: . United States Office of Water EPA 815-R-OO-026
Environmental Protection (4607) December 2000
Agency -.- Washington, DC 20460 www.epa.gov/safewater
^EPA ARSENIC IN DRINKING WATER RULE
ECONOMIC ANALYSIS
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EPA815-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, MD20814
Gerald D. Stedge, Ph.D.
Principal Investigator
December 2000
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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 anMCL 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
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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
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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 OtherBenefits 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
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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
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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 (|ig/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
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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 |ig/L and MCL
of 10 |ig/L 6-5
Exhibit 6-2b
System Compliance Technology Costs Assuming Influent Concentration of 50 |ig/L and MCL
of 10 |ig/L 6-9
Exhibit 6-3
Unit Resources Required for Monitoring, Implementation, and Administration 6-14
Exhibit 6-4a
vui
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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 |ig/L by System Service Type
(3% Discount Rate) 6-30
Exhibit 6-13
Total Annual NTNC Treatment Costs at MCL 5 |ig/L by System Service Type
(3% Discount Rate) 6-31
Exhibit 6-14
Total Annual NTNC Treatment Costs at MCL 10 |ig/L by System Service Type
(3% Discount Rate) 6-32
Exhibit 6-15
Total Annual NTNC Treatment Costs at MCL 20 |ig/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 (|ig/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 |ig/L 6-36
Exhibit 6-19
rx
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Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 5 |ig/L 6-36
Exhibit 6-20
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 10 |ig/L 6-37
Exhibit 6-21
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 20 |ig/L 6-37
Exhibit 6-22
National Compliance Costs Uncertainty Analysis
Frequency Distribution (MCL 10 |ig/L) 6-39
Exhibit 6-23
National Compliance Costs Uncertainty Analysis
Cumulative Distribution (MCL 10 |ig/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 |ig/L) 7-9
Exhibit 8-1
Profile of the Universe of Small Water Systems
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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 |ig/L) 8-7
Exhibit 8-3
Number of CWSs Expected to Undertake or Modify Treatment Practice
MCL 10 |ig/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 |ig/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
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Chapter 1 : Executive Summary
1.1 Regulatory Background
An enforceable standard of 50 |ig/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 |ig/L to 10
(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 |ig/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
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years in Taiwan has provided standardized mortality ratios (SMRs) for 23 cancerous and non-
cancerous 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 |ig/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 |ig/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 |ig/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
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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 jig/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 |ig/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
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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
(ug/L)
3
5
10
20
Total
Annual Cost
(7%)
$792.1
$471 .7
$205.6
$76.5
Annual Bladder
Cancer Health
Benefits1'2
$58.2 -$156.4
$52.0 -$11 3.3
$38.0 - $63.0
$20.1 -$21.5
Annual Lung
Cancer Health
Benefits1'2
$155.6 -$334.5
$139.1 -$242.3
$101 .6 -$134.7
$46.1 -$53.8
Total Annual
Health
Benefits1'2
$21 3.8 -$490.9
$191.1 -$355.6
$139.6 -$197.7
$66.2 - $75.33
Potential Non-Quantifiable
Health Benefits
• 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
1 May 1999 dollars.
2 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c).
3 For 20 pg/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 pg/L using the risk estimates adjusted for arsenic in cooking water and food.
For the revised MCL of 10 |ig/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 |ig/L, the estimated national cost of
compliance is $180.4 million at a discount rate of three percent, and $205.6 million at a discount rate of
seven percent.
Chapter 1, Executive Summary
1-4
Arsenic in Drinking Water Rule EA
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Exhibit 1-2
Total National Cost of Compliance ($ millions)
Discount Rate
cws
3% 7%
NTNC
3% 7%
TOTAL
3% 7%
MCL = 3 H.H/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$665.9 $756.5
$2.2 $3.0
$1.4 $1.6
$669.4 $761.0
$27.2 $29.6
$1.0 $1.4
$0.1 $0.2
$28.3 $31.1
$693.1 $786.0
$3.2 $4.4
$1.5 $1.7
$697.8 $792.1
MCL=ing/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$394.4 $448.5
$2.0 $2.8
$1.1 $1.3
$397.5 $452.5
$16.3 $17.6
$1.0 $1.3
$0.1 $0.2
$17.3 $19.1
$410.6 $466.1
$2.9 $4.1
$1.2 $1.4
$414.8 $471.7
MCL = 10 jig/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$169.6 $193.0
$1.8 $2.5
$0.9 $1.0
$172.3 $196.6
$7.0 $7.6
$0.9 $1.3
$0.1 $0.2
$8.1 $9.1
$176.7 $200.6
$2.7 $3.8
$1.0 $1.2
$180.4 $205.6
HCL=20ng/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$60.7 $69.0
$1.7 $2.4
$0.7 $0.8
$63.2 $72.3
$2.6 $2.8
$0.9 $1.3
$0.1 $0.2
$3.6 $4.2
$63.3 $71.8
$2.6 $3.7
$0.9 $1.0
$66.8 $76.5
Chapter 1, Executive Summary
1-5
Arsenic in Drinking Water Rule EA
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The net benefits and benefit-cost ratios of each regulatory option are provided in Exhibit 1-3. At the
revised MCL of 10 |ig/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 (ug/L)
3
5
10
20
3% Discount Rate
T3
1
1
T3
1
0)
Q.
Q.
3
Net Benefits
Benefit/Cost Ratio
Net Benefits
Benefit/Cost Ratio
$ (484.0)
0.3
$ (206.8)
0.7
$ (223.7)
0.5
$ (59.2)
0.9
$ (40.8)
0.8
$ 17.3
1.1
$ (0.6)
1.0
$ 8.5
1.1
7% Discount Rate
T3
O
_Q
1
T3
1
8.
Q.
3
Net Benefits
Benefit/Cost Ratio
Net Benefits
Benefit/Cost Ratio
$ (578.3)
0.3
$ (301.1)
0.6
$ (280.6)
0.4
$ (116.1)
0.8
$ (66.0)
0.7
$ (7.9)
1.0
$ (10.3)
0.9
$ (1.2)
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
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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 health-
related 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-of-
use 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.)
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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 |ig/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 |ig/L to 10 |ig/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).
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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 lexicological 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 |ig/L and 0.018 |ig/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.
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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.
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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 |ig/m3. 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 |ig/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 ng/day. An adult drinking 2 L/day of water containing 10 |ig/L of
arsenic would obtain 20 ng/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
|ig/L of arsenic would obtain almost 80 percent of the daily inorganic arsenic from food.
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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 |ig/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 |ig/day. Commenters recommended an MCL of 100 jig/L based on no
observed adverse health effects. EPA noted long-term chronic effects at 300 to 2,750 |ig/L, but no
chronic effects at 120 |ig/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 |ig/L. In 1992, the Clean Water Act criterion was recalculated based on an updated risk
assessment to yield 0.018 ng/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 jig/L based on an NAS conclusion that 50 jig/L balanced toxicity and possible
essentiality. EPA also requested comment on alternate MCLGs of 100 jig/L based on non-
carcinogenic effects and 0 |ig/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 |ig/L standard, the calculated U.S. lifetime risk ranged from 1 x 10"3 to 3 x 10"3.
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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 (in) levels below 200 to 250 jig 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.
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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 |ig/L and 0.018 |ig/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 |ig/L MCL is not adequately protective of human health and therefore
requires downward revision as promptly as possible.2
'The Arsenic Research Plan is published at http://www.epa.gov/ORDAVebPubs/final/arsenic.pdf.
2The NRC report is available at http://www.nap.edu/readingroom/enter2.cgi70309063337.html.
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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(l)).
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)(l)(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)(l)(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
3Mansfield (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
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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 safely. 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.
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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 |ig/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).
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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 jig/kg/day), the calculated
DWEL would be 0.3 |ig/kg/day times 70 kg divided by 2 L/day, or 10 |ig/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 |ig/L. It should be noted that the lexicological 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)).
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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 (l)(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 jig/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 |ig/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 jig/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.
Chapter3, Consideration of Regulatory Alternatives 3-3 Arsenic in Drinking Water Rule EA
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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 jig/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 jig/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 jig/L.
3.2.3 Monitoring
The current monitoring requirements for arsenic (40 CFR 141.23(1)) 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 (lOCs) regulated under the Phase D/V regulations. The revised rule would make the
following changes to the monitoring requirements for arsenic:
Chapter3, Consideration of Regulatory Alternatives 3-4 Arsenic in Drinking Water Rule EA
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• 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,
'Oxidation/filtration is BAT only when the Fe/As ratio is > 20:1.
Chapter3, Consideration of Regulatory Alternatives 3-5 Arsenic in Drinking Water Rule EA
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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 jig/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.
Chapter3, Consideration of Regulatory Alternatives 3-6 Arsenic in Drinking Water Rule EA
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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 non-
community 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
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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 privately-
owned 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. Eighty-
nine 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.
'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
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Exhibit 4-1
Total Number of Systems by Size, Type, and Ownership
SOURCE
<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
TOTAL
CWS
Ground Water
Public
Private
Total
Surface Water
Public
Private
Total
Total
1,335
12,942
14,277
394
698
1,092
15,369
4,678
10,380
15,058
1,117
886
2,003
17,061
2,868
1,821
4,689
917
303
1,220
5,909
4,167
1,547
5,714
2,012
408
2,420
8,134
1,993
466
2,459
1,656
188
1,844
4,303
1,011
205
1,216
1,436
171
1,607
2,823
105
26
131
260
40
300
431
50
11
61
217
44
261
322
16,207
28,303
44,510
8,009
3,053
1 1 ,062
54,352
NTOCWS
Ground Water
Public
Private
Total
Surface Water
Public
Private
Total
Total
1,725
7,965
9,690
58
213
271
9,961
3,108
3,930
7,038
63
232
295
7,333
1,163
815
1,978
19
87
106
2,084
337
355
692
24
56
80
772
23
39
62
6
17
23
85
9
5
14
3
1
4
18
0
0
0
1
0
1
1
0
0
0
1
0
1
1
6,365
13,109
19,474
175
606
781
20,255
Source: Safe Drinking Water Information System (SDWIS), December 1998 freeze.
Chapter 4, Baseline Analysis
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Arsenic in Drinking Water Rule EA
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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
< 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
Total
Community
Ground Water
859,777
3,741,017
3,457,163
10,631,422
14,095,015
25,004,779
8,609,455
14,575,556
2,855,494
83,829,678
Surface Water
61,450
570,448
921,449
4,797,855
10,995,980
36,819,575
20,500,370
65,375,183
28,658,586
168,700,896
Non-Transient
Non-Community
_
_
-
-
-
_
_
_
_
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), day care 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
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Arsenic in Drinking Water Rule EA
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Exhibit 4-3
Characteristics of NTNC Systems Affected by the Revised Rule
Service Area Type
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
TOTAL
SYSTEM CHARACTERISTICS
Number of
Systems
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
20.255
Average
Population
Served Per
System
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
Design Flow
(mgd)
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
Average Daily
Flow (mgd)
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
Source: EPA, 1999. Geometries and Characteristics of Public Water Systems, updated with the
December 1998 SDWIS freeze.
Chapter 4, Baseline Analysis
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Arsenic in Drinking Water Rule EA
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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
Percent! le
Mean
5th
50th (median)
95th
1
1
1
2
1
1
1
3
2
1
1
3
2
1
1
5
2
1
2
5
4
1
3
12
6
1
4
22
9
1
5
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
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Exhibit 4-5
Water Consumption per Residential
Connection
Population
< 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
_ . Mean Water
System
T Consumption
ype (kgal/yr)
Public
Private
Public
Private
Public
Private
Public
Private
Public
Private
Public
Private
Public
Private
Public
Private
81
92
93
110
97
88
82
102
87
124
108
110
122
96
127
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
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Exhibit 4-6
Design Capacity of CWS Plants
by Source, Ownership, and System Size
(Thousands of Gallons)
Primary Source/
Ownership Type
Ground Water
Public
Private
Purchased-Public
Purchased-Private
Surface Water
Public
Private
Purchased-Public
Purchased-Private
GW under
influence
Public
Private
Purchased-Public
Purchased-Private
Service Population Category
<25
6.27
4.84
6.50
-
0.89
1.30
1.14
3.19
0.04
1.12
-
-
-
-
-
25-100
21.86
29.46
21.34
5.71
4.99
20.32
25.79
18.13
5.71
4.99
22.16
33.29
21.53
-
2.54
101-500
86.86
123.67
77.30
27.37
24.78
92.60
130.90
75.69
29.01
24.65
87.20
1 1 1 .32
81.77
30.21
29.83
501-1,000
251.0
305.0
232.1
81.4
79.5
239.3
318.2
214.2
81.8
73.6
247.5
291.2
227.4
97.1
94.3
1,001-
3,300
619.5
740.3
560.6
223.0
200.6
617.9
807.8
527.3
241.1
213.8
631.6
760.0
618.5
209.3
-
3,301-
10,000
1,864
2,152
1,683
801
824
1,818
2,218
1,582
854
719
1,779
2,077
1,802
461
905
10,001-
50,000
6,673
7,365
6,347
3,380
2,748
6,682
7,887
6,165
3,698
2,933
7,499
8,992
-
2,319
-
50,001-
100,000
20,785
22,614
18,234
19,796
8,690
19,707
22,337
15,869
13,206
12,788
18,482
20,195
-
-
-
100,001-
1,000,000
67,379
67,994
75,629
26,765
-
69,224
77,298
61,381
43,650
29,270
-
-
-
-
-
>1, 000,000
392,939
401,175
-
-
-
554,759
584,889
296,609
-
-
-
-
-
-
-
Source: EPA, Geometries and Characteristics of Public Water Systems, Table B1.5.3.
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Exhibit 4-7
Daily Production of CWS Plants
by Source, Ownership, and System Size
(Thousands of Gallons)
Primary Source/
Ownership Type
Ground water
Public
Private
Purchased-Public
Purchased-Private
Surface Water
Public
Private
Purchased-Public
Purchased-Private
GW under
influence
Public
Private
Purchased-Public
Purchased-Private
Service Population Category
<25
1.35
0.96
1.39
-
0.85
0.39
0.28
0.95
0.04
1.06
-
-
-
-
-
25-100
5.33
6.72
4.80
5.11
4.54
6.91
7.51
6.15
5.11
4.54
5.41
7.70
4.85
-
2.36
101-500
24.40
33.20
20.30
23.50
21.60
33.70
41.60
28.60
24.90
21.50
24.50
29.50
21.30
25.90
25.9
501-1,000
78.50
90.50
69.30
68.20
67.30
90.70
106.20
87.30
68.50
62.40
77.30
86.00
67.70
80.90
79.4
1,001-
3,300
212
243
18
182
166
244
284
230
197
176
217
250
207
171
-
3,301-
10,000
715
796
635
634
656
753
823
748
675
575
679
765
686
370
719
10,001-
50,000
2,914
3,129
2,802
2,585
2,119
2,932
3,133
3,225
2,821
2,258
3,313
3,907
-
1,789
-
50,001-
100,000
10,187
10,900
9,121
14,496
6,502
9,069
9,387
8,907
9,766
9,472
8,951
9,611
-
-
-
100,001-
1,000,000
37,224
37,095
44,760
19,455
-
33,667
34,749
38,094
31,351
21,215
-
-
-
-
-
>1, 000,000
259,751
267,256
-
-
-
295,680
293,439
206,950
-
-
-
-
-
-
-
Source: EPA, Geometries and Characteristics of Public Water Systems, Table B1.5.1.
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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
Source/ Type
of Treatments
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
100,001-
1,000,000
> 1,000,000
Ground Water Systems
Ion Exchange
Reverse
Osmosis
Coagulation/
Flocc.
Lime/Soda Ash
Softening
Disinfection
0.7%
0.0%
1 .5%
2.1%
52.8%
1 .6%
1 .2%
5.4%
3.7%
77.9%
3.8%
0.0%
4.2%
4.1%
84.0%
1 .9%
0.9%
3.4%
5.2%
79.7%
4.6%
1 .2%
8.1%
7.0%
86.8%
3.3%
0.7%
15.1%
12.2%
96.5%
1 .2%
1 .2%
24.2%
17.4%
86.3%
0.0%
0.0%
25.2%
32.4%
96.4%
-
-
-
-
-
Surface Water Systems
Ion Exchange
Reverse
Osmosis
Coagulation/
Flocc.
Lime/Soda Ash
Softening
Disinfection
0.0%
0.0%
27.5%
3.9%
92.8%
0.0%
0.0%
52.6%
8.1%
94.1%
0.0%
0.0%
70.2%
20.5%
100.0%
0.0%
0.0%
78.5%
17.5%
100.0%
0.0%
0.0%
95.4%
10.8%
96.0%
0.0%
0.0%
94.5%
6.9%
98.0%
0.0%
0.0%
93.7%
5.7%
100.0%
0.0%
0.0%
99.5%
5.1%
100.0%
-
-
-
-
Source: EPA, Cosf and Technology Document for the Arsenic Rule, Tables 6-1 and 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 |ig/L to > 50 |ig/L. These projections were based on the
following national surveys:
Chapter 4, Baseline Analysis
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• 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 |ig/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 often different
concentration levels, ranging from 2 |ig/L to 50 |ig/L. Less than one percent of ground water and
surface water systems have a concentration level of arsenic greater than 50 jig/L. In contrast, 27
percent of ground water systems and 10 percent of surface water systems have an arsenic
concentration greater than 2 |ig/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 (H9/L)
Source
GW
SW
% of systems greater than (|ig/L)
235
27.3 19.9 12.1
9.8 5.6 3.0
10 15 20 25
5.3 3.1 2.0 1.4
0.80 0.46 0.32 0.24
30
1.1
0.19
40
0.64
0.13
50
0.43
0.10
Source: EPA, 2000. Arsenic Occurrence in Public Drinking Water Supplies.
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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 (ug/L) in the
range of:
>3to5
>5to10
>10to20
>20
Ground Water CWS
Number of Systems
% of systems
3,384
7.8%
2,949
6.8%
1,432
3.3%
870
2.0%
Surface Water CWS
Number of Systems
% of systems
270
2.5%
239
2.2%
51
0.5%
34
0.3%
Ground Water NTNCWS
Number of Systems
% of systems
1,677
8.6%
1,995
10.3%
635
3.3%
405
2.1%
Surface Water NTNCWS
Number of Systems
% of systems
20
2.5%
17
2.2%
4
0.5%
2
0.3%
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Chapter 5: Benefits Analysis
5.1 Nature of Regulatory Benefits
The benefits associated with reductions of arsenic in drinking water arise from a reduction in
adverse human health effects. To a lesser degree benefits may also accrue from an avoidance of
expensive consumer behaviors aimed at avoiding exposure, such as the purchase of bottled
water.
The value to consumers of a reduction in the risk of adverse health effects includes the following
components:
• The avoidance of medical costs and productivity losses associated with illness;
The avoidance of the pain and suffering associated with illness;
• The losses associated with risk and uncertainty of morbidity, also called the "risk
premium"; and
• The reduction in risk of premature mortality.
This conceptual valuation framework goes beyond 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 risk premium represents the damages associated with risk and uncertainty, captured in the
expression of consumers' willingness to pay for the reduction in risk of illness (Freeman, 1979).
This chapter first presents information on the multiple adverse health effects associated with
arsenic, followed by a quantitative risk analysis of a two arsenic-related endpoints, bladder
cancer and lung cancer. Because a large number of potential health effects cannot be quantified,
it is likely that the estimated benefits associated with avoidance of bladder and lung cancer
underestimate the total benefits of a reduction of arsenic in drinking water.
5.2 Health Effects
5.2.1 Overview
Exposure to arsenic has many potential health effects, which have been described in two recent
publications: Arsenic in Drinking Water by the National Research Council (NRC, 1999), and the
Agency for Toxic Substances and Disease Registry's Draft Toxicological Profile for Arsenic
(ATSDR, 1998, updated September 2000). These two sources provide descriptions of health
effects that are summarized in this section, along with additional information provided from the
recent literature.
Ingestion of inorganic arsenic can result in both cancer and non-cancer health effects (NRC,
1999). Exposure may also occur via other routes of exposure including inhalation and dermal
exposure. There is a large human effects database available for inorganic arsenic. However, the
effects of organic forms of arsenic are not as well characterized as those of inorganic arsenic.
Limited information suggests that the major organoarsenicals found in fish and shellfish
(arsenobetaine and arsenocholine) have little or no toxicity.
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It appears that some of the metabolites of inorganic arsenic may possess some toxicity. The final
rule addresses both organic and inorganic 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 exposure. Therefore, the
relationship between exposure and response is quite complex. This section describes potential
health effects but does not conclude that there are specific effects that occur due to the current
levels of arsenic in our country's drinking water.
5.2.2 Carcinogenic Effects
Arsenic's carcinogenic role was noted over 100 years ago (NCI, 1999) and has been studied since
that time. 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." (EPA, IRIS Web site, extracted 8/99).
The International Agency for Research on Cancer (IARC) concluded that inhalation of inorganic
arsenic caused skin and lung cancer in humans. The 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" (NRC,
1999). Ten epidemiological studies, covering eight organ systems, present quantitative data
useful for risk assessment (NRC, 1999, Table 4-1). The organ systems 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. Considering all cancers in aggregate, the NRC states in their Risk Characterization
section that "considering the data on bladder and lung cancer in both sexes noted in the studies in
chapter 4, 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 |ig/L; NRC, 1999).
New data provide additional health effects information on both carcinogenic and non-
carcinogenic effects of arsenic. A recently study by Tsai et al. (1999) of a population that has
been studied over many years in Taiwan has provided statistically significant standardized
mortality ratios (SMRs) for 23 cancerous and non-cancerous causes of death in women and 27
causes of death in men. 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 |ig/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."
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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. The SMRs calculated by
Tsai et al. (1999) used the one cause of death noted on the death certificates. Many chronic
diseases, including some cancers, do not result in mortality. Consequently, the impact indicated
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. For example, arsenic levels in the U.S. are not nearly 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.
5.2.3 Non-carcinogenic Effects
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.
Effects on specific organ systems reported in humans exposed to arsenic are listed below in
Exhibit 5-1 (NRC, 1999). Exhibit 5-1 provides descriptive information on the specific diseases
and/or symptoms associated with categories of diseases.
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Exhibit 5-1
Adverse Noncarcinogenic Health Effects Reported in Humans in NRC (1999) as
Potentially Associated with Arsenic, by Organ System Affected*
Cutaneous effects
1. hyperpigmentation
2. hyperkeratoses
3. melanosis
Gastrointestinal and hepatic
effects
4. noncirrhotic portal hypertension
5. gastrointestinal hemorrhage secondary to esophageal varices
6. hepatic enlargement
7. splenic enlargement
8. periportal fibrosis of the liver
9. obliterative intimal hypertrophy of intrahepatic venules resulting in obstruction of
portal venous flow, increased splenic pressures, and hypersplenism, and cirrhosis of
the liver
10. diarrhea
11. cramping
Cardiovascular and peripheral
vascular effects
12. peripheral vascular disease (blackfoot disease)
13. gangrene of the feet
14. coldness and numbness in the extremities
15. intermittent claudication
16. ulceration
17. spontaneous amputation
18. Raynaud's syndrome
19. acrocyanosis
20. ischemic heart disease
Cardiovascular and peripheral
vascular effects (in children)
21. arterial spasms in fingers and toes
22. esenteric artery thrombosis
23. cerebrovascular disease
24. extensive coronary occlusions
25. cerebrovascular occlusions
26. ischemia of the tongue
27. Raynaud's syndrome
28. gangrene in extremities
Hematological effects
29. anemia - normocytic, megoblastic
30. leukopenia - neutropenia, lymphopenia, eosinophilia
31. thrombocytopenia
32. reticulocytosis
33. erythroid hyperplasia
Pulmonary effects
34. chronic cough
35. restrictive and obstructive lung disease
36. emphysema
Immunological effects
37. impaired immune response (more specific effects observed in human cell studies and
animal studies—see source)
Neurological effects
38. peripheral neuropathy
Endocrine effects
39. diabetes mellitus
Reproductive and
developmental effects
40. spontaneous abortion
41. perinatal death
42. stillbirth
43. low birth weight
44. birth defects including coarctation of the aorta and others
45. neural tube defects
46. ophthalmic abnormalities
47. numerous skeletal abnormalities
48. urogenital abnormalities
49. growth retardation
Source: NRC (1999).
*Notes in parenthesis indicate where health effects were observed in animal studies rather than human studies. NRC
reports results of numerous animal reproductive and developmental studies and notes that there are "very few"
human studies.
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5.2.4 Susceptible Subgroups
This section discusses the nature of special susceptibilities and identifies population subgroups
that may be at higher risk than the general population when exposed to arsenic.
Definition
A susceptible subgroup exhibits a response that is different or enhanced when compared to the
responses of most people exposed to the same level of arsenic (ATSDR, 1998). Many diseases
affect certain subgroups of the population disproportionately. The subgroups may be defined by
age, gender, race, ethnicity, socioeconomic status, pre-existing medical conditions, behavioral or
physiological differences, or other characteristics. For example, there are pre-existing medical
conditions that will increase susceptibility to most toxins, such as a pre-existing disease in the
toxin's target organ. Very few diseases affect all population groups (ages, sexes, races) equally.
For purposes of evaluating potential benefits to different segments of the population, it is useful
to evaluate whether there are susceptible subpopulations that require consideration. The benefit
of reducing their exposure may be considerably higher than the benefit associated with reducing
exposure among the general population (on a per capita basis).
Special susceptibilities may be indicated by known differences in biological processes that are
essential to detoxification of a toxin. In addition to identifying susceptible subgroups based on
biological processes, susceptible subgroups are often identified by observing higher-than-average
rates of the disease of interest. Increases in the rates of reported diseases may be due to a variety
of factors. Some of these indicate an increased susceptibility; others are matters of personal
choice and may not be considered relevant in a benefits analysis. One way to approach this issue
is to evaluate increased susceptibility when it is based on an increased risk of disease due to
factors reasonably beyond the control of the subpopulation. Factors that are usually beyond the
control of the individual that may cause increased susceptibility include:
• Constitutional limitations (e.g., illnesses, genetic abnormalities, birth defects such
as enzyme deficiencies);
• Concurrent synergistic exposures that cannot reasonably be controlled (e.g., at
home or in the workplace); and
• Normal constitutional differences (i.e., differences based on sex, age, race,
ethnicity, etc.).
Other factors that are not usually considered beyond the individual's control include personal
choices, such as smoking, drinking, and drug use. Choice of place of residence or work may or
may not be treated as a relevant factor. Ultimately, the types of factors that should be included in
identifying susceptible subgroups is a matter of public policy.
No studies were located by ATSDR (1998) that focused exclusively 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 weight) in children, genetic predispositions, and dietary insufficiency (ATSDR, 1998), as
well as pre-existing health conditions.
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Children
One often-identified potential susceptible subgroup is children. Due to their increased fluid and
food intake in relation to their body weight (NAS, 1995), their dose (milligrams per kilogram of
body weight per day - mg/kg/day) of arsenic will be, on average, greater than that of adults. For
example, an intake of 1.2 liters per day in a 70 kg adult yields an overall water intake of 0.017
liters per kg of body weight. An infant who consumes 1 liter per day and weighs 10 kg is
consuming 0.1 liter per kg of body weight, 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 correspondingly
higher level, on a daily basis. Foy et al. noted that in studies of some chronic exposures, children
appear to be more severely affected, probably due to a higher exposure per body weight (1992
citation, reported in ATSDR, 1998). In certain circumstances, the increased daily dose in
children can be effectively considered for non-carcinogenic effects because toxicity is evaluated
in terms of exposures that can range from relatively short-term to long-term exposure. However,
carcinogenic effects (i.e., bladder cancer) are evaluated based on a lifetime of exposure, which
takes into consideration the elevated dose that occurs in children. Because the health effects
measured in this benefits assessment are bladder and lung cancer, a sensitivity analysis to
consider higher doses of arsenic during childhood was not necessary. However, the numerous
potential non-carcinogenic effects listed in Exhibit 5-1 may be of greater concern for children
than adults. Avoidance of these effects constitutes an unquantified benefit of the rule.
Genetic Predispositions and Dietary Insufficiency
Methylation of arsenic plays a role in the detoxification of inorganic arsenic, and individuals who
are deficient in essential enzymes for this process, or who have a dietary deficiency of methyl
donors (choline or methionine), may be at greater risk following inorganic arsenic exposure
(Buchet and Lauwerys, 1987; Vahter and Marafante, 1987; Brouwer et al., 1992 cited in ATSDR,
1998). However, liver disease may not increase risk at low levels of arsenic exposure since there
is a greater production of DMA in these patients. (Buchet et al., 1982; Geubel et al., 1988 cited in
ATSDR, 1998). Therefore, these factors are not expected to increase risk levels for a significant
portion of the U.S. population.
Individuals with Pre-existing Organ Susceptibilities
Individuals may have increased susceptibilities based on specific organ-related factors. Those
with pre-existing diseases (e.g., kidney disease), as well as those with congenital defects (a single
kidney) will be at greater risk from a toxin that either causes additional damage to that organ, or
that relies on that organ for detoxification.
In the case of arsenic, both the kidneys and liver are used to detoxify and remove the
contaminant. Both single high doses and long-term low doses may cause an accumulation of
arsenic in the liver and kidneys, which can impair function. In addition, these organs may be
directly damaged by arsenic exposure. A review of Exhibit 5-1 indicates that other organ
systems are targets of arsenic toxicity, including the cardiovascular system (heart, veins, arteries),
hematopoietic system, endocrine system, cutaneous system, pulmonary system, gastrointestinal
system, immune system, and peripheral nervous system. In individuals with pre-existing damage
Chapter 5, Benefits Analysis 5-6 Arsenic in Drinking Water Rule EA
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to these systems or congenital defects in the systems, the likelihood of risk is greater. Due to the
higher incidence of most types of disease among the elderly, they are more likely to have pre-
existing conditions in these organ systems.
Individuals Exposed via Non-water Sources
Although arsenic is ubiquitous at low levels, it is not generally found at levels of concern in food
or air, in the absence of elevated local sources. Where background levels are high, however,
(e.g., elevated levels in water) it is reasonable to consider the contribution to total exposure that
may occur from soil, food, and other local sources. When anthropogenic sources are known to
generate elevated arsenic levels in water (e.g., a local smelter), it is more likely that other media
may be contaminated as well. The total exposure from all sources is a critical component of
evaluating potential health risks and the benefits of avoiding contaminated drinking water in
these cases. A reduction in arsenic in drinking water will reduce the overall exposure to
individuals in living in contaminated areas (e.g., around certain Superfund sites) or workers
exposed to arsenic on the job. Total exposure from all sources is of particular concern for non-
cancer risks, because background levels from non-drinking water sources will determine whether
the total exposure leads to an exceedence of a threshold for effects.
5.3 Quantitative Benefits of Avoiding Cancer
5.3.1 Risk Assessment for Cancer Resulting from Arsenic Exposure
As noted, arsenic ingestion has been linked to a multitude of health effects, both cancerous and
non-cancerous. These health effects include cancer of the bladder, lungs, skin, kidney, nasal
passages, liver, and prostate. Arsenic ingestion has also been associated with cardiovascular,
pulmonary, immunological, neurological, endocrine, and reproductive and developmental effects.
A complete list of the arsenic-related health effects reported in humans has been shown in
Exhibit 5-1. Of all the health effects noted above, current research on arsenic exposure has only
been able to define scientifically defensible risks for bladder and lung cancer. That is, EPA has
adequate data to perform a risk assessment on bladder and lung cancer. Because there is
currently a lack of strong evidence on the risks of other arsenic-related health effects, the Agency
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 analysis of scientific data to determine the likelihood, nature,
and magnitude of harm to public health associated with particular agents, and involves three
main analytical components: hazard identification (dose-response assessment), exposure
assessment, and risk characterization.
Exhibit 5-2 illustrates the steps in a traditional risk assessment process for characterizing the
potential human cancer associated with contaminants in drinking water.
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Exhibit 5-2
Components of the Bladder Cancer Risk Assessment
HAZARD
IDENTIFICATION
Toxicity
(dose-response)
EXPOSURE
ASSESSMENT
RISK
CHARACTERIZATION
Exposure
Health Effects
Population Size^nd Distribution
Ingestion/Dose Human Intake Factors
Concentration of Contaminant in
Finished Drinking Water Supply and
Available for Human Consumption
Concentration of Contaminant in Source
Water
5.3.2 Community Water Systems
The following sections summarize how risk reductions were calculated for populations in
community water systems exposed to arsenic concentrations. The approach for this analysis
included five components. First, relative exposure factor distributions were developed, which
incorporate data from the recent EPA water consumption study with age, sex, and weight data.
Second, arsenic occurrence distributions were calculated for the population exposed to arsenic
levels above 3 |ig/L. Third, risk distributions for bladder and lung cancer were chosen for the
analysis from Morales et al. (2000). Fourth, EPA developed estimates of the projected bladder
and lung cancer risks faced by exposed populations using Monte-Carlo simulations, bringing
together the relative exposure factor, occurrence, and risk distributions. These simulations
resulted in upper bound estimates of the actual risks faced by U.S. populations exposed to arsenic
concentrations at or above 3 |ig/L in their drinking water. Finally, EPA made adjustments to the
lower bound risk estimates to reflect exposure to arsenic in cooking water and in food in Taiwan.
A more detailed description of the risk methodology is provided in Appendix B.
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Water Consumption
EPA recently updated its estimates of per capita daily average water consumption (EPA, 1999).
The estimates used data from the combined 1994, 1995, and 1996 Continuing Survey of Food
Intakes by Individuals (CSFII), conducted by the U.S. Department of Agriculture (USDA). The
CSFn is a complex, multistage area probability sample of the entire U.S. and is conducted to
survey the food and beverage intake of the U.S. Per capita water consumption estimates are
reported by source. Sources include community tap water, bottled water, and water from other
sources, including water from household wells and rain cisterns, and household and public
springs. For each source, the mean and percentiles of the distribution of average daily per capita
consumption are reported. The estimates are based on an average of two days of reported
consumption by survey respondents. The estimated mean daily average per capita consumption
of community tap water by individuals in the U.S. population is 1 liter/person/day. For total
water, which includes bottled water, the estimated mean daily average per capita consumption 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 estimated 90th percentile of the empirical distribution of daily average per capita
consumption of community tap water for the U. S. population is 2.1 liters/person/day; the
corresponding number for daily average per capita consumption of total water is 2.3
liters/person/day. In other words, current consumption data indicate that 90 percent of the U.S.
population consumes approximately 2 liters/person/day, or less.
Water consumption estimates for selected subpopulations in the U.S. are described in the CSFn,
including per capita water consumption by source for gender, region, age categories, economic
status, race, and residential status and separately for pregnant women, lactating women, and
women in childbearing years. The water consumption estimates by age and sex were used in the
computation of the relative exposure factors discussed below.
Relative Exposure Factors
Lifetime male and female relative exposure factors (REFs) for each of the broad age categories
used in the water consumption study were calculated, where the life-long REFs indicate the
sensitivity of exposure of an individual relative to the sensitivity of exposure of an "average"
person weighing 70 kilograms and consuming 2 liters of water per day, which is a "high end"
water consumption estimate according to the EPA water consumption study referred to above
(EPA, 1999). In these calculations, EPA combined the water consumption data with data on
population weight from the 1994 Statistical Abstract of the U.S. Distributions for both
community tap water and total water consumption were used because the community tap water
estimates may underestimate actual tap water consumption. The weight data included a mean and
a distribution of weight for male and females on a year-to-year basis. The means and standard
deviations of the life-long REFs derived from this analysis are shown in Exhibit 5-3.
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Exhibit 5-3
Life-Long Relative Exposure Factors
Male
Female
Community Water Consumption Data
Mean = 0.60
s.cf. = 0.61
Mean = 0.64
s.cf. = 0.6
Total Water Consumption Data
Mean = 0.73
s.cf. = 0.62
Mean = 0.79
s.cf. = 0.61
Arsenic Occurrence
EPA recently updated its estimates of arsenic occurrence and calculated separate occurrence
distributions for arsenic found in ground water and surface water systems. These occurrence
distributions were calculated for systems with arsenic concentrations of 3 ug/L or above.
Arsenic occurrence estimates are described in more detail in Chapter 4.
Risk Distributions
In its 1999 report, Arsenic in Drinking Water, the NRC analyzed bladder cancer risks using data
from Taiwan. In addition, the NRC examined evidence from human epidemiological studies in
Chile and Argentina, and concluded that risks of bladder and lung cancer had comparable risks to
those "in Taiwan at comparable levels of exposure" (NRC, 1999). The NRC also examined the
implications of applying different statistical analyses to the newly available Taiwanese data for
the purpose of characterizing bladder cancer risk. While the NRC's work did not constitute a
formal risk analysis, they did examine many statistical issues (e.g., measurement errors, age-
specific probabilities, body weight, water consumption rate, comparison populations, mortality
rates, choice of model) and provided a starting point for additional EPA analyses. The report
noted that "poor nutrition, low selenium concentrations in Taiwan, genetic and cultural
characteristics, and arsenic intake from food" were not accounted for in their analysis (NRC,
1999, p. 295). In the June 22, 2000, proposed rulemaking, EPA calculated bladder cancer risks
and benefits using the bladder cancer risk analysis from the 1999 NRC report. We also estimated
lung cancer benefits in a "What If analysis based on the statement in the 1999 NRC report that
"some studies have shown that excess lung cancer deaths attributed to arsenic are 2-5 fold greater
than the excess bladder cancer deaths" (NRC, 1999).
In July 2000, a peer-reviewed article by Morales et al. (2000) was published, which presented
additional analyses of bladder cancer risks as well as estimates of lung and liver cancer risks for
the same Taiwanese population analyzed in the NRC report. EPA summarized and analyzed the
new information from the Morales et al. (2000) article in a Notice of Data Availability published
on October 20, 2000 (65 FR 63027). Although the data used were the same as used by the NRC
to analyze 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). After
consultation with the primary authors (Morales and Ryan), EPA chose Model 1 with no
comparison population for further analysis.
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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 exposure is assumed to be zero. Most of the
models with comparison populations resulted in dose-response curves that were supralinear
(higher than a linear dose-response) at low doses. The curves were "forced down" at zero dose
because the comparison population consists of a large number of people with low risk and
assumed zero exposure. 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. First, there
is no basis in the data on arsenic's carcinogenic mode of action to support a supralinear curve as
being biologically plausible. To the contrary, the conclusion of the NRC Panel (NRC, 1999) was
that the mode of action data led one to expect 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 exposure of
the comparison population is zero, and that the study and comparison populations are the same in
all important ways except for arsenic exposure. Both of these assumptions may be incorrect:
NRC (1999) notes that "the Taiwanese-wide data do not clearly represent a population with zero
exposure to arsenic in drinking water"; and Morales et al. (2000) agree 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 large amount of data in the comparison
populations, the model results are relatively sensitive to assumptions about this group. For 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 fits the
data best, based on the Akaike Information Criterion (AIC), a standard criterion of model fit,
applied to the Poisson models. EPA did not consider the multi-stage Weibull model for
additional analysis, because of its greater sensitivity to the omission of individual villages
(Morales et al., 2000) and to the grouping of responses by village (NRC, 1999), as occurs in the
Taiwanese data. In Model 1, the dose effect is assumed to follow a linear function, and the age
effect is assumed to follow a quadratic function. The Agency decided that the more exhaustive
statistical analysis of the data provided by Morales et al. (2000), as analyzed by EPA, would be
the basis for the new risk calculations for the final rule (with further consideration of additional
risk analyses) and other pertinent information.
Estimated Risk Reductions
Estimated risk reductions for bladder and lung cancer at various MCL levels were developed
using Monte-Carlo simulations. Monte-Carlo analysis is a technique for analyzing problems
where there are a large number of combinations of input values, which makes it impossible to
calculate every possible result. A random number generator is used to select input values from
pre-defined distributions. For each set of random numbers, a single scenario's result is
calculated. As the simulation runs, the model is recalculated for each new scenario that
continues until a stopping criterion is reached.
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These simulations combined the distributions of relative exposure factors (REFs), occurrence at
or above 3 |ig/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 exposed to arsenic concentrations at or above 3 |ig/L in their drinking water.
Lower Bound Analyses
Two adjustments were made to the risk distributions resulting from the simulations described
above, reflecting uncertainty about the actual arsenic exposure in the Taiwan study area. First,
the Agency made an adjustment to the lower bound risk estimates to take into consideration the
effect of exposure to arsenic through water used in preparing food in Taiwan. The Taiwanese
staple foods were dried sweet potatoes and rice (Wu et al., 1989). Both the 1988 EPA Special
Report on Ingested Inorganic Arsenic and the 1999 NRC report assumed that an average
Taiwanese male weighed 55 kg and drank 3.5 liters of water daily, and that an average Taiwanese
female weighed 50 kg and drank 2 liters of water daily. Using these assumptions, along with an
assumption that Taiwanese men and women ate one cup of dry rice and two pounds of sweet
potatoes a day, the Agency re-estimated risks for bladder and lung cancer, using one additional
liter of water consumption for food preparation (i.e., the water absorbed by hydration 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 high arsenic concentration in the food consumed in Taiwan as compared to the U.S.
The food consumed daily in Taiwan contains about 50 jig, versus about 10 jig in the U.S. (NRC,
1999, pp. 50-51). Thus, the total consumption of inorganic arsenic (from food preparation and
drinking water) is considered, per kilogram of body weight, 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 |ig/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 |ig/kg/day basis.
Other factors contributing to lower bound uncertainty include the possibility of a sub-linear dose-
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 range is
predicted, although linearity cannot be ruled out" (NRC, 1999). The recent Utah study (Lewis et
al., 1999) provides some evidence that the shape of the dose-response curve may well be sub-
linear at low doses. Because sufficient mode of action data were not available, an adjustment
was not made to the risk estimates to reflect the possibility of a sub-linear dose-response curve.
Additional factors contributing to uncertainty include the use of village well data rather than
individual exposure data, deficiencies in the Taiwanese diet relative to the U.S. diet (selenium,
choline, etc.), and the baseline health status in the Taiwanese study area relative to U.S.
populations. The Agency 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.
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Estimated risk levels for bladder and lung cancer combined at various MCL levels are shown in
Exhibit 5-4 (a-c). The risk estimates without adjustments for exposure uncertainty through
cooking water and food are shown Exhibit 5-4 (a). These estimates incorporate occurrence data,
water consumption data, and male and female risk estimates. Lower bounds show estimates
using community water consumption data; upper bounds show estimates using total water
consumption data. Exhibit 5-4 (b) shows estimated risk levels for bladder and lung cancer
combined at various MCL levels with adjustments for exposure uncertainty through 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 village well data as opposed to individual exposure
data. Exhibit 5-4 (c) is a combination of Exhibit 5-4 (a) and Exhibit 5-4 (b), with the lower
bounds taken from Exhibit 5-4 (b), and the upper bounds taken from Exhibit 5-4 (a). Thus
Exhibit 5-4 (c) reflects the range of estimates before and after the exposure uncertainty
adjustments for cooking water and for food, along with the incorporation of water consumption
data, occurrence data, and cancer risk estimates. These estimates were used to estimate the range
of potential cases avoided at the various MCL levels.
The upper bound risk estimates in Exhibits 5-4 (a-c) reflect the following:
• The total water consumption estimates from the EPA water consumption study;
The occurrence distributions of arsenic in U.S. ground and surface water systems;
• Male and female risk estimates from Morales et al. (2000);
Not adjusting for arsenic exposure from cooking water in Taiwan; and
• Not adjusting for arsenic exposure from food in Taiwan.
The lower bound risk estimates in Exhibits 5-4 (a-c) reflect the following:
• The community water system estimates of water consumption from the EPA water
consumption study;
• The occurrence distributions of arsenic in U.S. ground and surface water systems;
• Male risk estimates from Morales et al. (2000);
• Adjusting for arsenic exposure from cooking water in Taiwan; and
• Adjusting for arsenic exposure from food in Taiwan.
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Exhibit 5-4 (a)
Cancer Risks for U.S. Populations
Exposed at or Above MCL Options, After Treatment1'2
(Without Adjustment for Arsenic in Food and Cooking Water)
MCL
(ug/L)
3
5
10
20
Mean Exposed
Population Risk
.93-1.25x10-4
1.63-2.02X10'4
2.41 -2.99x10'4
3.07- 3.85 x10'4
90th Percentile Exposed
Population Risk
1.95-2.42x10-4
3.47 -3.9x10'4
5.23-6.09x10'4
6.58- 8.37 x10'4
1Actual risks could be lower, given the various uncertainties discussed, or
higher, as these estimates assume that the probability of illness from arsenic
exposure in the U.S. is equal to the probability of death from arsenic exposure
among the arsenic study group.
2The estimated risks are male and female risks combined.
Exhibit 5-4 (b)
Cancer Risks for U.S. Populations
Exposed at or Above MCL Options, After Treatment1'2
(With Adjustment for Arsenic Exposure in Food and Cooking Water)
MCL
(ug/L)
3
5
10
20
Mean Exposed
Population Risk
.11 -.13x10'4
.27-.32x10-4
.63- .76x10'4
1.1 - 1.35x10'4
90th Percentile Exposed
Population Risk
.22-.26x10-4
.55-.62x10-4
1.32- 1.54x10'4
2.47-2.89x10'4
1Actual risks could be lower, given the various uncertainties discussed, or
higher, as these estimates assume that the probability of illness from arsenic
exposure in the U.S. is equal to the probability of death from arsenic exposure
among the arsenic study group.
2The estimated risks are for males.
Exhibit 5-4 (c)
Cancer Risks for U.S. Populations
Exposed at or Above MCL Options, After Treatment1
(Lower Bound With Food and Cooking Water Adjustment,
Upper Bound Without Food and Cooking Water Adjustment)
MCL
(ug/L)
3
5
10
20
Mean Exposed
Population Risk
.11 -1.25x10-4
.27-2.02x10'4
.63-2.99x10'4
1.1 -3.85x10-4
90th Percentile Exposed
Population Risk
.22-2.42x10-4
.55-3.9x10'4
1.32-6.09x10'4
2.47- 8.37 x10'4
1Actual risks could be lower, given the various uncertainties discussed, or
higher, as these estimates assume that the probability of illness from arsenic
exposure in the U.S. is equal to the probability of death from arsenic exposure
among the arsenic study group.
Chapter 5, Benefits Analysis
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5.3.3 Non-Transient Non-Community Water Systems
Determination of System and Individual Exposure Factors
In the past, the Agency has directly used SDWIS population estimates for assessing the risks
posed to users of NTNC water systems. In other words, it was assumed that the same person
received the exposure on a year-round basis. Under this approach it was generally assumed that
all NTNC users were exposed for 270 days out of the year and obtained 50 percent of their daily
consumption from these systems. As a comparison, TNC users are assumed to use the system for
only ten days per year.
With the recent completion of Geometries and Characteristics of Public Water Systems (EPA,
1999a), however, the Agency has developed a more comprehensive understanding of NTNC
water systems. These systems provide water in due course as part of operating another line of
business. Many systems are classified as NTNC, rather than TNC, water systems solely because
they employ sufficient workers to trigger the "25 persons served for over six months out of the
year" requirement. Client utilization of these systems is actually much less and more similar to
exposure in TNC water systems. For instance, it is fairly implausible that highway rest areas
along interstate highways serve the same population on a consistent basis (with the exception of
long distance truckers). Nevertheless, there are highway rest areas in both NTNC and TNC
system inventories. The Geometries and Characteristics of Public Water Systems report suggests
that population figures reported in SDWIS that have been used for past risk assessments
generally appear to reflect the number of workers in the establishment coupled with peak day
customer utilization.
Under these conditions, use of the SDWIS figures for population greatly overestimates the actual
individual exposure risk for most of the exposed population and also severely underestimates the
number of people exposed to NTNC water.1 Adequately characterizing individual and
population risks necessitates some adjustment of the SDWIS population figures. For chronic
contaminants, such as arsenic, health data reflect the consequences of a lifetime of exposure.
Consequently, risk assessment requires the estimation of the portion of total lifetime drinking
water consumption that any one individual would receive from a particular type of water system.
In turn, one needs to estimate the appropriate portions for daily, days per year, and year per
lifetime consumption. These estimates need to be prepared for both the workers at the facility
and the "customers" of the facility.
This adjustment was accomplished through a comprehensive review of government and trade
association statistics on entity utilization by Standard Industry Classification (SIC) code.
'For example, airports constitute only about a hundred of the NTNC water systems. Washington's Reagan
National and Dulles, Dallas/Fort Worth, Seattle/Tacoma, and Pittsburgh airports are the five largest of the airports.
SDWIS reports that these five airports serve about 300,000 people. In actuality, the Bureau of Transportation
Statistics (BTS) suggest that they serve about eleven million passengers per year. Examination of this information
and other BTS statistics suggests that these airports serve closer to seven million unique individuals over the course
of a year and that exposure occurs on an average of ten times per year per individual customer, not 270 times.
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These figures, coupled with SDWIS information relating to the portion of a particular industry
served by non-community water systems, made possible the development of two estimates
needed for the risk assessment: customer cycles per year and worker per population served per
day. These numbers are required to distinguish the more frequent and longer duration exposure
of workers from that of system customers.2 A more detailed characterization of the derivation of
these numbers is contained in the docket. Exhibit 5-5 provides the factors used in the NTNC risk
assessment to account for the intermittent nature of exposure.
Exhibit 5-5
Exposure Factors Used in the NTNC Risk Assessment
NTNCWS
Water
wholesalers
Nursing homes
Churches
Golf/country clubs
Food retailers
Non-food retailers
Restaurants
# cycles
peryr
1.00
1.00
1.00
4.50
2.00
4.50
2.00
worker/
pop/day
0.000
0.230
0.010
0.110
0.070
0.090
0.070
worker
fraction
daily
-
0.50
0.50
0.50
0.50
0.50
0.50
worker
days/yr
-
250
250
250
250
250
250
worker
exposure
years
-
40
40
40
40
40
40
customer
fraction
daily
0.25
1.00
0.50
0.50
0.25
0.25
0.25
days of
use/yr
270
365
52
52
185
52
185
customer
exposure
years
70
10
70
70
70
70
70
2For example, travel industry statistics provide information on total numbers of hotel stays, vacancy rates,
traveler age ranges, and average duration of stay. These figures can be combined with the SDWIS peak day
population estimates to allocate daily population among workers, customers, and vacancies. The combination of
these factors provides an estimate of the number of independent customer cycles experienced in a year.
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Exhibit 5-5
Exposure Factors Used in the NTNC Risk Assessment (continued)
NTNCWS
Hotels/motels
Prisons/jails
Service stations
Agricultural
products/services
Daycare centers
Schools
State parks
Medical facilities
Campgrounds/RV
Federal parks
Highway rest areas
Misc. recreation
service
Forest Service
Interstate carriers
Amusement parks
Summer camps
Airports
Military bases
Non-water utilities
Office parks
Manufacturing: Food
Manufacturing:
Non-food
Landfills
Fire departments
Construction
Mining
Migrant labor camps
#
cycles
peryr
86.00
1.33
7.00
7.00
1.00
1.00
26.00
16.40
22.50
26.00
50.70
26.00
26.00
93.00
90.00
8.50
36.50
worker/
pop/day
0.270
0.100
0.060
0.125
0.145
0.073
0.016
0.022
0.041
0.016
0.010
0.016
0.016
0.304
0.180
0.100
0.308
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
worker
fraction
daily
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.50
1.00
0.50
0.50
1.00
0.50
0.50
0.50
0.50
0.50
0.50
1.00
1.00
1.00
1.00
1.00
worker
days/yr
250
250
250
250
250
200
250
250
180
250
250
250
250
250
250
180
250
250
250
250
250
250
250
250
250
250
250
worker
exposure
years
40
40
40
40
10
40
40
40
40
40
40
40
40
40
10
10
40
40
40
40
40
40
40
40
40
40
40
customer
fraction
daily
1.00
1.00
0.25
0.25
0.50
0.50
0.50
1.00
1.00
0.50
0.50
1.00
1.00
0.50
0.50
1.00
0.25
days of
use/yr
3.4
270
52
52
250
200
14
6.7
5
14
7.2
14
14
2
1
7
10
customer
exposure
years
40
3
54
50
5
12
70
10.3
50
70
70
70
50
70
70
10
70
Once the population adjustment factors were derived, it was possible to determine the actual
population served by NTNC water systems. Exhibit 5-6 provides a breakout of these figures by
type of establishment.
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Although not included in Exhibit 5-6, there are other equally important characteristics to note
about these systems. With notable exceptions (such as the airports in Washington, DC, and
Seattle), the systems generally serve a fairly small population on any given day. In fact, 99
percent of the systems serve fewer than 3,300 users on a daily basis. This means that water
production costs will be relatively high on a per gallon basis.
Exhibit 5-6
Composition of NTNCs
(Percentage of Total NTNCWS Population Served by Sector)
Schools
Manufacturing
Airports
Office Parks
9.7
2.7
26.1
0.6
Medical
Facilities
Restaurants
Non-food Retail
Hotels/Motels
8
0.9
1.6
9.2
Interstate Carriers
State Parks
Amusement Parks
Highway Rest Area
7.1
8.6
17.7
1.0
Campgrounds
Misc.
Recreation
Other
1.3
1.8
3.5
Risk Calculation
Calculations of individual combined risk for bladder and lung cancer were prepared for each
industrial sector. Even within a given sector, however, risk varies as a function of an
individual's relative water consumption, body weight, vulnerability to arsenic exposure, and the
water arsenic concentration. Computationally, risks were estimated by performing Monte-Carlo
modeling. The approach used was similar to the modeling technique applied in estimating the
community water system risk estimation, but with two notable exceptions. First, each realization
in a given sector was multiplied by the portion of lifetime exposure factor presented in Exhibit
5-6 to reflect the decreased consumption associated with the NTNC system. Second, relative
exposure factors were limited to age-specific ratings where appropriate.3 For example, in the
case of school children, water consumption rates and weights for 6- to 18-year-olds were used.
To illustrate the process, it was assumed that a child would attend only NTNCWS-served schools
for all twelve years, a somewhat improbable likelihood. Further, it was assumed that a child
would get half of his or her daily water consumption at school (for an average first grader this
would correspond to roughly nine ounces of water per school day). Finally, it was assumed that
the child would have perfect attendance and attend school for 200 days per year.
The distribution of overall population risks was determined as part of the same simulation by
developing sector weightings to reflect the total portion of the NTNCWS population served by
each sector. Population weighted proportional sampling of the individual sectors provided an
overall distribution of risk among those exposed at NTNC systems.
3For example, water consumption among school children was weighted to reflect consumption between
ages 6 and 18, while factory worker consumption was weighted over ages 20 to 64.
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Exhibit 5-7 presents a summary of the risk analyses for regulation of arsenic in NTNC water
systems. Exhibit 5-8 presents risk figures for three particular sets of individuals: children in
daycare centers and schools, and construction workers. Construction and other strenuous activity
workers comprise an extremely small portion of the population served by NTNC systems (less
than 0.1 percent), but face the highest relative risks of all NTNCWS users (90th percentile risks of
0.4 to 2.3 x 1CT4 lifetime risk).
Exhibit 5-7
Mean Cancer Risks (Bladder and Lung combined),
Exposed Population, and Annual Cancer Benefits in NTNCs
Arsenic
Level
(M9/L)
3
5
10
20
baseline
Mean Exposed Population
Risk(104)
lower
bound
0.0000657
0.000162
0.000374
0.00064
0.000853
upper
bound
0.000952
0.00157
0.00243
0.00322
0.00391
Total Bladder and Lung
Cancer Cases Avoided
per Year
lower
bound
0.6
0.53
0.36
0.16
0.65
upper
bound
2.25
1.78
1.13
0.53
2.98
Exhibit 5-8
Sensitive Group Evaluation of Lifetime Combined Cancer Risks
Group
Forest Service, Construction and Mining Workers
School Children
Day Care Children
Mean Risk
0.2- 1.2x10'4
0.2-1.4x10-5
1.1 -7.3x10-6
90th Percentile Risk
0.4-2.3x10'4
0.5-2.8x10-5
0.25- 1.5 x10'5
However, there is considerable uncertainty about these exposure numbers, as it is quite likely that
they overestimate consumption. It is not possible to determine from the analysis of NTNC
systems the extent to which there is overlap of individual exposure between the various sectors.
NTNC establishments generally constitute a small portion of their SIC sectors. In conjunction
with the observation that NTNC populations would only serve about 11 percent of the total
population if all sectors were mutually exclusive, it would seem reasonable to treat the SIC
groups independently. However, it is equally plausible that there are communities where one
individual might go from an NTNC day care center to a series of NTNC schools and then work in
an NTNC factory. Unfortunately, the Agency presently has no basis for quantitatively estimating
the extent to which this would occur.
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5.4 Risk Assessment Results and Benefit Estimates
5.4.1 Cases Avoided
The lower and upper bound risk estimates from Exhibit 5-4 (c) were applied to the exposed
population to generate cases avoided for CWS systems serving fewer than one million customers.
Because the actual arsenic occurrence was known for the very large systems (those serving over a
million customers), their system-specific arsenic occurrence distributions could be directly
computed. The system specific arsenic distributions allowed direct calculation of avoided cancer
cases. The process, described in detail in Appendix B, utilizes the same risk estimates from
Morales et al. (2000) that were used in deriving the number of cases avoided in smaller CWS
systems. Cases avoided for NTNC systems were also computed separately, utilizing factors
developed to account for the intermittent nature of the exposure.
An upper bound adjustment was made to the number of bladder cancer cases avoided to reflect a
possible lower mortality rate in Taiwan than was assumed in the risk assessment process
described earlier. We also made this adjustment in the June 22, 2000, proposal. In the Taiwan
study area, information on arsenic related bladder and lung cancer deaths was reported. In order
to use these data to determine the probability of contracting bladder and lung cancer as a result of
exposure to arsenic, a probability of mortality given 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 high 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
care is not of high quality by U.S. standards. In its estimate of bladder cancer risk, the Agency
assumed that within the Taiwanese study area, the probability of contracting bladder cancer was
relatively close to the probability of dying from bladder cancer (that is, that the bladder cancer
incidence rate was equal to the bladder cancer mortality rate).
We do not have data on the rates of survival for bladder cancer in the Taiwanese villages in the
study and at the time of data collection. We do know that the relative survival rates for bladder
cancer in developing countries overall ranged from 23.5 percent to 66.1 percent in 1982-1992
{Cancer Survival in Developing Countries, International Agency for Research on Cancer, World
Health Organization, Publication No. 145, 1998). We also have some information on annual
bladder cancer mortality and incidence for the general population of Taiwan in 1996. The age-
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, January 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 general population of Taiwan, at present, is 45 percent. Since survival rates
have most likely improved over the years since the original Taiwanese study, this number
represents a lower bound on the survival rate for the original area under study (that is, one would
not expect a higher rate of survival in that area at that time). This has implications for the
bladder cancer risk estimates from the Taiwan data. If there were any persons with bladder
cancer who recovered and died from some other cause, then our estimate underestimated risk;
that is, there were more cancer cases than cancer deaths. Based on the above discussion, we
think bladder cancer incidence could be no more than two times bladder cancer mortality; and
that an 80 percent mortality rate would be plausible.
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Thus, we have adjusted the upper bound of cases avoided, which is used in the benefits analysis,
to reflect a possible mortality rate for bladder cancer of 80 percent. Because lung cancer
mortality rates are quite high, about 88 percent in the U.S. (EPA, 1998b), the assumption was
made that all lung cancers in the Taiwan study area resulted in fatalities.
The number of bladder, lung, and combined bladder and lung cases avoided at each MCL are
shown in Exhibits 5-9 (a), 5-9 (b), and 5-9 (c). These cases avoided include both CWS and
NTNC cases. The number of bladder cancer cases avoided range from 28.6 to 76.8 at an MCL of
3 |ig/L, 25.6 to 55.7 at an MCL of 5 |ig/L, 18.7 to 31.0 at an MCL of 10 |ig/L, and 9.9 to 10.6 at
an MCL of 20 |ig/L. The number of lung cancer cases avoided range from 28.6 to 61.5 at an
MCL of 3 |ig/L, 25.6 to 44.5 at an MCL of 5 |ig/L, 18.7 to 24.8 at an MCL of 10 |ig/L, and 8.5 to
9.9 at an MCL of 20 |ig/L. The number of combined bladder and lung cancer cases avoided range
from 57.2 to 138.3 at an MCL of 3 |ig/L, 51.1 to 100.2 at an MCL of 5 |ig/L, 37.4 to 55.7 at an
MCL of 10 |ig/L, and 19.0 to 19.8 at an MCL of 20 |ig/L.
The cases avoided were divided into premature fatality and morbidity cases based on U.S.
mortality rates. In the U.S. approximately one out of four individuals who is diagnosed with
bladder cancer actually dies from bladder cancer. The mortality rate for the U.S. is taken from a
cost of illness study recently completed by EPA (EPA, 1998b). For those diagnosed with bladder
cancer at the average age of diagnosis (70 years), the probabilities of dying of that disease during
each year post-diagnosis were summed over a 20-year period to obtain the value of 26 percent.
Mortality rates for U.S. bladder cancer patients have decreased overall by 24 percent from 1973
to 1996. For lung cancer, mortality rates are much higher. The comparable mortality rate for
lung cancer in the U.S. is 88 percent.
Exhibit 5-9 (a)
Annual Bladder Cancer Cases Avoided
from Reducing Arsenic in CWSs and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced
Mortality Cases*
7.4-20.0
6.6-14.5
4.9-8.0
2.6-2.8
Reduced Morbidity
Cases*
21.2-56.9
18.9-41.2
13.8-22.7
7.3-7.8
Total Cancer Cases
Avoided*
28.6 -76.8
25.6-55.7
18.7-31.0
9.9-10.6
* The lower-end estimate of bladder cancer cases avoided is calculated using the lower-end risk estimate from
Exhibit 5-9(c) and assumes that the conditional probability of mortality among the Taiwanese study group was 100
percent. The upper-end estimate of bladder cancer cases avoided is calculated using the upper-end risk estimate
from Exhibit 5-9(c) and assumes that the conditional probability of mortality among the Taiwanese study group was
80 percent.
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Exhibit 5-9 (b)
Annual Lung Cancer Cases Avoided
from Reducing Arsenic in CWSs and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced
Mortality Cases*
25.2-54.1
22.5-39.2
16.4-21.8
7.4-8.7**
Reduced Morbidity
Cases*
3.4-7.4
3.1 -5.3
2.2-3.0
1.0-1.2**
Total Cancer Cases
Avoided*
28.6-61.5
25.6-44.5
18.7-24.8
8.5-9.9**
' The lower and upper-end estimates of lung cancer cases avoided are calculated using the risk estimates from
Exhibit 5-9 (c) and assume that the conditional probability of mortality among the Taiwanese study group was 100
percent.
**For 20 ug/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 is higher at 20 ug/L
using the estimates adjusted for uncertainty.
Exhibit 5-9 (c)
Annual Total Cancer Cases Avoided
from Reducing Arsenic in CWSs and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced
Mortality Cases*
32.6-74.1
29.1 -53.7
21.3-29.8
10.2-11.3**
Reduced Morbidity
Cases*
24.6-64.2
22.0-46.5
16.1 -25.9
8.5-8.8
Total Cancer Cases
Avoided*
57.2-138.3
51.1 -100.2
37.4 - 55.7
19.0 -19.8**
* The lower-end estimate of bladder cancer cases avoided and the lung cancer estimates assume that the
conditional probability of mortality among the Taiwanese study group was 100 percent. The upper-end estimate of
bladder cancer cases avoided is calculated using the assumption that the conditional probability of mortality among
the Taiwanese study group was 80 percent.
**For 20 ug/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 is higher at 20 ug/L
using the estimates adjusted for uncertainty.
5.4.2 Economic Measurements of the Value of Risk Reduction
The evaluation stage in the analysis of risk reductions involves estimating the value of reducing
the risks. The following sections describe the use of benefits valuation techniques to estimate the
value of the risk reductions attributable to the regulatory options for arsenic in drinking water.
First, 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 analysis of this Economic Analysis are assumed to begin to
accrue on the effective date of the rule and are based on a calculation referred to as the "value of
a statistical life" (VSL).
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Of the many VSL studies, the Agency recommends using estimates from 26 specific studies that
have been peer reviewed and extensively reviewed within the Agency.4 These estimates, which
are derived from wage-risk and contingent valuation studies, range from $0.7 million to $16.3
million and approximate a Wiebull distribution with a mean of $4.8 million (in 1990 dollars).
Most of these 26 studies examine willingness to pay in the context of voluntary acceptance of
higher risks of immediate accidental death in the workplace in exchange for higher wages. This
value is sensitive to differences in population characteristics and perception of risks being
valued. This value could also be updated to include changes in income from 1990 to 1999,
which reflects the difference between the study population and the affected population, and
would increase monetary benefits since income growth in that time period has been 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 guidance on economic
analyses (Bennett, 2000). In order to directly compare the estimated national costs of
compliance, the VSL used in this analysis was updated from the January 1997 value to $6.1
million in May 1999 dollars, using the Consumer Price Index (CPI-U) for all items.
Several factors may influence the estimate of economic benefits associated with avoided cancer
fatalities, including:
1. A possible "cancer premium" (i.e., the additional value or sum that people may be willing
to pay to avoid the experiences of dread, pain and suffering, and diminished quality of life
associated with cancer-related illness and ultimate fatality);
2. The willingness of people to pay more over time to avoid mortality risk as their income
rises;
3. A possible premium for accepting involuntary risks as opposed to voluntary assumed
risks;
4. The greater risk aversion of the general population compared to the workers in the wage-
risk valuation studies;
5. "Altruism" or the willingness of people to pay more to reduce risk in other sectors of the
population; and
6. A consideration of health status and life years remaining at the time of premature
mortality.
Use of certain of these factors may significantly increase the present value estimate. EPA
therefore believes that adjustments should be considered simultaneously. The Agency also
believes that there is currently neither a clear consensus among economists about how to
simultaneously analyze each of these adjustments, nor are there adequate empirical data to
support definitive quantitative estimates for all potentially significant adjustment factors. As a
result, the primary estimates of economic benefits presented in the analysis of this rule rely on the
unadjusted estimate.
4 U.S. Environmental Protection Agency, The Benefits and Costs of the Clean Air Act, 1970 to 1990,
October 1997, Appendix I; and U.S. Environmental Protection Agency, Guidelines for Preparing Economic
Analysis (Review Draft), June 1999, Chapter 7.
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To assess the impacts of these other factors, EPA presents a sensitivity analysis that examines the
impacts of changes in assumptions of the latency period and incorporation of income growth, etc.
This sensitivity analysis is given in Section 5.5.
To estimate the monetary value of reduced fatal risks (i.e., risks of premature death from cancer)
predicted under different regulatory options, VSL estimates are multiplied by the number of
premature fatalities avoided. VSL does not refer to the value of an identifiable life, but instead 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 exposed population. For example, if
100,000 people would each experience a reduction of 1/100,000 in their risk of premature death
as the result of a regulation, the regulation can be said to "save" one statistical life (i.e., 100,000
x 1/100,000). If 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 changes in risk; they are not
values for saving a particular individual's life.
Estimates of the willingness 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
available for bladder or lung cancer. However, willingness to pay (WTP) data to avoid chronic
bronchitis is available and has previously been employed by the Office of Ground Water and
Drinking Water (the microbial/disinfection by-product [MDBP] rulemaking) as a surrogate to
estimate the WTP to avoid non-fatal bladder cancer. A WTP central tendency estimate of
$607,162 (in May 1999 dollars) is used to monetize the benefits of avoiding non-fatal cancers
(this value was updated from the $536,000 value EPA updated to 1997 dollars from the Viscusi
etal. [1991] study).
To ground-truth the use of the chronic bronchitis WTP value as a proxy for WTP for the
avoidance of non-fatal cases of bladder cancer, EPA has also developed cost-of-illness estimates
for bladder cancer, as reported in Exhibit 5-10. These estimates of direct medical costs are
derived from a study conducted by Baker et al. (1989), which uses data from a sample of
Medicare records for 1974-1981. These data include the total charges for inpatient hospital stays,
skilled nursing facility stays, home health agency charges, physician services, and other
outpatient and medical services. EPA combined these data with estimates of survival rates and
treatment time periods to determine the average costs of initial treatment and maintenance care
for patients who do not die of the disease. This value of $178,405, at a three percent discount
rate, serves as a low-end estimate of the WTP to avoid bladder cancer and does not include the
value of avoided pain and suffering, lost productivity, or risk premium.
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Exhibit 5-10
Lifetime Avoided Medical Costs for Survivors
(preliminary estimates1)
Type of
Cancer
Bladder
Date Data
Collected
1974-1981
Number of Cases Studied
5% of 1 974
Medicare patients
(sample from national statistics)
Estimated
Mortality Rate
26%
(after 20 years)
Mean Value per
Non-fatal Case
(Discount Rate)1
$178,405(3%)
$147,775(7%)
(for typical individual
diagnosed at age 70)
Source: U.S. Environmental Protection Agency, Cosf of Illness Handbook (draft), September 1998.
1 May 1999 dollars.
5.4.3 Estimates of Cancer Health Benefits of Arsenic Reduction
Benefits estimates were calculated based on the number of bladder and cancer cases avoided, as
given in Exhibits 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
based on the VSL estimates discussed earlier, as recommended by current EPA guidance for
cost/benefit analysis (EPA, 2000c). The avoided non-fatal cases were valued based on the
willingness to pay estimates for the avoidance of chronic bronchitis.
The results of the benefits valuation are presented in Exhibit 5-11. Total annual health benefits
resulting from bladder cancer cases avoided range from $58.2 to $156.4 million at an MCL of
3 ug/L, $52.0 to $113.3 million at an MCL of 5 ug/L, $38.0 to $63.0 million at an MCL of 10
ug/L, and $20.1 to $21.5 million at an MCL of 20 ug/L. Total annual health benefits from
avoided cases of lung cancer range from $155.6 to $334.5 million at an MCL of 3 ug/L, $139.1
to $242.3 million at an MCL of 5 ug/L, $101.6 to $134.7 million at an MCL of 10 ug/L, and
$46.1 to $53.8 million at an MCL of 20 ug/L. In addition, other potential non-quantifiable health
benefits are summarized in Exhibit 5-11.
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Exhibit 5-11
Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and
Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs
Arsenic
Level
(H9/L)
3
5
10
20
Total Annual
Cost (7%)
$792.1
$471.7
$205.6
$76.5
Annual Bladder
Cancer Health
Benefits12
$58.2 -$156.4
$52.0 -$11 3.3
$38.0 - $63.0
$20.1 -$21.5
($ millions
Annual Lung
Cancer Health
Benefits12
$155.6 -$334.5
$139.1 -$242.3
$101 .6 -$134.7
$46.1 - $53.8
Total Annual
Health Benefits1 2
$21 3.8 -$490.9
$191.1 -$355.6
$139.6 -$197.7
$66.2 - $75.33
Potential Non-Quantifiable
Health Benefits
Skin Cancer
Kidney Cancer
Cancer of the Nasal
Passages
Liver Cancer
Prostate Cancer
Cardiovascular Effects
Immunological Effects
Neurological Effects
Endocrine Effects
Reproductive and
Developmental Effects
1 May 1999 dollars.
2 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c).
3 For 20 pg/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 pg/L using the estimates adjusted for uncertainty.
5.5 Latency and Other Adjustments: A Sensitivity Analysis
For the final rulemaking analysis, some commenters have argued that the Agency should
consider an assumed time lag or latency period in its benefits calculations. The term "latency"
can be used in different ways, depending on the context. For example, health scientists tend to
define latency as the period beginning with the initial exposure to the carcinogen and ending
when the cancer is initially manifested (or diagnosed), while others consider latency as the period
between manifestation of the cancer and death. Latency, in this case, refers to the difference
between the time of initial exposure to environmental carcinogens and the actual mortality. Use
of such an approach might reduce significantly the present value of health risk reduction benefits
estimates.
In the Arsenic Rule, the Agency included qualitative language on the latency issue, including
descriptions of other adjustments that may influence the estimate of economic benefits associated
with avoided cancer fatalities. The Agency also agreed to ask the Science Advisory Board (SAB)
to conduct a review of the benefits transfer issues and possible adjustment factors associated with
economic valuation of mortality risks. A summary of the SAB's recommendations is shown in
the following section.
5.5.1 SAB Recommendations
EPA brought this issue before the Environmental Economics Advisory Committee (EEAC) of
EPA's SAB in a meeting held on February 25, 2000, in Washington, DC. The SAB submitted a
final report on their findings and recommendations to EPA on July 27, 2000.
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The EEAC report made a number of recommendations on the adjustment factors and benefit-cost
analysis in general. A copy of the final SAB report has been placed in the record for this
rulemaking.
The SAB EEAC noted that benefit-cost analysis, as described in the Agency's Guidelines (for
economic analysis), is not the only analytical tool, nor is efficiency the only appropriate criterion
for social decision making, but notes that it is important to carry out such analyses in an unbiased
manner with as much precision as possible. In its report, the SAB recommended that the Agency
continue to use a wage-risk based VSL as its primary estimate; any appropriate adjustments that
are made for timing and income growth should be part of the Agency's main analysis, while any
other adjustments should be accounted for in sensitivity analyses to show how results would
change if the VSL were adjusted for some of the major differences in the characteristics of the
risk and of the affected populations.
Specifically, the SAB report recommended that (1) health benefits brought 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 theprimary analysis; (2)
adjustments to the VSL for a "cancer premium" should be made as part of a sensitivity analysis;
(3) adjustments to the VSL for voluntariness and controllability should be made as part of a
sensitivity analysis; (4) altruism should be addressed in a sensitivity analysis 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 analysis are restrictive; (5) estimates of VSLs accruing in future
years should be adjusted in theprimary analysis to reflect anticipated income growth, using a
range of income elasticities; (6) adjustments to the VSL for risk aversion should be made in a
sensitivity analysis; (7) it is theoretically appropriate to calculate WTP for individuals whose
ages 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 risks are reduced.
After considering the SAB's recommendations, EPA has developed a sensitivity analysis of the
latency structure and associated benefits for the Arsenic Rule, as described in the next section.
This analysis consists of health risk reduction benefits that reflect adjustments for discounting,
incorporation of a range of latency period assumptions, adjustments for growth in income, and
incorporation of other factors such as voluntariness and controllability. Although the SAB
recommended accounting for latency in a primary benefits analysis, the Agency believes that 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 analysis. Sensitivity analyses are generally reserved for examining
the effects of accounting for highly uncertain factors, such as the estimation of latency periods,
on health risk reduction benefits estimates.
Defining a latency period is highly uncertain because the length of the latency period is often
poorly understood by health scientists. In some cases, information on the progression of a cancer
is based on animal studies, and extrapolation to humans is complex and uncertain. Even when
human studies are available, the dose considered may differ significantly from the dose generally
associated with drinking water contaminants (e.g., involve a high level of exposure over a short
time period, rather than a long-term, low level of exposure).
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The magnitude of the dose may in turn affect the resulting latency period. Information on latency
may be unavailable in many cases, or, if available, may be highly uncertain and vary significantly
across individuals.
5.5.2 Analytical Approach
For the latency sensitivity analysis, the health benefits have been broken into separate treatments
of morbidity and mortality. The mortality component of the total benefits is examined in this
analysis because a cancer latency period (i.e., the time period between initial exposure to
environmental carcinogens and the actual fatality) impacts arsenic-related fatalities only. For
purposes of this analysis, the Agency examined the impacts of various latency period
assumptions, adjustments for income growth, and incorporation of other adjustments, such as
voluntariness and controllability, on bladder and lung cancer fatalities associated with arsenic in
drinking water.
Because the latency period for arsenic-related bladder and lung cancers is unknown, EPA has
assumed a range of latency periods from 5 to 20 years. While both lung and bladder cancer have
relatively long average latencies, the lower end of the latency period is substantially less. As can
be seen by inspection of the Surveillance, Epidemiology, and End Results (SEER) data of the
National Cancer Institute, significant incidence of both cancers occurs in individuals in the 15- to
19-year-old age groups. This strongly 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 stage of the
cancer process and that may advance the expression of cancers initiated by other causes
(sometimes referred to as "promoting out" the cancerous effect). Therapeutic treatment with the
drug cyclophosphamide, which causes cell toxicity, has been seen to induce bladder cancer in as
little as 7 to 15 years in affected patients. This was of course a high dose treatment, but the
example serves to illustrate the ability of an agent to advance the development of cancer.
For these reasons, we believe latency periods of 5, 10, and 20 years serve as reasonable
approximations, in the absence of definitive data on arsenic-induced cancers, of the latency
periods for the sensitivity analysis.
Exhibit 5-12 shows the sensitivity of the primary analysis VSL estimate ($6.1 million, 1999
dollars) to changes in latency period assumptions and also with the incorporation of income
growth and other adjustment factors. As is shown in Exhibit 5-12, the adjusted VSL is greater
than the primary VSL ($6.77 million versus $6.1 million) at an income elasticity of 1.0, with
adjustments for income growth only. The lowest adjusted VSL value ($3.44 million) is yielded
over a 20-year latency period that includes discounting and income growth only (income
elasticity = 0.22). Assuming a seven percent discount rate, the highest adjusted VSL is also
$6.77 million (adjusted for income growth only [income elasticity = 1.0]). The lowest adjusted
VSL is $1.61 million (discounted over 20 years).
The first row of both the three and seven percent discount rate panels in Exhibit 5-12 shows the
VSL used in the primary analysis. Because this value has not been adjusted for discounting over
an assumed and unknown latency period, this value does not deviate from the original $6.1
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million used in the primary benefits analysis. The second and third rows of both the three and
seven percent panels show the adjustments to the primary VSL to account for changes in WTP
for fatal risk reductions associated with real income growth from 1990 to 1999. As real income
grows, the WTP to avoid fatal risks is also expected to increase at a rate corresponding to the
income elasticity of demand, as discussed below. This income growth, from the years 1990 to
1999, accounts for the differences in incomes of the VSL study population versus the population
affected by the Arsenic Rule. This does not include any income adjustments over a latency
period because of methodological issues that have not yet been resolved. However, pending the
resolution of these issues, EPA may include an adjustment for income growth over a latency
period in future analyses, as recommended by the SAB.
The fourth and fifth rows of both the three and seven percent panels illustrates the impacts of
adjusting the primary VSL for discounting and income growth over a range of assumed latency
periods. As is shown in Exhibit 5-12, this value decreases from $5.84 million assuming a five-
year latency period to $3.75 million assuming a 20 year 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 $1.75 million.
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Exhibit 5-12
Sensitivity of the Primary VSL Estimate to Changes in Latency Period Assumptions,
Income Growth, and Other Adjustments
($ millions, 1999)
Adjustment Factor
Latency Period (Years)
5
10
20
3 % Discount Rate
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth1 elasticity = 0.22
elasticity = 1 .0
Adjusted for Income Growth1 and Discounting elasticity = 0.22
elasticity = 1 .0
Adjusted for Income Growth1, Discounting, and 7% Increase for
Voluntariness and Controllability elasticity = 0.22
elasticity = 1 .0
6.1
6.22
6.77
5.37
5.84
5.74
6.25
6.1
6.22
6.77
4.63
5.04
4.95
5.39
6.1
6.22
6.77
3.44
3.75
3.69
4.01
Break-Even for Other Characteristics (as a percentage of the primary VSL estimate)
elasticity = 0.22
elasticity = 1 .0
6%
-2%
19%
12%
40%
34%
7 % Discount Rate
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth1 elasticity = 0.22
elasticity = 1 .0
Adjusted for Income Growth1 and Discounting elasticity = 0.22
elasticity = 1 .0
Adjusted for Income Growth1, Discounting, and 7% Increase for
Voluntariness and Controllability elasticity = 0.22
elasticity = 1 .0
6.1
6.22
6.77
4.44
4.83
4.75
5.17
6.1
6.22
6.77
3.16
3.44
3.38
3.68
6.1
6.22
6.77
1.61
1.75
1.72
1.87
Break-Even for Other Characteristics (as a percentage of the primary VSL estimate)
elasticity = 0.22
elasticity = 1 .0
22%
15%
45%
40%
72%
69%
1. This adjustment reflects the change in WTP based on real income growth from 1990 to 1999.
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The sixth and seventh rows of the three and seven percent panels illustrate the effects of
incorporating a seven percent increase for voluntariness and controllability as recommended for a
sensitivity analysis in the SAB report on valuing fatal cancer risk reductions (SAB, 2000). One
member of the SAB committee noted in the SAB report that this adjustment may be as high as
two times the primary VSL, but this value is highly speculative. The seven percent adjustment
accounts for empirical evidence in the literature that indicates individuals may place a higher
willingness to pay (WTP) on risks where exposure is neither voluntary nor controllable by the
individual.
In adjusting for both income growth and voluntariness and controllability, EPA used a range of
income elasticities from the economics literature. Income elasticity is the percent change in
demand for a good (in this case, WTP for fatal risk reductions) for every one percent change in
income. For example, an income elasticity of 1.0 implies that a 10 percent higher income level
results in a 10 percent higher WTP for fatal risk reductions. In a recent study (EPA, 2000c), EPA
reviewed the literature related to the income elasticity of demand for the prevention of fatal health
impacts. Based on data from cross-sectional studies of wage premiums, a range of elasticity
estimates for serious health impacts was developed, ranging from a lower-end estimate of 0.22 to
an upper-end estimate of 1.0.
There are several other characteristics that differ between the VSL estimates used in the primary
analysis and an ideal estimate specific to the case of cancer risks from arsenic. These include a
cancer premium, differences in risk aversion, altruism, age 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
directly in this sensitivity analysis. A more complete discussion of the other characteristics
identified by economists as having a potential impact on WTP to reduce mortality risks can be
found in Chapter Seven of the Agency's Guidelines for Preparing Economic Analyses (EPA,
2000c), which is available in the docket for this final rulemaking.
However, it is possible to use a "break even" analysis 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 primary benefits analysis (described earlier in this chapter). The last two rows of the three
and seven percent panels of Exhibit 5-12 attempt to answer this question in percentage terms. For
example, at a three percent discount rate over a ten year 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 Exhibit 5-12)
indicates that if accounting for these characteristics would increase VSL by more than 12 percent
then the primary analysis will tend to understate the value of risk reductions. If accounting for
these characteristics would not increase VSL by at least 12 percent then the primary analysis may
overstate benefits (a negative percentage indicates that the primary analysis understates benefits
unless the combined impact of these additional characteristics actually reduces VSL estimates).
Some researchers believe that the value of some of these characteristics will substantially add to
the unadjusted VSL (one study suggests that a cancer premium alone may be worth an additional
100 percent of primary VSL value [Revesz, 1999]). Some researchers also believe that some of
these characteristics have a negative effect on VSL, suggesting that some of these factors offset
one another. Until we know more about these various factors we cannot explicitly make
adjustments to existing VSL estimates.
Chapter 5, Benefits Analysis 5-31 Arsenic in Drinking Water Rule EA
-------
The SAB noted in their report that these characteristics require more empirical research prior to
incorporation into the Agency's primary benefits analysis, but could be explored as part of a
sensitivity analysis.
5.5.3 Results
Exhibit 5-13 illustrates the impacts of changes in VSL adjustment factor assumptions on the
estimated benefits for the range of fatal bladder and lung cancer cases avoided in the final Arsenic
Rule, assuming a three percent discount rate. The results of this analysis at a seven percent
discount rate are given in Exhibit 5-14. These results were calculated by applying the adjusted
VSLs from Exhibit 5-12 to the lower- and upper-bound estimates of fatal bladder and lung cancer
cases avoided as shown in Exhibit 5-9 (c). For purposes of this sensitivity analysis, EPA
presented combined bladder and lung cancer cases avoided in Exhibits 5-13 and 5-14. Health risk
reduction benefits attributable to reduced arsenic levels in both CWSs and NTNCWSs are
presented in these exhibits as well.
It is important to note that the monetized benefits estimates shown in this section reflect
quantifiable benefits only. As shown in Section 5.2, there are a significant number of non-
quantifiable benefits associated with regulating arsenic in drinking water. As a result, the
monetized benefits presented in the following exhibit represent a lower-bound estimate. Were
EPA able to quantify some of the currently non-quantifiable health effects and other benefits
associated with arsenic regulation, monetized benefits estimates could be significantly higher than
what are shown in the exhibit.
Chapter 5, Benefits Analysis 5-32 Arsenic in Drinking Water Rule EA
-------
Exhibit 5-13. Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits
Estimates to Changes in VSL Adjustment Factor Assumptions
($ millions, 1999, 3% discount rate)1
Arsenic Level (• g/L)
3
5
10
20
5 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E = 1.0
199-452
203-461
221-502
175-398
190-433
187-425
204-463
176-328
181-334
197-364
156-288
170-314
167-308
182-336
130-182
133-186
144-202
114-160
124-174
122-171
133-186
62-69
63-70
69-77
55-61
60-66
59-65
64-71
10 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E = 1.0
199-452
203-461
221-502
151-343
164-373
161-367
176-399
176-328
181-334
197-364
135-249
147-271
144-266
157-289
130-182
133-186
144-202
99-138
107-150
105-148
115-161
62-69
63-70
69-77
47-52
51-57
50-56
55-61
20 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E = 1.0
199-452
203-461
221-502
112-255
122-278
120-273
131-297
176-328
181-334
197-364
100-185
109-201
107-198
117-215
130-182
133-186
144-202
73-103
80-112
79-110
85-119
62-69
63-70
69-77
35-39
38-42
38-42
41-45
1. The lower- and upper-bound benefits estimates correspond to the lower- and upper-bound risk estimates and
cancer cases avoided as shown in section III.D.2 of this preamble.
2. This adjustment reflects the change in WTP based on real income growth from 1990 to 1999. E = income
elasticity.
Chapter 5, Benefits Analysis
5-33
Arsenic in Drinking Water Rule EA
-------
Exhibit 5-14
Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits Estimates to
Changes in VSL Adjustment Factor Assumptions
($ millions, 1999, 7% discount rate)1
Arsenic Level (• g/L)
3
5
10
20
5 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E = 1.0
199-452
203-461
221-502
145-329
157-358
155-352
168-383
178-328
181-334
197-364
129-238
141-259
138-255
150-278
130-182
133-186
144-202
95-132
103-144
102-142
110-154
62-69
63-70
69-77
45-50
50-55
49-54
53-58
10 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E= 1.0
199-452
203-461
221-502
103-234
112-255
110-251
120-273
178-328
181-334
197-364
92-170
100-185
98-182
107-198
130-182
133-186
144-202
67-94
73-103
72-101
78-110
62-69
63-70
69-77
32-36
35-39
35-38
38-42
20 Year Latency Period Assumption
Primary Analysis (No VSL Adjustment)
Adjusted for Income Growth2 E = 0.22
E = 1.0
Adjusted for Income Growth2 and Discounting E = 0.22
E = 1.0
Adjusted for Income Growth2, Discounting, and 7%
Increase for Voluntariness and Controllability E = 0.22
E = 1.0
199-452
203-461
221-502
53-119
57-130
56-127
61-139
178-328
181-334
197-364
47-86
51-94
50-92
54-100
130-182
133-186
144-202
34-48
37-52
37-51
40-56
62-69
63-70
69-77
16-18
18-20
18-20
19-21
1. The lower- and upper-bound benefits estimates correspond to the lower- and upper-bound risk estimates and
cancer cases avoided as shown in section III.D.2 of this preamble.
2. This adjustment reflects the change in WTP based on real income growth from 1990 to 1999. E = income
elasticity.
Chapter 5, Benefits Analysis
5-34
Arsenic in Drinking Water Rule EA
-------
As shown in Exhibits 5-13 and 5-14, the highest range of adjusted benefits estimates at the 10
|ig/L MCL ($144 - $202 million at three percent and seven percent) are yielded when benefits are
adjusted for income growth only with an income elasticity of 1.0. The lowest adjusted benefits
estimates at the 10 |ig/L MCL ($73 - $103 million at three percent, $34 - $48 million at seven
percent) are yielded under the assumption of a 20-year latency period that includes adjustments
for discounting and income growth (income elasticity = 0.22). These results indicate the high
degree of sensitivity of benefits estimates to different assumptions of a latency period and income
elasticity and also the inclusion of adjustments for income growth and voluntariness and
controllability.
5.6 Other Benefits of Reductions in Arsenic Exposure
It is well established that the public often avoids the use of tap water that is suspected to be
contaminated. In this context, contamination may suggest biological, chemical, or other water
quality issues. When public perception of water quality declines, consumers purchase bottled
water if they have the means to do so.
In addition or as an alternative, they may avoid the use of tap water, ingesting and cooking with
other liquids, substituting pre-mixed baby formula, and using other strategies to limit ingestion.
Consumer avoidance of tap water sources usually results in costs to the consumers, either in the
cost of obtaining substitute fluids or potential health impacts of reduced fluid intake. In addition,
there are numerous cases where government agencies have provided bottled water due to
biological or chemical contamination. The levels of contamination at which the government
activities occur vary depending on a variety of factors.
The relationship between arsenic in tap water and changes in consumer behavior or government
interventions is a complex one. Factors 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 governments is not
included in this benefits assessment. However, it is clear that many consumers purchase bottled
water (a multimillion dollar industry) or invest in other methods of improving drinking water
quality, such as point-of-use (POU) devices, specifically to avoid ingestion of contaminants such
as arsenic. Thus, it is reasonable to conclude that a reduction in arsenic contamination will have
the long-term effect of restoring some level of consumer confidence in the water supply.
Chapter 5, Benefits Analysis 5-35 Arsenic in Drinking Water Rule EA
-------
Chapter 6: Cost Analysis
6.1 Introduction
This chapter presents the national cost estimates for the Arsenic Rule. The costs associated with
the rule include: (1) costs borne by water systems 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 methodologies used to estimate costs, including the
following:
• A description of the technologies that may be used by systems to achieve the
MCL (Section 6.2.1);
• The unit costs of different technologies for complying with the MCLs (Section
6.2.2);
• System and State unit costs for monitoring and administration functions (Section
6.2.3); and
• The methods used to predict systems' 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 analysis, including the following:
A summary of national costs for the different regulatory options (Section 6.3.1);
• Costs by system size and type for the MCL options (Section 6.3.2); and
Household costs (Section 6.3.3).
Section 6.4 discusses the uncertainty inherent in the distribution of estimated national
compliance costs.
6.2 Methodology
6.2.1 Description of Available Technologies
In 1993, EPA developed a document entitled Treatment and Occurrence—Arsenic in Potable
Water Supplies (EPA, 1993), which summarized the results of pilot-scale studies examining
low-level arsenic removal, from 50 micrograms per liter (|ig/L) down to 1 |ig/L or less. EPA
convened a panel of outside experts in January 1994 to review this document and comment on
the ability of the technologies to achieve various MCLs. The Agency has since sought
stakeholder input on the use of various technologies for arsenic removal under different
conditions, and has incorporated that input into its estimates of technology performance and
costs. The results are documented in the Cost and Technology Document for the Arsenic Rule
(EPA, 2000d). The technology cost functions and removal efficiencies presented in that
document are used as inputs for the cost analyses presented in this EA.
Some technologies generate wastes that require disposal or pre-treatment (e.g., pre-oxidation or
corrosion control) in order to be effective. These associated requirements were identified for
Chapter 6, Cost Analysis 6-1 Arsenic in Drinking Water Rule EA
-------
different technologies and system types, and their costs were included in the costs of treatment
where relevant.
In addition to these centralized treatment options, small systems may elect to use point-of-use
(POU) devices to achieve compliance with the MCLs. POU involves treatment at the tap. The
available POU technologies for arsenic removal are essentially smaller versions of reverse
osmosis and activated alumina. These technologies will have to be maintained by the water
system, involving some additional recordkeeping and maintenance costs.
The result of the review of technologies that would effectively remove arsenic and bring a water
system into compliance is summarized in Exhibit 6-1. The list includes 13 treatment trains
available to systems, consisting of various combinations of compliance technologies, waste
disposal technologies, or pre-treatment technologies as required.
Chapter 6, Cost Analysis 6-2 Arsenic in Drinking Water Rule EA
-------
Exhibit 6-1
Arsenic Rule Treatment Trains by Compliance Technologies Component
with Associated Removal Efficiencies
Treatment Technology
1
2
3
4
5
6
7
8
9
10
11
12
13
Modify Li me Softening
Modify Coagul atj on/Fi Itratj on
Ailon Exchange (<20 mg/L SO4)
Ailon Exchange (20-50 mg/L SO4)
Coagulation Assisted Mcrofiltration
Coagulation Assisted Mcrofiltration
Oxidation nitration (Greensand)
Activated Aumina (pH 7 - pH 8)
Activated Aumina (pH 8 - pH 8.3)
Activated Aumina (23,100 BV) with pH adjustment (pH 6)
Activated Aumina (1 5,400 BV) with pH adjustment (pH 6)
POU Activated Aumina
POU Reverse Osmosis
V\aste Disposal Technology
POTW
• •
• •
. *
Non-
Hazardous
Landfill
• •
• •
. **
. **
. **
. **
Mechanical
De-V\atering
• •
Non-
Mechanical
De-V\ateri ng
• •
Corrosion
Control
• •
• •
Pre-
Qxidatjon0
• •
• •
• •
• •
• •
• •
• •
• •
• •
• •
• •
• •
• •
Removal
Efficiency
90%
95%
95%
95%
90%
90%
50%
95%
95%
95%
95%
90%
90%
° pre-oxidation incorporated into treatment trains based on a separate dedsion tree
* POTWfor backwash stream
** non-hazardous landfill (forspent media)
-------
6.2.2 Unit Costs and Compliance Assumptions
EPA estimated the costs of the various compliance technologies, including the centralized
treatment technologies associated waste disposal technologies, and POU treatment technologies,
excluding pre-treatment costs. Pre-treatment costs were separate treatment costs that apply to a
particular set of systems (some systems would already have pre-treatment in place). Costs of
each treatment train are estimated as functions of system size, design flow (used to calculate
capital costs) and average flow (used to calculate operating and maintenance costs). Exhibits 6-2
(a) and 6-2 (b) presents a summary of unit compliance technology costs by cost component for
the treatment trains listed in Exhibit 6-1, annualized over 20 years at a seven percent discount
rate. Costs are in May 1999 dollars and are based on average and design flows for median
populations of each system size category.
The unit costs are provided to demonstrate the range of costs across the treatment technologies
for an MCL of 10|ig/L, assuming either an influent arsenic concentration of 1 l|ig/L (low range
estimates shown in Exhibit 6-2(a)) or an influent arsenic concentration of 50|ig/L (high range
estimates shown in Exhibit 6-2(b)). EPA calculated these average unit costs for a single
contaminated entry point, assuming a publicly-owned ground water system with the average
number of entry points per system in that size category. 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 annualized over 20 years at a seven percent
discount rate. Detailed descriptions of the assumptions and methodologies used to develop the
underlying cost curves are available in the Cost and Technology Document for the Arsenic Rule
(EPA, 2000d).
Chapter 6, Cost Analysis 6-4 Arsenic and Drinking Water Rule EA
-------
Exhibit 6-2a
System Compliance Technology Costs Assuming Influent Concentration of 11 ug/L and MCL of 10 ug/L (Dollars)
Size Category
<100
101-500
501-1,000
1,001-3,300
Treatment Train No.
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
1
E 8,999 $
E 484 $
E - $
E - $
E 1,333 $
E 13,688 $
E 1,416 $
E - $
E - $
E 2,708 $
E 14,756 $
E 1,766 $
E - $
E - $
E 3,159 $
E 24,087 $
E 4,760 $
E - $
E - $
E 7,034 $
2
7,483 $
260 $
$
$
966 $
8,966 $
482 $
$
$
1,328 $
9,316 $
565 $
$
$
1,444 $
12,655 $
1,266 $
$
$
2,460 $
3
21,957 $
5,104 $
3,955 $
381 $
7,930 $
21,957 $
5,104 $
3,955 $
412 $
7,962 $
21,957 $
5,104 $
3,955 $
424 $
7,974 $
38,991 $
5,104 $
3,955 $
525 $
9,682 $
4
22,724 $
8,604 $
3,955 $
387 $
11,510 $
37,150 $
9,470 $
3,955 $
455 $
13,804 $
40,669 $
9,791 $
3,955 $
480 $
14,483 $
120,712 $
12,431 $
3,955 $
696 $
24,894 $
5
127,885 $
22,361 $
29,900 $
6,946 $
44,200 $
265,526 $
23,619 $
43,354 $
12,863 $
65,638 $
295,452 $
24,090 $
46,424 $
14,929 $
71,290 $
526,687 $
28,088 $
73,454 $
29,102 $
113,839 $
6
127,885
20,585
20,686
2,131
36,740
265,526
22,400
118,165
2,177
60,795
295,452
23,081
141,947
2,195
66,563
526,687
28,088
330,519
2,364
111,366
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1.
-------
Exhibit 6-2a (continued)
System Compliance Technology Costs Assuming Influent Concentration of 11 ug/L and MCL of 10 ug/L (Dollars)
Size Category
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
Treatment Train No.
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
1
$ 64,447 $
$ 14,961 $
$ - $
$ - $
$ 21,045 $
$ 247,207 $
$ 35,250 $
$ - $
$ - $
$ 58,584 $
$ 455,707 $
$ 61,149 $
$ - $
$ - $
$ 104,165 $
$ 1,462,373 $
$ 309,897 $
$ - $
$ - $
$ 447,935 $
2
40,103 $
4,833 $
$
$
8,618 $
168,801 $
17,001 $
$
$
32,934 $
315,625 $
32,533 $
$
$
62,326 $
918,353 $
177,044 $
$
$
263,730 $
3
38,991 $
5,104 $
3,955 $
869 $
10,027 $
38,991 $
5,104 $
3,955 $
1,593 $
10,750 $
38,991 $
5,104 $
5,085 $
2,516 $
11,780 $
38,991 $
5,104 $
5,085 $
12,132 $
21,396 $
4
211,802 $
20,403 $
3,955 $
1,434 $
42,203 $
362,184 $
31,688 $
3,955 $
2,984 $
69,233 $
529,645 $
54,032 $
5,085 $
4,962 $
109,470 $
1,873,015 $
168,459 $
5,085 $
25,570 $
371,308 $
5
1,069,210 $
38,522 $
121,208 $
32,307 $
183,196 $
1,793,771 $
55,413 $
209,000 $
45,793 $
290,253 $
2,368,818 $
59,325 $
309,158 $
52,569 $
364,675 $
6,887,505 $
96,658 $
954,312 $
178,509 $
1,015,379 $
6
1,069,210
38,522
762,407
9,170
220,583
1,793,771
55,413
1,610,846
50,349
427,134
2,368,818
59,325
2,381,322
66,722
574,426
6,887,505
96,658
9,517,736
237,418
1,882,614
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1.
-------
Exhibit 6-2a (continued)
System Compliance Technology Costs Assuming Influent Concentration of 11 ug/L and MCL of 10 ug/L (Dollars)
Size Category
<100
101-500
501-1,000
1,001-3,300
Treatment Train No.
Treatment Capital Coste (
Treatment O&M Costs (
Waste Disposal Capital Costs (
Waste Disposal O&M Costs (
Annual Costs (7%) S
Treatment Capital Costs S
Treatment O&M Costs (
Waste Disposal Capital Costs (
Waste Disposal O&M Costs (
Annual Costs (7%) S
Treatment Capital Costs S
Treatment O&M Costs (
Waste Disposal Capital Costs S
Waste Disposal O&M Costs (
Annual Costs (7%) S
Treatment Capital Costs S
Treatment O&M Costs (
Waste Disposal Capital Costs S
Waste Disposal O&M Costs (
Annual Costs (7%) S
7
> 15,023 $
> 7,711 $
> 3,955 $
> 446 $
> 9,949 $
> 63,059 $
> 8,540 $
> 3,955 $
> 571 $
> 15,437 $
> 73,464 $
> 8,904 $
> 3,955 $
> 618 $
> 16,830 $
> 170,709 $
> 12,006 $
> 3,955 $
> 1,016 $
> 29,509 $
8
13,629 $
4,414 $
$
12 $
5,712 $
29,131 $
6,065 $
$
78 $
8,892 $
32,912 $
6,684 $
$
103 $
9,893 $
60,846 $
11,930 $
$
313 $
17,986 $
9
13,629 $
6,944 $
$
22 $
8,253 $
29,131 $
10,087 $
$
150 $
12,986 $
32,912 $
11,265 $
$
197 $
14,569 $
60,846 $
21,255 $
$
602 $
27,600 $
10
45,787
6,050
-
5
10,377
62,507
7,494
-
34
13,428
66,586
8,036
-
44
14,365
97,616
12,627
-
135
21,977
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
11
45,787
6,643
-
8
10,972
62,507
8,437
-
51
14,388
66,586
9,110
-
67
15,462
97,616
14,814
-
203
24,231
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
12
4,671
6,725
-
-
7,390
27,027
39,804
-
-
43,652
34,915
51,591
-
-
56,562
97,980
146,709
-
-
160,659
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
13
13,619
4,433
-
-
6,372
78,866
26,552
-
-
37,781
101,897
34,475
-
-
48,983
286,071
98,728
-
-
139,458
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1. In Treatment Trains 8-11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and therefore, are quite low.
-------
Exhibit 6-2a (continued)
System Compliance Technology Costs Assuming Influent Concentration of 11 ug/L and MCL of 10 ug/L (Dollars)
Size Category
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
Treatment Train No.
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
7
$ 421,562 3
$ 22,659 3
$ 3,955 3
$ 2,381 3
$ 65,205 3
$ 787,837 3
$ 45,012 3
$ 5,085 3
$ 5,951 3
$ 125,809 3
$ 1,168,062 3
$ 73,549 3
$ 5,085 3
$ 9,606 3
$ 193,892 3
$ 4,098,917 3
$ 370,791 3
$ 5,085 3
$ 47,683 3
$ 805,863 3
8
> 159,129 3
> 29,916 3
5
> 1,033 3
> 45,970 3
> 324,276 3
> 67,654 3
5
> 2,545 3
> 100,809 3
> 512,683 3
> 122,590 3
5
> 4,476 3
> 175,459 3
> 2,257,773 3
> 629,270 3
5
> 24,581 3
> 866,968 3
9
> 159,129 3
> 55,506 3
5
> 1,988 3
> 72,514 3
> 324,276 3
> 127,369 3
5
> 4,895 3
> 162,873 3
> 512,683 3
> 231,264 3
5
> 8,608 3
> 288,265 3
> 2,257,773 3
> 1,199,321 3
5
> 47,274 3
> 1,459,713 3
10
> 205
> 28
)
'
> 48
> 386
> 61
>
, 1
> 98
> 593
> 109
>
, 1
> 167
> 2,506
> 548
'
> 10
> 796
,374 3
,369 3
5
447 3
,202 3
,442 3
,397 3
5
,102 3
,976 3
,012 3
,500 3
5
,938 3
,413 3
,335 3
,870 3
5
,642 3
,092 3
11
> 205,374 3
> 34,369 3
5
> 671 3
> 54,426 3
> 386,442 3
> 75,399 3
5
> 1,653 3
> 113,530 3
> 593,012 3
> 134,983 3
5
> 2,906 3
> 193,866 3
> 2,506,335 3
> 682,540 3
5
> 15,962 3
> 935,082 3
12
> 296
> 449
)
'
> 492
> 682
> 1,047
>
>
> 1,144
> 1,150
> 1,778
>
>
> 1,941
> 5,567
> 8,780
'
'
> 9,573
207
875
-
-
048
321
475
-
-
622
447
028
-
-
826
338
565
-
-
229
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
13
865,248
305,030
-
-
428,222
1,993,842
714,269
-
-
998,147
3,362,537
1,216,748
-
-
1,695,498
16,283,352
6,073,580
-
-
8,391,963
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1. In Treatment Trains 8-11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and therefore, are quite low.
-------
Exhibit 6-2b
System Compliance Technology Costs Assuming Influent Concentration of 50 ug/L and MCL of 10 ug/L (Dollars)
Size Category
<100
101-500
501-1,000
1,001-3,300
Treatment Train No.
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
1
E 8,999 $
E 484 $
E - $
E - $
E 1,333 $
E 13,688 $
E 1,416 $
E - $
E - $
E 2,708 $
E 14,756 $
E 1,766 $
E - $
E - $
E 3,159 $
E 24,087 $
E 4,760 $
E - $
E - $
E 7,034 $
2
7,483 $
260 $
$
$
966 $
8,966 $
482 $
$
$
1,328 $
9,316 $
565 $
$
$
1,444 $
12,655 $
1,266 $
$
$
2,460 $
3
26,970 $
5,365 $
3,955 $
392 $
8,676 $
43,632 $
5,365 $
3,955 $
490 $
10,346 $
43,632 $
5,365 $
3,955 $
526 $
10,383 $
43,632 $
5,365 $
3,955 $
836 $
10,692 $
4
29,332 $
8,924 $
3,955 $
412 $
12,478 $
117,795 $
11,527 $
3,955 $
621 $
23,640 $
126,653 $
12,469 $
3,955 $
699 $
25,497 $
218,240 $
19,699 $
3,955 $
1,362 $
42,035 $
5
193,923 $
21,251 $
36,236 $
9,187 $
52,164 $
508,282 $
26,696 $
71,219 $
24,844 $
106,241 $
564,187 $
28,148 $
77,743 $
29,269 $
118,010 $
1,103,278 $
37,737 $
124,926 $
40,238 $
193,909 $
6
193,923
21,251
65,339
2,148
47,872
508,282
26,696
316,779
2,301
106,877
564,187
28,148
358,515
2,367
117,611
1,103,278
37,737
793,148
8,074
224,820
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1.
-------
Exhibit 6-2b (continued)
System Compliance Technology Costs Assuming Influent Concentration of 50 ug/L and MCL of 10 ug/L (Dollars)
Size Category
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
Treatment Train No.
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
TreatmentCapital Costs
TreatmentO&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
1
$ 64,447 $
$ 14,961 $
$ - $
$ - $
$ 21,045 $
$ 247,207 $
$ 35,250 $
$ - $
$ - $
$ 58,584 $
$ 455,707 $
$ 61,149 $
$ - $
$ - $
$ 104,165 $
$ 1,462,373 $
$ 309,897 $
$ - $
$ - $
$ 447,935 $
2
40,103 $
4,833 $
$
$
8,618 $
168,801 $
17,001 $
$
$
32,934 $
315,625 $
32,533 $
it
!t>
it
!t>
62,326 $
918,353 $
177,044 $
$
$
263,730 $
3
43,632 $
5,365 $
5,085 $
1,897 $
11,860 $
43,632 $
5,365 $
5,085 $
4,124 $
14,087 $
43,632 $
5,365 $
5,085 $
6,967 $
16,930 $
43,632 $
5,365 $
5,571 $
36,579 $
46,588 $
4
490,994 $
45,678 $
5,085 $
3,637 $
96,141 $
923,917 $
75,188 $
5,085 $
8,409 $
171,288 $
1,378,931 $
110,599 $
5,085 $
14,501 $
255,741 $
3,623,972 $
328,792 $
5,571 $
77,955 $
749,350 $
5
2,255,079 $
56,923 $
285,807 $
48,028 $
344,793 $
3,571,834 $
65,568 $
513,238 $
72,683 $
523,853 $
5,074,043 $
76,604 $
717,287 $
110,698 $
733,963 $
18,245,297 $
203,223 $
2,275,373 $
477,280 $
2,617,509 $
6
2,255,079
56,923
2,123,020
42,687
512,872
3,571,834
65,568
4,281,260
95,250
902,095
5,074,043
76,604
6,653,715
145,696
1,329,318
18,245,297
203,223
28,628,219
672,537
5,300,288
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1.
-------
Exhibit 6-2b (continued)
System Compliance Technology Costs Assuming Influent Concentration of 50 ug/L and MCL of 10 ug/L (Dollars)
Size Category
<100
101-500
501-1,000
1,001-3,300
Treatment Train No.
Treatment Capital Coste $
Treatment O&M Costs $
Waste Disposal Capital Costs $
Waste Disposal O&M Costs $
Annual Costs (7%) $
Treatment Capital Costs $
Treatment O&M Costs $
Waste Disposal Capital Costs $
Waste Disposal O&M Costs $
Annual Costs (7%) $
Treatment Capital Costs $
Treatment O&M Costs $
Waste Disposal Capital Costs $
Waste Disposal O&M Costs $
Annual Costs (7%) $
Treatment Capital Costs $
Treatment O&M Costs $
Waste Disposal Capital Costs $
Waste Disposal O&M Costs $
Annual Costs (7%) $
7
24,983 $
7,747 $
3,955 $
464 $
10,943 $
104,869 $
9,495 $
3,955 $
694 $
20,462 $
104,869 $
9,495 $
3,955 $
694 $
20,462 $
283,894 $
15,866 $
3,955 $
1,511 $
44,547 $
8
20,733 $
5,021 $
-------
Exhibit 6-2b (continued)
System Compliance Technology Costs Assuming Influent Concentration of 50 ug/L and MCL of 10 ug/L (Dollars)
Size Category
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
Treatment Train No.
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
Treatment Capital Costs
Treatment O&M Costs
Waste Disposal Capital Costs
Waste Disposal O&M Costs
Annual Costs (7%)
7
$ 701,070 3
$ 35,414 3
$ 5,085 3
$ 4,721 3
$ 106,791 3
$ 1,310,195 3
$ 76,430 3
$ 5,085 3
$ 9,975 3
$ 210,559 3
$ 1,942,521 3
$ 128,791 3
$ 5,085 3
$ 16,683 3
$ 329,314 3
$ 6,816,616 3
$ 674,190 3
$ 5,598 3
$ 86,549 3
$ 1,404,708 3
8
> 468,896 3
> 90,018 3
5
> 3,183 3
> 137,461 3
> 977,574 3
> 207,386 3
5
> 7,840 3
> 307,502 3
> 1,557,893 3
> 357,213 3
5
> 13,785 3
> 518,052 3
> 6,933,014 3
> 1,917,857 3
5
> 75,712 3
> 2,647,996 3
9
> 468,896 3
> 169,031 3
5
> 6,122 3
> 219,413 3
> 977,574 3
> 393,274 3
5
> 15,079 3
> 500,628 3
> 1,557,893 3
> 679,531 3
5
> 26,512 3
> 853,098 3
> 6,933,014 3
> 3,661,282 3
5
> 145,611 3
> 4,461,320 3
10
> 545,004 3
> 81,254 3
5
> 1,378 3
> 134,077 3
> 1,102,719 3
> 183,031 3
5
> 3,394 3
> 290,514 3
> 1,738,984 3
> 312,954 3
5
> 5,968 3
> 483,070 3
> 7,632,284 3
> 1,666,275 3
5
> 32,778 3
> 2,419,486 3
11
> 545,004 3
> 99,783 3
5
> 2,067 3
> 153,294 3
> 1,102,719 3
> 226,620 3
5
> 5,091 3
> 335,800 3
> 1,738,984 3
> 388,534 3
5
> 8,952 3
> 561,634 3
> 7,632,284 3
> 2,075,085 3
5
> 49,166 3
> 2,844,684 3
12
> 296,207
> 449,875
)
'
> 492,048
> 682,321
> 1,047,475
>
>
> 1,144,622
> 1,150,447
> 1,778,028
>
>
> 1,941,826
> 5,567,338
> 8,780,565
'
'
> 9,573,229
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
13
865,248
305,030
-
-
428,222
1,993,842
714,269
-
-
998,147
3,362,537
1,216,748
-
-
1,695,498
16,283,352
6,073,580
-
-
8,391,963
NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry point, based on median
population and the average number of entry points per system in the service size category, for the treatment train technologies described in
Exhibit 6-1. In Treatment Trains 8-11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and therefore, are quite low.
-------
6.2.3 Monitoring and Administrative Costs
Monitoring Costs
Monitoring under the current Arsenic Rule occurs annually for surface water systems, and
triennially for ground water systems. Currently, when triggered by a violation the system must
perform three additional tests within the month. Under the revised rule to be promulgated in
January 2001, systems will still perform monitoring annually (for surface water systems) or every
three years (for ground water systems); however, when triggered by a violation, the system will
perform quarterly monitoring rather than three more samples in one month. All surface water
systems must collect samples no later than December 31, 2006, and all ground water systems
must collect samples by December 31, 2007, to demonstrate compliance with the revised MCL.
If quarterly monitoring is required it will continue until the State determines that the system is
"reliably and consistently" below the MCL or until the PWS installs treatment. States are able to
make this determination after ground water systems have taken two quarterly samples and
surface water systems have taken four quarterly samples. Additionally, States may grant a nine-
year monitoring waiver to qualifying systems, an option not previously available. To be eligible
for a waiver, a system must meet the following criteria:
1. Demonstrate adequate source water protection by completing a vulnerability
assessment; and
2. Demonstrate that three previous samples were below the MCL.
The monitoring requirements will impose new costs for some systems as follows:
• NTNCs will incur the full costs of the monitoring requirements for the first time,
unless they are located in States that already require NTNCs to monitor for
arsenic. For NTNCs that are currently required to monitor for arsenic, the
incremental monitoring costs will depend on how the revised national
requirements compare with the current State requirements. (It is assumed that
States currently require NTNCs to monitor using the ground water requirements.
It is also assumed that 96 percent of NTNCs use ground water sources, and 4
percent use surface water.)
• CWSs may incur additional costs if they find exceedances more frequently at the
revised MCL.
The cost of monitoring includes preparing and analyzing the sample. Collecting the sample,
arranging for delivery to the laboratory, and reviewing the results of the analysis is assumed to
require one hour of the system operator's time (at an estimated cost of $28 per hour). EPA has
assumed that all systems are equipped to collect samples. Therefore, no additional costs are
assumed for installation of taps, re-piping of wells or other investments to permit sampling. EPA
has assumed that systems will utilize one of two laboratory methods: (1) stabilized temperature
platform graphite furnace atomic absorption (STP-GFAA) or (2) graphite furnace atomic
absorption (GFAA). Both 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-year 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 system and the State are listed below in Exhibit 6-3. The cost of routine
monitoring, triggered monitoring, waiver application and public notification are all included in
the total system costs. Miscellaneous costs related to sending samples to be analyzed and
sending public notification to customers are also included in the system cost.
Exhibit 6-3
Unit Resources Required for Monitoring, Implementation, and Administration*
System Size Category
State Activity
Review a waiver
application
Record monitoring of a
sample result
Issue a single violation letter
Review a single permit
System Activity
Apply for a waiver
Take a sample
Report a sample
Prepare and Send Public
Notification
< 10,000 people
Hours
8
1
4
16
Rate
$41.47
$41.47
$41.47
$41.47
<3,000 people
Hours
16
1
1
8
Rate
$15.03
$15.03
$15.03
$15.03
> 10,000 people
Hours
8
1
4
32
Rate
$41.47
$41.47
$41.47
$41.47
>3,300 people
Hours
16
1
1
8
Rate
$29.03
$29.03
$29.03
$29.03
Source: Information Collection
*Estimates are provided in May
Request for the Public Water System Supervision Program.
1999 dollars, updated from 1997 dollars using the CPI-U for all items.
States will also be required to spend time responding to systems that report MCL exceedances or
systems that request a waiver (Exhibit 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 large systems. The number of hours required to review a single permit is twice as large for
systems serving more than 10,000 people than for systems serving less than 10,000 people. The
unit cost for all activities is consistent across all activities and size categories ($41.47 per hour)
(EPA, 1997).
Exhibit 6-3 also shows that the number of hours required at the system level to perform the
responsibilities related to monitoring is the same for systems serving fewer than 3,300 people and
systems serving more than 3,300 people. However, the hourly rate for systems serving more than
3,300 people ($29.03) is almost double the rate for systems serving fewer than 3,300 people
($15.03).
Chapter 6, Cost Analysis
6-14
Arsenic in Drinking Water Rule EA
-------
During the first year of implementation all systems will incur costs related to routine monitoring.
In addition, systems in violation will incur costs related to triggered quarterly monitoring. Under
the revised rule, a percentage of the systems will have monitoring waivers in subsequent years
when monitoring is otherwise required. Monitoring waivers are not granted under the existing
rule; therefore, the number of systems required to conduct routine monitoring under the revised
rule is less than that under the existing rule. For this reason, the annual net cost of monitoring
between the revised rule and the existing rule may be negative, or less expensive, after the initial
year of implementation. The inputs and methodology associated with this analysis are presented
in detail in the Information Collection Request for the Proposed Arsenic in Drinking Water Rule.
Administrative Costs
States and systems will incur administrative costs to implement the revised arsenic program
under the Arsenic Rule. States and systems will need to allocate time for their staff to establish
and maintain the programs necessary to comply with the revised arsenic standard and the new
monitoring requirements. Exhibit 6-4(a) lists the one-time State activities involved in starting up
the program following promulgation of the rule. For example, start-up activities may include
developing and adopting State regulations that meet the new Federal arsenic requirements.
Resources are estimated in terms of full-time equivalents (FTEs), which EPA has assumed to
cost $64,480 per FTE, including overhead and fringe. Systems also have start-up costs for
reviewing the rule and training operators. Exhibit 6-4(b) lists the one-time system start-up
activities. The two primary activities that systems will perform to comply with the revised
arsenic rule are reading and understanding the rule and operator training. For all systems the
estimated time required to review the rule is eight hours. Systems serving fewer than 10,000
people require an estimated time of 16 hours to train operators; the estimated time for systems
serving more than 10,000 people is 32 hours. The rate for all start-up activities for systems
serving fewer than 10,000 people is $15.03 per hour and $29.03 per hour for systems serving
more than 10,000 people.
Exhibit 6-4(a)
Estimated One-Time State Resources Required for Initiation of the Arsenic Rule
Administrative Activity
Estimated State
Resources (FTE)
One Time Start-up Activities
Regulation Adoption and Program Development
System Training and Technical Assistance (CWS)
System Training and Technical Assistance (NTNC)
Staff Training (CWS)
National Total*
0.2
0.5
0.5
0.12
73.92
Estimated Cost
$12,900
$32,240
$32,240
$7,740
$4,767,840
*National totals include estimates for all States, territories, and Tribes.
Chapter 6, Cost Analysis
6-15
Arsenic in Drinking Water Rule EA
-------
Exhibit 6-4(b)
Estimated One-Time System Resources Required for Initiation of the Arsenic Rule
System Size Category
One Time Start-up Activity
Reading and Understanding
Rule
Operator Training
< 10,000 people
Hours
8
16
Rate
$15.03
$15.03
> 10,000 people
Hours
8
32
Rate
$29.03
$29.03
Source: Information Collection Request for the Public Water System Supervision Program.
6.2.4 Predicting Compliance Decisions (Compliance Decision Tree)
There is substantial variability in how systems will elect to comply with the Arsenic Rule.
Choices of compliance method will vary depending on baseline source water arsenic
concentrations, system size and location, types of treatment currently in place, and availability of
alternative sources. In addition, the source water pH, total dissolved solids, sulfides, and other
salts can change the effectiveness of technologies in removing arsenic.
The EA reflects this variability by predicting a range of compliance responses for different
system types and sizes. The compliance decision tree specifies the percentage of systems in
different categories that will choose specific compliance options, given the removal required by
the MCL option and the baseline occurrence of arsenic in source water. For example, for a target
MCL of 10 |ig/L, the decision tree specifies the probability of different compliance choices for
systems with different baseline influent concentrations (e.g., <10 |ig/L, 10-20 u.g/L, etc.),
different sizes (e.g., population < or > 1,000), different sources (ground water or surface water),
and different existing treatment facilities. The compliance choices are defined by a treatment
technology and (where relevant) a waste disposal option, and/or pre-treatment technology.
EPA presented a draft of the compliance decision tree at an American Water Works Association
(AWWA) technical workgroup meeting in February 1999 and made revisions based on the
comments received at that meeting. The final compliance decision tree, as well as a discussion
of the assumptions made during its development, is provided in Appendix A ("Cost Analysis
Appendix") by system size and type.
6.2.5 Calculating Costs
Different methods were used to assess costs for three different categories of systems. A Monte-
Carlo simulation model (SafeWaterXL) was used to estimate costs for community water systems,
excluding the largest CWSs. A deterministic spreadsheet analysis was performed for NTNC
water systems, while a separate case-by-case analysis were performed for the very large systems
(serving more than one million people) that are expected to exceed one or more MCL options in
the baseline. The costs for the three system categories were then summed to calculate total
national costs.
Chapter 6, Cost Analysis
6-16
Arsenic in Drinking Water Rule EA
-------
The methodology for calculating the costs for each of these system categories is described
separately below, beginning with a description of the SafeWaterXL model. In addition, a
detailed description of the SafeWaterXL model is provided in Appendix C.
CIVS Cosfs
The national cost of compliance across CWSs (except those serving over one million people) was
estimated using SafeWaterXL, a Monte-Carlo simulation model developed in Microsoft® Excel
using the Crystal Ball© Monte-Carlo simulation add-in. SafeWaterXL forecasts a distribution of
costs around the mean compliance cost expected for each system size category. The Monte-
Carlo model provides the flexibility to incorporate as many data as are available, while
maintaining uncertainty bounds to prevent any individual input from skewing the results. When
sample data are not available as single point estimates, this technique is an invaluable tool.
Historically, most drinking water regulatory impact analyses used point estimates to describe the
average system-level costs. By using SafeWaterXL, this analysis contains more detailed
descriptions of system-level cost. SafeWater XL describes system-level costs in terms of a
distribution. From the distribution, mean and median costs are available, as well as percentile
costs.
Model Structure
SafeWaterXL determines regulatory compliance costs for individual systems and subsequently
calculates a national average. To do so, each system is assigned a random concentration from an
occurrence distribution. This system concentration is distributed across the number of sites of
possible contamination for that system. The average number of sites per system is determined
based on the distribution of system intake sites for the size category as estimated from the
CWSS. However, SafeWaterXL does not assume that all sites are equally likely to exceed the
MCL standard. The likelihood of contamination is determined on a site-by-site basis. The sum
of the mean arsenic concentration of all sites within a system must equal the mean arsenic
concentration of the system. Given this upper bound, each site is assigned a concentration based
on the assumed relative standard deviation around the mean system occurrence.
The model then compares the concentration at each site to the revised MCL standard; no costs
are incurred for those sites whose concentrations fall below the specified MCL. If the site is
determined to be in violation of the MCL, then SafeWaterXL calculates the percent reduction 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 excess removal to account for system over-
design).1 A treatment train is then assigned to the site based on a decision tree for the size and
type of the system. The decision tree and the selected treatment train reflect the removal
efficiencies of the chosen technology. For example, a technology is chosen based on matching
'No blending is assumed for the POU technologies.
Chapter 6, Cost Analysis 6-17 Arsenic in Drinking Water Rule EA
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the removal efficiencies and the percentage removal required at the site (SafeWaterXL identifies
three categories of required removal: < 50 percent, 50-90 percent, > 90 percent).2
In this manner, capital and O&M costs are calculated at the site level for the selected treatment
train. The system's cost of compliance is then determined by summing across the treating sites.
For each system in SDWIS in which a violation is expected, a cost is calculated with this
method, thereby creating an estimate of national compliance costs. Since household costs are
also calculated for each system, a similar distribution of the cost of compliance at the household
level is also created.
In order to develop more detailed results, the compliance decision tree is employed at the site
level, so that only those sites requiring treatment would incur costs. The resulting total national
compliance cost is expected to be a truer representation of the impact of the Arsenic Rule on
systems. The sections below will describe the data needed to develop cost estimates for the
entire universe of systems affected by the Arsenic Rule. After the discussion of data
requirements, the SafeWaterXL model is described as it is used for this rule.
Model Inputs
Number of Systems: The universe of public and private ground and surface water systems is
taken from the Safe Drinking Water Information System (SDWIS), EPA's national regulatory
database for the drinking water program. Based on data extracted in December 1998, a total of
54,352 CWSs and 20,255 NTNCs are subject to the new requirements under the Arsenic Rule. It
is necessary to compile this data by system size, water source, and ownership, as costs may vary
by these characteristics. SafeWaterXL calculates costs for public and private systems (the latter
also includes "other" or "ancillary" systems), and surface and ground water systems. A summary
table of this breakdown is provided in Chapter 4, "Baseline Analysis."
Entry Points per System: SafeWaterXL estimates each system's cost of compliance at the
treatment site level. This modeling approach is used because a system may include more than
one treatment site. Entry points are used as a proxy for potential or actual points of treatment.
For example, a given water system may have three entry points: one entry point that currently
treats, while two may not have treatment in place. Data on the distribution of the number of
system entry points for each size category and type were extracted from the Community Water
Supply Survey (CWSS). Linear interpolation was used to estimate values for the number of sites
in cases where there were no survey data (see Chapter 4, "Baseline Analysis"). SafeWater XL
uses this modified distribution of entry points for each system size and source water category.
Population Served by System: A system's size is determined by the number of people served by
that system. These numbers were extracted from the SDWIS database (see Chapter 4, "Baseline
Analysis"). Systems are grouped into eight categories to help identify systems with related
characteristics so that any data or resources may be pooled during analysis.
2The > 90 percent removal efficiency category is not relevant under the revised MCL of 10 ug/L.
Chapter 6, Cost Analysis 6-18 Arsenic in Drinking Water Rule EA
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SafeWaterXL recognizes the following size categories:
< 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 system's size 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 Systems report (EPA, 1999b). The equation form is shown
below.
Average Flow aA "(Population) A
2 "Average Flow
Design Flow max \ ,„ , . ,&n
* ' aD -(Population) D
Where: aA, bA, aD, bD = the regression parameters derived for flow vs.
population
Population = the population served by the appropriate system type and
primary source.
The regression parameters used in the cost model are provided in Exhibit 6-5. Values are
provided for design and average flow for public and private ground water and surface water
supplies. SafeWaterXL divides the resulting system design flow and average daily flow (kgpd)
equally among all entry points. Treatment costs are calculated only at the sites that exceed the
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
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Exhibit 6-5
Flow Regression Parameters
by Water Source and System Ownership
Average Row
a b
Design Row
a b
Ground \Afeter
Riblic
Rivate
FLiblic-FLirch
Rivate-Rjrch
0.08558
0.06670
0.04692
0.05004
1.05840
1.06280
1.10190
1.08340
0.54992
0.41682
0.31910
0.32150
0.95538
0.96078
0.99460
0.97940
Surface Water
Riblic
Rivate
Rjbic-Rjrch
Rivate-Rjrch
0.14004
0.09036
0.04692
0.05004
0.99703
1.03340
1.11020
1.08340
0.59028
0.35674
0.20920
0.20580
0.94573
0.96188
1.04520
1.00840
Average Consumption per Household: Household costs depend on the average annual
consumption per residential connection. These mean estimates are provided in Chapter 4,
"Baseline Analysis." Depending on the system's characteristics, SafeWaterXL multiplies the
appropriate mean consumption per year (kgal) with the system's computed cost per thousand
gallons to arrive at the average annual cost of compliance per household for a community water
system.
Mean System Occurrence: Arsenic occurrence data are based on EPA's Arsenic Occurrence in
Public Drinking Water Supplies report (EPA, 2000) and are represented by a lognormal
distribution. Baseline occurrence is distinguished between ground and surface water systems and
is provided in Chapter 4 ("Baseline Analysis") as a lognormal distribution. The distribution is
truncated at 50 |ig/L, the current arsenic standard, because it is assumed that all arsenic
reductions attributable to the new standard start at the previous standard (i.e., all systems are
currently in compliance with the current standard).
For use in the SafeWaterXL model, EPA performed a regression analysis that weighted actual
occurrence data by National Arsenic Occurrence Survey region. The analysis resulted in the
distribution of ground and surface water systems exceeding arsenic concentrations greater than 3,
5, 10, and 20 |ig/L as presented in Exhibit 6-6.
Chapter 6, Cost Analysis
6-20
Arsenic in Drinking Water Rule EA
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Exhibit 6-6
Arsenic Occurrence Distribution
(Log-Normal Regression Results)
Source
GW
SW
% of systems greater than (p,g/L)
3 5 10
19.7 12.0 5.3
5.6 3.0 1.12
20
2.0
0.37
For ground water systems, the percentages displayed in Exhibit 6-6 above were based on a
lognormal distribution with a mean of-0.25071 and a log standard deviation of 1.58257. Among
surface water systems, the percentages were based on a lognormal distribution with mean
-1.67805 and a log standard deviation of 1.7425.
Relative Intra-System Standard Deviation of Arsenic Concentrations: The relative intra-system
standard deviation of the site concentrations within a system is calculated using data from a 25
State arsenic occurrence study (EPA, 2000b). SafeWaterXL uses a default value of 0.64. This
standard deviation is applied to the mean system concentration to generate individual entry points
concentrations within the system.
Compliance Decision Trees: The decision trees represent EPA's best estimate of the treatment
train technologies system operators will choose to achieve a particular percentage reduction in
arsenic concentration. Decision trees are specific to the system's size categories and source
water. These are provided in Appendix A.
Removal Efficiencies, Treatment Target, and Blending: Each treatment train is associated with an
arsenic removal efficiency that is assumed to be constant across system types. The removal
efficiencies for the 13 treatment trains available under the Arsenic Rule were presented in
Exhibit 6-1. SafeWaterXL employs 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
target. Blending uses the entry point concentration and treatment train removal efficiency to
determine the fraction of flow required to obtain the treatment target. The treatment target is set
at 80 percent of the MCL and represents the level to which systems will be over-designed to
ensure compliance with the MCL.
SafeWaterXL employs the blending principle through the following equation at the entry point
level:
Fraction of flow treated
( TreatmentTarset i) «(o/0 Site Flow)
SiteConcentration
% Removal Efficiency
Chapter 6, Cost Analysis
6-21
Arsenic in Drinking Water Rule EA
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Where: Treatment Target = the target MCL with 80 percent safety factor
Site Concentration = arsenic concentration at the site
% Removal Efficiency = percent removal efficiency of treatment train chosen
% Site Flow = percent of total flow at that site.
Note that the blending technique is used only for those systems expected to require less than 90
percent removal in order to achieve compliance with the new MCL standard. In addition,
SafeWaterXL does not employ this technique for those systems that select treatment trains
involving POU devices.
Equipment Life, Discount Rate and Capitalization Rates: System and State implementation costs
are tracked for a 20-year period. This time frame was selected because water systems often
finance their capital improvements over a 20-year period. This period of analysis may result in
an overestimate of annualized costs because many types of equipment last longer than 20 years.
Two different adjustments are made in this analysis in order to render future costs comparable
with current costs, reflecting the fact that a cost outlay today is a greater burden than an
equivalent cost outlay sometime in the future. The first adjustment is made when the cost
estimates that are derived are being used as an input in benefit-cost analysis. In this instance,
costs are annualized using a social discount rate so that the costs of each regulatory option can be
directly compared with the annual benefits of the corresponding regulatory option.
Annualization is the same process as calculating a mortgage payment; 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 Agency
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 analysis. The annualized costs of each
regulatory option are calculated and displayed using both a seven percent discount rate, required
by the Office of Management and Budget (OMB), and a three percent discount rate, which the
Agency believes more closely approximates 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 analysis, such as an affordability analysis or an analysis of system-
level costs or household-level costs. In these cases, rather than use a social discount rate when
determining the annualized costs, an actual cost-of-capital rate is used instead. This rate should
reflect the true after-tax cost of capital water systems face, net of any government grants or
subsidies. The cost of capital rates used in this analysis are shown in Exhibit 6-7.
Chapter 6, Cost Analysis 6-22 Arsenic in Drinking Water Rule EA
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Exhibit 6-7
Summary of Recommended Cost of Capital Estimates
(as of March 1998)
_ . . T 0. _ . Estimated After-Tax
Ownership Type Size Category _ , _ . .
Cost of Capital
NON-SMALL
ln\«stor owned 10,001-50,000
>50,000
Publicly owned 10,001-50,000
>50,000
SMALL
Pri\ate 1-500
501-10,000
Public 1-500
501-10,000
Source: Development of Cost of Capital Estimates
Water Systems (Draft Final Report). Prepared for U
5.26%
5.94%
5.26%
5.23%
4.17%
4.17%
5.10%
5.20%
for Public
.S. EPA by
Apogee/Hagler Bailly, Inc. under subcontract to International
Consultants, Inc. June 1998.
NTNC Costs
The cost for NTNCs is estimated using the mean values for system population for each system
service category, as shown in Chapter 4. As with the CWSs, cost is annualized over a 20-year
period, at discount rates of three and seven percent. Assumptions regarding the monitoring
schedule correspond to the monitoring schedule for small ground water systems, 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 non-
community 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
SDWIS, and include those systems as described in Geometries and Characteristics of Public
Water Supplies (see Exhibit 6-8). For each service area type, the report lists the number of
systems and the average population served. The non-food manufacturing service area combines
16 categories that were listed separately in the report. For this service area, the number of
systems is the sum of the 16 categories, and the average population served is the mean of the
individual populations weighted by the number of corresponding systems. Each of these systems
has only a single site.
System Flows and Treatment Choices: For each service area, both design and average flows have
been derived by the Agency using literature values and best engineering judgment. There are no
primary survey data for non-community water systems that are equivalent to the CWSS-
provided data for the community water system flow calculations (Smith, 1999). The design flow
is used to calculate the treatment capital costs, while the average flow is used in the operating
and maintenance cost equations.
Chapter 6, Cost Analysis
6-23
Arsenic in Drinking Water Rule EA
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For the non-transient non-community water supplies, one of two treatment technologies was
chosen based on the level of the design flow. For service areas with design flows less than 2,000
gallons per day, POE activated alumina is used; for all others, centralized activated alumina is
chosen (Kapadia, 1999a). Both treatment trains include pre-oxidation, and the centralized
activated alumina also includes non-hazardous landfilling of the spent media (Kapadia, 1999a).
Mean Arsenic Occurrence: The arsenic occurrence distribution used for ground water
community water supplies is also used for non-transient non-community water supplies. The
number of systems exceeding the MCL for each service area was calculated from the percent of
the distribution between the MCL and 100 |ig/L. For this analysis, 100 jig/L was chosen as the
upper concentration limit because the non-transient non-community supplies have not been
previously regulated, and occurrence values above the 50 jig/L regulatory level are possible.
Removal Efficiencies, Treatment Target, and Blending: The removal efficiency associated with
both POE activated alumina and centralized activated alumina is 95 percent. The NTNC model
uses this efficiency with the blending principle in the case of centralized activated alumina to
determine the amount of flow that requires treatment in order for the site to meet the treatment
target. The treatment target is set at 80 percent of the MCL and represents the level to which
systems will be over-designed to ensure compliance with the MCL. For POE activated alumina
systems, all the flow is treated, which may result in finished water below the treatment target
concentration.
Equipment Life, Discount Rate, and Capitalization Rates: As with the community water
supplies, the system implementation costs are tracked for a 20-year period. For the two service
areas using POE activated alumina, construction and forest service, the equipment is assumed to
last ten years with purchases in year zero and year ten. For the centralized activated alumina the
equipment is estimated to last 20 years. The cost estimates are annualized in the same manner as
those for the community water supplies.
Chapter 6, Cost Analysis 6-24 Arsenic in Drinking Water Rule EA
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Exhibit 6-8
Non-Transient Non-Community System Characteristics and
Compliance Decision Tree
Service Area Type
Daycare Centers
highway Rest Areas
Hotels/Motels
Interstate Carriers
Medcal Facilities
Mobile Horre 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 dubs
Landfills
Mning
Amusement Parks
Mlitary Bases
M grant Labor Camps
Msc. Recreation Services
Nursing Homes
Office Parks
Prisons
Retailers (Non-food related)
Retailers (Food related)
State Parks
Non-Water Utilities
Manufacturing: Food
Manufacturing: Non-Food
TOTAL
SYSTEM CHARACTERISTICS
Number of
Systems
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
20,255
Average
Population
Served Per
System
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
Design Flow
(mgd)
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
Average Daily
Flow (mgd)
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
DECISION TREE
Activated
Alumina
Point of
Entry
j
J
Centralized
Activated
Alumina
j
j
J
J
J
J
J
J
j
j
j
j
j
J
J
J
J
J
j
j
j
j
j
j
J
J
J
J
J
J
j
j
j
Source: Geometries and Characteristics of Public Water Systems, EPA, May 1999.
Chapter 6, Cost Analysis
6-25
Arsenic in Drinking Water Rule EA
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Very Large CWS Costs
EPA evaluated the regulatory costs of compliance for very large systems that will be subject to
the new Arsenic Rule. The nation's 25 largest drinking water systems (i.e., those serving one
million people or more) supply approximately 38 million people and generally account for about
15 to 20 percent of all compliance-related costs. Accurately determining these costs for future
regulations is critical. As a result, EPA has developed compliance cost estimates for the arsenic
and radon regulations for each individual system that serves more than one million persons.
These cost estimates help EPA to more accurately assess the cost impacts and benefits of the
Arsenic Rule. The estimates also help the Agency identify lower cost regulatory options and
better understand current water systems' capabilities and constraints.
The system costs were calculated for the 24 public water systems that serve a retail population of
more than one million persons and one public water system that serves a wholesale population of
16 million persons. The following are distinguishing characteristics of these very large systems:
(1) A large number of entry points from diverse sources;
(2) Mixed sources (i.e., ground and surface water);
(3) Occurrence not conducive to mathematical modeling;
(4) Significant levels of wholesaling;
(5) Sophisticated in-place treatment;
(6) Retrofit costs dramatically influenced by site-specific factors; and
(7) Large amounts of waste management and disposal, which can contribute
substantial costs.
Generic models cannot incorporate all of these considerations; therefore, in-depth
characterizations and cost analyses were developed using several existing databases and surveys.
The profile for each system contains information such as design and average daily flows,
treatment facility diagrams, chemical feed processes, water quality parameters, system layouts,
and intake and aquifer locations. System and treatment data were obtained from the following
sources:
(1) The Information Collection Rule (1997);
(2) The Community Water Supply Survey (1995);
(3) The Association of Metropolitan Water Agencies Survey (1998);
(4) The Safe Drinking Water Information System (SDWIS); and
(5) The American Water Works Association WATERSTATS Survey (1997).
While these sources contained much of the information necessary to perform cost analyses, the
Agency was still missing some of the detailed arsenic occurrence data in these large water
systems. Where major gaps existed, especially in ground water systems, occurrence data
obtained from the States of Texas, California, and Arizona; the Metropolitan Water District of
Southern California Arsenic Study (1993); the National Inorganic and Radionuclides Study
(EPA, 1984); and utility data were used. Based on data from the studies, detailed costs estimates
were derived for each of the very large water systems.
Chapter 6, Cost Analysis 6-26 Arsenic in Drinking Water Rule EA
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Cost estimates were generated for each system at several MCL options. The total capital costs
and operational and maintenance (O&M) costs were calculated using the profile information
gathered on each system, conceptual designs (i.e., vendor estimates and RSMeans), and modified
EPA cost models (i.e., Water and WaterCost models). The models were modified based on the
general cost assumptions developed in the Phase I Water Treatment Cost Upgrades (EPA,
1998c).
EPA consulted with the system operators to determine how each system would comply with
various MCL options and to assess the costs of their compliance responses. Preliminary cost
estimates were sent to all of the systems for their review. Approximately 30 percent of the
systems responded by submitting revised estimates and/or detailed arsenic occurrence data.
Based on the information received, EPA revised the cost estimates for those systems. EPA
developed cost estimates for three very large systems that are expected to have arsenic levels
above the revised MCL. These systems are located in Houston, TX, Phoenix, AZ, and Los
Angeles, CA. This analysis resulted in the estimated costs listed in Exhibit 6-9.
Exhibit 6-9
Annual Treatment Costs for Three Large CWSs Expected to
Undertake or Modify Treatment Practice to Comply with the Arsenic Rule
($ millions)
Large CWSs
Phoenix, AZ
Annual cost (3%)
Annual cost (7%)
Houston, TX
Annual cost (3%)
Annual cost (7%)
Los Angeles, CA
Annual cost (3%)
Annual cost (7%)
Population
Served
1,360,751
2,216,830
3,700,000
MCL (ug/L)
3
$ 11.6
$ 13.2
$ 15.0
$ 16.0
$ 1.8
$ 1.8
5
$ 5.5
$ 6.3
$ 2.7
$ 2.9
$ 1.8
$ 1.8
10
$ 2.2
$ 2.5
$ 0.9
$ 1.0
$
$
20
$ 0.0
$ 0.0
$ 0.5
$ 0.5
$
$
* Exhibit updated on December 28, 2000 to reflect minor changes in cost estimates which ha\« not
been incorporated into subsequent exhibits. The impact is a $0.07 million o\«restimation of
national costs (less than 0.5% of total national costs)
6.3 Results
This section presents the results of the national cost analysis. Unless otherwise specified,
national costs are presented in May 1999 dollars throughout this chapter.
6.3.1 National Costs
Exhibit 6-10 shows the total national cost breakdown across the four MCL options for the
Arsenic Rule. The system and state cost components of the total annual compliance costs are
Chapter 6, Cost Analysis
6-27
Arsenic in Drinking Water Rule EA
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presented at discount rates of three and seven percent. Expected system costs include treatment
costs, monitoring costs, and administrative costs of compliance. State costs include monitoring
and administrative costs of implementation. These cost components are also displayed.
CWS costs are approximately $668.0 million at the 3 |ig/L MCL, $396.0 million at the 5 |ig/L
MCL, $171.4 million at the 10 |ig/L MCL, and $62.4 million at the 20 |ig/L MCL (at a three
percent discount rate). State costs associated with CWS administration, at a three percent
discount rate, are approximately $1.4 million at the 3 |ig/L MCL, $1.1 million at the 5 |ig/L
MCL, $0.9 million at the 10 |ig/L MCL, and $0.7 million at the 20 |ig/L MCL.
The cost to NTNCs ranges from $28 million at the 3 |ig/L MCL, $16 million at the 5 |ig/L MCL,
$7.9 million at the 10 |ig/L MCL, and $3.5 million at the 20 |ig/L MCL (at a three percent
discount rate). State costs associated with NTNC administration, at a three percent discount rate,
are approximately $0.1 million for each MCL.
Exhibit 6-10
Annual National System and State Compliance Costs
($ millions)
Discount Rate
CWS
3% 7%
NTNC
3% 7%
TOTAL
3% 7%
MCL = 3 \iglL
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$665.9 $756.5
$2.2 $3.0
$1.4 $1.6
$669.4 $761.0
$27.2 $29.6
$1.0 $1.4
$0.1 $0.2
$28.3 $31.1
$693.1 $786.0
$3.2 $4.4
$1.5 $1.7
$697.8 $792.1
MCL=SHS/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$394.4 $448.5
$2.0 $2.8
$1.1 $1.3
$397.5 $452.5
$16.3 $17.6
$1.0 $1.3
$0.1 $0.2
$17.3 $19.1
$410.6 $466.1
$2.9 $4.1
$1.2 $1.4
$414.8 $471.7
MCL = 10 p,g/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$169.6 $193.0
$1.8 $2.5
$0.9 $1.0
$172.3 $196.6
$7.0 $7.6
$0.9 $1.3
$0.1 $0.2
$8.1 $9.1
$176.7 $200.6
$2.7 $3.8
$1.0 $1.2
$180.4 $205.6
MCL =20 na/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$60.7 $69.0
$1.7 $2.4
$0.7 $0.8
$63.2 $72.3
$2.6 $2.8
$0.9 $1.3
$0.1 $0.2
$3.6 $4.2
$63.3 $71.8
$2.6 $3.7
$0.9 $1.0
$66.8 $76.5
Chapter 6, Cost Analysis
6-28
Arsenic in Drinking Water Rule EA
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6.3.2 Costs by System Size and Type
This section presents the overall national compliance costs for water systems and for states at
three and seven percent discount rates. Exhibit 6-11 shows a detailed breakout of national
treatment costs by CWS size category for the various MCLs.
Exhibits 6-12 through 6-15 show the national treatment costs for NTNC systems by NTNC
system service type for each MCL.
Exhibit 6-11
Total Annual CWS Treatment Costs Across MCL Options
by System Size ($ millions)
System Size
MCL (ug/L)
3
5
3%
<100
101-500
501-1,000
1001-3300
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
> 1,000, 000
Total
$
$
$
$
$
$
$
$
$
$
19.8
42.6
25.5
83.8
95.1
179.1
66.0
124.3
29.7
665.9
$
$
$
$
$
$
$
$
$
$
7%
<100
101-500
501-1,000
1001-3300
3,301-10,000
10,001-50,000
50,001-100,000
100,001-1,000,000
> 1,000, 000
Total
$
$
$
$
$
$
$
$
$
$
21.3
46.4
28.9
97.4
109.2
205.4
75.0
140.5
32.5
756.5
$
$
$
$
$
$
$
$
$
$
Discount Rate
12.3
25.7
15.2
50.5
55.9
108.7
39.0
75.2
11.8
394.4
Discount Rate
13.2
28.0
17.2
58.8
64.2
124.7
44.3
85.0
13.0
448.5
10
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
5.5
11.5
6.7
22.0
24.3
47.0
16.7
32.3
3.8
169.6
5.9
12.5
7.6
25.6
27.9
53.9
19.0
36.5
4.3
193.0
20
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
$
2.1
4.3
2.5
8.1
9.0
16.7
6.2
11.3
0.6
60.7
2.3
4.6
2.8
9.4
10.3
19.2
7.0
12.7
0.6
69.0
Chapter 6, Cost Analysis
6-29
Arsenic in Drinking Water Rule EA
-------
Exhibit 6-12
Total Annual NTNC Treatment Costs at MCL 3 ug/L by System Service Type
(3% Discount Rate)
Service Area Type
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
TOTAL
# of Systems
Above the MCL
159
3
69
57
72
20
82
1,657
10
9
52
72
20
19
45
24
8
4
21
23
15
23
31
19
6
51
26
187
13
137
28
16
98
151
757
3,988
Average
Population
Served Per
System
76
407
133
123
393
185
370
358
230
145
173
76
60
53
50
160
98
39
42
101
44
113
418
395
63
87
107
136
1,820
174
322
165
170
372
168
Average Annual
System Cost
$5,217
$5,456
$6,153
$5,074
$13,540
$6,666
$5,140
$7,177
$5,217
$6,353
$16,456
$6,221
$5,059
$4,733
$5,229
$6,329
$6,132
$5,309
$4,783
$5,661
$5,226
$5,697
$6,025
$9,883
$5,554
$5,050
$7,748
$5,386
$45,851
$5,133
$5,261
$5,199
$5,763
$8,066
$5,944
Annual
National Costs
$831,099
$16,144
$425,252
$286,723
$978,452
$136,496
$423,058
$11,890,922
$54,445
$57,538
$861,907
$450,734
$100,600
$92,258
$235,789
$153,287
$49,505
$20,908
$100,771
$129,308
$80,268
$133,490
$188,625
$184,853
$36,090
$257,531
$198,316
$1,007,456
$605,012
$702,356
$147,101
$84,966
$563,970
$1,219,753
$4,500,232
$27,206,235
Chapter 6, Cost Analysis
6-30
Arsenic in Drinking Water Rule EA
-------
Exhibit 6-13
Total Annual NTNC Treatment Costs at MCL 5 ug/L by System Service Type
(3% Discount Rate)
Service Area Type
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
TOTAL
# of Systems
Above the MCL
97
2
42
34
44
12
50
1,009
6
6
32
44
12
12
28
15
5
2
13
14
9
14
19
11
4
31
16
114
8
83
17
10
60
92
461
2,429
Average
Population
Served Per
System
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
1,820
174
322
165
170
372
168
Average Annual
System Cost
$5,196
$5,428
$6,069
$5,062
$12,959
$6,547
$5,124
$7,024
$5,196
$6,255
$15,679
$6,132
$5,048
$4,733
$5,207
$6,233
$6,050
$5,282
$4,783
$5,610
$5,205
$5,644
$5,950
$9,548
$5,511
$5,040
$7,556
$5,354
$43,104
$5,117
$5,237
$5,179
$5,705
$7,853
$5,874
Annual
National Costs
$504,051
$9,763
$255,418
$174,207
$570,242
$81,640
$256,824
$7,086,564
$33,020
$34,500
$500,052
$270,563
$61,134
$56,180
$143,590
$91,929
$29,740
$12,667
$61,354
$78,033
$48,676
$80,527
$113,424
$108,754
$21,804
$156,519
$117,780
$609,795
$346,270
$426,424
$89,168
$51,542
$339,983
$723,165
$2,708,131
$16,253,442
Chapter 6, Cost Analysis
6-31
Arsenic in Drinking Water Rule EA
-------
Exhibit 6-14
Total Annual NTNC Treatment Costs at MCL 10 ug/L by System Service Type
(3% Discount Rate)
Service Area Type
Daycare Centers
Highway Rest Areas
Hotels/Motels
Interstate Carriers
Medical Facilities
Mobile Home Parks
Restaurants
Schools
Seruce Stations
Summer Camps
Water Wholesalers
Agricultural Products/Serwces
Airparks
Construction
Churches
Campgrounds/RV Parks
Fire Departments
Federal Parks
Forest Seruce
Golf and Country Clubs
Landfills
Mining
Amusement Parks
Military Bases
Migrant Labor Camps
Misc. Recreation Serwces
Nursing Homes
Office Parks
Prisons
Retailers (Non-food related)
Retailers (Food related)
State Parks
Non-Water Utilities
Manufacturing: Food
Manufacturing: Non-Food
TOTAL
# of Systems
Above the MCL
43
1
19
15
20
6
22
448
3
2
14
20
5
5
12
7
2
1
6
6
4
6
8
5
2
14
7
51
4
37
8
4
26
41
205
1,080
Average
Population
Served Per
System
76
407
133
123
393
185
370
358
230
145
173
76
60
53
50
160
98
39
42
101
44
113
418
395
63
87
107
136
1,820
174
322
165
170
372
168
Average Annual
System Cost
$5,168
$5,377
$5,956
$5,047
$12,174
$6,387
$5,103
$6,818
$5,168
$6,124
$14,628
$6,012
$5,034
$4,733
$5,177
$6,104
$5,938
$5,245
$4,783
$5,542
$5,176
$5,572
$5,848
$9,095
$5,452
$5,027
$7,298
$5,310
$39,380
$5,097
$5,205
$5,153
$5,627
$7,566
$5,780
Annual
National Costs
$222,846
$4,299
$111,420
$77,207
$238,133
$35,405
$113,692
$3,057,578
$14,599
$15,014
$207,398
$117,930
$27,101
$24,974
$63,471
$40,017
$12,977
$5,592
$27,278
$34,263
$21,517
$35,340
$49,558
$45,053
$9,589
$69,397
$50,567
$268,854
$140,629
$188,796
$39,394
$22,794
$149,069
$309,707
$1,184,505
$7,036,973
Chapter 6, Cost Analysis
6-32
Arsenic in Drinking Water Rule EA
-------
Exhibit 6-15
Total Annual NTNC Treatment Costs at MCL 20 ug/L by System Service Type
(3% Discount Rate)
Service Area Type
Daycare Centers
Highway Rest Areas
Hotels/Motels
Interstate Carriers
Medical Facilities
Mobile Home Parks
Restaurants
Schools
Seruce Stations
Summer Camps
Water Wholesalers
Agricultural Products/Services
Airparks
Construction
Churches
Campgrounds/RV Parks
Fire Departments
Federal Parks
Forest Seruce
Golf and Country Clubs
Landfills
Mining
Amusement Parks
Military Bases
Migrant Labor Camps
Misc. Recreation Serwces
Nursing Homes
Office Parks
Prisons
Retailers (Non-food related)
Retailers (Food related)
State Parks
Non-Water Utilities
Manufacturing: Food
Manufacturing: Non-Food
TOTAL
# of Systems
Above the MCL
16
0
7
6
7
2
8
169
1
1
5
7
2
2
5
2
1
0
2
2
2
2
3
2
1
5
3
19
1
14
3
2
10
15
77
407
Average
Population
Served Per
System
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
1,820
174
322
165
170
372
168
Average Annual
System Cost
$5,135
$5,318
$5,823
$5,029
$11,259
$6,201
$5,078
$6,577
$5,135
$5,970
$14,025
$5,873
$5,018
$4,733
$5,143
$5,953
$5,808
$5,203
$4,783
$5,462
$5,142
$5,488
$5,729
$8,568
$5,383
$5,012
$6,997
$5,259
$35,041
$5,073
$5,167
$5,121
$5,536
$7,231
$5,670
Annual
National Costs
$83,500
$1,603
$41,085
$29,013
$83,054
$12,962
$42,666
$1,112,336
$5,470
$5,520
$74,986
$43,442
$10,187
$9,418
$23,777
$14,718
$4,786
$2,091
$10,287
$12,734
$8,061
$13,127
$18,310
$16,360
$3,570
$26,091
$18,282
$100,420
$47,189
$70,861
$14,748
$8,544
$55,308
$111,625
$438,184
$2,574,315
Chapter 6, Cost Analysis
6-33
Arsenic in Drinking Water Rule EA
-------
6.3.3 Costs per Household
Household level costs are considered a good proxy for the affordability of rule compliance with
regard to CWSs, since water systems recover costs at the household level through increased
water rates. This of course assumes that non-residential customers of water systems, such as
businesses, can pass along any increase in water costs to their customers through increased prices
on their goods or services. In order to calculate the number of households served by systems that
will treat, the expected number of treating systems is multiplied by the average number of
households per system (varies by system type and size). Exhibit 6-16 presents the total number
of households served by CWSs that treat, by size category.
Exhibit 6-16
Number of Households in CWSs Expected to Treat
by Size Category and MCL (M9/L) Option
3
5
10
20
<100
94,484
58,774
26,369
10,439
101-500
368,092
228,149
104,373
40,089
501-1,000
360
219
101
40
,709
,872
,866
,498
3,300
1,002,937
623,156
288,986
116,517
3,301-
10,000
1,619,822
1,019,288
475,599
193,541
10,001-
50,000
3,228,544
2,077,421
997,880
405,714
50,001-
100,000
1,453,603
905,886
469,157
188,798
100,001-
1,000,000
3,014,841
1,938,268
936,602
364,907
11
7
3
1
Total
,143,032
,070,814
,400,833
,360,503
SafeWaterXL determines household costs separately for each affected CWS, by first dividing the
CWS's annual compliance cost by the CWS's average daily flow (1,000 gallons per day), and
then multiplied by 365 days to determine the CWS's cost of compliance per 1,000 gallons
produced. Finally, the CWS's cost of compliance per 1,000 gallons (kgal) is multiplied by the
average annual consumption per residential connection (kgal), to arrive at the average annual cost
of compliance per household for the CWS. The estimates of average annual consumption per
residential connection used in this analysis are provided in Chapter 4, "Baseline Analysis."
Given expected household costs for each individual system, the average is then calculated for
each size category. Exhibit 6-17 shows the average annual household costs by system size,
across the four regulatory options.
The range of household costs for the MCL of 10 |ig/L ranges from less than $1 to approximately
$327; the costs for the MCL of 3 |ig/L range from less than $7 to $317; the costs for the MCL of
5 ng/L, range from less than $3 to $318; and the costs for the MCL of 20 |ig/L range from less
than $1 to $351.
In the smallest two size categories, average household costs decrease as the MCL decreases.
This somewhat counterintuitive result is due to the $500.00 affordability cap assumed in the
SafeWater XL simulations. As more systems are forced over the affordability cap, the systems'
costs are fixed at the costs associated with the POU technology. This results in lower average
household costs for these systems.
Chapter 6, Cost Analysis 6-34 Arsenic in Drinking Water Rule EA
-------
Exhibit 6-17
Average Annual Household Costs Across MCL Options by System Size
System Size
<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
All categories
MCL (^g/L)
3
$317.00
$166.91
$74.81
$63.76
$42.84
$38.40
$31.63
$25.29
$7.41
$41.34
5
$318.26
$164.02
$73.11
$61.94
$40.18
$36.07
$29.45
$23.34
$2.79
$36.95
10
$326.82
$162.50
$70.72
$58.24
$37.71
$32.37
$24.81
$20.52
$0.86
$31.85
20
$351.15
$166.72
$68.24
$54.36
$34.63
$29.05
$22.63
$19.26
$0.15
$23.95
Exhibits 6-18 through 6-21 compare the distribution of annual household costs across public
water systems serving fewer than 10,000 people, for MCLs of 3, 5, 10, and 20, respectively. The
exhibits demonstrate the maximum annual costs that different percentages of households in
treating systems face. Comparison of Exhibits 6-18 through 6-21 illustrates that regulatory
compliance costs decrease across MCLs. This observation is depicted by the consistent shift to
the left of cost curves across system size categories, when comparing incremental increases in the
MCL.
Chapter 6, Cost Analysis
6-35
Arsenic in Drinking Water Rule EA
-------
100% -
90%
80%
o 70%
O
I
•5
HI
3
§
O
fe
Q.
60%
50%
40%
30%
20%
10%
Exhibit 6-18
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 3 ug/L
$100 $200 $300 $400 $500
Maximum Annual Household Treatment Costs
$600
100% -,
0
I
HI
90%
80%
70%
Exhibit 6-1 9
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 5 ug/l_
10%
$100 $200 $300 $400 $500
Maximum Annual Household Treatment Costs
$600
Chapter 6, Cost Analysis
6-36
Arsenic in Drinking Water Rule EA
-------
100% n
90%
80%
• 70%
1
0
a
s
HI
Q.
60%
50%
40%
30%
20%
10%
Exhibit 6-20
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 10 ug/L
$100 $200 $300 $400 $500
Maximum Annual Household Treatment Costs
$600
100% -
3
O
I
•5
at
3
40%
30%
20%
10%
Exhibit 6-21
Annual Treatment Costs Per Household Across CWSs
Expected to Treat and Serving < 10,000 People
MCL 20 ug/l_
$100 $200 $300 $400 $500
Maximum Annual Household Treatment Costs
$600
Chapter 6, Cost Analysis
6-37
Arsenic in Drinking Water Rule EA
-------
6.4 National Compliance Costs Uncertainty Analysis
The national cost estimates discussed throughout this chapter were developed within the
SafeWaterXL modeling framework so that EPA could fully describe the variation in compliance
costs among systems in a single size category (rather than just the average cost for systems within
a size category). Hence, for each CWS size category, a distribution of compliance costs was
estimated. These distributions are now used to access the uncertainty inherent in the national
cost estimates.
A parametric bootstrap model was developed to estimate the distribution of national compliance
costs.3 The following steps were followed:
1. The distribution of costs for each CWS size and ownership cluster was pulled
from the SafeWaterXL model results for an MCL of 10 |ig/L.
2. The number of CWSs expected to modify or install treatment in each CWS size
and ownership cluster was pulled from the SafeWaterXL model results for an
MCLoflO|ig/L.
3. For each CWS size and ownership cluster, the model pulled a number of
observations from the distribution of costs associated with that CWS size and
ownership cluster (from step 1). The number of observations pulled was equal to
the number of CWSs expected to modify or install treatment in each CWS size
and ownership cluster (from step 2).
4. The observations (from step 3) were summed across all CWS size and ownership
clusters to calculate a single estimate of national costs for CWSs.
5. No cost distributions are available for the NTNC systems and the very large
CWSs. Therefore, after each single estimate of national costs for CWSs (from
step 4) was calculated, the mean costs for very large CWSs and NTNC systems
were added to it to calculate a single total national cost estimate.
6. Steps 3 through 5 were repeated 3,000 times to calculate a distribution of total
national costs.
The distribution of total national costs is shown in Exhibit 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 Exhibit 6-23. As this exhibit shows, the 10th and
90th percentile confidence interval for total national costs are $190 million and $227 million
respectively.
3 Only treatment costs were included in the uncertainty analysis. Also, the uncertainty analysis was
conducted assuming a commercial discount rate. Although this commercial discount rate varies by CWS size and
ownership, it approximates five percent for all PWSs.
Chapter 6, Cost Analysis 6-38 Arsenic in Drinking Water Rule EA
-------
o
-------
2
5
E
3
0
Exhibit 6-23
National Compliance Costs Uncertainty Analysis
Cumulative Distribution (MCL 10 ug/L)
Simulated MEAN = $199,166,463
Simulated STANDARD DEVIATION = $19 362 659
National Compliance Costs ($ Millions)
Chapter 6, Cost Analysis
6-40
Arsenic in Drinking Water Rule EA
-------
Chapter 7: Comparison of Costs and Benefits
7.1 Introduction
In this EA, EPA has analyzed the costs and benefits of regulating arsenic concentrations in
drinking water to four different MCL standards. The four options considered reflect increasing
levels of protection against exposure to arsenic in drinking water, employing a range of MCLs
from 20 |ig/L to 3 |ig/L. As the MCL provisions for the four options become increasingly strict,
the associated costs and benefits also increase incrementally. Chapter 5 ("Benefits Analysis")
describes in detail the estimated national health benefits of the Arsenic Rule options, while
Chapter 6 ("Cost Analysis") describes the projected national compliance cost estimates. This
chapter presents a summary and comparison of the national costs and benefits and a cost-
effectiveness analysis for each of the MCL options.
7.2 Summary of National Costs and Benefits
7.2.1 National Cost Estimates
National compliance costs to public water systems (PWSs) for treatment (both annualized capital
and operating and maintenance costs), monitoring and administrative activities, and costs to
States, including any one-time start-up costs, for regulatory implementation and enforcement,
were estimated and described in Chapter 6. The national costs for PWSs to comply with the four
MCL options range from $66.8 million (MCL=20 |ig/L) to $697.8 million (MCL=3 |ig/L)
annually based on a discount rate of three percent. Assuming a seven percent discount rate, the
range of total national cost for community water systems ranges from $76.5 million to $792.1
million annually.
7.2.2 National Benefits Estimates
Chapter 5 contains a detailed summary of the methodology used to estimate a range 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 range from $66.2 million (MCL=20 |ig/L) to $213.8 million (MCL=3
|ig/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 |ig/L to $490.9 million annually at an MCL of 3 |ig/L.
7.3 Comparison of Benefits and Costs
This section presents a comparison of total national benefits and costs for each of the Arsenic
Rule options considered. Three separate analyses are considered, including a summary of
benefit/cost ratios and net benefits, a direct comparison of aggregate national costs and benefits,
and the results of a cost-effectiveness analysis of each regulatory option.
Chapter 7, Comparison of Costs and Benefits 7-1 Arsenic in Drinking Water Rule EA
-------
7.3.1 National Net Benefits and National Benefit-Cost Comparison
Exhibit 7-1 describes the net benefits and the benefit/cost ratios under various MCL options for
PWSs at three and seven percent discount rates. Except for the upper bound benefit scenario at a
discount rate of three percent, the net benefits are negative and decreasing as the Arsenic Rule
MCL options become increasingly more stringent. For the same categories, the benefit/cost
ratios are less than one and decrease as the MCL becomes more stringent. For nearly all of the
options, costs outweigh the quantified benefits, with benefit/cost ratios all below or equal to one.
For example, the ratios range from 0.3 (MCL=3 |ig/L) to 1.0 (MCL=20 |ig/L) at a seven percent
discount rate. For the upper bound scenario at three percent the benefit/cost ratio exceeds one at
an MCL of 10 |ig/L and 20 |ig/L. Of the MCL options examined, the net benefits and benefit/cost
ratio are maximized at an MCL of 10 jig/L and a three percent discount rate.
Exhibit 7-1
Summary of Annual National Net Benefits and Benefit-Cost Ratios
($ millions)
MCL (u,g/L)
3
5
10
20
3% Discount Rate
•a
^
o
£2
a>
_o
•a
^
o
.Q
&_
a>
a.
a.
^
Net Benefits
Benefit/Cost Ratio
Net Benefits
Benefit/Cost Ratio
$ (484.0)
0.3
$ (206.8)
0.7
$ (223.7)
0.5
$ (59.2)
0.9
$ (40.8)
0.8
$ 17.3
1.1
$ (0.6)
1.0
$ 8.5
1.1
7% Discount Rate
lower bound
•a
c
^
o
£2
i_
a>
a.
a.
^
Net Benefits
Benefit/Cost Ratio
Net Benefits
Benefit/Cost Ratio
$ (578.3)
0.3
$ (301.1)
0.6
$ (280.6)
0.4
$ (116.1)
0.8
$ (66.0)
0.7
$ (7.9)
1.0
$ (10.3)
0.9
$ (1.2)
1.0
"Costs include treatment, O&M, monitoring, and administrative costs to CWSs and NTNCs and State costs
for administration of water programs.
Chapter 7, Comparison of Costs and Benefits
7-2
Arsenic in Drinking Water Rule EA
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Exhibit 7-2 graphically depicts the absolute difference between the total value of national costs
and benefits under each proposed MCL at a seven percent discount rate.
Exhibit 7-2
Comparison of Costs and Benefits
(7% Discount Rate, in $ millions)
$900.0
Exhibit 7-3 depicts the incremental costs and benefits of the rule as one moves from a less
stringent standard to a more stringent standard. Moving to an MCL of 20 |ig/L from the current
MCL of 50 |ig/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 |ig/L to 10 |ig/L results in
incremental costs of $129.1 million and incremental benefits of between $73.4 million and
$122.4 million. Moving beyond an MCL of 10 |ig/L towards a more stringent standard results in
incremental costs that far outweigh the incremental benefits, even under the upper bound benefits
scenario.
Chapter 7, Comparison of Costs and Benefits
7-3
Arsenic in Drinking Water Rule EA
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0
E
Exhibit 7-3
Comparison of Incremental Costs and Benefits
(7% Discount Rate, in $ millions)
$350.0
10
20
n Costs
$320.5
$266.0
$129.1
$76.5
H Benefits (upperbound)
$135.4
$157.9
$122.4
$75.3
0 Benefits (lower bound)
$22.7
$51.5
$73.4
$66.2
Exhibit 7-4 shows the results of an analysis in which the average national cost of achieving each
unit reduction in cases of cancer avoided was calculated. The average 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 ranges from $5.0 million to
$12.2 million at an MCL of 3 |ig/L, from $4.1 million to $8.1 million at an MCL of 5 |ig/L, from
$3.2 million to $4.8 million at an MCL of 10 |ig/L, and from $3.4 million to $3.5 million at an
MCL of 20 |ig/L. At a seven percent discount rate, the cost per cancer case avoided ranges from
$5.7 million to $13.8 million at an MCL of 3 |ig/L, from $4.7 million to $9.2 million at an MCL
of 5 |ig/L, from $3.7 million to $5.5 million at an MCL of 10 |ig/L, and from $3.9 million to $4.0
million at an MCL of 20 |ig/L.
Chapter 7, Comparison of Costs and Benefits
7-4
Arsenic in Drinking Water Rule EA
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Exhibit 7-4
Cost per Cancer Case Avoided
($ millions)
Arsenic Level
(jiQ/L)
lower bound**
upper bound**
3% Discount Rate
3
5
10
20
$
$
$
$
12.2
8.1
4.8
3.5
$
$
$
$
5.0
4.1
3.2
3.4
7% Discount Rate
3
5
10
20
$
$
$
$
13.8
9.2
5.5
4.0
$
$
$
$
5.7
4.7
3.7
3.9
"Lower/upper bounds correspond to estimates of bladder cancer cases awided.
7.3.2 Cost-Effectiveness
Cost-effectiveness analysis is another commonly used measure of the economic efficiency with
which regulatory options are meeting the intended regulatory objectives. Exhibit 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
the trend in marginal cost and benefits (expressed as health effects avoided) between each point
on these curves (corresponding to each MCL option). Points along these lines represent each
increment of cost that is incurred in order to achieve the next increment of risk reduction, i.e.,
additional cancer case avoided. The steepness of the curves under both benefits scenarios
suggests that additional increments of risk reduction and benefits are achieved at increasingly
greater cost to the nation.
Chapter 7, Comparison of Costs and Benefits
7-5
Arsenic in Drinking Water Rule EA
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Exhibit 7-5
Comparison of Annual Costs to Cases of Cancer per Year
(7% Discount Rate)
$900
40 60 80 100 120
Cancer Cases Avoided per Year
140
160
•based on lower bound estimates of avoided cases
-based on upper bound estimates of avoided cases
Exhibit 7-6 further reinforces the fact that as the MCL becomes more stringent, the incremental
cost per cancer case avoided increases. For example, the additional cases of cancer avoided in
moving from an MCL of 10 |ig/L to 5 |ig/L are achieved at a cost per case of $3.6 million
annually under the high bound and seven percent discount rate scenario. Similarly, in moving
from an MCL of 5 jig/L to a more stringent MCL of 3 |ig/L, the cost per case avoided increases
to $2.4 million per year under this same scenario.
Chapter 7, Comparison of Costs and Benefits
7-6
Arsenic in Drinking Water Rule EA
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Exhibit 7-6
Incremental Cost per Incremental Cancer Case Avoided
(7% Discount Rate, in $ millions)
$60.0
$50.0
-------
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 skin cancer, there are also a large number of other health effects associated with
arsenic, as presented in Exhibit 7-7, which are not monetized in this analysis, due to lack of
appropriate data.
Exhibit 7-7
Total Annual Cost, Estimated Monetized Total Cancer Health Benefits, and
Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs
Arsenic
Level
(M9/L)
3
5
10
20
Total Annual
Cost (7%)
$792.1
$471.7
$205.6
$76.5
Annual Bladder
Cancer Health
Benefits1'2
$58.2 -$156.4
$52.0 -$11 3.3
$38.0 - $63.0
$20.1 -$21.5
($ millions
Annual Lung
Cancer Health
Benefits1'2
$155.6 -$334.5
$139.1 -$242.3
$101 .6 -$134.7
$46.1 - $53.8
Total Annual
Health Benefits1'2
$21 3.8 -$490.9
$191.1 -$355.6
$139.6 -$197.7
$66.2 - $75.33
Potential Non-Quantifiable
Health Benefits
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
1 May 1999 dollars.
2 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c).
3 For 20 pg/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 pg/L using the estimates adjusted for uncertainty.
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 is the primary point-of-use
treatment, and it is expected that very small systems will use this treatment to a significant
extent. (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 7, Comparison of Costs and Benefits
Arsenic in Drinking Water Rule EA
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7.5 Benefits-Costs Uncertainty Analysis
The uncertainty surrounding the national cost of compliance was described in Chapter 6.
Exhibit 7-8 superimposes the distribution of national compliance costs onto the range of
monetized benefits associated with the rule at an MCL of 10 |ig/L. This exhibit illustrates that
there is approximately a 50 percent probability that the costs of the rule will be lower than the
monetized benefits of the rule under the upper bound benefit assumption.
Exhibit 7-8
National Compliance Costs and Benefits Uncertainty Analysis
Cumulative Cost Distribution vs. Benefits Range (MCL 10 ug/L)
100.00% -i
RANGE OF NATIONAL
BENEFITS
RANGE OF NATIONAL
COSTS
o
($ Millions)
Chapter 7, Comparison of Costs and Benefits
7-9
Arsenic in Drinking Water Rule EA
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Chapters: Economic Impact Analyses
8.1 Introduction
The Environmental Protection Agency (EPA) is required to perform a series of analyses that
addresses the distribution of regulatory impacts associated with the Arsenic Rule. This chapter
presents analyses that support EPA's compliance with the following Federal mandates:
• Executive Order 12886 (Regulatory Planning and Review);
Regulatory Flexibility Act (RFA) of 1980, as amended by the Small Business Regulatory
Enforcement Fairness Act (SBREFA) of 1996;
• National Affordability determination required by the 1996 amendments to the Safe
Drinking Water Act (SOWA);
Unfunded Mandates Reform Act (UMRA) of 1995;
• Technical, Financial, and Managerial Capacity Assessment required by Section
1420(d)(3) of the 1996 amendments to the Safe Drinking Water Act (SOWA);
• Executive Order 13045 (Protection of Children From Environmental Health Risks and
Safety Risks);
• Executive Order 12989 (Federal Actions to Address Environmental Justice in Minority
Populations and Low-Income Populations);
• Paperwork Reduction Act;
Health Risk Reduction and Cost Analysis (HRRCA) as required by Section 1412(b)(3)(C)
of the 1996 SDWA Amendments; and
• Initial Regulatory Flexibility Analysis (IRFA).
These analyses draw on the cost analyses presented in Chapter 6 and an analysis of
administrative requirements presented in a separate document, Information Collection Request
for the Arsenic Rule.
Several of these Federal mandates require an explanation of why the rule is necessary, the
statutory authority upon which it is based, and the primary objectives it is intended to achieve.
Background information on the problems addressed by the rule, and EPA's statutory authority for
promulgating the rule, are presented in Chapter 2. In this chapter, Section 8.2 presents the RFA
and SBREFA analysis 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
Federal rules. The minimization of economic burden, UMRA, system 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
environmental justice issues, and Section 8.10 contains the HRRCA.
8.2 Regulatory Flexibility Act and Small Business Regulatory Enforcement
Fairness Act
The RFA provides that, whenever an agency promulgates 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 general notice of rulemaking, the agency must prepare an initial and final regulatory
Chapter 8, Economic Impact Analyses 8-1 Arsenic in Drinking Water Rule EA
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flexibility analysis. The agency must prepare such an analysis when proposing a rule (or
promulgating a final rule) unless the head of the agency certifies that the rule will not have a
significant economic impact on a substantial number of small entities. EPA did not certified that
the proposed regulation would not have a significant economic impact on a substantial number of
small entities. Consequently, the Agency prepared an initial analysis of the proposal and,
because it has not certified the final rule, has now completed a final regulatory flexibility
analysis. EPA prepared these analyses in compliance with the requirements of the RFA
Under the RFA, the term "small entity" means "small business," "small governmental
jurisdiction" and "small organization." These terms are further defined by the Act. In the case of
a "small business," the term has the same meaning as a "small business concern" under section 3
of the Small Business Act. (Regulations of the Small Business Administration (SB A) at 13 CFR
121.201 have defined small businesses for Standard Industrial Classification (SIC) codes.)
"Small governmental jurisdiction" means the government of cities, counties, towns and villages,
among others, with a population of less than 50,000. A "small organization" is any not-for-profit
enterprise that is independently owned and operated. The RFA authorizes an agency to establish
other definitions of such terms which are appropriate to the agency's activities and publish such
definitions in the Federal Register after consultation with SBA and opportunity for public
comment. 5 U.S.C. § 601(3), (4) & (5).
8.2.1 Description of the Initial Regulatory Flexibility Analysis
The Regulatory Flexibility Act requires EPA to complete an Initial Regulatory Flexibility
Analysis (IRFA) addressing the following:
1. The need for the rule;
2. The objectives of and legal basis for the rule;
3. A description of, and where feasible, an estimate of the number of small entities to
which the rule will apply;
4. A description of the reporting, record keeping, and other compliance requirements
of the rule, including an estimate of the types of small entities that will be subject
to the requirements and the type of professional skills necessary for preparation of
reports or records;
5. An identification, to the extent practicable, of all relevant Federal rules that may
duplicate, overlap, or conflict with the rule; and
6. A description of "any significant regulatory alternatives" to the rule that
accomplish the stated objectives of the applicable statutes, and that minimize any
significant economic impact of the rule on small entities. Significant regulatory
alternatives may include:
Chapter 8, Economic Impact Analyses 8-2 Arsenic in Drinking Water Rule EA
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• • Establishing different compliance or reporting requirements or timetables
that take into account the resources of small entities;
• • Clarifying, consolidating, or simplifying compliance and reporting
requirements under the rule for small entities;
• • Using performance rather than design standards; and
Exempting small entities from coverage of the rule or any part of the rule.
If the initial assessment determines that a substantial number of small entities may face
significant impacts as a result of the rule, then a formal regulatory flexibility analysis may be
required.
Defining "Small Entities" Affected by the Rule
The Regulatory Flexibility Act (RFA) defines small entities as including "small businesses,"
"small governments," and "small organizations" (5 USC 601). The RFA references the
definition of "small business" found in the Small Business Act, which authorizes the Small
Business Administration (SBA) to further define "small business" by regulation. The SBA
defines small business by category of business using Standard Industrial Classification (SIC)
codes (13 CFR 121.201). For example, in the manufacturing sector, the SBA generally defines
small business in terms of number of employees; in the agriculture, mining, electric, gas, and
sanitary services sectors, the SBA generally defines small businesses in terms of annual receipts
(ranging from $0.5 million for crops to $25 million for certain types of pipelines). The RFA also
authorizes an agency to adopt an alternative definition of "small business" "where appropriate to
the activities of the Agency" after consultation with the SBA and opportunity for public
comment.
For the revised Arsenic Rule small entities are defined as those water systems that meet the
following criteria:
•• A "small business" is any small business concern that is independently owned and
operated and not dominant in its field as defined by the Small Business Act (15 USC
632). Examples of public water systems within this category include small, privately
owned, public water systems and for-profit businesses where provision of water may be
ancillary, such as mobile home parks or day care centers.
•• A "small organization" is any not-for-profit enterprise that is independently owned and
operated, not dominant in its field, and operates a public water system. Examples of
small organizations are churches, schools, and homeowners associations.
•• A "small governmental jurisdiction" is a city, county, town, school district or special
district with a population of less than 50,000 (5 USC 601) that operates a public water
system.
In 1998, EPA proposed that PWSs with populations of 10,000 or fewer persons be defined as
"small entities" within the context of the Consumer Confidence Report (CCR) rulemaking (63
FR 7620, February 13, 1998). EPA requested public comments on this alternative definition.
Chapter 8, Economic Impact Analyses 8-3 Arsenic in Drinking Water Rule EA
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For this rulemaking, the SB A Office of Advocacy agreed with the Agency's alternative
definition. EPA intends to define "small entity" in the same way for RFAs under SBREFA for
all future drinking water regulations, including the revised Arsenic Rule.
EPA selected this alternative definition for small water systems for several reasons:
•• A large proportion (94 percent) of all PWSs are small entities, although they serve
a minority of the population. Larger PWSs (those serving over 10,000 persons)
serve the majority of the population receiving water from public water systems.
•• 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 system size level.1 In general, the size
of a PWS is an important financial characteristic, as larger systems can spread
investments in fixed assets across a broader customer base. Smaller water
systems typically serve primarily residential customers. Larger systems have
fewer residential customers as a percentage of total water sales and more
commercial customers. Annual sales revenue per connection is significantly
higher for nonresidential than for residential connections.2 Similarly, larger
publicly owned systems are more likely to have rated bond issuances, another
indicator of financial strength.3
•• In the 1996 Amendments to the Safe Drinking Water Act (SDWA), several
measures creating regulatory relief defined small community water systems as
those serving 10,000 or fewer customers. One provision allows for alternative
means of delivery of the CCRs by systems serving 10,000 or fewer persons.
Another used the same cutoff for modifications to monitoring requirements and
for certain penalty provisions delegated to the States.4
•• EPA has previously used this criterion in both rulemaking and implementation
activities pertaining to PWSs. The total trihalomethane (TTHM) rule
promulgated by EPA in 1979 applied only to systems serving more than 10,000
persons. EPA chose the 10,000 cutoff in 1979 primarily out of a concern that
smaller systems would have to divert resources from other activities to comply
with the rule. In 1992, EPA initiated a regulatory negotiation process that resulted
in regulatory actions to provide additional protection from microbial contaminants
in drinking water while reducing health risks from disinfection byproducts. The
Interim Enhanced Surface Water Treatment Rule promulgated from this process
Community Water Systems Survey, Volume I: Overview, U.S. EPA Office of Water, p. 26. January 1997.
2 Id.,p. 14.
3 Id., p. 28.
House Report No. 104-632 (Commerce Committee), June 24, 1996 in US Code Congressional and Administrative News
(USCCAAN), 1996, 4, pp. 1373, 1401 and 1409, discussing §§132(b) and 1418(a) of the House bill.
Chapter 8, Economic Impact Analyses 8-4 Arsenic in Drinking Water Rule EA
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applied only to systems serving more than 10,000. The companion rule, the
Stage 1 Disinfection Byproducts Rule, deferred compliance with part of the
requirements for systems serving 10,000 or fewer persons.
For purposes of this analysis, therefore, "small entity" refers to any public water system that
serves 10,000 or fewer persons. Exhibit 8-1 shows the universe of small PWSs potentially
affected by the new arsenic standard.
Exhibit 8-1
Profile of the Universe of Small Water Systems
Regulated Under the Arsenic Rule
Type Water
System
Publicly-Owned:
cws
NCWS
Privately-Owned:
CWS
NCWS
Total Systems:
CWS
NCWS
TOTAL
System Size Category
<100
1,729
1,783
13,640
8,178
15,369
9,961
25,330
101-500
5,795
3,171
11,266
4,162
17,061
7,333
24,394
501-1,000
3,785
1,182
2,124
902
5,909
2,084
7,993
1,001-3,300
6,179
361
1,955
411
8,134
772
8,906
3,301-10,000
3,649
29
654
56
4,303
85
4,388
Source: Safe Drinking Water Information System (SDWIS), December 1998 freeze.
Determining What Number Constitutes a Substantial Number
In this analysis approximately 71,013 PWSs are defined as small entities. EPA SBREFA
guidance has several different criteria for what constitutes a substantial number of affected
entities.1 One of the criteria is that no more than 20 percent of systems affected by the revised
Arsenic Rule may experience economic impacts of one percent of their revenues or greater.
Measuring Significant Impacts
To evaluate the impact that a small entity is expected to incur as a result of the rule, this analysis
calculates the entity's ratio of annualized compliance costs as a percentage of sales (for privately
owned systems) or the entity's ratio of annualized compliance costs as a percentage of annual
governmental revenue or expenditures (for publicly owned systems). EPA guidance suggests
using one percent as a threshold for determining significance, although additional factors may be
considered. If compliance costs are less than one percent of sales or revenues, the regulation may
in most cases be presumed to have no significant impact on a substantial number of small
entities.5
'id.
Chapter 8, Economic Impact Analyses
8-5
Arsenic in Drinking Water Rule EA
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Categorizing Systems
EPA categorized affected small entities according to the categories identified in the SBREFA
guidance (i.e., small business, small government, and small organization). Public water system
inventories, managed by EPA and other organizations, traditionally categorize public water
systems by size and by the characteristics of the population served (i.e., community water system,
non-community water system). Therefore, detailed information by SIC or data on revenues or
sales are not readily available.
Estimating Revenue by RFA Category
The estimated revenues for small entities in Exhibit 8-2 are from the Bureau of the Census6; EPA
chemical monitoring reform rulemaking; and additional data on independent privately owned
CWSs, special districts, and authorities, which are from the CWS Survey. Exhibit 8-2 also
shows the numbers of small businesses, governments, and organizations, obtained using
information from EPA's Baseline Handbook.7 These numbers were used to determine the
weighted averages of estimated average revenue, as described in the column "Average Estimated
Revenues per System."
Small government systems include municipal, county, State, Federal, military, and special district
systems. Data on revenue for townships and municipalities were obtained from the 1992 Census
of Governments, converted to 1999 dollars by applying a conversion factor calculated from the
national income and product account tables of the U.S. Bureau of Economic Analysis.8
Specifically, the price deflators for 1992 and 1999 were obtained from Table 7.11, Chain-Type
Quantity and Price Indexes for Government, Chain-Type Price Indexes for State and Local
Governments. The average revenue for all small government PWSs was calculated at
$2,333,119.
Small businesses include both CWSs and NTNCWSs, such as privately owned community water
systems, mobile home parks, country clubs, hotels, manufacturers, hospitals, and other
establishments. For this analysis, all hospitals and day care centers were assumed to be
businesses. Although some hospitals may be nonprofit, they have unusually high revenues and
were included in the small business category to make the estimated revenue for small
organizations more conservative. Estimated average revenue for the small businesses affected by
the revised Arsenic Rule is $2,675,582.
61992 Census of Governments, GC92 (4)-4: Finances of Municipal and Township Governments, U.S. Dept. of
Commerce, Bureau of the Census.
Drinking Water Baseline Handbook Second Edition, EPA Contract No. 68-C6-0039. Prepared by International
Consultants, Inc.
8Methodology recommended by Bruce E. Baker, State and Local Governments, Government Division, U.S. Bureau of
Economic Analysis.
Chapter 8, Economic Impact Analyses 8-6 Arsenic in Drinking Water Rule EA
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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 ug/L)
Number of
Systems
Average
Estimated
Revenues per
System
Average
Compliance
Cost Per
System
Cost to
Revenue
Ratio
Water Systems that will Modify or Install Treatment
Small Government
Small Business
Small Organizations
All Small Entities
1,116
2,318
472
3,907
$2,333,119
$2,675,582
$5,990,914
$2,978,546
$41,999
$13,466
$6,828
$20,816
1.8001%
0.5033%
0.1140%
0.6989%
Water Systems that will Only Monitor
Small Government
Small Business
Small Organizations
All Small Entities
20,587
38,131
8,389
67,106
$2,333,119
$2,675,582
$5,990,914
$2,984,958
$37
$39
$53
$40
0.0016%
0.0015%
0.0009%
0.0014%
All Water Systems
Small Government
Small Business
Small Organizations
All Small Entities
21,703
40,449
8,861
71,013
$2,333,119
$2,675,582
$5,990,914
$2,984,605
$2,195
$809
$414
$1,183
0.0941%
0.0302%
0.0069%
0.0396%
Small organizations include primarily nonprofit NTNCWSs such as schools and homeowners
associations. The estimates for small nonprofit organizations serving more than 500 people are
actually higher than those for small businesses because the total number of such systems is small,
and a large proportion of these organizations are schools and colleges with large budgets. This
category also includes 50 percent of systems classified as "other." The average estimated
revenue for small organizations affected by the revised Arsenic Rule is $2,978,546.
EPA also calculated the average estimated revenue for all small entities. This estimate is
weighted to account for the number of small entities in each category (government, business, and
organization) affected by the revised Arsenic Rule. This overall average is $2,833,552.
Conducting the Screening Analysis
The final task of the initial assessment is to conduct the screening analysis and determine
whether the rule is expected to result in significant economic impacts on a substantial number of
small entities. The screening analysis involves the following three steps:
(1) Estimate the compliance cost of the rule to small PWSs. Estimated average per-
system compliance costs associated with the revised Arsenic Rule were taken
from the estimate prepared by EPA and presented in Chapter 6.
Chapter 8, Economic Impact Analyses
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Arsenic in Drinking Water Rule EA
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(2) Obtain data on the number of small PWSs and their revenues or expenditures.
The number of small PWSs expected to modify or install treatment are found in
Exhibit 8-2. These numbers are derived from the results of the SafeWaterXL
model described in Chapter 6.
(3) Compute small entity impacts. Using the data obtained in the preceding steps,
EPA calculated the ratio of total annual compliance costs as a percentage of
revenues or expenditures. These ratios, converted into percentages, are presented
in Exhibit 8-2 in the column "Cost to Revenue Ratio."
8.2.2 Initial Regulatory Flexibility Analysis Results
The results of the initial regulatory flexibility analysis are summarized below. As seen in
Exhibits 8-2 and 8-3, at a maximum contaminant level (MCL) of 10 |ig/L, 3,907 small PWSs are
expected to have to modify or install treatment.
Exhibit 8-3
Number of CWSs Expected to Undertake or Modify Treatment Practice
MCL 10
15,000
13,500
Exhibit 8-3 compares the number of CWSs expected to be affected by the promulgation of the
new standard to the number of systems not expected to undertake or modify any of their existing
treatment practices. Six percent of small CWSs and NTNC water systems are expected to have to
modify or install treatment.
EPA compared the ratio of compliance cost to revenue to the threshold value for significant
impacts of one percent under the revised arsenic standard of 10 |ig/L. In Exhibit 8-2, the ratios
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are displayed separately for small governments, small businesses, and small organizations, and
cumulatively for all small entities.
A significant impact is generally defined as costs equal to or greater than one percent of
revenues. Costs are equal to or greater than one percent of revenues only among small
government entities that are expected to modify or install treatment at the revised MCL. The vast
majority of water systems will see impacts less than one percent of their annual revenue.
However, EPA's estimates show a number of small systems that will incur significant costs.
Therefore, EPA is not certifying this rule as having no significant impact on small entities.
8.2.3 Summary of EPA's Small Business Consultations
As required by section 609(b) of the RFA, as amended by SBREFA, EPA also conducted
outreach to small entities and convened a Small Business Advocacy Review Panel to obtain
advice and recommendations of representatives of the small entities that potentially would be
subject to the rule's requirements.
EPA identified 22 representatives of small entities, in this situation small systems, that were most
likely to be subject to the proposal. In December 1998, EPA prepared and distributed to the
small entity representatives (SERs) an outreach document on the Arsenic Rule titled
"Information for Small Entity Representatives Regarding the Arsenic in Drinking Water Rule"
(EPA, 1998 ).
On December 18, 1998, EPA held a SER conference call for small systems from Washington,
DC, to provide a forum for input on key issues related to the planned proposal of the Arsenic in
Drinking Water Rule. These issues included, but were not limited to, issues related to the rule
development, such as arsenic health risks, treatment technologies, analytical methods, and
monitoring. Fifteen SERs from small water systems participated on the call from the following
States: Alabama, Arizona, California, Georgia, Massachusetts, Montana, Nebraska, New
Hampshire, New Jersey, Utah, Virginia, Washington, and Wisconsin.
Efforts to identify and incorporate small entity concerns into this rulemaking culminated with the
convening of a SBAR Panel on March 30, 1999, pursuant to section 609 of RFA/SBREF A. The
four person Panel was headed by EPA's Small Business Advocacy Chairperson and included the
Director of the Standards and Risk Management Division within EPA's Office of Ground Water
and Drinking Water, the Administrator of the Office of Information and Regulatory Affairs with
the Office of Management and Budget, and the Chief Counsel for Advocacy of the SB A. For a
60-day period starting on the convening date, the Panel reviewed technical background
information related to this rulemaking, reviewed comments provided by the SERs, and met on
several occasions. The Panel also conducted its own outreach to the SERs and held a conference
call on April 21, 1999, with the SERs to identify issues and explore alternative approaches for
accomplishing environmental protection goals while minimizing impacts to small entities.
Consistent with the RFA/SBREFA requirements, the Panel evaluated the assembled materials
and small-entity comments on issues related to the elements of the IRFA (See Section 8.2.1). A
copy of the June 4, 1999, Panel report is included in the docket for the Arsenic Rule (U.S. EPA,
1999).
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The revised rule addresses all of the recommendations on which the Panel reached consensus. In
addition, to help small systems comply with the Arsenic Rule, EPA is committed to addressing
several other Panel recommendations regarding guidance, which are discussed in detail in the
pages to follow.
Treatment Technologies, Waste Disposal, and Cost Estimates
The Panel recommended the following: further develop the preliminary treatment and waste
disposal cost estimates; fully consider these costs when identifying affordable compliance
technologies for all system size categories; and provide information to small water systems on
possible options for complying with the MCL, in addition to installing any listed compliance
technologies.
In response to these recommendations, the Treatment and Cost document describes development
of cost estimates for treatment and waste disposal; identification of affordable compliance
technologies, including the consideration of cost; and options for complying with the MCL other
than installing compliance technologies, such as selecting to regionalize.
Regarding 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 systems where
appropriate; account for all costs, including costs that may not routinely be explicitly calculated;
consider liability issues from POU/point-of-entry (POE) devices when evaluating their
appropriateness as compliance technologies; and investigate waste disposal issues with POE
devices.
In response to these recommendations, EPA included in the revised rule's preamble an expanded
description regarding available POU compliance treatment technologies and conditions under
which POU treatment may be appropriate for very small systems; a description of the
components that contribute to the POU cost estimates; and a discussion that clarifies that water
systems will be responsible for POU operation and maintenance to prevent liability issues from
customers maintaining equipment themselves.
Relevance of Other Drinking Water Regulations
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 technologies and determining whether they are nationally
affordable for small systems; and encourage systems to be forward-looking and test for multiple
contaminants to determine if and how they would be affected by the upcoming rules. In
response, the revised rule's preamble includes a discussion on the co-occurrence analysis 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. In addition, the preamble encourages systems to consider other upcoming rules when
making future plans for monitoring or treatment.
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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 regulatory
requirements; consider revising its approach to national affordability criteria, to the extent
allowed by statutory and regulatory requirements, to address the concern that the current
cumulative approach for adjusting the baseline household water bills is based on chronological
order rather than risk; and examine the data in the 1995 Community Water Supply Survey to
determine if in-place treatment baselines can be linked with the current annual water bill baseline
in each of the size categories for the revised Arsenic Rule.
In response to these recommendations, the treatment section of the revised rule's preamble
includes an expanded discussion about the national affordability criteria and how it may be
adjusted to account for new regulations. In addition, information regarding methodology and
rationale is available to explain the national affordability approach.
Monitoring and Arsenic Species
The Panel recommended the following: that EPA consider allowing States to use recent
compliance monitoring data to satisfy initial sampling requirements or to obtain a waiver; and
that EPA continue to explore whether or not to make a regulatory distinction between organic
and inorganic arsenic based on compliance costs and other considerations.
In response, the monitoring section of the rule's preamble describes the allowance of monitoring
data that meet analytical requirements and have reporting limits sufficiently below the revised
MCL and collected after 1990.
Considerations in Setting the MCL
The Panel recommended the following: in performing its obligations under SDWA, EPA should
take cognizance of the scientific findings, the large scientific uncertainties, the large potential
costs (including treatment and waste disposal costs), and the fact that this standard is scheduled
for review in the future; give full consideration to the provisions of the Executive Order 12866
and to the option of exercising the new statutory authority under SDWA §1412(b)(4)(C) and
§1412(b)(6)(A) in the development of the Arsenic Rule; and fully consider all of the "risk
management" components of its rulemaking effort to ensure that the financial and other impacts
on small systems 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.
In response to all these recommendations, EPA has described in detail the factors that were
considered in setting in the MCL and provides the rationale for this selection.
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Applicability of Proposal
The Panel recommended that EPA carefully consider the appropriateness of extending the scope
of the rule to non-transient non-community water systems (NTNCWSs).
In response, EPA has broadened the rule to include NTNCWSs. 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 coverage of these water systems.
Other Issues
The Panel recommended that EPA encourage small systems to discuss their infrastructure needs
for complying with the Arsenic Rule with their primacy agency to determine their eligibility for
Drinking Water State Revolving Fund (DWSRF) loans, and if eligible, to ask for assistance in
applying for the loans. In response, the UMRA analysis has been expanded to discuss funding
options for small systems and to encourage systems to be proactive in communicating with their
primacy agency.
Regarding health effects, the Panel recommended the following: further evaluate the Utah study
and its relationship to the studies on which the NRC report was based and give it appropriate
weight in the risk assessment for the revised arsenic standard; and examine the NRC
recommendations in the light of the uncertainties associated with the report's recommendations,
and any new data that may not have been considered in the NRC report. In response to these
recommendations, the benefits analysis includes a discussion of the qualitative benefits
evaluation and use of research data.
8.2.4 Small System Affordability
Section 1415(e)(l) of SDWA allows States to grant variances to small water systems (i.e.,
systems having fewer than 10,000 customers) in lieu of complying with an MCL if EPA
determines that there are no nationally affordable compliance technologies for that system
size/water quality combination. The system must then install an EPA-listed variance treatment
technology (§1412(b)(15)) that makes progress toward the MCL, if not necessarily reaching it.
To list variance technologies, three showings must be made:
(1) EPA must determine, on a national level, that there are no compliance
technologies that are affordable for the given small system size category/source
water quality combination.
(2) If there is no nationally affordable compliance technology, then EPA must identify
a variance technology that may not reach the MCL but that will allow small
systems to make progress toward the MCL (it must achieve the maximum
reduction affordable). This technology must also be listed as a small systems
variance technology by EPA in order for small systems to be able to rely on it for
regulatory purposes.
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(3) EPA must make a finding on a national level, that use of the variance technology
would be protective of public health.
States must then make a site-specific determination for each system as to whether or not the
system can afford to meet the MCL based on State-developed affordability criteria. If the State
determines that compliance is not affordable for the system, it may grant a variance, but it must
establish terms and conditions, as necessary, to ensure that the variance is adequately protective
of human health.
In the Agency's draft national-level affordability criteria published in the August 6, 1998 Federal
Register, EPA discussed the affordable treatment technology determinations for the contaminants
regulated before 1996. The national-level affordability criteria were derived as follows. First an
"affordability threshold" was calculated. The affordability threshold was based on the total
annual household water bill as a percentage of household income. In developing this threshold
value, EPA considered the percentage of median household income spent by an average
household on comparable goods and services such items as housing (28 percent), transportation
(16 percent), food (12 percent), energy and fuels (3.3 percent), telephone (1.9 percent), water and
other public services (0.7 percent), entertainment (4.4 percent) and alcohol and tobacco (1.5
percent).
Another of the key factors that EPA used to select an affordability threshold was cost
comparisons with other risk reduction activities for drinking water. Section 1412(b)(4)(E)(ii) of
the SDWA identifies both point-of-entry and point-of-use devices as options for compliance
technologies. EPA examined the projected costs of these options. EPA also investigated the
costs associated with supplying bottled water for drinking and cooking purposes. The median
income percentages that were associated with these risk reduction activities were: POE (> 2.5
percent), POU (2 percent) and bottled water (> 2.5 percent).
Based on the foregoing analysis, 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 system category was then subtracted from this threshold to
determine the additional expenditure per household that was considered affordable for new
treatment. This difference is referred to as the "available expenditure margin." Based on EPA's
1995 Community Water System Survey, median water bills were about $250 per year for small
system customers. Thus, an average available expenditure margin of up to $500 per year per
household was considered affordable for the contaminants regulated before 1996. EPA next
identified treatment technologies for all pre-1996 contaminants with average per household costs
below $500 per year. Therefore, it was not necessary to list any small system variance
technologies for existing contaminant rules.
Applying this criterion to the case of arsenic in drinking water, EPA has determined that
affordable technologies exist for all system size categories and has therefore not identified a
variance technology for any system size or source water combination at an MCL of 10 |ig/L (see
Exhibit 8-4). In other words, annual household costs after installation of the compliance
technology are projected to be below the available affordability threshold for all system size
categories for MCLs of 3, 5, 10, and 20 |ig/L.
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Exhibit 8-4
Mean Annual Costs to Households Served by CWSs, by Size Category
System Size
<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
All categories
MCL (^g/L)
3
$317.00
$166.91
$74.81
$63.76
$42.84
$38.40
$31.63
$25.29
$7.41
$41.34
5
$318.26
$164.02
$73.11
$61.94
$40.18
$36.07
$29.45
$23.34
$2.79
$36.95
10
$326.82
$162.50
$70.72
$58.24
$37.71
$32.37
$24.81
$20.52
$0.86
$31.85
20
$351.15
$166.72
$68.24
$54.36
$34.63
$29.05
$22.63
$19.26
$0.15
$23.95
EPA recognizes that individual water systems may have higher than average treatment costs,
fewer than average households to absorb these costs, or lower than average incomes, but believes
that the affordability criteria should be based on characteristics of typical systems and should not
address situations where costs might be extremely high or low or excessively burdensome. EPA
believes that there are other mechanisms that may address these situations to a certain extent. In
any case, EPA believes that small system variances should be the exception and not the rule.
EPA expects the available expenditure margin to be lower than $500 per household per year for
the Arsenic Rule because some sources of data, for example the Current Population Survey,
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
regulations promulgated after 1996, but before the Arsenic Rule is promulgated.
EPA notes, however, that high water costs are often associated with systems that have already
installed treatment to comply with an NPDWR. 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 technology. Assuming
that systems with high baseline water costs would need to install a new treatment technology to
comply with an NPDWR may thus overestimate the actual costs for some systems.
To investigate this issue, during the derivation of the national-level affordability criteria, EPA
examined a group of five small surface water systems with annual water bills above $500 per
household per year. All of these systems had installed disinfection and filtration technologies to
comply with the Surface Water Treatment Rule. If these systems were required to install
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treatment to comply with the revised arsenic standard, modification of the existing processes
would be much more cost-effective than adding a new technology. As a result, because these
systems have already made the investment in treatment technology, and the cost is incorporated
into current annual household water bills, costs to the household may not increase substantially.
Installing new technologies may interfere with in-place treatment or require additional treatment
to address side effects, which will increase costs over the arsenic treatment technology base
costs. For example, EPA assumed that CWSs would put corrosion control in place when the
percent removal required was greater than 90 percent.
EPA believes that there is another mechanism in the SDWA to address cost impacts on small
systems composed primarily of low-income households. Systems that meet criteria established
by the State could be classified as disadvantaged communities under §1452(d) of the SDWA.
They can receive additional subsidization under DWSRF, including forgiveness of principal.
Under DWSRF, States must provide a minimum of 15 percent of the available funds for loans to
small communities and have the option of providing up to 30 percent of the grant to provide
additional loan subsidies to the disadvantaged systems, as defined by the State.
8.3 Coordination With Other Federal Rules
Several Federal drinking water rules are under development involving treatment requirements
that may relate to the treatment of arsenic for this drinking water rule. Although it is very
difficult to determine how compliance with the Arsenic Rule might affect compliance with other
drinking water regulations, the following briefly describes each rule, the impact the Arsenic Rule
may have on that rule, and/or how each rule may impact the arsenic standard. The Arsenic Rule
will be promulgated in a similar time frame as the Ground Water Rule, the Radon Rule, and the
Microbial and Disinfection By-Product Rule.
8.3.1 Ground Water Rule (GWR)
The goals of the GWR 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, EPA
has the responsibility to develop a GWR that not only specifies the appropriate use of
disinfection, but also addresses other components of ground water systems. This general
provision is supplemented with an additional requirement that EPA develop regulations
specifying the use of disinfectants for ground water systems as necessary. To meet these
requirements, EPA is working with stakeholders to develop a final GWR by Spring 2001.
The GWR will result in more systems using disinfection. If a system does add a disinfection
technology, it may contribute to arsenic pre-oxidation. This largely depends on the type of
disinfection technology employed. For example, if a system chooses a technology such as
ultraviolet radiation, it may not affect arsenic pre-oxidation. However, if it chooses chlorination,
it will contribute to arsenic pre-oxidation. Arsenic pre-oxidation from arsenic (HI) to arsenic (V)
will enhance the removal efficiencies of the technologies. Another option is that systems may
use membrane filtration for the GWR. In that case, depending on the size of the membrane,
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some arsenic removal can be achieved. Thus, the GWR is expected to alleviate some of the
burden of the Arsenic Rule.
8.3.2 Radon
EPA proposed the Radon Rule in November 1999. One option for compliance with the Radon
Rule that systems may employ is coagulation and assisted microfiltration. This technology will
be sufficient to meet the revised arsenic standard as well. Thus, the Radon Rule is expected to
alleviate some of the burden of the Arsenic Rule.
8.3.3 Microbial and Disinfection By-Product Regulations
To control disinfection and disinfection by-products and to strengthen control of microbial
pathogens in drinking water, EPA has developed a group of interrelated regulations, as required
by the SDWA. These regulations, referred to collectively as the Microbial Disinfection By-
product (M/DBP) Rules, are intended to address risk trade-offs between the two different types
of contaminants.
EPA proposed a Stage 1 Disinfectants/Disinfection By-Products Rule (DBPR) and Interim
Enhanced Surface Water Treatment Rule (TESWTR) in July 1994. EPA issued the final Stage 1
DBPR and IESWTR in November 1998.
The Agency has finalized and is currently implementing a third rule, the Information Collection
Rule, that will provide data to support development of subsequent M/DBP regulations. These
subsequent rules include a Stage 2 DBPR and a companion Long-Term 2 Enhanced Surface
Water Treatment Rule (LT2ESWTR).
Stage 1 DBPR and IESWTR will primarily affect large surface water systems; thus, EPA does
not expect much overlap with small systems treating for arsenic. Stage 2 DBPR and possibly the
LT2ESWTR, however, could have significance as far as arsenic removal is concerned. For
systems removing DBF precursors, systems may use nanofiltration. The use of nanofiltration
would also be relevant for removing arsenic, and as a result, would ease some burden when
systems implement these later rules.
8.4 Minimization of Economic Burden
The revised Arsenic Rule includes several provisions that will insure that the economic burden to
water systems is minimized, while still ensuring that the public health objectives of the rule are
met. First, the rule is developed around the concept of a performance target known as the
maximum contaminant level (MCL). Rather than prescribe a single treatment technique that
must be installed in all water systems, EPA is only requiring those systems that currently provide
finished water with an arsenic concentration above the target to undertake or modify treatment.
As seen above, this will exclude the vast majority of systems from having to undertake any
additional treatment under the revised Arsenic Rule. In addition, if a system does have to
undertake or modify treatment, EPA is allowing systems to choose from a broad list of
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technologies and is encouraging systems to choose the treatment technique that minimizes their
total costs.
Second, EPA is allowing States to grant nine-year monitoring waivers to those systems 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
systems that currently provide finished water with low arsenic concentrations.
Finally, EPA is allowing small systems with finished water concentrations above the revised
MCL to install POU technologies. This option will further allow small systems to minimize their
total cost of compliance with the revised rule.
8.5 Unfunded Mandates Reform Act
Title H of the Unfunded Mandates Reform Act of 1995 (UMRA), P.L. 104-4, establishes
requirements for Federal agencies to assess the effects of their regulatory actions on State, local,
and Tribal governments, and the private sector. Under UMRA Section 202, EPA generally must
prepare a written statement, including a cost-benefit analysis, for proposed and final rules with
"Federal mandates" that may result in expenditures to State, local, and Tribal governments, in the
aggregate, or to the private sector, of $100 million or more in any one year.
Before promulgating an EPA rule for which a written statement is needed, Section 205 of the
UMRA generally requires EPA to identify and consider a reasonable number of regulatory
alternatives and adopt the least costly, most cost-effective or least burdensome alternative that
achieves the objectives of the rule. The provisions of Section 205 do not apply when they are
inconsistent with applicable law. Moreover, Section 205 allows EPA to adopt an alternative
other than the least costly, most cost-effective, or least burdensome alternative if the
Administrator publishes an explanation why the more "costly" alternative was preferred for the
final rule.
Prior to establishing any regulatory requirements that may significantly or uniquely affect small
governments, including Tribal governments, EPA must develop a small government agency plan
under Section 203 of the UMRA. The plan must provide for notifying potentially affected small
governments; enabling officials of affected small governments to have meaningful and timely
input in the development of EPA regulatory proposals with significant Federal intergovernmental
mandates; and informing, educating, and advising small governments on compliance with the
regulatory requirements.
EPA has determined that this rule contains a Federal mandate that may result in expenditures of
$100 million or more for State, local, and Tribal governments, in the aggregate and the private
sector in any one year. Accordingly, under Section 202 of the UMRA, EPA is obligated to
prepare a written statement addressing:
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1. The authorizing legislation;
2. Cost-benefit analysis including an analysis of the extent to which the costs of State, local,
and Tribal governments will be paid for by the Federal government;
3. Estimates of future compliance costs and disproportionate budgetary effects;
4. Macro-economic effects;
5. A summary of EPA's consultation with State, local, and Tribal governments and their
concerns, including a summary of the Agency's evaluation of those comments and
concerns; and
6. Identification and consideration of regulatory alternatives and the selection of the least
costly, most cost-effective or least burdensome alternative that achieves the objectives of
the rule.
The legislative authority for the Arsenic Rule is discussed in Chapter 2. Items two through five
are addressed below, with the exception of future compliance costs, which are discussed in
Chapter 6. Regulatory alternatives, the last item, are addressed in Chapters 3, 6, and 7.
8.5.1 Social Costs and Benefits
Chapters 5, 6, and 7 contain a detailed cost-benefit analysis in support of the Arsenic Rule. At a
seven percent discount rate, the Arsenic Rule is expected to have a total annualized cost of
$792.1 million for a MCL of 3 |ig/L, $471.7 million for a MCL 5 |ig/L, $205.6 million for a
MCL of 10 |ig/L, and $76.5 million for a MCL of 20 |ig/L.
EPA estimates that the Arsenic Rule will have total health benefits as a result of avoided bladder
and lung cancer cases of approximately $213.8 to $490.9 million if the MCL were set at 3 |ig/L,
$191.1 to $355.6 million if the MCL were set at 5 |ig/L, $139.6 to $197.7 million if the MCL
were set at 10 |ig/L, and $66.2 to $75.3 million if the MCL were set at 20 |ig/L. These monetized
health benefits of reducing arsenic exposures 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 exposure), there are annual fatal cancers and non-fatal cancers
associated with arsenic exposures through CWSs. At an arsenic MCL level of 3 |ig/L, an
estimated 33 to 74 fatal cancers and 25 to 64 non-fatal cancers per year are prevented; at a
arsenic level of 5 |ig/L, an estimated 29 to 54 fatal cancers and 22 to 47 non-fatal cancers per
year are prevented; at 10 |ig/L, 21 to 30 fatal and 16 to 26 non-fatal cancers per year are
prevented; and at 20 |ig/L, 10 to 11 fatal and approximately 9 non-fatal cancers per year are
prevented. A more detailed discussion of the total cancer risk and health benefits calculation
may be found in Chapter 5, "Benefits Analysis."
In addition to quantifiable benefits, in Chapter 5, EPA has identified many potential non-
quantifiable benefits associated with reducing arsenic exposures in drinking water. These
potential benefits are not able to be quantified at this time, but may include reduced risk of skin
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cancer and numerous non-cancerous health effects. In addition, certain non-health related
benefits may exists, such as ecological improvements and an increase in consumers' perception
of drinking water.
8.5.2 State Administrative Costs
States will incur a range of administrative costs in complying with the Arsenic Rule.
Administrative costs can include program management, inspections, and enforcement activities.
EPA estimates that the total annual costs of State administrative activities for compliance with
the MCL at a seven percent discount rate are approximately $1.7 million for an MCL of 3 |ig/L,
$1.4 million for an MCL of 5 |ig/L, $1.2 million for an MCL of 10|ig/L, and $1.0 million for an
MCLof20|ig/L.
Various Federal programs exist to provide financial assistance to State, local, and Tribal
governments in complying with this rule. The Federal government provides funding to States
that have a primary enforcement responsibility for their drinking water programs through the
Public Water Systems Supervision (PWSS) Grants program. Additional funding is available
from other programs administered either by EPA or other Federal agencies. These include the
Drinking Water State Revolving Fund (DWSRF) and Housing and Urban Development's
Community Development Block Grant Program. For example, the SDWA authorizes the
Administrator of the EPA to award capitalization grants to States, which in turn can provide low-
cost loans and other types of assistance to eligible public water systems. The DWSRF also
assists public water systems with financing the costs of infrastructure needed to achieve or
maintain compliance with SDWA requirements. Each State will have considerable flexibility to
determine the design of its program 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 DWSRF allotments for each fiscal year to assist in running the State drinking water
program.
Under PWSS Program Assistance Grants, the Administrator may make grants to States to carry
out public water system supervision programs. One State use of these funds is to develop
primacy programs. States may "contract" with other State agencies to assist in the development
or implementation of their primacy program. However, States may not use program assistance
grant funds to contract with regulated entities (i.e., water systems). PWSS Grants may be used
by States to set up and administer a State program that includes such activities as public
education, testing, training, technical assistance, development and administration of a
remediation grant and loan or incentive program (excludes the actual grant or loan funds), or
other regulatory or non-regulatory measures.
8.5.3 Future Compliance Costs and Disproportionate Budgetary Effects
To meet the requirement in Section 202 of the UMRA, EPA analyzed future compliance costs
and possible disproportionate budgetary effects of the MCL options. The Agency believes that
the cost estimates, shown in Exhibit 8-5 and discussed in more detail in Chapter 6, accurately
characterize future compliance costs of the revised rule.
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With regard to the disproportionate impacts, EPA considered available data sources in analyzing
the disproportionate impacts upon geographic or social segments of the nation or industry. To
the extent that there may be disproportionate impacts to low-income or other segments of the
population, EPA will prepare a small entity compliance guide, a monitoring/analytical manual,
and a small systems technology 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) Reviewing the impacts on small versus large systems;
(2) Reviewing the costs to public versus private water systems; and
(3) Reviewing the household costs for the revised rule.
The first measure, the national impacts on small versus large systems, is shown in Exhibit 8-5.
Small systems are defined as those systems serving 10,000 people or less, and large systems are
those systems serving more than 10,000 people.
The second measure of disproportionate impacts evaluated is the relative total costs to public
versus private water systems, by size. Exhibit 8-5 also presents the annual system level costs for
public and private systems by system size category for MCLs of 3 |ig/L, 5 |ig/L, 10 |ig/L, and 20
Hg/L. The costs are slightly lower for private systems across system sizes for all options. For
example, for systems serving less than 100 people at the 10 |ig/L MCL public system costs are
$7,948, and private system costs are $6,335.
Chapter 8, Economic Impact Analyses 8-20 Arsenic in Drinking Water Rule EA
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Exhibit 8-5
Average Annual Cost per CWS Exceeding the MCL, by Ownership
System Size
Treatment and Monitoring Costs
Public
Private
Total Cost
All Systems
MCL = 3 uglL
<100
101-500
501-1,000
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
$ 10,360,933
$ 6,388
$ 12,033
$ 21,659
$ 51,687
$ 112,397
$ 621,841
—
$ 6,546
$ 13,042
$ 23,720
$ 58,672
$ 129,531
$ 644,176
$ 10,360,933
MCL = 5 uglL
<100
101-500
501-1,000
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
$ 4,129,338
$ 6,384
$ 11,762
$ 21,175
$ 49,055
$ 103,388
$ 584,831
—
$ 6,551
$ 12,712
$ 23,146
$ 56,911
$ 120,621
$ 598,488
$ 4,129,338
WICL = 10 uglL
<100
101-500
501-1,000
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
$ 1,340,716
$ 6,335
$ 11,357
$ 20,042
$ 46,243
$ 98,138
$ 477,614
—
$ 6,494
$ 12,358
$ 22,100
$ 53,086
$ 111 ,646
$ 531,584
$ 1,340,716
MCL = 20 uglL
<100
101-500
501-1,000
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
$ 6,209
$ 11,065
$ 18,877
$ 42,869
$ 85,201
$ 443,463
-
$ 6,361
$ 11,902
$ 20,595
$ 48,779
$ 101,374
$ 475,909
$ 189,916
*Costs were calculated at a commercial interest rate and include system
treatment, monitoring, and administrative costs; note that systems serving over
1 million people are public surface water systems.
Chapter 8, Economic Impact Analyses
8-21
Arsenic in Drinking Water Rule EA
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The third measure, household costs, can also be used to gauge the impact of a regulation and to
determine whether there are disproportionately higher impacts in particular segments of the
population. A detailed analysis of household cost impacts by system size is presented in Chapter
6. The costs for households served by public and private water systems are presented in Exhibit
8-6. As expected, cost per household increases as system size decreases. Cost per household is
usually higher for households served by smaller systems than larger systems. This holds because
smaller systems produce less water than large systems and are therefore unable to utilize
economies of scale. Consequently, each household must bear a greater percentage share of the
system's costs.
Exhibit 8-6 presents the costs per household for systems exceeding the MCL. For each size
category there is a moderate difference in annual cost per household for 3 |ig/L, 5 |ig/L, 10 |ig/L,
and 20 |ig/L across source and ownership. In general, costs per household are higher for private
systems than for public systems. This difference could be attributable to a discrepancy in the cost
of capital for public versus private entities. For public systems, the cost per household ranges
from approximately $5 to $288 per year at 5 |ig/L and from approximately $5 to $285 per year at
10 |ig/L (excluding systems serving more than one million people). For private systems, the
ranges are $4 to $317 per year, and $4 to $314 per year for an MCL of 5 |ig/L and 10 |ig/L,
respectively.
To further evaluate the impacts of these household costs, the average costs per household were
compared to median household income data for each system-size category. The result of this
calculation, presented in Exhibit 8-7 for public and private systems, indicate a household's likely
share of incremental costs in terms of its household income. For all system sizes and MCLs,
average household costs as a percentage of median household income are less than one percent.
Among NTNCs, the average annual system cost ranges from approximately $5,000 to $39,000 at
the revised MCL of 10 |ig/L. These results for systems exceeding the MCL are presented in
Exhibit 8-8. At 3 |ig/L, 5 |ig/L, and 20 |ig/L, the average NTNC system cost ranges from $5,000
to $46,000, $5,000 to $43,000 and $5,000 to $35,000, respectively. More detail on the costs to
NTNCs at these arsenic concentrations are presented in Chapter 6.
Chapter 8, Economic Impact Analyses 8-22 Arsenic in Drinking Water Rule EA
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Exhibit 8-6
Annual Compliance Costs per Household for
CWSs Exceeding MCLs
System Size
Groundwater
Public
Private
Surface Water
Public
Private
MCL = 3 p,g/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
>1, 000,000
$ 285.93
$ 134.47
$ 79.11
$ 64.50
$ 45.79
$ 40.77
-
$ 319.62
$ 190.51
$ 76.64
$ 84.32
$ 65.42
$ 39.67
-
$ 218.47
$ 54.75
$ 15.22
$ 5.77
$ 3.74
$ 5.39
$ 7.41
$ 231.50
$ 72.52
$ 13.98
$ 7.52
$ 4.33
$ 4.62
-
MCL = 5 y,g/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
>1, 000,000
$ 287.87
$ 130.86
$ 76.45
$ 62.56
$ 42.18
$ 36.99
-
$ 316.80
$ 185.83
$ 74.18
$ 79.01
$ 59.84
$ 36.22
-
$ 212.32
$ 54.03
$ 14.91
$ 5.68
$ 3.52
$ 5.00
$ 2.79
$ 229.78
$ 72.33
$ 14.14
$ 7.03
$ 4.23
$ 4.26
-
MCL = 10 y,g/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
>1, 000,000
$ 285.03
$ 126.46
$ 72.51
$ 56.76
$ 38.08
$ 31.72
-
$ 314.11
$ 180.21
$ 69.87
$ 73.42
$ 55.35
$ 30.78
-
$ 214.23
$ 52.72
$ 14.23
$ 5.51
$ 3.13
$ 4.55
$ 0.86
$ 229.02
$ 71.01
$ 13.93
$ 6.81
$ 4.03
$ 3.99
-
MCL = 20 ng/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
>1, 000,000
$ 275.00
$ 120.19
$ 66.07
$ 50.44
$ 33.86
$ 26.59
-
$ 306.52
$ 174.69
$ 65.39
$ 67.25
$ 48.00
$ 26.02
-
$ 204.17
$ 51.42
$ 14.52
$ 5.21
$ 2.84
$ 4.14
$ 0.15
$ 228.82
$ 68.96
$ 13.39
$ 6.48
$ 3.69
$
-
*Costs to households were calculated at a commercial interest rate and include system
treatment, monitoring, and administrative costs; note that systems serving over 1 million
people are public surface water systems.
Chapter 8, Economic Impact Analyses
Arsenic in Drinking Water Rule EA
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Exhibit 8-7
Annual Compliance Costs per Household for CWSs Exceeding MCLs,
as a Percent of Median Household Income
System Size
Groundwater
Public
Private
Surface Water
Public
Private
MCL = 3u,g/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
> 1,000, 000
0.72%
0.34%
0.20%
0.16%
0.12%
0.10%
—
0.81%
0.48%
0.19%
0.21%
0.17%
0.10%
-
0.55%
0.14%
0.04%
0.01%
0.01%
0.01%
0.02%
0.58%
0.18%
0.04%
0.02%
0.01%
0.01%
-
MCL = 5wg/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
> 1,000, 000
0.73%
0.33%
0.19%
0.16%
0.11%
0.09%
—
0.80%
0.47%
0.19%
0.20%
0.15%
0.09%
-
0.54%
0.14%
0.04%
0.01%
0.01%
0.01%
0.01%
0.58%
0.18%
0.04%
0.02%
0.01%
0.01%
-
MCL=10|Lig/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
> 1,000, 000
0.72%
0.32%
0.18%
0.14%
0.10%
0.08%
—
0.79%
0.45%
0.18%
0.19%
0.14%
0.08%
-
0.54%
0.13%
0.04%
0.01%
0.01%
0.01%
0.00%
0.58%
0.18%
0.04%
0.02%
0.01%
0.01%
-
MCL=20wg/L
<100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-1,000,000
> 1,000, 000
0.69%
0.30%
0.17%
0.13%
0.09%
0.07%
-
0.77%
0.44%
0.16%
0.17%
0.12%
0.07%
-
0.51%
0.13%
0.04%
0.01%
0.01%
0.01%
0.00%
0.58%
0.17%
0.03%
0.02%
0.01%
0.00%
-
"Costs to household were calculated at a commercial interest rate and include system
treatment, monitoring, and administrative costs; median household income in May 1999
was $39,648 updated from the 1998 annual median household income from the Census
Bureau.
Chapter 8, Economic Impact Analyses
8-24
Arsenic in Drinking Water Rule EA
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Exhibit 8-8
Total Annual NTNC Treatment Costs at MCL 10 ug/L by System Service Type
(3% Discount Rate)
Service Area Type
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
TOTAL
# of Systems
Above the MCL
43
1
19
15
20
6
22
448
3
2
14
20
5
5
12
7
2
1
6
6
4
6
8
5
2
14
7
51
4
37
8
4
26
41
205
1,080
Average
Population
Served Per
System
76
407
133
123
393
185
370
358
230
145
173
76
60
53
50
160
98
39
42
101
44
113
418
395
63
87
107
136
1,820
174
322
165
170
372
168
Average Annual
System Cost
$5,168
$5,377
$5,956
$5,047
$12,174
$6,387
$5,103
$6,818
$5,168
$6,124
$14,628
$6,012
$5,034
$4,733
$5,177
$6,104
$5,938
$5,245
$4,783
$5,542
$5,176
$5,572
$5,848
$9,095
$5,452
$5,027
$7,298
$5,310
$39,380
$5,097
$5,205
$5,153
$5,627
$7,566
$5,780
Annual
National Costs
$222,846
$4,299
$111,420
$77,207
$238,133
$35,405
$113,692
$3,057,578
$14,599
$15,014
$207,398
$117,930
$27,101
$24,974
$63,471
$40,017
$12,977
$5,592
$27,278
$34,263
$21,517
$35,340
$49,558
$45,053
$9,589
$69,397
$50,567
$268,864
$140,629
$188,796
$39,394
$22,794
$149,069
$309,707
$1,184,505
$7,036,973
Chapter 8, Economic Impact Analyses
8-25
Arsenic in Drinking Water Rule EA
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8.5.4 Macroeconomic Effects
As required under UMRA Section 202, EPA is required to estimate the potential macro-
economic effects of the regulation. These include effects on productivity, economic growth, full
employment, 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 regulation reaches 0.25 percent to 0.5 percent of Gross Domestic Product (GDP). In 1998,
real GDP was $7,552 billion; thus, a rule would have to cost at least $18 billion annually to have
a measurable effect. A regulation with a smaller aggregate effect is unlikely to have any
measurable impact unless it is highly focused on a particular geographic region or economic
sector. The macro-economic effects on the national economy from the Arsenic Rule should be
negligible based on the fact that, assuming 100 percent compliance with an MCL, the total
annual costs are approximately $792 million at the 3 |ig/L level, $472 million at the 5 |ig/L level,
$206 million at the 10 jig/L level, and $77 million at the 20 jig/L level (at a seven percent
discount rate).
8.5.5 Consultation with State, Local, and Tribal Governments
Under UMRA section 204, EPA is to provide a summary of its consultation with elected
representatives (or their designated authorized employees) of affected State, local, and Tribal
governments in this rulemaking. EPA initiated consultations with governmental entities and the
private sector affected by this rulemaking through various means. This included five stakeholder
meetings announced in the Federal Register and open to anyone interested in attending in person
or by phone, and presentations at meetings of the American Water Works Association (AWWA),
the Association of State Drinking Water Administrators (ASDWA), the Association of California
Water Agencies (ACWA), and the Association of Metropolitan Water Agencies (AMWA).
Participants in EPA's stakeholder meetings also included representatives from the National Rural
Water Association, AMWA, ASDWA, AWWA, ACWA, Rural Community Assistance Program,
State departments of environmental protection, State health departments, State drinking water
programs, and a Tribe. EPA also made presentations at Tribal meetings in Nevada, Alaska, and
California.
To address the Arsenic Rule's impact on small entities, the Agency consulted with
representatives of small water systems and convened a Small Business Advocacy Review Panel
in accordance with the Regulatory Flexibility Act (RFA) as amended by the Small Business
Regulatory Enforcement Fairness Act (SBREFA). Two of the small entity representatives were
elected officials from local governments. EPA also invited State drinking water program
representatives to participate in a number of workgroup meetings. In addition to these
consultations, EPA participated in and gave presentations at AWWA's Technical Workgroup for
Arsenic. State public health department and drinking water program representatives, drinking
water districts, and ASDWA participated in the Technical Workgroup meetings. A summary of
State, local, and Tribal government concerns on this rulemaking is shown in the next section.
In order to inform and involve Tribal governments in the rulemaking process, EPA staff attended
the 16th Annual Consumer Conference of the National Indian Health Board on October 6-8, 1998,
in Anchorage, 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
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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 program,
solicit comments on key issues of potential interest in upcoming drinking water regulations, and
to solicit advice in identifying an effective consultative process with Tribes for the future.
EPA, in conjunction with the Inter Tribal Council of Arizona (ITCA), also convened a Tribal
consultation meeting on February 24-25, 1999, in Las Vegas, Nevada, to discuss ways to involve
Tribal representatives, both Tribal council members and tribal water utility operators, in the
stakeholder process. Approximately 25 representatives from a diverse group of Tribes attended
the two-day meeting. Meeting participants included representatives from the following Tribes:
Cherokee Nation, Nezperce Tribe, Jicarilla Apache Tribe, Blackfeet Tribe, Seminole Tribe of
Florida, Hopi Tribe, Cheyenne River Sioux Tribe, Menominee Indian Tribe, Tulalip Tribes,
Mississippi Band of Choctaw Indians, Narragansett Indian Tribe, and Yakama Nation.
The major meeting objectives were to:
(1) Identify key issues of concern to Tribal representatives;
(2) Solicit input on issues concerning current Office of Ground Water and Drinking
Water regulatory efforts;
(3) Solicit input and information that should be included in support of future drinking
water regulations; and
(4) Provide an effective format for Tribal involvement in EPA's regulatory
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 explanation 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 begin discussion on arsenic in drinking
water:
(1) What are the current arsenic levels in your water systems?
(2) What are Tribal water systems' affordability issues in regard to arsenic?
(3) Does your Tribe use well water, river water, or lake water?
(4) Does your Tribe purchase water from another drinking water utility?
The summary for the February 24-25, 1999, meeting was sent to all 565 Federally recognized
Tribes in the United States.
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 regulations affecting water systems;
discuss changes to operator certification requirements; discuss funding for Tribal water systems;
and discuss innovative approaches to regulatory cost reduction. Meeting summaries for EPA's
Tribal consultations are available in the public docket for this rulemaking.
Chapter 8, Economic Impact Analyses 8-27 Arsenic in Drinking Water Rule EA
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8.5.6 State, Local, and Tribal Government Concerns
State and local governments raised several concerns, including the high costs of the rule to small
systems; the burden of revising the State primacy program; the high degree of uncertainty
associated with the benefits; and the high costs of including non-transient non-community water
systems (NTNCWSs). EPA modified the revision of State primacy in order to decrease the
burden of the revised arsenic regulation in response to State concerns, to minimize paperwork
and documentation of existing programs that would manage the arsenic regulation.
Tribal representatives were generally supportive of regulations that would ensure a high level of
water quality but raised concerns over funding for regulations. With regard to the revised
Arsenic Rule, many Tribal representatives saw the health benefits as highly desirable, but felt
that unless additional funds were made available, implementing the regulation would be difficult
for many Tribes.
EPA understands the State, local, and Tribal government concerns with the above issues. The
Agency believes the options for small systems in this rulemaking will address stakeholder
concerns pertaining to small systems and will help to reduce the financial burden to these
systems.
8.5.7 Regulatory Alternatives Considered
As required under Section 205 of the UMRA, EPA considered several regulatory alternatives in
developing an MCL for arsenic in drinking water. In preparation for this consideration, EPA
evaluated arsenic levels of 3 |ig/L, 5 |ig/L, 10 |ig/L, and 20 |ig/L. EPA also evaluated national
costs and benefits of States choosing to reduce arsenic exposure in drinking water. EPA believes
that the regulatory approaches to arsenic described in the revised rule's preamble are the most
appropriate to accomplish the SDWA objectives.
8.5.8 Impacts on Small Governments
In developing this rule, EPA consulted with small governments pursuant to section 203 of the
UMRA to address impacts of regulatory requirements in the rule that might significantly or
uniquely affect small governments. In preparation for the revised Arsenic Rule, EPA conducted
analysis on small government impacts and included small government officials or their
designated representatives in the rulemaking process. EPA conducted stakeholder meetings on
the development of the Arsenic Rule that gave a variety of stakeholders, including small
governments, the opportunity for timely and meaningful participation in the regulatory
development process. Groups such as the National Association of Towns and Townships, the
National League of Cities, and the National Association of Counties participated in the
rulemaking process. Through such participation and exchange, EPA notified potentially affected
small governments of requirements under consideration during the development of the revised
rule and provided officials of affected small governments with an opportunity to have meaningful
and timely input into the development of the regulatory proposal.
Chapter 8, Economic Impact Analyses 8-28 Arsenic in Drinking Water Rule EA
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In addition, EPA will educate, inform, and advise small systems, including those run by small
governments, about the Arsenic Rule requirements. One of the most important components of
this process is the Small Entity Compliance Guide, required by the Small Business Regulatory
Enforcement Fairness Act of 1996 after the rule is promulgated. This plain-English guide will
explain what actions a small entity must take to comply with the rule. Also, the Agency is
developing fact sheets that concisely describe various aspects and requirements of the Arsenic
Rule.
8.6 Effect of Compliance with the Arsenic Rule on the Technical, Financial, and
Managerial Capacity of Public Water Systems
Section 1420(d)(3) of the SDWA as amended requires that, in promulgating an NPDWR, the
Administrator shall include an analysis of the likely effect of compliance with the regulation on
the technical, financial, and managerial capacity of public water systems. The following analysis
has been performed to fulfill this statutory obligation.
Overall water system capacity is defined in EPA guidance (EPA 816-R-98-006) (EPA 1998) as
the ability to plan for, achieve, and maintain compliance with applicable drinking water
standards. Capacity has three components: technical, managerial, and financial.
Technical capacity is the physical and operational ability of a water system to meet SDWA
requirements. Technical capacity refers to the physical infrastructure of the water system,
including the adequacy of source water and the adequacy of treatment, storage, and distribution
infrastructure. It also refers to the ability of system personnel to adequately operate and maintain
the system and to otherwise implement requisite technical knowledge. A water system's
technical capacity can be determined by examining key issues and questions, including:
Source water adequacy. Does the system have a reliable source of drinking water? Is the
source of generally good quality and adequately protected?
• Infrastructure adequacy. Can the system provide water that meets SDWA standards?
What is the condition of its infrastructure, including well(s) or source water intakes,
treatment, storage, and distribution? What is the infrastructure's life expectancy? Does
the system have a capital improvement plan?
Technical knowledge and implementation. Is the system's operator certified? Does the
operator have sufficient technical knowledge of applicable standards? Can the operator
effectively implement this technical knowledge? Does the operator understand the
system's technical and operational characteristics? Does the system have an effective
operation and maintenance program?
Managerial capacity is the ability of a water system to conduct its affairs in a manner enabling
the system to achieve and maintain compliance with SDWA requirements. Managerial capacity
refers to the system's institutional and administrative capabilities. Managerial capacity can be
assessed through key issues and questions, including:
Chapter 8, Economic Impact Analyses 8-29 Arsenic in Drinking Water Rule EA
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• Ownership accountability. Are the system owner(s) clearly identified? Can they be held
accountable for the system?
Staffing and organization. Are the system operator(s) and manager(s) clearly identified?
Is the system properly organized and staffed? Do personnel understand the management
aspects of regulatory requirements and system operations? Do they have adequate
expertise to manage water system operations? Do personnel have the necessary licenses
and certifications?
Effective external linkages. Does the system interact well with customers, regulators, and
other entities? Is the system aware of available external resources, such as technical and
financial assistance?
Financial capacity is a water system's ability to acquire and manage sufficient financial resources
to allow the system to achieve and maintain compliance with SDWA requirements. Financial
capacity can be assessed through key issues and questions, including:
Revenue sufficiency. Do revenues cover costs? Are water rates and charges adequate to
cover the cost of water?
• Credit worthiness. Is the system financially healthy? Does it have access to capital
through public or private sources?
Fiscal management and controls. Are adequate books and records maintained? Are
appropriate budgeting, accounting, and financial planning methods used? Does the
system manage its revenues effectively?
A complete technical, financial, and managerial capacity study is provided in the revised rule's
preamble.
8.7 Paperwork Reduction Act
The information collected as a result of this rule will allow the States and EPA to evaluate PWS
compliance with the rule. For the first three years after promulgation of this rule, the major
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 required to estimate the burden on PWSs for complying with the revised rule. Burden
means the total time, effort, or financial resources expended by persons to generate, maintain,
retain, disclose, or provide information to or for a Federal agency. This includes the time needed
to review instructions; develop, acquire, install, and utilize technology and systems for the
purposes of collecting, validating, and verifying information, processing and maintaining
information, and disclosing and providing information; adjust the existing ways to comply with
any previously applicable instructions and requirements; train personnel to be able to respond to
a collection of information; search data sources; complete and review the collection of
Chapter 8, Economic Impact Analyses 8-30 Arsenic in Drinking Water Rule EA
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information; and transmit or otherwise disclose the information. The Information Collection
Rule for the revised Arsenic Rule estimated a total burden of 3.09 million hours for 10 |ig/L.
8.8 Protecting Children from Environmental Health Risks and Safety Risks
Executive Order (EO) 13045 (62 FR 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
significant" 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. If the regulatory
action meets both criteria, EPA must evaluate the environmental health or safety effects of the
planned rule on children, and explain why the planned regulation is preferable to other
potentially effective and reasonably feasible alternatives considered by EPA.
As described in Chapter 5 ("Benefits Analysis"), there are insufficient toxicological data to
distinguish morbidity and mortality differences by age groups. No studies were located by
ATSDR (1998) that focused exclusively on evaluating unusual susceptibility to arsenic.
However, some members of the population are likely to be especially susceptible. For example,
Chapter 5 describes several non-carcinogenic effects that may be of greater concern to children
than adults, such as cardiovascular or reproductive effects. Similarly, arsenic has been suggested
to pose significant problems in fetal development. This increased susceptibility may be due to a
variety of factors. These factors include increased dose (intake per unit of body weight) in
children, genetic predispositions, and dietary insufficiency (ATSDR, 1998), as well as pre-
existing health conditions.
8.9 Environmental Justice
Executive Order 12898 establishes a Federal policy for incorporating environmental justice into
Federal agency missions by directing agencies to identify and address disproportionately high and
adverse human health or environmental effects of its programs, policies, and activities on
minority and low-income populations. The Executive Order requires the Agency to consider
environmental justice issues in the rulemaking and to consult with Environmental Justice (EJ)
stakeholders.
The Agency has considered environmental justice related issues concerning the potential impacts
of this regulation and has determined that there are no substantial disproportionate effects.
Because the Arsenic Rule applies to all community water systems, the majority of the population,
including minority and low-income populations will benefit from the additional health
protection.
8.10 Health Risk Reduction and Cost Analysis
Section 1412(b)(3)(C) of the 1996 Amendments requires EPA to prepare a Health Risk
Reduction and Cost Analysis (HRRCA) in support of any NPDWR that includes an MCL.
According to these requirements, EPA analyzed each of the following in revising the Arsenic
Rule:
Chapter 8, Economic Impact Analyses 8-31 Arsenic in Drinking Water Rule EA
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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
the result of treatment to comply with each level;
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
from reductions in co-occurring contaminants that may be attributed solely to compliance
with the MCL, excluding benefits resulting from compliance with other proposed or
promulgated regulations;
3. Quantifiable and non-quantifiable costs for which there is a factual basis in the
rulemaking record to conclude that such costs are likely to occur solely as a result of
compliance with the MCL, including monitoring, treatment, and other costs, and
excluding costs resulting from compliance with other proposed or promulgated
regulations;
4. The incremental costs and benefits associated with each alternative MCL considered;
5. The effects of the contaminant on the general population and on groups within the general
population, such as infants, children, pregnant women, the elderly, individuals with a
history of serious illness, or other sub-populations that are identified as likely to be at
greater risk of adverse health effects due to exposure to contaminants in drinking water
than the general population;
6. Any increased health risk that may occur as the result of compliance, including risks
associated with co-occurring contaminants; and
7. Other relevant factors, including the quality and extent of the information, the
uncertainties in the analysis, and factors with respect to the degree and nature of the risk.
This analysis summarizes EPA's estimates of the costs and benefits associated with various
arsenic levels. The summary tables below characterize aggregate costs and benefits, impacts on
affected entities, and tradeoffs between risk reduction and compliance costs.
8.10.1 Quantifiable and Non-Quantifiable Health Risk Reduction Benefits
Arsenic ingestion has been linked to a multitude of health effects, both cancerous and non-
cancerous. These health effects include cancer of the bladder, lungs, skin, kidney, nasal
passages, liver, and prostate. Arsenic ingestion has also been attributed to cardiovascular,
pulmonary, immunological, neurological, endocrine, and reproductive and developmental effects.
A complete list of the arsenic-related health effects reported in humans is shown in Chapter 5.
EPA has performed a risk assessment on bladder cancer and lung cancer. EPA then evaluated
the health benefits attributable to these total cancer cases avoided.
The quantifiable health benefits of reducing arsenic exposures in drinking water are attributable
to the reduced number of fatal and non-fatal bladder and lung cancers. The range of mean
Chapter 8, Economic Impact Analyses 8-32 Arsenic in Drinking Water Rule EA
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bladder and lung cancer risks for exposed populations at or above arsenic levels of 3, 5, 10, and
20 |ig/L in PWSs was described in Chapter 5. Exhibit 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 ug/L, corresponding to the range of mean bladder cancer
risks reported. Similarly, Exhibit 8-10 shows the total lung cancer cases avoided as a result of
reduced arsenic exposure in PWSs. The sum of bladder cancer cases avoided and lung cancer
cases avoided is shown in Exhibit 8-11.
Exhibit 8-9
Annual Bladder Cancer Cases Avoided from Reducing Arsenic in CWSs1 and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced Mortality
Cases**
7.4-20.0
6.6- 14.5
4.9-8.0
2.6-2.8
Reduced Morbidity
Cases**
21.2-56.9
18.9-41.2
13.8-22.7
7.3-7.8
Total Bladder Cancer
Cases Avoided*
28.6 - 76.8
25.6-55.7
18.7-31.0
9.9-10.6
* The lower-end estimate of bladder cancer cases avoided is calculated using the lower-end risk estimate from
Exhibit 5-9(c) and assumes that the conditional probability of mortality among the Taiwanese study group was 100
percent. The upper-end estimate of bladder cancer cases avoided is calculated using the upper-end risk estimate
from Exhibit 5-9(c) and assumes that the conditional probability of mortality among the Taiwanese study group was
80 percent.
**Assuming 20-year mortality rate in the U.S. of 26 percent.
***Cases avoided from NTNCS are included.
Exhibit 8-10
Annual Lung Cancer Cases Avoided from Reducing Arsenic in CWSs and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced Mortality
Cases**
25.2-54.1
22.5 - 39.2
16.4-21.8
7.4 - 8.7***
Reduced Morbidity
Cases**
3.4-7.4
3.1 -5.3
2.2-3.0
1 .0 - 1 .2***
Total Lung Cancer
Cases Avoided*
28.6-61.5
25.6 - 44.5
18.7-24.8
8.5 - 9.9***
* The lower and upper-end estimates of lung cancer cases avoided are calculated using the risk estimates from
Exhibit 5-9 (c) and assume that the conditional probability of mortality among the Taiwanese study group was 100
percent.
**Assuming 20-year mortality rate in the U.S. of 88 percent.
***For 20 ppb, 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 is higher at 20 using
the estimates adjusted for uncertainty.
****cases avoided from NTNCS are included.
Chapter 8, Economic Impact Analyses
Arsenic in Drinking Water Rule EA
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Exhibit 8-11
Annual Total Cancer Cases Avoided from Reducing Arsenic in CWSs and NTNCs
Arsenic Level
(ug/L)
3
5
10
20
Reduced Mortality
Cases**
32.6-74.1
29.1 -53.7
21.3-29.8
10.2- 11.3***
Reduced Morbidity
Cases**
24.6 - 64.2
22.0-46.5
16.1 -25.9
8.5-8.8
Total Cancer Cases
Avoided*
57.2-138.3
51.1 -100.2
37.4 - 55.7
19.0 - 19.8***
* The lower-end estimate of bladder cancer cases avoided and the lung cancer estimates assume that the
conditional probability of mortality among the Taiwanese study group was 100 percent. The upper-end estimate of
bladder cancer cases avoided is calculated using the assumption that the conditional probability of mortality among
the Taiwanese study group was 80 percent.
**Assuming 20-year mortality rate in the U.S. of 26 percent for bladder cancer and 88 percent for lung cancer.
***For 20 ppb, 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 is higher at 20 using
the estimates adjusted for uncertainty.
****Cases avoided from NTNCS are included.
The Agency developed monetized estimates of the health benefits associated with the risk
reductions from arsenic exposures. The approach used in this analysis for the measurement of
health risk reduction benefits is the monetary value of a statistical life (VSL) applied to each fatal
cancer avoided. For non-fatal cancers, willingness to pay (WTP) data to avoid chronic bronchitis
is used as a surrogate to estimate the WTP to avoid non-fatal bladder cancers. A WTP central
tendency estimate of $607,162 (May 1999$) is used to monetize 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).
The total national costs of the revised Arsenic Rule are summarized in Exhibit 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 range from $58.2 to $156.4 million at an MCL of 3 |ig/L, $52.0 to $113.3
million at an MCL of 5 |ig/L, $38.0 to $63.0 million at an MCL of 10 |ig/L, and $20.1 to $21.5
million at an MCL of 20 |ig/L. Total annual health benefits resulting from lung cancer cases
avoided range from $155.6 to $334.5 million at an MCL of 3 |ig/L, $139.1 to $242.3 million at
an MCL of 5 |ig/L, $101.6 to $134.7 million at an MCL of 10 |ig/L, and $46.1 to $53.8 million
atanMCLof20|ig/L.
Chapter 8, Economic Impact Analyses
Arsenic in Drinking Water Rule EA
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Exhibit 8-12
Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and
Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs
Arsenic
Level
(|jg/L)
3
5
10
20
Total Annual
Cost (7%)
$792.1
$471.7
$205.6
$76.5
Annual Bladder
Cancer Health
Benefits1'2
$58.2 -$156.4
$52.0 -$11 3.3
$38.0 - $63.0
$20.1 -$21.5
($ millions
Annual Lung
Cancer Health
Benefits1'2
$155.6 -$334.5
$139.1 -$242.3
$101 .6 -$134.7
$46.1 - $53.8
Total Annual
Health Benefits1'2
$21 3.8 -$490.9
$191.1 -$355.6
$139.6 -$197.7
$66.2 - $75.33
Potential Non-Quantifiable
Health Benefits
Skin Cancer
Kidney Cancer
Cancer of the Nasal
Passages
Liver Cancer
Prostate Cancer
Cardiovascular Effects
Immunological Effects
Neurological Effects
Endocrine Effects
Reproductive and
Developmental Effects
1 May 1999 dollars.
2 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c).
3 For 20 pg/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 pg/L using the estimates adjusted for uncertainty.
Reductions in arsenic exposures may also be associated with non-quantifiable benefits. EPA has
identified several potential non-health non-quantifiable benefits associated with regulating
arsenic in drinking water. These benefits may include any customer peace of mind from
knowing that their drinking water has been treated for arsenic. To the extent 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 buying bottled water or
installing home treatment systems, could also be reduced.
8.10.2 Quantifiable and Non-Quantifiable Costs
The costs of reducing arsenic to various levels are summarized in Exhibit 8-13, which shows that
as expected, aggregate arsenic mitigation costs increase with decreasing arsenic levels. Total
national costs at a seven percent discount rate range are $792.1 million per year at 3 |ig/L; $471.1
million per year at 5 |ig/L; $205.6 million per year at 10 |ig/L; $76.5 million per year at 20 |ig/L.
Chapter 8, Economic Impact Analyses
Arsenic in Drinking Water Rule EA
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Exhibit 8-13
Summary of the Total Annual National Costs of Compliance
($ millions)
Discount Rate
cws
3% 7%
NTNC
3% 7%
TOTAL
3% 7%
MCL = 3 p,g/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$665.9 $756.5
$2.2 $3.0
$1.4 $1.6
$669.4 $761.0
$27.2 $29.6
$1.0 $1.4
$0.1 $0.2
$28.3 $31.1
$693.1 $786.0
$3.2 $4.4
$1.5 $1.7
$697.8 $792.1
MCL =5 p,g/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$394.4 $448.5
$2.0 $2.8
$1.1 $1.3
$397.5 $452.5
$16.3 $17.6
$1.0 $1.3
$0.1 $0.2
$17.3 $19.1
$410.6 $466.1
$2.9 $4.1
$1.2 $1.4
$414.8 $471.7
MCL = 10 na/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$169.6 $193.0
$1.8 $2.5
$0.9 $1.0
$172.3 $196.6
$7.0 $7.6
$0.9 $1.3
$0.1 $0.2
$8.1 $9.1
$176.7 $200.6
$2.7 $3.8
$1.0 $1.2
$180.4 $205.6
MCL =20 p,g/L
System Costs
Treatment
Monitoring/
Administrative
State Costs
TOTAL COST
$60.7 $69.0
$1.7 $2.4
$0.7 $0.8
$63.2 $72.3
$2.6 $2.8
$0.9 $1.3
$0.1 $0.2
$3.6 $4.2
$63.3 $71.8
$2.6 $3.7
$0.9 $1.0
$66.8 $76.5
Chapter 8, Economic Impact Analyses
8-36
Arsenic in Drinking Water Rule EA
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EPA also assessed the cost impact of reducing arsenic in drinking water at the household level.
Exhibit 8-14 examines the cost per household for each system size category. As shown in the
table, costs per household decrease as system size increases. However, costs per household do
not vary significantly across arsenic levels. This is because costs do not vary significantly with
removal efficiency; once a system installs a treatment technology to meet an MCL, costs based
upon the removal efficiency that the treatment technology will be operated under remain
relatively flat. Usually, per household costs are, however, somewhat lower at less stringent
arsenic levels. This is due to the assumption that some systems would blend water at these levels
and treat only a portion of the flow in order to meet the target MCL. However, in the smallest
two size categories, average household costs decrease as the standard becomes more stringent.
This somewhat counterintuitive result is due to the $500.00 affordability cap assumed in the
SafeWater XL simulations. As more CWSs are forced over the affordability cap, the systems'
costs are fixed at the costs associated with the POU technology. This results in lower average
household costs for these systems.
Exhibit 8-14
Mean Annual Costs per Household in CWSs
System Size
<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
All categories
MCL (^g/L)
3
$317.00
$166.91
$74.81
$63.76
$42.84
$38.40
$31.63
$25.29
$7.41
$41.34
5
$318.26
$164.02
$73.11
$61.94
$40.18
$36.07
$29.45
$23.34
$2.79
$36.95
10
$326.82
$162.50
$70.72
$58.24
$37.71
$32.37
$24.81
$20.52
$0.86
$31.85
20
$351.15
$166.72
$68.24
$54.36
$34.63
$29.05
$22.63
$19.26
$0.15
$23.95
Chapter 8, Economic Impact Analyses
8-37
Arsenic in Drinking Water Rule EA
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Exhibit 8-15 illustrates the cost per bladder cancer case avoided, based on national cost estimates
which include all the costs of treatment, O&M, monitoring and administrative costs to CWSs and
NTNCs, and all State start-up costs and State costs for administration of water programs. At a
three percent discount rate, cost per case ranges from approximately $12.2 million at an arsenic
level of 3 |ig/L (lower bound estimate of avoided bladder cancer cases) to $3.4 million at an
MCL of 20 ug/L (upper bound of avoided bladder cancer cases). Similarly, the range at a seven
percent discount rate is $13.8 million to $3.9 million.
Exhibit 8-15
Cost per Cancer Case Avoided
($ millions)
Arsenic Level
(J19/L)
lower bound**
upper bound**
3% Discount Rate
3
5
10
20
$
$
$
$
12.2
8.1
4.8
3.5
$
$
$
$
5.0
4.1
3.2
3.4
7% Discount Rate
3
5
10
20
$
$
$
$
13.8
9.2
5.5
4.0
$
$
$
$
5.7
4.7
3.7
3.9
"Lower/upper bounds correspond to estimates of bladder cancer cases awided.
Chapter 8, Economic Impact Analyses
Arsenic in Drinking Water Rule EA
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Appendix A: Decision Tree and Large System Costs
A.1 Introduction
The purpose of this appendix is to present the rationale behind the development of the decision
tree and associated decision matrix. It includes an overview of the decision tree structure and
major factors impacting the decision- making process. The following list outlines the contents of
this appendix:
• Background- Presents a brief history of the arsenic regulation and the statutory
requirements impacting EPA and the decision-making process.
• Major Factors Affecting the Decision Tree - Presents the rationale for selecting
parameters which impact the decision tree, including MCL, population, water
type, region, and co-occurrence of solutes.
• Additional Factors Affecting the Decision Tree - Presents other parameters in
the process which impact the decision tree, including: corrosion control, pre-
oxidation, regionalization, and alternative technologies.
• Development of a Decision Tree - Presents the logic used for developing the
decision tree for treatment of arsenic to a final revised MCL of 10 |ig/L.
Very Large System Methodology - Discusses the cost estimates for the Nation's
25 largest drinking water systems.
A.2 Background
In 1998 and 1999, EPA conducted technology and cost evaluations for the removal of arsenic
from drinking water. These evaluations looked into the effectiveness of various removal
technologies and the capital and operations and maintenance (O&M) costs associated with each
process. The following were evaluated and determined effective to varying degrees:
• Modified Coagulation/Filtration (modifications to existing C/F plants);
Coagulation Assisted Microfiltration (CMF);
• Modified Lime Softening (modifications to existing LS plants);
Activated Alumina (AA);
• Ion Exchange (IX);
Greensand Filtration (GF); and
• Point-of-Use (POU) Treatment Options.
The technology and cost evaluation yielded a document entitled Technologies and Costs for the
Removal of Arsenic From Drinking Water (EPA, 2000c). The document includes detailed
evaluations of the above technologies, capital and O&M cost estimates for each of the listed
technologies, as well as other technologies that were considered ineffective or unproven.
EPA used the information contained in the technologies and costs (T&C) document to develop a
regulatory decision tree. The decision tree was then used to fashion a decision matrix which
Appendix A, Decision Tree and Large System Costs A-l Proposed Arsenic in Drinking Water Rule RIA
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contains the probability that a given system will choose a treatment technology based on the
percent removal required to meet the final revised MCL of 10 |ig/L . The decision matrix, unit
cost curves for treatment and waste disposal (illustrated in the T&C), treatment-in-place data and
occurrence estimates were used to develop national cost of compliance estimates.
A.3 Major Factors Affecting the Decision Tree
This section explains the rationale behind selecting each particular decision factor. Specifically,
this section will discuss the following:
the MCL target;
influent arsenic concentration;
• population;
region where the system is located;
• source water;
whether a system has existing treatment in place;
• co-occurrence of solutes; and
waste disposal issues.
A.3.1 MCL Target
Target treatment concentration (8 |ig/L) which is equal to 80 percent of the final revised MCL of
10 |ig/L was selected as the basis for the development of the Arsenic Rule decision tree. The
selection of a target treatment concentration was the first step in the decision process and was
essential for determining all other branches of the decision tree.
A.3.2 Influent Arsenic Concentration
Given the MCL, the influent arsenic concentration determines what percent removal of arsenic is
needed, if any, and lays the groundwork for remaining decisions in the tree; therefore, the
influent arsenic concentration was of major importance in developing the decision tree. Given
the maximum influent arsenic level of 50 |ig/L and at the final MCL of 10 |ig/L, no systems
would need to have a removal efficiency greater than 90 percent to treat for arsenic. Percent
removal is critical for determining what additional technologies may be feasible. For example, if
a ground water system has an influent arsenic level of 50 |ig/L, and the target treatment
concentration is 8 |ig/L, then approximately 80 percent removal is required.1
Required removal percentages in the decision tree are based on worst cast scenarios and
therefore correspond with the upper bound of the arsenic concentration range for each category.
Appendix A, Decision Tree and Large System Costs A-2 Proposed Arsenic in Drinking Water Rule RIA
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A.3.3 System Size
System size, or population, also plays a significant role in determining the treatment options
available to a system, as well as the affordability of a particular technology. EPA established
nine size categories 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
greater than 1,000,000.
Exceptions were made in the decision tree for particular systems. The Agency considered point-
of-use (POU) treatment as a viable option only for the two smallest categories of groundwater
systems. Systems serving greater 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.
In developing the probability of choosing a given technology for each of the size categories, the
Agency considered several factors such as available data on in-place treatments from Community
Water System Survey (CWSS). The logic used for developing the probabilities for each of the
size categories is detailed in section A.5 below.
A.3.4 Region
The region of the nation that a system resides in does not effect the treatment options available.
Therefore, the decision tree is structured in such a way that, regardless of the region, the branches
are identical, and in fact refer to the same pages within the decision tree. However, the number of
systems that may select a particular option as defined in the decision matrix, is region-specific.
EPA has decided that the nation can be divided into three regions for the purpose of the decision
making process: 1) Southwest Region; 2) Northwest Region; and 3) East Region. The regions
were selected based upon availability of water (i.e., scarcity of water) and availability of land. In
the Southwest Region, for example, water may be scarce and treatment technologies that generate
large volumes of reject water, such as RO, may not be appropriate. In the East Region, water
scarcity is much less a concern than the availability of land. Technologies or disposal options
that require significant amounts of land are less likely to be utilized in the East Region. The
Northwest Region, by comparison, is less affected by the scarcity of water or land availability
than either of the other two regions.
Appendix A, Decision Tree and Large System Costs A-3 Proposed Arsenic in Drinking Water Rule RIA
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A.3.5 Source Water
The source of the system's raw water, either ground water or surface water, plays a major role in
determining the technologies that may already be in use by a system and what treatment options
are available if a system needs to install a new facility.
For example, greensand filtration is affected by the level of iron in the raw water. Influent levels
greater than 300 mg/L (ppm) are conducive to removal of arsenic by greensand filtration.
Surface waters typically have low iron content, whereas ground waters often have levels in
excess of 300 mg/L (Subramanian, et al., 1997). Accordingly, greensand filtration was not
considered a viable removal technology for surface water systems, but is viable for ground water
systems.
To determine the types of treatment that are currently being utilized throughout the country by
source, EPA reviewed the Community Water Systems Survey (CWSS). EPA determined there
are few surface water systems utilizing RO, IX or AA. As a result, when approximating the
treatment in place options, RO, IX, and AA were omitted for surface water systems.
Arsenic removal is significantly more efficient when arsenic is present as arsenate (As5+).
Research has demonstrated many of the technologies considered perform poorly when arsenite
(As3+) is the predominant form (EPA, 2000). Arsenite can be easily oxidized to arsenate using
conventional oxidation methods, such as chlorination and potassium permanganate addition.
Ground waters typically contain higher levels of As3+, whereas As5+ is the dominant species in
surface waters. As a result, ground water systems are more likely to install pre-oxidation and use
higher oxidant doses, whereas surface water systems may be able to get by with little or no pre-
oxidation capacity.
A.3.6 Systems with Treatment In-Place
Information on in-place treatment technologies for all the flow categories of surface and ground
water systems was obtained from Table 6.2 of "Geometries and Characteristics of Public Water
Systems (EPA, 1999b) ." The Agency determined that many existing treatment facilities will be
able to achieve the necessary arsenic removal with little or no modification to their plant. Exhibit
A- 1 below outlines the treatment technologies included in the decision tree, the percent removal
assumed capable without modification or polishing, and the maximum percent removal.
A.3.7 Systems without Treatment In-Place
Many factors affect the decision tree when considering the addition of a treatment option for
systems with no current treatment in place. Source water type and quality, system size, required
arsenic removal, and removal achievable by a particular technology are all major considerations.
Many of these considerations have been discussed earlier in Section 4.
For ground water systems without treatment in-place, the most suitable treatment technologies
are IX and AA. For surface water systems 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
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adjustment and coagulation microfiltration are the most suitable. Modified CF and LS are for
those surface water systems that already have CF or LS in-place.
The SDWA identifies POE and POU treatment units as potentially affordable technologies, but
stipulates that POE and POU treatment systems "shall be owned, controlled and maintained by
the public water system, or by a person under contract with the public water system to ensure
proper operation and compliance with the maximum contaminant level or treatment technique
and equipped with mechanical warnings to ensure that customers are automatically notified of
operational problems."
Preliminary affordability determinations have shown that POU technologies will only be
considered viable for small systems. 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 expensive, thus increasing the breakpoint. As a
result only POU AA and POU RO compliance strategies were included in the decision tree for
the groundwater systems in the two smallest flow categories.
Exhibit A-1
Treatment Technologies for Systems with Treatment In-Place and Percent Removals
Assumed and Achievable
Treatment Technology
Coagulation/Filtration2
Lime Softening2
Coagulation Assisted Microfiltration
Ion Exchange
Activated Alumina
Reverse Osmosis
Greensand Filtration3
POU Activated Alumina
POU Reverse Osmosis
Percent Removal of
In-Place System
50
50
NA
NA
NA
NA
NA
NA
NA
Maximum Percent
Removal1
95
90
90
>95
>95
>95
80
>90
>90
1 - For Percent Removals of In-Place Systems that are very close to Maximum Percent Removals (e.g., 95 percent and > 95
percent) polishing steps may be required.
2 - Maximum Percent Removal involves modification to existing system in the form of additional chemical feed systems, pumping,
piping, etc.
NA - Not Applicable
A.3.8 Co-Occurrence of Solutes
There are a number of solutes and water quality parameters that may effect the viability 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
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detractors/benefactors for the use of a particular technology. The decision tree simply cannot
account for each individual situation where the influent water quality plays a role in selecting the
treatment option. Utilities are encouraged to read the T&C document (EPA, 2000d) to gather
additional information on parameters which impact the performance of a particular technology.
The decision tree uses influent sulfate and iron levels as decision factors in selecting treatment
technologies. For ground water sources, both sulfate and iron levels are considered. Ion
exchange is not considered a feasible treatment option when sulfate levels exceed 50 mg/L and
greensand filtration is not considered viable when the iron level falls below 300 mg/L. Sulfate
has been shown to decrease the effectiveness of ion exchange processes for arsenic removal;
therefore, an upper bound sulfate concentration of 50 mg/L was used in the final rule for
determination of ion exchange usage. Iron, on the other hand, significantly improves the
effectiveness of greensand filtration (Subramanian, et al., 1997). Greensand filtration is best
suited for ground waters (which typically contain higher levels of iron than surface waters) with
high influent levels of iron (300 mg/L). For purposes of approximating national cost, greensand
filtration is not considered a treatment option for surface water systems.
A.3.9 Waste Disposal
Waste handling and disposal options are specific to the treatment technology selected, therefore
the availability of disposal options does not vary by system size in the decision tree. However,
the probability that a system will utilize a particular option does vary with system size.
A.3.9.1 Mechanical Dewatering
Mechanical dewatering processes include centrifuges, vacuum-assisted dewatering beds, belt
filter presses, and plate and frame filter presses. Such processes generally have high capital, as
well as high O&M costs, compared to similar capacity non-mechanical dewatering processes
(e.g., storage lagoons). Due to the high costs, such processes are generally not suitable for very
small water systems.
Filter presses have been used in industrial processes for years and have been increasing in the
water treatment industry over the past several years. The devices have been successfully applied
to both lime softening process sludge and coagulation/filtration process sludge. Filter presses
require little land, have high capital costs, and are labor intensive.
Centrifuges have also been used in the water industry for years. Centrifugation is a continuous
process requiring minimal time to achieve the optimal coagulation/filtration. Centrifuges have
low land requirements and high capital costs. They are more labor intensive than non-
mechanical alternatives, but less intensive than filter presses. Again, due to the capital and O&M
requirements, centrifuges are more suitable for larger water systems.
Appendix A, Decision Tree and Large System Costs A-6 Proposed Arsenic in Drinking Water Rule RIA
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A.3.9.2 POTW Discharge
Indirect discharge (POTW discharge) is a commonly used method of disposal for filter backwash
and brine waste streams. Coagulation/filtration and lime softening sludge materials have also
been successfully disposed of in this manner. The primary cost associated with POTW discharge
is that of the piping. Additional costs associated with POTW discharge may include lift stations,
additional piping for access to the sewer system, and any cost incurred by the POTW in
accommodating the increased demands on the POTW.
A.3.9.3 Sanitary Landfill Disposal
Two forms of sanitary landfill are commonly used for disposal of water treatment byproducts:
monofills and commercial nonhazardous waste landfills. In some parts of the country,
decreasing landfill availability, rising costs, and increasing regulations are making landfill
disposal more expensive. Costs associated with the development of monofills are generally less
than those associated with commercial nonhazardous water landfill.
A.4 Additional Factors Affecting the Decision Tree
A.4.1 Pre-Oxidation
As mentioned above, inorganic arsenic occurs in two primary valence states, arsenite (As HI) and
arsenate (As V). As(ni) is dominant in ground waters while surface waters more typically
contain As(V). As(in) is easily oxidized to As(V) by conventional oxidation technologies such
as chlorination and potassium permanganate addition. Each of the treatment technologies
considered in the decision tree remove As(V) more readily than As(ni) and as a result may
require pre-oxidation.
In estimating national costs, it was assumed that only systems without pre-oxidation in-place
would add the necessary equipment. It is expected that no surface water systems will need to
install pre-oxidation for arsenic removal and that about fewer than 50 percent of the groundwater
systems may need to install pre-oxidation for arsenic removal. Ground water systems without
pre-oxidation should determine if pre-oxidation is necessary by determining if the arsenic is
present as As (in) or As (V). Ground water systems with predominantly As (V) will probably
not need pre-oxidation to meet the MCL. For single tap (POU) treatment options, centralized
pre-oxidation is required. Exhibit A-2 shows the number of systems that were assumed to require
addition of pre-oxidation.
Appendix A, Decision Tree and Large System Costs A-7 Proposed Arsenic in Drinking Water Rule RIA
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Exhibit A-2: Systems Needing to Add Pre-Oxidation
System Size
25-100
101-500
501-1000
1001-3300
3300-1 OK
10001-50K
50,001-100K
100.001-1M
Percent of Ground Water Systems
54
30
24
24
27
13
41
16
A.4.2 Corrosion Control
Many of the treatment technologies considered in the decision tree (e.g. AA, and IX) remove
hardness and alkalinity. Removal of hardness and alkalinity can reduce the pH of finished water
and lead to corrosion problems within the system. Hardness and alkalinity, at the appropriate
levels, act as buffers against corrosion in the treatment plant and distribution system. At these
levels, alkalinity and hardness form protective coatings (metal hydroxides), control pH and
enhance the buffer effect against corrosion. Where appropriate, corrosion control costs were
included with arsenic treatment in the decision tree. It was assumed that the in-place lime
softening and coagulation/flocculation plants had adequate corrosion control in-place.
A.4.3 Alternative Technologies
Technologies and Costs for the Removal of Arsenic from Drinking Water (EPA, 2000) evaluated
four arsenic removal technologies that were not included in the decision tree:
• Sulfur-Modified Iron,
Granular Ferric Hydroxide,
• Iron Filings, and
Iron Oxide Coated Sand.
The technologies were not included in the decision tree for reasons which are summarized below.
A.4.3.1 Sulfur-Modified Iron
A patented Sulfur-Modified Iron (SMI) process for arsenic removal has recently been developed.
During this process, powdered iron, powdered sulfur, and the oxidizing agent (H2O2 in
preliminary tests) are thoroughly mixed and added to the water to be treated. The oxidizing
agent serves to convert As(ni) to As(V). Arsenic removal utilizing the SMI process seems to be
Appendix A, Decision Tree and Large System Costs A-&
Proposed Arsenic in Drinking Water Rule RIA
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dependent on the iron to arsenic level as well as pH. Flow distribution problems were evident, as
several columns became partially plugged during operation.
All experimentation 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. It appears that O&M for such a system would be
expensive and would require a highly trained operator. Finally, by the admission of the
researchers, disposal costs might outweigh the increased adsorption capacity.
A.4.3.2 Granular Ferric Hydroxide
Granular ferric hydroxide is a technology that may combine very long run length without the
need to adjust pH. The technology has been demonstrated for arsenic removal full-scale in
England (Simms et al, 2000). A pilot-scale study for activated alumina was also conducted on
that water and showed run lengths much longer than observed in pilot-scale studies in the United
States. Due to the lack of published data showing performance for a range of water qualities,
granular ferric hydroxide was not designated a BAT. In addition, there is little published
information on the cost of the media, so it is difficult to evaluate cost. Granular ferric hydroxide
is being investigated in several ongoing studies and may be an effective technology for removing
arsenic.
A.4.3.3 Iron Filings
The Iron Filings process is essentially a filter technology, much like greensand filtration, wherein
the source water is filtered through a bed of sand and iron filings. Unlike some technologies (i.e.
ion exchange), sulfate is actually introduced in this process to encourage arsenopyrite
precipitation.
While this process seems to be quite effective, its use as a drinking water treatment technology
appears to be limited. There is no indication that this technology can reduce arsenic levels below
approximately 25 ppb. This technology also suffers from a study design which failed to test its
effectiveness at influent levels of concern in drinking water. Since the study design called for
such high influent levels - 470 to 20,000 ppb - there is no data to indicate how the technology
performs at normal source water arsenic levels, which most certainly are below the 470 ppb level
used in experimentation. This technology needs to be further evaluated before it should be
recommended as an approved arsenic removal technology for drinking water.
A.4.3.4 Iron Oxide Coated Sand
Iron oxide coated sand (IOCS) is a rare process that has shown some tendency for arsenic
removal. IOCS consists of sand grains coated with ferric hydroxide which are used in fixed bed
reactors to remove various dissolved metal species. Factors such as pH, arsenic oxidation state,
competing ions, EBCT, and regeneration time have significant effects on the removals achieved
with IOCS. Like other processes, the media must be regenerated upon exhaustion. IOCS has
only been tested at bench-scale. High levels of arsenite could reduce IOCS effectiveness because
the bonding is strong and may permanently damage the media. Natural organic matter may also
Appendix A, Decision Tree and Large System Costs A-9 Proposed Arsenic in Drinking Water Rule RIA
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be problematic for arsenic removal. IOCS also takes a considerable amount of time to produce in
a laboratory setting. At full-scale this would likely result in high capital cost.
A.5 Development of a Decision Tree
A.5.1 Surface Water Systems
The following describes the logic used for developing the decision tree for treatment of arsenic in
surface water systems in order to comply with the final MCL. For actual breakout of percentages
used in the decision tree, refer to the Exhibits A-7 to A-22.
1. Information on in-place treatment technologies for all the flow categories of surface water
systems was obtained from Table 6.2 of "Geometries and Characteristics of Public Water
Systems" (EPA, 1999b). This table is shown below as Exhibit A-3. Information
provided in the document on in-place treatments was based on data from Community
Water System Survey (CWSS), which EPA conducted in 1995 to obtain data to support
its development and evaluation of drinking water regulations.
2. Exhibit A-3 shows the percentage of systems with in-place Lime/Soda Ash Softening. It
was assumed that these systems would modify the existing treatment to comply with the
final MCL.
Exhibit A-3: Percent of Surface Water Systems with In-Place Treatment
System Size
25-100
101-500
501-1000
1001-3300
3300-1 OK
10001-50K
50,001-100K
100,001-1M
Lime/ Soda Ash Softening
3.9%
8.1%
20.5%
17.5%
10.8%
6.9%
5.7%
5.1%
Coagulation
Flocculation
27.5%
52.6%
70.2%
79%
95.4%
94.5%
93.7%
99.5%
Filtration
78.5%
71 .2%
79.3%
81.7%
86.5%
96.3%
88%
93.4%
Exhibit A-3 was also used to estimate the percentage of systems with existing
coagulation/filtration processes. In-place coagulation/flocculation was based on the
smaller (in terms of percent use) of filtration and coagulation/flocculation. The Agency
believes this is a conservative assumption for several reasons. The first is that the CWSS
data on in-place treatments was gathered 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
Proposed Arsenic in Drinking Water Rule RIA
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adopted in later years. The second is that no arsenic removal is assumed for systems with
filtration when the percentage is higher than the percentage for coagulation/flocculation.
4. The percent of remaining technologies likely to be used for arsenic treatment for each
flow category was obtained by subtracting from 100, the percentages assigned for
modified lime softening and modified coagulation /filtration per step 2 and 3 above. The
remaining technologies that were considered in the decision tree for treatment of arsenic
in surface water include coagulation microfiltration and activated alumina (AA). Systems
choosing AA may also choose to pH adjust. This decision is primarily dependent on
system size. Systems that serve less than 500 people (see step 6 below) are less likely to
pH adjust their raw water supplies because of technical complexity and need for skilled
labor. The Agency classified these systems in two natural pH categories. Systems that
have raw water with pH between 7 and 8 and systems with pH in raw water greater than
8. For systems that are likely to adjust pH to 6, the Agency considered two run length
options, low end (15,400 BV) and high end (23,100 BV).
5. Based on the Agency's best professional judgement, the Agency believes that for systems
serving more than 500 people, the selection of treatment for arsenic would likely be
distributed among pH adjusted AA with high end run length, pH adjusted AA with low
end run length, and coagulation microfiltration in 40:40:20 ratio. Coagulation/
microfiltration is more expensive than activated alumina. However, some surface water
systems may select it because they may get filtration credits or precursor removal along
with arsenic removal. The benefits of this treatment approach could not be quantified.
6. For systems serving less than 500 people, it is assumed that there will be no usage of
coagulation microfiltration technology, primarily because of its high capital cost,
technical complexity and need for skilled labor. The Agency believes for this group,
about 65 percent of systems with natural pH between 7 and 8 would likely use AA, about
23 percent systems with natural pH greater than 8 would likely use AA and remaining
systems would evenly use pH adjusted activated alumina options.
A.5.2 Ground Water Systems
The next section describes the logic used for developing the decision tree for treatment of arsenic
to a MCL of 10 ug/L for ground water systems.
1. Information on in-place treatment technologies for all the flow categories of ground water
systems was obtained from Table 6.1 of "Geometries and Characteristics of Public Water
Systems" (EPA, 1999b). The information provided in the document on in-place
treatments was based on data from Community Water System Survey (CWSS), which
EPA conducted in 1995 to obtain data to support its development and evaluation of
drinking water regulations.
2. For systems serving less than 10,000 people, the Agency selected roughly half the
percentage of systems with in-place of lime softening and coagulation/ flocculation
(Exhibit A-4). These systems would modify their existing treatment to meet arsenic
AppendixA, Decision Tree and Large System Costs A-ll Proposed Arsenic in Drinking Water Rule RIA
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MCL. For systems serving more than 10,000 people, the Agency assumed 4 percent for
each technology as the maximum percentage of systems with existing lime softening and
coagulation/ flocculation treatments. There was a concern that the much higher
percentages in might be due to mixed systems (groundwater and surface water) rather
than groundwater systems. Thus much lower percentages were used to estimate existing
treatment. Systems with existing treatment will modify it to meet the arsenic MCL.
Exhibit A-4: Percent of Ground Water Systems with In-Place Treatment
System Size
25-100
101-500
501-1000
1001-3300
3300-1 OK
10001-50K
50,001-100K
100.001-1M
Lime/ Soda Ash Softening
2.1%
3.7%
4.1%
5.2%
7.0%
12.2%
17.4%
32.4%
Coagulation
Flocculation
1 .5%
2.0%
4.2%
3.4%
8.1%
15.1%
24.2%
25.2%
For systems serving less than 100 people and requiring 50-90 percent removal of arsenic,
the decision tree assumed a 5 percent usage for each POU option (RO and AA). For
systems requiring less than 50 percent removal of arsenic, a 2 percent usage of each POU
option was assumed. POU options were used less if lower removal of arsenic was desired
because systems would have an opportunity for blending, which would make central
treatment more cost effective.
In the decision tree, for systems serving between 100-500 people and requiring 50-90
percent removal of arsenic, the Agency assumed a 3 percent usage for each POU
treatment option. For systems requiring less than 50 percent removal of arsenic, the
Agency assumed a 1 percent usage of each POU option. The Agency's assumption of
POU usage for this size system is based on the fact that the economic feasibility of POU
treatment for systems serving between 70 and 120 households. Therefore, this option
would be less preferred by systems in this size in comparison to systems serving less than
100 people. With the increase in households, the management of this treatment strategy
becomes progressively complex and cost prohibitive. For systems serving more than 500
people, the Agency did not consider any usage.
Anion Exchange (AX). The proposed rule decision tree utilized anion exchange to a great
extent. The upper bounds were based on the co-occurrence of sulfate (Table IX-7 of the
proposed rule). This table is replicated below as Exhibit A-5. Many comments on the
Appendix A, Decision Tree and Large System Costs A-12
Proposed Arsenic in Drinking Water Rule RIA
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proposed rule noted other problems that would limit the use of anion exchange. The first
was that the brine stream could be considered hazardous waste. Based on a review of this
issue, the evaporation pond and chemical precipitation options were eliminated.
Discharge to a POTW was not affected by this issue because of the domestic sewage
exclusion in 40 CFR 261.4. In addition, the Agency received comments suggesting that
stringent technically based local limits (TBLL) for arsenic and total dissolved solids
(TDS) in various jurisdictions nationwide would limit the use of publicly owned
treatment works (POTW) for discharge of anion exchange waste brine. Therefore, after
examining other potential restrictions on POTW discharge of waste brine, the Agency
believes lowering the usage of anion exchange with brine disposal to a POTW in the
decision tree would be appropriate. In 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 Water: Arsenic and Sulfate Co-occurrence
Influent Arsenic
<10ug/L
10-20ug/L
>20 ug/L
Likelihood of Sulfate (percent)
<25 mg/L
48
35
33
25-1 20 mg/L
33
39
38
>1 20 mg/L
19
26
30
It was assumed that sulfate concentration and percent waste brine volume (in relation to
background wastewater volume) are factors that would determine anion exchange
selection for arsenic treatment. Percent waste volume was related to removal efficiency.
Requiring lower removal efficiencies allow systems to treat a smaller volume of water
than at a higher removal efficiency. Systems will blend an untreated portion with a
treated portion of water to reduce costs while still complying with the MCL. Based 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 background wastewater volume also contributed to correlation
between anion exchange use and system size.
An increase in total dissolved solids from salt used for regeneration would likely restrict
the use of anion exchange in the arid Southwest. However, arsenic occurrence is not
limited to just the Southwest. There are areas in the mid-west and Northeast with arsenic
above the MCL. The upper bound for systems (small systems) using anion exchange
with POTW discharge was 7 percent. For many system size categories, anion exchange
with sulfate less than 20 mg/L is the least expensive option. However, it is only be
selected by 5 percent or less of the systems because of potential adverse impacts from
disposing the brine in the sanitary sewer system.
Appendix A, Decision Tree and Large System Costs A-13
Proposed Arsenic in Drinking Water Rule RIA
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6. Table IX-9 of the proposed rule presented the co-occurrence of iron and arsenic. This
table is replicated below as Exhibit A-6. Approximately 18 percent of the systems had
iron concentration above the secondary standard of 300 ug/L. One reference indicated
that a 20:1 Fe/As ratio could remove up to 80 percent of the arsenic. It was assumed that
two thirds of the systems above the secondary standard would have sufficient iron to
achieve high arsenic removals.
Exhibit A-6: Ground Water: Arsenic and Iron Co-occurrence
Influent Arsenic
<10ug/L
10-20 ug/L
>20 ug/L
Likelihood of Iron (percent)
<300 ug/L
82
81
71
>300 ug/L
18
19
29
Based on the Agency's best professional judgement, the Agency believes that for groundwater
systems serving less than 500 people, the selection of AA would likely be distributed among
systems in a 3:1 ratio for systems with a raw water natural pH between 7 and 8 and systems with
a raw water pH greater than 8. This is based on raw groundwater data from the USGS National
Water Information System that was analyzed in the co-occurrence report. Projections on the
percent of systems with raw water pH greater than 8 were made for each region. The highest
percentage for any region was approximately 25 percent. As a conservative estimate, this was
assumed nationwide.
For groundwater systems serving more than 500 people, the Agency believes that the selection of
AA would likely be distributed evenly among pH adjusted AA with high end run length (23,100
BV) and pH adjusted AA with low end run length (15,400 BV). The Agency also believes that
there would be a small percentage of systems serving more than 500 people that would continue
to use AA without pH adjustment. However, the Agency believes the usage of AA technology
without pH adjustment would decrease with increasing system size.
For groundwater systems serving 1,000 tol0,000 people, the Agency assumed a 10 percent usage
of coagulation microfiltration distributed evenly among mechanical dewatering and non-
mechanical dewatering options. For systems serving more than 10K people, the Agency assumed
a increased usage (14 percent) of coagulation microfiltration with mechanical dewatering
dominating in these size categories because of space consideration.
Appendix A, Decision Tree and Large System Costs A-14
Proposed Arsenic in Drinking Water Rule RIA
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Exhibit A-7
Probability Decision Tree: Ground Water Systems Serving • 400 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash stream and pre-oxidation
Activated Alumina (pH 7 -c|-| 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 -c|-| 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Percent of Treatment Required to
Achieve MCL
<50%
1.0
1.0
5.0
2.0
0.0
0.0
12.0
56.0
19.0
0.0
0.0
2.0
2.0
50-90%
1.0
1.0
3.0
1.0
0.0
0.0
0.0
63.0
21.0
0.0
0.0
5.0
5.0
>90%
1.0
1.0
2.0
1.0
0.0
0.0
0.0
70.0
23.0
0.0
0.0
0.0
2.0
Sum of Probabilities:
100.00
100.00
100.00
-------
Exhibit A-8
Probability Decision Tree: Ground Water Systems Serving 101-500 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
5.0
2.0
0.0
0.0
12.0
56.0
19.0
0.0
0.0
1.0
1.0
100.00
50-90%
2.0
2.0
3.0
1.0
0.0
0.0
0.0
63.0
21.0
2.0
0.0
3.0
3.0
100.00
>90%
2.0
2.0
2.0
1.0
0.0
0.0
0.0
64.0
22.0
3.0
3.0
0.0
1.0
100.00
-------
Exhibit A-9
Probability Decision Tree: Ground Water Systems Serving 501-1,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash stream and pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
5.0
2.0
0.0
0.0
12.0
25.0
2.0
25.0
25.0
0.0
0.0
100.00
50-90%
2.0
2.0
3.0
1.0
0.0
0.0
0.0
30.0
2.0
30.0
30.0
0.0
0.0
100.00
>90%
2.0
2.0
2.0
1.0
0.0
0.0
0.0
31.0
2.0
30.0
30.0
0.0
0.0
100.00
-------
Exhibit A-10
Probability Decision Tree: Ground Water Systems Serving 1,001-3,300 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
5.0
2.0
5.0
5.0
12.0
17.0
0.0
25.0
25.0
0.0
0.0
100.00
50-90%
2.0
2.0
3.0
1.0
5.0
5.0
0.0
16.0
0.0
33.0
33.0
0.0
0.0
100.00
>90%
2.0
2.0
2.0
1.0
5.0
5.0
0.0
17.0
0.0
33.0
33.0
0.0
0.0
100.00
-------
Exhibit A-11
Probability Decision Tree: Ground Water Systems Serving 3,301-10,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
3.0
4.0
5.0
2.0
8.0
2.0
0.0
24.0
0.0
26.0
26.0
0.0
0.0
100.00
50-90%
3.0
4.0
3.0
1.0
8.0
2.0
0.0
25.0
0.0
27.0
27.0
0.0
0.0
100.00
>90%
3.0
4.0
2.0
1.0
8.0
2.0
0.0
26.0
0.0
27.0
27.0
0.0
0.0
100.00
-------
Exhibit A-12
Probability Decision Tree: Ground Water Systems Serving 10,001-50,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
3.0
0.0
12.0
2.0
0.0
11.0
0.0
32.0
32.0
0.0
0.0
100.00
50-90%
4.0
4.0
1.0
0.0
12.0
2.0
0.0
11.0
0.0
33.0
33.0
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
12.0
2.0
0.0
11.0
0.0
34.0
33.0
0.0
0.0
100.00
-------
Exhibit A-13
Probability Decision Tree: Ground Water Systems Serving 50,001-100,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
3.0
0.0
12.0
2.0
0.0
7.0
0.0
34.0
34.0
0.0
0.0
100.00
50-90%
4.0
4.0
1.0
0.0
12.0
2.0
0.0
7.0
0.0
35.0
35.0
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
12.0
2.0
0.0
7.0
0.0
36.0
35.0
0.0
0.0
100.00
-------
Exhibit A-14
Probability Decision Tree: Ground Water Systems Serving 100,001-1,000,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
0.0
0.0
12.0
2.0
0.0
4.0
0.0
37.0
37.0
0.0
0.0
100.00
50-90%
4.0
4.0
0.0
0.0
12.0
2.0
0.0
4.0
0.0
37.0
37.0
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
12.0
2.0
0.0
4.0
0.0
37.0
37.0
0.0
0.0
100.00
-------
Exhibit A-15
Probability Decision Tree: Surface Water Systems Serving • 400 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 -PH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 -PH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
28.0
0.0
0.0
0.0
0.0
0.0
44.0
16.0
4.0
4.0
0.0
0.0
100.00
50-90%
4.0
28.0
0.0
0.0
0.0
0.0
0.0
44.0
16.0
4.0
4.0
0.0
0.0
100.00
>90%
4.0
28.0
0.0
0.0
0.0
0.0
0.0
44.0
16.0
4.0
4.0
0.0
0.0
100.00
-------
Exhibit A-16
Probability Decision Tree: Surface Water Systems Serving 101-500 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
8.0
53.0
0.0
0.0
0.0
0.0
0.0
24.0
9.0
3.0
3.0
0.0
0.0
100.00
50-90%
8.0
53.0
0.0
0.0
0.0
0.0
0.0
24.0
9.0
3.0
3.0
0.0
0.0
100.00
>90%
8.0
53.0
0.0
0.0
0.0
0.0
0.0
24.0
9.0
3.0
3.0
0.0
0.0
100.00
-------
Exhibit A-17
Probability Decision Tree: Surface Water Systems Serving 501-1,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
21.0
70.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
4.0
4.0
0.0
0.0
100.00
50-90%
21.0
70.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
4.0
4.0
0.0
0.0
100.00
>90%
21.0
70.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
4.0
4.0
0.0
0.0
100.00
-------
Exhibit A-18
Probability Decision Tree: Surface Water Systems Serving 1,001-3,300 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Percent of Treatment Required to
Achieve MCL
<50%
18.0
79.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
50-90%
18.0
79.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
>90%
18.0
79.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
Sum of Probabilities:
100.00
100.00
100.00
-------
Exhibit A-19
Probability Decision Tree: Surface Water Systems Serving 3,301-10,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
11.0
87.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
50-90%
11.0
87.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
>90%
11.0
87.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
-------
Exhibit A-20
Probability Decision Tree: Surface Water Systems Serving 10,001-50,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Percent of Treatment Required to
Achieve MCL
<50%
5.0
95.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
50-90%
5.0
95.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
>90%
5.0
95.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Sum of Probabilities:
100.00
100.00
100.00
-------
Exhibit A-21
Probability Decision Tree: Surface Water Systems Serving 50,001-100,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash stream and pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
6.0
88.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
2.0
3.0
0.0
0.0
100.00
50-90%
6.0
88.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
2.0
3.0
0.0
0.0
100.00
>90%
6.0
88.0
0.0
0.0
1.0
0.0
0.0
0.0
0.0
2.0
3.0
0.0
0.0
100.00
-------
Exhibit A-22
Probability Decision Tree: Surface Water Systems Serving 100,001-1,000,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash stream and pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
5.0
93.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
50-90%
5.0
93.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
>90%
5.0
93.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
100.00
-------
A.6 Very Large System Cost Methodology
EPA must conduct a thorough cost-benefit analysis, and provide comprehensive, informative,
and understandable information to the public about its regulatory efforts. As part of these
analyses, EPA evaluated the regulatory costs of compliance for very large systems, who would be
subject to the new arsenic drinking water regulation. The nation's 25 largest drinking water
systems (i.e., those serving a million people or more) supply approximately 38 million people
and generally account for about 15 to 20 percent of all compliance-related costs. Accurately
determining these costs for future regulations is critical. As a result, EPA has developed
compliance cost estimates for the arsenic and radon regulations for each individual system that
serves greater than 1 million persons. These cost estimates help EPA to more accurately assess
the cost impacts and benefits of the arsenic regulation. The estimates also help the Agency
identify lower cost regulatory options and better understand current water systems' capabilities
and constraints.
The system costs were calculated for the 24 public water systems that serve a retail population
greater than 1 million persons and one public water system that serves a wholesale population of
16 million persons. Exhibit A-23 lists these 25 public water systems. The distinguishing
characteristics of these very large systems include:
• a large number of entry points from diverse sources;
mixed (i.e. ground and surface) sources;
• occurrence not conducive to mathematical modeling;
• significant levels of wholesaling;
• sophisticated in-place treatment;
retrofit costs dramatically influenced by site-specific factors; and
• large amounts of waste management and disposal which can contribute substantial
costs.
Generic models cannot incorporate all of these considerations; therefore, in-depth
characterizations and cost analyses were developed utilizing several existing databases and
surveys.
The profile for each system contains information such as design and average daily flows,
treatment facility diagrams, chemical feed processes, water quality parameters, system layouts,
and intake and aquifer locations. System and treatment data were obtained from the following
sources:
• The Information Collection Rule (1997);
The Community Water Supply Survey (1995);
• The Association of Metropolitan Water Agencies Survey (1998);
• The Safe Drinking Water Information System (SDWIS); and
The American Water Works Association WATERSTATS Survey (1997)
While these sources contained much of the information necessary to perform cost analyses, the
Agency was still missing some of the detailed arsenic occurrence data in these large water
Appendix A, Decision Tree and Large System Costs A-31 Proposed Arsenic in Drinking Water Rule RIA
-------
systems. Where major gaps existed, especially in groundwater systems, occurrence data obtained
from the States of Texas, California, and Arizona, the Metropolitan Water District of Southern
California Arsenic Study (1993), the National Inorganic and Radionuclides Study (EPA, 1984),
and utilities were used. Based on data from the studies, detailed costs estimates were derived for
each of the very large water systems.
Exhibit A-23
List of Large Water Systems That Serve More Than 1 Million People
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
PWS ID #
AZ0407025
CA01 10005
CA1910067
CA1910087
CA3710020
CA3810001
CA4310011
CO01 16001
FL41 30871
GA1210001
IL0316000
MA6000000
MD01 50005
MD0300002
MI0001800
MO6010716
NY51 10526
NY7003493
OH1800311
PA1510001
PR0002591
TX0570004
TX1010013
TX150018
WA5377050
Utility Name
Phoenix Municipal Water System
East Bay Municipal Utility District
Los Angeles-City Dept. of Water and Power
Metropolitan Water District of Southern California
San Diego- City of
San Francisco Water Department
San Jose Water Company
Denver Water Board
Miami-Dade Water And Sewer Authority-Main System
City of Atlanta
City of Chicago
Massachusetts Water Resource Authority
Washington Suburban Sanitation Commission
Baltimore City
City of Detroit
St. Louis County Water County
Suffolk County Water Authority
New York City Aqueduct System
City of Cleveland
Philadelphia Water Department
San Juan Metropolitano
Dallas Water Utility
City of Houston- Public Works Department
San Antonio Water System
Seattle Public Utilities
Appendix A, Decision Tree and Large System Costs A-32
Proposed Arsenic in Drinking Water Rule RIA
-------
Cost estimates were generated for each system at several MCL options. The total capital costs
and operational and maintenance (O & M) costs were calculated using the profile information
gathered on each system, conceptual designs (i.e., vendor estimates and RS Means), and
modified EPA cost models (i.e., Water and WaterCost models). The models were modified
based on the general cost assumptions developed in the Phase I Water Treatment Cost Upgrades
(EPA, 1998).
Preliminary cost estimates were sent to all of the systems for their review. Approximately 30
percent of the systems responded by submitting revised estimates and/or detailed arsenic
occurrence data. Based on the information received, EPA revised the cost estimates for those
systems. Based on the results, only 3 of the very large systems had capital and/or O&M
expenditures for complying with a MCL of 10 |ig/L. More detailed costs estimates for each very
large water system can be found in Radon and Arsenic Regulatory Compliance Costs for the 25
Largest Public Water Systems document, which is located in the water docket.
Appendix A, Decision Tree and Large System Costs A-33 Proposed Arsenic in Drinking Water Rule RIA
-------
Appendix B: Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B.1 Community Water Systems Serving Fewer than One Million People
B.1.1 Introduction
EPA's estimation of the number of cancer cases resulting from current levels of exposure to
arsenic from drinking water in community water systems serving fewer than one million people,
and the number of those cases that would be avoided following implementation of a specified
arsenic MCL are obtained using the following basic risk algorithm.
Rfcd = C(As)Ind * [DWfcd * DWAdj] * Runit Equation B-l
The components of this risk algorithm are as follows.
C(As)Ind is the concentration of arsenic in drinking water that a given individual is exposed to, on
average, over the course of his or her lifetime. C(As)Ind is obtained from the occurrence
assessment distributions for surface water and ground water and is expressed in units of |ig/L.
DWInd is the daily drinking water consumption for a given individual, and is incorporated in this
model as a lifetime weighted average expressed in units of L/kg-day. As a lifetime weighted
average, this drinking water consumption value reflects differences in water consumption per
kilogram body weight that is observed to occur over an individual's lifetime. This variable is
also a function of the individual's sex.
DWAdj is an adjustment factor constant (= 70 kg + 2 L/day) that is applied to the weighted
average 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 average daily intake of
2 L/day and a lifetime average body weight of 70 kg.
It should be noted that the quantity [DWtod * DWAdj] is also referred to in this modeling effort as
the Lifetime Relative Exposure Factor (LREF). The LREF reflects a particular individual's
lifetime exposure to arsenic from drinking water, given that person's DWInd value relative to an
"average" individual consuming 2 L/day of water and weighing 70 kg. An LREF value less than
one indicates the person has less lifetime exposure (and therefore less risk) than such an "average
person" used to derive the unit risk factor; similarly a value greater than one indicates a higher
lifetime exposure and greater risk than that "average person".
RUnit 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 "expected cases per person per jig/day." It is important to
note that these unit risks, as derived from the Morales (2000) study are lifetime risks, that were
developed with an underlying assumption of 70 years of exposure and a lifetime average water
Appendix B, Assumptions and Methodology for B-l Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
consumption of 2 L/day and body weight of 70 kg. It should also be noted that the Morales
(2000) cancer risk factors used in this modeling, which are derived from an analysis 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 regulation utilizes Equation B-l in a
Monte Carlo simulation framework that provides information on the aggregate number of cases
of cancer occurring (and avoided) in the overall population, as well as a characterization of the
distribution of risks experienced by different individuals in the exposed population as a result of
individual variability in exposure conditions. Because some of the factors that result in
individual variability in exposure and risk are sex and source water dependent, the Monte Carlo
model also incorporates information on fraction of males and females in the population, and on
the proportion of individuals using surface water versus ground water as their primary
community water supply source.
As an overview of how the simulation model operates, it can be viewed as being similar to taking
a representative sample from the population exposed to arsenic in drinking water from
community water systems and using the results obtained from that sample to characterize the
overall risks of the population. In this modeling, a total of 2,000 iterations (samples) were used
for each model run.
In each iteration, an individual is selected, and identified as male or female and as a ground 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-l, based on the underlying
probability distributions developed for each of those variables, and specific to the sex and source
water as specified for that individual as appropriate.
The Equation B-l calculation is carried out to determine that individual's lifetime cancer risk,
Rtod. The results of all 2,000 iterations are aggregated, and the average individual risk across all
iterations is determined. This average risk value, multiplied by the number of individuals in the
populations served by the affected water systems, provides the number of cases of cancer
expected.
To complete the benefits modeling, a baseline with no reduction in the MCL (or arsenic levels 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
estimate of cases avoided.
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 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
B.1.2 Arsenic Concentrations in Finished Water of Community Water Systems
Serving Fewer than One Million People
This section provides further information on the variable C(As)tod in Equation B-l.
EPA has developed lognormal arsenic occurrence distributions for the nation's community
ground water and surface water systems serving fewer than one million people. These arsenic
occurrence distributions, which reflect the probability of arsenic concentrations occurring at
various levels in finished drinking water in surface and ground water systems, are used in the
benefits model to characterize the variability in arsenic drinking water concentrations
experienced by different individuals using these public water supplies.
Although the arsenic occurrence distributions were developed to characterize the full distribution
of finished water arsenic concentrations, the benefits modeling focused only on the portion of
those distribution exceeding 3 |ig/L, the lowest MCL option considered by EPA. EPA used the
separate lognormal occurrence probability distributions for ground water and surface to first
determine the number of people served by community water systems from each of those two
source waters (and the total) expected to have arsenic present above 3 |ig/L.
In the Monte Carlo simulation model, the selection of a value for C(As)Ind of Equation B-l in
each iteration involved two steps. First, using relative probabilities derived from the lognormal
occurrence distributions, an individual was selected and identified as being served by either
ground or surface water having an arsenic above 3 |ig/L. In the second step, a specific finished
water arsenic concentration was chosen at random from the appropriate ground or surface water
occurrence distribution in the range exceeding 3 |ig/L.
By including a sufficient number of iterations in the Monte Carlo model, the full range of
individual variability in exposure to different arsenic concentrations in the range of interest for
both surface water and ground water sources is obtained.
In the baseline analysis (that is, with no change to the 50 |ig/L MCL), the selected finished water
arsenic concentration value was used directly in the risk equation. In the model runs for various
MCL options, that value was compared to the MCL. If that value was less than or equal to the
MCL, it was also kept. If however the selected value exceeded the MCL, then it was multiplied
by a factor of 0.8 of the MCL value reflecting an assumption that systems would treat to a level
of 80% of the MCL. So, for example, if an iteration of a model run examining the 10 |ig/L MCL
option produced a finished water arsenic value of 25 |ig/L, that value was changed to 8 |ig/L. If
the model run were for the option of a 20 jig/L MCL, that value would be changed to 16 |ig/L.
It should be noted that for the purposes of the benefits modeling, the concentration used is
implied to be a lifetime average exposure level for the individual in that iteration.
B.1.3 Drinking Water Consumption
This section provides further information on the variables DWtod and DWAdj in Equation B-l.
Appendix B, Assumptions and Methodology for B-3 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
The variable DWtod reflects the differences (variability) in individual water consumption within
the exposed population. In Equation B-l, the variable DWInd is expressed in units of L/kg-day
reflecting differences in consumption among individuals in the population as a function of body
weight. This value is a lifetime average water consumption rate for individuals, recognizing that
consumption of water per kg body weight changes over a lifetime, particularly between infancy,
childhood and adulthood.
EPA obtained the distribution of individual weighted average lifetime water consumption values
in terms of L/kg-day by integrating available data on the distribution of water consumption, in
units of L/day, by males and females in the US in various age ranges with information on the
distribution of body weights for males and females within those same age ranges.
The age and sex specific distributions of drinking water consumption in L/day are provided by
data from the Continuing Survey of Food Intakes by Individuals (CSFII) for the years 1994-1996
conducted by the U.S. Department of Agriculture (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 analysis of drinking water consumption data in the CSFII provided the basis
for several alternative ways of viewing drinking water consumption, in particular, how to include
various direct water sources - for example, from community tap water, bottled water, household
wells - consumed directly as a beverage, and indirect water that is water from such sources that
is added to other foods during preparation at home or by food service establishments.
For the purposes of the arsenic benefits analysis, EPA chose to use two alternative sets of
drinking water distributions to characterize lower and upper bounds of risk.
For the lower bound analyses, EPA used the CSFII 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 average individual consumption (across
all ages and both sexes) of approximately 1.0 L/day, with a 90th percentile value of approximately
2.1 L/day.
For the upper bound analyses, EPA used the CSFII drinking water distribution for total water,
which includes community tap water, bottled water, and other sources, and also reflects both
direct and indirect consumption of that water. This upper bound distribution reflects an overall
average individual consumption (across all ages and both sexes) of approximately 1.2 L/day, with
a 90th percentile value of approximately 2.3 L/day.
For the purposes of the arsenic benefits analysis, it was necessary to integrate the age and sex
specific water consumption distributions (in L/day) with information available from Statistical
Abstracts (1994) providing body weight distributions for the same sex-age categories included in
the CSFII data. A submodel was run for this portion of the benefits analysis that effectively
generated DWInt values for individuals by "constructing" a lifetime weighted average water
Appendix B, Assumptions and Methodology for B-4 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
consumption value in units of L/kg-day. Five age categories, based on the manner in which
CSFn data were presented, were used for building these lifetime consumption values. These age
categories were:
< 1
1-10
11-19
20-64
65-70
Again, CSFn provided water consumption information separately for males and females in each
of these categories, and Statistical Abstracts (1994) provided body weight distributions for these
categories. In 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
average body weight for each of the five age categories is selected, and an average intake for each
age category is computed by dividing the water consumption value selected by the body weight
selected.
The individual's lifetime weighted average (DWInd in Equation B-l) is then computed by
averaging across the five age groups, weighting each appropriately for the number of years spent
in that age range.
An additional adjustment factor had to be incorporated into Equation B-l in order to account for
the fact that the cancer unit risk factors used were calculated with an underlying assumption that
it applied to an "average" person weighing 70 kg and consuming 2 L/day over the entire 70 year
lifetime (or 0.0286 L/kg-day). Since drinking water consumption is being modeled in this
analysis to explicitly account for the variability in water consumption as a function of body
weight, proceeding without this adjustment would overestimate the cancer risk for those
individuals with a lifetime weighted average 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
average.
Because, as noted from the CSFII data, average water consumption across all age and sex groups
is closer to 1.0 - 1.3 L/day and because lifetime average body weights are (especially for
females) lower than 70 kg, failing to make this adjustment would in the aggregate overestimate
cancer risk.
By applying the DWAdj adjustment factor of 70 kg/(2 L/day) to the water consumption values
obtained in the simulation, this correction for the underlying basis of the risk value is
accomplished.
The water consumption and adjustment discussed above are described in greater detailed in the
RIA and its accompanying Appendix B. In that analysis, the product of the water consumption
and the adjustment factor are described as the Lifetime Relative Exposure Factors (LREF), which
reflects the exposure and risk relative to the 70 kg, 2 L/day (i.e., 0.0286 L/kg-day) person. In that
Appendix B, Assumptions and Methodology for B-5 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
more detailed analysis, it is shown that the overall distribution of these factors tends to be
lognormal with means and standard deviations as shown in Exhibit B-l for both males and
females and the lower and upper bound water consumption distributions. In essence, these LREF
values indicate that, on average, individual exposure 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.
Exhibit B-1
Summary of Lifetime Relative Exposure Factors (LREF):
(Product of DW,nd * DWAdi. Overall Distributions are Lognormal)
Male
Female
Community Water Consumption Data
Mean = 0.60
s.d. = 0.61
Mean = 0.64
Total Water Consumption Data
Mean = 0.73
s.d. = 0.62
Mean = 0.79
B.1.4 Cancer Risk Factors
This section provides further information on the variable RUnit in Equation B-l.
In its 1999 report, "Arsenic in Drinking Water," the NRC analyzed bladder cancer risks using
data from Taiwan. In addition, NRC examined evidence from human epidemiological studies in
Chile and Argentina, and concluded that risks of bladder and lung cancer had comparable risks to
those "in Taiwan at comparable levels of exposure" (NRC, 1999). The NRC also examined the
implications of applying different statistical analyses to the newly available Taiwanese data for
the purpose of characterizing bladder cancer risk. While the NRC's work did not constitute a
formal risk analysis, they did examine many statistical issues (e.g., measurement errors, age-
specific probabilities, body weight, water consumption rate, comparison populations, mortality
rates, choice of model) and provided a starting point for additional EPA analyses. The report
noted that "poor nutrition, low selenium concentrations in Taiwan, genetic and cultural
characteristics, and arsenic intake from food" were not accounted for in their analysis (NRC,
1999, pg. 295). In the June 22, 2000 proposed rule, EPA calculated bladder cancer risks and
benefits using the bladder cancer risk analysis from the NRC report (NRC, 1999). We also
estimated lung cancer benefits in a "What If analysis based on the statement in the 1999 NRC
report that "some studies have shown that excess lung cancer deaths attributed to arsenic are 2-5
fold greater than the excess bladder cancer deaths" (NRC, 1999).
In July, 2000, a peer reviewed article by Morales et al. (2000) was published, which presented
additional analyses of bladder cancer risks as well as estimates of lung and liver cancer risks for
the same Taiwanese population analyzed in the NRC report. EPA summarized and analyzed the
new information from the Morales et al. (2000) article in a NODA published on October 20,
2000 (65 FR 63027; EPA, 2000). Although the data used were the same as used by the NRC to
analyze 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
Estimating Cancer Risks Avoided and Benefits
B-6
Arsenic in Drinking Water Rule EA
-------
without one of two comparison populations. After consultation with the primary authors
(Morales and Ryan), EPA chose Model 1 with no comparison population for further analysis.
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 exposure. Most of the models with
comparison populations resulted in dose-response curves that were supralinear (higher than a
linear dose response) at low doses. The curves were "forced down" near zero dose because the
comparison population consists of a large number of people with low risk and low exposure.
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. First, there is no basis in data on
arsenic's carcinogenic mode of action to support a supralinear curve as being biologically
plausible. To the contrary, the conclusion of the NRC panel (NRC, 1999) was that the mode of
action data led one to expect 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 except for arsenic exposure. Yet Morales et al.
(2000) agree that "[tjhere 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 large amount of data in the comparison populations, the model results are sensitive to
assumptions about this group. Evidence that supports these arguments are that the risks in the
comparison groups are substantially lower than in similarly exposed members of the study group
and the shape of the estimated dose-response changes sharply as a result. For 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 Information Criterion (AIC), a standard criterion of model fit,
applied to Poisson models. In Model 1, the relative risk of mortality at any time is assumed to
increase exponentially with a linear function of dose and a quadratic function of age.
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
age effect, and a multi-stage Weibull (MSW) model. Under Model 2, the points of departure for
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% higher for bladder cancer and for female lung cancer, and
38% lower for male lung cancer. EPA did not consider the MSW model for further analysis,
because this model is more sensitive to the omission of individual villages (Morales et al., 2000)
and to the grouping of responses by village (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 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
Considering all of these results, the Agency decided that the more exhaustive statistical analysis
of the data provided by Morales et al. (2000), as analyzed by EPA, would be the basis for the
new risk calculations for the final rule (with further consideration of additional risk analyses) and
other pertinent information. The Agency 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 analysis, and their conversion to the RUnit values of cases per person per |ig/L are shown
in Exhibit B-2, below.
Exhibit B-2
Risk Measures from Morales (2000) and as Used in this Benefit Analysis
ED01 (MQ/L)
Mean for RUnit (cases/person
per pg/L)
LED01 (ng/L)
Upper 95% CL for RUnit
(cases/person per gq/L)
Bladder Cancer
Males
395
2.53 x10'5
326
3.07 x10'5
Females
252
3.97 x10'5
211
4.74 x10'5
Lung Cancer
Males
364
2.75 x10'5
294
3.40 x10'5
Females
258
3.88 x10'5
213
4.69 x10'5
The ED01 values provided by Morales (2000) indicate that this is the arsenic concentration in
drinking water that if consumed by an individual over a lifetime (with the assumption of 2 L/day
and 70 kg body weight) has a 0.01 risk (i.e., 1% probability) of resulting in the indicated form of
cancer. The LED01 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-l, these risk measures are converted
to the units of cases/person per |ig/L needed for RUnit by simply dividing 0.01 by the
corresponding ED01 or LED01 |ig/L values.
In the Monte Carlo simulation, the RUnit value was incorporated as normal distribution with
parameters based on the mean and upper 95% confidence limit as shown in Exhibit 3-D.2
B.1.5 Upper and Lower Bound Considerations
In carrying out the arsenic benefits analysis, 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 noted in the preceding discussions. These are discussed more fully here.
For the upper bound analyses, EPA used:
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-8
Arsenic in Drinking Water Rule EA
-------
The surface water and ground water occurrence distributions as provided in the occurrence
analyses;
The drinking water consumption distribution using the total water consumption data from
CSFII (i.e., averaging approximately 1.2 L/day)
The unit cancer risk factor distribution based on the RUnit values shown in Exhibit 3.D.2.
For the lower bound analyses, EPA used:
The surface water and ground water occurrence distributions as provided in the occurrence
analyses (same as upper bound);
The drinking water consumption distribution using the community (tap) water consumption
data from CSFII (i.e., averaging approximately 1.0 L/day)
The unit cancer risk factor distribution based on the RUnit values shown in Exhibit 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. Both 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.
First, the Agency made an adjustment to the lower bound risk estimates to take into consideration
the effect of exposure to arsenic through water used in preparing food in Taiwan. The Taiwanese
staple foods were dried sweet potatoes and rice (Wu et al., 1989). Both the 1988 EPA "Special
Report on Ingested Inorganic Arsenic" report and the 1999 NRC report assumed that an average
Taiwanese male weighed 55 kg and drank 3.5 liters of water daily, and that an average Taiwanese
female weighed 50 kg and drank 2 liters of water daily. Using these assumptions, along with an
assumption that Taiwanese men and women ate one cup of dry rice and two pounds of sweet
potatoes a day, the Agency re-estimated risks for bladder and lung cancer, using one additional
liter water consumption for food preparation (i.e., the water absorbed by hydration 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 high arsenic concentration in the food consumed in Taiwan as compared to the U.S.
The food consumed daily in Taiwan contains about 50 • g, versus about 10 • g in the U.S. (NRC,
1999, pp. 50-51). Thus the total consumption of inorganic arsenic (from food preparation and
drinking water) is considered, per kilogram of body weight, 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 • 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 • g/kg/day basis.
Other factors contributing to lower bound uncertainty include the possibility of a sub-linear dose-
Appendix B, Assumptions and Methodology for B-9 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks 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 range is
predicted, although linearity cannot be ruled out." (NRC, 1999). The recent Utah study (Lewis et
al., 1999), described in section 5.G.l(b), provides some evidence that the shape of the dose-
response curve may well be sub-linear at low doses. Because sufficient mode of action data were
not available, an adjustment was not made to the risk estimates to reflect the possibility of a sub-
linear dose-response curve. Additional factors contributing to uncertainty include the use of
village well data rather than individual exposure data, deficiencies in the Taiwanese diet relative
to the U.S. diet (selenium, choline, etc.), and the baseline health status in the Taiwanese study
area relative to U.S. populations. The Agency 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 Carlo simulation performed for this benefits analysis using the risk algorithm shown
in Equation B-l produce distributions of individual risk values (R Ind) for the baseline and the
various MCL options considered, and for both the upper and lower bound sets of assumptions.
Exhibit B-3 provides some summary statistics for the resulting distribution of risks. Note that
the "exposed population" addressed in this table are those individuals using community ground
or surface water supplies serving fewer than one million people having arsenic levels greater than
3ug/L.
The key outputs resulting from this Monte Carlo simulation for estimating cancer cases avoided
are the mean risk values shown in Exhibit B-3. The application of these mean risk values to
estimate cases avoided is described in the following section.
Exhibit B-3
Cancer Risks for U.S. Populations
Exposed At or Above MCL Options, after Treatment
(Lower Bound With Food and Cooking Water Adjustment)
3
5
10
20
Mean Risk for Exposed
Population (Lower and Upper
Bounds)
0.11-1.25x1Q-4
0.27- 2.02 x10'4
0.63- 2.99 x10'4
1.10-3.85x10-4
90th Percentile Risk for Exposed
Population (Lower and Upper
Bounds)
0.22- 2.42 x10'4
0.55- 3.9 x10'4
1.32-6.09x10-4
2.47- 8.37 x10'4
B.1.7 Estimated Cancer Cases and Cases-Avoided
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-10
Arsenic in Drinking Water Rule EA
-------
To estimate the number of cancer cases avoided for the various MCL options it is necessary to
first calculate the number of cases expected at the baseline risk level (no change in the MCL, or
50 ng/L), and then for each MCL option. Baseline mean risk values and estimated mean risk
levels for the various MCL options (shown in Exhibit B-3) are multiplied by the total number of
people served by community ground and surface water systems serving fewer than one million
people. Because the lower bound risk adjustments are also made to the baseline risk (the risk at
50 |ig/L), the baseline number of expected cases in the adjusted risk scenario is not the same (it's
lower, just as the adjusted risks are lower) as the baseline number of expected cases in the
unadjusted risk scenario. The number of cases avoided at each MCL alternative is determined by
subtracting the number of cases remaining at each option from the appropriate baseline number
of cases. Thus, to estimate cases avoided, the number of remaining cases expected at the lower
risk levels are subtracted from the number of cases expected at the lower baseline level, and the
number of remaining cases expected at the higher risk levels are subtracted from the number of
cases expected at the higher baseline level.
An upper bound adjustment was made to the number of bladder cancer cases avoided to reflect a
possible lower mortality rate in Taiwan than was assumed in the risk assessment process
described earlier. EPA also made this adjustment in the June 22, 2000, proposal. In the Taiwan
study area, information on arsenic related bladder and lung cancer deaths was reported. In order
to use these data to determine the probability of contracting bladder and lung cancer as a result of
exposure to arsenic, a probability of mortality given 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 high by comparison to those in the
U.S., and an area of low incomes and poor diets, where the availability and quality of medical
care is not of high quality, by U.S. standards. In its estimate of bladder cancer risk, the Agency
assumed that within the Taiwanese study area, the probability of contracting bladder cancer was
relatively close to the probability of dying from bladder cancer (that is, that the bladder cancer
incidence rate was equal to the bladder cancer mortality rate).
We do not have data on the rates of survival for bladder cancer in the Taiwanese villages in the
study and at the time of data collection. We do know that the relative survival rates for bladder
cancer in developing countries overall ranged from 23.5% to 66.1 % in 1982-1992 ("Cancer
Survival in Developing Countries," International Agency for Research on Cancer, World Health
Organization, Publication No. 145, 1998). We also have some information on annual bladder
cancer mortality and incidence for the general population of Taiwan in 1996. The age-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, January 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 general population of Taiwan, at present, is 45%. Since survival rates have
most likely improved over the years since the original Taiwanese study, this number represents a
lower bound on the survival rate for the original area under study (that is, one would not expect a
higher rate of survival in that area at that time). This has implications for the bladder cancer risk
estimates from the Taiwan data. If there were any persons with bladder cancer who recovered
and died from some other cause, then our estimate underestimated risk; that is, there were more
Appendix B, Assumptions and Methodology for B-l 1 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
cancer cases than cancer deaths. Based on the above discussion, we think bladder cancer
incidence could be no more than 2 fold bladder cancer mortality; and that an 80% mortality rate
would be plausible. Thus we have adjusted the upper bound of cases avoided, which is used in
the benefits analysis, to reflect a possible mortality rate for bladder cancer of 80%. Because lung
cancer mortality rates are quite high, about 88% in the U.S.(US EPA, 1998b), the assumption
was made that all lung cancers in the Taiwan study area resulted in fatalities.
The total number bladder and lung cases avoided at each MCL are shown in Exhibit 3-D.3.
These cases avoided include CWS and NTNC cases. The number of bladder and lung cancer
cases avoided range from 57.2 to 138.3 at an MCL of 3 • g/L, 51.1 to 100.2 at an MCL of 5 • g/L,
37.4 to 55.7 at an MCL of 10 • g/L, and 19.0 to 19.8 at an MCL of 20 • g/L. The cases avoided
were divided into premature fatality and morbidity cases based on U.S. mortality rates. In the
U.S. approximately one out of four individuals who is diagnosed with bladder cancer actually
dies from bladder cancer. The mortality rate for the U.S. is taken from a cost of illness study
recently completed by EPA (US EPA, 1998b). For those diagnosed with bladder cancer at the
average age of diagnosis (70 years), the probability for dying of that disease during each year
post-diagnosis were summed over a 20-year period to obtain the value of 26 percent. Mortality
rates for U.S. bladder cancer patients have decreased overall by 24 percent from 1973 to 1996.
For lung cancer, mortality rates are much higher. The comparable mortality rate for lung cancer
in the U.S. is 88% (US EPA, 1998b).
B.2 Community Water Systems Serving More than One Million People
A separate analysis of the number of cancer cases and cases avoided was performed for
community water systems serving more than one million people each. This analysis was based
upon specific information available for each on the occurrence of arsenic in specific sources
(entry points) for those systems, the flows for those entry points, and the number of people
served by those specific systems.
Only three systems serving more than one million people were found to have arsenic levels in
one or more entry point exceeding 3 |ig/L: Phoenix, Houston, and Los Angeles.
The basic risk algorithm used for systems serving fewer than one million people as shown in
Equation B-l was also used for calculating cancer cases and cases avoided for the systems
serving more than one million people.
There were two primary difference in the application of Equation B-l for the systems serving
more than one million people relative to its application for systems serving fewer than one
million. First, the analysis was not done as a Monte Carlo simulation, but was based on average
values for the variables in the equation. For example, the RUnit values used were equivalent to the
mean risk values for the upper and lower bound risks as shown previously in exhibit 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-l 2 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
The water consumption and adjustment factors [DWtod * DWAdj] were simplified and used as
average values rather than distributions.
The arsenic water concentrations [C(As)Ind] used were calculated separately for each of the three
very large systems using system-specific data. These calculations were carried out as follows.
Data was available on the arsenic concentration at each of the ground water and surface water
entry points at each of these three very large systems. Data were also available on the average
daily flow for the ground water and surface water sources in total.
EPA used that information to calculate an initial average arsenic concentration, CInitial, for that
portion of the system exceeding a particular MCL option as follows.
C
Initial
t-GA
FP F
rjr GA 9 G
FP F
_^r GT rT _
FP F
^rGA 9 r G
FP F
r/rGT rT _
+ CSA
+
FP F
^r SA 9 rS
FP F
_rST rT _
FP F
r/rSA 9 rS
FP F
_r/rST rT _
where:
CGA =the average arsenic concentration in the ground water entry points affected at that MCL
option
CSA = the average arsenic concentration in the surface water entry points affected at that MCL
option
EPGA = the number of ground water entry points affected at that MCL option
EPGT = the total number of ground water entry points in that system
EPSA = the number of surface water entry points affected at that MCL option
EPST = the total number of surface water entry points in that system
FG = the total average daily flow from all ground water sources
Fs = the total average daily flow from all surface water sources
FT = the total average daily flow from all water sources
These CInitial values were used for C(As)Ind in Equation B-l 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 large systems was calculated as
being the same portion of the total population served by that system as the portion of total flow
affected at the given MCL option.
The post-regulatory cases remaining were calculated using the same procedure, except that a
constant value was used for C(As)tod that was equal to 0.8 * MCL value.
B.3 Non-Transient Non-Community Water Systems
B.3.1 Data Inputs
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-13
Arsenic in Drinking Water Rule EA
-------
Most of the data described above under the CWS risk model is also used in the NTNC risk
model. This includes water consumption, body weight, and lifetime risk estimates. Also, the
ground water arsenic concentrations at each MCL used in the CWS risk model are used in the
NTNC risk model.
B.3.1.1 NTNC Service Categories, Population and Exposure Time
The main differences between the CWS and NTNC risk models are how population is distributed
among the different types of establishments that make up the NTNC category of systems, and the
extent to which the worker and customer populations within a service category are exposed to
arsenic (both in terms of length of exposure and drinking water consumed).
In addition to the CWS data already discussed, Exhibits B-4 and B-5 provide all of the data
inputs necessary to model the bladder cancer risk associated with NTNC systems. First, note that
in Exhibit B-4, the NTNC universe has been divided into 35 service categories. This was
accomplished using the system descriptions in SDWIS (EPA, 1999b). For each service category,
the total number of NTNCs and the population served by these NTNCs is taken from SDWIS.
The population served by each NTNC often varies daily; the SDWIS population numbers are
interpreted to mean the peak population served (both workers and customers).
The next data field in Exhibit B-4 is the number of customer cycles per year, or the number of
times each year the customer base turns over. For example, if this parameter equals one, then the
same customer's are served each day. If the value is seven, then seven sets of customers use the
facility. The next field is the number of workers per person per day. For example, if the value is
0.1, as in the case of summer camps, then 10 percent of the peak population served (from
SDWIS) is assumed to be workers. Both the number of customer cycles per year assumptions
and workers per person per day data assumptions were made after investigating numerous data
sources, including trade-journals and trade association information.
The next set of data fields in Exhibit B-4 are assumptions about the characteristics of the workers
in each service type. The percent of workers' daily consumption is the percentage of drinking
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 category. The number of days a person works is
assumed to be 250 for all service categories. The number of years a person works at the NTNC
establishment is assumed to be either 40 or 10, depending on the service category.
Information regarding customer behavior is provided in the next set of data fields in Exhibit B-4.
The percent of customers' daily consumption is the percentage 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 category.
The number of days a customer visits the NTNC is provided for each service category. For
example, the value for nursing homes of 365 indicates that nursing home customers are served by
the nursing home year round, while the value for churches of 52 indicates that churches are
assumed to serve their customers once per week. The number of years a person is assumed to
visits each service category is also provided.
Appendix B, Assumptions and Methodology for B-14 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
Finally, the total exposed worker and customer populations for each service category are
provided in Exhibit B-4. These numbers are calculated as follows:
TCC = (PC*CCC)*(1-WPC)
TWC = PC*WPC
where:
TC = total number of customers
TW = total number of workers
P = SDWIS population
WP = workers per person per day
CC = number of customer cycles per year
c = NTNC service category
Exhibit B-5 provides the final set of data required to estimate bladder cancer risk from NTNCs.
The percent of worker lifetime exposure is the percent of lifetime water consumption which is
consumed at the NTNC by a worker. The percent of customer lifetime exposure is the percent of
lifetime water consumption consumed at the NTNC by a customer. These numbers are
calculated as follows:
PWDC *DW *YW
PWLE =—
PCLE,, =
365*70
PCDC *DC *YC
C 0 0
365*70
where;
PWLE = percent of worker lifetime exposure
PCLE = percent of customer lifetime exposure
PWDC = percentage of workers daily consumption
PCDC = percentage of customers daily consumption
DW = worker days per year
DC = customer days per year
YW = worker years
YC = customer years
Returning to Exhibit B-5, the worker age bracket is the age range (corresponding to the age
ranges used in the CWS risk analysis) that a NTNC worker is assumed to fall in. For all service
categories, the worker age bracket is assumed to be 20-64 years of age. The customer age
bracket is the age range (corresponding to the age ranges used in the CWS risk analysis) that a
NTNC customer is assumed to be in. For most service categories, the customer age bracket is
Appendix B, Assumptions and Methodology for B-15 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
assumed to be 0-70 years of age (all ages). However, certain service categories only serve certain
age groups (e.g. nursing homes and schools), therefore more specific age ranges are assumed.
Appendix B, Assumptions and Methodology for B-16 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
Exhibit B-4
NTNC Population and Exposure Time
Data
Water Wholesalers
Mobile Home Parks
Nursing Homes
Churches
Golf and Country Clubs
Retailers (Food related)
Retailers (Non-food related)
Restaurants
Hotels/Motels
Prisons/Jails
Service Stations
Agricultural Products/Services
Daycare Centers
Schools
State Parks
Medical Facilities
Campgrounds/RV Parks
Federal Parks
Highway Rest Areas
Misc. Recreation Services
Forest Service
Interstate Carriers
Amusement Parks
Summer Camps
Airports
Military Bases
Non-Water Utilities
Office Parks
Manufacturing: Food
Manufacturing: Non-Food
Landfills
Fire Departments
Construction
Mining
Migrant Labor Camps
Number
of
Systems
266
104
130
230
116
142
695
418
351
67
53
368
809
8,414
83
367
123
20
15
259
107
287
159
46
101
95
497
950
768
3,356
78
41
99
119
33
Total
SOW IS
Population
66,018
19,240
13,910
11,500
11,716
45,724
120,930
154,660
46,683
121,940
12,190
27,968
61,484
3,086,012
106,895
163,631
19,680
780
6,105
22,533
4,494
35,301
76,462
6,716
326,860
67,525
84,490
181,600
285,696
588,792
3,432
4,018
5,247
13,447
2,079
Number of
Customer
Cycles/Year
1.00
1.33
1.00
1.00
4.50
2.00
4.50
2.00
86.00
1.33
7.00
7.00
1.00
1.00
26.00
16.40
22.50
26.00
50.70
26.00
26.00
93.00
90.00
8.50
36.50
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Worker
Per
Person
Per Day
0
0.046
0.23
0.01
0.11
0.07
0.09
0.07
0.27
0.1
0.06
0.125
0.145
0.073
0.016
0.022
0.041
0.016
0.01
0.016
0.016
0.304
0.18
0.1
0.308
1
1
1
1
1
1
1
1
1
1
Percent of
Worker's
Daily
Consumption
n/a
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
100.0%
50.0%
50.0%
100.0%
50.0%
50.0%
50.0%
50.0%
50.0%
50.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Worker
Days Per
Year
n/a
250
250
250
250
250
250
250
250
250
250
250
250
200
250
250
180
250
250
250
250
250
250
180
250
250
250
250
250
250
250
250
250
250
250
Worker
Years
n/a
40
40
40
40
40
40
40
40
40
40
40
10
40
40
40
40
40
40
40
40
40
10
10
40
40
40
40
40
40
40
40
40
40
40
Percent of
Customer's
Daily
Consumption
25.0%
100.0%
100.0%
50.0%
50.0%
25.0%
25.0%
25.0%
100.0%
100.0%
25.0%
25.0%
50.0%
50.0%
50.0%
100.0%
100.0%
50.0%
50.0%
100.0%
100.0%
50.0%
50.0%
100.0%
25.0%
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Customer
Days Per
Year
270.00
270.00
365.00
52.00
52.00
185.00
52.00
185.00
3.40
270.00
52.00
52.00
250.00
200.00
14.00
6.70
5.00
14.00
7.20
14.00
14.00
2.00
1.00
7.00
10.00
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Customer
Years
70.00
35.00
10.00
70.00
70.00
70.00
70.00
70.00
40.00
3.00
54.00
50.00
5.00
12.00
70.00
10.30
50.00
70.00
70.00
70.00
50.00
70.00
70.00
10.00
70.00
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Total
Worker
Population
0
885
3,199
115
1,289
3,201
10,884
10,826
12,604
12,194
731
3,496
8,915
225,279
1,710
3,600
807
12
61
361
72
10,732
13,763
672
100,673
67,525
84,490
181,600
285,696
588,792
3,432
4,018
5,247
13,447
2,079
Total
Customer
Population
66,018
24,412
10,711
11,385
46,923
85,047
495,208
287,668
2,930,759
145,962
80,210
171,304
52,569
2,860,733
2,734,802
2,624,510
424,645
19,956
306,428
576,484
114,974
2,284,963
5,642,896
51,377
8,255,830
0
0
0
0
0
0
0
0
0
0
Subtotal = 1,662,407 30,305,774
TOTAL = 31,968,181
-------
Exhibit B-5
NTNC Percent of Lifetime Exposure and Age at Exposure
Water Wholesalers
Mobile Home Parks
Nursing Homes
Churches
Golf and Country Clubs
Retailers (Food related)
Retailers (Non-food related)
Restaurants
Hotels/Motels
Prisons/Jails
Service Stations
Agricultural Products/Services
Daycare Centers
Schools
State Parks
Medical Facilities
Campgrounds/RV Parks
Federal Parks
Highway Rest Areas
Misc. Recreation Services
Forest Service
Interstate Carriers
Amusement Parks
Summer Camps
Airports
Military Bases
Non-Water Utilities
Office Parks
Manufacturing: Food
Manufacturing: Non-Food
Landfills
Fire Departments
Construction
Mining
Migrant Labor Camps
Percent
of Worker
Lifetime
Exposure
0.00%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
4.89%
15.66%
19.57%
19.57%
14.09%
19.57%
19.57%
19.57%
39.14%
19.57%
4.89%
7.05%
19.57%
19.57%
19.57%
19.57%
19.57%
19.57%
39.14%
39.14%
39.14%
39.14%
39.14%
Percent of
Customer
Lifetime
Exposure
18.49%
36.99%
14.29%
7.12%
7.12%
12.67%
3.56%
12.67%
0.53%
3.17%
2.75%
2.54%
2.45%
4.70%
1.92%
0.27%
0.98%
1.92%
0.99%
3.84%
2.74%
0.27%
0.14%
0.27%
0.68%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
Worker
Age
Bracket
n/a
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
20 to 64
all
Customer
Age
Bracket
all
all
65+
all
all
all
all
all
all
20 to 64
16 to 70
all
<5
6 to 18
all
all
all
all
all
all
all
all
all
11 to 19
all
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-18
Arsenic in Drinking Water Rule EA
-------
B.3.2 The NTNC Risk Model
Just like the CWS risk analysis, the NTNC risk analysis is a Monte-Carlo based simulation
model. This section will explain each step is the simulation. The Monte-Carlo simulation is
conducted at each MCL option (50, 20, 10, 5 and 3 • g/L). In addition, for each MCL option, the
simulation is carried out for both the "Lower Bound" and "Upper Bound" scenarios just like in
the CWS case. Therefore, the simulation model is carried out ten times. Each of these ten "runs"
of the model is independent of the other, and can be discussed in isolation. Therefore, this
section will include a generalized discussion of the model. The inputs that are used will depend
on the MCL option and scenario being evaluated at the time. It is important not to confuse a
"run" of the model" as just described, and a model iteration. Each run of the model consists of
10,000 iterations. Within a single iteration, the model pulls a value for each variable from its
input distribution (e.g. body weight) 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 first step of each iteration is to calculate the relative exposure factor for each sex and age
category. This is done exactly as it was done in the CWS risk analysis. As shown in the
following equations, the relative exposure factor is a function of daily water consumption and
body weight.
where;
REF = relative exposure factor
C = daily water consumption (L)
W = body weight (kg)
i = model iteration number
a = age category
m = male
f = female
Next, the lifetime risk of bladder cancer (1/100,000 people) is calculated for workers and
customers of each sex for each service category. The next four equations, therefore are:
Appendix B, Assumptions and Methodology for B-19 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
WLRfcl = PWLEC1 * ASgl * (RF; / 50) *
E(REFfai*Zac)
a
2X
*100
WLRmci = PWLEci * AS . * (RF; / 50)
I(REFmai*Zac)
2X
*100
CLRmci = PCLEC1 * ASS1 * (RFj / 50)
E(REFmai*Zac)
= 100
CLRfci = PCLEC1 * ASgl * (RF1 / 50)
I(REFfai*ZJ
a
IX
*100
where;
WLR = worker lifetime risk (per 100,000 people)
CLR = customer lifetime risk (per 100,000 people)
AS = arsenic concentration (• g/L)
RF = risk of bladder cancer at 50 • g/L, 2 liters consumption per day, and 70 kg body weight
Z = years spent in age category
g = ground water
The sex of the worker and customer is then chosen for the iteration to determine the worker and
customer risk for each service category:
WLRC1 =
|WLRmci if RNj < MP
[WLRfci otherwise
CLRmci if RNj < MP
CLR = \
ci [CLRfci otherwise
where;
RNj = random number between 0 and 1
MP = percentage of the population that is male
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-20
Arsenic in Drinking Water Rule EA
-------
Finally, 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 categories. This is accomplished
using a population weighted probability distribution. First, the total worker and customer
populations served are computed.
Next, the probability that the lifetime risk for the model iteration will be equal to the worker
lifetime risk associated with a service category is calculated:
TW.
WPR =
(TW + TC)
where;
WPR = probability of choosing lifetime risk estimate for any iteration to be equal to the lifetime
risk estimate of a worker in a given service category
Likewise, the probability that the lifetime risk for the model iteration will be equal to the
customer lifetime risk associated with a service category is calculated:
TC
CPR =
(TW+TC)
where;
CPR = probability of choosing lifetime risk estimate for any iteration to be equal to the lifetime
risk estimate of a customer in a given service category
Given these probabilities, the lifetime risk estimate for each model iteration is chosen as follows:
LR; =
where;
LR = Lifetime risk (1/100,000)
WLRci with ProbabilityWPRC
CLRC1 with ProbabilityCPRC
Appendix B, Assumptions and Methodology for B-21 Arsenic in Drinking Water Rule EA
Estimating Cancer Risks Avoided and Benefits
-------
In order to calculate the expected number of cancer cases associated with the model run, the
mean lifetime risk is multiplied by the exposed population as follows:
CA =
ILR,
N
JTC+TW)
100,000
where;
CA = expected number of bladder cancer cases
N = number of iterations
Appendix B, Assumptions and Methodology for
Estimating Cancer Risks Avoided and Benefits
B-22
Arsenic in Drinking Water Rule EA
-------
Appendix C. Cost Model Methodology
C.1 Introduction
EPA used the regulatory cost model, SafeWaterXL, in estimating the annual national costs of
compliance for the Arsenic in Drinking Water Rule. SafeWaterXL is a Monte-Carlo simulation
model developed in Microsoft Excel using the Crystal Ball add-in.1 The model is programmed in
Visual Basic for Applications, the procedures and functions of which command for example, the
user interface and much of the business logic required. These procedures and functions call on
data and equations stored in Microsoft Excel spreadsheets, such as data on specific system
characteristics (e.g., the number of people served, the type and source of the water system, the
decision tree).
SafeWaterXL determines regulatory compliance costs for individual systems and subsequently
calculates a national average cost based on the mean value of these data points. SafeWaterXL
describes system-level costs in terms of a distribution, from which mean costs and percentile
costs are available. Mean costs reflect the costs of treatment trains selected. Treatment trains
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-oxidation technology (if necessary), treatment
technology, and waste disposal technology. This modeling approach presents information critical
to the assessment of system-level impacts and technology affordability by providing the average
compliance costs for each water system type and size category, and the range of costs within each
system size and type category.
In understanding how SafeWaterXL calculates annual national cost of compliance, it is important
to distinguish between an "iteration" and a "run" of the model. A single iteration of the model
represents a single system. This allows for variability in the water system configuration, current
treatment in place, and source water quality to be captured in the compliance cost estimates. A
model "run" uses data from the aggregate number of iterations to calculate summary cost
information for different system size categories. For any individual "run," only a single source
water type may be evaluated, and the results are stratified by sixteen groups: 8 size categories and
2 ownership types (public/private).
C.2 Data Inputs and Procedure (Single Model Iteration)
The fundamental steps required to conduct an iteration of SafeWaterXL are summarized below:
1. A system is selected from data files. A system is defined by the population it serves.
2. Each system is assigned a random concentration from an occurrence distribution.
^or Windows 95/98/NT: Excel 2000, registered trademark of Microsoft Corporation; Crystal Ball
Version 4.0, registered trademark of Decisioneering, Inc.
Appendix C, Cost Model Methodology C-l Arsenic in Drinking Water Rule EA
-------
3. The selected arsenic concentration for the system is distributed across the number of sites
(entry points) of possible contamination for that system based on the relative intra-system
standard deviation (RSD).
4. The concentration at each site is compared to the revised MCL standard to determine if
the site is in violation of the revised standard.
5. If the site is in violation of the revised MCL, the percentage removal of arsenic required
in order to reach the treatment target is calculated.
6. Based on the percentage removal required to meet the treatment target and on the decision
tree for the size and type of the system, a treatment train is then assigned to the site.
7. Using the removal efficiency of the treatment train chosen, the percentage of flow that
must be treated in order for the entry point to meet the treatment target, is calculated.
8. The percentage of flow that needs to treated is applied to the design flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:
treatment capital, waste disposal capital, and any pre-treatment capital costs).
9. Similarly, the percentage of flow that needs to treated is also applied to the average flow,
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 any pre-
treatment O&M costs).
10. The system'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 system cost is used to derive the cost per thousand gallons (cost/kgal)
delivered by the water system.
12. Annual household costs are then calculated based on the system's unit cost of delivery
(cost per thousand gallons) and the average annual household consumption per year.
13. If household costs are determined to exceed an affordability threshold of $500, a less
expensive treatment technology (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POU devices).
14. Otherwise, the results are forecasted for each iteration and another system is selected for
the next iteration.
This procedure is conducted for all of the size categories and national costs are then calculated.
Each step listed above is now described in detail.
A system is selected from data files.
The basic unit of analysis within the cost model is an individual CWS. The SafeWaterXL model
estimates regulatory cost based on a universe of CWSs using a December 1997 freeze of the Safe
Drinking Water Information System (SDWIS) dataset, which allows costs to community water
systems to be delimited by various system characteristics: source, ownership, and size. SDWIS
contains data on all public water systems as reported by States and EPA Regions. This
information is used to determine each system's primary raw water source (ground or surface
water), its ownership type (public or private), and the population served by the system (service
size category). Note that in SDWIS, systems under any influence of surface water are classified
as surface water systems.
Appendix C, Cost Model Methodology C-2 Arsenic in Drinking Water Rule EA
-------
Included in this group are surface water systems that receive a portion of their flow from ground
water sources. In SafeWaterXL, these "mixed systems" were reclassified as ground water
systems if they were determined to rely on ground water for more than 50 percent of their water
supply. Based on data from the Community Water System Survey (CWSS)2, systems were
systematically reassigned in order to maintain the same average number of people served for the
subset of systems. Approximately nine and twelve percent of non-purchased and purchased
surface water systems were reclassified as a result.
The universe of systems modeled in SafeWaterXL also excludes the largest systems, those
serving more than 900,000 people. These very large systems, although few in number, are
significant contributors to the national cost of compliance estimate. Therefore, for the Arsenic in
Drinking Water Rule, EPA did an independent analysis on the 25 very large systems (both
ground and surface water source systems) to determine which would be affected at various MCL
options. In addition, among the smallest systems (serving <100 people), approximately 150
ground water system 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 systems in this size category
(>14,000 systems), the effect of this modification was found to be insignificant.
In total, the resulting number of systems are distributed between two data files which the model
calls on for system information. The criterion for these two files is source water: ground or
surface. Then, within each file, CWSs3 are first grouped by size category, resulting in eight
different worksheets of data corresponding to each delimited category (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 SDWIS freeze used in SafeWaterXL is described in Exhibits
C-l and C-2 below for ground and surface water systems, respectively.
U.S. EPA. 1999. Geometries and Characteristics of Public Water Systems. Prepared for Office of
Ground Water and Drinking Water by Science Applications International Corporation. EPA Contract No. 69-C6-
0059.
3Note that public-purchased systems are analyzed as publicly-owned systems and similarly, private-
purchased systems are analyzed as privately-owned system.
Appendix C, Cost Model Methodology C-3 Arsenic in Drinking Water Rule EA
-------
Exhibit C-1.
Stratification of Community Ground Water Systems
System Size
Category
25-100
101-501
501-1,000
1,001-3,300
3,301-10,000
10,001-50,000
50,001-100,000
100,001-900,000
Total
Publicly-Owned
Non-
Purchased
1,217
4,141
2,574
3,847
2,027
1,078
126
74
15,084
Purchased
125
480
300
347
229
207
26
15
1,729
Privately-Owned
Non-
Purchased
12,893
10,242
1,798
1,599
493
259
27
18
27,329
Purchased
197
385
115
100
35
17
1
~
850
AIIGW
Systems
14,432
15,248
4,787
5,893
2,784
1,561
180
107
44,992
Exhibit C-2.
Stratification of Community Surface Water Systems
System Size
Category
25-100
101-501
501-1,000
1,001-3,300
3,301-10,000
10,001-50,000
50,001-100,000
100,001-900,000
Total
Publicly-Owned
Non-
Purchased
150
348
331
873
771
724
133
136
3,466
Purchased
209
634
476
930
567
387
61
33
3,297
Privately-Owned
Non-
Purchased
404
396
131
225
102
114
31
33
1,436
Purchased
293
490
212
280
104
35
3
3
1,420
AIISW
Systems
1,056
1,868
1,150
2,308
1,544
1,260
228
205
9,619
Systems in each worksheet are further defined by their ownership type and an exact number of
people served. A separate decision tree also exists for each size category, such that there are
sixteen in total available for analysis in SafeWaterXL, as presented in Appendix A.
Appendix C, Cost Model Methodology
C-4
Arsenic in Drinking Water Rule EA
-------
For example in this step, a system is selected from one of the data files. Recall that when a
model "run" is performed, only one source type may be analyzed at a time. The selection made
by the user triggers which data file is utilized. Once designated, assuming all size categories are
being analyzed, the model begins with the smallest size category (<100 people served).
Each system is assigned a random concentration from an occurrence distribution.
The system selected in Step 1 has various associated system characteristics. Each system is also
associated with an arsenic occurrence distribution based on the source water. However, these
distributions define the universe of systems with the same type of source water using a mean and
log standard deviation. To model a single system chosen from the data files, a random system
occurrence is selected from this distribution.
In this manner, contaminant occurrence information determines the average system concentration
given various system size and source water combinations. Exhibit 6-6 shows the estimated
finished water arsenic occurrence distribution for ground and surface water systems. For use in
the SafeWaterXL model, EPA performed a regression analysis that weighted actual occurrence
data by National Arsenic Occurrence Survey region. On the basis of this, EPA replicated the
estimated finished water distribution of ground and surface water systems through a log-normal
fit using two sets of distribution parameters. The analysis resulted in the following distribution
of systems exceeding various arsenic concentration levels:
Exhibit C-3
Arsenic Occurrence Distribution, Log-Normal Regression Results
Ground water
Surface water
3ug/L
19.7%
5.6%
5ug/i_
12.0%
3.0%
ioug/i_
5.3%
1.12%
20 ug/L
2.0%
0.37%
*Percentages represent systems exceeding the arsenic concentration
For ground water systems, the percentages displayed in Exhibit C-3 above were based on a
lognormal distribution with a mean of-0.2507 and a log standard deviation of 1.5828. Among
surface water systems, the percentages were based on a lognormal distribution of-1.6781 and a
log standard deviation of 1.7425.
The selected arsenic concentration for the system is distributed across the number of sites
(entry points) of possible contamination for that system based on the relative intra-system
standard deviation (RSD).
Once the system arsenic concentration is determined, the number of entry points, or sites of the
system, are determined. The number of sites a system has is another important system
characteristic to consider in the analysis because entry points are used as a proxy for the potential
or actual points of treatment. Since not all sites in the system are equally likely to exceed the
MCL standard, the likelihood of contamination is determined on a site-by-site basis. That is,
each system may have more than a single site treating independently.
Appendix C, Cost Model Methodology
C-5
Arsenic in Drinking Water Rule EA
-------
The average number of sites per system is determined based on the distribution of system intake
sites for the size category as estimated from the CWSS. The range of number of sites per system
is described in Exhibit C-4 for ground water systems, where a maximum of 37 possible sites was
modeled. Linear extrapolation was used to estimate values for the number of sites in cases where
survey data was not available.
Exhibit C-4
Distribution of Entry Points by Size Category Among Ground Water Systems
System Size
Category
<-100
101-500
501-1,000
1,001-5,000
5,001-10,000
10,001-50,000
50,001-100,000
100,001-900,000
Mean
1
1
2
2
2
4
6
9
5th
Percentile
1
1
1
1
1
1
1
1
50th
Percentile
(Median)
1
1
1
1
2
3
4
5
75th
Percentile
1
1
2
2
3
5
8
15
95th
Percentile
2
3
3
5
5
12
22
28
Maximum
4
10
4
6
15
19
37
30
Source: U.S. EPA. 1999. Geometries and Characteristics of Public Water Systems. Prepared for Office
of Ground Water and Drinking Water by Science Applications International Corporation. EPA Contract
No. 68-C6-0059.
Among surface water systems, fewer sites per system exist. About 95 percent of the systems that
serve fewer than 50,000 people have only a single entry point. Of the remaining surface water
systems that serve greater than 50,0001 people, the majority of the systems had fewer than three
entry points, although some in the 50,001-100,000 and 100,001-900,000 service size categories
were observed to have as many as six and four sites per system, respectively.
The SafeWaterXL model calculates potential costs of compliance at the entry point level,
allowing for a maximum of 37, but modeling only the estimated number attributable to each
system, based on the distribution described in Exhibit C-4. Once the number of sites within the
system is determined from the distribution, the concentration of the contaminant at the site is
calculated by applying the assumed relative intra-system standard deviation (RSD) around the
mean system concentration. The average concentration of arsenic for that system (from Step 2)
is assigned between all the system's sites using a log-normal distribution with the system
concentration as the mean, and the intra-system deviation as the standard deviation, which is
derived by multiplying the RSD by the system concentration. The RSD is an input ultimately
used to distribute the system 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-system deviation
based on the relationship expressed in Equation 1.
Appendix C, Cost Model Methodology
C-6
Arsenic in Drinking Water Rule EA
-------
Intra - System Standard Deviation
f- — (Eq.
System Concentration
This distribution used to assign site concentration is bound by zero at the lower limit and by the
maximum site concentration (Eq. 2) at the upper limit. Note however, that the sum of the mean
arsenic concentration of all sites within a system must still equal the mean arsenic concentration
of the system.
Max Site Cone. = (SysConc) X (# of sites) (Eq. 2)
where: SysConc = arsenic concentration for system
The maximum is set using the assumption that despite the number of entry points, if only one
entry is contaminated, its individual concentration cannot exceed a limit such that when averaged
across the number of possible sites, the overall concentration would exceed the original
concentration determined for that system.
For any given system that has more than a single site, the average system concentration of arsenic
for that system is assigned between all the system's sites using this method. Otherwise, if the
system has only a single site, then the site concentration must equal the system concentration.
The concentration at each site is compared to the revised MCL standard to determine if
the site is in violation of the standard.
Although the system concentration could itself fall below the MCL, once the system
concentration has been distributed between the possible number of entry points, one site may
significantly exceed the MCL while the other falls below the MCL such that their average still
equals the system concentration. For example, in a system with three sites, there may have two
sites whose individual site concentrations are well below the MCL and one site whose
concentration exceeds the MCL. In this example, only costs to the third site are calculated.
However, if a system has only one site, then that single site is assigned the entire system
concentration of arsenic.
For this reason, the concentration of each site of the system is individually compared to the MCL.
No costs are incurred for those sites whose concentrations fall below the specified MCL, as no
treatment is required. However, if the site is determined to be in violation of the MCL, then
treatment costs for regulatory compliance will be calculated and the model must record the data
and output information. To do so with the best approximation of the true costs of compliance,
only the portion of the system's flow that must be treated to achieve the target MCL level is
assigned a cost, as described in Step 5.
Appendix C, Cost Model Methodology C-7 Ar'senic in Drinking WaterRule EA
-------
• If the site is in violation of the revised MCL, the percentage removal required in order to
reach the treatment target is calculated.
If the site is determined to be in violation of the MCL, then SafeWaterXL calculates the percent
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 excess removal
to account for system over-design. The percent of contamination reduction required can be
expressed as:
(SiteConc- TrtTarget) ~ ->\
% removal = * —— ^^ (Eq- 3)
biteLonc.
where: % removal = percent removal required to meet treatment target
SiteConc = arsenic concentration at the treating site
TrtTarget = 80 percent of revised MCL
The magnitude of reduction required determines which treatment decision tree is used. A
technology is chosen depending on the percentage removal required and treatment train removal
efficiencies that will meet the target MCL. The model recognizes three categories of required
reduction: <50 percent, 50-90 percent, and >90 percent. Each category is represented by a
distinct decision tree of feasible technologies for the amount of removal required. For example,
if a site has an influent arsenic level of 50 |ig/L, and the target MCL is 2 |ig/L, then 96 percent
removal is required. Research indicates that lime softening is only capable of achieving
approximately 80 percent removal, therefore lime softening would not be a viable treatment
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.
Based on the percentage of removal required to meet the treatment target and on the
decision tree for the size and type of the system, a treatment train is then assigned to the
site.
Since entry points may have different site concentrations, it is likely that different treatment
technologies would be applied at different sites to meet the target MCL depending on the
percentage of removal required to meet the treatment target, and on the removal efficiency of the
treatment train selected. The variability of treatment train selection among sites is based on
probabilities defined in a decision tree, which contains a range of compliance responses for
different system types and sizes, and represent EPA's best estimate of the treatment train
technologies that system operators will choose to achieve a particular percentage reduction in
arsenic concentration. Specifically, the compliance decision trees are distributions that identify
the percentage of systems in different categories that will choose specific compliance options.
For example, the decision tree specifies the probability of different compliance choices for
systems with different removal percentages required, baseline influent concentrations, different
sizes (e.g., population served), and different sources (groundwater and surface water).
Appendix C, Cost Model Methodology C-8 Arsenic in Drinking Water Rule EA
-------
The decision trees are specific to the system's size categories and source water, and vary
according to the contaminant under consideration. SafeWaterXL uses sixteen distinct decision
trees in total: one for each of the eight system size categories with ground water and surface
water sources. Each decision tree contains a list of treatment trains with three sets of
probabilities that would apply to the site, depending on which of three required treatment
scenarios the site belongs (<50 percent, 50-90 percent, or >90 percent removal required as
described in Step 5). The actual decision tree is illustrated as a flowchart, and is often
summarized as a decision matrix, for a particular source water and size category. The matrices
used in this analysis were developed for the Revised Arsenic Rule and may be found in Appendix
A.
Appendix A describes the treatment technologies, their effectiveness, and the major factors that
affected the composition of a particular decision tree. Among some of the centralized treatment
options presented include: lime softening, anion exchange, activated alumina, reverse osmosis,
and coagulation assisted microfiltration. Some associated waste disposal technologies are also
described. Waste disposal technologies are specific to the treatment technology, although their
availability does vary between size categories. In addition to these centralized treatment options,
small systems may also elect to use point-of-entry (POE) devices to achieve compliance with the
MCLs, identified as affordable technologies by the SDWA. The available POE technologies for
arsenic removal are essentially smaller versions of reverse osmosis and activated alumina.
Using the removal efficiency of the treatment train chosen, the percentage of flow that
must be treated in order for the entry point to meet the treatment target, is calculated.
Once a treatment train is selected from the decision tree, the associated removal efficiency of the
technology is used with information on system flow to determine the amount of flow at the site
that must be treated in order to meet the treatment target. System 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 Water Systems report (U.S. EPA, May
1999). Both the equations, and the regression parameters employed in the SafeWaterXL cost
model are presented in the following two equations and Exhibit C-5, respectively.
Average Flow aA "(Population) A (Eq. 4)
[ 2 • Average Flow
Design Flow = max< , , ,/, (Eq. 5)
\aD-(p°Pulationr
where: aA, bA, aD, bD = regression parameters derived for flow vs. population
Population = population served by the system type and source
Appendix C, Cost Model Methodology C-9 Arsenic in Drinking Water Rule EA
-------
Exhibit C-5.
Flow Regression Parameters by System Source and Ownership Type
System Source and
Ownership Type
Average Flow
afl
b.
Design Flow
an
bn
Ground Water
Public
Private
Public-Purchased
Private-Purchased
0.08558
0.06670
0.04692
0.05004
1.05840
1.06280
1.10190
1.08340
0.54992
0.41682
0.31910
0.32150
0.95538
0.96078
0.99460
0.97940
Surface Water
Public
Private
Public-Purchased
Private-Purchased
0.14004
0.09036
0.04692
0.05004
0.99703
1.03340
1.11020
1.08340
0.59028
0.35674
0.20920
0.20580
0.94573
0.96188
1 .04520
1.00840
Source: U.S. EPA. 1999. Geometries and Characteristics of Public Water Systems. Prepared for Office
of Ground Water and Drinking Water by Science Applications International Corporation. EPA Contract
No. 68-C6-0059.
Based on these data, the system flow is determined in thousands of gallons per day (KGPD). The
system flow is then divided equally among the possible sites of contamination, regardless of
whether they are treating (i.e., violation of the revised MCL standard) or not. For example, a
system with four potential sites of contamination is modeled to have four sites, each with 25
percent of the total system flow. However, even with this distribution of system 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.
SafeWaterXL employs a "blending" principle to determine the amount of flow that requires
treatment in order for the entry point to meet the treatment target established by the MCL. The
treatment target is considered 80 percent of the MCL and represents the contaminant level to
which the design of systems will perform, to ensure adequate compliance with the MCL. To
reach this target, data on the removal efficiencies of the chosen treatment trains, the contaminant
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 expressed by the following relationship:
Fraction of Flow Treated =
( TrtTarget
\ SiteConc
-%RE
X (%SiteFlow)
(Eq. 6)
Appendix C, Cost Model Methodology
C-10
Arsenic in Drinking Water Rule EA
-------
where: TrtTarget = 80 percent of revised MCL
SiteConc = arsenic concentration at the site
% RE = % removal efficiency of treatment train chosen
% Site Flow = % of total system flow attributable to that site
Notice that the blending technique is applied at the entry point level, but it is not used for systems
selecting POU devices, as those options treat water at the tap rather than for the entire house.
Since treatment costs to reduce such high levels of contamination can be significant, blending is
an approach SafeWaterXL takes to best characterize the expected cost of compliance. In this
manner, treatment costs are tallied only among the sites that are expected to treat, for the portion
of the overall system flow that actually gets treated.
• The percentage of flow that needs to treated is applied to the design flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:
treatment capital, waste disposal capital, and any pre-treatment capital costs).
Each treatment train is defined by a treatment technology and (where relevant in order to be
effective) a waste disposal option, and/or pre-treatment technology. Therefore, the cost of the
treatment trains is related to its constituent capital and O&M cost components. Capital costs are
estimated as a function of design flow. When the treatment train has been selected, the overall
capital costs of these various components are aggregated to derive an overall capital cost
estimate. This is expressed in the following general treatment train cost functions at each site:
TrCcap = Tcap + WDcap + [(PFO)( P0cap}} (Eq. 7)
where: TrCcap = Treatment train capital cost at treating site
Tcap = Treatment technology capital cost at treating site
WDcap = Waste disposal technology capital cost at treating site
PPO = Probability of using pre-oxidation at treating site
POcap = Pre-oxidation technology capital cost at treating site
Depending on the source water conditions and on the treatment technologies involved, EPA
determined that some systems would require additional pre-oxidation. EPA developed a separate
decision tree to approximate the number of systems that would implement pre-oxidation
technologies when selecting a treatment train. The need for this separate decision tree was based
in part on the distribution of systems with and without treatment-in-place. For technology trains
in which pre-treatment is required, Exhibit C-6 summarizes the decision tree of probabilities by
system size that a system would require these technologies.
Each of the treatment technologies considered in the decision tree remove As(V) more readily
than As(ni) and as a result, pre-oxidation may be necessary depending upon source water
conditions. Systems without treatment in-place may already be chlorinating which may meet
pre-oxidation requirements. For those systems, pre-oxidation may or may not need to be
installed. Similarly, systems with treatment in-place may have pre-oxidation in-place, which
could meet the pre-oxidation requirements.
Appendix C, Cost Model Methodology C-ll Arsenic in Drinking Water Rule EA
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Exhibit C-6.
Probability of a System Requiring Pre-Oxidation
System Size Category
25-100
101-500
501-1,000
1,001-3,300
3,301-10,000
10,001-50,001
50,001-100,000
100,001-1,000,000
Pre-Oxidation
(GW systems)
0.54
0.30
0.24
0.24
0.27
0.13
0.41
0.16
Pre-Oxidation
(SW systems)
0.09
0.04
0
0
0.03
0.01
0.02
0
Source: Facsimile from Amit Kapadia, EPA OGWDW, July 27, 1999.
Similarly, the percentage of flow that needs to treated is also applied to the average flow, 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 any pre-treatment O&M costs).
Unlike capital costs, which are expressed as a total cost, operation and maintenance costs are
expressed as a cost per year, and are calculated as a function of average flow. The total O/M
costs for each treating site are aggregated to derive an annual system O/M cost for the treatment
technology. Treatment O&M cost, waste disposal O&M, and any pre-treatment O&M costs are
tallied. These conditions are expressed in the following general treatment train cost functions at
each site:
= 7"
J~ ,
O&Af
(Eq. 8)
where:
TrC
O&M
iO&M
WD
PO
O&M
O&M
= Treatment train O&M cost at treating site
= Treatment technology O&M cost at treating site
= Waste disposal technology O&M cost at treating site
= Pre-oxidation technology O&M cost at treating site
Since the treatment technologies produce residuals that may contain various levels of arsenic, the
O&M costs associated with the treatment train are an important consideration in the overall cost
of the technology chosen. The handing and disposal costs associated with these residuals can be
significant, and depend on a number of factors, such as the size and flow of the water system.
The amount of waste that is generated will affect which technology is implemented by a water
system. For example, some methods may be impractical for larger systems due to land
requirements. Alternatively, more expensive processes may be inappropriate for smaller system
due to the cost. Process oversight, transportation, and labor are all factors affecting the overall
cost of the process. In general, the more complex the handling and the disposal methods, the
more significant the maintenance requirements, and therefore the more costly.
Appendix C, Cost Model Methodology
C-12
Arsenic in Drinking Water Rule EA
-------
• The system'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, applying the amortization formula on the
capital cost component (Step 8) over a specified period of repayment, results in an overall annual
cost of treatment at a site:
TrC* = (TrCcap)i_(rr+irv] + TrC0&M (Eq. 9)
where: TrCtot = Annual total treatment train cost at treating site
TrCcap = Treatment train capital cost at treating site
r = Discount rate
rp = Repayment period
TrC0&M = Treatment train O&M cost at treating site
For the purposes of estimating the national cost of compliance, public water system and
implementation costs are tracked over a 20-year period. This time frame is used because many
public water systems often finance their capital improvements over 20 years. This may,
however, result in an overestimate of annualized costs because many types of equipment last
longer than 20 years. Capital and operational and maintenance (O&M) costs may be incurred at
different points throughout the time period. For this reason, two adjustments were made to the
estimated costs forecasted by SafeWaterXL in order to render future costs comparable with
current costs, reflecting the fact that a cost outlay today is a greater burden than an equivalent
cost outlay sometime in the future.
In the first instance, compliance costs that are subsequently used in cost-benefit analyses are
annualized using a social discount rate so that regulatory option costs (e.g. costs for an MCL of 5
|ig/L vs. an MCL of 10 |ig/L) may be directly compared to the annual benefits of the
corresponding regulatory option. Annualization is similar to the process involved in calculating
a mortgage payment; the result is a constant annual cost as expressed in Equation 9. The Agency
performs cost-benefit analyses using two social discount rates. As required by the Office of
Management and Budget (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
costs of compliance, as the Agency believes this rate more closely approximates the true social
discount rate.
In the second instance, compliance costs that are subsequently used in various economic impact
analyses as required by the SDWA and its Amendments, such as in affordability analyses, are
annualized using an actual cost-of-capital discount rate rather than a social discount rate.
Affordability analyses examine the costs of compliance to systems and individual households,
rather than on a national level. Costs to households are considered a good proxy for determining
the affordability of regulatory compliance, as described in the discussion on maximum allowable
household cost in Step 11 below.
Appendix C, Cost Model Methodology C-13 Arsenic in Drinking Water Rule EA
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They are dependent on system costs to the extent that system costs are recovered through
increased water rates. The cost-of-capital rate is used to reflect the true after-tax cost-of-capital
that water systems face, net of any government grants or subsidies. The recommended cost-of-
capital rates stratified by ownership, system type and size, as reported in Development of Cost of
Capital Estimates for Public Water Systems (U.S. EPA, 1998), were used in SafeWaterXL.
These were presented in Exhibit 6-7.
Together, the annualized capital and O&M cost components equal the annual cost of treatment.
When these costs are summed across all the treating sites in a system, the annual system cost is
calculated. In other words, the system's cost of compliance is determined by summing across the
treating sites. For each system in which a violation of the revised MCL is expected, this overall
cost is calculated:
where: i = System/model iteration
n = Number of treating sites in the system
SCir = Annual cost for system i at discount rate r
TrCtot = Annual total treatment train cost at treating site
• The annual system cost is used to derive the cost per thousand gallons (cost/kgal)
delivered by the water system.
Once the annual cost per system is determined by summing the costs of all the treating sites of
the system, this cost is used to determine the unit cost of delivery (cost per thousand gallons
delivered) for the system as a result of the new treatment technology. The system cost annualized
at the cost-of-capital discount rate is used in this calculation as it best represents the true cost
impact on the system. The cost per thousand gallons delivered is calculated as:
, 365 days 1000
Costkxal =
1Mgal
where: Costkgal = Cost per thousand gallons for the system
AF; = Average flow (MGD) of system i
sc; coc = Annual cost for system i at the cost-of-capital discount rate
Annual household costs are then calculated based on the system's unit cost of delivery
(cost per thousand gallons) and the average annual household consumption per year.
The system's cost per thousand gallons delivered is used to calculate household costs according
to Equation 12. The values used as estimates of the average annual tap water consumption per
year are presented in Exhibit 7. More detail was given in Chapter 4.
Appendix C, Cost Model Methodology C-14 Arsenic in Drinking Water Rule EA
-------
Cx OS I HHi *—- OStkgal' *—-,
HH
(Eq. 12)
where: Cost^ = Household cost per year for system i
CHH = Household consumption per year (kgal)
Exhibit 7.
Water Consumption per Residential Connection
System Size Category
<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
System Ownership Type
Public
81
93
97
82
87
108
122
127
Private
92
110
88
102
124
110
96
114
Source: EPA. 1997. CI/I/SS, Vol. II: Detailed Summary Result Tables and Methodology Report, Table 1 -
14.
If household costs are determined to exceed an affordability threshold of $500, a less
expensive treatment technology (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POU devices).
SafeWaterXL employs a maximum allowable household cost of $500, which forces systems who
initially choose a treatment train with annual household costs in excess of $500, to default to a
POE device, thereby seeking a less expensive method of compliance. In general, the results of
the model simulation showed that only the smallest systems (serving 25-500 people) are affected
by this threshold. Based on the overall number of systems in these two size categories (see
Exhibits 1 and 2), the number of systems affected is relatively small. SafeWaterXL does record
the number of systems exceeding this affordability threshold.
The system results are maintained in a database for further analysis.
C.2.1 Example Calculation (Single Iteration)
In this section, we demonstrate the process by which SafeWaterXL calculates the annual cost of
compliance for a single system assuming a target MCL of 5 |ig/L. Each step in the procedure
described in the previous section is addressed to exemplify how the many assumptions and data
inputs are pooled together in a single iteration.
Appendix C, Cost Model Methodology
C-15
Arsenic in Drinking Water Rule EA
-------
Given the following SafeWaterXL model setting selections by the user:
Source water = ground water;
• Ownership type = public;
MCL=10|ig/L;
Then, a single iteration of the model proceeds as follows:
1. A system is selected from data files.
A publicly-owned community ground water system with three entry points serving 10,000 people
is selected from the data files.
2. Each system is assigned a random concentration from an occurrence distribution.
Based on accompanying information in the data file for ground water systems, an average system
concentration of 11.03 |ig/L is selected from an occurrence distribution bound by a lognormal
mean of
-0.2507 and a log standard deviation of 1.5826.
3. The selected arsenic concentration for the system is distributed across the number of sites
(entry points) of possible contamination for that system based on the relative intra-system
standard deviation (RSD).
Since the system has three entry points, based on the average system concentration of 11.03 |ig/L,
the maximum site concentration is determined to be 33.10 |ig/L (= 11.03 * 3). Using the default
RSD of 0.64 and this limitation on the maximum site concentration, the three sites are assigned
concentrations of 8.89, 9.69, and 14.52 |ig/L, respectively. These three concentrations keep the
average system concentration at 11.03 |ig/L.
4. The concentration at each site is compared to the revised MCL standard to determine if
the site is in violation of the revised standard.
The first two sites are determined to have concentrations of 8.89|ig/L and 9.69|ig/L, both of
which are below the user selected MCL of 10 |ig/L. The final site of the system, however,
exceeds the MCL with a concentration of 14.52 |ig/L, and is the only site for which the
remainder of the calculations are conducted.
5. If the site is in violation of the revised MCL, the percentage of removal required in order
to reach the treatment target is calculated.
Appendix C, Cost Model Methodology C-16 Arsenic in Drinking Water Rule EA
-------
From Equation 3 above, the percent of removal required for a site with an influent concentration
of 14.52 |ig/L to reach the treatment target of 8 |ig/L (80 percent of MCL 10 |ig/L) equals 45
percent:
(SiteConc - TrtTarget) (l 4.52 - 8)
% removal = ^-^ = = 0.4490
SiteConc. 14.52
6. Based on the percentage of removal required to meet the treatment target and on the
decision tree for the size and type of the system, a treatment train is then assigned to the
site.
Using the decision tree for ground water systems for the size category serving 3,301-10,000
people, a treatment train is selected based on the probabilities from the "<50%" removal column
since this site requires 45 percent removal.
For this iteration, Treatment Train #6 (Coagulation/Microfiltration, Nonmechanical Dewatering,
Non-Hazardous Landfill) is selected. This treatment rain has a removal efficiency of 90 percent.
7. Using the removal efficiency of the treatment train chosen, the percentage of flow that
must be treated in order for the entry point to meet the treatment target is calculated.
The system flow must now be determined. Since the system in this iteration of the model is a
public groundwater system, using the flow equations (Equations 4 and 5) and the regression
parameters from Exhibit C-5, the design flow equals 3.646 MGD:
Design Flow = aD'(population)ba = (0.54992)- (10,000)°95538 = 3646.02393X ^— = 3.646
and the average flow equals 1.465 MGD:
Average Flow =a • (population^A =(0.08558)-(10,000y-05840 =1465.454309kgalx. 1Mgal =1.465
1000 legal
As described in Step 7 above, the system's total flow is evenly distributed among all the possible
sites. In this case, since there are three sites, each receives 33.3 percent of the total system flow.
Using the principle of blending, the fraction of the system's total flow that must be treated in
order for the site to meet the treatment target equals 16.6 percent:
fTrtTarge,
Fraction of Flow = ^ s"eC°''c L x (%SileFlfM') = -^^—'- x f 0.33 3) = 0.1663
- % RE —0.90 V /
Appendix C, Cost Model Methodology C-l 7 Arsenic in Drinking Water Rule EA
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8. The percentage of flow that needs to treated is applied to the design flow, which is then
used to derive the capital costs of the components of the treatment train (the sum of:
treatment capital, waste disposal capital, and any pre-treatment capital costs).
Applying the fraction of the system's total flow (16.6 percent) to the system's total design flow
(3.646 MOD) from Step 7 above, the design flow at the treating site can be calculated:
(3.646MG/)) x (0.166) = 0.606MGD
This adjusted flow is then used to determine the capital costs of the treatment train using the
various cost equations for the treatment capital and waste disposal capital. For 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 $2,664,77'I4 For design flow (x), the cost (y) can be calculated:
Treatment capital: x<0.1 y = -11935465x2 + 48800366x + 94324
0.110 y = 320x2 + 921471x +2129119
Based on a site design flow of 0.606 mgd, the third segment of the cost equation is used:
y=-483591(0.606)2 + 2308991(0.606) -273143
Similarly, for design flow (x) = the waste disposal capital cost (y) can be calculated from these
equations:
Waste Disposal capital: x<0.085 y = 3069360x - 790
0.0851.8 y = 1627970x + 326504
For the waste disposal capital cost, the second cost segment is used:
y= 1749352(0.606) -108017
In this example, based on the probability distribution listed in Exhibit 6, pre-oxidation was not
selected, therefore the pre-oxidation capital costs are not calculated and included in the capital
cost component of the treatment train.
4Costs presented in this example are in April 1998$, although post-processing of SafeWaterXL results
updated these costs to May 1999$ in the Regulatory Impact Analysis. Totals may not equal sample calculation
provided due to rounding of input variables.
Appendix C, Cost Model Methodology C-18 Arsenic in Drinking Water Rule EA
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9. Similarly, the percentage of flow that needs to treated is also applied to the average flow,
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 any pre-
treatment O&M costs).
Similarly, by applying the fraction of the system's total flow (16.6 percent) to the system's total
average flow (1.465 MOD) from Step 7 above, the average flow at the treating site can be
calculated as follows:
(1.465MGD) x (0.1663) = 0.244MGD
This flow is then used to determine the operation and maintenance costs of this treatment train
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. For average flow (x), the O&M cost (y) is:
Treatment O&M: x<0.03 y = 196829x+20264
0.034.3 y= 15236x +42350
Based on a site average flow of 0.244 MOD, the third segment of the cost equation is used:
y = 8OO81(0.244) + 26977
Similarly, for average flow (x), the waste disposal cost (y) is:
Waste Disposal O&M: x<0.085 y =-18812x2 +4686.1x + 2123.8
0.0850.72 y = 16.966x2 + 60792x + 28760
For the waste disposal O&M cost, the second cost segment is used:
y= 111819(0.244) -6950.5
Again, since pre-oxidation was not selected, no pre-oxidation O&M costs are calculated or
included in the O&M cost component of the treatment train.
10. The system'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
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From Step 8, the total capital costs for this treatment train equal $2,664,771. From Step 9, the
total O&M costs for the treatment train equal $66,809. Using a capital cost amortized at 5.26
percent5 over 20 years, the annual cost to the system equals $284,278:
The example displayed here uses the commercial rate, which is a closer approximation to the cost
of capital to water systems. Annual costs are also calculated at 3 and 7 percent, respectively, as
$245,923 and $318,344.
11. This annual system cost is used to derive the cost per thousand gallons (cost/kgal)
delivered by the water system.
The unit cost of water delivered by this system (cost per kgal per year) as a result of installing
treatment is determined by dividing the system cost by the system average flow. The system cost
that was derived using the commercial discount rate is used to arrive at a unit cost of $0.53:
12. Annual household costs are then calculated based on the system's unit cost of delivery
(cost per thousand gallons) and the average annual household consumption per year.
The cost per thousand gallons to the water system calculated in Step 11 is used to estimate the
annual cost to households as a result of regulatory compliance, by multiplying it with the average
annual household consumption of tap water for a system in that size category:
• Cnu = ($0.53) • (lOUgal) = $46.24
The annual water consumption per household is presented in Chapter 4 and stratified by size
category and ownership type.
13. If household costs are determined to exceed an affordability threshold of $500, a less
expensive treatment technology (POU device) is chosen and new costs are calculated
(Steps 7-12 above are repeated using data for POE devices).
5Commercial discount rates are presented in Exhibit 6-7 of Chapter 6 of the Regulatory Impact Analysis,
and determined by size category and ownership type.
Appendix C, Cost Model Methodology C-20 Arsenic in Drinking Water Rule EA
-------
Since the estimated annual household cost for this system is $46.24, this step does not affect the
calculations already discussed. As described earlier, this affordability threshold affects only the
smaller system size categories (<100 and 101-500). Therefore, the results of this iteration are
recorded and the next iteration is triggered in Step 14.
14. The results are maintained in a database.
C.3 Model Run
C.3.1 Number of Iterations
Once a single iteration is completed, the calculated system data is recorded. Among the cost data
forecasted for each iteration are the following:
• annual system cost (calculated at three discount rates: three percent, seven percent, cost-
of capital);
• system capital cost (calculated at one discount rate: cost-of capital);
system O&M cost (calculated at three discount rate: cost-of capital);
• cost per thousand gallons (calculated at one discount rate: cost-of capital); and
household cost (calculated at one discount rate: cost-of capital).
Once complete, another iteration is started. This is repeated N times, until the total number of
iterations (the total number of systems) for that size category is met, at which point the total
annual national cost estimate for that size category is determined.
Next, once each size category is finished, the first iteration of the next size category begins. The
cycles continue until all iterations of all eight size categories have been completed. The total
annual national cost across all systems is therefore the sum of the annual national costs for each
size category of systems, both publicly- and privately-owned.
If graphed against the estimated mean, the average system cost would generally fluctuate greatly
between iterations at the beginning of a model run. However, as the number of data points
increases, these fluctuations will dampen and should eventually converge on the estimated mean.
The number of iterations must be a multiple of the number of systems that belong to each size
category. This setting will avoid any systematic bias as the model cycles through all the systems
within each size category from smallest to largest.
Each cycle therefore represents the universe of systems in that category as pulled from SDWIS
(as summarized in Exhibits C-l and C-2). Using this method, approximately the same number of
non-zero data points should be generated when the same iteration settings are selected.
The anticipated number of non-zero data points is a function of the MCL, the occurrence
distribution, and the number of systems in the size category, where a non-zero data point is a
system that is required to treat and incurs treatment costs. For example, approximately eight
cycles of the universe of ground water systems serving less than 100 people (14,432 systems, as
Appendix C, Cost Model Methodology C-21 Arsenic in Drinking Water Rule EA
-------
shown in Exhibit 1) are required to achieve 20,000 data points given an MCL of 3 |ig/L, and an
occurrence distribution where 19.7 percent of the systems are expected to exceed the MCL. For
the purposes of regulatory analysis of arsenic in drinking water, a goal of 20,000 data points was
used in SafeWaterXL.
C.3.2 Model Outputs
The primary outputs of the SafeWaterXL model are national -level estimates of costs of
compliance, as well as distributions of cost to systems or households, across various water
system service size categories. To achieve these results, the output generated for each iteration,
as striated by water source, ownership, and service size category, are combined by SafeWaterXL
at the conclusion of the model run.
Average Annual System Cost (Calculated at the Cost-of Capital Discount Rate)
Each iteration of the model describes the treatment and cost profile for a single system in a single
size category. System cost is essentially equal to treatment cost, which is based on the treatment
train technology 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 water system: capital costs are estimated as a function of design flow, while O&M costs are
based on average flow. In addition to these treatment cost components, associated waste disposal
capital and O&M costs are also included. A portion of these systems are then estimated to
require pre-oxidation, which would add incremental costs to the total treatment cost.
In the case of calculating an average system cost, a commercial discount rate that is closer to the
actual cost of capital that systems might face is used:
Avg.SC = (Eq. 13)
& Jr
where: SCjr = Annual system cost for size category] at discount rate r
SCir = Annual cost for system i at discount rate r
j = Size category
nij = Number of systems in size category j
Although the equation above is used to calculated the average system cost for a particular size
category, the result represents one ownership and source type (e.g. average system cost for public
ground water systems serving <100). In order to combine the results for the two ownership types
for a single run, each system cost must be weighted by its respective number of treating systems
over the universe of systems in that size category:
c = •.JJ
x*"a° (n +n
\'lj(pub) T llj
Appendix C, Cost Model Methodology C-22 Arsenic in Drinking Water Rule EA
-------
where: SCj(tot) = Total annual system cost for size category]
SCi(pub) = Annual system cost for publicly-owned systems of size category]
SCi(prv) = Annual system cost privately-owned systems of size category]
nj(Pub) = Number of publicly-owned treating systems in size category]
nj(Prv) = Number of privately-owned treating systems in size category]
Average Annual Household Cost (Calculated at the Cost-of Capital Discount Rate)
Since household costs are also calculated for each system, a similar distribution of the cost of
compliance at the system level are also calculated at the household level:.
Hi)
Avg.Cost =^ -
& HHj ,
where: Cost^ = Annual household cost for size category]
CostjjHj = Household cost for system i
nij = Number of systems in size category]
Similarly, just as the average system cost was weighted across ownership types (Equation 14) the
average household cost for a single size category must be a weighted average taking into
consideration the number of households affected for each ownership type within the size
category.
Annual National Cost (Calculated at Two Discount Rates , 3 percent and 7 percent)
Annual cost for a system size category is determined by adding the total cost of compliance
across each treating system within that size category (e.g. the sum of all the system costs for each
iteration in that size category). This is a function of the individual system cost not the average
system cost, calculated at three and seven percent discount rates:
(Eq. 16)
1=1
where: ACjr = Annual cost for size category] at discount rate r
SCir = Annual cost for system i at discount rate r
Similarly, the annual national cost is total determined by adding the annual cost of compliance
across all the size categories (e.g. the sum of all the system costs for all the iterations in the run):
(Eq. 17)
j=i
where: ANCr = Annual national cost at discount rate r
Appendix C, Cost Model Methodology C-23 Arsenic in Drinking Water Rule EA
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Appendix D. What-lfCost Sensitivity Analysis
Chapter 6 of this report discusses the uncertainty associated with the National cost estimate.
Lacking information on exactly which systems will need to undertake activities to achieve
compliance, or what portion of those systems would require treatment, there will always be some
uncertainty associated with the actual costs likely to be incurred. The Agency conducted a Monte
Carlo simulation to provide a best estimate of probable costs and a sense of the relative precision
of the estimate. None of that analysis addresses potential bias in Agency estimates.
A number of commenters asserted that there were factors in the Agency analysis that could
significantly bias its estimate. The Agency disagrees with the issues raised for the reasons
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 changes in factors involving professional judgment
and where there is uncertainty with respect to the status quo of the water supply industry. The
factors considered relate to unit treatment costs and the compliance forecast (decision tree).
Modeling was not conducted relating to water system entry point configurations since the
Agency and commenters are in agreement that the entry point is the appropriate point for
consideration of compliance costs and commenters have demonstrated that changes in such
assumptions have minimal impact on national estimates. Likewise, factors, which could bias the
Agency's cost estimates downward, are not evaluated.1. These factors are not evaluated to give
the clearest picture of the absolute magnitude of the potential for underestimation. The data
discussed in this section are from a single Monte Carlo run of the Safewater XL model.
Unit treatment costs- The response to comment document contains a thorough critique of
commenter unit cost estimates. There are four areas, however, where anecdotal evidence
suggests costs beyond those evaluated by the Agency could be experienced by individual water
systems in their compliance efforts. In an effort to provide some context on the significance of
these concerns, modifications were made to the Agency's best estimate equations to incorporate
these factors. The following changes were incorporated into this analysis:
Accessory costs- Some commenters asserted that the costs for installing clearwells or storage to
achieve flow equalization after treatment, repiping around new treatment devices, and additional
pumping needed after pressure breaks for treatment would be incurred by water systems, aside
from the piping and pumping costs considered by the Agency. These commenters estimated that
such costs could add up to 76 percent to the capital costs of compliance.
Technologies costed by the Agency do include ancillary piping costs. Further, technologies,
which break pressure, like coagulation, included re-pumping costs. What neither the commenters,
nor the Agency have information on, however, is the extent to which additional storage might be
'A recently completed Agency report (Abt, 2000) suggests that many water systems achieve compliance
with some rules without major treatment reconstruction. In some cases, as many as a third of all systems were able
to achieve compliance without major reconstruction. Less capital intensive options than were costed in the
Agency's decision trees could include drilling a new well, reconfiguring intakes to blend to the MCL level, or
closing one, or more, wells and purchasing from a larger system can appreciably reduce costs.
Appendix D, What-lfCost Sensitivity Analysis D-l Arsenic in Drinking Water Rule EA
-------
required post treatment by water systems undertaking construction as part of their compliance
effort. This impact was evaluated by increasing treatment capital costs by 76 percent for those
systems that did not presently have disinfection (per EPA, 1999b). The Agency considered it
highly improbable that a system which presently conducted disinfection would not have adequate
storage or mixing zone capacity
Land costs- Some water systems undoubtedly will need to relocate entry points or acquire land
for the building of new treatment facilities. Commenters agree with the Agency that there is no
source of information for preparing a sound estimate of this impact. The issue is most likely to
arise with currently untreated entry points. One commenter estimated that land acquisition could
add five percent to compliance capital costs for ground water systems. While the Agency
believes land acquisition will not be a common occurrence, the what-if analysis included a five
percent increase in capital costs for land acquisition by ground water systems.
Permitting and pilot testing- The Agency has taken various approaches to the consideration of
permitting and pilot testing requirements in past cost analyses. While such costs are not expected
to be appreciable for most water systems, it is plausible that they could cause engineering costs to
exceed the fifty percent of direct costs currently costed. For the purposes of the what-if analysis,
the Agency is including three percent increases to direct capital costs for each factor per the
recommendations of the Technology Design Panel (EPA, 1997).
Compliance forecast/decision tree- In developing its compliance decision trees, the Agency
considers water quality factors, water availability, and cost. It is presumed that a water system
will adopt the lowest cost technology it can feasibly use. Admittedly, systems sometimes select
more expensive technologies, but do so to accomplish multiple treatment objectives. Lacking
comprehensive information on co-occurrence, the Agency is unable to consider the benefits or
costs of such actions. Regardless, they are not costs attributable to arsenic compliance.
The Agency made numerous modifications to the proposal decision tree in response to public
comment. The use of ion exchange, for instance, was greatly reduced in response to residuals
management concerns. To assess the impact of the decision tree upon National cost estimates,
the what-if analysis eliminated ion exchange (a relatively inexpensive technology) and greatly
increased the projected use of coagulation and microfiltration (the most expensive option for
many strata). Tables D-l through D-8 present the decision trees used in the analysis and can be
compared to the primary analysis decision trees in Appendix A.
Results- Table D-9 depicts the results of the model run in comparison to those generated by the
best estimate. It 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 What-if estimate is less than ten
percent greater than the Agency's original estimate. At the MCL option of five, however, the
what-if assumptions generate a twenty-five percent increase in the National cost estimate. These
results are consistent with those observed in the AWWARF Cost Implications Report
(AWWARF, 2000) wherein lower options were much more volatile in the face of varying
assumptions. While the Agency remains unpersuaded by many of the commenters arguments,
this analysis does support their concern relating to uncertainty at options beneath the selected
MCL.
Appendix D, What-IfCost Sensitivity Analysis D-2 Arsenic in Drinking Water Rule EA
-------
Exhibit D-1
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving • 400 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 -c|-| 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 -c|-| 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Percent of Treatment Required to
Achieve MCL
<50%
1.0
1.0
0.0
0.0
0.0
0.0
12.9
60.3
20.5
0.0
0.0
2.2
2.2
50-90%
1.0
1.0
0.0
0.0
0.0
0.0
12.4
57.3
19.1
0.0
0.0
4.6
4.6
>90%
1.0
1.0
0.0
0.0
0.0
0.0
0.0
72.2
23.7
0.0
0.0
0.0
2.1
Sum of Probabilities:
100.00
100.00
100.00
-------
Exhibit D-2
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 101-500 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash stream and pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent madia) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
0.0
0.0
0.0
0.0
12.9
60.4
20.5
0.0
0.0
1.1
1.1
100.00
50-90%
2.0
2.0
0.0
0.0
0.0
0.0
12.5
57.2
19.1
1.8
0.0
2.7
2.7
100.00
>90%
2.0
2.0
0.0
0.0
0.0
0.0
0.0
66.1
22.7
3.1
3.1
0.0
1.0
100.00
-------
Exhibit D-3
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 501-1,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
0.0
0.0
0.0
0.0
12.9
27.0
2.2
27.0
27.0
0.0
0.0
100.00
50-90%
2.0
2.0
0.0
0.0
0.0
0.0
12.5
27.2
1.8
27.2
27.2
0.0
0.0
100.00
>90%
2.0
2.0
0.0
0.0
0.0
0.0
0.0
32.0
2.1
31.0
31.0
0.0
0.0
100.00
-------
Exhibit D-4
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 1,001-3,300 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 rrg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 rrg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Mcrofiltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Mcrofiltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor baclwash stream and pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (1 5,400 BV) with pH adjustment (pH6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Fteverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
2.0
2.0
0.0
0.0
5.4
5.4
12.9
18.3
0.0
27.0
27.0
0.0
0.0
100.00
50-90%
2.0
2.0
0.0
0.0
4.5
4.5
12.5
14.5
0.0
30.0
30.0
0.0
0.0
100.00
>90%
2.0
2.0
0.0
0.0
5.2
5.2
0.0
17.5
0.0
34.1
34.1
0.0
0.0
100.00
-------
Exhibit D-5
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 3,301-10,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
3.0
4.0
0.0
0.0
8.7
2.2
0.0
26.0
0.0
28.1
28.1
0.0
0.0
100.00
50-90%
3.0
4.0
0.0
0.0
7.2
1.8
12.5
22.6
0.0
24.4
24.4
0.0
0.0
100.00
>90%
3.0
4.0
0.0
0.0
8.3
2.1
0.0
26.9
0.0
27.9
27.9
0.0
0.0
100.00
-------
Exhibit D-6
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 10,001-50,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
4.0
0.0
11.5
11.5
0.0
0.0
100.00
50-90%
4.0
4.0
0.0
0.0
63.0
2.0
4.1
3.3
0.0
9.8
9.8
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
3.8
0.0
11.8
11.4
0.0
0.0
100.00
-------
Exhibit D-7
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 50,001-100,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
2.5
0.0
12.2
12.2
0.0
0.0
100.00
50-90%
4.0
4.0
0.0
0.0
63.0
2.0
4.1
2.1
0.0
10.4
10.4
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
2.4
0.0
12.5
12.1
0.0
0.0
100.00
-------
Exhibit D-8
Probability Decision Tree: "What-lf" Sensitivity Analysis
Ground Water Systems Serving 100,001-1,000,000 People
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
Treatment Technology Train
Modify Lime Softening and pre-oxidation
Modify Coagulation/Filtration and pre-oxidation
Anion Exchange (<20 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Anion Exchange (20-50 mg/L SO4) and FOTWwaste disposal and pre-oxidation
Coagulation Assisted Microf iltration and mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Coagulation Assisted Microf iltration and non-mechanical dewatering/non-hazardous landfill waste disposal and pre-oxidation
Oxidation Filtration (Greensand) and FOTWfor backwash streamand pre-oxidation
Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent madia) and pre-oxidation
Activated Alumina (23,100 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
Activated Alumina (15,400 BV) with pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation
FOU Activated Alumina and pre-oxidation
FOU Reverse Osmosis and pre-oxidation
Sum of Probabilities:
Percent of Treatment Required to
Achieve MCL
<50%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
1.4
0.0
12.8
12.8
0.0
0.0
100.00
50-90%
4.0
4.0
0.0
0.0
63.0
2.0
4.1
1.2
0.0
10.9
10.9
0.0
0.0
100.00
>90%
4.0
4.0
0.0
0.0
63.0
2.0
0.0
1.4
0.0
12.8
12.8
0.0
0.0
100.00
-------
Exhibit D-9
What-lf Analysis Results
MCL Option
5
10
Best Estimate
$411 Million
$177 Million
What-lf Estimate
$515 Million
$192 Million
Appendix D, What-lf Cost Sensitivity Analysis D-ll Arsenic in Drinking Water Rule EA
-------
Appendix E: Benefits and Costs by System Size Category
The drinking water supply industry is subject to considerable economies of scale with respect to
the costs of treatment technologies. Per capita treatment costs steeply increase in inverse
proportion to system size. This is illustrated earlier in this report by Exhibit 6-17 wherein a
hundred-fold increase in household costs over the range of public water supplies can be observed
at the chosen MCL. Because there is such a large increase in relative costs, benefit-cost ratios
also show appreciable variation with system size. In response to comments received on the
proposal, the Agency is providing a subcategorization of the benefits and costs associated with
the various regulatory alternatives by system size.
Cost values for strata specific costs were taken from the National cost modeling effort and reflect
use of a three percent interest rate for annualizing capital costs. Benefits were calculated as a
product of the mean risk reductions (see Exhibit 5-4(c) and calculated as described in Appendix
B ), populations served by impacted sites (shown in Exhibit E-l and calculated per cost
methodology described in Appendix C), and costs per case avoided (as described in Chapter 8
and Appendix B). For the latter element, $6.1 million was assumed per cancer fatality and
$607,000 for non-fatal cancers. Exhibit E-l depicts the benefits by system size category and
Exhibit E-2 displays benefit cost ratios.
Exhibit E-l
Benefits by System Size
Population Stratum
Type
Upper
Upper
Upper
Upper
Lower
Lower
Lower
MCL
20
10
5
3
20
10
5
25-500
2.41
7.13
12.45
16.67
2.72
5.15
7.01
500-3300
7.90
23.34
40.75
54.57
8.91
16.85
22.94
3300-
10,000
9.09
26.85
46.89
62.80
10.25
19.39
26.39
10K-
1000K
45.18
133.50
233.11
312.18
50.97
96.40
131.20
Appendix E, Benefits and Costs by System Size Category E-l
Arsenic in Drinking Water Rule EA
-------
Exhibit E-2
Benefit/Cost Ratios by System Size
Population Stratum
Bound
MCL
Impacted Population
(thousands)
upper
upper
upper
upper
lower
lower
lower
20
10
5
3
20
10
5
25-500
961
0.38
0.42
0.33
0.27
0.43
0.30
0.18
500-3300
315
0.74
0.81
0.62
0.50
0.84
0.59
0.35
3300-
10,000
3,622
1.01
1.11
0.84
0.66
1.14
0.80
0.47
10K-
1000K
18,005
1.32
1.39
1.05
0.85
1.49
1.00
0.59
Appendix E, Benefits and Costs by System Size Category E-2
Arsenic in Drinking Water Rule EA
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