### EPA 815-R-00-026



# Arsenic in Drinking Water Rule
Economic Analysis

Developed for:

Office of Ground Water and Drinking Water

U.S. Environmental Protection Agency
401 M Street, S.W. Washington, DC 20460

John B. Bennett Work Assignment Manager

Developed by:

Abt Associates Inc. 4800 Montgomery Lane
Bethesda, MD 20814

Gerald D. Stedge, Ph.D. Principal Investigator

December 2000

## Contents

Chapter 1 : Executive Summary

................................................... 1-1

1.1 Regulatory Background

............................................ 1-1

1.2 Health Effects of Arsenic

........................................... 1-1

1.3 Regulatory Alternatives Considered

................................... 1-2

1.4 Benefits and Costs of the Proposed Rule

............................... 1-3

Chapter 2 : Need for the Revised Rule

.............................................. 2-1

2.1 Introduction

........................................................ 2-1

2.2 Public Health Concerns To Be Addressed

................................. 2-2

2.2.1 Health Effects of Arsenic

..................................... 2-2

2.2.2 Sources and Mechanisms of Exposure

........................... 2-4

2.3 Regulatory History

................................................ 2-5

2.4 Rationale for the Regulation

......................................... 2-7

2.4.1 Statutory Authority

.......................................... 2-8

2.4.2 Economic Rationale for Regulation

.............................. 2-8

Chapter 3 : Consideration of Regulatory Alternatives

................................... 3-1

3.1 Regulatory Approaches

............................................ 3-1

3.1.1 Determining the Standard

..................................... 3-1

3.1.2 Determining the MCLG

...................................... 3-1

3.1.3 Determining an MCL

........................................ 3-2

3.1.4 Variances

................................................. 3-3

3.1.5 Analytical Methods

......................................... 3-3

3.2 Regulatory Alternatives Considered and Final Rule

........................ 3-3

3.2.1 Applicability

............................................... 3-4

3.2.2 Maximum Contaminant Level

.................................. 3-4

3.2.3 Monitoring

................................................ 3-4

3.2.4 Compliance Technologies and Variances

......................... 3-5

3.2.5 Monitoring Waivers

......................................... 3-5

3.2.6 Implementation

............................................. 3-6

Chapter 4 : Baseline Analysis

..................................................... 4-1

4.1 Introduction

..................................................... 4-1

4.2 Industry Profile

................................................... 4-1

4.2.1 Definitions

................................................ 4-1

4.2.2 Sources of Industry Profile Data

................................ 4-2

4.2.3 Number and Size of Public Water Systems

....................... 4-2

4.2.4 System Size and Population Served

............................. 4-4

i ii

### 4.2.5 Number of Entry Points

...................................... 4-6

4.2.6 Number of Households

...................................... 4-6

4.2.7 Production Profile

.......................................... 4-7

4.2.8 Treatment Profile

.......................................... 4-10

4.3 Occurrences of Arsenic

........................................... 4-10

Chapter 5 : Benefits Analysis

..................................................... 5-1

5.1 Nature of Regulatory Benefits

........................................ 5-1

5.2 Health Effects

.................................................... 5-1

5.2.1 Overview

................................................. 5-1

5.2.2 Carcinogenic Effects

........................................ 5-2

5.2.3 Non-carcinogenic Effects

..................................... 5-3

5.2.4 Susceptible Subgroups

....................................... 5-5

5.3 Quantitative Benefits of Avoiding Cancer

............................... 5-7

5.3.1 Risk Assessment for Cancer Resulting from Arsenic Exposure

.......... 5-7

5.3.2 Community Water Systems

................................... 5-8

5.3.3 Non-Transient Non-Community Water Systems

................... 5-15

5.4 Risk Assessment Results and Benefit Estimates

.......................... 5-20

5.4.1 Cases Avoided

........................................... 5-20

5.4.2 Economic Measurements of the Value of Risk Reduction

............ 5-22

5.4.3 Estimates of Cancer Health Benefits of Arsenic Reduction

............ 5-25

5.5 Latency and Other Adjustments: A Sensitivity Analysis

.................... 5-26

5.5.1 SAB Recommendations

..................................... 5-26

5.5.2 Analytical Approach

........................................ 5-28

5.5.3 Results

.................................................. 5-32

5.6 Other Benefits of Reductions in Arsenic Exposure

........................ 5-35

Chapter 6 : Cost Analysis

....................................................... 6-1

6.1 Introduction

..................................................... 6-1

6.2 Methodology

.................................................... 6-1

6.2.1 Description of Available Technologies

............................ 6-1

6.2.2 Unit Costs and Compliance Assumptions

......................... 6-4

6.2.3 Monitoring and Administrative Costs

........................... 6-13

6.3 Results

........................................................ 6-27

6.3.1 National Costs

............................................ 6-27

6.3.2 Costs by System Size and Type

............................... 6-29

6.3.3 Costs per Household

....................................... 6-34

6.4 National Compliance Costs Uncertainty Analysis

........................ 6-38

Chapter 7 : Comparison of Costs and Benefits

........................................ 7-1

7.1 Introduction

..................................................... 7-1

iv

### 7.2 Summary of National Costs and Benefits

............................... 7-1

7.2.1 National Cost Estimates

...................................... 7-1

7.2.2 National Benefits Estimates

.................................... 7-1

7.3 Comparison of Benefits and Costs

.................................... 7-1

7.3.1 National Net Benefits and National Benefit-Cost Comparison

.......... 7-2

7.3.2 Cost-Effectiveness

.......................................... 7-5

7.4 Other Benefits

................................................... 7-7

7.5 Benefits-Costs Uncertainty Analysis

................................... 7-9

Chapter 8 : Economic Impact Analyses

............................................. 8-1

8.1 Introduction

..................................................... 8-1

8.2 Regulatory Flexibility Act and Small Business Regulatory Enforcement Fairness Act 8-1

8.2.1 Description of the Initial Regulatory Flexibility Analysis

............... 8-2

8.2.2 Initial Regulatory Flexibility Analysis Results

....................... 8-8

8.2.3 Summary of EPA’s Small Business Consultations

.................. 8-9

8.2.4 Small System Affordability

................................... 8-12

8.3 Coordination With Other Federal Rules

............................... 8-15

8.3.1 Ground Water Rule (GWR)

.................................. 8-15

8.3.2 Radon

.................................................. 8-16

8.3.3 Microbial and Disinfection By-Product Regulations

................. 8-16

8.4 Minimization of Economic Burden

.................................... 8-16

8.5 Unfunded Mandates Reform Act

.................................... 8-17

8.5.1 Social Costs and Benefits

.................................... 8-18

8.5.2 State Administrative Costs

................................... 8-19

8.5.3 Future Compliance Costs and Disproportionate Budgetary Effects

..... 8-19

8.5.4 Macroeconomic Effects

..................................... 8-26

8.5.5 Consultation with State, Local, and Tribal Governments

............. 8-26

8.5.6 State, Local, and Tribal Government Concerns

.................... 8-28

8.5.7 Regulatory Alternatives Considered

............................ 8-28

8.5.8 Impacts on Small Governments

............................... 8-28

8.6 Effect of Compliance with the Arsenic Rule on the Technical, Financial, and Managerial
Capacity of Public Water Systems

................................... 8-29

8.7 Paperwork Reduction Act

......................................... 8-30

8.8 Protecting Children from Environmental Health Risks and Safety Risks

........ 8-31

8.9 Environmental Justice

............................................. 8-31

8.10 Health Risk Reduction and Cost Analysis

.............................. 8-31

8.10.1 Quantifiable and Non-Quantifiable Health Risk Reduction Benefits

..... 8-32

8.10.2 Quantifiable and Non-Quantifiable Costs

........................ 8-35

v

### References

Appendix A. Decision Tree and Large System Costs
Appendix B. Assumptions and Methodology for Estimating Cancer Risks Avoided and Benefits
Appendix C. Cost Model Methodology
Appendix D. What If Cost Sensitivity Analysis
Appendix E. Benefits and Costs by System Size Category

vi

## Exhibits

Exhibit 1-1
Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and Non-Quantifiable

Health Benefits from Reducing Arsenic in PWSs

................................ 1-4

Exhibit 1-2
Total National Cost of Compliance ($ millions)

................................. 1-5

Exhibit 1-3
Net Benefits and Benefit-Cost Ratios of Each Regulatory Option ($ millions)

........... 1-6

Exhibit 4-1

Total Number of Systems by Size, Type, and Ownership

......................... 4-3

Exhibit 4-2

Total Population Served of Water Systems by Source Water, System Type, and Service
Population Category

..................................................... 4-4

Exhibit 4-3

Characteristics of NTNC Systems Affected by the Revised Rule

.................... 4-5

Exhibit 4-4

Average Number of Entry Points Per Ground Water System

....................... 4-6

Exhibit 4-5
Water Consumption per Residential Connection

................................ 4-7

Exhibit 4-6
Design Capacity of CWS Plants by Source, Ownership, and System Size

............. 4-8

Exhibit 4-7
Daily Production of CWS Plants by Source, Ownership, and System Size

............. 4-9

Exhibit 4-8
Percentage of CWSs with Various Treatments in Place

.......................... 4-10

Exhibit 4-9

Arsenic Occurrence in CWSs at Various Concentration Levels (μg/L)

............... 4-11

Exhibit 4-10

Statistical Estimates of Numbers of Systems with Average Finished Arsenic Concentrations in
Various Ranges

....................................................... 4-12

Exhibit 5-1
Adverse Non-carcinogenic Health Effects Reported in Humans in NRC 1999 as Potentially

Associated with Arsenic, by Organ System Affected

............................. 5-4

Exhibit 5-2
Components of the Bladder Cancer Risk Assessment

............................ 5-8

Exhibit 5-3
Life-long Relative Exposure Factors

........................................ 5-10

Exhibit 5-4

vii

### Cancer Risks for U.S. Populations Exposed at or Above MCL Options,

After Treatment

....................................................... 5-14

Exhibit 5-5
Exposure Factors Used in the NTNC Risk Assessment

......................... 5-16

Exhibit 5-6
Composition of NTNCs

................................................. 5-18

Exhibit 5-7
Mean Cancer Risks (Bladder and Lung Combined), Exposed Population, and Annual Cancer

Benefits in NTNCs

..................................................... 5-19

Exhibit 5-8
Sensitive Group Evaluation of Lifetime Combined Cancer Risks

................... 5-19

Exhibit 5-9
Annual Bladder Cancer Cases Avoided from Reducing Arsenic in CWSs

and NTNCs

.......................................................... 5-21

Exhibit 5-10

Lifetime Avoided Medical Costs for Survivors

................................ 5-25

Exhibit 5-11

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and Non-Quantifiable
Health Benefits from Reducing Arsenic in PWSs

............................... 5-26

Exhibit 5-12
Sensitivity of the Primary VSL Estimate to Changes in Latency Period Assumptions, Income
Growth, and Other Adjustments

........................................... 5-30

Exhibit 5-13
Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits Estimates to
Changes in VSL Adjustment Factor Assumptions (3% discount rate)

............... 5-33

Exhibit 5-14
Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits Estimates to
Changes in VSL Adjustment Factor Assumptions (7% discount rate)

............... 5-34

Exhibit 6-1
Arsenic Rule Treatment Trains by Compliance Technologies Component

with Associated Removal Efficiencies

........................................ 6-3

Exhibit 6-2a
System Compliance Technology Costs Assuming Influent Concentration of 11 μg/L and MCL
of 10 μg/L

............................................................ 6-5

Exhibit 6-2b
System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL
of 10 μg/L

............................................................ 6-9

Exhibit 6-3
Unit Resources Required for Monitoring, Implementation, and Administration

......... 6-14

Exhibit 6-4a

viii

### Estimated One-time State Resources Required for Initiation of the Arsenic Rule

........ 6-15

Exhibit 6-4b
Estimated One-time System Resources Required for Initiation of the Arsenic Rule

...... 6-16

Exhibit 6-5
Flow Regression Parameters by Water Source and System Ownership

.............. 6-20

Exhibit 6-6
Arsenic Occurrence Distribution (Log-Normal Regression Results)

................. 6-21

Exhibit 6-7
Summary of Recommended Cost of Capital Estimates (as of March 1998)

........... 6-23

Exhibit 6-8
Non-Transient Non-Community System Characteristics and
Compliance Decision Tree

............................................... 6-25

Exhibit 6-9
Annual Treatment Costs for Three Large CWSs Expected to
Undertake or Modify Treatment Practice to Comply with the Arsenic Rule

........... 6-27

Exhibit 6-10
Annual National System and State Compliance Costs

........................... 6-28

Exhibit 6-11
Total Annual CWS Treatment Costs Across MCL Options by System Size

.......... 6-29

Exhibit 6-12
Total Annual NTNC Treatment Costs at MCL 3 μg/L by System Service Type

(3% Discount Rate)

.................................................... 6-30

Exhibit 6-13
Total Annual NTNC Treatment Costs at MCL 5 μg/L by System Service Type

(3% Discount Rate)

.................................................... 6-31

Exhibit 6-14
Total Annual NTNC Treatment Costs at MCL 10 μg/L by System Service Type

(3% Discount Rate)

.................................................... 6-32

Exhibit 6-15
Total Annual NTNC Treatment Costs at MCL 20 μg/L by System Service Type

(3% Discount Rate)

.................................................... 6-33

Exhibit 6-16
Number of Households in CWSs Expected to Treat
by Size Category and MCL (μg/L) Option

................................... 6-34

Exhibit 6-17
Average Annual Household Costs Across MCL Options by System Size

............ 6-35

Exhibit 6-18

Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People

MCL 3 μg/L

......................................................... 6-36

Exhibit 6-19

ix

### Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People

MCL 5 μg/L

......................................................... 6-36

Exhibit 6-20

Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People

MCL 10 μg/L

........................................................ 6-37

Exhibit 6-21

Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People

MCL 20 μg/L

........................................................ 6-37

Exhibit 6-22
National Compliance Costs Uncertainty Analysis
Frequency Distribution (MCL 10 μg/L)

...................................... 6-39

Exhibit 6-23
National Compliance Costs Uncertainty Analysis
Cumulative Distribution (MCL 10 μg/L)

..................................... 6-40

Exhibit 7-1
Summary of Annual National Net Benefits and Benefit-Cost Ratios

.................. 7-2

Exhibit 7-2 Comparison of Costs and Benefits (7% Discount Rate, in $ millions)

................. 7-3

Exhibit 7-3 Comparison of Incremental Costs and Benefits (7% Discount Rate, in $ millions)

........ 7-4

Exhibit 7-4
Cost per Cancer Case Avoided

............................................ 7-5

Exhibit 7-5
Comparison of Annual Costs to Cases of Cancer per Year

(7% Discount Rate)

..................................................... 7-6

Exhibit 7-6
Incremental Cost per Incremental Cancer Case Avoided
(7% Discount Rate, in $ millions)

........................................... 7-7

Exhibit 7-7

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and Non-Quantifiable
Health Benefits from Reducing Arsenic in PWSs

................................ 7-8

Exhibit 7-8
National Compliance Costs and Benefits Uncertainty Analysis
Cumulative Cost Distribution vs. Benefits Range (MCL 10 μg/L)

.................... 7-9

Exhibit 8-1
Profile of the Universe of Small Water Systems

x

### Regulated Under the Arsenic Rule

.......................................... 8-5

Exhibit 8-2
Annual Cost of Compliance Costs as a Percentage of Revenues
by Type of Small Entity (PWSs that are Expected to Modify or Install Treatment at an MCL =

10 μg/L)

............................................................. 8-7

Exhibit 8-3
Number of CWSs Expected to Undertake or Modify Treatment Practice

MCL 10 μg/L

......................................................... 8-8

Exhibit 8-4
Mean Annual Costs to Households Served by CWSs, by Size Category

............. 8-14

Exhibit 8-5
Average Annual Cost per CWS Exceeding the MCL, by Ownership

................ 8-21

Exhibit 8-6
Annual Compliance Costs per Household for CWSs Exceeding MCLs

.............. 8-23

Exhibit 8-7
Annual Compliance Costs per Household for CWSs Exceeding MCLs,

as a Percent of Median Household Income

................................... 8-24

Exhibit 8-8
Total Annual NTNC Treatment Costs at MCL 10 μg/L by System Service Type

(3% Discount Rate)

.................................................... 8-25

Exhibit 8-9
Annual Bladder Cancer Cases Avoided from Reducing Arsenic

in CWSs and NTNCs

.................................................. 8-33

Exhibit 8-10
Annual Lung Cancer Cases Avoided from Reducing Arsenic

in CWSs and NTNCs

.................................................. 8-33

Exhibit 8-11
Annual Total Cancer Cases Avoided from Reducing Arsenic

in CWSs and NTNCs

.................................................. 8-34

Exhibit 8-12

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and Non-Quantifiable
Health Benefits from Reducing Arsenic in PWSs

............................... 8-35

Exhibit 8-13 Summary of the Total Annual National Costs of Compliance ($ millions)

............. 8-36

Exhibit 8-14
Mean Annual Costs per Household in CWSs

................................. 8-37

Exhibit 8-15 Cost per Cancer Case Avoided ($ millions)

.................................. 8-38

xi

## Chapter 1: Executive Summary

1.1 Regulatory Background

An enforceable standard of 50 μg/L currently exists for arsenic in community water systems under the
National Interim Primary Drinking Water Regulations (40 CFR 59566). In §1412(b)(12)(A) of the
SDWA, as amended in 1996, Congress specifically directed EPA to issue a final rule by January 1,
2001. Congress recently changed the deadline for the final rule to June 22, 2001 (Public Law 106­

377).

This document analyzes the impacts of the revised rule, which changes the current standard as follows:

(1) Reduces the current MCL for arsenic in community water systems from 50 μg/L to 10

μg/L;

(2) Requires non-transient non-community (NTNC) water systems to come into

compliance with the new standard; and

(3) Revises the current monitoring requirements to make them consistent with the Standard

Monitoring Framework (40 CFR 141.23(c)).

1.2 Health Effects of Arsenic

Arsenic’s carcinogenic role was noted over 100 years ago (NCI, 1999) and has been studied ever

since. The Agency has classified arsenic as a Class A human carcinogen, “based on sufficient evidence
from human data. An increased lung cancer mortality was observed in multiple human populations
exposed primarily through inhalation. Also, increased mortality from multiple internal organ cancers
(liver, kidney, lung, and bladder) and an increased incidence of skin cancer were observed in
populations consuming drinking water high in inorganic arsenic.”

A 1999 NRC report on arsenic states that “epidemiological studies ... clearly show associations of

arsenic with several internal cancers at exposure concentrations of several hundred micrograms per liter
of drinking water.” Ten epidemiological studies covering eight organ systems have quantitative data for

risk assessment (NRC, 1999, Table 4-1). The organ systems where cancers in humans have been
identified include skin, bladder, lung, kidney, nasal cavity, liver, and prostate.

Table 10-6 of the same NRC report provides risk parameters for three cancers: bladder, lung, and liver

cancer. Considering all cancers in aggregate, the NRC states that “considering the data on bladder and
lung cancer in both sexes noted in the studies ... a similar approach for all cancers could easily result in
a combined cancer risk on the order of 1 in 100" (at the current MCL of 50 μg/L).

New data provide additional health effects information on both carcinogenic and noncarcinogenic

effects of arsenic. A recent study by Tsai et al. (1999) of a population that has been studied over many

Chapter 1, Executive Summary 1-1 Arsenic in Drinking Water Rule EA

### years in Taiwan has provided standardized mortality ratios (SMRs) for 23 cancerous and noncancerous causes of death in women and 27 causes of death in men at statistically significant levels in an
area of Taiwan with elevated arsenic exposures (Tsai et al., 1999). SMRs are an expression of the

ratio between deaths that were observed in an area with elevated arsenic levels and those that were
expected to occur, based on the mortality experience of the populations in nearby areas without

elevated arsenic levels. Drinking water (250-1,140 μg/L) and soil (5.3-11.2 mg/kg) in the Tsai et al.
(1999) population study had very high arsenic content.

Tsai et al. (1999) identified “bronchitis, liver cirrhosis, nephropathy, intestinal cancer, rectal cancer,
laryngeal cancer, and cerebrovascular disease” as possibly “related to chronic arsenic exposure via
drinking water,” which had not been reported before. In addition, the study area had upper respiratory
tract cancers previously only related to occupational inhalation. High male mortality rate (SMR > 3)
existed for bladder, kidney, skin, lung, and nasal cavity cancers and for vascular disease. However, the
authors noted that the mortality range was marginal for leukemia, cerebrovascular disease, liver
cirrhosis, nephropathy, and diabetes. Females also had high mortalities for laryngeal cancer. There are,
of course, possible differences between the population and health care in Taiwan and the United States.
For example, arsenic levels in the U.S. are not as high as they were in the study area of Taiwan.
However, the study gives an indication of the types of health effects that may be associated with arsenic
exposure via drinking water.

Arsenic interferes with a number of essential physiological activities, including the actions of enzymes,
essential cations, and transcriptional events in cells (NRC, 1999). A wide variety of adverse health
effects have been associated with chronic ingestion of arsenic in drinking water, occurring at various
exposure levels.

1.3 Regulatory Alternatives Considered

In regulating a contaminant, EPA first sets a maximum contaminant level goal (MCLG), which
establishes the contaminant level at which no known or anticipated adverse health effects occur.
MCLGs are non-enforceable health goals. For this rulemaking, EPA is setting an MCLG of zero. EPA
then sets an enforceable maximum contaminant level (MCL) as close as technologically possible to the

MCLG. In addition, EPA may use its discretion in setting the MCL by choosing an MCL that is
protective of public health while also ensuring that the quantified and non-quantified costs are justified
by the quantified and non-quantified benefits of the rule. For this rulemaking, EPA is setting an MCL of
10 μg/L. Chapter 3 describes the process by which EPA determined both the MCLG and the MCL.

EPA considered a range of MCLs in developing the final Arsenic Rule, including MCLs of 3, 5, 10,
and 20 μg/L. EPA evaluated the following five factors to determine the revised MCL:

• The analytical capability and laboratory capacity;

• The likelihood of water systems choosing various compliance technologies for several
sizes of systems based on source water properties;

• The national occurrence of arsenic in water supplies;

Chapter 1, Executive Summary 1-2 Arsenic in Drinking Water Rule EA

### • Quantified and non-quantified costs and health risk reduction benefits likely to occur at

the MCLs considered; and

• The effects on sensitive subpopulations.

After evaluating the above factors, EPA considered an MCL of 3 μg/L since this is the level that has

been determined to be as close to the MCLG as is feasible. However, the Agency is using its
discretionary authority in §1412(b)(6)(A) to consider setting MCL at a less stringent level. The statute
requires that the alternative less stringent level be one which maximizes health risk reduction at a level

where costs and benefits are also considered. As a result, EPA considered the alternative MCL
options of 5, 10, and 20 μg/L.

The Agency also considered two regulatory options related to the applicability of the revised MCL.
Specifically, EPA investigated applying both the monitoring and treatment requirements of the Arsenic
Rule to both community water systems (CWSs) and NTNCs. A CWS is defined as a system that
provides piped water to at least 25 people or with at least 15 service connections year-round. An
NTNC is a public water system that is not defined as a CWS and that regularly serves at least 25 of the
same people for at least six months of the year. After considering the costs and benefits of the revised
rule with regard to both CWSs and NTNCs, EPA is requiring both CWS and NTNC water systems to
comply with all facets of the revised rule. The benefit-cost analysis upon which this decision is based is
provided in Chapters 5, 6, and 7 of this Economic Analysis (EA). Transient non-community systems,
which provide potable water to continuously changing populations, will not be subject to the revised

rule.

The revised rule also includes modifications to the current monitoring requirements, including the
availability of monitoring waivers. A detailed discussion of these changes can be found in Chapter 3.

1.4 Benefits and Costs of the Proposed Rule

Quantitative risk metrics (e.g., slope factors or reference doses) are necessary to evaluate cancer or

non-cancer risks. Although arsenic causes numerous health effects, bladder and lung cancer are the
only endpoints for which an Agency-approved metric for evaluating arsenic-related risk currently exists.
This cancer slope factor (SF) for bladder and lung cancer is used to calculate cases potentially avoided

due to the revised arsenic standard. Benefits estimates for avoided cases of bladder and lung cancer
were calculated using mean population risk estimates at various MCL levels. Lifetime risk estimates
were converted to annual risk factors and applied to the exposed population to determine the number

of cases avoided. These cases were divided into fatalities and non-fatal cases avoided, based on

survival information. The avoided premature fatalities were valued based on the VSL estimates
discussed in Chapter 5, as recommended by EPA current guidance for cost/benefit analysis. The
avoided non-fatal cases were valued based on the willingness to pay estimates for the avoidance of

chronic bronchitis. The upper bound estimates include the possibility of the incidence rate being
understated, depending on the survival rate for bladder cancer in the study area of Taiwan.

Chapter 1, Executive Summary 1-3 Arsenic in Drinking Water Rule EA

### Numerous other health effects that are likely to be avoided as a result of this rule may generate
significant benefits, and should not be discounted based on the fact that they cannot be quantified at this

time. The estimated total national monetized benefits of the proposed rule and the other rule options
considered are provided in Exhibit 1-1.

Exhibit 1-1
Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs ($ millions)

Arsenic

Level
(μg/L) Total

Annual Cost
(7%) Annual Bladder

Cancer Health

Benefits 1,2 Annual Lung

Cancer Health

Benefits 1,2 Total Annual

Health

Benefits 1,2 Potential Non-Quantifiable

Health Benefits

3 $792.1 $58.2 - $156.4 $155.6 - $334.5 $213.8 - $490.9 • Skin Cancer

• Kidney Cancer

• Cancer of the Nasal

Passages

• Liver Cancer

• Prostate Cancer

• Cardiovascular Effects

• Pulmonary Effects

• Immunological Effects

• Neurological Effects

• Endocrine Effects

• Reproductive and
Developmental Effects 5 $471.7 $52.0 - $113.3 $139.1 - $242.3 $191.1 - $355.6

10 $205.6 $38.0 - $63.0 $101.6 - $134.7 $139.6 - $197.7

20 $76.5 $20.1 - $21.5 $46.1 - $53.8 $66.2 - $75.3 3

1 May 1999 dollars.

2 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c).

3 For 20 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional
reduction from the higher level risk base case. Thus, the number of estimated cases avoided and estimated
benefits are higher at 20 μg/L using the risk estimates adjusted for arsenic in cooking water and food.



### For the revised MCL of 10 μg/L, the estimated monetized bladder and lung cancer health benefits range from $139.6 million to $197.7 million. More detail about these benefit estimates are found in
Chapter 5. Exhibit 1-2 shows the estimated national cost of compliance of the revised rule and the
other rule options that were considered. At the revised MCL of 10 μg/L, the estimated national cost of compliance is $180.4 million at a discount rate of three percent, and $205.6 million at a discount rate of

seven percent.

Chapter 1, Executive Summary 1-4 Arsenic in Drinking Water Rule EA

### Exhibit 1-2 Total National Cost of Compliance ($ millions)

Discount Rate 3% 7% 3% 7% 3% 7%

System Costs

Treatment $665.9 $756.5 $27.2 $29.6 $693.1 $786.0

Monitoring/

Administrative $2.2 $3.0 $1.0 $1.4 $3.2 $4.4

State Costs $1.4 $1.6 $0.1 $0.2 $1.5 $1.7

TOTAL COST $669.4 $761.0 $28.3 $31.1 $697.8 $792.1

System Costs

Treatment $394.4 $448.5 $16.3 $17.6 $410.6 $466.1
Monitoring/

Administrative $2.0 $2.8 $1.0 $1.3 $2.9 $4.1

State Costs $1.1 $1.3 $0.1 $0.2 $1.2 $1.4

TOTAL COST $397.5 $452.5 $17.3 $19.1 $414.8 $471.7

System Costs

Treatment $169.6 $193.0 $7.0 $7.6 $176.7 $200.6

Monitoring/

Administrative $1.8 $2.5 $0.9 $1.3 $2.7 $3.8

State Costs $0.9 $1.0 $0.1 $0.2 $1.0 $1.2

TOTAL COST $172.3 $196.6 $8.1 $9.1 $180.4 $205.6

System Costs

Treatment $60.7 $69.0 $2.6 $2.8 $63.3 $71.8

Monitoring/

Administrative $1.7 $2.4 $0.9 $1.3 $2.6 $3.7

State Costs $0.7 $0.8 $0.1 $0.2 $0.9 $1.0

TOTAL COST $63.2 $72.3 $3.6 $4.2 $66.8 $76.5 NTNC CWS

MCL = 10 m m

g/L

MCL =20 m m

g/L TOTAL

MCL = 3 m m

g/L

MCL =5 m m

g/L

Chapter 1, Executive Summary 1-5 Arsenic in Drinking Water Rule EA

### The net benefits and benefit-cost ratios of each regulatory option are provided in Exhibit 1-3. At the revised MCL of 10 μg/L, the net benefits range from a high of $17.3 million to a low of a negative
$40.8 million, at a discount rate of three percent. These net benefits correspond to benefit-cost ratios
of 0.8 and 1.1 (also at a three percent rate of discount).

Exhibit 1-3 Net Benefits and Benefit-Cost Ratios of Each Regulatory Option ($ millions)

MCL ( m g/L) 3 5 10 20

3% Discount Ratelower bound Net Benefits $ (484.0) (223.7) $ $ (40.8) $ (0.6)

Benefit/Cost Ratio 0.3 0.5 0.8 1.0upper bound Net Benefits $ (206.8) (59.2) $ $ 17.3 $ 8.5

Benefit/Cost Ratio 0.7 0.9 1.1 1.1

7% Discount Ratelower bound Net Benefits $ (578.3) (280.6) $ $ (66.0) $ (10.3)

Benefit/Cost Ratio 0.3 0.4 0.7 0.9upper bound Net Benefits $ (301.1) (116.1) $ $ (7.9) $ (1.2)

Benefit/Cost Ratio 0.6 0.8 1.0 1.0

*Costs include treatment, O&M, monitoring, and administrative costs to CWSs and NTNCs and State costs

for administration of water programs.

Chapter 1, Executive Summary 1-6 Arsenic in Drinking Water Rule EA

### As mentioned above, there are a number of important non-monetized benefits of reducing arsenic
exposure that are not included in the net benefit and benefit-cost calculations. Chief among these are
certain health impacts known to be caused by arsenic. Such nonquantifiable benefits may include skin
cancer, kidney cancer, cancer of the nasal passages, liver cancer, prostate cancer, cardiovascular
effects, pulmonary effects, immunological effects, neurological effects, endocrine effects, and customer
peace-of-mind benefits from knowing their drinking water has been treated for arsenic. For example, a
number of epidemiologic studies conducted in several countries (e.g., Taiwan, Japan, England,
Hungary, Mexico, Chile, and Argentina) report an association between arsenic in drinking water and
skin cancer in exposed populations. Early reports linking inorganic arsenic contamination of drinking
water to skin cancer came from Argentina (Neubauer, 1947, reviewing studies published as early as
1925) and Poland (Tseng et al., 1968). However, the first studies that observed dose-dependent
effects of arsenic associated with skin cancer came from Taiwan (Tseng et al., 1968; Tseng, 1977).
These studies focused EPA’s attention on the health effects of ingested arsenic. Studies conducted in
the U.S. have not demonstrated an association between inorganic arsenic in drinking water and skin

cancer. However, these studies may not have included enough people in their design to detect these
types of effects.

The potential monetized benefits associated with skin cancer reduction would not change the total
benefits of the rule to an appreciable degree, even if the assumption were made that the risk of skin
cancer were equivalent to that of bladder cancer, using EPA’s 1988 risk assessment. Skin cancer is highly treatable (at a cost of illness of less than $3,500 for basal and squamous cell carcinomas versus a
cost of illness of $178,000 for non-fatal bronchitis) in the U.S., with few fatalities (less than one

percent).

In addition to potentially reducing the risk of skin cancer, there are also a large number of other healthrelated benefits associated with arsenic reduction, as presented in Exhibit 1-1, which are not monetized
in this analysis due to lack of appropriate data.

Other benefits not monetized in this analysis include customer peace of mind from knowing drinking
water has been treated for arsenic and reduced treatment costs for currently unregulated contaminants
that may be co-treated with arsenic. To the extent that reverse osmosis is used for arsenic removal,

these benefits could be substantial. Reverse osmosis and activated alumina are the primary point-ofuse treatments for small systems. (These benefits of avoided treatment cannot currently be monetized;
however, they can be readily monetized in the future, as decisions are made about which currently
unregulated contaminants to regulate.)

Chapter 1, Executive Summary 1-7 Arsenic in Drinking Water Rule EA

## Chapter 2: Need for the Revised Rule

2.1 Introduction

The Safe Drinking Water Act (SDWA), as amended in 1996, requires EPA to identify and regulate
substances in drinking water that may have an adverse effect on public health and that are known or
anticipated to occur in public water supplies. National Primary Drinking Water Regulations
(NPDWRs) address risks to public health, and secondary regulations address aesthetic qualities (such
as taste, odor, or color) that relate to public acceptance of drinking water. For NPDWRs, EPA must
either establish a Maximum Contaminant Level (MCL) or, if it is not economically or technically feasible
to monitor the contaminant in drinking water, specify a treatment technique to remove the contaminant
or reduce its concentration in the water supply.

An enforceable standard of 50 μg/L currently exists for arsenic in community water systems under the
National Interim Primary Drinking Water Regulations (40 CFR 59566). In §1412(b)(12)(A) of the
SDWA, as amended in 1996, Congress specifically directed EPA to propose a NPDWR for arsenic
by January 1, 2000, and issue the final regulation by January 1, 2001. Congress recently changed the

deadline for the final rule to June 22, 2001 (Public Law 106-377).

This document analyzes the impacts of the rule, which revises the current standard as follows:

1) Reduces the current MCL for arsenic in community water systems from 50 μg/L to 10 μg/L;

2) Requires nontransient non-community water systems (NTNC) to comply with the new

standard; and

3) Revises the current monitoring requirements to make them consistent with the Standard

Monitoring Framework (40 CFR 141.23(c)).

Executive Order 12866, Regulatory Planning and Review, requires EPA to estimate the costs and

benefits of the Arsenic Rule in an economic analysis document (EA). This chapter of the EA discusses
the public health concerns being addressed by the rule, describes the history of regulatory efforts
concerning arsenic, and discusses the economic rationale for the rule. Subsequent chapters will
accomplish the following:

• Discuss the regulatory options considered by EPA (Chapter 3),

• Present the results of the baseline analysis (Chapter 4),

• Examine the benefits of the rule (Chapter 5),

• Present the results of the cost analysis (Chapter 6),

• Compare the costs and benefits of the rule and the regulatory options considered by

EPA (Chapter 7), and

• Discuss the potential economic impacts of the rule (Chapter 8).

Chapter 2, Need for the Revised Rule 2-1 Arsenic in Drinking Water Rule EA

### 2.2 Public Health Concerns To Be Addressed

This section describes the public health concerns addressed by the final Arsenic Rule. A description of
potential health effects associated with arsenic, including effects in sensitive subpopulations, along with
the sources of human exposure to arsenic, is presented. In addition, the section describes current
controls that address exposure to arsenic.

2.2.1 Health Effects of Arsenic

Arsenic is a naturally occurring element present in the environment in both organic and inorganic forms.
Inorganic arsenic, considered to be the more toxic form, is found in ground water, surface water, and
many foods. Chronic exposure to high levels of inorganic arsenic in drinking water has been found to
result in a variety of adverse health effects, including skin and internal cancers and cardiovascular and
neurological effects.

Exposures to organic forms of arsenic also occur through ingestion of food and metabolism of ingested
inorganic arsenic. Experimental data on the effects of organic forms of arsenic are not as well
characterized as those for inorganic arsenic, and thus are the subject for future research. Limited data
on the primary organic forms in fish and shellfish (arsenobetaine and arsenocholine) suggest that these
forms are relatively nontoxic. Other forms of organoarsenicals in foods have been even less well

characterized. Recent in vitro toxicity evidence indicates that the trivalent form of monomethylarsonic
acid is more toxic than either the trivalent (arsenite) or pentavalent (arsenate) forms of inorganic arsenic.
Additional data are needed in this area before the toxicological significance of the trivalent form of
monomethylarsonic acid is clear.

In 1996, EPA requested that the National Research Council of NAS conduct an independent review of
the arsenic toxicity data. NRC was asked to review EPA’s current criteria (50 μg/L and 0.018 μg/L),
evaluate use of recent Taiwan data and other studies to assess the carcinogenic and non-carcinogenic
health effects of arsenic, and recommend changes to EPA’s risk characterization for arsenic. NRC
issued its report on March 23, 1999 (NRC, 1999). The health effects of inorganic arsenic are
summarized below and are described in more detail in Chapter 5.

Cancer

There is a large human database available for inorganic arsenic, unlike most environmental

contaminants. However, there is substantial debate among the scientific community over the
interpretation of these data and their application in risk assessment. NRC found that a number of
epidemiologic studies conducted in several countries (e.g., Taiwan, Japan, England, Hungary, Mexico,
Chile, and Argentina) report an association between arsenic in drinking water and skin cancer in
exposed populations. Increased mortality from internal cancers of liver, bladder, kidney, and lung have
also been reported.

Chapter 2, Need for the Revised Rule 2-2 Arsenic in Drinking Water Rule EA

### EPA has identified arsenic as a group A “known” human carcinogen, based on increased risks of lung
cancer in workers exposed to airborne arsenic and dose-dependent increases in skin cancer risk in

Taiwan.

Non-Cancer Health Effects

In addition to cancer, NRC (1999) reported that arsenic exposures have been linked to other adverse

health effects. These include thickening of the skin, effects on the nervous system such as tingling and
loss of feeling in limbs, hearing impairment, effects on the heart and circulatory system, diabetes,
developmental effects, and effects on the gastrointestinal system and liver. Many of these effects are
observed at concentrations where cancer effects were observed in the epidemiology studies.

Sensitive Subpopulations

Certain sensitive individuals may be at a greater risk of serious illness from exposure to arsenic than the
general population. The NRC report (1999) noted that human sensitivity to the toxic effects of
inorganic arsenic exposure is likely to vary based on genetics, metabolism, diet, health status, sex, and
other possible factors. For example, reduced ability to methylate arsenic (convert inorganic arsenic into
less acutely toxic and more readily excreted forms) may result in retention of more arsenic in the body

and increased risk of toxic effects. However, there is insufficient evidence at the present time to
characterize the influence of such factors as age, sex, nutrition, and genetic polymorphism on the
expression of arsenic toxicity (NRC, 1999).

The following groups have been cited in various studies as possibly being particularly susceptible to

health effects from arsenic:

• **Children** are identified as especially susceptible because their dose of arsenic will be,
on average, higher than that of adults exposed to similar concentrations due to their
higher fluid and food intake relative to body weight. The NRC report cited one study
that suggests that children may have a lower arsenic-methylation efficiency than adults.

• **Pregnant and lactating women** are especially vulnerable because of possible adverse
reproductive and developmental effects of arsenic.

• **People with poor nutritional status** may have a reduced ability to methylate arsenic.

• **Individuals with pre-existing diseases that affect specific organs** —in particular,
kidney and liver problems—may be more susceptible to the effects of arsenic because
these organs act to detoxify arsenic in the body.
In addition, arsenic can directly damage these and other organ systems, as described

above. Individuals with pre-existing damage or congenital defects in these systems are
more susceptible to health effects from exposure to arsenic. The elderly are more likely
as a group to have pre-existing conditions in the susceptible organ systems.

Chapter 2, Need for the Revised Rule 2-3 Arsenic in Drinking Water Rule EA

### Section 5.2.4 discusses the susceptibility of these subgroups in more detail. Due to a lack of available
data, no quantitative analysis of the specific risks to sensitive populations was performed as part of this

EA.

2.2.2 Sources and Mechanisms of Exposure

Arsenic (As) is an element that occurs in the earth’s crust. Accordingly, there are natural sources of

exposure. Erosion and weathering of rocks deposit arsenic in water bodies and lead to the uptake of
arsenic by animals and plants. Consumption of food and water is the major source of arsenic exposure
for the majority of U.S. citizens. People may also be exposed from industrial sources, as arsenic is
used in semiconductor manufacturing, petroleum refining, wood preservatives, animal feed additives,

and herbicides.

Arsenic can combine with other elements to form inorganic and organic arsenicals. In general, inorganic
derivatives are regarded as more toxic than the organic forms. While food contains both inorganic and
organic arsenicals, primarily inorganic forms are present in water.

Recently, EPA developed estimates of human exposure to arsenic in drinking water, food, and air using
data from numerous Federal sampling surveys analyzing the occurrence of arsenic in public water
supplies, dietary foods, and ambient air. EPA’s national air sampling databases indicate very low
concentrations of arsenic in both urban and non-urban locations, at levels typically ranging from about

0.003 to 0.03 μg/m 3



### . Air is therefore an insignificant source of arsenic intake, typically representing less
than one percent of overall exposure.

EPA reviewed several local and regional studies for comparison purposes. Using the Total Diet Study
of the Food and Drug Administration (FDA), recent dietary analyses indicate that the average adult’s
total arsenic intake is about 53 μg/day. The FDA analytical methodology does not differentiate
between the organic and inorganic forms of arsenic. For most people living in the U.S., inorganic
arsenic exposure is primarily from food and water sources. Since the inorganic forms are considered to
be more toxic, it is important to estimate the amount of inorganic arsenic in the diet. To accomplish this
estimation, EPA used the FDA data along with a separate study that characterized arsenic species in

foods. This separate characterization indicated that about 20 percent of daily intake of dietary arsenic
is in the inorganic form. Conversely, most arsenic present in drinking water is in the form of inorganic
arsenic species.

Accounting for the organic forms of arsenic in food, the dietary intake of inorganic arsenic was
estimated to be approximately 14 μg/day. An adult drinking 2 L/day of water containing 10 μg/L of
arsenic would obtain 20 μg/day from drinking water, so that drinking water would contribute about 60
percent of total intake of inorganic arsenic. On the other hand, an adult drinking water containing 2
μg/L of arsenic would obtain almost 80 percent of the daily inorganic arsenic from food.

Chapter 2, Need for the Revised Rule 2-4 Arsenic in Drinking Water Rule EA

### 2.3 Regulatory History

This section provides a chronology and overview of regulatory actions affecting arsenic in drinking
water and recent efforts that have led to this rulemaking. It also summarizes the major studies and data
collection efforts that highlighted the need for a new rule.

**Current MCL:** In 1975, EPA set the National Interim Primary Drinking Water Regulation at 50 μg/L

(40 FR 59566, December 24, 1975). This standard was equal to the standard set in 1942 by the U.S.

Public Health Service for interstate water carriers, which was not based on a risk assessment. EPA
based the MCL on daily consumption of two liters of water providing approximately 10 percent of total
ingested arsenic of 900 μg/day. Commenters recommended an MCL of 100 μg/L based on no

observed adverse health effects. EPA noted long-term chronic effects at 300 to 2,750 μg/L, but no
chronic effects at 120 μg/L (US EPA, 1975, pg. 59576, EPA-570/9-76-003).

**Water Quality Criteria:** In 1980, EPA announced the availability of Water Quality Criteria
Documents to protect surface water bodies from pollutants under the Clean Water Act (45 FR 79318,

November 28, 1980). These criteria are used as guidance to the States in establishing surface water
quality standards and discharge limits for effluents. The criterion for protection of human health from
ingestion of arsenic in contaminated water and aquatic organisms was 2.2 nanograms per liter (ng/L), or

0.0022 μg/L. In 1992, the Clean Water Act criterion was recalculated based on an updated risk
assessment to yield 0.018 μg/L for arsenic (57 FR 60848, December 22, 1992).

**1983 Notice prior to proposal:** In an Advance Notice of Proposed Rulemaking (ANPRM)
published October 5, 1983 (48 FR 45502), EPA requested comment on whether the arsenic MCL
should consider carcinogenicity, other health effects, and nutritional requirements; and whether MCLs
are necessary for separate valence states.

**1985 Proposed MCLG:** In 1985, EPA proposed a non-enforceable Maximum Contaminant Level
Goal (MCLG) of 50 μg/L based on an NAS conclusion that 50 μg/L balanced toxicity and possible
essentiality. EPA also requested comment on alternate MCLGs of 100 μg/L based on noncarcinogenic effects and 0 μg/L based on carcinogenicity (50 FR 46936, November 13, 1985).

**1986 SDWA Amendments:** The 1986 SDWA Amendments converted the 1975 interim arsenic
standard to a NPDWR, subject to revision by 1989.

**1988 Risk Assessment Forum Report:** EPA’s Risk Assessment Forum wrote the Special Report

on Ingested Inorganic Arsenic: Skin Cancer; Nutritional Essentiality (EPA/625/3-87/013), in part,
to evaluate the validity of applying the Taiwan 1968/1977 data to dose-response assessments in the

U.S. At the 50 μg/L standard, the calculated U.S. lifetime risk ranged from 1 x 10 -3 

### to 3 x 10 -3



### .

Chapter 2, Need for the Revised Rule 2-5 Arsenic in Drinking Water Rule EA

### 1989: After reviewing EPA’s arsenic health effects studies in June 1988, the Science Advisory Board
(SAB) stated in its August 14, 1989, report the following:

• The essentiality of arsenic is suggestive but not definitive;

• Hyperkeratosis may not be a precursor of skin cancer;

• The Taiwan data are adequate to conclude that high doses of ingested arsenic can

cause skin cancer;

• The Taiwan study is inconclusive to determine cancer risk at levels ingested in the U.S.;

and

• As (III) levels below 200 to 250 μg per day may be detoxified.

SAB concluded that the dose-response is non-linear and reported that the 1988 Forum Report did not
apply non-linearity in its risk assessment.

**1989:** Uncertainty about arsenic risk assessment issues caused the Agency to miss the 1989 deadline
for proposing a revised NPDWR, and a citizen suit was filed against EPA. A consent decree was
entered by the court in June 1990 and was amended several times thereafter before being dismissed
after passage of the 1996 SDWA Amendments.

**The Safe Drinking Water Act Amendments of 1996,** in §1412(b)(12)(A), directed EPA to take
the following actions for arsenic:

• Develop an arsenic health effects research strategy within 180 days of enactment;

• Consult with the National Academy of Sciences, other Federal agencies, and interested
public and private entities in conducting the studies;

• Propose a revised MCL by January 1, 2000; and

• Issue a final rule by January 1, 2001.

In addition SDWA, as amended in 1996, directed EPA to:

• Assess health effects for sensitive populations;

• List both compliance and/or variance treatment technologies for small systems;

• Evaluate the incremental costs and benefits of different regulatory options, accounting
for the changes that may result from implementation of other rules;

• Issue an MCL that maximizes health benefits at a cost that is justified by the benefits;

• Review MCLs every six years or sooner.

The 1996 amendments also made the following changes:

• The effective date of MCLs is three to five years after promulgation of the final rule,

rather than 18 months.

Chapter 2, Need for the Revised Rule 2-6 Arsenic in Drinking Water Rule EA

### • Compliance for non-microbial contaminants can be achieved by use of point-of-use
(POU) or point-of-entry (POE) devices that are maintained by the small public water

system.

Congress authorized $2.5 million per year from 1997 to 2000 for the studies. Congress appropriated

$1 million to EPA for arsenic research in 1996 and 1997 and $1 million to the American Water Works

Association Research Foundation in subsequent years.

EPA proposed the arsenic regulation on June 22, 2000, in the Federal Register

. At the same time,
EPA is proceeding with its Arsenic Research Plan, which will address a variety of issues related to
exposure, treatment, and health effects. 1 

### In EPA’s appropriations bill for 2001, Public Law 106-377,
Congress directed EPA to issue the final arsenic rule by June 22, 2001, one year after proposal.

**NRC Report:** In 1996, EPA requested that the National Research Council of NAS conduct an
independent review of the arsenic toxicity data and evaluate the scientific validity of EPA’s 1988 risk
assessment for arsenic in drinking water. In addition, NRC was asked to review EPA’s current criteria
(50 μg/L and 0.018 μg/L), evaluate use of recent Taiwan data and other studies to assess the
carcinogenic and non-carcinogenic health effects of arsenic, and recommend changes to EPA’s risk

characterization for arsenic. NRC issued its report on March 23, 1999. The report had several main

conclusions:

• The Taiwan studies provide the best available evidence on the human health effects of
arsenic, and are supported by studies in Chile and Argentina that report similar results.
These studies show that chronic ingestion of inorganic arsenic at high doses causes
bladder and lung cancer, as well as skin cancer.

• Factors such as genetics, nutrition, and amount of arsenic in food can affect the U.S.

risk assessment.

• Non-cancer chronic effects include skin effects, cardiovascular and cerebrovascular
disease, diabetes, and reproductive effects.

• The molecular processes of arsenic toxicity are not well understood. Research can help
characterize the dose-response relationship for both cancer and non-cancer endpoints,
especially at low doses.

• The current 50 μg/L MCL is not adequately protective of human health and therefore
requires downward revision as promptly as possible. 2

1 The Arsenic Research Plan is published at http://www.epa.gov/ORD/WebPubs/final/arsenic.pdf.

2 The NRC report is available at http://www.nap.edu/readingroom/enter2.cgi?0309063337.html.

Chapter 2, Need for the Revised Rule 2-7 Arsenic in Drinking Water Rule EA

### 2.4 Rationale for the Regulation

This section discusses the economic rationale for choosing a regulatory approach to address the public
health consequences of drinking water contamination. EPA provides the economic rationale in
response to Executive Order Number 12866, Regulatory Planning and Review, 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 (§1, b(1)).

In addition, guidance from the Office of Management and Budget 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.” Therefore, the economic rationale presented in this section
should not be interpreted as EPA’s approach to implementing the SDWA. Instead, it is EPA’s
justification, as required by the Executive Order, for a regulatory approach to this public health issue.

2.4.1 Statutory Authority

Section 1412(b)(1)(A) of the SDWA requires EPA to establish National Primary Drinking Water
Regulations for contaminants that may have an adverse public health effect; that are known to occur or
that present a substantial likelihood of occurring once in public water systems (PWSs), at a frequency
and level of public concern; and that present a meaningful opportunity for health risk reduction for
persons served by PWSs. This general provision is supplemented by additional requirements that EPA
proposed a revised MCL for arsenic by January 1, 2000 (§1412(b)(1)(A)), and issue a final regulation
by June 22, 2001 (Public Law 106-377).

2.4.2 Economic Rationale for Regulation

In addition to the statutory directive to regulate arsenic, there is also economic rationale for government
regulation. In a perfectly competitive market, market forces guide buyers and sellers to attain the best
possible social outcome. A perfectly competitive market occurs when there are many producers of a
product selling to many buyers, and both producers and buyers have complete knowledge regarding
the products of each firm. Also, there must not be any barriers to entry into the industry, and producers
in the industry must not have any advantage over potential new producers. Several factors in the public
water supply industry do not satisfy the requirements for a perfect market and lead to market failures
that may require regulation.

First, water utilities are natural monopolies. A natural monopoly exists because it is not economically
efficient to have multiple suppliers competing to build multiple systems of pipelines, reservoirs, wells,

and other facilities. 3 

### Instead, a single firm or government entity performs these functions generally under

3 Mansfield (1975) states that natural monopolies exist because the average cost of producing the product
reaches a minimum at an output rate that is enough to satisfy the entire market at a price that is profitable. Multiple

Chapter 2, Need for the Revised Rule 2-8 Arsenic in Drinking Water Rule EA

### public control. Under monopoly conditions, consumers are provided only one level of service with
respect to the quality of the product, in this case drinking water quality. If consumers do not believe
that the market of safety in public health production is adequate, they cannot simply switch to another
water utility or perceived higher quality source of supply (e.g., bottled water) without incurring

additional cost.

Second, high information and transaction costs impede public understanding of the health and safety
issues concerning drinking water quality. The types of health risks potentially posed by trace quantities
of drinking water contaminants involve analysis and distillation of complex toxicological data and health

sciences. EPA recently developed the Consumer Confidence Report rule to make water quality
information more easily available to consumers. The Consumer Confidence Report rule requires
community water systems to mail their customers an annual report on local drinking water quality.
However, consumers will still have to analyze this information for its health risk implications. Even if
informed consumers are able to engage utilities regarding these health issues, the costs of such
engagement, known as “transaction costs” (in this case measured in personal time and commitment),
present another significant impediment to consumer expression of risk preference.

SDWA regulations are intended to provide a level of protection from exposure to drinking water
contaminants that would not otherwise occur in the existing market environment of public water supply.
The regulations set minimum performance requirements for all public water supplies in order to reduce
the risk confronted by all consumers from exposure to drinking water contaminants. SDWA
regulations are not intended to restructure market mechanisms or to establish competition in supply.
Rather, SDWA standards establish the level of service to be provided in order to better reflect public
preference for safety. The Federal regulations remove the high information and transaction costs by
acting on behalf of all consumers in balancing the risk reduction and the social costs of achieving this

reduction.

producers competing would produce the product at higher than minimum long-run average cost. Competition to
achieve lower average costs would drive prices down until a single supplier was victorious.

Chapter 2, Need for the Revised Rule 2-9 Arsenic in Drinking Water Rule EA

## Chapter 3: Consideration of Regulatory Alternatives

3.1 Regulatory Approaches

The Safe Drinking Water Act (SDWA) establishes EPA’s responsibility for ensuring the quality of
drinking water and defines the mechanisms available to the Agency to protect public health.
Specifically, the SDWA requires EPA to set enforceable MCLs when technically or economically
feasible or otherwise establish treatment technique requirements for specific contaminants in drinking

water. In meeting this mandate, EPA sets water quality standards by identifying which contaminants
should be regulated and establishing the levels of the contaminant that water systems must attain. This
section discusses the approach EPA used in determining the regulatory alternatives that were

considered.

3.1.1 Determining the Standard

In regulating a contaminant, EPA first sets a maximum contaminant level goal (MCLG), which
establishes the contaminant level at which no known or anticipated adverse health effects occur.
MCLGs are non-enforceable health goals. For this rulemaking, EPA set an MCLG of zero. EPA then
sets an enforceable maximum contaminant level (MCL) as close as technologically possible to the

MCLG. In addition, EPA may use its discretion in setting the MCL by choosing an MCL that is
protective of public health while also ensuring that the quantified and non-quantified costs are justified
by the quantified and non-quantified benefits of the rule. For this rulemaking, EPA is setting an MCL of
10 μg/L. The following sections describe the process by which EPA determined both the MCLG and

the MCL.

3.1.2 Determining the MCLG

**Carcinogens:** For many years, Congress supported a goal of zero tolerance for carcinogens in food
and water, and that goal was incorporated into the SDWA of 1974. Under this policy, contaminants
that are classified as probable human carcinogens have had MCLGs set at zero. EPA’s Office of
Science and Technology (OST) (in the Office of Water) develops a cancer risk range that quantifies the
probability that a person will develop cancer during a lifetime of ingesting water containing the regulated

contaminant.

Data used in risk estimates usually come from lifetime exposure studies in animals. To predict the risk

for humans, the oral doses used in animal studies are corrected for differences in animal and human size

and surface area.

In 1986, EPA published Guidelines for Carcinogen Risk Assessment in the Federal Register (51 FR

33992). At that time EPA’s default assumptions included low-dose linearity to extrapolate the cancer
risk range, which assumes that carcinogenic effects do not exhibit a threshold and that carcinogens pose
risks to humans at any concentration. EPA proposed revised Guidelines for Carcinogen Risk

Assessment in 1996 (61 FR 17960).

Chapter 3, Consideration of Regulatory Alternatives 3-1 Arsenic in Drinking Water Rule EA

### Non-carcinogens: MCLGs for non-carcinogens are based on Reference Doses (RfDs) and their
Drinking Water Equivalent Levels (DWELs).

The Reference Dose (RfD, formerly the Acceptable Daily Intake, or ADI), estimates the daily amount
of chemical a person, including sensitive humans, can ingest over a lifetime with little risk of causing

adverse health effects. RfDs are usually expressed in milligrams of chemical per kilogram of body
weight per day (mg/kg/day). Data from chronic (usually two years) or sub-chronic (usually 90 days)
studies of humans or animals provide estimates of the No- or- Lowest-Observed-Adverse-Effect Level
(NOAEL or LOAEL). The NOAEL (or LOAEL) is divided by a total uncertainty factor (UF) of 1 to
10,000 to obtain the RfD. In the final National Primary Drinking Water Regulations published on
January 30, 1991 (56 FR 3532), EPA applies a UF of 1, 3, or 10 when a NOAEL from a human
study is used to account for intraspecies variation and an uncertainty factor of 100 to a human LOAEL
to account for lack of a NOAEL and for species variation. The UFs provide a margin for variations in
species responses, data gaps, and less than lifetime exposures. Scientific judgement is used to select the
total UF for specific risk assessments.

The DWEL is calculated by multiplying the RfD by an assumed adult body weight of 70 kg
(approximately 154 pounds) and dividing by an average adult water consumption of 2 liters per day
(L/day). The DWEL assumes that 100 percent of the exposure comes from drinking water. The
MCLG is then determined by multiplying the DWEL by the percentage of the total daily exposure
contributed by drinking water (relative source contribution), set at 20 percent by default when adequate
data are not available, but set between 20 and 80 percent when adequate data are available to estimate

exposure. Based on the 1993 RfD (1993 Draft Criteria) for arsenic (0.3 μg/kg/day), the calculated
DWEL would be 0.3 μg/kg/day times 70 kg divided by 2 L/day, or 10 μg/L. Due to the three-fold
uncertainties noted in the Integrated Risk Information System (IRIS) file on arsenic, the DWEL could
be 3 to 30 μg/L. It should be noted that the toxicological studies used to determine the effect level and
the derivation of the RfD are different from the analysis conducted in 1975. Additionally, the current
policy on relative source contribution, including the default policy, are also different from those used in

1975.

3.1.3 Determining an MCL

Once an MCLG is established, EPA sets an enforceable standard—in most cases, a Maximum

Contaminant Level (MCL). The MCL is the maximum permissible level of a contaminant in water that
is delivered to any user of a public water system. EPA must set the MCL as close to the MCLG as

feasible. The SDWA defines feasible as the level that may be achieved with the use of the best
available technology, treatment techniques, and other means that EPA finds are available (after
examination for efficacy under field conditions), taking cost to large systems into consideration.

After determining an MCL based on affordable technology for large systems, EPA must complete an
economic analysis to determine whether the benefits of the standard justify the costs. If not, EPA may
adjust the MCL to a level that “maximizes health risk reduction benefits at a cost that is justified by the

benefits” (§1412(b)(6)).

Chapter 3, Consideration of Regulatory Alternatives 3-2 Arsenic in Drinking Water Rule EA

### 3.1.4 Variances

The 1996 SDWA identifies two classes of technologies for small systems: compliance and variance
technologies. A compliance technology is one that achieves compliance with the MCL or treatment
technique requirement. The 1996 Amendments require EPA to list affordable compliance technologies
for three categories of small systems: those serving 25 to 500 people, those serving 501 to 3,300
people, and those serving 3,301 to 10,000 people. If EPA cannot identify an affordable compliance
technology for a particular system category, it must then identify a variance technology instead. The
variance technology must achieve the maximum reduction that is affordable, considering the size of the
system and the quality of the source water, and must be protective of public health. If EPA lists such a
variance technology, small systems will be eligible to apply to the States for a small system variance.
States are authorized to grant variances from standards for systems serving up to 3,300 people if the
system cannot afford to comply with a rule and the system installs the EPA-approved variance
technology. States can grant variances to systems serving 3,301 to 10,000 people with EPA approval.

3.1.5 Analytical Methods

The determination of an MCL depends on the ability of laboratories to reliably measure the contaminant

at the MCL. The SDWA directs EPA to set an MCL “if in the judgement of the Administrator, it is
economically and technologically feasible to ascertain the level of such contaminant in water in public
water systems (§1401 (1)(c)(ii)).” EPA must therefore evaluate the available analytical methods to
determine a Practical Quantitation Limit (PQL), which is the minimum reliable quantification level that
most laboratories can be expected to meet during day-to-day operations. EPA has approved several
analytical methods to support compliance monitoring of arsenic at the current MCL (40 CFR 141.23).
In 1994, EPA evaluated available data and determined the PQL for arsenic to be 2.0 μg/L at an
acceptance limit of ± 40 percent. In its July 1995 report, EPA’s Science Advisory Board
recommended that EPA set the PQL for arsenic using acceptance limits similar to those applied for
other inorganics. Based on more recent information and these recommendations from the SAB, in
1999 EPA derived a PQL of 3 μg/L using an acceptance limit of ± 30 percent for arsenic (EPA,

1999a).

Available data estimate that over 75 percent of EPA Regional and State laboratories and at least 62
percent of non-EPA laboratories are capable of achieving acceptable results at 3 μg/L within a 30
percent acceptance window. While the PQL represents a stringent target for laboratory performance,
the Agency believes that most laboratories, using appropriate quality assurance and quality control
procedures, have the capacity to achieve this level on a routine basis.

3.2 Regulatory Alternatives Considered and Final Rule

This section describes the components of the final rule and the alternatives that were considered by the

Agency.

Chapter 3, Consideration of Regulatory Alternatives 3-3 Arsenic in Drinking Water Rule EA

### 3.2.1 Applicability

The Agency investigated applying the monitoring and treatment requirements of the proposed rule to
both community water systems (CWSs) and non-transient non-community (NTNC) water systems. A
CWS is defined as a system that provides piped water to at least 25 people or with at least 15 service
connections year-round. An NTNC system is a public water system that is not defined as a CWS and
that regularly serves at least 25 of the same people for at least six months of the year. After considering
the costs and benefits of the proposed rule with regard to both CWSs and NTNC systems, EPA
proposes to require both CWSs and NTNC water systems to comply with all facets of the proposed

rule. The benefit-cost analysis upon which this decision is based is provided in Chapters 5, 6, and 7 of

this EA. Transient non-community systems, which provide potable water to continuously changing
populations, will not be subject to the proposed rule. The rule applies to CWSs and NTNC systems
that produce water primarily from either ground or surface water sources.

3.2.2 Maximum Contaminant Level

EPA considered a range of MCLs in developing the proposed Arsenic Rule, including MCLs of 3, 5,
10, and 20 μg/L. EPA evaluated the following five factors to determine the proposed MCL:

• The analytical capability and laboratory capacity;

• The likelihood of water systems choosing various compliance technologies for several
sizes of systems based on source water properties;

• The national occurrence of arsenic in water supplies;

• Quantified and non-quantified costs and health risk reduction benefits likely to occur at

the MCLs considered; and

• The effects on sensitive subpopulations.

An MCL of 3 μg/L was considered since this is the level that has been determined to be as close to the

MCLG as is feasible. However, the Agency is using its discretionary authority in §1412(b)(6)(A) to
set MCL at a less stringent level. The statute requires that the alternative, less stringent level be one that

maximizes health risk reduction at a level where costs and benefits are balanced.

As a result, EPA considered the alternative MCL options of 5, 10, and 20 μg/L.

3.2.3 Monitoring

The current monitoring requirements for arsenic (40 CFR 141.23(l)) apply to community water systems
only. EPA is changing the current monitoring requirements to require systems to monitor for arsenic in
accordance with the provisions of 40 CFR 141.23(c), the Standard Monitoring Framework (SMF).
This change will make the arsenic requirements consistent with the requirements for inorganic
contaminants (IOCs) regulated under the Phase II/V regulations. The revised rule would make the
following changes to the monitoring requirements for arsenic:

Chapter 3, Consideration of Regulatory Alternatives 3-4 Arsenic in Drinking Water Rule EA

### • NTNC systems will be required to monitor for arsenic for the first time.

• MCL exceedances will trigger quarterly monitoring, as opposed to the current
requirements for three additional samples within one month when exceedances occur.

• The State will determine when the system is “reliably and consistently” below the MCL,
after a minimum number of samples following an exceedance (two samples for ground
water systems and four for surface water systems), and can return to the default
sampling frequency. (Currently, the system automatically returns to the default
monitoring frequency when a minimum of two consecutive samples are below the

MCL.)

• The State may grant a nine-year monitoring waiver to a system if it finds that arsenic
detections are the result of natural occurrence and not of human activity. (Currently, no
monitoring waivers are permitted.)

3.2.4 Compliance Technologies and Variances

EPA reviewed several technologies as best available technology (BAT) candidates for arsenic removal.
Those technologies capable of removing arsenic from source water that fulfill the SDWA requirements

for BAT determinations for arsenic are as follows:

• Anion exchange;

• Activated alumina (AA);

• Reverse osmosis (RO);

• Modified coagulation/filtration;

• Modified lime softening; and

• Oxidation/filtration (including greensand filtration). 1



### EPA has further determined that these technologies are affordable for all system size categories and has
therefore not identified a variance technology for any system size or source water combination at the
proposed MCL.

3.2.5 Monitoring Waivers

Under the final Arsenic Rule (§141.23(c)(3)), States may grant a nine-year monitoring waiver from
sampling requirements to water systems based on the analytical results from previous sampling and a
vulnerability assessment or the assessment from an approved source water assessment program
(provided that the assessments were designed to collect all of the necessary information needed to
complete a vulnerability assessment for a waiver). States issuing waivers must consider the
requirements in 40 CFR 141.23(c)(2)-(6). In order to qualify for a waiver, there must be three
previous samples from a sampling point (annual for surface water and three rounds for ground water)
with analytical results reported below the MCL. Grandfathered data collected after January 1, 1990,

1 Oxidation/filtration is BAT only when the Fe/As ratio is > 20:1.

Chapter 3, Consideration of Regulatory Alternatives 3-5 Arsenic in Drinking Water Rule EA

### that are consistent with the analytical methodology and detection limits of the proposed regulation may
be used for issuing sampling point waivers.

The current arsenic regulations §141.23(l)-(q) do not permit the use of monitoring waivers. However,
a State could now use the analytical results from the three previous compliance periods (1993 to 1995,
1996 to 1998, and 1999 to 2001) to issue ground water sampling point waivers. Surface water
systems must collect annual samples; thus, a State could use the previous three years’ sampling data
(1999, 2000, and 2001) to issue sampling point waivers. One sample must be collected during the
nine-year compliance cycle in which the waiver is effective, and the waiver must be renewed every nine

years. Vulnerability assessments must be based on a determination that the water system is not
susceptible to contamination and arsenic is not a result of human activity (i.e., it is naturally occurring).

Not all States have required systems to report arsenic results below 50 μg/L. In this case, the States
would not have adequate data to grant waivers until enough data are available to make the

determinations.

EPA believes that some States may have been regulating arsenic under the proposed standardized
inorganic framework. If so, those States will have to ensure that existing monitoring waivers have been
granted using data reported below the new MCL. Otherwise, States will have to notify the systems of
the new lower reporting requirements that need to be met to qualify for a waiver for the MCL.

3.2.6 Implementation

The following schedule is proposed for implementation of the rule:

• States must submit applications for primacy revisions within two years after
promulgation, unless a State requests and is granted a two-year extension.

• The rule will be effective five years after promulgation.

• All systems must complete initial sampling by December 31, 2007.

Chapter 3, Consideration of Regulatory Alternatives 3-6 Arsenic in Drinking Water Rule EA

## Chapter 4: Baseline Analysis

4.1 Introduction

This chapter presents baseline information to describe the operational and financial characteristics of
water systems in the absence of the Revised Arsenic Rule. The baseline information provides a basis
for EPA’s analysis of the costs, benefits and economic impacts of the regulatory options considered.
This chapter includes data on the number of water systems regulated, the population affected, current
treatment practices, raw and treated water quality, and socio-economic impacts.

The baseline is assumed to be current conditions, as reflected by the most recent available data. In
some cases, changes in the industry have occurred or will occur that are not reflected in the available
data; for example, changes in operations induced by a regulation that will take effect prior to the

Arsenic Rule.

4.2 Industry Profile

4.2.1 Definitions

According to EPA’s definition, public water systems (PWSs) include community water systems

(CWSs) and non-community water systems (NCWSs). NCWSs are further classified as either
transient or non-transient. The rule will affect all public water systems except for transient noncommunity water systems. The following definitions will help the reader follow the discussion in this
chapter:

• **Public water systems (PWSs)** serve 25 or more people or have 15 or more service

connections and operate at least 60 days per year. A PWS can be publicly or
privately-owned.

• **Community water systems (CWSs)** serve at least 15 service connections used by

year-round residents, or regularly serve at least 25 year-round residents.

**• Non-community water systems (NCWSs)**  do not have year-round residents, but

serve at least 15 service connections used by travelers or intermittent users for at least
60 days each year, or serve an average of 25 individuals for at least 60 days a year.

**• Non-transient non-community water systems (NTNCs)**  serve at least 25 of the

same persons over six months per year (e.g., factories, schools, office buildings, and
hospitals).

• **Transient non-community water systems (TNCs)** serve fewer than 25 of the same

persons over six months per year (e.g., many restaurants, rest stops, parks).

Public water systems are also classified by their water source: surface water (e.g., drawn from lakes,
streams, rivers, etc.) or ground water (e.g., drawn from wells or springs).

Chapter 4, Baseline Analysis 4-1 Arsenic in Drinking Water Rule EA

### 4.2.2 Sources of Industry Profile Data

EPA uses two primary sources of data to characterize the universe of water systems: the Safe Drinking
Water Information System (SDWIS) and the Community Water System Survey (CWSS).

EPA’s SDWIS contains data on all PWSs as reported by States and EPA Regions. This source
reflects both mandatory and optional reporting components. States must report the system location,
system type (CWS, NTNC, or TNC), primary raw water source (ground water or surface water), and

violations. Optional reporting fields include type of treatment and ownership type. Because providing
some data is discretionary, EPA does not have complete data on every system for these parameters.
This is particularly common for non-community systems.

The second source of information, the CWSS, is a detailed survey of surface and ground water CWSs
conducted by EPA in 1995 and published in 1997 (EPA, 1997b). The CWSS is stratified to represent
the complete population of CWSs across the U.S. The CWSS includes information such as revenues,
expenses, treatment practices, source water protection measures, and plant capacity. There is no
equivalent survey such as the CWSS to define treatment practices in non-community water systems.

4.2.3 Number and Size of Public Water Systems

Exhibit 4-1 shows the number of systems in the U.S. by source water (ground or surface) and system
size (measured by the number of people served), based on the December 1998 SDWIS data. 1 

### In the

U.S. there are a total of 63,984 ground water systems and 11,843 surface water systems, including

CWSs and NTNCs. All are potentially affected by the Arsenic Rule.

Some ground water sources (e.g., riverbank infiltration/galleries) are directly impacted by adjacent
source water bodies and are separately identified in SDWIS as ground water under the direct influence

of surface water (GWUDI). Since these systems would have similar occurrence as surface water
systems, GWUDI systems are considered surface water systems in this analysis. SDWIS also provides
system data by ownership. As previously described, PWSs include both publicly-owned and privatelyowned systems. This detail is also provided in Exhibit 4-1, where any system referred to as “other” in
the SDWIS database has been presented as a privately-owned system.

The majority (95 percent) of PWSs are small systems that serve fewer than 10,000 people. Eightynine percent of PWSs serve 3,300 people or fewer; 77 percent serve fewer than 1,000 people; 67
percent serve fewer than 500 people; and 34 percent serve fewer than 100 people.

1 The cost and benefit analyses are conducted using the 1997 SDWIS freeze. The 1998 SDWIS freeze is
presented here, as it was the most recent representation of the regulated entities.

Chapter 4, Baseline Analysis 4-2 Arsenic in Drinking Water Rule EA

### Exhibit 4-1 Total Number of Systems by Size, Type, and Ownership

SOURCE <100 101­

500 501­

1,000 1,001­ 3,301­

3,300 10,000 10,001­

50,000 50,001­ 100,001­

100,000 1,000,000 TOTAL

CWS

Ground Water

Public 1,335 4,678 2,868 4,167 1,993 1,011 105 50 16,207

Private 12,942 10,380 1,821 1,547 466 205 26 11 28,303

Total 14,277 15,058 4,689 5,714 2,459 1,216 131 61 44,510

Surface Water

Public 394 1,117 917 2,012 1,656 1,436 260 217 8,009

Private 698 886 303 408 188 171 40 44 3,053

Total 1,092 2,003 1,220 2,420 1,844 1,607 300 261 11,062

Total 15,369 17,061 5,909 8,134 4,303 2,823 431 322 54,352

NTNCWS

Ground Water

Public 1,725 3,108 1,163 337 23 9 0 0 6,365

Private 7,965 3,930 815 355 39 5 0 0 13,109

Total 9,690 7,038 1,978 692 62 14 0 0 19,474

Surface Water

Public 58 63 19 24 6 3 1 1 175

Private 213 232 87 56 17 1 0 0 606

Total 271 295 106 80 23 4 1 1 781

Total 9,961 7,333 2,084 772 85 18 1 1 20,255

Source: Safe Drinking Water Information System (SDWIS), December 1998 freeze.

Chapter 4, Baseline Analysis 4-3 Arsenic in Drinking Water Rule EA

### 4.2.4 System Size and Population Served

All PWSs are potentially subject to the requirements of the Arsenic Rule, with the exception of TNCs.
The majority of systems to be regulated are community water systems, which also serve, on average,
more people than NTNCs. Exhibit 4-2 provides information on the average populations served by
CWSs for each system size category, and the total population served by NTNCs.

Exhibit 4-2
Total Population Served of Water Systems by
Source Water, System Type, and Service Population Category

Service
Population

Category Community Non-Transient Non-Community Ground Water Surface Water

< 100 859,777 61,450

-

101–500 3,741,017 570,448

-

501–1,000 3,457,163 921,449

-

1,001–3,300 10,631,422 4,797,855

-

3,301–10,000 14,095,015 10,995,980

-

10,001–50,000 25,004,779 36,819,575

-

50,001–100,000 8,609,455 20,500,370

-

100,001-1,000,000 14,575,556 65,375,183

-

> 1,000,000 2,855,494 28,658,586

-

Total 83,829,678 168,700,896 31,968,181
Source: EPA, Safe Drinking Water Information System (SDWIS), December 1998 freeze.



### Those NTNCs determined to be affected by the Arsenic Rule are presented in Exhibit 4-3 by type of

system. The NTNC populations were taken from the 1998 SDWIS freeze. The NTNCs are much
smaller than CWSs on average and vary substantially in their characteristics. Schools account for more
than half of the affected NTNCs (8,414 of 20,255), followed by office parks (950), daycare centers
(809), food manufacturing facilities (768), and non-food related retailers (695). Prisons serve the
largest number of people on average (1,820). All other system types serve an average of 500 people

or fewer.

Chapter 4, Baseline Analysis 4-4 Arsenic in Drinking Water Rule EA

### Exhibit 4-3 Characteristics of NTNC Systems Affected by the Revised Rule

Service Area Type SYSTEM CHARACTERISTICS

Number of

Systems Average

Population

Served Per

System Design Flow (mgd) Average Daily Flow (mgd)

Daycare Centers

Highway Rest Areas

Hotels/Motels

Interstate Carriers

Medical Facilities

Mobile Home Parks

Restaurants

Schools

Service Stations
Summer Camps

Water Wholesalers
Agricultural Products/Services

Airparks

Construction

Churches Campgrounds/RV Parks

Fire Departments

Federal Parks

Forest Service
Golf and Country Clubs

Landfills

Mining

Amusement Parks

Military Bases Migrant Labor Camps

Misc. Recreation Services

Nursing Homes

Office Parks

Prisons
Retailers (Non-food related)

Retailers (Food related)

State Parks

Non-Water Utilities Manufacturing: Food
Manufacturing: Non-Food 809

15

351

287

367

104

418

8414

53

46

266

368

101

99

230

123

41

20

107

116

78

119

159

95

33

259

130

950

67

695

142

83

497

768

3845 76

407

133

123

393

185

370

358

230

146

173

76

60

53

50

160

98

39

42

101

44

113

418

395

63

87

107

136

1820

174

322

165

170

372

168 0.0051

0.0089

0.0189

0.0029

0.1166

0.0262

0.0039

0.0333

0.0051

0.0218

0.1637

0.0199

0.0026

0.0009

0.0053

0.0214

0.0186

0.0065

0.0014

0.0118

0.0053

0.0123

0.0171

0.0695

0.0102

0.0025

0.0411

0.0077

0.5322

0.0038

0.0058

0.0048

0.0133

0.0454

0.0157 0.0011

0.0020

0.0045

0.0006

0.0339

0.0065

0.0008

0.0085

0.0011

0.0053

0.0494

0.0048

0.0005

0.0002

0.0011

0.0052

0.0045

0.0014

0.0002

0.0027

0.0011

0.0028

0.0041

0.0192

0.0023

0.0005

0.0107

0.0017

0.1820

0.0008

0.0012

0.0010

0.0031

0.0120

0.0038

TOTAL 20,255

Source: EPA, 1999. Geometries and Characteristics of Public Water Systems, updated with the

December 1998 SDWIS freeze.

Chapter 4, Baseline Analysis 4-5 Arsenic in Drinking Water Rule EA

### 4.2.5 Number of Entry Points

If water systems employ more than one water supply source, they may have more than one treatment
facility. For estimation purposes this analysis assumes a treatment facility at every entry point to the
distribution system. As a result, the total number of entry points is an important determinant of
compliance costs. Exhibit 4-4 presents the distribution of entry points per ground water CWS by
system service population category.

Exhibit 4-4
Average Number of Entry Points per Ground Water System

Upper Bound

95%

Confidence Service Population Category

< 100 101­

500 501­

1,000 1,001 ­

3,300 3,301 ­

10,000 10,001 ­

50,000 50,001 ­

100,000 > 100,000

Percentile

Mean 1 1 2 2 2 4 6 9

5th 1 1 1 1 1 1 1 1

50th (median) 1 1 1 1 2 3 4 5

95th 2 3 3 5 5 12 22 28

Source: EPA, 1999. Geometries and Characteristics of Public Water Systems , Table 5.2.



### In this respect, surface water systems are unlike ground water systems in that little variation in the
number of entry points was reported among surface water systems. Even for large population
categories, the majority of surface water systems reported only one or two entry points. (EPA, 1999a).
This finding was supported by data recently collected from the Information Collection Request for large
surface water systems. Appendix C describes how the entry point distribution was incorporated into
the cost analysis for this rule.

4.2.6 Number of Households

Another method for estimating the effect of regulations on customers is to determine the cost per

household. This measure is often used instead of per capita cost because it is a more accurate
representation of how customers are billed: per household, not per person.

Exhibit 4-5 shows that household consumption does not vary substantially across size category or
ownership type. The mean water consumption ranges from 81,000 gallons per year to 127,000 gallons
per year per household.

Chapter 4, Baseline Analysis 4-6 Arsenic in Drinking Water Rule EA

### Exhibit 4-5
Water Consumption per Residential

Connection

Population System

Type Mean Water

Consumption*
(kgal/yr)

< 100 Public 81

Private 92

101-500 Public 93

Private 110

501-1,000 Public 97

Private 88

1,001-3,300 Public 82

Private 102

3,301-10,000 Public 87

Private 124

10,001-50,000 Public 108

Private 110

50,001-100,000 Public 122

Private 96

100,001-1,000,000 Public 127

Private 114

Source: *EPA, 1997. CWSS, Vol. II: Detailed

Summary Result Tables and Methodology

Report, Table 1-14;



### 4.2.7 Production Profile

Exhibit 4-6 shows the average design capacity (in thousands of gallons) of CWS plants by source,
ownership, and system size categories. Design capacity is the maximum amount of water a plant can

deliver. Exhibit 4-7 provides the daily production of CWSs (in thousands of gallons) for the same
categories. Daily production is the average amount of water a plant delivers in a day.

Chapter 4, Baseline Analysis 4-7 Arsenic in Drinking Water Rule EA

### Exhibit 4-6 Design Capacity of CWS Plants by Source, Ownership, and System Size (Thousands of Gallons)

Primary Source/ Service Population Category

Ownership Type 1,001­ 3,301­ 10,001­ 50,001­ 100,001­

<25 25-100 101-500 501-1,000 3,300 10,000 50,000 100,000 1,000,000 >1,000,000

Ground Water 6.27 21.86 86.86 251.0 619.5 1,864 6,673 20,785 67,379 392,939

Public 4.84 29.46 123.67 305.0 740.3 2,152 7,365 22,614 67,994 401,175

Private 6.50 21.34 77.30 232.1 560.6 1,683 6,347 18,234 75,629

- Purchased-Public

- 5.71 27.37 81.4 223.0 801 3,380 19,796 26,765

-
Purchased-Private 0.89 4.99 24.78 79.5 200.6 824 2,748 8,690

- -
Surface Water 1.30 20.32 92.60 239.3 617.9 1,818 6,682 19,707 69,224 554,759

Public 1.14 25.79 130.90 318.2 807.8 2,218 7,887 22,337 77,298 584,889

Private 3.19 18.13 75.69 214.2 527.3 1,582 6,165 15,869 61,381 296,609

Purchased-Public 0.04 5.71 29.01 81.8 241.1 854 3,698 13,206 43,650

-
Purchased-Private 1.12 4.99 24.65 73.6 213.8 719 2,933 12,788 29,270

-

GW under

influence - 22.16 87.20 247.5 631.6 1,779 7,499 18,482

- -

Public

- 33.29 111.32 291.2 760.0 2,077 8,992 20,195

- - Private

- 21.53 81.77 227.4 618.5 1,802

- - - - Purchased-Public

- - 30.21 97.1 209.3 461 2,319

- - - Purchased-Private

- 2.54 29.83 94.3

- 905

- - - -
Source: EPA, Geometries and Characteristics of Public Water Systems , Table B1.5.3.

### Exhibit 4-7 Daily Production of CWS Plants by Source, Ownership, and System Size (Thousands of Gallons)

Primary Source/ Service Population Category

Ownership Type 1,001­ 3,301­ 10,001­ 50,001­ 100,001­

<25 25-100 101-500 501-1,000 3,300 10,000 50,000 100,000 1,000,000 >1,000,000

Ground water 1.35 5.33 24.40 78.50 212 715 2,914 10,187 37,224 259,751

Public 0.96 6.72 33.20 90.50 243 796 3,129 10,900 37,095 267,256

Private 1.39 4.80 20.30 69.30 18 635 2,802 9,121 44,760

- Purchased-Public

- 5.11 23.50 68.20 182 634 2,585 14,496 19,455

-
Purchased-Private 0.85 4.54 21.60 67.30 166 656 2,119 6,502

- -
Surface Water 0.39 6.91 33.70 90.70 244 753 2,932 9,069 33,667 295,680

Public 0.28 7.51 41.60 106.20 284 823 3,133 9,387 34,749 293,439

Private 0.95 6.15 28.60 87.30 230 748 3,225 8,907 38,094 206,950

Purchased-Public 0.04 5.11 24.90 68.50 197 675 2,821 9,766 31,351

-
Purchased-Private 1.06 4.54 21.50 62.40 176 575 2,258 9,472 21,215

-

GW under

influence - 5.41 24.50 77.30 217 679 3,313 8,951

- -

Public

- 7.70 29.50 86.00 250 765 3,907 9,611

- - Private

- 4.85 21.30 67.70 207 686

- - - - Purchased-Public

- - 25.90 80.90 171 370 1,789

- - - Purchased-Private

- 2.36 25.9 79.4

- 719

- - - -
Source: EPA, Geometries and Characteristics of Public Water Systems , Table B1.5.1.

### 4.2.8 Treatment Profile

Exhibit 4-8 below presents information regarding in-place treatment technologies that affect arsenic

concentrations in delivered water. The current treatment in-place will determine the likely remedy that
systems will select in order to come into compliance with the new MCL.

Exhibit 4-8 Percentage of CWSs with Various Treatments in Place

Primary Service Population Category
Source/ Type

of Treatments < 100 101-500 501­

1,000 1,001­

3,300 3,301­

10,000 10,001­

50,000 50,001­

100,000 100,001­

1,000,000 > 1,000,000

Ground Water Systems

Ion Exchange 0.7% 1.6% 3.8% 1.9% 4.6% 3.3% 1.2% 0.0%

-

Reverse

Osmosis 0.0% 1.2% 0.0% 0.9% 1.2% 0.7% 1.2% 0.0%

-

Coagulation/

Flocc. 1.5% 5.4% 4.2% 3.4% 8.1% 15.1% 24.2% 25.2%

-

Lime/Soda Ash Softening 2.1% 3.7% 4.1% 5.2% 7.0% 12.2% 17.4% 32.4%

-

Disinfection 52.8% 77.9% 84.0% 79.7% 86.8% 96.5% 86.3% 96.4%

-

Surface Water Systems

Ion Exchange 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

-

Reverse

Osmosis 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

-

Coagulation/

Flocc. 27.5% 52.6% 70.2% 78.5% 95.4% 94.5% 93.7% 99.5%

-

Lime/Soda Ash Softening 3.9% 8.1% 20.5% 17.5% 10.8% 6.9% 5.7% 5.1%

-

Disinfection 92.8% 94.1% 100.0% 100.0% 96.0% 98.0% 100.0% 100.0%

Source: EPA, Cost and Technology Document for the Arsenic Rule , Tables 6-1and 6-2.



### 4.3 Occurrences of Arsenic

EPA has relied on a variety of data sources to evaluate the occurrence of arsenic in community water
systems and non-transient non-community systems. This information supports EPA’s assessment of
baseline conditions, including (1) the number of systems expected to exceed various MCL options, and

(2) the population exposed to different levels of arsenic.

In 1992, EPA conducted an analysis of the number of systems that would be impacted by various
arsenic MCL options, ranging from 0.5 μg/L to > 50 μg/L. These projections were based on the
following national surveys:

Chapter 4, Baseline Analysis 4-10 Arsenic in Drinking Water Rule EA

### • 1984-1986 National Inorganic and Radionuclide Survey (NIRS) for ground water

systems;

• 1976-1977 National Organic Monitoring Survey for surface water systems;

• 1978-1980 Rural Water Survey for surface water systems; and

• 1978 Community Water Supply Survey for surface water systems.

These data sources have several limitations. First, the surveys used for surface water systems were
conducted primarily before 1980. It is likely that arsenic occurrence has changed in the past two
decades due to changes in raw water sources or the addition of filtration treatment to comply with the

Surface Water Treatment Rule (SWTR). In addition, many of the survey responses had relatively high
minimum reporting limits (5 μg/L). Therefore, it is statistically difficult to extrapolate low-level arsenic

occurrence.

EPA (1999c) used the MCL compliance monitoring data from 25 States to develop an improved

estimate of national baseline arsenic occurrence. The estimates based on this data are comparable to

those based on the other sources listed above.

EPA used statistical techniques to assess:

(1) the national distribution of mean arsenic concentrations in water systems,

(2) the distribution of source means within systems, and

(3) the number of systems with at least one source above various MCLs.

Exhibit 4-9 shows the percentage of systems with an arsenic occurrence in excess of ten different
concentration levels, ranging from 2 μg/L to 50 μg/L. Less than one percent of ground water and
surface water systems have a concentration level of arsenic greater than 50 μg/L. In contrast, 27
percent of ground water systems and 10 percent of surface water systems have an arsenic
concentration greater than 2 μg/L. Exhibit 4-10 provides a summary of the number of systems
expected to exceed various MCLs.

Exhibit 4-9 Arsenic Occurrence in CWSs at Various Concentration Levels (μg/L)

Source % of systems greater than ( m m

g/L)

2 3 5 10 15 20 25 30 40 50

GW 27.3 19.9 12.1 5.3 3.1 2.0 1.4 1.1 0.64 0.43

SW 9.8 5.6 3.0 0.80 0.46 0.32 0.24 0.19 0.13 0.10

Source: EPA, 2000. Arsenic Occurrence in Public Drinking Water Supplies.

Chapter 4, Baseline Analysis 4-11 Arsenic in Drinking Water Rule EA

### Exhibit 4-10
Statistical Estimates of Numbers of Systems with
Average Finished Arsenic Concentrations in Various Ranges

System size (population served) Number of systems with mean arsenic concentration (μg/L) in the
range of:

>3 to 5 >5 to 10 >10 to 20 >20

Ground Water CWS

Number of Systems 3,384 2,949 1,432 870

% of systems 7.8% 6.8% 3.3% 2.0%

Surface Water CWS

Number of Systems 270 239 51 34

% of systems 2.5% 2.2% 0.5% 0.3%

Ground Water NTNCWS

Number of Systems 1,677 1,995 635 405

% of systems 8.6% 10.3% 3.3% 2.1%

Surface Water NTNCWS

Number of Systems 20 17 4 2

% of systems 2.5% 2.2% 0.5% 0.3%

Chapter 4, Baseline Analysis 4-12 Arsenic in Drinking Water Rule EA

## Chapter 5: Benefits A n aly s is

5.1 N ature of Regulatory Benefits

The benefits associated with reductions of arsenic in drinking water arise from a reduction in

adverse hum an heal t h effect s. To a l e sser deg r ee benefi t s m a y al so accrue from an avoi dance of

e x pe nsive c onsume r be ha vior s a ime d a t a voiding e x posur e

, suc h a s the pur c h a s e of bottle d

water.

The value to consumers of a reduction in the risk of adverse health effects includes the following

components:

• T he avoidance of medical costs and productivity losses associated with illness;

• T he a voida nc e of the pa in a nd suf f

e r i ng a ssoc i a t e d with illne ss;

• T he losse s a ssoc i a t e d with r i sk a nd unc e r ta inty of mor b idity , a l so c a lle d the “ r isk

pr e mium” ; a n d

• T he r e duc tion in r i sk of pr e m a t ur e mor t a lity

.

This conceptual valuation framework g o es bey ond valuing out-of-pocket medical costs and lost
time to include the value consumers place on avoiding pain and suffering and the risk premium.

The r i sk pr e mium r e pr e s e n ts the da ma g e s a ssoc i a t e d with r i sk a nd unc e r ta inty , c a p tur e d in the

ex pression of consumers’ willing n ess to pay for the reduction in risk of illness (F reeman, 1979).

This c h a p te r f

i r s t pr e s e n ts inf o r m a tion on the multiple a dve r s e he a lth e f f

e c t s a ssoc i a t e d with
arsenic, followed by a quantitative risk analy s is of a two arsenic-related endpoints, bladder
cancer and lung cancer. B ecause a larg e number of potential health effects cannot be quantified,

it is like l y tha t the e s tima te d be ne f its a ssoc i a t e d with a voida nc e of bla dde r a nd lung c a n c e r underestimate the total benefits of a reduction of arsenic in drinking water.

5.2 H ealt h Ef f ect s

5.2.1 O v e rv iew

Ex posure t o arseni c has m a ny pot ent i a l heal t h effect s, whi c h have been descri bed i n t w o recent publications: Arsenic in Drinking W a ter by the National Research Council (NRC, 1999), and the
Ag ency for Tox i c S ubst a nces and Di sease R e g i st ry ' s Draft Tox i c o logic a l Profile for Arse nic (ATSDR, 1998, updated September 2000). These two sources provide descriptions of health

effects that are summariz e d in this section, along with additional information provided from the

recent literature.

I n g e stion of inorg a nic arsenic can result in both cancer and non-cancer health effects (NRC,

1999). Ex posure may also occur via other routes of ex posure including inhalation and dermal

ex posure. There is a larg e human effects database available for inorg a nic arsenic. However, the

effect s of org a ni c form s of arseni c are not as wel l charact eri z ed as t hose of i norg a ni c arseni c.

L imited information sug g e sts that the major org a noarsenicals found in fish and shellfish
(arsenobetaine and arsenocholine) have little or no tox i city

.

Chapter 5, Benefits Analys is 5-1 A r s e nic in D r inking Water Rule EA

### I t a ppe a r s tha t some of the me ta bolite s of inor g a nic a r se nic ma y posse ss some tox i c ity . The f i na l
rule addresses both org a nic and inorg a nic forms of arsenic.

The nature of the health effects avoided by reducing arsenic levels in drinking water is a function
of characteristics unique to each individual and the level and timing of ex posure. Therefore, the
relationship between ex posure and response is quite complex

. This section describes potential

heal t h effect s but does not concl ude t h at t h ere are speci fi c effect s t h at occur due t o t h e current levels of arsenic in our country ’s drinking water.

5.2.2 C arcinogenic Effects

Arsenic’s carcinog enic role was noted over 100 y ears ag o (NCI , 1999) and has been studied since

tha t time

. The Ag e n c y ha s c l a ssif i e d a r se nic a s a Cla ss A huma n c a r c i nog e n, “ b a s e d on
suf f i c i e n t e v ide n c e f r o m huma n da ta . An inc r e a s e d lung c a n c e r mor t a lity wa s obse r ve d in
multiple human populations ex posed primarily throug h inhalation. Also, increased mortality

f r o m multiple inte r n a l or g a n c a n c e r s ( live r , kidne y

, lung , a nd bla dde r ) a nd a n inc r e a s e d inc i de nc e of skin cancer were observed in populations consuming drinking water hig h in inorg a nic
arsenic.” (EPA, I R I S W e b site, ex tracted 8/99).

The I n ternational Ag ency for Research on Cancer (I ARC) concluded that inhalation of inorg a nic
arsenic caused skin and lung cancer in humans. The 1999 NRC report on arsenic states that
“epidemiolog i cal studies ... clearly show associations of arsenic with several internal cancers at

ex posure concentrations of several hundred microg r ams per liter of drinking water” (NRC,
1999). Ten epidemiolog i cal studies, covering eig h t org a n sy stems, present quantitative data
useful for risk assessment (NRC, 1999, Table 4-1). The org a n sy stems where cancers in humans
have been identified include skin, bladder, lung , kidney

, nasal, liver, and prostate.

Table 10-6 of the NRC report provides risk parameters for three cancers: bladder, lung , and liver

cancer. C onsi d eri n g al l cancers i n ag g r eg at e, t h e NR C st at es i n t h ei r R i sk C h aract eri z at i o n section that “considering the data on bladder and lung cancer in both sex e s noted in the studies in

c h a p te r 4, a simila r a ppr oa c h f o r

a ll c a n c e r s c ould e a s ily r e sult in a c o mbine d c a nc e r r i sk on the
order of 1 in 100” (at the current MCL of 50 μg /L ; NRC, 1999).

New data provide additional health effects information on both carcinog enic and noncarcinog enic effects of arsenic. A recently study by Tsai et al. (1999) of a population that has
been studied over many y ears in Taiwan has provided statistically sig n ificant standardiz ed
mortality ratios (SMRs) for 23 cancerous and non-cancerous causes of death in women and 27

causes of death in men. SMRs are an ex pression of the ratio between deaths that were observed

i n an area wi t h el evat ed arseni c l e vel s and t hose t h at were ex pect ed t o occur, based on t h e mortality ex perience of the populations in nearby areas without elevated arsenic levels. Drinking
water (250-1,140 μg /L ) and soil (5.3-11.2 mg /kg ) in the Tsai et al. (1999) population study had

very hig h arsenic content.

Tsai et al. (1999) identified “bronchitis, liver cirrhosis, nephropathy

, intestinal cancer, rectal

cancer, l a ry ng eal cancer, and cerebrovascul ar di sease” as possi bl y “rel at ed t o chroni c arseni c

ex posure via drinking water.”

Chapter 5, Benefits Analys is 5-2 A r s e nic in D r inking Water Rule EA

### I n addition, the study area had upper respiratory tract cancers previously only related to
occupational inhalation. Hig h male mortality rate (SMR > 3) ex isted for bladder, kidney

, skin,
lung , and nasal cavity cancers and for vascular disease. However, the authors noted that the

mor t a lity r a ng e wa s ma r g ina l f o r

le uke mia , c e r e b r ova sc ula r dise a s e

, live r c i rr hosis, ne phr opa thy

,

a nd dia b e t e s

. F e ma le s a l so ha d hig h mor t a litie s f o r

la r y ng e a l c a nc e r

. The SMRs c a l c u la te d by
Tsai et al. (1999) used the one cause of death noted on the death certificates. Many chronic

dise a s e s , inc l uding some c a n c e r s, do not r e sult in mor t a lity . Conse que ntly , the impa c t indic a t e d
by the SMR will underestimate the total impact of these diseases.

There are, of course, differences between the population and health care in Taiwan and the

United States. F o r ex ample, arsenic levels in the U.S. are not nearly as hig h as they were in the
study area of Taiwan. However, the study g i ves an indication of the ty pes of health effects that

may be associated with arsenic ex posure via drinking water.

5.2.3 N on-carcinogenic Effects

Ar se nic inte r f e r e s with a numbe r of e sse ntia l phy siolog ic a l a c tivitie s, inc l uding the a c tions of

enz y mes, essential cations, and transcriptional events in cells (NRC, 1999). A wide variety of
adverse health effects have been associated with chronic ing e stion of arsenic in drinking water, occurring at various ex posure levels.

Effects on specific org a n sy stems reported in humans ex posed to arsenic are listed below in

Ex hibit 5-1 (NRC, 1999). Ex hibit 5-1 provides descriptive information on the specific diseases

and/ or sy m p t o m s associ at ed wi t h cat eg ori e s of di seases.

Chapter 5, Benefits Analys is 5-3 A r s e nic in D r inking Water Rule EA

### Exhi bi t 5- 1

A d v e r se Noncar ci nogeni c Heal t h Ef f ect s Repor t e d i n Hum a ns i n NRC ( 1999) as

Pot e nt i a l l y A ssoci at ed w i t h A r seni c , by O r gan Sy st em A f f ect ed*

Cut aneous ef f e c t s 1

. h yperpi gm ent at i o n

2. hyperk e rat o s e s
3. m e l anos i s

Gas t roi n t e s t i nal and hepat i c

e ffe cts 4. nonc i rrhot i c port a l hypert ens i o n

5. gas t r oi nt es t i nal hem orrhage s e c ondary t o es ophageal vari c e s
6. hepat i c enl argem ent

7. s p l eni c enl argem ent

8. peri port a l f i bros i s of t he l i v er
9. obl i t erat i v e i n t i m a l hypert r ophy of i n t r ahepat i c venul es res u l t i ng i n obs t r uc t i on of
port a l venous f l ow

, i n c r eas ed s p l eni c pres s u res

, and hypers p l eni s m

, and c i rrhos i s of

t he l i v er
10. di arrhea

11. c r am pi ng

Cardi o vas c u l a r and peri pheral

v a scu l a r e f fe cts 12. peri pheral vas c u l a r di s eas e (bl a c k f oot di s eas e)

13. gangrene of t he f eet

14. c o l dnes s and num bnes s i n t he ex t r em i t i e s
15. i n t e rm i t t ent c l audi c a t i on
16. ul c e rat i on

17. s pont aneous am put at i on
18. Raynaud’ s s y ndrom e
19. ac roc y anos i s
20. i s c hem i c heart di s eas e

Cardi o vas c u l a r and peri pheral

v a scu l a r e f fe cts ( i n ch i l d r e n ) 21. art e ri al s pas m s i n f i ngers and t oes

22. es ent eri c art e ry t h rom bos i s
23. c e rebrovas c u l a r di s eas e

24. ex t ens i v e c o ronary oc c l us i ons
25. c e rebrovas c u l a r oc c l us i ons
26. i s c hem i a of t he t ongue

27. Raynaud’ s s y ndrom e
28. gangrene i n ex t r em i t i e s

Hem a t o l ogi c a l ef f e c t s 29. anem i a - norm o c y t i c

, m egobl as t i c
30. leuk openia - neut ropenia, ly m phopenia, eos inophilia

31. t h rom boc yt openi a
3 2

. r e ti cu l o cy to si s
33. eryt hroi d hyperpl as i a

P u l m onary ef f e c t s 34. c h roni c c ough

35. res t ri c t i v e and obs t r uc t i ve l ung di s eas e
36. em phys e m a

I m m unol ogi c a l ef f e c t s 37. i m pai red i m m une res pons e (m ore s pec i f i c ef f e c t s obs erved i n hum an c e l l s t udi es and

ani m a l s t udi es —s ee s ourc e )

Neurol ogi c a l ef f e c t s 38. peri pheral neuropat hy

E ndoc rine ef f e c t s 39. diabet es m e llit us

Reproduc t i ve and

devel opm ent al ef f e c t s 40. s pont aneous abort i on

41. peri nat al deat h

4 2

. s t illb ir th

43. l o w bi rt h w e i ght

44. bi rt h def ec t s i n c l udi ng c oarc t at i on of t he aort a and ot hers

45. neural t ube def ec t s
46. opht hal m i c abnorm a l i t i e s

47. num erous s k e l e t a l abnorm a l i t i e s
48. urogeni t a l abnorm a l i t i e s
49. grow t h ret a rdat i o n

Sourc e : NRC (1999).

* N otes in parenthesis indicate w here health effects w e re observ ed in animal studies rather than human studies. N R C reports results of numerous animal reproductiv e and dev elopmental studies and notes that there are “v ery few ”

human studies.

Chapter 5, Benefits Analys is 5-4 A r s e nic in D r inking Water Rule EA

### 5.2.4 S usceptible Subgroups

This section discusses the nature of special susceptibilities and identifies population subg roups that may be at hig h er risk than the g e neral population when ex posed to arsenic.

Definition

A susceptible subg roup ex hibits a response that is different or enhanced when compared to the
responses of most people ex posed to the same level of arsenic (ATSDR, 1998). Many diseases
affect certain subg roups of the population disproportionately

. The subg roups may be defined by

ag e, g e nder, race, ethnicity , socioeconomic status, pre-ex isting medical conditions, behavioral or
phy si ol og i cal di fferences, or ot her charact eri s t i c s. For ex am pl e, t h ere are pre-ex i s t i n g m e di cal

c onditions tha t will inc r e a s e susc e p tibility to most tox i ns, suc h a s a pr e

- e x isting dise a s e in the

tox i n’s targ et org a n. Very few diseases affect all population g r oups (ag e s, sex e s, races) equally

. F o r purposes of evaluating potential benefits to different seg m ents of the population, it is useful
to evaluate whether there are susceptible subpopulations that require consideration. The benefit
of reducing their ex posure may be considerably hig h er than the benefit associated with reducing

ex posure among the g e neral population (on a per capita basis).

Special susceptibilities may be indicated by known differences in biolog ical processes that are

essential to detox i fication of a tox i n. I n addition to identify i ng susceptible subg roups based on
biolog ical processes, susceptible subg roups are often identified by observing hig h er-than-averag e
rates of the disease of interest. I n creases in the rates of reported diseases may be due to a variety

of

f

a c t or s. Some of the s e indic a t e a n inc r e a s e d susc e p tibility ; othe r s a r e ma tte r s of pe r s ona l
choice and may not be considered relevant in a benefits analy s is. One way to approach this issue

is to e v a l ua te inc r e a s e d susc e p tibility whe n it is ba se d on a n inc r e a s e d r i sk of dise a s e due to

fact ors reasonably beyond the control of the subpopulation. F actors that are usually bey ond the

c ontr o l of the individua l tha t ma y c a u se inc r e a s e d susc e p tibility inc l ude :

• C onstitutional limitations (e.g ., illnesses, g e netic abnormalities, birth defects such

as enz y m e defi ci enci es);

• C oncurrent sy nerg istic ex posures that cannot reasonably be controlled (e.g ., at

hom e or i n t h e workpl ace); and

• N or ma l c onstitutiona l dif f

e r e nc e s ( i .e ., dif f

e r e nc e s ba se d on se x

, a g e

, r a c e

, et hni ci t y , et c.).

Other factors that are not usually considered bey ond the individual’s control include personal

choi ces, such as sm oki ng , dri nki ng , and drug use. C hoi ce of pl ace of resi dence or work m a y or

may not be treated as a relevant factor. Ultimately , the ty pes of factors that should be included in
identify i ng susceptible subg roups is a matter of public policy

.

No studies were located by ATSDR (1998) that focused ex clusively on evaluating unusual
susceptibility to arsenic. However, some members of the population are likely to be especially
susceptible due to a variety of factors. These factors include increased dose (intake per unit of
body weig ht) in children, g e netic predispositions, and dietary insufficiency (ATSDR, 1998), as

we ll a s pr e

- e x isting he a lth c onditions.

Chapter 5, Benefits Analys is 5-5 A r s e nic in D r inking Water Rule EA

### Children

One often-identified potential susceptible subg roup is children. Due to their increased fluid and
food intake in relation to their body weig ht (NAS, 1995), their dose (millig rams per kilog r am of
body weig ht per day - mg /kg / day ) of arsenic will be, on averag e, g r eater than that of adults. F o r

ex ample, an intake of 1.2 liters per day in a 70 kg adult y i elds an overall water intake of 0.017
liters per kg of body weig ht. An infant who consumes 1 liter per day and weig hs 10 kg is
consuming 0.1 liter per kg of body weig ht, which is more than 5 times the water intake per kg of

an adult. Any contaminant that is present in the water will be delivered at a corresponding ly
hig h er level, on a daily basis. F o y et al. noted that in studies of some chronic ex posures, children
appear to be more severely affected, probably due to a hig h er ex posure per body weig ht (1992
citation, reported in ATSDR, 1998). I n certain circumstances, the increased daily dose in
children can be effectively considered for non-carcinog enic effects because tox i city is evaluated

in terms of ex posures that can rang e from relatively short-term to long -term ex posure. However,

c a r c i nog e n ic e f f

e c t s ( i .e ., bla dde r c a n c e r ) a r e e v a l ua te d ba se d on a lif e time of e x posur e

, whic h

t a kes i n t o consi d erat i on t h e el evat ed dose t h at occurs i n chi l d ren. Because t h e heal t h effect s

me a s ur e d in this be ne f its a sse ssme n t a r e bla dde r a nd lung c a n c e r , a se nsitivity a n a l y s is to
consider hig h er doses of arsenic during childhood was not necessary

. However, the numerous
potential non-carcinog enic effects listed in Ex hibit 5-1 may be of g r eater concern for children

than adults. Avoidance of these effects constitutes an unquantified benefit of the rule.

Genet i c Predisposit ions and D i et ary Insuf f i ciency

Methy l ation of arsenic play s a role in the detox i fication of inorg a nic arsenic, and individuals who

are deficient in essential enz y mes for this process, or who have a dietary deficiency of methy l
donors (choline or methionine), may be at g r eater risk following inorg a nic arsenic ex posure (B uchet and L a uwery s , 1987; Vahter and Marafante, 1987; B r ouwer et al., 1992 cited in ATSDR,

1998). However, liver disease may not increase risk at low levels of arsenic ex posure since there
is a g r eater production of DMA in these patients. (B uchet et al., 1982; Geubel et al., 1988 cited in

ATSDR, 1998). Therefore, these factors are not ex pected to increase risk levels for a sig n ificant
portion of the U.S. population.

Individuals wit h Pre- exist ing Organ Suscept i bilit ies

I ndividua ls ma y ha ve inc r e a s e d susc e p tibilitie s ba se d on spe c i f i c or g a n- r e la te d f a c t or s. Those
with pre-ex isting diseases (e.g ., kidney disease), as well as those with cong enital defects (a sing le

kidne y ) will be a t g r e a t e r r i sk f r o m a tox i n tha t e ithe r c a u se s a dditiona l da ma g e to tha t or g a n, or that relies on that org a n for detox i fication.

I n the case of arsenic, both the kidney s and liver are used to detox i fy and remove the

cont am i n ant

. Bot h si ng l e hi g h doses and l ong -t erm l o w doses m a y cause an accum u l a t i on of
arsenic in the liver and kidney s , which can impair function. I n addition, these org a ns may be
directly damag e d by arsenic ex posure. A review of Ex hibit 5-1 indicates that other org a n

sy st em s are t a rg et s of arseni c t o x i ci t y , i n cl udi ng t h e cardi ovascul ar sy st em (heart

, vei n s, art e ri es),
hematopoietic sy stem, endocrine sy stem, cutaneous sy stem, pulmonary sy stem, g a strointestinal

sy stem, immune sy stem, and peripheral nervous sy stem. I n individuals with pre-ex isting damag e

Chapter 5, Benefits Analys is 5-6 A r s e nic in D r inking Water Rule EA

### to these sy stems or cong enital defects in the sy stems, the likelihood of risk is g r eater. Due to the
hig h er incidence of most ty pes of disease among the elderly

, they are more likelyto have preex isting conditions in these org a n sy stems.

Individuals Exposed via Non-water Sources

Althoug h arsenic is ubiquitous at low levels, it is not g e nerally found at levels of concern in food

or air, in the absence of elevated local sources. W h ere backg r ound levels are hig h, however,
(e.g ., elevated levels in water) it is reasonable to consider the contribution to total ex posure that

may occur from soil, food, and other local sources. W h en anthropog enic sources are known to

g e ne r a te e l e v a t e d a r se nic le ve ls in wa te r ( e .g ., a loc a l sme lte r )

, it is mor e like l y tha t othe r me dia

may be contaminated as well. The total ex posure from all sources is a critical component of
evaluating potential health risks and the benefits of avoiding contaminated drinking water in

the s e c a s e s

. A r e duc tion in a r se nic in dr inking wa te r will r e duc e the ove r a ll e x posur e to individuals in living in contaminated areas (e.g ., around certain Superfund sites) or workers

ex posed to arsenic on the job. Total ex posure from all sources is of particular concern for noncancer risks, because backg r ound levels from non-drinking water sources will determine whether

t h e t o t a l ex posure l eads t o an ex ceedence of a t h reshol d for effect s.

5.3 Q uantitativ e Benefits of A v oiding Cancer

5.3.1 R isk A ssessment f o r C a ncer R esult ing f r om A r senic Exposure

As note d, a r se nic ing e stion ha s be e n linke d to a multitude of he a lth e f f

e c t s, both c a n c e r ous a n d

non-cancerous. These health effects include cancer of the bladder, lung s, skin, kidney

, nasal

passag e s, liver, and prostate. Arsenic ing e stion has also been associated with cardiovascular,
pulmonary , immunolog ical, neurolog ical, endocrine, and reproductive and developmental effects.
A complete list of the arsenic-related health effects reported in humans has been shown in

Ex hibit 5-1. Of all the health effects noted above, current research on arsenic ex posure has only
been able to define scientifically defensible risks for bladder and lung cancer. That is, EPA has
adequat e dat a t o perform a ri sk assessm ent on bl adder and l ung cancer. Because t h ere i s

current l y a l ack of st rong evi d ence on t h e ri sks of ot her arseni c-rel a t e d heal t h effect s, t h e Ag ency has based its assessment of the quantifiable health risk reduction benefits on the risks of arsenic
induced bladder and lung cancers.

Risk assessment is based on the analy s is of scientific data to determine the likelihood, nature,
and mag n itude of harm to public health associated with particular ag ents, and involves three
main analy tical components: haz a rd identification (dose-response assessment), ex posure assessment, and risk characteriz ation.

Ex hibit 5- 2 illustr a te s the ste p s in a tr a d itiona l r i sk a sse ssme n t pr oc e ss f o r

c h a r a c t e r izing the
potential human cancer associated with contaminants in drinking water.

Chapter 5, Benefits Analys is 5-7 A r s e nic in D r inking Water Rule EA

### Exhi bi t 5- 2 Component s of t h e Bl adder Cancer Ri sk A ssessment

HA Z A RD EXPOSURE RI SK

ID EN T I FIC A T ION A SSESSM ENT CHA RA CTERI Z A T I O N



### T o xi ci t y ( dose- r e sponse) × E xposure = Heal t h Ef f ect so



### Populat ion Siz e and Dist r ibut iono



### In ge sti o n / D o se H u ma n In ta k e F a cto r so



### Concent r a t i on of Cont am inant in

Finished Dr ink i ng W a t e r Supply and

Av ailable f o r Hum an Consum pt iono



### Concent r a t i on of Cont am inant in Sour ce
Wa t e r



### 5.3.2 C ommunit y Wat e r Sy st ems

The following sections summariz e how risk reductions were calculated for populations in

com m uni t y wat e r sy st em s ex posed t o arseni c concent r at i ons. The approach for t h i s anal y s i s included five components. F i rst, relative ex posure factor distributions were developed, which

i n corporat e dat a from t h e recent EP A wat e r consum pt i on st udy wi t h ag e, sex

, and wei g ht dat a

. Second, arsenic occurrence distributions were calculated for the population ex posed to arsenic
levels above 3 μg /L

. Third, risk distributions for bladder and lung cancer were chosen for the
analy s is from Morales et al. (2000). F ourth, EPA developed estimates of the projected bladder
and lung cancer risks faced by ex posed populations using Monte-Carlo simulations, bring i ng
tog e ther the relative ex posure factor, occurrence, and risk distributions. These simulations
resulted in upper bound estimates of the actual risks faced by U.S. populations ex posed to arsenic
concentrations at or above 3 μg /L in their drinking water. F i nally , EPA made adjustments to the

lower bound risk estimates to reflect ex posure to arsenic in cooking water and in food in Taiwan.
A more detailed description of the risk methodolog y is provided in Appendix B

.

Chapter 5, Benefits Analys is 5-8 A r s e nic in D r inking Water Rule EA

### Water Consumption

EPA recently updated its estimates of per capita daily averag e water consumption (EPA, 1999).
The estimates used data from the combined 1994, 1995, and 1996 Continuing Survey of F ood

I n takes by I ndividuals (CSF I I ) , conducted by the U.S. Department of Ag riculture (USDA). The

CSF I I is a complex

, multistag e area probability sample of the entire U.S. and is conducted to

survey the food and beverag e intake of the U.S. Per capita water consumption estimates are

r e por te d by sour c e

. Sour c e s inc l ude c o mmunity ta p wa te r

, bottle d wa te r

, a nd wa te r f

r o m othe r sources, including water from household wells and rain cisterns, and household and public
spring s. F o r each source, the mean and percentiles of the distribution of averag e daily per capita

c onsumption a r e r e por te d. The e s tima te s a r e ba se d on a n a v e r a g e of two da y s of r e por te d
consumption by survey respondents. The estimated mean daily averag e per capita consumption
of community tap water by individuals in the U.S. population is 1 liter/person/day

. F o r total

wa te r

, whic h inc l ude s bottle d wa te r

, the e s tima te d me a n da ily a v e r a g e pe r c a p ita c onsumption is

1.2 liters/person/day

. These estimates of water consumption are based on a sample of 15,303

individuals in the 50 States and the District of Columbia. The sample was selected to represent
the entire population of the U.S. based on 1990 Census data.

The e s tima te d 90th pe r c e n tile of the e m pir i c a l distr i bution of da ily a v e r a g e pe r c a p ita
consumption of community tap water for the U.S. population is 2.1 liters/person/day ; the
corresponding number for daily averag e per capita consumption of total water is 2.3

lite r s /pe r son/da y

. I n othe r wor d s, c u rr e nt c onsumption da ta indic a t e tha t 90 pe r c e n t of the U.S.
population consumes approx imately 2 liters/person/day

, or less.

W a ter consumption estimates for selected subpopulations in the U.S. are described in the CSF I I

, including per capita water consumption by source for g e nder, reg i on, ag e categ ories, economic

st at us, race, and resi dent i a l st at us and separat e l y for preg nant wom e n, l act at i n g wom e n, and

wome n in c h ildbe a r ing y e a r s. The wa te r c onsumption e s tima te s by a g e a nd se x we r e use d in the
computation of the relative ex posure factors discussed below.

R e lat i ve Exposure Fact ors

L i fetime male and female relative ex posure factors (REF s) for each of the broad ag e categ ories
used in the water consumption study were calculated, where the life-long REF s indicate the

se nsitivity of e x posur e of a n individua l r e la tive to the se nsitivity of e x posur e of a n “ a ve r a g e ”

pe r s on we ig hing 70 kilog r a m s a nd c onsuming 2 lite r s of wa te r pe r da y

, whic h is a “ h ig h e nd”
water consumption estimate according to the EPA water consumption study referred to above

(EPA, 1999). I n these calculations, EPA combined the water consumption data with data on
population weig ht from the 1994 Statistical Abstract of the U.S. Distributions for both

com m uni t y t a p wat e r and t o t a l wat e r consum pt i on were used because t h e com m uni t y t a p wat e r estimates may underestimate actual tap water consumption. The weig ht data included a mean and
a distribution of weig ht for male and females on a y ear-to-y ear basis. The means and standard
deviations of the life-long REF s derived from this analy s is are shown in Ex hibit 5-3.

Chapter 5, Benefits Analys is 5-9 A r s e nic in D r inking Water Rule EA

### Exhi bi t 5- 3

Li f e

- Long Rel a t i v e Exposure Fact ors

C o m m unity Wa te r C ons um ption D a ta T o ta l Wa te r C ons um ption D a ta

Ma l e M ean = 0. 60

s.d. = 0. 61 M ean = 0. 73

s.d. = 0. 62

Fe m a le M ean = 0. 64

s.d. = 0. 6 M ean = 0. 79

s.d. = 0. 61



### A r senic Occurrence

EPA recently updated its estimates of arsenic occurrence and calculated separate occurrence
distributions for arsenic found in g r ound water and surface water sy stems. These occurrence
distributions were calculated for sy stems with arsenic concentrations of 3 μg /L or above.

Ar se nic oc c u rr e nc e e s tima te s a r e de sc r i be d in mor e de ta il in Cha p te r 4.

Risk Distributions

I n its 1999 report, Arsenic in Drinking W a ter, t h e NR C anal y z ed bl adder cancer ri sks usi n g dat a
from Taiwan. I n addition, the NRC ex amined evidence from human epidemiolog i cal studies in
Chile and Arg e ntina, and concluded that risks of bladder and lung cancer had comparable risks to
those “in Taiwan at comparable levels of ex posure” (NRC, 1999). The NRC also ex amined the
implications of apply i ng different statistical analy s es to the newly available Taiwanese data for

the pur pose of c h a r a c t e r izing bla dde r c a n c e r r i sk. While the NRC’ s wor k did not c onstitute a
form al ri sk anal y s i s , t h ey di d ex am i n e m a ny st at i s t i cal i ssues (e.g ., m easurem ent errors, ag especific probabilities, body weig ht, water consumption rate, comparison populations, mortality
rates, choice of model) and provided a starting point for additional EPA analy s es. The report
noted that “poor nutrition, low selenium concentrations in Taiwan, g e netic and cultural
characteristics, and arsenic intake from food” were not accounted for in their analy s is (NRC,
1999, p. 295). I n the J une 22, 2000, proposed rulemaking , EPA calculated bladder cancer risks
and benefits using the bladder cancer risk analy s is from the 1999 NRC report. W e also estimated
lung cancer benefits in a “W hat I f ” analy s is based on the statement in the 1999 NRC report that

“some studies have shown that ex cess lung cancer deaths attributed to arsenic are 2-5 fold g r eater

than the ex cess bladder cancer deaths” (NRC, 1999).

I n J u ly 2000, a peer-reviewed article by Morales et al. (2000) was published, which presented

a dditiona l a n a l y s e s of bla dde r c a n c e r r i sks a s we ll a s e s tima te s of lung a nd live r c a n c e r r i sks f o r the same Taiwanese population analy z ed in the NRC report. EPA summariz e d and analy z ed the
new information from the Morales et al. (2000) article in a Notice of Data Availability published
on October 20, 2000 (65 F R 63027). Althoug h the data used were the same as used by the NRC
to analy z e bladder cancer risk in their 1999 publication, Morales et al. (2000) considered more
dose-response models and evaluated how well they fit the Taiwanese data, for both bladder

cancer ri sk and l ung cancer ri sk. Ten risk models were presented in Morales et al. (2000). After
consultation with the primary authors (Morales and Ry an), EPA chose Model 1 with no
comparison population for further analy s is.

Chapter 5, Benefits Analys is 5-10 Ar s e nic in D r inking Water Rule EA

### EPA believes that the models in Morales et al. (2000) without a comparison population are more
reliable than those with a comparison population. Models with no comparison population
estimate the arsenic dose-response curve only from the study population. Models with a
comparison population include mortality data from a similar population (in this case either all of
Taiwan or part of southwestern Taiwan), whose ex posure is assumed to be z e ro. Most of the
models with comparison populations resulted in dose-response curves that were supralinear
(hig her than a linear dose-response) at low doses. The curves were “forced down” at z e ro dose
because the comparison population consists of a larg e number of people with low risk and

assumed z e ro ex posure. EPA believes, based on discussions with the authors of Morales et al.
(2000), that models with a comparison population are less reliable, for two reasons. F i rst, there
is no basis in the data on arsenic’s carcinog enic mode of action to support a supralinear curve as
being biolog ically plausible. To the contrary , the conclusion of the NRC Panel (NRC, 1999) was

that the mode of action data led one to ex pect dose responses that would be either linear or less

t h an l i n ear at l o w dose. However, t h e NR C i ndi cat ed t h at avai l a bl e dat a are i n concl u si ve and
“...do not meet EPA’s 1996 stated criteria for departure from the default assumption of linearity ”
(NRC, 1999). Second, models that include comparison populations assume that the ex posure of
the comparison population is z e ro, and that the study and comparison populations are the same in
all important way s ex cept for arsenic ex posure. B o th of these assumptions may be incorrect:
NRC (1999) notes that “the Taiwanese-wide data do not clearly represent a population with z e ro

ex posure to arsenic in drinking water”; and Morales et al. (2000) ag ree that “[ t] here is reason to
believe that the urban Taiwanese population is not a comparable population for the poor rural
population used in this study .” Moreover, because of the larg e amount of data in the comparison
populations, the model results are relatively sensitive to assumptions about this g r oup. F o r these
reasons, EPA believes that the models without comparison populations are more reliable than

those with the m

.

Of the models that did not include a comparison population, EPA believes that Model 1 fits the

data best, based on the Akaike I n formation Criterion (AI C ), a standard criterion of model fit,

a pplie d to the Poisson mode ls. EPA did not c onside r the multi- sta g e We ibull mode l f o r additional analy s is, because of its g r eater sensitivity to the omission of individual villag e s (Morales et al., 2000) and to the g r ouping of responses by villag e (NRC, 1999), as occurs in the

Taiwanese data. I n Model 1, the dose effect is assumed to follow a linear function, and the ag e effect is assumed to follow a quadratic function. The Ag ency decided that the more ex haustive
statistical analy s is of the data provided by Morales et al. (2000), as analy z ed by EPA, would be
the basis for the new risk calculations for the final rule (with further consideration of additional
risk analy s es) and other pertinent information.

Estimated Risk Reductions

Estima te d r i sk r e duc tions f o r

bla dde r a nd lung c a n c e r a t va r i ous MCL le ve ls we r e de ve lope d
using Monte-Carlo simulations. Monte-Carlo analy s is is a technique for analy z ing problems
where there are a larg e number of combinations of input values, which makes it impossible to
calculate every possible result. A random number g e nerator is used to select input values from
pre-defined distributions. For each set of random numbers, a sing le scenario’s result is

cal cul a t e d. As t h e si m u l a t i on runs, t h e m odel i s recal cul a t e d for each new scenari o t h at continues until a stopping criterion is reached.

Chapter 5, Benefits Analys is 5-11 Ar s e nic in D r inking Water Rule EA

### These simulations combined the distributions of relative ex posure factors (REF s), occurrence at
or above 3 μg /L , and risks of bladder and lung cancer taken from the Morales et al. (2000)

article. The simulations resulted in upper bound estimates of the actual risks faced by
populations ex posed to arsenic concentrations at or above 3 μg /L in their drinking water.

Lower Bound Analyses

Two a d justme nts we r e ma de to the r i sk distr i butions r e sulting f r o m the simula tions de sc r i be d
above, reflecting uncertainty about the actual arsenic ex posure in the Taiwan study area. F i rst, the Ag ency made an adjustment to the lower bound risk estimates to take into consideration the

effect of ex posure to arsenic throug h water used in preparing food in Taiwan. The Tai w anese staple foods were dried sweet potatoes and rice (W u et al., 1989). B o th the 1988 EPA Special
Report on Ingested Inorganic Arsenic and the 1999 NRC report assumed that an averag e Taiwanese male weig hed 55 kg and drank 3.5 liters of water daily , and that an averag e Taiwanese

f

e ma le we ig he d 50 kg a nd dr a nk 2 lite r s of wa te r da ily

. Using the s e a ssumptions, a l ong with a n assumption that Taiwanese men and women ate one cup of dry rice and two pounds of sweet

pota t oe s a da y

, the Ag e n c y r e

- e stima te d r i sks f o r

bla dde r a nd lung c a n c e r , using one a dditiona l
liter of water consumption for food preparation (i.e., the water absorbed by hy dration during
cooking ). This adjustment was discussed and used in the October 20, 2000 NODA (65 FR

63027).

Second, an adjustment was made to the lower bound risk estimates to take into consideration the
relatively hig h arsenic concentration in the food consumed in Taiwan as compared to the U.S.
The food consumed daily in Taiwan contains about 50 μg , versus about 10 μg in the U.S. (NRC,
1999, pp. 50–51). Thus, the total consumption of inorg a nic arsenic (from food preparation and
drinking water) is considered, per kilog r am of body weig ht, in the process of these adjustments.
To carry them out, the relative contribution of arsenic in the drinking water that was consumed as
drinking water, on a μg /kg / day basis, was compared to the total amount of arsenic consumed in
drinking water, drinking water used for cooking , and in food, on a μg /kg / day basis.

Other factors contributing to lower bound uncertainty include the possibilityof a sub-linear doseresponse curve below the point of departure. The NRC noted “Of the several modes of action
that are considered most plausible, a sub-linear dose response curve in the low-dose rang e is
predicted, althoug h linearity cannot be ruled out” (NRC, 1999). The recent Utah study (L ewis et
al., 1999) provides some evidence that the shape of the dose-response curve maywell be subl i n ear at l o w doses. Because suffi ci ent m ode of act i on dat a were not avai l a bl e, an adj u st m e nt was not made to the risk estimates to reflect the possibility of a sub-linear dose-response curve.

Additiona l f a c t or s c ontr i buting to unc e r ta inty inc l ude the use of villa g e we ll da ta r a the r tha n

i ndi vi dual ex posure dat a , defi ci enci es i n t h e Tai w anese di et rel a t i v e t o t h e U.S

. di et (sel eni u m

, chol i n e, et c.), and t h e basel i n e heal t h st at us i n t h e Tai w anese st udy area rel a t i v e t o U.S

. populations. The Ag ency did not make adjustments to the risk estimates to reflect these
uncertainties because applicable peer-reviewed, quantitative studies on which to base such
adjustments were not available.

Chapter 5, Benefits Analys is 5-12 Ar s e nic in D r inking Water Rule EA

### Estima te d r i sk le ve ls f o r

bla dde r a nd lung c a n c e r c o mbine d a t va r i ous MCL le ve ls a r e shown in

Ex hibit 5-4 (a-c). The risk estimates without adjustments for ex posure uncertainty throug h
cooking water and food are shown Ex hibit 5-4 (a). These estimates incorporate occurrence data,
water consumption data, and male and female risk estimates. L o wer bounds show estimates
using community water consumption data; upper bounds show estimates using total water

c onsumption da ta

. Ex hibit 5- 4 ( b ) shows e s tima te d r i sk le ve ls f o r

bla dde r a nd lung c a n c e r
combined at various MCL levels with adjustments for ex posure uncertainty throug h cooking

water and food. These estimates incorporate occurrence data, water consumption data, and male
risk estimates, with lower bounds reflecting community water consumption data and upper
bounds reflecting total water consumption data. There are no adjustments for other factors that
contribute to uncertainty , such as the use of villag e well data as opposed to individual ex posure
data. Ex hibit 5-4 (c) is a combination of Ex hibit 5-4 (a) and Ex hibit 5-4 (b), with the lower

bounds taken from Ex hibit 5-4 (b), and the upper bounds taken from Ex hibit 5-4 (a). Thus

Ex hibit 5- 4 ( c ) r e f l e c t s the r a ng e of e s tima te s be f o r e a nd a f te r the e x posur e unc e r ta inty
adjustments for cooking water and for food, along with the incorporation of water consumption

da ta , oc c u r r e nc e da ta , a nd c a n c e r r i sk e s tima te s. The s e e s tima te s we r e use d to e s tima te the r a ng e of potential cases avoided at the various MCL levels.

The upper bound risk estimates in Ex hibits 5-4 (a-c) reflect the following :

• T he tota l wa te r c onsumption e s tima te s f r o m the EPA wa te r c onsumption study ;

• T he occurrence distributions of arsenic in U.S

. g r ound and surface water sy stems;

• M ale and female risk estimates from Morales et al. (2000);

• N ot adjusting for arsenic ex posure from cooking water in Taiwan; and

• N ot adjusting for arsenic ex posure from food in Taiwan.

The lower bound risk estimates in Ex hibits 5-4 (a-c) reflect the following :

• T he c o mmunity wa te r sy ste m e s tima te s of wa te r c onsumption f r o m the EPA wa te r consumption study ;

• T he occurrence distributions of arsenic in U.S

. g r ound and surface water sy stems;

• M ale risk estimates from Morales et al. (2000);

• A djusting for arsenic ex posure from cooking water in Taiwan; and

• A djusting for arsenic ex posure from food in Taiwan.

Chapter 5, Benefits Analys is 5-13 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 4 ( a )

Cancer Ri sks f o r U. S. Popul at i ons Exposed at or A bov e M C L O p t i ons, A f t e r T r eat ment 1, 2

(Without A d justment for A r senic in Food and Cooking Water)

MC L (μg/L) M ean Exp o sed Popula t ion R i s k 90 th Percen ti l e Exp o sed Popula t ion R i s k

3

. 93 -1. 25 x 10 -4 1. 95 - 2. 42 x 10 -4

5 1

. 63 - 2. 02 x 10 -4 3. 47 - 3. 9 x 10 -4

10 2. 41 - 2. 99 x 10 -4 5. 23 - 6. 09 x 10 -4

20 3. 07 - 3. 85 x 10 -4 6. 58 - 8. 37 x 10 -4

1 A c tual r i sks could be low e r

, giv en the v a r i ous uncer tainties discussed, or higher, as these estimates assume that the probability of illness from arsenic

ex posure in the U

. S. is equal to the probability of death from arsenic ex posure among the arsenic study group.

2 T he estimated risks are male and female risks combined.



### Exhi bi t 5- 4 ( b )

Cancer Ri sks f o r U. S. Popul at i ons Exposed at or A bov e M C L O p t i ons, A f t e r T r eat ment 1, 2

(With A d justment for A r senic Exposure in Food and Cooking Water)

MC L (μg/L) M ean Exp o sed Popula t ion R i s k 90 th Percen ti l e Exp o sed Popula t ion R i s k

3

. 11 -. 13 x 10 -4

. 22 - . 26 x 10 -4

5

. 27 - . 32 x 10 -4

. 55 - . 62 x 10 -4

10

. 63 - . 76 x 10 -4 1. 32 - 1. 54 x 10 -4

20 1. 1 - 1. 35 x 10 -4 2. 47 - 2. 89 x 10 -4

1 A c tual r i sks could be low e r

, giv en the v a r i ous uncer tainties discussed, or higher, as these estimates assume that the probability of illness from arsenic

ex posure in the U

. S. is equal to the probability of death from arsenic ex posure among the arsenic study group.

2 T he estimated r i sks ar e for males.



### Exhi bi t 5- 4 ( c )

Cancer Ri sks f o r U. S. Popul at i ons Exposed at or A bov e M C L O p t i ons, A f t e r T r eat ment 1

(Low er Bound With Food and Cooking Water A d justment, Upper Bound Without Food and Cooking Water A d justment)

MC L (μg/L) M ean Exp o sed Popula t ion R i s k 90 th Percen ti l e Exp o sed Popula t ion R i s k

3

. 11 -1. 25 x 10 -4

. 22 - 2. 42 x 10 -4

5

. 27 - 2. 02 x 10 -4

. 55 - 3. 9 x 10 -4

10

. 63 - 2. 99 x 10 -4 1. 32 - 6. 09 x 10 -4

20 1. 1 - 3. 85 x 10 -4 2. 47 - 8. 37 x 10 -4

1 A c tual r i sks could be low e r

, giv en the v a r i ous uncer tainties discussed, or higher, as these estimates assume that the probability of illness from arsenic

ex posure in the U

. S. is equal to the probability of death from arsenic ex posure among the arsenic study group.

Chapter 5, Benefits Analys is 5-14 Ar s e nic in D r inking Water Rule EA

### 5.3.3 N on- Transient N on- C o mmunit y Wat e r Sy st ems

Determination of System and Individual Exposure Factors

I n the past, the Ag ency has directly used SDW I S population estimates for assessing the risks
posed to users of NTNC water sy stems. I n other words, it was assumed that the same person

received the ex posure on a y ear-round basis. Under this approach it was g e nerally assumed that

all NTNC users were ex posed for 270 day s out of the y ear and obtained 50 percent of their daily
consumption from these sy stems. As a comparison, TNC users are assumed to use the sy stem for
only ten day s per y ear.

W i t h t h e recent com p l e t i on of Geometries and Characteristics of Public W a ter Systems (EP A

, 1999a), however, the Ag ency has developed a more comprehensive understanding of NTNC

water sy stems. These sy stems provide water in due course as part of operating another line of

busi n ess. Many sy st em s are cl assi fi ed as NTNC , rat h er t h an TNC

, wat e r sy st em s sol e l y because
they employ sufficient workers to trig g e r the “25 persons served for over six months out of the

y e a r ” r e quir e me nt. Clie nt utiliza tion of the s e sy ste m s is a c tua lly muc h le ss a nd mor e simila r to

e x posur e in TNC wa te r sy ste m s. F o r insta n c e

, it is f a ir ly impla usible tha t hig h wa y r e st a r e a s along interstate hig h way s serve the same population on a consistent basis (with the ex ception of
long distance truckers). Nevertheless, there are hig h way rest areas in both NTNC and TNC

sy stem inventories. The Geometries and Characteristics of Public W a ter Systems report sug g e sts that population fig u res reported in SDW I S that have been used for past risk assessments

g e nerally appear to reflect the number of workers in the establishment coupled with peak day

customer utiliz ation.

Under these conditions, use of the SDW I S fig u res for population g r eatly overestimates the actual

individual ex posure risk for most of the ex posed population and also severely underestimates the
number of people ex posed to NTNC water. 1 

### Adequately characteriz ing individual and
population risks necessitates some adjustment of the S D W I S population fig u res. For chronic

c onta mina n ts, suc h a s a r se nic

, he a lth da ta r e f l e c t the c onse que nc e s of a

lif e time of e x posur e

. Conse que ntly , r i sk a sse ssme n t r e quir e s the e s tima tion of the por tion of tota l lif e time dr inking

wat e r consum pt i on t h at any one i ndi vi dual woul d recei ve from a part i c ul ar t ype of wat e r sy st em

. I n tur n, one ne e d s to e s tima te the a ppr opr ia te por tions f o r

da ily , da y s pe r y e a r , a nd y e a r pe r lifetime consumption. These estimates need to be prepared for both the workers at the facility

a nd the “ c u stome r s” of the f a c ility

.

Thi s adj u st m e nt was accom p l i s hed t h roug h a com p rehensi v e revi ew of g overnm e nt and t r ade
association statistics on entity utiliz ation by Standard I ndustry Classification (SI C ) code.

1 F o r exam ple, airports cons titute only about a hundred of the N T N C w a ter s y s t em s

. Was hing ton’s Reag an

N a tional and D u lles

, D a llas / F o rt Worth, S eattle/Tacom a , and P itts burg h airports are the f i v e larg es t of the airports

. S D WIS reports that thes e f i v e airports s e rv e about 300,000 people. In actuality , the Bureau of Trans portation

S t atis tics (BTS ) s u g g e s t that they s e rv e about elev en m illion pas s e ng ers per y ear. Exam ination of this inf o rm ation

and other BTS s t atis tics s u g g e s t s that thes e airports s e rv e clos er to s e v e n m illion unique indiv i duals ov er the cours e
of

a y ear and that exposure occurs on an av erag e of ten tim es per y ear per indiv i dual custom er, not 270 tim es.

Chapter 5, Benefits Analys is 5-15 Ar s e nic in D r inking Water Rule EA

### These fig u res, coupled with SDW I S information relating to the portion of a particular industry
served by non-community water sy stems, made possible the development of two estimates
needed for the risk assessment: customer cy cles per y ear and worker per population served per
day

. These numbers are required to disting u ish the more frequent and long er duration ex posure of workers from that of sy stem customers. 2 

### A more detailed characteriz ation of the derivation of

these numbers is contained in the docket. Ex hibit 5-5 provides the factors used in the NTNC risk

assessment to account for the intermittent nature of ex posure.

Exhi bi t 5- 5
Exposure Fact ors Used i n t h e NT NC Ri sk A ssessment

NT NCW S # cy cl es

per y r w o rker/ pop/day w o rker

fracti o n

daily w o rker day s /y r w o rker

exposure

y

ears custom er
fracti o n

daily day s of

use/ y r custom er

exposure

y

ears

Wa t e r

w hol es al ers 1. 00 0. 000

- - - 0

. 2 5 270 70

Nurs i ng hom es 1. 00 0. 230 0. 50 250 40 1. 00 365 10

Churc hes 1. 00 0. 010 0. 50 250 40 0. 50 52 70

Gol f / c ount ry c l ubs 4. 50 0. 110 0. 50 250 40 0. 50 52 70

Food ret a i l e rs 2. 00 0. 070 0. 50 250 40 0. 25 185 70

Non-f ood ret a i l e rs 4. 50 0. 090 0. 50 250 40 0. 25 52 70

Res t aurant s 2

. 0 0 0

. 070 0. 50 250 40 0. 25 185 70

2 F o r exam ple, trav el indus try s t atis tics prov ide inf o rm ation on total num bers of hotel s t ay s

, v acancy rates

, trav eler ag e rang es , and av erag e duration of s t ay . Thes e f i g u res can be com b ined with the S D WIS peak day
population es tim ates to allocate daily population am ong w o rk ers

, cus t om ers

, and v acancies

. The com b ination of

thes e f actors prov ides an es tim ate of the num ber of independent cus t om er cy cles experienced in a y ear.

Chapter 5, Benefits Analys is 5-16 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 5
Exposure Fact ors Used i n t h e NT NC Ri sk A ssessment ( c ont i nued)

NT NCW S #

cy cl es

per y r w o rker/ pop/day w o rker

fracti o n

daily w o rker day s /y r w o rker

exposure

y

ears custom er
fracti o n

daily day s of

use/ y r custom er

exposure

y

ears

Hot e l s / m ot el s 86. 00 0. 270 0. 50 250 40 1. 00 3. 4 4 0

P r i s ons / j ai l s 1. 33 0. 100 0. 50 250 40 1. 00 270 3

S e rvi c e s t at i ons 7. 00 0. 060 0. 50 250 40 0. 25 52 54

A g ri c u l t ural produc t s / s ervi c e s 7

. 0 0 0

. 125 0. 50 250 40 0. 25 52 50

Dayc are c ent ers 1

. 0 0 0

. 145 0. 50 250 10 0. 50 250 5

S c hool s 1

. 0 0 0

. 073 0. 50 200 40 0. 50 200 12

S t at e park s 26. 00 0. 016 0. 50 250 40 0. 50 14 70

M e d i c a l fa c ilitie s 1 6

. 4 0 0

. 0 2 2 0

. 5 0 2 5 0 4 0 1

. 0 0 6

. 7 1 0

. 3

Cam pgrounds / R V 22. 50 0. 041 0. 50 180 40 1. 00 5 5 0

Federal park s 26. 00 0. 016 0. 50 250 40 0. 50 14 70

Hi ghw ay res t areas 50. 70 0. 010 0. 50 250 40 0. 50 7. 2 7 0

M i sc. r e cr e a t i o n

se r v i c e 26. 00 0. 016 0. 50 250 40 1. 00 14 70

Fores t S e rvi c e 26. 00 0. 016 1. 00 250 40 1. 00 14 50

I n t e rs t a t e c a rri e rs 93. 00 0. 304 0. 50 250 40 0. 50 2 7 0

A m us em ent park s 90. 00 0. 180 0. 50 250 10 0. 50 1 7 0

S u m m e r c a m p s 8

. 5 0 0

. 100 1. 00 180 10 1. 00 7 1 0

A i rport s 36. 50 0. 308 0. 50 250 40 0. 25 10 70

M ilita r y b a s e s 1

. 0 0 0 0

. 5 0 2 5 0 4 0

N o n

- w a te r u t ilitie s 1 .0 0 0 0

. 5 0 2 5 0 4 0

Of f i c e park s 1. 000 0. 50 250 40

M anuf ac t u ri ng: Food 1. 000 0. 50 250 40

M anuf ac t u ri ng:
Non-f ood 1. 000 0. 50 250 40

Landf ills 1. 000 1. 00 250 40

Fi re depart m ent s 1

. 000 1. 00 250 40

Cons t r uc t i on 1. 000 1. 00 250 40

M i ni ng 1. 000 1. 00 250 40

M i grant l abor c a m p s 1

. 000 1. 00 250 40



### Once the population adjustment factors were derived, it was possible to determine the actual
population served by NTNC water sy stems. Ex hibit 5-6 provides a breakout of these fig u res by

ty

pe of establishment.

Chapter 5, Benefits Analys is 5-17 Ar s e nic in D r inking Water Rule EA

### Althoug h not included in Ex hibit 5-6, there are other equally important characteristics to note
about these sy stems. W ith notable ex ceptions (such as the airports in W a shing t on, DC, and
Seattle), the sy stems g e nerally serve a fairly small population on any g i ven day

. I n fact, 99
percent of the sy stems serve fewer than 3,300 users on a daily basis. This means that water
production costs will be relatively hig h on a per g a llon basis.

Exhi bi t 5- 6 Composi t i on of NT NCs ( P ercent a ge of T o t a l NT NCWS Popul at i on Serv ed by Sect or)

Schools 9

. 7 M edical

F a cilit ies 8 I nt erst at e Carriers 7

. 1 Cam pgrounds 1. 3

M anufact u ring 2. 7 R est aurant s 0

. 9 St at e Park s 8

. 6 M i sc.
Recreat ion 1. 8

Airport s 26. 1 N on-food Ret a il 1. 6 A m u sem ent Park s 17. 7 O t her 3. 5

O ffice Park s 0

. 6 Hot e ls/ M ot els 9

. 2 Highway Rest Area 1. 0



### R i sk C a lculat ion

C a l c ul at i ons of i ndi vi dual com b i n ed ri sk for bl adder and l ung cancer were prepared for each

industrial sector. Even within a g i ven sector, however, risk varies as a function of an
individual’s relative water consumption, body weig ht, vulnerability to arsenic ex posure, and the

water arsenic concentration. Computationally , risks were estimated by performing Monte-Carlo

mode ling

. The a ppr oa c h use d wa s simila r to the mode ling te c hnique a pplie d in e s tima ting the
community water sy stem risk estimation, but with two notable ex ceptions. F i rst, each realiz ation

in a g i ve n se c t or wa s multiplie d by the por tion of lif e time e x posur e f a c t or pr e s e n te d in Ex hibit
5-6 to reflect the decreased consumption associated with the NTNC sy stem. Second, relative

e x posur e f a c t or s we r e limite d to a g e

- spe c i f i c r a ting s whe r e a ppr opr ia te

. 3 

### F o r ex ample, in the
case of school children, water consumption rates and weig hts for 6- to 18-y ear-olds were used.

To illustrate the process, it was assumed that a child would attend only NTNCW S -served schools
for all twelve y ears, a somewhat improbable likelihood. F u rther, it was assumed that a child
would g e t half of his or her daily water consumption at school (for an averag e first g r ader this
would correspond to roug hly nine ounces of water per school day )

. F i nally , it was assumed that
the child would have perfect attendance and attend school for 200 day s per y ear.

The distribution of overall population risks was determined as part of the same simulation by
developing sector weig hting s to reflect the total portion of the NTNCW S population served by

each sector. P opulation weig hted proportional sampling of the individual sectors provided an
overall distribution of risk among those ex posed at NTNC sy stems.

3 For exam ple, w a ter consum ption am ong school children w a s w e ig hted to ref l ect consum ption betw een

ag es 6 and 18, w h ile f actory w o rk er consum ption w a s w e ig hted ov er ag es 20 to 64.

Chapter 5, Benefits Analys is 5-18 Ar s e nic in D r inking Water Rule EA

### Ex hibit 5-7 presents a summary of the risk analy s es for reg u lation of arsenic in NTNC water

sy stems. Ex hibit 5-8 presents risk fig u res for three particular sets of individuals: children in
day care centers and schools, and construction workers. Construction and other strenuous activity
workers comprise an ex tremely small portion of the population served by NTNC sy stems (less
than 0.1 percent), but face the hig h est relative risks of all NTNCW S users (90 th 

### pe r c e n tile r i sks of

0.4 to 2.3 x 10 -4 

### lif e time r i sk)

.

Exhi bi t 5- 7

M ean Cancer Ri sks ( B l a dder and Lung combi n ed)

, Exposed Popul at i on, and A nnual Cancer Benef i t s i n NT NCs

A r sen i c

Le ve l M e a n Ex pos e d Popula t ion

Ri sk (10 -4 ) T o ta l B l a dde r a nd Lung

Can cer Cases A v o i d e d

p e r Year

(μg/L) lower

bound upper
bound lower

bound upper
bound

3 0

. 0000657 0. 000952 0. 6 2

. 2 5

5 0

. 000162 0. 00157 0. 53 1. 78

10 0. 000374 0. 00243 0. 36 1. 13

20 0. 00064 0. 00322 0. 16 0. 53

baseline 0

. 000853 0. 00391 0. 65 2. 98



### Exhi bi t 5- 8

Sensi t i v e G r oup Ev al uat i on of Li f e t i me Combi n ed Cancer Ri sks

G r o u p M ean Ri sk 90 th Pe r c e n tile R i s k

F o rest Serv ice, Const r uct i on and M i ning W o rk ers 0

. 2 - 1. 2 x 10 -4 0. 4 - 2. 3 x 10 -4

School Children 0

. 2 - 1. 4 x 10 -5 0. 5 - 2. 8 x 10 -5

Day Care Children 1

. 1 - 7. 3 x 10 -6 0. 25 - 1. 5 x 10 -5



### However, there is considerable uncertainty about these ex posure numbers, as it is quite likely that
they overestimate consumption. I t is not possible to determine from the analy s is of NTNC

sy stems the ex tent to which there is overlap of individual ex posure between the various sectors.

NTNC e s ta blishme n ts g e ne r a lly c onstitute a sma ll por tion of the i r SI C se c t or s. I n c onjunc tion
with the observation that NTNC populations would only serve about 11 percent of the total
population if all sectors were mutually ex clusive, it would seem reasonable to treat the SI C

g r oups independently

. However, it is equally plausible that there are communities where one
individual mig ht g o from an NTNC day care center to a series of NTNC schools and then work in

a n NTNC f a c t or y

. Unf o r t una te ly , the Ag e n c y pr e s e n tly ha s no ba sis f o r

qua ntita tive l y e s tima ting

the ex tent to which this would occur.

Chapter 5, Benefits Analys is 5-19 Ar s e nic in D r inking Water Rule EA

### 5.4 R isk A ssessment R esult s and B e nef i t Est i mat e s

5.4.1 C ases A v oided

The lower and upper bound risk estimates from Ex hibit 5-4 (c) were applied to the ex posed
population to g e nerate cases avoided for CW S sy stems serving fewer than one million customers.

B ecause the actual arsenic occurrence was known for the very larg e sy stems (those serving over a
million c u stome r s) , the i r sy ste m

- s pe c i f i c a r se nic oc c u rr e nc e distr i butions c ould be dir e c tly
computed. The sy stem specific arsenic distributions allowed direct calculation of avoided cancer

c a s e s

. The pr oc e ss, de sc r i be d in de ta il in Appe ndix B

, utilize s the sa me r i sk e s tima te s f r o m Morales et al. (2000) that were used in deriving the number of cases avoided in smaller CW S

sy ste m s. Ca se s a voide d f o r

NTNC sy ste m s we r e a l so c o mpute d se pa r a te ly , utilizing f a c t or s developed to account for the intermittent nature of the ex posure.

An upper bound adjustment was made to the number of bladder cancer cases avoided to reflect a
possible lowe r mor t a lity r a te in Ta iwa n tha n wa s a ssume d in the r i sk a sse ssme n t pr oc e s s
described earlier. W e also made this adjustment in the J une 22, 2000, proposal. I n the Taiwan
study area, information on arsenic related bladder and lung cancer deaths was reported. I n order

to use the s e da ta to de te r mine the pr oba bility of c ontr a c ting bla dde r a nd lung c a n c e r a s a r e sult of

ex posure to arsenic, a probability of mortality g i ven the onset of arsenic induced bladder and
lung cancer among the Taiwanese study population must be assumed. The study area in Taiwan
is a section where arsenic concentrations in the water are very hig h by comparison to those in the
U.S., and is an area of low incomes and poor diets, where the availability and quality of medical

c a r e is not of hig h qua lity by U.S. sta nda r d s. I n its e s tima te of bla dde r c a n c e r r i sk, the Ag e n c y

a ssume d tha t within the Ta iwa n e s e study a r e a

, the pr oba bility of c ontr a c ting bla dde r c a nc e r wa s

r e la tive l y c l ose to the pr oba bility of dy ing f r o m bla dde r c a nc e r ( t ha t is, tha t the bla dde r c a nc e r
inc i de nc e r a te wa s e qua l to the bla dde r c a n c e r mor t a lity r a te )

.

We do not ha ve da ta on the r a te s of sur v iva l f o r

bla dde r c a n c e r in the Ta iwa n e s e villa g e s in the
study and at the time of data collection. W e do know that the relative survival rates for bladder
cancer in developing countries overall rang ed from 23.5 percent to 66.1 percent in 1982-1992

( Cancer Survival in Developing Countries, I n t e rnat i onal Ag ency for R e search on C a ncer, W o rl d
Health Org a niz a tion, Publication No. 145, 1998). W e also have some information on annual
bladder cancer mortality and incidence for the g e neral population of Taiwan in 1996. The ag eadjusted annual incidence rates of bladder cancer for males and females, respectively

, were 7.36
and 3.09 per 100,000, with corresponding annual mortality rates of 3.21 and 1.44 per 100,000
(correspondence from Chen to Herman Gibb, J a nuary 3, 2000). Assuming that the proportion of
males and females in the population is equal, these numbers imply that the mortality rate for
bladder cancer in the g e neral population of Taiwan, at present, is 45 percent. Since survival rates
have most likely improved over the y ears since the orig inal Taiwanese study , this number
represents a lower bound on the survival rate for the orig inal area under study (that is, one would

not e x pe c t a hig h e r r a te of sur v iva l in tha t a r e a a t tha t time )

. This ha s implic a tions f o r

the

bla dde r c a n c e r r i sk e s tima te s f r o m the Ta iwa n da ta

. I f the r e we r e a n y pe r s ons with bla dde r cancer who recovered and died from some other cause, then our estimate underestimated risk;

that is, there were more cancer cases than cancer deaths. B a sed on the above discussion, we

think bla dde r c a n c e r inc i de nc e c ould be no mor e tha n two time s bla dde r c a n c e r mor t a lity ; a n d

tha t a n 80 pe r c e n t mor t a lity r a te would be pla u sible

.

Chapter 5, Benefits Analys is 5-20 Ar s e nic in D r inking Water Rule EA

### Thus, we have adjusted the upper bound of cases avoided, which is used in the benefits analy s is,
to reflect a possible mortality rate for bladder cancer of 80 percent. B ecause lung cancer mortality rates are quite hig h, about 88 percent in the U.S. (EPA, 1998b), the assumption was

ma de tha t a ll lung c a n c e r s in the Ta iwa n study a r e a r e sulte d in f a ta litie s.

The num ber of bl adder, l ung , and com b i n ed bl adder and l ung cases avoi ded at each MC L are
shown in Ex hibits 5-9 (a), 5-9 (b), and 5-9 (c). These cases avoided include both CW S and

NTNC cases. The number of bladder cancer cases avoided rang e from 28.6 to 76.8 at an MCL of
3 μg /L , 25.6 to 55.7 at an MCL of 5 μg /L , 18.7 to 31.0 at an MCL of 10 μg /L , and 9.9 to 10.6 at

an MCL of 20 μg /L . The number of lung cancer cases avoided rang e from 28.6 to 61.5 at an

MCL of 3 μg /L , 25.6 to 44.5 at an MCL of 5 μg /L , 18.7 to 24.8 at an MCL of 10 μg /L , and 8.5 to

9.9 at an MCL of 20 μg /L . The number of combined bladder and lung cancer cases avoided rang e
from 57.2 to 138.3 at an MCL of 3 μg /L , 51.1 to 100.2 at an MCL of 5 μg /L , 37.4 to 55.7 at an

MCL of 10 μg /L , and 19.0 to 19.8 at an MCL of 20 μg /L

.

The c a s e s a voide d we r e divide d into pr e m a t ur e f a ta lity a nd mor b idity c a s e s ba se d on U.S.

mor t a lity r a te s. I n the U.S. a ppr ox ima te ly one out of f

our individua ls who is dia g nose d with

bl adder cancer act ual l y di es from bl adder cancer. The mor t a lity r a te f o r

the U.S. is ta ke n f r o m a cost of illness study recently completed by EPA (EPA, 1998b). F o r those diag nosed with bladder

c a n c e r a t the a v e r a g e a g e of dia g nosis ( 70 y e a r s) , the pr oba bilitie s of dy ing of tha t dise a s e dur ing
each y ear post

- di ag nosi s were sum m e d over a 20-y ear peri od t o obt ai n t h e val u e of 26 percent

. Mortality rates for U.S. bladder cancer patients have decreased overall by 24 percent from 1973

to 1996. F o r lung cancer, mortality rates are much hig h er. The comparable mortality rate for
lung cancer in the U.S. is 88 percent.

Exhi bi t 5- 9 ( a )

A nnual Bl adder Cancer Cases A v oi ded

fro m R e d u c in g A r s e n ic in C W S s and NT NCs



### A r senic Lev e l (μg/L) R e duced

M o rt alit y C ases* Reduced M o rbidit y C ases* Tot al C a ncer C a ses

A v oided *****

3 7 .4 - 20.0 21.2 - 56.9 28.6 - 76.8

5 6 .6 - 14.5 18.9 - 41.2 25.6 - 55.7

10 4.9 - 8.0 13.8 - 22.7 18.7 - 31.0

20 2.6- 2.8 7 .3 - 7.8 9 .9 - 10.6

* T he low e r-end estimate of bladder cancer cases av oided is calculated using the low e r-end risk estimate from

Ex hibit 5-9(c) and assumes that the conditional probability of mortality among the T a iw anese study group w a s 100
percent. T he upper-end estimate of bladder cancer cases av oided is calculated using the upper-end risk estimate

from Ex hibit 5-9(c) and assumes that the conditional probability of mortality among the T a iw anese study group w a s 80 percent.

Chapter 5, Benefits Analys is 5-21 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 9 ( b )

A nnual Lung Cancer Cases A v oi ded

f r om Reduci ng A r seni c i n CWSs and NT NCs



### A r senic Lev e l (μg/L) R e duced

M o rt alit y C ases* Reduced M o rbidit y C ases* Tot al C a ncer C a ses

A v oided*

3 25.2 - 54.1 3 .4 - 7.4 28.6 - 61.5

5 22.5 - 39.2 3 .1 - 5.3 25.6 - 44.5

10 16.4 - 21.8 2 .2 - 3.0 18.7 - 24.8

20 7.4 - 8.7** 1 .0 - 1.2** 8 .5 - 9.9**

* T he low e r and upper-end estimates of lung cancer cases av oided are calculated using the risk estimates from

Ex hibit 5-9 (c) and assume that the conditional probability of mortality among the T a iw anese study group w a s 100
percent.

* * F or 20 μ g /L, the proportional reduction from the low e r lev e l risk base case is greater than the proportional reduction from the higher lev e l risk base case. T hus, the number of estimated cases av oided is higher at 20 μ g /L using the estimates adjusted for uncertainty

.



### Exhi bi t 5- 9 ( c )

A nnual T o t a l Cancer Cases A v oi ded

f r om Reduci ng A r seni c i n CWSs and NT NCs



### A r senic Lev e l (μg/L) R e duced

M o rt alit y C ases* Reduced M o rbidit y C ases* Tot al C a ncer C a ses

A v oided*

3 32.6 - 74.1 24.6 - 64.2 57.2 - 138.3

5 29.1 - 53.7 22.0 - 46.5 51.1

- 100.2

10 21.3 - 29.8 16.1 - 25.9 37.4

- 55.7

20 10.2 - 11.3** 8 .5 - 8.8 19.0

- 19.8**

* T he low e r-end estimate of bladder cancer cases av oided and the lung cancer estimates assume that the conditional probability of mortality among the T a iw anese study group w a s 100 percent. T he upper-end estimate of

bladder cancer cases av oided is calculated using the assumption that the conditional probability of mortality among
the T a iw anese study group w a s 80 percent.

* * F or 20 μ g /L, the proportional reduction from the low e r lev e l risk base case is greater than the proportional reduction from the higher lev e l risk base case. T hus the number of estimated cases av oided is higher at 20 μ g /L using the estimates adjusted for uncertainty

.



### 5.4.2 E conomic Measurements of the Value of Risk Reduction

The evaluation stag e in the analy s is of risk reductions involves estimating the value of reducing

the r i sks. The f o llowing se c tions de sc r i be the use of be ne f its va lua tion te c hnique s to e s tima te the
value of the risk reductions attributable to the reg u latory options for arsenic in drinking water.

F i rst, the approach for valuing the reductions in fatal risks is described, followed by a description
of the approach for valuing the reductions in non-fatal risks.

The benefits described in the primary analy s is of this Economic Analy s is are assumed to beg i n to

accrue on t h e effect i v e dat e of t h e rul e and are based on a cal cul a t i on referred t o as t h e “val ue of

a st at i s t i cal l i f e” (VS L ).

Chapter 5, Benefits Analys is 5-22 Ar s e nic in D r inking Water Rule EA

### Of the ma ny VSL studie s , the Ag e n c y r e c o mme nds using e s tima te s f r o m 26 spe c if ic studie s tha t have been peer revi ewed and ex t e nsi v el y revi ewed wi t h i n t h e Ag ency

. 4 

### The s e e s tima te s, whic h
are derived from wag e -risk and conting e nt valuation studies, rang e from $0.7 million to $16.3
million and approx imate a W i ebull distribution with a mean of $4.8 million (in 1990 dollars).

Most of these 26 studies ex amine willing n ess to pay in the contex t of voluntary acceptance of
hig h er risks of immediate accidental death in the workplace in ex chang e for hig h er wag e s. This
value is sensitive to differences in population characteristics and perception of risks being

valued. This value could also be updated to include chang e s in income from 1990 to 1999,
which reflects the difference between the study population and the affected population, and

would inc r e a s e mone ta r y be ne f its sinc e inc o me g r owth in tha t time pe r i od ha s be e n positive

.

EPA updated the VSL estimate from The Benefits and Costs of the Clean Air Act, 1970 to 1990 report to a value of $5.8 million in 1997 dollars, according to internal g u idance on economic
analy s es (B ennett, 2000). I n order to directly compare the estimated national costs of
compliance, the VSL used in this analy s is was updated from the J a nuary 1997 value to $6.1
million in May 1999 dollars, using the Consumer Price I ndex (CPI -U) for all items.

Several factors may influence the estimate of economic benefits associated with avoided cancer

f

a ta litie s, inc l uding :

1. A possible “cancer premium” (i.e., the additional value or sum that people may be willing

to pa y to a void the e x pe r i e n c e s of dr e a d, pa in a nd suf f

e r i ng , a nd diminishe d qua lity of lif e associated with cancer-related illness and ultimate fatality );

2. The willing n e ss of pe ople to pa y mor e ove r time to a void mor t a lity r i sk a s the i r inc o me rises;

3. A possible premium for accepting involuntary risks as opposed to voluntary assumed

risks;

4. The g r eater risk aversion of the g e neral population compared to the workers in the wag e

risk valuation studies;

5. “ A ltr uism” or the willing n e ss of pe ople to pa y mor e to r e duc e r i sk in othe r se c t or s of the
population; and

6. A c onside r a tion of he a lth sta t us a nd lif e y e a r s r e ma ining a t the time of pr e m a t ur e

mor t a lity

.

Use of c e r ta in of the s e f a c t or s ma y sig n if ic a n tly inc r e a s e the pr e s e n t va lue e s tima te

. EPA
therefore believes that adjustments should be considered simultaneously

. The Ag ency also
believes that there is currently neither a clear consensus among economists about how to

si m u l t a neousl y anal y z e each of t h ese adj u st m e nt s, nor are t h ere adequat e em pi ri cal dat a t o support definitive quantitative estimates for all potentially sig n ificant adjustment factors. As a
result, the primary estimates of economic benefits presented in the analy s is of this rule rely on the

una djuste d e s tima te

.

4 U.S. Env i ronm ental Protection Ag ency

, T h e Benefits and Cos t s of the Clean Air Act, 1970 to 1990

, October 1997, Appendix I; and U.S. Env i ronm ental Protection Ag ency

, Guidelines for Preparing Economic
Analys is ( R eview D r aft) , J une 1999, Chapter 7.

Chapter 5, Benefits Analys is 5-23 Ar s e nic in D r inking Water Rule EA

### To a sse ss the impa c t s of the s e othe r f

a c t or s, EPA pr e s e n ts a se nsitivity a n a l y s is tha t e x a mine s the
impacts of chang e s in assumptions of the latency period and incorporation of income g r owth, etc.
This sensitivity analy s is is g i ven in Section 5.5.

To e s tima te the mone ta r y va lue of r e duc e d f a ta l r i sks ( i .e ., r i sks of pr e m a t ur e de a t h f r o m c a n c e r )
predicted under different reg u latory options, VSL estimates are multiplied by the number of

pr e m a t ur e f a ta litie s a voide d. VSL doe s not r e f e r

to the va lue of a n ide n tif ia ble lif e

, but inste a d to the value of small reductions in mortality risks in a population. A “statistical” life is thus the

sum of small individual risk reductions across an entire ex posed population. F o r ex ample, if
100,000 people would each ex perience a reduction of 1/100,000 in their risk of premature death
as the result of a reg u lation, the reg u lation can be said to “save” one statistical life (i.e., 100,000

x 1/100,000). I f each member of the population of 100,000 were willing to pay $20 for the stated
risk reduction, the corresponding value of a statistical life would be $2 million (i.e., $20 x

100,000). VSL estimates are appropriate only for valuing small chang e s in risk; they are not values for saving a particular individual’s life.

Estimates of the willing n ess to pay to avoid treatable, non-fatal cancers are the ideal economic

measures used to value reductions in nonfatal risks. Unfortunately , this information is not

a v a ila ble f o r

bla dde r or lung c a n c e r

. Howe ve r

, willing n e ss to pa y ( W TP) da ta to a void c h r onic
bronchitis is available and has previously been employ ed by the Office of Ground W a ter and
Drinking W a ter (the microbial/disinfection by -product [ M DB P] rulemaking ) as a surrog a te to

estimate the W T P to avoid non-fatal bladder cancer. A W T P central tendency estimate of $607,162 (in May 1999 dollars) is used to monetiz e the benefits of avoiding non-fatal cancers (this value was updated from the $536,000 value EPA updated to 1997 dollars from the Viscusi

et al. [ 1991] study ).

To g r ound-truth the use of the chronic bronchitis W T P value as a prox y for W T P for the

a voida nc e of non- f a ta l c a s e s of bla dde r c a n c e r , EPA ha s a l so de ve lope d c o st- o f

- illne ss e s tima te s for bladder cancer, as reported in Ex hibit 5-10. These estimates of direct medical costs are
derived from a study conducted by B a ker et al. (1989), which uses data from a sample of

Medicare records for 1974-1981. These data include the total charg e s for inpatient hospital stay s,
skille d nur sing f a c ility sta y s, home he a lth a g e n c y c h a r g e s, phy sic i a n se r v ic e s , a nd othe r
outpa tie nt a nd me dic a l se r v ic e s

. EPA c o mbine d the s e da ta with e s tima te s of sur v iva l r a te s a n d

tr e a tme nt time pe r i ods to de te r mine the a v e r a g e c o sts of initia l tr e a tme nt a nd ma inte na nc e c a r e for patients who do not die of the disease. This value of $178,405, at a three percent discount

r a te , se r v e s a s a low- e nd e s tima te of the WTP to a void bla dde r c a n c e r a nd doe s not inc l ude the
value of avoided pain and suffering , lost productivity , or risk premium.

Chapter 5, Benefits Analys is 5-24 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 10

Li f e t i me A v oi ded M e di cal Cost s f o r Surv i v ors ( p rel i m i n ary est i m at es 1 

### )

T y pe of

Can cer Date Data

Co l l ected Nu mb er o f Cases Stu d i ed Estimated

M o r t a lity R a te M ean Val u e p e r
Non-fatal Case (D is c ount R a te ) 1

Bladder 1974-1981 5% of 1974

M edicare pat ient s (sam ple from nat ional st at ist i cs) 26% (aft er 20 y ears) $178, 405 (3%) $147, 775 (7%) (for t y pical indiv i dual diagnosed at age 70)

Source: U

. S. Env i ronmental Protection Agency

, C o st of Illness H andbook (draft) , September 1998.

1 M a y 1999 dollars.



### 5.4.3 E st imat es of C a ncer H ealt h B e nef i t s of A r senic R e duct i on

B e ne f its e s tima te s we r e c a l c u la te d ba se d on the numbe r of bla dde r a nd c a n c e r c a se s a voide d, a s

g i ven in Ex hibits 5-9 (a-c). The total cases avoided were divided into fatal and non-fatal cases,
based on survival information (EPA, 1998b). The avoided premature fatalities were valued

ba se d on the VSL e s tima te s disc usse d e a r lie r

, a s r e c o mme nde d by c u r r e nt EPA g u ida n c e f o r cost/benefit analy s is (EPA, 2000c). The avoided non-fatal cases were valued based on the
willing n e ss to pa y e s tima te s f o r

the a voida nc e of c h r onic br onc hitis.

The results of the benefits valuation are presented in Ex hibit 5-11. Total annual health benefits
resulting from bladder cancer cases avoided rang e from $58.2 to $156.4 million at an MCL of
3 μg /L , $52.0 to $113.3 million at an MCL of 5 μg /L , $38.0 to $63.0 million at an MCL of 10

μg /L , and $20.1 to $21.5 million at an MCL of 20 μg /L

. Total annual health benefits from
avoided cases of lung cancer rang e from $155.6 to $334.5 million at an MCL of 3 μg /L , $139.1

to $242.3 million at an MCL of 5 μg /L , $101.6 to $134.7 million at an MCL of 10 μg /L , and

$46.1 to $53.8 million at an MCL of 20 μg /L

. I n addition, other potential non-quantifiable health

benefits are summariz e d in Ex hibit 5-11.

Chapter 5, Benefits Analys is 5-25 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 11

T o t a l A nnual Cost

, Est i mat e d M onet i zed T o t a l Cancer Heal t h Benef i t s and

N o n

- Qu a n tifia b le H e a l th B e n e fits fro m R e d u c in g A r s e n ic in P W S s ($ millio n s )

A r seni c

Level ( μ g/L) T o t a l A nnual

Co st (7%) A nnual B l adder

Cancer Heal th

Ben e fi ts 1,2 A nnual Lung

Cancer Heal th

Ben e fi ts 1,2 T o t a l A nnual

Heal th Ben e fi ts 1,2 P o ten t i a l No n

- Qu an ti fi ab l e

Heal th Ben e fi ts

3 $792. 1 $58. 2 - $156. 4 $155. 6 - $334. 5 $213. 8 - $490. 9 • S k i n Canc er

• K i dney Canc er

• C anc er of t he Nas a l

P a s s ages

• L i v er Canc er

• P ros t at e Canc er

• C ardi ovas c u l a r E f f e c t s

• P ul m onary E f f e c t s

• I m m unol ogi c a l E f f e c t s

• N eurol ogi c a l E f f e c t s

• E ndoc ri ne E f f e c t s

• R eproduc t i ve and

Devel opm ent al E f f e c t s 5 $471. 7 $52. 0 - $113. 3 $139. 1 - $242. 3 $191. 1 - $355. 6

10 $205. 6 $38. 0 - $63. 0 $101. 6 - $134. 7 $139. 6 - $197. 7

20 $76. 5 $20. 1 - $21. 5 $46. 1 - $53. 8 $66. 2 - $75. 3 3

1 M a y 1999 dollars.

2 T hese monetary estimates are based on cases av oided giv en in Ex hibit 5-9 (a-c).

3 For 20 μ g /L, the proportional reduction from the low e r lev e l risk base case is greater than the proportional reduction from the higher lev e l risk base case. T hus, the number of estimated cases av oided and estimated benefits are higher at 20 μ g /L using the estimates adjusted for uncertainty

.



### 5.5 Latency and Other A d j u stments: A Sensitiv ity A n aly s is

F o r the final rulemaking analy s is, some commenters have arg u ed that the Ag ency should

c onside r a n a ssume d time la g or la te nc y pe r i od in its be ne f its c a l c u la tions. The te r m “ l a t e n c y ”
can be used in different way s , depending on the contex t. F o r ex ample, health scientists tend to

de f i ne la te nc y a s the pe r i od be g i nning with the initia l e x posur e to the c a r c i nog e n a nd e nding

whe n the c a n c e r is initia lly ma nif e ste d ( o r dia g nose d )

, while othe r s c onside r la te nc y a s the pe r i od

between manifestation of the cancer and death. L a tency

, in this case, refers to the difference

be twe e n the time of initia l e x posur e to e nvir onme n ta l c a r c inog e n s a nd the a c t ua l mor t a lity

. Use of such an approach mig ht reduce sig n ificantly the present value of health risk reduction benefits

e s tima te s.

I n the Ar se nic Rule , the Ag e n c y inc l ude d qua lita tive la ng ua g e on the la te nc y issue

, inc l uding
descriptions of other adjustments that may influence the estimate of economic benefits associated

with a voide d c a n c e r f

a ta litie s. The Ag e n c y a l so a g r e e d to a s k the Sc ie nc e Advisor y B o a r d ( S AB )
to conduct a review of the benefits transfer issues and possible adjustment factors associated with

e c onomic va lua tion of mor t a lity r i sks. A summa r y of the SAB ’ s r e c o mme nda tions is shown in

the f o llowing se c tion.

5.5.1 S A B R ecommendat i ons

EPA br oug ht this issue be f o r e the Envir onme n ta l Ec onomic s Advisor y Committe e ( EEAC) of

EPA’s SAB in a meeting held on F e bruary 25, 2000, in W a shing t on, DC. The SAB submitted a
final report on their finding s and recommendations to EPA on J u ly 27, 2000.

Chapter 5, Benefits Analys is 5-26 Ar s e nic in D r inking Water Rule EA

### The EEAC report made a number of recommendations on the adjustment factors and benefit-cost
analy s is in g e neral. A copy of the final SAB report has been placed in the record for this
rulemaking

.

The S A B EEAC not ed t h at benefi t

- cost anal y s i s , as descri bed i n t h e Ag ency ’s Gui d el i n es (for
economic analy s is), is not the only analy tical tool, nor is efficiency the only appropriate criterion
for social decision making , but notes that it is important to carry out such analy s es in an unbiased
manner with as much precision as possible. I n its report, the SAB recommended that the Ag ency

c ontinue to use a wa g e

- r i sk ba se d VSL a s its pr ima r y e s tima te ; a n y a ppr opr ia te a d justme nts tha t are made for timing and income g r owth should be part of the Ag ency ’s main analy s is, while any
other adjustments should be accounted for in sensitivity analy s es to show how results would
chang e i f t h e VS L were adj u st ed for som e of t h e m a j o r di fferences i n t h e charact eri s t i c s of t h e risk and of the affected populations.

Specifically , the SAB report recommended that (1) health benefits broug ht about by current policy initiatives (i.e., after a latency period) should be discounted to present value using the

same rate that is used to discount other future benefits and costs in the primary anal y s i s ; (2)
adjustments to the VS L for a “cancer premium” should be made as part of a se nsitiv ity anal y s i s ; (3) adjustments to the VSL for voluntariness and controllability should be made as part of a

se nsitiv ity analy s is; (4) altruism should be addressed in a se nsitiv ity analy s is and separately from
estimation of the value of a statistical cancer fatality , and the circumstances under which altruism
can be included in a benefit-cost analy s is are restrictive; (5) estimates of VSL s accruing in future

y ears should be adjusted in the primary a n a l y s is to r e f l e c t a n tic ipa t e d inc o me g r owth, using a

rang e of income elasticities; (6) adjustments to the VSL for risk aversion should be made in a

se nsitiv ity a n a l y s is; ( 7 ) it is the o re tic ally appropriate to calculate W T P for individuals whose

ag es correspond to those of the affected population, but more research should be conducted in
this area; and (8) no adjustment should be made to the VSL to reflect health status of persons

whose cancer ri sks are reduced.

Af te r c onside r ing the SAB ’ s r e c o mme nda tions, EPA ha s de ve lope d a se nsitivity a n a l y s is of the
latency structure and associated benefits for the Arsenic Rule, as described in the nex t section.
This analy s is consists of health risk reduction benefits that reflect adjustments for discounting

, incorporation of a rang e of latency period assumptions, adjustments for g r owth in income, and
incorporation of other factors such as voluntariness and controllability

. Althoug h the SAB

r e c o mme nde d a c c ounting f o r

la te nc y in a pr ima r y be ne f its a n a l y s is, the Ag e n c y be lie ve s tha t in
the absence of any sound scientific evidence on the duration of particular latency periods for
arsenic-related cancers, discounted benefits estimates for arsenic are more appropriately
accounted for in a sensitivity analy s is. Sensitivity analy s es are g e nerally reserved for ex amining

the e f f

e c t s of a c c ounting f o r

hig h ly unc e r ta in f a c t or s, suc h a s the e s tima tion of la te nc y pe r i ods,

on he a lth r i sk r e duc tion be ne f its e s tima te s.

Defi ni ng a l a t e ncy peri od i s hi g h l y uncert a i n because t h e l e ng t h of t h e l a t e ncy peri od i s oft e n poorly understood by health scientists. I n some cases, information on the prog ression of a cancer

is based on animal studies, and ex trapolation to humans is complex and uncertain. Even when

hum an st udi es are avai l a bl e, t h e dose consi d ered m a y di ffer si g n i f i cant l y from t h e dose g e neral l y associated with drinking water contaminants (e.g ., involve a hig h level of ex posure over a short
time period, rather than a long -term, low level of ex posure).

Chapter 5, Benefits Analys is 5-27 Ar s e nic in D r inking Water Rule EA

### The mag n itude of the dose may in turn affect the resulting latency period. I n formation on latency

may be unavailable in many cases, or, if available, may be hig h ly uncertain and vary sig n ificantly

across individuals.

5.5.2 A naly t i cal A pproach

F o r the la te nc y se nsitivity a n a l y s is, the he a lth be ne f its ha ve be e n br oke n into se pa r a te tr e a tme nts of morbidity and mortality

. The mortality component of the total benefits is ex amined in this
analy s is because a cancer latency period (i.e., the time period between initial ex posure to

e nvir onme n ta l c a r c i nog e n s a nd the a c t ua l f a ta lity ) impa c t s a r se nic

- r e la te d f a ta litie s only

. F o r purposes of this analy s is, the Ag ency ex amined the impacts of various latency period
assumptions, adjustments for income g r owth, and incorporation of other adjustments, such as

volunta r ine ss a nd c ontr o lla bility , on bla dde r a nd lung c a n c e r f

a ta litie s a ssoc i a t e d with a r se nic in
drinking water.

B ecause the latency period for arsenic-related bladder and lung cancers is unknown, EP A has
assumed a rang e of latency periods from 5 to 20 y ears. W h ile both lung and bladder cancer have

r e la tive l y long a v e r a g e la te nc ie s, the lowe r e nd of the la te nc y pe r i od is substa ntia lly le ss. As c a n
be se e n by inspe c tion of the Sur v e illa nc e

, Epide miolog y , a nd End Re sults ( S EER) da ta of the

Na tiona l Ca nc e r I n stitute , sig n if ic a n t inc i de nc e of both c a n c e r s oc c u r s in individua ls in the 15- to 19-y ear-old ag e g r oups. This strong ly indicates a short latency period for whatever the cause of
the cancer may have been.

Moreover, the mode of action for arsenic is suspected to be one that operates at a late stag e of the

c a n c e r pr oc e ss a nd tha t ma y a dva nc e the e x pr e ssion of c a n c e r s initia te d by othe r c a u se s ( s ome time s r e f e r r e d to a s “ p r o moting out” the c a n c e r ous e f f

e c t )

. The r a p e u tic tr e a tme nt with the
drug cy clophosphamide, which causes cell tox i city , has been seen to induce bladder cancer in as

little a s 7 to 15 y e a r s in a f f

e c t e d pa tie nts. This wa s of c our se a hig h dose tr e a tme nt, but the

e x a m ple se r v e s to illustr a te the a b ility of a n a g e n t to a dva nc e the de ve lopme n t of c a n c e r

.

F o r these reasons, we believe latency periods of 5, 10, and 20 y ears serve as reasonable

approx imations, in the absence of definitive data on arsenic-induced cancers, of the latency

pe r i ods f o r

the se nsitivity a n a l y s is.

Ex hibit 5-12 shows the sensitivity of the primary analy s is VSL estimate ($6.1 million, 1999
dollars) to chang e s in latency period assumptions and also with the incorporation of income

g r owth and other adjustment factors. As is shown in Ex hibit 5-12, the adjusted VSL is g r eater than the primary VSL ($6.77 million versus $6.1 million) at an income elasticity of 1.0, with
adjustments for income g r owth only

. The lowest adjusted VSL value ($3.44 million) is y i elded
over a 20-y ear latency period that includes discounting and income g r owth only (income
elasticity = 0.22). Assuming a seven percent discount rate, the hig h est adjusted VSL is also $6.77 million (adjusted for income g r owth only [ i ncome elasticity = 1.0] ). The lowest adjusted

VSL is $1.61 million (discounted over 20 y ears).

The first row of both the three and seven percent discount rate panels in Ex hibit 5-12 shows the

VS L used in the primary analy s is. B ecause this value has not been adjusted for discounting over
an assumed and unknown latency period, this value does not deviate from the orig inal $6.1

Chapter 5, Benefits Analys is 5-28 Ar s e nic in D r inking Water Rule EA

### million used in the primary benefits analy s is. The second and third rows of both the three and
seven percent panels show the adjustments to the primary VSL to account for chang e s in W T P for fatal risk reductions associated with real income g r owth from 1990 to 1999. As real income

g r ows, the W T P to avoid fatal risks is also ex pected to increase at a rate corresponding to the
income elasticity of demand, as discussed below. This income g r owth, from the y ears 1990 to

1999, accounts for the differences in incomes of the VS L study population versus the population
affected by the Arsenic Rule. This does not include any income adjustments over a latency
period because of methodolog ical issues that have not y e t been resolved. However, pending the

r e solution of the s e issue s , EPA ma y inc l ude a n a d justme nt f o r

inc o me g r owth ove r a

la te nc y period in future analy s es, as recommended by the SAB

.

The f our th a nd f i f

t h r o ws of both the thr e e a nd se ve n pe r c e n t pa ne ls illustr a te s the impa c t s of
adjusting the primary VSL for discounting and income g r owth over a rang e of assumed latency
periods. As is shown in Ex hibit 5-12, this value decreases from $5.84 million assuming a fivey ear latency period to $3.75 million assuming a 20 y ear latency period (at a three percent
discount rate and income elasticity of 1.0). At a seven percent discount rate, this value decreases

from $4.83 million to $1.75 million.

Chapter 5, Benefits Analys is 5-29 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 12

Sensi t i v i t y of t h e Pri m ary VSL Est i mat e t o Changes i n Lat e ncy Peri od A ssumpt i ons,

In c o me Gro w th , a n d Oth e r A d j u s t me n t s ($ millions, 1999)

A d jus t m e nt Fa c t or La te nc y Pe r i od (Ye a r s )

5 1 0 2 0

3 % D i s c ount R a te

Prim ary Analy s is (No VSL Adjust m ent ) 6

. 1 6. 1 6

. 1

Ad j u ste d f o r In co m e Gro w th 1 e l a s ti ci ty = 0

. 2 2

e l a s ti ci ty = 1

. 0 6

. 2 2 6

. 2 2 6

. 2 2

6 .7 7 6 .7 7 6 .7 7

Ad j u ste d f o r In co m e Gro w th 1 and Discount ing elast i cit y = 0. 22

e l a s ti ci ty = 1

. 0 5. 37 4. 63 3. 44

5 .8 4 5 .0 4 3 .7 5

Ad j u ste d f o r In co m e Gro w th 1

, Discount ing, and 7% I n crease for

Volunt ariness and Cont rollabilit y elast i cit y = 0. 22

e l a s ti ci ty = 1

. 0 5. 74 4. 95 3. 69

6 .2 5 5 .3 9 4 .0 1

Break -Ev en for O t her Charact e rist ics (as a percent age of t he prim ary VSL est i m a t e )

e l a s ti ci ty = 0

. 2 2

e l a s ti ci ty = 1

. 0 6 % 1 9 % 4 0 %

- 2 % 1 2 % 3 4 %

7 % D i s c ount R a te

Prim ary Analy s is (No VSL Adjust m ent ) 6

. 1 6. 1 6

. 1

Ad j u ste d f o r In co m e Gro w th 1 e l a s ti ci ty = 0

. 2 2

e l a s ti ci ty = 1

. 0 6

. 2 2 6

. 2 2 6

. 2 2

6 .7 7 6 .7 7 6 .7 7

Ad j u ste d f o r In co m e Gro w th 1 and Discount ing elast i cit y = 0. 22

e l a s ti ci ty = 1

. 0 4. 44 3. 16 1. 61

4 .8 3 3 .4 4 1 .7 5

Ad j u ste d f o r In co m e Gro w th 1

, Discount ing, and 7% I n crease for

Volunt ariness and Cont rollabilit y elast i cit y = 0. 22

e l a s ti ci ty = 1

. 0 4. 75 3. 38 1. 72

5 .1 7 3 .6 8 1 .8 7

Break -Ev en for O t her Charact e rist ics (as a percent age of t he prim ary VSL est i m a t e )

e l a s ti ci ty = 0

. 2 2

e l a s ti ci ty = 1

. 0 2 2 % 4 5 % 7 2 %

1 5 % 4 0 % 6 9 %

1. T h is adjustment reflects the change in W T P based on real income grow th from 1990 to 1999.

Chapter 5, Benefits Analys is 5-30 Ar s e nic in D r inking Water Rule EA

### The six t h a nd se ve nth r o ws of the thr e e a nd se ve n pe r c e n t pa ne ls illustr a te the e f f

e c t s of

inc o rpor a ting a se ve n pe r c e n t inc r e a s e f o r

volunta r ine ss a nd c ontr o lla bility a s r e c o mme nde d f o r

a sensitivity analy s is in the SAB report on valuing fatal cancer risk reductions (SAB , 2000). One

me mbe r of the SAB c o mmitte e note d in the SAB r e por t tha t this a d justme nt ma y be a s hig h a s
two time s the pr ima r y VSL

, but this va lue is hig h ly spe c u la tive

. The se ve n pe r c e n t a d justme nt accounts for empirical evidence in the literature that indicates individuals may place a hig h er willing n e ss to pa y ( W TP) on r i sks whe r e e x posur e is ne ithe r volunta r y nor c ontr o lla ble by the

individual.

I n a d justing f o r

both inc o me g r owth a nd volunta r ine ss a nd c ontr o lla bility , EPA use d a r a ng e of

income elasticities from the economics literature. I n come elasticity is the percent chang e in
demand for a g ood (in this case, W T P for fatal risk reductions) for every one percent chang e in

income. F o r ex ample, an income elasticity of 1.0 implies that a 10 percent hig h er income level
results in a 10 percent hig h er W T P for fatal risk reductions. I n a recent study (EPA, 2000c), EPA

r e vie w e d the lite r a tur e r e la te d to the inc o me e l a s tic ity of de ma nd f o r

the pr e v e n tion of f

a ta l he a lth
impacts. B a sed on data from cross-sectional studies of wag e premiums, a rang e of elasticity
estimates for serious health impacts was developed, rang ing from a lower-end estimate of 0.22 to
an upper-end estimate of 1.0.

The r e a r e se ve r a l othe r c h a r a c t e r istic s tha t dif f

e r

be twe e n the VSL e s tima te s use d in the pr ima r y

a n a l y s is a nd a n ide a l e s tima te spe c i f i c to the c a s e of c a n c e r r i sks f r o m a r se nic

. The s e inc l ude a cancer premium, differences in risk aversion, altruism, ag e of the individual affected, and a
morbidity component of the VSL mortality estimate. Very little empirical information is available
on the impact that these characteristics have on VSL estimates; thus, they are not accounted for

dir e c tly in this se nsitivity a n a l y s is. A mor e c o mple te disc ussion of the othe r c h a r a c t e r istic s
ide n tif ie d by e c onomists a s ha ving a pote n tia l impa c t on WTP to r e duc e mor t a lity r i sks c a n be
found in Chapter Seven of the Ag ency ’s Guidelines for Preparing Economic Analyses (EP A

, 2000c), which is available in the docket for this final rulemaking

.

However, it is possible to use a “break even” analy s is to address the question: what would the
impact on VSL of these additional characteristics need to be to produce the $6.1 million VSL used

in the pr ima r y be ne f its a n a l y s is ( d e s c r ibe d e a r lie r in this c h a p te r )

. The la st two r o ws of the thr e e and seven percent panels of Ex hibit 5-12 attempt to answer this question in percentag e terms. F o r

ex ample, at a three percent discount rate over a ten y ear latency period and income elasticity of
1.0, a factor of 12 percent (as shown in the bottom row of the three percent panel of Ex hibit 5-12)

i ndi cat es t h at i f account i n g for t h ese charact eri s t i c s woul d i n crease VS L by m o re t h an 12 percent
then the primary analy s is will tend to understate the value of risk reductions. I f accounting for

t h ese charact eri s t i c s woul d not i n crease VS L by at l east 12 percent t h en t h e pri m a ry anal y s i s m a y overstate benefits (a neg a tive percentag e indicates that the primary analy s is understates benefits

unle ss the c o mbine d impa c t of the s e a dditiona l c h a r a c t e r istic s a c t ua lly r e duc e s VSL e s tima te s)

.

Some r e se a r c h e r s be lie ve tha t the va lue of some of the s e c h a r a c t e r istic s will substa ntia lly a dd to
the unadjusted VSL (one study sug g e sts that a cancer premium alone may be worth an additional
100 percent of primary VSL value [ R evesz

, 1999] ). Some researchers also believe that some of

t h ese charact eri s t i c s have a neg a t i v e effect on VS L

, sug g e st i n g t h at som e of t h ese fact ors offset

one another. Until we know more about these various factors we cannot ex plicitly make

a d justme nts to e x isting VSL e s tima te s.

Chapter 5, Benefits Analys is 5-31 Ar s e nic in D r inking Water Rule EA

### The S A B not ed i n t h ei r report t h at t h ese charact eri s t i c s requi re m o re em pi ri cal research pri o r t o incorporation into the Ag ency ’s primary benefits analy s is, but could be ex plored as part of a

se nsitivity a n a l y s is.

5.5.3 R esult s

Ex hibit 5- 13 illustr a te s the impa c t s of c h a n g e s in VSL a d justme nt f a c t or a ssumptions on the

e s tima te d be ne f its f o r

the r a ng e of f

a ta l bla dde r a nd lung c a n c e r c a s e s a voide d in the f i na l Ar se nic
Rule, assuming a three percent discount rate. The results of this analy s is at a seven percent
discount rate are g i ven in Ex hibit 5-14. These results were calculated by apply i ng the adjusted

VSL s from Ex hibit 5-12 to the lower- and upper-bound estimates of fatal bladder and lung cancer

c a s e s a voide d a s shown in Ex hibit 5- 9 ( c )

. F o r pur pose s of this se nsitivity a n a l y s is, EPA
presented combined bladder and lung cancer cases avoided in Ex hibits 5-13 and 5-14. Health risk

reduction benefits attributable to reduced arsenic levels in both CW Ss and NTNCW S s are
present e d i n t h ese ex hi bi t s as wel l

.

I t is impor ta nt to note tha t the mone tize d be ne f its e s tima te s shown in this se c tion r e f l e c t quantifiable benefits only

. As shown in Section 5.2, there are a sig n ificant number of nonquantifiable benefits associated with reg u lating arsenic in drinking water. As a result, the

monetiz ed benefits presented in the following ex hibit represent a lower-bound estimate. W e re EPA able to quantify some of the currently non-quantifiable health effects and other benefits
associated with arsenic reg u lation, monetiz ed benefits estimates could be sig n ificantly hig h er than

what are shown i n t h e ex hi bi t

.

Chapter 5, Benefits Analys is 5-32 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 13. Sensi t i v i t y of Combi n ed A nnual Bl adder and Lung Cancer M o rt al i t y Benef i t s

Est i mat es t o Changes i n VSL A d just ment Fact or A ssumpt i ons ($ millions, 1999, 3% discount rate) 1

A r senic Lev e l ( F g/L) 3 5 10 20

5 Year Latency Period A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 176-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 175-398 156-288 114-160 55-61

190-433 170-314 124-174 60-66

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 187-425 167-308 122-171 59-65

204-463 182-336 133-186 64-71

10 Year Latency Per i od A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 176-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 151-343 135-249 99-138 47-52

164-373 147-271 107-150 51-57

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 161-367 144-266 105-148 50-56

176-399 157-289 115-161 55-61

20 Year Latency Per i od A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 176-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 112-255 100-185 73-103 35-39

122-278 109-201 80-112 38-42

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 120-273 107-198 79-110 38-42

131-297 117-215 85-119 41-45

1. T he low e r- and upper-bound benefits estimates correspond to the low e r- and upper-bound risk estimates and

cancer cases av oided as show n in section III.D .2 of this preamble.

2. T h is adjustment reflects the change in W T P based on real income grow th from 1990 to 1999. E = income elasticity

.

Chapter 5, Benefits Analys is 5-33 Ar s e nic in D r inking Water Rule EA

### Exhi bi t 5- 14

Sensi t i v i t y of Combi n ed A nnual Bl adder and Lung Cancer M o rt al i t y Benef i t s Est i mat es t o Changes i n VSL A d just ment Fact or A ssumpt i ons ($ millions, 1999, 7% discount rate) 1

A r senic Lev e l ( F g/L) 3 5 10 20

5 Year Latency Period A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 178-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 145-329 129-238 95-132 45-50

157-358 141-259 103-144 50-55

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 155-352 138-255 102-142 49-54

168-383 150-278 110-154 53-58

10 Year Latency Per i od A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 178-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 103-234 92-170 67-94 32-36

112-255 100-185 73-103 35-39

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 110-251 98-182 72-101 35-38

120-273 107-198 78-110 38-42

20 Year Latency Per i od A ssumption

Primary Analy s is (N o VSL Adjustment) 199-452 178-328 130-182 62-69

Adjusted for Income G r ow th 2 E = 0.22

E = 1.0 203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77

Adjusted for Income G r ow th 2 and D i scounting E = 0.22

E = 1.0 53-119 47-86 34-48 16-18

57-130 51-94 37-52 18-20

Adjusted for Income G r ow th 2 , D i scounting, and 7%

Increase for Voluntariness and C ontrollability E = 0.22

E = 1.0 56-127 50-92 37-51 18-20

61-139 54-100 40-56 19-21

1. T he low e r- and upper-bound benefits estimates correspond to the low e r- and upper-bound risk estimates and

cancer cases av oided as show n in section III.D .2 of this preamble.

2. T h is adjustment reflects the change in W T P based on real income grow th from 1990 to 1999. E = income elasticity

.

Chapter 5, Benefits Analys is 5-34 Ar s e nic in D r inking Water Rule EA

### As shown in Ex hibits 5-13 and 5-14, the hig h est rang e of adjusted benefits estimates at the 10

μg /L MCL ($144 - $202 million at three percent and seven percent) are y i elded when benefits are
adjusted for income g r owth only with an income elasticity of 1.0. The lowest adjusted benefits
estimates at the 10 μg /L MCL ($73 - $103 million at three percent, $34 - $48 million at seven
percent) are y i elded under the assumption of a 20-y ear latency period that includes adjustments
for discounting and income g r owth (income elasticity = 0.22). These results indicate the hig h

de g r e e of se nsitivity of be ne f its e s tima te s to dif f

e r e nt a ssumptions of a

la te nc y pe r i od a nd inc o me elasticity and also the inclusion of adjustments for income g r owth and voluntariness and

c ontr o lla bility

.

5.6 O ther Benefits of Reductions in A r senic Exposure

I t is well established that the public often avoids the use of tap water that is suspected to be

contaminated. I n this contex t, contamination may sug g e st biolog ical, chemical, or other water
quality issues. W h en public perception of water quality declines, consumers purchase bottled
water if they have the means to do so.

I n addition or as an alternative, they may avoid the use of tap water, ing e sting and cooking with
other liquids, substituting pre-mix ed baby formula, and using other strateg i es to limit ing e stion.
Consumer avoidance of tap water sources usually results in costs to the consumers, either in the

c o st of obta i ning substitute f l uids or pote n tia l he a lth impa c t s of r e duc e d f l uid inta ke

. I n a ddition,

the r e a r e nume r ous c a s e s whe r e g ove r n me nt a g e n c i e s ha ve pr ovide d bottle d wa te r due to biolog ical or chemical contamination. The levels of contamination at which the g overnment

a c tivitie s oc c u r va r y de pe nding on a va r i e t y of f

a c t or s.

The relationship between arsenic in tap water and chang e s in consumer behavior or g overnment interventions is a complex one. F actors that impact the choice to avoid tap water depend on
public information that is provided on levels of contamination, potential health effects, individual
aversions to risk taking , and other considerations. A quantitative evaluation of these responses
and the potential benefits of avoiding associated costs to the consumer or g overnments is not

inc l ude d in this be ne f its a sse ssme n t. Howe ve r

, it is c l e a r tha t ma ny c onsume r s pur c h a s e bottle d
water (a multimillion dollar industry ) or invest in other methods of improving drinking water

qua lity , suc h a s point- o f

- u se ( P OU) de vic e s , spe c i f i c a lly to a void ing e stion of c onta mina n ts suc h

a s a r se nic

. Thus, it is r e a s ona ble to c onc lude tha t a r e duc tion in a r se nic c onta mina tion will ha ve the long -term effect of restoring some level of consumer confidence in the water supply

.

Chapter 5, Benefits Analys is 5-35 Ar s e nic in D r inking Water Rule EA

## Chapter 6: Cost A n aly s is

6.1 I ntroduction

This c h a p te r pr e s e n ts the na tiona l c o st e s tima te s f o r

the Ar se nic Rule

. The c o sts a ssoc i a t e d with
the rule include: (1) costs borne by water sy stems to comply with the new MCL standard and
modified monitoring requirements, and (2) costs to the States to implement and enforce the rule.
Section 6.2 describes the inputs and methodolog ies used to estimate costs, including the

f

o llowing :

• A description of the technolog ies that may be used by sy stems to achieve the

MCL (Section 6.2.1);

• T he unit costs of different technolog ies for comply ing with the MCL s (Section

6.2.2);

• S y s te m a nd Sta t e unit c o sts f o r

monitor i ng a nd a d ministr a tion f unc tions ( S e c tion
6.2.3); and

• T he methods used to predict sy stems’ compliance methods (Section 6.2.4) and the
methods used to calculate costs (Section 6.2.5).

Section 6.3 presents the results of the cost analy s is, including the following :

• A summary of national costs for the different reg u latory options (Section 6.3.1);

• C osts by sy stem siz e and ty pe for the MCL options (Section 6.3.2); and

• H ousehold costs (Section 6.3.3).

Section 6.4 discusses the uncertainty inherent in the distribution of estimated national

com p l i a nce cost s.

6.2 M ethodology

6.2.1 D escription of A v ailable Technologies

I n 1993, EPA developed a document entitled Treatment and Occurrence—Arsenic in Potable

W

a ter Supplies (EPA, 1993), which summariz e d the results of pilot-scale studies ex amining

low- le ve l a r se nic r e mova l, f r o m 50 mic r o g r a m s pe r lite r ( μ g / L ) down to 1 μg /L or le ss. EPA
convened a panel of outside ex perts in J a nuary 1994 to review this document and comment on
the ability of the technolog ies to achieve various MCL s . The Ag ency has since soug ht
stakeholder input on the use of various technolog ies for arsenic removal under different
conditions, and has incorporated that input into its estimates of technolog y performance and

cost s. The resul t s are docum ent e d i n t h e Cost and Technology Document for the Arsenic Rule
(EPA, 2000d). The technolog y cost functions and removal efficiencies presented in that
document are used as inputs for the cost analy s es presented in this EA.

Some technolog ies g e nerate wastes that require disposal or pre-treatment (e.g ., pre-ox idation or
corrosion control) in order to be effective. These associated requirements were identified for

Chapter 6, Cost Analysis 6-1 A rsenic in Drinking Water Rule EA

### different technolog ies and sy stem ty pes, and their costs were included in the costs of treatment

where relevant.

I n addition to these centraliz ed treatment options, small sy stems may elect to use point-of-use
(POU) devices to achieve compliance with the MCL s

. POU involves treatment at the tap. The
available POU technolog ies for arsenic removal are essentially smaller versions of reverse

osmosis and activated alumina. These technolog ies will have to be maintained by the water

sy stem, involving some additional recordkeeping and maintenance costs.

The result of the review of technolog ies that would effectively remove arsenic and bring a water

sy ste m into c o mplia nc e is summa r i ze d in Ex hibit 6- 1. The list inc l ude s 13 tr e a tme nt tr a i ns available to sy stems, consisting of various combinations of compliance technolog ies, waste
disposal technolog ies, or pre-treatment technolog ies as required.

Chapter 6, Cost Analysis 6-2 A rsenic in Drinking Water Rule EAExhibit6-1ArsenicRuleTreatmentTrains byCompliance Technologies ComponentwithAssociated RemovalEfficienciesTreatmentTechnologyWaste DisposalTechnologyCorrosionControlPreOxidationoRemovalEfficiencyPOTWNon-HazardousLandfillMechanicalDe-WateringNonMechanicalDe-Watering1ModifyLimeSoftening790%2ModifyCoagulation/Filtration795%3AnionExchange(<20 mg/LSO4)7795%4AnionExchange(20-50mg/LSO4)7795%5Coagulation AssistedMicrofiltration77790%6Coagulation AssistedMicrofiltration77790%7Oxidation Filtration (Greensand)7*750%8ActivatedAlumina (pH7 -pH8)7**795%9ActivatedAlumina (pH8 -pH8.3)7**795%10ActivatedAlumina(23,100 BV)withpHadjustment(pH 6)7**7795%11ActivatedAlumina(15,400 BV)withpHadjustment(pH 6)7**7795%12POUActivatedAlumina790%13POUReverseOsmosis790%opre-oxidation incorporatedintotreatmenttrainsbasedonaseparatedecisiontree*POTWforbackwashstream**non-hazardouslandfill(forspentmedia)

### 6.2.2 U nit C o st s and C o mpliance A ssumpt i ons

EPA estimated the costs of the various compliance technolog ies, including the centralized
treatment technolog ies associated waste disposal technolog ies, and POU treatment technolog ies,

ex cluding pre-treatment costs. Pre-treatment costs were separate treatment costs that apply to a

part i c ul ar set of sy st em s (som e sy st em s woul d al ready have pre-t r eat m e nt i n pl ace). C o st s of
each treatment train are estimated as functions of sy stem siz e , desig n flow (used to calculate
capital costs) and averag e flow (used to calculate operating and maintenance costs). Ex hibits 6-2

(a) and 6-2 (b) presents a summary of unit compliance technolog y costs by cost component for

the treatment trains listed in Ex hibit 6-1, annualiz ed over 20 y e ars at a seven percent discount
rate. Costs are in May 1999 dollars and are based on averag e and desig n flows for median
populations of each sy stem siz e categ ory

.

The unit costs are provided to demonstrate the rang e of costs across the treatment technolog ies

for an MCL of 10μg / L

, assuming either an influent arsenic concentration of 11μg / L (low rang e

e s tima te s shown in Ex hibit 6- 2( a ) ) or a n inf l ue nt a r se nic c onc e n tr a tion of 50μg / L ( h ig h r a ng e

e s tima te s shown in Ex hibit 6- 2( b) )

. EPA c a l c u la te d the s e a v e r a g e unit c o sts f o r

a

sing le
contaminated entry point, assuming a publicly -owned g r ound water sy stem with the averag e number of entry points per sy stem in that siz e categ ory

. Note that the capital and operating ad
maintenance (O& M ) cost components are listed separately for the treatment and waste disposal
components of the treatment train. These costs are annualiz ed over 20 y ears at a seven percent discount rate. Detailed descriptions of the assumptions and methodolog ies used to develop the
underly i ng cost curves are available in the Cost and Technology Document for the Arsenic Rule
(EPA, 2000d).

Chapter 6, Cost Analysis 6-4 A rsenic and Drinking Water Rule EAExhibit6-2aSystem Compliance TechnologyCosts Assuming InfluentConcentration of11 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatment TrainNo.123456<100TreatmentCapitalCosts$8,999$7,483$21,957$22,724$127,885$127,885TreatmentO&MCosts$484$260$5,104$8,604$22,361$20,585Waste DisposalCapitalCosts$-$-$3,955$3,955$29,900$20,686WasteDisposalO&MCosts$-$-$381$387$6,946$2,131AnnualCosts(7%)$1,333$966$7,930$11,510$44,200$36,740101-500TreatmentCapitalCosts$13,688$8,966$21,957$37,150$265,526$265,526TreatmentO&MCosts$1,416$482$5,104$9,470$23,619$22,400Waste DisposalCapitalCosts$-$-$3,955$3,955$43,354$118,165WasteDisposalO&MCosts$-$-$412$455$12,863$2,177AnnualCosts(7%)$2,708$1,328$7,962$13,804$65,638$60,795501-1,000TreatmentCapitalCosts$14,756$9,316$21,957$40,669$295,452$295,452TreatmentO&MCosts$1,766$565$5,104$9,791$24,090$23,081Waste DisposalCapitalCosts$-$-$3,955$3,955$46,424$141,947WasteDisposalO&MCosts$-$-$424$480$14,929$2,195AnnualCosts(7%)$3,159$1,444$7,974$14,483$71,290$66,5631,001-3,300TreatmentCapitalCosts$24,087$12,655$38,991$120,712$526,687$526,687TreatmentO&MCosts$4,760$1,266$5,104$12,431$28,088$28,088Waste DisposalCapitalCosts$-$-$3,955$3,955$73,454$330,519WasteDisposalO&MCosts$-$-$525$696$29,102$2,364AnnualCosts(7%)$7,034$2,460$9,682$24,894$113,839$111,366NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.Exhibit6-2a (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of11 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.1234563,301-10,000TreatmentCapitalCosts$64,447$40,103$38,991$211,802$1,069,210$1,069,210TreatmentO&MCosts$14,961$4,833$5,104$20,403$38,522$38,522WasteDisposalCapitalCosts$-$-$3,955$3,955$121,208$762,407WasteDisposalO&MCosts$-$-$869$1,434$32,307$9,170AnnualCosts(7%)$21,045$8,618$10,027$42,203$183,196$220,58310,001-50,000TreatmentCapitalCosts$247,207$168,801$38,991$362,184$1,793,771$1,793,771TreatmentO&MCosts$35,250$17,001$5,104$31,688$55,413$55,413WasteDisposalCapitalCosts$-$-$3,955$3,955$209,000$1,610,846WasteDisposalO&MCosts$-$-$1,593$2,984$45,793$50,349AnnualCosts(7%)$58,584$32,934$10,750$69,233$290,253$427,13450,001-100,000TreatmentCapitalCosts$455,707$315,625$38,991$529,645$2,368,818$2,368,818TreatmentO&MCosts$61,149$32,533$5,104$54,032$59,325$59,325WasteDisposalCapitalCosts$-$-$5,085$5,085$309,158$2,381,322WasteDisposalO&MCosts$-$-$2,516$4,962$52,569$66,722AnnualCosts(7%)$104,165$62,326$11,780$109,470$364,675$574,426100,001-1,000,000TreatmentCapitalCosts$1,462,373$918,353$38,991$1,873,015$6,887,505$6,887,505TreatmentO&MCosts$309,897$177,044$5,104$168,459$96,658$96,658WasteDisposalCapitalCosts$-$-$5,085$5,085$954,312$9,517,736WasteDisposalO&MCosts$-$-$12,132$25,570$178,509$237,418AnnualCosts(7%)$447,935$263,730$21,396$371,308$1,015,379$1,882,614NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.Exhibit6-2a (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of11 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.78910111213<100TreatmentCapitalCosts$15,023$13,629$13,629$45,787$45,787$4,671$13,619TreatmentO&MCosts$7,711$4,414$6,944$6,050$6,643$6,725$4,433Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$446$12$22$5$8$-$-AnnualCosts(7%)$9,949$5,712$8,253$10,377$10,972$7,390$6,372101-500TreatmentCapitalCosts$63,059$29,131$29,131$62,507$62,507$27,027$78,866TreatmentO&MCosts$8,540$6,065$10,087$7,494$8,437$39,804$26,552Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$571$78$150$34$51$-$-AnnualCosts(7%)$15,437$8,892$12,986$13,428$14,388$43,652$37,781501-1,000TreatmentCapitalCosts$73,464$32,912$32,912$66,586$66,586$34,915$101,897TreatmentO&MCosts$8,904$6,684$11,265$8,036$9,110$51,591$34,475Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$618$103$197$44$67$-$-AnnualCosts(7%)$16,830$9,893$14,569$14,365$15,462$56,562$48,9831,001-3,300TreatmentCapitalCosts$170,709$60,846$60,846$97,616$97,616$97,980$286,071TreatmentO&MCosts$12,006$11,930$21,255$12,627$14,814$146,709$98,728Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$1,016$313$602$135$203$-$-AnnualCosts(7%)$29,509$17,986$27,600$21,977$24,231$160,659$139,458NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.InTreatmentTrains 8 -11,waste disposal O&Mcosts include onlynon-hazardous landfill tipping fees,and therefore,are quitelow.Exhibit6-2a (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of11 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.789101112133,301-10,000TreatmentCapitalCosts$421,562$159,129$159,129$205,374$205,374$296,207$865,248TreatmentO&MCosts$22,659$29,916$55,506$28,369$34,369$449,875$305,030Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$2,381$1,033$1,988$447$671$-$-AnnualCosts(7%)$65,205$45,970$72,514$48,202$54,426$492,048$428,22210,001-50,000TreatmentCapitalCosts$787,837$324,276$324,276$386,442$386,442$682,321$1,993,842TreatmentO&MCosts$45,012$67,654$127,369$61,397$75,399$1,047,475$714,269Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$5,951$2,545$4,895$1,102$1,653$-$-AnnualCosts(7%)$125,809$100,809$162,873$98,976$113,530$1,144,622$998,14750,001-100,000TreatmentCapitalCosts$1,168,062$512,683$512,683$593,012$593,012$1,150,447$3,362,537TreatmentO&MCosts$73,549$122,590$231,264$109,500$134,983$1,778,028$1,216,748Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$9,606$4,476$8,608$1,938$2,906$-$-AnnualCosts(7%)$193,892$175,459$288,265$167,413$193,866$1,941,826$1,695,498100,001-1,000,000TreatmentCapitalCosts$4,098,917$2,257,773$2,257,773$2,506,335$2,506,335$5,567,338$16,283,352TreatmentO&MCosts$370,791$629,270$1,199,321$548,870$682,540$8,780,565$6,073,580Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$47,683$24,581$47,274$10,642$15,962$-$-AnnualCosts(7%)$805,863$866,968$1,459,713$796,092$935,082$9,573,229$8,391,963NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.InTreatmentTrains 8 -11,waste disposal O&Mcosts include onlynon-hazardous landfill tipping fees,and therefore,are quitelow.Exhibit6-2bSystem Compliance TechnologyCosts Assuming InfluentConcentration of50 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatment TrainNo.123456<100TreatmentCapitalCosts$8,999$7,483$26,970$29,332$193,923$193,923TreatmentO&MCosts$484$260$5,365$8,924$21,251$21,251Waste DisposalCapitalCosts$-$-$3,955$3,955$36,236$65,339WasteDisposalO&MCosts$-$-$392$412$9,187$2,148AnnualCosts(7%)$1,333$966$8,676$12,478$52,164$47,872101-500TreatmentCapitalCosts$13,688$8,966$43,632$117,795$508,282$508,282TreatmentO&MCosts$1,416$482$5,365$11,527$26,696$26,696Waste DisposalCapitalCosts$-$-$3,955$3,955$71,219$316,779WasteDisposalO&MCosts$-$-$490$621$24,844$2,301AnnualCosts(7%)$2,708$1,328$10,346$23,640$106,241$106,877501-1,000TreatmentCapitalCosts$14,756$9,316$43,632$126,653$564,187$564,187TreatmentO&MCosts$1,766$565$5,365$12,469$28,148$28,148Waste DisposalCapitalCosts$-$-$3,955$3,955$77,743$358,515WasteDisposalO&MCosts$-$-$526$699$29,269$2,367AnnualCosts(7%)$3,159$1,444$10,383$25,497$118,010$117,6111,001-3,300TreatmentCapitalCosts$24,087$12,655$43,632$218,240$1,103,278$1,103,278TreatmentO&MCosts$4,760$1,266$5,365$19,699$37,737$37,737Waste DisposalCapitalCosts$-$-$3,955$3,955$124,926$793,148WasteDisposalO&MCosts$-$-$836$1,362$40,238$8,074AnnualCosts(7%)$7,034$2,460$10,692$42,035$193,909$224,820NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.Exhibit6-2b (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of50 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.1234563,301-10,000TreatmentCapitalCosts$64,447$40,103$43,632$490,994$2,255,079$2,255,079TreatmentO&MCosts$14,961$4,833$5,365$45,678$56,923$56,923WasteDisposalCapitalCosts$-$-$5,085$5,085$285,807$2,123,020WasteDisposalO&MCosts$-$-$1,897$3,637$48,028$42,687AnnualCosts(7%)$21,045$8,618$11,860$96,141$344,793$512,87210,001-50,000TreatmentCapitalCosts$247,207$168,801$43,632$923,917$3,571,834$3,571,834TreatmentO&MCosts$35,250$17,001$5,365$75,188$65,568$65,568WasteDisposalCapitalCosts$-$-$5,085$5,085$513,238$4,281,260WasteDisposalO&MCosts$-$-$4,124$8,409$72,683$95,250AnnualCosts(7%)$58,584$32,934$14,087$171,288$523,853$902,09550,001-100,000TreatmentCapitalCosts$455,707$315,625$43,632$1,378,931$5,074,043$5,074,043TreatmentO&MCosts$61,149$32,533$5,365$110,599$76,604$76,604WasteDisposalCapitalCosts$-$-$5,085$5,085$717,287$6,653,715WasteDisposalO&MCosts$-$-$6,967$14,501$110,698$145,696AnnualCosts(7%)$104,165$62,326$16,930$255,741$733,963$1,329,318100,001-1,000,000TreatmentCapitalCosts$1,462,373$918,353$43,632$3,623,972$18,245,297$18,245,297TreatmentO&MCosts$309,897$177,044$5,365$328,792$203,223$203,223WasteDisposalCapitalCosts$-$-$5,571$5,571$2,275,373$28,628,219WasteDisposalO&MCosts$-$-$36,579$77,955$477,280$672,537AnnualCosts(7%)$447,935$263,730$46,588$749,350$2,617,509$5,300,288NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.Exhibit6-2b (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of50 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.78910111213<100TreatmentCapitalCosts$24,983$20,733$20,733$53,449$53,449$4,671$13,619TreatmentO&MCosts$7,747$5,021$8,098$6,580$7,302$6,725$4,433Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$464$36$69$16$23$-$-AnnualCosts(7%)$10,943$7,014$10,125$11,641$12,371$7,390$6,372101-500TreatmentCapitalCosts$104,869$57,733$57,733$94,204$94,204$27,027$78,866TreatmentO&MCosts$9,495$10,104$17,779$11,029$12,829$39,804$26,552Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$694$240$461$104$156$-$-AnnualCosts(7%)$20,462$15,794$23,690$20,025$21,877$43,652$37,781501-1,000TreatmentCapitalCosts$104,869$57,733$57,733$94,204$94,204$27,027$78,866TreatmentO&MCosts$9,495$10,104$17,779$11,029$12,829$39,804$26,552Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$694$240$461$104$156$-$-AnnualCosts(7%)$20,462$15,794$23,690$20,025$21,877$43,652$37,7811,001-3,300TreatmentCapitalCosts$283,894$166,171$166,171$213,095$213,095$97,980$286,071TreatmentO&MCosts$15,866$28,169$52,180$26,840$32,470$146,709$98,728Waste DisposalCapitalCosts$3,955$-$-$-$-$-$-Waste DisposalO&MCosts$1,511$963$1,853$417$626$-$-AnnualCosts(7%)$44,547$44,818$69,718$47,372$53,211$160,659$139,458NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.InTreatmentTrains 8 -11,waste disposal O&Mcosts include onlynon-hazardous landfill tipping fees,and therefore,are quitelow.Exhibit6-2b (continued)System Compliance TechnologyCosts Assuming InfluentConcentration of50 μg/Land MCL of10 μg/L(Dollars)SizeCategoryTreatmentTrainNo.789101112133,301-10,000TreatmentCapitalCosts$701,070$468,896$468,896$545,004$545,004$296,207$865,248TreatmentO&MCosts$35,414$90,018$169,031$81,254$99,783$449,875$305,030Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$4,721$3,183$6,122$1,378$2,067$-$-AnnualCosts(7%)$106,791$137,461$219,413$134,077$153,294$492,048$428,22210,001-50,000TreatmentCapitalCosts$1,310,195$977,574$977,574$1,102,719$1,102,719$682,321$1,993,842TreatmentO&MCosts$76,430$207,386$393,274$183,031$226,620$1,047,475$714,269Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$9,975$7,840$15,079$3,394$5,091$-$-AnnualCosts(7%)$210,559$307,502$500,628$290,514$335,800$1,144,622$998,14750,001-100,000TreatmentCapitalCosts$1,942,521$1,557,893$1,557,893$1,738,984$1,738,984$1,150,447$3,362,537TreatmentO&MCosts$128,791$357,213$679,531$312,954$388,534$1,778,028$1,216,748Waste DisposalCapitalCosts$5,085$-$-$-$-$-$-Waste DisposalO&MCosts$16,683$13,785$26,512$5,968$8,952$-$-AnnualCosts(7%)$329,314$518,052$853,098$483,070$561,634$1,941,826$1,695,498100,001-1,000,000TreatmentCapitalCosts$6,816,616$6,933,014$6,933,014$7,632,284$7,632,284$5,567,338$16,283,352TreatmentO&MCosts$674,190$1,917,857$3,661,282$1,666,275$2,075,085$8,780,565$6,073,580Waste DisposalCapitalCosts$5,598$-$-$-$-$-$-Waste DisposalO&MCosts$86,549$75,712$145,611$32,778$49,166$-$-AnnualCosts(7%)$1,404,708$2,647,996$4,461,320$2,419,486$2,844,684$9,573,229$8,391,963NOTE:Average costs were calculated assuming a publicly-owned groundwater systemwith a single contaminated entrypoint,basedon medianpopulation and the average number of entrypoints per systemin the service sizecategory,for the treatmenttrain technologiesdescribed inExhibit6-1.InTreatmentTrains 8 -11,waste disposal O&Mcosts include onlynon-hazardous landfill tipping fees,and therefore,are quitelow.

### 6.2.3 M onitoring and A d ministrativ e Costs

Monitoring Costs

Monitoring under the current Arsenic Rule occurs annually for surface water sy stems, and
triennially for g r ound water sy stems. Currently , when trig g e red by a violation the sy stem must perform three additional tests within the month. Under the revised rule to be promulg a ted in

J a nuary 2001, sy stems will still perform monitoring annually (for surface water sy stems) or every
three y ears (for g r ound water sy stems); however, when trig g e red by a violation, the sy stem will
perform quart erl y m oni t o ri ng rat h er t h an t h ree m o re sam p l e s i n one m ont h. Al l surface wat e r

sy stems must collect samples no later than December 31, 2006, and all g r ound water sy stems must collect samples by December 31, 2007, to demonstrate compliance with the revised MCL

.

I f

qua r t e r ly monitor i ng is r e quir e d it will c ontinue until the Sta t e de te r mine s tha t the sy ste m is

“ r e lia bly a nd c onsiste ntly ” be low the MCL or until the PWS insta lls tr e a tme nt. Sta t e s a r e a b le to make this determination after g r ound water sy stems have taken two quarterly samples and
surface water sy stems have taken four quarterly samples. Additionally , States may g r ant a niney ear monitoring waiver to qualify i ng sy stems, an option not previously available. To be elig ible

for a wai v er, a sy st em m u st m eet t h e fol l o wi ng cri t e ri a:

1. De monstr a t e a d e qua te sour c e wa te r pr ote c tion by c o mple ting a vulne r a bility

assessment; and

2. De monstr a t e tha t thr e e pr e v ious sa mple s we r e be low the MCL

.

The monitor i ng r e quir e me nts will impose ne w c o sts f o r

some sy ste m s a s f o llows:

• N TNCs will inc u r the f u ll c o sts of the monitor i ng r e quir e me nts f o r

the f i r s t time

, unl ess t h ey are l o cat ed i n S t at es t h at al ready requi re NTNC s t o m oni t o r for

arsenic. F o r NTNCs that are currently required to monitor for arsenic, the

inc r e m e n ta l monitor i ng c o sts will de pe nd on how the r e vise d na tiona l

r e quir e me nts c o mpa r e with the c u rr e nt Sta t e r e quir e me nts. ( I t is a ssume d tha t States currently require NTNCs to monitor using the g r ound water requirements.

I t is also assumed that 96 percent of NTNCs use g r ound water sources, and 4

percent use surface wat e r.)

• C W S s m a y i n cur addi t i onal cost s i f t h ey fi nd ex ceedances m o re frequent l y at t h e
revised MCL

.

The c o st of monitor i ng inc l ude s pr e p a r ing a nd a n a l y z ing the sa mple

. Colle c ting the sa mple

,

a r

r a ng ing f o r

de live r y to the la bor a t or y

, a nd r e vie w ing the r e sults of the a n a l y s is is a ssume d to
require one hour of the sy stem operator’s time (at an estimated cost of $28 per hour). EPA has
assumed that all sy stems are equipped to collect samples. Therefore, no additional costs are

a ssume d f o r

insta lla tion of ta ps, r e

- p iping of we lls or othe r inve stme nts to pe r mit sa mpling

. EPA
has assumed that sy stems will utiliz e one of two laboratory methods: (1) stabiliz ed temperature
pl at form g r aphi t e furnace at om i c absorpt i on (S TP -GFAA) or (2) g r aphi t e furnace at om i c absorption (GF AA). B o th techniques cost $40 per sample.

Chapter 6, Cost Analysis 6-13 Arsenic in Drinking Water Rule EA

### Total net monitoring costs were estimated over a 20-y ear period at discount rates of three and

seven percent. The net costs are equal to the difference between the cost of the revised
monitoring requirements and the cost of the current monitoring requirements. Cost and hour
burden to the sy stem and the State are listed below in Ex hibit 6-3. The cost of routine
monitoring , trig g e red monitoring , waiver application and public notification are all included in
the total sy stem costs. Miscellaneous costs related to sending samples to be analy z ed and
sending public notification to customers are also included in the sy stem cost.

Exhi bi t 6- 3

Uni t Resources Requi red f o r M oni t o ri ng, I m pl ement a t i on, and A d mi ni st rat i on*



### Sy st em Size C a t e gory < 10,000 people > 10,000 people

St at e A c t i v i t y H ours R at e H ours R at e

R e v i ew a w a i v er appl i c ati o n 8 $41.47 8 $ 41.47

R e cor d moni tor i ng of a

sam p le result 1 $41.47 1 $41. 47

I ssue a single v i olat ion let t e r 4 $41. 47 4 $41. 47

Rev i ew a single perm i t 1 6 $41. 47 32 $41. 47

<3, 000 p e o p l e > 3, 300 p e o p l e

Sy stem A c ti v i ty Ho u r s R ate H o u r s R ate

Apply for a waiv er 16 $15. 03 16 $29. 03

Tak e a sam p le 1 $15. 03 1 $29. 03

Report a sam p le 1 $15. 03 1 $29. 03

Prepare and Send Public

N o ti f i ca ti o n 8 $15. 03 8 $29. 03

Source: I n f

o rm at ion Collect ion Request f

o r t he Public W a t

e r Syst em Supervision Program

. *Est im at es are prov ided in M a y 1999 dollars, updat ed from 1997 dollars using t he CPI

- U for all it em s.



### States will also be required to spend time responding to sy stems that report MCL ex ceedances or

sy stems that request a waiver (Ex h ibit 6-3). Hour burdens for States to review waiver
applications, record monitoring of a sample, and issue a violation letter are the same for small
and larg e sy stems. The number of hours required to review a sing le permit is twice as larg e for

sy stems serving more than 10,000 people than for sy stems serving less than 10,000 people. The

unit cost for all activities is consistent across all activities and siz e categ ories ($41.47 per hour)

(EPA, 1997).

Ex hibit 6-3 also shows that the number of hours required at the sy stem level to perform the
responsibilities related to monitoring is the same for sy stems serving fewer than 3,300 people and

sy stems serving more than 3,300 people. However, the hourly rate for sy stems serving more than 3,300 people ($29.03) is almost double the rate for sy stems serving fewer than 3,300 people ($15.03).

Chapter 6, Cost Analysis 6-14 Arsenic in Drinking Water Rule EA

### Dur i ng the f i r s t y e a r of imple me nta tion a ll sy ste m s will inc u r c o sts r e la te d to r outine monitor i ng

. I n addition, sy stems in violation will incur costs related to trig g e red quarterly monitoring

. Under

the r e vise d r u le , a pe r c e n ta g e of the sy ste m s will ha ve monitor i ng wa ive r s in subse que nt y e a r s when monitoring is otherwise required. Monitoring waivers are not g r anted under the ex isting
rule; therefore, the number of sy stems required to conduct routine monitoring under the revised

rule is less than that under the ex isting rule. F o r this reason, the annual net cost of monitoring

be twe e n the r e vise d r u le a nd the e x isting r u le ma y be ne g a tive

, or le ss e x pe nsive

, a f te r the initia l

y ear of implementation. The inputs and methodolog y associated with this analy s is are presented

in de ta il in the Information Collection Request for the Proposed Arsenic in Drinking W a ter Rule.

A d minist rat i ve C o st s

Sta t e s a nd sy ste m s will inc u r a d ministr a tive c o sts to imple me nt the r e vise d a r se nic pr og r a m
under the Arsenic Rule. States and sy stems will need to allocate time for their staff to establish
and maintain the prog rams necessary to comply with the revised arsenic standard and the new
monitoring requirements. Ex hibit 6-4(a) lists the one-time State activities involved in starting up
the pr og r a m f o llowing pr omulg a tion of the r u le

. F o r e x a m ple

, sta r t- up a c tivitie s ma y inc l ude
developing and adopting State reg u lations that meet the new F e deral arsenic requirements.

Re sour c e s a r e e s tima te d in te r m s of f

u ll- time e quiva le nts ( F TEs)

, whic h EPA ha s a ssume d to cost $64,480 per F TE, including overhead and fring e. Sy stems also have start-up costs for

r e vie w ing the r u le a nd tr a i ning ope r a tor s . Ex hibit 6- 4( b) lists the one

- time sy ste m sta r t- up

a c tivitie s. The two pr ima r y a c tivitie s tha t sy ste m s will pe r f o r m to c o mply with the r e vise d
arsenic rule are reading and understanding the rule and operator training

. F o r all sy stems the
estimated time required to review the rule is eig h t hours. Sy stems serving fewer than 10,000
people require an estimated time of 16 hours to train operators; the estimated time for sy stems serving more than 10,000 people is 32 hours. The rate for all start-up activities for sy stems serving fewer than 10,000 people is $15.03 per hour and $29.03 per hour for sy stems serving
more than 10,000 people.

Exhi bi t 6- 4( a)

Est i mat e d O n e- T i me St at e Resources Requi red f o r I n i t i a t i on of t h e A r seni c Rul e

A d ministrativ e A c tiv i ty Estimated State

Reso u r ces (F TE) E sti m ated Co st

One T i me Start-up A c tiv i ties

Regulat ion Adopt ion and Program Dev e lopm ent 0. 2 $12, 900

Sy st em Training and Technical Assist ance (CW S ) 0

. 5 $32, 240

Sy st em Training and Technical Assist ance (NTNC) 0. 5 $32, 240

St aff Training (CW S ) 0

. 1 2 $7, 740

National T o tal* 73. 92 $4, 767, 840

*Nat ional t o t a ls include est i m a t e s for all St at es, t e rrit o ries, and Tribes.

Chapter 6, Cost Analysis 6-15 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 4( b)

Est i mat e d O n e- T i me Sy st em Resources Requi red f o r I n i t i a t i on of t h e A r seni c Rul e

Sy stem Si ze Categ o r y < 10, 000 p e o p l e > 10, 000 p e o p l e

One T i m e Sta r t-up A c tivity H our s R a t e H our s R a t e

Reading and Underst anding

Rule 8 $15. 03 8 $29. 03

O perat or Training 16 $15. 03 32 $29. 03

Source: I n f

o rm at ion Collect ion Request f

o r t he Public W a t

e r Syst em Supervision Program

.



### 6.2.4 P redict ing C o mpliance D ecisions ( C ompliance D ecision Tree)

The r e is substa ntia l va r i a b ility in how sy ste m s will e l e c t to c o mply with the Ar se nic Rule

. Choices of compliance method will vary depending on baseline source water arsenic
concentrations, sy stem siz e and location, ty pes of treatment currently in place, and availability of

alternative sources. I n addition, the source water pH, total dissolved solids, sulfides, and other
salts can chang e the effectiveness of technolog ies in removing arsenic.

The EA reflects this variability by predicting a rang e of compliance responses for different

sy st em t y pes and si z e s. The com p l i a nce deci si on t r ee speci fi es t h e percent a g e of sy st em s i n different categ ories that will choose specific compliance options, g i ven the removal required by

t h e MC L opt i on and t h e basel i n e occurrence of arseni c i n source wat e r. For ex am pl e, for a t a rg et

MCL of 10 μg /L , the de c i sion tr e e spe c i f i e s the pr oba bility of dif f

e r e nt c o mplia nc e c hoic e s f o r

sy stems with different baseline influent concentrations (e.g ., <10 μg /L , 10-20 μg /L , etc.),

different siz e s (e.g ., population < or > 1,000), different sources (g round water or surface water),

a nd dif f

e r e nt e x isting tr e a tme nt f a c ilitie s. The c o mplia nc e c hoic e s a r e de f i ne d by a

tr e a tme nt technolog y and (where relevant) a waste disposal option, and/or pre-treatment technolog y

.

EP A present e d a draft of t h e com p l i a nce deci si on t r ee at an Am eri can W a t e r W o rks Associ at i o n (AW W A ) technical workg r oup meeting in F e bruary 1999 and made revisions based on the

com m e nt s recei ved at t h at m eet i n g

. The fi nal com p l i a nce deci si on t r ee, as wel l as a di scussi on of the assumptions made during its development, is provided in Appendix A (“Cost Analy s is
Appendix ” ) by sy stem siz e and ty pe.

6.2.5 C alculat i ng C o st s

Different methods were used to assess costs for three different categ ories of sy stems. A MonteCa r l o simula tion mode l ( S a f e W a t e r XL ) wa s use d to e s tima te c o sts f o r

c o mmunity wa te r sy ste m s,

ex cl udi ng t h e l a rg est C W S s

. A det e rm i n i s t i c spreadsheet anal y s i s was perform ed for NTNC

wat e r sy st em s, whi l e a separat e case-by -case anal y s i s were perform ed for t h e very l a rg e sy st em s (serving more than one million people) that are ex pected to ex ceed one or more MCL options in

t h e basel i n e. The cost s for t h e t h ree sy st em cat eg ori e s were t h en sum m e d t o cal c ul at e t o t a l

national costs.

Chapter 6, Cost Analysis 6-16 Arsenic in Drinking Water Rule EA

### The methodolog y for calculating the costs for each of these sy stem categ o ries is described
separately below, beg i nning with a description of the SafeW a terXL model. I n addition, a
detailed description of the SafeW a terXL model is provided in Appendix C.

CWS Cos t s

The na tiona l c o st of c o mplia nc e a c r oss CWSs ( e x c e p t those se r v ing ove r one million pe ople ) wa s

e s tima te d using Sa f e Wa te r X L

, a Monte

- Ca r l o simula tion mode l de ve lope d in Mic r osof t® Ex c e l

usi n g t h e C r y s t a l Bal l © Mont e-C a rl o si m u l a t i on add-i n. S a feW a t e rXL forecast s a di st ri but i on of
costs around the mean compliance cost ex pected for each sy stem siz e categ ory

. The MonteCa r l o mode l pr ovide s the f l e x ibility to inc o r por a t e a s ma ny da ta a s a r e a v a ila ble

, while
maintaining uncertainty bounds to prevent any individual input from skewing the results. W h en

sa mple da ta a r e not a v a ila ble a s sing le point e s tima te s, this te c hnique is a n inva lua b le tool.

Histor ic a lly , most dr inking wa te r r e g u la tor y impa c t a n a l y s e s use d point e s tima te s to de sc r i be the

averag e sy st em -l evel cost s. By usi n g S a feW a t e rXL

, t h i s anal y s i s cont ai ns m o re det a i l e d
descriptions of sy stem-level cost. SafeW a ter XL describes sy stem-level costs in terms of a

distribution. F r om the distribution, mean and median costs are available, as well as percentile

costs.

M odel Str u ctur e

SafeW a terXL determines reg u latory compliance costs for individual sy stems and subsequently
calculates a national averag e. To do so, each sy stem is assig n ed a random concentration from an

occurrence distribution. This sy stem concentration is distributed across the number of sites of
possible contamination for that sy stem. The averag e number of sites per sy stem is determined

ba se d on the distr i bution of sy ste m inta ke site s f o r

the size c a t e g or y a s e s tima te d f r o m the

CWSS. Howe ve r

, Sa f e Wa te r X L doe s not a ssume tha t a ll site s a r e e qua lly like l y to e x c e e d the

MCL standard. The likelihood of contamination is determined on a site-by

- site basis. The sum

of t h e m ean arseni c concent r at i on of al l si t e s wi t h i n a sy st em m u st equal t h e m ean arseni c concentration of the sy stem. Given this upper bound, each site is assig n ed a concentration based
on the assumed relative standard deviation around the mean sy stem occurrence.

The m odel t h en com p ares t h e concent r at i on at each si t e t o t h e revi sed MC L st andard; no cost s
are i n curred for t hose si t e s whose concent r at i ons fal l bel o w t h e speci fi ed MC L

. I f t h e si t e i s
de te r mine d to be in viola tion of the MCL

, the n Sa f e Wa te r X L c a l c u la te s the pe r c e n t r e duc tion in
arsenic concentration required to reduce the site concentration to 80 percent of the MCL standard
(this is a safety factor that includes a 20 percent ex cess removal to account for sy stem overdesig n ). 1 

### A treatment train is then assig n ed to the site based on a decision tree for the siz e and

t y

pe of t h e sy st em

. The deci si on t r ee and t h e sel ect ed t r eat m e nt t r ai n refl ect t h e rem oval
efficiencies of the chosen technolog y

. F o r ex ample, a technolog y is chosen based on matching

1 No blending is assum e d f o r the POU technolog ies.

Chapter 6, Cost Analysis 6-17 Arsenic in Drinking Water Rule EA

### t h e rem oval effi ci enci es and t h e percent a g e rem oval requi red at t h e si t e (S afeW at erXL i d ent i f i e s three categ ories of required removal: < 50 percent, 50-90 percent, > 90 percent). 2



### I n this ma nne r

, c a p ita l a nd O& M c o sts a r e c a l c u la te d a t the site le ve l f o r

the se le c t e d tr e a tme nt

tr a i n. The sy ste m ’ s c o st of c o mplia nc e is the n de te r mine d by summing a c r oss the tr e a ting site s. For each sy st em i n S D W I S i n whi c h a vi ol at i on i s ex pect ed, a cost i s cal cul a t e d wi t h t h i s method, thereby creating an estimate of national compliance costs. Since household costs are
also calculated for each sy stem, a similar distribution of the cost of compliance at the household

l e vel i s al so creat ed.

I n order to develop more detailed results, the compliance decision tree is employ ed at the site

le ve l, so tha t only those site s r e quir i ng tr e a tme nt would inc u r c o sts. The r e sulting tota l na tiona l

com p l i a nce cost i s ex pect ed t o be a t r uer represent a t i on of t h e i m p act of t h e Arseni c R u l e on

sy ste m s. The se c tions be low will de sc r i be the da ta ne e d e d to de ve lop c o st e s tima te s f o r

the
entire universe of sy stems affected by the Arsenic Rule. After the discussion of data
requirements, the SafeW a terXL model is described as it is used for this rule.

M odel Inputs

Number of Systems: The universe of public and private g r ound and surface water sy stems is
taken from the Safe Drinking W a ter I n formation Sy stem (SDW I S ), EPA’s national reg u latory
database for the drinking water prog ram. B a sed on data ex tracted in December 1998, a total of

54,352 CW Ss and 20,255 NTNCs are subject to the new requirements under the Arsenic Rule. I t is necessary to compile this data by sy stem siz e , water source, and ownership, as costs may vary by t h ese charact eri s t i c s. S a feW a t e rXL cal cul a t e s cost s for publ i c and pri v at e sy st em s (t he l a t t e r also includes “other” or “ancillary ” sy stems), and surface and g r ound water sy stems. A summary
table of this breakdown is provided in Chapter 4, “B aseline Analy s is.”

Entry Points pe r Sy ste m : SafeW a terXL estimates each sy stem’s cost of compliance at the

t r eat m e nt si t e l e vel

. Thi s m odel i n g approach i s used because a sy st em m a y i n cl ude m o re t h an
one treatment site. Entry points are used as a prox y for potential or actual points of treatment.

F o r ex ample, a g i ven water sy stem may have three entry points: one entry point that currently

t r eat s, whi l e t w o m a y not have t r eat m e nt i n pl ace. Dat a on t h e di st ri but i on of t h e num ber of

sy st em ent r y poi nt s for each si z e cat eg ory and t y pe were ex t r act e d from t h e C o m m uni t y W a t e r Supply Survey (CW SS). L i near interpolation was used to estimate values for the number of sites

i n cases where t h ere were no survey dat a (see C h apt e r 4, “Basel i n e Anal y s i s ”). S a feW a t e r XL

uses t h i s m odi fi ed di st ri but i on of ent r y poi nt s for each sy st em si z e and source wat e r cat eg ory

.

Population Served by System: A sy stem’s siz e is determined by the number of people served by

t h at sy st em

. These num bers were ex t r act ed from t h e S D W I S dat a base (see C h apt e r 4, “Basel i n e Analy s is”). Sy stems are g r ouped into eig h t categ ories to help identify sy stems with related
characteristics so that any data or resources may be pooled during analy s is.

2 The > 90 percent rem o v a l ef f i ciency categ ory is not relev a nt under the rev i sed MCL of 10 μg /L

.

Chapter 6, Cost Analysis 6-18 Arsenic in Drinking Water Rule EA

### S a feW a t e rXL recog n i z es t h e fol l o wi ng si z e cat eg ori e s:

• < 100

• 101-500

• 501-1000

• 1,001-3,300

• 3,301-10,000

• 10,001-50,000

• 50,001-100,000

• 100,001-1,000,000.

Flow Rate Parameters: A sy stem’s siz e is further defined by its flow, which is calculated as a
power law function of the population served. These functions were derived by EPA, and their
derivation can be found in the Model Sy stems report (EPA, 1999b). The equation form is shown

below.

Average Flow a A 

### # ( Population ) b A



### 2 # Average Flow Design Flow ma x
a D 

### # ( Population ) b D



### W

h ere: a A 

### , b A 

### , a D 

### , b
D 

### = the reg r ession parameters derived for flow vs.
population
Population = t he population served by the appropriate sy stem ty pe and
primary source.

The reg r ession parameters used in the cost model are provided in Ex hibit 6-5. Values are
provided for desig n and averag e flow for public and private g r ound water and surface water
supplie s. Sa f e Wa te r X L divide s the r e sulting sy ste m de sig n f l ow a nd a v e r a g e da ily f

l ow ( k g pd)
equal l y am ong al l ent r y poi nt s. Treat m e nt cost s are cal c ul at ed onl y at t h e si t e s t h at ex ceed t h e

MCL and only for the minimum portion of flow that must be treated in order to achieve the new
concentration standard, a process referred to as “blending .”

Chapter 6, Cost Analysis 6-19 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 5

Fl ow Regressi on Paramet e rs by Wat e r Source and Sy st em O w nershi p

A

v

er a g e F l o

w D e si g n F

l o

w

a b a b

G

r ou nd W a

t e r

P ubl i c 0. 08558 1. 05840 0. 54992 0. 95538

P

r i v at e 0

. 06670 1. 06280 0. 41682 0. 96078

P

ubl i c

- P ur c h 0. 04692 1. 10190 0. 31910 0. 99460

P

r i v at e- P u r c h 0

. 05004 1. 08340 0. 32150 0. 97940

S

u r f ace W a

t e r

P ubl i c 0. 14004 0. 99703 0. 59028 0. 94573

P

r i v at e 0

. 09036 1. 03340 0. 35674 0. 96188

P

ubl i c

- P ur c h 0. 04692 1. 11020 0. 20920 1. 04520

P

r i v at e- P u r c h 0

. 05004 1. 08340 0. 20580 1. 00840



### Average Consumption per Household: Household costs depend on the averag e annual
consumption per residential connection. These mean estimates are provided in Chapter 4,

“ B a s e line Ana l y s is.” De pe nding on the sy ste m ’ s c h a r a c t e r istic s, Sa f e Wa te r X L multiplie s the
appropriate mean consumption per y ear (kg a l) with the sy stem’s computed cost per thousand

g a llons to arrive at the averag e annual cost of compliance per household for a community water

sy stem.

Mean Syst em Occurrence: Arsenic occurrence data are based on EPA’s Arsenic Occurrence in
Public Drinking W a ter Supplies report (EPA, 2000) and are represented by a log normal

distribution. B a seline occurrence is disting u ished between g r ound and surface water sy stems and
is provided in Chapter 4 (“B a seline Analy s is”) as a log normal distribution. The distribution is

t r uncat ed at 50 μ g / L , t h e current arseni c st andard, because i t i s assum e d t h at al l arseni c reductions attributable to the new standard start at the previous standard (i.e., all sy stems are

c u rr e ntly in c o mplia nc e with the c u r r e nt sta nda r d )

.

F o r use in the SafeW a terXL model, EPA performed a reg r ession analy s is that weig hted actual
occurrence data by National Arsenic Occurrence Survey reg i on. The analy s is resulted in the
distribution of g r ound and surface water sy stems ex ceeding arsenic concentrations g r eater than 3,
5, 10, and 20 μg /L as presented in Ex hibit 6-6.

Chapter 6, Cost Analysis 6-20 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 6

A r seni c O ccurrence Di st ri but i o n ( Log- Normal Regressi on Resul t s)

3 5 10 20

GW 19

. 7 12

. 0 5. 3 2

. 0

SW 5. 6 3

. 0 1. 1 2 0. 3 7 %

o f sy st e m s g r e a t e r t h a n ( μ g/ L) S our c e



### F o r g r ound water sy stems, the percentag e s display e d in Ex hibit 6-6 above were based on a
log normal distribution with a mean of -0.25071 and a log standard deviation of 1.58257. Among

surface wat e r sy st em s, t h e percent a g e s were based on a l o g norm a l di st ri but i on wi t h m ean -1.67805 and a log standard deviation of 1.7425.

Relative Intra-System Standard Deviation of Arsenic Concentrations: The r e la tive intr a

- sy ste m standard deviation of the site concentrations within a sy stem is calculated using data from a 25
State arsenic occurrence study (EPA, 2000b). SafeW a terXL uses a default value of 0.64. This
standard deviation is applied to the mean sy stem concentration to g e nerate individual entry points

c onc e n tr a tions within the sy ste m

.

C o mpl i ance Deci si on T r ees: The de c i sion tr e e s r e pr e s e n t EPA’ s be st e s tima te of the tr e a tme nt train technolog ies sy stem operators will choose to achieve a particular percentag e reduction in

arsenic concentration. Decision trees are specific to the sy stem’s siz e categ ories and source

water. These are provided in Appendix A.

Removal Efficiencies, Treatment Target, and Blending: Each t r eat m e nt t r ai n i s associ at ed wi t h an arsenic removal efficiency that is assumed to be constant across sy stem ty pes. The removal
efficiencies for the 13 treatment trains available under the Arsenic Rule were presented in

Ex hibit 6-1. SafeW a terXL employ s these efficiencies, using the blending principle, to determine
the amount of flow that requires treatment in order for the entry point to meet the treatment

targ et. B l ending uses the entry point concentration and treatment train removal efficiency to determine the fraction of flow required to obtain the treatment targ et. The treatment targ et is set

a t 80 pe r c e n t of the MCL a nd r e pr e s e n ts the le ve l to whic h sy ste m s will be ove r

- d e s ig ne d to

e n sur e c o mplia nc e with the MCL

.

SafeW a terXL employ s the blending principle throug h the following equation at the entry point

le ve l:

( T r eatm entT arget 

### 1) # (% Site Flow )

SiteConcentr ation 

### Frac tion o f flow t re ate d

% Re mov a l E ffic ie nc y

Chapter 6, Cost Analysis 6-21 Arsenic in Drinking Water Rule EA

### Wh e r e : T reatment Targ et = t he targ et MCL with 80 percent safety factor

Site Conc e n tr a tion = a r s e n ic c onc e n tr a tion a t the site

% R e m oval Effi ci ency = percent removal efficiency of treatment train chosen

% Site F l ow = pe r c e n t of tota l f l ow a t tha t site

.

Note that the blending technique is used only for those sy stems ex pected to require less than 90
percent removal in order to achieve compliance with the new MCL standard. I n addition,

SafeW a terXL does not employ this technique for those sy stems that select treatment trains
involving POU devices.

Equipment Life, Discount Rate and Capitalization Rates: S y st em and S t at e i m p l e m e nt at i on cost s are tracked for a 20-y ear period. This time frame was selected because water sy stems often
finance their capital improvements over a 20-y ear period. This period of analy s is may result in

an overestimate of annualiz ed costs because many ty pes of equipment last long er than 20 y ears.

Two different adjustments are made in this analy s is in order to render future costs comparable

wi t h current cost s, refl ect i n g t h e fact t h at a cost out l a y t oday i s a g r eat er burden t h an an

e quiva le nt c o st outla y some time in the f u tur e

. The f i r s t a d justme nt is ma de whe n the c o st estimates that are derived are being used as an input in benefit-cost analy s is. I n this instance,

costs are annualiz ed using a social discount rate so that the costs of each reg u latory option can be
directly compared with the annual benefits of the corresponding reg u latory option.

Annualiz ation is the same process as calculating a mortg a g e pay m ent; the result is a constant
annual cost to compare with constant annual benefits.

The choice of an appropriate social discount rate has been, and continues to be, a very complex
and controversial issue among economists and policy makers alike. Therefore, the Ag ency compares costs and benefits using two alternative social discount rates, in part to determine the
effect the choice of social discount rate has on the analy s is. The annualiz ed costs of each

reg u latory option are calculated and display e d using both a seven percent discount rate, required
by the Office of Manag e ment and B udg et (OMB ), and a three percent discount rate, which the
Ag ency believes more closely approx imates the true social discount rate.

The second adjustment is made when the cost estimates that are derived are being used as an
input into an economic impact analy s is, such as an affordability analy s is or an analy s is of sy stemlevel costs or household-level costs. I n these cases, rather than use a social discount rate when
determining the annualiz ed costs, an actual cost-of-capital rate is used instead. This rate should

refl ect t h e t r ue aft e r-t ax cost of capi t a l wat e r sy st em s face, net of any g overnm e nt g r ant s or
subsidies. The cost of capital rates used in this analy s is are shown in Ex hibit 6-7.

Chapter 6, Cost Analysis 6-22 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 7 Summary of Recommended Cost of Capi t a l Est i mat es ( as of M a rch 1998)

O w ne r s hi p Ty pe S i z e C a t e g o ry E s ti m a te d A fte r

- T a x

Co s t o f Ca p i t a l

N O N- S M AL L

I n v e s t or o w ne d 1 0

, 001 -50

, 000 5. 2 6 %

> 5 0

, 000 5. 9 4 %

P u bl i c l y o w ne d 1 0

, 001 -50

, 000 5. 2 6 %

> 5 0

, 000 5. 2 3 %

SMA L L

P r i v a t e 1 -5 00 4. 1 7 %

50 1-10

, 0 0 0 4. 1 7 %

P u bl i c 1-5 0 0 5

. 1 0%

50 1-10

, 0 0 0 5. 2 0 %

So u r c e : D e v e l o p m e n t o f C o s t o f C a

p i ta l E s ti m a te s fo r P u b l

i c

Wa t e r S y

s t e m s (D ra f t F i n a l Repo rt ). P r ep ared f o r U. S

. E P A by

A p og ee/ Hagl er B a i l l y

, I n c

. u n d e r s u bc o n t r ac t t o I n t e rna t i o nal

C o ns ul t a nt s

, I n c

. J u ne 1 998

.



### NTNC Cos t s

The cost for NTNCs is estimated using the mean values for sy stem population for each sy stem service categ ory

, as shown in Chapter 4. As with the CW Ss, cost is annualiz ed over a 20-y ear period, at discount rates of three and seven percent. Assumptions reg a rding the monitoring
schedule correspond to the monitoring schedule for small g r ound water sy stems, including hour
burdens and hourly labor rates. The remaining assumptions required for determining cost are

described below.

Number of Systems, Sites per System, and the Population Served: The non-transient noncommunity water supply treatment decisions are modeled similarly to those for community water supplies. The number of non-transient non-community water supplies is taken from EPA’s

SDW I S, and include those sy stems as described in Geometries and Characteristics of Public

W

a ter Supplies (see Ex hi bi t 6-8). For each servi ce area t y pe, t h e report l i s t s t h e num ber of

sy stems and the averag e population served. The non-food manufacturing service area combines
16 categ ories that were listed separately in the report. F o r this service area, the number of

sy stems is the sum of the 16 categ ories, and the averag e population served is the mean of the
individual populations weig hted by the number of corresponding sy stems. Each of these sy stems has only a sing le site.

System Flows and Treatment Choices : For each servi ce area, bot h desi g n and averag e fl ows have

be e n de r i ve d by the Ag e n c y using lite r a tur e va lue s a nd be st e n g i ne e r ing judg me nt. The r e a r e no primary survey data for non-community water sy stems that are equivalent to the CW SSprovided data for the community water sy stem flow calculations (Smith, 1999). The desig n flow

is use d to c a l c u la te the tr e a tme nt c a p ita l c o sts, while the a v e r a g e f l ow is use d in the ope r a ting
and maintenance cost equations.

Chapter 6, Cost Analysis 6-23 Arsenic in Drinking Water Rule EA

### F o r the non-transient non-community water supplies, one of two treatment technolog ies was
chosen based on the level of the desig n flow. F o r service areas with desig n flows less than 2,000

g a llons pe r da y

, POE a c tiva t e d a l umina is use d ; f o r

a ll othe r s , c e ntr a lize d a c tiva t e d a l umina is
chosen (Kapadia, 1999a). B o th treatment trains include pre-ox idation, and the centraliz ed

activated alumina also includes non-haz a rdous landfilling of the spent media (Kapadia, 1999a).

Mean Arseni c Occurrence: The arsenic occurrence distribution used for g r ound water
community water supplies is also used for non-transient non-community water supplies. The

num ber of sy st em s ex ceedi n g t h e MC L for each servi ce area was cal cul a t e d from t h e percent of

the distribution between the MCL and 100 μg /L

. F o r this analy s is, 100 μg /L was chosen as the
upper concentration limit because the non-transient non-community supplies have not been
previously reg u lated, and occurrence values above the 50 μg /L reg u latory level are possible.

Removal Efficiencies, Treatment Target, and Blending : The rem oval effi ci ency associ at ed wi t h

bot h P O E act i v at ed al um i n a and cent r al i z ed act i v at ed al um i n a i s 95 percent

. The NTNC m odel

uses t h i s effi ci ency wi t h t h e bl endi ng pri n ci pl e i n t h e case of cent r al i z ed act i v at ed al um i n a t o determine the amount of flow that requires treatment in order for the site to meet the treatment

ta r g e t

. The tr e a tme nt ta r g e t is se t a t 80 pe r c e n t of the MCL a nd r e pr e s e n ts the le ve l to whic h

sy ste m s will be ove r

- d e s ig ne d to e n sur e c o mplia nc e with the MCL

. F o r POE a c tiva t e d a l umina

sy ste m s, a ll the f l ow is tr e a t e d, whic h ma y r e sult in f i nishe d wa te r be low the tr e a tme nt ta r g e t

concent r at i on.

Equipment Life, Discount Rate, and Capitalization Rates: As with the c o mmunity wa te r supplies, the sy stem implementation costs are tracked for a 20-y ear period. F o r the two service
areas using POE activated alumina, construction and forest service, the equipment is assumed to

l a st t e n y ears wi t h purchases i n y ear z e ro and y ear t e n. For t h e cent r al i z ed act i v at ed al um i n a t h e equipment is estimated to last 20 y ears. The cost estimates are annualiz ed in the same manner as

those f o r

the c o mmunity wa te r supplie s.

Chapter 6, Cost Analysis 6-24 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 8

Non- T r ansi ent Non- Communi t y Sy st em Charact eri s t i cs and Compl i a nce Deci si on T r ee

Ser v i c

e A

r ea Type SY STEM CH A

R

A

C

TERI STI C S D E C I S I O N T R E E

Num b

er

of
Syst em s A ver age Popul at i on

Ser ved Per

S

y

st em Desi gn Fl ow ( m

gd) A ver age Dai l y

Fl ow ( m gd) Ac t i v

a

t e

d

Al u m i n

a

Poi n t of

Ent r y C e

n

t r a liz e d

Ac

t i v

a

t e

d

Al u m i n

a

D

a yca re C

e n

t e r s

Hi g h w

a y Re s t A

r e

a

s

H

o t e l s

/ M

ot

el s

In

t e rs t a t e C

a rr i e rs

M

e

d i ca l F

a

ci l i t i e s

Mo b i l e H

o me P

a r k s

R

e

st

aur ant s

Sc ho ol s

Ser v i c e St at i ons

Sum m

er

Cam p s

W

a t e r

W hol esa l er s Agr i c u l t ur al Pr oduc t s / S

er

v i c e

s

Ai r par k s

Cons t r uc t i o n

Chur c h e s

Cam p

gr ound s/ R V

P

a r k s

Fi r e Depa r t m

e n

t s

F

e

d e ra l P

a rk s

F

o re s t S

e rv i c e

G

o l f

a nd Count r y

C

l ubs

Lan df i l l s

M

i ni ng

Am u s

em ent

Par k s

Mi l i t a r

y B

a

s e

s

M

i gr ant L

abor Cam p s

M

i s

c

. R e

c r ea t i on S

e r

v i c e

s

Nu r s i n g Ho me s

O

ffic e P

a rk s

Pr i s o n s

R

e t a i l er s ( N o n

- f ood r e l a t e

d )

R

e t a i l er s ( F

o

od r e l a t e

d )

St

at

e Par k s

N

on- W a t e r

U

t i l i t i e s

M

a nuf ac t u r i ng : Food

M

a nuf ac t u r i ng : N o n- Food 80 9

15

35 1

28

7

36

7

10

4

41 8

84 14

53

46

26

6

36

8

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99

23

0

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78

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9

95

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67

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83

49

7

76

8

38

45 7 6

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1 3

3

1 2

3

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35

8

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0

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6

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7 6

6 0

53

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0

98

39

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63

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1 0

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18

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1 7

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16

8 0

. 0 051

0

. 0

089

0. 0 189

0. 0

029

0. 1 166

0. 0

262

0. 0

039

0

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333

0

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0

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218

0. 1 637

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0

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0. 0

214

0. 0 186

0. 0

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0. 0 102

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0. 0

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0. 0

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0. 0

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0. 0

494

0. 0

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0. 0

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0. 0

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0. 0 120

0. 0

038 ↵

↵ ↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

↵

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↵

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↵

↵

↵

↵

↵

↵

TO T

A

L 20, 2 5

5

Sour c e : Geom et r i es and C har ac t e ris t ic s of Public W a t e r Sy s t em s

, EPA, M a y 1999.

Chapter 6, Cost Analysis 6-25 Arsenic in Drinking Water Rule EA

### Very Large CWS Costs

EPA e v a l ua te d the r e g u la tor y c o sts of c o mplia nc e f o r

ve r y la r g e sy ste m s tha t will be subje c t to the new Arsenic Rule. The nation’s 25 larg est drinking water sy stems (i.e., those serving one million people or more) supply approx imately 38 million people and g e nerally account for about
15 to 20 pe r c e n t of a ll c o mplia nc e

- r e la te d c o sts. Ac c u r a te ly de te r mining the s e c o sts f o r

f

u tur e

r e g u la tions is c r itic a l

. As a r e sult, EPA ha s de ve lope d c o mplia nc e c o st e s tima te s f o r

the a r se nic
and radon reg u lations for each individual sy stem that serves more than one million persons.
These cost estimates help EPA to more accurately assess the cost impacts and benefits of the

Ar se nic Rule

. The e s tima te s a l so he lp the Ag e n c y ide n tif y

lowe r c o st r e g u la tor y options a n d
better understand current water sy stems’ capabilities and constraints.

The sy stem costs were calculated for the 24 public water sy stems that serve a retail population of
more than one million persons and one public water sy stem that serves a wholesale population of
16 million pe r s ons. The f o llowing a r e disting u ishing c h a r a c t e r istic s of the s e ve r y la r g e sy ste m s:

(1) A larg e number of entry points from diverse sources;

(2) M ix ed sources (i.e., g r ound and surface water);

(3) O ccurrence not conducive to mathematical modeling ; (4) S ig nificant levels of wholesaling ; (5) S ophisticated in-place treatment;

(6) R et rofi t cost s dram at i cal l y i n fl uenced by si t e -speci fi c fact ors; and

(7) L arg e amounts of waste manag e ment and disposal, which can contribute

substa ntia l c o sts.

Generic models cannot incorporate all of these considerations; therefore, in-depth

characteriz ations and cost analy s es were developed using several ex isting databases and survey s.

The profi l e for each sy st em cont ai ns i n form at i on such as desi g n and averag e dai l y fl ows,

tr e a tme nt f a c ility dia g r a ms, c h e mic a l f e e d pr oc e sse s, wa te r qua lity pa r a me te r s , sy ste m la y outs, and intake and aquifer locations. Sy stem and treatment data were obtained from the following

sources:

(1) T he I n formation Collection Rule (1997);

(2) T he Community W a ter Supply Survey (1995);
(3) T he Association of Metropolitan W a ter Ag encies Survey (1998);
(4) T he Safe Drinking W a ter I n formation Sy stem (SDW I S ); and
(5) T he American W a ter W o rks Association W A TERSTATS Survey (1997).

W h ile these sources contained much of the information necessary to perform cost analy s es, the
Ag e n c y wa s still missing some of the de ta ile d a r se nic oc c u r r e nc e da ta in the s e la r g e wa te r

sy stems. W h ere major g a ps ex isted, especially in g r ound water sy stems, occurrence data

obta i ne d f r o m the Sta t e s of Te x a s, Ca lif or nia

, a nd Ar izona ; the Me tr opolita n Wa te r Distr i c t of
Southern California Arsenic Study (1993); the National I norg a nic and Radionuclides Study
(EPA, 1984); and utility data were used. B a sed on data from the studies, detailed costs estimates

were deri ved for each of t h e very l a rg e wat e r sy st em s.

Chapter 6, Cost Analysis 6-26 Arsenic in Drinking Water Rule EA

### Cost estimates were g e nerated for each sy stem at several MCL options. The total capital costs

a nd ope r a tiona l a nd ma inte na nc e ( O & M ) c o sts we r e c a l c u la te d using the pr of ile inf o r m a tion

g a thered on each sy stem, conceptual desig n s (i.e., vendor estimates and RS Means ), and modified
EPA cost models (i.e., W a ter and W a terCost models). The models were modified based on the

g e neral cost assumptions developed in the Phase I W a ter Treatment Cost Upg r ades (EPA,

1998c).

EP A consul t e d wi t h t h e sy st em operat o rs t o det e rm i n e how each sy st em woul d com p l y wi t h

various MCL options and to assess the costs of their compliance responses. Preliminary cost

e s tima te s we r e se nt to a ll of the sy ste m s f o r

the i r r e vie w

. Appr ox ima te ly 30 pe r c e n t of the

sy stems responded by submitting revised estimates and/or detailed arsenic occurrence data.

B a sed on the information received, EPA revised the cost estimates for those sy stems. EPA

de ve lope d c o st e s tima te s f o r

thr e e ve r y la r g e sy ste m s tha t a r e e x pe c t e d to ha ve a r se nic le ve ls

above the revised MCL

. These sy stems are located in Houston, TX, Phoenix

, AZ , and L o s Ang e le s, CA. This a n a l y s is r e sulte d in the e s tima te d c o sts liste d in Ex hibit 6- 9.

Exhi bi t 6- 9

A nnual T r eat ment Cost s f o r T h ree Large CWSs Expect ed t o
Undert ake or M odi f y T r eat ment Pract i ce t o Compl y w i t h t h e A r seni c Rul e ($ millio n s )

La r g e C W S s P opul a t i on

Se r v e d MC L ( μ g/ L)

3 5 1 0 2 0

P hoe ni x , A Z 1, 3 6 0

, 751

A n nu al c o s t (3% )

A n nu al c o s t (7% )

H ous t on, TX 2, 2 1 6

, 830 $

$ 11

. 6

13

. 2 $

$ 5

. 5 $

6

. 3 $ 2

. 2

2

. 5 $

$ 0

. 0

0

. 0

A n nu al c o s t (3% )

A n nu al c o s t (7% )

Los A nge l e s , C A

A n nu al c o s t (3% )

A n nu al c o s t (7% ) 3, 7 0 0

, 000 $

$

$

$ 15

. 0

16

. 0

1. 8

1. 8 $

$

$

$ 2

. 7 $

2

. 9 $

1

. 8 $

1

. 8 $ 0

. 9

1

. 0

-

- $

$

$

$ 0

. 5

0

. 5

-

-

* E x h i b i t up da t ed o n Dec e m b er 28

, 20 00 t o ref l ec t m i nor c h a nge s i n c o s t e s t i m a t e s w h i c h h a v e no t

be en i n c o rp ora t ed i n t o s u b s e que nt e x hi bi t s

. T he i m p a c t i s a $0. 0 7 m i l l i o n o v ere s t i m a t i on of

n a ti o n a l co sts ( l e s s th a n 0

. 5 % o f to ta l n a ti o n a l co sts )



### 6.3 R esult s

This section presents the results of the national cost analy s is. Unless otherwise specified,
national costs are presented in May 1999 dollars throug hout this chapter.

6.3.1 N at ional C o st s

Ex hibit 6-10 shows the total national cost breakdown across the four MCL options for the

Arsenic Rule. The sy stem and state cost components of the total annual compliance costs are

Chapter 6, Cost Analysis 6-27 Arsenic in Drinking Water Rule EA

### presented at discount rates of three and seven percent. Ex pected sy stem costs include treatment

c o sts, monitor i ng c o sts, a nd a d ministr a tive c o sts of c o mplia nc e

. Sta t e c o sts inc l ude monitor i ng and administrative costs of implementation. These cost components are also display e d.

CW S costs are approx imately $668.0 million at the 3 μg /L MCL

, $396.0 million at the 5 μg /L

MCL

, $171.4 million at the 10 μg /L MCL

, and $62.4 million at the 20 μg /L MCL (at a three
percent discount rate). State costs associated with CW S administration, at a three percent
discount rate, are approx imately $1.4 million at the 3 μg /L MCL

, $1.1 million at the 5 μg /L

MCL

, $0.9 million at the 10 μg /L MCL

, and $0.7 million at the 20 μg /L MCL

.

The cost to NTNCs rang es from $28 million at the 3 μg /L MCL

, $16 million at the 5 μg /L MCL

, $7.9 million at the 10 μg /L MCL

, and $3.5 million at the 20 μg /L MCL (at a three percent
discount rate). State costs associated with NTNC administration, at a three percent discount rate,

are approx imately $0.1 million for each MCL

.

Exhi bi t 6- 10

A nnual Nat i onal Sy st em and St at e Compl i a nce Cost s ($ millio n s )

Di s c o u n t Ra t e 3% 7% 3% 7% 3% 7%

Syst e m C o st s

T r eat m ent $665. 9 $756. 5 $27. 2 $29. 6 $693. 1 $786. 0

M o n i to r i n g /

Ad m i n i str a ti v e $2. 2 $3. 0 $1. 0 $1. 4 $3. 2 $4. 4

S t at e C o s t s $1. 4 $1. 6 $0. 1 $0. 2 $1. 5 $1. 7

TO TA L C O S T $669. 4 $761. 0 $28. 3 $31. 1 $697. 8 $792. 1

Syst e m C o st s

T r eat m ent $394. 4 $448. 5 $16. 3 $17. 6 $410. 6 $466. 1

M o n i to r i n g /

Ad m i n i str a ti v e $2. 0 $2. 8 $1. 0 $1. 3 $2. 9 $4. 1

S t at e C o s t s $1. 1 $1. 3 $0. 1 $0. 2 $1. 2 $1. 4

TO TA L C O S T $397. 5 $452. 5 $17. 3 $19. 1 $414. 8 $471. 7

Syst e m C o st s

T r eat m ent $169. 6 $193. 0 $7. 0 $7. 6 $176. 7 $200. 6

M o n i to r i n g /

Ad m i n i str a ti v e $1. 8 $2. 5 $0. 9 $1. 3 $2. 7 $3. 8

S t at e C o s t s $0. 9 $1. 0 $0. 1 $0. 2 $1. 0 $1. 2

TO TA L C O S T $172. 3 $196. 6 $8. 1 $9. 1 $180. 4 $205. 6

Syst e m C o st s

T r eat m ent $60. 7 $69. 0 $2. 6 $2. 8 $63. 3 $71. 8

M o n i to r i n g /

Ad m i n i str a ti v e $1. 7 $2. 4 $0. 9 $1. 3 $2. 6 $3. 7

S t at e C o s t s $0. 7 $0. 8 $0. 1 $0. 2 $0. 9 $1. 0

TO TA L C O S T $63. 2 $72. 3 $3. 6 $4. 2 $66. 8 $76. 5 NT NC CW S

M C L = 10 μ g/ L

M C L = 20 μ g/ L TO TA L

MC L = 3 μ g/ L

MC L = 5 μ g/ L

Chapter 6, Cost Analysis 6-28 Arsenic in Drinking Water Rule EA

### 6.3.2 C osts by Sy stem Size and Ty pe

Thi s sect i on present s t h e overal l nat i onal com p l i a nce cost s for wat e r sy st em s and for st at es at three and seven percent discount rates. Ex hibit 6-11 shows a detailed breakout of national
treatment costs by CW S siz e categ ory for the various MCL s

.

Ex hibits 6-12 throug h 6-15 show the national treatment costs for NTNC sy stems by NTNC

sy st em servi ce t ype for each MC L

.

Exhi bi t 6- 11

T o t a l A nnual CWS T r eat ment Cost s A c ross M C L O p t i ons

b y S y s t e m S i ze ($ millio n s )

S y s t e m S ize MC L ( μ g/ L)

3 5 10 20

3 % D i s c o unt R a t e

< 1 00 $ 19

. 8 1 2 .3 $ $ 5

. 5 $ 2

. 1

10 1-50 0 $ 4 2

. 6 2 5 .7 $ $ 1 1 .5 $ 4

. 3

50 1-1, 0 0 0 $ 2 5

. 5 1 5 .2 $ $ 6

. 7 $ 2

. 5

10 01

- 3 30 0 $ 8 3

. 8 5 0 .5 $ $ 2 2 .0 $ 8

. 1

3, 3 01-1 0

, 0 0 0 $ 95

. 1 5 5 .9 $ $ 2 4 .3 $ 9

. 0

10

, 001 -50, 0 0 0 $ 1 7 9

. 1 1 0 8

. 7 $ $ 4 7 .0 $ 1 6 .7

50

, 001 -100

, 000 $ 66

. 0 3 9 .0 $ $ 1 6 .7 $ 6

. 2

10 0, 00 1-1, 0 00, 0 0 0 $ 1 2 4

. 3 7 5 .2 $ $ 3 2 .3 $ 1 1 .3

> 1

, 0 00

, 000 $ 29

. 7 1 1 .8 $ $ 3

. 8 $ 0

. 6

T

o ta l $ 6 6 5 .9 3 9 4

. 4 $ $ 1 6 9

. 6 $ 6 0 .7

7 % D i s c o unt R a t e

< 1 00 $ 21

. 3 1 3 .2 $ $ 5

. 9 $ 2

. 3

10 1-50 0 $ 4 6

. 4 2 8 .0 $ $ 1 2 .5 $ 4

. 6

50 1-1, 0 0 0 $ 2 8

. 9 1 7 .2 $ $ 7

. 6 $ 2

. 8

10 01

- 3 30 0 $ 9 7

. 4 5 8 .8 $ $ 2 5 .6 $ 9

. 4

3, 3 01-1 0

, 0 0 0 $ 10 9. 2 6 4 .2 $ $ 2 7 .9 $ 1 0 .3

10

, 001 -50, 0 0 0 $ 2 0 5

. 4 1 2 4

. 7 $ $ 5 3 .9 $ 1 9 .2

50

, 001 -100

, 000 $ 75

. 0 4 4 .3 $ $ 1 9 .0 $ 7

. 0

10 0, 00 1-1, 0 00, 0 0 0 $ 1 4 0

. 5 8 5 .0 $ $ 3 6 .5 $ 1 2 .7

> 1

, 0 00

, 000 $ 32

. 5 1 3 .0 $ $ 4

. 3 $ 0

. 6

T

o ta l $ 7 5 6 .5 4 4 8

. 5 $ $ 1 9 3

. 0 $ 6 9 .0

Chapter 6, Cost Analysis 6-29 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 12

T o t a l A nnual NT NC T r eat ment Cost s at M C L 3 μg/ L by Sy st em Serv i ce T y pe ( 3 % Di scount Rat e )

S e r v i c e A r e a Ty pe # o f S y s t e m s

A

b o

v

e t h e M C L A v

er a g e

P opul a t i on

Se r v

e d Pe r Sy s t e m A v

e r a g e A nnua l

S y st

e m C o st A nnua l

Na t i o n a l Co s t s

D

a

y c a r e

C

e n t e r s

H i g h w a

y R e

s t A r e a

s

H o

t e l s / M o t e l s

I n t e r s t a t e

C

a r r i e r s

M e d i c a l F a c ilit i e s

Mob i l e H o me P a rk s

R

e s t a u ran t s

S c ho ol s

S e r v i c e S t a t i o n s

S u m m e r C

a m p s

W a t e r

W h ol es al e r s

A g r i c u l t u r a l P r od uc t s / S er v i c e s

A i r p ark s

C

o n s t r u c t i on

C h u r c h e s

C

a mp grou nd s / R V

P a r k s

F i re D e pa r t men t s

F e

deral P a rk s

F o r e

s t S e r v i c e

G o l f a n d C

o u n t r y

C l ub s

L

a n d f i l l s

M i n i ng

A m us eme n t P a rk s

M ilit a r y

B a s e s

Mi gran t La bo r C

a mp s

Mi s c

. R e c r e a

t i on S e rv i c e s

N u rs i n g H o mes

Of

f i c e P a r k s

P r i s on s

R

e

t a i l e rs (N o n -f oo

d r

e l a t ed)

R

e

t a i l e rs (F oo d r

e l a t ed)

S t a t e

P a rk s

N o n

- W a t e r

U

t ilit ie s

Man u f a

c t uri n g : F o od

Man u f a

c t uri n g : N o n

- Food

T O TA L 1 5 9

3

6 9

5 7

7

2

2 0

8 2

1

, 6 57

1 0

9

5 2

7

2

20

19

45

2 4

8

4

2 1

2 3

1 5

2 3

3 1

1 9

6

51

2 6

1 87

1 3

13

7

28

1 6

9 8

15 1

75 7

3

, 9 8 8 76

4 0

7

1 3

3

1 2 3

3 9 3

1 8

5

3 7

0

3 5 8

2 3

0

1 4

6

1 7

3

7 6

60

53

50

1 6 0

98

39

4

2

1 0 1

4

4

1 1 3

4 1 8

3 9

5

63

87

1 0

7

1 3

6

1

, 8 2 0

1 7

4

32

2

1 6

5

1 7

0

3 7

2

1 6 8 $5

, 2 17

$ 5, 46 6

$6

, 1 53

$ 5, 07 4

$ 1 3

, 5 4 0

$6

, 6 66

$5

, 1 40

$ 7, 17 7
$ 5, 21 7
$ 6, 35 3

$1 6, 45 6

$ 6, 22 1

$5

, 0 59

$4

, 7 33

$5

, 2 29

$6

, 3 29

$6

, 1 32

$5

, 3 09

$

4, 78 3

$5

, 6 61

$ 5, 22 6

$ 5, 69 7
$6

, 0 25
$ 9

, 8 8 3

$5

, 5 54

$5

, 0 50

$7

, 7 48

$ 5, 38 6

$4

5, 86 1

$5

, 1 33

$ 5

, 2 6 1

$5

, 1 99

$ 5

, 7 6 3

$8

, 0 66

$5

, 9 44 $8 31

, 0 99

$ 16

, 1 44

$4

25

, 2 52

$

28 6, 72 3

$ 9 7 8

, 4 5 2

$1 36

, 4 96

$4

23

, 0 58

$ 11

, 8 90

, 9 22

$ 54

, 4 45

$ 57

, 5 38

$ 8 6 1

, 9 0 7

$

45 0, 73 4

$1 00

, 6 00

$9

2, 25 8

$2 36

, 7 89

$1 53

, 2 87

$4

9, 50 5
$2 0, 90 8

$ 10 0, 77 1

$1 29

, 3 08

$ 80

, 2 68

$ 13 3, 49 0

$1 88

, 6 25
$ 1 8 4

, 8 6 3

$3

6, 09 0

$2 57

, 5 31

$1 98

, 3 16

$ 1, 00 7, 45 6

$ 6 0 5

, 0 1 2

$7

02

, 3 66

$ 1 4 7

, 1 0 1

$8

4, 96 6

$ 5 6 3

, 9 7 0

$1

, 2 19

, 7 53

$4

, 5 00

, 2 32

$2

7, 20 6, 23 5

Chapter 6, Cost Analysis 6-30 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 13

T o t a l A nnual NT NC T r eat ment Cost s at M C L 5 μg/ L by Sy st em Serv i ce T y pe ( 3 % Di scount Rat e )

S e r v i c e A r e a Ty pe # o f S y s t e m s

A

b o

v

e t h e M C L A v

er a g e

P opul a t i on

Se r v

e d Pe r Sy s t e m A v

e r a g e A nnua l

S y st

e m C o st A nnua l

Na t i o n a l Co s t s

D

a

y c ar e C e nt er s

H i g h w a

y R e

s t A r e a

s

H o

t e l s / M o t e l s

I n t e r s t a t e

C

a r r i e r s

M e d i c a l F a c ilit i e s

Mob i l e H o me P a rk s

R

e s t a u ran t s

S c ho ol s

S e rv i c e S t at i ons

S u m m e r C

a m p s

W a t e r

W h ol es al e r s

A g r i c u l t u r a l P r od uc t s / S er v i c e s

A i r p ark s

C

o n s t r u c t i on

C h u r c h e s

C

a mp grou nd s / R V

P a r k s

F i re D e pa r t men t s

F e

deral P a rk s

F o r e

s t S e r v i c e

G o l f a n d C

o u n t r y

C l ub s

La nd f i l l s

M i n i ng

A m us eme n t P a rk s

M ilit a r y

B a s e s

Mi gran t La bo r C

a mp s

Mi s c

. R e c r e a

t i on S e rv i c e s

N u rs i n g H o mes

Of

f i c e P a r k s

P r i s on s

R

e

t a i l e r s ( N on

- f o o

d

r

e l a t e d )

R

e

t a i l e rs (F oo d r

e l a t ed)

S t a t e

P a rk s

N o n

- W a t e r

U

t ilit ie s

M a nu f a

c t u r i n g: F o o d

Man u f a

c t uri n g : N o n

- Food

T O TA L 9 7

2

4

2

3

4

4

4

1 2

5 0

1

, 0 09

6

6

3

2

4

4

12

12

28

1 5

5

2

1 3

1 4

9

1 4

1 9

1 1

4

31

1 6

1 14

8

8 3

17

1 0

6 0

9 2

46 1

2

, 4 2

9 7 6

4 0

7

1 3

3

1 2 3

3 9 3

1 8

5

3 7

0

3 5 8

2 3

0

1 4

6

1 7

3

7 6

60

53

50

1 6 0

98

39

4

2

1 0 1

44

1 1 3

4 1 8

3 9

5

63

87

1 0

7

1 3

6

1, 82 0

1 7

4

32

2

1 6

5

1 7

0

3 7

2

1 6 8 $ 5, 19 6

$ 5, 42 8

$6

, 0 69

$ 5, 06 2

$ 1 2

, 9 5 9

$6

, 5 47

$5

, 1 24

$ 7, 02 4

$5

, 1 96

$ 6, 25 5
$1 5, 67 9

$ 6, 13 2

$5

, 0 48

$4

, 7 33

$5

, 2 07

$6

, 2 33

$6

, 0 50

$5

, 2 82

$

4, 78 3

$5

, 6 10

$5

, 2 05

$ 5, 64 4

$5

, 9 50
$ 9

, 5 4 8

$5

, 5 11

$5

, 0 40

$7

, 5 56

$ 5, 35 4

$

4

3

, 1 0 4

$ 5, 11 7
$ 5

, 2 3 7
$5

, 1 79

$ 5

, 7 0 5
$ 7, 85 3

$5

, 8 74 $ 50 4, 05 1

$ 9, 76 3

$2 55

, 4 18

$ 17 4, 20 7
$ 5 7 0

, 2 4

2

$8 1, 64 0

$2 56

, 8 24

$ 7, 08 6, 56 4

$3

3, 02 0

$ 34

, 5 00

$ 5 0 0

, 0 5 2

$

27 0, 56 3

$6 1, 13 4

$5 6, 18 0

$1 43

, 5 90

$9 1, 92 9

$2 9, 74 0

$1 2, 66 7
$ 61

, 3 64

$7

8, 03 3

$4

8, 67 6

$ 80

, 5 27

$1 13

, 4 24
$ 1 0 8

, 7 5 4

$2 1, 80 4

$1 56

, 5 19

$1 17

, 7 80

$ 60 9, 79 5
$3

46

, 2 70

$

42 6, 42 4

$ 8 9

, 1 6 8

$5 1, 54 2

$ 3

3 9

, 9 8 3

$ 72 3, 16 5
$2

, 7 08

, 1 31

$1 6, 25 3, 44 2

Chapter 6, Cost Analysis 6-31 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 14

T o t a l A nnual NT NC T r eat ment Cost s at M C L 10 μg/ L by Sy st em Serv i ce T y pe ( 3 % Di scount Rat e )

S e r v i c e A r e a Ty pe # o f S y s t e m s

A

b o

v

e t h e M C L A v

er a g e

P opul a t i on

Se r v

e d Pe r Sy s t e m A v

e r a g e A nnua l

S y st

e m C o st A nnua l

Na t i o n a l Co s t s

D

a

y c ar e C e nt er s

H i g h w a

y R e

s t A r e a

s

H o

t e l s / M o t e l s

I n te r s ta te

C

a r r i e r s

M e d i c a l F a c ilit i e s

M o bi l e H o m e P a r k s

R

e s t a u ran t s

S c ho ol s

S e rv i c e S t at i ons

S u m m e r C

a m p s

W a t e r

W h ol es al e r s

A g r i c u l t u r a l P r od uc t s / S er v i c e s

A i r p a r k s

C

o ns t r uc t i o n

C h u r c h e s

C

a mp grou nd s / R V

P a r k s

F i re D e pa r t men t s

F e

deral P a rk s

F o r e

s t S e rv i c e

Gol f an d C o un t r y

C l u b s

La nd f i l l s

Mi ni n g

A m u s e m en t P a r k s

M ilit a r y

B a s e s

Mi gran t La bo r C

a mp s

Mi s c

. R e c r e a

t i on S e rv i c e s

N u r s i n g H o m e s

O

f f i c e P a r k s

P r i s on s

R

e

t a i l e r s ( N on

- f o o

d

r

e l a t e d )

R

e

t a i l e rs (F oo d r

e l a t ed)

S t at e P a r k s

N o n

- W a t e r

U

t ilit ie s

M a nu f a

c t u r i n g: F o o d

Man u f a

c t uri n g : N o n

- Food

T O TA L 4 3

1

1 9

1 5

2 0

6

2 2

4

48

3

2

1 4

2 0

5

5

12

7

2

1

6

6

4

6

8

5

2

14

7

5 1

4

3 7

8

4

2 6

4 1

20

5

1

, 0 8 0 7 6

4 0

7

1 3

3

1 2 3

3 9 3

1 8

5

3 7

0

3 5 8

2 3

0

1 4

6

1 7

3

7 6

6 0

5 3

50

16 0

98

39

42

1 0 1

44

1 1 3

4 1 8

3 9

5

63

87

1 0

7

1 3

6

1, 82 0

1 7

4

3

2

2

1 6

5

1 7

0

3 7

2

1 6 8 $ 5, 16 8

$ 5, 37 7
$5

, 9 56

$ 5

, 0 4 7
$ 1 2

, 1 7 4

$ 6, 38 7
$5

, 1 03

$ 6, 81 8

$5

, 1 68

$ 6, 12 4

$1 4, 62 8

$ 6, 01 2

$ 5, 03 4

$

4, 73 3

$5

, 1 77
$ 6

, 1 0 4

$5

, 9 38

$5

, 2 45

$4

, 7 83

$ 5, 54 2

$5

, 1 76

$5

, 5 72

$ 5, 84 8
$ 9

, 0 9 5
$5

, 4 52

$5

, 0 27

$ 7, 29 8

$5

, 3 10

$ 3 9

, 3 8 0

$ 5, 09 7
$5

, 2 05

$ 5, 15 3

$ 5

, 6 2 7
$ 7, 56 6

$5

, 7 80 $ 22 2, 84 6

$

4, 29 9

$1 11

, 4 20

$ 7

7 ,2 0 7
$

2 3 8

, 1 3 3

$ 35

, 4 05

$1 13

, 6 92

$ 3, 05 7, 57 8

$1 4, 59 9

$ 15

, 0 14

$

2 0 7

, 3 9 8

$ 11 7, 93 0

$

27

, 1 01

$

24

, 9 74

$6

3, 47 1

$

4

0

, 0 1 7
$1 2, 97 7
$5

, 5 92

$2 7, 27 8

$ 34

, 2 63

$2 1, 51 7
$3

5, 34 0

$

49

, 5 58
$

4

6

, 0 5 3

$9

, 5 89

$6 9, 39 7
$ 50

, 5 67

$2 68

, 8 64

$1 40

, 6 29

$ 18 8, 79 6

$3 9, 39 4

$

22

, 7 94

$ 1 4 9

, 0 6 9

$ 30 9, 70 7
$1

, 1 84

, 5 05

$7

, 0 36

, 9 73

Chapter 6, Cost Analysis 6-32 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 15

T o t a l A nnual NT NC T r eat ment Cost s at M C L 20 μg/ L by Sy st em Serv i ce T y pe ( 3 % Di scount Rat e )

S e r v i c e A r ea T y p e # o

f S y st

e m s

A

bov e t h e M C L A v

er ag e

P opul a t i on

Se r v

e d

Pe r Sy s t e m A v

e r a g e A nnua l

S y st

e m C o st A nnua l

Na t i o n a l Co s t s

D

a

y c a r e

C

e nt er s

H i g h w ay R e

s t A r ea

s

H o

t e l s / M o t e l s

I n t e rs t a t e

C

a r r i e rs

M e d i c a l F a c ilit ie s

M o bi l e H o m e P a r k s

R

e s t au r a n t s

S c ho o l s

S e rv i c e S t a t i o ns

S u m m e r C

a m p s

W a t e r

W h o l es al ers

A g ri c u l t ural P r od uc t s / S erv i c e s

A i r p a r k s

C

o ns t r uc t i on

C h ur c h e s

C

a mp groun ds / R V

P a rk s

F i re D e part m ent s

F e

deral P a r k s

F o r e s t S e rv i c e

Gol f an d C

o un t r y C l u b s

La nd f i l l s

Mi ni n g

A m us emen t P a rk s

M ilit a r y

B a s e s

Mi gran t La bo r C

a mps

M i s c

. R e c r e a

t i on S e r v i c e s

N u r s i n g H o m e s

O

f f i c e P a r k s

P r i s ons

R

e

t a i l e r s ( N on

- f oo d r e l a t e

d )

R

e

t a i l e rs ( F o o d rel a t e

d)

S t at e P a r k s

N o n

- W a t e r

U

t ilit ie s

M a nu f a

c t u r i n g : F o od

M a nu f a

c t u r i n g : N o n- F o o d

T O T

A

L 1 6

0

7

6

7

2

8

1 69

1

1

5

7

2

2

5

2

1

0

2

2

2

2

3

2

1

5

3

1 9

1

1 4

3

2

1 0

1 5

7 7

4

0

7 7 6

4 0

7

1 3

3

1 2 3

3 9 3

1 8

5

3 7

0

3 5 8

2 3

0

1 4

6

17

3

76

6 0

5 3

5 0

16 0

98

39

42

1 0 1

44

1 1 3

41 8

3 9

5

63

8 7

1 0

7

1 3

6

1

, 8 2 0

1 7

4

3

2

2

1 6

5

1 7

0

3 7

2

1 6 8 $ 5, 13 5
$ 5, 31 8
$ 5, 82 3

$5

, 0 29

$ 1 1

, 2 5 9

$ 6, 20 1

$ 5, 07 8

$ 6, 57 7
$5

, 1 35

$ 5, 97 0

$ 1 4

, 0 2 5

$5

, 8 73

$ 5, 01 8

$

4, 73 3

$ 5, 14 3
$ 5

, 9 5 3

$5

, 8 08

$5

, 2 03

$4

, 7 83

$ 5, 46 2

$5

, 1 42
$5

, 4 88

$ 5

, 7 2 9

$ 8

, 5 6 8

$5

, 3 83

$ 5, 01 2

$ 6, 99 7
$5

, 2 59
$3

5, 04 1

$ 5, 07 3

$5

, 1 67

$ 5, 12 1

$ 5

, 5 3 6

$ 7, 23 1
$ 5, 67 0 $ 83

, 5 00

$ 1, 60 3
$

41

, 0 85

$2 9, 01 3

$ 8

3

, 0 5 4

$ 12

, 9 62

$

42

, 6 66

$ 1, 11 2, 33 6
$5

, 4 70

$ 5, 52 0

$7

4, 98 6

$4

3, 44 2

$ 10

, 1 87

$ 9, 41 8

$

23

, 7 77
$ 1 4

, 7 1 8

$4

, 7 86

$2

, 0 91

$1 0, 28 7
$ 12

, 7 34

$8

, 0 61
$1 3, 12 7
$ 1 8

, 3 1 0

$ 1 6

, 3 6 0

$3

, 5 70

$

26

, 0 91

$ 18

, 2 82

$1 00

, 4 20
$

4

7

, 1 8 9

$ 70

, 8 61

$1 4, 74 8

$ 8, 54 4

$ 5

5

, 3 0 8

$ 11 1, 62 5
$

43 8, 18 4

$2

, 5 74

, 3 15

Chapter 6, Cost Analysis 6-33 Arsenic in Drinking Water Rule EA

### 6.3.3 C osts per Household

Household level costs are considered a g ood prox y for the affordability of rule compliance with

reg a rd to CW Ss, since water sy stems recover costs at the household level throug h increased

water rates. This of course assumes that non-residential customers of water sy stems, such as

busi n esses, can pass al ong any i n crease i n wat e r cost s t o t h ei r cust om ers t h roug h i n creased pri ces on their g oods or services. I n order to calculate the number of households served by sy stems that

will tr e a t , the e x pe c t e d numbe r of tr e a ting sy ste m s is multiplie d by the a v e r a g e numbe r of
households per sy stem (varies by sy stem ty pe and siz e ). Ex hibit 6-16 presents the total number
of households served by CW Ss that treat, by siz e categ ory

.

Exhi bi t 6- 16

Number of Househol ds i n CWSs Expect ed t o T r eat by Si ze Cat e gory and M C L ( μ g/ L) O p t i on

< 1 00 10 1- 500 50 1- 1, 000 1, 00 1­

3, 30 0 3, 30 1­

10

, 0 00 10

, 0 01­

50

, 0 00 50

, 0 01­

10 0, 000 10 0, 001

­ 1, 00 0, 000 To t a l

3 94

, 4 84 36 8, 092 36 0, 709 1, 00 2, 937 1, 61 9, 822 3, 22 8, 544 1, 45 3, 603 3, 01 4, 841 11

, 1 43, 03 2

5 58

, 7 74 22 8, 149 21 9, 872 62 3, 156 1, 01 9, 288 2, 07 7, 421 90 5, 886 1, 93 8, 268 7, 07 0, 814

10 26

, 3 69 10 4, 373 10 1, 866 28 8, 986 47 5, 599 99 7, 880 46 9, 157 93 6, 602 3, 40 0, 833

20 10

, 4 39 40

, 0 89 40

, 4 98 11 6, 517 19 3, 541 40 5, 714 18 8, 798 36 4, 907 1, 36 0, 503



### S a feW a terXL determines household costs separately for each affected CW S

, by first dividing the

CW S’s annual compliance cost by the CW S’s averag e daily flow (1,000 g a llons per day ) , and
then multiplied by 365 day s to determine the CW S’s cost of compliance per 1,000 g a llons
produced. F i nally , the CW S’s cost of compliance per 1,000 g a llons (kg a l) is multiplied by the

averag e annual consumption per residential connection (kg a l), to arrive at the averag e annual cost
of compliance per household for the CW S. The estimates of averag e annual consumption per
residential connection used in this analy s is are provided in Chapter 4, “B aseline Analy s is.”

Given ex pected household costs for each individual sy stem, the averag e is then calculated for

each siz e categ ory

. Ex hibit 6-17 shows the averag e annual household costs by sy stem siz e

, across the four reg u latory options.

The rang e of household costs for the MCL of 10 μg /L rang es from less than $1 to approx imately
$327; the costs for the MCL of 3 μg /L rang e from less than $7 to $317; the costs for the MCL of
5 μg /L , rang e from less than $3 to $318; and the costs for the MCL of 20 μg /L rang e from less

than $1 to $351.

I n the smallest two siz e categ ories, averag e household costs decrease as the MCL decreases. This somewhat counterintuitive result is due to the $500.00 affordability cap assumed in the

Sa f e Wa te r XL simula tions. As mor e sy ste m s a r e f o r c e d ove r the a f f

o r d a b ility c a p, the sy ste m s’

costs are fix e d at the costs associated with the POU technolog y

. This results in lower averag e household costs for these sy stems.

Chapter 6, Cost Analysis 6-34 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 17

A

v erage A nnual Househol d Cost s A c ross M C L O p t i ons by Sy st em Si ze

MC L ( μ g/ L)
Sy s t e m S i z e

3 5 10 20

<1 0 0 $3 17

. 0 0 $ 3 1 8

. 26 $3 26

. 8 2 $ 3 5 1

. 15

10 1-5 0 0 $1 66

. 9 1 $ 1 6 4

. 02 $1 62

. 5 0 $ 1 6 6

. 72

50 1-1

, 000 $7 4. 8 1 $7 3. 1 1 $7 0. 7 2 $6 8. 2 4

1, 0 0 1

- 3, 30 0 $6 3. 7 6 $6 1. 9 4 $5 8. 2 4 $5 4. 3 6

3

, 30 1- 1 0

, 00 0 $4 2. 8 4 $4 0. 1 8 $3 7. 7 1 $3 4. 6 3

1 0

, 0 01

- 5 0, 0 0 0 $3 8. 4 0 $3 6. 0 7 $3 2. 3 7 $2 9. 0 5

5 0

, 0 01

- 1 00

, 0 0 0 $3 1. 6 3 $2 9. 4 5 $2 4. 8 1 $2 2. 6 3

10 0, 0 01-1

, 00 0, 00 0 $2 5. 2 9 $2 3. 3 4 $2 0. 5 2 $1 9. 2 6

> 1

, 0 00

, 0 00 $7

. 4 1 $ 2

. 79 $0

. 8 6 $ 0

. 15

A ll c a t e g o r ie s $4 1. 3 4 $3 6. 9 5 $3 1. 8 5 $2 3. 9 5



### Ex hibits 6-18 throug h 6-21 compare the distribution of annual household costs across public

water sy stems serving fewer than 10,000 people, for MCL s of 3, 5, 10, and 20, respectively

. The

ex hibits demonstrate the max imum annual costs that different percentag e s of households in
treating sy stems face. Comparison of Ex hibits 6-18 throug h 6-21 illustrates that reg u latory
compliance costs decrease across MCL s

. This observation is depicted by the consistent shift to

t h e l e ft of cost curves across sy st em si z e cat eg ori e s, when com p ari n g i n crem ent a l i n creases i n t h e

MCL

.

Chapter 6, Cost Analysis 6-35 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 18

A nnual T r eat ment Cost s Per Househol d A c ross CWSs
Expect ed t o T r eat and Serv i ng < 10, 000 Peopl e
MC L 3 μg /L

$0 $1 00 $2 00 $3 00 $4 00 $5 00 $6 00

M a x i m u m A n n u al H o u seh o l d T r eat m e n t C o st s



### Exhi bi t 6- 19

A nnual T r eat ment Cost s Per Househol d A c ross CWSs
Expect ed t o T r eat and Serv i ng < 10, 000 Peopl e
MC L 5 μg /L 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 10 0%Percentage of Households

0- 10 0

10 1- 500

50 1- 1, 00 0

1, 0 01- 3, 3 0 0

3, 3 01- 10

, 000

10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 10 0%Percentage of Households

0- 1 0 0

10 1- 5 0 0

50 1- 1

, 00 0

1, 001

- 3, 3 0 0

3, 301

- 10

, 0 0 0

$0 $1 00 $2 00 $3 00 $4 00 $5 00 $6 00

Max i m u m A n n u al H o u seh o l d T r eat m e n t C o s t s

Chapter 6, Cost Analysis 6-36 Arsenic in Drinking Water Rule EA

### Exhi bi t 6- 20

A nnual T r eat ment Cost s Per Househol d A c ross CWSs
Expect ed t o T r eat and Serv i ng < 10, 000 Peopl e

M C L 10 μg/ L

$0 $1 00 $2 00 $3 00 $4 00 $5 00 $6 00

M a x i mu m A n n u a l H o u s e h o l d T r e a t me n t C o s t s



### Exhi bi t 6- 21

A nnual T r eat ment Cost s Per Househol d A c ross CWSs
Expect ed t o T r eat and Serv i ng < 10, 000 Peopl e

M C L 20 μg/ L

$0 $1 00 $2 00 $3 00 $4 00 $5 00 $6 00

M a x i m u m A n n u al H o u seh ol d T r ea t m en t C o s t s 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 10 0%Percentage of Households

0- 10 0

10 1- 500

50 1- 1,00 0

1, 001

- 3

, 300

3, 301

- 1 0

, 00 0

10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 10 0%Percentage of Households

0- 1 0 0

10 1- 50 0

50 1- 1,0 0 0

1,0 01- 3

, 30 0

3,3 01- 1 0 ,0 00

Chapter 6, Cost Analysis 6-37 Arsenic in Drinking Water Rule EA

### 6.4 N at ional C o mpliance C o st s U n cert a int y A n aly s is

The national cost estimates discussed throug hout this chapter were developed within the

SafeW a terXL modeling framework so that EPA could fully describe the variation in compliance

cost s am ong sy st em s i n a si ng l e si z e cat eg ory (rat h er t h an j u st t h e averag e cost for sy st em s wi t h i n
a si z e cat eg ory )

. Hence, for each C W S si z e cat eg ory

, a di st ri but i on of com p l i a nce cost s was
estimated. These distributions are now used to access the uncertainty inherent in the national

c o st e s tima te s.

A parametric bootstrap model was developed to estimate the distribution of national compliance

costs. 3 

### The following steps were followed:

1. The di st ri but i on of cost s for each C W S si z e and ownershi p cl ust e r was pul l e d

f r o m the Sa f e Wa te r X L mode l r e sults f o r

a n MCL of 10 μg /L

.

2. The num ber of C W S s ex pect ed t o m odi fy or i n st al l t r eat m e nt i n each C W S si z e and ownership cluster was pulled from the SafeW a terXL model results for an

MCL of 10 μg /L

.

3. For each C W S si z e and ownershi p cl ust e r, t h e m odel pul l e d a num ber of

observations from the distribution of costs associated with that CW S siz e and

ownershi p cl ust e r (from st ep 1). The num ber of observat i ons pul l e d was equal t o

t h e num ber of C W S s ex pect ed t o m odi fy or i n st al l t r eat m e nt i n each C W S si z e
and ownershi p cl ust e r (from st ep 2).

4. The observat i ons (from st ep 3) were sum m e d across al l C W S si z e and ownershi p

c l uste r s to c a l c u la te a sing le e s tima te of na tiona l c o sts f o r

CWSs.

5. No cost distributions are available for the NTNC sy stems and the very larg e

CW Ss. Therefore, after each sing le estimate of national costs for CW Ss (from

st ep 4) was cal cul a t e d, t h e m ean cost s for very l a rg e C W S s and NTNC sy st em s

we r e a dde d to it to c a l c u la te a sing le tota l na tiona l c o st e s tima te

.

6. Steps 3 throug h 5 were repeated 3,000 times to calculate a distribution of total

national costs.

The distribution of total national costs is shown in Ex hibit 6-22. The simulated mean national
costs is $199 million, and the simulated standard deviation is $19 million. Also, the cumulative

distribution of total national costs is shown in Ex hibit 6-23. As this ex hibit shows, the 10 th 

### and

90 th 

### percentile confidence interval for total national costs are $190 million and $227 million

respect i v el y

.

3 O n ly treatm e nt cos t s were included in the uncertainty analy s is

. A l s o, the uncertainty analy s is was
conducted assum i ng a com m e rcial discount rate. Althoug h this com m e rcial discount rate v a ries by CWS size and

ow nership, it approxim a tes f i v e percent f o r all PWSs.

Chapter 6, Cost Analysis 6-38 Arsenic in Drinking Water Rule EA������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������������������������� ���������������������������������������������������������������������������

��������������������������������������������������������������������������� ���������������������������������������������������������������������������

���������������������������������������������������������������������������

��������������������������������������������������������������������������� ���������������������������������������������������������������������������

��������������������������������������������������������������������������� ��������������������������������������������������������������������������� ��������������������������������������������������������������������������� ��������������������������������������������������������������������������� ��������������������������������������������������������������������������� ���������������������������������������������������������������������������

$150 $155 $160 $165 $170 $175 $180 $185 $190 $195 $200 $205 $210 $215 $220 $225 $230 $235 $240 $245 $250 $255 $260 $265 $270 $275 

### Exhi bi t 6- 22

Nat i onal Compl i a nce Cost s Uncert a i n t y A n al y s i s Frequency Di st ri but i on ( M CL 10 μg/ L )

16

. 0 %

14

. 0 %

12

. 0 %

10

. 0 %

8. 0%

6. 0%

4. 0%

2. 0%

0. 0% �������������������������������������������������������������������������������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������������������������������������������������������������������������������

�������������������������������������������������������������������������������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������������������������������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������������������������� S i m u l a t

ed M E A N = $1 99, 166, 4 6 3

S i m u l a t

ed S T A N D A R D D E V I A T I O N $19 362, 659 = , M EANFrequency

Na tio n a l C o m p lia n c e C o s t s ($ M illio n s )

Chapter 6, Cost Analysis 6-39 Arsenic in Drinking Water Rule EA������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� �������������������������������������������������������������������������������������������������������������������������������

$150 $155 $160 $165 $170 $175 $180 $185 $190 $195 $200 $205 $210 $215 $220 $225 $230 $235 $240 $245 $250 $255 $260 $265 $270 $275Cumulative Probability 

### Exhi bi t 6- 23

Nat i onal Compl i a nce Cost s Uncert a i n t y A n al y s i s
Cumul a t i v e Di st ri but i on ( M C L 10 μg/ L )

100

. 00%

90. 0 0 %

80. 0 0 %

70. 0 0 %

60. 0 0 %

50. 0 0 %

40. 0 0 %

30. 0 0 %

20. 0 0 %

10. 0 0 %

. 00% �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� ��������������������������������������������������������

������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� ������������������������������������������������������������������������������������������������������������������������������� �������������������������������������������������������� Si m u l a t ed M EAN = $199, 166, 463

Si m u l a t ed S T AN D A R D D E VI ATI O N = $1 9, 362, 659 ME A N

N a t i on al C o m p lian c e C o st s ( $ M illion s )

Chapter 6, Cost Analysis 6-40 Arsenic in Drinking Water Rule EA

## Chapter 7: Comparison of Costs and Benefits

7.1 I ntroduction

I n this EA, EPA has analy z ed the costs and benefits of reg u lating arsenic concentrations in
drinking water to four different MCL standards. The four options considered reflect increasing
levels of protection ag ainst ex posure to arsenic in drinking water, employ ing a rang e of MCL s from 20 μg /L to 3 μg /L . As the MCL provisions for the four options become increasing l y strict,

t h e associ at ed cost s and benefi t s al so i n crease i n crem ent a l l y . C h apt e r 5 (“Benefi t s Anal y s i s ”)

de sc r i be s in de ta il the e s tima te d na tiona l he a lth be ne f its of the Ar se nic Rule options, while

Cha p te r 6 ( “ Cost Ana l y s is” ) de sc r i be s the pr oje c t e d na tiona l c o mplia nc e c o st e s tima te s. This
chapter presents a summaryand comparison of the national costs and benefits and a costeffect i v eness anal y s i s for each of t h e MC L opt i ons.

7.2 S ummary of National Costs and Benefits

7.2.1 N at ional C o st Est i mat e s

National compliance costs to public water sy stems (PW S s) for treatment (both annualiz ed capital

a nd ope r a ting a nd ma inte na nc e c o sts) , monitor i ng a nd a d ministr a tive a c tivitie s, a nd c o sts to

Sta t e s , inc l uding a n y one

- time sta r t- up c o sts, f o r

r e g u la tor y imple me nta tion a nd e n f o r c e m e n t,

we r e e s tima te d a nd de sc r i be d in Cha p te r 6. The na tiona l c o sts f o r

PWSs to c o mply with the f our

MCL options rang e from $66.8 million (MCL = 20 μg /L ) to $697.8 million (MCL = 3 μg /L )
annually based on a discount rate of three percent. Assuming a seven percent discount rate, the

rang e of total national cost for community water sy stems rang es from $76.5 million to $792.1
million annually

.

7

. 2

. 2 N a t i ona l Be ne fi ts E s ti ma te s

Chapter 5 contains a detailed summary of the methodolog y used to estimate a rang e of national

health benefits from avoided cancer cases as a result of the four Arsenic Rule MCL options. The
dollar value of the estimated health benefits associated with each of the four rule options was
calculated based on lower and upper bound estimates of avoided bladder and lung cancer cases. The national benefits rang e from $66.2 million (MCL = 20 μg /L ) to $213.8 million (MCL = 3

μg /L ) annually , based on the lower bound estimates of cancer cases avoided. Under the upper
bound scenario, the health benefits from avoided cancer increase from $75.3 million at an MCL
of 20 μg /L to $490.9 million annually at an MCL of 3 μg /L

.

7.3 C omparison of Benefits and Costs

This section presents a comparison of total national benefits and costs for each of the Arsenic
Rule options considered. Three separate analy s es are considered, including a summary of

be ne f it/c ost r a tios a nd ne t be ne f its, a dir e c t c o mpa r ison of a g g r e g a t e na tiona l c o sts a nd be ne f its,

and t h e resul t s of a cost -effect i v eness anal y s i s of each reg u l a t o ry opt i on.

Chapter 7, Com par is on of Cos t s and Benefits 7-1 A r s e nic in D r inking Water Rule EA

### 7.3.1 N ational Net Benefits and National Benefit-Cost Comparison

Ex hibit 7-1 describes the net benefits and the benefit/cost ratios under various MCL options for

PW Ss at three and seven percent discount rates. Ex cept for the upper bound benefit scenario at a
discount rate of three percent, the net benefits are neg a tive and decreasing as the Arsenic Rule

MCL options be c o me inc r e a s ing l y mor e str i ng e n t. F o r the sa me c a t e g or ie s, the be ne f it/c ost

rat i o s are l e ss t h an one and decrease as t h e MC L becom e s m o re st ri ng ent

. For nearl y al l of t h e options, c o sts outwe ig h the qua ntif ie d be ne f its, with be ne f it/c ost r a tios a ll be low or e qua l to one

. F o r ex ample, the ratios rang e from 0.3 (MCL =3 μg /L ) to 1.0 (MCL =20 μg /L ) at a seven percent

discount rate. F o r the upper bound scenario at three percent the benefit/cost ratio ex ceeds one at

a n MCL of 10 μg /L a nd 20 μg /L . Of the MCL options e x a mine d, the ne t be ne f its a nd be ne f it/c ost

ratio are max imiz ed at an MCL of 10 μg /L and a three percent discount rate.

Exhi bi t 7- 1 Summary of A nnual Nat i onal Net Benef i t s and Benef i t

- C ost Rat i os ($ millio n s )

MC L ( μ g/ L ) 3 5 10 20

3 % D i s c ount R a t elower bound N e t B e nef i t s $ ( 48 4. 0 ) ( 2 2 3 .7 ) $ $ ( 4 0

. 8 ) $ ( 0 .6 )

B e n e f i t/C o s t R a ti o 0 .3 0

. 5 0 .8 1

. 0upper bound N e t B e nef i t s $ ( 20 6. 8 ) ( 5 9

. 2 ) $ $ 1 7 .3 $ 8

. 5

B e n e f i t/C o s t R a ti o 0 .7 0

. 9 1 .1 1

. 1

7 % D i s c ount R a t elower bound N e t B e nef i t s $ ( 57 8. 3 ) ( 2 8 0 .6 ) $ $ ( 6 6

. 0 ) $ ( 1 0

. 3 )

B e n e f i t/C o s t R a ti o 0 .3 0

. 4 0 .7 0

. 9upper bound N e t B e nef i t s $ ( 30 1. 1 ) ( 1 1 6 .1 ) $ $ ( 7 .9 ) $ ( 1 .2 )

B e n e f i t/C o s t R a ti o 0 .6 0

. 8 1 .0 1

. 0

*C os t s i n c l u d e t r eat m e nt

, O & M

, m o n i t o r i n g

, a nd ad m i nis t r a t i v e c o s t s t o CW S s a n d NT NC s and S t at e c o s t s

f o r a d m i n i s t ra t i o n o f w a t e r p r o g ra m s

.

Chapter 7, Com par is on of Cos t s and Benefits 7-2 A r s e nic in D r inking Water Rule EA����������

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### Ex hibit 7-2 g r aphically depicts the absolute difference between the total value of national costs
and benefits under each proposed MCL at a seven percent discount rate.

Exhi bi t 7- 2 Compari s on of Cost s and Benef i t s

(7% D i scount R a te, in $ millions)

$9

00

. 0

$8

00

. 0

$7 00

. 0

$6

00

. 0

$5

00

. 0

$4

00

. 0

$3

00

. 0

$2

00

. 0

$1 00

. 0

$­ 3 5 10 20

$7 92

. 1 $4 71

. 7 $2 05

. 6 $7 6. 5

$4 91

. 0 $3 55

. 6 $1 97

. 7 $7 5. 3 B e ne f i t s (

u pp er bo un d)

$2 13

. 8 $1 91

. 1 $1 39

. 6 $6 6. 2 B e n e f i t s (

l ow er

bo un d) � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ��� ����� � ��� ����� � ��� ����� ��������� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ����� ����� � ����� ����� � ����� ����� ����������� � ���� ����� ���������� ���������� � ���� ����� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� ����� ���������� � ��� ����� � ��� ����� ���������$ millions

Co

s t

s



### Ex hibit 7-3 depicts the incremental costs and benefits of the rule as one moves from a less
string ent standard to a more string ent standard. Moving to an MCL of 20 μg /L from the current

MCL of 50 μg /L results in incremental costs of $76.5 million and incremental benefits of

between $66.2 million and $75.3 million. A move from 20 μg /L to 10 μg /L results in

incremental costs of $129.1 million and incremental benefits of between $73.4 million and

$122.4 million. Moving bey ond an MCL of 10 μg /L towards a more string ent standard results in
incremental costs that far outweig h the incremental benefits, even under the upper bound benefits

scenari o

.

Chapter 7, Com par is on of Cos t s and Benefits 7-3 A r s e nic in D r inking Water Rule EA����������

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### Exhi bi t 7- 3 Compari s on of I n crement a l Cost s and Benef i t s (7% D i scount R a te, in $ millions)$ millions

���� Co

st

s $35 0. 0

$30 0. 0

$25 0. 0

$20 0. 0

$15 0. 0

$10 0. 0

$50

. 0

$­ 3 5 10 20

$3 20

. 5 $2 66

. 0 $1 29

. 1 $7 6. 5

$1 35

. 4 $1 57

. 9 $1 22

. 4 $7 5. 3 t s (

u pp er b o u nd)

$2 2. 7 $5 1. 5 $7 3. 4 $6 6. 2 t s (

l o

w

er

bou nd ) � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ����� ����� � ����� �����

� ����� ����� � ����� ����� � ����� ����� � ����� ����� ����������� � ����� ���� ���������� � ���� ����� ���������� � ���� ����� � ����� ����� � ����� ����� � ����� ����� � ����� ����� � ����� ����� � ����� ����� � ����� ���� � ����� ���� � ����� ���� � ����� ���� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� �����

� ���� ����� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� ����� � ���� ����� � ���� ����� � ���� ����� ���������� � ����� ����� � ����� ����� ����������� ���������� ���������� � ���� ����� ���������� � ���� ����� � ���� ����� ���������� � ���� ����� � ���� �����

���� ���� B e n e f i

B e n e f i



### Ex hi bi t 7-4 shows t h e resul t s of an anal y s i s i n whi c h t h e averag e nat i onal cost of achi evi n g each

unit reduction in cases of cancer avoided was calculated. The averag e annual cost per cancer
case avoided was computed at each MCL option, for both three and seven percent discount rates.
At a three percent discount rate, the cost per cancer case avoided rang es from $5.0 million to

$12.2 million at an MCL of 3 μg /L , from $4.1 million to $8.1 million at an MCL of 5 μg /L , from

$3.2 million to $4.8 million at an MCL of 10 μg /L , and from $3.4 million to $3.5 million at an

MCL of 20 μg /L

. At a seven percent discount rate, the cost per cancer case avoided rang es from

$5.7 million to $13.8 million at an MCL of 3 μg /L , from $4.7 million to $9.2 million at an MCL
of 5 μg /L , from $3.7 million to $5.5 million at an MCL of 10 μg /L , and from $3.9 million to $4.0

million a t a n MCL of 20 μg /L

.

Chapter 7, Com par is on of Cos t s and Benefits 7-4 A r s e nic in D r inking Water Rule EA

### Exhi bi t 7- 4

Cost per Cancer Case A v oi ded ($ millio n s )

A r s e ni c Le v e l
( μ g/ L) l o w e r bound* * uppe r bound **

3 % D i s c ount R a t e

3

5

10

20 12

. 2 $ 5

. 0 $

8. 1 $ 4

. 1 $

4. 8 $ 3

. 2 $

3. 5 $ 3

. 4 $

7 % D i s c ount R a t e

3

5

10

20 13

. 8 $ 5

. 7 $

9. 2 $ 4

. 7 $

5. 5 $ 3

. 7 $

4. 0 $ 3

. 9 $

* * Lo w e r/ u p p e r bo und s c o rres p o nd t o es t i m a t e s o f bl ad de r c a n c er c a s e s a v o i de d.



### 7.3.2 C ost

- E f f ect iv eness

C o st -effect i v eness anal y s i s i s anot her com m onl y used m easure of t h e econom i c effi ci ency wi t h

whic h r e g u la tor y options a r e me e ting the inte nde d r e g u la tor y obje c tive s

. Ex hibit 7- 5 is a
comparison of annual national costs (computed at a seven percent discount rate) and annual cases

of cancer avoided at each MCL option. The two lines represent the cost per cancer case avoided
under the lower and upper bound estimates of cancer cases avoided. These plotted lines depict

t h e t r end i n m a rg i n al cost and benefi t s (ex p ressed as heal t h effect s avoi ded) bet w een each poi nt on these curves (corresponding to each MCL option). P o ints along these lines represent each

increment of cost that is incurred in order to achieve the nex t increment of risk reduction, i.e.,

additional cancer case avoided. The steepness of the curves under both benefits scenarios

sug g e sts that additional increments of risk reduction and benefits are achieved at increasing l y

g r eat er cost t o t h e nat i on.

Chapter 7, Com par is on of Cos t s and Benefits 7-5 A r s e nic in D r inking Water Rule EA

### Exhi bi t 7- 5 Compari s on of A nnual Cost s t o Cases of Cancer per Year ( 7 % Di scount Rat e )Annual Cost ($ millions) $9 00

$8 00

$7 00

$6 00

$5 00

$4 00

$3 00

$2 00

$1 00

$­ 3 μ g / L

5 μ g / L

10 μ g / L

20 μ g / L

- 2 0 4 0 6 0 8 0 1 00 1 2 0 1 40 1 6 0

C a nc er C a ses A v oi ded p e r Y e a r

ba s e d on l o w e r bo u n d es t i m a t e s of a v

oi d e d c a s e s b a s e d o n u p pe r bo u n d e s t i m a t e s o f av

o i de d c a s e s



### Ex hibit 7- 6 f u r t he r r e inf o r c e s the f a c t tha t a s the MCL be c o me s mor e str i ng e n t, the inc r e m e n ta l

cost per cancer case avoi ded i n creases. For ex am pl e, t h e addi t i onal cases of cancer avoi ded i n moving from an MCL of 10 μg /L to 5 μg /L are achieved at a cost per case of $3.6 million
annually under the hig h bound and seven percent discount rate scenario. Similarly

, in moving

from an MCL of 5 μg /L to a more string ent MCL of 3 μg /L , the cost per case avoided increases to $2.4 million per y ear under this same scenario.

Chapter 7, Com par is on of Cos t s and Benefits 7-6 A r s e nic in D r inking Water Rule EA������������������ ������������������ ������������������ ������������������ �����������������

����������������� ������������������

������������������

��� ���

��� ��� 

### Exhi bi t 7- 6

I n crement a l Cost per I n crement a l Cancer Case A v oi ded (7% D i scount R a te, in $ millions)

������������������ ������������������ � ������������ ����� ������������������ ������������������ � ����������� ����� � ����������� ����� � ����������� ����� � ����������� ����� ����������������� � ����������� ����� ����������������� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� � ������������ ����� ������������������ � ������������ ����� ������������������ $­ $10. 0 $20. 0 $30. 0 $40. 0 $50. 0 $60. 0Incremental Cost per IncrementalCancer Case ($ millions)

��� M C L 20 u g / L $4. 0 $3. 9 ��� M C L 10 u g / L $7. 0 $3. 6

M C L 5 u g / L $19. 4 $6. 0

M C L 3 u g / L $52. 5 $8. 4 Low er bou n d es t i m a t e s of av oi ded c a s e s U p p er bou n d es t i m a t e s of av oi ded c a s e s



### 7.4 Ot her B e nef i t s

Chapter 5 discusses a number of important non-monetiz ed benefits of reducing arsenic ex posure. Chief among these are certain health impacts known to be caused by arsenic. Such
nonquantifiable benefits may include skin cancer, kidney cancer, cancer of the nasal passag e s, liver cancer, prostate cancer, cardiovascular effects, pulmonary effects, immunolog ical effects,
neurolog ical effects, endocrine effects, and customer peace-of-mind benefits from knowing their
drinking water has been treated for arsenic. F o r ex ample, a number of epidemiolog i c studies
conducted in several countries (e.g ., Taiwan, J a pan, Eng l and, Hung ary

, Mex i co, Chile, and
Arg e ntina) report an association between arsenic in drinking water and skin cancer in ex posed
populations. Early reports linking inorg a nic arsenic contamination of drinking water to skin
cancer came from Arg e ntina (Neubauer, 1947, reviewing studies published as early as 1925) and
Poland (Tseng et al., 1968). However, the first studies that observed dose-dependent effects of
arsenic associated with skin cancer came from Taiwan (Tseng et al., 1968; Tseng

, 1977). These
studies focused EPA’s attention on the health effects of ing e sted arsenic. Studies conducted in
the U.S. have not demonstrated an association between inorg a nic arsenic in drinking water and

skin cancer. However, these studies may not have included enoug h people in their desig n to

det ect t h ese t ypes of effect s.

Chapter 7, Com par is on of Cos t s and Benefits 7-7 A r s e nic in D r inking Water Rule EA

5 μ g /L

### The potential monetiz ed benefits associated with skin cancer reduction would not chang e the

tota l be ne f its of the r u le to a n a ppr e c i a b le de g r e e

, e v e n if the a ssumption we r e ma de tha t the r i sk
of skin cancer were equivalent to that of bladder cancer, using EPA’s 1988 risk assessment. Skin
cancer is hig h ly treatable (at a cost of illness of less than $3,500 for basal and squamous cell
carcinomas versus a cost of illness of $178,000 for non-fatal bronchitis) in the U.S., with few

f

a ta litie s ( l e ss tha n one pe r c e n t)

.

I n addi t i on t o ski n cancer, t h ere are al so a l a rg e num ber of ot her heal t h effect s associ at ed wi t h
arsenic, as presented in Ex hibit 7-7, which are not monetiz ed in this analy s is, due to lack of
appropriate data.

Exhi bi t 7- 7

T o t a l A nnual Cost

, Est i mat e d M onet i zed T o t a l Cancer Heal t h Benef i t s , and

N o n

- Qu a n tifia b le H e a l th B e n e fits fro m R e d u c in g A r s e n ic in P W S s ($ millio n s )

A r s eni c

Level (μ g/ L) Tot a l A nnual

Cos t (7% ) A nnual B l adder

Canc er Heal t h

B enef i t s 1,2 A nnual Lung

Canc er Heal t h

B enef i t s 1,2 Tot a l A nnual

Heal t h B enef i t s 1,2 P o t ent i a l Non-Quant i f i abl e
Heal t h B enef i t s

3 $792. 1 $58. 2 - $156. 4 $155. 6 - $334. 5 $213. 8 - $490. 9 • S k i n Canc er

• K i dney Canc er

• C anc er of t he Nas a l

P a s s ages

• L i v er Canc er

• P ros t at e Canc er

• C ardi ovas c u l a r E f f e c t s

• P ul m onary E f f e c t s

• I m m unol ogi c a l E f f e c t s

• N eurol ogi c a l E f f e c t s

• E ndoc ri ne E f f e c t s

• R eproduc t i ve and

Devel opm ent al E f f e c t s 5 $471. 7 $52. 0 - $113. 3 $139. 1 - $242. 3 $191. 1 - $355. 6

10 $205. 6 $38. 0 - $63. 0 $101. 6 - $134. 7 $139. 6 - $197. 7

20 $76. 5 $20. 1 - $21. 5 $46. 1 - $53. 8 $66. 2 - $75. 3 3

1 M a y 1999 dollars.

2 T hese monetary estimates are based on cases av oided giv en in Ex hibit 5-9 (a-c).

3 For 20 μ g /L, the proportional reduction from the low e r lev e l risk base case is greater than the proportional reduction from the higher lev e l risk base case. T hus the number of estimated cases av oided and estimated benefits are higher at 20 μ g /L using the estimates adjusted for uncertainty

.



### Other benefits not monetiz ed in this analy s is include customer peace of mind from knowing
drinking water has been treated for arsenic and reduced treatment costs for currently unreg ulated
contaminants that may be co-treated with arsenic. To the ex tent that reverse osmosis is used for

arsenic removal, these benefits could be substantial. Reverse osmosis is the primary point-of-use

tr e a tme nt, a nd it is e x pe c t e d tha t ve r y sma ll sy ste m s will use this tr e a tme nt to a sig n if ic a n t

ex tent. (These benefits of avoided treatment cannot currently be monetiz ed; however, they can be readily monetiz ed in the future, as decisions are made about which currently unreg ulated

c onta mina n ts to r e g u la te .)

Chapter 7, Com par is on of Cos t s and Benefits 7-8 A r s e nic in D r inking Water Rule EA�����������������������������������������������������������������������

125 135 145 155 165 175 185 195 205 215 225 235 245 255 265 275 

### 7.5 B enef it s- C o st s U n cert a int y A n aly s is

The uncertainty surrounding the national cost of compliance was described in Chapter 6.

Ex hibit 7-8 superimposes the distribution of national compliance costs onto the rang e of

mone tize d be ne f its a ssoc i a t e d with the r u le a t a n MCL of 10 μg /L

. This e x hibit illustr a te s tha t

the r e is a ppr ox ima te ly a

50 pe r c e n t pr oba bility tha t the c o sts of the r u le will be lowe r tha n the

monetiz ed benefits of the rule under the upper bound benefit assumption.Cumulative Probability 

### Exhi bi t 7- 8

Nat i onal Compl i a nce Cost s and Benef i t s Uncert a i n t y A n al y s i s
Cumul a t i v e Cost Di st ri but i on v s

. Benef i t s Range ( M C L 10 μg/ L )

100. 00%

90. 00%

80. 00%

70. 00%

60. 00%

50. 00%

40. 00%

30. 00%

20. 00%

10. 00%

0. 00% R A NG E O F NA T I O N A L

CO S T S �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� �� ���������������������������������������������������������������� ����� ����������������������������������������������������������������������� R A NG E O F NA T I O N A L

BEN EFITS

( $ M illio n s )

Chapter 7, Com par is on of Cos t s and Benefits 7-9 A r s e nic in D r inking Water Rule EA

## Chapter 8: Economi c I m pact A n al y ses

8.1 I ntroduction

The Environmental Protection Ag ency (EPA) is required to perform a series of analy s es that
addresses the distribution of reg u latory impacts associated with the Arsenic Rule. This chapter
presents analy s es that support EPA’s compliance with the following F e deral mandates:

• E x ecutive Order 12886 (Reg ulatory Planning and Review);

• R eg ulatory F l ex ibility Act (RF A ) of 1980, as amended by the Small B u siness Reg u latory

Enforcement F a irness Act (SB R EF A) of 1996;

• N ational Affordability determination required by the 1996 amendments to the Safe
Drinking W a ter Act (S DW A);

• U nfunded Mandates Reform Act (UMRA) of 1995;

• T echnical, F i nancial, and Manag e rial Capacity Assessment required by Section
1420(d)(3) of the 1996 amendments to the Safe Drinking W a ter Act (SDW A);

• E x ecutive Order 13045 (Protection of Children F r om Environmental Health Risks and
Safety Risks);

• E x ecutive Order 12989 (F ederal Actions to Address Environmental J u stice in Minority
Populations and L o w-I n come Populations);

• P aperwork Reduction Act;

• H e a lth Risk Re duc tion a nd Cost Ana l y s is (HRRCA) a s re quire d by Se c tion 1412(b)(3)(C)

of the 1996 SDW A Amendments; and

• I nitia l Re g u la tor y F l e x ibility Ana l y s is ( I RF A)

.

These anal y s es draw on t h e cost anal y s es present e d i n C h apt e r 6 and an anal y s i s of

a d ministr a tive r e quir e me nts pr e s e n te d in a se pa r a te doc ume n t, Information Collection Request
for the Arse nic Rule

.

Several of these F e deral mandates require an ex planation of why the rule is necessary , the

statutory authority upon which it is based, and the primary objectives it is intended to achieve.

B ackg r ound information on the problems addressed by the rule, and EPA’s statutory authority for
promulg a ting the rule, are presented in Chapter 2. I n this chapter, Section 8.2 presents the RF A

and SB REF A analy s is of impacts on small entities. Also described are the economic impacts of

the rule on households. Section 8.3 discusses coordination of the Arsenic Rule with other

F e deral rules. The minimiz ation of economic burden, UMRA, sy stem capacity assessments, and
the Paperwork Reduction Act are addressed in Sections 8.4, 8.5, 8.6, and 8.7, respectively

. Section 8.8 discusses the rule’s protection of children’s health, Section 8.9 addresses

e nvironme n ta l justic e issue s , a nd Se c tion 8.10 c onta i ns the HRRCA.

8.2 R egulat ory Flexibilit y A c t and Small B u siness R e gulat ory Enf o rcement

Fairness A c t

The RF A provides that, whenever an ag ency promulg a tes a proposed or final rule under section
553 of the Administrative Procedure Act, after being required by that section or any other law to
publish a g e ne r a l notic e of r u le ma king , the a g e n c y must pr e p a r e a n initia l a nd f i na l r e g u la tor y

Chapter 8, Economic Impact Analyses 8-1 A rsenic in Drinking Water Rule EA

### flex ibility analy s is. The ag ency must prepare such an analy s is when proposing a rule (or

pr omulg a ting a f

i na l r u le ) unle ss the he a d of the a g e n c y c e r tif ie s tha t the r u le will not ha ve a sig n if ic a n t e c onomic impa c t on a substa ntia l numbe r of sma ll e n titie s. EPA did not c e r tif ie d tha t the proposed reg u lation would not have a sig n ificant economic impact on a substantial number of

small entities. Consequently , the Ag ency prepared an initial analy s is of the proposal and,

because it has not certified the final rule, has now completed a final reg u latory flex ibility

anal y s i s

. EP A prepared t h ese anal y s es i n com p l i a nce wi t h t h e requi rem e nt s of t h e R F A

Unde r the RF A, the te r m “ s ma ll e n tity ” me a n s “ s ma ll busine ss,” “ s ma ll g ove r n me nta l
jurisdiction” and “small org a niz a tion.” These terms are further defined by the Act. I n the case of
a “small business,” the term has the same meaning as a “small business concern” under section 3

of the Small B u siness Act. (Reg ulations of the Small B u siness Administration (SB A ) at 13 CF R

121.201 have defined small businesses for Standard I ndustrial Classification (SI C ) codes.)
“Small g overnmental jurisdiction” means the g overnment of cities, counties, towns and villag e s,

among others, with a population of less than 50,000. A “small org a niz a tion” is any not-for-profit
enterprise that is independently owned and operated. The RF A authoriz es an ag ency to establish
other definitions of such terms which are appropriate to the ag ency ’s activities and publish such

definitions in the F e deral Reg i ster after consultation with SB A and opportunity for public

comment. 5 U.S.C. § 601(3), (4) & (5).

8.2.1 D escript i on of t h e Init ial R e gulat ory Flexibilit y A n aly s is

The Re g u la tor y F l e x ibility Ac t r e quir e s EPA to c o mple te a n I n itia l Re g u la tor y F l e x ibility
Analy s is (I RF A) addressing the following :

1. The need for t h e rul e ;

2. The objectives of and leg a l basis for the rule;

3. A de sc r i ption of , a nd whe r e f e a s ible , a n e s tima te of the numbe r of sma ll e n titie s to

whic h the r u le will a pply ;

4. A description of the reporting

, record keeping

, and other compliance requirements

of

the r u le , inc l uding a n e s tima te of the ty pe s of sma ll e n titie s tha t will be subje c t to the requirements and the ty pe of professional skills necessary for preparation of
reports or records;

5. An identification, to the ex tent practicable, of all relevant F e deral rules that may
duplicate, overlap, or conflict with the rule; and

6. A de sc r i ption of “ a n y sig n if ic a n t r e g u la tor y a lte r n a tive s ” to the r u le tha t accomplish the stated objectives of the applicable statutes, and that minimiz e any sig n if ic a n t e c onomic impa c t of the r u le on sma ll e n titie s. Sig n if ic a n t r e g u la tor y

a lte r n a tive s ma y inc l ude :

Chapter 8, Economic Impact Analyses 8-2 A rsenic in Drinking Water Rule EA

###  Esta blishing dif f

e r e nt c o mplia nc e or r e por ting r e quir e me nts or time ta ble s that take into account the resources of small entities;

 Clarify i ng , consolidating

, or simplify i ng compliance and reporting
requirements under the rule for small entities;

 Usi n g perform ance rat h er t h an desi g n st andards; and

 Ex e m pting sma ll e n titie s f r o m c ove r a g e of the r u le or a n y pa r t of the r u le

.

I f

the initia l a sse ssme n t de te r mine s tha t a substa ntia l numbe r of sma ll e n titie s ma y f

a c e sig n if ic a n t impa c t s a s a r e sult of the r u le , the n a f

o r m a l r e g u la tor y f

l e x ibility a n a l y s is ma y be
required.

De fi ni ng “S ma l l E n ti ti e s ” Affe c t e d by the Rul e

The Re g u la tor y F l e x ibility Ac t ( R F A ) de f i ne s sma ll e n titie s a s inc l uding “ s ma ll busine sse s,”
“small g overnments,” and “small org a niz a tions” (5 USC 601). The RF A references the

definition of “small business” found in the Small B u siness Act, which authoriz es the Small

B u siness Administration (SB A ) to further define “small business” by reg u lation. The SB A
defines small business by categ ory of business using Standard I ndustrial Classification (SI C )
codes (13 CF R 121.201). F o r ex ample, in the manufacturing sector, the SB A g e nerally defines

sma ll busine ss in te r m s of numbe r of e m ploy e e s ; in the a g r i c u ltur e , mining

, e l e c tr ic , g a s, a n d
sanitary services sectors, the S B A g e nerally defines small businesses in terms of annual receipts
(rang ing from $0.5 million for crops to $25 million for certain ty pes of pipelines). The RF A also

authoriz es an ag ency to adopt an alternative definition of “small business” “where appropriate to
the activities of the Ag ency ” after consultation with the SB A and opportunity for public

c o mme nt.

F o r the r e vise d Ar se nic Rule sma ll e n titie s a r e de f i ne d a s those wa te r sy ste m s tha t me e t the

f

o llowing c r ite r i a :

& 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 B u siness Act (15 USC

632). Ex amples of public water sy stems within this categ ory include small, privately
owned, public water sy stems and for-profit businesses where provision of water may be

a n c illa r y , suc h a s mobile home pa r k s or da y c a r e c e n te r s

.

& A “small org a niz a tion” is any not-for-profit enterprise that is independently owned and
operated, not dominant in its field, and operates a public water sy stem. Ex amples of
small org a niz a tions are churches, schools, and homeowners associations.

& A “small g overnmental jurisdiction” is a city , county

, town, school district or special
district with a population of less than 50,000 (5 USC 601) that operates a public water

sy stem.

I n 1998, EPA proposed that PW Ss with populations of 10,000 or fewer persons be defined as

“ s ma ll e n titie s” within the c onte x t of the Consume r Conf ide n c e Re por t ( CCR) r u le ma king ( 6 3

F R 7620, F e bruary 13, 1998). EPA requested public comments on this alternative definition.

Chapter 8, Economic Impact Analyses 8-3 A rsenic in Drinking Water Rule EA

### For t h i s rul e m a ki ng , t h e S B A Offi ce of Advocacy ag reed wi t h t h e Ag ency ’s al t e rnat i v e
definition. EPA intends to define “small entity ” in the same way for RF As under SB REF A for
all future drinking water reg u lations, including the revised Arsenic Rule.

EPA se le c t e d this a lte r n a tive de f i nition f o r

sma ll wa te r sy ste m s f o r

se ve r a l r e a s ons:

& A larg e proportion (94 percent) of all PW Ss are small entities, althoug h they serve a minority of the population. L a rg er PW Ss (those serving over 10,000 persons)
serve the majority of the population receiving water from public water sy stems.

& Certain key financial ratios (e.g ., total debt as a ratio of total revenue) show a
distinct break point at the 10,000 or fewer sy stem siz e level. 1 

### I n g e neral, the siz e
of a P W S i s an i m port a nt fi nanci a l charact eri s t i c , as l a rg er sy st em s can spread

investments in fix e d assets across a broader customer base. Smaller water

sy stems ty pically serve primarily residential customers. L a rg er sy stems have

f

e we r r e side ntia l c u stome r s a s a pe r c e n ta g e of tota l wa te r sa le s a nd mor e
commercial customers. Annual sales revenue per connection is sig n ificantly
hig h er for nonresidential than for residential connections. 2 

### Simila r l y

, la r g e r publicly owned sy stems are more likely to have rated bond issuances, another
indicator of financial streng th. 3



### & I n the 1996 Amendments to the Safe Drinking W a ter Act (SDW A), several

me a s ur e s c r e a ting r e g u la tor y r e lie f de f i ne d sma ll c o mmunity wa te r sy ste m s a s those serving 10,000 or fewer customers. One provision allows for alternative

me a n s of de live r y of the CCRs by sy ste m s se rving 10,000 or fe we r pe rsons. Another used the same cutoff for modifications to monitoring requirements and
for certain penalty provisions deleg a ted to the States. 4



### & EPA has previously used this criterion in both rulemaking and implementation

a c tivitie s pe r t a i ning to PWSs. The tota l tr iha l ome t ha ne ( TTHM) r u le
promulg a ted by EPA in 1979 applied only to sy stems serving more than 10,000

persons. EPA chose the 10,000 cutoff in 1979 primarily out of a concern that

sma lle r sy ste m s would ha ve to dive r t r e sour c e s f r o m othe r a c tivitie s to c o mply

with the rule. I n 1992, EPA initiated a reg u latory neg o tiation process that resulted
in reg u latory actions to provide additional protection from microbial contaminants
in drinking water while reducing health risks from disinfection by products. The

I n t e ri m Enhanced S u rface W a t e r Treat m e nt R u l e prom ul g a t e d from t h i s process

1 Co mmu n i t y Wa t e r S y st ems S u r vey, V o l u me I: Overvi ew , U

. S. EP A O f f i c e of W a te r

, p. 26. J a nua r y 1997.

2 Id ., p. 14



### .

3 Id ., p. 28.

4 H ous e Re por t N o . 104- 632 ( C om m e r c e C o m m itte e ) , J une 24, 1996 in U S

C ode C ongr e s s i onal and Adm i nis t r a tiv e N e w s (U SCCA A N ), 1996, 4, pp. 1373, 1401 a nd 1409, dis c us s i ng §§132(b) a nd 1418(a ) of the H ous e bill.

Chapter 8, Economic Impact Analyses 8-4 A rsenic in Drinking Water Rule EA

### applied only to sy stems serving more than 10,000. The companion rule, the
Stag e 1 Disinfection B y products Rule, deferred compliance with part of the
requirements for sy stems serving 10,000 or fewer persons.

F o r purposes of this analy s is, therefore, “small entity ” refers to any public water sy stem that
serves 10,000 or fewer persons. Ex hibit 8-1 shows the universe of small PW Ss potentially

affect ed by t h e new arseni c st andard.

Exhi bi t 8- 1

Prof i l e of t h e Uni v erse of Smal l Wat e r Sy st ems Regul at ed Under t h e A r seni c Rul e

Ty pe W a t e r Sy s t e m Sy s t e m Siz e C a t e g o r y

< 100 10 1- 5 0 0 5 0 1

- 1

, 0 0 0 1, 001

- 3

, 300 3, 301

- 1 0

, 00 0

Pu b l ic l y

- O w n e d :
C W S

N C W S 1

, 729

1

, 783 5, 795

3, 171 3, 785

1, 182 6, 179

36 1 3, 649

2 9

P r i v at el y

- O w n e d :
C W S

N C W S 1 3

, 64 0

8

, 178 1 1

, 26 6

4, 162 2

, 124

90 2 1, 955

4 1 1 65 4

56

T o t a l S y st e m s:

C W S

N C W S

TO TA L 1 5

, 36 9

9

, 961

25

, 3 3 0 1 7

, 06 1

7, 333

24

, 3 9 4 5

, 909

2, 084

7, 993 8, 134

77 2

8, 906 4, 303

8 5

4, 388

S o u r c e : S a f e D r i n k i ng W a t e r I n f o r m a t i o n S y s t em ( S D W I S )

, D e c e m b er 199 8 f r eez e.



### Determining What Number Constitutes a Substantial Number

I n this analy s is approx imately 71,013 PW Ss are defined as small entities. EPA SB REF A

g u ida n c e ha s se ve r a l dif f

e r e nt c r ite r i a f

o r

wha t c onstitute s a substa ntia l numbe r of a f f

e c t e d

e n titie s. 1 

### One of the criteria is that no more than 20 percent of sy stems affected by the revised
Arsenic Rule may ex perience economic impacts of one percent of their revenues or g r eater.

M

easuring Signif i cant Impact s

To e v a l ua te the impa c t tha t a sma ll e n tity is e x pe c t e d to inc u r a s a r e sult of the r u le , this a n a l y s is
calculates the entity ’s ratio of annualiz ed compliance costs as a percentag e of sales (for privately
owned sy stems) or the entity ’s ratio of annualiz ed compliance costs as a percentag e of annual

g overnmental revenue or ex penditures (for publicly owned sy stems). EPA g u idance sug g e sts using one percent as a threshold for determining sig n ificance, althoug h additional factors may be

considered. I f compliance costs are less than one percent of sales or revenues, the reg u lation may
in most cases be presumed to have no sig n ificant impact on a substantial number of small

e n titie s. 5

5 Id

.

Chapter 8, Economic Impact Analyses 8-5 A rsenic in Drinking Water Rule EA

### Categorizing Systems

EPA categ oriz ed affected small entities according to the categ ories identified in the SB REF A

g u idance (i.e., small business, small g overnment, and small org a niz a tion). Public water sy stem inventories, manag e d by EPA and other org a niz a tions, traditionally categ oriz e public water

sy stems by siz e and by the characteristics of the population served (i.e., community water sy stem, non-community water sy stem). Therefore, detailed information by SI C or data on revenues or

sal e s are not readi l y avai l a bl e.

Estimating Revenue by RFA Category

The e s tima te d r e ve nue s f o r

sma ll e n titie s in Ex hibit 8- 2 a r e f r o m the B u r e a u of the Ce nsus 6 

### ; EPA
chemical monitoring reform rulemaking ; and additional data on independent privately owned
CWSs, spe c i a l distr i c t s, a nd a u thor itie s, whic h a r e f r o m the CWS Sur v e y

. Ex hibit 8- 2 a l so shows the numbers of small businesses, g overnments, and org a niz a tions, obtained using

information from EPA’s B a seline Handbook. 7 

### These numbers were used to determine the

we ig hte d a v e r a g e s of e s tima te d a v e r a g e r e ve nue , a s de sc r i be d in the c o lumn “ A ve r a g e Estima te d
Revenues per Sy stem.”

Small g overnment sy stems include municipal, county

, State, F e deral, military , and special district

sy ste m s. Da ta on r e ve nue f o r

townships a nd munic i pa litie s we r e obta i ne d f r o m the 1992 Census
of Governments , converted to 1999 dollars by apply i ng a conversion factor calculated from the
national income and product account tables of the U.S

. B u reau of Economic Analy s is. 8



### Specifically , the price deflators for 1992 and 1999 were obtained from Table 7.11, Chain-Type
Quantity and Price Indexes for Government , Chain-Ty pe Price I ndex e s for State and L o cal

Governments. The averag e revenue for all small g overnment PW Ss was calculated at
$2,333,119.

Small businesses include both CW Ss and NTNCW S s, such as privately owned community water

sy stems, mobile home parks, country clubs, hotels, manufacturers, hospitals, and other

e s ta blishme n ts. F o r this a n a l y s is, a ll hospita ls a nd da y c a r e c e n te r s we r e a ssume d to be

businesses. Althoug h some hospitals may be nonprofit, they have unusually hig h revenues and

we r e inc l ude d in the sma ll busine ss c a t e g or y to ma ke the e s tima te d r e ve nue f o r

sma l l

or g a niza tions mor e c onse r va tive

. Estima te d a v e r a g e r e ve nue f o r

the sma ll busine sse s a f f

e c t e d by
the revised Arsenic Rule is $2,675,582.

6 1992 C e ns us of G o v e r nm e n ts



### , G C 92 ( 4 )

- 4 : Fina nc e s of Munic i pa l a nd T o w n s h ip G o v e r n m e nts



### , U. S

. Dep t

. o f

Co m m e rce, Bu reau o f t h e Cen s u s

.

7 D r ink i ng W a te r Bas e line H andbook Se c ond Edition, EP A Contra c t N o . 68-C6-0039. P r e p a r e d by Inte rna tiona l

C ons ulta nts

, I n c

.

8 Me thodolog y r e c o m m e nde d by B r uc e E. B a k e r

, Sta t e a nd L o c a l G o v e r n m e nts

, G o v e r n m e nt D i v i s i on, U

. S. B u r e a u of

Ec onom ic A n a l y s is

.

Chapter 8, Economic Impact Analyses 8-6 A rsenic in Drinking Water Rule EA

### Exhi bi t 8- 2

A nnual Cost of Compl i a nce Cost s as a Percent a ge of Rev e nues by T y pe of Smal l Ent i t y ( P WSs t h at are Expect ed t o M odi f y or I n st al l T r eat ment at an M C L = 10 μg/ L )

Nu m b e r o f

Sy s t e m s A v er ag e

E s

ti m a te d

R e v e nue s pe r Sy s t e m A v er ag e

Co m p l i a n c e

Co s t P e r Sy s t e m Co s t to

R e v e nue

Ra t i o

Wat e r S y s t em s t h at w i l l M o d i f y o r I n s t a l l T r eat m e n t

Sm a l l G o v e r n me n t

S m a l l B u si n e s s

S m a l l O r ga ni z a t i ons

Al l S m a l l E n ti ti e s 1, 116

2, 318

472

3, 907 $2, 33 3, 1 1 9
$2, 67 5, 5 8 2
$5, 99 0, 9 1 4
$2, 97 8, 5 4 6 $41

, 9 99

$13

, 4 66

$6, 82 8

$20

, 8 16 1. 800 1%

0. 503 3%

0

. 114 0%

0. 698 9%

W a t e r S y s t e m s t h a t w i ll O n ly M o n i t o r

Sm a l l G o v e r n me n t

S m a l l B u si n e s s

S m a l l O r ga ni z a t i ons

Al l S m a l l E n ti ti e s 20, 58 7

38, 13 1

8, 389

67, 10 6 $2, 33 3, 1 1 9
$2, 67 5, 5 8 2
$5, 99 0, 9 1 4
$2, 98 4, 9 5 8 $37

$39

$53

$40 0. 001 6%

0. 001 5%

0. 000 9%

0. 001 4%

Al l W a t e r S y s t e m s

Sm a l l G o v e r n me n t

S m a l l B u si n e s s

S m a l l O r ga ni z a t i ons

Al l S m a l l E n ti ti e s 21, 70 3

40, 44 9

8, 861

71, 01 3 $2, 33 3, 1 1 9
$2, 67 5, 5 8 2
$5, 99 0, 9 1 4
$2, 98 4, 6 0 5 $2, 19 5
$80 9

$41 4
$1, 18 3 0

. 094 1%

0

. 030 2%

0

. 006 9%

0

. 039 6%



### Small org a niz a tions include primarily nonprofit NTNCW S s such as schools and homeowners

associations. The estimates for small nonprofit org a niz a tions serving more than 500 people are

act ual l y hi g h er t h an t hose for sm al l busi n esses because t h e t o t a l num ber of such sy st em s i s sm al l

, and a larg e proportion of these org a niz a tions are schools and colleg e s with larg e budg ets. This

c a t e g or y a l so inc l ude s 50 pe r c e n t of sy ste m s c l a ssif i e d a s “ o the r .” The a v e r a g e e s tima te d
revenue for small org a niz a tions affected by the revised Arsenic Rule is $2,978,546.

EPA a l so c a l c u la te d the a v e r a g e e s tima te d r e ve nue f o r

a ll sma ll e n titie s. This e s tima te is
weig hted to account for the number of small entities in each categ ory (g overnment, business, and

org a niz a tion) affected by the revised Arsenic Rule. This overall averag e is $2,833,552.

Conducting the Screening Analysis

The final task of the initial assessment is to conduct the screening analy s is and determine

whe t he r the r u le is e x pe c t e d to r e sult in sig n if ic a n t e c onomic impa c t s on a substa ntia l numbe r of

small entities. The screening analy s is involves the following three steps:

(1) Estimate the c o mplianc e c o st of the rule to small PW Ss

. Estima te d a v e r a g e pe r

sy st em com p l i a nce cost s associ at ed wi t h t h e revi sed Arseni c R u l e were t a ken

f r o m the e s tima te pr e p a r e d by EPA a nd pr e s e n te d in Cha p te r 6.

Chapter 8, Economic Impact Analyses 8-7 A rsenic in Drinking Water Rule EA������� ������� ������� ������� ������� ������� ������

������� �������

�������

������� ������� ������� ������� ������� ������ �������

��� ��� ��� 

### (2) Obtain data on the number of small PW Ss and their revenues or expenditures.

The number of small PW Ss ex pected to modify or install treatment are found in

Ex hibit 8-2. These numbers are derived from the results of the SafeW a terXL model described in Chapter 6.

(3) Compute small e n tity impac ts

. Usi n g t h e dat a obt ai ned i n t h e precedi n g st eps, EPA calculated the ratio of total annual compliance costs as a percentag e of

revenues or ex penditures. These ratios, converted into percentag e s, are presented

in Ex hibit 8-2 in the column “Cost to Revenue Ratio.”

8.2.2 I nit i al Regulat ory Flexibilit y A n aly s is Result s

The r e sults of the initia l r e g u la tor y f

l e x ibility a n a l y s is a r e summa r i ze d be low. As se e n in

Ex hibits 8-2 and 8-3, at a max imum contaminant level (MCL ) of 10 μg /L , 3,907 small PW Ss are

ex pected to have to modify or install treatment.

Exhi bi t 8- 3

Number of CWSs Expect ed t o Undert ake or M odi f y T r eat ment Pract i c e

M C L 10 μg/ L

15, 0 0 0

13, 5 0 0

12, 0 0 0

10, 5 0 0

9, 00 0Number of Systems

7, 50 0

6, 00 0

4, 50 0

3, 00 0

1, 50 0

0

T r ea t i ng G W s y s t em s 855 940 310 421 215

N o t tre a ti n g G W s y s t e m s 13, 4 2 2 14, 1 1 8 4

, 3 7 9 5, 29 3 2

, 2 4 4 ��� T r ea t i ng S W s y s t em s 11 21 12 24 18 ��� N o t tre a ti n g S W s y s t e m s 1, 08 1 1

, 9 8 2 1, 20 8 2

, 3 9 6 1, 82 6



### Ex hibit 8-3 compares the number of CW Ss ex pected to be affected by the promulg a tion of the
new standard to the number of sy stems not ex pected to undertake or modify any of their ex isting

t r eat m e nt pract i ces. S i x percent of sm al l C W S s and NTNC wat e r sy st em s are ex pect ed t o have t o
modif y

or insta ll tr e a tme nt.

EPA c o mpa r e d the r a tio of c o mplia nc e c o st to r e ve nue to the thr e shold va lue f o r

sig n if ic a n t impacts of one percent under the revised arsenic standard of 10 μg /L

. I n Ex hibit 8-2, the ratios ������� ������� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� � � ����� ������� ������ ������ ������ ������ ������ ������ ������ ������ ������ ������ ������ ������ ������ ������ � � ����� � � ����� � � ����� ������� � � ����� � � ����� � � ����� � � ����� ������� � � ����� ������� ������� � � ����� ������� ������� ������ ������ � � ����� �������

< 100 101- 500 501- 1, 00 0 1

, 0 0 1

- 3

, 300 3, 30 1- 10

, 000

Chapter 8, Economic Impact Analyses 8-8 A rsenic in Drinking Water Rule EA

### are display e d separately for small g overnments, small businesses, and small org a niz a tions, and

c u mula tive l y f

o r

a ll sma ll e n titie s.

A sig n ificant impact is g e nerally defined as costs equal to or g r eater than one percent of

revenues. Costs are equal to or g r eater than one percent of revenues only among small

g ove r n me nt e n titie s tha t a r e e x pe c t e d to modif y

or insta ll tr e a tme nt a t the r e vise d MCL

. The va st majority of water sy stems will see impacts less than one percent of their annual revenue.

Howe ve r

, EPA’ s e s tima te s show a numbe r of sma ll sy ste m s tha t will inc u r sig n if ic a n t c o sts.

The r e f or e

, EPA is not c e r tif y i ng this r u le a s ha ving no sig n if ic a n t impa c t on sma ll e n titie s.

8.2.3 S ummary of EPA ’s Small B u siness C onsult a t i ons

As required by section 609(b) of the RF A, as amended by SB REF A , EPA also conducted

outreach to small entities and convened a Small B u siness Advocacy Review Panel to obtain

a dvic e a nd r e c o mme nda tions of r e pr e s e n ta tive s of the sma ll e n titie s tha t pote n tia lly would be
subject to the rule’s requirements.

EPA ide n tif ie d 22 r e pr e s e n ta tive s of sma ll e n titie s, in this situa tion sma ll sy ste m s, tha t we r e most likely to be subject to the proposal. I n December 1998, EP A prepared and distributed to the
small entity representatives (SERs) an outreach document on the Arsenic Rule titled

“ I nf or ma tion f o r

Sma ll Entity Re pr e s e n ta tive s Re g a r d ing the Ar se nic in Dr inking Wa te r Rule ”
(EPA, 1998 ).

On December 18, 1998, EP A held a S E R conference call for small sy stems from W a shing t on, DC, to provide a forum for input on key issues related to the planned proposal of the Arsenic in

Dr inking Wa te r Rule

. The s e issue s inc l ude d, but we r e not limite d to, issue s r e la te d to the r u le
development, such as arsenic health risks, treatment technolog ies, analy tical methods, and

monitor i ng

. F i f t e e n SERs f r o m sma ll wa te r sy ste m s pa r tic ipa t e d on the c a ll f r o m the f o llowing

States: Alabama, Ariz ona, California, Georg i a, Massachusetts, Montana, Nebraska, New
Hampshire, New J e rsey , Utah, Virg inia, W a shing t on, and W i sconsin.

Ef f

o r t s to ide n tif y

a nd inc o r por a t e sma ll e n tity c onc e r ns into this r u le ma king c u lmina t e d with the
convening of a SB AR Panel on March 30, 1999, pursuant to section 609 of RF A/SB REF A

. The
four person P a nel was headed by EP A’s S m al l Busi ness Advocacy C h ai rperson and i n cl uded t h e Director of the Standards and Risk Manag e ment Division within EPA’s Office of Ground W a ter and Drinking W a ter, the Administrator of the Office of I n formation and Reg u latory Affairs with
the Office of Manag e ment and B udg et, and the Chief Counsel for Advocacy of the S B A. For a 60-day period starting on the convening date, the Panel reviewed technical backg r ound
information related to this rulemaking , reviewed comments provided by the SERs, and met on

several occasions. The P a nel also conducted its own outreach to the S E Rs and held a conference
call on April 21, 1999, with the SERs to identify issues and ex plore alternative approaches for
accomplishing environmental protection g o als while minimiz ing impacts to small entities.

Consiste nt with the RF A/SB REF A r e quir e me nts, the Pa ne l e v a l ua te d the a sse mble d ma te r i a l s and small-entity comments on issues related to the elements of the I R F A (See Section 8.2.1) . A

copy of the J une 4, 1999, Panel report is included in the docket for the Arsenic Rule (U.S. EPA,

1999).

Chapter 8, Economic Impact Analyses 8-9 A rsenic in Drinking Water Rule EA

### The revi sed rul e addresses al l of t h e recom m e ndat i ons on whi c h t h e P a nel reached consensus. I n addition, to help small sy stems comply with the Arsenic Rule, EPA is committed to addressing
several other Panel recommendations reg a rding g u idance, which are discussed in detail in the

pa g e s to f o llow.

Treatment Technologies, Waste Disposal, and Cost Estimates

The Pa ne l r e c o mme nde d the f o llowing : f u r t he r de ve lop the pr e limina r y tr e a tme nt a nd wa ste disposa l c o st e s tima te s; f u lly c onside r the s e c o sts whe n ide n tif y i ng a f f

o r d a b le c o mplia nc e technolog ies for all sy stem siz e categ ories; and provide information to small water sy stems on possible options f o r

c o mply ing with the MCL

, in a ddition to insta lling a n y liste d c o mplia nc e technolog ies.

I n response to these recommendations, the Treatment and Cost document describes development

of

c o st e s tima te s f o r

tr e a tme nt a nd wa ste disposa l; ide n tif ic a tion of a f f

o r d a b le c o mplia nc e technolog ies, including the consideration of cost; and options for comply ing with the MCL other
than installing compliance technolog ies, such as selecting to reg i onaliz e.

Reg a rding point-of-use (POU) devices, the Panel recommended the following : continue to
promote the use of POU devices as alternative treatment options for very small sy stems where
appropriate; account for all costs, including costs that may not routinely be ex plicitly calculated;

c onside r lia bility issue s f r o m POU/point- o f

- e ntr y ( P OE) de vic e s whe n e v a l ua ting the i r appropriateness as compliance technolog ies; and investig ate waste disposal issues with POE

devices.

I n response to these recommendations, EPA included in the revised rule’s preamble an ex panded
description reg a rding available POU compliance treatment technolog ies and conditions under
which POU treatment may be appropriate for very small sy stems; a description of the
components that contribute to the POU cost estimates; and a discussion that clarifies that water

sy stems will be responsible for POU operation and maintenance to prevent liability issues from

c u stome r s ma inta ining e quipme n t the m se lve s

.

R e levance of Ot her D r inking W a t e r R e gulat ions

The Panel recommended the following : include discussion of the co-occurrence of arsenic and
radon in the Arsenic Rule; take possible interactions among treatments for different contaminants
into account in costing compliance technolog ies and determining whether they are nationally
affordable for small sy stems; and encourag e sy stems to be forward-looking and test for multiple
contaminants to determine if and how they would be affected by the upcoming rules. I n response, the revised rule’s preamble includes a discussion on the co-occurrence analy s is of
radon and arsenic: the treatment section of the preamble describes the relationship of treatment
for arsenic with other drinking water rules and how this issue was taken into account in cost

estimates. I n addition, the preamble encourag es sy stems to consider other upcoming rules when
making future plans for monitoring or treatment.

Chapter 8, Economic Impact Analyses 8-10 Arsenic in Drinking Water Rule EA

### Small Systems Variance Technologies and National Affordability Criteria

The Panel recommended the following : include a discussion of the issues surrounding
appropriate adjustment of its national affordability criteria to account for new reg u latory

r e quir e me nts; c onside r r e vising its a ppr oa c h to na tiona l a f f

o r d a b ility c r ite r i a

, to the e x te nt allowed by statutory and reg u latory requirements, to address the concern that the current
cumulative approach for adjusting the baseline household water bills is based on chronolog ical

order rather than risk; and ex amine the data in the 1995 Community W a ter Supply Survey to determine if in-place treatment baselines can be linked with the current annual water bill baseline

i n each of t h e si z e cat eg ori e s for t h e revi sed Arseni c R u l e

.

I n response to these recommendations, the treatment section of the revised rule’s preamble

includes an ex panded discussion about the national affordability criteria and how it may be
adjusted to account for new reg u lations. I n addition, information reg a rding methodolog y and

r a tiona le is a v a ila ble to e x pla i n the na tiona l a f f

o r d a b ility a ppr oa c h

.

Monitoring and Arsenic Species

The P a nel recom m e nded t h e fol l o wi ng : t h at EP A consi d er al l o wi ng S t at es t o use recent

c o mplia nc e monitor i ng da ta to sa tisf y

initia l sa mpling r e quir e me nts or to obta i n a wa ive r ; a n d

that EPA continue to ex plore whether or not to make a reg u latory distinction between org a nic
and inorg a nic arsenic based on compliance costs and other considerations.

I n response, the monitoring section of the rule’s preamble describes the allowance of monitoring

da ta tha t me e t a n a l y tic a l r e quir e me nts a nd ha ve r e por ting limits suf f i c i e n tly be low the r e vise d

MCL and collected after 1990.

Considerations in Setting the MCL

The Panel recommended the following : in performing its oblig ations under SDW A , EPA should

ta ke c o g n iza n c e of the sc ie ntif ic f i nding s, the la r g e sc ie ntif ic unc e r ta intie s, the la r g e pote n tia l
costs (including treatment and waste disposal costs), and the fact that this standard is scheduled
for review in the future; g i ve full consideration to the provisions of the Ex ecutive Order 12866
and to the option of ex ercising the new statutory authority under SDW A §1412(b)(4)(C) and
§1412(b)(6)(A) in the development of the Arsenic Rule; and fully consider all of the “risk

manag e ment” components of its rulemaking effort to ensure that the financial and other impacts
on small sy stems are factored into its decision-making processes. The Panel also recommended
that EPA take into account both quantifiable and non-quantifiable costs and benefits of the
standard and the needs of sensitive sub-populations.

I n response to all these recommendations, EPA has described in detail the factors that were

c onside r e d in se tting in the MCL a nd pr ovide s the r a tiona le f o r

this se le c tion.

Chapter 8, Economic Impact Analyses 8-11 Arsenic in Drinking Water Rule EA

### Applicability of Proposal

The Panel recommended that EPA carefully consider the appropriateness of ex tending the scope
of the rule to non-transient non-community water sy stems (NTNCW Ss).

I n response, EPA has broadened the rule to include NTNCW S s. EPA has described the basis for

this decision in the MCL section of the preamble, which includes a discussion of the incremental
costs and benefits attributable to coverag e of these water sy stems.

Ot her Issues

The P a nel recom m e nded t h at EP A encourag e sm al l sy st em s t o di scuss t h ei r i n frast ruct ure needs

f

o r

c o mply ing with the Ar se nic Rule with the i r pr ima c y a g e n c y to de te r mine the i r e lig ibility f

o r Drinking W a ter State Revolving F und (DW S RF ) loans, and if elig ible, to ask for assistance in
apply i ng for the loans. I n response, the UMRA analy s is has been ex panded to discuss funding
options for small sy stems and to encourag e sy stems to be proactive in communicating with their
pri m acy ag ency

.

Re g a r d ing he a lth e f f

e c t s, the Pa ne l r e c o mme nde d the f o llowing : f u r t he r e v a l ua te the Uta h study
and its relationship to the studies on which the NRC report was based and g i ve it appropriate

wei g ht i n t h e ri sk assessm ent for t h e revi sed arseni c st andard; and ex am i n e t h e NR C

r e c o mme nda tions in the lig ht of the unc e r ta intie s a ssoc i a t e d with the r e por t’ s r e c o mme nda tions,
and any new data that may not have been considered in the NRC report. I n response to these

r e c o mme nda tions, the be ne f its a n a l y s is inc l ude s a disc ussion of the qua lita tive be ne f its

evaluation and use of research data.

8.2.4 S mall Sy st em A f f o rdabilit y

Section 1415(e)(1) of SDW A allows States to g r ant variances to small water sy stems (i.e.,

sy stems having fewer than 10,000 customers) in lieu of comply ing with an MCL if EPA
determines that there are no nationally affordable compliance technolog ies for that sy stem

siz e /water quality combination. The sy stem must then install an EPA-listed variance treatment
technolog y (§1412(b)(15)) that makes prog ress toward the MCL

, if not necessarily reaching it.
To list variance technolog ies, three showing s must be made:

( 1 ) EPA must de te r mine

, on a na tiona l le ve l, tha t the r e a r e no c o mplia nc e technolog ies that are affordable for the g i ven small sy stem siz e categ ory / source

wa te r qua lity c o mbina tion.

(2) I f there is no nationally affordable compliance technolog y

, then EPA must identify
a variance technolog y that may not reach the MCL but that will allow small

sy ste m s to ma ke pr og r e ss towa r d the MCL ( it must a c h ie ve the ma x imum
reduction affordable). This technolog y must also be listed as a small sy stems variance technolog y by EPA in order for small sy stems to be able to rely on it for

reg u latory purposes.

Chapter 8, Economic Impact Analyses 8-12 Arsenic in Drinking Water Rule EA

### (3) EPA must make a finding on a national level, that use of the variance technolog y would be protective of public health.

S t at es m u st t h en m a ke a si t e -speci fi c det e rm i n at i on for each sy st em as t o whet her or not t h e

sy ste m c a n a f f

o r d to me e t the MCL ba se d on Sta t e

- de ve lope d a f f

o r d a b ility c r ite r i a

. I f the Sta t e
de te r mine s tha t c o mplia nc e is not a f f

o r d a b le f o r

the sy ste m , it ma y g r a n t a va r i a n c e

, but it must
establish terms and conditions, as necessary , to ensure that the variance is adequately protective

of human health.

I n the Ag ency ’s draft national-level affordability criteria published in the Aug u st 6, 1998 Federal

Register , EPA discussed the affordable treatment technolog y determinations for the contaminants

reg u lated before 1996. The national-level affordability criteria were derived as follows. F i rst an

“ a f f

o r d a b ility thr e shold” wa s c a l c u la te d. The a f f

o r d a b ility thr e shold wa s ba se d on the tota l
annual household water bill as a percentag e of household income. I n developing this threshold
value, EPA considered the percentag e of median household income spent by an averag e household on comparable g oods and services such items as housing (28 percent), transportation
(16 percent), food (12 percent), energ y 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).

Anothe r of the ke y f

a c t or s tha t EPA use d to se le c t a n a f f

o r d a b ility thr e shold wa s c o st comparisons with other risk reduction activities for drinking water. Section 1412(b)(4)(E)(ii) of

the SDW A identifies both point-of-entry and point-of-use devices as options for compliance
technolog ies. EPA ex amined the projected costs of these options. EPA also investig ated the
costs associated with supply i ng bottled water for drinking and cooking purposes. The median

inc o me pe r c e n ta g e s tha t we r e a ssoc i a t e d with the s e r i sk r e duc tion a c tivitie s we r e : POE ( > 2.5
percent), POU (2 percent) and bottled water (> 2.5 percent).

B a sed on the foreg o ing analy s is, EPA developed an affordability criteria of 2.5 percent of median household income, or about $750, for the affordability threshold (EPA, 1998). The median water
bill for households in each small sy stem categ ory was then subtracted from this threshold to

determine the additional ex penditure per household that was considered affordable for new

treatment. This difference is referred to as the “available ex penditure marg in.” B a sed on EPA’s
1995 Community W a ter Sy stem Survey , median water bills were about $250 per y ear for small

sy stem customers. Thus, an averag e available ex penditure marg in of up to $500 per y ear per household was considered affordable for the contaminants reg u lated before 1996. EPA nex t identified treatment technolog ies for all pre-1996 contaminants with averag e per household costs below $500 per y ear. Therefore, it was not necessary to list any small sy stem variance
technolog ies for ex isting contaminant rules.

Apply i ng this criterion to the case of arsenic in drinking water, EPA has determined that
affordable technolog ies ex ist for all sy stem siz e categ ories and has therefore not identified a
variance technolog y for any sy stem siz e or source water combination at an MCL of 10 μg /L (see

Ex hibit 8-4). I n other words, annual household costs after installation of the compliance
technolog y are projected to be below the available affordability threshold for all sy stem siz e
categ ories for MCL s of 3, 5, 10, and 20 μg /L

.

Chapter 8, Economic Impact Analyses 8-13 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 4

M ean A nnual Cost s t o Househol ds Serv ed by CWSs, by Si ze Cat e gory

MC L ( μ g/ L)
Sy s t e m Si z e

3 5 10 20

<1 0 0 $3 17

. 0 0 $ 3 1 8

. 26 $3 26

. 8 2 $ 3 5 1

. 15

10 1-5 0 0 $1 66

. 9 1 $ 1 6 4

. 02 $1 62

. 5 0 $ 1 6 6

. 72

50 1-1

, 00 0 $7 4. 8 1 $7 3. 1 1 $7 0. 7 2 $6 8. 2 4

1

, 00 1- 3

, 30 0 $6 3. 7 6 $6 1. 9 4 $5 8. 2 4 $5 4. 3 6

3, 3 0 1

- 10

, 000 $4 2. 8 4 $4 0. 1 8 $3 7. 7 1 $3 4. 6 3

10

, 0 0 1 -5 0, 00 0 $3 8. 4 0 $3 6. 0 7 $3 2. 3 7 $2 9. 0 5

50

, 0 0 1 -1 00, 0 0 0 $3 1. 6 3 $2 9. 4 5 $2 4. 8 1 $2 2. 6 3

10 0, 0 0 1

- 1, 00 0, 0 0 0 $2 5. 2 9 $2 3. 3 4 $2 0. 5 2 $1 9. 2 6

>1 ,0 0 0 ,0 0 0 $7

. 4 1 $ 2

. 79 $0

. 8 6 $ 0

. 15

A ll c a t e g o r i e s $4 1. 3 4 $3 6. 9 5 $3 1. 8 5 $2 3. 9 5



### EP A recog n i z es t h at i ndi vi dual wat e r sy st em s m a y have hi g h er t h an averag e t r eat m e nt cost s, fewer than averag e households to absorb these costs, or lower than averag e incomes, but believes
that the affordability criteria should be based on characteristics of ty pical sy stems and should not
address situations where costs mig ht be ex tremely hig h or low or ex cessively burdensome. EPA

bel i e ves t h at t h ere are ot her m echani s m s t h at m a y address t h ese si t u at i ons t o a cert a i n ex t e nt

. I n

any case, EPA believes that small sy stem variances should be the ex ception and not the rule.

EPA ex pects the available ex penditure marg in to be lower than $500 per household per y ear for

the Arsenic Rule because some sources of data, for ex ample the Current P opulation S u rvey

, indicate that water rates are currently increasing faster than median household income. Thus, the
“baseline” for annual water bills will rise as treatment is installed for compliance with

reg u lations promulg a ted after 1996, but before the Arsenic Rule is promulg a ted.

EP A not es, however, t h at hi g h wat e r cost s are oft e n associ at ed wi t h sy st em s t h at have al ready
installed treatment to comply with an NPDW R. Such in-place treatment facilities may facilitate
compliance with future standards. EPA’s approach to establishing the national-level
affordability criteria did not incorporate a baseline for in-place treatment technolog y

. Assuming
that sy stems with hig h baseline water costs would need to install a new treatment technolog y to

c o mply with a n NPDWR ma y thus ove r e stima te the a c t ua l c o sts f o r

some sy ste m s.

To inve stig a t e this issue

, dur ing the de r i va tion of the na tiona l- le ve l a f f

o r d a b ility c r ite r i a

, EPA

ex amined a g r oup of five small surface water sy stems with annual water bills above $500 per
household per y ear. All of these sy stems had installed disinfection and filtration technolog ies to

com p l y wi t h t h e S u rface W a t e r Treat m e nt R u l e

. I f t h ese sy st em s were requi red t o i n st al l

Chapter 8, Economic Impact Analyses 8-14 Arsenic in Drinking Water Rule EA

### treatment to comply with the revised arsenic standard, modification of the ex isting processes would be much more cost-effective than adding a new technolog y

. As a result, because these

sy stems have already made the investment in treatment technolog y

, and the cost is incorporated
into current annual household water bills, costs to the household may not increase substantially

.

I n stalling new technolog ies may interfere with in-place treatment or require additional treatment
to address side effects, which will increase costs over the arsenic treatment technolog y base

cost s. For ex am pl e, EP A assum e d t h at C W S s woul d put corrosi on cont rol i n pl ace when t h e percent removal required was g r eater than 90 percent.

EPA be lie ve s tha t the r e is a nothe r me c h a n ism in the SDWA to a ddr e ss c o st impa c t s on sma l l

sy stems composed primarily of low-income households. Sy stems that meet criteria established
by the State could be classified as disadvantag ed communities under §1452(d) of the SDWA.
They can receive additional subsidiz ation under DW SRF

, including forg iveness of principal.

Under DW SRF

, States must provide a minimum of 15 percent of the available funds for loans to

sma ll c o mmunitie s a nd ha ve the option of pr oviding up to 30 pe r c e n t of the g r a n t to pr ovide
additional loan subsidies to the disadvantag ed sy stems, as defined by the State.

8.3 C oordination W i th Other Federal Rules

Several F e deral drinking water rules are under development involving treatment requirements
that may relate to the treatment of arsenic for this drinking water rule. Althoug h it is very

dif f i c u lt to de te r mine how c o mplia nc e with the Ar se nic Rule mig ht a f f

e c t c o mplia nc e with othe r drinking water reg u lations, the following briefly describes each rule, the impact the Arsenic Rule

m a y have on t h at rul e , and/ or how each rul e m a y i m p act t h e arseni c st andard. The Arseni c R u l e will be promulg a ted in a similar time frame as the Ground W a ter Rule, the Radon Rule, and the

Microbial and Disinfection B y -Product Rule.

8.3.1 G round W a ter Rule (GW R )

The g o als of the GW R are to: (1) provide a consistent level of public health protection; (2)
prevent waterborne microbial disease outbreaks; (3) reduce endemic waterborne disease; and (4)
prevent fecal contamination from reaching consumers. To ensure public health protection, EP A
has the responsibility to develop a GW R that not only specifies the appropriate use of
disinfection, but also addresses other components of g r ound water sy stems. This g e neral
provision is supplemented with an additional requirement that EPA develop reg u lations
specify ing the use of disinfectants for g r ound water sy stems as necessary

. To meet these
requirements, EPA is working with stakeholders to develop a final GW R by Spring 2001.

The GW R will result in more sy stems using disinfection. I f a sy stem does add a disinfection
technolog y

, it may contribute to arsenic pre-ox idation. This larg ely depends on the ty pe of
disinfection technolog y employ ed. F o r ex ample, if a sy stem chooses a technolog y such as
ultraviolet radiation, it may not affect arsenic pre-ox idation. However, if it chooses chlorination,
it will contribute to arsenic pre-ox idation. Arsenic pre-ox idation from arsenic ( III) t o a r s e n i c ( V )
will enhance the removal efficiencies of the technolog ies. Another option is that sy stems may

use me mbr a ne f iltr a tion f o r

the GWR. I n tha t c a s e

, de pe nding on the size of the me mbr a ne

,

Chapter 8, Economic Impact Analyses 8-15 Arsenic in Drinking Water Rule EA

### some arsenic removal can be achieved. Thus, the GW R is ex pected to alleviate some of the

burden of the Arsenic Rule.

8.3.2 R adon

EPA proposed the Radon Rule in November 1999. One option for compliance with the Radon
Rule that sy stems may employ is coag ulation and assisted microfiltration. This technolog y will

be sufficient to meet the revised arsenic standard as well. Thus, the Radon Rule is ex pected to

alleviate some of the burden of the Arsenic Rule.

8.3.3 M icrobial and Disinfection By -Product Regulations

To control disinfection and disinfection by -products and to streng then control of microbial
pathog ens in drinking water, EPA has developed a g r oup of interrelated reg u lations, as required
by the SDW A

. These reg u lations, referred to collectively as the Microbial Disinfection B y

product (M/DB P ) Rules, are intended to address risk trade-offs between the two different ty pes
of contaminants.

EPA proposed a Stag e 1 Disinfectants/Disinfection B y -Products Rule (DB P R) and I n terim

Enhanced S u rface W a ter Treatment Rule (I ES W T R) in J u ly 1994. EP A issued the final S t ag e 1

DB PR and I E SW TR in November 1998.

The Ag e n c y ha s f i na lize d a nd is c u r r e ntly imple me nting a thir d r u le , the I n f o r m a tion Colle c tion
Rule, that will provide data to support development of subsequent M/DB P reg u lations. These
subsequent rules include a Stag e 2 DB PR and a companion L ong -Term 2 Enhanced Surface

Wa te r Tr e a tme nt Rule ( L T2ESWTR)

.

Stag e 1 DB PR and I E SW TR will primarily affect larg e surface water sy stems; thus, EPA does

not ex pect much overlap with small sy stems treating for arsenic. Stag e 2 DB PR and possibly the

L T 2ESW TR, however, could have sig n ificance as far as arsenic removal is concerned. F o r

sy stems removing DB P precursors, sy stems may use nanofiltration. The use of nanofiltration
would also be relevant for removing arsenic, and as a result, would ease some burden when

sy ste m s imple me nt the s e la te r r u le s.

8.4 M inimization of Economic Burden

The revised Arsenic Rule includes several provisions that will insure that the economic burden to

water sy stems is minimiz ed, while still ensuring that the public health objectives of the rule are

met. F i rst, the rule is developed around the concept of a performance targ et known as the

ma x imum c onta mina n t le ve l ( M CL )

. Ra the r tha n pr e s c r ibe a sing le tr e a tme nt te c hnique tha t

must be insta lle d in a ll wa te r sy ste m s

, EPA is only requiring those sy stems that currently provide
finished water with an arsenic concentration above the targ et to undertake or modify treatment.
As seen above, this will ex clude the vast majority of sy stems from having to undertake any

additional treatment under the revised Arsenic Rule. I n addition, if a sy stem does have to
undertake or modify treatment, EPA is allowing sy stems to choose from a broad list of

Chapter 8, Economic Impact Analyses 8-16 Arsenic in Drinking Water Rule EA

### technolog ies and is encourag ing sy stems to choose the treatment technique that minimiz es their

tota l c o sts.

Second, EPA is allowing States to g r ant nine-y ear monitoring waivers to those sy stems that have
a history of arsenic monitoring results below the revised MCL

, and that do not show a substantial

risk of future arsenic contamination. This provision of the rule will further reduce the cost to

sy stems that currently provide finished water with low arsenic concentrations.

F i nally , EPA is allowing small sy stems with finished water concentrations above the revised

MCL to install POU technolog ies. This option will further allow small sy stems to minimiz e their

tota l c o st of c o mplia nc e with the r e vise d r u le

.

8.5 U nfunded Mandates Reform A c t

Title I I of the Unfunded Mandates Reform Act of 1995 (UMRA), P.L

. 104-4, establishes
requi rem e nt s for Federal ag enci es t o assess t h e effect s of t h ei r reg u l a t o ry act i ons on S t at e, l o cal

, and Tribal g overnments, and the private sector. Under UMRA Section 202, EPA g e nerally must prepare a written statement, including a cost-benefit analy s is, for proposed and final rules with

“ F e d e r a l ma nda te s” tha t ma y r e sult in e x pe nditur e s to Sta t e

, loc a l , a nd Tr iba l g ove r n me nts, in the

ag g r eg ate, or to the private sector, of $100 million or more in any one y ear.

B e fore promulg a ting an EPA rule for which a written statement is needed, Section 205 of the
UMRA g e nerally requires EPA to identify and consider a reasonable number of reg u latory
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

othe r tha n the le a s t c o stly , most c o st- e f f

e c tive

, or le a s t bur de nsome a lte r n a tive if the

Administr a t or publishe s a n e x pla n a tion why the mor e “ c o stly ” a lte r n a tive wa s pr e f e r

r e d f o r

the

fi nal rul e

.

Pr ior to e s ta blishing a n y r e g u la tor y r e quir e me nts tha t ma y sig n if ic a n tly or unique ly a f f

e c t sma l l

g overnments, including Tribal g overnments, EPA must develop a small g overnment ag ency plan

under Section 203 of the UMRA. The plan must provide for notify i ng potentially affected small

g ove r n me nts; e n a b ling of f i c i a l s of a f f

e c t e d sma ll g ove r n me nts to ha ve me a n ing f ul a nd time ly
input in the development of EPA reg u latory proposals with sig n ificant F e deral interg overnmental
mandates; and informing

, educating

, and advising small g overnments on compliance with the

reg u l a t o ry requi rem e nt s.

EPA ha s de te r mine d tha t this r u le c onta i ns a F e de r a l ma nda te tha t ma y r e sult in e x pe nditur e s of $100 million or more for State, local, and Tribal g overnments, in the ag g r eg ate and the private
sector in any one y ear. According l y

, under Section 202 of the UMRA, EPA is oblig ated to

pr e p a r e a wr itte n sta t e m e n t a ddr e ssing :

Chapter 8, Economic Impact Analyses 8-17 Arsenic in Drinking Water Rule EA

### 1. The a u thor izing le g i sla tion;

2. C o st -benefi t anal y s i s i n cl udi ng an anal y s i s of t h e ex t e nt t o whi c h t h e cost s of S t at e, l o cal

,

a nd Tr iba l g ove r n me nts will be pa id f o r

by the F e de r a l g ove r n me nt;

3. Estimates of future compliance costs and disproportionate budg etary effects;

4. Macro-econom i c effect s;

5. A summary of EPA’s consultation with State, local, and Tribal g overnments and their
concerns, including a summary of the Ag ency ’s evaluation of those comments and

concerns; and

6. I d entification and consideration of reg u latory alternatives and the selection of the least

cost l y , m o st cost -effect i v e or l east burdensom e al t e rnat i v e t h at achi e ves t h e obj ect i v es of

the r u le

.

The leg i slative authority for the Arsenic Rule is discussed in Chapter 2. I t ems two throug h five

are addressed below, with the ex ception of future compliance costs, which are discussed in
Chapter 6. Reg u latory alternatives, the last item, are addressed in Chapters 3, 6, and 7.

8.5.1 S ocial C o st s and B e nef i t s

Chapters 5, 6, and 7 contain a detailed cost-benefit analy s is in support of the Arsenic Rule. At a
seven percent discount rate, the Arsenic Rule is ex pected to have a total annualiz ed cost of

$792.1 million for a MCL of 3 μg /L , $471.7 million for a MCL 5 μg /L , $205.6 million for a

MCL of 10 μg /L , and $76.5 million for a MCL of 20 μg /L

.

EPA e s tima te s tha t the Ar se nic Rule will ha ve tota l he a lth be ne f its a s a r e sult of a voide d bla dde r and lung cancer cases of approx imately $213.8 to $490.9 million if the MCL were set at 3 μg /L

, $191.1 to $355.6 million if the MCL were set at 5 μg /L , $139.6 to $197.7 million if the MCL
were set at 10 μg /L , and $66.2 to $75.3 million if the MCL were set at 20 μg /L . These monetized
health benefits of reducing arsenic ex posures in drinking water are attributable to the reduced
incidence of fatal and non-fatal bladder cancer and lung cancer. Currently under baseline
assumptions (no control of arsenic ex posure), there are annual fatal cancers and non-fatal cancers

associated with arsenic ex posures throug h CW Ss. At an arsenic MCL level of 3 μg /L , an estimated 33 to 74 fatal cancers and 25 to 64 non-fatal cancers per y e ar are prevented; at a
arsenic level of 5 μg /L , an estimated 29 to 54 fatal cancers and 22 to 47 non-fatal cancers per

y ear are prevented; at 10 μg /L , 21 to 30 fatal and 16 to 26 non-fatal cancers per y ear are prevented; and at 20 μg /L , 10 to 11 fatal and approx imately 9 non-fatal cancers per y ear are prevented. A more detailed discussion of the total cancer risk and health benefits calculation

may be found in Chapter 5, “B enefits Analy s is.”

I n addition to quantifiable benefits, in Chapter 5, EPA has identified manypotential nonquantifiable benefits associated with reducing arsenic ex posures in drinking water. These

pote n tia l be ne f its a r e not a b le to be qua ntif ie d a t this time , but ma y inc l ude r e duc e d r i sk of skin

Chapter 8, Economic Impact Analyses 8-18 Arsenic in Drinking Water Rule EA

### cancer and numerous non-cancerous health effects. I n addition, certain non-health related
benefits may ex ists, such as ecolog i cal improvements and an increase in consumers’ perception
of drinking water.

8.5.2 S t a t e A d minist rat i v e C o st s

Sta t e s will inc u r a

r a ng e of a d ministr a tive c o sts in c o mply ing with the Ar se nic Rule

. Administr a tive c o sts c a n inc l ude pr og r a m ma na g e me nt, inspe c tions, a nd e n f o r c e m e n t a c tivitie s. EPA estimates that the total annual costs of State administrative activities for compliance with

the MCL at a seven percent discount rate are approx imately $1.7 million for an MCL of 3 μg /L

, $1.4 million for an MCL of 5 μg /L , $1.2 million for an MCL of 10μg / L

, and $1.0 million for an

MCL of 20μg / L

.

Various F e deral prog rams ex ist to provide financial assistance to State, local, and Tribal

g overnments in comply ing with this rule. The F e deral g overnment provides funding to States
that have a primary enforcement responsibility for their drinking water prog rams throug h the

Public W a ter Sy stems Supervision (PW SS) Grants prog ram. Additional funding is available
from other prog rams administered either by EPA or other F e deral ag encies. These include the
Drinking W a ter State Revolving F und (DW S RF ) and Housing and Urban Development’s
Community Development B l ock Grant Prog ram. F o r ex ample, the SDW A authoriz es the

Administr a t or of the EPA to a w a r d c a p ita liza tion g r a n ts to Sta t e s , whic h in tur n c a n pr ovide lowcost loans and other ty pes of assistance to elig ible public water sy stems. The DW SRF also
assists public water sy stems with financing the costs of infrastructure needed to achieve or

ma inta in c o mplia nc e with SDWA r e quir e me nts. Ea c h Sta t e will ha ve c onside r a b le f l e x ibility to determine the desig n of its prog ram and to direct funding toward its most pressing compliance
and public health protection needs. States may also, on a matching basis, use up to ten percent of

their DW S R F allotments for each fiscal y ear to assist in running the S t ate drinking water

prog ram.

Unde r PWSS Pr og r a m Assista n c e Gr a n ts, the Administr a t or ma y ma ke g r a n ts to Sta t e s to c a r r y out public water sy stem supervision prog rams. One State use of these funds is to develop
primacy prog rams. States may “contract” with other State ag encies to assist in the development
or implementation of their primacy prog ram. However, States may not use prog ram assistance

g r ant funds to contract with reg u lated entities (i.e., water sy stems). PWSS Grants may be used
by States to set up and administer a State prog ram that includes such activities as public
education, testing

, training , technical assistance, development and administration of a
remediation g r ant and loan or incentive prog ram (ex c ludes the actual g r ant or loan funds), or
other reg u latory or non-reg u latory measures.

8.5.3 Future Compliance Costs and Disproportionate Budgetary Effects

To meet the requirement in Section 202 of the UMRA, EPA analy z ed future compliance costs
and possible disproportionate budg etary effects of the MCL options. The Ag ency believes that

the cost estimates, shown in Ex hibit 8-5 and discussed in more detail in Chapter 6, accurately

charact eri z e fut u re com p l i a nce cost s of t h e revi sed rul e

.

Chapter 8, Economic Impact Analyses 8-19 Arsenic in Drinking Water Rule EA

### W ith reg a rd to the disproportionate impacts, EPA considered available data sources in analy z ing
the disproportionate impacts upon g e og raphic or social seg m ents of the nation or industry

. To

the ex tent that there may be disproportionate impacts to low-income or other seg m ents of the
population, EPA will prepare a small entity compliance g u ide, a monitoring /analy tical manual,
and a small sy stems technolog y manual that will assist the public and private sector. To fully
consider the potential disproportionate impacts of this revised rule, EPA also developed three

other measures:

( 1 ) R e v ie wing the impa c t s on sma ll ve r s us la r g e sy ste m s; (2) R eviewing the costs to public versus private water sy stems; and

(3) R eviewing the household costs for the revised rule.

The first measure, the national impacts on small versus larg e sy stems, is shown in Ex hibit 8-5.
Small sy stems are defined as those sy stems serving 10,000 people or less, and larg e sy stems are those sy stems serving more than 10,000 people.

The second measure of disproportionate impacts evaluated is the relative total costs to public
versus private water sy stems, by siz e

. Ex hibit 8-5 also presents the annual sy stem level costs for
public and private sy stems by sy stem siz e categ ory for MCL s of 3 μg /L , 5 μg /L , 10 μg /L , and 20

μg /L

. The costs are slig htly lower for private sy stems across sy stem siz e s for all options. F o r

ex ample, for sy stems serving less than 100 people at the 10 μg /L MCL public sy stem costs are $7,948, and private sy stem costs are $6,335.

Chapter 8, Economic Impact Analyses 8-20 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 5

A

v erage A nnual Cost per CWS Exceedi ng t h e M C L, by O w nershi p

S y s t em S i z e Tr e a t m e nt a nd M o n i t o r i n g C o s t s T o t al C o s t

P u b l ic P r iv a t e A ll Sy s t e m s

MC L = 3 μ g/ L

< 100

101- 500

501- 1, 00 0

1, 001- 3, 300

3, 301- 10

, 000

10, 001- 1

, 000, 000

> 1

, 000, 000 8, 020 $

15, 319 $

25, 069 $

61, 375 $

133, 297 $

648, 756 $

10, 360, 9 3 3 $ 6

, 3 8 8 $

1 2

, 0 3 3 $

2 1

, 6 5 9 $

5 1

, 6 8 7 $

112, 397 $

621, 841 $

- - $

$

$

$

$

$

$ 6

, 5 4 6

1 3

, 0 4 2

2 3

, 7 2 0

5 8

, 6 7 2

129, 531

644, 176

10, 360, 9 3 3

MC L = 5 μ g/ L

< 100

101- 500

501- 1, 00 0

1, 001- 3, 300

3, 301- 10

, 000

10, 001- 1

, 000, 000

> 1

, 000, 000 8, 065 $

14, 845 $

24, 406 $

59, 998 $

124, 483 $

601, 335 $

4, 129, 33 8 $ 6

, 3 8 4 $

1 1

, 7 6 2 $

2 1

, 1 7 5 $

4 9

, 0 5 5 $

103, 388 $

584, 831 $

- - $

$

$

$

$

$

$ 6

, 5 5 1

1 2

, 7 1 2

2 3

, 1 4 6

5 6

, 9 1 1

120, 621

598, 488

4, 129, 33 8

M C L = 10 μ g/ L

< 100

101- 500

501- 1, 00 0

1, 001- 3, 300

3, 301- 10

, 000

10, 001- 1

, 000, 000

> 1

, 000, 000 7, 948 $

14, 503 $

23, 424 $

55, 789 $

114, 790 $

543, 053 $

1, 340, 71 6 $ 6

, 3 3 5 $

1 1

, 3 5 7 $

2 0

, 0 4 2 $

4 6

, 2 4 3 $

98, 138 $

477, 614 $

- - $

$

$

$

$

$

$ 6

, 4 9 4

1 2

, 3 5 8

2 2

, 1 0 0

5 3

, 0 8 6

111, 646

531, 584

1, 340, 71 6

M C L = 20 μ g/ L

< 100

101- 500

501- 1, 00 0

1, 001- 3, 300

3, 301- 10

, 000

10, 001- 1

, 000, 000

> 1

, 000, 000 7, 785 $

13, 814 $

21, 733 $

51, 116 $

105, 155 $

482, 300 $

189, 916 $ 6

, 2 0 9 $

1 1

, 0 6 5 $

1 8

, 8 7 7 $

4 2

, 8 6 9 $

85, 201 $

443, 463 $

- - $

$

$

$

$

$

$ 6

, 3 6 1

1 1

, 9 0 2

2 0

, 5 9 5

4 8

, 7 7 9

101, 374

475, 909

189, 916

* C os t s w e r e c a l c ul at ed at a c o m m er c i al i n t e r e s t r a t e and i n c l ude syst e m

t r eat m ent

, m oni t o r i ng

, and adm i n i s t r at i v e c o s t s ; not e t hat s y s t e m s s e r v

i n g ov er

1 m i l l i on peopl e ar e p ubl i c s u r f ac e w a t e r s y s t em s

.

Chapter 8, Economic Impact Analyses 8-21 Arsenic in Drinking Water Rule EA

### The third measure, household costs, can also be used to g a ug e the impact of a reg u lation and to
determine whether there are disproportionately hig h er impacts in particular seg m ents of the
population. A detailed analy s is of household cost impacts by sy stem siz e is presented in Chapter

6. The costs for households served by public and private water sy stems are presented in Ex hibit

8-6. As ex pected, cost per household increases as sy stem siz e decreases. Cost per household is
usually hig h er for households served by smaller sy stems than larg er sy stems. This holds because

sma lle r sy ste m s pr oduc e le ss wa te r tha n la r g e sy ste m s a nd a r e the r e f or e una ble to utilize
economies of scale. Consequently , each household must bear a g r eater percentag e share of the

sy stem’s costs.

Ex hibit 8-6 presents the costs per household for sy stems ex ceeding the MCL

. For each siz e
categ ory there is a moderate difference in annual cost per household for 3 μg /L , 5 μg /L , 10 μg /L

, and 20 μg /L across source and ownership. I n g e neral, costs per household are hig h er for private

sy stems than for public sy stems. This difference could be attributable to a discrepancy in the cost
of capital for public versus private entities. F o r public sy stems, the cost per household rang es from approx imately $5 to $288 per y ear at 5 μg /L and from approx imately $5 to $285 per y e ar at 10 μg /L ( e x c luding sy ste m s se r v ing mor e tha n one million pe ople )

. F o r pr iva t e sy ste m s, the

rang es are $4 to $317 per y ear, and $4 to $314 per y ear for an MCL of 5 μg /L and 10 μg /L

, respect i v el y

.

To further evaluate the impacts of these household costs, the averag e costs per household were
compared to median household income data for each sy stem-siz e categ ory

. The result of this
calculation, presented in Ex hibit 8-7 for public and private sy stems, indicate a household’s likely

share of incremental costs in terms of its household income. F o r all sy stem siz e s and MCL s

, averag e household costs as a percentag e of median household income are less than one percent.

Among NTNCs, the averag e annual sy stem cost rang es from approx imately $5,000 to $39,000 at

t h e revi sed MC L of 10 μ g / L

. These resul t s for sy st em s ex ceedi n g t h e MC L are present e d i n

Ex hibit 8-8. At 3 μg /L , 5 μg /L , and 20 μg /L , the averag e NTNC sy stem cost rang es from $5,000 to $46,000, $5,000 to $43,000 and $5,000 to $35,000, respectively

. More detail on the costs to

NTNC s at t h ese arseni c concent r at i ons are present e d i n C h apt e r 6.

Chapter 8, Economic Impact Analyses 8-22 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 6

A nnual Compl i a nce Cost s per Househol d f o r
CWSs Exceedi ng M C Ls

Sy s t e m Si z e G r o u n d w at er S u r f a c e W a t e r

P u b lic P r iv a t e P u b lic P r iv a t e

MC L = 3 μ g/ L

< 1 00

101- 500

501- 1, 000

1, 00 1-3, 300

3, 30 1-10, 00 0

10, 0 01-1, 00 0, 000

> 1

, 000, 000 $

$

$

$

$

$ 285. 93

134. 47

79. 1 1

64. 5 0

45. 7 9

40. 7 7

-- 319. 62 $

190. 51 $

7 6

. 6 4 $

8 4

. 3 2 $

6 5

. 4 2 $

3 9

. 6 7 $

-- $

$

$

$

$

$

$ 218. 47

5 4

. 7 5

1 5

. 2 2

5

. 7 7

3

. 7 4

5

. 3 9

7. 41 231. 50 $

7 2

. 5 2 $

1 3

. 9 8 $

7

. 5 2 $

4

. 3 3 $

4

. 6 2 $

- -

MC L = 5 μ g/ L

< 1 00

101- 500

501- 1, 000

1, 00 1-3, 300

3, 30 1-10, 00 0

10, 0 01-1, 00 0, 000

> 1

, 000, 000 $

$

$

$

$

$ 287. 87

130. 86

76. 4 5

62. 5 6

42. 1 8

36. 9 9

-- 316. 80 $

185. 83 $

7 4

. 1 8 $

7 9

. 0 1 $

5 9

. 8 4 $

3 6

. 2 2 $

-- $

$

$

$

$

$

$ 212. 32

5 4

. 0 3

1 4

. 9 1

5

. 6 8

3

. 5 2

5

. 0 0

2. 79 229. 78 $

7 2

. 3 3 $

1 4

. 1 4 $

7

. 0 3 $

4

. 2 3 $

4

. 2 6 $

- -

M C L = 10 μ g/ L

< 1 00

101- 500

501- 1, 000

1, 00 1-3, 300

3, 30 1-10, 00 0

10, 0 01-1, 00 0, 000

> 1

, 000, 000 $

$

$

$

$

$ 285. 03

126. 46

72. 5 1

56. 7 6

38. 0 8

31. 7 2

-- 314. 11 $

180. 21 $

6 9

. 8 7 $

7 3

. 4 2 $

5 5

. 3 5 $

3 0

. 7 8 $

-- $

$

$

$

$

$

$ 214. 23

5 2

. 7 2

1 4

. 2 3

5

. 5 1

3

. 1 3

4

. 5 5

0. 86 229. 02 $

7 1

. 0 1 $

1 3

. 9 3 $

6

. 8 1 $

4

. 0 3 $

3

. 9 9 $

- -

M C L = 20 μ g/ L

< 1 00

101- 500

501- 1, 000

1, 00 1-3, 300

3, 30 1-10, 00 0

10, 0 01-1, 00 0, 000

> 1

, 000, 000 $

$

$

$

$

$ 275. 00

120. 19

66. 0 7

50. 4 4

33. 8 6

26. 5 9

-- 306. 52 $

174. 69 $

6 5

. 3 9 $

6 7

. 2 5 $

4 8

. 0 0 $

2 6

. 0 2 $

-- $

$

$

$

$

$

$ 204. 17

5 1

. 4 2

1 4

. 5 2

5

. 2 1

2

. 8 4

4

. 1 4

0. 15 228. 82 $

6 8

. 9 6 $

1 3

. 3 9 $

6

. 4 8 $

3

. 6 9 $

- $

- -

* C os t s t o h ous ehol ds w e r e c a l c ul at ed at a c o m m erc i al i n t e res t r a t e and i n c l ude s y s t em

t r e a t m ent

, m o n i t o ri ng, and adm i n i s t r at i v e c o s t s ; not e t hat syste m s se r v

i n g o v e r

1 m illio n peopl e are pu bl i c s u rf ac e w a t e r s y s t e m s

.

Chapter 8, Economic Impact Analyses 8-23 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 7

A nnual Compl i a nce Cost s per Househol d f o r CWSs Exceedi ng M C Ls,

as a Percent of M e di an Househol d I n come

Sy s t e m Siz e G r o u n d w at er S u r f ac e Wa t e r

Pu b lic Pr i v a t e P u b lic Pr i v a t e

MC L = 3 μ g/ L

< 1 00

101-500

501-1, 000

1, 0 01- 3, 3 0 0

3, 3 01- 10, 000

10, 001- 1, 000, 00 0

> 1

, 000, 000 0. 7 2 %

0. 3 4 %

0. 2 0 %

0

. 1 6%

0. 1 2 %

0

. 1 0%

- - 0

. 8 1%

0

. 4 8%

0

. 1 9%

0. 2 1 %

0

. 1 7%

0. 1 0 %

- - 0. 5 5 %

0. 1 4 %

0. 0 4 %

0

. 0 1%

0. 0 1 %

0

. 0 1%

0. 0 2 % 0

. 5 8%

0

. 1 8%

0

. 0 4%

0. 0 2 %

0

. 0 1%

0. 0 1 %

- -

MC L = 5 μ g/ L

< 1 00

101-500

501-1, 000

1, 0 01- 3, 3 0 0

3, 3 01- 10, 000

10, 001- 1, 000, 00 0

> 1

, 000, 000 0. 7 3 %

0. 3 3 %

0. 1 9 %

0

. 1 6%

0. 1 1 %

0

. 0 9%

- - 0

. 8 0%

0

. 4 7%

0

. 1 9%

0. 2 0 %

0

. 1 5%

0. 0 9 %

- - 0. 5 4 %

0. 1 4 %

0. 0 4 %

0

. 0 1%

0. 0 1 %

0

. 0 1%

0. 0 1 % 0

. 5 8%

0

. 1 8%

0

. 0 4%

0. 0 2 %

0

. 0 1%

0. 0 1 %

- -

M C L = 10 μ g/ L

< 1 00

101-500

501-1, 000

1, 0 01- 3, 3 0 0

3, 3 01- 10, 000

10, 001- 1, 000, 00 0

> 1

, 000, 000 0. 7 2 %

0. 3 2 %

0. 1 8 %

0

. 1 4%

0. 1 0 %

0

. 0 8%

- - 0

. 7 9%

0

. 4 5%

0

. 1 8%

0. 1 9 %

0

. 1 4%

0. 0 8 %

- - 0. 5 4 %

0. 1 3 %

0. 0 4 %

0

. 0 1%

0. 0 1 %

0

. 0 1%

0. 0 0 % 0

. 5 8%

0

. 1 8%

0

. 0 4%

0. 0 2 %

0

. 0 1%

0. 0 1 %

- -

M C L = 20 μ g/ L

< 1 00

101-500

501-1, 000

1, 0 01- 3, 3 0 0

3, 3 01- 10, 000

10, 001- 1, 000, 00 0

> 1

, 000, 000 0. 6 9 %

0. 3 0 %

0. 1 7 %

0

. 1 3%

0. 0 9 %

0

. 0 7%

- - 0

. 7 7%

0

. 4 4%

0

. 1 6%

0. 1 7 %

0

. 1 2%

0. 0 7 %

- - 0. 5 1 %

0. 1 3 %

0. 0 4 %

0

. 0 1%

0. 0 1 %

0

. 0 1%

0. 0 0 % 0

. 5 8%

0

. 1 7%

0

. 0 3%

0. 0 2 %

0

. 0 1%

0. 0 0 %

- -

* C os t s t o hous e hol d w e r e c a l c ul at ed at a c o m m erc i al i n t e res t rat e a nd i n c l ude syste m

t r e a t m e n t

, m oni t o ri ng, an d adm i n i s t r at i v e c o s t s ; m edi a n hous ehol d i n c o m e i n M a y 1999

w a s $3 9, 648 updat ed f r om t he 1998 annual m edi an hous eh ol d i n c o m e f r om t h e C ens us

B u r eau

.

Chapter 8, Economic Impact Analyses 8-24 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 8

T o t a l A nnual NT NC T r eat ment Cost s at M C L 10 μg/ L by Sy st em Serv i ce T y pe ( 3 % Di scount Rat e )

S e r v i c e A r e a Ty pe # o f S y

s t e m s

A

b o

v

e t h e M C L A v

er a g e

P opul a t i on

Se r v

e d Pe r Sy s t e m A v

e r a g e A nnua l

S

y

st

e m C o st A nnua l

Na t i o n a l Co s t s

D

a

y c ar e C e nt er s

H i g h w

a

y

R

e

s t A r e a

s

H o

t e l s / M o t e l s

I n te r s ta te

C

a r r i e r s

M e d i ca l F a cilit i e s

M o bi l e H o m e P a r k s

R

e s t a u r a n

t s

S c ho ol s

S e r v i c e S t at i ons

S u m m e r C

a m p s

W a t e r

W h ol es al e r s

A g r i c u l t u r a l P r od uc t s / S er v i c e s

A i r p a r k s

C

o ns t r uc t i o n

C

h u r c h e s

C

a m p gr

ou nd s / R V

P a r k s

F i r

e

D

e pa r t m e n t s

F e

der al P a r k s

F o r e

s t S e r v i c e

Gol f an d C o un t r y

C l u b s

La nd fi l l s

M i ni n g

A m u s e m en t P a r k s

M ilit a r y

B a s e s

M i gr an

t La bo r C

a m p s

M i s c

. R e c r e

a

t i on S e r v i c e s

N u r s i n g H o m e s

O

ffi c e P a r k s

P r i s on s

R

e

t a i l e r s ( N on

- f o o

d

r

e l a t e d )

R

e

t a i l e r s ( F oo d r

e l a t ed)

S t at e P a r k s

N o n

- W a t e r

U

t ilit ie s

M a nu f a

c t u r i n g: F o o d

M a n u fa c t ur i n g : N o n

- Food

T

O

TA L 4 3

1

1 9

1 5

2 0

6

2 2

4

48

3

2

1 4

2 0

5

5

12

7

2

1

6

6

4

6

8

5

2

14

7

5 1

4

3 7

8

4

2 6

4 1

20

5

1

, 0 8

0 7 6

4 0

7

1 3

3

1 2 3

3 9

3

1 8

5

3 7

0

3

5

8

2 3

0

1 4

6

1 7

3

7 6

6 0

5 3

50

16

0

98

39

42

1 0 1

44

1 1 3

4 1 8

3 9

5

63

87

1 0

7

1 3

6

1, 82 0

1 7

4

3

2

2

1 6

5

1 7

0

3 7

2

1 6

8 $ 5, 16 8

$

5, 37 7
$5

, 9 56
$

5

, 0 4 7
$ 1 2

, 1 7 4
$ 6, 38 7
$5

, 1 03
$ 6, 81 8
$5

, 1 68

$ 6, 12 4
$1 4, 62 8

$ 6, 01 2
$

5, 03 4
$

4, 73 3
$5

, 1 77
$ 6

, 1 0 4
$5

, 9 38

$5

, 2 45
$4

, 7 83
$

5, 54 2
$5

, 1 76
$5

, 5 72
$

5, 84 8
$ 9

, 0 9 5
$5

, 4 52

$5

, 0 27
$ 7, 29 8
$5

, 3 10
$ 3

9

, 3 8 0
$

5, 09 7
$5

, 2 05
$

5, 15 3
$

5

, 6 2 7
$ 7, 56 6
$5

, 7 80 $ 22 2, 84 6

$

4, 29 9
$1 11

, 4 20
$ 7

7 ,2 0 7
$

2 3 8

, 1 3 3
$ 35

, 4 05
$1 13

, 6 92
$ 3, 05 7, 57 8
$1 4, 59 9

$ 15

, 0 14
$

2 0 7

, 3 9 8

$ 11 7, 93 0

$

27

, 1 01
$

24

, 9 74
$6

3, 47 1
$

4

0

, 0 1 7
$1 2, 97 7
$5

, 5 92
$2 7, 27 8
$ 34

, 2 63
$2 1, 51 7
$3

5, 34 0
$

49

, 5 58
$

4

6

, 0 5 3
$9

, 5 89

$6

9, 39 7
$

50

, 5 67
$2 68

, 8 64
$1 40

, 6 29
$ 18 8, 79 6

$3

9, 39 4
$

22

, 7 94
$ 1 4 9

, 0 6 9

$ 30 9, 70 7
$1

, 1 84

, 5 05

$7

, 0 36

, 9 73

Chapter 8, Economic Impact Analyses 8-25 Arsenic in Drinking Water Rule EA

### 8.5.4 M acroeconomic Effects

As required under UMRA Section 202, EPA is required to estimate the potential macroeconomic effects of the reg u lation. These include effects on productivity , economic g r owth, full
employ ment, creation of productive jobs, and international competitiveness. Macro-economic
effects tend to be measurable in nationwide econometric models only if the economic impact of
the reg u lation reaches 0.25 percent to 0.5 percent of Gross Domestic P r oduct (GDP ). I n 1998, real GDP was $7,552 billion; thus, a rule would have to cost at least $18 billion annually to have

a m easurabl e effect

. A reg u l a t i on wi t h a sm al l e r ag g r eg at e effect i s unl i k el y t o have any
measurable impact unless it is hig h ly focused on a particular g e og raphic reg i on or economic

sector. The macro-economic effects on the national economy from the Arsenic Rule should be

neg lig ible based on the fact that, assuming 100 percent compliance with an MCL

, the total
annual costs are approx imately $792 million at the 3 μg /L level, $472 million at the 5 μg /L level, $206 million at the 10 μg /L level, and $77 million at the 20 μg /L level (at a seven percent
discount rate).

8.5.5 C onsultation w i th State, Local, and Tribal Gov e rnments

Under UMRA section 204, EPA is to provide a summary of its consultation with elected

represent a t i v es (or t h ei r desi g n at ed aut hori z ed em pl oy ees) of affect ed S t at e, l o cal , and Tri b al

g ove r n me nts in this r u le ma king

. EPA initia te d c onsulta tions with g ove r n me nta l e n titie s a nd the
private sector affected by this rulemaking throug h various means. This included five stakeholder
meeting s announced in the Federal Register and open to any one interested in attending in person
or by phone, and presentations at meeting s of the American W a ter W o rks Association (AW W A),
the Association of State Drinking W a ter Administrators (ASDW A ), the Association of California

Wa te r Ag e n c i e s ( A CWA) , a nd the Assoc i a tion of Me tr opolita n Wa te r Ag e n c i e s ( A MWA)

. Pa r tic ipa n ts in EPA’ s sta k e holde r me e ting s a l so inc l ude d r e pr e s e n ta tive s f r o m the Na tiona l Rur a l

W a ter Association, AMW A , ASDW A, AW W A , ACW A , Rural Community Assistance Prog ram, State departments of environmental protection, State health departments, State drinking water

prog rams, and a Tribe. EPA also made presentations at Tribal meeting s in Nevada, Alaska, and

California.

To a ddr e ss the Ar se nic Rule ’ s impa c t on sma ll e n titie s, the Ag e n c y c onsulte d with
representatives of small water sy stems and convened a S m all B u siness Advocacy Review P a nel
in accordance with the Reg u latory F l ex ibility Act (RF A ) as amended by the Small B u siness

Re g u la tor y Enf o r c e m e n t F a ir ne ss Ac t ( S B R EF A)

. Two of the sma ll e n tity r e pr e s e n ta tive s we r e elected officials from local g overnments. EPA also invited State drinking water prog ram representatives to participate in a number of workg r oup meeting s

. I n addition to these
consultations, EPA participated in and g a ve presentations at AW W A ’s Technical W o rkg r oup for

Arsenic. State public health department and drinking water prog ram representatives, drinking

water districts, and ASDW A participated in the Technical W o rkg r oup meeting s . A summary of
State, local, and Tribal g overnment concerns on this rulemaking is shown in the nex t section.

I n order to inform and involve Tribal g overnments in the rulemaking process, EPA staff attended

the 16 th 

### Annual Consumer Conference of the National I ndian Health B o ard on October 6-8, 1998,
in Anchorag e, Alaska. Over 900 attendees representing Tribes from across the country were in

Chapter 8, Economic Impact Analyses 8-26 Arsenic in Drinking Water Rule EA

### attendance. During the conference, EPA conducted two workshops for meeting participants.
The objectives of the workshops were to present an overview of EPA’s drinking water prog ram, solicit comments on key issues of potential interest in upcoming drinking water reg u lations, and

to solic it a dvic e in ide n tif y i ng a n e f f

e c tive c onsulta tive pr oc e ss with Tr ibe s f o r

the f u tur e

.

EPA, in conjunction with the I n ter Tribal Council of Ariz ona (I TCA), also convened a Tribal
consultation meeting on F e bruary 24-25, 1999, in L a s Veg a s, Nevada, to discuss way s to involve
Tribal representatives, both Tribal council members and tribal water utility operators, in the
stakeholder process. Approx imately 25 representatives from a diverse g r oup of Tribes attended

the two- da y me e ting

. Me e ting pa r tic ipa n ts inc l ude d r e pr e s e n ta tive s f r o m the f o llowing Tr ibe s : Cherokee Nation, Nez p erce Tribe, J i carilla Apache Tribe, B l ackfeet Tribe, Seminole Tribe of

F l orida, Hopi Tribe, Chey enne River Sioux Tribe, Menominee I ndian Tribe, Tulalip Tribes,
Mississippi B a nd of Choctaw I ndians, Narrag a nsett I ndian Tribe, and Yakama Nation.

The ma jor me e ting obje c tive s we r e to:

(1) I dentify key issues of concern to Tribal representatives;

(2) S olicit input on issues concerning current Office of Ground W a ter and Drinking

W a t e r reg u l a t o ry effort s; (3) S olicit input and information that should be included in support of future drinking

wa te r r e g u la tions; a nd

(4) P rovide an effective format for Tribal involvement in EPA’s reg u latory
development process.

EPA staff also provided an overview on the forthcoming Arsenic Rule at the meeting

. The
presentation included the health concerns associated with arsenic, EPA’s current position on
arsenic in drinking water, the definition of an MCL

, an ex planation of the difference between
point-of-use and point-of-entry treatment devices, and specific issues for Tribes. The following
questions were posed to the Tribal representatives to beg i n discussion on arsenic in drinking

water:

(1) W hat are the current arsenic levels in y our water sy stems?
( 2 ) W ha t a r e Tr iba l wa te r sy ste m s’ a f f

o r d a b ility issue s in r e g a r d to a r se nic ?
(3) D oes y our Tribe use well water, river water, or lake water?

( 4 ) D oe s y our Tr ibe pur c h a s e wa te r f

r o m a nothe r dr inking wa te r utility ?

The summary for the F e bruary 24-25, 1999, meeting was sent to all 565 F e derally recog n iz ed

Tr ibe s in the Unite d Sta t e s

.

EPA also conducted a series of workshops at the Annual Conference of the National Tribal
Environmental Council, which was held on May 18-20, 1999, in Eureka, California.
Representatives from over 50 Tribes attended all, or part, of these sessions. The objectives of the
workshops were to provide an overview of forthcoming EPA reg u lations affecting water sy stems; discuss chang e s to operator certification requirements; discuss funding for Tribal water sy stems; and discuss innovative approaches to reg u latory cost reduction. Meeting summaries for EPA’s

Tr iba l c onsulta tions a r e a v a ila ble in the public doc ke t f o r

this r u le ma king

.

Chapter 8, Economic Impact Analyses 8-27 Arsenic in Drinking Water Rule EA

### 8.5.6 S tate, Local, and Tribal Gov e rnment Concerns

State and local g overnments raised several concerns, including the hig h costs of the rule to small

sy stems; the burden of revising the State primacy prog ram; the hig h deg r ee of uncertainty
associated with the benefits; and the hig h costs of including non-transient non-community water

sy stems (NTNCW Ss). EPA modified the revision of State primacy in order to decrease the
burden of the revised arsenic reg u lation in response to State concerns, to minimize paperwork

and documentation of ex isting prog rams that would manag e the arsenic reg u lation.

Tribal representatives were g e nerally supportive of reg u lations that would ensure a hig h level of
water quality but raised concerns over funding for reg u lations. With reg a rd to the revised
Arsenic Rule, many Tribal representatives saw the health benefits as hig h ly desirable, but felt
that unless additional funds were made available, implementing the reg u lation would be difficult
for many Tribes.

EPA understands the State, local, and Tribal g overnment concerns with the above issues. The
Ag e n c y be lie ve s the options f o r

sma ll sy ste m s in this r u le ma king will a ddr e ss sta k e holde r

c onc e r ns pe r t a i ning to sma ll sy ste m s a nd will he lp to r e duc e the f i na nc ia l bur de n to the s e

sy stems.

8.5.7 R egulat ory A l t e rnat iv es C onsidered

As required under Section 205 of the UMRA, EPA considered several reg u latory alternatives in
developing an MCL for arsenic in drinking water. I n preparation for this consideration, EPA
evaluated arsenic levels of 3 μg /L , 5 μg /L , 10 μg /L , and 20 μg /L . EPA also evaluated national
costs and benefits of States choosing to reduce arsenic ex posure in drinking water. EPA believes

t h at t h e reg u l a t o ry approaches t o arseni c descri bed i n t h e revi sed rul e ’s pream bl e are t h e m o st appropri a t e t o accom p l i s h t h e S D W A obj ect i v es.

8.5.8 I mpact s on Small Gov e rnment s

I n developing this rule, EPA consulted with small g overnments pursuant to section 203 of the

UMRA to a ddr e ss impa c t s of r e g u la tor y r e quir e me nts in the r u le tha t mig ht sig n if ic a n tly or uniquely affect small g overnments. I n preparation for the revised Arsenic Rule, EPA conducted
analy s is on small g overnment impacts and included small g overnment officials or their
desig n ated representatives in the rulemaking process. EPA conducted stakeholder meeting s on the development of the Arsenic Rule that g a ve a variety of stakeholders, including small

g overnments, the opportunity for timely and meaning f ul participation in the reg u latory
development process. Groups such as the National Association of Towns and Townships, the

National L eag ue of Cities, and the National Association of Counties participated in the
rulemaking process. Throug h such participation and ex chang e , EPA notified potentially affected
small g overnments of requirements under consideration during the development of the revised
rule and provided officials of affected small g overnments with an opportunity to have meaning f ul
and timely input into the development of the reg u latory proposal.

Chapter 8, Economic Impact Analyses 8-28 Arsenic in Drinking Water Rule EA

### I n addition, EPA will educate, inform, and advise small sy stems, including those run by small

g overnments, about the Arsenic Rule requirements. One of the most important components of
this pr oc e ss is the Sma ll Entity Complia nc e Guide

, r e quir e d by the Sma ll B u sine ss Re g u la tor y
Enforcement F a irness Act of 1996 after the rule is promulg a ted. This plain-Eng lish g u ide will

e x pla i n wha t a c tions a sma ll e n tity must ta ke to c o mply with the r u le

. Also, the Ag e n c y is
developing fact sheets that concisely describe various aspects and requirements of the Arsenic

Rule

.

8.6 E f f ect of C o mpliance w i t h t h e A r senic R u le on t h e Technical, Financial, and Managerial Capacity of Public W a ter Sy stems

Section 1420(d)(3) of the SDW A as amended requires that, in promulg a ting an NPDW R, the

Administr a t or sha ll inc l ude a n a n a l y s is of the like l y e f f

e c t of c o mplia nc e with the r e g u la tion on
the technical, financial, and manag e rial capacity of public water sy stems. The following analy s is

ha s be e n pe r f o r m e d to f u lf ill this sta t utor y oblig a tion.

Overall water sy stem capacity is defined in EPA g u idance (EPA 816-R-98-006) (EPA 1998) as

the a b ility to pla n f o r

, a c h ie ve , a nd ma inta in c o mplia nc e with a pplic a b le dr inking wa te r standards. Capacity has three components: technical, manag e rial, and financial.

Te c hnic a l c a p a c ity is the phy sic a l a nd ope r a tiona l a b ility of a

wa te r sy ste m to me e t SDWA
requi rem e nt s. Techni cal capaci t y refers t o t h e phy si cal i n frast ruct ure of t h e wat e r sy st em

, including the adequacy of source water and the adequacy of treatment, storag e, and distribution

infrastructure. I t also refers to the ability of sy stem personnel to adequately operate and maintain
the sy stem and to otherwise implement requisite technical knowledg e. A water sy stem’s
technical capacity can be determined by ex amining key issues and questions, including :

• S ource water adequacy

. Does the sy stem have a reliable source of drinking water? I s the
source of g e nerally g ood quality and adequately protected?

• I nfrastructure adequacy

. Can the sy stem provide water that meets SDW A standards?

W h at is the condition of its infrastructure, including well(s) or source water intakes,

t r eat m e nt , st orag e, and di st ri but i on? W h at i s t h e i n frast ruct ure’s l i f e ex pect ancy ? Does the sy stem have a capital improvement plan?

• T echnical knowledg e and implementation. I s the sy stem’s operator certified? Does the
operator have sufficient technical knowledg e of applicable standards? Can the operator
effectively implement this technical knowledg e? Does the operator understand the

sy st em ’s t echni cal and operat i onal charact eri s t i c s? Does t h e sy st em have an effect i v e operation and maintenance prog ram?

Manag e rial capacity is the ability of a water sy stem to conduct its affairs in a manner enabling

the sy ste m to a c h ie ve a nd ma inta in c o mplia nc e with SDWA r e quir e me nts. Ma na g e r i a l c a p a c ity

r e f e r s to the sy ste m ’ s institutiona l a nd a d ministr a tive c a p a b ilitie s. Ma na g e r i a l c a pa c ity c a n be
assessed throug h key issues and questions, including :

Chapter 8, Economic Impact Analyses 8-29 Arsenic in Drinking Water Rule EA

### • Ownership accountability . Are the sy stem owner(s) clearly identified? Can they be held
accountable for the sy stem?

• S taffing and org a niz a tion. Are the sy stem operator(s) and manag e r(s) clearly identified?

I s the sy stem properly org a niz e d and staffed? Do personnel understand the manag e ment aspects of reg u latory requirements and sy stem operations? Do they have adequate

ex pertise to manag e water sy stem operations? Do personnel have the necessary licenses

and certifications?

• E f f

e c tive e x te r n a l linka g e s. Doe s the sy ste m inte r a c t we ll with c u stome r s, r e g u la tor s , a n d

othe r e n titie s? I s the sy ste m a w a r e of a v a ila ble e x te r n a l r e sour c e s , suc h a s te c hnic a l a n d

fi nanci a l assi st ance?

F i na nc ia l c a p a c ity is a wa te r sy ste m ’ s a b ility to a c quir e a nd ma na g e suf f i c i e n t f i na nc ia l r e sour c e s

to a llow the sy ste m to a c h ie ve a nd ma inta in c o mplia nc e with SDWA r e quir e me nts. F i na nc ia l
capacity can be assessed throug h key issues and questions, including :

• R evenue sufficiency . Do revenues cover costs? Are water rates and charg e s adequate to

cover the cost of water?

• C redi t wort hi ness. I s t h e sy st em fi nanci a l l y heal t h y ? Does i t have access t o capi t a l
throug h public or private sources?

• F iscal manag e ment and controls. Are adequate books and records maintained? Are
appropriate budg eting

, accounting

, and financial planning methods used? Does the

sy stem manag e its revenues effectively ?

A complete technical, financial, and manag e rial capacity study is provided in the revised rule’s

pream bl e.

8.7 P aperw o rk R e duct i on A c t

The inf o r m a tion c o lle c t e d a s a r e sult of this r u le will a llow the Sta t e s a nd EPA to e v a l ua te PWS

c o mplia nc e with the r u le

. F o r the f i r s t thr e e y e a r s a f te r pr omulg a tion of this r u le , the ma jor
information requirements pertain to reading and understanding the rule and operator training

. Responses to the request for information are mandatory (Part 141). The information collected is

not confidential.

EPA is r e quir e d to e s tima te the bur de n on PWSs f o r

c o mply ing with the r e vise d r u le

. B u r d e n

me a n s the tota l time , e f f

o r t , or f

i na nc ia l r e sour c e s e x pe nde d by pe r s ons to g e ne r a te , ma inta in,

r e ta in, disc lose , or pr ovide inf o r m a tion to or f

o r

a

F e de r a l a g e n c y

. This inc l ude s the time ne e d e d
to review instructions; develop, acquire, install, and utiliz e technolog y and sy stems for the
purposes of collecting

, validating

, and verify ing information, processing and maintaining
information, and disclosing and providing information; adjust the ex isting way s 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

Chapter 8, Economic Impact Analyses 8-30 Arsenic in Drinking Water Rule EA

### information; and transmit or otherwise disclose the information. The I n formation Collection
Rule for the revised Arsenic Rule estimated a total burden of 3.09 million hours for 10 μg /L

.

8.8 P rot ect ing C h ildren f r om Env i ronment a l H ealt h R i sks and Saf e t y R i sks

Ex ecutive Order (EO) 13045 (62 F R 19885, April 23, 1997) applies to any rule initiated after
April 21, 1997, or proposed after April 21, 1998, that (1) is determined to be “economically
sig n ificant” as defined under EO 12866 and (2) concerns an environmental health or safety risk
that EPA has reason to believe may have a disproportionate effect on children. I f the reg u latory
action meets both criteria, EPA must evaluate the environmental health or safety effects of the
planned rule on children, and ex plain why the planned reg u lation is preferable to other

pot ent i a l l y effect i v e and reasonabl y feasi b l e al t e rnat i v es consi d ered by EP A.

As de sc r i be d in Cha p te r 5 ( “ B e ne f its Ana l y s is” ) , the r e a r e insuf f i c i e n t tox i c o log i c a l da ta to disting u ish morbidity and mortality differences by ag e g r oups. No studies were located by
ATSDR (1998) that focused ex clusively on evaluating unusual susceptibility to arsenic.
However, some members of the population are likely to be especially susceptible. F o r ex ample,
Chapter 5 describes several non-carcinog enic effects that may be of g r eater concern to children
than adults, such as cardiovascular or reproductive effects. Similarly

, arsenic has been sug g e sted

to pose sig n if ic a n t pr oble m s in f e ta l de ve lopme n t. This inc r e a s e d susc e p tibility ma y be due to a variety of factors. These factors include increased dose (intake per unit of body weig ht) in
children, g e netic predispositions, and dietary insufficiency(ATSDR, 1998), as well as pree x isting he a lth c onditions.

8.9 E nv ironment a l Just ice

Ex ecutive Order 12898 establishes a F e deral policy for incorporating environmental justice into

F e deral ag ency missions by directing ag encies to identify and address disproportionately hig h and

a dve r s e huma n he a lth or e nvir onme n ta l e f f

e c t s of its pr og r a ms, polic ie s, a nd a c tivitie s on minority and low-income populations. The Ex ecutive Order requires the Ag ency to consider

e nvir onme n ta l justic e issue s in the r u le ma king a nd to c onsult with Envir onme n ta l J u stic e ( E J )

stakeholders.

The Ag ency has consi d ered envi ronm ent a l j u st i ce rel a t e d i ssues concerni ng t h e pot ent i a l i m p act s of this reg u lation and has determined that there are no substantial disproportionate effects.

B ecause the Arsenic Rule applies to all community water sy stems, the majority of the population,
including minority and low-income populations will benefit from the additional health
protection.

8.10 H ealt h R i sk R e duct i on and C o st A n aly s is

Section 1412(b)(3)(C) of the 1996 Amendments requires EPA to prepare a Health Risk

Re duc tion a nd Cost Ana l y s is (HRRCA) in support of a n y NPDWR tha t inc l ude s a n MCL

. Accordi n g t o t h ese requi rem e nt s, EP A anal y z ed each of t h e fol l o wi ng i n revi si ng t h e Arseni c
Rule :

Chapter 8, Economic Impact Analyses 8-31 Arsenic in Drinking Water Rule EA

### 1. Quantifiable and non-quantifiable health risk reduction benefits for which there is a
factual basis in the rulemaking record to conclude that such benefits are likely to occur as

t h e resul t of t r eat m e nt t o com p l y wi t h each l e vel ;

2. Quantifiable and non-quantifiable health risk reduction benefits for which there is a
factual basis in the rulemaking record to conclude that such benefits are likely to occur

f r o m r e duc tions in c o

- o c c u r r i ng c onta mina n ts tha t ma y be a ttr ibute d sole ly to c o mplia nc e
with the MCL

, ex cluding benefits resulting from compliance with other proposed or
promulg a ted reg u lations;

3. Quantifiable and non-quantifiable costs for which there is a factual basis in the

rul e m a ki ng record t o concl ude t h at such cost s are l i k el y t o occur sol e l y as a resul t of
compliance with the MCL

, including monitoring , treatment, and other costs, and

ex cluding costs resulting from compliance with other proposed or promulg a ted

r e g u la tions;

4. The i n crem ent a l cost s and benefi t s associ at ed wi t h each al t e rnat i v e MC L consi d ered;

5. The effects of the contaminant on the g e neral population and on g r oups within the g e neral
population, such as infants, children, preg nant women, the elderly

, individuals with a
history of serious illness, or other sub-populations that are identified as likely to be at

g r eater risk of adverse health effects due to ex posure to contaminants in drinking water than the g e neral population;

6. Any i n creased heal t h ri sk t h at m a y occur as t h e resul t of com p l i a nce, i n cl udi ng ri sks

associ at ed wi t h co-occurri ng cont am i n ant s ; and

7. Other relevant factors, including the quality and ex tent of the information, the
uncertainties in the analy s is, and factors with respect to the deg r ee and nature of the risk.

This a n a l y s is summa r i ze s EPA’ s e s tima te s of the c o sts a nd be ne f its a ssoc i a t e d with va r i ous
arseni c l e vel s

. The sum m a ry t a bl es bel o w charact eri z e ag g r eg at e cost s and benefi t s , i m p act s on

a f

f

e c t e d e n titie s, a nd tr a d e o f f

s be twe e n r i sk r e duc tion a nd c o mplia nc e c o sts.

8.10.1 Q uantifiable and Non-Quantifiable Health Risk Reduction Benefits

Arsenic ing e stion has been linked to a multitude of health effects, both cancerous and noncancerous. These health effects include cancer of the bladder, lung s, skin, kidney

, nasal

passag e s, liver, and prostate. Arsenic ing e stion has also been attributed to cardiovascular,
pulmonary , immunolog ical, neurolog ical, endocrine, and reproductive and developmental effects.

A c o mple te list of the a r se nic

- r e la te d he a lth e f f

e c t s r e por te d in huma n s is shown in Cha p te r 5.
EPA has performed a risk assessment on bladder cancer and lung cancer. EPA then evaluated

the he a lth be ne f its a ttr ibuta b le to the s e tota l c a n c e r c a s e s a voide d.

The quantifiable health benefits of reducing arsenic ex posures in drinking water are attributable
to the reduced number of fatal and non-fatal bladder and lung cancers. The rang e of mean

Chapter 8, Economic Impact Analyses 8-32 Arsenic in Drinking Water Rule EA

### bladder and lung cancer risks for ex posed populations at or above arsenic levels of 3, 5, 10, and
20 μg /L in PW Ss was described in Chapter 5. Ex hibit 8-9 shows the health risk reductions
(number of total bladder cancers avoided and the proportions of fatal and non-fatal bladder
cancers avoided) at 3, 5, 10, and 20 μg /L , corresponding to the rang e of mean bladder cancer

r i sks r e por te d. Simila r l y

, Ex hibit 8- 10 shows the tota l lung c a n c e r c a s e s a voide d a s a r e sult of

reduced arsenic ex posure in PW Ss. The sum of bladder cancer cases avoided and lung cancer
cases avoided is shown in Ex hibit 8-11.

Exhi bi t 8- 9

A nnual Bl adder Cancer Cases A v oi ded f r om Reduci ng A r seni c i n CWSs 1 

### and NT NCs

A r sen i c L e v e l (μg/L) Red u ced M o rtal i t y
Cases** R e duc e d M o r b idity

Cases** To tal Bl ad d e r Can cer
Cases A v o i d e d *

3 7

. 4 - 20. 0 21. 2 - 56. 9 28. 6 - 76. 8

5 6

. 6 - 14. 5 18. 9 - 41. 2 25. 6 - 55. 7

10 4. 9 - 8. 0 13. 8 - 22. 7 18. 7 - 31. 0

20 2. 6 - 2. 8 7

. 3 - 7. 8 9

. 9 - 10. 6

* T he low e r-end estimate of bladder cancer cases av oided is calculated using the low e r-end risk estimate from

Ex hibit 5-9(c) and assumes that the conditional probability of mortality among the T a iw anese study group w a s 100
percent. T he upper-end estimate of bladder cancer cases av oided is calculated using the upper-end risk estimate

from Ex hibit 5-9(c) and assumes that the conditional probability of mortality among the T a iw anese study group w a s 80 percent.

* * A ssuming 20-y ear mortality rate in the U

. S. of 26 percent.

***Cas es av oided from NT NCS are inc l uded.



### Exhi bi t 8- 10

A nnual Lung Cancer Cases A v oi ded f r om Reduci ng A r seni c i n CWSs and NT NCs

A r sen i c L e v e l (μg/L) Red u ced M o rtal i t y
Cases** R e duc e d M o r b idity

Cases* ***** T o ta l Lung C a nc e r
Cases A v o i d e d *****

3 25. 2 - 54. 1 3

. 4 - 7. 4 28. 6 - 61. 5

5 22. 5 - 39. 2 3

. 1 - 5. 3 25. 6 - 44. 5

10 16. 4 - 21. 8 2

. 2 - 3. 0 18. 7 - 24. 8

20 7. 4 - 8. 7*** 1. 0 - 1. 2*** 8. 5 - 9. 9***

* T he low e r and upper-end estimates of lung cancer cases av oided are calculated using the risk estimates from

Ex hibit 5-9 (c) and assume that the conditional probability of mortality among the T a iw anese study group w a s 100
percent.

* * A ssuming 20-y ear mortality rate in the U

. S. of 88 percent. ***For 20 ppb, the proportional reduc tion from the low e r lev e l ris k bas e c a s e is greater than the proportional reduction from the higher lev e l risk base case. T hus the number of estimated cases av oided is higher at 20 using the estimates adjusted for uncertainty

.  c as es av oided from NT NCS are inc l uded.

Chapter 8, Economic Impact Analyses 8-33 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 11

A nnual T o t a l Cancer Cases A v oi ded f r om Reduci ng A r seni c i n CWSs and NT NCs

A r sen i c L e v e l (μg/L) Red u ced M o rtal i t y
Cases**  R e duc e d M o r b idity

Cases** To tal Can cer Cases

A v oide d*

3 32. 6 - 74. 1 24. 6 - 64. 2 57. 2 - 138. 3

5 29. 1 - 53. 7 22. 0 - 46. 5 51. 1 - 100. 2

10 21. 3 - 29. 8 16. 1 - 25. 9 37. 4

- 55. 7

20 10. 2 - 11. 3*** 8. 5 - 8. 8 19. 0 - 19. 8***

* T he low e r-end estimate of bladder cancer cases av oided and the lung cancer estimates assume that the conditional probability of mortality among the T a iw anese study group w a s 100 percent. T he upper-end estimate of

bladder cancer cases av oided is calculated using the assumption that the conditional probability of mortality among
the T a iw anese study group w a s 80 percent.

* * A ssuming 20-y ear mortality rate in the U

. S. of 26 percent for bladder cancer and 88 percent for lung cancer. ***For 20 ppb, the proportional reduc tion from the low e r lev e l ris k bas e c a s e is greater than the proportional reduction from the higher lev e l risk base case. T hus the number of estimated cases av oided is higher at 20 using the estimates adjusted for uncertainty

. ****Cas es av oided from NT NCS are inc l uded.



### The Ag e n c y de ve lope d mone tize d e s tima te s of the he a lth be ne f its a ssoc i a t e d with the r i sk

reductions from arsenic ex posures. The approach used in this analy s is for the measurement of

heal t h ri sk reduct i on benefi t s i s t h e m onet a ry val u e of a st at i s t i cal l i f e (VS L ) appl i e d t o each fat a l

c a n c e r a voide d. F o r non- f a ta l c a n c e r s, willing n e ss to pa y ( W TP) da ta to a void c h r onic br onc hitis
is used as a surrog a te to estimate the W T P to avoid non-fatal bladder cancers. A W T P central
tendency estimate of $607,162 (May 1999$) is used to monetiz e the benefits of avoiding nonfatal cancers (this value was updated from the $536,000 value EPA updated to 1997 dollars from
the Viscusi et al. 1991 study ).

The total national costs of the revised Arsenic Rule are summariz e d in Ex hibit 8-12, along with
the annual bladder cancer and lung cancer health benefits, and any non-quantifiable health

benefits from other arsenic health effects. Total annual health benefits resulting from bladder
cancer cases avoided rang e from $58.2 to $156.4 million at an MCL of 3 μg /L

, $52.0 to $113.3

million at an MCL of 5 μg /L

, $38.0 to $63.0 million at an MCL of 10 μg /L , and $20.1 to $21.5

million at an MCL of 20 μg /L

. Total annual health benefits resulting from lung cancer cases avoided rang e from $155.6 to $334.5 million at an MCL of 3 μg /L

, $139.1 to $242.3 million at

an MCL of 5 μg /L

, $101.6 to $134.7 million at an MCL of 10 μg /L , and $46.1 to $53.8 million

at an MCL of 20 μg /L

.

Chapter 8, Economic Impact Analyses 8-34 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 12

T o t a l A nnual Cost

, Est i mat e d M onet i zed T o t a l Cancer Heal t h Benef i t s and

N o n

- Qu a n tifia b le H e a l th B e n e fits fro m R e d u c in g A r s e n ic in P W S s ($ millio n s )

A r s eni c

Level (μ g/ L) Tot a l A nnual

Cos t (7% ) A nnual B l adder

Canc er Heal t h

B enef i t s 1,2 A nnual Lung

Canc er Heal t h

B enef i t s 1,2 Tot a l A nnual

Heal t h B enef i t s 1,2 P o t ent i a l Non-Quant i f i abl e
Heal t h B enef i t s

3 $792. 1 $58. 2 - $156. 4 $155. 6 - $334. 5 $213. 8 - $490. 9 • S k i n Canc er

• K i dney Canc er

• C anc er of t he Nas a l

P a s s ages

• L i v er Canc er

• P ros t at e Canc er

• C ardi ovas c u l a r E f f e c t s

• P ul m onary E f f e c t s

• I m m unol ogi c a l E f f e c t s

• N eurol ogi c a l E f f e c t s

• E ndoc ri ne E f f e c t s

• R eproduc t i ve and

Devel opm ent al E f f e c t s 5 $471. 7 $52. 0 - $113. 3 $139. 1 - $242. 3 $191. 1 - $355. 6

10 $205. 6 $38. 0 - $63. 0 $101. 6 - $134. 7 $139. 6 - $197. 7

20 $76. 5 $20. 1 - $21. 5 $46. 1 - $53. 8 $66. 2 - $75. 3 3

1 M a y 1999 dollars.

2 T hese monetary estimates are based on cases av oided giv en in Ex hibit 5-9 (a-c).

3 For 20 μ g /L, the proportional reduction from the low e r lev e l risk base case is greater than the proportional reduction from the higher lev e l risk base case. T hus the number of estimated cases av oided and estimated benefits are higher at 20 μ g /L using the estimates adjusted for uncertainty

.



### Reductions in arsenic ex posures may also be associated with non-quantifiable benefits. EPA has
identified several potential non-health non-quantifiable benefits associated with reg u lating

arseni c i n dri nki ng wat e r. These benefi t s m a y i n cl ude any cust om er peace of m i nd from
knowing that their drinking water has been treated for arsenic. To the ex tent that the Arsenic
Rule can reduce households’ perception of the health risks associated with arsenic in drinking
water, household averting actions and costs to avoid these risks, such as buy ing bottled water or

insta lling home tr e a tme nt sy ste m s, c ould a l so be r e duc e d

.

8.10.2 Q uant if iable and N on- Quant i f i able C o st s

The costs of reducing arsenic to various levels are summariz e d in Ex hibit 8-13, which shows that

a s e x pe c t e d, a g g r e g a t e a r se nic mitig a tion c o sts inc r e a s e with de c r e a sing a r se nic le ve ls. Tota l
national costs at a seven percent discount rate rang e are $792.1 million per y e ar at 3 μg /L ; $471.1
million per y ear at 5 μg /L ; $205.6 million per y ear at 10 μg /L ; $76.5 million per y ear at 20 μg /L

.

Chapter 8, Economic Impact Analyses 8-35 Arsenic in Drinking Water Rule EA

### Exhi bi t 8- 13 Summary of t h e T o t a l A nnual Nat i onal Cost s of Compl i a nce ($ millio n s )

Di s c o u n t Ra t e 3% 7% 3% 7% 3% 7%

Syst e m C o st s

T r eat m ent $665. 9 $756. 5 $27. 2 $29. 6 $693. 1 $786. 0

M o n i to r i n g /

Ad m i n i str a ti v e $2. 2 $3. 0 $1. 0 $1. 4 $3. 2 $4. 4

S t at e C o s t s $1. 4 $1. 6 $0. 1 $0. 2 $1. 5 $1. 7

TO TA L C O S T $669. 4 $761. 0 $28. 3 $31. 1 $697. 8 $792. 1

Syst e m C o st s

T r eat m ent $394. 4 $448. 5 $16. 3 $17. 6 $410. 6 $466. 1

M o n i to r i n g /

Ad m i n i str a ti v e $2. 0 $2. 8 $1. 0 $1. 3 $2. 9 $4. 1

S t at e C o s t s $1. 1 $1. 3 $0. 1 $0. 2 $1. 2 $1. 4

TO TA L C O S T $397. 5 $452. 5 $17. 3 $19. 1 $414. 8 $471. 7

Syst e m C o st s

T r eat m ent $169. 6 $193. 0 $7. 0 $7. 6 $176. 7 $200. 6

M o n i to r i n g /

Ad m i n i str a ti v e $1. 8 $2. 5 $0. 9 $1. 3 $2. 7 $3. 8

S t at e C o s t s $0. 9 $1. 0 $0. 1 $0. 2 $1. 0 $1. 2

TO TA L C O S T $172. 3 $196. 6 $8. 1 $9. 1 $180. 4 $205. 6

Syst e m C o st s

T r eat m ent $60. 7 $69. 0 $2. 6 $2. 8 $63. 3 $71. 8

M o n i to r i n g /

Ad m i n i str a ti v e $1. 7 $2. 4 $0. 9 $1. 3 $2. 6 $3. 7

S t at e C o s t s $0. 7 $0. 8 $0. 1 $0. 2 $0. 9 $1. 0

TO TA L C O S T $63. 2 $72. 3 $3. 6 $4. 2 $66. 8 $76. 5 NT NC CW S

M C L = 10 μ g/ L

M C L = 20 μ g/ L TO TA L

MC L = 3 μ g/ L

MC L = 5 μ g/ L

Chapter 8, Economic Impact Analyses 8-36 Arsenic in Drinking Water Rule EA

### EPA also assessed the cost impact of reducing arsenic in drinking water at the household level.

Ex hibit 8-14 ex amines the cost per household for each sy stem siz e categ ory

. As shown in the
table, costs per household decrease as sy stem siz e increases. However, costs per household do

not vary si g n i f i cant l y across arseni c l e vel s

. Thi s i s because cost s do not vary si g n i f i cant l y wi t h
removal efficiency ; once a sy stem installs a treatment technolog y to meet an MCL

, costs based
upon the removal efficiency that the treatment technolog y will be operated under remain
relatively flat. Usually , per household costs are, however, somewhat lower at less string ent

arsenic levels. This is due to the assumption that some sy stems would blend water at these levels
and treat only a portion of the flow in order to meet the targ et MCL

. However, in the smallest

two siz e categ ories, averag e household costs decrease as the standard becomes more string ent. This somewhat counterintuitive result is due to the $500.00 affordability cap assumed in the

Sa f e Wa te r XL simula tions. As mor e CWSs a r e f o r c e d ove r the a f f

o r d a b ility c a p, the sy ste m s’

costs are fix e d at the costs associated with the POU technolog y

. This results in lower averag e household costs for these sy stems.

Exhi bi t 8- 14

M ean A nnual Cost s per Househol d i n CWSs

MC L ( μ g/ L )
Sy s

t e m Si z e

3 5 10 20

<1 0 0 $31 7. 00 $31 8. 26 $32 6. 82 $35 1. 15

101

- 500 $16 6. 91 $16 4. 02 $16 2. 50 $16 6. 72

501

- 1

, 0 0 0 $74

. 8 1 $73

. 1 1 $70

. 7 2 $68

. 2 4

1, 0 01- 3, 300 $63

. 7 6 $61

. 9 4 $58

. 2 4 $54

. 3 6

3, 3 01- 10

, 000 $42

. 8 4 $40

. 1 8 $37

. 7 1 $34

. 6 3

10, 001- 5 0

, 000 $38

. 4 0 $36

. 0 7 $32

. 3 7 $29

. 0 5

50, 001- 1 00, 00 0 $31

. 6 3 $29

. 4 5 $24

. 8 1 $22

. 6 3

100

, 001-1, 000

, 000 $25

. 2 9 $23

. 3 4 $20

. 5 2 $19

. 2 6

> 1

, 000, 0 0 0 $7. 41 $2. 79 $0. 86 $0. 15

A l l c a te gor i e s $41

. 3 4 $36

. 9 5 $31

. 8 5 $23

. 9 5

Chapter 8, Economic Impact Analyses 8-37 Arsenic in Drinking Water Rule EA

### Ex hibit 8- 15 illustr a te s the c o st pe r bla dde r c a n c e r c a s e a voide d, ba se d on na tiona l c o st e s tima te s
whic h inc l ude a ll the c o sts of tr e a tme nt, O& M, monitor i ng a nd a d ministr a tive c o sts to CWSs a n d
NTNCs, and all State start-up costs and State costs for administration of water prog rams. At a
three percent discount rate, cost per case rang es from approx imately $12.2 million at an arsenic
level of 3 μg /L (lower bound estimate of avoided bladder cancer cases) to $3.4 million at an

MCL of 20 μg /L (upper bound of avoided bladder cancer cases). Similarly

, the rang e at a seven percent discount rate is $13.8 million to $3.9 million.

Exhi bi t 8- 15

Cost per Cancer Case A v oi ded ($ millio n s )

A r s e ni c Le v e l
( μ g/ L) l o w e r bound* * uppe r bound **

3 % D i s c ount R a t e

3

5

10

20 12

. 2 $ 5

. 0 $

8. 1 $ 4

. 1 $

4. 8 $ 3

. 2 $

3. 5 $ 3

. 4 $

7 % D i s c ount R a t e

3

5

10

20 13

. 8 $ 5

. 7 $

9. 2 $ 4

. 7 $

5. 5 $ 3

. 7 $

4. 0 $ 3

. 9 $

* * Lo w e r/ u p p e r bo und s c o rres p o nd t o es t i m a t e s o f bl ad de r c a n c er c a s e s a v o i de d.

Chapter 8, Economic Impact Analyses 8-38 Arsenic in Drinking Water Rule EA

## A ppendix A : Decision Tree and Large Sy stem Costs

A

. 1 I ntroduction

The purpose of this appendix is to present the rationale behind the development of the decision

t r ee and associ at ed deci si on m a t r i x

. I t i n cl udes an overvi e w of t h e deci si on t r ee st ruct ure and

ma jor f

a c t or s impa c ting the de c i sion- ma king pr oc e ss. The f o llowing list outline s the c onte n ts of
this appendix :

**• B**  **ac kgr**  **o und**  - Presents a brief history of the arsenic reg u lation and the statutory
requirements impacting EPA and the decision-making process.

• **Major F a**  **ctors Af f** 

**ecti n**  **g th e Deci**  **si on**  **T ree**  - Pr e s e n ts the r a tiona le f o r

se le c ting
parameters which impact the decision tree, including MCL

, population, water

ty

pe, reg i on, and co-occurrence of solutes.

• **Ad d**  **i ti**  **on al**  **F a**  **ctors Af f** 

**ecti n**  **g th e Deci**  **si on**  **T ree**  - Presents other parameters in
the process which impact the decision tree, including : corrosion control, preox idation, reg i onaliz ation, and alternative technolog ies.

• **Devel o**  **p m**  **en t of**  **a Deci si**  **on T**  **ree** - Presents the log i c used for developing the

decision tree for treatment of arsenic to a final revised MCL of 10 μg /L

.

• **Very L a**  **rge S y**  **stem Meth**  **o d**  **o l**  **ogy** - Disc usse s the c o st e s tima te s f o r

the Na tion’ s 25 larg est drinking water sy stems.

A

. 2 B ackground

I n 1998 and 1999, EPA conducted technolog y and cost evaluations for the removal of arsenic
from drinking water. These evaluations looked into the effectiveness of various removal
technolog ies and the capital and operations and maintenance (O& M ) costs associated with each

process. The following were evaluated and determined effective to vary ing deg r ees:

• M odif i e d Coa g ula tion/F iltr a tion ( m odif i c a tions to e x isting C/F pla n ts) ;

• C oa g u la tion Assiste d Mic r of iltr a tion ( C MF ) ;

• M odified L ime Softening (modifications to ex isting L S plants);

• A ct i v at ed Al um i n a (AA);

• I on Ex chang e (I X);

• G r e e n sa nd F iltr a tion ( G F ) ; a n d

• P oint-of-Use (POU) Treatment Options.

The technolog y and cost evaluation y i elded a document entitled Technologies and Costs for the
Removal of Arsenic From Drinking W a ter (EPA, 2000c). The document includes detailed
evaluations of the above technolog ies, capital and O& M cost estimates for each of the listed
technolog ies, as well as other technolog ies that were considered ineffective or unproven.

EPA used the information contained in the technolog ies and costs (T& C ) document to develop a

reg u latory decision tree. The decision tree was then used to fashion a decision matrix which

Appendix A, Decision Tree and Large System Costs A -1 Proposed Arsenic in Drinking Water Rule RIA

### contains the probability that a g i ven sy stem will choose a treatment technolog y based on the
percent removal required to meet the final revised MCL of 10 μg /L

. The decision matrix , unit
cost curves for treatment and waste disposal (illustrated in the T& C), treatment-in-place data and

oc c u rr e nc e e s tima te s we r e use d to de ve lop na tiona l c o st of c o mplia nc e e s tima te s.

A

. 3 M aj or Fact ors A f f ect ing t h e D ecision Tree

Thi s sect i on ex pl ai ns t h e rat i onal e behi nd sel ect i n g each part i c ul ar deci si on fact or. S p eci fi cal l y

, this se c tion will disc uss the f o llowing :

• t he MCL ta r g e t;

• i nfl u ent arseni c concent r at i on;

• population;

• r eg i on where t h e sy st em i s l o cat ed;

• s ource water;

• w het h er a sy st em has ex i s t i n g t r eat m e nt i n pl ace;

• c o-occurrence of solutes; and

• w aste disposal issues.

A

. 3.1 M C L Target

Targ et treatment concentration (8 μg /L ) which is equal to 80 percent of the final revised MCL of
10 μg /L was selected as the basis for the development of the Arsenic Rule decision tree. The
selection of a targ et treatment concentration was the first step in the decision process and was

e sse ntia l f o r

de te r mining a ll othe r br a n c h e s of the de c i sion tr e e

.

A

. 3.2 I nf luent A r senic C oncent r at ion

Given the MCL

, the influent arsenic concentration determines what percent removal of arsenic is
needed, if any

, and lay s the g r oundwork for remaining decisions in the tree; therefore, the
influent arsenic concentration was of major importance in developing the decision tree. Given

the max imum influent arsenic level of 50 μg /L and at the final MCL of 10 μg /L , no sy stems

woul d need t o have a rem oval effi ci ency g r eat er t h an 90 percent t o t r eat for arseni c. P e rcent removal is critical for determining what additional technolog ies may be feasible. F o r ex ample, if

a g r ound water sy stem has an influent arsenic level of 50 μg /L , and the targ et treatment concentration is 8 μg /L , then approx imately 80 percent removal is required. 1

1 

### R e quired rem o v a l percentag e s in the decision tree are based on w o rst cast scenarios and
therefore correspond w ith the upper bound of the arsenic concentration rang e for each categ ory

.

Appendix A, Decision Tree and Large System Costs A -2 Proposed Arsenic in Drinking Water Rule RIA

### A. 3

. 3 S y s t e m S i z e

Sy stem siz e , or population, also play s a sig n ificant role in determining the treatment options
available to a sy stem, as well as the affordability of a particular technolog y

. EPA established

nine siz e categ ories to be used in the decision tree and EA process:

• 25 to 100;

• 101-500;

• 501-1,000;

• 1,001-3,300;

• 3,301-10,000;

• 10,001-50,000;

• 50,001-100,000;

• 100,001-1,000,000; and

• g reater than 1,000,000.

Ex ceptions were made in the decision tree for particular sy stems. The Ag encyconsidered pointof-use (POU) treatment as a viable option only for the two smallest categ ories of g r oundwater

sy stems. Sy stems serving g r eater than 1,000,000 were addressed on a case-by

- case basis by EPA,
and therefore, were not considered within the scope of the decision tree process.

I n developing the probability of choosing a g i ven technolog y for each of the siz e categ ories, the
Ag ency consi d ered several fact ors such as avai l a bl e dat a on i n -pl ace t r eat m e nt s from C o m m uni t y

Wa te r Sy ste m Sur v e y ( C WSS) . The log i c use d f o r

de ve loping the pr oba bilitie s f o r

e a c h of the

siz e categ ories is detailed in section A.5 below.

A

. 3.4 R egion

The reg i on of the nation that a sy stem resides in does not effect the treatment options available.
Therefore, the decision tree is structured in such a way that, reg a rdless of the reg i on, the branches
are identical, and in fact refer to the same pag e s within the decision tree. However, the number of

sy stems that may select a particular option as defined in the decision matrix , is reg i on-specific.

EPA has decided that the nation can be divided into three reg i ons for the purpose of the decision
making process: 1) Southwest Reg i on; 2) Northwest Reg i on; and 3) East Reg i on. The reg i ons were selected based upon availability of water (i.e., scarcity of water) and availability of land. I n the Southwest Reg i on, for ex ample, water may be scarce and treatment technolog ies that g e nerate larg e volumes of reject water, such as RO, may not be appropriate. I n the East Reg i on, water scarcity is much less a concern than the availability of land. Technolog ies or disposal options
that require sig n ificant amounts of land are less likely to be utiliz ed in the East Reg i on. The
Northwest Reg i on, by comparison, is less affected by the scarcity of water or land availability

tha n either of the other two reg i ons.

Appendix A, Decision Tree and Large System Costs A -3 Proposed Arsenic in Drinking Water Rule RIA

### A

. 3.5 S ource Wat e r

The source of the sy stem’s raw water, either g r ound water or surface water, play s a major role in
determining the technolog ies that may already be in use by a sy stem and what treatment options

a r e a v a ila ble if a

sy ste m ne e d s to insta ll a ne w f a c ility

.

F o r e x a m ple

, g r e e n sa nd f iltr a tion is a f f

e c t e d by the le ve l of ir on in the r a w wa te r

. I n f l ue nt le ve ls

g r eater than 300 mg /L (ppm) are conducive to removal of arsenic by g r eensand filtration.

S u rface waters ty pically have low iron content, whereas g r ound waters often have levels in

ex cess of 300 mg /L (Subramanian, et al., 1997). According l y

, g r eensand filtration was not
considered a viable removal technolog y for surface water sy stems, but is viable for g r ound water

sy stems.

To determine the ty pes of treatment that are currently being utiliz ed throug hout the country by
source, EPA reviewed the Community W a ter Sy stems Survey (CW SS). EPA determined there
are few surface water sy stems utiliz ing RO, I X or AA. As a result, when approx imating the
treatment in place options, RO, I X , and AA were omitted for surface water sy stems.

Arseni c rem oval i s si g n i f i cant l y m o re effi ci ent when arseni c i s present as arsenat e (As 5+ 

### ).
Research has demonstrated many of the technolog ies considered perform poorly when arsenite

(As 3+ 

### ) is the predominant form (EPA, 2000). Arsenite can be easily ox idiz ed to arsenate using

conventional ox idation methods, such as chlorination and potassium permang a nate addition.
Ground waters ty pically contain hig h er levels of As 3+ 

### , whereas As 5+ 

### is the domina n t spe c i e s in

surface waters. As a result, g r ound water sy stems are more likely to install pre-ox idation and use
hig h er ox idant doses, whereas surface water sy stems may be able to g e t bywith little or no preox ida tion c a p a c ity

.

A

. 3.6 S y s t e ms w i t h Treat ment In- P lace

I n formation on in-place treatment technolog ies for all the flow categ ories of surface and g r ound

water sy stems was obtained from Table 6.2 of “Geometries and Characteristics of Public W a ter Sy stems (EPA, 1999b) .” The Ag ency determined that many ex isting treatment facilities will be

a b le to a c h ie ve the ne c e ssa r y a r se nic r e mova l with little or no modif i c a tion to the i r pla n t. Ex hibit
A- 1 below outlines the treatment technolog ies included in the decision tree, the percent removal
assumed capable without modification or polishing , and the max imum percent removal.

A

. 3.7 S y s tems w i thout Treatment In-Place

Many factors affect the decision tree when considering the addition of a treatment option for

sy stems with no current treatment in place. Source water ty pe and quality , sy stem siz e , required
arsenic removal, and removal achievable by a particular technolog y are all major considerations.
Many of these considerations have been discussed earlier in Section 4.

For g r ound water sy stems without treatment in-place, the most suitable treatment technolog ies

are I X and AA. For surface water sy stems with no treatment in-place, AA with and without pH

Appendix A, Decision Tree and Large System Costs A -4 Proposed Arsenic in Drinking Water Rule RIA

### a d justme nt a nd c o a g ula tion mic r o f iltr a tion a r e the most suita ble

. Modif i e d CF a nd L S a r e f o r

t hose surface wat e r sy st em s t h at al ready have C F or L S i n -pl ace.

The SDW A identifies POE and POU treatment units as potentially affordable technolog ies, but
stipulates that POE and POU treatment sy stems “shall be owned, controlled and maintained by
the public water sy stem, or by a person under contract with the public water sy stem to ensure

pr ope r ope r a tion a nd c o mplia nc e with the ma x imum c onta mina n t le ve l or tr e a tme nt te c hnique
and equipped with mechanical warning s to ensure that customers are automatically notified of
operational problems.”

Preliminary affordability determinations have shown that POU technolog ies will only be
considered viable for small sy stems. These determinations have shown the cost breakpoint to be
in the area of 200 persons served. This estimate does not account for waste disposal costs, which

would make central treatment estimates more ex pensive, thus increasing the breakpoint. As a
result only POU AA and POU RO compliance strateg i es were included in the decision tree for
the g r oundwater sy stems in the two smallest flow categ ories.

Exhi bi t A

- 1

T r eat ment T echnol ogi es f o r Sy st ems w i t h T r eat ment I n

- P l ace and Percent Remov a l s

A ssumed and A c hi ev abl e

T r e a t m e nt T e c hnology Pe r c e n t R e m o va l of

I n -Pl ace Sy stem M axi mu m Percen t

Remo v a l 1

Coagulat ion/ F ilt rat i on 2 50 95

Lim e Soft ening 2 50 90

Coagulat ion Assist ed M i crofilt rat i on NA 90

I on Ex change NA >95

Act i v a t ed Alum ina N A > 95

Rev e rse O s m o sis N A > 95

G r eensand F ilt rat i on 3 NA 80

PO U Act i v a t ed Alum ina N A > 90

PO U Rev e rse O s m o sis N A >9 

### 0

1 - For P e rc ent Rem o val s of I n -P l a c e S y s t em s t hat are very c l os e t o M a x i m u m P e rc ent Rem o val s (e. g

. , 95 perc ent and > 95

perc ent ) pol i s hi ng s t eps m a y be requi red.

2 - M a x i m u m P e rc ent Rem o val i n vol v es m odi f i c a t i on t o ex i s t i ng s y s t em i n t he f o rm of addi t i onal c hem i c al f eed s y s t em s

, pum pi ng, pi pi ng, et c

.

NA - Not A ppl i c abl e



### A

. 3.8 C o- Occurrence of Solut e s

The r e a r e a numbe r of solute s a nd wa te r qua lity pa r a me te r s tha t ma y e f f

e c t the via b ility of a particular treatment option. Total dissolved solids (TDS), silica, sulfate and iron can all be major

Appendix A, Decision Tree and Large System Costs A -5 Proposed Arsenic in Drinking Water Rule RIA

### detractors/benefactors for the use of a particular technolog y

. The decision tree simply cannot account for each individual situation where the influent water quality play s a role in selecting the
treatment option. Utilities are encourag ed to read the T& C document (EPA, 2000d) to g a ther
additional information on parameters which impact the performance of a particular technolog y

.

The decision tree uses influent sulfate and iron levels as decision factors in selecting treatment technolog ies. F o r g r ound water sources, both sulfate and iron levels are considered. I o n

ex chang e i s not consi d ered a feasi b l e t r eat m e nt opt i on when sul f at e l e vel s ex ceed 50 m g / L and

g r eensand filtration is not considered viable when the iron level falls below 300 mg /L . Sulfate

has been shown t o decrease t h e effect i v eness of i on ex chang e processes for arseni c rem oval ; therefore, an upper bound sulfate concentration of 50 mg /L was used in the final rule for

determination of ion ex chang e usag e. Ir on, on the other hand, sig n ificantly improves the
effectiveness of g r eensand filtration (Subramanian, et al., 1997). Greensand filtration is best
suited for g r ound waters (which ty pically contain hig h er levels of iron than surface waters) with
hig h influent levels of iron (300 mg /L ). F o r purposes of approx imating national cost, g r eensand

filtration is not considered a treatment option for surface water sy stems.

A

. 3.9 W ast e D i sposal

W a ste handling and disposal options are specific to the treatment technolog y selected, therefore

the a v a ila bility of disposa l options doe s not va r y by sy ste m size in the de c i sion tr e e

. Howe ve r

, the pr oba bility tha t a sy ste m will utilize a pa r tic ula r option doe s va r y with sy ste m size

.

A

. 3.9.1 M echanical D e w a t e ring

Mechanical dewatering processes include centrifug es, vacuum-assisted dewatering beds, belt

f ilte r pr e sse s, a nd pla t e a nd f r a me f ilte r pr e sse s. Suc h pr oc e sse s g e ne r a lly ha ve hig h c a p ita l, a s well as hig h O& M costs, compared to similar capacity non-mechanical dewatering processes (e.g ., storag e lag oons). Due to the hig h costs, such processes are g e nerally not suitable for very
small water sy stems.

F ilter presses have been used in industrial processes for y ears and have been increasing in the
water treatment industry over the past several y ears. The devices have been successfully applied

to both lime sof t e n ing pr oc e ss sludg e a nd c o a g ula tion/f iltr a tion pr oc e ss sludg e

. F ilte r pr e sse s require little land, have hig h capital costs, and are labor intensive.

Centrifug e s have also been used in the water industry for y ears. Centrifug a tion is a continuous
process requiring minimal time to achieve the optimal coag ulation/filtration. Centrifug e s have
low land requirements and hig h capital costs. Theyare more labor intensive than nonme c h a n ic a l a lte r n a tive s , but le ss inte nsive tha n f ilte r pr e sse s. Ag a i n, due to the c a p ita l a nd O& M

r e quir e me nts, c e n tr if ug e s a r e mor e suita ble f o r

la r g e r wa te r sy ste m s.

Appendix A, Decision Tree and Large System Costs A -6 Proposed Arsenic in Drinking Water Rule RIA

### A

. 3.9.2 POTW D i scharge

I ndirect discharg e (POTW discharg e) is a commonly used method of disposal for filter backwash

a nd br ine wa ste str e a m s. Coa g ula tion/f iltr a tion a nd lime sof t e n ing sludg e ma te r i a l s ha ve a l so been successfully disposed of in this manner. The primary cost associated with POTW discharg e is that of the piping

. Additional costs associated with POTW discharg e may include lift stations,

addi t i onal pi pi ng for access t o t h e sewer sy st em , and any cost i n curred by t h e P O TW i n

accom m odat i n g t h e i n creased dem a nds on t h e P O TW

.

A

. 3.9.3 Sanit a ry Landf ill Disposal

Two forms of sanitary landfill are commonly used for disposal of water treatment by products:

monofills and commercial nonhaz a rdous waste landfills. I n some parts of the country

, de c r e a s ing la ndf ill a v a ila bility , r i sing c o sts, a nd inc r e a s ing r e g u la tions a r e ma king la ndf ill
disposal more ex pensive. Costs associated with the development of monofills are g e nerally less

than those associated with commercial nonhaz a rdous water landfill.

A

. 4 A ddit i onal Fact ors A f f ect ing t h e D ecision Tree

A

. 4.1 Pre- Oxidat ion

As mentioned above, inorg a nic arsenic occurs in two primary valence states, arsenite (As III) a n d

a r s e n a t e ( A s V )

. A s ( III) i s d o m i n a n t i n g r ound waters while surface waters more ty pically

c o n t a i n A s ( V )

. A s ( III) i s e a s i l y o x i d i z e d t o A s ( V ) b y c onventional ox idation technolog ies such
as chlorination and potassium permang a nate addition. Each of the treatment technolog ies

c o n s i d e r e d i n t h e d e c i s i o n t r e e r e m o v e A s ( V ) m o r e r e a d i l y t h a n A s ( III) a n d a s a r e s u l t m a y require pre-ox idation.

I n estimating national costs, it was assumed that only sy stems without pre-ox idation in-place
would add the necessary equipment. I t is ex pected that no surface water sy stems will need to
install pre-ox idation for arsenic removal and that about fewer than 50 percent of the g r oundwater

sy stems may need to install pre-ox idation for arsenic removal. Ground water sy stems without

pre-ox idation should determine if pre-ox idation is necessary by determining if the arsenic is

p r e s e n t a s A s ( III) o r A s ( V )

. G r ound water sy stems with predominantly As (V) will probably
not need pre-ox idation to meet the MCL

. F o r sing le tap (POU) treatment options, centraliz ed

pre-ox idation is required. Ex hibit A-2 shows the number of sy stems that were assumed to require
addition of pre-ox idation.

Appendix A, Decision Tree and Large System Costs A -7 Proposed Arsenic in Drinking Water Rule RIA

### Exhibit A

- 2: Sy st ems N eeding t o A dd Pre- Oxidat ion

Sy s t e m Size Pe r c e n t of Gr ound Wa te r Sy s t e m s

25-100 54

101-500 30

501-1000 24

1001-3300 24

3300-10K 27

10001-50K 13

50, 001-100K 41

100, 001-1M 16



### A

. 4.2 C orrosion Control

Many of the treatment technolog ies considered in the decision tree (e.g . AA, and I X ) remove hardness and alkalinity

. Removal of hardness and alkalinity can reduce the pH of finished water
and lead to corrosion problems within the sy stem. Hardness and alkalinity , at the appropriate
levels, act as buffers ag ainst corrosion in the treatment plant and distribution sy stem. At these
levels, alkalinity and hardness form protective coating s (metal hy drox ides), control pH and
enhance the buffer effect ag ainst corrosion. W h ere appropriate, corrosion control costs were

inc l ude d with a r se nic tr e a tme nt in the de c i sion tr e e

. I t wa s a ssume d tha t the in- p la c e lime
softening and coag ulation/flocculation plants had adequate corrosion control in-place.

A

. 4.3 A lternativ e Technologies

Technologies and Costs for the Removal of Arsenic from Drinking W a ter (EPA, 2000) evaluated
four arsenic removal technolog ies that were not included in the decision tree:

• S ulfur-Modified I r on,

• G ranular F e rric Hy drox ide,

• Ir on F iling s , a nd

• Iron Ox ide Coated Sand.

The technolog ies were not included in the decision tree for reasons which are summariz e d below.

A

. 4.3.1 Sulf ur- M odif i ed Iron

A pat e nt ed S u l f ur-Modi fi ed I r on (S MI ) process for arseni c rem oval has recent l y been devel oped.
During this process, powdered iron, powdered sulfur, and the ox idiz ing ag ent (H 2 

### O 2 

### in

pr e limina r y te sts) a r e thor oug hly mix e d a nd a dde d to the wa te r to be tr e a t e d

. The ox idizing

ag ent serves to convert As( III) t o A s ( V )

. A r s e n i c r e m o v a l u tilizing the SMI pr oc e ss se e m s to be

Appendix A, Decision Tree and Large System Costs A -8 Proposed Arsenic in Drinking Water Rule RIA

### dependent on the iron to arsenic level as well as pH. F l ow distribution problems were evident, as

several col u m n s becam e part i a l l y pl ug g e d duri n g operat i on.

All ex perimentation on the SMI process has been at the bench-scale level, and involves only
batch processes. The literature is unclear about removal efficiency since results varied from less
than 10 to 99 percent, depending on conditions. I t appears that O& M for such a sy stem would be

ex pensive and would require a hig h ly trained operator. F i nally , by the admission of the

researchers, di sposal cost s m i g ht out wei g h t h e i n creased adsorpt i on capaci t y

.

A

. 4.3.2 Granular Ferric H y droxide

Granular ferric hydroxide is a technolog y that may combine very long run leng th without the
need to adjust pH. The technolog y has been demonstrated for arsenic removal full-scale in
Eng l and (Simms et al, 2000). A pilot-scale study for activated alumina was also conducted on
that water and showed run leng ths much long er than observed in pilot-scale studies in the United

Sta t e s

. Due to the la c k of publishe d da ta showing pe r f o r m a n c e f o r

a

r a ng e of wa te r qua litie s,

g r anular ferric hy drox ide was not desig n ated a B A T. I n addition, there is little published

information on the cost of the media, so it is difficult to evaluate cost. Granular ferric hy drox ide
is being investig ated in several ong oing studies and may be an effective technolog y for removing

arseni c.

A

. 4.3.3 Iron Filings

The I r on F iling s process is essentially a filter technolog y

, much like g r eensand filtration, wherein
the source water is filtered throug h a bed of sand and iron filing s

. Unlike some technolog ies (i.e.

ion ex chang e ), sulfate is actually introduced in this process to encourag e arsenopy rite
precipitation.

W h ile this process seems to be quite effective, its use as a drinking water treatment technolog y appears to be limited. There is no indication that this technolog y can reduce arsenic levels below

approx imately 25 ppb. This technolog y also suffers from a study desig n which failed to test its
effectiveness at influent levels of concern in drinking water. Since the study desig n called for
such hig h influent levels - 470 to 20,000 ppb - there is no data to indicate how the technolog y performs at normal source water arsenic levels, which most certainly are below the 470 ppb level

used in ex perimentation. This technolog y needs to be further evaluated before it should be
recommended as an approved arsenic removal technolog y for drinking water.

A

. 4.3.4 Iron Oxide C o at ed Sand

I r on ox ide coated sand (I OCS) is a rare process that has shown some tendency for arsenic

removal. I O CS consists of sand g r ains coated with ferric hy drox ide which are used in fix e d bed

react ors t o rem ove vari ous di ssol v ed m e t a l speci es. Fact ors such as pH, arseni c ox i d at i on st at e,

c o mpe ting ions, EB CT, a nd r e g e ne r a tion time ha ve sig n if ic a n t e f f

e c t s on the r e mova ls a c h ie ve d

with I O CS. L i ke other processes, the media must be reg e nerated upon ex haustion. I O CS has
only been tested at bench-scale. Hig h levels of arsenite could reduce I O CS effectiveness because
the bonding is strong and may permanently damag e the media. Natural org a nic matter may also

Appendix A, Decision Tree and Large System Costs A -9 Proposed Arsenic in Drinking Water Rule RIA

### be problematic for arsenic removal. I O CS also takes a considerable amount of time to produce in

a

la bor a t or y se tting

. At f u ll- sc a l e this would like l y r e sult in hig h c a p ita l c o st.

A. 5 D e v e lopment of a D ecision Tree

A

. 5.1 S urf ace Wat e r Sy st ems

The following describes the log i c used for developing the decision tree for treatment of arsenic in
surface water sy stems in order to comply with the final MCL

. For actual breakout of percentag e s used in the decision tree, refer to the Ex hibits A-7 to A-22.

1. I n formation on in-place treatment technolog ies for all the flow categ ories of surface water

sy stems was obtained from Table 6.2 of “Geometries and Characteristics of Public W a ter Sy stems” (EPA, 1999b). This table is shown below as Ex hibit A-3. I n formation
provi ded i n t h e docum ent on i n -pl ace t r eat m e nt s was based on dat a from C o m m uni t y

W a ter Sy stem Survey (CW SS), which EPA conducted in 1995 to obtain data to support
its development and evaluation of drinking water reg u lations.

2. Ex hi bi t A-3 shows t h e percent a g e of sy st em s wi t h i n -pl ace L i m e / S oda Ash S o ft eni n g

. I t

wa s a ssume d tha t the s e sy ste m s would modif y

the e x isting tr e a tme nt to c o mply with the

final MCL

.

Exhibit A

- 3: Percent of Surf ace Wat e r Sy st ems w i t h In- P lace Treat ment

Sy st em Siz e Lim e / Soda Ash Soft ening Coagulat ion

Flocculation F ilt rat i on

25-100 3. 9% 27. 5% 78. 5%

101-500 8. 1% 52. 6% 71. 2%

501-1000 20. 5% 70. 2% 79. 3%

1001-3300 17. 5% 79% 81. 7%

3300-10K 10. 8% 95. 4% 86. 5%

10001-50K 6. 9% 94. 5% 96. 3%

50, 001-100K 5. 7% 93. 7% 88%

100, 001-1M 5. 1% 99. 5% 93. 4%



### 3. Ex hibit A- 3 wa s a l so use d to e s tima te the pe r c e n ta g e of sy ste m s with e x isting

coag ulation/filtration processes. I n -place coag ulation/flocculation was based on the
smaller (in terms of percent use) of filtration and coag ulation/flocculation. The Ag ency
be lie ve s this is a c onse r va tive a ssumption f o r

se ve r a l r e a s ons. The f i r s t is tha t the CWSS
data on in-place treatments was g a thered in 1995 and 1996, which may not be reflective
of requirements under surface water treatment and disinfection by -product rules that were

Appendix A, Decision Tree and Large System Costs A -10 P roposed Arsenic in Drinking Water Rule RIA

### adopted in later y ears. The second is that no arsenic removal is assumed for sy stems with
filtration when the percentag e is hig h er than the percentag e for coag ulation/flocculation.

4. The percent of remaining technolog ies likely to be used for arsenic treatment for each
flow categ ory was obtained by subtracting from 100, the percentag e s assig n ed for
modified lime softening and modified coag ulation /filtration per step 2 and 3 above. The
remaining technolog ies that were considered in the decision tree for treatment of arsenic
in surface water include coag ulation microfiltration and activated alumina (AA). Sy stems choosing AA may also choose to pH adjust. This decision is primarily dependent on

sy stem siz e

. Sy stems that serve less than 500 people (see step 6 below) are less likely to pH adjust their raw water supplies because of technical complex ity and need for skilled

l a bor. The Ag ency cl assi fi ed t h ese sy st em s i n t w o nat u ral pH cat eg ori e s. S y st em s t h at have raw water with pH between 7 and 8 and sy stems with pH in raw water g r eater than

8. F o r sy stems that are likely to adjust pH to 6, the Ag ency considered two run leng th
options, low end (15,400 B V ) and hig h end (23,100 B V ).

5. B a sed on the Ag ency ’s best professional judg ement, the Ag ency believes that for sy stems serving more than 500 people, the selection of treatment for arsenic would likely be
distributed among pH adjusted AA with hig h end run leng th, pH adjusted AA with low

e nd r un le ng th, a nd c o a g ula tion mic r o f iltr a tion in 40:40:20 r a tio. Coa g ula tion/

mic r o f iltr a tion is mor e e x pe nsive tha n a c tiva t e d a l umina

. Howe ve r

, some sur f a c e wa te r

sy stems may select it because they may g e t filtration credits or precursor removal along

with arsenic removal. The benefits of this treatment approach could not be quantified.

6. F o r sy stems serving less than 500 people, it is assumed that there will be no usag e of

coag ulation microfiltration technolog y

, primarily because of its hig h capital cost,
technical complex ity and need for skilled labor. The Ag ency believes for this g r oup, about 65 percent of sy stems with natural pH between 7 and 8 would likely use AA, about
23 percent sy stems with natural pH g r eater than 8 would likely use AA and remaining

sy st em s woul d evenl y use pH adj u st ed act i v at ed al um i n a opt i ons.

A

. 5.2 G round W a ter Sy stems

The nex t section describes the log i c used for developing the decision tree for treatment of arsenic

to a MCL of 10 ug /L for g r ound water sy stems.

1. I n formation on in-place treatment technolog ies for all the flow categ ories of g r ound water

sy stems was obtained from Table 6.1 of “Geometries and Characteristics of Public W a ter Sy stems” (EPA, 1999b). The information provided in the document on in-place
treatments was based on data from Community W a ter Sy stem Survey (CW SS), which
EPA conducted in 1995 to obtain data to support its development and evaluation of
drinking water reg u lations.

2. F o r sy stems serving less than 10,000 people, the Ag ency selected roug hly half the

percentag e of sy stems with in-place of lime softening and coag ulation/ flocculation

(Ex h ibit A-4). These sy stems would modify their ex isting treatment to meet arsenic

Appendix A, Decision Tree and Large System Costs A -11 P roposed Arsenic in Drinking Water Rule RIA

### MCL

. F o r sy stems serving more than 10,000 people, the Ag ency assumed 4 percent for
each technolog y as the max imum percentag e of sy stems with ex isting lime softening and

coag ul at i on/ fl occul a t i on t r eat m e nt s. There was a concern t h at t h e m u ch hi g h er
percentag e s in mig ht be due to mix ed sy stems (g roundwater and surface water) rather
than g r oundwater sy stems. Thus much lower percentag e s were used to estimate ex isting

tr e a tme nt. Sy ste m s with e x isting tr e a tme nt will modif y

it to me e t the a r se nic MCL

.

Exhibit A

- 4: Percent of Ground Water Sy stems w i th In-Place Treatment

Sy st em Siz e Lim e / Soda Ash Soft ening Coagulat ion

Flocculation

25-100 2. 1% 1. 5%

101-500 3. 7% 2. 0%

501-1000 4. 1% 4. 2%

1001-3300 5. 2% 3. 4%

3300-10K 7. 0% 8. 1%

10001-50K 12. 2% 15. 1%

50, 001-100K 17. 4% 24. 2%

100, 001-1M 32. 4% 25. 2%



### 3. F o r sy stems serving less than 100 people and requiring 50-90 percent removal of arsenic,

t h e deci si on t r ee assum e d a 5 percent usag e for each P OU opt i on (R O and AA). For

sy stems requiring less than 50 percent removal of arsenic, a 2 percent usag e of each POU
option was assumed. POU options were used less if lower removal of arsenic was desired
because sy stems would have an opportunity for blending , which would make central

tr e a tme nt mor e c o st e f f

e c tive

.

4. I n the decision tree, for sy stems serving between 100-500 people and requiring 50-90

percent rem oval of arseni c, t h e Ag ency assum e d a 3 percent usag e for each P O U treatment option. F o r sy stems requiring less than 50 percent removal of arsenic, the
Ag ency assumed a 1 percent usag e of each P OU option. The Ag ency ’s assumption of

POU usa g e f o r

this size sy ste m is ba se d on the f a c t tha t the e c onomic f e a s ibility of POU
treatment for sy stems serving between 70 and 120 households. Therefore, this option
would be less preferred by sy stems in this siz e in comparison to sy stems serving less than
100 people. W ith the increase in households, the manag e ment of this treatment strateg y
be c o me s pr og r e ssive ly c o mple x a nd c o st pr ohibitive

. F o r sy ste m s se r v ing mor e tha n 500
people, the Ag ency did not consider any usag e.

5. Anion Ex chang e (AX). The proposed rule decision tree utilized anion ex chang e to a g r eat

ex tent. The upper bounds were based on the co-occurrence of sulfate (Table I X -7 of the
proposed rule). This table is replicated below as Ex hibit A-5. Many comments on the

Appendix A, Decision Tree and Large System Costs A -12 P roposed Arsenic in Drinking Water Rule RIA

### proposed rule noted other problems that would limit the use of anion ex chang e

. The first

was that the brine stream could be considered haz a rdous waste. B a sed on a review of this
issue, the evaporation pond and chemical precipitation options were eliminated.

Di scharg e t o a P O TW was not affect ed by t h i s i ssue because of t h e dom est i c sewag e

ex clusion in 40 CF R 261.4. I n addition, the Ag ency received comments sug g e sting that

str i ng e n t te c hnic a lly ba se d loc a l limits ( T B L L ) f o r

a r se nic a nd tota l dissolve d solids
(TDS) in various jurisdictions nationwide would limit the use of publicly owned

t r eat m e nt works (P OTW ) for di scharg e of ani on ex chang e wast e bri n e. Therefore, aft e r

ex amining other potential restrictions on POTW discharg e of waste brine, the Ag ency believes lowering the usag e of anion ex chang e with brine disposal to a POTW in the
decision tree would be appropriate. I n addition, the upper sulfate concentration has been
reduced to 50 mg /L because of concerns about its effect on TDS increase.

Exhibit A

- 5: Ground W a ter: A r senic and Sulfate Co-occurrence

Inf l uent Ar seni c L i k el i hood of Sul f ate ( per cent)

< 25 mg /L 25- 120 mg /L > 1 20 mg /L

< 10 ug /L 48 33 19

10- 20 ug /L 35 39 26

> 20 ug /L 33 38 30

I t was assumed that sulfate concentration and percent waste brine volume (in relation to
backg r ound wastewater volume) are factors that would determine anion ex chang e
selection for arsenic treatment. Percent waste volume was related to removal efficiency

. Requiring lower removal efficiencies allow sy stems to treat a smaller volume of water

tha n a t a hig h e r r e mova l e f f i c i e n c y

. Sy ste m s will ble nd a n untr e a t e d por tion with a

tr e a t e d por tion of wa te r to r e duc e c o sts while still c o mply ing with the MCL

. B a se d on
volume considerations, the option with sulfate less than or equal to 20 mg /L was selected
about three times more frequently than the option with sulfate between 20 and 50 mg /L

. The brine volume to backg r ound wastewater volume also contributed to correlation

bet w een ani on ex chang e use and sy st em si z e

.

An inc r e a s e in tota l dissolve d solids f r o m sa lt use d f o r

r e g e ne r a tion would like l y r e str i c t

the use of anion ex chang e in the arid Southwest. However, arsenic occurrence is not

limite d to just the Southwe s t. The r e a r e a r e a s in the mid- w e s t a nd Nor t he a s t with a r se nic

above the MCL

. The upper bound for sy stems (small sy stems) using anion ex chang e
with POTW discharg e was 7 percent. F o r many sy stem siz e categ ories, anion ex chang e with sulfate less than 20 mg /L is the least ex pensive option. However, it is only be

sel ect ed by 5 percent or l e ss of t h e sy st em s because of pot ent i a l adverse i m p act s from
disposing the br ine in the sa nita r y se we r sy ste m

.

Appendix A, Decision Tree and Large System Costs A -13 P roposed Arsenic in Drinking Water Rule RIA

### 6. Table I X -9 of the proposed rule presented the co-occurrence of iron and arsenic. This
table is replicated below as Ex hibit A-6. Approx imately 18 percent of the sy stems had
iron concentration above the secondary standard of 300 ug /L

. One reference indicated

that a 20:1 F e /As ratio could remove up to 80 percent of the arsenic. I t was assumed that
two thirds of the sy stems above the secondary standard would have sufficient iron to
achieve hig h arsenic removals.

Exhibit A

- 6: Ground W a ter: A r senic and Iron Co-occurrence

Inf l uent Ar seni c L i k el i hood of Ir on ( per cent)

< 300 ug /L > 300 ug /L

< 10 ug /L 82 18

10- 20 ug /L 81 19

> 20 ug /L 71 29

B a sed on the Ag ency ’s best professional judg ement, the Ag ency believes that for g r oundwater

sy stems serving less than 500 people, the selection of AA would likely be distributed among

sy stems in a 3:1 ratio for sy stems with a raw water natural pH between 7 and 8 and sy stems with
a raw water pH g r eater than 8. This is based on raw g r oundwater data from the USGS National

W a t e r I n form at i on S y st em t h at was anal y z ed i n t h e co-occurrence report

. P r oj ect i ons on t h e percent of sy stems with raw water pH g r eater than 8 were made for each reg i on. The hig h est

pe r c e n ta g e f o r

a n y r e g i on wa s a ppr ox ima te ly 25 pe r c e n t. As a c onse r va tive e s tima te , this wa s
assumed nationwide.

F o r g r oundwater sy stems serving more than 500 people, the Ag ency believes that the selection of
AA would likely be distributed evenly among pH adjusted AA with hig h end run leng th (23,100

B V ) and pH adjusted AA with low end run leng th (15,400 B V ). The Ag ency also believes that
there would be a small percentag e of sy stems serving more than 500 people that would continue
to use AA without pH adjustment. However, the Ag ency believes the usag e of AA technolog y without pH adjustment would decrease with increasing sy stem siz e

.

F o r g r oundwater sy stems serving 1,000 to10,000 people, the Ag ency assumed a 10 percent usag e of coag ulation microfiltration distributed evenly among mechanical dewatering and nonmechanical dewatering options. F o r sy stems serving more than 10K people, the Ag ency assumed

a

inc r e a s e d usa g e ( 14 pe r c e n t) of c o a g ula tion mic r o f iltr a tion with me c h a n ic a l de wa te r i ng
dom i n at i n g i n t h ese si z e cat eg ori e s because of space consi d erat i on.

Appendix A, Decision Tree and Large System Costs A -14 P roposed Arsenic in Drinking Water Rule RIAExhibitA-7ProbabilityDecision Tree: Ground Water Systems Serving100 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation1.01.01.02ModifyCoagulation/Filtration and pre-oxidation1.01.01.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation5.03.02.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation2.01.01.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation56.063.070.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation19.021.023.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.012POUActivated Alumina and pre-oxidation2.05.00.013POUReverse Osmosisand pre-oxidation2.05.02.0SumofProbabilities:100.00100.00100.00ExhibitA-8ProbabilityDecision Tree: Ground Water Systems Serving 101-500 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation5.03.02.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation2.01.01.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation56.063.064.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation19.021.022.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.02.03.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.03.012POUActivated Alumina and pre-oxidation1.03.00.013POUReverse Osmosisand pre-oxidation1.03.01.0SumofProbabilities:100.00100.00100.00ExhibitA-9ProbabilityDecision Tree: Ground Water Systems Serving 501-1,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation5.03.02.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation2.01.01.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation25.030.031.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation2.02.02.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation25.030.030.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation25.030.030.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-10ProbabilityDecision Tree: Ground Water Systems Serving 1,001-3,300 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation5.03.02.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation2.01.01.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation5.05.05.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation5.05.05.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation17.016.017.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation25.033.033.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation25.033.033.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-11ProbabilityDecision Tree: Ground Water Systems Serving 3,301-10,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation3.03.03.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation5.03.02.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation2.01.01.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation8.08.08.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation24.025.026.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation26.027.027.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation26.027.027.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-12ProbabilityDecision Tree: Ground Water Systems Serving 10,001-50,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation3.01.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation12.012.012.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation11.011.011.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation32.033.034.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation32.033.033.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-13ProbabilityDecision Tree: Ground Water Systems Serving 50,001-100,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation3.01.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation12.012.012.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation7.07.07.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation34.035.036.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation34.035.035.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-14ProbabilityDecision Tree: Ground Water Systems Serving 100,001-1,000,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation12.012.012.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation4.04.04.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation37.037.037.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation37.037.037.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-15ProbabilityDecision Tree: Surface Water Systems Serving100 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation28.028.028.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation44.044.044.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation16.016.016.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation4.04.04.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation4.04.04.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-16ProbabilityDecision Tree: Surface Water Systems Serving 101-500 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation8.08.08.02ModifyCoagulation/Filtration and pre-oxidation53.053.053.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation24.024.024.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation9.09.09.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation3.03.03.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation3.03.03.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-17ProbabilityDecision Tree: Surface Water Systems Serving 501-1,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation21.021.021.02ModifyCoagulation/Filtration and pre-oxidation70.070.070.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation1.01.01.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation4.04.04.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation4.04.04.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-18ProbabilityDecision Tree: Surface Water Systems Serving 1,001-3,300 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation18.018.018.02ModifyCoagulation/Filtration and pre-oxidation79.079.079.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation1.01.01.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-19ProbabilityDecision Tree: Surface Water Systems Serving 3,301-10,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation11.011.011.02ModifyCoagulation/Filtration and pre-oxidation87.087.087.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-20ProbabilityDecision Tree: Surface Water Systems Serving 10,001-50,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation5.05.05.02ModifyCoagulation/Filtration and pre-oxidation95.095.095.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-21ProbabilityDecision Tree: Surface Water Systems Serving 50,001-100,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation6.06.06.02ModifyCoagulation/Filtration and pre-oxidation88.088.088.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation1.01.01.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation2.02.02.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation3.03.03.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitA-22ProbabilityDecision Tree: Surface Water Systems Serving 100,001-1,000,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation5.05.05.02ModifyCoagulation/Filtration and pre-oxidation93.093.093.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.00.00.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation0.00.00.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation1.01.01.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00

### A

. 6 Very Large Sy stem Cost Methodology

EPA must conduct a thoroug h cost-benefit analy s is, and provide comprehensive, informative,
and understandable information to the public about its reg u latory efforts. As part of these
analy s es, EPA evaluated the reg u latory costs of compliance for very larg e sy stems, who would be
subject to the new arsenic drinking water reg u lation. The nation’s 25 larg est drinking water

sy stems (i.e., those serving a million people or more) supply approx imately 38 million people
and g e nerally account for about 15 to 20 percent of all compliance-related costs. Accurately

de te r mining the s e c o sts f o r

f

u tur e r e g u la tions is c r itic a l

. As a r e sult, EPA ha s de ve lope d
compliance cost estimates for the arsenic and radon reg u lations for each individual sy stem that

serves g r eater than 1 million persons. These cost estimates help EPA to more accurately assess the cost impacts and benefits of the arsenic reg u lation. The estimates also help the Ag ency identify lower cost reg u latory options and better understand current water sy stems’ capabilities

and constraints.

The sy stem costs were calculated for the 24 public water sy stems that serve a retail population

g r eater than 1 million persons and one public water sy stem that serves a wholesale population of
16 million persons. Ex hibit A-23 lists these 25 public water sy stems. The disting u ishing

charact eri s t i c s of t h ese very l a rg e sy st em s i n cl ude:

• a larg e number of entry points from diverse sources;

• mix ed (i.e. g r ound and surface) sources;

• o ccurrence not conducive to mathematical modeling ;

• s ig nificant levels of wholesaling ;

• s ophisticated in-place treatment;

• r et rofi t cost s dram at i cal l y i n fl uenced by si t e -speci fi c fact ors; and

• l arg e amounts of waste manag e ment and disposal which can contribute substantial

costs.

Generic models cannot incorporate all of these considerations; therefore, in-depth

c h a r a c t e r iza tions a nd c o st a n a l y s e s we r e de ve lope d utilizing se ve r a l e x isting da ta ba se s a n d

survey s.

The profi l e for each sy st em cont ai ns i n form at i on such as desi g n and averag e dai l y fl ows,

tr e a tme nt f a c ility dia g r a ms, c h e mic a l f e e d pr oc e sse s, wa te r qua lity pa r a me te r s , sy ste m la y outs, and intake and aquifer locations. Sy stem and treatment data were obtained from the following

sources:

• T he I n formation Collection Rule (1997);

• T he Community W a ter Supply Survey (1995);

• T he Association of Metropolitan W a ter Ag encies Survey (1998);

• T he Safe Drinking W a ter I n formation Sy stem (SDW I S ); and

• T he American W a ter W o rks Association W A TERSTATS Survey (1997)

W h ile these sources contained much of the information necessary to perform cost analy s es, the
Ag e n c y wa s still missing some of the de ta ile d a r se nic oc c u r r e nc e da ta in the s e la r g e wa te r

Appendix A, Decision Tree and Large System Costs A -31 P roposed Arsenic in Drinking Water Rule RIA

### sy stems. W h ere major g a ps ex isted, especially in g r oundwater sy stems, occurrence data obtained

f r o m the Sta t e s of Te x a s, Ca lif or nia

, a nd Ar izona , the Me tr opolita n Wa te r Distr i c t of Southe r n California Arsenic Study (1993), the National I norg a nic and Radionuclides Study (EPA, 1984),

a nd utilitie s we r e use d. B a se d on da ta f

r o m the studie s , de ta ile d c o sts e s tima te s we r e de r i ve d f o r
each of t h e very l a rg e wat e r sy st em s.

Exhibit A

- 23

List of Large Wat e r Sy st ems That Serv e M o re Than 1 M illion People

PWS ID # U tility N a m e

1 A Z 0407025 Phoenix M unicipal W a t e r Sy st em

2 C A0110005 East Bay M unicipal Ut ilit y Dist r ict

3 C A1910067 Los Angeles-Cit y Dept

. of W a t e r and Power

4 C A1910087 M e t r opolit an W a t e r Dist r ict of Sout hern California

5 C A3710020 San Diego- Cit y of

6 C A3810001 San F r ancisco W a t e r Depart m ent

7 C A4310011 San Jose W a t e r Com pany

8 C O 0116001 Denv er W a t e r Board

9 F L4130871 M i am i-Dade W a t e r And Sewer Aut horit y

- M a in Sy st em

10 G A 1210001 Cit y of At lant a

11 I L0316000 Cit y of Chicago

12 M A 6000000 M a ssachuset t s W a t e r Resource Aut horit y

13 M D 0150005 W a shingt on Suburban Sanit a t i on Com m i ssion

14 M D 0300002 Balt im ore Cit y

15 M I 0001800 Cit y of Det r oit

16 M O 6010716 St

. Louis Count y W a t e r Count y

17 NY 5110526 Suffolk Count y W a t e r Aut horit y

18 NY 7003493 New Y o rk Cit y Aqueduct Sy st em

19 O H 1800311 Cit y of Clev e land

20 PA1510001 Philadelphia W a t e r Depart m ent

21 PR0002591 San Juan M e t r opolit ano

22 TX0570004 Dallas W a t e r Ut ilit y

23 TX1010013 Cit y of Houst on- Public W o rk s Depart m ent

24 TX150018 San Ant onio W a t e r Sy st em

25 W A 5377050 Seat t l e Public Ut ilit ies

Appendix A, Decision Tree and Large System Costs A -32 P roposed Arsenic in Drinking Water Rule RIA

### Cost estimates were g e nerated for each sy stem at several MCL options. The total capital costs
and operational and maintenance (O & M) costs were calculated using the profile information

g a thered on each sy stem, conceptual desig n s (i.e., vendor estimates and RS Means), and
modified EPA cost models (i.e., W a ter and W a terCost models). The models were modified
based on the g e neral cost assumptions developed in the Phase I W a ter Treatment Cost Upg r ades

(EPA, 1998).

Pr e limina r y c o st e s tima te s we r e se nt to a ll of the sy ste m s f o r

the i r r e vie w

. Appr ox ima te ly 30
percent of the sy stems responded by submitting revised estimates and/or detailed arsenic

occurrence data. B a sed on the information received, EPA revised the cost estimates for those

sy stems. B a sed on the results, only 3 of the very larg e sy stems had capital and/or O& M

ex penditures for comply ing with a MCL of 10 μg /L

. More detailed costs estimates for each very
larg e water sy stem can be found in Radon and Arsenic Reg u latory Compliance Costs for the 25

L a r g e s t Public Wa te r Sy ste m s doc ume n t, whic h is loc a t e d in the wa te r doc ke t.

Appendix A, Decision Tree and Large System Costs A -33 P roposed Arsenic in Drinking Water Rule RIA

## A ppendi x B: A ssumpti ons and M e thodol ogy for Estimating Cancer Risks A v oided and Benefits

B.1 Communit y Wat e r Sy st ems Serv ing Few e r t h an One M illion People

B.1.1 Introduction

EPA’ s e s tima tion of the numbe r of c a n c e r c a s e s r e sulting f r o m c u r r e nt le ve ls of e x posur e to

a r se nic f r o m dr inking wa te r in c o mmunity wa te r sy ste m s se r v ing f e we r tha n one million pe ople

, and the number of those cases that would be avoided following implementation of a specified

arsenic MCL are obtained using the following basic risk alg o rithm.

R In d 

### = C ( As) In d 

### * [ D W In d 

### * DW Ad j 

### ] * R Un i t 

### Equation B-1

The components of this risk alg o rithm are as follows.

**C(As) Ind**  

### is the concentration of arsenic in drinking water that a g i ven individual is ex posed to, on

a v e r a g e

, ove r the c our se of his or he r lif e time

. C( As) In d 

### is obtained from the occurrence
assessment distributions for surface water and g r ound water and is ex pressed in units of μ g /L

.

**DW Ind**  

### is the daily drinking water consumption for a g i ven individual, and is incorporated in this

mode l a s a lif e time we ig hte d a v e r a g e e x pr e sse d in units of L

/ kg

- d a y

. As a lif e time we ig hte d

averag e, this drinking water consumption value reflects differences in water consumption per
kilog r am body weig ht that is observed to occur over an individual’s lifetime. This variable is

also a function of the individual’s sex

.

**DW Ad**  **j** 

### is an adjustment factor constant ( = 70 kg ÷ 2 L / day ) that is applied to the weig hted

averag e drinking water consumption values for individuals to account for the fact that the unit
cancer risk factor (as described below) is based upon an assumed lifetime averag e daily intake of

2 L / day and a lifetime averag e body weig ht of 70 kg

.

I t should be noted that the quantity [ D W In d 

### * DW Ad j 

### ] is a l so r e f e r r e d to in this mode ling e f f

o r t a s
the L i f e time Re la tive Ex posur e F a c t or ( L REF )

. The L R EF r e f l e c t s a pa r tic ula r individua l’ s

lif e time e x posur e to a r se nic f r o m dr inking wa te r

, g i ve n tha t pe r s on’ s DW In d 

### va lue r e la tive to a n “averag e” individual consuming 2 L / day of water and weig hing 70 kg

. An L R EF value less than

one indic a t e s the pe r s on ha s le ss lif e time e x posur e ( a nd the r e f or e le ss r i sk) tha n suc h a n “ a v e r a g e

pe r s on” use d to de r i ve the unit r i sk f a c t or ; simila r l y a

va lue g r e a t e r tha n one indic a t e s a hig h e r

lif e time e x posur e a nd g r e a t e r r i sk tha n tha t “ a v e r a g e pe r s on”

.

**R Uni**  **t** 

### is the unit cancer risk factor for the specific endpoint of concern (e.g ., bladder cancer, or
lung cancer). This factor is in units of “ex pected cases per person per μg /day .” I t is important to
note that these unit risks, as derived from the Morales (2000) study are lifetime risks, that were
developed with an underly i ng assumption of 70 y ears of ex posure and a lifetime averag e water

Appendix B, Assumptions and Methodology for B-1 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### consumption of 2 L / day and body weig ht of 70 kg

. I t should also be noted that the Morales
(2000) cancer risk factors used in this modeling

, which are derived from an analy s is of the
Taiwan data, are specific to a particular cancer endpoint (bladder, lung ) and are sex

- dependent.

The benefit modeling performed in support of the arsenic reg u lation utilizes Equation B

- 1 in a
Monte Carlo simulation framework that provides information on the ag g r eg ate number of cases
of cancer occurring (and avoided) in the overall population, as well as a characteriz ation of the

distribution of risks ex perienced by different individuals in the ex posed population as a result of
individual variability in ex posure conditions. B ecause some of the factors that result in

individua l va r i a b ility in e x posur e a nd r i sk a r e se x a nd sour c e wa te r de pe nde nt, the Monte Ca r l o model also incorporates information on fraction of males and females in the population, and on
the proportion of individuals using surface water versus g r ound water as their primary
community water supply source.

As a n ove r v ie w of how the simula tion mode l ope r a te s, it c a n be vie w e d a s be ing simila r to ta king
a representative sample from the population ex posed to arsenic in drinking water from

c o mmunity wa te r sy ste m s a nd using the r e sults obta i ne d f r o m tha t sa mple to c h a r a c te r i ze the
overall risks of the population. I n this modeling

, a total of 2,000 iterations (samples) were used

for each model run.

I n each iteration, an individual is selected, and identified as male or female and as a g r ound water
or surface water user, based on estimated probabilities associated with those characteristics.
Then, a value is selected for each of the parameters in Equation B

- 1, based on the underly i ng probability distributions developed for each of those variables, and specific to the sex and source
water as specified for that individual as appropriate.

The Equa tion B

- 1 c a l c u la tion is c a r r i e d out to de te r mine tha t individua l’ s lif e time c a nc e r r i sk,

R In d 

### . The results of all 2,000 iterations are ag g r eg ated, and the averag e individual risk across all

ite r a tions is de te r mine d. This a v e r a g e r i sk va lue

, multiplie d by the numbe r of individua ls in the
populations served by the affected water sy stems, provides the number of cases of cancer

ex pect ed.

To c o mple te the be ne f its mode ling

, a ba se line with no r e duc tion in the MCL ( o r a r se nic le ve ls in
drinking water) is run first, with subsequent runs reflecting reductions in occurrence levels
corresponding to the particular MCL being evaluated. The number of cancer cases estimated for

these runs at the various MCL options is subtracted from the baseline cancer cases to obtain the

e s tima te of c a s e s a voide d.

The following sections provide further discussion of the components of the model, including
further information on how upper and lower bounds for the benefits estimates were established,
how additional adjustments have been made to account for the differences in dietary intake of
arsenic, and to reflect differences in cancer mortality rates between the affected US population
and the Taiwan population that served as the basis of the unit risk factors.

Appendix B, Assumptions and Methodology for B-2 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### B

. 1.2 A r senic C oncent r at ions in Finished Wat e r of C o mmunit y Wat e r Sy st ems
Serv ing Few e r t h an One M illion People

This section provides further information on the variable C(As) In d 

### in Equation B

- 1.

EPA has developed log normal arsenic occurrence distributions for the nation’s community

g r ound water and surface water sy stems serving fewer than one million people. These arsenic

oc c u rr e nc e distr i butions, whic h r e f l e c t the pr oba bility of a r se nic c onc e n tr a tions oc c u rr i ng a t various levels in finished drinking water in surface and g r ound water sy stems, are used in the

be ne f its mode l to c h a r a c t e r ize the va r i a b ility in a r se nic dr inking wa te r c onc e n tr a tions

ex perienced by different individuals using these public water supplies.

Althoug h the arsenic occurrence distributions were developed to characteriz e the full distribution
of finished water arsenic concentrations, the benefits modeling focused only on the portion of

t hose di st ri but i on ex ceedi n g 3 μ g / L , t h e l o west MC L opt i on consi d ered by EP A. EP A used t h e separate log normal occurrence probability distributions for g r ound water and surface to first

det e rm i n e t h e num ber of peopl e served by com m uni t y wat e r sy st em s from each of t hose t w o source waters (and the total) ex pected to have arsenic present above 3 μg /L

.

I n the Monte Carlo simulation model, the selection of a value for C(As) In d 

### of Equation B

- 1 in
each iteration involved two steps. F i rst, using relative probabilities derived from the log normal
occurrence distributions, an individual was selected and identified as being served by either

g r ound or surface water having an arsenic above 3 μ g /L

. I n the second step, a specific finished
water arsenic concentration was chosen at random from the appropriate g r ound or surface water

occurrence di st ri but i on i n t h e rang e ex ceedi n g 3 μ g / L

.

B y including a sufficient number of iterations in the Monte Carlo model, the full rang e of

individua l va r i a b ility in e x posur e to dif f

e r e nt a r se nic c onc e n tr a tions in the r a ng e of inte r e st f o r both surface water and g r ound water sources is obtained.

I n the ba se line a n a l y s is ( t ha t is, with no c h a n g e to the 50 μg /L MCL ) , the se le c t e d f i nishe d wa te r arsenic concentration value was used directly in the risk equation. I n the model runs for various

MCL options, that value was compared to the MCL

. I f that value was less than or equal to the

MCL

, it was also kept. I f however the selected value ex ceeded the MCL

, then it was multiplied
by a factor of 0.8 of the MCL value reflecting an assumption that sy stems would treat to a level

of 80% of the MCL

. So, for ex ample, if an iteration of a model run ex amining the 10 μg /L MCL
option produced a finished water arsenic value of 25 μg /L , that value was chang e d to 8 μg /L

. I f
the model run were for the option of a 20 μg /L MCL

, that value would be chang e d to 16 μg /L

.

I t should be noted that for the purposes of the benefits modeling

, the concentration used is
implied to be a lifetime averag e ex posure level for the individual in that iteration.

B.1.3 Drinking W a ter Consumption

This section provides further information on the variables DW In d 

### and DW Ad j 

### in Equation B

- 1.

Appendix B, Assumptions and Methodology for B-3 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### The vari abl e DW In d 

### r e f l e c t s the dif f

e r e nc e s ( v a r ia bility ) in individua l wa te r c onsumption within

the ex posed population. I n Equation B

- 1, the variable DW In d 

### is ex pressed in units of L / kg -day
reflecting differences in consumption among individuals in the population as a function of body

we ig ht. This va lue is a lif e time a v e r a g e wa te r c onsumption r a te f o r

individua ls, r e c o g n izing tha t consumption of water per kg body weig ht chang e s over a lifetime, particularly between infancy

, childhood and adulthood.

EPA obta i ne d the distr i bution of individua l we ig hte d a v e r a g e lif e time wa te r c onsumption va lue s
in terms of L / kg -day by integ r ating available data on the distribution of water consumption, in

units of L / day

, by males and females in the US in various ag e rang es with information on the
distribution of body weig hts for males and females within those same ag e rang es.

The ag e and sex specific distributions of drinking water consumption in L / day are provided by
data from the Continuing Survey of F ood I n takes by I ndividuals (CSF I I ) for the y ears 1994-1996
conducted by the U.S. Department of Ag riculture (USDA) and presented in EPA (1999). The
data were collected from a sample population of 15,303 individuals in the 50 states and the
District of Columbia that was chosen to be representative of the US population based on the

1990 census data.

The collection and analy s is of drinking water consumption data in the CSF I I provided the basis
for several alternative way s of viewing drinking water consumption, in particular, how to include

various direct water sources – for ex ample, from community tap water, bottled water, household
wells – consumed directly as a beverag e , and indirect water that is water from such sources that
is added to other foods during preparation at home or by food service establishments.

F o r the purposes of the arsenic benefits analy s is, EPA chose to use two alternative sets of
drinking water distributions to characteriz e lower and upper bounds of risk.

F o r the lower bound analy s es, EPA used the CSF I I drinking water distribution limited to the
community tap water source, but which included both direct and indirect consumption of that

water. This lower bound distribution reflects an overall averag e individual consumption (across
all ag es and both sex e s) of approx imately 1.0 L / day

, with a 90 th 

### pe r c e n tile va lue of a ppr ox ima te ly

2.1 L / day

.

F o r the upper bound analy s es, EPA used the CSF I I drinking water distribution for total water,

whic h inc l ude s c o mmunity ta p wa te r

, bottle d wa te r

, a nd othe r sour c e s , a nd a l so r e f l e c t s both
direct and indirect consumption of that water. This upper bound distribution reflects an overall

averag e individual consumption (across all ag es and both sex e s) of approx imately 1.2 L / day

, with

a 90 th 

### percentile value of approx imately 2.3 L / day

.

For t h e purposes of t h e arseni c benefi t s anal y s i s , i t was necessary t o i n t e g r at e t h e ag e and sex
specific water consumption distributions (in L / day ) with information available from Statistical
Abstracts (1994) providing body weig ht distributions for the same sex

- ag e categ ories included in

the CSF I I data. A submodel was run for this portion of the benefits analy s is that effectively

g e nerated DW In t 

### va lue s f o r

individua ls by “ c onstr uc ting ” a lif e time we ig hte d a v e r a g e wa te r

Appendix B, Assumptions and Methodology for B-4 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### consumption value in units of L / kg -day

. F i ve ag e categ ories, based on the manner in which

CSF I I da ta we r e pr e s e n te d, we r e use d f o r

building the s e lif e time c onsumption va lue s

. The s e a g e

cat eg ori e s were:

< 1

1 – 10

11 – 19

20 – 64

65 – 70

Ag ai n, C S FI I provi ded wat e r consum pt i on i n form at i on separat e l y for m a l e s and fem a l e s i n each
of these categ ories, and Statistical Abstracts (1994) provided body weig ht distributions for these

categ ories. I n the simulation, an individual is selected, male or female according to the
proportions of 51.9% male, 48.1% female. A value for water consumption in L / day and an

averag e body weig ht for each of the five ag e categ ories is selected, and an averag e intake for each

ag e categ ory is computed by dividing the water consumption value selected by the body weig ht

sel ect ed.

The individua l’ s lif e time we ig hte d a v e r a g e ( D W In d 

### in Equation B

- 1) is then computed by

averag ing across the five ag e g r oups, weig hting each appropriately for the number of y ears spent

i n t h at ag e rang e.

An additional adjustment factor had to be incorporated into Equation B

- 1 in order to account for
the fact that the cancer unit risk factors used were calculated with an underly i ng assumption that
it applied to an “averag e” person weig hing 70 kg and consuming 2 L / day over the entire 70 y ear lifetime (or 0.0286 L / kg -day ). Since drinking water consumption is being modeled in this
analy s is to ex plicitly account for the variability in water consumption as a function of body
weig ht, proceeding without this adjustment would overestimate the cancer risk for those
individuals with a lifetime weig hted averag e consumption of less than 0.0286 L / kg -day , and
similarly would underestimate it for those consuming more than 0.0286 L / kg -day as a lifetime

averag e.

B ecause, as noted from the CS FI I data, averag e water consumption across all ag e and sex g r oups
is closer to 1.0 – 1.3 L / day and because lifetime averag e body weig hts are (especially for

f

e ma le s) lowe r tha n 70 kg , f a iling to ma ke this a d justme nt would in the a g g r e g a t e ove r e stima te

cancer ri sk.

B y apply i ng the DW Ad j 

### adjustment factor of 70 kg /(2 L / day ) to the water consumption values
obtained in the simulation, this correction for the underly i ng basis of the risk value is

accom p l i s hed.

The water consumption and adjustment discussed above are described in g r eater detailed in the

RI A and its accompany i ng Appendix B

. I n that analy s is, the product of the water consumption

a nd the a d justme nt f a c t or a r e de sc r i be d a s the L i f e time Re la tive Ex posur e F a c t or s ( L REF ) , whic h

reflects the ex posure and risk relative to the 70 kg , 2 L / day (i.e., 0.0286 L / kg -day ) person. I n that

Appendix B, Assumptions and Methodology for B-5 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### more detailed analy s is, it is shown that the overall distribution of these factors tends to be
log normal with means and standard deviations as shown in Ex hibit B

- 1 for both males and
females and the lower and upper bound water consumption distributions. I n essence, these L R EF values indicate that, on averag e, individual ex posure and risk are about 60% to 80% of what they
would be if every individual were assumed to be a 70 kg , 2 L / day person.

Exhi bi t B- 1 Summary of Li f e t i me Rel a t i v e Exposure Fact ors ( L REF) : ( P roduct of DW In d 

### * D W Ad j 

### . O v eral l Di st ri but i ons are Lognormal )

Community Water Consumption Data Total Water Consumption Data

Male Mean = 0.60

s.d. = 0.61 Mean = 0.73

s.d. = 0.62

Female Mean = 0.64 Mean = 0.79



### B

. 1.4 C a ncer R i sk Fact ors

This section provides further information on the variable R Un i t 

### in Equation B

- 1.

I n its 1999 report, “Arsenic in Drinking W a ter,” the NRC analy z ed bladder cancer risks using

data from Taiwan. I n addition, NRC ex amined evidence from human epidemiolog i cal studies in
Chile and Arg e ntina, and concluded that risks of bladder and lung cancer had comparable risks to
those “in Taiwan at comparable levels of ex posure” (NRC, 1999). The NRC also ex amined the
implications of apply i ng different statistical analy s es to the newly available Taiwanese data for

the pur pose of c h a r a c t e r izing bla dde r c a n c e r r i sk. While the NRC’ s wor k did not c onstitute a
form al ri sk anal y s i s , t h ey di d ex am i n e m a ny st at i s t i cal i ssues (e.g ., m easurem ent errors, ag especific probabilities, body weig ht, water consumption rate, comparison populations, mortality
rates, choice of model) and provided a starting point for additional EPA analy s es. The report
noted that “poor nutrition, low selenium concentrations in Taiwan, g e netic and cultural
characteristics, and arsenic intake from food” were not accounted for in their analy s is (NRC,
1999, pg . 295). I n the J une 22, 2000 proposed rule, EPA calculated bladder cancer risks and
benefits using the bladder cancer risk analy s is from the NRC report (NRC, 1999). W e also
estimated lung cancer benefits in a “W hat I f ” analy s is based on the statement in the 1999 NRC
report that “some studies have shown that ex cess lung cancer deaths attributed to arsenic are 2-5
fold g r eater than the ex cess bladder cancer deaths” (NRC, 1999).

I n J u ly , 2000, a peer reviewed article by Morales et al. (2000) was published, which presented

a dditiona l a n a l y s e s of bla dde r c a n c e r r i sks a s we ll a s e s tima te s of lung a nd live r c a n c e r r i sks f o r the same Taiwanese population analy z ed in the NRC report. EPA summariz e d and analy z ed the
new information from the Morales et al. (2000) article in a NODA published on October 20,
2000 (65 F R 63027; EPA, 2000). Althoug h the data used were the same as used by the NRC to
analy z e bladder cancer risk in their 1999 publication, Morales et al. (2000) considered more
dose-response models and evaluated how well they fit the Taiwanese data for both bladder cancer
risk and lung cancer risk. Ten risk models were presented in Morales et al. (2000) used with and

Appendix B, Assumptions and Methodology for B-6 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### without one of two comparison populations. After consultation with the primary authors
(Morales and Ry an), EPA chose Model 1 with no comparison population for further analy s is.

EPA believes that the models in Morales et al. (2000) without a comparison population are more
reliable than those with a comparison population. Models with no comparison population
estimate the arsenic dose-response curve only from the study population. Models with a
comparison population include mortality data from a similar population (in this case either all of
Taiwan or part of southwestern Taiwan) with low arsenic ex posure. Most of the models with
comparison populations resulted in dose-response curves that were supralinear (hig her than a
linear dose response) at low doses. The curves were “forced down” near z e ro dose because the
comparison population consists of a larg e number of people with low risk and low ex posure. EPA believes, based on discussions with the authors of Morales et al. (2000), that models with a
comparison population are less reliable, for two reasons. F i rst, there is no basis in data on
arsenic’s carcinog enic mode of action to support a supralinear curve as being biolog ically
plausible. To the contrary , the conclusion of the NRC panel (NRC, 1999) was that the mode of

action data led one to ex pect dose responses that would be either linear or less than linear at low

dose. However, the NRC indicated that available data are inconclusive and “...do not meet
EPA’s 1996 stated criteria for departure from the default assumption of linearity .”(NRC, 1999)

Second, models that include comparison populations assume that the study and comparison
populations are the same in all important respects ex cept for arsenic ex posure. Yet Morales et al.
(2000) ag ree that “[ t] here is reason to believe that the urban Taiwanese population is not a
comparable population for the poor rural population used in this study .” Moreover, because of
the larg e amount of data in the comparison populations, the model results are sensitive to
assumptions about this g r oup. Evidence that supports these arg u ments are that the risks in the
comparison g r oups are substantially lower than in similarly ex posed members of the study g r oup and the shape of the estimated dose-response chang e s sharply as a result. F o r these reasons, EPA
believes that the models without comparison populations are more reliable than those with them.
Of the models that did not include a comparison population, EPA believes that Model 1 best fits

the data, based on the Akaike I n formation Criterion (AI C ), a standard criterion of model fit,

a pplie d to Poisson mode ls. I n Mode l 1, the r e la tive r i sk of mor t a lity a t a n y time is a ssume d to

increase ex ponentially with a linear function of dose and a quadratic function of ag e.

Morales et al. (2000) reported that two other models without comparison populations also fit the

Taiwan data well: Model 2, another Poisson model with a nonparametric instead of quadratic

a g e e f f

e c t , a nd a multi- sta g e We ibull ( M SW) mode l. Unde r Mode l 2, the points of de pa r t ur e f o r male and female bladder and lung cancer are from 1% to 11% lower than under Model 1, but

within the 95% confidence bounds from Model 1. Model 2 therefore implies essentially the
same bladder and lung cancer risks as Model 1. Under the MSW model, compared to Model 1,
points of departure are 45% to 60% hig h er for bladder cancer and for female lung cancer, and
38% lower for male lung cancer. EPA did not consider the MSW model for further analy s is,
because this model is more sensitive to the omission of individual villag e s (Morales et al., 2000)
and to the g r ouping of responses by villag e (NRC, 1999), as occurs in the Taiwanese data.

However, if the MSW model were correct, it would imply a 14% lower combined risk of lung
and bladder cancers than Model 1, among males and females combined.

Appendix B, Assumptions and Methodology for B-7 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### C onsi d eri n g al l of t h ese resul t s , t h e Ag ency deci ded t h at t h e m o re ex haust i v e st at i s t i cal anal y s i s of the data provided by Morales et al. (2000), as analy z ed by EPA, would be the basis for the
new risk calculations for the final rule (with further consideration of additional risk analy s es) and
other pertinent information. The Ag ency views the results of the alternative models described
above as an additional uncertainty which was considered in the decision concerning the selection

of the final MCL

.

The specific lifetime risk measures provided in the Morales (2000) study that were used in this
benefits analy s is, and their conversion to the R Un i t 

### values of cases per person per μg /L are shown

in Ex hibit B

- 2, below.

Exhibit B-2

R i sk M easures f r om M o rales ( 2000) and as U sed in t h is B e nef i t A n aly s is

Bladder Cancer Lung Cancer

Males F emales Males F emales

ED 01 

### (μg/L)

395 252 364 258

Mean for R Un i t 

### (cases/person per μg/L) 2 .53 x 10 -5 

### 3.97 x 10 -5 

### 2.75 x 10 -5 

### 3.88 x 10 -5



### LED 01 

### ( 

### μ g/L)

326 211 294 213

U pper 95% C L for R Un i t 

### (cases/person per μg/L) 3 .07 x 10 -5 

### 4.74 x 10 -5 

### 3.40 x 10 -5 

### 4.69 x 10 -5



### The ED 01 

### values provided by Morales (2000) indicate that this is the arsenic concentration in

dr inking wa te r tha t if c onsume d by a n individua l ove r a

lif e time ( w ith the a ssumption of 2 L / da y and 70 kg body weig ht) has a 0.01 risk (i.e., 1% probability ) of resulting in the indicated form of

cancer. The L E D 01 

### is the lower 95% confidence bound on the dose producing that 0.01 risk

To be used in the benefits calculation shown in Equation B

- 1, these risk measures are converted
to the units of cases/person per μg /L needed for R Un i t 

### by simply dividing 0.01 by the
corresponding ED 01 

### or L E D 01 

### μg /L values.

I n the Monte Carlo simulation, the R Un i t 

### value was incorporated as normal distribution with
parameters based on the mean and upper 95% confidence limit as shown in Ex hibit 3-D.2

B.1.5 Upper and Low er Bound Considerations

I n carry ing out the arsenic benefits analy s is, differing assumptions were used in an effort to
establish upper and lower bounds on the estimated risks and avoided cases of cancer associated

with the arsenic MCL

. Some of the factors considered in the upper and lower bound estimates

were not ed i n t h e precedi n g di scussi ons. These are di scussed m o re ful l y here.

F o r the upper bound analy s es, EPA used:

Appendix B, Assumptions and Methodology for B-8 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits& 

### The surface water and g r ound water occurrence distributions as provided in the occurrence

anal y s es;

& 

### The drinking water consumption distribution using the total water consumption data from

CSF I I (i.e., averag ing approx imately 1.2 L / day )

& 

### The unit cancer risk factor distribution based on the R Un i t 

### values shown in Ex hibit 3.D.2.

F o r the lower bound analy s es, EPA used:

& 

### The surface water and g r ound water occurrence distributions as provided in the occurrence
analy s es (same as upper bound);

& 

### The drinking water consumption distribution using the community (tap) water consumption

data from CSF I I (i.e., averag ing approx imately 1.0 L / day )

& 

### The unit cancer risk factor distribution based on the R Un i t 

### values shown in Ex hibit B

- 2 for
males only (applied to both males and females), with further downward adjustments for
potential contributions from water used in cooking and from food in the Taiwan population

used to derive the risk factors

The use of the two different drinking water consumption distributions in establishing upper and
lower bounds estimates were discussed previously

. The other two adjustments noted in the third

bullet for the lower bound estimates are described further here. B o th of these adjustments reflect
possible contributions to the cancer cases observed in the Taiwan study associated with arsenic in
the water or food for that population that would not necessarily apply to the US population.

F i rst, the Ag ency made an adjustment to the lower bound risk estimates to take into consideration

the effect of ex posure to arsenic throug h water used in preparing food in Taiwan. The Taiwanese
staple foods were dried sweet potatoes and rice (W u et al., 1989). B o th the 1988 EPA “Special
Report on I n g e sted I norg a nic Arsenic” report and the 1999 NRC report assumed that an averag e Taiwanese male weig hed 55 kg and drank 3.5 liters of water daily , and that an averag e Taiwanese

f

e ma le we ig he d 50 kg a nd dr a nk 2 lite r s of wa te r da ily

. Using the s e a ssumptions, a l ong with a n assumption that Taiwanese men and women ate one cup of dry rice and two pounds of sweet

pota t oe s a da y

, the Ag e n c y r e

- e stima te d r i sks f o r

bla dde r a nd lung c a n c e r , using one a dditiona l
liter water consumption for food preparation (i.e., the water absorbed by hy dration during
cooking ). This adjustment was discussed and used in the October 20, 2000 NODA (65 FR

63027).

Second, an adjustment was made to the lower bound risk estimates to take into consideration the
relatively hig h arsenic concentration in the food consumed in Taiwan as compared to the U.S.
The food consumed daily in Taiwan contains about 50 F g

, versus about 10 F g in the U.S. ( N RC,
1999, pp. 50–51). Thus the total consumption of inorg a nic arsenic (from food preparation and
drinking water) is considered, per kilog r am of body weig ht, in the process of these adjustments.
To carry them out, the relative contribution of arsenic in the drinking water that was consumed as
drinking water, on a F g / kg /day basis, was compared to the total amount of arsenic consumed in
drinking water, drinking water used for cooking , and in food, on a F g / kg /day basis.

Other factors contributing to lower bound uncertainty include the possibilityof a sub-linear doseAppendix B, Assumptions and Methodology for B-9 A rsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### response curve below the point of departure. The NRC noted “Of the several modes of action
that are considered most plausible, a sub-linear dose response curve in the low-dose rang e is
predicted, althoug h linearity cannot be ruled out.” (NRC,1999). The recent Utah study (L ewis et
al., 1999), described in section 5.G.1(b), provides some evidence that the shape of the doseresponse curve may well be sub-linear at low doses. B ecause sufficient mode of action data were

not a v a ila ble

, a n a d justme nt wa s not ma de to the r i sk e s tima te s to r e f l e c t the possibility of a

sublinear dose-response curve. Additional factors contributing to uncertainty include the use of

villa g e we ll da ta r a the r tha n individua l e x posur e da ta , de f i c i e n c i e s in the Ta iwa n e s e die t r e la tive

t o t h e U.S

. di et (sel eni u m

, chol i n e, et c.), and t h e basel i n e heal t h st at us i n t h e Tai w anese st udy
area relative to U.S. populations. The Ag ency did not make adjustments to the risk estimates to
reflect these uncertainties because applicable peer-reviewed, quantitative studies on which to
base such adjustments were not available.

B.1.6 Estimated Population Risk Values

The Monte Ca r l o simula tion pe r f o r m e d f o r

this be ne f its a n a l y s is using the r i sk a l g o r ithm shown
in Equation B

- 1 produce distributions of individual risk values (R In d 

### ) f o r

the ba se line a nd the

various MCL options considered, and for both the upper and lower bound sets of assumptions.

Ex hibit B

- 3 pr ovide s some summa r y sta tistic s f o r

the r e sulting distr i bution of r i sks. Note tha t

the “ex posed population” addressed in this table are those individuals using community g r ound
or surface water supplies serving fewer than one million people having arsenic levels g r eater than
3 μg /L

.

The ke y outputs r e sulting f r o m this Monte Ca r l o simula tion f o r

e s tima ting c a n c e r c a se s a voide d

are the mean risk values shown in Ex hibit B

- 3. The application of these mean risk values to

e s tima te c a s e s a voide d is de sc r i be d in the f o llowing se c tion.

Exhibit B-3 Cancer Risks for U.S. Populations
Exposed A t or A bov e MCL Options, after Treatment
( Low er Bound Wi t h Food and Cooki ng Wat e r A d just ment )

Mean R i sk for Exposed Population (Lower and Upper Bounds) 90 th



### Percentile R i sk for Exposed Population (Lower and Upper Bounds)

3 0 .11 -1.25 x 10 -4 

### 0.22 - 2.42 x 10 -4



### 5 0 .27 - 2.02 x 10 -4 

### 0.55 - 3.9 x 10 -4



### 10 0.63 - 2.99 x 10 -4 

### 1.32 - 6.09 x 10 -4



### 20 1.10 - 3.85 x 10 -4 

### 2.47 - 8.37 x 10 -4



### B

. 1.7 Est i mat e d C a ncer C ases and C ases- A v oided

Appendix B, Assumptions and Methodology for B-10 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### To estimate the number of cancer cases avoided for the various MCL options it is necessary to

fi rst cal cul a t e t h e num ber of cases ex pect ed at t h e basel i n e ri sk l e vel (no chang e i n t h e MC L

, or

50 μ 

### g / L ) , and then for each MCL option. B a seline mean risk values and estimated mean risk

le ve ls f o r

the va r i ous MCL options ( s hown in Ex hibit B

- 3) a r e multiplie d by the tota l numbe r of
people served by community g r ound and surface water sy stems serving fewer than one million
people. B ecause the lower bound risk adjustments are also made to the baseline risk (the risk at

50 μ g / L ) , t h e basel i n e num ber of ex pect ed cases i n t h e adj u st ed ri sk scenari o i s not t h e sam e (i t ’ s

l o wer, j u st as t h e adj u st ed ri sks are l o wer) as t h e basel i n e num ber of ex pect ed cases i n t h e unadj ust e d ri sk scenari o. The num ber of cases avoi ded at each MC L al t e rnat i v e i s det e rm i n ed by

subt ract i n g t h e num ber of cases rem a i n i n g at each opt i on from t h e appropri a t e basel i n e num ber

of

c a s e s

. Thus, to e s tima te c a s e s a voide d, the numbe r of r e ma ining c a s e s e x pe c t e d a t the lowe r

ri sk l e vel s are subt ract ed from t h e num ber of cases ex pect ed at t h e l o wer basel i n e l e vel

, and t h e number of remaining cases ex pected at the hig h er risk levels are subtracted from the number of

cases ex pect ed at t h e hi g h er basel i n e l e vel

.

An upper bound adjustment was made to the number of bladder cancer cases avoided to reflect a
possible lowe r mor t a lity r a te in Ta iwa n tha n wa s a ssume d in the r i sk a sse ssme n t pr oc e s s
described earlier. EPA also made this adjustment in the J une 22, 2000, proposal. I n the Taiwan
study area, information on arsenic related bladder and lung cancer deaths was reported. I n order

to use the s e da ta to de te r mine the pr oba bility of c ontr a c ting bla dde r a nd lung c a n c e r a s a r e sult of

ex posure to arsenic, a probability of mortality g i ven the onset of arsenic induced bladder and
lung cancer among the Taiwanese study population must be assumed. The study area in Taiwan
is a section where arsenic concentrations in the water are very hig h by comparison to those in the
U.S., and an area of low incomes and poor diets, where the availability and quality of medical

c a r e is not of hig h qua lity , by U.S. sta nda r d s. I n its e s tima te of bla dde r c a n c e r r i sk, the Ag e n c y

a ssume d tha t within the Ta iwa n e s e study a r e a

, the pr oba bility of c ontr a c ting bla dde r c a nc e r wa s

r e la tive l y c l ose to the pr oba bility of dy ing f r o m bla dde r c a nc e r ( t ha t is, tha t the bla dde r c a nc e r
inc i de nc e r a te wa s e qua l to the bla dde r c a n c e r mor t a lity r a te )

.

We do not ha ve da ta on the r a te s of sur v iva l f o r

bla dde r c a n c e r in the Ta iwa n e s e villa g e s in the
study and at the time of data collection. W e do know that the relative survival rates for bladder
cancer in developing countries overall rang ed from 23.5% to 66.1 % in 1982-1992 (“Cancer
Survival in Developing Countries,” I n ternational Ag ency for Research on Cancer, W o rld Health
Org a niz a tion, Publication No. 145, 1998). W e also have some information on annual bladder
cancer mortality and incidence for the g e neral population of Taiwan in 1996. The ag e-adjusted
annual incidence rates of bladder cancer for males and females, respectively

, were 7.36 and 3.09
per 100,000, with corresponding annual mortality rates of 3.21 and 1.44 per 100,000
(correspondence from Chen to Herman Gibb, J a nuary 3, 2000). Assuming that the proportion of
males and females in the population is equal, these numbers imply that the mortality rate for
bladder cancer in the g e neral population of Taiwan, at present, is 45%. Since survival rates have
most likely improved over the y ears since the orig inal Taiwanese study , this number represents a
lower bound on the survival rate for the orig inal area under study (that is, one would not ex pect a hig h e r r a te of sur v iva l in tha t a r e a a t tha t time )

. This ha s implic a tions f o r

the bla dde r c a n c e r r i sk

e s tima te s f r o m the Ta iwa n da ta

. I f the r e we r e a n y pe r s ons with bla dde r c a n c e r who r e c ove r e d

and died from some other cause, then our estimate underestimated risk; that is, there were more

Appendix B, Assumptions and Methodology for B-11 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### cancer cases than cancer deaths. B a sed on the above discussion, we think bladder cancer

inc i de nc e c ould be no mor e tha n 2 f o ld bla dde r c a n c e r mor t a lity ; a nd tha t a n 80% mor t a lity r a te would be plausible. Thus we have adjusted the upper bound of cases avoided, which is used in
the benefits analy s is, to reflect a possible mortality rate for bladder cancer of 80%. B ecause lung
cancer mortality rates are quite hig h, about 88% in the U.S.(US EPA, 1998b), the assumption

wa s ma de tha t a ll lung c a n c e r s in the Ta iwa n study a r e a r e sulte d in f a ta litie s.

The total number bladder and lung cases avoided at each MCL are shown in Ex hibit 3-D.3.

These cases avoided include CW S and NTNC cases. The number of bladder and lung cancer cases avoided rang e from 57.2 to 138.3 at an MCL of 3 F g / L

, 51.1 to 100.2 at an MCL of 5 F g/ L

, 37.4 to 55.7 at an MCL of 10 F g / L

, and 19.0 to 19.8 at an MCL of 20 F g / L

. The cases avoided

we r e divide d into pr e m a t ur e f a ta lity a nd mor b idity c a s e s ba se d on U.S. mor t a lity r a te s. I n the

U.S. approx imately one out of four individuals who is diag nosed with bladder cancer actually

di es from bl adder cancer. The mor t a lity r a te f o r

the U.S. is ta ke n f r o m a c o st of illne ss study
recently completed by EP A (US EP A, 1998b). For those diag nosed with bladder cancer at the

a v e r a g e a g e of dia g nosis ( 70 y e a r s) , the pr oba bility f

o r

dy ing of tha t dise a s e dur ing e a c h y e a r
post- dia g nosis we r e summe d ove r a

20- y e a r pe r i od to obta i n the va lue of 26 pe r c e n t. Mor t a lity
rates for U.S. bladder cancer patients have decreased overall by 24 percent from 1973 to 1996.

F o r lung c a n c e r , mor t a lity r a te s a r e muc h hig h e r

. The c o mpa r a b le mor t a lity r a te f o r

lung c a n c e r in the U.S. is 88% (US EPA, 1998b).

B.2 Communit y Wat e r Sy st ems Serv ing M o re t h an One M illion People

A separate analy s is of the number of cancer cases and cases avoided was performed for
community water sy stems serving more than one million people each. This analy s is was based
upon specific information available for each on the occurrence of arsenic in specific sources
(entry points) for those sy stems, the flows for those entry points, and the number of people
served by t hose speci fi c sy st em s.

Only three sy stems serving more than one million people were found to have arsenic levels in

one or more entry point ex ceeding 3 μ g /L : P hoenix

, Houston, and L o s Ang e les.

The ba sic r i sk a l g o r ithm use d f o r

sy ste m s se r v ing f e we r tha n one million pe ople a s shown in
Equat i on B-1 was al so used for cal cul a t i n g cancer cases and cases avoi ded for t h e sy st em s

se r v ing mor e tha n one million pe ople

.

There were two primary difference in the application of Equation B

- 1 for the sy stems serving

mor e tha n one million pe ople r e la tive to its a pplic a tion f o r

sy ste m s se r v ing f e we r tha n one
million. F i rst, the analy s is was not done as a Monte Carlo simulation, but was based on averag e values for the variables in the equation. F o r ex ample. the R Un i t 

### values used were equivalent to the
mean risk values for the upper and lower bound risks as shown previously in ex hibit B

- 2 (with
the various adjustments made to the lower bound value for the potential impacts of other intakes
as described earlier).

Appendix B, Assumptions and Methodology for B-12 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### The water consumption and adjustment factors [ D W In d 

### * DW Ad j 

### ] were simplified and used as

averag e val u es rat h er t h an di st ri but i ons.

The arseni c wat e r concent r at i ons [ C (As) In d 

### ] used were cal cul a t e d separat e l y for each of t h e t h ree

very l a rg e sy st em s usi n g sy st em -speci fi c dat a

. These cal cul a t i ons were carri ed out as fol l o ws.

Data was available on the arsenic concentration at each of the g r ound water and surface water

ent r y poi nt s at each of t h ese t h ree very l a rg e sy st em s. Dat a were al so avai l a bl e on t h e averag e daily flow for the g r ound water and surface water sources in total.

EPA used that information to calculate an initial averag e arsenic concentration, C I n itial 

### , for t h at

port i on of t h e sy st em ex ceedi n g a part i c ul ar MC L opt i on as fol l o ws.

SA 

## + C
GA 

## C

C Initial



## +

where:

C GA 

### =the averag e arsenic concentration in the g r ound water entry points affected at that MCL
option

C SA 

### = t h e averag e arseni c concent r at i on i n t h e surface wat e r ent r y poi nt s affect ed at t h at MC L option

EP GA 

### = the number of g r ound water entry points affected at that MCL option

EP GT 

### = the total number of g r ound water entry points in that sy stem

EP SA 

### = t h e num ber of surface wat e r ent r y poi nt s affect ed at t h at MC L opt i o n

EP ST 

### = t h e t o t a l num ber of surface wat e r ent r y poi nt s i n t h at sy st em

F G 

### = the total averag e daily flow from all g r ound water sources

F S 

### = t h e t o t a l averag e dai l y fl ow from al l surface wat e r sources

F T 

### = the tota l a v e r a g e da ily f

l ow f r o m a ll wa te r sour c e s

These C I n itial 

### values were used for C(As) In d 

### in Equation B

- 1 to calculate the number of baseline
cases in the population affected by the particular MCL option. The number of individuals in the
population affected for a particular option at each of the very larg e sy stems was calculated as
being the same portion of the total population served by that sy stem as the portion of total flow
affected at the g i ven MCL option.

The post- r e g u la tor y c a s e s r e ma ining we r e c a l c u la te d using the sa me pr oc e dur e

, e x c e p t tha t a
constant value was used for C(As) In d 

### that was equal to 0.8 * MCL value.

B

. 3 N on- Transient N on- C o mmunit y Wat e r Sy st ems

B.3.1 Data Inputs 

##    EP SA 

## F S



## EP ST 

## F
T 

##   •

    S



## EP ST 

## F
T 

##  

• EP SA 

## F     G



## EP GT 

## F
T 

##          EP GA 

## F

• 

EP GA 

## F G



## EP GT 

## F
T 

## •  
   =

Appendix B, Assumptions and Methodology for B-13 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### Most of the data described above under the CW S risk model is also used in the NTNC risk

model. This includes water consumption, body weig ht, and lifetime risk estimates. Also, the

g r ound water arsenic concentrations at each MCL used in the CW S risk model are used in the

NTNC risk model.

B. 3. 1. 1 NT NC Serv i ce Cat e gori es, Popul at i on and Exposure T i me



### The main differences between the CW S and NTNC risk models are how population is distributed

among the different ty pes of establishments that make up the NTNC categ ory of sy stems, and the

ex tent to which the worker and customer populations within a service categ ory are ex posed to
arsenic (both in terms of leng th of ex posure and drinking water consumed).

I n addition to the CW S data already discussed, Ex hibits B

- 4 and B

- 5 provide all of the data
inputs necessary to model the bladder cancer risk associated with NTNC sy stems. First, note that

in Ex hibit B

- 4, the NTNC universe has been divided into 35 service categ ories. This was
accomplished using the sy stem descriptions in S D W I S (EP A , 1999b). For each service categ o ry

, the total number of NTNCs and the population served by these NTNCs is taken from SDW I S.
The population served by each NTNC often varies daily ; the S D W I S population numbers are
interpreted to mean the peak population served (both workers and customers).

The nex t data field in Ex hibit B

- 4 is the number of customer cy cles per y ear, or the number of
times each y ear the customer base turns over. F o r ex ample, if this parameter equals one, then the

sam e cust om er’s are served each day

. I f t h e val u e i s seven, t h en seven set s of cust om ers use t h e

f

a c ility

. The ne x t f i e l d is the numbe r of wor k e r s pe r pe r s on pe r da y

. F o r e x a m ple

, if the va lue is
0.1, as in the case of summer camps, then 10 percent of the peak population served (from

SDW I S) is assumed to be workers. B o th the number of customer cy cles per y ear assumptions
and workers per person per day data assumptions were made after investig ating numerous data
sources, including trade-journals and trade association information.

The nex t set of data fields in Ex hibit B

- 4 are assumptions about the characteristics of the workers

i n each servi ce t y pe. The percent of workers’ dai l y consum pt i on i s t h e percent a g e of dri nki ng water consumed on a work day that is consumed at work. This value is assumed to be either 50
percent or 100 percent, depending on the service categ ory

. The number of day s a person works is
assumed to be 250 for all service categ ories. The number of y ears a person works at the NTNC
establishment is assumed to be either 40 or 10, depending on the service categ ory

.

I n formation reg a rding customer behavior is provided in the nex t set of data fields in Ex hibit B

- 4.
The percent of customers’ daily consumption is the percentag e of total drinking water consumed
on a day that the customer visits the NTNC, that is consumed at the NTNC. This value is
assumed to be either 25 percent, 50 percent or 100 percent, depending on the service categ ory

. The num ber of day s a cust om er vi si t s t h e NTNC i s provi ded for each servi ce cat eg ory

. For

ex ample, the value for nursing homes of 365 indicates that nursing home customers are served by
the nursing home y ear round, while the value for churches of 52 indicates that churches are
assumed to serve their customers once per week. The number of y ears a person is assumed to

vi si t s each servi ce cat eg ory i s al so provi ded.

Appendix B, Assumptions and Methodology for B-14 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### Finally , the total ex posed worker and customer populations for each service categ ory are provided in Ex hibit B

- 4. These numbers are calculated as follows:



### TC

c 

### = P

c 

### C C

c 

### ) * (
− W P

c 

### (* 1 )

TW = P * W P

c c c



### where:

TC = total number of customers

TW = total number of workers

P = SDW I S population

W P = workers per person per day
CC = number of customer cy cles per y ear

c = NTNC servi ce cat eg ory

Ex hibit B

- 5 pr ovide s the f i na l se t of da ta r e quir e d to e s tima te bla dde r c a n c e r r i sk f r o m NTNCs.

The pe r c e n t of wor k e r lif e time e x posur e is the pe r c e n t of lif e time wa te r c onsumption whic h is

c onsume d a t the NTNC by a

wor k e r

. The pe r c e n t of c u stome r lif e time e x posur e is the pe r c e n t of

lif e time wa te r c onsumption c onsume d a t the NTNC by a

c u stome r

. The s e numbe r s a r e
cal cul a t e d as fol l o ws:



### P W DC * DW * YW PWLE = c c c

c 

### 365 * 70



### P C DC * DC * YC PC LE = c c c

c 

### 36 5 * 7 0

where;

PWL E = pe r c e n t of wor k e r lif e time e x posur e

PCL E = pe r c e n t of c u stome r lif e time e x posur e

PW DC = percentag e of workers daily consumption
PCDC = percentag e of customers daily consumption

DW = worker day s per y ear DC = customer day s per y ear

YW = worker y ears

YC = cust om er y ears

Returning to Ex hibit B

- 5, the worker ag e bracket is the ag e rang e (corresponding to the ag e

r a ng e s use d in the CWS r i sk a n a l y s is) tha t a NTNC wor k e r is a ssume d to f a ll in. F o r a ll se r v ic e

cat eg ori e s, t h e worker ag e bracket i s assum e d t o be 20-64 y ears of ag e. The cust om er ag e bracket is the ag e rang e (corresponding to the ag e rang es used in the CW S risk analy s is) that a

NTNC cust om er i s assum e d t o be i n. For m o st servi ce cat eg ori e s, t h e cust om er ag e bracket i s

Appendix B, Assumptions and Methodology for B-15 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### assum e d t o be 0-70 y ears of ag e (al l ag es). However, cert a i n servi ce cat eg ori e s onl y serve cert a i n

ag e g r oups (e.g . nursing homes and schools), therefore more specific ag e rang es are assumed.

Appendix B, Assumptions and Methodology for B-16 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and BenefitsExhibit B-4NTNC Population and Exposure Time DataNumberofSystemsTotalSDWISPopulationNumberofCustomerCycles/YearWorkerPerPersonPerDayPercentofWorker'sDailyConsumptionWorkerDays PerYearWorkerYearsPercentofCustomer'sDailyConsumptionCustomerDays PerYearCustomerYearsTotalWorkerPopulationTotalCustomerPopulationWaterWholesalers26666,0181.000n/an/an/a25.0%270.0070.00066,018MobileHomeParks10419,2401.330.04650.0%25040100.0%270.0035.0088524,412NursingHomes13013,9101.000.2350.0%25040100.0%365.0010.003,19910,711Churches23011,5001.000.0150.0%2504050.0%52.0070.0011511,385GolfandCountryClubs11611,7164.500.1150.0%2504050.0%52.0070.001,28946,923Retailers (Food related)14245,7242.000.0750.0%2504025.0%185.0070.003,20185,047Retailers (Non-food related)695120,9304.500.0950.0%2504025.0%52.0070.0010,884495,208Restaurants418154,6602.000.0750.0%2504025.0%185.0070.0010,826287,668Hotels/Motels35146,68386.000.2750.0%25040100.0%3.4040.0012,6042,930,759Prisons/Jails67121,9401.330.150.0%25040100.0%270.003.0012,194145,962ServiceStations5312,1907.000.0650.0%2504025.0%52.0054.0073180,210AgriculturalProducts/Services36827,9687.000.12550.0%2504025.0%52.0050.003,496171,304DaycareCenters80961,4841.000.14550.0%2501050.0%250.005.008,91552,569Schools8,4143,086,0121.000.07350.0%2004050.0%200.0012.00225,2792,860,733State Parks83106,89526.000.01650.0%2504050.0%14.0070.001,7102,734,802MedicalFacilities367163,63116.400.02250.0%25040100.0%6.7010.303,6002,624,510Campgrounds/RVParks12319,68022.500.04150.0%18040100.0%5.0050.00807424,645FederalParks2078026.000.01650.0%2504050.0%14.0070.001219,956HighwayRestAreas156,10550.700.0150.0%2504050.0%7.2070.0061306,428Misc.RecreationServices25922,53326.000.01650.0%25040100.0%14.0070.00361576,484ForestService1074,49426.000.016100.0%25040100.0%14.0050.0072114,974InterstateCarriers28735,30193.000.30450.0%2504050.0%2.0070.0010,7322,284,963AmusementParks15976,46290.000.1850.0%2501050.0%1.0070.0013,7635,642,896SummerCamps466,7168.500.1100.0%18010100.0%7.0010.0067251,377Airports101326,86036.500.30850.0%2504025.0%10.0070.00100,6738,255,830MilitaryBases9567,525n/a150.0%25040n/an/an/a67,5250Non-WaterUtilities49784,490n/a150.0%25040n/an/an/a84,4900OfficeParks950181,600n/a150.0%25040n/an/an/a181,6000Manufacturing:Food768285,696n/a150.0%25040n/an/an/a285,6960Manufacturing:Non-Food3,356588,792n/a150.0%25040n/an/an/a588,7920Landfills783,432n/a1100.0%25040n/an/an/a3,4320FireDepartments414,018n/a1100.0%25040n/an/an/a4,0180Construction995,247n/a1100.0%25040n/an/an/a5,2470Mining11913,447n/a1100.0%25040n/an/an/a13,4470MigrantLaborCamps332,079n/a1100.0%25040n/an/an/a2,0790Subtotal=TOTAL=1,662,40730,305,77431,968,181

### Exhibit B-5 NTNC Percent of Lifetime Exposure and A g e at Exposure

Per c e n t

of

W o r k er

Li f e t i m e

Ex p os ur e Per c e n t of

C u st om er

Li f e t i m e

Ex p os ur e Wo r k e r Ag e

B r ac ket C u st om er Ag e

B r ac ket

W a t e r W h ol es al e r s 0

. 0 0 % 18

. 4 9% n/ a a l l

M o b i l e H o m e P a r k s 1 9. 57 % 3 6. 99 % 2 0 t o 64 a l l

N u r s i n g H o m e s 1 9. 57 % 1 4. 29 % 2 0 t o 64 6 5 +

C h ur c h e s 19

. 5 7% 7. 12 % 2 0 t o 6 4 al l

G o l f a n d Co un t r y C l ub s 1 9. 57 % 7

. 1 2% 2 0 t o 64 a l l

R

e t a i l e r s ( F o o d r e l a t e d) 19

. 5 7% 12

. 6 7% 20 t o 6 4 al l

R

e t a i l er s ( N on

- f oo d r e l a t e d) 1 9

. 5 7 % 3

. 5 6 % 2 0 t o 64 a l l

R

e s t a u r a n t s 1 9. 57 % 1 2. 67 % 2 0 t o 64 a l l

H o t e l s / M o t e l s 1 9. 57 % 0

. 5 3% 2 0 t o 64 a l l

Pr i s o n s / J a i l s 1 9. 57 % 3

. 1 7% 2 0 t o 64 2 0 t o 64

S e r v i c e S t at i o n s 19

. 5 7% 2. 75 % 2 0 t o 6 4 16 t o 7 0
Agr i c u l t ur al Pr o d u c t s / S e r v i c e s 1 9. 57 % 2

. 5 4% 2 0 t o 64 a l l

Day c a r e C e n t er s 4

. 8 9% 2

. 4 5 % 2 0 t o 64 < 5

S c hoo l s 15

. 6 6% 4. 70 % 2 0 t o 6 4 6 t o 18

St a t e Par k s 1 9. 57 % 1

. 9 2% 2 0 t o 64 a l l

M e di c a l Fa c i l i t i es 19

. 5 7% 0. 27 % 2 0 t o 6 4 al l

Cam p gr o u n d s / R

V Par k s 1 4. 09 % 0

. 9 8% 2 0 t o 64 a l l

F e d e r a l Par k s 1 9. 57 % 1

. 9 2% 2 0 t o 64 a l l

H i g h w a y R e st Ar e a s 1 9. 57 % 0

. 9 9% 2 0 t o 64 a l l

M i sc

. R e c r eat i o n S e r v i c e s 19

. 5 7% 3. 84 % 2 0 t o 6 4 al l

F o r e s t Se r v i c e 3 9. 14 % 2

. 7 4% 2 0 t o 64 a l l

I n t e r s t a t e C a r r i e r s 19

. 5 7% 0. 27 % 2 0 t o 6 4 al l

Am us em e n t Par k s 4

. 8 9% 0

. 1 4 % 2 0 t o 64 a l l

Sum m e r Ca m p s 7

. 0 5% 0

. 2 7 % 2 0 t o 64 1 1 t o 19

A i r por t s 19

. 5 7% 0. 68 % 2 0 t o 6 4 al l

M i l i t a r y Bas e s 1 9. 57 % 0

. 0 0% 2 0 t o 64 n / a

N o n

- W a t e r U t i l i t i e s 1 9. 57 % 0

. 0 0% 2 0 t o 64 n / a

O

f f i c e Pa r k s 1 9. 57 % 0

. 0 0% 2 0 t o 64 n / a

M a nuf ac t u r i n g : Fo od 19

. 5 7% 0. 00 % 2 0 t o 6 4 n/ a

M a nuf ac t u r i n g : N o n- Foo d 19

. 5 7% 0. 00 % 2 0 t o 6 4 n/ a

La nd f i l l s 39

. 1 4% 0. 00 % 2 0 t o 6 4 n/ a

F i r e De pa r t m e n t s 3 9. 14 % 0

. 0 0% 2 0 t o 64 n / a

C o nst r uc t i on 39

. 1 4% 0. 00 % 2 0 t o 6 4 n/ a

M i ni ng 39

. 1 4% 0. 00 % 2 0 t o 6 4 n/ a

M i gr an t La bo r C a m p s 3 9

. 1 4 % 0

. 0 0 % al l n / a

Appendix B, Assumptions and Methodology for B-18 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### B.3

. 2 The NTNC Ris k Mode l

J u st like the CWS r i sk a n a l y s is, the NTNC r i sk a n a l y s is is a Monte

- Ca r l o ba se d simula tion

model. This section will ex plain each step is the simulation. The Monte-Carlo simulation is

conducted at each MCL option (50, 20, 10, 5 and 3 F g / L )

. I n addition, for each MCL option, the

simulation is carried out for both the “L ower B ound” and “Upper B ound” scenarios just like in

the CWS c a s e

. The r e f or e

, the simula tion mode l is c a r r i e d out te n time s. Ea c h of the s e te n “ r uns”
of the model is independent of the other, and can be discussed in isolation. Therefore, this
section will include a g e neraliz ed discussion of the model. The inputs that are used will depend

on the MCL option a nd sc e n a r io be ing e v a l ua te d a t the time . I t is impor ta nt not to c onf use a “run” of the model” as just described, and a model iteration. Each run of the model consists of

10,000 iterations. W ithin a sing le iteration, the model pulls a value for each variable from its
input distribution (e.g . body weig ht) and calculates a value for each output variable (e.g . lifetime
risk). This is done for 10,000 times for each model run. The results of the model run is the
distribution of the 10,000 values for each output variable.

The fi rst st ep of each i t e rat i on i s t o cal cul a t e t h e rel a t i v e ex posure fact or for each sex and ag e
categ ory

. This is done ex actly as it was done in the CW S risk analy s is. As shown in the
following equations, the relative ex posure factor is a function of daily water consumption and
body weig ht.

REF

ma i 

### =    70   

*   C

ma i 

###  

2  W

ma i 

### 



### RE F fa i 

### =    70   

*   C
fa i 

###  

2  W fa i 

### 

where;

R E F = rel a t i v e ex posure fact or C = daily water consumption (L )

W = body weig ht (kg )

i = model iteration number

a = ag e cat eg ory

m = ma le

f = fem a l e

Nex t , the lifetime risk of bladder cancer (1/100,000 people) is calculated for workers and

cust om ers of each sex for each servi ce cat eg ory

. The nex t four equat i ons, t h erefore are:

Appendix B, Assumptions and Methodology for B-19 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

# ∑   ( RE F fa i 

### * Z

a c 

### )

WLR fc i 

### = P W L E

c i 

### * A S

g i 

### * ( R F i 

### / 50 ) * a 

### * 100     

# ∑     Z

ac

a



# ∑   ( REF mai 

### * Z

a c 

### )         WLR P W L E

c i 

### * A S

g i 

### * ( R F i 

### / 50 ) * a 

### * 100 = 

# ∑ mci 

### Z

ac

a



# ∑   ( RE F

ma i 

### * Z

a c 

### )



# ∑     CL R P CL E

c i 

### * A S

g i 

### * ( R F i 

### / 50 ) * a 

### * 100 =
mc i 

### Z

ac 

###    

a



### ( REF fai 

### * Z

a c 

### ) 

# ∑       CLR P CLE

c i 

### * A S

g i 

### * ( R F i 

### / 50 ) * a 

### * 100 = 

# ∑ fci 

### Z

ac 

###    

a 

### where;

W L R = worker lifetime risk (per 100,000 people)

CL R = customer lifetime risk (per 100,000 people)

AS = arseni c concent r at i on ( F g/ L )

RF = risk of bladder cancer at 50 F g / L

, 2 liters consumption per day

, and 70 kg body weig ht

Z = y ears spent i n ag e cat eg ory

g = g r ound water

The sex of t h e worker and cust om er i s t h en chosen for t h e i t e rat i on t o det e rm i n e t h e worker and

cust om er ri sk for each servi ce cat eg ory :



### ≤ WL R i f R N M P    = mci 1 

### WL R ci 

### WL R fci 

### o t h e r wi s e

≤ CLR i f R N M P    = mci 1 

### CLR ci 

### CLR fci 

### o therwi se

where;

RN 1 

### = random number between 0 and 1
MP = percentag e of the population that is male

Appendix B, Assumptions and Methodology for B-20 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### F i nally , the lifetime risk for the model iteration is determined by choosing among the 70
combinations of worker and customer risk over of the 35 service categ ories. This is accomplished
using a population weig hted probability distribution. F i rst, the total worker and customer
populations served are computed.



### TC = 

# ∑ TC

c

c



### TW = 

# ∑ TW

c

c



### Ne x t , the pr oba bility tha t the lif e time r i sk f o r

the mode l ite r a tion will be e qua l to the wor k e r

lif e time r i sk a ssoc i a t e d with a se r v ic e c a t e g or y is c a l c u la te d:



### TW WP R = c

c 

### ( TW + TC )

where;

W P R = probability of choosing lifetime risk estimate for any iteration to be equal to the lifetime

r i sk e s tima te of a

wor k e r in a g i ve n se r v ic e c a t e g or y

L i ke wise , the pr oba bility tha t the lif e time r i sk f o r

the mode l ite r a tion will be e qua l to the

c u stome r lif e time r i sk a ssoc i a t e d with a se r v ic e c a t e g or y is c a l c u la te d:



### TC CPR = c

c 

### ( TW + TC )

where;

CPR = probability of choosing lifetime risk estimate for any iteration to be equal to the lifetime

r i sk e s tima te of a

c u stome r in a g i ve n se r v ic e c a t e g or y

Given these probabilities, the lifetime risk estimate for each model iteration is chosen as follows:



###  W L R ci 

### w i t h Pr oba bi lity W P R

c 

### 

LR i 

### =  M   C L R ci 

### w i t h Pr oba bi lity C P R

c



### where;

L R = L i fetime risk (1/100,000)

Appendix B, Assumptions and Methodology for B-21 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

### I n order to calculate the ex pected number of cancer cases associated with the model run, the
mean lifetime risk is multiplied by the ex posed population as follows:



### 

CA      = N 

# ∑

i 1 = 

### LR i 

### 

* ( TC + TW )

N 10 0 0 0 0

,     

where;

C A = ex pect ed num ber of bl adder cancer cases

N = number of iterations

Appendix B, Assumptions and Methodology for B-22 Arsenic in Drinking Water Rule EA

Es tim ating Cancer Ris k s Avoided and Benefits

## A ppendi x C. Cost M odel M e thodol ogy

C.1 Introduction

EPA used the reg u latory cost model, SafeW a terXL

, in estimating the annual national costs of

c o mplia nc e f o r

the Ar se nic in Dr inking Wa te r Rule

. Sa f e Wa te r X L is a Monte

- Ca r l o simula tion
model developed in Microsoft Ex cel using the Cry s tal B a ll add-in. 1 

### The model is prog rammed in

Visual B a sic for Applications, the procedures and functions of which command for ex ample, the

user i n t e rface and m u ch of t h e busi n ess l o g i c requi red. These procedures and funct i ons cal l on data and equations stored in Microsoft Ex cel spreadsheets, such as data on specific sy stem characteristics (e.g ., the number of people served, the ty pe and source of the water sy stem, the

deci si on t r ee).

SafeW a terXL determines reg u latory compliance costs for individual sy stems and subsequently
calculates a national averag e cost based on the mean value of these data points. SafeW a terXL describes sy stem-level costs in terms of a distribution, from which mean costs and percentile

cost s are avai l a bl e. Mean cost s refl ect t h e cost s of t r eat m e nt t r ai ns sel ect ed. Treat m e nt t r ai ns consist of two main cost components, capital (the cost of constructing or installing equipment)
and operation and maintenance (O& M , annual cost of operating equipment and performing
routine maintenance) costs for: pre-treatment pre-ox idation technolog y (if necessary ), treatment
technolog y

, and waste disposal technolog y

. This modeling approach presents information critical
to the assessment of sy stem-level impacts and technolog y affordability by providing the averag e

com p l i a nce cost s for each wat e r sy st em t ype and si z e cat eg ory

, and t h e rang e of cost s wi t h i n each

sy stem siz e and ty pe categ ory

.

I n understanding how SafeW a terXL calculates annual national cost of compliance, it is important
to disting u ish between an “iteration” and a “run” of the model. A sing le iteration of the model
represents a sing le sy stem. This allows for variability in the water sy stem config uration, current
treatment in place, and source water quality to be captured in the compliance cost estimates. A
model “run” uses data from the ag g r eg ate number of iterations to calculate summary cost information for different sy stem siz e categ ories. F o r any individual “run,” only a sing le source

water ty pe may be evaluated, and the results are stratified by six t een g r oups: 8 siz e categ ories and
2 ownership ty pes (public/private).

C.2 Data Inputs and Procedure (Single Model Iteration)

The fundamental steps required to conduct an iteration of SafeW a terXL are summariz e d below:

1. A sy stem is selected from data files. A sy stem is defined by the population it serves.

2. Each sy stem is assig n ed a random concentration from an occurrence distribution.

1 For Window s 95/98/NT: Excel 2000, reg i stered tradem ark of Microsof t Corporation; Cry s tal Ball
Version 4.0, reg i stered tradem ark of Decisioneering

, Inc.

Appendix C, Cost Model Methodology C-1 A rsenic in Drinking Water Rule EA

### 3. The selected arsenic concentration for the sy stem is distributed across the number of sites
(entry points) of possible contamination for that sy stem based on the relative intra-sy stem standard deviation (RSD).

4. The concent r at i on at each si t e i s com p ared t o t h e revi sed MC L st andard t o det e rm i n e i f

the site is in violation of the revised standard.

5. I f the site is in violation of the revised MCL

, the percentag e removal of arsenic required

i n order t o reach t h e t r eat m e nt t a rg et i s cal cul a t e d.

6. B a sed on the percentag e removal required to meet the treatment targ et and on the decision

tr e e f o r

the size a nd ty pe of the sy ste m , a tr e a tme nt tr a i n is the n a ssig n e d to the site

. 7. Using the removal efficiency of the treatment train chosen, the percentag e of flow that

must be tr e a t e d in or de r f

o r

the e n tr y point to me e t the tr e a tme nt ta r g e t , is c a l c u la te d.

8. The percentag e of flow that needs to treated is applied to the desig n flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:

tr e a tme nt c a p ita l, wa ste disposa l c a p ita l, a nd a n y pr e

- tr e a tme nt c a p ita l c o sts)

. 9. Simila r l y

, the pe r c e n ta g e of f

l ow tha t ne e d s to tr e a t e d is a l so a pplie d to the a v e r a g e f l ow, which is then used to derive the operation and maintenance costs of the components of
the treatment train (the sum of: treatment O& M, waste disposal O& M, and anypretreatment O& M costs).

10. The sy stem’s total annual treatment costs are calculated for the selected treatment train at
various discount rates, by summing the treatment costs (annualized capital plus annual

O& M cost components) across all treating sites.

11. This annual sy stem cost is used to derive the cost per thousand g a llons (cost/kg a l)

del i v ered by t h e wat e r sy st em

. 12. Annual household costs are then calculated based on the sy stem’s unit cost of delivery
(cost per thousand g a llons) and the averag e annual household consumption per y e ar.

13. I f household costs are determined to ex ceed an affordability threshold of $500, a less

ex pensive treatment technolog y (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POU devices).

14. Ot herwi s e, t h e resul t s are forecast e d for each i t e rat i on and anot her sy st em i s sel ect ed for

the ne x t ite r a tion.

This procedure is conducted for all of the siz e categ ories and national costs are then calculated.
Each step listed above is now described in detail.

• A sy ste m is se le c t e d f r o m da ta f

ile s.

The basic unit of analy s is within the cost model is an individual CW S. The SafeW a terXL model
estimates reg u latory cost based on a universe of CW Ss using a December 1997 freez e of the Safe

Dr inking Wa te r I n f o r m a tion Sy ste m ( S DWI S ) da ta se t, whic h a llows c o sts to c o mmunity wa te r

sy ste m s to be de limite d by va r i ous sy ste m c h a r a c t e r istic s: sour c e

, owne r s hip, a nd size

. SDWI S
contains data on all public water sy stems as reported by States and EPA Reg i ons. This
information is used to determine each sy stem’s primary raw water source (g round or surface
water), its ownership ty pe (public or private), and the population served by the sy stem (service

siz e categ ory )

. Note that in S D W I S

, sy stems under any influence of surface water are classified

as surface wat e r sy st em s.

Appendix C, Cost Model Methodology C-2 A rsenic in Drinking Water Rule EA

### I n cluded in this g r oup are surface water sy stems that receive a portion of their flow from g r ound

water sources. I n SafeW a terXL

, these “mix ed sy stems” were reclassified as g r ound water

sy stems if they were determined to rely on g r ound water for more than 50 percent of their water
supply

. B a sed on data from the Community W a ter Sy stem Survey (CW SS) 2 

### , sy stems were

sy stematically reassig n ed in order to maintain the same averag e number of people served for the
subset of sy stems. Approx imately nine and twelve percent of non-purchased and purchased

surface wat e r sy st em s were recl assi fi ed as a resul t

.

The universe of sy stems modeled in SafeW a terXL also ex cludes the larg est sy stems, those
serving more than 900,000 people. These very larg e sy stems, althoug h few in number, are
sig n if ic a n t c ontr i butor s to the na tiona l c o st of c o mplia nc e e s tima te

. The r e f or e

, f o r

the Ar se nic in
Drinking W a ter Rule, EPA did an independent analy s is on the 25 very larg e sy stems (both

g r ound and surface water source sy stems) to determine which would be affected at various MCL
options. I n addition, among the smallest sy stems (serving <100 people), approx imately 150

g r ound water sy stem were found to serve fewer than 25 people, but for modeling purposes were all assumed to serve 25 people. Due to the sheer number of sy stems in this siz e categ ory (>14,000 sy stems), the effect of this modification was found to be insig n ificant.

I n tota l, the r e sulting numbe r of sy ste m s a r e distr i bute d be twe e n two da ta f

ile s whic h the mode l
calls on for sy stem information. The criterion for these two files is source water: g r ound or

surface. Then, wi t h i n each fi l e , C W S s 3 

### are first g r ouped by siz e categ ory

, resulting in eig h t different worksheets of data corresponding to each delimited categ ory (25-100; 101-500; 501­
1,000; 1,100-3,300; 3,301-10,000; 10,001-50,000; 50,001-100,000; 100,001-90,000). The
resulting stratification of the 1997 SDW I S freez e used in SafeW a terXL is described in Ex hibits
C-1 and C-2 below for g r ound and surface water sy stems, respectively

.

2 U.S. EPA. 1999. Geometries and Characteristics of Public Water Systems

. P r epared f o r O f f i ce of

Ground Water and Drink i ng Water by Science Applications International Corporation. EPA Contract No. 69- C6­

0059.

3 N o te that public- purchas ed s y s t em s are analy zed as publicly

- o wned s y s t em s and s i m ilarly

, priv atepurchas ed s y s t em s are analy zed as priv ately

- owned s y s t em

.

Appendix C, Cost Model Methodology C-3 A rsenic in Drinking Water Rule EA

### Exhi bi t C- 1.

St rat i f i cat i on of Communi t y G r ound Wat e r Sy st ems

Sy stem Si ze
C a te gor y Public ly -Ow n e d Pr iva t e l y

- Ow ne d

A ll GW Sy stems N on-

Pu rch ased Pu rch ased No n

Pu rch ased Pu rch ased

25-100 1, 217 125 12, 893 197 14, 432

101-501 4, 141 480 10, 242 385 15, 248

501-1, 000 2, 574 300 1, 798 115 4, 787

1, 001-3, 300 3, 847 347 1, 599 100 5, 893

3, 301-10, 000 2, 027 229 493 35 2, 784

10, 001-50, 000 1, 078 207 259 17 1, 561

50, 001-100, 000 126 26 27 1 180

100, 001-900, 000 74 15 18

-- 107

To t a l 15, 084 1, 729 27, 329 850 44, 992



### Exhi bi t C- 2.

St rat i f i cat i on of Communi t y Surf ace Wat e r Sy st ems

Sy stem Si ze
C a te gor y Public ly -Ow n e d Pr iva t e l y

- Ow ne d

A ll SW Sy stems N on-

Pu rch ased Pu rch ased No n

Pu rch ased Pu rch ased

25-100 150 209 404 293 1, 056

101-501 348 634 396 490 1, 868

501-1, 000 331 476 131 212 1, 150

1, 001-3, 300 873 930 225 280 2, 308

3, 301-10, 000 771 567 102 104 1, 544

10, 001-50, 000 724 387 114 35 1, 260

50, 001-100, 000 133 61 31 3 228

100, 001-900, 000 136 33 33 3 205

To t a l 3, 466 3, 297 1, 436 1, 420 9, 619



### S y st em s i n each worksheet are furt her defi ned by t h ei r ownershi p t y pe and an ex act num ber of
peopl e served. A separat e deci si on t r ee al so ex i s t s for each si z e cat eg ory

, such t h at t h ere are
six t e e n in tota l a v a ila ble f o r

a n a l y s is in Sa f e Wa te r X L

, a s pr e s e n te d in Appe ndix A.

Appendix C, Cost Model Methodology C-4 A rsenic in Drinking Water Rule EA

### For ex am pl e i n t h i s st ep, a sy st em i s sel ect ed from one of t h e dat a fi l e s. R ecal l t h at when a

mode l “ r un” is pe r f o r m e d, only one sour c e ty pe ma y be a n a l y z e d a t a time

. The se le c tion ma de
by the use r tr ig g e r s whic h da ta f

ile is utilize d. Onc e de sig n a t e d, a ssuming a ll size c a t e g or ie s a r e being analy z ed, the model beg i ns with the smallest siz e categ ory (<100 people served).

• E ach sy stem is assig n ed a random concentration from an occurrence distribution.

The sy st em sel ect ed i n S t ep 1 has vari ous associ at ed sy st em charact e ri st i c s. Each sy st em i s al so
associated with an arsenic occurrence distribution based on the source water. However, these
distributions define the universe of sy stems with the same ty pe of source water using a mean and
log standard deviation. To model a sing le sy stem chosen from the data files, a random sy stem

occurrence is selected from this distribution.

I n t h i s m a nner, cont am i n ant occurrence i n form at i on det e rm i n es t h e averag e sy st em concent r at i o n

g i ve n va r i ous sy ste m size a nd sour c e wa te r c o mbina tions. Ex hibit 6- 6 shows the e s tima te d
finished water arsenic occurrence distribution for g r ound and surface water sy stems. For use in

t h e S a feW a t e rXL m odel

, EP A perform ed a reg r essi on anal y s i s t h at wei g ht ed act u al occurrence data by National Arsenic Occurrence Survey reg i on. On the basis of this, EPA replicated the
estimated finished water distribution of g r ound and surface water sy stems throug h a log

- normal
fit using two sets of distribution parameters. The analy s is resulted in the following distribution
of sy st em s ex ceedi n g vari ous arseni c concent r at i on l e vel s :

Exhi bi t C- 3

A r seni c O ccurrence Di st ri but i on, Log- Normal Regressi on Resul t s

3 μ g / L 5 μ g / L 10 μ g / L 20 μ g / L

Gr ound w a te r 19. 7% 12. 0% 5. 3% 2. 0%

Su rface w a ter 5. 6% 3. 0% 1. 12% 0. 37%

*Percent ages represent sy st em s ex ceeding t he arsenic concent rat i on



### F o r g r ound water sy stems, the percentag e s display e d in Ex hibit C-3 above were based on a
log normal distribution with a mean of -0.2507 and a log standard deviation of 1.5828. Among
surface water sy stems, the percentag e s were based on a log normal distribution of -1.6781 and a
log standard deviation of 1.7425.

• T he selected arsenic concentration for the sy stem is distributed across the number of sites
(entry points) of possible contamination for that sy stem based on the relative intra-sy stem standard deviation (RSD).

Once the sy stem arsenic concentration is determined, the number of entry points, or sites of the

sy stem, are determined. The number of sites a sy stem has is another important sy stem

charact eri s t i c t o consi d er i n t h e anal y s i s because ent r y poi nt s are used as a prox y for t h e pot ent i a l

or act ual poi nt s of t r eat m e nt

. S i nce not al l si t e s i n t h e sy st em are equal l y l i k el y t o ex ceed t h e

MCL standard, the likelihood of contamination is determined on a site-by

- site basis. That is,
each sy st em m a y have m o re t h an a si ng l e si t e t r eat i n g i ndependent l y

.

Appendix C, Cost Model Methodology C-5 A rsenic in Drinking Water Rule EA

### The averag e number of sites per sy stem is determined based on the distribution of sy stem intake

site s f o r

the size c a t e g or y a s e s tima te d f r o m the CWSS. The r a ng e of numbe r of site s pe r sy ste m
is described in Ex hibit C-4 for g r ound water sy stems, where a max imum of 37 possible sites was

mode le d. L i ne a r e x tr a pola tion wa s use d to e s tima te va lue s f o r

the numbe r of site s in c a s e s whe r e

survey data was not available.

Exhi bi t C- 4

Di st ri but i on of Ent r y Poi n t s by Si ze Cat e gory A m ong G r ound Wat e r Sy st ems

Sy stem Si ze
C a te gor y M ean 5 th

Percen ti l e 50 th

Percen ti l e (M edian) 75 th

Percen ti l e 95 th

Percen ti l e M axi mu m

<

- 1 0 0 1 1 1 1 2 4

101-500 1 1 1 1 3 1 0

501-1, 000 2 1 1 2 3 4

1, 001-5, 000 2 1 1 2 5 6

5, 001-10, 000 2 1 2 3 5 1 5

10, 001-50, 000 4 1 3 5 12 19

50, 001-100, 000 6 1 4 8 22 37

100, 001-900, 000 9 1 5 1 5 2 8 3 0

Source: U. S. EPA. 1999. G eom et ries and Charact e rist ics of Public W a t

e r Syst em s

. Prepared for O ffice

of G r ound W a t e r and Drink i ng W a t e r by Science Applicat ions I n t e rnat ional Corporat ion. EPA Cont ract

No. 68-C6-0059.



### Among surface water sy stems, fewer sites per sy stem ex ist. About 95 percent of the sy stems that
serve fewer than 50,000 people have only a sing le entry point. Of the remaining surface water

sy stems that serve g r eater than 50,0001 people, the majority of the sy stems had fewer than three

entry points, althoug h some in the 50,001-100,000 and 100,001-900,000 service siz e categ ories
were observed to have as many as six and four sites per sy stem, respectively

.

The Sa f e Wa te r X L mode l c a l c u la te s pote n tia l c o sts of c o mplia nc e a t the e n tr y point le ve l,
allowing for a max imum of 37, but modeling only the estimated number attributable to each

sy stem, based on the distribution described in Ex hibit C-4. Once the number of sites within the

sy stem is determined from the distribution, the concentration of the contaminant at the site is
calculated by apply i ng the assumed relative intra-sy stem standard deviation (RSD) around the

mean sy stem concentration. The averag e concentration of arsenic for that sy stem (from S t ep 2)

is a ssig n e d be twe e n a ll the sy ste m ’ s site s using a log

- nor ma l distr i bution with the sy ste m concentration as the mean, and the intra-sy stem deviation as the standard deviation, which is
derived by multiply ing the RSD by the sy stem concentration. The RSD is an input ultimately
used to distribute the sy stem occurrence between the various entry points of the site. The RSD is
a model input provided by the user that feeds into the calculation of the intra-sy stem deviation
based on the relationship ex pressed in Equation 1.

Appendix C, Cost Model Methodology C-6 A rsenic in Drinking Water Rule EA

### In tra

- Sy stem Stand ard Devi at ion RS D = (Eq. 1) 

### Sy stem Concen tra tio n

This distribution used to assig n site concentration is bound by z e ro at the lower limit and by the

max imum site concentration (Eq. 2) at the upper limit. Note however, that the sum of the mean

a r se nic c onc e n tr a tion of a ll site s within a sy ste m must still e qua l the me a n a r se nic c onc e n tr a tion
of the sy stem.



### M a

x

Si te Con c

. = 

# ( Sy sC o n c × # of sit e s (Eq. 2) 

# ) ( )

where: S y sC onc = a rseni c concent r at i on for sy st em

The max imum is set using the assumption that despite the number of entry points, if only one
entry is contaminated, its individual concentration cannot ex ceed a limit such that when averag ed

across t h e num ber of possi bl e si t e s, t h e overal l concent r at i on woul d ex ceed t h e ori g i n al

c onc e n tr a tion de te r mine d f o r

tha t sy ste m

.

For any g i ven sy st em t h at has m o re t h an a si ng l e si t e , t h e averag e sy st em concent r at i on of arseni c for that sy stem is assig n ed between all the sy stem’s sites using this method. Otherwise, if the

sy stem has only a sing le site, then the site concentration must equal the sy stem concentration.

• T he concent r at i on at each si t e i s com p ared t o t h e revi sed MC L st andard t o det e rm i n e i f

the site is in violation of the standard.

Althoug h the sy stem concentration could itself fall below the MCL

, once the sy stem concentration has been distributed between the possible number of entry points, one site may
sig n ificantly ex ceed the MCL while the other falls below the MCL such that their averag e still
equals the sy stem concentration. F o r ex ample, in a sy stem with three sites, there may have two

sites whose individual site concentrations are well below the MCL and one site whose

concent r at i on ex ceeds t h e MC L

. I n t h i s ex am pl e, onl y cost s t o t h e t h i r d si t e are cal cul a t e d.
However, if a sy stem has only one site, then that sing le site is assig n ed the entire sy stem

concentration of arsenic.

For this reason, the concentration of each site of the sy stem is individually compared to the MCL

. No cost s are i n curred for t hose si t e s whose concent r at i ons fal l bel o w t h e speci fi ed MC L

, as no treatment is required. However, if the site is determined to be in violation of the MCL

, then

tr e a tme nt c o sts f o r

r e g u la tor y c o mplia nc e will be c a l c u la te d a nd the mode l must r e c o r d the da ta and output information. To do so with the best approx imation of the true costs of compliance,
only the portion of the sy stem’s flow that must be treated to achieve the targ et MCL level is
assig n ed a cost, as described in Step 5.

Appendix C, Cost Model Methodology C-7 A rsenic in Drinking Water Rule EA

### • I f the site is in violation of the revised MCL

, the percentag e removal required in order to

reach t h e t r eat m e nt t a rg et i s cal cul a t e d.

I f

the site is de te r mine d to be in viola tion of the MCL

, the n Sa f e Wa te r X L c a l c u la te s the pe r c e n t reduction in the site’s arsenic concentration required to reduce the site concentration to 80
percent of the MCL standard. This is a safety factor which includes a 20 percent ex cess removal
to account for sy stem over-desig n. The percent of contamination reduction required can be

ex pressed as:



# ( S ite C o n c

− Tr t T ar ge t 

# ) (Eq. 3) 

### % re mova l = S ite C o n c

.

where: % removal = percent removal required to meet treatment targ et

Site Conc = a r s e n ic c onc e n tr a tion a t the tr e a ting site
TrtTarg e t = 80 percent of revised MCL

The mag n itude of reduction required determines which treatment decision tree is used. A
technolog y is chosen depending on the percentag e removal required and treatment train removal

e f

f i c i e n c i e s tha t will me e t the ta r g e t MCL

. The mode l r e c o g n ize s thr e e c a t e g or ie s of r e quir e d
reduction: <50 percent, 50-90 percent, and >90 percent. Each categ ory is represented by a distinct decision tree of feasible technolog ies for the amount of removal required. F o r ex ample,
if a site has an influent arsenic level of 50 μg /L , and the targ et MCL is 2 μg /L , then 96 percent

r e mova l is r e quir e d. Re se a r c h indic a t e s tha t lime sof t e n ing is only c a p a b le of a c h ie ving

a ppr ox ima te ly 80 pe r c e n t r e mova l, the r e f or e lime sof t e n ing would not be a via b le tr e a tme nt option for that site. Therefore, with information about the appropriate amount of removal
required for the site to achieve compliance, the model is directed to the corresponding decision

tree for a distribution of treatment trains from which to make a selection.

• B ased on the percentag e of removal required to meet the treatment targ et and on the

decision tree for the siz e and ty pe of the sy stem, a treatment train is then assig n ed to the

site

.

Since entry points may have different site concentrations, it is likely that different treatment
technolog ies would be applied at different sites to meet the targ et MCL depending on the

percentag e of removal required to meet the treatment targ et, and on the removal efficiency of the

tr e a tme nt tr a i n se le c t e d. The va r i a b ility of tr e a tme nt tr a i n se le c tion a m ong site s is ba se d on
probabilities defined in a decision tree, which contains a rang e of compliance responses for

dif f

e r e nt sy ste m ty pe s a nd size s, a nd r e pr e s e n t EPA’ s be st e s tima te of the tr e a tme nt tr a i n technolog ies that sy stem operators will choose to achieve a particular percentag e reduction in

arsenic concentration. Specifically , the compliance decision trees are distributions that identify
the percentag e of sy stems in different categ ories that will choose specific compliance options.

F o r e x a m ple

, the de c i sion tr e e spe c i f i e s the pr oba bility of dif f

e r e nt c o mplia nc e c hoic e s f o r

sy stems with different removal percentag e s required, baseline influent concentrations, different

siz e s (e.g ., population served), and different sources (g roundwater and surface water).

Appendix C, Cost Model Methodology C-8 A rsenic in Drinking Water Rule EA

### ⋅

⋅ The deci si on t r ees are speci fi c t o t h e sy st em ’s si z e cat eg ori e s and source wat e r, and vary
according to the contaminant under consideration. S a feW a terXL uses six t een distinct decision
trees in total: one for each of the eig h t sy stem siz e categ ories with g r ound water and surface

water sources. Each decision tree contains a list of treatment trains with three sets of

pr oba bilitie s tha t would a pply to the site , de pe nding on whic h of thr e e r e quir e d tr e a tme nt scenarios the site belong s (<50 percent, 50-90 percent, or >90 percent removal required as

de sc r i be d in Ste p 5)

. The a c t ua l de c i sion tr e e is illustr a te d a s a f

l owc h a r t, a nd is of te n
summariz e d as a decision matrix , for a particular source water and siz e categ ory

. The matrices
used in this analy s is were developed for the Revised Arsenic Rule and may be found in Appendix

A.

Appendix A describes the treatment technolog ies, their effectiveness, and the major factors that
affected the composition of a particular decision tree. Among some of the centraliz ed treatment
options pr e s e n te d inc l ude : lime sof t e n ing

, a n ion e x c h a n g e , a c tiva t e d a l umina

, r e ve r s e osmosis,
and coag ulation assisted microfiltration. Some associated waste disposal technolog ies are also

described. W a ste disposal technolog ies are specific to the treatment technolog y

, althoug h their

a v a ila bility doe s va r y be twe e n size c a t e g or ie s. I n a ddition to the s e c e n tr a lize d tr e a tme nt options,
small sy stems may also elect to use point-of-entry (POE) devices to achieve compliance with the

MCL s , identified as affordable technolog ies by the SDW A

. The available POE technolog ies for
arsenic removal are essentially smaller versions of reverse osmosis and activated alumina.

• U sing the removal efficiency of the treatment train chosen, the percentag e of flow that

must be tr e a t e d in or de r f

o r

the e n tr y point to me e t the tr e a tme nt ta r g e t , is c a l c u la te d.

Once a t r eat m e nt t r ai n i s sel ect ed from t h e deci si on t r ee, t h e associ at ed rem oval effi ci ency of t h e technolog y is used with information on sy stem flow to determine the amount of flow at the site
that must be treated in order to meet the treatment targ et. Sy stem flow is calculated as a power
law function of the population served. EPA derived these functions, the derivation of which can

be found in the Geometries and Characteristics of Public W a ter Systems report (U.S. EPA, May
1999). B o th the equations, and the reg r ession parameters employ ed in the SafeW a terXL cost model are presented in the following two equations and Ex hibit C-5, respectively

.

Average Flow a A 

### # ( Population ) b A 

### (Eq. 4)



### D e s i gn Fl ow = m ax 

# ) (    2 A v e r a g e F l o w

P opu latio n b

D 

# a D 

### (Eq. 5)

where: a A 

### , b A 

### , a D 

### , b D 

### = reg r ession parameters derived for flow vs. population
Population = population served by the sy stem ty pe and source

Appendix C, Cost Model Methodology C-9 A rsenic in Drinking Water Rule EA

### Exhi bi t C- 5.

Fl ow Regressi on Paramet e rs by Sy st em Source and O w nershi p T y pe

Sy stem So u r ce an d

Ow ne r s hip T y pe A v e r a g e Flow D e s i gn Flow

a A b A a D b D

G r ound W a t

e r

Public 0. 08558 1. 05840 0. 54992 0. 95538

Priv at e 0

. 06670 1. 06280 0. 41682 0. 96078

Public-Purchased 0. 04692 1. 10190 0. 31910 0. 99460

Priv at e-Purchased 0. 05004 1. 08340 0. 32150 0. 97940

Surf ace W a t

e r

Public 0. 14004 0. 99703 0. 59028 0. 94573

Priv at e 0

. 09036 1. 03340 0. 35674 0. 96188

Public-Purchased 0. 04692 1. 11020 0. 20920 1. 04520

Priv at e-Purchased 0. 05004 1. 08340 0. 20580 1. 00840

Source: U. S. EPA. 1999. G eom et ries and Charact e rist ics of Public W a t

e r Syst em s

. Prepared for O ffice

of G r ound W a t e r and Drink i ng W a t e r by Science Applicat ions I n t e rnat ional Corporat ion. EPA Cont ract

No. 68-C6-0059.



### B a sed on these data, the sy stem flow is determined in thousands of g a llons per day (KGPD). The

sy stem flow is then divided equally among the possible sites of contamination, reg a rdless of
whether they are treating (i.e., violation of the revised MCL standard) or not. F o r ex ample, a

sy st em wi t h four pot ent i a l si t e s of cont am i n at i on i s m odel e d t o have four si t e s, each wi t h 25
percent of the total sy stem flow. However, even with this distribution of sy stem flow between
the number of sites, the resulting flow assumed at each site is further adjusted for treating sites,
such that only the portion of flow that must be treated to lower the arsenic concentration is
accounted for in the subsequent cost estimate.

SafeW a terXL employ s a “blending ” principle to determine the amount of flow that requires
treatment in order for the entry point to meet the treatment targ et established by the MCL

. The

tr e a tme nt ta r g e t is c onside r e d 80 pe r c e n t of the MCL a nd r e pr e s e n ts the c onta mina n t le ve l to

whic h the de sig n of sy ste m s will pe r f o r m , to e n sur e a d e qua te c o mplia nc e with the MCL

. To

reach t h i s t a rg et , dat a on t h e rem oval effi ci enci es of t h e chosen t r eat m e nt t r ai ns, t h e cont am i n ant occurrence at the site, and the percent of flow apportioned to that entry point are used to

determine the fraction of flow needed to be treated, as ex pressed by the following relationship:

 T r tT ar get   
Si teC o nc − 1   

### (Eq. 6) F r ac tio n o f Fl ow T r

eat e d = × 

### ( % S ite Fl ow 

### )

- %RE

Appendix C, Cost Model Methodology C-10 Arsenic in Drinking Water Rule EA

### where: TrtTarg e t = 80 percent of revised MCL

Site Conc = a r s e n ic c onc e n tr a tion a t the site

% R E = % removal efficiency of treatment train chosen

% Site F l ow = % of tota l sy ste m f l ow a ttr ibuta b le to tha t site

Notice that the blending technique is applied at the entry point level, but it is not used for sy stems selecting POU devices, as those options treat water at the tap rather than for the entire house.
Since treatment costs to reduce such hig h levels of contamination can be sig n ificant, blending is
an approach S a feW a t e rXL t a kes t o best charact eri z e t h e ex pect ed cost of com p l i a nce. I n t h i s

ma nne r

, tr e a tme nt c o sts a r e ta llie d only a m ong the site s tha t a r e e x pe c t e d to tr e a t , f o r

the por tion
of the overall sy stem flow that actually g e ts treated.

• T he percentag e of flow that needs to treated is applied to the desig n flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:

tr e a tme nt c a p ita l, wa ste disposa l c a p ita l, a nd a n y pr e

- tr e a tme nt c a p ita l c o sts)

.

Each treatment train is defined by a treatment technolog y and (where relevant in order to be
effective) a waste disposal option, and/or pre-treatment technolog y

. Therefore, the cost of the
treatment trains is related to its constituent capital and O& M cost components. Capital costs are

e s tima te d a s a f

unc tion of de sig n f l ow. Whe n the tr e a tme nt tr a i n ha s be e n se le c t e d, the ove r a ll
capital costs of these various components are ag g r eg ated to derive an overall capital cost

estimate. This is ex pressed in the following g e neral treatment train cost functions at each site:



## Tr C = 

## T + 

## WD + 

# [ ( P 

# ) 

# ( P O 

# ) 

# ] (Eq. 7)

cap c ap cap P O c ap



### where: TrC = T r e a tme nt tr a i n c a p ita l c o st a t tr e a ting site

cap 

### T = T reatment technolog y capital cost at treating site

cap 

### WD

cap 

### = W aste disposal technolog y capital cost at treating site

P PO 

### = P r oba bility of using pr e

- ox ida tion a t tr e a ting site

PO

cap 

### = P re-ox i dation technolog y capital cost at treating site

Depending on the source water conditions and on the treatment technolog ies involved, EPA
determined that some sy stems would require additional pre-ox idation. EPA developed a separate
decision tree to approx imate the number of sy stems that would implement pre-ox idation
technolog ies when selecting a treatment train. The need for this separate decision tree was based
in part on the distribution of sy stems with and without treatment-in-place. For technolog y trains

in whic h pr e

- tr e a tme nt is r e quir e d, Ex hibit C- 6 summa r i ze s the de c i sion tr e e of pr oba bilitie s by

sy stem siz e that a sy stem would require these technolog ies.

Each of the treatment technolog ies considered in the decision tree remove As(V) more readily

t h a n A s ( III) a n d a s a r e s u l t

, p r e

- o x i d a t i o n m a y b e n ecessary depending upon source water

conditions. S y stems without treatment in-place may already be chlorinating which may meet

pre-ox idation requirements. F o r those sy stems, pre-ox idation may or may not need to be

installed. Similarly

, sy stems with treatment in-place may have pre-ox idation in-place, which
could meet the pre-ox idation requirements.

Appendix C, Cost Model Methodology C-11 Arsenic in Drinking Water Rule EA

### Exhi bi t C- 6.

P r o b a b ility o f a S y s t e m R e q u i rin g P r e

- Ox id a t io n

Sy s t e m Size C a te gor y P r e -Ox i da tion (G W sy stems) Pr e

- Ox ida t ion (SW sy stems)

25-100 0. 54 0. 09

101-500 0. 30 0. 04

501-1, 000 0. 24 0

1, 001-3, 300 0. 24 0

3, 301-10, 000 0. 27 0. 03

10, 001-50, 001 0. 13 0. 01

50, 001-100, 000 0. 41 0. 02

100, 001-1, 000, 000 0. 16 0

Source: F a csim ile f r om Am it Kapadia, EPA O G W DW

, July 27, 1999.



### Simila r l y

, the pe r c e n ta g e of f

l ow tha t ne e d s to tr e a t e d is a l so a pplie d to the a v e r a g e f l ow, whic h
is then used to derive the operation and maintenance costs of the components of the treatment
train (the sum of: treatment O& M, waste disposal O& M, and any pre-treatment O& M costs).

Unl i k e capi t a l cost s, whi c h are ex pressed as a t o t a l cost , operat i on and m a i n t e nance cost s are

ex pressed as a cost per y ear, and are cal cul a t e d as a funct i on of averag e fl ow. The t o t a l O/ M costs for each treating site are ag g r eg ated to derive an annual sy stem O/M cost for the treatment
technolog y

. Treatment O& M cost, waste disposal O& M, and any pre-treatment O& M costs are

tallied. These conditions are ex pressed in the following g e neral treatment train cost functions at

each si t e :



## Tr C

& = 

## T

O M & + 

## WD

O & M + 

# [ ( P 

# ) ( P O

O & M 

# ) 

# ] (Eq. 8)

OM P O



### where: TrC O& M 

### = T r e a tme nt tr a i n O& M c o st a t tr e a ting site

T O& M 

### = T reatment technolog y O& M cost at treating site

WD O& M 

### = W aste disposal technolog y O& M cost at treating site

PO O& M 

### = P re-ox i dation technolog y O& M cost at treating site

Since the treatment technolog ies produce residuals that may contain various levels of arsenic, the

O&M cost s associ at ed wi t h t h e t r eat m e nt t r ai n are an i m port a nt consi d erat i on i n t h e overal l cost of the technolog y chosen. The handing and disposal costs associated with these residuals can be
sig n ificant, and depend on a number of factors, such as the siz e and flow of the water sy stem. The amount of waste that is g e nerated will affect which technolog y is implemented by a water

sy stem. F o r ex ample, some methods may be impractical for larg er sy stems due to land
requirements. Alternatively

, more ex pensive processes may be inappropriate for smaller sy stem

due to the cost. Process oversig ht, transportation, and labor are all factors affecting the overall
cost of the process. I n g e neral, the more complex the handling and the disposal methods, the

mor e sig n if ic a n t the ma inte na nc e r e quir e me nts, a nd the r e f or e the mor e c o stly

.

Appendix C, Cost Model Methodology C-12 Arsenic in Drinking Water Rule EA

### • T he sy stem’s total annual treatment costs are calculated for the selected treatment train at
various discount rates, by summing the treatment costs (annualized capital plus annual

O& M cost components) across all treating sites.

Since operation and maintenance costs are annual, apply i ng the amortiz ation formula on the
capital cost component (Step 8) over a specified period of repay m ent, results in an overall annual

cost of treatment at a site:



# Tr C

& 

### (Eq. 9)

tot 

### = 

# ( T r C

c ap 

# )   

1

− 

### ( r r

+ 1 

### )

− rp 

###   

+ 

# Tr C

OM



### where: TrC

to t 

### = A nnual total treatment train cost at treating site

TrC = T r e a tme nt tr a i n c a p ita l c o st a t tr e a ting site

cap



### r = Discount rate

rp = R epay ment period

TrC O& M 

### = T r e a tme nt tr a i n O& M c o st a t tr e a ting site

F o r the purposes of estimating the national cost of compliance, public water sy stem and
implementation costs are tracked over a 20-y ear period. This time frame is used because many
public water sy stems often finance their capital improvements over 20 y ears. This may

, however, result in an overestimate of annualiz ed costs because many types of equipment last
long er than 20 y ears. Capital and operational and maintenance (O& M ) costs may be incurred at
different points throug hout the time period. F o r this reason, two adjustments were made to the
estimated costs forecasted by SafeW a terXL in order to render future costs comparable with
current costs, reflecting the fact that a cost outlay today is a g r eater burden than an equivalent

c o st outla y some time in the f u tur e

.

I n t h e fi rst i n st ance, com p l i a nce cost s t h at are subsequent l y used i n cost -benefi t anal y s es are
annualiz ed using a social discount rate so that reg u latory option costs (e.g . costs for an MCL of 5

μg /L vs. an MCL of 10 μg /L ) may be directly compared to the annual benefits of the
corresponding reg u latory option. Annualiz ation is similar to the process involved in calculating

a mortg a g e pay m ent; the result is a constant annual cost as ex pressed in Equation 9. The Ag ency performs cost-benefit analy s es using two social discount rates. As required by the Office of
Manag e ment and B udg et (OMB ), a seven percent discount rate is used in estimating the national
cost of compliance in a rulemaking

. A three percent discount rate is also used to estimate the

c o sts of c o mplia nc e

, a s the Ag e n c y be lie ve s this r a te mor e c l ose l y a ppr ox ima te s the tr ue soc i a l

discount rate.

I n the second instance, compliance costs that are subsequently used in various economic impact

a n a l y s e s a s r e quir e d by the SDWA a nd its Ame ndme n ts, suc h a s in a f f

o r d a b ility a n a l y s e s , a r e
annualiz ed using an actual cost-of-capital discount rate rather than a social discount rate.
Affordability analy s es ex amine the costs of compliance to sy stems and individual households,

rather than on a national level. Costs to households are considered a g ood prox y for determining

the a f f

o r d a b ility of r e g u la tor y c o mplia nc e

, a s de sc r i be d in the disc ussion on ma x imum a llowa ble
household cost in Step 11 below.

Appendix C, Cost Model Methodology C-13 Arsenic in Drinking Water Rule EA

### They are dependent on sy stem costs to the ex tent that sy stem costs are recovered throug h

i n creased wat e r rat e s. The cost -of-capi t a l rat e i s used t o refl ect t h e t r ue aft e r-t ax cost -of-capi t a l

t h at wat e r sy st em s face, net of any g overnm e nt g r ant s or subsi d i e s. The recom m e nded cost -ofcapital rates stratified by ownership, sy stem ty pe and siz e , as reported in Devel opment of C o st of
Capital Estimate s for Public W a te r Sy ste m s (U.S. EPA, 1998), were used in SafeW a terXL

. These were presented in Ex hibit 6-7.

Tog e ther, the annualiz ed capital and O& M cost components equal the annual cost of treatment.

W h en these costs are summed across all the treating sites in a sy stem, the annual sy stem cost is

c a l c u la te d. I n othe r wor d s, the sy ste m ’ s c o st of c o mplia nc e is de te r mine d by summing a c r oss the

t r eat i n g si t e s. For each sy st em i n whi c h a vi ol at i on of t h e revi sed MC L i s ex pect ed, t h i s overal l

cost i s cal cul a t e d:



# SC

= 

# ∑ n 

# ( TrC

to t n

, 

# ) (Eq. 10)

ir

n = 1



### whe r e : i = Sy ste m/mode l ite r a tion

n = Numbe r of tr e a ting site s in the sy ste m

SC ir 

### = A nnual cost for sy stem i at discount rate r

TrC

to t 

### = A nnual total treatment train cost at treating site

• T he annual sy stem cost is used to derive the cost per thousand g a llons (cost/kg a l)

del i v ered by t h e wat e r sy st em

.

Once the annual cost per sy stem is determined by summing the costs of all the treating sites of
the sy stem, this cost is used to determine the unit cost of delivery (cost per thousand g a llons
delivered) for the sy stem as a result of the new treatment technolog y

. The sy stem cost annualiz ed
at the cost-of-capital discount rate is used in this calculation as it best represents the true cost
impact on the sy stem. The cost per thousand g a llons delivered is calculated as:



# Cos t kgal = 

# S C

i c oc ÷   

# AF

⋅ 36 5 d a y s 10 00 kga l   

### (Eq. 11)

⋅

,  i 1 y r 1 M g a l 



### where: C o st kg a l 

### = C ost per thousand g a llons for the sy stem

AF i 

### = A verag e flow (MGD) of sy stem i

S C i

, c o c 

### = A nnual cost for sy stem i at the cost-of-capital discount rate

• A nnual household costs are then calculated based on the sy stem’s unit cost of delivery
(cost per thousand g a llons) and the averag e annual household consumption per y e ar.

The sy stem’s cost per thousand g a llons delivered is used to calculate household costs according
to Equation 12. The values used as estimates of the averag e annual tap water consumption per

y ear are presented in Ex hibit 7. More detail was g i ven in Chapter 4.

Appendix C, Cost Model Methodology C-14 Arsenic in Drinking Water Rule EA

# Cos t = 

# Cos t

⋅ 

# C (Eq. 12)
HHi k g a l HH



### where: C o st HHi 

### = H ousehold cost per y ear for sy stem i

C HH 

### = H ousehold consumption per y ear (kg a l)

Exhi bi t 7.

Wat e r Consumpt i on per Resi dent i a l Connect i o n

Sy s t e m Size C a te gor y S y s te m Ow ne r s hip T y pe

Public Pr iva t e

<100 81 92

101-500 93 110

501-1, 000 97 88

1, 001-3, 300 82 102

3, 301-10, 000 87 124

10, 001-50, 000 108 110

50, 001-100, 000 122 96

100, 001-1, 000, 000 127 114

Source: EPA. 1997. CW SS, Vol. II: Detailed Sum m a ry Result Tables and M e thodology Report

, Table 1­

14.



### • I f household costs are determined to ex ceed an affordability threshold of $500, a less

ex pensive treatment technolog y (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POU devices).

SafeW a terXL employ s a max imum allowable household cost of $500, which forces sy stems who
initially choose a treatment train with annual household costs in ex cess of $500, to default to a
POE device, thereby seeking a less ex pensive method of compliance. I n g e neral, the results of
the model simulation showed that only the smallest sy stems (serving 25-500 people) are affected
by this threshold. B a sed on the overall number of sy stems in these two siz e categ ories (see

Ex hibits 1 and 2), the number of sy stems affected is relatively small. SafeW a terXL does record
the number of sy stems ex ceeding this affordability threshold.

• T he sy ste m r e sults a r e ma inta ine d in a da ta ba se f o r

f

u r t he r a n a l y s is.

C

. 2.1 Example C a lculat ion ( S ingle It erat ion)

I n this section, we demonstrate the process by which SafeW a terXL calculates the annual cost of
compliance for a sing le sy stem assuming a targ et MCL of 5 μg /L

. Each step in the procedure
described in the previous section is addressed to ex emplify how the many assumptions and data
inputs are pooled tog e ther in a sing le iteration.

Appendix C, Cost Model Methodology C-15 Arsenic in Drinking Water Rule EA

### Give n the f o llowing Sa f e Wa te r X L mode l se tting se le c tions by the use r :

• S ource water = g r ound water;

• Ownership ty pe = public;

• M CL = 10 μg /L ;

Then, a si ng l e i t e rat i on of t h e m odel proceeds as fol l o ws:

1. A sy ste m is se le c t e d f r o m da ta f

ile s.

A publicly -owned community g r ound water sy stem with three entry points serving 10,000 people

is se le c t e d f r o m the da ta f

ile s.

2. Each sy stem is assig n ed a random concentration from an occurrence distribution.

B a sed on accompany i ng information in the data file for g r ound water sy stems, an averag e sy stem concentration of 11.03 μg /L is selected from an occurrence distribution bound by a log normal

mean of
-0.2507 and a log standard deviation of 1.5826.

3. The selected arsenic concentration for the sy stem is distributed across the number of sites
(entry points) of possible contamination for that sy stem based on the relative intra-sy stem standard deviation (RSD).

Since the sy stem has three entry points, based on the averag e sy stem concentration of 11.03 μg /L

, the max imum site concentration is determined to be 33.10 μg /L (= 11.03 * 3). Using the default

RSD of 0.64 and this limitation on the max imum site concentration, the three sites are assig n ed
concentrations of 8.89, 9.69, and 14.52 μg /L , respectively

. These three concentrations keep the

averag e sy stem concentration at 11.03 μg /L

.

4. The concent r at i on at each si t e i s com p ared t o t h e revi sed MC L st andard t o det e rm i n e i f

the site is in violation of the revised standard.

The first two sites are determined to have concentrations of 8.89μg / L and 9.69μg / L

, both of

which are below the user selected MCL of 10 μg /L

. The final site of the sy stem, however,

ex ceeds the MCL with a concentration of 14.52 μ g /L , and is the only site for which the

remainder of the calculations are conducted.

5. I f the site is in violation of the revised MCL

, the percentag e of removal required in order

t o reach t h e t r eat m e nt t a rg et i s cal cul a t e d.

Appendix C, Cost Model Methodology C-16 Arsenic in Drinking Water Rule EA

### F r om Equation 3 above, the percent of removal required for a site with an influent concentration
of 14.52 μ g /L to reach the treatment targ et of 8 μ g /L (80 percent of MCL 10 μ g /L ) equals 45

percent :



# ( SiteConc
− Tr t T ar g e t 

# ) ( 14 52 8 

### )

. − % removal = = = 0 4490

. SiteC onc. 14 52

.



### 6. B a sed on the percentag e of removal required to meet the treatment targ et and on the

decision tree for the siz e and ty pe of the sy stem, a treatment train is then assig n ed to the

site

.

Using the decision tree for g r ound water sy stems for the siz e categ ory serving 3,301-10,000

pe ople

, a tr e a tme nt tr a i n is se le c t e d ba se d on the pr oba bilitie s f r o m the “ < 50% ” r e mova l c o lumn
since this site requires 45 percent removal.

F o r this iteration, Treatment Train #6 (Coag u lation/Microfiltration, Nonmechanical Dewatering

, Non-Haz a rdous L a ndfill) is selected. This treatment rain has a removal efficiency of 90 percent.

7. Using the removal efficiency of the treatment train chosen, the percentag e of flow that

must be tr e a t e d in or de r f

o r

the e n tr y point to me e t the tr e a tme nt ta r g e t is c a l c u la te d.

The sy stem flow must now be determined. Since the sy stem in this iteration of the model is a
public g r oundwater sy stem, using the flow equations (Equations 4 and 5) and the reg r ession
parameters from Ex hibit C-5, the desig n flow equals 3.646 MGD:

D

. 

### D e s i gn F l ow = 

# a D 

### ⋅ 

# ( po pu la ti on 

# ) b

= ( . 0 5 49 92 ) ( ⋅ , ) = 3 64 6 0 23 93

. × 1 Mg al

= 36 4 6 1 0 0 0 0 0 95538



### . 10 00 kg al



### and the averag e flow equals 1.465 MGD:

A **.** Ave r age F l ow 

## a A 0 08558 1 058 40 1465 454309 1 M gal

**.** = ⋅ 

## ( population 

## ) b

= **(. )**  **(**

**,** ⋅ 10 000 **)** =

**.** kgal × 1000 kgal = 1 465



### As described in Step 7 above, the sy stem’s total flow is evenly distributed among all the possible

sites. I n this case, since there are three sites, each receives 33.3 percent of the total sy stem flow.
Using the principle of blending , the fraction of the sy stem’s total flow that must be treated in
order for the site to meet the treatment targ et equals 16.6 percent:

 Tr tTa r get   8   
SiteC o nc − 1    
14 52 − 1   

− 

###  

### ( ) . 0 9 0  

.   0 166 3 Fr actio n o f Flow = × %Si t e F l o w = × 0 3 3 3 =

.

- % R E
−

.

Appendix C, Cost Model Methodology C-17 Arsenic in Drinking Water Rule EA

### 8. The percentag e of flow that needs to treated is applied to the desig n flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:

tr e a tme nt c a p ita l, wa ste disposa l c a p ita l, a nd a n y pr e

- tr e a tme nt c a p ita l c o sts)

.

Apply i ng the fraction of the sy stem’s total flow (16.6 percent) to the sy stem’s total desig n flow

(3.646 MGD) from Step 7 above, the desig n flow at the treating site can be calculated:



### ( . MGD ) × ( 0 1 66

. ) =

. 3 6 46 0 6 06 M GD

This a d juste d f l ow is the n use d to de te r mine the c a p ita l c o sts of the tr e a tme nt tr a i n using the
various cost equations for the treatment capital and waste disposal capital. F o r this treatment train, the treatment capital cost is $1,495,716 and the waste disposal capital cost is $1,169,055, for a total capital cost of $2,664,771. 4 

### F o r desig n flow (x ), the cost (y ) can be calculated:

Tr e a tme nt c a p ita l : x <0.1 y = -11935465x 2 

### + 48800366x + 94324

0.1<x < 0.27 y = 2343199x + 228653

0.27<x < 1 y = -483591x 2 

### + 2308991x + 273143

<1x < 10 y = 1030810x + 1067733

x > 10 y = 320x 2 

### + 921471x + 2129119

B a sed on a site desig n flow of 0.606 mg d, the third seg m ent of the cost equation is used:



## 48 35 91 0 6 0 6 

## (

. 

## ) 2 

## + 23 08 991 0 6 0 6 

## ) y =− 

## (

. − 27 31 43

Simila r l y

, f o r

de sig n f l ow ( x ) = the wa ste disposa l c a p ita l c o st ( y ) c a n be c a l c u la te d f r o m the s e equations:

W a st e Di sposal capi t a l : x <0.085 y = 3069360x - 790

0.085<x < 1.8 y = 1749352x - 108017

x > 1.8 y = 1627970x + 326504

F o r the waste disposal capital cost, the second cost seg m ent is used:



# (

. 

# ) 108017 y = 1749352 0 606

−

I n this e x a m ple

, ba se d on the pr oba bility distr i bution liste d in Ex hibit 6, pr e

- ox ida tion wa s not

sel ect ed, t h erefore t h e pre-ox i d at i on capi t a l cost s are not cal cul a t e d and i n cl uded i n t h e capi t a l
cost component of the treatment train.

4 Cos t s pres ented in this exam ple are in A p ril 1998$, althoug h pos t- proces s i ng of S a f eWaterX L res u lts
updated these costs to May 1999$ in the Reg u latory Im pact Analy s is. Totals m a y not equal sam p le calculation

prov ided due to rounding of input v a riables.

Appendix C, Cost Model Methodology C-18 Arsenic in Drinking Water Rule EA

### 9. Simila r l y

, the pe r c e n ta g e of f

l ow tha t ne e d s to tr e a t e d is a l so a pplie d to the a v e r a g e f l ow, which is then used to derive the operation and maintenance costs of the components of
the treatment train (the sum of: treatment O& M, waste disposal O& M, and anypretreatment O& M costs).

Similarly

, by apply i ng the fraction of the sy stem’s total flow (16.6 percent) to the sy stem’s total

averag e flow (1.465 MGD) from Step 7 above, the averag e flow at the treating site can be

cal cul a t e d as fol l o ws:



### (. MGD ) × ( 0 1 66 3

. ) =

. 1 4 65 0 2 4 4 M GD

This f l ow is the n use d to de te r mine the ope r a tion a nd ma inte na nc e c o sts of this tr e a tme nt tr a i n using the various cost equations for treatment O& M and waste disposal O& M. The treatment

O& M cost is $46,500 and the waste disposal O& M cost is $20,309, for a total annual O& M cost of $66,809. F o r averag e flow (x ), the O& M cost (y ) is:

Treatment O& M : x <0.03 y = 196829x +20264

0.03<x < 0.09 y = 136332x + 22139

0.09<x < 0.36 y = 80081x + 26977

0.36<x < 4.3 y = 13311x + 51014

x > 4.3 y = 15236x + 42350

B a sed on a site averag e flow of 0.244 MGD, the third seg m ent of the cost equation is used:



# (

. 

# ) + 26 977 y = 80 081 0 2 4 4

Simila r l y

, f o r

a v e r a g e f l ow ( x )

, the wa ste disposa l c o st ( y ) is:

W a ste Disposal O& M : x <0.085 y = -18812x 2 

### + 4686.1x + 2123.8

0.085<x < 0.72 y = 111819x - 6950.5

x > 0.72 y = 16.966x 2 

### + 60792x + 28760

F o r the waste disposal O& M cost, the second cost seg m ent is used:



## (

. 

## ) 6 9 5 0 5

. y = 11 181 9 0 24 4
−

Ag ain, since pre-ox idation was not selected, no pre-ox idation O& M costs are calculated or

included in the O& M cost component of the treatment train.

10. The sy stem’s total annual treatment costs are calculated for the selected treatment train at
various discount rates, by summing the treatment costs (annualized capital plus annual

O& M cost components) across all treating sites.

Appendix C, Cost Model Methodology C-19 Arsenic in Drinking Water Rule EA

### F r om Step 8, the total capital costs for this treatment train equal $2,664,771. F r om Step 9, the

total O& M costs for the treatment train equal $66,809. Using a capital cost amortiz ed at 5.26

percent 5 

### over 20 y ears, the annual cost to the sy stem equals $284,278:

.

= 

# ( TrC

cap 

# )   

1

− 

### ( r r

+ 1 

### )

− rp 

###   

+ 

# T rC

OM 

### = 

## ( $2

, 66 4 7 7 1

, 

## )   

1

− 

### (

. 0 0 52 6

+ 1 

### ) (

− ) 

###   

+ $6 6

, 80 9 = $2 84

, 2 7 8

& 20 

### 0 05 26



### The ex ample display e d here uses the commercial rate, which is a closer approx imation to the cost
of capital to water sy stems. Annual costs are also calculated at 3 and 7 percent, respectively

, as $245,923 and $318,344.

11. This annual sy stem cost is used to derive the cost per thousand g a llons (cost/kg a l)

del i v ered by t h e wat e r sy st em

.

The unit c o st of wa te r de live r e d by this sy ste m ( c ost pe r kg a l pe r y e a r ) a s a r e sult of insta lling
treatment is determined by dividing the sy stem cost by the sy stem averag e flow. The sy stem cost that was derived using the commercial discount rate is used to arrive at a unit cost of $0.53:



## SC  365 day s

⋅ 1000 kga l  

. 

### )

⋅ 365 1000  = 53 = ir ÷   

## AF

i ⋅ 1 yr 1 Mgal   = 

### ( $284

, 278 

### ) ÷   

### ( 1 465 1 ⋅ 1  $0

.



### 12. Annual household costs are then calculated based on the sy stem’s unit cost of delivery
(cost per thousand g a llons) and the averag e annual household consumption per y e ar.

The cost per thousand g a llons to the water sy stem calculated in Step 11 is used to estimate the
annual cost to households as a result of reg u latory compliance, by multiply ing it with the averag e annual household consumption of tap water for a sy stem in that siz e categ ory :

= 

## Co st kg al i

, ⋅ 

## C

H H = 

### ( $0

. 53 

### )

⋅ 

## ( 108 kg al 

## )

= $46

. 24



### The annual water consumption per household is presented in Chapter 4 and stratified by siz e
categ ory and ownership ty pe.

13. I f household costs are determined to ex ceed an affordability threshold of $500, a less

ex pensive treatment technolog y (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POE devices).

5 Com m e rcial discount rates are presented in Exhibit 6- 7 of Chapter 6 of the Reg u latory Im pact Analy s is,

and determ ined by size categ ory and ow nership ty pe.

Appendix C, Cost Model Methodology C-20 Arsenic in Drinking Water Rule EA

### Since the estimated annual household cost for this sy stem is $46.24, this step does not affect the

c a l c u la tions a l r e a d y disc usse d. As de sc r i be d e a r lie r

, this a f f

o r d a b ility thr e shold a f f

e c t s only the
smaller sy stem siz e categ ories (<100 and 101-500). Therefore, the results of this iteration are

recorded and the nex t iteration is trig g e red in Step 14.

14. The r e sults a r e ma inta ine d in a da ta ba se

.

C.3 Mode l Run

C

. 3.1 N u mber of It erat ions

Onc e a sing le ite r a tion is c o mple te d, the c a l c u la te d sy ste m da ta is r e c o r d e d. Among the c o st da ta

forecast e d for each i t e rat i on are t h e fol l o wi ng :

• a nnual sy stem cost (calculated at three discount rates: three percent, seven percent, costof

c a p ita l) ;

• s y s tem capital cost (calculated at one discount rate: cost-of capital);

• s y s tem O& M cost (calculated at three discount rate: cost-of capital);

• c ost per thousand g a llons (calculated at one discount rate: cost-of capital); and

• household cost (calculated at one discount rate: cost-of capital).

Onc e c o mple te , a nothe r ite r a tion is sta r te d. This is r e pe a t e d N time s, until the tota l numbe r of
iterations (the total number of sy stems) for that siz e categ ory is met, at which point the total

annual national cost estimate for that siz e categ ory is determined.

Nex t , once each si z e cat eg ory i s fi ni shed, t h e fi rst i t e rat i on of t h e nex t si z e cat eg ory beg i ns. The

c y c l e s c ontinue until a ll ite r a tions of a ll e i g h t size c a t e g or ie s ha ve be e n c o mple te d. The tota l
annual national cost across all sy stems is therefore the sum of the annual national costs for each

siz e categ ory of sy stems, both publicly - and privately

- owned.

I f

g r a phe d a g a i nst the e s tima te d me a n, the a v e r a g e sy ste m c o st would g e ne r a lly f

l uc tua t e g r e a tly
between iterations at the beg i nning of a model run. However, as the number of data points
increases, these fluctuations will dampen and should eventually converg e on the estimated mean.
The number of iterations must be a multiple of the number of sy stems that belong to each siz e

c a t e g or y

. This se tting will a void a n y sy ste m a tic bia s a s the mode l c y c l e s thr oug h a ll the sy ste m s
wi t h i n each si z e cat eg ory from sm al l e st t o l a rg est

.

Each cy cl e t h erefore represent s t h e uni verse of sy st em s i n t h at cat eg ory as pul l e d from S D W I S
(as summariz e d in Ex hibits C-1 and C-2). Using this method, approx imately the same number of

non-z e ro data points should be g e nerated when the same iteration setting s are selected.

The anticipated number of non-z e ro data points is a function of the MCL

, the occurrence
distribution, and the number of sy stems in the siz e categ ory

, where a non-z e ro data point is a

sy stem that is required to treat and incurs treatment costs. F o r ex ample, approx imately eig h t

cy cles of the universe of g r ound water sy stems serving less than 100 people (14,432 sy stems, as

Appendix C, Cost Model Methodology C-21 Arsenic in Drinking Water Rule EA

### shown in Ex hibit 1) are required to achieve 20,000 data points g i ven an MCL of 3 μg /L , and an
occurrence distribution where 19.7 percent of the sy stems are ex pected to ex ceed the MCL

. For the purposes of reg u latory analy s is of arsenic in drinking water, a g o al of 20,000 data points was

used in SafeW a terXL

.

C.3.2 Model Outputs

The pr ima r y outputs of the Sa f e Wa te r X L mode l a r e na tiona l- le ve l e s tima te s of c o sts of
compliance, as well as distributions of cost to sy stems or households, across various water

sy st em servi ce si z e cat eg ori e s. To achi e ve t h ese resul t s , t h e out put g e nerat e d for each i t e rat i on, as striated by water source, ownership, and service siz e categ ory

, are combined by SafeW a terXL

at the conclusion of the model run.

Averag e Annual Sy stem Cost (Calculated at the Cost-of Capital Discount Rate)

Each iteration of the model describes the treatment and cost profile for a sing le sy stem in a sing le

siz e categ ory

. Sy stem cost is essentially equal to treatment cost, which is based on the treatment
train technolog y chosen and the capital and operating and maintenance (O& M ) costs of that

selected treatment train. These costs are in turn a function of the amount of flow processed by

the wa te r sy ste m: c a p ita l c o sts a r e e s tima te d a s a f

unc tion of de sig n f l ow, while O& M c o sts a r e based on averag e flow. I n addition to these treatment cost components, associated waste disposal

c a p ita l a nd O& M c o sts a r e a l so inc l ude d. A por tion of the s e sy ste m s a r e the n e s tima te d to
require pre-ox idation, which would add incremental costs to the total treatment cost.

I n the case of calculating an averag e sy stem cost, a commercial discount rate that is closer to the

act ual cost of capi t a l t h at sy st em s m i g ht face i s used:

m j 

## ∑ 

## ( SC 

## )

Av g S C

jr i = 1 ir 

### (Eq. 13)



## . = 

## m j



### where: S C jr 

### = A nnual sy stem cost for siz e categ ory j at discount rate r

SC ir 

### = A nnual cost for sy stem i at discount rate r
j = S i z e cat eg ory

m

j 

### = N umber of sy stems in siz e categ ory j

Althoug h the equation above is used to calculated the averag e sy stem cost for a particular siz e
categ ory

, the result represents one ownership and source ty pe (e.g . averag e sy stem cost for public

g r ound water sy stems serving <100). I n order to combine the results for the two ownership ty pes for a sing le run, each sy stem cost must be weig hted by its respective number of treating sy stems over the universe of sy stems in that siz e categ ory :

      

## Av g S C

. j pub ( )   

# ( n j pub ( ) 

# ) +   

## Av g S C

j p r v

  

# ( n j p r v



# )

. Av g S C

. j t ot al ) = 

# ( + 

# ) ( ) ( )

( 

## n j pub ) 

## n j ) ( ( p rv 

### (Eq. 14)

Appendix C, Cost Model Methodology C-22 Arsenic in Drinking Water Rule EA

### where: S C j( to t) 

### = T otal annual sy stem cost for siz e categ ory j

SC i ( pub) 

### = A nnual sy stem cost for publicly -owned sy stems of siz e categ ory j

SC i( p r v ) 

### = A nnual sy stem cost privately

- owned sy stems of siz e categ o ry j

n

j ( pub) 

### = N umber of publicly -owned treating sy stems in siz e categ ory j

n

j( p r v ) 

### = N umber of privately

- owned treating sy stems in siz e categ ory j

Averag e Annual Household Cost (Calculated at the Cost-of Capital Discount Rate)

Since household costs are also calculated for each sy stem, a similar distribution of the cost of
compliance at the sy stem level are also calculated at the household level:.

m j 

## ∑ Cos t

HH i
1 

## Av g C os t

. HH j = i = 

## ( ) (Eq. 15)



## m

j



### where: C o st HHj 

### = A nnual household cost for siz e categ ory j

Cost HHi 

### = H ousehold cost for sy stem i

m

j 

### = N umber of sy stems in siz e categ ory j

Simila r l y

, just a s the a v e r a g e sy ste m c o st wa s we ig hte d a c r o ss owne r s hip ty pe s ( E qua tion 14) the

averag e household cost for a sing le siz e categ ory must be a weig hted averag e taking into
consideration the number of households affected for each ownership ty pe within the siz e

cat eg ory

.

Annual National Cost (Calculated at Two Discount Rates , 3 percent and 7 percent)

Annual cost for a sy stem siz e categ ory is determined by adding the total cost of compliance

across each t r eat i n g sy st em wi t h i n t h at si z e cat eg ory (e.g . t h e sum of al l t h e sy st em cost s for each

iteration in that siz e categ ory )

. This is a function of the individual sy stem cost not the averag e

sy stem cost, calculated at three and seven percent discount rates:

m j 

## AC

jr = 

## ∑ 

# ( SC

ir 

# ) (Eq. 16)

i =

1



### where: AC jr 

### = A nnual cost for siz e categ ory j at discount rate r

SC ir 

### = A nnual cost for sy stem i at discount rate r

Similarly

, the annual national cost is total determined by adding the annual cost of compliance

a c r oss a ll the size c a t e g or ie s ( e .g . the sum of a ll the sy ste m c o sts f o r

a ll the ite r a tions in the r un) :



## ANC

r = 

## ∑ 8 

# ( A C
j r 

# ) (Eq. 17)

j =

1



### where: ANC

r 

### = A nnual national cost at discount rate r

Appendix C, Cost Model Methodology C-23 Arsenic in Drinking Water Rule EA

## A ppendi x D. What-If C o st Sen s itiv ity A n aly s is

Cha p te r 6 of this r e por t disc usse s the unc e r ta inty a ssoc i a t e d with the Na tiona l c o st e s tima te

. L acking information on ex actly which sy stems will need to undertake activities to achieve

c o mplia nc e

, or wha t por tion of those sy ste m s would r e quir e tr e a tme nt, the r e will a l wa y s be some uncertainty associated with the actual costs likely to be incurred. The Ag ency conducted a Monte

Ca r l o simula tion to pr ovide a be st e s tima te of pr oba ble c o sts a nd a se nse of the r e la tive pr e c i sion

of

the e s tima te

. None of tha t a n a l y s is a ddr e sse s pote n tia l bia s in Ag e n c y e s tima te s.

A num ber of com m e nt ers assert ed t h at t h ere were fact ors i n t h e Ag ency anal y s i s t h at coul d
sig n if ic a n tly bia s its e s tima te

. The Ag e n c y disa g r e e s with the issue s r a ise d f o r

the r e a s ons detailed in the response to comment document. This Appendix will not attempt to address all of

those concerns. Rather, it describes a SafewaterXL simulation conducted to assess the
sensitivity of the National cost estimate to chang e s in factors involving professional judg ment and where there is uncertainty with respect to the status quo of the water supply industry

. The

fact ors consi d ered rel a t e t o uni t t r eat m e nt cost s and t h e com p l i a nce forecast (deci s i on t r ee).
Modeling was not conducted relating to water sy stem entry point config urations since the
Ag ency and com m e nt ers are i n ag reem ent t h at t h e ent r y poi nt i s t h e appropri a t e poi nt for
consideration of compliance costs and commenters have demonstrated that chang e s in such

a ssumptions ha ve minima l impa c t on na tiona l e s tima te s. L i ke wise , f a c t or s, whic h c ould bia s the
Ag e n c y ’ s c o st e s tima te s downwa r d, a r e not e v a l ua te d. 1



### . These factors are not evaluated to g i ve the clearest picture of the absolute mag n itude of the potential for underestimation. The data
discussed in this section are from a sing le Monte Carlo run of the Safewater XL model.

**Un i**  **t treatm**  **en t costs-**  The response to comment document contains a thoroug h critique of

c o mme nte r unit c o st e s tima te s. The r e a r e f our a r e a s , howe v e r , whe r e a n e c dota l e v ide n c e

sug g e sts costs bey ond those evaluated by the Ag ency could be ex perienced by individual water

sy stems in their compliance efforts. I n an effort to provide some contex t on the sig n ificance of

the s e c onc e r ns, modif i c a tions we r e ma de to the Ag e n c y ’ s be st e s tima te e qua tions to inc o r por a t e

t h ese fact ors. The fol l o wi ng chang e s were i n corporat ed i n t o t h i s anal y s i s :

**Accessory costs-** Some c o mme nte r s a sse r t e d tha t the c o sts f o r

insta lling c l e a r we lls or stor a g e to achieve flow equaliz ation after treatment, repiping around new treatment devices, and additional
pumping needed after pressure breaks for treatment would be incurred by water sy stems, aside

f r o m the piping a nd pumping c o sts c onside r e d by the Ag e n c y

. The s e c o mme nte r s e s tima te d tha t such costs could add up to 76 percent to the capital costs of compliance.

Technolog ies costed by the Ag ency do include ancillary piping costs. F u rther, technolog ies,
which break pressure, like coag ulation, included re-pumping costs. W h at neither the commenters,
nor the Ag ency have information on, however, is the ex tent to which additional storag e mig ht be

1 A recently com p leted A g ency report (A bt, 2000) s u g g e s t s that m a ny w a ter s y s t em s achiev e com p liance

w ith som e rules w ithout m a j o r treatm e nt reconstruction. In som e cases, as m a ny as a third of all sy stem s w e re able

to achiev e com p liance w ithout m a j o r reconstruction. L e ss capital intensiv e options than w e re costed in the

A g ency ’s decis i on trees could include drilling a new well, reconf ig uring intak e s to blend to the M C L lev e l, or
closing one, or m o re, w e lls and purchasing f r om a larg er sy stem can appreciably reduce costs.

Appendix D

, What-If Cos t Sens itivity Analys is D

- 1 A r s e nic in D r inking Water Rule EA

### required post treatment by water sy stems undertaking construction as part of their compliance

effort. This impact was evaluated by increasing treatment capital costs by 76 percent for those

sy stems that did not presently have disinfection (per EPA, 1999b). The Ag ency considered it
hig h ly improbable that a sy stem which presently conducted disinfection would not have adequate

storag e or mix ing z one capacity

**Land costs-** Some water sy stems undoubtedly will need to relocate entry points or acquire land

f

o r

the building of ne w tr e a tme nt f a c ilitie s. Comme nte r s a g r e e with the Ag e n c y tha t the r e is no
source of information for preparing a sound estimate of this impact. The issue is most likely to

a r ise with c u r r e ntly untr e a t e d e n tr y points. One c o mme nte r e s tima te d tha t la nd a c quisition c ould
add five percent to compliance capital costs for g r ound water sy stems. W h ile the Ag ency
be lie ve s la nd a c quisition will not be a c o mmon oc c u rr e nc e

, the wha t

- i f a n a l y s is inc l ude d a f

i ve percent increase in capital costs for land acquisition by g r ound water sy stems.

**P erm**  **i tti**  **n g**  **an d**  **p i**  **l o**  **t testi n**  **g-** The Ag ency has taken various approaches to the consideration of

pe r mitting a nd pilot te sting r e quir e me nts in pa st c o st a n a l y s e s

. While suc h c o sts a r e not e x pe c t e d

t o be appreci abl e for m o st wat e r sy st em s, i t i s pl ausi bl e t h at t h ey coul d cause eng i neeri n g cost s t o

ex ceed t h e fi ft y percent of di rect cost s current l y cost ed. For t h e purposes of t h e what -i f anal y s i s

, t h e Ag ency i s i n cl udi ng t h ree percent i n creases t o di rect capi t a l cost s for each fact or per t h e recommendations of the Technolog y Desig n Panel (EPA, 1997).

**Com p**  **l i**  **a n**  **ce f o**  **recast/ d**  **eci si**  **on tree-**  I n developing its compliance decision trees, the Ag ency

c onside r s wa te r qua lity f

a c t or s, wa te r a v a ila bility , a nd c o st. I t is pr e s ume d tha t a wa te r sy ste m will adopt the lowest cost technolog y it can feasibly use. Admittedly

, sy stems sometimes select

more ex pensive technolog ies, but do so to accomplish multiple treatment objectives. L a cking
comprehensive information on co-occurrence, the Ag ency is unable to consider the benefits or

cost s of such act i ons. R e g a rdl e ss, t h ey are not cost s at t r i but abl e t o arseni c com p l i a nce.

The Ag ency made numerous modifications to the proposal decision tree in response to public

comment. The use of ion ex chang e , for instance, was g r eatly reduced in response to residuals

manag e ment concerns. To assess the impact of the decision tree upon National cost estimates,
the what-if analy s is eliminated ion ex chang e (a relatively inex pensive technolog y ) and g r eatly

inc r e a s e d the pr oje c t e d use of c o a g ula tion a nd mic r o f iltr a tion ( t he most e x pe nsive option f o r

many strata). Tables D-1 throug h D-8 present the decision trees used in the analy s is and can be

com p ared t o t h e pri m a ry anal y s i s deci si on t r ees i n Appendi x A.

**Results-** Table D-9 depicts the results of the model run in comparison to those g e nerated by the

best estimate. I t is interesting to note that, at the MCL option of 10, the 95 percent confidence

interval on the best estimate is $215 million dollars. The W h at-I f estimate is less than ten

pe r c e n t g r e a t e r tha n the Ag e n c y ’ s or ig ina l e s tima te

. At the MCL option of f

i ve , howe v e r , the

wha t

- i f a ssumptions g e ne r a te a twe n ty

- f i ve pe r c e n t inc r e a s e in the Na tiona l c o st e s tima te

. The s e
results are consistent with those observed in the AW W A RF Cost I m plications Report

(AW W A RF , 2000) wherein lower options were much more volatile in the face of vary ing
assumptions. W h ile the Ag ency remains unpersuaded by many of the commenters arg u ments, this analy s is does support their concern relating to uncertainty at options beneath the selected

MCL

.

Appendix D

, What-If Cos t Sens itivity Analys is D

- 2 A r s e nic in D r inking Water Rule EAExhibitD-1ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving100 PeoplePercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%No.TreatmentTechnologyTrain1ModifyLimeSofteningandpre-oxidation1.01.01.02ModifyCoagulation/Filtration and pre-oxidation1.01.01.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.912.40.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation60.357.372.29Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation20.519.123.710Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.00.012POUActivated Alumina and pre-oxidation2.24.60.013POUReverse Osmosisand pre-oxidation2.24.62.1SumofProbabilities:100.00100.00100.00ExhibitD-2ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 101-500 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.912.50.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation60.457.266.19Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation20.519.122.710Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.01.83.111Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation0.00.03.112POUActivated Alumina and pre-oxidation1.12.70.013POUReverse Osmosisand pre-oxidation1.12.71.0SumofProbabilities:100.00100.00100.00ExhibitD-3ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 501-1,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation0.00.00.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation0.00.00.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.912.50.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation27.027.232.09Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation2.21.82.110Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation27.027.231.011Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation27.027.231.012POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitD-4ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 1,001-3,300 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation2.02.02.02ModifyCoagulation/Filtration and pre-oxidation2.02.02.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation5.44.55.26Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation5.44.55.27Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation12.912.50.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation18.314.517.59Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspentmedia)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment(pH6)/corrosion controlandnon-hazardouslandfill(forspentmedia)and pre-oxidation27.030.034.111Activated Alumina(15,400BV)withpHadjustment(pH6)/corrosion controlandnon-hazardouslandfill(forspentmedia)and pre-oxidation27.030.034.112POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitD-5ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 3,301-10,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation3.03.03.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation8.77.28.36Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.21.82.17Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.012.50.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation26.022.626.99Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation28.124.427.911Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation28.124.427.912POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitD-6ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 10,001-50,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation63.063.063.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.04.10.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation4.03.33.89Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation11.59.811.811Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation11.59.811.412POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitD-7ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 50,001-100,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation63.063.063.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.04.10.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation2.52.12.49Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation12.210.412.511Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation12.210.412.112POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00ExhibitD-8ProbabilityDecisionTree:“What-If” SensitivityAnalysisGround Water Systems Serving 100,001-1,000,000 PeopleNo.TreatmentTechnologyTrainPercentofTreatmentRequiredtoAchieve MCL<50%50-90%>90%1ModifyLimeSofteningandpre-oxidation4.04.04.02ModifyCoagulation/Filtration and pre-oxidation4.04.04.03AnionExchange (<20 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.04AnionExchange (20-50 mg/LSO4)andPOTWwaste disposaland pre-oxidation0.00.00.05Coagulation Assisted Microfiltrationand mechanicaldewatering/non-hazardouslandfillwastedisposaland pre-oxidation63.063.063.06Coagulation Assisted Microfiltrationand non-mechanicaldewatering/non-hazardouslandfillwaste disposalandpre-oxidation2.02.02.07Oxidation Filtration (Greensand)and POTWforbackwashstreamand pre-oxidation0.04.10.08Activated Alumina(pH7 -pH8)andnon-hazardouslandfill(forspentmedia)andpre-oxidation1.41.21.49Activated Alumina(pH8 -pH8.3)and non-hazardouslandfill(forspent media)and pre-oxidation0.00.00.010Activated Alumina(23,100BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation12.810.912.811Activated Alumina(15,400BV)withpHadjustment (pH6)/corrosion controlandnon-hazardouslandfill(forspent media)and pre-oxidation12.810.912.812POUActivated Alumina and pre-oxidation0.00.00.013POUReverse Osmosisand pre-oxidation0.00.00.0SumofProbabilities:100.00100.00100.00

### Exhibit D-9

What

- I f A n aly s is R esult s

MC L Op tio n B e s t E s tima te Wh a t -If E s tima te

5 $411 M illion $515 M illion

10 $177 M illion $192 M illion

Appendix D

, What-If Cos t Sens itivity Analys is D

- 11 Ar s e nic in D r inking Water Rule EA

## A ppendi x E: Benefi ts and Costs by Sy stem Si z e Categor y

The drinking water supply industry is subject to considerable economies of scale with respect to
the costs of treatment technolog ies. Per capita treatment costs steeply increase in inverse
proportion to sy stem siz e . This is illustrated earlier in this report by Ex hibit 6-17 wherein a
hundred-fold increase in household costs over the rang e of public water supplies can be observed

at t h e chosen MC L

. Because t h ere i s such a l a rg e i n crease i n rel a t i v e cost s, benefi t

- cost rat i o s also show appreciable variation with sy stem siz e

. I n response to comments received on the
proposal, the Ag ency is providing a subcateg oriz ation of the benefits and costs associated with
the various reg u latory alternatives by sy stem siz e

.

C o st val u es for st rat a speci fi c cost s were t a ken from t h e Nat i onal cost m odel i n g effort and refl ect use of a three percent interest rate for annualiz ing capital costs. B e nefits were calculated as a
product of the mean risk reductions (see Ex hibit 5-4(c) and calculated as described in Appendix

B ), populations served by impacted sites (shown in Ex hibit E-1 and calculated per cost
methodolog y described in Appendix C), and costs per case avoided (as described in Chapter 8
and Appendix B )

. F o r the latter element, $6.1 million was assumed per cancer fatality and
$607,000 for non-fatal cancers. Ex hibit E-1 depicts the benefits by sy stem siz e categ ory and

Ex hibit E-2 display s benefit cost ratios.



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Appendix E, Benefits and Cos t s by Sys t em Siz e Categor y E -1 Ar s e nic in D r inking Water Rule EA

### Ex **h i**  **b**

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Appendix E, Benefits and Cos t s by Sys t em Siz e Categor y E -2 Ar s e nic in D r inking Water Rule EA