EPA 815-R-00-026

Arsenic in Drinking Water Rule 

Economic Analysis 

Developed for: 

Office of Ground Water and Drinking Water 

U.S. Environmental Protection Agency 

401 M Street, S.W. 

Washington, DC 20460 

John B. Bennett

 Work Assignment Manager 

Developed by: 

Abt Associates Inc. 

4800 Montgomery Lane 

Bethesda, MD 20814 

Gerald D. Stedge, Ph.D. 

Principal Investigator 

December 2000 
Contents

Chapter 1: Executive Summary ................................................... 1-1

1.1 Regulatory Background ............................................ 1-1

1.2 Health Effects of Arsenic ........................................... 1-1

1.3 Regulatory Alternatives Considered ................................... 1-2

1.4 Benefits and Costs of the Proposed Rule ............................... 1-3

Chapter 2: Need for the Revised Rule .............................................. 2-1

2.1 Introduction ........................................................ 2-1

2.2 Public Health Concerns To Be Addressed ................................. 2-2

2.2.1 Health Effects of Arsenic ..................................... 2-2

2.2.2 Sources and Mechanisms of Exposure ........................... 2-4

2.3 Regulatory History ................................................ 2-5

2.4 Rationale for the Regulation ......................................... 2-7

2.4.1 Statutory Authority .......................................... 2-8

2.4.2 Economic Rationale for Regulation .............................. 2-8

Chapter 3: Consideration of Regulatory Alternatives ................................... 3-1

3.1 Regulatory Approaches ............................................ 3-1

3.1.1 Determining the Standard ..................................... 3-1

3.1.2 Determining the MCLG ...................................... 3-1

3.1.3 Determining an MCL ........................................ 3-2

3.1.4 Variances ................................................. 3-3

3.1.5 Analytical Methods ......................................... 3-3

3.2 Regulatory Alternatives Considered and Final Rule ........................ 3-3

3.2.1 Applicability ............................................... 3-4

3.2.2 Maximum Contaminant Level .................................. 3-4

3.2.3 Monitoring ................................................ 3-4

3.2.4 Compliance Technologies and Variances ......................... 3-5

3.2.5 Monitoring Waivers ......................................... 3-5

3.2.6 Implementation ............................................. 3-6

Chapter 4: Baseline Analysis ..................................................... 4-1

4.1 Introduction ..................................................... 4-1

4.2 Industry Profile ................................................... 4-1

4.2.1 Definitions ................................................ 4-1

4.2.2 Sources of Industry Profile Data ................................ 4-2

4.2.3 Number and Size of Public Water Systems ....................... 4-2

4.2.4 System Size and Population Served ............................. 4-4

iii
4.2.5 Number of Entry Points ...................................... 4-6

4.2.6 Number of Households ...................................... 4-6

4.2.7 Production Profile .......................................... 4-7

4.2.8 Treatment Profile .......................................... 4-10

4.3 Occurrences of Arsenic ........................................... 4-10

Chapter 5: Benefits Analysis ..................................................... 5-1

5.1 Nature of Regulatory Benefits ........................................ 5-1

5.2 Health Effects .................................................... 5-1

5.2.1 Overview ................................................. 5-1

5.2.2 Carcinogenic Effects ........................................ 5-2

5.2.3 Non-carcinogenic Effects ..................................... 5-3

5.2.4 Susceptible Subgroups ....................................... 5-5

5.3 Quantitative Benefits of Avoiding Cancer ............................... 5-7

5.3.1 Risk Assessment for Cancer Resulting from Arsenic Exposure .......... 5-7

5.3.2 Community Water Systems ................................... 5-8

5.3.3 Non-Transient Non-Community Water Systems ................... 5-15

5.4 Risk Assessment Results and Benefit Estimates .......................... 5-20

5.4.1 Cases Avoided ........................................... 5-20

5.4.2 Economic Measurements of the Value of Risk Reduction ............ 5-22

5.4.3 Estimates of Cancer Health Benefits of Arsenic Reduction ............ 5-25

5.5 Latency and Other Adjustments: A Sensitivity Analysis .................... 5-26

5.5.1 SAB Recommendations ..................................... 5-26

5.5.2 Analytical Approach ........................................ 5-28

5.5.3 Results .................................................. 5-32

5.6 Other Benefits of Reductions in Arsenic Exposure ........................ 5-35

Chapter 6: Cost Analysis ....................................................... 6-1

6.1 Introduction ..................................................... 6-1

6.2 Methodology .................................................... 6-1

6.2.1 Description of Available Technologies ............................ 6-1

6.2.2 Unit Costs and Compliance Assumptions ......................... 6-4

6.2.3 Monitoring and Administrative Costs ........................... 6-13

6.3 Results ........................................................ 6-27

6.3.1 National Costs ............................................ 6-27

6.3.2 Costs by System Size and Type ............................... 6-29

6.3.3 Costs per Household ....................................... 6-34

6.4 National Compliance Costs Uncertainty Analysis ........................ 6-38

Chapter 7: Comparison of Costs and Benefits ........................................ 7-1

7.1 Introduction ..................................................... 7-1

iv 
7.2 Summary of National Costs and Benefits ............................... 7-1

7.2.1 National Cost Estimates ...................................... 7-1

7.2.2 National Benefits Estimates .................................... 7-1

7.3 Comparison of Benefits and Costs .................................... 7-1

7.3.1 National Net Benefits and National Benefit-Cost Comparison .......... 7-2

7.3.2 Cost-Effectiveness .......................................... 7-5

7.4 Other Benefits ................................................... 7-7

7.5 Benefits-Costs Uncertainty Analysis ................................... 7-9

Chapter 8: Economic Impact Analyses ............................................. 8-1

8.1 Introduction ..................................................... 8-1

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

8.2.1 Description of the Initial Regulatory Flexibility Analysis ............... 8-2

8.2.2 Initial Regulatory Flexibility Analysis Results ....................... 8-8

8.2.3 Summary of EPA’s Small Business Consultations .................. 8-9

8.2.4 Small System Affordability ................................... 8-12

8.3 Coordination With Other Federal Rules ............................... 8-15

8.3.1 Ground Water Rule (GWR) .................................. 8-15

8.3.2 Radon .................................................. 8-16

8.3.3 Microbial and Disinfection By-Product Regulations ................. 8-16

8.4 Minimization of Economic Burden .................................... 8-16

8.5 Unfunded Mandates Reform Act .................................... 8-17

8.5.1 Social Costs and Benefits .................................... 8-18

8.5.2 State Administrative Costs ................................... 8-19

8.5.3 Future Compliance Costs and Disproportionate Budgetary Effects ..... 8-19

8.5.4 Macroeconomic Effects ..................................... 8-26

8.5.5 Consultation with State, Local, and Tribal Governments ............. 8-26

8.5.6 State, Local, and Tribal Government Concerns .................... 8-28

8.5.7 Regulatory Alternatives Considered ............................ 8-28

8.5.8 Impacts on Small Governments ............................... 8-28

8.6 Effect of Compliance with the Arsenic Rule on the Technical, Financial, and Managerial

Capacity of Public Water Systems ................................... 8-29

8.7 Paperwork Reduction Act ......................................... 8-30

8.8 Protecting Children from Environmental Health Risks and Safety Risks ........ 8-31

8.9 Environmental Justice ............................................. 8-31

8.10 Health Risk Reduction and Cost Analysis .............................. 8-31

8.10.1 Quantifiable and Non-Quantifiable Health Risk Reduction Benefits ..... 8-32

8.10.2 Quantifiable and Non-Quantifiable Costs ........................ 8-35

v 
References 

Appendix A. Decision Tree and Large System Costs 

Appendix B. Assumptions and Methodology for Estimating Cancer Risks Avoided and Benefits 

Appendix C. Cost Model Methodology 

Appendix D. What If Cost Sensitivity Analysis 

Appendix E. Benefits and Costs by System Size Category 

vi 
Exhibits

Exhibit 1-1

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

Health Benefits from Reducing Arsenic in PWSs ................................ 1-4

Exhibit 1-2

Total National Cost of Compliance ($ millions) ................................. 1-5

Exhibit 1-3

Net Benefits and Benefit-Cost Ratios of Each Regulatory Option ($ millions) ........... 1-6

Exhibit 4-1

Total Number of Systems by Size, Type, and Ownership ......................... 4-3

Exhibit 4-2

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

Population Category ..................................................... 4-4

Exhibit 4-3

Characteristics of NTNC Systems Affected by the Revised Rule .................... 4-5

Exhibit 4-4

Average Number of Entry Points Per Ground Water System ....................... 4-6

Exhibit 4-5

Water Consumption per Residential Connection ................................ 4-7

Exhibit 4-6

Design Capacity of CWS Plants by Source, Ownership, and System Size ............. 4-8

Exhibit 4-7

Daily Production of CWS Plants by Source, Ownership, and System Size ............. 4-9

Exhibit 4-8

Percentage of CWSs with Various Treatments in Place .......................... 4-10

Exhibit 4-9

Arsenic Occurrence in CWSs at Various Concentration Levels (μg/L) ............... 4-11

Exhibit 4-10

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

Various Ranges ....................................................... 4-12

Exhibit 5-1

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

Associated with Arsenic, by Organ System Affected ............................. 5-4

Exhibit 5-2

Components of the Bladder Cancer Risk Assessment ............................ 5-8

Exhibit 5-3

Life-long Relative Exposure Factors ........................................ 5-10

Exhibit 5-4

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

After Treatment ....................................................... 5-14

Exhibit 5-5

Exposure Factors Used in the NTNC Risk Assessment ......................... 5-16

Exhibit 5-6

Composition of NTNCs ................................................. 5-18

Exhibit 5-7

Mean Cancer Risks (Bladder and Lung Combined), Exposed Population, and Annual Cancer 

Benefits in NTNCs..................................................... 5-19

Exhibit 5-8

Sensitive Group Evaluation of Lifetime Combined Cancer Risks ................... 5-19

Exhibit 5-9

Annual Bladder Cancer Cases Avoided from Reducing Arsenic in CWSs 

and NTNCs.......................................................... 5-21

Exhibit 5-10

Lifetime Avoided Medical Costs for Survivors ................................ 5-25

Exhibit 5-11

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

Health Benefits from Reducing Arsenic in PWSs ............................... 5-26

Exhibit 5-12

Sensitivity of the Primary VSL Estimate to Changes in Latency Period Assumptions, Income 

Growth, and Other Adjustments ........................................... 5-30

Exhibit 5-13

Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits Estimates to 

Changes in VSL Adjustment Factor Assumptions (3% discount rate) ............... 5-33

Exhibit 5-14

Sensitivity of Combined Annual Bladder and Lung Cancer Mortality Benefits Estimates to 

Changes in VSL Adjustment Factor Assumptions (7% discount rate) ............... 5-34

Exhibit 6-1

Arsenic Rule Treatment Trains by Compliance Technologies Component 

with Associated Removal Efficiencies ........................................ 6-3

Exhibit 6-2a

System Compliance Technology Costs Assuming Influent Concentration of 11 μg/L and MCL 

of 10 μg/L ............................................................ 6-5

Exhibit 6-2b

System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL 

of 10 μg/L ............................................................ 6-9

Exhibit 6-3

Unit Resources Required for Monitoring, Implementation, and Administration ......... 6-14

Exhibit 6-4a

viii 
Estimated One-time State Resources Required for Initiation of the Arsenic Rule ........ 6-15

Exhibit 6-4b

Estimated One-time System Resources Required for Initiation of the Arsenic Rule ...... 6-16

Exhibit 6-5

Flow Regression Parameters by Water Source and System Ownership .............. 6-20

Exhibit 6-6

Arsenic Occurrence Distribution (Log-Normal Regression Results) ................. 6-21

Exhibit 6-7 

Summary of Recommended Cost of Capital Estimates (as of March 1998) ........... 6-23

Exhibit 6-8

Non-Transient Non-Community System Characteristics and 

Compliance Decision Tree ............................................... 6-25

Exhibit 6-9

Annual Treatment Costs for Three Large CWSs Expected to 

Undertake or Modify Treatment Practice to Comply with the Arsenic Rule ........... 6-27

Exhibit 6-10

Annual National System and State Compliance Costs ........................... 6-28

Exhibit 6-11

Total Annual CWS Treatment Costs Across MCL Options by System Size .......... 6-29

Exhibit 6-12

Total Annual NTNC Treatment Costs at MCL 3 μg/L by System Service Type 

(3% Discount Rate) .................................................... 6-30

Exhibit 6-13

Total Annual NTNC Treatment Costs at MCL 5 μg/L by System Service Type 

(3% Discount Rate) .................................................... 6-31

Exhibit 6-14

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

(3% Discount Rate) .................................................... 6-32

Exhibit 6-15

Total Annual NTNC Treatment Costs at MCL 20 μg/L by System Service Type 

(3% Discount Rate) .................................................... 6-33

Exhibit 6-16

Number of Households in CWSs Expected to Treat 

by Size Category and MCL (μg/L) Option ................................... 6-34

Exhibit 6-17

Average Annual Household Costs Across MCL Options by System Size ............ 6-35

Exhibit 6-18

Annual Treatment Costs Per Household Across CWSs 

Expected to Treat and Serving < 10,000 People 

MCL 3 μg/L ......................................................... 6-36

Exhibit 6-19

ix 
Annual Treatment Costs Per Household Across CWSs 

Expected to Treat and Serving < 10,000 People 

MCL 5 μg/L ......................................................... 6-36

Exhibit 6-20

Annual Treatment Costs Per Household Across CWSs 

Expected to Treat and Serving < 10,000 People 

MCL 10 μg/L ........................................................ 6-37

Exhibit 6-21

Annual Treatment Costs Per Household Across CWSs 

Expected to Treat and Serving < 10,000 People 

MCL 20 μg/L ........................................................ 6-37

Exhibit 6-22

National Compliance Costs Uncertainty Analysis 

Frequency Distribution (MCL 10 μg/L) ...................................... 6-39

Exhibit 6-23

National Compliance Costs Uncertainty Analysis 

Cumulative Distribution (MCL 10 μg/L) ..................................... 6-40

Exhibit 7-1

Summary of Annual National Net Benefits and Benefit-Cost Ratios .................. 7-2

Exhibit 7-2

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

Exhibit 7-3

Comparison of Incremental Costs and Benefits (7% Discount Rate, in $ millions) ........ 7-4

Exhibit 7-4

Cost per Cancer Case Avoided ............................................ 7-5

Exhibit 7-5

Comparison of Annual Costs to Cases of Cancer per Year 

(7% Discount Rate) ..................................................... 7-6

Exhibit 7-6

Incremental Cost per Incremental Cancer Case Avoided 

(7% Discount Rate, in $ millions) ........................................... 7-7

Exhibit 7-7

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

Health Benefits from Reducing Arsenic in PWSs ................................ 7-8

Exhibit 7-8

National Compliance Costs and Benefits Uncertainty Analysis 

Cumulative Cost Distribution vs. Benefits Range (MCL 10 μg/L) .................... 7-9

Exhibit 8-1

Profile of the Universe of Small Water Systems

x 
Regulated Under the Arsenic Rule .......................................... 8-5

Exhibit 8-2

Annual Cost of Compliance Costs as a Percentage of Revenues 

by Type of Small Entity (PWSs that are Expected to Modify or Install Treatment at an MCL = 

10 μg/L) ............................................................. 8-7

Exhibit 8-3

Number of CWSs Expected to Undertake or Modify Treatment Practice 

MCL 10 μg/L ......................................................... 8-8

Exhibit 8-4

Mean Annual Costs to Households Served by CWSs, by Size Category ............. 8-14

Exhibit 8-5

Average Annual Cost per CWS Exceeding the MCL, by Ownership ................ 8-21

Exhibit 8-6

Annual Compliance Costs per Household for CWSs Exceeding MCLs .............. 8-23

Exhibit 8-7

Annual Compliance Costs per Household for CWSs Exceeding MCLs, 

as a Percent of Median Household Income ................................... 8-24

Exhibit 8-8

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

(3% Discount Rate) .................................................... 8-25

Exhibit 8-9

Annual Bladder Cancer Cases Avoided from Reducing Arsenic 

in CWSs and NTNCs .................................................. 8-33

Exhibit 8-10

Annual Lung Cancer Cases Avoided from Reducing Arsenic 

in CWSs and NTNCs .................................................. 8-33

Exhibit 8-11

Annual Total Cancer Cases Avoided from Reducing Arsenic 

in CWSs and NTNCs .................................................. 8-34

Exhibit 8-12

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

Health Benefits from Reducing Arsenic in PWSs ............................... 8-35

Exhibit 8-13

Summary of the Total Annual National Costs of Compliance ($ millions) ............. 8-36

Exhibit 8-14

Mean Annual Costs per Household in CWSs ................................. 8-37

Exhibit 8-15

Cost per Cancer Case Avoided ($ millions) .................................. 8-38

xi 
Chapter 1: Executive Summary 

1.1 Regulatory Background 

An enforceable standard of 50 μg/L currently exists for arsenic in community water systems under the 

National Interim Primary Drinking Water Regulations (40 CFR 59566). In §1412(b)(12)(A) of the 

SDWA, as amended in 1996, Congress specifically directed EPA to issue a final rule by January 1, 

2001. Congress recently changed the deadline for the final rule to June 22, 2001 (Public Law 106­

377). 

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

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

μg/L; 

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

compliance with the new standard; and 

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

Monitoring Framework (40 CFR 141.23(c)). 

1.2 Health Effects of Arsenic 

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

since. The Agency has classified arsenic as a Class A human carcinogen, “based on sufficient evidence 

from human data. An increased lung cancer mortality was observed in multiple human populations 

exposed primarily through inhalation. Also, increased mortality from multiple internal organ cancers 

(liver, kidney, lung, and bladder) and an increased incidence of skin cancer were observed in 

populations consuming drinking water high in inorganic arsenic.” 

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

arsenic with several internal cancers at exposure concentrations of several hundred micrograms per liter 

of drinking water.” Ten epidemiological studies covering eight organ systems have quantitative data for 

risk assessment (NRC, 1999, Table 4-1). The organ systems where cancers in humans have been 

identified include skin, bladder, lung, kidney, nasal cavity, liver, and prostate. 

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

cancer. Considering all cancers in aggregate, the NRC states that “considering the data on bladder and 

lung cancer in both sexes noted in the studies ... a similar approach for all cancers could easily result in 

a combined cancer risk on the order of 1 in 100" (at the current MCL of 50 μg/L). 

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

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

Chapter 1, Executive Summary 1-1 Arsenic in Drinking Water Rule EA 
years in Taiwan has provided standardized mortality ratios (SMRs) for 23 cancerous and noncancerous causes of death in women and 27 causes of death in men at statistically significant levels in an 

area of Taiwan with elevated arsenic exposures (Tsai et al., 1999). SMRs are an expression of the 

ratio between deaths that were observed in an area with elevated arsenic levels and those that were 

expected to occur, based on the mortality experience of the populations in nearby areas without 

elevated arsenic levels. Drinking water (250-1,140 μg/L) and soil (5.3-11.2 mg/kg) in the Tsai et al. 

(1999) population study had very high arsenic content. 

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

laryngeal cancer, and cerebrovascular disease” as possibly “related to chronic arsenic exposure via 

drinking water,” which had not been reported before. In addition, the study area had upper respiratory 

tract cancers previously only related to occupational inhalation. High male mortality rate (SMR > 3) 

existed for bladder, kidney, skin, lung, and nasal cavity cancers and for vascular disease. However, the 

authors noted that the mortality range was marginal for leukemia, cerebrovascular disease, liver 

cirrhosis, nephropathy, and diabetes. Females also had high mortalities for laryngeal cancer. There are, 

of course, possible differences between the population and health care in Taiwan and the United States. 

For example, arsenic levels in the U.S. are not as high as they were in the study area of Taiwan. 

However, the study gives an indication of the types of health effects that may be associated with arsenic 

exposure via drinking water. 

Arsenic interferes with a number of essential physiological activities, including the actions of enzymes, 

essential cations, and transcriptional events in cells (NRC, 1999). A wide variety of adverse health 

effects have been associated with chronic ingestion of arsenic in drinking water, occurring at various 

exposure levels. 

1.3 Regulatory Alternatives Considered 

In regulating a contaminant, EPA first sets a maximum contaminant level goal (MCLG), which 

establishes the contaminant level at which no known or anticipated adverse health effects occur. 

MCLGs are non-enforceable health goals. For this rulemaking, EPA is setting an MCLG of zero. EPA 

then sets an enforceable maximum contaminant level (MCL) as close as technologically possible to the 

MCLG. In addition, EPA may use its discretion in setting the MCL by choosing an MCL that is 

protective of public health while also ensuring that the quantified and non-quantified costs are justified 

by the quantified and non-quantified benefits of the rule. For this rulemaking, EPA is setting an MCL of 

10 μg/L. Chapter 3 describes the process by which EPA determined both the MCLG and the MCL. 

EPA considered a range of MCLs in developing the final Arsenic Rule, including MCLs of 3, 5, 10, 

and 20 μg/L. EPA evaluated the following five factors to determine the revised MCL: 

• The analytical capability and laboratory capacity; 

• The likelihood of water systems choosing various compliance technologies for several 

sizes of systems based on source water properties; 

• The national occurrence of arsenic in water supplies; 

Chapter 1, Executive Summary 1-2 Arsenic in Drinking Water Rule EA 
• Quantified and non-quantified costs and health risk reduction benefits likely to occur at 

the MCLs considered; and 

• The effects on sensitive subpopulations. 

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

been determined to be as close to the MCLG as is feasible. However, the Agency is using its 

discretionary authority in §1412(b)(6)(A) to consider setting MCL at a less stringent level. The statute 

requires that the alternative less stringent level be one which maximizes health risk reduction at a level 

where costs and benefits are also considered. As a result, EPA considered the alternative MCL 

options of 5, 10, and 20 μg/L. 

The Agency also considered two regulatory options related to the applicability of the revised MCL. 

Specifically, EPA investigated applying both the monitoring and treatment requirements of the Arsenic 

Rule to both community water systems (CWSs) and NTNCs. A CWS is defined as a system that 

provides piped water to at least 25 people or with at least 15 service connections year-round. An 

NTNC is a public water system that is not defined as a CWS and that regularly serves at least 25 of the 

same people for at least six months of the year. After considering the costs and benefits of the revised 

rule with regard to both CWSs and NTNCs, EPA is requiring both CWS and NTNC water systems to 

comply with all facets of the revised rule. The benefit-cost analysis upon which this decision is based is 

provided in Chapters 5, 6, and 7 of this Economic Analysis (EA). Transient non-community systems, 

which provide potable water to continuously changing populations, will not be subject to the revised 

rule. 

The revised rule also includes modifications to the current monitoring requirements, including the 

availability of monitoring waivers. A detailed discussion of these changes can be found in Chapter 3. 

1.4 Benefits and Costs of the Proposed Rule 

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

non-cancer risks. Although arsenic causes numerous health effects, bladder and lung cancer are the 

only endpoints for which an Agency-approved metric for evaluating arsenic-related risk currently exists. 

This cancer slope factor (SF) for bladder and lung cancer is used to calculate cases potentially avoided 

due to the revised arsenic standard. Benefits estimates for avoided cases of bladder and lung cancer 

were calculated using mean population risk estimates at various MCL levels. Lifetime risk estimates 

were converted to annual risk factors and applied to the exposed population to determine the number 

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

survival information. The avoided premature fatalities were valued based on the VSL estimates 

discussed in Chapter 5, as recommended by EPA current guidance for cost/benefit analysis. The 

avoided non-fatal cases were valued based on the willingness to pay estimates for the avoidance of 

chronic bronchitis. The upper bound estimates include the possibility of the incidence rate being 

understated, depending on the survival rate for bladder cancer in the study area of Taiwan. 

Chapter 1, Executive Summary 1-3 Arsenic in Drinking Water Rule EA 
Numerous other health effects that are likely to be avoided as a result of this rule may generate 

significant benefits, and should not be discounted based on the fact that they cannot be quantified at this 

time. The estimated total national monetized benefits of the proposed rule and the other rule options 

considered are provided in Exhibit 1-1. 

Exhibit 1-1

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and

Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs

($ millions)

Arsenic 

Level 

(μg/L) 

Total 

Annual Cost 

(7%) 

Annual Bladder 

Cancer Health 

Benefits1,2 

Annual Lung 

Cancer Health 

Benefits1,2 

Total Annual 

Health 

Benefits1,2 

Potential Non-Quantifiable 

Health Benefits 

3 $792.1 $58.2 - $156.4 $155.6 - $334.5 $213.8 - $490.9 

• Skin Cancer 

• Kidney Cancer 

• Cancer of the Nasal 

Passages 

• Liver Cancer 

• Prostate Cancer 

• Cardiovascular Effects 

• Pulmonary Effects 

• Immunological Effects 

• Neurological Effects 

• Endocrine Effects 

• Reproductive and 

Developmental Effects 

5 $471.7 $52.0 - $113.3 $139.1 - $242.3 $191.1 - $355.6 

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

20 $76.5 $20.1 - $21.5 $46.1 - $53.8 $66.2 - $75.33 

1

 May 1999 dollars.

2

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

3

 For 20 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional

reduction from the higher level risk base case. Thus, the number of estimated cases avoided and estimated

benefits are higher at 20 μg/L using the risk estimates adjusted for arsenic in cooking water and food.

For the revised MCL of 10 μg/L, the estimated monetized bladder and lung cancer health benefits 

range from $139.6 million to $197.7 million. More detail about these benefit estimates are found in 

Chapter 5. Exhibit 1-2 shows the estimated national cost of compliance of the revised rule and the 

other rule options that were considered. At the revised MCL of 10 μg/L, the estimated national cost of 

compliance is $180.4 million at a discount rate of three percent, and $205.6 million at a discount rate of 

seven percent. 

Chapter 1, Executive Summary 1-4 Arsenic in Drinking Water Rule EA 
Exhibit 1-2

Total National Cost of Compliance ($ millions)

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

System Costs 

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

Monitoring/ 

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

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

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

System Costs 

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

Monitoring/ 

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

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

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

System Costs 

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

Monitoring/ 

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

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

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

System Costs 

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

Monitoring/ 

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

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

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

CWS NTNC

MCL = 10 mmg/L 

MCL =20 mmg/L 

TOTAL 

MCL = 3 mmg/L 

MCL =5 mmg/L 

Chapter 1, Executive Summary 1-5 Arsenic in Drinking Water Rule EA 
The net benefits and benefit-cost ratios of each regulatory option are provided in Exhibit 1-3. At the 

revised MCL of 10 μg/L, the net benefits range from a high of $17.3 million to a low of a negative 

$40.8 million, at a discount rate of three percent. These net benefits correspond to benefit-cost ratios 

of 0.8 and 1.1 (also at a three percent rate of discount). 

Exhibit 1-3 

Net Benefits and Benefit-Cost Ratios of Each Regulatory Option 

($ millions) 

MCL (mg/L) 3 5 10 20 

3% Discount Rate 

lower bound

Net Benefits $ (484.0) $ (223.7) $ (40.8) $ (0.6) 

Benefit/Cost Ratio 0.3 0.5 0.8 1.0 

upper bound

Net Benefits $ (206.8) $ (59.2) $ 17.3 $ 8.5 

Benefit/Cost Ratio 0.7 0.9 1.1 1.1 

7% Discount Rate 

lower bound

Net Benefits $ (578.3) $ (280.6) $ (66.0) $ (10.3) 

Benefit/Cost Ratio 0.3 0.4 0.7 0.9 

upper bound

Net Benefits $ (301.1) $ (116.1) $ (7.9) $ (1.2) 

Benefit/Cost Ratio 0.6 0.8 1.0 1.0 

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

for administration of water programs. 

Chapter 1, Executive Summary 1-6 Arsenic in Drinking Water Rule EA 
As mentioned above, there are a number of important non-monetized benefits of reducing arsenic 

exposure that are not included in the net benefit and benefit-cost calculations. Chief among these are 

certain health impacts known to be caused by arsenic. Such nonquantifiable benefits may include skin 

cancer, kidney cancer, cancer of the nasal passages, liver cancer, prostate cancer, cardiovascular 

effects, pulmonary effects, immunological effects, neurological effects, endocrine effects, and customer 

peace-of-mind benefits from knowing their drinking water has been treated for arsenic. For example, a 

number of epidemiologic studies conducted in several countries (e.g., Taiwan, Japan, England, 

Hungary, Mexico, Chile, and Argentina) report an association between arsenic in drinking water and 

skin cancer in exposed populations. Early reports linking inorganic arsenic contamination of drinking 

water to skin cancer came from Argentina (Neubauer, 1947, reviewing studies published as early as 

1925) and Poland (Tseng et al., 1968). However, the first studies that observed dose-dependent 

effects of arsenic associated with skin cancer came from Taiwan (Tseng et al., 1968; Tseng, 1977). 

These studies focused EPA’s attention on the health effects of ingested arsenic. Studies conducted in 

the U.S. have not demonstrated an association between inorganic arsenic in drinking water and skin 

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

types of effects. 

The potential monetized benefits associated with skin cancer reduction would not change the total 

benefits of the rule to an appreciable degree, even if the assumption were made that the risk of skin 

cancer were equivalent to that of bladder cancer, using EPA’s 1988 risk assessment. Skin cancer is 

highly treatable (at a cost of illness of less than $3,500 for basal and squamous cell carcinomas versus a 

cost of illness of $178,000 for non-fatal bronchitis) in the U.S., with few fatalities (less than one 

percent). 

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

in this analysis due to lack of appropriate data. 

Other benefits not monetized in this analysis include customer peace of mind from knowing drinking 

water has been treated for arsenic and reduced treatment costs for currently unregulated contaminants 

that may be co-treated with arsenic. To the extent that reverse osmosis is used for arsenic removal, 

these benefits could be substantial. Reverse osmosis and activated alumina are the primary point-ofuse treatments for small systems. (These benefits of avoided treatment cannot currently be monetized; 

however, they can be readily monetized in the future, as decisions are made about which currently 

unregulated contaminants to regulate.) 

Chapter 1, Executive Summary 1-7 Arsenic in Drinking Water Rule EA 
Chapter 2: Need for the Revised Rule 

2.1 Introduction 

The Safe Drinking Water Act (SDWA), as amended in 1996, requires EPA to identify and regulate 

substances in drinking water that may have an adverse effect on public health and that are known or 

anticipated to occur in public water supplies. National Primary Drinking Water Regulations 

(NPDWRs) address risks to public health, and secondary regulations address aesthetic qualities (such 

as taste, odor, or color) that relate to public acceptance of drinking water. For NPDWRs, EPA must 

either establish a Maximum Contaminant Level (MCL) or, if it is not economically or technically feasible 

to monitor the contaminant in drinking water, specify a treatment technique to remove the contaminant 

or reduce its concentration in the water supply. 

An enforceable standard of 50 μg/L currently exists for arsenic in community water systems under the 

National Interim Primary Drinking Water Regulations (40 CFR 59566). In §1412(b)(12)(A) of the 

SDWA, as amended in 1996, Congress specifically directed EPA to propose a NPDWR for arsenic 

by January 1, 2000, and issue the final regulation by January 1, 2001. Congress recently changed the 

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

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

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

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

standard; and 

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

Monitoring Framework (40 CFR 141.23(c)). 

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

benefits of the Arsenic Rule in an economic analysis document (EA). This chapter of the EA discusses 

the public health concerns being addressed by the rule, describes the history of regulatory efforts 

concerning arsenic, and discusses the economic rationale for the rule. Subsequent chapters will 

accomplish the following: 

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

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

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

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

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

EPA (Chapter 7), and 

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

Chapter 2, Need for the Revised Rule 2-1 Arsenic in Drinking Water Rule EA 
2.2 Public Health Concerns To Be Addressed 

This section describes the public health concerns addressed by the final Arsenic Rule. A description of 

potential health effects associated with arsenic, including effects in sensitive subpopulations, along with 

the sources of human exposure to arsenic, is presented. In addition, the section describes current 

controls that address exposure to arsenic. 

2.2.1 Health Effects of Arsenic 

Arsenic is a naturally occurring element present in the environment in both organic and inorganic forms. 

Inorganic arsenic, considered to be the more toxic form, is found in ground water, surface water, and 

many foods. Chronic exposure to high levels of inorganic arsenic in drinking water has been found to 

result in a variety of adverse health effects, including skin and internal cancers and cardiovascular and 

neurological effects. 

Exposures to organic forms of arsenic also occur through ingestion of food and metabolism of ingested 

inorganic arsenic. Experimental data on the effects of organic forms of arsenic are not as well 

characterized as those for inorganic arsenic, and thus are the subject for future research. Limited data 

on the primary organic forms in fish and shellfish (arsenobetaine and arsenocholine) suggest that these 

forms are relatively nontoxic. Other forms of organoarsenicals in foods have been even less well 

characterized. Recent in vitro toxicity evidence indicates that the trivalent form of monomethylarsonic 

acid is more toxic than either the trivalent (arsenite) or pentavalent (arsenate) forms of inorganic arsenic. 

Additional data are needed in this area before the toxicological significance of the trivalent form of 

monomethylarsonic acid is clear. 

In 1996, EPA requested that the National Research Council of NAS conduct an independent review of 

the arsenic toxicity data. NRC was asked to review EPA’s current criteria (50 μg/L and 0.018 μg/L), 

evaluate use of recent Taiwan data and other studies to assess the carcinogenic and non-carcinogenic 

health effects of arsenic, and recommend changes to EPA’s risk characterization for arsenic. NRC 

issued its report on March 23, 1999 (NRC, 1999). The health effects of inorganic arsenic are 

summarized below and are described in more detail in Chapter 5. 

Cancer 

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

contaminants. However, there is substantial debate among the scientific community over the 

interpretation of these data and their application in risk assessment. NRC found that a number of 

epidemiologic studies conducted in several countries (e.g., Taiwan, Japan, England, Hungary, Mexico, 

Chile, and Argentina) report an association between arsenic in drinking water and skin cancer in 

exposed populations. Increased mortality from internal cancers of liver, bladder, kidney, and lung have 

also been reported. 

Chapter 2, Need for the Revised Rule 2-2 Arsenic in Drinking Water Rule EA 
EPA has identified arsenic as a group A “known” human carcinogen, based on increased risks of lung 

cancer in workers exposed to airborne arsenic and dose-dependent increases in skin cancer risk in 

Taiwan. 

Non-Cancer Health Effects 

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

health effects. These include thickening of the skin, effects on the nervous system such as tingling and 

loss of feeling in limbs, hearing impairment, effects on the heart and circulatory system, diabetes, 

developmental effects, and effects on the gastrointestinal system and liver. Many of these effects are 

observed at concentrations where cancer effects were observed in the epidemiology studies. 

Sensitive Subpopulations 

Certain sensitive individuals may be at a greater risk of serious illness from exposure to arsenic than the 

general population. The NRC report (1999) noted that human sensitivity to the toxic effects of 

inorganic arsenic exposure is likely to vary based on genetics, metabolism, diet, health status, sex, and 

other possible factors. For example, reduced ability to methylate arsenic (convert inorganic arsenic into 

less acutely toxic and more readily excreted forms) may result in retention of more arsenic in the body 

and increased risk of toxic effects. However, there is insufficient evidence at the present time to 

characterize the influence of such factors as age, sex, nutrition, and genetic polymorphism on the 

expression of arsenic toxicity (NRC, 1999). 

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

health effects from arsenic: 

• Childrenare identified as especially susceptible because their dose of arsenic will be, 

on average, higher than that of adults exposed to similar concentrations due to their 

higher fluid and food intake relative to body weight. The NRC report cited one study 

that suggests that children may have a lower arsenic-methylation efficiency than adults. 

• Pregnant and lactating women are especially vulnerable because of possible adverse 

reproductive and developmental effects of arsenic. 

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

• Individuals with pre-existing diseases that affect specific organs —in particular, 

kidney and liver problems—may be more susceptible to the effects of arsenic because 

these organs act to detoxify arsenic in the body. 

In addition, arsenic can directly damage these and other organ systems, as described 

above. Individuals with pre-existing damage or congenital defects in these systems are 

more susceptible to health effects from exposure to arsenic. The elderly are more likely 

as a group to have pre-existing conditions in the susceptible organ systems. 

Chapter 2, Need for the Revised Rule 2-3 Arsenic in Drinking Water Rule EA 
Section 5.2.4 discusses the susceptibility of these subgroups in more detail. Due to a lack of available 

data, no quantitative analysis of the specific risks to sensitive populations was performed as part of this 

EA. 

2.2.2 Sources and Mechanisms of Exposure 

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

exposure. Erosion and weathering of rocks deposit arsenic in water bodies and lead to the uptake of 

arsenic by animals and plants. Consumption of food and water is the major source of arsenic exposure 

for the majority of U.S. citizens. People may also be exposed from industrial sources, as arsenic is 

used in semiconductor manufacturing, petroleum refining, wood preservatives, animal feed additives, 

and herbicides. 

Arsenic can combine with other elements to form inorganic and organic arsenicals. In general, inorganic 

derivatives are regarded as more toxic than the organic forms. While food contains both inorganic and 

organic arsenicals, primarily inorganic forms are present in water. 

Recently, EPA developed estimates of human exposure to arsenic in drinking water, food, and air using 

data from numerous Federal sampling surveys analyzing the occurrence of arsenic in public water 

supplies, dietary foods, and ambient air. EPA’s national air sampling databases indicate very low 

concentrations of arsenic in both urban and non-urban locations, at levels typically ranging from about 

0.003 to 0.03 μg/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 μg/day. The FDA analytical methodology does not differentiate 

between the organic and inorganic forms of arsenic. For most people living in the U.S., inorganic 

arsenic exposure is primarily from food and water sources. Since the inorganic forms are considered to 

be more toxic, it is important to estimate the amount of inorganic arsenic in the diet. To accomplish this 

estimation, EPA used the FDA data along with a separate study that characterized arsenic species in 

foods. This separate characterization indicated that about 20 percent of daily intake of dietary arsenic 

is in the inorganic form. Conversely, most arsenic present in drinking water is in the form of inorganic 

arsenic species. 

Accounting for the organic forms of arsenic in food, the dietary intake of inorganic arsenic was 

estimated to be approximately 14 μg/day. An adult drinking 2 L/day of water containing 10 μg/L of 

arsenic would obtain 20 μg/day from drinking water, so that drinking water would contribute about 60 

percent of total intake of inorganic arsenic. On the other hand, an adult drinking water containing 2 

μg/L of arsenic would obtain almost 80 percent of the daily inorganic arsenic from food. 

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

This section provides a chronology and overview of regulatory actions affecting arsenic in drinking 

water and recent efforts that have led to this rulemaking. It also summarizes the major studies and data 

collection efforts that highlighted the need for a new rule. 

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

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

Public Health Service for interstate water carriers, which was not based on a risk assessment. EPA 

based the MCL on daily consumption of two liters of water providing approximately 10 percent of total 

ingested arsenic of 900 μg/day. Commenters recommended an MCL of 100 μg/L based on no 

observed adverse health effects. EPA noted long-term chronic effects at 300 to 2,750 μg/L, but no 

chronic effects at 120 μg/L (US EPA, 1975, pg. 59576, EPA-570/9-76-003). 

Water Quality Criteria: In 1980, EPA announced the availability of Water Quality Criteria 

Documents to protect surface water bodies from pollutants under the Clean Water Act (45 FR 79318, 

November 28, 1980). These criteria are used as guidance to the States in establishing surface water 

quality standards and discharge limits for effluents. The criterion for protection of human health from 

ingestion of arsenic in contaminated water and aquatic organisms was 2.2 nanograms per liter (ng/L), or 

0.0022 μg/L. In 1992, the Clean Water Act criterion was recalculated based on an updated risk 

assessment to yield 0.018 μg/L for arsenic (57 FR 60848, December 22, 1992). 

1983 Notice prior to proposal: In an Advance Notice of Proposed Rulemaking (ANPRM) 

published October 5, 1983 (48 FR 45502), EPA requested comment on whether the arsenic MCL 

should consider carcinogenicity, other health effects, and nutritional requirements; and whether MCLs 

are necessary for separate valence states. 

1985 Proposed MCLG: In 1985, EPA proposed a non-enforceable Maximum Contaminant Level 

Goal (MCLG) of 50 μg/L based on an NAS conclusion that 50 μg/L balanced toxicity and possible 

essentiality. EPA also requested comment on alternate MCLGs of 100 μg/L based on noncarcinogenic effects and 0 μg/L based on carcinogenicity (50 FR 46936, November 13, 1985). 

1986 SDWA Amendments: The 1986 SDWA Amendments converted the 1975 interim arsenic 

standard to a NPDWR, subject to revision by 1989. 

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

on Ingested Inorganic Arsenic: Skin Cancer; Nutritional Essentiality (EPA/625/3-87/013), in part, 

to evaluate the validity of applying the Taiwan 1968/1977 data to dose-response assessments in the 

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

Chapter 2, Need for the Revised Rule 2-5 Arsenic in Drinking Water Rule EA 
1989: After reviewing EPA’s arsenic health effects studies in June 1988, the Science Advisory Board 

(SAB) stated in its August 14, 1989, report the following: 

• The essentiality of arsenic is suggestive but not definitive; 

• Hyperkeratosis may not be a precursor of skin cancer; 

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

cause skin cancer; 

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

and 

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

SAB concluded that the dose-response is non-linear and reported that the 1988 Forum Report did not 

apply non-linearity in its risk assessment. 

1989: Uncertainty about arsenic risk assessment issues caused the Agency to miss the 1989 deadline 

for proposing a revised NPDWR, and a citizen suit was filed against EPA. A consent decree was 

entered by the court in June 1990 and was amended several times thereafter before being dismissed 

after passage of the 1996 SDWA Amendments. 

The Safe Drinking Water Act Amendments of 1996, in §1412(b)(12)(A), directed EPA to take 

the following actions for arsenic: 

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

• Consult with the National Academy of Sciences, other Federal agencies, and interested 

public and private entities in conducting the studies; 

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

• Issue a final rule by January 1, 2001. 

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

• Assess health effects for sensitive populations; 

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

• Evaluate the incremental costs and benefits of different regulatory options, accounting 

for the changes that may result from implementation of other rules; 

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

• Review MCLs every six years or sooner. 

The 1996 amendments also made the following changes: 

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

rather than 18 months. 

Chapter 2, Need for the Revised Rule 2-6 Arsenic in Drinking Water Rule EA 
• Compliance for non-microbial contaminants can be achieved by use of point-of-use 

(POU) or point-of-entry (POE) devices that are maintained by the small public water 

system. 

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

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

Association Research Foundation in subsequent years. 

EPA proposed the arsenic regulation on June 22, 2000, in the Federal Register. At the same time, 

EPA is proceeding with its Arsenic Research Plan, which will address a variety of issues related to 

exposure, treatment, and health effects.1 In EPA’s appropriations bill for 2001, Public Law 106-377, 

Congress directed EPA to issue the final arsenic rule by June 22, 2001, one year after proposal. 

NRC Report: In 1996, EPA requested that the National Research Council of NAS conduct an 

independent review of the arsenic toxicity data and evaluate the scientific validity of EPA’s 1988 risk 

assessment for arsenic in drinking water. In addition, NRC was asked to review EPA’s current criteria 

(50 μg/L and 0.018 μg/L), evaluate use of recent Taiwan data and other studies to assess the 

carcinogenic and non-carcinogenic health effects of arsenic, and recommend changes to EPA’s risk 

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

conclusions: 

• The Taiwan studies provide the best available evidence on the human health effects of 

arsenic, and are supported by studies in Chile and Argentina that report similar results. 

These studies show that chronic ingestion of inorganic arsenic at high doses causes 

bladder and lung cancer, as well as skin cancer. 

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

risk assessment. 

• Non-cancer chronic effects include skin effects, cardiovascular and cerebrovascular 

disease, diabetes, and reproductive effects. 

• The molecular processes of arsenic toxicity are not well understood. Research can help 

characterize the dose-response relationship for both cancer and non-cancer endpoints, 

especially at low doses. 

• The current 50 μg/L MCL is not adequately protective of human health and therefore 

requires downward revision as promptly as possible.2 

1

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

2

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

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

This section discusses the economic rationale for choosing a regulatory approach to address the public 

health consequences of drinking water contamination. EPA provides the economic rationale in 

response to Executive Order Number 12866, Regulatory Planning and Review, which states: 

[E]ach agency shall identify the problem that it intends to address (including, where 

applicable, the failures of the private markets or public institutions that warrant new 

agency action) as well as assess the significance of that problem (§1, b(1)). 

In addition, guidance from the Office of Management and Budget dated January 11, 1996, states that 

“in order to establish the need for the proposed action, the analysis should discuss whether the problem 

constitutes a significant market failure.” Therefore, the economic rationale presented in this section 

should not be interpreted as EPA’s approach to implementing the SDWA. Instead, it is EPA’s 

justification, as required by the Executive Order, for a regulatory approach to this public health issue. 

2.4.1 Statutory Authority 

Section 1412(b)(1)(A) of the SDWA requires EPA to establish National Primary Drinking Water 

Regulations for contaminants that may have an adverse public health effect; that are known to occur or 

that present a substantial likelihood of occurring once in public water systems (PWSs), at a frequency 

and level of public concern; and that present a meaningful opportunity for health risk reduction for 

persons served by PWSs. This general provision is supplemented by additional requirements that EPA 

proposed a revised MCL for arsenic by January 1, 2000 (§1412(b)(1)(A)), and issue a final regulation 

by June 22, 2001 (Public Law 106-377). 

2.4.2 Economic Rationale for Regulation 

In addition to the statutory directive to regulate arsenic, there is also economic rationale for government 

regulation. In a perfectly competitive market, market forces guide buyers and sellers to attain the best 

possible social outcome. A perfectly competitive market occurs when there are many producers of a 

product selling to many buyers, and both producers and buyers have complete knowledge regarding 

the products of each firm. Also, there must not be any barriers to entry into the industry, and producers 

in the industry must not have any advantage over potential new producers. Several factors in the public 

water supply industry do not satisfy the requirements for a perfect market and lead to market failures 

that may require regulation. 

First, water utilities are natural monopolies. A natural monopoly exists because it is not economically 

efficient to have multiple suppliers competing to build multiple systems of pipelines, reservoirs, wells, 

and other facilities.3 Instead, a single firm or government entity performs these functions generally under 

3

Mansfield (1975) states that natural monopolies exist because the average cost of producing the product 

reaches a minimum at an output rate that is enough to satisfy the entire market at a price that is profitable. Multiple 

Chapter 2, Need for the Revised Rule 2-8 Arsenic in Drinking Water Rule EA 
public control. Under monopoly conditions, consumers are provided only one level of service with 

respect to the quality of the product, in this case drinking water quality. If consumers do not believe 

that the market of safety in public health production is adequate, they cannot simply switch to another 

water utility or perceived higher quality source of supply (e.g., bottled water) without incurring 

additional cost. 

Second, high information and transaction costs impede public understanding of the health and safety 

issues concerning drinking water quality. The types of health risks potentially posed by trace quantities 

of drinking water contaminants involve analysis and distillation of complex toxicological data and health 

sciences. EPA recently developed the Consumer Confidence Report rule to make water quality 

information more easily available to consumers. The Consumer Confidence Report rule requires 

community water systems to mail their customers an annual report on local drinking water quality. 

However, consumers will still have to analyze this information for its health risk implications. Even if 

informed consumers are able to engage utilities regarding these health issues, the costs of such 

engagement, known as “transaction costs” (in this case measured in personal time and commitment), 

present another significant impediment to consumer expression of risk preference. 

SDWA regulations are intended to provide a level of protection from exposure to drinking water 

contaminants that would not otherwise occur in the existing market environment of public water supply. 

The regulations set minimum performance requirements for all public water supplies in order to reduce 

the risk confronted by all consumers from exposure to drinking water contaminants. SDWA 

regulations are not intended to restructure market mechanisms or to establish competition in supply. 

Rather, SDWA standards establish the level of service to be provided in order to better reflect public 

preference for safety. The Federal regulations remove the high information and transaction costs by 

acting on behalf of all consumers in balancing the risk reduction and the social costs of achieving this 

reduction. 

producers competing would produce the product at higher than minimum long-run average cost. Competition to 

achieve lower average costs would drive prices down until a single supplier was victorious. 

Chapter 2, Need for the Revised Rule 2-9 Arsenic in Drinking Water Rule EA 
Chapter 3: Consideration of Regulatory Alternatives 

3.1 Regulatory Approaches 

The Safe Drinking Water Act (SDWA) establishes EPA’s responsibility for ensuring the quality of 

drinking water and defines the mechanisms available to the Agency to protect public health. 

Specifically, the SDWA requires EPA to set enforceable MCLs when technically or economically 

feasible or otherwise establish treatment technique requirements for specific contaminants in drinking 

water. In meeting this mandate, EPA sets water quality standards by identifying which contaminants 

should be regulated and establishing the levels of the contaminant that water systems must attain. This 

section discusses the approach EPA used in determining the regulatory alternatives that were 

considered. 

3.1.1 Determining the Standard 

In regulating a contaminant, EPA first sets a maximum contaminant level goal (MCLG), which 

establishes the contaminant level at which no known or anticipated adverse health effects occur. 

MCLGs are non-enforceable health goals. For this rulemaking, EPA set an MCLG of zero. EPA then 

sets an enforceable maximum contaminant level (MCL) as close as technologically possible to the 

MCLG. In addition, EPA may use its discretion in setting the MCL by choosing an MCL that is 

protective of public health while also ensuring that the quantified and non-quantified costs are justified 

by the quantified and non-quantified benefits of the rule. For this rulemaking, EPA is setting an MCL of 

10 μg/L. The following sections describe the process by which EPA determined both the MCLG and 

the MCL. 

3.1.2 Determining the MCLG 

Carcinogens: For many years, Congress supported a goal of zero tolerance for carcinogens in food 

and water, and that goal was incorporated into the SDWA of 1974. Under this policy, contaminants 

that are classified as probable human carcinogens have had MCLGs set at zero. EPA’s Office of 

Science and Technology (OST) (in the Office of Water) develops a cancer risk range that quantifies the 

probability that a person will develop cancer during a lifetime of ingesting water containing the regulated 

contaminant. 

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

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

and surface area. 

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

33992). At that time EPA’s default assumptions included low-dose linearity to extrapolate the cancer 

risk range, which assumes that carcinogenic effects do not exhibit a threshold and that carcinogens pose 

risks to humans at any concentration. EPA proposed revised Guidelines for Carcinogen Risk 

Assessment in 1996 (61 FR 17960). 

Chapter 3, Consideration of Regulatory Alternatives 3-1 Arsenic in Drinking Water Rule EA 
Non-carcinogens: MCLGs for non-carcinogens are based on Reference Doses (RfDs) and their 

Drinking Water Equivalent Levels (DWELs). 

The Reference Dose (RfD, formerly the Acceptable Daily Intake, or ADI), estimates the daily amount 

of chemical a person, including sensitive humans, can ingest over a lifetime with little risk of causing 

adverse health effects. RfDs are usually expressed in milligrams of chemical per kilogram of body 

weight per day (mg/kg/day). Data from chronic (usually two years) or sub-chronic (usually 90 days) 

studies of humans or animals provide estimates of the No- or- Lowest-Observed-Adverse-Effect Level 

(NOAEL or LOAEL). The NOAEL (or LOAEL) is divided by a total uncertainty factor (UF) of 1 to 

10,000 to obtain the RfD. In the final National Primary Drinking Water Regulations published on 

January 30, 1991 (56 FR 3532), EPA applies a UF of 1, 3, or 10 when a NOAEL from a human 

study is used to account for intraspecies variation and an uncertainty factor of 100 to a human LOAEL 

to account for lack of a NOAEL and for species variation. The UFs provide a margin for variations in 

species responses, data gaps, and less than lifetime exposures. Scientific judgement is used to select the 

total UF for specific risk assessments. 

The DWEL is calculated by multiplying the RfD by an assumed adult body weight of 70 kg 

(approximately 154 pounds) and dividing by an average adult water consumption of 2 liters per day 

(L/day). The DWEL assumes that 100 percent of the exposure comes from drinking water. The 

MCLG is then determined by multiplying the DWEL by the percentage of the total daily exposure 

contributed by drinking water (relative source contribution), set at 20 percent by default when adequate 

data are not available, but set between 20 and 80 percent when adequate data are available to estimate 

exposure. Based on the 1993 RfD (1993 Draft Criteria) for arsenic (0.3 μg/kg/day), the calculated 

DWEL would be 0.3 μg/kg/day times 70 kg divided by 2 L/day, or 10 μg/L. Due to the three-fold 

uncertainties noted in the Integrated Risk Information System (IRIS) file on arsenic, the DWEL could 

be 3 to 30 μg/L. It should be noted that the toxicological studies used to determine the effect level and 

the derivation of the RfD are different from the analysis conducted in 1975. Additionally, the current 

policy on relative source contribution, including the default policy, are also different from those used in 

1975. 

3.1.3 Determining an MCL 

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

Contaminant Level (MCL). The MCL is the maximum permissible level of a contaminant in water that 

is delivered to any user of a public water system. EPA must set the MCL as close to the MCLG as 

feasible. The SDWA defines feasible as the level that may be achieved with the use of the best 

available technology, treatment techniques, and other means that EPA finds are available (after 

examination for efficacy under field conditions), taking cost to large systems into consideration. 

After determining an MCL based on affordable technology for large systems, EPA must complete an 

economic analysis to determine whether the benefits of the standard justify the costs. If not, EPA may 

adjust the MCL to a level that “maximizes health risk reduction benefits at a cost that is justified by the 

benefits” (§1412(b)(6)). 

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

The 1996 SDWA identifies two classes of technologies for small systems: compliance and variance 

technologies. A compliance technology is one that achieves compliance with the MCL or treatment 

technique requirement. The 1996 Amendments require EPA to list affordable compliance technologies 

for three categories of small systems: those serving 25 to 500 people, those serving 501 to 3,300 

people, and those serving 3,301 to 10,000 people. If EPA cannot identify an affordable compliance 

technology for a particular system category, it must then identify a variance technology instead. The 

variance technology must achieve the maximum reduction that is affordable, considering the size of the 

system and the quality of the source water, and must be protective of public health. If EPA lists such a 

variance technology, small systems will be eligible to apply to the States for a small system variance. 

States are authorized to grant variances from standards for systems serving up to 3,300 people if the 

system cannot afford to comply with a rule and the system installs the EPA-approved variance 

technology. States can grant variances to systems serving 3,301 to 10,000 people with EPA approval. 

3.1.5 Analytical Methods 

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

at the MCL. The SDWA directs EPA to set an MCL “if in the judgement of the Administrator, it is 

economically and technologically feasible to ascertain the level of such contaminant in water in public 

water systems (§1401 (1)(c)(ii)).” EPA must therefore evaluate the available analytical methods to 

determine a Practical Quantitation Limit (PQL), which is the minimum reliable quantification level that 

most laboratories can be expected to meet during day-to-day operations. EPA has approved several 

analytical methods to support compliance monitoring of arsenic at the current MCL (40 CFR 141.23). 

In 1994, EPA evaluated available data and determined the PQL for arsenic to be 2.0 μg/L at an 

acceptance limit of ± 40 percent. In its July 1995 report, EPA’s Science Advisory Board 

recommended that EPA set the PQL for arsenic using acceptance limits similar to those applied for 

other inorganics. Based on more recent information and these recommendations from the SAB, in 

1999 EPA derived a PQL of 3 μg/L using an acceptance limit of ± 30 percent for arsenic (EPA, 

1999a). 

Available data estimate that over 75 percent of EPA Regional and State laboratories and at least 62 

percent of non-EPA laboratories are capable of achieving acceptable results at 3 μg/L within a 30 

percent acceptance window. While the PQL represents a stringent target for laboratory performance, 

the Agency believes that most laboratories, using appropriate quality assurance and quality control 

procedures, have the capacity to achieve this level on a routine basis. 

3.2 Regulatory Alternatives Considered and Final Rule 

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

Agency. 

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

The Agency investigated applying the monitoring and treatment requirements of the proposed rule to 

both community water systems (CWSs) and non-transient non-community (NTNC) water systems. A 

CWS is defined as a system that provides piped water to at least 25 people or with at least 15 service 

connections year-round. An NTNC system is a public water system that is not defined as a CWS and 

that regularly serves at least 25 of the same people for at least six months of the year. After considering 

the costs and benefits of the proposed rule with regard to both CWSs and NTNC systems, EPA 

proposes to require both CWSs and NTNC water systems to comply with all facets of the proposed 

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

this EA. Transient non-community systems, which provide potable water to continuously changing 

populations, will not be subject to the proposed rule. The rule applies to CWSs and NTNC systems 

that produce water primarily from either ground or surface water sources. 

3.2.2 Maximum Contaminant Level 

EPA considered a range of MCLs in developing the proposed Arsenic Rule, including MCLs of 3, 5, 

10, and 20 μg/L. EPA evaluated the following five factors to determine the proposed MCL: 

• The analytical capability and laboratory capacity; 

• The likelihood of water systems choosing various compliance technologies for several 

sizes of systems based on source water properties; 

• The national occurrence of arsenic in water supplies; 

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

the MCLs considered; and 

• The effects on sensitive subpopulations. 

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

MCLG as is feasible. However, the Agency is using its discretionary authority in §1412(b)(6)(A) to 

set MCL at a less stringent level. The statute requires that the alternative, less stringent level be one that 

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

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

3.2.3 Monitoring 

The current monitoring requirements for arsenic (40 CFR 141.23(l)) apply to community water systems 

only. EPA is changing the current monitoring requirements to require systems to monitor for arsenic in 

accordance with the provisions of 40 CFR 141.23(c), the Standard Monitoring Framework (SMF). 

This change will make the arsenic requirements consistent with the requirements for inorganic 

contaminants (IOCs) regulated under the Phase II/V regulations. The revised rule would make the 

following changes to the monitoring requirements for arsenic: 

Chapter 3, Consideration of Regulatory Alternatives 3-4 Arsenic in Drinking Water Rule EA 
• NTNC systems will be required to monitor for arsenic for the first time. 

• MCL exceedances will trigger quarterly monitoring, as opposed to the current 

requirements for three additional samples within one month when exceedances occur. 

• The State will determine when the system is “reliably and consistently” below the MCL, 

after a minimum number of samples following an exceedance (two samples for ground 

water systems and four for surface water systems), and can return to the default 

sampling frequency. (Currently, the system automatically returns to the default 

monitoring frequency when a minimum of two consecutive samples are below the 

MCL.) 

• The State may grant a nine-year monitoring waiver to a system if it finds that arsenic 

detections are the result of natural occurrence and not of human activity. (Currently, no 

monitoring waivers are permitted.) 

3.2.4 Compliance Technologies and Variances 

EPA reviewed several technologies as best available technology (BAT) candidates for arsenic removal. 

Those technologies capable of removing arsenic from source water that fulfill the SDWA requirements 

for BAT determinations for arsenic are as follows: 

• Anion exchange; 

• Activated alumina (AA); 

• Reverse osmosis (RO); 

• Modified coagulation/filtration; 

• Modified lime softening; and 

• Oxidation/filtration (including greensand filtration).1 

EPA has further determined that these technologies are affordable for all system size categories and has 

therefore not identified a variance technology for any system size or source water combination at the 

proposed MCL. 

3.2.5 Monitoring Waivers 

Under the final Arsenic Rule (§141.23(c)(3)), States may grant a nine-year monitoring waiver from 

sampling requirements to water systems based on the analytical results from previous sampling and a 

vulnerability assessment or the assessment from an approved source water assessment program 

(provided that the assessments were designed to collect all of the necessary information needed to 

complete a vulnerability assessment for a waiver). States issuing waivers must consider the 

requirements in 40 CFR 141.23(c)(2)-(6). In order to qualify for a waiver, there must be three 

previous samples from a sampling point (annual for surface water and three rounds for ground water) 

with analytical results reported below the MCL. Grandfathered data collected after January 1, 1990, 

1

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

Chapter 3, Consideration of Regulatory Alternatives 3-5 Arsenic in Drinking Water Rule EA 
that are consistent with the analytical methodology and detection limits of the proposed regulation may 

be used for issuing sampling point waivers. 

The current arsenic regulations §141.23(l)-(q) do not permit the use of monitoring waivers. However, 

a State could now use the analytical results from the three previous compliance periods (1993 to 1995, 

1996 to 1998, and 1999 to 2001) to issue ground water sampling point waivers. Surface water 

systems must collect annual samples; thus, a State could use the previous three years’ sampling data 

(1999, 2000, and 2001) to issue sampling point waivers. One sample must be collected during the 

nine-year compliance cycle in which the waiver is effective, and the waiver must be renewed every nine 

years. Vulnerability assessments must be based on a determination that the water system is not 

susceptible to contamination and arsenic is not a result of human activity (i.e., it is naturally occurring). 

Not all States have required systems to report arsenic results below 50 μg/L. In this case, the States 

would not have adequate data to grant waivers until enough data are available to make the 

determinations. 

EPA believes that some States may have been regulating arsenic under the proposed standardized 

inorganic framework. If so, those States will have to ensure that existing monitoring waivers have been 

granted using data reported below the new MCL. Otherwise, States will have to notify the systems of 

the new lower reporting requirements that need to be met to qualify for a waiver for the MCL. 

3.2.6 Implementation 

The following schedule is proposed for implementation of the rule: 

• States must submit applications for primacy revisions within two years after 

promulgation, unless a State requests and is granted a two-year extension. 

• The rule will be effective five years after promulgation. 

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

Chapter 3, Consideration of Regulatory Alternatives 3-6 Arsenic in Drinking Water Rule EA 
Chapter 4: Baseline Analysis

4.1 Introduction 

This chapter presents baseline information to describe the operational and financial characteristics of 

water systems in the absence of the Revised Arsenic Rule. The baseline information provides a basis 

for EPA’s analysis of the costs, benefits and economic impacts of the regulatory options considered. 

This chapter includes data on the number of water systems regulated, the population affected, current 

treatment practices, raw and treated water quality, and socio-economic impacts. 

The baseline is assumed to be current conditions, as reflected by the most recent available data. In 

some cases, changes in the industry have occurred or will occur that are not reflected in the available 

data; for example, changes in operations induced by a regulation that will take effect prior to the 

Arsenic Rule. 

4.2 Industry Profile 

4.2.1 Definitions 

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

(CWSs) and non-community water systems (NCWSs). NCWSs are further classified as either 

transient or non-transient. The rule will affect all public water systems except for transient noncommunity water systems. The following definitions will help the reader follow the discussion in this 

chapter: 

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

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

privately-owned. 

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

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

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

serve at least 15 service connections used by travelers or intermittent users for at least 

60 days each year, or serve an average of 25 individuals for at least 60 days a year. 

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

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

hospitals). 

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

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

Public water systems are also classified by their water source: surface water (e.g., drawn from lakes, 

streams, rivers, etc.) or ground water (e.g., drawn from wells or springs). 

Chapter 4, Baseline Analysis 4-1 Arsenic in Drinking Water Rule EA 
4.2.2 Sources of Industry Profile Data 

EPA uses two primary sources of data to characterize the universe of water systems: the Safe Drinking 

Water Information System (SDWIS) and the Community Water System Survey (CWSS). 

EPA’s SDWIS contains data on all PWSs as reported by States and EPA Regions. This source 

reflects both mandatory and optional reporting components. States must report the system location, 

system type (CWS, NTNC, or TNC), primary raw water source (ground water or surface water), and 

violations. Optional reporting fields include type of treatment and ownership type. Because providing 

some data is discretionary, EPA does not have complete data on every system for these parameters. 

This is particularly common for non-community systems. 

The second source of information, the CWSS, is a detailed survey of surface and ground water CWSs 

conducted by EPA in 1995 and published in 1997 (EPA, 1997b). The CWSS is stratified to represent 

the complete population of CWSs across the U.S. The CWSS includes information such as revenues, 

expenses, treatment practices, source water protection measures, and plant capacity. There is no 

equivalent survey such as the CWSS to define treatment practices in non-community water systems. 

4.2.3 Number and Size of Public Water Systems 

Exhibit 4-1 shows the number of systems in the U.S. by source water (ground or surface) and system 

size (measured by the number of people served), based on the December 1998 SDWIS data.1 In the 

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

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

Some ground water sources (e.g., riverbank infiltration/galleries) are directly impacted by adjacent 

source water bodies and are separately identified in SDWIS as ground water under the direct influence 

of surface water (GWUDI). Since these systems would have similar occurrence as surface water 

systems, GWUDI systems are considered surface water systems in this analysis. SDWIS also provides 

system data by ownership. As previously described, PWSs include both publicly-owned and privatelyowned systems. This detail is also provided in Exhibit 4-1, where any system referred to as “other” in 

the SDWIS database has been presented as a privately-owned system. 

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

percent serve fewer than 500 people; and 34 percent serve fewer than 100 people. 

1

The cost and benefit analyses are conducted using the 1997 SDWIS freeze. The 1998 SDWIS freeze is 

presented here, as it was the most recent representation of the regulated entities. 

Chapter 4, Baseline Analysis 4-2 Arsenic in Drinking Water Rule EA 
Exhibit 4-1

Total Number of Systems by Size, Type, and Ownership

SOURCE <100 101­

500 

501­

1,000 

1,001­ 3,301­

3,300 10,000 

10,001­

50,000 

50,001­ 100,001­

100,000 1,000,000 

TOTAL 

CWS 

Ground Water 

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

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

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

Surface Water 

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

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

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

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

NTNCWS 

Ground Water 

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

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

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

Surface Water 

Public 58 63 19 24 6 3 1 1 175 

Private 213 232 87 56 17 1 0 0 606 

Total 271 295 106 80 23 4 1 1 781 

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

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

Chapter 4, Baseline Analysis 4-3 Arsenic in Drinking Water Rule EA 
4.2.4 System Size and Population Served 

All PWSs are potentially subject to the requirements of the Arsenic Rule, with the exception of TNCs. 

The majority of systems to be regulated are community water systems, which also serve, on average, 

more people than NTNCs. Exhibit 4-2 provides information on the average populations served by 

CWSs for each system size category, and the total population served by NTNCs. 

Exhibit 4-2

Total Population Served of Water Systems by

Source Water, System Type, and Service Population Category

Service 

Population 

Category 

Community Non-Transient 

Non-Community Ground Water Surface Water 

< 100 859,777 61,450 -

101–500 3,741,017 570,448 -

501–1,000 3,457,163 921,449 -

1,001–3,300 10,631,422 4,797,855 -

3,301–10,000 14,095,015 10,995,980 -

10,001–50,000 25,004,779 36,819,575 -

50,001–100,000 8,609,455 20,500,370 -

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

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

Total 83,829,678 168,700,896 31,968,181 

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

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

system. The NTNC populations were taken from the 1998 SDWIS freeze. The NTNCs are much 

smaller than CWSs on average and vary substantially in their characteristics. Schools account for more 

than half of the affected NTNCs (8,414 of 20,255), followed by office parks (950), daycare centers 

(809), food manufacturing facilities (768), and non-food related retailers (695). Prisons serve the 

largest number of people on average (1,820). All other system types serve an average of 500 people 

or fewer. 

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

Characteristics of NTNC Systems Affected by the Revised Rule

Service Area Type 

SYSTEM CHARACTERISTICS 

Number of 

Systems 

Average 

Population 

Served Per 

System 

Design Flow 

(mgd) 

Average Daily 

Flow (mgd) 

Daycare Centers 

Highway Rest Areas 

Hotels/Motels 

Interstate Carriers 

Medical Facilities 

Mobile Home Parks 

Restaurants 

Schools 

Service Stations 

Summer Camps 

Water Wholesalers 

Agricultural Products/Services 

Airparks 

Construction 

Churches 

Campgrounds/RV Parks 

Fire Departments 

Federal Parks 

Forest Service 

Golf and Country Clubs 

Landfills 

Mining 

Amusement Parks 

Military Bases 

Migrant Labor Camps 

Misc. Recreation Services 

Nursing Homes 

Office Parks 

Prisons 

Retailers (Non-food related) 

Retailers (Food related) 

State Parks 

Non-Water Utilities 

Manufacturing: Food 

Manufacturing: Non-Food 

809 

15 

351 

287 

367 

104 

418 

8414 

53 

46 

266 

368 

101 

99 

230 

123 

41 

20 

107 

116 

78 

119 

159 

95 

33 

259 

130 

950 

67 

695 

142 

83 

497 

768 

3845 

76 

407 

133 

123 

393 

185 

370 

358 

230 

146 

173 

76 

60 

53 

50 

160 

98 

39 

42 

101 

44 

113 

418 

395 

63 

87 

107 

136 

1820 

174 

322 

165 

170 

372 

168 

0.0051 

0.0089 

0.0189 

0.0029 

0.1166 

0.0262 

0.0039 

0.0333 

0.0051 

0.0218 

0.1637 

0.0199 

0.0026 

0.0009 

0.0053 

0.0214 

0.0186 

0.0065 

0.0014 

0.0118 

0.0053 

0.0123 

0.0171 

0.0695 

0.0102 

0.0025 

0.0411 

0.0077 

0.5322 

0.0038 

0.0058 

0.0048 

0.0133 

0.0454 

0.0157 

0.0011 

0.0020 

0.0045 

0.0006 

0.0339 

0.0065 

0.0008 

0.0085 

0.0011 

0.0053 

0.0494 

0.0048 

0.0005 

0.0002 

0.0011 

0.0052 

0.0045 

0.0014 

0.0002 

0.0027 

0.0011 

0.0028 

0.0041 

0.0192 

0.0023 

0.0005 

0.0107 

0.0017 

0.1820 

0.0008 

0.0012 

0.0010 

0.0031 

0.0120 

0.0038 

TOTAL 20,255 

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

December 1998 SDWIS freeze. 

Chapter 4, Baseline Analysis 4-5 Arsenic in Drinking Water Rule EA 
4.2.5 Number of Entry Points 

If water systems employ more than one water supply source, they may have more than one treatment 

facility. For estimation purposes this analysis assumes a treatment facility at every entry point to the 

distribution system. As a result, the total number of entry points is an important determinant of 

compliance costs. Exhibit 4-4 presents the distribution of entry points per ground water CWS by 

system service population category. 

Exhibit 4-4

Average Number of Entry Points per Ground Water System

Upper Bound 

95% 

Confidence 

Service Population Category 

< 100 

101­

500 

501­

1,000 

1,001 ­

3,300 

3,301 ­

10,000 

10,001 ­

50,000 

50,001 ­

100,000 > 100,000 

Percentile 

Mean 1 1 2 2 2 4 6 9 

5th 1 1 1 1 1 1 1 1 

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

95th 2 3 3 5 5 12 22 28 

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

In this respect, surface water systems are unlike ground water systems in that little variation in the 

number of entry points was reported among surface water systems. Even for large population 

categories, the majority of surface water systems reported only one or two entry points. (EPA, 1999a). 

This finding was supported by data recently collected from the Information Collection Request for large 

surface water systems. Appendix C describes how the entry point distribution was incorporated into 

the cost analysis for this rule. 

4.2.6 Number of Households 

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

household. This measure is often used instead of per capita cost because it is a more accurate 

representation of how customers are billed: per household, not per person. 

Exhibit 4-5 shows that household consumption does not vary substantially across size category or 

ownership type. The mean water consumption ranges from 81,000 gallons per year to 127,000 gallons 

per year per household. 

Chapter 4, Baseline Analysis 4-6 Arsenic in Drinking Water Rule EA 
Exhibit 4-5

Water Consumption per Residential

Connection

Population System 

Type 

Mean Water 

Consumption* 

(kgal/yr) 

< 100 Public 81 

Private 92 

101-500 Public 93 

Private 110 

501-1,000 Public 97 

Private 88 

1,001-3,300 Public 82 

Private 102 

3,301-10,000 Public 87 

Private 124 

10,001-50,000 Public 108 

Private 110 

50,001-100,000 Public 122 

Private 96 

100,001-1,000,000 Public 127 

Private 114 

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

Summary Result Tables and Methodology 

Report, Table 1-14; 

4.2.7 Production Profile 

Exhibit 4-6 shows the average design capacity (in thousands of gallons) of CWS plants by source, 

ownership, and system size categories. Design capacity is the maximum amount of water a plant can 

deliver. Exhibit 4-7 provides the daily production of CWSs (in thousands of gallons) for the same 

categories. Daily production is the average amount of water a plant delivers in a day. 

Chapter 4, Baseline Analysis 4-7 Arsenic in Drinking Water Rule EA 
Exhibit 4-6

Design Capacity of CWS Plants

by Source, Ownership, and System Size

(Thousands of Gallons)

Primary Source/ Service Population Category 

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

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

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

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

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

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

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

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

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

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

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

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

GW under 

influence 

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

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

Private - 21.53 81.77 227.4 618.5 1,802 - - - -

Purchased-Public - - 30.21 97.1 209.3 461 2,319 - - -

Purchased-Private - 2.54 29.83 94.3 - 905 - - - -

Source: EPA, Geometries and Characteristics of Public Water Systems, Table B1.5.3. 
Exhibit 4-7

Daily Production of CWS Plants

by Source, Ownership, and System Size

(Thousands of Gallons)

Primary Source/ Service Population Category 

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

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

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

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

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

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

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

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

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

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

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

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

GW under 

influence 

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

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

Private - 4.85 21.30 67.70 207 686 - - - -

Purchased-Public - - 25.90 80.90 171 370 1,789 - - -

Purchased-Private - 2.36 25.9 79.4 - 719 - - - -

Source: EPA, Geometries and Characteristics of Public Water Systems, Table B1.5.1. 
4.2.8 Treatment Profile 

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

concentrations in delivered water. The current treatment in-place will determine the likely remedy that 

systems will select in order to come into compliance with the new MCL. 

Exhibit 4-8

Percentage of CWSs with Various Treatments in Place

Primary Service Population Category 

Source/ Type 

of Treatments < 100 101-500 

501­

1,000 

1,001­

3,300 

3,301­

10,000 

10,001­

50,000 

50,001­

100,000 

100,001­

1,000,000 > 1,000,000 

Ground Water Systems 

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

Reverse 

Osmosis 

0.0% 1.2% 0.0% 0.9% 1.2% 0.7% 1.2% 0.0% -

Coagulation/ 

Flocc. 

1.5% 5.4% 4.2% 3.4% 8.1% 15.1% 24.2% 25.2% -

Lime/Soda Ash 

Softening 

2.1% 3.7% 4.1% 5.2% 7.0% 12.2% 17.4% 32.4% -

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

Surface Water Systems 

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

Reverse 

Osmosis 

0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% -

Coagulation/ 

Flocc. 

27.5% 52.6% 70.2% 78.5% 95.4% 94.5% 93.7% 99.5% -

Lime/Soda Ash 

Softening 

3.9% 8.1% 20.5% 17.5% 10.8% 6.9% 5.7% 5.1% -

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

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

4.3 Occurrences of Arsenic 

EPA has relied on a variety of data sources to evaluate the occurrence of arsenic in community water 

systems and non-transient non-community systems. This information supports EPA’s assessment of 

baseline conditions, including (1) the number of systems expected to exceed various MCL options, and 

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

In 1992, EPA conducted an analysis of the number of systems that would be impacted by various 

arsenic MCL options, ranging from 0.5 μg/L to > 50 μg/L. These projections were based on the 

following national surveys: 

Chapter 4, Baseline Analysis 4-10 Arsenic in Drinking Water Rule EA 
• 1984-1986 National Inorganic and Radionuclide Survey (NIRS) for ground water 

systems; 

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

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

• 1978 Community Water Supply Survey for surface water systems. 

These data sources have several limitations. First, the surveys used for surface water systems were 

conducted primarily before 1980. It is likely that arsenic occurrence has changed in the past two 

decades due to changes in raw water sources or the addition of filtration treatment to comply with the 

Surface Water Treatment Rule (SWTR). In addition, many of the survey responses had relatively high 

minimum reporting limits (5 μg/L). Therefore, it is statistically difficult to extrapolate low-level arsenic 

occurrence. 

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

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

those based on the other sources listed above. 

EPA used statistical techniques to assess: 

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

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

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

Exhibit 4-9 shows the percentage of systems with an arsenic occurrence in excess of ten different 

concentration levels, ranging from 2 μg/L to 50 μg/L. Less than one percent of ground water and 

surface water systems have a concentration level of arsenic greater than 50 μg/L. In contrast, 27 

percent of ground water systems and 10 percent of surface water systems have an arsenic 

concentration greater than 2 μg/L. Exhibit 4-10 provides a summary of the number of systems 

expected to exceed various MCLs. 

Exhibit 4-9

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

Source % of systems greater than (mmg/L) 

2 3 5 10 15 20 25 30 40 50 

GW 27.3 19.9 12.1 5.3 3.1 2.0 1.4 1.1 0.64 0.43 

SW 9.8 5.6 3.0 0.80 0.46 0.32 0.24 0.19 0.13 0.10 

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

Chapter 4, Baseline Analysis 4-11 Arsenic in Drinking Water Rule EA 
Exhibit 4-10

Statistical Estimates of Numbers of Systems with 

Average Finished Arsenic Concentrations in Various Ranges

System size (population served) 

Number of systems with mean arsenic concentration (μg/L) in the 

range of: 

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

Ground Water CWS 

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

% of systems 7.8% 6.8% 3.3% 2.0% 

Surface Water CWS 

Number of Systems 270 239 51 34 

% of systems 2.5% 2.2% 0.5% 0.3% 

Ground Water NTNCWS 

Number of Systems 1,677 1,995 635 405 

% of systems 8.6% 10.3% 3.3% 2.1% 

Surface Water NTNCWS 

Number of Systems 20 17 4 2 

% of systems 2.5% 2.2% 0.5% 0.3% 

Chapter 4, Baseline Analysis 4-12 Arsenic in Drinking Water Rule EA 
Chapter 5: Benefits 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. 

Chapter 5, Benefits Analysis 5-1 Arsenic in Drinking Water Rule EA 
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 μg/L; NRC, 1999). 

New data provide additional health effects information on both carcinogenic and noncarcinogenic 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 μg/L) and soil (5.3-11.2 mg/kg) in the Tsai et al. (1999) population study had 

very high arsenic content. 

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

cancer, laryngeal cancer, and cerebrovascular disease” as possibly “related to chronic arsenic 

exposure via drinking water.” 

Chapter 5, Benefits Analysis 5-2 Arsenic in Drinking Water Rule EA 
 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. 

Chapter 5, Benefits Analysis 5-3 Arsenic in Drinking Water Rule EA
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.

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

Chapter 5, Benefits Analysis 5-5 Arsenic in Drinking Water Rule EA 
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 
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 preexisting 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 noncancer 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. 

Chapter 5, Benefits Analysis 5-7 Arsenic in Drinking Water Rule EA 
Exhibit 5-2

Components of the Bladder Cancer Risk Assessment

HAZARD EXPOSURE RISK 

IDENTIFICATION ASSESSMENT CHARACTERIZATION 

Toxicity 

(dose-response) × Exposure = Health Effects 

o

Population Size and Distribution 

o

Ingestion/Dose Human Intake Factors 

Concentration of Cont

o

aminant in

Finished Drinking Water Supply and

Available for Human Consumption

Concentration of Contam

o

inant 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 μg/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 μg/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. 

Chapter 5, Benefits Analysis 5-8 Arsenic in Drinking Water Rule EA 
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 

CSFII 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 CSFII, 

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. 

Chapter 5, Benefits Analysis 5-9 Arsenic in Drinking Water Rule EA 
Exhibit 5-3

Life-Long Relative Exposure Factors

Community Water Consumption Data Total Water Consumption Data 

Male Mean = 0.60 

s.d. = 0.61 

Mean = 0.73 

s.d. = 0.62 

Female Mean = 0.64 

s.d. = 0.6 

Mean = 0.79 

s.d. = 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 μg/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, agespecific 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. 

Chapter 5, Benefits Analysis 5-10 Arsenic in Drinking Water Rule EA 
EPA believes that the models in Morales et al. (2000) without a comparison population are more 

reliable than those with a comparison population. Models with no comparison population 

estimate the arsenic dose-response curve only from the study population. Models with a 

comparison population include mortality data from a similar population (in this case either all of 

Taiwan or part of southwestern Taiwan), whose 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. 

Chapter 5, Benefits Analysis 5-11 Arsenic in Drinking Water Rule EA 
These simulations combined the distributions of relative exposure factors (REFs), occurrence at 

or above 3 μg/L, and risks of bladder and lung cancer taken from the Morales et al. (2000) 

article. The simulations resulted in upper bound estimates of the actual risks faced by 

populations exposed to arsenic concentrations at or above 3 μg/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 μg, versus about 10 μg 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 μg/kg/day basis, was compared to the total amount of arsenic consumed in 

drinking water, drinking water used for cooking, and in food, on a μg/kg/day basis. 

Other factors contributing to lower bound uncertainty include the possibility of a sub-linear doseresponse curve below the point of departure. The NRC noted “Of the several modes of action 

that are considered most plausible, a sub-linear dose response curve in the low-dose 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 sublinear 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. 

Chapter 5, Benefits Analysis 5-12 Arsenic in Drinking Water Rule EA 
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. 

Chapter 5, Benefits Analysis 5-13 Arsenic in Drinking Water Rule EA 
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 

(μg/L) 

Mean Exposed 

Population Risk 

90th Percentile Exposed 

Population Risk 

3 .93 -1.25 x 10-4 1.95 - 2.42 x 10-4 

5 1.63 - 2.02 x 10-4 3.47 - 3.9 x 10-4 

10 2.41 - 2.99 x 10-4 5.23 - 6.09 x 10-4 

20 3.07 - 3.85 x 10-4 6.58 - 8.37 x 10-4 

1

Actual 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. 2

The 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 

(μg/L) 

Mean Exposed 

Population Risk 

90th Percentile Exposed 

Population Risk 

3 .11 -.13 x 10-4 .22 - .26 x 10-4 

5 .27 - .32 x 10-4 .55 - .62 x 10-4 

10 .63 - .76 x 10-4 1.32 - 1.54 x 10-4 

20 1.1 - 1.35 x 10-4 2.47 - 2.89 x 10-4 

1

Actual 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. 2

The 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 

(μg/L) 

Mean Exposed 

Population Risk 

90th Percentile Exposed 

Population Risk 

3 .11 -1.25 x 10-4 .22 - 2.42 x 10-4 

5 .27 - 2.02 x 10-4 .55 - 3.9 x 10-4 

10 .63 - 2.99 x 10-4 1.32 - 6.09 x 10-4 

20 1.1 - 3.85 x 10-4 2.47 - 8.37 x 10-4 

1

Actual 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 5-14 Arsenic in Drinking Water Rule EA 
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. 

1

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. 

Chapter 5, Benefits Analysis 5-15 Arsenic in Drinking Water Rule EA 
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 

# cycles 

per yr 

worker/ 

pop/day 

worker 

fraction 

daily 

worker 

days/yr 

worker 

exposure 

years 

customer 

fraction 

daily 

days of 

use/yr 

customer 

exposure 

years 

Water 

wholesalers 

1.00 0.000 - - - 0.25 270 70 

Nursing homes 1.00 0.230 0.50 250 40 1.00 365 10 

Churches 1.00 0.010 0.50 250 40 0.50 52 70 

Golf/country clubs 4.50 0.110 0.50 250 40 0.50 52 70 

Food retailers 2.00 0.070 0.50 250 40 0.25 185 70 

Non-food retailers 4.50 0.090 0.50 250 40 0.25 52 70 

Restaurants 2.00 0.070 0.50 250 40 0.25 185 70 

2

For 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. 

Chapter 5, Benefits Analysis 5-16 Arsenic in Drinking Water Rule EA 
Exhibit 5-5

Exposure Factors Used in the NTNC Risk Assessment (continued)

NTNCWS 

# 

cycles 

per yr 

worker/ 

pop/day 

worker 

fraction 

daily 

worker 

days/yr 

worker 

exposure 

years 

customer 

fraction 

daily 

days of 

use/yr 

customer 

exposure 

years 

Hotels/motels 86.00 0.270 0.50 250 40 1.00 3.4 40 

Prisons/jails 1.33 0.100 0.50 250 40 1.00 270 3 

Service stations 7.00 0.060 0.50 250 40 0.25 52 54 

Agricultural 

products/services 7.00 0.125 0.50 250 40 0.25 52 50 

Daycare centers 1.00 0.145 0.50 250 10 0.50 250 5 

Schools 1.00 0.073 0.50 200 40 0.50 200 12 

State parks 26.00 0.016 0.50 250 40 0.50 14 70 

Medical facilities 16.40 0.022 0.50 250 40 1.00 6.7 10.3 

Campgrounds/RV 22.50 0.041 0.50 180 40 1.00 5 50 

Federal parks 26.00 0.016 0.50 250 40 0.50 14 70 

Highway rest areas 50.70 0.010 0.50 250 40 0.50 7.2 70 

Misc. recreation 

service 

26.00 0.016 0.50 250 40 1.00 14 70 

Forest Service 26.00 0.016 1.00 250 40 1.00 14 50 

Interstate carriers 93.00 0.304 0.50 250 40 0.50 2 70 

Amusement parks 90.00 0.180 0.50 250 10 0.50 1 70 

Summer camps 8.50 0.100 1.00 180 10 1.00 7 10 

Airports 36.50 0.308 0.50 250 40 0.25 10 70 

Military bases 1.000 0.50 250 40 

Non-water utilities 1.000 0.50 250 40 

Office parks 1.000 0.50 250 40 

Manufacturing: Food 1.000 0.50 250 40 

Manufacturing: 

Non-food 

1.000 0.50 250 40 

Landfills 1.000 1.00 250 40 

Fire departments 1.000 1.00 250 40 

Construction 1.000 1.00 250 40 

Mining 1.000 1.00 250 40 

Migrant labor camps 1.000 1.00 250 40 

Once the population adjustment factors were derived, it was possible to determine the actual 

population served by NTNC water systems. Exhibit 5-6 provides a breakout of these figures by 

type of establishment. 

Chapter 5, Benefits Analysis 5-17 Arsenic in Drinking Water Rule EA 
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 9.7 Medical 

Facilities 

8 Interstate Carriers 7.1 Campgrounds 1.3 

Manufacturing 2.7 Restaurants 0.9 State Parks 8.6 Misc. 

Recreation 

1.8 

Airports 26.1 Non-food Retail 1.6 Amusement Parks 17.7 Other 3.5 

Office Parks 0.6 Hotels/Motels 9.2 Highway Rest Area 1.0 

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. 

3

For 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. 

Chapter 5, Benefits Analysis 5-18 Arsenic in Drinking Water Rule EA 
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 10-4 lifetime risk). 

Exhibit 5-7

Mean Cancer Risks (Bladder and Lung combined),

Exposed Population, and Annual Cancer Benefits in NTNCs

Arsenic 

Level 

Mean Exposed Population 

Risk (10-4) 

Total Bladder and Lung 

Cancer Cases Avoided 

per Year 

(μg/L) lower 

bound 

upper 

bound 

lower 

bound 

upper 

bound 

3 0.0000657 0.000952 0.6 2.25 

5 0.000162 0.00157 0.53 1.78 

10 0.000374 0.00243 0.36 1.13 

20 0.00064 0.00322 0.16 0.53 

baseline 0.000853 0.00391 0.65 2.98 

Exhibit 5-8

Sensitive Group Evaluation of Lifetime Combined Cancer Risks

Group Mean Risk 90th Percentile Risk 

Forest Service, Construction and Mining Workers 0.2 - 1.2 x 10-4 0.4 - 2.3 x 10-4 

School Children 0.2 - 1.4 x 10-5 0.5 - 2.8 x 10-5 

Day Care Children 1.1 - 7.3 x 10-6 0.25 - 1.5 x 10-5 

However, there is considerable uncertainty about these 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. 

Chapter 5, Benefits Analysis 5-19 Arsenic in Drinking Water Rule EA 
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 ageadjusted 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. 

Chapter 5, Benefits Analysis 5-20 Arsenic in Drinking Water Rule EA 
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 μg/L, 25.6 to 55.7 at an MCL of 5 μg/L, 18.7 to 31.0 at an MCL of 10 μg/L, and 9.9 to 10.6 at 

an MCL of 20 μg/L. The number of lung cancer cases avoided range from 28.6 to 61.5 at an 

MCL of 3 μg/L, 25.6 to 44.5 at an MCL of 5 μg/L, 18.7 to 24.8 at an MCL of 10 μg/L, and 8.5 to 

9.9 at an MCL of 20 μg/L. The number of combined bladder and lung cancer cases avoided range 

from 57.2 to 138.3 at an MCL of 3 μg/L, 51.1 to 100.2 at an MCL of 5 μg/L, 37.4 to 55.7 at an 

MCL of 10 μg/L, and 19.0 to 19.8 at an MCL of 20 μg/L. 

The 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 

(μg/L) 

Reduced 

Mortality Cases* 

Reduced Morbidity 

Cases* 

Total Cancer Cases 

Avoided* 

3 7.4 - 20.0 21.2 - 56.9 28.6 -76.8 

5 6.6 - 14.5 18.9 - 41.2 25.6 - 55.7 

10 4.9 - 8.0 13.8 - 22.7 18.7 - 31.0 

20 2.6- 2.8 7.3 - 7.8 9.9 - 10.6 

* 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. 

Chapter 5, Benefits Analysis 5-21 Arsenic in Drinking Water Rule EA 
Exhibit 5-9 (b)

Annual Lung Cancer Cases Avoided 

from Reducing Arsenic in CWSs and NTNCs

Arsenic Level 

(μg/L) 

Reduced 

Mortality Cases* 

Reduced Morbidity 

Cases* 

Total Cancer Cases 

Avoided* 

3 25.2 - 54.1 3.4 - 7.4 28.6 - 61.5 

5 22.5 - 39.2 3.1 - 5.3 25.6 - 44.5 

10 16.4 - 21.8 2.2 - 3.0 18.7 - 24.8 

20 7.4 - 8.7** 1.0 - 1.2** 8.5 - 9.9** 

* 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 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional 

reduction from the higher level risk base case. Thus, the number of estimated cases avoided is higher at 20 μg/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 

(μg/L) 

Reduced 

Mortality Cases* 

Reduced Morbidity 

Cases* 

Total Cancer Cases 

Avoided* 

3 32.6 - 74.1 24.6 - 64.2 57.2 - 138.3 

5 29.1 - 53.7 22.0 - 46.5 51.1 - 100.2 

10 21.3 - 29.8 16.1 - 25.9 37.4 - 55.7 

20 10.2 - 11.3** 8.5 - 8.8 19.0 - 19.8** 

* 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 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional 

reduction from the higher level risk base case. Thus the number of estimated cases avoided is higher at 20 μg/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). 

Chapter 5, Benefits Analysis 5-22 Arsenic in Drinking Water Rule EA 
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 wagerisk 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. 

Chapter 5, Benefits Analysis 5-23 Arsenic in Drinking Water Rule EA 
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 

et al. [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. 

Chapter 5, Benefits Analysis 5-24 Arsenic in Drinking Water Rule EA 
Exhibit 5-10

Lifetime Avoided Medical Costs for Survivors

(preliminary estimates1

)

Type of 

Cancer 

Date Data 

Collected Number of Cases Studied 

Estimated 

Mortality Rate 

Mean Value per 

Non-fatal Case 

(Discount Rate)

 1 

Bladder 1974-1981 5% of 1974 

Medicare patients 

(sample from national statistics) 

26% 

(after 20 years) 

$178,405 (3%) 

$147,775 (7%) 

(for typical individual 

diagnosed at age 70) 

Source: U.S. Environmental Protection Agency, Cost 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 μg/L, $52.0 to $113.3 million at an MCL of 5 μg/L, $38.0 to $63.0 million at an MCL of 10 

μg/L, and $20.1 to $21.5 million at an MCL of 20 μg/L. Total annual health benefits from 

avoided cases of lung cancer range from $155.6 to $334.5 million at an MCL of 3 μg/L, $139.1 

to $242.3 million at an MCL of 5 μg/L, $101.6 to $134.7 million at an MCL of 10 μg/L, and 

$46.1 to $53.8 million at an MCL of 20 μg/L. In addition, other potential non-quantifiable health 

benefits are summarized in Exhibit 5-11. 

Chapter 5, Benefits Analysis 5-25 Arsenic in Drinking Water Rule EA 
Exhibit 5-11

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and

Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs

($ millions)

Arsenic 

Level 

(μg/L) 

Total Annual 

Cost (7%) 

Annual Bladder 

Cancer Health 

Benefits1,2 

Annual Lung 

Cancer Health 

Benefits1,2 

Total Annual 

Health Benefits1,2 

Potential Non-Quantifiable 

Health Benefits 

3 $792.1 $58.2 - $156.4 $155.6 - $334.5 $213.8 - $490.9 

• Skin Cancer 

• Kidney Cancer 

• Cancer of the Nasal 

Passages 

• Liver Cancer 

• Prostate Cancer 

• Cardiovascular Effects 

• Pulmonary Effects 

• Immunological Effects 

• Neurological Effects 

• Endocrine Effects 

• Reproductive and 

Developmental Effects 

5 $471.7 $52.0 - $113.3 $139.1 - $242.3 $191.1 - $355.6 

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

20 $76.5 $20.1 - $21.5 $46.1 - $53.8 $66.2 - $75.33 

1

 May 1999 dollars. 2

 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c). 3

 For 20 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional

reduction from the higher level risk base case. Thus, the number of estimated cases avoided and estimated

benefits are higher at 20 μg/L using the 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. 

Chapter 5, Benefits Analysis 5-26 Arsenic in Drinking Water Rule EA 
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 the primary 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 the primary 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). 

Chapter 5, Benefits Analysis 5-27 Arsenic in Drinking Water Rule EA 
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 

Chapter 5, Benefits Analysis 5-28 Arsenic in Drinking Water Rule EA 
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 fiveyear 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. 

Chapter 5, Benefits Analysis 5-29 Arsenic in Drinking Water Rule EA 
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) 6.1 6.1 6.1 

Adjusted for Income Growth1

 elasticity = 0.22 

 elasticity = 1.0 

6.22 6.22 6.22

6.77 6.77 6.77 

Adjusted for Income Growth1

 and Discounting elasticity = 0.22 

 elasticity = 1.0 

5.37 4.63 3.44

5.84 5.04 3.75 

Adjusted for Income Growth1

, Discounting, and 7% Increase for 

Voluntariness and Controllability elasticity = 0.22 

 elasticity = 1.0 

5.74 4.95 3.69

6.25 5.39 4.01 

Break-Even for Other Characteristics (as a percentage of the primary VSL estimate) 

 elasticity = 0.22 

 elasticity = 1.0 

6 % 19 % 40 %

-2 % 12 % 34 % 

7 % Discount Rate 

Primary Analysis (No VSL Adjustment) 6.1 6.1 6.1 

Adjusted for Income Growth1

 elasticity = 0.22 

 elasticity = 1.0 

6.22 6.22 6.22

6.77 6.77 6.77 

Adjusted for Income Growth1

 and Discounting elasticity = 0.22 

 elasticity = 1.0 

4.44 3.16 1.61

4.83 3.44 1.75 

Adjusted for Income Growth1

, Discounting, and 7% Increase for 

Voluntariness and Controllability elasticity = 0.22 

 elasticity = 1.0 

4.75 3.38 1.72

5.17 3.68 1.87 

Break-Even for Other Characteristics (as a percentage of the primary VSL estimate) 

 elasticity = 0.22 

 elasticity = 1.0 

22 % 45 % 72 %

15 % 40 % 69 % 

1. This adjustment reflects the change in WTP based on real income growth from 1990 to 1999. 

Chapter 5, Benefits Analysis 5-30 Arsenic in Drinking Water Rule EA 
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 nonquantifiable 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 (Fg/L) 3 5 10 20 

5 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 176-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

175-398 156-288 114-160 55-61

190-433 170-314 124-174 60-66 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

187-425 167-308 122-171 59-65

204-463 182-336 133-186 64-71 

10 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 176-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

151-343 135-249 99-138 47-52

164-373 147-271 107-150 51-57 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

161-367 144-266 105-148 50-56

176-399 157-289 115-161 55-61 

20 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 176-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

112-255 100-185 73-103 35-39

122-278 109-201 80-112 38-42 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

120-273 107-198 79-110 38-42

131-297 117-215 85-119 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 (Fg/L) 3 5 10 20 

5 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 178-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

145-329 129-238 95-132 45-50

157-358 141-259 103-144 50-55 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

155-352 138-255 102-142 49-54

168-383 150-278 110-154 53-58 

10 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 178-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

103-234 92-170 67-94 32-36

112-255 100-185 73-103 35-39 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

110-251 98-182 72-101 35-38

120-273 107-198 78-110 38-42 

20 Year Latency Period Assumption 

Primary Analysis (No VSL Adjustment) 199-452 178-328 130-182 62-69 

Adjusted for Income Growth2 E = 0.22 

E = 1.0 

203-461 181-334 133-186 63-70

221-502 197-364 144-202 69-77 

Adjusted for Income Growth2 and Discounting E = 0.22 

E = 1.0 

53-119 47-86 34-48 16-18

57-130 51-94 37-52 18-20 

Adjusted for Income Growth2, Discounting, and 7% 

Increase for Voluntariness and Controllability E = 0.22 

E = 1.0 

56-127 50-92 37-51 18-20

61-139 54-100 40-56 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 

μg/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 μg/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 (μg/L) down to 1 μg/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 

Waste Disposal Technology 

Corrosion 

Control 

PreOxidatio

POTW 

Non- Hazardous 

Landfill 

Mechanical 

De-Watering 

NonMechanical 

De-Watering 

1 Modify Lime Softening 7 2 Modify Coagulation/Filtration 7 3 Anion Exchange (<20 mg/L SO4) 7 7 4 Anion Exchange (20-50 mg/L SO4) 7 7 5 Coagulation Assisted Microfiltration 7 7 7 6 Coagulation Assisted Microfiltration 7 7 7 7 Oxidation Filtration (Greensand) 7* 7 

8 Activated Alumina (pH 7 - pH 8) 7** 7 9 Activated Alumina (pH 8 - pH 8.3) 7** 7 

10 Activated Alumina (23,100 BV) with pH adjustment (pH 6) 7** 7 7 11 Activated Alumina (15,400 BV) with pH adjustment (pH 6) 7** 7 7 12 POU Activated Alumina 7 13 POU Reverse Osmosis 7 

o pre-oxidation incorporated into treatment trains based on a separate decision tree 

* POTWfor backwash stream ** non-hazardous landfill (for spent 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 10μg/L, assuming either an influent arsenic concentration of 11μg/L (low range 

estimates shown in Exhibit 6-2(a)) or an influent arsenic concentration of 50μg/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 μg/L and MCL of 10 μ

Size Category Treatment Train No. 1 2 3 4 5 

< 100 

Treatment Capital Costs $ 8,999 $ 7,483 $ 21,957 $ 22,724 $ 127,885 

Treatment O&M Costs $ 484 $ 260 $ 5,104 $ 8,604 $ 22,361 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 29,900 

Waste Disposal O&M Costs $ - $ - $ 381 $ 387 $ 6,946 

Annual Costs (7% ) $ 1,333 $ 966 $ 7,930 $ 11,510 $ 44,200 

101-500 

Treatment Capital Costs $ 13,688 $ 8,966 $ 21,957 $ 37,150 $ 265,526 

Treatment O&M Costs $ 1,416 $ 482 $ 5,104 $ 9,470 $ 23,619 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 43,354 

Waste Disposal O&M Costs $ - $ - $ 412 $ 455 $ 12,863 

Annual Costs (7% ) $ 2,708 $ 1,328 $ 7,962 $ 13,804 $ 65,638 

501-1,000 

Treatment Capital Costs $ 14,756 $ 9,316 $ 21,957 $ 40,669 $ 295,452 

Treatment O&M Costs $ 1,766 $ 565 $ 5,104 $ 9,791 $ 24,090 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 46,424 

Waste Disposal O&M Costs $ - $ - $ 424 $ 480 $ 14,929 

Annual Costs (7% ) $ 3,159 $ 1,444 $ 7,974 $ 14,483 $ 71,290 

1,001-3,300 

Treatment Capital Costs $ 24,087 $ 12,655 $ 38,991 $ 120,712 $ 526,687 

Treatment O&M Costs $ 4,760 $ 1,266 $ 5,104 $ 12,431 $ 28,088 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 73,454 

Waste Disposal O&M Costs $ - $ - $ 525 $ 696 $ 29,102 

Annual Costs (7% ) $ 7,034 $ 2,460 $ 9,682 $ 24,894 $ 113,839 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. 
Exhibit 6-2a (continued)

System Compliance Technology Costs Assuming Influent Concentration of 11 μg/L and MCL of 10 μg

Size Category Treatment Train No. 1 2 3 4 5 

3,301-10,000 

Treatment Capital Costs $ 64,447 $ 40,103 $ 38,991 $ 211,802 $ 1,069,210 Treatment O&M Costs $ 14,961 $ 4,833 $ 5,104 $ 20,403 $ 38,522 Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 121,208 Waste Disposal O&M Costs $ - $ - $ 869 $ 1,434 $ 32,307 Annual Costs (7% ) $ 21,045 $ 8,618 $ 10,027 $ 42,203 $ 183,196 

10,001-50,000 

Treatment Capital Costs $ 247,207 $ 168,801 $ 38,991 $ 362,184 $ 1,793,771 Treatment O&M Costs $ 35,250 $ 17,001 $ 5,104 $ 31,688 $ 55,413 Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 209,000 Waste Disposal O&M Costs $ - $ - $ 1,593 $ 2,984 $ 45,793 Annual Costs (7% ) $ 58,584 $ 32,934 $ 10,750 $ 69,233 $ 290,253 

50,001-100,000 

Treatment Capital Costs $ 455,707 $ 315,625 $ 38,991 $ 529,645 $ 2,368,818 Treatment O&M Costs $ 61,149 $ 32,533 $ 5,104 $ 54,032 $ 59,325 Waste Disposal Capital Costs $ - $ - $ 5,085 $ 5,085 $ 309,158 Waste Disposal O&M Costs $ - $ - $ 2,516 $ 4,962 $ 52,569 Annual Costs (7% ) $ 104,165 $ 62,326 $ 11,780 $ 109,470 $ 364,675 

100,001-1,000,000 

Treatment Capital Costs $ 1,462,373 $ 918,353 $ 38,991 $ 1,873,015 $ 6,887,505 Treatment O&M Costs $ 309,897 $ 177,044 $ 5,104 $ 168,459 $ 96,658 Waste Disposal Capital Costs $ - $ - $ 5,085 $ 5,085 $ 954,312 Waste Disposal O&M Costs $ - $ - $ 12,132 $ 25,570 $ 178,509 Annual Costs (7% ) $ 447,935 $ 263,730 $ 21,396 $ 371,308 $ 1,015,379 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. 
Exhibit 6-2a (continued)

System Compliance Technology Costs Assuming Influent Concentration of 11 μg/L and MCL of 1

Size Category Treatment Train No. 7 8 9 10 11 

< 100 

Treatment Capital Costs $ 15,023 $ 13,629 $ 13,629 $ 45,787 $ 45,787 $ Treatment O&M Costs $ 7,711 $ 4,414 $ 6,944 $ 6,050 $ 6,643 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 446 $ 12 $ 22 $ 5 $ 8 $ Annual Costs (7% ) $ 9,949 $ 5,712 $ 8,253 $ 10,377 $ 10,972 $ 

101-500 

Treatment Capital Costs $ 63,059 $ 29,131 $ 29,131 $ 62,507 $ 62,507 $ Treatment O&M Costs $ 8,540 $ 6,065 $ 10,087 $ 7,494 $ 8,437 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 571 $ 78 $ 150 $ 34 $ 51 $ Annual Costs (7% ) $ 15,437 $ 8,892 $ 12,986 $ 13,428 $ 14,388 $ 

501-1,000 

Treatment Capital Costs $ 73,464 $ 32,912 $ 32,912 $ 66,586 $ 66,586 $ Treatment O&M Costs $ 8,904 $ 6,684 $ 11,265 $ 8,036 $ 9,110 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 618 $ 103 $ 197 $ 44 $ 67 $ Annual Costs (7% ) $ 16,830 $ 9,893 $ 14,569 $ 14,365 $ 15,462 $ 

1,001-3,300 

Treatment Capital Costs $ 170,709 $ 60,846 $ 60,846 $ 97,616 $ 97,616 $ Treatment O&M Costs $ 12,006 $ 11,930 $ 21,255 $ 12,627 $ 14,814 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 1,016 $ 313 $ 602 $ 135 $ 203 $ Annual Costs (7% ) $ 29,509 $ 17,986 $ 27,600 $ 21,977 $ 24,231 $ 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. In Treatment Trains 8 -11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and the
Exhibit 6-2a (continued)

System Compliance Technology Costs Assuming Influent Concentration of 11 μg/L and MCL of 10 

Size Category Treatment Train No. 7 8 9 10 11 

3,301-10,000 

Treatment Capital Costs $ 421,562 $ 159,129 $ 159,129 $ 205,374 $ 205,374 $ Treatment O&M Costs $ 22,659 $ 29,916 $ 55,506 $ 28,369 $ 34,369 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 2,381 $ 1,033 $ 1,988 $ 447 $ 671 $ Annual Costs (7% ) $ 65,205 $ 45,970 $ 72,514 $ 48,202 $ 54,426 $ 

10,001-50,000 

Treatment Capital Costs $ 787,837 $ 324,276 $ 324,276 $ 386,442 $ 386,442 $ Treatment O&M Costs $ 45,012 $ 67,654 $ 127,369 $ 61,397 $ 75,399 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 5,951 $ 2,545 $ 4,895 $ 1,102 $ 1,653 $ Annual Costs (7% ) $ 125,809 $ 100,809 $ 162,873 $ 98,976 $ 113,530 $ 

50,001-100,000 

Treatment Capital Costs $ 1,168,062 $ 512,683 $ 512,683 $ 593,012 $ 593,012 $ Treatment O&M Costs $ 73,549 $ 122,590 $ 231,264 $ 109,500 $ 134,983 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 9,606 $ 4,476 $ 8,608 $ 1,938 $ 2,906 $ Annual Costs (7% ) $ 193,892 $ 175,459 $ 288,265 $ 167,413 $ 193,866 $ 

100,001-1,000,000 

Treatment Capital Costs $ 4,098,917 $ 2,257,773 $ 2,257,773 $ 2,506,335 $ 2,506,335 $ Treatment O&M Costs $ 370,791 $ 629,270 $ 1,199,321 $ 548,870 $ 682,540 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 47,683 $ 24,581 $ 47,274 $ 10,642 $ 15,962 $ Annual Costs (7% ) $ 805,863 $ 866,968 $ 1,459,713 $ 796,092 $ 935,082 $ 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. In Treatment Trains 8 -11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and th
Exhibit 6-2b

System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL of 10 μ

Size Category Treatment Train No. 1 2 3 4 5 

< 100 

Treatment Capital Costs $ 8,999 $ 7,483 $ 26,970 $ 29,332 $ 193,923 

Treatment O&M Costs $ 484 $ 260 $ 5,365 $ 8,924 $ 21,251 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 36,236 

Waste Disposal O&M Costs $ - $ - $ 392 $ 412 $ 9,187 

Annual Costs (7% ) $ 1,333 $ 966 $ 8,676 $ 12,478 $ 52,164 

101-500 

Treatment Capital Costs $ 13,688 $ 8,966 $ 43,632 $ 117,795 $ 508,282 

Treatment O&M Costs $ 1,416 $ 482 $ 5,365 $ 11,527 $ 26,696 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 71,219 

Waste Disposal O&M Costs $ - $ - $ 490 $ 621 $ 24,844 

Annual Costs (7% ) $ 2,708 $ 1,328 $ 10,346 $ 23,640 $ 106,241 

501-1,000 

Treatment Capital Costs $ 14,756 $ 9,316 $ 43,632 $ 126,653 $ 564,187 

Treatment O&M Costs $ 1,766 $ 565 $ 5,365 $ 12,469 $ 28,148 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 77,743 

Waste Disposal O&M Costs $ - $ - $ 526 $ 699 $ 29,269 

Annual Costs (7% ) $ 3,159 $ 1,444 $ 10,383 $ 25,497 $ 118,010 

1,001-3,300 

Treatment Capital Costs $ 24,087 $ 12,655 $ 43,632 $ 218,240 $ 1,103,278 

Treatment O&M Costs $ 4,760 $ 1,266 $ 5,365 $ 19,699 $ 37,737 

Waste Disposal Capital Costs $ - $ - $ 3,955 $ 3,955 $ 124,926 

Waste Disposal O&M Costs $ - $ - $ 836 $ 1,362 $ 40,238 

Annual Costs (7% ) $ 7,034 $ 2,460 $ 10,692 $ 42,035 $ 193,909 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. 
Exhibit 6-2b (continued)

System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL of 10 μg

Size Category Treatment Train No. 1 2 3 4 5 

3,301-10,000 

Treatment Capital Costs $ 64,447 $ 40,103 $ 43,632 $ 490,994 $ 2,255,079 Treatment O&M Costs $ 14,961 $ 4,833 $ 5,365 $ 45,678 $ 56,923 Waste Disposal Capital Costs $ - $ - $ 5,085 $ 5,085 $ 285,807 Waste Disposal O&M Costs $ - $ - $ 1,897 $ 3,637 $ 48,028 Annual Costs (7% ) $ 21,045 $ 8,618 $ 11,860 $ 96,141 $ 344,793 

10,001-50,000 

Treatment Capital Costs $ 247,207 $ 168,801 $ 43,632 $ 923,917 $ 3,571,834 Treatment O&M Costs $ 35,250 $ 17,001 $ 5,365 $ 75,188 $ 65,568 Waste Disposal Capital Costs $ - $ - $ 5,085 $ 5,085 $ 513,238 Waste Disposal O&M Costs $ - $ - $ 4,124 $ 8,409 $ 72,683 Annual Costs (7% ) $ 58,584 $ 32,934 $ 14,087 $ 171,288 $ 523,853 

50,001-100,000 

Treatment Capital Costs $ 455,707 $ 315,625 $ 43,632 $ 1,378,931 $ 5,074,043 Treatment O&M Costs $ 61,149 $ 32,533 $ 5,365 $ 110,599 $ 76,604 Waste Disposal Capital Costs $ - $ - $ 5,085 $ 5,085 $ 717,287 Waste Disposal O&M Costs $ - $ - $ 6,967 $ 14,501 $ 110,698 Annual Costs (7% ) $ 104,165 $ 62,326 $ 16,930 $ 255,741 $ 733,963 

100,001-1,000,000 

Treatment Capital Costs $ 1,462,373 $ 918,353 $ 43,632 $ 3,623,972 $ 18,245,297 Treatment O&M Costs $ 309,897 $ 177,044 $ 5,365 $ 328,792 $ 203,223 Waste Disposal Capital Costs $ - $ - $ 5,571 $ 5,571 $ 2,275,373 Waste Disposal O&M Costs $ - $ - $ 36,579 $ 77,955 $ 477,280 Annual Costs (7% ) $ 447,935 $ 263,730 $ 46,588 $ 749,350 $ 2,617,509 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. 
Exhibit 6-2b (continued)

System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL of 10 

Size Category Treatment Train No. 7 8 9 10 11 

< 100 

Treatment Capital Costs $ 24,983 $ 20,733 $ 20,733 $ 53,449 $ 53,449 $ Treatment O&M Costs $ 7,747 $ 5,021 $ 8,098 $ 6,580 $ 7,302 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 464 $ 36 $ 69 $ 16 $ 23 $ Annual Costs (7% ) $ 10,943 $ 7,014 $ 10,125 $ 11,641 $ 12,371 $ 

101-500 

Treatment Capital Costs $ 104,869 $ 57,733 $ 57,733 $ 94,204 $ 94,204 $ Treatment O&M Costs $ 9,495 $ 10,104 $ 17,779 $ 11,029 $ 12,829 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 694 $ 240 $ 461 $ 104 $ 156 $ Annual Costs (7% ) $ 20,462 $ 15,794 $ 23,690 $ 20,025 $ 21,877 $ 

501-1,000 

Treatment Capital Costs $ 104,869 $ 57,733 $ 57,733 $ 94,204 $ 94,204 $ Treatment O&M Costs $ 9,495 $ 10,104 $ 17,779 $ 11,029 $ 12,829 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 694 $ 240 $ 461 $ 104 $ 156 $ Annual Costs (7% ) $ 20,462 $ 15,794 $ 23,690 $ 20,025 $ 21,877 $ 

1,001-3,300 

Treatment Capital Costs $ 283,894 $ 166,171 $ 166,171 $ 213,095 $ 213,095 $ Treatment O&M Costs $ 15,866 $ 28,169 $ 52,180 $ 26,840 $ 32,470 $ Waste Disposal Capital Costs $ 3,955 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 1,511 $ 963 $ 1,853 $ 417 $ 626 $ Annual Costs (7% ) $ 44,547 $ 44,818 $ 69,718 $ 47,372 $ 53,211 $ 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. In Treatment Trains 8 -11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and th
Exhibit 6-2b (continued)

System Compliance Technology Costs Assuming Influent Concentration of 50 μg/L and MCL of 10 

Size Category Treatment Train No. 7 8 9 10 11 

3,301-10,000 

Treatment Capital Costs $ 701,070 $ 468,896 $ 468,896 $ 545,004 $ 545,004 $ Treatment O&M Costs $ 35,414 $ 90,018 $ 169,031 $ 81,254 $ 99,783 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ 

Waste Disposal O&M Costs $ 4,721 $ 3,183 $ 6,122 $ 1,378 $ 2,067 $ 

Annual Costs (7% ) $ 106,791 $ 137,461 $ 219,413 $ 134,077 $ 153,294 $ 

10,001-50,000 

Treatment Capital Costs $ 1,310,195 $ 977,574 $ 977,574 $ 1,102,719 $ 1,102,719 $ Treatment O&M Costs $ 76,430 $ 207,386 $ 393,274 $ 183,031 $ 226,620 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 9,975 $ 7,840 $ 15,079 $ 3,394 $ 5,091 $ Annual Costs (7% ) $ 210,559 $ 307,502 $ 500,628 $ 290,514 $ 335,800 $ 

50,001-100,000 

Treatment Capital Costs $ 1,942,521 $ 1,557,893 $ 1,557,893 $ 1,738,984 $ 1,738,984 $ Treatment O&M Costs $ 128,791 $ 357,213 $ 679,531 $ 312,954 $ 388,534 $ Waste Disposal Capital Costs $ 5,085 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 16,683 $ 13,785 $ 26,512 $ 5,968 $ 8,952 $ Annual Costs (7% ) $ 329,314 $ 518,052 $ 853,098 $ 483,070 $ 561,634 $ 

100,001-1,000,000 

Treatment Capital Costs $ 6,816,616 $ 6,933,014 $ 6,933,014 $ 7,632,284 $ 7,632,284 $ Treatment O&M Costs $ 674,190 $ 1,917,857 $ 3,661,282 $ 1,666,275 $ 2,075,085 $ Waste Disposal Capital Costs $ 5,598 $ - $ - $ - $ - $ Waste Disposal O&M Costs $ 86,549 $ 75,712 $ 145,611 $ 32,778 $ 49,166 $ Annual Costs (7% ) $ 1,404,708 $ 2,647,996 $ 4,461,320 $ 2,419,486 $ 2,844,684 $ 

NOTE: Average costs were calculated assuming a publicly-owned groundwater system with a single contaminated entry population and the average number of entry points per system in the service size category, for the treatment train technolExhibit 6-1. In Treatment Trains 8 -11, waste disposal O&M costs include only non-hazardous landfill tipping fees, and th
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 nineyear 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 < 10,000 people > 10,000 people 

State Activity Hours Rate Hours Rate 

Review a waiver 

application 

8 $41.47 8 $41.47 

Record monitoring of a 

sample result 

1 $41.47 1 $41.47 

Issue a single violation letter 4 $41.47 4 $41.47 

Review a single permit 16 $41.47 32 $41.47 

<3,000 people >3,300 people 

System Activity Hours Rate Hours Rate 

Apply for a waiver 16 $15.03 16 $29.03 

Take a sample 1 $15.03 1 $29.03 

Report a sample 1 $15.03 1 $29.03 

Prepare and Send Public 

Notification 

8 $15.03 8 $29.03 

Source: Information Collection Request for the Public Water System Supervision Program. 

*Estimates are provided in May 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) Estimated Cost 

One Time Start-up Activities 

Regulation Adoption and Program Development 0.2 $12,900 

System Training and Technical Assistance (CWS) 0.5 $32,240 

System Training and Technical Assistance (NTNC) 0.5 $32,240 

Staff Training (CWS) 0.12 $7,740 

National Total* 73.92 $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 < 10,000 people > 10,000 people 

One Time Start-up Activity Hours Rate Hours Rate 

Reading and Understanding 

Rule 

8 $15.03 8 $29.03 

Operator Training 16 $15.03 32 $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 μg/L, the decision tree specifies the probability of different compliance choices for 

systems with different baseline influent concentrations (e.g., <10 μg/L, 10-20 μg/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 MonteCarlo 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. 

CWS Costs 

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 MonteCarlo 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 overdesign).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 

1

No blending is assumed for the POU technologies. 

Chapter 6, Cost Analysis 6-17 Arsenic in Drinking Water Rule EA 
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. 

2

The > 90 percent removal efficiency category is not relevant under the revised MCL of 10 μg/L. 

Chapter 6, Cost Analysis 6-18 Arsenic in Drinking Water Rule EA 
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)

bA 

2 # Average Flow 

Design Flow max 

aD # (Population)

bD 

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 
Exhibit 6-5

Flow Regression Parameters

by Water Source and System Ownership

Average Flow Design Flow 

a b a b 

Ground Water 

Public 0.08558 1.05840 0.54992 0.95538 

Private 0.06670 1.06280 0.41682 0.96078 

Public-Purch 0.04692 1.10190 0.31910 0.99460 

Private-Purch 0.05004 1.08340 0.32150 0.97940 

Surface Water 

Public 0.14004 0.99703 0.59028 0.94573 

Private 0.09036 1.03340 0.35674 0.96188 

Public-Purch 0.04692 1.11020 0.20920 1.04520 

Private-Purch 0.05004 1.08340 0.20580 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 μg/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 μg/L as presented in Exhibit 6-6. 

Chapter 6, Cost Analysis 6-20 Arsenic in Drinking Water Rule EA 
Exhibit 6-6

Arsenic Occurrence Distribution

(Log-Normal Regression Results)

3 5 10 20 

GW 19.7 12.0 5.3 2.0 

SW 5.6 3.0 1.12 0.37 

% of systems greater than (μg/L) Source 

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: 

( TreatmentTarget 1) # (% Site Flow) Frac SiteConcentration tion of flow treated 

% Removal Efficiency 

Chapter 6, Cost Analysis 6-21 Arsenic in Drinking Water Rule EA 
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 systemlevel 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 
Exhibit 6-7 

Summary of Recommended Cost of Capital Estimates 

(as of March 1998)

Ownership Type Size Category 

Estimated After-Tax 

Cost of Capital 

NON-SMALL 

Investor owned 10,001-50,000 5.26% 

>50,000 5.94% 

Publicly owned 10,001-50,000 5.26% 

>50,000 5.23% 

SMALL 

Private 1-500 4.17% 

501-10,000 4.17% 

Public 1-500 5.10% 

501-10,000 5.20% 

Source: Development of Cost of Capital Estimates for Public 

Water Systems (Draft Final Report). Prepared for U.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 noncommunity water supply treatment decisions are modeled similarly to those for community water 

supplies. The number of non-transient non-community water supplies is taken from EPA’s 

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 CWSSprovided 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 
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 μg/L. For this analysis, 100 μg/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 μg/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 
Exhibit 6-8

Non-Transient Non-Community System Characteristics and

Compliance Decision Tree 

Service Area Type 

SYSTEM CHARACTERISTICS DECISION TREE

Number of 

Systems 

Average 

Population 

Served Per 

System 

Design Flow 

(mgd) 

Average Daily 

Flow (mgd) 

Activated 

Alumina 

Point of 

Entry 

Centralized 

Activated 

Alumina 

Daycare Centers 

Highway Rest Areas 

Hotels/Motels 

Interstate Carriers 

Medical Facilities 

Mobile Home Parks 

Restaurants 

Schools 

Service Stations 

Summer Camps 

Water Wholesalers 

Agricultural Products/Services 

Airparks 

Construction 

Churches 

Campgrounds/RV Parks 

Fire Departments 

Federal Parks 

Forest Service 

Golf and Country Clubs 

Landfills 

Mining 

Amusement Parks 

Military Bases 

Migrant Labor Camps 

Misc. Recreation Services 

Nursing Homes 

Office Parks 

Prisons 

Retailers (Non-food related) 

Retailers (Food related) 

State Parks 

Non-Water Utilities 

Manufacturing: Food 

Manufacturing: Non-Food 

809 

15 

351 

287 

367 

104 

418 

8414 

53 

46 

266 

368 

101 

99 

230 

123 

41 

20 

107 

116 

78 

119 

159 

95 

33 

259 

130 

950 

67 

695 

142 

83 

497 

768 

3845 

76 

407 

133 

123 

393 

185 

370 

358 

230 

146 

173 

76 

60 

53 

50 

160 

98 

39 

42 

101 

44 

113 

418 

395 

63 

87 

107 

136 

1820 

174 

322 

165 

170 

372 

168 

0.0051 

0.0089 

0.0189 

0.0029 

0.1166 

0.0262 

0.0039 

0.0333 

0.0051 

0.0218 

0.1637 

0.0199 

0.0026 

0.0009 

0.0053 

0.0214 

0.0186 

0.0065 

0.0014 

0.0118 

0.0053 

0.0123 

0.0171 

0.0695 

0.0102 

0.0025 

0.0411 

0.0077 

0.5322 

0.0038 

0.0058 

0.0048 

0.0133 

0.0454 

0.0157 

0.0011 

0.0020 

0.0045 

0.0006 

0.0339 

0.0065 

0.0008 

0.0085 

0.0011 

0.0053 

0.0494 

0.0048 

0.0005 

0.0002 

0.0011 

0.0052 

0.0045 

0.0014 

0.0002 

0.0027 

0.0011 

0.0028 

0.0041 

0.0192 

0.0023 

0.0005 

0.0107 

0.0017 

0.1820 

0.0008 

0.0012 

0.0010 

0.0031 

0.0120 

0.0038 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

↵ 

TOTAL 20,255 

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

Chapter 6, Cost Analysis 6-25 Arsenic in Drinking Water Rule EA 
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 
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, 

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 

Population 

Served 

MCL (μg/L) 

3 5 10 20 

Phoenix, AZ 1,360,751 

Annual cost (3%) 

Annual cost (7%) 

Houston, TX 2,216,830 

$ 

$ 

11.6 

13.2 

$ 

$ 

5.5 $ 

6.3 $ 

2.2 

2.5 

$ 

$ 

0.0 

0.0 

Annual cost (3%) 

Annual cost (7%) 

Los Angeles, CA 

Annual cost (3%) 

Annual cost (7%) 

3,700,000 

$ 

$ 

$ 

$ 

15.0 

16.0 

1.8 

1.8 

$ 

$ 

$ 

$ 

2.7 $ 

2.9 $ 

1.8 $ 

1.8 $ 

0.9 

1.0 

-

-

$ 

$ 

$ 

$ 

0.5 

0.5 

-

-

* Exhibit updated on December 28, 2000 to reflect minor changes in cost estimates which have not 

been incorporated into subsequent exhibits. The impact is a $0.07 million overestimation 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 
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 μg/L MCL, $396.0 million at the 5 μg/L 

MCL, $171.4 million at the 10 μg/L MCL, and $62.4 million at the 20 μg/L MCL (at a three 

percent discount rate). State costs associated with CWS administration, at a three percent 

discount rate, are approximately $1.4 million at the 3 μg/L MCL, $1.1 million at the 5 μg/L 

MCL, $0.9 million at the 10 μg/L MCL, and $0.7 million at the 20 μg/L MCL. 

The cost to NTNCs ranges from $28 million at the 3 μg/L MCL, $16 million at the 5 μg/L MCL, 

$7.9 million at the 10 μg/L MCL, and $3.5 million at the 20 μg/L MCL (at a three percent 

discount rate). State costs associated with NTNC administration, at a three percent discount rate, 

are approximately $0.1 million for each MCL. 

Exhibit 6-10 

Annual National System and State Compliance Costs 

($ millions) 

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

CWS NTNC

MCL = 10 μg/L 

MCL =20 μg/L 

TOTAL 

MCL = 3 μg/L 

MCL =5 μg/L 

Chapter 6, Cost Analysis 6-28 Arsenic in Drinking Water Rule EA 
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 (μg/L) 

3 5 10 20 

3% Discount Rate 

<100 $ 19.8 $ 12.3 $ 5.5 $ 2.1 

101-500 $ 42.6 $ 25.7 $ 11.5 $ 4.3 

501-1,000 $ 25.5 $ 15.2 $ 6.7 $ 2.5 

1001-3300 $ 83.8 $ 50.5 $ 22.0 $ 8.1 

3,301-10,000 $ 95.1 $ 55.9 $ 24.3 $ 9.0 

10,001-50,000 $ 179.1 $ 108.7 $ 47.0 $ 16.7 

50,001-100,000 $ 66.0 $ 39.0 $ 16.7 $ 6.2 

100,001-1,000,000 $ 124.3 $ 75.2 $ 32.3 $ 11.3 

>1,000,000 $ 29.7 $ 11.8 $ 3.8 $ 0.6 

Total $ 665.9 $ 394.4 $ 169.6 $ 60.7 

7% Discount Rate 

<100 $ 21.3 $ 13.2 $ 5.9 $ 2.3 

101-500 $ 46.4 $ 28.0 $ 12.5 $ 4.6 

501-1,000 $ 28.9 $ 17.2 $ 7.6 $ 2.8 

1001-3300 $ 97.4 $ 58.8 $ 25.6 $ 9.4 

3,301-10,000 $ 109.2 $ 64.2 $ 27.9 $ 10.3 

10,001-50,000 $ 205.4 $ 124.7 $ 53.9 $ 19.2 

50,001-100,000 $ 75.0 $ 44.3 $ 19.0 $ 7.0 

100,001-1,000,000 $ 140.5 $ 85.0 $ 36.5 $ 12.7 

>1,000,000 $ 32.5 $ 13.0 $ 4.3 $ 0.6 

Total $ 756.5 $ 448.5 $ 193.0 $ 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 μg/L by System Service Type

(3% Discount Rate)

Service Area Type 

# of Systems 

Above the MCL 

Average 

Population 

Served Per 

System 

Average Annual 

System Cost 

Annual 

National Costs 

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 

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 

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 

$5,217 

$5,466 

$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 

$45,861 

$5,133 

$5,261 

$5,199 

$5,763 

$8,066 

$5,944 

$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 

$236,789 

$153,287 

$49,505 

$20,908 

$100,771 

$129,308 

$80,268 

$133,490 

$188,625 

$184,863 

$36,090 

$257,531 

$198,316 

$1,007,456 

$605,012 

$702,366 

$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 μg/L by System Service Type

(3% Discount Rate)

Service Area Type 

# of Systems 

Above the MCL 

Average 

Population 

Served Per 

System 

Average Annual 

System Cost 

Annual 

National Costs 

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 

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 

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 

$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 

$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 

$61,364 

$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 μg/L by System Service Type

(3% Discount Rate)

Service Area Type 

# of Systems 

Above the MCL 

Average 

Population 

Served Per 

System 

Average Annual 

System Cost 

Annual 

National Costs 

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 

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 

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 

$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 

$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 

$46,053 

$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 6, Cost Analysis 6-32 Arsenic in Drinking Water Rule EA 
Exhibit 6-15

Total Annual NTNC Treatment Costs at MCL 20 μg/L by System Service Type

(3% Discount Rate)

Service Area Type 

# of Systems 

Above the MCL 

Average 

Population 

Served Per 

System 

Average Annual 

System Cost 

Annual 

National Costs 

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 

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 

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 

$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 

$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 (μg/L) Option

<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 

3 94,484 368,092 360,709 1,002,937 1,619,822 3,228,544 1,453,603 3,014,841 11,143,032 

5 58,774 228,149 219,872 623,156 1,019,288 2,077,421 905,886 1,938,268 7,070,814 

10 26,369 104,373 101,866 288,986 475,599 997,880 469,157 936,602 3,400,833 

20 10,439 40,089 40,498 116,517 193,541 405,714 188,798 364,907 1,360,503 

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 μg/L ranges from less than $1 to approximately 

$327; the costs for the MCL of 3 μg/L range from less than $7 to $317; the costs for the MCL of 

5 μg/L, range from less than $3 to $318; and the costs for the MCL of 20 μg/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

MCL (μg/L) 

System Size 

3 5 10 20 

<100 $317.00 $318.26 $326.82 $351.15 

101-500 $166.91 $164.02 $162.50 $166.72 

501-1,000 $74.81 $73.11 $70.72 $68.24 

1,001-3,300 $63.76 $61.94 $58.24 $54.36 

3,301-10,000 $42.84 $40.18 $37.71 $34.63 

10,001-50,000 $38.40 $36.07 $32.37 $29.05 

50,001-100,000 $31.63 $29.45 $24.81 $22.63 

100,001-1,000,000 $25.29 $23.34 $20.52 $19.26 

>1,000,000 $7.41 $2.79 $0.86 $0.15 

All categories $41.34 $36.95 $31.85 $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 
Exhibit 6-18

Annual Treatment Costs Per Household Across CWSs

Expected to Treat and Serving < 10,000 People

MCL 3 μg/L

$0 $100 $200 $300 $400 $500 $600 

Maximum Annual Household Treatment Costs 

Exhibit 6-19

Annual Treatment Costs Per Household Across CWSs

Expected to Treat and Serving < 10,000 People

MCL 5 μg/L

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percentage of Households

0-100 

101-500 

501-1,000 

1,001-3,300 

3,301-10,000 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percentage of Households

0-100 

101-500 

501-1,000 

1,001-3,300 

3,301-10,000 

$0 $100 $200 $300 $400 $500 $600 

Maximum Annual Household Treatment Costs 

Chapter 6, Cost Analysis 6-36 Arsenic in Drinking Water Rule EA 
Exhibit 6-20

Annual Treatment Costs Per Household Across CWSs

Expected to Treat and Serving < 10,000 People

MCL 10 μg/L

$0 $100 $200 $300 $400 $500 $600 

Maximum Annual Household Treatment Costs 

Exhibit 6-21

Annual Treatment Costs Per Household Across CWSs

Expected to Treat and Serving < 10,000 People

MCL 20 μg/L

$0 $100 $200 $300 $400 $500 $600 

Maximum Annual Household Treatment Costs 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percentage of Households

0-100 

101-500 

501-1,000 

1,001-3,300 

3,301-10,000 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

Percentage of Households

0-100 

101-500 

501-1,000 

1,001-3,300 

3,301-10,000 

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 μg/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 

MCL of 10 μg/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 
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Exhibit 6-22

National Compliance Costs Uncertainty Analysis

Frequency Distribution (MCL 10 μg/L)

16.0% 

14.0% 

12.0% 

10.0% 

8.0% 

6.0% 

4.0% 

2.0% 

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S i m u l a t ed M E A N = $1 99, 166, 4 6 3 

S i m u l a t ed S T A N D A R D D E V I A T I O N = $19 , 362, 659

M EAN 

Frequency 

National Compliance Costs ($ Millions) 

Chapter 6, Cost Analysis 6-39 Arsenic in Drinking Water Rule EA 
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$150 $155 $160 $165 $170 $175 $180 $185 $190 

$195 $200 

$205 $210 $215 $220 $225 $230 $235 $240 $245 $250 $255 $260 $265 $270 $275 

Cumulative Probability

Exhibit 6-23

National Compliance Costs Uncertainty Analysis

Cumulative Distribution (MCL 10 μg/L)

100.00% 

90.00% 

80.00% 

70.00% 

60.00% 

50.00% 

40.00% 

30.00% 

20.00% 

10.00%

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Si m u l a t ed M EAN = $199, 166, 463 

Si m u l a t ed S T AN D A R D D E VI ATI O N = $1 9, 362, 659 

ME A N 

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 μg/L to 3 μg/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 costeffectiveness 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 μg/L) to $697.8 million (MCL=3 μg/L) 

annually based on a discount rate of three percent. Assuming a seven percent discount rate, the 

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 μg/L) to $213.8 million (MCL=3 

μg/L) annually, based on the lower bound estimates of cancer cases avoided. Under the upper 

bound scenario, the health benefits from avoided cancer increase from $75.3 million at an MCL 

of 20 μg/L to $490.9 million annually at an MCL of 3 μg/L. 

7.3 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 μg/L) to 1.0 (MCL=20 μg/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 μg/L and 20 μg/L. Of the MCL options examined, the net benefits and benefit/cost 

ratio are maximized at an MCL of 10 μg/L and a three percent discount rate. 

Exhibit 7-1 

Summary of Annual National Net Benefits and Benefit-Cost Ratios 

($ millions) 

MCL (μg/L) 3 5 10 20 

3% Discount Rate 

lower bound

Net Benefits $ (484.0) $ (223.7) $ (40.8) $ (0.6) 

Benefit/Cost Ratio 0.3 0.5 0.8 1.0 

upper bound

Net Benefits $ (206.8) $ (59.2) $ 17.3 $ 8.5 

Benefit/Cost Ratio 0.7 0.9 1.1 1.1 

7% Discount Rate 

lower bound

Net Benefits $ (578.3) $ (280.6) $ (66.0) $ (10.3) 

Benefit/Cost Ratio 0.3 0.4 0.7 0.9 

upper bound

Net Benefits $ (301.1) $ (116.1) $ (7.9) $ (1.2) 

Benefit/Cost Ratio 0.6 0.8 1.0 1.0 

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

for administration of water programs. 

Chapter 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 

$800.0 

$700.0 

$600.0 

$500.0 

$400.0 

$300.0 

$200.0 

$100.0 

$­

3 5 10 20 

 $792.1 $471.7 $205.6 $76.5 

Benefits (upper bound) $491.0 $355.6 $197.7 $75.3 

Benefits (lower bound) $213.8 $191.1 $139.6 $66.2 

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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 μg/L from the current 

MCL of 50 μg/L results in incremental costs of $76.5 million and incremental benefits of 

between $66.2 million and $75.3 million. A move from 20 μg/L to 10 μg/L results in 

incremental costs of $129.1 million and incremental benefits of between $73.4 million and 

$122.4 million. Moving beyond an MCL of 10 μg/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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Exhibit 7-3

Comparison of Incremental Costs and Benefits

(7% Discount Rate, in $ millions)

$ millions 

���� Costs

$350.0

$300.0

$250.0

$200.0

$150.0

$100.0

$50.0

$­

3 5 10 20 

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ts (upper bound) $135.4 $157.9 $122.4 $75.3 

ts (lower bound) $22.7 $51.5 $73.4 $66.2 

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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 μg/L, from $4.1 million to $8.1 million at an MCL of 5 μg/L, from 

$3.2 million to $4.8 million at an MCL of 10 μg/L, and from $3.4 million to $3.5 million at an 

MCL of 20 μg/L. At a seven percent discount rate, the cost per cancer case avoided ranges from 

$5.7 million to $13.8 million at an MCL of 3 μg/L, from $4.7 million to $9.2 million at an MCL 

of 5 μg/L, from $3.7 million to $5.5 million at an MCL of 10 μg/L, and from $3.9 million to $4.0 

million at an MCL of 20 μg/L. 

Chapter 7, Comparison of Costs and Benefits 7-4 Arsenic in Drinking Water Rule EA 
Exhibit 7-4

Cost per Cancer Case Avoided

($ millions)

Arsenic Level 

(μg/L) lower bound** upper bound** 

3% Discount Rate 

3 

5 

10 

20 

$ 12.2 $ 5.0

$ 8.1 $ 4.1

$ 4.8 $ 3.2

$ 3.5 $ 3.4

7% Discount Rate 

3 

5 

10 

20 

$ 13.8 $ 5.7

$ 9.2 $ 4.7

$ 5.5 $ 3.7

$ 4.0 $ 3.9

**Lower/upper bounds correspond to estimates of bladder cancer cases avoided. 

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 
Exhibit 7-5

Comparison of Annual Costs to Cases of Cancer per Year

(7% Discount Rate)

Annual Cost ($ millions) 

$900 

$800 

$700 

$600 

$500 

$400 

$300 

$200 

$100 

$­

3 μg/L

5 μg/L 

10 μg/L 

20 μg/L 

- 20 40 60 80 100 120 140 160 

Cancer Cases Avoided per Year 

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 μg/L to 5 μg/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 μg/L to a more stringent MCL of 3 μg/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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Incremental Cost per Incremental Cancer Case Avoided

(7% Discount Rate, in $ millions)

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MCL 5 ug/L $19.4 $6.0 

MCL 3 ug/L $52.5 $8.4 

Lower bound estimates of avoided cases Upper bound estimates of avoided cases 

7.4 Other Benefits 

Chapter 5 discusses a number of important non-monetized benefits of reducing arsenic exposure. 

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. 

Chapter 7, Comparison of Costs and Benefits 7-7 Arsenic in Drinking Water Rule EA 

5 μg/L 
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

($ millions)

Arsenic 

Level 

(μg/L) 

Total Annual 

Cost (7%) 

Annual Bladder 

Cancer Health 

Benefits1,2 

Annual Lung 

Cancer Health 

Benefits1,2 

Total Annual 

Health Benefits1,2 

Potential Non-Quantifiable 

Health Benefits 

3 $792.1 $58.2 - $156.4 $155.6 - $334.5 $213.8 - $490.9 

• Skin Cancer 

• Kidney Cancer 

• Cancer of the Nasal 

Passages 

• Liver Cancer 

• Prostate Cancer 

• Cardiovascular Effects 

• Pulmonary Effects 

• Immunological Effects 

• Neurological Effects 

• Endocrine Effects 

• Reproductive and 

Developmental Effects 

5 $471.7 $52.0 - $113.3 $139.1 - $242.3 $191.1 - $355.6 

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

20 $76.5 $20.1 - $21.5 $46.1 - $53.8 $66.2 - $75.33 

1

 May 1999 dollars. 2

 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c). 3

 For 20 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional

reduction from the higher level risk base case. Thus the number of estimated cases avoided and estimated

benefits are higher at 20 μg/L using the 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 7-8 Arsenic in Drinking Water Rule EA 
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125 135 145 155 165 175 185 195 205 215 225 235 245 255 265 275 

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 μg/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. Cumulative Probability

Exhibit 7-8

National Compliance Costs and Benefits Uncertainty Analysis

Cumulative Cost Distribution vs. Benefits Range (MCL 10 μg/L)

100.00% 

90.00% 

80.00% 

70.00% 

60.00% 

50.00% 

40.00% 

30.00% 

20.00% 

10.00% 

0.00% 

RANGE OF NATIONAL 

COSTS 

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Chapter 7, Comparison of Costs and Benefits 7-9 Arsenic in Drinking Water Rule EA 
Chapter 8: 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 (SDWA); 

• 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 (SDWA); 

• 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 
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 (SBA) 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 
 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 
For this rulemaking, the SBA 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 

1 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. 

4 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 
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 

System Size Category 

<100 101-500 501-1,000 1,001-3,300 3,301-10,000 

Publicly-Owned: 

CWS 

NCWS 

1,729 

1,783 

5,795 

3,171 

3,785 

1,182 

6,179 

361 

3,649 

29 

Privately-Owned: 

CWS 

NCWS 

13,640 

8,178 

11,266 

4,162 

2,124 

902 

1,955 

411 

654 

56 

Total Systems: 

CWS 

NCWS 

TOTAL 

15,369 

9,961 

25,330 

17,061 

7,333 

24,394 

5,909 

2,084 

7,993 

8,134 

772 

8,906 

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 

5 Id. 

Chapter 8, Economic Impact Analyses 8-5 Arsenic in Drinking Water Rule EA 
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. 

6

1992 Census of Governments, GC92 (4)-4: Finances of Municipal and Township Governments, U.S. Dept. of 

Commerce, Bureau of the Census. 

7

Drinking Water Baseline Handbook Second Edition, EPA Contract No. 68-C6-0039. Prepared by International 

Consultants, Inc. 

8

Methodology 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 
Exhibit 8-2

Annual Cost of Compliance Costs as a Percentage of Revenues

by Type of Small Entity

(PWSs that are Expected to Modify or Install Treatment at an MCL = 10 μg/L)

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 persystem 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 8-7 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 μg/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 μg/L 

15,000 

13,500 

12,000 

10,500 

9,000 

Number of Systems

7,500 

6,000 

4,500 

3,000 

1,500 

0 

Treating GW systems 855 940 310 421 215 

Not treating GW systems 13,422 14,118 4,379 5,293 2,244 

��� Treating SW systems 11 21 12 24 18 

��� Not treating SW systems 1,081 1,982 1,208 2,396 1,826 

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 μg/L. In Exhibit 8-2, the ratios 

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Chapter 8, Economic Impact Analyses 8-8 Arsenic in Drinking Water Rule EA 
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/SBREFA. 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 SBA. 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). 

Chapter 8, Economic Impact Analyses 8-9 Arsenic in Drinking Water Rule EA 
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. 

Chapter 8, Economic Impact Analyses 8-10 Arsenic in Drinking Water Rule EA 
Small Systems Variance Technologies and National Affordability Criteria 

The Panel recommended the following: include a discussion of the issues surrounding 

appropriate adjustment of its national affordability criteria to account for new 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. 

Chapter 8, Economic Impact Analyses 8-11 Arsenic in Drinking Water Rule EA 
Applicability of Proposal 

The Panel recommended that EPA carefully consider the appropriateness of 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)(1) 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. 

Chapter 8, Economic Impact Analyses 8-12 Arsenic in Drinking Water Rule EA 
(3) EPA must make a finding on a national level, that use of the variance 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 μg/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 μg/L. 

Chapter 8, Economic Impact Analyses 8-13 Arsenic in Drinking Water Rule EA 
Exhibit 8-4

Mean Annual Costs to Households Served by CWSs, by Size Category

MCL (μg/L) 

System Size 

3 5 10 20 

<100 $317.00 $318.26 $326.82 $351.15 

101-500 $166.91 $164.02 $162.50 $166.72 

501-1,000 $74.81 $73.11 $70.72 $68.24 

1,001-3,300 $63.76 $61.94 $58.24 $54.36 

3,301-10,000 $42.84 $40.18 $37.71 $34.63 

10,001-50,000 $38.40 $36.07 $32.37 $29.05 

50,001-100,000 $31.63 $29.45 $24.81 $22.63 

100,001-1,000,000 $25.29 $23.34 $20.52 $19.26 

>1,000,000 $7.41 $2.79 $0.86 $0.15 

All categories $41.34 $36.95 $31.85 $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 

Chapter 8, Economic Impact Analyses 8-14 Arsenic in Drinking Water Rule EA 
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 (III) 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, 

Chapter 8, Economic Impact Analyses 8-15 Arsenic in Drinking Water Rule EA 
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 Byproduct (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 (IESWTR) 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 DBP 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 

Chapter 8, Economic Impact Analyses 8-16 Arsenic in Drinking Water Rule EA 
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 II 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: 

Chapter 8, Economic Impact Analyses 8-17 Arsenic in Drinking Water Rule EA 
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 μg/L, $471.7 million for a MCL 5 μg/L, $205.6 million for a 

MCL of 10 μg/L, and $76.5 million for a MCL of 20 μg/L. 

EPA 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 μg/L, 

$191.1 to $355.6 million if the MCL were set at 5 μg/L, $139.6 to $197.7 million if the MCL 

were set at 10 μg/L, and $66.2 to $75.3 million if the MCL were set at 20 μg/L. These monetized 

health benefits of reducing arsenic 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 μg/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 μg/L, an estimated 29 to 54 fatal cancers and 22 to 47 non-fatal cancers per 

year are prevented; at 10 μg/L, 21 to 30 fatal and 16 to 26 non-fatal cancers per year are 

prevented; and at 20 μg/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 nonquantifiable 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 

Chapter 8, Economic Impact Analyses 8-18 Arsenic in Drinking Water Rule EA 
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 μg/L, 

$1.4 million for an MCL of 5 μg/L, $1.2 million for an MCL of 10μg/L, and $1.0 million for an 

MCL of 20μg/L. 

Various 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 lowcost 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. 

Chapter 8, Economic Impact Analyses 8-19 Arsenic in Drinking Water Rule EA 
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 μg/L, 5 μg/L, 10 μg/L, and 20 

μg/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 μg/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 
Exhibit 8-5

Average Annual Cost per CWS Exceeding the MCL, by Ownership

System Size Treatment and Monitoring Costs Total Cost 

Public Private All Systems 

MCL = 3 μg/L 

<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 μg/L 

<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 

MCL = 10 μg/L 

<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 μg/L 

<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 
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 μg/L, 5 μg/L, 10 μg/L, 

and 20 μg/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 μg/L and from approximately $5 to $285 per year at 

10 μg/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 μg/L and 10 μg/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 μg/L. These results for systems exceeding the MCL are presented in 

Exhibit 8-8. At 3 μg/L, 5 μg/L, and 20 μg/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 
Exhibit 8-6

Annual Compliance Costs per Household for 

CWSs Exceeding MCLs

System Size 

Groundwater Surface Water 

Public Private Public Private 

MCL = 3 μg/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 μg/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 μg/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 μg/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 8-23 Arsenic in Drinking Water Rule EA 
Exhibit 8-7

Annual Compliance Costs per Household for CWSs Exceeding MCLs,

as a Percent of Median Household Income

System Size 

Groundwater Surface Water 

Public Private Public Private 

MCL = 3 μg/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 = 5 μg/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 μg/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 = 20 μg/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 
Exhibit 8-8

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

(3% Discount Rate)

Service Area Type 

# of Systems 

Above the MCL 

Average 

Population 

Served Per 

System 

Average Annual 

System Cost 

Annual 

National Costs 

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 

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 

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 

$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 

$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 

$46,053 

$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 
8.5.4 Macroeconomic Effects 

As required under UMRA Section 202, EPA is required to estimate the potential macroeconomic 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 μg/L level, $472 million at the 5 μg/L level, 

$206 million at the 10 μg/L level, and $77 million at the 20 μg/L level (at a seven percent 

discount rate). 

8.5.5 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 
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 
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 μg/L, 5 μg/L, 10 μg/L, and 20 μg/L. EPA also evaluated national 

costs and benefits of States choosing to reduce arsenic 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 
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 
• 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 
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 μg/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 preexisting 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 
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 noncancerous. 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 
bladder and lung cancer risks for exposed populations at or above arsenic levels of 3, 5, 10, and 

20 μg/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 μg/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 

(μg/L) 

Reduced Mortality 

Cases** 

Reduced Morbidity 

Cases** 

Total Bladder Cancer 

Cases Avoided* 

3 7.4 - 20.0 21.2 - 56.9 28.6 - 76.8 

5 6.6 - 14.5 18.9 - 41.2 25.6 - 55.7 

10 4.9 - 8.0 13.8 - 22.7 18.7 - 31.0 

20 2.6 - 2.8 7.3 - 7.8 9.9 - 10.6 

* 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 

(μg/L) 

Reduced Mortality 

Cases** 

Reduced Morbidity 

Cases** 

Total Lung Cancer 

Cases Avoided* 

3 25.2 - 54.1 3.4 - 7.4 28.6 - 61.5 

5 22.5 - 39.2 3.1 - 5.3 25.6 - 44.5 

10 16.4 - 21.8 2.2 - 3.0 18.7 - 24.8 

20 7.4 - 8.7*** 1.0 - 1.2*** 8.5 - 9.9*** 

* 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 8-33 Arsenic in Drinking Water Rule EA 
Exhibit 8-11

Annual Total Cancer Cases Avoided from Reducing Arsenic in CWSs and NTNCs

Arsenic Level 

(μg/L) 

Reduced Mortality 

Cases**  

Reduced Morbidity 

Cases** 

Total Cancer Cases 

Avoided* 

3 32.6 - 74.1 24.6 - 64.2 57.2 - 138.3 

5 29.1 - 53.7 22.0 - 46.5 51.1 - 100.2 

10 21.3 - 29.8 16.1 - 25.9 37.4 - 55.7 

20 10.2 - 11.3*** 8.5 - 8.8 19.0 - 19.8*** 

* 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 nonfatal cancers (this value was updated from the $536,000 value EPA updated to 1997 dollars from 

the Viscusi et al. 1991 study). 

The total national costs of the revised Arsenic Rule are 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 μg/L, $52.0 to $113.3 

million at an MCL of 5 μg/L, $38.0 to $63.0 million at an MCL of 10 μg/L, and $20.1 to $21.5 

million at an MCL of 20 μg/L. Total annual health benefits resulting from lung cancer cases 

avoided range from $155.6 to $334.5 million at an MCL of 3 μg/L, $139.1 to $242.3 million at 

an MCL of 5 μg/L, $101.6 to $134.7 million at an MCL of 10 μg/L, and $46.1 to $53.8 million 

at an MCL of 20 μg/L. 

Chapter 8, Economic Impact Analyses 8-34 Arsenic in Drinking Water Rule EA 
Exhibit 8-12

Total Annual Cost, Estimated Monetized Total Cancer Health Benefits and

Non-Quantifiable Health Benefits from Reducing Arsenic in PWSs

($ millions)

Arsenic 

Level 

(μg/L) 

Total Annual 

Cost (7%) 

Annual Bladder 

Cancer Health 

Benefits1,2 

Annual Lung 

Cancer Health 

Benefits1,2 

Total Annual 

Health Benefits1,2 

Potential Non-Quantifiable 

Health Benefits 

3 $792.1 $58.2 - $156.4 $155.6 - $334.5 $213.8 - $490.9 

• Skin Cancer 

• Kidney Cancer 

• Cancer of the Nasal 

Passages 

• Liver Cancer 

• Prostate Cancer 

• Cardiovascular Effects 

• Pulmonary Effects 

• Immunological Effects 

• Neurological Effects 

• Endocrine Effects 

• Reproductive and 

Developmental Effects 

5 $471.7 $52.0 - $113.3 $139.1 - $242.3 $191.1 - $355.6 

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

20 $76.5 $20.1 - $21.5 $46.1 - $53.8 $66.2 - $75.33 

1

 May 1999 dollars. 2

 These monetary estimates are based on cases avoided given in Exhibit 5-9 (a-c). 3

 For 20 μg/L, the proportional reduction from the lower level risk base case is greater than the proportional

reduction from the higher level risk base case. Thus the number of estimated cases avoided and estimated

benefits are higher at 20 μg/L using the 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 μg/L; $471.1 

million per year at 5 μg/L; $205.6 million per year at 10 μg/L; $76.5 million per year at 20 μg/L. 

Chapter 8, Economic Impact Analyses 8-35 Arsenic in Drinking Water Rule EA 
Exhibit 8-13

Summary of the Total Annual National Costs of Compliance

($ millions)

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

System Costs 

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

Monitoring/ 

Administrative 

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

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

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

CWS NTNC

MCL = 10 μg/L 

MCL =20 μg/L 

TOTAL 

MCL = 3 μg/L 

MCL =5 μg/L 

Chapter 8, Economic Impact Analyses 8-36 Arsenic in Drinking Water Rule EA 
EPA also assessed the cost impact of reducing arsenic in drinking water at the household level. 

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

MCL (μg/L) 

System Size 

3 5 10 20 

<100 $317.00 $318.26 $326.82 $351.15 

101-500 $166.91 $164.02 $162.50 $166.72 

501-1,000 $74.81 $73.11 $70.72 $68.24 

1,001-3,300 $63.76 $61.94 $58.24 $54.36 

3,301-10,000 $42.84 $40.18 $37.71 $34.63 

10,001-50,000 $38.40 $36.07 $32.37 $29.05 

50,001-100,000 $31.63 $29.45 $24.81 $22.63 

100,001-1,000,000 $25.29 $23.34 $20.52 $19.26 

>1,000,000 $7.41 $2.79 $0.86 $0.15 

All categories $41.34 $36.95 $31.85 $23.95 

Chapter 8, Economic Impact Analyses 8-37 Arsenic in Drinking Water Rule EA 
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 μg/L (lower bound estimate of avoided bladder cancer cases) to $3.4 million at an 

MCL of 20 μg/L (upper bound of avoided bladder cancer cases). Similarly, the 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 

(μg/L) lower bound**  upper bound** 

3% Discount Rate 

3 

5 

10 

20 

$ 12.2 $ 5.0

$ 8.1 $ 4.1

$ 4.8 $ 3.2

$ 3.5 $ 3.4

7% Discount Rate 

3 

5 

10 

20 

$ 13.8 $ 5.7

$ 9.2 $ 4.7

$ 5.5 $ 3.7

$ 4.0 $ 3.9

**Lower/upper bounds correspond to estimates of bladder cancer cases avoided. 

Chapter 8, Economic Impact Analyses 8-38 Arsenic in Drinking Water Rule EA 
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, preoxidation, 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 μg/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-1 Proposed Arsenic in Drinking Water Rule RIA 
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 μg/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 μg/L) which is equal to 80 percent of the final revised MCL of 

10 μg/L was selected as the basis for the development of the Arsenic Rule decision tree. The 

selection of a 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 μg/L and at the final MCL of 10 μg/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 μg/L, and the target treatment 

concentration is 8 μg/L, then approximately 80 percent removal is required.1 

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 
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 pointof-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 
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 preoxidation 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 
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 Percent Removal of 

In-Place System 

Maximum Percent 

Removal

1 

Coagulation/Filtration2 50 95 

Lime Softening2 50 90 

Coagulation Assisted Microfiltration NA 90 

Ion Exchange NA >95 

Activated Alumina NA >95 

Reverse Osmosis NA >95 

Greensand Filtration3 NA 80 

POU Activated Alumina NA >90 

POU Reverse Osmosis NA >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 
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 nonmechanical 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 
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 III) and 

arsenate (As V). As(III) is dominant in ground waters while surface waters more typically 

contain As(V). As(III) 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(III) 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 (III) 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 
Exhibit A-2: Systems Needing to Add Pre-Oxidation 

System Size Percent of Ground Water Systems 

25-100 54 

101-500 30 

501-1000 24 

1001-3300 24 

3300-10K 27 

10001-50K 13 

50,001-100K 41 

100,001-1M 16 

A.4.2 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(III) to As(V). Arsenic removal utilizing the SMI process seems to be 

Appendix A, Decision Tree and Large System Costs A-8 Proposed Arsenic in Drinking Water Rule RIA 
dependent on the iron to arsenic level as well as pH. 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 
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 Lime/ Soda Ash Softening Coagulation 

Flocculation 

Filtration 

25-100 3.9% 27.5% 78.5% 

101-500 8.1% 52.6% 71.2% 

501-1000 20.5% 70.2% 79.3% 

1001-3300 17.5% 79% 81.7% 

3300-10K 10.8% 95.4% 86.5% 

10001-50K 6.9% 94.5% 96.3% 

50,001-100K 5.7% 93.7% 88% 

100,001-1M 5.1% 99.5% 93.4% 

3. 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 
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 

Appendix A, Decision Tree and Large System Costs A-11 Proposed Arsenic in Drinking Water Rule RIA 
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 Lime/ Soda Ash Softening Coagulation 

Flocculation 

25-100 2.1% 1.5% 

101-500 3.7% 2.0% 

501-1000 4.1% 4.2% 

1001-3300 5.2% 3.4% 

3300-10K 7.0% 8.1% 

10001-50K 12.2% 15.1% 

50,001-100K 17.4% 24.2% 

100,001-1M 32.4% 25.2% 

3. 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. 

4. 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. 

5. 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 
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 Likelihood of Sulfate (percent) 

<25 mg/L 25-120 mg/L >120 mg/L 

<10 ug/L 48 33 19 

10-20 ug/L 35 39 26 

>20 ug/L 33 38 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 
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 Likelihood of Iron (percent) 

<300 ug/L >300 ug/L 

<10 ug/L 82 18 

10-20 ug/L 81 19 

>20 ug/L 71 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 to10,000 people, the Agency assumed a 10 percent usage 

of coagulation microfiltration distributed evenly among mechanical dewatering and nonmechanical 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 
Exhibit A-7

Probability Decision Tree: Ground Water Systems Serving 100 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 1.0 2 Modify Coagulation/Filtration and pre-oxidation 1.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 5.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 2.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.0 8 Activated Alumina (pH 7 -pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 56.0 9 Activated Alumina (pH 8 -pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 19.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 12 POU Activated Alumina and pre-oxidation 2.0 13 POU Reverse Osmosis and pre-oxidation 2.0 

Sum of Probabilities: 100.00 
Exhibit A-8

Probability Decision Tree: Ground Water Systems Serving 101-500 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 5.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 2.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 56.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 19.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 12 POU Activated Alumina and pre-oxidation 1.0 13 POU Reverse Osmosis and pre-oxidation 1.0 

Sum of Probabilities: 100.00 
Exhibit A-9

Probability Decision Tree: Ground Water Systems Serving 501-1,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 5.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 2.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 25.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 2.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 25.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 25.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-10

Probability Decision Tree: Ground Water Systems Serving 1,001-3,300 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 5.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 2.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 5.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 5.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 17.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 25.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 25.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-11

Probability Decision Tree: Ground Water Systems Serving 3,301-10,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 3.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 5.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 2.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 8.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 24.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 26.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 26.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-12

Probability Decision Tree: Ground Water Systems Serving 10,001-50,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 3.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 12.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 11.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 32.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 32.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-13

Probability Decision Tree: Ground Water Systems Serving 50,001-100,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 3.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 12.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 7.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 34.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 34.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-14

Probability Decision Tree: Ground Water Systems Serving 100,001-1,000,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 12.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 4.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 37.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 37.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-15

Probability Decision Tree: Surface Water Systems Serving 100 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 28.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 -pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 44.0 9 Activated Alumina (pH 8 -pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 16.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 4.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 4.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-16

Probability Decision Tree: Surface Water Systems Serving 101-500 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 8.0 2 Modify Coagulation/Filtration and pre-oxidation 53.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 24.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 9.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 3.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 3.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-17

Probability Decision Tree: Surface Water Systems Serving 501-1,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 21.0 2 Modify Coagulation/Filtration and pre-oxidation 70.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 1.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 4.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 4.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-18

Probability Decision Tree: Surface Water Systems Serving 1,001-3,

No. Treatment Technology Train 

1 Modify Lime Softening and pre-oxidation 2 Modify Coagulation/Filtration and pre-oxidation 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 

6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxid11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxid12 POU Activated Alumina and pre-oxidation 13 POU Reverse Osmosis and pre-oxidation 

Sum of Probabi
Exhibit A-19

Probability Decision Tree: Surface Water Systems Serving 3,301-10,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 11.0 2 Modify Coagulation/Filtration and pre-oxidation 87.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 1.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 1.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-20

Probability Decision Tree: Surface Water Systems Serving 10,001-50,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 5.0 2 Modify Coagulation/Filtration and pre-oxidation 95.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-21

Probability Decision Tree: Surface Water Systems Serving 50,001-100,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 6.0 

2 Modify Coagulation/Filtration and pre-oxidation 88.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 1.0 

6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 2.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 3.0 12 POU Activated Alumina and pre-oxidation 0.0 

13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit A-22

Probability Decision Tree: Surface Water Systems Serving 100,001-1,000,000 Peopl

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 5.0 

2 Modify Coagulation/Filtration and pre-oxidation 93.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 1.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 1.0 12 POU Activated Alumina and pre-oxidation 0.0 

13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 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

PWS ID # Utility Name 

1 AZ0407025 Phoenix Municipal Water System 

2 CA0110005 East Bay Municipal Utility District 

3 CA1910067 Los Angeles-City Dept. of Water and Power 

4 CA1910087 Metropolitan Water District of Southern California 

5 CA3710020 San Diego- City of 

6 CA3810001 San Francisco Water Department 

7 CA4310011 San Jose Water Company 

8 CO0116001 Denver Water Board 

9 FL4130871 Miami-Dade Water And Sewer Authority-Main System 

10 GA1210001 City of Atlanta 

11 IL0316000 City of Chicago 

12 MA6000000 Massachusetts Water Resource Authority 

13 MD0150005 Washington Suburban Sanitation Commission 

14 MD0300002 Baltimore City 

15 MI0001800 City of Detroit 

16 MO6010716 St. Louis County Water County 

17 NY5110526 Suffolk County Water Authority 

18 NY7003493 New York City Aqueduct System 

19 OH1800311 City of Cleveland 

20 PA1510001 Philadelphia Water Department 

21 PR0002591 San Juan Metropolitano 

22 TX0570004 Dallas Water Utility 

23 TX1010013 City of Houston- Public Works Department 

24 TX150018 San Antonio Water System 

25 WA5377050 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 μg/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. 

RInd = C(As)Ind * [DWInd * DWAdj] * RUnit Equation B-1 

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 μg/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 [DWInd * 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 μg/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-1 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-1 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-1, 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-1 calculation is carried out to determine that individual’s lifetime cancer risk, 

RInd. 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)Ind in Equation B-1. 

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 μg/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 μg/L. 

In the Monte Carlo simulation model, the selection of a value for C(As)Ind of Equation B-1 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 μg/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 μg/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 μg/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 μg/L MCL 

option produced a finished water arsenic value of 25 μg/L, that value was changed to 8 μg/L. If 

the model run were for the option of a 20 μg/L MCL, that value would be changed to 16 μg/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 DWInd and DWAdj in Equation B-1. 

Appendix B, Assumptions and Methodology for B-3 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
The variable DWInd reflects the differences (variability) in individual water consumption within 

the exposed population. In Equation B-1, 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 

CSFII 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, CSFII 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-1) 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-1 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-1 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 DWInd * DWAdj

. Overall Distributions are Lognormal)

Community Water Consumption Data Total Water Consumption Data 

Male Mean = 0.60 

s.d. = 0.61 

Mean = 0.73 

s.d. = 0.62 

Female Mean = 0.64 Mean = 0.79 

B.1.4 Cancer Risk Factors 

This section provides further information on the variable RUnit in Equation B-1. 

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, agespecific 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 B-6 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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 “[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 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 μg/L are shown 

in Exhibit B-2, below. 

Exhibit B-2 

Risk Measures from Morales (2000) and as Used in this Benefit Analysis

Bladder Cancer Lung Cancer 

Males Females Males Females 

ED01 (μg/L) 

395 252 364 258 

Mean for RUnit

 (cases/person 

per μg/L) 2.53 x 10-5 3.97 x 10-5 2.75 x 10-5 3.88 x 10-5 

LED01 (μg/L) 

326 211 294 213 

Upper 95% CL for RUnit 

(cases/person per μg/L) 3.07 x 10-5 4.74 x 10-5 3.40 x 10-5 4.69 x 10-5 

The 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-1, these risk measures are converted 

to the units of cases/person per μg/L needed for RUnit by simply dividing 0.01 by the 

corresponding ED01 or LED01 μg/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 B-8 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
& 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 Fg, versus about 10 Fg 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 Fg/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 Fg/kg/day basis. 

Other factors contributing to lower bound uncertainty include the possibility of a sub-linear doseAppendix 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.1(b), provides some evidence that the shape of the doseresponse 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 sublinear 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-1 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 

3 μg/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)

Mean Risk for Exposed 

Population (Lower and Upper 

Bounds) 

90th Percentile Risk for Exposed 

Population (Lower and Upper 

Bounds) 

3 0.11 -1.25 x 10-4 0.22 - 2.42 x 10-4 

5 0.27 - 2.02 x 10-4 0.55 - 3.9 x 10-4 

10 0.63 - 2.99 x 10-4 1.32 - 6.09 x 10-4 

20 1.10 - 3.85 x 10-4 2.47 - 8.37 x 10-4 

B.1.7 Estimated Cancer Cases and Cases-Avoided 

Appendix B, Assumptions and Methodology for B-10 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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 μg/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 μg/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-11 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 Fg/L, 51.1 to 100.2 at an MCL of 5 Fg/L, 

37.4 to 55.7 at an MCL of 10 Fg/L, and 19.0 to 19.8 at an MCL of 20 Fg/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 μg/L: Phoenix, Houston, and Los Angeles. 

The basic risk algorithm used for systems serving fewer than one million people as shown in 

Equation B-1 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-1 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-12 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
The water consumption and adjustment factors [DWInd * 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. 

CGA + CSA

C Initial 

+


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-1 to calculate the number of baseline 

cases in the population affected by the particular MCL option. The number of individuals in the 

population affected for a particular option at each of the very 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)Ind that was equal to 0.8 * MCL value. 

B.3 Non-Transient Non-Community Water Systems 

B.3.1 Data Inputs 









EPSA FS 

EPST FT 





•





 




S 

EPST FT 


 


•


EPSA F 




 


G 

EPGT FT 


 






 


 




EPGA F 

•





EPGA FG 

EPGT FT 

•















=


Appendix B, Assumptions and Methodology for B-13 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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 CC c )*( − WP c (* 1 ) 

TW = P *WP c c c 

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 = c c c 

c 365*70 

PCDC *DC *YC 

PCLE = c c c 

c 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

Number 

of 

Systems 

Total 

SDWIS 

Population 

Number of 

Customer 

Cycles/Year 

Worker 

Per 

Person 

Per Day 

Percent of 

Worker's 

Daily 

Consumption 

Worker 

Days Per 

Year 

Worker 

Years 

Percent of 

Customer's 

Daily 

Consumption 

Customer 

Days Per 

Year 

Cust

Yea

Water Wholesalers 266 66,018 1.00 0 n/a n/a n/a 25.0% 270.00 Mobile Home Parks 104 19,240 1.33 0.046 50.0% 250 40 100.0% 270.00 Nursing Homes 130 13,910 1.00 0.23 50.0% 250 40 100.0% 365.00 Churches 230 11,500 1.00 0.01 50.0% 250 40 50.0% 52.00 Golf and Country Clubs 116 11,716 4.50 0.11 50.0% 250 40 50.0% 52.00 Retailers (Food related) 142 45,724 2.00 0.07 50.0% 250 40 25.0% 185.00 Retailers (Non-food related) 695 120,930 4.50 0.09 50.0% 250 40 25.0% 52.00 Restaurants 418 154,660 2.00 0.07 50.0% 250 40 25.0% 185.00 Hotels/Motels 351 46,683 86.00 0.27 50.0% 250 40 100.0% 3.40 Prisons/Jails 67 121,940 1.33 0.1 50.0% 250 40 100.0% 270.00 Service Stations 53 12,190 7.00 0.06 50.0% 250 40 25.0% 52.00 Agricultural Products/Services 368 27,968 7.00 0.125 50.0% 250 40 25.0% 52.00 Daycare Centers 809 61,484 1.00 0.145 50.0% 250 10 50.0% 250.00 Schools 8,414 3,086,012 1.00 0.073 50.0% 200 40 50.0% 200.00 State Parks 83 106,895 26.00 0.016 50.0% 250 40 50.0% 14.00 Medical Facilities 367 163,631 16.40 0.022 50.0% 250 40 100.0% 6.70 Campgrounds/RV Parks 123 19,680 22.50 0.041 50.0% 180 40 100.0% 5.00 Federal Parks 20 780 26.00 0.016 50.0% 250 40 50.0% 14.00 Highway Rest Areas 15 6,105 50.70 0.01 50.0% 250 40 50.0% 7.20 Misc. Recreation Services 259 22,533 26.00 0.016 50.0% 250 40 100.0% 14.00 Forest Service 107 4,494 26.00 0.016 100.0% 250 40 100.0% 14.00 Interstate Carriers 287 35,301 93.00 0.304 50.0% 250 40 50.0% 2.00 Amusement Parks 159 76,462 90.00 0.18 50.0% 250 10 50.0% 1.00 Summer Camps 46 6,716 8.50 0.1 100.0% 180 10 100.0% 7.00 Airports 101 326,860 36.50 0.308 50.0% 250 40 25.0% 10.00 Military Bases 95 67,525 n/a 1 50.0% 250 40 n/a n/a n/Non-Water Utilities 497 84,490 n/a 1 50.0% 250 40 n/a n/a n/Office Parks 950 181,600 n/a 1 50.0% 250 40 n/a n/a n/Manufacturing: Food 768 285,696 n/a 1 50.0% 250 40 n/a n/a n/Manufacturing: Non-Food 3,356 588,792 n/a 1 50.0% 250 40 n/a n/a n/Landfills 78 3,432 n/a 1 100.0% 250 40 n/a n/a n/Fire Departments 41 4,018 n/a 1 100.0% 250 40 n/a n/a n/Construction 99 5,247 n/a 1 100.0% 250 40 n/a n/a n/Mining 119 13,447 n/a 1 100.0% 250 40 n/a n/a n/Migrant Labor Camps 33 2,079 n/a 1 100.0% 250 40 n/a n/a n/

Subt

TOT
Exhibit B-5

NTNC Percent of Lifetime Exposure and Age at Exposure

Percent 

of Worker 

Lifetime 

Exposure 

Percent of 

Customer 

Lifetime 

Exposure 

Worker 

Age 

Bracket 

Customer 

Age 

Bracket 

Water Wholesalers 0.00% 18.49% n/a all 

Mobile Home Parks 19.57% 36.99% 20 to 64 all 

Nursing Homes 19.57% 14.29% 20 to 64 65+ 

Churches 19.57% 7.12% 20 to 64 all 

Golf and Country Clubs 19.57% 7.12% 20 to 64 all 

Retailers (Food related) 19.57% 12.67% 20 to 64 all 

Retailers (Non-food related) 19.57% 3.56% 20 to 64 all 

Restaurants 19.57% 12.67% 20 to 64 all 

Hotels/Motels 19.57% 0.53% 20 to 64 all 

Prisons/Jails 19.57% 3.17% 20 to 64 20 to 64 

Service Stations 19.57% 2.75% 20 to 64 16 to 70 

Agricultural Products/Services 19.57% 2.54% 20 to 64 all 

Daycare Centers 4.89% 2.45% 20 to 64 <5 

Schools 15.66% 4.70% 20 to 64 6 to 18 

State Parks 19.57% 1.92% 20 to 64 all 

Medical Facilities 19.57% 0.27% 20 to 64 all 

Campgrounds/RV Parks 14.09% 0.98% 20 to 64 all 

Federal Parks 19.57% 1.92% 20 to 64 all 

Highway Rest Areas 19.57% 0.99% 20 to 64 all 

Misc. Recreation Services 19.57% 3.84% 20 to 64 all 

Forest Service 39.14% 2.74% 20 to 64 all 

Interstate Carriers 19.57% 0.27% 20 to 64 all 

Amusement Parks 4.89% 0.14% 20 to 64 all 

Summer Camps 7.05% 0.27% 20 to 64 11 to 19 

Airports 19.57% 0.68% 20 to 64 all 

Military Bases 19.57% 0.00% 20 to 64 n/a 

Non-Water Utilities 19.57% 0.00% 20 to 64 n/a 

Office Parks 19.57% 0.00% 20 to 64 n/a 

Manufacturing: Food 19.57% 0.00% 20 to 64 n/a 

Manufacturing: Non-Food 19.57% 0.00% 20 to 64 n/a 

Landfills 39.14% 0.00% 20 to 64 n/a 

Fire Departments 39.14% 0.00% 20 to 64 n/a 

Construction 39.14% 0.00% 20 to 64 n/a 

Mining 39.14% 0.00% 20 to 64 n/a 

Migrant Labor Camps 39.14% 0.00% all n/a 

Appendix B, Assumptions and Methodology for B-18 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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 Fg/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. 

REFmai = 



 70 





 *

 Cmai  

2  Wmai 

REF fai = 



 70 





 *

 Cfai  

2  Wfai 

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 
∑
  (REF 
 fai 

*Zac ) 

WLRfci =
PWLE ci * AS gi *( RF i / 50)* a *100  






 ∑


 





 Zac 

a 

∑
  (REF 
 mai 

*Zac )  








 








WLR PWLE ci *AS gi *( RF i / 50)* a =
 *100 ∑
 mci Zac 

a 

∑
  (REF 
 mai 

*Zac ) 

∑


 







CLR PCLE ci * AS gi *( RF i / 50)* a 

mci =
 *100

Zac 

 






 a 

(REFfai *Zac  ∑
 )
 


  CLR 
 PCLE ci 

*AS gi *( RF i / 50)* a =
 *100 ∑
 fci  Zac 
 


 a 

where;

WLR = worker lifetime risk (per 100,000 people)

CLR = customer lifetime risk (per 100,000 people)

AS = arsenic concentration (Fg/L)

RF = risk of bladder cancer at 50 Fg/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:

WLR if RN ≤
MP 

 = 

mci 1

WLR ci WLR fci otherwise 

CLR if RN ≤
MP 

 

= 

mci 1 CLRci CLRfci otherwise 

where; 

RN1 = random number between 0 and 1 

MP = percentage of the population that is male 

Appendix B, Assumptions and Methodology for B-20 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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. 

TC = ∑TCc 

c 

TW = ∑ TWc 

c 

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 = c 

c (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 = c 

c (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: 

WLR ci with Pr obability WPR c

 LRi = M


 CLR ci with Pr obability CPR c 

where;

LR = Lifetime risk (1/100,000)

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

 

 







= 

N 

∑ 

i=1

LRi 




*

(TC +
TW)

N 100 , 000 

 

 








where; 

CA = expected number of bladder cancer cases 

N = number of iterations 

Appendix B, Assumptions and Methodology for B-22 Arsenic in Drinking Water Rule EA 

Estimating Cancer Risks Avoided and Benefits 
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. 

1

For 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-1 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 pretreatment 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, CWSs

3

 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-1 and C-2 below for ground and surface water systems, respectively. 

2

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. 

3

Note that public-purchased systems are analyzed as publicly-owned systems and similarly, privatepurchased 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 

Publicly-Owned Privately-Owned 

All GW 

Non- Systems 

Purchased 

Purchased NonPurchased Purchased 

25-100 1,217 125 12,893 197 14,432 

101-501 4,141 480 10,242 385 15,248 

501-1,000 2,574 300 1,798 115 4,787 

1,001-3,300 3,847 347 1,599 100 5,893 

3,301-10,000 2,027 229 493 35 2,784 

10,001-50,000 1,078 207 259 17 1,561 

50,001-100,000 126 26 27 1 180 

100,001-900,000 74 15 18 -- 107 

Total 15,084 1,729 27,329 850 44,992 

Exhibit C-2.

Stratification of Community Surface Water Systems

System Size 

Category 

Publicly-Owned Privately-Owned 

All SW 

Non- Systems 

Purchased 

Purchased NonPurchased Purchased 

25-100 150 209 404 293 1,056 

101-501 348 634 396 490 1,868 

501-1,000 331 476 131 212 1,150 

1,001-3,300 873 930 225 280 2,308 

3,301-10,000 771 567 102 104 1,544 

10,001-50,000 724 387 114 35 1,260 

50,001-100,000 133 61 31 3 228 

100,001-900,000 136 33 33 3 205 

Total 3,466 3,297 1,436 1,420 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

3 μg/L 5 μg/L 10 μg/L 20 μg/L 

Ground water 19.7% 12.0% 5.3% 2.0% 

Surface water 5.6% 3.0% 1.12% 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 

Mean 5th 

Percentile 

50th 

Percentile 

(Median) 

75th 

Percentile 

95th 

Percentile 

Maximum 

<-100 1 1 1 1 2 4 

101-500 1 1 1 1 3 10 

501-1,000 2 1 1 2 3 4 

1,001-5,000 2 1 1 2 5 6 

5,001-10,000 2 1 2 3 5 15 

10,001-50,000 4 1 3 5 12 19 

50,001-100,000 6 1 4 8 22 37 

100,001-900,000 9 1 5 15 28 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 

RSD =	 (Eq. 1) 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 Conc.= (SysConc) ( × # 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 Arsenic in Drinking Water Rule 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)	 % remova (Eq. 3) l = SiteConc. 

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 μg/L, and the target MCL is 2 μg/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)

bA (Eq. 4) 

Design Flow = max (
 )








2 Average Flow 

Population bD

aD 

(Eq. 5) 

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 Design Flow 

aA bA aD bD 

Ground Water 

Public 0.08558 1.05840 0.54992 0.95538 

Private 0.06670 1.06280 0.41682 0.96078 

Public-Purchased 0.04692 1.10190 0.31910 0.99460 

Private-Purchased 0.05004 1.08340 0.32150 0.97940 

Surface Water 

Public 0.14004 0.99703 0.59028 0.94573 

Private 0.09036 1.03340 0.35674 0.96188 

Public-Purchased 0.04692 1.11020 0.20920 1.04520 

Private-Purchased 0.05004 1.08340 0.20580 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: 

 TrtTarget 




 SiteConc − 1



 (Eq. 6) Fraction o f Flow Treated = × (%SiteFlow) - % RE 

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: 

TrC = T + WD + [(P )( PO )] (Eq. 7) cap cap cap PO cap 

where: TrC = Treatment train capital cost at treating site cap 

T = Treatment technology capital cost at treating site cap 

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(III) 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-11 Arsenic in Drinking Water Rule EA 
Exhibit C-6.

Probability of a System Requiring Pre-Oxidation

System Size Category Pre-Oxidation 

(GW systems) 

Pre-Oxidation 

(SW systems) 

25-100 0.54 0.09 

101-500 0.30 0.04 

501-1,000 0.24 0 

1,001-3,300 0.24 0 

3,301-10,000 0.27 0.03 

10,001-50,001 0.13 0.01 

50,001-100,000 0.41 0.02 

100,001-1,000,000 0.16 0 

Source: 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: 

TrC & = TO M& + WDO& M + [(P )( PO O& M )] (Eq. 8) OM PO 

where: TrCO&M = Treatment train O&M cost at treating site 

TO&M = Treatment technology O&M cost at treating site 

WDO&M = Waste disposal technology O&M cost at treating site 

POO&M = 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 & (Eq. 9) tot = (TrC cap )



 

1− (r

r 

+ 1)

−rp 



 + TrC OM 

where: TrCtot = Annual total treatment train cost at treating site 

TrC = Treatment train capital cost at treating site cap 

r = Discount rate 

rp = Repayment period 

TrCO&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 

μg/L vs. an MCL of 10 μg/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 
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-ofcapital 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: 

SC = ∑ 

n (TrCtot , n )	 (Eq. 10) ir n=1 

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: 

Cost kgal = SC i coc ÷ 

 AF ⋅ 

365 days 1000 kgal 

 ⋅ (Eq. 11) ,  i 1 yr 1 Mgal 

where: Costkgal = Cost per thousand gallons for the system 

AFi = Average flow (MGD) of system i 

SC i, 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 
Cost = Cost HHi ⋅C (Eq. 12) kgal HH 

where: CostHHi = Household cost per year for system i 

CHH = Household consumption per year (kgal) 

Exhibit 7. 

Water Consumption per Residential Connection 

System Size Category System Ownership Type 

Public Private 

<100 81 92 

101-500 93 110 

501-1,000 97 88 

1,001-3,300 82 102 

3,301-10,000 87 124 

10,001-50,000 108 110 

50,001-100,000 122 96 

100,001-1,000,000 127 114 

Source: EPA. 1997. CWSS, 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 μg/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 μg/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 μg/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 μg/L, 

the maximum site concentration is determined to be 33.10 μg/L (= 11.03 * 3). Using the default 

RSD of 0.64 and this limitation on the maximum site concentration, the three sites are assigned 

concentrations of 8.89, 9.69, and 14.52 μg/L, respectively. These three concentrations keep the 

average system concentration at 11.03 μg/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 8.89μg/L and 9.69μg/L, both of 

which are below the user selected MCL of 10 μg/L. The final site of the system, however, 

exceeds the MCL with a concentration of 14.52 μg/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 μg/L to reach the treatment target of 8 μg/L (80 percent of MCL 10 μg/L) equals 45 

percent: 

( SiteConc − TrtTarget) ( 14. 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: 

D . Design Flow = aD ⋅( population) b = ( . 0 54992 ) ⋅ ( , ) = 3646. 02393 × 

1Mgal 

10 000 = 3646 0 95538 . 1000kgal 

and the average flow equals 1.465 MGD: 

A . Average Flow a A 0 08558 1 05840 1465 454309 1Mgal = ⋅(population) . b =(. )⋅(10 ,000) = . kgal ×

1000kgal =1 465 

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: 

 TrtTarget 	  8  



 SiteConc − 1



 

 14 52 − 1



  −

 ( ) .

0 90 

 .  Fraction of Flow =	 × %SiteFlow = × 0 333  = 0. 1663 - % RE − . 

Appendix C, Cost Model Methodology C-17 Arsenic in Drinking Water Rule EA 
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 MGD) from Step 7 above, the design flow at the treating site can be calculated: 

( . 3646MGD) × (0. 166 ) = 0 .606 MGD 

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 $2,664,771.4 For design flow (x), the cost (y) can be calculated: 

Treatment capital: x<0.1 y = -11935465x2 + 48800366x + 94324 

0.1<x<0.27 y = 2343199x + 228653 

0.27<x<1 y = -483591x2 + 2308991x + 273143 

<1x<10 y = 1030810x + 1067733 

x>10 y = 320x2 + 921471x + 2129119 

Based on a site design flow of 0.606 mgd, the third segment of the cost equation is used: 

483591 ( 0 . 606 )

2 

y =−	 + 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 

0.085<x<1.8 y = 1749352x - 108017 

x>1.8 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. 

4

Costs 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 
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 pretreatment 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 MGD) from Step 7 above, the average flow at the treating site can be 

calculated as follows: 

(. 1465MGD) × (0. 1663 ) = 0 .244 MGD 

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 

0.03<x<0.09 y = 136332x + 22139 

0.09<x<0.36 y = 80081x + 26977 

0.36<x<4.3 y = 13311x + 51014 

x>4.3 y = 15236x + 42350 

Based on a site average flow of 0.244 MGD, the third segment of the cost equation is used: 

y = 80081 ( 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 

0.085<x<0.72 y = 111819x - 6950.5 

x>0.72 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 
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: 

. = (TrCcap)



 

1− (r

r 

+ 1)

−rp 



 + TrC OM = ($2, 664 , 771 )





 

1− ( .

0 0526 

+ 1)

(− )





 

+ $66, 809 = $284, 278 & 20 0 0526 

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: 

SC  365 days 

⋅ 

1000 kgal  . )⋅ 365 1000 = = 53 ir ÷ 

 AFi ⋅ 1yr 1 Mgal  = ($284, 278)÷ 



(1465 1 ⋅ 1  $0. 

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: 

= Cost kgal , i ⋅CHH = ($0. 53)⋅(108kgal ) = $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). 

5

Commercial 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, costof 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-1 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 μg/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: 

mj 

∑(SC )

Avg SC 

jr 

i =1 ir (Eq. 13) . = mj 

where: SCjr = Annual system cost for size category j at discount rate r 

SCir = Annual cost for system i at discount rate r 

j = Size category 

mj = 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: 

    

 Avg . SC

j ( pub)

(nj ( pub)) + 

 Avg SC 

j prv 

 . (nj prv ) Avg . SC

j total) 

=

( + )

( ) ( ) 

( 

nj ( pub) nj ( prv )

(Eq. 14) 

Appendix C, Cost Model Methodology C-22 Arsenic in Drinking Water Rule EA 
where: SCj(tot) = Total annual system cost for size category j 

SCi(pub) = Annual system cost for publicly-owned systems of size category j 

SCi(prv) = Annual system cost privately-owned systems of size category j 

nj(pub) = Number of publicly-owned treating systems in size category j 

nj(prv) = Number of privately-owned treating systems in size category j 

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:. 

mj 

∑ Cost HHi 1 Avg . Cost HHj 

= i =

( ) (Eq. 15) 

mj 

where: CostHHj = Annual household cost for size category j 

CostHHi = Household cost for system i 

mj = Number of systems in size category j 

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: 

mj 

ACjr = ∑(SCir )	 (Eq. 16) i =1 

where: ACjr = Annual cost for size category j 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): 

ANCr = ∑

8 ( ACjr )	 (Eq. 17) 

j =1 

where: ANCr = Annual national cost at discount rate r 

Appendix C, Cost Model Methodology C-23 Arsenic in Drinking Water Rule EA 
Appendix D. What-If Cost 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 

1

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-If Cost Sensitivity Analysis D-1 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-1 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-If Cost Sensitivity Analysis D-2 Arsenic in Drinking Water Rule EA 
Exhibit D-1

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 100 People

Percent of 

No. Treatment Technology Train <50% 

1 Modify Lime Softening and pre-oxidation 1.0 2 Modify Coagulation/Filtration and pre-oxidation 1.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.9 8 Activated Alumina (pH 7 -pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 60.3 9 Activated Alumina (pH 8 -pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 20.5 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 12 POU Activated Alumina and pre-oxidation 2.2 13 POU Reverse Osmosis and pre-oxidation 2.2 

Sum of Probabilities: 100.00 
Exhibit D-2

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 101-500 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.9 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 60.4 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 20.5 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 0.0 12 POU Activated Alumina and pre-oxidation 1.1 13 POU Reverse Osmosis and pre-oxidation 1.1 

Sum of Probabilities: 100.00 
Exhibit D-3

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 501-1,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 0.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.9 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 27.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 2.2 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 27.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 27.0 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-4

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 1,001-3,300 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 2.0 2 Modify Coagulation/Filtration and pre-oxidation 2.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 5.4 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 5.4 7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 12.9 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 18.3 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 27.0 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 27.0 12 POU Activated Alumina and pre-oxidation 0.0 

13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-5

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 3,301-10,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 3.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 8.7 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.2 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 26.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 28.1 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 28.1 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-6

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 10,001-50,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 63.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 4.0 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 11.5 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 11.5 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-7

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 50,001-100,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 63.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 2.5 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 12.2 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 12.2 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-8

Probability Decision Tree: “What-If” Sensitivity Analysis

Ground Water Systems Serving 100,001-1,000,000 People

No. Treatment Technology Train 

Percent o

<50% 

1 Modify Lime Softening and pre-oxidation 4.0 2 Modify Coagulation/Filtration and pre-oxidation 4.0 3 Anion Exchange (<20 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 4 Anion Exchange (20-50 mg/L SO4) and POTW w aste disposal and pre-oxidation 0.0 5 Coagulation Assisted Microfiltration and mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 63.0 6 Coagulation Assisted Microfiltration and non-mechanical dew atering/non-hazardous landfill w aste disposal and pre-oxidation 2.0 

7 Oxidation Filtration (Greensand) and POTW for backw ash stream and pre-oxidation 0.0 8 Activated Alumina (pH 7 - pH 8) and non-hazardous landfill (for spent media) and pre-oxidation 1.4 9 Activated Alumina (pH 8 - pH 8.3) and non-hazardous landfill (for spent media) and pre-oxidation 0.0 

10 Activated Alumina (23,100 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 12.8 11 Activated Alumina (15,400 BV) w ith pH adjustment (pH 6)/corrosion control and non-hazardous landfill (for spent media) and pre-oxidation 12.8 12 POU Activated Alumina and pre-oxidation 0.0 13 POU Reverse Osmosis and pre-oxidation 0.0 

Sum of Probabilities: 100.00 
Exhibit D-9

What-If Analysis Results

MCL Option Best Estimate What-If Estimate 

5 $411 Million $515 Million 

10 $177 Million $192 Million 

Appendix D, What-If Cost Sensitivity Analysis D-11 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-1 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-1 depicts the benefits by system size category and 

Exhibit E-2 displays benefit cost ratios. 

Exhibit E-1 

Benefits by System Size 

Population Stratum 

Type MCL 25-500 500-3300 

3300­

10,000 

10K1000K 

Upper 20 2.41 7.90 9.09 45.18 

Upper 10 7.13 23.34 26.85 133.50 

Upper 5 12.45 40.75 46.89 233.11 

Upper 3 16.67 54.57 62.80 312.18 

Lower 20 2.72 8.91 10.25 50.97 

Lower 10 5.15 16.85 19.39 96.40 

Lower 5 7.01 22.94 26.39 131.20 

Appendix E, Benefits and Costs by System Size Category E-1 Arsenic in Drinking Water Rule EA 
Exhibit E-2 

Benefit/Cost Ratios by System Size 

Population Stratum 

3300­ 10KBound MCL 25-500 500-3300 10,000 1000K 

Impacted Population 

(thousands) 961 315 3,622 18,005 

upper 20 0.38 0.74 1.01 1.32 

upper 10 0.42 0.81 1.11 1.39 

upper 5 0.33 0.62 0.84 1.05 

upper 3 0.27 0.50 0.66 0.85 

lower 20 0.43 0.84 1.14 1.49 

lower 10 0.30 0.59 0.80 1.00 

lower 5 0.18 0.35 0.47 0.59 

Appendix E, Benefits and Costs by System Size Category E-2 Arsenic in Drinking Water Rule EA