient
to
quantify
the
value
of
preventing
potential
adverse
reproductive
and
developmental
health
effects
in
the
primary
benefits
analysis,
the
number
of
cases
avoided
and
associated
value
could
be
significant
(
see
Section
5.9).
Likewise,
the
value
of
other
health
and
non­
health
benefits
could
be
substantial.
Thus,
the
primary
benefits
analysis
is
a
conservative
quantification
of
the
total
benefits
of
this
regulation.

To
calculate
the
total
value
of
benefits
derived
from
reductions
in
bladder
cancer
cases
as
a
result
of
the
Stage
2
DBPR,
a
stream
of
estimated
monetary
benefits
is
calculated
by
combining
the
annual
cases
avoided
(
Exhibit
5.21)
with
valuation
inputs
(
Exhibit
5.25)
using
Monte
Carlo
simulation.
Use
of
a
Monte
Carlo
simulation
allows
the
characterization
of
uncertainty
around
final
modeling
outputs
based
on
the
uncertainty
underlying
the
various
valuation
inputs.
The
Stage
2
DBPR
benefits
model
uses
distributions
of
VSL,
WTP,
and
income
elasticity
values
to
attribute
monetary
values
(
with
uncertainty
bounds)
to
the
number
of
bladder
cancer
cases
avoided.
The
values
for
cancer
cases
avoided
at
both
the
2
and
17
percent
PAR
values16
and
for
both
WTP
estimates
(
for
curable
lymphoma
and
chronic
bronchitis)
were
calculated
and
carried
through
the
Stage
2
DBPR
benefits
model.
The
results
for
fatal,
non­
fatal,
and
total
benefits
are
presented
in
Exhibits
5.26
(
note
that
the
analysis
assumptions,
e.
g.
2
%
PAR
WTP
for
Lymphoma,
are
in
the
table
headings).

Calculating
and
Discounting
the
Stream
of
Benefits
To
allow
comparison
of
future
streams
of
costs
and
benefits,
it
is
common
practice
to
adjust
both
streams
to
a
present
value
(
PV)
using
a
social
discount
rate.
This
process
takes
into
account
the
time
preference
that
society
places
on
expenditures
and
benefits
and
allows
comparison
of
cost
and
benefit
streams
that
vary
over
a
given
time
period.
17
A
present
value
for
any
future
period
can
be
calculated
using
the
following
equation:

PV
=
V(
t)
/
(
1
+
R)
t
Where:
t
=
The
number
of
years
from
the
reference
period
(
year
0
of
the
benefits
stream)
R
=
Social
discount
rate
V(
t)
=
The
benefits
occurring
t
years
from
the
reference
period
There
is
much
discussion
among
economists
of
the
proper
social
discount
rate
to
use
for
policy
analysis.
Therefore,
for
Stage
2
DBPR
benefits
analyses,
PV
calculations
are
made
using
two
social
discount
rates
thought
to
best
represent
current
policy
evaluation
methodologies,
3
and
7
percent.
Historically,
the
use
of
3
percent
is
based
on
rates
of
return
on
relatively
risk­
free
investments,
as
described
in
the
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j).
The
rate
of
7
percent
is
a
recommendation
of
OMB
as
an
estimate
of
"
before­
tax
rate
of
return
to
incremental
private
investment"
(
USEPA
1996b).
To
allow
evaluation
on
an
annual
basis,
the
total
PV
of
benefits
are
annualized
using
the
same
social
discount
rates.
Exhibit
5.27
presents
the
annualized
present
value
of
estimated
benefits
for
the
Stage
2
DBPR
over
the
25­
year
time
frame
for
analysis.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
71
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2004
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2005
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2006
4.4
$
3.9
$
0.7
$
10.1
$
7.3
$
6.3
$
1.1
$
16.6
$
11.7
$
10.2
$
1.9
$
26.7
$

2007
10.7
$
9.3
$
1.8
$
24.3
$
17.5
$
15.2
$
2.7
$
40.1
$
28.2
$
24.5
$
4.5
$
64.4
$

2008
18.0
$
15.7
$
3.0
$
41.0
$
29.5
$
25.6
$
4.6
$
67.6
$
47.5
$
41.3
$
7.6
$
108.6
$

2009
26.1
$
22.7
$
4.3
$
59.4
$
42.7
$
37.1
$
6.6
$
97.9
$
68.9
$
59.9
$
11.0
$
157.3
$

2010
34.8
$
30.3
$
5.8
$
79.1
$
57.0
$
49.5
$
8.8
$
130.5
$
91.8
$
79.8
$
14.6
$
209.7
$

2011
44.0
$
38.3
$
7.3
$
100.1
$
72.0
$
62.6
$
11.2
$
165.0
$
116.0
$
100.9
$
18.5
$
265.1
$

2012
49.2
$
42.8
$
8.2
$
111.8
$
80.5
$
70.0
$
12.5
$
184.4
$
129.7
$
112.8
$
20.6
$
296.3
$

2013
52.9
$
46.1
$
8.8
$
120.4
$
86.7
$
75.3
$
13.4
$
198.5
$
139.6
$
121.4
$
22.2
$
318.9
$

2014
56.0
$
48.7
$
9.3
$
127.3
$
91.7
$
79.7
$
14.2
$
210.0
$
147.6
$
128.4
$
23.5
$
337.3
$

2015
58.3
$
50.8
$
9.7
$
132.7
$
95.6
$
83.1
$
14.8
$
218.9
$
153.9
$
133.9
$
24.5
$
351.6
$

2016
60.3
$
52.6
$
10.0
$
137.3
$
98.9
$
85.9
$
15.3
$
226.5
$
159.2
$
138.5
$
25.3
$
363.8
$

2017
62.1
$
54.1
$
10.3
$
141.3
$
101.8
$
88.5
$
15.8
$
233.2
$
163.9
$
142.6
$
26.0
$
374.5
$

2018
63.7
$
55.5
$
10.5
$
145.0
$
104.4
$
90.8
$
16.2
$
239.2
$
168.1
$
146.2
$
26.7
$
384.2
$

2019
65.2
$
56.8
$
10.8
$
148.4
$
106.9
$
92.9
$
16.5
$
244.8
$
172.1
$
149.7
$
27.3
$
393.2
$

2020
66.6
$
58.0
$
11.0
$
151.6
$
109.2
$
94.9
$
16.9
$
250.1
$
175.8
$
152.9
$
27.9
$
401.7
$

2021
67.9
$
59.2
$
11.2
$
154.6
$
111.4
$
96.8
$
17.2
$
255.1
$
179.3
$
156.0
$
28.5
$
409.7
$

2022
69.2
$
60.3
$
11.4
$
157.5
$
113.5
$
98.6
$
17.6
$
260.0
$
182.7
$
158.9
$
29.0
$
417.5
$

2023
70.4
$
61.3
$
11.6
$
160.3
$
115.5
$
100.4
$
17.9
$
264.6
$
185.9
$
161.7
$
29.5
$
424.9
$

2024
71.6
$
62.4
$
11.8
$
163.1
$
117.5
$
102.1
$
18.2
$
269.2
$
189.1
$
164.5
$
30.0
$
432.2
$

2025
72.8
$
63.4
$
12.0
$
165.7
$
119.4
$
103.8
$
18.5
$
273.6
$
192.2
$
167.2
$
30.5
$
439.3
$

2026
74.0
$
64.4
$
12.2
$
168.3
$
121.3
$
105.4
$
18.8
$
277.9
$
195.3
$
169.8
$
31.0
$
446.3
$

2027
75.1
$
65.4
$
12.3
$
170.9
$
123.2
$
107.1
$
19.1
$
282.2
$
198.2
$
172.4
$
31.4
$
453.1
$

Total
1,173.6
$
1,022.0
$
194.0
$
2,670.0
$
1,923.2
$
1,671.6
$
297.8
$
4,406.2
$
3,096.7
$
2,693.5
$
491.8
$
7,076.2
$
Mean
Value
Median
Value
Mean
Value
Median
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Non­
Fatal
Cases
Total
2%
Estimate
of
PAR,
WTP
for
Lymphoma
as
the
Basis
for
Non­
Fatal
Cases
Fatal
Cases
Year
Mean
Value
Median
Value
90
Percent
Confidence
Bound
Exhibit
5.26
Non­
discounted
Stream
of
Benefits
from
the
Stage
2
DBPR
Preferred
Regulatory
Alternative,
All
Systems,
TTHM
as
Indicator
Notes:
All
values
in
millions
of
year
2000
dollars.
Detail
may
not
add
to
totals
due
to
independent
rounding.
EPA
recognizes
that
the
lower
bound
estimate
of
benefits
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

Source:
Exhibit
F.
2u.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
72
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2004
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2005
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2006
38.8
$
33.8
$
6.5
$
88.1
$
63.4
$
55.1
$
9.8
$
145.3
$
102.2
$
88.9
$
16.3
$
233.4
$

2007
93.4
$
81.3
$
15.6
$
212.2
$
152.8
$
132.8
$
23.6
$
350.0
$
246.1
$
214.1
$
39.2
$
562.2
$

2008
157.3
$
137.0
$
26.2
$
357.6
$
257.4
$
223.7
$
39.8
$
589.7
$
414.7
$
360.7
$
66.1
$
947.4
$

2009
227.9
$
198.5
$
37.9
$
518.1
$
373.0
$
324.2
$
57.7
$
854.5
$
600.9
$
522.7
$
95.7
$
1,372.7
$

2010
303.8
$
264.6
$
50.5
$
690.6
$
497.2
$
432.1
$
77.0
$
1,139.1
$
801.0
$
696.7
$
127.5
$
1,829.8
$

2011
384.1
$
334.5
$
63.8
$
873.3
$
628.7
$
546.4
$
97.3
$
1,440.4
$
1,012.8
$
880.9
$
161.2
$
2,313.7
$

2012
429.1
$
373.7
$
71.3
$
975.8
$
702.6
$
610.6
$
108.8
$
1,609.7
$
1,131.7
$
984.4
$
180.0
$
2,585.5
$

2013
461.9
$
402.2
$
76.7
$
1,050.3
$
756.3
$
657.3
$
117.1
$
1,732.7
$
1,218.1
$
1,059.6
$
193.7
$
2,783.0
$

2014
488.5
$
425.4
$
81.0
$
1,110.9
$
800.0
$
695.3
$
123.8
$
1,832.8
$
1,288.4
$
1,120.7
$
204.9
$
2,943.8
$

2015
509.2
$
443.4
$
84.4
$
1,158.1
$
834.0
$
724.9
$
129.1
$
1,910.7
$
1,343.2
$
1,168.3
$
213.5
$
3,068.9
$

2016
526.7
$
458.7
$
87.2
$
1,198.0
$
862.8
$
749.9
$
133.6
$
1,976.7
$
1,389.4
$
1,208.6
$
220.8
$
3,174.7
$

2017
542.1
$
472.1
$
89.7
$
1,233.2
$
888.2
$
772.0
$
137.5
$
2,034.9
$
1,430.3
$
1,244.1
$
227.2
$
3,268.1
$

2018
556.1
$
484.3
$
92.0
$
1,265.2
$
911.2
$
792.1
$
141.1
$
2,087.8
$
1,467.4
$
1,276.3
$
233.1
$
3,353.0
$

2019
569.1
$
495.6
$
94.1
$
1,294.8
$
932.6
$
810.6
$
144.4
$
2,136.8
$
1,501.7
$
1,306.2
$
238.5
$
3,431.6
$

2020
581.3
$
506.2
$
96.0
$
1,322.7
$
952.8
$
828.1
$
147.5
$
2,182.9
$
1,534.0
$
1,334.3
$
243.5
$
3,505.5
$

2021
592.9
$
516.3
$
97.9
$
1,349.2
$
971.9
$
844.8
$
150.5
$
2,226.8
$
1,564.8
$
1,361.0
$
248.3
$
3,575.9
$

2022
604.0
$
526.0
$
99.6
$
1,374.6
$
990.3
$
860.7
$
153.3
$
2,268.8
$
1,594.3
$
1,386.7
$
253.0
$
3,643.4
$

2023
614.8
$
535.3
$
101.3
$
1,399.1
$
1,008.0
$
876.1
$
156.1
$
2,309.5
$
1,622.8
$
1,411.4
$
257.4
$
3,708.6
$

2024
625.2
$
544.4
$
103.0
$
1,423.0
$
1,025.3
$
891.1
$
158.8
$
2,349.0
$
1,650.5
$
1,435.5
$
261.7
$
3,772.0
$

2025
635.4
$
553.2
$
104.6
$
1,446.3
$
1,042.1
$
905.8
$
161.4
$
2,387.6
$
1,677.5
$
1,459.0
$
266.0
$
3,833.9
$

2026
645.4
$
561.9
$
106.2
$
1,469.2
$
1,058.6
$
920.1
$
163.9
$
2,425.5
$
1,704.0
$
1,482.0
$
270.1
$
3,894.7
$

2027
655.2
$
570.5
$
107.7
$
1,491.7
$
1,074.9
$
934.3
$
166.5
$
2,462.8
$
1,730.2
$
1,504.7
$
274.2
$
3,954.5
$

Total
10,242.2
$
8,918.9
$
1,693.3
$
23,302.0
$
16,783.9
$
14,588.1
$
2,598.6
$
38,454.2
$
27,026.1
$
23,507.0
$
4,291.9
$
61,756.2
$
Mean
Value
Median
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Median
Value
90
Percent
Confidence
Bound
Mean
Value
Median
Value
Year
17%
Estimate
of
PAR,
WTP
for
Lymphoma
as
the
Basis
for
Non­
Fatal
Cases
Total
Fatal
Cases
Non­
Fatal
Cases
Mean
Value
Exhibit
5.26
Non­
discounted
Stream
of
Benefits
from
the
Stage
2
DBPR
Preferred
Regulatory
Alternative,
All
Systems,
TTHM
as
Indicator
(
cont.)

Notes:
All
values
in
millions
of
year
2000
dollars.
Detail
may
not
add
to
totals
due
to
independent
rounding.
EPA
recognizes
that
the
lower
bound
estimate
of
benefits
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

Source:
Exhibit
F.
2u.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
73
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2004
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2005
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2006
4.4
$
3.9
$
0.7
$
10.1
$
1.3
$
1.2
$
0.6
$
2.3
$
5.7
$
5.0
$
1.3
$
12.4
$

2007
10.7
$
9.3
$
1.8
$
24.3
$
3.1
$
2.8
$
1.4
$
5.6
$
13.8
$
12.1
$
3.2
$
29.9
$

2008
18.0
$
15.7
$
3.0
$
41.0
$
5.2
$
4.8
$
2.3
$
9.4
$
23.2
$
20.5
$
5.3
$
50.4
$

2009
26.1
$
22.7
$
4.3
$
59.4
$
7.5
$
6.9
$
3.4
$
13.7
$
33.6
$
29.6
$
7.7
$
73.0
$

2010
34.8
$
30.3
$
5.8
$
79.1
$
10.0
$
9.2
$
4.5
$
18.2
$
44.8
$
39.5
$
10.3
$
97.3
$

2011
44.0
$
38.3
$
7.3
$
100.1
$
12.6
$
11.6
$
5.7
$
23.0
$
56.6
$
49.9
$
13.0
$
123.1
$

2012
49.2
$
42.8
$
8.2
$
111.8
$
14.0
$
12.9
$
6.3
$
25.7
$
63.2
$
55.7
$
14.5
$
137.5
$

2013
52.9
$
46.1
$
8.8
$
120.4
$
15.1
$
13.9
$
6.8
$
27.6
$
68.0
$
60.0
$
15.6
$
147.9
$

2014
56.0
$
48.7
$
9.3
$
127.3
$
15.9
$
14.7
$
7.2
$
29.1
$
71.9
$
63.4
$
16.5
$
156.4
$

2015
58.3
$
50.8
$
9.7
$
132.7
$
16.6
$
15.3
$
7.5
$
30.3
$
74.9
$
66.1
$
17.1
$
163.0
$

2016
60.3
$
52.6
$
10.0
$
137.3
$
17.1
$
15.8
$
7.7
$
31.3
$
77.4
$
68.3
$
17.7
$
168.6
$

2017
62.1
$
54.1
$
10.3
$
141.3
$
17.6
$
16.2
$
7.9
$
32.2
$
79.7
$
70.3
$
18.2
$
173.5
$

2018
63.7
$
55.5
$
10.5
$
145.0
$
18.0
$
16.6
$
8.1
$
33.0
$
81.7
$
72.1
$
18.6
$
177.9
$

2019
65.2
$
56.8
$
10.8
$
148.4
$
18.4
$
17.0
$
8.3
$
33.7
$
83.6
$
73.7
$
19.0
$
182.1
$

2020
66.6
$
58.0
$
11.0
$
151.6
$
18.7
$
17.3
$
8.4
$
34.4
$
85.3
$
75.3
$
19.4
$
186.0
$

2021
67.9
$
59.2
$
11.2
$
154.6
$
19.1
$
17.6
$
8.6
$
35.0
$
87.0
$
76.7
$
19.8
$
189.6
$

2022
69.2
$
60.3
$
11.4
$
157.5
$
19.4
$
17.9
$
8.7
$
35.7
$
88.6
$
78.1
$
20.1
$
193.2
$

2023
70.4
$
61.3
$
11.6
$
160.3
$
19.7
$
18.2
$
8.9
$
36.2
$
90.2
$
79.5
$
20.5
$
196.6
$

2024
71.6
$
62.4
$
11.8
$
163.1
$
20.0
$
18.5
$
9.0
$
36.8
$
91.7
$
80.8
$
20.8
$
199.8
$

2025
72.8
$
63.4
$
12.0
$
165.7
$
20.3
$
18.7
$
9.1
$
37.3
$
93.1
$
82.1
$
21.1
$
203.0
$

2026
74.0
$
64.4
$
12.2
$
168.3
$
20.6
$
19.0
$
9.3
$
37.8
$
94.5
$
83.4
$
21.4
$
206.2
$

2027
75.1
$
65.4
$
12.3
$
170.9
$
20.9
$
19.3
$
9.4
$
38.4
$
95.9
$
84.6
$
21.7
$
209.3
$

Total
1,173.6
$
1,022.0
$
194.0
$
2,670.0
$
330.8
$
304.9
$
148.9
$
606.7
$
1,504.4
$
1,326.9
$
342.9
$
3,276.8
$
Mean
Value
Median
Value
Mean
Value
Median
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Non­
Fatal
Cases
Total
2%
Estimate
of
PAR
WTP
for
Chronic
Bronchitis
as
the
Basis
for
Non­
Fatal
Cases
Fatal
Cases
Year
Mean
Value
Median
Value
90
Percent
Confidence
Bound
Exhibit
5.26
Non­
discounted
Stream
of
Benefits
from
the
Stage
2
DBPR
Preferred
Regulatory
Alternative,
All
Systems,
TTHM
as
Indicator
(
cont.)

Notes:
All
values
in
millions
of
year
2000
dollars.
Detail
may
not
add
to
totals
due
to
independent
rounding.
EPA
recognizes
that
the
lower
bound
estimate
of
benefits
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

Source:
Exhibit
F.
3u.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
74
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2004
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2005
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

2006
38.8
$
33.8
$
6.5
$
88.1
$
11.2
$
10.3
$
5.0
$
20.4
$
49.9
$
44.0
$
11.5
$
108.5
$

2007
93.4
$
81.3
$
15.6
$
212.2
$
26.8
$
24.7
$
12.1
$
49.0
$
120.2
$
106.0
$
27.7
$
261.3
$

2008
157.3
$
137.0
$
26.2
$
357.6
$
45.1
$
41.5
$
20.4
$
82.5
$
202.4
$
178.5
$
46.6
$
440.1
$

2009
227.9
$
198.5
$
37.9
$
518.1
$
65.3
$
60.1
$
29.4
$
119.3
$
293.2
$
258.6
$
67.4
$
637.4
$

2010
303.8
$
264.6
$
50.5
$
690.6
$
86.9
$
80.0
$
39.2
$
158.7
$
390.6
$
344.6
$
89.7
$
849.4
$

2011
384.1
$
334.5
$
63.8
$
873.3
$
109.6
$
101.0
$
49.4
$
200.7
$
493.7
$
435.5
$
113.3
$
1,073.9
$

2012
429.1
$
373.7
$
71.3
$
975.8
$
122.3
$
112.7
$
55.1
$
224.1
$
551.5
$
486.5
$
126.4
$
1,199.9
$

2013
461.9
$
402.2
$
76.7
$
1,050.3
$
131.5
$
121.2
$
59.2
$
240.6
$
593.3
$
523.4
$
135.9
$
1,291.0
$

2014
488.5
$
425.4
$
81.0
$
1,110.9
$
138.8
$
128.0
$
62.6
$
254.1
$
627.3
$
553.4
$
143.6
$
1,365.1
$

2015
509.2
$
443.4
$
84.4
$
1,158.1
$
144.5
$
133.2
$
65.0
$
264.6
$
653.6
$
576.6
$
149.4
$
1,422.7
$

2016
526.7
$
458.7
$
87.2
$
1,198.0
$
149.2
$
137.6
$
67.1
$
273.2
$
675.9
$
596.2
$
154.3
$
1,471.2
$

2017
542.1
$
472.1
$
89.7
$
1,233.2
$
153.3
$
141.4
$
69.0
$
280.9
$
695.4
$
613.5
$
158.7
$
1,514.1
$

2018
556.1
$
484.3
$
92.0
$
1,265.2
$
157.0
$
144.8
$
70.6
$
287.8
$
713.1
$
629.1
$
162.6
$
1,553.0
$

2019
569.1
$
495.6
$
94.1
$
1,294.8
$
160.4
$
147.9
$
72.1
$
294.1
$
729.5
$
643.5
$
166.2
$
1,588.9
$

2020
581.3
$
506.2
$
96.0
$
1,322.7
$
163.6
$
150.8
$
73.5
$
300.3
$
744.8
$
657.0
$
169.5
$
1,622.9
$

2021
592.9
$
516.3
$
97.9
$
1,349.2
$
166.5
$
153.5
$
74.9
$
305.8
$
759.4
$
669.7
$
172.8
$
1,654.9
$

2022
604.0
$
526.0
$
99.6
$
1,374.6
$
169.3
$
156.1
$
76.2
$
311.2
$
773.4
$
682.0
$
175.8
$
1,685.7
$

2023
614.8
$
535.3
$
101.3
$
1,399.1
$
172.1
$
158.6
$
77.4
$
316.3
$
786.8
$
693.9
$
178.7
$
1,715.5
$

2024
625.2
$
544.4
$
103.0
$
1,423.0
$
174.7
$
161.1
$
78.5
$
321.1
$
799.9
$
705.4
$
181.5
$
1,744.1
$

2025
635.4
$
553.2
$
104.6
$
1,446.3
$
177.2
$
163.4
$
79.8
$
325.7
$
812.6
$
716.6
$
184.4
$
1,772.0
$

2026
645.4
$
561.9
$
106.2
$
1,469.2
$
179.6
$
165.7
$
80.9
$
330.2
$
825.0
$
727.6
$
187.1
$
1,799.4
$

2027
655.2
$
570.5
$
107.7
$
1,491.7
$
182.0
$
168.0
$
81.9
$
334.8
$
837.3
$
738.5
$
189.6
$
1,826.4
$

Total
10,242.2
$
8,918.9
$
1,693.3
$
23,302.0
$
2,886.8
$
2,661.4
$
1,299.2
$
5,295.2
$
13,129.0
$
11,580.2
$
2,992.5
$
28,597.2
$
Mean
Value
Median
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Median
Value
90
Percent
Confidence
Bound
Mean
Value
Median
Value
Year
17%
Estimate
of
PAR
WTP
for
Chronic
Bronchitis
as
the
Basis
for
Non­
Fatal
Cases
Total
Fatal
Cases
Non­
Fatal
Cases
Mean
Value
Exhibit
5.26
Non­
discounted
Stream
of
Benefits
from
the
Stage
2
DBPR
Preferred
Regulatory
Alternative,
All
Systems,
TTHM
as
Indicator
(
cont.)

Notes:
All
values
in
millions
of
year
2000
dollars.
Detail
may
not
add
to
totals
due
to
independent
rounding.
EPA
recognizes
that
the
lower
bound
estimate
of
benefits
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

Source:
Exhibit
F.
3u.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
75
July
2003
Exhibit
5.27
Benefits
Summary
for
the
Stage
2
DBPR,
Preferred
Regulatory
Alternative
(
Millions,
2000$)

Adverse
Reproductive
and
Developmental
Health
Effects
Avoided
Causality
has
not
been
established,
and
numbers
and
types
of
cases
avoided,
as
well
as
the
value
of
such
cases,
were
not
quantified
in
the
primary
benefits
analysis.
Given
the
numbers
of
women
of
child
bearing
age
exposed
(
58
million),
the
evidence
indicates
that
the
number
of
cases
and
the
value
of
preventing
those
cases
could
be
significant.
See
results
of
the
illustrative
calculation
in
Section
5.9
Number
and
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
1
Causality
has
not
been
established;
however,
the
weight
of
evidence
supports
PAR
estimates
of
potential
benefits.
Zero
is
within
the
range
of
potential
benefits,
but
evidence
indicates
that
both
the
number
of
cases
and
the
value
of
preventing
those
cases
could
be
significant
(
see
below).

PAR
Annual
Average
Cases
Avoided
Discount
Rate,
WTP
for
Non­
Fatal
Cases
Annualized
Benefits
of
Cases
Avoided
(
90
%
Confidence
Bounds
2)

Value
of
Fatal
Cases
Avoided
Value
of
Non­
Fatal
Cases
Avoided
Value
of
Total
Cases
Avoided
2
%
20.9
3
%,
Lymphoma
$
42.8
($
7.1
­
97.4)
$
70.2
($
10.9
­
160.7)
$
113.0
($
17.9
­
258.2)

7
%
Lymphoma
$
37.1
($
6.1
­
84.4)
$
60.8
($
9.4
­
139.3)
$
97.9
($
15.6
­
223.7)

3
%
Bronchitis
$
42.8
($
7.1
­
97.4)
$
12.1
($
5.4
­
22.2)
$
54.9
($
12.5
­
119.6)

7
%
Bronchitis
$
37.1
($
6.1
­
84.4)
$
10.5
($
4.7
­
19.2)
$
47.6
($
10.9
­
103.7)

17
%
182.2
3
%,
Lymphoma
$
373.8
($
61.8
­
850.3)
$
612.4
($
94.8
­
1,403.1)
$
986.2
($
156.6
­
2,253.4)

7
%
Lymphoma
$
323.9
($
53.6
­
736.7)
$
530.6
($
82.1
­
1,215.6)
$
854.4
($
135.8
­
1.952.3)

3
%
Bronchitis
$
373.8
($
61.8
­
850.3)
$
105.5
($
47.5
­
193.5)
$
479.3
($
109.3
­
1.043.7)

7
%
Bronchitis
$
323.9
($
53.6
­
736.7)
$
91.6
($
41.2
­
167.9)
$
415.5
($
94.9
­
904.6)

Other
Health
Benefits
Qualitative
assessment
indicates
that
the
value
of
other
health
benefits
could
be
positive
and
significant.

Non­
Health
Benefits
Qualitative
assessment
indicates
that
the
value
of
non­
health
benefits
could
be
positive.
Notes:
Detail
may
not
add
to
totals
due
to
independent
rounding.
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
Summarized
from
detailed
figures
presented
in
Appendix
E
(
Exhibits
E.
17d
and
E.
17g)
and
F
(
Exhibits
F.
2v
and
F.
2w,
F.
3v
and
F.
3w).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
76
July
2003
5.6.4
Comparison
of
the
Value
of
Benefits
for
Regulatory
Alternatives
This
section
compares
the
benefits
of
decreasing
DBP
occurrence
under
the
Stage
2
DBPR
preferred
alternative
with
the
three
evaluated
alternatives.
The
alternatives
are
summarized
below
(
see
Chapter
4
for
a
more
detailed
discussion):

Preferred
Alternative:
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
as
an
LRAA;
bromate
MCL
of
10
µ
g/
L
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point
(
no
change
from
the
Stage
1
DBPR
for
bromate).

Alternative
1:
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
as
an
LRAA;
bromate
MCL
of
5
µ
g/
L
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point.

Alternative
2:
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
as
the
single
maximum
value
for
any
sample
taken
during
the
year;
bromate
MCL
of
10
µ
g/
L
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point
(
no
change
from
the
Stage
1
DBPR
for
bromate).

Alternative
3:
40
µ
g/
L
TTHM
and
30
µ
g/
L
HAA5
as
an
RAA
of
all
distribution
samples
taken;
bromate
MCL
of
10
µ
g/
L
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point
(
no
change
from
the
Stage
1
DBPR
for
bromate).

Exhibit
5.28
compares
the
value
of
benefits
for
all
Stage
2
DBPR
regulatory
alternatives,
using
TTHM
as
an
indicator
for
reduction
in
all
DBPs.
Although
the
primary
objective
of
the
Stage
2
DBPR
is
to
reduce
the
unquantified
risks
of
adverse
potential
reproductive
and
developmental
health
effects,
the
exhibit
also
shows
that
the
quantified
benefits
of
reducing
cancer
cases
are
considerable
regardless
of
which
alternative
is
chosen.
Chapter
6
examines
the
costs
of
these
Alternatives,
and
Chapter
9
compares
the
benefits
and
costs
of
the
alternatives.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
77
July
2003
Exhibit
5.28
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
All
Stage
2
DBPR
Regulatory
Alternatives
(
Millions,
2000$)
1
Discount
Rate,
WTP
for
Non­
Fatal
Cases
Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
2%
PAR
Average
Annual
Number
of
Cases
Avoided
21
22
135
161
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
113
($
18
­
258)
$
117
($
19
­
268)
$
773
($
116
­
1,675)
$
873
($
139
­
1,995)

7
%
Lymphoma
$
98
($
16
­
224)
$
102
($
16
­
232)
$
636
($
101
­
$
1,452)
$
757
($
120
­
1,730)

3
%
Bronchitis
$
55
($
13
­
120)
$
57
(
13
­
124)
$
356
($
81
­
776)
$
424
($
97
­
924)

7
%
Bronchitis
$
48
($
11
­
104)
$
49
($
11
­
108)
$
309
($
71
­
673)
$
368
($
84
­
802)

17%
PAR
Value
Average
Number
of
Cases
Avoided
182
189
1,182
1,408
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
986
($
157
­
2,253)
$
1,024
($
163
­
2340)
$
6,398
($
1,016
­
14,619)
$
7,621
($
1,211
­
17,415)

7
%
Lymphoma
$
854
($
136
­
1,952)
$
887
($
141
­
2,027)
$
5,546
($
881
­
12,672)
$
6,607
($
1,050
­
15,097)

3
%
Bronchitis
$
479
($
109
­
1,044)
$
498
($
114
­
1084)
$
3,109
($
709
­
6771)
$
3,704
($
845
­
8,066)

7
%
Bronchitis
$
415
($
95
­
905)
$
431
($
99
­
940)
$
2,697
($
616
­
5,871)
$
3,213
($
734
­
6,995)
Notes:
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
Summarized
from
detailed
figures
presented
in
Appendix
E
(
Exhibits
E.
17d
and
g,
E.
19d
and
g,
E.
20d
and
g,
E.
21d
and
g)
and
Appendix
F
(
Exhibits
F.
2v
and
w,
F.
3v
and
w,
F.
6d
and
e,
F.
7d
and
e,
F.
8d
and
3,
F.
9d
and
e,
F.
10d
and
e,
F.
11d
and
e).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
78
July
2003
5.7
Uncertainties
In
addition
to
the
uncertainties
quantified
as
part
of
the
benefits
evaluation,
there
are
other
uncertainties
that
could
result
in
either
an
over­
or
under­
estimation
of
the
benefits
presented
in
this
chapter.
Exhibit
5.29
presents
a
summary
of
these
issues,
references
the
section
or
appendix
where
the
information
is
introduced,
and
estimates
the
potential
effects
that
each
may
have
on
national
benefits
estimates.
Two
of
the
greatest
uncertainties
affecting
the
benefits
of
the
Stage
2
DBPR
are
related
to
unquantified
benefits
estimates,
as
indicated
by
a
bold
"
X"
in
Exhibit
5.29.
Both
of
these
factors
result
in
an
underestimation
of
quantified
Stage
2
DBPR
benefits.
Another
area
of
uncertainty
is
the
effect
of
the
IDSE
on
the
compliance
forecast
 
this
uncertainty
is
addressed
in
a
sensitivity
analysis
in
Chapter
7.

In
addition
to
the
uncertainties
listed
in
Exhibit
5.29,
the
potential
costs
or
benefits
of
a
possible
interactive
effect
from
the
promulgation
of
more
than
one
rule
in
a
short
period
of
time
are
also
unquantified.
EPA
has
taken
into
account
compliance
with
the
Stage
1
DBPR
and
considered
the
potential
impacts
of
the
Ground
Water
Rule,
the
Arsenic
Rule,
and
the
LT2ESWTR,
but
has
not
attempted
to
estimate
the
cumulative
effects
of
the
passage
of
other
new
regulations
along
with
the
Stage
2
DBPR.

5.8
Sensitivity
Analyses
To
quantify
the
effects
that
differences
in
major
modeling
assumptions
would
have
on
the
benefits
analysis,
sensitivity
analyses
were
performed.
This
sections
presents
results
for
one
analysis:
the
elimination
of
cessation
lag
calculations.
Additional
sensitivity
analyses
were
performed
to
evaluate
the
impact
of
uncertainties
in
the
compliance
forecast
(
e.
g.,
related
to
impacts
of
the
initial
distribution
system
evaluation,
consecutive
systems,
etc.)
on
benefits
estimates.
Results
for
these
sensitivity
analyses
are
presented
in
Chapter
7.

To
gauge
the
magnitude
of
the
impact
on
benefits
valuation
stemming
from
incorporation
of
cessation
lag
assumption
into
the
model,
the
cessation
lag
computation
was
taken
out
of
the
model,
keeping
all
other
parameters
the
same.
Thus,
the
risk
and
associated
cases
avoided
were
assumed
to
reach
a
new
equilibrium
immediately
upon
installation
of
treatment
equipment.
The
summary
results
of
this
analysis
are
also
shown
in
Exhibit
5.30
(
Appendix
F
contains
detailed
spreadsheets
of
case
reductions
and
valuations
by
year).
This
sensitivity
analysis
shows
that
removal
of
the
cessation
lag
assumptions
from
the
model
results
in
an
increase
of
benefits
by
approximately
40
to
60
percent
from
the
values
shown
in
the
primary
analysis,
depending
on
the
PAR
value
and
discount
rate
used.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
5­
79
July
2003
Exhibit
5.29
Uncertainties
and
Possible
Effect
on
Estimate
of
Benefits
Uncertainty
Section
with
Full
Discussion
of
Uncertainty
Effect
on
Benefit
Estimate
Underestimate
Overestimate
Unknown
Impact
Uncertainty
in
data
quality
of
model
inputs
and
assumptions
for
SWAT
Appendix
A
X
Accuracy
of
the
SWAT
DBP
predictions
and
technology
selections
Appendix
A
X
Uncertainty
in
deriving
percent
DBP
reductions
for
ground
water
and
small
surface
water
systems
from
SWAT
data.
Appendix
A
Section
4.2
X
20%
operational
safety
factor
in
assessing
plant
compliance
Appendix
A,
Appendix
B
X
Value
of
potential
reproductive
and
developmental
health
effects
avoided
is
not
quantified
in
the
primary
analysis
5.6.1
X
Analysis
of
reduction
in
DBP
occurrence
does
not
include
results
of
IDSE
5.4
X
Benefits
of
reduced
cancers
other
than
bladder
cancer
are
not
included
in
the
quantitative
analysis
5.5
X
DBPs
have
a
linear
dose­
response
relationship
for
bladder
cancer
effects
5.5
X
Analysis
of
exposure
reduction
assumes
TTHM
and
HAA5
to
be
proxies
for
all
chlorination
DBPs
5.5
X
SWAT's
predicted
DBP
reduction
from
Stage
1
to
Stage
2
are
good
representations
of
occurrence
levels
for
all
systems
(
adjusted
for
percent
non­
compliers)
5.4.2
X
Uncertainty
in
valuation
inputs
(
WTP
and
VSL
5.6
X
PAR
value
range
of
2­
17
percent
used
to
calculate
the
number
of
bladder
cancer
cases
avoided
is
not
absolute.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
5.2.2
X
Note:
Several
of
these
uncertainties
also
impact
costs
(
see
Chapter
6).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
5­
80
Exhibit
5.30
Comparison
of
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
Stage
2
DBPR
Sensitivity
Analysis
(
Millions,
2000$)

Discount
Rate,
WTP
for
Non­
Fatal
Cases
Preferred
Alternative
Sensitivity
Analysis
for
No
Cessation
Lag
and
No
Latency
2%
PAR
Average
Annual
of
Cases
Avoided
21
28
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
113
($
18
­
258)
$
153
($
24
­
349)

7
%
Lymphoma
$
98
($
16
­
224)
$
140
($
22
­
320)

3
%
Bronchitis
$
55
($
13
­
120)
$
74
($
17
­
162)

7
%
Bronchitis
$
48
($
11
­
104)
$
68
($
16
­
$
148)

17%
PAR
Value
Average
Number
of
Cases
Avoided
182
241
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
986
($
157
­
2,253)
$
1,334
($
212
­
3,048)

7
%
Lymphoma
$
854
($
136
­
1,952)
$
1,221
($
194
­
$
2,789)

3
%
Bronchitis
$
479
($
109
­
1,044)
$
649
($
148
­
1,413)

7
%
Bronchitis
$
415
($
95
­
905)
$
594
($
136
­
1,293)
Notes:
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
For
preferred
alternative,
see
Exhibit
5.27.
For
the
sensitivity
analysis,
quantitative
values
are
summarized
from
detailed
figures
presented
in
Appendix
E
(
Exhibits
E.
22d
and
g)
and
Appendix
F
(
Exhibits
F.
12d
and
e,
F.
13d
and
e).
18Use
of
unadjusted
OR/
RR
estimates
has
the
effect
of
excluding
possible
biases
from
known
confounders;
however,
EPA
believes
the
unadjusted
estimates
are
adequate
for
purposes
of
the
illustrative
calculations
presented
here
19The
calculated
lower
95%
confidence
intervals
on
PAR
for
all
three
studies
were
less
than
zero;
however,
they
were
truncated
at
zero
for
this
analysis.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
5­
81
5.9
Potential
Fetal
Losses
Avoided
EPA
concurs
with
the
conclusion
presented
by
Simmons
et
al.
(
2002)
that
"
the
epidemiologic
data,
although
not
conclusive,
are
suggestive
of
potential
developmental,
reproductive,
or
carcinogenic
health
effects
in
humans
exposed
to
DBPs."
EPA
does
not
believe
the
available
evidence
provides
an
adequate
basis
for
quantifying
potential
reproductive/
developmental
risks
(
see
Section
5.2.1
for
a
complete
discussion
of
the
reproductive
and
developmental
health
effects
of
DBPs).
Nevertheless,
given
the
widespread
nature
of
exposure
to
DBPs,
the
importance
our
society
places
on
reproductive/
developmental
health,
and
the
large
number
of
fetal
losses
experienced
each
year
in
the
US
(
nearly
1
million),
the
Agency
believes
that
it
is
important
to
provide
some
quantitative
indication
of
the
potential
risk
suggested
by
some
of
the
published
results
on
reproductive/
developmental
endpoints,
despite
the
absence
of
certainty
regarding
a
causal
link
between
disinfection
byproducts
and
these
risks.
To
do
this,
illustrative
PAR
calculations
from
several
studies
on
the
relationship
between
chlorinated
water
exposure
and
fetal
loss
have
been
adapted
and
applied
to
national
statistics
on
annual
incidence
of
fetal
loss
(
shown
in
section
5.9.1).
Section
5.9.2
discusses
valuation
of
these
potential
fetal
losses
avoided.

5.9.1
Reproductive
Effects
Illustrative
Calculation
EPA
has
calculated
the
unadjusted
Odds
Ratios
(
OR's)
or
Relative
Risks
(
RR's)
associated
with
each
of
the
three
distinct
population­
based
epidemiological
studies
of
fetal
loss
published:
Waller
et
al.
2001,
King
et
al.
2000a,
and
Savitz
et
al.
1995.
Exhibit
5.31
summarizes
these
studies
 
all
three
are
high
quality
studies
that
have
sufficient
sample
sizes
and
high
response
rates,
adjustments
for
known
confounders18,
and
have
exposure
assessment
information
from
water
treatment
data,
residential
histories,
and
THM
measurements.
Because
the
populations
in
these
three
studies
appear
to
have
TTHM
exposures
significantly
greater
than
those
of
the
general
US
population,
EPA
has
chosen
to
scale
the
results
using
ICR
data
to
derive
PAR
values
that
are
more
relevant
to
the
general
US
population
(
Appendix
G).

These
three
studies
(
using
unadjusted
data
to
allow
for
comparability,
and
scaled
to
the
TTHM
levels
reported
in
the
ICR
data
base)
yield
median
PARs
of
0.4%,
1.7%,
and
1.7%
(
with
95%
confidence
intervals
for
each
of
the
studies
of
0
to
4%
19).
Using
the
prevalence
of
fetal
loss
reported
by
CDC,
the
median
PARs
for
these
three
studies
suggest
that
the
incidence
of
fetal
loss
attributable
to
exposure
to
chlorinated
drinking
water
could
range
from
3,900
to
16,700
annually.
As
part
of
the
analysis
to
evaluate
potential
reduction
in
fetal
loss
for
the
Stage
2
DBPR,
EPA
assumed
that
reductions
in
risk
are
proportional
to
the
28
percent
reductions
in
the
number
of
locations
having
one
or
more
quarterly
TTHM
measurements
that
exceed
the
study
population
cut­
offs
(>
75
to
>
81
ug/
l,
depending
on
study).
This
analysis
would
imply
that
a
range
of
1,100
to
4,700
fetal
losses
could
be
avoided
per
year
as
a
result
of
the
Stage
2
DBPR.
Refer
to
Appendix
G
for
derivation
of
PARs
and
detailed
calculation
of
fetal
losses
avoided.

Caution
is
required
in
interpreting
the
numbers
derived
above
because
there
may
be
significant
differences
in
the
study
exposure
populations
versus
the
national
exposure
(
e.
g.,
different
types
of
DBP
mixtures
having
similar
TTHM
levels).
The
estimates
presented
here
are
not
part
of
EPA's
quantitative
benefits
analysis,
and
the
ranges
are
not
meant
to
suggest
upper
and
lower
bounds.
Rather,
they
are
intended
to
illustrate
quantitatively
the
potential
risk
implications
of
some
of
the
published
results.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
5­
82
Exhibit
5.31
Summary
of
the
Fetal
Loss
Human
Epidemiology
Studies
Study
Population
Exposure
Assessment
Outcome
Results1
Potential
Confounders
Waller
et
al.
2001
Prospective
cohort
of
4,209
pregnant
women
in
prepaid
health
plan
in
CA
1989­
91
Averaged
all
distribution
TTHM
measurements
taken
within
the
subjects
first
trimester
or
average
measurements
taken
within
30
days
of
first
trimester.
Spontaneous
abortion
(
#
20
weeks
of
gestation)
Recalculated
80mg/
L
compared
to
<
80
mg/
L
for
unweighted
utilitywide
average
RR=
1.25
(
0.99,1.6)

Study
based
prevalence
of
exposure
=
15%
Gestational
age
at
interview,
maternal
age,
cigarette
smoking,
history
of
pregnancy
loss,
maternal
race,
employment
during
pregnancy
King
et
al.
2000a
Populationbased
retrospective
cohort
of
47,275
births
in
Nova
Scotia,
Canada
1988­
1995
Linked
mother's
residence
at
time
of
delivery
to
the
levels
of
specific
TTHMs
monitored
in
the
PWS
and
averaged
predicted
values
of
byproduct
level
for
the
months
covering
the
pregnancy
Stillbirth
Recalculated
75
mg/
L
compared
to
<
75
mg/
L
RR=
1.28
(
95%
CI
0.98,
1.7)

Study
based
prevalence
of
exposure
=
32%
Smoking,
maternal
age
Savitz
et
al.
1995
Populationbased
casecontrol
study
of
126
cases
and
122
controls
in
NC
1988­
91
Fourth
week
of
pregnancy
used
to
assign
the
reported
quarterly
average
TTHM
Spontaneous
abortion
Recalculated
81
mg/
L
compared
to
<
81
mg/
L
OR=
1.06
(
0.6,1.8)

Study
based
prevalence
of
exposure
=
35%
Maternal
age,
race,
education,
marital
status,
poverty
level,
smoking,
alcohol
use,
nausea,
employment
1OR
and
RR
values
were
recalculated
using
crude
Odds
Ratios
for
the
fetal
loss
sensitivity
analysis.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
5­
83
5.9.2
Value
of
Reductions
in
Fetal
Losses
Avoided
EPA
has
not
monetized
the
value
of
potential
fetal
loss
but
recognizes
the
significant
value
of
improvement
in
developmental
and
reproductive
health.
See
section
5.6.1
for
a
discussion
of
the
value
of
reducing
reproductive
and
developmental
health
risks.

The
agency
is
investigating
further
work
specific
to
the
case
of
fetal
loss
valuation.
One
possible
area
of
further
research
is
the
value
that
prospective
parents
attach
to
reducing
risks
during
pregnancy.
In
this
regard,
the
substantial
lifestyle
changes
that
prospective
parents
often
undertake
during
pregnancy
suggests
that
reducing
these
kinds
of
risks
is
of
value.
A
second
possible
area
of
further
investigation
would
be
work
on
benefit
transfer
methodologies
that
address
how
existing
studies
can
inform
the
estimation
of
the
benefits
of
reduced
fetal
loss.

In
the
absence
of
valuation
studies
specific
to
the
health
endpoints
of
regulations,
the
Agency
typically
draws
upon
existing
studies
of
similar
health
endpoints
to
estimate
benefits.
The
"
transfer"
of
the
results
of
these
studies
to
value
similar
health
endpoints
must
be
done
carefully
and
methodically,
controlling
for
differences
in
the
health
endpoints
and
in
the
relevant
populations.
Some
researchers
have
attempted
to
transfer
values
using
sophisticated
analytical
techniques
such
as
preference
calibration
methods
(
e.
g.,
Smith,
et
al.
2002).
Regardless
of
the
approach
used,
"
benefit
transfer"
requires
systematic
comparison
of
the
similarities
and
differences
in
the
health
effects
in
the
studies
and
those
resulting
from
the
regulation.
Application
of
benefit
transfer
leads
to
a
detailed
qualitative
examination
of
the
implications
of
using
those
studies
and
potentially
to
empirical
adjustments
to
the
results
of
the
existing
studies.

Without
more
information
and
discussion
on
these
subjects,
EPA
cannot
fully
consider
and
describe
the
implications
of
relying
upon
existing
studies.
However,
research
on
valuation
and
benefit
transfer
continues
to
progress
and
the
Agency
anticipates
that
new
research
will
support
further
efforts
to
value
reproductive
and
developmental
endpoints.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
1
July
2003
6.
Cost
Analysis
6.1
Introduction
This
chapter
estimates
the
national
costs
of
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
National
costs
include
costs
of
implementation,
Initial
Distribution
System
Evaluations
(
IDSEs),
treatment
changes
(
capital
and
Operations
and
Maintenance
(
O&
M)),
additional
routine
monitoring,
and
significant
excursion
evaluations.

The
data
presented
in
this
chapter
are
derived
from
analyses
of
the
Information
Collection
Rule
(
ICR)
data,
ICR
Supplemental
Survey
data,
National
Rural
Water
Survey
data,
Surface
Water
Analytical
Tool
(
SWAT)
model
results,
the
American
Water
Works
Association
Water
Utility
Database
(
Water:\
STATS)
(
AWWA
2000),
State/
Primacy
Agency
data,
and
results
of
two
expert
opinion
processes
for
small
systems.
For
a
complete
explanation
of
these
data
sources,
see
Chapter
3
and
Appendices
A
and
B.

Section
6.1.1
of
this
chapter
summarizes
the
overall
methodology
and
data
inputs
used
to
estimate
total
national
costs.
Section
6.2
presents
a
summary
of
national
costs
along
with
the
estimated
number
of
systems
and
States/
Primacy
Agencies
expected
to
incur
treatment
and
non­
treatment
costs
as
a
result
of
the
various
Stage
2
DBPR
activities.
The
methodology
for
developing
non­
treatment
costs
and
breakouts
of
costs
for
different
activities
is
provided
in
Section
6.3.
Section
6.4
provides
a
detailed
description
of
the
methodology
for
estimating
treatment
costs.
Section
6.5
builds
on
the
nominal
cost
estimates
in
sections
6.3
and
6.4
by
projecting
them
over
a
25­
year
period
according
to
the
Stage
2
DBPR
compliance
schedule,
estimating
the
present
value
of
each
cost,
and
annualizing
each
over
a
25­
year
period.
Household
costs
are
presented
next
(
section
6.6),
followed
by
discussions
of
unquantified
costs
(
section
6.7),
uncertainty
(
section
6.8),
and
lastly,
comparison
of
regulatory
alternatives
(
section
6.9).

In
support
of
this
chapter:

°
Appendix
H
offers
a
more
complete
explanation
of
the
laboratory
costs
and
labor
hours
for
implementation,
IDSE,
and
additional
routine
monitoring,
as
well
as
the
assumptions
and
calculations
for
the
significant
excursion
evaluation
costs.

°
Appendices
A
and
B
explain
the
derivation
of
the
compliance
forecasts
(
i.
e.,
the
number
of
plants
changing
technology
and
which
technologies
they
select)
for
surface
water
and
disinfecting
ground
water
systems,
respectively.
Appendix
C
provides
supplemental
compliance
forecasts
for
the
Stage
1
DBPR
and
Stage
2
DBPR
regulatory
alternatives.

°
Appendix
D
contains
the
rule
implementation
schedule
for
different
system
types
and
rule
activities
(
used
in
projecting
and
annualizing
costs
over
a
25­
year
period).

°
Appendix
J
presents
additional
detail
for
technology
unit
costs.

°
Appendix
K
presents
cost
projections,
present
value
estimates,
and
annualization
of
costs
for
all
Stage
2
DBPR
regulatory
alternatives
and
sensitivity
analyses.

°
Appendix
L
contains
the
Stage
2
DBPR
cost
model.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
2
July
2003
6.1.1
Overview
of
Methodology
for
Quantifying
Stage
2
DBPR
Costs
To
estimate
the
national
costs
of
the
Stage
2
DBPR,
the
Environmental
Protection
Agency
(
EPA)
calculated
the
incremental
costs
to
be
incurred
by
public
water
systems
(
PWSs)
and
their
States/
Primacy
Agencies
from
the
Stage
1
DBPR
to
the
Stage
2
DBPR.
Cost
analyses
for
PWSs
include
an
identification
of
treatment
process
improvements
that
systems
may
make,
as
well
as
estimates
of
the
costs
to
implement
the
rule,
conduct
IDSEs,
perform
additional
routine
monitoring,
and
evaluate
significant
excursion
events.
System
costs
were
estimated
for
different
system
types
(
CWS
or
NTNCWS),
source
water
types
(
ground
or
surface),
and
size
categories
(
nine
size
categories
are
used
based
on
population
served,
consistent
with
the
drinking
water
Baseline
Handbook).
State/
Primacy
Agency
cost
analyses
include
estimates
of
the
labor
burdens
that
States/
Primacy
Agencies
would
face,
such
as
training
employees
on
the
requirements
of
the
Stage
2
DBPR,
responding
to
PWS
reports,
and
recordkeeping.

All
cost
calculations
are
performed
in
the
Stage
2
DBPR
Cost
Model
(
USEPA
2003j).
Exhibit
6.1
shows
the
major
components
of
the
model
and
illustrates
how
they
work
together.
The
model
is
made
up
of
a
number
of
Microsoft
®
Excel
2002
(
Excel)
workbooks
that
are
linked
to
each
other,
as
well
as
macros
and
other
functions
that
perform
the
various
cost
calculations.
Each
Excel
workbook
in
the
model
contains
an
introduction
sheet
describing
the
function
of
every
model
worksheet.
All
input
data
sources
are
referenced
to
their
source
documents.
Appendix
L
provides
the
model
documentation
along
with
a
CD
containing
all
the
data
files
and
models.
Sections
6.1.1.1
through
6.1.1.5
provide
a
brief
description
of
each
cost
model
component.
A
discussion
of
the
uncertainty
in
national
cost
estimates
follows
in
section
6.1.1.6.

6.1.1.1
Baseline
Data
Inputs
Baseline
data
inputs
include
the
number
and
size
of
systems
in
the
United
States,
the
percent
of
ground
water
systems
that
disinfect,
and
average
number
of
treatment
plants
per
system.
Derivations
of
the
water
industry
baselines
for
the
Stage
2
DBPR
are
discussed
in
Chapter
3.
As
noted
in
section
3.4,
EPA
uses
different
baselines
for
calculating
treatment
costs
versus
non­
treatment­
related
rule
activities
 
the
Stage
2
DBPR
System
Baseline
is
used
to
estimate
costs
of
non­
treatment
rule
activities
in
Appendix
H,
while
the
Stage
2
DBPR
Plant
Baseline
is
used
to
estimate
treatment
costs
in
section
6.4.
Both
the
system
and
plant
baselines
are
broken
out
by
system
and
source
water
type
and
size,
based
on
EPA's
nine
standard
size
categories
(
consistent
with
the
Drinking
Water
Baseline
Handbook;
USEPA,
2001h).
To
estimate
non­
treatment
costs
in
Appendix
H,
the
system
baseline
is
reorganized
into
different
system
size
categories
to
reflect
Stage
2
DBPR
monitoring
requirements.

In
addition
to
the
industry
baseline,
there
are
other
types
of
baseline
inputs
used
in
the
Stage
2
DBPR
Cost
Model.
The
derivation
of
two
of
these
inputs,
labor
rates
and
laboratory
fees,
are
discussed
in
detail
below.

Labor
Rates
Labor
costs
to
PWSs
presented
in
the
Stage
2
DBPR
Economic
Analysis
(
EA)
are
estimated
using
hourly
labor
rates
for
technical
and
managerial
labor
categories.
Labor
rates
representative
of
national
averages,
as
reported
by
the
Bureau
of
Labor
Statistics
(
BLS),
are
used
in
all
analyses.
For
technical
labor,
the
year
2000
mean
hourly
wage
rate
of
$
15.60
for
Standard
Occupational
Classification
(
SOC)
51­
8031,
"
Water
and
Liquid
Waste
Treatment
Plant
and
System
Operators,"
is
used.
For
managerial
labor,
the
year
2000
mean
hourly
wage
rate
of
$
28.07
for
SOC
17­
2051,
"
Civil
Engineers,"
is
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
3
July
2003
Baseline
Inputs
Technology
Unit
Costs
Technology
Selection
Forecasts
Cost
Models
Non­
Treatment
Cost
Model
Treatment
Cost
Model
Projections
and
Discounting
National
Costs
Household
Costs
Results
used
(
BLS
2001b).
To
account
for
the
cost
of
fringe
benefits,
a
60
percent
loading
factor
is
applied
to
each
of
the
BLS
rates,
resulting
in
a
technical
rate
of
$
24.96
per
hour
and
a
managerial
rate
of
$
44.91
per
hour.

Exhibit
6.1
Stage
2
DBPR
Cost
Model
Components
EPA
recognizes
that
there
may
be
significant
variation
in
labor
rates
among
PWSs.
However,
data
are
not
currently
available
that
would
allow
statistically
valid
assignment
of
labor
rates
to
specific
PWSs
based
on
characteristics
such
as
system
size
or
classification.
In
the
absence
of
such
data,
and
because
analyses
in
this
EA
are
performed
on
a
national
level,
the
BLS
data
are
used.
1
ECI
information
found
on
the
web
site
www.
bls.
gov.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
4
July
2003
Labor
costs
attributable
to
States/
Primacy
Agencies
are
estimated
based
on
an
average
annual
full­
time
equivalent
(
FTE)
labor
cost,
including
overhead,
of
$
55,000
(
1997$).
This
rate
was
established
based
on
State
input
during
the
development
of
the
State
Workload
Model
in
1997.
For
use
in
Stage
2
DBPR
EA
analyses,
the
$
55,000
annual
rate
was
updated
to
a
year
2000
price
level
of
$
60,086
using
Employment
Cost
Index
Information
(
ECI)
information1
and
converted
to
an
hourly
basis
(
1
FTE
=
2,080
hours)
to
establish
a
State/
Primacy
Agency
rate
of
$
28.89
per
hour.

Laboratory
Fees
A
laboratory
fee,
expressed
as
a
cost
per
sample,
is
associated
with
total
trihalomethane
(
TTHM)
and
haloacetic
acid
(
HAA5)
monitoring
costs
for
IDSE
and
additional
routine
monitoring.
Based
on
laboratory
costs
reported
in
the
1996
ICR,
EPA
estimated
the
laboratory
fee
at
$
220
per
sample
for
all
size
categories.
This
rate
includes
shipping
and
is
applied
to
all
systems
in
this
analysis
because
the
variation
is
not
expected
to
be
significant.
Some
of
the
factors
that
may
cause
this
rate
to
vary
in
practice
are
system
size,
the
number
of
samples
processed
(
quantity
discounts),
and
potential
limited
laboratory
capacity
for
the
one­
year
IDSE
monitoring.
For
example,
larger
plants
likely
have
laboratory
facilities
onsite
and
are
unlikely
to
face
shipment
costs.
Although
laboratory
costs
will
be
lower
for
multiple
samples,
there
are
no
estimates
of
the
number
of
systems
that
might
try
to
take
advantage
of
this
savings,
nor
which
laboratories
will
be
able
to
handle
the
large
number
of
samples
over
the
one­
year
period
of
IDSE
monitoring.
Laboratory
fees
are
not
expected
to
differ
substantially
between
disinfecting
ground
water
systems
and
surface
water
systems.

6.1.1.2
Technology
Unit
Costs
and
Technology
Selection
Forecasts
Available
technologies
for
reducing
DBPs
were
identified
during
the
Stage
2
Microbial­
Disinfectants/
Disinfection
Byproducts
(
M­
DBP)
Federal
Advisory
Committees
Act
(
FACA)
deliberations
(
USEPA
2000p).
These
include
alternative
disinfectants
such
as
ozone,
ultraviolet
light
(
UV),
and
chlorine
dioxide,
as
well
as
DBP
precursor
removal
technologies
such
as
microfiltration
or
ultrafiltration.
Converting
to
chloramines
for
residual
disinfection
was
also
identified
as
a
relatively
inexpensive
technology
that
can
limit
DBP
formation
in
many
distribution
systems.

Unit
cost
estimates
for
these
technologies
are
in
the
form
of
"
dollars
per
plant"
for
initial
capital
and
yearly
O&
M
activities.
Derivation
of
unit
costs
for
a
wide
range
of
plant
sizes,
represented
by
different
design
and
average
daily
flow
rates,
are
provided
in
the
document,
Technologies
and
Costs
for
Control
of
Microbial
Contaminants
and
Disinfection
Byproducts
(
USEPA
2003o).
EPA
uses
mean
design
and
average
daily
flow
for
each
of
the
nine
system
size
categories
(
shown
in
Exhibit
3.6)
to
estimate
unit
costs
for
each
technology
for
each
system
type,
source
water
type,
and
size
category.
This
process
is
described
in
detail
in
section
6.4.1.

Compliance
forecasts
(
or
technology
selection
forecasts)
are
estimates
of
how
many
plants
will
change
technology
to
meet
certain
regulatory
criteria
and
which
technologies
these
plants
will
select.

Section
3.3
provides
an
overview
of
the
tools
used
to
generate
the
compliance
forecasts.
A
detailed
description
of
the
derivation
of
the
forecasts
for
surface
and
ground
water
plants
are
in
Appendices
A
and
B,
respectively.
2
For
purposes
of
analyses
in
this
EA,
all
present
value
figures
are
presented
at
a
year
2000
price
level.

Present
value
calculations
are
performed
to
the
expected
year
rule
implementation
(
2003).

3
See
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j)
for
a
full
discussion
of
the
use
of
social
discount
rates
in
the
evaluation
of
policy
decisions.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
5
July
2003
6.1.1.3
Projections
and
Discounting
Nominal
cost
estimates
for
both
non­
treatment
and
treatment
activities
are
of
two
kinds:
(
1)
onetime
costs
that
occur
near
the
beginning
of
the
rule
implementation
period,
and
(
2)
annual
"
steady­
state"
costs
that
systems
and
States/
Primacy
Agencies
will
incur
after
systems
have
made
necessary
changes
to
treatment
and/
or
monitoring
to
comply
with
the
Stage
2B
DBPR.
For
the
purposes
of
this
EA,
onetime
and
steady­
state
costs
were
projected
over
a
25­
year
time
period
to
coincide
with
the
estimated
life
span
of
capital
equipment
(
typically
estimated
as
20
years
for
most
technologies)
and
an
average
time­
lag
of
up
to
five
years
for
technology
installation
after
rule
promulgation.
The
projected
schedules
for
all
rule
activities
are
summarized
in
Appendix
D.

As
described
previously
in
the
Chapter
5
discussion
of
benefits,
it
is
common
practice
to
adjust
benefits
and
costs
to
a
present
value2
using
a
social
discount
rate
so
that
they
can
be
compared
to
one
another.
This
process
takes
into
account
the
time
preference
that
society
places
on
expenditures
and
allows
comparison
of
cost
and
benefit
streams
that
are
variable
over
a
given
time
period.
3
Similar
to
calculating
the
present
value
of
benefits
(
see
section
5.6.3),
the
present
value
of
costs
for
any
future
period
can
be
calculated
using
the
following
equation:

PV
=
V(
t)
/
(
1
+
R)
t
Where:
t
=
The
number
of
years
from
the
reference
period
R
=
Social
discount
rate
V(
t)
=
The
cost
occurring
t
years
from
the
reference
period
There
is
much
discussion
among
economists
of
the
proper
social
discount
rate
to
use
for
policy
analysis.
Therefore,
for
Stage
2
DBPR
cost
analyses,
present
value
calculations
are
made
using
two
social
discount
rates
thought
to
best
represent
current
policy
evaluation
methodologies,
3
and
7
percent.
Historically,
the
use
of
a
3
percent
is
based
on
rates
of
return
on
relatively
risk­
free
investments,
as
described
in
the
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j).
The
rate
of
7
percent
is
a
recommendation
of
the
Office
of
Management
and
Budget
(
OMB)
as
an
estimate
of
"
before­
tax
rate
of
return
to
incremental
private
investment"
(
USEPA
1996b).
For
any
future
cost,
the
higher
the
discount
rate,
the
lower
the
present
value.
Specifically,
a
future
cost
(
or
stream
of
costs)
evaluated
at
a
7
percent
social
discount
rate
will
always
result
in
a
lower
total
present
value
cost
than
the
same
future
cost
evaluated
at
a
3
percent
rate.

To
allow
evaluation
on
an
annual
basis,
the
total
present
value
costs
are
annualized
using
the
same
social
discount
rates
(
3
and
7
percent)
over
25
years.
When
applying
social
discount
rates
to
annualize
costs,
the
higher
the
discount
rate,
the
higher
the
annualized
cost.
Thus,
the
magnitudes
of
the
discount
rates
influence
costs
in
the
opposite
direction
(
i.
e.,
a
present
value
cost
annualized
at
a
7
percent
rate
will
always
result
in
higher
values
than
the
same
present
value
cost
annualized
at
a
3
percent
rate).
The
final
relationship
between
annualized
costs
at
3
and
7
percent
is
dependent
on
the
time
frame
for
4
Cost­
of­
capital
estimates
are
used
to
account
for
interest
payments
that
PWSs
may
incur
and
pass
along
to
customers
in
the
form
of
water
bill
increases.
These
rates
may
be
different
than
social
discount
rates
(
3
and
7
percent)
used
elsewhere
in
the
economic
analysis.
Social
discount
rates
are
more
appropriate
for
estimating
economic
impacts
on
a
national
level.
See
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
USEPA
2000j)
for
a
full
discussion
of
the
use
of
social
discount
rates
in
the
evaluation
of
policy
decisions.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
6
July
2003
annualization,
as
well
as
when
the
costs
are
incurred
(
as
set
forth
in
the
Rule
Activity
Schedule
in
Appendix
D).
Given
a
long
enough
time
frame,
the
7
percent
annualized
value
will
eventually
be
greater
than
the
3
percent
annualized
value.

Values
derived
based
on
this
methodology
are
presented
in
subsequent
sections
of
Chapter
6.
Detailed
spreadsheets
of
all
cost
calculations
are
provided
in
Appendix
K.

6.1.1.4
Household
Costs
EPA
assumes
that
generally,
systems
may
pass
some
or
all
of
the
costs
of
a
new
regulation
on
to
their
customers
in
the
form
of
rate
increases.
Household
costs,
which
are
in
units
of
$
per
household
per
year,
are
estimated
in
this
chapter
to
provide
a
measure
of
the
increase
in
water
bills
that
is
expected
to
result
from
the
Stage
2
DBPR.
A
distribution
of
possible
household
costs
is
developed
within
each
system
size
category
depending
on
which
non­
treatment
activities
are
performed
and
which
treatment
is
selected,
if
any.
Data
inputs
specific
to
household
cost
calculations
are
shown
in
Exhibits
6.2.
A
description
of
the
household
cost
methodology
is
provided
below.

1)
The
number
of
households
served
per
plant
is
calculated
by
dividing
the
total
households
served
(
Exhibit
3.7)
by
the
total
number
of
plants
(
Exhibit
3.4).

2)
The
number
of
plants
performing
non­
treatment
and
treatment­
related
rule
activities
are
derived
in
section
6.4
and
Appendix
H
(
non­
treatment
activities
are
estimated
on
a
persystem
basis.
The
percent
of
systems
performing
non­
treatment­
related
rule
activities
are
assumed
to
be
equivalent
to
percent
of
plants
performing
those
activities).

3)
Costs­
of­
capital
rates
are
used
to
amortize
one­
time
costs
over
a
20­
year
period.
The
rates,
summarized
in
Exhibit
6.2,
are
derived
from
Development
of
Cost
of
Capital
Estimates
for
Public
Water
Systems,
Final
Report
(
USEPA
2001j).
4
Amortized
one­
time
costs
are
added
to
annual
costs
to
produce
annual
plant­
level
costs
for
each
technology
and
for
each
nontreatment
related
rule
activity
in
units
of
$
per
plant
per
year.

4)
Average
daily
flow
(
presented
in
Chapter
3,
Exhibit
3.6)
is
converted
to
1,000
gallons
per
plant
per
year
and
used
to
convert
$
per
plant
per
year
(
from
step
3)
to
$
per
1,000
gallons
per
year.

5)
Estimated
household
usage
rate
(
1,000
gallons
per
year)
is
used
to
convert
$
per
1,000
gallons
per
year
(
from
step
4)
to
$
per
household
per
year.
Exhibit
6.2
summarizes
the
mean
household
usage
rates
used
to
estimate
household
costs
in
this
chapter.
These
are
as
presented
in
the
Baseline
Handbook,
as
derived
from
the
1995
Community
Water
Systems
Survey
(
CWSS)
(
note
that
household
usage
rates
for
the
affordability
analysis
in
Chapter
8
are
median
values
from
1995
CWSS
data,
whereas
the
values
in
Exhibit
6.2
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
7
July
2003
Mean
Annual
Water
Usage
per
Household
(
1,000
gallons)
Public
Cost
of
Capital
Rate
Private
Cost
of
Capital
Rate
A
B
C
£
100
83
5.31%
6.22%
101­
500
83
5.31%
6.22%
501­
1,000
104
5.51%
6.22%
1,001­
3,300
87
5.51%
6.22%
3,301­
10,000
97
5.51%
6.22%
10,001­
50,000
109
5.20%
5.66%
50,001­
100,000
119
5.24%
6.27%
100,001­
1
Million
125
5.24%
6.27%
>
1
Million
125
5.24%
6.27%

Sources:
(
A)
Derived
from
the
Third
Edition
of
the
Baseline
Handbook
(
USEPA,
Table
C.
4.2.3,
all
systems.
Rates
for
systems
serving
<
500
people
revised
based
on
further
analysis
by
EPA.
(
B)
and
(
C)
Development
of
Cost
of
Capital
Estimates
for
Public
Water
Systems,
Final
Report
(
USEPA,
2001j).
System
Size
(
Population
Served)
are
mean
values).
EPA
recognizes
that
there
may
be
significant
variation
in
household
water
usage
between
specific
PWSs
(
table
C.
4.2.3
of
the
handbook
presents
confidence
intervals
around
these
estimates),
but
believes
that
mean
usage
rate
values
are
adequate
for
characterizing
household
costs.

6)
Estimates
of
$
per
household
per
year
(
step
5)
are
combined
with
number
of
households
incurring
costs
for
each
activity
(
step
2)
to
generate
distributions
of
possible
household
costs.

Exhibit
6.2
Household
Cost
Inputs
6.1.1.5
Modeled
Uncertainty
in
National
Costs
As
noted
throughout
this
EA,
EPA
recognizes
that
there
is
variability
among
many
of
the
input
parameters
to
the
Stage
2
DBPR
cost
model
(
e.
g.,
plants
per
system,
population
served,
flow
per
population,
labor
rates,
etc.).
In
most
cases,
there
is
insufficient
information
to
fully
characterize
the
distribution
of
variability
on
a
national
scale.
EPA
believes
that
mean
values
for
the
various
input
parameters
are
adequate
to
generate
EPA's
best
estimate
of
national
costs
for
the
rule.

EPA
recognizes
that
there
is
uncertainty
in
the
national
cost
estimates,
and
has
characterized
the
uncertainty
around
the
mean
unit
technology
costs
in
the
Stage
2
DBPR
cost
model.
To
simulate
the
effect
of
this
uncertainty
on
national
costs,
the
model
uses
the
"
Crystal
Ball"
program
to
perform
a
Monte
Carlo
simulation
in
Excel.
The
assumptions
for
modeling
uncertainty
in
unit
costs
are
described
in
section
6.4.1.
The
results
for
the
uncertainty
analysis
are
presented
in
the
form
of
90
percent
confidence
bounds
around
the
mean
total
national
cost
estimates.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
8
July
2003
6.2
Summary
of
the
National
Costs
of
the
Stage
2
DBPR
(
Preferred
Alternative)

This
section
presents
the
estimated
number
of
systems
expected
to
incur
costs
as
a
result
of
the
various
Stage
2
DBPR
activities.
It
also
summarizes
the
one­
time
costs
and
annualized
costs
of
the
rule.
Costs
are
broken
out
in
several
ways,
such
as
by
rule
activity,
type
of
system,
source
water
category,
and
system
size.
All
costs
presented
in
this
section
are
for
the
Preferred
Regulatory
Alternative
for
the
Stage
2
DBPR.
Cost
estimates
for
the
other
regulatory
alternatives
were
derived
using
the
same
methods
as
for
the
Preferred
Regulatory
Alternative
and
are
presented
in
section
6.9.

6.2.1
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
Exhibit
6.3
shows
the
baseline
number
of
systems
subject
to
the
Stage
2
DBPR
and
the
estimated
number
of
those
systems
performing
various
rule
activities
(
implementation,
IDSE
monitoring,
additional
routine
monitoring,
and
significant
excursion
evaluations).
Appendix
H
provides
the
derivation
of
these
values.

As
shown
in
Column
E,
only
69
percent
of
surface
water
and
7
percent
of
ground
water
community
water
systems
(
CWSs)
are
predicted
to
conduct
monitoring
as
part
of
the
IDSE
Standard
Monitoring
Program
(
SMP).
Systems
not
conducting
the
SMP
include
those
serving
fewer
than
500
people
that
receive
a
waiver
(
if
their
high
TTHM
and
HAA5
sites
are
in
the
same
location)
and
those
that
can
qualify
for
the
40/
30
certification
(
systems
with
all
Stage
1
DBPR
data
less
than
or
equal
to
40
µ
g/
L
TTHM
and
30
µ
g/
L
HAA5
are
eligible).
Systems
not
conducting
the
IDSE
SMP
also
include
those
that
perform
a
System­
Specific
Study
(
SSS)
instead
of
an
SMP.

EPA
estimates
that
some
surface
water
systems
serving
between
500
and
9,999
people
and
some
ground
water
systems
serving
between
500
to
99,999
people
will
conduct
additional
routine
monitoring
beyond
the
Stage
1
DBPR
requirements.
However,
the
number
of
compliance
monitoring
samples
for
some
consecutive
systems
will
be
reduced
from
the
Stage
1
DBPR
to
the
Stage
2
DBPR
because
requirements
for
some
systems
are
changing
from
plant­
based
requirements
to
population­
based
requirements
(
see
Appendix
H
for
a
detailed
discussion
of
additional
routine
monitoring).
EPA
estimates
that
a
minority
of
systems
(
approximately
16
percent
overall)
will
conduct
additional
routine
monitoring
beyond
the
Stage
1
DBPR
requirements.

Because
Stage
2
DBPR
compliance
is
based
on
an
annual
average
of
samples
collected
at
each
site,
EPA
expects
that
a
proportion
of
Stage
2­
compliant
systems
will
observe
DBP
concentrations
high
enough
to
trigger
the
requirement
for
a
significant
excursion
evaluation.
Column
H
shows
the
estimated
number
of
systems
that
may
conduct
significant
excursion
evaluations.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
9
July
2003
A
B
C=
B/
A*
100
D
E=
D/
A*
100
F
G=
F/
A*
100
H
I=
H/
A*
100
£
100
1,283
1,283
100%
289.2
23%
0.0
0%
0.0
0%
101­
500
2,120
2,120
100%
546.4
26%
42.5
2%
2.0
0%
501­
1,000
1,313
1,313
100%
1,179.3
90%
546.6
42%
26.2
2%
1,001­
3,300
2,467
2,467
100%
2,215.8
90%
1,027.0
42%
49.3
2%
3,301­
10,000
1,928
1,928
100%
1,722.8
89%
1,084.3
56%
42.3
2%
10,001­
50,000
1,690
1,690
100%
1,454.0
86%
0.0
0%
133.2
8%
50,001­
100,000
313
313
100%
255.3
82%
0.0
0%
40.6
13%
100,001­
1
Million
276
276
100%
213.3
77%
0.0
0%
41.1
15%
>
1
Million
13
13
100%
9.9
76%
0.0
0%
3.3
25%

National
Totals
11,403
11,403
100%
7,886
69%
2,700
24%
338
3%

£
100
7,601
7,601
100%
236.2
3%
0.0
0%
0.0
0%
101­
500
11,836
11,836
100%
392.6
3%
118.6
1%
0.0
0%
501­
1,000
4,089
4,089
100%
482.0
12%
1,691.9
41%
0.0
0%
1,001­
3,300
4,869
4,869
100%
573.9
12%
2,014.5
41%
0.0
0%
3,301­
10,000
2,288
2,288
100%
270.5
12%
946.6
41%
0.0
0%
10,001­
50,000
1,232
1,232
100%
218.0
18%
493.7
40%
0.0
0%
50,001­
100,000
129
129
100%
22.8
18%
51.6
40%
0.0
0%
100,001­
1
Million
60
60
100%
16.0
27%
22.8
38%
0.0
0%
>
1
Million
2
2
100%
1.0
50%
0.9
44%
0.0
0%
National
Totals
32,105
32,105
100%
2,213
7%
5,341
17%
0
0%

£
100
303
303
100%
0.0
0%
0.0
0%
0.0
0%
101­
500
302
302
100%
0.0
0%
0.0
0%
0.0
0%
501­
1,000
109
109
100%
0.0
0%
0.0
0%
0.0
0%
1,001­
3,300
74
74
100%
0.0
0%
0.0
0%
0.0
0%
3,301­
10,000
22
22
100%
0.0
0%
6.0
27%
0.0
0%
10,001­
50,000
9
9
100%
8.0
89%
4.0
44%
0.0
0%
50,001­
100,000
1
1
100%
1.0
100%
1.0
100%
0.0
0%
100,001­
1
Million
1
1
100%
1.0
100%
1.0
100%
0.0
0%
>
1
Million
0
0
­
0.0
­
0.0
­
0.0
­

National
Totals
821
821
100%
10
1%
12
1%
0
0%

£
100
3,662
3,662
100%
0.0
0%
0.0
0%
0.0
0%
101­
500
2,624
2,624
100%
0.0
0%
0.8
0%
0.0
0%
501­
1,000
717
717
100%
0.0
0%
5.1
1%
0.0
0%
1,001­
3,300
267
267
100%
0.0
0%
1.9
1%
0.0
0%
3,301­
10,000
27
27
100%
0.1
0%
0.3
1%
0.0
0%
10,001­
50,000
4
4
100%
0.9
19%
0.9
19%
0.0
0%
50,001­
100,000
0
0
100%
0.1
19%
0.1
19%
0.0
0%
100,001­
1
Million
1
1
100%
0.0
0%
0.0
0%
0.0
0%
>
1
Million
0
0
­
0.0
­
0.0
­
0.0
­
National
Totals
7,303
7,303
100%
1
0%
9
0%
0
0%

GRAND
TOTAL
51,632
51,632
100%
10,110
20%
8,062
16%
338
1%

Sources:
(
A)
Exhibit
3.3,
column
K.
Surface
Water
and
Mixed
CWSs
IDSE
Monitoring
Additional
Routine
Monitoring
System
Size
(
Population
Served)
Stage
2
DBPR
System
Baseline
Number
and
Percent
of
Systems
Performing
Various
Rule
Activities
Implementation
Significant
Excursion
Evaluations
Ground
Water
Only
CWSs
Surface
Water
and
Mixed
NTNCWSs
Ground
Water
Only
NTNCWSs
(
B),
(
D),
(
F),
and
(
H):
Appendix
H,
Exhibit
H.
14a.
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.
The
derivations
of
systems
affected
are
done
using
the
Stage
2B
monitoring
size
categories
(
see
section
H.
1
for
a
description
of
these
categories
and
rationale
for
their
use).
The
estimated
number
of
systems
performing
each
activity
by
the
monitoring
categories
(
as
summarized
in
Exhibit
H.
12)
are
apportioned
back
to
the
standard
9
size
categories
using
percentages.
Therefore,
the
number
of
systems
conducting
each
activity
shown
in
Columns
D,
E,
and
F
of
this
exhibit
are
fractions
in
some
cases.
Also,
Column
D
does
not
include
the
number
of
systems
performing
SSS's
(
refer
to
Appendix
H,
Exhibits
H.
4a
and
H.
4b
for
this
estimate).
Exhibit
6.3
Number
of
Systems
Subject
to
Non­
Treatment­
Related
Rule
Activities
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
10
July
2003
6.2.2
Plants
Adding
Treatment
Exhibit
6.4
shows
the
baseline
number
of
plants
and
the
estimated
percent
of
those
plants
adding
treatment.
The
estimated
percent
of
plants
adding
treatment
is
2.8
percent
for
all
systems
(
see
column
C,
"
Grand
Total
All
Plants"
in
Exhibit
6.4).
A
higher
percentage
of
surface
water
plants
are
predicted
to
add
treatment
compared
to
ground
water
plants.
However,
the
baseline
number
of
ground
water
plants
is
larger
than
that
of
surface
water
plants,
so
there
is
a
larger
number
of
ground
water
plants
adding
treatment.

Although
the
number
of
plants
adding
treatment
is
small,
treatment
costs
make
up
a
significant
portion
of
the
total
costs
of
the
rule
(
more
than
80
percent
of
total
rule
costs).
EPA
recognizes
that
the
number
of
plants
changing
technology
in
Exhibit
6.4
may
be
understated
because
plants
may
find
higher
TTHM
or
HAA5
concentrations
at
new
sites
identified
during
the
IDSE.
The
number
plants
adding
chloramines
or
advanced
technology,
however,
may
be
overstated
because
low­
cost
alternatives
(
such
as
changing
distribution
system
operations
or
consolidation
with
another
system)
were
not
considered.
Moreover,
EPA
believes
that
the
estimated
number
of
ground
water
and
small
surface
water
plants
adding
chloramines
or
changing
technology
may
be
biased
upward
because
their
monitoring
requirements
are
expected
to
be
very
similar
from
the
Stage
1
to
Stage
2
DBPR.
Chapter
7
provides
a
more
complete
discussion,
in
addition
to
a
quantitative
analysis
to
assess
the
effects
of
those
uncertainties.
It
is
not
known
in
which
direction
these
uncertainties
influence
the
estimates
in
Exhibit
6.4,
but
EPA
believes
this
net
impact
to
be
low.

6.2.3
Summary
of
One­
Time
Costs
One­
time
costs
for
systems
include
initial
capital,
implementation,
and
IDSE
costs.
State/
Primacy
Agency
costs
include
those
associated
with
implementation
and
IDSEs.
Exhibit
6.5
summarizes
estimated
total
initial
capital
and
other
one­
time
costs
of
the
Stage
2
DBPR
for
systems
and
States/
Primacy
Agencies.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
11
July
2003
System
Size
(
Population
Served)
Stage
2
DBPR
Plant
Baseline
A
B=
C*
A
C
£
100
470
21
4.4%
101­
500
799
26
3.3%
501­
1,000
505
17
3.3%
1,001­
3,300
1,103
41
3.7%
3,301­
10,000
1,213
45
3.7%
10,001­
50,000
1,287
75
5.8%
50,001­
100,000
538
31
5.8%
100,001­
1
Million
572
33
5.8%
>
1
Million
74
4
5.8%
National
Totals
6,560
293
4.5%

£
100
7,772
211
2.7%
101­
500
15,725
461
2.9%
501­
1,000
6,133
180
2.9%
1,001­
3,300
7,890
184
2.3%
3,301­
10,000
4,975
116
2.3%
10,001­
50,000
5,367
112
2.1%
50,001­
100,000
738
15
2.1%
100,001­
1
Million
875
17
1.9%
>
1
Million
18
0
1.9%
National
Totals
49,495
1,296
2.6%

£
100
298
13
4.4%
101­
500
301
10
3.3%
501­
1,000
108
4
3.3%
1,001­
3,300
72
3
3.7%
3,301­
10,000
23
1
3.7%
10,001­
50,000
9
1
5.8%
50,001­
100,000
1
0
5.8%
100,001­
1
Million
1
0
5.8%
>
1
Million
0
0
0.0%
National
Totals
813
31
3.8%

£
100
3,662
99
2.7%
101­
500
2,624
77
2.9%
501­
1,000
717
21
2.9%
1,001­
3,300
267
6
2.3%
3,301­
10,000
27
1
2.3%
10,001­
50,000
4
0
2.1%
50,001­
100,000
0
0
2.1%
100,001­
1
Million
1
0
1.9%
>
1
Million
0
0
0.0%
National
Totals
7,303
204
2.8%

Grand
Total
All
Plants
64,171
1,824
2.8%

Note:
Detail
may
not
add
to
totals
due
to
independent
rounding.

Sources:
(
A)
Exhibit
3.4,
column
Q.
Number
and
Percentage
of
Plants
Adding
Treatment
(
C)
Total
percentage
adding
treatment
for
surface
water
plants
(
Exhibit
6.14a)
and
ground
water
plants
(
Exhibit
6.16a).
Primarily
Ground
Water
NTNCWSs
Primarily
Surface
Water
CWSs
Primarily
Ground
Water
CWSs
Primarily
Suface
Water
NTNCWSs
Exhibit
6.4
Number
and
Percent
of
Plants
Adding
Treatment
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
12
July
2003
Surface
Water
Disinfecting
Ground
Water
Serving
£
10,000
Serving
>
10,000
Serving
£
10,000
Serving
>
10,000
Total
Total
Initial
Capital
Costs
for
the
Rule
50.0
$
214.64
$
108.3
$
100.3
$
473.3
$

(
90%
Confidence
Bounds)
($
43.1
­
57.1)
($
188.2
­
240.9)
($
91.5
­
125.1)
($
90.0
­
110.7)

CWS
Total
Initial
Capital
46.26
$
213.8
$
96.9
$
100.1
$
457.0
$

(
90%
Confidence
Bounds)
($
39.8
­
52.7)
($
187.4
­
239.9)
($
81.6
­
112.1)
($
89.8
­
110.4)

NTNCWS
Total
Initial
Capital
3.79
$
0.9
$
11.4
$
0.3
$
16.3
$

(
90%
Confidence
Bounds)
($
3.2
­
4.4)
($
0.7
­
1.0)
($
9.8
­
13.0)
($
0.2
­
0.3)

CWS
One­
Time
Costs
16.7
$
47.9
$
8.1
$
2.7
$
75.4
$

Implementation
1.5
$
0.4
$
4.1
$
0.2
$
6.2
$

IDSE
15.2
$
47.4
$
4.0
$
2.5
$
69.2
$

NTNCWS
One­
Time
Costs
0.1
$
0.2
$
0.9
$
0.0
$
1.2
$

Implementation
0.1
$
0.0
$
0.9
$
0.0
$
1.0
$

IDSE
­
$
0.2
$
0.0
$
0.0
$
0.2
$

State/
Primacy
Agency
One­
Time
Costs
14.4
$

Implementation
6.7
$

IDSE
7.7
$

Note:
Detail
may
not
add
due
to
independent
rounding.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Sources:
Initial
Capital
Costs
from
Exhibit
6.18.
Implementation
and
IDSE
costs
from
Exhibit
6.7.
Exhibit
6.5
Initial
Capital
and
One­
Time
Costs
for
the
Stage
2
DBPR
($
Millions)
5
The
Stage
2
DBPR
is
being
proposed
in
two
phases:
Stage
2A
requires
all
systems
to
comply
with
TTHM/
HAA5
MCLs
of
120/
100
µ
g/
L
measured
as
locational
running
averages
(
LRAAs)
at
each
Stage
1
DBPR
monitoring
site
and
must
continue
to
comply
with
the
Stage
1
DBPR
TTHM/
HAA5
MCLs
of
80/
60
µ
g/
L,
measured
as
running
annual
averages
(
RAAs).
Stage
2B
(
starting
six
years
after
rule
promulgation)
includes
systems
serving
at
least
10,000
people
must
comply
with
TTHM/
HAA5
MCLs
of
80/
60
µ
g/
L
measured
as
LRAAs
at
the
monitoring
sites
identified
during
an
IDSE
(
see
Chapter
1
for
further
description).
All
monitoring
costs
for
this
chapter
are
based
on
Stage
2B.

6
100
percent
purchasing
systems
buy
or
otherwise
receive
all
of
their
finished
water
from
another
system.

7
Producing
systems
do
not
buy
or
otherwise
receive
all
of
their
water
(
i.
e.,
they
produce
some
or
all
of
their
own
finished
water).

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
13
July
2003
6.2.4
Summary
of
Total
Annualized
Costs
Exhibit
6.6a
and
b
summarize
the
total
annualized
costs
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
at
3
and
7
percent
discount
rates,
respectively.
These
costs
are
derived
from
onetime
costs
and
steady­
state
annual
costs
(
i.
e.,
the
total
annual
costs
expected
after
all
systems
and
States
implement
the
rule)
in
section
6.3
(
non­
treatment
activity
costs)
and
6.4
(
treatment
costs).
The
methodology
for
calculating
the
present
value
of
costs
and
annualizing
is
discussed
in
sections
6.1.1
and
6.5.

6.3
Non­
Treatment
Costs
for
Systems
and
States/
Primacy
Agencies
This
section
presents
the
estimated
national
costs
for
systems
and
States/
Primacy
Agencies
to
perform
Stage
2
DBPR
rule
activities
that
are
not
related
to
treatment.
Chapter
1
contains
a
summary
of
the
Stage
2
DBPR
that
describes
these
activities.
The
following
subsections
provide
a
brief
summary
of
each
activity
and
key
assumptions
used
to
estimate
costs
for
each:

6.3.1
Rule
Implementation
6.3.2
Initial
Distribution
System
Evaluations
6.3.3
Additional
Routine
Monitoring
6.3.4
Significant
Excursion
Evaluations
Appendix
H
provides
a
detailed
methodology
and
calculations
for
all
non­
treatment­
related
costs.
Note
that
cost
calculations
in
Appendix
H
are
performed
using
system
inventory
data
broken
out
by
alternative
system
size
categories
(
different
from
the
standard
nine
system
size
categories
used
elsewhere
in
this
EA)
that
EPA
believes
to
be
more
appropriate
for
establishing
number
of
samples
required
per
system.
Section
6.3.5
summarizes
the
one­
time
and
steady­
state
annual
costs
for
all
non­
treatmentrelated
Stage
2
DBPR
activities.

For
the
IDSE
and
Stage
2B
routine
monitoring5,
the
Stage
2
DBPR
sets
forth
different
requirements
for
consecutive
systems
that
buy
all
of
their
water
(
these
are
defined
as
"
100
percent
purchasing
systems"
6)
than
for
all
other
systems
(
these
are
defined
as
"
producing
systems"
7).
Monitoring
requirements
for
100
percent
purchasing
systems
are
not
based
on
the
number
of
plants
as
in
the
Stage
1
DBPR.
They
are
based
solely
on
population
served
and
source
water
type.
This
approach
is
called
the
"
population­
based"
monitoring
approach.
A
"
plant­
based"
monitoring
approach,
which
is
consistent
with
the
Stage
1
DBPR,
applies
to
all
other
producing
systems.
Costs
in
Appendix
H
are
calculated
separately
for
100
percent
purchasing
and
for
producing
systems.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
14
July
2003
Total
System
Costs
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Implementation
IDSE
Monitoring
Significant
Excursion
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

£
 
10,000
$
2.23
$
1.92
$
2.54
$
3.94
$
3.66
$
4.22
$
0.08
$
0.84
$
1.20
$
0.00
$
8.30
$
7.71
$
8.89
>
10,000
$
10.76
$
9.44
$
12.08
$
10.08
$
9.50
$
10.67
$
0.02
$
2.68
­$
2.14
$
0.01
$
21.42
$
19.51
$
23.33
£
10,000
$
0.18
$
0.15
$
0.21
$
0.43
$
0.40
$
0.46
$
0.01
$
0.00
$
0.00
$
0.00
$
0.62
$
0.56
$
0.68
>
10,000
$
0.04
$
0.04
$
0.05
$
0.04
$
0.04
$
0.04
$
0.00
$
0.01
$
0.01
$
0.00
$
0.10
$
0.10
$
0.11
£
10,000
$
4.68
$
3.94
$
5.41
$
5.60
$
5.19
$
6.00
$
0.21
$
0.21
$
1.16
$
0.00
$
11.85
$
10.71
$
12.99
>
10,000
$
5.04
$
4.52
$
5.56
$
7.31
$
6.87
$
7.77
$
0.01
$
0.14
$
1.68
$
0.00
$
14.19
$
13.23
$
15.17
£
10,000
$
0.55
$
0.47
$
0.63
$
0.81
$
0.74
$
0.88
$
0.05
$
0.00
$
0.00
$
0.00
$
1.41
$
1.26
$
1.56
>
10,000
$
0.01
$
0.01
$
0.01
$
0.02
$
0.02
$
0.02
$
0.00
$
0.00
$
0.00
$
0.00
$
0.04
$
0.03
$
0.04
TOTAL
$
23.49
$
20.49
$
26.49
$
28.23
$
26.41
$
30.07
$
0.38
$
3.89
$
1.92
$
0.01
$
57.93
$
53.12
$
62.77
$
1.14
$
59.08
$
54.26
$
63.91
Notes:
Detail
may
not
add
due
to
independent
rounding.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Present
value
in
millions
of
$
2000
dollars.
Estimates
are
discounted
to
2003.
Sources
Capital
Costs:
SW
CWS,
Exhibit
K.
2bb;
SW
NTNCWS,
Exhibit
K.
2bf;
GW
CWS,
Exhibit
K.
2bj;
GW
NTNCWS,
Exhibit
K.
2bn.
O&
M
Costs:
SW
CWS,
Exhibit
K.
2bc;
SW
NTNCWS,
Exhibit
K.
2bg;
GW
CWS,
Exhibit
K.
2bk;
GW
NTNCWS,
Exhibit
K.
2bo.
Non­
Treatment
Costs:
SW
CWS,
Exhibit
K.
2bd;
SW
NTNCWS,
Exhibit
K.
2bh;
GW
CWS,
Exhibit
K.
2bl;
GW
NTNCWS,
Exhibit
K.
2bp.
State
Costs;
Appendix
H,
Exhibit
H.
15.
Capital
Costs
Mean
Value
90
Percent
Confidence
Bound
O&
M
Costs
Mean
Value
90
Percent
Confidence
Bound
Non­
Treatment
Costs
(
Point
Estimate)

Mean
Value
Mean
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
System
Costs
Total
Costs
of
the
Rule
Surface
Water
CWSs
Surface
Water
NTNCWSs
Ground
Water
CWSs
Ground
Water
NTNCWSs
System
Size
(
Population
Served)
State
Costs
Exhibit
6.6a
Total
Annualized
Costs
for
Stage
2
DBPR
Rule
Activities
($
Millions/
Year,
3
Percent
Discount
Rate)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
15
July
2003
Total
System
Costs
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Implementation
IDSE
Monitoring
Significant
Excursion
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

£
 
10,000
$
2.69
$
2.31
$
3.06
$
3.56
$
3.31
$
3.81
$
0.11
$
1.21
$
1.03
$
0.00
$
8.61
$
7.98
$
9.24
>
10,000
$
13.62
$
11.94
$
15.29
$
9.38
$
8.85
$
9.93
$
0.03
$
3.94
­$
1.89
$
0.01
$
25.09
$
22.88
$
27.31
£
10,000
$
0.22
$
0.19
$
0.25
$
0.39
$
0.36
$
0.41
$
0.01
$
0.00
$
0.00
$
0.00
$
0.62
$
0.55
$
0.68
>
10,000
$
0.05
$
0.05
$
0.06
$
0.03
$
0.03
$
0.04
$
0.00
$
0.01
$
0.01
$
0.00
$
0.12
$
0.11
$
0.12
£
10,000
$
5.63
$
4.74
$
6.51
$
5.06
$
4.69
$
5.43
$
0.28
$
0.28
$
0.99
$
0.00
$
12.24
$
10.98
$
13.49
>
10,000
$
6.38
$
5.72
$
7.04
$
6.81
$
6.40
$
7.23
$
0.02
$
0.21
$
1.48
$
0.00
$
14.89
$
13.83
$
15.97
£
10,000
$
0.66
$
0.57
$
0.75
$
0.74
$
0.67
$
0.80
$
0.06
$
0.00
$
0.00
$
0.00
$
1.46
$
1.30
$
1.62
>
10,000
$
0.02
$
0.01
$
0.02
$
0.02
$
0.02
$
0.02
$
0.00
$
0.00
$
0.00
$
0.00
$
0.04
$
0.03
$
0.04
TOTAL
$
29.26
$
25.54
$
32.98
$
25.99
$
24.32
$
27.68
$
0.51
$
5.66
$
1.64
$
0.01
$
63.07
$
57.67
$
68.48
$
1.48
$
64.55
$
59.16
$
69.96
Notes:
Detail
may
not
add
due
to
independent
rounding.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Present
value
in
millions
of
$
2000
dollars.
Estimates
are
discounted
to
2003.
Sources
Capital
Costs:
SW
CWS,
Exhibit
K.
2br;
SW
NTNCWS,
Exhibit
K.
2bv;
GW
CWS,
Exhibit
K.
2bz;
GW
NTNCWS,
Exhibit
K.
2cd.
O&
M
Costs:
SW
CWS,
Exhibit
K.
2bs;
SW
NTNCWS,
Exhibit
K.
2bw;
GW
CWS,
Exhibit
K.
2ca;
GW
NTNCWS,
Exhibit
K.
2ce.
Non­
Treatment
Costs:
SW
CWS,
Exhibit
K.
2bt;
SW
NTNCWS,
Exhibit
K.
2bx;
GW
CWS,
Exhibit
K.
2cb;
GW
NTNCWS,
Exhibit
K.
2cf.
State
Costs:
Appendix
H,
Exhibit
H.
15.
System
Costs
State
Costs
Total
Costs
of
the
Rule
System
Size
(
Population
Served)
Capital
Costs
O&
M
Costs
Non­
Treatment
Costs
(
Point
Estimate)

Mean
Value
90
Percent
Confidence
Bound
Mean
Value
Surface
Water
CWSs
Surface
Water
NTNCWSs
Ground
Water
CWSs
Ground
Water
NTNCWSs
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Mean
Value
Mean
Value
90
Percent
Confidence
Bound
Exhibit
6.6b
Total
Annualized
Costs
for
Stage
2
DBPR
Rule
Activities
($
Millions/
Year,
7
Percent
Discount
Rate)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
16
July
2003
Although
it
is
consistent
with
the
Stage
1
DBPR,
EPA
has
identified
several
potential
issues
with
the
plant­
based
approach,
such
as:

°
The
number
of
required
sample
sites
may
be
either
excessive
or
insufficient
in
representing
DBP
occurrence
throughout
the
system,
particularly
in
situations
where
a
small
system
uses
multiple
plants,
or
where
a
very
large
systems
using
a
small
number
of
plants.

°
Plant­
based
sampling
requirements
for
mixed
systems
(
i.
e.,
those
receiving
disinfected
surface
water
and
ground
water
in
their
distribution
system)
may
be
excessive,
depending
upon
the
system's
characteristics.

°
Plant­
based
monitoring
requirements
pose
unique
implementation
issues
for
systems
with
temporary
supplies
during
the
year.

The
Stage
2
DBPR
preamble
describes
these
issues
in
detail
and
requests
comment
on
them,
particularly
the
significance
of
a
plant­
based
versus
a
population­
based
monitoring
approach.
Appendix
I
compares
costs
and
burden
of
the
two
approaches.

EPA
is
also
considering
an
alternative
schedule
for
the
IDSE
(
starting
2
years
later
for
all
systems)
and
an
alternative
to
the
IDSE
whereby
it
is
replaced
with
increased
monitoring
during
the
first
year
to
reduce
the
burden
on
systems
and
EPA
Regions
and
increase
the
technical
involvement
of
the
States.
The
cost
implications
of
these
IDSE
alternatives
are
presented
in
Appendix
I.

6.3.1
Rule
Implementation
Public
Water
Systems
All
systems
subject
to
the
Stage
2
DBPR
will
incur
one­
time
costs
that
include
time
for
staff
to
read
the
rule
and
become
familiar
with
its
provisions
and
to
train
employees
on
rule
requirements.
The
technical
and
managerial
labor
rates
presented
in
section
6.1.1
were
used
along
with
estimates
of
labor
hours
to
generate
implementation
costs
for
all
systems.
The
mix
of
labor
rates
used
to
estimate
implementation
costs
vary
by
activity
and
system
size
as
summarized
in
Appendix
H.

States/
Primacy
Agencies
With
the
exception
of
the
IDSE,
the
Stage
2
DBPR
is
similar
to
the
Stage
1
DBPR,
which
States
have
already
implemented;
therefore,
additional
implementation
costs
for
the
Stage
2
DBPR
will
be
minimal.
State/
Primacy
Agency
implementation
activities
include:

°
Public
notification
°
Regulation
adoption
and
program
development
°
Training
State/
Primacy
Agency
staff
°
Training
PWS
staff
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
17
July
2003
°
Technical
assistance
°
Updating
the
data
management
system
The
number
of
FTEs
required
per
activity
was
estimated
by
EPA
based
on
previous
experience
with
other
rules.
State/
Primacy
Agency
activities
include
public
notification
(
0.1
FTEs),
regulation
adoption
and
program
implementation
(
0.50
FTEs),
training
State/
Primacy
Agency
staff
(
0.25
FTEs),
training
PWS
staff
and
technical
assistance
(
1.00
FTE),
and
updating
the
management
system
(
0.10
FTEs).
The
labor
rates
used
to
estimate
State/
Primacy
Agency
costs
are
presented
in
section
6.1.1.
The
number
of
States
and
territories
included
the
50
States
(
or
EPA
regions
were
States
do
not
have
primacy),
6
territories,
and
1
tribal
government.

6.3.2
Initial
Distribution
System
Evaluations
Public
Water
Systems
The
purpose
of
the
IDSE
is
to
identify
compliance
monitoring
sites
that
are
representative
of
the
highest
TTHM
and
HAA5
levels
in
the
distribution
system.
IDSEs
can
be
performed
by
either
(
1)
conducting
an
SMP
or
(
2)
completing
an
SSS
that
may
include
historical
data
or
hydraulic
modeling
results.
Nontransient
noncommunity
water
systems
(
NTNCWSs)
serving
fewer
than
10,000
people
are
not
subject
to
IDSE
requirements
of
the
Stage
2
DBPR.
A
system
does
not
have
to
perform
the
IDSE
if:
(
1)
all
Stage
1
DBPR
compliance
samples
are
less
than
or
equal
to
40
:
g/
L
for
TTHM
and
30
:
g/
L
for
HAA5,
or
(
2)
the
system
serves
less
than
500
people
and
its
Stage
1
DBPR
site
represents
both
high
TTHM
and
high
HAA5
concentrations.

For
systems
performing
an
IDSE,
costs
will
be
incurred
for
evaluating
their
distribution
systems
to
identify
sampling
sites,
sampling,
and
reporting
results.
Systems
electing
to
complete
an
SSS
may
not
incur
sampling
costs;
however,
they
will
still
incur
labor
costs
for
completing
and
submitting
the
report.
Also,
some
systems
that
do
not
perform
the
IDSE
may
have
more
sampling
sites
required
under
the
Stage
2
DBPR
than
under
the
Stage
1
DBPR
and,
thus,
incur
a
small
labor
cost
for
selecting
new
Stage
2B
sites.
A
detailed
description
of
the
process
that
EPA
used
to
estimate
the
total
national
IDSE
costs,
as
well
as
detailed
calculation
tables,
are
presented
in
Appendix
H.

States/
Primacy
Agencies
States/
Primacy
Agencies
also
will
incur
costs
as
a
result
of
the
IDSEs.
The
activities
they
will
conduct
include
analyzing
PWS
IDSE
reports,
making
determinations,
consulting
with
PWSs,
and
IDSE
recordkeeping.

6.3.3
Additional
Routine
Monitoring
Public
Water
Systems
Many
systems
will
have
the
same
monitoring
requirements
as
under
the
Stage
1
DBPR
and
will,
thus,
incur
no
additional
costs
for
this
activity.
As
described
in
Chapter
1,
consecutive
systems
that
buy
all
of
their
finished
water
(
100
percent
purchasing
systems)
have
a
modified
monitoring
scheme
based
only
on
population
served
and
source
water
type
(
not
number
of
plants,
as
for
the
Stage
1
DBPR).
As
a
result,
these
systems
may
have
more
or
fewer
monitoring
sites
between
the
Stage
1
and
Stage
2
DBPRs,
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
18
July
2003
depending
on
how
the
State/
Primacy
Agency
determined
their
Stage
1
monitoring
requirements.
Incremental
costs
will
be
negative
for
systems
that
have
fewer
sites
than
the
Stage
1
DBPR
(
see
Exhibit
H.
8a
in
Appendix
H).
Total
costs
for
all
systems
for
additional
routine
monitoring,
however,
are
positive.

For
all
other
systems
(
producing
systems),
only
a
portion
may
have
one
additional
site
per
plant.
Surface
water
systems
serving
500
to
9,999
people
and
disinfecting
ground
water
systems
serving
at
least
500
people
may
have
to
take
an
additional
sample
for
each
sample
period
if
their
high
TTHM
concentrations
occur
at
a
different
location
than
their
high
HAA5
concentrations.

Estimates
of
numbers
of
systems
that
have
additional
monitoring
sites
are
provided
in
Appendix
H.
Costs
for
additional
routine
monitoring
include
laboratory
analysis
and
labor
for
taking
the
sample.

States/
Primacy
Agencies
States/
Primacy
Agencies
will
incur
costs
for
additional
routine
monitoring
related
to
review
and
evaluation
of
monitoring
data
submitted
by
systems.

6.3.4
Significant
Excursion
Evaluations
Public
Water
Systems
To
address
excess
DBP
levels
that
may
occasionally
occur
(
but
do
not
cause
rule
violations),
the
Stage
2
DBPR
contains
a
provision
for
significant
DBP
excursions.
If
a
significant
excursion
occurs,
systems
must
conduct
a
significant
excursion
evaluation
and
discuss
the
evaluation
with
the
State/
Primacy
Agency
no
later
than
the
next
sanitary
survey.
A
significant
excursion
evaluation
must
include
an
examination
of
distribution
system
operational
practices
and
how
these
practices
may
be
modified
to
reduce
TTHM
and
HAA5
levels.

For
systems
that
experience
a
significant
excursion,
a
labor
cost
will
be
incurred
for
investigating
and
documenting
the
cause.
EPA
assumes
that
review
of
significant
DBP
excursion
evaluations
will
occur
as
part
of
the
normal
review
process
during
the
sanitary
survey
and
allocates
no
additional
cost
to
systems
for
this
activity.
Appendix
H
provides
estimates
of
the
number
of
systems
expected
to
experience
a
significant
excursion
and
the
associated
costs.

States/
Primacy
Agencies
EPA
assumes
that
review
of
significant
DBP
excursion
evaluations
will
occur
as
part
of
the
normal
review
process
during
the
sanitary
survey
and
allocates
no
additional
cost
to
States/
Primacy
Agencies
for
this
activity.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
19
July
2003
6.3.5
Results
(
One­
Time
and
Annual
Steady­
State
Costs)

Exhibit
6.7
summarizes
the
one­
time
system
costs
for
implementation
and
IDSEs,
along
with
the
annual
steady­
state
costs
for
additional
routine
monitoring
and
significant
excursion
evaluations.
Note
that
IDSE
costs
make
up
the
majority
of
the
one­
time
costs.
Additional
routine
monitoring
costs
are
much
larger
than
the
significant
excursion
yearly
costs,
mainly
because
of
TTHM/
HAA5
laboratory
fees.

One­
time
and
annual
costs
(
steady­
state)
for
States/
Primacy
Agencies
are
summarized
in
Appendix
H,
Exhibit
H.
15.
Total
one­
time
costs
for
implementation
and
IDSEs
are
approximately
$
14.4
million
(
including
$
6.7
million
for
implementation
activities
and
$
7.7
million
for
IDSE
activities),
while
annual
costs
for
additional
routine
monitoring
are
approximately
$
0.34
million.

6.4
Treatment
Costs
Treatment
costs
(
capital
and
O&
M)
make
up
the
bulk
of
the
costs
associated
with
the
Stage
2
DBPR.
This
section
reviews
the
cost
methodology
used
and
total
costs
for
the
Preferred
Regulatory
Alternative
as
follows:

6.4.1
Presents
the
treatment
technologies
available
to
systems
for
meeting
the
Stage
2
DBPR
and
describes
how
unit
costs
were
derived
for
each.
This
section
also
describes
how
uncertainty
in
unit
costs
is
incorporated
into
the
Stage
2
DBPR
cost
model.

6.4.2
Summarizes
the
methodology
for
generating
compliance
forecasts
(
number
of
systems
that
need
to
add
treatment
and
the
treatment
they
select)
for
surface
water
and
ground
water
plants
and
presents
compliance
forecasts
for
surface
and
ground
water
systems.

6.4.3
Presents
results
in
the
form
of
total
initial
capital
and
steady­
state
O&
M
costs.

Section
6.5
builds
on
results
from
this
section
by
showing
how
costs
are
projected
according
to
the
Stage
2
DBPR
compliance
schedule,
how
present
values
are
calculated
for
those
costs,
and
how
results
are
annualized
over
25
years
to
produce
the
total
annualized
costs
of
the
rule.

6.4.1
Technologies
and
Unit
Costs
Systems
that
exceed
the
TTHM
and
HAA5
MCLs
set
by
the
Stage
2
DBPR
will
have
to
take
action
to
bring
themselves
into
compliance.
For
the
purpose
of
estimating
the
costs
of
the
Stage
2
DBPR,
EPA
assumes
that
this
action
always
involves
treatment
modifications
at
the
plant.
In
reality,
some
systems
may
make
other
less
costly
improvements
(
such
as
modifying
their
distribution
system
operations
or
flushing)
or
may
choose
to
consolidate
with
another
system.
Thus,
national
costs
presented
in
this
EA
are
most
likely
over­
stated
(
see
section
6.8
for
a
summary
of
uncertainties
in
the
analysis).

Section
6.4.1.1
describes
the
treatment
technologies
and
their
operating
conditions
used
to
predict
national
treatment
costs
of
the
Stage
2
DBPR.
Section
6.4.1.2
discusses
alternatives
to
treatment
identified
by
EPA
and
others
during
the
Federal
Advisory
Committees
Act
(
FACA)
process
and
explains
why
these
processes
are
not
included
in
the
cost
analysis
for
the
Stage
2
DBPR.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
20
July
2003
One
Time­
Costs
($)
Annual
Costs
(
Steady
State)
($)

Implementation
IDSE
Total
Additional
Routine
Monitoring
Significant
Excursion
Evaluations
Total
A
B
C=
A+
B
D
E
F=
D+
E
£
100
192,142
$
371,431
$
563,573
$
(
19,929)
$
­
$
(
19,929)
$

101­
500
319,933
$
803,707
$
1,123,641
$
(
554)
$
60
$
(
495)
$

501­
1,000
228,068
$
2,825,436
$
3,053,504
$
396,375
$
768
$
397,142
$

1,001­
3,300
428,518
$
5,308,722
$
5,737,240
$
744,749
$
1,442
$
746,192
$

3,301­
10,000
334,894
$
5,878,472
$
6,213,366
$
764,000
$
1,284
$
765,284
$

10,001­
50,000
294,016
$
29,533,457
$
29,827,473
$
(
2,475,923)
$
8,004
$
(
2,467,919)
$

50,001­
100,000
72,491
$
8,808,897
$
8,881,388
$
(
615,042)
$
2,525
$
(
612,517)
$

100,001­
1
Million
63,922
$
8,434,192
$
8,498,113
$
(
30,375)
$
2,541
$
(
27,834)
$

>
1
Million
3,011
$
643,422
$
646,433
$
(
4,899)
$
196
$
(
4,703)
$

National
Totals
1,936,994
$
62,607,736
$
64,544,730
$
(
1,241,599)
$
16,820
$
(
1,224,779)
$

£
100
948,627
$
403,626
$
1,352,253
$
(
3,511)
$
­
$
(
3,511)
$

101­
500
1,482,800
$
687,968
$
2,170,768
$
39,488
$
­
$
39,488
$

501­
1,000
591,883
$
1,065,493
$
1,657,376
$
639,156
$
­
$
639,156
$

1,001­
3,300
704,760
$
1,268,690
$
1,973,450
$
761,047
$
­
$
761,047
$

3,301­
10,000
331,202
$
613,342
$
944,543
$
376,555
$
­
$
376,555
$

10,001­
50,000
178,272
$
1,987,279
$
2,165,551
$
2,032,063
$
­
$
2,032,063
$

50,001­
100,000
18,638
$
207,766
$
226,405
$
212,449
$
­
$
212,449
$

100,001­
1
Million
8,684
$
316,278
$
324,961
$
204,365
$
­
$
204,365
$

>
1
Million
320
$
20,850
$
21,170
$
8,260
$
­
$
8,260
$
National
Totals
4,265,185
$
6,571,291
$
10,836,476
$
4,269,872
$
­
$
4,269,872
$

£
100
37,814
$
­
$
37,814
$
­
$
­
$
­
$

101­
500
38,168
$
­
$
38,168
$
­
$
­
$
­
$

501­
1,000
15,778
$
­
$
15,778
$
­
$
­
$
­
$

1,001­
3,300
10,712
$
­
$
10,712
$
­
$
­
$
­
$

3,301­
10,000
3,185
$
­
$
3,185
$
5,879
$
­
$
5,879
$

10,001­
50,000
1,303
$
114,278
$
115,581
$
7,839
$
­
$
7,839
$

50,001­
100,000
174
$
23,979
$
24,153
$
3,919
$
­
$
3,919
$

100,001­
1
Million
174
$
35,969
$
36,143
$
7,839
$
­
$
7,839
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$

National
Totals
107,307
$
174,227
$
281,533
$
25,476
$
­
$
25,476
$

£
100
457,015
$
­
$
457,015
$
­
$
­
$
­
$

101­
500
329,625
$
­
$
329,625
$
186
$
­
$
186
$

501­
1,000
103,772
$
­
$
103,772
$
1,258
$
­
$
1,258
$

1,001­
3,300
38,627
$
­
$
38,627
$
468
$
­
$
468
$

3,301­
10,000
3,963
$
206
$
4,169
$
310
$
­
$
310
$

10,001­
50,000
620
$
2,474
$
3,094
$
3,149
$
­
$
3,149
$

50,001­
100,000
52
$
206
$
258
$
262
$
­
$
262
$

100,001­
1
Million
145
$
87
$
232
$
­
$
­
$
­
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$

National
Totals
933,818
$
2,973
$
936,791
$
5,634
$
­
$
5,634
$

Grand
Total
All
Systems
7,243,304
$
69,356,227
$
76,599,531
$
3,059,382
$
16,820
$
3,076,202
$

Notes:
Detail
may
not
add
due
to
independent
rounding.
Source:
Exhibit
H.
14b.
See
Exhibit
H.
12b
for
estimated
costs
for
non­
treatment
related
rule
activities
broken
out
according
to
the
Stage
2B
monitoring
system
size
categories.
100%
Ground
Water
NTNCWSs
System
Size
(
Population
Served)

Surface
Water
and
Mixed
CWSs
100%
Ground
Water
CWSs
Surface
Water
and
Mixed
NTNCWSs
Exhibit
6.7
Summary
of
System
Costs
for
Non­
Treatment
Related
Stage
2
DBPR
Rule
Activities
(
One­
Time
and
Steady­
State)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
21
July
2003
6.4.1.1
Technologies
Used
to
Estimate
Treatment
Costs
This
section
discusses
the
technologies
available
for
surface
water
plants
first,
followed
by
the
technologies
used
for
ground
water
plants.
A
discussion
of
uncertainties
in
unit
costs
follows.
A
summary
of
unit
treatment
costs
is
presented
at
the
end
of
the
section.
Appendix
J
supports
the
data
in
section
6.4.1.1,
showing
the
detailed
derivation
of
unit
costs
over
the
entire
range
of
expected
plant
flows.

Technologies
for
Surface
Water
Plants
Exhibit
6.8a
lists
the
treatment
technologies
that
are
available
to
surface
water
plants
for
complying
with
Stage
1
DBPR
and
Stage
2
DBPR
regulatory
alternatives.
The
technologies
are
identical
to
those
presented
in
the
SWAT
Decision
Tree
(
Chapter
3
and
Appendix
A)
with
the
exception
of
the
following:

°
Adjusting
disinfection
dose
°
Moving
the
point
of
chlorination
°
Enhanced
coagulation/
enhanced
softening
(
required
for
the
Stage
1
DBPR)

°
Turbo
coagulation
As
noted
in
section
3.61,
these
technologies
represent
operational
changes
to
existing
treatment
configurations.
Although
these
changes
may
result
in
small
increases
in
chemical
costs
or
minor
capital
improvements,
EPA
assumes
their
costs
to
be
negligible
when
compared
to
the
costs
of
the
advanced
technologies
(
e.
g.,
UV,
ozone,
granulated
activated
carbon,
microfiltration/
ultra­
filtration).
Also,
most
systems
that
are
able
to
use
these
technologies
are
predicted
to
do
so
to
meet
the
Stage
1
DBPR.
For
these
reasons,
the
predicted
costs
for
the
Stage
2
DBPR
do
not
include
costs
for
operational
changes
(
section
6.8
summarizes
uncertainties
in
national
cost
estimates).

Although
EPA
assumes
that
large
surface
water
plants
serving
more
than
100,000
people
can
select
any
of
the
technologies
presented
in
Exhibit
6.8a,
small
plants
may
not
be
able
to
use
a
particular
technology
because
of
operational
constraints
or
other
reasons.
Limitations
on
the
use
of
technologies
by
small
systems,
summarized
in
the
second
column
in
Exhibit
6.8a,
were
identified
during
the
small
surface
water
expert
review
process
(
see
Appendix
A
for
details).

The
last
column
in
Exhibit
6.8a
identifies
the
design
criteria
and
operating
conditions
for
each
technology
used
in
this
EA
to
generate
costs.
To
capture
the
range
of
costs,
the
Technology
and
Cost
(
T&
C)
document
evaluated
technologies
over
a
range
of
possible
influent
water
qualities
and
operating
conditions
(
USEPA
2003o).
For
the
purposes
of
estimating
the
costs
of
the
Stage
2
DBPR,
the
Technical
Workgroup
(
TWG)
selected
water
quality
and
operating
parameters
that
would
capture
the
typical
circumstances
under
which
plants
may
use
the
technology.
EPA
does
not
propose
that
all
systems
would
operate
under
these
conditions,
but
they
suffice
to
generate
capital
and
O&
M
costs
typical
of
the
range
of
system
types
and
sizes.
While
these
assumptions
simplify
the
true
variety
of
operating
conditions,
EPA
believes
they
capture
reasonable
estimates
of
national
costs.
The
uncertainties
associated
with
selecting
these
operational
parameters
and
conditions
are
summarized
in
section
6.8.

Appendix
A
presents
additional
information
on
how
each
technology
was
modeled
in
SWAT,
including
log
removal
and
disinfection
credits
for
Giardia
and
viruses.
Note
that,
for
UV,
the
disinfection
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
22
July
2003
credit
for
viruses
was
2.0
logs
for
all
runs.
The
primary
disinfectant
(
usually
chlorine)
dose
was
then
modified
to
meet
the
remaining
disinfection
requirements.

Some
advanced
technologies
were
considered
in
combination
for
surface
water
systems
to
meet
the
Stage
2
DBPR
(
as
modeled
in
SWAT).
When
technologies
are
a
combination
of
two
or
more
unit
processes
(
e.
g.,
Granular
Activated
Carbon
 
20­
Minute
Contact
Time
(
GAC20)
with
Advanced
Disinfectants
such
as
Chlorine
Dioxide
or
Ozone),
the
technology
unit
costs
are
assumed
to
be
the
sum
of
the
costs
for
each
unit
process.
For
example,
the
cost
for
implementing
GAC20
with
an
Advanced
Disinfectant
(
e.
g.,
Ozone)
is
equal
to
the
sum
of
GAC20
and
Ozone
unit
costs.
This
may
over­
estimate
unit
costs
since
some
economies
of
scale
are
expected
when
two
or
more
technologies
are
installed
at
the
same
time.

Technologies
for
Ground
Water
Plants
Exhibit
6.8b
lists
the
treatment
technologies
used
to
estimate
costs
of
the
Stage
1
DBPR
and
Stage
2
DBPR
regulatory
alternatives
for
ground
water
plants.
There
are
fewer
technologies
for
disinfecting
ground
water
plants
than
for
surface
water
plants.
As
noted
in
Chapter
3
and
Appendix
B,
the
ICR
Ground
Water
Delphi
process
concluded
that
disinfecting
ground
water
systems
would
choose
primarily
from
four
treatment
technologies
 
conversion
to
chloramines,
ozone,
GAC20,
and
nanofiltration.
Limitations
on
technology
use
by
small
systems,
as
identified
during
the
small
ground
water
expert
review
process,
are
provided
in
the
second
column.

Because
UV
was
still
very
much
an
emerging
technology
when
the
Ground
Water
Delphi
process
was
conducted
(
Spring,
2000),
UV
was
not
considered
as
a
treatment
option
for
large
ground
water
plants
for
either
the
Stage
1
or
Stage
2
DBPRs.
UV
was,
however,
considered
an
available
technology
for
small
ground
water
systems
to
meet
Stage
2
DBPR
requirements.
The
small­
system
expert
reviewers
assumed
UV
would
be
used
instead
of
chlorine
to
achieve
4.0
logs
of
virus
inactivation
in
all
circumstances.
EPA
currently
estimates
the
dose
required
to
inactivate
4.0
logs
of
Adenovirus
to
be
on
the
order
of
200
mJ/
cm2,
much
higher
than
the
UV
dose
of
40
mJ/
cm2
assumed
in
the
T&
C
document
for
surface
water
systems
(
USEPA
2003o).
Thus,
the
unit
cost
estimates
shown
in
Exhibit
6.8b
for
UV
($/
plant)
for
small
ground
water
plants
reflect
new
estimates
for
a
higher
dose
of
200
mJ/
cm2.

Unit
Costs
for
the
Stage
2
DBPR
Mean
unit
costs
for
each
of
EPA's
standard
nine
system
size
categories
are
derived
from
the
T&
C
document
(
USEPA
2003o).
The
T&
C
document
contains
between
16
and
20
point
estimates
of
capital
and
O&
M
costs
over
the
range
of
expected
design
and
average
flow
rates.
Appendix
J
displays
these
point
estimates
for
the
technologies
and
design
criteria
and
operating
conditions
listed
in
Exhibits
6.8a
and
b.
In
previous
T&
C
drafts,
non­
linear
cost
curves
were
generated
for
specific
flow
ranges
based
on
a
more
limited
set
of
point
estimates.
Because
the
number
of
point
estimates
for
the
unit
costs
was
increased
to
better
represent
the
full
range
of
expected
flows,
EPA
believes
that
direct
straight
line
interpolation
between
the
point
values
is
adequate
for
characterizing
the
changes
in
unit
costs
as
flow
increases
or
decreases.
Along
with
the
16
to
20
point
estimates,
Appendix
J
graphically
shows
the
relationship
of
unit
cost
and
flow
(
i.
e.,
the
point
estimates
connected
by
straight
lines).

Unit
costs
for
each
technology,
system
type,
source
water
type,
and
size
category
are
estimated
using
(
1)
the
unit
cost
data
in
Appendix
J
and
(
2)
the
mean
design
and
average
daily
flow
values
presented
in
Exhibit
3.6.
For
example,
the
design
flow
for
UV
for
surface
water
plants
in
CWSs
serving
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
23
July
2003
between
10,000
and
50,000
people
is
estimated
to
be
5.30691
MGD
(
the
value
in
Exhibit
3.6
is
truncated
to
5.307
MGD).
Exhibit
J.
5
shows
that
the
capital
cost
for
UV
surface
water
plants
is
$
408,427
for
a
design
flow
of
3.5
MGD
and
$
660,687
for
a
design
flow
of
7.0
MGD.
The
cost
for
a
5.30691
MGD
plant
can
be
calculated
by
linear
interpolation
as:

Unit
Cost
=
$
408,427
+
($
660,687
­
$
408,427)
*
(
5.30691
MGD
­
3.5
MGD)/(
7.0
MGD
­
3.5
MGD)

Unit
Cost
=
$
538,659
Exhibits
6.9a­
c
and
6.10a­
c
summarize
annual
O&
M
costs
($/
plant/
year),
capital
costs
($/
plant),
and
household
costs
($/
household/
year)
for
surface
and
ground
water
technologies,
respectively.
Note
that
unit
costs
are
different
for
surface
and
ground
water
plants
because
they
are
based
on
different
mean
design
and
average
daily
flows
per
plant
as
shown
in
Exhibit
3.6
for
each
system
size
category.
Costs
are
provided
for
each
technology
and
for
each
of
the
nine
population
size
categories
for
plants
in
CWSs.
Unit
costs
for
NTNCWSs
are
not
presented,
but
can
be
derived
from
the
data
in
Appendix
J
using
NTNCWS
flows
as
summarized
in
Exhibit
3.6.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
24
July
2003
Exhibit
6.8a
Treatment
Technologies
for
Surface
Water
Plants
Technology
Constraints
Design
Criteria
and
Operating
Conditions
Switching
to
chloramines
(
CLM)
as
a
residual
disinfectant
Can
be
used
alone
or
in
conjunction
with
all
other
technologies
in
this
exhibit
Ammonia
dose
=
0.55
mg/
L
(
output
from
SWAT)

Chlorine
dioxide
(
CLO2)
Assumed
not
practical
for
systems
serving
100
people
or
fewer
EPA
assumed
that
plants
will
not
build
a
new
contact
basin
for
chlorine
dioxide
ClO2
dose
=
1.25
mg/
L
Ultraviolet
light
disinfection
(
UV)
1
None
Median
water
quality
parameters
 
UV254
=
0.051
cm­
1,
turbidity
=
0.1
NTU,
alkalinity
=
60
mg/
L
as
CaCO3,
hardness
=
100
mg/
L
as
CaCO3
Dose
=
40
mJ/
cm2
Ozone
Assumed
not
practical
for
systems
serving
100
people
or
fewer
Design
dose
=
3.2
mg/
L,
contact
time
=
12
minutes2
Microfiltration
/
Ultrafiltration
(
MF/
UF)
None
Median
water
quality
parameters
 
Temperature=
10
°
C,
disposal
to
sewer
Granular
activated
carbon
filtration,
emptybed
contact
time
of
10
minutes
(
GAC10)
Assumed
not
practical
for
small
systems
serving
10,000
people
or
fewer
Reactivation
frequency
=
360
days
3
On­
site
regeneration
GAC10
+
Advanced
Disinfectants
Assumed
not
practical
for
small
systems
serving
10,000
people
or
fewer
Chlorine
dioxide
as
the
advanced
disinfectant
Reactivation
frequency
=
360
days
3
On­
site
regeneration
Granular
activated
carbon
filtration,
emptybed
contact
time
of
20
minutes
(
GAC20)
None
Reactivation
frequency
=
90
days
3
Onsite
regeneration
used
for
systems
serving
>
10,000
Media
replacement
used
for
systems
serving
<
10,000
GAC20
+
Advanced
Disinfectants
None
Systems
serving
>
10,000
(
GAC20
+
chlorine
dioxide)
Systems
serving
101
­
10,000
(
GAC20
+
ozone)
Systems
serving
<
100
(
GAC20
+
UV)
On­
site
media
regeneration
used
for
systems
serving
>
10,000
Media
replacement
used
for
systems
serving
<
10,000
Membranes
(
MF/
UF
+
nanofiltration
[
NF])
None
Median
water
quality
parameters
 
MF/
UF:
10
°
C,
disposal
to
sewer
NF:
10
°
C,
ocean
discharge
Notes:
1
Available
for
Stage
2
DBPR
regulatory
alternatives
only;
not
considered
available
for
the
Stage
1
DBPR.
UV
was
assumed
to
be
used
as
a
supplement
to
chlorine
to
achieve
some
of
the
required
Giardia
and
virus
inactivation,
thereby
reducing
chlorine
dosages.
2
Dose
does
not
consider
Cryptosporidium
inactivation,
and,
therefore,
may
not
represent
what
systems
would
do
to
meet
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR)
requirements.
However,
the
higher
dose
is
accounted
for
in
the
LT2ESWTR
EA.
3
Median
reactivation
frequency
generated
by
SWAT.

Source:
T&
C
document
(
USEPA
2003o),
FACA
deliberations
for
Stage
2
technologies
(
USEPA
2000p).
SWAT
Decision
Tree
(
Appendix
A),
and
Small
Surface
Water
Delphi
Groups
(
Appendix
A).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
25
July
2003
Exhibit
6.8b
Treatment
Technologies
for
Disinfecting
Ground
Water
Plants
Technology
Constraints
Design
Criteria
and
Operating
Conditions
Switching
to
CLM
as
a
Residual
Disinfectant
This
advanced
technology
can
be
used
alone
or
in
conjunction
with
all
the
following
technologies
Ammonia
dose
=
0.15
mg/
L1
UV2
Was
considered
only
for
small
systems
with
populations
of
101
to
9,999
people
Median
water
quality
parameters
 
UV254
=
0.051
cm­
1,
turbidity
=
0.1
NTU,
alkalinity
=
60
mg/
L
as
CaCO3,
hardness
=
100
mg/
L
as
CaCO3
Dose
=
approximately
200
mJ/
cm
Ozone
Assumed
not
practical
for
systems
serving
100
or
fewer
people
Design
dose
=
approximately
3.2
mg/
L,
contact
time
=
12
minutes
GAC20
None
Reactivation
frequency
=
240
days
3
On­
site
regeneration
used
for
systems
serving
more
than
10,000
Media
replacement
used
for
systems
serving
10,000
or
fewer
Nanofiltration
None
Median
water
quality
parameters
 
Temperature=
10
°
C,
ocean
discharge
Notes:
1
Dose
based
on
decisions
from
the
ICR
Ground
Water
Delphi
Group.
2
Available
for
Stage
2
DBPR
regulatory
alternatives
only;
not
considered
available
for
the
Stage
1
DBPR.
3
Reactivation
frequency
based
on
decisions
from
the
ICR
Ground
Water
Delphi
Group.

Source:
T&
C
document
(
USEPA
2003o),
FACA
deliberations
for
Stage
2
technologies
(
USEPA
2000p),
and
ICR
and
Small
Ground
Water
Delphi
Groups
(
Appendix
B).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
26
July
2003
System
Size
(
Population
Served)
Plant
Design
Flow
(
MGD)
CLM
CLO2
UV
Ozone
MF/
UF
GAC10
GAC10+
AD
GAC20
GAC20+
AD
Membranes
£
100
0.02
$
27,912
$
12,290
$
195,780
$
49,092
$
61,383
$
267,764
101­
500
0.08
$
27,912
$
31,610
$
23,286
$
306,733
$
373,543
$
122,745
$
429,478
$
520,958
501­
1,000
0.22
$
32,751
$
37,879
$
45,349
$
369,250
$
660,013
$
277,100
$
646,350
$
924,433
1,001­
3,300
0.57
$
39,412
$
41,018
$
85,235
$
526,634
$
999,812
$
612,051
$
1,138,684
$
1,547,250
3,301­
10,000
1.40
$
80,696
$
80,008
$
252,258
$
838,817
$
1,908,348
$
1,648,226
$
2,487,043
$
3,186,040
10,001­
50,000
5.31
$
80,696
$
195,786
$
538,659
$
1,730,528
$
5,589,628
$
2,551,722
$
2,747,508
$
4,204,626
$
4,400,412
$
10,534,960
50,001­
100,000
8.28
$
82,616
$
212,286
$
742,575
$
2,235,129
$
8,154,642
$
3,483,285
$
3,695,571
$
5,810,626
$
6,022,912
$
15,725,380
100,001­
1
Million
29.69
$
165,386
$
329,184
$
2,028,345
$
5,108,783
$
24,903,615
$
8,594,998
$
8,924,182
$
14,689,716
$
15,018,901
$
49,177,144
>
1
Million
191.61
$
461,990
$
827,573
$
11,127,634
$
21,647,379
$
135,145,122
$
34,041,536
$
34,869,108
$
59,705,859
$
60,533,432
$
250,437,418
System
Size
(
Population
Served)
Plant­
Average
Daily
Flow
(
MGD)
CLM
CLO2
UV
Ozone
MF/
UF
GAC10
GAC10+
AD
GAC20
GAC20+
AD
Membranes
£
100
0.01
$
1,572
$
3,563
$
7,763
$
20,780
$
24,343
$
16,932
101­
500
0.03
$
1,597
$
15,087
$
4,613
$
56,559
$
12,196
$
47,927
$
104,486
$
29,172
501­
1,000
0.08
$
3,038
$
16,831
$
6,127
$
57,150
$
26,555
$
62,104
$
119,254
$
64,437
1,001­
3,300
0.23
$
3,100
$
17,900
$
8,116
$
58,350
$
41,352
$
122,580
$
180,930
$
110,925
3,301­
10,000
0.58
$
6,340
$
20,197
$
10,423
$
61,564
$
90,131
$
187,653
$
249,216
$
252,904
10,001­
50,000
2.33
$
9,266
$
23,271
$
15,220
$
78,851
$
255,435
$
101,023
$
124,294
$
289,147
$
312,418
$
806,702
50,001­
100,000
3.81
$
11,094
$
26,421
$
17,275
$
91,751
$
399,619
$
135,646
$
162,067
$
381,837
$
408,258
$
1,282,212
100,001­
1
Million
14.51
$
20,209
$
47,108
$
32,558
$
182,317
$
1,324,136
$
331,319
$
378,427
$
1,058,799
$
1,105,907
$
4,442,174
>
1
Million
102.57
$
69,083
$
186,738
$
162,112
$
973,448
$
8,475,397
$
1,669,231
$
1,855,969
$
5,772,375
$
5,959,113
$
28,833,411
Exhibit
6.9a
Capital
Costs
($/
Plant)
for
CWS
Surface
Water
Plants
Exhibit
6.9b
Annual
O&
M
Costs
($/
Plant/
Year)
for
CWS
Surface
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
27
July
2003
System
Size
(
Population
Served)
Average
Yearly
Flow
(
kgal)
CLM
CLO2
UV
Ozone
MF/
UF
GAC10
GAC10+
AD
GAC20
GAC20+
AD
Membranes
£
100
83
$
133.25
$
154.51
$
825.78
$
835.70
$
990.21
$
1,340.19
101­
500
83
$
27.28
$
122.03
$
45.28
$
567.55
$
302.14
$
400.72
$
968.27
$
504.85
501­
1,000
104
$
17.82
$
61.43
$
30.56
$
271.09
$
252.87
$
262.33
$
533.42
$
437.67
1,001­
3,300
87
$
6.13
$
20.40
$
14.61
$
98.11
$
119.96
$
166.33
$
264.44
$
230.46
3,301­
10,000
97
$
4.62
$
9.48
$
11.14
$
46.52
$
88.24
$
114.90
$
161.41
$
183.41
10,001­
50,000
109
$
1.56
$
3.87
$
5.84
$
21.72
$
70.23
$
30.53
$
34.40
$
62.38
$
66.25
$
164.40
50,001­
100,000
119
$
0.64
$
1.57
$
2.81
$
9.86
$
38.29
$
15.11
$
16.67
$
30.74
$
32.31
$
92.07
100,001­
1
Million
125
$
0.31
$
0.68
$
1.82
$
5.49
$
30.74
$
9.47
$
10.14
$
20.65
$
21.33
$
77.28
>
1
Million
125
$
0.11
$
0.27
$
1.13
$
2.89
$
20.53
$
4.68
$
4.95
$
11.18
$
11.45
$
51.73
Source:
Derived
using
the
design
and
average
daily
flows
in
Exhibit
3.6
and
unit
cost
curves
in
Appendix
J.
Household
costs
are
generated
using
the
mean
household
usage
rate
and
the
cost
of
capital
discount
rates
in
Exhibit
6.2
Exhibit
6.9c
Household
Unit
Costs
($/
Household/
Year)
for
CWS
Surface
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
28
July
2003
System
Size
(
Population
Served)
Plant
Design
Flow
(
MGD)
CLM
UV
Ozone
GAC20
NF
£
100
0.02
$
27,912
$
23,861
$
306,733
$
50,608
$
73,532
101­
500
0.07
$
27,912
$
36,018
$
306,733
$
102,757
$
126,777
501­
1,000
0.17
$
29,198
$
63,497
$
328,171
$
217,941
$
212,740
1,001­
3,300
0.39
$
37,609
$
123,845
$
443,204
$
444,258
$
378,099
3,301­
10,000
0.90
$
48,050
$
371,054
$
629,790
$
1,030,057
$
812,081
10,001­
50,000
1.64
$
80,696
$
945,191
$
1,603,154
$
1,544,905
50,001­
100,000
4.22
$
80,696
$
1,532,936
$
3,167,013
$
3,950,992
100,001­
1
Million
8.01
$
82,205
$
2,193,195
$
5,099,663
$
7,341,270
>
1
Million
45.68
$
95,696
$
7,294,404
$
18,742,012
$
35,018,125
System
Size
(
Population
Served)
Plant­
Average
Daily
Flow
(
MGD)
CLM
UV
Ozone
GAC20
NF
£
100
0.01
$
1,566
$
4,113
$
56,531
$
11,009
$
8,756
101­
500
0.02
$
1,570
$
5,442
$
56,531
$
20,611
$
12,322
501­
1,000
0.05
$
1,580
$
7,135
$
56,677
$
35,377
$
29,653
1,001­
3,300
0.13
$
2,983
$
9,534
$
57,501
$
55,154
$
48,408
3,301­
10,000
0.34
$
4,246
$
11,462
$
59,204
$
97,752
$
109,825
10,001­
50,000
0.71
$
6,131
$
62,830
$
108,019
$
191,547
50,001­
100,000
2.07
$
7,594
$
76,546
$
157,008
$
491,463
100,001­
1
Million
4.46
$
9,205
$
97,357
$
242,493
$
1,025,376
>
1
Million
30.37
$
20,049
$
319,992
$
1,048,412
$
6,321,801
Exhibit
6.10a
Capital
Cost
($/
Plant/
Year)
for
CWS
Disinfecting
Ground
Water
Plants
Exhibit
6.10b
Annual
O&
M
Costs
($/
Plant/
Year)
for
CWS
Disinfecting
Ground
Water
Plants
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
29
July
2003
System
Size
(
Population
Served)
Mean
Annual
Water
Usage
per
HH
(
kgal)
CLM
UV
Ozone
GAC20
NF
£
100
83
$
171.52
$
264.87
$
3,561.05
$
659.24
$
649.26
101­
500
83
$
36.93
$
79.31
$
769.87
$
273.41
$
215.85
501­
1,000
104
$
14.78
$
45.57
$
307.42
$
195.95
$
173.55
1,001­
3,300
87
$
6.88
$
22.32
$
105.97
$
103.45
$
89.68
3,301­
10,000
97
$
3.11
$
16.02
$
42.10
$
69.19
$
66.83
10,001­
50,000
109
$
1.33
$
14.69
$
25.07
$
33.31
50,001­
100,000
119
$
0.46
$
6.55
$
13.50
$
26.34
100,001­
1
Million
125
$
0.14
$
2.36
$
5.62
$
13.79
>
1
Million
125
$
0.03
$
1.14
$
3.20
$
11.39
Source:
Derived
using
the
design
and
average
daily
flows
in
Exhibit
3.6
and
unit
cost
curves
in
Appendix
J.
Household
costs
are
generated
using
the
mean
household
usage
rate
and
the
cost
of
capital
discount
rates
in
Exhibit
6.2
Exhibit
6.10c
Household
Unit
Costs
($/
Household/
Year)
for
CWS
Disinfecting
Ground
Water
Plants
Uncertainties
in
Unit
Costs
As
stated
in
section
6.1.1,
EPA
recognizes
that
there
are
both
variability
and
uncertainty
in
unit
cost
estimates
for
treatment.
Variability
is
expected
in
the
actual
costs
that
will
be
experienced
by
different
water
systems
with
similar
flows
installing
the
same
treatment
technology.
Otherwise
similar
systems
may
experience
different
capital
and/
or
O&
M
costs
due
to
site­
specific
factors.
Inputs
to
unit
costs
such
as
water
quality
conditions,
labor
rates,
and
land
costs
can
be
highly
variable
and
increase
the
system­
to­
system
variability
in
unit
costs.
In
developing
the
unit
cost
estimates,
there
is
insufficient
information
to
fully
characterize
what
the
distribution
of
this
variability
will
be
on
a
national
scale
for
all
of
the
treatments
and
all
possible
conditions.

The
unit
costs
for
this
EA
are
developed
as
average
or
representative
estimates
of
what
these
unit
costs
will
be
nationally.
That
is,
in
developing
unit
costs,
design
criteria
for
the
technologies
were
selected
to
represent
typical,
or
average,
conditions
for
the
universe
of
systems.
As
a
result,
there
is
uncertainty
inherent
in
these
unit
cost
estimates
as
they
are
based
on
independent
assumptions
with
supporting
data
and
vendor
quotes,
where
available,
rather
than
on
an
detailed
aggregation
of
State,
regional,
or
local
estimates
based
on
actual
field
conditions.
In
this
EA,
uncertainty
in
these
national
average
unit
cost
factors
is
characterized
as
a
triangular
distribution
with
minimum
and
maximum
values
set
at
the
following
percentages
relative
to
the
best
estimate:

°
Capital
costs:
+/­
30%

°
O&
M
costs:
+/­
15%

These
percentages
were
developed
by
EPA
based
on
input
from
engineering
professionals
and
reflect
recommendations
from
the
National
Drinking
Water
Advisory
Council
(
NDWAC)
(
2001)
in
their
review
of
the
national
cost
estimation
methodology
for
the
Arsenic
Rule.
EPA
believes
that
the
uncertainties
in
capital
and
O&
M
costs
for
a
given
treatment
technology
are
independent
of
one
another
and
that
uncertainties
across
all
technologies
are
independent.
8
These
compliance
forecasts
are
for
Stage
2B,
which
requires
that
compliance
be
met
at
revised
sampling
locations
identified
during
the
IDSE.
Systems
must
also
meet
transitional
MCLs
of
120
:
g/
L
for
TTHM
and
100
:
g/
L
for
HAA5
calculated
as
the
locational
running
annual
average
(
LRAA)
based
on
Stage
1
monitoring
sites
under
Stage
2A.
EPA
assumes
that
any
incremental
costs
incurred
to
meet
Stage
2A
requirements
will
be
negligible.
Therefore,
it
was
estimated
that
all
costs
would
be
incurred
to
meet
Stage
2B
requirements.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
30
July
2003
The
uncertainty
in
unit
costs
is
characterized
by
the
median
and
90
percent
confidence
bounds
shown
in
the
national
cost
summary
exhibits
in
section
6.2
and
later
in
this
chapter.

6.4.1.2
Alternatives
to
Treatment
During
the
FACA
process,
the
M­
DBP
TWG
identified
many
activities
that
systems
potentially
could
use
to
reduce
TTHM
and
HAA5
levels
in
the
distribution
system
by
reducing
average
residence
time,
including:

°
Flushing
more
frequently,
or
looping
sections
of
the
distribution
system
to
eliminate
dead
ends.

°
Modifying
portions
of
the
distribution
system
with
problematic
DBP
levels.

°
Optimizing
storage
to
minimize
retention
time
in
the
distribution
system.

The
costs
for
these
activities
could
range
from
close
to
zero
(
e.
g.,
changing
tank
operations
without
making
capital
improvements)
to
more
substantial
costs
for
reconfiguring
storage
facilities
or
looping
distribution
system
networks.
The
benefits
from
distribution
system
activities
that
reduce
DBP
concentrations
also
vary
widely
and
are
dependent
on
system­
specific
conditions.
Therefore,
these
activities
were
not
evaluated
in
this
EA
(
see
section
6.7
for
a
discussion
of
unquantifiable
costs).

Other
alternatives
to
treatment
that
could
reduce
TTHM
and
HAA5
levels
in
the
distribution
system
include
connecting
to
a
nearby
water
system
or
identifying
another
water
source
that
has
lower
DBP
precursor
levels.
While
the
latter
may
not
be
feasible
for
some
remote
systems,
EPA
estimates
that
more
than
22
percent
of
all
small
systems
are
located
within
metropolitan
regions
where
distances
between
neighboring
utilities
will
not
present
a
prohibitive
barrier.
To
estimate
this
percentage,
EPA
used
the
April
2000
Safe
Drinking
Water
Information
System
(
SDWIS)
database
to
compare
the
zip
codes
for
CWSs
that
serve
100
or
fewer
people
and
medium
and
large
CWSs.
EPA
then
determined
that
out
of
the
446
surface
water
CWSs
that
serve
100
or
fewer
people,
98
(
22
percent)
have
zip
codes
that
are
identical
to
those
for
medium
and
large
CWSs
(
however,
size
of
the
zip
code
zone
was
not
considered).
Consolidation
with
another
water
system
may
represent
the
least­
cost
alternative
for
many
small
systems.

6.4.2
Compliance
Forecasts
This
section
summarizes
the
methodology
used
to
develop
the
compliance
forecasts
for
surface
and
ground
water
systems
and
presents
the
results
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative.
8
Compliance
forecasts
for
the
other
regulatory
alternatives
are
presented
in
Appendix
C.

The
treatment
compliance
forecast
for
the
Stage
2
DBPR
has
two
components:
9
As
noted
in
Chapter
3,
the
Stage
1
RIA
predictions
were
not
used
for
the
pre­
Stage
2
baseline
in
this
EA
because
new
tools
and
data
became
available
to
better
characterize
plants.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
31
July
2003
°
The
percent
of
plants
that
must
add
treatment
to
comply
with
Stage
2
DBPR
requirements.
°
The
percent
of
plants
selecting
specific
treatment
technologies.

This
information,
coupled
with
the
baseline
data
presented
in
Chapter
3,
provides
an
estimate
of
the
total
number
of
plants
using
specific
technologies
to
meet
the
requirements
of
the
Stage
2
DBPR.

6.4.2.1
Overview
of
Compliance
Forecast
Methodology
EPA
used
various
tools
to
develop
the
compliance
forecast
for
the
Stage
2
DBPR
regulatory
alternatives.
Because
of
inherent
differences
in
water
quality
and
treatment
configurations,
different
methods
were
used
for
surface
and
disinfecting
ground
water
systems
and
for
large,
medium,
and
small
system
sizes.
Exhibit
6.11
summarizes
the
tools
used
to
develop
the
treatment
compliance
forecast.
Detailed
descriptions
of
these
tools
are
in
the
referenced
appendices.

Exhibit
6.11
Tools
Used
to
Develop
the
Stage
2
DBPR
Compliance
Forecasts
System
Size
(
Population
Served)
Source
Water
Category
Surface
Water
(
Appendix
A)
Disinfecting
Ground
Water
(
Appendix
B)

Large
(>
100,000
people)
SWAT
ICR
Ground
Water
Delphi
Group
Medium
(
10,001
to
100,000
people)
Extrapolation
from
SWAT
Extrapolation
from
large
ground
water
system
results
Small
(<
10,000
people)
Extrapolation
from
SWAT,
adjusted
to
deal
with
small
system­
specific
issues
Extrapolation
from
large
ground
water
system
results,
adjusted
to
deal
with
small
systemspecific
issues
For
cost
and
benefit
analyses,
the
compliance
forecast
should
reflect
technology
changes
from
the
pre­
Stage
2
baseline
(
i.
e.,
after
implementation
of
the
Stage
1
DBPR).
The
best
data
available
to
characterize
systems
are
from
the
ICR,
which
does
not
reflect
treatment
changes
that
may
occur
as
a
result
of
the
Stage
1
DBPR.
Therefore,
the
compliance
forecast
for
the
Stage
2
DBPR
must
account
for
treatment
changes
that
will
occur
as
a
result
of
the
Stage
1
DBPR.
9
The
M­
DBP
committee
considered
a
straightforward,
2­
step
approach
for
estimating
the
Stage
2
DBPR
compliance
forecast,
whereby
compliance
forecasts
would
be
developed
from
pre­
Stage
1
to
pre­
Stage
2
conditions,
then
from
pre­
Stage
2
to
post­
Stage
2
conditions
(
the
second
step
being
used
for
costing).
This
approach
was
not
selected,
however,
due
to
biases
in
SWAT.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
32
July
2003
As
shown
in
Exhibit
6.11,
SWAT
was
the
main
tool
used
to
generate
the
compliance
forecast
for
surface
water
systems.
Analysis
of
SWAT
in
Appendix
A
shows
that
SWAT
may
predict
more
technology
changes
than
ICR
between
Stage
1
and
Stage
2.
This
could
lead
to
an
overprediction
of
the
number
of
plants
selecting
advanced
technologies
and
over­
specification
of
the
advanced
technologies
they
select.
(
For
example,
SWAT
may
conclude
that
a
plant
must
add
membranes
to
meet
Stage
2
based
on
predicted
DBP
data,
when
in
actuality,
the
plant
could
use
a
less
expensive
technology
that
removes
less
DBPs,
such
as
converting
to
chloramines,
to
meet
the
rule.)

To
minimize
potential
biases
in
SWAT,
the
M­
DBP
committee
decided
upon
a
4­
step
compliance
forecast
methodology
instead
of
the
2­
step
approach.
The
4­
step
process
begins
with
the
pre­
Stage
1
baseline
using
ICR
data,
predicts
the
technology
changes
for
the
Stage
1
DBPR,
predicts
the
changes
for
the
Stage
2
DBPR
using
the
same
pre­
Stage
1
baseline,
and
takes
the
difference
of
the
two
to
estimate
costs
and
benefits.
Exhibit
6.12
summarizes
the
steps
for
estimating
the
Stage
2
DBPR
compliance
forecast
and
lists
the
exhibits
that
present
the
results
of
each
step.

Exhibit
6.12
Stage
2
DBPR
Compliance
Forecast
Summary
Step
Description
of
Step
Summary
of
Results
for
the
Preferred
Regulatory
Alternative1
1
Model
a
pre­
Stage
1
baseline
scenario
(
Technologies­
in­
Place).
Exhibits
3.15
and
3.16
2
Model
technology
selection
to
meet
Stage
1
DBPR
requirements
from
pre­
Stage
1
baseline
conditions
(
Stage
1
DBPR
Technology
Selection).
Exhibits
C.
1
and
C.
2
3
Model
technology
selection
to
meet
Stage
2
DBPR
requirements
from
pre­
Stage
1
baseline
conditions
(
Stage
2
DBPR
Technology
Selection).
Exhibits
C.
3
and
C.
4
4
Subtract
the
results
in
Step
2
from
Step
3
and
adjust
to
obtain
the
incremental
impact
(
Technology
Selection
Delta).
Exhibits
6.14
and
6.162
1
The
first
exhibit
referenced
shows
results
for
surface
water
plants,
the
second
for
ground
water
plants.
2
Values
used
for
cost
calculations.

This
process
effectively
minimizes
the
bias
in
SWAT
DBP
predictions
(
see
analysis
in
Appendix
A).
The
disadvantage
of
the
4­
step
process
is
that
the
compliance
forecasts
do
not
explicitly
take
into
account
treatment­
in­
place
following
Stage
1
when
considering
Stage
2
DBPR
requirements.
The
availability
of
UV
disinfection
exacerbates
this
issue.
UV
is
an
emerging
technology
that
has
just
recently
been
shown
to
be
an
effective
disinfectant
for
many
microorganisms
of
concern
in
drinking
water.
When
developing
the
compliance
forecast,
EPA
considered
UV
an
available
technology
for
meeting
Stage
2
requirements,
but
not
Stage
1
requirements.
Some
plants
were
then
predicted
to
use
UV
for
the
Stage
2
DBPR
instead
of
more
expensive
technologies
such
as
ozone,
MF/
UF,
or
GAC
that
were
selected
for
the
Stage
1
DBPR
forecasts.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
33
July
2003
To
account
for
different
technologies
being
available
for
the
Stage
1
DBPR
versus
the
Stage
2
DBPR,
EPA
modeled
the
Stage
2
DBPR
regulatory
alternatives
with
and
without
UV
as
an
available
technology.
Adjustments
were
then
made
to
the
Stage
2
DBPR
technology
selection
forecasts
to
ensure
that
advanced
technologies
were
not
reduced
from
the
Stage
1
to
the
Stage
2
DBPR.
Appendices
A
and
B
provide
detail
on
these
adjustments,
including
(
in
most
cases)
a
flow
diagram
and
sample
calculations.
6.4.2.2
Surface
Water
Compliance
Forecasts
Appendix
A
presents
detailed
information
on
the
compliance
forecast
methodology
for
large,
medium,
and
small
surface
water
systems.
To
summarize,
modeled
results
from
SWAT
were
used
directly
for
large
and
medium
surface
water
systems.
SWAT
forecasts
were
modified
to
produce
small
system
compliance
forecasts
based
on
differences
in
water
quality,
regulatory
history,
and
operational
constraints.
Adjustments
were
made
to
the
Stage
2
DBPR
compliance
forecasts
to
correct
for
the
Stage
1
DBPR
baseline
(
as
noted
in
the
previous
section,
UV
was
allowed
for
Stage
2,
but
not
for
Stage
1).
The
Stage
1
DBPR
technology
selection
forecast
was
subtracted
from
the
Stage
2
DBPR
technology
selection
forecast
(
both
forecasts
are
predicted
from
the
pre­
Stage
1
DBPR
baseline)
to
produce
the
incremental
technology
changes
for
the
Stage
2
DBPR
(
or
the
technology
selection
deltas).

Exhibit
6.13
provides
a
graphical
representation
to
aid
the
reader
in
interpreting
surface
water
plant
technology
selection
forecast
results.
Note
that,
as
shown
in
Exhibit
6.13,
chloramine
use
is
applied
as
a
percent
of
all
surface
water
plants,
regardless
of
whether
or
not
they
use
advanced
technologies.
Exhibits
6.14a
and
6.14b
presents
the
technology
selection
deltas
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
for
surface
water
systems.
Chloramine
use
is
estimated
this
way
because,
although
SWAT
evaluates
each
plant
individually
for
suitability
of
changing
to
chloramine
use,
eligible
plants
are
assigned
chloramine
use
through
a
Monte
Carlo
probability
function
that
is
based
upon
an
assumed
maximum
overall
level
of
chloramine
use
nationally.
This
maximum
national
chloramine
usage
level
is
intended
to
reflect
site­
specific
circumstances
and
other
local
factors
that
would
preclude
chloramine
usage
at
some
plants
for
reasons
other
than
technical
suitability.
Thus,
SWAT
produces
a
total
percent
converting
to
chloramines
(
with
and
without
advanced
disinfection)
for
all
plants
subject
to
the
rule
(
see
Appendix
A
for
more
information
on
how
SWAT
models
chloramines).

Exhibit
6.15
presents
the
final
post­
Stage
2
DPBR
technologies­
in­
place
for
surface
water
systems
under
the
Preferred
Regulatory
Alternative.
For
plants
in
small
systems
serving
10,000
people
or
fewer,
post­
Stage
2
DBPR
technologies­
in­
place
can
be
derived
by
adding
the
predicted
pre­
Stage
2
technologies­
in­
place
(
Exhibit
3.17)
to
the
technology
selections
in
Exhibit
6.14.
This
is
not
true,
however,
for
large
and
medium
surface
water
systems
 
separate
SWAT
predictions
must
be
used
(
USEPA
2001e).
This
is
because
some
large
and
medium
systems
with
advanced
technologies
in
place
under
pre­
Stage
1
conditions
are
predicted
to
move
within
the
SWAT
decision
tree
to
meet
DBP
regulations
(
unlike
small
systems
which
are
assumed
to
have
little
to
no
advanced
technologies
for
pre­
Stage
1).
In
other
words,
a
plant
starting
with
an
advanced
technology
for
pre­
Stage
1
conditions
can
be
predicted
by
SWAT
to
need
a
more
advanced
(
and
more
expensive)
technology
to
meet
Stage
1
or
Stage
2
regulatory
requirements.
The
technology
selection
forecasts
capture
only
the
new
technologies
selected
for
rule
compliance
 
the
corresponding
reduction
in
less
expensive
technologies
from
which
plants
are
predicted
to
move
is
not
captured
in
the
technology
selection
output.
The
SWAT
ending
technology
predictions,
however,
so
incorporate
reductions
in
less
expensive
advanced
technologies
to
represent
plant
use
for
a
given
regulatory
period.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
34
July
2003
Total
Percent
Converting
to
CLM
(
column
K)
=
(
II)
+
(
III)
Not
Adding
Treatment
or
making
operational
changes
to
existing
treatment
configurations
*
Converting
to
CLM
Only
(
III)
Adding
Advanced
Technology
Only
(
I)

Adding
Advanced
Technology
and
Converting
to
CLM
(
II)

Total
Percent
Adding
Technology
(
column
L)
=
(
I)
+
(
II)
+
(
III)
Exhibit
6.13
Interpretation
of
Technology
Selection
Forecasts
for
Surface
Water
Plants
(
Can
Be
Used
with
Technology
Selection
or
Technology
Selection
Deltas)

Notes:
Outer
circle
represents
all
surface
water
systems
subject
to
the
Stage
2
DBPR.
This
is
a
schematic
representation
only
(
not
actual
data)
*
Operational
changes
to
existing
treatment
configurations
are
not
costed
in
this
EA.
See
Section
6.4.1.1
for
a
list
of
operational
changes
considered
in
the
surface
water
compliance
forecast
and
Exhibit
5.19
for
the
percent
of
plants
expected
to
make
these
changes
to
meet
the
Stage
2
DBPR
.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
35
July
2003
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
Advanced
Disinfectants
GAC20
GAC20
+
Advanced
Disinfectants
A
B
C
D
E
F
G
H
I
J
K
L
=
SUM(
A:
J)
£
100
0.8%
4
3.1%
14
0.0%
0
0.0%
0
0.6%
3
0.0%
0
3.0%
14
4.4%
21
101­
500
2.1%
17
0.0%
0
0.4%
3
0.0%
0
0.0%
0
0.0%
0
0.7%
6
0.0%
0
3.6%
29
3.3%
26
501­
1,000
2.1%
11
0.0%
0
0.4%
2
0.0%
0
0.0%
0
0.0%
0
0.7%
4
0.0%
0
3.6%
18
3.3%
17
1,001
­
3,300
2.5%
27
0.0%
0
0.5%
5
0.0%
0
0.0%
0
0.0%
0
0.7%
8
0.0%
0
4.0%
45
3.7%
41
3,301­
10,000
2.5%
30
0.0%
0
0.5%
6
0.0%
0
0.0%
0
0.0%
0
0.7%
9
0.0%
0
4.0%
49
3.7%
45
10,001­
50,000
3.6%
46
0.4%
5
0.7%
9
0.0%
0
0.0%
0
0.0%
0
0.7%
9
0.4%
5
0.0%
0
0.0%
0
5.1%
66
5.8%
75
50,001­
100,000
3.6%
19
0.4%
2
0.7%
4
0.0%
0
0.0%
0
0.0%
0
0.7%
4
0.4%
2
0.0%
0
0.0%
0
5.1%
28
5.8%
31
100,001­
1
Million
3.6%
21
0.4%
2
0.7%
4
0.0%
0
0.0%
0
0.0%
0
0.7%
4
0.4%
2
0.0%
0
0.0%
0
5.1%
29
5.8%
33
>
1
Million
3.6%
3
0.4%
0
0.7%
1
0.0%
0
0.0%
0
0.0%
0
0.7%
1
0.4%
0
0.0%
0
0.0%
0
5.1%
4
5.8%
4
Total
%,
Plants
2.7%
178
0.1%
9
0.7%
49
0.0%
0
0.0%
0
0.0%
0
0.3%
18
0.1%
9
0.4%
29
0.0%
0
4.3%
282
4.5%
293
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
Source:
Technology
Selection
for
the
Stage
2
Preferred
Alternative
minus
the
Stage
1
Technology
Selection
from
Appendix
C,
Exhibit
C.
1a.
Total
Adding
Technology
Total
Converting
to
CLM
System
Size
(
Population
Served)
Converting
to
CLM
Only
Advanced
Technologies
Membranes
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
Advanced
Disinfectants
GAC20
GAC20
+
Advanced
Disinfectants
A
B
C
D
E
F
G
H
I
J
K
L
=
SUM(
A:
J)
£
100
0.8%
2
3.1%
9
0.0%
0
0.0%
0
0.6%
2
0.0%
0
3.0%
9
4.4%
13
101­
500
2.1%
6
0.0%
0
0.4%
1
0.0%
0
0.0%
0
0.0%
0
0.7%
2
0.0%
0
3.6%
11
3.3%
10
501­
1,000
2.1%
2
0.0%
0
0.4%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
1
0.0%
0
3.6%
4
3.3%
4
1,001
­
3,300
2.5%
2
0.0%
0
0.5%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
1
0.0%
0
4.0%
3
3.7%
3
3,301­
10,000
2.5%
1
0.0%
0
0.5%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
0
0.0%
0
4.0%
1
3.7%
1
10,001­
50,000
3.6%
0
0.4%
0
0.7%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
0
0.4%
0
0.0%
0
0.0%
0
5.1%
0
5.8%
1
50,001­
100,000
3.6%
0
0.4%
0
0.7%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
0
0.4%
0
0.0%
0
0.0%
0
5.1%
0
5.8%
0
100,001­
1
Million
3.6%
0
0.4%
0
0.7%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
0
0.4%
0
0.0%
0
0.0%
0
5.1%
0
5.8%
0
>
1
Million
3.6%
0
0.4%
0
0.7%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
0
0.4%
0
0.0%
0
0.0%
0
5.1%
0
5.8%
0
Total
%,
Plants
1.7%
14
0.0%
0
1.4%
11
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.7%
5
0.0%
0
3.5%
28
3.8%
31
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
Source:
Technology
Selection
for
the
Stage
2
Preferred
Alternative
minus
the
Stage
1
Technology
Selection
from
Appendix
C,
Exhibit
C.
1b.
Total
Adding
Technology
Total
Converting
to
CLM
System
Size
(
Population
Served)
Converting
to
CLM
Only
Advanced
Technologies
Membranes
Exhibit
6.14a
Technology
Selection
Deltas
for
CWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
Exhibit
6.14b
Technology
Selection
Deltas
for
NTNCWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
36
July
2003
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGY
(
with
CL2
or
CLM)

CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
38.5%
181
31.3%
147
69.8%
328
3.1%
14
18.6%
88
3.8%
18
0.6%
3
4.1%
19
30.2%
142
42.6%
200
101­
500
32.4%
259
37.7%
301
70.2%
560
2.4%
19
0.4%
3
11.9%
95
9.9%
79
2.3%
19
1.6%
13
1.3%
10
29.8%
238
51.1%
408
501­
1,000
32.4%
164
37.7%
190
70.2%
354
2.4%
12
0.4%
2
11.9%
60
9.9%
50
2.3%
12
1.6%
8
1.3%
7
29.8%
151
51.1%
258
1,001
­
3,300
29.8%
329
43.9%
485
73.8%
814
5.1%
56
0.5%
5
10.1%
111
5.4%
60
2.6%
28
1.8%
20
0.7%
8
26.2%
289
56.8%
627
3,301­
10,000
29.8%
362
43.9%
533
73.8%
895
5.1%
62
0.5%
6
10.1%
122
5.4%
66
2.6%
31
1.8%
22
0.7%
9
26.2%
318
56.8%
689
10,001­
50,000
33.7%
434
38.5%
495
72.2%
929
7.0%
90
0.7%
9
12.8%
165
1.8%
24
2.2%
28
1.8%
24
0.7%
9
0.0%
0
0.7%
9
27.8%
358
56.8%
731
50,001­
100,000
33.7%
181
38.5%
207
72.2%
388
7.0%
37
0.7%
4
12.8%
69
1.8%
10
2.2%
12
1.8%
10
0.7%
4
0.0%
0
0.7%
4
27.8%
150
56.8%
305
100,001­
1
Million
33.7%
193
38.5%
220
72.2%
413
7.0%
40
0.7%
4
12.8%
73
1.8%
10
2.2%
13
1.8%
10
0.7%
4
0.0%
0
0.7%
4
27.8%
159
56.8%
325
>
1
Million
33.7%
25
38.5%
28
72.2%
53
7.0%
5
0.7%
1
12.8%
9
1.8%
1
2.2%
2
1.8%
1
0.7%
1
0.0%
0
0.7%
1
27.8%
20
56.8%
42
Total
%,
Plants
32.4%
2,127
39.7%
2,607
72.2%
4,734
4.9%
320
0.7%
49
10.7%
705
5.9%
388
0.8%
54
0.7%
45
1.9%
126
1.0%
66
1.1%
72
27.8%
1,826
54.6%
3,585
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
No
advanced
technologies
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Surface
water
systems
serving
10,000
people
or
less:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
2
Baseline
(
Exhibit
3.17)
to
the
Technology
Selection
Delta
for
the
Stage
2
Preferred
Alternative.
TOTAL
USING
CLM
System
Size
(
Population
Served)

NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGY
(
with
CL2
or
CLM)

CL2
CLM
TOTAL
Chlorine
Dioxide
UV
Ozone
MF/
UF
GAC10
GAC10
+
AD
GAC20
GAC20
+
AD
Membranes
TOTAL
A
B
C
D
E
F
G
H
I
J
K
L
M
=
SUM(
D:
L)
N
£
100
38.5%
115
31.3%
93
69.8%
208
3.1%
9
18.6%
56
3.8%
11
0.6%
2
4.1%
12
30.2%
90
42.6%
127
101­
500
32.4%
98
37.7%
114
70.2%
211
2.4%
7
0.4%
1
11.9%
36
9.9%
30
2.3%
7
1.6%
5
1.3%
4
29.8%
90
51.1%
154
501­
1,000
32.4%
35
37.7%
41
70.2%
76
2.4%
3
0.4%
0
11.9%
13
9.9%
11
2.3%
3
1.6%
2
1.3%
1
29.8%
32
51.1%
55
1,001
­
3,300
29.8%
21
43.9%
32
73.8%
53
5.1%
4
0.5%
0
10.1%
7
5.4%
4
2.6%
2
1.8%
1
0.7%
1
26.2%
19
56.8%
41
3,301­
10,000
29.8%
7
43.9%
10
73.8%
17
5.1%
1
0.5%
0
10.1%
2
5.4%
1
2.6%
1
1.8%
0
0.7%
0
26.2%
6
56.8%
13
10,001­
50,000
33.7%
3
38.5%
3
72.2%
6
7.0%
1
0.7%
0
12.8%
1
1.8%
0
2.2%
0
1.8%
0
0.7%
0
0.0%
0
0.7%
0
27.8%
3
56.8%
5
50,001­
100,000
33.7%
0
38.5%
0
72.2%
1
7.0%
0
0.7%
0
12.8%
0
1.8%
0
2.2%
0
1.8%
0
0.7%
0
0.0%
0
0.7%
0
27.8%
0
56.8%
1
100,001­
1
Million
33.7%
0
38.5%
0
72.2%
1
7.0%
0
0.7%
0
12.8%
0
1.8%
0
2.2%
0
1.8%
0
0.7%
0
0.0%
0
0.7%
0
27.8%
0
56.8%
1
>
1
Million
33.7%
0
38.5%
0
72.2%
0
7.0%
0
0.7%
0
12.8%
0
1.8%
0
2.2%
0
1.8%
0
0.7%
0
0.0%
0
0.7%
0
27.8%
0
56.8%
0
Total
%,
Plants
34.4%
280
36.1%
293
70.5%
573
1.9%
15
1.4%
11
7.3%
60
12.5%
102
0.0%
0
0.0%
0
2.9%
23
1.3%
10
2.3%
18
29.5%
240
48.7%
396
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
No
advanced
technologies
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Surface
water
systems
serving
10,000
people
or
less:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
2
Baseline
(
Exhibit
3.17)
to
the
Technology
Selection
Delta
for
the
Stage
2
Preferred
Alternative.
TOTAL
USING
CLM
System
Size
(
Population
Served)
Exhibit
6.15a
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
Exhibit
6.15b
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Surface
Water
Plants,
Preferred
Regulatory
Alternative
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
37
July
2003
6.4.2.3
Ground
Water
Compliance
Forecasts
Appendix
B
provides
a
detailed
methodology
and
the
results
for
the
compliance
forecasts
for
all
ground
water
systems.
In
summary,
the
compliance
forecast
for
large
ground
water
plants
was
generated
using
the
ICR
Ground
Water
Delphi
Process,
which
convened
a
group
of
ground
water
system
experts.
The
results
were
stratified
based
on
plant
location
(
Florida
or
Non­
Florida)
and
extrapolated
to
national
levels.
Because
large
and
medium
ground
water
plants
are
very
similar
with
respect
to
treatment
configurations
and
well
fields,
the
compliance
forecast
for
large
ground
water
plants
was
also
used
for
medium
ground
water
plants
(
the
same
Florida/
Non­
Florida
stratification
was
applied).
The
compliance
forecast
for
small
ground
water
plants
was
based
on
results
of
the
Large
Ground
Water
Delphi
process,
but
was
adjusted
to
account
for
differences
in
total
organic
carbon
(
TOC),
softening
use,
and
Florida/
Non­
Florida
proportions.

Exhibits
6.16a
and
6.16b
present
the
technology
selection
deltas
that
were
used
for
costing
purposes.
EPA
used
these
deltas
to
estimate
the
ground
water
treatment
costs
of
complying
with
the
Stage
2
DBPR.
Exhibits
6.17a
and
6.17b
present
EPA's
prediction
of
technologies
that
will
be
employed
after
systems
comply
with
the
Stage
2
DBPR.

6.4.2.4
Uncertainties
in
Compliance
Forecast
There
are
uncertainties
associated
with
the
estimates
of
plants
making
treatment
changes
in
Exhibit
6.14
One
is
the
effect
of
the
IDSE
on
predictions
of
non­
compliance.
The
number
of
plants
adding
chloramines
or
advanced
technology
could
be
understated
because
plants
may
find
higher
TTHM
or
HAA5
concentrations
at
new
sites
identified
during
the
IDSE.
The
number
of
plants
adding
chloramines
or
advanced
technology,
however,
may
be
overstated
because
of
conservative
assumptions
used
in
the
analysis.
For
example,
compliance
determination
for
plants
is
made
assuming
a
20
percent
margin
of
safety
under
the
MCLs.
Systems
complying
by
switching
to
chloramines
may
choose
to
meet
the
Stage
2
MCLs
with
a
much
smaller
margin
of
safety
since
chloramines
dampen
the
variability
of
DBP
concentrations
on
distribution
systems.
Also,
EPA
believes
that
the
estimated
number
of
ground
water
and
small
surface
water
plants
changing
technology
may
be
biased
upward
because
their
monitoring
requirements
and,
thus,
compliance
calculation,
are
expected
to
be
very
similar
from
the
Stage
1
to
Stage
2
DBPR.
Chapter
7
provides
a
more
complete
discussion
of
these
uncertainties
and
includes
a
quantitative
analysis
to
assess
their
effects.
It
is
not
known
in
which
direction
the
net
impact
of
these
uncertainties
influences
the
estimates
in
Exhibit
6.14.

6.4.3
Results
(
Initial
Capital
and
Steady­
State
O&
M
Costs)

To
estimate
the
total
national
costs
of
treatment,
the
plant
unit
costs
(
capital
and
O&
M
in
$/
plant
as
summarized
in
Exhibits
6.9
and
6.10)
are
multiplied
by
the
Stage
2
DBPR
technology
selection
deltas
(
Exhibits
6.14
and
6.16).
The
calculations
are
performed
for
surface
and
ground
water
plants
and
CWS
and
NTNCWS
systems
separately.
These
costs
are
summed
across
technologies
and
size
categories
to
estimate
the
total
treatment
costs
for
Stage
2
DBPR.

Exhibit
6.18
summarizes
the
estimated
initial
capital
investment
and
annual
steady­
state
O&
M
costs.
Results
for
these
two
exhibits
are
broken
out
by
system
type,
source
water
type,
and
system
size
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
38
July
2003
6­
38
category.
Appendix
K
and
Exhibits
K.
1b
through
K.
1d
provide
similar
cost
information
(
total
initial
capital
and
steady­
state
O&
M
costs)
for
the
Stage
2
DBPR
regulatory
alternatives.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
39
July
2003
CLM
Only
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
Total
Converting
to
CLM
Total
Adding
Technology
A
B
C
D
E
F
G
H
I
J
=
A+
C+
E+
G+
I
K
=
SUM(
A:
I)
£
100
1.0%
80
0.0%
0
1.3%
98
0.0%
0
0.0%
0
0.4%
33
0.0%
0
0.0%
0
0.0%
0
2.3%
178
2.7%
211
101­
500
1.3%
210
0.0%
0
1.4%
225
0.0%
0
0.0%
0
0.2%
25
0.0%
0
0.0%
0
0.0%
0
2.8%
436
2.9%
461
501­
1,000
1.3%
82
0.0%
0
1.4%
88
0.0%
0
0.0%
0
0.2%
10
0.0%
0
0.0%
0
0.0%
0
2.8%
170
2.9%
180
1,001
­
3,300
1.0%
79
0.0%
0
1.3%
102
0.0%
0
0.0%
0
0.0%
0
0.0%
3
0.0%
0
0.0%
0
2.3%
184
2.3%
184
3,301­
10,000
1.0%
50
0.0%
0
1.3%
64
0.0%
0
0.0%
0
0.0%
0
0.0%
2
0.0%
0
0.0%
0
2.3%
116
2.3%
116
10,001­
50,000
1.4%
76
0.1%
3
0.2%
12
0.0%
0
0.2%
8
0.0%
2
0.2%
11
2.0%
108
2.1%
112
50,001­
100,000
1.4%
10
0.1%
0
0.2%
2
0.0%
0
0.2%
1
0.0%
0
0.2%
2
2.0%
15
2.1%
15
100,001­
1
Million
1.3%
11
0.1%
0
0.2%
2
0.0%
0
0.1%
1
0.0%
0
0.2%
2
1.9%
16
1.9%
17
>
1
Million
1.3%
0
0.1%
0
0.2%
0
0.0%
0
0.1%
0
0.0%
0
0.2%
0
1.9%
0
1.9%
0
Total
%,
Plants
1.21%
599
0.00%
0
1.17%
578
0.01%
4
0.03%
15
0.14%
68
0.03%
16
0.00%
2
0.03%
15
2.5%
1,223
2.6%
1,296
Membranes
CL2
Membranes
CLM
System
Size
(
Population
Served)

CLM
Only
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
Total
Converting
to
CLM
Total
Adding
Technology
A
B
C
D
E
F
G
H
I
J
=
A+
C+
E+
G+
I
K
=
SUM(
A:
I)
£
100
1.0%
38
0.0%
0
1.3%
46
0.0%
0
0.0%
0
0.4%
15
0.0%
0
0.0%
0
0.0%
0
2.3%
84
2.7%
99
101­
500
1.3%
35
0.0%
0
1.4%
38
0.0%
0
0.0%
0
0.2%
4
0.0%
0
0.0%
0
0.0%
0
2.8%
73
2.9%
77
501­
1,000
1.3%
10
0.0%
0
1.4%
10
0.0%
0
0.0%
0
0.2%
1
0.0%
0
0.0%
0
0.0%
0
2.8%
20
2.9%
21
1,001
­
3,300
1.0%
3
0.0%
0
1.3%
3
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
2.3%
6
2.3%
6
3,301­
10,000
1.0%
0
0.0%
0
1.3%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
0.0%
0
2.3%
1
2.3%
1
10,001­
50,000
1.4%
0
0.1%
0
0.2%
0
0.0%
0
0.2%
0
0.0%
0
0.2%
0
2.0%
0
2.1%
0
50,001­
100,000
1.4%
0
0.1%
0
0.2%
0
0.0%
0
0.2%
0
0.0%
0
0.2%
0
2.0%
0
2.1%
0
100,001­
1
Million
1.3%
0
0.1%
0
0.2%
0
0.0%
0
0.1%
0
0.0%
0
0.2%
0
1.9%
0
1.9%
0
>
1
Million
1.3%
0
0.1%
0
0.2%
0
0.0%
0
0.1%
0
0.0%
0
0.2%
0
1.9%
0
1.9%
0
Total
%,
Plants
1.17%
85
0.00%
0
1.34%
98
0.00%
0
0.00%
0
0.28%
21
0.00%
0
0.00%
0
0.00%
0
2.5%
183
2.8%
204
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
Source:
Technology
Selection
for
the
Stage
2
Preferred
Alternative
minus
the
Stage
1
Technology
Selection
from
Appendix
C,
Exhibit
C.
2b.
Membranes
CL2
Membranes
CLM
System
Size
(
Population
Served)
Exhibit
6.16a
Technology
Selection
Deltas
for
CWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
Exhibit
6.16b
Technology
Selection
Deltas
for
NTNCWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
40
July
2003
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGIES
CL2
CLM
TOTAL
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
A
B
C
=
A+
B
D
E
F
G
H
I
J
K
L
=
SUM(
D:
K)
M
=
B+
E+
G+
I+
K
£
100
92.5%
7,186
3.9%
301
96.3%
7,488
0.0%
0
1.3%
98
0.0%
0
0.0%
0
0.4%
33
1.0%
80
0.4%
31
0.5%
41
3.7%
284
6.7%
521
101­
500
92.9%
14,608
3.8%
599
96.7%
15,206
0.0%
0
1.4%
225
0.1%
22
0.4%
67
0.2%
25
0.6%
88
0.1%
18
0.5%
73
3.3%
519
6.7%
1,052
501­
1,000
92.9%
5,697
3.8%
234
5,931
0.0%
0
1.4%
88
0.1%
9
0.4%
26
0.2%
10
0.6%
34
0.1%
7
0.5%
28
3.3%
202
6.7%
410
1,001
­
3,300
94.2%
7,436
3.0%
239
97.3%
7,675
0.0%
0
1.3%
102
0.2%
18
0.7%
55
0.0%
0
0.1%
7
0.0%
3
0.4%
30
2.7%
215
5.5%
432
3,301­
10,000
94.2%
4,689
3.0%
151
4,840
0.0%
0
1.3%
64
0.2%
12
0.7%
35
0.0%
0
0.1%
4
0.0%
2
0.4%
19
2.7%
136
5.5%
273
10,001­
50,000
87.0%
4,671
8.7%
467
95.7%
5,137
0.9%
48
1.0%
54
0.0%
0
0.2%
10
1.7%
91
0.5%
26
4.3%
230
10.4%
557
50,001­
100,000
87.0%
643
8.7%
64
707
0.9%
7
1.0%
7
0.0%
0
0.2%
1
1.7%
13
0.5%
4
4.3%
32
10.4%
77
100,001­
1
Million
87.7%
767
8.3%
73
96.0%
840
0.9%
8
0.9%
8
0.0%
0
0.2%
1
1.7%
15
0.4%
4
4.0%
35
9.8%
86
>
1
Million
87.7%
16
8.3%
2
17
0.9%
0
0.9%
0
0.0%
0
0.2%
0
1.7%
0
0.4%
0
4.0%
1
9.8%
2
Total
%,
Plants
92.4%
45,713
4.3%
2,128
96.7%
47,841
0.0%
0
1.2%
578
0.3%
124
0.5%
253
0.1%
68
0.5%
227
0.4%
180
0.5%
224
3.3%
1,653
6.9%
3,409
System
Size
(
Population
Served)
TOTAL
USING
CLM
Membranes
CL2
Membranes
CLM
NO
ADVANCED
TECHNOLOGIES
1
WITH
ADVANCED
TECHNOLOGIES
CL2
CLM
TOTAL
UV
CL2
UV
CLM
Ozone
CL2
Ozone
CLM
GAC20
CL2
GAC20
CLM
TOTAL
A
B
C
=
A+
B
D
E
F
G
H
I
J
K
L
=
SUM(
D:
K)
M
=
B+
E+
G+
I+
K
£
100
92.5%
3,386
3.9%
142
96.3%
3,528
0.0%
0
1.3%
46
0.0%
0
0.0%
0
0.4%
15
1.0%
38
0.4%
15
0.5%
19
3.7%
134
6.7%
246
101­
500
92.9%
2,438
3.8%
100
96.7%
2,538
0.0%
0
1.4%
38
0.1%
4
0.4%
11
0.2%
4
0.6%
15
0.1%
3
0.5%
12
3.3%
87
6.7%
176
501­
1,000
92.9%
666
3.8%
27
693
0.0%
0
1.4%
10
0.1%
1
0.4%
3
0.2%
1
0.6%
4
0.1%
1
0.5%
3
3.3%
24
6.7%
48
1,001
­
3,300
94.2%
251
3.0%
8
97.3%
259
0.0%
0
1.3%
3
0.2%
1
0.7%
2
0.0%
0
0.1%
0
0.0%
0
0.4%
1
2.7%
7
5.5%
15
3,301­
10,000
94.2%
26
3.0%
1
27
0.0%
0
1.3%
0
0.2%
0
0.7%
0
0.0%
0
0.1%
0
0.0%
0
0.4%
0
2.7%
1
5.5%
1
10,001­
50,000
87.0%
4
8.7%
0
95.7%
4
0.9%
0
1.0%
0
0.0%
0
0.2%
0
1.7%
0
0.5%
0
4.3%
0
10.4%
0
50,001­
100,000
87.0%
0
8.7%
0
0
0.9%
0
1.0%
0
0.0%
0
0.2%
0
1.7%
0
0.5%
0
4.3%
0
10.4%
0
100,001­
1
Million
87.7%
1
8.3%
0
96.0%
1
0.9%
0
0.9%
0
0.0%
0
0.2%
0
1.7%
0
0.4%
0
4.0%
0
9.8%
0
>
1
Million
87.7%
0
8.3%
0
0
0.9%
0
0.9%
0
0.0%
0
0.2%
0
1.7%
0
0.4%
0
4.0%
0
9.8%
0
Total
%,
Plants
92.7%
6,772
3.8%
279
96.5%
7,051
0.0%
0
1.3%
98
0.1%
5
0.2%
16
0.3%
21
0.8%
57
0.3%
19
0.5%
36
3.5%
252
6.7%
486
Note:
Detail
may
not
add
to
totals
due
to
independent
rounding
1
No
advanced
technologies
includes
conventional,
non­
conventional,
and
softening
plants.
Source:
Add
Technologies­
in­
Place
for
the
Pre­
Stage
2
Baseline
(
Exhibit
3.18)
to
the
Technology
Selection
Delta
for
the
Stage
2
Preferred
Alternative.
System
Size
(
Population
Served)
TOTAL
USING
CLM
Membranes
CL2
Membranes
CLM
Exhibit
6.17a
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
CWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
Exhibit
6.17b
Post­
Stage
2
DBPR
Technologies­
in­
Place
for
NTNCWS
Disinfecting
Ground
Water
Plants,
Preferred
Regulatory
Alternative
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
41
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

<
100
0.76
$
0.75
$
0.61
$
0.90
$
0.14
$
0.14
$
0.14
$
0.15
$

101­
500
3.43
$
3.43
$
2.90
$
3.96
$
0.65
$
0.65
$
0.60
$
0.70
$

501­
1,000
3.14
$
3.14
$
2.66
$
3.62
$
0.50
$
0.50
$
0.46
$
0.54
$

1,001­
3,300
11.42
$
11.42
$
9.83
$
13.03
$
1.64
$
1.64
$
1.52
$
1.76
$

3,301­
10K
27.52
$
27.50
$
23.86
$
31.21
$
2.58
$
2.58
$
2.40
$
2.76
$

10,001­
50K
57.05
$
57.09
$
50.18
$
63.84
$
3.40
$
3.40
$
3.22
$
3.59
$

50,001­
100K
31.63
$
31.65
$
27.80
$
35.43
$
1.82
$
1.82
$
1.72
$
1.92
$

100,001­
1M
82.26
$
82.29
$
72.18
$
92.25
$
4.64
$
4.64
$
4.37
$
4.91
$

>
1
Million
42.85
$
42.87
$
37.27
$
48.40
$
2.96
$
2.96
$
2.77
$
3.15
$

All
Sizes
260.04
$
260.16
$
227.28
$
292.63
$
18.33
$
18.33
$
17.20
$
19.48
$

<
100
0.47
$
0.47
$
0.38
$
0.56
$
0.09
$
0.09
$
0.08
$
0.09
$

101­
500
1.31
$
1.31
$
1.11
$
1.51
$
0.25
$
0.25
$
0.23
$
0.27
$

501­
1,000
0.72
$
0.72
$
0.61
$
0.83
$
0.11
$
0.11
$
0.10
$
0.12
$

1,001­
3,300
0.72
$
0.72
$
0.62
$
0.83
$
0.10
$
0.10
$
0.10
$
0.11
$

3,301­
10K
0.57
$
0.57
$
0.49
$
0.64
$
0.05
$
0.05
$
0.05
$
0.05
$

10,001­
50K
0.51
$
0.51
$
0.45
$
0.58
$
0.03
$
0.03
$
0.03
$
0.03
$

50,001­
100K
0.13
$
0.13
$
0.12
$
0.15
$
0.01
$
0.01
$
0.01
$
0.01
$

100,001­
1M
0.21
$
0.21
$
0.18
$
0.23
$
0.01
$
0.01
$
0.01
$
0.01
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
4.64
$
4.64
$
3.95
$
5.33
$
0.65
$
0.65
$
0.60
$
0.69
$

264.68
$
264.80
$
231.23
$
297.96
$
18.98
$
18.98
$
17.80
$
20.17
$

<
100
8.98
$
8.98
$
7.79
$
10.18
$
1.05
$
1.05
$
0.98
$
1.11
$

101­
500
22.85
$
22.85
$
19.63
$
26.07
$
2.43
$
2.43
$
2.25
$
2.60
$

501­
1,000
12.67
$
12.68
$
10.88
$
14.46
$
1.24
$
1.24
$
1.16
$
1.33
$

1,001­
3,300
20.95
$
20.95
$
17.48
$
24.40
$
1.70
$
1.70
$
1.56
$
1.83
$

3,301­
10K
31.47
$
31.46
$
25.85
$
37.05
$
1.43
$
1.43
$
1.32
$
1.53
$

10,001­
50K
55.86
$
55.85
$
50.42
$
61.34
$
4.98
$
4.97
$
4.71
$
5.25
$

50,001­
100K
14.96
$
14.96
$
13.38
$
16.55
$
1.33
$
1.33
$
1.24
$
1.41
$

100,001­
1M
26.96
$
26.96
$
24.00
$
29.97
$
2.68
$
2.68
$
2.50
$
2.87
$

>
1
Million
2.28
$
2.28
$
2.01
$
2.56
$
0.31
$
0.31
$
0.28
$
0.33
$

All
Sizes
196.99
$
196.97
$
171.45
$
222.58
$
17.13
$
17.13
$
16.00
$
18.28
$

<
100
4.18
$
4.18
$
3.65
$
4.71
$
0.47
$
0.47
$
0.42
$
0.50
$

101­
500
4.16
$
4.16
$
3.59
$
4.74
$
0.43
$
0.43
$
0.39
$
0.46
$

501­
1,000
1.90
$
1.90
$
1.64
$
2.16
$
0.18
$
0.18
$
0.16
$
0.20
$

1,001­
3,300
0.88
$
0.88
$
0.74
$
1.03
$
0.06
$
0.06
$
0.05
$
0.06
$

3,301­
10K
0.28
$
0.28
$
0.23
$
0.33
$
0.01
$
0.01
$
0.01
$
0.01
$

10,001­
50K
0.12
$
0.12
$
0.11
$
0.13
$
0.01
$
0.01
$
0.01
$
0.01
$

50,001­
100K
0.02
$
0.02
$
0.02
$
0.03
$
0.00
$
0.00
$
0.00
$
0.00
$

100,001­
1M
0.12
$
0.12
$
0.11
$
0.13
$
0.01
$
0.01
$
0.01
$
0.01
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
11.66
$
11.67
$
10.08
$
13.27
$
1.17
$
1.17
$
1.06
$
1.27
$

208.66
$
208.64
$
181.52
$
235.85
$
18.30
$
18.29
$
17.06
$
19.54
$

473.34
$
473.45
$
412.76
$
533.81
$
37.27
$
37.27
$
34.86
$
39.71
$

Notes:

Source:
O&
M
Costs
Mean
Value
Median
Value
90
Percent
Confidence
Bound
Subtotal
Surface
Water
CWSs
NTNCWSs
Source
Mean
Value
Median
Value
90
Percent
Confidence
Bound
System
Classification
System
Size
(
population
served)
Capital
Costs
Ground
Water
CWSs
NTNCWSs
Subtotal
Total
All
values
in
millions
of
year
2000
dollars.

Detail
may
not
add
exactly
to
totals
due
to
independent
roundinH.
Derived
by
multiplying
unit
costs
in
Exhibits
6.9
and
6.10
by
Technology
Selection
Deltas
in
Exhibits
6.14
and
6.16
for
the
Preferred
Alternative,
summed
for
all
technologies.
This
exhibit
is
identical
to
Exhibit
K.
1a.
Exhibit
6.18
Total
Initial
Capital
Costs
($
Millions)
and
Steady­
State
O&
M
Costs
($
Millions/
Year)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
42
July
2003
6.5
Projecting
and
Discounting
Costs
As
described
in
detail
in
section
6.1.1.4,
it
is
common
practice
to
adjust
cost
values
that
occur
at
some
point
in
the
future
to
a
common,
present
value
using
social
discount
rates
so
that
they
can
be
compared
to
monetized
benefits.
In
summary,
the
methodology
for
projecting
and
discounting
costs
is
as
follows:

°
Project
all
nominal
costs
(
treatment,
non­
treatment,
and
State)
over
a
25­
year
time
horizon
based
on
the
rule
implementation
schedule
in
Appendix
D.

°
Calculate
total
present
value
costs
using
social
discount
rates.
The
same
rates
were
used
as
for
the
benefits
calculation:
3
and
7
percent
(
see
section
6.1.1.4
for
a
discussion
of
these
rates).

°
Annualize
the
costs
over
25
years
using
the
same
social
discount
rates.

Appendix
K
contains
results
from
each
step
above
for
each
regulatory
alternative.
For
the
Preferred
Alternative,
Exhibits
K.
2a
through
K.
2ar
show
the
nominal
costs
projected
over
the
rule
schedule,
and
Exhibits
K.
2as
through
K.
2cf
show
the
present
value
of
each
cost
calculated
to
the
expected
year
of
rule
implementation
(
2003).
The
annualization
step
is
shown
at
the
bottom
of
the
present
value
exhibits.

Exhibits
6.19a
and
6.19b
present
the
stream
of
present
value
costs
and
the
total
annualized
costs
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
at
3
and
7
percent
discount
rates,
respectively.
These
tables
are
equivalent
to
Exhibits
K.
2as
and
K.
2aw
in
Appendix
K.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
43
July
2003
Primacy
Agencies
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
30.3
$
30.3
$
30.3
$
0.1
$
0.1
$
0.1
$
1.4
$
1.4
$
1.4
$
0.0
$
0.0
$
0.0
$
4.4
$
36.2
$
36.2
$
36.2
$

2004
28.6
$
28.6
$
28.6
$
0.1
$
0.1
$
0.1
$
1.2
$
1.2
$
1.2
$
0.0
$
0.0
$
0.0
$
4.6
$
34.5
$
34.5
$
34.5
$

2005
41.2
$
36.2
$
46.1
$
0.6
$
0.6
$
0.7
$
30.1
$
26.7
$
33.4
$
1.8
$
1.6
$
2.0
$
0.6
$
74.3
$
65.7
$
82.9
$

2006
46.4
$
41.4
$
51.3
$
0.7
$
0.6
$
0.8
$
33.3
$
29.9
$
36.8
$
1.4
$
1.3
$
1.6
$
5.4
$
87.3
$
78.6
$
95.9
$

2007
43.6
$
38.6
$
48.5
$
0.7
$
0.6
$
0.8
$
30.8
$
27.4
$
34.3
$
1.5
$
1.3
$
1.7
$
0.3
$
76.9
$
68.2
$
85.6
$

2008
44.8
$
39.8
$
49.8
$
0.8
$
0.7
$
0.9
$
33.8
$
30.3
$
37.3
$
2.0
$
1.8
$
2.2
$
0.3
$
81.6
$
72.9
$
90.4
$

2009
44.4
$
39.4
$
49.3
$
0.8
$
0.7
$
0.9
$
34.1
$
30.6
$
37.7
$
1.6
$
1.4
$
1.8
$
0.3
$
81.2
$
72.5
$
90.0
$

2010
44.8
$
39.8
$
49.7
$
0.8
$
0.7
$
0.9
$
36.9
$
33.3
$
40.4
$
1.7
$
1.5
$
1.9
$
0.3
$
84.5
$
75.7
$
93.3
$

2011
16.6
$
15.2
$
18.0
$
0.8
$
0.7
$
0.8
$
24.0
$
21.9
$
26.2
$
1.7
$
1.5
$
1.9
$
0.3
$
43.4
$
39.6
$
47.2
$

2012
16.6
$
15.2
$
18.0
$
0.8
$
0.7
$
0.9
$
24.0
$
21.9
$
26.1
$
1.8
$
1.6
$
2.0
$
0.3
$
43.4
$
39.6
$
47.2
$

2013
16.6
$
15.2
$
17.9
$
0.8
$
0.7
$
0.9
$
23.9
$
21.8
$
26.1
$
1.8
$
1.6
$
2.0
$
0.3
$
43.4
$
39.6
$
47.2
$

2014
12.4
$
11.5
$
13.2
$
0.5
$
0.5
$
0.5
$
15.5
$
14.6
$
16.3
$
0.8
$
0.8
$
0.9
$
0.2
$
29.4
$
27.7
$
31.2
$

2015
12.0
$
11.2
$
12.8
$
0.5
$
0.4
$
0.5
$
15.0
$
14.2
$
15.8
$
0.8
$
0.7
$
0.9
$
0.2
$
28.5
$
26.8
$
30.3
$

2016
11.6
$
10.9
$
12.4
$
0.5
$
0.4
$
0.5
$
14.6
$
13.8
$
15.4
$
0.8
$
0.7
$
0.9
$
0.2
$
27.7
$
26.1
$
29.4
$

2017
11.3
$
10.6
$
12.1
$
0.4
$
0.4
$
0.5
$
14.1
$
13.4
$
14.9
$
0.8
$
0.7
$
0.8
$
0.2
$
26.9
$
25.3
$
28.5
$

2018
11.0
$
10.3
$
11.7
$
0.4
$
0.4
$
0.5
$
13.7
$
13.0
$
14.5
$
0.8
$
0.7
$
0.8
$
0.2
$
26.1
$
24.6
$
27.7
$

2019
10.7
$
10.0
$
11.4
$
0.4
$
0.4
$
0.4
$
13.3
$
12.6
$
14.1
$
0.7
$
0.7
$
0.8
$
0.2
$
25.4
$
23.9
$
26.9
$

2020
10.3
$
9.7
$
11.0
$
0.4
$
0.4
$
0.4
$
12.9
$
12.3
$
13.6
$
0.7
$
0.6
$
0.8
$
0.2
$
24.6
$
23.2
$
26.1
$

2021
10.0
$
9.4
$
10.7
$
0.4
$
0.4
$
0.4
$
12.6
$
11.9
$
13.2
$
0.7
$
0.6
$
0.7
$
0.2
$
23.9
$
22.5
$
25.3
$

2022
9.8
$
9.1
$
10.4
$
0.4
$
0.4
$
0.4
$
12.2
$
11.6
$
12.9
$
0.7
$
0.6
$
0.7
$
0.2
$
23.2
$
21.8
$
24.6
$

2023
9.5
$
8.8
$
10.1
$
0.4
$
0.3
$
0.4
$
11.8
$
11.2
$
12.5
$
0.6
$
0.6
$
0.7
$
0.2
$
22.5
$
21.2
$
23.9
$

2024
9.2
$
8.6
$
9.8
$
0.4
$
0.3
$
0.4
$
11.5
$
10.9
$
12.1
$
0.6
$
0.6
$
0.7
$
0.2
$
21.9
$
20.6
$
23.2
$

2025
8.9
$
8.3
$
9.5
$
0.4
$
0.3
$
0.4
$
11.2
$
10.6
$
11.8
$
0.6
$
0.6
$
0.7
$
0.2
$
21.2
$
20.0
$
22.5
$

2026
8.7
$
8.1
$
9.2
$
0.3
$
0.3
$
0.4
$
10.8
$
10.3
$
11.4
$
0.6
$
0.5
$
0.6
$
0.2
$
20.6
$
19.4
$
21.9
$

2027
8.4
$
7.9
$
9.0
$
0.3
$
0.3
$
0.4
$
10.5
$
10.0
$
11.1
$
0.6
$
0.5
$
0.6
$
0.2
$
20.0
$
18.8
$
21.2
$

Total
517.5
$
474.1
$
561.0
$
12.6
$
11.4
$
13.7
$
453.4
$
416.9
$
490.3
$
25.2
$
22.6
$
27.8
$
19.9
$
1,028.7
$
944.8
$
1,112.9
$

Ann.
29.7
$
27.2
$
32.2
$
0.7
$
0.7
$
0.8
$
26.0
$
23.9
$
28.2
$
1.4
$
1.3
$
1.6
$
1.1
$
59.1
$
54.3
$
63.9
$

Notes:

Ann
=
value
of
total
annualized
at
discount
rate.

Source:
Identical
to
K.
2as,
which
is
derived
from
Exhibits
K.
2a
through
rr.
90
Percent
Confidence
Bound
Total
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Surface
Water
NTNCWS
Disinfecting
Ground
Water
NTNCWS
Surface
Water
CWS
Mean
Value
Disinfecting
Ground
Water
CWS
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.
Mean
Value
Mean
Value
90
Percent
Confidence
Bound
Point
Estimate
Mean
Value
90
Percent
Confidence
Bound
Mean
Value
Exhibit
6.19a
Total
Annualized
Costs
at
3
Percent
Social
Discount
Rate
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
44
July
2003
Primacy
Agencies
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
30.3
$
30.3
$
30.3
$
0.1
$
0.1
$
0.1
$
1.4
$
1.4
$
1.4
$
0.0
$
0.0
$
0.0
$
4.4
$
36.2
$
36.2
$
36.2
$

2004
27.6
$
27.6
$
27.6
$
0.1
$
0.1
$
0.1
$
1.2
$
1.2
$
1.2
$
0.0
$
0.0
$
0.0
$
4.4
$
33.2
$
33.2
$
33.2
$

2005
38.2
$
33.6
$
42.7
$
0.6
$
0.5
$
0.7
$
27.9
$
24.7
$
31.0
$
1.7
$
1.5
$
1.8
$
0.6
$
68.8
$
60.9
$
76.8
$

2006
41.4
$
36.9
$
45.8
$
0.6
$
0.5
$
0.7
$
29.7
$
26.7
$
32.8
$
1.3
$
1.1
$
1.4
$
4.9
$
77.8
$
70.1
$
85.6
$

2007
37.4
$
33.1
$
41.7
$
0.6
$
0.5
$
0.7
$
26.5
$
23.5
$
29.5
$
1.3
$
1.1
$
1.5
$
0.3
$
66.0
$
58.6
$
73.5
$

2008
37.0
$
32.9
$
41.1
$
0.6
$
0.6
$
0.7
$
27.9
$
25.0
$
30.8
$
1.6
$
1.5
$
1.8
$
0.2
$
67.5
$
60.3
$
74.7
$

2009
35.3
$
31.3
$
39.2
$
0.6
$
0.6
$
0.7
$
27.2
$
24.4
$
30.0
$
1.3
$
1.2
$
1.5
$
0.2
$
64.6
$
57.7
$
71.6
$

2010
34.3
$
30.5
$
38.1
$
0.6
$
0.6
$
0.7
$
28.2
$
25.5
$
31.0
$
1.3
$
1.2
$
1.5
$
0.2
$
64.7
$
58.0
$
71.4
$

2011
12.2
$
11.2
$
13.3
$
0.6
$
0.5
$
0.6
$
17.7
$
16.1
$
19.3
$
1.3
$
1.1
$
1.4
$
0.2
$
32.0
$
29.2
$
34.8
$

2012
11.8
$
10.8
$
12.8
$
0.6
$
0.5
$
0.6
$
17.0
$
15.5
$
18.5
$
1.3
$
1.1
$
1.4
$
0.2
$
30.8
$
28.1
$
33.5
$

2013
11.3
$
10.4
$
12.3
$
0.6
$
0.5
$
0.6
$
16.4
$
14.9
$
17.8
$
1.2
$
1.1
$
1.4
$
0.2
$
29.6
$
27.1
$
32.2
$

2014
8.1
$
7.6
$
8.7
$
0.3
$
0.3
$
0.3
$
10.2
$
9.6
$
10.7
$
0.6
$
0.5
$
0.6
$
0.2
$
19.3
$
18.2
$
20.5
$

2015
7.6
$
7.1
$
8.1
$
0.3
$
0.3
$
0.3
$
9.5
$
9.0
$
10.0
$
0.5
$
0.5
$
0.6
$
0.2
$
18.1
$
17.0
$
19.2
$

2016
7.1
$
6.6
$
7.6
$
0.3
$
0.3
$
0.3
$
8.9
$
8.4
$
9.4
$
0.5
$
0.4
$
0.5
$
0.1
$
16.9
$
15.9
$
17.9
$

2017
6.6
$
6.2
$
7.1
$
0.3
$
0.2
$
0.3
$
8.3
$
7.9
$
8.7
$
0.5
$
0.4
$
0.5
$
0.1
$
15.8
$
14.8
$
16.7
$

2018
6.2
$
5.8
$
6.6
$
0.2
$
0.2
$
0.3
$
7.8
$
7.3
$
8.2
$
0.4
$
0.4
$
0.5
$
0.1
$
14.7
$
13.9
$
15.6
$

2019
5.8
$
5.4
$
6.2
$
0.2
$
0.2
$
0.2
$
7.2
$
6.9
$
7.6
$
0.4
$
0.4
$
0.4
$
0.1
$
13.8
$
13.0
$
14.6
$

2020
5.4
$
5.1
$
5.8
$
0.2
$
0.2
$
0.2
$
6.8
$
6.4
$
7.1
$
0.4
$
0.3
$
0.4
$
0.1
$
12.9
$
12.1
$
13.7
$

2021
5.1
$
4.7
$
5.4
$
0.2
$
0.2
$
0.2
$
6.3
$
6.0
$
6.7
$
0.3
$
0.3
$
0.4
$
0.1
$
12.0
$
11.3
$
12.8
$

2022
4.7
$
4.4
$
5.0
$
0.2
$
0.2
$
0.2
$
5.9
$
5.6
$
6.2
$
0.3
$
0.3
$
0.4
$
0.1
$
11.3
$
10.6
$
11.9
$

2023
4.4
$
4.1
$
4.7
$
0.2
$
0.2
$
0.2
$
5.5
$
5.2
$
5.8
$
0.3
$
0.3
$
0.3
$
0.1
$
10.5
$
9.9
$
11.1
$

2024
4.1
$
3.9
$
4.4
$
0.2
$
0.2
$
0.2
$
5.2
$
4.9
$
5.4
$
0.3
$
0.3
$
0.3
$
0.1
$
9.8
$
9.2
$
10.4
$

2025
3.9
$
3.6
$
4.1
$
0.2
$
0.1
$
0.2
$
4.8
$
4.6
$
5.1
$
0.3
$
0.2
$
0.3
$
0.1
$
9.2
$
8.6
$
9.7
$

2026
3.6
$
3.4
$
3.8
$
0.1
$
0.1
$
0.2
$
4.5
$
4.3
$
4.8
$
0.2
$
0.2
$
0.3
$
0.1
$
8.6
$
8.1
$
9.1
$

2027
3.4
$
3.1
$
3.6
$
0.1
$
0.1
$
0.1
$
4.2
$
4.0
$
4.4
$
0.2
$
0.2
$
0.3
$
0.1
$
8.0
$
7.5
$
8.5
$

Total
392.8
$
359.6
$
425.9
$
8.5
$
7.7
$
9.4
$
316.2
$
289.1
$
343.4
$
17.5
$
15.6
$
19.3
$
17.3
$
752.3
$
689.4
$
815.3
$

Ann.
33.7
$
30.9
$
36.5
$
0.7
$
0.7
$
0.8
$
27.1
$
24.8
$
29.5
$
1.5
$
1.3
$
1.7
$
1.5
$
64.6
$
59.2
$
70.0
$

Notes:

Ann
=
value
of
total
annualized
at
discount
rate.

Source:
Identical
to
Exhibit
K.
2.
aw,
which
is
derived
from
Exhibits
K.
2a
through
K.
2ar.
Total
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Surface
Water
NTNCWS
Disinfecting
Ground
Water
NTNCWS
Mean
Value
Mean
Value
Disinfecting
Ground
Water
CWS
90
Percent
Confidence
Bound
Surface
Water
CWS
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.
Mean
Value
Mean
Value
Mean
Value
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Point
Estimate
Exhibit
6.19b
Total
Annualized
Costs
at
7
Percent
Social
Discount
Rate
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
45
July
2003
6.6
Household
Costs
EPA
assumes
that
systems
will,
to
the
extent
possible,
pass
cost
increases
on
to
their
customers
through
increases
in
water
rates.
Exhibit
6.20
presents
the
mean,
median,
and
90th
percentile
of
expected
increases,
along
with
the
percent
of
households
that
are
expected
to
face
an
increase
of
$
1
or
less
per
month
($
12
or
less
per
year)
or
$
10
or
less
each
month
($
120
or
less
per
year).
Data
are
provided
for
all
systems
subject
to
the
rule
and
also
only
the
subset
of
systems
adding
treatment.
Note
that
household
cost
increases
in
Exhibit
6.20
includes
costs
for
non­
treatment­
related
rule
activities
(
implementation,
IDSE,
additional
routine
monitoring,
and
significant
excursion
evaluations).

Exhibit
6.21
shows
the
cumulative
distribution
of
household
cost
increases
for
all
systems,
and
Exhibit
6.22
shows
the
distribution
of
household
cost
increases
for
only
those
systems
adding
treatment.
Additionally,
Exhibit
6.22
separately
shows
the
cumulative
distributions
for
systems
adding
treatment
for
the
five
small
system
size
categories.

As
shown
in
Exhibit
6.20,
the
mean,
median,
and
90th
percentile
household
cost
for
all
systems
(
including
those
that
do
not
add
treatment)
are
$
0.51,
$
0.02,
and
$
0.47,
respectively.
The
mean,
median,
and
90th
percentile
household
costs
for
systems
that
install
new
treatment
technologies
are
$
8.52,
$
1.22
and
$
20.57,
respectively.
Note
that
the
number
of
households
affected
by
plants
installing
treatment
could
be
greater
than
shown
in
Exhibit
6.20
because
an
entire
system
would
most
likely
incur
costs
even
if
less
than
the
total
number
of
plants
for
that
system
add
treatment
(
this
would
result
in
lower
household
costs,
however).

EPA
estimates
that,
as
a
whole,
households
subject
to
the
Stage
2
DBPR
face
minimal
increases
in
their
annual
costs.
Approximately
86
percent
of
the
households
potentially
subject
to
the
rule
are
served
by
systems
serving
at
least
10,000
people;
these
systems
experience
the
lowest
increases
in
costs
due
to
significant
economies
of
scale.
Households
served
by
small
systems
that
add
treatment
will
face
the
greatest
increases
in
annual
costs.
Exhibit
6.22c
provides
additional
detail
regarding
the
distribution
of
household
costs
for
small
systems.

Although
cost
model
results
predict
that
a
few
very
small
systems
will
experience
large
household
cost
increases
as
a
result
of
adding
advanced
technology
for
the
Stage
2
DBPR,
these
predictions
are
probably
not
realistic
because
small
systems
have
other
alternatives
available
to
them
besides
adding
treatment.
For
example,
some
of
these
systems
currently
may
be
operated
on
a
part­
time
basis;
therefore,
they
may
be
able
to
modify
the
current
operational
schedule
or
use
excessive
capacity
to
avoid
installing
a
costly
technology
to
comply
with
the
Stage
2
DBPR.
The
system
also
may
identify
another
water
source
that
has
lower
TTHM
and
HAA5
precursor
levels.
Systems
that
can
identify
such
an
alternate
water
source
may
not
have
to
treat
that
water
as
intensely
as
their
current
source,
resulting
in
lower
treatment
costs.
Systems
may
elect
to
connect
to
a
neighboring
water
system.
While
connecting
to
another
system
may
not
be
feasible
for
some
remote
systems,
EPA
estimates
that
more
than
22
percent
of
all
small
water
systems
are
located
within
metropolitan
regions
(
USEPA
2000d)
where
distances
between
neighboring
systems
will
not
present
a
prohibitive
barrier.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
46
July
2003
Total
Number
of
Households
Served
Mean
Annual
Household
Cost
Increase
Median
Annual
Household
Cost
Increase
90th
Percentile
Annual
Household
Cost
Increase
95th
Percentile
Annual
Household
Cost
Increase
Percentage
of
Annual
Household
Cost
Increase
<
$
12
Percentage
of
Annual
Household
Cost
Increase
<
$
120
All
Systems
98,254,000
(
100.0)
$
0.51
$
0.02
$
0.47
$
0.79
99.24%
99.96%
All
Small
Systems
14,522,000
(
100.0)
$
1.66
$
0.18
$
0.90
$
2.96
98.23%
99.74%
SW
£
10,000
3,165,000
(
3.2%)
$
3.72
$
0.90
$
2.96
$
5.51
97.89%
99.09%
SW
>
10,000
58,876,000
(
59.9%)
$
0.34
$
0.00
$
0.32
$
0.33
99.35%
100.00%
GW
£
10,000
11,357,000
(
11.6%)
$
1.08
$
0.11
$
0.53
$
1.37
98.37%
99.92%
GW
>
10,000
24,857,000
(
25.3%)
$
0.23
$
0.01
$
0.47
$
0.47
99.57%
100.00%
Households
Served
by
Plants
Adding
Treatment
Number
of
Households
Served
(
Percent
of
Total)
Mean
Annual
Household
Cost
Increase
Median
Annual
Household
Cost
Increase
90th
Percentile
Annual
Household
Cost
Increase
95th
Percentile
Annual
Household
Cost
Increase
Percentage
of
Household
Cost
Increase
<
$
12
Percentage
of
Household
Cost
Increase
<
$
120
All
Systems
4,793,000
(
4.9%)
$
8.52
$
1.22
$
20.57
$
33.98
84.47%
99.18%
All
Small
Systems
422,000
(
2.9%)
$
43.78
$
19.05
$
117.68
$
166.67
39.38%
91.12%
SW
£
10,000
142,000
(
4.5%)
$
60.64
$
9.08
$
166.67
$
270.04
54.36%
79.78%
SW
>
10,000
3,868,000
(
6.6%)
$
5.02
$
1.02
$
11.58
$
23.56
90.16%
99.96%
GW
£
10,000
279,000
(
2.5%)
$
35.18
$
19.22
$
72.07
$
117.68
33.71%
96.94%
GW
>
10,000
504,000
(
2.0%)
$
5.90
$
1.33
$
26.33
$
33.24
78.73%
100.00%

Source:
Results
represent
the
sum
of
treatment
and
non­
treatment
costs.
Household
costs
for
treatment
are
derived
from
household
unit
costs
in
Exhibits
6.9c
and
6.10c
combined
with
technology
selection
deltas
in
Exhibits
6.14
and
6.16.
Household
costs
for
non­
treatment­
related
rule
activities
are
derived
from
mean
costs
for
each
system
size
category
for
implementation,
IDSE,
additional
routine
monitoring,
and
significant
excursion
(
as
derived
in
Appendix
H).
See
section
6.1.1
for
additional
information
on
the
derivation
of
household
costs.
Notes:
Detail
may
not
to
total
add
due
to
independent
rounding.
Number
of
households
served
by
systems
adding
treatment
will
be
higher
than
households
served
by
plants
adding
treatment
because
an
entire
system
will
incur
costs
even
if
less
than
the
total
number
of
plants
for
that
system
add
treatment
(
this
would
result
in
lower
household
costs,
however).
Exhibit
6.20
Annual
Household
Cost
Increases
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
47
July
2003
$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
0%
20%
40%
60%
80%
100%

Cumulative
Percent
of
Households
(
N
=
62,037,306)
Annual
Household
Costs
($/
HH/
Year)

$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
99.5%
99.6%
99.7%
99.8%
99.9%
100.0%
Exhibit
6.21a
Household
Cost
Distributions,
All
Surface
Water
Systems
Subject
to
the
Rule
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
48
July
2003
$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
0%
20%
40%
60%
80%
100%

Cumulative
Percent
of
Households
(
N
=
32,721,321)
Annual
Household
Costs
($/
HH/
Year)

$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
99.5%
99.6%
99.7%
99.8%
99.9%
100.0%
Exhibit
6.21b
Household
Cost
Distributions,
All
Ground
Water
Systems
Subject
to
the
Rule
Source:
See
Exhibit
6.20.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
49
July
2003
$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
0%
20%
40%
60%
80%
100%

Cumulative
Percent
of
Households
(
N
=
4,009,873)
Annual
Household
Costs
($/
HH/
Year)

$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
99.5%
99.6%
99.7%
99.8%
99.9%
100.0%
Exhibit
6.22a
Household
Cost
Distributions,
Surface
Water
Systems
Adding
Treatment
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
50
July
2003
$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
0%
20%
40%
60%
80%
100%

Cumulative
Percent
of
Households
(
N
=
727,256)
Annual
Household
Costs
($/
HH/
Year)

$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
99.5%
99.6%
99.7%
99.8%
99.9%
100.0%
Exhibit
6.22b
Household
Cost
Distributions,
Ground
Water
Systems
Adding
Treatment
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
51
July
2003
$
0
$
200
$
400
$
600
$
800
$
1,000
$
1,200
$
1,400
$
1,600
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%

Cumulative
Percent
Affected
(
N
=
391,332)
Annual
Household
Costs
($/
HH/
Year)
S1
S2
S3
S4
S5
Exhibit
6.22c
Household
Cost
Distributions,
Small
Systems
Adding
Treatment
(
Surface
and
Ground)

Note:
S1=
systems
serving
<
100;
S2=
systems
serving
101­
500;
S3=
systems
serving
501­
1,000;
S4=
systems
serving
1,001­
3,300;
S5=
systems
serving
3,301­
10,000.

Source:
See
Exhibit
6.20.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
52
July
2003
6.7
Unquantifiable
Costs
All
significant
costs
that
EPA
has
identified
have
been
quantified.
In
some
instances,
EPA
did
not
include
a
potential
cost
element
because
its
effects
are
relatively
minor
and
difficult
to
estimate.
For
example,
it
may
be
less
costly
for
a
small
system
to
merge
with
neighboring
systems
than
to
add
advanced
treatment.
Such
changes
have
both
costs
(
legal
fees
and
connecting
infrastructure)
and
benefits
(
economies
of
scale).
Likewise,
costs
for
procuring
a
new
source
of
water
would
have
costs
for
new
infrastructure,
but
could
result
in
lower
treatment
costs.
In
the
absence
of
detailed
information
needed
to
evaluate
situations
such
as
these,
EPA
has
included
a
discussion
of
possible
effects
where
appropriate.
In
general,
however,
the
expected
net
effect
of
such
situations
is
lower
costs
to
PWSs.
Thus,
the
EA
tends
to
present
conservatively
high
estimates
of
costs
in
relation
to
unquantifiable
costs.
Such
unquantifiable
costs
are
also
taken
into
account
in
the
evaluation
of
uncertainties
discussed
below.

6.8
Uncertainty
Analysis
The
uncertainties
in
this
cost
analysis
could
result
in
either
an
over­
estimate
or
under­
estimate
of
the
costs
as
presented
in
this
chapter.
Exhibit
6.23
presents
a
summary
of
these
issues,
references
the
section
or
appendix
where
the
information
is
introduced,
and
estimates
the
effects
that
each
may
have
on
national
costs.
Two
of
the
greatest
uncertainties
affecting
the
costs
of
the
Stage
2
DBPR
are
the
SWAT
predictions
and
the
uncertainties
in
the
compliance
forecast.
Uncertainties
associated
with
SWAT
are
discussed
in
detail
in
other
sections,
as
indicated
in
Exhibit
6.23.
Sensitivity
analyses
were
performed
to
assess
the
impact
of
uncertainties
in
the
compliance
forecast.
The
resulting
cost
and
benefits
estimates,
are
provided
in
Chapter
7.

Also
unquantifiable
are
the
potential
costs
or
benefits
of
a
possible
interactive
effect
from
the
promulgation
of
more
than
one
rule
in
a
short
period
of
time.
EPA
has
taken
into
account
compliance
with
the
Stage
1
DBPR
and
the
Ground
Water
Rule,
but
it
has
not
attempted
to
estimate
the
cumulative
effects
of
the
passage
of
other
new
regulations
along
with
the
Stage
2
DBPR.
Particularly,
benefit/
cost
analysis
for
the
Stage
2
DBPR
and
its
companion
rule,
the
LT2ESWTR,
are
performed
independently,
overstating
costs
for
some
portion
of
estimated
national
costs
for
surface
water
systems.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
53
July
2003
Exhibit
6.23
Cost
Uncertainty
Summary
Uncertainty
Section
With
Full
Discussion
of
Uncertainty
Effect
on
Estimate
of
National
Costs
Underestimate
Overestimate
Unknown
Impact
Uncertainty
in
data
quality
of
model
inputs
for
SWAT
Appendix
A
X
Plant­
level
analysis
of
compliance
determination
and
treatment
requirements
used
in
SWAT
Appendix
A
X
SWAT
model
settings
and
assumptions
Appendix
A
X
Predictive
accuracy
of
the
willingness
to
pay
(
WTP)
model
for
regulated
DBPs
Appendix
A
X
20%
operational
safety
factor
in
assessing
plant
compliance
Appendix
A
Appendix
B
X
Treatment
costs
do
not
include
costs
for
operational
changes
in
SWAT
6.4.1.1
X
Medium
operational
and
water
quality
parameters
considered
for
technology
unit
costs
6.4.1.1
X
Economies
of
scale
for
combination
technologies
not
considered
6.4.1.1
X
Low­
cost
alternatives
to
treatment
not
considered
6.4.1.2
X
IDSE
may
affect
compliance
forecast
Chapter
7
X
Compliance
forecast
for
ground
water
and
small
surface
water
systems
may
be
overstated.
Safety
factor
for
Chloramine
systems
may
be
too
high.
7.2
X
Note:
Bold
"
X"
indicates
a
relatively
high
area
of
uncertainty
for
which
EPA
has
conducted
a
sensitivity
analysis
(
see
Chapter
7).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
6­
54
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

Preferred
59.1
$
54.3
$
63.9
$
64.6
$
59.2
$
70.0
$
Alt.
1
182.3
$
165.1
$
199.6
$
195.1
$
175.9
$
214.3
$
Alt.
2
409.6
$
383.6
$
435.7
$
442.7
$
413.4
$
472.2
$
Alt.
3
594.3
$
556.3
$
631.9
$
644.2
$
601.1
$
686.9
$
Note:
Source:
Appendix
K.
For
the
Preferred
Alternative,
see
Exhibit
K.
2as
for
3%
and
K.
2aw
for
7%.
For
Alternative
1,
see
Exhibit
K.
3i
for
3%
and
K.
3m
for
7%.
For
Alternative
2,
see
Exhibit
K.
4i
fr
3%
and
K.
4m
for
7%.
For
Alternative
3,
see
Exhibit
K.
5i
for
3%
and
K.
5m
for
7%.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Rule
Alternative
Total
Annualized
Cost
($
Millions)
3
Percent
Discount
Rate
7
Percent
Discount
Rate
Mean
Estimate
90
Percent
Confidence
Bound
Mean
Estimate
90
Percent
Confidence
Bound
6.9
Comparison
of
Regulatory
Alternatives
During
the
development
of
the
Stage
2
DBPR,
many
regulatory
alternatives
were
considered.
Of
these
alternatives,
four
(
including
the
Preferred
Alternative
analyzed
in
this
chapter)
were
chosen
for
further,
in­
depth
analysis.
Chapter
4
provides
a
description
of
each
alternative.
Appendices
A
and
B
present
compliance
forecasts
for
the
Preferred
Alternative,
and
Appendix
C
presents
the
compliance
forecasts
for
the
other
three
alternatives,
including
the
technology
selection
deltas.

The
same
process
used
for
developing
costs
for
the
Preferred
Alternative
was
used
to
develop
costs
for
the
other
alternatives.
Unit
costs
(
Exhibits
6.9
and
6.10)
were
multiplied
by
the
technology
selection
deltas
presented
in
Appendix
C,
and
results
were
summed
for
all
technologies.
Exhibit
6.24
presents
the
summary
of
annualized
costs
for
each
alternative
(
detailed
costs
for
each
alternative
are
presented
in
Appendix
K).
While
the
total
annualized
costs
in
Exhibit
6.24
include
costs
for
nontreatment
related
rule
activities
(
implementation,
IDSE,
additional
routine
monitoring,
and
significant
excursions),
any
increase
in
cost
for
the
regulatory
alternatives
is
fully
attributable
to
treatment
costs.

Exhibit
6.24
Total
Annualized
Cost
for
the
Stage
2
DBPR
Regulatory
Alternatives
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
1
July
2003
7.
Compliance
Forecast
Sensitivity
Analyses
7.1
Introduction
Some
of
the
uncertainties
in
the
inputs
and
assumptions
used
to
estimate
the
impact
of
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR)
could
lead
to
an
under­
estimate
of
costs
or
benefits
(
or
both),
while
others
may
lead
to
an
over­
estimate.
One
particularly
important
area
of
uncertainty
is
the
effect
that
the
Initial
Distribution
System
Evaluation
(
IDSE)
will
have
on
the
actual
number
of
plants
needed
to
make
a
treatment
change
and
which
treatment
technology
they
can
use
to
comply
with
the
rule
relative
to
the
number
estimated
by
the
Surface
Water
Analytical
Tool
(
SWAT)
and
other
compliance
forecast
methods.
A
second
important
area
of
uncertainty
is
the
predicted
number
of
small
surface
water
plants
and
ground
water
plants
changing
treatment,
given
that
their
Stage
2
DBPR
monitoring
requirements
may
be
the
same
as
their
Stage
1
requirements.

The
purpose
of
the
IDSE
is
to
identify
compliance
monitoring
sites
that
are
representative
of
high
total
trihalomethane
(
TTHM)
and
haloacetic
acid
(
HAA5)
concentrations
in
the
distribution
system.
The
IDSE
may
result
in
systems
finding
higher
distribution
system
disinfection
byproduct
(
DBP)
concentrations
than
predicted
by
SWAT.
The
degree
to
which
this
occurs
influences
the
extent
to
which
plants
may
have
to
add
treatment
to
meet
the
requirements
of
the
Stage
2
DBPR
(
i.
e.,
there
may
be
more
plants
changing
technology
than
are
indicated
for
the
preferred
alternative),
which
would
result
in
higher
costs
and
benefits.
EPA
performed
an
IDSE
sensitivity
analysis
to
quantify
this
potential
effect.
The
methodology
and
results
of
the
IDSE
sensitivity
analysis
are
described
in
Section
7.2.

The
Environmental
Protection
Agency
(
EPA)
believes
that
the
results
of
the
IDSE
sensitivity
analysis
in
section
7.2
provide
an
upper
bound
for
the
cost
and
benefit
estimate.
EPA
believes
that
this
upper
bound
is
unlikely
to
be
reached
by
the
actual
costs
of
the
rule,
however,
because
of
conservative
assumptions
used
to
predict
treatment
changes
that
may
lead
to
over­
predictions
in
costs
and
benefits.
For
example,
compliance
determination
for
plants
is
made
assuming
a
20
percent
margin
of
safety
under
the
MCLs.
Systems
complying
by
switching
to
chloramines
may
choose
to
meet
the
Stage
2
MCLs
with
a
much
smaller
margin
of
safety
since
chloramines
dampen
the
variability
of
DBP
concentrations
on
distribution
systems.

EPA
also
believes
that
the
estimated
number
of
ground
water
and
small
surface
water
plants
changing
technology
and
their
technology
selections
may
be
biased
upward
because
their
monitoring
requirements
and,
thus,
compliance
calculation,
are
expected
to
be
very
similar
from
the
Stage
1
to
Stage
2
DBPR.
The
Stage
1
DBPR
required
only
one
compliance
monitoring
location
(
at
the
point
of
maximum
residence
time)
for
producing
surface
water
systems
serving
between
500
and
10,000
people
and
for
all
ground
water
systems.
The
Stage
2
DBPR
requires
that
these
systems
add
an
additional
site
if
they
determine
that
their
high
TTHM
and
high
HAA5
concentrations
do
not
occur
at
the
same
location.
If
systems
maintain
a
single
monitoring
location
for
the
Stage
2
DBPR,
as
many
are
expected
to
do,
calculation
of
compliance
will
produce
the
same
results
for
the
running
annual
average
(
RAA)
and
locational
running
annual
average
(
LRAA)
measure,
implying
that
they
are
not
likely
to
add
treatment
for
the
Stage
2
DBPR
if
they
comply
with
the
Stage
1
DBPR.
Based
on
evaluation
of
Information
Collection
Rule
(
ICR)
data
and
additional
analyses
for
producing
systems
in
Appendix
H,
EPA
estimates
that
only
41%
of
ground
water
systems
serving
at
least
500
people
and
41%
of
all
surface
water
systems
serving
500
to
10,000
people
will
have
to
add
an
additional
site
for
Stage
2
(
See
Exhibit
H.
8b).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
2
July
2003
To
gauge
the
impact
of
the
potential
high
bias
in
the
compliance
forecast,
EPA
prepared
another
sensitivity
analysis
(
the
"
minimal
impact"
sensitivity
analysis)
that
assumed
that
no
small
surface
water
systems
and
none
of
the
ground
water
systems
make
treatment
changes
to
comply
with
the
Stage
2
DBPR.
The
methodology
and
results
for
this
analysis
are
summarized
in
section
7.3.

7.2
IDSE
Sensitivity
Analysis
To
evaluate
the
potential
impacts
of
the
IDSE
on
costs
and
benefits,
two
sensitivity
analyses
were
performed
(
IDSE
No.
1
and
IDSE
No.
2).
Each
predicts
increases
in
the
percentage
of
plants
that
would
add
treatment
due
to
the
IDSE.
To
simulate
the
increase
in
the
percentage
adding
treatment,
SWAT
was
used
to
develop
large
surface
water
compliance
forecasts
for
LRAA
regulatory
alternatives
at
5
µ
g/
L
(
IDSE
No.
1)
and
10
µ
g/
L
(
IDSE
No.
2)
below
the
TTHM
and
HAA5
MCLs
of
80
and
60
µ
g/
L.
All
analyses
were
evaluated
using
a
20
percent
safety
factor
(
as
in
the
primary
analysis).
The
same
process
used
for
developing
costs
for
the
Preferred
Regulatory
Alternative
was
used
to
develop
costs
for
the
IDSE
sensitivity
analyses.
(
Unit
costs
in
Exhibits
6.9
and
6.10
were
multiplied
by
the
selection
delta
numbers
presented
in
Appendix
C,
Exhibits
C.
31
and
C.
32).
There
is
no
expected
change
in
nontreatment
costs.

Because
small
systems
typically
have
smaller
and
less
complex
distribution
systems,
they
are
less
likely
to
find
higher
TTHM
and
HAA5
concentrations
due
to
the
IDSE.
The
following
adjustments
were
made
to
reduce
the
impacts
of
the
IDSE
on
small
water
systems.

°
The
percentage
changing
technology
and
the
subsequent
increase
in
small
surface
water
system
and
small
ground
water
system
costs
for
IDSE
No.
1
and
No.
2
were
reduced
by
approximately
one­
half.

°
For
all
systems
serving
fewer
than
500
people,
the
costs
for
IDSE
1
and
2
were
further
reduced
to
account
for
systems
receiving
very­
small­
system
waivers
from
the
IDSE
(
75%
are
predicted
to
receive
a
State
waiver;
see
Appendix
H).

°
Because
nontransient
noncommunity
water
systems
(
NTNCWSs)
serving
fewer
than
10,000
are
exempt
from
the
IDSE,
their
treatment
costs
were
assumed
not
to
be
affected
in
the
sensitivity
analysis.

All
compliance
forecasts
(
ending
technologies,
selection
technologies,
and
deltas)
for
IDSE
sensitivity
analyses
are
presented
in
Appendix
C.
Exhibit
7.1
summarizes
the
potential
increase
in
the
percent
of
plants
adding
treatment
that
were
analyzed
under
the
two
IDSE
sensitivity
analyses.
Exhibit
7.2
compares
annual
cases
avoided,
and
the
value
of
benefits
derived
from
those
cases,
for
the
two
IDSE
sensitivity
analyses
to
the
Preferred
Alternative.
Note
that
benefits
(
cases
avoided
and
monetized
benefits)
increase
more
than
three­
fold
for
IDSE
Sensitivity
Analysis
No.
2.

Exhibit
7.3
compares
total
initial
capital
costs
for
the
Preferred
Regulatory
Alternative
and
for
the
two
IDSE
sensitivity
analyses.
Note
that
for
IDSE
Sensitivity
Analysis
No.
2,
the
capital
costs
of
the
rule
are
more
than
doubled.
Exhibits
7.4a
and
7.4b
compare
the
total
annualized
costs
of
the
rule
for
the
IDSE
sensitivity
analyses
to
those
of
the
Preferred
Regulatory
Alternative
at
3
and
7
percent
discount
rates,
respectively.
Total
annualized
costs
include
treatment
costs,
which
changed
for
the
sensitivity
analysis,
and
non­
treatment
costs,
which
are
the
same
for
each.
Additional
cost
breakouts
for
the
IDSE
sensitivity
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
3
July
2003
Percent
Adding
Treatment
Preferred
Alternative
IDSE
No.
1
IDSE
No.
2
SW
£
10,000
3.7%
4.6%
4.8%
SW
>
10,000
5.8%
9.9%
15.1%
GW
£
10,000
2.7%
2.8%
2.9%
GW
>
10,000
2.1%
3.2%
3.6%
analyses
(
Operations
and
Maintenance
(
O&
M),
total
annualized
costs
for
different
public
water
system
(
PWS)
types
and
source
types),
can
be
found
in
Appendix
K
(
sections
K.
6
and
K.
7).

Exhibit
7.1
Total
Percent
Adding
Treatment
from
Stage
1
to
Stage
2
for
IDSE
No.
1
and
IDSE
No.
2
(
CWSs)

Source:
Derived
from
Technology
Selection
Deltas
in
Chapter
6
(
Preferred
Alternative)
and
Appendix
C,
Exhibits
C.
31
and
C.
32
(
IDSE
sensitivity
analyses),
weighted
average
of
three
small
system
size
categories
(
0
­
100,
101
­
1,000,
and
1,000
­
10,000)
and
two
large
system
size
categories
(
10,000
­
100,000,
>
100,000),
adjusted
for
small
systems
as
described
in
section
7.2.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
4
July
2003
Exhibit
7.2
Comparison
of
Estimated
Annual
Cases
and
Annualized
Benefits
for
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative
(
Millions,
2000$)
1
Discount
Rate,
WTP
for
Non­
Fatal
Cases
Preferred
Alternative
IDSE
Sensitivity
Analysis
1
IDSE
Sensitivity
Analysis
2
2%
PAR
Average
Number
of
Annual
Cancer
Cases
Avoided
21
43
66
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
113
($
18
­
258)
$
231
($
37
­
527)
$
360
($
57
­
822)

7
%
Lymphoma
$
98
($
16
­
224)
$
200
($
32
­
457)
$
312
($
50
­
713)

3
%
Bronchitis
$
55
($
13
­
120)
$
112
($
26
­
244)
$
175
($
40
­
381)

7
%
Bronchitis
$
48
($
11
­
104)
$
97
($
22
­
212)
$
152
($
35
­
330)

17%
PAR
Value
Average
Number
of
Annual
Cancer
Cases
Avoided
182
372
580
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
986
($
157
­
2,253)
$
2,014
($
320
­
4,603)
$
3,140
($
499
­
7,175)

7
%
Lymphoma
$
854
($
136
­
1,952)
$
1,746
($
277
­
3,989)
$
2,722
($
433
­
6,219)

3
%
Bronchitis
$
479
($
109
­
1,044)
$
979
($
223
­
2,132)
$
1,526
($
348
­
3,323)

7
%
Bronchitis
$
415
($
95
­
905)
$
849
($
194
­
1,848)
$
1,323
($
302
­
2,882)

Notes:
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
For
preferred
alternative,
see
Exhibit
5.29.
For
IDSE
sensitivity
analyses
number
1,
see
Exhibits
E.
23d
and
g,
F.
14d
and
e,
F.
15d
and
e.
For
IDSE
sensitivity
analysis
number
2,
see
Exhibits
E.
24d
and
g,
F.
16d
and
e,
and
F.
17d
and
e.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
5
July
2003
Preferred
Alternative
IDSE
Sensitivity
1
IDSE
Sensitivity
2
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

<
100
0.76
$
0.61
$
0.90
$
1.08
$
0.86
$
1.29
$
1.51
$
1.27
$
1.74
$

101­
500
3.43
$
2.90
$
3.96
$
5.12
$
4.36
$
5.86
$
9.61
$
8.64
$
10.57
$

501­
1,000
3.14
$
2.66
$
3.62
$
4.76
$
4.07
$
5.44
$
9.92
$
8.99
$
10.86
$

1,001­
3,300
11.42
$
9.83
$
13.03
$
17.65
$
15.28
$
20.07
$
24.77
$
22.08
$
27.49
$

3,301­
10K
27.52
$
23.86
$
31.21
$
42.91
$
37.45
$
48.47
$
63.92
$
57.42
$
70.60
$

10,001­
50K
57.05
$
50.18
$
63.84
$
88.55
$
77.56
$
99.57
$
156.49
$
141.52
$
171.66
$

50,001­
100K
31.63
$
27.80
$
35.43
$
49.12
$
42.94
$
55.30
$
87.38
$
78.92
$
95.94
$

100,001­
1M
82.26
$
72.18
$
92.25
$
129.90
$
113.36
$
146.45
$
231.46
$
208.59
$
254.49
$

>
1
Million
42.85
$
37.27
$
48.40
$
73.81
$
64.21
$
83.25
$
129.91
$
116.57
$
143.36
$

All
Sizes
260.04
$
227.28
$
292.63
$
412.88
$
360.08
$
465.70
$
714.95
$
644.02
$
786.70
$

<
100
0.47
$
0.38
$
0.56
$
0.67
$
0.54
$
0.80
$
0.92
$
0.79
$
1.06
$

101­
500
1.31
$
1.11
$
1.51
$
1.96
$
1.68
$
2.25
$
3.72
$
3.35
$
4.08
$

501­
1,000
0.72
$
0.61
$
0.83
$
1.09
$
0.93
$
1.24
$
2.25
$
2.04
$
2.46
$

1,001­
3,300
0.72
$
0.62
$
0.83
$
1.12
$
0.97
$
1.27
$
1.57
$
1.39
$
1.74
$

3,301­
10K
0.57
$
0.49
$
0.64
$
0.88
$
0.77
$
1.00
$
1.32
$
1.18
$
1.46
$

10,001­
50K
0.51
$
0.45
$
0.58
$
0.80
$
0.70
$
0.89
$
1.42
$
1.28
$
1.55
$

50,001­
100K
0.13
$
0.12
$
0.15
$
0.21
$
0.18
$
0.24
$
0.37
$
0.34
$
0.41
$

100,001­
1M
0.21
$
0.18
$
0.23
$
0.33
$
0.29
$
0.37
$
0.58
$
0.53
$
0.64
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
4.64
$
3.95
$
5.33
$
7.06
$
6.06
$
8.06
$
12.16
$
10.89
$
13.40
$

264.68
$
231.23
$
297.96
$
419.94
$
366.14
$
473.76
$
727.11
$
654.91
$
800.10
$

<
100
8.98
$
7.79
$
10.18
$
11.06
$
9.66
$
12.47
$
12.09
$
10.57
$
13.61
$

101­
500
22.85
$
19.63
$
26.07
$
23.91
$
20.58
$
27.24
$
24.43
$
21.01
$
27.79
$

501­
1,000
12.67
$
10.88
$
14.46
$
13.19
$
11.35
$
15.04
$
13.44
$
11.58
$
15.30
$

1,001­
3,300
20.95
$
17.48
$
24.40
$
21.23
$
17.74
$
24.69
$
21.38
$
17.90
$
24.81
$

3,301­
10K
31.47
$
25.85
$
37.05
$
31.83
$
26.16
$
37.44
$
32.02
$
26.41
$
37.56
$

10,001­
50K
55.86
$
50.42
$
61.34
$
89.54
$
81.02
$
98.14
$
100.67
$
91.08
$
110.33
$

50,001­
100K
14.96
$
13.38
$
16.55
$
23.78
$
21.37
$
26.20
$
26.69
$
23.96
$
29.45
$

100,001­
1M
26.96
$
24.00
$
29.97
$
41.39
$
37.00
$
45.80
$
46.13
$
41.17
$
51.12
$

>
1
Million
2.28
$
2.01
$
2.56
$
3.50
$
3.09
$
3.91
$
3.90
$
3.44
$
4.36
$

All
Sizes
196.99
$
171.45
$
222.58
$
259.44
$
227.96
$
290.93
$
280.76
$
247.12
$
314.33
$

<
100
4.18
$
3.65
$
4.71
$
5.14
$
4.52
$
5.78
$
5.63
$
4.94
$
6.31
$

101­
500
4.16
$
3.59
$
4.74
$
4.34
$
3.76
$
4.94
$
4.44
$
3.84
$
5.03
$

501­
1,000
1.90
$
1.64
$
2.16
$
1.98
$
1.71
$
2.24
$
2.02
$
1.75
$
2.28
$

1,001­
3,300
0.88
$
0.74
$
1.03
$
0.89
$
0.75
$
1.04
$
0.90
$
0.75
$
1.05
$

3,301­
10K
0.28
$
0.23
$
0.33
$
0.28
$
0.23
$
0.33
$
0.28
$
0.23
$
0.33
$

10,001­
50K
0.12
$
0.11
$
0.13
$
0.19
$
0.17
$
0.21
$
0.21
$
0.19
$
0.24
$

50,001­
100K
0.02
$
0.02
$
0.03
$
0.04
$
0.03
$
0.04
$
0.04
$
0.04
$
0.04
$

100,001­
1M
0.12
$
0.11
$
0.13
$
0.18
$
0.16
$
0.20
$
0.21
$
0.18
$
0.23
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
11.66
$
10.08
$
13.27
$
13.05
$
11.33
$
14.79
$
13.73
$
11.91
$
15.52
$

208.66
$
181.52
$
235.85
$
272.49
$
239.29
$
305.71
$
294.48
$
259.03
$
329.85
$

473.34
$
412.76
$
533.81
$
692.43
$
605.43
$
779.47
$
1,021.59
$
913.95
$
1,129.95
$

Notes:

Source:
Total
All
values
in
millions
of
year
2000
dollars.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.
Derived
from
Appendix
K,
Exhibit
K.
1a
for
the
Preferred
Alternative,
K.
1e
for
IDSE
Sensitivity
Analysis
1,
and
K.
1f
for
IDSE
Sensitivity
Analysis
2.
Ground
Water
CWSs
NTNCWSs
Subtotal
Mean
Value
Mean
Value
Subtotal
Surface
Water
CWSs
NTNCWSs
Source
Mean
Value
System
Classification
System
Size
(
population
served)
Exhibit
7.3
Comparison
of
the
Total
Initial
Capital
Costs
for
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
6
July
2003
Preferred
Alternative
IDSE
Sensitivity
1
IDSE
Sensitivity
2
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$

2004
34.5
$
34.5
$
34.5
$
34.5
$
34.5
$
34.5
$
34.5
$
34.5
$
34.5
$

2005
74.3
$
65.7
$
82.9
$
108.4
$
95.8
$
121.1
$
160.3
$
144.5
$
176.3
$

2006
87.3
$
78.6
$
95.9
$
121.8
$
109.2
$
134.5
$
174.6
$
158.8
$
190.6
$

2007
76.9
$
68.2
$
85.6
$
111.8
$
99.1
$
124.5
$
165.4
$
149.6
$
181.4
$

2008
81.6
$
72.9
$
90.4
$
116.9
$
104.2
$
129.6
$
171.2
$
155.4
$
187.2
$

2009
81.2
$
72.5
$
90.0
$
116.7
$
104.0
$
129.4
$
171.7
$
155.9
$
187.7
$

2010
84.5
$
75.7
$
93.3
$
120.2
$
107.5
$
132.9
$
175.7
$
159.9
$
191.7
$

2011
43.4
$
39.6
$
47.2
$
53.8
$
49.2
$
58.5
$
70.9
$
65.6
$
76.2
$

2012
43.4
$
39.6
$
47.2
$
53.9
$
49.2
$
58.5
$
70.9
$
65.7
$
76.1
$

2013
43.4
$
39.6
$
47.2
$
53.9
$
49.2
$
58.5
$
70.8
$
65.6
$
76.1
$

2014
29.4
$
27.7
$
31.2
$
36.9
$
34.7
$
39.2
$
49.8
$
47.2
$
52.5
$

2015
28.5
$
26.8
$
30.3
$
35.9
$
33.7
$
38.1
$
48.4
$
45.8
$
51.0
$

2016
27.7
$
26.1
$
29.4
$
34.8
$
32.7
$
36.9
$
47.0
$
44.5
$
49.5
$

2017
26.9
$
25.3
$
28.5
$
33.8
$
31.7
$
35.9
$
45.6
$
43.2
$
48.0
$

2018
26.1
$
24.6
$
27.7
$
32.8
$
30.8
$
34.8
$
44.3
$
41.9
$
46.6
$

2019
25.4
$
23.9
$
26.9
$
31.9
$
29.9
$
33.8
$
43.0
$
40.7
$
45.3
$

2020
24.6
$
23.2
$
26.1
$
30.9
$
29.1
$
32.8
$
41.7
$
39.5
$
44.0
$

2021
23.9
$
22.5
$
25.3
$
30.0
$
28.2
$
31.9
$
40.5
$
38.4
$
42.7
$

2022
23.2
$
21.8
$
24.6
$
29.2
$
27.4
$
30.9
$
39.3
$
37.2
$
41.4
$

2023
22.5
$
21.2
$
23.9
$
28.3
$
26.6
$
30.0
$
38.2
$
36.2
$
40.2
$

2024
21.9
$
20.6
$
23.2
$
27.5
$
25.8
$
29.2
$
37.1
$
35.1
$
39.1
$

2025
21.2
$
20.0
$
22.5
$
26.7
$
25.1
$
28.3
$
36.0
$
34.1
$
37.9
$

2026
20.6
$
19.4
$
21.9
$
25.9
$
24.3
$
27.5
$
34.9
$
33.1
$
36.8
$

2027
20.0
$
18.8
$
21.2
$
25.2
$
23.6
$
26.7
$
33.9
$
32.1
$
35.7
$

Total
1,028.7
$
944.8
$
1,112.9
$
1,358.1
$
1,241.8
$
1,474.4
$
1,882.2
$
1,740.7
$
2,024.6
$

Ann.
59.1
$
54.3
$
63.9
$
78.0
$
71.3
$
84.7
$
108.1
$
100.0
$
116.3
$

Notes:
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.

Ann
=
value
of
total
annualized
at
discount
rate.

Source:
Derived
from
Appendix
K,
Exhibit
K.
2as
for
the
Preferred
Alternative,
K.
6i
for
IDSE
Sensitivity
Analysis
1,
and
K.
7i
for
IDSE
Sensitivity
Analysis
2.
Mean
Value
Mean
Value
Mean
Value
Exhibit
7.4a
Comparison
of
Annualized
Costs
for
the
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative,
3
Percent
Discount
Rate
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
7
July
2003
Preferred
Alternative
IDSE
Sensitivity
1
IDSE
Sensitivity
2
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$
36.2
$

2004
33.2
$
33.2
$
33.2
$
33.2
$
33.2
$
33.2
$
33.2
$
33.2
$
33.2
$

2005
68.8
$
60.9
$
76.8
$
100.5
$
88.8
$
112.2
$
148.5
$
133.9
$
163.3
$

2006
77.8
$
70.1
$
85.6
$
108.7
$
97.4
$
120.0
$
155.8
$
141.6
$
170.0
$

2007
66.0
$
58.6
$
73.5
$
96.0
$
85.1
$
106.9
$
142.1
$
128.4
$
155.8
$

2008
67.5
$
60.3
$
74.7
$
96.6
$
86.1
$
107.1
$
141.5
$
128.4
$
154.7
$

2009
64.6
$
57.7
$
71.6
$
92.9
$
82.8
$
103.0
$
136.6
$
124.0
$
149.3
$

2010
64.7
$
58.0
$
71.4
$
92.1
$
82.3
$
101.8
$
134.6
$
122.5
$
146.8
$

2011
32.0
$
29.2
$
34.8
$
39.7
$
36.3
$
43.1
$
52.3
$
48.4
$
56.1
$

2012
30.8
$
28.1
$
33.5
$
38.2
$
34.9
$
41.5
$
50.3
$
46.6
$
54.0
$

2013
29.6
$
27.1
$
32.2
$
36.8
$
33.6
$
39.9
$
48.4
$
44.8
$
52.0
$

2014
19.3
$
18.2
$
20.5
$
24.3
$
22.8
$
25.8
$
32.8
$
31.0
$
34.5
$

2015
18.1
$
17.0
$
19.2
$
22.7
$
21.3
$
24.1
$
30.6
$
29.0
$
32.3
$

2016
16.9
$
15.9
$
17.9
$
21.2
$
19.9
$
22.5
$
28.6
$
27.1
$
30.1
$

2017
15.8
$
14.8
$
16.7
$
19.8
$
18.6
$
21.0
$
26.7
$
25.3
$
28.2
$

2018
14.7
$
13.9
$
15.6
$
18.5
$
17.4
$
19.7
$
25.0
$
23.7
$
26.3
$

2019
13.8
$
13.0
$
14.6
$
17.3
$
16.3
$
18.4
$
23.4
$
22.1
$
24.6
$

2020
12.9
$
12.1
$
13.7
$
16.2
$
15.2
$
17.2
$
21.8
$
20.7
$
23.0
$

2021
12.0
$
11.3
$
12.8
$
15.1
$
14.2
$
16.1
$
20.4
$
19.3
$
21.5
$

2022
11.3
$
10.6
$
11.9
$
14.1
$
13.3
$
15.0
$
19.1
$
18.1
$
20.1
$

2023
10.5
$
9.9
$
11.1
$
13.2
$
12.4
$
14.0
$
17.8
$
16.9
$
18.8
$

2024
9.8
$
9.2
$
10.4
$
12.4
$
11.6
$
13.1
$
16.7
$
15.8
$
17.5
$

2025
9.2
$
8.6
$
9.7
$
11.5
$
10.8
$
12.2
$
15.6
$
14.7
$
16.4
$

2026
8.6
$
8.1
$
9.1
$
10.8
$
10.1
$
11.4
$
14.6
$
13.8
$
15.3
$

2027
8.0
$
7.5
$
8.5
$
10.1
$
9.5
$
10.7
$
13.6
$
12.9
$
14.3
$

Total
752.3
$
689.4
$
815.3
$
998.3
$
910.2
$
1,086.3
$
1,386.2
$
1,278.5
$
1,494.5
$

Ann.
64.6
$
59.2
$
70.0
$
85.7
$
78.1
$
93.2
$
118.9
$
109.7
$
128.2
$

Notes:
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.

Ann
=
value
of
total
annualized
at
discount
rate.

Source:
Derived
from
Appendix
J,
Exhibit
K.
2aw
for
the
Preferred
Alternative,
K.
6m
for
IDSE
Sensitivity
Analysis
1,
and
K.
7m
for
IDSE
Sensitivity
Analysis
2.
Mean
Value
Mean
Value
Mean
Value
Exhibit
7.4b
Comparison
of
Annualized
Costs
for
the
IDSE
Sensitivity
Analyses
and
the
Preferred
Alternative,
7
Percent
Discount
Rate
($
Millions)
1
Since
the
Minimal
Impact
Sensitivity
Analysis
only
considers
the
costs
and
benefits
from
large
surface
water
systems,
Appendices
E,
F,
and
J
do
not
contain
separate
sections
for
this
sensitivity
analysis.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
8
July
2003
7.3
Minimal
Impact
Sensitivity
Analysis
For
this
analysis,
EPA
assumed
that
no
surface
water
plants
serving
fewer
than
10,000
people
and
no
ground
water
plants
would
have
to
add
treatment
to
meet
Stage
2
DBPR
requirements.
The
only
costs
and
benefits
are
associated
with
the
large
surface
water
systems.
1
Exhibit
7.5
compares
the
estimated
annual
benefits
for
the
Minimal
Impact
Sensitivity
Analysis
to
those
of
the
Preferred
Regulatory
Alternative.
Exhibit
7.6
compares
the
estimated
initial
capital
costs
for
the
Minimal
Impact
Sensitivity
Analysis
to
the
Preferred
Regulatory
Alternative.
Exhibits
7.7a
and
7.7b
compare
the
total
annualized
costs
of
the
rule
(
including
treatment
and
non­
treatment
costs)
for
the
Minimal
Impact
Sensitivity
Analysis
to
those
of
the
Preferred
Regulatory
Alternative
at
3
and
7
percent
discount
rates,
respectively.

Note
that
while
the
cost
figures
are
reduced
dramatically
for
this
sensitivity
analysis
(
from
$
59.1
million
to
$
21.4
million
using
a
3
percent
discount
rate
for
the
Preferred
Regulatory
Alternative
to
the
Minimal
Impacts
Sensitivity
Analysis,
respectively),
the
benefits
are
not
dramatically
reduced
(
from
$
113
million
to
$
98
million
using
a
3
percent
discount
rate
at
the
2
percent
PAR
value
for
the
Preferred
Regulatory
Alternative
to
the
Minimal
Impacts
Sensitivity
Analysis,
respectively).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
9
July
2003
Exhibit
7.5
Comparison
of
Estimated
Annual
Cases
and
Annualized
Benefits
for
Minimal
Impact
Sensitivity
Analysis
and
the
Preferred
Alternative
(
Millions,
2000$)
1
Discount
Rate,
WTP
for
Non­
Fatal
Cases
Preferred
Alternative
Minimal
Impact
Sensitivity
Analysis
2%
PAR
Average
Number
of
Annual
Cancer
Cases
Avoided
21
158
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
113
($
18
­
258)
$
98
($
17
­
$
239)

7
%
Lymphoma
$
98
($
16
­
224)
$
85
($
14
­
$
208)

3
%
Bronchitis
$
55
($
13
­
120)
$
48
($
12
­
$
111)

7
%
Bronchitis
$
48
($
11
­
104)
$
41
($
10
­
$
96)

17%
PAR
Value
Average
Number
of
Annual
Cancer
Cases
Avoided
182
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3
%,
Lymphoma
$
986
($
157
­
2,253)
$
854
($
145
­
$
2087)

7
%
Lymphoma
$
854
($
136
­
1,952)
$
742
($
126
­
$
1812)

3
%
Bronchitis
$
479
($
109
­
1,044)
$
415
($
101
­
$
967)

7
%
Bronchitis
$
415
($
95
­
905)
$
361
($
88
­
$
840)

Notes:
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
For
preferred
alternative,
see
Exhibit
5.29.
For
the
sensitivity
analysis,
see
the
preferred
alternative
results
for
large
SW
systems
(
USEPA
2003i).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
10
July
2003
Preferred
Alternative
Minimal
Impacts
Sensitivity
Analysis
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

<
100
0.76
$
0.61
$
0.90
$
­
$
­
$
­
$

101­
500
3.43
$
2.90
$
3.96
$
­
$
­
$
­
$

501­
1,000
3.14
$
2.66
$
3.62
$
­
$
­
$
­
$

1,001­
3,300
11.42
$
9.83
$
13.03
$
­
$
­
$
­
$

3,301­
10K
27.52
$
23.86
$
31.21
$
­
$
­
$
­
$

10,001­
50K
57.05
$
50.18
$
63.84
$
57.05
$
50.18
$
63.84
$

50,001­
100K
31.63
$
27.80
$
35.43
$
31.63
$
27.80
$
35.43
$

100,001­
1M
82.26
$
72.18
$
92.25
$
82.26
$
72.18
$
92.25
$

>
1
Million
42.85
$
37.27
$
48.40
$
42.85
$
37.27
$
48.40
$

All
Sizes
260.04
$
227.28
$
292.63
$
213.78
$
187.44
$
239.92
$

<
100
0.47
$
0.38
$
0.56
$
­
$
­
$
­
$

101­
500
1.31
$
1.11
$
1.51
$
­
$
­
$
­
$

501­
1,000
0.72
$
0.61
$
0.83
$
­
$
­
$
­
$

1,001­
3,300
0.72
$
0.62
$
0.83
$
­
$
­
$
­
$

3,301­
10K
0.57
$
0.49
$
0.64
$
­
$
­
$
­
$

10,001­
50K
0.51
$
0.45
$
0.58
$
0.51
$
0.45
$
0.58
$

50,001­
100K
0.13
$
0.12
$
0.15
$
0.13
$
0.12
$
0.15
$

100,001­
1M
0.21
$
0.18
$
0.23
$
0.21
$
0.18
$
0.23
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
4.64
$
3.95
$
5.33
$
0.85
$
0.75
$
0.96
$

264.68
$
231.23
$
297.96
$
214.64
$
188.18
$
240.88
$

<
100
8.98
$
7.79
$
10.18
$
­
$
­
$
­
$

101­
500
22.85
$
19.63
$
26.07
$
­
$
­
$
­
$

501­
1,000
12.67
$
10.88
$
14.46
$
­
$
­
$
­
$

1,001­
3,300
20.95
$
17.48
$
24.40
$
­
$
­
$
­
$

3,301­
10K
31.47
$
25.85
$
37.05
$
­
$
­
$
­
$

10,001­
50K
55.86
$
50.42
$
61.34
$
­
$
­
$
­
$

50,001­
100K
14.96
$
13.38
$
16.55
$
­
$
­
$
­
$

100,001­
1M
26.96
$
24.00
$
29.97
$
­
$
­
$
­
$

>
1
Million
2.28
$
2.01
$
2.56
$
­
$
­
$
­
$

All
Sizes
196.99
$
171.45
$
222.58
$
­
$
­
$
­
$

<
100
4.18
$
3.65
$
4.71
$
­
$
­
$
­
$

101­
500
4.16
$
3.59
$
4.74
$
­
$
­
$
­
$

501­
1,000
1.90
$
1.64
$
2.16
$
­
$
­
$
­
$

1,001­
3,300
0.88
$
0.74
$
1.03
$
­
$
­
$
­
$

3,301­
10K
0.28
$
0.23
$
0.33
$
­
$
­
$
­
$

10,001­
50K
0.12
$
0.11
$
0.13
$
­
$
­
$
­
$

50,001­
100K
0.02
$
0.02
$
0.03
$
­
$
­
$
­
$

100,001­
1M
0.12
$
0.11
$
0.13
$
­
$
­
$
­
$

>
1
Million
­
$
­
$
­
$
­
$
­
$
­
$

All
Sizes
11.66
$
10.08
$
13.27
$
­
$
­
$
­
$

208.66
$
181.52
$
235.85
$
­
$
­
$
­
$

473.34
$
412.76
$
533.81
$
214.64
$
188.18
$
240.88
$

Notes:

Source:
Mean
Value
Subtotal
Surface
Water
CWSs
NTNCWSs
Source
Mean
Value
System
Classification
System
Size
(
population
served)

Ground
Water
CWSs
NTNCWSs
Subtotal
Total
All
values
in
millions
of
year
2000
dollars.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.
Derived
from
Appendix
K,
Exhibit
K.
1a
for
the
Preferred
Alternative.
The
Minimal
Impact
Sensitivity
Analysis
is
the
Preferred
Alternative
with
no
costs
for
small
surface
water
systems
and
all
ground
water
systems.
Exhibit
7.6
Comparison
of
Initial
Capital
Costs
for
the
Minimal
Impact
Sensitivity
Analysis
and
the
Preferred
Alternative
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
11
July
2003
Preferred
Alternative
Minimal
Impact
Sensitivity
Analysis
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
36.2
$
36.2
$
36.2
$
23.9
$
23.9
$
23.9
$

2004
34.5
$
34.5
$
34.5
$
23.0
$
23.0
$
23.0
$

2005
74.3
$
65.7
$
82.9
$
35.6
$
31.3
$
39.8
$

2006
87.3
$
78.6
$
95.9
$
36.7
$
32.5
$
40.9
$

2007
76.9
$
68.2
$
85.6
$
37.4
$
33.1
$
41.6
$

2008
81.6
$
72.9
$
90.4
$
38.1
$
33.9
$
42.3
$

2009
81.2
$
72.5
$
90.0
$
37.5
$
33.3
$
41.7
$

2010
84.5
$
75.7
$
93.3
$
36.9
$
32.7
$
41.0
$

2011
43.4
$
39.6
$
47.2
$
7.7
$
7.1
$
8.3
$

2012
43.4
$
39.6
$
47.2
$
7.4
$
6.9
$
8.0
$

2013
43.4
$
39.6
$
47.2
$
7.2
$
6.7
$
7.8
$

2014
29.4
$
27.7
$
31.2
$
7.0
$
6.5
$
7.6
$

2015
28.5
$
26.8
$
30.3
$
6.8
$
6.3
$
7.3
$

2016
27.7
$
26.1
$
29.4
$
6.6
$
6.1
$
7.1
$

2017
26.9
$
25.3
$
28.5
$
6.4
$
5.9
$
6.9
$

2018
26.1
$
24.6
$
27.7
$
6.2
$
5.8
$
6.7
$

2019
25.4
$
23.9
$
26.9
$
6.0
$
5.6
$
6.5
$

2020
24.6
$
23.2
$
26.1
$
5.9
$
5.4
$
6.3
$

2021
23.9
$
22.5
$
25.3
$
5.7
$
5.3
$
6.1
$

2022
23.2
$
21.8
$
24.6
$
5.5
$
5.1
$
6.0
$

2023
22.5
$
21.2
$
23.9
$
5.4
$
5.0
$
5.8
$

2024
21.9
$
20.6
$
23.2
$
5.2
$
4.8
$
5.6
$

2025
21.2
$
20.0
$
22.5
$
5.1
$
4.7
$
5.5
$

2026
20.6
$
19.4
$
21.9
$
4.9
$
4.5
$
5.3
$

2027
20.0
$
18.8
$
21.2
$
4.8
$
4.4
$
5.1
$

Total
1,028.7
$
944.8
$
1,112.9
$
372.9
$
339.8
$
406.2
$

Ann.
59.1
$
54.3
$
63.9
$
21.4
$
19.5
$
23.3
$

Notes:

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.

Ann
=
value
of
total
annualized
at
discount
rate.
Source:
Mean
Value
Mean
Value
Derived
from
Derived
from
Appendix
K,
Exhibit
K.
2as
for
the
Preferred
Alternative.
The
Minimal
Impact
Sensitivity
Analysis
is
the
Preferred
Alternative
with
no
costs
for
small
surface
water
systems
and
all
ground
water
systems.
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Exhibit
7.7a
Comparison
of
Annualized
Costs
for
the
Minimal
Impact
Sensitivity
Analyses
and
the
Preferred
Alternative,
3
Percent
Discount
Rate
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
7­
12
July
2003
Preferred
Alternative
Minimal
Impact
Sensitivity
Analysis
90
Percent
Confidence
Bound
90
Percent
Confidence
Bound
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

2003
36.2
$
36.2
$
36.2
$
23.9
$
23.9
$
23.9
$

2004
33.2
$
33.2
$
33.2
$
22.2
$
22.2
$
22.2
$

2005
68.8
$
60.9
$
76.8
$
33.0
$
29.0
$
36.9
$

2006
77.8
$
70.1
$
85.6
$
32.7
$
29.0
$
36.5
$

2007
66.0
$
58.6
$
73.5
$
32.1
$
28.4
$
35.7
$

2008
67.5
$
60.3
$
74.7
$
31.5
$
28.0
$
35.0
$

2009
64.6
$
57.7
$
71.6
$
29.8
$
26.5
$
33.1
$

2010
64.7
$
58.0
$
71.4
$
28.2
$
25.0
$
31.4
$

2011
32.0
$
29.2
$
34.8
$
5.6
$
5.2
$
6.1
$

2012
30.8
$
28.1
$
33.5
$
5.3
$
4.9
$
5.7
$

2013
29.6
$
27.1
$
32.2
$
4.9
$
4.6
$
5.3
$

2014
19.3
$
18.2
$
20.5
$
4.6
$
4.3
$
5.0
$

2015
18.1
$
17.0
$
19.2
$
4.3
$
4.0
$
4.6
$

2016
16.9
$
15.9
$
17.9
$
4.0
$
3.7
$
4.3
$

2017
15.8
$
14.8
$
16.7
$
3.8
$
3.5
$
4.1
$

2018
14.7
$
13.9
$
15.6
$
3.5
$
3.3
$
3.8
$

2019
13.8
$
13.0
$
14.6
$
3.3
$
3.0
$
3.5
$

2020
12.9
$
12.1
$
13.7
$
3.1
$
2.8
$
3.3
$

2021
12.0
$
11.3
$
12.8
$
2.9
$
2.7
$
3.1
$

2022
11.3
$
10.6
$
11.9
$
2.7
$
2.5
$
2.9
$

2023
10.5
$
9.9
$
11.1
$
2.5
$
2.3
$
2.7
$

2024
9.8
$
9.2
$
10.4
$
2.3
$
2.2
$
2.5
$

2025
9.2
$
8.6
$
9.7
$
2.2
$
2.0
$
2.4
$

2026
8.6
$
8.1
$
9.1
$
2.0
$
1.9
$
2.2
$

2027
8.0
$
7.5
$
8.5
$
1.9
$
1.8
$
2.1
$

Total
752.3
$
689.4
$
815.3
$
292.4
$
266.6
$
318.3
$

Ann.
64.6
$
59.2
$
70.0
$
25.1
$
22.9
$
27.3
$

Notes:

Detail
may
not
add
exactly
to
totals
due
to
independent
rounding.

Ann
=
value
of
total
annualized
at
discount
rate.
Source:
Derived
from
Derived
from
Appendix
K,
Exhibit
K.
2aw
for
the
Preferred
Alternative.
The
Minimal
Impact
Sensitivity
Analysis
is
the
Preferred
Alternative
with
no
costs
for
small
surface
water
systems
and
all
ground
water
systems.
Mean
Value
Mean
Value
Present
values
in
millions
of
2000
dollars.
Estimates
are
discounted
to
2003.
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Exhibit
7.7b
Comparison
of
Annualized
Costs
for
the
Minimal
Impact
Sensitivity
Analyses
and
the
Preferred
Alternative,
7
Percent
Discount
Rate
($
Millions)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
1
8.
Economic
Impact
Analysis
8.1
Introduction
As
part
of
the
rulemaking
process,
the
Environmental
Protection
Agency
(
EPA)
is
required
to
address
the
potential
direct
and
indirect
burdens
that
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR)
may
place
on
certain
types
of
governments,
businesses,
and
populations.
This
chapter
presents
the
analyses
EPA
has
performed
in
accordance
with
the
following
12
Federal
requirements.

1)
The
Regulatory
Flexibility
Act
(
RFA)
of
1980,
as
amended
by
the
Small
Business
Regulatory
Enforcement
Fairness
Act
(
SBREFA)
of
1996.
2)
An
analysis
of
small
system
affordability
to
determine
variance
technologies
in
accordance
with
Section
1415(
e)(
1)
of
the
1996
Safe
Drinking
Water
Act
(
SDWA)
Amendments.
3)
Feasible
technologies
available
to
all
systems
as
required
by
Section
1412(
b)(
4)(
E)
of
the
1996
SDWA
Amendments.
4)
A
Technical,
Financial,
and
Managerial
Capacity
Assessment
as
required
by
Section
1420(
d)(
3)
of
the
1996
SDWA
Amendments.
5)
The
Paperwork
Reduction
Act
(
A
separate
Information
Collection
Request
document
contains
the
complete
analysis).
6)
The
Unfunded
Mandates
Reform
Act
(
UMRA)
of
1995.
7)
Executive
Order
13175
(
Consultation
and
Coordination
with
Indian
Tribal
Governments).
8)
Impacts
on
sensitive
subpopulations
as
required
by
Section
1412(
b)(
3)(
c)(
i)
of
the
1996
SDWA
Amendments.
9)
Executive
Order
13045
(
Protection
of
Children
from
Environmental
Health
Risks
and
Safety
Risks).
10)
Executive
Order
12898
(
Federal
Actions
to
Address
Environmental
Justice
in
Minority
Populations
and
Low­
Income
Populations).
11)
Executive
Order
13132
(
Federalism).
12)
Executive
Order
13211
(
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use).

Many
of
the
requirements
and
executive
orders
listed
above
call
for
an
explanation
of
why
the
rule
is
necessary,
the
statutory
authority
for
the
rule,
and
the
primary
objectives
that
the
rule
is
intended
to
achieve
(
refer
to
Chapter
2
for
more
information
regarding
the
objectives
of
the
rule).
More
specifically,
they
are
designed
to
assess
the
financial
and
health
effects
of
the
rule
on
sensitive,
low­
income,
and
Tribal
populations
as
well
as
on
small
systems.
The
chapter
also
examines
how
much
additional
capacity
systems
will
need
to
meet
Stage
2
DBPR
requirements
and
whether
there
are
existing,
feasible
technologies
and
treatment
techniques
available
to
meet
rule
requirements.

8.2
Regulatory
Flexibility
Act
and
Small
Business
Regulatory
Enforcement
Fairness
Act
The
RFA,
as
amended
by
the
SBREFA
of
1996
(
5
U.
S.
C.
§
601
et
seq.),
generally
requires
an
agency
to
prepare
a
regulatory
flexibility
analysis
for
any
rule
subject
to
notice
and
comment
rulemaking
requirements
under
the
Administrative
Procedure
Act
or
other
statute,
unless
the
Agency
certifies
that
the
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities
(
5
U.
S.
C.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
2
603(
a)).
EPA
must
analyze
the
impacts
of
a
regulation
on
all
entities
and
individually
for
each
type
of
entity,
including
public
water
systems
(
PWSs)
run
by
small
businesses,
small
governments,
and
small
organizations.
Small
entities
include
small
businesses,
small
organizations,
and
small
governmental
jurisdictions.

Defining
Small
Entities
Affected
by
the
Rule
The
RFA
defines
small
entities
as
including
"
small
businesses,"
"
small
governments,"
and
"
small
organizations"
(
5
U.
S.
C.
601).
The
RFA
references
the
definition
of
"
small
business"
found
in
the
Small
Business
Act,
which
authorizes
the
Small
Business
Administration
(
SBA)
to
further
define
"
small
business"
by
regulation.
The
SBA
defines
small
businesses
by
category
using
the
North
American
Industry
Classification
System
(
NAICS).
For
example,
in
the
manufacturing
sector,
the
SBA
generally
defines
small
business
in
terms
of
number
of
employees;
in
the
agriculture,
mining,
and
electric,
gas,
and
sanitary
services
sectors,
the
SBA
generally
defines
small
businesses
in
terms
of
annual
receipts
(
ranging
from
$
0.5
million
for
crops
to
$
25
million
for
certain
types
of
pipelines).
The
RFA
also
authorizes
an
agency
to
adopt
alternative
definitions
for
each
category
of
small
entity
"
which
are
appropriate
to
the
activities
of
the
Agency
after
proposing
the
alternative
definition(
s)
in
the
Federal
Register
and
taking
comment"
(
5
U.
S.
C.
§
601(
3)­(
5)).
In
addition
to
the
above,
agencies
must
consult
with
SBA's
Chief
Council
for
Advocacy
to
establish
an
alternative
small
business
definition.

The
screening
analysis
uses
the
following
definitions
of
small
entities
affected
by
the
Stage
2
DBPR:

°
A
"
small
business"
is
any
small
business
concern
that
is
independently
owned
and
operated
and
not
dominant
in
its
field
as
defined
by
the
Small
Business
Act
(
15
U.
S.
C.
632).
Examples
of
PWSs
within
this
category
include
small,
privately
owned
PWSs
and
for­
profit
businesses
where
provision
of
water
may
be
ancillary,
such
as
mobile
home
parks
or
day­
care
centers.

°
A
"
small
organization"
under
the
Stage
2
DBPR
is
any
not­
for­
profit
enterprise
that
is
independently
owned
and
operated,
not
dominant
in
its
field,
and
operates
a
PWS.
Examples
of
small
organizations
include
churches,
schools,
and
homeowners
associations.

°
A
"
small
governmental
jurisdiction"
is
a
city,
county,
town,
school
district,
or
special
district
with
a
population
of
less
than
50,000
(
5
U.
S.
C.
601)
that
operates
a
PWS.

The
Stage
2
DBPR
applies
to
all
community
water
systems
(
CWSs)
and
nontransient
noncommunity
water
systems
(
NTNCWSs)
that
add
a
disinfectant
other
than
ultraviolet
light
(
UV)
or
that
deliver
water
that
has
been
treated
with
a
disinfectant
other
than
UV.
The
NAICS
code
for
PWSs
is
22131
(
Administration
of
Water
Supply
and
Irrigation
Programs)
and
State
agencies
that
include
drinking
water
programs
are
classified
as
92411
(
Administration
of
Air
and
Water
Resources
and
Solid
Waste
Management
Programs)
or
923312
(
Administration
of
Public
Health
Programs).
Ancillary
systems
(
i.
e.,
those
that
supplement
the
function
of
other
establishments
like
factories,
power
plants,
mobile
home
parks,
etc.)
cannot
be
categorized
in
a
single
NAICS
code.
For
ancillary
systems,
the
NAICS
code
is
that
of
the
primary
establishment
or
industry.

For
purposes
of
assessing
the
impacts
of
the
Stage
2
DBPR
on
small
entities,
EPA
considered
small
entities
to
be
PWSs
serving
10,000
or
fewer
people,
which
is
the
cut­
off
level
specified
by
Congress
in
the
1996
Amendments
to
the
SDWA
for
small
system
flexibility
provisions.
Because
this
definition
does
not
correspond
to
the
definitions
for
small
businesses,
governments,
and
nonprofit
organizations,
EPA
1
Revenue
information
was
used
whenever
available.
When
it
was
not
available,
different
measures,
such
as
sales
or
annual
operating
expenditures,
were
used.

2
System
information
in
this
chapter
is
from
the
system
baseline
presented
in
Chapter
3
(
Exhibit
3.3).
Discussions
of
plants
changing
technology
refer
to
the
Stage
2
DBPR
treatment
plants
and
baseline
(
Exhibit
3.4).
Systems
conducting
rule
activities
are
presented
in
Exhibit
6.3,
and
plants
adding
treatment
are
presented
in
Exhibit
6.4.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
3
requested
comment
on
an
alternative
definition
of
a
small
entity
in
the
preamble
to
the
proposed
Consumer
Confidence
Report
(
CCR)
regulation
(
63
FR
7620
February
13,
1998).
Comments
showed
that
stakeholders
support
the
proposed
alternative
definition.
EPA
also
consulted
with
the
SBA
Office
of
Advocacy
on
the
definition
as
it
relates
to
small
business
analysis.
In
the
preamble
to
the
final
CCR
regulation
(
63
FR
4511
August
19,
1998),
EPA
stated
its
intent
to
establish
this
alternative
definition
for
regulatory
flexibility
assessments
under
the
RFA
for
all
drinking
water
regulations
and
has,
thus,
used
it
for
the
Stage
2
DBPR.

EPA
conducted
a
screening
analysis
to
determine
if
the
Stage
2
DBPR
would
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.
In
this
analysis,
EPA
evaluated
the
potential
economic
impact
of
the
rule
on
small
entities
by
comparing
annualized
compliance
costs
as
a
percentage
of
annual
revenues1
for
different
small
entity
classifications.
Chapter
3
of
this
Economic
Analysis
(
EA)
provides
data
on
the
small
entities
potentially
subject
to
the
Stage
2
DBPR,
and
Chapter
6
discusses
changes
systems
would
need
to
make,
as
well
as
the
likely
costs.
2
Using
information
from
these
two
chapters,
along
with
additional
information
from
the
Safe
Drinking
Water
Information
System
(
SDWIS),
the
Community
Water
System
Survey
(
CWSS),
and
the
U.
S.
Census,
EPA
conducted
a
quantitative
analysis
of
small
system
impacts
resulting
from
the
rule.

Measuring
Significant
Impacts
To
evaluate
the
impact
that
a
small
entity
is
expected
to
incur
as
a
result
of
the
rule,
this
analysis
calculates
the
entity's
annualized
compliance
costs
as
a
percentage
of
sales
(
for
privately
owned
systems)
or
the
entity's
annualized
compliance
costs
as
a
percentage
of
annual
governmental
revenue
or
expenditures
(
for
publicly
owned
systems).
EPA
guidance
suggests
using
1
percent
as
a
threshold
for
determining
significance,
although
additional
factors
may
be
considered.
If
compliance
costs
are
less
than
1
percent
of
sales
or
revenues,
the
regulation
may
in
most
cases
be
presumed
to
have
no
significant
impact
(
U.
S.
House
of
Representatives
1996).
In
addition,
if
no
more
than
100
systems
experience
economic
impacts
of
3
percent
of
their
revenues
or
greater,
than
in
most
cases
there
is
no
significant
impact.

Exhibits
8.1a
and
8.1b
present
the
data
that
EPA
used
for
the
screening
analysis.
Using
this
data,
EPA
calculated
the
annual
compliance
costs
per
system
as
a
percentage
of
revenues
or
expenditures.
These
percentages
are
presented
in
Column
D.
The
numbers
of
systems
expected
to
incur
costs
of
more
than
1
and
3
percent
of
their
revenues
are
presented
in
Columns
F
and
H,
respectively.
The
numbers
of
systems
experiencing
impacts
of
more
than
1
and
3
percent
of
their
revenues
were
compared
to
the
total
number
of
systems
in
each
size
category
to
calculate
percentages,
shown
in
Columns
E
and
G.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
4
Cost
per
System
Cost
per
System
per
Revenue
Percent
of
Systems
Number
of
Systems
Percent
of
Systems
Number
of
Systems
B
C
D
=
C/
B
E
F=
A*
E
G
H=
A*
G
Small
Governments
2,238
50%
$
2,396,249
$
2,079
0.09%
1.67%
37
1.09%
24
<
100
384
$
2,396,249
$
35
0.00%
1.27%
5
0.00%
­
101­
500
513
$
2,396,249
$
404
0.02%
1.53%
8
1.17%
6
501­
1,000
283
$
2,396,249
$
2,698
0.11%
1.58%
4
1.46%
4
1,001­
3,300
538
$
2,396,249
$
2,316
0.10%
1.79%
10
1.32%
7
3,301­
10,000
519
$
2,396,249
$
2,079
0.09%
5.61%
29
3.71%
19
Small
Businesses
1,835
41%
$
2,391,978
$
2,079
0.09%
1.67%
31
1.09%
20
<
100
315
$
2,391,978
$
35
0.00%
1.27%
4
0.00%
­
101­
500
421
$
2,391,978
$
404
0.02%
1.57%
7
1.17%
5
501­
1,000
232
$
2,391,978
$
2,698
0.11%
1.58%
4
1.46%
3
1,001­
3,300
441
$
2,391,978
$
2,316
0.10%
1.79%
8
1.32%
6
3,301­
10,000
426
$
2,391,978
$
2,079
0.09%
5.61%
24
3.71%
16
Small
Organizations
403
9%
$
4,446,165
$
2,079
0.05%
1.27%
5
0.76%
3
<
100
69
$
4,446,165
$
35
0.00%
0.00%
­
0.00%
­
101­
500
92
$
4,446,165
$
404
0.01%
1.44%
1
0.61%
1
501­
1,000
51
$
4,446,165
$
2,698
0.06%
1.46%
1
0.75%
0
1,001­
3,300
97
$
4,446,165
$
2,316
0.05%
1.32%
1
0.93%
1
3,301­
10,000
94
$
4,446,165
$
2,079
0.05%
5.02%
5
3.71%
3
All
Small
Entities
4,476
100%
$
2,578,991
$
2,079
0.08%
1.67%
75
1.09%
49
<
100
768
$
2,578,991
$
35
0.00%
1.27%
10
0.00%
­
101­
500
1,027
$
2,578,991
$
404
0.02%
1.44%
15
1.17%
12
501­
1,000
567
$
2,578,991
$
2,698
0.10%
1.58%
9
1.46%
8
1,001­
3,300
1,075
$
2,578,991
$
2,316
0.09%
1.55%
17
1.32%
14
3,301­
10,000
1,039
$
2,578,991
$
2,079
0.08%
5.61%
58
3.71%
39
Entity
by
System
Size
Number
of
Small
Systems
(
Percent)
Average
Annual
Estimated
Revenues1
per
System
($)
A
Systems
Experiencing
Costs
of
>
3%
of
their
Revenues
Systems
Experiencing
Costs
of
>
1%
of
their
Revenues
Annualized
80th
Percentile
Compliance
Cost
($)
Exhibit
8.1a
Annualized
Compliance
Cost
as
a
Percentage
of
Revenues
for
All
Small
Entities
Using
Surface
Water
and
GWUDI
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
5
Cost
per
System
Cost
per
System
per
Revenue
Percent
of
Systems
Number
of
Systems
Percent
of
Systems
Number
of
Systems
B
C
D
=
C/
B
E
F=
A*
E
G
H=
A*
G
Small
Governments
19,133
50%
$
2,396,249
$
12
0.00%
0.28%
54
0.10%
19
<
100
5,641
$
2,396,249
$
11
0.00%
0.00%
­
0.00%
­
101­
500
7,269
$
2,396,249
$
11
0.00%
0.13%
9
0.00%
­
501­
1,000
2,403
$
2,396,249
$
390
0.02%
0.75%
18
0.07%
2
1,001­
3,300
2,599
$
2,396,249
$
385
0.02%
1.26%
33
0.04%
1
3,301­
10,000
1,221
$
2,396,249
$
388
0.02%
1.32%
16
1.32%
16
Small
Businesses
15,689
41%
$
2,391,978
$
12
0.00%
0.28%
44
0.10%
16
<
100
4,625
$
2,391,978
$
11
0.00%
0.00%
­
0.00%
­
101­
500
5,960
$
2,391,978
$
11
0.00%
0.13%
8
0.00%
­
501­
1,000
1,970
$
2,391,978
$
390
0.02%
0.75%
15
0.07%
1
1,001­
3,300
2,131
$
2,391,978
$
385
0.02%
1.26%
27
0.04%
1
3,301­
10,000
1,001
$
2,391,978
$
388
0.02%
1.32%
13
1.32%
13
Small
Organizations
3,444
9%
$
4,446,165
$
12
0.00%
0.10%
4
0.01%
0
<
100
1,015
$
4,446,165
$
11
0.00%
0.00%
­
0.00%
­
101­
500
1,308
$
4,446,165
$
11
0.00%
0.00%
­
0.00%
­
501­
1,000
433
$
4,446,165
$
390
0.01%
0.14%
1
0.00%
­
1,001­
3,300
468
$
4,446,165
$
385
0.01%
0.04%
0
0.02%
0
3,301­
10,000
220
$
4,446,165
$
388
0.01%
1.32%
3
0.04%
0
All
Small
Entities
38,265
100%
$
2,578,991
$
12
0.00%
0.28%
109
0.10%
38
<
100
11,282
$
2,578,991
$
11
0.00%
0.00%
­
0.00%
­
101­
500
14,537
$
2,578,991
$
11
0.00%
0.13%
19
0.00%
­
501­
1,000
4,806
$
2,578,991
$
390
0.02%
0.14%
7
0.07%
3
1,001­
3,300
5,198
$
2,578,991
$
385
0.01%
1.26%
66
0.04%
2
3,301­
10,000
2,443
$
2,578,991
$
388
0.02%
1.32%
32
1.32%
32
A
Entity
by
System
Size
Number
of
Small
Systems
(
Percent)
Average
Annual
Estimated
Revenues1
per
System
($)
Annualized
80th
Percentile
Compliance
Cost
($)
Systems
Experiencing
Costs
of
>
1%
of
their
Revenues
Systems
Experiencing
Costs
of
>
3%
of
their
Revenues
Exhibit
8.1b
Annualized
Compliance
Cost
as
a
Percentage
of
Revenues
for
All
Small
Entities
Using
Ground
Water
Only
Note:
Detail
may
not
add
due
to
independent
rounding.
1
Revenue
information
was
used
whenever
available.
When
it
was
not
available,
different
measures,
such
as
sales
or
annual
operating
expenditures,
were
used.
Data
were
not
available
to
differentiate
revenue
by
system
size.

Sources:
(
A)
Number
of
disinfecting
community
water
systems
(
CWSs)
and
nontransient
noncommunity
water
systems
(
NTNCWSs)
serving
fewer
than
10,000
people
from
the
system
baseline
in
Exhibit
3.4,
multiplied
by
50%,
41%,
and
9%
to
obtain
number
of
small
government,
small
businesses,
and
small
organizations,
respectively.
(
B)
Small
Governments:
Revenues
from
1992
Census
of
Governments,
GC92(
4)­
4:
Finances
of
Municipal
and
Township
Governments,
U.
S.
Dept.
of
Commerce,
Bureau
of
the
Census;
price
deflators
from
Table
7.11,
Chain­
Type
Quantity
and
Price
Indexes
for
Government.
All
other
price
adjustments
based
on
Consumer
Price
Index.
(
C)
Compliance
costs
were
derived
from
the
Stage
2
DBPR
Cost
Model
(
USEPA
2003j).
Costs
represent
present
values
annualized
over
25
years
at
a
3
percent
discount
rate.
(
E,
G)
Derived
from
the
Stage
2
DBPR
Cost
Model
(
USEPA
2003j).

The
ratio
of
compliance
cost
to
revenue
was
calculated
using
the
80th
percentile
of
annualized
(
at
3
percent)
compliance
costs
and
the
average
annual
revenue.
The
average
revenue
for
all
was
used
for
all
systems
and
size
categories
because
no
information
on
the
distribution
of
annual
revenues
was
available.
The
resulting
overall
cost­
to­
revenue
ratio
for
all
small
entity
PWSs
using
surface
water
or
GWUDI
was
0.08
percent,
and
the
ratio
for
small
entity
PWSs
using
ground
water
was
0
percent.
The
use
of
the
80th
percentile
compliance
cost
to
determine
the
ratio
implies
that
80
percent
of
systems
affected
by
the
Stage
2
DBPR
have
lower
compliance
costs,
and
therefore,
80
percent
of
systems
using
surface
water
or
GWUDI
have
ratios
of
even
less
than
0.08
percent.
Thus,
the
threshold
of
20
percent
of
systems
having
costs
as
percentages
of
revenues
of
1
percent
or
more
is
not
exceeded.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
6
Further,
EPA
determined
that
a
total
of
75
small
entity
PWSs
using
surface
water
or
GWUDI
and
109
small
entity
PWSs
using
ground
water,
representing
1.67
and
0.28
percent
of
all
small
entity
PWSs
affected
by
the
Stage
2
DBPR,
respectively,
will
experience
an
impact
of
1
percent
or
greater
of
average
annual
revenues.
This
is
less
than
the
criteria
of
1,000
systems
or
20
percent
of
systems
used
to
determine
significant
impact.
Within
each
class
of
small
entity,
the
number
of
PWSs
using
surface
water
or
GWUDI
experiencing
an
impact
of
1
percent
or
greater
of
average
annual
revenues
ranges
from
5
(
small
organization
PWSs)
to
37
(
small
government
PWSs),
which
is
1.27
to
1.67
percent
of
the
systems
in
each
category.
The
number
of
PWSs
using
ground
water
experiencing
an
impact
of
1
percent
or
greater
of
average
annual
revenues
ranges
from
4
(
small
organization
PWSs)
to
54
(
small
government
PWSs),
which
is
0.10
to
0.28
percent
of
the
systems
in
each
category.

Further,
the
Agency
has
determined
that
49
small
entity
PWSs
using
surface
water
or
GWUDI
and
38
small
entity
PWSs
using
ground
water,
representing
1.09
and
0.10
percent
of
all
small
entity
PWSs
subject
to
the
Stage
2
DBPR,
respectively,
will
experience
an
impact
of
3
percent
or
greater
of
average
annual
revenues.
This
is
less
than
the
criterion
of
100
systems
used
to
determine
significant
impact
at
this
cost
level.
Considering
each
class
of
small
entity,
the
number
of
PWSs
using
surface
water
or
GWUDI
experiencing
an
impact
of
3
percent
or
greater
of
average
annual
revenues
ranges
from
3
(
small
organization
PWS)
to
24
(
small
government
PWSs),
which
is
0.76
to
1.09
percent
of
the
systems
in
each
category,
respectively.
The
number
of
PWSs
using
ground
water
experiencing
an
impact
of
3
percent
or
greater
of
average
annual
revenues
ranges
from
0
(
small
organization
PWSs)
to
19
(
small
government
PWSs),
which
is
0.01
to
0.10
percent
of
the
systems
in
each
category.

Based
on
the
information
presented
in
Exhibits
8.1a
and
8.1b,
EPA
certifies
that
the
Stage
2
DBPR
will
not
lead
to
significant
economic
impacts
for
a
substantial
number
of
small
entities
and,
therefore,
is
not
required
by
the
RFA,
as
amended
by
SBREFA,
to
conduct
an
IRFA
or
a
FRFA.

Obtaining
Data
on
the
Number
of
Small
PWSs
and
Their
Revenues
or
Expenditures
EPA
obtained
data
on
the
number
of
PWSs
in
each
small
entity
category,
which
are
presented
in
Column
A
of
Exhibits
8.1a
and
8.1b.
The
numbers
of
PWSs
and
their
distribution
among
categories
are
derived
from
EPA's
Baseline
Handbook
(
USEPA
2001h).

EPA
also
estimated
the
annual
revenues
or
expenditures
of
small
PWSs,
presented
in
Column
B
of
Exhibits
8.1a
and
8.1b.
PWS
inventories,
managed
by
EPA
and
other
organizations,
have
traditionally
been
categorized
by
size
and
by
the
characteristics
of
the
population
served
(
i.
e.,
CWSs,
NTNCWSs,
and
TNCWSs)
rather
than
by
NAICS
code.
Revenues
by
NAICS
code
are
not
readily
applicable
to
EPA's
categorization
of
systems.
Therefore,
alternative
methods
for
determining
revenue
were
developed,
as
discussed
below.

The
estimated
revenues
for
small
entities
in
Exhibits
8.1a
and
8.1b
are
from
the
Bureau
of
the
Census
(
U.
S.
Department
of
Commerce
1992),
the
Safe
Drinking
Water
Information
System
(
SDWIS),
and
additional
data
on
independent
privately
owned
CWSs,
special
districts,
and
authorities
from
the
1995
Community
Water
System
Survey
(
USEPA
1997c).
Column
A
of
Exhibits
8.1a
and
8.1b
shows
the
numbers
of
systems
classified
as
small
businesses,
governments,
and
organizations,
obtained
using
information
from
the
Third
Edition
of
the
Baseline
Handbook
(
USEPA
2001h).
These
numbers
were
used
to
determine
the
weighted
averages
of
estimated
revenue.
Column
B
shows
the
estimated
revenues.
3Methodology
recommended
by
Bruce
E.
Baker,
State
and
Local
Governments,
Government
Division,
U.
S.
Bureau
of
Economic
Analysis.

4The
"
other"
category
contains
systems
that
do
not
yet
have
a
specific
function
identified.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
7
Small
government
systems
include
municipal,
county,
state,
federal,
military,
and
special
district
systems.
Data
on
revenue
for
townships
and
municipalities
were
obtained
from
the
1992
Census
of
Governments
(
U.
S.
Department
of
Commerce
1992),
converted
to
2000
dollars
by
applying
a
conversion
factor
calculated
from
the
national
income
and
product
account
tables
of
the
U.
S.
Bureau
of
Economic
Analysis.
3
Specifically,
the
price
deflators
for
1992
and
2000
were
obtained
from
Chain­
Type
Price
Indexes
for
State
and
Local
Governments
(
U.
S.
Department
of
Commerce
2002).
The
average
revenue
for
all
small
governments
with
PWSs
was
calculated
at
$
2,396,249.

Small
business­
run
PWSs
in
Exhibits
8.1a
and
8.1b
include
both
CWSs
and
NTNCWSs,
such
as
privately
owned
CWSs,
mobile
home
parks,
country
clubs,
hotels,
manufacturers,
hospitals,
and
other
establishments.
For
this
analysis,
all
hospitals
and
day
care
centers
are
assumed
to
be
businesses,
as
are
50
percent
of
systems
classified
as
"
other."
4
Estimated
average
revenue
for
the
small
businesses
affected
by
the
Stage
2
DBPR
is
$
2,391,978.

Small
organizations
include
primarily
nonprofit
NTNCWS
such
as
schools
and
homeowners
associations.
The
revenue
estimates
for
small
nonprofit
organizations
serving
more
than
500
people
are
actually
higher
than
those
for
small
businesses
because
the
total
number
of
such
systems
is
small,
and
a
large
proportion
of
these
organizations
are
schools
and
colleges
with
large
budgets.
This
category
also
includes
50
percent
of
systems
classified
as
"
other."
The
average
estimated
revenue
for
small
organizations
affected
by
the
Stage
2
DBPR
is
$
4,446,165.

EPA
also
calculated
the
average
estimated
revenue
for
all
small
entity
PWSs.
This
estimate
is
weighted
to
account
for
the
number
of
small
entity
PWSs
in
each
category
(
government,
business,
and
organization)
affected
by
the
Stage
2
DBPR.
This
overall
average
is
$
2,578,991.

Summary
of
the
SBREFA
Process
The
RFA,
as
amended
by
SBREFA,
and
Section
203
of
UMRA
require
EPA
to
provide
small
governments
with
an
opportunity
for
timely
and
meaningful
participation
in
the
regulatory
development
process.
EPA
provided
stakeholders,
including
small
governments,
with
several
opportunities
to
provide
input
on
the
Stage
2
DBPR.
For
example,
EPA
conducted
three
outreach
conference
calls
in
Washington,
DC
to
solicit
feedback
and
information
from
the
Small
Entity
Representatives
(
SERs)
on
issues
regarding
Stage
2
DBPR
impacts
on
small
systems.
SERs
included
small
system
operators,
local
government
officials,
and
small
nonprofit
organizations.

During
the
first
call,
held
on
January
28,
2000,
EPA
presented
an
overview
of
the
SDWA,
as
amended
in
1996
and
SBREFA.
Issues
and
schedules
for
the
Stage
2
DBPR
rules
were
also
discussed.
The
second
call
was
held
on
February
25,
2000.
EPA
presented
the
stakeholders
with
an
overview
of
the
EPA
regulatory
development
process
and
background
on
the
development
of
the
Stage
2
Microbial­
Disinfectants/
Disinfection
Byproduct
(
M­
DBP)
Rules,
particularly
regarding
health
risks,
issues/
options
identified
by
the
Federal
Advisory
Committees
Act
(
FACA)
Committee,
and
Disinfection
Byproduct
(
DBP)
and
microbial
occurrence
in
small
systems.
The
third
meeting
was
held
on
April
7,
2000.
EPA
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
8
presented
SERs
with
a
cost
estimate
and
an
impact
analysis
for
selected
regulatory
options.
In
addition,
EPA
presented
SERs
with
schedules
for
the
FACA
and
SBREFA
processes.

These
three
outreach
calls
generated
a
wide
range
of
information,
issues,
and
technical
input
from
SERs.
To
provide
SERs
with
a
foundation
for
commenting
on
these
rules,
EPA
provided
them
with
extensive
background
information.
In
general,
the
SERs
were
concerned
about
the
impact
of
these
proposed
rules
on
small
water
systems
(
because
of
their
small
staff
and
limited
budgets),
small
systems'
ability
to
acquire
the
technical
and
financial
capability
to
implement
requirements,
maintaining
the
flexibility
to
tailor
requirements
to
their
needs,
and
limitations
of
small
systems.
The
Agency
used
the
feedback
received
during
these
meetings
in
developing
the
Stage
2
DBPR.
EPA
also
mailed
a
draft
version
of
the
preamble
to
the
attendees
of
these
meetings.

The
Agency
convened
a
Small
Business
Advocacy
Review
(
SBAR)
Panel,
in
accordance
with
the
RFA,
as
amended
by
SBREFA,
to
address
small
entity
concerns,
including
those
of
small
local
governments.
EPA
convened
the
SBAR
Panel
after
completing
the
consultation
meetings
with
SERs
on
the
Stage
2
DBPR.
Eight
of
the
small
entities
represented
small
governments.
SER's
concerns
were
provided
to
the
SBAR
Panel
when
the
Panel
convened
on
April
25,
2000.

8.3
Small
System
Affordability
Section
1415(
e)(
1)
of
SDWA
allows
States/
Primacy
Agencies
to
grant
variances
to
small
water
systems
(
i.
e.,
those
serving
fewer
than
10,000
people)
in
lieu
of
complying
with
a
maximum
contaminant
level
(
MCL)
if
EPA
determines
that
no
nationally
affordable
compliance
technologies
exist
for
that
system
size/
water
quality
combination.
These
variances
may
only
be
granted
when
EPA
has
identified
a
variance
technology
under
Section
1412(
b)(
15)
for
the
contaminant,
system
size,
and
source
water
quality
in
question.
The
system
must
then
install
an
EPA­
listed
variance
treatment
technology
(
§
1412(
b)(
15))
that
makes
progress
toward
the
MCL,
if
not
necessarily
reaching
it.
To
list
variance
technologies,
three
showings
must
be
made.

1)
EPA
must
determine,
on
a
national
level,
that
there
are
no
compliance
technologies
that
are
available
and
affordable
for
the
given
small
system
size
category/
source
water
quality
combination.

2)
If
there
is
no
nationally
affordable
compliance
technology,
then
EPA
must
identify
a
variance
technology
that
may
not
reach
the
MCL,
but
that
will
allow
small
systems
to
make
progress
toward
the
MCL
(
it
must
achieve
the
maximum
reduction
affordable).
This
technology
must
also
be
listed
as
a
small
system
variance
technology
by
EPA
in
order
for
small
systems
to
be
able
to
rely
on
it
for
regulatory
purposes.

3)
EPA
must
make
a
finding,
on
a
national
level,
that
the
use
of
the
variance
technology
would
be
protective
of
public
health.

The
State/
Primacy
Agency
must
then
make
a
site­
specific
determination
for
each
system
as
to
whether
the
system
can
afford
to
meet
the
MCL
based
on
affordability
criteria
developed
by
the
State/
Primacy
Agency.
If
the
State/
Primacy
Agency
determines
that
compliance
is
not
affordable
for
the
system,
it
may
grant
a
variance,
but
it
must
establish
terms
and
conditions,
as
necessary,
to
ensure
that
the
variance
adequately
protects
human
health.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
9
The
1996
SDWA
Amendments
identify
three
categories
of
small
PWSs
that
need
to
be
addressed:
(
1)
those
serving
a
population
of
3,301
to
10,000;
(
2)
those
serving
a
population
of
501
to
3,300;
and
(
3)
those
serving
a
population
of
25
to
500.
SDWA
requires
EPA
to
make
determinations
of
available
compliance
technologies
and,
if
needed,
variance
technologies
for
each
size
category.
A
compliance
technology
is
a
technology
that
is
affordable
and
that
achieves
compliance
with
the
MCL
and/
or
treatment
technique.
Compliance
technologies
can
include
point­
of­
entry
(
POE)
or
point­
of­
use
(
POU)
treatment
units.
Variance
technologies
are
specified
only
for
those
system
size/
source
water
quality
combinations
for
which
there
are
no
listed
compliance
technologies.

The
following
sections
show
how
small
system
affordability
was
evaluated
for
the
Stage
2
DBPR.
The
analysis
is
consistent
with
the
methodology
used
in
the
document
National­
Level
Affordability
Criteria
Under
the
1996
Amendments
to
the
Safe
Drinking
Water
Act
(
USEPA
1998c)
and
the
Variance
Technology
Findings
for
Contaminants
Regulated
Before
1996
(
USEPA
1998d).
Because
EPA
determined
that
affordable
compliance
technologies
are
available
for
all
small
systems
for
the
Stage
2
DBPR,
EPA
did
not
identify
any
variance
technologies.

8.3.1
Affordability
Threshold
EPA
discussed
its
draft
national­
level
affordability
criteria
in
the
August
6,
1998,
Federal
Register
for
the
contaminants
regulated
before
1996.
National­
level
affordability
criteria
were
developed
by
identifying
an
"
affordability
threshold"
(
i.
e.,
the
total
annual
household
water
bill
that
would
be
considered
affordable).
In
developing
this
threshold,
EPA
considered
the
percentage
of
median
household
income
(
MHI)
spent
by
an
average
household
on
comparable
goods
and
services,
including
housing
(
28
percent),
transportation
(
16
percent),
food
(
12
percent),
energy
and
fuels
(
3.3
percent),
telephone
(
1.9
percent),
water
and
other
public
services
(
0.7
percent),
entertainment
(
4.4
percent),
and
alcohol
and
tobacco
(
1.5
percent).
Another
key
factor
that
EPA
used
to
select
an
affordability
threshold
was
cost
comparisons
with
other
risk
reduction
activities
for
drinking
water.
Section
1412(
b)(
4)(
E)(
ii)
of
SDWA
identifies
both
POU
and
POE
devices
as
compliance
technologies
for
small
systems.
EPA
examined
the
projected
costs
of
these
options,
and
also
investigated
the
costs
associated
with
supplying
bottled
water
for
drinking
and
cooking.
The
median
income
percentages
associated
with
these
riskreduction
activities
were
more
than
2.5
percent
for
POE
devices
and
bottled
water,
and
2
percent
for
POU
devices.
Based
on
the
foregoing
analysis,
EPA
developed
an
affordability
criterion
of
2.5
percent
of
MHI,
or
approximately
$
800
(
2000
dollars),
for
the
affordability
threshold
(
USEPA
1998c).

The
median
water
bill
for
households
in
each
small
system
size
category
was
subtracted
from
the
affordability
threshold
to
obtain
the
affordable
level
of
expenditure
per
household
for
new
treatment.
This
difference
is
referred
to
as
the
"
available
expenditure
margin."
Based
on
EPA's
1995
CWSS,
median
water
bills
were
about
$
250
per
year
for
small
system
customers.
Thus,
an
average
available
expenditure
margin
of
up
to
$
550
per
year
was
considered
affordable
for
the
contaminants
regulated
before
1996.
However,
the
available
expenditure
margins
are
expected
to
change
because
water
rates
and
MHI
have
increased.
The
1995
MHI
was
updated
to
2000
dollars
using
the
Consumer
Price
Index
(
CPI)
(
BLS
2001a).
The
results
are
shown
in
Exhibit
8.2.
The
baseline
for
annual
water
bills
(
median
water
bill
from
the
1995
CWSS)
also
increased
to
account
for
regulations
promulgated
after
1996,
but
before
the
Stage
2
DBPR
is
promulgated.
5
Costs
from
the
Radionuclides
Rule
were
not
included
in
this
analysis;
however,
they
are
assumed
to
be
small.
EPA
is
currently
receiving
input
from
a
NDWAC
Working
Group
on
the
national­
level
affordability
criteria.
This
process
is
expected
to
conclude
in
January
2003
with
a
report
that
will
be
sent
to
the
NDWAC
for
their
review
before
it
is
sent
to
EPA.
EPA
is
reviewing
a
draft
report
published
by
the
Science
Advisory
Board's
Environmental
Economics
Advisory
Committee
on
November
14,
2002
on
its
review
of
the
national­
level
affordability
criteria.
One
of
the
charges
given
to
both
groups
was
to
evaluate
the
process
used
by
EPA
to
adjust
the
baseline
water
bills
to
account
for
costs
attributable
to
regulations
promulgated
after
1996.
The
estimate
presented
in
this
EA
was
derived
by
spreading
total
annual
or
annualized
costs
for
each
rule
(
at
a
3
percent
discount
rate)
over
the
total
number
of
households
by
size
category.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
10
MHI
(
2000)
Pre­
1996
Median
Waterbills
(
2000)
Adjusted
Waterbills
%
MHI
for
Waterbills
A
B
C
D=
C/
A
E=
A*
2.5%
F=
E­
C
0
­
500
35,148
$
241
$
290
$
0.83%
879
$
588
$
501
­
3,300
30,893
$
210
$
230
$
0.74%
772
$
542
$
3,301
­
10,000
31,559
$
207
$
219
$
0.69%
789
$
570
$
Affordability
Threshold
Available
Expenditure
Margin
Baseline
(
2000$)
Small
System
Available
Expenditures
Population
Served
For
each
rule
promulgated
after
1996,
the
total
national
costs
for
each
small
size
category
were
averaged
over
the
number
of
households
within
that
size
category.
The
mean
costs
per
household
for
each
size
category
were
added
to
the
national
median
annual
household
water
bills.
This
was
done
for
the
following
rules:
the
Arsenic
Rule,
Interim
Enhanced
Surface
Water
Treatment
Rule
(
IESWTR),
Long
Term
1
Enhanced
Surface
Water
Treatment
Rule
(
LT1ESWTR),
Stage
1
DBPR,
Filter
Backwash
Recycling
Rule,
Consumer
Confidence
Rule,
and
Public
Notification
Rule.
5
As
some
rules
affect
ground
and
surface
water
systems
disproportionately,
the
adjusted
water
bill
is
likely
to
be
an
over­
estimate
of
the
true
cost
of
the
rules.
However,
the
adjusted
water
bill
may
also
under­
estimate
costs,
which
were
spread
over
the
total
number
of
households
by
size
category,
as
opposed
to
only
the
households
affected
by
each
rule.
Exhibit
8.2
presents
the
analysis
before
and
after
the
baseline
water
bill
was
adjusted
for
regulations
promulgated
after
1996.

Exhibit
8.2
Derivation
of
Available
Expenditure
Margin
Note:
Detail
may
not
add
due
to
independent
rounding.
MHI=
Median
household
income;
HH=
households;
the
baseline
numbers
and
affordability
threshold
reflect
the
25­
500
population
served
category,
but
the
average
household
cost
for
this
category
also
contains
those
systems
serving
0­
25
people.
The
0­
25
system
size
category
accounts
for
only
0.8%
of
all
systems
serving
0­
500
people.

Sources:
(
A)
Variance
Technology
Findings
for
Contaminants
Regulated
Before
1996
(
USEPA
1998d),
adjusted
to
2000$
using
the
Consumer
Price
Index
(
BLS
2001a).
(
B)
1995
CWSS
(
as
reported
in
the
document
Variance
Technology
Findings
for
Contaminants
Regulated
Before
1996),
adjusted
to
2000$
using
the
Consumer
Price
Index
(
BLS
2001a).
(
C)
Pre­
1996
Median
Water
Bills
(
2000)
from
Column
B
plus
mean
HH
costs
for
drinking
water
rules
since
1996,
except
Radionuclides
Rule.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
11
Median
Average
Daily
Flow
Design
Flow
a
b
c
d
=
1.15*
c
25­
500
0.015
0.058
72
83
501­
3,300
0.17
0.5
74
85
3,301­
10,000
0.7
1.8
77
89
System
Size
(
Population
Served)
Median
HH
Consumption
Rates
(
kgal/
yr)
Flows
(
mgd)
HH
Consumption
Rate
Used
for
Costing
8.3.2
Affordable
Compliance
Technologies
Section
1412(
b)(
4)(
E)(
ii)
of
SDWA,
as
amended
in
1996,
requires
EPA
to
list
technologies
that
achieve
compliance
with
MCLs
established
under
the
Act
that
are
affordable
and
applicable
to
typical
small
drinking
water
systems.
Owners
and
operators
may
choose
any
technology
or
technique
that
best
suits
their
conditions,
as
long
as
the
MCL
is
met.

This
section
presents
household
costs
($
per
household
per
year)
for
various
technologies
for
comparison
to
the
available
expenditure
margin
in
Exhibit
8.2.
The
methodology
for
generating
household
cost
estimates
is
explained
in
detail
in
section
6.1.1.
In
general,
the
analysis
in
this
section
followed
the
methodology
in
section
6.1.1;
however,
some
inputs
for
household
cost
calculations
in
this
section
are
different
and,
in
some
cases,
are
conservatively
high
compared
to
data
used
to
generate
household
cost
distributions
in
Chapter
6.
A
conservatively
high
estimate
of
household
costs
is
used
to
more
accurately
reflect
the
high­
end
variability
in
household
costs.
This
allows
affordability
of
the
Stage
2
DBPR
to
be
more
confidently
assessed
across
the
range
of
all
affected
small
systems.

The
size
categories
specified
in
SDWA
for
affordable
technology
determinations
are
different
than
the
nine
standard
size
categories
used
in
the
majority
of
this
Economic
Analysis,
and
subsequently,
mean
design
and
average
daily
flows
for
each
category
are
different.
The
Variance
Technology
Findings
Document
(
USEPA
1998d)
describes
in
detail
the
derivation
of
design
and
average
flows
(
values
are
shown
in
Exhibit
8.3).

Exhibit
8.3
Affordability
Analysis
Inputs
Source:
a,
b,
and
c:
Variance
Technology
Findings
for
Contaminants
Regulated
Before
1996
(
USEPA
1998d).
d.
Consumption
rates
were
adjusted
upward
by
15
percent
to
account
for
distribution
system
leaks.

For
each
technology,
unit
treatment
costs
($
per
1,000
gallons)
are
estimated
using
the
flow
rates
shown
in
Exhibit
8.3
and
technology
unit
costs
in
Appendix
I
(
see
Exhibit
I.
27
for
details
on
the
derivation
of
unit
treatment
costs).
Capital
costs
were
annualized
using
a
7
percent
discount
rate
rather
than
the
costs­
of­
capital
rates
used
to
generate
the
distribution
of
household
costs
in
Chapter
6.
The
unit
treatment
costs
($
per
1,000
gallons)
were
multiplied
by
annual
household
consumption
rates
to
determine
the
annual
household
cost
increase
($
per
household)
for
each
treatment
technology.
Annual
consumption
rates
are
shown
in
Exhibit
8.3
and
represent
median
yearly
consumption
rates
based
on
results
from
the
1995
Community
Water
System
Survey
(
CWSS).
(
Note
that
mean
yearly
household
consumption
rates
are
shown
in
Exhibit
6.2
and
are
used
for
household
cost
estimates
in
Chapter
6).
The
values
shown
in
6Although
the
size
categories
specified
by
SDWA
for
the
affordability
analysis
does
not
specifically
cover
systems
serving
fewer
than
25
people
(
per
SDWA),
these
systems
are
included
in
all
other
analyses
in
this
EA
and
are
accounted
for
in
Exhibit
8.4c.
Thus,
the
estimate
of
the
number
of
systems
and
households
experiencing
cost
increases
in
Exhibit
8.4c
is
conservatively
high.

7
Source:
A
total
fo
1,535
small
plants
are
predicted
to
add
treatment,
derived
from
Exhibit
6.4
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
12
Exhibit
8.3
were
adjusted
upward
by
15
percent
to
account
for
water
lost
in
the
distribution
system
due
to
leaks.

Exhibits
8.4a
and
8.4b
show
the
compliance
technologies
for
the
Stage
2
DBPR
for
surface
water
and
ground
water
systems
along
with
their
mean
annual
household
costs
for
each
of
the
three
size
categories.
Exhibit
8.4c
presents
annual
household
cost
increases
for
all
households
served
by
plants
installing
treatment
to
comply
with
the
Stage
2
DBPR
for
systems
serving
0
to
500,
501
to
3,300
and
3,301
to
10,000
people6.
The
mean,
median,
90th
percentile,
and
95th
percentile
values
are
shown
as
well
as
the
available
expenditure
margin
and
the
number
of
households
and
plants
that
will
experience
annual
cost
increases
above
the
available
expenditure
margin.

With
very
few
exceptions,
the
household
costs
for
technologies
in
Exhibits
8.4a
and
8.4b
are
below
the
available
expenditure
margin.
The
only
technology
selected
for
the
Stage
2
DBPR
Preferred
Regulatory
Alternative
slightly
above
the
available
expenditure
margin
for
surface
water
systems
serving
0
to
500
people
was
Granular
Activated
Carbon
 
20­
Minute
Contact
Time
(
GAC20)
(
90­
day
reactivation
frequency)
with
advanced
disinfectants.
As
shown
in
Exhibit
8.4c,
approximately
22
plants
(
approximately
1.4
percent
of
all
small
plants
adding
treatment)
7
in
surface
water
systems
serving
fewer
than
500
people
are
expected
to
select
GAC20
plus
advanced
disinfectants
to
comply
with
the
Stage
2
DBPR.

EPA
believes,
however,
that
the
number
of
plants
in
small
systems
predicted
to
add
advanced
technologies
(
including
GAC20)
is
overstated
for
two
reasons:
1)
distribution
system
modifications
are
not
considered
in
the
compliance
forecast,
and
2)
Stage
2
DBPR
requirements
for
small
systems
are
similar
to
Stage
1
DBPR
requirements
and
may
not
trigger
compliance
violations,
as
explained
in
the
minimal
impacts
sensitivity
analysis
in
Chapter
7.

Very
few
households
will
experience
increases
above
the
available
expenditure
margin
as
a
result
of
adding
advanced
technology
to
comply
with
the
Stage
2
DBPR.
This
number
is
probably
overestimated
because
systems
may
be
able
to
comply
with
the
rule
using
methods
other
than
advanced
treatment.
For
example,
systems
operating
on
a
part­
time
basis
may
be
able
to
modify
their
operational
schedule
or
use
excessive
capacity
to
comply
with
the
Stage
2
DBPR
rather
than
install
a
costly
technology.
Some
systems
may
identify
an
alternative
water
source
that
has
lower
TTHM
and
HAA5
precursor
levels,
which
would
require
less
intense
treatment
and
result
in
lower
treatment
costs.
Other
systems
may
elect
to
connect
to
a
neighboring
water
system.
While
connecting
to
another
system
may
not
be
feasible
for
certain
remote
systems,
EPA
estimates
that
more
than
22
percent
of
all
small
water
systems
are
located
within
metropolitan
regions
(
USEPA
2000d)
where
distances
between
neighboring
systems
will
not
present
a
prohibitive
barrier.
Refer
to
Chapter
6
for
a
more
detailed
discussion
of
household
cost
increases.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
13
0­
500
501­
3,300
3,301­
10,000
Chloramines
(
0.15
mg/
L)
63.75
$
9.24
$
4.91
$
Chlorine
Dioxide
(
1.25
mg/
L)
1
270.16
$
29.25
$
9.91
$
UV
(
40mJ/
cm2)
88.90
$
20.15
$
13.30
$
Ozone
(
0.5­
log
dose)
1
1,292.81
$
143.18
$
55.05
$
MF/
UF
1
576.84
$
170.11
$
112.62
$
GAC20
(
EBCT=
20
min,
90
day
regeneration)
1
639.35
$
206.61
$
131.67
$
GAC20
+
Advanced
Disinfectants
728.25
$
349.79
$
186.72
$
Integrated
Membranes1
915.12
$
309.94
$
234.56
$
System
Size
(
Population
Served)
Compliance
Technologies
0­
500
501­
3,300
3,301­
10,000
Chloramines
(
0.15
mg/
L)
63.57
$
9.10
$
4.76
$
UV
(
200mJ/
cm2)
126.03
$
33.64
$
26.22
$
Ozone
(
0.5­
log
dose)
1
1,292.81
$
143.18
$
55.05
$
GAC20
(
EBCT=
20
min,
240
day
regeneration)
1
409.40
$
156.58
$
93.42
$
Nanofiltration
1
338.29
$
139.83
$
121.94
$
System
Size
(
Population
Served)
Compliance
Technologies
Systems
Size
(
population
served)
Number
of
Households
Served
by
Plants
Adding
Treatment
(
Percent
of
all
Households
Subject
to
the
Stage
2
DBPR
Mean
Annual
Household
Cost
Increase
Median
Annual
Household
Cost
Increase
90th
Percentile
Annual
Household
Cost
Increase
95th
Percentile
Annual
Household
Cost
Increase
Available
Expenditure
Margin
($/
hh/
yr)
Number
of
Housholds
with
Annual
Cost
Increases
Greater
then
the
Available
Expenditure
Margin
Number
of
Plants
with
Annual
Cost
Increases
Greater
than
the
Available
Expenditure
Margin
A
B
C
D
E
F
G
H
0
­
500
42,355
(
3.0%)
$
184.55
$
189.59
$
189.59
$
409.40
$
588
1,325
22
501
­
3,300
158,044
(
2.8%)
$
47.74
$
38.48
$
152.41
$
215.85
$
542
0
0
3,301
­
10,000
221,110
(
3.0%)
$
33.21
$
13.30
$
98.18
$
186.72
$
570
0
0
Exhibit
8.4a
Affordable
Compliance
Technologies
and
Household
Unit
Treatment
Costs
($/
HH/
Year)
for
Surface
Water
Systems
Exhibit
8.4b
Affordable
Compliance
Technologies
and
Household
Unit
Treatment
Costs
($/
HH/
Year)
for
Ground
Water
Systems
Notes:
Shaded
cells
represent
technologies
that
were
not
in
the
decision
tree
for
part
or
all
of
the
size
category.
Costs
annualized
at
a
7%
discount
rate.
1.
Zero
percent
of
plants
selected
this
technology.

Source:
Exhibit
J.
27.

Exhibit
8.4c
Distribution
of
Household
Unit
Treatment
Costs
for
Plants
Adding
Treatment
Notes:
Household
unit
costs
reflect
treatment
costs
only,
as
presented
in
Exhibits
8.4a
and
8.4b.

Source:
Household
unit
costs
in
Exhibits
8.4a
and
8.4b
combined
with
technology
selection
deltas
in
Exhibits
6.14
and
6.16.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
14
Low­
or
even
no­
cost
alternatives
that
would
reduce
total
trihalomethanes
(
TTHM)
and
haloacetic
acid
(
HAA5)
levels
in
the
distribution
system
by
reducing
average
residence
time
include
flushing
distribution
mains
more
frequently,
modifying
the
problematic
portions
of
the
system,
and
optimizing
storage
to
minimize
retention
time.
These
were
not
considered
in
the
Stage
2
DBPR
compliance
forecast
(
see
section
6.4.1.2
for
a
more
detailed
discussion
of
alternatives
to
treatment).
These
activities
could
be
used
to
help
systems
meet
compliance
by
using
a
less
expensive
technology
than
GAC20.

Under
the
Stage
1
DBPR,
surface
and
ground
water
systems
serving
fewer
than
500
people
must
have
one
site
for
TTHM
and
HAA5
monitoring.
Under
the
Stage
2
DBPR,
systems
have
to
add
a
site
if
their
highest
TTHM
and
HAA5
concentrations
are
at
different
locations.
EPA
estimates
that
approximately
3/
4
of
systems
serving
fewer
than
100
people
will
have
one
site
representing
both
their
highest
TTHM
and
HAA5
concentration
for
the
Stage
2
DBPR.
Systems
with
one
site
for
Stage
1
and
one
site
for
the
Stage
2
DBPR
would
produce
the
same
measure
of
compliance
whether
based
on
a
running
annual
average
(
RAA)
(
Stage
1
compliance)
or
a
locational
running
annual
average
(
LRAA)
(
Stage
2
compliance)
calculation.

In
addition,
it
is
anticipated
that
systems
currently
predicted
by
EPA
to
select
GAC20
may,
in
fact,
be
able
to
use
less
expensive
technologies
by
the
time
the
Stage
2
DBPR
is
implemented.
This
is
because
the
compliance
decision
tree
(
summarized
in
Chapter
3
and
described
in
detail
in
Appendices
A
and
B)
reflects
current
limitations
on
the
use
of
inexpensive
technologies
(
e.
g.,
chloramines
and
UV)
based
on
operational
and
constructability
constraints.
These
limitations
may
not
exist
by
the
time
the
rule
is
implemented
due
to
advances
in
treatment
and
new
innovations
by
manufacturers.

8.3.3
Funding
Options
for
Disadvantaged
Systems
EPA
believes
that
there
is
another
mechanism
in
SDWA
to
address
cost
impacts
on
small
systems
composed
primarily
of
low­
income
households.
Systems
that
meet
criteria
established
by
the
State/
Primacy
Agency
could
be
classified
as
disadvantaged
communities
under
§
1452(
d)
of
the
SDWA.
They
can
receive
additional
subsidies
through
the
Drinking
Water
State
Revolving
Fund
(
DWSRF),
including
forgiveness
of
principal.
Under
DWSRF,
States/
Primacy
Agencies
must
provide
a
minimum
of
15
percent
of
the
available
funds
for
infrastructure
loans
to
systems
serving
10,000
or
fewer
people.
Two
percent
of
the
State's/
Primacy
Agency's
grant
is
set­
aside
funding
that
can
only
be
used
to
provide
technical
assistance
to
small
systems.
In
addition,
up
to
14
percent
of
the
State's/
Primacy
Agency's
grant
may
be
used
to
provide
technical,
managerial,
and
financial
assistance
to
all
system
sizes.
For
small
systems
that
are
disadvantaged,
as
defined
by
the
State/
Primacy
Agency,
up
to
30
percent
of
a
State's/
Primacy
Agency's
DWSRF
may
be
used
for
increased
loan
subsidies.

Small
systems
will
be
encouraged
to
discuss
their
infrastructure
needs
for
complying
with
the
Stage
2
DBPR
with
their
State/
Primacy
Agency
to
determine
their
eligibility
for
DWSRF
loans,
and,
if
eligible,
to
ask
for
assistance
in
applying
for
the
loans.

8.4
Feasible
Treatment
Technologies
for
All
Systems
In
accordance
with
Section
1412(
b)(
4)(
E)
of
the
1996
SDWA
Amendments,
EPA
examined
whether
there
were
existing,
feasible
technologies
and
treatment
techniques
available
that
would
allow
systems
to
meet
the
Stage
2
DBPR
requirements.
EPA
examined
alternatives
for
best
available
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
15
technologies
(
BATs)
using
two
methods:
Information
Collection
Rule
(
ICR)
treatment
studies
and
Surface
Water
Analytical
Tool
(
SWAT)
predictions.
A
discussion
of
the
evaluation
is
provided
in
sections
8.4.1
and
8.4.2.
Results
from
these
two
evaluations
show
that
all
systems
can
meet
the
TTHM
and
HAA5
LRAA
MCLs
(
80
µ
g/
L
and
60
µ
g/
L,
respectively)
using
one
of
the
three
following
technologies:

1)
GAC
adsorbers
with
at
least
10
minutes
of
empty­
bed
contact
time
and
an
annual
average
reactivation/
replacement
frequency
no
greater
than
120
days.

2)
Enhanced
coagualtion
and
nanofiltration
using
a
membrane
with
a
molecular
weight
cutoff
of
1000
Daltons
or
less
(
or
demonstrated
to
reject
at
least
80
percent
of
the
influent
total
organic
carbon
(
TOC)
concentration
under
typical
operating
conditions).

3)
GAC
adsorbers
with
at
least
20
minutes
of
empty­
bed
contact
time
and
an
annual
average
reactivation/
replacement
frequency
no
greater
than
240
days.

Section
8.4.3
discusses
BATs
specifically
for
consecutive
systems.

8.4.1
ICR
Treatment
Studies
The
ICR
treatment
studies
were
designed
to
evaluate
the
technical
feasibility
of
using
GAC
and
nanofiltration
to
remove
DBP
precursors
prior
to
the
addition
of
chlorine
based
disinfectants
(
USEPA
2000q;
Hooper
and
Allgeier
2002).
Applicability
to
the
ICR
treatment
study
requirement
was
based
on
TOC
levels
in
the
source
or
finished
water.
Specifically,
surface
water
plants
with
annual
average
source
water
TOC
concentrations
greater
than
4
mg/
L
and
ground
water
plants
with
annual
average
finished
water
TOC
concentrations
greater
than
2
mg/
L
were
required
to
conduct
treatment
studies.
Thus,
the
plants
required
to
conduct
treatment
studies
generally
had
waters
with
organic
DBP
precursor
levels
that
were
significantly
higher
than
the
national
means
of
3.2
mg/
L
and
1.5
mg/
L
for
ICR
surface
and
ground
water
plants,
respectively
(
USEPA
2003l).

Plants
that
used
GAC
typically
evaluated
performance
at
two
empty­
bed
contact
times,
10
and
20
minutes,
and
over
a
range
of
operational
times
to
evaluate
the
unsteady
nature
of
TOC
removal
by
GAC.
This
allowed
GAC
performance
to
be
assessed
with
respect
to
empty­
bed
contact
time,
as
well
as
reactivation/
replacement
frequency.
Plants
that
conducted
membrane
treatment
studies
evaluated
one
or
two
nanofiltration
membranes
with
molecular
weight
cutoffs
less
than
1,000
Daltons.
Regardless
of
the
technology
evaluated,
all
treatment
studies
evaluated
DBP
formation
after
treatment
under
distribution
system
conditions
representative
of
the
full­
scale
plant
at
the
average
residence
time,
using
free
chlorine
as
the
primary
and
residual
disinfectant.

Based
on
the
ICR
treatment
study,
GAC
would
be
an
appropriate
technology
for
surface
water
systems
and
some
ground
water
systems
with
influent
TOC
concentrations
below
approximately
6
mg/
L
(
based
on
the
ICR
and
National
Rural
Water
Association
(
NRWA)
data,
over
90
percent
of
plants
have
average
influent
TOC
levels
below
6
mg/
L)
(
USEPA
2003l).
Larger
systems
would
likely
realize
an
economic
benefit
from
on­
site
reactivation,
which
could
allow
them
to
use
smaller,
10­
minute
empty­
bed
contact
time
contactors
with
more
frequent
reactivation
(
i.
e.,
120
days
or
less).
Most
small
utilities
would
not
find
it
economically
advantageous
to
install
on­
site
carbon
reactivation
facilities,
and,
thus,
would
opt
for
larger,
20­
minute
empty­
bed
contact
time
contactors,
with
less
frequent
carbon
replacement
(
i.
e.,
240
days
or
less).
EPA
recognizes
that
some
small
systems
attempting
to
implement
GAC20
may
face
GAC
supply
challenges.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
16
Theoretically,
there
is
a
linear
relationship
between
empty­
bed
contact
time
and
reactivation
interval.
Assuming
equivalent
performance,
a
doubling
of
the
empty­
bed
contact
time
would
be
expected
to
result
in
a
doubling
of
the
reactivation
interval.
If
this
is
the
case,
the
10­
minute
empty­
bed
contact
time
contactor
reactivated
at
120
days
should
result
in
equivalent
performance
to
a
20­
minute
empty­
bed
contact
time
contactor
reactivated
at
240
days.
However,
the
ICR
treatment
study
data
demonstrated
that
the
20­
minute
contactors
generally
outperform
the
10­
minute
contactors
on
a
normalized
basis.
On
the
other
hand,
larger
systems
will
typically
operate
with
a
larger
number
of
parallel
contactors
compared
to
small
systems,
resulting
in
improved
performance.
Thus,
the
benefit
that
small
systems
gain
by
using
a
larger
empty­
bed
contact
time
will
be
offset
by
use
of
a
smaller
number
of
parallel
contactors.
Based
on
these
considerations,
the
proposed
reactivation/
replacement
interval
for
the
20­
minute
contactor
is
simply
double
the
reactivation/
replacement
interval
for
a
10­
minute
contactor.

The
ICR
treatment
study
data
demonstrated
that
approximately
70
percent
of
the
surface
water
plants
that
conducted
GAC
studies
could
meet
the
80/
60
µ
g/
L
TTHM/
HAA5
MCLs
with
a
20
percent
safety
factor
using
GAC
with
10
minutes
of
empty­
bed
contact
time
and
a
120­
day
reactivation
frequency.
The
ICR
treatment
study
data
also
showed
that
78
percent
of
the
plants
could
meet
the
MCLs
using
GAC
with
20
minutes
of
empty­
bed
contact
time
and
a
240­
day
reactivation
frequency.
As
discussed
previously,
the
treatment
studies
were
conducted
at
plants
with
poorer
water
quality
than
the
national
average.
Therefore,
EPA
believes
that
the
percentages
of
plants
in
the
GAC
studies
that
could
meet
the
MCLs
with
the
proposed
BATs
translate
to
much
higher
percentages
of
plants
nationwide.

The
ICR
treatment
study
results
also
demonstrated
that
GAC
was
not
an
effective
DBP
control
technology
for
ground
water
sources
with
high
TOC
concentrations
(
i.
e.,
above
approximately
6
mg/
L).
However,
the
results
of
the
membrane
treatment
studies
showed
that
all
ground
water
plants
could
meet
the
80/
60
µ
g/
L
TTHM/
HAA5
MCLs
with
a
20
percent
safety
factor
at
the
average
distribution
system
residence
time
using
nanofiltration
(
USEPA
2000q;
Hooper
and
Allgeier
2002).
Although
nanofiltration
is
generally
more
expensive
than
GAC,
it
would
be
less
expensive
than
GAC
for
high
TOC
ground
waters
that
require
minimal
pretreatment.
Also,
nanofiltration
is
an
accepted
technology
for
treatment
of
high
TOC
ground
waters
in
areas
of
the
country
with
elevated
TOC
levels
in
ground
waters,
such
as
Florida
and
parts
of
the
southwest.

8.4.2
BAT
Evaluation
Using
SWAT
The
second
method
that
EPA
used
to
examine
alternatives
for
BAT
was
SWAT
(
McGuire
2001).
EPA
considered
the
following
BAT
options:

°
Enhanced
coagulation
(
EC)/
softening
with
chlorine
°
EC/
softening
with
chlorine
and
no
pre­
disinfection
°
EC
and
GAC10
°
EC
and
GAC20
°
EC
and
chloramines
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
17
EC/
softening
is
required
under
the
Stage
1
DBPR
for
conventional
plants.
In
the
model,
GAC10
was
defined
as
granular
activated
carbon
with
an
empty­
bed
contact
time
of
10
minutes
and
a
reactivation
frequency
of
no
more
than
90
days.
GAC20
was
defined
as
granular
activated
carbon
with
an
empty­
bed
contact
time
of
20
minutes
and
a
reactivation
or
replacement
frequency
of
no
more
than
90
days.
EPA
assumed
that
systems
would
be
operating
to
achieve
both
the
Stage
2B
MCLs
of
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
as
an
LRAA
and
the
Surface
Water
Treatment
Rule
(
SWTR)
removal
and
inactivation
requirements
of
3­
log
for
Giardia
and
4­
log
for
viruses.
EPA
also
evaluated
the
BAT
options
under
the
assumption
that
plants
operate
to
achieve
DBP
levels
20
percent
below
the
MCL
(
safety
factor).
These
assumptions
along
with
other
inputs
for
the
SWAT
runs
are
consistent
with
those
specified
in
Appendix
A.

The
compliance
percentages
forecasted
by
SWAT
are
indicated
in
Exhibit
8.5.
EPA
estimates
that
over
97
percent
of
large
systems
will
be
able
to
achieve
the
Stage
2B
MCLs,
regardless
of
postdisinfection
choice,
if
they
apply
the
proposed
BAT
(
i.
e.,
EC
and
GAC10).
As
shown
in
the
current
Occurrence
Document
(
USEPA
2003l),
the
source
water
quality
(
e.
g.,
DBP
precursor
levels)
in
medium
and
small
systems
is
comparable
to
or
better
than
that
for
the
large
systems.
Based
on
the
large
system
estimate,
EPA
believes
it
is
conservative
to
assume
that
at
least
90
percent
of
medium
and
small
systems
will
be
able
to
achieve
the
Stage
2B
MCLs
if
they
were
to
apply
the
proposed
BAT.
EPA
realizes
that
it
may
not
be
economically
feasible
for
small
systems
to
install
and
operate
an
on­
site
GAC
reactivation
facility.
Thus,
it
is
assumed
that
small
systems
will
adapt
GAC20
(
with
240
days
of
empty­
bed
contact
time)
in
a
replacement
mode
for
their
BAT
considerations.
Some
small
systems
may
find
that
another
defined
BAT,
like
nanofiltration,
will
be
cheaper
than
the
GAC20
in
a
replacement
mode
because
their
specific
geographic
locations
may
lead
to
a
relatively
high
cost
of
routine
GAC
shipment.

Exhibit
8.5
SWAT
Model
Predictions
of
Percent
of
Large
Plants
in
Compliance
with
TTHM
and
HAA5
Stage
2B
MCLs
after
Application
of
Specified
Treatment
Technologies
Technology
Compliance
with
80/
60
LRAA
Compliance
with
64/
48
LRAA
(
20%
Safety
Factor)

Residual
Disinfectant
All
Systems
Residual
Disinfectant
All
Systems
Chlorine
Chloramine
Chlorine
Chloramine
EC
73.5%
76.9%
74.8%
57.2%
65.4%
60.4%

EC
(
no
pre­
disinfection)
73.4%
88.0%
78.4%
44.1%
62.7%
50.5%

EC
&
GAC10
100%
97.1%
99.1%
100%
95.7%
98.6%

EC
&
GAC20
100%
100%
100%
100%
100%
100%

EC
&
All
Chloramines
NA
83.9%
NA
NA
73.6%
NA
Source:
McGuire
(
2001).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
18
8.4.3
BATs
for
Consecutive
Systems
EPA
is
also
proposing
a
BAT
for
consecutive
systems
to
meet
the
TTHM
and
HAA5
MCLs
of
80
and
60
µ
g/
L,
respectively.
Presumably,
consecutive
systems
that
may
need
to
employ
the
BAT
are
receiving
water
from
their
wholesaler(
s)
that
just
barely
or
does
not
meet
the
MCLs.
Removal
of
TTHM
and
HAA5
is
difficult
after
they
have
formed.
EPA
believes
that
the
best
compliance
strategy
for
consecutive
systems
is
to
specify
water
quality
in
their
contractual
agreements
with
their
wholesaler(
s).
However,
this
is
a
private
agreement
over
which
EPA
does
not
have
jurisdiction.
There
are
expected
to
be
wholesalers
treating
water
with
whom
consecutive
systems
cannot
work
out
agreements
to
enable
the
consecutive
systems
to
meet
the
MCLs.
EPA
is
proposing
chloramination
as
BAT
for
these
consecutive
systems,
with
management
of
hydraulic
flow
and
storage
to
minimize
residence
time
in
the
distribution
system.
The
associated
BAT
provision
to
manage
hydraulic
flow
and
minimize
residence
time
in
the
distribution
system
is
to
facilitate
the
maintenance
of
the
chloramine
residual
and
minimize
the
likelihood
of
nitrification.
If
consecutive
systems
receive
chlorinated
water
that
is
close
to,
but
lower
than
the
MCLs,
they
should
in
most
cases
be
able
to
use
chloramination
to
stop
the
formation
of
TTHM
and
HAA5
in
their
distribution
system
and
thereby
meet
the
MCL.
If
consecutive
systems
are
already
receiving
chloraminated
water
from
the
wholesaler
that
is
meeting
the
MCLs,
the
consecutive
system
should
also
be
able
to
meet
the
MCL.
In
either
of
these
situations,
distribution
system
flow
maintenance
is
important
for
maintaining
the
chloramine
residual.

EPA
believes
that
the
various
BATs
proposed
for
wholesale
systems
are
not
appropriate
for
consecutive
systems,
because
each
of
these
BATs,
when
applied
to
water
with
high
levels
of
DBPs,
raises
other
concerns.
EPA
believes
GAC
is
not
a
good
BAT
for
consecutive
systems
because
GAC
is
not
cost­
effective
for
removing
DBPs.
Dioxin
is
a
potent
carcinogen
and
a
byproduct
of
GAC
regeneration
when
GAC
has
been
used
to
adsorb
chlorinated
DBPs.
While
nanofiltraton
is
effective
for
removing
TOC,
it
is
generally
not
effective
for
removing
TTHM
and
HAA5.
Nanofiltration
can
be
moderately
effective
at
removing
TTHM
and
HAA5,
but
only
with
membranes
that
have
a
very
low
molecular
weight
cutoff
and
very
high
cost
of
operation.
Therefore,
EPA
believes
that
nanofiltraton
is
not
a
good
BAT
for
consecutive
systems.

8.5
Effect
of
Compliance
with
the
Stage
2
DBPR
on
the
Technical,
Managerial,
and
Financial
Capacity
of
Public
Water
Systems
Section
1420(
d)(
3)
of
SDWA,
as
amended,
requires
that,
in
promulgating
a
National
Primary
Drinking
Water
Regulation
(
NPDWR),
the
Administrator
shall
include
an
analysis
of
the
likely
effect
of
compliance
with
the
regulation
on
the
technical,
managerial,
and
financial
(
TMF)
capacity
of
PWSs.
The
following
analysis
fulfills
this
statutory
obligation
by
identifying
the
incremental
impact
that
the
Stage
2
DBPR
will
have
on
the
TMF
of
regulated
water
systems.
Analyses
presented
in
this
document
reflect
only
the
impact
of
new
or
revised
requirements,
as
established
by
the
Stage
2
DBPR;
the
impacts
of
previously
established
requirements
on
system
capacity
are
not
considered.

Overall
water
system
capacity
is
defined
in
Guidance
on
Implementing
the
Capacity
Development
Provisions
of
the
Safe
Drinking
Water
Act
Amendments
of
1996
(
USEPA
1998e)
as
the
ability
to
plan
for,
achieve,
and
maintain
compliance
with
applicable
drinking
water
standards.
Capacity
encompasses
three
components:
technical,
managerial,
and
financial.
Technical
capacity
is
the
operational
ability
of
a
water
system
to
meet
SDWA
requirements.
Key
issues
of
technical
capacity
include:
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
19
°
Source
water
adequacy
 
Does
the
system
have
a
reliable
source
of
water
with
adequate
quantity?
Is
the
source
generally
of
good
quality
and
adequately
protected?

°
Infrastructure
adequacy
 
Can
the
system
provide
water
that
meets
SDWA
standards?
What
is
the
condition
of
its
infrastructure,
including
wells
or
source
water
intakes,
treatment
and
storage
facilities,
and
distribution
systems?
What
is
the
infrastructure's
life
expectancy?
Does
the
system
have
a
capital
improvement
plan?

°
Technical
knowledge
and
implementation
 
Are
the
system's
operators
certified?
Do
the
operators
have
sufficient
knowledge
of
applicable
standards?
Can
the
operators
effectively
implement
this
technical
knowledge?
Do
the
operators
understand
the
system's
technical
and
operational
characteristics?
Does
the
system
have
an
effective
O&
M
program?

Managerial
capacity
is
the
ability
of
a
water
system's
managers
to
make
financial,
operating,
and
staffing
decisions
that
enable
the
system
to
achieve
and
maintain
compliance
with
SDWA
requirements.
Key
issues
include:

°
Ownership
accountability
 
Are
the
owners
clearly
identified?
Can
they
be
held
accountable
for
the
system?

°
Staffing
and
organization
 
Are
the
operators
and
managers
clearly
identified?
Is
the
system
properly
organized
and
staffed?
Do
personnel
understand
the
management
aspects
of
regulatory
requirements
and
system
operations?
Do
they
have
adequate
expertise
to
manage
water
system
operations
(
i.
e.,
to
conduct
implementation,
IDSE,
additional
routine
monitoring,
and
significant
excursion
evaluation
activities
to
meet
the
Stage
2
DBPR
requirements)?
Do
personnel
have
the
necessary
licenses
and
certifications?

°
Effective
external
linkages
 
Does
the
system
interact
well
with
customers,
regulators,
and
other
entities?
Is
the
system
aware
of
available
external
resources,
such
as
technical
and
financial
assistance?

Financial
capacity
is
a
water
system's
ability
to
acquire
and
manage
sufficient
financial
resources
to
allow
the
system
to
achieve
and
maintain
compliance
with
SDWA
requirements.
Key
issues
include:

°
Revenue
sufficiency
 
Do
revenues
cover
costs?

°
Creditworthiness
 
Is
the
system
financially
healthy?
Does
it
have
access
to
capital
through
public
or
private
sources?

°
Fiscal
management
and
controls
 
Are
adequate
books
and
records
maintained?
Are
appropriate
budgeting,
accounting,
and
financial
planning
methods
used?
Does
the
system
manage
its
revenues
effectively?
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
20
8.5.1
Requirements
of
the
Preferred
Regulatory
Alternative
The
Stage
2
DBPR
establishes
four
new
requirements
that
may
affect
the
TMF
capacity
of
affected
PWSs:

1)
Compliance
with
MCLs
established
for
TTHM
and
HAA5
measured
as
an
LRAA.
This
requirement
will
be
implemented
in
two
distinct
stages.

°
Stage
2A:
MCLs
of
120
µ
g/
L
and
100
µ
g/
L
for
TTHM
and
HAA5,
respectively,
measured
as
LRAAs
at
the
monitoring
sites
established
under
the
Stage
1
DBPR
(
USEPA
1998k).

°
Stage
2B:
MCLs
of
80
µ
g/
L
and
60
µ
g/
L
for
TTHM
and
HAA5,
respectively,
measured
as
LRAAs
at
the
monitoring
sites
identified
as
a
result
of
the
IDSEs
required
under
the
Stage
2
DBPR.

2)
Conducting
an
IDSE
to
identify
the
locations
within
a
distribution
system
with
the
highest
TTHM
and
HAA5
levels.

3)
Additional
routine
monitoring
for
DBPs.

4)
If
a
significant
DBP
excursion
occurs,
systems
must
conduct
a
significant
excursion
evaluation
and
discuss
the
evaluation
with
the
State/
Primacy
Agency
no
later
than
their
next
sanitary
survey.

In
addition,
personnel
from
systems
regulated
under
the
Stage
2
DBPR
will
need
to
familiarize
themselves
with
the
rule
and
its
requirements.
This
capacity
analysis
is
presented
only
for
the
Preferred
Alternative.

8.5.2
Systems
Subject
to
the
Stage
2
DBPR
The
Stage
2
DBPR
will
apply
to
all
CWSs
and
NTNCWSs
that
add
a
primary
or
residual
disinfectant
other
than
UV,
or
that
deliver
water
that
has
been
treated
with
a
disinfectant
other
than
UV.
The
Stage
2
DBPR
may
affect
43,508
CWSs
and
8,124
NTNCWSs
 
51,632
systems
in
all.
While
most
will
not,
some
systems
may
require
increased
TMF
capacity
to
comply
with
the
new
requirements,
or
will
need
to
tailor
their
choices
to
match
their
capacities.

8.5.3
Impact
of
the
Stage
2
DBPR
on
System
Capacity
The
estimates
presented
in
Exhibits
8.6
and
8.7
reflect
the
anticipated
impact
of
the
Stage
2
DBPR
on
small
system
capacity
based
on
the
measures
that
systems
are
expected
to
adopt
to
meet
the
requirements
of
the
rule
(
e.
g.,
selecting
monitoring
sites
for
the
IDSE,
installing/
upgrading
treatment,
operator
training,
communication
with
regulators
and
the
service
community,
etc.).
The
extent
of
the
impact
of
a
particular
requirement
on
system
capacity
is
estimated
using
a
scale
of
0­
5,
where
0
represents
a
requirement
that
is
not
anticipated
to
have
any
impact
on
system
capacity,
1
represents
a
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
21
requirement
that
is
expected
to
have
a
minimal
impact
on
system
capacity,
and
5
represents
a
requirement
that
is
anticipated
to
have
a
very
significant
impact
on
system
capacity.

Criteria
used
to
develop
the
scores
and
associated
impacts
are
discussed
further
in
section
8.5.5.

8.5.4
Final
Analysis
of
Impact
of
the
Stage
2
DBPR
on
Small
System
Capacity
The
final
analysis
of
the
impact
of
a
rule
on
system
capacity
presented
in
Exhibit
8.8.
Section
8.5.5
provides
details
on
score
derivations
and
criteria
used
to
develop
the
scores
and
associated
impacts.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
22
Exhibit
8.6
Estimated
Impact
of
the
Stage
2
DBPR
on
Small
System
Capacity
(
0
=
no
impact,
1
=
minimal
impact,
and
5
=
very
significant
impact)

Requirement
Number
of
Systems/
Plants
(
Percent)
Technical
Capacity
Managerial
Capacity
Financial
Capacity
Source
Water
Adequacy
Infrastructure
Adequacy
Technical
Knowledge
&

Implementation
Ownership
Accountability
Staffing
&
Organization
Effective
External
Linkages
Revenue
Sufficiency
Credit
Worthiness
Fiscal
Mgmt.
&

Controls
Familiarization
with
requirements
of
the
rule
47,901
systems
(
100%)
0
0
1
0
1
0
0
0
0
Conducting
IDSE
monitoring
7,909
systems
(
17%)
0
0
2
1
0
2
3
0
1
Plants
with
major
treatment
changes
1,535
plants
(
3%)
2
4
4
2
2
3
5
5
3
Additional
routine
monitoring
7,486
systems
(
16%)
0
0
1
0
0
0
3
0
0
Significant
excursions
120
systems
(
0.3%)
0
0
1
1
1
1
0
0
0
Notes:
(
1)
To
analyze
the
impact
of
these
requirements
on
system
capacity,
the
requirements
believed
to
have
the
most
and
the
least
impact
on
affected
systems
(
i.
e.,
the
installation
of
treatment
to
ensure
compliance
with
the
LRAA
MCLs
for
TTHM
and
HAA5,
and
familiarization
with
the
requirements
of
the
rule,
respectively),
were
analyzed
first.
These
initial
analyses
were
then
used
as
the
bases
against
which
the
relative
impact
of
the
remaining
requirements
were
assessed.
The
impact
estimates
developed
for
each
requirement
were
also
compared
to
those
developed
for
the
Arsenic
Rule
and
the
Long
Term
2
Enhanced
Surface
Water
Treatment
Rule
(
LT2ESWTR)
to
ensure
cross­
rule
consistency
and
to
enable
cross­
rule
comparisons.
(
2)
The
scores
presented
above
represent
the
worst­
case
scenario;
the
requirements
of
this
rule
are
expected
to
have
less
impact
on
the
capacity
of
most
systems
affected
by
each
requirement.

Source:
Number
and
percent
of
small
systems
subject
to
each
rule
activity
from
Exhibit
6.3
(
sum
of
surface
water/
GWUDI),
and
ground
water
CWSs
and
NTNCWSs
serving
10,000
people
or
fewer).
Number
of
small
plants
making
treatment
changes
from
Exhibit
6.4
(
sum
of
surface
water/
GWUDI,
and
ground
water
CWSs
and
NTNCWSs
serving
10,000
people
or
fewer).
Impact
on
capacity
is
determined
relative
to
previous
regulations
based
on
the
cost
and
number
of
systems/
plants
that
require
additional
capacity
to
comply
with
each
requirement,
as
described
in
section
8.5.5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
23
Exhibit
8.7
Estimated
Impact
of
the
Stage
2
DBPR
on
Large
System
Capacity
(
0
=
no
impact,
1
=
minimal
impact,
and
5
=
very
significant
impact)

Requirement
Number
of
Systems/
Plants
(
Percent)
Technical
Capacity
Managerial
Capacity
Financial
Capacity
Source
Water
Adequacy
Infrastructure
Adequacy
Technical
Knowledge
&

Implementation
Ownership
Accountability
Staffing
&
Organization
Effective
External
Linkages
Revenue
Sufficiency
Credit
Worthiness
Fiscal
Mgmt.
&

Controls
Familiarization
with
requirements
of
the
rule
3,731
systems
(
100%)
0
0
1
0
1
0
0
0
0
Conducting
IDSE
monitoring
2,201
systems
(
59%)

289
plants
(
8%)
2
3
3
2
2
2
4
4
3
Additional
routine
monitoring
576
systems
(
15%)
0
0
0
0
0
0
1
0
0
Significant
excursions
218
systems
(
6%)
0
0
0
1
0
1
0
0
0
Notes:
(
1)
To
analyze
the
impact
of
these
requirements
on
system
capacity,
the
requirements
believed
to
have
the
most
and
the
least
impact
on
affected
systems
(
i.
e.,
the
installation
of
treatment
to
ensure
compliance
with
the
LRAA
MCLs
for
TTHM
and
HAA5,
and
familiarization
with
the
requirements
of
the
rule,
respectively),
were
analyzed
first.
These
initial
analyses
were
then
used
as
the
bases
against
which
the
relative
impact
of
the
remaining
requirements
were
assessed.
The
impact
estimates
developed
for
each
requirement
were
also
compared
to
those
developed
for
the
Arsenic
Rule
and
the
LT2ESWTR
to
ensure
cross­
rule
consistency
and
to
enable
cross­
rule
comparisons.
(
2)
The
scores
presented
above
represent
the
worst
case
scenario;
the
requirements
of
this
rule
are
expected
to
have
less
impact
on
the
capacity
of
most
systems
affected
by
each
requirement.

Source:
Number
and
percent
of
large
systems
subject
to
each
rule
activity
from
Exhibit
6.3
(
sum
of
surface
water/
GWUDI,
and
ground
water
CWSs
and
NTNCWSs
serving
more
than
10,000
people).
Number
of
large
plants
making
treatment
changes
from
Exhibit
6.4
(
sum
of
surface
water/
GWUDI,
and
ground
water
CWSs
and
NTNCWSs
serving
more
than
10,000
people).
Impact
on
capacity
is
determined
relative
to
previous
regulations
based
on
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
24
the
cost
and
number
of
systems/
plants
that
require
additional
capacity
to
comply
with
each
requirement,
as
described
in
section
8.5.5.

Exhibit
8.8
Impact
of
the
Stage
2
DBPR
on
CWS
and
NTNCWS
Capacity1
Type
of
Water
System
Minimal
Impact
Small
Impact
Significant
Impact
Small
Systems
CWSs
70%
27%
3%

NTNCWSs
96%
<
1%
3%

Total
75%
22%
3%

Large
Systems
CWSs
96%
0%
3%

NTNCWSs
94%
0%
4%

Total
96%
0%
3%

1
Minimal
and
small
impact
numbers
were
generated
based
on
plants;
significant
impact
numbers
were
generated
based
on
systems.
Note:
Totals
may
not
add
to
100
percent
due
to
individual
rounding.

Source:
The
groups,
minimal,
small,
and
significant
impact,
are
based
on
the
scores
presented
in
Exhibits
8.6
and
8.7,
as
described
in
section
8.5.5.

8.5.5
Derivation
of
Stage
2
DBPR
Scores
EPA
developed
a
5­
point
scoring
system
to
analyze
the
likely
effect
of
compliance
with
an
NPDWR
on
the
technical,
managerial,
and
financial
capacity
of
PWSs.
For
each
regulation,
it
is
necessary
to
complete
the
following
steps:

1)
Determine
the
type
and
number
of
PWSs
to
which
the
regulation
applies.

2)
List
all
of
the
requirements
of
the
regulation.

3)
Determine
the
type
and
number
of
PWSs
to
which
each
requirement
applies.

4)
Evaluate
the
impact
of
each
requirement
on
the
capacity
of
affected
PWSs.

The
determination
of
the
universe
of
affected
systems
and
the
evaluation
of
the
capacity
impact
of
individual
requirements
requires
the
use
of
the
cost
and
technical
information
contained
in
SDWIS,
EAs
developed
for
other
rules,
information
collection
requests,
and
other
supporting
documentation
for
the
rule.
These
data
sources
are
also
used
to
develop
a
qualitative
description
of
the
expected
response
of
affected
systems
to
each
requirement.

The
overall
evaluation
of
the
impact
of
a
requirement
on
the
affected
systems,
presented
in
Exhibits
8.6
and
8.7,
is
based
on
the
impact
of
each
requirement
on
nine
sub­
categories
of
capacity
 
three
sub­
categories
under
each
of
the
broader
divisions
of
technical,
managerial,
and
financial
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
25
capacity.
Within
these
sub­
categories,
scores
are
assigned
based
on
the
additional
capacity
affected
systems
will
need
to
develop
to
comply
with
a
requirement.

To
ensure
the
ability
to
make
cross­
rule
comparisons,
to
standardize
the
assignment
of
numerical
scores,
and
to
minimize
the
subjectivity
of
the
scoring
system,
the
requirements
made
on
systems
by
the
regulation
in
question
are
compared
to
the
requirements
of
those
regulations
for
which
capacity
impact
analyses
have
already
been
conducted
(
e.
g.,
the
Arsenic
Rule,
Radon
Rule,
Filter
Backwash
Recycling
Rule,
LT1ESWTR,
etc.).
Similar
requirements
will
be
assigned
similar
impact
scores.
Once
initial
scores
have
been
assigned,
they
are
reviewed
by
small­
system
engineers
and
the
EPA
Small
System
Coordinator
to
ensure
that
the
scores
are
representative
of
the
extent
of
the
impact
of
each
requirement
on
the
universe
of
affected
systems.

A
system
regulated
under
a
single
very
challenging
requirement
(
rated
a
5
in
Exhibits
8.6
and
8.7),
and
a
system
that
must
meet
two
or
more
somewhat
less
challenging
requirements
(
for
example,
one
rated
a
4
and
another
a
3
in
Exhibits
8.6
and
8.7)
may
need
to
raise
their
rates
to
consumers,
introduce
new
fees,
train
new
workers,
or
buy,
install,
and
operate
new
capital
equipment
to
meet
rule
requirements.
Systems
that
must
only
read
the
rule
to
determine
if
they
will
need
to
comply,
or
systems
that
must
meet
requirements
with
impact
scores
of
1
or
in
some
cases
2,
will
not
have
to
make
major
changes
to
the
way
in
which
they
conduct
business
to
comply
with
the
Stage
2
DBPR.

In
the
final
analysis
of
the
impact
of
a
rule
on
system
capacity
presented
in
Exhibit
8.8,
systems
are
placed
into
groups
that
face
"
minimal,"
"
small,"
and
"
significant"
challenges
to
their
capacity
based
on
the
cumulative
impact
scores
assigned
to
the
requirements
with
which
they
must
comply.
Therefore,
both
a
system
regulated
under
a
single
very
challenging
requirement
(
rated
a
5),
and
a
system
that
must
meet
two
or
more
somewhat
less
challenging
requirements
(
for
example,
one
rated
a
4
and
another
a
3)
would
both
be
considered
to
face
a
"
significant"
challenge
to
their
capacity.
These
systems
may
need
to
raise
their
rates
to
consumers,
introduce
new
fees,
train
new
workers,
or
buy,
install,
and
operate
new
capital
equipment
to
meet
rule
requirements.
In
general,
systems
that
must
meet
multiple
requirements
with
impact
scores
of
3,
or
meet
two
or
more
less
burdensome
requirements
(
for
example
one
rated
a
3
and
one
rated
a
2)
are
considered
to
face
a
"
small"
challenge
to
their
capacity.
Finally,
systems
that
must
only
read
the
rule
to
determine
if
they
will
need
to
comply,
or
systems
that
must
meet
requirements
with
impact
scores
of
1
or
in
some
cases
2,
are
considered
to
face
only
a
"
minimal"
challenge
to
their
capacity.
These
systems
will
not
have
to
make
major
changes
to
the
way
they
conduct
business
to
comply
with
the
Stage
2
DBPR.

These
group
assignments
are
reviewed
by
the
EPA
Small
System
Coordinator,
the
EPA
Rule
Manager,
and
other
EPA
staff
cognizant
of
small
system
issues,
to
ensure
that
they
accurately
reflect
the
cumulative
impact
of
the
rule
requirements
on
system
capacity.
Any
disagreements
over
the
assignments
are
discussed.
The
EPA
Rule
Manager,
the
EPA
Small
System
Coordinator,
and
other
EPA
staff
discuss
the
rationale
for
the
disagreement
and
evaluate
whether
the
assignments
need
to
be
adjusted.
EPA
only
adjusts
the
assignments
after
review
of
the
rule
support
documents
and
an
analysis
of
the
expected
system
response
to
the
rule
requirements.

8.5.5.1
Familiarization
with
the
Stage
2
DBPR
The
requirements
established
under
the
Stage
2
DBPR
are
straightforward
(
use
of
LRAA
instead
of
RAA
to
determine
compliance
with
the
MCLs
for
DBPs)
and
grounded
in
requirements
previously
established
under
the
Stage
1
DBPR.
As
a
result,
it
is
not
expected
that
small
or
large
systems
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
26
regulated
under
this
rule
will
face
more
than
a
minimal
challenge
to
their
technical
or
managerial
capacity
as
a
result
of
efforts
to
familiarize
themselves
with
the
Stage
2
DBPR.
Furthermore,
familiarization
with
the
rule
will
not
impact
the
financial
capacity
of
either
large
or
small
systems.

8.5.5.2
Conducting
an
Initial
Distribution
System
Evaluation
The
IDSE
was
incorporated
into
the
Stage
2
DBPR
to
ensure
that
the
locations
at
which
systems
monitor
for
DBPs
are
sites
at
which
TTHM
and
HAA5
values
are
highest.
IDSEs
are
required
for
most
PWSs
under
the
Stage
2
DBPR,
but
will
not
affect
the
capacity
of
all
systems
subject
to
the
requirement
to
the
same
extent.
Some
systems
will
be
able
to
meet
this
requirement
without
conducting
extensive
additional
monitoring
through
an
IDSE
waiver.
An
IDSE
waiver
may
be
granted
to
CWSs
serving
fewer
than
500
people
with
Stage
1
DBPR
sites
that
represent
both
the
highest
TTHM
and
HAA5
concentrations.
Systems
with
all
Stage
1
DBPR
TTHM
and
HAA5
data
less
than
or
equal
to
40/
30
µ
g/
L,
respectively,
may
qualify
for
the
40/
30
certification
and
not
perform
the
IDSE.
NTNCWSs
that
serve
10,000
or
fewer
people
are
not
subject
to
the
IDSE
requirement.
It
is
expected
that
large
surface
water
systems
will
typically
be
required
to
conduct
the
greatest
amount
of
monitoring
for
the
IDSE,
while
small
ground
water
systems
will
be
required
to
conduct
the
least.

Prior
to
the
implementation
of
an
IDSE,
systems
required
to
monitor
for
DBPs
will
need
to
select
monitoring
locations.
Identifying
appropriate
sampling
locations
is
expected
to
require
a
modest
improvement
in
the
technical
and
managerial
capacity
of
many
systems.
This
requirement
will
have
a
much
smaller
impact
on
the
capacity
of
systems
that
do
not
have
to
monitor.
While
these
systems
may
need
to
reinforce
their
connections
with
regulatory
agencies
to
obtain
waivers
for
the
IDSE
requirement
and
to
meet
reporting
requirements,
they
will
not
be
required
to
conduct
as
many
new
technical
analyses
of
their
distribution
system
and
its
impact
on
finished
water
quality.
Regardless
of
whether
a
system
must
conduct
additional
monitoring
for
the
IDSE,
this
requirement
will
have
an
impact
on
ownership
accountability,
since
all
new
or
historic
monitoring
data
must
be
logged
and
submitted
to
the
appropriate
regulatory
agency.

It
is
expected
that
large
surface
water
systems
will
typically
be
required
to
conduct
the
greatest
amount
of
monitoring
for
the
IDSE,
while
small
ground
water
systems
will
be
required
to
conduct
the
least.
Lab
analysis
of
samples
for
TTHM
and
HAA5
are
expensive
(
estimated
at
$
220
per
sample,
see
Chapter
6
for
discussion
of
laboratory
costs).
While
these
costs
are
not
typically
prohibitive
for
large
systems,
they
may
represent
a
significant
challenge
to
the
financial
capacity
of
small
systems.
Some
of
these
systems
will
need
to
revisit
their
current
budgeting
practices
and
fee
structures
to
meet
these
additional
costs.

8.5.5.3
Compliance
with
MCLs
for
TTHM
and
HAA5
The
impact
on
the
managerial
capacity
of
systems
affected
by
the
revised
DBP
MCLs
is
not
anticipated
to
be
as
great
as
the
technical
and
financial
challenges.
However,
system
managers
will
need
to
review
the
implications
of
the
revised
method
for
measuring
compliance
with
the
MCLs
for
TTHM
and
HAA5,
and
may
need
to
hire
more
highly
certified
operators
or
provide
additional
training
for
existing
operators
to
ensure
that
system
staff
can
safely
and
effectively
operate
all
new
elements
of
the
system's
treatment
train
at
all
times.
In
addition,
systems
will
need
to
rely
on,
and
improve
upon,
their
communication
with
regulators,
technical
and
financial
assistance
providers,
and
their
service
community.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
27
Systems
whose
finished
water
does
meet
the
MCLs
for
TTHM
or
HAA5
based
on
LRAAs
will
need
to
adjust,
change,
or
enhance
their
treatment
practices.
The
installation,
operation,
and
maintenance
of
new
treatment
technologies
will
require
a
substantial
enhancement
of
these
systems'
technical
capacity,
particularly
for
small
systems.
Specifically,
source
water
adequacy
may
be
reduced
if
marginal
sources
are
no
longer
viable.
The
system
may
also
need
to
improve
its
infrastructure,
and
system
operators
will
require
correspondingly
greater
technical
expertise
to
operate
new
treatment
processes.

Note,
however,
that
based
on
the
recommendations
of
the
Small
Surface
Water
System
Delphi
Group
convened
by
the
Agency,
EPA
assumed
for
the
purposes
of
the
capacity
impact
analysis
that
small
surface
water
systems
would
not
install
technologies
that
were
beyond
their
technical
or
managerial
capacity
in
order
to
meet
the
requirements
of
this
rule.
For
example,
very
small
systems
(
those
serving
fewer
than
500
people)
would
not
install
chlorine
dioxide
treatment
because
it
requires
a
system
operator
to
be
in
the
plant
every
day.
Instead,
EPA
assumed
these
smallest
systems
would
install
UV
or
membrane
technologies,
which
do
not
require
a
system
operator
to
be
present
each
day.
While
the
operation
and
maintenance
of
membrane
treatment
elements
may
challenge
the
technical
capacity
of
small
system
operators,
UV
treatment
is
easy
to
implement,
does
not
require
the
same
level
of
technical
know­
how,
and
is
relatively
low
cost.
As
a
result,
only
some
of
those
small
systems
that
must
install
treatment
to
meet
the
MCLs
for
TTHM
and
HAA5
are
expected
to
experience
the
full
impact
detailed
in
Exhibit
8.6;
the
scores
presented
in
the
table
represent
the
"
worst­
case"
scenario
for
small
systems.

While
some
small
systems
that
must
install
new
treatment
to
meet
the
revised
MCL
requirement
will
face
a
substantial
challenge
to
their
capacity,
it
is
expected
that
this
requirement
will
not
have
as
dramatic
of
an
impact
on
large
systems
for
a
number
of
reasons.

Management
for
both
large
and
small
systems
will
need
to
work
closely
with
regulatory
agencies
to
receive
approval
on
proposed
design/
treatment
modifications.
System
operators
who
must
work
with
new
technologies
will
require
additional
training,
while
system
owners
may
need
to
seek
out
additional
or
new
sources
of
funding
to
reduce
the
financial
burden
of
the
installation
of
new
treatment
equipment
on
their
customers.
Systems
that
met
the
DBP
requirements
under
the
Stage
1
DBPR,
but
that
will
need
to
make
substantive
changes
to
comply
with
the
Stage
2
DBPR
requirements,
will
need
to
provide
their
service
community
with
a
clear
explanation
of
the
trade­
offs
between
microbial
safety
and
DBPs,
the
steps
that
the
system
is
taking
to
meet
these
competing
requirements
while
continuing
to
ensure
public
safety,
and
their
rationale
for
implementing
new
or
higher
fees
to
pay
for
system
improvements.

Since
larger
systems
tend
to
have
more
developed
relationships
with
regulatory
personnel,
as
well
as
more
established
means
of
communicating
with
their
customers,
the
impact
on
the
managerial
capacity
of
small
systems
is
expected
to
be
greater
than
the
impact
on
the
managerial
capacity
of
large
systems.
Further,
large
system
operators
tend
to
have
a
higher
level
of
expertise
than
their
small
system
counterparts.
As
a
result,
large
system
operators
will
not
require
as
much
training
to
adequately
operate
and
maintain
any
new
treatment
that
must
be
installed.
This
requirement
will
not
pose
as
great
of
a
technical
or
managerial
challenge
to
large
systems.

The
impact
of
the
Stage
2
DBPR
on
the
financial
capacity
of
regulated
systems
is
closely
tied
to
the
rule's
impact
on
the
technical
capacity
of
these
systems.
Systems
that
must
install
additional
treatment
processes
or
upgrade
their
current
treatment
processes
will
face
high
costs.
These
costs
may
pose
particular
difficulties
for
many
of
the
affected
systems
since
the
majority
are
relatively
small
(
i.
e.,
serving
fewer
than
3,300
customers),
and
therefore
typically
have
a
smaller
revenue
base
and
fewer
households
over
which
they
can
distribute
additional
costs.
In
addition,
large
systems
may
take
better
advantage
of
economies
of
scale
than
smaller
systems
because
they
buy
larger
quantities
of
chemicals
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
28
and
equipment.
However,
it
is
anticipated
that
some
systems
may
elect
to
develop
an
alternative
source
(
e.
g.,
one
with
lower
levels
of
naturally­
occurring
organic
material)
or
interconnect
with
a
nearby
system
if
treatment
costs
prove
prohibitive.

To
obtain
funding
from
either
public
or
private
sources,
systems
will
need
to
demonstrate
sound
financial
accounting
and
budgeting
practices,
and
the
ability
to
repay
their
debts.
As
a
result,
many
of
the
smallest
systems
that
do
not
currently
charge
explicitly
for
water
service
(
e.
g.,
mobile
home
parks,
camp
grounds,
etc.)
may
need
to
begin
billing
their
customers.
Those
systems
that
already
charge
for
water
service
will
likely
need
to
increase
their
rates
(
frequently
requiring
approval
of
the
local
public
utilities
commission
or
public
services
commission,
board
approval,
or
vote
within
the
service
boundary),
and
improve
their
recordkeeping
procedures.
Again,
this
poses
less
of
a
challenge
to
large
systems
that
have
established
billing
practices
and
have
developed
close
relationships
with
public
utilities
commissions.

Therefore,
on
the
basis
of
the
TMF
challenges
posed
by
this
requirement,
it
is
anticipated
that
the
implementation
of
the
revised
monitoring
methodology
will
have
a
substantial
impact
on
the
capacity
of
the
1,535
small
plants
and
289
large
plants
that
are
expected
to
make
treatment
changes
to
reduce
DBP
concentrations
to
comply
with
this
rule
(
see
Exhibit
6.4).

8.5.5.4
Additional
Routine
Monitoring
It
is
anticipated
that
the
additional
routine
monitoring
required
for
some
systems
will
have
a
relatively
limited
impact
on
system
capacity.
These
systems
already
have
experience
sampling
for
DBPs
and
only
a
small
number
of
additional
samples
will
be
required
(
four
for
surface
water
systems
and
one
for
ground
water
systems
on
an
annual
basis).
Nonetheless,
it
is
important
to
consider
that
the
monitoring
costs
may
strain
the
financial
capacity
of
some
small
systems,
especially
since
the
sampling
costs
are
high
for
TTHM
and
HAA5.
Additional
routine
monitoring
is
expected
to
have
minimal
impact
on
the
capacity
of
large
systems
since
costs
will
be
spread
across
a
large
population
base.

8.5.5.5
Significant
Excursion
If
a
significant
excursion
occurs,
the
system
must
conduct
a
significant
excursion
evaluation
and
discuss
this
evaluation
with
the
State/
Primacy
Agency
during
its
next
sanitary
survey
(
or
sooner).
This
evaluation
involves
an
examination
of
the
system's
distribution
system
and
operational
practices
and
how
they
might
be
modified
to
reduce
TTHM
and
HAA5
levels.
Based
on
the
conclusions
of
their
evaluation,
some
systems
may
install
additional
treatment
or
modify
their
distribution
system
(
e.
g.,
replace
a
storage
tank).
However,
since
such
modifications
are
not
required,
they
are
not
considered
for
the
purposes
of
this
analysis.

A
significant
excursion
evaluation
will
require
system
operators
to
have
a
thorough
knowledge
of
the
components
of
their
treatment
train
and
distribution
system.
Further,
some
system
operators,
particularly
small
system
operators,
may
require
additional
training
or
input
from
State/
Primacy
Agency
or
local
extension
agents
to
effectively
conduct
a
significant
excursion
evaluation.
This
requirement
may
also
have
a
small
impact
on
the
managerial
capacity
of
some
systems,
since
owners
will
be
required
to
ensure
that
these
evaluations
are
conducted
and
that
the
results
are
discussed
during
the
sanitary
survey.
Note,
however,
that
this
requirement
does
not
require
systems
to
notify
the
public
or
provide
an
explanation
in
their
CCRs
 
minimizing
the
need
for
them
to
further
develop
their
public
outreach
efforts.
Finally,
given
the
performance
of
a
significant
excursion
evaluation
is
expected
to
take
only
1
to
2
hours
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
29
(
depending
on
system
size),
this
requirement
will
probably
not
have
any
impact
on
the
financial
capacity
of
large
or
small
systems.
Large
systems
with
more
complex
distribution
networks
are
expected
to
spend
more
time
per
excursion
than
smaller,
simpler
systems.
The
rate
of
excursions
is
also
expected
to
decrease
over
time
as
systems
begin
identifying
the
cause
and
working
with
their
States/
Primacy
Agencies
to
reduce
future
excursions.

8.5.6
Rationale
for
Scores
The
baseline
assumed
for
the
purposes
of
this
analysis,
which
identifies
the
incremental
impact
of
the
Stage
2
DBPR
on
the
TMF
capacity
of
systems,
is
complete
implementation
of
the
Stage
1
DBPR,
the
IESWTR,
and
the
LT1ESWTR.
As
a
result,
it
is
anticipated
that
many
of
the
systems
facing
the
most
difficult
DBP
challenges
will
have
made
appropriate
modifications
to
their
treatment
process
(
e.
g.,
changed
point
of
disinfection,
installed
membrane
technologies,
etc.)
to
achieve
compliance
with
these
rules,
and,
therefore,
will
not
need
to
install
additional
treatment
technology
to
achieve
compliance
with
the
Stage
2
DBPR.
However,
the
revised
methodology
for
measuring
system
compliance
with
the
MCLs
for
TTHM
and
HAA5
(
i.
e.,
LRAA)
will
require
systems
to
reduce
peak
levels
in
DBP
concentrations
within
their
distribution
systems.
Since
an
LRAA
represents
a
more
stringent
testing
standard
than
an
RAA,
it
is
likely
that
some
systems
that
previously
met
requirements
established
by
the
Stage
1
DBPR
will
be
required
to
make
changes
to
their
treatment
processes
to
comply
with
the
Stage
2
DBPR.
The
impact
of
the
requirement
established
by
the
more
stringent
phase
(
Stage
2B)
of
rule
implementation
was
analyzed
for
the
purpose
of
this
analysis.
The
derivation
of
the
scores
assigned
in
Exhibits
8.6
and
8.7
and
the
rationale
behind
them
is
described
in
section
8.5.5.

8.5.7
Summary
The
Stage
2
DBPR
may
have
a
substantial
impact
on
the
capacity
of
the
1,535
plants
in
small
systems
and
289
plants
in
large
systems
that
must
make
changes
to
their
treatment
process
to
meet
the
Stage
2
DBPR
requirements.
However,
while
the
impact
to
these
systems
is
potentially
significant,
only
2.8
percent
of
all
plants
regulated
under
the
Stage
2
DBPR
(
1,824
of
64,171)
will
be
affected
by
this
requirement.
Since
individual
systems
may
employ
more
than
one
plant,
it
is
likely
that
fewer
than
1,824
systems
(
2.8
percent
of
systems)
will
be
affected
by
this
requirement.
The
new
IDSE
and
monitoring
requirements
are
expected
to
have
a
small
impact
on
the
technical
and
managerial
capacity
of
small
systems,
a
moderate
impact
on
the
financial
capacity
of
some
small
systems,
and
a
much
lesser
impact
on
large
systems.
The
capacity
of
systems
that
must
conduct
a
significant
excursion
evaluation
will
only
be
impacted
in
a
minor
way,
while
those
systems
that
must
only
familiarize
themselves
with
the
rule
(
the
large
majority
of
systems)
will
not
face
any
capacity
impact
as
a
result
of
the
Stage
2
DBPR.
Exhibit
8.8
summarizes
the
varying
impact
on
the
capacity
of
CWSs
and
NTNCWSs
associated
with
implementing
the
Stage
2
DBPR.

8.6
Paperwork
Reduction
Act
The
information
collected
as
a
result
of
the
Stage
2
DBPR
will
allow
the
States/
Primacy
Agencies
and
EPA
to
determine
appropriate
requirements
for
specific
systems
and
to
evaluate
compliance
with
the
rule.
The
Paperwork
Reduction
Act
requires
EPA
to
estimate
the
burden
of
complying
with
the
rule
on
PWSs,
States,
and
territories.
Burden
means
the
total
time,
effort,
and
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
30
Average
Annual
Burden
(
Hours)
Average
Annual
Labor
Costs
($
Millions)
Average
Annual
O&
M
Costs
($
Millions)
Average
Annual
Capital
Costs
($
Millions)
Average
Annual
Costs
($
Millions)

NTNCWSs
7,060
$
0.2
$
0.1
$
0
$
0.2
CWSs
140,164
$
3.7
$
17.9
$
0
$
21.6
States
and
Territories
101,345
$
2.9
$
0.0
$
0
$
2.9
Total
248,568
$
6.8
$
18.0
$
0
$
24.7
financial
resources
required
to
generate,
maintain,
retain,
disclose,
or
provide
information
to
or
for
a
Federal
agency.
This
burden
includes
the
time
needed
to:

°
Review
instructions
°
Develop,
acquire,
install,
and
utilize
technology
and
systems
for
the
purposes
of
collecting,
validating,
and
verifying
information
°
Process
and
maintain
information,
and
disclose
and
provide
information
°
Adjust
the
existing
ways
to
comply
with
any
previously
applicable
instructions
and
requirements
°
Train
personnel
to
be
able
to
respond
to
a
collection
of
information
°
Search
data
sources
°
Complete
and
review
the
collection
of
information
°
Transmit
or
otherwise
disclose
the
information
For
the
first
3
years
following
promulgation
of
the
proposed
rule,
the
major
information
requirements
involve
monitoring
activities,
which
include
conducting
the
IDSE
and
submission
of
the
IDSE
report,
and
tracking
compliance.
The
information
collection
requirements
are
mandatory
under
Part
141,
the
NPDWRs,
and
the
information
collected
is
not
confidential.
This
information
will
allow
the
systems
to
determine
appropriate
treatment
requirements
and
will
allow
States/
Primacy
Agencies
and
EPA
to
evaluate
systems'
compliance
with
the
rule.
The
calculation
of
Stage
2
DBPR
burden
and
costs
can
be
found
in
Information
Collection
Request
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
USEPA
2003h).
Exhibit
8.9
provides
a
summary
of
the
results
of
the
Information
Collection
Request
calculations.

Exhibit
8.9
Summary
of
Average
Annual
Burden
Hours
and
Labor
Costs
Note:
Figures
represent
burden
and
cost
for
the
3­
year
Information
Collection
Request
approval
only.
Detail
may
not
add
due
to
independent
rounding.

Source:
Information
Collection
Request
for
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
USEPA
2003h).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
31
The
preliminary
estimate
of
annual
average
burden
hours
for
Stage
2
DBPR
for
States/
Primacy
Agencies
and
systems
is
248,568
hours.
The
annual
average
aggregate
cost
estimate
is
$
18.0
million
for
operation
and
maintenance
as
a
purchase
of
service
for
lab
work.
EPA
assumes
that
the
disinfecting
systems
affected
by
the
Stage
2
DBPR
have
already
purchased
the
basic
equipment
to
record
chlorine
concentrations,
disinfection
efficacy,
etc.
Therefore,
there
are
no
capital
start­
up
costs
associated
with
information
collection
under
this
rule.
The
burden
hour
per
response
is
2.59
hours,
and
the
frequency
for
response
(
average
responses
per
respondent)
is
11.8
annually.
Respondents
include
57
States/
Primacy
Agencies
and
24,221
PWSs.
The
estimated
number
of
likely
respondents
per
year
is
8,131.

8.7
Unfunded
Mandates
Reform
Act
Analysis
Title
II
of
the
UMRA
of
1995,
Public
Law
104­
4,
establishes
requirements
for
Federal
agencies
to
assess
the
effects
of
their
regulatory
actions
on
State,
Local,
and
Tribal
governments,
and
the
private
sector.
Under
UMRA
Section
202,
EPA
generally
must
prepare
a
written
statement,
including
a
costbenefit
analysis,
for
proposed
and
final
rules
with
"
Federal
mandates"
that
may
result
in
expenditures
by
State,
Local,
and
Tribal
governments,
in
the
aggregate,
or
by
the
private
sector,
of
$
100
million
or
more
in
any
1
year.
Before
promulgating
an
EPA
rule
for
which
a
written
statement
is
needed
under
Section
202,
Section
205
of
the
UMRA
generally
requires
EPA
to
identify
and
consider
a
reasonable
number
of
regulatory
alternatives
and
adopt
the
least
costly,
most
cost­
effective,
or
least
burdensome
alternative
that
achieves
the
objectives
of
the
rule.
The
provisions
of
Section
205
do
not
apply
when
they
are
inconsistent
with
applicable
law.
Moreover,
Section
205
allows
EPA
to
adopt
an
alternative
other
than
the
least
costly,
most
cost­
effective,
or
least
burdensome
alternative
if
the
Administrator
publishes
with
the
final
rule
an
explanation
why
that
alternative
was
not
adopted.

EPA
has
determined
that
this
rule
does
not
contain
a
Federal
mandate
that
may
result
in
expenditures
of
$
100
million
or
more
for
State,
Local
and
Tribal
governments,
in
the
aggregate,
or
the
private
sector
in
any
one
year.
Based
on
total
estimated
nominal
costs
incurred
by
year
that
are
presented
in
Chapter
9
of
this
EA,
costs
for
public
or
private
systems
are
not
expected
to
exceed
$
100
million
in
any
one
year.
In
addition,
total
estimated
annualized
costs
of
this
rule
are
$
59
to
$
65
million
for
all
systems,
including
labor
burdens
that
States
would
face,
such
as
training
employees
on
the
requirements
of
the
Stage
2
DBPR,
responding
to
PWS
reports,
and
record
keeping.
Thus,
the
Stage
2
DBPR
is
not
subject
to
the
requirements
of
sections
202
and
205
of
the
UMRA.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
32
3%
Discount
Rate
7%
Discount
Rate
Percent
of
3%
Grand
Total
Costs
Percent
of
7%
Grand
Total
Costs
Surface
Water
Systems
Costs
26.5
$
30.1
$
45%
47%
Ground
Water
Systems
Costs
19.9
$
20.8
$
34%
32%
State
Costs
1.1
$
1.5
$
2%
2%
Tribal
Costs
0.3
$
0.3
$
0%
0%

Total
Public
47.9
$
52.7
$
81%
82%
Surface
Water
Systems
Costs
3.8
$
4.2
$
6%
7%
Ground
Water
Systems
Costs
7.4
$
7.7
$
13%
12%

Total
Private
11.2
$
11.9
$
19%
18%

GRAND
TOTAL
59.1
$
64.6
$
100%
100%
Exhibit
8.10
Public
and
Private
Costs
for
the
Stage
2
DBPR
(
Annualized
at
3
and
7
Percent)

Note:
Detail
may
not
add
due
to
independent
rounding.

Source:
Derived
from
Exhibit
6.6
(
costs)
and
Exhibit
3.4
(
public/
private
breakout).

Consultation
with
Small
Governments
Before
the
Agency
establishes
any
regulatory
requirements
that
may
significantly
or
uniquely
affect
small
governments,
including
Tribal
governments,
it
must
develop,
under
Section
203
of
the
UMRA,
a
small
government
agency
plan.
The
plan
must
provide
for
the
notification
of
potentially
affected
small
governments,
enabling
officials
of
affected
small
governments
to
have
meaningful
and
timely
input
in
the
development
of
EPA
regulatory
proposals
with
significant
Federal
intergovernmental
mandates
and
informing,
educating,
and
advising
small
governments
on
compliance
with
the
regulatory
requirements.

EPA
has
determined
that
the
Stage
2
DBPR
contains
no
regulatory
requirements
that
might
significantly
or
uniquely
affect
a
substantial
number
of
small
governments
(
see
Exhibit
8.1).
Since
the
Stage
2
DBPR
affects
all
size
systems
and
the
impact
on
small
entities
will
be
0
to
0.08
percent
of
revenues,
the
Stage
2
DBPR
is
not
subject
to
the
requirements
of
Section
203
of
UMRA.
EPA
consulted
with
small
governments,
nevertheless,
to
address
impacts
of
regulatory
requirements
in
the
rule
that
might
uniquely
affect
small
governments.
As
described
in
section
8.2,
a
variety
of
stakeholders,
including
small
governments,
had
the
opportunity
for
timely
and
meaningful
participation
in
the
regulatory
development
process
through
the
SBREFA
process,
public
stakeholder
meetings,
and
Tribal
meetings.
Representatives
of
small
governments
took
part
in
the
SBREFA
process
for
this
rulemaking
and
they
attended
public
stakeholder
meetings.
Through
such
participation
and
exchange,
EPA
notified
several
potentially
affected
small
governments
of
requirements
under
consideration
and
provided
officials
of
affected
small
governments
with
an
opportunity
to
have
meaningful
and
timely
input
into
the
development
of
this
regulatory
proposal.

Consultation
with
State,
Local,
and
Tribal
Governments
Section
204
of
UMRA
requires
the
Agency
to
develop
an
effective
process
to
permit
elected
officers
of
State,
Local,
and
Tribal
governments
(
or
their
designated
authorized
employees)
to
provide
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
33
meaningful
and
timely
input
in
the
development
of
regulatory
proposals
that
contain
significant
Federal
intergovernmental
mandates.
Consistent
with
these
provisions,
EPA
held
consultations
with
the
governmental
entities
affected
by
this
rule
prior
to
proposal,
as
described
in
sections
8.2
and
8.8.

Representatives
from
State,
Local
and
Tribal
governments
were
also
involved
with
the
development
of
the
Agreement
in
Principle,
which
was
developed
early
in
the
regulatory
process.
EPA
provided
the
Association
of
State
Drinking
Water
Administrators
(
ASDWA)
with
an
opportunity
to
comment
before
officially
proposing
the
Stage
2
DBPR.
EPA
accepted
comments
from
ASDWA
and
other
FACA
members,
such
as
the
National
League
of
Cities
(
NLC),
on
a
draft
of
the
Stage
2
DBPR
posted
on
their
website.

In
addition
to
these
efforts,
EPA
will
educate,
inform,
and
advise
small
systems,
including
those
run
by
small
governments,
about
the
Stage
2
DBPR
requirements.
The
Agency
is
developing
plain­
English
guidance
that
will
explain
what
actions
a
small
entity
must
take
to
comply
with
the
rule.
Also,
the
Agency
has
developed
fact
sheets
that
concisely
describe
various
aspects
and
requirements
of
the
Stage
2
DBPR.
Additional
details
on
Tribal
involvement
in
the
rulemaking
process
can
be
found
in
section
8.8.

Disproportionate
Budgetary
Effects
After
exploring
possible
disproportionate
effects
of
the
Stage
2
DBPR
on
geographic
areas
and
groups
of
customers,
EPA
determined
that
the
Stage
2
DBPR
may
have
disproportionate
budgetary
effects
on
certain
geographic
regions.
Higher
TOC
levels
in
source
water
present
special
challenges
to
some
areas
of
the
country
(
for
detailed
analysis,
see
sections
3.3.4
and
3.5.2
and
Appendix
B).
Ground
water
systems
in
Florida,
in
particular,
will
be
heavily
impacted
by
the
Stage
2
DBPR
due
to
the
high
levels
of
TOC
in
their
source
water
and
the
large
number
of
ground
water
systems
located
in
the
State.
Other
areas
with
high
levels
of
precursors,
such
as
TOC
or
bromide,
will
also
be
adversely
affected.
However,
those
systems
with
high
precursor
and
DBP
levels
are
also
the
ones
most
likely
to
receive
the
greatest
benefit
from
the
rule.

The
SBREFA
process
determined
that
there
is
no
disproportionate
budgetary
effect
on
State,
Local,
or
Tribal
governments.
This
process
is
discussed
in
more
detail
in
Section
8.2
for
State
and
Local
governments.
EPA
also
performed
an
impact
analysis
for
public
and
private
systems
(
Exhibit
8.10),
which
showed
no
disproportionate
budgetary
effect.

In
addition
to
the
analyses
summarized
above,
EPA
assessed
an
additional
area
of
potential
disproportionate
impact:
the
impacts
on
urban
versus
rural
communities.
Based
on
the
costs
presented
in
Exhibit
8.11,
there
is
not
a
disproportionate
impact
on
rural
versus
urban
communities.
For
this
analysis,
small
water
systems
(
i.
e.,
systems
serving
fewer
than
10,000
people)
were
assumed
to
represent
rural
areas
since
small
water
systems
are
generally
located
in
more
rural
communities.
Large
water
systems
(
i.
e.,
systems
serving
at
least
10,000
people)
were
assumed
to
represent
urban
areas
since
most
urban
areas
are
served
by
a
few
large
systems.
As
seen
by
the
figures
in
Exhibit
8.11,
the
costs
of
the
rule
are
greater
for
large
systems,
which
serve
more
people
and
have
a
greater
economic
base
over
which
they
can
spread
their
costs.
Small
water
systems
have
fewer
costs
and
also
have
many
more
systems
over
which
those
costs
are
spread.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
34
Annual
Cost
to
Systems
Serving
£
10,000
People
($
Millions)
Annual
Cost
to
Systems
Serving
>
10,000
People
($
Millions)
Source
Water
Category
3
Percent
7
Percent
3
Percent
7
Percent
Surface
Water
Systems
8.2
$
8.5
$
21.4
$
25.1
$
Ground
Water
Systems
11.7
$
12.1
$
14.2
$
14.9
$
Tribal
Systems
0.2
$
0.2
$
0.0
$
0.0
$
Total
20.2
$
20.8
$
35.6
$
40.0
$

Annual
Cost
to
Systems
Serving
£
10,000
People
($
Millions)
Annual
Cost
to
Systems
Serving
>
10,000
People
($
Millions)
Source
Water
Category
3
Percent
7
Percent
3
Percent
7
Percent
Surface
Water
Systems
0.6
$
0.6
$
0.1
$
0.1
$
Ground
Water
Systems
1.4
$
1.5
$
0.0
$
0.0
$
Tribal
Systems
0.0
$
0.0
$
­
$
­
$
Total
2.0
$
2.1
$
0.1
$
0.2
$
Exhibit
8.11a
Annualized
Cost
of
Compliance
for
CWSs
(
3
and
7
Percent
Discount
Rates)
($
Millions)

Exhibit
8.11b
Annualized
Cost
of
Compliance
for
NTNCWSs
(
3
and
7
Percent
Discount
Rates)
($
Millions)

Note:
Detail
may
not
add
due
to
independent
rounding
(
some
data
are
rounded
to
zero
if
less
than
$
0.05
million).

Source:
Derived
from
Exhibit
6.6;
for
this
exhibit,
Tribal
system
costs
are
apportioned
by
the
percent
of
Tribal
systems
in
each
size
category
and
source
water
type
(
see
Exhibit
8.12).

8.8
Indian
Tribal
Governments
Executive
Order
13175,
entitled
"
Consultation
and
Coordination
with
Indian
Tribal
Governments"
(
65
FR
67249;
November
9,
2000),
requires
EPA
to
develop
"
an
accountable
process
to
ensure
meaningful
and
timely
input
by
Tribal
officials
in
the
development
of
regulatory
policies
that
have
Tribal
implications."
The
Executive
Order
defines
"
policies
that
have
Tribal
implications"
to
include
regulations
that
have
"
substantial
direct
effects
on
one
or
more
Indian
Tribes,
on
the
relationship
between
the
Federal
government
and
the
Indian
Tribes,
or
on
the
distribution
of
power
and
responsibilities
between
the
Federal
government
and
Indian
Tribes."

Under
Executive
Order
13175,
EPA
may
not
issue
a
regulation
that
has
Tribal
implications,
that
imposes
substantial
direct
compliance
costs,
and
that
is
not
required
by
statute,
unless
the
Federal
government
provides
the
funds
necessary
to
pay
the
direct
compliance
costs
incurred
by
Tribal
governments,
or
EPA
consults
with
Tribal
officials
early
in
the
process
of
developing
the
proposed
regulation
and
develops
a
Tribal
summary
impact
statement.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
35
EPA
has
concluded
that
the
Stage
2
DBPR
may
have
Tribal
implications,
because
it
may
have
substantial
direct
compliance
costs
on
Tribal
governments,
on
the
relationship
between
the
Federal
government
and
Indian
Tribes,
or
on
the
distribution
of
power
and
responsibilities
between
the
Federal
government
and
Indian
Tribes,
as
specified
in
Executive
Order
13175.

Total
Tribal
costs
are
estimated
to
be
approximately
$
199,372
per
year
(
at
a
3
percent
discount
rate)
and
this
cost
is
distributed
across
559
Tribal
systems.
The
cost
for
individual
systems
depend
on
system
size
and
source
water
type.
Of
the
559
Tribes
that
may
be
affected
by
the
Stage
2
DBPR,
502
use
ground
water
as
a
source
and
57
systems
use
surface
water
or
GWUDI.
Since
the
majority
of
Tribal
systems
are
ground
water
systems
serving
fewer
than
500
people,
approximately
10
percent
of
all
Tribal
systems
will
likely
have
to
conduct
an
IDSE.
As
a
result,
the
Stage
2
DBPR
is
most
likely
to
have
an
impact
on
Tribes
using
surface
water
or
GWUDI
serving
more
than
500
people.
Accordingly,
EPA
provides
the
following
Tribal
summary
impact
statement,
as
required
by
Section
5(
b)
of
Executive
Order
13175.
The
results
of
the
analysis
conducted
for
the
Tribal
summary
impact
statement
are
presented
in
Exhibit
8.12.

EPA
consulted
with
Tribal
officials
early
in
the
process
of
developing
this
regulation
to
permit
them
to
have
meaningful
and
timely
input
into
its
development.
Consistent
with
Executive
Order
13175,
EPA
engaged
in
outreach
and
consultation
efforts
with
Tribal
officials
in
the
development
of
the
Stage
2
DBPR.
The
most
long­
term
participation
of
Tribes
was
on
the
Federal
Advisory
Committee
through
a
representative
of
the
All
Indian
Pueblo
Council
(
AIPC),
which
is
associated
with
approximately
20
Tribes.
In
February
1999,
at
the
Las
Vegas
EPA/
Inter­
Tribal
Council
of
Arizona,
a
number
of
Tribal
representatives
requested
the
AIPC
representative
to
be
the
FACA
representative
for
Federal
Tribes,
given
his
knowledge
of
drinking
water
systems.

In
addition
to
obtaining
FACA
Tribal
input,
EPA
presented
the
Stage
2
DBPR
at
the
16th
Annual
Consumer
Conference
of
the
National
Indian
Health
Board,
the
Environmental
Council's
Annual
Conference
in
April
2000,
and
the
EPA/
Inter­
Tribal
Council
of
Arizona,
Inc.
Tribal
consultation
meeting.
Over
900
attendees
representing
Tribes
from
across
the
country
attended
the
National
Indian
Health
Board's
Consumer
Conference,
and
over
100
Tribes
were
represented
at
the
annual
conference
of
the
National
Tribal
Environmental
Council.
Representatives
from
15
Tribes
participated
at
the
EPA/
Inter­
Tribal
Council
of
Arizona
meeting.
At
the
first
two
conferences,
an
EPA
representative
conducted
two
workshops
on
EPA's
drinking
water
program
and
upcoming
regulations,
including
the
Stage
2
DBPR.
The
presentation
materials
and
meeting
summary
were
sent
to
over
500
Tribes
and
Tribal
organizations.

Fact
sheets
describing
the
requirements
of
the
Stage
2
DBPR
and
requesting
Tribal
input
were
distributed
at
an
annual
EPA
Tribal
meeting
in
San
Francisco,
and
at
a
Native
American
Water
Works
Association
meeting
in
Scottsdale,
Arizona.
EPA
also
worked
through
its
Regional
Indian
Coordinators
and
the
National
Tribal
Operations
Committee
to
raise
awareness
of
the
development
of
the
rule.
EPA
mailed
fact
sheets
on
the
Stage
2
DBPR
to
all
of
the
Federally
recognized
Tribes
in
November
2000,
as
well
as
the
Tribal
Caucus
of
the
National
Tribal
Operations
Committee.

A
few
Tribes
responded
by
requesting
more
information
and
expressing
concern
about
having
to
implement
too
many
regulations.
Some
members
of
the
Tribal
Caucus
noted
that
the
rule
would
have
a
benefit.
They
also
expressed
a
concern
about
infrastructure
costs
and
the
lack
of
funding
attached
to
the
rule.
In
response
to
one
Tribal
representative's
comments
on
the
November
2000
mailout,
EPA
explained
the
health
protection
benefit
expected
to
be
gained
by
the
Stage
2
DBPR.
EPA
also
directed
those
who
asked
for
more
information
to
the
Agreement
in
Principle
on
the
EPA
website.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
36
As
another
step
in
Tribal
consultation,
EPA
held
a
teleconference
for
Tribal
representatives
on
January
24,
2002.
Prior
to
the
teleconference,
invitations
were
sent
to
all
of
the
Federally­
recognized
Tribes,
along
with
fact
sheets
explaining
the
rule.
Twelve
Tribal
representatives
and
four
regional
Tribal
Program
Coordinators
attended.
The
Tribal
representatives
requested
further
explanation
of
the
rule
and
expressed
concerns
about
funding
sources.
EPA
also
received
calls
from
Tribes
after
the
teleconference
that
provided
EPA
with
additional
feedback.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
37
Percent
of
Systems
Number
of
Systems
Percent
of
Systems
Number
of
Systems
Percent
of
Systems
Number
of
Systems
Percent
of
Systems
Number
of
Systems
A
B
C
=
B
*
A
D
E
=
D
*
A
F
G
=
F
*
A
H
I
=
H
*
A
J
K
=
A
*
J
Primarily
Surface
Water
CWSs
£
100
13
100%
13
23%
3
0%
0
0%
0
123
$
1,598
$
101­
500
18
100%
18
26%
5
2%
0
0%
0
326
$
5,875
$
501­
1,000
7
100%
7
90%
6
42%
3
2%
0
709
$
4,963
$
1,001­
3,300
13
100%
13
90%
12
42%
5
2%
0
1,021
$
13,268
$
3,301­
10,000
4
100%
4
89%
4
56%
2
2%
0
2,077
$
8,307
$
10,001­
50,000
1
100%
1
86%
1
0%
0
8%
0
3,280
$
3,280
$
50,001­
100,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
100,001­
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
>
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
National
Subtotal
56
56
30
11
1
37,292
$

Primarily
Disinfecting
Ground
Water
CWSs
£
100
104
100%
104
3%
3
0%
0
0%
0
164
$
17,074
$
101­
500
236
100%
236
3%
8
1%
2
0%
0
251
$
59,308
$
501­
1,000
70
100%
70
12%
8
41%
29
0%
0
487
$
34,116
$
1,001­
3,300
46
100%
46
12%
5
41%
19
0%
0
577
$
26,554
$
3,301­
10,000
14
100%
14
12%
2
41%
6
0%
0
1,235
$
17,293
$
10,001­
50,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
50,001­
100,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
100,001­
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
>
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
National
Subtotal
470
470
26
56
0
154,344
$

Primarily
Surface
Water
NTNCWSs
£
100
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
101­
500
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
501­
1,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
1,001­
3,300
1
100%
1
0%
0
0%
0
0%
0
1,489
$
1,489
$
3,301­
10,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
10,001­
50,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
50,001­
100,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
100,001­
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
>
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
National
Subtotal
1
1
0
0
0
1,489
$

Primarily
Disinfecting
Ground
Water
NTNCWSs
£
100
16
100%
16
0%
0
0%
0
0%
0
152
$
2,436
$
101­
500
11
100%
11
0%
0
0%
0
0%
0
199
$
2,193
$
501­
1,000
1
100%
1
0%
0
1%
0
0%
0
315
$
315
$
1,001­
3,300
4
100%
4
0%
0
1%
0
0%
0
326
$
1,302
$
3,301­
10,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
10,001­
50,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
50,001­
100,000
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
100,001­
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
>
1
Million
0
NA
NA
NA
NA
NA
NA
NA
NA
­
$
­
$
National
Subtotal
32
32
0
0
0
6,246
$

TOTALS
559
559
56
67
1
199,372
$
System
Size/
Type
Number
of
Tribal
Systems
Affected
by
the
Stage
2
DBPR
Mean
Annualized
Cost
per
System
Estimated
Total
Tribal
Costs
Systems
Conducting
Implementation
Activities
Systems
Conducting
IDSE
Monitoring
Systems
Conducting
Additional
Routine
Monitoring
Systems
Conducting
Significant
Excursion
Activities
Exhibit
8.12
Annual
Cost
of
Compliance
for
Tribal
Systems
by
System
Type
and
Size
(
Annualized
at
3
Percent)

Sources:
(
A)
Number
of
Indian
Lands
from
SDWIS
4th
Quarter
FY2000
data.
(
B,
D,
F,
and
H)
Derived
from
Exhibit
H.
14a.
(
J)
Mean
costs
are
total
annualized
costs
(
Exhibits
K.
2ba,
K.
2be,
K.
2bi,
K.
2bm)
divided
by
the
number
of
primarily
ground
or
primarily
surface
water
CWSs
or
NTNCWSs
in
the
size
category
(
Exhibit
3.4,
column
E).

8.9
Impacts
on
Sensitive
Subpopulations
EPA's
Office
of
Water
has
historically
considered
risks
to
sensitive
subpopulations
(
including
fetuses,
infants,
and
children)
in
establishing
drinking
water
assessments,
advisories
or
other
guidance,
and
standards
(
USEPA
1989c;
USEPA
1991a).
The
disinfection
of
public
drinking
water
supplies
to
prevent
waterborne
disease
is
the
most
successful
public
health
program
in
U.
S.
history
(
USEPA
1991a).
However,
numerous
DBPs
that
result
from
the
chemical
disinfection
may
have
potential
health
risks.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
38
Thus,
maximizing
health
protection
for
sensitive
subpopulations
requires
balancing
risks
to
achieve
the
recognized
benefits
of
controlling
waterborne
pathogens
while
minimizing
risk
of
potential
DBP
toxicity.
Experience
shows
that
waterborne
disease
from
pathogens
in
drinking
water
is
a
major
concern
for
children
and
other
subgroups
(
e.
g.,
the
elderly,
the
immune­
compromised,
and
pregnant
women)
because
of
their
greater
vulnerabilities
(
Gerba
et
al.
1996).
EPA
believes
that,
based
on
animal
studies,
there
may
also
be
potential
risks
posed
by
DBPs
to
children
and
pregnant
women
(
USEPA
1998f).

In
developing
this
rule,
risks
to
sensitive
subpopulations,
including
children,
were
taken
into
account
in
the
assessments
of
disinfectants
and
DBPs
(
see
sections
5.2.1,
5.3.3,
and
5.6.1).
A
description
of
the
data
available
for
evaluating
risks
to
children
and
the
conclusions
drawn
can
be
found
in
the
public
docket
for
this
rulemaking
(
USEPA
1998g;
USEPA
2002h).
The
Agency
has
evaluated
alternative
regulatory
options
and
selected
the
option
that
balances
cost
with
providing
significant
benefits.
It
should
be
noted
that
the
LT2ESWTR,
which
accompanies
this
rule,
provides
better
controls
of
pathogens
and
achieves
the
goal
of
increasing
the
protection
of
children.

SDWA
identifies
pregnant
women
as
a
sensitive
subpopulation.
Epidemiological
and
toxicological
research
suggests
a
potential
association
between
exposure
to
DBPs
and
adverse
reproductive
and
developmental
health
effects
such
as
spontaneous
abortion,
still
birth,
neural
tube
defects,
cardiovascular
effects,
and
low
birth
weight.
The
primary
objective
of
the
Stage
2
DBPR
is
to
protect
pregnant
women
and
their
fetuses
from
adverse
health
effects
that
may
be
caused
by
exposure
to
elevated
DBP
levels.
In
this
respect,
any
benefits
derived
from
implementation
of
Stage
2
DBPR
provisions
should
have
a
positive
health
impact
on
this
sensitive
subpopulation.
Benefits
for
other
sensitive
subpopulations
(
e.
g.,
infants,
toddlers,
the
elderly,
and
seriously
ill
individuals),
while
not
specifically
quantifiable,
also
should
be
positive
to
the
extent
that
reduction
of
DBPs
have
a
beneficial
impact
on
any
member
of
the
general
population.
Research
outlining
the
potential
health
benefits
of
the
Stage
2
DBPR
to
both
sensitive
subpopulations
and
the
general
public
is
discussed
in
greater
detail
in
Chapter
5
of
this
EA.

8.9.1
Protecting
Children
from
Environmental
Health
Risks
and
Safety
Risks
Executive
Order
13045
(
62
FR
19885
April
23,
1997)
applies
to
any
rule
initiated
after
April
21,
1998,
that
(
1)
is
determined
to
be
"
economically
significant"
as
defined
under
Executive
Order
12866;
and
(
2)
concerns
an
environmental,
health,
or
safety
risk
that
EPA
has
reason
to
believe
may
have
a
disproportionate
effect
on
children.
If
the
regulatory
action
meets
both
criteria,
EPA
must
evaluate
the
environmental
health
or
safety
effects
of
the
planned
rule
on
children,
and
explain
why
the
planned
regulation
is
preferable
to
other
potentially
effective
and
reasonably
feasible
alternatives
considered
by
the
Agency.

While
the
Stage
2
DBPR
is
not
subject
to
the
Executive
Order
because
it
is
not
economically
significant
as
defined
in
Executive
Order
12866,
EPA
nonetheless
believes
that
the
environmental
health
or
safety
risk
(
i.
e.,
the
risk
associated
with
DBPs)
addressed
by
this
action
may
have
a
disproportionate
effect
on
children.
EPA
has
consistently
and
explicitly
considered
risks
to
infants
and
children
in
all
assessments
developed
for
this
rulemaking
and
presents
the
environmental
health
and
safety
effects
of
DBPs
on
children
in
sections
5.2.1
and
5.6.1.
For
each
of
the
DBPs
included
in
the
Stage
2
DBPR,
EPA
has
compiled
analyses
of
the
available
data
used
for
deriving
the
maximum
contaminant
level
goal
(
MCLG)
to
determine
if
these
values
are
protective
for
fetuses
and
children.

The
observed
adverse
effects
in
most
of
the
available
studies
are
at
higher
doses
than
the
established
MCLGs
for
these
contaminants.
EPA
has
analyzed
the
available
toxicological
and
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
39
epidemiological
data
in
the
report
entitled,
Disinfection
Byproduct
Technical
Review
Panel
Report
on
Health
Risks
to
Fetuses,
Infants
and
Children
(
USEPA
2002h).
In
the
report,
EPA
notes
that
bromodichloromethane
(
BDCM),
bromoform,
dichloroacetic
acid
(
DCAA),
and
bromate
are
considered
likely
carcinogens
for
humans.
MCLGs
of
zero
were
selected
after
consideration
of
the
potential
carcinogenicity
of
these
chemicals.
These
MCLGs
protect
both
children
and
adults.
The
MCLGs
for
chloroform,
dibromochloromethane
(
DBCM),
monochloroacetic
acid
(
MCAA),
and
trichloroacetic
acid
(
TCAA)
were
based
on
systemic
toxicity.
The
No­
Observed­
Adverse­
Effect­
Level
(
NOAEL)/
Lowest­
Observed­
Adverse­
Effect­
Level
(
LOAELs)
used
to
derive
these
numbers
are
lower
than
the
NOAEL/
LOAELs
for
developmental
effects;
and,
thus,
are
protective
of
unborn
fetuses,
infants
and
children
for
developmental
malformations
for
exposure
to
these
DBPs.
The
data
on
monobromoacetic
acid
(
MBAA)
and
dibromoacetic
acid
(
DBAA)
are
insufficient
for
the
derivation
of
an
MCLG.

Therefore,
the
Agency
concluded
that
it
does
not
have
reason
to
believe
that
the
environmental
health
risks
or
safety
risks
addressed
by
the
action
in
the
Stage
2
DBPR
present
a
disproportionate
risk
to
children.
Similarly,
the
MCLGs
of
all
DBPs
in
the
rule
help
protect
fetuses,
infants,
and
children
from
potential
adverse
developmental/
reproductive
effects.

8.10
Environmental
Justice
Executive
Order
12898
(
59
FR
7629)
establishes
a
Federal
policy
for
incorporating
environmental
justice
into
Federal
agency
missions
by
directing
agencies
to
identify
and
address
disproportionately
high
and
adverse
human
health
or
environmental
effects
of
its
programs,
policies,
and
activities
on
minority
and
low­
income
populations.
The
Agency
has
considered
environmental
justice­
related
issues
concerning
the
potential
impacts
of
this
action
and
consulted
with
minority
and
low­
income
stakeholders.

Two
aspects
of
the
Stage
2
DBPR
comply
with
the
order
that
requires
the
Agency
to
consider
environmental
justice
issues
in
the
rulemaking
and
to
consult
with
stakeholders
representing
a
variety
of
economic
and
ethnic
backgrounds.
These
include:
(
1)
the
overall
nature
of
the
rule,
and
(
2)
the
convening
of
a
stakeholder
meeting
specifically
to
address
environmental
justice
issues.

The
Stage
1
DBPR
has
served
as
a
template
for
the
development
of
the
Stage
2
DBPR.
As
such,
the
Agency
also
built
on
the
efforts
conducted
during
the
Stage
1
DBPR
development
to
comply
with
Executive
Order
12898.
On
March
12,
1998,
the
Agency
held
a
stakeholder
meeting
to
address
various
components
of
pending
drinking
water
regulations
and
how
they
might
impact
sensitive
subpopulations,
minority
populations,
and
low­
income
populations.
This
meeting
was
a
continuation
of
stakeholder
meetings
that
started
in
1995
to
obtain
input
on
the
Agency's
Drinking
Water
Programs.
Topics
discussed
included
treatment
techniques,
costs
and
benefits,
data
quality,
health
effects,
and
the
regulatory
process.
Participants
were
national,
State,
Tribal,
municipal,
and
individual
stakeholders.
EPA
conducted
the
meeting
by
video
conference
call
between
11
cities.
The
major
objectives
for
the
March
12,
1998,
meeting
included
the
following:

°
Solicit
ideas
from
stakeholders
on
known
issues
concerning
current
drinking
water
regulatory
efforts.

°
Identify
key
areas
of
concern
to
stakeholders.
8
Source:
Exhibit
H.
15.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
40
°
Receive
suggestions
from
stakeholders
concerning
ways
to
increase
representation
of
communities
in
the
Office
of
Ground
Water
and
Drinking
Water
(
OGWDW)
regulatory
efforts.

In
addition,
EPA
developed
a
plain­
English
guide
for
this
meeting
to
assist
stakeholders
in
understanding
the
multiple,
and
sometimes
complex,
issues
surrounding
drinking
water
regulations.

The
Stage
2
DBPR
and
other
drinking
water
regulations
promulgated
or
under
development
are
expected
to
have
a
positive
effect
on
human
health
regardless
of
the
social
or
economic
status
of
a
specific
population.
The
Stage
2
DBPR
serves
to
provide
a
similar
level
of
drinking
water
protection
to
all
groups.
Where
water
systems
have
high
DBP
levels,
they
must
reduce
levels
to
meet
the
MCLs.
Further,
to
the
extent
that
DBP
levels
in
drinking
water
might
be
disproportionately
high
now
among
minority
or
low­
income
populations
(
which
is
unknown),
the
Stage
2
DBPR
will
work
to
remove
those
differences.
Thus,
the
Stage
2
DBPR
meets
the
intent
of
Federal
policy
requiring
incorporation
of
environmental
justice
into
Federal
agency
missions.

The
Stage
2
DBPR
applies
uniformly
to
CWSs
and
NTNCWSs
that
add
a
disinfectant
other
than
UV
light
or
that
deliver
water
that
has
been
chemically
disinfected.
Consequently,
the
health
protection
from
DBP
exposure
that
this
rule
provides
is
equal
across
all
income
and
minority
groups
served
by
systems
regulated
by
this
rule.

8.11
Federalism
Executive
Order
13132,
"
Federalism"
(
64
FR
43255
August
10,
1999),
requires
EPA
to
develop
an
accountable
process
to
ensure
"
meaningful
and
timely
input
by
State
and
Local
officials
in
the
development
of
regulatory
policies
that
have
federalism
implications."
"
Policies
that
have
federalism
implications"
are
defined
in
the
executive
order
to
include
regulations
that
have
"
substantial
direct
effects
on
the
States,
on
the
relationship
between
the
national
government
and
the
States,
or
on
the
distribution
of
power
and
responsibilities
among
the
various
levels
of
government."

Under
Section
6(
b)
of
Executive
Order
13132,
EPA
may
not
issue
a
regulation
that
has
federalism
implications,
imposes
substantial
direct
compliance
costs,
and
is
not
required
by
statute,
unless
the
Federal
government
provides
the
funds
necessary
to
pay
the
direct
compliance
costs
incurred
by
State
and
Local
governments,
or
consults
with
State
and
Local
officials
early
in
the
process
of
developing
the
proposed
regulation.

EPA
has
concluded
that
the
Stage
2
DPBR
will
not
have
federalism
implications.
It
will
not
impose
substantial
direct
effects
on
the
States,
on
the
relationship
between
national
government
and
the
States,
or
on
the
distribution
of
power
and
responsibilities
among
various
levels
of
government,
as
specified
in
Executive
Order
13132.
The
Stage
2
DBPR
has
one­
time
costs
for
implementation
of
approximately
$
7.2
million.
8
Thus,
the
requirements
of
Sections
6(
b)
and
6(
c)
of
the
executive
order
do
not
apply
to
this
rule.

In
the
spirit
of
Executive
Order
13132,
EPA
consulted
with
State
and
Local
officials
early
in
the
process
of
developing
the
Stage
2
DPBR
to
permit
them
to
have
meaningful
and
timely
input
into
its
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
41
development.
On
February
20,
2001,
EPA
held
a
dialogue
with
representatives
of
State
and
Local
governmental
organizations
including
those
that
represent
elected
officials.
Representatives
from
the
following
organizations
attended
the
consultation
meeting:
ASDWA,
the
National
Governors'
Association
(
NGA),
the
National
Conference
of
State
Legislatures
(
NCSL),
the
International
City/
County
Management
Association
(
ICMA),
NLC,
the
County
Executives
of
America,
and
health
departments.
At
the
consultation
meeting,
questions
ranged
from
a
basic
inquiry
into
how
Cryptosporidium
gets
into
water
to
more
detailed
queries
about
anticipated
implementation
guidance,
procedures,
and
schedules.
No
concerns
were
expressed.
Some
of
the
State
and
Local
organizations
that
attended
this
governmental
dialogue
meeting
were
also
participants
in
the
Stage
2
M­
DBP
Federal
Advisory
Committee
and
signed
the
Agreement
in
Principle.
In
addition,
EPA
consulted
with
a
mayor
in
the
SBREFA
consultation.
EPA
considered
all
input
from
these
consultations
in
the
development
of
the
Stage
2
DBPR.

8.12
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use
Executive
Order
13211,
"
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use"
(
66
FR
28355
May
22,
2001),
provides
that
agencies
shall
prepare
and
submit
to
the
Administrator
of
the
Office
of
Information
and
Regulatory
Affairs,
OMB,
a
Statement
of
Energy
Effects
for
certain
actions
identified
as
"
significant
energy
actions."
Section
4(
b)
of
Executive
Order
13211
defines
"
significant
energy
actions"
as
"
any
action
by
an
agency
(
normally
published
in
the
Federal
Register)
that
promulgates
or
is
expected
to
lead
to
the
promulgation
of
a
final
rule
or
regulation,
including
notices
of
inquiry,
advance
notices
of
proposed
rulemaking,
and
notices
of
proposed
rulemaking:
(
1)(
i)
that
is
a
significant
regulatory
action
under
Executive
Order
12866
or
any
successor
order,
and
(
ii)
is
likely
to
have
a
significant
adverse
effect
on
the
supply,
distribution,
or
use
of
energy;
or
(
2)
that
is
designated
by
the
Administrator
of
the
Office
of
Information
and
Regulatory
Affairs
as
a
significant
energy
action."

The
Stage
2
DBPR
has
not
been
designated
by
the
Administrator
of
the
Office
of
Information
and
Regulatory
Affairs
as
a
significant
energy
action
because
it
is
not
likely
to
have
a
significant
adverse
effect
on
the
supply,
distribution,
or
use
of
energy.
This
determination
is
based
on
the
analysis
presented
below.

Energy
Supply
The
first
consideration
is
whether
the
Stage
2
DBPR
would
adversely
affect
the
supply
of
energy.
The
Stage
2
DBPR
does
not
regulate
power
generation,
either
directly
or
indirectly
and
the
public
and
private
utilities
that
the
Stage
2
DBPR
regulates
do
not,
as
a
rule,
generate
power.
Further,
the
cost
increases
borne
by
customers
of
water
utilities
as
a
result
of
the
Stage
2
DBPR
are
a
small
percentage
of
the
total
cost
of
water,
except
for
a
few
small
systems
that
will
need
to
spread
the
cost
of
installing
advanced
technologies
over
a
narrow
customer
base.
Therefore,
the
customers
that
are
power
generation
utilities
are
unlikely
to
face
any
significant
effects
as
a
result
of
the
Stage
2
DBPR.
In
summary,
the
Stage
2
DBPR
does
not
regulate
the
supply
of
energy,
does
not
generally
regulate
the
utilities
that
supply
energy,
and
is
unlikely
to
significantly
affect
the
customer
base
of
energy
suppliers.
Thus,
the
Stage
2
DBPR
would
not
adversely
affect
the
supply
of
energy.

In
response
to
the
Stage
2
DBPR,
some
water
utilities
are
expected
to
increase
their
energy
use,
and
those
impacts
are
discussed
later
in
this
section.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
42
Energy
Distribution
The
second
consideration
is
whether
the
Stage
2
DBPR
would
adversely
affect
the
distribution
of
energy.
The
Stage
2
DBPR
does
not
regulate
any
aspect
of
energy
distribution.
PWSs
that
are
regulated
by
the
Stage
2
DBPR
already
have
electrical
service.
As
derived
later
in
this
section,
the
Stage
2
DBPR
is
projected
to
increase
peak
electricity
demand
at
water
utilities
by
only
0.006
percent.
Therefore,
EPA
estimates
that
the
existing
connections
are
adequate
and
that
the
Stage
2
DBPR
has
no
discernable
adverse
effect
on
energy
distribution.

Energy
Use
The
third
consideration
is
whether
the
Stage
2
DBPR
would
adversely
affect
the
use
of
energy.
Because
some
PWSs
are
expected
to
add
treatment
technologies
that
use
electrical
power,
this
potential
impact
of
the
Stage
2
DBPR
on
the
use
of
energy
requires
further
evaluation.
The
analyses
that
underlay
the
estimation
of
costs
in
Chapter
6
for
the
Stage
2
DBPR
are
national
in
scope
and
do
not
identify
specific
plants
or
utilities
that
may
install
treatment
in
response
to
the
rule.
As
a
result,
no
analysis
of
the
effect
on
specific
energy
suppliers
is
possible
with
the
available
data.
The
approach
used
to
estimate
the
impact
of
energy
use,
therefore,
focuses
on
national­
level
impacts.
The
analysis
estimates
the
additional
energy
use
due
to
the
Stage
2
DBPR,
and
compares
that
to
the
national
levels
of
power
generation
in
terms
of
average
and
peak
loads.

The
first
step
in
the
analysis
is
to
estimate
the
energy
used
by
the
technologies
expected
to
be
installed
as
a
result
of
the
Stage
2
DBPR.
Energy
use
is
not
directly
stated
in
Technologies
and
Costs
for
Control
of
Microbial
Contaminants
and
Disinfection
By­
Products
(
USEPA
2003o),
but
the
annual
cost
of
energy
for
each
technology
addition
or
upgrade
necessitated
by
the
Stage
2
DBPR
is
provided.
An
estimate
of
plant­
level
energy
use
is
derived
by
dividing
the
total
energy
cost
per
plant
for
a
range
of
flows
by
an
average
national
cost
of
electricity
of
$
0.076/
kWh
(
USDOE
2002).
The
energy
use
per
plant
for
each
flow
range
and
technology
is
then
multiplied
by
the
number
of
plants
predicted
to
install
each
technology
in
a
given
flow
range
(
technology
selection
forecasts
are
presented
in
Chapter
6).
The
energy
requirements
for
each
flow
range
are
then
added
to
produce
a
national
total.
No
electricity
use
is
subtracted
to
account
for
the
technologies
that
may
be
replaced
by
new
technologies,
resulting
in
a
conservative
estimate
of
the
increase
in
energy
use.
Exhibit
8.13
shows
the
estimated
energy
use
for
each
Stage
2
DBPR
compliance
technology
in
kilowatt
hours
per
year
(
kWh/
y).
The
incremental
national
annual
energy
usage
is
approximately
0.08
million
megawatt­
hours
(
mWh).
Although
the
energy
usage
after
implementing
the
Stage
2
DBPR
is
expected
to
be
greater
than
before
implementation
(
advanced
technologies
typically
require
more
energy
than
conventional
technologies),
the
net
increase
in
energy
usage
is
not
expected
to
be
significant.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
43
(
a)
(
b)

Chloramines
(
with
and
without
advanced
tech.)
1,719
2,610,918
Chlorine
Dioxide
9
37,335
UV
736
11,033,906
Ozone
19
1,545,741
MF/
UF
0
1,821
GAC10
­
­
GAC10
+
Adv.
Disinfectants
18
14,914,955
GAC20
113
24,049,135
GAC20
+
Adv.
Disinfectants
34
4,366,613
NF
­
­
Membranes
17
17,680,345
TOTAL
2,667
76,240,768
Total
Increase
in
Energy
Usage
as
a
Result
of
the
Stage
2
DBPR
(
kWh/
yr)
Number
of
Plants
Selecting
the
Technology
Technology
Exhibit
8.13
Increase
in
Energy
Usage
as
a
Result
of
the
Stage
2
DBPR
Notes:
Detail
may
not
add
due
to
independent
rounding.

Sources:
(
a)
Number
of
plants
selecting
each
technology
are
derived
from
Exhibits
6.14a,
6.14b,
6.16a,
and
6.16b.
Note
that
the
number
of
plants
selecting
chloramines
is
the
number
of
plants
selecting
chloramines
only
PLUS
the
number
selecting
chloramines
with
advanced
technology
(
making
the
total
in
this
exhibit
higher
than
the
total
number
of
plants
changing
technology
in
Exhibit
6.4).
(
b)
Energy
costs
derived
from
the
Technologies
and
Costs
Document
(
USEPA
2003o)
for
the
treatment
plant
design
conditions
listed
in
Exhibit
6.8.
Energy
costs
were
converted
to
energy
usage
by
dividing
the
costs
by
the
unit
costs
for
energy
listed
in
Table
4­
3
of
the
Technologies
and
Costs
Document.
Energy
usage
is
different
for
different
size
categories;
the
average
per
plant
is
the
weighted
average
for
all
plants
selecting
the
technology.

Exhibit
8.14
provides
a
sample
calculation
for
chloramines
showing
the
increase
in
energy
usage
as
a
result
of
the
Stage
2
DBPR.

To
determine
if
the
additional
energy
required
for
systems
to
comply
with
the
rule
would
have
a
significant
adverse
effect
on
the
use
of
energy,
EPA
compared
the
numbers
in
Exhibit
8.13
to
the
national
production
figures
for
electricity.
According
to
the
U.
S.
Department
of
Energy's
Energy
Information
Administration,
electricity
producers
generated
3,800
million
megawatt
hours
(
mWh)
of
electricity
in
2001
(
USDOE
2002).
Therefore,
even
using
the
highest
assumed
energy
use
for
the
Stage
2
DBPR
(
i.
e.,
76,240,768
kWh/
y),
the
rule
when
fully
implemented
would
result
in
only
a
0.002
percent
increase
in
annual
average
energy
use.
This
calculation
is
shown
below:

1.
76,240,768
kWh/
y
*
(
mWh/
1,000
kWh)
=
76,240
mWh/
y
2.
76,240
mWh/
y
÷
3,800,000,000
mWh/
y
*
100
=
0.002%
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
44
Number
of
Total
Energy
Usage
Average
Daily
Total
No.
Plants
Annual
Energy
Annual
Energy
for
Plants
Selecting
Flow
per
Plant
of
Selecting
Cost
per
Plant
Requirement
Chloramines
(
mgd)
Plants
Chloramines
($/
plant/
yr)
(
kWhr/
plant/
yr)
(
kWhr/
year)

A
B
C
D
E
=
D/$
0.076
per
kWhr
F
=
C*
E
Primarily
Surface
Water
CWSs
<
100
0.007
470
14
67
876
12,474
101
­
500
0.03
799
29
67
876
25,433
501
­
1,000
0.08
505
18
124
1,633
29,980
1,001
­
3,300
0.23
1,103
45
124
1,633
72,800
3,301
­
10,000
0.58
1,213
49
200
2,632
128,923
10,001
­
50,000
2.33
1,287
66
200
2,632
173,684
50,001
­
100,000
3.81
538
28
200
2,632
72,585
100,001
­
1
Million
14.51
572
29
300
3,947
115,874
>
1
Million
102.57
74
4
4,232
55,685
210,177
Primarily
Ground
Water
CWSs
<
100
0.01
7,772
178
67
876
156,081
101
­
500
0.02
15,725
436
67
876
381,584
501
­
1,000
0.05
6,133
170
67
876
148,832
1,001
­
3,300
0.13
7,890
184
124
1,633
300,217
3,301
­
10,000
0.34
4,975
116
124
1,633
189,303
10,001
­
50,000
0.71
5,367
108
200
2,632
283,550
50,001
­
100,000
2.07
738
15
200
2,632
39,005
100,001
­
1
Million
4.46
875
16
200
2,632
42,651
>
1
Million
30.37
18
0
200
2,632
887
Primarily
Surface
Water
NTNCWSs
<
100
0.01
298
0
67
876
0
101
­
500
0.03
301
13
67
876
11,602
501
­
1,000
0.09
108
10
124
1,633
16,164
1,001
­
3,300
0.22
72
4
124
1,633
5,800
3,301
­
10,000
0.66
23
3
200
2,632
7,010
10,001
­
50,000
3.48
9
1
200
2,632
2,239
50,001
­
100,000
12.43
1
1
300
3,947
2,060
100,001
­
1
Million
22.94
1
0
300
3,947
229
>
1
Million
­
0
0
­
­
­

Primarily
Ground
Water
NTNCWSs
<
100
0.005
3,662
84
67
876
73,550
101
­
500
0.03
2,624
73
67
876
63,684
501
­
1,000
0.08
717
20
124
1,633
32,422
1,001
­
3,300
0.19
267
6
124
1,633
10,150
3,301
­
10,000
0.60
27
1
200
2,632
1,679
10,001
­
50,000
2.65
4
0
200
2,632
235
50,001
­
100,000
7.96
0
0
200
2,632
20
100,001
­
1
Million
33.61
1
0
200
2,632
36
>
1
Million
­
0
0
­
­
­

TOTALS
64,171
1,719
1,519
2,610,918
System
Size
(
Population
Served)
Chloramines
(
Ground
Water,
Ammonia
Dose
=
0.15
mg/
l;
Surface
Water,
Ammonia
Dose
=
0.55
mg/
l)
Exhibit
8.14
Sample
Calculation
for
Determining
Increase
in
Energy
Usage:
Chloramines
Notes:
Detail
may
not
add
due
to
independent
rounding.

Sources:
(
A)
The
flows
are
taken
from
Exhibit
3.6.
(
B)
The
baseline
number
of
plants
are
taken
from
Exhibit
3.4.
(
C)
Number
of
plants
selecting
chloramines
are
taken
from
Exhibits
6.14a,
6.14b,
6.16a,
6.16b.
(
D)
The
electricity
cost
per
plant
is
taken
from
the
Technologies
and
Costs
document
(
USEPA
2003o).
(
E)
Electricity
cost
is
$
0.076/
KWh,
as
presented
in
the
Technologies
and
Costs
Document
(
USEPA
2003o).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
July
2003
8­
45
In
addition
to
average
energy
use,
the
impact
at
times
of
peak
power
demand
is
important.
To
examine
whether
increased
energy
usage
might
significantly
affect
the
capacity
margins
of
energy
suppliers,
their
peak
season
generating
capacity
reserve
was
compared
to
an
estimate
of
peak
incremental
power
demand
by
water
utilities.
Both
energy
use
and
water
use
peak
in
the
summer
months,
so
the
most
significant
effects
on
supply
would
be
seen
then.
In
the
summer
of
2001,
U.
S.
generation
capacity
exceeded
consumption
by
15
percent,
or
approximately
120,000
mW
(
USDOE
2002).
Assuming
around­
the­
clock
operation
of
water
treatment
plants,
the
total
energy
requirement
for
the
Stage
2
DBPR
(
Exhibit
8.13)
can
be
divided
by
8,760
hours
per
year
to
obtain
an
average
power
demand
of
8.7
mW.
This
is
only
0.006
percent
of
the
capacity
margin
available
at
peak
use.
This
calculation
is
presented
below:

1.
76,240,768
kWh/
y
*
(
y/
8,760
hr)
*
(
mW/
1,000
kW)
=
8.7
mW
2.
8.7
mW
÷
120,000
mW
*
100
=
0.007%

Assuming
that
power
demand
is
proportional
to
water
flow
through
the
plant
and
that
peak
flow
can
be
as
high
as
twice
the
average
daily
flow
during
the
summer
months,
about
17.4
mW
(
8.7
mW
x
2)
could
be
needed
for
treatment
technologies
installed
to
comply
with
the
Stage
2
DBPR.
This
is
still
only
a
very
small
fraction
(
0.015
percent)
of
the
U.
S.
capacity
margin
available
at
peak
use
(
120,000
mW).

Although
EPA
recognizes
that
not
all
regions
have
a
15
percent
capacity
margin
and
that
this
margin
varies
across
regions
and
through
time,
this
analysis
reflects
the
effect
of
the
rule
on
national
energy
supply,
distribution,
and
use.
While
certain
areas
have
experienced
shortfalls
in
generating
capacity
in
the
recent
past,
a
peak
incremental
power
requirement
of
17.4
mW
nationwide
is
not
likely
to
significantly
change
the
energy
supply,
distribution,
or
use
in
any
given
area.

Conclusion
The
Stage
2
DBPR
is
not
a
"
significant
energy
action"
as
defined
in
Executive
Order
13211,
"
Actions
Concerning
Regulations
That
Significantly
Affect
Energy
Supply,
Distribution,
or
Use"
(
66
FR
28355
May
22,
2001)
because
it
is
not
likely
to
have
a
significant
adverse
effect
on
the
supply,
distribution,
or
use
of
energy
(
based
on
annual
average
use
and
conditions
of
peak
power
demand).

The
total
increase
in
energy
usage
by
water
systems
as
a
result
of
the
Stage
2
DBPR
is
predicted
to
be
less
than
68
million
kWh/
y,
which
is
less
than
two­
thousandths
of
1
percent
of
the
total
energy
produced
in
2001.
While
the
rule
may
have
some
adverse
energy
effects,
EPA
does
not
believe
that
this
constitutes
a
significant
adverse
effect
on
the
energy
supply.
1Because
specific
estimates
of
WTP
for
avoiding
non­
fatal
bladder
cancer
are
not
available,
EPA
estimated
the
WTP
from
two
other
non­
fatal
illnesses:
chronic
bronchitis
and
curable
lymphoma.

2
The
number
of
cases
avoided
and
the
resulting
benefits
were
calculated
using
both
TTHM
and
haloacetic
acids
(
HAA5)
as
indicators
of
exposure
to
all
DBPs.
However,
because
results
for
both
indicators
were
similar,
only
the
results
of
calculations
using
TTHM
as
an
indicator
are
presented,
to
simplify
presentation.
Detailed
results
for
all
analyses
using
both
TTHM
and
HAA5
as
indicators
are
presented
in
Appendix
F.

Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
1
July
2003
9.
Comparison
of
Benefits
and
Costs
of
the
Stage
2
DBPR
9.1
Evaluation
of
National
Benefits
and
Costs
of
the
Stage
2
DBPR
This
chapter
presents
a
summary
and
comparison
of
the
benefits
and
costs
of
the
Stage
2
Disinfectants
and
Disinfection
Byproducts
Rule
(
DBPR).
Evaluation
on
a
national
level
shows
that
the
benefits
derived
from
the
Stage
2
DBPR
is
likely
to
exceed
the
costs.
The
following
sections
present
summary
results
from
the
body
of
the
economic
analysis,
followed
by
a
discussion
of
the
results.
The
first
sections
focus
on
analysis
of
the
Preferred
Regulatory
Alternative,
followed
by
a
comparison
of
this
alternative
to
the
other
alternatives
considered.

9.1.1
National
Benefits
Summary
EPA
has
determined
from
its
analysis
of
the
available
animal
toxicological
studies
and
human
epidemiological
studies
that
the
Stage
2
DBPR
could
provide
benefits
resulting
from
reduced
incidence
of
adverse
reproductive
and
developmental
effects
and
reduced
incidence
of
cancer,
particularly
bladder
cancer.

The
main
category
of
benefits
that
EPA
has
quantified
is
the
expected
range
of
avoided
new
cases
of
bladder
cancer
each
year,
including
both
fatal
and
non­
fatal
cases.
In
addition,
EPA
has
estimated
the
monetized
value
of
avoiding
these
cases
using
estimates
of
willingness
to
pay
(
WTP)
for
non­
fatal
cancer1
and
the
value
of
statistical
life
(
VSL)
for
fatal
cancer
cases.
Exhibit
9.1
summarizes
these
quantified
benefits
estimates
based
on
total
trihalomethane
(
TTHM)
reduction
as
an
indicator2
for
reduced
levels
of
all
disinfection
byproducts
(
DBPs)

Because
of
limitations
in
the
available
data,
it
is
not
possible
to
quantify
all
of
the
health
benefits
of
the
Stage
2
DBPR.
In
particular,
the
science
is
not
strong
enough
to
quantify
the
risk
of
reproductive
and
developmental
health
effects
resulting
from
DBP
exposure.
To
help
inform
the
assessment
of
the
Stage
2
DBPR
benefits,
EPA
has
prepared
an
illustrative
calculation
for
one
specific
reproductive
effects
end­
point
(
fetal
loss).
Results
from
this
analysis
show
that
1,100
to
4,700
fetal
losses
could
potentially
be
avoided
annually
as
a
result
of
the
Stage
2
DBPR.
Other
unquantified
health
and
non­
health
benefits
derived
from
rule
implementation
also
could
contribute
to
the
overall
value
of
benefits.
Unquantified
benefits
are
discussed
in
detail
in
Chapter
5
and
are
summarized
below
in
Exhibit
9.1.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
2
July
2003
Exhibit
9.1
Summary
of
Estimated
National
Benefits
of
the
Stage
2
DBPR
Benefit
Group(
s)
Affected
Type
of
Cost
Avoided
Medical
Care
Pain
&
Suffering
Lifetime
Care
Other
Unquantified
Benefits
Resulting
from
the
Stage
2
DBPR
Adverse
Reproductive
Health
Effects
Avoided
Women
(
and
men)
of
reproductive
age
T
T
T
Pregnant
women
T
T
T
Developmental
Health
Effects
Avoided
(
e.
g.,
congenital
anomalies)
Fetuses
T
T
Children/
adults
with
birth
defects
T
T
T
Other
Adverse
Health
Effects
Avoided
(
Reduction
in
other
cancers
and
benefits
from
reduction
of
other
DBPs,
co­
occurring
contaminants,
or
emerging
contaminants)
All
individuals
exposed
to
elevated
levels
of
DBPs
in
drinking
water
T
T
T
T
Adverse
Non­
Health
Effects
Avoided
(
Perceptions
of
drinking
water
quality,
ecological,
and
other
unknown
effects)
All
individuals
T
Estimated
Quantified
Benefits
Resulting
from
the
Stage
2
DBPR
Bladder
Cancer
Cases
Avoided
1
All
individuals
exposed
to
elevated
levels
of
DBPs
in
drinking
water
T
T
T
T
The
estimated
monetary
value
of
avoided
bladder
cancer
cases
attributable
to
the
Stage
2
DBPR
ranges
from
$
113
million
to
$
986
million
using
the
WTP
for
lymphoma
as
the
basis
for
valuing
non­
fatal
cancer
cases
and
a
3%
discount
rate
for
annualization;
$
98
million
to
$
854
million
using
the
WTP
for
lymphoma
as
the
basis
for
valuing
non­
fatal
cancer
cases
and
a
7%
discount
rate
for
annualization;
$
55
million
to
$
479
million
using
the
WTP
for
chronic
bronchitis
as
the
basis
for
valuing
non­
fatal
cancer
cases
and
a
3%
discount
rate
for
annualization;
and
$
48
million
to
$
416
million
using
the
WTP
for
chronic
bronchitis
as
the
basis
for
valuing
non­
fatal
cancer
cases
and
a
7%
discount
rate
for
annualization.
Notes:
1.
Benefits
are
based
on
TTHM
as
an
indicator
for
all
DBPS.
Monetized
values
represent
present
values
in
millions
of
year
2000
dollars.
Estimates
are
discounted
to
2003.
The
range
of
monetized
benefits
shown
reflects
2
and
17
percent
estimates
of
Population
Attributable
Risk
(
PAR).
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
a
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
drinking
water
and
bladder
cancer.
Source:
Discussions
of
these
health
effects
and
monetization
of
avoiding
them
are
presented
in
Chapter
5.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
3
July
2003
9.1.2
National
Cost
Summary
The
national
annual
costs
of
the
Stage
2
DBPR
results
from
cost
incurred
for
activities
associated
with
rule
implementation,
Initial
Distribution
System
Evaluations
(
IDSEs),
additional
routine
monitoring,
significant
excursion
evaluations,
and
changes
in
treatment
technologies
by
some
water
systems.
The
estimated
mean
annualized
cost
of
the
Stage
2
DBPR
is
$
59.1
million
at
a
3­
percent
discount
rate
and
$
64.6
million
at
a
7
percent
discount
rate
(
see
Exhibits
6.19a
and
6.19b).

9.1.3
Comparison
of
National
Benefits
and
Costs
The
Stage
2
DBPR
will
be
implemented
over
time
and,
therefore,
the
treatment
costs
incurred
by
the
affected
systems
and
benefits
realized
by
the
populations
they
serve
will
differ
by
year.
Exhibit
9.2
summarizes
the
nominal
(
undiscounted)
cost
and
benefit
estimates
for
the
Stage
2
DBPR,
according
to
the
implementation
schedule
(
presented
in
Appendix
D),
over
the
25­
year
analysis
period
of
this
EA.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
4
July
2003
2%
PAR,
WTP
for
Lymphoma
17%
PAR,
WTP
for
Lymphoma
2%
PAR,
WTP
for
Bronchitis
17%
PAR,
WTP
for
Bronchitis
2003
$
31.8
$
0.0
$
0.0
$
0.0
$
0.0
2004
$
30.8
$
0.0
$
0.0
$
0.0
$
0.0
2005
$
78.2
$
0.0
$
0.0
$
0.0
$
0.0
2006
$
89.4
$
11.7
$
102.2
$
5.7
$
49.9
2007
$
86.2
$
28.2
$
246.1
$
13.8
$
120.2
2008
$
94.3
$
47.5
$
414.7
$
23.2
$
202.4
2009
$
96.7
$
68.9
$
600.9
$
33.6
$
293.2
2010
$
103.6
$
91.8
$
801.0
$
44.8
$
390.6
2011
$
54.6
$
116.0
$
1,012.8
$
56.6
$
493.7
2012
$
56.3
$
129.7
$
1,131.7
$
63.2
$
551.5
2013
$
57.9
$
139.6
$
1,218.1
$
68.0
$
593.3
2014
$
40.3
$
147.6
$
1,288.4
$
71.9
$
627.3
2015
$
40.3
$
153.9
$
1,343.2
$
74.9
$
653.6
2016
$
40.3
$
159.2
$
1,389.4
$
77.4
$
675.9
2017
$
40.3
$
163.9
$
1,430.3
$
79.7
$
695.4
2018
$
40.3
$
168.1
$
1,467.4
$
81.7
$
713.1
2019
$
40.3
$
172.1
$
1,501.7
$
83.6
$
729.5
2020
$
40.3
$
175.8
$
1,534.0
$
85.3
$
744.8
2021
$
40.3
$
179.3
$
1,564.8
$
87.0
$
759.4
2022
$
40.3
$
182.7
$
1,594.3
$
88.6
$
773.4
2023
$
40.3
$
185.9
$
1,622.8
$
90.2
$
786.8
2024
$
40.3
$
189.1
$
1,650.5
$
91.7
$
799.9
2025
$
40.3
$
192.2
$
1,677.5
$
93.1
$
812.6
2026
$
40.3
$
195.3
$
1,704.0
$
94.5
$
825.0
2027
$
40.3
$
198.2
$
1,730.2
$
95.9
$
837.3
Source:

Benefits
from
Appendix
F,
Exhibit
F.
2u
and
F.
3u,
mean
values.
Year
Stage
2
DBPR
System
Costs
System
Costs
from
Appendix
K,
Exhibit
K.
2aq,
mean
value.
Stage
2
DBPR
Benefits
(
TTHM
as
Indicator)
Exhibit
9.2
Summary
of
Nominal
Benefit
and
Cost
Estimates
by
Year
Incurred,
Preferred
Alternative
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
5
July
2003
Unquantified
Benefits
Estimated
Annualized
Value
of
Quantified
National
Benefits
0
800
900
400
500
600
Estimated
Annualized
National
Costs
700
100
200
300
It
is
assumed
that
implementation
of
this
rule
will
begin
in
2003.
In
the
first
few
years,
before
systems
have
installed
treatment,
no
benefits
are
realized,
although
costs
are
incurred
for
rule
implementation
and
the
IDSE.
As
systems
begin
to
install
treatment,
avoided
cancer
cases
are
projected
to
occur
in
the
year
following
installation
of
treatment
and
each
year
thereafter,
adjusted
to
account
for
cessation
lag
(
see
section
5.5.2
for
a
description
of
adjustments
made
to
projected
cancer
cases
avoided
to
account
for
cessation
lag).
By
2013,
all
treatment
is
projected
to
be
installed,
and
yearly
system
costs
thereafter
are
constant,
representing
only
operations
and
maintenance
(
O&
M),
monitoring,
and
significant
excursion
yearly
costs.

Costs
and
benefits
are
adjusted
to
present
value
(
based
on
2003
dollars)
and
annualized
over
25
years
at
a
3
and
7
percent
social
discount
rate
to
generate
the
average
annualized
values.
Exhibit
9.3
compares
estimated
average
annualized
benefits
with
costs.
As
demonstrated
by
the
graphic
in
the
exhibit,
the
estimated
quantified
benefits
of
the
rule
are
generally
much
larger
than
the
estimated
costs.
EPA
recognizes
that
the
quantified
benefits,
based
on
reduced
cases
of
bladder
cancer,
as
shown
in
Exhibit
ES.
9,
could
be
zero
for
all
alternatives
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.
It
is
important
to
note,
however,
that
the
nonquantified
benefits
(
e.
g.,
reduction
in
developmental
and
reproductive
risk)
are
not
included
in
the
primary
benefits
analysis
but
could
be
substantial.

Exhibit
9.3
Estimated
Annualized
National
Costs
and
Benefits
($
Millions)

Note:
All
values
in
year
2000
dollars.

Source:
Derived
from
Exhibit
5.27
(
benefits)
and
Exhibit
6.19
(
costs).
Figure
represents
the
minimum
and
maximum
estimates
at
both
3
and
7
percent
social
discount
rates.

9.2
Effects
of
Uncertainties
on
the
Estimation
of
Net
National
Benefits
Detailed
discussions
of
the
assumptions
and
uncertainties
associated
with
national
benefits
and
costs
are
contained
in
Chapters
3,
5,
and
6.
A
summary
of
the
most
important
assumptions,
and
the
effects
of
uncertainty
in
those
assumptions
on
the
benefits
and
cost
analyses,
are
presented
in
Exhibit
9.4.
See
Exhibits
3.26,
5.29,
and
6.23
for
a
full
listing
of
assumptions
for
which
there
is
uncertainty.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
6
July
2003
Exhibit
9.4
Effects
of
Uncertainties
on
National
Estimates
Assumptions
for
Which
There
Is
Uncertainty
Section
with
Full
Discussion
of
Uncertainty
Potential
Effect
on
Benefit
Estimate
Potential
Effect
on
Cost
Estimates
Underestimat
e
Overestimate
Unknown
Impact
Underestimat
e
Overestimate
Unknow
n
Impact
Value
of
reproductive
and
developmental
health
effects
avoided
is
not
quantified
in
primary
benefits
analysis
5.8.1
X
Low­
cost
alternatives
to
treatment
not
considered
6.4.1.2
X
IDSE
may
affect
compliance
forecast
7
X
X
Compliance
forecast
for
ground
water
and
small
surface
water
systems
may
be
overstated.
Safety
factor
for
chloramine
systems
may
be
too
high.
7
X
X
One
key
area
of
uncertainty
is
the
effect
of
the
IDSE
on
predictions
of
non­
compliance.
The
number
of
plants
predicted
to
change
technology
could
be
understated
because
plants
may
find
higher
TTHM
or
HAA5
concentrations
at
new
sites
identified
during
the
IDSE.
Because
treatment
changes
are
by
far
the
most
costly
component
of
this
rule,
this
could
have
a
significant
effect
on
costs.
However,
such
an
increase
in
treatment
changes
would
also
have
an
associated
benefit
derived
from
additional
DBP
reduction
beyond
that
currently
included
in
the
benefits
analysis.
Thus,
any
change
in
IDSE
results
would
tend
to
increase
both
costs
and
benefits.
IDSE
sensitivity
analyses
were
performed
for
both
costs
and
benefits
to
assess
these
possible
effects.
The
figures
in
Exhibits
9.5
and
9.6
compare
the
ranges
of
values
derived
for
these
sensitivity
analyses
to
the
range
of
values
derived
from
the
main
analysis
for
costs
and
benefits,
respectively.

The
exhibits
show
that
results
are
very
sensitive
to
changes
in
predicted
treatment
technologies
that
may
arise
out
of
IDSEs,
but
the
value
of
benefits
will
increase
by
a
greater
magnitude
than
the
corresponding
increase
in
costs.
While
the
high­
end
annualized
cost
estimate
could
almost
double
(
up
to
$
119
million),
the
corresponding
high­
end
annualized
bladder
cancer
benefits
estimate
could
more
than
triple
(
up
to
$
3
billion).
Thus,
the
uncertainty
component
of
the
economic
analysis
with
the
greatest
sensitivity
to
change
(
treatment
requirements
arising
from
IDSEs)
could
result
in
a
disproportionate
increase
in
benefits,
resulting
in
an
increase
in
the
margin
by
which
benefits
exceed
costs.
A
detailed
discussion
of
the
IDSE
sensitivity
analyses
for
benefits
and
costs
is
presented
in
Chapter
7.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
7
July
2003
Preferred
Alternative
IDSE
Sensitivity
0
100
200
Preferred
Alternative
IDSE
Sensitivity
2,000
2,500
3,000
0
500
1,000
1,500
Exhibit
9.5
IDSE
Sensitivity
Cost
Range
Comparison
($
Millions)

Note:
All
values
in
year
2000
dollars.

Source:
Derived
from
Chapter
6,
Exhibit
6.19
(
Preferred
Alternative),
and
Chapter
7,
Exhibit
7.4
(
IDSE
Sensitivity).

Exhibit
9.6
IDSE
Sensitivity
Benefit
Range
Comparison
($
Millions)

Note:
Monetized
benefits
reflect
estimated
bladder
cancer
cases
avoided
as
a
result
of
the
Stage
2
DBPR.
All
values
in
year
2000
dollars.

Source:
Derived
from
Chapter
5,
Exhibit
5.27
(
Preferred
Alternative),
and
Chapter
7,
Exhibit
7.2
(
IDSE
Sensitivity).

EPA
believes
that
these
high­
end
cost
estimates
are
unlikely
because
of
conservative
assumptions
used
to
predict
treatment
changes
that
may
lead
to
over­
predictions
in
costs.
For
example,
compliance
determination
for
plants
is
made
assuming
a
20
percent
margin
of
safety
under
the
MCLs.
Systems
complying
by
switching
to
chloramine
disinfection
may
choose
to
meet
the
Stage
2
MCLs
with
a
much
smaller
margin
of
safety,
since
chloramines
dampen
the
variability
of
DBP
concentrations
on
distribution
systems.
Also,
EPA
believes
that
the
estimated
number
of
ground
water
and
small
surface
water
plants
changing
technology
may
be
biased
upward
because
their
monitoring
requirements
and,
thus,
compliance
calculation
are
expected
to
be
very
similar
for
the
Stage
1
and
Stage
2
DBPRs.
The
Stage
1
DBPR
required
only
one
compliance
monitoring
location
(
at
the
point
of
maximum
residence
time)
for
producing
surface
water
systems
serving
between
500
and
10,000
people
and
for
all
ground
water
systems.
The
Stage
2
DBPR
requires
these
systems
to
add
an
additional
site
if
they
determine
that
their
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
8
July
2003
high
TTHM
and
high
HAA5
concentrations
do
not
occur
at
the
same
location.
If
systems
maintain
a
single
monitoring
location
for
the
Stage
2
DBPR,
as
many
are
expected
to
do,
calculation
of
compliance
will
produce
the
same
results
for
the
running
annual
average
(
RAA)
and
locational
running
annual
average
(
LRAA)
measure,
implying
that
they
are
not
likely
to
add
treatment
for
the
Stage
2
DBPR
if
they
comply
with
the
Stage
1
DBPR.

To
gauge
the
impact
of
the
potential
high
bias
in
the
compliance
forecast,
EPA
conducted
another
sensitivity
analysis,
which
assumed
that
no
surface
water
plants
serving
fewer
than
10,000
people
and
no
ground
water
plants
would
add
treatment
to
meet
Stage
2
DBPR
requirements
(
i.
e.,
only
costs
are
for
large
surface
water
systems).
Under
this
analysis,
the
average
cost
figures
are
reduced
from
$
59.1
million
or
$
64.6
million
to
$
21.4
million
or
$
25.1
million
using
a
3
percent
or
7
percent
discount
rate,
respectively,
for
the
Preferred
Regulatory
Alternative.
Chapter
7
contains
a
detailed
explanation
of
the
this
sensitivity
analysis
and
additional
results.

9.3
Breakeven
Analysis
One
way
to
evaluate
effectiveness
of
the
regulation
is
to
calculate
how
many
bladder
cancer
cases
would
have
to
be
avoided
annually
to
compensate
for
costs
(
i.
e.,
for
the
Stage
2
DBPR
to
"
break
even")
without
considering
adverse
reproductive
and
developmental
health
effects.
If
the
estimated
present
value
cost
of
the
rule
is
$
59.1
million
annually
(
3
percent
discount
rate)
or
$
64.6
million
annually
(
7
percent
discount
rate),
the
range
of
bladder
cancer
cases
that
must
be
avoided
annually
is
12
to
13
cases
using
the
WTP
for
lymphoma
as
the
basis
for
valuing
non­
fatal
cancer
cases,
and
25
to
27
cases
using
the
WTP
for
chronic
bronchitis
as
the
basis
for
valuing
non­
fatal
cases.
Exhibit
9.7
presents
these
breakeven
points.

Exhibit
9.7
Estimated
Breakeven
Points
(
Number
of
Bladder
Cancer
Cases
Avoided)

WTP
for
Lymphoma
as
Basis
for
Non­
Fatal
Cancer
Cases
WTP
for
Chronic
Bronchitis
as
Basis
for
Non­
Fatal
Cancer
Cases
3%
Discount
Rate
7%
Discount
Rate
3%
Discount
Rate
7%
Discount
Rate
12
13
25
27
Source:
Derived
from
Appendices
E,
F,
and
J.

As
stated
in
Chapter
5,
the
estimated
PAR
percentages
from
epidemiological
studies
range
from
2
percent
to
17
percent.
Those
values
are
"
best
estimates"
derived
from
the
study
data
and
are
the
values
used
in
the
quantitative
benefits
analysis
for
the
Stage
2
DBPR.
(
EPA
recognizes
that
the
number
of
cases
avoided
could
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
drinking
water
and
bladder
cancer).
Using
these
values
and
TTHM
as
an
indicator
for
all
DBP
removal,
between
21
and
182
bladder
cancer
cases
are
estimated
to
be
avoided
through
promulgation
of
the
Stage
2
DBPR.
The
breakeven
values
in
Exhibit
9.7
are
near
the
low
end
of
this
range.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
9
July
2003
9.4
Comparison
of
Regulatory
Alternatives
As
discussed
in
Chapter
4,
the
development
and
evaluation
of
regulatory
alternatives
was
undertaken
as
part
of
a
consultation
process
convened
under
the
Federal
Advisory
Committees
Act
(
FACA).
The
FACA
process
narrowed
hundreds
of
regulatory
options
down
to
four
major
alternatives
for
further
evaluation,
one
of
which
was
designated
in
an
Agreement
in
Principle
(
65
FR
83015
December
2000)
as
the
preferred
alternative.
These
four
alternatives
are
summarized
below.

Preferred
Alternative:
Maximum
contaminant
levels
(
MCLs)
of
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
measured
as
LRAAs;
bromate
MCL
of
10
µ
g/
L
measured
as
a
RAA
based
on
monthly
samples
taken
at
the
finished
water
point
(
no
change
in
bromate
MCL
from
the
Stage
1
DBPR).

Alternative
1:
MCLs
of
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
measured
as
LRAAs;
bromate
MCL
of
5
µ
g/
L
measured
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point
(
same
at
the
Preferred
Alternative
except
for
changing
the
bromate
MCL
from
the
Stage
1
DBPR
level).

Alternative
2:
MCLs
of
80
µ
g/
L
TTHM
and
60
µ
g/
L
HAA5
measured
as
the
single
maximum
value
for
any
sample
taken
during
the
year;
bromate
MCL
of
10
µ
g/
L
measured
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point.

Alternative
3:
MCLs
of
40
µ
g/
L
TTHM
and
30
µ
g/
L
HAA5
measured
as
RAAs
of
all
distribution
samples
taken;
bromate
MCL
of
10
µ
g/
L
measured
as
an
RAA
based
on
monthly
samples
taken
at
the
finished
water
point.

The
following
sections
evaluate
the
benefits
and
costs
of
decreasing
TTHM
occurrence
for
the
Stage
2
DBPR
Preferred
Alternative
in
comparison
to
the
three
alternatives.

9.4.1
Comparison
of
Reductions
in
DBP
Occurrence
Given
the
goal
of
the
Stage
2
DBPR
is
to
reduce
adverse
health
effects
by
reducing
exposure
to
DBPs
in
drinking
water,
a
useful
starting
point
for
comparing
regulatory
alternatives
is
a
comparison
of
the
DBP
reduction
estimated
for
each
alternative.
Exhibit
9.8
presents
percent
DBP
occurrence
reductions
for
the
Stage
2
DBPR
regulatory
alternatives.
The
reductions
presented
in
Exhibit
9.8
are
calculated
as
the
average
of
annual
plant
means
at
the
point
representing
average
residence
time
in
the
distribution
system
for
each
regulatory
alternative.

Although
Exhibit
9.8
shows
much
greater
percent
reductions
in
DBP
exposure
for
Alternatives
2
and
3,
these
figures
tell
very
little
without
further
evaluation.
Specifically,
these
values
need
to
be
evaluated
in
the
context
of
the
costs
and
benefits
of
each
alternative.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
10
July
2003
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)
Lower
(
5th
%
tile)
Upper
(
95th
%
tile)

Preferred
59.1
$
54.3
$
63.9
$
64.6
$
59.2
$
70.0
$
Alt.
1
182.3
$
165.1
$
199.6
$
195.1
$
175.9
$
214.3
$
Alt.
2
409.6
$
383.6
$
435.7
$
442.7
$
413.4
$
472.2
$
Alt.
3
594.3
$
556.3
$
631.9
$
644.2
$
601.1
$
686.9
$
Rule
Alternative
Total
Annualized
Cost
($
Millions)
3
Percent
Discount
Rate
7
Percent
Discount
Rate
Mean
Estimate
90
Percent
Confidence
Bound
Mean
Estimate
90
Percent
Confidence
Bound
Exhibit
9.8
Comparison
of
DBP
Reduction
(
of
Annual
Plant
Mean
TTHM
Data)

DBP
Indicator
Rule
Alternative
Average
Percent
DBP
Reduction
TTHM
Preferred
4.1%

Alternative
1
4.3%

Alternative
2
26.7%

Alternative
3
31.8%

Source:
Percent
reduction
derived
from
total
cancer
case
reductions
(
cases
reduced
by
Stage
2
divided
by
pre­
Stage
2
cases)
in
Appendix
E,
Exhibits
E.
17a,
E.
19a,
E.
20a,
and
E.
21a
for
the
Preferred
Alternative,
Alternative
1,
Alternative
2,
and
Alternative
3,
respectively.

9.4.2
Comparison
of
Benefits
and
Costs
To
make
meaningful
comparisons
between
regulatory
alternatives,
it
is
first
necessary
to
look
at
the
final
benefit
and
cost
numbers
derived
for
each.
Exhibit
9.9
presents
the
annualized
present
value
costs
for
each
alternative
considered,
followed
by
presentation
of
benefits
in
Exhibit
9.10.

Exhibit
9.9
Comparison
of
Annualized
Costs
for
Regulatory
Alternatives
Note:
90
percent
confidence
bounds
reflect
uncertainty
in
unit
treatment
costs.
Source:
Exhibit
6.24.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
11
July
2003
Exhibit
9.10
Comparison
of
Number
and
Annualized
Value
of
Estimated
Bladder
Cancer
Cases
Avoided
for
Regulatory
Alternatives
(
Millions,
2000$)
1
Discount
Rate,
WTP
for
Non­
Fatal
Cases
Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
2%
PAR
Value
Average
Annual
Number
of
Cases
Avoided
21
22
135
161
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3%
Lymphoma
$
113
($
18
­
258)
$
117
($
19
­
268)
$
773
($
116
­
1,675)
$
873
($
139
­
1,995)

7%
Lymphoma
$
98
($
16
­
224)
$
102
($
16
­
232)
$
636
($
101
­
$
1,452)
$
757
($
120
­
1,730)

3%
Bronchitis
$
55
($
13
­
120)
$
57
(
13
­
124)
$
356
($
81
­
776)
$
424
($
97
­
924)

7%
Bronchitis
$
48
($
11
­
104)
$
49
($
11
­
108)
$
309
($
71
­
673)
$
368
($
84
­
802)

17%
PAR
Value
Average
Annual
Number
of
Cases
Avoided
182
189
1,182
1,408
Annualized
Benefits
of
Cases
Avoided
(
90%
Confidence
Bounds)
2
3%
Lymphoma
$
986
($
157
­
2,253)
$
1,024
($
163
­
2340)
$
6,398
($
1,016
­
14,619)
$
7,621
($
1,211
­
17,415)

7%
Lymphoma
$
854
($
136
­
1,952)
$
887
($
141
­
2,027)
$
5,546
($
881
­
12,672)
$
6,607
($
1,050
­
15,097)

3%
Bronchitis
$
479
($
109
­
1,044)
$
498
($
114
­
1084)
$
3,109
($
709
­
6771)
$
3,704
($
845
­
8,066)

7%
Bronchitis
$
415
($
95
­
905)
$
431
($
99
­
940)
$
2,697
($
616
­
5,871)
$
3213
($
734
­
6,995)

Notes:
1.
Based
on
TTHM
as
indicator.
EPA
recognizes
that
the
lower
bound
estimate
may
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer
2.
The
90
percent
confidence
bounds
shown
in
the
exhibit
reflect
uncertainty
in
the
VSL,
WTP,
and
income
elasticity
adjustment.

Source:
Exhibit
5.28.

Although
summary
tables
of
both
costs
and
benefits
are
provided
for
evaluation,
tables
providing
direct
measures
of
net
benefits
(
benefits
minus
costs)
and
incremental
net
benefits
(
comparisons
of
net
benefits
between
alternatives)
have
not
been
included
in
this
analysis.
Since
significant
Stage
2
DBPR
benefits
are
potentially
attributable
to
avoidance
of
adverse
reproductive
and
developmental
health
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
12
July
2003
effects,
which
are
not
quantified
in
the
primary
benefits
analysis,
presentation
of
a
quantitative
benefits
and
costs
comparison
(
net
benefits)
would
not
be
representative
of
the
true
net
benefits
of
the
rule.
However,
evaluation
of
the
figures
in
Exhibits
9.9
and
9.10
does
show
that
benefits
are
very
likely
to
exceed
costs.
Equally
important,
the
addition
of
any
benefits
attributable
to
the
non­
quantified
categories
would
add
to
the
benefits
without
any
increase
in
costs,
making
it
likely
that
the
full
range
of
benefits
would
be
significantly
higher
than
the
values
presented
above.

As
shown
in
Exhibits
9.9
and
9.10,
estimated
costs
for
Alternative
1
are
more
than
twice
those
for
the
Preferred
Alternative,
though
quantified
benefits
based
on
bladder
cancer
cases
avoided
are
nearly
the
same.
The
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
they
were
concerned
that
lowering
the
bromate
level
to
5
µ
g/
L
could
have
adverse
effects
on
microbial
protection
(
see
Chapter
4
for
a
full
discussion).

The
range
of
quantified
benefits
increases
significantly
with
Alternatives
2
and
3.
However,
the
associated
costs
also
increase
significantly.
(
Cost
figures
in
Exhibit
ES.
9
show
estimated
values
between
$
384
and
$
682
million
per
year.)
Although
the
benefits
for
Alternatives
2
and
3
are
potentially
significant,
the
M­
DBP
Advisory
Committee
did
not
favor
this
alternative
because
it
believed
that
the
current
health
effects
data
are
not
certain
enough
to
warrant
such
a
potentially
expensive
regulation.

9.4.3
Cost­
Effectiveness
Evaluation
of
the
relative
merits
of
one
alternative
over
another
is
often
made
with
respect
to
cost­
effectiveness.
This
concept
can
be
defined
simply
as
getting
the
greatest
benefits
for
a
given
expenditure
or
imposing
the
least
cost
for
a
given
level
of
benefits.
Exhibit
9.11
depicts
the
annualized
value
of
estimated
benefits
and
costs
for
the
four
alternatives
at
a
3
percent
discount
rate
(
comparisons
at
a
7
percent
discount
rate
would
look
similar;
thus
they
were
not
included,
for
brevity).
Four
estimates
of
average
monetized
benefits
are
shown,
representing
2
and
17
percent
PAR
estimates
and
WTP
for
curable
lymphoma
and
chronic
bronchitis
as
the
basis
for
valuing
non­
fatal
bladder
cancer
cases
avoided.

For
each
alternative,
the
mean
of
its
benefit
estimate
is
graphed.
At
that
level
of
benefits,
there
is
a
corresponding
cost
estimate
shown.
The
trend
line
connects
the
mean
estimates
of
benefits
and
costs
for
each
alternative.
These
graphs
help
to
show
the
concept
of
cost­
effectiveness
and
to
compare
the
alternatives.
In
Exhibit
9.11,
any
alternative
to
the
right
of
and
below
the
other
alternatives
would
be
more
cost­
effective
and
"
dominate"
alternatives
that
provide
fewer
benefits
at
higher
costs.

The
alternatives
shown
in
Exhibit
9.11
map
the
boundaries
of
the
cost­
effective
alternatives.
In
addition
to
allowing
a
visual
test
of
cost­
effectiveness,
the
exhibit
shows
information
about
the
incremental
benefits
of
each
alternative.
Compared
to
Alternative
1,
the
Preferred
Alternative
achieves
comparable
benefits
at
a
relatively
lower
cost.
Alternatives
3
and
4
achieve
much
greater
benefits,
at
dramatically
higher
incremental
cost.
The
Preferred
Alternative
appears
to
be
the
best
value;
other
alternatives
have
either
higher
costs
for
nearly
the
same
level
of
benefits
(
Alternative
1)
or
much
greater
benefits,
at
dramatically
higher
costs
(
Alternatives
3
and
4).
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
13
July
2003
2%
PAR
value,
WTP
for
Lymphoma
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
800
$
900
$
1,000
Benefits
($
Millions)
Costs
($
Millions)

Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
17%
PAR
Value,
WTP
for
Lymphoma
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
0
$
1,000
$
2,000
$
3,000
$
4,000
$
5,000
$
6,000
$
7,000
$
8,000
$
9,000
Benefits
($
Millions)
Costs
($
Millions)

Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
Exhibit
9.11
Comparison
of
Annualized
Costs
and
Benefits
for
the
Stage
2
Regulatory
Alternatives
(
3
%
Discount
Rate)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
14
July
2003
2%
PAR
value,
WTP
for
Bronchitis
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
800
$
900
$
1,000
Benefits
($
Millions)
Costs
($
Millions)

Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
17%
PAR
value,
WTP
for
Bronchitis
$
0
$
100
$
200
$
300
$
400
$
500
$
600
$
700
$
0
$
1,000
$
2,000
$
3,000
$
4,000
$
5,000
$
6,000
$
7,000
$
8,000
$
9,000
Benefits
($
Millions)
Costs
($
Millions)

Preferred
Alternative
Alternative
1
Alternative
2
Alternative
3
Exhibit
9.11
Comparison
of
Annualized
Costs
and
Benefits
for
the
Stage
2
Regulatory
Alternatives
(
3
%
Discount
Rate)
(
Continued)
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
15
July
2003
2%
PAR
Estimate
17%
PAR
Estimate
2%
PAR
Estimate
17%
PAR
Estimate
Preferred
Alt.
1
Alt.
2
Alt.
3
Preferred
2.8
$
0.3
$
3.1
$
0.4
$
Alt.
1
8.4
$
1.0
$
9.0
$
1.0
$
Alt.
2
3.0
$
0.3
$
3.3
$
0.4
$
Alt.
3
3.7
$
0.4
$
4.0
$
0.5
$

Preferred
Alt.
1
Alt.
2
Alt.
3
Causality
has
not
been
established,
and
numbers
and
types
of
cases
avoided,
as
well
as
the
value
of
such
cases,
were
not
quantified
in
the
primary
benefits
analysis.
Given
the
numbers
of
women
of
child
bearing
age
exposed
(
58
million),
the
evidence
indicates
that
the
number
of
cases
and
the
value
of
preventing
those
cases
could
be
significant.
See
results
of
the
illustrative
calculation
in
Section
5.9
Avoided
Adverse
Reproductive
and
Developmental
Health
Effects
N/
A
Benefit
Category
DBP
Surrogate
Qualitative
assessment
indicates
that
the
value
of
other
health
benefits
could
be
positive
and
significant.
Cost
Per
Case
Avoided
(
7%
Discount
Rate)

Avoided
Cases
of
Bladder
Cancer
Other
Health
and
Non­
Health
Effects
Avoided
N/
A
Cost
Per
Case
Avoided
(
3%
Discount
Rate)

Rule
Alternative
TTHM
Note:
Values
presented
in
figures
are
annualized
present
values
in
year
2000
dollars.
Estimates
are
discounted
to
2003.
Source:
Exhibits
9.9
and
9.10.
For
the
Stage
2
DBPR
alternatives,
cost­
effectiveness
may
also
be
evaluated
in
terms
of
the
cost
for
each
case
avoided.
EPA
has
performed
this
analysis
for
the
quantified
benefits
of
the
Stage
2
DBPR.
Although
a
similar
analysis
cannot
be
made
for
the
unquantified
benefits
of
the
rule,
it
is
expected
that
the
results
would
follow
the
same
general
pattern.
For
purposes
of
evaluating
cost­
effectiveness,
the
lower
the
cost
per
case
avoided,
the
more
cost­
effective
the
alternative
is
believed
to
be.
Exhibit
9.12
presents
the
cost
per
case
avoided
for
each
regulatory
alternative.

Exhibit
9.12
shows
that
the
lowest
estimate
of
cost
per
case
avoided
for
the
Preferred
Alternative
is
always
lower
than
or
equal
to
the
lowest
estimate
of
cost
per
case
avoided
for
the
other
alternatives,
indicating
that
the
Preferred
Alternative
is
the
most
cost­
effective
by
this
measure.
Alternatives
2
and
3
have
costs
per
case
avoided
closest
to
those
of
the
Preferred
Alternative.
However,
as
discussed
in
the
evaluation
above,
there
are
overriding
issues
regarding
cost
in
relation
to
the
uncertainty
in
the
health
effects
data
that
led
EPA
to
select
the
Preferred
Alternative.
The
remaining
alternative
(
Alternative
1)
is
the
least
cost­
effective
by
the
measure
of
cost
per
illness
avoided
and
also
has
other
overriding
concerns
(
i.
e.,
the
possible
compromising
of
microbial
protection).

Exhibit
9.12
Comparison
of
Estimated
Cost
Per
Case
Avoided
for
the
Regulatory
Alternatives
($
Millions,
2000$)

Notes:
Cost
per
case
avoided
values
represent
present
values
in
year
2000
dollars
($
Millions).
Estimates
are
discounted
to
2003.

Source:
Derived
from
estimated
cases
avoided
and
national
annualized
costs
presented
in
Exhibits
9.9
and
9.10.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
9­
16
July
2003
9.5
Summary
of
Conclusions
The
following
is
a
summary
of
the
important
points
that
must
be
considered
when
weighing
the
benefits
and
costs
of
the
Stage
2
DBPR.

1)
The
quantified
benefits
estimate
is
potentially
understated
because
it
does
not
include
the
benefits
for
reductions
in
adverse
reproductive
and
developmental
health
effects,
other
health
effects,
and
non­
health
effects
associated
with
DBP
reduction
(
Exhibits
9.1
and
9.10).
At
the
same
time,
EPA
recognizes
that
the
low
end
of
the
quantified
benefits
estimates
could
be
as
low
as
zero
since
causality
has
not
yet
been
established
between
exposure
to
chlorinated
water
and
bladder
cancer.

2)
The
mean
cost
estimate
of
$
59.1
(
3
percent
discount
rate)
to
$
64.6
million
(
7
percent
discount
rate)
represents
EPA's
best
estimate
of
the
monetary
impacts
of
the
Stage
2
DBPR.
In
addition,
sensitivity
analyses
reflecting
uncertainties
in
IDSE
predictions
show
that,
for
any
potential
higher
cost
estimate,
there
will
likely
be
an
even
greater
increase
in
the
benefits
(
Exhibits
9.5
and
9.6).

3)
The
Preferred
Alternative
provides
the
greatest
benefits
at
a
cost
level
that
is
considered
reasonable
(
i.
e.,
is
not
cost
prohibitive)
given
the
uncertainties
in
health
effects
data.
Although
Alternatives
2
and
3
have
a
greater
benefit,
EPA
rejected
these
alternatives
because
it
is
believed
that
the
health
effects
data
are
not
certain
enough
to
warrant
such
expensive
regulations
(
Exhibits
9.9
and
9.10).

4)
Evaluation
of
the
cost­
effectiveness
of
the
Preferred
Alternative
shows
it
to
be
the
most
effective
according
to
the
measures
evaluated
(
Exhibits
9.11
and
9.12).

5)
The
breakeven
points
for
the
estimated
costs
associated
with
the
Stage
2
DBPR
range
from
12
to
13
annual
bladder
cancer
cases
using
the
WTP
for
lymphoma
as
the
basis
for
valuing
non­
fatal
cancer
cases,
and
25
to
27
annual
bladder
cancer
cases
using
the
WTP
for
chronic
bronchitis
as
the
basis
for
valuing
non­
fatal
cases.
These
are
near
the
low
end
of
the
range
of
estimated
bladder
cancer
cases
avoided
(
21
to
182).

As
a
result
of
all
these
considerations,
EPA
believes
that
the
annual
benefits
of
the
Stage
2
DBPR
will
likely
exceed
the
annualized
national
costs
and
will
be
effective
in
minimizing
the
risks
to
consumers
from
exposure
to
DBPs
in
drinking
water.
Economic
Analysis
for
the
Stage
2
DBPR
Proposal
R­
1
July
2003
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2003
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S.
Environmental
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2003c.
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U.
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2003d.
Drinking
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U.
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2003e.
Drinking
Water
Criteria
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U.
S.
Environmental
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2003f.
Drinking
Water
Criteria
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U.
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Environmental
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U.
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Environmental
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U.
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Environmental
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2003.

U.
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Environmental
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Surface
Water
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Arlington,
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2003.

U.
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Environmental
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Environmental
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2003.
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DBPR
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2003
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S.
Environmental
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2003q.
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2003.
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Environmental
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U.
S.
Environmental
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Technical
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U.
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U.
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U.
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Environmental
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2001.

U.
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Environmental
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RSAC­
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005.
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U.
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Environmental
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Environmental
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U.
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Environmental
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2000n.
Stage
2
M­
DBP
Agreement
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Disinfection
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M­
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Federal
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2000.
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Environmental
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2000p.
Stage
2
M/
DBP
FACA
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November
1997
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2000.
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Environmental
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U.
S.
Environmental
Protection
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2000r.
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MX:
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U.
S.
Environmental
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2000s.
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Capita
Water
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96
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Technology.
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0046
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99­
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U.
S.
Environmental
Protection
Agency.
1999a.
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Illness
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Office
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Pollution
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Toxics.
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Cost
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September,
1999.
54
pp.

U.
S.
Environmental
Protection
Agency.
1999b.
Draft
Methodology
for
Assessing
Regulatory
Impacts
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Technical,
Managerial,
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Spreadsheet
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xls).

U.
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Environmental
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1999c.
Health
Assessment
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External
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Science
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Economic
Analysis
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Stage
2
DBPR
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R­
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July
2003
U.
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Environmental
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Agency.
1999d.
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Risk
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Risk
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Environmental
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1998a.
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Stage
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002.
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U.
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Environmental
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1998b.
Regulatory
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Analysis
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Interim
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Surface
Water
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Washington,
DC.
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003.
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1998.

U.
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Environmental
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Agency.
1998c.
National­
Level
Affordability
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Beecher,
Ph.
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August,
1998.

U.
S.
Environmental
Protection
Agency.
1998d.
Variance
Technology
Findings
for
Contaminants
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Before
1996.
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1998.
EPA
815­
R­
98­
003.

U.
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Environmental
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1998e.
Guidance
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1998.
EPA
816­
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U.
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Environmental
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1998f.
National
Primary
Drinking
Water
Regulations;
Disinfectants
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Byproducts;
Notice
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Data
Availability;
Proposed
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Fed.
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1998
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Environmental
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1998g.
Health
Risks
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Fetuses,
Infants,
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Children
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19,
1998.
EPA
815­
B­
98­
009.
PB
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U.
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Environmental
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Agency.
1998h.
Quantification
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Cancer
Risk
from
Exposure
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Water.
Office
of
Science
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Office
of
Water.
Washington,
DC.
March
13,
1998.

U.
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Environmental
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1998i.
Health
Risk
Assessment/
Characterization
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Water
Disinfectant
Byproduct
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Office
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Technology,
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Water.
Washington,
DC.
March
13,
1998.

U.
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Environmental
Protection
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1998j.
Health
Risk
Assessment/
Characterization
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Water
Disinfectant
Byproduct
Chloroform.
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Science
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Water.
Washington,
DC.
March
13,
1998.

U.
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Environmental
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1998k.
National
Primary
Drinking
Water
Regulations:
Disinfectants
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Disinfection
Byproducts;
Final
Rule.
Federal
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63(
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69476.
December
16,
1998.

U.
S.
Environmental
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Agency.
1998l.
National
Primary
Drinking
Water
Regulations:
Interim
Enhanced
Surface
Water
Treatment;
Final
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December
16,
1998.
Economic
Analysis
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DBPR
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July
2003
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S.
Environmental
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1998m.
Comment
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U.
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Environmental
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1997a.
Summaries
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New
Health
Effects
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Office
of
Science
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Technology,
Office
of
Water.
Washington,
DC.
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1997.

U.
S.
Environmental
Protection
Agency.
1997b.
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Benefits
and
Costs
of
the
Clean
Air
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1970­
1990.
Prepared
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S.
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U.
S.
Environmental
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Agency.
1997c.
Community
Water
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R­
97­
001b.

U.
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Environmental
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1997d.
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Water
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Water.
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1997.
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R­
97­
001b.

U.
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Environmental
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Agency.
1997e.
Comment
Response
Database
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1
Disinfection
Byproducts
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U.
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Environmental
Protection
Agency.
1997f.
National
Primary
Drinking
Water
Regulations;
Disinfectants
and
Disinfection
Byproducts;
Notice
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Data
Availability;
Proposed
Rule.
Fed.
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November
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1997.

U.
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Environmental
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Quality
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Project
Plan
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Implementation
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U.
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Environmental
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U.
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Environmental
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Economic
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1996c.
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U.
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Environmental
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U.
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U.
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Disinfection
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July
2003
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