REGULATORY BWCT ANALYSIS:
BENEFITS AM) COSTS OF PROPOSED
SUFACE WATER TREATMENT RULE
AND TOTAL OOLIFTO RULE
PREPARED FOR:
ENVIROWENTAL PROTECTION AGENCY
OFFICE OF DRINKING WATER
WASHINGTON. DC 20460
PREPARED By:
WADE MILLER ASSOCIATES, INC.
1911 N. FORT I^ER DRIVE
ARLINGTON, VA 22209
SEPTEMBER 1. 1987
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REGULATORY IMPACT ANALYSIS:
BENEFITS AND COSTS OF PROPOSED
SURFACE WATER TREATMENT RULE
AND TOTAL COLIFORM RULE
Prepared For:
Environmental Protection Agency
Office of Drinking Water
Washington, DC 20460
Prepared By:
Wade Miller Associates, Inc.
1911 N. Fort Myer Drive
Arlington, VA 22209
Prepared as Part of:
Contract No. 68-01-7034
Task Order No. C-l
Mr. Joseph Gearo, Project Officer
Mr. Carl Kessler, Task Officer
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ERRATA
Several late changes in proposed specifications of both the
Surface Water Treatment Rule and the Total Col i form Rule produced
changes in the estimates of total national costs which were not
fully incorporated into the text of this document.
The total annual cost of compliance with performance re-
quirements for filtered surface water systems is estimated to be
$95 million per year. Costs for finished water turbidity moni-
toring and monitoring of chlorine residual in the distribution
system were not included in this total, however. These cost ele-
ments could add as much as another $16 million per year to the
total annual cost estimate, although other considerations could
cause the net effect to be smaller than this amount. An explana-
tion is provided on page 4-29.
The total annual cost of the Total Coliform Rule is estima-
ted to be in a range of $70 to $170 million per year, depending
on the extent to which States exercise the flexibility provided
in the proposed rule. The cost models in Appendix D assume a re-
quirement for a periodic sanitary survey for undis infected
groundwater systems (page D-3) . This requirement was subseouent-
ly dropped, resulting in a $9 million per year reduction in the
case estimate — from $170 million to $161 million. The
.
best case estimate of $70 million is unaffected by the change.
Additionally, changes in the requirements for analyzing check
samples to confirm positive results were omitted from the cost
models in Appendix p. The net effect of changes in the check
sample requirements is estimated to result in additional costs of
$2 million per year. Thus, the fully revised best and worst case
estimates are $72 million per year and $163 million per year.
Accordingly, the following changes are noted:
Page 1-7; Fourth Para: change $70 to $72
change $46 to $47
change $24 to $25
change $170 to $163
change $126 to $122
change $44 to $41
Page 4-32; Third Para: change $70 to $72
change $170 to $163
Page 4-32; Fourth Para: change $126 to $122
change $44 to $41
change $46 to $47
change $24 to $25
Page 4-34; First Para: change $161 to $154
change $61 to $63
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TABLE OF CONTENTS
1. INTRODUCTION AND SUMMARY 1-1
1.1 Introduction 1-1
1.2 Problem Definition 1-1
1.3 Market Imperfections, the Need for Federal
Regulation, and Consideration of Regulatory
Alternatives 1-3
1.4 Assessment of Total Costs 1-5
1.5 Assessment of Benefits 1-7
1.6 Regulatory Flexibility Act and Paperwork
Reduction Act Analyses 1-9
2. PROBLEM DEFINITION 2-1
2.1 Microbial Contaminants and the Incidence of
Waterborne Disease 2-1
2.2 Available Treatment Technology: The Multiple
Barriers Approach 2-15
2.2.1 Monitoring 2-15
2.2.2 Treatment 2-17
2.3 Exposure Profile of Public Water Systems 2-18
2.3.1 Number of Unfiltered Water Systems and
Population Exposed 2-19
2.3.2 Regional Distribution of Unfiltered
Systems and Correlation to Waterborne
Disease Outbreaks 2-23
2.3.3 Number, Treatment Profile, and Turbidity
Performance of Filtered Water Systems
and Population Exposed 2-23
2.3.4 Number of Systems Without Disinfection
and Population Exposed 2-32
2.3.5 Regional Distribution of Undisinfected
Systems and Correlation to Outbreaks
of Waterborne Disease 2-36
2.3.6 Number of Systems in Violation of
Existing Coliform Regulations and
Population Exposed 2-36
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TABLE OF CONTENTS (continued)
PAGE
3. MARKET IMPERFECTIONS, THE MEED FOR FEDERAL REGULA-
TION, CONSIDERATION OF REGULATORY ALTERNATIVES 3-1
Uniqueness of the Regulation of Drinking Water 3-1
The "Public" Nature of Water Supply 3-1
3.1 The Nature of the Imperfections 3-3
Flaws in the Revelation of Consumer Preferences 3-5
Flaws in Pricing and Capacity Planning 3-6
3.2 The Need for Federal Regulation 3-7
Publicly Owned Water Systems 3-7
Privately Owned Water Systems 3-8
A Model of "Perfect" Public Choice 3-9
3.3 Consideration of Regulatory Alternatives 3-11
Introduction 3-11
3.3.1 Alternatives and Factors Considered
in Developing the Surface Water
Treatment Rule 3-13
3.3.2 Alternatives and Factors Considered
in Developing the Total Coliform Rule 3-19
3.3.3 Alternatives and Basis for Monitoring
Requirements 3-21
4. ASSESSMENT OF COSTS 4-1
4.1 Costs to .Presently Unfiltered Systems 4-3
4.1.1 Unfiltered Systems Serving Fewer Than
100,000 People 4-4
4.1.2 Unfiltered Systems Serving More Than
100,000 People 4-16
4.1.3 Summary of Cost Estimates for Unfiltered
Systems 4-21
4.2 Costs to Presently Filtered Systems 4-22
4.3 Costs of Compliance With the Proposed Coliform
Rule 4-29
4.4 Implementation Costs to State Regulatory
Programs 4-34
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TABLE OF CONTENTS (continued)
PAGE
5. ASSESSMENT OF BENEFITS 5-1
5.1 Aggregate Analysis 5-2
5.2 System Level Analysis 5-11
6. REGULATORY FLEXIBILITY ACT ANALYSIS AND PAPERWORK
REDUCTION ACT ANALYSIS 6-1
6.1 Regulatory Flexibility Act Analysis 6-1
6.1.1 Purpose of Regulation 6-3
6.1.2 Number of Systems Affected 6-3
6.1.3 Economic Impacts of Filtration,
Turbidity Performance, and Total
Coliform Regulations on Small Water
Systems 6-5
6.2 Paperwork Analysis 6-7
6.2.1 Paperwork Reduction Act 6-7
6.2.2 Requirements of the Paperwork Reduction
Act 6-7
6.2.3 Number of Systems Affected/Respondent
-Burden 6-8
7. SUMMARY OF COSTS, BENEFITS, AND SOURCES OF UNCER- 7-1
TAINTY
APPENDIX A — DECISION TREES FOR UNFILTERED SYSTEMS
SERVING FEWER THAN 100,000 PERSONS
APPENDIX B — DECISION TREE AND COST MODEL FOR COMPLIANCE
OF FILTERED SYSTEMS WITH TURBIDITY
PERFORMANCE REQUIREMENT
APPENDIX C — SPREADSHEET MODELS FOR COMPUTING COSTS
OF MONITORING FOR THE SURFACE WATER
TREATMENT RULE
APPENDIX D — SPREADSHEET MODELS FOR COMPUTING COSTS
OF MONITORING FOR THE TOTAL COLIFORM RULE
APPENDIX E — SYSTEM LEVEL ANALYSES FOR 15
LARGE SYSTEMS
APPENDIX F — SYSTEM LEVEL ANALYSES FOR 9
GENERIC SIZE CATEGORIES
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LIST OF EXHIBITS
2-1 Waterborne Illnesses and Causative Agents 2-2
2-2 Typhoid .Deaths Over Time 2-3
2-3 Etiology of Waterborne Outbreaks (1920-83) 2-5
2-4 Waterborne Disease Outbreaks (1920-1983) 2-6
2-5 Cases of Waterborne Disease (1920-1983) 2-7
2-6 Water Supply Deficiencies Responsible for
Waterborne Outbreaks (1971-85) 2-10
2-7 Waterborne Outbreaks of Giardiasis Classified
by Type of Water Treatment or Water System
Deficiency (1965-1984) 2-11
2-8 Waterborne Disease Outbreaks (1946-1983) 2-13
2-9 Number of Community Water Systems (Plants)
Having Filtered Versus Unfiltered Surface
Water Supplies by Size Category and
Estimated Population Served 2-20
2"10 Unfiltered Community Water Systems Served by
Surface Water 2-22
2-11 Unfiltered Community Surface Water Systems
Serving More than 100,000 Persons 2-24
2-12 Unfiltered Non-Community Water Systems Served
by Surface Water 2-25
2-13 Regional Patterns in Community Systems ~
Unfiltered Systems and Disease Outbreaks 2-26
2-14 Regional Patterns — Non-Community Systems
Unfiltered Systems and Disease Outbreaks 2-27
2-15 State Regulatory Requirements for Filtration
of Surface Water Supplies 2-28
2-16 Filtered Community Water Systems Served by
Surface Water 2-29
2-17 Profile of Treatment-in-Place in Filtered
Community Water Systems 2-30
2-18 Type of Treatment in Place in Filtered
Community Surface Water Systems (By Size
of System) 2-31
2-19 Filtered-Non-Community Water Systems Served
by Surface Water 2-33
2-20 Current Turbidity Performance in Community
Surface Water Systems 2-34
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LIST OP EXHIBITS (Continued)
EXHIBIT
2-21 Number of Community Water Systems Having
Disinfected Versus Undisinfected Ground Water
Supplies by Size Category and Estimated
Population Served 2-35
2-22 State Regulatory Requirements for Disinfection
of Groundwater Supplies 2-37
3-1 Historical Trend of Water Utility Bills 3-4
3^2 Coliform Monitoring for Unfiltered Surface
Systems 3-22
3-3 Coliform Monitoring for Filtered Surface
Systems 3-23
3-4 Coliform Monitoring for Undisinfected Ground
Water Systems 3-24
3-5 Coliform Monitoring for Disinfected Ground
Water Systems 3-25
4-1 -Alternative Processes for Removing Microbio-
logical Contaminants 4-2
4-2 Capital Expenditures for Filtration 4-5
4-3 Capital Cost of Filtration Compliance Options 4-7
4-4 unit Production Costs of Filtration Compliance
Options 4_8
4-5 Summary of Annual Costs to Meet Exception
Criteria 4_9
4-6 Compliance Strategies of Unfiltered Systems
Serving < 100,000 4_H
4-7 Compliance Choices for Alternative Filtration
Exception Criteria 4-12
4-8 Total National Costs — Alternative Filtration
Exception Criteria 4-14
4-9 Estimated Treatment Cost for Fourteen Unfil-
tered Surface Water Systems Serving More
Than 100,000 Persons 4-17
4-10 Number of Systems Above Alternative Average
Turbidity Levels 4-23
4-11 Net Incremental Costs of Turbidity Alternatives 4-25
4-12 Likely Compliance Choices To Improve Turbidiry
Performance 4-26
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LIST OF EXHIBITS (Continued)
EXHIBIT PAGE
4-13 Total National Costs — Turbidity Performance
Requirement 4-28
4-14 Filtered Water Systems Requiring Improvement
in Turbidity Performance 4-30
4-15 Total Cost Impact of Coliform Monitoring on
Community Versus Non-Community Water Systems 4-33
4-16 Total Cost Impact of Coliform Monitoring on
Groundwater Versus Surface Water Systems 4-35
5-1 Size Distribution of CWSs 5-3
5-2 Details of Methodology for System Level
Analysis 5-15
5-3 Framework of Breakeven Analysis 5-20
5-4 Sample Output of System Net Benefits Analysis 5-22
5-5 Breakeven Thresholds For Systems Serving:
More Than 100,000 Persons 5-25
5-6 Breakeven Thresholds For Systems Serving:
Between 10,000 And 100,000 Persons 5-26
5-7 Breakeven Thresholds For Systems Serving:
Between 1000 And 10,000 Persons 5-27
5-8 Breakeven Thresholds For Systems Serving:
Fewer Than 1000 Persons 5-28
5-9 Breakeven Analysis of Installing Filtration
Assuming p(Outbreak) « 1/50 Years 5-31
5-10 - Breakeven Analysis of Installing Filtration
Assuming p(Outbreak) = 1/100 Years 5-32
7-1 Total Capital Costs 7-2
7-2 Total Annual Costs 7-3
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1. INTRODUCTION AND SUMMARY
l.l Introduction
This report contains an analysis of the costs and benefits
of controlling microbial contaminants in drinking water; through
the promulgation of two regulations: 1) the Surface Water Treat-
ment Rule (SWTR); and 2) the Total Coliform Rule. This regula-
tory impact analysis (RIA) was prepared in accordance with Execu-
tive Order 12291 which requires that the costs and benefits of
all major rules be examined and compared. The major topical
areas covered in this RIA are as follows:
o Problem Definition;
o Market Imperfections, the Need for Federal Regulation,
and Consideration of Regulatory Alternatives;
o Assessment of Total Costs;
o Assessment of Benefits;
o Regulatory Flexibility Act and Paperwork Reduction Act
Analyses;
o A Summary of Costs and Benefits.
This initial chapter contains a summary of results. Detailed
analyses of costs and benefits are included in Chapters 4 and 5.
1.2 Problem Definition
The fact that a number of infectious diseases can be trans-
mitted by drinking water is well known. These diseases include
both death causing diseases such as typhoid fever and cholera as
well as other diseases, such as giardiasis, which are less likely
to be fatal, but can cause prolonged illness and severe discom-
fort to infected individuals. Typically, the disease causing
organisms — various types of bacteria, viruses, and cysts—
enter the water as a result of unsanitary practices. These
include contamination from human and animal waste deposits in the
watershed, leaking sewers or septic tanks, cross-connections with
other sources of water, and back-siphonage resulting from nega--
tive pressure.
The number of waterborae disease outbreaks and cases de-
creased dramatically after chlorine was introduced in 1908 and
subsequently became widely used as a disinfectant. The number of
deaths attributable to typhoid fever and cholera had dropped to
virtually zero by the middle of the 20th century. By 1960, most
observers apparently believed that the problem of waterborne
disease outbreaks had been solved.
1-1
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During the period 1961-1983, both the reported number of
waterborne disease outbreaks and total cases of disease increased
substantially from the previous two decades (1941-1960), however.
According to Craun,1 the total number of reported outbreaks was
577 during this latter period and the total number of reported
cases amounted to 153,566. Several factors are thought to be
responsible for these dramatic increases: 1) complacency in
reporting; 2) poor or inadequate operation and maintenance of
treatment facilities; 3) increased vulnerability of water sources
due to increases in population and population density; 4) changes
in the nature of contaminants; and 5) use of inadequate indicator
organisms for detection.
All of these are important factors. Underreporting of
waterborne illnesses is thought to be great; knowledgeable
observers feel the actual number of cases is understated by at
least a factor of four. Many existing treatment facilities also
are not operated and maintained properly, allowing microbial
disease causing agents to pass through the treatment plant. Many
communities have not installed filtration in the belief that
their water sources are not vulnerable to contamination or that
watershed management and adequate storage can achieve the same
results as filtration.
One of the microorganisms that has caused a growing number
of outbreaks and reported cases in., the past decade is Giardia
Iambiia. Giardia lamblia is a protozoan cyst that is difficult
to inactivate using chlorination as typically practiced. Because
they are relatively large (i.e., 6-7 microns in diameter),
Giardia cysts can best be removed by filtration plus ^disinfec-
tion, using higher than normal concentrations of chlorine and
longer than normal contact times. A water system that does not
practice filtration and uses standard chlorine concentrations and
contact times (e.g., l.o mg/1 and 30 minutes) probably will not
_b«_Affective in removing or inactivating Giardia cysts.
It is notable that the first confirmed outbreak of giardi-
asis occurred in 1965, yet Giardia has accounted for the largest
number of reported outbreaks every year since 1978. It is likely
that giardiasis had been diagnosed as the more generic "gastroen-
teritis" for some indeterminate period of time.
Detection of Giardia. viruses, and other so-called "oppor-
tunistic pathogens" in source water, treatment processes, and
finished drinking water is difficult and labor intensive, requir-
ing skills that are not available to many utilities. Because no
routine, easy to perform, analytical method has yet to be devel-
oped, Giardia and other pathogens are best controlled by using
best available treatment technologies.
1 Craun, Gunther F., An Overview of Statistics on Acute and
Chronic—Water Contamination Problems. presented at Fourth
Domestic Water Quality Symposium, December, 1985.
1-2
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A combination of control strategies encompassing filtration;
disinfection; good watershed management; periodic sanitary sur-
veys; and monitoring for turbidity, total coliforms, and chlorine
residual are needed to effectively mitigate and control water-
borne disease causing microbial contaminants. Establishing a
number of preventive measures or barriers between the microbial
contaminants and the consumer, including a combination of treat-
ments, often is referred to as the "multiple barriers" approach
in conventional sanitary engineering theory.
Best available treatment technologies have been specified by
the Agency and include slow sand filtration, diatomaceous earth
filtration, direct filtration, conventional treatment, and vari-
ous disinfectants such as ozone and chlorine. These technologies
are described fully in the "Cost and Technology Document" devel-
oped by the Criteria and Standards Division of ODW.
The number of unfiltered surface supplies and the population
exposed was estimated through a survey conducted by the Associat-
ion of State Drinking Water Administrators (ASDWA). Through a
survey of all states, it was determined that approximately 1346
community water systems and 1536 non-community water systems have
unfiltered surface sources.
The total population exposed is estimated to be approxi-
mately 21.1 million persons served by community water systems and
another 300,000 served by non-community water systems. Of the
estimated 1346 community water systems that have unfiltered sur-
face sources, 15 large systems serving greater than 100,000 per-
sons, serve a total population of 15.93 million, or more than 75
percent of the total population exposed.
A number of filtered supplies also will likely have to
upgrade their systems to comply with the SWTR and the TCR. The
number of filtered systems expected to be impacted is approxi-
mately 5128 of an estimated 6919 total filtered water systems.
1.3 Market Imperfections, The Need for Federal Regulation/ and
Consideration of Regulatory Alternatives
Regulation of drinking water is different from most other
EPA regulations. Unlike environmental protection regulations
(e.g., NPDES), the, contaminant to which the public is actually
exposed is the direct object of regulation. The point of
regulatory intervention is, therefore, the performance of public
water systems.
Another unique feature that distinguishes drinking water
regulations is the fact that a transaction occurs between the
public water system and the consumer. Although this transaction
is subject to numerous market imperfections, resulting in a
flawed price signal to the consumer, the mere fact that there is
a transaction permits insights into the consumer's "willingness
1-3
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to pay" for drinking water. Analysis of benefits therefore need
not be confined to the conventional "damages avoided" approach
used in the development of most environmental regulations.
Public water supply is an example of a natural monopoly. It
would not be efficient to have multiple suppliers competing to
serve the same community. A natural monopoly is an example of
"market failure." The competitive forces that would normally
shape "production" decisions are absent.
There are two fundamental imperfections affecting the pro-
vision of public water supply: imperfect revelation of consumer
preferences and flawed pricing policy. Water has traditionally
been underpriced, partially because a number of important attri-
butes related to the historical abundance and purity of available
sources have been taken for granted and thus not been reflected
in the price signal or the demand response. As an essential
element of infrastructure, the reliability and safety of water
supply is taken for granted by society as a whole. Yet these
infrastructure related attributes are not reflected in any
transactions.
With respect to flaws in the revelation of consumer prefer-
ences, there is evidence, as reflected in the rapid sales growth
of point-of-use devices and bottled water, that there is a
consumer "willingness to pay" for an extra margin of safety.
Although this is revealed in the markets for these substitute
goods, it is not revealed in the transaction between public water
systems and consumers.
It is this "extra margin of safety" desired by consumers and
by society as a whole, that justifies Federal intervention. The
need for a margin of safety is reflected in the statutory lang-
uage of both the 1974 and 1986 Acts. The SDWA states that "each
maximum contaminant level goal... shall be set at the level at
which no known or anticipated adverse effects on the health of
persons occur and which allows an adequate margin of safety."
. The "market failure" induced by conditions of natural mono-
poly is a failure of the mechanism of "private choice" to reveal
preferences through consumer response to prices. This failure is
evident in both publicly owned and privately owned (but publicly
regulated) water systems. It is a condition that cannot be fully
corrected at the state and local levels of government due to
imperfections in the "public choice" processes by decisionmakers
at these levels.
In previous rulemaking actions, the Environmental Protection
Agency had the flexibility of considering alternatives ranging
from the establishment of a maximum contaminant level (MCL) to a
monitoring requirement to developing and making health advisories
available to state and local entities. The Agency does not have
that flexibility with respect to the Surface Water Treatment Rule
and the Total Coliform Rule. The Congress, in the 1986 Safe
1-4
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Drinking Water Act Amendments, requires the Agency to "promulgate
... regulations specifying criteria under which filtration ... is
required as a treatment technique for public water systems sup-
plied by surface water sources." Through the use of such speci-
fic language, the Congress, in effect, limited the range of
alternative regulatory strategies that could be considered.
In developing the SWTR, the Agency was thus limited to con-
sidering a number of filtration/disinfection policy alternatives
of varying stringency and impact. The four options considered
range from a mandatory filtration requirement with no exceptions
to provision of exceptions for water systems having two points of
redundant disinfection and which can achieve a 3-Log removal of
Giardia cysts and a 4-Log removal of enteric viruses.
Four different turbidity policy alternatives also were con-
sidered. These four alternatives range from Alternative 1—
keeping the same turbidity standard as it now exists in the
NIPDWR (i.e., not to exceed 1.0 NTU on a monthly average basis)
to Alternative 4 ~ requiring a turbidity of less than 0.4 NTU 95
percent of the time with an average turbidity of approximately
0.2 NTU. The purpose of the turbidity requirement is to measure
filtration effectiveness.
EPA is proposing to change the current coliform MCL, which
is based on density limits for single samples and a monthly
average, to one based on the presence or absence of coliforms in
a single sample. The minimum number of samples that a system
serving fewer than 3300 persons must analyze will increase,
thereby reducing the potential for "false negatives." Smaller
systems will have to collect and analyze a minimum of five
samples per month. As an option, periodic sanitary surveys may
be substituted for some monitoring, at state discretion. Larger
systems with unfiltered supplies will have to conduct sanitary
surveys on a more frequent basis.
1.4 Assessment of Total Costs
The proposed surface water treatment rule has potential cost
impacts on four groups of public water systems:
1. 1346 unfiltered community surface water systems
2. 1536 unfiltered non-community surface water systems
2882 total unfiltered water systems
3. 4611 filtered community surface water systems
4. 2308 filtered non-community surface water systems
6919 total filtered water systems
All 2882 unfiltered surface water systems will be affected
by the surface water treatment rule to at least some degree.
However, there are procedures for obtaining an exception to the
filtration requirement which could reduce the cost impact on some
of those systems.
1-5
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Of the 6919 filtered surface water systems, it is estimated
that 5128 will incur compliance costs. Of these 5128 systems, it
is estimated that 1409 are in violation of the current turbidity
MCL. The increment of cost required for these 1409 systems to
comply with the current standard was not included in the total
cost of complying with the proposed surface water treatment rule.
The total projected cost of the surface water treatment rule
is as follows:
Capital Cost Annualized Cost
($Millions) ($Millions/Yr.)
Unfiltered Systems 1613 216
Filtered Systems 333 95
State Implementation 0 28
TOTAL 1946 . 339
These totals are based on costs for Alternative C—
exceptions are allowed for systems providing disinfection
sufficient to achieve a 3/4 log removal of Giardia and viruses.
As many as 457 systems (16% of total unfiltered systems) are
conceivably eligible candidates for an exception. The total
annual cost estimate of $311 million is intended to represent the
total "social" cost to the nation for purposes of making bene-
fit/cost comparisons.
A "worst case" analysis was also performed in which it was
assumed there is no provision for unfiltered systems to obtain an
exception to the filtration requirement. On this basis, the
total capital cost to unfiltered systems is estimated to be
$2.423 billion and the total annualized cost using a three per-
cent discount rate is estimated to be $308 million. Thus, by
comparison, the exception provisions (of Alternative C) will
reduce required capital outlays by about $810 million and annu-
alized costs by $92 million dollars.
Costs of installing filtration have been estimated at the
system level for various water system size categories. The total
national cost for the 2882 currently unfiltered systems was esti-
mated using a procedure of forecasting likely compliance choices.
Compliance choices of 2867 of these unfiltered systems which each
serve fewer than 100,000 people are projected to be as follows:
457 Systems Seek An Exception To The Filtration Requirement
899 Systems Switch To An Alternate Source (Ground or Purchased)
221 Systems Install A Package Treatment Plant
58 Systems Install Conventional Treatment
1-6
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89 Systems Install Direct Filtration
115 Systems Install Diatomaceous Earth Filtration
990 Systems Install Slow Sand Filtration
38 systems Install Ultrafiltration
.Special attention must be given to the large proportion of
total costs attributable to the 15 unfiltered systems serving
greater than 100,000 persons each. These 15 systems account for
approximately 42 percent of total costs in the worst case scen-
ario. These 15 systems also account for approximately 75 percent
of the estimated 21.4 million people exposed to unfiltered sur-
face water.
The total national cost of the proposed turbidity require-
ment (i.e., for filtered systems) was estimated via a methodology
using survey data from a stratified random sample of over 500
plants. The net effect of the proposed turbidity requirement
will cause 3719 additional systems to undertake compliance
actions to reduce turbidity. The total national capital cost to
comply with the turbidity requirements is $333 million. The
total annualized cost is estimated at $95 million. •
State implementation costs for the SWTR are estimated at
$111.45 million. It is assumed that these costs will be spread
over a four year period, thus resulting in an annualized cost of
$27.86 million.
The cost of the Total Coliform Rule was estimated assuming
maximum state flexibility (i.e., allowing reduced monitoring
frequencies if conditions warrant) and with no assumed state
flexibility. Assuming maximum state flexibility, total estimated
costs amount to $70 million, $46 million for non-community sys-
tems and $24 million for community systems. Assuming no state
flexibility, the total estimate is $170 million, $126 million for
non-community systems and $44 for community systems.
1.5 Assessment of Benefits
.The Surface Water Treatment Rule (SWTR) must be viewed as
two sets of requirements forming a comprehensive strategy to pre-
vent microbial contamination in surface water systems. Since
costs differ between filtered and unfiltered surface water sys-
tems, benefits are evaluated in separate analyses.
.- f The economic benefits of drinking water standards may be
defined as the total willingness to pay for safe potable water.
The safety attribute of the good is the relevant aspect of demand
to be the focus of analysis. The willingness to pay for safety
in drinking water may be regarded as consisting of two compo-
nents: 1) the expected value of the damages that would be incur-
red in the absence of the standard; and 2) the value of an extra
margin of safety which provides assurance to consumers, and to
society as a whole, that it can be taken for granted the water is
safe to drink.
1-7
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Given the current state of economic research related to
drinking water, it is not possible to quantify the latter of
these two components. There is evidence from several places
which indicates the second component of the willingness to pay
for safe drinking water may be quite significant. This missing
component of benefit .must therefore be kept in mind while Review-
ing results of analyses based on the narrower concept of the
expected value of quantifiable damages.
The annual expected value of the damages resulting from
incidence of waterborne disease were hypothetically computed for
15 large unfiltered systems serving more than 100,000 persons and
for a gradient of nine smaller size categories serving between 25
and 100,000 persons. In each case, the estimated annual losses
from waterborne disease were compared to the estimated annual
cost of installing filtration. The primary conclusion to be
drawn from the results is that a positive net gain from install-
ing filtration is feasible in all but the three smallest system
size categories (systems serving <1000 persons).
The analysis assumes the endemic level of waterborne disease
to be 1.0 percent of the exposed population per year in systems
serving fewer than 100,000 persons and 0.5 percent of the exposed
population in systems serving more than 100,000. The annual
probability of outbreak of waterborne disease was evaluated under
two assumptions: one per 50 years, and one per 100 years. If the
assumptions used are reasonable, these results imply that the
central thrust of the Surface Water Treatment Rule to initiate a
national effort to re-assess the need for filtration is a worth-
while undertaking on the basis of the expected value of quantifi-
able damages alone.
At the national level, all that can be assessed is the over-
all reasonableness of the proposal because costs and benefits are
ultimately site-specific. The Safe Drinking Water Act specifies
that state regulators will make case-by-case determinations of
the need for filtration. Given the extremely site-specific
nature of the key variables which enter into the decision, this
approach to implementation is very appropriate.
Of course, filtration is only one approach to preventing
waterborne disease outbreaks. There are disinfection and moni-
toring strategies for obtaining an exception to the filtration
requirement and turbidity performance requirements for systems
which already filter. These two types of compliance activities
impose costs which can be measured against the same benefits—
the damages avoided by preventing waterborne disease.
In light of results for filtration, the analysis of net
social gains for systems obtaining an exception is self-evident.
If the same damages can be avoided at significantly less cost.
net gains will be significantly greater.
1-8
-------
The prospects for net social gains from the turbidity per-
formance requirement were evaluated for hypothetical water sys-
tems of varying sizes. Net gains are overwhelming for all system
size categories serving more than 1000 people. For systems serv-
ing fewer than 1000 people, net losses appear, but there are many
caveats that apply to this result. One caveat is that many small
systems which have difficulty meeting performance requirements
may represent situations where an older plant is in need of
replacement.
The costs of the groundwater portion of the Total Coliform
Rule are different in concept from the costs to surface water
systems in that they relate to only one aspect — monitoring of
coliforms — of the total approach to avoiding contamination from
microbial Contaminants. The most significant requirement of the
Total Coliform Rule is an increase in the minimum number of sam-
ples (to five/month) which small water systems must collect and
analyze. The proposal is based on results of statistical anal-
ysis which has shown that the present level of monitoring in
small systems is inadequate to compensate for the probability of
obtaining false negatives.
The benefit of the Total Coliform Rule derives from the
value of the monitoring information it will provide. However,
given the technical findings which form the basis for the pro-
posal, it is clear that the value of such monitoring data is zero
(or negative) until a certain number of samples have been col-
lected and analyzed — the number proposed in the rule. Coliform
monitoring is a fundamental component of water treatment for con-
trol of microbial contaminants. Though the absence of coliforms
provides incomplete assurance that other pathogens are absent
also, the presence of coliforms is a fairly good indication there
is a problem worth investigating, conceivably involving a broad
range of disease agents related to fecal contamination. It is
believed the extra cost of obtaining a statistically reliable
number of samples would be deemed worthwhile by the public health
profession.
1.6 Regulatory Flexibility, Affordability, and Paperwork Reduc-
tion Analyses
Of the estimated 199,390 community and non-community water
supplies serving fewer than 50,000 persons, 2845 (1.4 percent)
have unfiltered surface supplies and are therefore subject to
compliance under the Surface Water Treatment Rule. of the
199,390 community and non-community water supplies serving fewer
than 50,000 persons, 6457 are served by surface supplies that
currently filter. Of this total, 4888 (2.5 percent of all public
surface water supplies serving less than 50,000) exceed the
proposed average turbidity performance requirement of 0.3 NTU and
therefore would not comply with the proposed rule.
1-9
-------
The proposed Total Coliform Rule would impose more stringent
total coliform monitoring requirements primarily on public water
systems serving fewer than 3300 persons. It is estimated that
there are 193,609 community and non-community water systems which
would be affected by these requirements. Of these, 193,588 serve
fewer than 50,000 persons.
EPA guidelines on compliance with the Regulatory Flexibility
Act indicate that, in general, a "substantial" number of small
entities is more than 20 percent of the total. Therefore, by the
20 percent rule, the proposed coliform regulations would affect a
"substantial" number of small water utilities.
The coliform rule will impact primarily systems which serve
fewer than 3300 persons. The total annual costs of the rule will
be between $70 million and $170 million. These annual costs will
be distributed across a large number of systems, however, and
will not produce more than a one or two percent increase in the
average overall cost of production.
The range in the cost estimate for the coliform rule is
attributable primarily to the flexibility and discretion afforded
to state primacy agencies in implementation. State flexibility
and discretion is important for other portions of the regulations
as well. The filtration proposal intentionally avoids setting
specific technological requirements, providing details on opera-
tion and design as guidance only. This will allow states exten-
sive flexibility for tailoring requirements to site-specific con-
ditions, thereby achieving maximum efficiency for small systems..
In addition to the wording of the proposed rule, the SDWA itself
incorporates exemption provisions which afford states the oppor-
tunity to mitigate economic impacts on small systems.
A detailed discussion of the number of water systems
affected by monitoring and paperwork requirements associated with
the proposed rules is provided in the Information Collection
Request Documents.
1-10
-------
2. PROBLEM DEFINITION
2.1 Microbial Contaminants and the Incidence of Waterborne Dis-
ease
Waterborne diseases can result when humans come into contact
with waters which contain harmful microbial organisms called
pathogens. These organisms may overcome the natural defenses of
the body and cause disease. In addition to cholera and typhoid
fever, other ailments and infectious diseases also can result
from consumption of contaminated drinking waters. The most
common of these are gastroenteritis, dysentery, and infectious
hepatitis. Whereas these infections are less likely to be fatal
than are cholera and typhoid fever, they can cause prolonged
illness and severe discomfort to the affected individuals. In
sensitive population groups, such as infants, the elderly, and
the already infirm, death can result. Exhibit 2-1 presents a
short list of some of the conventional microbiological contam-
inants of drinking water and the diseases they cause.
The fact that each of these diseases can be transmitted by
drinking water is well known. The various disease-causing
organisms — various types of bacteria, viruses, and cysts—
typically enter the water as a result of unsanitary practices.
The most common sources of contamination are from human and
animal waste deposits in the watershed, leaking sewers or septic
tanks, cross-connections with other sources of water, or back
siphonage resulting from negative pressure in the water distri-
bution system.
Prior to the introduction of chlorine as a water disin-
fectant in this country in 1908 and its subsequent widespread use
in the U.S. and other countries, waterborne diseases were
prevalent. Microbiological contamination of drinking water
sources first became a large-scale public health problem as a
result of the migration of large numbers of people to cities
during the Industrial Revolution. An 1848 cholera epidemic in
London in which over 14,000 people perished is often cited as the
most devastating example of a waterborne disease outbreak.
It was not until the period between 1850 and 1900 that the
presence of microorganisms was correlated with the incidence of
various diseases (the Germ Theory of disease) and microbiological
contamination of water supplies was identified as an important
disease vector. These discoveries led to a flurry of activity in
the water treatment field in the early part of this century,
which has been referred to as the "Great Sanitary Awakening.1*
Widespread adoption of filtration and disinfection techniques in
the early to mid-1900s as standard treatment practices led to a
marked reduction in the incidence of waterborne disease, as
illustrated in Exhibit 2-2.
2-1
-------
EXHIBIT 2-1
WATERBORNE ILLNESSES AKD CAUSATIVE AGENTS
ILLNESS
AGENT
Typhoid fever
Paratyphoid fever
Bacillary dysentery
Cholera
Amoebic dysentery
Infectious hepatitis
(Hepatitus A)
Giardiasis
Gastroenteritis
Salmonella typhi. (bacterium)
Salmonella paratyphi. (bacterium)
Shiqella spp., (bacterium)
Vibrio cholerae. (bacterium)
Endamoeba histolytica. (protozoan)
Hepatitis A Agent (virus)
Giardia Iambiia. (protozoan)
Rotavirus, Norwalk Agent (viruses)
Campylobacter j e~i uni. Yersinia
enterocoliticus (bacteria), as well
as other bacteria and viruses
Source: U.S. Environmental Protection Agency, Microorganism
Removal for Small Water Systems. June, 1983, p. II-3.
2-2
-------
EXHIBIT 2-2
500.
Filtration begins
,Nov. 1.1907
Chlorination begins
/Fulltime- 1915
1.
1895.1900.19051 1910.1915.1920. 1925. 1930.
YEARS
Figure 1. Typhoid deaths over time
Source: Clark, R.M., Goodrich, J.A. and Ireland, J.C., "Cost and Benefits
of Drinking Water Treatment," Journal of Environmental Systems,
Vol. 14, 1984-85.
2-3
-------
Improvements in the level of sewage treatment provided
produced further public health benefits. By the 1950s, however,
the successful efforts at reducing waterborne disease outbreaks
had given way to a sense of complacency. Until the recent (i.e.,
1980s) upsurge in both the number of outbreaks and reported
cases, it was generally assumed that the waterborne disease
problem had been solved.
Exhibit 2-3 presents a summary tabulation of data regarding
reported waterborne disease outbreaks in three time periods:
1920-40, 1941-60, and 1961-83. In the 1920-40 period, typhoid
fever was the most frequent type of reported outbreak. There
were nearly 1000 deaths attributed to waterborne disease—
almost 900 from typhoid fever alone. By the 1941-60 period,
however, typhoid had fallen to second place in number of reported
outbreaks and accounted for only 54 deaths. In the 1961-83
period, typhoid fever ranked sixth in number of reported out-
breaks and accounted for no deaths. The availability of peni-
cillin and other antibiotics probably played a role in reducing
the number of deaths.
While the progress against death-causing diseases such as
typhoid fever is impressive, there is another pattern evident in
Exhibit 2-3 which gives rise to other public health concerns.
Both the number of reported outbreaks and the number of cases of
illness reported, after being reduced during the 1920-40 and
1941-60 reporting periods, reversed directions and increased
significantly between the 1941-60 period and the 1961-83 period.
Exhibits 2-4 and 2-5 illustrate this trend reversal graphically
on an annual basis.
Several factors, when considered together, can be offered to
explain this pattern:
!• Complacency In Reporting — Less attention apparently was
paid to reporting of waterborne diseases during the 1941-60
period in the belief that the problem had already been
solved. Improved reporting practices in the 1961-83 period
revealed there is more of a problem remaining than previously
recognized.
2. Poor or Inadequate O & M of Treatment Facilities — It is
well known that many water treatment plants are not operated
and maintained properly. Many others are not designed to
provide proper system reliability and redundancy. Many plant
operators also are not properly trained or educated. These
factors, along with an unwarranted confidence in the level of
protection afforded by the treatment processes in place,
probably contributed to the increased incidence in outbreaks
and cases.
3. Increased Vulnerability Due to Population Growth — Many
water systems that use undisinfected groundwater supplies or
only disinfect prior to distribution, were deemed adequate
2-4
-------
EXHIBIT 2-3
ETIOLOGY OF WATERBORNE OUTBREAKS
1920-83
TIME
PERIOD
1920-40
X941-60
1961-83
Source:
DISEASE
Typhoid Fever
Gastroenteritis
Shigellosis
Amebiasis
Hepatitis A
Chemical Poisoning
TOTAL
Gastroenteritis
Typhoid Fever
Shigellosis
Hepatitis A
Salmonellosis
Chemical Poisoning
Para-Typhoid Fever
Amebiasis
Tularemia
Leptospirosis
Poliomelitis
TOTAL
Gastroenteritis
Giardiasis
Chemical Poisoning
Shigellosis
Hepatitis A
Typhoid Fever
Salmonellosis
Viral Gastroenteritis
(Norwalk)
Campy lobacterios is
Toxigenic £. coli
Gastroenteritis
Amebiasis
Viral Gastroenteritis
(rotavirus)
Cholera
Yersiniosis
Para-Typhoid Fever
TOTAL
Craun. Gunther F. An Overview
Water Contamination Problems.
NUMBER OF
OUTBREAKS
372
144
10
2
1
1
530
265
94
25
23
4
4
3
2
2
1
1
424
266
84
55
52
51
19
17
16
5
5
3
1
1
1
^
577
of Statistics
Presented at
CASES OF
ILLNESS
13,761
176,725
3,308
1,416
28
92
195,330
54,439
1,945
8,951
930
31
44
19
36
6
9
16
66,426
86,740
22,897
3,788
7,462
1,626
330
18,951
3,973
4,773
1,188
39
1,761
17
16
5
153,566
on Acute and
DEATHS
889
2
0
98
0
0
989
3
54
8
0
0
4
0
2
0
0
0
71
0
0
7
6
1
0
3
0
0
4
2
0
0
0
0
23
Chronic
Fourth Domestic Water
Quality Symposium, December, 1985.
2-5
-------
EXHIBIT 2-4
WATERBORNE DISEASE OUTBREAKS
1920-1983
ro
40
30
20
10
NO DATA
FOR 1937
20253035404550556065 70 75 80 83
YEAR
Source: Craun, Gunther, F. An Overview of Statistics on Acute and Chronic Water Contamination
Problems. Presented at Fourth Domestic Water Quality Symposium, December, 1985.
-------
EXHIBIT 2-5
CASES OF WATERBORNE DISEASE
1920-1983
to
I
20000-
15000-
10000-
50OO-
0
/
'
,
/
/
J ?
' /
/ /
/
/
49C
r
J.
s
/
/ ^
>
y
f
s
y /
/ ^
^
y /*
^2
li
M
31697
INO DATA '
IFOR 1937 i
/
/
/
^
f
',
',
X
4
/
/
/
/
x
/
X
/
Y
^Int/
^
x
•J
^
£ '
/ ,
' ^ pii
^ /
/ /
41&4
^ /
/ ' /
J /
/ ^
^ /
J x •*
X / /
^ / '
/ ^ x
^ /
r
/•
/
y
/*
-
j
~
y
'
/
x
/
y
f
PVi
TrM
,
/
^
'
/
'
/
'
X
^
^
171 '
M ra ^3i__ ^
^^2 l/f v^fnLf^^jfJV
/ R P
/ rKJ K
^vd/V'vS
><
y<
J
/
J
^
/
/
Bf '
^K '
TTT
'
jl
/
' ^
^ ^
/ /
X
/•
/<
^
/
'/
',
/
> 7
¥TT
!
/ 3
' < r
' ^
/ '
/ '
/
/
/
f
20 25 30 35 40 45 50 55 60 65 70 75 80 83
YEAR
Source: Craun, Gunther F. AnOverview of Satistics on Acute, and Chronic Water Contamination
Problems. Presented at Fourth Domestic Water Quality Symposium, December, 1985.
-------
for decades. With growing populations and the associated
increase in the number of sources of contamination, many of
these same systems have become vulnerable to contamination.
A number of systems have not responded to changing population
and growth patterns and, as a result, can no longer with
certainty provide water that is free of disease causing
microbial agents.
4. Changes In the Nature of The Contaminants — The current
level of infestation of Giardia Iambiia appears to be a
recent phenomenon. There may have been recent genetic
changes in Giardia causing it to be more infective or
virulent. Alternatively, Giardia could have simply escaped
identification until recently due to the difficulty of
detection and analysis. Other new disease agents such as
Legionella and Crypto sporidium also have recently been
identified.
5. Use of Inadequate Indicator Organisms — it has long been
recognized that the standard organism used as an indicator of
microbiological safety for more than half a century is
inadequate. The total califorms test, although a useful
tool, does not detect or quantify viruses, protozoan cysts,
or other disease causing agents that may be in the water.
Outbreaks of giardiasis in Camas, Washington and in Colorado
occurred in water supplies that were in compliance with the
microbiological standard included in the NIPDWR, thus
demonstrating the shortcomings of the coliform test and the
current maximum contaminant level (MCL) with respect to
protection of the public health.
Available evidence suggests that each of these factors is a
contributor to current observed trends of increasing incidence in
waterborne diseases. Yet no one of them is completely respons-
ible for the trends observed.
With respect to the first factor, it is a well documented
fact that there is significant underreporting of waterborne
diseases.1'2 Poor or inadequate operation and maintenance of
treatment facilities is likewise well documented. Data on
reported waterborne disease outbreaks indicate that faulty O&M of
filtration and disinfection processes or lack of redundancy is
^•Hopkins, R., et al., "Waterborne Disease in Colorado: Three
Years Surveillance and 18 Outbreaks," American Journal of Public
Health. Vol. 73, No. 3, 1985.
2Jakubowski, W., et al. "Methods for Detection of Giardia
Cysts in Water Supplies." In: Jakubowski and Hoff.
2-8
-------
frequently a causal factor.3 Distribution system failures also
account for a large proportion of outbreaks.
Regarding the third factor, data on reported outbreaks
indicate that the lack of filtration and disinfection treatment
processes is often responsible for outbreaks. This typically
occurs in those water systems that did not install filtration or
disinfection because of the absence of nearby sources of contami-
nation.4 Exhibits 2-6 and 2-7 illustrate the relative contri-
butions of the major water supply deficiencies in reported out-
breaks over the 1971-85 period.
As noted above, the nature of waterbome disease causing
agents is changing. It is notable that the first confirmed
outbreak of giardiasis occurred in 1965, yet Giardia has ac-
counted for the largest number of reported outbreaks every year
since 1978. It is likely that giardiasis had been diagnosed as
the more generic "gastroenteritis" for some indeterminate period
prior to 1965. The largest outbreak of giardiasis is believed to
have infected over 50,000 people in Portland, Oregon in 1954-55.
The etiology was never officially confirmed, but it is strongly
suspected to have been a giardiasis outbreak.
Because the number of pathogens in the water is extremely
low and because they occur in wide variety, they are difficult to
isolate and quantify. Measurement of coliform organisms has thus
been the standard indicator of microbiological "safety" for
decades. The presence of coliforms suggests that pathogens may
also be present. However, the absence of coliforms does not
necessarily indicate that the pathogens have been removed.
Health professionals who specialize in drinking water now
recognize the necessity of monitoring for specific organisms such
as Giardia lamblia. various strains of viruses, and organisms
such as Crypto sporidium. The scientific community did not have
this knowledge regarding specific pathogens (or the ability to
detect them routinely) in the 1940-1970 period. Enhanced
knowledge and somewhat better analytical techniques have contri-
buted toward the recent increase in reported outbreaks and cases.
Despite recent increases in the number of reported out-
breaks, it should not be concluded that protection from microbio-
logical contamination of drinking water is subsiding or declin-
ing. The number of cases of reported illness must be viewed in
light of changes in reporting practices and population growth.
3Craun, Gunther F. "An Overview of Statistics on Acute and
Chronic Water Contamination Problems," Presented at: Fourth
Domestic Water Quality Symposium, December, 1985.
4Ibid.
2-9
-------
EXHIBIT 2-6
WATER SUPPLY DEFICIENCIES RESPONSIBLE
FOR WATERBORNE OUTBREAKS
1971-85
SOURCE OF
DEFICIENCY
OUTBREAKS
REPORTED
ILLNESSES
Surface Water Source:
Untreated
Disinfection Only, or
Inadequate Disinfection
Disinfection With Other
15
67
Source: Craun, Gunther F., May, 1987.
2-10
1,458
23,028
Treatment
Filtration
Totals
Ground Water Source:
Untreated
Inadequate Disinfection
Disinfection With Other
Treatment
Totals
Distribution System:
Cross-connection
Contamination of Mains/Plumbing
Contamination of Storage
Corrosive Water
Totals
GRAND TOTAL
Outbreaks
Illnesses
4
-20
106
154
90
_i
245
44
14
11
-JLP.
79
(REPORTED)
98
9.852
34,436
- -
11,266
40,893
22
52,181
8,124
3,413
-6,244
147
17,928
430
104,545
-------
EXHIBIT 2-7
WATERBORNE OUTBREAKS OF GIARDIASIS CLASSIFIED BY TYPE OF
WATER TREATMENT OR WATER SYSTEM DEFICIENCY
1965-1984
WATER
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
SOURCE AND TREATMENT/DEFICIENCY
Surface water source, chlorination only*
Surface water source, filtration
Surface water source, untreated
Cross-connection
Groundwater, untreated:
a. well water source
b. spring source
Groundwater, chlorination only
a. well water source
b. spring source
Contamination during main repair
Contamination of cistern
Consumption of water from nonpotable-tap
Consumption of water while swimming, diving
Insufficient information to classify
TOTAL
OUTBREAKS
39
15
12
4
4
2
2
2
2
1
1
2
_i
90
CASES
12,088
7,440
322
2,220
27
44
126
29
1,313
5
7
90
65
23,776
,.* Includes three outbreaks and 76 cases of illness where filtration was
available but not used. In one outbreak filtration facilities were used
intermittently and in two outbreaks filtration facilities were bypassed.
'Source: Craun, G.F., and Jakubowski, W. "Status of Waterbome Giardiasis
; Outbreaks and Monitoring Methods." American Water Resources
Assoc., Water Related Health Issues Symposium, November, 1986,
Atlanta.
2-11
-------
Craun5 points out that the population rate of reported waterborne
illness has declined from eight cases per 100,000 person-years
during 1920 to 1940 to four cases per 100,000 person-years during
1971 to 1983. Thus, despite the recent rise in the number of
cases reported, the rate of incidence relative to population
appears to have declined. Considering the difference in report-
ing practices, the decline in incidence may be even more signifi-
cant than indicated by this comparison.
A more refined set of outbreak data for shorter and more
recent time periods is presented in Exhibit 2-8. Several trends
are evident. As suspected, the number of outbreaks labelled as
gastroenteritis, often meaning the specific etiology was not
confirmed, has decreased in the 1980s reflecting the new aware-
ness of giardiasis and improved methods of identifying viral
pathogens. The number of outbreaks attributed to giardiasis has
thus risen accordingly as indicated by these data. The number of
outbreaks attributed to viral pathogens appears to have stabi-
lized while the number of outbreaks attributed to bacterial
agents appears to be declining.
One hypothesis which explains these patterns is that the
types of treatment processes installed in the earlier part of
this century — when properly operated and maintained — are
succeeding to some degree in removing or inactivating conven-
tional microbial contaminants such as enteric bacteria, but are
less successful in controlling Giardia cysts and viruses.
This hypothesis is consistent with recent research findings
regarding; treatment effectiveness. Giardia and viruses are much
more resistant than bacteria to chlorination. Giardia cysts and
viruses are able to pass through filtration plants which are
poorly operated and maintained. Moreover, recent research
indicates that viable Giardia cysts and viruses occur in finished
waters which meet present coliform standards and contain a 0.2
mg/1 chlorine residual as recommended in the NIPDWR. As noted
above, outbreaks of disease have been documented in systems that
comply with the present coliform standard (e.g., Camas and
Leavenworth, WA). Moreover, it has been shown that both cysts
and viruses can pass through filtration plants meeting the
current turbidity standard of 1.0 NTU.6
Giardia and viruses are not the only "new" pathogens of
concern in the water industry. Leoionella and an entire class of
organisms called "opportunistic pathogens" have generated new
causes for concern in drinking water treatment. The Organisms In
5Ibid.
6U.S. EPA - Office of Drinking Water, Technologies And Costs
For Removal of Microbial Contaminants From Potable Water Supp-
lies. February 1987.
2-12
-------
EXHIBIT 2-8
WATERBORNE DISEASE OUTBREAKS
1946-1983
1946-801
1972-812
1981-833
Bacterial
Viral
Parasite
Chemical
Unknown
(Gastroenteritis)
_f_
146
79
48
49
350
672
i
22
12
7
7
52
_J_
40
21
50
41
181
335
%
12
6
15
12
55
JL.
10
11 -
38
8
-AS
112
4
9
10
34
7
40
1 Lippy, E.G. and Waitrip, S.C., "Waterborne Disease
Outbreaks — 1946-1980: A Thirty-Five Year Perspective," Journal
of the AWWA. February 1984.
2 Craun, G.F.,- and Jakubowski, W. , "Status of Waterborne
Giardiasis Outbreaks and Monitoring Methods," American- Water
Resources Association, Water Related Health Issues Symposium,
November, 1986, Atlanta, GA.
3 Center for Disease Control, "Foodborne and Waterborne
Disease Outbreaks, Annual Summaries, 1981, 1982, 1983." U.S.
Department of Health and Human Services, Atlanta, GA.
2-13
-------
Water Committee of the American Water Works Association (AWWA)
issued the following statement recently:7
"Anxiety about Leaionella may represent only the tip of
the iceberg as far as unknown pathogens are concerned.
Classic water treatment practice has focused on
reducing enteric pathogens. The coliform group has
been used as an indicator of either source water
acceptability or disinfection efficiency, because if
coliforms are present, enteric pathogens may also be
present and may have survived treatment. Such is not
the case with all pathogens. Leaionella and Lecrion-
ella-like organisms are pathogens that are transmitted
through aerosolization and inhalation rather than by
ingestion. Other pathogens with potential for trans-
mission through inhalation of drinking water aerosols
are Mycobacterium. Pseudomonas, and Klebsiella.
Microbial allergens may also present a problem."
"When they come into body contact, opportunistic
pathogens also are a concern, especially for hospital
patients. Waterbome organisms that have caused
secondary infections in hospitals include Pseudomonas
putida r P. multophila. P. aeruginosa. Acinetobacter
calcoaceticus. Alcaliaenes faecalis. and Flavobacteriun
species. The problem may be complicated further if
opportunistic pathogens become antibiotic resistant
through acquisition of plasmids from resistant bacter-
ia, thereby making patient treatment more difficult."
The AWWA committee's mention of "plasmids" -- a newly
popularized term in the lexicon of genetic engineering — brings
to mind a range of conceivable health concerns which could
ultimately have significance. As society stands at the door of
unprecedented breakthroughs in biotechnology, it is prudent to
consider the potential for additional threats to drinking water.
Massive efforts being applied to amelioration of damage from
toxic chemicals and hazardous wastes have revealed that drinking
water is a major exposure route through which the human health
side effects of chemical technology manifest themselves.
Reflection on the potential side effects of biotechnology suggest
that drinking water may once again be a significant exposure
pathway.
In summary, conventional water treatment processes provide
reasonably good protection against many common enteric pathogens,
such as coliform bacteria, when these systems are properly
operated and supported by back-up systems in the event of
7AWWA Organisms in Water Committee, "Committee Report:
Microbiological Considerations for Drinking Water Regulation
Revisions," Journal of the American Water Works Association. Vol.
79, No. 5, pp. 81-88, May, 1985.
2-14
-------
failure. However, the level of protection against other forms of
pathogens such as Giardia cysts, viruses, "opportunistic"
pathogens, and potential future pathogens of unknown variety, is
less complete given current operating practices. In many systems
where filtration and disinfection were not installed heretofore
due to the perceived absence of contaminant sources, that
determination should be reviewed in light of the present level of
population pressures and the current understanding of conceivable
microbial threats.
2.2 Available Treatment Technology: The Multiple Barriers Ap-
proach
The multiple barriers theory of sanitary engineering is
based on the belief that as many barriers as possible should be
erected between contaminants and their associated threat to
public health and consumers themselves. In its application to
the removal or inactivation of pathogenic microbial agents in
drinking water, this multiple barriers approach includes a
combination of treatment techniques. An example of a single
barrier would be some form of filtration (e.g., slow sand) or
combination of clarification and filtration. Adding disinfection
to filtration provides a second barrier. A good watershed
management program and performance of periodic sanitary surveys
provide additional barriers. Frequent monitoring can reveal
whether or not a water source is contaminated and the exact level
of contamination can be determined and compared to relevant
standards.
2.2.1 Monitoring
Detection of microbial contaminants through monitoring is
not simple due to the lack of effective analytical methodologies.
Monitoring for the presence of microbial contaminants is compli-
cated by the fact that their presence may be stochastic. That is
to say that their presence in relatively low numbers introduces
the possibility of false negatives when only a fixed volume of
water is sampled. Alternatively, they may be present in concent-
rated "slug flows" produced by natural population fluctuations or
man-made events (e.g., overflow of a sewage pump station) which
could escape detection completely if they pass through between
sampling intervals. Accurate detection is important due to the
fact there is no "safe" dose for microbial contaminants; one
Giardia cyst, for example, is sufficient to cause infection.
A second difficulty arises from the fact that detection and
identification of microbial contaminants is a time-consuming,
labor intensive process. Sampling for many organisms involves
incubation to stimulate the growth needed for identification.
Other contaminants, including Giardia lamblia. often require a
microscope to confirm their presence. Such measurements provide
useful data with which to confirm or assess the effectiveness of
2-15
-------
treatment retrospectively; however, the lag time involved makes
them useless as "real-time" indicators of plant performance.
Two types of biological analyses are typically performed in
the water industry. The predominant type of analysis is for
coliform bacteria. This test is relatively inexpensive and, as a
result, multiple tests are periodically performed as a way of
reducing the probability of false negatives.
One of the functions of the total coliform analysis is to
document the effectiveness of disinfection. Coliform samples are
collected at representative points in the distribution system to
assure that a residual is maintained, thus preventing bacterial
regrowth at the extremities of the distribution network.
The heterotrophic plate count (HPC) reveals the presence of
the entire spectrum of disease-causing bacteria. Performed only
occasionally, it is a useful supplement to coliform monitoring
because different pathogens respond differently to treatment
processes. The rate of waterborne diseases outbreaks in systems
meeting coliform standards is low, but as noted earlier, it is
not zero.
Physical and chemical measurements are used as "real-time"
or continual indicators of treatment plant performance. Turbid-
ity and chlorine residual are typically measured for this
purpose.
In filtration plants, turbidity is an indicator of the
efficacy of the treatment process in removing particulate matter.
This particulate matter may interfere with disinfection by
coating, adsorbing, or otherwise shielding the microbes from
contact with the disinfectant. This interference with the
disinfection process may be sustained in the water distribution
system where secondary regrowth of microbes may occur.
Measurements of turbidity, pH, temperature, contact time,
and chlorine residual provide plant operators with the necessary
data to assess the effectiveness of disinfection on a real-time
basis. Additionally, measurement of chlorine residual in the
distribution system provides some assurance against secondary re-
growth .
Biological, physical, and chemical indicators of treatment
effectiveness are inadequate when considered on an individual
basis. Together however, they provide substantial insight into
the process. Even with all the data provided by these indi-
cators, a degree of uncertainty remains. It was recently found,
for example, that enteric viruses can occur in filtered finished
water which meets current coliform (1/100 ml) and turbidity (1.0
NTU) standards and contains >0.2 mg/1 free chlorine.8
8Qp. c_it., note #6 supra. pp. 11-14.
2-16
-------
Throughout the period since the "Great Sanitary Awakening,"
sanitary engineers have incorporated routine monitoring in their
"treatment" strategies for removing microbial contaminants from
drinking water. It would be impractical to attempt a simple
"black box" approach to water treatment design that guaranteed
removal through over-compensated application of hardware and
chemicals. The information provided by an integrated biological/
physical/chemical monitoring strategy is a much more economical
way to offset the uncertainty inherent in the problem.
2.2.2 Treatment
The fundamental strategy employed in treating drinking water
for removal of microbial contaminants is referred to as the
"multiple barriers" approach. The objective is to employ a
combination of physical and chemical means of removing or
inactivating microorganisms. The number and extent of barriers
used in any individual treatment process has typically been a
function of the level of perceived risk of microbial contamin-
ation as indicated by monitoring data.
For example, there are a large number of undisinfected
groundwater systems in the U.S. This situation has evolved
largely from the rationale that treatment of groundwater is
unnecessary where there are no sources of contamination. In
surface water treatment, the degree of treatment necessary has
been regarded as being a function of the influent raw water
quality. Surface waters in some parts of the country are
regarded as being so pristine that only disinfection is neces-
sary. In other municipalities, direct filtration (followed by
disinfection) is believed to represent adequate treatment. A
majority of surface water sources, however, require full conven-
tional treatment, consisting of chemical addition, coagulation,
sedimentation, filtration, and disinfection.
Another aspect of the multiple barriers strategy concerns
the need for back-up systems in the event of system failure.
This need has become apparent as a result of reported waterborne
disease outbreaks, a significant proportion of which have been
attributed to system failures.
The one principal shortcoming in the legacy of the "Great
Sanitary Awakening" is that it provided no mechanism for improv-
ing or updating the multiple barriers approach once in place. In
fact, once treatments are initially installed, a sense of
complacency can develop in the belief that the problem has been
solved. Installation of capital equipment is too often regarded
as the major step in solving the problem, drawing emphasis away
from the role of proper operation and maintenance as an equally
important part of the solution.
The record of reported outbreaks of waterborne disease
indicates that the major deficiencies in water treatment can be
classified into the following major groups:
2-17
-------
o absence of treatment in places where the need was not
previously apparent;
o presence of only a single barrier and/or the absence of
back-up systems;
o presence of one or several barriers, but with inadequate
operation and maintenance to assure efficacy;
o presence of one or several barriers with a level of
efficacy and/or a level of operation and maintenance
which is no longer adequate in light of evidence regard-
ing some of the "newer" varieties of contaminants.
EPA has identified a number of forms of surface water
treatment which, when operated to sufficiently stringent perform-
ance standards, have the demonstrated capability to assure
removal of microbial contaminants with a high degree of confi-
dence, including the "newer" contaminants of concern.9 Three-log
removal efficiencies (i.e., 99.9%) for Giardia cysts and four-log
removal efficiencies (i.e., 99.99%) for viruses have been
documented when filtration and disinfection are both adequately
deployed and operated. The specific filtration technologies
identified by EPA include the following:
o conventional treatment;
o direct filtration;
o diatomaceous earth filtration;
o slow sand filtration;
o package treatment systems;
o ultrafiltration; and
o cartridge filters.
Detailed descriptions of these technologies are provided in
EPA's "Cost and Technology Document" referenced earlier.
2.3 Exposure Profile of Public Water Systems
Microbiological contaminants are ubiquitous in the raw water
in all surface water supplies and many groundwater supplies. The
"occurrence" of these contaminants in finished water must
therefore be assessed in terms of both the presence and efficacy
of appropriate treatment technology (barriers). Both approaches
have been pursued, resulting in the production of three sets of
"occurrence data."
9OP. cit.. note #6 supra.
2-18
-------
The Association of State Drinking Water Administrators
(ASDWA) conducted a survey10 in which each state was asked to
perform a census of the type of treatment-in-place in surface
water systems and the extent of disinfection in place in surface
and groundwater systems.11 These data were then used to
construct a statistical profile of the situation nationwide. In
a second part of the ASDWA survey effort, states provided data on
finished water turbidity performance from a random sample of over
500 surface water systems.
To assess the performance of both surface and groundwater
systems in removing coliforms, the extent of violation of the
existing MCL for coliforms was evaluated by a sort of the
compliance monitoring results in the FRDS data base.
These three sets of "occurrence data" are summarized below;
they also form the basis for the assessment of total national
costs and benefits discussed in Chapters 4 and 5.
2.3.1 Number of Unfiltered Water systems And Population Exposed
Exhibit 2-9 presents data on the number and size of filtered
and unfiltered community surface water systems.12 A key finding
of the ASDWA survey is that purchased surface water is, for the
most part, filtered. Notable exceptions in areas such as New
1°Survey To Support Analysis of The Impacts of Proposed
Recrulations Concerning Filtration and Disinfection of Public
Water Supplies. Association of State Drinking Water Administra-
tors, September 22, 1986.
11The type of treatment-in-place is currently an optional
reporting item in the EPA Office of Drinking Water's Federal
Reporting Data System (FRDS) . Thus, the lack of a response is
interpreted as a lack of treatment. For example, a recent sort
of FRDS indicated the presence of 2984 community surface water
systems (in the fifty states and Puerto Rico) which Jllack"
filtration. This is more than twice the number indicated by
results of the ASDWA survey.
12The ASDWA estimate is for the fifty states and Puerto
Rico. The total number of community surface water systems
actually producing (vs. purchasing) surface water is estimated by
ASDWA to be 5957. This compares roughly to the FRDS estimate of
6400. It is not clear which is correct. Much of the difference
may be attributable to variable interpretations of the definition
of a surface water system. In many cases, for example, springs
are counted as surface water systems in FRDS while they were
considered groundwater systems by respondents to the ASDWA
survey. The discrepancy between the two estimates is centered in
the small system size categories where there are a number of
uncertainties present in both FRDS and the ASDWA data. ASDWA
survey results are used in the analysis.
2-19
-------
EXHIBIT 2-9
NUMBER OF COMMUNITY WATER SYSTEMS (PLANTS) HAVING FILTERED VERSUS
UNFILTERED SURFACE HATER SUPPLIES BY SIZE CATEGORY
AND ESTIMATED POPULATION SERVED
Community Water System Size Categories
25 101 501 1001 3301 10,001 25,001 50,001 75,001 100,001 500,001
to to to to to to to to to to to 1,000,000
100 500 1000 3300 10,000 25,000 50,000 75,000 100,000 500,000 1,000,000 + TOTALS*
Filtered 523 474 537 814 996 501 303 114 98 166 10 12 4611
Niwber
of
Plants Unflltered 310 305 217 226 160 65 25 13 10 93 3 1316
or
to Systens
^ Total" 833 779 754 1010 1156 569 328 157 108 175 13 15 5957
O
Filtered 0.08 0.51 1.11 3.87 9.22 11.66 15.02 9.55 9.25 31.78 19-97 18.51 133.56
Estimated .
Population
Served Unfiltered 0.02 0.08 0.17 0.45 0.97 0.98 0.88 0.76 0.85 1.98 2.11 11.55 21.10
(•ill ions)
Total1 0.09 0.57 1.28 4.33 10.20 12.64 15.91 10.31 10.09 36.77 22.38 30.09 151.66
•Totals may not add due to rounding.
Source: Association of State Drinking Water Administrators, A Survey to Support Analysis of Proposed Regulations Concerning
filtration and Disinfection of Public Water Supplies, September, 1986.
-------
York City and Boston were taken into account. The "number of
systems" data represent only systems which actually produce water
from surface sources. The "population exposed" data represent
both direct and indirect (i.e., those on purchased water systems)
consumers of surface waters. It is assumed that purchased water
relationships will be unchanged. That is, systems selling-
surface water will install required treatments at levels of
capacity equivalent to their current internal and external
requirements.
Some uncertainty about treatment-in-place exists even at the
state level with regard to the very small system size categories.
Thus, ASDWA results for community surface water systems are
stated as a range, as follows:
Unfiltered Systems Population Exposed
Low Estimate 1210 21.07 million
Most Probable 1346 21.10 million
High Estimate 1486 21.14 million
The difference of 276 systems between the high and low
estimates represents a difference of only 0.07 million people in
the estimate of population exposed. This results from the fact
that most unfiltered surface water systems are in the small size
range. This is further illustrated in the following table and in
Exhibit 2-10 which profile the number of systems and population
served by size for the most probable case.
Unfiltered Systems Population Exposed
System Size Range # % # (mil) %
25 - 10,000 1218 90.4 1.69 8.0
10,000 - 100,000 113 8.4 3.47 16.5
100,000 4- 3J5 1.2 15.94 75.5
1346 21.1
These data show that although over 90 percent of the
unfiltered systems are in the smallest size categories, they
serve only eight percent of the population exposed. Conversely,
the one percent of the total unfiltered systems which serve over
100,000 persons account for over 75 percent of the population
exposed.
ASDWA made a special effort to identify, by name, the
unfiltered systems serving more than 100,000 people by name and
to learn as much about them as possible. Several systems were
eliminated from this list if they appeared likely to install
2-21
-------
EXHIBIT 2-10
UNFILTERED COMMUNITY WATER SYSTEMS
SERVED BY SURFACE WATER
i j
KJ
ro
Number of Systems
(By System Size)*
Population Exposed
(Millions)
Small 1218
Medium
3.5
Large 15
Medium 113
Total = 1346
Total = 21.1 Million
* Small systems serve less than 10,000 persons; Medium, 10,000 to 100,000; and Large, more than
100,000.
Source: ASDWA Survey, September. 1986.
-------
filtration regardless of Federal regulatory action. The list of
large systems is presented in Exhibit 2-11. ASDWA obtained
"ballpark" cost estimates for installation of filtration in these
large systems and the flow and capacity data necessary to develop
an independent set of cost estimates for comparison purposes.
ASDWA also asked its members to estimate the total number of
unfiltered non-community surface water systems. Of the total
3844 non-community surface water systems listed in FRDS, survey
results indicate 1536 are unfiltered. Although the total number
of unfiltered public water systems more than doubles when non-
community systems are considered, the additional population
exposed is only about 300,000 under the most probable case (see
Exhibit 2-12).
2.3.2 Regional Distribution of Unfiltered Systems and Correla-
tion to Waterborne Disease outbreaks
A comparison of the ASDWA survey results to data collected
by the Center for Disease Control (CDC) appears to support a
relationship between the presence of unfiltered surface water and
the incidence of waterborne disease outbreaks. States in Regions
I-III and VIII-X account for 97 percent of all unfiltered
community surface water systems and 94 percent of all waterborne
disease outbreaks in community surface water systems reported to
CDC over the ten year period from 1974 to 1983. Comparing
similar data for non-communitv systems reveals the same pattern
(See Exhibits 2-13 and 2-14).
In other regions of the country, there are blocks of states
that would be relatively unaffected by a mandatory filtration
requirement. Eighteen states have no unfiltered community
surface water systems (see Exhibit 2-15); another six have only
one or two such systems. In 20 of these states there is cur-
rently a mandatory filtration policy in place. Of the unfiltered
community surface water systems documented in the survey, EPA
Regions IV, V, VI, and VII account for only 2.6 percent.
Similarly, 25 states have no unfiltered non-community surface
water systems, and another two states have only one or two. Of
the unfiltered non-communitv surface water systems documented in
the survey, EPA Regions IV, V, VI, and VII account for only 8.1
percent.
2.3.3 Number, Treatment Profile, and Turbidity Performance of
Filtered Water systems and Population Exposed
The ASDWA survey produced a statistical profile of the type
of filtration processes currently in place in community water
systems (by size of system) which will be used to project
national impacts of turbidity performance requirements on systems
already filtering. The profile is presented in Exhibits 2-16, 2-
17 and 2-18. An estimate of the population exposed to each form
of treatment can be derived from this profile. Small and very
•
2-23
-------
EXHIBIT 2-11
UNFILTERED COMMUNITY SURFACE WATER SYSTEMS
SERVING MORE THAN 100,000 PERSONS
1
to
N)
•Boston, MA
•Portland, ME
Newark, NJ
New York, NY
Syracuse, NY
Utica, NY
Scranton, PA
Wilkes-Barre, PA
Bethlehem, PA
•Greenville, SC
San Francisco, CA
Reno-Sparks, NV
Seattle, WA
Tacotna, V/A
•Portland, OR
TOT A I «^
Pop.
Served
(106)
2.350
0.146
0.600
7.*»04
0.235
0.120
0.161
0.234
0.103
0.569
1.800
0.174
1.090
0.225
0.719
ic Q^n
i _> . y ju
Avg.
Daily
Prod.
(MGD)
300
22
58
1500
50
21
33
49
25
42
300
80
159
80
118
Capacity
Currently
Filtered or
Planned
(MGD)
0
0
45
300
0
0
34
18
0
30
65
18
0
0
0
Additional
Filtration
Capacity
Needed
(MGD)
400
50
85
1700
55
26
12
38
36
97
400
66
287
137
225
3614 000
Estimated
Capital
Cost,
($x106)
150
35
40
1500
35
20
10
33
25
60
100
40
90
60
100
22Q8 000
Probable
Type
of
Plant
C
DF/SS
DF
DE
DF
DF
C
DF
DF
C & DF
DF
DF
DF
C
C
•Systems currently using chloramines for disinfection.
1 Several large systems such as Rochester, NY were deleted from the original list
because it was deemed likely they will install filtration irrespective of Federal
regulatory action.
Source: ASDWA Survey, September, 1986.
-------
EXHIBIT 2-12
UNFILTERED NON-COMMUNITY WATER SYSTEMS
SERVED BY SURFACE WATER
Number of Systems
(By System Size)*
Population Exposed
(Millions)
i j
I 3
ui
Very Small
1428
Very Small
0.2
Small
108
Total = 1536
Total = 0.3 Mllion
* Very Small systems serve fewer than 1000 persons; Small, 1000-10,000. There are no unfiltered
NCWS serving greater than 10,000.
Source: ASDWA Survey, September, 1986.
-------
EXHIBIT 2-13
REGIONAL PATTERNS IN COMMUNITY SYSTEMS -
UNFILTERED SYSTEMS AND DISEASE OUTBREAKS
Unfiltered Surface Systems Outbreaks in Surface Systems
(By EPA Region) (By EPA Region)
I 1
i ;
c
I, II & III
878
i, ii & in
28
All Others
34
VIII, IX & X
434
VIII, IX & X
49
All Others
5
Total = 1346
Total = 82
Source: ASDWA Survey &: CDC Data, 1974-83
-------
EXHIBIT 2-14
REGIONAL PATTERNS - NONCOMMUNITY SYSTEMS
UNFILTERED SYSTEMS AND DISEASE OUTBREAKS
Unfiltered Surface Systems Outbreaks in Surface Systems
(By EPA Region) (By EPA Region)
t j
i -
- j
I, II & III
705
VIII, DC & X
15
All Others
124
All Others
5
VIII, IX & X
707
Total = 1536
Total = 25
Source: ASDWA Survey & CDC Data, 1974-83
-------
EXHIBIT 2-15
STATE REGULATOR! REQUIREMENTS FOR FILTRATION
OF SURFACE WATER SUPPLIES
STATE DRINKING WATER
PROGRAM MANDATORY
FILTRATION POLICIES
FOR SURFACE WATER SUPPLIES
to
I
KJ
00
NO MANDATORY
FILTRATION POLICY,
BUT NO UNFILTERED
SYSTEMS PRESENT
m
STRICT MANDATORY
FILTRATION POLICY,
NO UNFILTERED
SYSTEMS PRESENT
MANDATORY FILTRATION
POLICY, BUT NOT ALL
SYSTEMS YET IN
COMPLIANCE
(10)
MANDATORY FILTRATION
POLICY, BUT WITH
•GRANDFATHER CLAUSE"
OR OTHER EXCEPTIONS
(6)
NO
FILTRATION
REQUIREMENT
(16)
() t nunber of stale programs with regulatory requirenenta In that category.
Source: ASDWA Survey, Stpttnber, 1986.
-------
EXHIBIT 2-16
FILTERED COMMUNITY WATER SYSTEMS
SERVED BY SURFACE WATER
Number of Systems
(By System Size)
Population Served
(Millions)
to
I
10
vD
Small
3344
Large
218
Medium
1049
1
Medium
45.48
Small
1479
Large
73.29
Total = 133.56
* Small systems serve less than 10,000 persons; Medium, 10,000 to 100,000; and Large, more than
100,000.
Source: ASDWA Survey. September, 1986,
-------
EHdBIT 2-17
PROFILE OF TREATMENT-IN-PLACE
IN FILTERED COMMUNITY WATER SYSTEMS
i j
i
Id
O
Profile of All Plants
Detail of Conventional Plants
2035 No Soft. It Rapid Sand
Pressure Fill.
565
Direct Fill.
157
136
Slow Sand/D.E
Conventional
3753
1097
No Soft. & Dual/
Mixed Media
Soft. & Dual/
Multi-Media
235
386
Soft. & Rapid Sand
Total = 4611
Total = 3753
Source: ASDWA Survey, September, 1986.
-------
EXHIBIT 2-18
TYPE OF TREATMENT IN PLACE IN
FILTERED COMMUNITY SUBFACE HATER SYSTEMS
(BT SIZE OF SYSTEM)
CoMunlty Water System Size Categories
Type of
Filtration
Process
Slow Sand
Direct Filtration
Gravity-Rapid Sand
Direct Filtration
Gravity-Dual Mixed Media
Dlatomaceoua Earth
Other Pressure Filters
Conventional Treatment
With Softening and Rapid
Sand Filters
Conventional Treatment
With Softening and Dual/
Mixed Media
Conventional Treatment
Without Softening and
Rapid Sand Filter*
Conventional Treatment
Without Softening and
Dual/Mixed Media
25
to
100
23
37
4
4
228
8
5
170
44
101
to
500
10
13
9
14
185
16
4
171
52
501
to
1000
11
12
5
12
39
59
13
281
105
1001
to
3300
9
11
7
11
40
57
37
133
209
3301
to
10,000
11
13
14
IB
38
101
59
487
255
10,001
to
25.000
2
4
4
3
25
61
42
183
180
25.001
to
50,000
1
4
2
0
4
32
33
123
104
50,001
to
75,000
0
1
2
2
0
20
17
55
47
75.001 100,001 500,001
to to to 1,000,000
100,000 500,000 1,000,000 +
020 0
201 0
452 1
120 0
420 0
3 24 1 1
8 13 3 1
42 63 19 B
31 55 11 1
TOTALS
69
98
59
67
565
386
235
2035
1097
Source: ASOWA Survey, Septenber, 1986.
-------
small systems account for oyer 72 percent of the "universe" but
only 11 percent of the population served.
Exhibit 2-19 summarizes data regarding filtered non-commun-
ity systems. There are approximately 2300 systems in this
category serving a population of 1.23 million persons. Approxi-
mately 98 percent of these systems are in the smallest size
categories.
The ASDWA survey produced data relating the current turbid-
ity performance of community surface water systems and the type
of treatment process in place (see Exhibit 2-20). The pattern
shown appears to support the conventional sanitary engineering
belief that more complete treatment produces lower finished water
turbidity. Moreover, since the interim standard is much higher
than the levels evaluated in the survey, it is possible that
true turbidity levels may be lower than the data suggest. Many
operators may simply not be prepared nor inclined to go to the
additional effort required to obtain this level of accuracy under
the current requirements. With the advent of refined measurement
capabilities and the use of continuous turbidimeters, however,
these biases may be eliminated from future results.
Several important factors regarding the data should be
noted. First, a relationship between turbidity performance and
system size is not apparent; instead, the 500 data points appear
to be randomly scattered. Second, turbidity performance of
package plants does not appear to differ from that achieved in
centralized plants. Finally, many plants are not currently using
a primary coagulant in their treatment processes.
2.3.4 Number of Systems without Disinfection And Population Ex-
posed
ASDWA survey results indicate that approximately 154 of the
1348 unfiltered community surface water systems are also without
disinfection. All unfiltered and undisinfected community surface
systems serve populations of less than 10,000 persons; most serve
fewer than 3300 persons.
The ASDWA survey asked state program personnel to perform a
census of the extent to which community groundwater systems are
disinfected.13 Results indicate that of a total 46,208 systems,
19,227 are fully disinfected; 4323 are partially disinfected; and
22,658 are completely without disinfection (see Exhibit 2-21).
These results were compared to FRDS data as a rough consis-
tency check. FRDS reports a total of 47,616 community ground-
13Accounting for purchased water and for populations served
by large systems (those serving > 100,000 population) was
performed via procedures similar to those described for surface
water systems above.
2-32
-------
EXHIBIT 2-19
FILTERED NON-COMMUNITY WATER SYSTEMS
SERVED BY SURFACE WATER
V
Number of Systems
(By System Size)*
Population Served
(Millions)
Small
2262
Medium/Large
46
Total = 2308
Small
0.754
Medium
0.112
Large
0.36
Total = 1.23
* Small systems serve less than 10,000 persons; Medium, 10,000 to 100,000; and Large, more than
100,000.
Source: ASDWA Survey, September, 1986.
-------
• 2
w
EXHIBIT 2-20
CURRENT TURBIDITY PERFORMANCE
IN COMMUNITY SURFACE WATER SYSTEMS
% Systems Above Indicated Turbidity
100
0 0.2 0.4 0.6 0.8 1.0
Monthly Average Turbidity (NTUs)
—••" Unfiltered H— Direct Filt.
Source: ASDWA Survey, September, 1986.
Conventional
Conv. & Other
-------
EXHIBIT 2-21
NUHBER OF CfitUUlMIII WATER STSTEHS HAVING DISINFECTED VERSUS UNDISIMFECTED
GROUND HATER SUPPLIES BT SIZE CATEGORT AND ESTIMATED POPULATION SERVED
CoMunlty Water Syaten Size Categories
Disinfected
Partially
NuBber Disinfected
of
Systeas
Not
Disinfected
Total*
CO
Ui Disinfected
Estinated Partially
Population Disinfected
Served
(Billions)
Not
Disinfected
Total"
25
to
100
1,281
1,095
11,700
17,079
0.25
0.06
0.63
0.95
101
to
500
5,795
1,830
7,729
15,351
1.57
0.45 •
1.83
3.85
501 10
to t
1000 33
2,858 3,
650
1,530 1
5.038 5
2.31 7.
0.48 0.
1.12 2.
3.91 10
01
o
00
590
166
,129
,185
11
83
05
.00
3301 10,001 25,00
to to to
10,000 25,000 50,001
1,618 677 211
231 39 11
129 112 26
2,308 823 278
9.66 10.87 8.41
1.30 0.58 0.35
2.37 1.66 0.79
13-31 13.11 9.54
1 50,001 75,00
to to
) 75,000 100,0
71 17
1 0
3 0
77 17
1.53 1-36
0.06 0
0.17 0
1.77 1.36
1 100,001 500,001
to to 1,000,000 TOTALS
00 500,000 1,000,000 + *
39 1 0 19,227
- - 1.323
00 0 22,658
39 4 0 46,208
7.60 2.76 0 56.13
O 0 0 4.11
00 0 10.62
7.60 2.76 0 71.16
•Totals may not add due to rounding.
Source: ASDWA Survey, September, 1986.
-------
water systems — 1408 more than reported in the survey. The FRDS
estimate of the number of such systems without disinfection is
27,954 which is 973 more than the 26,981 reported to be either
partially or completely without disinfection in the survey.
ASDWA survey estimates are thus very close to the FRDS
estimates, considering the total number of systems involved.
Most of the discrepancy between the two estimates is in the
smallest system size range. In addition, survey results indicate
far fewer large systems to be lacking disinfection than indicated
in FRDS. These are consistent findings in light of the voluntary
nature of this reporting element. These uncertainties introduce
an error of approximately three to four percent in the estimate
of the total systems in these categories.
ASDWA data indicate that the roughly 27,000 undisinfected or
partially disinfected community groundwater systems serve a total
population of approximately 15 million people. More than 26,000
(96 percent) serve populations of fewer than 3300. However, the
total population served by the 852 larger systems amounts to 7.28
million — roughly half the total population exposed.
ASDWA also asked respondents to assess the number of
undisinfected non-community groundwater systems. Of the 139,739
non-communitv groundwater systems listed in FRDS, survey results
indicate 112,635 (80.6%) are believed to be undisinfected.
2.3.5 Regional Distribution of Undisinfected Systems And Cor-
relation to Outbreaks of Waterbome Disease
Survey results do not indicate a relationship between the
presence of undisinfected community groundwater systems and the
incidence of waterborne disease outbreaks. Comparison of survey
results in each state to waterborne disease outbreak data
reported to the CDC in each state yields no apparent correlation
between the two. Neither is there a correlation evident in
comparison of similar data for undisinfected non-community
groundwater systemsT
ASDWA survey results indicate there are only ten states in
which there are no undisinfected community groundwater systems
(see Exhibit 2-22). State mandatory disinfection requirements
are in place in nine of these 10 states. Only Kansas and
Kentucky have requirements stringent enough that there are also
no undisinfected non-communitv groundwater systems present.
2.3.6 Number of systems In violation of Existing Coliform Regu-
lations And Population Exposed
The FRDS data base was employed to assess the extent to
which the existing coliform MCL is violated and the associated
population exposed. This provides a candidate lower bound
estimate of the occurrence of coliforms in finished water. It is
2-36
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EXHIBIT 2-22
STATE REGULATORY REQUIREMENTS FOR
DISINFECTION OF GROUNDWATER SUPPLIES
STATE DRINKING WATER
PROGRAM MANDATORY DISINFECTION
POLICIES FOR GROUNDWATER SUPPLIES
K)
STRICT MANDATORY MANDATORY DISINFECTION MANDATORY DISINFECTION NO DISINFECTION
DISINFECTION POLICY, POLICY, BUT APPLICABLE POLICY FOR ALL PWS, REQUIREMENT
NO EXCEPTIONS TO CWS ONLY WITH EXCEPTIONS
(U) (8) (15) (23)
() r number of state programs with regulatory requirements in that category.
Source: ASDWA Survey, September, 1986.
-------
a lover bound estimate for two reasons: 1) monitoring and
reporting violators may also be MCL violators; and 2) the revised
regulations, which feature a more strictly defined MCL, will
expose more violations.
Coliform MCL violations were studied over a five year period
from 1981 to 1985. Over this period, there was a total of 45,205
reported violations of the coliform MCL. Of these, 14,233 were
duplicates — multiple violations by the same systems.
Eliminating the duplicates, there were 30,972 systems that
had at least one violation of the coliform MCL. Of these, 19,254
were community systems while 11,718 were non-community systems.
It is likely that these data understate the extent of coliform
violations in non-community systems because the degree of
monitoring and reporting violation is greater and existing
monitoring requirements are much less frequent.
It is estimated that the 30,972 systems having at least one
violation serve 48 million people. However, 45 million of these
are served by the 19,254 community systems, while only three
million are served by the 11,718 non-community systems.
Approximately 91 percent of the community systems reporting
violations serve populations of less than 3300 and account for
only 15 percent of the total population exposure. Among the non-
community systems reporting violations, 99 percent serve fewer
than 3300 people and account for 60 percent of the total popu-
lation exposure.
The following table summarizes the distribution of violating
systems according to source.
Systems Violating The Colifom MCL
Water Source Community Systems Hon—Community Systems
Ground 15,926 10,566
Purchased Ground 940 106
Surface 2077 975
Purchased Surf. 311 71
TOTAL 19,254 11,718
The community groundwater violators represent about one-
third of all community groundwater systems. The non-community
groundwater violators represent only eight percent of all non-
community groundwater systems, but this proportion is probably
distorted by less frequent reporting requirements of this group.
2-38
-------
The community surface water violators account for roughly
one-third of all community surface water systems. The non-
community surface water violators account for about 25 percent of
all non-community surface water systems.
2-39
-------
3. MARKET IMPERFECTIONS, THE NEED FOR FEDERAL REGULATION, AND
CONSIDERATION OF REGULATORY ALTERNATIVES
Uniqueness of the Regulation of Drinking Water
EPA regulations are typically aimed at controlling the
environmental release of pollutants from industrial or municipal
sources. Regulatory intervention is justified because the envir-
onmental impact of such releases would otherwise be external to
the decisionmaking of pollutant generators. Since the public's
level of demand for environmental quality and protection from
environmental health threats is not revealed by market trans-
actions, the benefit of regulatory intervention is evaluated in
terms of the estimated "damage avoided" by reductions in
potential exposures of human and environmental receptors.
Regulation of drinking water is uniquely different from
other regulatory endeavors of the Environmental Protection
Agency. First, the dose of contaminant to which the public is
actually exposed is the direct object of regulation. The point
of regulatory intervention, therefore, is the performance of more
than 203,000 public water supply systems in the United States.
As discussed below, state and local institutional structures are
such that protection of public health is not uniformly factored
into the decisionmaking processes of all public water systems.
State Public Water System Supervision (PWSS) programs are like-
wise uneven in their regulatory approach and effectiveness.
Federal intervention is thus required to assure uniform protec-
tion of public health.
The further uniqueness of drinking water regulation stems
from the fact that there is a transaction between the water
system and the consumer. This transaction is affected by numer-
ous imperfections which result in a flawed price signal to the
consumer. For a variety of reasons, water has historically been
underpriced in most regions of the country. This condition has
important implications for analysis of the economic efficiency of
Federal drinking water regulations.
Despite flaws in the transaction, the mere fact there is one
permits insights into the "willingness to pay" for drinking
water. Thus, analysis of benefits need not be confined to the
"damage avoided" approach. However, literal interpretations of
market behavior that do not take account of the effects of flawed
pricing, are prone to error.
The "Public" Nature of Water Supply .
Public water supply is an example of a "natural monopoly."
It would not be efficient to have multiple suppliers competing to
build, operate, and maintain multiple systems of pipelines,
reservoirs, wells and other facilities. It is more efficient
that a single entity perform these functions under public con-
trol .
3-1
-------
While not a pure "public good" in the economic sense, water
supply is nonetheless a "publicly provided good" in the sense
that there is a significant government role in the pricing and
production decisions of the industry. "Public" water supplies
are typically either publicly owned and operated as a routine
function of local government, or privately owned and publicly
regulated as a routine function of state government.
Economists employ the concept of a "production function" to
specify conceivable combinations of inputs to a production pro-
cess which can be employed to produce alternative combinations of
outputs. In competitive markets, producers attempt to find the
optimal combinations of inputs and outputs to suit prevailing
market conditions. Thus, the physical options in production are
fixed by technical factors, but the choice between them is market
driven.
A natural monopoly such as water supply is an example of
"market failure." The competitive forces that would normally
shape production decisions "fail" to perform. The production
function for publicly provided goods ~ the "social production
function"1 — therefore embodies not only physical production
relationships between input and output combinations, but also a
method for choosing among them. There are two essential quest-
ions that must be answered in order to make optimal production
decisions for publicly provided goods:2
o What price should be charged to assure optimal utiliza-
tion of any given level of service?
o What is the optimal level of service to provide?
In answer to these two questions, economic theory recom-
mends, in the ideal, that prices be set equal to marginal cost
and that decisions regarding the level of service be determined
on the basis of comparisons of benefits and costs.-3 In other
words, institutions responsible for publicly provided goods
should strive to mimic the processes of competitive markets.
In competitive markets, these two questions are answered
simultaneously and continuously by multiple suppliers. This is a
successful way of operating because, across a range of price lev-
els, consumer preferences for different levels of service are
ischultze, C.L., The Polities And Economics—of—Public
Spending. 1968, The Brookings Institution, Washington, D.C.,
ninth printing, 1977, p.56.
2Layard and Walters, Mieroeconomic Theory. 1978, McGraw
Hill, New York, NY, p.171 and p.196.
3op. cit.. Layard and Walters, p.174.
3-2
-------
revealed in the transactions taking place in the market. There
are two essential differences in the case of publicly provided
goods: 1) differential preferences regarding the level of ser-
vice are not fully revealed in the face of a single monopoly
price; and 2) depending on the institutional arrangements in
place, there may or may not be a functional relationship between
the price charged and the level of service provided.
3.1 The Nature of the Imperfections
Imperfect revelation of consumer preferences and flawed
pricing policy are the two fundamental imperfections affecting
the provision of public water supply. When it is said that water
supply has been historically "underpriced,"4 the effects of these
imperfections are implied. Water has been underpriced in one
sense because there are a number of important attributes related
to the relative abundance and purity of available sources which
have long been taken for granted and thus not been reflected in
the price signal or the demand response. In another sense, water
has been underpriced because the historical cost of water has
been so low that pricing practices unrelated to the cost of ser-
vice have evolved in many places.
The effect of these two concepts of underpricing are evident
in the historical trend of water utility bills. The top panel of
Exhibit 3-1 presents a comparison of annual family utility bills
over the period from 1952 to 1984.5 The bottom panel presents
the same comparison in terms of the percentage of median family
income. It is clear from these diagrams that water and sewer
rates have grown at a markedly slower pace than those of all
other utilities. In fact, the proportion of median family income
consumed by water and sewer charges declined over the period.
Several researchers have analyzed such time series data and con-
firmed that the real price of water supply has in fact
declined.6'7 Many cases can be cited where wastewater costs have
increased dramatically in the last decade, and been further
propelled by inflation, but the trend in water supply is still
flat in real terms.
4Under-pricing is a recurrent theme in the literature on
water supply. See, for example the July 1981 Journal of The
American Water Works Association "Viewpoint" article by Abel
Wolman.
5BLS data.
6Mann, P.C., and LeFrancois, P.R., "The Real Price of Urban
Water," Journal of the American Water Works Association. January
1982, Vol. 74, No. 1.
7Beattie, B.R. and Foster, H.S., "Can Prices Tame The
Inflationary Tiger?" Journal of the American Water Works Associ-
ation. August 1980, Vol 72, No. 8.
3-3
-------
EXHIBIT 3-1
Annual Family Bills
for Selected Utilities 1952-1984
$70
S3 600-
3 i
£> 500—i
400—i
j
300—i
Electric
Phone
— — • Nature! Gas
—— Water (and Sewer)
$717
/ 608
/
.- 497
200-J,,ea.
100— j «•••••_ -
1 //-"
j 29__ — '
1 1
1950 1950
/'.••''/
x ^
\ \
1970 1980
Year
^- 143
1
1990
Percent of Median Family Income
Spent on Selected Utilities 1952-1984
0
i M
u
a
£> 5-
•*4
1 4-
Cb
I 3-
••4
^
V
a-)
e. —
SH
O
^ 1-
u
V
cu
Electric
ou<»»»«»
rnone
Natural Gas
Water (and Sewer)
\
VN>X
s
*•?. ^^-^ ,j.n
2.2Z .*"*». " ^2.31
-----. ^ ^^~ -*
1 •« --^--
j
— T i 1 i
1950 I960 1970 1980 1990
Year
3-4
-------
Flaws In The Revelation of Consumer Preferences
Centrally supplied potable water is a "multi-attribute good"
which has multiple uses. There are two major classes of attri-
butes: quantity features and quality features. These may also be
referred to as "pressure" and "purity."
Keeping pressure in the pipes is a day-to-day responsibility
which is met by maintaining adequate capacity and reliable per-
formance throughout the water system, from the raw water sour-
ce (s) through treatment, storage, and distribution. In addition
to the economic benefits of having a central water supply for a
multitude of residential, commercial, and industrial uses, the
pressure in the pipes also serves a public safety purpose in pro-
viding fire fighting capability. Overlaid on these use-specific
attributes is another, more general attribute — reliability. As
in all categories of infrastructure, there is an implied warranty
that the system will not fail. Reliability of water service is
taken for granted. The public reaches for the tap with the same
confidence exhibited in flipping a light switch.
The purity of the water delivered to water system customers
is assured by adequate capacity and performance of the treatment
facilities. The purity attribute has four important dimensions:
1) aesthetic appeal (taste, odor, and appearance); 2) safety from
acute health risks; 3) safety from chronic health risks; and, 4)
public confidence that the water is safe to drink. This last
attribute constitutes another implied warranty. Similar to other
categories of infrastructure that affect public safety, the
safety of potable water is largely taken for granted. For the
most part, people fill a coffee pot with the same nonchalance
that they exhibit in driving across a bridge or stepping onto the
elevator of an office building.
To assure provision of the optimal level of each of the
multiple attributes of public water supply, each must be given
appropriate weight in the production decisions of local water
systems. Despite the fact most consumers have taken all of these
attributes for granted for many years, the weights assigned in
local decisionmaking processes have not always been optimal. The
performance of water systems is commonly regarded as adequate as
long as the most "visible" attributes (pressure, aesthetic ap-
peal, and protection from acute health risks) are delivered on a
continuous basis. These most "visible" attributes are accorded
the greatest weight in decisionmaking. Problems involving plan-
ning for long term needs (e.g., infrastructure maintenance and
replacement, chronic health risks) or low probability events
(e.g., drought, waterborne disease outbreak) have much less
visibility in the local "public choice" environment and tend to
be underweighted in decisionmaking.
3-5
-------
Flaws in Pricing and Capacity Planning
Provision of water supply has historically been regarded as
a "service delivery function." For several decades, there have
been persistent warnings of a coming "water crisis" — an era of
greater relative scarcity which will force recognition of water
as a "commodity." Most knowledgeable observers agree that, con-
trary to the statements in the popular press, the United States
is not actually "running out of water," but rather is "approach-
ing the limits of inexpensive water."8 In the final analysis,
water supply is both a service and a commodity; both characteris-
tics are present in the quantity and quality attributes of the
good.
Over the historical period of relative abundance, a service
orientation of "meeting capacity requirements" has predominated
in local decisionmaking processes. Another facet of the service
orientation is a strongly held belief in some places that water
supply should be provided at an affordable price (and supported
by subsidy if necessary) as a public service. To adjust to con-
ditions of relative scarcity, however, a majority of industry
observers agree that a commodity orientation towards pricing and
capacity planning must also be incorporated in local decision-
making.'
Looking to the future, there is an approaching convergence
involving the factors which have historically been under-weighted
in local decisionmaking. Increased relative scarcity will make
"raw" (untreated) source water (the basic commodity) more expen-
sive. Treatment requirements imposed by the Safe Drinking Water
Act Amendments of 1986 will increase the cost of producing
"finished" water at the treatment plant. Deteriorating infra-
structure, as manifest in leaky distribution systems, will
increase the cost of "delivered" water at the consumer's tap
either through continued leakage of increasingly valuable treated
water or through the cost of making overdue repairs.
Underpricing always implies over capacity: The cost of
drinking water regulations will be greater because of over-
capacity. One result of drinking water regulation, therefore,
will be a reduction in the extent of over capacity. There are
already examples of water systems which have initiated more
aggressive capacity management to reduce their anticipated cost
of compliance with drinking water regulations. The economic
efficiency of this adjustment cannot be quantified, but it
appears the net effect will be to build resource allocation
8Frederick, K., "The Legacy of Cheap Water," Resources.
Resources for the Future, Inc., Spring, 1986.
9For example: Lamm, Richard D., "Kicking The Cheap Water
Habit: A New Era In Water Management," in Water Values and
Markets: Emerging Management Tools, The Freshwater Foundation,
Navarre, Minnesota, 1986.
3-6
-------
principles into the behavior of water systems. Drawing on the
"theory of the second best," the direction of the resultant
change in society's welfare will be positive. This must be kept
in mind while evaluating drinking water regulations because the
estimated costs of compliance are based on existing notions of
capacity.
Many industry observers concur that consumers may be in for
a significant "rate shock" when the above noted convergence of
factors affecting capacity costs takes hold. Industry spokes-
persons have stressed the need to educate the public regarding
the true value of potable water in order to dampen a feared
public outcry. Indeed, given the nature of the imperfections,
such public education would be an efficient intervention. While
it is true that the historic price level has been artificially
low and, while this will affect the response of consumers to
corrective changes in prices, it is not clear that this response
implies anything about the consumer's true willingness to pay.
When price signals are distorted, the demand response cannot be
literally interpreted'.
3.2 The Need for Federal Regulation
The "market failure" induced by conditions of natural mono-
poly is a failure of the mechanism of "private choice" to reveal
preferences through consumer responses to prices. The under-
weighting of certain attributes of public water supply in local
decisionmaking processes reflects a failure of the "social pro-
duction function" — a failure of "public choice." This failure
is evident in both publicly owned and privately owned (publicly
regulated) water systems as discussed below. It cannot be fully
corrected at the local or state level.
Publicly Owned Water Systems
Many publicly owned water systems exist in institutional
settings in which water system revenues and costs are commingled
with the affairs of local government. When water systems are
fiscally commingled with multi-purpose local governments there is
no means of assuring optimal pricing and production decisions for
water supply. In the commingled setting, outcomes will be opti-
mal only in cases where the weights assigned to the multiple
attributes of public water supply are the same as those that
would be produced when the water supply "objective function" is
considered by itself.
Commingled budgeting precludes establishment of a rational
relationship between the revenues generated by the water system
and its level of expenditure.10 When revenues are wholly or
10Goldstein, J., "Full-Cost Water Pricing," Journal of the
American Water Works Association. February 1986.
3-7
-------
partially contributed to the general fund, the water system is
left to compete for subsidies along with other public needs
through a process unrelated to the amount of revenue generated by
water rates.
The separation of revenues from expenditures produces not
only arbitrary and suboptimal patterns of expenditure, but arbi-
trary pricing policies as well. General fund financing creates
an air of uncertainty11 which fosters "fiscal illusion" — the
perceived relationship between the cost of the service and the
level of service provided.12 In this regard, water supply is
generally perceived as an excellent bargain because of the his-
torical trend towards underpricing.
There are, of course, many water systems which have achieved
some degree of fiscal autonomy through either an alternative
institutional design (regional authorities, special districts,
etc.) or through the discipline of enterprise fund accounting
whereby water system revenues and expenditures are kept separate.
Privately Owned Water Systems
In 45 states, privately owned water systems must obtain
approval for rate increases from state public utility commissions
(FUCs). Conventional principles of public utility regulation
would be expected to establish a full-cost basis in the relation-
ship between prices, costs, and revenues. Ideally, this would
permit privately owned water systems to apply appropriate weights
to the multiple attributes of water supply in their production
decisions. In practice, however, there are flaws in the rate
regulation process and, in particular, flaws in its application
to water utilities.
There are two major classes of privately owned water sys-
tems: 1) investor owned systems which have professional manage-
ment; and 2) small systems without professional management
belonging to homeowner associations, trailer parks, and similar
non-municipal entities. In general, the first class of systems
tends to be successful in negotiating rate increases with the
PUCs. The smaller private systems are ill equipped to prepare
or defend rate proposals and, as a result, many do not even apply
for rate increases.
The problems inherent in PUC regulation of small water
systems have been the subject of a number of recent studies by
the National Regulatory Research Institute (NRRI) under sponsor-
ship of the National Association of Regulatory Utility Commis-
sioners (NARUC). One set of findings confirms that the PUC
11Buchanan, J.M., Public Finance In A Democratic Process.
Chapel Hill, University of North Carolina Press, 1967.
12Mueller, D.C., Public Choice. Cambridge University Press,
1979., p. 90.
3-8
-------
regulatory process has presented a number of barriers in its
application to small water utilities. First, the total dollar
value of water utilities under commission jurisdiction is esti-
mated to be less than one percent of the total for all util-
ities.13 The procedures required of large gas, electric, and
telephone utilities in rate cases are clearly out of proportion
to small water utilities, 60 percent of which have annual rev-
enues of less than $15,000.14 Yet water utilities are present
in significant numbers, accounting for 34 percent of all regu-
lated utilities and 43 percent of all rate cases in 1981. The
NRRI studies have identified strategies for improving the regu-
latory process used by numerous states.
A second finding of the NRRI studies, however, is that the
source of small water system problems do not result entirely from
complex rate setting. Many small systems are simply not viable
economic entities. Strategies for preventing future creation of
such systems and encouraging existing ones to be absorbed by
larger systems may be the only long-term solutions.
A Model of "Perfect" Public Choice
In evaluating the performance or imperfections of markets,
economists rely on the hypothetical concept of "perfect" markets,
or "perfectly competitive" markets. Among other conditions,
perfect competition requires that there be no monopoly power
among suppliers and that all participants possess "perfect infor-
mation. " It is instructive to envision how a "perfect" public
choice process might apply to water supply.
An appropriate model of perfect public choice for delivery
of water supply services, or other public works, has been
presented.15 Assuming perfect information, it might be possible
to obtain accurate revelation of consumer preferences through the"
vehicle of an insurance sale. The water system would offer con-
sumers a choice between two types of insurance policies relating
to the need to install a new treatment process for removal of
contaminants. :
The first type of policy would insure those concerned about
increases in their water bills against such losses in the event
that the decision is made to purchase a new treatment process.
The second type of policy would insure those concerned about
13Lawton, R. and Davis, V., Commission Regulation of Small
Water Utilitiest Some Issues and Solutions. May 1983, The
National Regulatory Research Institute, Columbus, Ohio.
14Mann, P., Dreese, R., Tucker, M., Commission Regulation of
Small Water Utilities; Mergers and Acquisitions. October 1986,
The National Regulatory Research Institute, Columbus, Ohio.
15Thompson, E. A., "A Pareto Optimal Group Decision Pro-
cess," in G. Tullock, ed. Papers on Non-Market Decision Making.
Univ. of Virginia: Charlottesville, 1966, pp.133-40.
3-9
-------
their health against damages incurred from the contaminants if
the water utility decides not to install the new treatment pro-
cess. Consumers wishing to hedge could purchase some of each
type of insurance, thus revealing their mixed preferences. Those
electing not to participate would reveal their indifference; they
would not be "free riders," however, as their abstinence would
directly affect their welfare. In arriving at its decision, the
water system would determine which insurance policy generated the
greatest revenue. The proceeds of the insurance sale would be
used to pay the claims of the losers, making the outcome "pareto
optimal" in that no one would be made worse off.
Upon closer scrutiny, there are flaws in this model of per-
fect public choice. Determining the correct insurance premiums
to charge is a difficult problem, for example. However, the
insurance strategy for revealing consumer preferences highlights
a crucial point. The optimal level of service in public water
supply depends ultimately upon the level of certainty desired by
consumers and the extent of their willingness to pay an extra
premium for certainty — for the privilege of being able to "take
it for granted" that the water is safe to drink.
By several indicators, the willingness to pay for the safety
attributes of public water supply appears to be very strong.
Markets for bottled water and point-of-use treatment — repre-
senting substitute goods for the potable component of demand—
have been characterized by surging annual growth rates since the
mid-1970s. The pattern seems coincident with increasing public
awareness of toxic and hazardous chemical risks. On a per gallon
basis these alternatives are approximately 1000 times more expen-
sive than centrally supplied potable water.
Results of a recent survey of public attitudes conducted by
the AWWA Research Foundation provide further evidence of the
strength of this component of demand.16 A national probability
sample of 1205 water utility customers was asked what they would
be willing to pay to remove a contaminant from their drinking
water which posed a lifetime risk of causing their death equiva-
lent to their risk of being struck and killed by lightning.
Fifty-five percent of respondents indicated they would be willing
to pay an average of $6.53 per month to avoid this risk. It
seems unbelievable that a such significant proportion of people
would be willing to pay such a sum for what amounts to "lightning
insurance." The dilemma of attempting to perfect the local
public choice process is made clear, however, by the reciprocal
finding of this AWWARF question — forty-five percent of respon-
dents indicated they would be willing to pay nothing to remove
this risk.
16Audits and Surveys, Inc., Public Attitudes Toward Drinking
Water Issues. American Water Works Association Research Founda-
tion, December 1985.
3-10
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At the margin, it is the willingness to pay for an extra
increment of safety that is critical to optimal decisionmaking.
Not only is it difficult to assess preferences at such a margin,
local decisionmaking processes are not capable of excluding other
external factors from affecting this public choice at the margin.
Thus, regulatory intervention is necessary to establish uniform
goals for the level of safety to be achieved.
It has been asserted that Federal regulatory action is not
necessary to provide a set of uniform national health goals; that
this same end could be achieved perhaps in the form of EPA health
advisories or through establishment of an authoritative "national
drinking water toxicology board". This concept ignores the non-
trivial fact that interpretation of toxicological data involves a
considerable amount of subjective judgement which implicitly
embodies a benefit/cost comparison. A "national drinking water
toxicology board" or similar entity would be making benefit/cost
trade-offs implicitly rather than explicitly through the formal
rulemaking procedures employed by EPA in development of regulat-
ions.
Moreover, implementation of actions to achieve such unen-
forceable goals would still be subject to the influence of
external factors which enter into local public choice processes.
State regulation, it has been rebutted, is all that would be
required to assure implementation by local entities. This
overlooks the fact the public choice decisionmaking arena extends
to the state level where external factors (e.g., the political
implications of required expenditures, other priorities of state
PUCs, etc.) may still affect outcomes. With respect to the
Surface Water Treatment Rule (SWTR) , the states have asked for a
strict Federal rule to leverage their own authority.
The Safe Drinking Water Act (SDWA) instructs EPA to estab-
lish drinking water . standards at levels designed to avoid adverse
effects on the health of persons and allow for a margin of
safety. Intuitively, this mandate intends to produce the same
optimal outcome at the margin which would otherwise be produced
if there were no flaws in local public choice processes. There
are no other Federal regulatory authorities which warrant con-
sideration as alternative approaches. SDWA is perfectly designed
for this purpose and the mandate is consistent with principles of
economic efficiency.
3.3 Consideration of Regulatory Alternatives
EPA has proposed the Surface Water Treatment Rule (SWTR) and
the Total Col i form Rule (TCR) in accordance with the requirements
of the SDWA Amendments of 1986. The SDWA mandates that EPA
promulgate a national primary drinking water regulation (NPDWR)
specifying criteria under which filtration will be required as a
3-11
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treatment technique for public water systems supplied by surface
water sources (SDWA, Section 1412 [b] [7] [C] [i] ) . EPA is also
required to promulgate national primary drinking water regula-
tions requiring disinfection as a treatment technique for all
public water systems by December 19, 1989 (SDWA, Section 1412
The 1986 SDWA Amendments require the EPA to publish maximum
contaminant level goals and promulgate NPDWRs for the 83 contam-
-nants listed in the Advance Notices of Proposed Rulemaking at 47
Fed. Rea. 45502 (March 4, 1982) and 48 Fed. Egg. 45502 (October
5, 1983). This list of contaminants includes turbidity and five
microbiological contaminants: viruses, Giardia lamblia. £eqj.op-
ella. heterotrophic bacteria, and coliforms.
National Primary Drinking Water Regulations under the SDWA
are to include monitoring requirements (Section 1401 [1][D]).
Specifically, the Act requires that "there must be criteria and
standards to assure a supply of drinking water which ^ dependably
complies with such maximum contaminant levels; including quality
control and testing procedures to insure compliance with such
levels and to insure proper operation and maintenance of the
system, ..."
Since the proposed standards, treatment requirements, and
monitoring have been mandated by the statute, EPA is limited in
its consideration of alternative regulatory approaches. EPA does
not have the flexibility to consider taking "no action" nor can
the Agency propose that states establish the necessary standards
and monitoring requirements based on Federal guidance.
It was the intent of the Congress to limit the range of
alternative regulatory strategies for implementation of the SDWA.
The reason for the prescribed regulatory approach is that current
Federal and state approaches to regulating microbiological con-
tamination have not completely controlled the occurrence of
waterborne disease outbreaks. Between 1971-1985, there were 447
reported outbreaks of waterborne disease affecting more than
105,000 people. This substantial number of disease outbreaks and
cases is a major reason for proposing these regulations.
In establishing the SWTR and TCR, EPA's objective's to pro-
pose a regulatory approach that has substantial flexibility built
into it, thereby achieving maximum health benefits. Thus, EPA
considered several different options for both the standards them-
selves and the associated monitoring requirements. The options
were both developed and selected for inclusion in the rules based
on technical input from EPA staff as well as comments received
from the water industry, state regulatory programs, and the
scientific community. This section examines the alternatives
considered and the basis for selection of options by EPA.
3-12
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3.3.1 Alternatives and Factors Considered in Developing the
Surface Water Treatment Rule
Filtration/Disinfection
EPA considered four different filtration/disinfection policy
alternatives in developing the SWTR:
o Alternative A — A mandatory filtration requirement with
no exceptions.
o Alternative B -- Provide exceptions for systems having a
single point of redundant disinfection achieving a 2 Log
removal for Giardia cysts and a 3-Log removal of enteric
viruses.
o Alternative C — Provide exceptions for systems having a
single point of redundant disinfection achieving a 3-Log
removal of Giardia cysts and a 4-Log removal of enteric
viruses.
o Alternative D — Provide exceptions for systems having
two points of redundant disinfection achieving a 3-Log
removal of Giardia cysts and a 4-Log removal of enteric
viruses.
EPA is proposing Alternative C as the requirements for fil-
tration and disinfection in the SWTR. This alternative is pro-
posed on the basis of several scientific, technical and economic
factors which are discussed in the following paragraphs.
The proposed rule requires disinfection for all systems with
surface water sources, with no variances or exemptions allowed.
The reason for this provision is that all surface sources have a
significant probability of being subject to contamination from
pathogenic bacteria, viruses, and Giardia Iambiia. Currently
available water quality indicators (e.g., total coliforms, tur-
bidity) are not adequate by themselves for demonstrating that
surface water is not at risk from contamination of pathogenic
organisms. A properly maintained and operated disinfection
system is essential for controlling waterborne diseases. More-
over, clarification and filtration by themselves do not provide
adequate removal of pathogenic bacteria, cysts, and viruses.
Disinfection is necessary to supplement these processes and pro-
vide the most effective treatment barrier for these organisms.
At a 1985 workshop on filtration, disinfection and microbial
monitoring sponsored by EPA, participants representing utilities,
state regulatory programs, and the scientific community recom-
mended that disinfection be required, with no variances allowed,
for all systems using surface water sources.17
17Regli, S., and Berger, P. (eds.)/ "Workshop on Filtration,
Disinfection, and Microbial Monitoring, April 15-17, 1985,
Baltimore, MD," Office'of Drinking Water, U.S. EPA, 1987.
3-13
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In addition to developing treatment alternatives, options
were considered for other major criteria of the proposed rule,
including the definition of surface water and coverage of the
rule. The purpose of the proposed definition of "surface water"
is to include under the requirements of the rule all systems
which may be subject to surface water contamination which might
contain Giardia lamblia. Giardia cysts are orders of magnitude
larger than viruses and are thus much more readily removed by
natural filtration processes within the ground. Giardia cysts
are much more resistant than viruses and bacteria to disinfection
and require filtration or very stringent disinfection to be
adequately treated. When disinfection requirements for ground-
water are proposed at a later date, they will address the concept
of viral contamination in such supplies.
Drinking water supplies originating from infiltration gal-
leries, springs, and wells have been found to be contaminated by
Giardia cysts*8,19 These data indicate that not all water from
beneath the surface of the ground is adequately filtered by pas-
sage through the ground or protected from surface water so as to
provide reasonable safeguards from contamination of Giardia.
Since a major purpose of the SWTR is to control Giardia. the
proposed definition of "surface water" includes springs, infil-
tration galleries, wells, and other collectors which are directly
influenced by surface water. The term "direct influence" is to
be defined on a case-by-case basis by the State.
EPA is proposing treatment requirements which achieve at
least 99.9 percent (3-Log) removal and/or inactivation of Giardia
cysts. All waterborne giardiasis outbreaks have occurred in
systems with no treatment in place or with faulty water treatment
plant design or poor operation. Conversely, no properly operated
water treatment plant using both filtration and disinfection has
been implicated in a waterborne giardiasis outbreak. Laboratory
and pilot-scale studies support that these technologies, under
appropriate design and operating conditions, remove and/or
inactivate greater than or equal to 99.9 percent Giardia
cysts.20, 21 In addition, at the 1985 workshop participants
18Hoffbuhr, J.W., Blair, J., Bartleson, M., and Karlin, R.,
"Use of Particulate Analysis for Source and Water Treatment
Evaluation," Presented at American Water Works Association Annual
Water Quality Technology Conference, Portland, OR, Nov. 16-20, 1986.
19Hibler, C.P., "Analysis of Municipal Water Samples for
Cysts of Giardia." Report prepared for Office of Drinking Water,
U.S. EPA, January 1987.
20U.S. Environmental Protection Agency> Office of Drinking
Water, Criteria and Standards Division, "Draft Guidance Manual
for the surface Water Treatment Rule," 1987.
3-14
-------
recommended that if a system was allowed not to filter, one of
the requirements that it should have to meet would be 99.9 per-
cent inactivation of Giardia cysts by disinfection.
Some systems might not actually need a 99.9 percent removal
and/or inactivation of Giardia cysts to provide adequately safe
water to their customers. The alternative is to establish an MCL
standard for Giardia and perform monitoring of the cysts. How-
ever, this approach is not technically or economically feasible
for several reasons: 1) the only available analytical methods
require levels of expertise that utility personnel generally do
not have; 2) analysis by independent laboratories is expensive;
3) analytical validation procedures have not yet been estab-
lished; 4) systems would need to monitor inordinately large and
frequent samples to ensure that the water does not pose an unrea-
sonable risk to health of the population served; and 5) it is not
possible to assure the detection of contaminant levels in advance
of any level that will actually cause or contribute to any in-
creased health risk. Therefore, it is believed appropriate to
require that all systems using surface water achieve a minimum
removal/inactivation of 99.9 percent of all Giardia cysts.
EPA is proposing treatment regulations which would require
99.99 percent (or 4 Log) removal and/or inactivation of enteric
viruses in drinking water. Virus removal by clarification and
filtration can be expected to range from 90 percent to 99.7
percent for conventional treatment, 90 to 99 percent for direct
filtration with coagulation-flocculation, zero to greater than 99
percent for diatomaceous earth filtration and slow sand filtra-
tion.22,23 The reasons cited for not proposing an MCL and moni-
toring requirements for Giardia also apply to the feasibility of
establishing an MCL and monitoring requirements for enteric
viruses.
21Amirtharajah, A., "Variance Analysis and Criteria for
Treatment Regulations," Journal of the American Water Works
Association, p. 34., March 1986.
22Engelbrecht, R.S., "Proceedings of a Workshop on Assess-
ment of Microbiology and Turbidity Standards for Drinking Water,
December 1981," Berger, P and Argaman, Y. (eds), U.S. EPA
Publication 570-9-83-001, 1983.
23Logsdon, G.S., "Comparison of Some Filtration Processes
Appropriate for Giardia Cysts Removal," Presented at Calgary
Giardia Conference, Calgary, Canada, Feb. 1987.
3-15
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Virus inactivation by disinfection depends upon the type of
disinfectant, disinfectant residual, disinfectant contact time,
and may be affected by the ionic environment and clumping.24 The
AWWA Committee on Viruses in Drinking Water has recommended that
following conventional treatment, a free chlorine concentration
of 1.0 mg/1 be maintained for at least 30 minutes at a water pH
not to exceed 8.0, in order to reasonably assure virologically
safe water.25 These recommended disinfection conditions can be
expected to achieve greater than a 99.99 percent inactivation of
most enteric viruses for which data exists.26
Well operated systems with filtration and disinfection can
be expected to achieve at least 99.99 percent removal and/or
inactivation of viruses. Since no waterborne disease outbreak
has ever been implicated in a well operated water treatment plant
using filtration and disinfection, it is believed that at least a
99.99 percent reduction of enteric viruses is necessary to ensure
an adequate margin of safety.
Alternatives for Design and Operating Criteria
A minimum performance level is specified in the proposed
rule rather than minimal design and operating conditions to allow
for a variety of technical solutions. Guidance for evaluating
viral reduction by filtration and disinfection processes, with
appropriate safety factors, are provided in the SWTR Guidance
Manual.
Historically states have had the responsibility of estab-
lishing design and operating criteria for public drinking water
plants. This has been accomplished through organizations such as
the Water Supply Committee of the Great Lakes - Upper Mississippi
River Board of State Sanitary Engineers (i.e., The Ten States
Standards), and interaction between state programs and standards
setting organizations such as the AWWA.
24Hoff, J.C., " Inactivation of Microbial Agents by Chemical
Disinfectants," Drinking Water Research Development, Office of
Research and Development, U.S. EPA, Cincinnati, Ohio, 1986.
25American Water Works Association, "Committee Report on
Viruses in Drinking Water," Journal of the AWWA, Vol. 71, pp.
441-444, August 1979.
26Hoff, J.C. "Inactivation of Microbial Agents by Chemical
Disinfectants," Drinking Water Research Development, Office of
Research and Development, U.S. EPA, Cincinnati, Ohio, 1986.
3-16
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It is believed that states should continue to have the
responsibility for setting design and operating criteria. The
SWTR defines treatment processes that can be used to meet minimum
performance criteria and states are delegated the responsibility
to set design and operating conditions to ensure that these
performance criteria are met.
It is more expedient for states to incorporate change in
existing design and operating criteria, so as to meet require-
ments of the SWTR, than for EPA to establish new standards for
states to adopt. The EPA Guidance Manual provides guidance on
how design and operating criteria may need to be changed to
assure that performance criteria in the SWTR are met.
Finished Water Turbidity
Four policy alternatives were considered for plants using
direct filtration or conventional treatment:
o Alternative 1 — Same as current NIPDWR standard, monthly
average turbidity not to exceed 1.0 NTU;
o Alternative 2 — Turbidity less than 1.0 NTU 95 percent
of the time, average turbidity approximately 0.5 NTU;
o Alternative 3 — Turbidity less than 0.5 NTU 95 percent
of the time, average turbidity approximately 0.3 NTU;
o Alternative 4 — Turbidity less than 0.4 NTU 95 percent
of the time, average turbidity approximately 0.2 NTU.
EPA is proposing Alternative 3 in the SWTR, with more
lenient requirements applying to slow sand and diatomaceous earth
plants.
The proposed turbidity performance requirements for systems
that filter are more stringent than those of the existing HCL.
Systems using conventional treatment and direct filtration can
meet the existing criteria while not optimizing pretreatment,
which is essential for effective pathogen removal. The purpose
of the performance criteria (average 0.3 NTU) for conventional
treatment and direct filtration is to ensure that utilities
optimize pretreatment.
Turbidity of filtered water in slow sand and diatomaceous
earth filtration has been shown to be relatively less important
for Giardia removal. Therefore, the proposed turbidity perform-
ance criteria (average 1.0 NTU) are less stringent than for
conventional treatment or direct filtration.
3-17
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Raw Water Turbidity
The proposed raw water turbidity requirements for systems
which do not filter approximate the existing turbidity MCL, which
has been in effect since 1977. These turbidity requirements
differ from the existing MCL requirements in that they specify:
1) monitoring once every four hours rather than once per day; and
2) an upper limit of 5 NTU for any time versus a two-day average
of 5 NTU.
The proposed regulations require turbidity measurements to
be made at least every four hours for filtered water, whereas the
current regulations require sampling only once per day. The
increased monitoring frequency is necessary to ensure more repre-
sentative sampling of turbidity since significant fluctuations in
turbidity levels can occur during a 24-hour period. Turbidity is
also required to evaluate the microbiological quality of drinking
water for the following reasons:
o turbidity is related to the microbiological content of
water; removal of turbidity results in proportionate
removal of microorganisms present in raw water sources
since most organisms are attached to the solids which
comprise raw water turbidity;
o the removal of turbidity reduces the chlorine demand of
treated water; and
o turbidity interferes with disinfection processes and with
the total coliform measurement in treated water.
EPA believes that the raw water quality upper limit of_5 NTU
provides a more appropriate margin of safety than the existing
two day average limit of 5 NTU, for ensuring that raw water qual-
ity will not interfere significantly with disinfection. Increases
in turbidity occurrence to greater than 5 NTU have been shown to
correlate with decreases in disinfection effectiveness in unfil-
tered source waters.27 In addition, high turbidity waters may be
unaesthetic in appearance and cause consumers to avoid the use of
the public supply.
The proposed raw water monthly limit of 1 NTU for systems
which do not filter is higher than the turbidity limits proposed
for systems which do filter because: 1) additional filtration
exception standards reduce the probability of viral occurrence in
source water; 2) interference with Giardia inactivation by tur-
27LeChavalier, M., Evans, T. and Seidler, R. "Effect of
Turbidity on chlorination Efficiency and Bacterial Persistence In
Drinking Water," Journal of Applied Environmental Microbiology,
Vol. 42, pp. 159-167, 1981.
3-18
-------
bidity levels below the standard is unlikely to occur due to the
relative large size of the cysts; and 3) other requirements for
systems that do not filter will identify interference with dis-
infection.
3.3.2 Alternatives and Factors Considered in Developing the
Total Coliform Rule
As required by the SDWA of 1974, EPA published the National
Interim Primary Drinking Water Regulations (NIPDWRs) which estab-
lished regulations for ten inorganic chemicals, six pesticides,
and two microbiological contaminants (i.e., total coliform bac-
teria and turbidity). The total coliform regulation, including
the MCL and minimum monitoring frequency, were based upon the U.S
Public Health Service Regulations of 1962. This interim coliform
regulation, which is still in effect, applies to both community
and non-community water systems. There are currently two coli-
form MCLs: a single-sample MCL and a monthly average MCL. Both
HCLs are based on the number of coliform bacteria detected in the
sample.
The interim regulations do not cover heterotrophic bacteria,
nor is EPA proposing an MCLG or MCL at this time. Heterotrophic
bacteria measured by the heterotrophic plate count procedure
imprecisely counts both some bacterial pathogens and mostly
innocuous bacteria. Therefore, it is likely to be impossible to
specify a scientifically rational MCLG or MCL other than zero.
The health benefits of meeting a level of zero versus some higher
level may be negligible, if not adverse, because of the possible
health risks resulting from disinfection by-products.
The proposed regulation is based on the heterotrophic ana-
lytic method interface with coliform analysis. A problem assoc-
iated with heterotrophic bacteria is that higher densities of
such bacteria interfere with total coliform analysis. EPA is
proposing to require monitoring for heterotrophic bacteria only
when there is evidence that high levels of these organisms are
interfering with total coliform analysis. If total coliform
samples produce an invalid result, a second sample must be ana-
lyzed for both total coliform and heterotrophic plate count. If
HPC is greater than 500 colonies/ml, then the sample is consid-
ered coliform positive, even if the initial total coliform anal-
ysis is negative.
The coliform MCLs in the interim regulations, as indicated
previously, include density limits for single samples and the
monthly average. EPA is proposing to change this by basing the
MCLs on the presence or absence of coliforms in a sample rather
than a particular concentration. The rationale for this approach
3-19
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is that the data presented in the literature to date28 do not
demonstrate a quantitative relationship between coliform concen-
trations and the potential for waterbome disease outbreak.
The presence/absence MCL approach has several advantages: 1)
the sensitivity of the procedure is improved because simple
detection of the presence of coliforms is more precise than the
determination of whether the coliform densities fall above or
below a specific value; 2} the sample transit time problem is
less acute, since a decrease in coliform density between sample
collection and analysis would seldom result in complete eradica-
tion of all coliforms; and 3) data truncation implicit in the
analytical methodology is reduced as a calculation difficulty.
The monthly average MCL in the interim regulation has been
criticized because the tendency toward variability of coliform
counts greatly reduces precision (i.e., has a large standard
deviation). The presence/absence concept eliminates this
problem.
EPA also recognizes some shortcomings associated with the
presence/absence concept. High coliform levels may relate to
high pathogen densities on occasion. In addition, the current
regulations have been in force for decades and both state offi-
cials and public water system operators are familiar with them.
Nevertheless, it is believed that the positive features of the
presence-absence concept outweigh the disadvantages.
The presence/absence method was recommended to EPA by a
workshop held in December 1981 sponsored by EPA's Office of
Drinking Water. The purpose of the workshop was to assess
microbiological and turbidity standards for drinking water.
The monthly MCL would allow systems collecting fewer than 40
samples per month to have one positive sample per month without
violating the rule. If 40 or more samples are collected, no more
than five percent of the samples may be positive. For a small
system, however, this proposed monthly MCL would allow a sizeable
proportion of samples to be positive for coliforms (e.g., if a
system collects five samples per month, 20 percent of the water
samples could contain coliforms month after month). It is likely
that such water is of poor quality and may endanger public
health. For this reason, a long-term MCL is also being proposed.
28United States Environmental Protection Agency, Office of
Drinking Water, "Drinking Water Criteria Document of Total
Coliforms," PB 86-118148, National Technical Information
Service, Springfield, VA, 1984.
3-20
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EPA examined several alternatives for setting the long-term
MCL, based on the presence/absence concept. EPA examined the
alternatives based on the relationship between the percentage of
positive coliform samples allowed and the actual quality of the
water by using a binomial distribution formula. EPA is proposing
to base the long-term MCL on 60 samples, because this value is
sufficiently large for the statistical calculations to be valid,
yet small enough to be practical for use in MCL calculations.
Furthermore, data indicates that if 60 samples are collected and
95 percent are negative for coliforms, then there is a 95 per-
cent confidence that the fraction of water with coliforms present
is less than 10 percent.29 EPA proposes to define this as rea-
sonably safe water; under the proposed long-term MCL, no more
than five percent of the most recent 60 samples could be positive
for coliforms.
The interim regulations indicate that non-community and some
small community water systems may reduce their monitoring fre-
quency on the basis of sanitary survey results. EPA proposes to
expand the role of sanitary surveys as a requirement for all
public water systems that 1)' use surface water without filtration
or 2) use groundwater without disinfection. EPA also proposes to
allow a state to reduce the monitoring frequency below five
samples per month for systems serving 3300 persons or less. The
coliform monitoring requirements are summarized in Exhibits 3-2
through 3-5.
The purpose of sanitary surveys is to serve as a second line
of defense to alert public water systems and primacy agents of
possible health risks which might not be apparent form routine
sampling because of uneven distribution of coliforms in the
distribution systems. The survey also examines variability in
surface water quality, the length of time between sample collec-
tions, the length of time between sample collection and receipt
of analytical results, and lack of data on water quality in parts
of the distribution system not included in recent sampling sites.
This is especially critical for populations served by unfiltered
surface waters and non-disinfected groundwater.
3.3.3 Alternatives and Basis for Monitoring Requirements
EPA developed and examined several alternative sets of mon-
itoring and reporting requirements for both the SWTR and the TCR.
The monitoring and reporting alternatives and the basis for the
options selected for each rule are discussed in the Information
Collection Request (ICR) submitted for each proposed rule. The
ICRs are submitted in accordance with the Paperwork Reduction Act
of 1980.
29Pipes, W, "Monitoring of Microbial Water Quality," In:
Assessment of Microbiology and Turbidity Standards for Drinking
Water, U.S. EPA, 1983.
3-21
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COLIFORM MONITORING FOR UNFILTERED
SURFACE WATER SYSTEMS
25-500
POPULATION
NJ
N)
NO
FLEXIBILITY
5 SAMPLES
PER MONTH &
SAN SURV/YR
UNFILTERED
SURFACE WATER
SYSTEMS
500-3300
POPULATION
NO
FLEXIBILITY
5 SAMPLES
PER MONTH &
SAN SURV/YR
>3300
POPULATION
COMMUNITY
WATER
SYSTEMS
NON-COMMUNITY
WATER
SYSTEMS
SAME MONITORING
PLUS SANITARY
SURVEY/YEAR
MONITORS
AS COMMUNITY
SYSTEMS
-------
COLIFORM MONITORING FOR FILTERED
SURFACE WATER SYSTEMS
nLTHKD
SURTACI VATU
SYSTCUS
•3-000
POPULATION
SOO-3SOO
POPUUTION
HO
Tuasam
Ld
to
runaunr
a SAMPLE*
PEI iiotmi
>3SOO
poruunoN
NO
FUHBIUTY
I SAMPLE/MONTH
* SANITAKY SUFVIY
/S YUM
6 SA1IPUCS
PEI MONTH
couuimmr
»ATT»
StSTKMS
3 SAUPUS/UONTH
At IANTTAKV SURVCY
/S YIAKS
NON-COUUUNTTY
WATEK
NO NET
CHANCE
UONfTORS
AS coionrnmr
svmus
-------
COLIFORM MONITORING FOR UNDISINFECTED
GROUNDWATER SYSTEMS
utnuHMRcno
aBotnonuTSi
frstcus
IM-13M
FOPOU.TUM
HO
lumuri
CO
ro
4s
tttnuun
ft UUMJtt
/KOHTH*1AM
SDKTCT/tl Y>S
HO
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rum OUT
/HDHTH **AH
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roruunoN
/MOHTB It tAH
COHVOMTT
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nrjtou
11AUPUS
/MOH1B klU*
SOITET/SYM
VlTOt
sranxs
FUM SAN JUE7TT
/STBS
IUMITOU
-------
COLIFORM MONITORING FOR DISINFECTED
GROUNDWATER SYSTEMS
DISINFECTED
CRQUNDVATER
SYSTEMS
E3-SOO
POPULATION
BOO-3300
POPULATION
>3SOO
POPUUIION
NO
rumamr
co
IvJ
Ln
FLEXIBILITY
S SAMPLES
PER MONTH
MO
I SAMPLE/MONTH
* SANITARY SURVEY
/S YEARS
FLEHBUiTY
D SAMPLES
PER MONTH
COMMUNITY
WATER
SYSTEMS
3 SIMPLES/MONTH
At SANITARY SURVEY
/S YEARS
HON-COMMUNITY
WATER
SYSTEMS
NO NET
CHANGE
MONITORS
AS COMMUNITY
SYSTEMS
-------
In developing monitoring requirements under the SWTR and
TCR, EPA considered which level of government was most appropri-
ate for determining monitoring standards. Further, to take into
account the complexities of collecting representative samples in
individual systems, and the potential for variability of water
quality over time in surface and ground water systems, the fol-
lowing variables were considered in developing monitoring
options: 1) the number of samples to be taken; 2) the frequency
of sampling; 3) the location of sampling points; 4) which systems
should sample; and 5) when the sampling should be performed.
3-26
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4. ASSESSMENT OF COSTS
Implementation of the multiple barriers approach to removing
microbial contaminants from drinking water involves a combination
of treatment and monitoring. The adequacy of the treatment bar-
riers and of their operation is continuously confirmed by the
monitoring information.
In devising a multiple barriers strategy, it is appropriate
to regard the system boundary as extending from the extremities
of the watershed to the extremities of the water distribution
system. Various combinations of monitoring and contaminant
removal/inactivation activities could be designed for each ele-
ment of the system (i.e., watershed, treatment, storage, distri-
bution) . Thus, there are a number of technical trade-offs avail-
able within the "production function" of providing microbiolog-
ically safe drinking water. The comparative total national costs
of alternative strategies for producing such water are evaluated
in this chapter.
Together the Surface Water Treatment Rule (SWTR) and the
Coliform Rule prescribe a complete regimen of treatment and
performance requirements for surface water systems. These are
illustrated graphically in Exhibit 4-1. Requirements are speci-
fied for both filtered and unfiltered systems.
For unfiltered systems seeking an exception to the filtra-
tion requirement, an adequate array of other barriers to micro-
bial contamination coupled with extensive monitoring must be in
place to demonstrate a level of treatment equivalent to that
achieved by filtration. It has been demonstrated that modern
filtration technologies coupled with disinfection can achieve a
99.9 percent (3-Log) reduction in Giardia cysts and a 99.99 per-
cent (4-Log) reduction in viruses under proper operating condi-
tions.1
Hence, disinfection sufficient to achieve a three and four
(3/4) log reduction of Giardia/viruses is the proposed require-
ment for unfiltered systems. Systems unable to meet this re-
quirement will have to install filtration. The ability to meet
this level of efficacy in disinfection must be demonstrated
through raw and finished water monitoring data on levels of
turbidity, coliforms, pH and water temperature, and chlorine
residual. Also, a watershed management program is required as an
additional barrier.
technologies and Costs for Removal of Microbial
Contaminants From Potable Water Supplies. U.S. EPA, Office of
Drinking Water, February 1987.
4-1
-------
EXHIBIT 4-1
ALTERNATIVE PROCESSES FOR
REMOVING MICROBIOLOGICAL CONTAMINANTS
FILTRATION
REQUIREMENTS
^Coag. + Settling Finished
^^^ + Filtration Water Distribution
•^ + Disinfection Turbidity System
Raw
Charac
•
t
1
! Water Raw
1 Shed "*" Water
1
1 '•
1
^^*>^ or
and Residual Col i form
^"*Dir. Filtration Monitoring and Residual
+ Disinfection
Water
teristics
i
i
Treatment
^ Process
,
1
i
1
Monitoring
» <
1
•
Finished Distribution
*~ Water ^ System
i
i
k
1
Water
Shed
Kanagement
and
Sanitary
Surveys
Raw Water
Coliform
and
Turbidity
Monitoring
Finished Water
pH, Temp
and Residual
Monitoring
Distribution
System
Coliform
and Residual
Monitoring
3/4 Log Disinfection
and
Back-Up Disinfection
EXCEPTION
REQUIREMENTS
4-2
-------
For filtered systems, it has been demonstrated that effi-
cient removal of microorganisms is associated with low effluent
turbidities.2 Thus, new turbidity monitoring requirements are
specified for filtered systems together with new monitoring
requirements for coliforms and chlorine residual. These require-
ments are intended to assure that the performance of filter
plants matches their potential for 3/4 log removals.
There are a number of technical trade-offs available within
the production function for filtration. In essence, the strength
of the barrier put in place is variable, depending on the speci-
fic combination of unit processes used in conjunction with the
filtration unit process. While direct filtration will suffice
for some situations, other site specific conditions will require
the use of chemical addition and perhaps settling prior to the
filtration step. The efficacy of chemical addition can be en-
hanced by a number of techniques including rapid mix, pH adjust-
ment, and the use of specialized polymers and dual/multi media
filtering materials. It is likely that many existing filtration
plants will have to be upgraded_ to incorporate these techniques
to meet the new performance requirements.
The requirements of the Coliform Rule also extend to ground-
water systems. It has been demonstrated that the frequency of
coliform sampling previously required of small water systems is
inadequate to assure the absence of microorganisms with a rea-
sonable degree of statistical confidence.3 Thus, the required
monitoring frequency will be increased.
Separate analyses of the total national cost are presented
in this chapter for: 1) presently unfiltered systems; 2) pres-
ently filtered systems; and 3) the impact of the Coliform Rule.
Additionally, the costs of implementation to be borne by state
drinking water programs are evaluated. A summary section pre-
sents a tabulation of the total costs embodied in the regulatory
proposal.
4.1 costs to Presently Unfiltered systems
Four alternative approaches to specifying the filtration
requirement of the Surface Water Treatment Rule have been con-
sidered. These are listed below:
alternative A — A mandatory filtration requirement with no
exceptions provided for alternative multiple barrier strategies.
This is conceived as an extreme high cost scenario to provide an
2ibid.
3Pipes, W. and Christian, R. . sampling Frequency—
Mierobial Drinking Water Regulation. US EPA 570/9-82-001, U.S.
EPA, 1982.
4-3
-------
estimate of the upper bound of total national cost. It would not
be practical unless it were believed that there is no alternative
strategy which can provide equivalent treatment.
Alternative B — Allow exceptions for systems providing disinfec-
tion sufficient to achieve a two and three (2/3) log removal of
Giardia and viruses. This alternative is inconsistent with the
documented level of treatment efficiency achievable through fil-
tration and disinfection, but is evaluated to assess whether
there is an effect on total national cost from a less stringent
requirement, reflecting a lower margin of safety.
Alternative C — Allow exceptions for systems providing disinfec-
tion sufficient to achieve a 3/4 log removal of Giardia and vir-
uses. This is the proposed alternative which is intended to pro-
vide an equivalent level of treatment to that attainable with
filtration.
Alternative D — Allow exceptions for systems providing two
points of disinfection, both sufficient to achieve a 3/4 log
removal of Giardia and viruses. This alternative would include
an additional barrier in strategies for treating unfiltered
water. The need for such an additional margin of safety is not
clear, but it permits evaluation of the total national cost of a
more stringent treatment requirement.
The potential range between the estimated total national
capital cost of the proposed Alternative C and the worst case
Alternative A is illustrated in Exhibit 4-2. As indicated in the
diagram, it is important to distinguish between the extent of
cost contribution attributable to systems serving fewer than
100,000 persons and the proportion attributable to the 15 unfil-
tered systems serving more than 100,000 persons. Accordingly,
the cost analysis is presented in two parts.
4.1.1 Unfiltered Systems Serving Fewer Than 100,000 People
According to the survey conducted by the Association of
State Drinking Water Administrators (ASDWA)4, discussed in Chap-
ter 2, there are approximately 1331 community and 1536 non-
community unfiltered surface water systems which serve popula-
tions of fewer than 100,000 persons. In fact, 1218 of the com-
munity unfiltered systems (90%) and all of the non-community
unfiltered systems serve populations of fewer than 10,000 per-
sons.
^survey To Support Analysis of The Impacts—of—Propose^
Regulations Concerning Filtration And Disinfection—of—Public
water Supplies. Association of State Drinking Water
Administrators, September 22, 1986.
4-4
-------
EXHIBIT 4-2
Capital Expenditures for Filtration
$ Billions
A
Total: $1.6 4.1 Billion
3 -
Ul
2 -
1.838
2.298
<100K >100K
Systems Serving
•H Alternative C Alternative A
-------
Most unfiltered systems disinfect. However, there are an
estimated 154 community systems and 178 non-community systems
which provide no treatment. It is conceivable that some of these
are spring fed systems.
The comparative system level costs of the most likely
compliance options available to small water systems are sum-
marized in Exhibits 4-3 and 4-4. By comparison, the system level
costs of obtaining an exception to the filtration requirement are
presented in Exhibit 4-5.s The unfiltered systems will likely
fall into four broad groups:
1. Those which have raw water of sufficient quality that
obtaining an exception to the filtration requirement is
feasible;
2. Those which have raw water characteristics that will
permit use of economical technologies such as slow sand
or diatomaceous earth filtration;
3. Those which will require a more complete and expensive
form of treatment, such as that provided by a package
plant; and
4. Those for whom conversion to a ground water source or to
water purchased from another system will be the most
economical option.
Turbidity data generated by the ASDWA survey6 was employed
to make an assessment of the conceivable number of systems which
could be candidates for the exception or for the more economical
treatment technologies. A panel of engineers responsible for
developing the system level cost data were asked to forecast the
distribution of the total population of unfiltered water systems
serving fewer than 100,000 persons across the compliance options.
This analysis was performed using a decision tree which was then
converted to a tabular form. The decision trees are included as
Appendix A. A separate decision tree was evaluated for each
alternative. Within each alternative, separate decision trees
were evaluated for systems which currently have no treatment and
for systems which currently disinfect only. Separate sets of
decision trees were evaluated for community and non-community
systems.
5The details of the requirements for obtaining an exception
have been changed several times since these estimates appeared in
the last version of the cost and technology document (February
1987). However, these numbers are still roughly representative
of the correct range for the cost of obtaining an exception.
6OP. cit.. ASDWA, 1986.
4-6
-------
EXHIBIT 4-3
CAPITAL COST OP FILTRATION
COMPLIANCE OPTIONS
($ Thousands)
system
capacity
(MGD)
0.07
0.15
0.34
0.84
2.50
Package
Treatment
Plants
$ 278
295
428
773
1770
Diatomaceous
Earth
$ 221
285
374
570
1573
Slow
Sand
$ 145
273
508
603
1213
Ultra-
Filtration
$ 142
269
503
1144
__
Ground Water
Conversion
$ 56
75
115
2O5
4-7
-------
EXHIBIT 4-4
UNIT PRODUCTION COSTS OP FILTRATION
COMPLIANCE OPTIONS
(t/iooo gal.)
system
Capacity
fMGD)
0.07
Package
Treatment
Plants
945
Diatomaceous Slow
Earth Sand
673 378
Ultra
Filtration
456
Ground Water
Conversion
303
0.15
277
227
205
227
118
0.34
195
135
133
179
60
0.84
114
67
55
138
35
2.50
73
66
34
4-8
-------
EXHIBIT 4-5
SUMMARY OF ANNUAL COSTS TO MEET EXCEPTION CRITERIA
Category
1
2
3
4
5
6
7
8
9
10
11
12
Average
Plow,
mad
0.013
0.045
0.133
0.40
30
25
6.75
11.50
20.00
55.50
205
650
1,
3,
Total Annual
Cost,
SlOOO/vr
9.6
10.9
13.8
16.8
30.1
39.0
41.1
50.1
62.5
97.2
178
314
Total Annual
Cost,
6/1000 aal
202
66.4
28.4
11.5
6.3
3.3
1.7
1.2
0.9
0.5
0.2
0.1
4-9
-------
Results of the decision tree analysis for the proposed
Alternative C are summarized in the illustration of Exhibit 4-6.
The scenario implied by these compliance choices is one in which
the affected water systems favor the least cost solutions.
Almost 900 (i.e., 899) of the 2867 systems (31%) will likely
develop alternate sources. This could include drilling a well
(the basis used for costing purposes); purchasing water from, or
being absorbed by, another water system; or converting a spring
into a groundwater source through construction of a deep intake.
Based on analysis of the turbidity data from the ASDWA sur-
vey, it is forecast that as many as 457 systems (16%) are con-
ceivably eligible candidates for an exception to the filtration
requirement. Of the 1511 systems (53%) that will probably have
to install filtration, 990 are believed to have sufficiently good
raw water quality to permit use of slow sand filtration. More
than 100 (i.e., 115) are expected to be able to employ diatoma-
ceous earth filtration. Only 221 are expected to install package
treatment plants and only 56 are expected to install conventional
treatment facilities. The supporting rationale for this scenario
is that the unfiltered systems could not, for the most part, have
persisted for so long unless they had relatively good raw water
quality.
Compliance choices forecast for the other alternatives were
only marginally different from this base scenario, reflecting
primarily differences in the number of systems eligible for the
exception. The compliance choices forecast for the four alter-
natives are summarized in Exhibit 4-7.
Exhibit 4-8 presents a summary tabulation of the total
national cost attributable to each of the four alternatives.
These estimates were constructed using the Office of Drinking
Water's model (i.e., ATm) which multiplies the number of systems
selecting each compliance option by the cost of each option and
then performs various summations to provide profiles of total
national cost.
The results in Exhibit 4-8 indicate that there is no sub-
stantial cost difference between Alternatives B, C, and D. This
is partially a result of the fact these alternatives consider
variations in the exception criteria; many systems are still
assumed to filter in each case, however, and the cost of filtra-
tion dominates the national totals. The estimated capital cost
of the worst case, Alternative A, is $1.494 billion compared to
$1.093 billion for the proposed Alternative C. Capital cost
savings of $401 million are therefore attributable to the pro-
vision for exceptions.
These results are subject to some error due to late changes
in the monitoring requirements which were not incorporated in the
total cost model. Specifically, the finished water monitoring
requirements used for systems obtaining an exception included
monitoring for Giardia. viruses, and heterotrophic plate count
4-10
-------
EXHIBIT 4-6
Compliance Strategies
Of Unfiltered Systems Serving < 100,000
Alt. Sources 899
Exceptions 457
Filtration 1511
Slow Sand 990
Package Trt. 221
Diatom. Earth 115
Direct- Filt. 89
Convent. 58
Untrafilt. 38
General Compliance Strategies
Total = 2887
Filtration Choices
Total = 1511
-------
EXHIBIT 4-7
COMPLIANCE CHOICES FOR
ALTERNATIVE FILTRATION EXCEPTION CRITERIA —
COMMUNITY WATER SYSTEMS
Size Category: 25-100 101- 501- 1001- 3301- 10K- 25K- 50K- 75K- TOTAL
»****+««»*»** **MM«W*M«*«**«W*4«««***tM««««««**«««W**H*t*****«*«**H**WM»*»
Alternative A -- No Exceptions
Alternate Source
Obtain Exception
Install Filtration
Totals
Alternative B — Exceptions:
Alternate Source
Obtain Exception
Install Filtration
Totals
Alternative C — Exceptions:
Alternate Source
Obtain Exception
Install Filtration
Totals
Alternative D ~ Exceptions:
Alternate Source
Obtain Exception
Install Filtration
Totals
155
0
155
310
2/3
131
24
155
310
3/4
131
24
155
310
3/4
131
24
155
310
76
0
229
305
Log. Reioval
90
48
16B
305
Log. Reioval
90
48
168
305
Log. Reaoval
90
46
16B
305
43
0
174
217
34
43
140
217
34
43
140
217
fc
34
43
140
217
23
0
203
226
23
53
150
226
23
53
150
226
Redundancy
23
53
150
226
0
0
160
160
0
57
103
160
0
46
114
160
0
46
114
160
0
0
65
65
0
29
36
65
0
23
42
65
0
23
42
65
0
0
25
25
0
11
14
25
0
9
16
25
0
9
16
25
0
0
13
13
0
6
7
13
0
6
7
13
0
6
7
13
0 '.
0 i
10 t
10 !
0
5
5
10
0 ',
4 :
& :
10 :
0
4
6
10
297
0
1,034
1,331
277
276
77B
1,331
277
257
797
1,331
_••
277
257
797
1,331
4-12
-------
EXHIBIT 4-7 (Cont.)
COMPLIANCE CHOICES FOR
ALTERNATIVE FILTRATION EXCEPTION CRITERIA —
NON-COMMUNITY WATER SYSTEMS
Size Category: 25-100 101- 501-
m
-------
EXHIBIT 4-8
TOTAL NATIONAL COSTS —
ALTERNATIVE FILTRATION EXCEPTION CRITERIA
Sire Categ: 25-100
t*lH****ttMttHH**H
101- 501-
XXXXXXXXXXtXXXXXJ
1001- 3301-
UXXXXXXXXXXXXXXXJ
Alternative A — Mo
oMunity: Capital
DM
' Annualized
on-Coinunity: Capital
DM
' Annualized
otal: Capital
DM
' Annualized
onunity: Capital
OW1
' Annualized
on-Cowunity: Capital
out
' Annualized
otal: Capital
DM
' Annualized
ouunity: Capital
DM
' Annualized
on-CoMunity: Capital
DM
' Annualized
otal: Capital
OUI
' Annualized
ouunity. Capital
DM
1 Annualized
on-Couunity: Capital
out
' Annualized
otal: Capital
OUI
' Annualized
29
1
3
91
5
11
119
6
14
28
2
4
84
5
11
111
7
15
28
2
4
84
5
11
111
7
15
2B
2
4
84
5
11
111
7
15
64
2
7
84
3
9
148
6
16
Alternative
50
3
6
64
4
8
114
7
15
Alternative
50
3
6
64
4
8
114
7
15
Alternative
50
3
6
64
4
B
' 114
7
15
77
4
10
20
1
2
97
5
12
8 -
63
5
9
17
1
2
80
6
11
C -
63
5
9
17
1
2
80
6
11
D-
64
5
9
17
1
2
80
6
11
150
10
20
19
1
2
169
11
23
Exceptions;
113
9
17
16
1
2
128
10
19
Exceptions:
113
9
17
16
1
2
129
11
19
Exceptions:
114
9
17
16
1
2
130
11
19
10K-
IXXXXXXXJ
25K-
L XX XX XX
50K- 75K-
XXXXXXXXXXXXXXXXXXJ
TOTAL
LXXXXXXX
Exceptions
262
3
21
14
0
1
276
3
22
2/3
209
5
19
9
0
1
218
5
20
3/4
226
5
20
10
0
1
236
5
21
3/4
227
5
21
10
0
1
238
6
22
216
15
29
0
0
0
216
15
29
144
10
20
0
0
0
144
10
20
156
9
19
0
0
0
156
9
19
169
11
22
0
0
0
16?
11
22
1,266
66
152
228
10
25
1,494
77
177
Log. Reioval
130
11
19
0
0
0
130
11
19
86
7
13
0
0
0
86
7
13
83
5
11
0
0
0
83
5
11
90
6
12
0
0
0
90
6
12
852
52
109
189
12
25
1,041
64
134
Log. Reioval
145
12
21
0
0
0
145
12
21
95
8
14
0
0
0
95
8
14
Lag. Reioval i
146
12
22
0
0
0
146
12
22
96
8
14
0
0
0
96
8
14
83
5
11
0
0
0
88
5
11
Redundancy
38
6
12
0
0
0
98
6
12
95
6
13
0
0
0
95
6
13
95
7
13
0
0
0
95
7
13
903
55
115
190
12
25
1,093
67
140
908
56
117
191
12
25
1,099
48
142
-------
(HPC). These requirements have subsequently been dropped from
the( proposed rule. Offsetting this error is the fact that
finished water turbidity monitoring was omitted for systems which
install filtration; and, monitoring of the chlorine residual in
the distribution system was omitted for both systems installing
filtration and systems obtaining an exception.
The excess finished water monitoring requirements for sys-
tems obtaining an exception result in an over estimate of annual
costs by about $4.0 million dollars per year. The omitted
requirements would add approximately $4.5 million in annual
costs. Thus, errors in the results produced by these late
changes in the proposed rule are small relative to the total cost
and roughly offsetting. Corrected spreadsheet models documenting
the monitoring costs of the proposed SWTR are included in
Appendix C.
A sensitivity analysis of the base scenario supporting the
decision tree inputs was performed to provide additional in-
sights. If only half as many systems were eligible candidates
for the exception and alternate source options, an additional 678
systems would be required to install filtration. Since this
represents an increase of 45 percent in the number of systems
installing filtration, it is estimated that costs would increase
proportionately. The capital cost of Alternative C would
increase to $1.585 billion.
Applying the same assumption regarding the alternate source
option to Alternative A, the number of systems requiring the
installation of filtration would increase by 23 percent, implying
a capital cost of $1.838 billion. The results of this sensi-
tivity analysis may be used to form a high scenario. This
scenario probably the high cost end of the range of conceivable
outcomes. The base scenario is considered most likely.
A sensitivity analysis of the estimates of total annualized
cost illustrates the effect of different assumptions regarding
the social discount rate. In the base analysis presented in
Exhibit 4-8, a 3.0 percent rate is used. The effect of 5.0
percent and 7.0 percent assumptions on annual cost estimates for
alternatives A and C is shown in the following summary table.
For simplicity, these estimates assume a 20 year economic life.
In fact the concrete structures, which account for 30 to 50
percent of total capital costs, have an economic life of at least
40 to 50 years. so, the 20-year assumption produces an over-
estimate of the true annual cost.
4-15
-------
Summary of Cost Estimates
For Systems Serving < 100.000
Alternative A Alternative C
Base High Base High
Capital Cost 1494 1838 1093 1585
($ Millions)
Total Annual!zed Cost
($ Millions/Yr)
@ 3.0%
§ 5.0%
@ 7.0%
177
197
218
218
242
268
140
155
170
203
255
247
4.1.2 Unfiltered Systems serving More Than 100,000 People
Exhibit 4-9 presents a comparison of two sets of cost
estimates for 14 large cities serving more than 100,000 persons
which have unfiltered surface water supplies. The average flows
and capacities given in the table were obtained from the survey
conducted by the Association of State Drinking Water Admini-
strators (ASDWA).7 The ASDWA survey also attempted to obtain
informal "ballpark" estimates of the capital costs of installing
filtration and the likely type of plant from a combination of
state and local sources. These estimates are of variable qual-
ity. In some places, preliminary engineering studies have been
performed, in other cases the estimates are purely judgmental.
For purposes of comparison, the flow and capacity data
obtained by ASDWA was evaluated using the Office of Drinking
Water's cost models.8 As evident in Exhibit 4-9, these cost
estimates are uniformly lower than those obtained by ASDWA. In
total, the ASDWA estimates indicate a capital cost of $798 mil-
lion versus $607 million using the EPA cost models, a difference
of about 30 percent.
There are a number of conceivable reasons for the differ-
ences. First, the EPA cost models did not have complete site
specific information; the only parameters included in the
analysis were type of plant, flow, and capacity. Most impor-
7OP. cit.. ASDWA, 1986.
8oc. cit.. U.S. EPA, 1987.
4-16
-------
KXHI HIT 4—9
ESTTMRIED TREMMENT COST FOR
City
Boston, MA
Portland, ME
Newark, NT
Syracuse, NY
Utica, NY
Scranton, PA
Wilkes-Barre, PA
Bethlehem, PA
Greenville, SC
Greenville, SC
San Francisco, CA
Reno-Sparks, NV
Seattle, WA
Tacoma, WA
Portland, OR
POORTE
Type
of
Plant
C
ss
DF
DF
DF
C
DF
DF
C
DF
DF
DF
DF
C
C
FTM TTKin-1 if IT:
MDRE
New
Capacity
nerd
400
50
85
55
26
12
38
36
48.5
48.5
400
66
287
137
225
HUD SURFACE
THAN 100, 0(
Average
Flow,
rood
300
22
38
50
21
8.6
33
25
16
16
258
63
159
80
118
HATER SYSTEMS
)0 PERSONS
ASOHA
SURVEY
Estimated
Capital
Cost
(Smillions)
150
35
40
35
20
10
33
25
60
60
100
40
90
60
100 t
798
SERVING
Capital
Cost
137
19
25
20
13
8
16
15
26
18
90
22
63
55
Jfl
607
O&M Cost
(Smillions/yrl
10.5
0.14
1.4
1.5
0.75
0.5
1.0
0.91
1.3
0.82
6.5
1.7
4.4
3.4
5.1
4-17
-------
tantly, the EPA cost models do not include real estate costs
which could become a significant factor in this large system size
range. Consequently, the ASDWA estimates may be regarded as an
upper bound which incorporates these site specific variables.
Another major area of uncertainty, omitted from Exhibit 4-9,
is the cost estimate for a fifteenth large unfiltered system,
namely New York City. The New York City water system serves
approximately 7.4 million people, compared to a total of 8.53
million people served by the other 14 large systems. Capital
cost estimates for filtering the Catskill/Delaware portions of
the New York City supply may be selected from the following:
o §1.5 billion capital cost — estimated by extrapolating
estimated costs of constructing the Croton plant to the
unfiltered portions of the New York City water system;9
o $1.05 billion capital cost; $90 million/yr. O&M; for
diatomaceous earth filtration — EPA cost models.
o $566 million capital cost; $77 million/yr. O&M; for
conventional treatment — EPA cost models.
o $322 million capital cost; $48 million/yr. O&M; for
direct filtration —- EPA cost models.
The best estimate to use for New York City is unclear. The
absence of real estate costs and other site specific variables in
the EPA cost models is probably more significant in the case of
New York City than anywhere else. The New York City system is
extremely complex and, according to most observers, an engineer-
ing feasibility study would be required to develop believable
capital and O&M cost estimates.
One factor which contributes to excessively high costs is
the wasteful use of capacity. New York City is one of the last
large cities in the nation to institute metering of water con-
sumption. A metering program has only recently been instituted
which will take until 1995 to complete and will not require sub-
metering of apartments.10 It is difficult to compare consumption
rates between areas of differing climate, population density,
incomes, and cultural influences. However, it seems noteworthy
that the per capita capacity requirement of the New York City
water system is 1.5 times that of Boston which has recently
completed an aggressive program to install meters and rehabil-
itate its distribution system.
Assessment of the Likely Financial Impacts of a
Mandatory Filtration Regulation on Two Large Water Systems. Wade
Miller Associates, prepared for the U.S. EPA, Office of Drinking
Water, May 1986.
10Frederick, K.D., "Watering The Big Apple", Resources.
Winter 1986, Resources For The Future, Washington, D.C.
4-18
-------
New York City also has much room for improvement in capacity
utilization through renovations to the distribution system. The
City averages nearly two main breaks a day.11 The City has
launched a $5 billion program to improve the transmission and
distribution system, including a new third city tunnel which will
provide needed redundancy. It will, however, require many years
to complete.
Finally, the fiscal management of the New York City water
system has contributed to a level of water use well above the
national average.12 The average family in New York City pays
approximately $100 per year for water service.13 For many years
water system revenues and expenditures were commingled with the
affairs of the city government, complicating fiscal management.
Recently, the city has acted to establish the water system as a
separate enterprise for fiscal purposes. This will no doubt
improve pricing practices and the efficiency of capacity utili-
zation. Across the river in New Jersey, the privately owned
Hackensack Water Company charges the average family $250 per year
for water service.14
According to the New York City Bureau of Water Supply, 1.7
billion gallons per day of filtration capacity would have to be
installed. It is not clear to what extent this capacity
requirement may be reduced by the time the City begins actual
construction. The cost of filtration is ample incentive to
eliminate wasteful use of capacity. However, expenditures to
reduce the amount of filtration capacity required through elim-
ination of waste should not be regarded as costs attributable to
the Surface Water Treatment Rule.
Considering all of the above factors, the New York City
costs are considered to lie in a range of $322 million to $1.5
billion. These estimates may be used to complete the high and
low scenarios given in Exhibit 4-9. Total costs of filtering all
15 large systems (i.e., Alternative A) may be characterized in a
range as follows:
"•ibid.
3-2 ibid.
14 Communications with Hackensack Water Company,
4-19
-------
Total Costs of Alternative A
To 15 Systems Serving >100.000
Base Scenario High Scenario
capital Cost 929 2298
($ Millions)
Total Annualized Cost
($ Millions/Yr)
@ 3.0% 131 289
@ 5.0% 143 319
@ 7.0% 156 352
The annualized costs in the above table are provisional
estimates, based on an economic life of 20 years. In fact, thj
concrete structures to be put in place have an economic life oj
at least 40 or 50 years. So, the 20-year assumption produces ai
over-estimate of the true annual cost. j
In evaluating the impacts associated with Alternative C
which provides an exception to the filtration requirement, it was
necessary to devise an estimate of the degree of cost savingj
which may result from the availability of the exception. Withouj
detailed site specific data, it is impossible to assess which oj
the 15 large systems might qualify for the exception. That is ii
fact the reason for the statutory requirement of case-by-casi
determinations to be made by states. Further, it is impossibly
to accurately assess the costs that will be incurred by any oj
these large systems which attempt to seek an exception, as thesi
will also be site specific.
As a means of deriving an estimate, the percentage cosl
savings between Alternative A (no exceptions) and Alternative <
were computed for systems serving 50,000 to 100,000 persons fro:
the analysis presented in Section 4.1.1. Systems above 50,00i
population generally operate on the same scale since many pro-
cesses are modular in nature. Hence, unit costs are comparable
The percentage cost savings for these systems obtained in Sectio:
4.1.1 have been applied to Section 4.2.2 results for Alternativi
A to generate the following estimates for Alternative C.
4-20
-------
Total Costs of Alternative C
To 15 Systems Serving > 100.000
Base Scenario High Scenario
Capital Cost 520 1286
($ Millions)
Total Annualized Cost
($ Millions/Yr)
@ 3.0% 76 168
@ 5.0% 83 185
@ 7.0% 91 204
These results indicate the potential cost savings among the
15 large cities made possible by the exception are substantial.
Capital cost savings are in a range of $409 million to $1 bil-
lion. Annual cost savings are in a range of $55 to 148 million
per year.
Results for alternatives B and D were developed on the same
basis and indicate that there is little difference between these
alternatives and Alternative C.
4.1.3 Summary of cost Estimates For Unfiltered systems
The following table provides a summary of the cumulative
results for systems serving fewer than 100,000 persons and sys-
tems serving more than 100,000 persons.
Summary of Cost Estimates
For All Unfiltered Systems
Alternative A Alternative C
Base High Base High
Capital Cost 2423 4136 1613 2871
($ Millions)
Total Annualized Cost
($ Millions/Yr)
6 3.0% 308 507 216 371
6 5.0% 340 561 238 410
@ 7.0% 374 620 261 451
4-21
-------
4.2 Costs To Presently Filtered Systems
The national cost of four alternative turbidity performance
requirements for filtered systems has been evaluated. These are
as follows:
o Alternative 1 ~ Status quo; monthly average turbidity
not to exceed 1.0 NTU.
o Alternative 2 — Turbidity less than 1.0 NTU 95 percent
of the time (average approximately 0.5 NTU).
o Alternative 3 —• Turbidity less than 0.5 NTU 95 percent
of the time (average approximately 0.3 NTU).
o Alternative 4 — Turbidity less than 0.4 NTU 95 percent
of the time (average approximately 0.2 NTU).
The method for computing total national costs hinges on the
ASDWA survey data15 from a random sample of over 500 plants. It
provides a profile of the type of filtration technologies cur-
rently in place and of their turbidity performance (see Exhibit
2-17). For each category of treatment-in-place, an estimate was
made of the number of systems currently above each of the average
turbidities specified in the policy alternatives. These esti-
mates are summarized in Exhibit 4-10. For the systems above each
specified turbidity level, a "decision tree" was developed to
forecast likely choices of compliance actions. Compliance strat-
egies included combinations of the following:
o hiring a consulting engineer to perform a diagnostic
analysis;
o improving O&M practices;
o adding rapid mix;
o adding pH adjustment;
o replacing filter media;
o adding polymer;
o adding alum or FeCl2; and
o adding flocculation or contact chambers.
For systems which currently employ slow sand or diatomaceous
earth filtration, a more lenient turbidity performance standard
of 1.0 NTU will apply. it was assumed the only compliance costs
affecting these systems would be an additional increment of O&M
cost.
Alternative 1 represents a continuation of the status quo,
or the present MCL for turbidity (average of 1.0 NTU). The ASDWA
survey data suggest an estimated 864 "primary" community surface
water systems are in violation of the current MCL. The term
"primary" is intended to distinguish systems which actually pro-
15op. cit.. ASDWA, 1986.
4-22
-------
EXHIBIT 4-10
NUMBER OF SYSTEMS ABOVE
ALTERNATIVE AVERAGE TURBIDITY LEVELS
'Si:s Category 25-100 101- SOS- 1001- 3300- 10K- 25k- 50K- 75K- 100K- 500K- 1 XIL- TOTAL!
!M**««*0*tt««*««««m*«H««»*«««»««mm«t««^^
! Alternative 2 — Average Turbidity 0.5 NTU ;
ICcaianity
ISIcr-CsMunity
i Total
i
ICaaaunity
!Ncn-Zoaaunity
ITatsi
<
1
• «»••«
:
ICaasunity
IKon-Caaaunity
ITstal
384
997
1,381
475
1234
1,709
510
1323
1.B33
316
440
756
397
553
950
448
623
1,071
245
55
310
391
103
494
455
120
575
281 336
35 14
316 350
Alternative 3
517 630
65 27
582 657
Alternative 4
672 921
94 35
756. 356
123
0
123
-- Average
312
1
i
313
-- Avsrags
402
1
403
64
0
64
30
0
30
Turbidity 0.3
183
0
1S3
Turbi
239
0
239
32
0
82
dity 0.2
109
0
109
24
v
24
NTU
57
0
57
NTU
74
i
4
75
13
A
V
IB
78
0
78
112
*
113
3 1
0 0
3 1
18 5
0 0
18 5
26 :
0 0
26 3
1.325
1,551
3,37i
i 3,145
i 1,983
! 5,128
! 3,376
! 2, IBB
! 6,064
4-23
-------
duce (i.e./ treat) surface water from systems purchasing treated
surface water. It is the "primary" surface systems which operate
filter plants and are therefore affected by turbidity compliance
requirements. If it is assumed that the same proportion of
"primary" non-community surface systems exceed the current MCL,
it would imply there are 545 such systems.
An estimate of 1409 (864 community and 545 non-community)
violators of the current turbidity MCL compares favorably with
FRDS data. A recent FRDS summary of FY-85 data shows 519 MCL
violators and 1661 monitoring and reporting violators. Despite
the fact these FRDS numbers also include purchased water systems,
the numbers are relatively close, considering the unknowns
embodied in the monitoring and reporting violations (i.e., they
may represent MCL violations as well.).
For regulatory impact analysis, only the additional incre-
ment of cost imposed by the revised regulations is to be counted.
Thus, the cost of compliance for current violators should not be
counted as a cost of the proposed regulations. The national
costs of compliance with Alternative 1 were computed, but are not
compared to the other alternatives. Alternative 1 would impose
total capital costs of $70 million and total annual costs (@3%)
of $18.5 million. Instead, these costs have been subtracted from
the costs of the other alternatives to leave them "net" of the
cost of compliance with existing regulations. The comparisons
presented in Exhibit 4-11 are therefore between the net incre-
mental costs of Alternatives 2, 3, and 4.
A separate decision tree was evaluated for each alternative
producing separate estimates of national costs. The national
costs imposed by compliance actions of non-community systems was
evaluated for each of the alternatives on the basis of assump-
tions that the turbidity performance and average costs of com-
pliance are similar to those estimated for community systems. A
summary of all results is presented below. All annual costs are
estimated at 3 percent over 20 years. Since the costs imposed
are predominantly- operation and maintenance costs, use of a 5
percent or 7 percent discount rate causes a difference of less
than $1 million per year in the total annual cost. As a sample,
the decision tree and cost model for the proposed Alternative 3
are included in Appendix B. A summary of the compliance choices
forecast for community systems under Alternative 3 is presented
in Exhibit 4-12.
4-24
-------
EXHIBIT 4-11
NET INCREMENTAL COSTS OF TURBIDITY ALTERNATIVES
(millions of dollars)
Size Categ: 25-100
MHimHttMMM******1
CoMunity: Capital
out
1 Annualized
Non-Couunity: Capital
owl
' Annual i zed
Total: Capital
OKI
' Annuitized
Couunity: Capital
OHI
' Annualized
Non-CoMtinity: Capital
OU
1 Annualized
Total: Capital
DM
' Annualized
Coaiunity: Capital
OIH
' Annualized
Non-CoBiunity: Capital
DM
* Annualized
Total: Capital
OUI
• Annualized
3
1
I
7
2
2
9
2
3
5
1
1
14
3
4
20
4
5
7
1
2
19
4
5
27
5
7
101-
WMM
3
1
1
5
1
1
3
2
2
7
1
2
10
2
3
17
3
5
10
2
3
14
3
4
24
5
6
501- 1001- 3301- IOK-
ttitt{itfif»*l**X»UimtI*Xl
Alternative
5
2
2
1
1
1
6
3
3
Alternative
10
4
4
3
1
1
12
5
6
Alternative
13
5
6
3
1
2
16
6
7
2 --
3
4
4
1
0
1
9
4
5
A — —
19
9
10
2
1
i
1
22
10
11
4 — —
27
12
14
3
2
2
31
13
16
Average
26
6
7
1
0
0
27
6
e
Average
59
12
16
2
1
1
61
13
17
Average
84
17
22
4
1
1
87
17
23
25K-
1111.11
Turbidity
13
2
3
0
0
0
13
2
3
10
2
f
-J
0
0
0
10
2
3
Turbidity
40
7
10
0
0
0
40
7
10
30
6
3
0
0
0
30
6
8
Turbidity
56
10
14
0
0
0
56
10
14
42
.. B
11
0
0
0
42
B
11
50K- 75K-
tttHtiti*****
0.5 NTU
7
1
2
0
0
0
7
1
2
0.3 NTU
20
4
5
0
0
0
20
4
5
0.2 NTU
2B
5
7
0
0
0
28
5
7
8
1
2
0
0
0
B
I
2
24
4
5
0
0
0
24
4
5
32
5
7
0
0
0
32
5
7
100K- 500K- 1 NIL- TOTAL
ttiMif M **»**x*****x»****xi
9
1
2
0
0
0
9
1
2
50
6
10
0
0
0
50.
6
10
81
9
15
1
0
0
32
9
15
5
1
1
0
0
0
5
1
1
24
5
7
0
0
0
24
5
7
36
B
10
0
0
0
34
8
10
3 101
1 22
1 29
0 15
0 4
0 5
3 116
1 26
1 34
14 301
5 64
6 85
0 32
0 7
0 10
14 333
5 72
6 95
21 439
8 90
9 119
0 45
0 10
0 13
21 484
8 100
9 132
4-25
-------
f
Cr"1
LIKELY COMPLIANCE CHOICES TO IMPROVE
TURBIDITY PERFORMANCE
of Community Systems
3145
Engineering Services Polymer Rapid Mix pH Adjustment Add/Contact Primary Coagul.
-------
Turbidity Performance Requirement
Total National Cost (Millions)
Community Systems Non-Community Systems All Systems
Alt Aver T Capital Annual Capital Annual Capital Annual
2
3
4
(0
(0
(0
.5
.3
.2
NTU)
NTU)
NTU)
101
301
439
29
85
119
15
32
45
5
10
13
116
333
434
34
95
132
The most obvious conclusion to be drawn from the above
results is that there is a significant cost gradient between
Alternative 2 and Alternative 4. In terms of annual cost,
Alternative 4 costs nearly four times as much as Alternative 2.
This is illustrated graphically in Exhibit 4-13.
The shape and slope of the total cost curve shown in Exhibit
4-13 is determined by the joint influence of two inputs: 1) the
decision tree estimates of likely compliance actions; and 2) the
turbidity performance profile estimated from the ASDWA survey
data. In both cases there is error in the inputs which is
believed to impart an asymmetric bias — skewing the results to
the high end of the conceivable range.
The judgmental decision tree inputs are subject to a ten-
dency towards "over-engineering" because this particular set of
compliance options is a menu of non-exclusive remedies. The
tendency is to select several options. Another factor affecting
.these estimates of total national costs is the error inherent in
measurement of turbidity. It is conceivable that many water
systems are currently monitoring well enough to evaluate perform-
ance relative to the existing standard of 1.0 NTU, but without
much precision below this level. The lower levels of alterna-
tives 2, 3, and 4 are proposed in conjunction with a requirement
for more sophisticated monitoring methods. These methods may
show that the number of systems needing to take compliance action
has been overstated by the ASDWA survey results which reflect
current monitoring techniques.
Thus, the curve in Exhibit 4-13 must be evaluated with an
understanding of the uncertainties embodied in it. If the
exponential portion of the curve is shifted only slightly to the
left, the total national cost of Alternative 3 and possibly
Alternative 4 could be significantly lower than indicated in the
present results.
4-27
-------
EXHIBIT 4-13
(0
140
TOTAL NATIONAL COSTS - TURBIDITY
PERFORMANCE REQUIREMENT
•
Total Annual Cost (Million 1986 $)
120 -
100 -
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Monthly Average Turbidity (NTUs)
-------
The distribution of the total impact of a turbidity perform-
ance requirement is presented in the following profile of the
results for Alternative 3 (for both community and non-community
systems) :
Turbidity Performance Requirement
Impact Profilet Alternative 3
No . Systems
Size Category
100,000+
10K to 100K
Under 10K
Affected
101
635
4392
Population
Exposed
(Mil)
42
22
5.5
Canital
Cost
(Mil)
88
114
132
Annual
Cost
(Mil)
23
28
44
Cents Per
1000 Gal *•*
1
2
5-55
The above impact profile indicates that the greatest cost
impacts from a turbidity performance requirement would be felt in
the smaller system size categories. Approximately 86 percent of
the affected water systems and 46 percent of total annual costs
are in the small size range despite the fact they account for
only eight percent of the total population exposed. This is
illustrated graphically in Exhibit 4-14.
In addition to costs reported in the above table, the SWTR
will impose additional monitoring requirements on filtered sys-
tems for measuring finished water turbidity and the chlorine
residual in the distribution system. These requirements might
add as much as an additional $16 million/year to total annual
costs. Due to late changes, these costs were not included in the
total cost models. However, many larger systems already perform
these measurements and the "improving O&M -practices" compliance
option in the national cost model may also overlap with these
same cost elements. Spreadsheet models documenting the
monitoring costs associated with the SWTR are contained in
Appendix C.
4.3 Costs of Compliance With The Proposed Coliform Rule
Proposed revisions to the coliform regulations will require
more frequent monitoring by small systems and, at the same time,
tighten the definition of a "positive" sample. These changes are
16These are "average" costs; representing an average across
all compliance options and across several subsidiary size
categories.
4-29
-------
Filtered Water Systems Requiring
Improvement in Turbidity Performance
Small
5.5
Medium
22
Population Exposed
(Millions)
Meduim
28
Annual Cost
($Million/Year)
-------
needed because the current monitoring frequency in small systems
is inadequate to assure that "negatives" are not "false nega-
tives." Initially, the result will be a larger number of systems
reporting coliform violations. Two types of costs will result:
1) increased monitoring costs; and 2) remedial action costs to
correct the circumstances that cause violations.
Only the monitoring costs are counted in this analysis. The
remedial action costs are not quantified. Three conclusions were
drawn regarding the remedial action costs.
First, there is no appropriate set of "occurrence data" with
which to assess the number of systems that would be likely to
incur remedial action costs. Two approaches to occurrence anal-
ysis were explored, as described in Chapter 2. The number of
undisinfected water systems was estimated in the ASDWA survey.
However, it seems there is no established causative relationship
between the absence of disinfection and the presence of coliform
violations. In fact, a rule of thumb followed in many states
uses the coliform monitoring data as a trigger for requiring
mandatory disinfection of groundwater sources. Thus, many of the
27,000 undisinfected community groundwater systems in the country
have maintained this status by repeatedly demonstrating the
absence of coliforms.
A second approach to occurrence analysis was to use the PROS
data base to estimate the total number of unique violators of the
coliform MCL over the last five years. While data indicating the
presence of 31,000 such violators is interesting, there is no way
to tell how many additional violators would be identified under
the proposed revisions to the monitoring requirements.
Secondly, there is no appropriate set of cost data with
which to compute the total national costs of coliform related
remedial actions. It is not clear that the cost of installing
disinfection equipment is appropriate, for example, because it is
not clear that undisinfected systems are the ones that pose a
threat to public health. It may be more likely -that remedial
actions will consist of highly variable cost elements such as
upgrading existing disinfection equipment or improving operating
and maintenance practices.
Finally, it became clear in the course of analysis that the
remedial action costs are in fact attributable to the existing
coliform regulations (assuming enforcement) or to the forthcoming
disinfection regulation covering groundwater systems. The only
real "net" effect of proposed revisions to the coliform regu-
lations will be to impose an extra increment of monitoring cost
and expose violators earlier than they would be exposed under
existing regulations.
Viewing the presence or absence of coliforms as a stochastic
variable and assuming compliance with existing regulations is
strictly enforced, the same number of water systems would even-
4-31
-------
tuallv be singled out for remedial action. Thus the only net
resource losses to society would be the increment of additional
monitoring costs and the time value of the money spent on accel-
erated remedial expenditures. This impact will be truncated by
EPA's promulgation of a final disinfection rule for groundwater
systems, expected to occur in January, 1991. Hence, the effect
during the interim period is expected to be negligible.
The increment of additional monitoring costs was quantified
using an assumption of $15 per sample for collection, shipping,
and analytical costs (by a commercial lab). The proposed rule
affects primarily small systems where the distribution system is
not extensive. Sample collection is assumed to be joint with
other activities of the water system's generally part-time staff.
For surface water systems, it is assumed that all affected
systems will collect the number of samples specified in the
proposal. This is a worst case in which the state flexibility
afforded in the proposal (e.g., substituting sanitary surveys for
some monitoring, etc.) 'is not exercised. Costs to groundwater
systems are evaluated under two assumptions: 1) no exercise of
state flexibility ~ a worse case; and 2) maximum exercise of
state flexibility — a best case.
Based on these assumptions, the total national costs of the
additional monitoring are estimated to be $170 million annually
in the worst case and $70 million/year in the best case. The
spreadsheet models used to compute these estimates are contained
in Appendix D. In summary, the results are as follows:
Coliform Monitoring Requirements
Total National Cost fMillions!
Community Systems Non-Community Systems Aj.1 Systems
Capital Annual Capital Annual Capital Annual
No State 0 44 0 126 0 170
Flexibility
Maximum 0 24 0 46 0 70
Flexibility
In the worst case, $126 million of the total cost would be
borne by non-community systems while $44 million would be borne
by community systems. In the best case, $46 million of the total
cost would be borne by non-community systems while $24 million
would be borne by community systems. Exhibit 4-15 illustrates
this distribution.
4-32
-------
TOTAL COST IMPACT OF COLIFORM MONITORING
ON COMMUNITY VS. NON COMM. WATER SYSTEMS
j! Millions/Year)
With no slate flexibility
With maximum state flexibility
Non-Community
$126
LO
Non- Community
$46
Community
$44
Community
S24
Total = I1VO
Total = 170
-------
In the worst case, $161 million of total cost would be borne
by ground water systems while $9 million would be borne by sur-
face water systems. In the best case, $61 million of the total
cost would be borne by groundwater systems while the cost to
surface water systems would remain the same at $9 million.
Exhibit 4-16 illustrates this distribution.
In the worst case analysis, the proposed regulations will
require an additional 10,742,260 coliform samples/year, all of
them in small water systems. In the best case, an additional
3,410,884 coliform samples per year will be required of these
same small systems. Most of these will be required of non-
community systems which will be forced to switch from quarterly
to monthly sampling.
The 52,129 community water systems and 141,480 non-community
water systems affected by these requirements serve a total of 63
million people.
4.4 Implementation Costs To State Regulatory Programs
Within 18 months of the promulgation of the Surface Water
Treatment Rule (SWTR), states having primary enforcement respon-
sibility under SDWA must incorporate the new regulations in their
state regulations. Within the following 12 months, they must
make "determinations," using the criteria in the rule, as to
which systems must filter. Following the determinations, 18
months are allowed for systems to obtain compliance.
This implementation program will require considerable effort
by state regulatory programs. Not only must determinations be
made regarding unfiltered systems, but determinations must also
be made regarding filtered systems to confirm that their filtra-
tion practices are adequate in terms of the performance require-
ments specified in the SWTR.
One of the findings of the survey of existing treatment
performed by the Association of State Drinking Water Administra-
tors (ASDWA)17 is that while a number of states have excellent
data bases, as of 1985 many others lack a complete, up-to-date
inventory of the treatment-in-place in surface water systems.
Treatment-in-place is only a voluntary reporting element to FRDS
under state/EPA primacy agreements. Few states have complete
information regarding non-community systems. It appears, there-
fore, that considerable effort will have to be expended just to
develop the basic inventory necessary for implementation of the
proposed SWTR.
17oo. Cit.. ASDWA, 1986.
4-34
-------
TOTAL COST IMPACT OF COLIFORM MONITORING
ON GROUND VS. SURFACE WATER SYSTEMS
($ Millions/Year)
With no stale flexibility
With maximum state flexibility
i
Ground
$161
Ground
$61
Surface
$9
Total = $170
Total = 170
-------
In a 1986 survey effort, the Association of State Drinking
Water Administrators (ASDWA)18 solicited estimates of the amount
of effort conceivably involved. A preliminary outline of SWTH
requirements was attached to the questionnaire. The results
indicated that many respondents did not fully appreciate the
extent of the implementation requirements. For example, several
responses from states which have mandatory filtration laws
already in place indicated zero additional cost. The need to
also make "determinations" with respect to turbidity and other
SWTR performance requirements applicable to filtered systems was
obviously overlooked by these respondents. The estimate produced
by the survey is that an additional $6.9 million per year will be
required over a five year period (1987-1991) to implement the
SWTR.
The EPA Office of Drinking Water has developed an indepen-
dent estimate of the effort to be required of state programs in
implementing the SWTR from making determinations through over-
seeing construction. The assumptions are as follows:
Implementation Effort Required Per System
(Person Years)
System Size Category Filtered Systems Unfiltered Systems
< 10,000 0.25 0.25
10,000 to 50,000 0.25 0.50
50,000 to 100,000 0.50 1.00
100,000+ 1.00 5.00
Based on these assumptions, and the number of systems in
each category, the total estimated cost of implementation is
$111.45 million. If this is spread over four years, the annu-
alized costs are $27.86 million per year. If implementation
takes longer to complete, total costs will remain the same
(except for the time value of money) while annualized costs will
be reduced.
18A Survey of Resource Needs of State Drinking Water
Programs. Association of state Drinking Water Administrators,
April 1987.
4-36
-------
5. ASSESSMENT OF BENEFITS
The analysis presented in this chapter concerns both the
assessment of benefits and the comparison of costs and benefits.
The comparison of costs and benefits is considered in the same
chapter because data and methodologies involved in assessing
benefits are affected by a number of significant sources of
uncertainty.
It becomes necessary, therefore, to turn the question of
benefits and costs around, in places, and ask the question in an
alternative fashion: "What would have to be assumed about bene-
fits in order to conclude that the level of benefits is compar-
able to that of the costs?" When the answer to this alternative
form of the question is known, the key to the analysis then
becomes assessing the reasonableness of the required assumptions
in light of the inherent uncertainties.
It is important to note that a regulatory impact analysis
(RIA) containing an analysis of costs and benefits is required
for compliance with Executive Order 12291, but is not the basis
for decisionmaking under the SDWA.
Removal of microbiological contaminants from drinking water
must be viewed as a total process in the sense of the diagram
presented as Exhibit 4-1. A combination of treatment techniques,
monitoring strategies, and other measures is applied to the over-
all water supply system for the purpose of reducing the exposure
to microbial waterborne disease agents. It is therefore the
"reduction in the risk of waterborne disease" which constitutes
the benefit of efforts to remove these microbial contaminants.
The value of a reduction in risk to an individual is the amount
that person would be willing to pay to achieve it, other things
being equal.1
Economic research has not yet produced quantitative esti-
mates of the marginal willingness to pay for an extra margin of
safety in drinking water — the insurance attribute discussed in
preceding chapters. Thus, the commonly used alternative approach
of evaluating "damages avoided" has been adopted for purposes of
quantitative analysis. However, it must be noted that there is
an implied warranty implicit in the nature of consumption (as
discussed in Chapter 3) which suggests there is some extra mea-
sure of willingness to pay for safety in drinking water that goes
beyond the expected value of avoided damages.
In other words, there is benefit in simply knowing that the
water coming out of the tap is safe to drink. Resources for the
Future investigators have posed a reciprocal statement of this
1Freeman, A. M., The Benefits of Environmental Improvement.
Resources for The Future, Washington, D.C., 1979, P. 168.
5-1
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benefit concept in terms of a type of damage, calling it, in
effect, "anxiety damages"2 (i.e., not knowing whether the water
is safe to drink) . Moreover, they point out that if loss of
confidence in a water system is sufficient to produce averting
behavior among its customers, the social costs could be quite
significant. It is therefore critical to note that this poten-
tially important category of damages is not included in the quan-
titative analysis. It is of further importance to recognize that
the Safe Drinking Water Act requires drinking water standards to
incorporate a margin of safety.
The costs of the Surface Water Treatment Rule (SWTR) and the
surface water portion of the Coliform Rule apply to the same
benefits. The two sets of requirements must be viewed as two
parts of an integrated strategy to prevent microbial contamina-
tion in surface water systems. Since costs differ between fil-
tered and unfiltered surface water systems, they are evaluated in
separate analyses.
The costs of the aroundwater portion of the Coliform Rule
are different in concept from the costs to surface water systems
in that they relate to only one aspect (i.e., monitoring of coli-
forms) of the total approach to avoiding contamination from
microbial contaminants. The focus of analysis is a comparison of
the additional increment of monitoring cost versus the additional
increment of benefit derived from the monitoring data. Despite
the narrow focus of the g;roundwater portion of the Coliform Rule,
data is also presented in this chapter which characterizes the
overall size of the benefit target in groundwater systems (e.g.,
the number of waterborne disease outbreaks, cases of disease,
etc.).
This chapter is organized in two major sections which pre-
sent two different types of analyses. In the first section,
aggregate benefits and costs to the nation are assessed. The net
benefits at the level of individual water systems are the subject
of the second section.
5.1 Aggregate Analysis
Executive Order 12291 requires development of an estimate of
the total costs and total benefits to the nation imposed by pro-
posed regulations. Unfortunately, such numbers lend themselves
to simple aggregate benefit/cost comparisons. The structure of
the water industry, illustrated in Exhibit 5-1, causes such
aggregate comparisons to produce a deceiving picture of the true
relationship between benefits and costs at the level of indivi-
dual water systems. Aggregate cost-benefit comparisons are
2Harrington, W., Krupnick, A, and Spofford, W., The Benefits
of Preventing An Outbreak of Giardiasis Due To Drinking Water
Contamination. Resources For The Future, September, 1985, P.9-6.
5-2
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EXHIBIT 5-1
u.
10
SIZE DISTRIBUTION OF CWSs
FY 1985
% Distribution
70- 63.9
60 -
25-500 501-3.3K 3.3K-10K 10K-100K
Population Size Categories
D9 Total # of Systems
> 100K
Total Pop Served
-------
flawed in that they tend to average together an excess of posi-
tive net benefits in very large water systems with an excess of
negative net benefits in very small water systems.
It is advantageous to view the aggregate estimates as illu-
strative indicators of the "order of magnitude" of the problem at
the national level. Net benefits should be analyzed only at the
system level as discussed in the second half of this chapter.
With respect to the problem of microbial contamination of
water supplies, there is an additional flaw inherent in aggregate
analysis. The primary type of damage to be avoided is the inci-
dence of waterborne disease. This damage is manifest in two
forms: 1) there is an endemic level of disease which persists
continuously because some microorganisms are able to escape
treatment for a variety of reasons; and, 2) there are episodic
outbreaks of disease when large numbers of pathogens are able to
escape treatment and become present in water delivered to con-
sumers .
The damages inflicted by outbreak events include much more
than the direct costs to the individuals who become ill such as
medical expenses and time lost from work or leisure. In a study
of the 1983-84 outbreak of giardiasis which occurred in Luzerne
County, PA,3 Resources for the Future investigators estimated
that such costs accounted for only 15.5 percent of the total
social loss. The majority of the social costs were due to the
averting behavior of individuals engaging in activities such as
boiling water or purchasing bottled water. There were also costs
borne by businesses, units of government, and the local water
utility. These categories of costs are unique to each individual
outbreak event and cannot be generalized. Thus, the only out-
break damages which can be aggregated are the costs to indivi-
duals who become ill. This is indicated by the number of cases
of disease reported as a result of waterborne disease outbreaks.
Beyond the fact that the number of cases of waterborne dis-
ease is an incomplete- indicator of total benefits, the available
data with which to assess this indicator are notoriously incom-
plete. The Center for Disease Control (CDC) in Atlanta, operates
a joint program with EPA to collect reports of incidences of
waterborne disease outbreak and tabulate national totals on an
annual basis. Neither CDC nor EPA has significant resources
allocated to the task of conducting follow-up investigations or
in-depth epidemiological studies. The data are collected, tabu-
lated, and broadly interpreted. CDC terms the reporting system a
"passive" one.4 Several EPA investigators have performed de-
3ibid.
4Center for Disease Control, Water-Related Disease Out-
breaks; Annual Summary 1982. U.S. Department of Health And Human
Services, Atlanta, 6A.
5-4
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tailed reviews of the data to try to fill in missing entries,
conduct limited follow-ups, and reconstruct a better data base
for analysis. However, the numerous sources of error are too
great to overcome completely.
Underreporting is the major problem in the CDC data base.
CDC analysts suspect the data "contains only a small and variable
fraction of the outbreaks and cases that occur each year in the
United States."5 For extensive periods, no reports were filed by
over half the states. Conversely, 46 percent of the outbreaks
reported in 1982 were reported by four states. The four states,
however, consisted of Colorado, Vermont, Washington, and Pennsyl-
vania. The first three had recently received EPA grants to dem-
onstrate means of improving surveillance systems. Pennsylvania,
on the other hand, already has a well-developed surveillance
system. This suggests that better surveillance nationwide could
reveal a much larger problem than present data indicate.
The predominant symptoms of waterbome disease are acute
gastrointestinal pain, diarrhea, and nausea. Approximately half
of all reported cases are characterized generically as "gastroen-
teritis," meaning a specific etiologic agent was not identified.
Such symptoms could, of course, result from a number of other
causes as well (e.g., food poisoning). It has been estimated
that gastroenteritis is second only to the common cold as the
most frequent illness affecting the population of the United
States.6
Despite all of the aforementioned analytical and conceptual
problems with aggregate benefit analysis, an attempt must none-
theless be made to estimate the total number of cases of water-
borne disease which may be avoided through improved water treat-
ment. The steps entailed in fabricating such an estimate are
outlined below.
For unfiltered surface water systems, the outbreaks of
waterbome disease reported to CDC over the period 1971 to 1985
are as follows (from Exhibit 2-6):
CDC Data 1971-85
Type of Unfiltered System Outbreaks Cases
Systems With No Treatment 15 1,458
Systems With Disinfection Only 67 23,028
5ibid.
^Acute Conditions! Incidence And Associated Disability.
United States July 1974 - June 1975. National Center For Health
Statistics, Series 10, No. 114, U.S. Dept. Of Health Education
and Welfare, Washington, D.C., 1977.
5-5
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Using this data, the average number of outbreaks per year
and the average number of cases per outbreak are computed.
Average Number of Reported Outbreaks Per Year
No Treatment: 15 outbreaks/15 yrs - 1 outbreak/yr
Disinfection: 67 outbreaks/15 yrs = 4.467 outbreaks/yr
Total « 1 + 4.467 » 5.467 outbreaks/yr
Average Number of Reported Cases Per Reported Outbreak
No Treatment: 1,458 cases/15 outbreaks =97.2 cases/outbreak
Disinfection: 23,028 cases/67 outbreaks * 343.7 cases/outbreak
There are believed to be two types of underreporting which
affect the CDC data. First, the number of outbreaks is believed
to be underreported. And, second, the number of cases of disease
associated with outbreaks that are reported is believed to be
underreported also.
A recent project to improve surveillance of outbreaks in
Colorado resulted in a four-fold increase in reported outbreaks.7
It is assumed the Colorado result is a representative estimate of
the extent of underreporting of outbreaks. To produce a lower
bound estimate of the number of cases of disease per year, it is
assumed there is no underreporting of the number of cases per
outbreak. Under this assumption, the lower bound is computed as
follows.
Lower Bound Estimate of The Number of Outbreak Cases Per Year
In Unfiltered Systems
No Treatment:
1 outbreak/yr x 4 x 97.2 cases/outbreak » 388.8 cases/yr
Disinfection:
4.467 outbreaks/yr x 4 x 343.7 cases/outbreak » 6,141.2 cases/yr
Total - 388.8 + 6,141.2 - 6,530 cases/yr
An estimate of the upper bound of the number of cases per
year may be developed by assuming the maximum plausible attack
rate for all outbreaks and applying it to the total population
served by the affected water systems. The total population
served by the affected water systems is developed using the
following data from the ASDWA survey:
7Hopkins, R., et. al., "Waterborne Disease In Colorado:
Three Years Surveillance and Eighteen Outbreaks," American
Journal of Public Health. V.7, No. 3, 1985.
5-6
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Number of Unfiltered Water Systems
Community Systems Serving > 100,000 15
Community Systems Serving < 100,000 1,331
Non-community Systems Serving < 100,000 1,536
The systems serving fewer than 100,000 persons and the sys-
tems serving more than 100,000 persons are analyzed separately.
There are 2,867 (1,331 + 1,536) community and non-community
unfiltered surface water systems serving fewer than 100,000 per-
sons. Most of these systems are quite small. For the group, the
average population served per system is 1,974. Using this aver-
age population, the total population exposed per year in systems
experiencing outbreaks can be computed, as follows:
Total Population Exposed
In Unfiltered Systems Serving <100fOOO And Experiencing Outbreaks
5.467 outbreaks/yr x 4 x 1,974 persons exposed = 43,167 persons
exposed/yr
Available data on reported outbreaks indicates that attack
rates can be fairly high in small water systems. This finding is
supported by engineering rationale, small systems can be quickly
and near universally contaminated simply because they are small
in physical extent, thus leading to high attack rates. The
highest attack rates reported in small systems are in the neigh-
borhood of 50 percent. Using this as an assumption, the maximum
number of cases of disease in this system size category is com-
puted as follows:
Maximum Number of Outbreak Cases
In Unfiltered Systems Serving <100.000 And Experiencing Outbreaks
43,167 persons exposed/yr x 0.5 attack rate » 21,584 cases/yr
In systems serving more than 100,000 persons, both outbreak
rates and attack rates appear to be lower. In the 1983 giardia-
sis outbreak in Luzerne County, PA, Resources for the Future
estimates there were 6,000 cases. The late 1970's and early
1980's have been characterized by one or two outbreaks of this
magnitude per year. To represent the group of 15 large unfilter-
ed systems, it is assumed that there is one outbreak per year of
the same size as that which affected Luzerne County, PA. Thus,
the total upper bound estimate of the number of cases of disease
per year due to outbreaks is as follows:
Upper Bound Estimate of The Number of Outbreak Cases Per Year
In All Unfiltered Systems
21,584 cases/yr in systems serving < 100,000 + 6,000 cases/yr in
systems serving > 100,000 » 27,584 cases/yr
5-7
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To obtain •the complete picture, it is necessary to also
develop an estimate of the total number of cases of disease per
year that are attributable to the endemic condition in unfiltered
water systems. The endemic level of disease is expressed in
terms of the percent of the population exposed that will be sick
per year, as follows.
endemic level » number of cases/yr in unfiltered systems x 100%
total population of unfiltered systems
It is important to recognize that it is the endemic level in
unfiltered systems that is of interest. In Luzerne County, PA,
the endemic level of giardiasis was estimated to be one percent.
EPA has been unable to find other estimates of the endemic level
of waterbome disease in unfiltered systems. It is believed,
however, that the endemic level in the larger unfiltered systems
is not as great as it might be in very small unfiltered systems
for many of the same reasons that outbreak attack rates differ.
Therefore, the following assumptions have been chosen as upper
and lower bounds for the endemic level of waterborne disease in
unfiltered systems.
Upper And Lower Bound Estimates For The Endemic Level
Of Waterborne Disease In Unfiltered Systems
Upper Lower
Bound Bound
Large Water Systems 0.5 % 0.25 %
Smaller Water Systems 1.0 % 0.5 %
Applying these assumptions for the endemic level of disease
to the total populations exposed in the two size classes of water
systems yields estimates of the total number of cases of disease
attributable to the endemic level, as follows:
Upper Bound Estimates of The Number of Cases
Of Waterborne Disease In Unfiltered Systems
Attributable To The Endemic Level
Large Systems:
16,000,000 persons exposed/yr x .005 » 80,000 cases/yr
Smaller Systems:
5,649,353 persons exposed/yr x .01 » 56,494 cases/yr
Total:
80,000 4- 56,494 - 136,494 cases/yr
5-8
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Lower Bound Estimates of The Number of Cases
Of Waterborne Disease In Unfiltered Systems
Attributable To The Endemic Level
Large Systems:
16,000,000 persons exposed/yr ^ .0025 « 40,000 cases/yr
Smaller Systems:
5,649,353 persons exposed/yr x .005 « 28,247 cases/yr
Total:
40,000 + 28,247 - 68,247 cases/yr
The total number of cases of waterborae disease in unfilter-
ed systems annually is computed by summing the respective upper
and lower bound results for the outbreak analysis and the endemic
level analysis. These grand totals are as follows:
Estimated Total Number of Cases of Waterborne Disease Per Year
In Unfiltered Systems
Upper Lower
Bound Bound
Outbreak Cases 27,584 6,530
Endemic Cases 136.494 68.247
Total Cases 164,078 74,777
Estimates of the number of cases of waterbome disease per
year in filtered water systems were also developed using an
exactly analogous methodology to that described above for unfil-
tered systems. The data source for outbreaks in filtered systems
is the CDC data summarized in Exhibit 2-6. The ASDWA survey is
the data source for the number and size of filtered systems that
have an average turbidity between 0.3 and 1.0 NTU. All assump-
tions and steps in the procedure are identical except that the
endemic level assumptions were halved for filtered systems. The
resulting estimates of the number of cases of waterborne disease
in filtered systems are as follows:
Estimated Total Number of Cases of Waterborne Disease Per Year
In Filtered Systems
Upper Lover
Bound Bound
Outbreak Cases 35,159 2,653
Endemic Cases 269.543 134.772
Total Cases 304,702 137,425
5-9
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On the surface, there appears to be reason to question
whether cases of waterborne disease in filtered systems could not
be avoided simply through improved compliance with existing tur-
bidity standards. Part of the scientific basis for the proposed
SWTR, however, is the very fact that there have been documented
outbreaks in systems meeting the present turbidity standard. It
has been demonstrated that Giardia cysts and viruses can pass
through direct filtration and conventional treatment plants meet-
ing a standard of 1.0 NTU.
As discussed at the outset of this chapter, aggregate esti-
mates of the number of cases of disease avoided invite aggregate-
level cost-benefit comparisons in the form of estimates of the
"cost per case of disease avoided." Such estimates are poor, and
perhaps misleading, indicators of the true relationship between
benefits and costs in the water industry. Nonetheless, estimates
of the cost per case avoided have been requested in this regula-
tory impact analysis. Such estimates are presented below based
on the upper and lower bounds of the number of cases of disease
derived above and the extreme high and low total annual cost
estimates presented in Chapter IV for SWTR compliance by unfil-
tered systems and filtered systems.
Cost Per Case Calculations
($'s/case)
Upper Lower
Bound Bound
Unfiltered Systems
High Cost Scenario 3,779 8,291
Low Cost Scenario 1,317 2,889
Filtered Systems
High Cost Scenario 433 961
Low Cost Scenario 112 247
As noted elsewhere, the portion of the Total Coliform Rule
'which applies to groundwater systems is only part of the total
approach to control of microbial contaminants in ground water.
Thus/ while the number of cases of waterborne disease in ground-
water systems is the overall target to which the Total Coliform
Rule applies, those cases of disease will not be eliminated by
coliform monitoring alone. Nonetheless, so that the size of the
target in groundwater systems may be appreciated, an estimate of
the total number of cases of disease in groundwater systems has
been developed. The data sources and methodology are identical
to those described above for unfiltered surface water systems
except that the assumptions regarding the endemic level of dis-
ease have been halved. Results are as follows:
5-10
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Estimated Number of Cases of Waterbome Disease
In Groimdvater Systems
Upper Lower
Bound Bound
Outbreak Cases 22,592 13,912
Endemic Cases 499.474 249.737
Total Cases 522,066 263,649
5.2 System Level Analysis
The economic benefits of drinking water standards may be
defined as the total willingness to pay for safe potable water.
The safety attribute of the good is the relevant aspect of demand
to be the focus of analysis. The willingness to pay for safety
in drinking water may be regarded as consisting of two compo-
nents: (1) the expected value of the damages that would be incur-
red in the absence of the standard; and, (2) the value of an
extra margin of safety — a warranty — which provides assurance
to consumers, and to society as a whole, that it can be taken for
granted the water is safe to drink.
Given the current state of economic research related to
drinking water, it is not possible to quantify the latter of
these two components. There is evidence from several places
which indicates the second component of the willingness to pay
for safe drinking water may be quite significant. This missing
component of benefit must therefore be kept in mind while review-
ing results of analyses based on the narrower concept of the
expected value of quantifiable damages.
EPA developed a model to estimate the hypothetical economic
damages resulting from the endemic occurrence and outbreak occur-
rence of waterbome giardiasis and other waterbome disease. The
damages are the costs to communities from water contamination,
such as medical costs to the afflicted individuals, resources
used to avoid contaminated water, lost productivity and leisure
due to illness, and costs involved with detecting and eradicating
the contaminant. 'These costs are borne by businesses and govern-
ment agencies as well as individuals.
The "HOPED" model is an extension of methodology developed
in an EPA sponsored study conducted by Resources for the Future
(RTF)8 in which the economic losses to a community in Pennsyl-
vania from an actual outbreak of giardiasis were estimated.
RTF warned EPA analysts that the methodology was difficult
to extend to other cases without actually performing other case
studies due to the strong influence and interaction of numerous
8Op. cit., Resources For The Future, 1985.
5-11
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site-specific and event-specific variables. The resulting model
is basically a "what if" model that allows the user to evaluate
the effect of various input assumptions on the damage estimate.
This need for user initialization lends allegorical validity to
the name selected for the model. In this mode, HOPED can be used
to perform a simple "breakeven analysis" addressing the question,
"What do you have to assume about the damage function in order to
equal the costs of filtration?" Evaluation of the reasonableness
of the required assumptions can then serve to inform decisionmak-
ing.
RFF was commissioned by the U.S. Environmental Protection
Agency to develop a basic framework for estimating the economic
losses from an outbreak of waterborne giardiasis and then to use
this methodology to estimate the economic losses for a known out-
break. Proper estimation of economic losses must rely heavily on
definitions and concepts that are well-grounded in economic
theory. Hence, RFF was the logical source for this pathbreaking
research. RFF evaluated the giardiasis outbreak in Luzeme County
which struck in the fall of 1983 and continued through the summer
of 1984.
Four major cost categories were identified: costs to indi-
viduals, costs to businesses, costs to government agencies, and
costs to water utilities. Surveys were made of the community in
Luzeme County to quantify these losses. Based on these survey
results, estimates were made of the losses from the Luzerne
County outbreak. To account for uncertainty in some of the
parameters, such as variation in the value of time of the resi-
dents in the community, RFF bracketed their results by estimating
high and low scenarios. Total costs of the outbreak ranged from
$55.5 million to $23.3 million for the respective scenarios. The
table below presents a summary of these cost estimates.
ESTIMATES FROM THE RFF STUDY
OF THE ECONOMIC LOSSES DUE TO THE LUZERNE COUNTY
OUTBREAK OF GIARDIASIS
($ MILLIONS)
Losses to Individuals
Averting Behavior
Lost Leisure Time
Lost Work
Medical Costs
TOTAL
Losses to Businesses
Losses to govt. Agencies
Losses to Water Utilities
TOTAL
HIGH
ESTIMATES
38.5
5.3
2.2
1.1
47.1
6.3
0.3
LOW
ESTIMATES
12.1
2.9
1.3
1.0
17.3
3.8
.3
55.5
23.27
5-12
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RTF's findings revealed that losses to individuals were the
most significant costs for the community. This cost category was
comprised of four cost elements: averting behavior, lost leisure
time, lost work time, and medical costs. Of these, averting
behavior represented the greatest proportion of costs ranging
from $38.5 million to $12.1 million, for the high and low
scenarios, respectively. Thus, losses from averting behavior by
individuals represented the greatest burden of the Luzerne county
outbreak, accounting for approximately 70 percent and 50 percent
of the total costs of the outbreak in the high and low scenarios.
The remaining losses for individuals, lost leisure time,
lost work time and medical costs amounted to $10.8 million and
$5.2 million in sum for the high and low cases. These repre-
sented approximately 20 percent of the total costs for both
scenarios.
Losses to businesses were estimated to be $6.3 million for
the high scenario and $3.8 million for the low scenario. Losses
to water utilities and governments, were estimated at $1.8 mil-
lion and $0.3 million, respectively, with no variation in the
high and low scenarios.
The costs estimates prepared by RFF, while thorough and
comprehensive, have omitted several costs elements, due to time
and resource constraints. Intangible costs such as pain and
suffering are not included. Losses of highly valued leisure
time, such as lost vacation plans, were not accounted for. Costs
due to mis-diagnosis also were unaccounted for. Also, the esti-
mates of losses to businesses excluded costs to some of the busi-
nesses in the community such as hotels, motels, and meat packers
that would be expected to incur losses. The businesses included
were restaurants, bars, hospitals, dentists, nursing homes,
schools and day care centers. Omission of these other cost items
introduces a downward bias to RTF's cost estimates.
RFF investigators identified the difficulties of applying
their methodology, which estimated the benefits of avoiding a
giardiasis outbreak that had already occurred, to assess the
benefits of avoiding future outbreaks. The major difficulty with
such an application is that the severity of an outbreak, that is
the duration of the discovery interval and the boil water advi-
sory, will vary and in fact will be unique to each catastrophic
outbreak event. These are the key variables which determine the
level of averting costs.
Furthermore, averting behavior of individuals will vary in
different communities because of variation in the value of time,
differences in population density, and personal preferences and
attitudes. The averting strategies adopted in Luzerne County and
their associated costs are unique to that community because of
these factors. Therefore, it would be incorrect to apply the
average averting cost found in the Luzerne County community to
other communities.
5-13
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The MOPED model for estimating the expected damages of hypo-
thetical outbreaks of waterborne disease is based on the RFF
study. It projects losses for two of their major cost categor-
ies: costs to individuals and costs to businesses. The remain-
ing two categories, costs to government agencies, and costs to
water utilities, were not incorporated into the model as these
are event-specific costs.
The model generalizes beyond the scope of the RFF study to
estimate damages for outbreaks of all types of waterborne disease
and damages attributable to the endemic level occurrence. Sep-
arate analyses ~ "mini-case-studies" — were performed for each
of the fifteen large unfiltered systems identified in the ASDWA
survey and for a gradient of nine generic size classes of systems
serving fewer than 100,000 persons. A case study of a rotavirus
outbreak in Eagle/Vail CO9 was used to adapt the model to smaller
system size ranges and extend to other types of disease agents.
MOPED requires user specification of parameters that are
unique to each community studied: demographic characteristics,
wage rates, number of business entities, schools, hospitals, day
care centers, and nursing homes. Data were gathered from various
sources such as the U.S. Census Bureau and trade associations as
appropriate for each case studied. An overview of the basis for
different categories of inputs is provided in Exhibit 5-2.
To account for the uniqueness in severity of an outbreak,
MOPED incorporates a sensitivity analysis, by calculating losses
for three levels of severity: high, medium, and moderate scen-
arios. To estimate parameters for the outbreak duration period
for these three scenarios, data on 20 reported outbreaks pres-
ented in the RFF study were analyzed. These data revealed that
the reported outbreaks had durations ranging from one to seven
months. The mean duration was 2.9 months, with 40 percent of the
outbreaks lasting two months, and 15 percent of the outbreaks
lasting five months. Durations may be longer in larger systems
such as Luzerne County due to the lag in recognizing an outbreak
event. In smaller systems, attack rates are likely to be higher
due to the small size of the system and lack of recognition is
therefore less likely. Given these considerations, the following
assumptions were made:
Outbreak Intensity Assumptions
(Duration In weeks)
gyatem Size Category Severe Medium Moderate
> 50,000 30 22 13
3300 - 50,000 22 22 13
< 3300 13 13 13
9Hopkins, R., Karlin, R., Gaspard, G.B., and Smades, R.,
"Gastroenteritis: Case Study of A Colorado Outbreak," Journal of
The American Water Works Association, January, 1986.
5-14
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EXHIBIT 5-2
DETAILS OF METHODOLOGY
FOR SYSTEM LEVEL ANALYSIS
1. Duration of outbreak and Length of Boil Water Advisory-
high, medium, and low assumptions based on review of reported
outbreaks and adjusted by system size category.
2. Clinical Attack Rate — high, medium, and low assumptions
based on review of reported outbreaks and adjusted by system
size category.
e aod Daaocrraphio
1. Population Served — 1st hand data for the 15 large systems;
averages for the nine generic size categories.
2. Number of Households; Percent of Population Employed Versus
Homemakers And Retired — 1980 Census; Population Character-
istics.
3. Percent of Population That Are Caretakers — Default assump-
tion: same as Luzerne County.
4. Wage Rates — 1980 Census data on total salaries and wages
divided by BLS data on the number of hours worked. Specific
data for 15 large cities; national averages for nine generic
cases .
Direct Medical Costa (2% of RFF damages)
Default assumptions from Luzerne County for: number of doctor
visits; number of E.R. visits; costs of lab tests; medication;
time in travel; and hospital izat ion.
iiOflt Work Time and Lost Productivity (4% of RFP damages)
Default assumptions from Luzerne County for: number of work days
lost (per employed person) ; number of days sick but working; and
number of days lost caretaking.
Lost Lieaure Tine (10% of KIT damages)
Default assumption from Luzerne County for the amount of liesure
time lost.
5-15
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EXHIBIT 5-2 (Cont'd.)
Averting Behavior (69% of RFP damages)
High Scenario — 100% use bottled water
Low Scenario — 100% boil water
Leases to Businesses (11% of RF7 damages)
1. For 15 large cities, number of restaurants, bars, hospitals,
day care centers, dentists, and schools was taken from U.S.
Census, County Business Patterns.
2. For nine generic cases, number of establishments was scaled
(based on Luzerne County) as a function of population from
the 75,000 to 100,000 category down to the 3300 to 10,000
category. For the four categories below 3300 population,
analysis of business losses was dropped.
3. Elasticity of demand for restaurant services was available
from the National Restaurant Association for estimating
losses in consumers surplus. NRA data on restaurant profits
and sales was available for evaluating lost profits. Wage
rates for employees engaged in averting activities were
estimated using data from the U.S. Census, County Business
Patterns.
4. By default, unit costs of averting actions in the different
types of business establishments were taken from Luzerne
County results.
Losses to Govanwnap'fcs and Water Utilities (4% of RTF damages)
Accept RTF determination that this variable is hopelessly site-
specific and event-specific. No attempt to estimate. However,
it must be noted that this category of damages may be much more
significant in small systems than it was in Luzerne County.
5-16
-------
These three scenarios are assigned equal weights to collapse
this dimension of variability into a "representative" outbreak in
presentation of MOPED results. The duration of the outbreak is
related to another critical variable: the length of the boil
water advisory. Based on analysis of the findings in both
Luzerne County, PA and Eagle/Vail, CO, the following assumptions
were made:
Boil Water Advisory
(Duration In Weeks)
System Size Cateaorv Severe
> 50,000
3300 - 50,000
< 3300
24
16
7
Medium
16
16
7
Moderate
7
7
7
Also, the clinical attack rate, which is the percent of the
community stricken, is varied in the three outbreak scenarios to
account for differences in severity. The clinical attack rate
inputs were also based on comparative findings in Luzerne County,
PA versus Eagle/Vail, CO. The assumptions are summarized as
follows:
Attack Rate Assumptions
(Percent of Population)
System Size Category
> 50,000
3300 - 50,000
< 3300
Severe
8
20
45
Medium
8
15
20
Moderate
8
10
10
The attack rates are applied to the population served in
order to obtain estimates of costs to individuals. The popula-
tion served also factors into the computation of averting costs.
The actual populations served by the 15 large water systems was
used in the analysis. This results in a somewhat lower damage
estimate because these 15 large systems are located in major
metropolitan areas characterized by extensive home-to-work com-
muting and interstate visitation. Thus, the population exposed
is estimated conservatively.
MOPED builds on the findings of the RFF study to account for
the uniqueness of averting behavior among communities. Rather
than using the average averting costs determined for Luzerne
5-17
-------
County, the model calculates high and low estimates for each of
the three outbreak scenarios based on the extreme strategies for
averting behavior as revealed in RTF's survey of the stricken
community. The high estimates assume that all individuals in the
community purchase bottle water in their attempts to avoid the
giardia contaminated tap water. The low estimates assume that
all individuals in the community chose to boil water as an avert-
ing strategy. Therefore, these two estimates represent upper and
lower bounds for costs associated with averting behavior, which
was shown to be the most significant cost category in the RFF
study.
Many of the other statistics used in MOPED that are more
generic across communities, were assumed to be the same as in the
Luzerne County outbreak. In general these were related to less
significant cost elements. For example, the duration of illness
and average number of trips to physicians for victims stricken
with giardiasis are statistics which would be expected to vary
only slightly between individuals in different communities.
Finally, two cost elements which RFF identified in the
Luzerne County study were not included in the MOPED. These were
costs to government agencies and costs to water utilities.
Because of the nature of these two cost elements, it is not pos-
sible to model them on an a priori basis. These costs will be
unique to a specific outbreak and depend on such factors as the
specific configuration of a water system. In small systems, the
coping costs incurred by local governments and utilities may be
quite significant. In a case such as Luzerne County, they amount
to a small proportion of total damages. In Eagle/Vail, however,
these costs were estimated to be on the order of $90,000 which is
substantial for a community of 3540 residents.
MOPED was used to estimate the economic costs for the
Luzerne County outbreak excluding the costs to government agen-
cies and to water utilities. The results are listed below:
ESTIMATES FROM MOPED
OF THE ECONOMIC LOSSES DUE TO THE LUZERNE COUNTY
OUTBREAK OF GIARDIASIS
($S MILLION)
Losses to Individuals:
Averting Behavior
Lost Leisure Time
Lost Work
Medical Costs
TOTAL
Losses to Businesses
TOTAL
HIGH
ESTIMATES
41.4
4.0
2.0
1.7
51.1
6.0
57.0
LOW
ESTIMATES
13.1
2.9
1.3
1.7
19.0
3.4
22.4
5-18
-------
These estimates from MOPED compare favorably with the esti-
mates from RFF for the two cost categories, losses to individuals
and losses to businesses. RTF's cost estimates are stated in
1984 dollars, while WMA's estimates are in 1986 dollars.
The MOPED estimate for losses to individuals is approxi-
mately eight percent higher than RFF's estimate in the high
scenario and nine percent higher for the low estimates. After
accounting for inflation, this difference is less than five per-
cent, which is insignificant.
Specifically, individual losses due to averting behavior
were $41.4 million and $13.1 million for the high and low esti-
mates of MOPED, which correspond even closer to the RFF estimates
of $38.5 million and $12.1 million, respectively, after adjusting
these numbers for inflation. Because this is the most signifi-
cant cost element associated with the outbreak, it is crucial
that MOPED produces estimates for averting behavior that corres-
pond closely with the RFF results in this calibration run for
Luzerne County.
Estimates from MOPED for lost leisure time and lost work are
slightly lower than the estimates made by RFF for these cost ele-
ments for both the high and low cases. However, these costs
account for a relatively small proportion of the total losses
from the outbreak,and, therefore, do not result in a significant
overall impact. Also, the estimates for losses to businesses
produced by MOPED are slightly less than the RFF estimates, but
again this difference is not significant because of small size in
comparison to total losses resulting from the outbreak.
By far the two most important input assumptions to the MOPED
model are the assumed probability of an outbreak of waterborne
disease and the assumed endemic level of waterborne disease. The
model was constructed to allow evaluation of a broad range of
"what if" assumptions regarding these two variables. The diagram
in Exhibit 5-3 illustrates the framework of the breakeven anal-
ysis supported by the model. The graph illustrates the nature of
the trade-off between treatment costs and the total damages pro-
duced by the two types of disease incidence.
The problem facing a local water system manager may be
regarded as one of finding the least cost option. On the one
hand, the annual cost of installing treatment, represented by the
horizontal line on the graph, is invariant with respect to the
degree of risk of waterborne disease outbreak or the endemic
level of disease. On the other hand, the annual expected value
of the damages of waterborne disease, from either an outbreak or
an endemic condition, is a function of the level of risk. Based
on his assessment of the risk of contamination, a system manager
could make a rational decision regarding the need for filtration
using this framework.
5-19
-------
EXHIBIT 5-3
FRAMEWORK OF BREAKEVEN ANALYSIS
Ui
10
o
E [LOSS]
MILLIONS
PER YEAR
ANNUAL COST
OF FILTERING
ANNUAL E [DAMAGES]
FROM NOT FILTERING
I I
ANNUAL PROBABILITY OF OUTBREAK
P
i i
ANNUAL ENDEMIC LEVEL
(% OF POPULATION)
-------
If the annual expected value of the damages exceeds the
annual cost of filtration (i.e., the crossover point in the dia-
gram) , then filtration is a breakeven proposition for the system,
based on quantifiable damages alone. If, on the other hand, the
preferred set of assumptions regarding the annual endemic level
of disease and the annual probability of outbreak do not produce
a damage function that equals or exceeds the level of the annual
cost of filtration, the difference may be made up by a judgement
regarding the extent of additional willingness to pay for a
margin of safety.
To evaluate the combined effects of both the probability of
outbreak assumption and the endemic level assumption, MOPED
produces a summary output report. A sample MOPED output report1
is presented in Exhibit 5-4. The MOPED output report provides
tables of net losses or gains produced by subtracting the annual
cost of installing filtration (annualized at 3 percent10) from
the annual expected value of the damages associated with various
combinations of assumptions regarding the endemic level and the
probability of outbreak.
The points in these tables where net losses or gains
approach zero indicate points at which filtration is a breakeven
proposition on the basis of quantifiable damages alone. Results
are presented for four scenarios, encompassing high and low
ranges of treatment costs and damage estimates. A final summary
table presents a profile of the liklihood of obtaining positive
net gains by summing the number of positive reults across the
four cost scenarios for each combination of assumptions regarding
the probability of outbreak and the endemic level of disease.
Appendix E presents output reports for each of the 15
unfiltered systems serving more than 100,000 persons. Appendix F
contains output reports for the gradient of nine generic size
categories serving fewer than 100,000 persons.
Exhibits 5-5 through 5-8 present a summary of the MOPED
results. The diagrams in these Exhibits display the set of all
feasible breakeven points for each system size category. This is
shown in the diagram by the diagonal lines which reflect the
relative contributions of the endemic and outbreak assumptions to
total damages. In some cases, the threshold level of assumptions
10A risk-free, inflation-free interest rate is the proper
basis for annualizing when costs are being compared to benefits
because financial risk and the risk of inflation are artifacts of
financial markets that have no relevance to benefits and produce
an assymetric bias in the comparison. Benefits should be
compared on the basis of the true social cost of capital; the
pure time value of money. This is appropriately regarded as a
long-term concept. Estimates typically range from 3 to 5
percent. There is much disagreement in the economic literature
over the choice of a number to use.
5-21
-------
EXHIBIT 5-4
SAMPLE OUTPUT OF SYSTEM LEVEL NET BENEFITS ANALYSIS
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.98
Damages -from Endemic Level o-f I'/. 1.721
Damages -From A Representative Outbreak 67.717
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.9
<".) . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
o.s
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
— *7
_/~l
_ D
— 1
-1
-1
-1
-1
-1
-0
-0
-0
0
0
0
1
1
1
1
1
1
0.005
— *?
-1
-1
-1
-1
» 1
-1
-0
-0
-0
0
0
0
1
1
1
1
1
1
o
2
0.01
-1
-1
-1
-1
-1
-0
-0
-0
o
0
0
1
1
1
1
1
1
2
o
*i~
*2
2
0 . 02
-1
-0
-0
-0
0
0
0
1
1
1
1
1
1
~\
^.
o
*^
^»
^
•^1
*•}
Tt
3
0. 03
0
0
0
1
1
1
1
1
1
*-\
^
o
^1
4L.
O
2
TJ
-?
• '^j
3
|7|
•••
0. 04
1
1
1
1
1
•"!*
T?
2
*?
2
^7
C*
3
--•
w
"T
7T
4
4
4
4
0.05
1
2
2
^
*^»
*n
~\
•Zi
3
3
O
^T
"^
4
4
4
4
4
5
5
'5
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost ot Filtration 1.98
Damages -from Endemic Level o-f I"/. 1.177
Damages -from A Representative Outbreak 26.372
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.9
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1 .6
1.7
1.8
1.9
2.0
O
*-t
_2
_o
-2
—.0
-1
» 1
-1
-1
-1
-1
-1
-1
-0
-0
— o
-0
0
0
0
0
0 . 005
— T>
-«*!>
— O
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
0
0
0
0
1
0 . 0 1
-2
_^\
-1
— 1
-1
w» ^
-1
-1
-1
-1
-1
-0
-0
-0
-0
0
0
o
0
1
1
5-22
0.02
-1
_ 1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
0
0
o
o
1
1
1
1
0.03
-1
— 1
-1
-1
-1
-1
-o
-0
-0
-0
-0
0
0
0
o
1
1
1
1
1
1
O.O4
-1
— 1
-1
-1
-0
-0
-0
-0
0
0
0
0
0
1
1
1
1
1
1
1
1
0.05
-1
w I
-0
-0
-0
-0
0
0
0
0
1
1
1
1
1
1
1
1
1
2
*^
-------
EXHIBIT 5-4 (Cont'd.)
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.55
Damages -from Endemic Level o-f 17. 1.721
Damages -from A Representative Outbreak 67.717
ANNUAL PROBABILITY OF OUTBREAK
-1.5 0 0.005 0.01 0.02 O.03 0.04 0.05
E 0.0 -2 -1 -1 -0 0 1 2
N 0.1 -1 -1 -1 -0 1 1 2
D 0.2 -1 -1-1 0 1 22
£ 0.3 -1 -1 -0 0122
M 0.4 -1 -1 -0 0 1 2 3
I 0.5 -1 -0 -0 1123
C 0.6 -1 -0 01223
0.7 -0 -0 01223
L 0.8 -0 0 1 1 2 3 3
E 0.9 -0 0112 3 3
VI.0 0 1 1 2 2 3 4
El.l 0 1 1 2 2 3 4
L 1.2 1112334
1.3 1112334
1.4 1 122344
1.5 1 122344
1.6 1 2 2 3 3 4 5
1.7 1223345
1.8 2223445
1.9 2223445
2.0 2 2 3 3 4 5 5
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 1.55
Damages -from Endemic Level o-f I"/. 1.177
Damages -from A Representative Outbreak 26.372
ANNUAL PROBABILITY OF OUTBREAK
-1.5
E 0.0
N 0.1
D 0.2
E 0.3
M 0.4
I 0.5
C 0.6
0.7
L 0.8
E 0.9
V 1.0
E 1.1
L 1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
•2
•1
•1
•1
•1
•1
1
•1
•1
•0
0
•0
0
•0
0
0
0
0
1
1
1
0 . 005
-1
-1
-1
-1
-1
™> 1
—• 1
-1
-0
-0
-0
-o
-0
0
0
0
0
1
1
1
1
0.01
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
0
0
0
0
0
1
1
1
1
1
5-23
0.02
-1
— 1
-1
-1
-1
-0
-o
-o
-0
0
o
0
0
1
1
1
1
1
1
1
1
0.03
-1
-1
-1
-0
-0
-0
-0
0
0
0
0
1
1
1
1
1
1
1
1
1
2
0.04
-0
-0
-0
-0
-0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
0.05
-0
-0
0
0
0
0
o
1
1
1
1
1
1
1
1
2
2
2
2
2
2
-------
EXHIBIT 5-4 (Cont'd.)
LIKELIHOOD OF OBTAINING KUSITIVE MET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
D
E
M
C
L
E
U
V
1
u.
o.o
0.1
O T
* . o
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
0
0
0
0
0
0
1
1
2
3
3
T
4
4
0.005
0
0
0
0
0
o
0
0
1
1
2
2
3
3
4
4
4
0 . 0 1
0
0
0
o
0
0
1
1
~>
3
^
3
3
4
4
4
4
0. 02
0
0
1
1
2
2
-»
3
3
4
4
4
4
4
4
0. 03
2
2
2
^
3
"T
3
4
4
4
4
4
4
4
4
0 . 04
2
2
2
3
3
4
4
4
4
4
4
4
4
4
4
4
0 . 05
2
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
5-24
-------
Ln
NJ
Ui
EXHIBIT 5-5
BREAKEVEN THRESHOLDS
FOR SYSTEMS SERVING > 100K
Annual
Endemic2'0
Level
(Percent
1.51
of Pop-
ulation)
l.O
I I
0 .005 .01 .02 .03 .04
Annual Probability of Outbreak
(Percent)
I
.05
-------
Ul
EXHIBIT 5-6
BREAKEVEN THRESHOLDS
FOR SYSTEMS SERVING 10K TO 100K
Annual
Endemic
Level
2.0
(Percent
l.o
of Pop-
ulation)
l.O
0.5
0 .005
I I I I
.01 .02 .03 .04
Annual Probability of Outbreak
(Percent)
n
.05
-------
to
EXHIBIT 5-7
BREAKEVEN THRESHOLDS
FOR SYSTEMS SERVING IK to 10K
Annual
Endemic 2'°
Level
(Percent
1.5
of Pop-
ulation)
1.0
0.5
f
IK - 3.3K
III II
.005 .01 -02 .03 .04
Annual Probability of Outbreak
(Percent)
I
.05
-------
Ln
to
CD
EXHIBIT 5-8
BREAKEVEN THRESHOLDS
FOR SYSTEMS SERVING < 1000
Annual
Endemic 2-°—|
Level I
(Percent
•^•"—i
of Pop-
ulation)
1.0
0.5
501 - 1000
r
0
1
.005
1
.01
1
.02
1
.03
1
.04
1
.05
Annual Probability of Outbreak
(Percent)
* SYSTEMS SERVING BETWEEN 25 - 500 EXCEED CHART BOUNDARIES
-------
necessary appears to bear an inverse relationship to system size.
This is the result of the higher attack rate assumption. The
effect of that assumption is weaker in the smallest size categor-
ies, however.
The probability of outbreak and the endemic level are not
known with certainty even at the local level. At the national
level, there have been no attempts to quantify these variables
until recently. Craun11 has produced the following analysis of
the rate of incidence of waterborne disease outbreaks using the
CDC data base in conjunction with the ASDWA survey data base on
the number of filtered and unfiltered (both untreated and dis-
infected only) community water systems.
Estimated Outbreak Rates In Community Surface Systems
Type of System
Untreated
Disinfection Only
Filtered & Disinfected
Outbreaks/1000 Systems
32.5
40.5
5.0
The use of community water systems in this analysis is sig-
nificant. It is suspected that community systems have a lower
degree of underreporting than non-community systems, making these
estimated outbreak rates less prone to error. Nonetheless under-
reporting is still present in these data. Using an underreport-
ing factor of four and the ASDWA survey data, the above estimates
may be restated in terms of the implied recurrence intervals and
annual probabilities of outbreak, as follows:
Estimated Recurrence Intervals And Annual Outbreak Probabilities
Type of System
Untreated
Disinfection Only
Filtered & Disinfected
Recurrence
Interval
115
93
750
Annual Outbreak
Probability
0.0087
0.0108
0.0013
^Communications with G. Craun, May 1987,
5-29
-------
The effect of errors in the CDC reporting process are evi-
dent in these estimates. It seems incredulous that outbreaks
would occur only once in every 115 years in systems using
untreated surface water. This is probably the result of poor
reporting by such systems. The other two estimates of outbreak
probability might be considered reasonable if numerous other
sources of bias can be overlooked.
In interpreting the two candidate estimates of outbreak
probability, it must be recognized that they are "average" out-
break rates. The probability of outbreak should properly be
regarded as a distribution. There are some systems which main-
tain they can achieve as low a risk of waterborne disease as
filtered systems (1 outbreak/750 years) with disinfection only.
There are also systems in both the disinfection only and the
filtered groups which have had repeat outbreaks within the last
20 years.
For purposes of this system level analysis, systems with
1/750 annual outbreak probabilities are not very interesting.
They will probably qualify for an exception to the filtration
requirement. It is more interesting to evaluate systems at the
margin; to assess what breakeven probability of outbreak is
required in order to make filtration a worthwhile consideration
on the basis of quantifiable damages alone. Two summaries of
MOPED output are presented in Exhibits 5-9 and 5-10. Exhibit 5-9
assumes a probability of outbreak of 1/50 years. Exhibit 5-10
assumes a probability of outbreak of 1/100 years.
For these analyses, an endemic level of 1.0 percent was
assumed for systems serving fewer than 100,000 persons. An
endemic level of 0.5 is assumed for systems serving more than
100,000 persons. These are believed to be representative of
levels in systems at risk. Again, systems that are good candi-
dates for an exception to the filtration requirement might not be
characterized by such levels.
The low treatment cost results from HOPED were used in this
analysis. These costs are based on slow sand technology for
small systems and direct filtration technology for larger sys-
tems. At the margin, raw water quality should be good enough to
allow use of these technologies. When raw water characteristics
indicate a need for full conventional treatment or a package
plant, often there is no need for risk assessment to aid in
decisionmaking because the need to filter is clear.
Exhibits 5-9 and 5-10 present results in terms of high and
low scenarios, reflecting the high and low damages estimates of
HOPED. These were modelled after the RFF methodology. The
principal difference between scenarios is the extent of costs
assumed due to averting behavior. It is believed this category
of costs is very significant and the high damage scenario is
regarded as being more accurate.
5-30
-------
BREAKEVEN ANALYSIS OF INSTALLING FILTRATION
ASSUMING p(OUTBREAK) » 1/50 YEARS
ANNUAL EXPECTED
V
to
OUTBREAK DAMAGES
(f Millions 1
LARGE MATER SYSTEMS
BOSTON, HA
PORTLAND,HE
N£KARK,NJ
NEW YORK, NY
SYRACUSE, NY
UTICA, NY
SCRANTON, PA
NILKES-BARRE, PA
BETHLEHEM, PA
GREENVILLE, SC
SAN FRANCISCO, CA
RENO-SPARKS, NV
SEATTLE, HA
TACOHA, HA
PORTLAND, OR
SMALLER POPULATION
75,001-100,000
50,001-75,000
25,001-50,000
10,001-25,000
3,301-10,000
1,001-3,300
SOI -1,000
101-500
25-100
HIGH
1361.61
80.62
345.84
4168.48
136.00
67.72
90.51
131.66
60.12
306.29
1058.50
100.36
659.59
134.91
426.20
CATEGORIES
49. IB
34.71
21.74
9.72
3.2B
1.23
0.40
0.14
0.03
LON
558.98
32.62
142.87
USB. 55
55.31
26.37
3B.97
56.69
26.46
122. 98
443.36
43.76
284.50
53.40
179.14
19.35
13.49
9.80
4.41
1.49
0.63
0.22
0,08
0.02
VALUE OF OUTBREAK
DAMAGES
<(Hillions/yr>
HIGH
27.23
1.61
6.92
83.37
2.72
1.35
1.61
2.63
1.20
6.13
21.17
2.01
13.19
2.70
8.56
0.98
0.69
0.43
0.19
0.07
0.02
0.01
0.00
0.00
LOH
11.18
0.65
2.86
33.17
1.11
0.53
0.78
1.13
0.53
2.46
8.87
0.8B
5.69
1.07
3.58
0.39
0.27
0.20
0.09
0.03
0.01
0.00
0.00
0.00
ANNUAL ENDEMIC
DAMAGES
(IMillions/yr)
HIGH
18.98
1.01
4.81
52.87
1.89
0.86
1.24
1.80
0.91
3.56
15.35
1.44
10.64
2.04
6.41
1.23
0.88
0.52
0.24
0.08
0.03
0.01
0.00
0.00
LDN
14.06
0.76
3.62
39.56
1.38
0.39
1.02
1.49
0.75
2.72
11.65
1.1?
8.17
1.36
2.39
0.91
0.65
0.38
0.18
O.Ob
0.02
0.01
0.00
0.00
TOTAL ANNUAL
DAMAGES
UMillions/yr)
HIGH
46.22
2.62
11.73
136.24
4.61
2.21
3.05
4.43
2.11
9.69
36.52
3.45
23.84
4.74
14.97
2.21
1.57
0.95
0.43
0.15
0.05
0.02
0.01
0.00
LOV
25.24
1.41
6.48
72.73
2.48
1.12
1. 80
2.62
1.28
5.18
20.52
2.07
13.86
2.43
5.98
1.30
0.92
0.58
0.26
0.09
0.03
0.01
0.00
0.00
ANNUAL
COST OF
FILTRATION
(tKil/yr)
19.63
2.17
3.86
77.07
3.64
1.98
1. 11
3.02
2.44
5.77
12.95
4.15
9.93
7.05
11.19
1.85
1.34
0.74
0.25
0.10
0.05
0.04
0.02
0.01
NET
OR
LOSS
GAIN
(IHillions/yr)
HIGH
26.59
0.45
7.87
59.17
0.97
0.23
1.94
1.41
-0.33
3.92
23.57
-0.70
13.91
-2.31
3. 78
0.368
0.237
0.220
0.17B
0.051
0.003
-0.017
-0.012
-0.008
LOH
5.61
-0.76
2.62
-4.34
-1.16
-0.66
0.6?
-0.40
-1.16
-0.59
7.57
-2.08
3.93
-4.62
-5.21
-0.551
-0.417
-0.155
0.010
-0.006
-0.015
-0.024
-0.014
-O.OOB
-------
EXHIBIT 5-1O
BREAKEVEN ANALYSIS OF INSTALLING FILTRATION
ASSUMING p(OUTBREAK) =1/100 YEARS
ANNUAL ESPECTED
Oi
w
K3
OUTBREAK DAMAGES
(i Hillions)
LAR6E HATER SYSTEHS
BOSTON, HA
PORTLAND, HE
NEHARK,NJ
NEM YORK, NY
SYRACUSE, NY
UTICA, NY
SCR ANTON, PA
NILKES-BARRE, PA
BETHLEHEM, PA
GREENVILLE, SC
SAN FRANCISCO, CA
RENO-SPARKS, NV
SEATTLE, HA
TACOHA, HA
PORTLAND, OR
SMALLER POPULATION
75,001-100,000
50,001-75,000
25,001-50,000
10,001-25,000
3,301-10,000
1,001-3,300
501-1,000
101-500
25-100
HIGH
1361.61
80.62
345.86
4168. 48
136.00
67.72
90.51
131.66
60.12
306.29
1058.50
100.36
659.59
134.91
428.20
CATEGORIES
49.18
34.71
21.74
9.72
3.20
1.23
0.40
0.14
0.03
LOH
558.98
32.62
142.87
1658.55
55.31
26.37
38.97
56.69
26.46
122.98
443.36
43.76
284.50
53.40
179.16
19.35
13.49
9. BO
4.41
1.49
0.63
0.22
0.08
0.02
VALUE OF OUTBREAK
DAMAGES
OHillions/yr)
HIGH
13.62
O.BI
3.46
41.68
1.36
0.68
0.91
1.32
0.60
3.06
. 10.59
1.00
6.60
1.35
4.28
0.49
0.35
0.22
0.10
0.03
0.01
0.00
0.00
0.00
LOH
5.59
0.33
1.43
16.59
0.55
0.26
0.39
0.57
0.26
1.23
4.43
0.44
2.85
0.53
1.79
0.19
0.13
0.10
0.04
0.01
0.01
0.00
0.00
0.00
ANNUAL ENDEMIC
DAMAGES
(IHillions/yr)
HIGH
18.98
1.01
4.81
52.87
1.89
0.86
1.24
l.BO
0.91
3.56
15.35
1.44
10.64
2.04
6.41
1.23
0.8B
0.52
0.24
0.08
0.03
0.01
0.00
0.00
LOH
14.06
0.76
3.62
39.56
1.38
0.59
1.02
1.49
0.75
2.72
11.65
1.19
8.17
1.36
2.39
0.91
0.65
0.3B
0.18
0.06
0.02
0.01
0.00
0.00
TOTAL ANNUAL
DAMAGES
(tHillions/yr)
HIGH
32.60
1.82
8.27
94.56
3.25
1.54
2.14
3.11
1.51
6.62
25.93
2.45
17.24
3.39
10.69
1.72
1.23
0.74
0.33
0.11
0.04
0.01
0.00
0.00
LOH
19.65
1.09
5.05
56.14
1.93
0.85
1.41
2.05
1.01
3.95
16.09
1.63
11.02
1.89
4.19
1.10
0.78
0.48
0.22
0.07
0.03
0.01
0.00
0.00
ANNUAL
COST OF
FILTRATION
ItNil/yr)
19.63
2.17
3. 86
77.07
3.64
1.98
1.11
3.02
2.44
5.77
12.95
4.15
9.93
7.05
11.19
1.85
1.34
0.74
0.25
0.10
0.05
0.04
0.02
0.01
NET
OR
LOSS
GAIN
UMillions/yr)
HIGH
12.97
-0.35
4.41
17.49
-0.39
-0.44
1.03
0.09
-0.93
0.85
12.98
-1.70
7.31
-3.66
-0.50
-0.124
-0.110
0.002
0.081
0.018
-0.010
-0.021
-0.013
-O.OOB
LOH
0.02
-1.08
1.19
-20.93
-1.71
-1.13
0.30
-0.97
-1.43
-1.82
3.14
-2.52
1.09
-5.16
-7.00
-0.744
-0.552
-0.253
-0.034
-0.021
-0.022
-0.026
-0.015
-O.OOB
-------
Using the above described assumptions, results are presented
for each of the 15 large cities and for the gradient of nine
smaller size categories. The principal conclusion to be drawn
from these results is that they lie in a range where they repre-
sent mostly positive net gains under these assumptions in all but
the three smallest system size categories (systems serving <1000
persons). If the assumptions are reasonable, these results imply
that the central thrust of the Surface Water Treatment Rule to
initiate a national effort to re-assess the need for filtration
is a worthwhile undertaking on the basis of quantifiable damages
alone.
At the national level, all that can be assessed is the
overall reasonableness of the proposal. The Safe Drinking Water
Act specifies that state regulators will make case-by-case
determinations of the need for filtration. Given the extremely
site-specific nature of the key variables which enter into the
above described optimizing framework, this approach to implemen-
tation seems exclusively appropriate.
Of course, filtration is only one approach to preventing
waterbome disease outbreaks. There are disinfection and moni-
toring strategies for obtaining an exception to the filtration
requirement and turbidity performance requirements for systems
which already filter. These two types of compliance activities
impose costs which can also be measured against the damages
avoided by preventing waterbome disease. In light of results
for filtration, the analysis of net social gains for systems
obtaining an exception is self-evident. If the same damages can
be avoided at significantly less cost, net gains will be signif-
icantly greater.
The prospects for net social gains from the turbidity per-
formance requirement were also evaluated for hypothetical water
systems of varying sizes using MOPED. Net gains are overwhelming
for all system size categories serving more than 1000 people.
For systems serving fewer than 1000 people, net losses appear,
but there are many caveats that apply to this result. One caveat
is that many small systems which have difficulty meeting perform-
ance requirements may represent situations where an older plant
is in need of replacement.
The costs of the groundwater portion of the Total Coliform
Rule are different in concept from the costs to surface water
systems in that they relate to only one aspect — monitoring of
coliforms — of the total approach to avoiding contamination from
microbial contaminants. The most significant requirement of the
Total Coliform Rule is an increase in the minimum number of
samples (to five/month) which small water systems must collect
and analyze. The proposal is based on results of statistical
analysis which has shown that the present level of monitoring in
small systems is inadequate to compensate for the probability of
obtaining false negatives.
5-33
-------
The benefit of the Total Coliform Rule derives from the
value of the monitoring information it will provide. However,
given the technical findings which form the basis for the pro-
posal, it is clear that the value of such monitoring data is zero
(or negative) until a certain number of samples have been col-
lected and analyzed ~ the number proposed in the rule. Coliform
monitoring is a fundamental component of water treatment for con-
trol of microbial contaminants. Though the absence of coliforms
provides incomplete assurance that other pathogens are absent
also, the presence of coliforms is a fairly good indication there
is a problem worth investigating, conceivably involving a broad
range of disease agents related to fecal contamination. Thus,
coliform monitoring indirectly results in a reduction in the risk
of waterbome disease.
A recent poll of state drinking water program administrat-
ors12 indicated that the value they place on coliform monitoring
data is very great in surface water systems and greater than
expected in groundwater systems. It is concluded therefore, that
the extra cost of obtaining a statistically reliable number of
samples would be deemed worthwhile by the public health profess-
ion.
12Informal poll of 32 state program administrators taken by
ASDWA at their 1987 annual conference, February 1987.
5-34
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6. REGULATORY FLEXIBILITY ACT ANALYSIS
AND PAPERWORK REDUCTION ACT ANALYSIS
6.1 Regulatory Flexibility Act Analysis
The Regulatory Flexibility Act (RFA), enacted on September
19, 1980, requires all executive agencies to explicitly consider
small entities in their regulatory design and implementation
process. The purpose of the RFA is to encourage regulatory
agencies to minimize the disproportionate burden that falls on
small entities. The three specific objectives of the RFA are
listed below:
1. To increase agencies' awareness of their regulatory
impact on small entities;
2. To compel agencies to explicitly analyze, explain, and
publish regulatory impacts on small entities; and
3. To encourage agencies to provide regulatory relief to
small entities while still accomplishing their statutory
mandates.
These objectives are accomplished through the requirements of
regulatory flexibility analyses for proposed regulations. If a
regulation does not have a "significant" impact on a substantial
number of small entities, then the regulatory flexibility anal-
ysis will consist of a certification to that effect.
Prior to conducting a regulatory flexibility analysis, a
regulatory agency such as EPA must define a small entity.1 The
RFA defines small entities as including small businesses, organ-
izations, and governments.2 Small businesses are defined as any
business which is independently owned and operated and not dom-
inant in its field.3 Small organizations are defined as any
non-profit enterprise which is independently owned and operated
and is not dominant in its field. Finally, small government
entities are defined as those city, county, town, township, vil-
lage, school district, or special district governments serving a
population of less than 50,000 persons.4
1It should be noted that, under the Safe Drinking Water Act,
EPA's Office of Drinking Water employs a different definition of
small water systems from that used here. The analyses presented
in this section are prepared only for compliance with the RFA.
2Regulatory Flexibility Act of 1980, PL 96-354, Section 601(6).
315 USC, Section 632.
4op. cit.. note #1 supra. Sections 601(4) and 601(5).
6-1
-------
Community water systems can be divided into three ownership
categories for purpose of RFA analysis: 1) publicly owned, 2)
investor owned, and 3) ancillary systems. Publicly owned systems
are those owned by governmental entities; investor owned systems
are privately owned; and ancillary systems are those small sys-
tems that are ancillary to other enterprises such as mobile home
parks or hospitals. According to EPA, there are 26,424 publicly
owned community water systems.5 Of this total, 98 percent serve
fewer than 50,000 persons.
Investor owned water systems are firms primarily engaged in
production and distribution of water to consumers.6 According to
regulations published in accordance with the RFA, these companies
are considered to be small businesses if their annual receipts
are less than $3.5 million.7 To apply this standard to public
water systems, the Consumer Price Index for water and sewage
maintenance was used to deflate operating costs from February
1984, to February, 1980 dollars. This procedure suggests that
the upper limit for a small water utility would be $2.4 million
per year in 1980 dollars. EPA estimates that systems serving
populations of 50,000 persons is roughly the cut-off for systems
generating revenues of $2.4 million.8' Revenues for investor
owned water systems serving 25,000-50,000 persons averaged $1.97
million in 1980. For investor owned systems serving 50,000—
75,000 persons, revenues in 1980 averaged about $3.16 million.
Since no more recent data regarding operating revenues of public
water systems are available, public systems serving 50,000 per-
sons and less will be considered "small entities" for the pur-
poses of the regulatory flexibility analysis.
There is some question, however, as to whether all investor
owned water utilities serving fewer than 50,000 persons qualify
as small businesses. Many of these utilities are not individual-
ly owned, but are owned and controlled by large holding companies
such as American Water Works Service Co. and General Water
Works. In addition, every investor owned utility operates in a
franchised area and thus constitutes a natural monopoly. This
raises the question of whether domination in a limited geographic
area is the same as dominance in a field of enterprise. The
Small Business Administration considers dominance to mean on a
national basis; therefore, no individual water utility can be
dominant in the marketplace.
5U.S. Environmental Protection Agency - Office of Drinking
Water survey of Operating and Financial Characteristics of
Community Water Systems. October, 1982.
6SIC 4941.
749 Federal Register. No. 28, p. 5035, 1984.
8op.cit. note # 4 supra.
6-2
-------
All ancillary community water systems serve fewer than 500
persons according to EPA's 1980 survey. These could be consi-
dered small entities; however, the main activity of the enter-
prise may be sufficiently large to disqualify some organizations
as small entities. However, at least 74 percent of ancillary
systems are mobile home parks;9 it seems unlikely that other
revenue sources at these facilities would be sufficient to offset
the burden of regulations significantly. Nevertheless, it is not
possible to determine precisely how many ancillary systems con-
stitute small entities due to the lack of data.
6.1.1 Purpose of Regulation
Under the Safe Drinking Water Act, EPA is authorized to set
maximum contaminant levels (MCLs) for those contaminants in
drinking water which may have any adverse effect on the health of
persons. If the Administrator finds that it is not technologic-
ally or economically feasible to ascertain the level of a con-
taminant which is to be regulated, a treatment technique require-
ment may be promulgated in lieu of establishing an MCL. More-
over, the SDWA mandates that the Administrator shall "...promul-
gate regulations which specify criteria under which filtration is
required for public [surface] water systems."10
The purpose of this regulation is to reduce public health
risks by limiting human exposure to microbiological contaminants
in drinking water, and to comply with the provisions of the SDWA.
6.1.2 Number of systems Affected
Because of the acute health risks associated with microbio-
logical contaminants, the ubiquitous nature of their occurrence
in surface water, and the generally limited treatment currently
in place, the Surface Water Treatment Rule and turbidity perform-
ance requirements are likely to affect small surface water sys-
tems. However, these surface water systems constitute only a
small percentage of the total number of public water supplies
serving fewer than 50,000 persons. Conversely, the proposed
total coliform rule will apply to a comparatively large number of
small systems. However, as explained in the affordability anal-
ysis below, the costs per household for these requirements -is-
estimated to be very low even for the smallest system sizes.
Of the estimated 199,390 community and non-community water
supplies serving fewer than 50,000 persons, 2845 (1.4 percent)
currently have unfiltered surface supplies and therefore are
9Ibid.
10Safe Drinking Water Act Amendments of 1986, P.L. 99-339,
Section 1412 (b)(7)(C).
6-3
-------
subject to compliance under the SWTR. The likely compliance
strategies for public water systems for each of four regulatory
alternatives considered for the filtration requirement are sum-
marized in Exhibit 4-7. For the proposed alternative (i.e.,
regulatory Alternative C), 1346 of the unfiltered public surface
water systems serving fewer than 50,000 persons are expected to
select a compliance strategy other than installing filtration.
The remaining 1499 unfiltered public surface water systems
serving fewer than 50,000 persons will install some form of
filtration technology. Exhibit 4-6 illustrates the types of
filtration technologies available to smaller systems and the
proportion of systems likely to choose each technology.
Of the 199,390 community and non-community water supplies
serving fewer than 50,000 persons, 6457 are currently filtering
their surface water supplies and of these, 4888 (2.5 percent of
all public surface water supplies serving less than 50,000)
exceed the proposed average turbidity performance requirement of
0.3 NTU (see Exhibit 4-8). These systems would be required to
modify or upgrade their treatment processes in order to meet the
turbidity performance requirement and thereby comply with the
regulation.
The proposed total coliform rule would impose more stringent
total coliform monitoring requirements on public water systems
serving fewer than 3300 persons. EPA estimates that there are
currently 193,609 community and non-community water systems which
would be subject to these requirements.11 Of these, 193,588
serve fewer than 50,000 persons.
EPA guidelines on compliance with the Regulatory Flexibility
Act indicate that, in general, a "substantial" number of small
entities is more than 20 percent of the total. Therefore, by the
20 percent rule, only the coliform regulations would affect a
"substantial" number of small water utilities. These results are
summarized in the following tabulation.
Estimated Number of Small Entities Affected
Number of Affected Percent of All
Systems Serving Systems Serving < 50,000
< 50.000 Affected
SWTR 7,733 3.9
TCR 193,588 97.0
11U.S. EPA - Office of Drinking Water Information Collection
"Request for Total Coliform Rule. 1987.
6-4
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6.1.3 Economic Impacts of Filtration, Turbidity Performance, and
Total Coliform Regulations on Small Water Systems
Exhibit 4-8 shows aggregate annual cost of compliance with
the filtration rule for systems serving 50,000 or fewer people.
These costs reflect average expenditures for all compliance op-
tions combined. These include installation of treatment, devel-
opment of an alternate source, and seeking an exception to the
rule. The data indicate that at treatment efficiencies equal to
a theoretical three and four log removal of Giardia cysts and
viruses, respectively, total annualized costs are approximately
$116 million for the 2,845 affected systems serving 50,000 or
fewer people. Total capital costs to be borne by these systems
amount to $910 million.
Exhibit 4-11 shows aggregate annual costs of compliance with
the turbidity performance requirement on a per system basis.
These costs include modification and upgrading of existing treat-
ment processes to achieve greater optimization. The data indi-
cate that for the 6,457 systems serving fewer than 50,000 people
which currently exceed the proposed level of 0.3 NTU, total
annualized costs are approximately $62 million. Capital costs
for these systems will be $201 million.
Exhibits 4-15 and 4-16 illustrate the total cost impacts of
the coliform rule. As indicated above, the rule will impact
primarily systems which serve fewer than 3300 persons. The total
annual costs of the rule will be between $70 million and $170
million. The entire cost is annual cost since the only comp-
liance action is monitoring. Capital costs are zero. The range
in the cost estimates for the coliform rule is attributable
primarily to the flexibility and discretion afforded to state
agencies in implementation. Under the proposal, states are
permitted to allow systems to substitute alternative protective
activities (e.g., sanitary surveys) for reduced monitoring. If
states exercise this flexibility extensively, costs are likely to
be nearer to the low end of the range. Conversely, if states
take a more stringent approach in implementing the requirement,
costs will approach the higher estimate.
State flexibility and discretion is important for other
portions of the regulations as well. The filtration proposal
intentionally avoids setting specific technological requirements,
providing details on operation and design as guidance only. This
will allow states extensive flexibility for tailoring require-
ments to site-specific conditions, thereby achieving maximum
efficiency for small systems. In addition to the wording of the
proposed rule, the SDWA itself incorporates mechanisms to afford
states the capabilities to mitigate economic impacts on small
systems. At least for some systems in the smallest size categor-
ies (i.e., less than 150 service connections), the most important
such mechanism may be the authority to exempt systems from regu-
latory requirements on economic grounds while alternative means
of compliance are sought.
6-5
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Under the Regulatory Flexibility Act (RFA), annual costs of
compliance are to be compared to the existing cost of production.
In the water industry, this outwardly simple comparison is some-
what elusive for a variety of reasons. First, it is not clear
exactly what the cost of production is in the water industry.
The cost of production is reflected .in the price of the product
in most industries, but as discussed in Chapter 3, pricing
practices in the water industry are highly variable and not
necessarily reflective of the full costs of production. As a
surrogate for the cost of production, data on the revenue per
thousand gallons of water produced has been evaluated. Using the
Consumer Price Index to adjust data from the 1980 Survey of
Operating and Financial Characteristics of Community Water
Supplies to 1986 dollars, produces an average figure for systems
serving fewer than 50,000 persons of $2.15 per thousand gallons.
Using data from the same survey on the average daily flows
produced by systems of various sizes, the estimated annual costs
of the proposed regulations, cited above, can be converted to a
cents-per-thousand gallons basis. This reflects the incremental
additional cost of production. The table below compares these
incremental amounts to the present level of production cost. For
the surface water treatment rule, an average of the incremental
costs imposed on filtered and unfiltered systems is presented.
Incremental
Additional Production Cost Percentage Increase
fCents/1000 Gal. Produced! In Production Cost
SWTR 15.1 7
TCR 1.6 - 3.9 0.7 - 1.8
Agency guidance regarding the Regulatory Flexibility Act
(RFA) defines a percentage increase in production cost of five
percent or more as a significant impact. According to the
figures above, the Surface Water Treatment Rule exceeds this
threshold while the Total Coliform Rule does not.
RFA guidelines also call for an analysis of whether the com-
pliance costs as a percent of sales for small entities are 10
percent or more higher than compliance costs as a percent of
sales for large entities. It is not feasible to perform a con-
sistent evaluation using this criterion with respect to the water
industry because the 50,000 population benchmark represents a
dividing line between two very different scales of operation and
associated economies of scale. Thus comparing costs above and
below this size benchmark is a comparison of apples and oranges.
RFA guidelines further require an analysis of the extent to
which capital costs of compliance represent a significant portion
of capital available to small entities and whether the require-
6-6
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ments of the regulation are likely to result in closures of small
entities. While it seems certain that some small entities will
encounter financial problems in achieving compliance, the data
with which to estimate the extent of such problems does not
exist. The SDWA has explicit exemption procedures, however,
specifically designed to accommodate the financial problems of
small water systems.
6.2 Paperwork Analysis
6.2.1 Paperwork Reduction Act
Among the purposes of the Paperwork Reduction Act (PRA)12
are as follows:
o minimization of the federal paperwork burden for indivi-
duals, small businesses, state and local governments, and
other persons; and
o minimization of the costs to the federal government of
collecting, maintaining, using, and disseminating infor-
mation.
Water utilities and state water supply agencies will be required
to maintain records on monitoring of coliforms and turbidity and
report results to the EPA; this is likely to be the largest com-
ponent of paperwork associated with establishment of federal SWTR
and TCR regulations. The Paperwork Reduction Act is intended to
minimize the burden imposed on utilities and states as they
strive to protect the public health by implementing the provi-
sions of the SDWA.
6.2.2 Requirements of the Paperwork Reduction Act
EPA is required to submit to the Office of Management and
Budget (OMB) proposed information collection requests. EPA also
must submit a copy of proposed rules containing an information
collection requirement. These proposed rules must be submitted
no later than publication of a notice of proposed rulemaking in
the Federal Register. When a final rule is published in the
Federal Register, EPA must explain how any information collection
requirements have been designed to be responsive to public com-
ments. OMB determines the necessity, practicality, and utility
of the information being requested, and if approval of the
request is made, OMB will issue a control order.
Under the Safe Drinking Water Act, EPA is authorized to
regulate contaminants in drinking water to protect the public
health. Microbiological contaminants are known to constitute an
12Public Law 96-511; 94 STAT 2812
6-7
-------
acute health risk. To determine whether a specific water system
exceeds an MCL for coliform bacteria, or to determine whether a
system is practicing filtration and/or disinfection satisfac-
torily, EPA must require water systems to collect and analyze
samples and report results to the relevant primacy agent (i.e.,
either the applicable EPA regional office or the states). In the
case of microbiological contaminants, EPA, the states, water
utilities, and the public would use monitoring information for
two purposes: 1) to determine the presence of contaminants which
may immediately affect human health; and 2) determine the reli-
ability of a system to provide waters free of microbiological
contaminants. This monitoring data would also allow appropriate
action plans and removal decisions to be made by affected util-
ities.
6.2.3 Number of Systems Affected/Respondent Burden
A detailed discussion of the number of water systems af-
fected by monitoring and paperwork requirements associated with
the proposed rules is provided in the Information Collection
Request Documents.
6-8
-------
7. SUMMARY OF COSTS, BENEFITS, AND SOURCES OF UNCERTAINTY
The total costs of implementing the Surface Water Treatment
Rule and the Total Coliform Rule are summarized in Exhibits 7-1
and 7-2 for capital and annual costs, respectively. In the final
analysis, there are myriad sources of uncertainty concerning the
factors which will determine the actual costs of these two rules.
Accordingly, Exhibits 7-1 and 7-2 present estimates which bracket
the conceivable range of outcomes.
Costs will be incurred by presently unfiltered systems in
the course of either installing filtration, obtaining an excep-
tion to the filtration requirement through comparable treatment
utilizing disinfection and other measures, or through converting
to an alternate source of supply (i.e., groundwater or purchased
water). Much of the variation between the costs of regulatory
alternatives and within a given regulatory alternative results
from uncertainty in forecasting the responses of 2867 unfiltered
water systems. Another major source of uncertainty is the cost
of installing filtration in the 15 large unfiltered systems which
serve more than 100,000 persons. Site specific engineering feas-
ibility studies would be required for all of these locations in
order to produce firm estimates.
Finally, the need for filtration is a determination that is
to be made by the states and not by EPA. The result of the EPA
regulatory action is adequately characterized by the ranges
presented. State regulatory actions will determine the level of
costs ultimately incurred.
Costs incurred by filtered systems are subject to a similar
source of uncertainty in the forecasting of compliance behavior.
In addition, the data on existing turbidity performance used to
estimate the number of systems affected is subject to an asymmet-
ric measurement error that tends to produce high estimates.
Implementation of the Total Coliform Rule is designed to
allow for considerable exercise of flexibility by states. The
extent to which this flexibility will be utilized can only be
broadly characterized. The estimates presented assume that no
flexibility is allowed for surface water systems. For ground-
water systems, high and low bounds are presented.
The benefits to be derived from implementation of the sur-
face Water Treatment Rule and the Total Coliform Rule will mani-
fest themselves by a reduction in the risk of microbiological
contamination of public water supplies, and consequent outbreak
of waterborne diseases. The available data regarding the inci-
dence of waterborne disease are affected by enormous uncertainty.
While it is not possible to develop statistically reliable esti-
mates of the extent of waterborne disease, the reported data is
adequate to indicate the presence of several disturbing trends.
7-1
-------
EXHIBIT 7-1
TOTAL CAPITAL COSTS
($Millions)
HIGH
SURFACE WATER TREATMENT RULE
Unfiltered Systems
>100,000
10,000 to 100,000
1000 to 10,000
25 to 1000
LOW
929-2298
685-843
445-547
364-448
492-1217
389-568
346-505
305-445
PROPOSED
520-1286
423-614
365-529
305-442
TOTALS
2436-4136
1532-2735
1613-2871
Filtered Systems
>100/000
10,000 to 100,000
1000 to 10,000
25 to 1000
139
158
118
69
17
38
37
24
87
114
83
49
TOTALS
484
116
333
7QTAL COLIFORM RULE
Surface Water Systems
1000 to 10,000
25 to 1000
0
0
0
0
0
0
TOTALS
G-round Water Systems
1000 to 10,000
25 to 1000
0
0
0
0
0
0
TOTALS
7-2
-------
EXHIBIT 7-2
TOTAL ANNUAL COSTS
($Millions/Yr. Q 3% over 20 Years)
HIGH
SURFACE WATER TREATMENT RULE
Unfiltered Systems
>100,000
10,000 to 100,000
1000 to 10,000
25 to 1000
LOW
131-289
90-111
45-55
42-52
PROPOSED
72-162
55-80
39-57
41-60
76-168
59-85
40-58
41-60
TOTALS
Filtered Systems
>100,000
10,000 to 100,000
1000 to 10,000
25 to 1000
308-507
139
158
118
69
207-359
3
10
13
8
216-371
23
28
28
16
TOTALS
484
34
95
fWTAL COLIFOI
Surface Water Systems
10,000+
1000 to 10,000
25 to 1000
0.3
1.4
7.2
0.3
1.4
7.2
0.3
1.4
7.2
TOTALS
Water Systems
10,000+
1000 to 10,000
25 to 1000
8.9
0.6
6.8
154.2
8.9
0.6
5.8
54.4
8.9
0.6
5.8-6.8
54.4-154.2
TOTALS
161.6
60.8
60.8-161.6
7-3
-------
The economic benefits of drinking water standards may be
defined as the total willingness to pay for safe potable water.
The safety attribute of the good is the relevant aspect of demand
to be the focus of analysis. The willingness to pay for safety
in drinking water may be regarded as consisting of two compo-
nents: (1) the expected value of the damages that would be incur-
red in the absence of the standard; and, (2) the value of an
extra margin of safety — a warranty — which provides assurance
to consumers, and to society as a whole, that it can be taken for
granted the water is safe to drink.
Given the current state of economic research related to
drinking water, it is not possible to quantify the latter of
these two components. There is evidence from several places
which indicates the second component of the willingness to pay
for safe drinking water may be quite significant. This missing
component of benefit must therefore be kept in mind while
reviewing results of analyses based on the narrower concept of
the expected value of quantifiable damages.
The annual expected value of the damages resulting from
incidence of waterborne disease were hypothetically computed for
15 large unfiltered systems serving more than 100,000 persons and
for a gradient of nine smaller size categories serving between 25
and 100,000 persons. In each case, the estimated annual losses
from waterborne disease were compared to the • estimated annual
cost of installing filtration. The primary conclusion to be
drawn from the results is that a positive net gain from install-
ing filtration is feasible in all but the three smallest system
size categories (systems serving <1000 persons).
The analysis assumes the endemic level of waterborne disease
to be 1.0 percent of the exposed population per year in systems
serving fewer than 100,000 persons and 0.5 percent of the exposed
population in systems serving more than 100,000. The annual
probability of outbreak of waterborne disease was evaluated under
two assumptions: one per 50 years, and one per 100 years. If the
assumptions used are reasonable, these results imply that the
central thrust of the Surface Water Treatment Rule to initiate a
national effort to re-assess the need for filtration is a worth-
while undertaking on the basis of the expected value of quantifi-
able damages alone.
At the national level, all that can be assessed is the over-
all reasonableness of the proposal because costs and benefits are
ultimately site-specific. The Safe Drinking Water Act specifies
that state regulators will make case-by-case determinations of
the need for filtration. Given the extremely site-specific
nature of the key variables which enter into the decision, this
approach to implementation is very appropriate.
Of course, filtration is only one approach to preventing
waterborne disease outbreaks. There are disinfection and moni-
toring strategies for obtaining an exception to the filtration
7-4
-------
requirement and turbidity performance requirements for systems
which already filter. These two types of compliance activities
impose costs which can be measured against the same benefits—
the damages avoided by preventing waterbome disease.
In light of results for filtration, the analysis of nex
social gains for systems obtaining an exception is self-evident.
If the same damages can be avoided at significantly less cost,
net gains will be significantly greater.
The prospects for net social gains from the turbidity per-
formance requirement were evaluated for hypothetical water sys-
tems of varying sizes. Net gains are overwhelming for all system
size categories serving more than 1000 people. For systems serv-
ing fewer than 1000 people, net losses appear, but there are many
caveats that apply to this result. One caveat is that many small
systems which have difficulty meeting performance requirements
may represent situations where an older plant is in need of
replacement.
The costs of the groundwater portion of the Total Coliform
Rule are different in concept from the costs to surface water
systems in that they relate to only one aspect — monitoring of
coliforms ~ of the total approach to avoiding contamination from
microbial contaminants. The most significant requirement of the
Total Coliform Rule is an increase in the minimum number of
samples (to five/month) which small water systems must collect
and analyze. The proposal is based on results of statistical
analysis which has shown that the present level of monitoring in
small systems is inadequate to compensate for the probability of
obtaining false negatives.
The benefit of the Total Coliform Rule derives from the
value of the monitoring information it will provide. However,
given the technical findings which form the basis for the pro-
posal, it is clear that the value of such monitoring data is zero
(or negative) until a certain number of samples have been col-
lected and analyzed ~ the number proposed in the rule. Coliform
monitoring is a fundamental component of water treatment for
control of microbial contaminants. Though the absence of coli-
forms provides incomplete assurance that other pathogens are
absent also, the presence of coliforms is a fairly good indicat-
ion there is a problem worth investigating, conceivably involving
a broad range of disease agents related to fecal contamination.
It is believed the extra cost of obtaining a statistically
reliable number of samples would be deemed worthwhile by the
public health profession.
It is obvious from the summary presented in Exhibit 7-1 and
7-2 that the proposed rules will produce significant impacts on
small water systems. The state flexibility provided in the
approach to implementation is the major factor which will offset
the potential for inducing any extreme economic hardships. The
expanded exemption provisions of the 1986 Amendments to the Safe
7-5
-------
Drinking Water Act lay the groundwork for states to begin a
process of helping small systems to overcome their financial
difficulties and assure protection of public health.
7-6
-------
APPENDIX A
DECISION TREES FOR UNFILTERED SYSTEMS
SERVING FEWER THAN 100,000 PERSONS
-------
NDEXOFTKNS
TtflE 1-1 — GCMUANX QtttCES FOB UflUIHED BXffCE. WKIER SKTO6 (CttMJNUH
VHICH CURPENM HAW NO TTEKC€NT IN PLACE
COMIinY WfflER SXSIEM SIZE CAIHDRIES
TDTOL # SSIDBi
(154)
CPTICNS
1. Alternate Source
2. Package Treatment
Plant
3* Conventional
Treatment Plant
4. ABW Conventional
Treatment Plant
5. Direct Filtration
(Pressure)
6. Direct Filtration
(With Flcoculatkn)
7. Direct Filtration
Population Population Population Population Pcpulatlcn
25-100 101-500 501-1,000 1,001-3,300 3,301-10,000
Cost
3.03
9.45
NA
NA
NA
NA
m
9 sys Cost
(67) VIWJ
50X 1.18
2.77
NA
NA
NA
NA
- m
l»i
f sys Cost
(39) VUG
25* 0.60
15* 1.95
NA
NA
3.39
NA
NA
t sys Cost
(24) VTn3
20* 0.35
20* 1.14
NA
NA
1.47
1.60
1.41
f sys Cost
(19) VIWJ
10* NA
25* 0.73
1.08
0.92
0.83
5* 0.95
10* 0.85
f sys
(5)
•-_•- _•!•_•_
25*
15*
15*
(Without Flcoculatlcn)
8. DiatoiBcecus
Earth Plant
9. Slew Sand
Filtraticn Plant
2.58 20* 1.61 20* 0.80 20* OJ2 20*
50* 2.29 35* 1.49 35* 0.65 25* 0.38 25*
10. Ultraftltraticn
Plant
5.22
2.51
5* 1.95
5X 1.48
5*
-------
2/3 ICG FEEUCFICN
1-2 — OMUANCE CHUCES FDR IWTUHe) SlfFACE WKR SKIH6 (OMiMEf SYSTEMS)
MUCH CUWeHDT HAVE ID TOKMNT IN PLACE
OOtUfflY WHER SYSTEM SEE aOEDORIES
TOTAL 1 SYSTEMS:
(154)
CCmiAKZ
CPHOB
1. Alternate Source
2. Cbtaln Exception by:
a. Add 03 & C12 Resid.
3. Package Treatment
Plant
4. Conventional
Treatment Plant
5. ABW Conventional
Treatment Plant
6. Direct Filtration
(Pressure)
7. Direct Filtration
(With Flooculatlcn)
8. Direct Filtration
(Without Flccculatlcn)
9. Diatorececus
Earth Plant
10. Slew Sand
Filtration Plant
11. Itttrafatraticti
Population Population
25-100 101-600
Cost t sys Cost
$/TH3 (67) VUG
3.03 50* 1.18
3.74 1.28
M, — 2.T,
NA MA
NA _ NA
NA NA
NA NA
jift NA
7.46 2.58
•v
4.44 50* 2.29
5.22 2.51
1 sys
(39)
23*
20*
1C*
10*
30*
5*
Population Population Population
501-1,000 1,001-3,300 3,301-10,000
Cost
$Tn3
0.60
0.67
1.95
m
NA
3.39
NA
NA
1.61
1.49
1.95
1 sys Cost I sys Cost
(24) &ThG (19) VWJ
20* 0.35 10* NA
20* 0.31 20* 0.16
15* 1.14 23* 0.73
NA 1.08
NA 0.92
— w — (U8
1.60 5* 0.95
1.41 5* 0.85
10* 0.80 15* 0.72
30* 0.65 20* 0.38
5* 1.U8 NA
1 sys
(5)
20*
20*
10*
10*
20*
20*
— -*—
Plait
-------
3/4 UE PHXJCnDN
TAH£ 1-3 — GCmiMCE CHOKES FOR ItFILTHH) SUPFACEWIOTR SKKM3 (OOMMIY 3SIBG)
\WCH CURPEMLSf HAVE M) THEKMOT IN FtflCE
COMJHTIY WATER SK5TCM SIZE CAIHCRIES
TOTAL » SXSTC>6:
(154)
(OTUANCE
cpnrjtB
1. Alternate Soiree
2. Obtain Bccepticn by:
a. Add 03 & C12 Resid.
Plant
4. Conventional
Treatment Plant
5. AEW Conventional
Treatment Plant
6. Direct Filtration
(Pressure)
7. Direct Filtration
(With Flooculaticn)
8. Direct Filtration
(Without Flccculation)
9. Diatcmacecus
Earth Plant
10. Slew Sard
Filtration Plant
11. Ultrafiltraticn
Population Population Pcpulaticn Population Population
25-100 101-600 501-1,000 1,001-3,300 3,301-10,000
Cost # sys Cost
vnc (67) $TK]
3.03 50* 1.18
3.74 1.28
9.45 _ 2.77
NA •- NA
NH NA
Nft ~__~~ NA
m. jft
NA NA
7.U6 2.58
4.44 50* 2.29
5.22 2.51
$ sys Cost
(39) &TKJ
23* 0.60
20* 0.67
10* 1.95
NA
MA
w^_v* BWI
3.39
— W
NA
10* 1.61
30* 1.49
5* 1.95
ff sys Cost
20* 0.35
20* 0.31
15* 1.14
NA
NA
1.47
1.60
1.41
10* 0.80
30* 0.65
5* 1.48
t sys Cost
(19) fcTbG
10* NA
20* 0.16
25* 0.73
1.08
0.92
0.83
5* 0.95
5* 0.85
15* 0.72
20* 0.38
m
tf sys
(5)
20*
20*
10*
10*
20*
20*
Plant
-------
_V«* LUJ n&UCl'UM HO.lt 1MU KUNIS U- HUUOtNT MSUFtUTIDN
TAHEl^~CCmiAN£(HnaESFCRU^^
ccmwnY W/OER SYSTCM SEE CWBDDRIES
TOOL * SXSTO6: Pcpulaticn Pcpulaticn Pcpulaticn Pcpulaticn Pcpulaticn
(154) 25-100 101-600 501-1,000 1,001-3,300 3,301-10,000
aHUME Cost
OPTIONS VIKJ
1. Altercate Source 3.Q3
2. Obtain Exception by: 3.85
a. Add 03 & C12 Besld.
. racKgge ireeunent 9*45
Plant
J 1. Conventional NA
*T\~W^i Hi ^tt" Pi £Vkf"
iicnuit_riu riciiu
5. AEU Conventional NA
TVeatmait Plait
6. Direct Filtration NA
(Pressure)
7. Direct Filtraticn NA
(With Flccculaticn)
8. Direct Filtraticn NA
(Without Flccculaticn)
9. Diatareceous 7.46
Earth Plant
10. Slew Sard 4.44
Filtraticn Plant
11. ULtrafQtration 5.22
f sys Cost
50* 1.18
1.33
2.77
NA
NA
. im
iv%
NA
Mft
__^__ 1W»
2.58
50* 2.29
2.51
9 sys Cost
(39) 3/IKJ
25* 0.60
20* 0.70
10* 1.95
NA
NA
3.39
NA
NA
10* 1.61
30* 1.49
5* 1.95
t sys Cost
(24) $/IrG
20* 0.35
20* 0.33
15* 1.14
MA
•«••»* fWl
NA
— w
1.60
1.41
10* 0.80
30* 0.65
5* 1.48
t sys Cost
(19) */lb3
10* NA
20* 0.17
25* 0.73
1.08
0.92
0.83
5* 0.95
5* 0.85
15* 0.72
20* 0.38
^
ff sys
(5)
_____
20*
20*
10*
10*
20*
20*
Plant
-------
TAEtE 2-1 -.OCH1JAKE POKES FOR IMT13HH) SUFATC VOTER SSTCM5 (COMJKnY SEEMS)
VHHH CUWMUr
HRVE CHI DISUFBCnCN IN FLKE
OOHMIY HWER SKSKH SEE
IDEAL f 9BIQ6:
(1177)
(HHJANCE
CFTEDNS
1. Alternate Sorce
2. RackBge Treatment
Plait
> 3. Gcnventknal
01 Treatment Plait
4. AEH Cawentlcnal
Trestncnt Plait
5. Direct Filtraticn
(Pressure)
6. Direct Flltratlcn
(With Fl«« ••-»--_--«••
NA
1.16 20*
1.33 36*
1.79 9*
GffTBQCKIES
Population
1,001-3,300
Cost f sys
$TH3 (207)
0.35 10*
l.tt 23*
NA _
NA _
1.37
1.50 5*
1.31 10*
0.70 20*
0.55 23*
1.38 5*
Population
3,301-10,000
Gcet f sys
4/IH3 (155)
NA
0.73 23*
1* —
0.88
0.79
0.91 15*
0.81 19*
0.68 20*
0.3«» 23*
NA
Population
10,001-50,000
Gcet 1 sys
1/nc (90)
NA
0.52
0.65 20*
0.55 20*
O.JI6
0.55 20*
0.51 20*
O.U8 10*
0.28 10*
W
Population
50,031-100,000
Gcet f sys
fcTH} (23)
m _
NA
0.58 20*
0.5U 20*
Ml —
O.fT 23*
OJ43 30*
O.H6 9*
K*
tt\
Plant
-------
— OMUHNCE OOnXS FCR UfOUEHED OfFACE HA3ER SSSIHB (OmWTIY SEISMS)
VHCH OHonur HAVE ou DEDracnai m PUCE
ttmtOTf VOTER SEIEM SEE CWHCRIES
TOOL * SKSIH6:
(1TH)
OOfUANCE
GPTEDNS
1. Alternate Source
2. Cbtaln Exceptloi By:
a. AWOSChly
b. 3hcr CT KXV2CO & Md C12 RecLti
c. Incr CT 150-200 4 Add C12 Redun
d. *tt C12 Rednfency
. 3. Package Treatment
i, Plat
4. Conventional
Treatment Plant
5. AEH CcnvenUoral
Treatment Plant
6. Direct Filtration
(Pressure)
7. Direct Filtration
(With Flooculatdcn)
8. Direct Filtration
(Without Flocculatkn)
9. DiatxoEcecus
Earth Plant
10. Slew Sard
Filtration Plait
11. ULtrafiltraticn
Peculation Pcpjlatlcn PopuLatloi Population
25-100 101-500 501-1,000 1,001-3,300
Cost
VUG
3.03
3.31
2.45
2.38
2.30
ftff
Ml
NH
Ml
Ml
6.80
3.78
4.56
I sys Cost
(243) VHC
40* 1.18
10* 1.13
0.84
0.80
0.76
2.77
NH
— *
— •*
Ml
2.34
45* 2.05
5* 2.27
f sys Cost
(a56) vnc
30* 0.60
15* 0.57
0.37
0.35
1C* 1.95
Ml
Ml
3.23
Ml
1C* 1.45
30* 1.33
5* 1.79
f sys Cost
(193) VMS
15* 0.35
20* 0.23
0.16
0.15
0.13
15* 1.14
— *
— *
1.37
1.50
1.31
15* 0.70
30* 0.55
5* 1.38
f sys
(207)
1C*
16*
4*
23
—
_
5*
5*
11*
20*
Population
3,301-10,000
Cost
Vive
Ml
0.14
0.09
0.08
0.07
0.73
1.04
0.88
0.79
0.91
0.81
0.68
0.34
Ml
i sys
(155)
9
13
8*
20*
1C*
10*
10*
10*
4*
— .
Population
10,001-60,000
Cost
4/nc
Ml
0.07
0.04
0.03
0.03
0.52
0.65
0.55
0.46
0.55
0.51
0.48
0.28
Ml
f sys
(90)
a
13
13
13
1
15*
15*
- " ••
11*
11*
4*
• ••
.
PopOatlcn
50,001-100,000
Cost
l/nc
Ml
0.04
0.02
0.02
0.01
Ml
0.58
0.54
0.41
0.47
0.43
0.46
Ml
Ml
1 sys
(23)
1*
81
16*
20*
" T "
13
13
1 '
13
13
4*
•
Plait
-------
TAO£ 2-3 — OGMUAKE OOKES FDR UNTUnO SUFACE WOER SfSTCHS (COftWnY SKSIHC)
VMCH OHBflUr HWE CMY DBMBCEICN IN PUCE
OHUfCIY WOEH SBIEM SEE CAHDDRIES
TOOL f SBTO6:
(1177)
CPTOE
1. Alternate Sort*
2. Obtain Exception By:
a. Add 03 Only
b. Ihcr CT 150-300 4 Add C12 Rain
c. Ihcr CT 230-300 & Add C12 Redn
d. Add C12 Redutfcrcy
Plant
4. Conventional
Treatment Plant
5. AEH Ccnvaticnal
Treatment Plant
6. Direct Filtration
(Pressure)
7. Direct Flltraticn
(With F]oorul9t1m)
8. Direct Flltraticn
(Without Flccculatlon)
9. DiatoiBoecuB
Earth Plait
10. Slow Sard
Filtration Plant
11. ULtrafiltraticn
Population Population Population Pcpula
25-100 101-600 501-1,000 1,001-3
Cost
3.03
3.31
2.46
2.32
2.30
9.45
»
HI
m.
6.80
3.78
4.56
f sys Cost
(243) *mc
40* 1.18
10* 1.13
0.85
0.77
0.76
2.77
NH
— m
— *
— m
2.34
45* 2.05
5* 2.27
f sys Cost
(266) 4/IW
30* 0.60
15* 0.57
0.38
033
10* 1.95
— *
— *
3.23
__ ua
•— — • rat
(A
10* 1.45
30* 1.33
5* 1.79
f sys Cost
(193) */Ih3
15* 0.35
20* 0.25
0.17
0.14
0.13
15* 1.W
— *
tA
1.37
1.50
1.31
15* 0.70
30* 0.55
5* 1.38
tlm Prpilflticn
,300 3,301-10,000
f sys Cost
(207) VM
10} NH
a9 0.14
4S 0.09
0.07
0.07
25* 0.73
1.04
0.88
0.79
5* 0.91
5* 0.81
11* 0.68
20* 0.34
— — — JA
1 sys
(155)
ie*
8*
5*
20*
10*
10*
10*
10*
11*
—
-
Population
10,001-60,000
Cost
Fft
0.07
0.04
0.03
0.03
0.52
0.66
0.55
0.46
0.55
0.51
0.48
0.28
MR
I sys
(90)
12*
12*
8*
4*
15*
10*
15*
15*
9*
- - - -
Peculation
50,001-100,000
Ccet
1/nc
»
0.04
0.02
0.01
0.01
IA
0.58
0.54
0.41
0.^7
0.43
0.46
tA
tA
i sys
(23)
9
16*
13
at
1C*
19
15*
15*
6*
—
Plait
-------
tut F. SUl — m*UMEE CHOKES FCB UFMCTED SURFACE WMEH atSHHS (OJHMTlf SC5IB6)
VtiDCH OHODLSr WWE OJCC WSWHTDON IN PLACE
omim VBOER sram SEE oranoES
TOOL f SKSEM5:
(1177)
COfUANX
OPUCNS
1. Alternate Soiree
2. Obtain Exception By:
a. Ml 03 & Ml C12 Redntfency
d! Ml C12 Redtn & 2nd PtHfl
3. Package Treatnent
Plait
»
» 1. Conventional
TVcatment Plcnt
5. tOI Conventicrai
Treatment Plant
6. Direct Flltraticn
(Presstre)
7. Direct FiltiBticn
(With Floooulatloi)
8. Direct Filtration
(Without Flooculsticn)
Q. Difltonacecus
PqptQatlcn Populaticn Pcpulff
25-100 101-600 50V-1
Ccet
4/nc
3.03
3.39
3.00
2.86
2.81
M
>
m
m
NA
HA
6.80
f sys Cost
10* 1.18
10* 1.17
0.97
0.97
0.96
' 2.77
m.
NH
— *
— *
(A
2.31
I sys Cost
(266) 4/I1C
30* 0.60
15* 0.60
0.51
0.16
0.16
10* 1.95
m
— m
3.23
— *
NA
10* 1.15
bkn Pcpfla
,000 1,001-3,300
f sys Cost
(193) 1/IW3
19* 0.35
20* 0.26
0.25
0.22
0.21
15* 1.14
*
— *
1.37
1.50
1.31
19* 0.70
i sys
(207)
10*
20*
1*
25*
5*
5*
11*
Population
3,301-10,000
Cost
Nft
0.11
0.13
0.11
0.11
0.73
1.01
0.88
0.79
0.91
0.81
0.68
I sys
(155)
16*
8*
5*
20*
10*
10*
10*
10*
11*
Population
10,001-60,000
Ccet
(A
0.07
0.07
0.05
0.05
0.52
0.66
0.55
0.16
0.55
0.51
0.18
f sys
(90)
13
13
ft
IK
— —
15*
1C*
15*
15*
9*
Population
50,001-100,000
Cost
vac
NA
0.03
0.03
0.03
0.02
NA
0.58
0.51
0.11
0.17
0.13
0.16
I sys
(23)
8*
16*
13
8*
— —
10*
101
___
15*
19*
Garth Plait
10. Slew art 3.78 45* 2.05 30* 1.33 30* 0.55 20* 0.31 0.28 NA
Filtration Plait
11. ItttrafUtratlcn 4*56 5* 2.27 9* 1.79 5* 1.38 Nil NA NA
Plant
-------
NDBOFIICNS
TftELE 1-1 — OMUATCE CHOICES FCR UITLIHH) SURFME WATER SSI06
VHICH CUKeHCr HAVE ND TFEKMNr IN PLACE
WATUt SEllM SLZt CftltlJdtlES
TOWLf SSSEMS:
(178)
OCMUANCE
CPIIDN5
1. Alternate Source
2. Padage Treatment
Plait
3. Conventional
1. AEW Conventional
"Treatment Plant
5. Direct Filtration
Pctxilaticn
25-100
Cost 1 sys
$/Th3 (111)
3.03 50*
NA
NA
NA
Population
101-500
Cost I sys
I/M (52)
1.18 33*
2.77 15*
NA
Population
501-1,000
Cost t sys
VIW) (7)
0.60 30*
1.95 20*
NA
NA
3.39
Population
1,001-3,303
Cost 1 sys
$TH3 (1)
0.35 25*
1.11 25*
NA
NA
1.VT
Pcpflation
3,301-10,000
Cost
0.73
1.08
0.92
0.83
f sys
(1)
50*
(Pressure)
6. Direct Filtration
(With Flccculaticn)
7. Direct FUtraticn
(Without Flccculaticn)
8. DiatoiBcecus
Earth Plant
9. Slow Sand
Filtration Plant
10. Ultranitration
Plant
7.H6
5.22
NA
NA
2.58
NA
NA
1.61
1.60
0.80
0.95
0.85
0.72
2.29 5C* 1.19 50* 0.65 50* 0.38 50*
2.51
1.95
1.48
NA
-------
TAELE
— GOfUMCE CHUCES FCR IffFOLIEICD SUFACE WATER SKSTCHS
VWCH OHOOLSf WWE NO TFEKMNT HJ PUCE
VKTCR SfSTCM SEE CftTEQOKIES
TOTAL f SKSID6:
(178)
GOfUANCE
GPTIDN5
1. Alternate Source
2. Obtain Exception By:
a. Add 03 & C12 Hesid
3rv«J— »— -» IVLJLIL|»LJ j_jl
. Pacioge Ireatinait
Plant
4. Ccnventicnal
Treatment Plant
5. AEW Cewenticnal
Treatment Plant
6. Direct Filtration
(Pnesare)
7. Direct Filtration
(With Flcoculatloi)
8. Direct Filtraticn
(Without Flooculation)
9. DiatcnBceoB
Population Population Population Population Population
25-100 101-500 501-1,000 1,001-3,300 3,301-10,00)
Cost 1 sys Cost
$/IHJ (114)
-------
1-3 — CCmiANCE CHOKES FOR UnLIHH) SUFACE WKffiH
VHICH cuwenur HAVE ID TFomfNT IN PUCE
WATER SYSTEM SIZE CJUHUUlS
TOOL f SXS1H6:
(178)
OCmiANCE
CPEDQNS
1. Altemate Source
2. Cbtain Exception By:
a. Mi 03 & C12 Resid
. Package Trauma*
Plant
1. Ccnventicnal
TttEiuient riant
5. AW CcnventicnBl
Treatment Plant
6. Direct Filtration
(Presare)
7. Direct Filtraticn
(With Flccculaticn)
8. Direct Filtraticn
(Without Flccculaticn)
9. Diatoiececus
Earth Plant
10. Slew Sard
Filtration Plant
11. Ultraflltraticn
Population Population
25-100 101-600
Ccet f sys Cost 1 sys
VTrfi (111) VTM (52)
3.03 50* 1.18 30*
3.71 1.28 20*
9.15 2.77 10*
NA NA
MA — — NA — —
* — * —
NA — NA —
» _ NA —
7.H6 2.58
4.11 50* 2.29 10*
5.22 2.51
Population
501-1,000
Cost * sys
*/fW* (T\
tytti} (.{)
0.60 23*
0.67 20*
1.95 15*
NA
3.39
NA
NA
1.61
1.19 10*
1.95
Population
1,001-3,300
Cost i sys
$/TrC (1)
0.35 15*
0.31 20*
1.11 23*
NA
NA
1.17
1.60
1.H1
0.80
0.65 1C*
1.U8
Population
3,301-10,000
Cost f sys
*/TW> f*\
3/lrli lu
0.16
0.73
1.08 -
0.92 -
0.83 -
0.95 -
0.85 -
0.72 -
0.38
NA
•••*•
20*
10*
MBB^B*
»•"•!•
MMI^B
^•^•M
!•••*•
10*
MH^B
Plant
-------
TAELE 1-4 — CCmiANCE CHOICES FOR UITLIEJED SUFACE HAIEB SfSIBtS!
VHICH OUVOOLir HAVE K) TTEAimff DJ PLACE
W/QtK SBltM Jil/E CftitUUkliii
IDEAL 1 SEEMS:
(178)
OmiANCE
CPEIDNS
1. Alternate Sorce
2. Obtain Exception By:
a. Add 03 & C12 Resid
3. Package Treatment
Plant
4. ConventicnaL
£ Treatment Plant
N)
5. ABW Conventional
TreataEnt Plant
6. Direct Filtraticn
(Pressire)
7. Direct Filtration
(With FloocuLaticn)
8. Direct Filtraticn
(Without Flooculaticn)
9. Diatomoeous
Earth Plant
10. Slew Sand
Filtraticn Plant
11. ULtrattltraticn
Population Peculation Population Population Pcpulaticn
2MCO 101-600 501-1,000 1,001-3,300 3,301-10,000
Cost * sys Cost I sys Cost
fcrtrfi (114) ^TrG (52) VThO
3.03 50* 1.18 30* 0.60
3.85 1.33 20* 0.70
9.45 2.77 10* 1.95
» _ . — »
jft w 3.39
m m NA
m — M — NA
7.46 2.58 1.61
4.4M 50* 2.29 40* 1.49
5.22 2.51 1.95
I sys Cost
(7) 1/IrG
25* 0.35
20* 0.33
15* l.W
— m
NH
— '*
1^0
— 1JH
0.80
40* 0.65
1.48
I sys Cost
(4) 1/IrG
15* MA
20* 0.17
25* 0.73
1.08
0.92
0.83
0.95
0.85
0.72
40* 0.38
NA
I sys
(1)
20*
40*
1
•'•
40*
— —
Plant
-------
K)EXCEPFDOt&
TM£ 2-1 - OMUMCE CHOKES FOR IWFUJOTD SUFJICE WOTRSKFEM5
WHICH CURPENLir HW/E OCX KSMBCnDN IN PLACE
WOTR SYSTEM SEE CAIKBRIES
TOTAL I SSTCK5:
(1358)
OMPUWCE
CPITDIB
1. Alternate Soiree
2. Pads^ge TV^Ut^mt
Pl£t»t
3. Conventional
Treatnent Plant
1. AEH Ccnventional
Treatment Plant
5. Direct Filtration
(Presare)
6. Direct Filtration
(With FLcoculation)
7. Direct Filtraticn
(Without Flooculatlcn)
8. DiatorBceous
Earth Plant
9. Slew Sand
Filtration Plant
10. ULtranitraticn
Population
25-100
Cost t sys
tTVG (869)
3.03 50*
9.15
m —
m _
m —
m
MA -
Jvm ^^^^^^^
6.80
3.78 50*
1.56
Population
101-500
Cost 1 sys
*/ThG (393)
1.18 35*
2.77 15*
NA
MA
IV* ^^^«^^™
NA
m _
NA
2.31
2.05 50*
2.27
Population
501-1,000
Cost i sys
0.60 30*
1.95 3D*
NA
^ —
3.23
NA
NA
1.15
1.33 50*
1.79
Population
1,001-3,300
Cost 1 sys
VM (33) .
0.35 25*
1.11 23*
NA
NA _
1.37
1.50
1.31
0.70
0.55 50*
1.38
Population
3,301-10,000
Cost i sys
$/Ihj (9)
N&
AWl ^^^^^^^
0.73 50*
1* —
0.88
0.79
0.91
0.81
0.68
0.31 50*
NA
Population
10,001-50,000
Cost i sys
J/IHJ (0)
NA
0.52
0.66 50*
0.55
0.16
0.55
0.51 50*
0.18
0.28
MA
Population
50,001-100,000
Cost
NA
NA
0.58
0.51
0.11
o.vr
0.13
0.16
NA
NA
1 sys
(0)
50*
50*
Plant
-------
TAttE 2-2 — OOmiANCE CHHCES FOR l*FILJEfH> SURFACE WHER SYSTO6!
WffCH OKFBOIX HAVE CHI KSDfBCnDN IN PLACE
WA3ER SYSTEM SIZE CATEGORIES
TOOL * SXSIB6:
(13B8)
QOmJANCE
OPTIONS
1. Alternate Soiree
2. Obtain Exception By:
a. Add 03 Only
b. Ihcr CT 100-200 & Ml C12 Recta
c. Ihcr CT 150-200 & Add C12 Redun
d. Add C12 Redundancy
3. Package Treatment
Plant
jf 4. Conventional
j> Treatment Plant
5. AEW Conventional
IV .ii.j .,_,.>- fll r^JL
lieauiEiit riant
6. Direct Flltraticn
(Pressure)
7. Direct Flltraticn
(With Flajculatlcn)
8. Direct Filtration
(Without Flooculatlai)
9. Dlatanacecus
Earth Plant
10. Slow Sard
Filtration Plant
11. Uttrafiltratlcn
Population
25-103
Cost I sys
W*G (859)
3.03 45*
3.31 10*
2)38 —
2.30
9* —
Uft .
1T1 ^^i^^^—
NA
NA
NA
NA
6.80
3.78 45*
4.56
Population Population Population
101-500 501-1,000 1,001-3,300
Cost
1.18
1.13
0.84
0.80
0.76
2.77
NA
NA
NA
NA
NA
2.34
2.05
2.27
I sys Cost
(393) VM
35* 0.60
20* 0.57
0.37
0.35
10* 1.95
NA
NA
3.23
NA
NA
1.45
35* 1.33
1.79
i sys Cost 1 sys
(54) yQC (33)
23* 0.35 16*
20* 0.25 16*
0.16 4*
0.15 4*
0.13
20* 1.14 25*
NA
_____ NA _____
1.37
- — 1.50
1.31
0.70
35* 0.55 35*
, . 1.38
Population
3,301-10,000
Cost i sys
*/TlC (9)
NA
0.14 8*
0.09 12*
0.08 8*
0.07 8*
0.73 30*
1.04
0.88
0.79
0.91
0.81
0.68
0.34 34*
NA •— -—
Population
10,001-50,000
Cost i sys
1/TtC (0)
NA
0.07 8*
0.04 12*
0.03 12*
0.03 12*
0.52 30*
0.66
0.55
0.46
0.55
0.51
0.48
0.28 26*
NA
Population
50,031-100,000
Cost
NA
0.04
0.02
0.02
0.01
NA
0.58
0.54
0.41
0.47
0.43
0.46
m
NA
1 sys
(0)
4*
8*
16*
20*
•
— —
24*
24*
4*
— _
Plant
-------
TAELE 2-3 — CCHUMCE CHOKES FOR ItFlUBED SUFACEUA1ER SSKMS
WTCH cuHeou HAVE our rasnecnoi m PUCE
WMER SEEM SEE CAlUUUtS
TOOL f SYS1B6:
(1358)
OCMPLUNCE
cmctB
1. Alternate Source
2. Cbtaln Exception By:
a. Aid 03 Only
b. Incr CT 100-300 & Mi C12 Bedn
c. Incr CT 150-200 & Add C12 Rectn
d. Add d12 Redundancy
3. Piackgge Treatment
Plait
"4. Ccnventicnal
n Treatment Plant
5. AEW Ccnventicnal
Treatment Plant
6. Direct Filtration
• (Pressure)
7. Direct Filtration
(With Flccculaticn)
8. Direct Filtration
(Without Flccculaticn)
9. DiatoiBoecus
Earth Plant
10. Slew Sand
Filtration Plant
11. mtrafUtratkn
Pen flat! on
25-100
Cost f sys
VttG (869)
3.03 43*
3.31 10*
2.*32
2.30
9.45
NA
Nd
m —
m
NH
6.80
3.78 45*
4.56
Population
101-500
Cost § sys
vnc (393)
1.18 33*
1.13 20*
0.85
0.77
0.76
2.77 10*
Nft
m —
m
" ~~
* —
2.34 — — -
2.05 35*
2.27
Population
501-1,000
Cost f sys
I/M (54)
0.60 25*
0.57 20*
0.38
0.33
1.95 20*
N* —
m —
3.23
VK.
W
1.45
1.33 35*
1.79
Population
1,001-3,300
Cost f sys
$/IH5 (33)
0.35 16*
0.25 20*
0.17 4*
0.14
0.13
1.14 25*
m.
Nd
1.37
1.50
1.31
0.70
0.55 35*
1.33
Population
3,301-10,000
Cost f sys
t/M (9)
fft — — —
0.14 16*
0.09 8*
0.07 5*
0.07
0.73 36*
1* —
0.88
0.79
0.91
0.81
0.68
0.34 33*
MA -• - - -
twi ^^^»^^»
Population
10,001-50,000
Cost f sys
1/IhG (0)
» _
0.07 13
0.04 13
0.03 8*
0.03 4*
0.52 39*
0.66
0.55
0.46
0.55
0.51
0.48
0.28 25*
NA — — —
Population
50,001-100,00)
Cost
m
0.04
0.02
0.01
0.01
m
0.58
0.54
0.41
0.47
0.43
0.46
fft
M
i sys
(0)
8*
16*
13
— —
25*
25*
6*
— .
Plant
-------
WIE2-4 — OMUANCE CHOKES FOR UNTLTCHD SUFAOE WOTR SGSIEMS
UflOt OUREBOUr HAVE OUT BEDR
EnEW IN PLACE
WMBSE
TOOL 1 SSSTO6:
(1358)
GCmiANX
CFODN5
1. Alternate Source
2. Obtain Exception By:
a. Mi 03 4 Ml C12 Redundancy
d. Mi C12 Rain & 2ni FWR
3. Package Treatment
Plant
*«
*4. (Conventional
Treatment Plant
5. AEW CcrwoTticnal
Treatment Plant
6. Direct Filtration
(Pressire)
7. Direct Filtration
(With Flccculaticn)
8. Direct Filtration
(Without Flccculaticn)
9. Diatcmacecus
Earth Plant
10. Slew Sard
Filtration Plant
11. Ultrafiltration
Population Population
25-KB 101-600
Cost
VUG
3.03
3.39
3.00
2.86
9.45
NA
*
NA
NA
NA
6.80
3.78
4.56
1 sys Cost f sys
(869) */&C (393)
45* 1.18 35*
10* 1.17 20*
0.97
0.97
0.96
— "» m
— " —
. . . . _ NA —
NA
_____ flu
_ NA —
2.34
45* 2.05 35*
•^ •• •• _£•£»( "
IEM SEE CAmiMES
Population Pcpula
501-1,000 1,001-3
Cost
0.60
0.60
0.51
0.46
0.46
1.95
NA
NA
3.23
NA
NA
1.45
1.33
1.79
I sys Cost
(54)
-------
APPENDIX B
DECISION TREE AND COST MODEL FOR
COMPLIANCE OF FILTERED SYSTEMS
WITH TURBIDITY PERFORMANCE REQUIREMENT
-------
TABLE 3 ~ COMPLIANCE COSTS FOR SYSTEHS HAVING CONVENTIONAL TREATMENT KITH NO SOFTENING AND RAPID SAND FILTERS
POPULATION SIZE CATEBORYi 23-100 101-50050MK 1-3.3K 3.3-10K10-25K 25-50K 50-75K 7S-100K.1H-.5H .5-1H 1 HIL TOTALS
I SYSTEMS
1 H/AVE. TURBIDITY > 0.3
1 H/AVE. TURBIDITY > 0.3
S to IMPROVE 0(H
t to IMPROVE OUI
DIAWOSTIC/installation (I OOO's)
TOTAL CAPITAL COST (t OOO's)
EXTRA Old/installation (t OOO's/yr)
TOTAL EXTRA OUI (t OOO's/yr)
ANNUAL COST/installation (» OOO's/yr)
TOTAL ANNUAL COST (f OOO's/yr)
S «out/RAPID HIX
1 HOUt/RAPIO HIX
S to install RAPID HIX
t to install RAPID HIX
CAPITAL COST/installation (1 OOO's)
TOTAL CAPITAL COST (* OOO's)
OUt COST/installation ($ OOO's/yr)
TOTAL OUI COST (t OOO's/yr)
ANNUAL COST/installation (» OOO's/yr)
TOTAL ANNUAL COST <» OOO's/yr)
1 MOut/pH ADJUSTMENT
1 mut/pH ADJUSTHENT
1 to install pH ADJUSTMENT
1 to install pH ADJUSTHENT
CAPITAL COST/installation (1 OOO's)
TOTAL CAPITAL COST (* OOO's)
OUI COST/installation ($ OOO's/yr)
TOTAL OU COST (t OOO's/yr)
ANNUAL COST/installation ($ OOO's/yr)
TOTAL ANNUAL COST <« OOO's/yr)
S HOUt/POLYHER
t HOttt/POLYHER
I to install POLYHER
t to install POLYMER
CAPITAL COST/installation (« OOO's)
TOTAL CAPITAL COST (t OOO's)
OUI COST/installation ($ OOO's/yr)
TOTAL OUI COST (1 OOO's/yr)
ANNUAL COST/installation ($ OOO's/yr)
TOTAL ANNUAL COST (t OOO's/yr)
TABLE 3 TOTALS
CAPITAL COST/installation (f OOO's)
TOTAL CAPITAL COST (I OOO's)
OUI COST/installation (1 OOO's/yr)
TOTAL OUI COST (t OOO's/yr)
ANNUAL COST/ instil lit ion (t OOO's/yr)
TOTAL ANNUAL COST I* OOO's/yr)
ANNUAL COST/Housthold (Is/yr)
CENTS/Thousand Gallons
170
O.B
143.4
1
143.6
5
718
3.0
431
3.3
479
0.25
35.9
0.55
19.7
13.2
261
2.B
55
3.7
73
0.3
43.1
0.75
32.3
2.6
84
1.1
34
1.2
40
0.7
100.5
0.55
55.3
15.9
879
1.6
88
2.7
147
13.5
1942
4.2
608
5.1
739
108
108.44
171
0.7
126.4
I
126.4
10
1264
6.0
758
6.7
843
0.25
31.6
0.55
17.4
17.5
304
2.9
50
4.1
71
0.3
37.9
0.75
28.4
3.0
84
1.4
38
1.5
44
0.7
88.5
0.55
48.7
22.9
1117
1.7
83
3.2
158
21.9
2768
7.4
930
8,8
1116
47
47.31
281
0.7
207.7
I
207.7
10
2077
8.2
1703
8.9
1843
0.25
51.9
0.55
28.6
22.5
642
7
200
8.5
243
0.3
62.3
0.75
46.7
3.7
171
3.3
152
3.5
163
0.7
145.4
0.55
80.0
32.0
2555
4.0
320
6.1
491
26.2
5445
11.4
2374
13.2
2740
39
39.31
433
0.6
274.3
1
274.3
20
5486
16.4
4498
17.7
4867
0.2
54.9
0.55
30.2
30.9
932
7.9
238
10.0
301
0.3
82.3
0.75
61.7
5.6
343
5.9
364
6.3
387
0.6
164.6
0.53
90.5
49.9
4518
4.3
386
7.6
689
41.1
11279
20.0
3487
22.8
6243
30
29.79
487
0.6
308.5
1
308.5
20
6170
16.3
5019
17.6
5434
0.2
61.7
0.65
40.1
47.7
1913
13.3
533
16.5
662
0.3
92.6
0.85
78.7
27.5
2159
5.6
441
7.4
586
0.6
183.1
0.63
120.3
175.6
21127
6.9
829
18.7
2250
101.7
31370
22.1
6823
29.0
8931
13
13.11
183
0.6
115.9
1
113.9
30
3478
19.2
2224
21.2
2458
0.1
11.6
0.65
7.5
63.7
480
22.4
169
26.7
201
0.3
34.8
0.85
29.6
31.3
924
11.0
323
13.1
387
0.6
69.6
0.65
45.2
274.9
12430
8.9
400
27.3
1236
149.3
17311
26.9
3119
36.9
4282
3
2.51
123
0.6
77.9
1
77.9
40
3117
23.7
1849
26.4
2058
0.1
7.8
0.65
5.1
88.2
447
38.2
193
44.1
223
0.3
23.4
0.85
19.9
36.4
722
20.8
413
23.2
462
0.5
39.0
0.63
23.3
468.9
11874
12.2
309
43.7
1107
207.4
16160
35.5
2764
49.4
3850
1
1.09
55
0.6
34.8
1
34.8
SO
1742
30.9
1077
34.3
42 63
0.6 0.4
26.6 26.6
1 1
26.6 26.6
SO 75
1330 1995
38.8 53.0
1033 1411
42.2 58.1
1I9T 1122 1545
0.05
1.7
0.75
1.3
139
182
69.2
90
78.5
103
0.3
10.3
0.85
8.9
47.1
418
34.1
303
37.3
331
0.3
17.4
0.73
13.1
706.4
9230
16.7
219
64.2
839
332.1
11572
48.5
1689
70.8
2467
0
0.41
0.05 0
1.3 0.0
0.73 0.73
1.0 0.0
218 587
218 0
116 313
116 0
130.7 352.5
130 0
0.3 0.15
8.0 4.0
0.95 0.95
7.6 3.8
63.2 123.0
479 466
37.6 155.7
436 590
61.8 163.9
469 621
0.3 0.4
13.3 10.6
0.75 0.75
10.0 8.0
1132.5 3022.9
11499 24128
24.7 38.1
246 464
102.1 261.3
1019 2085
508.4 999.4
13526 26590
68.8 92.6
1831 2465
103.0 159.8
2740 4252
0 0
0.26 0.15
1? 8
0.4 0.4
8.0 3.4
1 1
8.0 3.4
100 100
802 338
174.3 540.7
1398 1827
181.0 347.4
1432 1849
0 0
0.0 0.0
0.73 0.75
0.0 0.0
2100 6670
0 0
1130 3540
0 0
1271.2 3988.4
0 0
0.15 0.15
1.2 0.5
0.95 0.95
1.1 0.5
281.7 564.1
322 272
571.7 1807.4
654 870
590.6 1845.3
675 888
0.4 0.4
3.2 1.4
0.73 0.75
2.4 1.0
3863.1 6182.9
9299 6267
197.3 619.2
475 628
437.0 1034.8
1100 1049
1299.1 2033.2
10424 6876
314.9 984.0
2327 3324
402.3 1120.8
3228 3787
0 0
0.03 0.01
2035
1334
1334
28517
23229
23144
238
131
5378
1646
2007
400
319
6444
4621
5054
838
500
114923
4445
12171
155262
33941
44377
-------
TABLE 4 - COMPLIANCE COSTS FOR SYSTEMS HAVING CONVENTIONAL TREATMENT NITH NO SOFTENING AND DUAL OR HULTI MEDIA FILTERS
POPULATION SI2E CATEGORY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-75K 75-100K.1H-.5H .5-1N 1 MIL TOTALS
t SYSTEMS
S H/AVE. TURBIDITY > 0.3
1 H/AVE. TURBIDITY > 0.3
I to IMPROVE DIM
t to IMPROVE OtH
DIABHJSTIC/instaliation (t 000'$)
TOTAL CAPITAL COST (« OOO's)
EXTRA OHl/installation ($ OOO's/yr)
TOTAL EXTRA DIM (1 OOO's/yr)
AMUAL COST/in*tallation (s OOO's/yr)
TOTAL ANNUAL COST <« OOO's/yr)
I mut/RAPID MIX
t HOUt/RAPIO MIX
I to install RAPID MIX
1 to install RAPID MIX
CAPITAL COST/installation ($ OOO's)
TOTAL CAPITAL COST (« OOO's)
OUI COST/installation (1 OOO's/yr)
TOTAL OMI COST « OOO's/yr)
ANNUAL COST/installation (t OOO's/yr)
TOTAL ANNUAL COST If OOO's/yr)
I MOut/pH ADJUSTMENT
1 MOut/pH ADJUSTMENT
J to install pH ADJUSTMENT
I to install pH ADJUSTMENT
CAPITAL COST/installation ($ OOO's)
TOTAL CAPITAL COST (1 OOO's)
OtH COST/installation (t OOO's/yr)
TOTAL OtH COST (1 OOO's/yr)
ANNUAL COST/installation (1 OOO's/yr)
TOTAL ANNUAL COST (» OOO's/yr)
S mut/POLYHER
t HOUt/POLYMER
J to install POLYMER
1 to install POLYMER
CAPITAL COST/installation (1 OOO's)
TOTAL CAPITAL COST ($ OOO's)
OU COST/installation (1 OOO's/yr)
TOTAL OKI COST « OOO's/yr)
MUM. COST/installation (1 OOO's/yr)
TOTAL ANNUAL COST (t OOO's/yr)
TABLE 4 TOTALS
CAPITAL COST/installation (f OOO's)
TOTAL CAPITAL COST ($ OOO'S)
OIK cOST/installation (t OOO's/yr)
TOTAL OkH COST (t OOO's/yr)
MODAL COST/installation (t OOO's/yr)
TOTAL ANNUAL COST (1 OOO's/yr)
ANNUAL COST/Housihold (Is/yr)
CENTS/Thousand Sal Ions
44
0.7
31.1
I
31.124
5
1S6
3.0
93
3.3
104
0.3
9.3
0.55
5.1
13.2
68
2.B
14
3.7
19
0.5
15.6
0.75
11.7
3
30
1.1
12
1.2
14
0.6
18.7
0.75
14.0
12.1
170
1.6
22
2.4
34
13.6
423
4.6
142
5.5
171
116
115.68
52
0.5
27.5
1
27.450
10
275
6.0
165
6.7
183
0.3
8.2
0.55
4.5
17.5
79
2.9
13
4.1
IB
0.5
13.7
0.75
10.3
3
30
1.4
14
1.5
16
0.6
16.5
0.75
12.4
15.2
188
1.7
21
2.7
34
20.9
573
7.7
213
9.2
251
49
49.14
105
0.5
55.4
1
55.429
10
554
8.2
455
8.7
492
0.3
16.6
0.55
9.1
22.5
204
7
64
8.5
78
0.5
27.7
0.75
20.8
4
76
3.3
68
3.5
73
0.6
33.3
0.75
24.9
18.5
460
4.0
100
5.2
131
23.4
1296
12.4
686
13.9
773
' 51
51.15
209
0.5
110.3
1
110.33
20
2207
16.4
1809
17.7
1958
0.15
16.5
0.55
9.1
30.9
281
7.9
72
10.0
91
0.2
22.1
0.75
16.5
6
92
5.9
98
6.3
104
0.5
55.2
0.75
41.4
23.8
985
4.3
176
5.9
243
32.3
3565
19.5
2155
21.7
2395
53
52.70
255
0.5
IV. t
1
134.61
20
2692
16.3
2190
17.6
2371
0.1
13.5
0.65
8.7
47.7
417
13.3
116
16.5
144
0.2
26.9
0.85
22.9
27
628
5.6
128
7.4
170
0.5
67.3
0.85
57.2
92.8
5309
6.9
394
13.1
751
67.2
9047
21.0
2829
25.5
3437
23
23.27
180
0.5
95.0
1
95.022
30
2851
19.2
1823
21.2
2015
0.1
9.5
0.65
6.2
63.7
393
22.4
138
26.7
165
0.1
9.5
0.85
8.1
31
252
11.0
89
13.1
106
0.5
47.5
0.85
40.4
105.8
4273
8.9
358
16.0
645
81.8
7770
25.3
2408
30.8
2930
8
7.94
104
0.5
54.9
1
54.901
40
2196
23.7
1303
26.4
1450
0.1
5.5
0.65
3.6
88.2
315
38.2
136
44.1
157
0.1
5.5
0.85
4.7
36
170
20.8
97
23.2
108
0.4
22.0
0.85
18.7
133.3
2488
12.2
227
21.1
395
94.1
5169
32.1
1763
38.4
2111
3
2.75
47
0.4
19.8
1
19.849
SO
992
30.9
614
34.3
680
0.05
1.0
0.75
0.7
139
103
69.2
52
78.5
SB
0.1
2.0
0.85
1.7
47
79
34.1
SB
37.3
63
0.4
7.9
0.85
6.7
159.7
1078
16.7
113
27.5
185
113.5
2253
42.1
836
49.7
987
1
0.76
34
0.4
14.4
1
14.358
50
718
38.8
557
42.2
606
0.05
0.7
0.75
0.5
218
117
116
62
130.7
70
0.1
1.4
0.95
1.4
63
86
57.6
79
61.8
84
0.4
5.7
0.95
5.5
209.7
1144
24.7
135
38.8
211
143.9
2066
58.0
833
67.7
972
0
0.43
55
0.4
23.2
I
23.227
75
1742
53.0
1232
5B.1
1349
0
0.0
0.75
0.0
587
0
313
0
352.5
0
0
0.0
0.95
0.0
123
0
155.7
0
163.9
0
0.3
7.0
0.95
6.6
438.9
2905
58.1
384
87.6
580
200.1
4648
69.6
1616
83.0
1929
0
0.31
11 1
0.4 0.4
4.6 0.4
1 1
4.6455 0.4223
100 100
465 42
174.3 540.7
810 22B
181.0 547.4
841 231
0 0
0.0 0.0
0.75 0.75
0.0 0.0
2100 6670
0 0
1130 3540
0 0
1271.2 39B8.4
0 0
0 0
0.0 0.0
0.95 0.95
0.0 0.0
282 564
0 0
571.7 1807.4
0 0
590.6 1845.3
0 0
0.3 0.3
1.4 0.1
0.95 0.95
1.3 0.1
1279.1 3598.9
1693 433
197.3 619.2
261 75
283.3 861.1
375 104
464.5 1123.7
215B 475
230.5 717.1
1071 303
261.7 792.8
1216 335
0 0
0.05 0.00
1097
571
371
14889
11279
12280
91
48
1981
168
802
124
TO
1444
641
739
283
229
21129
2267
3687
39443
148S5
17507
B-2
-------
TABLE 3 ~ COMPLIANCE COSTS FOR SYSTEMS HAVING CONVENTIONAL TREATMENT NITH SOFTENING AND RAPID SAND FILTERS
POPULATION SIZE CATEGORY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-75K 75-100K.1H-.5H ,5-lN 1 NIL TOTALS
1 SYSTEMS
J H/AVE. TURBIDITY > 0.3
1 «/AVE. TURBIDITY > 0.3
I to IMPROVE OtH
1 to IMPROVE OUI
DIAGNOSTlC/installation (« 000 'si
TOTAL CAPITAL COST (1 000' s)
EXTRA OWI/installation (* OOO's/yr)
TOTAL EITRA OtH (» OOO's/yr)
ANNUAL COST/installation (i OOO's/yr)
TOTAL ANNUAL COST (« OOO's/yr)
I HOttt/RAPID MIX
t MMit/RAPID MIX
S to install RAPID MIX
1 to install RAPID MIX
CAPITAL COST/installation (S OOO's)
TOTAL CAPITAL COST (1 OOO's)
OUt COST/installation (* OOO's/yr)
TOTAL OtH COST U OOO's/yr)
ANNUAL COST/installation (» OOO's/yr)
TOTAL ANNUAL COST (» OOO's/yr)
S MOut/pH ADJUSTMENT
I HOUt/pN ADJUSTMENT
S to install pH ADJUSTMENT
I to install pH ADJUSTMENT
CAPITAL COST/installation (I OOO's)
TOTAL CAPITAL COST <« OOO's)
OtH COST/installation (« OOO's/yr)
TOTAL OtH COST (1 OOO's/yr)
ANNUAL COST/installation (t OOO's/yr)
TOTAL ANNUAL COST (t OOO's/yr)
\ NOUt/POLYMER
t wut/POLYHER
J to install POLYMER
* to install POLYMER
CAPITAL COST/installation (» OOO's)
TOTAL CAPITAL COST (* OOO's)
Otfl COST/installation (t OOO's/yr)
TOTAL OUI COST (1 OOO's/yr)
ANNUAL COST/installation (t OOO's/yr)
TOTAL ANNUAL COST (t OOO's/yr)
TABLE 5 TOTALS
CAPITAL COST/installation (1 OOO's)
TOTAL CAPITAL COST <» OOO's)
Out COST/installation (« OOO's/yr)
TOTAL OtH COST (t OOO's/yr)
ANNUAL COST/installation (« OOO's/yr)
TOTAL ANNUAL COST (* OOO's/yr)
ANNUAL COST /Household (Is/yr)
CENTS/Thousand Gallons
B
1.0
7.6
1
7.6017
5
3B
3.0
23
3.3
25
0.6
4.6
0.55
2.5
13.2
33
2.8
7
3.7
9
0.3
2.3
1
2.3
3
6
1.1
2
1.2
3
0.7
5.3212
0.55
2.9266
15.9
47
1.6
5
2.7
B
16.3
124
4.9
37
5.9
45
123
125.34
16
O.B
13.5
1
13.514
10
135
6.0
81
6.7
90
0.6
8.1
0.55
4.5
17.5
78
2.9
13
4.1
18
0.3
4.1
1
4.1
3
12
1.4
5
1.5
6
0.7
9.4599
0.55
5.2029
22.9
119
1.7
9
3.2
17
25.5
345
8.0
108
9.7
131
105
105.31
5?
0.7
43.6
1
43.604
10
436
8.2
3SB
8.9
387
0.6
26.2
0.55
14.4
22.5
324
7
101
8.5
122
0.3
13.1
1
13.1
4
48
3.3
43
3.5
46
0.7
30.523
0.55
16.787
32.0
536
4.0
67
6.1
103
30.8
1344
13.0
568
15.1
658
178
178.37
57
0.6
36.1
1
36.108
20
722
16.4
592
17.7
641
0.2
7.2
0.55
4.0
30.9
123
7.9
31
10.0
40
0.3
10.8
1
10.8
6
60
5.9
64
6.3
68
0.6
21.665
0.55
11.915
49.9
595
4.3
51
7.6
91
41.5
1500
20.4
738
23.2
839
76
75.60
101
0.6
64.0
1
63.981
20
1280
16.3
1041
17.6
1127
0.2
12.8
0.65
8.3
47.7
397
13.3
111
16.5
137
0.3
19.2
1
19.2
27
527
5.6
107
7.4
143
0.6
38.388
0.65
24.952
175.6
4382
6.9
172
18.7
467
102.9
6585
22.4
1431
29.3
1874
52
51.95
61
0.6
38.6
1
38.642
30
1159
19.2
741
21.2
819
0.1
3.9
0.65
2.5
63.7
160
22.4
56
26.7
67
0.2
7.7
1
7.7
31
242
11.0
85
13.1
101
0.6
23.185
0.65
15.070
274.9
4143
8.9
133
27.3
412
147.6
5704
26.3
1016
36.2
1400
16
15.52
32
0.6
20.3
1
20.271
40
811
23.7
481
26.4
535
0.1
2.0
0.65
1.3
88.2
116
38.2
50
44.1
SB
0.2
4.1
I
4.1
36
147
20.8
84
23.2
94
0.5
10.135
0.65
6.5881
468.9
3089
12.2
80
43.7
2BB
205.4
4164
34.3
696
48.1
976
5
5.21
20
0.6
12.7
1
12.669
50
633
30.9
392
34.3
434
0.1
1.3
0.75
1.0
139
132
69.2
66
78.5
75
0.2
2.5
1
2.5
47
119
34.1
86
37.3
94
0.5
6.3348
0.75
4.7511
706.4
3356
16.7
80
64.2
305
334.7
4241
49.2
623
71.7
908
3
2.85
3 24
0.6 0.5
1J 12.7
1 1
1.9004 12.669
50 75
95 950
38.8 53.0
74 672
42.2 58.1
80 736
0.1 0.05
0.2 0.6
0.75 0.75
0.1 0.5
218 587
31 279
116 313
17 149
130.7 352.5
1? 167
0.2 0.1
0.4 1.3
1 1
0.4 1.3
63 123
24 156
57.6 155.7
22 197
61.8 163.9
23 208
0.5 0.4
0.9502 5.0678
0.75 0.75
0.7126 3.8008
1152.5 3022.9
821 11490
24.7 5B.1
IB 221
102.1 261.3
73 993
511.2 1016.2
971 12875
66.3 97.B
130 1239
102.6 166.1
195 2104
0 1
0.35 1.37
4 1
0.5 0.5
2.1 0.5
1 1
2.1116 0.5279
100 100
211 S3
174.3 540.7
368 285
181.0 547.4
382 289
0.05 0.05
0.1 0.0
0.75 0.75
0.1 0.0
2100 6670
166 132
1130 3540
89 70
1271.2 3988.4
101 79
0.1 0.1
0.2 0.1
1 1
0.2 0.1
282 564
59 30
571.7 1807.4
121 95
590.6 1845.3
125 97
0.4 0.4
0.8446 0.2111
0.75 0.75
0.6334 0.15B3
3863.1 6182.9
2447 979
197.3 619.2
125 9B
457.0 1034.8
290 164
1365.8 2261.4
2884 1194
333.0 1039.9
703 549
424.8 1191.9
897 629
0 0
0.16 0.03
386
254
254
6524
5108
5546
£?
39
1971
7fl>
992
46
46
ICO
913
1009
122
94
32005
105B
3209
41930
7838
10657
B-3
-------
TABLE 6 — COMPLIANCE COSTS FOR SYSTEMS HAVING CONVENTIONAL TREATMENT KITH SOFTENING AND DUAL OR HULTI MEDIA FILTERS
POPULATION SIZE CATEGORY: 25-100 101-500501-1K 1-3.3K 3.3-IOK10-2SK 25-50K 50-75K 75-100K.1H-.5H .S-1H 1 MIL TOTALS
I SYSTEMS 5 4 13 37 59 42 33 17 8 13 3 1 235
I «/AVE. TURBIDITY > 0.3 O.B 0.7 0.4 0.4 0.6 0.4 0.6 0.4 0.6 0.5 0.5 0.5
I H/AVE. TURBIDITY > 0.3 4.2 3.0 8.2 23.4 37.4 26.6 20.9 10.8 5.1 6.9 1.6 0.5 149
I to IMPROVE OtH 1 1 1 1 1 1 I 1 1 1 1 1
I to IMPROVE OUI 4.2 3.0 8.2 23.4 37.4 26.6 20.9 10.8 5.1 6.9 1.6 0.5 149
DIAWOSTIC/initalUtion (t 000's) 5 10 10 20 20 30 40 SO 50 75 100 100
TOTAL CAPITAL COST (* 000's) 21 30 82 469 748 798 836 538 253 515 158 S3 4501
EXTRA Ott/initallation ($ OOO's/yr) 3.0 6.0 8.2 16.4 16.3 19.2 23.7 30.9 38.8 53.0 174.3 540.7
TOTAL EXTRA OIH « OOO's/yr) 13 18 68 384 608 510 496 333 197 364 276 2B5 3552
ANNUAL COST/iitftalUtion (t OOO's/yr) 3.3 6.7 8.9 17.7 17.6 21.2 26.4 34.3 42.2 58.1 181.0 547.4
TOTAL ANNUAL COST ($ OOO's/yr) 14 20 73 416 658 564 552 369 214 399 287 269 38S5
I NOut/RAPID Mil 0.6 0.6 0.6 0.2 0.2 0.1 0.1 0.1 0.1 0.05 0.05 0.05
I wxit/RAPID MIX 2.5 1.8 4.9 4.7 7.5 2.7 2.1 1.1 0.5 0.3 0.1 0.0 26
t to install RAPID MIX 0.55 0.55 0.55 0.55 0.65 0.65 0.65 0.75 0.75 0.75 0.75 0.75
I to install RAPID MIX 1.4 1.0 2.7 2.6 4.9 1.7 1.4 0.8 0.4 0.3 0.1 0.0 17
CAPITAL COST/installation (t 000's) 13.2 17.5 22.5 30.9 47.7 63.7 88.2 139 218 587 2100 6670
TOTAL CAPITAL COST (» OOO's) 18 17 61 80 232 110 120 112 83 151 125 132 1241
OM COST/initallation (t OOO's/yr) 2.8 2.9 7 7.9 13.3 22.4 38.2 69.2 116 313 1130 3540
TOTAL DIM COST (I OOO's/yr) 4 3 19 20 65 39 52 56 44 81 67 70 319
ANNUAL COST/installation ($ OOO's/yr) 3.7 4.1 8.5 10.0 16.5 26.7 44.1 78.5 130.7 352.5 1271.2 3988.4
TOTAL ANNUAL COST (»OOO's/yr) 5 4 23 26 80 46 60 63 50 91 75 79 603
J HOUt/pH ADJUSTMENT 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.05 0.05 0.05
t wwt/pH ADJUSTMENT 1.3 0.9 2.5 4.7 7.5 5.3 4.2 2.2 1.0 0.3 0.1 0.0 30
I to install pH ADJUSTMENT 111111111111
I to install pH ADJUSTMENT 1.3 0.9 2.5 4.7 7.5 5.3 4.2 2.2 1.0 0.3 0.1 0.0 30
CAPITAL COST/installation ($ OOO's) 3 3 4 6 27 31 36 47 63 123 282 564
TOTAL CAPITAL COST ($ OOO's) 3 3 9 26 205 166 152 101 64 42 22 15 809
OU COST/installation ($ OOO's/yr) 1.1 1.4 3.3 5.9 5.6 11.0 20.8 34.1 57.6 155.7 571.7 1807.4
TOTAL OH COST (* OOO's/yr) 1 1 8 28 42 59 87 73 SB 53 45 48 504
ANNUAL COST/installation (I OOO's/yr) 1.2 1.5 3.5 6.3 7.4 13.1 23.2 37.3 61.8 163.9 590.6 1845.3
TOTAL ANNUAL COST (* OOO's/yr) 2 1 9 29 56 70 97 80 63 56 47 49 558
I HOUt/POLYNER 0.6 0.6 0.6 0.5 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.3
I HOut/POLYHER 2.5 1.8 4.9 11.7 18.7 13.3 8.4 4.3 2.0 2.1 0.5 0.2 70
I to install POLYMER 0.75 0.75 0.75 0.75 0.85 0.85 0.85 0.85 0.95 0.95 0.95 0.95
I to install POLYMER 1.9 1.3 3.7 8.8 15.9 11.3 7.1 3.7 1.9 2.0 0.5 0.2 58
CAPITAL COST/installation (t OOO's) 12.1 15.2 18.5 23.8 92.8 105.8 133.3 159.7 209.7 438.9 1279.1 3598.9
TOTAL CAPITAL COST (t OOO's) 23 20 68 209 1474 1197 948 585 404 858 577 541 6905
QM COST/installation (I OOO's/yr) 1.6 1.7 4.0 4.3 6.9 8.9 12.2 16.7 24.7 58.1 197.3 619.2
TOTAL OM COST « OOO's/yr) 3 2 15 37 109 100 87 61 47 114 89 93 758
Ham rtnTMntt'11'""" (* OOO's/yr) 2.4 2.7 5.2 5.9 13.1 16.0 21.1 27.5 38.8 87.6 283.3 861.1
TOTAL ANNUAL COST « OOO's/yr) 5 4 19 52 209 181 150 101 75 171 128 130 1223
TABLE 6 TOTALS
CAPITAL COST/iMtallation (t OOO's) 15.6 23.5 26.8 33.4 71.1 85.4 98.3 124.1 158.7 228.2 557.4 1404.0
TOTAL CAPITAL COST ($ OOO's) 66 70 221 784 2658 2271 2056 1337 804 1566 883 741 13457
OM COST/inftallation (I OOO's/yr) 5.0 8.1 13.3 20.0 22.0 26.6 34.5 48.6 68.4 87.1 301.5 940.3
TOTAL OWI COST (I OOO's/yr) 21 24 109 470 824 708 721 524 347 612 477 496 5333
COST/installation (t OOO's/yr) 6.0 9.7 15.1 22.3 26.8 32.3 41.1 57.0 79.1 104.5 338.9 1034.6
TOTAL AUNUAL COST (I OOO's/yr) 25 29. 124 523 1003 861 860 613 401 717 537 546 6238
ANNUAL COST/Housihold (Is/yr) 127 41 61 85 50 17 8 3 1 1 0 0
CENTS/Thousand Gallons 126.57 41.37 60.60 84.75 50.04 17.18 8.26 3.46 1.30 0.84 0.17 0.05
B-4
-------
TABU 7 - COMPLIANCE COSTS FOR SYSTEMS HA VINS SRAVITY DIRECT FILTRATION KITH RAPID SAM FILTERS
POPULATION SIZE CATEGORY: 3-100 tOt-300301-U 1-3.3K 3.3-10HO-2K 23-50K 50-75K 75-100X.lH-.5lt .5-lN 1 NIL TOTALS
1 SYSTEMS
I i/AVE. TURBIDITY > O.I
1 «/AVE. TURBIDITY > 0.3
t to IMPROVE OU
1 to IMPROVE OU
DIASNQSTIC/initilUtiM (1 000 'il
TOTAL CAPITAL COST (t OOO'i)
EITRA OU/initallatiM (1 OOC'i/yr)
TOTAL EITRA OU (1 OOO'i/yr)
ANNUAL COST/initlllitiM (1 OOO'i/yrl
TOTAL ANNUAL COST (1 Wi/yr)
1 lout/ALIM OR FECL2
1 MUt/ALUIt OR FECL2
I to instill ALUM OR FECL2
1 to iniUll ALUM OR FECL2
CAPITAL COST/instillation It OOO'll
TOTAL CAPITAL COST (1 OOO'i)
OU COST/initallation (t OOO'j/yrl
TOTAL OIN COST (1 OOO'l/yrl
ANNUAL COST/inttilUtion If OM'i/yr)
TOTAL ANNUAL COST (t OOO'i/yrl
t WMt/RAPIl Nil
1 Mut/RAPID Nil
I ta irut.ll RAPID Mil
1 to imtall RAPID Nil
J7
0.8
30.7
1
M.i57
5
133
2.1
64
:.4
75
0.35
10.7
1
10.7
12.2
130.?
2.3
24.7
3.1
13
O.B
24. 5
0.55
13.5
13
O.I
10. S
1
10.771
10
101
4.2
IS
4.1
52
0.35
3.8
1
3.8
15.9
59.9
2.4
1.8
3.7
14
0.8
8.6
o.ss
4.7
12
0.8
9.9
1
9.9430
10
99
5.6
54
4.3
62
0.35
3.2
1
3.5
20.3
70.4
5.4
18.8
4.8
24
0.8
8.0
0.55
4.4
11
0.7
7.8
1
7.8124
20
154
11.0
84
12.4
97
0.3
2.3
1
7.3
28
45.4
7.7
18.0
9.6
22
0.7
5.5
0.55
3.0
13
0.7
9.2
1
9.232B
20
183
12.1
112
13.4
124
0.3
2.8
I
2.8
40.7
112.7
4.1
11.4
4.8
19
0.7
4.S
0.45
4.2
4
0.7
7.8
I
2.8408
30
85
14.8
42
16.9
48
0.2
0.6
1
0.4
47.1
26.8
7.9
4.5
11.1
4
0.4
1.7
0.45
1.1
4
0.7
7.8
1
2.8408
40
114
18.9
54
21.4
41
0.1
0.3
1
0.3
58.1
16.5
14.9
4.2
18.8
5
0.6
1.7
0.65
1.1
1
0.7
0.7
1
0.7102
SO
36
23.9
17
27.2
19
0.05
0.0
1
0.0
70.4
2.5
24.4
0.9
29.1
1
0.5
0.4
0.75
0.3
2
0.7
1.4
I
1.4204
50
71
26.3
37
29.6
42
0.05
0.1
t
0.1
81.6
5.8
41.3
2.9
46.8
3
O.J
0.7
0.75
0.5
0
0.6
0.0
1
0
75
0
38.4
0
43.5
0
0.03
0.0
1
0.0
128
0.0
112
0.0
120.6
0
0.4
0.0
0.75
0.0
1
0.6
0.6
1
0.5918
100
39
116.7
69
123.4
73
0.05
0.0
1
0.0
250
7.4
402
U.9
418.8
12
0.4
0.2
0.75
0.2
0
0.6
0.0
1
0
100
0
357.9
0
364.7
0
0.05
0.0
1
0.0
575
0.0
1245
0.0
1283.7
0
0.4
0.0
0.75
0.0
98
77
77
1066
582
654
24
24
499
107
141
58
33
luTSi CAPITAL COST (t OOO'i) 178 S3 98 93 200 71 98 37 116 0 373
0 1347
OU COST/iMtallition (I OOO'i/yrl 2.1 2.9 7 7.9 13.3 22.4 38.2 69.2 116 313 1130 3540
TOTAL OU COST (I OOO'i/yr) 38 14 31 24 56 25 42 18 62
0 201
0 510
ANNUAL COST/infUllition (t OOO'i/yr) 3.7 4.1 8.5 10.0 16.5 26.7 44.1 78.5 130.7 352.51271.23988.4
TOTAL ANNUAL COST II OOO's/yrl SO
19 37 30 69 30 49
21 70
224
600
t wut/pH ADJUSTMENT
1 MUt/pH ADJUSTMENT
S to instill pM ADJUSTMENT
t to instill pH ADJUSTMENT
CAPITAL COST/insUlUtion (t OOO'i)
TOTAL CAPITAL COST (1 OOO'll
OU CDST/iniUllitiofi II OOO's/yrl
TOTAL OU COST (f OOO's/yrl
ANNUAL COST/instlllition It OOO'i/yr)
TOTAL ANNUAL COST It OOO'i/yr)
S Mut/aOC t CONTACT CHAMBER
1 Mut/aOC t CONTACT CHAMBER
t to instill FLOC i CONTACT
1 to instill ROC I CONTACT
CAPITAL COST/installation (t OOO'il
TOTAL CAPITAL COST (t OOO'sl
OU CDST/instillitiM (t OOO'i/yr)
TOTAL OU COST It OOO's/yrl
ANNUAL COST/ittitillitioR II OOO's/yrl
TOTAL ANNUAL COST II OOO's/yrl
I NUt/POLYMER
1 Mut/POLYHER
I to instill POLYMER
• to install POLYKER
CAPITAL COST/instillitin II OOO'sl
TOTAL CAPITAL COST II OOO'll
OU COSmnsttlUtion It OOO's/yrl
TOTAL OU COST It OOO's/yr)
ANNUAL COST/initillition It OOO's/yrl
TOTAL ANNUAL COST II OOO's/yr)
TABLE 7 TOTALS
CAPITAL COST/initlllition It OOO'sl
TOTAL CAPITAL COST (t OOO'i)
OU COST/installatloa II OOO's/yr)
TOTAL OU COST It OOO's/yrl
ANNUAL COST/instillition (1 OM's/yrl
TOTAL ANNUAL COST (t OOO'i/yr)
ANNUAL CDST/Houtihold IH/yr)
CENTS/Tnwsui- Billons
O.f
0.75
20.7
3
54
1.1
22
1.2
25
O.I
24.5
0.55
13.5
16.5
223
1
13
2.1
28
0.6
18.4
0.55
10.1
15.9
161
1.6
16
2.7
27
29.3
900
5.8
178
7.1
239
164
164.01
0.9
0.75
7.3
3
21
1.4
10
1.5
11
O.I
1.6
0.55
4.7
33.2
157
1.1
S
3.3
16
0.4
6.S
0.55
3.6
22.9
82
1.7
6
3.2
12
47.4
511
8.3
90
11.5
124
25
24.66
0.75
6.7
4
24
3.3
22
3.3
23
0.8
B.O
0.55
4.4
58.3
255
2.3
10
4.2
27
0.4
6.0
0.55
3.3
32.0
105
4.0
13
6.1
20
65.7
653
15.1
150
' 19.5
194
13
13.03
6.2
0.75
4.7
6
24
5.9
28
4.3
29
0.75
5.9
0.55
3.2
117.3
378
2.7
9
10.4
34
0.5
3.9
0.55
2.1
49.9
107
4.3
9
7.4
14
105.7
124
2.2
173
29.3
229
5
5.11
7.4
0.85
4.3
27
172
3.6
35
7.4
47
0.75
6.9
0.43
4.5
362
1629
3.8
17
28.1
127
0.5
4.6
0.65
3.0
175.6
527
6.9
21
18.7
56
306.1
2826
27.3
252
47.9
442
3
3.04
0.85
1.7
31
53
11.0
19
13.1
22
0.65
1.8
0.63
1.2
584.6
702
5.6
7
44.9
54
O.S
1.4
0.65
0.
274.
25
8.
27.
25
419.2
1191
36.9
105
65.1
IBS
1
0.51
0.7
2.0
0.85
1.7
36
41
20.8
35
23.2
39
0.65
1.1
0.65
1.2
789.8
948
8.7
10
61.8
74
0.5
1.4
0.63
0.9
461.9
433
12.2
11
43.7
40
587.9
1670
55.3
157
94.B
269
0
0.36
0.6
0.63
0.4
47
17
34.1
12
37.3
13
0.65
0.5
0.65
0.3
1138.9
342
14.3
4
91.1
27
O.S
0.4
0.75
0.3
706.4
188
16.7
4
64.2
17
875.8
422
80.8
57
139.7
99
0
0.08
0.4 O.S
0.95 0.95
O.B 0.0
63 123
31 0
57.6 155.7
47 0
41. B 143.9
54 0
0.63 0.6
0.9 0.0
0.73 0.7S
0.7 0.0
1636.1 3422
1133 0
22.9 53.9
16 0
132.9 283.9
92 0
0.9 0.4
0.7 0.0
0.73 0.73
0.5 0.0
1152.3 3022.9
614 0
24.7 51.1
13 0
102.1 261.3
54 0
1401.6 EM
1991 0
125.0 EM
171 0
219.2 ERR
311 0
0 0
O.lt 0.00
0.5 0.5
0.95 0.95
0.3 0.0
282 564
79 0
571.7 1807.4
141 0
590.6 1845.3
166 0
0.6 0.6
0.4 0.0
0.75 0.73
0.3 0.0
11859 30470
31SB 0
182 549
48 0
979.2 2417.2
241 0
0.4 0.4
0.2 0.0
0.75 0.75
0.2 0.0
3863.1 4112.9
484 0
197.3 419.2
33 0
457.0 1034.8
81 0
7372 EM
4343 0
888.4 EM
526 0
1384.0 EM
819 0
0 0
0.04 0.00
63
SO
560
390
427
59
34
8923
140
740
43
25
3156
137
349
15553
1866
2912
B-5
-------
TABU 8 ~ COMPLIANCE COSTS FOR SYSTEMS HAVINS GRAVITY DIRECT FILTRATION KITH DUAL OX MULTI-MEDIA FILTERS
POPULATION SIZE CATEBORY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-73! 7S-100K.1H-.5H .MM 1 MIL TOTALS
1 SYSTEMS
I «/AVE. TURBIDITY > 0 1
1 i/AVE. TURBIDITY > 0 1
I to IHPMVE DM
1 to IVROVE OU
DIAENOSTIC/tnitlllitiM l» 000' I)
TOTAL CAPITAL COST (1 000' I)
EITRA OU/intUUition (1 OOO't/yr)
TOTAL EITRA OUI (1 OOO'l/yr)
ANNUAL COST/initllUtion (1 OOO'i/yr)
TOTAL ANNUAL COST (1 OOO'l/yr)
4
1
3.0774
5
15
2.1
4
2.4
7
9
1
4.9244
10
a
4.2
29
4.9
34
5
1
3.8470
10
38
5.4
22
4.3
24
7
1
4.5572
20
11
11.0
50
12.4
Si
14
0.7
1
9.1144
20
182
12.1
110
13.4
123
4
0.7
1
2.6041
30
78
14.8
39
14.9
44
2
0.7
1
1.3020
40
52
1B.9
25
21.4
28
2
0.7
1
1.3020
SO
45
23.9
31
27.2
35
4
0.7
1
2.4041
50
130
24.3
48
29.6
77
5
0.5
2.7
1
2.6633
75
200
3B.4
102
43.5
116
2
0.5
1
1.0453
100
107
116.7
124
123.4
131
1
05
(1 5
1
0.5324
100
53
357.9
191
364.7
194
59
40
40
1082
798
870
S •out/ALUII OR FECL2 0.35 0.35 0.35 0.2 0.2 0.1 0.1 0.05 0.05 0.05 O.D5 O.OS
1 »out /ALUH OR FECL2
1 to UlUll ALUH OR FECL2
1 to instill ALUH OR FECL2
CAPITAL COST/iniUllition (1 OOO'D
TOTAL CAPITAL COST (1 OOO'tl
OUI COST/intUllition It OOO'l/yr)
TOTAL OU COST (t OOO'i/yrl
ANNUAL COST/initlllition (t OOO'l/yr)
TOTAL ANNUAL COST (1 OOO'l/yr)
t tout/ RAPID HII
1 MUt/RAPID Nil
t to initlll RAPID HII
1 to imtill RAPID HII
CAPITAL COST/initillition (I OOO'll
TOTAL CAPITAL COST (1 OOO'D
OM COST/iniUlUtion II OOO'i/yrl
TOTAL OU COST (t OOO'l/yr)
ANNUAL COST/iniUlUtion 11 OOO'i/yrl
TOTAL ANNUAL COST II OOO'i/yrl
t MUt/pH ADJUSTMENT
1 MMt/pM ADJUSTMENT
1 to imtill pH ADJUSTMENT
1 to initlll pH ADJUSTMENT
CAPITAL CQST/initilUtion It OOO'D
TOTAL CAPITAL COST It OOO'll
OU COST/initilUtion (1 OOO'i/yrl
TOTAL OU COST (t OOO'i/yrl
ANNUAL COST/iniUlUtion (1 OOO'i/yrl
TOTAL ANNUAL COST (t OOO'l/yr)
1 Mut/FLOC t CONTACT CHAMBER
1 Mut/FLOC I CONTACT CHAMBER
1 to intill FLOC t CONTACT
t to imtill FLOC 1 CONTACT
CAPITAL CDST/UtttUition II OOO'D
TOTAL CAPITAL COST It OOO'D
OU COST/imtilUtiM It OOO'l/yr)
TOTAL OU COST It OOO'l/yr)
ANNUAL COST/iniUllition II OOO'l/yr)
TOTAL ANNUAL COST It OOO'l/yr)
j Mut/potma
1 wut/POLYHER
t to initlll POLYMER
1 to iniUll POLYMER
CAPITAL COST/inittlUtion II OOO'D
TOTAL CAPITAL COST (t OOO'D
OM COST/initilUtion It OOO'i/yrl
TOTAL OU COST It OOO'l/yr)
ANNUAL COST/iniUUition II OOO't/yr)
TOTAL ANNUAL COST It OOO'l/yr)
1
1 t
12.2
13.1
2.3
2 1
3.1
3
1.4
0.55
13.2
10
2.B
2
3.7
3
0.75
3
3
1.1
I
1.2
2
0.4
l.B
0.55
1.0
14.5
17
1
I
2.1
2
0.45
1.4
0.75
1.0
12.1
13
1.4
2
2.4
3
1
2.4
15.9
38.5
2.4
6.3
3.7
9
3.1
0.55
17.5
30
2.9
5
4.1
7
0.75
3
8
1.4
4
1.5
4
0.6
4.2
0.55
2.3
33.2
74
1.1
3
3.3
8
0.45
3.1
0.75
2.3
15.2
34
1.7
4
2.7
4
1
1.3
20.3
27.3
5.4
7.3
6.B
9
1.7
o.ss
22.5
21
7
7
8.5
8
0.75
4
6
3.3
5
3.5
6
0.6
2.3
0.55
1.3
58.3
74
2.3
3
4.2
B
0.45
1.7
0.75
1.3
18.5
24
4.0
S
3.2
7
1
0.9
28
25.5
7.7
7.0
9.4
9
1.8
0.25
30.9
31
7.9
B
10.0
10
0.75
6
9
5.9
10
6.3
11
O.SS
2.S
0.55
1.4
117.3
142
2.7
4
10.6
IS
0.35
1.4
0.75
1.2
23. B
28
4.3
5
3.9
7
1
1.8
40.7
74.2
4.1
7.5
4.8
12
3.4
0.65
47.7
113
13.3
32
16.5
39
0.85
27
106
S.6
22
7.4
27
O.SS
S.O
0.45
3.3
362
1180
3.8
12
28.1
92
0.35
3.2
0.85
2.7
92.8
2S2
6.9
19
13.1
34
1
0.3
47.1
12.3
7.9
2.1
11.1
3
0.3
0.8
0.65
63.7
32
22.4
11
26.7
14
0.85
31
28
11.0
10
13.1
12
0.5
1.3
0.65
0.8
584.6
495
5.6
S
44.9
38
0.25
0.7
O.SS
0.6
105.8
59
8.9
5
16.0
9
fl.
SB.
7.
14.
1.
18.8
2
0.3
0.4
0.65
8B.2
22
38.2
10
44.1
11
0.85
36
16
20.8
9
23.2
10
0.5
0.7
0.65
0.4
789.8
334
8.7
4
61.9
24
0.25
0.3
0.85
0.3
133.3
37
12.2
3
21.1
4
0.
70.
4.
24.
1.
29.
2
0.2
0.3
0.75
139
27
49.2
14
76.5
IS
0.85
47
16
34.1
11
37.3
12
0.5
0.7
0.65
0.4
1138.9
482
14.5
6
91.1
39
0.15
0.2
0.8S
0.2
159.7
27
16.7
3
27.5
5
1 1
0.1 0.1
81.6 128
10.6 17.0
41.3 112
3.4 14.9
46.8 120.6
6 16
0.5 0.3
0.75 0.75
21B 587
85 117
116 313
45 63
130.7 352.S
SI 70
0.9S 0.95
0.7 0.3
63 123
47 31
57.6 155.7
43 39
61.8 143.9
44 41
O.S 0.35
1.3 0.9
0.73 0.75
1.0 0.7
1636.1 3422
1591 2392
22.9 53.9
22 38
132.1 283.9
130 198
0.1S 0.1S
0.4 0.4
0.95 0.9S
0.4 0.4
209.7 438.9
78 167
24.7 58.1
9 22
38.8 87.4
14 33
0.1 0.0
I 1
0.1 0.0
250 575
13.3 15.3
402 1245
21.4 33.2
418.8 12B3.7
22 34
0.1 0.1
0.73 0.75
2100 6670
148 266
1130 3540
90 141
1271.2 39B8.4
102 159
0.1 0.1
0.1 0.1
0.95 0.95
0.1 0.1
282 564
29 29
571.7 1807.4
58 91
590.6 1845.3
60 93
0.35 0.35
0.4 0.2
0.75 0.75
0.3 0.1
11859 30470
3316 4260
182 569
51 80
979.2 2617.2
274 364
0.1S 0.15
0.2 0.1
0.95 0.95
0.2 0.1
1279.1 3598.9
194 273
197.3 619.2
30 47
283.3 861.1
43 45
B
8
259
111
128
14
8
924
427
489
18
14
328
304
326
21
13
14386
228
1195
13
11
1186
154
234
TABLE 8 TOTALS
CAPITAL COST/inttllUtion II OOO'D
TOTAL CAPITAL COST (t OOO'll
OU COST/initillition (t 000't/yr)
TOTAL OU COST It OOO'i/yr)
ANNUAL COST/initillltion II OOO'l/yr)
TOTAL ANNUAL COST It OOO'l/yr)
ANNUAL COST/Houutold (li/yr)
23.1
71
4.9
15
6.5
20
136
16.06
37.2
258
7.3
51
9.8'
68
135
134.35
49.6
191
12.7
49
14.0
62
41
41.22
74.2
347
1B.4
84
23.6
107
24
23.90
209.2
1907
22.2
202
36.2
330
23
22.61
270.2
704
27.4
71
43.6
119
3
3.23
360.4
469
40.3
53
64.6
84
1
1.11
476.9
621
51.0
66
83.1
108
1
0.64
74B.2 1097.9
1948
74.2
193
124.5
324
I
1.44
2924
104.7
279
178.5
475
1
0.76
3592
3827
3S1.B
375
593.2
632
0
0.27
9194
4897 18143
1095.0
583 2021
1713.0
912 3242
0
0.12
B-6
-------
.t i TABLE 9 - COMPLIANCE COSTS FOR SYSTEMS HAVING SLON SAND FILTERS
POPULATION SIZE CATE60RY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-7SK 75-100K.1H-.5H .5-1H 1 «L TDTAl
I SYSTEMS 23 10 11 9 11 2 1 00200*
S to IMPROVE Otn
I to IMPROVE OtH
'HAf . DIAGNOSTIC/installation (« OOO's)
TOTAL CAPITAL COST (« OOO's)
IRA EXTRA OlH/installation ($ OOO's/yr)
TOTAL EITRA OM ($ OOO's/yr)
ANNUAL COST/installation ($ OOO's/yr)
TOTAL ANNUAL COST (* OOO's/yr)
ANNUAL COST/Household ($s/yr)
1
23.0
S
115
0.2
6
0.6
13
12
1
10.0
10
100
0.5
5
1.2
12
3
1
11.0
10
110
1.0
11
1.7
19
2
1
9.0
20
180
1.8
16
3.1
28
1
I
11.0
20
220
2.1
23
3.4
37
0
1
2.0
30
60
2.7
5
4.7
9
0
1
1.0
40
40
3.1
3
5.8
6
0
0
0.0
50
0
0.0
0
3.4
0
0
0
0.0
50
0
0.0
0
3.4
0
0
0
0.0
75
0
0.0
0
5.0
0
0
0
0.0
100
0
0.0
0
6.7
0
0
0
0,0
100
0
0.0
0
6.7
0
0
i
B;
CENTS/Thousand Gallons 12.14 3.05 1.67 O.B4 0.34 0.03 0.01 0.00 0.00 0.00 0.00 0.00
B-7
-------
TABLE 10 - COMPLIANCE COSTS FOR SYSTEHS HAVING DIATOHACEOUS EARTH FILTERS
POPULATION SHE CATEGORY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-75K 75-100K.lfl-.5H .5-1H 1 NIL TOTALS
I SYSTEHS 4 14 12 11 18 3 0 2 1 2 0 0 67
1 to IMPROVE OtH 1 1 1 1 1 1 1 1 I 1 00
I to IMPROVE OtH 4.0 14.0 12.0 11.0 1B.O 3.0 0.0 2.0 1.0 2.0 0.0 0.0 6?
DIAGNOSTIC/instalUtion « OOO's) 5 10 10 20 20 30 40 50 50 75 100 100
TOTAL CAPITAL COST (f OOO's) 20 140 120 220 360 90 0 100 50 150 0 0 125°
EITRA OWI/installation ($ OOO's/yr) 1.9 2.7 4.B 7.3 13.7 19.7 24.7 30.6 35.1 55.1 O.O 0.0
TOTAL EXTRA OiH (« OOO's/yr) 8 38 SB 80 247 59 0 61 35 110 0 0 6™
ANNUAL COST/installation ($ OOO's/yr) 2.2 3.4 5.5 8.6 15.0 21.8 27.3 34.0 38.5 60.2 6.7 6.7
TOTAL ANNUAL COST (» OOO's/yr) 9 47 66 95 271 65 0 68 38 120 0 0 'BO
ANNUAL COST/Household (Is/yr) 47 72 34 16 14 1 0 0 0 0 0 0
CENTS/Thousand Gallons 46.91 71.86 33.94 16.24 14.27 1.38 0.00 0.40 0.13 0.1S 0.00 0.00
B-8
-------
TABLE 11 ~ COMPLIANCE COSTS FOR SYSTEHS HAVIN6 PRESSURE FILTERS
POPULATION SIZE CATEBORY: 25-100 101-500501-lK 1-3.3K 3.3-10K10-25K 25-50K 50-75K 75-100K.1IK5H .5-lH 1 NIL TOTALS
t SYSTEMS 228 185 39 40 38 25 4 0 4 2 0 0 565
I to IMPROVE OIH 1 1 1 1 1 1 1 1 1 1 0 0
I to IMPROVE DM 228,0 1B5.0 39.0 40.0 38.0 25.0 4.0 0.0 4.0 2.0 0.0 0.0 545
DIASNOSTIC/instailation <$ OOO's) 5 10 10 20 20 30 40 50 50 75 100 100
TOTAL CAPITAL COST It OOO's) 1140 1850 390 800 760 750 160 0 200 150 0 0 6200
EXTRA OM/installation ($ OOO's/yr) 7.5 10.5 9.6 12.2 13.1 14.9 18.5 23.4 25.6 37.0 0.0 0.0
TOTAL EXTRA DM (t OOO's/yr) 1710 1943 374 4B6 498 373 74 0 102 74 0 0 5633
ANNUAL COST/instilUtion (t OOO's/yr) 7.8 11.2 10.3 13.5 14.4 16.9 21.1 26.8 29.0 42.1 6.7 6.7
TOTAL ANNUAL COST ($ OOO's/yr) 1787 2067 400 540 549 423 85 0 116 84 0 0 6050
I to install RAPID HIX O.S5 0.55 0.55 0.55 0.65 0.65 0.65 0.75 0.75 0.75 0.75 0.75
* to install RAPID HIX 125.4 101.8 21.5 22.0 24.7 16.3 2.6 0.0 3.0 1.5 0.0 0.0 319
CAPITAL COST/installation (I OOO's) 13.2 17.5 22.5 30.9 47.7 63.7 88.2 139 218 587 2100 6670
TOTAL CAPITAL COST ($ OOO's) 165S 1781 483 680 1178 1035 229 0 654 881 0 0 B575
OiH COST/installation (S OOO's/yr) 2.8 2.9 7 7.9 13.3 22.4 38.2 69.2 116 313 1130 3540
TOTAL OM COST (f OOO's/yr) 351 295 150 174 329 364 99 0 348 470 0 0 2579
ANNUAL COST/installation (» OOO's/yr) 3.7 4.1 8.5 10.0 16.5 26.7 44.1 78.5 130.7 352.5 1271.2 3988.4
TOTAL ANNUAL COST (S OOO's/yr) 462 415 163 219 408 434 115 0 392 529 0 0 3156
S to install FLOC I CONTACT 0.55 0.55 0.55 0.55 0.65 0.65 0.65 0.65 0.75 0.75 0.75 0.75
t to install FLOC i CONTACT 125.4 101.8 21.5 22.0 24.7 16.3 2.6 0.0 3.0 1.5 0.0 0.0 319
CAPITAL COST/installation (» OOO's) 16.5 33.2 58.3 117.3 362 584.6 789.8 1138.9 1636.1 3422 11859 30470
TOTAL CAPITAL COST (t OOO's) 2069 337B 1251 25B1 B941 9500 2053 0 4908 5133 0 0 39814
OUI COST/installation ($ OOO's/yr) 1 1.1 2.3 2.7 3.8 5.6 8.7 14.5 22.9 53.9 182 569
TOTAL DM COST ($ OOO's/yr) 125 112 49 59 94 91 23 0 69 81 0 0 703
ANNUAL COST/installation (* OOO's/yr) 2.1 3.3 6.2 10.6 28.1 44.9 61.8 91.1 132.9 283.9 979.2 2617.2
TOTAL ANNUAL COST (« OOO's/yr) 264 339 133 233 695 730 161 0 399 426 0 0 3379
S to install POLYHER 0.55 0.55 0.55 0.55 0.65 0.65 0.65 0.75 0.75 0.75 0.75 0.75
t to install POLYHER 125.4 101.8 21.5 22.0 24.7 16.3 2.6 0.0 3.0 1.5 0.0 0.0 319
CAPITAL COST/installation (I OOO's) 15.9 22.9 32.0 49.9 175.6 274.9 468.9 706.41152.53022.93863.16182.9
TOTAL CAPITAL COST (S OOO's) 1995 2335 665 1098 4337 4467 1219 0 3458 4534 0 0 24129
OH COST/installation (I OOO's/yr) 1.6 1.7 4.0 4.3 6.9 8.9 12.2 16.7 24.7 58.1 197.3 619.2
TOTAL OiH COST (» OOO's/yr) 200 173 86 94 170 144 32 0 74 87 0 0 1060
ANNUAL COST/installation (S OOO's/yr) 2.7 3.2 6.1 7.6 18.7 27.3 43.7 64.2 102.1 261.3 457.C 1034.8
TOTAL ANNUAL COST « OOO's/yr) 334 330 132 168 462 444 114 0 306 392 0 0 2682
TABLE 11 TOTALS
CAPITAL COST/installation ($ OOO's) 30.1 50.5 72.0 129.0 400.4 630.1 915.5 ERR 2305.0 5348.9 ERR ERR
TOTAL CAPITAL COST (» OOO's) 6859 9344 2809 5158 15217 15752 3662 0 9220 10698 0 0 78719
OU1 COST/installation (s OOO's/yr) 10.5 13.6 16.9 20.3 28.7 38.9 56.9 ERR 148.3 355.7 ERR ERR
TOTAL OIH COST ($ OOO's/yr) 2387 2522 659 813 1090 972 227 0 593 711 0 0 9975
ANNUAL COST/installation ($ OOO's/yr) 12.5 17.0 21.7 29.0 55.6 81.2 118.4 ERR 303.2 715.3 ERR ERR
TOTAL ANNUAL COST (t OOO's/yr) 2848 3150 848 1160 2113 2031 474 0 1213 1431 0 0 15267
ANNUAL COST/Housihold (Sl/yr) 263 84 8321000000
CENTS/Thousand Gallons 263.25 84.12 7.66 3.49 1.95 0.75 0.08 0.00 0.07 0.03 0.00 0.00
B-9
-------
TABLE 12 — SUMMARY OF COMPLIANCE COSTS FOR SURFACE HATER SYSTEMS
POPULATION SIZE CATEGORY: 25-100 101-500501-1K 1-3.3K 3.3-10K10-25K 25-50K 50-75K 75-100K.1M-.5H .5-1H 1
FILTERED SYSTEMS - TABLES 3 TO 11
t SYSTEMS
t SYSTEMS AFFECTED
CAPITAL COST/installation (t 000 'si
TOTAL CAPITAL COST (t OOO's)
OUI COST/installation (t OOO's/yr)
TOTAL OUI COST (t OOO's/yr)
ANNUAL COST/installation ($ OOO's/yr)
TOTAL ANNUAL COST (t OOO's/yr)
ANNUAL COST/Housthold <«s/yr)
CENTS/Thousand Gallons
523
475.3
22.1
10520
7.2
3402
8.6
4109
182
182.20
474
397.0
35.5
14107
10.0
3980
12.4
4928
63
63.13
537
390.7
31.2
12188
11.9
4664
14.0
5483
24
23.77
814
516.5
46.2
23859
19.4
10017
22.5
11621
17
16.75
996
629.8
111.4
70190
21.8
13720
29.3
18439
8
8.18
504
311.6
163.2
50853
27.2
8463
38.1
11882
2
2.11
303
183.1
182.3
33390
34.9
6385
47.1
8629
1
0.74
144
82.1
252.6
20746
47.0
3857
63.9
5251
0
0.26
98
57.0
536.8
30576
72.7
4139
108.8
6195
0
0.18
166
78.0
761.9
59450
90.1
7032
141.3
11028
0
0.11
40
18.0
1361.6
24538
315.1
5679
406.6
7329
0
0.02
TOTALS
12
5.4
3145
2632
14184 364602
975.2
5256 76594.
1152.2
6209 101103
0
0.01
B-10
-------
APPENDIX C
SPREADSHEET MODELS FOR COMPUTING COSTS
OF MONITORING FOR THE
SURFACE WATER TREATMENT RULE
-------
DM Mia CHIFOM MMITMIN CMTt
OTOTEHO OITMIIM M EICEHIOH
O
i autumn (MTER IYIIEM
1 HIE
i uiEOMia
1 29-100
1 101-900
1 901-1000
1 1WI-1WO
1 3WI-IOK
1 10K-29I
I29K-9K
1 90K-79K
1 79K-100K
1 > 100K
I
1 TD1M.I
1
1 HOR-OMMHin
1 HIE
1 UTEOORIU
1 23-100
1 101-900
1 1001-3100
1 1UI-IOK
1 IM-2X
1 29X-90K
1 90K-TX
1 79K-IOOK
1 > tOM
1 TOIM.I
WRIER OF
lYOTEHI
,••••••••
24.)
47.7
41.4
93.9
44.0
21.4
9i?
4.4
241
HNHOURt
/MMLTIII
• ••-•••M*
0.1413
0.1413
0.1413
0.1413
0.1413
0.1413
0.1413
0.1401
0.1411
0.1401
FREOUERCT UIQR
rttna fa
**»••••••• •••••
1
2
2
4
5
3
TOTM.
TOIM.
NOUtO LUM HOURS LMM HOUM
MEEK
0.1?
O.I?
0.34
0.34
0.90
0.47
0.04
0.04
0.14
0.04
•••••••
MTER SYSTEM
(RMEROF
oniEM
O4.f
Of.O
12.2
1.7
2.4
0.0
0.0
0.0
0.0
0.0
Iff
/MMLYOII
0.1411
fclffi
0.141)
0.1411
0.141)
0.1411
O.I4D
0.141)
0.1411
FREQUENCY LUOR
PERVEEK PEI
.
2
1
4
9
9
9
9
HOURS
MEEK
O.I?
0*.34
0.90
0.4?
0.04
0.04
0.04
0.04
raiYSTEi
••••••••••
1.79
0.79
17.90
17.90
24.29
39.01
43.74
43.74
43.74
43.74
* OMMMM •••
TOTM.
UMRNOURI
PER MITER
Tra
0.79
17.90
17.90
24.29
13.01
41.74
41.74
41.74
41.74
PER YEM
•••••*•••
213
417
740
114
1,204
Olf
114
290
111
241
9,431
•••••••••••M
TOTM.
LAIN HOURS
PEITEMI
741
?7f
214
19)
42
0
0
0
0
0
i,no
IOTM. MOI.
MOT pa
IMIER
•••••••••
41,900
1,900
3,000
3000
4,900
4,000
3,100
3100
3,100
3,100
»»•«••* •••••«
IOTM. MM.
COST MR
ITITER
01,900
1900
1,000
3,000
4,900
4,000
),IOO
3,100
1,100
1,100
1
TOTM. 1
CM! PER 1
TEW 1
mmmmmmm |
034,490 t
71,990 I
130 200 1
140 440 1
204,7791
140,400 1
2? 100 1
17 711 1
11 440 1
10,400 I
1
4023,40? 1
TOIM. 1
COST PER 1
TEW 1
0110,190 1
113 900 1
14 400 1
24 140 1
10,420 1
1
1
1
1
1
1117,210 1
.....U..U.I
I Ml MTER ITHEtt OIHIRIM M EICEPTIOR
I HIE MIHER OF LMM HOUM COST PER
I C4TESMIEI OIBIEItt PER YEM YEM
1 29-100
! 101-900
1 901-1000
1 I04I-1WO
1 3301-IOK
1 IOK-29K
1 29X-90X
1 90K-79X
1 T3K-IOOK
1 >IOOX
! TOTM.I
| ••••*••«••••*••••
111.2
114.7
99.4
42.2
40.1
23.4
1.0
9.7
4.4
4.0
441
171
1,114
173
i,on
1 240
lit
314
290
111
243
7,411
!•••••*•••
1144,000
209090
144000
104,400
217,319
140400
27100
17712
11440
11,400
41,140,117
••••••••••••
MTEl Caiti lir mttii iir«ln| Itti thu 23,000 »KI«II aiwu* ualyil* yirlortii
Coiti to ifitm itrvlio •«• tkM 29,000 pwioul itiuHt Mtlrtli »»r(
kf « irlwti .
ky **W utility »*IMM!
-------
MM VAia TUtllim MMIIMIM COSTI
UriLTOKI SYSTEM OITA1NIM EICEPT10M
1 COMMITT MTU SYSTEM
1
1
i SIZE
1 CATESORia
1 23-100
1 101-300
1 901-1000
1 1001-3300
1 3301-10*
1 10X-23K
1 23K-30K
1 90K-73K
I79K-IOOK
1 >IOOK
1 TOTALi
\tmmmmmmmmmmmtmt
1 ROM-COlMMITy
1
(SIZE
1 CATEOORIEI
1 2SMOO
1 101-900
1 301-1000
1 1001-3300
1 3301-IOX
1 IOK-23K
1 2X-90K
1 30K-73K
1 7X-IOOK
1 >IOOK
1 TOTALi
UPM tan rw MUM
IAMR HOUM LAMR HOUM
NUKKR OF /CALIBMTIOR /AMLYS1S
SYSTEM II/SAYI ISAHPLIM)
24.3 0.0833 0.0147
47.7 0.0833 0.0147
43.4 0.0033 0.0147
31.9 0.0033 0.0147
44.0 0.0033 0.0147
21.4 0.0031 0.0147
t.O 0.0833 0.0147
3.7 0.0833 0.0147
4.4 0.0033 0.0147
4.0 0.0033 0.0147
243
NATO SYSTEM
SAMPLIRS LAMR HOUM TOTAL LASOR COST
FREQUENCY LABOR HOUM PEI YEM LAMM HOUM PU SYSTEM
PO OAT Pa SAY Pa SYSTEM PER YEM PEI YEM
.17
.17
.17
.17
.17
.17
.17
.17
0.17
0.17
40.08 1,47* (424
40.00 2*04 424
40.08 2 442 424
44.08 3294 424
40.00 27*8 424
40.88 1 421 424
40.80 348 424
40.M 348 424
40.80 240 424
40.10 343 424
14,033
TOTAL
LASOR COOT
pa YEM
(10,334
20,320
184*4
227*2
1*903
»*72
3034
2431
1071
2,337
(112,233
CAPITAL
COST pa
SYSTEM
(2,000
2000
2000
2,000
2,000
2,000
0
0
0
AMNUALIZa
CAPITAL
CMT/IVIT
0437
437
437
437
437
437
0
0
LAMM COSI PER HUUKI
LAMM HOUM LAMNI HOUM
MMSa OF /CALISMTION /ANALYSIS
SYSTEM (I/SAY! ISAHPLIMI
OU 0.0033 9.t\tt
81.0 0.0833 0.0147
12.2 0.0033 0.0147
1.7 0.0033 0.0147
2.4 0.0033 0.0147
0.0 0.0033 0.0147
0.0 0.0033 0.0147
0.0 0.0033 0.0147
0.0 0.0033 0.0147
0.0 0.0033 0.0147
Iff
SANPLIM
FREQUENCY
KR NT
LAMM HOUM TOTAL IAMR COSI
LAMR HOUM Pa YEM LAN! HOUM Pa SYSTEM
pa MY pa SYSia pa YEM pa YEM
:!l
.17
.17
.17
.17
.17
40.80 3,2*
40.01 3 41
40.80 74!
40.81 93
40.88 14
40.M
40.M
40.01
44.08
40.08
(424
424
1 424
424
1 424
424
424
424
424
424
12,124
! ALUMia STOIENS OSTAiilM M iuEPTIOR
s
1 SIZE
1 CATEBORIES
1 23-100
1 101-900
1 901-1000
1 1001-3300
1 330I-10K
1 IOK-29X
1 29K-90K
1 90K-73K
1 73K-IOOK
1 > INK
1 TOIALi
TOTAL TOTAL
RUMEN OF LAMM HOUM LOW COST
SYSTEMS Pa YEM PER YEM
111.2 4,770 (47,3*1
134.7 1,323 38,230
91.4 3,313 23,4*3
42.2 3,717 24,900
41.3 2 141 20,308
23.4 1,423 f,*72
f.O 340 1,034
3.7 340 2,430
4.4 240 1,073
4.0 343 2,337
443 20,140 01*7,110
TOTAL AM.
CAPITAL
COSY
(40,941
31,700
24,282
27,144
21,018
I02H
0
0
0
0
(1*1,024
TOTAL ANN.
COST pa
YEM
(13.M4
117 ISO
47,*77
33,472
41 484
20,1*2
3834
2,431
1,173
2,337
(3(0,144
TOTAL
LAMM COST
pa YEM
(37,031
37*2*
3 1*1
3714
1,004
0
0
0
0
0
(14,001
CAPITAL
COST PEI
SYSTEM
(2,000
2000
2000
2000
2,000
2,000
0
0
0
0
MMUALIZa
CAPITAL
COST/SYST
(437
437
437
437
437
437
0
0
0
0
(7
TOTAL MM.
CAPITAL
COST
010,412
24032
18*34
23,334
20,047
10,21*
0
0
(104,040
•••••••••MB
(7
TOTAL ANN.
CAPITAL
COST
(37,131
38,843
1,320
3 BOO
1,031
(04,*84
SYSTEM
(043
043
043
843
043
843
424
424
424
424
TOTAL MM.
COST pa
SYSTa
(843
843
043
143
843
843
424
424
424
424
TOTM. MM.
COST pa
YEM
(20,*40
41 140
37 430
44 148
3*430
20 1*2
3834
2,431
1,873
2,337
(214,273
TOTAL AM.
COST pa
YEM
I74,*83
74,7*0
10327
7,324
2,034
0171,171
NOTEi AMWII iwckMt o» turkMUr taaltarlR|
lor iy*ttn Mf»U| Itti tku 23,000 MMOM M< MWMI lir|«r •tllltii tlriU| kui Mtk
-------
FINISHES
ma KMIIMIN CMTI ra »»• TEIT. i cut
«riLT«£i SYSTEM nniiiM Eidriion
.MM tttlMML
COMMITY Mia SYSTEM
UMM CHT If! HOUR! II
SHE
UTECMIES
23-100
101-300
301-1000
IOOI-3WO
3301-IOK
IOC-2X
23K-3W
30K-7K
73K-IOOK
>IOM
IOTM.I
NUHia Of UMM HOUM
IYSTEM /MULYSII
24.3 .1470
47.7 .1470
43.0 .1470
33.3 .1470
44.0 .1470
2).« .1470
t.O .1470
3.7 .1470
4.4 .1470
4.0 0.1470
241
SMVUM
FttOUEKCY
ra KMTN
30.42
30.42
30.42
N.42
30.42
N.42
0.00
0.00
0.00
0.00
UMM HOUM YOYM. MMIM.
UMM HOUM KRYEM UMM HOUM UMM COST
ramm rasrsia KHYEM rasnia
3.00 M.t4
3.00 M.n
3.00 M.n
3.M M.n
3.00 M.n
3.01 M.t4
0.00 0.00
0.00 0.00
0.00 0.00
0.00 0.00
1,401 0427
2|444 427
3 2M 427
2001 427
1 427 427
0 0
0 0
• o o
0 0
14,323
TITM.
UMM COOT
KIYEM
010,370
20333
10320
22 022
11401
1114
0
0
0
0
0101 ,4M
CtflYM. MMMLIIES YOYM. MM. TOTM. MM. TOTM, MM.
COSira CATITM. CtfllM. COSTKI COST rt«
SYSia CMT/SYST COST SYSTEM YEM
03,000 11,011 024,331 01,311 034,100
3,000 ,0n 37,071
3,000 |0n 47,314
3.000 iOn 3S|)St
3000 On 90,141
3000 On 23,340
000
000
SO 0
0 0
42M.IOO
1,311 72,434
311 43104
311 SI 211
,)lt 41,777
311 33,3)4
0 0
0 0
0 0
0 0
0341, 7M
MM-CONHUHITV
MIEI SYSTEM
UMM COST ra HOURI 07
SUE
UTEOOSia
23-100
101-300
301-1000
IOOI-3MO
3301-IOK
IOK-2K
23K-3W
30K-7X
7X-IOOK
>IOOK
TIIN.I
MMKtOF UNO HOUM
IY8TEM /MMLVSIS
' ^ f oTl470
st!o o!i4?o
12.2 .1470
0.7 .1470
2.4 .1470
«.I470
.1470
0.0 .1470
0.0 .1470
0.0 .1470
Itf
smiM
FKMJEKY
raitttii
N.42
N.42
N.42
N.42
N.42
N.42
0.00
0.00
0.00
0.00
UMM HOUM HIM. MMJM.
UMM HOUM KR YEM UMM HUM UMM COSY
ra MMTM ra srsia
Til 4o7l4
3.00 M.n
3.01 M.n
3.00 M.n
3.M M.n
3.00 M.n
0.00 0.00
0.00 0.00
0.00 0.00
0.00 0.00
^"Mra"n«EM"oswmM"^
SUE
CITEMMIES
23-100
101-900
301-1000
IOOI-3WO
3301-IOX
IOK-2X
23K-30K
30K-79K
73X-IOOK
) IOOK
IOIM.I
YOYM.
•ma OF UMM HOUM
SYSTEM KIYEM
III. 2 4,77t
1)4.7 1,)))
33.4 3,3lt
42.2 ) 711
41.4 2,147
2).4 1,427
t.O 0
3.7 0
4.4 0
4.0 0
44) 24,4*4
TOTM.
UMM COST
ra YEM
047,433
303)4
2)724
243)4
204)2
11U
0
0
0
0
0114,443
TOTAL MM. TOIM.
WITH COST m
tan YEM
4121,400 OI4S.S4I
I4t 241 20731)
M704 SUM
47 MO t4 422
92,711 7),42I
23,341 33334
0 0
0 0
0 0
0 0
I477.3U 4444,231
ra YEM ra svsia
Tni o«7
3,424 427
330 427
144 427
427
0
0
0
12,144
TOTM.
UMM COST
KIYEM
0)7,OU
37171
3,204
3713
1,024
013,003
WriTM. MMMLIia TOTM, MM. IOTM.
COSTKI CtflTM. CMMTM. COST
Mi. TOTM. MM.
Kl COSTKI
SYSia CMT/SYSY COST SYSTEM YEM
03,000 4l,0n 014,177 01.311 IDI.IM
3,000 Jon 17,170
3,000 ,0n 13,320
3,000 |0n 1,411
3000 ,0n 2 420
siooo ;on
0 0
0 0
0 0
0217,407
Sit 133 141
311 II 324
311 1)211
311 3 444
Sit 0
0 0
0 0
0 0
0 0
ON2,4n
KOIEi Atwtn itllttlit i«rvU| |r«t«r UM 23,000 fttttn
ki>i ulflciMt
-------
COSt OF tlSTUMIUM SYSTEM NONITORINB FOB CHLORINE IESIMAL
WFHTE8EB SYSTEMS uttutw EICEPTIONS
o
1 COMMUNITY HATER SYSTEMS
1
1
1
! SUE
! CATEGORIES
• „...» -..._
t 23-100
t 101-300
1 501-1000
1 1001-3300
! 3301-IOK
! IOK-23K
1 23K-SOK
1 30K-75K
> 75MOOK
: > IOOK
1 SAMPLES
NUMBER OF PER MONTH
SYSTEMS PER SYSTEM
24.3 3
47.7 3
43.4 5
33.5 5
46.0 8
23.4 20
9.0 40
3.7 63
4.4 90
6.0 200
1 SAMPLES
PER YEAR
PER SYSTEM
40
60
60
60
240-
480
780
1,010
2 400
•»*•«••••»*
TOTALl
SAMPLES
PER YEAR
1,438
2842
2,604
3209
4,411
5,616
4320
4,462
4732
14,400
t************
LABOR HOURS
PER SAMPLE
O.OB33
0.0833
0.0833
0.0833
0.0833
0.0833
0.0833
0.0833
0.0833
0.0833
LABOR COST PER HOURi
LABOR HOURS
PER YEAR
PER SYSTEM
3.00
3.00
9.00
3.00
8.00
19.99
37.98
64.97
Bf.96
199.92
i TOTALl 243
TOTAL
PER YEAR
121
238
217
267
340
372
396
1,200
4,006
ANNUAL
LABOR COST
PER SYSTEM
435
35
35
35
lit
280
455
630
1,399
TOTAL
LABOR COST
PER YEAR
4830
1,669
1,518
1,871
W
2,319
2602
2,771
8J397
421,043
CAPITAL
COST PER
SAMPLE
11.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
47
ANNUALI1EB
CAPITAL
C03T/5YST
460
6»
60
60
96
240
480
780
1,080
2,400
TOTAL ANN.
CAPITAL
COST
41,438
2,862
2,604
3,209
W
4,320
4,462
4,732
14,400
448,094
TOTAL ANN.
COST PER
SYSTEM
495
95
95
93
760
1,235
1,710
3,799
I NON-COMMUNITY
HATER SYSTEMS
! LABOR COST PER HOURi
I
j
1 SUE
I CATEGORIES
1 25-100
! 101-300
! 501-1000
! 1001-3300
1 3301-IOK
t IOK-23K
1 2SK-S0K
1 30K-73K
1 73K-IOOK
1 > IOOK
1
! TOTALl
1 SAMPLES
NUMBER OF PER MONTH
SYSTEMS PER SYSTEM
B6.9 3
89.0 3
12.2 3
8.7 5
2.4 a
0.0 20
0.0 40
0.0 65
0.0 90
O.I 200
199
1 SAMPLES
PER YEAR
PER SYSTEM
to
to
60
60
96
240
480
780
1,080
2 400
TOTALl
SAMPLES
PER YEAR
3^214
3340
732
522
230
1 ALL HATER SYSTEMS OBTAINING AN EICEPriOH
1
1
1
1 SUE
I CATEGORIES
! 23-100
! 101-300
: soi-iooo
1 1001-3300
1 3301- W
1 IOK-25X
! 25K-30K
1 50K-75K
1 7SK-IOOK
! > IOOK
! TOIALl
TOTAL
NUHIER OF LABOR HOURS
SYSTEMS PER YEAR
111.2 334
136.7 6B3
33.6 278
42.2 311
48.4 367
23.4 448
9.0 360
3.7 372
4.4 396
6.0 1,200
463 3,009
TOTAL
LABOR COST
PER YEAR
13,190
4 783
1 943
2 175
2,707
3773
2519
2,602
2771
8,397
133,043
TOTAL ANN.
CAPITAL
COST
16,672
a 202
3336
3,731
4,642
5,616
4,320
4,462
4,752
14,400
460,132
LABOR HOURS
LAB8R WHIRS
PER SAMPLE
0.0833
0.0833
O.OB33
0.0133
0.0833
0.0833
0.0833
0.0833
0.0833
0.0833
TOTAL
COST PEA
YEAR
110,562
I29B3
5,261
3 906
7341
1191
6 839
7,063
7523
22,797
493,193
PER YEAR
PER SYSTEM
3.00
3.00
3.00
3.00
8.00
19.99
39.98
64.97
89.94
199.92
TOTAL
LABOR HOURS
PER YEAR
434
443
61
43
19
1,003
ANNUAL
LABOR COST
PER SYSTEM
133
33
33
35
56
140
280
455
630
1,399
TOTAL
LABOR COST
PER YEAR
43,040
3,114
427
304
134
17,020
CAPITAL
COST PER
SAMPLE
41.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
47
ANNUALIIEB
CAPITAL
COST/SYST
460
60
60
60
96
W
480
780
1,080
2,400
TOTAL ANN.
CAPITAL
COST
45,214
5,340
732
522
230
412,038
TOTAL ANN.
COST PER
SYSTEM
195
95
95
95
152
760
1,235
1,710
3,799
TOTAL ANN.
COST PER
YEAR
42,308
4,331
4,122
S.OBO
tali
6,839
7,063
7,323
22,797
476,137
TOTAL ANN.
COST PER
YEAR
48,254
8,454
1 159
1 fl JT
•I i
BJCv
A
V
0
419,038
-------
IMITMT SURVEY*. NATEWHO MNMEKNT MOMM CMT/lUtWI
lYflEM OOTAIMM M ElCttUON
1 COMMITY HATES SYSTEM
1 SUE
1 CATESMIEI
1 29-100
1 101-900
1 901-1000
1 1001-1300
1 HOI-IK
1 IOK-2SK
1 25K-SOK
1 30K.-7X
1 TSK-IOOt
1 HOOK
1
1 TBTALt
umaoF
SYSTEM
um^rTr -i
24.3
47.7
43.4
93.9
44.0
23.4
1.0
9.7
4.4
4.0
241
TOTAL
MUMPER i
SYITTJ
T-Tilmmm-i
40
110
171
322
3S4
»41
1,373
1003
2400
1024
TOTAL
AM HUM
ravEM
M44
9244
7700
17 Iff
24 WO
22019
12393
10323
10940
94,144
147,443
ANNUAL
COST PER
SYIIER
11,000
2300
3,700
4700
12,200
lf,400
20400
37400
90,000
110,000
TOTAL
COST PER
YEAR
•• i 1 ITT
124,300
IOt.710
140900
391,314
940,3tO
431,440
237,400
213,072
220,000
1,121,000
l3,4t2,40S
1 mKONMUn SATO SYSTEM
1 SUE
1 CATESM1ES
123-100
1 111-300
1 901-1000
1 1001-3300
1 3WI-10X
1 IOK-23JC
1 2JK-SOK
1 301-731
1 73K-100X
1 > IOOK
1 TOTALl
HMD OF
SYSTEM
••— — •
14
It
12
S
2
1
0
0
S
1H
TOTAL
MUMPER 1
SYSTEM
-•-..•—
40
110
ITS
322
904
141
1,373
I.S09
Z400
1,024
TOTAL
KRYEAR
4,171
1124
2,147
2004
1,302
20,390
1 TOTAL MTU SYSTEM
1
1 SUE
1 CAIE60SIES
1 29-100
1 101-900
1 301-1000
1 1001-3300
1 330I-10K
1 IOK-2H
1 2SK-50K
1 90K-73K
1 73K-IOOK
1 > IOOK
1
1 TOTALl
HUMES OF
SYSTEM
iiu
134.7
33.4
42.2
4S.3
23.4
9*9
a
4.0
443
•*•••*•*•••
TOTAL
LAIOSHOUU
PEIYEAI
3,331
I30T2
1S7S
20004
21 210
22013
12333
10,323
10940
94,144
-------
FINISH! MTU TWIItlTY HONlTOItlM COITI
MSTM11M FIITMTIW
1 COMMITT MTU IYSTEM
1
1
I SUE
1 CAIESORIES
1 23-100
1 101-900
1 901-1000
1 1001-3300
1 3UI-10X
1 10K-23K
1 23MOK
I30K-73K
1 7X-IOOK
1 >10N
1
1 TOTALi
1 WKOHMITY
1
1
1 SUE
1 CAIE80RIE9
1 29-100
1 101-900
1 901-1000
1 I001-3JOO
1 3301-IOK
1 IOK-23K
1 23K-90K
1 30K-73K
1 73MOOK
1 >100K
1
1 TSTALl
LAMM COS! PER WURl
LAMM HOURI USOR HOURS
NUHKR OF /CALIOMTION /ANALYSIS
SYSTEM II/MYI ISANPLIN8)
„•„...• r -_ _• i r n .1 ,n
133.0 O.OOJJ 0.0147
147.1 0.08)3 0.0147
131.1 0.08)3 0.0147
190.8 0.0133 0.01(7
114.1 O.OOJJ 0.0147
41.4 0.0833 0.0147
14.0 0.0833 0.0147
7.1 0.0833 0.0147
3.4 0.0833 0.0147
1.8 0.08)3 8.0147
804
MTU SYSTEMS
SAHPIINS
PER MT PU MT
.. i -.,ru -. • J^T r j
0.17
0.17
0.17
0.17
1:1
0.17
0.17
0.17
8.17
UNM HOURS
PERVEM
Ptt SYSTEM
• • ji 1
(0.88
(0.88
40.88
(0.88
(0.88
(0.88
(0.88
(0.88
(0.88
(O.SS
TOTAL
LAMM HOURS
pa YEM
• •••• • .!••
1,437
10213
8314
1132
4144
2933
174
443
341
948
41,071
LAMM COST
PaSTITEM
pa YEM
•••••--.»-
1424
424
424
424
424
424
424
424
424
424
TSTAL
UOORCOST
PUTUR
••••••••••
144,037
71 411
31400
43124
40403
17721
4011
3103
2)87
3,834
1343,332
CAPITAL
COST Pa
STSTDI
•••••••
02,000
2,000
2,000
2,000
2,000
2,000
0
0
0
ANMUALIIE8
CAPITAL
COSI/8TST
«*« 1. • •••!•
1437
437
437
437
437
437
8
8
8
LAMM COST PER HOURi
LAMM HOURS LAMM HOURS
NUHKR OF /CALIBRATION /ANALYSIS
SYSTEMS II/MYI ISANPLIN8I
448.1 0.0833 1.01(7
202.1 0.0833 0.01(7
JJ.4 0.0833 8.0147
22.4 0.08)3 0.0147
7.4 0.0133 0.01(7
0.0 0.0833 0.01(7
0.0 1.0833 0.01(7
0.0 0.0833 0.01(7
0.0 8.0833 8.01(7
0.0 O.OUJ 0.01(7
714
SMPL1N6
FREQUENCY LAMM HOURS
PER MT PER MT
3 0.17
9 0.17
0.17
0.17
0.17
0.17
O.I
0.17
0.17
0.17
UNR HOURS
PER TEM
pa SYSTEM
(0.88
(0.88
(0.88
(0.88
(0.88
(0.88
(0.88
(0.88
(0.18
40.88
TOTAL
pa TEM
27,278
12330
2043
1 344
449
0
0
0
0
0
43,900
LAMM COST
Pa SYSTEM
PU TEM
1424
424
424
474
424
424
424
424
424
424
TOTAL
LAMM COST
pa TEM
0110,147
04,441
14,218
1344
31254
0)04,417
CAPITAL
COBTPU
8TSTEH
oijooo
2,000
2000
2,000
2000
2000
0
0
8
8
ANUALIIEI
CAPITAL
CMI/ITST
0437
437
4)7
4)7
4)7
4)7
1
0
8
0
17
TOTAL ANN.
CAPITAL
COST
• ••••«•••
147.412
7),240
41,079
43,308
41,808
11,141
1
0
1
•JJ3.310
17
TOTAL ANN.
CAPITAL
COST
0113,472
88,381
14,432
178)
3,3)7
1312,032
TSTAL ANN.
COST Pa
SYSTEM
mmmmmmmm
1843
843
84)
843
SH
424
424
424
424
TOTAL MM.
COST Pa
STSTEH
1843
843
843
84)
843
84)
424
424
424
424
TOTAL ANN.
COST PO
TEM
•••••-••
1133,741
144730
120(74
121434
W4I3
33814
4,811
3,103
2,317
),BJ4
1471,042
TOTAL ANN.
COST pa
TEM
«3U,(20
173,038
28130
11321
(.31)
1414,321
1 ALL HATER IYSTEM INSTALLIM FILTRATION
1
1
HUE
1 MTESORIES
1 29-100
1 101-900
Siooi-ttM
1 3301-IOK
1 IOK-23K
1 2X-9W
I90K-7SK
I7X-IOOK
1 > 100K
1
1 TOTALi
TOTAL TOTAL
MM8ER OF LAMM HOURS LAMM COST
SYSTEMS PER YEM PER YEM
403.1 34,713 1297,004
J70.4 22,943 197140
173.4 10 997 73 811
172.4 10 414 73472
121.7 7,401 91,841
41.4 233) 17721
K.O 174 (811
7.3 44) 3103
3.( 341 2,387
1.0 340 3,834
1321 12,378 I44S.041
TOTAL ANN. TOTAL ANN.
CAPITAL COST PER
COST YEM
•743,344 IttMU
1(1,141 311,781
73 727 141,424
79211 148,74)
93 144 103004
18,148 19,814
0 (811
0 3 10)
0 2,387
0 3,834
1447,342 11,213,311
WTEi AIUMI ftvckiM »l turkltfltr MiUirli|
for iptm itrvUf Ini U« 23,000 ptriMi tut IIIUHI lirjir vtllltti flni
-------
coin FOR CMLMIIC
: KIIMML MMI1MIM M (ISTIUUTIOM EMTR» POMT
COtUUTYMATI
SUE
CATE60RIES
23-1*0
101-30*
IMI-3MO
33*1-10*
1N-23K
23K-30K
SOK-73K
7X-IOOK
> IOOK
TOTALi
Nn-comuMin
RUE
CATEGOtlES
23-10*
101-30*
3*1-100*
1001-1300
1301-10*:
IN-23K
29K-30K
3K-75K
7SMOOC
>IOOK
IOTM.I
9 SYSTEM
RUUER OF LASOR HOUM
SYSTEM /ANALYSIS
133.0
I47.R
131.1
130.0
1 14.1
41.4
14.0
7.1
9.4
1.0
004
MATER SYi
RUnEROF
SYSTEM
440.0
207.1
13.4
22.4
7.4
0.0
0.0
0.0
(.0
0.0
714
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.01U
0.0117
IEM
8MPLIM
FREQUENCY
30.42
34.42
30.42
30.42
30.42
3*. 42
*.«*
0.00
0.00
0.**
LASOR MOMS
PER mm
2.71
2.71
2.71
2.71
2.71
2.71
(.0*
0.00
0.00
0.00
UN* HOURS TOTAL
PER TEM LAKMHOUM
PER SYSTEM PER TEM
33.44 9,117
33.44 3,411
33.44 4,400
33.44 3011
33.44 3114
33.44 1 312
0.00 0
0.00 0
0.00 *
0.0* •
23,70*
ANNUAL TOTAL CAPITAL
LAMM COST
PER SYSTEM
(234
214
234
234
0
0
0
0
UNROOT
PER KM
(34,301
33,'ll4
24713
1,744
0
0
0
0
0171,137
COST PER
SYSTEM
03,000
3000
3000
300*
3000
3,000
0
0
0
0
UN* COS? PER NOURl
LAMM HOUM
/MMLTS1S
0.0117
(.0117
0.0117
0.0117
0.0117
0.0117
(.0117
0.0117
(.0117
0.0117
BMPLIM
FREQUENCY
PER MATH
30M2
30.42
30.42
10.42
30.42
0.00
0.00
0.00
0.00
LAM HOUM
PER MOUTH
2.71
2.71
2.7f
2.71
2.71
2.71
0.**
•.00
0.00
0.00
UUJOR HOUM TOTAL
PER KM LMOR HOUM
PER SYSTEM PER KM
33.44 14,111
11.44 47N
31.44 1,121
33.44 730
33.44 234
33.44 0
0.00 0
0.00 0
0.00 0
0.00 0
23,101
ANNUM.
LASOR COST
PER SYSTEM
(234
234
234
234
234
234
0
0
0
0
TOTAL
U(ORCOST
PER KM
1104,130
47,314
3)247
1 710
0
0
0
0
0
0147,342
CAPITAL
COST PEA
SYSTEM
(3,000
3000
3,000
3000
3000
(7
ANMMLIIO
CAPITAL
COST/SYST
t'on
.on
on
on
0
0
0
0
17
ANNUALIIEO
CAPITAL
C8ST/5YST
01, on
ion
1,012
1,012
i.on
•
TOTAL AW.
CAPITAL
COST
"mi^ni
1(1141
132,4(0
141 770
121,320
43,411
l)
0
0
0
((1S,773
TOTAL MM.
CAPITM
COST
(4(1,170
221 472
1443*
24,434
0,341
(700,041
TOTAL ANN.
COST PER
SYSTEM
(1,324
324
,324
324
324
J324
0
0
•
TOTAL ANN.
COST PER
IYHEM
41,324
1,324
1,324
1,324
1,124
234
0
0
0
0
TOTAL AH.
COST PER
YEM
(203,337
222444
1*3447
lit 104
131 233
33143
0
0
*
0
(l,*ll,732
ISTM. MM.
COST PER
KM
(314,120
24*100
44,481
21703
10,131
(147,431
ALL HATER SYSTEM INSTALLIHR FILTRATION
SUE
CATEOORIES
29-100
101-300
301-1*00
1001-3NO
HOI-IK
IK-MK
29K-3W
SW-73K
7X-IOOK
> IOOT
TOIM.I
•• «••••*••*•••«
MUNKROF
SYSTEM
403.0
370.4
173.4
172.4
121.7
41.4
14.0
7.1
3.4
1.0
TOTAL
UUJOR HOUM
PER KM
"loiioo
12,401
3,003
3,741
4072
1,312
0
0
0
0
1121 41,417
••(MM ••• •••••••••»••«
TOTAL
UUJOR COST
PER YEM
(141,230
R4(IO
40 IK
40,303
20,303
1744
0
0
0
0
(347,310
••••••*•••••
TOTAL ARM.
CAPITAL
COST
(430,111
404421
111 311
US 224
I32J04I
43,411
0
0
*
*
II, MS, 143
•••••*»**••*
TOTAL
COST PER
YEM
(711,437
411431
221,114
22(410
141,344
33,143
0
0
(
0
(1,144,143
KJIEi *»MM ntllltlM Mr«l*« iriittr tkM 23,00*
«lfi«<» kit* MlltclMt
-------
COST OF BlSWBtmOR 8YSTER HON1TDRINB FM CHLORINE RESItUAL
SISTERS 1N3TALL1RB FILTRATION
COMUNUY RATER StSTEHS
SUE
CATEGORIES
25-100
101-300
Ml-IOOO
1001-3300
w
2SK-90K
50MH
75K-IOOK
> ION
TBTALl
NQN-COmUNITY
ISAKPIEB
WNEROF PER NORTH
SYSTEM PER SYSTER
ISS.O S
IA7.B 3
139.9 )
IM.O S
tl 2!
li.O 40
7.3 45
5,4 fO
9.0 200
• SAMPLES
PER TEAR
PER. SYSTEH
M
40
M
to
A
4BO
7BO
1,060
2400
TOTALI
SMPLES
PER YEAR
9,W4
10043
1391
9000
10,949
99B4
7 480
3171
604B
21 400
LABOR HOURS
LAMM HOURS PER YEAR
PEftSAKPLE PER SYSTEM
0.0833 3.00
0.0833 3.00
0.0833 3.00
O.OB33 3.00
m ,1:8
O.OB33 39.98
0.0833 44.97
0.0833 89.74
0.0833 199.92
Hi
TOTAL
LABOR HOURS
PER YEAR
773
838
499
750
ill
440
473
301
1,799
8,221
AKNUAL
LABOR COST
PER SYSIEN
133
33
35
33
lio-
280
433
UO
1,399
LABOR COST PER HOURi
TOTAL
LABOR COST
PER YEAR
(3,423
3,849
4,893
3,248
W:
4,478
3311
3,527
12,393
157,549
CAPITAL
COST PER
SAMPLE
11.00
.00
.00
.00
:o1
.00
.00
.00
.00
07
ANWALI1EB
CAPITAL
COSUSYST
140
40
40
40
2n
480
780
1,080
2,400
TOTAL ANN.
CAPITAL
COST
19,300
10043
8,391
9000
•w
7 480
5,478
4,048
21,400
l?8,493
TOTAL ANN.
COST PER
SYSIER
)95
93
93
95
l§i
740
1,233
1 710
3799
MTU SYSTEM
LABOR COST P£A HOURi
SUE
CATEGORIES
29-100
101-300
SOI-IOOO
1001-1300
3301- IK
IOK-29K
2H-SOK
SM-73X
73K-IOOK
> IOOK
TOTALi
ISAHPLES
NUMBER OF PER NORTH
SYSTEHS PERSTSTER
MB. I
202. S
». I
22. S
7. B
ft. 20
0. 40
0. «5
0. 90
0. 200
713
(SAMPLES
PER YEAR
PER SVSTEN
40
40
40
40
94
240
4BO
7BO
1,080
2,400
TOTAL 1
SAMPLES
PER YEAR
24,885
12,171
2013
1 344
713
ALL HATER STSTEHS INSTALLING FILTRATION
SUE
CATEGORIES
23-100
1(1-300
Ml-IOOO
1001-3300
330I-10K
IOK-2SK
23K-SOK
SOK-7K
73K-IOOK
)IOOK
TOTALi
TOTAL
NUNBER OF LABOR HOURS
SYSTERS PER YEAR
40). 1 MM
370.1 1,852
I/J.4 947
172.4 B&2
121.7 971
41.4 B32
14.0 440
7.3 471
3.4 904
9.0 1,799
1321 II,BI3
TOTAL
LABOR COST
PER YEAR
»2t,09B
12944
4,047
4033
4,812
SB22
447B
3311
1327
12,393
IB2.708
TOTAL ANR.
CAPITAL
COST
134, 1B3
22214
10,404
10344
II 402
9914
7,480
3478
4,0»
21,400
1141,842
LABOR HOURS
LABOR HOURS PER YEAR
PERSARPLE KRSYSTEN
O.OB33 3.00
0.0833 3.00
0.0831 3.00
0.0833 3.00
0.0833 8.00
0.0833 19.99
0.0833 39.98
0.0833 44.97
0.0833 89.94
O.OB33 199.92
TOTAL
COST PER
YEAR
137,281
33202
14 471
14 379
11494
13801
12 138
8989
9373
34^193
1224,330
*
TOTAL
LABOR HOURS
PER YEAR
2,239
1,014
148
112
41
0
0
0
0
0
3,394
ANNUAL
LABOR COST
PER SYSTEH
*I5
33
33
33
34
140
280
453
430
1,399
TOTAL
LABOR COST
PER YEAR
113,475
7097
1,174
7B5
428
125,139
CAPITAL
COST PER
SARPLE
11.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
17
ANNUALIZEB
CAPITAL
COST/SYST
140
40
40
40
9i
240
480
780
1,080
2,400
TOTAL ANN.
CAPITAL
COST
t24,8B3
12,171
2,013
1,344
733
143,147
TOTAL ANN.
COST PER
SYSTEH
195
95
95
95
132
380
740
1,233
1,7(0
3799
TOTAL ANN.
COSTFU
YEAR
114,723
13934
13,284
14,248
17 333
13804
12,158
8,989
9373
34,193
1154,244
TOTAL ANN.
COST PER
YEAR
142,558
19248
3 187
2 131
1,141
g
0
0
148,304
-------
FMIIHEI win lumiim imnniN tun
BTB1EM dMOTLY FILTUIM
9
vO
COMMIT Mia mim
BIIE
CATESUia
23-100
101-300
301-1000
IOOI-UM
3301-IM
IK-231
25MM
30K-73I
79K-1NK
) 10K
TBTALi
NOR-COMUNITV
urn HOURS um HOURS
NUMBER OF /CALIMATIM /AMLT8I8
8T8TEM U/BATI ISAHPLIMI
32) 0.08)) 0.0147
474 0.0833 0.0147
3)7 0.083) 0.0147
814 0.08)3 8.0147
114 (.083) 0.0147
904 0.0*)) 0.8147
30) *.OB3) 0.0147
144 (.0833 (.0147
1* 0.0833 0.0147
211 0.0833 8.8147
4411
Miamim
BAHPLIM LABOR HOURS
FRE0UFJCT
pa BAT
m
LABOR HOURS
ra TEM
ra BAT pa mm
0.17
(.17
0.17
0.17
(.17
(.17
0.17
(.17
(.17
(.17
40.8*
40.N
40. N
40.81
40.88
40. 88
40.88
40.18
40.18
40.88
TOTAL
LAMM HOURS
pa TEM
31,841
28838
32,414
41,338
40438
3*483
1*447
8747
3,144
13,272
2*0,727
LABOR COST
ra STSTEN
pa TEM
(424
424
424
424
424
424
424
424
424
424
LABOR CUT Pa HOURi
TOTAL
LABOR COtT
raiuR
(272,881
202,004
228833
344101
424,441
214 712
121 131
41 3i1
41,743
12,104
(1,143,088
CAPITAL
CUT PU
ittia
(2,00*
2,000
2(0*
2,00*
2,00*
2JOO*
*
I
*
AMUALlin
CAPITAL
CUT/BTIT
(4)7
437
437
437
437
437
0
§
•
LABOR CUT Pa NOURt
(HE
CATEBORIE3
23-100
101-3*0
301-1000
IMi-3300
3301-IK
IOK-23K
2SK-30K
30K-73K
73MOK
>IOOK
TBIRLi
LABOR HOURS LABOR HOURS
UlUa OF /CALIBMTim /AIALYSII
BTBTERS I1/8ATI ISANPLIIM)
1.3S8 (.0833 0.0147
440 0.08)3 0.0147
142 0.083) 0.0147
102 0.0833 0.0147
42 0.0833 0.0147
0.0833 0.0147
•.0833 8.0147
8.08)3 8.0147
(.0833 8.8147
0.08)) 0.0147
2)01
8ANPLIM
FREQUFJCT
pa BAT
LABOR HOURS
pa TEM
ra BAT pa ITSTEI
Tl7
.17
.17
.17
.17
.17
.17
.17
(.17
0.17
ALL Mia mim CURROTLV FILIPIM
SUE
CATEGORIES
23-100
1(1-300
301-1000
1001-3300
3341-IOK
IM-23K
23K-30K
3W-73K
73MOOK
> IOM
TOTALi
•••••••••••••M
TOTAL TOTAL
mim PER TEM pa TEM
1,811 114,311 tBO;,433
I 134 41040 483281
471 41 331 281,372
114 M 748 310,371
1,038 43,114 442,341
304 30 804 213,444
303 11,447 121,1)1
144 1,747 41 341
11 4027 42 111
211 13,333 13,332
4111 421,243 (2,148,41*
TOTAL AM.
CAPITAL
COST
4821,470
413 240
214,333
4W.034
43)313
2201(0
•
•
•
«
12,487,373
numram
TOTAL AM.
COST pa
TEM
(1,42), 104
171,322
383,103
710,411
813484
4)4424
121131
41,341
42111
13,332
13,4)4,27)
40.88
40.88
44.88
40.88
40.81
40.88
40.H
40.88
40.88
40.M
TOTAL
FfR TEM
82^478
48182
8443
4,210
2337
122
0
0
41
41
140,314
LABOR COST
ra irsiti
pa TEM
(424
424
424
424
424
424
424
424
424
424
TOTAL
LABOR COST
PttTEM
(378,744
281 273
40,317
4)47*
17,81*
832
«
0
424
424
11(3,41*
CAPITAL
COST PER
ITSTEI
' (2,00*
2,00*
2,008
2,000
2000
2,00*
*
8
*
•
AMUALI2EB
CAPITAL
CU1/STST
437
437
437
437
437
0
8
0
'
(7
TOTAL AM.
CAPITAL
CUT
(228,403
2*7,003
234311
333,41*
43417)
220JI07
0
0
«
(1,484,411
(7
TOTAL AM.
CAPITAL
COST
1313,044
288233
42814
44343
18342
873
8
*
*
•
(1,007,074
TOTAL AM.
curra
srsia
(84)
84)
143
141
84)
14)
424
424
424
424
TOTAL AM.
COST PER
srsia
(143
14)
84)
84)
843
843
424
424
424
424
TOTAL AM.
cnira
TEM
(431,214
401,012
443374
7(2314
831442
434411
121,131
41,341
41 743
12,1*4
(3,443,3(7
TOTAL AM.
CUT pa
TEM
(I,I7I,8I(
341310
122331
88013
34242
1,724
0
0
424
424
(1, 110,484
NOTEi AHUM pwckiM il turkldlty §o«Uorl»| tqvlpMit lor lydui nrvt*| lift tkM 23,000 pirioni utt UMMI lir|tr vtilltit t\rnii htvl tuck
-------
«. m OUMINE ^sanaar* '•" "in
S SlUNITY MTO SYSTEM
1
I SUE
ICATESMIES
1 901-1000
1 1001-3300
1 3301-IOC
1 IOK-29K
1 29K-90X
I90X-73I
1 79K-IOOX
1 HOOK
1
1 TOTALi
NUMaOF
SYSTEM
923
SB
K
904
303
'«
2IS
4,411
/ANALYSIS
M«7
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
O.MI7
IAN1IM
FREOUFJCY LAOOR MUM
pa mm Famm
3M2 2.71
30.42 2.71
30.42 2.71
30.42 2.71
30.42 2.71
30.42 2.71
0.00 0.00
0.00 0.00
0.00 0.00
0.00 0.00
LAM HOUM
Pa YEAR L
PUITtTEN
33.44
33.44
33.44
33.44
33.44
33.44
0.00
0.00
0.00
0.00
TOTAL
MM MUM
pa YEW
I7|l70
27)231
33,321
o
0
0
120,744
ANNUAL
LAMM COST
FUSYSTEN
0234
234
234
234
234
234
0
0
0
1 NON-COMMUNITY NATER SYSTEM
1
1
HUE
luiania
1 29-100
1 101-900
1 901-1000
1 1001-3300
1 3301-IM
1 IW-29X
1 29K-90K
ISOK-7X
1 79K-IOOK
1 > IOM
! TOTALi
LAMM COST PO HOUAl
TOTAL
LAMM COST
PO YEAR
1122,901
III03I
123700
110473
233,304
110,090
0
0
0
4101,349
CAPITAL
cut pa
SYSTEN
" 01,000
1000
1000
1000
1000
5000
0
0
0
UK* aai ru mm
NuaaoF
SYSTEM
1,390
440
142
102
42
2,300
LAOOR HOURS
/ANALYSIS
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
0.0117
O.MI7
0.0117
0.0117
!"ALL MTalnrois cuMaav FRTUIM
i
i
i
1 SITE
1 CATESORIU
I BH. --•-«- IT
1 29-100
1 101-900
t 901-1000
1 1001-3300
t 3301-IOX
1 IOK-23K
1 29K-3W
1 90X-79K
1 79K-IOK
1 ) IOM
1 TOTAL!
MTEl ASWMI
NUNKROF
SYSTEM
••••-••••
I.MI
1 134
471
114
1,030
904
303
114
W
211
TOTAL
UOMHOUM
FO YEAR
••••••-••
42,144
37147
22722
$9
14132
0
0
0
0
SAHF1IM
FREQUENCY UOOR HOUM
FfR MONTH PEA MONTI
3M2 TTI
30.42 2.71
30.42 2.71
30.42 2.71
30.42 2.71
30.42 2.71
0.00 0.00
0.00 0.00
0.00 0.00
0.00 0.00
TOTAL TOTAL ANN.
LAMM COST CAPITAL
PiRYEAA COST
•••--••••• •••••••
4440,410 12,093,474
249431 1 230101
191091 741 332
214,944 1,000,001
243144 1 I332M
110,927 932,491
0 0
0 0
0 0
0 0
4,111 201,133 11,441,320 44,710,137
lUIUIn Mr»l«| triittf
Uu 29,000 M"Mi i
UUJOR HOUU TOTAL
Pa YEAR LAMM MUM
PUSHTU pa YEAR
33.44
31.44
31.44
31.04
33.44
33.44
0.00
0.00
0.00
0.00
TOTAL
COST PER
YEAR
•»-»«»•
12,414,204
1993,732
100,303
1,214493
1374,432
470,171
0
0
0
0
.i!:i»:»i.
rtlif hiv* U
43,443
3|4IJ
1,409
0
0°
0
77,144
ANNUAL
LAMMCMI
FUSYSTEN
0234
234
234
234
234
234
0
0
0
lIlMflt.
TOTAL
LAMMCMI
Pa YEAR
I3IS.10I
194400
33242
23113
1SJO
441
0
0
0
1940,143
CAPITAL
con pa
SYSTEM
01,000
1,000
1000
9000
1,000
1000
0
0
0
07
AMUALlia
CAPITAL
CMT/1YST
11,012
0
0
0
07
AMUALIIE1
CAPITAL
CMT/SYIT
ri'i'i'i'ii
0
0
0
TOTAL AM.
w»
504,217
100,725
1,007433
590)247
0
0
0
04,201,244
TOTAL ANN.
CAPITAL
COST
01,402,444
720 9N
199034
III 344
49034
2.IS4
0
0
0
02,317,411
I
TOTAL AM. TOTAL AM.
COST pa COST ra
snia YEM
11,324 4413,120
324 421,944
J324 712,009
,324 1,071,311
324 1 320,730
,324 440,329
0 0
0 0
• •
0 0
13,102,412
TOTAL AM. TOTAL ANN.
COST pa CUT ra
SYSTEN YEAR
liJ324 OI.000.7U
324 S79.IN
,324 IMJ2N
324 139,291
,324 99,410
l) $
0 0
0 0
0 0
03,097,094
-------
COST OF iisTRiWTioN STSTEN MMUMIW f« CHLORINE RESIDUAL
SYSTEMS CURRENTLY fILTE81N8
mwmwmmmvmmmmmmmmmmmmmmmmmmmmmmmmmmmmn
COMMUNIT1 NATEI SYSTEMS
SIZE
CATEGORIES
29-100
191-909
501-1000
1001-3390
3301-IOK
IOK-25K
23K-90K
39K-79K
75K-IOOX
> IOOK
TOTAL!
NUM8EROF
SYSTEMS
523
474
537
814
994
504
103
144
91
218
4411
9 SAMPLER
PER MONTH
PER SYSTEM
5
5
S
29*
49
43
99
200
••••••• vvra
1 SAMPLES
PEIVEAR
PER SYSTEM
to
to
to
to
94
240
480
780
1,080
2,400
••••••• *w ••
TOTAli
SAMPLES
PER YEAR
31,380
28,440
32220
48840
93114
120,940
145,448
112 321
103140
323,209
mmmwmmwmmmmmm
mmummmmmmmmwmwmmmwmmmmmmmmmmmfmmfmmmfm^mmmmmmmmmmmmmmmmmmmm*
LAMM COST PER HOURi
UKR HOURS
LAMM HOURS PER YEAR
PER SAMPLE PER SYSTEM
.0133
.0133
.0133
.0833
.0833
.0133
.0833
.0833
.0833
.0133
5.00
5.00
5.00
5.04
8.09
19.99
39.98
44.97
89.94
199.92
TOTAL
LABOR HOURS
PER YEAR
2,414
2349
2,484
4,048
7943
10,074
12119
9,354
8814
43|5B3
103,447
ANNUAL
LAIOR COST
PER SYSTEM
133
33
33
33
34
140
280
435
430
1,399
'•MKWimiilir
TOTAL
LAMM COST
PER YEAR
111,298
14383
18787
28,479
33,734
70932
84804
45494
41 715
309,078
1723,524
CAPITAL
COST PER
SAMPLE
*'oo
!oo
.00
.00
.00
.09
.09
.00
.99
NATER SYSTEMS
LAMM COST PER HOURt
SUE
CATEGORIES
29-100
101-900
901-1000
1001-3300
3301-IOK
IOK-23K
23K-30K
30K-79K
75K-IOOX
> IOOK
TOTALl
NUMBER OF
SYSTEMS
U98
440
142
102
42
0
1
1
2,308
1 SAMPLES
PER MONTH
PER SYSTEM
5
5
3
29
40
49
90
200
1 SAMPLES
PER YEAR
PER SYSTEM
to
to
to
to
94
240
480
780
1,080
2400
TOTALI
SAMPLES
PER YEAR
81,480
39,400
8320
4,120
4032
480
0
0
1,089
2409
LAIOR HOURS
LAMM HOURS
PER SAMPLE
0.0133
0.0133
0.0133
0.0833
0.0833
0.0833
9.0133
0.0833
9.0133
0.0833
'ATrMTErSYSTEMs'cURRENTLY FILTERINB
SUE
CATECOIIES
23-100
101-300
301-1000
1001-3300
JJOI-10K
IOK-2SK
23K-30K
30K-73K
7SK-IOOK
> IOOK
TOTAli
NUIHEROF
SYSTEMS
1,881
1,134
479
914
1,038
904
303
144
99
219
4,919
TOTAL
LAMM HOURS
PER YEAR
9,401
5 US
3,394
4578
8,101
10 114
12,113
9334
8,904
43,782
115,418
TOTAL
LABOR COST
PER YEAR
445,809
39474
23793
32,047
98 103
70112
84,804
43,494
42,343
304,477
1809,324
TOTAL ANN.
CAPITAL
COST
1112,849
48049
49,740
54 940
99,448
121,440
145,440
112,320
104,929
529J400
11,387,948
TOTAL
COST PER
YEAR
1178,449
197 714
44,493
87,007
197,753
192,232
230244
177,114
149245
812,077
12,197,292
PER YEAR
PER SYSTEM
Toi
5.99
5.00
5.00
8.00
19.99
39.91
44.97
89.94
199.92
TOTAL
LAMM HOURS
PER YEAR
4,787
3,299
118
919
334
49
9
9
99
200
11,971
ANNUAL
LAIOR COST
PER SYSTEM
«3
33
33
33
34
140
210
439
430
1,399
TOTAL
LUOA COST
PER YEAR
147,511
23091
4,948
3919
2,351
280
0
0
t30
1,399
183,798
CAPITAL
COST PER
SAMtE
11.99
.09
.00
.99
.09
.90
.90
.00
.09
.00
17
ANNUAL I1EI
CAPITAL
COST/SYST
(49
40
to
to
94
240
480
710
1,080
2,400
TOTAL ANN.
CAPITAL
COST
931,380
28,448
32220
48,840
9S,41t
120949
143,440
112329
193849
523,209
TOTAL ANN.
COST PER
SYSTER
195
95
93
95
132
380
749
1,233
1,719
3,799
11,244,254
17
MMUM.UEI
CAPITAL
C8ST/SYST
140
40
40
40
94
240
480
710
1,080
2,400
TOTAL ANN.
CAPITAL
COST
181,489
39,499
8329
4,129
4032
489
9
0
1,089
2J499
1143,712
TOTAL ANN.
COST PER
SYSTEM
193
91
93
95
152
380
• 740
1,233
1 710
3799
TOTAL ANN.
COST pa
YEAR
149,478
43,023
91,097
77,319
191,370
191 492
239,244
177,814
147,999
828,278
11,949,782
TOTAL ANN.
COST PER
YEAR
1128,991
42,491
13488
9,489
4,383
749
9
9
1,719
3,799
1227,319
-------
APPENDIX D
SPREADSHEET MODELS FOR COMPUTING COSTS
OF MONITORING FOR THE
TOTAL COLIFORM RULE
-------
COSTS t MMM OF HONITMIM FM SURFACE MTE1 SYSTEM
Him MURAIIM k I1SIMFECI10N
M FLEUIILU1
ICOmUNITY SURFACE MTU SYSTEMS
Size Catefory
25-100
101-500
301-1000
1001-3300
3300-IOX
IOK-25K
25K-50K
SOK-75K
73K-IOOK
IOOIC-50W
500K-I NIL
OVER 1 MIL
Tetal
0 Saeples
Nuektr el CurrMtly
Syttet* Required/Yr
1,453 12
2,122 12
1,473 12
2,237 24
7,307
Celt el Saeple Analyitsi
Proposed 8
Saeples
Per Viar
40
40
40
40
XSBM***Sass**xfttn««Mu»*»*9S:**>*si**s*z*x*«*
NOKOmUNUY SURFACE MATER STSIEHS
lacreitid 8
el Saiples
/Systie/Year
40
41
40
34
Total 8
Additional
Saepl if
47,744
101,854
71,740
80,532
323,872
AM. Cest
e< Hoeltor.
/Syst/Vcar
1720
720
720
340
,«««,„„«
its
Tetal Celt
el AM.
ItooitorUf
11,044,140
1,327,040
1,074,400
1,207,780
14,831,380
,„.,.,«.„
Lakor Hours
Per Saeple
0.1413
0.1483
0.1483
0.1483
•"""•-"
Additional
labor Hours
PIT Systee
O.I
8.1
0.1
4.1
—"•"""=
Tetal AM.
laker Hours
11,730
17,142
12,077
13,334
54,311
•«*»««•»"
Coil el Saeple Analyiisi 115
Si ic Catteery
23-100
101-300
301-1000
1001-3300
3100-IOK
10K-25K
2SK-SOK
50K-7ST
7SK-100K
lOMC-SOOK
500K-I RIL
OVER 1 RIL
(Total
1 Saeeles
Nuekir el Currently
Syittei Rtquir*d/Yr
2,734
1,214
241
141
30
31
4,474
Propose! 1
Satplfi
Per Year
40
40
40
40
74
240
400
700
1,080
2,040
3,120
4,800
Increase* 1
e( Saaples
/Systie/Year
54
34
54
34
72
234
474
774
1,074
2,034
3,114
4,774
Tetal 1
Additional
Saiplei
154,224
47,774
13,474
1,280
2,740
12,034
1,704
0
1,074
2,034
0
0
245,574
Add. Coft
el Monitor.
/Syst/Viar
1840
B40
840
840
1,380
3,340
7,140
11,440
14,140
30,340
44,740
71,740
Total Cost
el U4.
Hoeitorlni
12,313,340
1,044,440
242,440
124,320
41,400
180,340
28,340
0
14,140
30,540
0
0
13,783,740
Laker Hours
Per Saiple
0.1483
0.1483
O.I4B3
0.1413
0.1413
0.1413
0.1413
0.1(83
0.1483
0.1403
0.1403
0.1403
Additional
Laker Hours
Per Systte
7.4
7.4
7.4
7.4
13.5
37.7
80.1
130.4
181. 1
342.7
524.4
807.2
Total AM.
Labor Hours
23,754
11,743
2,271
1,373
443
2,024
320
0
181
343
0
0
44,700
-------
ro
COSIS I 8WDEM OF HONIIDR1N6 FOt SURFACE MAIE8 SYSTERS
MIIH FILTRAtlOM I 81SINFECTION
NO FUII81LITT
!AU SURFACE WTEI SYSIEHS
! Total 1 M4. Coit
•uiktr •< MditioMl of HoRitar.
Silt Category Syitm Saipln /Sytt/Vcir
23-100
101-300
301-1004
1001-3300
3300-IOK
IOK-23K
25K-30K
30K-73K
7SK-IOOK
IOOK-SOOK
5001-1 NIL
OVER 1 MIL
llotil
4,207
1,3*8
1,73*
2,385
31
SI
4
0
1
1
0
0
11,783
223,1*8
171,432
83,251
88,820
2,7*0
12,03*
1,104
0
1,07*
2,03*
0
0
58f,48B
II ,3*0
,3*0
,5*0
,380
,380
,340
7,140
ll,*40
1*,14*
30,340
44,74*
71,140
Total Cost
el Mi. Total Ut.
KMltorU| Lakor Hour I
13,331,521
2,574,480
1,278,841
1,332,300
41,400
180,540
28,340
•
I*,I40
30,340
•
•
18,842,320
37,*14
28,88*
14,341
14,948
4*3
2,02*
321
1
181
343
0
0
11,211
-------
costs i HJRMR or MNITORINB FM SMWBUMER SYSIMS
NUHOUl lISUFECnM
M flEIlllLW
I ,„,.,......»»..
.mmmmmmm****
U.U.....U.
ICONINITV SMUIWMER SYSTEMS
Slit Cattfory
25-100
101-300
301-1000
1001-3300
3300-10K
IOK-2SK
2SK-SOK
50K-73K
75K-IOOK
IOOK-SOOK
SOOK-I MIL
OVER 1 MIL
Total
Huobir of
Syitm
12,773
1,834
2,271
1,470
474
133
38
27,483
,«„.««..
1 Satflti
CttTTMtly
iHplrri'Yr
4
4
4
8
74
240
480
780
1,080
2,040
3,120
4,804
•Bsca*a»*s«a
NOR-CONUIITY 6ROUUM1ER SYSTEMS
Silt Cattfory
23-100
101-500
301-1000
1001-1100
3300- IOK
IOK-25K
25K-50K
SOK-TSK
7SK-IOOK
IOOX-500K
300K-I OIL
OVER 1 NIL
Nuiber of
Syitm
74,127
17,444
3,311
431
102
5
1
0
0
0
0
0
75,447
8 Satfltt
Currently
Rtqulrto/Yr
4
4
«MM.«««..«m«MM..».m.»..«»»»«««»«»«««»«»«»»"'
Cost ol SaocU Analyiisi (13
fropoitd 8 iKriistf 8 Total 1 Mi. Cost Total Cott
Saofltt of Saoplts Mtltio.il tf Monitor. of AM. Labor Howl
ftr Ytar /tyitM/ytar Sutltt «y*t/Ytar Itonitorlnt. ftr Saiplt
40 34 724,400 1840 (10,877,000
40 34 3)1,824 840 8,277,340
M 54 127,174 840 1,707,440
40 32 87,880 780 1,318,200
74 00
240 0 0
480 00
780 * *
1,08* » •
2,040 0 0
3,12* 0 0
4,800 0 0
1,471,480 122,402,200
„„„.«„,»«..».»»»»«».«»««.»»««'«»""""•
Ceit of Samlt Analysis! (15
froposH 8 Ucrtastd 1 Total 1 Md. Cost Total Colt
Saoplti of Satplil Additional of Monitor. of Ml.
Ptr Ytar SsyittiSytar Saaplts /Syit/Ytar Honitori«|
40 54 4,151,224 «B40 142,248,340
40 34 774,774 840 14,454,440
40 34 174,414 840 2,141,248
40 34 25,348 840 380,320
74 72 7,184 1,180 148,740
240 214 1,180 1,540 17,700
480 474 474 7,140 7,140
780 774 0 11,448
1,080 1,874 0 14,140
2,040 2,034 0 30,540
3,120 3,114 0 44,740
4,800 4,774 0 71,740
5,341,224 (80,418,340
0.1481
0.1481
0.1481
0.1481
««••——
Labor Hours
ftr Saoilt
.1483
.1481
.1481
.1481
.1481
.1481
.1481
.1481
.1481
.1481
.1481
.1481
Additional
labor Hows
ftr Systto
7.4
7.
7.
8.
.............
Additional
Labor Hours
ftr Syitti
7.4
7.4
7.4
13.3
17.7
80. 1
130.4
181. 1
342.7
524.4
807.2
Total Kit.
Labor Hoyrs
122,287
72,872
21,404
14,770
231,331
»•**""«•«•
Total AM.
tabor Hour*
478,451
144,423
11,010
4,247
1,571
Iff
80
902,274
Cost ol
Sail t try
Swvty
100
300
750
750
.200
.200
.200
.200
.200
.200
.200
200
•••«••*****«*
Rtpiat AMwaliiri
Uttrval Cost ftr
lYtirs) SyttM
140
40
250
250
400
400
400
4N
400
400
400
400
•S3XBB*BSBBBBXBBX*C*BXBB
II
it
II
Total II
AM. Cost II
Sat. Surv. II
. .... I*
1778,50* I!
571,240 II
347,750 !!
422,500 II
278,400 it
42,000 !!
13,200 li
1,400 ti
0 II
0 II
0 II
0 t!
II
12,717,170 II
sctasxKXaaaaJ {
Total Cost
ftr Syittt
Ptr Ytar
1700
700
1070
IOJO
400
400
400
400
400
400
400
400
.**...».».
Total
Cost
(11,477,500
8,848,400
2,475,110
1,740,700
278,400
42,000
15,200
1,400
0
0
0
0
(23,111,110
i:
Cost of
Satitary
•„_„--_
survty
100
MO
750
730
,200
,200
,200
,200
,200
,200
,200
,200
Rcitat AitMialUfd
Uttrval Colt
(Ytaril SIB. S«rv.
40
40
230
230
400
400
400
400
400
400
400
400
it
.,
Total ::
AM. Cost II
San. Surv. It
14,447,740 II
1,044,748 II
877,750 It
111,230 II
40,800 tl
2,000 II
400 it
0 II
o :i
o i:
0 it
0 1!
(4,528,700 '.:
Total Coit
Ptr Syitti
ftr Itar
(100
100
1,070
1,070
1,780
1,140
7,340
12,040
14,340
10,140
47,140
72,340
Total
Annual! ltd
Cost
(44,714,1(0
13,701, 4W
3,824,110
471,770
181,340
17,700
7,340
4
0
0
0
0
(84,147,040
-------
COS1S k WKKN Of NONITmiM FD8 GMNMMMKR STSKHS
IM.L HOUUIMTER
Silt Cttcforv
23-100
101-500
301-1000
1001-3300
3300-IM
IOK-25K
25K-SOK
30K-7SK
7SMOM
looK-seox
SOOK-I III
OVER 1 III
ITotii
SISTERS
Nwbtr ol
Syttns
87,104
27,300
3,782
2,143
102
3
122,437
B*X*S*XSSS»M
Total 1
MditiMil
Saoolci
4,877,824
1,528,800
323,7f2
113,248
f,384
1,180
474
8
0
0
0
0
4,834,704
NilHOUI 81S1NFECUOI
NO FLEIIIILIIT
Cost ol
MdUionil
ItooHorUl
173,147,340
22,f32,000
4,834,880
1,178,770
140,740
17,700
7,140
0
0
0
1102,820,340
Total Ui.
Labor Hour*
820,931
737,277
34,4f4
lf,040
l,57f
Iff
80
8
0
0
8
0
1,133,447
Total
AM. Coil
Su. Surv.
13,224,240
1,438,000
1,443,300
333,730
3lf,200
44,000
13,400
1,400
0
0
0
0
»f,243,810
Total Coil
ftr Systn
ftr Tear
11,800
1,800
2,180
2,120
2,180
4,340
7,f40
12,440
U,f40
31,340
47,940
72,740
Total
huwaliiri
Cost
I78,3f3,400
24,370,000
4,302,380
2,234,470
«5f,UO
81,700
22,740
1,400
8
0
8
0
1112,044,430
-------
COSH t MUCH OF MMI1W1W fM UflUHBWkIM SYSTEM
MITN HSIHfECTIM
10 FIEIIHLITY
|»U*UM»MN
MM«a*W*«MMMMU
!••••«•••••• 1
uuManxra* | umuiMim
icomMUY itouwATEi SYSTEM
Slit Cittfory
25-100
101 -SM
501-1000
1001-3)00
3300-IOK
IK-2SX
2X-SOK
SOK-73K
TX-ioor
100K-300K
500K-I MIL
OVER I III
1 Sup lit
Htwbtr ei CwfMtly
Syitm Rtq«irid/Yr
4,321
i,040
3.011
3,741
Protest* 1
SaaflM
Ptr Ytar
40
M
M
M
Itcriiifd 1
ei SaoilM
Cott ii Su«li tailriiti 113
ItUl 1 «M. Coil lot il Coit
AMitlMul •! UMitor. il AM.
/tystti/ytir Supltt /Syit/Tiir Honitiritf
Si
34
34
32
Total 17,IJ»
,
NCN-COIHUIITr «OUHIIAI« SYSTEMS
Sill Cattfory
23-100
1*1-100
501-1000
1001-3300
I300-1MC
IOK-2X
KK-SOK
30K-7X
73K-IOOK
IOOK-SOOK
SOOK-I MIL
OVER 1 MIL
1
Until
1 Saoiltt
father of Cirrtttly
Syittn Re*,iiirid/Yr
24,707
10,472
4,453
1,007
247
22
10
4
2
7
0
0
41,357
Proposed 1
SatplH
Fir Ytar
to
M
M
M
14
240
480
780
1,090
2,040
3,120
4,100
Increased 1
•1 Suylti
/lyitii/reir
34
34
34
34
n
234
474
774
1,074
2,034
3,114
4,774
242,200 »40 43,433,000
331,240 140 3,073,400
148,414 840 2,527,240
173,474 780 2,733,140
0
0
0
0
0
0
0
0 0
744,732 114,170,780
Cut of S*«fli Aailriii: 113
Total 8 Mi. Cost Totil Coit
Mill Mil o< ItMittr. ol M.
Suilti /Syit/Ytir Daaltorlnf
1,381,704 1840 420,733,340
378,732 840 8,981,280
240,344 840 3,708,320
34,372 840 843,880
22,708 1,380 343,420
3,172 3,340 77,880
4,740 7,140 71,400
4,434 11,440 47,840
2,132 14.140 31,280
14,252 30,340 213,780
0 44,740 0
0 71,740 0
2,333,334 435,300,040
MtitiOMl
likar Maart Ukor Howt
PK Siiflt
0.1483
0.1483
0.1483
0.1481
Labor Howi
Ptr Suilt
0.1483
0.1483
.1483
.1483
.1483
.1483
.1183
.1483
.1483
.1483
.1483
.1483
Ptr Syitt*
7.4
7.4
7.
8.
Additional
Lakor Houri
PIT Systti
7.4
1.4
1.4
1.4
13.3
31.7
80.1
130.4
181. 1
342.7
324.4
807.2
Total Md.
Lakor Houri
40,742
34,124
28,378
32,132
158,778
Total Add.
Lakor NOUM
232,877
100,770
43,834
7,411
3,833
874
801
784
342
2,377
0
0
374,044
Cntvl
SMltary
Survty
1300
300
730
730
Cost ol
Suitary
Survey
1300
300
750
730
,200
,200
,200
,200
.200
,200
.MO
,200
IMIU*S«U«UlM»B»«MB>umtM| |
II
II
II
Iff tat AMMllirt Totil II
Mtrvil Cott Ptr Am. Cost II
(Ttjfil Sritti SM. Sir*. II
40 40 40 II
II
II
II
II
II
II
II
1!
II
I!
::
n
to it
n
n
n
fteptat Total II
littml hinualiiri AM. Cast II
lltiril Coit San. SUM. II
40 40 tO II
0 II
0 II
0 II
0 II
0 II
0 il
0 II
0 II
0 II
0 II
0 !!
II
40 II
Total Coit
Ptr 8iritM
Pic Ttar
4840
84«
840
780
Total Coit
Per Syiteo
Ptr Ytar
4840
840
840
840
1380
3540
7140
11440
14140
30540
44740
71740
t!72,420
Tttal
Anwallitd
Cott
4J.U3.000
3,073,400
2,527,240
2,733,140
414,170,980
Total
Annual! ltd
Coit
120,733,340
1,181,280
3,708,520
643,880
343,420
",880
71,400
47,840
32,280
213,780
0
0
435,300,040
-------
COSTS 4 Mm OF NnUTIMINS FOR EROUUNATU StSTERS
KITH DISINFECTION
NO FLEIIIIL1IT
| zxsinmunm
IM.L SROUUWTER
Sill Cttiforr
23-100
101-500
301-1000
1001-3300
3300-10K
IW-23K
23K-30K
30K-75K
73K-IOOX
10MC-300K
304C-I MIL
OVER 1 NIL
(Total
)*•••*•••••*••*«
*»**•«»*«***
SYSTEMS
Nuiktr ol
Sytttii
27,034
14,732
7,444
4,770
247
22
10
4
2
7
0
0
38,474
Total 8
Saopltt
1,423,704
134 712
427,181
232,048
22,108
3,112
4,740
4,454
2,152
14,232
0
0
3,218,048
•BaMHHMSS
Cost ol Total Total Cmt
Motional Total Mi. AM. Cost ftr Syttto
HMltorlOf Labor Hourt Sao. SUM. Ptr Yttr
24,188,340
14,054,880
4,437,748
3,781,020
343,420
77,880
71,400
41,840
32,280
213,780
0
0
41,471,020
273,440 40 41,180
157,414
72,232
42,423
3,833
874
801
784
342
2,371
0
•
1,480
1,480
1,420
1,180
1,540
7,140
11,440
14,140
30,340
44,740
71,140
353,043 40 4173,720
!•••»•••> ••U SS • UMS * • • * • •*»** •••
•»««•• SKXSBB
Total
tenualiiH
Cait
424,388,540
14,034,880
4,437,740
3,781,020
343,420
77,880
71,400
41,840
32,280
211,780
0
0
411,471 ,020
I99*x***mm*»*
-------
10IM. COSH k MRKN OF MNIIORIM FOR MOMHMUR SYSTEM
NO annum
ICDHMMm HOUMWTER SISIEHS
Sin Catofory
23-100
101-500
301-1000
1001-3300
3300-101
1K-25K
2X-50K
50K-7SK
7SK-IOOK
IOOK-300K
300K-I MIL
OVER 1 MIL
Total
ss sen ssscx sis
Nmoorol
SfstMt
17,300
13,194
3,282
3,453
494
133
38
44,122
NON-COIMMITY BMWNATU
Sin Catefory
23-100
101-300
501-1000
1001-3300
3300-IM
IMC-2SK
23X-50K
5WC-7W
75X-IOOK
100K-300K
300K-I HIL
OVER 1 NIL
1 Total
( «n«B> »»•»»
Nuokir of
SplllS
98,838
28,138
8,144
1,440
331
27
II
117,004
»**»«»»
Total 1
AUitloMl
Saoolis
1 948,800
818,044
293,792
281,334
2,418,212
xcnsuussi
SYSTEM
Total 1
AMitiMal
Saooln
3,514,928
1,373,728
437,184
81,740
12,292
4,172
3,234
4,434
2,152
14,252
0
0
7,714,340
Cost ol
AMitloial
ItaitorlM
414,312,000
11,130,940
4,414,880
4,233,144
434,373,110
•S3 SMMC CM *
Cost of
Additional
IMtoriM,
413,123,920
23,433,920
4,H7,7M
1,224,400
414,380
95,380
71,340
49,840
32,2B»
213,780
0
0
4115,718,400
Total AM.
lakor Hours
143,049
149,798
49,782
47,722
410,131
icnxsntvasK
Total AM.
Lakor Himri
911,328
243,195
74,944
11,740
3,413
1,072
881
784
342
2,399
0
0
1,298,340
Total
AM. Cost
San. Sttf*.
1778,300
391,240
347,730
422,300
278,400
42,400
13,200
1,400
0
0
0
0
42,717,190
•SUSUUMS
Total
AM, Coit
Su. far*.
44,447,740
1,044,740
177,730
113,230
40,800
2,000
400
44,321,700
Total Cost
for Sfitta
PIT Voar
41,740
1,740
1,930
1,111
400
400
400
400
400
400
400
400
110,421
•*»«•»••*«
Total Cost
Ptr Sfitti
Por Itir
41,740
1,741
1,930
1,930
3,140
7,480
14,480
21,480
32,480
41,480
91,884
144,280
4318,440
Total
AnwaliiH
Cost
415,310,300
11,942,200
3,004,410
4,473,840
271,400
42,000
13,200
1,400
0
t
0
0
419,291,170
SBMSMSMMS
Total
Aamaliico'
Cost
417,471,440
24,482,480
7,733,310
1,319,450
523,180
97,580
78,940
44,840
12,280
211,780
0
0
4122,247,100
-------
T8ML COSTS i BURKI OF MW1IMIIH FOR 6MUMM1EI SYSTEM
NO FLEIIIILITT
GO
I •*=»»«••**»•«
IMJ. 6MUMMUTU
Sin Cattforf
23-100
101-500
901-1000
1001-3300
I300-IOK
tows*
23X-SOK
90X-7SK
75K-IOOK
10W-500K
900K-I NIL
OVER 1 NIL
1 Total
SYSTEM
Nvtbir
o«
Systfti
114
44
13
4
1
181
,138
,032
,444
,113
,04?
182
4»
10
2
7
0
8
,824
Total 8
Additional
Saofln
4,303,728
2,449,792
732,974
349,314
32,292
4,372
9,234
4,434
2,152
14,232
0
•
10,132,772
w»H*«**>*»*
Cost of
MfitiMi!
No*itoriii|
97
34
It
9
132
,333,920
,984,880
,294,440
,479,740
484,380
93,380
78,540
49,840
32,280
213,780
0
0
,291,580
Total Mi,
Labor HOUM
1,094,377
414,993
124,724
41,483
9,433
1,072
881
784
342
2,399
0
8
1,708,712
""*"
«*aU*
total
fan. Cost
Su. Suf¥.
(5,224,240
1,438
1,443
333
319
44
IS
1
19,245
••••••I
,000
,500
,750
,200
,000
,400
,400
0
0
0
0
:!!!.,
Total Cnt
fir Syitet
ttr T«ar
13,480
3,480
3,840
3,740
1,340
7,880
15,080
24,080
33,080
41,880
94,280
144,480
0399,080
Total
AonoaliitJ
CMt
0102,782,
38,424,
12,740,
4,013,
803,
159,
94,
71,
MI
«3,
140
BOO
140
490
380
380
140
440
280
780
0
0
0141,537,470
«•»*••«•••*»
-------
TOTAL COSTS I MROa OF MMITOftM FOR COLIflfttt
NORSI CASE SCENMIft - NO MHI1MIMI FUIIIILIT1
vO
m*mxn*xmmmmmmm*****mm**
COMMITY NATO SVSTEHB
hut if of
Sin Cattoory Sfitnt
29-100
101-500
501-1000
1*01-1300
IIOO-IOK
IOK-2SK
2SK-30X
50K-73K
TSK-IOOr
IOOK-SOOK
SOOT-I NIL
ova i NIL
mil
11,731
11,014
4,777
7,4M
4f4
133
n
•
32,121
mmmmmmmnt
Mil 1
MlltlMll
Saifln
1,031,341
m.no
347,332
344,061
2,742,10*
••»«•••••••••
Total Co*t
of AM.
NonitariM
113,370,140
14,170,100
3,313,200
3,441,320
141,431,340
!**•«***** «•*!
*»*M*mmxx*MXU
Total Mi.
lakor Howt
174,707
I44,t40
41,831
41,274
444,842
I»M*M»*B*B
Util Tatil
All. CMt «MB4lllt<
SM. Swv. Celt
1770,300
311,240
347,730
(22,300
270,400
42,000
13,200
1,400
0
0
0
0
$2,717,170
MMMBMM*
114,134,440
13,470,040
4,001,030
3.M1.020
270,400
42,000
13,200
1,400
•
»
0
0
144,141,730
••• *••*••«•*«
*u****«*u*a
NON-COMKin IMTEI StSTEM
Silt Cattoary
23- I0»
101-300
301-1000
1001-3300
3300-IK
IOK-23K
23X-30K
50K-73K
75X-IOOK
IDOK-SOOK
SOOK-I MIL
OVER 1 NIL
IToUl
Nviktrol
Sfftiit
IOI,3f2
2T.IM
1,403
1,401
311
71
13
141,400
Total 0
Mlltioul
SaoylM
3,4lf,l32
1,443,304
470,400
W,0«
33,032
10,400
7,140
4,434
3,228
14,2*1
0
0
7,100,134
CMtOl
AdditlMll
NooitoriM
183,337,200
24,482,340
7,040,200
1,330,720
323,780
274,120
107,100
4f,840
40,420
244,320
0
0
$117,702, J«
Total Ht.
Lakor Howl
137,404
274,130
71,213
13,133
3,811
3,018
1,202
784
343
2,741
0
0
1,343,040
Ifltil
AM. Coit
SM. SUM.
14,447,740
1,044,740
177,730
113,230
40,800
2,000
400
14,320,700
Total
Anniiilliri
Coit
$01,703,020
23,721,320
7,137,130
1,443,170
344,380
278,120
107,300
41,840
40,420
244,320
0
0
$124,231,040
-------
COStS I OWKM OF MNUOftlM F« COLIFOWIS
CASE SCMAMO - NO MMUOJtltt FLEI18ILIU
,um»x»«**iunsa*Ki«a*»»uxa»»x>»»»»«»**«"*>l
iiu. VAU8 STSiens
1 Tetil 8 Cost el Total
1 (hub* of AMitinul MtltioMl lolil Ad.. Am. Cost
t Slit C«ttjor» Syittu S»«fl« HwiltoriM lakor Hours SM. Swv.
j
125-100
t 101-300
1 501-1000
1 1001-3100
1 1300-IOK
1 1W-23K
1 2SK-30K
isor-7»
t 73K-100K
1 IOOK-SOOC
1 300K-I ML
1 OVER 1 ML
1
ltat.1
120,343
47,400
15,182
1,210
1,077
233
S3
10
1
1
0
0
113,401
4,727,41* MOO.113,440
2,437,424
838,232
434,114
33,032
18,408
7,140
4,454
3,220
14,288
0
0
10,742,240
•••*•»•• n*
31,341,140
12,573,480
4,812,040
525,780
274,120
107,100
41,840
40,470
244,320
0
0
1141,133,100
1
Ttttl 1
AomitlUri 1
Cist 1
1,132,271 *1,224,240 «I04,I4I,400 1
443,878
141,074
71,43:
4,811
1,018
1,202
784
341
2,741
0
0
1,007,172
1,438,000
1,443,300
535,730
111,206
44,000
13,400
1,400
8
0
0
0
11,243,010
41,111,340 1
14,018,180 1
7,347,710 t
844,180 1
140,120 1
122,700 1
71,440 1
48,420 1
244,120 1
0 1
0 1
1
*I70.37!,710 1
-------
COSTS 1 NMEI V NONITMIM FM SMUMMUICR SVSTtlB
lUHOn tUIMFECIlW
1ITN rilllllLIIT
| auuxaunuu
MaMMBMi
•••••••• MKRU
MSMBMUl
asxazunrau
u»*m»uiu
uauananaa
ICOmUNIlY SMMOKATai SYSTEMS
Cost if Sufli Antlyslii
Sin Cattiory
23-100
101-300
301-1000
1001-3300
JJOO-IOK
IOK-23K
2SK-50K
30K-73K
7SK-IOOK
IOOK-300K
500K-1 NIL
OVER 1 NIL
Total
Nwltr of
SysttM
I2,)73
),854
2,271
I.4W
414
133
j|
27,481
iwi-conmmm BROUNOHATER
ISantlM
Currtitly
RttjirttVYr
4
4
4
1
)4
240
480
780
1,080
2,040
3,120
4,800
SYSTEMS
ProooM4 1
Saiplts
Ptr liar
12
14
40
40
)4
240
480
710
1,080
2,040
1,120
4,800
iKTMStf 1
if Saoilu
/Systtn/Vtar
1
12
34
32
Total 1
Adit tl mat
Saopltt
101,800
113,128
127,174
•7,880
8
0
0
0
0
0
0
0
414,184
AM. Cost
of (tail tor.
/Syst/Ytar
(120
480
840
780
113
Tital Cost
il AM.
Nonitoriii
11,337,000
4.721.WO
I.W7.440
1,118,200
laker Hours
Ptr Saitl*
0.1483
0.1483
0.1481
0.1481
AMltioMl
Labor Hours
PIT Systti
1.3
3.4
).
1.
f),3l2,740
Mat AM.
Laior Hours
17,470
33,070
21,404
14,7)0
104,731
Cost if Satilt Analysis*
Sin Cattiory
23-100
101-300
301-1000
1001-3300
3300-IWC
IOK-2SK
23K-30K
50K-7SK
75K-IOOK
IOOK-SOOK
300K-I NIL
OVER 1 NIL
ITotal
Nuiktr of
Systns
74,12)
17,444
1,311
431
102
3
1
0
0
0
0
0
TS.447
1 S»flti
Currently
ItiHirM/Yr
4
4
Propist. 1
Satflti
Ptr Ttar
12
34
40
40
)4
240
480
780
1,080
2,040
1,120
4,800
Incrtastl 1
of Sailltf
/systti/ytar
•
12
34
34
)2
214
474
774
1,074
2,014
1,114
4,7)4
Total 0
115
AM. Cost
AMitionil of Monitor.
Saitlts
3)1,012
338,272
1)4,414
23,141
),3B4
1,110
474
1,314,321
/Syst/Ytar
1120
480
640
840
1,180
1,340
7,140
II, 440
14,140
30,340
44,740
7I,)40
Cojt of
AMitloul
R»»itorli|
18,8)3,480
8,174,080
2,)4),240
380,520
140,740
17,700
7,140
120,744, 920
laior Hours
Ptr Satili
.1481
.1411
.1481
.1481
.1481
.1411
.1481
.1481
.1481
.1481
.1481
.1411
AMItlMal
labor Hours
Ptr Systn
1.3
3.4
1.
).
13.
1).
BO.
130.
181.
342.
524.
807.
Total AM.
Laior Hours
tt,S07
)1,M7
13,0)0
4,24)
1,37)
I))
80
Cost if
Saaltary
Sumy
300
100
730
750
,200
,200
,200
,200
,200
,200
,200
,200
Cost of
Sanitary
Sumy
NO
300
730
730
,200
,200
,200
,200
,200
,200
,200
,200
212,)I2 !
*""*****"***'*"""**"' ""***! I*****'******'*'"""""
M
II
II
1!
Rtptat Amualliri Tital II Total Cost Total
Uttrvil Cost PIT AM. Cost II Ptr Syttt* Annuillit*
(Ycarsl Systti S«. Sir*. II Ptr Ytar Cost
II • m -i i m * m mm
1100 11,2)7,300 II 4220 12,854,300
100 )83,400 !l 380 3,713,120
250 547,730 II 1,0)0 2,473,1)0
250 422,500 II 1,030 1,740,700
400 271,400 II 400 271,400
400 42,000 II 400 42,000
400 15,200 II 400 13,200
400 1,400 II 400 1,400
400 0 II 400 0
400 0 II 400 0
400 0 !! 400 0
400 0 II 400 0
II
13,430,350 II 113,143,110
'
II
!!
Rtptat Total II Total Cost Total
Interval Aniualiitd Am. Cast !l Ptr Systn Am.iUittf
(Ytarsl Cost Sa*. Surv. II Ptr Ytar Cost
3 100 I7.4I2.WO II 1220 114,108,180
1 100 1,744,400 II 380 10,118,480
1 230 877,730 II 1,0)0 3,824,))0
1 230 111,250 II 1,0)0 4)1,770
1 400 40,800 II 1,780 181,540
1 400 2,000 II 1,)40 l),700
1 400 400 II 7,540 7,540
1 400 0 II 12,040 0
1 400 01! 14,340 0
1 400 0 II 30,)40 0
3 400 0 II 47,140 0
1 400 0 I! 72,140 0
1 1
110,1)1,700 II I30,)54,420
-------
COSTS I WRKN OF MMITORIM FM 6MUNWMIER SYSTEMS
KIIHOUI HSIIKCTin
KITH FUIIIIUlt
******* *s««s**ssc£s*«sscsu*»»ss«na*
t«U GROUNNAIU STSIEHS
N>
Sitt GittfVf
25-104
101-500
301-100*
1001-3300
3300-10K
IOK-8K
2ST-SOK
3K-7SK
Tsr-ioor
lOOX-MOK
300K-I BIl
ova i in
Ihwkir ol
Systtts
17,104
27,300
5,782
2,14)
rn
140
Jf
4
0
0
0
0
Totil 1
AUitiMU
Sufln
ift.R]
97J,4ft
123,7?
111,24
f.M
1,111
47
Cost •(
1 UditiMil
IhMitorlit
2 *10,<32,WO
» 11,IM,WO
2 4,836,880
1 1,4*1,720
1 140,740
) 17,700
1 7,140
0
*
0
0
0
Total M
Uknr Hoar
117,27
147,02
34,41
lf,0i<
i,sr
ir
II
Total
. «M. Cflft
i Sad Surf.
7 U.710,400
7 2,730,000
1 1,443,300
) 333,750
1 llt.200
r 44,000
» IJ.MO
1,400
0
0
0
0
Total Cost
Ptr Syitt*
TV Ttar
0440
1,140
2,180
2,120
2,180
4,340
7,940
12,440
U,«0
31,340
47,340
72,740
Total
AMuili»4
Colt
lit, 142,880
13,814,000
4,302,180
2,214,470
43«,UO
11,700
22,7(0
1,400
0
•
8
1
(Total
123,310 2,018,312110,277,480 331,714013,822,030 1201,340 «4«,OW,730
••*«***»«•>•»*»«•*»«««***«•
-------
COS1S i MUCH If MNHIOHM F08 »OUNN»UI IIStEM
vm luimcnoN
NUN FlEIlllUTt
•nsacsMMMawttBUUBi
•MMMKOW
ICOMMMITT ttOUNMMIEl SYSTEMS
Cost ol Saoolt ftoalysiu 113
Site Cattoory
23-100
101-500
501-100*
1001-330*
3300-IOK
IOK-25K
23K-50K
SOK-7SK
75K-IOOK
IOOK-500K
I.500K-I MIL
OVER 1 R1L
total
1 Saoolts
Ruoktr it Cwrittly
Sytttts Rtfuirtl/Yr
4,325 4
1,040
3,011
3,713
0
0
17,131
NON-COKNUNITY 6MUNMMTE8 SYSTEMS
Protosto' 8 iBcrtiiif 1
SMI Its ol Saoolts
rtr Vtv /Syitta/Ytar
12
12
31 3
31 2*
vn*fnntm«3roxa»sm
Total 1
Mlitlonat
tuples
34,100
48,320
11,332
103,314
284,131
Ut. Cost Total Cost
ol Hooitor. ol Ut.
/Syst/Ytar Root tor lot
1120 1311,000
120 724,800
489 1,443,28*
420 1,380,410
14,211,340
Lakor Hours
rtr Saooli
0.1181
0.1413
0.1413
0.1181
Mlitiooal
lakor Houri
*tr Systto
1.
1.
3.
4.
Total Ut.
Lakor Hours
3,823
8,132
11,211
17,733
47,104
Cost ol Saaolt taalysisi 115
Slit Catttory
25-100
101-500
501-1000
1001-3300
3300-IOK
10K-23K
23K-30K
SOK-73K
73K-IOOIC
100K-500K
300K-I NIL
OVER 1 HIL
ITotal
1 Saoolti
Huoktr ol Currently
Systtts Rttuirri/Yr
21,701 4
10,1*2
4,133
1,007
241
22
10
1
2
7
0
I
41,357
rrooosto' 1 iKrtmf- 8
Saaplts ol Saoplts
rtr Ytw /Systti/Ytar
12 8
12 8
31 32
31 32
11 12
240 231
480 471
780 771
1,080 1,071
2,040 2,031
3,120 3,111
4,800 4,711
Total 1
feUitlMll
SaoylM
117,172
83,331
148,811
32,224
22,108
3,112
4,740
4,131
2,132
14,232
0
0
318,248
Ut. Cost Total Cost
ol Hooitor. ol Ml.
/Syst/Ytar RMitori*|
1120 12,113,080
120 1,283,040
480 2,233,440
480 483,310
1,380 343,120
3,54* 77,880
7,140 71,400
11,440 11,840
11,140 32,280
30,540 213,780
44,740 0
71,140 0
17,773,720
Lakor Hours
rtr Saoplt
.118)
.1183
.1183
.118)
.1183
.1183
.118)
.1183
.1183
.1183
.1483
.1483
Lakor Houri
rtr Systti
1.3
1.3
3.4
3.
13.
31.
80.
130.
181.
342.7
324.4
807.2
Total Ut.
lakor Hours
33,218
14,311
23,05*
5,421
3,833
874
801
784
312
2,311
«
0
87,221
Cost ol
Saiitary
Sumy
30*
300
730
750
Cost ol
Saiitary
Sumy
1300
300
750
750
,200
,200
,200
,200
,200
,200
,200
,200
II
II
II
Rtatat AnMallto*: Total II
lottrtal Cost rtr AM. Cost II
(Ytarsl Systto Sao. Surv. II
110 1251,500 II
10 312,400 II
IS* 431,130 II
ISO 314,430 II
II
II
II
II
II
II
I!
II
II
11,131,000 II
'
II
1!
II
fttptat «Muallit< Total II
lottrval Cost rtr «M. Cost II
(Ytarsl SystM Sao, Surv. II
10 11,482,340 II
10 141,320 II
ISO 117,130 11
ISO 131,030 II
II
II
II
II
II
11
II
II
II
12,173,010 II
Total Cost
rtr Systto
rtr Year
1180
180
130
37*
Total Cost
rtr Systto
r*r Ytar
1180
180
130
130
1380
3540
7140
11140
11140
30340
44740
71140
total
Muni lilt-
Cost
1778,500
1,087,200
1,811,130
2,144,110
0
13,107,540
Total
Annual 1 in-
cest
14,447,120
1,124,340
2,131,310
134,410
343,12*
77,880
71,400
11,840
32,280
213,780
0
0
110,741,780
-------
I—"
-IS
COSTS I 8URKI OF MMUOIIW FM (ROUKMMTQI SVSIEHS
NIIH 81SINFECT10H
KITH FLEII1IL1TI
IM.L 6MUNMMTER
SYSTEMS
Total 8
NMkir ol MOtional
Sin Catcfory
23-100
101-500
301-1000
1001-3300
3300-IOK
IOK-2SK
25K-3K
SOK-75K
7SK-100K
IOOK-300K
500K-1 MIL
OVE8 1 ML
ITotal
Imrauunnx
SfltMl
21,034
14,732
7,444
4,770
241
22
10
4
2
7
0
0
38,414
SatplM
232,272
133,854
245,248
137,388
22,908
5,112
4,740
4,434
2,152
14,232
0
0
802,884
•sasssssna
Cost ol
MCitioMl
HnitorlM
13,484,080
2,007,840
3,478,720
2,043,820
343,620
77,880
71,400
41,840
32,288
213,780
0
0
12,043,240
Total Ui.
lakor Hour*
31,011
22,528
41,273
23,154
3,853
874
801
784
342
2,311
8
0
133,123
Total Total Coit
AM. toft Per SystM
Sa». SUM. Per Ttar
01,742,040 1340
1,003,120 340
1,141,400 1,240
713,300 1,200
1,380
3,540
7,140
11.440
14,148
30,540
44,740
71,140
14,411,040 1112,240
Total
*MU*Uiri
Cott
13,224,120
3,011,740
4,828,328
2,771,320
343,420
77,880
71,400
41,840
32,280
213,780
8
0
114,454,320
-------
TOTAL COSTS
i SUROEN OF HDNITORIM FOR 6ROUNHMTE8 SYSTEMS
HUH REII81LITY
[ HBSSM SSMit *•««•»«•«•»•»*•»***«•**•
ICOmUMIIY SMMUNATER SYSTEMS
Total 8
Silt Cattoory
25-100
101-500
301-1000
1001-3300
3300-10K
IOK-2SK
2SK-SOK
50K-75K
73K-IOOK
IOM-50K
SOOK-I MIL
OVER I MIL
Total
**************
MMktr of
Systoos
17,300
13,894
5,282
5,453
194
155
38
44,822
RSM»Ha*B«
NON-CONUim 6ROUWHMIER
Site Catifory
25-100
101-300
301-1000
1001-3300
JJOO-101C
IOK-2SK
2SK-50K
30K-73X
75K-IOOK
IOOK-500K
500K-1 MIL
OVER 1 MIL
Uotal
Nuottr o<
Syitnt
98,838
28,138
8,164
1,440
331
27
II
4
2
7
0
0
137,004
AMitlonal
Saoflci
138,400
343,048
223,528
193,244
918,820
************
SYSTEMS
Total 8
AMitlooal
Siifltt
790,704
443,808
345,312
57,392
32,292
6,372
3,236
4,434
2,132
14,232
0
0
1,902,374
Total Coit
ol AM.
Monitor!*!
12,074,000
3,434,720
3,332,920
2,898,640
113,702,300
8MKMHMSBI
Total Coit
ol AM.
IhMitorUi
Ml, 860,540
9,637,120
5,182,480
843,880
484,380
93,380
78,340
49,840
32,280
213,780
0
0
128,538,440
Total AM.
taker Houri
23,293
41,202
37,420
32,523
134,437
'»»«•»•"•"»
Total AM.
Ltlor Hoort
133,071
108,333
58,130
9,493
3,433
1,072
881
784
342
2,399
0
0
320,204
Total
Aoo. Coit
Si*. Surv.
01,557,000
1,347,800
1,019,400
984,950
271,400
42,000
15,200
1,400
0
0
0
8
13,248,330
************
Total
AM. Coit
Sao. Sw».
,8,899,448
2,384,120
1,575,700
244,300
40,800
2,000
400
0
0
0
0
0
113,144,740
Total Coit
Per Syttco
Por Ytar
1400
740
1,720
1,400
400
400
400
400
400
400
400
400
i***********
Total Coit
Per Syitto
Per Yoar
1400
740
1,720
1,720
3,140
7,480
14,680
23,480
32,480
41,480
93,880
144,280
»3B5,920
Total
AMualiiri
Coit
13,433,000
4,802,520
4,372,320
3,885,410
278,400
42,000
15,200
1,400
0
0
0
0
119,050,430
************
Total
(Mvaliittf
Coit
120,754,000
12,043,240
4,758,380
1,128,180
523,180
97,580
78,940
49,840
32,284
211,780
0
0
«4I, 705,400
-------
HIM. COSTS I WRKN OF MMITMIN6 FM SUUMIMIER StSUItS
HIM FIHIIILIIY
SM4. 6ROUNDMTEI SfSIEHS
Kuibtr oi
Slit Category Syitm
21-100
101-500
SOI-10M
1001-3300
1MO-IOK
IMC-23K
2X-SOK
SOK-7X
WHOM
lOOK-SOW
SOOK-I Nil
OVER 1 NIL
IT«UI
I ••*•••••••*••••»
IU.13I
4«,032
11,444
*,»I3
1,04?
192
4T
' I*
2
7
0
0
111,824
Total 1 Cut of Total lotal Cost Total
Mfltlona! Udditiootl Total Md. fcw. Cost Ptr SystM «jumalin4
Supln Hoflltori«| iapr Houri Sw. Surv.
f2f,!04 »l3,»Ji,5M
1,007,454 IS,IIIIB4»
54»,040 I,S33,MO
230.U4 3,742,540
12.2T2 414,380
4,372 M,5M
9,23i 78,340
4,434 4f,840
2,132 32.2H
14,232 213,780
0 0
• 0
2,121, 3U M2,320,T40
134,348 410,452,440
1H.553 3,713,120
H,74f 2,3n,IOO
42,214 1,231,230
9,413 3lt,200
1,072 44,000
881 13,400
784 1,400
342 0
2,3tt 0
0 0
« 0
474,841 111,413,110
fit Yltf Colt
4800 *24,1B?,000
1,320 18,843,740
3,440 II.IM.700
3,120 3,«l3,nO
3,340 801,380
7,880 l3t,3N
13,080 f4,!40
24,080 71,440
11,080 12,280
41,880 213,780
H.2BO 0
144,480 0
llf],400 140,734,030
-------
t
h->
«J
TOIM. COSTS I WIDER OF RMITDRIM FOR COLlfOWB
REST CASE SCEHMIO - KM1IUI RDUTDR1HB rUMHLIHf
;nuMB»nuuu*»»**>»
lOHMMlIY HATER SYSTEMS
I
I
I
I Nubfr ol
i Sin Cattoory Syitttt
I 23-100
I 101-500
Totil 1
MdiUoul
Suit"
Cost tl
ftMitiMal Total AM.
HooUoriii Lakor Howl
Total
*M. Cmt
SM. Stirv.
tamullit* 1
Ce$t t
I 301-1000
I IOtl-1100
t 3100-IOK
I IOC-2SK
I 23K-30K
I 30K-7SK
I TX-tOOK
I IOOK-300K
t SOOK-l NIL
I OVER I NIL
t
I Total
(«asa
16,731
18,014
4,777
7,490
494
133
38
52,129
WTER SVSIEIIS
I
I
t
t
t
I Silt Cattfory
1
! 23-100
I 101-300
: 301-iooo
I 1001-3300
I 3100-IM
! IMC-23K
I 25K-30X
I 30K-75K
t 75K-100K
I IOOK-SOOK
', SOOK-l NIL
I OVER I NIL
I
I Total
,144 3,122,140 33,031 (1,357,000
,504 4,982,340 76,144 1,347,800
1,288 4,429,320 49,497 1,019,400
1,774 4,104,410 44,077 984,930
278,400
42,000
13,200
1,400
0
0
0
0
2,712 118,440,480 209,148 13,248,330
MBBBMBM
14,479,140 1
8,310,340 1
3,448,720 1
3,093,390 i
278,400 1
42,000 1
13,200 t
1,400 1
01
0 1
0 1
0 1
1
123,909,030 1
•»**•••*«•••• |
1
1
Total I
ol Additional
SyttiM Satplti
Cost ol
Mfittoiul Total Mi.
toil torl«j Labor Hourt
101,392
29,384
8,403
1,408
381
78
15
944,928
711,384
139,008
43,660
13,052
18,408
7,140
4,434
3,226
14,288
0
0
114,171,920
10,701,740
3,383,120
988,200
323,780
274,120
107,100
49,840
46,420
244,320
0
0
159,031
120,094
40,421
11,068
3,699
3,098
1,202
784
343
2,741
b
0
Total
ADR. Cost
Sao. SUM.
18,693,440
2,184,120
1,573,700
244,300
40,600
2,000
400
0
0
0
0
0
I
Total I
Annual in* I
Coit I
021,049,140 I
11,089,860 I
4,940,820 I
1,232,300 !
544,3601
278,120 I
107,300 I
49,840 I
48,420 t
244,120 t
0 I
0 I
I
141,480 2,148,172 112,522,380 144,901 111,144,740 I45.487.340 I
-------
WT* COSTS I MMEN OF MMIIORIW FOR COtlFORflS
KST CASE SCENARIO - MI1NM MNITMIN8 FUIIIUUY
l-«
00
1*11 MIER SISTERS
NiMbtr oi
Slti Catiiory
25-100
101-500
501-1000
1001-1100
HOO-IOK
IOX-2SK
25K-50K
SOK-7SX
7SK-IOW
IOOK-SOOK
500K-1 NIL
OVER 1 RIL
Total
Syttcas
120,145
47,400
IS, 112
9|29I
1,077
211
51
10
1
1
0
0
191,609
Totil 1
Mditiooal
Cost ol
MditlMil Total Ml.
Sattlts Honitori*| Likor Hours
1,151,072
1,179,081
454,294
139,454
15,052
11,401
7,140
4,454
1,221
14,281
0
0
1,410,814
$17,794,000
17,414,120
9,814,440
3,0*4,840
325,780
274,120
107,100
49,840
48,420
244,120
0
0
151,141,240
194,042
191,441
110,118
57,144
5,199
1,098
1,202
784
34)
7,741
0
0
374,052
Totil
MM. Cost
S». Surv.
110,452,440
1,711,920
2,595,100
1,251,250
119,200
44,000
15,400
1,400
0
0
0
0
118,411,110
X«*S* ••*••»*
Total
AMUilllttf
Cost
$27,741,520
21,420,240
12,499,540
i.144,090
I4«,*SO
140,120
122,700
71,440
41,420
244,120
0
0
»4f,594,170
-------
APPENDIX E
SYSTEM LEVEL BREAKEVEN ANALYSES
FOR 15 LARGE SYSTEMS
-------
2
4*
I/I
I/)
2
i_j
UJ
TREATMENT COST VS. ENDEMIC DAMAGES
80
70 -
60 -
50 -
40 -
30 -
20 -
10 -
BOSTON, MA
0.2 0.4 0.6 0.8 1 1.2 1.4
ENDEMIC LEVEL (X OF POP/YR)
1.6 1.8
TREATMENT COST VS. OUTBREAK DAMAGES
(A
BOSTON, MA
30 -
20 -
10 -
0.005 0X11 0.01« 0.02 0.025 0.03 0.035 0.04 0.045 0.05
ANNUAL P(OUTSREAK) (X)
E-l
-------
BOSTON, MA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 19.63
Damages -from Endemic Level of 17. 37.966
Damages -from A Representative Outbreak 1361.614
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-19.
0.0
0. 1
0 . 2
0 . 3
0.4
0.5
0.6
0.7
0. 8
0.9
1 . 0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-20
-16
-12
-8
-4
— 1
•I>
7
11
15
13
22
26
30
34
37
41
45
49
53
56
0.005
4 T
I •-.'
-9
—5
-1
*-\
6
10
14
13
21
25
29
•->•!'
37
40
44
43
52
56
59
63
0.01
-6
-2
2
5
9
13
17
21
24
28
32
36
40
43
47
51
55
59
62
66
70
0 . 02
8
11
15
19
23
27
30
34
38
42
46
49
53
57
61
65
68
72
76
80
84
0.03
21
25
29
. j. ,^>
36
40
44
48
52
55
59
63
67
71
74
78
82
86
90
93
97
0.04
35
39
42
46
50
54
58
61
65
69
73
77
ao
84
88
92
96
99
103
107
111
0 . 05
48
52
56
60
64
67
71
75
79
83
86
90
94
98
1O2
105
109
113
117
121
124
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 19.63
Damages -from Endemic Level of 17. 28.13
Damages from A Representative Outbreak 558.975
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
-19.
0.0
0 . 1
0 - 2
0 . 3
0.4
0.5
0 . 6
0.7
0.3
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-20
-17
-14
-11
-8
-6
— 3
0
T;
6
9
11
14
17
20
*"?T
25
28
31
34
37
O.OO5
-17
-14
-11
—8
-6
— "^
•-»
0
c»
6
a
11
14
17
2O
*">~T
•h_'»'
25
28
31
34
37
39
0.01
-14
-11
-8
-6
""•-•
0
3
6
8
11
14
17
20
•"?"?
25
28
31
34
37
39
42
0.02
-8
-6
—3
-0
3
6
8
11
14
17
20
22
25
23
31
34
37
39
42
45
48
0.03
-3
-O
3
6
8
11
14
17
20
22
25
28
31
34
37
39
42
45
48
51
53
0.04
O*
6
8
11
14
17
20
22
25
28
31
34
36
39
42
45
48
51
53
56
59
O.O5
8
11
14
17
20
22
25
28
31
34
36
39
42
45
48
51
53
56
59
62
65
E-2
-------
BOSTON, MA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-F Filtration 18,34
Damages -from Endemic L^vel o-f 17. 37.. 966
Damages from A Representative Outbreak 1361.614
ANNUAL PROBABILITY OF OUTBREAK
£
N
D
E
M
I
C
L
cr
V
E
L
-13.
0.0
0. 1
0.2
0.3
0.4
0.5
O.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.3
1.9
2.0
0
-19
-15
-11
-7
-4
0
4
8
12
IS
19
f~\~?
4^0
27
31
34
33
42
46
49
53
57
0 . 005
-12
-8
-4
-1
^T
7
11
15
18
(">*T*
26
30
34
37
41
45
49
53
56
60
64
0 . 0 1
-3
-1
»7
6
10
14
ia
21
25
29
•;>•->
37
40
44
49
52
56
59
63
67
71
0.02
3
12
16
20
24
27
31
35
39
43
46
50
54
58
62
65
69
73
77
81
84
0 . 03
T^
*--i-
26
30
•-'•j'
37
41
45
49
52
56
60
64
68
71
75
79
S3
37
90
94
99
0 . 04
36
39
43
47
51
55
53
62
66
70
74
77
81
95
Q9
93
96
100
104
103
112
0.05
49
53
57
61
64
68
72
76
80
93
37
91
95
99
102
106
110
114
118
121
125
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost Q-f Filtration 18.84
Damages from Endemic Level o-f IV. 28.13
Damages from A Representative Outbreak 558.975
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
-18.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-19
-16
-13
-10
-8
-5
-»*"?
1
4
6
9
12
15
18
21
23
26
29
T***
•-'-i.
35
37
O.005
-16
-13
-10
-8
-5
_'^
1
4
6
9
12
15
18
21
•?-?*
26
29
T*1
•_>-i-
35
37
40
O.O1
-13
-10
-a
-5
_O
4U
1
4
6
9
12
15
18
21
*-!•»
*-'~'
26
29
32
35
37
4O
43
0.02
-8
-5
_O
•1
4.
4
6
9
12
15
18
20
23
26
29
32
35
37
4O
43
46
49
0 . 03
-2
1
4
6
9
12
15
IS
20
23
26
29
T">
•-j**^
34
37
40
43
46
49
51
54
0.04
4
6
9
12
15
18
20
23
26
29
32
34
37
40
43
46
49
51
54
57
60
O.O5
9
12
15
18
20
23
26
29
^T1""*
•—*-;.
34
37
40
43
46
43
51
54
57
60
63
65
E-3
-------
BOSTON, MA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
0 . C'
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 . 0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
o
1
2
4
4
4
4
4
4
4
4
4
4
4
4
0 . 005
0
0
0
0
2
2
4
4
4
4
4
4
4
4
4
4
4
4
4
0.01
o
o
2
2
2
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0 . 02
**}
r»
*"?
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0 . 03
2
TT
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0. O4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0 . 05
q
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
E-4
-------
in
I
ifl
W
2
tf
4.5
TREATMENT COST VS. ENDEMIC DAMAGES
PORTLAND. ME
4 -
15
3
2.5
2
1.5 •
1 -
0.5-
0.2 0,4 0.6 0.8 1 1.2
ENDEMIC LEVEL (JC OF
1.4 1.6
I
1.8
I
M
ut
TREATMENT COST VS. OUTBREAK DAMAGES
4.5
PORTLAND, ME
4 -
3.5 -
3
2.5
2
1.6
1 -
0.5 -
0.005 0.01 0.015 '0X12 0.025 0.03 0.035 0.04 0.045 0.05
ANNUAL f>(OUTBR£AK) (X)
E-5
-------
PORTLAND, ME
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-F Filtration 2.17
Damages -from Endemic Level o-F 17. 2.021
Damages -from A Representative Outbreak 80.618
E
N
D
E
M
I
C
L
E
V
E
L
-2. 1
O.O
0. 1
0.2
0.3
0.4
O.5
O.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
ANNUAL PROBABILITY OF OUTBREAK
0
•2.
2
•2
2
•1
1
•1
1
•1
•0
•0
0
0
0
1
1
1
1
1
0.005
_^v
-2
-1
-1
-1
-1
w 1
-0
-0
0
0
0
1
1
1
1
1
2
2
0.01
-1
-1
-1
-1
-1
-0
-0
o
0
0
1
1
1
1
1
2
2
2
2
0 . 02
-1
-0
-0
0
0
0
1
1
1
1
1
2
2
2
2
2
3
•^
3
O.03
0
0
1
1
1
1
1
2
2
2
2
2
3
3
T;
3
3
4
4
0.04
1
1
1
3
3
4
4
4
4
4
2.0
.;•
3
4
4
0 . 05
T
3
3
4
4
4
4
4
5
5
5
5
5
6
6
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 2.17
Damages -From Endemic Level o-f 17. 1.523
Damages -from A Representative Outbreak
32.62!
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2. 1
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-2
-2
— O
-2
-2
-1
-1
-1
-1
-1
-1
-O
-0
-0
-0
o
0
0
1
1
1
O.005
-2
-2
-2
*-i
£.
-1
-1
-1
-I
-1
-1
-0
-0
-0
-0
o
(I)
0
1
1
1
1
0.01
— *>
— O
-2
— 1
-1
-1
-1
-1
-1
-0
-0
-0
-0
0
0
0
1
1
1
1
1
0.02
— o
-1
-1
-1
-1
-1
-1
-o
-o
-0
o
0
0
0
1
1
1
i
1
1
^
0.03
-1
-1
-1
-1
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-0
-0
-0
0
o
0
0
1
1
A
1
1
1
1
2
r>
T*
0 . 04
-1
-1
-1
-0
-0
-0
0
0
0
1
1
1
1
1
1
1
o
t>
f^t
'••>
o
0.05
-1
-0
-0
-0
0
0
0
1
1
1
1
1
1
1
*7»
^
*~
2
2
•?
T>
3
E-6
-------
run: i UHIVL/ , IMC.
LOW TREATMENT COST - HIBH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.24
Damages from Endemic Level o-f I'/. 2.021
Damages -from A Representative Outbreak 80.618
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.2
0.0
0. 1
0.2
0.3
0.4
O.5
0.6
0.7
o.a
0.9
1 . 0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1
iir <
-1
-1
-0
-0
-0
0
0
1
1
1
1
1
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2
2
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2
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0.005
-1
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0
o
1
1
1
1
1
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2
2
2
o
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•«•
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Z
O.O1
-0
-0
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0
0
1
1
1
I
1
2
2
2
2
2
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3
•-•
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4
0.02
0
1
1
1
1
1
2
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2
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3
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3
4
4
4
4
4
0.03
1
1
r»
£.
o
4^
r»
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"^
•— •
..!>
-^1"
•— •
3
4
4
4
4
4
5
5
5
5
0 . O4
O
^
4^.
^>
O
3
3
3
•j>
4
4
4
4
4
5
5
5
5
5
6
6
6
0.05
w
3
3
T
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4
4
4
4
4
5
5
5
5
5
6
6
6
6
6
7
7
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-F Filtration 1.24
Damages from Endemic Level o-f 17. 1.523
Damages -from A Representative Outbreak
32.625
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.2
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
0
-1
-1
-1
— 1
-1
-0
-0
-0
-0
0
0
0
1
1
1
1
1
1
2
2
0.005
-1
-1
-1
-1
-0
-0
-0
-0
0
0
0
1
1
1
1
1
1
o
o
"%
X.
0.01
-1
-1
— 1
-0
-0
-0
0
0
0
0
1
1
1
1
1
1
o
2
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2
0.02
-1
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0
0
0
0
1
1
1
1
1
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ji.
2
^
ra
0.03
-0
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0
0
0
1
1
1
1
1
1
1
2
f^
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2
^
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2
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0.04
0
0
0
1
1
1
1
1
1
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^
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3
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3
0.05
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1
1
1
1
1
1
1
•?
2
2
2
"^
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•-•
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3
•-•
3
•j>
2.0
E-7
-------
PORTLAND, ME
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
0.0
0. 1
0.2
O.3
O.4
O.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
l.B
0
o
o
0
0
0
0
0
1
1
o
2
3
3
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3
4
4
4
4
0 . 005
0
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0
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1
1
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3
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4
4
4
4
4
0 . 0 1
0
0
0
1
1
1
2
3
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3
3
4
4
4
4
4
4
0 . 02
1
1
1
1
•^f
•— •
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3
3
4
4
4
4
4
4
4
4
4
0 . 03
<-i
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3
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3
T_
4
4
4
4
4
4
4
4
4
4
4
0 . 04
•^
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1 ^t
4
4
4
4
4
4
4
4
4
4
4
4
4
0 . 05
3
-T
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4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
E-8
-------
^•^
I
M
Ul
Q
TREATMENT COST VS. ENDEMIC DAMAGES
NEWARK, NJ
0.4
0.6 O6 1 1.2
ENDEMIC LEVEL (X OF POP/YR)
1.4
1.6
1.8
X^
I
01
TREATMENT COST VS. OUTBREAK DAMAGES
NEWARK, NO
0.01 S 0.02 0.02S 0433
ANNUAL P(OUTBREAK) (X)
E-9
O.O46 0.05
-------
NEWARK, NJ
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 3.86
Damages -from Endemic Level of 17. 9.618
Damages from A Representative Outbreak 345.861
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
_-T O
"~ -~f • O
0 . 0
0.1
O.2
O.3
O.4
O.5
0.6
0.7
O.8
O.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-4
-3
_O
-1
-0
1
2
• ~j
4
5
6
7
3
9
10
11
12
12
13
14
15
0 . 005
..T*
-1
-0
1
*^>
•Zf
4
5
6
7
7
8
9
1O
11
12
13
14
15
16
17
O.O1
-0
1
r>
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
IB
19
0.02
•'j
4
5
6
7
8
9
10
11
12
13
14
15
16
17
17
18
19
20
21
22
0.03
7
7
8
9
10
11
12
13
14
15
16
17
18
19
2O
21
22
23
24
25
26
0.04
10
11
12
13
14
15
16
17
18
19
20
21
22
22
23
24
25
26
27
28
29
0.05
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
•^*n
*J»j£.
33
HIBH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cast of Filtration 3.86
Damages from Endemic Level of 17. 7.244
Damages from A Representative Outbreak
142.874
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-3.8
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
l.l
1.2
1.3
1.4
1.5
1.6
1«_
.7
I —
.8
I.—
.9
^
«.o
0
-4
""•i>
—2
-2
-1
-0
0
1
•>
•Zf
•i
4
5
6
6
7
8
8
9
10
11
O. 005
™"-j>
_2
_2
-1
-0
0
1
2
O
•— •
4
5
6
6
7
a
8
9
10
11
11
0.01
— T>
— *7
-1
-0
0
1
2
"T
•_•
T
W
4
5
6
6
7
8
a
9
10
11
11
12
0.02
-1
-0
0
1
2
3
3
4
5
6
6
7
8
8
9
1O
11
11
12
13
13
0.03
0
I
2
3
3
4
5
5
6
7
8
3
9
10
11
11
12
13
13
14
15
0 . 04
2
3
3
4
5
5
6
7
8
8
9
10
11
11
12
13
13
14
15
16
16
0.05
3
4
5
5
6
7
8
8
9
1O
11
11
12
13
13
14
15
16
16
17
18
E-10
-------
NEWARK, NJ
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.94
Damages -from Endemic Level o-f IX 9.618
Damages -from A Representative Outbreak "
545.861
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.9
0.0
0. 1
O.2
O.3
0.4
0.5
O.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
"""•j»
-2
-1
-0
1
"^
•j*
4
5
6
7
8
9
10
11
11
12
13
14
15
16
O . O05
-1
-0
1
2
o
4
5
6
6
7
8
9
10
11
12
13
14
15
16
17
18
0.01
1
1
2
3
4
5
6
7
3
9
10
11
12
13
14
15
16
17
18
19
20
0 . 02
4
5
6
7
3
9
10
11
12
13
14
15
16
16
17
18
19
20
21
"?r>
23
0. 03
7
8
9
1O
11
12
13
14
15
16
17
18
19
20
21
'•^'-l
*L,*±
OT
Jim'mf
24
25
26
27
0 . 04
11
12
13
14
15
16
17
18
19
20
21
21
22
23
24
25
26
27
28
29
30
0.05
14
15
16
17
18
19
20
21
*T»O
23
24
25
26
27
28
29
30
31
32
•— ' •— '
34
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.94
Damages -from Endemic Level o-f IX 7.244
Damages -from A Representative Outbreak
142.874
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.9
O.O
0. 1
0.2
"0.3
0.4
O.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
—3
-2
-1
-1
-0
1
1
2
•— •
4
4
5
6
6
7
3
9
9
10
11
12
0.005
-2
_2
-1
-0
1
1
<7»
•jf
4
4
5
6
6
7
B
9
9
10
11
12
12
0.01
-2
-1
-0
1
1
2
'Lf
4
4
5
6
6
7
a
9
9
10
11
12
12
13
0 . 02
-0
1
1
2
T
4
4
5
6
6
7
8
9
9
10
11
12
12
13
14
14
0.03
1
2
3
4
4
5
6
6
7
8
9
9
10
11
11
12
13
14
14
15
16
0.04
3
3
4
5
6
6
7
a
9
9
10
11
11
12
13
14
14
15
16
17
17
0.05
4
5
6
6
7
8
9
9
10
11
11
12
13
14
14
15
16
17
17
18
19
E-ll
-------
NEWARK, NJ
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0
0.005
0.01
0.02
0. 03
0.04
O.O«
E
N
D
E
M
I
C
L
E
V
E
L
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
O.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
o
0
0
0
1
w
4
4
4
4
4
4
4
4
4
4
4
4
4
0
0
1
2
TJ
4
4
4
4
4
4
4
4
4
4
4
4
4
4
1
*"?
O
•— '
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
O
•-'
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
A
•4
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
E-12
-------
TREATMENT COST VS. ENDEMIC DAMAGES
NEW YORK, NY
220
in
6
ia
ENDEMIC LEVEL (36 OF PQP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
NEW YORK. NY
210
HI
I
0.005 0.01
0.015 '0.02 0.025 0.03
ANNUAL P(OUTBREAK) (X)
E-13
0.035
0.045 O.OS
-------
INC.W T onr-., TVY
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 77.07
Damages from Endemic Level o-f IX 105.746
Damages -from A Representative Outbreak 4168.481
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-77.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-77
-66
-56
-45
-35
-24
-14
— »^T
8
18
29
39
50
60
71
82
92
103
113
124
134
0 . 005
-56
-46
-35
-25
-14
—3
7
18
28
39
50
60
71
81
92
102
113
124
134
145
155
0.01
—35
-25
-14
-4
7
17
28
39
49
60
70
81
92
102
113
123
134
144
155
166
176
0.02
6
17
27
38
49
59
70
80
91
101
112
123
133
144
154
165
175
186
197
207
218
0.03
48
59
69
80
90
101
111
122
133
143
154
164
175
185
196
207
217
228
238
249
259
0.04
90
100
111
121
132
143
153
164
174
185
195
206
217
227
238
248
259
269
280
291
301
0 . 05
131
142
153
163
174
184
195
2O5
216
227
237
248
258
269
279
290
301
311
322
332
343
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 77.07
Damages -from Endemic Level o-f IX 79.11
Damages from A Representative Outbreak 1658.549
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-77.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-77
-69
-61
-53
-45
-38
-30
-22
-14
-6
2
10
18
26
34
42
50
57
65
73
81
0 . 005
-69
-61
-53
-45
-37
-29
-21
-13
-5
2
10
18
26
34
42
50
58
66
74
82
89
0.01
-60
-53
-45
-37
-29
-21
-13
-5
|7|
11
19
27
34
42
50
58
66
74
82
90
98
0 . 02
-44
-36
-28
-20
-12
-4
4
11
19
27
35
43
51
59
67
75
83
91
98
106
114
0.03
-27
-19
-11
-4
4
12
2O
28
36
44
52
60
68
76
83
91
99
1O7
115
123
131
0.04
-11
—3
5
13
21
29
37
45
53
6O
68
76
84
92
100
108
116
124
132
140
147
0.05
6
14
22
30
38
45
53
61
69
77
85
93
101
109
117
125
132
140
148
156
164
E-14
-------
IMC.W T ur\r-.
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 47.95
Damages -from Endemic Level a-f 17. 105.746
Damages from A Representative Outbreak
4168.481
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-47.
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-48
-37
-27
-16
-6
5
15
26
37
47
53
68
79
90
100
111
121
132
142
153
164
0 . OO5
-27
-17
-6
5
15
26
36
47
57
68
79
89
100
110
121
132
142
153
163
174
184
0 . 0 1
-6
4
15
25
36
47
57
68
78
89
99
1 1 0
121
131
142
152
163
174
134
195
205
0.02
35
46
57
67
78
88
99
1O9
120
131
141
152
162
173
183
194
205
215
226
236
247
0.03
77
88
98
109
119
130
141
151
162
172
183
193
204
215
r*o«=r
jL..i^vJ
236
246
257
267
278
289
0 . 04
119
129
140
151
161
172
182
193
203
214
'•*'•* cr
rf^^.V-1
235
246
256
267
277
288
299
3O9
320
330
0 . 05
160
171
182
192
203
213
"^24
234
245
256
266
277
287
298
309
319
330
340
351
361
372
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost a-f Filtration 47.95
Damages -from Endemic Level o-f 17. 79.11
Damages -from A Representative Outbreak
1653.549
ANNUAL PROBABILITY OF OUTBREAK
E
M
D
E
M
I
C
L
E
V
E
L
-47.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0,7
0.8
0.9
1.0
1» 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-48
-40
-32
-24
-16
-8
-0
7
15
TT
.C.'»'
31
39
47
55
63
71
79
87
94
102
110
0 . 005
-40
— T1
-24
-16
-8
-0
8
16
24
T*™»
•«' *i.
39
47
55
63
71
79
87
^5
103
111
119
0 . 0 1
-31
'*»T
~"*LO
-16
-8
0
8
16
24
T^"V
•J>^_
40
48
56
64
71
79
37
95
103
111
119
127
0 . 02
-15
-7
1
9
17
25
•_!• • J1
41
49
56
64
72
80-
38
96
104
112
120
128
136
143
0.03
r~y
10
18
26
•—••!•
41
49
57
65
73
81
89
97
105
113
120
128
136
144
152
1 60
0 . 04
18
26
34
42
50
58
66
74
82
90
98
105
113
121
129
137
145
153
161
169
177
0.05
35
43
51
59
67
75
82
90
98
106
114
122
130
138
146
154
162
169
177
135
193
E-15
-------
NEW YORK, NY
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0 . 3
0.4
0.5
0.6
0.7
- 0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
o
0
o
0
o
1
1
2
~?t
"T
4
4
4
4
4
4
4
4
4
0 . 005
0
o
o
1
1
1
?
^r
3
4
4
4
4
4
4
4
4
4
4
0 . 0 1
O
1
1
1
T
3
3
3
4
4
4
4
4
4
4
4
4
4
4
0.02
2
2
7;
Tf
T
T
4
4
4
4
4
4
4
4
4
4
4
4
4
0.03
T
"T
^
Tj
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0.04
]T
^T
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0.05
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
E-16
-------
M
§
_i
2
-4A-
Q
TREATMENT COST VS. ENDEMIC DAMAGES
6 -
4 -
3-
2 -
1 -
SYRACUSE. NY
0.2 0.4 0.6 0.6 1 1.2 1.4 1.6 1.8
ENDEMIC LEVEL (X OF POP/YR)
f
-5-
§
tf
TREATMENT COST VS. OUTBREAK DAMAGES
SYRACUSE. NY
5 -
4 -
3-
2 -
1 -
o.oos oat o.ora 'ouj2 0.023
ANNUAL P(OUTBREAK) (X)
E-17
0.055 0.04 0.046 04)5
-------
SYRACUSE,NY
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 3.64
Damages from Endemic Level o-f IX 3.783
Damages -from A Representative Outbreak 136.0O4
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-3.6
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
O-8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-4
— -.!>
~-'j
— 0
-2
_2
-1
-1
-1
-0
0
1
1
1
o
4-
*"\
*».
2
3
•»•
4
4
0. 005
~-'j
— -^>
— ->
..
^\
-1
-1
-1
-0
0
o
1
1
<->
2
_2
3
•>
--'
4
4
5
0.01
-2
_2
-2
-1
-1
-0
-0
o
1
1
2
-!•
2
-T
•->
•W"
3
4
4
5
5
5
0.02
-1
-1
-0
0
1
1
1
2
«?
2
T
•J
•Ir
4
4
4
5
5
6
6
6
7
0 . 03
0
1
1
*-$
*}
^j
+m,
3
•— '
•3
4
4
5
5
5
6
6
6
7
7
S
8
0.04
^>
*"?
.^»
3
3
4
4
4
5
5
6
6
6
7
7
7
3
8
9
9
9
0 . 05
3
4
4
4
5
5
5
6
6
7
7
7
8
8
8
9
9
10
10
10
11
HISH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 3.64
Damages -From Endemic Level of 17. 2.753
Damages from A Representative Outbreak
55.308
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-3.6
o.o
O. 1
0.2
0.3
0.4
O.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
i.a
1.9
2.0
0
-4
_T
••>
*~O
-3
~~-i
-2
_2
-2
-1
-1
-1
-1
-0
-0
0
0
1
1
1
2
•>
0.005
-3
-3
-3
TT
•J
-2
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4
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5
E-18
-------
SYRACUSE,NY
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.73
Damages -from Endemic Level of 17. 3.783
Damages -From A Representative Outbreak 136.004
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.7
O.O
0. 1
0.2
0.3
0.4
0.5
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0.7
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0.9
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1.5
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10
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5
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6
6
6
7
7
7
3
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9
9
9
10
10
11
11
11
12
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.73
Damages -from Endemic Level o-f IV. 2.753
Damages -from A Representative Outbreak 55,308
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.7
0.0
0.1
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0.3
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E-19
-------
SYRACUSE,NY
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0 . 2
0.3
0.4
0.5
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4
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4
4
4
4
4
4
4
4
4
4
4
4
4
E-20
-------
in
M
in
Q
TREATMENT COST VS. ENDEMIC DAMAGES
3.5
3-
2.5 -
1.5-
1 -
0.5-
UT1CA, NY
0.2 0.4 0.6 OS 1 1.2 1.4 1.6 1.8
ENDEMIC LEVEL (X OF POP/YR)
i
I
REATMENT COST VS. OUTBREAK DAMAGES
T
UTX*, NY
3.5
3-
2.5-
1.5-
1 -
0.5-
0 O.OO5 OJ31
0.016 . 0.02 0.025 OU33 O.O36 OX»4 O.O46 OJOS
ANNUAL P(OUTBfl£AK) (X)
E-21
-------
UTICA, NY
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 1.9B
Damages from Endemic Level of 17. 1.721
Damages -from A Representative Outbreak 67.717
ANNUAL PROBABILITY OF OUTBREAK
-1.9 0 0. 0<35 0. 0 i 0. 02 0. 03 0. 04 0. 05
E 0.0 -2 -2 -1 -1011
N 0.1 -2 -1 -1 -0 0 1 2
D O.2 -2 -1 -1 -0 0 1 2
E 0.3 -1 -1 -1 -0 112
M 0.4 -1 -1 -1 0112
I 0.5 -1 -1 -0 0122
C 0.6 -1 -1 -0 0122
0.7 -1 -0 -01 123
L 0.8 -1 -0 01 123
E 0.9 -0 -0 01223
V 1.0 -0 0 0 1223
E 1.1 -0 0 11233
L 1.2 0 0 1 1 2 3 3
1.3 O 1 1 2 2 3 4
1.4 0 1 1 2 2 3 4
1.5 1112334
1.6 1112334
1.7 1 1 2 2 3 4 4
1.8 1 1 2 2 3 4 5
1.9 1 2 2 3 3 4 5
2.0 1 2 2 3 3 4 5
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 1.98
Damages from Endemic Level of 17. 1.177
Damages from A Representative Outbreak 26.372
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.9
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
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E-22
-------
UTICA, NY
LOW TREATMENT COST - HIGH DAMASE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.55
Damages -from Endemic Level of I"/. 1.721
Damages -from A Representative Outbreak 67.717
ANNUAL PROBABILITY OF OUTBREAK
-1.5 0 0.005 0.01 0.02 0.03 0.04
£ 0.0
N O. 1
D 0.2
£ 0.3
M 0.4
I 0.5
C 0.6
0.7
L 0.9
E 0.9
V 1.0 0 1 1 2 2 3 4
E 1 • 1 0 1 1 2 2 3 4
L 1-2 1 1 1 2 3 3 4
1.3 1 1 1 2 3 3 4
1.4 1 1 2 2 3 4 4
1.5 1 1 2 2 3 4 4
1.6 1223345
1.7
1.8
1.9
2.0
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 1.55
Damages -from Endemic Level o-f 1% 1.177
Damages -from A Representative Outbreak 26.372
ANNUAL PROBABILITY OF OUTBREAK
•2
1
•1
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•1
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0
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1
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E-23
-------
UTICA, NY
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
e
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
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1.3
1.4
1.5
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1.8
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E-24
-------
TREATMENT COST VS. ENDEMIC DAMAGES
_l
to
M
3
4 -
3 -
2 -
SCRAMTON, PA
0.2 0.4 0.6 0.8 1 t.2 1.4 1.6 1.8
ENDEMIC LEVEL (X OF POP/YR)
I
i
TREATMENT COST VS. OUTBREAK DAMAGES
0.6-
SCRANTON, PA
0.005 0.01 0.015 0432 ' 0.025 0.05
ANNUAL P(OUTBREAK) (X)
E-25
0.03S OJ34 0.045 0.05
-------
SCRANTON, PA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.11
Damages -from Endemic Level o-f 17. 2.472
Damages -from A Representative Outbreak 90.507
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1. 1
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
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0.9
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1.2
1.3
1.4
1.5
1.6
1.7
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4
4
4
5
5
5
5
6
6
6
-------
SCRANTON, PA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.98
Damages from Endemic Level o-f 1% 2.472
Damages -from A Representative Outbreak 90.507
ANNUAL PROBABILITY OF OUTBREAK
E
Nl
D
E
M
I
C
L
E
V
E
L
-0.9
0.0
0.1
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0.3
0.4
0.5
0.6
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0.9
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LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.98
Damages -from Endemic Level o-f IX 2.046
Damages -from A Representative Outbreak 38.967
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
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L
E
V
E
L
-0.9
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o
.;•
3
4
4
4
4
4
5
5
5
E-27
-------
SCRANTON, PA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 0.04 0.05
E
N
D
E
M
I
C
L
E
V
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L
0 . 0
0. 1
0.2
0 . 3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
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1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
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4
4
4
4
4
4
4
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4
4
4
4
4
4
4
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4
4
4
4
4
4
4
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4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
E-28
-------
6
M
M
Q
TREATMENT COST VS. ENDEMIC DAMAGES
7 -i
6-
6 -
4 -
1 -
WILKES-BARRE. PA
0.2 0.4 O.6 0.8 1 1.2
ENDEMIC LEVEL (X OF POP/YR)
1.4 1.6 1.8
TREATMENT COST VS. OUTBREAK DAMAGES
WILKES-BARRE, PA
5-
4 -
2 -
1 -
0.005 0.01 0.01 S • 0.02 0.025 0X93 0.035 0434 O.O4S OXIS
ANNUAL P(QUTBREAK) (X)
E-29
-------
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 3.02
Damages -from Endemic Level o-f 17. 3.594
Damages -from A Representative Outbreak 131. 657
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-Z . 0
o.o
O. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
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6
6
6
7
7
3
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9
9
10
10
10
11
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 3.02
Damages -from Endemic Level o-f 17. 2.973
Damages from A Representative Outbreak 56.685
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
e
L
-3.0
0.0
0. 1
0.2
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0.7
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5
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E-30
-------
WILKES-BARRE, PA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 1.98
Damages -from Endemic Level o-f I'/. 3.594
Damages -from A Representative Outbreak 131.657
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.9
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
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0
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4
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6
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7
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4
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5
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6
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8
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9
9
9
10
10
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6
6
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7
7
7
8
3
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9
9
10
10
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11
11
11
12
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.98
Damages -from Endemic Level o-f 17. 2.973
Damages -From A Representative Outbreak 56.685
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L.
E
V
E
L
-1.9
0.0
0.1
0.2
0.3
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1.9
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6
6
6
7
7
E-31
-------
WILKES-BARRE, PA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 0. 04 O. O!
E
N
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E
M
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L
£
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1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
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1
2
2
3
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4
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E-32
-------
TREATMENT COST VS. ENDEMIC DAMAGES
BETHLEHEM, PA
3.5 -
>
\
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2.5 -
2 -
1.6 -
1 -
0.6 -
0.2 0.4 0.6 0.8 1 1.2
ENCCMIC LEVEL (X OF POP/VR)
1.4
1.6
1.8
TREATMENT COST VS. OUTBREAK DAMAGES
M
I
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2
in
1/1
Q
2.2
BETHLEHEM. PA
0.005 0.01 0.015 0.02 0,025
ANNUAL P(OUTBflEAK) (X)
E-33
OJ35
-------
BETHLEHEM, PA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.44
Damages from Endemic Level o-f 1% 1.821
Damages -from A Representative Outbreak 60.121
ANNUAL PROBABILITY OF OUTBREAK
0.05
1
1
1
1
1
1
E
N
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E
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1.2
1.3
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1.5
1.6
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3
3
3
3
3
3
4
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 2.44
Damages -from Endemic Level o-f 17. 1.497
Damages -from A Representative Outbreak 26.465
ANNUAL PROBABILITY OF OUTBREAK
•j
4
4
4
4
E
N
D
E
M
I
C
L
E
V
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-2.4
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E-34
-------
BETHLEHEM, PA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.83
Damages •from Endemic Level o-f \.7. 1.821
Damages -from A Representative Outbreak 60. 121
ANNUAL PROBABILITY OF OUTBREAK
0.05
1
1
E
N
D
E
M
I
C
L
E
V
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L
-1.8
0 . 0
0. 1
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0.3
0.4
0.5
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0.7
0.3
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1.2
1.3
1.4
1.5
1.6
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1.9
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3
3
3
3
3
3!
4
4
4
4
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.33
Damages -from Endemic Level o-f I'/. 1.497
Damages -from A Representative Outbreak 26.465
ANNUAL PROBABILITY OF OUTBREAK
™" 1 • tl
E 0.0
N 0. 1
D 0.2
E 0.3
M 0.4
I 0.5
C 0.6
0.7
L 0.8
E 0.9
V 1.0
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1.3
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4
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1
1
1
2
2
2
2
2
2
2
-------
BETHLEHEM, PA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 O.01 0.02 0.03 O.04 0.05
E
N
D
E
M
I
C
L
E
V
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0. 0
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0.3
0.4
0.5
0.6
0.7
0.8
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1.3
1.4
1.5
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3
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4
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4
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4
4
4
4
4
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E-36
-------
TREATMENT COST VS. ENDEMIC DAMAGES
in
I
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in
Q.
15-
14 -
13 -
12 -
11 -
10 -
9 -
a -
7 -
6 -
6-
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3 -
2-
1 -
0-
GREENVILLE. SC
0.2 0.4 0.6 0.8 1 1.2
ENDEMIC LEVEL (X OF POP/YR)
1.4
1.6
1.8
TREATMENT COST VS. OUTBREAK DAMAGES
-
4
GREENVILLE, SC
O.OO5 O.O1 O.O15 0.02 0.026 0.03 O.O3S 0.04 O.O4S O.O5
ANNUAL P(OUTBREAK) (X)
E-37
-------
GREENVILLE, SC
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 5.77
Damages -from Endemic Level o-f l"/i 7. 121
Damages -from A Representative Outbreak 306.294
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
-5.7
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.3
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
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1
2
3
4
4
5
6
6
7
3
9
9
10
0.01
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0
1
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4
4
5
6
7
7
8
9
9
10
11
12
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0
1
2
2
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4
5
5
6
7
7
a
9
10
10
11
12
12
13
14
15
0.03
O
4
5
6
6
7
8
3
9
10
11
11
12
13
13
14
15
16
16
17
19
0.04
6
7
8
9
9
10
11
11
12
13
14
14
15
16
16
17
18
19
19
2O
21
0.05
10
10
11
12
12
13
14
15
15
16
17
17
18
19
20
20
21
r>r>
22
23
24
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 5.77
Damages from Endemic Level o-f 17. 5.448
Damages -from A Representative Outbreak
122.935
ANNUAL PROBABILITY OF OUTBREAK
r
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1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
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8
9
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10
11
11
E-38
-------
GREENVILLE, SC
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 4.9
Damages from Endemic Level o-f 1/C 7.121
Damages -from A Representative Outbreak 306.294
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-4.8
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
i.a
1.9
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5
5
6
7
7
8
9
10
10
11
0.01
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-1
-0
0
1
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3
4
5
5
6
7
8
8
9
10
10
11
12
13
0.02
1
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•^
o
•_>
4
5
6
6
7
8
8
9
10
11
11
12
13
13
14
15
16
0.03
4
5
6
7
7
8
9
9
10
11
12
12
13
14
14
15
lo
16
17
18
19
0.04
7
8
9
10
1O
11
12
12
13
14
15
15
16
17
17
18
19
20
20
21
22
0.05
11
• 11
12
13
13
14
15
15
16
17
18
18
19
20
20
21
22
23
23
24
25
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost a* Filtration 4.8
Damages -from Endemic Level o-f 17. 5.448
Damages -from A Representative Outbreak 122.985
ANNUAL PROBABILITY OF OUTBREAK.
E
N
D
E
M
1
C
L
E
V
£-
L
-4.8
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0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.3
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
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4
4
5
5
6
6
7
7
8
3
9
10
10
11
11
12
12
E-39
-------
GREENVILLE, SC
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
o
o
o
0
0
0
0
1
1
TT
3
4
4
4
4
4
4
4
4
0.005
0
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0
1
2
2
T
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4
4
4
4
4
4
4
4
4
0.01
0
0
0
1
2
2
2
3
3
4
4
4
4
4
4
4
4
4
4
0. O2
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2
2
2
2
3
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4
4
4
4
4
4
4
4
4
4
4
4
0 . 03
2
2
2
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4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
O.O4
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3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
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Or
O,
A
4
Or
E-AO
-------
§
tf
TREATMENT COST VS. ENDEMIC DAMAGES
10 -
SAN FRANCISCO, CA
ENDEMIC LEVEL (X OF PQP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
SAN FRANCISCO, CA
0 0.005 0.01 0.015 0.02 0.025 0.03 O.O35 O.O4 0.045
ANNUAL P(OUTBREAK) (X)
E-41
-------
SAN FRANCISCO, CA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 12.95
Damages -from Endemic Level of 17. 30.69
Damages from A Representative Outbreak 1058.498
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
l_
E
V*
E
L
-12.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1,3
1.9
2.0
0
-13
-10
-7
-4
-1
2
5
9
12
15
18
21
24
27
30
33
36
39
42
45
48
0 . 005
-3
-5
_T(
2
5
8
11
14
17
20
23
26
29
32
35
38
41
45
48
51
54
0.01
_»^
1
4
7
10
13
16
19
22
25
28
31
34
38
41
44
47
50
53
56
59
0 . 02
8
11
14
17
20
24
27
30
33
36
39
42
45
48
51
54
57
60
63
67
70
0.03
19
22
25
28
31
34
^*7
*J • /
40
43
46
49
53
56
59
62
65
68
71
74
77
30
O.O4
29
32
36
39
42
45
48
51
54
57
60
63
66
69
72
75
78
82
85
88
91
0.05
40
43
46
49
52
55
58
61
65
63
71
74
77
80
83
86
89
92
95
98
101
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 12.95
Damages from Endemic Level of 1% 23.304
Damages from A Representative Outbreak 443.36^
ANNUAL PROBABILITY OF OUTBREAK
E
n
E
M
I
c
1
l«
E
l_
l*
-12.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-13
-11
-8
-6
-4
-1
1
3
6
3
10
13
15
17
20
22
24
27
29
31
34
0.005
-11
-a
-6
—4
-1
1
T;
6
8
10
13
15
17
20
'">*">
24
27
29
31
34
36
0.01
-9
-6
-4
-2
1
3
5
B
10
12
15
17
19
22
24
26
29
31
•— * •«•
36
38
0.02
-4
-2
1
3
5
3
10
12
15
17
19
22
24
26
29
31
33
36
38
40
43
0.03
0
^T
5
7
10
12
14
17
19
21
24
26
28
31
33
35
38
40
42
45
47
0.04
5
7
9
12
14
16
19
21
23
26
28
30
33
35
37
40
42
44
47
49
51
0.05
9
12
14
16
19
21
23
26
28
30
33
35
37
40
42
44
47
49
51
53
56
E-42
-------
SAN FRANCISCO, CA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 12.03
Damages -from Endemic Level o-f 1/C 30.69
Damages -from A Representative Outbreak 1058.498
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-12.
O.O
O. 1
0.2
0.3
0.4
O.5
0.6
0.7
o.a
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-12
-9
-6
-3
0
3
6
9
13
16
19
22
25
28
31
34
37
40
43
46
49
0 . 005
-7
-4
-1
2
6
9
12
15
18
21
24
27
30
33
36
39
42
45
49
52
55
0.01
-1
2
5
8
11
14
17
20
23
26
29
32
35
38
42
45
48
51
54
57
60
0.02
9
12
15
18
21
24
28
31
34
37
40
43
46
49
52
55
58
61
64
67
71
0.03
20
23
26
29
32
35
38
41
44
47
5O
53
57
60
63
66
69
72
75
78
81
0.04
3O
33
36
40
43
46
49
52
55
58
61
64
67
70
73
76
79
B2
86
39
92
0.05
41
44
47
50
53
56
59
62
65
69
72
75
78
81
84
87
90
93
96
99
102
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 12.03
Damages -from Endemic Level o-f 17. 23.304
Damages -from A Representative Outbreak 443.363
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-12.
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-12
-10
-7
-5
-3
-0
2
4
7
9
11
14
16
18
21
23
25
28
30
32
35
O.O05
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-7
-5
-3
-0
2
4
6
9
11
13
16
18
20
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25
27
30
T**n
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34
37
0.01
-8
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2
4
6
9
11
13
16
13
20
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25
27
30
32
34
37
39
0.02
-3
-1
1
4
6
8
11
13
15
IB
20
22
25
27
29
32
34
36
39
41
43
0 . 03
1
4
6
8
11
13
15
18
20
22
25
27
29
32
34
36
39
41
43
46
48
0.04
6
8
10
13
15
17
20
22
24
27
29
31
34
36
38
41
43
45
48
5O
52
0.05
10
12
15
17
19
22
24
26
29
31
33
36
38
40
43
45
47
50
52
54
57
E-43
-------
SAN FRANCISCO, CA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK'
O O.OO5 0.01 O.O2 0.03 0.04 O.05
E
N
D
E
M
I
C
L
E
V
E
L
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
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0
0
0
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4
4
4
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4
4
4
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4
4
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0
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4
4
4
4
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4
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4
4
4
4
4
4
4
4
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4
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4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
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4
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4
4
4
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4
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4
4
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4
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4
4
4
4
4
4
4
E-44
-------
M
I
10
in
Q
TREATMENT COST VS. ENDEMIC DAMAGES
2 -
RENO-SPARKS, NV
0.2 0.4 0.6 Q& 1 1.2 1.4
ENDEMIC LEVEL (X OF PQP/YR)
1.6 1.8
M
.1-
01
M
2
TREATMENT COST VS. OUTBREAK DAMAGES
RENO-SPARKS, NV
5-
0.005 0X11 0.01 S '0.02 0.025 0.03 0.035 0.04 0.04S 0X15
ANNUAL P(OUTBR£AK) (X)
E-A5
-------
RENO-SPARKS, NV
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 4.15
Damages -from Endemic Level o-f I*/. 2.886
Damages -From A Representative Outbreak 100.357
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
r
c
L
E
V
E
L
-4. 1
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.3
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
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1
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1
2
O.OO5
-4
~*"O
—•3
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w
-2
-2
_2
-2
-1
-1
-1
-0
-0
0
0
1
1
1
*->
2
2
0.01
-3
-3
-3
-2
-2
— r>
-1
-1
*~ 1
-1
-0
0
0
1
1
1
1
^>
o
*•
2
••1*
0 . 02
-2
— T>
-2
-1
-1
— 1
-O
-0
0
0
1
1
1
2
o
^
2
3
o
3
4
0.03
-1
-1
-1
-0
0
0
1
1
1
1
•?
2
2
3
3
3
•j
4
4
4
5
0.04
-O
O
0
1
1
1
•7
2
•7
2
3
3
4
4
4
4
5
5
5
6
0 . 05
1
1
1
->
2
•^
^
3
3
4
4
4
5
5
5
5
6
6
6
7
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 4.15
Damages from Endemic Level of 17. 2.386
Damages from A Representative Outbreak 43.756
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-4. 1
0.0
O. 1
0.2
O.3
0.4
0.5
0.6
0.7
O.B
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
t.9
2.0
0
-4
-4
-4
—3
-3
~3
T
•j
-2
— O
-2
-2
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-1
-1
-1
-1
-0
-0
0
0
1
0.005
-4
~4
—3
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•«>
~3
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_ ^
_2
_2
-2
-1
-1
-1
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o
0
1
1
0.01
-4
-3
-3
— .^>
-3
— T
•^
-2
-.0
—2
-2
-1
«• t
-1
-1
-0
-0
0
0
1
1
1
0.02
-3
-3
-3
-3
-^i
-2
_*^&
-2
-1
-1
-1
-1
-0
-0
o
o
1
1
1
1
1
0.03
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A.
_^k
_2
-1
-1
-1
-i
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0
o
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1
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1
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^
0 . 04
—2
_o
,£.
-2
-2
-1
-1
-1
-1
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-0
-0
0
0
1
1
1
1
->
2
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*-$
0.05
-2
™.T>
-1
-1
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-1
-0
-0
o
o
1
1
1
1
•?
2
^>
2
T
•->
•Jit
E-46
-------
RENO-SPARKS, NV
LOW TREATMENT COST - HI6H DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 3.O5
Damages from Endemic Level of 17. 2.386
Damages -From A Representative Outbreak 1O0.357
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-3.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
O.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
_T
-3
-2
—2
-2
-2
-1
-1
-I
-0
-0
0
0
1
1
1
2
2
2
o
•^
0 . 005
-3
-2
-2
_2
-1
-1
-1
-1
-0
0
0
1
1
1
1
2
2
2
3
~Zt
O
0.01
-2
—2
-1
-1
-1
-1
-0
-0
0
1
1
1
1
2
2
2
T|
T
3
3
4
0.02
-1
-1
-O
-0
0
0
1
1
1
2
2
2
2
3
Tt
T
4
4
4
4
5
0.03
-0
0
1
1
1
1
2
2
2
"T
T;
T
T,
4
4
4
5
5
5
5
6
0 . 04
1
1
2
2
2
2
~T
3
|T
4
4
4
4
5
5
5
6
6
6
6
7
0.05
2
2
3
^
^T
^T
4
4
4
5
5
5
5
6
6
6
7
7
7
7
a
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 3.O5
Damages from Endemic Level o-f 17. 2.386
Damages -from A Representative Outbreak 43.756
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-3 . 0
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1 . 3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-3
-3
™*-j>
_2
— O
— "?
—2
-1
-1
-1
-1
-0
-0
0
0
1
1
1
1
1
2
0.005
-3
-3
— ^
-2
— *^
_2
-1
-1
-1
-1
-0
-0
o
o
1
1
1
1
1
2
^
0.01
~"-^
-2
— 7
-2
—2
-1
-1
-1
•"• 1
-0
-0
0
0
0
1
1
1
1
*^l
2
2
0.02
_*?
-2
_i
ji.
-1
-1
-1
-1
-1
-0
-0
0
0
1
1
1
1
»->
2
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*?
•*
•^f
0.03
-2
— 1
-1
-1
-1
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-0
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0
0
1
1
1
1
•^
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«£.
^
2
•^f
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-— *
O.04
«. 1
— 1
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-0
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0
0
1
1
1
1
^
o
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2
3
3
3
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Tt
0 . 05
-1
-1
-0
-0
0
o
1
1
1
1
^
TI
^>
2
T>
•j
•— •
3
3
4
4
E-47
-------
RENO-SPARKS, NV
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
O 0.005 0.01 0.02 0.03 0.04 O. OS
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
o
0
0
0
0
0
0
0
0
0
1
1
2
2
•— •
3
•^f
4
0
0
0
0
0
0
0
o
0
1
1
1
2
-r
•j
3
•j>
3
4
4
o
0
0
0
0
o
0
0
1
1
1
~+
•— *
o
3
3
-i
4
4
4
0
0
0
0
1
1
1
1
^
•^
•-•
•!•
3
3
4
4
4
4
4
o
1
1
1
2
i
*}
2
3
•j<
3
3
4
4
4
4
4
4
4
1
•?
2
*2
*"^
jC
<™\
*£.
3
C'
3
3
3
4
4
4
4
4
4
4
4
•—*
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•-y
^^
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3
-— *
A
A
4-
4
A
4
A
A
A
A
E-48
-------
in
i/i
3
i«j
u
TREATMENT COST VS. ENDEMIC DAMAGES
SEATTLE. WA
45
40 -
35-
30 -
25-
20-
16-
1O
0.2 0.4 0.6 0.8 1 1.2 1.4
ENDEMIC LEVEL (X OF POP/YR)
1.6
1.8
in
\
M
M
3
TREATMENT COST VS. OUTBREAK DAMAGES
34
32 -
30-
28 -
26-
24 -
22 -
20-
18-
16 -
14 -
12-
10
8-
6 -
4 -
2-
0
SEATTLE WA
O.OOS 0.01 O.O1S ' O.02
0.02S
0.03 0.035 OJ04 0.04S 0X35
ANNUAL P(OUTBREAK) (X)
E-49
-------
SEATTLE, WA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 9.93
Damages -from Endemic Level o-f 171 21.288
Damages -from A Representative Outbreak ,659.587
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-9.9
0 . 0
0. 1
0.2
O.3
O.4
0.5
0.6
0.7
O.Q
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-10
-8
-6
-4
-1
1
•jf
5
7
9
11
13
16
IB
20
22
24
26
28
31
33
0.005
-7
-5
— T*
*1
-0
"?
4
6
a
10
13
15
17
19
21
*trr
4^.--'
25
27
30
32
34
36
0.01
""•i
-1
1
•Zf
5
7
9
12
14
16
18
20
22
24
26
29
31
33
35
37
39
O.02
•J
5
8
10
12
14
16
18
20
""?*"?
25
27
29
31
33
35
37
39
42
44
46
0.03
10
12
14
16
18
21
23
25
27
29
31
33
35
38
40
42
44
46
48
5O
52
0.04
16
19
21
*-\^
^••>
25
27
29
31
33
36
38
4O
42
44
46
48
51
53
55
57
59
0 . 05
23
25
27
29
32
34
36
38
40
42
44
46
49
51
53
55
57
59
61
63
66
HIGH TREATMENT COST - LOW DAMASE ESTIMATE SCENARIO
Annual Cost of Filtration 9.93
Damages -from Endemic Level o-f 1% 16.348
Damages -from A Representative Outbreak
284.503
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-9.9
O.O
0. 1
0.2
0.3
0.4
0.5
O.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-10
-a
-7
-5
-3
—2
-0
2
3
5
6
8
10
11
13
15
16
18
19
21
•^T
*-•-!'
0.005
-9
-7
— cr
*J
-4
'"I
*L
-0
1
3
5
6
8
9
11
13
14
16
18
19
21
*-»-*
^•_'
24
0.01
-7
-5
-4
« *?
-1
1
•->
4
b
3
9
11
13
14
Ifa
17
19
21
22
24
26
0 . 02
—4
—3
-1
1
^\
4
6
7
9
10
12
14
15
17
19
20
*^*^
24
25
27
28
0.03
mia •«
O
~p
4
5
7
8
10
12
13
15
17
18
2O
21
^1T
4^O
25
26
28
3O
31
0.04
1
•••
5
6
8
10
11
13
15
16
18
19
21
23
24
26
28
29
31
•J>O»
34
0.05
4
6
8
9
11
12
14
16
17
19
21
r>*?
24
26
27
29
30
T"1
•_*«^
34
35
37
E-50
-------
SEATTLE, WA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 8.27
Damages from Endemic Level o-f 17. 21.2S8
Damages -from A Representative Outbreak 659.587
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-8.2
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1. 0
1. 1
1.2
1.3
1.4
1. 5
1. 6
1 . 7
1.8
1. 9
2. 0
0
~6
-4
-2
0
2
5
7
9
11
13
15
17
19
22
24
26
28
30
32
34
0 . 005
-5
-1
1
4
6
8
10
12
14
16
18
21
23
25
27
29
31
33
35
38
0 . 0 1
-2
0
3
5
7
9
11
13
15
17
20
22
24
26
28
30
32
35
37
39
41
0.02
5
7
9
11
13
16
18
20
22
24
26
28
30
•-•0-
35
37
39
41
43
45
47
0 . 03
12
14
16
18
20
22
24
26
29
31
33
35
37
39
41
43
46
48
50
52
54
TI ~",
0.04
18
20
22
24
27
29
31
33
35
37
39
42
44
46
48
50
52
54
56
59
61
0.05
25
27
29
31
40
37
4O
42
44
46
48
50
52
55
57
59
61
63
65
67
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 8.27
Damages -from Endemic Level o-f 17. 16.348
Damages -from A Representative Outbreak 234.503
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
0 . 0
0. 1
0.2
0 . 3
0. 4
0.5
0.6
0.7
0.8
0.9
l.O
1 . 1
1.2
1 . 3
1.4
1.5
1 .6
1.7
1.3
1.9
2.0
0
-8
-7
-5
—3
-0
2
5
6
B
10
11
13
15
16
18
20
21
23
24
0. O05
-7
-5
-4
-2
-0
1
3
5
6
8
10
11
13
14
16
18
19
21
23
24
26
0.01
-5
-4
-2
-1
1
•-*
4
6
8
9
11
13
14
16
17
19
21
24
26
27
E-51
0.02
-1
1
2
4
6
7
9
10
12
14
15
17
19
2O
22
24
25
27
28
3O
0.03
o
4
5
7
3
10
12
13
15
17
18
20
22
25
26
28
30
31
33
0.04
6
8
10
11
13
16
18
19
21
24
26
28
29
31
33
34
36
0.05
i i
A
-------
SEATTLE, WA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0
0. 005
0.01
0. 02
0. 03
0.04
0.05
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0 . 2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.3
0
o
0
o
1
2
3
4
4
4
4
4
4
4
4
4
4
4
4
0
0
0
1
2
3
4
4
4
4
4
4
4
4
4
4
4
4
4
0
1
^
^i
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4 .
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T;
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
^
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
E-52
-------
TREATMENT COST VS. ENDEMIC DAMAGES
N
D
n
I
E
L
*
in
3
i
in
w
2
i_i
u
TACOMA, WA
ENDEMIC LEVEL (X OF
N
D
n
I
E
L
VI
o
i
TREATMENT COST VS. OUTBREAK DAMAGES
TACOMA, WA
o.ooa 0^1
0.01 s 0.02 0.029 oas 0.025 0494 0.0*6
ANNUAL P(OUT8REAK) (X)
E-53
-------
TACOMA, WA
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 7.05
Damages from Endemic Level of \7. 4.085
Damages from A Representative Outbreak 134.9O7
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-7.0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
l.S
1.9
2.0
0
-7
-7
-6
-6
-5
-5
-5
-4
-4
-3
-3
-3
-2
-2
-1
-1
-1
-O
0
1
1
0.005
-6
-6
-6
-5
-5
-4
-4
_&
-™.j>
-3
— *?
"• j£
-1
-1
-1
-0
0
1
1
1
2
0.01
-6
-5
-5
-4
-4
-4
-3
-3
_2
-2
—2
-1
-1
-0
0
0
1
1
2
2
2
0.02
-4
-4
-4
-3
-3
-2
-2
-1
-1
-1
-0
0
1
1
1
2
2
3
3
3
4
0.03
-3
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-2
-2
•• \
-1
-1
-0
0
1
1
1
2
2
•^f
3
4
4
4
5
5
O.04
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0
1
1
2
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*nt
3
O
4
4
4
5
5
6
6
7
0.05
-0
0
1
1
1
2
2
3
3
c-
4
4
5
5
5
6
6
7
7
7
e
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 7.05
Damages from Endemic Level of 1% 2.722
Damages from A Representative Outbreak 5"
ANNUAL PROBABILITY OF OUTBREAK
S97
E
N
D
E
M
I
C
L
E
V
E
L
-7.0
0.0
0. 1
0.2
0.3
O.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-7
-7
-7
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-4
_^
•«•
™-.Ir
-3
-2
-2
_*?
-2
0.005
-7
-7
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-4
-3
—c-
—3
_2
-2
-2
-2
-1
0.01
-7
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-4
_•?!
_T;
_T|
-2
-2
—2
_2
-1
*» 1
0.02
-6
-6
-5
-5
-5
-5
-4
-4
-4
—4
-3
—3
— T
-2
-2
-2
—2
-1
-1
-1
-1
0.03
—5
-5
-5
-5
-4
-4
-4
—4
-3
-3
-3
-2
-2
-2
-2
-1
-1
-1
-1
-0
-0
0.04
-5
-5
-4
—4
-4
-4
-3
-3
-3
""" -tit
-2
-2
_2
-1
-1
-1
— 1
-0
-0
0
1
0.05
-4
-4
-4
-4
-3
-3
-3
-2
-2
-2
—2
-1
-1
-1
-1
-O
-0
0
1
1
1
E-54
-------
TACOMA, WA
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 6.73
Damages -from Endemic Level o-F 1% 4.085
Damages -from A Representative Outbreak 134.907
ANNUAL PROBABILITY OF OUTBREAK
-6.7
E
N
D
E
M
I
C
L
E
V
E
L
0.0
O. 1
0.2
0.3
0.4
0.5
O.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.3
1.9
2.0
0
-7
-6
-6
-6
-5
-5
-4
-4
—3
_T
••»
^
•_»
_2
-2
-1
-1
w 1
-0
0
1
1
1
0.005
-6
-6
-5
-5
-4
-4
-4
_T
•J
—3
—2
-2
-2
-1
-1
-0
0
0
1
1
2
O
«^B
0.01
-5
—5
-5
-4
-4
-3
—3
-3
-2
— *}
A*
-1
-1
-0
-0
0
1
1
^
d»
2
2
3
0.02
-4
-4
-3
-3
-2
-2
-2
-1
-1
-O
0
O
1
1
2
2
2
3
3
4
4
0.03
-3
-2
-2
-1
-1
-1
-0
0
1
1
1
2
2
3
3
3
4
4
5
5
5
0.04
«Ht I
-1
-1
-O
0
1
1
*7*
^
O
3
3
4
4
4
5
5
6
6
6
7
0 . 05
-0
0
1
1
2
2
*^
.^i
3
4
4
4
5
5
6
6
7
7
7
e
9
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 6.75
Damages -from Endemic Level o-f 17. 2.722
Damages -from A Representative Outbreak 53.397
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-6.7
0.0
0.1
0.2
0.3
0.4
0.5
0.6
O.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-7
-6
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-3
-3
-3
-3
-2
-2
-2
-2
-1
0.005
"""D
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-3
-3
_ T
-3
-2
-2
_2
_^>
-1
-1
O.01
-6
-6
-6
-5
-5
-5
-5
-4
-4
-4
-3
-3
—3
-3
—2
-2
— i
— T
-1
-1
— 1
0.02
-6
S~
vj
-5
-5
-5
-4
-4
-4
-4
-3
-3
-3
-2
-2
-2
_2
-1
-1
-1
-1
-0
0.03
-5
-5
-5
-4
-4
-4
-4
-3
-3
-3
-2
-2
-2
—2
-1
-1
_ 1
-1
-0
0
0
0.04
-5
—4
-4
-4
-4
-3
-3
-3
-2
-2
-2
-2
-1
-1
-1
-1
-0
0
0
1
1
0.05
-4
-4
-4
-3
-3
-3
-2
-2
-2
-2
-1
-1
-1
-1
-0
0
0
1
1
1
1
E-55
-------
TACOMA, WA
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 0.04 O.O5
O
*^>
2
2
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
0
0
0
0
O
o
0
0
0
0
0
0
0
1
2
2
2
0
0
0
0
0
0
0
0
0
o
0
0
0
0
2
^
4.
2
2
2
0
0
0
0
0
0
0
0
0
0
1
2
2
•3
2
2
2
2
2
0
0
0
0
0
0
0
1
2
*^
2
2
2
2
^
A.
2
2
2
2
0
0
0
0
1
•?
1
^
2
•2
2
2
2
*"%
*•
2
2
2
2
-^>
3
2
4
4
E-56
-------
TREATMENT COST VS. ENDEMIC DAMAGES
in
I
j
in
i/i
2
i_>
u
PORTLAND. OR
ENDEMIC LEVEL (X OF POP/YR)
O
(/I
M
3
TREATMENT COST VS. OUTBREAK DAMAGES
PORTLAND. OR
22
0,015 ' 0.02 0.025 O.O3 O.03S OJ34 O.O45
ANNUAL
P(OUg»jEAK)
-------
PORTLAND, OR
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 11.19
Damages from Endemic Level o-f 17. 12.817"'
Damages -from A Representative Outbreak 428.201
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-11.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.-0
0
-11
-10
-9
-7
-6
-5
— o
-2
-1
0
2
3
4
5
7
8
9
11
12
13
14
0.005
-9
-8
-6
-5
-4
«y
•J*
••» 1
-0
1
^
4
5
6
8
9
10
11
13
14
15
17
0.01
—"7
-6
-4
—3
-2
-0
1
2
3
5
6
7
8
10
11
12
14
15
16
17
19
0.02
-3
-1
-0
1
3
4
5
6
8
9
1O
11
13
14
15
17
18
19
20
22
23
0.03
2
3
4
6
7
8
9
11
12
13
14
16
17
18
20
21
22
23
25
26
27
0.04
6
7
9
10
11
12
14
15
16
17
19
20
21
23
24
25
26
28
29
30
32
O.O5
10
12
13
14
15
17
18
19
20
22
23
24
26
27
28
29
31
32
33
35
36
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 11.19
Damages from Endemic Level of IX 4.79
Damages from A Representative Outbreak 179.158
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-11.
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-11
-11
-10
-10
-9
-9
-8
— R
-7
-7
-6
-6
-5
-5
—4
-4
-4
_-!f
-3
-2
-2
0.005
-10
-10
-9
-9
«™Q
-a
-7
-7
-6
-6
-6
-5
-5
-4
-4
-3
-3
-2
-2
-1
-1
0.01
-9
-9
-8
-8
-7
-7
-7
-6
-6
"•^
-5
—4
-4
-3
-3
_»?
-2
-1
— 1
-0
0
0.02
-B
-7
-7
-6
-6
-5
-5
-4
-4
-3
-3
-2
— i?
-1
-1
-0
0
1
1
1
2
0.03
-6
-5
-5
-4
-4
-3
-3
-2
-2
-2
-1
-1
-0
0
1
1
2
o
*•
3
•^>
4
0.04
-4
—4
— -i
-3
— *?
_ ^>
-1
-1
-0
O
1
1
2
2
^
3
4
4
5
5
6
0.05
_2
-2
-1
-1
-0
0
1
1
2
2
3
3
4
4
4
5
5
6
6
7
7
E-58
-------
PORTLAND, OR
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 9.97
Damages from Endemic Level of 17C 12.817
Damages from A Representative Outbreak 428.201
ANNUAL PROBABILITY OF OUTBREAK
-9.9
E
N
D
E
M
I
C
L
E
V
E
L
0.0
0.1
0.2
0.3
0.4
0.5
O.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-10
-9
-7
-6
-5
-4
—2
-1
0
2
3
4
5
7
8
9
11
12
13
14
16
0.005
-8
-7
—5
-4
-3
-1
-0
1
2
4
5
6
8
9
10
11
13
14
15
17
18
0.01
-6
-4
-3
O
~~i.
-1
1
2
3
5
6
7
8
10
11
12
14
15
16
17
19
20
0.02
-1
-0
1
2
4
5
6
8
9
10
11
13
14
15
17
IS
19
20
22
23
24
0.03
3
4
5
7
8
9
11
12
13
14
16
17
18
20
21
22
23
25
26
27
29
0.04
7
8
10
11
12
14
15
16
17
19
2O
21
23
24
25
26
28
29
30
32
33
0.05
11
13
14
15
17
18
19
20
22
23
24
26
27
28
29
31
32
33
35
36
37
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 9.97
Damages from Endemic Level of 17. 4.79
Damages from A Representative Outbreak 179.158
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-9.9
0.0
O. 1
0.2
0.3
O.4
0.5
O.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-10
-9
-9
-9
-8
-8
-7
-7
-6
-6
-5
-5
-4
-4
-3
-3
-2
-2
-1
-1
-0
0.005
-9
-9
-8
-8
-7
-7
-6
-6
-5
-5
-4
-4
—•^
-3
-2
-2
-1
-1
-0
0
1
0.01
-8
-8
-7
-7
-6
-6
-5
-5
-4
-4
-3
-3
_2
—2
-1
-1
-1
-0
0
1
1
0.02
-6
-6
-5
-5
-4
-4
-4
-3
-3
-2
_*j
-I
-1
-0
0
1
1
2
*•>
4»
3
TJ
0.03
-5
-4
-4
-3
-3
_2
_2
-1
-1
-0
0
1
1
2
f
•tt
3
4
4
5
5
0.04
-3
-2
*•*?
-1
-1
-0
O
1
1
2
2
2
3
3
4
4
5
5
6
6
7
0.05
-1
-1
-0
0
- 1
1
2
2
3
•i
4
4
5
5
6
6
7
7
8
3
9
E-59
-------
PORTLAND, OR
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 0.04 <-> OS
E 0.0 0 0 0 0 2 t " •?
N 0.1 o 0 0 022 ^
D 0.2 0 0 O 1 2 2 ~
E 0.3 0 0 0 2 2 2 ^
M 0.4 0 0 0 22 2 3
I 0.5 0 0 1 2 2 2 4
CO. 6 0 0 2 2 2 3 4
0.7 012223 4
LO.B 1 2 2 2 2 3 4
E 0.9 2 2 2 22 4 4
VI. 0 2 2 2 2 3 4 4
El.l 2 2 2 2 34 4
L 1-2 222234 4
1.3 2 2 2 2 4 4 4
1-4 2 2.2 3 4 4 4
1.5 222344 4
1.6 222444 4
1.7 2 2 2 4 4 4 *
1.8 2 2 3 4 4 4 4
E-60
-------
APPENDIX F
SYSTEM LEVEL BREAKEVEN ANALYSES
FOR 9 GENERIC SIZE CATEGORIES
-------
S+*.
I
.1
2
M
M
3
TREATMENT COST VS. ENDEMIC DAMAGES
75.001 - 100.000 POPULATION
2.8
0.2
0.4
0.6 0.8 t 1.2
ENDEMIC LEVEL (X OF POP/YR)
1.4
1.6
1.8
Irt
0
TREATMENT COST VS. OUTBREAK DAMAGES
75,001 - 100,000 POPULATION
0.005 0.01 0.015 -0.02 0.02S 0.03 0.035 0.04 0.04S 0.05
AMNUAL P(OUTBREAK) (X)
F-l
-------
75.O01 - 100,000 POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration
.658
Damages -from Endemic Level o-f I"/. 1.231
Damages -from A Representative Outbreak
49.181
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.6
0 . 0
0. 1
0.2
0.3
O.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
l.S
1.9
2.0
0
-2.66
-2.53
-2.41
-2.29
-2. 17
-2.04
-1.92
-1.80
-1.67
-1.55
-1.43
-1.30
-1. 18
-1.06
-O.93
-0.81
-O.69
-0.57
-O.44
-0.32
-0.20
0 . 005
-2.41
-2.29
-2. 17
-2.04
-1.92
-1.80
-1.67
-1.55
-1.43
-1.30
-1. 18
-1.06
-0.93
-0.81
-0.69
-0.57
-0.44
-0.32
-0.20
-0.07
0.05
0.01
-2. 17
-2.04
-1.92
-1.80
-1.67
-1.55
-1.43
-1.30
-1. 18
-1.06
-0.94
-0.81
-0.69
-0.57
-O.44
-0.32
-0.20
-0.07
O.O5
0. 17
0.30
0 . 02
-1.67
-1.55
-1.43
-1.31
-1. 18
-1.06
-0.94
-0.81
-0.69
-0.57
-0.44
-0 . 32
-0.20
-0.07
0.05
0. 17
0.30
0.42
0.54
0.66
0.79
0 . 03
-1. 18
-1.06
-0.94
-0.81
-0.69
-0.57
-0.44
-0 . 32
-0.20
-0.07
0.05
0.17
0.29
0.42
0.54
0.66
0.79
0.91
1.03
1. 16
1.28
0.04
-0.69
-0.57
-0.44
-0.32
-0,20
-0.08
0.05
0. 17
0.29
0.42
0.54
0.66
0.79
0.91
1.03
1. 16
1.28
1 . 40
1.53
1.65
1.77
0 . 05
-0.20
-0.08
0.05
0. 17
0.29
0.42
O.54
0.66
0.79
O.91
1.03
1.16
1.28
1.40
1.52
1.65
1.77
1.89
2.02
2.14
2.26
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 2.658
Damages from Endemic Level of IX 0.909
Damages from A Representative Outbreak 19.35"
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-2.6
0.0
0. 1
O.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-2.66
-2.57
-2.48
-2.39
-2.29
-2.20
-2. 11
-2. O2
-1.93
-1.84
-1.75
-1.66
-1.57
-1.48
-1.39
-1.29 -
-1.20
-1. 11
-1.O2
-0.93
-0.84
0.005
-2.56
-2.47
-2.38
-2.29
-2.20
-2. 11
-2.02
-1.92
- 1 . 83
-1.74
-1.65
-1.56
-1.47
-1.38
-1.29
-1.20
-1.11
-1.02
-O.93
-0.83
-0.74
0.01
-2.46
-2.37
-2.28
-2.19
-2. 10
-2.01
-1.92
-1.83
-1.74
-1.65
-1.56
-1.46
-1.37
-1.28
-1.19
-1. 10
-1.01
-0.92
-0.83
-0. 74
.-0.65
0.02
-2.27
-2. 18
-2.09
-2.00
-1.91
-1.82
-1 . 73
-1.63
-1.54
-1.45
-1.36
-1.27
-1. 18
-1.09
-1.00
-0.91
-O.82
-0.73
-0.63
-0.54
-0.45
0.03
-2.08
-1.99
-1.90
-1.80
-1.71
-1.62
-1.53
-1.44
-1.35
-1.26
-1.17
-1.08
-O.99
-0.90
-0.80
-0.71
-O.62
-O.53
-0.44
-0.35
-0.26
O.O4
-1.88
-1.79
-1.70
-1.61
-1.52
-1.43
-1.34
-1.25
-1.16
-1.07
-0.97
-0.88
-O.79
-0.70
-0.61
-0.52
-0.43
-0.34
-0.25
-0.16
-0.07
0.05
-1.69
-1.60
-1.51
-1.42
-1.33
-1,24
-1.14
-1.05
-0.96
-0.87
-0.78
-0.69
-O,60
-0.51
-0.42
-0.33
-0.24
-O. 15
-0.05
0,04
0. 13
F-2
-------
75.O01 - 1OO,000 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.847
Damages -from Endemic Level oi 1% 1.231
Damages -from A Representative Outbreak 49.181
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.8
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1.85
-1.72
-1.60
-1.48
-1.35
-1.23
-1. 11
-O.99
-O.86
-0.74
-0.62
-O.49
-O.37
-O.25
-O.I 2
-o.oo
O. 12
0.25
O.37
0.49
0.62
0 . 005
-1.60
-1.48
1 "TET
X • >«^\J
-1.23
-1. 11
-0.99
-0 . 86
-0.74
-0.62
-0.49
-0.37
-0.25
-0. 12
-0.00
0. 12
0.25
0.37
0.49
0.61
0.74
0.86
0 . 0 1
-1.36
-1.23
-1. 11
-0.99
-0.86
-0.74
-0 . 62
-0 . 49
-0 . 37
-0.25
-0. 12
-0.00
0. 12
0.25
0.37
0.49
0.61
0.74
0.86
0.98
1. 11
0.02
-0.86
-0.74
-0.62
-0.49
-0.37
-0.25
-0. 12
-0 . 00
0. 12
0.24
0.37
0 . 49
0.61
0.74
0.86
0.98
1. 11
1.23
1.35
1.48
1.60
0 . 03
-0.37
-0.25
-0.13
-0.00
0.12
O.24
0.37
0 . 49
0.61
0.74
O.S6
0.98
1.11
1.23
1.35
1.47
1.60
1.72
1.84
1.97
2.09
0.04
0. 12
0.24
0.37
0.49
0.61
0.74
0.86
0.98
1. 11
1.23
1.35
1.47
1.60
1.72
1.84
1.97
2.09
2.21
2.34
2.46
2.58
0 . 05
0.61
0.74
0.86
0.98
1. 10
1.23
1.35
1.47
1 . 60
1.72
1.84
1.97
2.09
2.21
2.34
2.46
2.58
2.70
2.83
2.95
3.07
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.847
Damages -from Endemic Level o-f I'/. 0.909
Damages from A Representative Outbreak 19.:
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.8
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
O.9
l.O
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1.85
-1.76
-1.67
-1.57
-1.48
-1.39
-1.30
-1.21
-1. 12
-1.O3
-O.94
-0.85
-0.76
-0.67
-0.57
-0.48
-0.39
-0.30
-0.21
-0. 12
-0.03
O . O05
-1.75
-1.66
-1.57
-1.48
-1.39
-1.30
-1.20
-1. 11
- 1 . 02
-0.93
-0.84
-0.75
-0.66
-0.57
-0.48
-0.39
-0 . 30
-0.20
-0. 11
-0.02
0.07
0.01
-1.65
-1.56
-1.47
-1.38
-1.29
-1.20
-1. 11
- 1 . 02
-O.93
-0.84
-O.74
-0.65
-0.56
-O.47
-O.3S
-O.29
-0.20
-O. 11
-O.02
0.07
• 0. 16
0.02
-1.46
-1.37
-1.28
-1.19
-1.10
-1.01
-0.91
-0.82
-0.73
-0.64
-0.55
-0.46
-0.37
-0.28
-0. 19
-0. 10
-0.01
0.09
0. 18
0.27
0.36
0.03
-1.27
-1.18
-1.08
-0.99
-0.90
-0.81
-0.72
-0 . 63
-O.54
-0 . 45
-0.36
-0.27
-O.18
-O.O8
O.01
0. 10
0. 19
0.28
0.37
0.46
0.55
0.04
-1.07
-0.98
-0.89
-0.80
-0.71
-0 . 62
-0.53
-0.44
-0 . 35
-0.25
-0. 16
-0.07
0.02
0. 11
0.20
0.29
0.38
0.47
0.56
0.65
0.75
0.05
-0.88
-O.79
-0.70
-0.61
-0.52
-0.42
-0 . 33
-0.24
-0. 15
-O.06
0.03
0.12
0.21
O.30
0.39
0.48
0.58
0.67
0.76
0.85
0.94
F-3
-------
75,001 - 100,000 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 O.005 0.01 0.02 0.03 O.O4 0.05
1 " 1
1 1
1 2
1 2
1 2
1 2
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
O.8
0.9
1.0
' 1.1
1.2
1.3
1.4
1.5
1.6
1.7
l.B
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
2
0
0
0
0
0
0
0
0
1
1
1
1
1
1
•J
2
2
3
3
0
0
0
0
1
1
1
1
1
1
2
2
*"?
2
— *
•^
3
3
3
3
3
3
3
F-4
-------
TREATMENT COST VS. ENDEMIC DAMAGES
I
I/I
0
V)
in
2
1.8
50.001 - 75,000 POPULATION
0.8 1
ENDEMIC LEVEL (X OF POP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
o
in
§
i^
UJ
1.8
50.001 - 75.000 POPULATION
0.005 0.01 0.015 0.02 • 0.025 0.05
ANNUAL P(QUTBREAK) (X)
F-5
0.035 0.04 0.045 0.05
-------
su.OiJl - 7 b. <->«>.' POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.719
Damages -from Endemic Level o-f I"/. 0.879
Damages -from A Representative Outbreak 34.714
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-1.7
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1.72
- 1 . 63
-1.54
-1.46
-1.37
-1.28
-1. 19
- 1 . 10
- 1 . 02
-0.93
-0.84
-0.75
-0.66
-0 . 58
-0.49
-0.40
-0.31
-0 . 22
-0. 14
-0.05
0.04
0 . 005
-1.55
-1.46
-1.37
-1.28
-1.19
-1. 11
-1.02
-O.93
-0.84
-0.75
-0.67
-0.58
-0.49
-O.40
-0.31
-0.23
-0. 14
-0.05
0.04
0. 12
0.21
0.01
-1.37
-1.28
- 1 . 20
-1.11
-1.02
-0.93
-0.84
-0.76
-0.67
-0.58
-0.49
-0.40
-0.32
-0.23
-0. 14
-0.05
0.03
0. 12
0.21
0.30
0.39
0.02
-1.02
-0.94
-0.85
-0.76
-0.67
-0.59
-0.50
-0.41
-0.32
-0.23
-0. 15
-0.06
0.03
0. 12
0.21
0.29
0.38
0.47
0.56
0.65
0.73
OF OUTBREAK
0 . 03
-0 . 68
-0.59
-0.50
-0.41
-0.33
-0.24
-0. 15
-0.06
0.03
0.11
0.20
0.29
0.38
0.47
0.55
0.64
0.73
0.82
0.90
0.99
1.08
0.04
-0.33
-0.24
-0. 15
-0.07
0.02
0. 11
0.20
0.28
0.37
0.46
0.55
0.64
0.72
0.81
0.90
0.99
1.08
1. 16
1.25
1.34
1.43
0 . 05
0.02
0. 10
0. 19
0.28
0 . 37
0.46
0.54
0.63
0.72
0.81
0.90
0.98
1.07
1.16
1.25
1.34
1.42
1.51
1.60
1.69
1.77
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.719
Damages -from Endemic Level o-f I'/. 0.649
Damages -from A Representative Outbreak
13.486
ANNUAL PROBABILITY
E
N
D
E
H
I
C
L
E
V
E
L
-1.7
o.o
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1.72
-1.65
-1.59
-1.52
-1.46
-1.39
-1.33
-1.26
-1.20
-1. 13
-1.07
-1.01
-0.94
-0.88
-0.81
-0.75
-0.68
-0 . 62
-0.55
-0.49
-0.42
0.005
-1.65
-1.59
-1.52
-1.46
-1.39
-1.33
-1.26
-1.20
-1.13"
-1.07
-1.00
-O.94
-0.87
-0.81
-0.74
-0.68
-0.61
-0.55
-0. 48
-0.42
-0.35
0.01
-1.58
-1.52
-1.45
-1.39
-1.32
-1.26
-1.19
-1.13
-1.06
-1.00
-0.94
-0.87
-0.81
-0.74
-0.68
-0.61
-0.55
-0.48
-0.42
-0.35
-rO.29
0.02
-1.45
-1.38
-1.32
-1.25
-1.19
-1. 12
-1.06
-0.99
-0.93
-0.87
-o.ao
-0.74
-0.67
-0.61
-0.54
-0.48
-0.41
-0.35
-O.28
-0.22
-0. 15
OF OUTBREAK
0.03
-1.31
-1.25
-1.18
-1.12
- 1 . 05
-0.99
-0.93
-0.86
-0.80
-0.73
-0.67
-0.60
-0.54
-0.47
-0.41
-0.34
-0.28
-0.21
-0.15
-0.08
-0.02
0.04
-1.18
-1.11
-1.05
-0.98
-0.92
-0.86
-0.79
-0.73
-0.66
-0.60
-0.53
-0.47
-0.40
-0.34
-0.27
-0.21
-0. 14
-0.08
-0.01
0.05
0. 12
0.05
-1.04
-0.98
-0.91
-0.85
-0.79
-0.72
-0.66
-0.59
-0.53
-O.46
-0.4O
-0.33
-0.27
-0.20
-0.14
-0 . 07
-0.01
0.06
0. 12
0.19
0.25
F-6
-------
5u,O01 - 75,000 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.336
Damages -From Endemic Level o-f 17. 0.879
Damages •from A Representative Outbreak 34.714
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
4 -~
1 » •_>
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
o.s
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-1.34
-1.25
-1. 16
-1.07
-0.98
-0.90
-0.81
-0.72
-0 . 63
-0.54
-0 . 46
-0.37
-0.28
-0. 19
-0.11
-0 . 02
0.07
0. 16
0.25
0.33
0.42
0 . 005
-1. 16
- 1 . 07
-0.99
-0.90
-0.81
-0.72
-O.64
-0.55
-0.46
-0.37
-0.28
-0.20
-0. 11
-0.02
0.07
0. 16
0.24
0.33
0.42
0.51
0.60
0.01
-0.99
-0.90
-0.81
-0 . 73
-0 . 64
-0 . 55
-0.46
-0 . 37
-0.29
-0 . 2O
-0. 11
-0.02
0.07
0.15
0.24
0.33
0.42
0.51
0.59
0.68
0.77
0.02
-0 . 64
-0.55
-0.47
-0.38
-0.29
-0.20
-0. 11
-0 . 03
0.06
0. 15
0.24
0 . 33
0.41
0.50
0.59
0.68
0.76
0.85
0.94
1 . 03
1. 12
0.03
-0.29
-O.21
-0. 12
-0.03
O.06
0. 14
0.23
0.32
0.41
0 . 50
0.58
0.67
0.76
0.85
O.94
1.02
1. 11
1.20
1.29
1.38
1.46
0.04
0.05
0. 14
0.23
0.32
0.40
0.49
0 . 58
0.67
0.76
0 . 84
0.93
1.02
1. 11
1.20
1.28
1.37
1.46
1.55
1.63
1.72
1.81
0 . 05
0.40
0.49
0.58
0.66
0.75
0.84
0.93
1.02
1. 10
1. 19
1.28
1.37
1.45
1.54
1.63
1.72
1.81
1.89
1.98
2.07
2. 16
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 1.336
Damages -from Endemic Level of 17. 0.649
Damages from A Representative Outbreak 13.486
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-1.3
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
- 1 . 34
-1.27
-1.21
-1. 14
-1.08
-1.01
-0.95
-0.88
-0.82
-0.75
-0 . 69
-0.62
-0.56
-O.49
-0.43
-0 . 36
-0.30
-0.23
-O. 17
-0.10
-O.04
0.005
-1.27
-1.20
-1. 14
-1.07
-1.01
-O.94
-0.88
-0.81
-0.75
-0.68
-0.62
-0.55
-0.49
-0.42
-0.36
-0.30
-0.23
-0. 17
-0. 10
-0.04
0.03
0.01
- 1 . 20
-1.14
- 1 . 07
-1.01
-0.94
-0.88
-0.81
-0 . 75
-0.68
-0.62
-0 . 55
-0.49
-0.42
-0.36
-0.29
-0.23
-0.16
-0.10
-0.03
0 . 03
.0.10
0.02
-1.07
-1.00
-0.94
-0.87
-0.81
-0.74
-0.68
-0.61
-0.55
-0.48
-0. 42
-0.35
-0.29
-0.22
-0. 16
-0.09
-0.03
0.04
0. 10
0. 17
0.23
0.03
-0.93
-0.87
-0 . 80
-0.74
-0 . 67
-0.61
-0.54
-0.48
-O.41
-0.35
-0.28
-0.22
-0.15
-O.09
-0.02
0.04
0.11
0.17
0.24
0.30
O.37
0.04
-0.80
-0.73
-0.67
-0.60
-0.54
-0.47
-0.41
-0 . 34
-0 . 28
-0.21
-0. 15
-0.08
-0.02
0.05
0. 11
0. 18
0.24
0.31
0.37
0.44
0.50
0.05
-0 . 66
-0.60
-0.53
-0.47
-0.40
-0.34
-0.27
-0.21
-0. 14
-0.08
-O.O1
0.05
0. 12
0. 18
0.25
0.31
0.3B
0.44
0.51
0.57
0.64
F-7
-------
50,001 - 75,000 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
E 0.0
N 0.1
D 0.2
E 0.3
M 0.4
I 0.5
C 0.6
0.7
L 0.8
E 0.9
V 1.0
E 1.1
L 1.2
1.3
1.4
1.5
1.6
1.7
1.8
ANNUAL PROBABILITY OF OUTBREAK
o
0
o
o
0
0
0
0
0
0
0
0
0
0
0
0
o
1
1
1
0 . 005
0
o
0
0
0
o
0
0
0
0
o
0
o
0
1
1
1
1
2
0.01
0
o
0
0
0
0
0
0
0
0
0
0
1
1
1
1
2
2
2
0.02
0
0
0
0
o
0
0
0
1
1
1
1
2
2
2
2
2
3
3
O.O3
0
0
0
0
1
1
1
1
^l
2
^
*.
2
2
2
2
3
3
3
OF
O.O4
1
1
- 1
1
^i
2
^>
2
o
2
T1
2
<^>
3
o
T
•j
3
3
3
O.O5
2
2
2
2
2
*?
2
•->
2
^t
*^
3
3
•*'
3
3
^
w
4
4
F-8
-------
TREATMENT COST VS. ENDEMIC DAMAGES
Ul
§
S
tf
25,001 - 50.000 POPULATION
1 1.2
ENDEMIC LEVEL (X OF POP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
_i
2
M
M
3
i»j
UJ
25,001 - 50.000 POPULATION
1.1
0.9-
0.8-
0.7 -
0.6 -
0.5 -
0.4 -
0.3 -
0.2-
0.1 -
0
0.005 0.01 O.Q16 OJ02 0.025 0.03
ANNUAL P(OUTBREAK) (X)
F-9
0.035 OJ34 0.045
-------
25.001 - 50,OOO POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.974
Damages -from Endemic Level of 1% 0.52
Damages -from A Representative Outbreak 21.743
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0 . 9
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
i.a
1.9
2.0
0
-0 . 97
-0.92
-0.87
-0 . 82
-0.77
-0.71
-0 . 66
-0.61
-O.56
-0.51
-0.45
-0.40
-0.35
-0.30
-0.25
-0. 19
-0. 14
-O.09
-O.04
0.01
0 . 07
0 . 005
-0.87
-0.81
-0.76
-0.71
-O.66
-0.61
-0.55
-0 . 50
-0.45
-0.40
-0.35
-0.29
-0.24
-0. 19
-0. 14
-0.09
-0.03
0.02
0.07
0. 12
0. 17
0.01
-0.76
-0.70
-0.65
-0.60
-0.55
-0.50
-0.44
-O.39
-0.34
-0.29
-0.24
-0.18
-0. 13
-0.08
-0 . 03
O.O2
0.08
0.13
0.18
0.23
0.28
0 . 02
-0.54
-0.49
-0.44
-0.38
-0.33
-0.28
-0.23
-0. 18
-0. 12
-0.07
-0.02
0.03
0.08
0. 14
0. 19
0.24
0.29
0.34
0.40
0.45
0.50
OF OUTBREAK
0 . 03
-0 . 32
-0.27
-0 . 22
-0. 17
-0. 11
-0.06
-0.01
0.04
• O.09
0. 15
0.20
0.25
0.30
0.35
0.41
O.46
0.51
0.56
0.61
0.67
0.72
0.04
-0. 10
-0.05
-0.00
0.05
0. 10
0. 16
0.21
0.26
0.31
0.36
0.42
0.47
0.52
0.57
0.62
0.68
0.73
0.78
0.83
0.88
0.94
0.05
0. 11
0. 17
0.22
0.27
0.32
0.37
0.43
0.48
0.53
0.58
0.63
0.69
0.74
0.79
0.84
0.89
0.95
1 . 00
1 . 05
1. 10
1. 15
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.974
Damages from Endemic Level o-f 17. 0.384
Damages -from A Representative Outbreak
9.8
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.9
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.97
-0.94
-0.90
-O.86
-0.82
-0.78
-0.74
-O.71
-0.67
"~O • oO
-O.59
-0 . 55
-0.51
-0.47
-0.44
-O.40
-0.36
-O.32
-0.28
-0.24
-O.21
0.005
-0.92
-0.89
-0.85
-0.81
-0.77
-0.73
-0.69
-0.66
-0.62
-0.58
-0.54
-0.50
-0.46
-0.43
-0.39
-O.35
-0.31
-0.27
-0.23
-0.20
-0. 16
0.01
-0.88
-0.84
-0.80
-0.76
-0.72
-0.68
-0.65
-O.61
-0.57
-0.53
-0.49
-0.45
-0.42
-0.38
-0.34
-0.30
-0.26
-0.22
-0. 18
-O. 15
•K). 11
0.02
-0.78
-0.74
-0.70
-0.66
-0.62
-0.59
-0.55
-O.51
-0.47
-0.43
-0.39
-0.36
-0.32
-0.28
-0.24
-0.20
-0. 16
-0. 13
-0.09
-0 . 05
-0.01
0.03
-0.68
-O.64
-0.60
-0.56
-0.53
-0.49
-0.45
-0.41
-O.37
-0.33
-0.30
-0.26
-0.22
-0.18
-0.14
-0.10
-0.07
-O.03
0.01
0.05
0.09
0.04
-0.58
-0.54
-0.51
-0.47
-0.43
-0.39
-0.35
-0,31
-0.27
-0.24
-0.20
-0. 16
-0. 12
-0 . 08
-0.04
-0.01
0.03
0.07
0. 11
0. 15
0. 19
0.05
-0.48
-0.45
-O.41
-0 . 37
-0.33
-0.29
-0.25
-0 . 22
-0. 18
-0. 14
-0. 10
-0.06
-0.02
. 0.02
0 . 05
0.09
0. 13
0.17
0.21
0.25
0.28
F-10
-------
25,001 - 50,000 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.735
Damages from Endemic Level of I'/. 0.52
Damages -from A Representative Outbreak 21.743
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.7
0 . 0
0. 1
0.2
0 . 3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
o
-0.74
-0 . 68
™"O • o--«
-0 . 58
-0.53
-0.48
-0.42
-0.37
-0.32
-0.27
-0.21
-0. 16
-0.11
-0.06
-0.01
0.05
0. 10
0. 15
0.20
0.25
0.31
0 . 005
-0 . 63
-0.57
-0.52
-0.47
-0.42
-0.37
-0.31
-O.26
-0.21
-0. 16
-0.11
-0.05
-0.00
0.05
0. 10
0. 15
0.21
0.26
0.31
0.36
0.41
0.01
-0.52
-0.47
-0.41
-0.36
-0.31
-0 . 26
-0.21
-0 . 1 5
-0 . 1 0
-0.05
0 . 00
0 . 05
0. 11
0. 16
0.21
0.26
0.31
0.37
0.42
0.47
0.52
0 . 02
-O.30
-O.25
-0.20
-0. 14
-0. 09
-0.04
0.01
0.06
0. 12
0. 17
0.22
0.27
0.32
0.38
0.43
0.48
0.53
0.58
0.64
0.69
0.74
0 . 03
-0 . 08
-0.03
0.02
0.07
0. 13
0. 18
0.23
0.28
0 . 33
0.39
0.44
0.49
0.54
0.59
0.65
0.70
0.75
0.80
0.85
0.91
0.96
0.04
0. 13
0. 19
0.24
0.29
0.34
0.39
0.45
0.50
0.55
0 . 60
0.65
0.71
0.76
0.81
0.86
0.91
0.97
1 . 02
1.07
1. 12
1. 17
0 . 05
0 . 35
0.4O
0.46
0.51
0.56
0.61
0.66
0.72
0.77
0.82
0.87
0.92
0.98
1.03
1.08
1. 13
1. 18
1.24
1.29
1 . 34
1.39
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.735
Damages -from Endemic Level o-f 1/C O.384
Damages -from A Representative Outbreak 9.8
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.7
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.74
-0.7O
-0.66
-0.62
-0.58
-0.54
-0.50
-0.47
-0 . 43
-O.39
-0.35
-O.31
-O.27
-0.24
-0 . 20
-0. 16
-0. 12
-0 . 08
-0.04
-O.01
0.03
0.005
-0.69
-0.65
-0.61
-0.57
-0.53
-0.49
-0.46
-0.42
-0.38
-0.34
-0.30
-0.26
-0.23
-0.19
-0. 15
-0.11
-0.07
-0 . 03
0.01
O.O4
0.08
0.01
-0.64
-O.6O
-0.56
-0.52
-0.48
-0.44
-0.41
-0.37
-0.33
-0.29
-0.25
-0.21
-0. 18
-0. 14
-0. 10
-0.06
-0.02
0.02
0.05
0.09
•0. 13
0.02
-0.54
-0.50
-O.46
-0.42
-0.39
-0.35
-0.31
-0.27
-0.23
-O. 19
-0. 15
-0. 12
-O.O8
-0.04
-0.00
0.04
0.08
0. 11
0. 15
O. 19
0.23
0.03
-0.44
-0 . 4O
-0.36
-0.33
-0.29
-0.25
-0.21
-0.17
-0. 13
-0. 10
-0.06
-0.02
0.02
0.06
0. 10
0. 14
0. 17
0.21
0.25
0.29
0.33
0.04
-0.34
-0.30
-0.27
-0.23
-0. 19
-0. 15
-0. 11
-0.07
-O.O4
0.00
0.04
0.08
0. 12
0. 16
0. 19
0.23
0.27
0.31
0.35
0.39
0.43
0.05
-0.24
-0.21
-0. 17
-0.13
-0.09
-0.05
-0.01
0.02
0.06
0. 10
0.14
0. 18
0.22
0.25
0.29
0.33
0.37
0.41
0.45
0.48
0.52
F-ll
-------
25,001 - 50,000 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 O.04 O.O5
1 2
1 2
1 2
2 2
> .
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0 . 3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
o
0
0
0
0
0
0
o
1
1
1
1
2
c*
0
0
0
0
0
0
0
0
0
o
1
1
1
1
1
o
2
3
3
0
o
0
0
0
0
1
1
1
1
1
*-\
rfu
*^l
2
2
^
•->
3
3
3
0
O
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3
3
4
I i
! i
F-12
-------
TREATMENT COST VS. ENDEMIC DAMAGES
I
2
9
10,001 - 25.000 POPUATON
0.2 0.4 0.6 0.8 1 1.2 1.4 1,6 1.fl
ENDEMIC LEVEL (X OF POP/YR)
I
o
M
W
2
TREATMENT COST VS. OUTBREAK DAMAGES
10,001 - 25.000 POPULATION
0.1 -
O.O26 O.O3
ANNUAL P(OUTBREAK) (X)
F-13
O.03S OJD4 0.045 0.05
-------
i C» ,
*^.hJ 9 *.*W r wi ui—rn i A ^*«
HIGH TREATMENT COST - HIBH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration O.564
Damages from Endemic Level of I"/. 0.237
Damages -from A Representative Outbreak 9.724
ANNUAL PROBABILITY
e
N
D
E
M
I
C
L
£
V
E
U
-0.5
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.3
1.9
2.0
0
-0.56
-0.54
-0.52
-0.49
-0.47
-0.45
-0.42
-0.4O
-0.37
-0. 35
—0. 33
-0.30
-0.28
-0.26
-0.23
-0.21
-0. 18
-0.16
-O. 14
-0. 11
-0.09
0.005
-0.52
-0. 49
-O. 47
-0. 44
-0. 42
-O. 40
-O. 37
-0.35
-0. 33
-0.30
-0. 28
-0.25
-0.23
-0.21
-0. 18
-0. 16
-0. 14
-O. 11
-O.09
-0.07
-0.04
0.01
-O.47
-0.44
-0.42
-0.40
-O.37
-0.35
-0.32
-0.30
-0.28
-0.25
-0.23
-0.21
-0. 18
-0. 16
-0.13
-0.11
-0.09
-0.06
-O.04
-0.02
0.01
0.02
-O.37
-0.35
-0.32
-0.30
-0.27
-0.25
-0.23
-0.20
-0. 18
-O. 16
-0. 13
-0. 11
-0.09
-0.06
-0.04
-0.01
0.01
0.03
0.06
0.08
0. 10
OF OUTBREAK
0.03
-0.27
-0.25
-0.22
-0.20
-0. 18
-0.15
-0. 13
-0.11
-0.08
-0.06
-0.04
-0.01
0.01
0.04
0.06
0.08
0. 11
0.13
0.15
0.18
0.20
0.04
-0. 18
-0.15
-0.13
-0. 10
-0.08
-0.06
-0.03
-0.01
0.01
0.04
0.06
O.O9
0. 11
0. 13
0. 16
0. 18
0.2O
0.23
0.25
0.28
0.30
0.05
-0.08
-0.05
-0^ 03
-0.01
0.02
0.04
0.06
0.09
0.11
0. 14
0.16
0.18
0,21
0.23
0.25
0.28
0 . 30
0.33
0.35
0.37
0.40
HI6H TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 0.564
Damages from Endemic Level of I/. O
Damages from A Representative Outbreak
4.411
e
N
D
e
M
i
c
L
e
V
e
L
-0.5
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
O
-0.56
-0.55
-0.53
-0.51
-0.49
-0.48
-0.46
-0.44
-0.42
-0.41
-0.39
-0.37
-0.35
-0.34
-0.32
-0.30
-0.28
-0.27
-0.25
-0.23
-0.21
0.005
-0.54
-0.52
-0.51
-0.49
-O.47
-0.45
-O.44
-0.42
-0. 40
-0.38
-O.37
-0.35
-0.33
-0.31
-0.30
-0.28
-0. 26
-0. 24
-0. 23
-0.21
-0. 19
ANNUAL PROBABILITY
0.01 0.02
-0.52 -0.48
-0.50 -0.46
-0.48 -0.44
-0.47 -0.42
-0.45 -0.41
-0.43 -0.39
-0.41 -0.37
-0.40 -0.35
-0.38 -0.34
-0.36 -0.32
-0.34 -O.30
-0.33 -0.28
-0.31 -0.27
-0.29 -0.25
-0.27 -0.23
-0.26 -0.21
-0.24 -0.20
-0.22 -0.18
-0.20 -0. 16
-0. 19 -0. 14
-0.17 -0.13
OF OUTBREAK
0.03
-0.43
-0.41
-0.40
-0.38
-0.36
-0.34
-0.33
-0.31
-0.29
-0.27
-0.26
-0.24
-0.22
-0.20
-0. 19
-0. 17
-0.15
-0. 13
-0.12
-0. 10
-0.08
0.04
-0.39
-0.37
-0.35
-0.34
-0.32
-0.30
-0.28
-0.27
-0.25
-0.23
-0.21
-0.20
-0. 18
-0. 16
-0. 14
-0. 13
-0. 11
-0.09
-0.07
-0 . 06
-0.04
0.05
-0.34
-0 . 33
-0.31
-0.29
-0.27
-0.26
-0.24
-0.22
-0.20
-0. 19
-0. 17
-0.15
-0. 13
-0. 12
-0.10
-0.08
-0.06
-0.05
-0.03
-0.01
0.01
F-14
-------
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration ___ 0.253
Damages -from Endemic Lsvel o-f 1/C 0.237
Damages -from A Representative Outbreak 9.724
ANNUAL PROBABILITY OF OUTBREAK
-0.2
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0.1
O.2
0.3
O.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-O.25
-0.23
-0.21
-0. 18
-0. 16
-0. 13
-0. 11
-0.09
-0 . 06
-0 . 04
-0 . 02
0.01
0.03
0.06
0.08
0. 10
0. 13
O. 15
0. 17
0 . 20
0.22
0 . 005
-O.20
-0. 18
-0.16
-0. 13
-0. 11
-O.09
-0.06
-O. 04
-0.01
0.01
0.03
0. 06
0.08
0. 10
0. 13
0. 15
O. 17
O.20
0.22
0.25
0.27
0.01
-0.16
-0.13
-0.11
-0.08
-O.O6
-0.04
-O.O1
0.01
0.03
0 . 06
0 . 08
0.10
0.13
0.15
0.18
0.20
O.22
0.25
0 . 27
0.29
0.32
0.02
-0.06
-0.03
-0.01
0.01
0.04
0.06
0.08
0. 11
0. 13
0. 15
0. 18
0.20
0.23
0.25
0.27
0.30
0.32
0.34
0.37
0 . 39
0.42
0 . 03
O.O4
0.06
0.09
0.11
0. 13
0. 16
O. 18
0.20
0.23
0.25
0.28
0.30
0.32
0.35
0.37
0.39
0.42
O.44
0.47
0.49
0,51
0.04
0. 14
0. 16
0. 18
0.21
0.23
0.25
0.28
0.30
0.33
0.35
0.37
0.4O
0.42
0.44
0.47
0.49
0.52
0.54
0.56
0.59
0.61
0.05
0.23
0.26
0.2B
0.30
0.33
O.35
0.3B
O.40
0.42
0.45
0.47
0.49
0.52
0.54
0.57
0.59
0.61
0.64
0.66
0.6B
0.71
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration O.253
Damages -from Endemic Level o-f 1% 0.175
Damages from A Representative Outbreak 4.411
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.2
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.3
1.9
2.0
0
-0.25
-0.24
-0.22
-0.20
-0. 18
-0.17
-0. 15
-0.13
-0.11
-0.10
-0.08
-0.06
-0.04
-0.03
-0.01
0.01
0.03
0.04
0.06
0.08
0. 10
0 . 005
-0.23
-0.21
-0.20
-0. 18
-0. 16
-0. 14
-0. 13
-0. 11
-0.09
-0.07
-O.06
-0.04
-O.02
-0.00
0.01
0.03
0.05
0.07
0.08
0. 10
0. 12
0.01
-0.21
-0.19
-0. 17
-0.16
-0.14
-0.12
-0.10
-0.09
-0 . 07
-0.05
-0.03
-0.02
0 . 00
0.02
0.04
O . O5
0.07
0 . 09
0. 11
0. 12
0.14
0.02
-0. 16
-0. 15
-0. 13
-0. 11
-0.09
-0.08
-0.06
-0.04
-0.02
-0.01
0.01
0.03
0.05
0.06
0.08
0. 10
0. 12
0. 13
0. 15
0. 17
0. 19
0.03
-0. 12
-O. 10
-0.09
-0.07
-0.05
-0.03
-O.02
0.00
0.02
0.04
0.05
O.07
0.09
O. 11
0. 12
0. 14
O. 16
0. 18
0.19
0.21
O.23
0.04
-0.08
-0.06
-0.04
-0.02
-0.01
0.01
0.03
0.05
0.06
0.08
0. 10
0. 12
0. 13
0. 15
0. 17
0. 19
0.20
0.22
0.24
0.26
0.27
0.05
-0.03
-0.01
0.00
0.02
0.04
0.06
0.07
0.09
0. 11
0. 13
0. 14
0. 16
0.18
0.20
0.21
0.23
0.25
0.27
0.28
0.30
0.32
F-15
-------
10,001 - 25,000 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0 0.005 0.01 0.02 0.03 0.04 O.O5
E o.O 0 0 0 0111
N 0.1 0 0 0 0 111
D 0.2 0 0 0 0112
E 0.3 0 0 0 1 1-1 2
M 0.4 o 0 0 1 1 1 3
I 0.5 0 0 0112 3
C 0.6 0 0 0 1 1 2 3
0.7 0 0 1 1 2 2 3
L 0.8 0 0 1 1 2 3 3
E 0.9 0 1 1 ! 2 3 3
V i.o 0 1 1 2 2 3 3
E l.i 1 1 1 2 -2 3 3
L 1.2 1 1 2 2 3 o o
1.3 1 1 2 2 3 3 3
1.4 1 2 2 2 3 3 3
1.5 2 2 2 2 3 * 3
1.6 2 2 2 3 3 3 3
1.7 2 2 2 3 3 ^ £
1.8 2 2 2 o- ^ -i ->
F-16
-------
_i
2
(/I
(/I
3
TREATMENT COST VS. ENDEMIC DAMAGES
O.26
3.301 - 10.000 POPULATION
0.2
0.4
0.6 OS 1 1.2
ENDEMIC LEVEL (X OF POP/Y")
1.4
1.6
1.8
TREATMENT COST VS. OUTBREAK DAMAGES
^*.
2
in
2
3.3O1 - 10,000 POPULATION
0.26
0.005 0.01 0.015 0.02 0.025 0.03
ANNUAL P(OUTBREAK) (X) .
F-17
0.035 0.04 0,045 OX)5
-------
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.249
Damages from Endemic Level o-f 17. 0.081
Damages •from A Representative Outbreak 3.276
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.2
0.0
0. 1
O.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.25
-0.24
-0.23
-O.22
-0.22
-0.21
-0.20
-0. 19
-0. 18
-0. 18
-0. 17
-0. 16
-0. 15
-0. 14
-0. 14
-0. 13
-0. 12
-0. 11
-O. 10
-0. 10
-0.09
0.005
-0.23
-0.22
-0.22
-O.21
-0.20
-0. 19
-O. 18
-O. 18
-0. 17
-0. 16
-0. 15
-0. 14
-0. 14
-O. 13
-0. 12
-0. 11
-0. 10
-0.09
-O.09
-0.08
-0 . 07
0.01
-0.22
-0.21
-O.20
-0. 19
-0. 18
-0. 18
-0. 17
-O. 16
-0. 15
-0. 14
-0. 14
-0. 13
-0. 12
-O. 11
-0. 10
-0.09
-0.09
-O.08
-0 . 07
-O. 06
-0.05
0.02
-0.18
-0. 18
-0. 17
-0. 16
-0. 15
-0.14
-0. 13
-0.13
-0. 12
-0. 11
-0. 10
-O.09
-0.09
-0.08
-0.07
-0.06
-0.05
-0.05
-0.04
-0.03
-0.02
0.03
-0. 15
-0. 14
-O. 13
-0. 13
-0.12
-0. 11
-0. 10
-0.09
-0.09
-0.08
-0.07
-0.06
-0.05
-0.05
-0.04
-0.03
-0.02
-0.01
-0.00
0.00
0.01
0.04
-0.12
-0. 11
-0. 10
-0.09
-0.09
-0.08
-0.07
-0.06
-0.05
-O.O5
-0.04
-O.03
-0.02
-0.01
-0.00
0.00
0.01
0 . 02
O.03
0.04
0.04
0.05
-0.09
-0.08
-0.07
-0.-06
-0.05
-O. 04
-0.04
-0.03
-0.02
-0.01
-0.00
0.00
0.01
0.02
0 . 03
0.04
0.04
0.05
0.06
0.07
0.08
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.249
Damages from Endemic Level o-f 17. 0.06
Damages -from A Representative Outbreak
1.491
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0.2
0.0
0. 1
0.2
0.3
0-4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.25
-0.24
-0.24
-0.23
-0.23
-0.22
-0.21
-0.21
-0.20
-0.20
-0. 19
-0. 18
-0. 18
-0. 17
-0.17
-0. 16
-0. 15
-0. 15
-0. 14
-0. 14
-0. 13
0.005
-O.24
-0.24
-0.23
-0.22
-0.22
-0.21
-0.21
-0.20
-0. 19
-0. 19
-0.18
-0. 18
-0. 17
-0. 16
-0. 16
-0. 15
-0. 15
-0. 14
-0. 13
-0. 13
-0. 12
O.01
-O.23
-0.23
-0.22
-0.22
-0.21
-0.20
-O.20
-0. 19
-O. 19
-0. 18
-0. 17
-0. 17
-0. 16
-0. 16
-0. 15
-0. 14
-0. 14
-0. 13
-0. 13
-0.12
-0. 11
0.02
-0.22
-0.21
-0.21
-0.20
-0.20
-0.19
-0. 18
-0. 18
-0.17
-0. 17
-0. 16
-0, 15
-0. 15
-0. 14
-0. 14
-0. 13
-0.12
-0.12
-0.11
-0. 11
-0.10
OF OUTBREAK
0.03
-0.20
-0.20
-0. 19
-0.19
-0.18
-0. 17
-0.17
-0. 16
-0. 16
-0. 15
-0. 14
-0. 14
-0. 13
-0. 13
-0. 12
-0. 11
-O. 11
-0. 10
-0. 10
-0.09
-0.08
0,04
-0. 19
-0. 18
-0. 18
-0. 17
-0. 17
-0. 16
-O. 15
-0. 15
-0. 14
-0.14
-0.13
-0. 12
-0. 12
-0. 11
-0. 11
-0. 10
-0.09
-0.09
-o.oa
-0.08
-0.07
0.05
-0. 17
-0. 17
-0. 16
-0. 16
-0. 15
-0. 14
-0. 14
-0. 13
-0. 13
-0. 12
-0. 11
-0. 11
-0. 10
-0. 10
-0.09
-0.08
-0.08
-0.07
-0.07
-0.06
-0.05
F-18
-------
3,301 - 10,OOO POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.096
Damages -from Endemic Level of IY. 0.081
Damages -from A Representative Outbreak
3.276
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0.1
0.2
O.3
0.4
0.5
0.6
0.7
o.a
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
i.e
1.9
2.0
0
-0. 10
-0.09
-0.08
-O.O7
-O.06
-0.06
-0.05
-0.04
-0.03
-0 . 02
-O.02
-0.01
0 . OO
0.01
0 . 02
0.03
0.03
0.04
0 . 05
0.06
0 . 07
0.005
-0.08
-0.07
-0.06
-O.O6
-0.05
-0.04
-0.03
-0.02
-O.O1
-O.01
O.OO
O.O1
0.02
O.03
O.03
0.04
0.05
0.06
0.07
0.07
0.08
0.01
-0.06
-0.06
-0.05
-O.04
-0.03
-0.02
-0.01
-0.01
0.00
0.01
0 . 02
0 . 03
0.03
0.04
0.05
0.06
0.07
0.07
0.08
0.09
0. 10
0.02
-0.03
-0.02
-O.01
-O.01
0.00
0.01
0.02
0.03
O.03
0.04
0.05
0.06
0.07
0.07
0.08
0.09
0. 10
0. 11
0. 12
0. 12
O. 13
0.03
0.00
0.01
0.02
0.03
0.03
0.04
0.05
0.06
0 . 07
0.08
0.08
0.09
0.10
0.11
0.12
0. 12
0.13
0.14
0.15
0.16
0. 16
0.04
0.04
0.04
O..O5
0.06
O.O7
0.08
0.08
0.09
0. 10
0. 11
0. 12
0. 12
0. 13
0. 14
0. 15
O. 16
0. 16
0.17
0. 18
0. 19
0.20
0.05
0.07
0.08
0.08
0.09
0. 10
0. 11
0. 12
0. 12
0. 13
0. 14
0..15
0. 16
0. 17
0. 17
0. 18
0. 19
0.20
0.21
0.21
Ooo
• 4m^
0.23
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.096
Damages -from Endemic Level o-f 17. O.O6
Damages from A Representative Outbreak
1.491
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.10
-0.09
-0.08
-0.08
-0.07
-0.07
-O.06
-0.05
-O.05
-0.04
-0.04
-0.03
-0.02
-0.02
-0.01
-0 . 0 1
-0 . 00
0.01
0.01
0 . 02
0.02
0.005
-0.09
-0.08
-0.08
-0.07
-0.06
-0.06
-0.05
-0.05
-0.04
-0.03
-0.03
-0.02
-0.02
-0.01
-0.00
0.00
0.01
0.01
0.02
0.03
0.03
0.01
-0.08
-0.08
-0.07
-0.06
-0.06
-0.05
-0.05
-0.04
-0 . 03
-0 . 03
-0.02
-0.02
-0.01
-0.00
0.00
0.01
0.01
0.02
0.03
0.03
0.04
0.02
-0.07
-0.06
-0.05
-0.05
-0.04
-O.04
-0.03
-0.02
-O.02
-0.01
-0.01
-0.00
0.01
0.01
0.02
0.02
0.03
0.04
0.04
0.05
0.05
0.03
-0.05
-0.05
-0.04
-O.03
-0.03
-0.02
-0.02
-0.01
-0.00
0.00
0.01
0.01
0.02
0.03
0.03
0.04
0.04
0.05
O.06
0.06
0.07
0.04
-0.04
-0.03
-O.02
-0.02
-0.01
-0.01
-0.00
0.01
O.O1
0.02
0.02
0.03
0.04
0.04
0.05
0.05
0.06
0.07
O.O7
0.08
0.08
0.05
-0.02
-0.02
-0.01
-0.00
0.00
0.01
0.01
0.02
0.03
0.03
0.04
0.04
0.05
0 . 06
0.06
0.07
0.07
0.08
0.09
0.09
0. 10
F-19
-------
E
N
D
E
M
I
C
L
E
V
E
L
3,301 - 10,OOO POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
0.0
0. 1
0.2
0. 3
0.4
0.5
0.6
0.7
O.B
0.9
1.0
1. 1
1.2
1.3
1.4
,5
,6
1.7
1.8
0
ANNUAL PROBABILITY OF OUTBREAK
0.005
0.01
O.O2
0
0
o
0
0
0
0
0
0
0
0
0
1
1
1
1
1
2
2
0
o
0
0
0
0
0
0
0
0
1
1
1
1
1
2
2
2
2
0
o
0
0
0
0
0
0
1
1
1
1
1
1
2
2
2
2
2
0
0
0
o
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
O.03
O.O4
0.05
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
2
2
^>
o
^.
2
2
*"»
4^
2
3
3
3
3
1
1
1
1
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
F-20
-------
TREATMENT COST VS. ENDEMIC DAMAGES
in
o
W
in
2,
uT"
0.15
0.12 -
0.11 -
0.1 -
0.09 -
OJOS -
0.07 -
0.06 -
0.05 -
0.04 -
OJ33 -
Ofl2 -
O.O1 -
0
1,001 - 3.300 POPULATION
ENDEMIC LEVEL (X OF POP/YR)
M
V)
2
tf
TREATMENT COST VS. OUTBREAK DAMAGES
0.13
0.12 -
0.11 -
0.1 -
O.O9 -
0.08 -
0.07 -
o.oe -
oos -
OXJ* -
O.O3 -
0.02 -
0.01 -
0
1,001 - 3.300 POPULATION
0.005 0X11 0.015 0.02 0.025 0.03
ANNUAL P(OUTBR£AK) (X)
F-21
0.035 0X14 0.045 0.05
-------
- .i,iQt.) POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.124
Damages -from Endemic Level o-f I'/. 0.025
Damages -from A Representative Outbreak 1.225
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0. 1
0.0
0. 1
0.2
0.3
0.4
O.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0. 12
-0. 12
-0. 12
-0.12
-O. 11
-0. 11
-0.11
-0. 11
-0. 10
-0.10
-0. 10
-O. 10
-O.O9
-0.09
-0.09
-0.09
-o.oa
-0.08
-o.oa
-0.08
-0.07
0.005
-0. 12
-0. 12
-0.11
-O. 11
-0. 11
-0. 11
-0. 10
-0. 10
-0. 10
-0. 10
-0.09
-0.09
-0.09
-0.09
-0.08
-0.08
-0.08
-0.08
-0.07
-0.07
-0. 07
0.01
-O. 11
-0. 11
-0. 11
-0. 10
-0.10
-O. 10
-0. 10
-0.09
-0.09
-0.09
-0.09
-0 . 08
-O.08
-0.08
-0.08
-O.07
-0.07
-0.07
-0.07
-0.06
-0.06
0.02
-0. 10
-0. 10
-0.09
-0.09
-0.09
-0.09
-0.08
-0.08
-0.08
-0.08
-0 . 07
-0.07
-0.07
-0.07
-0.06
-O.06
-0.06
-0.06
-0.05
-0.05
-0.05
OF OUTBREAK
0.03
-O.09
-0.08
-0.08
-0.08
-0.08
-0.07
-0.07
-0.07
-0.07
-0.06
-O.06
-O.06
-0.06
-O.05
-0.05
-O.05
-O.05
-0.04
-O.04
-0.04
-0.04
0.04
-0.08
-0.07
-0.07
-0.07
-0.06
-0.06
-0.06
-0.06
-0.05
-0.05
-O.O5
-0.05
-O.O4
-0.04
-0.04
-0.04
-0.03
-0.03
-0.03
-O.O3
-0.02
0 . 05
-O.O6
-0.06
-0.06
-0.06
-0.05
-O.O5
-0 . 05
-0 . 05
-0.04
-0.04
-0.04
-0.04
-0 . 03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0 . 02
-0.01
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.124
Damages •from Endemic Level o-f 17. 0.019
Damages -from A Representative Outbreak
0.6279
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0. 1
0.0
0. 1
0.2
0.3
O.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.12
-0. 12
-0. 12
-0. 12
-0. 12
-0. 11
-0 . 1 1
-0. 11
-0. 11
-O. 11
-0. 11
-0. 10
-0. 10
-0.10
-0. 10
-0. 10
-0.09
-O.O9
-O.09
-0.09
-0.09
0.005
-0. 12
-0.12
-0. 12
-0. 12
-0. 11
-0. 11
-0. 11
-0. 11
-0. 11
-0. 10
-0. 10
-0. 10
-0. 10
-0. 10
-0.09
-0.09
-0. 09
-0.09
-0.09
-0.08
-0.08
0.01
-0.12
-0. 12
-0.11
-0.11
-0.11
-0.11
-O. 11
-0.10
-0. 10
-0. 10
-O. 10
-0.10
-0.09 .
-0.09
-0 . 09
-0.09
-0 . 09
-O.O9
-O.08
-0.08
-0.08
0.02
-0.11
-0. 11
-0. 11
-0. 11
-0.10
-0. 10
-0. 10
-0. 10
-0. 10
-0.09
-0.09
-0.09
-0.09
-0.09
-0.08
-0.08
-0.08
-0.08
-0.08
-0.08
-0.07
OF OUTBREAK
0.03
-O. 11
-0. 10
-0. 10
-0. 10
-0. 10
-0. 10
-0.09
-0.09
-0.09
-0.09
-0.09
-0.08
-0.08
-0.08
-0.08
-0.08
-O.O7
-O.O7
-0.07
-0,07
-0.07
0.04
-0.10
-0. 10
-0.10
-0 . 09
-0.09
-0.09
-0.09
-0.09
-0.08
-0.08
-o.oa
-0.08
-0.08
-0.07
-0.07
-0.07
-0.07
-0.07
-0.06
-0.06
-0.06
O.O5
-0.09
-0.09
-0.09
-O.O9
-0.09
-0.08
-0 . 08
-0.08
-O.OB
-0.08
-0.07
-O.07
-0.07
-0.07
-0.07
-0.06
-O.O6
-0.06
-0.06
-0.06
-0.05
F-22
-------
1,001 - 3,300 -POPOLATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 0.047
Damages -from Endemic Level o-f 1% O.O25
Damages -from A Representative Outbreak 1.225
ANNUAL PROBABILITY OF OUTBREAK
-0 . 0
E
N
D
E
M
I
C .
L
E
V
E
L
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
l.S
1.9
2.0
0
-0.05
-0.04
-0.04
-0.04
-0.04
-O.O3
-0.03
-0.03
-0.03
-0.02
-O.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
0.00
0.00
0.005
-O.04
-0.04
-O.04
-O.03
-0.03
-O.03
-0.03
-0.02
-0.02
-0.02
-O.02
-O.01
-0.01
-0.01
-0.01
-0.00
-0.00
0.00
0.00
O.01
0.01
0.01
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.01
-O.O1
-0.01
-0.01
-0.00
-0.00
0.00
0.00
0.01
0.01
0.01
0.01
O.02
0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
0.00
0.00
0.01
0.01
0.01
0.01
0.02
0.02
0.02
0.02
0.03
0.03
0.03
-0.01
-0.01
-0.01
-0.00
-0.00
0.00
0.00
0.01
0.01
0.01
O.01
0.02
O.02
0.02
0.02
0.03
0.03
O.03
0.03
O.04
0.04
0.04
0.00
0.00
0.01
0.01
0.01
O.O1
0.02
0.02
0.02
0.02
0 . 03
0.03
0.03
0.03
0.04
0.04
0.04
0.04
0.05
0.05
0.05
0.05
0.01
0.02
O.O2
0.02
O.02
0.03
0.03
0.03
0.03
0.04
O.O4
0.04
0.04
0.05
0.05
O.05
0.05
0.06
0.06
O.06
0.06
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-F Filtration 0.047
Damages -from Endemic Level o-f 17. 0.019
Damages -from A Representative Outbreak
0.6279
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0.1
0.2
O. 3
0.4
0.5
0.6
0.7
O.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.05
-0.05
-0.04
-0.04
-0.04
-0.04
-0.04
-0.03
-O.03
-0.03
-O.03
-0.03
-0.02
-0 . 02
-0.02
-0.02
-0.02
-0.01
-O.01
-0.01
-0.01
0.005
-0.04
-0.04
-0.04
-0.04
-0.04
-0.03
-0.03
-0.03
-O.03
-0.03
-0.02
-0,02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
0.01
-0.04
-0.04
-0.04
-0.04
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-O.O2
-0.02
-0.01
-0.01
-0.01
-0.01
-O.01
-0.00
-0.00
0.02
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
-0.00
0.00
0.00
0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-O.OO
-0.00
0 . 00
0.00
0.00
0.01
0.01
0.01
0.04
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
- -0.01
-0.00
-O.OO
-0.00
0.00
O.OO
0.00
0.01
0.01
0.01
0.01
0.01
0.02
0.05
-O.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
-0.00
0.00
0.00
0.01
O.O1
0.01
0.01
0.01
0.01
0.02
0.02
0.02
0.02
F-23
-------
1,001 - 3,300 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
F,
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1. 4
1.5
1.6
1.7
1.8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
O.OO5
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0.01
0
0
0
o
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0 . 02
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
0 . 03
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
0.04
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
*^l
0 . 05
1
1
1
1
1
1
1
1
1
2
2
2
2
•^i
2
2
2
2
2
F-24
-------
w
I/I
3
TREATMENT COST VS. ENDEMIC DAMAGES
0.07
0.06 -
0.05 -
0.0* -
0.03 -
0.02 -
0.01 -
5O1 - 1 .OOO POPULATION
0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
ENDEMIC LEVEL (X OF PQP/YR)
£
in
tn
3
TREATMENT COST VS. OUTBREAK DAMAGES
5O1 - 1.000 POPULATION
0.07
0.06 -
OXJS -
3 0.04 -
0.03 -
0.02 H
0.01 -
0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 O.05
ANNUAL P(OUTBREAK) (*)
-------
rorui_HTioiM
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 0.07
Damages from Endemic Level of 17* 0.01
Damages from A Representative Outbreak O.4022
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-O.07
-0.07
-0.07
-0.07
-0.07
-0.07
-0 . 06
-0.06
-0.06
-0.06
-0.06
-0.06
-O.06
-0.06
-0.06
-0.06
-0.05
-0.05
-0 . 05
-0.05
-0.05
0.005
-0.07
-0.07
-0.07
-0.06
-0.06
-O.06
-0.06
-0.06
-0 . 06
-0.06
-0.06
-0.06
-O.06
-O.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0 . 05
-0.05
0.01
-0.07
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0 . 05
-0.05
0.02
-0.06
-0.06
-0.06
-0.06
-0.06
-O.06
-O.06
-0.05
-0.05
-0.05
-0.05
-0.05
-O.05
-0.05
-0.05
-0.05
-0.05
-O.04
-O.O4
-0.04
-0,04
OF OUTBREAK
0.03
-0.06
-0.06
-0.06
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0 . 05
-0.05
-0.05
-0.05
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
0.04
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0. 04
-0.04
-0.04
-O.O4
-0.03
-0 . 03
0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.04
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 0.07
Damages from Endemic Level of I'/. 0.007
Damages from A Representative Outbreak
0.2201
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-O.O
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.07
-0.07
-0.07
-0.07
-0.07
-0.07
-0.07
-0.07
-0.06
-0 . 06
-0.06
-0.06
-0.06
-0 . 06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
0.005
-O.O7
-0.07
-0.07
-0.07
-O.07
-0.07
-O.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-O.06
-0.06
-0.06
-0.06
-0.05
O.01
-O.07
-0.07
-0.07
-0.07
-0.06
-0.06
-0.06
-0.06
-O.06
-0.06
-O.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.05
-0.05
0.02
-0.07
-O.06
-0.06
-0.06
-0.06
-O.06
-O.06
-0.06
-0.06
-0.06
-O.06
-0.06
-0.06
-0.06
-0.06
-0 . 06
-0.05
-0.05
-0.05
-0.05
-O.05
OF OUTBREAK
0.03
-0.06
-0.06
-0.06
-0.06
-0.06
-O.O6
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
0.04
-0.06
-O.O6
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.06
-0.05
-O.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
O.05
-0.06
-O.06
-0.06
-0.06
-0.06
-0.06
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0.05
-0 . 05
-0.05
-0.05
-0.05
-0.04
F-26
-------
501 - 1,000 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost of Filtration 0.035
Damages -from Endemic Level of IV. O.O1
Damages -from A Representative Outbreak 0.4022
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-O.O
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.04
-0.03
-0.03
-0.03
-0.03
-O.O3
-0.03
-O.O3
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0 . 02
-0.02
-0 . 02
-0.02
-0.02
0.005
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-O.02
-0.01
-0.01
-0 . 0 1
0.01
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-0.01
-0.01
-0.01
-0.01
-O.01
0.02
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-O.O1
-O.O1
-0.01
-0.01
-0.01
-0.01
OF OUTBREAK
0.03
-0.02
-0.02
-0.02
-0,02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.O1
-0.01
-0.01
-0.00
-o.oo
-0.00
0.04
-O.02
-0.02
-0.02
-0.02
-O.01
-O.01
-0.01
-0.01
-0.01
-0.01
-O.01
-O.01
-0.01
-0.01
-0.00
-o.oo
-0.00
-o.oo
-0 . 00
0.00
0 . OO
0.05
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.00
-0.00
-0.00
-0.00
-0.00
0.00
0.00
0.00
0.00
0.00
0.01
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.035
Damages from Endemic Level o-f 1/C O.OO7
Damages from A Representative Outbreak
0.2201
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0. 3
0.4
0.5
0.6
0.7
O.S
0.9
1.0
1. 1
1.2
• 1.3
1.4
1.5
1.6
1.7
i.a
1.9
2.0
0
-0.04
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0 . 02
-0.02
-0.02
-0 . 02
-0 . 02
-0.02
0.005
-O.03
-O.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-O.03
-O.02
-O.02
-0.02
-0.02
-0.02
-O.02
-0.02
-O.02
0.01
-0.03
-O.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-O.03
-0.03
-0.02
-0.02
-0.02
-O.02
-0.02
-0.02
-0.02
-0.02
-0.02
0.02
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.O2
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
OF OUTBREAK
0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0,02
-O.O2
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
0.04
-0.03
-0 . 03
-O.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-0.02
-0.01
-O..01
-O.01
-0.01
-0.01
0.05
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0. 02
-O.02
-0.02
-O.02
-0.02
-0 . 02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
7-27
-------
501 - 1,000 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
0.005
0.01
0.02
0.03
0. 04
0.05
E
N
D
E
M
I
C
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
O.B
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
o
0
o
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
o
0
0
0
0
0 ,
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
1
1
1
1
F-28
-------
TREATMENT COST VS. ENDEMIC DAMAGES
101-500 POPULATION
0.035
0.03 -
£ O.O25 -
3 O.02 -
0.015-
1ft
(ft
O
W 0X31 -
0.005 -
1.2 1.4 1.6 1.8
0.2 0.4 O.6 0-8
ENDEMIC LEVEL (X OF POP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
1O1 - 500 POPULATION
0.035
0.03 -
0.025 -
in
I
(fl
M
Q
O.02 -
0.015 -J
0.01 -
0.005 -
0 0.005 0X31
O.O15 OJ32 0.025
ANNUAL P(OUTBPCAK) (X)
F-29
O.O35 0.04 0.045 0X35
-------
101 - 500 POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.035
Damages -from Endemic Level o-f 17. 0.0034
Damages -from A Representative Outbreak 0.1404
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0 . 0
0 . 0
0.1
0.2
O.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0 . 04
-0.03
-0.03
-0 . 03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
0.005
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
0.01
-O.03
-0.03
-0.03
-O . O3
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-O.O3
-0 . 03
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-O.O3
0 . 02
-0 . 03
-0 . 03
-0 . 03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
0.03
-0 . 03
-0 . 03
-0 . 03
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-O.03
-0 . 03
-O.03
-0.03
-0.03
-O.03
-O.03
-O.03
-0.03
-0.03
-O.02
-0.02
-O.02
0.04
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
0.05
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-0.02
-0.02
-O.02
-0.02
-0.02
HIGH TREATMENT COST - LOW DAMAGE" ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.035
Damages -from Endemic Level o-f IV. O.0025
Damages -from A Representative Outbreak 0.0768
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
O.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.04
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-O.03
-0.03
-0.03
-O.O3
-0.03
-0.03
-0.03
-0.03
0.005
-0.03
-0.03
-0.03
-0. 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-O.03
-0.03
-O.03
-0.03
-O.03
-0.03
-0.03
0.01
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-O.03
-0.03
-0.03
-O.03
-0.03
-O.O3
-O.03
-0.03
-O.03
-0.03
-0.03
-0.03
'-0.03
0.02
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
O.03
-0.03
-0.03
-O.03
-O.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
0.04
-0.03
-0.03
-0.03
. -0.03
-0.03
-0.03
-0.03
-0.03
-O.O3
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
0.05
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-0.03
-O.03
-O.O3
-0.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
F-30
-------
101 - 500 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.018
Damages -from Endemic Level o-f I"/. 0.0034
Damages •from A Representative Outbreak
0.1404
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0 . 02
-0 . 02
-0.02
-0.02
-0.02
-0 . 02
-0.02
-0.02
-0.02
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
0.005
-0.02
-0.02
-0.02
-0. 02
-0.02
-0.02
-O.02
-0.01
-0.01
-0.01
-0.01
-O.01
-O.01
-0.01
-0.01
-O.01
-O.01
-0.01
-0.01
-0.01
-0.01
0.01
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.02
-0.02
-0 . 0 1
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
OF OUTBREAK
0 . 03
-0 . 0 1
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0 . 0 1
-0.01
-0.01
-0.01
-0 . 0 1
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
0.04
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0 . 05
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.O1
-0.01
-0.00
-0 . 00
-o.oo
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO '
Annual Cost o-f Filtration 0.018
Damages -from Endemic Level of 17. 0.0025
Damages -From A Representative Outbreak
0.0768
ANNUAL PROBABILITY
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-O.02
-O.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.005
-0.02
-0.02
-0.02
-0^02
-0.02
-0.02
-0.02
-O.02
-0. 02
-0.02
-0. 02
-0.01
-0.01
-0.01
-O.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
0.01
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
OF OUTBREAK
0.03
-0.02
-0.02
-0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0 . 0 1
-0.01
-0.01
0.04
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.05
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
F-31
-------
101 - SCO POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
O . 0
0. 1
O.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0 . 005
0
o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.01
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 . 02
0
o
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
o
0
0 . 03
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.04
o
0
0
0
0
0
o
0
o
0
0
0
o
0
0
0
0
0
0
O.O5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
F-32
-------
TREATMENT COST VS. ENDEMIC DAMAGES
25 - 100 POPULATION
MILLIONS/YR)
S
E[LOSS]
.UONS/YR)
^
«»
n
M
s,
U*
0.03 -
0.028 -
O.Q26 -
0.024 -
0.022-
O.O2 -
O.O18 -
0.016 -
0.01 4 -
0.012 -
0.01 -
O.OO8 -
0.006 -
0.004 -
0.002 -
0 -
C
— = '
| «™«ggf= | •'• 1 1 i i i i
) 0.2 0.4 0.6 0^ 1 1-2 1.4 1.6 1.8 2
ENDEMIC LEVEL (X OF POP/YR)
TREATMENT COST VS. OUTBREAK DAMAGES
0.03 -
0.028 -
0.026 -
0.024 -
0.022-
OJD2 -
O.O18 -
0.016 -
0.014-
0.012 -
0.01 -
0.008 -
0.006 -
0.004 -
0.002-
0 -
I
25-100 POPULATION
"
-
3 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05
ANNUAL £(QUTBREAK) (X)
-------
25 - 100 POPULATION
HIGH TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.03
Damages -from Endemic Level o-f 17. 0.0008
Damages -from A Representative Outbreak 0.0327
ANNUAL PROBABILITY
-n . o
E
N
D
E
M
I
c
L
E
V
E
L
0 . 0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
i.a
1.9
2.0
0
-0.03
-0.03
-O.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-O.O3
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
0 . 005
-0.03
-0.03
-0 . 03
-0.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
. -0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0 . 03
-0 . 03
0.01
-0 . 03
-0 . 03
-0.03
-0.03
-0.03
-O.03
-0.03
-0 . 03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
0.02
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.O3
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
OF OUTBREAK
0.03
-0 . 03
-0.03
-0.03
-0 . 03
-O.03
-0 . 03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
0 . 04
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0 . 03
-O.03
-0.03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-O.03
-0.03
-0.03
' -0 . 03
0.05
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
HIGH TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.03
Damages -from Endemic Level o-f 17. 0.0006
Damages from A Representative Outbreak
0.0179
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
-0.0
0.0
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
O
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-O.03
-O.03
-0 . 03
-0.03
-0.03
-0.03
0.005
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-0.03
-0.03
-O.03
-O.O3
-0.03
-0.03
-O.03
-O.O3
-O.03
-0.03
-0.03
-0.03
-0.03
0.01
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-O.03
-0.03
-0.03
-0.03
-0.03
-0.03
0.02
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-O.03
-0.03
-0.03
-0.03
-0.03
0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.C3
-0,03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
0.04
-O.03
-0 . 03
-0.03
-0 . 03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-0.03
-O.03
-O.03
-O.03
-0.03
-0.03
-0.03
-0.03
0.05
-0.03
-0.03
-0 . 03
-0.03
-0 . 03
-O.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
-0.03
-0 . 03
-0.03
-0.03
-0.03
-0.03
F-34
-------
25 - 100 POPULATION
LOW TREATMENT COST - HIGH DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.009
Damages from Endemic Level o-f 17. 0.0008
Damages -from A Representative Outbreak 0.0327
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-0.0
0.0
0.1
O.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.O
0
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
0.005
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-O.01
-0.01
-O.01.
-O.01
-0.01
-0.01
-0.01
0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0 . 03
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-O.01
-O.01
-0 . 0 1
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
0.04
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0 . 05
-0.01
-0.01
-0.01
-O.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
LOW TREATMENT COST - LOW DAMAGE ESTIMATE SCENARIO
Annual Cost o-f Filtration 0.009
Damages -from Endemic Level o-f 17. O.OOO6
Damages -from A Representative Outbreak 0.0179
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
C
L
E
V
E
L
-O.O
o.o
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
0
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-O.O1
-O.01
-0.01
-0.01
-0.01
-O.01
-O.01
-0.01
-0.01
-0.01
-0.01
O.005
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0,01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.O I
-0.01
-O.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
0.02
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
0 . 03
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.01
0.04
-O.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0.01
-0 . 0 1
-0.01
-0.01
-O.01
-0.01
0.05
-O.01
-0.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-O.01
-0.01
-0.01
-0.01
-0.01
-0.01
-O.O1
-0.01
-0.01
-0.01
-0.01
-0.01
F-35
-------
25 - 100 POPULATION
LIKELIHOOD OF OBTAINING POSITIVE NET BENEFITS FROM FILTRATION
ANNUAL PROBABILITY OF OUTBREAK
E
N
D
E
M
I
c
L
E
V
E
L
O.O
0. 1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
l.O
1. 1
1.2
1.3
1.4
1.5
1.6
1.7
i.e
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.01
0
0
0
0
0
0
0
0.
0
0
0
0
0
0
0
0
0
0
0
0.02
o
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0.03
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.04
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.05
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
F-36
------- |