7A-600/5-75 001
£BRUARY 1975
                      Socioeconomic Environmental Studies Series
     Evaluation of Alternative Methods
                   for Financing
     Municipal  Waste Treatment Works
                               Office of Research and Development
                               U.S. Environmental Protection Agency
                               Washington D. C.

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               RESEARCH REPORTING SERIES


Research reports of the Office of Research and Development,
Environmental Protection Agency, have been grouped into five
series.  These five broad categories were established to
facilitate further development and application of environmental
technology.  Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface
in related fields.  The five series are:

     1.  Environmental Health Effects Research
     2.  Environmental 'Protection Technology
     3.  Ecological Research
     4.  Environmental Monitoring
     5.  Socioeconorrtic Environmental Studies


This report has,been assigned to the SOCIOECOHOMIC ENVIRONMENTAL STUDIES
series.  This series describes research on the socioeconomic impact of
environmental piroblems.  This covers recycling and other recovery
operations with emphasis on monetary incentives.  The non-scientific
realms of legal systems, cultural valuen, and business systems are
also involved.  Because of their interdisciplinary scope, system
evaluations an<| environmental management reports are included in this
series*

This report has DOon reviewed by the Office of Research and
Development.  Approval docs, not signify that the contents
necessarily reflect the views and policies of the Environmental
Protection Agency, nor does mention of trade names or commercial
products constitute endorsement or recommendation for use.

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                                        EPA-600/5-75-001
                                        March 1975
  EVALUATION OF ALTERNATIVE METHODS FOR
FINANCING MUNICIPAL WASTE TREATMENT WORKS
                        By

                Russell J. deLucia
                 Lewis M. Koppel
                 Daniel F. Luecke
                 Sandra J. Robinson
                Penelope H. Schafer
                 Douglas V. Smith
                 Judith J. Wagner
               Contract No. 68-01 -2411
                   ROAP 21AXN06
                  Project No. 1BA030
                    Project Officer

                  Dr. Marshall Rose
      Washington Environmental Research Center
               Washington, D.C. 20460
                   Prepared for

         Office of Research and Development
       U. S. Environmental Protection Agency
             Washington, D.C. 20460

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                         ABSTRACT

This report is part of a continuing investigation by the
EPA of alternative financing programs for treatment plant
facilities undertaken in response to Section 317 of The
Water Pollution Control Act Amendments of 1972.  This re-
port presents findings and recommendations regarding alter-
native financing programs.  The report reviews the current
programs, describes criteria for the evaluation of financing
programs and discusses some differences of current programs
in light of these criteria.  Important features of alterna-
tive financing programs are discussed and analysis of fea-
tures that could be changed to improve program preference
according to the criteria is presented.

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                         CONTENTS



                                                   Page



Abstract



List of Figures



List of Tables



Acknowledgments



Sections



       Executive Summary                             1



         Findings                                    3



         Recommendations                             4




1      Introduction                                  6



         Description of Problem                      6



        • Wastewater System Definition                7



         Assumptions of the Study                   11



         Criteria                                   14



         Financing Alternatives                     14



         Report Organization                        14




2      The Present Situation                        16



         Background                                 16



         The Current Federal Grant Program          17



           Allotments                               17



           Project Priority Lists                   18



           Facility Planning                        20
                            111

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            CONTENTS  (continued)

                                           Page

    Reimbursement                           20

    Grant Application and Approval          20

    Grant Award                             21

    Project Costs                           22

    Grant Percentage                        22

  The State Programs:  A Summary            22

  Local Financing Programs                  29

    Traditional Methods of Financing        30

    Currently "Popular" Methods of          30
    Financing

      User Charge Financing                 30

      Special Assessments                 * 31

      Revenue Bonds                         32

      Intermunicipal Arrangements to
      Provide Financing                     32

    Choosing a Finance Program              33


Selection Criteria and Features
of Financing Alternatives                   34

  Introduction                              34

  Criteria                                  35

  Deficiencies in Existing Programs         38

  Features of Alternatives                  40

    Allotment and Grant Formulas            40
                     IV

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            CONTENTS (continued)
      The Allotment Formula                 41

      The Grant Formula                     45

  Eligible Items and a Consideration of
  the Total Wastewater System               49

  Loan Programs                             52

  Operation and Maintenance Grants          54

  Planning and Performance Standards        55

    Planning Standards and
    Cost Estimating                         57

      Continuing Performance Standards
      and the Leverage on Operation
      and Maintenance                       58

      Effecting Changes in Operation
      and Maintenance:  Some Examples       59

  Conclusions                               61


Quantitative Analysis of Financing
Alternatives                                62

  Introduction                              62

  The Community Classification Scheme       63

  Results                                   67

  The Municipal Model and Analysis          71

    Approach to the Model                   71

  Criteria, Impact Measures and
  Local Choice                              72

  What the Model Can Tell Us                73

  The Cases                                 73

                      v

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                  CONTENTS  (continued)

                                                 Page

        How  the Model Works                       76

        Review of Assumptions                     86

        Results                                   87

        A National  Operation and Maintenance
        Grant Analysis                            100

        Conclusions                              108


5      Bibliography


Appendices

A      Legislative History of Federal
       Wastewater Financing Programs              116

         Public Law 660:  1955-56                 118

         Federal Water Pollution Control
         Act Amendments:  1961                    122

         1966 Amendments:  The Clean Water
         Restoration Act                          123

         Water Quality  Improvement Act:   1968     125

         Water Quality  Improvement Act:   1970     126

          Public Law 92-500:   1972                 127


 B       Current Federal  Grant Program             129

          Facility Planning                        129

          Grant Application  and Approval          130

          Project Costs                             132
                             VI

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                   CONTENTS (continued)

                                                  Page

       Issues in Fiscal Federalism                134

         Types of Grants                          136

         Allotment Formula                        141

         Shift Toward Block Grants                145

         References                               146
D      Analysis of Time Patterns of
       Expenditures                               147
E      Municipal Classification Analysis          165

         Relevant Characteristics                 165

           Availability of Data                   166

           Classification Methodology Adopted     168

           Results                                172

           Definitions of Class Variables         185


F      Example of Simulation Model Calculation    187
                             VII

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                          FIGURES
 1     Typical Wastewater Systems                      9

 2     Decision Periods Within Planning Period        76

 3     Per Capita Municipal Cost for Biological
      Treatment branch 12, with Various grant
      levels                                         93

 4     Per Capita Municipal* Cost with No Grants
      and 75,000 Initial Population                  96

 5     First Year Per  Capita  Municipal Cost  as a
      Function of  Grant Levels  (Case C:   City
      of 75,000 with  Biological Treatment)           97

 6     First Year Per  Capita  Municipal Cost  as a
      Function of  Grant Levels  (Cases A  & D:
      Cities  of  25,000 and  500,000 with  Biological
      Treatment)                                     ^°

 7     Per Capita Municipal  Cost  for  Grant Based  on
      Existing Population and Grant  Based on
      Projected  Population  (75%  Capital  and 0% O&M)  101

 8     First Year Per  Capita Municipal Debt  as a
      Function of  Capital Grant  (0%  O&M grant)       102

 9     Operation  of Allotment Formula Based  on Per
      Capita  Income with  Uniform Matching Grant      143

10     BOD  Removal  Time Patterns  75%  Capital Grant   149

11      Source  Control  Time Pattern 75% Capital Grant 150
                            Vlll

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No.
                           TABLES

                                                     Page
1     State Programs for Financing of Municipal       23
      Waste Treatment Works

2     State Construction Grant Programs               28
      Number of State Programs in Various
      Categories

3     State "Needs" Ranking                           42

4     Implications of Operation and Maintenance       60
      Problems and Some Solutions

5     Population/Growth Rate Contingency Table        65
                                                      68
6     Chi-Square  Statistic
      Financing Alternatives Examined with the
      Simulation  Model                                74
 8     Definition  of  Cases

 9     Treatment  Decision  Options                      78

10     Parameters  of O&M Cost Functions               81

11      Parameters of Capital Cost  Functions           82

12      Present Value of Local Costs for City of 2     88
       25,000 with 1% Growth Rate, No Ancillary
       Costs, No industry and No Existing Upgradable
       Treatment Capacity (Discount Rates of 7 & 10%)

13     Present Value of Total Costs, Cities with 1%    89
       Growth Rate, No Industry

14     Present Value of Total Costs, Cities with 5%    91
       Growth Rate and No Industry

15     Costs of Operation and Maintenance  Grant       105
       Program
                               IX

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                     TABLES (continued)

No.                                                   Page

16-21   State Control Totals for Various Expendi-     152-
        tures in Order of Increasing Facility Cost    157

22-27   State Control Total for Various Expendi-      159-
        tures in Order of Increasing BOD Removed/     164
        Dollar

28      Population/Growth Rate Contingency Table      171

29      Chi-Square Statistic                          173

30      Population/Percent Low Income Families        175
        Contingency Table

31      Population/Median Family Income Contingency
        Table                                         176

32a-c   Population/Three Income Classes               177-
        Contingency Tables                            179

33      Population/Per Capita Debt Contingency Table  180

34      Population/Per Capita Revenue                 181
        Contingency Table

35      Population/Per Capita Sewered Contingency     182
        Table

36      Population/Excess Capacity Contingency Table  183

37      Population/Industrial Share Contingency Table 184

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                      ACKNOWLEDGMENTS
Meta Systems Inc wishes to acknowledge the guidance, reviews
and professional critique provided by the Project Officer,
Dr. Marshall Rose and his colleague Dr. John Goldstein.
Many people, all too numerous to name, of EPA at both the
regional and headquarters offices and of all fifty state
agencies cooperated in providing information and guidance,
and for this we express our gratitude.
                              XI

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                     EXECUTIVE SUMMARY

The Water Pollution Control Act Amendments of 1972  provide
for 75 percent federal grants for treatment plant facili-
ties.  The method of financing the municipal expenditures
mandated by the legislation was a ma3or issue of concern in
debates preceding the adoption of the Amendments.  Section
317 of the Amendments specifically recognized the need for
continuing investigation of alternative financing programs
by the Environmental Protection Agency (EPA) .

Three important issues raised by critics of  the current
financing program are:

1.   the  inefficiency  in the  allocation of  resources to
     water pollution control?

 2.   the  rate  at which water  quality  improvement
     proceeds ;  and

 3.   the  distributional  and equity impacts of the program.

 This study,  one  part of the continuing i^f^f^ion  of
 alternative financing programs for treatment plant facili
 ties, considers  these issues.
e^s'of SS'^tT^r^.ra.'-
equalizing effects of grants on per "Pitacost and o ost
                        ™~«*
 per dollar of personal %™~«*%!£Z5£ Requirements and


 described  in this  report.



  tified   Selected alternatives were analyzed against  the
             -

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a classification analysis of community types and a formal
though simple model of the impacts on municipalities of
alternative financing schemes.  Due to data limitations
these analyses were based on examples of municipalities with
populations greater than 25,000.*  Because inclusion of
smaller communities in the analysis will broaden the range
of per capita costs and the range of local waste reduction
options (to make individual treatment and land disposal
more attractive), our conclusions can only be expected to
be reinforced.  Finally, recommendations for federal policy
to more effectively enhance the quality of our nation's
waters and to more equitably share the costs of water pollu-
tion control were developed.

Two assumptions are important to this study.  The first of
these is that the spirit of the Amendments will be met.
With certain specific exceptions all municipalities will
have to meet the mandate of the law.  The second assumption
is that in general existing wastewater treatment systems
are operated inadequately so that an incentive for better
use of wastewater systems is an important consideration in
the design of a financing program.

Findings of this study suggest need for increased awareness
of the equity implications of financing alternatives.  This
is because the 1972 Amendments require all municipalities
to control pollution (essentially no local choice exists)
no matter to whom the benefits accrue, and because there
are large differences in cost burdens placed on communities.
                                                  I
Seven characteristics are used to describe each financing
alternative analyzed in this study:  (1) allotment formula
(for distribution to states); (2) grant formula (for distri-
bution of funds to municipalities); (3)  extent of wastewater
system eligible for assistance;  (4) size of construction
loan; (5)  size of operation and maintenance grant; (6)
planning standards; and (7) plant performance standards.
     *  Data problems caused by delays in publication of the
     1972 Census of Governments, costs of assessing socio-
     economic information from the 1972 Census of Population
     and reliability of data in the 1973 Survey of Needs
     were considerable,  we are confident, however, that
     best use has been made of available data and that fur-
     ther information will merely add corroborative detail.

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The following pages present the findings and recommendations
of this study.
FINDINGS
1.  The effectiveness of any financing program designed to
comply with the 1972 Amendments is primarily dependent on
facility performance.  A financing program can be designed
to provide continuing incentives to municipalities to
operate and maintain facilities effectively.

2   Grants for operation and maintenance of municipal
wastewater treatment facilities cannot only provide incen-
tive  to keep  facilities well-maintained and effectively
operated but  can  also reduce local incentives  to overcapi-
talize.

3   The current allotment  formula provides  no  incentive  to
states to  proceed with  treatment facility construction at
a  faster rate than the  national average  or  to  ensure  ettec-
tive  facility performance.

 4.   Current restriction of project  eligibility to  treatment
 plants  and ancillary facilities results  in  certaincases in
 local adoption of waste treatment  or reduction measures  that
 are not least costly.
struc
 5.  The tcommunity characteristics of population,
 rate, fiscal situation, wastewater system ^ara
 industrial share of wastewater load and family inc
 ture exhibit wide variations across the nation and
 with varying ancillary needs imply large differences £MP«
 capita  costs borne by communities under the existing federal
 construction, grants program.
               t                          u
 of  the water  pollution  expenditures  required  by  current
 legislation.



  for large numbers of communities.
  R   The present value of local costs is not significantly
  altered by selection of 10, 20 or 30 year design periods

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for determination of treatment plant capacity.   Consequently,
localities will tend to choose the larger plant because of
the difficulties of financing frequent bond issues and
because of the political attractiveness of growth-oriented
planning.  Efficiency losses of such decisions may not be
great; short-run budget implications could be considerable.

9.  The alternative of a construction grant program that
restricts the size of treatment facilities to meet only
existing population makes more severe the variation in per
capita costs across communities and encourages selection of
inefficiently-sized facilities, many of which will rapidly
become overloaded.

RECOMMENDATIONS

1.  Federal financing programs should be altered to include
provisions specifically designed to encourage effective
plant performance.  Programs might best include grants to
assist with operation and maintenance costs.  Supplemental
operation and maintenance grants would increase the federal
share of total costs, reduce incentives to overcapitalize
and undermaintain, encourage treatment facility performance
of an acceptable  standard and modestly reduce the inequitable
spread of per capita costs among communities.

In the event a supplemental operation and maintenance grant
is not adopted, the construction grant program should be
restructured as an annual transfer payment conditional on
meeting  performance standards.  Improvements in BOD removal
efficiencies of 5 to 15 percent may be expected at minimal
increased cost with such performance^ incentives.

2.  Waste reduction at least cost should be the .criterion
for eligibility of project components so that projects to
reduce waste discharged to a treatment plant would be  fund-
able.  Furthermore, individual treatment systems  should be
preferred to centralized treatment where soil and hydrologic
conditions permit and costs are lower.

3.  A financing program should include requirements for
planning and design review based  on  augmented cost-effective-
ness guidelines.  Incentives  for  engineers  to recommend
facilities more costly than necessary must  be eliminated.

4.  The  grant formula design should  include several compo-
nents.   Per capita financial burdens across municipalities

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should be made more nearly equal with provisions in the
formula to account for the cost effects of a municipality's
population size, growth rate, income structure, percentage
of industrial flow and the need to build ancillary facili-
ties.  Special compensating provisions should be made to
municipalities to reflect the cost impact on low-income
groups.  The grant formula would achieve more equitable
results if coupled with an operation and maintenance grant
program.

5.  The equity arguments in favor of a 75 percent construc-
tion grant mitigate against any reduction in the grant
percent/ especially considering the modest federal contri-
bution to the total cost to municipalities of nationally-
mandated water pollution control, unless such a reduction
is coupled with an operation and maintenance grant and a
new grant formula for per capita cost equalizing among
communities.

6.  The allotment formula should continue to be based pri-
marily on needs with an incentive structure to induce use
of state capital grant monies for communities for which
immediate federal aid is not available (but which have
complied with cost-effectiveness guidelines)  and to foster
operation and maintenance programs that are oriented
toward improving plant performance.  Illinois has a program
of the first type; New York has one of the second.

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                         SECTION 1

                        INTRODUCTION

DESCRIPTION OF PROBLEM

A continuing theme in legislative and executive discussions
of water quality improvement has been the appropriate means
to finance pollution abatement.  In debates preceding adop-
tion by the U.S. Congress of the Water Pollution Control Act
Amendments of 1972, methods of financing the enormous expen-
ditures required for the municipal waste discharge reductions
mandated by the Amendments were a major concern.*  The
Amendments as finally adopted and passed over the President's
veto provide for 75 percent federal grants for facility .con-
struction with no specified state participation required.
(The Senate bill provided for a 70 percent federal grant if
the state participated with a 10 percent grant, and the
House bill provided for a 75 percent federal grant if the
state participated with a 15 percent grant or loan.  No
state participation would have led to further grants of 60
percent under either bill.)  The Amendments further provide
for an Environmental Financing Authority to assure municipal
access to funds to finance its share of project costs and
for an allocation of funds among states according to need
for treatment plant construction.

The 1972 Amendments also contain Section 317 mandating the
continuing investigation of "alternative methods of financ-
ing the cost of preventing, controlling, and abating
pollution..." as directed in the Water Quality Improvement
Act of 1970.  Given the diversity of proposals debated
prior to adoption of the 1972 Amendments, the current range
of state-level financing mechanisms, and experience to date
with the financing of municipal wastewater treatment works,
a number of outstanding issues present themselves for
investigation under Section 317.  These issues relate to
increased efficiency in allocation of resources to water
pollution control, to the rate at which water quality
improvement proceeds, to administrative feasibility and
     *  Library of Congress, "A Legislative History of the
     Water Pollution Control Act Amendments of 1972/"
     Government Printing Office, 1973.

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the distributional and equity impact of alternative
mechanisms.

As one element of the continuing study mandated by Section
317 of the Amendments, this study focuses on alternative
federal programs for financing municipal wastewater treat-
ment works.  Before discussing the organization of this
report and the study approach, it may be helpful to briefly
describe the physical structure and characteristics of
municipal wastewater systems.  The following part of Section
1 discusses the assumptions underlying this study and the
criteria against which alternative financing programs are
analyzed.

WASTEWATER SYSTEM DEFINITION

From a practical point of view once a community is supplied
with at least 5 gallons per capita per day, it becomes
absolutely essential to provide for the removal of the
spent water through individual or community sewer systems.
Although 30 percent of the present U.S. population lacks a
community sewerage system — usually in such cases dispos-
ing of the wastewater by individual systems consisting of
subsurface irrigation — the remainder of the population,
however, will discharge their wastes into community sewerage
systems constructed over many decades and sometimes centuries,

Wastewater systems* can be described as consisting of collec-
tion, treatment and disposal works, although frequently
systems are without treatment works.  Collection works trans-
port both wastewater from households (domestic sewage) and
wastewater from manufacturers (industrial wastes) thus
municipal sewage generally includes both domestic and indus-
trial wastes.  If the collection works transport storm water
runoff as well as municipal sewage, the transporting conduits
are called combined sewers.  If storm water and municipal
sewage are collected and transported separately, such systems
are referred to as separate.  Combined sewers are usually
found in old cities such as Boston, Massachusetts.  In many
areas systems are a mixture of combined sewers in older dis-
tricts and separate systems in newer areas.  The collection
     *  This system definition draws from Fair, Gordon
     Maskew and John Charles Geyer, Water Supply and Waste-
     Water Disposal, John Wiley & Sons, Inc., New York, 1954.

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works usually consist of a tree  (bush) type network of
sewers often of rectangular or radial pattern  (see Figure
1).  The networks frequently have an implicit hierarchy;
wastes are discharged into lateral sewers, laterals to sub-
mains, sub-mains to main (trunk) sewers  (or to interceptors),
interceptors to outfalls or to treatment facilities.  The
sewer systems are usually free flow and drain downhill
except where pumping stations and force mains  (sewers flow-
ing under pressure) are present for topographical or
economic reasons.

The term interceptor is also used in the case when effluent
from one or more treatment plants is transported for addi-
tional treatment or ultimate disposal.*  In combined
systems, interceptors (destined for a treatment plant)
generally are designed to carry the maximum dry weather
flow or some multiple of average dry weather flow.  The
additional storm runoff is allowed to overflow into the
receiving water body that the interceptor is designed to
protect.  Some combined system interceptors and associated
storm water works have been designed to partially capture
the flushing portion of storm water runoff and the pollu-
tant load it carries either for separate treatment or treat-
ment with the municipal sewage.

Infiltration and exfiltration can be major problems in
wastewater systems; both are functions of the height of the
groundwater table, the soil type, the tightness of sewer
joints and the level of maintenance of the sewer system.
Infiltration — the entry of groundwater, either directly
from the saturated ground or from percolation following
rainfall — is a problem because it reduces the capacity
of the sewer to transport wastewater and increases the flow
which must be handled by the treatment works.  Exfiltration,
the loss of wastewater from sewers, is undesirable since it
may pollute local groundwaters.

Municipal treatment works are frequently classified as pri-
mary, secondary or tertiary treatment plants depending on
their level of pollutant removal.  The 1972 Amendments have
introduced a new set of terms — best-practicable and best-
available.   Operationally,  on the basis of EPA "guidelines,"
     *  In reports by different consulting firms or engineer-
     ing texts, the usage of the different terms, main sewer,
     trunk sewer, interceptor, etc., is not without incon-
     sistencies.
                             8

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                   District boundary
                    or divide .^
                     Pumping station
                                Tidal estuary

              (a) Rectangular  pattern
                                                      Treatment
                                                        Works
                                      Outfall
                       Irrigation
                       fields
            Treatment
              works
River
                          Treatment
                           works
              (b)   Radial  pattern
Figure 1    Typical  wastewater systems*

      after  Fair, G.M., Geyer, J.C.,and  D.A. Okun,
      Water and Wostewater Engineering ,  Vol. 1,
      Water  Supply  and Wastewater Removal,
      John  Wiley ft Sons, Inc., New York, 1966-

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these are equivalent to "super"  secondary and tertiary
type treatments.

Primary treatment usually consists of one or more treatment
units based on physical processes, but often connotes any
set of processes preliminary to secondary treatment.   Fre-
quent process types are:  screening for the removal of bulky
floating or suspended matter and sedimentation for the
removal of some of the heavier suspended matter.  Adequately
maintained and operated primary treatment plants remove some
30-35 percent of the organic pollutant and approximately half
of the suspended solids in municipal sewage.

Secondary treatment frequently consists of a series of
treatment units:  one biological process and one or more
complementary physical  (sedimentation) and/or chemical
(chemical precipitation) processes.  The most common of
these biological processes are activated sludge processes,
trickling filters and stabilization ponds.  The general
principle is the use of biological growth to convert the
suspended and dissolved material  into settleable solids --
the  secondary sludge.  Secondary  treatment works frequently
have chlorination units for the destruction of  pathogenic
bacteria and other  organisms.  Adequately operated and
maintained secondary treatment works can be expected to
remove  80-90+ percent of the organic pollutant  and 80+ per-
cent of  the suspended solids.

Tertiary treatment  works usually  consist of additional
 (after  secondary biological) chemical and/or physical treat-
ment processes.  These  processes  are normally aimed  at
Nitrogen and/or Phosphorus  removal,  e.g., Phosphorus  preci-
pitation or Nitrogen  stripping.   However, additional  removals
of  organic and/or  suspended matter can  also  be  the design
aim.  The  latter design aim is  frequently achieved by the
addition of  a  filtration process  after  biological  secondary
creating a "super"  secondary treatment  plant.   Further  process
additions  to  such  a treatment  plant lead to a tertiary  type
plant.   Removal  percentages in excess  of 99  percent  can be
achieved,  but  at high cost.

In  some cases  the  chain of primary and biological secondary
is  replaced  by a series of physical/chemical processes.

Irrespective of the processes  used, there are both liquid
effluent and either solid (dewatered sludge)  or liquid  ^
 sludge suspension requiring ultimate disposal.   The usuax
                             10

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case is for liquid effluent disposal to a water source and
sludge transported either to land disposal or ocean dis-
posal.  In some cases there is land disposal of both liquid
effluent and sludge.

While the focus of this study is on the financing of treat-
ment works at the end of the wastewater system, there are
strong efficiency arguments for considering financing pro-
grams that include a larger part of the wastewater system.*
This point is briefly discussed in Section 3 of this report.

ASSUMPTIONS OF THE STUDY

Existing wastewater systems represent a significant amount
of capital in place and current projections of ne.cessary
capital needs to meet the requirements of the Amendments
are staggering."*"  There is an obvious need to make better
use of existing capital and to operate new capital invest-
ments properly.  One assumption in this study is that
incentive for better use of the wastewater systems is an
important, if not primary, part in design of financing
alternatives.  A very cost-effective expenditure on waste-
water systems is better maintenance and operation.

Another important assumption in this study is that the
spirit of the 1972 Amendments will be met; namely, that all
municipal sources will be constrained by federal mandate to
achieve at least best-practicable treatment.  This markedly
limits the municipal options examined in our analysis.  The
only relevant questions are:  how big a plant to build and
whether to initially build and operate a secondary, best-
practicable, or best-available treatment facility.
     *  The same effectiveness argument can made regarding
     maintenance and operation of the collection system.

     +  "Costs of Construction of Publicly-Owned Wastewater
     Treatment Works, 1973 'Needs' Survey," Report to the
     Congress, U.S. Environmental Protection Agency,
     Washington, D.C. , 1973.
                            11

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 The  literature* on federal  cost-sharing programs in water
 resources investment emphasizes  that  local cost-sharing
 proportions should be equal to the ratio of local to social
 benefits received at the margin.  The authors maintain that
 this rule does not readily  apply to the problem of financing
 treatment facilities under  the 1972 Amendments, since under
 the Amendments there is little or no  choice allowed the
 community with respect to controlling pollution or not.

 The Amendments set the restoration and maintenance of the
 chemical, physical and biological integrity of the nation's
 water as a national goal and set a policy of federal finan-
 cial assistance in the construction of publicly owned waste
 treatment works.

 There are subtle political  and economic distinctions between
 the water pollution control program as defined by the Amend-
ments and other water resources  programs.   The arguments
 for local cost-sharing in proportion to benefits for other
programs are in general valid.+  Much of the literature
     *  See, for example, Loughlin, j. c., "Cost-Sharing
     for Federal Water Resource Programs with Emphasis on
     Flood Protection," Water Resources Research,  VI, No. 2;
     and Marshall, H, E.7 "Economic Efficiency Implications
     of Federal-Local Cost Sharing in Water Resource Develop-
     ment," Water Resources Research, VI, No. 3.

     The recent National Water Commissions report criticizes
     federal subsidies in general, and EPA's present financ-
     ing program in particular, as leading to inefficiencies.
     See Water Policies for the Future, final report of the
     National Water Commission to the President and to the
     Congress of the United States, Washington, D.C.,
     U.S.  Government Printing Office, 1973.

     +  However, studies making this argument are  often
     insensitive to the question of incidence of the local
     share of costs on lower income groups.
                            12

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 regarding cost-sharing is based on examples of flood control,
 irrigation, recreation and navigation.  Three characteris-
 tics are pertinent to the cost-sharing argument:

 1.  the presence of local benefits;

 2.  acceptable state-of-the-art techniques for quantitative
    benefit estimation; and

 3.  the existence of local or state choice regarding
    project adoption.

 The first characteristic is usually present to at least
 some extent.  However, investment in water quality control
 is perhaps the strongest example in the water sector of
 externalities — and frequently much if not almost all of
 the benefits accruing to the downstream users.  The present
 mandated program dictates a large percentage* of local cost
 burden independent of the implicit benefit share.  The
 latter two characteristics are not present for water pollu-
 tion control programs.

 The Amendments provide for partial financing of facilities
 but mandates local participation.  The approach is not one
 of providing only an incentive, but rather legislating a
 mechanism to enforce mandated behavior while providing a
 sweetener of partial financing.

 The legislation is quite unique in this sense.  It is
 markedly different from other water resources, environmen-
 tal, health, education, and welfare programs of fiscal
 federalism.   The universal characteristic found in other
 categorical  programs is partial federal grants as an incen-
 tive for local or state governments to participate and thus
provide a specific public good.  In all cases participation
 is not mandatory.

 The study does not argue that federal goals with respect to
equity/distributional issues are to be attained solely via
     *  Recall that present federal cost-sharing program
     supports 75 percent of capital costs and no OM&E costs.
     As the analysis in Section 4 indicates, this implies
     that the community share of total treatment costs is
     at least 50 percent and frequently as much as 75 percent.
                            13

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 the environmental quality program but rather that more  heed
 must be paid to these  issues  in evaluating environmental
 quality policy;  this study attempts  to do so.

 CRITERIA

 Federal financing programs are  evaluated  against four
 criteria:   effectiveness  as measured by number of sources
 brought into compliance and/or  mass  of pollutant removed?
 efficiency  as measured by the resource costs of price
 distorting  effects of  grants; equity as measured by  the
 equalizing  effects of  grants  on per  capita cost and  the cost
 per^dollar  of personal income across communities;  and fea-
 sibility as measured by administrative requirements  as  well
 as  political and  legal precedents.

 These criteria  are utilized in  qualitative and quantitative
 analyses of existing programs and  of a range of suggested
 program modifications.  As noted earlier,  equity assumes
 major importance  because  of the study's findings with
 respect to  the  large differences in  cost  burdens placed on
 unlike  communities by  uniform,  national-interest motivated
 treatment requirements.

 FINANCING ALTERNATIVES

 Financing alternatives are  described according to charac-
 teristics,  each of them variable over a range  in order  to
 achieve  the  desirable  federal program.  These  characteris-
 tics are:   (1) allotment  formula (for distribution of funds
 to  states);  (2)  grant  formula (for distribution  of funds
 to  communities);  (3) extent of  wastewater  system eligible
 for assistance;  (4) size of construction loan;  (5) size of
operation and maintenance grant; (6)   planning  standards;
and  (7)  plant performance standards.

REPORT ORGANIZATION

Section  2 of this  report reviews the  current federal  and
state programs for aiding municipalities to  finance con-
struction of wastewater treatment plants.   Section 3
describes the four criteria for  financing  program evalua-
tion and enumerates some deficiencies  of current programs
seen in  light of these criteria.  Section  3 then discusses
important features of alternative financing programs  and
                            14

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identifies those features that could be changed to improve
program performance according to the criteria.  Section 4
continues this analysis with quantitative estimates of the
impacts of alternative financing programs and will summarize
conclusions pinpointing current program deficiencies and
recommending action for improvement.
                             15

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                         SECTION 2

                   THE PRESENT SITUATION

BACKGROUND

In debates preceding adoption by the U.S. Congress of the
Water Pollution Control Act Amendments of 1972, a major set
of issues revolved about methods of financing the enormous
expenditures required for the municipal waste discharge
reductions mandated by the Amendments.*

Section 317 of the Amendments recognizes the need for con-
tinued analysis of the means of financing and states that
the Environmental Protection Agency

     shall continue to investigate and study the
     possibility of alternative methods of
     financing the cost of preventing, controlling
     and abating pollution as directed in the Water
     Quality Improvement Act of 1970.

This study is one of a series of complementary studies
undertaken under the impetus of Section 317.

Given the diversity of proposals debated prior to adoption
of the 1972 Amendments, the range of state-level financing
mechanisms, and experience to date with the financing of
municipal wastewater treatment works, a number of outstand-
ing issues present themselves for investigation under
Section 317.  These issues relate to increased efficiency
in allocation of resources to water pollution control, to
the rate at which water quality improvement proceeds, and
to the administrative feasibility and distributional equity
impacts of alternative mechanisms.  The focus of this study
is on the examination of these issues as they relate to the
federal financing of municipal wastewater treatment plants
and associated ancillary works only.  Other studies cur-
rently underway for the Environmental Protection Agency
(EPA)  are examining financing alternatives for other parts
of the waste generation/collection/transport/treatment
system.

This section of the report describes the present situation
including the current federal grant program, a summary


     *  Library of Congress, "A Legislative History of the
     Water Pollution Control Act Amendments of 1972,"
     Washington, D.C., Government Printing Office, 1973.
                            16

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discussion of the state programs, and a brief discussion of
local financing programs.

THE CURRENT FEDERAL GRANT PROGRAM

The most significant features of the current construction
grant system are:  allotments, priority lists, facility
planning, reimbursement, application and award, allowable
project costs, and the grant percentage.  Each of these
features is discussed briefly here? for further details,
see Appendix B,*  We should point out that the system is
relatively new; regulations, guidelines, and details are
continually being updated.

Allotments

The 1972 Amendments provided for authorizations of $5, $6,
and $7 billion for fiscal years ending June 30, 1973, 1974,
and 1975, respectively.  These authorizations  in theory
provide the basis for an allotment of grants  to the states
according to the ratio that the most recent congressionally
approved estimate of the cost of constructing  all needed
publicly owned wastewater treatment works in  a state bears
to the most recent congressionally approved estimate of the
cost of construction of all publicly owned wastewater treat-
ment works in all the states.4'   In practice outlay estimates
of total allotment are based not on authorizations^but on  a
"normal" rate of grant award based upon previous  (i.e.,
pre-1972 Amendments) experience modified by new provisions
of the 1972 Amendments.  Thus, for fiscal years ending
June 30, 1973, and June  30, 1974, total allotments of
$2 billion and $3 billion, respectively, were used.

Under the 1972 Amendments no appropriation  is required  to
incur contractual obligations, i.e., to award grants.  Once
a grant application  is approved  by the EPA,  that  approval
      *   Basic  sources  were:   Michael  Quigley  and Michael
      Cook of the  construction grants  program;  a May  16,
      1973 memo of Robert Pri,  "Grants for the Construction
      of  Wastewater Treatment Works;"  a draft  of proposed
      regulations  for grants  (40  CPR 35.900 et sgg.)  Decem-
      ber 4, 1973? and  other  regulations,  guidelines  and
      planning  documents.
      *   See P.L.  92-500, Section 205, and Table III  of
      House Public Works Committee Print No. 92-50; and P.L.
      93-243, and  Tables I,  II, and III of House Public
      Works Committee Print No. 93-28; for the actual ratios
      to  be used.
                             17

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becomes an obligation of the federal government to pay its
share of the project costs;  specific appropriations must
then be sought to liquidate  the contractual obligations so
incurred by the award of a grant.   Knowledge of the level
and time pattern of obligations allows accurate determina-
tion of the pattern of outlays that will be necessary.

State allotments are available for obligation for a period
of one year following the close of the fiscal year for
which the sums were authorized.  Funds remaining unobligated
at that time are reallocated to the other states on the
basis of the most recent allotment ratio.  Funds obligated
but remaining after final payment or project termination are
credited to the state as an additional allotment sum.

Project Priority Lists

States submit to EPA regional administrators "project lists"
that provide the basis for the priority ranking of the
projects to be considered for grant approval.  Preparation
of this list requires five steps:   (1) annual state strategy
submission assessing water pollution problems and control
strategies; (2) state segment priority list preparation
ranking all segments in a state taking into account severity
of pollution problems, population affected, need for preser-
vation of high-quality waters, and other national priorities;
(3) municipal discharge inventory list preparation according
to 303(e) guidelines; (4) project selection criteria state-
ment reflecting segment criteria and excluding criteria
based on financial need, municipality's readiness to begin
construction, or ability to meet 1983-1985 goals; and  (5)
project list preparation applying the criteria of the fourth
step to the municipal discharge inventory list of the third,
but including only projects that can be funded from current
allotment funds.

Regional administrators in reviewing project lists have been
advised in the "Water Strategy Paper"* to modify state
lists according to the following guidelines stated in order
of importance:
     *  U.S. Environmental Protection Agency, "Water
     Strategy Paper, Second Edition, A Statement of Policy
     for Implementing the Requirements of 1972 Federal Water
     Pollution Control Act Amendments," Draft, December  7,
     1973.
                            18

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       a.   Projects which are  required  to meet water
       quality  standards and which must comply with
       the  enforceable provisions of the Law—i.e.,
       treatment works that provide secondary treat-
       ment or  any higher level of treatment dictated
       by water quality standards.  Included in this
       category are ancillary  improvements which must
       be done  in conjunction  with an award, such as
       a cost-effective solution to certified exces-
       sive infiltration into  sewers.

       b.   Projects which are  not required to meet
       water quality standards but which must comply
       with the enforceable provisions  of the Law--
       i.e., treatment works that provide secondary
       treatment.  This would  include ancillary improve-
       ments as described in Step a. above.

       c.   Projects that are desirable  in terms of
       water quality improvement, but against which
       the  enforceable provisions of the Law for
       secondary treatment can not be applied—e.g.,
       storm and combined sewers.  These projects
       will be  subject only to the treatment require-
       ments necessary to meet water quality standards.

       d.   Projects which are not dischargers—e.g.,
       collection sewers or recycled water supplies.
       Collection sewers may be given higher priority
      where there is a special problem of groundwater
       contamination, or where they are an integral
      part of a waste treatment system (which includes
       a treatment plant)  for a community which pre-
      viously was without such a system.   This ranking
      of importance does not mean that all projects in
      class a.  must be funded before initiating projects
      in class b.,  and so forth.*

Public hearings must be held on project lists and project
list modifications.4"  The lists are submitted to regional
      *  "Water Strategy Paper," pp. 19-20.
      +  This requirement is waived for fiscal year 1974
      funding if time is insufficient, and may be waived
      for modified lists in the future.
                            19

-------
administrators within 60 days of any funds allotment to the
states; the regional administrator has 30 days to act.  Not
less than 5 percent of each allotment for fiscal year 1975
and later years must be reserved for grant increases.

EPA requirements explicitly give responsibility to the
states for determining the amount and timing of federal
assistance to each municipality.

Facility Planning

The current water quality legislation provides for a three-
step funding of wastewater treatment plants.  The first
step is for the municipality/state,  to submit facility plans
and related studies  to  the EPA;  in  the second step,  con-
             .
Step  1,  2  and  3,  respectively.  Other  arrangements  are
possible but additional  requirements must  be met.   For  these
specifics  see  Appendix B.

Reimbursement

If Step  1  planning  is initiated without a  federal grant
prior to July  1,  1974, and is  completed to the standards  set
forth in published  regulations, then reimbursement  is
allowed  in conjunction with the award  of a Step 2,  Step 3,
or the combination  Step  2/3 grant.

Step  2 costs for  preparation of  final  construction  drawings
and specifications  initiated prior  to  July 1,  1974  may  also
be reimbursed as  part of a subsequent  grant under the
priority system.*  No Step 3 grant  can be  awarded  if initia-
tion of  project construction has  occurred.

Grant Application and Approval

Applications for grants  and grant amendments are first sub-
mitted to the state agency to  be certified as to priority
and to be forwarded to  the EPA regional office.  Grant


      *  Step 1 and Step 2 reimbursement is permitted under
      draft regulations  although there is a possibility this
      will change before publication of final regulations.
                             20

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approval demands a multitude of requirements be met.
Generally, these requirements include submitting plans that
meet certain grant and physical plant criteria; that con-
sider priority and allotment conditions; that have obtained
and complied with necessary permits, regulations, and laws;
and that do not violate certain cost specifications.  The
complete and detailed list of requirements is not presented
here because of its length, but is detailed in Appendix B.

Grant Award

Approval of a grant application constitutes a contractual
obligation of the federal government to pay its share of
allowable project costs.  Grants are made directly to the
municipality.

Grants will normally be for Step 1, Step 2, or Step 3 proj-
ects, but where compelling water quality enforcement
considerations, serious public health problems, or minimiza-
tion of administrative requirements for small projects
warrant, a Step 2/3 grant may be awarded.  Detailed
construction drawings and specifications must be approved
by EPA before initiation of construction.

Any grant must be for an "operable" portion of a wastewater
treatment works; the treatment works do not (under draft
regulations)  have to be "complete."  Consequently, although
no grant for a treatment works may be made from funds allo-
cated . for any fiscal year beginning after June 30, 1974
(unless provision is made for application of best-practicable
treatment over the life of the treatment works), a grant
may be made for an operable portion of a treatment works
where that portion does not provide best-practicable treat-
ment if the complete works will provide best-practicable
treatment and a schedule for completion of the complete
works is submitted to EPA.

In addition to grant conditions already enumerated and
given in Appendix B, the following additional conditions
are imposed on grant awards:  conditions prohibiting non-
restrictive specifications but including bonding and
insurance, equal employment opportunity, and EPA access
conditions, provision for an operation and maintenance
plan including a manual, an emergency response program,
properly trained personnel, adequate budget, operational
reports, and laboratory testing; and the institution of an
affirmative program for the utilization of small and

                            21

-------
 minority businesses in the case of grants over $10 million.
 Additional conditions are imposed on contracts for personal-
 and professional services, and for engineering, planning,
 architectural and related services, including prohibition
 of the cost-plus-percentage-of-cost or percentage-of-
 construction-cost types of fee contracts, and on construction
 contracts.

 Project Costs

 Those project costs that are allowed in the current federal
 grant program include salaries and consultant services;
 materials and laboratory supplies; preparation of reports
 and drawings; planning, compliance,  and evaluation costs;
 and costs related to physical relocation, construction, and
 landscaping.   Costs that are not allowed are for planning
 and costs not directly related to the project or not
 approved; early project completion bonuses;  personal injury
 compensation; fines, penalties,  or interest; and local
 operating expenses  and site acquisition.   Complete lists
 for both allowed and unallowed costs are presented in
 Appendix B.

 Grant Percentage

 Discussion  is ongoing  within  EPA regarding the possibility
 of less than  75  percent grants.   In  the May  16,  1973 memo
 of Robert Fri a  provision  is  made  for  supplemental funding
 whereby states,  after  showing financial ability and intent
 and after waiving all  reimbursement  claims,  can make up
 the difference between the  actual  EPA  grant  (when  it became
 necessary to  provide less  than  75  percent grants)  and the
 eligible  (75  percent)  EPA  rate.  Each  municipality's  share
 would  not be  allowed to  exceed  25  percent.

 THE STATE PROGRAMS:  A SUMMARY

 In  general terms, well-developed programs  exist in  the
 large, urbanized  states  (e.g., Illinois, New York)  while
 many of the less-developed states have  no  programs  (for
 example, Arkansas and North Dakota).  The  majority  of state
 programs fall between these two extremes.  Table 1 pre-
 sents the elements of each of the state's programs.  There
 are three specific types of programs:   construction grant
programs, construction loan programs, and programs offering
operation and maintenance subsidies.
                            22

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Table 1.  STATE PROGRAMS FOR FINANCING
   OF MUNICIPAL WASTE TREATMENT WORKS
•mi
kl«b»»*
klooko

trtoMot
CollforaU
CDlo»oo
eoMoetloM

rioruo
OOKO.U



	 — — 	 1
CDMTWCTION cmurr
DfTAIU
Ho
to 25* if •llalbla but no
'•daral q rant.
5* Matching funds for ninl-
clpalltlaa racvlvlnv • 151
If* «|r«f>fci nothing tor
•uHlelpalltiaa rwaUina
no IPA grant.
Ho
12 1/1, MtcMm* fMnd*
lor municipalities rtcalv-
Lnq 73% EPA qranti nothlnf
It no IPA qcwtt.
« f«» •mnlclpalUU* r»-
C*lvl*9 KPA 4C*ntfei 23%
for •wnlcipalitU* which
•r« cllqlbl* f'», but do
not r*c*lv«. KPA  eoncld«r*d.
1M (or •witcipaLitUi
r«««ivtnq IPA «r«it>t up
to 100% Cor •uniclptU-
tloo allqlbl* Cor, but
not roe*l»lnt, K»A qrant.
H% for «UAlelp«Utlo»
reeolvlwt IPA 71 tad • •pkuoo' (mdln* teMo*
for ollwottoa of ouu fwHi > otaold bo
oualkod.
lAui profroa for pro- oad ohort t*no-f laoneiof
o^ot*. •

luto »ro-fl«i«iii tuo IM troota u o»u«l-
polltloo.

-
                   23

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Table 1.  (continued)
•TUT!
IndUM
IOM

******
•Mtonky
LHlflUM
M»tM
mn\u*
NBMAOtW
a»tt»
aUcUfM .

UOOiMip-i
PUM-i
COH8TWCTION GHAUT
DETAILS
10% far *uniclp*lltloa
receiving BPA qrvnti*
nothing for Mnlcipjlltl**
not raeolving CPA granta.
HO
At pr«*ont no pro?!-**, bat

Mo
Ha
No itita program but pot-
alblllty of St grant
from Appalachian national
tto
(M« 'loana'l
IH for m>nlel|>4Utl*l
rvocivlnff RPA qmnt
(Jlthnuqh up to 29% pr>-
vLdvd for in l*wt .
Nothing for MunicliMill-
tlo« which do not r«caiv«
up to *7 \/l\ to nninlrl(>*lL-
tln rfA n|I<|lt>ln htit nr>
Tumi! •nd protect can«ldftr«d
uri<*nti nothing If not KPA
• Uiibl*.
151 qr«nt to BuiilelpAUtlM
C«c*l«ln9 EPA qranti up to
t«« if CFA «Uqibl« but M
il to'-unlcfp-TUn1. r«0*i«-
Inq IP* f»ntf nothing t»
tho*« r«o«iviMf no It*
«r«nt.
1** (up fco 1»» if •K*rd-
•hip «••••) to •vnietpcii-
tl*« r*«*lvinf IPA irant)
in 9*n«ral itothlnf if net
IPft vlifibU. but e«n f«t
»« If «
reu» ...1UKU
lot Binoc iapartaftc*).





•c*-UI«n>t lou%« «»«IUbU far »U~.tM.
Mo rratrvi »«» 11* »lllle« Cor eo..tr^tlo"
•t •••«• «~1 trMtHUt pUktl In «r..t «k.n
M^U* t**k» •" O1I1M-





          24

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Table 1.   (continued)
tTATI
Montana

Ihmda



•« Hailoa



Camilla*






eamUM
conmuerim cum
OKTMLS
No
racaLvinq EPA qcanti noth-
ing otharwlaa.


IneraiBonta ovar Ufa of
bond laiua - 9lv«» poMr
ovar O«H.
EPA allqtbla but no limim
and ira hl«h anough on
priority lint.
»tth KPA rrrnnti norhtnq
if no EPA dC.nt. Thare
!• Another atrttc prnqroi
* •Ithou'lh MldnNt u»od
for trMtMnt warki •
olvlnq • trontwinfc grant
or 112.000 par projact.


arantai nothing for projacta
irfllch ara not tp» allalDla.
11 l/J% (or •unlelpalttlaa
•1th EPA qnntt !!» (or
•untclpaluiaa «hlc» an .
m tUclbla but racalia
no arant.



IPA fravti BaaUw of )»«
atalo tra«t tm* *kar«akla*
aoaamltla*. '

araati aetklao •Itkoot IPA
t»M.
-
LOAM
•OCTA2LJ











•ot loana «v.U-
abU from Una
•f «.«. - «Mr-
allr ~ olff.f-
a«t but ot aa-
•lataM* vh.r«
cndlt ratlaa
la loi.
araatr loot If
M m trant
a«t aatlafy
Wito IPA ataa-
aaraa.

for •oa-«**aft
eo«t«. MaviMB
lam la M» at
utal



04H PnOCMH
DCTAIU



Ho
(but M* OM
affacti of
arant)

Ito
but proorM
alonq Hm
York 04M pro-
trmm llnaa
balm «onal-
darad to ra-


OM CMtl paid by
ItaM
M

Ho
k»
•o
'miaiix' «aal
praa»«a»lUl
alato parlna ft
a r~» •( Initial
MMttattlo*
eoata oklcn >»ra
«M acaaiUlaaal

••
•on
MfllTAHCl
BTfUU


















HTU





laaaa anllakl* Cor plaMlM and o>ai«a.



•UU flanail.








        25

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Table 1.   (continued)
fTATl


TmMMM
ft***
Jtah
V«r*mt
Tlrvlnla

MMhi*«to*i
w*Jt Virginia
VI MOB • In

CONSTRUCTION GftAHT
DETAILS

(tl though 2*1 theoretically
poiiltimi nothing without
Ho
(•M *lo«n**>
HO

15t with EPA •rintct JS» trlth'
out EPA gtantai If «b*t«§
•ilitlnq pollution - not for
gfavth And d«w«lo(Mant •!•••-
101 (or minleipaltfeUa vhlch
without EPA qf*rtt.
H» with tf\ gf«fttt Mthtfi4
without BfA qrirtt.
»«o
but 13* on advanced tr«*t»nnt
cMti. I» if «U«lbU b«C
no ETA fTMt.
M0
COMSTRUCTIO* "C*° 	
LOAK (UN rnOGRAM USISTANCa
DETAIL! DrtAlLS DETAILS
Ho

«t 'grjnt' (to Ha
tM pflid tMCkt if
qtt EPA qranti
nothlnq without
IPA grant
J5% '^r«Bt" (to 9e
b« p«L4 fr*cK»
with EPA qrantf
100% withOMt
EPA 9»nt and
conildvrln^
finirclml n^d.

NO
No

•0 NO
MO
•Ut MHtiMt «tJt«
P*rtleip«tiM U
«DWMnhlp urf
•OC^TAtlflH


•oru





•Mt* pr«-fin*nc« pl«nnl»9t
10Mt* *r* c*cov«r*d.


•t*t« «!*•• 1001 IcMd* on
prv-con«tmctlon •ctivlti***



          26

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The construction grant programs are the most developed and
interesting means for state financing of municipal waste-
water treatment works.  The range of programs which exists
is presented in Table 2 (which is directly derived from
Table 1).   The numbers in each column indicate the number
of state programs falling into each category.

The table illustrates that the most common form of state
program is a construction grant program under which match-
ing grants are awarded to municipalities receiving the
75 percent EPA grant under Public Law 92-500.  In general,
the grant is simply a "tack-on" to the EPA grant — the
same priority system and the same list of eligible items
pertain.   The awards under these programs vary from 5 to
25 percent.  The situation concerning municipalities
which are eligible for EPA grants, but which do not receive
such grants  (due to a combination of their position on the
state priority system and the shortfall in federal alloca-
tions) , varies widely.  The most common state action is
simply to exclude these municipalities from the state grant
program (for example, Indiana).  There are a number of
states, however, in which the state will give a grant to
municipalities in this category.  These allocations range
from 25 percent  (the most common, Colorado, for instance)
up to a maximum of 100 percent  (which can be offered in
Hawaii) .

The most important and interesting deviation from this form
is the Illinois program.  Under this program the Illinois
EPA allocates the federal allotment in accordance with EPA
directives.  The state funds are then used to offer 75
percent construction grants to those municipalities which
are eligible for, but have not received, federal grants.
No matching grants are given.

The second kind of state program is the construction loan
program, which was introduced in a number of southern states
(Louisiana,  for instance) under Public Law 660.  This pro-
gram was officially called a "grant" since the state offered
a 25 percent matching "grant" to enable the municipalities
to get the full federal grant  (of 50 percent).  In fact,
however, the municipalities were required to repay the
"grant" to the state  as they were loans in all respects
(other than  nominal).  In most of the states where this
kind of program was instituted, they continued to function
although sometimes  (Mississippi) at a reduced level; in
other states  (Louisiana) this program has, with the passage
of Public Law 92-500, been abolished.

                            27

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                      Table  2.  STATE CONSTRUCTION GRANT PROGRAMS
                                NUMBER OF STATE PROGRAMS IN VARIOUS CATEGORIES
Level of State Grant
for Municipalities
Receiving an EPA
Grant
None (0%)
Low (5-10%)
High (12.5-25%)
Level of State Grant for
But Not Receiving
None
(0%)
21(l)
7
9<2,3)
Low
(5-15%)
0
0
0
• Municipalities Eligible for,
, 75 Percent EPA Grant
Medium
(15-30%)
1(1)
2
4(2>
High
(Over 30%)
1
1
2(3)
^       Oregon falls in two categories.  There  are  a  fraction of municipalities which
oo  are eligible for, but do not receive, an EPA grant and which, in addition, are not
   considered "hardship" communities, and therefore do not  receive 30% state construc-
   tion grants.

   (2)
        Minnesota falls in two categories.  The standard 15% state grant is raised
   for municipalities, not receiving EPA grants, which are  considered to be health
   hazards in Minnesota.

        Maryland has a program for the issuing  of 87.5% state grants to "urgent"
   cases which receive no federal grant.

-------
The third program is operation and maintenance.  The only
operative operation and maintenance subsidy program is in
New York.  New York State pays one-third of operating
expenses.  This program has attracted the attention of at
least one other state (New Mexico) where it is being con-
sidered as an alternative to the construction grant program.
Operation and maintenance subsidy programs are also being
considered in Washington and Minnesota.

Pennsylvania has a program under which the state annually
pays the municipality 2 percent of the initial non-subsi-
dized construction costs.  While this may well be considered
to be a construction grant, the state agency sees it as a
program for assisting the municipalities in meeting their
operation and maintenance costs.  Pennsylvania does not use
the apparent potential of the program to enforce satisfac-
tory operation and maintenance.  New Hampshire, by contrast,
which pays construction grants (of 20 percent) in principal
and interest installments each year over the life of the
bond issue, recognizes the potential to use this financing
mechanism to affect treatment facility operation.

LOCAL FINANCING PROGRAMS

During the fiscal year 1970-71 the federal government
expended $776.9 million for water quality control activities.
Of this, 89.7 percent was distributed to state and local
governments through federal grant programs.  The $493.2
million that flowed through EPA's grant program for con-
structing waste treatment facilities amounted to 70.7 percent
of federal intergovernmental payments for water quality
control.*

During the same period of time the nation's 48 largest
cities spent $650.3 million on water quality control acti-
vities, 65 percent of which ($422.8 million)  was capital
outlay for new construction or improvement of existing
sewage treatment plants.  These cities raised $248.8
million — 38 percent of their total water quality control
expenditures — from sewerage charges.  The 32 counties
out of the 58 with a population of 500,000 or more which
     *  U.S. Department of Commerce, Bureau of the Census:
     Environmental Quality Control, Finances and Employment
     for Selected Large Governmental Units.  Fiscal Year
     1970-71, p. 3-5.

                            29

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reported expenditures on water quality control spent
$160.8 million — $123.5 million (76.8 percent) on capital
outlay and $36.5 million for current operation.*  The 38
largest SMSA's in the country spent $1.4 billion on water
quality control of which $887 million  (64.8 percent) went
to capital outlay.  Sewerage charges from local governments
within these SMSA's returned $492.5 million or 35.2 percent
of the total expenditures.

Traditional Methods of Financing

Local financing of municipal services has traditionally
relied most heavily on property taxes.  Although property
taxes will continue to be the largest single source of
local revenue, their general decline is prompting munici-
palities to seek other funding arrangements.+  For both
state and local governments the share of revenues derived
from federal sources is increasing (13.8 percent in 1960
to 16.7 percent in 1970); the share from state sources is
growing (from 40.8 to 44.0 percent);  and the share from
local sources is declining (from 45.8 in 1960 to 39.3
percent in 1970).

With the decline in the use of property taxes, a cramped
bond market, high interest rates and increasing costs,
local governments have tried a variety of other revenue
sources including special assessments, intermunicipal
arrangements, revenue bonds, and, increasingly, a wide
array of user or service charges levied for providing
waste treatment service to a variety of customers.

Currently "Popular" Methods of Financing

User Charge Financing — Financing the cost of operation
and debt expenses through charges to those who use the
     *  Many of the counties that reported no expenditures
     contain municipal governments or special districts
     that handle water quality control.

        Local property taxes have been providing a decreas-
     ing proportion of state and local general revenues
     (from 31.3 percent in 1960 to 25.2 percent in 1970.
     Tax Foundation Inc.,  Research Publication (New Series
     No. 28), "The Financial Outlook for State and Local
     Government 1980," 1973, p. 82.

                            30

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service is not new.*  In the 20 years between 1950 and
1970 municipal revenues from property taxes only tripled
compared to a seven-fold increase in special charges
revenue.  In the 1972 Amendments to the Federal Water
Pollution Control Act, the user charge became a required
practice for any municipality seeking a federal grant for
construction of waste treatment plants.  Unfortunately such
user charges represent one of the most regressive forms of
revenue collection utilized by any level of government.+
Charges are also not deductible from federal income taxes,
which places the loan squarely on the local charge payer's
shoulders.*

Special Assessments — Special assessments have an even
longer history than user charges as a means of financing
public improvements on the basis of benefits.  The special
assessment has evolved as a tax used predominantly by muni-
cipalities and levied only on the area that would be
demonstrably benefited by a proposed improvement.  The levy
is apportioned on the basis of benefits and the assessments
can be made liens on the benefited property.  The proceeds
go to pay the cost of local improvements.

Special assessments are generally initiated by the munici-
pal government or by petition of property owners.  Property
is assessed through an apportionment system based on
benefits, usually according to frontage, zone, or area.
Property is less frequently assessed on the basis of prop-
erty valuation or the direct benefit a piece of property
will receive.  Municipalities more often use one of several
plans to finance special assessments:  special assessment
bonds, special certificates of liens to the contractor,
temporary loans from city funds, or advance payments from
assessed property owners.  In most cases assessments are
     *  Tax Foundation Inc., "The Financial Outlook for
     State and Local Government 1980," p. 6.
     +  Public Interest Economics Center, "Who Bears the
     Cost of Pollution Control?  The Impact on the Distri-
     bution of Income of Financing Federally Required
     Pollution Control," Report for Council on Environmental
     Quality, Washington, D.C., August 1973, pp. 25-26.
     *  Tax Foundation Inc., "The Financial Outlook for
     State and Local Government 1980," p. 6.
                             31

-------
not allowed to exceed the cost of the service and thus do
not reflect any increased value of property which an improve-
ment might bring.

Revenue Bonds — Use of revenue bonds in conjunction with
user charges puts the sewage treatment service into a
utility classification.  These bonds are usually outside
state-imposed debt limits and therefore are not subject to
interest rate ceilings and do not require voter approval.
There is precedent for treatment systems to become self-
supporting through such financing.

Intermunicipal Arrangements to Provide Financing —  In a
number of situations treatment facilities have provided the
occasion for municipal cooperation.  Communities which con-
tribute their wastes to another community's facility pay a
pro rata share of the capital cost of all facilities
reserved for cost under their contract plus a pro rata
share of all operating costs involved.  In most cases the
sewage service is provided just at cost.  In other arrange-
ments the contributors are charged on the basis of metered
water use.  These charges can resemble "suburban surcharges"
over the cost to city users or they can be on a volume
basis.  Sometimes a large city will contract with a county
which arranges sub-contracts with its cities.  On occasion
a city will provide area-wide services to surrounding
municipalities and counties.

Another approach is a joint venture between two cities that
collaborate to build a single treatment plant withotft
creating a separate agency.  One city then contracts with
the other for service, paying a share based on a mutually
agreed upon factor, such as volume rates, that can be
adjusted to accommodate industrial wastes or changing flows.

Another type of cooperation is the special intermunicipal
district which may be formed by a group of contiguous
governments.  Districts may be formed though state legis-
lation and local ordinance or government action.  Generally
this type of district is financed from funds generated by
each participating municipality through assessments on
property within the district, sewer service charges,
property taxes, sewer connection charges, general tax funds,
and bond issues.

Finally, there are intermunicipal sewerage authorities
that are independent and self-supporting.  Such authorities

                            32

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are frequently almost entirely free of  supervision by.their
parent government(s).  Authorities may  take on general and
revenue bond obligations, set and charge user rates, borrow,
and, in some cases,  even tax.

Choosing a Finance Program

The choice of one method of financing waste treatment works
over another appears to be a function of size of the muni-
cipality making the  decision.  U.S. Census information shows
that cities under 500,000 depend on service charges for a
larger share of their general income than do larger cities.
These same cities also seem to use fewer alternative sources
than the larger cities that impose more non-property taxes.
Cities under 50,000  received 17 percent of their revenues
from non-property taxes; cities of one million or more
obtained 34 percent.  Smaller cities are often prohibited
from levying sales and income taxes by  law, a practice
which makes user charges all the more attractive.  For all
cities, charges are  about equal to costs; but for the 43
largest cities they  only provide 35 percent of costs.  Some
reasons for the lower use by large cities are the complexity
of collection and administration on a large scale and the
impact of service charges on the poor.

A similar relation between size and practice is found in the
use of special assessments.  Again cities of 500,000 or less
have shown an increased use, but larger cities have shown a
marked drop in such  revenue.  Cities of less than 25,000
increased their use of special assessments by 35.3 percent.
Much of .this trend may be due to the rapid spurt of growth
that smaller sized cities in suburban areas are undergoing.

Selection of user charge schedule is also a function of
municipal size.  Small municipalities of 2,500 and under
most often use the uniform flat rate because it is easy to
administer.  The modified flat rate (flat rate varied
according to customer)  and the water use formula are more
often used by towns over 5,000.  Few communities use plumb-
ing fixture or water meter and sewer connections as a
basis for rates.
                            33

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                        SECTION 3

                  SELECTION CRITERIA AND

             FEATURES OF FINANCING ALTERNATIVES

INTRODUCTION

In the second section of this report the current federal
program for aiding municipalities to finance the construc-
tion of wastewater treatment plants was described.   In
addition, examples of some of the state programs were pre-
sented.  In this section four criteria — effectiveness,
efficiency, equity and feasibility — for evaluating the
current system will be described and some of the deficien-
cies these criteria suggest will be identified.  Secondly,
seven important features of possible alternative financing
programs will be presented and discussed in terms of the
criteria.  The features include:

1.  allotment formulas (for distribution of funds to
    states);

2.  grant formulas (for distribution of funds to communi-
    ties) ;

3.  components of the wastewater systems eligible for
    assistance;

4.  construction loans;

5.  operation and maintenance grants;

6.  planning standards to be imposed on communities seeking
    funds; and

7.  the institution and type of plant performance standards
    once a treatment facility is in operation.

Two additional features of any financing scheme are the
size of the grant to a municipality, i.e., percentage of
costs to be subsidized, and the time pattern of the grant.
Discussion of issues associated with grant size will appear
in the context of allotment formulas, grant formulas, opera-
tion and maintenance grants, and construction  loans, while
those associated with timing will appear in the context of
plant performance standards.

                            34

-------
 It is  clear that  there  is  a  difference  in  the  relative  role
 of the above list of  components.

 Some of these items —  planning  standards,  program allot-
 ment formulas,  and grant formulas  — would be  components
 of any financing  scheme while  not  explicitly specifying
 the type of assistance  the federal government  provides  to
 municipalities--the  type  of this  assistance being speci-
 fied by other components,  e.g.,  construction and/or O&M
 grants and  construction loans.   Also it  is  obvious that all
 four criteria are not equally  important  in  assessing each
 of the items.   For example,  effectiveness  and  feasibility
 would  appear to be most important  in discussing  an O&M
 grant  or plant  performance standards while  efficiency and
 equity would be more  important when considering  the amount
 of grants or an allotment  formula.

 The presentation  in this section is limited to a discussion
 of criteria,  deficiencies of current programs  and  features
 of alternative  programs.  The quantitative  analysis appears
 in the next  section of  the report.  The  discussion in this
 section is  not  exhaustive or complete because  some of the
 arguments for or  against a particular feature  of a financ-
 ing program  can be made more easily in quantitative terms.
 These  arguments are presented in the subsequent  section of
 the report.

 CRITERIA

 Effectiveness of  a water pollution control program may  be
 measured  in  terms  of  pollutant mass removed, sources brought
 into compliance,  or length of river, lakeshore or  ocean
 front  brought to  an acceptable water quality level.  Depend-
 ing on which  of these definitions  is used, effectiveness may
 be  a trivial  or important criterion in assessing a  financing
 scheme.   if  the number of sources brought into compliance
 is  the  one used,  then effectiveness is unimportant  in the
 light  of  the  1972  Amendments.  This is because the  1972
Amendments require municipalities to attain certain treat-
ment levels by  1977 and 1983 and because the Congress has
demonstrated  a  determination to appropriate sufficient
monies  to assist  communities to meet these treatment levels.
As discussed  in Section 1,  this study assumes  the  spirit of
the 1972 Amendments will be met and that, with certain  spe-
cific exceptions,  nearly all municipalities will be in
compliance with the law by 1977  (or within a few years  of
                            35

-------
1977) and by 1983, so that alternative financing programs
will not differ as to effectiveness of pollution control.
Exceptions to this generalization are:

1.  simplification of the current system of construction
    grants might hasten the pre-1977 rate of compliance)
    and

2.  fiscal bottlenecks at the federal level that could
    delay substantial compliance with the 1977 objectives
    by one or two years could be lessened by grant-reducing
    schemes  (although any such schemes that were designed
    to alleviate federal bottlenecks would exacerbate
    bottlenecks at the local level).

If, however, effectiveness is to be measured in terms of
pollutant mass removed or the length of river brought to
an acceptable water quality level,  then it is of some
importance in assessing alternatives.  In spite of the  fact
that plants must be built, whatever the method of financing,
different grant programs will either encourage or discourage
the proper operation of a treatment plant once it is con-
structed.

Thus, schemes providing a financial incentive to properly
operate a treatment plant would be  expected to have greater
effectiveness than current schemes  lacking a means of
ensuring attainment of performance  standards.  Therefore,
in this report effectiveness will only be relevant for
evaluating alternatives with respect to attainment of per-
formance standards.

Because there is no adequate measure of the benefits to be
derived from the wastewater treatment requirements legis-
lated by the 1972 Amendments, the criterion of efficiency*
provides no  standard for determining the amount of resources
the  federal government ought to commit to its grant program
or the way in which these resources ought to be allocated.
However, if  concern is limited to treatment cost decisions,
      *   in  this  context  efficiency  is  defined  in  global
      terms.  That  is  to  say,  a  decision  is  efficient if
      resources are allocated  in such a fashion that mar-
      ginal  social  abatement benefits are equal to marginal
      social control costs.
                             36

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then the criterion of efficiency can be useful in identify-
ing those alternatives which will allow a community to meet
the requirements of the Act at least social cost.  Some of
the areas in which inefficiencies may arise are in the
overcapitalization of a treatment facility, the improper
selection of a treatment technology (e.g., conventional
secondary treatment rather than some form of physical/
chemical treatment), the rejection of a regional treatment
scheme in favor of smaller local facilities, or the selec-
tion of a centralized collection and treatment system rather
than individual on-site disposal.

Another criterion used in evaluating alternative financing
schemes is the incidence of cost-bearing — who pays for
water pollution control.  A more equj.table program is de-
fined as one which more nearly equalizes the financial
burden among citizens where financial burden is a function
of cost ultimately borne by a person and that person's
ability to pay.  Because a companion study is assessing
impact of financing alternatives on individuals (spread in
homogeneous communities across the land), this study
focuses on community impact differences:  specifically on
differences in per capita costs from community to community
and in local costs per dollar of family income from commu-
nity to community.*  Fiscal impacts of alternatives on
federal, state and local budgets are estimated with such
considerations in mind.  It must be emphasized, however,
that this study does not address the issue of local govern-
ment financing and its impact on individuals nor even the
aggregate effect of federal fiscal policy on individual
income distribution or incidence of costs.

The notion of feasibility has at least two components in
the context of financing programs — administrative feasi-
bility and political feasibility.  In this report no attempt
will be made to define either of these components for
neither is easily defined except at the most superficial
level.  However, it is important to point out that feasi-
bility is not ignored.  The issues associated with
administrative feasibility will be dealt with by identifying


     *  Dorfman, Nancy S. and Norman H. Jones, Jr., "Inci-
     dence of Alternative Financing Methods for the Municipal
     Treatment Facilities Program," prepared for Environmen-
     tal Protection Agency by Public Interest Economics
     Center, Washington, D.C., June 14, 1974.     ~
                            37

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 those features of a particular financing alternative which
 clearly will require that more resources be put into admini-
 stering the program because of its complexity.   Although
 there is no intention of dismissing the importance of
 political feasibility when considering the feasibility of a
 financing scheme, it is not a major issue in this report.
 This is the case because all the components of  the alterna-
 tive financing programs discussed in the report have their
 precedents in the legislative history of federal water
 policy or current and proposed state programs.

 DEFICIENCIES IN EXISTING PROGRAMS

 If  the current federal financing program is assessed against
 the four criteria of effectiveness,  efficiency,  equity and
 feasibility., likely deficiencies can be pointed to on all
 four measures.   Some of these shortcomings will be discussed
 below with suggestions for remedies.   These and others will
 be  elaborated in the following subsection "Features of
 Alternatives"  and those which are particularly  susceptible
 to  quantitative analysis will also be discussed in Section
 4.

 On  the effectiveness measure,  as it  has been  defined above,
 the current  federal  financing program is sorely  lacking.
 It  contains  no  provisions  to  insure  or encourage  the proper
 operation  of treatment facilities.   The 75 percent construc-
 tion  grant makes  the requirement of  building  a  plant more
 palatable  to communities  than it otherwise might  be,  thus
 encouraging  more  rapid compliance, but the problems of
 operating  the plant  to achieve  the highest levels  of removal
 are  ignored.  Such a shortcoming may  be very  serious since
 in  the  absence  of any  incentive  to operate and maintain  a
 plant  properly  there may be ample  incentive for a  community
 to  reduce  current expenditures  to  the  detriment of  plant
 performance.  Also,  the present  federal  program does  not
 encourage  states to  spend  their  water  pollution control
 funds effectively. .  Currently most states  which have  some
 kind of program to aid communities in meeting the  cost of
 treating their waste merely add  to the  capital grant  offered
by the  federal government.*
     *  There are some exceptions to this approach.  For
     example, New York has an O&M subsidy program and
     Illinois has a policy of using its funds to increase
     the number of proposed plants on the priority list to
     receive grants.

                            38

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Using the efficiency criterion suggests some additional
deficiencies.  Many of the critics of the current program
argue that the 75 percent capital grant and the additional
state grant, if there is a state program, results in a
price distortion which may encourage over-investment in
plant capital.  If this were the case, it could prove to be
a very ironic twist, since, as will be shown in Section 4,
under some circumstances a capital grant of 75 percent may
reduce the present value of total cost to the community by
as little as 20 percent.

Also from the perspective of efficiency it is important to
note that the present grant program excludes from its list
of eligible items individual treatment units such as septic
tanks.  Such a situation may cause certain communities to
buy a collection system and centralized treatment plant
because, in spite of the fact that the plant and its collec-
tors may be more expensive when counted in terms of total
resources used, the price to the community will be lower
because such a system is eligible for a grant.

For all practical purposes equity is ignored under the
current grant formula.  It is ignored because the financing
program pays no attention to either inter-community differ-
ences in facility costs or the heterogeneous nature of
communities in terms of such things as wealth measures.  In
Section 4 it will be shown that the fiscal burden placed
upon communities with different characteristics can vary
substantially.

The administrative feasibility of the program is a moot
point.  Clearly there are some bottlenecks, e.g., meeting
the requirements of the permit system, and the regional
offices of EPA and the state water quality offices feel as
though they are overburdened, but there is no provision of
the 1972 Amendments pertaining to the grant program which
is, on the face of it, administratively infeasible.  It is
more likely that the commitment of funds to administer the
program is inadequate.

Possibilities for improvement of the federal financing pro-
gram include the following:

1.   financing should be designed to provide an incentive to
    improved facility performance;

2.   financing should reduce the resource allocation losses
    thought to be associated with current planning decisions

                            39

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     losses arising from construction of oversized facilities
     or of choice of treatment processes which may be too
     capital-intensive;

 3.   financing should encourage states to spend their pollu-
     tion control monies roost effectively? and

 4,   financing should be designed to reduce currently large
     disparities in the burden of water pollution control
     among communities and individuals.

 FEATURES OF ALTERNATIVES*

 The  presentation of alternatives will be organized around
 the  seven features or components described above.  Although
 each of the features may affect performance as measured
 according to more than one criterion, the discussion of
 effects will be limited to pointing out the impacts on the
 most important criterion (or criteria) associated with that
 feature.

Allotment and Grant Formulas

 The  allotment or state allocation formula is the basis on
which federal authorizations (for whatever financing alter-
native)  are distributed to the various states.   The grant
 formula is the basis on which the size of the transfer
payment to be given to the individual city or sewer district
is determined.*
     *  Appendix C presents the arguments for structuring
     financing programs with different characteristics in
     the broader context of fiscal federalism.  The discus-
     sion in this section is specific to alternatives for
     financing wastewater works but there are analogies for
     the issues discussed in numerous financing programs.
     Some of these are discussed in Appendix C and a broad
     review of other programs influenced the discussion in
     this section.

        In the rest of this discussion, for simplicity in
     exposition, the "city" will be used synonomously with
     the grant recipient, although in reality the institu-
     tion building and operating a municipal treatment plant
     is often a sewer district or authority or some other
     institution created by one or more cities.
                            40

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 The present state allocation formula is based solely on
 needs.   Prior to the 1972 Amendments the pollution control
 allotment was based primarily on population.   However,
 population is often a poor surrogate for needs as shown in
 Table 3.   The present grant formula is  a simple 75 percent
 of the  eligible capital  costs and some  associated planning
 and design costs.   These eligible costs in the present  pro-
 gram are  detailed in Appendix B.

 Grants  may or may not have matching provisions.   Matching
 provisions may be built  into the grant  formula or an incen-
 tive for  matching grants may be  built into the allotment
 formula.   As  discussed in Section 2,  the current program
 requires  25 percent local or state monies on  capital costs
 and 100 percent local or state monies for operation and
 maintenance costs.   The  alternatives  discussed here all
 require local participation but  only  some require state
 participation.                             —	

 The Allotment Formula — The allotment  formula could reason-
 ably be based on  three classes of measures:   needs,  current
 and/or  past efforts,  and revenue  capacity,  where one measure
 of  revenue capacity  is per capita income.

 The ratio  between  the approved cost estimate  of  constructing
 all needed municipal  plants  in a  state  to the cost estimate
 for construction of  all  needed municipal plants  in all  the
 states  is  the  current basis  for  determining needs.   As
 stated  previously, the total population  was traditionally
 used as_the basis  for determining needs.   Difficulties
 arise with  this because  different kinds  of  resources, in
 varying amounts, are  required  depending  on  specific  area
 characteristics.

 There are both efficiency  and  equity  issues associated  with
 these difficulties  (issues also relevant  to a  discussion  of
 the grant  formula with its focus  on the municipality rather
 than the state).  if one assumes  that municipalities select
 the alternative with  lowest  total  resource  costs,  the
 existing need measure may be distorted in the  relative  dis-
 tribution of eligible versus ineligible costs  across states.
 For example, in highly urbanized  states  land costs  (for
biological or physical/chemical)  may be a much higher per-
 centage of total capital costs than in less urban  states,
and these land costs are not covered under the existing
grant program.  Furthermore, the definition of eligible
costs limits examination of alternatives and thus precludes


                            41

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                          TABLE  3.
   State

 Alabama
 Alaska
 Arizona
 Arkansas
 California
 Colorado
 Connecticut
 Delaware
 District of
   Columbia
 Florida
 Georgia
 Hawaii
 Idaho
 Illinois
 Indiana
 Iowa
 Kansas
 Kentucky
 Louisiana
 Maine
 Maryland
 Massachusetts
 Michigan
 Minnesota
 Mississippi
 Missouri
 Montana
 Nebraska
 Nevada
 New Hampshire
 New Jersey
 New Mexico
 New York
North Carolina
North Dakota
Ohio
Ranking by
  Total
 "Needs"(1)

    33
    44
    41
    38
     2
    34
    10
    39

    13
     8
    17
    29
    47
     4
    15
    31
    25
    16
    32
    37
    24
     9
     6
    14
    40
    18
    48
    35
    42
    30
     5
    46
     1
    19
    49
     7
                             Ranking by
                               Needs
                             Categories
31
41
42
25
 1
30
25
38

48
 6
11
24
45
 4
18
26
28
16
34
33
15
12
 8
19
36
10
47
43
37
27
 3
46
 2
13
50
 5
Ranking by
Population

    21
    51
    33
    32
     1
    29
    24
    47

    41
     9
    15
    40
    43
     5
    11
    25
    28
    23
    20
    38
    17
    10
     7
    19
    30
    13
    45
    35
    48
    42
     8
    37
     2
    12
    46
     6
                            42

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                   TABLE 3.   (continued)

                            Ranking by
              Ranking by      Needs
                Total       Categories     Ranking by
  State        "Needs"U)     I+II+IVaU)    Population

Oklahoma          26            22             27
Oregon            28            32             31
Pennsylvania       37              3
Rhode Island      36            40             39
South Carolina    22            17             26
South Dakota      50            49             44
Tennessee         23            23             18
Texas             20            14              4
Utah              43            39             36
Vermont           45            44             49
Virginia          11             9             14
Washington        12            20             22
West Virginia     27            29             34
Wisconsin         21            21             16
Wyoming           51            51             50
(  J   See "Report to the Congress, Costs of Construction
of Publicly-Owned Wastewater Treatment Works, 1973
'Needs' Survey," U.S. Environmental Protection Agency,
revised November, 1973.
/ 2)
     These are the categories this study is explicitly
examining.
                            43

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 selection  of  some  alternatives  that  would  minimize  total
 resource costs.   (Individual treatment systems  are  thus
 excluded from grant  eligibility.)

 The  use of effort  measures  is an  attractive  addition to
 the  allotment formula  as  an incentive  for  state programs  to
 accelerate plant construction.  The  incentive can be struc-
 tured  on current effort measures,  such as  increasing the
 state  allocation in  states  where monies are  available to
 the  city in lieu of, or prior to,  availability  of federal
 monies.  Some states did  construct treatment plants prior
 to receiving  federal monies/  monies  promised by the 1966
 legislation.   For  these states  the equity  argument  is
 strong,.and the inclusion of needs already met  is equally
 forceful.

 The  allotment formula  could contain  a  provision for needs
 already met — for example,  in  proportion  to the construc-
 tion costs  of those cities  which have  achieved  secondary
 or best-practicable treatment in recent years.*  This would
 necessitate defining a base year and estimating capital in
 place  for  that year.

 Finally, a  formula could  be structured such  that the state
 allotment would increase  if the state  funded (from its own
 monies) cities not high enough  on  the  priority  list to
 receive federal funding.  This would encourage the short-
 term control  of additional  point sources for the same level
 of federal  program dollar.   The Illinois water pollution
 control program operates  in  this manner, presently, without
 the incentive.  This could  markedly  affect the short-run
 difference  in number of point sources  controlled and mass
 of pollutant  removed.

An alternative would be to provide an  additional allocation
 if a state provided O&M subsidies, thus reducing the poten-
tial distortions associated with "capital only" grants, and
hence impacting the equity  and effectiveness criteria.   The
     *  If, for example, the allotment formula considered
     only needs and needs met, an alternative might be to
     allocate 80 percent of authorization on the basis of
     needs only and the remaining 20 percent incentive on
     needs met.
                            44

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state of New York has a program of operation and maintenance
grants and there is evidence to indicate that it is effec-
tive in improving plant performance.

There are two important assumptions or beliefs .implicit in
the above discussion.  The first is that any allotment
formula should encourage states to assist in financing
municipal wastewater treatment and the second is that this
participation should be something other- than a matching
capital grants program.  This reflects equity, efficiency,
and effectiveness criteria.  As the discussion in Section 4
will show, rarely does the present federal share represent
even half of total treatment cost and for large numbers of
cases it represents less than one-quarter of total costs.
The requirements of the 1972 Amendments and national
interests, as discussed in Section 2, argue on an equity
basis against reducing the capital subsidy unless an O&M
subsidy is also introduced.  Increasing the capital subsidy
beyond 75 percent, however, increases the "price effect"
such that even use of other characteristics  (such as planning
standards) cannot protect against efficiency losses.  This
argues against incentives for state matching monies on
capital.  Also, as will be discussed below, an O&M subsidy
may provide the leverage necessary to insure plant perfor-
mance .

The Grant Formula — The important criteria  for  judging
grant formulas are equity and effectiveness.   Inequities
can be reduced explicitly with grant formulas.   Thus the
formula should reflect measures of per  capita  cost required
to meet best-practicable treatment and  should  be dependent
on per capita income and fiscal capacity.  The crucial
incentive issue is to  induce proper operation  and mainte-
nance of existing  and  new plants  and is associated with  the
question of operation  and maintenance grants and perfor-
mance standards.   These are discussed later  in this  section.

The  1972 Amendments  do not place  the same  financial  burden
on all communities.  The water pollution control literature
shows that  financing programs have  traditionally focused
only  on the differences of  large  versus small  communities
as reflected  in varying per  capita  costs resulting  from
scale economies.   However,  it  is  also  important  to  consider
differences in  revenue capacity among  cities of  the  same
size  (or different sizes).   Analysis  in the  following  sec-
tion (Section 4)  indicates  that municipalities are  markedly
non-homogenous  in both the  characteristics that  influence:

                             45

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(1) the requirements to meet the mandated treatment levels;
and (2) the financing of these requirements.  Although pre-
vious federal grant formulas in water pollution control have
not explicitly had income and/or fiscal capacity variables
among their provisions, there are several examples of such
formulations in numerous other federal grant programs.  The
particular national objective orientation of the Amendments
as discussed in Section 2 and the significant evidence of
the distributional consequence presented quantitatively in
Section 4 suggest designing grant formulas to approach a
more equitable distribution of local costs.

This suggestion arises since many other federal programs
have made some allowances in either the allotment and/or
grant formulas for differences in income and/or fiscal
capacity as well as for differences in needs or costs.
These programs have been both for public facility construc-
tion and for the provision of services.  There is consider-
able precedent for relatively complex formulas being
utilized to achieve a mixture of objectives.  The complicated
revenue-sharing formulas are obvious examples of such
approaches.*  The grant formula could be constructed to
     *  For a discussion of the general revenue-sharing for
     mulas, see "Questions and Answers Relating to Revenue-
     Sharing," State Government:  The Journal of State
     Affairs, Vol. 46, Winter 1973, No. 1, pp. 30-31.  Addi
     tional examples are the following:

     Title I of the ESEA of 1965 — grants to local school
     districts (through state agency)

                T**        T*1
       A. .  = P.  i or P.  us  whichever is larger
        T T     "1 ^BMV     "1 ^W^^HBV
        1D     D  2      :  2

     where  AI . = magnitude of grant to jth school district
             13   in the ith state

            P.  = the population of "deprived" children in
             3    the jth district (basically from families
                  with incomes below $3,000)

            E.  = average per child expenditure for elemen-
             1    tary and secondary education in ith state

            E   = average per child expenditure in U.S.

                            46

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incorporate both total costs and per capita costs as mea-
sures of needs and potential distributional inequities and
income (or another surrogate) as a measure of fiscal capa-
city.*
     (footnote continued from previous page)

     This formula provides partial correction for cost dif-
     ferences and tends to define requirements for programs
     for deprived children in terms of the standard of
     support for education in state or nation.

     Another example is in the area of Child Welfare Ser-
     vices.   (A similar form is used for grants to Community
     Mental Health Centers.)   The allocations are determined
     by a formula of the form:

                    P (1.0 - 0.5 y /y)
       A. = a^ + a
        i    0   "I Z.jP.jU.O - 0.5) y±/y)


     where  A,.^ = magnitude of grant to ith state

            aQ = small constant to cover administrative
                 expenses

            P.^ = number of children under 21 in the ith
                 state

            P. = number of children under 21 in jth state
                 (all other states)

            y. = average per capita income in ith state

            y  = average per capita income in U.S.

     In addition, the matching ratio for each state (Fi) is
     a function of the per capita income in that state.

        F±  =  1.0-0.5 (y±/y)

     *  If,  for example, as is suggested in this report, the
     grants  become annual transfer payments on both capital
     and O&M expenditures, an attractive grant formula would
     be of the form
                            47

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(footnote continued from previous page)

   G. = f  (total annual costs)  + f2 (per capita costs)
             + f  (fiscal capacity)

where G:  is the annual grant to the ith community and
flf f2, and f3 are functions.  A possible "linear"
form would be the following:

                 c*           5*
   G. = ac. + 3 -~± — c  + y r-i-^ ci '
                a - c        i - c

where  C. = total annual costs for community i
        i
       c. = per capita annual costs for community i

       5 . = per capita income for community i

       c  = average national per capita costs

       T.  = average national per capita income

       c  = the highest expected per capita community
            costs
                  (c. < c  for all i)
                    i —
       /\
       5  = the lowest expected per capita community
            income      *
                  (£  >_ 5  for all i)

       c* = the "more than average" per capita costs
        1   for community i

               =  0 if c. <_  c,

               =  c. - H if ci> c

       £* = the "less than average" per capita income
        1   for community i

               =  0 if 5± >. I,

               =  5 - ?i if g± < I

                       48

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ELIGIBLE ITEMS AND A CONSIDERATION OF
THE TOTAL WASTEWATER SYSTEM

Formally, this study is restricted to considerations of
wastewater treatment plants — nominally this is further
restricted to "sanitary" wastes as opposed to storm drain-
age and combined wastes.  It is true that wastewater
treatment plants traditionally have been designed to accept
and treat wastewater, whatever its quality and quantity, as
it arrives at the plant.  In order to gain some perspective
on possibly useful modifications of this traditional approach
and their relationship to financing alternatives, it is
appropriate to digress briefly from the assigned task and
consider some of the early history of sewerage practices
and some important features of the total wastewater system.

Sewers have been built in the United States since the 17th
Century.  Initially sewers were laid as a result of private
enterprise:  a householder or group of householders would
build whatever type of structure they wished — on the
     (footnote continued from previous page)

            a = a fixed fraction of cost to be granted
                irrespective of community costs and/or
                income — perhaps a = .25,

            3 = a maximum additional fraction of costs to
                be granted dependent on excess of the
                community per capita costs,

                   . 2 _< 3 £ . 3, and

            y = a maximum additional fraction of costs to
                be granted dependent on the extent to which
                the community fiscal capacity (as measured
                by average income) falls below the national
                average — .2 £ y <_ .3.

     Such a grant formula provides for a minimum (a) frac-
     tion of costs to be borne by the federal government,
     and the total fraction to increase directly with per
     capita costs in excess of the average and with income
     less than the average.  Numerous non-linear variations
     of this approach could be suggested — for example,
     a multiplicative additional factor could be a joint
     function of both excess per capita costs and income.

                              49

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shortest line to the receiving body of water.*  Since they
owned the drain, all newcomers would have to "buy in" —
or build their own.  Residents of Boston, for example,
proceeded in this manner until 150 years ago when the city
began to provide such a basic service.

When cities began to take over the sewer systems, they
merely added on to what was already in place.  As a result,
many systems are old (very old)  in a large proportion of
the overall drainage network.  Also, they were often built
with little attention to performance characteristics that
affected their potential contribution to pollution con-
tainments.  Preeminently, performance characteristics were
thought of in hydraulic terms, with deposition control, for
example, assuming a secondary position.  In addition, few
records were kept of what was built, much less how the
system may have been modified over the decades, or what its
present condition may be.  One consequence of these circum-
stances is that such systems are not often very watertight.
Wastewater can leak out under some conditions leading to
noisome conditions in basements and the like, and possibly
to hazardous cross-connections with the system that distri-
butes fresh water.  Also, groundwaters can leak into the
drainage systems.

The normal practice for designing a plant is to take such
infiltration as a given parameter that will not be modi-
fied.  For example, a competent consulting engineering
firm recently designed an interceptor for a large city in the
northeastern part of the United States based, in part, on
assumed infiltration rates as high as 4,000 gpd/acre.  Such
an "infiltration" rate would exceed a mean annual rainfall
of 53 inches per year.   To translate this into people, a
density of 20 persons per acre and a per capita wastewater
discharge of 100 gallons per day would imply a dry weather
flow of 2,000 gallons per acre per day.  The design infil-
tration rate exceeds this flow by 100 percent.  In this
case tidegate repair and other means of restoring the
integrity of the collection system should have been con-
sidered before specifying new capacity of interceptors,
pumping stations and treatment plants.
     *  Some were as simple as ditches unlined on the
     bottom with unmortared bricks for sidewalls and
     wooden planks for tops.
                            50

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 Additionally,  such seemingly innocuous practices as the
 connection of  roof drains may significantly dilute the dry
 weather flow during storm periods,  with the concomitant
 result that the excessive increases in hydraulic flows
 causes a considerable decrease in the capacity of the treat-
 ment plant to  remove pollutants.   Undermaintenance of the
 collection system is another problem.   For example, prior
 to the installation of a new operating and control program
 in the drainage system of Minneapolis-St.  Paul — a modern
 updating that  includes telemetering and telecontrol ~ the
 existing system was "tuned up" to the original operating
 specifications.   That is,  hydraulic control works, such as
 leaping weirs  and other control structures,  were adjusted
 or replaced as needed.   Reportedly,  the increase in sus-
 pended solids  loadings,  and those of other pollutants,
.received at the plant during runoff periods were substan-
 tially increased,  thus reducing the volume of  pollutants
 that would have been dumped directly in the Mississippi
 River.

 In each of these cases it  is possible to see alternative
 policies for maintenance,  operation and regulation which
 would either reduce or substantially even  out  the hydraulic
 loading on the waste treatment facilities.   Even though old,
 the faults in  many systems are minor.   For example,  a recent
 inspection of  a portion  of the Boston system showed that
 the replacement of a few bricks at  a control weir decreased
 the intrusion  of sea water.   The  effect was  to reduce the
 treatment  plant load by  several tens of thousands of popu-
 lation  equivalents.   Such  faults  can be discovered by more
 thorough inspection and  documentation  of existing systems.

 In some cases  elaborate  schemes,  such  as television inspec-
 tion and recording are worthwhile.   In many  others,  simply
 going and  looking,  backed  up by elementary physical and
 chemical analyses,  will  expose many  minor  shortcomings,
 easily  correctable,  that will  substantially  improve system
 effectiveness.    In still other cases,  policies  that result
 in the  disconnection of downspouts  from sanitary  sewerage
 systems  have been  found  to  be  remarkably effective  alterna-
 tives to treatment plant expansions.   There  can be  no doubt
 that  improved maintenance  and  operation of collection
 systems  could  increase the  effectiveness of  the existing
 investments without  requiring  greatly  increased investments
 in waste treatment facilities,  the additional  capacity  of
which may  only be  used for  a  few hours  a year.
                            51

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Another issue associated with the w11?16.^8^*?1^ the

                  ^

                ^^^
Vermoncominunities that had at that time
final designs for central treatment plants.*  He estimate
the additional resource cost ^centralized systems com-
pared with individual treatment to be  $8 million.  The
individual treatment alternative, however,  is not being
selected because of ineligibility for  federal grants.

Clearly, a grant program which is not  designed  to account
for the issues raised in the context of  a  total wastewater
collection and treatment system is going to encourage
inefficient  capital decisions and ineffective JP6"^??  °J
a system.  Constructing a  new treatment  plant to be  attached
to an antiquated collection system with  numerous  ^legal
storm connections  and little integrity is  bound to  lead  to
an inefficient design.  The plant will have to  be built  to
accommodate  significant  infiltration,  increasing need  capa-
ci?Hy as much as 100 percent.   In  addition, the effective
operation of the plant would depend  on the hydrograph  of
wastewater  flows particularly as  it  was  affected by the
 "illegal" connections.
 The implications of excluding individual treaf«nt ™jj*
 from receiving grants are obvious.   Many small communities,
 ac?ing as cos? minimizes, will select the alternative for
 which they pay the least regardless of the total resource
 costs.

 LOAN PROGRAMS

 Systems can be financed by a grant program, J loan Program,
 or a combination of the two.  The present federal Program
 consists of grants augmented in some cases oy_.jdu
 programs.  Pure loan programs are more limited than grant
      *  Hnmm  w  R   "Municipal Ownership of Individual
      ^r^H-rT^ qvstems " in Proceedings of Sewage Treatment
      £t£S *SE"£i RurarSprionference at Dartmouth
      College, Hanover, New Hampshire, March, 1971.
                             52

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 programs in the percentage of costs they can assume   The
      ...inability to borrow necessary funds on
      reasonable terms does  not prevent any State
      or local public body from carrying out any
      project for construction  of waste treatment
      works  determined eligible for assistance...*

 The  structure of the Environmental Financing Authority is
 currently under development.                   utiior«y is
 —n*    lo.aVs  complemented with  some  grant  aspects,  it
 cannot  contribute the  significant cost share which  is  avail-
 m£?  JSrM8 +Urr!"t grant Pr°9ra*-  As the examples in the
 SelatS ™ ?   indicate, in many cases the annual  capital
 than  IQ n£     ^ln^erest and capital payment) represent less
 ™aL?   Percent of total  (capital associated and  annual O&M
               f  ?n interest-free loan is provided,  which
               UJ1 CaPltal costs bY approximately 50 percent,
          n«,    i°fit0tal annual costs this Deduction repre-
          usually  less  than 30 percent.
nSSr-mo ^e ?!riodfc transfer payment feature of some loan
programs ^attractive for two reasons.  First they spread
the required federal expenditures over an extended peiiod
SnfniUS"  ?6C2nd they might be used to facilitate the
enforcement of performance standards.  Such standards are
very useful for meeting the effectiveness criterion, as
discussed elsewhere in this section.

One example of the use of annual transfer payments are the
reaeral programs to aid local public housing authorities
in covering construction costs.   In addition, since 1969
some of the operating and maintenance costs of local authori-
ties have been covered by the federal government.  The grants


     *  Public Law 92-500, 92nd  Congress, S.  2770,  October
     18, 1972;  Environmental Financing.,  Section 12(c),  p.  85.

        These cases utilize a 30-year capital amortization
     period with 6 percent interest charges.
                           53

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to cover the construction costs are of the form of annual
payments to the local housing authority to cover interest
and amortization.*  Public housing authority bonds to cover
construction costs are issued by the federal government in
the name of the local housing authority, and are tax-free
under the federal tax code.  In the case of sewage treat-
ment capital costs, the federal government might use the
potential withholding of interest and amortization payments
to local governments as an incentive for them to meet the
performance standards.  In such a case the bonds would have
to be issued by the local authority.  The question remains
as to how the market would evaluate the uncertainty asso-
ciated with the conditional backing of the federal govern-
ment.  Public housing authority bonds are considered to be
about as secure as other federal obligations, which means
they carry interest rates considerably lower than those of
municipal bonds.

OPERATION AND MAINTENANCE GRANTS

The present federal program covers essentially capital items
only.  New York State has the only state operation and
maintenance grant program.  The alternatives considered in
this report examine both capital and operation and mainte-
nance programs.

It can be argued that because operation and maintenance
costs are not subsidized, municipal grant recipients are
biased towards the selection of capital-intensive alterna-
tives.  A strong advantage of a financing program which
supports both capital and O&M costs is  the possibility of
equalizing local share ratios of these  costs and, hence,
eliminating the bias.  Theoretically, if there is no differ-
ential grant on capital or operating costs, then municipali-
ties acting as cost minimizers will select the most efficient


     *  Before construction begins, the Department of
     Housing and Urban Development  enters  into an annual
     contributions contract covering  interest and amortiza-
     tion on long-term bonds issued by  the  local  housing
     authority after  construction  is  completed.   This  agree-
     ment cannot exceed  forty years.  This  is discussed  in
     Aaron  Henry  J., Shelter  and  Subsidies;  Who Benefits
     from Federal  Housing  Policies? The Brookings  Institu-
     tion, Washington, D.C., 1972,  pp.  112-113.
                            54

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 treatment alternative  (from a national and local view-
 point) .*

 However, the bias towards selection of capital-intensive
 alternatives is not simply one of "price effect" stemming
 from differential subsidies.  Two other issues are signi-
 ficant.  The first is the limited evidence that munici-
 palities do not weigh capital and O&M dollars equally.  The
 result is that municipal budgeting process decisions favor
 capital-intensive programs.  The second issue is whether
 all potential treatment alternatives receive adequate exa-
 mination or whether the present incentive built into the
 engineering fee structure and professional inertia result
 in capital-intensive designs.

 Perhaps more important, operation and maintenance grants
may be attractive because they are not lump sum payments
but continuing transfers which can be made to depend on the
performance of treatment plants.  New York State has found
that its O&M grant program is an effective and flexible
mechanism for improving plant performance and insuring com-
pliance with state regulations.+

PLANNING AND PERFORMANCE STANDARDS

Financing alternatives may be linked to a variety of
planning and performance criteria.   The current federal
program requires approved facilities planning,  but the
amount of the grant is not dependent on type of planning.


     *  We have examined the distorting influence of this
     grant in recent studies of market mechanisms for control
     of pollution,  "Effluent Charges:   Is the Price Right?"
     Environmental  Protection Agency,  Washington,  D.C.,
     September,  1973.   Utilizing recently developed cost
     data for the Cleveland-Akron area on biological, phys-
     ical,  chemical and land-oriented  treatment schemes,
     Raymond studied the potential  efficiency losses stem-
     ming from this Lias,  "Impact of Federal Financing Pro-
     visions on the Federal  Water Pollution Control Act
     Amendments  of  1972,"  unpublished  manuscript,  Center
     for Urban  Regionalism,  Kent State University.

     +   Meta Systems  Inc.,  "New York State Aid  for Operation
     and Maintenance  of Sewage Treatment  PLants:   Implica-
     tions  for  Federal Policy,"  for  Environmental  Protection
     Agency,  Washington,  D.C.,  November,  1973.

                           55

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Alternatives could either make grant size a function of the
type of planning or merely make grant approval dependent on
certain planning having been done within prescribed guide-
lines.  For example, grant approval could be conditional on
facilities  planning having been integrated with comprehen-
sive land use planning.

A list of general characteristics of performance criteria
includes the following:

-  enactment and enforcement of a sewer use ordinance;

-  qualified operators, adequate in number;

-  adequate laboratory testing capabilities, under effective
   sampling and analytical supervision;

-  adequate infiltration study, with a satisfactory program
   for abatement, updated as necessary;

-  monthly operating reports;

-  audited accounting records of costs;

-  acceptable plant performance in terms of:

      good housekeeping practices,

      compliance with permit to discharge,

      safety program,

      upgrading program,

      production, within practical limits,  of  the  degree  of
      treatment which  the process  is designed  to produce
      under conditions of design flow  and  loading,  and

      relationship  to  stream standards;

-  adequate reporting  of the bypass  or overflow incidents;
   and

-  annual  engineering  reporting on collection  and  treat-
   ment  plant performance,  with recommendations (prepared
                             56

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   by qualified in-house engineering staff or outside
   consultant).*

Planning Standards and Cost Estimating

In the past municipalities and their consultants did not
fully examine a range of treatment alternatives, and there
was little pressure either from state or regional EPA
authorities to do so.  The new guidelines for facilities
planning are explicit in discussing the need for detailed
analysis of treatment alternatives.  If these guidelines
are stiffened and if appropriate regional review is initi-
ated, this can serve to force examination of all viable
alternatives and selection of efficient and effective,
rather than local, least-cost alternatives.

Such review of the adequacy of the waste treatment plans
can be facilitated by the development of regionally  (or
state) adjusted cost standards for various treatment alter-
natives.  However, the development of adequate  review
standards dependent on costs will be a difficult task given
the great variability in design practice and cost estimating
procedures across the nation.

There have been some quantitative empirical studies of
variability in design practice.  One such  study, conducted
in Wisconsin during  1967, was concerned with the design
practices for storm  drainage in use in the state.   Thirty-
two cities were surveyed.  The median  (1966) population was
30,000 and the range was  from 7,500 to 770,000  and the
areas varied in size from 9.8 square miles to 96.5 square
miles.   The survey included  a questionnaire on  sewerage
system problems,  sewage treatment plant  experience after
rain or  snowmelt, and the like.

In addition, each city was presented with  a well-defined
 (albeit  hypothetical) storm  drainage design problem  for a
      *   Meta Systems  Inc.,  "New York State Aid for Opera-
      tion and Maintenance of Sewage Treatment Plants:
      Implications for Federal Policy."

      +   Ardis, C. V., Dueker, K. J., and A. T. Lenz, "Storm
      Drainage Practices of Thirty-Two Cities," Journal of
      Hydraulics Division, ASCE, 95 (HYl), 383-408 (1969).
                             57

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15-acre residential area.  The engineering calculations
involved in the study were not trivial (at least one pro-
fessional man-day was required in each city).   Many differ-
ences in practices were noted in the detailed evaluation.
Some of the differences could be explained in terms of
local attitudes toward urban flooding, and others to
possible use of outmoded technical analysis.   For our pur-
poses, however, it is sufficient to note that the total
costs estimated for the designs presented by the engineering
departments ranged from $7,000 to almost $70,000.  Although
the variability in the design and cost estimate of treatment
works may not be as extreme, statistical studies of costs
of existing treatment plants which have been undertaken show
a wide range of costs.*

There appear to be two alternatives for developing cost
review procedures.  One approach is engineering design
review which is based on detailed itemized cost studies.
The other is the standardized cost function approach which
relies on the development of average cost estimates func-
tionally dependent on standard design variables such as
flow and concentration.  Although the adoption of the former
procedure probably would lead to more efficient designs, it
implies a commitment of substantial resources to the admini-
strative task of review.  The latter approach, while
administratively less costly, would also be less reliable.
A review of the current literature on cost estimating indi-
cates that it would be difficult to identify errors of less
than 20 to 30 percent.  Assuming that some form of the
standardized cost function is to be utilized, this argues
strongly for limiting the "price effect" of the capital
grant.  At over 75 percent the incentive for overexpenditure
on capital from the local perspective is high and the ability
to detect it is limited.

Continuing Performance Standards and the Leverage on
Operation and Maintenance — The financing alternatives
could also be keyed to a set of continuing performance
standards where the grant is forthcoming only if perfor-
mance standards are met.  Such a program provides leverage
to induce improved operation and maintenance of treatment
     *  Shah, Kanti and George Reid, "Techniques for Esti-
     mating Construction Costs of Waste Treatment Plants,"
     J. Water Pollution Control Federation, 42, No. 5,
     Part 1, May, 1970.
                            58

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systems.  There would be no lump sum transfer to the muni-
cipality, rather payments would be made on an annual basis
depending on plant performance.  It could be built into
either loan or grant programs, with some of the interest
and/or capital amortization grant being subject to perfor-
mance standards.  The present federal program does not
include this characteristic.

An adequate financing program for water quality management
will include provisions that assure the continuing perfor-
mance -- to some specified levels — of the investment in
collection and treatment systems.  Unfortunately, the pre-
vailing attitude has been to emphasize the planning, design
and construction of such works, but not their performance.
Informal surveys of hundreds of plants indicate many
instances of poor housekeeping practices.  In such cases,
improvements of the order of 5 to 15 percent in removal
efficiencies can be expected at negligible increases in
operation and maintenance costs.*

Effecting Changes in Operation and Maintenance:  Some
Examples — Table 4 on the following page presents common
operation and maintenance problems.+  It lists the
     *  We feel confident in this assertion because our
     involvement in this area has been significant over a
     long period of time.  Specifically important are:  the
     observations and experience at numerous treatment
     plants, primarily by two of our principals, Joseph J.
     Harrington and Harold A. Thomas, Jr.; the earlier
     research on the design and operation theory for treat-
     ment plants by Thomas, and recently by William Pisano
     and Joseph J. Harrington; the numerous discussion of
     the issues with other professionals; and, finally,
     the additional experience resulting from our recent
     study of the New York State O&M program.

        Other examples could have been added such as gross
     operator negligence (e.g., utilizing only some of the
     primary tanks or shutting off aerators), or the more
     subtle issue of inadequate monitoring of a sensitive
     process  (e.g., allowing digestion to go "sour").
                            59

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              Table  4,

   Operation or
Maintenance Problem

 Treatment Plant

    Wrong mix liquor
    SS concentration
IMPLICATIONS OF OPERATION AND MAINTENANCE PROBLEMS
AND SOME SOLUTIONS


              Implication
  Lower (than design)  organic removal
  in  activated sludge  system
          Solution
Measure more frequently, change
recirculation and cell residence
time
    Uncalibrated flow
    meters

    Lack of rotameter
    Infrequent sludge
    cleaning in primary
    units

    Poorly maintained
    or cleaned effluent
    weirs

    Clogged manifolds
    on trickling filter

 Collection System

    Inadequate infiltra-
    tion control
    Inadequate cleaning
    of interceptors
   Improper chemical dosage and poor
   performance in secondary clarifiers

   Inadequate or differential aeration
   in some tanks — poor performance
   (lower DO poor settling floe)

   Lifting and flotation resulting from
   anaerobic gas discharge decreases
   primary removal levels

   Non-linear hydraulic effects leading
   to lower removals
   Uneven loading decreases net effective
   capacity reducing removals
   Hydraulic overload or too-diluted a
   solution for trickling filter —
   removals reduced
   Solids bypass plant during scouring
   high flows
Calibrate meters, adjust dosage
rates

Install rotameter, split air
measurement and adjust for each
tank

Adjust removal frequency with
loading rate
Maintain and clean regularly
Clean manifolds regularly
Institute a program to control
infiltration
Clean interceptor regularly

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implications of these problems and suggests solutions.   The
purpose is to illustrate how leverage can be applied to O&M
problems and how changes might result.

Some of the problems cited in the table directly affect
such parameters as effective capacity and loading intensity.
The empirical relationships which have been developed for
treatment plant removal efficiencies as a function of these
and other parameters show that manipulation of these para-
meters by dealing with the problems of the type cited in
Table 4 would lead to the 5 to 15 percent increase in
removal efficiency referred to above.  The process of
effecting these changes, of course, would be one of gradual
change, but these improvements are probably possible in more
than half of the plants in this country.

The solutions given in the table are ones that would be
induced by a performance standards program that includes
monitoring, operating guidelines, and fiscal incentives.
None of the solutions require significant plant changes.
Some are merely housekeeping types of changes; most require
more regular operation with a trained person; some imply
additional costs  (men, chemicals, power).  All result in
better plant performance.  In addition to ameliorating old
problems, plant performance standards would insure that
similar problems did not occur in new plants.

CONCLUSIONS

The discussion and arguments presented in this section,
while not leading to the design of a  financing program, do
suggest what features of any scheme will provide  some con-
trol of program performance as measured  by the criteria.
Efficiency can be affected by altering the design of allot-
ment and grant formulas, by improving planning standards,
and by modifying  the list of eligible wastewater  system
components.  Effectiveness can be  increased by initiating
an O&M grant program a'nd by developing and  implementing
plant performance standards.  Insuring a more equitable
distribution of the cost burden can be accomplished by
modifying the grant formulas.  None of the  suggestions
made in this section are infeasible  from either an admini-
strative or political perspective.  On the  other  hand,  it
is obvious that any financing program designed to perform
well on the three other criteria will be a  program
requiring considerable  resources  for  administration.
                            61

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                          SECTION  4

      QUANTITATIVE ANALYSIS OF  FINANCING ALTERNATIVES

 INTRODUCTION

 The  previous  section  of  the  report  discussed  alternative
 grant programs  that the  federal government  might consider
 to finance  a  portion  of  the  expenditures  for  wastewater
 treatment required  by the 1972 Amendments.  The earlier
 discussion  suggests that alternative  grant  programs might
 be appropriately characterized by seven  features.   In this
 section a limited number of  alternatives  are  quantitatively
 examined.   These alternatives  are associated  most explicitly
 with the grant  formula.   They  vary  in three characteristics:
 size and time pattern of construction grant and size  of
 operation and maintenance grant.  The discussion in the  pre-
 vious section also  suggests  that  the  fiscal impact on
 municipalities  and  the distributional impact  on individuals
 will vary greatly depending  on the  variables  of population,
.revenue base, current budget,  family  income,  growth rate,
 condition of  existing sewerage system, and  industrial com-
 ponent of waste flow.  In this section the  implications  of
 these differences  for local  fiscal  impact and for equity
 are  identified  and  related to  alternative financing programs.

 First, the  results  of a community classification scheme  are
 discussed:    (1) to  illustrate  the heterogeneity of communi-
 ties in terms of population, growth rate, percent low income,
 per  capita  revenue, per capita debt,  median family income,
 percent sewered, existing treatment capacity  and industrial
 share; (2)  to identify significant relationships between _
 these community characteristics;  and  (3)  to provide a basis
 for  evaluating  municipal model results.*  Second, a model
 of municipal decisionmaking with respect to wastewater
 treatment plant construction time and design capacity is
 employed in order to estimate how alternative financing
 schemes and community characteristics affect efficient re-
 source allocation measures of community and federal finan-
 cial  impact  and the  equitable sharing of the costs of
      *  Details of the community classification scheme are
      presented in Appendix E.
                              62

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water pollution control.  Third, the 1973 Survey
of Needs is utilized to estimate the state and national
fiscal impacts of alternative financing schemes.  These
three areas of analysis, together with the qualitative
analysis in Section 3, allow the drawing of conclusions and
recommendations regarding alternative financing programs.

THE COMMUNITY CLASSIFICATION SCHEME

The classification scheme relates to community population
size such characteristics as population growth rate, median
family income, per capita revenue, per capita debt, percen-
tage of population sewered, existing treatment capacity,
and percentage of industrial sewer flow.  The data used in
the scheme are taken from the computer tapes of the City
and County Data Book (Census Bureau) and the 1973 Survey of
Needs (EPA).   The classification methodology adopted is
based on the hypothesis that such characteristics as growth
rate, per capita revenue, or percentage of the population
sewered vary with population size and that in addition for
communities in a given population size group these charac-
teristics also vary.  To test this hypothesis, simple
contingency table analysis is performed on the following
set of variables:

a.  Population (1970) vs. Growth Rate (1960-1970);

b.  Population vs. Percent Low Income;

c.  Population vs. Per Capita Expenditures;

d.  Population vs. Per Capita Debt;

e.  Population vs. Median Family Income;

f.  Population vs. Per Capita Revenue;

g.  Population vs. Percent of Families with Income less
    than X Dollars;

h.  Population vs. Percent Sewered;

i.  Population vs. Excess Treatment Capacity; and

j.  Population vs. Industrial Share.
                             63

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 The  contingency tables* display,  in a discrete  format,  the
 relationship between the  independent variable  (in  all cases
 population) and a characteristic  or dependent variable,
 e.g., growth rate.  Each  row of a table represents a range
 of city  sizes and each column  a range of  values for a par-
 ticular  dependent variable.  For  example,  in Table 5 all
'the  entries in the  second row  are cities  with populations
 between  25,000 and  37,500.  The sixth column in that table
 contains all entries for  cities with a growth rate between
 zero percent and 5  percent.  The  last two rows  of  the table,
 labeled  "PERCENT" and "TOTAL," are the marginal distribu-
 tion and total number of  entries  in each  growth rate
 category.  The right most column  of the table,  labeled
 "TOTAL," contains the marginal distribution and number  of
 cities in each population group.

 The  cells in a table contain four numbers:

 1.   the  percent of  row totals, i.e., the  percentage of
     cities in a given size  range  which fall into a given
     dependent variable category;

 2.   percent of sub-table  total, i.e., the percent  of all
     cities in the sample  which fall into  a given dependent
     variable category;
      *   Contingency  tables  are  constructed  from sets  of dis-
      crete  categories  of  two  variables.   Using a contingency
      table,  it  can be  determined whether  or not a relation-
      ship exists between  the  variables.   The test is  based
      upon the hypothesis  that the  pattern of the entries in
      the cells  of a  contingency table  are functions of the
      discrete marginal distributions of the two variables,
      i.e.,  that the  variables are  independent.  (The  marginal
      distribution of a variable which  takes on discrete
      values  is  the frequency  function  of  that variable inde-
      pendent of other  variables.)   The statistic'most often
      used in this test is the Chi-square  statistic.  If the
      significance of the  Chi-square statistic is of the
      order  of  .01, then it  is reasonable  to reject the hypo-
      thesis  that the variables  are independent.  The  rejec-
      tion of this hypothesis  implies that the variables do
      possess some sort of relationship.   An examination of
      the table  usually leads  to some understanding of the
      nature of  this  relationship.
                             64

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                                              Table  5.
. - 	 	 VARI4I
(.KDWIll AATI
>yOX >l»t >IO« > »< <>-•>! r--,C ?CT
D*C etc »i»c ntr ntr* mr iur i.,/- .»./- ....••

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"• '
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POPULATION ".' "•'"'
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* 6
iioo.ct
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7.ST
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1" TOTAL


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63



"in •*
a*

PIUENT O.Ot O.OX O.Ot O.«t »».?« "**.«>» 10.St "*.21 1.51 l.»f 100. «
	 , 	 JMU. 	 0.... p 	 0... . «._ 7U. . 4*2 .... •* 3> 12 15 Bl»
      CELL CNTIttS AM »t»ClfNT (>•• HIM TOTALS
                      HtC-llil Or SUt-IABLf TOTAL
      -. 	.	 H«'ieTl!O VAtUfi
                                       **.*16».	STCNIPICAMT At. .O44..MITH 10 OfCMfS OF
 TAktt SbMHAKV

"TOTAL »tl.Hb[ll GF UNIT!, IN TAW*
       Of L-N1TV ONlTTFb OIF TU
                                                  t*
 * DECREASE
 "INCREASE
                                                65

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^   exoected values,  i.e.,  the number of cities in a given
    size range which  might be expected to fall in a certain
    dependent variable category if city size and the depen-
    dent variable were, in fact, independent; and

4.  the number of cell entries, i.e., the number of cities
    in the sample in  a given size range and a given depen-
    dent variable category.

For example, in Table 5 the cell delineated by the second
row and the sixth column contains these numbers for cities
between 25,000 and 37,500 with growth rates between zero
percent and 5 percent.  An examination of this cell indicates
that 57.5 percent of the cities in this size range have
growth rates between zero and  5 percent.  20.5 percent of
all cities in the sample are in this size range and have
growth rates within this range.  In addition,  if  size and
growth rate were independent,  104.6 cities would  be expected
to fall into this cell, whereas the actual number of cell
entries is 169 or more than expected.

The other important numbers in the tables are  the Chi-
square statistic, level of significance andn^r^s °|  „
freedom.  These  appear in  the  row labeled,  "CHI-SQUARE.
in Table 5, for  example, the Chi-square statistic has a
value of 44.616  with a significance  of  .044  for  30  ^&&s
of freedom.*   In other words,  if growth rate and  population
 size are independent,  the  probability  of obtaining  a Chi-
 square value of  44.616 with  30 degrees  of  freedom is  .044.

 In the  interpretation  of  the  contingency tables,  the  first
 to assume that  there  is  some relationship between population
 and the dependent variable.   If,  on the basis of signifi
 cance,  a relationship is found,  then examination °£ «£
 expected values and the  actual cell entries suggests what
 the nature of that relationship may be.  For example, if
 the cells in the northwest portion and the southeast por-
 tion of the contingency  table showed positive differences


      *  The degrees of freedom in a contingency table of r
      rows and c columns  is equal to (r-1)(c-1).  In Table
      5  for example,  there are 7 rows with entries  (r=7)
      aid 6 columns (c=6), thus (r-1)(c-1) = 6x5 = 30   For
      an explanation of this expression, see Hoel, H. P.,
      Introduction tn Mathematical Statistics   (3rd  edition)
      John Wiley & Sons,  Inc., New York, 1963, p. 253.
                             66

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between the actual cell entry and the expected cell values
and the cells in the northeast and southwest showed nega-
tive differences, then it could be said that there was a
positive relationship between the independent variable and
dependent variable.

RESULTS

The Chi-square statistic is significant at under the .001
level, with degrees of freedom ranging from 24-48, in all
but four cases (see Table 6).  The exceptions are for
growth rate (.044, 30), percentage of families with income
greater than $25,000 (.015, 42), percentage of population
sewered (.422, 30), and percentage of industrial waste flow
(.002, 30).  Of this group the only truly insignificant
relationship exists between community size and the percen-
tage of population sewered.*
                                   *
With the highly significant Chi-square statistic in most
cases, comparison of actual and expected cell entries
suggests the following observations for places of over
25,000 population:

a.  growth rate is inversely related to city size
    (Table 5) ;

b.  the percentage of low income families in larger cities
    is higher than in smaller cities (Table 30);

c.  more small cities than expected have high median family
    incomes (Table 31) ;

d.  smaller cities demonstrate a greater spread in median
    family incomes than larger cities (Table 31);

e.  smaller cities show a greater range in income than
    expected and larger cities show a smaller range than
    expected (Tables 32(a) through 32(c);
     *  Population figures in the 1973 Survey of Needs are
     known to be unreliable.  Since it is that set of
     figures used in the construction of this contingency
     table, the unreliability of the data may be the cause
     of this result.
                             67

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             Table 6.   CHI-SQUARE STATISTIC


                               Level of         Degree of
Dependent Variable           Significance        Freedom

Growth Rate                      -044               30

Percent Low Income Families     <.001               24

Median Family Income            <.001               24

Percent With Income 3000        <.001               36

Percent With Income 3-5000      <.001               24

Percent With Income 5-7000      <.001               24

Per Capita Debt                 <.001               30

Per Capita Revenue              <.001               36

Percent Sewered                  .422               30

Excess Treatment Capacity       <.001               24

Percent Industrial Share         .002               30
                             68

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f.  larger cities have a smaller per capita debt than
    smaller cities  (Table 33);

g.  smaller cities have lower per capita revenues than
    larger cities  (Table 34);

h.  there appears to be no significant relationship between
    percent sewered and community size for communities of
    over 25,000 population (Table 35);

i.  smaller cities tend to have more excess capacity than
    larger communities (Table 36); and

j.  more small communities than expected have a high indus-
    trial share and fewer moderate size communities than
    expected have a high industrial share (Table 37).

An examination of the percentage-of-row-total entries shows
clearly that all of the characteristics, while depending on
population in some fashion, demonstrate rather significant
variations within given population groups.

The results of the classification scheme do not suggest
relationships which are particularly surprising, but they
are important when considering alternative financing schemes,
given that communities must build treatment plants and pay
a substantial portion of the total cost.  The relationships
are of three types:  (1)  those with unfavorable fiscal or
equity implications for small cities; (2)  those with unfavor-
able implications for large cities;  and (3)  those with
implications which are independent of city size.

The relationships between city size and growth rate, per
capita debt, and per capita revenue fall into the first
group.  The growth rate tends to be higher "in smaller cities
and with a more rapid increase in population size comes the
need to build a relatively larger treatment plant.   This
results in higher per capita costs in the early years of
operation.   From a national perspective this leads to an
inequitable distribution of costs.   Per capita debt and
per capita revenue are not necessarily related to equity,
but rather to fiscal issues.   Later in this section of the
report figures appear which show that the per capita debt is
higher for small communities.  These figures show that even
with a capital grant, a small community with a low per capita
debt may face an immediate increase of over 20 percent in
                             69

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 this debt figure.   Such a sharp rise affects  the price a
 municipality pays  to borrow money.   Per capita revenue is
 probably less important than debt,  particularly if revenues
 for the  facility are obtained from  a user  charge.   However,
 as  with  debt,  the  percentage change in  per capita revenue
 necessitated by  the construction of a plant can be consid-
 erable.

 For larger cities  the factors that  have important implica-
 tions  for municipal financing are the relatively high
 percentage of  low  income  families,  the  median family income
 and the  excess treatment  capacity.   A positive relationship
 exists between the percentage of low income families and
 city size and, as  would be  expected from this relationship,
 the median family  income  in large cities is lower  than the
 average  for all  the cities  in the sample.   Thus,  given the
 portion  of the local  cost and the manner in which  revenues
 to  finance this  share  are obtained,  low income families
 in  large  cities  bear  relatively  high  costs  in relation to
 their income.  Excess  capacity tends  to be  inversely
 related  to community  size.   Thus, at  this point  in  time,
 because  larger cities  do not have as  much excess capacity
 as  smaller cities,  they will be  required to do more in the
 aggregate  and on a per  capita basis than smaller ones  to
 increase  their treatment capacity to  meet the  1977 and 1983
 requirements of  the 1972 Amendments.

 The  third  set of relationships,  those which are independent
 of city size, illustrates the heterogeneity of cities,  even
within a given size range.  All of the  characteristics have
 a considerable range within  any given population class as
well as across city size.  As obvious as this may be,  a
 grant formula which does not take this diversity into  con-
 sideration will not account  for fiscal impact and equity  in
 the  financing of treatment facilities.*
     *  One important qualification which must be placed on
     this discussion concerns the sample of cities used to
     create the contingency tables.  Approximately 56 per-
     cent of the population, all those living in cities of
     less than 25,000,  are ignored in the contingency tables
     constructed from the City and County Data Book.   It
     might be ,expected that the situation in these communi-
     ties is considerably different from that which is
     represented in the sample used but inclusion of these
     smaller communities can only be expected to further

                            70

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A full set of contingency tables can be found in Appendix
E.  In the following paragraphs a municipal model is pre-
sented that elaborates for various grant formulas some of
the effects on total and per capita costs of such variables
as community size, population growth rate, and percentage
of industrial flow.

THE MUNICIPAL MODEL AND ANALYSIS

Approach to the Model

One theory* of the municipal expenditure decision process
views local budgeting as being driven by internal forces:
the resolution of intragovernmental conflicts.  This theory
suggests that decisions are made through a negotiation pro-
cess among the parties in the municipal bureaucracy and
that this occurs largely independent of local preferences.
Proponents of this view focu? their analysis on the series
of steps that usually constitutes a budgeting process
including departmental requests, executive recommendations
and legislative appropriations, and see a municipal budget
as incrementally changing, driven by the internal bargain-
ing process."1"

The opposing point of view is based largely on economic and
political theories of collective decisionmaking.  This
theory sees decisions with respect to municipal expenditures
as being made by officials attempting to meet the needs and
preferences of their constituents — these preferences being
     (footnote from previous page continued)
     emphasize the conclusions regarding community hetero-
     geneity and the spread of program impacts.  In addition,
     the units of analysis in the City and County Data Book
     figures, cities, are not compatible with the units of
     analysis, treatment facilities, in the 1973 Survey of
     Needs.
     *  For review of the literature, see, for example,
     Appendix A:  "Review of Literature on the Budgeting
     Process" in Scott, Claudia, Forecasting Local Govern-
     ment Spending, The Urban Institute, Washington, D.C.,
     1972.

     +  An often cited example of this view is Crecine, J.
     P., Governmental Problem Solving:  A Computer Simula-
     tion'''^ the Municipal Economy/ Rand McNally, Chicago,
     1964.But as Scott (ibid.)points out, Crecine also
     views budgeting as an optimizing process to maximize
     net social welfare.

-------
a function of social, economic and demographic character-
istics of the community.

Both theories have contributed to our modeling of municipal
choice of treatment plant, but under the 1972 Amendments
most local choice has been removed.  Currently, municipali-
ties are being directed to achieve secondary or best-
practicable treatment and this requirement is independent
of the needs or preferences of the community, and of the
public works department's relative negotiating power in
capital expenditure budgetary decisionmaking.

CRITERIA, IMPACT MEASURES AND LOCAL CHOICE

The issue of local choice is relevant to this analysis
since this choice may be affected by alternative financing
programs.  These programs may affect what local choice is
actually made in contrast to what choice should be made
when viewed from the national social perspective.  Local
decisions may be influenced by criteria and impact measures
other than national efficiency.  Alternative criteria and
impact measures considered in this section reflect a syn-
thesis of the local financing literature and of impressions
developed through our professional experience with local
and regional institutions.  These criteria are present
value of local costs, per capita local cost burden, per
capita debt burden and administrative feasibility of fre-
quent plant construction.

Under the assumptions of our analysis, local choice excludes
options not to build or to delay inordinately.  Municipali-
ties may, however, initially build at the secondary treat-
ment level and move up to best-practicable treatment
according to a schedule approved before construction bv EPA
but not later than July 1, 1983.

Municipalities may also select the treatment process with
its degree of capital and operating intensities.  The ana-
lysis was designed to consider biological and physical/
chemical processes, but because cost data available to us
showed biological treatment to be less costly from both
capital and operation and maintenance standpoints, only a
few examples are presented using physical/chemical pro-
cesses.  General data on land treatment were not available.
Finally, selection of plant scale and mechanisms for financ-
ing the local share of costs are local decisions, constrained,
of course, by EPA regulations.

                            72

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WHAT THE MODEL CAN TELL US

The simulation model examines a combination of cases
adjudged most relevant based on the classification analysis
and those financing alternatives described in Table ?.
National efficiency (least resource cost) criterion and the
other impact measures discussed above -- present value of
local costs, per capita local cost burden, per capita debt
burden and administrative feasibility, are evaluated for
each case and each financing alternative.  The results
tell us how financing alternatives affect community and
federal financial impact — whether, for example, some
alternatives narrow the variation in costs across communi-
ties- the implications of alternative financing programs
and locTl choice criteria for selection of the most effi-
cient treatment option; and the equity of cost burdens for
a given financing alternative when examined across communi-
ties with different characteristics.

THE CASES

The model was run for representative cities defined by the
following parameters:   growth rate, percentage of industrial
waste flow in total sewage; and the ancillary cost factor.*
Eight representative cities are investigated-, comprising all
combinations of:  1 percent and 5 percent growth rate, zero
percent and 50 percent industrial flow and the presence or
absence of ancillary requirements.  Four city sizes are con-
sidered ranging in population from 25,000 to 500,000.  The
costs of biological treatment are computed and for a popu-
lation of 75,000, the costs of the physical/chemical
treatment alternative are calculated.

The representative cities shown in Table 8 and discussed
below cover many of the municipal characteristics that
were shown to be significant in the city classification
     *  The ancillary cost factor reflects the necessity of
     constructing interceptors and pumping stations in con-
     junction with building a treatment plant.  In the model
     the factor is a function of population size and ranges
     from approximately .5 for small communities to 2.5 for
     large municipalities.  The use of this factor is
     explained below in the discussion of cost functions.
                            73

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                                    Table  7.
Alternative
Capital Grant
    Percent
O&M Grant
 Percent
Additional
Variation
1

2

3
4
5
6
j ?
*0

75

75
50
50
50
75
0
/ Capital grant in each
0 I decision period for
1 design population
25 1
<
1
25
50
0


Grant for capacity fo
i in 4 +• t 2«1 r^nr-^^^^ st- 4 <~irt /*vyi

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                           Table 8.   DEFINITION OP CASES
                         Ancillary Works
                             Required
                            2
Ancillary Works
 Not Required
Population
(Thousands)
Physical-
chemical
                     Each cell is of the form a/r, where
                        i is the yearly population growth rate (percent)
                        r is the industrial share of flow (percent).

                     Example:  Case 6C is that of a city of 75,000 present
                        population with a 5% growth rate, 0% industrial
                        flow, which selects biological treatment of wastes
                        and needs no building of ancillary works.

-------
analysis.   The  following discussion .does not include cities
considered  to have highly atypical characteristics.

HOW THE MODEL WORKS

The model examines two sets of decisions:  when to build
best-practicable  treatment and what capacity to build under
alternative  financing schemes.   A planning period of 29
years is assumed  with three decision periods as pictured
below.*
     1974/75            1983/84       1993/94        2003/O4
     •*	9 years	^^	TO years—*^	10 years	».

     to                    t,             t2                ts


     Figure 2  Decision periods within  planning period
The possible combinations of decisions  (or branches of the
decision tree) are defined by  the  following rules:

1.  three decisions are made,  one  at  t  ,  one at t,, one at
    t...                               01
     *  The length and number  of the  decision  periods are
     model parameters that can be varied.-   However,  all
     results are presented for the three periods  shown.   The
     length of the first period results from  the  difference
     between present time and the point  (1983)  ..I*er  the new
     standards are operative.  The two additional 10-year
     periods, although arbitrary, reflect  the fact that
     rarely would a treatment plant be built  more frequently
     than every 10 years.
                            76

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2.  at t0/ either secondary or best-practicable treatment
    may be chosen.

3.  at each decision point ti , capacity sufficient for the
    population at either t± + 1, t± + 2, or t±+3 may be built.
4.  best-practicable treatment must be chosen at or before

    V
5.  if, at t0/ the building of secondary treatment capacity
    for the population at t2 or t3 is chosen, subsequent
    decisions are limited to upgrading this capacity to
    best-practicable .

These rules result in twenty possible branches of the deci-
sion tree, as shown in Table 9.  The decision tree is the
same for both biological and physical/chemical treatment.

In Table 9, Pi denotes the population* at time t^  If r
is the yearly population growth rate, then
where ti and t0 are in years.  APmn denotes the  increment
of population from time tn to time tm:
or
     AP    =  P  - P
       mn      m    n
      P    =  P  + AP
       m       n     mn
The symbols  S, B,  and U  denote  the  decisions  made.   S
denotes building a secondary  treatment facility;  B  denotes
building  a best-practicable facility;  U denotes the upgrad-
ing of a  secondary facility to  a  best-practicable facility
of the same  capacity.  These  symbols  can also be .interpreted
as the costs of building the  facilities, in which case the
      *   Population is  a surrogate for capacity.
                             77

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           Table 9.   TREATMENT DECISION  OPTIONS
Option
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Decision 1
Cost
B(P3)
B(P2)

B(P1)
s(P3)
s(P2)
s(Pi}
Decision 2
Cost
	
	

B(AP21)
B(AP31)
B(AP41)
u(P2)
u(P3)
u(P2)
U(P1)+B(AP21)
U(P1)+B(AP31)
U(P1)+B(AP41)
U(P1)+B(AP51)
Decision 3
Cost
	
B(AP32)
B(AP42)
B(AP52)
B(AP32)
B(AP42)
B(AP52)
	
• 	
U(AP32)
	
B(AP32)
B(AP42)
B(AP52)
B(AP32)
B(AP42)
B(AP52)
	
	
	
S denotes
B denotes
U denotes
a secondary  facility.
a best-practicable facility.
upgrading a  secondary facility to best-practicable.
                     78

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cost associated with any branch of the decision tree is the
sum of the costs in that row of the table.  For example,

     cost of branch 10  =  cost of secondary for population
                           at time t

                           +  cost of upgrading part of
                              secondary to best-practicable
                              (upgrade results in best-
                              practicable for population ?2)

                           +  cost of upgrading remaining
                              secondary (for population
                              AP,0 = P, - P0) to best-prac-
                              tic'able.3    2

The model defines B - S + U.  Furthermore, all runs assume
no existing capacity* (hence there are no AP's as arguments
in the first column of Table 9) although the model is
designed with the capability of analyzing existing capacity.
Each cost function used in the model is of the form


     CCAP  -  aAblX2b2  <1 +


for capital costs, and

                v^
     C0&M  ~  a2X3


for O&M costs.

The variables and parameters are:

     X,  =  design population equivalent  (see below),
            in persons;

     X2  =  design flow, mgd;
     *  Existing capacity implies another decision tree,
     which can be derived using the rules above  (the deci-
     sion tree is an input to the program).  The cost
     figures for cases with existing capacity lie in the
     range of the results for no existing capacity, as one
     would expect.
                             79

-------
     X3  =  actual flow, mgd;

     ¥   =  design population, in persons;

     f   =  ancillary works factor  (dimensionless).

Values for the parameters are given in Tables 10 and 11.
The population equivalent, X , is obtained using the follow-
ing expression.*

     v   _  8.33X0C
      1  ~  	—
             0.17

where 8.33  =  conversion constant, 8.33 Ibs/million gallons
               per mg/£,

      0.17  =  Ibs of 5-day biochemical oxygen demand (BOD)
               per capita per day,+

      C     =  BOD  of wastewater in mg/Jl.


The model calculates flow by assuming an average per capita
flow generally 200 gallons per capita per day (gpcd) and
multiplying by population.  The factor f(Y)  is used to
include the additional costs of constructing interceptors
and pumping stations in those cases for which these costs
are relevant.   This factor is a function of population,*
with values as follows:
     *  Although K! is a function of X2, C is also a vari-
     able so that capital cost is really a function of flow
     and organic load.  The expression for capital cost in
     terms of X± and X2 is used because that is the form
     most often found in the literature on cost functions.
     See, for example, Shah, Kanti and George Reid, "Tech-
     niques for Estimating Construction Costs of Waste
     Treatment Plants," J. Water Pollution Control Federation,
     42, No.  5, Part 1, May, 1970.

        For a discussion of Ibs of BOD5 per capita per day,
     that might be expected in municipal waste, see Fair
     and Geyer, op. cit., pp. 262-264.
     *  Michel, Robert L., "Factors Affecting Construction
     Costs of Municipal Sewer Projects," draft report,
     Federal Water Quality Administration, August, 1970.

                            80

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        Table 10.  PARAMETERS OF O&M COST FUNCTIONS

                                  Biological Treatment
                                   13.

                                   042

                                   022
_

876

650
     Type

Activated Sludge

Filtration

Sludge Handling:
  Sludge Pump

  Sludge Digester

  Sludge Holding Tank

  Vacuum Filtration

  Incineration
Coagulation and
Sedimentation

Filtration

Carbon Adsorption
  X  < 10 mgd
   j •"•

  X3 > 10 mgd

Chlorination

Sludge Handling:
  (as above)

Note;  Secondary biological treatment is defined as activa-
ted sludge + sludge handling.  Upgrading is defined as the
addition of filtration.
.0021
.0095
.0015
.063
.0089
Physical/Chemical
.0147
.0136
.1058
.0502
.0043
.452
.712
.530
.706
.570
Treatment
.986
.638
.483
.808
.905
                            81

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      Table 11.  PARAMETERS OF CAPITAL COST FUNCTIONS

                                  Biological Treatment

     Type

Activated Sludge

Filtration

Sludge Handling:

  Sludge Pump

  Sludge Digester

  Sludge Holding Tank

  Vacuum Filtration

  Incineration
Coagulation and
Sedimentation

Filtration

Carbon Adsorption

  X2 <_ 10 mgd

  X2 > 10 mgd

Chlorination

Sludge Handling:
  (as above)

Note:  Secondary biological treatment is defined as activa-
ted sludge + sludge handling.  Upgrading is defined as the
addition of filtration.
.00812
.122
.0125
.0575
.0224
.326
.0150
.461
0
0
0
0
0
0
Physical/Chemical
.067
.122
.546
.293
.0202
0
0
0
0
0
.262
.656
.480
.650
.590
.540
.560
Treatment
.890
.656
.613
.983
.664
                            82

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         500   but  >       0    f =  0.373
         999            500        0.384
       2,499            999        0.498
       4,999          2,499        0.722
       9,999          4,999        0.790
      24,999          9,999        1.060
      49,999         24,999        1.487
      99,999         49,999        1.533
    249,999         99,999        1.763
    250,000                      2.473
The parameters of the cost functions are taken from the
literature and are either standard engineering estimates*
or results of statistical analyses of survey-obtained data."1"
In all cases, the costs given by these parameters and func-
tional forms are not exact, but are mean estimates.  For
example, cost functions resulting from regression analyses,
as in the work of Shah and Reid, have associated with them
some standard error of estimate; that is, only part of the
variation in costs over the sample analyzed can be ex-
plained by the function at hand.  The rest of the variation
is stochastic in nature.  These functions do, however, give
reasonably good estimates of cost (i.e., they are not wrong
by an order of magnitude) and are adequate when comparing
different timestreams of costs, treatment level, and timing.

The computer program for this model runs in interactive mode
and accepts as input data the following quantities:

1.  per capita flow (gpcd);

2.  BOD concentration (mg/&);

3.  initial population (1,000's of persons);

4.  length of planning periods 1,  2,  3;

5.  annual population growth rate  (percent);
     *  Shah and Reid, op. cit.

     +  Black and Veatch, "Estimating Costs and Manpower
     Requirements for Conventional Wastewater-Treatment
     Facilities," for Environmental Protection Agency,
     Project No. 17090 DAN, October, 1971.

                            83

-------
 6.  industrial share (percent);

 7.  whether biological or physical/chemical treatment and
     ancillary works required or not;

 8.  payment period (years);

 9.  federal capital grant (percent);

10.  federal operation and maintenance grant (percent);

11.  discount rate (percent);

12.  existing capacity (1,000's of persons);

13.  different inflation rate  (if costs of wastewater
     treatment facilities are expected to increase at a
     different rate than the national rate of inflation)
     (percent);

14.  interest rate; and

15.  whether grant is given for designs based on existing
     or projected populations.

 Output can be displayed for the following items, for any or
 all branches of the decision tree, using the local, federal
 or total share of costs:

 1.  capital cost;

 2.  per capita capital cost  (three periods);

 3.  operation and maintenance timestream;

 4.  per capita operation and maintenance timestream;

 5.  capital + operation and maintenance timestream;

 6.  per capita capital + operation and maintenance timestream;

 7.  per capita capital timestream;

 or the present value of any of these items.

 A precis of the important steps the program takes is as
 follows:

                             84

-------
 1.   Populations are calculated,  using the  initial  popula-
     tion and the growth rate.

 2.   The capital cost is calculated  for each  branch of the
     decision tree.

 3.   An equal-payment timestream  of  capital costs is calcu-
     lated using the interest rate.

 4.   An operation and maintenance timestream  is  calculated
     using the population  in each year.

 5.   The user then selects what he wishes displayed.   If he
     wants subsidized costs, the  subsidy is calcula :ed and
     subtracted from the cost.  If he  wants the  present
     value,  the timestream is summed using  the discount rate.
     If he wants municipal or industrial shares, these are
     broken out.   If he  wants per capita costs,  the costs
     are divided by  the  appropriate population figure.

 This cycle is  repeated  each time the  user  gives a  new set
 of parameters.   An  example of the calculation the  model
 performs  is  presented in Appendix F.

 Since  the  model has  no  explicit  normative  structure,  the
 user must  select a  treatment option based  on alternative
 criteria  —  minimum total cost,  or minimum local cost, for
 example.   The  discussion below examines the implications  of
 these  alternative criteria for particular  representative
 cities.   In  most of  the examples  discussed, comparisons are
 shown  for  the  selection of the option based on minimum
 present value  of total resource  costs  (the socially least-
 costly option  to meet the mandated control level).

 Unless otherwise noted, it is assumed in each of the  cases
 discussed that each  community finances  its capital expen-
 diture with  a  30 year equal payment scheme based on capital
borrowing at 6 percent interest  and that the present  values
of resource  costs are calculated on a discount rate of 7
percent reflecting the Water Resources Council guidelines
as adopted by EPA regulations.*


     *  Federal Register, Vol.  38, No.  174, Monday, Septem-
     ber 10, 1973, "Title 40—Protection of the Environment,
     Chapter 1—Environmental Protection Agency, Subchapter
     D--Grants, Part 35—State  and Local Assistance, Appen-
     dix A—Cost Effectiveness  Analysis,"  pp. 24639-24640
     Section (f)(5).
                            85

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REVIEW OF ASSUMPTIONS

It is useful at this point, prior to discussing results of
the simulation model analysis, to review the important
assumptions in the model and its analytical framework.

Some of these assumptions have been explicitly stated earl-
ier in this report, others are implicit in the model
structure and cost of treatment functions utilized.

The most important assumption stated a number of times in
this report is that the municipality must select a particu-
lar treatment option.  A no-treatment or significant-delay
option is not included.  Another assumption is the limita-
tion of treatment options to the discrete number considered
rather than a series of options.  However, the option with
capacity based on 10 year increments and a range of treat-
ment levels does bound the range of options.

There are a number of assumptions implicit in the model
structure and the cost functions employed.  First, it is
assumed that selection is primarily between mode and degree
of treatment, i.e., physical/chemical vs. biological,
secondary vs. best-practicable.  For a given mode and
treatment level, there is a single point production function
and cost functions are dependent on scale.  Thus, the rela-
tive ratio of capital to O&M costs to achieve a given
treatment level cannot really be varied except by changing
treatment modes, i.e., using physical/chemical rather than
biological.  The only qualifier results from the fact that
unit operating costs are a function of treatment plant  size,
hence the operating  costs  of a plant with excess capacity
has slightly different operating expenses than one operating
at capacity.

Although it  is known that  tradeoff between  capital and  O&M
is possible, there  is no basis  in the professional litera-
ture  for estimating  such production  functions  that could
have been utilized  in this analysis.

The limitation of  then comparing only between  treatment
needs to examine  relative  capital vs. O&M resources  used is
further  constrained  by the paucity  of generalized  developed
cost  literature on  physical/chemical and  land  treatment
options.  The  limited generalized cost  literature  on physi-
cal/chemical indicates that  it  is universally  dominated by
biological  and there is no generalized  cost literature on
land  treatment.
                             86

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There are unquestionably specific cases in which physical/
chemical or land treatment would dominate biological options,
but at this writing the technological relationships and cost
functions are not available to provide the type of comparison
that would be useful.

RESULTS

Table 12 shows the present value (PV) of local costs of the
four least costly treatment options for case 1A (see Table
8).   In this case the small federal share of total present
value of treatment costs is noteworthy.  For a city of
25,000 and a 1 percent growth rate, no ancillary costs and
no industrial load, the PV at 7 percent discount rate of
total costs is given in Table 13 to be $6.617 million.
This is the minimum total cost represented by option 12.
In this case the model calculations show that the PV of
capital costs is 37 percent of this $6.617 million.  Local
costs with a 75 percent construction grant are $4.772
million (see Table 12).  Thus, federal aid is only 28
percent of. total costs.*

It is interesting to consider the implications of choosing
one of the other options.  Option 11, building 30 years of
secondary capacity initially, would be more attractive from
a local point of view under a choice criteria of minimizing
administrative burden since it provides more initial capa-
city and necessitates only one upgrading.  The local
administrative burden, in terms of the frequency of under-
taking the planning grant application, construction and
bond issuance, is less than that of option 12.  At the 7
percent discount rate the PV of local costs for these
options is the same.  At the higher  (10 percent) discount
rate the PV local cost for a lesser administrative cost is
an extra $0.15 million ($3.688 -x $3.673).  The national
efficiency losses associated with such a difference are
small ($.002 million at 7 percent, $.07 million at 10 per-
cent) the capital requirements of an extra 10 years of
initial capacity are significant.  Consequently, if federal
budget limitations constrain the r.ate of facility construc-
tion, such an additional requirement for grant monies can
        6.617 - 4.772  =   Q  m
            6.617         1UU
                             87

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             Table 12.   PRESENT  VALUE OF LOCAL  COSTS FOR CITY  OF 25,000
                 WITH 1%  GROWTH RATE, NO  ANCILLARY COSTS,  NO INDUSTRY
                   AND NO EXISTING UPGRADABLE TREATMENT  CAPACITY
                            (DISCOUNT RATES OF 7% AND 10%)
                                                The  Four Least Costly Options $X10

Grant
50% Capital
75% Capital (present
program)
50% Capital; 25% O&M
50% Capital; 50% O&M
7% Discount Rate Option
12 11 , 10 15
5.387
4.772
4.347
3.308
5.388
4.772
4.349
3.310
5.391
4.774
4.352
3.313
5.456
4.806
4.416
3.377
10% Discount Rate Option
12 11 10 15
4.248
3.673
3.474
2.699
4.279
3.688
3.504
2.730
4.280
3.689
3.506
2.731
4.286
3.692
3.511
2.737
00
00
     Options;
         12
11
10
         Decision 1

       Build secondary
       for P,
                Build secondary
                for P
                Build secondary
                for P3
   Decision  2

Upgrade to best-prac-
ticable for  P_

Upgrade to best-prac-
ticable for  P3

Upgrade to best-prac-
ticable for  P~
   Decision 3

Build best-practicable
for AP32
Upgrade to best-practicable
                                                      for AP
                                                           32
         15     Build secondary
                for P
                              Upgrade to best-practi-
                              cable for PI and build
                              best-practicable for

                              AP32
Build best-practicable for

AP32

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                             Table  13.   PRESENT VALUE OF TOTAL COSTS,
                              CITIES  WITH  1%  GROWTH RATE, NO  INDUSTRY
                               7% Discount Pate
                                                        10% Discount Rate
   Population/Option
     12
11
                             10
    15
                                  12
                                                               11
                                                                          10
                                                                     15
    25 Thousand
6.617*
              6.6
                                      10.281
        6.62
                             0.299
 6.75J
                                                                          8.820
                                                                                  5.46C
                                                                8.973
                                                                        5.462
                                                          8.979
                                                                                                            9.007
    75 Thousand
L4.645,
     2.452
                                      27.487
        14.67
                                                                     11.89^
                       12.02
                             2.523
                                                                         L9.198
                                                     12.032
                                                                9.537
                                                         L9.549
                                                                                 12.03
                                                                                                            9.565
   250 Thousand
                          3.708
                 63.886
       35.60)
           '63.995
36.09;
   "€5.721
                                               28.69;
                                                  "55.081
                                                                                 29.00
                                                                                     i6.182
           29.01
               "56.217
            28.99;
               '56.129
   500 Thousand
00
vo
                       .,0.
             59.67f
                [04.917
       59.71
                                   60.475
            5.090
      .697
           47.97
                                                    0.130
48.50J
   '91.924
48.49
   ^1.979
48.43;
   "91.719
                     *    Without ancillary costs

                     **   With ancillary costs
                     Note:  The relative ranking of options remains the same  for each
                     of these populations for local PV based on the grants  shown in
                     Table 12.

-------
have important national implications for the rate of water
pollution control.  The primary implication is for much
larger initial costs and higher budget requirements in the
early years of the program or, alternatively, greater
delays in the early program years if a limited budget covers
fewer municipal requirements.

Table 12 presents the present value of local costs for the
four least-cost  (PV) decision options.  The costs are for a
small city with low growth rate, no ancillary costs and no
industry.  The PV ranking, based on local costs, is the same
ranking as that based on total costs as shown in Table 13.
Table 13 indicates that this relative ranking of treatment
options by PV of total costs is maintained for other city
sizes whether or not there are ancillary costs, or a low
growth rate and no significant industrial load.  The rank-
ing in Table 13 is preserved for PV of local costs under
the financing options shown in Table 12.  For a given
financing program, the difference in PV, either local or
national, between the more attractive options is small.
Thus, the PV associated with the selection of the more
costly option is itself hardly significant, but again the
implications for the short-term federal budget can be signi-
ficant.

Continuing the earlier discussion, it is useful to consider
some implications of municipal selection of option 11 based
on local administrative criteria.  For the cases presented
in Table 13 without  ancillary requirements, the efficiency
losses as measured in the PV of total costs at 7 percent
range from $.002 million for the 25,000 population case
discussed above to $.099 Billion for the city of 500,000
population.  The efficiency losses may be considered insig-
nificant.  The difference in initial capital requirement,
however, ranges  from $.15 to $1.1 million and 75 percent  of
this would represent additional federal budgetary require-
ments being incurred earlier in the program rather than
later.

Table 14 shows that for populations from 25,000 to 500,000
having high growth rates, option 12 has the least PV of
total and local costs at the lower discount rate, while
option 15 has the least PV at the higher discount rate.

At the lower discount rate the ranking after option 12
changes for cities with high growth rates  (Table 14) rela-
tive to those with lower growth rates  (Tables 12 and 13) .
The rankings in Table 14 are maintained when based on

                            90

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                               Table  14.   PRESENT VALUE OF TOTAL  COSTS
                               CITIES WITH  5%  GROWTH  RATE AND  NO  INDUSTRY
                              7%  Discount Rate
                                                            10% Discount Rate
Population/Option
    •
     12
    15
                             18
                                                           .(1)
               15
                                                               12
                                                             18
 25 Thousand
10.527V
             10.63
                                               L8.132
                       11.06
                                                    L4.056
                                                             14.819
                                                                                       4.790
 75 Thousand
23.265
23.4°
                                   39.315
                         23.93;
                            '40.645
24.36J
   "39.923
                                                                  17.94
                                                               31.534
                                                         18.61'
                                                             "S3.031
                            2.638
250 Thousand
56.305,
    09.163
56.6
                         57.78,
                                   10.369
                4.29
                                                                             43.
                                                               91.054
                                                                                       2.582
500 Thousand
94.305,
  J.78.929
94.78;
    .80.612
                         96.63
           71.9
                                                                      44.458
73.22;
   .48.775
                  *    Without ancillary costs

                  **   With ancillary costs
                  Note:   The relative ranking of options remains the same  for each of these
                  populations for local PV based on the grants shown in Table 12.
                  (1)   Notice  the reversal of 18 and 2 at 75,000, 250,000 population with
                  ancillary costs.
                  <2)   For 500,000 populatidn With ancillary costs,  branch 2 is ranked 3
                  and  branch 5 is ranked 4.

-------
local cost present values for any of the grant programs
presented in Table 12.

Tables 12 through 14 indicate the ranking of options
based on PV of either local or total costs is quite stable
for the four financing alternatives and two discount rates
presented.  This stability of ranking breaks down at
higher discount rates.  Under the present value criterion,
this would suggest building less capacity initially.  These
tables also indicate that for particular municipal cases,
the PV difference between options is usually quite small.

These overall results are not terribly startling.  The
options are from the same treatment mode — biological
the options differ primarily in capacity and treatment
level timing selection.  The relative percentages of the
capital and O&M cost stream of the different options are
quite close; hence, under the present value criteria these
financing alternatives impact the cost stream  to nearly the
same degree.

Figures 3(a) through  3(f) present the local peL capita cost
streams for a number  of  cases defined in Table 8 under
the alternative levels of federal financing.   These cost
streams are based on  the assumption  that municipalities
select the treatment  option that minimizes  the present
value of  local costs.  For the options  considered  and  the
discount  rate used  (7 percent),  this option (option 12   is
also the  option with  the minimum present value of  total
cost.

The per  capita costs  vary considerably  under  any of the
financing programs  discussed  thus  far  in  this  section.
Similar  variation  in  per capita  costs  can  be  observed  under
different assumptions of local  selection  criteria.   If,  for
example,  the  cities select option  11,  which implies a  lower
administrative burden,  then  the  per capita timestream  of
costs  demonstrates  the  same  relative variation.

The  cases presented in these figures are  representative  of
the  range of  results  of the  analysis.   Other cases from
Table  8  would generally lie  within the band represented
by the cases  in  these figures.

Figure 3(a)  shows  that,  with no grant, per capita costs can
easily differ by as much as  a factor of four between commu-
nities representative of large numbers of real, communities.


                             92

-------
  30
  20
_

§10
  1   20
                          •--5
            J	I	I    .    I
    0       10      20
              YEARS
    (a)  0%  capital,  0%  08M
     10
30    0

        10       20
          YEARS
(b) 75% capital,  0% 0 8M
30


           10      20

              YEARS
    t c)  50 % capital,  0% 0 8 M
30

                  YEARS
      (d) 50% capital, 25% 0 a M
  Figure  3  Per capita municipal cost for  biological  treatment
            branch 12,  with various  grant levels
            (	25,000;	500,000)
                             93

-------
20
(O
on
<
_J
_J
O in
0 IU



— 20


IU

^
I 1 " I L 	 ~~'f o
—


~ ^«» ** ,5
•^a _ /
---=— 	 -=*~-^ss'
-,- r- , -—7—1*
        10      20      30

(e) 75% capital, 25% 08 M
30
        10      20
          YEARS
(f)  50% copital,  50% 08M
Figure 3   (cont.)
                       94

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The existing program  [Figure 3(b)], although decreasing ,
the absolute per capita costs, does not markedly change the
variation in costs among communities and thus does little
to diminish this inequity.  A 75 percent capital, 25 percent
operation and maintenance grant program  [Figure 3(e)] nar-
rows the spread in per capita costs, but there can still be
a factor in excess of two between per capita costs borne by
different cities.

The growth rates and population/industrial share depicted
in Figure 3 represent the majority of the population/
growth rate classes and population/industrial share classes
identified in the classification analysis  (see Tables 5
and 37).   Figure 4 emphasizes the variation in per
capita costs for cities of 75,000 with different growth
rates and industrial loads.  As in Figure 3 the cost
streams presented are for the least present value options
only; examples for both biological  (cases C) and physical/
chemical (cases E) are presented.  In the biological cases
option 12 is the least cost while in the physical/chemical
cases option 2 or 5 is the least cost option.

Figures 5 and 6 provide further emphasis of these
points.  In both figures the first year per capita costs
(for option 12) are shown for a range of capital and operat-
ing cost grant levels.  Figure 5 considers a city of
75,000 population and shows the impact of growth rate, in-
dustrial load and ancillary costs on per capita costs.  The
presence of significant industrial load decreases per capita
costs.  The decrease results from the lower marginal costs
associated with a larger treatment plant  (economies of
scale) which treats both domestic and industrial waste load.
Since it is assumed that industry shares cost in proportion
to its share of the flow, the municipal costs share is
lower than the total costs without industry.  Hence, costs
per capita are also lower.  In other case comparisons the
presence of ancillary needs — interceptor and pumping
stations in addition to treatment works -- increase total
costs and hence per capita costs.

Figure 6 presents first year per capita costs for small
(25,000 population)  and large (500,000 population) communi-
ties with a variety of characteristics.  The variation in
per capita costs is even more dramatic than in Figure 5.
                             95

-------
                           YEARS
             (a)  Case E:  physical chemical treatment
                                                        30
  30r—
CO
a:
  biological and physical/chemical
                 treatment

 Figure  4  Per capita municipal  cost  with no grants  and
           75,000 initial population
                             96

-------
I5r—
                % capital grant
            (a)  0% 0&M grant
                             5C
                                15
               25
          %OaM grant
       (b)  50% capital grant
50   0
                                               1
                                                  25
                                               %  OSM grant
                                         (c)  75%capital grant
Rgure 5  Rrst year per capita municipal cost  as  a function of grant
         levels (Case C-- city of 75,000 with biological treatment)
50
                             97

-------
30
25
20
 15
 10
  0
 Fig 6
                1
                      1
        25
         % capital grant
        (a) 0% GSM grant

First year per capita municipal cost as a
function  of grant levels (Cases  A & Dt
cities of 25,000 and 500,000 with
biological treatment)
                        98

-------
  201^
   15
C/5

5  10
o
Q
20
     0          25        50

            % of 0 & M grant

        (b)  50% capital grant


     Figure 6    (cont.)
 15
 10
                                                            4D
   0                    25
        %of oaM grant

     (c)  75% capital grant
                               99

-------
The locally-borne per capita costs range — for the cases
shown, and for the present grant program — from less than
$5 per capita/year to over $25.  The addition of an opera-
tion and maintenance grant reduces the variation in per
capita costs, but significant variation still exists.

Financing programs which only subsidize the requirements of
existing populations further exacerbate variations in per
capita costs.  In general, cities with higher growth rates
are more seriously affected.  Figure 7 presents the dif-
ference in per capita costs for a few cases in which the
present 75 percent capital grant is compared with a grant
program that funds only that capacity needed by the exist-
ing population.  The cases selected do not represent
extreme situations, but nonetheless the impacts are signi-
ficant.  Such a grant limitation increases already high per
capita costs for case 1A, a city of 25,000 population, with
no ancillary costs, a 1 percent growth rate, and no indus-
try.  Case 4D, a large city of 500,000 population, again
with no ancillary costs, but this time with a high growth
rate, has per capita costs that almost double under this
financial program.  The impact of this curtailed grant pro-
gram on a small city (25,000 population) with no industry
and a high growth rate  (5 percent) but no ancillary costs,
is to increase annual per capita costs by over 20 percent --
as presented in Figure 7.

Figure 8 presents the first year per capita debt for some
of the cases examined above.  As expected, as the capital
grant increases, the per capita debt decreases.  In the
range of 50-75 percent there is still, however, a large
spread in the implicit per capita debt ranging from less
than $20 per capita to over $100.  The impact for some
communities can be significant.

A NATIONAL OPERATION AND MAINTENANCE GRANT ANALYSIS

In this section the federal cost of an operation and main-
tenance grant program is discussed.  The 1973 Survey of
Needs data base is used in this analysis.  The computation
of the cost of an O&M program is straightforward.  However,
there are some problems due to the fact that not all the
records are complete.

To compute the costs of an O&M program, functions are
developed which relate the O&M costs for a facility to the
                            100

-------
  20
GC
O 10
Q

                     10
                            YEARS
20
30
     Figure 7  Per capita municipal cost for grant based  on
              existing  population (—) and grant based  on
              projected population (	)  (75%capital and
              0% OSM)
                           101

-------
                25
       50
% capital grant
75
100
Figure 8  First year per capita municipal debt as a function of
         capital  grant (0% 0 SM  grant)
                          102

-------
state's capital cost estimates for that facility.  Expres-
sions that define annual operation and maintenance costs
for various types of treatment plants or unit processes as
functions of estimated capital costs are obtained by assum-
ing that, for a given process, the capital and operation
and maintenance cost functions are of forms similar to
those in the previous section:
                  o
     C, .  =  a, . X lj
             a
             a2j
where
     C    =  capital cost in $ x 106 for a treatment plant
             or unit process type j;

     C    =  annual operation and maintenance costs in
       3     $ x 106;

     X    =  flow in mgd;

and the ot's and B's are parameters.  The parameters are
obtained as explained before.  From these one obtains
the function relating O&M cost to capital cost the expres-
sion:
                                            /\
An operation and maintenance cost estimate, C2j  for each
treatment facility can then be obtained by using the capi-
tal cost estimate, GIJ  as the argument in this equation.
The individual facility costs can then be summed on a state,
regional or national basis.

To compensate for incomplete data, a chain of default data
is used which enables us to utilize the available data to
the greatest possible extent.  As the items crucial to the
analysis were the capital cost of the facility and its BOD
removal level, each facility record was subjected to the
following processing:
                            103

-------
a.  If no capital cost was given, the record was not used.

b.  If capital cost was given, but no BOD removal level was
    given (i.e., one or both of the figures for influent
    and effluent BOD levels was absent), a figure of 170
    mg/£ (85 percent removal of 200 mg/£ influent) was
    assumed for the BOD removal level.

c.  If a flow figure was given, it was then used to calcu-
    late the total BOD removal.

d.  If no flow figure was given, an attempt was made to
    calculate one from the 1970 population.

      i.  If no 1970 population was given, the record was
          not used.

     ii.  If a 1970 population was given, a 1990 design
          population was calculated from it using a 2
          percent growth rate.

    iii.  Tjje flow was then calculated from the 1990 popu-
          lation assuming a per capita flow of 120 gpcd.

Table 15 presents estimates for each state for annual
operation and maintenance costs.  For the records used the
total .of the states' estimates is $3.02 billion.  These
results show that a 25 percent operation and maintenance
grant would cost approximately $.75 billion per year for
the proposed new plants and additions to existing plants
required to meet the legislative mandate.  This estimate  is
probably somewhat low since all of the records for each
state's new facilities were not usable in computing the
$3.02 billion estimate.*

Estimates of the cost of providing operation and maintenance
grants to existing facilities were made by first determining
the replacement value of existing facilities.
     *  In Table 15,  the column  labeled  "Percent  Used"
     shows that 57.3 percent of all  the treatment  facili-
     ties records were used.  The figure  is based  upon a
     ratio of new facilities records which were  usable to
     all of the treatment facilities records  contained in
     the needs survey.
                             104

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Table 15.  COSTS OF OPERATION AND MAINTENANCE GRANT PROGRAM


Region
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
District of
Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
No.
4
10
9
6
9
8
1
3

3
4
4
9
10
5
5
7
7
4
6
1
3
1
5
5
4
7
8
O&M
Cost
($X106)
12.34
18.58
15.81
6.71
385.56
29.07
52.89
16.48

6.27
141.87
30.47
40.76
4.26
150.97
39.84
34.54
15.32
35.30
6.95
16.72
78.08
74.02
103.39
69.94
8.09
75.49
6.39
Treatment
Facility
Records
202
71
140
119
654
173
123
25

2
229
349
49
59
596
236
314
162
124
214
142
80
85
223
234
93
263
63

Records
Used
135
60
71
115
353
117
33
16

1
110
210
30
34
359
148
261
126
76
130
88
40
38
109
115
73
151
30

Percent
Used
66.8
84.5
50.7
96.6
54.0
67.6
26.8
64.0

50.0
48.0
60.2
61.2
57.6
60.2
62.7
83.1
77.8
61.3
60.7
62.0
50.0
44.7
48.9
49.1
78.5
57.4
47.6
                              105

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Table 15.   (continued)
O&M
Region Cost
State No. ($X10 )
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Wake Island
American Samoa
Guam
Puerto Rico
Trust Terr.
Virgin Islands

7
9
1
2
6
2
4
8
5
6
10
3
1
4
8
4
6
8
1
3
10
3
5
8
9
9
9
2
9
2

22.38
24.28
45.78
335.48
5.68
300.23
35.89
0.42
197.09
14.98
19.87
150.83
13.57
29.27
3.19
41.97
40.60
18.76
6.86
98.14
56.98
11.61
42.27
0.83
	
0.35
1.85
22.88
0.21
1.29
3,019.65

Treatment
Facility
Records
148
44
91
248
40
647
182
95
502
202
87
726
25
382
113
140
683
107
105
638
105
401
186
36
0
3
7
45
8
4
11,024
106
Records
Used
115
20
79
123
23
273
122
54
295
181
6
430
17
249
53
70
294
72
71
200
68
310
79
34
0
3
6
36
0
4
6,316

Percent
used
77.7
45.5
86.8
49.6
57.5
42.2
67.0
56.8
58.8
89.6
6.9
59.2
68.0
65.2
46.9
50.0
43.0
67.3
67.6
31.3
64.8
77.3
42.5
94.4
0.0
100.0
85.7
80.0
0.0
100.0
57.3


-------
in the 1972 Economics of Clean Water a replacement value of
$18.87 billion (1971 dollars)  is reported based upon
records for 12,380 facilities.*  To be comparable with the
1973 dollars used in this report, the figure is approximately
$21.42 billion.  In an analysis of the usable records on
existing facilities (7,498) in the 1973 Survey of Needs an
estimate of $11.69 billion (1973 dollars) was obtained.
Multiplying $11.69 by the ratio of the number of records
used in the 1971 estimate  (12,320) to the number of records
used in 1973  (7,498) this figure becomes $19.7 billion,  it
is reasonable to assume then that those existing facilities
in the country for which information is available have a
replacement value of approximately $20 billion.

Next the works of Smith and of Black and Veatch were re-
viewed *   Estimates of the ratio  of annual operating and
maintenance costs to capital costs were  found  to vary  from
0.06 to over  0.15,  depending on  treatment
  .             .,
 scale.   Reasoning that  current  operation  and
 costs  are  rising more rapidly than  capital  costs,  it  has
 been assumed  that the appropriate ratio to  use  is  o.i^.

 Thus,  using a replacement value of  $20 billion  and annual
 O&M to capital cost ratio of 0.12,  we f11^^ *  ?^sts
 program providing  funds for 25  percent of ^e annual  costs
 would  require $0.6  billion.  The total cost of  a 25 percent
 O&M grant  program,  for  new and  existing  facilities, is
 therefore  estimated to  be $1.35 billion.

 There  are  several  qualifications which must be placed on
 this  estimate:

 a.  there may be double counting in that some of the new
     facilities will be replacing existing facilities,
      *  Economics of Clean Water, Vol. I, 1972, p. 120

      +  Municipal Waste Treatment Facilities Evaluation
      Model, Meta Systems Inc., 1974, p.  8.

      *  Smith, R. ,  "Cost of Conventional and Advanced Treat-
      ment of Was^water ," J. Water Pollution Control Federa-
      SS,  September,  1968, pp.  1546-lb74;  and Black and
      Veatch, op.  cit.
                             107

-------
b.  the replacement value underestimates the total replace-
    ment value of facilities since records on all facilities
    are not available; and

c.  there is reason to believe that the figures on the 1973
    Survey of Needs (capital cost figures) and used herein
    to estimate O&M costs, are substantially overstated.

Finally, it should be pointed out that the cost estimates
are for treatment only and not for the maintenance of
collection systems.

CONCLUSIONS

The current federal program of 75 percent construction
grants results in only a modest  federal contribution to the
total municipal water pollution  control costs mandated by
the 1972 Amendments:  less than  25 percent of total costs
for large numbers of  communities.

The community characteristics of population, growth rate,
fiscal situation, wastewater system characteristics, indus-
trial share of wastewater  load and family income  structure
exhibit wide variations  across the nation and along with
varying ancillary needs  imply large differences  in per
capita costs borne  by communities under the  existing  federal
construction grants program.  For example,  the results  of
contingency table  analysis of population  and industrial flow
data  taken  from  the 1973 Survey  of Needs  demonstrate  a  clear
relationship between  community  size and percentage of  indus-
trial flow.  More  importantly,  the analysis  shows that  the
percentage  of  industrial flow is distributed bimodally  with
community  size.  What that means is that  many  communities
of a  given  size  have  very low industrial  flows and many
have  high  industrial  flows.  We  can expect,  then, that a
 large number  of  municipalities  with rather  similar charac-
 teristics  (except  for the presence of industrial flow)  will
have  rather different per capita costs.   Therefore in order
 to alleviate  inequitable per capita  costs burdens,  indus-
 trial flow and other  community  characteristics should be
 included in the  grant formula.

 The alternative  of a  construction grant program that re-
 stricts  the size of treatment facilities to meet only
existing population makes more  severe the variation in per
 capita costs  across communities and results in a less
 efficient utilization of resources.


                             108

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The equity arguments in favor of a 75 percent construction
grant mitigate against any reduction in the grant percent,
especially considering the modest federal contribution to
the total cost to municipalities of nationally-mandated
water pollution control unless such a reduction is coupled
with an operation and maintenance grant.  But even the
inclusion of a significant operation and maintenance grant
percentage does not eliminate the extreme variation of cost
burden.

This situation of serious differences in per capita costs
may be aggravated by the distribution of family income and
the serious differences in communities' ability to finance
these costs.   (See tables in Appendix E.)  Focusing on the
family income question, we have seen that the range of
median family income is not insignificant across municipali-
ties of a given size.  If it can be assumed that family
income and the presence of industry are independent, then
there will be a fair number of poorer communities with
higher per capita costs being paid by a population that
contains a large number of poor families.  If the presence
of industry and family income are correlated positively,
then the situation is worse; while if they are correlated
negatively, this effect is reduced somewhat.

The potential implications for some income classes also
can be quite significant, again for those cases that under
the financing programs presented in Figures 4 to 5
result in first year per capita costs of $10-20.  If these
costs were paid through user charges, there could be
extreme group distribution impacts.  A $10-20/year per capita
user charge (nearly equivalent to a head tax non-deductible
from federal income .taxes)  is a strongly regressive mechan-
ism.  Property taxes to finance this $10-20 may be less
regressive in impact, but are beyond analysis of this study.
Mechanisms are necessary to eliminate such potential regres-
sive impacts.   But more analysis is needed.

The analysis furthermore indicates that there are substan-
tial differences in communities' abilities to finance these
costs, i.e., revenue capacities of communities are drasti-
cally different as shown in Table 34.

The implication is that the local burden of federal require-
ments for waste treatment (the local cost per dollar of
revenue capacity)  varies significantly.  As a consequence,
                            109

-------
we  think  the  highest priority  should be  given  to  the
development of new policy  tools  that permit  restructuring
of  the grant  program such  that the burden  on communities
becomes less  inequitable.  This  may be accomplished through
a grant formula that reflects  both differences  in costs to
communities and differences  in communities'  abilities to
finance those costs, i.e., differences in  communities'
revenue capacity.

Current practice for federal programs that attempt to
reflect differences in community revenue capacity is to use
personal  income as a measure of  revenue  capacity.  Although
we  are familiar with the theoretical and practical diffi-
culties of use of income as a  measure of revenue  capacity,*
we  believe that it should be possible to derive a meaningful
and useful grant formula based upon income as a measure of
community revenue capacity with  the possibility of modifi-
cation depending on large differences in local wealth
(assessed valuation of property), tourism, and revenues de-
rived from exploitation of mineral resources.

Hence, there  is a need on equity grounds for a new complex
grant formula.  The grant formula design might include
several components.   Per capita  financial burdens across
municipalities should be made more nearly equal with provi-
sions in the  formula to account  for the cost effects of a
municipality's population size, growth rate, income struc-
ture, percentage of industrial flow and the need  to build
ancillary facilities.   Special compensating provisions
should be made to municipalities  to reflect the cost impact
on  low income groups.
     *   Advisory Commission on Intergovernmental Relations,
     "Measuring  the Fiscal Capacity and Effort of State and
     Local  Areas,"  Washington, D.C.,  Government Printing
     Office, March, 1971.
                            110

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                        SECTION 5

                       BIBLIOGRAPHY
1.   Advisory Commission on Intergovernmental Relations,
"Measuring the Fiscal Capacity and Effort of State and
Local Areas," Washington, D.C., Government Printing Office,
March 1971.

2.   Advisory Commission on Intergovernmental Relations,
"State-Local Finances and Suggested Legislation," Washing-
ton, D.C., Government Printing Office, 1971.

3.   Ardis, C. V., K. J. Dueker and A. T. Lenz, "Storm
Drainage Practices of Thirty-two Cities," Journal of
Hydraulics Division  (ASCE), 95_, (HY1), (1969), pp. 383-408.

4.   Arrow, K. J., "A Utilitarian Approach to the Concept
of Equality in Public Expenditures," Quarterly Journal of
Economics, Vol. 58:3 (August 1971), pp. 409-415.

5.   Bahl, R. W.  and R. J. Saunders,  "Factors Associated
with Variations in State and Local Government Spending,"
Journal of Finance, Vol. 21 (September 1966), pp. 523-534.

6.   Barlow, R.,  "Efficiency Aspects of Local School
Finances," Journal of Political Economy, Vol. 78:5  (Sep./
Oct. 1970), pp. 1028-1039.

7.   Bergstrom, T.,  "A Note on Efficient Taxation," Journal
of Political Economy, Vol. 81:1 (Jan./Feb.  1973), pp. 187-191,

8.   Break, G.  F., Intergovernmental  Fiscal  Relations in the
United States,  Washington, D.C.:  Brookings,  1967.

9.   Buchanan,  J.  M. and C. J. Goetz,  "Efficiency Limits of
Fiscal Mobility:   An Assessment of  the Tiebout  Model,"
Journal of Public Economics,  Vol. 1  (April  1972).

10.  Congressional Research Service,  "Property  Taxation:
Aspects of Land Use  and  Local Government Revenues," for the
Subcommittee  on Intergovernmental Relations of  the  Senate
Committee  on  Government  Operations," Washington,  D.C.,
Government Printing  Office, February 24, 1971.

 11.  Crecine,  John P.,  "A Simulation of  Municipal Budgeting:
 The Impact of Problem  Environment," Ira  Sharkansky,  ed.,
 Policy Analysis in Political  Science.

                            Ill

-------
 12.  Edelson, N. M.,  "Efficiency Aspects of Local School
 Finance:  Comments and Extensions," Journal of Political
 Economy, Vol. 81:1 (Jan./Feb.  1973) , pp. 158-173.

 13.  Environmental Policy Division of the Congressional
 Research Service of the Library of Congress, "A Legisla-
 tive History of the Water Pollution Control Act Amendments
 of 1972 Together with a Section-by-section Index," Volumes
 1 and 2, Serial No. 93-1, Washington, D.C., Government
 Printing Office, 1973.

 14.  Feldstein, Martin, "Wealth Neutrality and Local Choice
 in Public Education," Harvard  Institute of Economic Research,
 Harvard University, Discussion Paper No. 293,  May 1973,
 revised July 1973.

 15.  Gramlich,  E.,  "Alternative Federal Policies for Stimu-
 lating State and Local  Expenditures:   A Comparison of Their
 Effects," National  Tax  Journal,  Vol.  21 (June  1968),  pp.  119-129.

 16.  Gramlich,  E. ,  "Effect of  Federal Grants on State-Local
 Expenditures:   A Review of the Econometric  Literature," Pro-
 ceedings of 62nd Annual Conference on Taxation,  National
 Tax Association,  1969.~~

 17.  Grubb,  W.  Norton,  "The Distribution of Costs and Bene-
 fits in an Urban Public School System,"  National Tax  Journal,
 2_4, 1 (March 1971) , pp. 1-12.	

 18.  Hartman, R.  w.,  "Higher Education Subsidies:   An Analysis
 of Selected  Programs  in Current  Legislation,"  The Economics of
 Federal Subsidy Programs,  Part 4,  Joint  Economic Committee,
 U.S.  Congress,  Washington,  D.C., Government Printing  Office,
 August  28,  1972.

 19.   Henderson, J. M.,  "Local  Government Expenditures:  A
 Social  Welfare  Analysis,"  Review of Economics  and Statistics,
 Vol.  50  (May 1968), pp. 156-163.	

 20.   Hirsch, W. Z., "Determinants of Public  Education
 Expenditures," National Tax Journal, Vol. 13 (March 1960),
 pp. 24-40.

 21.   Hirsch, W. Z., The Economics of State  and Local Govern-
ment, New York:  McGraw-Hill,   1970.

 22.  Hirsch, W. Z. and M.  Marcus, "Inter-community Spillovers
and the Provision of Public Education,"  Kyklos, Vol. 22:4  (1969).
                            112

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23.  Huiran, W. R., "Municipal Ownership of Individual Treat-
ment Systems, in Proceedings of Sewage Treatmen-L in Small
Towns and Rural Areas, (Conference at Dartmouth College,
March 1971) .

24.  Inman, R., "Towards an Econometric Model of Local
Budgeting," Proceedings of the 64th Annual Conference on
Taxation, National Tax Association, 1971.

25.  Johnson, J. A.,  "Economic Analysis of Sewer Service
Charge Formulas," Land Economics, No. 47, 1  (1971).

26.  Joint Economic Committee, U.S. Congress, "Revenue
Sharing and  Its Alternatives," Washington, D.C., Government
Printing  Office, July 1967.

27.  Mieszkowski, P., "Tax Incidence  Theory," Journal of
Economic  Literature,  1_, 4  (December 1969), pp.  1103-1124.

28.  Morss,  E.  R.,  "Some Thoughts  on  the  Determinants of
State  and Local  Expenditures," National Tax  Journal, Vol.
19 (March 1966),  pp.  95-103.

29.  Musgrave,  R. A.  and P.  B. Musgrave,  Public Finance in
Theory and Practice,  New York:   McGraw-Hill, 1973.

 30.  Mushkin,  S.  J.  and J.  F.  Cotton, Sharing Federal Funds
 for  State and Local Needs,  New York:   Praeger,  1969.

 31.  Mushkin,  S.  J.  and J.  F.  Cotton, Functional Federalism,
Washington, D.C.:  George  Washington University, 1968.

 32.  National Tax Journal,  "Symposium of Federal Fiscal Support
 for State and Local Governments,"  24, 2  (June 1971).

 33.   New Jersey Tax Policy Committee, "The Use and Costs of
 Public Credit," Part IV of the Report of the New Jersey Tax
 Policy Committee, Trenton, New Jersey, February 23, 1972.

 34.   Oates, W. E.,  Fiscal Federalism, New York:  Harcourt,
 Brace, Jovanovich, 1972.

 35.  O'Brien, T., "Grants-in-Aid:  Some  Further Answers,"
 National Tax Journal, Vol. 24 (March 1971) .

 36.  Osman, J. W., "The Dual Impact  of Federal Aid on  State
 and Local Government Expenditures,"  National Tax  Journal,
 Vol.  19  (December 1966) , pp. 362-372.

                             113

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37.  Public Interest Economics Center,  "Who Bears the Cost of
Pollution Control, The Impact on the Distribution of Income
of Financing Federally Required Pollution Control,"  report
prepared for the Council on Environmental Quality and the
U.S. Environmental Protection Agency, August 15,  1973.

38.  Raymond, Richard, "Impact of Federal Financing Provisions
in the Federal Water Pollution Control Act Amendments of 1972,"
unpublished manuscript, Center for Urban Regionalism, Kent
State University.

39.  Sacks, S. and R. Harris, "The Determinants of State and
Local Government Expenditures and Intergovernmental Flows of
Funds," National Tax Journal, Vol. 17 (March 1964), pp. 75-85.

40.  Scott, Claudia Devita, Forecasting Local Government
Spending, Washington, D.C.: The Urban Institute,  1972.

41.  Smith, David L. , "The Response of State and Local Govern-
ments to Federal Grants," National Tax Journal, 21, 3  (September
1968), pp. 349-357.

42.  Stern, D., "Effects of Alternative State Aid Formulas on
the Distribution of Public School Expenditures in Massachu-
setts," Review of Economics and Statistics, Vol.  55:11(Febru-
ary 1973), pp. 91-97.

43.  Tax Foundation, Inc., "The Federal Outlook for State and
Local Government 1980," Research Publication (New Series) No.  28,
1973.

44.  Tax Foundation, Inc., "Tax Burden and Benefits of Govern-
ment Expenditures by Income Class, 1961 and 1965," 1967.

45.  Tiebout, C. M., "A Pure Theory of Local Expenditures,"
Journal of Political Economy, Vol. 64 (October 1956).

46.  U.S. Bureau of  the Census,"Environmental Quality  Control,
Finances and Employment for Selected Large Governmental Units:
Fiscal 1970-71," GSS-No. 63, Washington, D.C., Government
Printing Office, 1972.

47.  U.S. Environmental Protection Agency, "Water Strategy
Paper, Second Edition, A Statement of Policy for Implementing
the Requirements of  the 1972 Federal Water Pollution  Control
Act Amendments," Draft, December 7, 1973.

48.  U.S. Environmental Protection Agency, Office of  Water
Programs, "Alternative Financing Methods for Clean Water
Economic Report," September 1971.
                            114

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49.  U.S. Federal Reserve Bank of Boston,  Financing Public
Schools,  A New England School Development Council Conference
held in cooperation with Harvard Graduate School of Educa-
tion and Federal Reserve Bank of Boston,  January 1972,
Federal Reserve Bank of Boston Conference Series No. 7.

50.  Urban Systems Research and Engineering, Inc., "Methods
of Financing the Cost of Preventing, Controlling, and Abating
Water Pollution from Point Sources," report prepared for the
U.S. Environmental Protection Agency, Office of Water Pro-
grams, Contract No. 68-01-0002, August 1971.

51.  Weiss, Steven J., "Existing Disparities in Public School
Finance  and Proposals for Reform," Research Report to the
Federal  Reserve Bank of Boston, No. 46, February  1970.

52.  Whitelaw, W. Ed, "The City, City Hall, and the Municipal
Budget," John P. Crecine, ed., Financing the Metropolis.
                             115

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                        APPENDIX A

                  LEGISLATIVE HISTORY OF

           FEDERAL WASTEWATER FINANCING PROGRAMS

The current version of the Federal Water Pollution Control
Act has its roots in Public Law 80-845, passed in 1948,
which authorized loans and other assistance to states and
municipalities trying to deal with water pollution.  Public
Law 80-845 declared it to be the policy of Congress

     to recognize, preserve, and protect the primary
     responsibilities and rights of the States in
     controlling water pollution, to support and aid
     technical research to devise and perfect methods
     of treatment of industrial wastes which are not
     susceptible to known effective methods of treat-
     ment, and to provide Federal technical services
     to State and interstate agencies and to indus-
     tries, and financial aid to State and interstate
     agencies and to municipalities, in the formula-
     tion and execution of their stream pollution
     abatement programs.   [Section 1]

The Surgeon General under the Public Health Service, the
Federal Works Administrator, and the Federal Security  Admini-
strator were  to administer the  program.  Under  Section 5  the
Federal Works Administrator was authorized to make loans  to
states, municipalities, or interstate  agencies  to  construct
treatment works preventing the  discharge of untreated  or
inadequately  treated wastes.  Loans  could  also  cover the
preparation of engineering reports,  plans, and  specifica-
tions.  Loans were  to be made only if  a project was approved
by the Surgeon General  and appropriate state  agency and was
part of a  "comprehensive" plan.  Loans were  limited to a
federal share of  33.3 percent of the "estimated reasonable
cost"  or  $250,000,  whichever was smaller,  and carried  an
interest  rate of  2  percent.   Section 5 also  provided that:

     bonds  or other obligations evidencing any such
      loan (1) must be duly  authorized and issued
     pursuant to  State  and  local law,  and (2)  may,
      as to the  security thereof and  the payment of
     principal  thereof and interest  thereon,  be
      subordinated [with agreement of Federal Works
                             116

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     Administrator] to other bonds or obligations of
     the obligor issued to finance such project or
     that may then be outstanding.

Projects were to be ranked by considering the "public
benefit to be derived," the "propriety of Federal aid in
such construction," the relation of the full costs of con-
struction and maintaining works to public interest and
necessity, and the "adequacy of provisions ... for assuring
proper and efficient operation and maintenance of the works"
after construction.

Public Law 80-845 authorized $22.5 million for loans under
Section 5 for each fiscal year from 1948 to 1953  [Section
7] and $1 million for those years for grants for the pre-
liminary planning and engineering work on approved projects.
Public 82-579 extended the life of 80-845 until June, 1956.
The funds, however, were never actually appropriated.*

Public Law 80-845 was substantially amended in 1955-56,
1961, 1965-66, and 1972.  Since 1948 the debate around and
modifications to the water pollution control legislation
related to the construction of waste treatment works have
focused on several central issues:  (1) the proper role and
authority of states in managing their environmental affairs,
particularly waste treatment; (2) the size contribution or
"share" the federal government should provide to state
pollution control projects;  (3)  the distribution formula
used to determine how available federal money should be
allocated among states, and among municipalities of differ-
ent sizes; and (4)  the criteria or safeguards used to insure
efficient use of federal funds.

Over time several things have become clear.  The extent and
severity of pollution in this country is outstripping any
provisions for its abatement and control.  The formula for
the distribution of funds to states and among various locali-
ties brings with it a bias and several disadvantages.  Delays
     *  U.S. Senate, Hearings of the Senate Committee on
     Water and Air Pollution Control, 84th Congress, 1st
     Session, Washington, D.C., Government Printing Office,
     1964, p. 52.
                            117

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in obtaining federal financial assistance have led many
states and municipalities to put off pollution control plans
or to take initiative in financing their own treatment
works.  In general total authorizations have steadily in-
creased in recognition of the dimensions of the pollution
problem, although actual appropriations have consistently
fallen short of authorized levels.  The formulas for deter-
mining the federal share and the distribution of money to
states have been changed repeatedly in an effort to meet
all the interests involved.  Although federal involvement
has increased over the years, some states and municipali-
ties have found it more expedient to pre-finance their
treatment facilities rather than wait for federal money
before they initiate construction.

PUBLIC LAW 660:  1955-56

During the 1955-56 Congressional sessions, two bills  (S.
890 and H.R. 9540) were introduced to replace Public Law
80-845 which was about to expire.  In both bills the
Surgeon General, through the Public Health Service under
the Department of Health, Education, and Welfare  (HEW), was
authorized to investigate pollution sources and causes, and
to make grants for research, demonstration projects, and
training personnel to operate and maintain treatment plants.
S. 890 provided that the Surgeon General would

      from time to time make allotments to the several
      States, in accordance with regulations, on the
      basis of  (1) the population,  (2) the extent of
      the water pollution problem, and  (3) the finan-
      cial need of the respective States.*

The Surgeon General also was given the broad power to  allo-
cate  money to interstate agencies on "such basis as  [he]
finds reasonable and equitable.""1"

The importance of recognizing and preserving "the primary
responsibilities of the States in preventing and controlling
water pollution"* was emphasized as was  the proposed
      *  Water  Pollution Control Act  Amendments  of  1956,
      Public  Law  660,  84th  Congress,  Chapter 518,  2nd
      Session,  S.  890.

      +  Ibid.

      *  Ibid.
        	                118

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legislation to provide the support and aid in technical
research, which was seen as the most effective stimulant to
state control programs.  HEW officials testified at Senate
Public Works Committee Hearings in April, 1955 that

     experience with other health programs has
     demonstrated the value of matching grants in
     stimulating States to provide their own re-
     sources to do an effective job.

It was argued that federal support was most effective in
the form of planning, research, consulting, and technical
assistance on tasks which most states could not adequately
perform but which were critical to carrying out construction
of treatment works.

In line with the argument that matching funds would stimu-
late state involvement in pollution control, S. 890,
Section 5 spelled out a formula for the federal share in
control projects:

     The 'Federal share1 for any State shall be 100 per
     centum less that percentage which bears the same
     ratio to 50 per centum as the per capita income
     of such State bears to the per capita income to
     the continental United States  (except Alaska) ,
     except that  (A) the Federal share shall in no case
     be more than 66 2/3 per centum or less than 33 I/ J
     per centum, and (B) the Federal share for Hawaii
               ,
     and Alaska shall be 50  per centum,  an^f°%P^
     Rico and the Virgin Islands shall be 66  2/3 per
     centum.

     The 'Federal share' shall be promulgated ...  on the
     basis of the average of the per capita incomes of
     the Stales and of ?he continental United States for
     the three most recent consecutive years  for which
     satisfactory data are available from the Department
     of Commerce.
            .*   Q=^h c-t-afe received a share of money based

                                 '
                                                        N0
™ howevL? "as^receiSe a share more than 66.6 percent
                            119

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or less than  33.3 percent of the actual  cost of the local
project.*

H R  9540  Section  6, provided direct federal grants to



i^n^s^^
struction loans authorized  (but never appropriated) in 194 8 ,
SS^iS Provided  for matching grants to states  munici-
palities, intermunicipal  agencies, and interstate fancies,
for the planning and construction of treatment  works.  Grants
were to be SSteS  to 33.3  percent of the estimated "reason-
      cost of construction  or $300,000, whichever was
 should be borne by the users of the  service, not by the
 rederal  government in the form of grants. +   (A?othe^1^:,
 S  9827  provided for grants of up to 50 percent of the cost

 of construction.)

 The conference and final version of  the bills provided two
 SinS-   for  the Surgeon General to  make grants for con-
 fruition of  "necesslry" treatment works and for a number



      *   Let x.  =  per capita income for state i


            x  =  national average  per capita income


            r  =  100 - -^  '50, if
                          X

            f  =  "Federal share" in percentage


             f  =  r,  if  33.3 1 r <_ 66.6


             f   =  33.3,  if  r  <  33.3


                 =  66.6,  if  r  >  66.6

      +  Congressional Record,  June  13, 1956, p.  10240 ff.
                            120

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of more specific criteria for the awarding of grants.   Like
the original Federal Water Pollution Control Act, no grant
was to be awarded unless the project was approved by the
appropriate state water pollution control agency and the
Surgeon General, and unless it was included in a "comprehen-
sive" pollution program; no grant was to be for more than
30 percent of the estimated reasonable cost or up to $250,000,
whichever was smaller, and the grantee had to agree to pay
the remaining cost.  Applicants had to demonstrate that
there would be "proper and efficient operation and mainte-
nance" of treatment works after completion, and treatment
operation had to conform to state pollution control plans.*
In making his decision about allocations, the Surgeon
General was instructed to consider the public benefits to
be derived from the project, the relation of ultimate costs
to public necessity, and the adequacy of provisions for
operation and maintenance.+

Fifty percent of appropriated grant sums were to be allotted
to states on the basis of the ratio that the population of
each state bore to all the population in all states.

The other 50 percent of appropriated funds was to be allot-
ted to each state based on a complicated ratio formula.
Each state would receive an allotment determined by divid-
ing the per capita income of the entire United States by
the per capita income of each state/ adding all  50 quotients
so derived, and determining the ratio that each  state's quo-
tient bore to the total of the quotients.*  Of the $50
million authorized by the Act, 50 percent of the appropriations
     *  Ibid., Section 6(b)(3).

        Ibid., Section 6(c).

        Let x   =  per capita income for state i
             i
            x   =  national average per capita income
            y   =  population of state i
             i
            s   =  the state fraction of appropriation
                   grant sum

                                   (x/x.)

                -  50
                            121

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were to go to municipalities of 250,000 or less.*   Con-
struction" was defined to include preliminary planning,
engineering and feasibility studies, and improvement or
extension of treatment works.+

The 1955-56 sessions also were presented with a dozen bills
providing for the amortization by industry at an accelera
ted rate of 60 months of the cost of industrial treatment
works for tax purposes, provided the facilities were in
stalled on the basis of demand from local governmental bodies
and that the facility was part of an overall program for
pollution control.  Municipalities had complained that indus-
trial wastes was one of the problems they could not handle
through their ordinary residential treatment works.  None of
these bills, however, were  incorporated into Public Law 660.

FEDERAL WATER POLLUTION CONTROL ACT AMENDMENTS:  1961

In  1961 the major changes made in the  Federal Water Pollu-
tion Control Act were  to increase the  annual amortization
of  funds  and to raise  the ceiling on maximum grants to a
sinale project.  The Amendments of  1961 increased  the  annual
amortization  for construction  grants on a graduated scale
from  $50  million in fiscal  year  1961 to $80 million in
fiscal year  1962,  $90  million  in  fiscal year 1963,  and $100
million  for  fiscal  years 1964-1967.*   Again, 50  percent of
the appropriated funds were earmarked  for cities of 125,000
or  under.  Maximum grants were increased  from  30 percent  or
 $250,000,  whichever was  smaller,  to 30 percent  or  $600,000,
whichever was  smaller.**

 Several  other features were added to  the  Act.   A project
 serving  more than  one  municipality  could  be  funded by  apply-
 ing the  grant formula  to  each  community's portion  of  the
 project  as if it were  a  separate project.   The  sum of  the
 maximum grants or  $2.4 million,  whichever was  smaller, was
 to  be made until  all applications were funded  which met the
 regulations  in effect prior to the Amendments  and  which
 were filed with the appropriate  state agency during the
 first twelve months after enactment of the  1961 Amendments.
      *  Public Law 660, Section 6(d).
              , Section 6(e)
      *  Federal Water Pollution Control Act Amendments of
      1961, Public Law 87-88, 87th Congress, H.R. 6441, July
      20, 1961, Section 5(d) .
      **  ibid. , Section 5(a).
                             122

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This Act further provided that all money allotted to states
which remained unobligated-for six months beyond the 18-
month allotment period, could be reallocated to states with
an excess of approved projects.*  The administrative agent
of the Federal Water Pollution Control Act, as amended, was
changed from the Surgeon General to the Secretary of Health,
Education, and Welfare.

1966 AMENDMENTS:  THE CLEAN WATER RESTORATION ACT

During the 1966 session of Congress, debate over the Federal
Water Pollution Control Act Amendments centered on the for-
mula for granting federal money to  local projects.  The
testimony at hearings on the large  number of bills submitted
to amend the Federal Water Pollution Control Act presented
an enormous amount of data documenting the increasing
demand and critical need for pollution control projects and
the flaws and biases of the existing legislation.   Wit-
nesses described how the 30 percent limit on grants discri-
minated against both the largest communities and the
smallest towns.  A needs survey conducted and presented_by
the Conference of Sanitary Engineers showed that 70 projects
in the current backlog of applications would qualify  for
grants over  $600,000 but under  $1 million,  for  a total of
$49.6 million if the ceiling  for grants  were  $1 million.
Forty other  projects would qualify  for over $1  million but
under $2 million,  for  a  total cost  of  $183.8 million  if the
ceiling were $2 million.  Eighteen  proposed projects  were
so  large  that  30 percent of  their  cost would  be $2 million,
with  a  total cost  of  $255 million.   On  the other  hand, many
small towns  could  not  even qualify for maximum grants on
the basis  of their population counts,  nor did they have the
capability to  finance  treatment works  on their own.*

The slowness in receiving  federal grants was  repeatedly
mentioned as a deterrent,  both  because municipalities de-
 layed construction in the  hopes of eventually receiving
 federal dollars,  and because even approved projects could
 experience lag times of nearly  two years.  A number of
      *  Ibid., Section 5(c)

      +  Hearings, U.S. Senate Committee on Public Works,
      May 19, 1965.

      *  Ibid., p. 89


                             123

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witnesses stressed the importance of allowing swifter
reallocation of monies that were unused.

The size of the pollution problem prompted the introduction
of a large number of bills aimed at easing the costs of
municipal financing of treatment works.  Again on the basis
of the burden industrial wastes placed on municipal systems,
66 bills were filed to allow a tax deduction for construc-
tion costs of treatment facilities.  Another dozen was filed
to provide money to help retire municipal bonds.  There was
also interest in providing money to help train people for
the efficient operation and maintenance of new facilities.
Debate on several bills during hearings raised the idea of
reimbursing states for pre-financing of treatment works.

The bills which eventually became Public Law 89-753 initi-
ally authorized increasing the authorization for construc-
tion grants to $150 million in 1967, up to $1.25 billion
in 1971.*  Again at least 50 percent of the first $100
million appropriated was to go to municipalities of 250,000
or less.

The general allotment  formula to states was the same:  the
first  $100 million appropriated in a fiscal year was  to go
to states on the basis of population and per capita income
weighted equally; sums appropriated above  $100 million were
to be  allotted on a straight population basis with a  10
percent incentive for  regional planning of projects.  State
allotments were usable for the reimbursement of state or
local  money used prior to June, 1971 and after June,  1966
for projects built without federal assistance  (if approved)
or with less than the  federal share allowable  if sufficient
funds  were available.

The grant allocation  formula was  changed substantially  in
this  law with  a number of built-in incentives  attached.
The federal government was committed to provide  30 percent
of the cost of treatment works  if  the  state  provided  25
percent of the cost.   The  federal  share would  be increased
to 40  percent  if  the  state picked up  30 percent of  the
cost.  If the  state had  adopted  enforceable  water quality
standards for  the waters the  treatment project affected,
      *  Clean Water Restoration Act of 1966, Public Law
      89-753,  89th Congress, S. 2947, November 3, 1966,
      Title II, Section 205.
                             124

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the federal share would increase to 50 percent if the state
only contributed 25 percent.  Again the criteria established
in the 1961 Amendments for selecting projects remained the
same, with emphasis on the state determination of priority.
River basin plans were eligible for a 50 percent federal
share.  The ceiling on individual projects was eliminated,
and there was a provision included for loans of up to $250
million.

The committee report on the proposed Amendments stressed
once again the need for tax incentives to industry to treat
their own wastes.  The existing Act contained a provision
for a 7 percent investment credit for the acquisition of
air or water pollution facilities, which was retained in
the Amendments with the provision that facilities met
federal and state specifications.*

WATER QUALITY IMPROVEMENT ACT:  1968

In 1968 the grant system was altered to include contracts
for up to 30 years to pay the federal share of construction
costs.  Contracts differed from grants in that they pro-
vided a loan to cities which could be issued more quickly
than a grant.   The federal share could also be eventually
recovered.  The allotment of these contracts remained the
same as grants.  The monies available for contracts was to
be calculated according to the ratio of the population of
each state to the population of all the states, with 50
percent of the first $100 million appropriated to go to
cities of 250,000 or less.  The contracts could be used to
pay off municipal bonds which had been used to pay for
treatment works.  The Act also approved one-time grants for
improving the operation of treatment works, on which con-
struction was initiated after passage of the Act.  These
grants were not to exceed 25 percent of the cost of operat-
ing such treatment works, and in no event were to be over
50 percent of the cost of improving operation during a 12-
month period.   The authorization for this grant program was
$25 million.
     *  S. 2857 proposed to increase the tax credit to 14
     percent, but it was not acted upon.  See Congressional
     Record, 89th Congress, October 17, 1966, p. 27247.
                            125

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WATER QUALITY IMPROVEMENT ACT:  1970

In 1970 a variety of bills was presented to increase the
federal share and the total and annual authorizations for
pollution treatment programs.  The Administration bill
(S. 3472) estimated that $1 billion federal input was suf-
ficient to cover both the backlog and the increasing needs
until 1974.  This bill also proposed to reimburse states
for prepayment from current appropriations, and a companion
bill suggested an Environmental Financing Authority to be
managed through the Treasury Department to assist states
and localities in borrowing funds they could not obtain
through grants.  The allocation of funds was to be made on
the basis of a new formula which considered population and
the severity of local pollution conditions.  Sixty percent
of the federal funds was to be allocated by population and
income; 20 percent was to go to those states which paid at
least 25 percent of the cost of all assisted projects,
distributed on a population basis; and 20 percent was to
be allocated on the basis of the severity of the water pol-
lution problems and the local ability to use funds for
basin-wide plans.  This last 20 percent was considered
"discretionary money" to offset the needs of especially
large projects; first priority would go to reimburse states
that had pre-financed plans.  (The 1966 Amendments had
encouraged a number of states and localities to pass bond
issues or arrange other means to finance the federal share
of costs in anticipation of reimbursement, and by 1969 over
$300 million in backlog payments was due.*)

Another bill, S. 3687, challenged the Administration esti-
mate of needs and proposed to authorize $2.5 billion a year
for six years.  The formula in this bill was similar to the
earlier 1955 bill with the federal share being 100 percent
minus the complicated percent calculated from ratios of per
capita income in individual states to the entire country.
At the time, only 16 states were providing the matching
shares to raise the federal share above 30 percent.

The Amendments of 1970 as finally passed contained Title I •
the Water Quality Improvement Act — which made few changes
in the sections related to construction grants for waste
treatment works.  The federal government's commitment to
     *  Senate Public Works Committee Hearings, Subcommittee
     on Air and Water Pollution, April 20, 1970, p. 250.
                            126

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make grants or contracts related to training students "to
enter an occupation which involves the design, operation,
and maintenance of treatment works, and other facilities
whose purpose is water quality control" was expanded by
the stipulations in a newly added section (Section 16).

The 1970 Amendments (Title II) also replaced the Federal
Water Pollution Control Administration with the Federal
Water Quality Administration.  Authorizations remained at
the level voted in 1966, or $1 billion for the fiscal year
ending June, 1970 and $1.25 billion for the fiscal year
ending June 30, 1971.

PUBLIC LAW 92-500:  1972

The next major overhaul of the Federal Water Pollution
Control Act came in 1972.  Title II, called "Grants for
Construction of Treatment Works," expanded the purposes of
the Act and specified goals related to new technology
(including reclamation and recycling).  Although federal
financial assistance is not limited to this revised Act or
its predecessors (HUD, EPA, and FHA, for example, all have
authority to grant funds for treatment plants), the new Act
has taken precedence over most other funding sources.
Authorizing legislation for other grant sources have not
been considered in this discussion.

Several broad new conditions were placed by the 1972 Amend-
ments on the allocation of grants after June 30, 1974,
including that:

   Projects provide for the application of best-practicable
   waste treatment technology over the life of the works;

   Projects will consider and allow for the application of
   new technology for reclaiming or recycling water;
   and

   Each sewer collection system discharging into the treat-
   ment works is not subject  to excessive infiltration.

The Amendments as finally adopted and passed  over  the
President's veto provide for  75 percent federal grants-for
facility construction with no specified state participation
required.   (The Senate  bill provided  for a  70 percent
federal grant if the state participated with  a  10  percent
grant; the  House bill provided for  a  75 percent  federal


                             127

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fssure municipal access to funds to finance its share of
project cos?sPand for the allocation of funds among states
according to need for treatment plant construction.
                             128

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                        APPENDIX B

               CURRENT FEDERAL GRANT PROGRAM

FACILITY PLANNING

As explained in the text, the three-step funding procedure
includes

Step 1  facilities plans and related studies;

Step 2  construction drawings and specifications and
        sewer system rehabilitation if required; and

Step 3  building of an operable treatment works.

Grants may be awarded for Step 1, Step 2, Step 3, or proj-
ects that combine Steps 2 and 3.  Step 2, Step 3, or Step
2/3 projects, however, can only be funded if facilities
planning (Step 1)  requirements have been satisfied.

These requirements include:

   treatment works description;

   complete waste treatment system description;

-  sewer system evaluation;

-  cost-effectiveness analysis;

   copy of permit to discharge;

   comments of agencies with reference to A-95 and
   208 planning requirements;

   public reactions;*

   legal, financial, and managerial capabilities
   statement; and

-  civil rights statement.
     *  There are certain explicit public participation
     requirements.
                            129

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 For Step 2, Step 3, or Step 2/3 grants from funds authorized
 for any fiscal year beginning after June 30, 1974, best-
 practicable wastewater treatment technology must serve as
 the basis for planning and design unless application of
 best-practicable treatment would not meet water quality
 standards.   In that case the plan must provide for meeting
 those standards.

 GRANT APPLICATION AND APPROVAL

 Grant approval requires the determination

 (a)   that a facilities plan has been approved before award
 of  Step 2 or Step 3 grant funds.

 (b)   that proposed works are in conformity with any approved
 303(e)  basin plans.

 (c)   that proposed works are state certified as to priority.

 (d)   that grant award will not cause the total of all
 grants  to that state's applicants to exceed the state's
 allotment.

 (e)   that the applicant agrees to pay all non-federal project
 costs.   (Grant payments are made  directly to the municipal
 authority constructing the treatment works and it is a
 responsibility of that authority  to collect any state con-
 tribution.

 (f)   that a copy of  the NPDES  permit be  provided.

 (g)   that user charge  and  industrial cost recovery regula-
 tions will  be complied with.

 (h)   that the proposed site will  be available  and that the
 Relocation  and Land  Acquisition Policies  Act of 1970 as
 well  as other federal  regulations  or statutes  will be com-
 plied with.

 (i)   that NEPA environmental impact assessments have been
 performed.

 (j)  that the  Civil  Rights  Act  of  1964 has  been complied
with.

 (k)   that satisfactory provision has  been made  to  assure
proper and efficient operation  and  maintenance  of  the

                            130

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facility and that the state will have an effective opera-
tion and maintenance monitoring program to assure compliance
with applicable permit and grant conditions.

{1}  that if the project includes sewage collection system
work, such work is either for replacement or major rehabili-
tation of an existing sewer system and is necessary to the
performance of the wastewater treatment works, or is for a
new sewer system in a community in existence on October 18,
1972, (where the bulk of the expected flow in the system
will originate from the community habitation in existence
on that date) with sufficient existing or planned capacity
to adequately treat such collected sewage.

(m)  that fiscal year 1975 or later grants are for best-
practicable wastewater treatment technology over the life
of the works and that the applicant has allowed  (as appro-
priate and to the extent practicable) for the later
application of technology to eliminate the discharge of
pollutants.*

 (n)  that project costs do not  include:   costs allocable to
treatment of pollutants in industrial wastes  unless the
applicant is required to remove such pollutants  introduced
from non-industrial  sources; costs allocable  to  treatment
of wastes from federal government activities  that  another
federal  agency has  agreed to pay; or the  unexpended balance
of the  amounts retained by the  applicant  for  future recon-
struction and  expansion pursuant to  industrial cost+recovery
regulations, together with interest  earned  thereon.

 (o)  that  initiation of construction has  not  occurred.

 (p)  that  the  applicant  is the  designated 208(d)  area
-------
(q)   that the proposed wastewater treatment works will
comply with all federal and state environmental laws,
including the Clean Air Act.

(r)   that each sewer system discharging into the wastewater
treatment works is not and will not be subject to excessive
infiltration/inflow.  The determination that this is the
case requires an infiltration/inflow analysis according to
guidelines  (including a cost-effectiveness analysis of costs
of eliminating the infiltration/inflow conditions and of
transporting and treating the infiltration/inflow) and, when
necessary, a sewer system evaluation survey followed by
rehabilitation of the sewer system.*

(s)   that a sewer use ordinance prohibiting any new connec-
tions from inflow sources into the sanitary sewer portions
of the sewer system and ensuring that new sewers and
connections are properly designed and constructed will be
enacted and enforced.

(t)   that industrial pre-treatment requirements will be
met.

PROJECT COSTS

Allowable costs include:

-  salaries, benefits and expendable material  incurred
   by grantee;

-  costs under construction contracts;

-  professional and consultant  services;

-  facility planning;

   sewer  system evaluation;

-  feasibility and  engineering  reports;

-  certain  relocation costs connected with land
   acquisition;
      *  Such rehabilitation work may be approved as Step 2
      work;  it may also, under certain conditions, proceed
      as Step 3 work, although this is expected to occur
      infrequently.
                             132

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   costs of complying with NEPA;

-  preparation of drawings, specifications, and estimates;

   landscaping;

   construction supervision;

-  removal and relocation of utilities;

   materials for the project;

-  laboratory supplies needed to initiate plant
   operations;

   operation and maintenance manual preparation; and

-  project identification signs.


Costs not allowable include:

-  basin or area planning not directly related to the
   project;

-  bonus payments not legally required for early project
   completion;

   personal injury compensation or damages;

   fines and penalties;

   unapproved costs;

-  interest on bond to finance project;

   ordinary operating expenses of  local government; and

-  site acquisition, except  for  land  acquired  after October
   17, 1972,  that will be  an integral part of  the treatment
    (e.g.,  land  for  spray irrigation of sewage  effluent, but
   not land  for  oxidation  ponds)  if approved by EPA.
                             133

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                        APPENDIX C

                ISSUES IN FISCAL FEDERALISM
Starting with its early history,  the United States has a
relatively decentralized fiscal structure with over 80,000
government units providing services and raising revenues.
Strong arguments support this multi-unit, multi-level form
of government.*  Undoubtedly the most important theoretical
armament is a decentralized fiscal structure provides a
means £y which individual preferences can be honored   Since
each local government unit is able to choose its own level
eacn locai 9uv^       warietv of public service-tax bundles






their own demands.  However, determination  of  level of  ser
vices and allocation of costs  is by ma3ority vote  of  the
members  in any given unit, and consequently minority  inte
rests can be protected only  if these minorities  are
concentrated in  a  few districts or  if  ^J9heV  *   addi-
government intervenes to  protect their  interests.  An addi
tional  argument  in favor  of  a  system of many  small units  is
that those who  benefit  from  a  service  should  pay for  it.
The benefit  area of many  services  is relatively  small,  such
as a police  or  fire station.   Thus,  the argument runs,  the
unit of government that is responsible for providing the
revenues should also  be small.   To complicate matters,
 lowever, there  is often a non-equivalence of  benefit areas
 for the various government services demanded  in  a locality
 and special-purpose districts  are  frequently  organized.

 In place of a complex system of overlapping special-purpose
 districts,  various services have often been consolidated
 into a simpler set of local government units, although the
 problem of overlapping districts remains in most urban
 areas   Consequen?ly, the benefits from services Provided
 in one district often spill over into  surrounding districts.
 This can lead to an undersupply of the service because the
 groups who bear the entire cost and who determine the  level
 of service do not receive all the benefits.  When comparing


      *  For a complete listing of these references,  see  the
      last page of this appendix.
                              134

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  the  cost of the service to the benefits derived,  they will
  not  include the benefits received by other members of society
  who  are  outside this  specific  jurisdiction.  Consequently,
  the  value of the benefits  is underestimated relative to the
  cost.  In a like manner  these  spill-overs  can lead to an
  oyersupply  of a negative externality  such  as water pollu-
  tion resulting  from a waste discharger  located on the edge
 of a town.  Therefore, the first reason for intergovernmen-
 tal transfers is to help correct this problem by allowing
 those, outside the jurisdiction to contribute to the provi-
 sion of a service they desire,  or to the removal of a
 negative externality.









 and new patterns of de                -          Provision,
g*™ be


In addition to the non-equivalence of benefit  and  cost
areas, a second reason for having intergovernmental  ?
fers, especially from the federal level!  is ™ encouraae
the provision of certain "merit goods" such as e^Sca^on
that are considered desirable by society.  A third r~easo~n
is the need for the federal government to effect some  re-
distribution of income.  Instead of approaching redistri-
bution directly in terms of some form of guaranteed  income,
the federal government has subsidized the provision  of
various goods such as low- income housing.  In  this way the
poor receive more of certain goods that the government
feels they should receive, but not of all goods.

Grants from federal and state governments may  also be  pro-
vided in order to equalize the position of local fiscal
units.  These grants are motivated by the need to  correct
inter-individual differences and by the desire to  correct
locational inefficiencies.  Some jurisdictions may be  hard
pressed to provide certain services essential  for  business
                            135

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because of the composition of their tax base.  These differ-
ences in ability are undesirable in that they distort
locational decisions, especially of businesses, through
differences in the tax rate.

TYPES OF GRANTS

Grants can be categorized according to three characteris-
tics.  First, the grant can contain matching provisions
which require the recipient jurisdiction to match each
dollar of federal funds with a certain amount of its own
money.  Some grants do not contain any matching provision
and thus use other criteria to determine the size of the
transfer.  Second, a grant can be restricted to specific
expenditures, frequently called a categorical grant; or it
can be unrestricted, also called a general or block grant.
Third, grants can also be based on some measure of fiscal
capacity and/or on a measure of the amount of service which
needs to be provided such as the size of the target popula-
tion.

The matching provision lowers the relative price of the
public service.  With a matching ratio pf 50:50, the local
government gets $1 worth of service for each 50$ of its own
money it spends.  This reduction in the relative price will
normally result in an increase in the amount of public
goods provided.  The additional amount purchased will depend
in part on the price elasticity of the good in question.
There is also an income effect because with the grant the
community has more money to spend in total.  Therefore,
there is likely to also be an increase in the amount of pri-
vate goods purchased by the recipient community.

Grants with no matching provision are equivalent to an
income transfer to the jurisdiction.  Even though the grant
is given to the local government, it can result in a tax
cut that allows increased private consumption because the
community always has the option of simply replacing its own
funds with the grant money.  Therefore, if the goal of a
grant is to encourage the provision of more public goods,
as opposed to private goods, then a matching grant is more
effective.

With a non-matching grant there is little difference between
a categorical and a block grant (as long as the categorical
grant is less than what would be spent anyway).  This is
                            136

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 due to the fact that they both are an increase in income.
 If the non-matching grant is limited to certain expenditures
 (categorical)/  then the relevant comparison (with regard to
 the goal of increasing the provision of this public good)
 is between the  amount of expenditures without the grant and
 the size of the grant.   With a matching provision,  the cate-
 gorical grant  lowers the price of that specific good
 relative to all other public goods and all private goods.
 Thus,  if the provision of a specific public good is to be
 encouraged,  as  opposed to all public goods, a matching
 categorical grant is more effective than a matching block
 grant.   Categorical grants can be limited to the provision
 of a certain service or to certain inputs for a certain
 service such as capital investments in municipal wastewater
 treatment.

 Even with a categorical matching grant a community  may
 decide  to use only part of its prior expenditures to meet
 the  matching provision  and to use the rest to  increase
 expenditure  on  other public  goods or to  reduce  the  tax
 rate.   Such  substitution depends on the  relative  price and
 income  elasticities.  Some grant programs  have  tried to
 insure  that  all  federal money is directed  toward  an increase
 in the  level of  service.   An example  is  the  Senate version
 of the  Education Amendments  of  1972 which  provide for  a pro-
 gram where the  federal  government pays 50  percent of the
 increased amount of  state  scholarship grants provided  over
 a base year.*

 The third characteristic of  grants is the use of measures
of fiscal capacity and/or need.   In many cases per capita
 income is used on the assumption  that people with less
 income are less  able to provide themselves with public
services.  Perhaps a better measure is of the type developed
by the Advisory Commission on Intergovernmental Relations.+
     *  Hartman, R. W.,  "Higher Education Subsidies:  An
     Analvsis of Selected Programs in Current Legislation,"
     The Economic? af Federal Subsidy Programs,  Part 4,
     Joint Economic Committee, Congress or rne United
     States, August 28,  1972, p.  481.

     +  Advisory Commission on Intergovernmental Relations,
     Measuring *** Fiscal Capacity and Effort of State and
     Local Areas/, Washington. B.C.,  Government Printing
     Office, 1971.

                            137

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They argue that it is the amount of tax revenue available,
not the average income, that is relevant.  For each kind of
state and local tax a rate is determined which, if applied
throughout the nation, would produce an amount equal to the
actual yield of that tax.  For each state the potential
yield of each type of tax is estimated at this nation-wide
rate; and the potential yields are summed to arrive at its
total tax capacity.  This same approach has been applied to
non-tax sources of incomes, such as fees and charges, to
yield a total revenue capacity for each state.  The actual
revenues collected in each state have been compared to this
revenue capacity to provide a measure of the relative tax
effort.

It is important to remember that this is a measure of the
government's effort, not a measure of the size of the burden
on its citizens, although the two will be somewhat related.
The study of tax incidence is complicated and presently
filled with disagreements although there is agreement that
certain taxes are shifted from those who initially pay them
to someone else.  For example, the bulk of the sales and
excise taxes collected from producers, wholesalers, and
retailers are passed along to the buying public in the form
of higher prices or a specific charge.  In areas with a
large number of tourists, revenue can be raised through
taxes on hotel and motel accommodations, restaurant meals,
and amusement.  Thus, it is not valid to simply assume that
states making large efforts are states with a heavy burden
on local residents.

Financial capacity measures have played a role in many state
programs of aid for education.  As of 1966-67, approximately
37 percent of all state aid and 69 percent of all state
educational aid involved some adjustment for local capacity
differences.*  In most cases the property base rather than
the potential yield of all revenues is used to measure
capacity.  School expenditures rather than total local ex-
penditures are used to measure effort.  In 1968, 25 federal
grant programs disbursed funds with some allowance for
differences in fiscal capacity.  Of these, seven were grant
programs for public facility construction and 18 were for
the provision of public services.4"  Personal income is
     *  Ibid., p. 33.

        Ibid., p. 11
                            138

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always the measure of  fiscal capacity used for federal
grants.  However, the  Advisory Commission on Intergovernmen-
tal Relations study shows that for certain states there is
a wide divergence between per capita income and revenue
capacity.  For 24 states, per capita income under-indicates
relative revenue capacity by at least 5 percent; and for
five of these it under-indicates from 24 to 37 percent.
Likewise for ten states, per capita income over-indicates
relative revenue capacity by over 5 percent.

The common measure of  effort is to compare taxes to personal
income.  The current revenue-sharing formulas include this
type of measure of effort.  However, for some states this
also is a poor measure of effort.  For ten states the tradi-
tional taxes/income measure under-indicates relative revenue
effort by over 5 percent; and for 18 states it over-indicates
the revenue effort.

A related issue is a measure of need.  This is usually
established in terms of target population  (school age chil-
dren, total population, families in poverty, etc.).  Almost
all HEW grants include a measure of target population.  One
problem with this is that different members of the same
population set may have different needs.  For example, it
requires more resources to provide a given level of housing
in the northeast than  it does in the south simply because
of differences in climate.  In addition, there may be dif-
ferences in the costs  of providing a given level of service.
Most of the housing subsidy programs require a certain
quality of construction and size of unit, and then subsidize
or take over the mortgage, thus implicitly allowing for
differences in costs.

The equalizing effectiveness of using measures of fiscal
capacity and/or need to allocate funds is often severely
diluted by placing a limit on the total amount of funds any
community may receive.  This is a technique used by various
states in their programs to subsidize education, where
expenditures are matched up to 110 or 125 percent of the
state average.  If a community spends money in excess of
.the amount matched by  the grant program  (a closed-end
matching grant), then  the grant no longer has a price
effect but only an income effect.

These various characteristics can be used  in combination to
achieve specific goals or to correct certain problems.  The
                             139

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type of grant best suited for correction of spill-overs is
a categorical grant aimed at that specific service, with a
matching provision.  Measures of need are not included.
The matching rate should be equal to the ratio of external
benefits (benefits accruing to those outside the providing
jurisdiction) to total benefits.  In other words, those
outside of the jurisdiction providing the service pay their
share of the cost.  If the purpose of the grant is to en-
courage the provision of merit goods, then a matching non-
need related grant is appropriate.  If all public goods
are considered to be merit goods, then this could be a
block grant; otherwise, it should be categorical.  In order
to equalize the fiscal capacities of jurisdictions, a block
grant with a need measure can be used.  Equalization plus
encouragement of the provision of merit goods can result
from the use of a categorical grant with a measure of need.

The use of grants by the federal government to stimulate
the provision of public services dates back to early land
grants given to encourage the building of schools.  Monetary
grants date back at least to 1879 when a program was started
to provide books for the blind.  These early grants were
usually offered in equal per capita amounts to each state,
subject to a dollar-for-dollar matching formula.  During the
Depression, a measure of financial need was added to the
formulas used, such as that for the emergency relief program
and the Social Security Act of 1935.  The enactment of the
School Lunch Program in 1946 introduced the use of a variable
matching ratio.  This had already been used by some states
in their grants to local schools.  The 1948 Amendment to the
Hill-Burton Act provided for separate aid for innovation
and experimentation.

The amount of funds and the number of grants has increased
significantly in recent years.  In 1960 federal grants
totaled $19 billion and in 1970 they were $23.9 billion,
with an estimated $45 billion in 1973.  There appears to be
a continuing trend towards more centralized revenue collec-
tion combined with local expenditure decisions.  In 1940,
11.6 percent of state revenues were in the form of federal
grants, and 23.6 percent of local revenues were in the form
of state grants.  By 1970 this had grown to 22.1 percent of
state revenues from federal grants and 32.7 percent of local
revenues from state grants, with only about 3 percent of
local revenues coming directly from federal grants.

In addition to this growth in amount of aid, the pattern
of cost sharing has changed.  Federal shares have tended to

                            140

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increase, but the ratios have also become more diverse.
Where once the accepted ratio was 50:50, the federal govern-
ment has paid up to 90 percent of the cost of Neighborhood
Youth Corps projects, Adult Basic Education, and Community
Action Programs.  (Of course, revenue-sharing is equivalent
to a federal matching percentage of 100 percent.)   The
matching ratios have been applied as if they were a precise
tool for the fine tuning of a public decision.  Variable
ratios have been used to encourage organizational changes
in government or the provision of services considered to be
of top priority.  Federal aid for college construction is
one-third, unless it is construction of a facility for a
community college in which case the federal government pays
40 percent.  Under the highway trust fund grants for cer-
tain primary and secondary roads were 50 percent, but for
the interstate system the grants were 90 percent.  There
has also been an increased emphasis on planning.  Under the
1964 Urban Mass Transportation Act, federal funds would
finance up to two-thirds of the net project cost if there
was an urban transportation plan; otherwise grants of one-
half of costs were allowed.  This has been coupled with
direct professional consultation and technical help to
states and localities.

ALLOTMENT FORMULA

After the general characteristics of a grant program are
established, the allotment formula must be established.
The actual amount of funds available to any jurisdiction  is
based on the allotment formula used.  In addition,  there
may be matching requirements.  The most common allotment
formula is one based on the  size of the target population,
such as total population, school age children or welfare
recipients, for example:
        Ai  =  ao +

where  A±  =   allotment  for  the  ith state

       P.  =   target  population  in  ith state

       P   =   total target population in nation as a whole
                             141

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       a   =  a constant to cover administrative costs,
        0     usually very small

       a   =  a constant set by legislation.


Population is a crude measure of need for it does not con-
sider differences in costs, nor does it consider differences
in capacity.  However, it is easy to apply and is used in
the majority of HEW grants.  In addition, the majority of
grants use a uniform matching rate.  The matching rate varies
between programs, running from 33.3 percent for higher
education facilities  (which are not part of a community
college) to 90 percent for Adult Basic Education and the
National Teachers Corps.  In some cases the allotment for-
mula includes a measure of per capita income in addition to
the target population.  This is a more refined measure of
need.  One example is the allotment to a state for basic
support of Vocational Rehabilitation:
       Ai
where  A.
         1
        p.
=  a.
p
E
i
.P .
D D
1.
1.
0
0
- 0.
- 0.
5
5
/y . \ 2
(y -\ 2
   allotment to ith state

   constant set by size of appropriation

   population in ith state

   per capita income in ith state

   per capita income for the United States
 Thus as a state's per capita income rises in relation to
 the national average, its allotment decreases.  With this
 type of allotment formula, the state with the lower per
 capita income is eligible for more money, but if the match-
 ing rate is uniform, this state does not necessarily
 receive more help in reaching any level of expenditures.
 Figure 9 illustrates this.
                             142

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     Total  expenditures  per capita on program

Figure  9  Operation of  allotment formula based on per capita income
          with uniform matching  grant
                                143

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In Figure 9

     OA   =  budget line with no aid,

     OBC  =  budget line of wealthier state with
             matching grant up to
     ODE  =  budget line of poor state with matching
             grant up to OX2 .

If both states provide Xx or less service, they face the
same relative price; if both states provide between X^ and
XT service, the wealthier community faces a higher relative
price; and if both states provide X2 or more service, they
both face the same relative price, although state expendi-
tures of the poorer state is less than that of the wealthier
state; if operating between X1 and X2 , the grant to the
wealthier state is equivalent to a non-matching grant
whereas that to the poorer state is a matching grant; and
if they are operating at X3, then it is equivalent to a
non-matching grant for both.

An alternative approach is to have the allotment based on
the relative target population, with a matching ratio which
varies with the relative income of the state.  This is the
approach used in  the Library Services and Construction Act.
The allotment to  the ith state  is:
      Ai   =   ao  +  ai l~'
 The  federal  share  in  matching to  the  ith state is:
       p.   .
 As a result of this formula the poor state is not eligible
 for any more funds than the wealthier one is, but the
 relative price is lower.   Thus there is a greater incentive
 to the poorer state to use the funds available to it.

 Several of the welfare and public health aid programs
 include per capita income in both the allotment and the
                             144

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 matching ratio formulas.  For these particular programs,  per
 capita income is a measure of both need and fiscal capacity
 As an example, in the Hill-Burton Hospital facilities con-
 struction grant, the relative income factor is weighted:
       A.
        i
=  a.
                  P.
                   i
            1.0 - 0.5
                       1.0 - 0.5
 and
       F.
        i
=  1.0 - 0.5
 The  squaring  of  the  income  factor (y./y)  is  meant to  be  a
 measure  of need.   By incorporating fiscal measures in both
 the  allotment and  the matching  ratios,  it is possible to
 provide  incentives for low-income states  to  provide the
 same level of service as  high-income  states, and  to do so
 at less  cost  to  the  low-income  state.

 SHIFT TOWARD  BLOCK GRANTS

 The  Nixon administration  has  fostered a move towards  lump-
 ing  together  existing categorical aid programs  into a
 limited  number of  broad-purpose grants, thus reducing the
 merit good and redistributional aspects of many programs
 while simplifying  the administrative requirements.  The  1972
 Amendments to the  Social  Security Act have essentially
 transformed an open-ended matching grant  for social ser-
 vices into a population-based block grant.   Thv. Manpower
 Development and Training  Act  of 1973 consolidated a large
 number of categorical manpower programs into a  block  grant.

 While it is too early to  know the full  impact of  a  shift
 from categorical to block grants,  certain  features  already
 are emerging.  Most likely there  will be  a redistribution
 of funds away from large  inner cities.  One  reason  for this
 is that many categorical  grants were focused on problems
 found almost exclusively  in large  cities.  The  objectives
nfJr°CT gr<^s.are more  general,  using broader indices  of
need.  in addition to  the question  of resources to  finance
                            145

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 programs t  the categorical grant strategy concerned itself
 with, the need to establish n&w institutions in order to get
 •    services started,   yhus wider broad black grants w^
       expect to see a  shift away from many of the special
       ms now supported by categorical grants aa
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                        APPENDIX D

         ANALYSIS OP TIME PATTERNS OF EXPENDITURES

This appendix examines the time pattern of attaining the
goals of the 1972 Amendments under various assumptions
regarding funding levels and construction priorities.  The
analysis is based on use of the 1973 Survey of Needs and
utilizes a model which extends the capacity of the national
model discussed in Section 4 to answer the following ques-
tions:

1.  for a given number of dollars and grant level, how
    many of the new or modified treatment plants can be
    built;

2.  for a given number of dollars and grant level, how
    many pounds of BOD can be removed from wastewater
    streams.

Answering these questions using the 1973 Survey of Needs is
a rather straightforward matter although the analysis is
complicated slightly for question (2) by the fact that all
the records are not complete.  The answer to the first ques-
tion can be obtained by assuming:  (1) that the federal
government authorizes a given dollar amount for the capital
subsidy program; (2) that the money is distributed to the
states on the basis of stated need, i.e., the ratio of a
state's dollar to the national aggregate; (3) that the
grant is to be a given percentage of capital costs (e.g.,
75 percent); and (4) facilities are built when grant monies
are available.

As discussed in Section 4, assumptions are made to account
for the lack of information in the Survey of Needs record.
However, as more information is needed for this analysis,
not all records are utilized.  In fact, only 6,300 of the
total 11,000 non-sewer records were utilized in the analysis
of this appendix.  This is a serious limitation.

Two alternative construction priorities are examined.  The
first is that each state will build all treatment plants
starting with the least expensive until grant funds are
exhausted.  Such a procedure provides an estimate of the
maximum number of subsidized treatment plants that can be
built.  The second assumes that each state allocates its
share of a priority list based on a BOD removed per facility

                            147

-------
cost criterion, i.e., grant funds are distributed as a
function of pounds of BOD removed per dollar until the
monies run out.

Figures 10 and 11 present for the 75 percent capital grant
the national time pattern of achievement under two alterna-
tive financing patterns of $2 or $3 billion per year for
treatment plants only.  Based on the 1973 Survey of Needs
percentage of treatment to total costs of 40 percent, this
would be the equivalent of federal grant expenditures
respectively of $5 or $7.5 billion per year.

In all cases the time patterns show decreasing returns
after the first year.  Tables 16 through 27 present the
results disaggregated by states.  In each case the tables
are for cumulative federal expenditures.  Thus,  for example,
Table 19 represents  the results  from a cumulative federal
expenditure of $6 billion which  can represent either  3
years at $2 billion  per year or  2 years at  $3 billion per
year.

In the model which produces these tables, the cumulative
expenditures are  assumed to be allotted to  the individual
states based on the  current allotment  formula, i.e.,  in
proportion of  that state's needs to total national  needs.
The model produces the  state-by-state  totals based  on a
discrete number of treatment plants under the priority of
increasing facility  cost for Tables  16 through 21 and a
priority of  increasing  BOD removed per dollar  for Tables
22  through 27.  A result of  this discrete process is
that  the-particular  expenditure  level  is not completely
exhausted.

This  process  is basically  as  follows:   let  the federal
allocation for a  particular  state  be $Y.   If  the federal
cost  to  build the first N  plants in  the state  priority  list
is  $Z where  Z  < Y and the  federal  cost to  build  N+l plants
is  V  where V > Y, then the totals  for that state are based
on  N  plants  and the  quantity (Y-Z)  is not  expended.
                             148

-------
     30i—
  BOO
removed
 IbxlO6
                       o 2(5) billion/year  in order of inc. facil. cost
                       A 3(7.5)
                       a 2(5)      "      in order of  inc. BOD/$
                       x 3(7.5)

      o	I	i	f-
                                   YEARS
       KEY:  a(b)  billion/year  implies an expenditure of federal
             construction  grant monies of  $a billion/year for treatment
             Plants  only  and   a total federal grant expenditure of
             $b  billion year


   Figure 10   BOD  removal time patterns 75% capital grant
                                    149

-------
      6 —
Sources
under
control
  xio3
                     o  2(5) billion/year in order of inc  facil. cost
                     A 317.5)
                     a  2 (5)      "      in order of inc. BOD/$
                     x 3(7.5)
                                   1
1
1
                                     YEARS
        KEY-' a(b)  billion/year implies  an expenditure of  federal
             construction grant monies of $a bill ion /year for treatment
             plants only  and   o total federal  grant  expenditure of
             $b  billion year


   Figure 11   Source control  time  pattern 75% capital grant

                                   150

-------
TABLES 16 THROUGH 21

State BOD removals and sources controlled for cumulative
federal expenditures of $2, $4, $6, $8, $9 billion under
the priority of construction in order of increasing facility
cost.
                             151

-------
OF
1
2
3
f 4
-5
r £ '

ra
9
10
11
'12
13
14
15
r"i h
* 17
18
1 *>
'7(J
71
2?
J»3

25
?6
27
!"'8
* '9
30
31
'32
33
34

"36
37
3fl
39
'40
41
4?
43
44
45
46
47
4 a
49
50
•i?
53
*>4
55
56
57
ALA 3AM A
AL\S'(A
A* I Z1MA
ARKANSAS
CAL IFORNIA
COL m. AO'l
r.nNNrcTicuT
nELAWA^E
niSTKICT OF COLUMBIA
FL 1KIOA
GE1RGIA
H\JAIl
IDAH1
ILLIN'HS
INDIANA
IOWA
KANSAS
KFNTUCKY
1 n.jisiANA
V-MNF
M4'< YL AN1
MASSNCHUSETTS
MICHIGAN
MIMNcSOT/\
MISSISSIPPI
MISSOURI
MHN TANA
Nr JRASKA
NFVAOA
f*jF'4 HA^^S'MRf"
MCJ JTRSCY
NEV MCXICO
NFW YOitK
nn < TH CA^HI INA
NORTH DAKOTA
OHT 0
OKLAHOMA
tl i c: ^Q ^\
PfxJNSYl VANI A
PUT HP ISLAND
SOUTH CAT,!. INA
SOUTH OAKOTA
T^NJNPSSFF
f p x A *>
UTAH
Y ro M'T ^ T
VRT.INIA
WASHINGTON
WFST VIRGINIA
WISCONSIN
WAKC rsL^N^
A 'APR 1C' AM SAMOA
G! t\ M
PUCRTH KICO
T" 9121500. -
... ~ w" . A
849560481
42549563.
	 ___. 22484976.
3411000.
119816016.
29033136.
• "~ mm:~
31910944.
13927500.
	 14168250. -
27835472.
39524224.
81310320.
... 	 28889184.
11301750.
43373136.
2697750.
	 7343250.
3135750.
18100496.
145222240.
	 3436500.
228416396.
40875616.
1484250.
— 	 — 101806384.
26633120.
11225250.
86375824.
	 6955500.
31467424.
2104500.
25385952.
	 36124848.
91&8000.
6186000.
54508128.
	 _._. 28922960.
17912944.
27035104.
1538250.
••— 0.
0.
1008750.
21596224.
0.
457500.
- - 1942943232.
                                                                                          OCM

-------
                                               Table 17.
Ul ^
RtUCVAL IN ORDER DF INCREASING CAPITAL NfFO , t

1
2
3
A
' 5
6
7
P
9
10
11
12
13
1A
15
16
17
16
19
20
21
22
23
2*,
«!'•
' 26.
27

"29
30
31
, 32
, 33
3A
35
36
37

39
AO
Al
A?
A3
A*
A5
A6
A7
19
50
51
52
1 53
f.A
55
56
57
TOTAL
STATE
ALAEAHA
ALASKA
ARIZONA
ARKANSAS
CALIFORNIA
COLORADO
CONNECTICUT
OELAWARE
DISTRICT CF CULUMLIA
(-LTRIOA
GEORGIA
HA,/ All
IDAHO
ILLINOIS
INDIANA
IOWA
KANSAS
KENTUCKY
LOUISIANA.
MA 1 KU-
MAR YL AN C
MASSAC.Hl'^CTTS
MICHIbAN
MINNESOTA
MISSISSIPPI
MISSULRI
MONTANA
NEBRASKA
NFVAl'A
NtW HAMPSHIRE-
NLH JLKStY
NCW MEXICO
NtW YORK
NORTH CAROLINA
NORTH DAKOTA
OHIO
C.KLAHrhA
tRF:CLN
PENNSYLVANIA
RMC'Ot ISLAND
St't.'TH C*-.MiLlMA
SOUTH f.AKOTA
TENNESSEE

UTAH
VERMONT
VIRGINIA
WEST VIRGINIA
'/t 1 i> c L' i'v 3 1 f'.
HYOMINl-
WAKL ISLAND
AMERICAN SAMOA
00AM
PUERTO RICO
TRUST lE*-.ftlTf:P.IFS
VIRGIN ISLANDS

TOTAL 100
2T77A3.
28312.
26 f>i*09.
7976$.
1574*81.
1781- "^b.
A6616.
23W 1 .
i s i r r. ? .
V66t!l f* .
A62PA7.
1131A250.
POAOA.
3f Cb57.
26AOVA.
31 2509.
1 1 V 5 {.• T» .
2AI;OV*.
I'tOSVA.
1 (*K At* ° .
1C'.. 5 1,7 ?.

2tl3ivl
1 1 fc> A t> 6 .
1 133Vi .
2(:8U 12.
It 176.
?/ loo*- .
^ 2A2 6 .
?2 5506 .
(,|- ^. ^^ j* a
7^2O3 .
10SC 653.
63 A i' IP.
32700.
t 5 1 i i< 7.
230071.
6J-V22.
t S^^OS .
lJ>!- 10.
A799AO.
A13i>U.
510101.

1 1 f. O2 f .
? VI 7? .
622A3*.
If-:i9t!fl
1 1" 5 2 1* /* •
A 2 7 1> I .
O.
5175 »
2 ^5^.
2500A3.
0.
1 6BOf .
27927936.
LOO RFMOVI D
SC077.
i-903.
Af> It 6.
AC9R3.
110£il5».
1 'f 253 .
25760.
17A23.
°«

K,5f03l
ll?3A9fO.
7P57.
26^081.
"OA'ift .
16^033.
5A177.
169530.
13065U.
^C7A 7 •
7t Cj22 •
5Cj6^«0.
177352.
6V17U
A39B8.
93°7 1 .
l*A7*f .
A6023.
5^6'^.
AJ-771.
206H*. 1 .
1 o ] 1 '• .
2760S1.
1656B1.
2101H.
?37h3A.

('P c'2i! .
27AL67.
fs6V3 .
1 4 cr 5 # ? .
21tVA.
6 V 1 r' 1^ »
A?9?17.
I'OC31.
P05A .
2 0096 A.
P7P59I
*^^ 1^ V *
27^05.
0.
0.
1113.
69069.
0.
9152.
17A16COO.
                                                        3000000000. AVAILABLE.  75.00* CAPITAL,   0.0 t  0
                                                                                   ~ ~        CAPITAL
                                                                                                T5553152.
                                                                                                11556000.
                                                                                                12509250.
* KFMOVfeU
A3. 50
2O. 85
15. 1A
51.38
	 70.37
77.31
55. 76
72.62
0.0
28.36
40. 1A
99.30
~ ' 9.77
7A.D9
37.2B
53.77
	 A5.31
68.06
5A.31
A7.C-3

16^9A
63.04
59.91
3C.79
45.18
83.27
1A.34
25.25
U'.97
23.37
24. Al
2';. 31
26.12
62.37
27. 9A
27.36
100.00
43.30
6.37
3C. 33
52.17
13. f 6
69. 17
17.65
27.51
33.57
A*. 71
A7.61
30.32
64.56
0.0
0.0
A. 37
35.62
0.0
54.45
62.36
# RtMOVFO #
99
4t-
62
99
""-• 327 * 	
106
22
14
0 "":"
b5
179
IB
' 30 	
344
126
2A9
ice "••""
59
107
69
- 33 ---
25
101
112
61
142
26
109
1 8 -T
56
9A
1A
2A6
89
50

'T"~' 155 "~
6
351
9
203
A9
5A
273
::;"• 47 ^:r,i
36
... 183 ., ,
59
28A
65
31
0
. ::: o .: ::
2
25 : :
0
2 •••;•
5A17 6
TOTAL
135
60
71
115
353-—
117
33
16
I "*
110
210
30
34 —
359
148
261
126 -
76
130
PO
40 —
38
109
115
73 .
151
30
115
20 '-
79
123
?3 „
273
122
54
295 _
181 ^
6
430
17
2A9 ~
53
70
294
72 "
71
200
6b
310
79
34
0
3
6
36
0

316
           e «  -—3
              OtM
                                                                                              ~3B5951232.~"
                                                                                                25202960.
                                                                                                35900208.
                                                                                                 9121500.
                                                                                                      0.
                                                                                               12V657'»OA.
                                                                                                637377AA.
                                                                                                3511H720.
                                                                                              "  6?7°000.'
                                                                                                2973750.
                                                                                               3690966A.
                                                                                               5AA31A2A.
                                                                                            ""'136AC500.
                                                                                                9528750.
                                                                                            ;i_ 77845088.
                                                                                               AA603184.
                                                                                            T" 26929964.
                                                                                               3V53C38A.
                                                                                                2A12750.
                                                                                                      0.
                                                                                                      0.
                                                                                                1000750.
                                                                                               32096192.

                                                                                            :~  22087501
                                                                                             2901912320.
                ."4
                                                                                               AA2A9088.
                                                                                               32AA3AAO.
                                                                                              ' 27A19952.
                                                                                               A706318A.
                                                                                               20A81728.
                                                                                               21337A56.
                                                                                               A7073712.
                                                                                               57h2A;2A.
                                                                                              120391196.
175t6000.
6A9L3856.
 AA30250.
111B7750.
 3135750."
2f015A56.
                                                                                              3ASr!l70»JR.
                                                                                               61720272.
                                                                                                223A250.
                                                                                              15320150A.
                                                                                               A0390976.
                                                                                               2217«2A8.
                                                                                              12902nPBO.

-------
Table 18.
•JF/JinvAL IM n^DFR OF INCHFAStN'i CAPITAL
1

3
' 4
5

7
' B
' 9
10
11
'12
13
14
1 c
L ^
*16
17
IB
19
70
it
<%• 4
22
73
24
?5
,27
29
30
T?
j c
33
34
35
37
i n
J O
a a
~ T
41
42
f. *l
*t J
44
45

46
47
•43
T <*
4Q
^ ^
sn
1 * 3
*)U
«>» ™
Al. A 1AM A

A1 1 7'1M A
ARKANSAS
CM IFfCWIA

C IN "IF C TiryT
OR A.MRf. '
ntSTrflCT OF COLUMBIA
TLn1} j n /\
GC1«C, I A
I QAH 1
ILL INOIS
I -NT I A N A

KANSAS
KCN TUCKY
LOIJISI ANA
M M r J F

"lA^ SACMUSFTTS
M 1C HI •", AN

M ISSIS SIPPI
MISS I'l^l
MHNTA^A
NEVADA
NfH HAMPSHIRE
f\; c j •.( c x I C T
NR-J YTRK
N')-
6L6. 23991. 191253. 966-H8. 462847. 11314250. 80404. 330357. J12509J 119565. 249093. 240594. 105439, 1055H72. 29 Q 00 3. 281319. ll'>466. 11339't. 203012. 10176. 3'M002. 22426. 225506. 885222 . 78293 . IOT0653. 6342H. 33700. 0512B7. 63c/22r lTj5inI 47^940. 41 333. 510101. I 110261 S2243>. 23300?. 133903. 135252. 42762. 0. 5175. ?5454. 250043. 0. 16806. 27927936. BOO ftfMGVED 127040. T042. 5C710. 51848. 1242365. 150064. 28369. 22927. 0. 4B8721. 212661. 11240150. 9949. 311/74. 110441. 183751. 65950. 186099. 169135. 55239. 93771. 67956. 217169. 90'109 . 61650. 104531. 8982. 4J247. 5663. 50496. 263316. 22725. 329769. 229777. 24907. 300235. 126947. 63922. 339335. 11462. 1/3976. 392 JO. 77574. . 4H1977. 23863. S007 . 229723. 149717. 110040. 63913. 29513. 9821 2433. 121658. , 0. • 9152. 18711472. 75 lUVt-rUf «v* REMOVED 55.78 28. '» I 19.10 65.00 78.90 83.91 60.86 95.57 0.0 50.55 45.95 99.35 12.37 81 .86 41.82 58.80 55.16 75.03 70,30 52.38 8.98 22.73 77.20 78.71 54.37 50.25 88.26 15.34 25.25 22.39 29.75 -• 29.02 30.24 36.23 73.91 35.27 38.46 100.00 53.46 8 .40 36.25 94.79 15.21 77.67 24,45 31.04 36.91 ' 51.98 59.83 34.49 67.06 0.0 18.97 9.56 48.65 0.0 54.45 67.00 \ 1 1_ «OL C 9 f -> * * KEMUVED * no 51 65 107 337 109 24 15 0 94 189 20 ~ 31 350 133 - '- 253 115 64 116 75 35 28 105 113 65 145 27 111 18 60 102 —- 15 255 97 51 2/0 165 6 375 " 10 215 51 5 8 285 52 41 137 62 300 69 32 0 1 } 28 0 2 5697 TOfAi 135 60 71 115 353 117 33 16 1 110 210 30 34 359 148 261 126 76 130 88 40 3d 109 115 73 151 30 115 20 79 123 23 273 122 54 295 181 6 430 17 249 53 70 294 72 71 200 68 310 79 34 0 3 6 36 0 4 6316 33o95824. 16134000. 16778992. 24204672. 518088704. 33902944. 44525200. 20258992. 0. 176503952. 85504208. 45362208. 8154000. 230327648. 60061280. 45834656. 36477680. 63053904. 2/835440. 28561424. 64454192. 78824208. 152723792. 53347392. 23766000. 82376030. 5465250. - 14585250. 3135750. 35710448. 290357248. 6381750.: 463332864. 81100976. 2834250. ' 203908912. 53642656. 22175248. 172534752. 15280500. 62483472. 3913500. 4879/152. 72675824. 18553488. 12265500. 104413056. 578B2672. 35335856. 51015616. 3296250. 0. 750000. 1903750. 43548688. 3860246016. \
-------
                  r!- Of-  INCM
U1
   1   ALACAMA
   2   ALASKA
   2   ARIZONA
   4   ARKANSAS
'   5   CALIFORNIA
   6   COLORAOO
   7   CINNhCTICUT
   ft   DfLAWARt
L  9   DISTRICT OF COLUMLIA
  10   FLORIDA
.  11   GEORGIA
  12   HAWAII
:  13   IDAHO
  14   ILLINOIS
  15   INDIANA
  16   10.VA
.  17   KANSAS
  18   KENTUCKY
,  19   LOUISIANA
  20   MAINf
i  21   MAKYLANC         .   ..
  22   MASSACHUSETTS
  23   MICHIGAN
  24   MINNt :.f *
*• *• & *•' ^t
250043!
o .
16B06.
27927936.
Table
NFFD , i
bf'D K il'il' VI.
164378.
5??94!
7976fc.
1450015.
l'-4V04.
34024.
?2C127.
0.
585028.
322475.
11256621.
27(46.
372514.
152991.
93929!
206161.
211537.
65514.
614956.
105211.
27R417.

15224l!
9T93.
65320.
5663.
87270.
365796.

85?. 11 4 1
33700 !
6FC'2 ? .
415114.
255 24 3 !

"35193!
1 1 V2 1 .

175126!
i ift i?7.
A * C* A <- • *
29533.
f»-
v/ •
•^ >. -i ^ *
171039!
0»
9152!
22012032.
19.



!>9V9990t»2C. AVAILAhLE. 75 , OOJ CAPITAL; C/.O t 0 6 M
D * RLMUVtU # RbMOVtD « TOTAL , 	 CAPITAL^ 	 OtM.
72.18
39.5O
. 19.70
100. OO
' 02. OB
86.6?
72.99
95.57
0.0
60.51
- 69.67
99.49
34.63
97.81
?7.93
. 72.15
	 * ' 7C.56
82.77
87.92
62.10
' '." .,:.... 58.24
35.19
98.97
97.94
67.90
73.19
97.21
20.35
- .:.:' :.:: 25.25
38.70
41.32
46.09
""""..." 78.13
60.99
100.00
49. ?8
""" 61. 89
lOf'.OO
t5.39
, 14.43
•".-' . 53. IB
94.79
43.58
88.02
. •/.•. 29.82
40.7?
61. ?8
74.8«»
95.23
62.68
69.06
o.o
18.97
«>.56
68.40
0.0
54.45
78.82
12 1-
67
115
345
112
28
15
0
102
201
24
32
355
139
	 257
12?
70
127
'.~T §7
33
loe
i LA^
^" 68
140
29
113
18
68
113
18
r-sr 265
109
54
176
6
404
12
•~ •": 230
51
.. 64
	 ,.... 291
. .u, , 5 8
51
191
65
" 308
74
32
0
;:.:-.;•" i
3
31
2
6003
60
71
115
353
117
33
16
1
110
210
30
34
359
148
261
76
130
88
~ 40
38
109
1 15
151
30
115
20
79
123
23
273
54
295
181
6
430
17
249
53
70
294
"Trr." 72
71
200
68
310
79
34
0
." ' : 3
6
36
O
6316
2530H720.
21082464.
36969*32.
"-•—" 754F56704. ~~
4 ft 6 0 2 c' 28 .
65921184.
20^56902.
" 	 o. '." '•"••
i 2524096P8.
• 12744f624.
69203920.
-:. '. ~r: r.~ i o 20 a ? 5 o . ; ',:77."*~.^!
3/944354)4.
84548768. .; :
,_„., 70112128.,
9?72b36o!
40565104.
4091 h400.
" ' T" 92P07V36. : .""T
123074192.
229186272. :'
864?2384.
"T" 33710992, ;-——-«.
12BB72320.
9045750;
,T 2313t75o! ••-.-..— .^
5A672624.
43480064O. ',"
9777000.
7""—~" 685586944. y-7%
121533408.
4634750. ->\
30?7?l?tiO.
C035H352. ~~"'~','~!*?
2217524B.
259401104. ~ -.•--
2294699?.
93357136. T"' ~T^

74275360. ., 7r:
99756PCO.
""~I"T. "27?27184. •'" "T2
19211232.
156610032. . .„:„
76781904.
	 T0740064. 	 '
79920592.
3296250.
O.
750000. •••--—•-:
1°OH750.
.: 62B23680. " '..""."
0.
2208750. r :~"
5675237376.

-------
o\
PP--nvAI IN fTtoeR OF INCREASING CAPITAL
STATE TOTAL BUD

2 ALASKA

4 ARKANS*S
5 CALIFORNIA
ft CO! OR A DO
__ 7 CONNECTICUT

9 DISTRICT OF COLUMBIA
10 FL1RIOA
11 GFORG IA
'12 HA mi " " 	 ~ 	
13 IDAHO
14 ILL INOIS
15 IMOIANA
fl6 IOWA
17 KANSAS
18 KENTUCKY
*20 KM NE
21 MMYLAN9
2? MASSACHUSETTS
23 MICHIGAN
? 5 MISSISSIPPI
7 f> M t S S !1 ' 1 R I
27 MONT\NA
^28 NE'^^ASKA
''9 NEVADA
30 NCW HAMPSHIRE
31 \'C4 JFRSFY

34 N'"« TH CA»OI IN A
15 NT'TH DAKOTA
~}f> OHT n

*x o n^c^'iv'
39 PENNSYLVANIA
41 SOUTH CAROLINA
42 SJ'JTH DAKOTA
43 TENNESSEE
45 UTAH
46 V^rc MON T

•48 WASHINGTON
4" V»c PUERTO RTCO
•56 TUIIST TERRITORIES
57 VIRGIN ISLANDS
10TAL
217 743.
20312.
265S09.
797^3.
1574681.
178838.
46*i 16.
23091.
191253.
966J18.
462847.
11314250. "
B0404.
330857.
2640-74.
3l?509.
. 249093^
240594.
105489.
i:)55872.
299003.
231319.
11 >>66.
1 1 3 3 04 .
20R012.
10176.
321002.
22426.
225506.
385222.
78293,
1090653.
634218.
33700.
3512S7.
3 30(171.

S34303I
4 7V 940 1
41333.
510101.
670519.
118026.
? Q ? 78
522*19 ^
233002.
183908.
1.15282.
42762.
0.
5175.
25454.
250043.
0.
16306.
27927936.
Table 20.
NFFD , t 8000000000. AVAILABI.Ei rr>75.00|
B'JO REMOVED S REMOVED (K REMOVED * TOTA
202829.
13721.
65262.
79768.
1551307.
157989.
38256.
22927.
0.
655280.
444776.
11272694.
73383.
373398.
200325.
252308.
106956.
219481.
240596.
30603.
901534.
142098.
281320.
11J090.
89000.
153659.
9H93.
65320.
5663.
101096.
394122.
56787.
958780.
472590.
33700.
6636'34.
311078.
68922.
531750.
4*805.
41*927.
39230.
330909.
620260.
53838.
14113.
432932.
220199.
18391>.
129959.
33173.
0.
982.
3025.
180338.
0.
15703.
24124176.
89.06
48.46
24.58
100.00
98.52
88.3'4
82.07
~ 	 95.57
0.0
67. 7«
96.10
— r— """* 99.63
91.89
98.04
75.85
	 -"-" 80.74
89.45
38.11
100.00
76.41
35.38
47.52
100.00
- 97.94
78.49
73.87
97.21
20.35
25.25
44.83
44.52
	 72.53
87.91
74.52
100.00
77.96
94.25
100.00
83.77
32.82
86.45
94.79
64.87
99.96
45.62
48.21
69.55
-76.46
100.00
70.14
77.58
On
.u
18.97
11.89
72.00
t\ f\
...... 0.0
93.43
86.38
131
58
68
115
349
114
30
15
0
106
206
-— :-" 27
t3
7
143
	 259
130
85
38
35
	 109
70
149
29
113
18
118
21
270
117
54
292
180
6
420
14
239
' 51
67
293
63
58
194
•- — 66
310
76
33

4
33
... 	 . f\
\i
3
6154
1>5
60
71
115
353
117
33
16
no
210
•-*•- 30
34
359
148
	 261
126
76
130
88
40
38
109
	 115
73
151
30
20
79
123
-* ^ j
122
54
29!>
18 I
6
430
17
249
53
70
72
71
200
	 68
310
79
34

6
36
..... 	 . n
\J
4
6316
00* CAPITAL,   0.0
TOTAL      CAPITAL
	         68274464.
            33671200.
            30397456.
            36969632.
          1022730496.
            61551664.
            84835408.
       	  20258992.
                   0.
           324204544.
           169864848.
       1	  95669888.
            13058250.
          . 426763264.
           115219984.
       	  90856368.
            64982128.
           117701840.
            46904080.
       —-   56231136.
           127509680.
           154199184.
           317386240.
       -—-  86*22384.
            43910992.
           164872320.
              9045750.
       	  22388976.
              3135750.
            69695120.
           555346688.
       	  14355750.
           885140992.
            165834352.
              463*250.
       	401264128.
            102613072.
             22175248.
           343935232.
        	   36003240.
            12348*576.
              3913500.
             97999344.
        	 126989280.
             37493400.
             25560208.
            207428512.
       	   97444400.
             65201552.
            100345328.
              5264250.
                    0.
               750000.
              3377250.
             81348656.
       	         0.
              5430000.
          7392022528.
                                                                                                      X 0 t M
                                                                                                             OCM

-------
ui



RlNUVAL IN t'KPEX CF 1NCRE /> S7 Mf. CAPITAL

1
2
3

*~ 5
6
7
S
IT 9
10
... 11

r 13

: 15
It
r 17
ie
IV
20
fe 21
22
: 23
24
r. 25
26
K 27
2P
. 2V
30
r.' ai
32
r 33
34
: 35
36
; 37
36
39
40

' 42
43
44
* 45
46
47
46
7 49
5C
1 51
52
"53
54
55
56
" 57
TOTAL
MATE
ALAtAMA
ALASKA
ARIZONA
ARKANSAS
CALIFORNIA
COlOkALK!
CL'NNICIICUT

DISTRICT CF COLUMBIA
fLORTDA
GttJRGIA
HAWAII
IDAHO
ILLINOIS
INDIANA
IOWA
KANSAS
KENTUCKY
LOUISIANA
MAINE
MARYLAND
MASSACHUSETTS
MICHIGAN
MINNESOTA
MISSISSIPPI
MISSOURI
MONTANA
Ml- fiR^k Sf A
NFVAL-A
NtW HAMPSHIRE
NLW JERSEY
NFW MCXICO
NEW YORK
NORTH CAROLINA
NURTH DAKUTA
OHIO
OKLAHOMA
CRK-L 0 b t> 7 .
« 64 094.
31?50V.
1 1 9 5 6 5 .
1 4°bf*3 .
240594.
10 t>'»Bf'.
1055P.72.
?V90()3 .
281319.
115466.
113394.
2CP012.
1017C.
3? 1O(>• r^
LOl, K'-MHVtD
i 20C (>1 .
I ? 7 2 1 .
(, ' i ? ( 2 .
7 '.76 P.
1572572.
If 6329.
" 1' 7 5 7 .
22927.
0.
656197.
445560.
11204043.
73RB3. :::"•

2 5 P ' 2 * .
25230E.

J2867 ?'.
240^96.
6T438 .
901534.
146465.
281320. •
113090.

l4'3659r
9B93.
6 E 3 2 f ' «
1 **"'-*> 7 .
10t'744.
427399.
67P44. '
10^0522 . -

337001
7f01"3.
330075.
66°22.
562 1P7.
A4F05.
4366O2.
4 1 ?3? .
3t:3109.
6 ? 0 *- 2 0 .
63^C5. :'..:','
16F6fc.
44£620.
254644.
183V12.
151456.
42762.
O.
3477. I".
3025.
186276.
0.
15703. '^
?4915?32.
J99744H. AVAILAF
X Rf-MHVfL' U RE
9 1 . f> 5
48.46
24.58
ICO. CO
99.87 '"'
93.01
83.14
95.57
0.0 "
67.87
96.27
99.73
" \91.89 .—
99.91
97.81
60.74
~T- 100.00 ;^."

icoldo
.__., 78.15,.^ 	

48^98
100.00
97.94
"r~ 85.11 "•"'"
73.87
97.21
2O.35
""" 6».39 " 	
48.22
48.28
86.65
;: 99.99 :
91.18
100 .00
92.24 i,w_._
"" 100.00 '• ^
100.00
U8.56
32.62
90.97
99. b6
71.18
100.00
..: ; 54.15 .:":::..
57.62
72.11
CB.4?
100.00
81.74
100.00
0.0
'17. 67.2O,1**I:^
11.89
;..••.:• ..?*. so .
— o.o .^__
L? ,
MOVtE
133
5B
68
115
350
115
31
15
0
107
207
28
33 '
358
144
259
126
74
130
86 ,
38
36
1D9
114
71 f
149
29
113 	
19
74
120
22
272 "..
120
54
293 .r

6
425
14
242
5?
68
294
65
60
195
67
310
77
34
.:?-•
4
34
o_,..
"" 89l2l 6203
75. nn? C/
' f» TOTAL
135
60
71
115
>-r .353
117
33
16
" 1 --
110
210
30
	 34 Tr~
359
148

— 126--^
76
130
88
"*"""" 40 ""
38
109
1 15
,,,„ ?3 .—
151
30

-- 20 •-
79
123
23
" 273 -
122
54
. 295
181 -~'
6
430
17
249
53
70
294
"::. 72 .:
71
200
68
310 :
79
34
,^_. 0 	
6 " "*
36
-.— i-
6316
                                                                                          CAPITALt   C.C ? 0 t H
                                                                                                 CAPITAL        -
OCM
                                                                                                  33<71200
                                                                                                1134180352.
                                                                                                  69426656.
                                                                                                 103941648.
                                                                                                  2025h992.

                                                                                                 361704448*
                                                                                                 10B7198t8.
                                                                                                  1305S250.'
                                                                                                 522304768.
                                                                                                 12721ot»f<4.
                                                                                                  90856368.
                                                                                                  77657120.
                                                                                                 135t26f32.
                                                                                                  469040HO.
                                                                                                  6?981136.
                                                                                                 I2750«fPO.
                                                                                                 17707^-176.
                                                                                                 317386240.
                                                                                                  664Z23E4.
                                                                                                  50735984.
                                                                                                 164872320.
                                                                                                   9045750.
                                                                                                  65201552.
                                                                                                 117895328.
                                                                                                   7514250.
                                                                                                         0.
                                                                                                   3377250.
                                                                                                .94604896.

                                                                                                """5A30000I
                                                                                                8297119744.
                                                                                                  49410736.
                                                                                                  £2703(156.
                                                                                                 645P71616.
                                                                                                  16478250,
                                                                                                1008278764."
                                                                                                 187*03072.
                                                                                                   4634250.
                                                                                                 429164032.
                                                                                                 116165568.
                                                                                                  22175248.
                                                                                                 381334272.
                                                                                                  36fCf?40.
                                                                                                 137793POH.
                                                                                                   91t3500.
                                                                                                 114264632.
                                                                                                 14'fi353760.
                                                                                                  42545&8B.
                                                                                                  26095696.
                                                                                                 2300031'04.

-------
TABLES 22 THROUGH 27

State BOD removals and sources controlled for cumulative
federal expenditures of $2, $4, $6, $8, $9 billion under
the priority of construction in order of increasing
pounds of BOD removed per dollar
                            158

-------
                                                 Table  22.
           T A r ('•
V£)
     5
     6
     7

   rs
    10
    11

   ;ji

    15
   rif
    17
    18
    19
   '70
    21

    ?3
                      f)F
Al
AU7TJA
A^< \NSAS
f AL f FfVrjI \

CONNFCTICUT
PFLAWARE
OfSTK ICT  OF COLUMBIA
FL DRinA
GFT^GI A
HAWAII
IOAHT
ILI  INJIS
1 NT I UNA
rnwA
KAMSA5
KFNTUCKY
LHIJI SI ANA
   : YLANH
"ASS\CHi)SFTTS
MICHIGAN
        M ? S S I" S S I F-
?7
r28
30
31
•?2
33
~\ 4
3 1
16
37
38
39
40
41
4?
44
'45
46
47
"£* f\
49
SO
5 1
52
53
54
55
'56
57
rOTAt
NHNTAMA
NFTRASKA
MFtf HAMPSHIRE
N'F V J F"3 SF Y
IVFW i^xfcn
NFtf YORK
NT( TH CAPHI INA
M01LTH OAKOTA
run
0F
UTAH
yr? Mn v T
V I •>. <~, I N I A
WASHINGTON
WFST V1T.IMIA
wr SC.T.NM N
HY^IMIMH
WA
-------
Table 23.
MMI
1
2
3
4
; 5
6
. 7
6
9
10
11
12
: 12
14
'. 15
16
17
If
19
20
' 21
22
... 23
24
-.. 25
26
27
in
IT. 29
30'
31
, 32
?.. 33
3*»
. 35
r 36
r 37
36
39
4O
'' 41
42
43
44
• " t f
' 45
46
47
40
;' 4«,
50
51
52
! 52
54
55
56
:. 57
DVAl it! MFUft (IF ULCRUMM- 1 HP/TOI
STAlfc 101AL ;>(J[..
ALALA.'iA
ALASKA
AK] ZLIf.'A
ARKANSAS
CALIFORNIA
CL'Lf'kAOO
CC'MNLCTICUT
CFLAWAKt
DISTRICT OF COLUMBIA
FLOK1DA
Gt-OkMA
hAWAI 1
UAHU
ILLINOIS
INDIANA
IOUA
KANSAS
KtUTUCKY
LOUISIANA
MAlNt
MARYLAND
MASSACHUSETTS
MICHIGAN
M1NNISOTA
MISS 1SSIPPI
MISSOUHI
MONTANA
N F b R A S- K A
NLVADA
MtW HAMPSHIRE
NEW JLK.SE.Y
N£H MtXltr;
NEW YORK
NORTH CAKOLINA
NLRTH DAKOTA
CiHlG
CKLAHCHA
Of^GON
PcMNSYLVANIA
RHUOE ISLAND
SCUTH CAROLINA
SOUTH fiAMiTA
TfNNEiStE
TfXAS
UlAH .,
VERMONT
VIRGINIA
WASHINGTON
wm VIRGINIA
WISCONSIN
WYOMING '
WAKE li,L/fll>
AMLR1CAN SAMOA
GUAM
PUF.KTO RICO
TRUS1 TfcRRITORIHS
VIRGIN ISLANDS
P27/4 3 »
i:t-::12.

7 ^ 1 1 ^*
I* 7AoM I
1 "7 f ^ fe ^ H
166161
? 3 C> v 1 .
1 V I 2f> 3 .
9t 6 4 i, v .
1O c 5 1 72 .
JlO^(|f,-jf
2 ft 1 3 1 V .
1 1 5466 .
1 1 — • 3 ^' 4 .
2 (^t 0 1 2 .
10176.
321002.
^22426.

f ' 1* 5 i.' 2 2 .
7fi £ 9 3 •
1G9C653 .
6 34 ? 1 P .
33700.
851287.
330071.
6E922.
6341-03.
13|.510.

4 1 2 f ' P .
5H101.
620M9.
116026,
2 ^27? .
622439.
2f.'t 002.
1 1 ? V 0 1" •
1 F* 282 .
42762.
0.
5175.
25454.
250043.
O.
16K06.
TOTAL 27927936.
LLAR , t r.OOOOOOOOO. AVAILABLE,
PfHi KMPVED * RFVHVfO * KFMtiV
I ( 3 4 f ' C .
^ ''0 1 •
1«?6V4 .
73 f1 1( ^'
1411763I

3 151 7T
17079.
o. ~ 	 '
62A2P1.
3f5664.
ii*?r??o3»
f. ^ ^£ *•) 9
?3V776.
1 V07C>1 •
17542t*.
t'5r'40« " ~ "' ""
19S979.

£•*? ^"^ A »
522120. •

2276501
85.026.
tf-560. . " .
1 1 C !> V fc *
9103.
ri 055 .
5663. . ..'. . . "3jr!°r./ .
1*0794.
5S4f'04.
^5604.
BB&852. "" ~~'^".'
401040.
2A645.
557395.
20P247. ' .' "
6P922.
449413.
7^~ 7£ 7 .
3 j20t4 *
?^b If 8 .
?f 1 17 9 ,
535231.
46456. . _ I" .,_Z
10612.
300359.
190848.
1'7{|C'23.
110159.
25256.
0.
o. ;:: .
0.
177755. „ ; „
0.
8773. "' "*~"T
22146400.
71.75
30.02
4.78
9?.' 3
69.65

67ltl
71.19
0.0
64.57
79.00
99.46
62.49
89.21
72.23
56.14
71.79
78.68
79.25
59.09
4*/.45
2t.24
80.92
73.64
. 58.70
53.17
89.45
6.56
25.25
66.87
66.06
32.70
80.76
63.23
7<».07
65.48
63.09
100.00
70. PO
56.25
69.19
92. ?2
51.20
86.26
39.36
36.25
48.26
66. ?7
75.05
59.46
59.07
0.0
0.0
0.0
71.09
0.0
""52.20"
79.30
» ?
9
12

191
76
14
11
' - 0
3W
97
9
15
285
77
131
, . : "55
28
52
45
V."."" 2

63
09
r r—- ^5
b6
22
21
, 18
16
39
4
T: vi 2 e

L 29
61
7 29
6
199
3
r, - -- 6?
30
16
159
.r. 9
18
78
^~~- 38

22
- 14
0
: : o
0
7

•*^*n*v -•« v ^
2822
75.00J CAPITAL, 0.0 t D £ H
ro * infAL CAPIIAI
135
60
71
115
353
117
33
-,- lft

110
210
30
34
359
148
261
""126
76
130
88
"~ 40
38
109

"~" 73
151
30
115
32~ 20
79
123
23
7T 273
122
54
295
' 181
6
430
17
'TT' 249
53
70
294
rr 72
71
: 200
68

79
34
O
T 	 3
6
36
0
. •» 4
6316
25451120.

750750*

" " " " 3C6-3 lC
-------
Table 24.
RFMHVAL IN ORDER OF OECR

1
2
3
r* 4^
5
6
7
r 9 :
9
10
It
r\ 2
*13
• 14
'15
f i £
I 7
18
'19
' 21
i 22
23
*"24
"75
26
' ?7
r28
10
V31
^32
' 31
• 34
15
T36
37
39
T40
4 1
47
43
*~44
45
46
47
f-A O
j *» I »
49
50
S I
r5?
"53
•54
55
r 56
' 57
TOTAL
STATT
ALA JAMA
rtl A SKA
ARIZONA
ARKANSAS
CALIFORNIA
COL OR A 00
CONNECTICUT
PFLAVARE
OISTR ICT OF COLUMBIA
FIORIOA
GCORG I A
HAWAII
IDAHO
ILLINHS
INOIANA
IOWA
KANSAS
KFNTUCKY
L'JiJISI ANA
MMYLAND
M'^SS'VCHUSETTS
MICHIGAN
MINNESOTA
MISSISSIPPI
MISSOURI
MONT AN 1
NFU'USK'V
NT^ HAMPSHIRE
NCW J F ^ S P Y
NGrf MEXICO
NPW YORK
NIHTH CAROLINA
MIRTH DAKOTA
O'-ll 0
OKLAHOMA
PP\JN SYLVAN I A
RHIT^ ISLAND
SO, IT! CAROLINA
SOJTM OAKOTA
TPNNF SSFC
TEXAS'
UTAH
VFR M'JNT
VIRGINIA
WPST VIRGINIA
WISCONSIN
WYOMING
W/KP ISLAND
AMERICAN SAMOA
GUAM
PtJFRTO PICO
TRUST TEPRITORIF.S
VIRGIN ISLANDS

SING UDOfnOLLAR , t 4000000000. AVAILABLE, 75.00* CAPITAL. 0,0 Z 0 C H
TOTAL *ai BOH REMOVED « KEMUVED * REMOVED « TOTAL dApiTAL DIM
227743.
23312.
265509.
79763.
1574681.
170833.
46616.
23991.
191253.
966818.
462847.
11314250.
30404.
380857.
264094.
312509.
119565.
249093.
240594.
105489.
1055372.
299003.
281319.
115466.
113394.
208012.
10176.
2242&I
225516.
815222.
7829J.
109J653.
634218.
33700.
351237.
330071.
f il O "J *)
*t •") * £ £ •
634803.
116510.
479940.
41398.
510101.

H8026I
29273.
622439.
713002.
H3903.
1 5J 5? 8 2 .
42762.
0.
5175.
25454.
250043.
0.
16806.
27927936.
131105.
6501.
12694.
77705.
1502391.
157710.
32977.
22927.
0.
629452.
406293.
11265614.
70238.
367447.
209717.
241362.
97723.
206939.
212913.
71271.
844959.
84452.
263994.
85026.
80020.
174445.
9833.
"> 1 TICK
i 1 U55.
5663.
170146.
660179.

9605921
489202.
32428.
663784.
253549.
63922.
506545.
97160.
379307.
39213.
261179.
572650.
65324.
14534.
379311.
196507.
156476.
115598.
25258.
0.
0.
0.
203851.
0.
8773.
23692800.
79.56
30.02
4.78
97.41
95.41
85.39
70.74
	 " 95.57 —
0.0
65.11
87.78
99.57 ~
87.42
96.48
79.41
	 77.23 	
81.73 ~
33.03
80.49
— 67.56 "
80.02
28.24
93.84
	 -" 	 73.64
70.57
83.86
96.63
— -••-•- f. C^/i
O 9 JO
25.25
75.45
74.58
42.19 -~~
38.07
77.13
96.23
77 .97
76.82
100.00
79.80
71.17
79.03
94.74
51.20
92.29
55.35
49.64
60.94
•68.23
85.08
62.39
59.07
-•••- 0.0
0.0
0.0
81.53
	 "---• 0.0 	
52.20 '-•
84.84
66
9
12
94
255
14
~"~ 1 5
-- o
39
116
12
20
328
88
™ 156
"87
42
73
- 53
8
7
77
89
47
106
27
•y f
4LL
18
26
58
•- 5
167
33
34
131
43
6
266
4
93
48
16
194
15
19
89
40
275
30
14
0
0
6
10
0
1
3583
135
60
71

?I!
' 16
1
110
210
	 30
34
359
143
	 261
126
76
130
	 88
40
38
109
. 115
73
151
30
113
20
79
123
~" 23
273
122
54
295
181
6
430
249
53
70
294
72
71
200
68
— - 310
79
34
0
3
6
36
	 0
4
6316
' 33620800.
8442000.
750750.
- 	 24545872. 	 — '
520893696.
27200896.
40054480.
-"TIZTT 20258960. 	 T-'-i^i
"*""' '" 0. 	 "* '
133460816.
85875376.
	 45380192. 	
814^750. "*'•
239430464.
54633632.
— ^ 	 39092000. 	 	 -,
- 36124944.
59141088.
27766320.
	 " 	 27414656. 	 TT!
62492944. *"
35205728.
161935232.
...- _,_..__ 3&^316^8« ' ~^*^''' ' "" •*<*
24823488.
84801216.
6U51750.
~" -'r™~ 707250. " ^'jiET
3133750. ~-~t^**>i-
37306336.
286741504.
— — 	 5829000. 	 1" — T
463066880.
81118336.
3338250.
202285520. 	
53480736. "
22175232. ^ ,,
171207968.
	 15573750. 	 •—" —
62608944.
3853500.
30350448.
	 72854992. 	 -•—
18707232.
11631000. •>-.--„,«.
108205072. '
— •— '• 46644608. 	 • • • ••
35068688. 	
44360912.
1453500.
. 	 	 r»
y. - — —
0.
0.
43342480.
	 T- 	 •*-- - - " " 0« -^-w— — mr*r9~-m
1751250. ~
3671270400.

-------
Table 25.
ElfHOVA^ORDER OF. .MCREASING^OD/DOLLA^ ^t^
E~.l ALABAMA :.
2 ALASKA
L_., 3 ARIZONA
4 ARKANSAS
El. 5 CALIFORNIA •
fc CCLLKADO
K£.7 CONNECTICUT . ' .
6 DELAWARE
•19 DISTRICT OF.CQtUMBlA-
10 FLORIDA
L, 11 GEORGIA
12 HAWAII
H. 13 IDAHO
14 ILLINOIS
C 15 INDIANA
16 IOWA
Bs 17 KANSAS . . .::; ".:; ;:/. ',."'
18 KENTUCKY
E. 19 LOUISIANA
2O MAINE
tL2l MARYLAND 	 	 .-~.~.
22 MASSACHUSETTS
L. 23 MICHIGAN
24 MINNESOTA

26 MISSOURI 	 	
£127 MONTANA . • . . .
2& NEBRASKA ,, .,
•29 NEVADA L^L-—l~L~
30 NEW HAMPSHIRE
CL 31 NEW JERSEY
32 NFW MEXICO
C-33 NcW YLKK .L. .....
34 NORTH CAROLINA
.^ 35 NORTH DAKOTA
3t fHIO
K.37 OKLAHOMA . ...:1 .."'..-
38 OREGON
C 39 PENNSYLVANIA
40 RHODE ISLAND
d*l SOUTH CAROLINA . ....'.
42 SOUTH DAKOTA
L. 43 TENNESSEE
44 TEXAS
II 45 UTAH - - ...
4t VEKMUNT
t- 47 VIRGINIA
48 WASHINGTON . .
C-49 WtST VIRGINIA
50 WISCONSIN
C_51 WYOMING 	
5i HAKE ISLAND
tlii AMERICAN SAMOA
54 GUAM
I. 55 PUERTO RICO
56 TRUST TERRITORIES
C 57 VIRGIN ISLANDS
TOTAL
??7743.
28212.
265509.
7176B.
1 - 7468 1 .
1 7 6 b 3 b .
46616.
. 23991.
191253.
966hlb.
462647.
11314250.
8C4C4."
r b Ofa 5 7 .
2t.4094.
312509.
1 1956-5 .
24SO93 .
24C594.
1 054 f^9 .
i_ .1055872 .
?99003 .
P81319.
' 115466 .
113394.

101761
321002.
.^.,22426. .
225506 .
, B85222.
7^2*^3 *
: : 1090653.
634218.
33700.
U51?fa7.
"„.: 330071.
68922.
634803.
136510..
.. .. _' .1 479^40 •
41 3b8 .
S10101.
620519.
. '.. . 11 t'O26 .
29278.
62243°.
288002.
_ 18390C.
1 B528? .
. . 42762.
0.
5175.
/ *« 4 £> ^* •
250043.
0.
let 06.
27927V3'..
204196.
8501.
237333.
79767.
lf.6? 984.
17i' 6 67 .
39V09.
22927.
0 .
872370.
435807.
1126TM4.
7 ? 4 6 3 .
377907.
2 5 ? 1 4 5 .
3 D3 5C'6 .
1 1 4 fi i 3 .
218^63.
23F-i73 .
f- h6 ? 3 .
E 6*7 i>5 6 «
2 ? 22 1 0 .
27PZ21.
113047.
B 9 V 1 1« .
195400.
9K02.
21055.
« . £663.
1^1307.
764347.
5 S ? V ^ *
1051 H7t.
567474.
33700.
/ fi O 9 2 4 .
. 2E7343.
6f'922.
56(3*?5.
1O^ i'79 .
422349.
39?13.
365036.
tlf<362.
hO'^0 *? •
21097.
4 £0^76.
? 4 2 0 1 9 .
17V113.
157358.
36836.
0.
2*1 9t .
1?475.
22C199.
O.
I5"i.''4.
2^6 81^40.
         5999996926. AVA1LABLF,  75
               RF MOVED
                 B9.tt
                 30.02
                 69.39
                 100.00
                 99.45
                 Of.. £5
                 Ofi.M
                 95. T7
                  0.0
                 90.73
                 94.16
                 <*o.57
                 90.12
                 99.23
                 95.4f<
                 97.15
                 96.03
                 87.1:7
                 99. Oil
                 b4.01
                 &2.19
                 74.32
                 98. «3
                 97. °0
                 7".1">
                 93.94
                 97.11
                  6.56
                 2! .25
                 84.83
                 66.35
                 70.63
                 96.40
                 B9.4h
                 10O.OO
                 P7.04
                 fc:7.C5
                 100.00
                 89.54
                 77.12
                 8 P. 00
                 94.74
                 71.56
                 99.65
                 ti'.i5
                 72.06
                 7?. 36
                 84.03
                 97.39
                 «1.93
                  86.14
                   o.n
                 46.; 73
                  5;. "4
                 91.26
                  91.96
KEMOVtD #
9
34

333
100
If
(i

161

3M*)
124
107
47
II1-
66
12
14
106

5b
130
2!>

18
3°
67

21t
61
54
1''7

f.
3fc4
f
140
411
20
26?

27
134
55
301
39

O
1
1
ir.

•f
476.'
60
71
115
31.3
117
16
1
110
210
30
359
146
126
76
130
£8
40
315
109
115
73
151
"0
115
?0
79
li'3
23
?73
122
f»*»
2^5
Ibl
6
430
17
249
53
70
294
72
71
200
68
310
79
34
0
3
£>
36
U
4
6316
    CAPITAL,   0.0  Z  0 C M
TOTAL      CAPITAL
            4646.S376.
             844^000.
            2537Vb72.
            3t.c<9520.
           7^9373184.
               .
                    0.
           I-64!.4f'T6U.
           119:-77792.
             453801V2
             K1107M>.
           360211200.
             4311136.0
            123636688.
            2227S636U.
              t t7<750.
               7C/rr,0
              312'.7!.0.
             11011500
             2217f?l-.2
            2574t'7776.
                    '
              3(53500.
            109ib7792
             27152656
             H-'-'(i44rO
            1J.13V7328
              42:20000.
                    0
                                                          0.
                                                    497i.-J.-00
                                                 561173TS92

-------
cn
CO
    13
    10
   T20
    21
    25

    33
    34
    30
    40
    41
    42
    4T
    44
    45
    46
    47
             IN rRDFR  OF
        ALA
        CALIFORNIA
     CONNECTICUT
     OFI A-.JARE
     DISTRICT  OF
     FL.TUDA
     GFTRf, I A
     HAM*I I .
                     COLUMBIA
        ILLINOIS
        INTIAMA
     KANSAS
     KCNTIJCKY
     LTJISIANA
     MASSACHUSETTS
     MICHIGAN
     •1JVNESOTA
     MISSISSIPPI
     M JNITANA
     NETR'VSKA
            JF?RSFY
            CAROLINA
            OAKUTA
        OKLA10MA
                I A
            ISLAND
            CAROLINA
     StUTH  JJAKUTA
     TFNNESSFF
     TTXAS
     UTAH
        WASHTNOT3N
 SO
 51
'52
' 53
 54
^55

 57
TOTAL
        MISC )
        WYOMING
        Wi565 .
249)93.
240594.
105437.
1355872.
?99003.
231 319.
115466.
113394.
208012.
1017o.

??550&I
885222.
78293.
1090653 .
634213.
33700.
351287.
3*0071 .
6T922.
(>34303.
1*6510.
479940.
41 388 .
510101.
6>0519.
119026.
29278.
•62243-).
15)3938 .
18520?.
42762.
0.
5175.
25454.
250043.
0 .
16306.
27927936.
Table
fUJD RF MOVED
221250.
24006.
246446.
79767.
1571937.
177515.
42645.
22927.
0.
942975.
460280.
11299330.
72463.
380197.
26U53.
311397. -
119338.
237203.
240594.
95351.
867856.
239303.
281318.
113047.
105361.
204762.
9882.
228097.
5663.
205166.
816579.
67518.
1089775.
610697.
33700.
827597.
323268.
6*922.
597990.
117163.
463458.
39213.
430849.
620256.
94857.
24903.
5i)5596.
2478 19.
183907.
173690.
38763.
0.
2496.
13475.
238887.
0.
15703.
26719984.
26.

8000000000. AVAILABLE,
* REMLVED « REMOVED
97.15
84.79
92.32
100.00
99.83
99.26
91.48
95.57
0.0
97.53
99.45
	 99.87
90.12
99.83
93.89
	 99.80
99.81
95.23
100.00
90.39
82.19
80.20
100.00
	 97.90
92.92
98.44
97.11
71.06
25.25
90.98
92.25
	 86.24
99.92
96.29
100.00
•-•.••-• 97.22
99.45
100.00
94.20
85.83
96.57
94.74
84.46
99.96
80.37
85.06
81.23
. 86.05
100.00
93.74
90.65
0.0
48.23
52.94
95.54
0.0
93.43
95.67
115
20
43
115
348
113
26
15
0
91
192
16
22
356
___ 136
124
130
75
12
109
-- 113
66
L2a
11
51
96
11
268
79
54
255
172
6
372
202
48
28
291
32
40
149
	 57
- 310
56
2o
I
19
--:- 0 •
3
5415

75.00| CAP!
* TOTAL
135
60
71
115
353
117
11
1
110
210 	
34
359
148
- 261 — "-
126
76
130 _
40
73
151
30
115
20
79
123
23
273
122
54
295
181
6
430
17 	
249
53
70
294 .
72
71
200
68
310
79
34
0
3
6
36
0
4
6316

TAL, 0.0 X 0
CAPITAL
63314240.
32501168.
29866304.
36969520.
1027144192.
66553184.
91733168.
20258960.
0.
347591936.
172032576.
-* 92149424.
10110750.
456734720.
120253616.
	 88184784. "
73681728.
124860512.
46903648.
53997568.
71892672.
144636688.
317385728.
84343968.
47878416.
170255232.
63/6750.
31096464.
3135750.
72771408.
56375^264.
146/1500.
903191040.
161708528.
4634250.
- 409584640.
1076854&6.
22175232.
346192396.
	 28994976.
126505872.
3853500.
88272624.
126771120.
36230128.
25423408.
198713968.
91491536.
65200464.
103423232.
5203500.
0.
922500.
2925000.
85807424.
	 0*
5430000.
7436824576*
                                                                                                                06M

-------
    Table 27
R L Ml

i
t
$
4
5
6
7
8
9
10
11
12
13
14
15
16
17
IP
19
20
21
22
23
24
25
26
27

29
30
31

33
34
35
36
?7

39
40
41
42
43

45
46
47
48
IV/L IK t;r.MR ( f ntcfu
1.
462847.
11314250.
1 0404.'
3 b C li 5 Y .
2640V4.
317509.
1 1°565 .
249093.
2 4 0 S 9 4 .
1 ('5'» 8*; .
1 0 ^ 5 fc 7 2 .
299l'03 .
J8131V.
1 1^466.
113394.
iCfcM?.
10176.

"224261
i'2f - Of .
6 b bZ 22.
7 8 i* ° ^ .
1090653.
6?421t>.
33700.
8M2B7.
330071.
t~ *^ V 2 2 .
6. 34 103 .
1 ^>f *> 1O.
47V°40.
413PP.
510101.
c ro5iv.
llt-O/Jt .
2 9 i' 7 li .
62243''.
*? P P ( *0 X
LLAR , J-
unt^ F.tMflVfD
??? C.;7V .
?! 321.
2^6446.
79767.
1573004.
177875.
43020.
?2<527.
0.
V 5> t f • *? ^ •
461558.
11304312.
79151.
^ t'O^C'A •
261879.
312155.
119564.
2? 720 3.
2405S4.
°b ?5 1 «
100<^0f3 .
271495.
2H1 118 .
113047.
109177. ..
2C4762.
96-82.
242 KiO.
1S.337.
?1US08.
6 3*? 176.
71 44b .
1090475.
«.?F 704.
33700.
«?422?.
33C071.
t -J; V? £ •
606r>18.
1?« 733.
^71770.
41332.
47'??.f-0.
6^0 1> 1 b •
102046.
26127.
50D596.

 II  V. .  _  _
 M  WAKE ISlANLi
 JI--  AMLklCAN SA^
 54  C-UAM
 i!»  fUtKTU KICO
 56  TRUST
 57  V1PG1N liLAMDf
TOTAL
   42762.
       0.
    5175.
   2T454.
  250043.
       0.
  . m-ofr.
27927936.
   427*2.
       0.
   13475.
       0.
   J5703.
27104944.
D7440. AVAILABLE, 7f>
RfMOV-D
97.91

92182
100.00
09.89
99.46
92. f 9
95.57
0.0
99. 1«
99.72
99.91
98.44
99.91
99.16
99. H9
r 100.00 ~
95.23
100.00
90.39
94.91
90. f»0
100.00
97.90
"6.28
98.44
97.11
75.64
" 60.39
93.26
94. GO
91.26

99l 13
100.00
98.01
100.00
100.00
95.54
92. P4
98.30
99.86
93.98
100.00
. 86.46

8ll?3
86.05
100.00
97.50
100.00
0.0
48.23
52.94
95.54
0.0
93.43
97.05
# RF MO Vr 0 ii
121
33
43
115
349
115
27
15
0
101
197
18
27
358
142
..._-.... 2.58

55
130
75
	 ' 20

109 '
113
"•' ' 68 '"• ' '
147
28
41
........ 19 .„-
54
102
14
271
97
54
279
"' 181

389
9
" 222 "
52
35
294
-. 	 41 "
46
140

310
50
34
0
1

19
0
' 3
5646
.00* CAPITALt P.O ? 0
TMTAL
135
60
71
115
353
117
33
16
1
110
210
30
34
359
148
261
126 r
76
130
88
40
38
1O9
115
73
151
30
115
20
79
123
23
273
122
54
295
181
6
430
17
249
53
70
294
72
71
200
68
310
79
34
0

6
36
0
4 "
6316
CAPITAL
7203619?.
36611080.
?9t-. f t 304 .
36969520.
1160167424.
72463920.
96 ?SA 160»
2025H960.
0.
392399B72.
163620064.
1051b4*-16.
""*" ' 17P2r'?16.
522303232.
135023328.
' 9451*2272.
----•'" 77656720.
124P60512.
4690"*t 48 .
	 	 53°°7f«68..
^^,r— ~. ^ ^37 c ^ 3 6B .
!P96366fci8.
3173f<572e.
84H43968.
55573408.
170255232.
2C'1 12 •
19b713968.
91491536.
6520^464.
120472976.
7514250.
0.
' " 922500.
2925000.
85807424.
0.
5^*30000 •
8350772736.
                                                              C H
                                                                 OCM
                                                                  "7
                                                                  "F.

-------
                        APPENDIX E

             MUNICIPAL CLASSIFICATION ANALYSIS

RELEVANT CHARACTERISTICS

The objective of the classification scheme is to place
communities in the nation into categories representative
of different plant design and financing situations and to
relate these to environmental, community, and individual
impacts.  Our working hypothesis was that there are sets
of characteristics that affect (1) decisions made by cities
regarding choice of process types and project size in
treatment plants and (2) the fiscal and distributional
impacts resulting from these decisions and the particular
financing program in effect.

The plant size decision is affected by existing and pro-
jected flow:  functions of sewered population, growth rate,
industrial load, and existing treatment capacity,* and by
administrative cash flow and debt burden.  The fiscal impact
and the distribution of the cost burden over  individuals are
a function of existing debt, tax base, local  financing
mechanisms, and distribution of family income and wealth.
On the basis of these considerations and data available,
the following list of community characteristics"1" was com-
piled:

a.  population;

b.  population growth rate;

c.  per capita income  (or median  family  income);

d.  revenues per capita;

e.  debt per capita;
      *   For  a  discussion  of  the  implications of growth on
      treatment demand  and traditional  design rules,  see
      Muhich, A.  J.,  "Capacity  Expansion  of Water Treatment
      Facilities,"  Ph.D. Thesis,  Harvard  University,  1966.
      +   See  "Definitions  of  Class  Variables" below.
                             165

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f.  percentage of population sewered;

g.  value in existing treatment capacity; and

h.  industrial hydraulic load as a percentage of total
    present hydraulic load.

The classification scheme is used to develop profiles of
communities as background to estimating environmental and
financial impact of municipal decisions made in response
to the 1977 and 1983 treatment regulations and to alterna-
tive financing programs.

Availability of Data

Sources of data for the above list are as follows:

(1)  Population data are taken from the 1970 Population
Census.  Unfortunately, such data are not as readily avail-
able as one would expect; just to retrieve populations of
places under 25,000 population requires manipulation of 62
reels of tape (1st count, file B).  Populations of places
over 25,000 are available from the City and County Data
Book* computer tape and populations together with counties
are listed in that book for places of over 2,500 inhabi-
tants.  There is no readily available source of population
data  (to say nothing of other data) for places under 2,500
inhabitants.  Because of data retrieval costs, classifica-
tion analyses therefore were performed only for places of
over 25,000 population.

(2)  Population growth rate data are available from the
Census Bureau and the Bureau of Economic Analysis; these
include population projections.  For the purposes of the
classification analysis, 1960-1970 population change data
were used from the City and County Data Book computer tape.

(3)  Income data are available from four sources:

      (a)  Regional Accounts Division, Office of Business
          Economics (QBE);

      (b)  Internal Revenue Service  (IRS);
     *  Bureau of the Census, Social and Economic
     Statistics Administration, U.S. Department of Commerce,
     "1972 City and County Data Book," May, 1973.

                            166

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     c.   Census Bureau;  and

     d.   Sales Management Survey of Buying Power (and other
         private services such as National Planning Associa-
         tion and Market Guide).

QBE and IRS data are not useful to this study;  QBE data are
on a where-earned basis; IRS data are on a "selected major
metropolitan area" and zip code area basis.  Sales Manage-
ment* income data are updated annually, give "effective
buying income" (essentially disposable income)  by income
class, and are available on tapes.  Census Bureau data,
however, can be used more conveniently and inexpensively
as described below.

The 1970 Census of Population has estimates of 1969 income
(wages or salary, net non-farm and farm self-employment,
retirement including social security, public assistance,
interest and dividends, net rental, and other income
excluding receipts from sale of personal property, capital
gains, lump-sum insurance or inheritance payments, or pay-
ments in kind).  These are based on a 20 percent sample for
places.  Manipulation of the 104 reels of  tape  (4th count,
file C), however, would be expensive and time consuming.
The alternative chosen is use of City and  County Data Book
data for places over 25,000 population.

(4)  Revenues  per capita data come from the Governments
Division of the Census Bureau.   Two series are  relevant:
the quinquennial census of governments and the  annual
governmental  finances review.   The latest  Census of Govern-
ments for which all data are available is  the 1967;  some
data for the  1972 Census had been published by  mid-February
1974, including those dealing with property values, but
financial data on revenues, expenditures,  and debt were not
available in  time to be used in this study.  The  latest
"Governmental  Finances" is  for  1971-72, published  early
1974, which deals with  cities above 25,000 population.

The City and  County Data Book gives the following  financial
data  for cities above 25,000 population,  based  on  1969-70
data:   general revenue  total; intergovernmental revenue;
taxes total;  property taxes; sales and gross  (tax)  receipts;
expenditures  total; debt outstanding and  expenditures on
      *   Sales  Management  Survey  of  Buying Power,  Part I,
      July 23,  1973,  and Part  II, October 29,  1973.

                             167

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education; highways; public welfare; police and fire; and
sanitation including sewerage.

Data for places above 25,000 population in on the City and
County Data Book computer tape and these data for municipal
revenues, expenditures and debt outstanding were used in
the classification analysis.

(5)  Debt information sources are the same as for revenue
data described above.

(6)  Information on percentage sewered, existing treatment
capital and industrial share of load is contained on the
EPA 1973 Survey of Needs* computer tape.  It has been
possible to utilize these data in the classification ana-
lysis.  Two important qualifications must be mentioned,
however.  Previous work with these data shows that they
contain a large number of unuseable records and that the
units of analysis, treatment facilities, are not necessarily
comparable with the municipalities in the City and County
Data Book.  Consequently, contingency table analyses for
these three characteristics are conducted using population
data and municipality definitions from the Survey of Needs,
not from the 1970 Census.

Classification Methodology Adopted

Because of the difficulties and expense associated with
using the data sources described above, the analysis is
made using the City and County Data Book computer tape and
the 1973 Survey of Needs tape.4"  The classification metho-
dology adopted is based on the assumption that items  (b)
through  (h) in the above list are functions of population
size, and that within a given population group significant
variation exists.  To verify  these  assumptions,  simple
      *   "1973  Survey  of  Needs  for  Municipal  Wastewater
      Treatment Facilities,"  Form EPA-1,  Environmental
      Protection Agency.

      +   The  City  and  County  Data Book  tape excludes cities
      under 25,000 (56 percent  of the population)  and the
      Survey  of Needs  tape  contains a large number of unuse-
      able records.  Results, therefore,  must be viewed with
      these considerable  limitations in mind.  The conclu-
      sions,  however,  are made  all  the'more dramatic by this
      exclusion of smaller  communities  with their higher unit
      costs of  treatment.

                             168

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contingency table analysis* is performed on the following
sets of variables:"4"

a.  Population  (1970) vs. Growth Rate  (1960-1970);

b.  Population vs. Percent Low Income;

c.  Population vs. Per Capita Expenditures;

d.  Population vs. Per Capita Debt;

e.  Population vs. Mediam Family Income;

f.  Population vs. Per Capita Revenue;

g.  Population vs. Percent of Families with Income "less
    than" X Dollars;

h.  Population vs. Percent Sewered;

i.  Population vs. Excess Treatment Capacity; and

j.  Population vs. Industrial Share.

The existence of a significant relationship between popula-
tion and one of the other variables is determined on the
basis of the Chi-square statistic.  The nature of the rela-
tionship is suggested by comparing the expected cell entry
aid the actual cell entry.  The expected cell entry is a
function of the marginal distributions of population and
thS dependent variable (e.g., population growth rate) and
the total number of observations.  The actual cell entry
is the numSer of municipalities that fall into a certain
iS11 defined by population size dependent variable value.
The idlntilicationof a pattern of expected cell entry and
actual Sell entry differences may lead to some understand-
?n« nf the nature of the relationship.  The approach does
not lead lo ^ ^ambiguous interpretation, but it is
helpful in identifying ways in which community size may be


     *  For a discussion of contingency table analysis and
     the use of the Chi-square statistic in such analysis,
     see  for example, Hoel, P. G., Introduction of Mathe-
     matical Statistics, John Wiley & Sons, Inc., New York,
     1963 (3rd edition) pp. 252-255.
     +  See "Definitions of Class Variables" below.
                            169

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 related to the other variables.   The variation of a parti-
 cular characteristic for a given population group can be
 ascertained from the percentage-of-row-total entries for
 the population group.

 The contingency tables display,  in a discrete format, the
 relationship between the independent variable (in all cases,
 population)  and a characteristic or dependent variable,  e.g.
 growth rate.   Each row of a table represents a range of
 city sizes and each column a range of values for a particu-
 lar dependent variable.   For example,  in Table 28,  all the
 entries in the second  row are cities with populations
 between 25,000 and 37,500.   The  sixth column in that table
 contains all entries for cities  with a growth rate between
 zero percent and 5 percent.   The last two rows of the table,
 labeled "PERCENT" and  "TOTAL," are the marginal distribu-
 tion and total number  of entries in each growth rate
 category.   The right most column of the table, labeled
 "TOTAL," contains the  marginal distribution and number of
 cities in each population group.

 The cells in a table contain four numbers:

 1.   the percent of row totals or the percentage of cities
     in a given size range which  fall into a given dependent
     variable  category;

 2.   percent  of sub-table total or the  percent of all
     cities  in the sample which fall into a  given dependent
     variable  category;

 3.   expected  values or the  number of cities in a given size
     range which might  be expected to fall in a certain
     dependent variable category  if city size and the depen-
     dent variable were,  in  fact,  independent;  and

 4.   the number of cell entries or the  number of cities in
     the  sample  in a given size range and a  given dependent
     variable  category.

 For  example,  in  Table  28 the cell delineated by the second
 row  and  the sixth column contains  these numbers  for cities
between  25,000  and  37,500 with growth  rates between zero
percent  and 5 percent.   An examination  of this  cell indi-
cates  that 57.5 percent  of the cities  in this  size  range
have growth rates between zero and  5 percent.  Also,  20.5
percent  of all  cities  in  the  sample  are  in  this  size  range


                             170

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                                          Table   28.
                                                          VAMMI
                                      >IOX
                                             > f.*
                                                                                         >?CT






O1OOO
1
._ 	 _. '_ 	 	 	
.
.-w •»._-.. . ....^ . . w _...

, ., , .«.^™_ ,
O75OO
2

	 	 a 	 , . 	 M _ 	 	



•ococo
3
VA*f*>
^OPuLATltp**
	 .


<71000
~ *




I50000
7
VMItl
WUUT10N -
*•*•»» ^ « ^*
o*c etc
1 2
a-wu ..j-^-.. |
1
1
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1
I
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1 1 1- .1-1 ]
. . I I
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. , O.OI ., O.OI
1 1
I t
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1 p 1 1 IP t ' • I
I
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O.OI O.O
1
1
.(*
40.31 «b.?
I
1
40 i ei
31. 4T I 47.91
7.71 1 4.»t
ll-.Jl ><»..-
1
t
?? 1 37

34. 9X I 44.41
2.7t 1 3.4t
If-.f] >*.3
1
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i PI i f i i - p .I •
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4.5X I ».2f
1 23.31 4«.
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r 37 i 4j
i i i p '•' i.i i '
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INC INC.
7 »
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, 4.31 5.31 .
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31 71 .94
*_—• ___^i .. . -|
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1 I
1 t 1O.K
» I 11 ••»

                fpfHCtNT
urrt* ecu rtxrurts  AK« n»ctnr nt- HIM TOTALS
                     MrCCNT OF -U.-1ABLC TOT/kL
  ....    _      (XMCTKO VAIUCS
                                                                     10.3*
                                                                     ..  «S
4.2S
 3»
  l.St
.... t*.
 l.BS  IbO.OS
..19	125
                                        4.616*		  SttWIf 1CAKT »l .044 WITH  30 OTfiMfS OP FKIt-OM .	
TA.tU
TOttL fiOhttH OF initTS  1« T*tC»
MIMk«« fir l-NIIi nHlTTfC, OtlF TU
* DECREASE
"INCREASE
                                                171

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and have growth rate within this range.  In addition, if
size and growth rate were independent, 104.6 cities would
be expected to fall into this cell, whereas the actual
number of cell entries is 169 or more than expected.

The other important numbers in the tables are the Chi-
square statistic, level of significance and degrees of
freedom.  These appear in the row labeled, "CHI-SQUARE."
In Table 28, for example, the Chi-square statistic has a
value of 44.616 with a significance of .044 for 30 degrees
of freedom.  In other words, if growth rate and population
size are independent, the probability of obtaining a Chi-
square value of 44.616 with 30 degrees of freedom is ,044.

In the interpretation of the contingency tables, the first
number at which to look is the significance of the Chi-
square statistic.  If it is less than  .01, it is reasonable
to assume that there is some relationship between popula-
tion and the dependent variable.  If, on the basis of
significance, a relationship is found, then examination of
the expected values and the actual cell entries suggests
what the nature of that relationship may be.  For example,
if the cells in the northwest portion  and southeast  portion
of the contingency table showed positive differences
between the actual cell entry and the  expected cell  values
and the cells in the northeast and southwest showed  nega-
tive differences, then it could be said that there was  a
positive relationship between the  independent and dependent
variables.

Results

The Chi-square  statistic  is  significant at  under  the .001
level, with degrees of freedom  ranging from 24-48,  in  all
but four cases  (see Table  29).   The  exceptions  are  for
growth  rate  (.044,  30), percentage of families  with income
greater than  $25,000  (.015,  42),  percentage of  population
sewered  (.422,  30), and percentage of industrial  waste flow
 (.002,  30).   Of this  group  the  only  truly  insignificant
relationship  exists between community size  and  the  percen-
tage of population  sewered.*
      *   Population figures in the 1973 Survey of Needs are
      known to be unreliable.   Since it is that set of
      figures used in the construction of this contingency
      table,  the unreliability of the data may be the cause
      of this result.
                             172

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             Table 29.   CHI-SQUARE STATISTIC


                                Level of      Degree of
Dependent Variable            Significance     Freedom

Growth Rate                       .044           30

Percent Low Income Families      <.001           24

Median Family Income             <.001           24

Percent with Income 3000         <.001           36

Percent with Income 3-5000       <.001           24

Percent with Income 5-7000       <.001           24

Per Capita Debt                  <.001           30

Per Capita Revenue               <.001           36

Percent Sewered                   .422           30

Excess Treatment Capacity        <.001           24

Percent Industrial Share          .002           30
                             173

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With the highly significant Chi-square statistic in most
cases, comparison of actual and expected cell entries
suggests the following for places of over 25,000 popula-
tion :

a.  growth rate is inversely related to city size
    (Table 28) ;

b.  the percentage of low income families in larger cities
    is higher than in smaller cities  (Table 30);

c.  more small cities than expected have high median family
    incomes  (Table 31) ;

d.  smaller  cities demonstrate a greater spread in median
    family incomes than larger cities  (Table 31);

e.  smaller  cities show a greater range in income than
    expected and larger cities show a  smaller range than
    expected (Tables  32(a) through 32(c) ;

f.  larger cities have a higher per capita debt than smaller
    cities  (Table 33);

g.  smaller  cities have lower per capita revenues than
    larger cities  (Table 34);

h.  there appears to  be no  significant relationship between
    percent  sewered  and community size for communities  of
    over 25,000 population  (Table 35);

i.  smaller  cities tend to  have more  excess  capacity than
    larger communities  (Table 36) ;

j.  more small communities  than expected have  a high indus-
    trial share and  fewer moderate  size communities  than
    expected have a  high  industrial  share  (Table 37) .

An  examination of the percentage-of-row-total  entries  shows
clearly that all of  the characteristics, while depending on
population  in  some  fashion, demonstrate rather significant
variations within given population  groups.
                             174

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                                              Table  30.
                                                             VAKItl
                                                             t If* INCrmt FAM1UIS

                                                               <60    <70     <«o

'
<• • ooa
1
	 	 ..._. .__._. _.
— - 	 . .


O7340
... 	 	 	 2. 	 ..

ooocio .
VAII9I
WUJLATION
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•4



. 	  I! 0000
7 " "
WPULATITH
FtfttlNT
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72.7t 1^2. TT
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     Ctll 'NTKIFS «Mf  CFRONT (IF K'lkl TOTALS
                      HP.CCMT dF SUO-TAKLE TOTAL
             	     tXPttUO VALUCi
CHI-SkliAME	
                                       JS«.2t»...   .. .SXCMIMC»NCe UMCEK .001 KITH 2* MCllfFS Of
T07AI KUM«f* » UNITS  10 TAtlC
                                                  175

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                                        Table  31.
                                                VAM(IU)

<2!000
1

07SCO
	 . 1 .. _

< 44000
3
VAtlVI

	 .. . ..4 - 	
<1 7 loon
7
0.0
c
. 0.0
n

n.o
b

o.n
0
0.0
.0
0.0
0
o.o
0
7.11*1.

0.1*
1 .
. . .-
3S.7*
JOI

11.2*
144.

1B.S*
1M
'
'
».«*
. 73 .
'
4}
'
ll.lt
»4
               ..WAI
 O.Ot    0.2*    1.1*   47.5*   44.M    J.7*    O.OX  10O.M
. O       J     tfc     401     3X4      11     .. 0   . .1+4
      CILL
CHl-I.bUtl-l
                          rr or K»
                             Of iUb-TAtLE TOTAL
                    • Mf'CTfl) VALI»S
                                                    SICNiriCANCI UNbfH  .001 NITH 24 MCRfiS
lABlf  WMAAT

TO1AL  MU«k'» W UNITS IN TAILF
                                              176

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                                          Table  32(a).
                         40t



< 2 5000
1
	 	 	



O7SCO


_.. ... .. _
_ <»ccoo . .
3
VAM9I
POI.LATIG*


<7»oeo
4



_.... .. <1CCCOO
*




OSOOOO
4




MSOOOO
T
V*^l*l
POPULATION
PIRCtftT
TOTAL

.
0.2


0
31.61
11.31
..-*'»»

«S
19. ••
^.'•X
3!..B
3C
74.4*
4.5*
»*.2

3d
37. Of
r.fi
17.4


17.71
0.9X
14.6


a
1.1*
o.i*
21. •


1
_____
23./I
t*«>
If'O.Pt
C.I*
0.5


1
41.2*
14.71
. ui.r


51.35
9.*t
77.3
7*
47 4T
«.«(
7J.2

7*
4«.)3
4.*?
Ji.J

37

3.t»
<9.<


3?
»7.l\
4.PT
44.1


49
,
'6.VX
396


0.2


0
16.91
6.01
66.3

SI
20.»t
3.f>Z
33. V
32
JO.9t
3.7;
34.4

31
I7.*«
!.%«
16.1

13
JO. 71
2.3C
13.9


IV
42.»i
4.7S
20.7


40
_____
22. OZ
1(6


O.I


0
S.OT
7. 61
17.8

24
s.et
1.1S
9.1
v
• IV
o.«:
».2

s
I.Jt
'l.lt
4.4

1

O.SX
3.T


4
•*.JX
o.st
• *.*


4
1 "'
5.91
. so..


o.o


o
J.3*
0.81
5.0
,
7
2..T
O.3*
2.6
4
1 4T
0.4T
2.6
-
3


1.2

0


1.0


0


t.*


O
-
1.71
.»*
--.«_.]
1
]
a. .11


o


O.4

O


0.2
0

0.1X
O.2

1


0.1


	

0.1


o


0.1


o
" •
o.is
1


0.0


o
^™ ™" "^™"

0.4

o


0.2
n

0.1Z
0.7

t
"

O.I




0.1


o
— — -^_—

O.I


o
— — -
• O.IS
.... .1
• ••« «

o.o


0


0.0

o


0.0
0


o.o

0


0.0




O.A


o
•••—•MM*

o.»


0
"
O.OS
.. .. 0
"

t.u


0


0.0

o


0.11
0


0.0

0


O.P




o.n


0
"

O.I)


0

O.OS
. 0.




o.ix
1 .




301



1ft. 71
154



IR.it

	 -


r -.9i





7.5S
63




II. IS
94

IOO.OS
•44
 urn* ctLi  LNTRIIS *«t Pint INI OF NOM
                       M*CtNT UF SUU-TABLE TOTAL
                       IX»ltTkC. VMUES
JPMI-SCUMC.
	»*.**«««•     SICNtFICANT.I UMOflt..OOI HITH 3* Dt6«f*i OF FRtfOOH
 TAkLf SUNHAfcV

 TOTAL ritNtkk  I* UNITS I* m.Lt
                                                    •44
                                                 177

-------
                                       Table  32(b).
                                                       VAM11I
                                                       t UIIH iw.iwt  3000-4999*
0-»t S-l('t 10-lit I4-7OX 2O-J4J ?4-1OX 3O-1»t 34-40S >4O«
173
...

	
<240OO

	 . 	 . 	 _^___ .



<37400
.. 	 _ 	 	




150GOO
7
VAM9I
POPULATION
MOn.Ot I
I O.lt I
0.21 0.41 O.A


. . 0
26. Zt
9.4Z
-S1.7

79

13. 6T
.2.St
It. 1


2t
14. IT
i.tr
2*.««

72

21.3:

12.9


It
-'
9. 5*
0.71
lO.fc


b
.»^___
I. It
O.lt
It.


I .
I
1 I 0
J9.9t 1 ?4.«
14. ?t I *.*t
.137.31 .93.1
1
1
120 I 75

46. «T I 31. ?X
«.it I 5.7t
70.21 47.4
I
1
72 I 46
50. tX I J0.1X
v.4t 1 5*£t
71. 7\ +H.V
T
I
79 I 47
. i 	 I —
46. »t I 70.01
l.tiX I l.b<
34.21 23.2
I
I
42 I . 15
• n i |
44. 4« t 44. 4t
3.3X t 3.3X
2f.7J l«.S
I
I
If 1 2B
I 	
4T.7T T M.H
5. It I 5.71
42.91 29.
I
1
1 I 43 I *»
1 1
4 5
I
I
0.11 'o.n
.1 ....
I
0 I 0
8.31 I 0.71
J.OT I 0.2T
17. >I . 1.4
1
1
29 1 2
	 ,y 	
7. ax i o.t;
1.4t I O.lt
(.91 0.7
1
1
12 I 1
4.M I 0.*X
O.bt I O.lt
9.11 0.7
1
I
71 »
-I
?.7t I '
0.7X 1
4.4T O.4
1
1
2 t ..,„ .0
•| 	
Let 1
n.it I
3.71 0.3
I
I
1 1 O
^
2. IX I
0.21 I
4.51 . 0.4
1
I
z i o
-I
6


0.0


0


. . 0.0

o
«__«•


0.0


0


0.0

o
-
"


0.0


0
.M— «~_


0.0


0
— — —


0.0


o
___
T •
t
1
O.OI O.f>
I 	 .
I
0 1 0
1
1
o.oi . o.o
I
1
O I 0
1
1
I .
O.OI fi.O
I
I
. 01 ..0
1
... 1
I
0.01 fl.ft
t
1
0 I 0
I
t
I
O.OT O.O
T
1
..01 0
!••••• II —I II
I
1
O.OI 0.0
1
..I '•"
01 0
1.
I •
1
O.OI n.p
I
I
01 0
11 -1
*


0.0
_ - -

o


_ 0.0

o
^»^— —

-
o.o


o


O.O

o
.. . .


o.c
'

. 0
— —


o.c


b
MMMM»»


0.0


o
— — —
TOTAL



	 . ..
O.I*
1


	 . _.
39.71
301





l(.2t




. n.sx
1S6
. .




ft.9t
	 75...





7.3t
43





ll.lt
94

PHlCtNT 17. 2X 45. At JO. 9t S.MS O.AI O.Ot O.OX O.Ot O.Ot 100. Ot
	 _ 	 TOTAL. .. 145 385 261 . 4» .. .* . .. 0.. 	 0. .. 0. O . •»» .
 UPMK CUt fNlMI! *«r  PfkCCMT Of  HOM TOTALS
                      PEICEMT OF  SUU-TACLE TOTAL
                      tXPECUO VALIItS


^HI-SCUAME	  _73,732»»*
S.IGMIFICA-KE unot* ..ooi WITH 24 ncwttEi OF
 TASK


 TOTAL NUMblK OF UNITS I* TASU
                                              178

-------
                                        Table  32(c).
                                                        X WITH IkCUHE 9000-6494*
                         0-»*
                                                                                          TOIAl
 UW» CCU ENTRIES ARt PERCEN7 OS Row TUTALS
                     MkCtHT UF SUfc-IAklt 1MAL
	   -  .  . -  .....  fXWCTfO VALU»*
                                      »*.7*7«»*
                                                   SIM1FKMU UNWR .Ml UUH 74 HEMMS Of MtEDO*
 TOTAt NUMtfH Of UHIli IN t*Ur
                                             179

-------
                                      Table  33.
1
1
O7SOO
	 	 . 2
3
<7W>00
	 	 4. 	
	 -.-••-
 150000 	
7" '
¥*»(*)
KPUIATIPN
TOm
.<•«
93. OI 45. n
I
I
• 7 1 49
S.M.TT i 2*.n;
».5X 1 7. ft
44.71 21.6
1
I
4* I ?l
55.6X 1 31. W
4.3S T 7.57
.17.61 !».?
t
I.
3* I *0
z!»; i s*3t
53.11 7».«
I
I
21 I 4J
P»K C»P1T
*750i <1OUO\
1 4
I
I
0.11 0.0
I
I
O J O
4.5X 1 1.1X
Lit 1 0.5X
77.41 . ».C
I
I
17 I 4
5.<>} 1 2.PX
l.lt I .0.41
12.71 7.8
I
f 1 3
6.4X I 1.3X
1.7X 1 0.2*
13.01 2.4
1
I
IP 1 2
1.3- 1 *.0-(
0.9X I 0.4X
6.71 1.4
1
I
71 J
9.5S I 3.2<
0.7T I 0.7X
5.21 i.;
I
I
61 •*
25.15 I 1.1X
2.9X I. 0.11
7.41 1.7
I.. ...
1
73 I 1
67 IS
i cnn
0.0
0
0.71
_.'U7
r
l.IX
*n.v
2
0.6T
o.tx
».(•
1
0.4
O
0.4
O
O.A
'A
t U«-| f
ff
O.P
0
l.IX
0.4X
- 7."
1
0.7X
O.U
1.1
1
n.it
1.2
1
O.f
O
0.5
O
1.IC
0.1X
(j.r
i
'0.7X
. . 4
                                                                  33.41
                                                                  li.wt
                                                                  19.4X
                                                                    7*
                                                                    A3
                                                                   11. U
ClLt
CHI-iltUK
                            or *PW TPT*l$
                            0^ SUb-TMlt 101 At
 TMLE
 TOTAL ncm.f* cr iwm in
.HW«M.Of..U«IT>J»«IlHC DUC TO BLANKS
                                            180

-------
                                          Table  34.
                                                 VAM(11)
MWILATIim
                                         I 24.71 I
                                         I  7.7« I
                                      4.91   11.11
                                      .   I .     I _
                                         I      1  ll.lt
                                      T I   22 1    •*
                mem?
                TOTAL
».*«  ?*.TT
 I*    2>*
31. U
 2M
II. ft
        4.0S
         4(
                9.SS
ll.lt  lOO.Ot
          TH1K.ITV A*f MhCFNT tit KPM TC7AIS
                            ff SM-lAblC TITTAl
                             VAIMS
                                                   SIWIlf-KA^CE UNKt .001 WITH  U KCMtS Of
TAUI
            ft UftlT* IN
      M IM1TI ONITT^K HOC  Wl
                                             181

-------
                                      Table  35.
                                            V«K(II
                                            rfy f.rm


                               SJ-*0(  &0-70C  70-11C
          »>COCO
Vl«( I)
POPUHTION
          uciaoo
          tiMOUO
          ... 7	

I
AS2.7
152
6.4*
10. 7
e
7.71
4
10.51
6.*

It
7.91
J.I

*
12.11
J.d
4
13. 11
7.S
9

^
2.51
41.0
**
3.0
0
3.81
1.3

1.8

3
2.61
C.9

I
o.«
0
*2.l
3

3
2.31
42.2
41
3.0
1
5.81
1.2
3
I.S

0
0.9

0
6.11
O.tt
2
3.41
2.1
3

4
3.21
«.».»

6.41
4,6
8
7.T1
1.9
4
2.8

J
1. 31
t.4

2
12.11
1.2
4
4.61
3.2
4

5
5.14
•J1.4
1-,
6. 41
8
3.41
. 2.T
2
2.6(
4.3

I
5.3<
2.U

2
A. 11
l.T
2
. .'»•«•
..

( . 	
6 TOTAL
78.21 1
lllli.t\ . ... '.......
1
l_ M-ZI . ,
UO'I 1 im
78.41 1
97.11
I
1 5.T|
99 1 I7i
71.21 1
40.41 . ....... 	 	 	
1
37 1 52
• ••« 1
78.91 1 . '
SQ.m
I
I J-*'
6J 1 76
.«*_*«.• t
H.tl I ~ "
29.51
1
! 1.71
30 1 IS-
63.61 1
25.61 ...___
1 !.'*!
21 1 13
r.>.4i i
.. *T.5I 	 . 	 	 	 	
1
1 *.0(
63 i ar
CHI-;OU»»(
                TO Tit
                          U4
                                                        .3l	rt^l	100. Jf.
                                                       us    it,9<    zttr
                                      30.»7a
                                                                          10
T(JT»L IW«
-------
              Table  36.

~

Uiooo

~ 	 »'-

-"- -,„«.-•
- ...
V»Ve i i
WUL4TION
ucoaoo

iisacoo
	 . 	 A

•1*0000
• -.. ... ,
iiwi
OCF
1

0.3
0
0.0
0
. 0.3
0
... 0.3


_ O.tf
0
. o.o
-
0
0.9
	
.5CI

*
l.Ct
i 1 4, •)
190
10. »
li
. 4.6
..*4.S
.___ 	 .,

3.i
1
3.0
6
*.<•(
1.2

0-501


*>64.3
003
is.ai
47.5
*•
21.31
20.9
it
20 .M
2«.l


i-..j
21
Id. 21
13. 5
16
30.91
23.4

1*01
e*t6ss
4
iOU.l
-
JIM
in. 4
141
66.6
92.6

•f
37.61
4S.6
It
48.91
43,1
. :.
43
47.1)1
74.1

MUOI
f. ^CE^iS
5
14. TC
"It. 4
•>24
14.21
4S.3
4*
17.61
14.9
24
9.01
... .27. »

17
1«.4I
l«
14,81
12.9
li
13.21
22.3
2)
•. uoi " 	 "• — ••
ItCEJi
6 T<1T*1
11.21 I " ' ~ " 	
mi. 21
1
1144 I 6270 	
15.21 1
34.JI
t

2J.9I ..
I '
1 l.vl
H I 136 ~ 	 —
19.01 1 ' - - -
. 3J.il
J 2.61
36 t 189 	
12.-*! 1 ' 	 	 	
-( 	 _
12 l"~93 	 	 -
11.41 J " 	 " 	 	
15. SI
l \.n .
n i es 	 	 • 	
4.61 1 '" 	 ' '-• '• -' — - -•
; 	 .-Li—iff*, 	
1 I l»z 	
T-UC -~^l-^^itt^^^r-to^---iIit<-l?5i?t
                 183

-------
                                   Table  37.
                       0-404


                       1
IJ-20I


2
JU-nH  *0

4      i
,2»U«U

. _. U7JCO
iseooo ~~ ' '
	 j 	
	 4
VMI 11

itcjoao
I1SJCOO
.ISJCOO
7
_ ._, ., ,, ,. ft*1-**"
TUHt
33.11
41*. 3
4(id
43.71
sa.o
64
36.01
. 26.2
31
39.01
._36.0
46
21.91
-J
Ib
21.61
21.4
Jo. 9
3(t
2J.4C
A6I.Z
3S7
23.71
44.1
17.41
20.0
'
15
. 27.4
29
24. 7(
'
1*
24.31
16.3
17
27.31
2*.l
33
-Jil.il.
14. 7(
211.?
229
10.01
24.1
16
22.11
13.2
13.61
10.1
16
13.71
11.2
10
It. 71
10.7
11
14.01
U.)
ia
13.31
9.31
I'ld.T
144
11. 6<
14.1
22
11.61
a. 7
10
14.41
11.9
17
16.41
_..7.«
12
7.11
7.1
5
10.71
. 12.2
13
lfl.il
339 223
ui. ;
1 1/
4.21
11.7
n
. . 6.2
',
3.41
a. s
4
12.31
S.2
IS. 71
t.n
11
"t.7
n
15. HI
217. <•
244
7.»l
26.0
1*
7.01
ll. a
6
5.11
.16., 2
6
11.01
10.3
a. 6i
9.6
6
14 .0(
.14.6
ir
	 7.21 _, 13.71.
70.11
t»j»
., 	 	 	
190
, ...
1.91
•6
	
5. 11
U*
. 	 	 '. 	
3.11
73 	 " —
1.21
70
121
|tinti)|
2213
                                     S7.60)**
                                                SICtllflCANT AT  .002 KITH 30
                                                                               It*
_TOT»L
      Of
            3F W417> IN UOU _________
         LNirS OMIITEU DUi TO 6LAMS
      —	_ 2211		
              mis
                                     184

-------
Definitions of Class Variables

The variables used in generating contingency tables for
this analysis are defined as follows:*

a.  Population — (CCDB) total 1970 population, Item 303;
    (NS) total resident population 1972-73, Question
    16a{2).

b.  Yearly Growth Rate — (CCDB) computed from percent
    population change, 1960-1970, Item 305.

c.  Percent Low Income ~ (CCDB) percent of all families
    below the low income level, Item 368.

d.  Per Capita Expenditures —  (CCDB) per capita expendi-
    tures  (excluding capital outlays), Item 419.

e.  Per Capita Debt —  (CCDB) debt outstanding, Item 425,
    divided by population, as in (a) above.

f.  Median Family Income —  (CCDB)  median family income
    for all families, Item 361.

g.  Per Capita Revenue — (CCDB) per capita total general
    revenue (excluding interlocal revenue), Item 411.

h.  Percent of Families with Income "less than" X Dollars —
    (CCDB) percent of families with family income in 1969:

      (i)  less than $3,000  (Item 354)

     (ii)  from $3,000 to $4,999 (Item 355)

    (iii)  from $5,000 to $6,999 (Item 356)

     (iv)  from $7,000 to $9,999 (Item 357)

      (v)  from $10,000 to $14,999  (Item  358)
     *  Items are identified by "CCDB11 for items occurring
     in the City and County Data Book, Table  6, and by  "NS"
     for items occurring in the Needs Survey.
                            185

-------
      (vi)  from $15,000 to  $24,999  (Item  359)

     (vii)  greater than $25,000  (Item  360).

i.  Percent Sewered —  (NS) sum of resident  [Question
    16c(2)R] and non-resident  [Question 16c(2)N] population
    receiving collection from this facility  1972-73, divided
    by population  [as in (a) above], all multiplied by  100.

j.  Excess Treatment Capacity —  (NS)  ratio  of present
    design flow 1972-73 [Question 17a(3)] to total flow
    1972-73 [Question 17a(l)], minus unity,  all multiplied
    by 100.

k.  Industrial Share — (NS) ratio of  total  industrial  flow
    1972-73 [Question 17b(l)] to total flow  1972-73  [Question
    17a(3)], multiplied by 100.
                            186

-------
                         APPENDIX F

           EXAMPLE OF SIMULATION MODEL CALCULATION

 Consider the timestream shown in Figure 4-lc, for per
 capita municipal cost for Branch 12, biological treatment,
 with a 50 percent capital grant and 25 percent operation
 and maintenance grant.  The following demonstrates how some
 numbers on the case 1 curve, for 25,000 initial population,
 zero percent industrial load, and 1 percent growth rate, are
 calculated.  There are three sets of capital and operation
 and maintenance costs which must be computed:  S{P2); U(P2);
 and B(AP32).  in this example we will illustrate how the
 capital costs for S(P2) and U(P2) are computed as well as
 the first year operation and maintenance costs for S(P2),
 the first year per capita total cost (unsubsidized),  and the
 first year per capita total cost with a .50 percent capital
 grant and 25 percent operation and maintenance grant.

 BRANCH 12

      S(P2)   :  U(P2)   :  B(AP32)


 CAPITAL COSTS

 I-  S(P2)  =  5(30202.7)

         Q  =  (120 gpcd) (30202.7p)  =  3.624 mgd

      P.E.  =  (49) (3.624)   (200)   =  35518

8(30202.7)  =  (.00812)  (35518)'461  (3.624)'262

                           + .0125(3.624)*48

                           + 0.0575(3.624)<65

                           + 0.0224(3.624)*59

                           + 0.326(3.624)'54

                           + 0.015(3.624)'56

            =  1.425 + 0.023 + 0.133 + 0.048 + 0.653 + 0.031

            =  2.313

                             187

-------
Equal payment factor, 30 years, 6%
          •°6     =  0.0726
              30
Equal payment amount  =

      0.0726(2.313 $M)  =  $168,000


First year per capita capital  -


      $168,000  =  $6<65
       25,250


Tenth year per capita  (from  decision  1)   =
       $168,000  =   $6<08
       27,615.6      *
 2.   u(P2)   =   U(30202.7)   =  (0.122)  (3.624)'656


            =   0.2839 $M
 Equal payment amount  =


       (0.0726) (0.2839 $M)  =  $20,612


 Tenth year per capita capital (from decision 2)


       $20,612   =  $(K75
       27,615.6   •
                              188

-------
 Tenth year per capita capital (total)


       $6.08 + 0.75  =  $6.83



 OPERATION AND MAINTENANCE COSTS



 3.   First year O&M cost for S(P  )  is gotten using first
     year population 25,250:     z

       Q      =  120 gpcd (25,250?)   =  3.03 mgd

       Cost  =  (.042)  (3.03)*876

                     + (.0021)  (3.03)<452

                     + (.0095)  (3.03)*712

                     + (.0015)  (3.03)*530

                     + (.063)  (3.03)*706

                     + (.0089)  (3.03)*540

            =   0.1109  + 0.0035 + 0.0209 +  0.0027

                     +  0.1378 + 0.0162

            =   0.292  $M



First year per capita  O&M cost

      =  $292,000  _
          25,250   ~   511.56



4.   First year per capita total  cost (unsubsidized)


      =  $6.65 + 11.56  =  $18.21
                            189

-------
5.   First year per capita total cost (subsidized at 50%
    capital and 25% O&M)
      =  .50($6.65)  + .75($11.56)

      =  $12.00
                             190

-------
 SELECTED WATER
 RESOURCES ABSTRACTS

 INPUT TRANSACTION FORM
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Evaluation  of  Alternative Methods for Financing
Municipal Waste Treatment Works
          Russell J. deLucla,  Lewis M. Koppel, Daniel
F. Luecke,  Sandra Robinson,  Penelope Schaefer,  Douglaif
            S. Rtriii Du!e

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V. Smith,  Judith Wagner
Meta Systems,  Inc.
843 Massachusetts Avenue
Cambridge,  Mass.  02139
 12, Spur.:,,.;HIS 0  :':;.-:it:i/r>    •
                 Environmental  Protection Agency


   Environmental Protection Agency report number, EPA-600/5-75-001
           PE 1BA030  R/T 21 AXM 06
            68-01-2411
            13.  i'ype of fccpuri and
               Pcriul . j.'i'rad
            Final Report
     This  report is part of  a  continuing investigation by the  EPA of
alternative  financing programs for treatment plant facilities  undertaken
in response  to Section 317 of  The Water Pollution Control Act  Amendments
of 1972.   This report presents findings and recommendations regarding
alternative  financing programs.   The report reviews the current  programs,
describes  criteria for the evaluation of financing programs and  discusses
some differences of current  programs in light  of  these criteria.   Impor-
tant features  of alternative financing programs  are discussed  and analysis
of features  that could be changed to improve program preference  according
to the criteria is presented.
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Send To:

WATER RESOURCES SCIENTIFIC INFORMATION CENTEM
O*. DEPARTMENT OP THE INTERIOR
WASHINGTON. O.C. M140
       Russell J.
                                        Meta  Systems

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