OF REGIONAL SOLID WASTE HANDLING
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OF REGIONAL SOLID WASTE HANDLING
This report (SW- 15c) was prepared for the Bureau of Solid Waste Management
by NORMAN MORSE and EDWIN W. ROTH
Cornell Aeronautical Laboratory, Inc.
under contract no. PH 86-67-254
U.S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE
Public Health Service
Environmental Health Service
Bureau of Solid Waste Management
1970
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Public Health Service Publication No. 2065
LIBRARY OF CONGRESS CATALOG CARD NO. 70-607064
For sale by the Superintendent of Documents, U.S. Government Printing Office
Washington, D.C. 20402 - Price $2.50
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FOREWORD
Effective solid waste management has been hampered by traditional
solutions confined to political boundaries. If ever-increasing
quantities of solid wastes are to be collected and disposed of,
political entities must cooperate and seek solutions together. The
solid waste management activities of one community do affect its
neighbors. Possible savings by a cooperative, regional approach to
solid waste management are evident. For example, two small commu-
nities may be able to operate one sanitary landfill less expensively
than each operating alone. Or, one large collection system can be
more efficient than several smaller ones.
If communities wish to cooperate in solving their solid waste
management problems, the optimal use of their facilities and per-
sonnel must be found. Today's complicated solid waste systems
suggest an approach that considers all interactions. A system may
not be optimized by selecting the best components independently,
because interactions between components are very significant. A
systems analysis approach can provide a technique by which all com-
ponents and their interactions are considered, and the total system
optimized.
This study develops a systems analysis methodology for regional
solid waste management. Although this initial effort is far from
comprehensive, it can serve as a model for planners in the applica-
tion of quantitative techniques for establishing more efficient
solid waste systems.
—RICHARD D. VAUGHAN, Director
Bureau of Solid Waste Management
ill
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TABLE OF CONTENTS
Page No.
Section 1. INTRODUCTION, SUMMARY, AND RECOMMENDATIONS 1
1.1 Factors Affecting Growth of the Solid Waste
Problem 3
1.2 The Solid Waste Disposal Act of 1965 7
1.3 Objectives of Solid Waste Management Research 9
1.4 Summary 13
1.5 Recommendations 17
Section 2. SYSTEMS ANALYSIS OF REGIONAL SOLID WASTE MANAGE-
MENT 19
2.1 Introduction 19
2.2 Solid Waste Management as a Subsystem of a Regional
Waste Management System 21
2.3 The Role of Deleterious Effects in Deriving
Effectiveness Measures for Solid Waste Management
Systems 30
2.4 An Approach to Measurement of the Effectiveness of
a Regional Solid Waste Management System 34
2.5 Other Measures of Effectiveness 39
Section 3. THE STRUCTURE OF REGIONAL SOLID WASTE MANAGEMENT
SYSTEMS EVALUATION 41
3.1 Purpose of Studying the Structure 41
3.2 Major Elements of the Structure 42
3.3 The Finer Structure of Solid Waste Management
System Evaluation 48
3.4 A Minimum Acceptable Performance Screen 52
3.5 Requirements for Submodels and for Input Data 53
3.5.1 Submodel Requirements 54
3.5.2 Requirements for Input Data 56
3.6 The Structure as a Guide to Analysis on the Current
Project 60
Section 4. A FACILITY CHOICE MODEL AS AN AID IN REGIONAL
SOLID WASTE MANAGEMENT DECISION MAKING 62
4.1 Introduction 62
4.2 Basics of Source Assignment and Facility Choice
Problems 67
4.2.1 The Decision to Install a Processing Plant - One
Alternative Landfill Site 68
4.2.2 The Choice Among Several Disposal Sites in a
Region 81
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TABLE OF CONTENTS
Page No.
4.2.3 The Decision to Install a Processing Plant -
Several Alternative Disposal Sites 94
4.3 A Static Model for Choosing Among Several
Processing and Disposal Facilities 98
4.3.1 General Description 98
4.3.2 Distance Data Required '. 104
4.3.3 Uses of the Static Model 105
4.4 Application of the Model to Balance Costs Against
Various Levels of Deleterious Effects of Solid
Waste 106
4.5 Experience with the Facility Selection Model 110
4.6 Facility Submodel Requirements 114
4.7 Facility Selection as a Sequence of Choices over
Time 118
REFERENCES 121
Appendix A THE BUFFALO STANDARD METROPOLITAN STATISTICAL
AREA (SMSA) A-l
A. 1 Introduction. A-l
A.2 Geologic and Geographic Profile of Erie and
Niagara Counties A-2
A.2.1 Geologic Highlights A-2
A.2.2 Geographic Highlights of the Buffalo SMSA A-5
A. 3 The Local Government and Population Distribution
Within the Two Counties A-ll
A. 3.1 Local Government Structure A-ll
A. 3.2 Population Distribution A-12
A.3.3 Economic Profile of the Erie-Niagara Area A-17
Appendix B BUFFALO SMSA SOLID WASTE GENERATION B-l
B.I Introduction B-l
B.2 Description of Solid Waste B-2
B.2.1 Categories of Solid Waste B-2
B.2.2 Categorization of Solid Waste - For What Purpose?. B-4
B.2.3 State of Solid Waste Information Pertaining to
' the Buffalo SMSA B-6
B.3 Spatial Distribution of Solid Waste Generated B-7
B.4 Estimate of Current Solid Waste Generation in
Erie County B~9
B.5 Future Solid Waste Generation B-10
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TABLE OF CONTENTS
Page No.
Appendix C BUFFALO SMSA SOLID WASTE SYSTEMS C-l
C.I Overview of Current Solid Waste Handling
Operations C-l
C.2 Current Solid Waste Handling Practices C-4
C.2.1 Erie County - Inventory of Disposal Sites and
Processing Plants C-5
C.2.2 Niagara County - Inventory of Disposal Sites and
Processing Plants C-9
C.3 Comments on Current Solid Waste Handling
Practices and Facilities C-14
Appendix D TECHNOLOGICAL AND MANAGEMENT OPTIONS FOR BUFFALO
SMSA SOLID WASTE HANDLING D-l
D.I Statement of Developing Problems and Associated
Solid Waste Handling Requirements D-l
D.2 Currently Planned and Considered Technological
and Management Options D-4
D.2.1 The City of Buffalo Activity D-5
D.2.2 A Demonstration Within Niagara County D-6
D.2.3 Town of West Seneca - An Example of Facility
Conversion D-6
D.2.4 Carborundum Company Uni-Melt. A Technological
Innovation Being Examined D-7
D.3 Feasible Technological and Management Options D-8
Appendix E CONCEPTUAL SCREEN AND SCREENING PROCEDURE FOR
PRELIMINARY ASSESSMENT OF SOLID WASTE OPERATIONS
AND SYSTEMS E-l
E.I Introduction E-l
E.2 Formulation of a Screen and Screening Procedure.... E-4
E.3 Summary E-10
Appendix F INTRODUCING PRIVATE SOLID WASTE HANDLING INTO
REGIONAL SOLID WASTE MANAGEMENT PLANNING F-l
F. 1 Introduction F-l
F.2 Common and Diverse Objectives of Public and
Private Solid Waste Management F-2
F. 3 Preliminary Model F-6
F.3.1 Processing Plant Parameters F-8
F.3.2 Refuse Collected Parameters F-8
F. 3.3 Transportation Parameters F-9
F.3.4 Disposal Site Parameters F-9
F.3.5 Life of Disposal Site i F-9
F.3.6 System (1) - Municipal Solid Waste Processed and
Disposed - Private Waste Disposed Directly F-10
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TABLE OF CONTENTS
Page No.
F.3.7 System (2) - Both Municipal and Private
Solid Waste Processed Within Cooperative
Processing Facility And Then Disposed. F-l 1
F.3.8 Illustrative Example F-12
F.4 Results and Conclusions. .... F-13
Appendix G ESTIMATION OF OPERATING COSTS FOR REFUSE TRANS-
PORTATION IN THE CITY OF BUFFALO... G-1
G.I Summary G-l
G.2 Method of Estimation G-l
G.3 Calculation of the M-Quantities and the Cost
Estimate G-8
G.4 Other Cost Components G-9
Appendix H A COMPUTER PROGRAM FOR GENERATING AND LISTING
ALL NCK COMBINATIONS H-l
Appendix I LISTING AND SAMPLE OUTPUT OF THE FACILITY
SELECTION MODEL. 1-1
Appendix J ANALYSIS FOR FACILITY SELECTION OVER TIME J-l
J.I Assumptions j-1
J.2 Input Parameters and Definitions J-2
J.3 Conditions for Solution J-5
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LIST OF FIGURES
Figure Page No.
1 Simplified Regional Planning-Decision Making Hierarchy 25
2 Total Regional Waste Management and Pollution Control 26
System
3 Overview of Regional Solid Waste Management System 43
Evaluation
4 An Evaluation Model Within a Series of Runs 45
5 Detailed Structure of Regional Solid Waste Management 49
System Evaluation
6(a) Boundary of Region Where Processing is Preferred, 71
0 < Cj - c2 < cTd
6(b) Boundary of Region Where Processing is Preferred, 71
-c < 0
7 Variable Cost Advantage of Incineration as a Function 78
of Distance from the Central Business District
8 The Decision to Build or Not to Build an Incinerator 80
Illustrative Case
9 Region of Preference Between Two Alternative Disposal 86
Sites T i ~ =—
10 Regions of Preference Among Ten Illustrative Landfill 87
Sites, Large Number of Infinitesimally Small Source
Areas Assumed
11 Regions of Preference Among Ten Illustrative Landfill 88
Sites, Source Areas Represented by Census Tracts
12 Choice Among the Landfill Sites of Fig. 10 and the 90
Corresponding Service Areas. Amortized Fixed Cost
of Each Facility = $20,000 Annually
13 Choice Among the Landfill Sites of Fig. 10 and the 91
Corresponding Service Areas. Amortized Fixed Cost
of Each Facility = $60,000 Annually
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LIST OF FIGURES
Figure Page No.
14 Choice Among the Landfill Sites of Fig. 10 and the 93
Corresponding Service Areas. A =0; A,=A = A =A=A
= $60,000 Annually
A.I The Buffalo Standard Metropolitan Statistical Area A-3
A.2 Geological Cross Section from Wilson (Niagara County) A-4
to Springville (Erie County)
A. 3 Erie-Niagara General Soil Associations A-8
B.I Estimated Total Refuse Quantities Per Square Mile B-21
for Census Tracts Within Buffalo City and Adjacent
Area, 1966 (Tons Per Day Per Square Mile)
B.2 Estimated Total Refuse Quantities Per Square Mile for B-22
Census Tract in Erie County, New York, Which Are
Outside Buffalo City and Adjacent Area, 1966
(Tons Per Day Per Square Mile)
C.I Organized Refuse Disposal by Municipalities C-3
C.2 Location of Existing Refuse Disposal Sites in Erie C-6
County
C.3 Map of Niagara County C-13
E.I Relationships of Costs and Particulate Matter Levels E-3
E.2 Conceptual Screen and Screening Process E-6
F.I Location of Disposal Sites Relative to Single Process- F-7
ing Plant
F.2 Cumulative Cost for Public and Private Sectors vs. F-15
Elapsed Time
F.3 Aggregate Cumulative Cost vs. Elapsed Time F-16
F.4 Cost Per Day for Public and Private Refuse Handling F-17
Systems
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LIST OF FIGURES
Figure Page No.
H.I Flow Chart for Subroutine COMB H-3
H.2 FORTRAN Listing for Subroutine COMB H-4
H.3 Sample Computer Output of CR for K = 1,2,3 and 4 H-5
I.I FORTRAN Listing of Facility Selection Model 1-3
1.2 Sample Output of Facility Selection Model 1-9
J.I Projected Fixed Cost Schedule J-l
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LIST OF TABLES
Table Page
1 Urban Population Growth 4
2 Key to Symbols Used in Flow Diagram of Detailed 50
Systems Evaluation Structure
A.I Key to Soil Associations Map Erie-Niagara Region A-9
A.2 Population of Erie County, New York, by Minor Civil A-13
Divisions: April 18, 1966, and April 1, 1960
A. 3 Projected Populations of Cities and Towns in
Erie County A-14
A.4 Population of Niagara County, New York, by Minor Civil A-16
Divisions: April 3, 1967, and April 1, 1960
A.5 Erie-Niagara Employment Categories, 1966 A-18
(Nonagricultural Establishments)
A.6 Erie-Niagara Area Employment 1958-1966 A-19
A.7 Erie-Niagara Area Employment Projections A-21
Major Industry Groups 1960-2000
B.I Solid Waste Materials by Kind, Composition, Combustible B-3
Volume, and Sources
B.2 Estimated Refuse for Census Tracts Within City of Buffalo, B-ll
1966 (Tons Per Day)
B.3 Estimated Refuse Quantities Per Square Mile for Census B-13
Tracts Within City of Buffalo 1966 (Tons Per Day Per
Square Mile)
B.4 Estimated Refuse Quantities for Census Tracts in Erie B-15
County Outside City of Buffalo, 1966 (Tons Per Year)
B.5 Estimated Refuse Quantities Per Square Mile for Census B-18
Tracts in Erie County Outside City of Buffalo (1966)
(Tons Per Day Per Square Mile)
B.6 Annual Refuse Tonnage by Census Tracts -- City of Buffalo B-25
B.7 Annual Tons of Refuse Per Capita -- City of Buffalo B-27
B.8 Annual Tons of Refuse Per Square Mile — City of Buffalo B-29
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LIST OF TABLES
Table Page No.
B.9 Annual Refuse Tonnage by Census Tracts -- Erie County B-31
Outside Buffalo
B.10 Annual Tons of Refuse Per Capita — Census Tracts in B-34
Erie County Outside Buffalo
B.ll Annual Tons of Refuse Per Square Mile -- Census Tracts B-35
in Erie County Outside Buffalo
B.12 Commercial and Industrial Refuse in Erie County Outside B-38
City of Buffalo (Tons Per Year)
C.I Erie County Disposal Sites C-8
C.2 Incinerator and Truck Transfer Operations - Erie County C-10
C.3 Niagara County Disposal Sites (As of June 1966) C-12
F.I Public and Private Refuse System Costs F-14
G.I Location and Distance Information, Refuse Collection G-4
Districts and Facilities, City of Buffalo
G.2 Refuse Quantity Information, City of Buffalo, 1966 G-6
Number of Truckloads Generated During the Year
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SECTION 1. INTRODUCTION, SUWARY AND RECOWENDATIONS
Within the normal activities of a society and its population, waste
in a variety of forms is generated. In general the activities of production,
distribution and consumption each entails the receipt of material, its trans-
position in form and/or composition, and movement to some other recipient.
>.
It has been demonstrated amply that associated with these activities are
streams of waste which over the years have become alarmingly larger and more
complex in nature. With the growing severity of the solid waste problem,
there has occurred, at least on the part of the Federal Government, a broader
awareness of the need for drastic measures, both fiscal and technological,
to alleviate the problem. It is problematic whether an appropriate degree
of interest, concern and responsibility exists, however, at the most critical
levels—the producers of waste and those directly concerned with its proper
management.
It is difficult to define what is meant by waste. Broadly stated,
waste is a material that its producer does not want (Ref. 2). Although the
product may have value to someone (either in its present or in a converted
state), if its producer does not ask for reimbursement for its removal it is
considered to be waste, and at some stage, will enter a waste handling system,
either private or public. The point at which it is discarded is considered
to be the beginning of a waste management system. There are operational
problems in using this definition, however:
(a) Waste is directly related to the producer and his lack
of use for the commodity. Since the material may have
either direct or indirect benefits to the community, region,
or nation, a useful material may or may not be considered
waste, depending on whether the producer's attitude
coincides with the public's attitude.
The word "wastes" is a more accurate term than the singular, because the
appropriate reference is usually to one or more wastes in any form - solid,
liquid and gaseous - or any combination of them. However for simplicity, the
singular form is used in reading for adjectives and adverbs (Ref. 1.)
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(b) The mere absence of a purchaser of the "waste" from the
producer places the commodity in the "waste category"
where it might otherwise be considered valuable. The
classification of certain scrap materials as waste or
not will fluctuate with the market for those scrap materials.
(c) Producer attitudes and scrap material markets change
over time. Thus, changes in such conditions as
material usage and availability, general economic factors,
location of waste produced to potential users, etc.,
influences the inclusion or exclusion of commodities from
the waste category.
By assuming current waste producer attitudes and current practices
with regard to fluctuating markets for scrap materials, an examination of
waste management can be made without having to resolve conceptual difficulties
arising from these limitations on the strict definition of "waste". In a
more general problem context than is appropriate for the current study, the
definition of waste would be modified significantly by enlarging the spatial
and temporal limitations, relaxing the economic constraints and introducing
other variant factors (e.g., material substitutions, new processes, etc.)
which coul.d influence the classification of the commodity. It is evident
that as the definition of waste is modified, the producers, amount and com-
position of the commodity would change appreciably.
This study was directed toward development of some methodological
first steps at systems analysis of regional solid waste management systems.
The scope was regional, and it was sufficient to look toward short- to medium-
range problems during these first stages. For these reasons, and since the
development of analytical techniques did not depend crucially on the inclusion
or exclusion of specific materials from the waste category, the adoption of
current techniques and practices is believed to be appropriate for the present
study.
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1.1 Factors Affecting Growth of the Solid Waste Problem
An exploration of the factors affecting the growth of the solid
waste problem would be redundant since this subject has already been treated in
the literature (Ref. 3 and 4). Rather,a brief summary of the current and
foreseeable trends in the problems associated with solid waste would be helpful
in providing a basis for appreciating the importance of deriving an effective
solid waste management system.
As mentioned above, virtually all human activities and endeavors produce
solid waste. The basic factors affecting the increased amount of solid waste are
the increasing population of the United States and its improved standard of living
(in an economic sense). Since 1940 the population of the Country increased from
131,613,400 people to an estimated U.S. population in 1967 of approximately
198,608,000. This represents an increase of approximately 51 percent.
During the same time period the U.S. Gross National Product increased from
99.7 billion dollars to 789.7 billion dollars, an unadjusted increase of
approximately 690 percent or an adjusted increase of 232 percent. The joint
effect of these two factors on solid waste production along with decreasing
salvage and materials reclamation activities has resulted in an increase
in solid waste production from 70 million tons per year to roughly 175 million
tons per year (Ref. 5), a 2.5 fold increase or an increase of 3 to 3-1/2
percent per annum. As a further explanation of the significant increase in
solid waste, beyond the population and economic growth factors is the impact
of industrial and technological changes in terms of the composition of
materials utilized in manufacture and reduced price of product. For example,
with the reduction of the price of paper products, nonreuscable materials
are being substituted for more permanent products (e.g. paper napkins for
linen or cotton napkins).
These changes have not only increased the magnitude of the solid
waste stream, but have affected its composition as well. In addition to the
higher proportion of paper content, the proportion which is biologically degrad-
able is decreasing with the increased use of plastics and metal containers, and
the further adoption of the throwaway glass bottle. Furthermore, the substitu-
tion of aluminum containers for ones made of steel alloys has increased the
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proportion of solid wastes which will require extremely long time periods to
elapse before they decompose.
Along with a rapidly increasing population over the last twenty-
eight years, the United States has experienced a period of intense urbaniza-
tion. In 1940, 56.5 percent of the total U.S. population lived in areas classified
2
as urban by the Bureau of Census. The urban population growth trend for the
years 1950, 1960 and 1970 (est.) are shown in Table 1.
Table 1. URBAN POPULATION GROWTH
Year Population in Urban Areas
(percent)
1950 64.2
1960 69.8
1970 75.1 (est.)
Based on a projected U.S. population of 250 million people in 1980, it is
further estimated that 79 percent of this population will reside in urban
areas. An examination of the populations residing in rural and urban areas
reveals that the size of the rural population remains virtually constant
and thus nearly all the population growth is being experienced within the
urban areas (Ref. 6).
Thus as more and more of the population resides in the urban areas
of the.United States there results a greater amount of solid waste produced
per square mile. This is the result of increasing population density as well
as rapidly increasing solid waste generation per capita. Moreover, the
general shortage of unused and available facilities for individuals residing
in urban areas to either temporarily or permanently store unused materials
forces a greater proportion of such materials into the solid waste stream.
This results in the collection of greater amounts per capita than is required
"Urban populations include all persons living in incorporated or unincorporated
communities of 2,500 population or more, or in densely settled urban fringe
around cities of 50,000 inhabitants or more." 1960 definition from Business
Fact Book 1963, Part 2, Population and Housing, State of New York Department
of Commerce.
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in rural regions as well as making more frequent collection necessary. The
increase in concentration of waste production introduces the following problems
when developing effective and economic long-range waste handling plans:
(a) Local governments are experiencing a scarcity of
land which is available for the disposal of solid waste.
Either the available land sources are located at
considerable distances from the main contributors to the
waste streams or they are dependent on other municipalities
for land. The factor of distance adds a significant cost
to providing the service to the community whereas the factor
of dependency introduces significant uncertainty for long-
term uninterrupted operations (the San Francisco-Brisbane
situation is an excellent case in point).
(b) The increase in population density has the affect of
reducing the number of options available to the solid
waste managers of individual municipalities in the
processing and disposal of the community's solid waste.
This reduction of available options is closely tied to
the limitation of readily accessible land and the
proximity of the population to the waste processing and
disposal operations and their characteristics, which are
typically considered objectionable by the public.
Of equal importance to such quantifiable factors as numbers of people,
population distribution, economic growth indicators, and land use and its
availability in discussion the factors associated with the growing solid waste
problem are the attitudes of people toward their environment. The increasing
amount of information and publicity concerning environmental pollution is
evidence of increased interest and action by community leaders with regard to
environmental appearance. This may be taken as some indication that people
are increasingly dissatisfied with having amenities and services provided on a
marginal basis. These changing attitudes and demands have found expression in
such Federal programs as the Demonstration Cities and Urban Development Act of
1966 (to improve the quality of urban life), the Highway Beautification Act
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(to improve the appearance of the country-side), the Solid Waste Disposal
Act of 1965 as well as a variety of federal and state-supported urban renewal
acts and projects.
With these changing attitudes, people are no longer willing to
tolerate a variety of unsightly and/or potentially health-menacing practices
associated with solid waste handling. Open dumps, and dumps with open burning,
although still plentiful throughout the United Stated, are slowly being elimin-
ated; unsanitary landfill practices are being eliminated due to health
ordinances and statutes; open and/or uncovered collection vehicles are being
replaced. The need for substitutes for these practices and facilities amounts
to a general requirement for increased system performance. Associated with
the requirement for improved performance and greater benefits is the cost
incurred in achieving these higher levels of operation. It is the explicit
recognition and determination of the increased costs and the benefits obtained
which must be available to the population and their decision makers when
assessing changes to the methods of handling solid waste.
In 1962, the American Public Works Association pointed out that the
annual public outlay for refuse collection and disposal services of over $1.5
billion is exceeded only by expenditures for schools and roads (Ref. 7).
The storage, collection, transportation, processing and disposal of solid
waste is one of the major budget items within urban areas. In addition to the
expenditures by local governmental agencies, the editors of Refuse Removal
Journal (Ref. 8) have estimated that the annual expenditures of the private
sanitation industry are over $1.3 billion. Thus with increasing labor and
equipment costs and the larger amounts of solid waste being collected and
disposed, it is estimated that the total direct cost is somewhat in excess of
$3 billion annually.
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Beyond the direct costs of solid waste management are those indirect
costs associated with the deleterious effects derived from solid waste and
its handling. Although it is not possible to establish a cost budget relating
the effects to a monetary measure, in part because of the subjective com-
ponents associated with certain effects (odors, unsightliness, flies, etc.)
and the lack of basic knowledge pertaining to cause-effects (e.g., relation-
ships of respiratory diseases and particulate matter), there are a variety
of indirect costs which are measurable. Among these costs are those related
to additional cleaning and/or painting of household furnishings, streets,
houses, cars, etc.; losses in tax revenues; losses in income due to illness,
accidents and diseases; degradation in agricultural quality and crop yields;
and deterioration of national resources. Although no systematic and successful
estimate of the indirect costs has been achieved, it is believed that the
estimate derived would exceed the direct costs associated with solid waste
handling. If this belief is correct, the usefulness and validity of cost
benefit analyses which are restricted to direct costs exclusively must be
viewed as providing only partial guidance and in certain instances may be
highly misleading since the deleterious effects associated with different
methods of collection, processing and disposal vary significantly.
1.2 The Solid Waste Disposal Act of 1965
In recognition of the current seriousness of the threat to the
environment and the growing concerns and changing attitudes of the population,
the Federal government has made a commitment to support and assist in a
coordinated national effort to alleviate solid waste problems. This
commitment is embodied in Title II of Public Law 89-272, the Solid Waste
Disposal Act, which was signed into law on October 20, 1965. In summary,
the Act authorizes specific action in six areas of need (Ref. 9): (1) grant
support for local and state projects to demonstrate new and improved waste
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disposal technology; (2) grant support for the development of area-wide
solid waste management systems to end fragmentation of responsibilities
among small communities; (3) grant support for State surveys of solid waste
handling needs and the development of statewide plans for meeting needs;
(4) research, both direct and grant-supported, to establish the basis for
new approaches to solid waste handling; (5) training programs, both direct
and grant-supported, to alleviate critical shortages of trained personnel;
(6) technical assistance to local and state governments with solid waste
problems. The Act commits the Federal government to the role of supporting
partner with local and state agencies in solving solid waste problems. Primary
responsibility for solid waste handling and carrying out programs for improved
practices remains at the local and state levels.
The actions authorized by the Act recognize that the develop-
ment of acceptable solid waste handling solutions transcends the economic
and technological capabilities of local communities. Additionally,
because the effects of solid waste handling practices are in many instances
experienced beyond the local community, the desirability of establishing
regional solid waste management districts is suggested. Rather than having
the Federal government establish solid waste regions as is being done for
Air Quality Regions, the responsibility for improving solid waste handling
practices is being left with the local community. The Federal government
views its role in the area of solid waste as providing fiscal and technical
support.
Among the factors which appear to motivate the decision to maintain
the responsibility for carrying out programs and improvements at the state
and local levels are
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(a) The options available and/or suitable to communities
vary considerably.
(b) The political and population receptivity to solving
their solid waste problems, and the quality of service
desired, are markedly different.
Although the broad definition of the solid waste handling problem may be
specified, the detailed examinations and analyses to be performed and the
.osible solution set to be derived must be related to characteristics and
needs of the individual region, if they are to be appropriate and useful.
1.3 Objectives of Solid Waste Management Research
The objectives of this study are to define and perform a systems
analysis of the solid waste handling problems confronting regional decision
makers. As a systems analysis investigation, the functions of solid waste
handling — collection, transportation, processing and disposal must be con-
sidered as integrated and coordinated activities rather than individual and
independent operations. Additionally, the interrelationships between solid
waste handling and the handling of liquid and gaseous wastes must be recognized
since, as has been shown by others, numerous aspects of the solid waste problems
could be eliminated readily by appropriate transformations of solid waste into
liquid or gaseous waste. Thus the proper understanding and actions taken
relative to solid waste management should be made with full cognizance of their
impacts on the other waste streams and their effects on total environmental
pollution.
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A question of great significance in solid waste manage^ -: is the
following — what is or are the desired objectives of solid wastt HAH Cement?
At the most simplistic level, the objective is to relocate the solid waste
to an area which is unobjectionable to the population, and is performed at the
lowest cost. Another stated objective is to transform solid waste into inert
material which does not pollute the environment and to accomplish this trans-
formation in a manner which is acceptable to the standards (e.g., sensory,
aesthetic) prescribed by the population. Still another objective is to reclaim
and reuse, as much as possible, the solid waste materials which are currently
destroyed. At present there does not appear to be an objective or compatible
set of objectives which has been made explicit and which is useable at various
decision making levels concerned with solid waste management. Although it is
understood that the objective of solid waste management is not invariant with
time, it is important to make explicit the goals so as to assist the planners,
and to allow for their review periodically and determine whether or not they
are still relevant.
Consider for the moment that a study of solid waste handling had been
initiated in 1930 with the objective of providing assistance for solid waste
planning out to the year 1965. Beyond the fact that the current concerns relative
to solid waste handling were virtually nonexistent at that time, except for
a limited number of sanitarians, the examination would have in all probability,
been addressed to a localized municipal area and to one or more handling
functions which would have been treated as independent activities. But of much
greater importance, those planners, concerned with making projections of solid
waste generation and handling requirements, were confronted with having to make
assumptions pertaining to the following factors (similar to those facing current
investigators):
(a) Size of population residing in municipality.
(b) Rate of change in urbanization migration.
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(c) Introduction of new residential housing forms and associated
population densities.
(d) Increased generation of refuse per capita as reflected
by changes in income levels and standards of living.
(e) Economic projections of commercial and industrial expansion
and modification of products and processes and their
associated solid waste generation.
(f) Changes in the composition of refuse -- anticipation of
reduction in quantity of ash; increase of paper, bottles, cans;
introduction of plastics, etc.
(g) Reduction and/or disappearance of available land for solid
waste processing and disposal.
(h) Modification of attitudes and changes in legislation with respect
to acceptable levels of solid waste handling practices.
This list of factors could be expanded many times but it is apparent that
most, if not all, of the above could not have been anticipated with any reason-
able degree of accuracy for the purposes of the proper planning of solid waste
facilities. Along with demographic, economic and land use factors, projections
pertaining to technological innovations and modifications had to be considered.
Here the planners were more successful since although technological improvements
had been introduced over this 30-35 year period, the basic processes and options
available have remained fairly constant. Although materials handling and trans-
port equipment have improved significantly, and processing and disposal practices
have changed, the modifications can be characterized by greater efficiency
rather than by technological innovation. In general, the outputs of these
planners were a single projection of the future which was made using rather
crude estimating and statistical techniques, and a series of recommendations
for individual processes and facilities.
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Now consider the present time, and the approaches being utilized
by investigators who are attempting to benefit from some of the shortcomings
of past studies in providing planning tools and assistance to decision makers.
Three basic considerations are starting to be explicitly introduced into these
investigations:
(1) Waste management, be it solid, liquid or gaseous, is
being examined on a regional basis; the size and definition
of the region is dependent on the particular waste and
its associated pollution effects and the geographical
location of the area being studied.
(2) Recognition is given to the interrelationships among
the waste streams (solid, liquid and gaseous) in develop-
ing solutions to the solid waste handling problems.
(3) Solid waste handling, involving the interrelated
functions of collection, transport, processing and
disposal, is viewed as a system and is approached using
the methods of systems analysis.
Many, if not all, of the factors (a through h above) are still as
elusive as they were previously although the statistical techniques available
for projecting are more sophisticated. The systems analyst with the assistance
of regional planners, demographers, and economists makes a series of plausible
assumptions concerning the future and develops projections for each assumption
or set of assumptions. This approach to forecasting and projecting results
in a variety of projections concerning the future. Now, given a large number
of candidate alternative solid waste systems, evaluations can be performed
utilizing all the projections derived, and results, in terms of cost and
performance measures, can be obtained for each set of projections. The final
step in this analysis process is the performance of sensitivity analyses,
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that is, the determination of the quantitative sensitivity of the measured
system outputs to the indivdiual projections made. It is the presentation
of these forms of results to the decision makers which provides them with an
appreciation of the relationships among the assumptions, projections, system
and outputs.
The role and responsibility of the analyst are to provide a spectrum
of choices, whereas the responsibility of those involved in decision making
is to select those assumptions and conditions which, in their judgment and
authority, most closely represent the interests and needs of the region. In
view of the uncertainties associated with the above factors, those candidate
systems whose performance measures and cost are within acceptable limits and
are not highly sensitive to changes in the projected factors represent
desirable candidates for selection. In view of these analytical requirements,
the main objectives of this study were to define the considerations which
should be introduced into the examination of regional solid waste management,
to formulate a comprehensive solid waste system evaluation structure, and to
develop some detailed mathematical models for assisting in the decision-
making process.
1.4 Summary
A
Directed toward the objectives outlined in Section 1.3, examination
of many of the factors and trends leading to the current crises in solid waste
management and overall environmental pollution was carried out, leading to
the formulation of an overall solid waste system evaluation structure and the
development of some mathematical models. This effort represents a start
toward more comprehensive systems analyses with regard to solid waste systems.
It is expected that these contributions will eventually lead to more objective
and quantitative bases for establishing solid waste system requirements for
planners and policy decision makers during the next generation. Even in its
present form, the facility selection model of Section 4 represents a tool of
more than modest usefulness.
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A literature search and consideration of specific problem types
and their manifestations within the Buffalo SMSA permitted the examination
described in Section 2 of measures of effectiveness. It was concluded that
along with measures of pollutants and costs, some measure of the land useage
associated with the solid waste disposal system offered a promising possibility
as a measure of effectiveness. This is not necessarily the only useful measure
of effectiveness in addition to pollutants; but before attempting to work
with other measures, this one was adopted as the initial trial.
This approach was utilized in developing the evaluation model
structure of Section 3. The process of developing the model structure was
a necessary step in providing an orderly means of considering different
systems analysis models and comparing them with regard to scope, overlap or
complementarity, and compatibility. As a result of this effort, a comprehensive
list of data items required for solid waste system analysis is given, together
with a list of required submodels and a description of their functions. This
is not to say that system analysis cannot be carried on without all the items
listed or all the submodels; it does say that all items are present at least
in some implicit form in any systems analysis; if an item is not explicit
in the model it is because it is being substituted for by some simplification
device or it is being held constant by assumption.
As part of the evaluation model structure a conceptual screen and
screening procedure was developed which permits a systematic approach to the
examination of candidate systems to determine whether they meet the acceptance
levels of performance prescribed by or imposed on the region. The screening
procedure is useful in rejecting candidate systems which cannot meet the
standards prior to the more extensive and expensive procedure of system
evaluation as described in Section 3.
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. As a result of the studies described in Section 3, it was decided
that development of a model as comprehensive as the entire evaluation structure
was inappropriate for this limited level of effort and short time duration
study. It was decided instead to concentrate on a more limited modeling effort
which, (a) could be completed in a relatively short time period, (b) would
require data that was already available from the Buffalo SMSA and, (c) could
be put to use in actual regional decision-making. A static model, with a
manageable level of detail, for choosing among alternative facilities and making
assignments of source areas to the facilities chosen was developed. This
model was useful in the following respects:
(1) Since the model was computerized, large numbers of
alternative specific system configurations could be
compared;
(2) Through series of runs under systematically varied input
parameters, the characteristics of economically
desirable systems could be defined, thus allowing
design of a system configuration toward those
characteristics;
(3) The minimum cost yielded by the model for any set of
input parameters and possible choices of facilities
can be used as a normative value. Thus a system
configuration which violates the facility choices and
service area assignments corresponding to the
minimum cost represents an additional cost which is
presumed to pay for the elimination of some
undersirable aspect of the minimum cost configuration.
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The application of (3) is fundamental to one method of introducing into the
analysis the "trading-off" of costs against various levels of deleterious
effects (Section 4.4).
The model developed is described in Section 4. The same section
contains comments on potential applications of the model and some experience
already obtained with the model. The facility selection model leads naturally
to a more comprehensive next-stage development which could not be achieved
on the present study but which is achievable through further study of scope
similar to the present one.
A further major segment of work on this study was the compilation
and analysis of data descriptive of the Buffalo SMSA. The results of this
work are contained in the various appendices. In particular, estimates of
residential and non-residential refuse for all census tracts throughout
Erie County were obtained and projected in five-year periods out to the year
2000, and an estimate was derived of the operating cost per mile of Buffalo
collection vehicles in spite of the absence of maintenance records and
odometer readings.
As part of the examination of solid waste handling operations and
planning in the Buffalo SMSA and elsewhere it was observed that an artificial
separation was maintained between residential solid waste and solid waste
generated at most other sources. The results of a preliminary analysis
(Appendix F) demonstrated the economics of scale which could be realized if
all waste planning and operations within a region were coordinated and
the available land could be utilized more efficiently. Further examinations
of this form of coordination appear warranted.
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1.5 Recommendations
The recommendations being made are a result of observing and assessing
the significant gap currently existing between the knowledge derived from
research programs of solid waste techniques and mathematical approaches to
solid waste management, and the general level of consulting services avail-
able to individual communities, with their apparent limitations (limited support,
incomplete data, single forecasts and derivation of a. "blueprint" for solving
the community's problems). What is strongly lacking is the availability of
suitable and useful regional information, and the necessary methodological
and evaluative approaches which should be accessible in suitable forms to both
the regional planners and the consultants in the solid waste field.
In outline form, a two to three year program is recommended having
the above objectives, and which includes the following activities:
1. Provide appropriate projections and forecasting techniques
for estimating future residential, commercial and industrial
solid waste generation quantities. Included here would be
the collection and presentation of data pertaining to waste
generation coefficients associated with sources of generation.
2. Establish the form and content of a regional solid waste
management information system which contains: (i) necessary
time series data on solid waste generation sources (including
location, types, quantities and handling practices);
(ii) current regional solid waste handling practices relative
to collection, transport, processing and disposal, (iii) cost
data bank for all solid waste activities.
3. Maintain information on liquid and gaseous waste management
practices and interrelating pollution effects with solid waste
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handling. This information would include, to the degree possible,
the deleterious effects associated with all waste handling
and objective measures of these effects.
4. Gather, evaluate and translate the available mathematical
models used for operations and planning (e.g. facility location
determination), in a form which enables them to be applied
by planners and solid waste consultants.
5. Develop an information gathering approach and method of
transforming research and development results on new processes
and equipments which would allow for their being synthesized
and evaluated.
6. Formulate operationally-useful evaluation system models
which are applicable under conditions when a large digital
computer is available and when only desk calculators or
slide rules are available. The evaluation system models
would be described in sufficient detail so as to allow for
their application without extensive training. These models
would be structured in a fashion that permits their being
changed, if and when, new or improved submodels become
available.
Although the above recommended program will be difficult to accomplish
in the form outlined, the value to be derived by the planning and consulting
communities as well as some organizations responsible for solid waste operations
would be exceptionally high. In brief, having the above capabilities available
would permit the planners to perform some preliminary assessments of the region's
waste management problems, would enhance the effectiveness of the consultants,
and would provide the regional decision makers with a sounder, quantitative
basis for selecting from among alternative solid waste candidates.
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SECTION 2. SYSTEMS ANALYSIS OF REGIONAL SOLID WASTE MANAGEMENT
'There is an increasing acceptance of the argument that a
systems approach to urban and regional pollution problems
has become imperative. The present complexities of
environmental problems and the knowledge that, as time goes
on, these issues will become even more complex and inter-
related makes this conclusion inescapable. The system
should be one that can be tailored or adapted to socio-
geographic areas (not generally congruent with political sub-
divisions) of varying sizes and heterogeneity, and can be
modified or extended as needs arise. Analyses undertaken
for such systems can provide the information required for
action today, and will furnish invaluable leads to the
research needed to provide the bases for tomorrow's
programs" (Ref. 3)
2.1 Introduction
The title of this section, Systems Analysis of Regional Solid Waste
Management, incorporates the methodological approach utilized and the
spatial extent selected in defining and investigating some of the problems
of solid waste handling. No attempt will be made to describe formally the
philosophy, methodologies, and techniques of systems analysis since this has
been accomplished by many authors. (See R. N. McKean, Efficiency in Govern-
ment Through Systems Analysis, New York, John Wiley and Sons, 1958, and
Charles J. Hitch and Roland N. McKean, The Economics of Defense in the
Nuclear Age, New York, Atheneum, 1966.)
The concept of a region has been employed within this study since it
is generally accepted that long-term and successful approaches to the
problems associated with solid waste handling usually encompass a geographic
area which is larger, or at least different from, the traditional political
boundaries. Some of the most cogent reasons employed for examining solid
wastes on a regional basis are:
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(a) Solid waste disposal is a subportion of the waste
disposal problem, and solutions to the problems of solid
waste are highly interrelated with other waste problems.
(b) The extent of the pollution effects associated with
potential solutions of the waste disposal problems
transcend, and in virtually all instances, have little
relationship to political boundaries.
(c) The set of options available for solving the solid waste
handling problems increases as the size of the geographic
areas is enlarged. Among the factors supporting this
statement are (1) greater available economic resources
and opportunities to achieve economies of scale, and
(2) the presence of sufficient land resources which can
be dedicated to the needs of solid waste disposal.
A variety of studies and surveys, e.g. of the Detroit Region (Ref. 12),
Metropolitan Toronto, Northeastern Illinois (Ref. 13), and the Capitol
Region of Connecticut (Ref. 14), have suggested the desirability of regional
approaches to solid waste management in many areas.
The Buffalo Standard Metropolitan Statistical Area, which consists
of the Counties of Erie and Niagara, was selected to serve as the empirical
basis for this study. This region represents a viable interrelated economic
and planning entity (as defined by the Department of Housing and Urban
Development) and contains a variety of community types and land-use patterns.
The Buffalo Region was used to suggest problem areas and as a source of data
for suggesting relationships, determining the orders of magnitude of various
descriptive parameters, and providing inputs to the models developed. As the
study progressed, it developed that greatest use was made of data from Erie
County, and relatively little from the rest of the SMSA. The attempt,
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however, was to describe problems in terms of general models which could be
applied to both counties in the SMSA, the SMSA as a whole, or in fact to
other regions in the United States.
The systems analysis effort of this study and the related efforts
of data collection, analysis and model building related to regional solid
waste management are predicated upon a conceptualization of a regional
environmental control and waste management decision-making structure and on
the objectives of a regional solid waste management system within the struct-
ure. One cannot claim that the detailed decision-making structure of any
particular region actually does follow the clean organizational lines of the
conceptual structure. In particular, except when described in the broadest
terms the decision-making bodies within Erie and Niagara Countries do not fall
into this pattern. What is postulated, however, is that representation of
regional decision-making as_ if_ it were structured according to the conceptual-
ization is useful in indicating the types and levels of decisions which must
be made (whatever the detailed structure) and the information requirements
for those decisions. The selection of measures of waste management system
effectiveness and the measurement of performance of alternative solid waste
handling systems for the region, are based upon this concept of the regional
system.
2.2 Solid Waste Management as a Subsystem of a Regional Waste
Management System
In the performance of a systems analysis, the measures of system
effectiveness which are selected should be in quantifiable terms which relate
to the function or service being performed in as direct a manner as possible.
In the context of regional solid waste management there are a number of
choices; examples of effectiveness measures may be related to the following
attributes:
Pest and Vector Propagation
Other Physically Disagreeable or Harmful Effects
Safety Hazards
Incidence of Disease
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Convenience to the Waste Producer
Adaptability to Statutory or Other Changes in Requirements
System Reliability
Production of Saleable By-products
Salvage of Resources for Return to the Economy
Conservation of Land Resources
The appropriate form and level of importance to be given these
measures is discussed later within this section. However it is recognized
that the performance of any candidate system could be determined on the
bases of measurements of the above factors providing that the system operation
is not objectionable in terms of gaseous and liquid wastes, and associated
air and water pollution standards. In other words, two systems would not
be judged equivalent if they perform similarly with regard to the factors
given above, yet (for example) one introduces large quantities of pollutants
into the air. As another example, a system which incorporates the widespread
use of refuse grinders and employs the sewer for refuse disposal could provide
a high level of land conservation but at the cost of a drastically worsened
sewage disposal problem and a potentially serious water pollution problem.
As has been well recognized and documented, solid waste handling
problems are intricately bound up with many other aspects of waste handling
and environmental pollution. These relationships result in difficulties
in studying solid waste management if the approach utilized is to consider
air and water pollution simply as effects of the solid waste management
system. Clearly, air and water pollution are measures of effectiveness appropriate
to the entire regional environmental control and waste management system,
of which the solid waste management system is only one portion. Thus, operating
within the solid waste management system alone, it is not possible to optimize
regional waste (i.e., solid, liquid, gaseous) management. From this statement,
the following two conclusions may be drawn:
(a) If the solid waste management system is studied
separately from the remainder of the regional waste
management system, it should be done by treating solid
waste management as a subsystem. Such as,
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those properties or performance measures which affect
other portions of the overall system would be measured
and provided as inputs to analyses of tradeoffs among the
various subsystems.
(b) The measures of effectiveness and performance of the solid
waste management subsystem per se should be based on the
subsystem function exclusively, although their interpretation
will necessarily be relative to the measures related to the
other subsystems.
The designer of the solid waste management system is in some
respects in a similar position to the designer of the military weapon
system who needs a definition of effectiveness to evaluate alternative
concepts. In a general sense, the effectiveness of the weapon system
is its contribution, as part of the entire arsenal of the nation's weapons,
to the military strength of the country. This definition is too general
to be useful and almost impossible to measure quantitatively. The useful
measures of effectiveness are more likely to be described in terms of expected
kills, increased size of enemy force required to oppose the system, etc.
The principle of selection of effectiveness measures can be summarized as
follows:
The effectiveness measures should be appropriate to the
decision-making level employing the measure; i.e., effectiveness
should measure the results of the decision being made and not
the results of choices or actions beyond the range of responsibility
of the decision-maker. On the other hand, the measures should
be sufficiently comprehensive so as to be of use to the
decision-maker at the next higher level.
In general, planning decisions with regard to solid waste management
are viewed as constituting a functional responsibility within the regional
planning decision-making complex. For example, within Erie County, the Commis-
sioner of Planning and his staff play a major role in developing solid waste
management concepts. The various responsibilities within the decision-making
complex form a hierarchy corresponding to the functions within the regional
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political structure of the officials involved in making planning-decisions.
A simplified pattern of regional planning-decision making is shown on Fig. 1
The entire planning hierarchy is not shown but only that portion which
includes solid waste management planning has been expanded to illustrate
various decision-making levels.
Within the hierarchy, the highest decision-making level in regional
planning is viewed as involving interactions among economic development, land
use, transportation, environmental control and waste management as well as several
other areas not shown. Subsumed under the environmental control and waste manage-
ment area, decisions are made involving interactions among the problem areas
dealing with liquid wastes, gaseous wastes and solid wastes. Simultaneously,
decision-making activity is carried on within the subordinate problem areas.
The activity is a continuing iterative process, with results at the higher
level constraining the analyses on the lower level while results within the
lower level problem areas impose input changes on evaluations at the higher
level. Decisions at the higher level do not necessarily supercede those taken
at the lower level; the "levels" relate to the detail of the information used
in the system evaluation and decision-making activity, rather than to political
power.
The principle stated above.related to the solid waste management
problem,indicates that decisions regarding the water and air pollution aspects
of solid waste management are in effect decisions taken at the next higher
level - environmental control and waste management. Thus systems analyses
with regard to solid waste management should be structured so as to assist
the decision-maker responsible for environmental control and waste management —
a decision-making level responsible for waste management in its totality.
The information flow relating to that decision-making level is
illustrated in Figure 2. The structure consists of three parallel subsystems:
one involving gaseous waste management and air pollution, one involving liquid
waste management and water pollution, and the third involving solid waste
management and land pollution. The three subsystems are completely inter-
connected, which means that the problem confronting each subsystem results
from the total environmental situation (i.e., the region's total waste and
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KJ
__ ..r .
1
r --'---
»
|
ECONOMIC
DEVELOPMENT
1
LAND USE
PLANNING
1
REGIONAL PLANNING
1 ____!
ENVIRONMENTAL
CONTROL AND WASTE
MANAGEMENT
LIQUID
WASTES
i
i
TRANSPORTATION |
1
i _ _ 1
GASEOUS
WASTES
1
SOLID
WASTES
Figure 1 SIMPLIFIED REGIONAL PLANNING-DEC IS ION MAKING HIERARCHY
-------
TOTAL WASTE AND POLLUTANT PRODUCING ENVIRONMENT
SUBSYSTEM INPUTS WHICH ARE OUTPUTS
GASEOUS WASTE
MANAGEMENT
SUBSYSTEM
SUBSYSTEM
COSTS
1
SOLID
WASTES
WATER !
POLLUTANTS '
AND LIQUID
WASTES
IMPROVED L_
AIR
QUALITY
OF OTHER SUBSYSTEMS
LIQUID WASTE
MANAGEMENT
SUBSYSTEM
SUBSYSTEM
COSTS
SOLID
WASTES
AIR
POLLUTANTS
IMPROVED
WATER RESOURCE
QUALITY
SOLID WASTE
MANAGEMENT
SUBSYSTEM
SUBSYSTEM
COSTS
I
AIR
POLLUTANTS
SUBSYSTEM
EFFECTIVENESS
TOTAL COST OF
REGIONAL WASTE
MANAGEMENT SYSTEM
WATER
POLLUTANTS
AND LIQUID
WASTES
EFFECTIVENESS OF REGIONAL
WASTE MANAGEMENT
SYSTEM
Figure 2 TOTAL REGIONAL WASTE MANAGEMENT AND POLLUTION CONTROL SYSTEM
-------
pollutant producing activities, excepting pollution control and waste removal
activities) and from side effects of waste or pollution management activities
within the other two subsystems. For example, the input to the liquid waste
management subsystem results from all liquid pollutant-producing activities
of the household, industrial, and public sectors of the region. Included in
this input are the introduction of solid waste grindings into the sewer system
which provides a partial relief to the solid waste management subsystem and
other products of solid waste disposal operations such as waste waters
resulting from incinerator residue quenching operations, and leachants
into the ground waters resulting from landfill operations.
At the total waste management system level, the requirements
for information regarding any candidate subsystem consist of the following:
(a) Amount of pollution of interest to the given subsystem
which remains after the waste has gone through the
subsystem;
(b) Direct costs of the subsystem;
(c) Pollutant outputs by the subsystem which are of
interest to the other subsystems.
If, for each of the three subsystems, the above outputs are established as
a function of the input amounts of waste and pollutants received (as a
result of water management or pollution control activities associated
with the other subsystems), the decision-maker of the total waste manage-
ment system has the essential information necessary for decisions regarding
the overall .system. Given any combination of postulated subsystems,
and assuming appropriate analytical models, the following properties of
the overall system can be investigated:
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(1) Cgmjg_at_ib_ilityand Balance
By virtue of the output pollutant and waste data associated
with the individual subsystems, a determination can be made
of each subsystem's capability to handle all the wastes or
pollution conveyed to its part of the system. For example,
if the liquid waste exceeds the design capacity of the
liquid waste subsystem, then these subsystems, when examined
jointly, are incompatible. Subsystems which can function
together in the sense that no capacity violations or
exceedances of technological capabilities would result are
compatible. On the other hand, a compatible system is
conceivable in which there are subsubsysterns whose entire
capacity or capability cannot be utilized, thus representing
an inefficient use of resources. A desirable system is one
in which there is a state of balance; each subsystem is
just large enough and has just enough technological capabi-
lity to handle all waste and/or pollutant inputs to it from
the general environment as well as from outputs from the other
subsystems. Since facilities must be planned to serve over
substantial lengths of time over which the quantities of
wastes of various types will change, the concept of balance
must admit some unused capacity over the lifetimes of the
facilities to admit performance over the entire range of
projected input quantities.
(2) Total Direct Costs
Since one of the descriptors of any subsystem is its direct
costs, the total costs of any balanced system can be
determined, as defined above, by the addition of the
individual subsystem costs.
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(3) Overall System Effectiveness
Each subsystem, in addition to direct costs and information
pertaining to waste and pollutant outputs to the other sub-
systems, has been described with regard to the improved
: environment resulting from the operation of the subsystem
on given input amounts of pollutants and wastes. The
aggregation of these data from the three subsystems of any
balanced system constitutes the information upon which an
evaluation of total waste system effectiveness can be
performed. These data represent the amount of pollutants
or wastes remaining in the environment.
Having discussed the nature of systems analysis with regard to
the total regional waste management and environmental control system, and
its relationship with the solid waste subsystem, there remains the question
of the nature of system analysis specifically with regard to the solid waste
management subsystem. That measures are required of subsystem direct costs,
and of quantities of land, water, and air pollutants which are output by
the subsystem, have already been indicated. But there are many possible
configurations of the subsystem which might appear similar on the basis of
these types of measurements alone. In particular, the interactions among the
variety of waste sources, of solid waste types, of processing and materials
handling techniques, and of operating, management, and regulative bodies,
which characterize the complex called the solid waste management subsystem,
make choices among subsystem configurations difficult. A set of measures
of effectiveness appropriate to choices at this level is required; these
measures would be basic to systems analyses devoted to choosing among
alternative solid waste management subsystem configurations.
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2.3 The Role of Deleterious Effects in Deriving Effectiveness Measures
for Solid Waste Management Systems
On possible way to describe the effectiveness of the subsystem
concerned with solid waste handling is to measure various deleterious effects,
which are to be as small as possible in a "good" system of any given cost.
In addition to air and water pollution, with which we have already dealt,
commonly mentioned deleterious effects of solid waste and of solid waste
handling practices may be grouped as follows :
(a) Pest and Vector Propagation (Flies, Other Insects, Rodents)
(b) Other Physically Disagreeable or Harmful Effects
(Toxicity, Odor, Unsightliness, Interference with
Wild Life)
(c) Safety Hazards
(d) Incidence of Disease (Human Disease, Animal Disease,
Plant Disease and Crop Damage)
Certainly an ideal system for managing solid wastes would have all these
effects at a minimum level. Moreover, a concern for most of these factors
in combination is at the root of the reason for waste removal (beyond the
problem of having insufficient storage capacity); in other words waste is
nuisance material which must be removed from its source locations fundamentally
because of most of these factors.
A comprehensive literature survey of the health aspects or disease
relationships of solid wastes as well as the injury and safety considera-
tions associated with solid waste handling is contained in Ref. 10.
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It does not appear that a measure of effectiveness based heavily
on these deleterious effects would be of greatest assistance in making
decisions relative to solid wast handling systems. There are several reasons
to support this contention. First, if many factors are combined in a measure
of effectiveness, there is a danger that the measure will be insensitive to any
individual factor. A desire to be all-inclusive can result in de-emphasis, for
example, on the importance of the scarcity of available land in many areas. In
other words, from the point of view of deci si on-making with regard to subsystem
planning, it is desirable to attempt to isolate a smalj^ number^ of items which
appear to be intricately involved in the tradeoff process incident to subsystem
design and which are basic to solid waste management problems as they occur
in the real world. As will be seen from subsequent discussion, there are
other measures potentially more useful for decision-making in the face of the
dilemmas typically troubling the regional planner than the deleterious effects
listed.
A second, and more fundamental, reason for desiring to emphasize
factors other than the deleterious effects is that these effects are not
"traded-off" during subsystem design. Instead, these effects are recognized,
perhaps implicitly, by keeping them within acceptable levels and paying the
costs. Conceptually, any system planned with levels higher than these acceptance
levels has zero effectiveness and is not to be considered. The concept of
acceptance levels and their use in screening solid waste handling systems
are expanded upon in Appendix H.
For example, there would be a threat of fly and rodent propagation,
as well as such other deleterious effects as odor, if a system of non-removal of
waste was contemplated. Therefore, a service is performed by any system which
removes waste at all, to the degree that the fly and rodent propagation (and other
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deleterious effects) at the source of waste generation are reduced. This
approach is most useful, however, in explaining why removal of waste from the
local source within some minimal time is necessary; in other words a statement is
given of the necessity for some system which will not give fly and rodent
propagation the time and conditions required to become established. In
designing the system, however, "trading-off" with regard to various levels of
these nuisances plays no operationally-useful role. In the conceptual or
design phase of a system no one thinks of allowing a higher level of fly propa-
gation in exchange for a lower rat population. Similarly, there is no implica-
tion that a system with a relatively low rate of fly propagation is significantly
worse than a system accompanied by even less flies; nor is there any
implication that a system which allows rodents to propagate is any better than
a second system which allows even more to propagate. In other words, the
realistic decisions made on the level of broadest impact on the system design
assume that there is a maximum level of nuisances and pests which will not be
exceeded. Any system which exceeds these levels is unacceptable, no matter
what its other properties. Conversely, any system in which these effects appear
at below maximum acceptable levels is not considered better for that reason,
except in the rare case where two systems are equivalent in all other respects.
In summary it can be stated that a low rating with regard to one deleterious
effect cannot be offset by a particularly high rating with regard to another.
Therefore, pest and vector propagation, other physically disagreeable
or harmful effects, and safety hazards to the public are introduced into our
analyses as .side conditions and are not part of a primary measure of system effec-
tiveness. Any system which does not meet minimal acceptable levels with respect
to these factors are assigned zero effectiveness. The study has proceeded under
this condition by assuming that the acceptance levels associated with the
various standards would, if possible, be specified by either laws and legisla-
tion or by subjective/objective positions taken by regional representatives
associated with solid waste handling.
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While the establishment of public health as the primary measure
of social costs would lead to conclusions given, it is not clear that
from an economic or land-use point of view one would reach the same
conclusion with regard to some of the "other physically disagreeable or
harmful effects." Fire hazards are appropriately included among these
effects. For example, the unsightliness or odor associated with a waste
disposal facility may have a second-order but quantitatively significant
effect on the usefulness of land parcels in the vicinity of the facility
proper. The possibility of relating the physically disagreeable or
harmful effects to the economic and land use measures discussed further
on bears further investigation. Experience to date has amply demonstrated
that the economic impact on values and uses of land in the vicinity of a
disposal facility is primarily a function of public attitudes and good
public relations rather than being related exclusively to the presence of
the facility.
Safety hazards to the region at large is an effect already
mentioned as one to be handled similarly to the "other physically disagreeable
or harmful effects." On the other hand, safety hazards to refuse collection,
processing and disposal personnel are costs to the system itself rather than
social costs and are believed not to have an equivalent place among the
measures of effectiveness. To the extent that a given system might be so
lethal or dangerous as to be intolerable to the public, a side condition
would of course be set to preclude the use of such a system. However, it
does not appear that any of the major candidate system types comes so close
to falling in this category that it would be worth the trouble to include
safety hazards as an explicit side condition. As far as differences in terms
of injuries is concerned, these should arise naturally as additional elements
within the collection, processing and disposal costs.
The "incidence of disease" effects have not been included since they
are functions of more basic effects which are already represented previously.
Human disease, for example, is already implicitly incorporated by virtue of the
role played within the analysis of the "tradeoffs" with air and water pollution,
and by virtue of the controls on pest and vector propagation, toxicity,
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and safety hazards. In spite of the difficulty in establishing relationships
between diseases and waste disposal practices, one might consider adopting the
"incidence of disease" effects for explicit treatment, in which case it would
be desirable to eliminate the more basic effects correlated with them. For
example human disease incidence which is traceable to solid wastes and
solid waste management practices depends in part on disease vector propagation.
If human diseases were included among the measure of effectiveness, it would be
desirable to eliminate vector propagation. However, the latter effect is
objectionable for reasons other than disease incidence. As reported by an
Aerojet-General Corp. study (Ref. 11),flies and rodents are objectionable far
beyond their disease-carrying capability. The same study indi-
cated in general a rather low weighting to the "incidence of disease" effects
compared to other deleterious effects.
To summarize, it is believed that there are factors other than the
aforementioned deleterious effects which are most directly involved in the
actual design trade-offs facing planners of regional waste disposal systems.
These factors are discussed in the following subsection of the report. Many
of the deleterious effects, as outlined above, are of interest to the extent
that acceptance levels are necessary as specifications for systems being
designed and evaluated. Some of the effects are reflected in land use, con-
servation, and other economic factors, and therefore should affect the measures
to be discussed.
2.4 An Approach to Measurement of the Effectiveness of a Regional Solid
Waste Management System
The following is a discussion of effects which are not directly con-
cerned with public health per se, but which are measures of effects which can
be crucial to the success or failure of any solid waste management system.
Specifically, these are:
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(a) Production of Saleable By-Products
(b) Salvage of Resources for Return to the Economy
(c) Conservation of Land Resources
There is a widespread feeling around the country that one of the
more serious bad effects of common solid waste disposal practices is the dissi-
4
pation of the nation's resources. It follows, therefore, that a good system
is one which conserves these resources to a large extent. In its most
extreme form, this argument stresses those cases where wealth is actually
produced in the waste processing/disposal cycle. For example, the value of
compost created within a system is an indicator of its effectiveness, and the
enhanced value of swamp- or tide-land reclaimed as the result of fill operations
is another indicator of effectiveness.
As far as wealth-enhancing effects are concerned, the provisions of
the Solid Waste Disposal Act do not specify that production of wealth is a
major objective of any waste-management system. To the extent that it would be
established as an objective, one is dealing with overall regional or national
economic planning—a much higher decision-level. For this situation, an appro-
priate system analysis would investigate the role of solid waste management as
a subsystem within the regional economic system and a measure specific to the
operations of the subsystem as a part of the economic system would have to be
defined. It is not at all clear that the item of we a 1th-enhancement attributed
to the solid waste management subsystem constitutes such a measure. In other
words, the subsystem which produces the most wealth, for a given level of costs
or investment is not necessarily part of the regional economic system configu-
ration which produces the most wealth for a given expenditure.
In establishing the Solid Wastes Program of the National Center for Urban and
Industrial Health, the Surgeon General of the Public Health Service noted the
following provision of the Solid Waste Disposal Act..."to initiate and accel-
erate a national research and development program for new and improved methods
of proper and economic solid waste disposal, including studies directed
toward the conservation of natural resources by reducing the amount of waste
and unsalvageable materials and by recovery and utilization of potential
resources in solid wastes."
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On the other hand, it does seem that the conservation of resources
gets close to the heart of the solid waste management problem. When con-'
sidering the land resource, the need to conserve resources is not only a long-
range desideratum or a higher-level ideal reflected in indirect ways in
decisions made with regard to solid waste management, but is related in a most
direct way to the problem at the operating level. The scarcity of land near
the population centers for which there are few or no competing land uses, and
the knowledge that if land in the less densely populated areas is used for
waste disposal, it might not be available to society at the time other com-
peting land uses become manifest, are problems faced every day by regional
officials in planning waste processing and disposal facilities. So it would
appear that a subsystem which, for acceptable levels of air pollution and
water pollution, and for a given level of expenditures, competes the least
with other land uses (in other words which conserves the most land) as the
region develops, is highly desirable. In this sense, some of the wealth-
enhancing effects dismissed previously as being tangential, such as land
reclamation, now actually do tend to indicate high system effectiveness for
given cost levels. For while no credit has been given the system for the
wealth (land) it has (for all practical purposes) created, credit is given
the system by virtue of its not having used a corresponding acreage of scarce
land resource somewhere else.
Much the same argument could be made with regard to resources
other than land; in other words, the measure of effectiveness could reflect the
quantities of raw materials returned in various forms to society rather than
destroyed. Saleable by-products then are interesting not as examples of wealth-
enhancement but as conserved resources. The desirability of including this
measure depends on the basic objectives set for the waste-disposal system.
Essentially, it relates to the time-frame of the problem: the more one wants
to provide a tool useful over, say, fifteen, twenty or even thirty years, the
more appropriate it is to adopt a measure of effectiveness which incorporates
land conservation. The more one wants to look ahead, working from the attitude
that it is economically undesirable to dispose of materials rather than recycling
them through the economy, the more desirable, even necessary, it is to include
the conservation of other resources than land. Of course, the scarcity of the
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materials to be conserved would have to be considered, and the economies
associated with the conservation of the specific materials. It would appear
that this type of consideration should most appropriately be introduced at
several levels of decision-making higher than the regional waste management
or solid waste management levels.
It is concluded as the result of the arguments included here and in
Section 2.3 that to be most useful for decision-making with regard to the
configuration of the regional solid waste management system, the measures of
effectiveness should include the factors related to conservation of the land
resource. The land use and land availability aspect should be emphasized
since, unless solid waste is converted so that one essentially turns the
problem into an air pollution or liquid waste problem, the waste must in
one form or another be returned to the land. It should be recalled that
the solid waste handling problem as such did not achieve nationwide serious-
ness until the scarcity of land in various localities became critical. It
appears (although it involves a reverse of scale, resulting in a measure
of ineffectiveness) that a natural measure is the number of acres of land
devoted to waste disposal and for which there are alternative (competing)
land uses.
In order to measure the effectiveness of a given solid waste manage-
ment subsystem according to the approach just outlined, it would be necessary
to first define the time period over which the system is to be utilized, and the
types of facilities within the system. For any trial system, the sites of all
facilities to be used during the period, and estimates of the amounts of time
within the time period that each will be used for solid waste handling purposes
should ideally be designated. This might prove to be a difficult item to provide
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where the utilization time period is long or where the system concept is still
in preliminary form. It is not infrequent that regional officials have only
a general idea of the locale of their next generation of landfills, say ten
to fifteen years into the future. In these cases a cubic yardage require-
ment would have to be combined with knowledge of the terrain characteristics
of the general neighborhoods of the predicted sites in order to derive an
acreage estimate.
To be consistent in the application of the concept of minimising
interference between handling operations and expanding demands for land for
other uses, the acreage counted should not only include the processing and
disposal sites proper, but also adjacent or attached parcels of land whose
use will be limited by virtue of the existence of the processing and disposal
facilities. The inclusion of additional acreage or a buffer zone would
accomplish several things. First of all, it would account for the relative
undesirability of sites within the highly developed urban areas because of
the presumed higher tendency to encroach upon neighboring properties in terms
of restricting land use or preventing higher real estate values. Moreover, it
would allow the desirability of good disposal practices to be manifest by
reducing the adjacent acreage which is negatively affected. Thus, open dumps
should be highly ineffective, unless they are isolated within a sparsely popu-
lated area, by virtue of relatively large areas affected by them compared to,
say, well-operated sanitary landfills. On the other hand, such examples as
the Palos Verdes Landfill in Los Angeles County, California would contribute
low ineffectiveness (i.e. high effectiveness) because there are virtually no
negative effects on the neighboring properties.
For those cases mentioned above where only approximate site locations
are given it would be necessary to develop general rules relating the distance
from the boundary of a disposal site adversely affected, to sites of various
types and to sites within surrounding areas of various types. Ideally, it
would also be necessary to compile information on the "recuperability" of land
used for disposal purposes; that is on the lengths of time required for settling,
etc. before the land can be used for various alternative purposes.
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The information indicated in the preceding paragraphs, that is,
acreage estimates of all facilities to be used during the period, the time
segments of the period during which each will constitute a denial to the
region of lands which would have been available for other existing purposes,
amended to account for effects on adjacent land, would be combined to yield
the "ineffectiveness measure". The total acreage required for solid waste
handling purposes would be determined as a function of time. The function
would be the basis of an effectiveness measure to be used within the
systems analysis of the regional solid waste management system.
2.5 Other Measures of Effectiveness
Several other measures of solid waste system performance have
been suggested, namely:
Convenience to the Waste Producer
Adaptability to Statutory or Other Changes in Requirements,
System Reliability
Certainly all of these are desirable properties of solid waste management
systems. Here again, there is a question of the degree to which these factors
are "traded off" during system design, or whether some acceptable performance
level is established.
Although the convenience pattern appeared too well-established in
many municipalities within the SMSA to admit any trading-off (e.g. it
would be politically impossible in the City of Buffalo to remove roll-out
service) there are evidences in the newly developing areas of the Region
(where the individual contract with a private collector is still the rule)
that some cost-vs.-convenience weighing is explicitly practiced when more
highly organized forms of collection and disposal are considered or established.
And there have been ample evidences of a willingness on the part of Erie
County officials to pay more for a system which would not put County disposal
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operations at the mercy of the officials of a single town who might have an
unanticipated change of heart at a future time. Thus it appears that some
trading-off is actually practiced with regard to the adaptability factor.
Finally, municipal and County officials in the SMSA are well aware of the
dangers of operating with a single facility without a viable alternative to
use in emergencies, and of the fact that they are incurring expense in order
to avoid unreliable service. Although they are not treating this factor
quantitatively, they are implicitly weighing costs against reliability.
It appears that these factors hold some promise as measures of
effectiveness. Especially with regard to reliability, these factors appear
to lend themselves to quantification to an encouraging degree. Since other
measures (i.e. costs, acreage, pollutants of the various types) appeared more
promising, however, in providing a first cut at systems analysis in regional
solid waste management, these measures were not subjected to substantial
investigation in the face of more pressing study requirements.
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SECTIONS. THE STRUCTURE OF REGIONAL SOLID WASTE MANAGEMENT SYSTEMS
EVALUATION
3.1 Purpose of Studying the Structure
In this section the methodological structure of evaluating regional
solid waste management systems is examined. The elements of the evaluation
process are identified and the relationships among the elements are traced.
The structure given can be considered a generalized system analysis
model in the sense that many models which may be proposed for the analysis or
evaluation of waste management systems would fit within this general structure.
Indeed, if submodels and data of sufficient quantity and detail were available,
or if the time required to develop and/or gather these were available, an
evaluation model identical to the structure presented here might be contemplated.
For present purposes, however, the structure is not considered a model since
it does not allow for the actual manipulation of information nor can it be
used as such to produce results used in system analysis.
Construction of the model structure represents a necessary step in
the process of developing an appropriate system analysis approach to the solid
waste management context. A vehicle is provided wherein different system analysis
models can be examined in an orderly way and compared with regard to scope,
overlap or complementarity, and compatibility. In terms of the elements which
comprise any system evaluation in the solid waste context, it is easy to
clarify with respect to any specific system analysis model exactly those
elements which are: (i) held fixed, (ii) those which are being varied parametri-
cally, (iii) those which are being simulated or modelled, and (iv) those which
must be supplied as input data. There follows from the step of developing the
structure a number of decisions regarding "first cut" analyses that can be made
and the modelling and data needs required for them. Also there follows a more
definite specification of modelling and data gathering steps which should
closely follow in order to yield operationally-useful systems analyses £s
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early as possible. Section 3.6 contains a description of specific guidance
to current and future work yielded by the evaluation structure.
3.2 Major Elements of the Structure
In Section 3.3, the systems evaluation structure is presented in
detail. The following material provides an overview of the major features
of the evaluation structure with regard to information types within any
evaluation model. Fig. 3 contains this overview model structure.
The structure consists of the essential elements required for the
assessment of candidate regional solid waste management systems. Some atten-
tion has been given to the collection function in this structure in recognition
of the fact that this function is a factor in systems evaluation in general.
It is noted that the decision in Erie County to leave collection to the
individual municipalities is in effect an implicit judgment that minimal
acceptable collection service can be provided in this manner at acceptable
costs. Secondly, the collection function is shown in order to illustrate the
role played by this factor in relationship to other factors. Before describing
Fig. 3 in more detail, several fundamental comments should be made with
regard to this structure.
First of all, the structure is based on the idea, already expressed in
Section 2, that solid waste management is an interrelated portion of the total
waste management system, and therefore the evaluation of the solid waste
management system must yield measurements of air and water pollution along
with its other outputs. Furthermore, land use measurements as they relate to
urban, surburban, and rural portions of the region are important in evaluating
the solid waste management system. By this is meant the acreage used in the
various portions of the region by any candidate system being evaluated.
Similarly, within the developed areas, it is of interest to measure the
acreage used by the system in portions of those areas characterized by generalized
land use; e.g. the residential, commercial, and industrial portions of the
developed areas.
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If one "exercises" the model structure a single time through,
it will only yield measurements of the types indicated in Fig. 3 and will
not, for example, yield deleterious effects data or other indirect cost
data except to the extent that these are represented by air pollution, water
pollution, and acreage use measurements. This does not mean that the latter
are not represented in the analysis, however, for system analysis is viewed
as involving many runs of the evaluation model, where the input data are
varied parametrically to correspond to different candidate systems. Among
other parametric variations that may be contemplated are some representing
an assortment of performance or service levels. A series of runs in which,
as an example, the operating standards at landfills are systematically tightened
or improved so as to affect costs, capacities, and the types of waste which
might be routed to the various disposal sites, would effectively yield information
relating landfill indirect costs to the direct costs and to the other measures
of effectiveness of the solid waste management system, even though Fig. 3
does not explicitly show means of deriving such relationships. Fig. 4
represents an evaluation model structured as in the remainder of this section
(Section 3) being used within a series of runs over which performance standards
are systematicaly varied, in order to generate information relating to indirect
costs or deleterious effects.
Related to the previous comment, system optimization or other
i
management decision-making guidance can be provided by the model structure
only by means of series of runs with system characteristics systematically
varied from run to run. Thus there is no place in the structure for decision-
making with regard to (e.g.) source (refuse generation) area - facility
assignment or time-phasing of processing plant capacities; only the results
of any decision or possible decision can be given by the evaluation structure
as given. From this point of view, the advantage of decision algorithms
can be looked upon as requiring a reduced number of "runs" through the evaluation
model in order to reach a system configuration which yields satisfactory
cost and performance measurements.
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AN EVALUATION MODEL WITHIN A SERIES OF RUNS
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Another way of viewing the relationship between decision-making
algorithms or optimization models, as discussed in Section 4, and the evaluation
structure of this section is more germane to the conduct of the present
study. System analysis, being concerned with most efficient operations under
stated conditions and with the balancing of conflicting factors, is necessarily
involved with optimization analyses and decision algorithms. The development
of the evaluation structure helps to reveal optimization models which might
be designed, and helps the analyst to decide which of the many models possible
might be the most fruitful.
Finally, it should be noted that the structure includes considerations
of material flow, cost budgeting, and an evolving solid waste system. Candidate
systems can be examined over t time periods without restricting the examination
either to a single time period (e.g. one year) or to a prespecified time
period (e.g. 20 years or to the year 2000).
Referring to Fig. 3 , the locations and quantities of refuse
by type for Erie County and at a specified time period (e.g. 1966) are established
The degree of refinement in classifying the solid waste types is in large
measure dependent on the properties of the processing plants and disposal
sites being examined. So as to allow for the broadest range of systems
to be examined, the categorization of solid waste is sufficiently detailed
so that differences in plant and site technology could be measured. Based
on a set of routing algorithms or disciplines, the regional solid waste, by
location and type are assigned to specific processing plants and/or to disposal
sites. In either case, specific accounting, in the aggregate, is made of
the quantities, by type, which are transported to the processing plant and/or
disposal site. Maintaining information of this nature then allows for a
period-by-period comparison of the material processing and disposal requirements
and the extant available capacities of these facilities. Within the structure,
additional facilities with their associated capacities are scheduled for
and thus a time-phased routing schedule is established.
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The outputs to be derived relative to candidate solid waste systems
are:
o Gaseous wastes and air pollutants, by type and quantity
o Liquid wastes and liquid pollutants, by type and quantity
o Processing by-products with respect to processing plants
o Acreage occupied and "influenced" by plants and sites, by
subregion type.
For each of the major activities, including the direct cost of
collection, a cost budgeting is made. By direct cost of collection is
meant those costs associated with the handling of the solid waste up to the
time when the waste is in direct transit to the processing plant and/or
disposal site. Included within the cost budget for plants and sites are
the capital or investment costs, the operating and maintenance costs of the
facilities, and finally the transportation costs for handling the solid
waste from the source areas to the processing plants and then to the disposal
sites or to the disposal sites directly.
This in summary is an overview of the evaluation model and some
of the factors being introduced into or underlying the model structure.
Upon completing the computations for a single time period, many of the inputs
require updating (e.g. volume of solid waste generated based on per capita
generation rates, changes in population, and economic activity; processing
plant capacity increases (if required), disposal site residual capacity, etc.)
With these new inputs, the computation for the next time period is initiated.
Thus for any prescribed number of time periods, information is available, on
a time series basis, of the effectiveness, costs, pollutants derived and,
if and what types of performance standard violations have been experienced.
This last output is established under the conditions that acceptable
performance standards with respect to the deleterious effects have been
specified for that "run" through the evaluation model.
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3.3 The Finer Structure of Solid Waste Management System Evaluation
The flow diagram in Fig. 5 represents the finer structure
of evaluation of a solid waste management system. Besides providing more
detail than the structure as presented in Fig. 3 , this representation
differs in its greater resemblance to an actual computation model. Where
the overview structure emphasized data types and their relationships to
one another, this structure concentrates on specific data items and the
order in which they may be developed one from another, following a predesigned
set of computational instructions.
In examining the flow diagram it may be helpful to consult Table 2,
which contains a key to some of the symbols used.
For the reasons indicated in Section 2, the primary emphasis of
the model is directed toward the solid waste processing and disposal functions.
The collection function of the system is treated from the viewpoints of
transporting the waste from individual source areas to processing plants
or disposal sites and assigning a cost of the actual collection. Future
generations of this structure or a large-scale working evaluation model
would incorporate collection routines which allow for assessments of alternative
collection systems, and the implications of regionalizing this function
along with the other functions of the solid waste handling system.
The first significant steps in the structure are the computational
routines for determining the quantity of solid waste to be collected prior
to subsequent processing and disposal. The total quantity of solid waste to
be collected differs from the amount generated by such activities as on-
site processing and/or disposal sites includes grinders, incinerators,
compost heaps, and some forms of on-site dumping or land filling. In those
regions where on-site open burning is permissible,
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Entity Indexed by
TIME PERIODS IT
SOURCE AREAS I
PROCESSING PLANT TYPES J
PLANTS OF TYPE J IP
DISPOSAL FACILITY TYPES K
DISPOSAL FACILITIES OF TYPE K ID
No. of Given Entity
Contained in System
NTPER
NSAREA
NPLTYP
NJ
NDFTYP
NK
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this form of processing would be included. Since Erie County does not permit
on-site open burning, this process would be excluded from the options available
in applying the structure to local problems. In addition to computing the
reduction in volume and weight, estimates would be made of the gaseous components
and particulate matter introduced into the air, and the quantity of material
to be processed at the sewage treatment plant.
The next two major blocks of steps in the structure involve analyses
of the processing plants and disposal facilities. These steps are outlined
together since the form and outputs of each analysis are quite similar. For
each plant of a specified type (e.g. incinerator, compost, etc.), a material-
time flow is maintained and based on its operating characteristics, estimates
are derived of the gaseous effluents, particulate matter emitted, sewage
outputted, by-products recovered, residue derived and the processing costs
entailed. These estimates are then aggregated for all plants of a given
type. A comparable set of calculations and estimates are made for all
the processing plant types, over all source areas whose solid wastes are
transported to these plants and over the time periods being investigated.
The residue or reduced solid waste is then transported to the appropriate
disposal facility which had been previously determined and stored within
the routing data store. In examining the disposal facility routine, the
primary differences from the previous stage are (a) the determination of
the capacity utilized by the waste transported directly from source areas
or residue from processing plants and (b) the estimates of the water pollutants.
In both the processing plant and disposal site routines, computations are
made of the acreage affected. As mentioned previously, the land affected is
the land actually utilized plus the buffer zone. The size of the buffer
zone is a function of the location of the facility (urban, suburban or
rural, residential, commercial, industrial), and the types and levels
of the deleterious effects.
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As illustrated within Fig. 5 , the outputs derived are:
Disposal Costs
Processing Costs
Transportation Costs
Remaining Capacity at the Disposal Sites
Acreage Used or Affected, by Subregion Type
By-Products, by Type
Liquid Wastes and Water Pollutants
Particulate Matter Emitted
Gaseous Effluents, by Type
In addition to the outputs, estimates are made of the collection costs, and
a determination is to be made regarding violations of preset minimal perform-
ance standards with regard to deleterious effects. The latter determination
is discussed further in the succeeding Section 3.4.
3.4 A Minimum Acceptable Performance Screen
Before performing an evaluation of any candidate system or subsystem
within the formal evaluation structure, an initial filtering or screening
procedure of the processing plant or disposal facility with respect to
its associated deleterious effects would be made. Information would be
gathered from and with responsible regional officials to obtain regionally-
acceptable deleterious effects constraint levels. Alternatively, trial levels
can be set in order to assess the effects on the system of various acceptance
levels. Thus the filtering process involves, for individual plants or
facilities, a comparison of its deleterious effects (individually) and
the appropriate constraint level. Where the plant or facility either operates
below the constraint level (pass when below, reject when above) or can
be modified so as to operate below, the candidate is admissible for system
evaluation. For each subsystem which cannot meet the levels prescribed,
that is, does not pass all levels, the sub-system is not considered for
further evaluation. To the extent that this filtering can be accomplished,
this step insures first that the candidate system to be evaluated performs within
the regionally-derived deleterious effect constraint levels and secondly,
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eliminates the need to perform the lengthy evaluation (over time and source
areas) of systems which would be rejected.
Further attention is given in Appendix E to the formal aspects
of construction of minimal acceptable performance screens.
3.5 Requirements for Submodels and for Input Data
The requirements for submodels and input data are lumped together
since they are to a large extent complementary: a required item must either
be supplied directly as input data or else must be generated by means of
a submodel. In the latter case, other, more basic, data items will be
required as inputs. For example, refuse quantities for all future time
periods can be required as inputs, or alternatively, these can be derived
by means of planning-type population and land-use projections and a submodel
relating refuse quantities to populations and to economic activity. In
the latter case, the planning projections would be required as inputs,
as would the parameters of the submodel.
Thus it is almost inevitable that there be some lack of definition
in submodel and data requirements, since it is not appropriate during
development of the evaluation structure to be rigid regarding the choice of
elements to model and those data to supply directly. The list of requirements
which follows is consistent with the structure as given in Fig. 5. It
should be understood in the light of the preceding remarks that deviation
from this list of "requirements" will occur in actual evaluation model
design due to unavailability in the field of certain types of data, or
due to the evident difficulty of deriving submodels of various types. It
would be desirable in analyzing a given region to know the constituency
of refuse material as well as the quantity in order to assess, for example,
the effect of introduction of more household garbage grinders. This data
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is not likely to be available for many regions, so a submodel relating
constituency to (say) family size and/or income might be preferred. To give
another example, the operating characteristics of incinerators as functions of
the input refuse material appears to be an extremely difficult modelling task.
Therefore, for the present the analyst must be content with results based
on operations on refuse with "average" constituency. Data on the latter are
relatively easy to come by.
3.5.1 Submodel Requirements
In order to satisfy the structure given in Fig. 3, it would
be useful to have the following submodels. However, as noted above, in those
instances where the basic data required by the submodels are not available or
the internal submodel relationships are unknown, planning factor-type informa-
tion can be utilized in deriving the needed data inputs.
(a) TIME-PHASED SOLID WASTES CONTENT AND QUANTITY PREDICTIONS
This submodel would relate per capita growth in refuse quantities, and
content of residential refuse, to population characteristics (such as income,
household size, and rural vs. urban characteristics). The outputs of this
model would then be superimposed upon the population growth and projections
of other population characteristics in the various source areas (typical
regional planning information) to supply source quantity and content information
for the residential sector for any future time period. Similarly, another
submodel would relate refuse quantity and content to characteristics of com-
mercial and industrial activity (such as size of firms, soft vs. hard industry,
food processing or not) and superimpose this information on projections of
levels of activity of the various characteristic categories in the source
areas to obtain same quantity and content information for the commercial
and industrial sectors.
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(b) PROCESSING PLANT OUTPUTS
One submodel is required for each processing plant type (processing
plants also include railroad and truck transfer stations). The submodel for a
given process accepts variable quantities of refuse over some range of
constituent materials, and, considering the parametric information
describing the process and related anti-pollution devices, yields a description
of the results of the process in terms of the following quantities:
gas effluents by type
particulate matter emitted
outputs to the sewage system
solid residue by type
by-products by type
(c) PROCESSING PLANT COSTS
A submodel is required for each processing plant type which yields
processing costs as a function of the size (capacity) of plant, the quantities
processed, and the specific parametric information descriptive of the process.
The submodel would distinguish between fixed and variable costs, so that
given a specific location for a processing plant of a given type, acquisition
and capital cost data specific to the locality, a total cost of processing
can be determined for that plant which includes the fixed cost of establishing
a plant at the specific location.
(d) DISPOSAL FACILITY OPERATION
This submodel accepts variable quantities of input to the disposal
facility (site) over some range of constituent materials, and, considering
the capacity of the site and the parametric information describing the
disposal site operation, yields a description of the results of the operation
in terms of the following quantities:
volume utilized in disposal of refuse
capacity remaining
acreage equivalent of volume utilized
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(e) DISPOSAL FACILITY COSTS
A submodel is required which yields disposal costs as a function
of the size of the disposal facility, the quantities disposed, and the
specific parametric information descriptive of the disposal function. The
submodel would distinguish between fixed and variable costs, so that given
a specific location and acquisition and capital cost data specific to the
locality, a total cost of disposal can be determined which includes the
fixed cost of establishing a disposal facility at the specific location.
(f) TRANSPORTATION COSTS
This submodel accepts as inputs a given routing schedule among
source areas, processing plants, and disposal sites, together with quantity
information and transportation equipment information specific to each route
employed, and yields transportation costs. Incorporated in this model
are the map-related constraints implied by the necessity of following the
road/street network of the region in determining trip distances.
(g) LAND USE SUBREGIONS
A scheme is required for deriving the required division of the
region into subregions with regard to urban, suburban and rural characteristics;
with regard to predominant land uses (i.e. residential, commercial, industrial),
and with regard to lands being in-use or not being utilized or committed.
In the latter case, the non-utilized land must be classified according
to its developability or usefulness for agricultural purposes. Application
of the scheme to the subject region (in the present case, Erie County)
would be required after completion of the methodological study.
3.5.2 Requirements for Input Data
Data required as inputs to the structure, assuming that it possesses
submodels as just described, consist of the following:
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(a) SOURCE AREA DESCRIPTIVE DATA
A source area is a closed geographical area which contains a population
and in many instances commercial and/or industrial solid waste producing
activities. Wherever possible, primarily in the region's towns, the boundaries
of the source areas correspond to the U.S. Census Tracts. Within some
cities (e.g., Buffalo) it may be preferable to use collection districts
as basic source areas since most solid waste data is gathered and stored by
collection districts. Data required for each source area are:
population
(categorized according to the requirements of the content-residential
quantity prediction submodel)
commercial and industrial activity
(described according to the requirements of the content-non-
residential quantity prediction submodel)
area
(b) MAP DATA
The location of each source area and each processing plant or disposal
facility must be given, according to some coordinate system. Ideally, distances
traversed should be determined by travel on existing streets and highways. Thus,
unless a submodel is supplied which allows the traffic network to be "followed"
automatically, the distances from each source area to each facility destination,
and the distances between the inter-facility connections used by the system,
must be given as inputs.
(c) REGIONAL PLANNING DATA
Projections of changes in population over time with regard to its
descriptive characteristics and with regard to distribution over the region
will be required to appropriately relate predicted quantities to subregions
within the region. Projections are required also of levels and types of
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commercial industrial activity as distributed over the region. Since a
description of all processing plants and disposal facilities is contemplated
which includes a categorization of the location of the plant or facility
according to subregional type, the commercial-industrial subregional projections
will be required in order to relate the categorization to regional development
over time.
(d) DESCRIPTIVE DATA REGARDING PROCESSING PLANTS AND DISPOSAL FACILITIES
Data requirements are dictated by the output submodels of the
processing plants and disposal facilities, the cost submodels, and the
requirement for land employment output information. Specific requirements
are: Location and a Classification of the Location by Subregion Type.
It appears useful to categorize the land within a region as urban, rural
and suburban (less densely populated than urban but more so than rural).
Furthermore within the urban category, the location of the plant or site
should be further identified as to its relationship to industrial, commercial
or residential land use. A somewhat similar categorization of land use
within the rural and suburban subregions would be required.
(1) Acreage of Site
Given the location by subregion type, the acreage of the site
is determined based on the land actually dedicated to the plant or site
plus the necessary buffer zone about the plant or site. The purpose of
the buffer zone is to reduce the amount of nuisance to the population and
other land uses which are located within the vicinity of the plant or site.
In part, the size of the buffer zone is a function of the deleterious effects
which are associated with the plant or site and the location, by type,
within which the facility is to be established.
(2) Process and/or Disposal Operations Parameters
These are the data required as inputs to the processing plant/disposal
facility output submodels. They include such items as handling rates, material
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salvage properties, residue and pollutant-producing properties, depth of fill,
compaction ratios, etc.
(3) Capacity.
(e) DESCRIPTIVE DATA REGARDING TRANSPORTATION EQUIPMENT
As inputs to the transportation cost model, the equipment used
over each route followed must be known, as well as the number of truckloads
of refuse hauled, for transportation costs are most easily handled on a
cost per mile basis for truck loads of a given description. For the various
types of waste transported and for the equipment used to haul those materials,
one needs information regarding
o Tons of solid waste per truckload or, if more handy, for
the type of waste under discussion
o Volume of waste per truckload.
(f) COST INPUT DATA
Input data are required by the various processing plant, disposal
facility, and transportation cost submodels. These items primarily refer
to the direct costs associated with the major solid waste system functions,
for example the cost per mile of truckloads of given descriptions. Important
additional items, however, are the fixed costs to be associated with facilities
of various descriptions, given specific locations for them. These latter
items reflect, among other things, land values in the various localities
within the region.
(g) ROUTING INFORMATION
Any system description contains as part of its most basic data
that information which prescribes the destination of refuse of the various
types originating in each of the source areas. Furthermore, the residue
or process output at each of the processing plants must have a specified
destination or destinations determined from among the disposal facilities.
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Since the evaluation structure is oriented toward yielding measurements
on a given regional system, the routing information must be listed among
the inputs to such a structure. However, efficient routings and choice
of facilities is a prime subject of system analysis as described in Section
3.2; that is, in order to design a good system one determines (an iterative
process) an efficient routing by conceptually evaluating a large number
of trial systems with routings varied from trial to trial. Actually, this
is accomplished by means of a facility selection and source area assignment
algorithm.(See Section 4.)
It should be noted that routings and the set of active facilities
cannot be made once and for all, for processing plants become obsolete
and landfill sites become filled. Thus routing information must be time-
related; that is, a prescription for origins (source area), intermediate
stops (processing plants), and destinations(disposal sites) must be given
for each time period covered. The prescription must be such that no plant
is used longer than the design life of plants of that type and the capacity
limitations of a landfill is not violated.
3.6 The Structure as a Guide to Analysis on the Current Project
The major contribution of the structure is in providing a guide
to actual model-building on the current project. To be sure, given a study
effort of appropriate length and support, it would be possible to develop a
model corresponding to the entire structure, and go even further by computeriz-
ing the "routings" selection function. As a result, a comprehensive facility
choice and source area assignment model would be achieved which permits
evaluations of the system configuration thereby derived. Long-term efforts
of this sort are being attempted; see for example [Ref. 15]. For present
purposes, a modelling effort of more limited scope is appropriate, one which
compromised among the following:
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a) the effort could be completed in a relatively short time
period;
b) the data required was readily available, preferably pertaining
to the Buffalo area;
c) the output of the model could be put to use in assisting
decision-making with regard to regional solid waste systems.
As already implied in the previous figures and in the foregoing
discussion, development of rules for choosing among alternative facilities
and making assignments of source areas to the facilities chosen is the
central task of system analysis in the solid waste management context.
Therefore, it was decided to develop a model of this type with a manageable
level of detail. Consideration for the time involved on the one hand and
data limitations on the other eliminated much detail from consideration
as part of the model, for example, relating per capita generation of residential
refuse to income or other population characteristics, relating commercial
and industrial refuse generation to indicators of economic activity within
various categories of industrial and/or commercial establishments, attention
to constituent materials within the totality of refuse, introduction of
distances "along the road network" as opposed to straight line distances.
It was planned to begin by treating the facility choice problem
as a static problem (i.e. source quantities are constant over time and
there are no capacity limitations on disposal facilities considered). Linear
approximations to all processing, disposal, and cost functions would be
assumed. The model derived would be applied to Erie County data in order
to illustrate general applicability and capability to assist with a broad
range of planning questions. Next, the approach adopted would be extended
to planning for facilities with limited life and with capacity limitations.
The static model was developed and is the subject of the initial
portion of Section 4. Following this material, the plan for the dynamic model
is included in Section 4.7.
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SECTION 4. A FACILITY CHOICE MODEL AS AN AID IN REGIONAL SOLID WASTE
MANAGEMENT DECISION MAKING
4.1 Introduction
In this section, a model is described which yields, for a given
set of potential facilities of specified types and locations,
a) a selection of those facilities, and
b) an assignment of source areas to facilities,
such that the total cost of the facilities and operations with those
facilities is minimized over all possible selections and assignments.
Both fixed and variable costs are considered. "Facilities" in this context
refers to both processing plants (e.g. incinerators, transfer stations) and
disposal facilities (i.e. sanitary landfills). In the case of processing
plants, the model has the capability of choosing a disposal facility as the
destination of the output (e.g. incinerator residue, transferred and/or
compacted refuse) on a minimum cost basis.
It should not be inferred that providing minimum cost configurations
from among a fixed set of potential facilities (which are associated with a
set of performance levels of many characteristics which cannot be expected
to behave in some well-ordered way) is the most that can be expected of
system analysis in solid wastes management. Indeed, one needs only to look
to the venerable open-burning city dump solution to the municipal disposal
problem for evidence that a minimum-cost solution is not necessarily a best
or even a good solution. The spirit of the approach is rather that from
among system configurations which are equivalent in a system performance sense,
or which represent a set of system performances among which there is no
particular preference, it is best to choose that configuration which costs
the least. Therefore, it is useful in several ways which are enumerated
further on, to be able to find a minimum cost configuration from a set of
alternative system configurations.
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It has been observed that, even with explicit performance
measurement set aside for the moment, there have been few tools for
regional officials to use merely to accomplish cost minimization over a
wide number of choices. The typical procedure appears to be solicitation of
a handful of alternative system configurations from an engineering or
planning agency within the regional governmental structure or from a
consultant especially hired for the purpose. The costs associated with
each of the alternatives are computed, and at best one achieves a minimum
cost over the few alternatives considered. The choice of those alternatives,
while not arbitrary, are nevertheless not systematically generated and one
is left in many cases with the uneasy feeling that there are better alterna-
tives which might have been considered.
The model presented in this section represents a contribution in
at least these two modest respects:
o By enabling a large number of alternatives to be compared,
thereby reducing the chances of ignoring a good alternative.
o By allowing, through series of runs under systematically
varied input parameters, the characteristics of economically
most desirable systems to be defined. Or, at the very least
to obtain some idea of system configurations which are
clearly inferior to other possibilities, given various
combinations of input parameters such as processing and
disposal costs, distances to disposal facilities, and volume
reduction achieved during processing.
The latter point represents the first step in the direction of generating
some principles of good system design. Answers to questions of the
following types can be answered:
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What combinations of processing costs, distances to disposal
sites, volume reduction achieved in processing, transportation
costs, disposal costs, and refuse quantity generated in the
service area of the processing plant make processing more
economical than direct disposal? : ,
Are there areas within the region where such combinations are
achievable through transfer station operations? Through
incineration? Through more efficient incineration (greater
volume reduction, reduced disposal cost)? Through cleaner
incineration (increased processing cost)?
In servicing all areas where processing is not indicated,
what combinations of distances, disposal costs, transportation
costs, and refuse quantities generated over various portions
of the region correspond to situations where a single disposal
site is the economical choice? What combinations indicate two
landfills? Other numbers of landfills?
In answering,questions such as these, it will be noted that the service levels
implied by the parametric entries and the resultant outputs are not treated
explicitly. However, every input figure represents some service level, at
least implicitly, for a portion of the system. Runs under different cost
parameters or operating parameters represent runs with systems having
different operating characteristics. If these different operating character-
istics correspond to differences in system performance with respect to
increase or reduction of undesirable effects of solid wastes, the different
minimum costs achieved under the several sets of operating characteristics
represent the cost differentials among the several levels of undesirable effects,
For example, it is noted above that cleaner incineration, in terms of air
pollutants, can be represented by runs in which the processing costs are
higher. The higher processing costs in the latter runs imply, in general,
different minimum cost system configurations. Where incineration might have
been economical under the higher air pollution level, it may be economical if
cleaner operations are contemplated to eliminate processing and dispose of the
refuse by direct landfill. The cost differential, between incineration with
the original air pollution level and employing direct landfill methods for the
area which would have been served by the incinerator, can be thought of as the
cost of making the reduction in air pollution.
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Note that for this argument to be made it is necessary that,
under the higher air pollution level, the use of the incinerator in its
assigned area be indicated by minimum cost considerations. In other words,
if incineration were not economic over that service area, then the system
cost could be reduced by eliminating incineration in favor of direct landfill,
even without making the comparison with the cost of the contemplated
incineration improvement. Assuming that the level of operations at the
landfill were satisfactory, it would make no sense to associate this system
cost reduction with anything except adherence to the principle that among
alternative systems which are equally satisfactory on a performance basis,
it is sensible to choose that system which minimizes costs. (In the same
spirit, in the example where incineration is used even though direct landfill
would be the minimum cost method, the cost differential could be interpreted as
the cost of eliminating certain undesirable effects of landfills, or as a'
cost the community is willing to pay in order to conserve remaining landfill
capacity.) This example illustrates the crucial role played by minimum cost
considerations even though the evaluation of a system is not solely based on
costs.
The implication of the preceding discussion is that there is a
third respect in which the model presented in the following subsections
represents a contribution to better regional solid wastes management system
analysis, namely:
o By yielding, for any set of input values and possible
choices of facilities, a unique cost which can be used
as a normative value. Thus any system configuration which
violates the choices and assignments corresponding to the
minimum cost represents an additional cost which is presumed
to pay for the elimination of some undesirable aspect of the
minimum cost configuration.
This latter use of the minimum cost facility selection and source assignment
model is the most valuable from the point of view of systems modeling. For
it offers to regional officials a formal means of associating total system
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costs to system changes which effect improvements in performance in specified
ways. While the model as it stands lacks the degree of detail which it might
be desirable to have, nevertheless this notion of how to balance performance
against costs appears worthy of trial.
Explicitly, then, the notion is to develop models whereby regional
and/or local officials can derive the system costs of achieving various
performance levels, where the latter is represented in descriptive, multi-
variate terms just as it is in the real world. No attempt is made to
balance, e.g., a quantity of air pollution against a quantity of landfill
leachant to the water table. Rather, the system description includes the
descriptions of the incinerators and landfills as distinct items. In the
simple model, the air and water pollution resulting from the facilities must
be inferred; in a more complex model, these would be given as outputs. In
either case, differences among various system configurations with regard to
bad effects can be matched against cost differentials. An improved performance
system will presumably be adopted by regional authorities if the cost differen-
tial is small enough.
The model described in this section was designed as a first step in
the application of this notion to the specific problem context. Further
development along these lines would include explicit attention to the time
factor and the necessity for capacity constraints in the model as the sequence
of decisions over time is considered. With the completion of this step, it
will then be appropriate to develop a model which will include some of the
detail omitted from the first stage model.
In Section 4.2, several special case problems are discussed in
order to introduce the general approach and the notation. In Section 4.3,
the model itself is described, and the potential of using it to weigh costs
against elimination of undesirable effects of solid waste is made more explicit
in Section 4.4. In Section 4.5 the experience achieved thus far with the
model is discussed; the requirement for several facility submodels is noted
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in Section 4.6. Finally, a preliminary approach to the problem of extending
this model to cover time-phasing of facility establishment and retirement is
given in Section 4.7.
4.2 Basics of Source Assignment and Facility Choice Problems
In the following subsections, facilities are to be selected and
assigned to service portions of some circumscribed region, which will be
idealized as a closed region R in the (x,y) plane. A collection of I
refuse sources is given, the location of the i— source being at (x.,y.)
[1 * i ^ IJ. The quantity of refuse per time period is known for each i;
this is represented by the symbol q..
The point sources (x^.y^) are idealizations of small areas such
as census tracts, collection districts, or other functionally defined
collections of residences and/or businesses which are geographically homogeneous
This discretization of the waste-generating mechanism is necessary because
data (whether refuse quantities, or populations from which refuse quantities
are inferred) do not exist in density form and only are available for discrete
geographical sectors within any region under study. Were the other data of the
problem extremely precise, it would be possible to construct a model which
is based on individual households as source units and thereby have density
of population represented in another form. However, a real case for the neces-
sity of such fine detail would have to be made before embarking on such a
costly and time-consuming course. It is postulated that the discrete
representation is sufficiently fine for the present purpose of displaying the
utility of this general approach.
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4.2.1 The Decision to Install a Processing Plant - One Alternative
Landfill Site.
The installation of a processing plant (incinerator, transfer
station) is being considered, with its location at (x,y) = (0,0) if the
decision to install the plant is made. An available disposal (landfill) site
is located at (x,y) = (d,0), where d is in miles, and it is assumed
that the site has adequate capacity for purposes of this problem. The
problem is to distinguish that region, if any, where it would be preferable to
use the processing plant, and the complementary region where it would be
preferable to transport the larger volume of unprocessed refuse directly to
the disposal site. Under the processing alternative, all refuse from a
particular source i is transported to the processing plant, where it is
processed and reduced in volume according to the ratio
p = [volume of output] / [volume of input]
The reduced-volume product is transported to the disposal site
for final disposal. Straight-line distances are used in computing transporta-
tion costs. It should be noted that the preferences indicated are limited
to the two alternatives given, and do not necessarily imply that one or the
other will actually be adopted at a particular point (x,y) *in preference
to some third alternative.
The following unit costs hold:
cp = cost of processing ($/truckload)
c * cost of transportation of refuse delivered to facilities
in collection vehicles ($/truckload-mi)
c'T x cost of transportation of processing plant output to the
disposal facility ($/truckload-mi)
CD a cost of disposal of refuse or of processing plant output,
assumed to be the same ($/truckload)
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Therefore, one has the operating cost of the incinerator for each unit
quantity processed equal to bj • cp + p(c'Td + CD) , and the corresponding
operating cost of the landfill is given by b2 - CD- It is further assumed
that the capitalization and fixed costs associated with facilities of either
type are linear with daily capacity: that is, the capital cost per day of
the incinerator is AX + a^, if it is built, and that of the landfill is
A + a-q., where q. stands for the daily capacity of Facility j (j-1,2).
Thus the total cost is divided into fixed and variable portions, with the variable
cost of processing and disposal of a truckload of waste generated at i, if
processed at the incinerator, equal to GI = *l + bj, and the variable cost
of disposal of a truckload of waste generated at i, if disposed of at the
landfill without processing, equal to c2 - a2 + b2<
If d.. « distance from Source i to Facility j (i=l,....,I; j = 1,2),
then the total variable cost of processing and disposing of refuse collected
at Source i (including transportation of the collected refuse to the incinerator
or the landfill, but not including collection itself) is given by (c. •»• c d. .)q.
1 J ' !J 1
if Facility j is built and assigned to Source i. Using the constants
defined, it is noted that for a specific source i it is cheaper to process or
not to process according as c + c d.. or c + c d.. is the lesser. Supposing
that c + cd..0.
Similarly, if Cj + cTd-i > C2 * °Td'2 but refuse from So"1"06 i is processed
at (0,0) before disposal, the overall system cost would be increased by
[Cj + ^11 ~ C2 ~ c-rd.jjq^ 0. It follows that the sources where processing
is preferable on a marginal cost basis and those where direct disposal is
preferable on a marginal cost basis are separated by the boundary which is
defined by the equation c. * cTd-i * C2 * CTd'2' or
dil- di2 ' 'C2 - V/CT
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In other words, the desired boundary is the locus of points where
"N x2 * X2 - ^l(x-d)2 * y2 » (c2 - Cj)/^. Thus for -(yKcj - c2c2> tne left-hand "branch" of the hyperbola will define the boundary,
so that the regions will be shaped as indicated in Fig. 6(a). Where C2>ct»
the right-hand "branch" will apply and the regions will appear as in
Fig. 6(b). If c s c the regions will be separated by the straight line
x=d/2.
It is of interest to examine the various ranges of values of c.-c_
with regard to their operational meaning. The inequality c - c =-c d,
a condition where no hyperbola is defined, may be rewritten as
cTd + cp + p c'Td + pcD « Cp,
which means that it is cheaper to process a cubic yard of refuse generated
ajt the disposal site and then return the reduced-volume product for final
disposal, than it is to dispose of it unprocessed without transportation.
Under those circumstances it is clear that for all sources i processing is
preferable to disposal at the given site. Just the opposite occurs when
ci - C2 = C<*» wnich may oe rewritten as
c
pc'Td + pcD * cTd
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PLANT
DISPOSE DIRECT
DISPOSAL
SITE
1
Figure 6 (a)
BOUNDARY OF REGION WHERE PROCESSING IS PREFERRED,
0 < c - C< cd
PLANT
PROCESS
Figure 6 (b)
BOUNDARY OF REGION WHERE PROCESSING IS PREFERRED,
- cjd < C] - G£ < 0
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The latter inequality means that a cubic yard of refuse generated a_t the
site of_ the processing plant can be more cheaply disposed of unprocessed
than processed. Thus for refuse generated at other sources i, it is
a fortiori true that disposal at (d,0) without processing is preferable
to processing.
The conditions -cTd
-------
Cp » $12 per truckload
CD = $ 3 per truckload
CT = $ 2 per round-trip mile per truckload
c'T» $ 2 per round-trip mile per truckload
p - 0.2
Then one has c^ ~ 4.50 + 12.00 + 0.2(2d + 3.00)
= 17.10 «• 0.40d
C2 = 3.00
= 7.05 * 0.20d
According to the preceding analysis, since c.>c_, a region resembling
Fig. 6 (a) will exist providing 7.05 + 0.20d8.8. In other
words, if there is available landfill space within 8.8 miles, one can't
even define a region where incineration is potentially advantageous.
Interesting questions are raised by this conclusion for in fact
there are existing incinerator facilities operating with available landfill
close by. It is possible that the figures used are inaccurate, but the
conclusion is so definitely dominated by the high cp value that it is
doubtful whether the relatively small changes which might result from more
detailed study of the costs would cause a major qualitative change in the
conclusion. At best, the value 8.8 might be raised or lowered. It should
be kept in mind that in Erie County there are at least two examples of
incinerators (Buffalo West Side and Cheektowaga) with disposal sites within
a mile or two of them.
-73-
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A better possible explanation is that the time factor plays no
role in the analysis and that volume and capacity descriptions with regard
to the given landfill area are not considered. It may be that the diffi-
culties in acquisition of suitable areas and the limitations on the total
available area suitable for disposal sites impels decision-makers to behave
as if disposal were more expensive. In other words, higher values are
imputed to c in order to allocate to each cubic yard of disposed material
the acquisition costs and indirect costs involved in devoting land, a
scarce commodity, to this particular use. For example, suppose CD = 17.10
$/truckload, with all other constants as originally given. Then
0
-------
Then one has c. « 1.35 + 6.00 + (0.40d + 3.00)
- 10.35 + 0.40d
C2 = 3.00
3.675 * 0.2d
which is less than d whenever d > 4.6 miles. Thus the region where truck
transfer is preferred to direct disposal without truck transfer cannot be
defined if the disposal site is within 4.6 miles; whenever a site does exist
which is further away than 4.6 miles, the region where truck transfer is
preferred over direct landfill resembles the one pictured in Fig. 6 (a).
In the paragraphs above, regions of preference for service by
a processing plant rather than by a direct landfill facility were described.
Existence of an area where processing is preferred refers to a collection of
sources such that, given that both facilities were in existence, it
would be cheapter to be serviced by the processing plant rather than by the
landfill with no intervening process. This still does not settle the question
of when and when not to build the anticipated processing plant. If R consists
of two non-overlapping areas R. and R~ where processing is and is not pre-
ferred, and if R. is non-empty (the cases in the example above where d was
sufficiently small to prevent the boundary hyperbola from being defined are
cases where R. is empty and R-R2) , then further rules are needed to guide the
decision on the building of the facility.
Recall that the capital costs associated with any facility consist
of fixed and variable portions. Intuitively, it is clear that if the sub-
region where processing is preferred is not a high-quantity generator of refuse,
then the decision not to establish the plant should be made. Similarly, if
the fixed costs involved in establishing the plant are sufficiently high compared
with the landfill facility, the decision not to establish the plant would be
«ade, since the high fixed cost would be large compared to the increased
-75-
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operating costs due to disposing without processing of refuse from RI>
This suggests that in order to appropriately make the decision regarding
the establishment of a processing plant, the refuse quantities q^ [previously
defined] and the fixed costs A. must be brought into the analysis.
Consider a disposal system in which all refuse originating in R^
is processed before disposal while all refuse originating in R2 is
delivered to the disposal site (d,0) for disposal without processing.
Let the symbol JE , where S is a subset of the region R, be interpreted
*}
to mean "sum over all indices i for which (x.,y.) is in set S". If R. is
empty, no processing is performed at all in R and the cost C of the system
is the constant value L, where
2 R
£
-------
That is, if C(system with no processing)
-------
d = 25
d = 20
-K d = 15
d = 10
(a) TRANSLATION NORTH OF THE
CENTRAL BUSINESS DISTRICT
CO
Q
CO
d = 25
d = 20
d = 15
d = 10
(b) TRANSLATION EAST OF THE
CENTRAL BUSINESS DISTRICT
CO
o
o
(c) TRANSLATION SOUTH OF THE
d = 25 CENTRAL BUSINESS DISTRICT
0123
DISTANCE FROM THE CENTRAL
BUSINESS DISTRICT
Figure 7 VARIABLE COST ADVANTAGE OF INCINERATION AS A FUNCTION OF
DISTANCE FROM THE CENTRAL BUSINESS DISTRICT
-78-
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against distance from the central business district. In (a), the locations
are successively farther to the north, in (b) they are successively farther
to the east, and in (c) they are successively farther to the south. One plot
for each of the distances d = 10, 15, 20, 25 is given in each of (a), (b),
(c); in each case the potential landfill location is d miles due east of the
incinerator site.
The plots of Fig. 7 illustrate the following points:
(a) On the basis of transportation, processing, and disposal costs
alone (i.e., excepting collection costs, where transportation of collected
refuse is separated from the "collection" function) the distance to the
landfill has a stronger effect on costs than the location of the incinerator
within the city;
(b) The characterization of advantageous locations for processing
plants is strongly dependent on the landfill locations.
In particular, the plots show that whatever the distance d, costs are relatively
insensitive to relocations of the incinerator north and south of the central
business district, but that the advantage that incineration has over direct
landfill increases with easterly locations of the incinerator (i.e., in the
direction of the landfill). In other words, if the potential landfill sites
are all in one direction, it appears that the best location for one incinerator
would be at the edge of town lying in that direction, providing that the
variable cost advantage is large enough to override the fixed costs associated
with the incinerator.
To illustrate the effect of fixed costs, Fig. 8 shows one of the
curves of the previous figure, namely where d=15 and the potential locations
are all easterly of the central business district. It should be noted that
the vertical axis of Fig. 7 gives not only the variable cost advantage of
incineration, but is also interpretable as the maximum fixed cost which would
allow establishment of the incinerator. (This interpretation follows from
the inequality which gives the condition for establishment of the
-79-
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2500
2000
1500
VARIABLE COST ADVANTAGE
OF INCINERATION, d = 15.mi
1000
TOTAL COST ADVANTAGE OF INCINERATION WITH
d = 15 AND INDICATED INCINERATOR LOCATION
500
DO NOT
ESTABLISH
INCINERATOR
FIXED COST DIFFERENCE A, BETWEEN
INCINERATOR AND LANDFILL
ESTABLISH
INCINERATOR
I
I
I
I 2 3
MILES EAST FROM CENTRAL BUSINESS DISTRICT
Figure 8 THE DECISION TO BUILD OR NOT TO BUILD
AN INCINERATOR, ILLUSTRATIVE CASE
-80-
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facility.) The second curve of Fig. 8 is an illustrative plot of A.,
fixed costs (on a per day basis) of establishing a basic incinerator,
against distance from the central business district. It says that,
primarily as the result of higher real estate values in the central
business district, A.s [fixed costs of a basic incinerator], expressed
on a per day basis, is $1800 per day in the central business district and
diminishes according to the illustrative curve down to $500 per day 3 miles
to the east. The result is that no incinerator can economically be built (USING
THIS ILLUSTRATIVE DATA) within 1.2 miles of the central business district.
Beyond that distance, there is an advantage to incineration, which, in
this illustration, increases with distance of the incinerator location
east of the central business district. Locating the incinerator three
miles to the east, it would be over $1500 per day cheaper to establish an
incinerator than not to establish it (and use the landfill site 15 miles
away.)
The drive of the analysis to place the incinerator at the edge
of town is strongly influenced by the location of the unique landfill site.
There will be more of a tendency to a central location under a (perhaps
•ore realistic) assumption of several landfills, in some variety of
directions. This could be examined with a model such as that of Section
4.2.3, where the decision to install an incinerator, against several
alternative landfill sites is discussed. In the following Section,
however, it is handy to first discuss the choice among a set of potential
landfill sites and service areas assignments appropriate to the choice.
4.2.2 The Choice Among Several Disposal Sites in a Region
In Section 4.2.3, the decision to install a processing
plant is examined for a region in which there are several disposal sites.
In that section, the rule for deciding whether or not processing is
-81-
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preferred for a given source (x., y.) is based on a comparison of the
processing alternative with the best alternative for that (x.,y.) among
all the disposal sites. Therefore, it is appropriate to examine the question
of preferences among disposal sites prior to discussing the decision
regarding whether or not to process.
Similar to the earlier analyses, no restrictions are placed on
the availability or the capacities of these sites, except insofar as these
may be reflected in the unit disposal costs. At this time, the number and
location of sites are given, and there is no concern for the problem of
appropriately locating sites and furnishing the most efficient numbers. It
has already been pointed out how central to the entire approach it is for
service areas associated with all facilities, including disposal sites,
to be determined according to a minimum-cost criterion consistent with the
one used in Section 4.2.1. It is, of course, of interest per se what
the service areas, so determined, look like.
4.2.2.1 Simple Preference Among a Given Set of Disposal Sites
To begin, J disposal sites are given, the J site being located
at the point (x' y') of R, j = 1,...,J. Similar to Section 4.2.1, the
capital cost per day of disposal site j is given by A. + a.Q. where Q. is
the daily number of truckloads delivered to the site, the operating cost
per truckload is b. = c^, where c^. has the same interpretation as a
unit disposal cost with respect to the j site as c.. did in Section
4.2.1 with respect to the disposal site of that analysis. Thus the total
cost per day of operating the j site at a level of Q. truckloads per
day is A. + (a.* b.) Q. where A. represents a fixed cost and the
3 3 3 J J
sum c. = a. + b . represents a variable cost per unit.
-82-
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Since it is assumed that the J sites are prescribed beforehand,
i
the total £ A. of the fixed costs represents an immutable portion of
the total cost. Total cost minimization can be achieved only by making
the total of the variable costs and transportation costs as small as
possible. For present purposes, therefore, the fixed costs A. can be ignored.
As in Section 4.2.1, let d.. be the distance from Source i
to Site j, i = 1, ... ,1; j=l,..., J. Consider an arbitrary source
(x., y.) in R. The variable cost per unit, of transportation to, and
disposal at, Site j is given by c_d.. + c.• For a given i, it is
preferable to dispose of refuse at that site which minimizes c_d. . + c.
over all j, 1 < j < J.
It is assumed that there are no two disposal sites j. and J2 such
that c > c. and
jl J2
~\|
1
(x. - x )2 + (y - y )2 < (c - c
Roughly speaking, this says that the difference in disposal costs between
the sites is large relative to the cost of traveling between them. Suppose
there were two sites satisfying the preceding inequality. Then if for some
source (x., y.)» the inequality
i J2 * J2 ^2
were to hold, it would also be true that
"\|(x , x )2 + (y - y )2 - "\|(x - x )2 + (y - y )2 > (c. - c.
1 i J2 * J2 i Jl Jl Jl J
)/CT
2 l
-83-
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But there are no points (x.ty.) such that this occurs, for
1|(x.-x )2 * (y.-y. )2 - l|(x -x )2 + (y.-y. )2 < T|(x -x )2 * (y. -y.
K i J2 i J2 I x Jl x Jl " I Jl 32 Jl J
tor all (x. ,y.) . (The latter is the triangle inequality.) It follows
therefore, that for all (x. , y. ), it is cheaper to dispose at Site j- than at
Site j. , and the latter can be eliminated from the problem.
Assuming that J sites are given, and that for each pair of sites
j and j- with c. >c. , the inequality
J J
holds, then R is divided into J sub region R., R_,..., R_, where by
definition R. is the set of all (x. , y.) in R such that
|(v
mm
1*j'
[CT ||
That is, R. is the set of points (x. ,y.) where disposal at Site j is
preferred to all other sites.
Any pair of sites j. and j- implies a partition of R into two
subregions, one where Site j, is preferred over Site j., and the other
where Site J2 is preferred over site j.. Assume that c. £ c. ; then
the boundary between the two subregions satisfies
A|(x-x. )2 + Cy-Xa )2 - A|(x-x )2 + (y-y. )2 = (c - c ) / c
1 J 3 ' J J J J2
-84-
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If c. « c. , this boundary is a straight line*. If c. >c. , the boundary
is half a Hyperbola, specifically that half which corresponds to having a
positive quantity on the right hand side of the equation. The effect is that
Site j, is preferred within the convex region surrounding (x. , y. ), and Site j_
^1^2
is preferred within the larger, complementary region, which includes (x. ,y. ).
J 2 J 2
(It should be noted that Site j. has the more expensive variable costs.)
Figure 9 illustrates the shapes of the regions of preference between two
disposal sites.
Since any pair of sites gives rise to a partitioning of R by means
of a hyperbola as just described (the straight line of the c. = c. case is
J j J2
considered a degenerate hyperbola), and since finding the sub-regions R.
involves comparing the costs c. for all pairs of sites, the process of
defining the R. is equivalent to checking the inequalities which hold in the
subregions which result from superimposing the J(J-l) / 2 hyperbolas correspond-
ing to the possible pairs of disposal sites. For example, R. must be the
interaction of the (J-l) sets
in R cx.-x.) + (y) - (x. - xh) + (yryh)= CVCJ)/CT
•£.
defined for 1 = h = J,h t j. The latter are distinguished by means of (J-l)
of the total of J(J-l)/2 hyperbolas of the problem, specifically the
(J-l) hyperbolas corresponding to comparisons with Site j.
To illustrate, ten landfill sites were selected arbitrarily as
potential landfill sites for non-urban Erie County. These locations are in-
dicated by the circled numbers of Figure 10 . in this illustration, the
costs associated with all facilities are assumed to be the same, c. = 3.00
as in the previous section. Transportation costs are also carried over from
there, c_, = $2 per truck load.
Specifically, the perpendicular bisector of the line segment connecting
(x , y ) with (x , y. ).
-85-
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(DISPOSAL LESS
EXPENSIVE)
PREFER SITE j2
(DISPOSAL MORE
EXPENSIVE)
PREFER SITE j,
Figure 9 REGION OF PREFERENCE BETWEEN TWO ALTERNATIVE DISPOSAL SITES,
-86-
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Boundanes Which Ate Not Tract L
-------
BOUNDARY SYMBOLS
Census Trad Bound»'*s
Wino* C<«i< Di
Otrwr Tract
Boundar.es Which *'* Not Tract Lines
______ M.r»0« Civil DiviMXt L>f
Figure 11
REGIONS OF PREFERENCE AMONG TEN ILLUSTRATIVE LANDFILL SITES,
SOURCE AREAS REPRESENTED BY CENSUS TRACTS.
-88-
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and large in number, application of the above argument would result in the
service areas indicated in Fig. 10 . However, since the distribution of
refuse sources is approximated by the set of discrete sources corresponding
to census tracts, the service areas are distorted into those shown in
Fig. 11.
It should be emphasized that this result is not equivalent to a
recommendation that all these facilities be put into existence, merely
that the service areas be as designated if all these facilities are given.
With the introduction of fixed costs into the analysis, it is sometimes
cheaper to incur increased variable costs by eliminating one or more
facilities in order to save even larger fixed costs.
4.2.2.2 The Effect of Fixed Costs on the Choice of Disposal Sites
In Section 4.3 the rationale is given for an analysis which
permits a minimum cost choice from among a given set of facilities to be made.
In Appendix I the details of a computer model which performs this analysis
are given. In the present section the purpose is to lay the groundwork
for the succeeding discussion of processing plant installation by understanding
t
what is meant by the given set of landfill facilities and how that set might
be arrived at. Therefore as illustrative material the results of several
runs of the facility selection computer model are presented here, where the
model was applied to the set of landfill facilities depicted in Figs. 10 and
11 under several assumptions regarding fixed costs.
In Figs. 12 and 13, the same set of ten landfill sites are
considered, with c. * $3.00 per truckload for all sites and c_ » $2.00 per
mile per truckload. In Fig. 12, all facilities are assumed to have a fixed
cost amortized at $20,000 per year. In Fig. 13, the common fixed cost is
$60,000 per year. It will be noted that with the $20,000 fixed costs, Sites
2 and 5 are eliminated. When the fixed costs are at the higher $60,000 figure,
Sites 3, 9 and 10 are further eliminated. Therefore, with ten sites given
as in Fig. 10 , and with the fixed and variable costs given as in Fig. 13,
-89-
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Boundaries Which Are Not Tract Lines.
__ ^ _ Minor Ctv.1 D-vn-on t-o
Fiaure 12 CHOICE AMONG THE LANDFILL SITES OF FIGURE 10, AND THE
CORRESPONDING SERVICE AREAS. AMORTIZED FIXED COST OF
EACH FACILITY = $20,000 ANNUALLY
-90-
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Boundaries Which Are Not Tract Lines
Mino* Civil D-viS-O" Lin*
to 13
CHOICE AMOMG THE LANDFILL SITES OF FIGURE 10, AND THE COJ^SPONDING
SERVICE AREAS. AMORTIZED FIXED COST OF EACH FACILITY = $60,000 ANNUALLY
-91-
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there would be only five landfills, located as in the latter figure, and the
service areas would be as indicated in the same figure if minimum costs are
to be achieved.
This example illustrates the increased undesirability of proximitems
landfills as capital costs increase. It also illustrates the interaction of
that general rule with population density. For while Sites 5, 9 and 10 cannot
be justified because they are too close to Sites 4 and 6, the higher waste
generation densities in the northern part of the county allow Sites 1, 7,
and 8 all to remain in spite of their being closer together than (say) Site 10
is to Site 6.
The manifestation of the tendency to eliminate proximitous landfills
which is specific to this particular example is always to favor the landfills
in the populated areas over those in the isolated areas. That is because
the fixed costs and disposal costs are all equal, and therefore, the choice
is being made essentially on the basis of transportation costs. In a more
realistic example, the costs of the rural sites would be lowered to reflect
lower acquisition costs and perhaps less taxing operating requirements and
there will be more of a tendency for the remote sites to drive out nearby sites
in spite of higher transportation costs.
To the extent that higher operating standards for landfills are
reflected in higher costs, the tendency to eliminate proximitous landfills
reproduces the recent experience of less-populated towns and villages which
heretofore had suffered no economic hardship in maintaining separate open-
burning dump facilities for each of a myriad of jurisdictions. With the
imposition of higher operating standards at the State and County levels,
these smaller jurisdictions have been less able to "go it alone" and have
either sought consolidated facilities or, at the very least, have turned
the disposal problem over to private operators who, by providing service
to a large number of jurisdictions, in effect provide consolidation of a
different sort. At any rate the economies of scale are realized.
-92-
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-
BOUNDARY SYMBOLS
'OSuS Tract Boundaries
Boundaries W'hich Are Not Tract Lines
_ — Minor Civil Diwiiion t'f>»
Figure 14 CHOICE AMONG THE LANDFILL SITES OF FIGURE 10, AND THE CORRESPONDING
SERVICE AREAS. A2 = 0; A, = A4 = A6 = A7 = A8 = $60,000 ANNUALLY
-93-
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Finally, one further example is given to show the effect of a site
with cost advantages over the other sites. The five sites 1,4,6,7,8 were
tried, with fixed costs all equal to$50,000 per year as before, along with
Site 2, which now is assumed to have no fixed cost. Variable costs c. are
equal in all six facilities, c. » $3. per truckload; CT = $2. per mile per
truckload as before. It is as if Site 2 is an existing facility, where
the others are potential facilities requiring some initial capitalization.
The results are given in Fig. 14 , where it will be seen that Site 2 has a
substantial service area. Site 2, having been eliminated even in Fig. 12,
clearly is at a disadvantage with regard to transportation costs. Here
is an example then, where that disadvantage is washed out by a fixed cost
advantage to result in making existence of the additional facility economical.
4.2.3 The Decision to Install a Processing Plant - Several Alternative
Disposal Sites
Now it is assumed that (J-l) disposal sites have been chosen for
the region R, and the latter has been divided into (J-l) subregions R., ...,
RT which represent the service areas of the (J-l) sites. In this section
the problem is treated of characterizing those situations where it would be
desirable to introduce a processing plant into the region. If introduced, the
plant would be located at a specific location (x* ,y'T) in in R.. Under
j j x
these circumstances, it makes sense to assume that all processing plant
products will be disposed of at Disposal Site 1.
All notation used is as defined in previous sections.
Consider now an arbitrary source in R. It must belong to one of
the R.. Clearly, the decision regarding whether processing or direct disposal
is preferable at a specific source in R. involves only the plant and Disposal
Site j, for disposal at any other site could only increase the total cost of
the disposal system. Thus, for points within R., the determination of preference
for processing, or for direct disposal, on a unit cost basis, is much
like the original problem of determining the region of preference for
processing, with only one alternative disposal site.
-94-
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The only difference is that for sources in R. with j t 1, processed
refuse is taken to a different disposal site (Site 1) than nonprocessed
refuse (Site j). Instead of Cj - AJ + bj • 3j * cp + p (c'Td + CD-) for each jfl,
as would be implied by direct analogy with the case of one alternative disposal
site, one has Cj=a. + b, » a.j + cp * p(c'Td + CDI) no matter which disposal
site is of interest. Here, d ="\/(xl. - x* )2 + (y'. - y')2;note also that
I j j j J
c. * a. + b. = a. + CD. is required for determining preference between Disposal
Site j and potential Processing Plant J.
Specifically, for Source i located within R. the region of preference
for processing is R . which is the set of all sources i in R. such that
JJ J
CT l"lJ - V S cj - CJ
where d.j and d.. represent the distances from i to the processing
plant site and to Disposal Site j, respectively. In other words, suppose
the analysis of Section 4.2.1 were performed using Site j as the single site,
and using the revised c. instead of the original, and suppose that as the result
J
of that analysis the region of preference for processing over direct disposal at
Site j were determined. Let R' be that region. Then the desired region
JJ
R.. of points within R. where processing is preferred to direct disposal
JJ 3
at Site j (hence preferred to direct disposal at any other site) is merely
RT. » R' .^R.. The region R. - RT. is the region where direct disposal at
JJ JJ 3 J J3
Site j is preferred both to processing and to direct disposal at any other site.
It follows that the region R is partitioned into the following sets,
which intersect only at their boundaries: RT » Rr,1-' ... *~> R, T » the set
u J1 J , J ~ i
of points in R where processing is preferred, and the (J-l) sets R. - RT.
J JJ
where direct disposal at the various disposal sites, without processing,
is preferred. Consider the disposal system in which all refuse originating in
R, is processed before disposal (at Site 1) and all refuse originating in R. - R_
j j j
is delivered to disposal Site j for disposal without processing. If R. is
«pty, no processing is performed at all in R and the cost C of the system is
the constant value L, where
-95-
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J-l J-l
L- ZA. + ZZ [cTd.. + c ] q.
j = l J j«l R. ! 1J -1
If Rt is non-empty, the cost of this system is
J
J.I
» L + A. + T 7 [cT(d. T-d..) * (CT-C.)] q.
J *Z\ n— T lJ 1J J J 1
J — i K , .
J Jj
Note that the square-bracketed quantity in the summand is negative over
the interior of RT.. Therefore, if it is assumed that the fixed cost A.
Jj J
of the processing plant is incurred, it follows by definition of the R 's
and by the argument used previously for the case J«2 that any other partition
of R into areas to be served by the plant and by the respective disposal
sites could not produce a smaller cost.
It follows that the given system is the minimum cost system, as
in the case J»2, (i.e. one alternative disposal site) if
C (system with no processing) = C (system where processing is performed in R..)
Thus the minimum cost system employs + processing for refuse originating
in Rj whenever
J-l
If the left hand side < A., then processing is not introduced.
v
The square-bracketed quantity in the summation is positive in R^,
and it is clear that processing will be attractive only if refuse quantities
are high within RT. This is consistent with the general practice of
J
adopting incineration only for areas of high population density.
It does not necessarily follow that the most economical system is
the one which has the incinerator location at the point of highest population
-96-
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concentration, or of the highest concentration of solid waste sources. This
is because the fixed cost A. must depend on the location of the plant.
u
In particular, acquisition of sufficient property within the area of highest
solid waste source concentration can involve extremely high fixed costs
relative to another location for the plant within an area of lower concentra-
tion.
This can be stated succintly as follows: Let the left hand side
of the preceding inequality be denoted S. Then the cost of the disposal
system may be written
C - L - (S-AT) when S - A.
j J
• L otherwise
The minimum cost system is not the one with the greatest S, but the one which
•aximizes (S-A,). The idea of the preceding paragraph is that one can conceivably
J
gain in S by use of a location right in the center of population or waste
source density, but incur an A. that is so much larger that the difference
(S-A.) is small.
j
As illustrations of analyses which can be performed using this
•odel, consider the following:
1. The example illustrated by Figure 7 could be extended to the case
tfhere the alternative is not one disposal site to the east, but several sites
surrounding the city. It might then be expected that the directional effect
of the single disposal site would be removed, and even though the Central
Business District might not be the best location for the incinerator due
to prohibitive acquisition costs (or the cost of operating with minimal
deleterious effects in that neighborhood) some location other than the edge of
the city might be best.
2. A similar analysis could be run with constants adjusted to reflect
truck transfer operations. The output could be combined with data from the
incinerator analysis in order to determine those combinations of distances and
-97-
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costs which indicate incinerator operation, those which indicate transfer-
landfill operations, and those which indicate no processing at all.
3. An acceptable configuration of landfill sites could be chosen to
serve the non-urban county, and the desirability of introducing processing
into the most (i.e. excluding Buffalo) densely populated part of the county
could be examined under various assumptions regarding processing costs and
processing ratios p.
4.3 A Static Model for Choosing Among Several Processing and
Disposal Facilities
4.3.1 General Description
The approach described in Subsection 4.2 is easily extended to cover
a broader class of problems regarding facility choice. A "facility" is either
a processing plant (e.g., incinerator, truck transfer station) or a disposal
site (i.e, a sanitary landfill).
There are J facilities under consideration, indexed by j, l=j=J.
Solid waste generation is approximated by point sources corresponding, typically,
to census tracts, collection districts, or other sectors within the region as
a whole. There are I sectors, indexed by i, l$i*I. The quantity of refuse
originating in i is q.. As in the preceding Sections, each facility j has
associated with it a fixed cost A. and a variable cost c., where c. = a.+b.
with a. being a cost per unit of increasing the capacity of the facility one
more unit, and b. is the unit operating cost. The cost of transportation of
a unit quantity of refuse delivered to facilities in collection vehicles is
c per mile. The distance d.. is the distance from Source i to Facility j.
And here we define the new symbol k.. = total variable cost per unit of
processing and/or disposal of waste generated at i, if i, is in the service area
of Facility j.
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In the previous discussion, either J consisted of all disposal
sites or there was only one processing plant considered. In the latter case,
discussion centered around the processing plant. Here the more general problem
is addressed of specification of a logical procedure for determining which of
a set of facilities to establish, and the service areas corresponding to the
facilities in the chosen set. In particular, choice can be made from among
a selection of processing plants and a selection of disposal sites. The
procedure is amenable to computer processing, and a FORTRAN program is given
in Appendix I for finding the collection of facilities, and the service area
assigned to each facility, which will (process and) dispose of the solid wastes
of the region with minimum cost.
Broadly speaking, the number, type, and location of facilities is
specified, and the minimum cost selection is made from among the given collec-
tion. For each facility j selected, the service area R. is obtained, which
is the set of sources i serviced by j. The capacity Q.= £- q. of Facility j
J Kj 1
is determined by the model; the amortized capital cost per time period, of
providing a facility of that capacity (per time period) is given by A.+a.Q.,
also determined by the model.
If non-empty regions of preference R.,...,Rj are obtained by com-
paring costs k.. as in Section 4.2.2, the variable cost portion of total
cost will be minimized, by use of that set and by use of the service areas
implied by R.,..., R , over any subset of those facilities. This however does
l J
not minimize total cost, since by eliminating a facility, and reassigning the
i's within its service area to other facilities, the resultant increase in
variable costs can possibly be more than offset by saving the fixed cost of
the facility eliminated.
The problem can be phrased as follows. To each source sector i
assign exactly one facility j(i). Let F = [j | jsj(i) for at least one i].
PROBLEM: Assign to each source i one facility j(i) so as to minimize
f V iVuai"!
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Stated in this way, where it is implied that the constants k.. are fixed before-
hand, the problem may be solved by special integer-programming techniques
known as zero-one integer programming. In the present context, having all
constants k^. fixed beforehand is equivalent to predetermining a disposal site
destination for the output of each processing plant in the problem. Since
cost minimization can possibly involve elimination of one of the disposal sites
from the system, this assumption can be troublesome. Since there are some
problems of interest which do not involve processing questions, and since it
is realistic in other problems to predetermine landfill destinations for the
processing output which are not included among the disposal facility choices
(e.g., certain landfills are for incinerator residue alone) the fixed k..
assumption does not necessarily render useless any techniques based on that
assumption.
It would be better not to be bothered by that assumption, however,
and for other reasons as well as this one, a technique was developed which did
not require that all processing plants be preassigned a disposal site to receive
its output. Assume for the moment that the k.. are fixed beforehand. Note
J ^
that of J potential facilities, there are 2 -1 possible selections. For
example, of the four facilities A, B, C, D, there are 15 possible selections
of facilities:
A
B
C
D
alone
alone
alone
alone
A
A
A
B
B
C
and
and
and
and
and
and
B
C
D
C
D
D
A,
A,
A,
B,
B
B
C
C
and
and
and
and
C
D
D
D
All of A, B, C, D
Given any individual selection, the minimum cost under that selection is achieved
by assigning to each i that facility, from among those in the selection, which
minimizes k... The minimum cost over all selections is therefore achievable
*J J
by a systematic comparison of the costs associated with each of the 2 -1
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possible selections. The objective of the zero-one (and in fact all) integer
programming techniques is to circumvent the need to examine all (2 -1) selections
making a number of tests on the array of k. .-values. Often, entire sets of
selections (e.g., all selections which include a certain facility) can be elimin-
ated if the collection of k. .'s display various properties. For example:
as usual let R. be the set of all sources i such that ^ILk =k. . , i.e.,
J l*h£J ih 13 '
k^ is the least of k^,..., k^ for those i in R.. For each i in R. determine
the index j'(i) associated with the next best k. . available for that i. Then
if R- ^kij' (i)~kij^i ~ Aj (i>e- the variable cost penalty incurred by letting
each i be served by its j'(i) rather than by j is smaller than the fixed cost
of j) then clearly Facility j can be eliminated from consideration. By per-
forming a number of tests of this type the number of selections actually
examined can be cut down considerably. However, if the number of facilities
is moderate, the amount of testing itself represents a considerable amount of
effort compared with straightforward evaluation of all possible selections.
The approach of reviewing all (2 -1) possible selections in a routine fashion
appears to be little less efficient, if at all, for the cases with k..'s fixed
beforehand. But it offers an additional advantage in not requiring that disposal
sites be assigned to processing plants before the analysis begins.
For the assumption that ki . constants are all determined beforehand
is equivalent to saying that for all processing plants the operating costs
per unit quantity are
b. = CpUMcj.d'. * c'Dj]
similar to Subsection 4.2.1, where
cp(j) = cost of processing per unit quantity of input
p. = reduction or conversion factor
= [output in output units] /[input in input units]
c' = cost per mile of hauling a unit quantity of output
d! = distance to (predetermined) point of disposal of output
c' . = cost per unit quantity for disposal of output at the
(predetermined) disposal site assigned to Facility j.
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If that assumption is not made, and b. can change depending on the trial selection
of facilities because under a given selection a more advantageous disposal
site may be available for the output of processing Facility j, then the expression
for b. must be rewritten for each trial selection. Assuming that under a
specific trial selection the destination of the output of Facility j is disposal
Facility j1,
bj • cp(J> * Pj
where d'(jfj') is the distance between the two facilities j and j1, and
CD(J') is the unit cost of disposal at Facility j1. Under any selection,
the disposal site assigned to processing Facility j corresponds to the
index j• which minimizes the bracketed quantity over all disposal sites
in the given selection.
A straightforward series of steps can readily be inferred from the
discussion which are amenable to digital computer programming, and which lead
to a minimum cost selection of facilities and service area assignments for
each of the selected facilities. A computer routine which performs these steps
is given in Appendix I. The program is based on a subroutine, described in
Appendix H, which allows all of the 2 -1 possible selections out of J facilities
to be generated in turn.
For each selection, the minimum cost configuration of service areas
is found, and the corresponding cost is computed. This quantity is compared
with the lowest previous cost found in the selections reviewed prior to the
current one. If the cost achieved with the current selection is less than or
equal to the best previous one, the facility selection, configuration of service
areas, and cost achieved are printed out. If the cost achieved with the current
selection has been bettered by a previous selection, the routine continues with
the next selection supplied by the selection generating subroutine. After all
possible selections have been reviewed, the last selection printed out (or the
last several if there are any ties) is the minimum cost selection.
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Steps taken by the routine with regard to each of the (2 -1) selec-
tions are as follows:
1. Does the selection contain any disposal sites?
(If so, go on to Step 2; if not, the selection is
not a feasible selection and the program skips the
rest of these steps and calls the selection generating
subroutine for the next selection.)
2. Does the selection contain any processing plants?
(If not, go directly to Step 4.)
3. For each processing plant (say Facility j) compare
the quantities [c'd1 (j,h) + c (h)] where h runs over
all disposal sites in the selection. Let the
minimizing h be designated j'. Facility j1 is the
disposal site assigned to receive the output of
Facility j. Compute b. = cp(j) + p. [c^d1 (j , j') +
cn(j')] f°r each processing plant, and c. = a.+b..
4. For each disposal site (say Facility j), let b. =
cn(j) and compute c. = a.+b..
5. For each source (say Source i) compare the quantities
k.. = [cTd..+c.] where j runs over all facilities in the
selection. Let the minimizing j be designated j(i).
Facility j(i) is the facility whose service area contains
Source i. If there are two or more j's which determine
the minimum k.., record this fact, but let j(i) = the smallest
of the minimizing indexes.
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I
6. Compute ^A. + £-. k. ...^q., where the first sum
3 i=l i,J UJ i
is over all facilities in the selection. This is the
minimum cost possible with the current selection of
facilities; this quantity is compared with the minimum
costs achieved with the other previously generated
selections.
It should be noted that for an arbitrary Facility j, the service
area under any selection is the set of sources i such that j(i)=i. It should
further be noted that the quantity Q.« 2.q., where the sum is over all sources
in the service area of j under the minimum cost selection, determines the
quantity of unprocessed refuse to be received by Facility j in each time period.
There are no capacity figures set as constraints on facility sizes in this
model, and the quantities Q. are used as indicators of desirable facility sizes
within a planning context.
4.3.2 Distance Data Required
In order to compute the required constants k.. the distances d..
corresponding to each pair (i,j) are required, among other data. With regard
to the d..'s, road distances rather than straight-line distances should be given.
Since it is extremely tedious, and possibly not too fruitful to provide actual
road distances between each source and each facility location appearing on any
run of the program, an estimate of the form
[road distance] = o(. • [straight line distance]
is used, with evidently satisfactory results. The requirement is for IJ distances,
so that use of the estimate eliminates need for a considerable amount of input
information. The distances can be computed if one includes among the inputs
the locations of all facilities on some coordinate system. Besides the IJ
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distances d.., there will also be need for some of the (_) distances between
pairs of facilities; these are represented by the distances d'(j) and d'(j,j')
of the foregoing text. It should be noted that indications exist of the size
of the factor ct, . Results quoted in [Ref. 35] specify
-------
• Run through a similar series with parameters reflecting
transfer station operations, to determine the distances
over which such operations would be economical.
• In the above situations change cost relationships or
process reduction parameters from run to run to see how
the distances for economical operations under incinera-
tion, transfer and direct landfill are affected by costs
or the process input-output relationship.
• With fixed transportation and landfill costs, vary
landfill locations over the county and distance between
landfills from run to run in order to determine how
closely landfills can economically be placed as a
function of various population density levels.
4.4 Application of the Model to Balance Costs Against Various Levels of
Deleterious Effects of Solid Waste
In Section 4.1, it was suggested that the minimum cost approach
was basic to the idea of allowing the difference in costs between two system
configurations to be identified with the levels of service inherent in the
two configurations. In effect, what was said was that the cost differences
among systems configured differently were attributable to differences in
service rendered by the different systems as well as inefficient use of the
facilities available under any configuration (e.g. improperly defined service
areas from the point of view of minimum system costs). By use of a minimum
cost concept as in the facility choice model described above, the portion of
the cost differential attributable to inefficiencies is minimized and the
differentials can therefore be interpreted as reflecting the costs of
different levels or types of service.
This is not the same as quantifying deleterious effects of solid
wastes, in the sense-of measuring the^loss to the community due to those
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deleterious effects in dollar terms (e.g. increased cleaning and painting
costs due to incinerator effluents in the air). Nor does it provide a
measure of dis-service or level of bad effects on some non-monetary value
scale such as has been developed by .Aerojet-General [Ref. 11]. It does, however,
offer an analytical means whereby regional decision makers can weigh costs
against benefits of regional system configurations with stated operational
characteristics. Given two system configurations displaying characteristics
(including bad effects of solid wastes) between which decision makers at the
regional level have no marked preference, the cheapest configuration will
presumably be preferred. If the characteristics of one system configuration
are preferred over those of a second, it is the task of the decision makers
to decide whether the difference in costs, which is the price of the preferred
configuration as compared with the other, is acceptably low. This is good
systems planning procedure, and any analysis which advances the capability
for making this decision is presumably good systems analysis.
This argument bears on development of a facility choice model in the
following way. The cost relationships introduced in previous sections, namely
Cost per time unit of Facility j = A. * c.Q.
r j 3 jx.,
and the operational parameters used to determine the c.'s themselves, implicitly
reflect quality of operations and levels of bad effects of solid wastes and
solid wastes processing and disposal practices. Just as series of runs were
contemplated over which locations and types of facilities were varied, one
can also think of series within which quality of operations is changed from
run to run.
For example, suppose for an incinerator facility, say Facility j,
three sets of operational parameters are considered which will be designated
as GOOD, BETTER, and EXCELLENT modes of operations. Suppose that these
designations represent quality differences in terms of volume reduction and
quality of residue as well as amounts of particulate and gaseous effluents.
Specific plant descriptions designed to characterize the three quality
designations will lead to estimates of volume reduction, quality of residue,
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and amounts of particulate and gaseous effluents for the three modes of
operations, as a function of level of operations in terms of average quantity
incinerated per unit time. From these, reduction factor values corresponding
to the three modes, which can be designed p. , p. , p. respectively, can
be derived for use within minimum cost computations. In addition, associated
with each of the designations there will be a pair of cost constants,
A' ' , c. ' to reflect GOOD operations
A. , c: ' to reflect BETTER operations
, cfE) to reflect EXCELLENT operations.
A series of runs in which the various sets of constants are
changed from run to run will result in the following:
a. The amounts of residue under the three modes will differ. Because
of this, the transportation costs will differ and the landfill
requirements for disposal of residue will differ under the three
modes .
b. The minimum cost system configurations under the three modes
will differ. This is a reflection of the different amounts of
residue and the different transportation costs as well as the
differences among the G, B, and E sets of fixed and variable costs.
In general, even where the incinerator is. economically justified
under all three modes of operation, the average quantity Q. of
refuse to be incinerated each unit time period will be different
among the three modes, as will the service area assignments.
c. The minimum costs themselves under the three modes will differ.
These different costs are more than the mere statement of the total
costs
* cj« . A°» * =f >
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per time period to build and operate Facility j under the G, B, and E
modes respectively. Because of the system relationships involved
(more incinerated implying more residue, implying higher transporta-
tion costs and required landfill space, implying higher landfill
costs, and so on) the cost differentials under the three modes of
operations refer to the total system cost of the minimum cost systems
derived under the three sets of input data.
d. From the quantities Q> * , Q, Q obtained under the respective
modes, and from detailed process descriptions of incinerators
representative of tne three modes of operation, calculations can be
made of the air pollutant emissions to be expected under the three
modes. These can be expected to differ markedly. This data,
together with the landfill space requirements and knowledge of the
locations involved, affords the decision maker a picture of
relative bad effects of solid waste under the three modes. The
different bad effects levels can be compared by the decision
maker and weighed against the different costs involved in bringing
them about to see if potential improvements are worth the
additional cost.
It should be realized that this approach does not depend on there
being exactly three modes or any other specific number, and that the "G-B-E"
classification was used above merely for illustrative purposes. In practice,
something akin to the "G-B-E" definition of modes of operations might be
adapted from a facility checklist and scoring technique such as has been under
development by the U.S. Public Health Service. Or, the modes of operations
might reflect measurable engineering performance rather than a qualitative
categorization of operations. In fact, the modes might reflect a performance
measure which is in concept a continuous parameter, for example incinerators
classified according to the percent of pollutants the anti-pollution devices
are designed to remove.
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4.5 Experience with the Facility Selection Model
This study was methodological, and the primary concerns with the
facility selection static model were whether it would produce the types of
answers it was expected to, and whether it could do so within reasonable
limitations on time, effort, and expense. Performance of actual system analyses
were of interest only in the sense of providing a real context for development
of the tool. Moreover, it was believed that extensive running of the program
as applied to current Erie County problems would be inappropriate without a
credible collection of submodels relating costs and operations of facilities of
various types. This point is elaborated upon in Section 4.6.
In this short section some general comments will be made on the
operation of the program. Then the runs made thus far with the program
will be enumerated, and those not previously presented in the foregoing
discussion will be elaborated upon.
The computer program for the facilities choice static model performs
its tasks with brute force rather than guile. With only a superficial
examination it is easy to see that it is wasteful of steps and storage; it
probably wastes computer time as well. No effort at all has been expended on
optimizing this program in any way. It should also be mentioned that the
program embodies two features which work against short running times: (1) if
any source can fall into one of several service areas without enlarging the
minimum cost configuration, this is noted in the output, (2) if more than one
selection of facilities exists which yields the minimum cost over all selections,
the equality is noted in the output and the service area assignments associated
with each of the selections are each printed out. The figures employed during
the computation are in "floating point" form which makes detection of costs
which are exactly equal a non-trivial task.
In spite of all this, the computer times experienced with the program
have been quite satisfactory. All runs have had the number of facilities J no
more than ten. With J=10, there are 2 - 1 « 1023 possible selections to
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cycle through. An early test run using J = 10 and the number of sources I = 20
was completed in 25 seconds (of which approximately half was devoted to
loading and operating system steps) on the IBM 360/65 at CAL. A more recent
run (which was used to derive Fig. 12) had I * 110, the number of sources in
Erie County excluding Buffalo, and J = 10. Independent of compiling, loading,
and other operating system steps, the run was completed in 94 seconds. Since the
program was designed for testing concepts and for development of a characterization
of good system configurations, it is not necessary that this program be capable
of reproducing the entire existing County "system" which has over 30 separate
facilities. Rather, it is expected that the expressed purpose can be best
served by studies in which J is not too large; for such studies the computer
times are certainly within the tolerable range.
To date, the following runs have been made, over and above
runs completed during the debugging stage.
1. Forty runs, on data from the City of Buffalo, used to derive Fig. 7.
Results have been discussed in Section 4.2.1.
2. Four runs, on data from Erie County except Buffalo, used to
derive Figs. 11-14. Results have been discussed in Section 4.2.2.
3. One run, on data from Erie County except Buffalo, used to illustrate
use of the model with a mix of facility types. Discussed in next
paragraph.
4. Fourteen runs, on data from the City of Buffalo, used to consider
various possibilities for incinerator sites within the City of
Buffalo. Discussed several paragraphs farther on.
As already indicated, the first two sets of runs have been discussed elsewhere.
The other two will be described right here.
The single run on County data excluding Buffalo had J=5, with three
landfills, one incinerator, and one truck transfer station. The landfills were
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at locations 2, 5, and 10 of Figure 10; from previous runs it was reasonable
that this trio would not tend to eliminate one another, and the selection
makes sense from the point of view of land availability. The incinerator
location was an arbitrary one in the City of Tonawanda, the area of highest
waste generation density in Erie County excluding Buffalo. It was selected since
it appeared that if there were one area outside Buffalo where incineration might
be advantageous, that would be the one. The transfer station was situated at
location 6 of Fig. 10; it seemed a likely spot since it is a fair distance
from any of the landfills and it is a suburban population center.
The facilities data used on this run was the same as that used in
Section 4.2.1 with one exception: where c_ = 3 $/truckload as in the former section,
Cg = cjo » 6 $/truckload was used to account for the fact that location 2 is
the site of an existing landfill while land in the vicinity of locations 5 and
10 would have to be acquired and developed into landfills, and for the fact
that excavation costs at location 2 are minimal since it is the site of a dry
bed stone quarry. It is realistic to make A2 = 0. Since the fixed costs
associated with the rural landfills are small compared to the processing
plants and certainly compared to the total cost, the simplifying assumption
A5 = A10 " ° could be safeiX made. Fixed costs associated with the incinerator
and transfer station were amortized at $60,000 and $10,000 per year, respectively.
(Note again, the capital cost of a facility is not amortized at A. per year, but
at A. + a.Q. per year, where Q. is the average quantity per year input to
the facility.)
The results were that the incinerator is justified while the transfer
station is not. It should be noted that the approximate location of 6 has
been suggested as the site of a truck transfer station, but only with location
2 as an alternative, not location 10. The incinerator would send its residue
to location 2 of the three available in the run; in reality there is a small amount
of landfill nearby, reserved for special types of refuse, which makes a better
destination, but this is of no particular interest in the present discussion.
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This run was the one whose output appears in Appendix I; the selection
(1*2,3,4) on the printout refers to sites 2, 5, 10, and the incinerator in Ton-
wanda, respectively.
The set of 14 runs on City of Buffalo data was for the purpose of
investigating whether other locations in the City would be more suitable than
the ones actually used. In all runs, it was assumed that the Squaw Island
Incinerator (West Side) was a fixture, although its capacity was left to be
decided (i.e. operations at current capacity were assumed to cost nothing
except operating costs, while expansion to larger capacities would involve
additional variable costs). The following general tendencies were found in
the data:
1, The minimum cost solution is to expand the West Side Incinerator so
it can service all of Buffalo, unless the variable costs per ton at
the East Side Incinerator (c_) and the variable costs per ton at the
West Side (c.) are approximately equal or c2c1 and Buffalo does proceed with a new
^ L '"'-*~ ~*
plant, the resultant system cost less the minimum cost (achieved
by building enough capacity in the WS plant to handle the whole city)
can be considered the cost of insurance against total breakdown of the
entire system or the cost of some degree of flexibility of the system.
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2. There evidently are no conditions under which more than two
incinerators could be economically justified.
3. of a variety of materially different locations within the City,
no location ever beats out the present site of the ES incinerator
as the site of a second incinerator except a location in the heart
of the central business district, and this can only be done by
making fixed cost assumptions for the downtown location which are
unrealistically competitive with the ES site. Moreover, the runs
were done under the assumption that the downtown site and the ES
site would dispose of their residue on the Squaw Island site, near
the WS incinerator. As was indicated in Section 4.2.1, if an
alternative site east of the city, or in the eastern part of the
city, were provided to receive the residue of the ES facility, what
preference there is for a central site will be even further lessened.
Incidentally, a site sometimes proposed in South Buffalo cannot be
economically justified even if the assumption is made that the
fixed costs are competitive with those of the ES site. The latter
tips the scales unreasonably in favor of the South Buffalo site,
since it does not belong to the City and the ES site of course does.
The preference of the ES site over the one in South Buffalo is mani-
fest in spite of the fact that it was assumed that on-site disposal
of residue would be possible at the South Buffalo facility, if it
were built.
4.6 Facility Submodel Requirements
As has been indicated elsewhere, full use of the facility selection
model to perform comprehensive system analyses requires submodels of facility
operations and costs. Submodels of all facility types which might conceivably
be part of the regional system are required, including landfills, incinerators,
transfer stations, composting plants, etc. Submodels will also be required of
major subtypes, for example "cut-and-cover" landfill operations as distinct
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from operations where an existing excavation or low in the terrain is filled, or
truck transfer stations as distinct from rail transfer stations.
These submodels need not necessarily be complex; in fact the entire
preceding discussion rather dictates that they be simple in structure. It is
•ore important that they be valid, and widely accepted as such, within the error
tolerances appropriate for the context in which they are used, than it is that
they describe the operations in minute detail. It should not be forgotten that
the use of these submodels, and of the entire facility selection model, is to aid
regional officials working in an area where it is possible to hear arguments at a
county agency meeting over whether a new incinerator (with capacity and location
thoroughly understood and operating characteristics generally understood) will
cost five or ten million dollars!
The following comments will apply to facilities meeting a fixed
standard of operations, whether that be good, better, excellent, or conceivably,
a low standard. Subsequently, comments will be made on supplying the required
data for each of a given set of standards.
With respect to each facility type or major subtype, and given a
fixed standard of operations, the requirement is for a description of a typical
facility of the given standard, described as a function of the average quantity
of refuse per time period that is input to the facility. It is, of course,
possible to collect empirical data on facilities of various sizes, but this
•ethod is not too fruitful in at least three respects:
1. All facilities of a given size (capacity) are not identical or even
similar with regard to anti-pollution control devices or measures,
neighborhood land values, quality of structure, etc. Nor, clearly,
are all facilities with comparable anti-pollution controls found to
have the same capacity. Attempts to cross-classify make the number
of items within any cross-classification too small to yield valid
generalizations.
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2. Descriptive data on existing facilities represent a range of
facility construction dates and hence a range of construction and
operational practices as well as a changing cost level. Thus it
is even difficult to get a picture of present costs from past data,
not to mention future costs.
3. New facilities tend to outstrip past facilities in size as well as
performance, and extrapolations are necessary to yield estimates
based on past data. For example, it is difficult to find data
describing operations of incinerators of 1200 tons per day capacity.
Likewise it is impossible to find empirical data on incinerators with
electrostatic precipitators.
It is more expensive, but better practice to define a set of bench-
mark operating capacities, and for each capacity have specialists in the design,
construction, and operation of facilities of the given type or subtype generate
a typical facility of the given capacity and meeting the underlying standard.
A description of each facility could be generated therefrom. This description
would include:
Acreage Required (Including any Buffer Zones)
Structures Required
Square Feet in each Structure
Administrative Personnel Required
Operating Personnel Required
Dollar Costs of these Personnel
Construction and Installation of Equipment
Dollar Cost of Construction of Equipment
Dollar Cost of Installation of Equipment
Other Equipment, such as Motor Vehicles
Large Items of Maintenance and Frequency
Labor and Materials for Routine Maintenance
Materials Required for Operations
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From such a detailed list and current cost data, the cost of a facility in any
region and any time period could easily be assessed, if only the dollar items on
the list are reviewed periodically and updated with the same expertise as was
applied to the original. Moreover, if information is gathered regarding land
values in the area of a potential facility, it is easy to convert the "Acreage
Required" information into a cost item.
The result is that for each capacity a complete evaluation of capital
and operating costs would be available, and this would be based on a facility
of known and stated characteristics. Inclusion of other items in the description
referring to pollutant emissions, quantities of output material (for processing
plants), and landfill capacity used per time period enable the requirements for
information on the operating characteristics of the facilities to be satisfied.
Plotting costs against capacities, and using some interpolation, one obtains
a function of costs vs. capacity for each facility type (and underlying
standard of operations).
It is expected that this function will be approximated well by a
linear function. There are indications that this is often the case; see,
e.g. [Ref. 30]. If it is the case, the required constants A.,c. are a natural
consequence. If a curvilinear function is required, a piecewise linear
approximation to the function can be found; the analysis as has been presented
earlier will no longer suffice, but some modification of the model which can
handle piecewise linearity would not be difficult to come by. Remembering the
argument over five vs. ten million dollars cited earlier, it is believed that
considerable progress would result even if linear function approximations were
forced onto all cases. In either case, obtaining the basic estimates and
deriving the functions would appear desirable.
Now including in system analysis the many standards of operations
Hhich are possible for a given facility type requires that the process above
begone through for all quality levels to be included. This requires then, that
before going through the steps indicated above, the experts must first agree on
a set of levels to investigate. This does not necessarily mean that the effort
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multiplies by the number of levels to be considered. For example, in designing
two incinerators with different air pollution standards for the same type of
pollution control device, a completely new plant will not have to be considered
for each. Rather one basic plant would be considered, with further effort
devoted to the changes necessary to adopt the different device in the second
case. This is not double work, e.g. the space required to house and service
the furnaces should be the same in both cases.
4.7 Facility Selection as a Sequence of Choices over Time
The approach thus far has been to consider facility selection as a
static process, so that, for example, the assumption could be made that the
operating level of a facility and its capacity were one and the same. In
actuality, this is not the case; and throughout the lifetime of a facility,
particularly large processing plants such as incinerators, there will ordinarly
be some portion of the capacity of the facility which is unused, since the
capacity will have been set in anticipation of future, rather than present
needs at the time of its design.
This need to recognize changing population patterns over the region
and per capita increases in waste generation, and in addition to recognize the
varied ages of existing facilities and that the capacities of the various
disposal sites will occur at different times in the future must be met by a
facility selection model which treats selection as a dynamic, rather than a
static process.
Although the model described above does not explicitly treat
decisions over time, it can be used at any stage within a sequence of decisions
to make choices for that stage alone. A criterion of goodness of a method of
making decisions over time is fundamentally some measure of the closeness
which the choices made can be kept to the most desirable possible set of
facilities considering each time point individually and independent of the rest.
Since the latter choices are deriveable with the model described herein, this
static model is of use in developing a concept of good sequential decisions and
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in evaluating sequences of choices for given time-related spatial distributions
of generated refuse.
Considerable time has been spent on this study in an attempt to treat
the dynamic problem as a natural extension of the static problem through the ^
application of zero-one integer programming techniques. These efforts were not
successful, nor were other efforts to achieve rigorous extremalization of some
function reflecting costs over many time periods through use of dynamic
programming. In both cases, the difficulty lay in writing conditions which
would establish the continuity of service of facilities; in other words, it
proved difficult to prevent facilities from dropping out of service for one or
more time periods, and then appearing again some time in the future.
•
Without further experience with the static model, it is difficult
to say just how sophisticated a tool one really needs. With running of the
static model over a succession of time periods independently, it might prove
that patterns shift slowly enough to prevent such service discontinuities from
occurring even with no explicit side condition which forbids it. If that should
be the case, it would be inappropriate to devote a great amount of further
effort in search of a true optimization technique.
As an interim, practicable approach, the following intuitively
suggestive procedure is proposed:
1. Discretize the total time period under consideration into a
succession of equal time intervals. An elemental duration of
from two to five years may represent a suitable compromise
between the opposing desires of few intervals and relative
constancy within a single interval.
2. Minimize total cost (fixed plus operating) incurred at each
time interval, sequentially; at each step use conditions
determined by previous steps. The static optimization model
may be applied here.
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3. Introduce a global optimality criterion. One that seems both
reasonable and simple is to minimize the sum of per capita total
costs over all the time intervals of the period under consideration.
(Discounting of future expenditures does not appear to be appropriate
here as the funds are not available in advance, being basically
derived from current tax revenues.) This criterion recognizes
that minimizing total costs can place an undue burden on the
population of an area with high growth potential before the
bulk of the population arrives to foot the bill.
4. If in the solution obtained in Step 2 a given collection
district or a processing plant output has the same destination
oveY all of the time intervals, then that destination is
maintained for our final solution. If on the other hand, the
destination is first DQ, changing to Dj at time interval tj,
changing to DZ at t2>..., and finally to Dn at tn (from
thence to end to total period), then in our final solution
this sequence of destinations is still maintained (for the
given collection district or processing plant output) with the
exception that t. t_,...,t are permitted to vary over all
• 9 ** ll
possible values (but still maintaining the given order). Such
variations are permitted to take place simultaneously for all
collection districts or processing plant outputs which have non-
constant destinations in Step 2, and that combination of altered
transition times which satisfies our global optimality criterion
of Step 3 becomes our final solution.
If for example, we have a problem with ten time intervals and
five cases of single destination transition during total period, then total
number of combinations is 10 and the brute force method of complete exhaustion
is probably feasible. If, however, more cases and more destination transitions
per case occur, then programming procedures of greater efficiency would probably
have to be found, or there would then be justification for continuing to look
for a high-powered optimization technique.
A specific set of assumptions and format for structuring the
problem according to this approach is presented in Appendix J.
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REFERENCES
1. Anderson, R.T. (ed,). Waste Management: A Report of the Second
Regional Plan, New York, N.Y. Regional Plan Association, Mar. 1968.
2. California Waste Management Study. Aerojet General Corp., Report No.
3056 (Final), Aug. 1965.
3. Waste Management and Control. National Academy of Sciences-National
Research Council Publication 1400. Washington, D.C., 1966.
4. Municipal Refuse Disposal. American Public Works Association.
Chicago,Illinois, 1966.
5. Solid Waste Handling in Metropolitan Areas. U.S. Department of Health,
Education, and Welfare. Washington, D.C., Feb. 1964.
6. A Strategy for a Living Environment. Task Force on Environmental Health
and Related Problems, U.S. Department of Health, Education, and Welfare,
June 1967.
7. Bugher, R.D. Progress Begins with Research. The APWA Reporter,
29(4):1, Apr. 1962.
8. Anonymous. Figure in APWA Release Gives Wrong Impression. Refuse
Removal Journal, 5(10):6, Oct. 1962.
9. Weaver, L. (ed.) Proceedings The Surgeon General's Conference on
Solid Waste Management. Department of Health, Education,and Welfare,
Cincinnati, Ohio, 1967.
10. Hanks, T. G. Solid Waste/Disease Relationships: A Literature Survey
Aerojet General Corp., Public Health Publication No. 999-UIH-6
Cincinnati, Ohio, 1967.
11. Fresno Region Solid Waste Management Study (Interim Report). Volume 1
Study Report Aerojet-General Corp. June 1967.
12. Refuse Disposal Plan for the Detroit Region. Detroit Metropolitan Area
Regional Planning Commission, Detroit, Michigan, Jan. 1964.
13. Refuse Disposal Needs and Practices in Northeastern, Illinois. Techni-
cal Report No. 3, Northeastern Illinois Metropolitan Area Planning
Commission, Chicago, Illinois, June 1963.
14. Refuse Study (Prepared for Capitol Region Planning Agency) UPA Project:
CONN P-27 Feb. 1963.
IS. Golueke, C.G., and P. H. McGauhey. Comprehensive Studies of Solid Wastes
Management. University of California Sanitary Engineering Research
Laboratory (SERL) Report No. 67-7 May 1967.
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REFERENCES
16. Urban Characteristics of the Niagara Frontier: An Inventory. State
University of New York at Buffalo, Buffalo, N.Y., 1964.
17. Myers, L. B. An Economic Analysis of the Western New York Region:
Basic Inventory and Analysis Phase, Cornell Aeronautical Laboratory, Inc.
Report No. VY-2233-G-1, Aug. 15, 1966.
18. Special Census of Erie County, New York. U.S. Department of Commerce
Series P-28 No. 143S, Washington, D.C., Oct. 21, 1966.
19. Special Census of Niagara County, New York. U.S. Department of Commerce
Series P-28 No. 1451 (Rev), Washington, D.C., Sep. 5, 1967.
20. A Growth Strategy for the Erie-Niagara Areas: Economic Profile Erie-
Niagara Area. Greater Buffalo Development Foundation, Buffalo, N.Y.,
July 1967.
21. Hume, N. Management Information System Studied for Los Angeles, Refuse
Removal Journal 10(11):39, Nov. 1967.
22. Michaels, A. Report on Refuse Disposal for Niagara County, New York
Philadelphia, Pa. 19106, June 9, 1966.
23. Hill, T.P., and A. Michaels. Special Refuse Disposal Report for City
of Buffalo, New York. Day and Zimmermann, Inc., Philadelphia, Pa.
Dec. 10, 1966.
24. Hill, T.P., A. Michaels and R.M. Daniel. Refuse Disposal Report for
County of Erie. Day and Zimmermann, Inc., Philadelphia, Pa. June 12,
1967.
25. Fresno Region Solid Waste Management Study. Vol. II - Appendixes
Report No. 3413 (Interim) Aerojet-General Corp., June 1967.
26. Beckenbach, E. F. (ed.). Applied Combinatorial Mathematics, New York,
N.Y., John Wiley and Sons, inc., 1964.
27. Green, J. A., N.S. Lister, and B. Whitworth. Refuse Disposal in the
Tyneside/Wearside Area: The Evidence for Cooperation. Local Government
Operational Research Unit, Reading England, Feb. 1967.
28. Britten, A.A., and B. Whitworth. Replacement of Refuse Collection Vehicles
Which and When to Buy. Local Government Operational Research Unit,
Reading, England, no date.
29. Whitworth, B. Refuse Disposal An Analysis of Alternatives Local Govern-
ment Operational Research Unit, Reading, England, no date.
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REFERENCES
30. Green, J.A. Economic Factors to Consider in Choosing Incineration
Plant. Municipal Engineering pg 177-178, Feb. 3, 1967.
31. Spielberg, K. An Algorithm for the Simple Plant Location problem
With Some Side Conditions. IBM Corp. Tech. Rept. No. 320-2900
Nov. 1967.
32. Lerake, C.E., and K. Spielberg Direct Search Zero - One and Mixed
Integer Programming. IBM Corp. Tech. Rept. No. 320-2911,
June 1966.
33. Pierce, J.F. Application of Combinatorial Programming to a Class of
All-Zero-One Integer Programming Problems IBM Corp. Tech. Rept.
No. 320-2002, July 1966.
34. Zaun, W.L., The Orange County Refuse Disposal Program. County of
Orange Road Department, Orange County, California, June 17, 1965.
35. Arora, S.R., and W.R. Bunker. Examining Costs in Solid Waste Disposal,
Public Works, pg 134-136, Oct. 1967.
36. Environmental Health Planning Guide. U.S. Public Health Service
Publication No. 823, Washington, D.C., 1962.
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IPPENDIX A: THE BUFFALO STANDARD METROPOLITAN STATISTICAL AREA (SMSA)
(.1 Introduction
The material contained in Appendix A is provided in order to
present some of the salient factors which have a direct bearing on the generation
of solid waste and some of the pertinent factors to be incorporated in examining
the solid waste management problems of the Buffalo SMSA. Although a comprehensive
description of this region would entail a huge amount of material and data,
ill of which has some relevance to solid waste handling problems, it
is possible to distill from this extensive information a more limited description
vhich is germane as well as useful to an examination and analysis of solid
mste handling.
The appendix is organized in the following subjects
• Geologic and geographic profile of Erie and Niagara
counties
• Local government and population distribution within
the two counties
• Economic profile of the Buffalo SMSA
Much of the material to be presented has been obtained through
suamarizing pertinent papers which were published within "Urban Characteristics
of the Niagara Frontier: An Inventory," State University of New York at Buffalo
1964 (Ref. 16).
In a sense, this Appendix can also be viewed as a restrictive inven-
tory which is related to our current project. Although much of the information
has not been used directly within the study, it has provided some signifi-
cmt insights into some of the realities confronting planners and decision-
ukers, e.g., the large number of political, independent subdivisions; the
tliaactic factors which may affect particular solid waste handling solutions;
the variety and quantity of solid waste which is generated by business and
industry activity, etc. It is only through a broad understanding and apprecia-
A-l
-------
tion of the composition of the specific region that meaningful solid waste
analysis and implementation can be performed which hopefully will have relevance
for the future.
A. 2 Geologic and Geographic Profile of Erie and Niagara Counties
A.2.1 Geological Highlights
The Buffalo SMSA (also referred to as the Niagara Frontier), com-
prising the Counties of Erie and Niagara in the State of New York lies between
north latitude 40°28* and 43°23' and west longitude 78°29' and 78°03'. The
area is bounded on the north by Lake Ontario, on the west by Lake Erie and
the Niagara River, and on the south by Cattaraugus Creek. The land area of
the two county region is 1587 square miles with a maximum north-south dimension
of approximately 67 miles and a maximum east-west-diroension of approximately
37 miles. Erie and Niagara Counties, and the natural boundaries of this region
are shown on Figure A.I.
Topographically Erie and Niagara Counties are divided into four
distinct areas separated by three escarpments. The four areas are the Ontario,
Tonawanda-Chippewa, and Erie Plains, and the northern edge of the Allegheny
Plateau. The Niagara escarpment, the Onondaga escarpment, and the Portage
escarpment separate the four areas into a terrace form pattern which slopes
northward from an elevation of about 2000 feet on the Allegheny Plateau to
246 feet at Lake Ontario. A geologic cross section from the northern portion
of Niagara County to the southern portion of Erie County, illustrating the
following brief topographic description as shown on Fig. A. 2.
The Ontario Plain comprising the northern portion of Niagara County,
is bounded on the north by Lake Ontario and on the south by the Niagara escarp-
ment. The average elevation of this plain is 200 feet. The Tonawanda-Chippewa
Plain separated from the Ontario Plain to the north by the Niagara escarpment has
an average elevation of about 600 feet. The surface of the plain is essentially
A-2
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-~\
-1— ^—r|_l
I .......... I I—I
BUFFALO
METROPOLITAN
ARE*
Figure A.I THE BUFFALO STANDARD METROPOLITAN STATISTICAL AREA
A-3
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ONTARIO
PLAIN
ELEVATION
EOOO'-l
1000'-^
-
o1 J
WILSON
285'
TONAWANDA
CHIPPEWA
PLAIN
_WIAGARA
ESCARPMENT
ERIE
PLAIN
ALLEGHENY PLATEAU
—PORTAOE ESCARPMENT
—ONONDAOA
ESCARPMENT
SPRINOVILLE
1800'
LAKE
ONTARIO
246'
QUEENSTON SHALE
MEDINA SANDSTONES
CLINTON LIMESTONE
ROCHESTER SHALE '
LOCKPORT DOLOMITE —
I 1 1- -I 1
0 10 20
-------
level and is cut by the Niagara River. The southern boundary of the Tonawanda-
Ghippewa Plain is the Onondaga escarpment. The Erie Plain is an essentially
level surface south of the Onondaga escarpment and a gentle descent begins in
i low region near Lake Erie. Finally, the Allegheny Plateau is located at the
southern edge of the Erie Plain and is defined by the range of low hills which
reach an elevation of about 2000 feet on hill summits and continues to rise
south of Erie County.
The greatest resource of the Great Lakes area is an enormous supply
of excellent water. Water shortages in Erie and Niagara Counties are not
vaningful; in general under unusual circumstances, they reflect a lack of
adequate pumping and distribution systems. The City of Buffalo, using two
pimping stations, obtains its water supply from the Niagara River. The Western
New York Water Authority pumps its water from Lake Erie. Water obtained from
both the Niagara River and Lake Erie is classified as being medium hard, containing
125 parts per million of dissolved inorganic solids. It should be noted that
septic tank effluents or sewage disposal plants drain into most of the major
streams of Erie and Niagara Counties particularly in their lower courses.
A.2.2. Geographic Highlights of the Buffalo SMSA
The three main factors within the geographic profile which is included
here because of their significance to the problems of solid waste are (a) climate
and weather, (b) soils and, (c) land utilization patterns. Another factor
which is of significance, the major transportation facilities, are not
outlined although they have been considered (in particular trafficway networks)
in some of the analysis performed within this project and by the planners of
solid waste systems (e.g. rail networks and facilities for a potential rail
transfer plan).
(a) Climate and Weather
Because of its interior and northerly location in the Nation,
the Buffalo region receives many polar fronts passing through the area. Associated
A-S
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with these fronts are variations in weather that occur from day to day and even
from hour to hour. Temperatures are decidedly affected by the invasion of fronts,
and most of these bring cooler weather, primarily from continental polar air
masses descending from Canada. Additionally the temperature regime is considerably
affected by the presence of Lake Erie. The summers are several degrees cooler
than they would be if no lake influences were present. During winter, Lakes
Erie and Ontario contribute considerably milder temperatures to this region then
are typical farther inland.
Among some of the other effects on Buffalo's climate and weather
which can, in part, be attributed to Lake Erie, are
(1) Increased length of the frost-free season by as much as
two-three weeks
(2) Reduced likelihood of smog and smoke over the area because
of the higher wind velocities
(3) Increased amount of precipitation
(4) Increased amount of sunshine in summer, as measured by the
average percentage of possible sunshine.
In summary, the local influences of Lakes Erie and Ontario, and the
somewhat higher areas of the Allegheny Plateau and the Niagara Escarpment do
give a somewhat unique character to the climate and weather of the Buffalo SMS A.
Such factors as mild winters, cool summers, delayed springs and prolonged falls
are a direct result of the Lakes. The heavy snow falls in winter, plus the
relatively uniform precipitation regime throughout the year also are partly
caused by the control of the Lakes. The relief of the Allegheny Plateau
further contributes to the unique character of the local climate by bringing
heavy snowfall, and cooler winter and summer temperatures than would be found
in more low-lying areas.
A-6
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(b) Soil
Of the great soil groups that are found in the United States, Erie
tnd Niagara Counties have together three: gray-brown podzolics, bog and half-bog
soils, and alluvial soils. With the exception of alluvial or organic soils, the
soils of the Erie-Niagara Region have developed from glacial drifts, and
associated sands, clays and silts. Some of these soils have developed a
layer of tightly packed materials in the subsoil that is slowly permeable to
water. Because the pores are small and the horizon or layer holds so little
water available to plants, few roots develop in it. Such an impervious layer
is known as fragipan and this layer has caused many areas to be rather poorly
drained; even some of the moderately sloping areas. A rather high proportion
of the New York State drainage problems are a result of the fragipan layer.
A further categorization of the soil groups, known as soil associations,
are included on Fig. A.3 and Table A.I since this categorization is a better
indicator of the soil properties which have a direct effect on some solid waste
•anagement alternatives; in particular the location of sanitary landfill sites,
which would be assessed. Among the soil factors which are of direct interest
are the drainage, fertility, structure and bearing capacity characteristics
of the soils.
In summary, drainage is the predominant problem with respect to the
soil in the Buffalo SMSA. The slowness of drainage limits the uses of the land
for residential purposes particularly where individual homes are dependent on
septic tanks or drainage fields for the disposal of waste materials.
(c) Land-utilization Patterns
Four rather distinct regions make up the Buffalo SMSA; each of
which reflects the evolution or change of land use that has occurred over
the years. Both centrifugal and centripetal forces have been at work on the
development of the area and are bringing about further changes to both the
central city and its surrounding suburbs.
A-7
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•
SOUBCC :
DEPARTMENT Of AGRONOMY
CORNELL UNIVtRSlTY - 1*59
Figure A.3 ERIE-NIAGARA GENERAL SOIL ASSOCIATIONS
A-8
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Table A.I
KEY TO SOIL ASSOCIATIONS MAP
ERIE-NIAGARA REGION
Smbol
A
AA
CC
CD
CT
DR
EL
ES
F
FT
HH
HK
OH
OS
P
WM
U
Soil
Association
Alton,
Colosse and
Ottawa
Aurora-
Angola
Caneadea-
Canadice
Collamer-
Dunkirk
Chenango-
Tioga,
Howard-
Chagrin
Darien-
Romulus
Erie
Langford
Elmwood-
Swanton
Framington
and Nollis
Fulton-
Toledo
Howard-
Hoosic,
Chenango,
Arkport
Hilton
Ontario-
Hilton
Odessa-
Schoharie
Palmyra,
Kars and
Herkimer
Wooster-
Mardin
Undiffer-
entiated
urban lands
Drainage
Poor
Mod. well
to poor
Mod. well
to poor
Well to
mod.
Well
Mod. well
to poor
Mod. well
to poor
Mod. well
to poor
Well
Poor to
very poor
Well
Mod. well
Well to
mod.
Well to
mod. poor
Well to
excessive
Well to
mod. well
Fertility
Mod. to
low
Poor
Poor
Mod.
High
Poor
High to
mod.
High
High if
deep
Fair
Low
Mod. to
good
High
Poor to
fair
High
Mod.
Structure
Coarse
Med.-
fine
Fine
Med.
Good
Mod.
fine
Med. to
med.
coarse
Fine
Med.
Fine
Fine
Med.
fine
Med. to
mod. fine
Med.
fine
Med.
Med.
Bearinc
Capacity
Fair
Good
Good
Fair
Good
Good
Good
Poor
Good
Fair
Fair
Good
Good
Fair
Good
Fair
Composition
Sandy and
gravelly
loam
Silt loam,
silty clay
loam
Silt loam
Silt loam
Silt loam,
gravelly
loam
Silty clay
loam
Silt loam
Sandy loam
Stony loam,
silt loam
Silty clay
loam
Silt loam,
gravelly
loam
Silt loam,
gravelly
loam
Gravelly
loam
Silty clay
loam
Gravelly
loam
Silt loam,
gravelly
loam
Wee: SoiU and Soil Association of N.Y., Cornell Extension Bulletin 930 NYS College of Agriculture at Cornell University, Ithaca, N.Y. ItSS;
*d Soil Surreys of Erie and Niagara Counties, N.Y.S. issued 1929 and 1947 respectively. Cornell Agricultural Experiment Station and U.S. D«pt
• Agriculture, Bureau of Chemistry and Soils.
A-9
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The compact urban areas are made up of two subareas which can be
designated as blighted (in need of development and rehabilitation), and
conservation (in need of general environmental improvement). The blighted
subareas generally represent the early settlements in Buffalo, Black Rock,
the Tonawandas, Niagara Falls, and Lockport where the age and deterioration
of the physical structures and/or environmental deficiencies have combined
to produce areas of blight and obsolescence. With few exceptions, the cities
of the region are engaged in rehabilitation and revitalization of these core
areas of blight. The second subregion can be characterized as having
deficiencies in the general environment rather than structural deficiencies.
Within this area one finds strip commercial development as well as a scattera-
tion of industrial uses.
The developing suburban areas include such towns as Tonawanda,
Amherst, Cheektowaga and West Seneca outside of Buffalo, the towns of Lewiston
and Niagara outside of Niagara Falls, and the area of the Town of Lockport
south of the City of Lockport. As typical of most metropolitan areas, these
areas can be characterized primarily by post-war suburban growth adjacent to
the cities. The typical structural development is one-story ranch housing or
expandable bungalow, and the shopping plaza.
The suburban fringe areas are typified by scatteration and linear
development, and are located between the developing suburban areas and the
principal rural areas. This area is more extensive in the northern part of the
Buffalo SMSA where level topography, dispersion of major urban centers, and
greater amounts of highway network have fostered far-flung dispersion. This
regional class is characterized by large open' areas which are rapidly being
broken up by scattered subdivisions and frontage development along existing
highways.
The remainder of the region is predominantly rural farm area including
fruit farms, vegetable crops, and dairying. The fruit farms and cropland
of the region predominate along the edge of Lake Ontario in Niagara County and
A-10
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m the Erie Plain Lowlands in Erie County where the climate is stabilized by
the Lakes. Dairy farming is located mainly in the uplands in the southern
pan of Erie County. In some areas, the lack of adequate building codes and
toning ordinance has enabled the development of "jerry-built" non-farm residences,
improperly planned trailer camps, and a sprinkling of automobile junk yards.
These uses are more prevalent on the marginal rural lands in the Tonawanda
Creek basin.
A,3 Local Government and Population Distribution Within the Two
Counties
A.3.1 Local Government Structure
In attempting to analyze the regional approaches to solid waste
unagement it is of primary importance to be aware of the local governmental
structure of the region and the implications of the various forms of government.
Ihe political structure of the Buffalo SMSA can be conveniently grouped, in the
light of history and function, into three categories: towns and counties; cities
ad villages; and special purpose units which for the most part are established
to render a single service. Erie County consists of three (3) cities, 25 towns,
IS villages, 36 school districts, 884 special districts* for a total of 963
local government units. Niagara County consists of three (3) cities, 12 towns,
5 villages, 10 school districts, 98 special districts* for a total of 128 local
government units.
Within New York State, the principal that there should be a substantial
aount of local home rule has been long recognized. "Home Rule" refers to the
{rant of powers to local governmental units and restrictions upon state legisla-
ture intervention in local affairs. Local governmental powers gives the
citizens of the city or other units of government the power to determine the
form and structure of their government. Along with this power, there is the
'includes the following kinds of districts: Fire, Fire Protection, Street
lighting, Sewer, Drainage, Water, Refuse and Garbage, Park, Consolidated
Health and others.
A-ll
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broad power to determine what operating departments shall be established and how
the officials responsible for their operations shall be selected. Additionally,
the "bill of rights" for local governments which is applicable to all counties,
cities, towns and villages grants to each the right to provide services and
facilities on a joint or cooperative basis and at the same time to protect
its boundaries.
A.3.2 Population Distribution
(a) Erie County
The total population of Erie County, New York, on April 18, 1966
was 1,087,183, according to the final results of a special census taken by the
Bureau of the Census, Department of Commerce. This figure represents an
increase of 22,495, or 2.1 percent, over the population of April 1, 1960, which
was 1,064,688. The population statistics for minor civil divisions and the
increases since 1960 are shown in Table A.2. Projections of this County popula-
tion for the years 1975, 1980 and 2000 were obtained from the Office of the
Commissioner of Planning, Erie County. Using this information, estimates of
populations were performed on a five-year increment basis up to the year 2000.
The total array of population information, by cities and towns within Erie
County is presented in Table A.3.
(b) Niagara County
The Bureau of the Census conducted a special census for Niagara
County, New York. The special census population as of April 3, 1967 was
234,477. This figure represents a decrease of 7,792 or 3.2 percent, from the
242,269 persons as of April 1, 1960. The population statistics for minor civil
divisions (cities, towns and villages) within the County and the changes
since 1960 are shown in Table A.4.
A-12
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Table A.2
POPULATION OF ERIE COUNTY, NEW YORK, BY MINOR CIVIL DIVISIONS:
APRIL 18, 1966, AND APRIL 1, 1960
(Minus sign (-) denotes decrease)
Minor civil divisions
April 18,
1966
April 1,
1960
Increase,
April 1, 1960, to
April 18, 1966
Number
Percent
Erie County
Alden town
Alden village
Amberst tovm
Williamsville village
Aurora town
East Aurora village
Boston town
Brant town
Farnham village
Buffalo city
Cheektowaga town
Depew village (pt.}
Sloan village
Clarence town
Golden town.
Collins town
Gowanda village (pt.)
Concord town
Springville village
Eden town
ELma town
Evans town
Angola village
Grand Island town
Hamburg town
Blasdell village
Hamburg village
Holland town
Lackawanna city
Lancaster town
Depew village (pt,)
Lancaster village
Barilla town
Newstead town
Akron village
Korth Collins town
North Collins village
Orchard .Park town.
Orchard Park village
Sardinia town
Tonawanda city
Tonawanda town
Kenmore village
Vales town
Vest Seneca town
Cattaraugus Indian Reservation (pt.).
Tonawanda Indian Reservation
1,087,183
9,445
2,694
79,147
6,559
13,970
6,796
6,273
2,532
480
481,453
10,,017
11,202
5,493
17,001
2,624
7,861
1,050
7,162
4,137
7,391
9,113
13,110
2,550
11,294
44,500
3,786
9,493
2,678
28,717
29,570
7,107
13,408
2,872
6,151
2,786
4,046
1,721
17,867
3,506
2,292
21,946
109,702
21,146
2,640
43,397
1,400
12
1,064,688
7,615
2,042
62,837
6,316
12,888
6,791
5,106
2,290
422
532,759
84,056
7,359
5,803
13,267
2,384
6,984
1,079
6,452
3,352
6,630
7,468
12,078
2,499
9,607
41,288
3,909
9,145
2,304
29,564
25,605
6,221
12,254
2,252
5,825
2,841
3,805
1,574
15,876
3,278
2,145
21,561
105,032
21,261
1,910
33,644
1,426
30
22,495
1,830
652
16,310
243
1,082
5
1,167
242
58
-51,306
16,961
3,843
-310
3,734
240
877
-29
710
285
761
1,645
1,032
51
1,687
3,212
-123
343
374
-847
3,965
836
1,154
620
326
-55
241
147
1,991
228
147
385
4,670
-115
730
9,753
-26
-18
2.1
24.0
31.9
26.0
3.8
8.4
0.1
22.9
10.6
13.7
-9.6
20.2
52.2
-5 3
28.1
10.1
12.6
-2.7
11.0
7.4
11.5
22.0
8.5
2.0
17.6
7.8
-3.1
3.8
16.2
-2.9
15.5
14.2
9.4
27.5
5.6
-1.9
6.3
9.3
12.5
7.0
6.9
1.8
4.4
-0.5
38.2
29.0
-1.8
(B)
B Base less than 100.
A-13
-------
Table A.3 PROJECTED POPULATIONS OF CITIES AND TOWNS IN ERIE COUNTY
MINOR CIVIL DIVISION
ALDEN (T)
AMHERST (T)
AURORA (T)
BOSTON (T)
BRANT (T)
BUFFALO (C)
CHEEKTOWAGA (T)
CLARENCE (T)
GOLDEN (T)
COLLINS (T)
CONCORD (T)
EDEN (T)
ELMA (T)
EVANS (T)
GRAND ISLAND (T)
HAMBURG (T)
HOLLAND (T)
LACKAWANNA (C)
LANCASTER (T)
MARILLA (T)
NEWSTEAD (T)
NORTH COLLINS (T)
ORCHARD PARK (T)
SARDINIA (T)
1970
10500
89000
15000
7500
3000
460000
113000
18500
3000
8500
8000
8000
10000
14000
12500
50000
3000
29000
33500
3000
7000
4500
20500
2500
1975
12000
103000
17500
9700
3500
448000
127500
22000
3900
9300
9100
9100
12500
16000
15000
60000
4100
29700
40000
3400
8000
5200
25000
2700
1980
14000
120000
20500
12000
4000
440000
140000
25000
4500
10500
10500
10500
15500
19000
18500
72500
5000
30500
48000
4000
9000
6000
31000
3000
1985
15800
138000
23000
13300
4400
437000
145000
28000
5000
11900
11700
12000
17500
22000
21500
84000
5700
31300
53000
4400
9900
6700
35000
3400
1990
17300
147000
26000
14600
4800
437000
147000
30500
5400
13300
12800
12900
19000
23500
23000
90000
6200
32000
59000
4800
10800
7200
38000
3600
1995
18400
154000
27500
15700
5200
440000
149000
32500
5700
14500
13700
13800
20000
25000
24000
95000
6700
32500
63000
5200
11500
7600
40000
3800
2000
19000
160000
28000
16500
5500
450000
150000
34000
6000
15400
14500
14500
21000
26000
25000
98500
7000
33000
65500
5500
12000
9PPO
42000
4000
>
H-
Ji.
-------
Table A. 3 PROJECTED POPULATIONS OF CITIES AND TOWNS IN ERIE COUNTY (Cont.)
MINOR CIVIL DIVISION
TONAWANDA (C)
TONAWANDA (T)
WALES (T)
WEST SENECA (T)
CATT. INDIAN RES.
ERIE COUNTY
1970
22000
112000
3000
48000
1500
1120000
1975
22500
116000
3900
60000
1350
1199950
1980
23000
120000
4500
78000
1000
1300000
1985
23000
120000
5000
84000
800
1371500
1990
23000
120000
5400
87000
650
1421750
1995
23000
120000
5700
89000
550
1462550
2000
23000
120000
6000
90000
500
1500400
in
-------
Table A.4
POPULATION OF NIAGARA COUNTY, NEW YORK, BY MINOR CIVIL DIVISIONS:
APRIL 3, 1967, AND APRIL 1, 1960
»* *
(itLnus sign (-) denotes decrease)
Place
April 3,
1967
April 1,
1960
Increase
Number
Percent
Niagara County
Cambria town ,
Hartland town ,
Middleport village (pt.)
Lewistcn town ,
Lewiston village
Lockport city
Lockport town
Newfane town.
Niagara town
Niagara Falls city
North Tonawanda city '. ,
Pendleton town ,
Porter town ,
Youngstown village ,
Royalton town
Middleport village (pt.)
Somerset town. ,
Barker village
Wheatfield town
Wilson town.
Wilson village ,
Tonawanda Indian Reservation (pt.).
Tuscarora Indian Reservation
234,477
242,269
4,124
3,786
142
15,148
3,337
25,616
7,709
9,097
8,769
88,286
35,994
4,412
6,628
1,915
7,034
1,762
2,453
553
9,356
4,962
1,271
1,103
3,661
3,577
142.
13,686
3,320
26,443
6,492
8,523
7,503
102,394
34,757
3,589
7,309
1,848
6,585
1,740
2,489
528
8,008
5,319
1,320
1,934
-7,792
463
209
1,462
17
-827
1,217
574
1,266
-14,108
1,237
823
-681
67
449
22
-36
25
1,348
-357
49
-831
-3.2
12.6
5.8
10.7
0.5
-3.1
18.7
6.7
16.9
.-13.8
3.6
22.9
-9.3
3.6
6.8
1.3
-1.4
4.7
16.8
-6.7
3.7
-43.0
- Represents zero.
A-16
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A.3.3 Economic Profile of the Erie-Niagara Area
A brief economic profile of the Buffalo SMSA is included in this
Appendix because of the contributions that the various economic sectors provide
to the regional waste streams. Although no single economic indicator, e.g.
tuber of employees, income generated, productivity, etc., is currently available
for relating the impact of economic activity on solid waste, a study is being
performed at the University of California (Ref. 15) to develop an
economic input-output matrix and to derive relationships between this matrix
and regional solid waste generation by individual economic sectors. The development
of the matrix and its relationships with solid waste generation would be an
invaluable tool for making projections of the types and quantities of solid
nste to be handled, and for assessing alternative systems and their capabilities
for handling various quantities and types of industrial and commercial waste.
As a single measure, employment within individual employment categories
can be a useful proxy in indicating changing levels of economic activity within
the category. Assuming that the relationship between number of employees and
solid waste generated within the employment category can be measured, it should
lie fairly routine to estimate changes in solid waste for changing employment
levels. Caution in making these estimates must be exercised since these
relationships are dependent on materials, methods and other technological
Aanges which can affect the types and quantities of waste generated per unit
tf labor input.
The economic description of the Buffalo SMSA is described, in part,
in terms of employment because of the seeming relationship between industrial
od commercially-generated solid waste and given employment levels. A regional
economic discussion is useful because of the relationship between employment
ipportunities, or the lack thereof, and migratory patterns. The level of migration
resulting from changes in the region's economic activity plays an obvious role
« the levels of residential solid waste generated.
A summary of the 1966 Erie-Niagara employment breakdown by broad
Wployment categories is presented in Table A.5.
A-17
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Table A.5 ERIE-NIAGARA EMPLOYMENT CATEGORIES 1966
(Nonagricultural Establishments)
Category Total Percent of Employment
Manufacturing 38.6%
Trade 19.2
Government 14.2
Services 13.3
Transportation § Private Utilities 6.7
Contract Construction 4.2
Finance, Insurance, Real Estate 3.7
It is apparent that manufacturing provides the largest percentage of jobs in
the Buffalo SMSA, and in comparison with the Nation it is substantially larger
(38.6% vs. 29.8%). Along with this static representation of the employment
for a given year (1966), it is useful for protective purposes to examine the rates
of change which have been experienced. sThe form of the information, presented in
Table A.6, Erie-Niagara Area Employment, for the years 1958 and 1966 depicts
levels of employment in each of the categories shown in Table A.5 although the
percent changes are in terms of absolute employment levels in each sector rather
than among the employment categories, as a percent of total employment.
Based on the past and present employment data as well as an assessment
of the Area's economic strengths and weaknesses vis a vis the Nation, it is
anticipated that employment opportunities in the Buffalo SMSA are expected to
increase by about half by the year 2000. This increase compares with an
anticipated doubling for the Nation. The industrial employment mix in
the area will shift dramatically with the proportion of the working population
in manufacturing declining from roughly two-fifths in 1950 to less than one-
third in 2000.
Manufacturing employment will probably increase by about one-quarter
by the year 2000, as increased production requirements will be met largely by
improved technology rather than by proportionate increases in manpower. Most
A-18
-------
Table A.6
Eri«-Niagara Area Employment
1958.1966
Industry
Total Nonagricultural Employment
Manufacturing
Durable Goods
Abrasive Cement & Plastic Products
Primary Metals Industry
Fabricated Metals Including Ordnance....
Machinery Except Electrical
Electrical Machinery, Equipment, Supplies
Transportation Equipment
Nondurable Goods
Food & Kindred Products
Apparel & Textile Mill Products
Paper & Allied Products
Printing & Publishing
Chemicals & Allied Products
Rubber & Miscellaneous Plastic Products
Nonmanufacturing
Contract Construction
Transportation & Public Utilities
Wholesale & Retail Trade
Finance, Insurance & Real Estate
Service & Miscellaneous
Government. .
1958
432,300
175,500
114,900
8,500
31,200
14.300
13,100
11,800
30,600
60,600
16,400
4,200
7,200
7,600
17,500
4.000
256,800
22,500
34,300
86,600
15,500
51,400
46,400
1966
472,800
180,500
123,300
8,200
33,600
14,100
15,000
15,000
31,400
57,200
14,100
3,600
7,000
8,400
16,000
4,700
292,200
20.200
31,900
91,900
16,900
64,400
67.000
Percent
Change
+ 9.4
+ 2.8
+ 7.3
— 3.5
+ 7.7
— 1.4
+14.5
+27.1
+ 2.6
— 5.6
—14.0
—14.3
— 2.8
+10.5
— 8.6
+17.5
+13.8
—10.2
— 7.0
+ 6.1
+ 9.0
+25.3
+44.4
SOURCE: NYS Department of Labor. Division of Employment.
A-19
-------
of the expansion in jobs will be concentrated in the growing machinery and
transportation equipment industries. Gains on the already well developed
primary metals lines will be relatively moderate. Nondurable goods gains
will be limited, with absolute declines expected in textiles and apparel. The
chemicals industry will be characterized by rapid technological changes and
geographic shifts and can only anticipate modest personnel gains by 2000.
This projection assumes a reversal in the downtrend of recent years.
Nonmanufacturing jobs in the Buffalo SMSA are expected to double
by 2000. All nonfactory lines except the extractive lines in the metropolitan
area should show substantial employment gains as the shift from a producing
to a servicing job market continues. Greatest advances are most likely to
occur in fields such as personal and business services, amusement and
recreation, medical services and education. Retail and wholesale gains will
be second only to that of the services and will reflect proliferation of
demands for the amenities by an increasingly affluent society.
The emphasis on manufacturing tends to obscure the gaining importance
of education, medical and scientific research, government and nonindustrial
fields. The great metalworking - machinery - auto and chemical complex that
has been the manufacturing strength of the Buffalo SMSA economy will continue
to play a leading role. Table A.7 depicts the relative gains in nonmanufacturing
jobs in the years ahead and indicates that these employment categories will
greatly exceed those for manufacturing categories by the year 2000.
A-20
-------
Table A.7
Erie-Niagara Area Employment Projections —
Major Industry Groups
1960-2000
Manufacturing
Manufacturing.
Food & Food Products
Textiles
Apparel
Furniture & Wood Products
Printing ft Publishing
Chemicals
Primary Metals & Fabricated Products.
Machinery
Transportation Equipment
Nonmamifacturing
Construction
Transportation, Communication and
Public Utilities
Wholesale and Retail Trade
Finance, Insurance & Real Estate...
Services
Public Administration
1960
181,166
16,039
1,376
2,600
4,096
10,417
17,660
46,197
26,863
30,597
289,695
27,388
35,915
85,047
16,849
87,644
18,553
5,575
1980
199,000
16,700
1,200
2,400
4,100
12,000
18,800
49,000
33,600
35,000
395,000
27,800
44,800
121,600
22,900
133,800
25,800
4,600
sooo
218,500
17,400
1,000
2,200
4,100
13,900
20,000
51,800
41,300
40,000
540,900
36,800
53,300
169,300
30,200
198,000
34,900
3,900
Agriculture. Forestry & Fisheries
SOURCE: U. S. Census Bureau, N. Y. S. Division of Water Resources, and GBDF.
A-21
-------
APPENDIX B: BUFFALO SMSA SOLID WASTE GENERATION
B.I Introduction
Included in Appendix B are descriptions of the broad categories
of solid waste; the various alternatives for depicting the solid waste of a
region as it related to specific objectives; estimates of current solid waste
generated; and finally projections of solid waste generated to the year
2000. Although the term generation is employed, it is recognized that it is
some combination of generation and collection. For example in those rural resi-
dential areas where sufficient land is available, some of the solid waste is
disposed of on-site and may not be accounted for in the regional totals. Also,
in those areas where home food grinders are found, a significant amount of
garbage enters the liquid waste stream and is not accounted for in the
regional solid waste generation category. Additional sources of error in
estimating the regional solid waste generated result from on-site open
burning and home incinerator practices. Each of these practices are beneficial
from the standpoint that the load on the regional solid waste system is
reduced, to varying degrees. However unless the magnitude of solid waste
disposed of by these methods can be assessed, the consequences on any regional
solid waste handling system of terminating these practices would be very
difficult to assess.
As a result of discussions with responsible City and County officials,
and representatives of the private sector of the solid waste industry, it has
been found that there doesn't exist a comprehensive and accurate estimate of
solid waste generated in the Buffalo SMSA. A review of many reports and
documents, as well as discussions with representatives of the Solid Wastes
Program, reveals that this lack of comprehensive and accurate information is
wide-spread. To correct this important deficiency,major fundings and efforts
are being supported to obtain more complete and accurate information so as to
better understand the scope of the solid waste handling problems and to allow
for better planning.
B-l
-------
In spite of these shortcomings it is both possible and necessary
to perform the requisite planning although caution must be exercised in
accepting and utilizing the extant data. To overcome the limitations of this
data and projections derived therefrom, it is necessary to introduce
a variety of logical and consistent assumptions concerning
solid waste generation and to establish the sensitivity of the solid waste
handling solutions to variations in the assumptions and the derived projections.
B.2 Description of Solid Waste
Although some of the contents of this portion of the Appendix are
contained within other documents and in some instances are either direct
quotes or paraphrases of published material, the information is included for its
relevance to the latter portions of the Appendix and for greater completeness of
the discussion. Whereas the description of solid waste should be given
more extensive treatments, the following description is indicative
of the types of information and data required to aid solid waste managers.
B.2.1 Categories of Solid Waste
In the main, solid waste and refuse are synonomous terms. The
constituents of solid waste may be classified in numerous ways. One of the more
useful classification schemes, as described in Ref. 4, is based on the kinds
of materials which,constitute solid waste: garbage, rubbish, ashes, street
refuse, dead animals, abandoned automobiles, industrial wastes, demolition
wastes, construction wastes, sewage treatment residues and special wastes.
Table BJ groups refuse materials by kind, composition, percent combustible
volume, percent noncombustible volume, and some of the major sources of the
refuse.
B-2
-------
Table B.I
SOLID WASTE MATERIALS BY KIND, COMPOSITION,
COMBUSTIBLE VOLUME, AND SOURCES
KIND
Refuse
Garbage
Rubbish
Ashes
Street
Refuse
Dead
Animals
Abandoned
Vehicles
Industrial
Wastes
Demolition
Wastes
Construction
Wastes
Special
Wastes
Sewage
Treatment
Residue
COMPOSITION
Wastes from preparation,
cooking, and serving of food;
market wastes; wastes from
handling, storage, and sale
of produce
Combustible: paper, cartons,
boxes, barrels, wood, excel-
sior, tree branches, yard trim-
mings, wood furniture, bedding
dunnage
Noncomuustible: metals, tin
cans, metal furniture, dirt,
glass, crockery, minerals
Residue from fires used for
cooking and heating and from
on-site incineration
Sweepings, dirt, leaves, catch
basin dirt, contents of litter
receptacles
Cats, dogs, horses, cows
Unwanted cars and trucks left
on publ ic property
Food processing wastes, boiler
house cinders, lumber scraps,
shavings
Lumber, pipes, brick, masonry,
and other construction mate-
rials from razed buildings and
other structures
Scrap lumber, pipe, other
construction materials
Hazardous solids and liquids:
explosives, pathological
wastes, radioactive materials
Solids from coarse screening
and from grit chambers; septic
tank sludge
COMBUSTIBLE
VOLUME (%)
90-100
70-85
0
0
30-70
95
0-10
40-90
5-25
5-25
80-95
75-90
NONCOMBUSTIBLE
VOLUME (%}
0-10
15-30
100
100
30-70
5
90-100
10-60
75-95
75-95
5-20
10-25
SOURCES
leaseholds,
restaurants,
institutions, stores,
markets
Streets, sidewalks,
alleys, vacant lots
Factories, power
plants
Demol it ion sites to
be used for new
buildings, renewal
projects, expressways
New construction,
remodel ing
Households, hotels,
hospitals, institu-
tions, stores,
industry
Sewage treatment
plants; septic tanks
B-3
-------
B.2.2 Categorization of Solid Waste - For What Purpose?
As the formulation of evaluation structures and mathematical models
in systems analysis i£ predicted on a specific question or questions being
examined so should the development of a typology or categorization scheme
for solid waste be responsive to the uses to which the information
would be applied. Within Section B.I it was stated that there is a
lack of information on a comprehensive and well-established basis of solid waste
generation in the Buffalo SMSA as well as most other regions in the United States.
What is implied by this statement is that the information currently available
meets certain limited needs but is either lacking or inadequate for many other
needs for efficient solid waste management. The evidence of these data deficiencies
is best appreciated when examining the approaches taken by most studies of the
problems of solid waste management. Almost universally, one of the first steps
taken is to design a survey, collect and collate solid waste information. Based
on the time, funds and effort available, this activity is pursued in varying
degrees of detail and completeness. Since most of these studies are of the
broad planning variety, the types of data being collected and analyzed are
related to the more general aspects of the planning function.
Among the major purposes to which solid waste information is applied
are (1) operations; (2) planning and; (3) research. Each of these purposes
has information requirements which can be grossly described as common and
unique. As examples of common information are such elements as the types and
the projection of changes in types and amounts of solid waste generated. With
respect to unique information needs, the operations function is concerned with
the work loads of specific and individual crews and pieces of equipment,
current maintenance problems and schedules, manpower recruitment and training
status — virtually all of this information pertains to the here and now.
The planning function is in need of information which allows for the
consideration of the types of major system modifications which would improve
the "system operation" both on a near-term and long-term basis. These
improvements and the types of information required are restricted to those
decisions and implementations which can be directly influenced by the solid
waste planners. As vital portions of these information requirements are
B-4
-------
(i) long-range projections (up to 25 years or more) of types and quantities
of solid waste which would be generated; (ii) anticipations and assessments
of changes in the attitudes of the population with respect to solid waste
handling practices, (iii) pending or foreseeable legislation which influences
and/or limits solid waste decisions; and (iv) technological innovations. The
unique information needs of the research function are difficult to describe
since they are highly dependent on problems which either are in the definitional
phase or have not been defined. It can be stated that whereas the
operator's needs are closely related to the present, the planners
needs relate to those problems which they can directly influence, and the
researcher's needs are not bounded. As examples of the researcher's
information needs are the properties (chemical, physical) of refuse
constituents as they relate to a specific research waste handling technique
(e.g. high temperature incineration) being studied; and the incidence of
illness and fatality as related to various air pollution constituents which
are traceable to solid various waste handling practices.
No attempt has been made in this study to set up a categorization
scheme for meeting the information requirements of these different interests.
However, emphasizing this deficiency, which is currently but all too
slowly being recognized, is of value and in particular noting the need for
recognizing the unique information requirements of the three major functions.
Hie development and operation of regional solid waste data banks which are
responsive to the operators and planners is technically feasible with the
advent of electronic data processing and it could also meet certain needs of
researchers. A significant effort in this direction is being undertaken by
the Los Angeles Bureau of Sanitation [ Ref. 21 ]. Although the main orientation
of this information system is to meet the needs of the operation function, it
is an indication of what could be done for the planners and to some degree,
the researchers.
B-5
-------
B.2.3 State of Solid Waste Information Pertaining to the
Buffalo SMSA
Within the past two years, two broad planning studies were performed
of refuse disposal for the Buffalo SMSA; a 1966 study of Niagara County and a
1967 study of Erie County (Refs. 2? and 24). Both investigations, of
rather modest effort, were confronted with the problem of obtaining current
solid waste handling information which was required to assist in establishing
the processing and disposal facility requirements out to the year 2000. Through
the use of sampling surveys, data of varying quality and completeness were
obtained. Using this information with various assumptions and national
planning coefficients, a variety of material flow and cost analyses was
performed and recommendations for new processing and disposal facilities over
the time period of interest were made. Within the limitations confronting
the consultants, it appears that they provided useful planning directions but it
is evident that the foundations of their planning recommendations, as well
as those derived by most consultants are highly dependent on the solid waste
information available and the assumptions made. An examination of the studies
did not indicate any sensitivity analyses of the recommendations relative to
the assumptions employed or the estimates made.
Among the many factors which present difficulties in obtaining a
reliable estimate of the solid waste generated and handled in the Buffalo
SMSA are:
(1) A lack of uniformity in the types and details of the
information collected by the political subdivisions within the region provid-
ing refuse collection and disposal functions.
(2) Little and imprecise information is maintained by private
collectors and private disposal operators as to the sources, types and
quantities of refuse handled.
B-6
-------
(3) No up-to-date inventories are maintained of on-site
disposal facilities in terms of available capacities or their expected
operating lives.
(4) No information is maintained which indicates the types and
mount of refuse processed or disposed of on-site by residential sources
md other sources.
(5) Where information is collected and maintained by private
collectors, it is difficult to obtain these data because of the competitive
nature of the industry and their fears of improper disclosure.
(6) The lack of an operative measurement equipment at certain
incinerators and disposal sites.
The above factors, by and large, are quite similar for most other regions.
Yet in spite of these limitations it is possible to develop a gross picture
of the solid waste handling in the Buffalo SMSA which is being used for
operational and planning purposes.
B.3 Spatial Distribution of Solid Waste Generated.
The current manner of depicting the spatial distribution of solid waste
generated in the Buffalo SMSA is a conglomerate of collection districts, civil
boundaries and specific locations. The establishment and stability of collection
districts are largely dependent on work load considerations and on some equitable
sharing of the total collection burden. Thus the size and number of districts
we influenced by such factors as population shifts, urban renewal, equipment
capacity, etc. Civil boundaries with respect to solid waste collection are
wed for the administrative and taxing conveniences and have little or no
B-7
-------
relationship to the effective management of solid waste. In some special
situations, specific locations are used to depict the location of solid waste
generation; where the type and/or quantity of solid waste is either unique
or very large.
After reviewing a number of different methods of describing the
spatial distribution of solid waste generation, it was decided to employ the
census tracts, as defined by the Bureau of Census, U.S. Department of
Commerce. For the examination of collection, transportation and facility
siting problems, it appeared that the towns and cities represent too large
an area to employ for analysis. The advantages of employing a census tract
system for analyzing solid waste problems are as follows:
(1) The boundaries are fairly stable. Although some alternations
have been made to the boundaries over the years, the changes
have been in the form of subdivisions of the original
boundaries with the new designations being related to the
original ones;
(2) The secondary source data (e.g. population, land-use, income,
households etc.) which is useful for estimating current per
capita solid waste generation and for projecting residential
generation is gathered and operated on a census tract basis;
(3) Census tract areas are sufficiently small so as to allow
for the use of a "pseudo-point" source for tract solid waste
generation in the analysis of transportation of solid waste to
processing plants and/or disposal sites;
(4) Census tracts are contained entirely within major political
subdivisions and thus, by appropriate aggregation, the waste
generation of an entire political subdivision can be derived;
(5) Finally, greater socio-economic homogeneity is found within a
single census tract than exists within the larger political
subdivisions.
B-8
-------
1,4 Estimate of Current Solid Waste Generation in Erie County
Although the term generation has been used primarily throughout
this Appendix it is more accurate to describe the following information as
n estimate of solid waste collected. Virtually all of the available data
lourpes which have been examined refer to the solid waste collected by public
nd private solid waste operators. Two exceptions to this have been the partial
surveys made within the aforementioned Erie and Niagara County Studies. Within
tie Erie County Study a sample survey was conducted by mailed questionnaires
if certain service and industrial organizations and a rather gross adjustment
His made to account for the non-respondents to the questionnaire. No over-all
estimates were included of on-site incineration or grinders. With respect
to the Niagara County Study, a survey was made which was restricted to the
Urge industrial firms with no estimate of on-site disposal practices being
shewn.
An estimation of the current solid waste "collected" by census
tricts was made for the City of Buffalo,* and the remainder of Erie County.
Since the data available for the City of Buffalo are in terms of the collection
districts, the data was subsequently translated into the census tract basis
teing utilized within this study. This translation was predicated primarily
ma uniform population distribution being assumed for the individual collection
districts except for those instances where the land-use patterns (e.g. parks,
industrial areas, shopping centers, institutions, etc.) indicated otherwise.
llthough the City of Buffalo collection included some nonresidential refuse
(light commercial), no data are available to estimate the proportions of
nfuse which is obtained from residences and the proportions from the other
lources. The estimation procedure for the remainder of Erie County entailed
the assignment of the total amount of refuse (exclusive of that which is clearly
identified as generated by commerce and industry) to the census tracts in direct
proportion to the populations residing within each tract.
The data utilized was provided by the Office of the Commissioner of Streets
wd Sanitation, City of Buffalo.
B-9
-------
The results of these estimating procedures are shown in Tables
B.2 and B.3 (City of Buffalo), Tables B.4 and B.5 (Remainder of Brie
County), and Figs. B.I and B.2
B.5 Future Solid Waste Generation
As described in Waste Management (Ref. 1), estimating future solid
waste is difficult because of the many variables influencing the estimate.
The two most significant factors affecting the magnitude and characteristics
of generated solid waste have been the significant changes in packaging practices
and in fuel selection. The impact of packaging practices, which has resulted
in a sizable increase in the amount of paper and paper products as well as
the proportion of these materials constituting refuse, has resulted in a decrease
in food wastes. Additionally, plastics associated with packaging is being
encountered and it can be expected that the quantity will increase significantly
over the 35 year projection period. Noncombustible solid waste have increased
as a result of industry decisions concerning nonreturnability of containers
and the expanded uses of cans. With respect to fuels used for household heating
and industrial applications, there is a continuous diminution in ashes, in
particular within household heating, and it can be expected that the increased
uses of gas, oil and nuclear fuels will result in the virtual disappearance
of ashes by the end of the 35-year planning period.
With these major changes as well as others being brought about
by technological and economic factors the composition (type of materials and
their proportions) of refuse will be affected and thus influence the processing
and disposal decisions. For example, aluminum and plastics are virtually
nondegradable. Aluminum may be incinerated at high temperatures, but this
results in gaseous wastes which could lower air quality. A similar affect
is experienced from the incineration of plastics. Glass when introduced into
a normal temperature incincerator will melt but seldom burn and is nondegradable
in landfills. It has been found that the degradability of plastic-lined
paper containers is very low.
B-10
-------
Table B.2
ESTIMATED REFUSE QUANTITIES FOR CENSUS TRACTS
WITHIN CITY OF BUFFALO, 1966 (TONS PER DAY)
CENSUS
TRACT
1
2
3
4
5
6
7
8
9
10
11
12
13
11
15
16
17
IB
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
COORDINATES
5.95, 2,50
6.31, 3.60
5.30, 3.49
5.90, 4.52
4.59, 4,30
6.88, 2.50
7.50, 2.50
6.91, 3.17
7.00, 3.62
7.59, 3.60
7.00, 4.30
4.90, 5.20
3.90, 5.10
4.44, 5.96
5.12, 6.00
5.95, 6.30
5.89, 5.73
5.72, 5.15
7.39, 4.75
6.55, 5.39
7.25, 5.55
7.65, 5.30
7.15, 6.14
7,20, 6.60
4.30, 6.45
5.05, 6.65
5.74, 6.95
6.71, 7.10
6.80, 7.60
7.60, 7.50
4.63, 7.10
4.55, 7.92
5.15, 8.05
6.00, 8.40
5.99, 7.74
6.83, 8.25
PRIVATE COLLECTION
TOTAL
26.96
63.54
22.23
31.62
—
—
—
— -
—
5.46
—
18.38
43.31
10.85
—
8.35
7.08
5.31
—
14.15
—
—
--
2.88
75.23
--
4.65
4.31
—
--
5.31
7.65
4.31
76.27
33.35
1.35
NON-COMBUSTIBLE
26.96
63.54
22.23
15.81
__
—
__
—
--
2.73
—
9.19
32.48
2.71
__ •
2.09
3.54
2.66
--
10.61
--
—
—
0.72
37.62
—
2,33
2.16
—
~
2.12
3.06
1.08
68.64
26.68
0.34
COMBUSTIBLE
„
MIB
• _
15.81
__
__
_.
__
__
2.73
__
9.19
10.83
8.14
—
6.26
3.54
2.65
—
3.54
—
—
—
2.16
37.61
—
2.32
2.15
--
—
3.19
4.59
3.23
7.63
6.67
1.01
MUNICIPAL
COMBUSTIBLE
5,84
12.10
2.45
1.54
6.06
13.25
9.01
12.85
5.94
14.83
7.55
9.17
6.80
26.86
14.10
19.82
6.95
2.81
7.92
10.55
2.09
4.56
8.57
15.04
41.12
6.38
26.98
14.99
11.09
6.50
20.49
26.66
26,30
11.90
16.65
11.71
TOTAL
COMBUSTIBLE
5.84
12.10
2.45
17.35
6.06
13.25
9.01
12.85
5.94
17.56
7.55
18.36
17.63
35.00
14.10
26.08
10.49
5.46
7.92
14.09
2.09
4.56
8.57
17.20
78.73
6.38
29.30
17.14
11.09
6.50
23.68
31.25
29.53
19.53
23.32
12.72
TOTAL
REFUSE
32.80
75.64
24.68
33.16
6.06
13.25
9.01
12.85
5.94
20.29
7.55
27.55
50.11
37.71
14.10
28.17
14.03
8.12
7.92
24.70
2.09
4.56
8.57
17.92
116.35
6.38
31 .63
19.30
11.09
6.50
25.80
34.31
30.61
88.17
50.00
13.06
-------
Table B.2 (Cont.)
ESTIMATED REFUSE QUANTITIES FOR CENSUS TRACTS
WITHIN CITY OF BUFFALO, 1966 (TONS PER DAY)
CENSUS
TRACT
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63A
63B
64
65A
65B
66A
66B
67
68
69
70
71
72
COORDINATES
7.40, 8.25
7.80, 8.29
6.42, 9.15
5.85, 9.49
7.49, 9.00
6.90, 9.70
7.50,10.40
7.59, 9.71
5.83,10.55
6.78,11.14
6.70,10.45
5.15,10.66
4.59,10.71
3.80,10.80
4.63,11.24
5.35, 9.35
4.65, 9.50
4.14, 9.99
2.90,10.04
3.10,10.84
2.40,10.74
2.22,11.30
2.15, 9.95
2.70, 9.01
2.50, 8.31
3.25, 9.40
3.30, 8.80
3.81, 8.96
4.30, 8.84
3.25, 8.32
3.99, 8.35
3.29, 8.01
3.90, 8.01
3.64, 7.59
3 . 60 i 6 . 99
2.90, 7.60
2.50, 7.26
2.95, 6.50
3.45, 5.95
PRIVATE COLLECTION
TOTAL
__
—
23.19
12.81
—
22.73
—
—
3.31
__
—
— •
—
28.50
—
—
—
36.50
39.08
23.69
9.35
—
--
10.04
1.85
~
~
—
—
—
~
~
~
~
14.42
~
2.88
6.42
NON-COMBUSTIBLE
-**
—
9.28
3.20
—
11.37
—
—
0.85
—
—
—
—
22.80
—
~
.
29.20
31.26
17.77
7.01
—
—
7.53
0.46
•»••
—
.
—
—
..
—
—
—
- 3.61
—
—
1.44
3.21
COMBUSTIBLE
—
—
13.91
9.61
—
11.36
~
—
2.46
—
—
—
5.70
—
~
—
7.30
7.82
5.92
2.34
•— .
—
2.51
1.39
--
—
—
—
—
—
--
—
—
10.81
—
—
1.44
3.21
MUNICIPAL
COMBUSTIBLE
11.16
6.51
10.08
16.22
12.04
7.71
12.33
13.77
13.68
12.28
12.04
8.69
9.98
5.70
10.40
15.06
1.72
8.00
9.50
9.99
7.77
20.10
9.78
10.50
9.98
11.20
10.86
8.12
1.93
5.54
7.53
7.12
4.82
14.76
12.26
23.28
11.77
25.35
2.82
TOTAL
COMBUSTIBLE
11.16
6.51
23.99
25.83
12.04
19.07
12.33
13.77
16.14
12.28
12.04
8.69
9.98
11.40
10.40
15.06
1.72
15.30
17.32
15.91
10.11
20.10
9.78
13.01
11.37
11.20
10.86
8.12
1.93
5.54
7.53
7.12
4.82
14.76
23.07
23.28
11.77
26.79
6.03
TOTAL
REFUSE
11.16
6.51
33.27
29.03
12.04
30.44
12.33
13.77
16.99
12.28
12.04
8.69
9.98
34.20
10.40
15.06
1.72
44.50
48.58
33.68
17.12
20.10
9.78
20.54
11.83
11.20
10,86
8.12
1.93
5.54
7.53
7.12
4.82
14.76
26.68
23.28
11.77
28.23
9.24
TOTALS 707.32 488.29 219.03 859.78 1078.81 1567.10
B-12
-------
Table B.3
ESTIMATED REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS TRACTS
WITHIN CITY OF BUFFALO 1966 (TONS PER DAY PER SQUARE MILE)
CENSUS
TRACT
1
2
3
1
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
COORDINATES
5.95, 2.50
6.34, 3.60
5.30, 3.49
5.90, 4.52
4.59, 4.30
6.88, 2.50
7.50, 2.50
6.91, 3.17
7.00, 3.62
7.59, 3.60
7.00, 4.30
4.90, 5.20
3.90, 5.10
4.44, 5.96
5.12, 6.00
5.95, 6.30
5.89, 5.73
5.72, 5.15
7.39, 4.75
6.55, 5.39
7.25, 5.55
7.65, 5.30
7.15, 6.14
7.20, 6.60
4.30, 6.45
5.05, 6.65
5.74, 6.95
6.71, 7.10
6.80, 7.60
7.60, 7.50
4.63, 7.10
4.55, 7.92
5.15, 8.05
6.00, 8.40
5.99, 7.74
6.83, 8.25
AREA
(SQ.MI.)
1.61
0.50
2.18
0.56
1.37
0.45
0.42
0.43
0.22
0.83
0.59
0.69
1.10
0.50
0.41
0.57
0.49
0.35
0.49
0.78
0.46
0.28
0.49
0.75
0.60
0.18
0.67
0.52
0.33
0.51
0.60
0.68
0.69
0.59
0.62
0.51
MUNICIPAL
COMBUSTIBLE
3.62
24.20
1.12
2.75
4.42
29.44
21.45
29.88
27.00
17.86
12.79
13.28
6.18
53.72
34.39
34.77
14.18
8.02
16.16
13.52
4.54
16.28
17.48
20.05
68.53
35.44
40.26
28.82
33.60
12.74
34.15
39.20
38.11
20.16
26.85
22.96
TOTAL
COMBUSTIBLE
3.62
24.20
1.12
30.98
4.42
29.44
21.45
29.88
27.00
21.15
12.79
26.60
16.02
70.00
34.39
45.75
21.40
15.60
16.16
18.06
4.54
16.28
17.48
22.93
131.21
35.44
43.73
32.96
33.60
12.74
39.46
45.95
42.79
33.10
37.61
24.94
TOTAL
REFUSE
20.37
1 51 . 28
11.32
59.21
4.42
29.44
21.45
29.88
27.00
24.44
12.79
39.92
45.55
75.42
34.39
49.42
28.63
23.20
16.16
31.66
4.54
16.28
17.48
23.89
193.91
35.44
47.20
37.11
33.60
12.74
43.00
50.45
44.36
149.44
80.64
25.60
B-13
-------
Table B.3 (Cont.)
ESTIMATED REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS TRACTS
WITHIN CITY OF BUFFALO 1966 (TONS PER DAY PER SQUARE MILE)
CENSUS
TRACT
37
38
39
40
41
. 42
43
44
,45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63A
63B
64
65A
65B
66A
66B
67
68
69
70
71
72
COORDINATES
7.40, 8.25
7.80, 8.29
6.42, 9.15
5.85, 9.49
7.49, 9.00
6.90, 9.70
7.50,10.40
7.59, 9.71
5.83,10.55
6.78,11.14
6.70,10.45
5.15,10.66
4.59,10.71
3.80,10.80
4.63,11.24
5.35, 9.35
4.65, 9.50
4.14, 9.99
2.90,10.04
3.10,10.84
2.40,10.74
2.22,11.30
2.15, 9.95
2.70, 9.01
2.50, 8.31
3.25, 9.40
3.30, 8.80
3.81, 8.96
4.30, 8.84
3.25, 8.32
3.99, 8.35
3.29, 8.01
3.90, 8.01
3.64, 7.59
3.60, 6.99
2.90, 7.60
2.50, 7.26
2.95, 6.50
3.45, 5.95
AREA
(SQ.MI.)
0.46
0.24
0.63
0.77
0.51
0.40
0.47
0.59
0.78
0.80
0.62
0.40
0.45
0.51
0.45
0.67
0.80
0.77
0.59
0.82
0.36
0.66
0.49
0.74
0.47
0.38
0.24
0.39
0.24
0.19
0.28
0.15
0.16
0.54
0.35
0.49
0.56
0.66
0.57
MUNICIPAL
COMBUSTIBLE
24.26
27.12
,16.00
21.06
23.60
19.27
26.23
23.33
17.53
15.35
19.41
21.72
22.17
11.17
23.11
22.47
2.15
10.38
16.10
12.18
21.58
30.45
19.95
14.18
21.23
29.47
45.25
20.82
8.04
29.15
26.89
47.46
30.12
27.33
35.02
47.51
21.01
38.40
4.94
TOTAL
COMBUSTIBLE
24.26
27.12
38.07
33.54
23.60
47.67
26.23
23.33
20.69
15.35
19.41
21.72
22.17
22.35
23.11
22.47
2.15
19.87
29.35
19.40
28.08
30.45
19.95
17.58
24.19
29.47
45.25
20.82
8.04
29.15
26.89
47.46
30.12
27.33
65.91
47.51
21.01
40.59
10.57
TOTAL
REFUSE
24.26
27.12
52.80
37.70
23.60
76.10
26.23
23.33
21.78
15.35
19.41
21.72
22.17
67.05
23.11
22.47
2.15
57.79
82.33
41.07
47.55
30.45
19.95
27.75
25.17
29.47
45.25
20.82
8.04
29.15
26.89
47.46
30.12
27.33
76.22
47.51
21.01
42.77
16.21
AVERAGES ^i^*"' ZQ-]* 25.28 36.72
B-14
-------
Table B.iV
ESTIMATED REFUSE QUANTITIES FOR CENSUS TRACTS IN ERIE COUNTY
OUTSIDE CITY OF BUFFALO, 1966 (TONS PER YEAR)
CENSUS
TRACT
73A
73B
711
75
76
77
78
79A
79B
80A
SOB
81A
816
82A
82B
83
84
85
86
87
88
89
90
91A
91B
: 91 C
:'91D
92
x
f 93A
93B
94A
94B
• 95A '
!•' 958
96
97
'•98
99
100A
'1008
101 A
101 B
POLITICAL
SUBDIVISION
GRAND ISLAND (T)
GRAND ISLAND (T)
TON A WAN DA (C)
TON AW AN DA (C)
TONAWANDA (C)
TONAWANDA (C)
TONAWANDA (C)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
KEN MO RE (V)
KENMORE (V)
KENMORE (V)
KENMORE (V)
WILLIAMSVILLE (V)
AMHERST (T|
AMHERST 1T)
AMHERST (T)
AMHERST (T)
AMHERST (T)
AMHERST (T)
AMHERST (T)
AMHEfrST (T).
AMHERST (T)
AMHERST (T)
AMHERST (T)
AMHERST (T)
AMHERST (T)
OEPEW WALSO H5
DEPEW (V)
SLOAN (V)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
COORDINATES
0.0 15.8
- 2.3 13.8
4.34 15.95
3.85 15.75
1. 29 15.05
3.15 15. 49
2.50 15.04
5.63 15.08
5.75 13.40
5.90 12.60
5.48 11.90
4.34 13*76
4.50 12.65
3.50 13.80
3.50 12.69
2.10 13.84
1.46 12.45
4.38 11.50
4.30 11.93
3.75 11.90
3.25 11.80
11.00 11.70
11.30 16.40
7.50 16.70
7.40 14.20
9.60 14.20
8.80 13.30
7.20 13.60
6.79 12.14
7.36 12.57
8.10 12.35
9.80 12.30
8.10 11.30
9.85 11.19
12.45 11.78
12.60 8.39
12.91 7.40
8.34 6.55
11.70 10.10
11.95 9.14
9.60 10.06
9.50 9.20
REFUSE
RESIDENTIAL
2,203
3,797
622
1,007
2,527
3,363
3,981
9,714
5,595
4,509
7,362
3,788
2,942
1,829
2,620
2,346
2,078
1,603
2,920
3,248
2,446
3,315
3,525
942
1,021
4,756
1,943
2,323
3,660
2,053
3,774
2,782
3,437
4,461
2,008
4,317
895
2,556
2,380
5,365
6,360
2,883
COMMERCIAL/
INDUSTRIAL
—
2,400
..
—
—
20,105
23,806
—
--
—
—
—
—
—
—
15,211
13,478
—
—
~
—
3,780
—
--
--
'
—
2,630
4,183
2,347
—
—
—
5,060
—
—
--
3,188
4
3,596
~
• M>
TOTAL
COMBUSTIBLE
2,203
4,997
622
1,007
2,527
13,416
15,884
9,714
5,595
4,509
7,362
3,788
2,942
1,829
2,620
9,952
8,817
1,603
2,920
3,248
2,446
5,205
3,525
942
1,021
4,756
1,943
3,638
5,752
3,227
3,774
2,782
3,437
6,991
2,008
4,317
895
4,150
2,380
7,163
6,360
2,883
REFUSE
2,203
6,197
622
1,007
2,527
23,468
27,787
9,714
5,595
4,509
7,362
3,788
2,942
1,829
2,620
17,557
15,556
1,603
2,920
3,248
2,446
7,095
3,525
942
1,021
4,756
1,943
4,953
7,843
4,400
3,774
2,782
3,437
9,521
2,008
4,317
895
5,744
2,380
8,961
6,360
2,883
B-15
-------
Table B.4 (Cont.)
ESTIMATED REFUSE QUANTITIES FOR CENSUS TRACTS IN ERIE COUNTY
OUTSIDE CITY OF BUFFALO, 1966 (TONS PER YEAR)
CENSUS
TRACT
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120A
120B
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141 A
1418
POLITICAL
SUBDIVISION
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
BLASOELL (V)
HAMBURG (T)
HAMBURG (T)
HAMBURG (T)
HAMBURG (V)
HAMBURG (V)
HAMBURG (V)
ORCHARD PARK (T)
ORCHARD PARK (V)
ORCHARD PARK (T)
AURORA (T)
EAST AURORA (V)
EAST AURORA (V)
ELMA (T)
ELMA (T)
COORDINATES
8.33 9.74
8.02 8.10
8.40 7.82
8.50 8.32
9.72 8.70
9.39 7.80
11.72 6.38
9.70 6.38
8.71 5.40
8.30 5.70
11.84 3.82
9.02 4.15
8.05 3.45
8.70 3.34
9.53 2.90
9.20 2.35
11.65 2.48
12.12 1.58
8.66 1.17
10.29 0.73
5.35 1.82
5.10 0.99
6.10 1.30
6.05 0.55
7.60 1.15
6.95 0.79
6.60 1.59
5.8 -0.5
7.0 -1.9
5.5 -1.8
2.2 -4.9
4.7 -6.1
6.0 -5.9
4.8 -4.9
10.2 -4.9
10.3 -2.7
10.2 -1.1
15.8 -4.4
16.8 -2.8
16.9 -2.2
17.2 1.4
14.2 1.1
REFUSE
RESIDENTIAL
4,385
874
1,482
1,529
1,830
2,174
3,261
3,700
1,294
1,715
1,904
2,440
1,547
918
1,204
2,333
1,703
2,751
3,140
3,060
933
2,207
2,061
1,689
3,918
1,093
99
1,446
2,767
1,597
4,505
3,058
1,486
2,141
3,427
1,962
4,611
5,392
2,277
2,831
2,159
2,541
COMMERCIAL/
INDUSTRIAL
5,469
1 ,090
—
1,908
2,283
2,712
~
4,615
—
2,139
—
—
--
—
—
—
—
12,300
~
~
1,050
~
2,320
1,900
—
1,230
—
—
—
35,000
~
~
-_
—
--
4,000
.-
--
4,270
3,430
900
1,000
TOTAL
COMBUSTIBLE
7,120
1,419
1,482
2,483
1,141
1,356
3,261
2,307
1,294
2,785
1,904
2,440
1,547
918
1,204
2,333
1,703
8,901
3,140
3,060
1,458
2,207
3,221
2,639
3,918
1,708
99
1,446
2,767
19,097
4,505
3,058
1,486
2,141
3,427
3,962
4,611
5,392
2,135
1,715
2,609
3,041
REFUSE
9,854
1,964
1,482
3,437
4,113
4,886
3,261
8,315
1,294
3,854
1,904
2,440
1,547
918
1,204
2,333
1,703
15,051
3,140
3,060
1,983
2,207
4,381
3,589
3,918
2,323
99
1,446
2,767
36 , 597
4,505
3,058
1,486
2,141
3,427
5,962
4,611
5,392
4,270
6,261
3,059
3,541
B-16
-------
Table B.H (Cont.)
ESTIMATED REFUSE QUANTITIES FOR CENSUS TRACTS IN ERIE COUNTY
OUTSIDE CITY OF BUFFALO, 1966 (TONS PER YEAR)
CENSUS
TRACT
142 A
142B
143
144
145
146A
146B
147
148
149
ISO
150
150
151
151
152
,153
154
155
156
157
158
159
160
161
162
POLITICAL
SUBDIVISION
LANCASTER (T)
LANCASTER (T)
LANCASTER (V)
LANCASTER (V)
DEPEW(T)(ALSO 97S98)
CLARENCE (T)
CLARENCE (T)
CLARENCE (T)
NEWSTEAD (T)
ALDEN {T)
MAR ILL A (T)
WALES (T)
HOLLAND (T)
COLDEN (T)
SARDINIA (T)
BOSTON (T)
EDEN (T)
EVANS (T)
EVANS (T)
BRANT (T)
NORTH COLLINS (T)
CONCORD (T)
SPRINGVILLE (V)
COLLINS (T)
GO WAN DA STATE HOSP.
CATTARAUGUS IND.RES.
COORDINATES
15.8 9.1
15.8 5.5
14.1 6.4
14.1 7.3
13.95 8.10
14.3 11.4
14.2 14.2
16.9 16.1
21.8 15.4
21.9 8.0
21.2 1.7
21.9 -4.4
21.9 -10.7
15.8 -10.7
21.0 -15.3
9.8 -10.7
3.6 -10.8
-2.5 -9.0
-3.5 -12.3
-3.9 -15.3
4.3 -16.8
12.6 -18.2
14.6 -21.0
4.3 -22.4
0.9 -22.6
-3.2 -18.1
REFUSE
RESIDENTIAL
3,388
2,124
4,474
3,688
4,326
2,022
1,450
2,728
2,800
3,700
,300
,100
,100
,000
,000
2,600
2,500
4,317
5,983
,350
,200
,267
,733
,521
,379
400
COMMERCIAL/
INDUSTRIAL
—
—
3,400
2,800
—
3,600
~
~
1,300
2,000
600
600
600
600
500
1,300
1,600
—
2,800
500
800
—
1,500
1,700
—
—
TOTAL
COMBUSTIBLE
3,388
2,124
6,174
5,088
4,326
3,822
1,450
2,728
3,450
4,700
,600
,400
,400
,300
,250
3,250
3,300
4,317
7,383
1,600
1,600
1 , 267
2,483
2,371
1,379
400
REFUSE
3,388
2,124
7,874
6,488
4,326
5,622
1,450
2,728
4,100
5,700
1,900
1,700
1,700
1,600
1,500
3,900
4,100
4,317
8,783
1,850
2,000
1,267
3,233
3,221
1,379
400
TOTALS 293,150 213,600 399,950 506,750
B-17
-------
Table B.5
ESTIMATED REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS TRACTS
IN ERIE COUNTY OUTSIDE CITY OF BUFFALO, 1966
(TONS PER DAY PER SQUARE MILE)
CENSUS
TRACT
73A
73B
74
75
76
77
78
79A
798
BOA
BOB
81A
BIB
82A
828
83
84
65
86
87
88
89
90
91A
91 B
91C
910
92
93A
938
94A
948
95A
958
96
97
98
99
100 A
1008
101A
1018
POLITICAL
SUBDIVISION
GRAND ISLAND (T)
GRAND ISLAND (T)
TON AMANDA (C)
TONAWANDA (C)
TONAWANDA (C)
TONAWANDA (C)
TONAWANDA (C)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
TONAWANDA (T)
KENMORE (V)
KENHORE (V)
KENMORE (V).
KENHORE (V)
WILLIAHSVILLE (V)
AHHERST (T)
AMHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
AHHERST (T)
DEPEW (V)i
DEPEW (V)J A"" 145
SLOAN (V)
CHEEKTOWWGA (T)
CHEEKTOWWGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
COORDINATES
0.0 15.8
-2.3 13.8
4.34 15.95
3.85 15.75
4.29 15.05
3.45 15.49
2.50 15.04
5.63 15.08
5.75 13.40
5.90 12.60
5.48 11.90
4.34 13.76
4.50 12.65
3.50 13.80
3.50 12.69
2.10 13.84
1.46 12.45
4.38 1 .50
4.30 1 .93
3.75 1 .90
3.25 1 .80
11.00 1 .70
11.30 16.40
7.50 16.70
7.40 14.20
9.60 14.20
8.80 13.30
7.20 13.60
6.79 12.14
7.36 12.57
8.10 12.35
9.80 12.30
8.10 11.30
9.85 11.19
12.45 11.78
12.60 8.39
12.91 7.40
8.34 6.55
11.70 10.10
11.95 9.14
9.60 10.06
9.50 9.20
AREA
(SQ.MI.)
16.9
18.3
0.72
0.23
0.67
0.69
1.39
3.80
1.45
1.09
1.48
1.29
0.75
1.10
0.60
3.82
4.62
0.32
0.44
0.32
0.32
1.20
18.9
8.27
3.51
5.96
2.16
2.49
0.37
0.79
.20
.44
.19
.61
4.40
.76
.34
0.70
2.76
1.85
1.51
0.86
TOTAL
COMBUSTIBLE
0.50
1.05
3.32
16.84
14.51
74.78
43.95
9.83
14.84
15.91
19.13
11.29
15.09
6.40
16.79
10.02
7.34
19.27
25.52
39.04
29.40
16.68
0.72
0.44
1.12
3.07
3.46
5.02
59.79
15.71
12.10
7.43
11.11
16.70
1.76
9.43
2.57
22.80
3.32
14.89
16.20
12.89
REFUSE
0.50
1.30
3.32
16.84
14.51
130.81
76.89
9.83
14.84
15.91
19.13
11.29
15.09
6.40
16.79
17.68
12.95
19.27
25.52
39.04
29.40
22.74
0.72
0.44
1.12
3.07
3.46
7.65
81.53
21.42
12.10
7.43
11.11
22.74
1.76
9.43
2.57
31.56
3.32
18.63
16.20
12.89
B-18
-------
Table B.5 (Cont.)
ESTIMATED REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS TRACTS
IN ERIE COUNTY OUTSIDE CITY OF BUFFALO, 1966
(TONS PER DAY PER SQUARE MILE)
CENSUS
TRACT-
102
103
104
105
106
107
.108
109
110
111
112
113
114
115
116
117
118
119
120 A
120B
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141A
141B
POLITICAL
SUBDIVISION
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
CHEEKTOWAGA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
WEST SENECA (T)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
LACKAWANNA (C)
BLASOELL (V)
HAMBURG (T)
HAMBURG (T)
HAMBURG (T)
HAMBURG (V)
HAMBURG (V)
HAMBURG (V)
ORCHARD PARK (T)
ORCHARD PARK (V)
ORCHARD PARK (T)
AURORA (T)
EAST AURORA (V)
EAST AURORA (V)
ELMA (T)
ELMA (T)
COORDINATES
8.33 9.74
8.02 8.10
8.40 7.82
8.50 8.32
9.72 8.70
9.39 7.80
11.72 6.38
9.70 6.38
8.71 5.40
8.30 5.70
11.84 3.82
9.02 4.15
8.05 3.45
8.70 3.34
9.53 2.90
9.20 2.35
11.65 2.48
12.12 1.58
8.66 1.17
10.29 0.73
5.35 1.82
5.10 0.99
6.10 1.30
6.05 0.55
7.60 1.15
6.95 0.79
6.60 1.59
5.80 -0.5
7.0 -1.9
5.5 -1.8
2.2 -4.9
4.7 -6.1
6.0 -5.9
4.8 -4.9
10.2 -4.9
10.3 -2.7
10.2 -1.1
15.8 -4.4
16.8 -2.8
16.9 -2.2
17.2 1.4
14.2 1.1
AREA
(SQ.MI.)
1.61
0.39
0.16
0.59
0.47
2.18
7.82
2.69
0.39
0.42
4.77
2.45
0.31
0.92
0.74
1.28
1.51
3.69
2.68
3.15
0.44
1.99
0.49
0.60
1.44
1.07
0.04
0.89
5.92
4.82
8.99
19.60
0.56
1.41
24.7
1.28
12.8
34.2
1.14
1.43
18.7
15.9
TOTAL
COMBUSTIBLE
17.91
13.99
35.63
16.19
24.32
6.23
1.60
8.59
12.76
25.50
1.54
3.83
19.19
3.84
6.25
7.01
4.34
9.28
4.51
3.74
12.74
4.27
25.28
16.92
10.46
6.14
9.52
6.25
1.80
15.24
1.93
0.60
10.21
5.84
0.53
11.91
1.39
0.61
14.89
12.23
0.54
0.74
REFUSE
23.54
19.37
35.63
22.4!
33.66
8.62
1.60
11.89
12.76
35.29
1.54
3.83
19.19
3.84
6.25
7.01
4.34
15.69
4.51
3.74
17.33
4.27
34.39
23.01
10.46
8.35
9.52
6.25
1.80
29.20
1.93
0.60
10.21
5.84
0.53
17.91
1.39
0.61
22.09
16.84
0.63
0.86
B-19
-------
Table B.5 (Cont.)
ESTIMATED REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS TRACTS
IN ERIE COUNTY OUTSIDE CITY OF BUFFALO, 1966
(TONS PER DAY PER SQUARE MILE)
CENSUS
TRACT
142A
142B
143
144
145
; me &
RGB
147
148
149
150
150
150
151
151
152
153
154
155
158
157
J58
159
160
161
162
POLITICAL
SUBDIVISION
LANCASTER (T)
LANCASTER (T)
LANCASTER (V)
LANCASTER (V)
DEP£W(T)(ALS097&9S)
CLARENCE (T)
CLARENCE (T)
CLARENCE (T)
NEWSTEAD (T)
ALDEN (T)
MAR ILL A (T)
WALES (T)
HOLLAND (T)
COLDEN (T)
SARDINIA (T)
BOSTON (T)
EDEN (T)
EVANS (T)
EVANS (T)
BRANT (T)
NORTH COLLINS (T)
CONCORD (T)
SPRINGVILLE (V)
COLLINS (T)
60WANDA STATE HOSP.
CATTARAUGUS IND.RES.
COORDINATES
15.3 9.1
15.8 5.5
11.1 6.4
14.1 7.3
13.95 8.1
14.3 11.4
14.2 14.2
16.9 JG.l
21.8 15.4
21.9 8.0
21.2 1.7
21.9 -4.4
21.9 -10.7
15.8 -10.7
21.0 -15.3
9.8 -10.7
3.6 -10.8
-2.5 -9.0
-3.5 -12.3
-3.9 -15.3
4.3 -16.8
12.6 -18.2
14.6 -21.0
4.3 -22.4
0.9 -22.6
-3.2 -13.1
AREA
(SQ.MI.)
21.9
13.7
1.21
1.52
1.70
4.19
11.2
38. 5(-)
51.2
34.6
27.5
36.0
36.0
36.0
50.8
35.7
39.9
19.7
22.2
25.9
43.3
67.0
3.44
46.6
1.07
13.7
TOTAL
COMBUSTIBLE
0.60
0.60
19.62
12.87
9.79
3.51
0.50
0.27
0.26
0.52
0.22
0.15
0.15
0.14
0.09
0.35
0.32
0.84
1.28
0.24
0.14
0.07
2.78
0.20
4.96
0.11
REFUSE
0.60
0.60
25.03
16.42
9.79
5.16
0.50
0.27
0.31
0.63
0.27
0.18
0.18
0.17
0.11
0.42
0.39
0.84
1.52
0.27
0.17
0.07
3.61
0.27
4.96
0.11
B-20
-------
PAGE NOT
AVAILABLE
DIGITALLY
-------
BOUNDARY SYMBOLS
Census Tract Boundaries.
•^^ . . . «_-^ Slate L>ne
^-^^^ — «»-^-^— Corporate Limit Line
^^^^— - MtntM Civil Division Line
.- . Oiner Tract Lines
Boundaries Which Are Not Tract Lines:
__ . Minor Civil Ovision Lin«
Figure B.2 ESTIMATED TOTAL REFUSE QUANTITIES PER SQUARE MILE FOR CENSUS
TRACTS IN ERIE COUNTY, NEW YORK, WHICH ARE OUTSIDE BUFFALO CITY
AND ADJACENT AREA, 1966 (TONS PER DAY PER SQUARE MILE)
B-22
-------
The above are samples of current changes in solid waste quantities
ad characteristics which have been observed but whose ultimate magnitudes
ie difficult to forecast. It can be expected that many new developments
Meeting solid waste are likely to take place by the year 2000.
Two major factors which have a profound influence on the quantity
({solid waste generation are the projected population of the region and the
ptoss regional product. The problems of deriving projections of the U.S.
jopulation and the gross national product out to the year 2000 are exceedingly
tifficult but are considered less difficult then making similar types of projections
it the regional level. With the increased mobility of both the U.S. population
ad economic activity, the scope and nature of this migration with respect
to a particular region is a large unknown.
Although the magnitude of these changes cannot be accurately predicted
tie directions of these changes are clearly discernible. Qualitatively, it
nbe expected that there will be increases in both the refuse generated
*r capita per unit time, and the amounts of solid waste produced by the industrial
ad service sectors will increase in some relationship with increases in the
(toss national product. For purposes of this study it was decided to accept
ml use the planning factors indicated within the National Academy of Sciences -
ktional Research Council Study (Ref. 3).
(a) The residential per capita generation of solid waste will
increase by approximately two percent per annum*
(b) The commercial and industrial generation of solid wastes will
increase annually by four percent.
Ms rate of increase appears to be representative of the increases experienced
tythe City of Buffalo since 1960.
B-23
-------
Utilizing the current estimates of solid waste generation in the
Buffalo SMSA, the projections of population changes within the census tracts
of the region; the assumption of no significant changes in the size of the
industrial, commercial and service sectors; and the above projection factors,
the following tables (Tables B.6 through B.12), represent an estimate of future
solid waste generation. For the purposes of the analytical planning tools
described in Sections 3 and 4 within the report, having projections for five
year increments out to the year 2000 appear adequate. The development of
comparable estimates on an annual basis could in no way refine the estimates
in view of the broad assumptions which were introduced as well as the many
unknown and intangible factors.
This basic information is apparently critical for purposes of
planning and research, and it is of importance that significant time and effort
be devoted within the Solid Wastes Program to the development of projection
models which can be used at the regional level. However, as has been mentioned
earlier, efforts should be made to obtain a more accurate estimate of the
current types and quantities of solid waste generated, and this information
should be categorized as to residential, commercial and industrial sources.
Using this information base, a range of projections should be made using a
range of assumptions pertaining to changes in quantity and type of solid waste
generated and the sensitivity of the "recommended" facility alternatives
should be tested for the range of projections utilized.
B-24
-------
00
I
to
in
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
1966
Table B.6
ANNUAL REFUSE TONNAGE RY CENSUS TRACTS
CITY OF BUFFALO
197C
1975
1980
1985
1990
1995
2000
1518
3144
636
400
1576
3444
2341
3341
1543
3856
1962
2383
1465
6984
3664
3854
1R05
711
2058
1183
544
1185
2228
3910
10691
1659
7013
3897
2882
1688
5326
6932
6R39
3094
4327
3045
2900
1692
262C
4215
1570
3252
657
414
163C
3561
2421
3455
1596
3988
2029
2465
1516
7222
3790
3986
1867
756
2128
1224
562
1225
2305
4044
11056
1716
7253
4031
2981
1746
5509
7169
7072
3200
4475
3149
2999
1750
2710
436C
1698
3497
707
445
1753
3829
2603
3715
1716
4289
2182
2651
1630
7766
4075
4286
2008
813
2288
1316
605
1317
2478
4348
11889
1845
7799
4334
3205
1878
5923
7708
7605
3441
4812
3386
3225
1881
2914
46R8
1830
3792
767
483
1901
4153
2823
4029
1861
4650
2366
2874
1767
8421
4419
4647
2177
881
2481
1427
656
1429
2687
4715
12892
2000
8457
4700
3476
2036
6423
8359
8246
3731
5218
3672
3497
2040
3159
5083
2007
4158
841
530
2085
4554
3096
4418
2041
5099
2595
3152
1938
9234
4845
5096
2387
966
2721
1565
719
1567
2947
5170
14136
2194
9273
5154
3811
2233
7043
9166
9043
4091
5722
4027
3835
2237
3464
5574
2216
4591
928
585
2302
5028
3418
4878
2254
5630
2865
3480
2140
10196
5350
5627
2636
1067
3004
1728
794
1730
3254
5709
15608
2422
10239
5690
4208
2465
7776
10120
9984
4517
6318
4446
4234
^ 2470
3825
6154
2464
5103
1032
650
2559
5589
3800
5422
2505
6259
3185
3869
2379
11334
5947
6255
2930
1186
3340
1921
883
1923
3617
6346
17350
2693
11382
6326
4678
2740
8645
11250
11099
5021
7023
4942
4707
2746
4252
6841
2782
5762
1165
734
2889
6311
4291
6123
2829
7067
3596
4368
2686
12798
6715
7063
3309
1339
3771
2169
997
2171
4084
7166
19591
3040
12852
7143
5282
3094
9761
12703
12532
5670
7930
5581
5315
3101
4801
7725
-------
Table B.6 (Cont.)
ANNUAL REFUSE TONNAGE BY CENSUS TRACTS
CITY OF BUFFALO (CCNT.l
w
ro
41
42
43
44
45
46
47
48
49
SO
51
52
53
54
55
56
57
58
59
60
61
62
63A
63B
64
65A
65B
66 A
668
67
68
69
70
71
72
1966
1970
3129
?004
3206
3581
3555
3192
3129
2259
?593
1483
2704
3916
447
2079
2469
2597
2018
5224
2543
2729
2593
2910
2822
2111
501
1439
1957
1850
1253
3837
3188
6053
3060
6590
733
3236
2073
3315
3703
3677
3301
3236
2336
2682
1533
2796
4050
462
2150
2554
2686
2088
5403
263C
2822
2682
3010
2919
2183
518
1488
2024
1913
1296
3968
3297
626C
3165
6816
758
1975
3479
2229
3565
3982
3954
3550
3480
2512
2884
1649
3007
4354
497
2312
2746
2888
2245
5810
2828
3035
2884
3237
3139
2347
557
1600
2176
2057
1394
4267
3545
6731
3403
7329
815
1980
3773
2417
3866
4318
4287
3849
3773
2724
3127
1788
3260
4722
539
2507
2978
3132
2434
6300
3066
3291
3127
3510
3404
2546
604
1735
2360
2230
1511
4627
3844
7299
369C
7947
884
1985
1990
1995
2000
4137
2650
4239
4735
4701
4221
4138
2987
3429
1961
3575
5178
591
2749
3265
3434
2669
6908
3362
3609
3429
3849
3732
2791
662
1903
2588
2446
1657
5073
4215
8004
4046
8715
969
4568
2926
4680
5228
5191
4661
4568
3298
3786
2165
3947
5717
653
3036
3605
3792
2947
7627
3712
3984
3786
4249
4121
3082
731
2101
2857
2700
1830
5602
4654
8837
4468
9622
1070
5078
3253
5203
5812
5770
5181
5079
3666
4209
2406
4388
6355
726
3375
4008
4215
3276
8479
4127
4429
4209
4724
4581
3426
813
2335
3176
3002
2034
6227
5174
9823
4966
10696
1189
5734
3673
5875
6562
6516
5850
5735
4140
4753
2717
4955
7176
820
3811
4526
4760
3699
9574
4660
5002
4753
5334
5173
3869
918
2637
3587
3390
2297
7031
5842
11092
5608
12078
1343
-------
CO
NJ
Table B.7
ANNUAL TONS OF REFUSE PER CAPITA
CITY OF BUFFALO
1966 1970 1975 1980 1985 1990 1995 2000
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
0.449
0.449
0.450
0.330
0.330
0.449
0.423
0.437
0.436
C.423
0.413
0.385
0.445
0.763
C.390
0.452
0.464
0.342
0.415
0.476
0.454
0.415
0.440
0.472
1.145
C.390
0.469
0.484
0.432
0.432
0.462
0.450
0.433
0.434
0.433
0.435
0.432
0.432
0.440
0.453
0.4R6
0.486
0.487
0.357
0.357
0.486
0.457
0.473
0.472
0.457
0.447
0.416
0.482
0.826
0.423
0.489
0.502
0.371
0.450
0.515
0.491
0.450
0.476
0.511
1.240
0.423
0.508
0.524
0.467
0.468
0.500
0.487
0.469
0.470
0.468
0.470
0.468
C.468
0.476
0.490
0.537
0.537
0. 537
0.394
0.394
0.537
0.505
0.522
0.521
0.505
0.493
0.460
0.532
0.912
0.467
0.540
0.554
0.409
0.497
0.569
0.543
0.496
0.526
0.564
1.369
0.467
0.561
0.578
0.516
0.517
0.552
0.538
0.518
0.518
0.517
0.519
0.517
0.517
0.526
0.541
0.593
0.593
0.593
0.435
0.435
0.593
0.557
0.576
0.575
0.558
0.544
0.508
0.587
1.007
0.515
0.596
0.612
0.452
C.548
0.628
0.599
0.548
0.580
0.623
1.511
0.515
0.619
C.638
0.569
0.571
0.609
0.594
C.572
0.572
0.571
0.574
0.570
0.571
0.581
0.598
0.655
0.654
0.655
0.481
0.480
0.654
0.616
0.636
0.635
0.616
0.601
0.560
0.64R
1.111
0.569
0.658
0.675
0.499
0.605
0.693
0.661
0.605
0.641
0.688
1.668
0.569
0.683
0.705
0.629
0.630
0.673
0.655
0.631
0.632
0.630
0.633
0.630
0.630
0.641
0.660
0.723
0.723
0.723
0.531
0.530
0.723
0.680
0.703
0.701
0.680
0.663
0.619
0.716
1.227
0.628
0.726
0.746
0.551
0.668
0.766
0.730
0.668
0.707
0.760
1.842
0.628
0.755
0.778
0.694
0.695
0.743
0.724
0.697
C.698
0.696
0.699
0.695
0.696
0.708
0.729
0.798
0.798
0.798
0.586
0.5S6
0.798
0.750
0.776
C.774
0.750
0.733
0.683
0.790
1.355
0.693
0.602
0.823
0.606
0.738
0.845
0.806
0.738
0.781
0.839
2.034
0.693
0.833
0.659
0.766
0.768
C.820
0.799
0.770
0.770
0.768
0.772
0.768
0.768
0.781
0.805
0.681
C.881
0.882
0.647
0.647
0.881
0.828
0.857
0.854
0.829
0.809
0.754
0.872
1.496
0.765
0.885
0.909
0.671
0.815
0.933
0.89C
0.814
0.862
0.926
2.245
0.765
0.920
0.949
C.846
0.848
0.905
0.882
0.850
0.851
0.848
0.852
0.646
0.848
0.863
C.888
-------
09
1966
Table B.7 (Cont.)
ANNUAL TCNS OF 9EFUSF PFR CAPITA
CITY OF BUFFALO {CONT.I
1970
1975
19*0
1985
1990
1995
2000
41
42
43
44
45
46
47
46
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63 A
638
64
65A
65B
66 A
66B
67
68
69
70
71
72
0.389
0.410
0.437
0.389
0.467
0.459
0.441
0. 4 16
0.285
Q.425
0.444
0.418
0.387
0.404
0.423
0.428
0.496
0.496
0.495
0.347
0.337
0.556
0.486
0.543
0.500
0.337
0.48?
0.461
0.482
0.483
0.502
0.459
0.469
0.511
0.355
0.421
0.444
0.473
0.421
0.505
0.497
0.477
C.450
0.309
0.460
0.481
0.453
0.419
0.437
0,458
0.464
0.536
0.536
0.536
C. ;r»*.
0.36>t
C.602
0.526
0.587
0.541
0.364
C.522
0.499
0.522
0.523
0.544
0.497
0.508
0.553
0.384
0.465
0.490
0.523
0.465
0.558
0.548
0.527
0.497
0.341
0.508
0.531
0.500
0.463
0.483
0.505
0.512
0.592
0.592
0.592
0.415
0.402
0.665
0.581
3.648
0.597
0.402
0.576
0.551
0.576
C.578
0.600
0.549
0.561
0.611
0.424
0.513
0.541
0.577
0.513
0.616
0.605
0.581
0.548
0.377
0.561
0.586
0.552
0.511
0.533
0.558
0.565
0.654
0.654
0.654
0.458
0.444
0.734
0.642
0.716
0.659
0.444
0.636
0.608
0.636
0.638
0.663
0 . 606
C.619
0.675
0.468
0.566
0.598
0.637
C.566
0.680
0.668
0.642
0.606
0.416
0.619
0.647
0.6C9
0.564
0.589
0*616
0.624
0.722
0.722
0.722
0.506
0.490
0.810
0.7C8
0.791
0.728
0.490
0.702
0.671
0.702
0.704
0.732
0.669
0.684
0.745
0.517
0.625
C.660
0.703
0.625
0.750
0.738
0.709
0.669
0.459
0.684
0.714
0.673
0.623
0.650
0.680
0.689
0.797
0.797
0.797
0.558
0.541
0.894
0.782
0.873
0.804
0.542
0.775
0.741
0.775
0.777
0.808
0.738
0.755
0.822
0.571
0.690
0.726
, 0.777
0.690
0.829
0.815
0.782
0.738
0.507
0.755
0.788
0.743
0.687
0.717
0.751
0.761
0.880
C.880
0.880
0.616
0.596
0.987
0.864
0.964
0.888
0.596
0.856
0.618
0.856
0.858
0.892
0.815
0.833
C.908
0.631
0.762
0. 804
CA £ Tf
• 857
0» + •)
• 762
ۥ915
0.900
0.864
C.815
0.560
0.833
0.871
0.820
0,759
0.792
0.829
C.840
0.972
0.972
0.971
0.681
C.660
1.090
0.953
1.064
0.980
0.660
0.945
0.904
0.945
0.948
0.985
0.900
0.920
1.002
0.696
-------
W
N>
tO
Table B,8
ANNUAL TCNS OF REFUSE PER SQUARE PILE
CITY OF BUFFALO
1970
1975
1980
1985
1990
1995
200C
I
2
3
Jr
4
5
X
6
7
q
10
1 1
12
I 3
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
943
6289
291
715
1151
7653
5575
777C
701B
4646
3326
3455
1332
13968
8938
676?
3685
2089
4200
1517
1183
4232
4548
5214
17818
9218
10468
7496
8735
3311
8878
10194
9911
5244
6980
5971
6305
7051
4159
5475
975
6504
101
740
1190
7915
5765
8036
7258
4805
3440
3573
1378
14445
9244
6993
3811
2160
4344
1569
12?3
4377
4704
5392
18427
9534
10826
7752
9033
3424
9181
10543
10250
5424
7219
6176
6521
7292
4301
5662
1048
6994
324
796
1279
8511
6199
8641
7804
5167
3699
3fl4?
1481
15533
9940
7519
4098
2323
4671
1687
1315
4707
5058
5798
19815
10251
11640
8336
9713
3682
9873
11336
11022
5832
7762
6641
7011
7841
4625
6088
1137
7584
351
863
1387
9229
6722
9370
8462
5603
40U
4166
1606
16843
10778
8154
4444
2519
5065
1830
1426
5104
5485
6287
21486
11116
12622
9039
10533
3993
10705
12292
11952
6324
8417
7201
7603
8502
5015
6602
1246
8316
385
946
1521
10120
7372
10275
9280
6144
4398
4568
1762
18469
11819
8941
4873
2762
5554
2006
1564
5597
6015
6894
23561
12189
13841
9912
11550
4378
11739
13479
13106
6935
9229
7896
8337
9323
5499
7239
1376
9182
426
1045
1680
11173
8139
11344
10245
6783
4856
5044
1945
20392
13049
9871
5380
3049
6132
2215
1727
6179
6641
7612
26013
13458
15282
10943
12752
4834
12961
14882
14470
7656
10190
8718
9205
10294
6072
7993
1530
10207
473
1161
1867
12420
9048
12611
11389
7541
5398
5607
2162
22669
14506
10974
5981
3390
6816
2463
1920
6869
7382
8462
28917
14961
16988
12165
14176
5374
14408
16544
16085
6511
11328
9691
10233
11443
6750
8885
1728
11525
534
1311
2109
14025
10216
14240
12861
8515
6096
6331
2442
25597
16360
12391
6753
3828
7697
2781
2168
7756
8336
9555
32653
16893
19183
13736
16007
6068
16269
18681
18163
9611
12791
10943
11554
12921
7f,22
10033
-------
Table B.8 (Cont.)
ANNUAL TONS OF REFUSE PER SQUARE *ILE
CITY OF BUFFALC (CONT.J
00
g
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63A
63B
64
65A
65 B
66A
66 B
67
68
69
70
71
72
1966
6135
5011
6821
6069
4558
399C
5047
5648
5764
2908
6GC9
5844
559
2700
4186
3167
5608
7916
5190
3688
5518
766C
11762
5413
2088
7575
6990
12333
7835
71 C6
9109
12353
546!
9986
1286
1970
6345
5183
7C54
6277
4714
4127
5220
5841
5961
3007
6214
6044
578
2793
4329
3276
5800
8187
5367
3814
5707
7922
12164
5598
2160
7834
7229
12755
8103
7349
9420
12776
5652
10327
1330
1975
6823
5573
7586
6750
5069
4438
5613
6281
6410
3233
6662
6499
622
3003
4655
3522
6236
8803
5771
4101
6137
8518
13080
6020
2322
8424
7773
13715
8713
7902
10129
13737
6077
11105
1430
1980
7398
6043
8225
7319
5497
4812
6C86
6811
6951
3506
7246
7048
674
3256
5C48
3820
6762
9546
6258
4447
6654
9237
14183
6528
2518
9134
8429
14873
9446
8568
10984
14896
6590
12042
1551
1985
8113
6627
9020
8026
6027
5277
6674
7469
7622
1845
7945
7728
739
3571
5535
4188
7415
10467
6863
4877
7297
10129
15553
7158
2761
10016
9243
16309
10360
9396
12044
16335
7226
13204
1700
1990
8957
7317
9958
8861
6655
5826
7369
8246
8415
4245
8772
8532
816
3943
6111
4624
8187
11557
7577
5385
8056
11183
17172
7903
3049
11059
10205
18006
11439
10374
13298
18035
7978
14579
1877
1995
9957
8133
11070
9851
7398
6476
8191
9167
9355
4719
9752
9485
907
4383
6793
5141
9101
12847
8423
5986
8956
12432
19089
8786
3389
12293
11345
20016
12716
11532
14783
20048
886S
16206
2087
2000
11243
9184
12500
11123
•354
7313
9250
10351
10563
5329
11011
10711
1025
4949
7671
5805
10277
14507
9511
6759
10113
14038
21555
9921
3827
13881
1241C
.3iwU2
14359
J.3022
•6692
22638
10015
18300
2357
-------
GRI
CTN
TTN
CO
AMH
CHK
1966
Table B.9
ANNUAL KEFUSE TONNAGE BY CENSUS TRACTS
ERIE COUNTY OUTSIOF BUFFALO
197C
1975
1980
1985
1990
1995
2000
73A
738
7*
75
76
77
78
79A
79B
80A
SOB
81A
81B
82A
82B
83
84
85
86
87
88
89
90
91A
918
91C
910
92
93A
938
94A
948
95A
958
96
97
98
99
100A
1008
2202
3797
622
1006
2527
1362
3981
9714
«5<54
4508
7362
3788
2942
1829
262C
2345
2078
16G2
2919
3248
2446
1314
1524
942
1020
4756
1943
2323
366C
2053
1773
2781
1436
4461
2007
4317
894
2555
238C
5165
2618
4549
674
1092
2742
3648
412C
10715
6182
4982
8116
41 86
3?51
2021
2895
2592
2296
177C
3226
1589
2703
4034
4290
1146
1242
5789
2365
2827
4455
2499
4593
1385
4183
5429
2443
5227
1083
1004
288?
6496
3496
6027
762
1233
3096
4120
487R
12275
7069
5697
9101
4787
3718
2311
1311
2964
2626
2025
3689
4104
3091
5155
5481
1465
1587
7357
?022
3611
5693
3193
5869
4326
5344
6918
3122
6512
1349
3855
3590
8092
4760
8207
860
1391
3494
4649
. 5505
14020
8074
6507
10626
5467
4246
2640
3782
3385
2999
2312
4213
4688
3530
6631
7051
1884
2042
9514
3887
4647
7322
4107
7549
5564
6875
8924
4C16
7894
163ft
4671
435?
9810
6108
10531
949
1536
3858
5133
6078
15480
8915
7184
11732
6036
4688
2914
4175
3737
3312
2553
4652
5175
3897
8419
8952
219?
2591
12080
4935
5901
9297
5215
9585
7C65
8729
11331
5100
9027
1870
5144
4977
11213
7214
12438
1048
1*96
4?60
5668
6711
17091
9843
7932
12951
6664
5176
3218
4610
4126
1656
2819
5136
5714
4103
9902
10528
2814
1049
14208
5804
6940
10915
6134
11273
8309
10266
11326
5998
10104
?. 094
5981
5S71
12557
8311
14329
1157
1873
4703
6258
7409
18869
10867
8757
14301
7358
5715
3553
5090
4556
4037
3112
5671
6309
4751
11453
12178
3255
1527
16433
6714
8027
1264R
7095
13039
9611
11874
15414
6917
11308
2343
6694
6234
1405?
9559
16480
1278
2068
5193
69C9
8181
70833
11998
9669
15789
8124
6310
3922
5620
5030
4457
3436
6261
6966
5246
13138
13969
3733
4046
18851
7701
9208
14508
8138
14957
11075
13621
17681
7958
12568
2604
7440
6929
15619
-------
Table B.9 (Cont.)
ANNUAL REFUSF TCNNAGE BY r.fNSUS TKACTS
EH IF COUNTY OUTSinE BUFFAin (CONT.I
WSN
03
10
LKA
HAM
OPK
AUR
101A
1018
102
103
104
105
106
107
108
109
110
III
112
113
114
115
116
117
118
119
120A
1?OB
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
1966
636C
2883
4384
874
1481
1529
183C
2174
3260
370C
1293
1714
1904
?439
1546
917
1203
2333
1703
2751
3140
3059
932
2207
2061
1688
3918
1092
99
1446
2766
1596
4505
305E
1486
2140
3426
1962
4611
539?
197C
7701
3491
5309
1058
1793
1851
2216
2632
3948
44flC
1566
2076
2279
2921
1851
1098
1441
2793
2039
3294
3759
3663
1019
2412
2253
1845
4283
1194
108
1759
3364
1942
5479
3719
1807
2603
4255
2437
5726
6266
1975
1985
1990
1995
2000
9593
4349
6613
1 318
2234
2306
2760
3279
4918
5581
1951
2586
3146
4031
2555
1515
1989
3855
2814
4546
5188
5C55
1157
2728
2547
2037
4843
1350
122
2330
4457
2573
7259
492B
2394
3449
57?9
3281
7710
807?
11630
5272
8018
1598
2708
2796
3347
3975
5962
6766
2365
3136
4515
5736
3667
2175
2855
5533
4039
6525
7446
7256
1307
3091
2888
2366
5491
1531
138
3109
5947
3432
9684
6574
3194
4601
7844
4492
10556
10440
13299
6029
9168
1829
3097
3197
3827
4546
6818
7737
2704
3586
5369
6879
4360
2587
3394
6579
4803
7758
8854
P627
1480
3504
3271
2681
6221
1735
157
3977
7607
4391
12388
8410
4C86
5886
9778
5599
13159
12932
14986
6748
10262
?046
3467
3579
4284
5088
7631
8660
3027
4013
6139
7867
4986
2958
3882
7523
5492
8871
10124
9865
1671
3955
3694
3026
7022
1958
177
4704
8999
5194
14655
9949
4834
6962
11721
6712
15774
1614C
16659
7552
11484
2289
3880
4005
4794
5694
8540
9692
3387
4492
6934
8R85
5632
3341
4384
8497
6203
10020
11435
11143
1874
4435
4142
3393
7874
2196
199
5483
10488
6053
17079
11594
5633
8114
13622
7801
18332
18848
18516
8394
12765
2545
4312
4452
5328
M29
9492
10772
3765
4992
7742
9920
62B8
3730
4895
9487
6925
11187
12767
12441
2101
4972
4644
3804
8828
2461
223
6276
12006
6930
19551
13273
6449
9289
15791
9043
21252
21 188
-------
00
w
Table B.9 (Cont.)
ANNUAl REFUSE TONNAGE BY CENSUS TRACTS
FRIE COUNTY 1UTSTDF BUFFALO CCCNT.)
1970
1975
1980
1985
1990
1995
20CO
ELM
LAN
CLA
NEW
ALO
HCL
WAR
ML
CDN
SAR
BCS
EON
FVS
BRA
NCL
CCN
CCL
INO
139
140
141A
1418
142A
142B
143
144
145
1464
146B
147
148
149
150
150
150
151
151
152
153
154
155
156
157
158
159
160
161
162
2277
2830
2158
2541
1387
?124
4473
1688
4326
2021
1450
7728
2799
3699
1099
1299
1099
999
999
2599
2499
4317
5982
1349
1199
1267
1732
1520
1379
399
2646
3289
2564
3018
4154
2605
54S5
45??
5305
2380
1708
3213
3449
4452
1333
1469
1353
1237
line
3364
2929
4990
6915
1731
1444
1532
2095
1779
1614
459
3409
4237
3519
4165
5476
3434
7211
5962
6991
3126
2242
4219
4352
5617
2012
1839
1942
1776
1407
4804
3678
6296
8726
2210
1843
19?4
2611
2149
1950
457
44C9
5480
4845
57C2
7255
4553
95 « I
7899
9266
392?
2814
5293
5405
7216
2709
2388
2471
?26?
1727
6562
4686
8255
11440
2814
234*
2451
3352
?6PC
2430
373
546?
6788
6039
7108
8R45
5547
11680
9630
11296
4850
3479
6545
6565
9016
3410
2901
3034
2775
2161
8030
5911
10554
14625
3417
2894
3015
4124
3353
3041
330
6817
8473
7239
8521
10871
6817
14356
11836
13883
5832
4184
7872
7907
10900
4096
3494
3618
3309
2526
9732
7018
12446
17249
4116
3434
3642
4981
4138
3753
296
7960
9894
8413
9903
12816
8037
16925
13954
16367
6862
4923
9261
9296
12800
4887
4179
4217
3857
2944
11555
8289
14619
20259
4923
4002
4304
5886
4980
4518
276
8949
11123
9754
11480
14711
9226
19428
16017
1878R
7926
5686
10697
10709
14593
5637
4881
4901
4483
3421
13408
9616
16786
23263
5749
4651
5029
6878
5840
5297
277
-------
Jable B.10
ANNUAL TONS~hF REFUSE PER CAPITA
CENSUS TRACTS IN FR IF COUNTY OUTSIDE BUFFALO
19*6
Co
i
<**
GR ISLNO
CV TWNDA
TN TWNDA
AWHERST
CHKTUAGA
M SENECA
LKAWANNA
HAMBURG
ORCHD PK
AURORA
EL HA
LANCSTER
CLARENCE
NEWSTEAD
ALOEN
HOLLAND
PARILLA
MALES
CCLDEN
SARDINIA
BOSTON
EOEN
EVANS
BPANT
N COLLNS
CONCORD
COLLINS
I NO RESV
0.5?1
0.524
0.483
0.505
0.465
0.484
0.418
0.382
0.560
0.752
0.516
0.6C9
0.365
0.455
0.392
0.411
0.453
0.417
0 . 38 1
0.436
0.414
0.338
0.786
0.533
C.297
0.419
0.369
0.283
1970
0.575
C.567
0.523
0.547
0.504
C.452
0.414
0.606
0.814
0.558
C.659
0.395
0.493
0.424
0.445
0.490
0.451
0.413
0.472
C.449
0.366
0.850
0.577
0.321
0.453
0.399
0.307
1975
3.635
0. 626
0.577
0.604
0.556
0.578
0.499
0.457
0.669
0.898
0.616
0.727
0.436
0.544
0.468
0.491
0.541
0.498
0.455
0.521
0.495
0.404
0.939
0.637
0.354
0.501
0.441
0.339
198C
0.701
0.691
C.637
0.667
C.614
0.638
0.551
0.504
0.738
0.99?
0.681
0.803
0.481
0.601
C.517
C.542
C.597
0.550
0.503
0.576
0.547
0.446
1.037
0.704
0.391
0.553
0.487
0.374
1985
1990
1995
0.774
0.763
0.704
0.736
0.678
0.705
0.609
0.557
0.815
1.095
0.751
0.887
0.531
0.663
0.571
0.598
0.659
0.607
0.555
0.636
0.604
0.493
1.145
0.777
0.432
0.610
0.537
0.413
0.854
0.843
0.777
0.813
0.748
0.778
0.672
0.614
0.900
1.209
O."30
0.979
0.587
0.732
0.630
0.661
0.728
0.670
0.613
0.702
0.667
0.544
1.264
0.858
0.477
0.674
0.593
0.456
0.943
0.931
0.858
0.897
0.826
0.859
0.742
0.678
0.994
1.335
0.916
1.041
0.648
0.808
0.696
0.729
0.804
0.740
0.677
0.775
0.736
0.601
1.395
0.947
0.527
0.744
0.655
0.50)
2000
1.042
1.027
0.947
0.991
0.912
0.949
0.819
0.749
I.C97
1.474
1.011
1.193
0.715
0.892
0.768
0.805
0.887
0.817
0.747
C.855
0.813
0.663
1.540
1.045
0.581
0.821
0.723
0.555
-------
Table B.ll
ANNUAL TCNS OF REFUSE PER
CENSUS TRACTS IN ERIE COUNTY
oo
w
in
6RI
CTN
TTN
AMH
CHK
73 A
738
74
75
76
77
78
79A
798
80A
SOB
81A
818
82A
828
83
84
85
86
87
88
89
90
91A
918
91C
910
92
93A
93B
94A
948
95A
958
96
97
98
99
100A
1008
1966
130
207
863
4373
3771
4872
2864
2556
3857
4135
4974
2936
3922
1662
4366
613
449
5006
6634
10150
7643
2761
186
113
290
797
899
932
9891
2598
3144
1931
2887
2770
2*52
667
365C
862
2900
1970
156
248
936
4747
4092
5286
3107
2825
4263
4570
5497
3244
4334
1837
4825
678
496
5531
7331
11215
8446
3361
226
138
353
971
1094
1135
12040
3163
3827
2350
3515
3372
555
2969
808
4420
1044
3511
1975
206
329
1058
5360
4620
5971
3509
3230
4875
5226
6285
3710
4957
2100
5518
775
568
6328
8384
12825
9659
4295
290
177
452
1241
1399
1451
15386
4041
4890
3004
44QO
430Q
709
3700
1006
5507
1300
1980
281
448
1194
6047
5214
6737
3960
3689
5568
5969
7179
4237
5661
2400
6303
886
649
7225
9575
14650
11031
5525
373
227
581
1596
1799
1866
19789
5198
6290
3863
5777
5542
912
4485
1220
6675
1576
530?
SQUARE HUE
OUTSIDE BUFFALO
1985
361
575
1318
6678
5758
7439
4372
4073
6148
6590
7927
4679
6250
2649
6958
978
716
7978
10572
16171
12178
7015
473
289
738
2026
2284
?369
25127
6601
7987
4906
7335
7037
1159
5128
1395
7634
1803
6063
1990
1995
426
679
1455
7373
6358
8214
4828
4497
6788
7277
8752
5,165
6,901
2925
7V683
1080
791
8809
11672
17856
13446
8251
557
340
868
2383
2687
7787
29554
7764
9394
5770
86*6
8277
1363
574(0
1562
8544
2018
6787
491
783
1606
8143
7019
9069
5330
4965
7494
8033
9662
5703
7620
3230
8483
1192
873
9725
12888
19715
14846
9544
644
393
1004
2757
3108
3223
34183
8981
10865
6674
9978
9573
1576
6425
1748
9562
2258
7595
2000
565
90 C
1775
8991
775C
10013
5885
5482
8274
8870
10668
6297
8413
3565
9366
1316
964
10737
14229
21768
16393
10948
739
451
1152
3162
3565
3697
3921C
10301
12464
7656
11446
10981
180R
7140
1943
10628
251G
8442
-------
Table B.I1 (Cont.)
ANNUAL TONS OF REFUSE PER SQUARE MILE
CFNSUS TRACTS IN ERIE CCUNTY OUTSIDE BUFFALO
(CONT.I
101 A
101B
102
103
105
106
107
106
109
110
111
MSN 112
113
115
116
117
118
119
120A
12 OB
LKA 121
122
123
124
125
126
127
HAM 128
129
130
131
132
133
134
CPK 135
136
137
AUK 138
1966
4211
3352
2722
2241
9256
2591
3893
997
416
1175
3315
4080
399
995
4987
996
1625
1822
1127
745
1171
971
2118
1109
4206
2813
2720
1020
2475
1624
467
331
501
156
2653
1517
138
1532
360
157
1970
5100
4059
3297
2712
11206
3137
4714
1207
504
1665
4015
4942
477
1192
5970
1193
1947
2182
1350
892
1402
1162
2315
1212
4597
3075
2974
1115
2700
1976
568
402
609
189
3226
1846
172
1903
447
183
1975
6352
5056
4107
3379
13962
390R
5872
1504
628
2074
5002
6157
659
1645
8241
1646
2687
3011
1863
1231
1935
1604
2618
1370
5197
3478
1363
1261
3050
2617
752
533
807
251
4275
2446
231
2563
602
236
1980
7701
6130
4980
4097
16925
4738
7121
1823
762
2515
6064
7466
946
2361
11829
2364
3858
4322
2674
1768
2778
2303
2970
1554
5893
3943
3813
1430
3450
3493
1004
712
1077
335
5703
3263
317
3509
824
3C5
1985
9807
7010
5694
4687
19356
5418
8142
2085
871
2876
6933
8538
1125
2807
14064
2811
4586
5139
3180
2102
3303
2738
3363
1760
6679
4468
4320
1621
3925
4468
1284,
910
1377
429
7296
4174
395
4374
1024
378
1990
9858
7846
6373
5246
21668
6066
9114
2333
975
3219
7761
9554
1287
3211
16083
3215
5245
5877
3637
2404
3777
3131
3797
1987
7538
5043
4876
1829
4425
5285
1520
1077
163C
507
8632
4937
474
5243
1232
471
1995
11032
8781
7132
5869
24250
6788
10200
2611
1092
3602
8684
10695
1453
3626
18167
3631
5924
6638
4107
2715
4266
3537
4259
22?8
8453
5655
5468
2052
4975
1771
1255
1899
591
10058
5754
551
6094
1432
551
2000
12262
9760
7928
6525
2A950
7545
11336
2903
1213
4004
9653
11885
1623
4048
20283
4054
6614
7411
4986
3031
4763
3949
4775
2498
9477
6340
613C
2300
5575
7051
2028
1437
2174
677
11916
6987
639
7064
166C
619
-------
Table B.ll (Cont.)
ANNUAL TONS OF REFUSE PER SQUARE *ILF
CENSUS TRACTS IN FRIF COUNTY C1UTSIOE BUFFAIO
JCUNT
139
ELM 141A
141B
LAN 142A
142«
DO
I
Ol
145
CLA 146A
1468
147
MEM 148
ALD 149
MOL 190
MAM 150
MAL 150
CON 151
SAR 151
DOS 152
EON 153
fVS 154
155
BRA 156
NCL 157
CON 156
159
COL 160
161
IND 162
1966
19S7
1979
115
159
154
155
3696
2426
2544
462
129
7C
54
106
30
47
30
27
19
72
62
219
269
52
27
18
503
32
1288
29
1970
2321
2300
137
189
189
190
4533
2975
3120
568
152
83
67
128
37
53
37
14
23
94
73
253
311
66
13
22
609
38
1508
33
1975
2990
2962
IR9
261
250
250
597ft
3922
4113
746
200
109
85
162
55
66
53
49
27
134
92
319
393
86
4?
28
764
46
1822
33
198C
3867
3832
25*5
358
331
332
7918
5196
5450
936
251
137
105
209
75
86
68
62
33
183
117
419
515
1C8
54
36
974
57
2271
27
1985
4791
4746
3?2
447
4C3
404
9652
6335
6644
1157
310
170
128
260
94
105
84
77
42
224
148
535
658
131
66
45
1198
71
2842
?4
1990
5979
5925
387
535
496
497
11864
7786
8166
1391
373
204
154
315
113
127
100
91
49
272
175
631
776
158
79
54
1447
88
15C7
21
1995
6982
6918
449
622
585
586
13987
9180
9627
1637
439
240
181
369
135
151
117
107
57
323
207
742
912
92
64
1711
106
4222
20
200C
7850
7778
521
722
671
673
16056
10537
11051
1891
507
277
209
421
156
177
136
124
67
375
241
852
1047
221
107
75
1999
125
4950
2C
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PAGE NOT
AVAILABLE
DIGITALLY
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iPPENDIX C BUFFALO SMSA SOLID WASTE SYSTEMS
C.1 Overview of Current Solid Waste Handling Operations
The main characterizations of the solid waste systems and practices
rithin the Buffalo SMSA are independence of operation and minimal coordination
aong the municipalities and with the private disposal services. Operating
aider the principal of home rule, each city, town and to some degree, village,
iithin the two Counties has examined its solid waste handling problems and
leveloped its own course of action. The spectrum of selected courses of actior
range from total municipally-owned and operated collection, processing and
disposal functions to municipalities which provide only an open dump. In those
instances where the municipality owns and operates the solid waste handling
system, the services provided are restricted to residences and to small commercial
establishments. Even within the former category, the types and/or amounts
of solid waste collected per residence per pick-up is restricted. There are
w instances within the Buffalo SMSA of a municipally operated solid waste
system which provides all the handling services to all the sources of solid
naste generation within its jurisdiction. In general, the forms of solid
laste handling within the two Counties can be outlined as
• Municipally-owned and operated collection, processing and
disposal with supplementation by private collection and
disposal services.
• Municipally-contracted solid waste collection and disposal for
residential and light commercial generation of refuse; large
commercial and industrial sources privately contracted for
solid waste handling services.
• Individually-contracted solid waste collection and disposal with
private operators.
C-l
-------
• Municipally-operated dump with generation sources
transporting their own refuse.
• Privately-operated dump with generation sources transporting
their own refuse.
An examination made of the refuse disposal services provided in Erie
County revealed that only in the more densely populated portions of the County
and a number of villages outside these areas are services provided on an
"organized basis". Included in this category of service are the three cities
of the County — Buffalo, Lackawanna and Tonawanda; the towns of Aurora,
Cheektowaga, Lackawanna and Tonawanda; and the villages of Alden, Angola,
Blasdell, Depew, Farnham, Gowanda, Hamburg, Kenmore, Lancaster, North Collins,
Sloan, Springville and Williamsville (see Fig. C.I). It was further established
that the towns of Amherst, Hamburg and Lancaster, plus the villages of Akron
and Orchard Park were areas currently in need of organized refuse disposal.
By the year 2000 with the projected population increases, other towns within
the County must provide solutions for their refuse disposal needs. This
examination of needs utilized population density* as the primary measure for
establishing the adequacy of refuse disposal services.
Within Niagara County the three cities of Lockport, Niagara Falls and
North Tonawanda provide refuse disposal services for all residential and
a limited number of small commercial establishments. With respect to the
remainder of the County, a substantial portion of the village and township
residences and commercial establishments are served by private refuse haulers
either by direct contract with the individuals served or by contract with the
village or township.
* A rule-of-thumb given in Ref. 36 was interpreted as follows. A government
controlled refuse disposal source is desirable when the population density
exceeds 1000 persons per square mile. For densities between 500 and 1000
persons per square mile, an organized service should be planned under the
conditions of concentrations of one family per acre being-prevalent to a
considerable degree. For densities below 500 persons per square mile, an
organized service is not considered necessary.
C-2
-------
ONTARIO CANADA
HOLLAND
BRANT
HbRTh
J£5>LLINS
NORTH COLLINS
r
i
i
i
i
_i_
1 z
1
t
-1 ^
£,
o
1 >
WAUQUA COUNTY
L Js
CATTARAUGUS COUNTY
SOURCE: DAY & ZIMMERMAMH, INC. (REF. 2t, P.16) ^
Figure C.I ORGANIZED REFUSE DISPOSAL BY MUNICIPALITIES
C-3
KEY
AREAS CURRENTLY SERVED 8Y
ORGANIZED REFUSE DISPOSAL
AREAS CURRENTLY IN NEED OF
ORGANIZED REFUSE DISPOSAL
AREAS EXPECTED TO NEED ORGAN-
IZED REFUSE DISPOSAL SERVICE
IN 1980
AREAS EXPECTED TO NEED ORGAN-
I IZED REFUSE DISPOSAL SERVICE
IN 20OO
-------
C.2 Current Solid Waste Handling Practices
A description and synthesis of solid waste handling should begin with
the collection function and then proceed to the subsequent stage of the system;
be it processing or disposal. From the viewpoint of the recipient of the
solid waste handling service the collection function is of greatest interest
and concern for several significant reasons. Of primary importance, the
generator of solid waste has the responsibility of storing the refuse from the
time of generation until it is collected and transported from his location.
During this storage period, and depending on the environmental factors, (e.g.
temperature, precipitation) and storage facilities, he may be subjected to
such effects or concerns as unsightliness, odors, flies, vermin, dust, etc.,
all of which may be very objectionable. Secondly, from a direct monetary
viewpoint, the cost of the collection function relative to the total cost
of solid waste handling ranges from between two-thirds and three-quarters
of the total cost. For example, in Ref. 2 it is noted that the collection
cost per ton is approximately $10 as compared to a total refuse handling cost
of $14.75 per ton. On the assumption that the per capita solid waste generation
rate is 4.5 Ibs. per day at present and the family unit consists of four persons,
it is not unreasonable to assign a cost of roughly $30 per annum to the family
unit for the collection function alone. In essence these two factors, storage
and associated effects, and cost, are the recipients' main concern and interest
in the solid waste problem.
Within the Buffalo SMSA, and as evidenced by the planning studies
performed for each County, the planning organizations have concluded that
the bases for regional!zation would be the processing and/or disposal functions,
and that the collection function would be performed on a local option basis.
It should not be inferred that these planners are unaware of the concerns and
interests of the generators of solid waste. Rather, it has been decided that
because of the (1) current poor disposal practices; (2) scarcity of available
land; (3) air pollution and water pollution resultants of solid waste handling;
(4) fund limitations of small municipalities and; (5) economies of scale
C-4
-------
operienced through cooperation and regional!zation, the disposal function
should be given the highest priority and secondly the processing functions.
In keeping with this priority ordering, which it should be added appears to
ke in general agreement with other regional approaches to solid waste handling,
the descriptions of Erie and Niagara Counties' current solid waste handling
jrtctices are organized into the two main functional categories - disposal
Bid processing.
C.2.1 Erie County - Inventory of Disposal Sites and Processing
Plants
C.2.1.1 Erie County Disposal Sites
The following description of the Erie County disposal sites is a
siMwry of the information provided in the Day and Ziiranermann refuse
disposal report for Erie County (Ref.24 ).
A total of 31 operating disposal sites (landfills) are located in Erie
iwnty of which four are situated within the City of Buffalo. Of the 31 landfills,
aly two were found to meet all the requirements of acceptability set forth
in the New York State Sanitary Code Part 19 - Refuse Disposal. Seven of the
lites were considered acceptable except for minor regulation infractions.
if the remaining 22 disposal sites, 12 indicate evidence of attempts being
«de to be operated as sanitary landfills and the remaining ten were generally
prated as open dumps. This last group was found to have inadequate land
(lack of control of insects, rodents and fires. Fig. C. 2 depicts the location
if existing refuse disposal sites and the numbers to the upper right of the
ircles indicate the results of an evaluation of the land fills. The number 1
iijnifies a landfill fulfilling the requirements of the State Sanitary Code;
8the condition of the operation of the landfill deteriorates, the associated
*Uth rating number increases. The number 4 specifies an open dump; that is,
Jen uncontrolled dumping and burning.
C-S
-------
ONTARIO
CHAUTAUOUA COUNTY
KEY
LANDFILL SITE
INCINERATOR
1 TRUCK
JTRANSFER
CATTARAUGUS COUNTY
SOURCE: DAY AND ZIMMERMAN*, INC. (REF. 24, P.48)
I INCWMATM A CMMHTtD
TO 7KUCK TMMWt STAT1OM
IN ItCT.
MHOR NUMm INMDI ItWKX
mi MTCRCMCE IN TEXT.
S. WKMCIItPT NUMEM REFtD
TO PMLIC NEALTM EVMLIMTMN
Figure C.2 LOCATION OF EXISTING REFUSE DISPOSAL SITES IN ERIE COUNTY
C-6
-------
The landfills, described in Table C.I , represent a spectrum of
mership and operation. As shown in the table, ownership is both public
tity, town and village) and private with no strong relationship discernible
ttween types of ownership and quality of operation. However it can be seen
kat the town operated disposal sites are rated (on the average) between 3
id 4, the city operated sites are rated between 2 and 3, and the privately-
prated sites are rated between 2 and 3.
Within the above survey, it was found that there is a significant
ifference in the operating costs of large versus small disposal sites.
ami nation of the operating cost information reveals that the costs associated
ith small disposal sites (25,000 cu. yards per year or less) would be of the order
ISO cents to over $1.00 per cubic yard, whereas the larger operation disposal
ites have operating costs in the order of 30$ per cubic yard. In part it
ithe high unit operating cost of small disposal sites that causes these site
praters to seek money-saving shortcuts which result in poor operations and
leir poor public health rating.
A tabulation of the space currently available on the disposal sites
isted in Table C.I reveals that there is approximately 20 million cubic yards
[available capacity. Using a refuse compactability ratio of approximately
•1:1, the current landfills are capable of receiving approximately 50 million
iic yards of refuse as collected. Based on an estimated landfill capacity
ipirement per year of three million cubic yards, the total landfill capacity
(the present disposal sites would be completely exhausted in 17 years. Since
is estimate does not take into account the availability of specific disposal
ites to the various sources of solid waste generation in terms of distance
(the willingness of municipalities to share the available capacity, the
'-year estimate is a very optimistic. In fact, the situation confronting many
•unities at present is quite critical.
C.2.1.2 Erie County Processing Plants
In Erie County the processing of solid waste is performed primarily
C-7
-------
Table C.I ERIE COUNTY DISPOSAL SITES
Remaining Life
(years) Rating
BHC.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
name
City of Lackawanna
City of Tonawanda
Town of Anherst
Town of Brant
Town of Cheektowaga
NYS Highway Dept.
Pfohl Bros
Joe Ball
Town of Collins
Collins Center
Eden Sanitation
Service
Town of Elma
Town of Evans
Fox and Vassals
Ed Ball
Lancaster Sanitary
Landfill Inc.
Tankesley
Town of Newstead
M^^«»« A^**»
Lackawanna
Tonawanda
Anherst
Brant
Cheektowaga
Cheektowaga
Cheektowaga
Colden
Collins
Collins
Eden
Elma
Evans
Evans
Evans
Lancaster
Marilla
Newstead
City
City
Town
Town
Town
NYS
Private
Private
Town
Town
Private
Town
Town
Private
Private
Private
Private
Town
Town of North Collins North Collins Town
Butenkinst Site
Hugh Smith Landfill
Town of Tonawanda
Seaway Industrial
Development Corp.
Town of Wales
Town of W. Seneca
Village of Depew
Village of Gowanda
Squaw Island
LaSalle Quarry
South Park
Tifft Street
Orchard Park
Sardinia
Tonawanda
Tonawanda
Wales
W. Seneca
Depew
Gowanda
Buffalo
Buffalo
Buffalo
Buffalo
Private
Private
Town
Private
Town
Town
Village
Village
City
City
City
Private
20
40
2
40
1
7
1
?
40
7
15
?
7
1
7
9
40
?
40
40
25
2
15
7
?
2
[long life]
35
1-3
7
[very long
life]
2
2
3
4
3
4
2
4
4
4
2
3
4
3
3
2
3
4
3
4
3
3
1
4
4
3
1
3
3
2
2
C-8
-------
by incineration. Currently there are six municipal incinerators which serve
the cities of Buffalo (two facilities), Lackawanna and Tonawanda, the towns of
Tonawanda and Cheektowaga. With the exception of Buffalo's East Side Incinerator
all the furnaces within these six facilities have been installed since 1945
with the most recent one being installed in 1959.
All the incinerators in Erie County are natural draft plants and
thus it would be impossible to introduce air pollution control devices to the
furnace outlets without installing induced draft fans to overcome the
pressure drop. At preset none of the facilities has air pollution control
devices adequate to meet the current County Health Department standards.
Extensive modifications are well underway at the Buffalo West Side Plant
including air pollution control devices which it is claimed will permit this
facility to operate within the County's air pollution standards.
A summary of the incinerator operations is included in Table C.2 .
This table includes some of the pertinent furnace design information, the
operating data and appropriate cost data associated with each facility. Also
included in this table is the information on the West Seneca facility which was
initially operated as an incinerator and since early in 1968 has begun
operations as a truck transfer station. It should be noted that the one-way
disposal haul distance from the West Seneca transfer station to the Disposal
Site (Site #16 - Lancaster Sanitary Landfill) is approximately 15 miles.
C.2.2 Niagara County - Inventory of Disposal Sites and Processing
Plants
C.2.2.1 Niagara County Disposal Sites
The disposal sites in Niagara County can be broadly categorized
as publically-owned and lease-operated sanitary landfills, open burning dumps,
modified sanitary landfills, and burning dumps and landfills, and industrially
owned and operated landfills. The Cities of Niagara Falls, North Tonawanda
and Lockport, and the towns of Hartland, Lewiston, Lockport, Newfane, Niagara,
Royalton, Wheatfield and Wilson operate on-lease disposal sites.
C-9
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PAGE NOT
AVAILABLE
DIGITALLY
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Table c.3 summarizes disposal site information which is derived
from A. Michael's Refuse Disposal Report (Ref. 22 ). Included in the table are
the name of the political subdivision, the type of disposal site being operated
and additional remarks such as expected life of the site, specific pollution
problems, etc.
The map of Niagara County (Fig. C-3) provides a reference of
the spatial relationships among the towns and cities. The locations of the
disposal sites have not been shown since they have not been included within
the analyses described in Section 4 of this report.
C.2.2.2 Niagara County Processing Plants
The Cities of Niagara Falls and North Tonawanda both operate incin-
erators for the processing of residential and light commercial refuse. In
1965, Niagara Falls incinerated approximately 44,400 tons of refuse out of
a total amount of 46,000 tons or 96 percent. The City of North Tonawanda
disposed of approximately 8000 tons of refuse at its incinerator out of a total
surveyed quantity of 20,500 tons, or 39 percent. The amount of incinerated
solid waste included some industrial material which was hauled to the plant
by private industry.
One note of interest is the comparison of the costs per ton of
processing for each incinerator. The Niagara Falls incinerator processed
44,400 tons in 1965 and the average cost per ton was $5.35. The North Tonawanda
incinerator, operating at one shift per day, processed 8000 tons in 1965 and
the average cost per ton was $8.00. Whereas the cost experience of Niagara Falls
Has comparable to incinerator experiences in the Northeastern part of the U.S.,
the higher cost per ton of the North Tonawanda incinerator is a strong indication
of the cost inefficiency associated with very small scale operations.
C-ll
-------
Table C.3 NIAGARA COUNTY DISPOSAL SITES
(as of June 1966)
Name
Type Operation
Remarks
Cities
Niagara Falls
North Tonawanda
Lockport
Towns
Hartland
Lewiston
Lockport
Newfane
Niagara
Royalton
WheatfieId
Wilson
Modified landfill
Open burning dump
Sanitary landfill
Sanitary landfill § open
burning dump
Modified landfill
Open burning dump
Modified sanitary
landfill
Sanitary landfill and
open burning dump
Open burning dump
Modified landfills
Supposed to operate as
sanitary landfill
Cut and cover land fill
operation
Disposal of incinerator residue
Virtually filled - being
replaced by site with life of
2-5 years
Considerable amount of smoke
and fly ash
< 1 year of fill life
30 year fill life
Insect and rodent nuisance
exists - potential fire
hazard
Attractive to insects and
rodents; causes air
pollution, and is fire hazard
Hells in area contaminated
by operation
Numerous rat harborages
Minimal available space
2 sites - Bancroft site has
long history of nuisance
violations
Complaints of rats and
rubbish fires
Well operated
C-12
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Ul
Tuscarora
Reservation
Tonawanda
Reservation
Figure C.3 MAP OF NIAGARA COUNTY
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C.3 Comments on Current Solid Waste Handling Practices and Facilities
A general appraisal, of current solid waste handling practices and
facilities in Erie and Niagara Counties leads to the conclusion that
•
much is required to be done to improve the services to the producers of solid
waste, and that the level of operation of facilities require drastic upgrading.
The residential sources of refuse, which are serviced by municipally-
operated systems, are provided limited service in terms of the types and quantities
of refuse which is collected. The large commercial and industrial producers
of solid waste must utilize privately-operated systems which, outside of requiring
licenses from the area they service, are not included in any regional planning.
Outside of the Erie County Refuse Agency which is primarily an advisory group,
and the recently established Niagara County Refuse District., there are no
evidences of cooperation and joint planning. Thus, as is indicated earlier,
only certain portions of Erie County are covered by organized refuse handling
services; this lack of service is more prevalent in Niagara County.
In summarizing the status and operations of disposal sites and
processing plants two aspects were prominent. First, on an over-all basis,
the majority of these facilities are being operated in a manner which is either
aesthetically unsatisfactory, or in need of major improvement to meet health
requirements, or both. None of the incinerators in Erie County is currently
able to meet the minimum air pollution standards. Many of the landfills are
open dumps, with some burning, which serve as breeding areas for insects,
and vermin, and as sources of air and water pollution. Second, in view of
the small size of many of the landfills, several of the incinerators and the
transfer station, the cost per ton of refuse is either higher than that found
in the Northeastern part of U.S. or the level of service provided per dollar
is lower.
It is quite evident that there is a need for consolidation of solid
waste handling services, thereby allowing for greater economies of scale to
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be realized and to allow for the selection of alternative approaches from
a greater spectrum of options which would normally be available to the individual
political subdivisions. With respect to the economy of scale factor, an increase
of the landfill operation from 100 tons a day to 500 tons a day of refuse
handled could result in a cost reduction of approximately one-half, for a similar
level of service. As an example of an expanded option spectrum, unless the
quantity of refuse handled by a rail transfer station is of the order of 500
tons, it would not prove to be an economic alternative to consider seriously.
Finally, in examining the current disposal site patterns and practices
it is clear that an impending shortage of available, accessible land for refuse
disposal is being experienced and will develop into a major problem. One
contributing factor is the lack of recognition and planning between the private
and publically-owned and operated refuse disposal systems. To a large extent
they are competing for this scarce resource —land— and only through a coopera-
tive effort can this scarce commodity be utilized more efficiently -- to the
benefit of the producers of solid waste and to the operators of the solid
waste systems.
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APPENDIX D TECHNOLOGICAL AND MANAGEMENT OPTIONS FOR BUFFALO SMSA
SOLID WASTE HANDLING
D.I Statement of Developing Problems and Associated Solid Waste Handling
Requirements
Prior to the discussion of. developing problems and the types of
requirements which may solve or alleviate these problems it should be mentioned
that one of the major difficulties, if not the major one, is defining
problems in the absence of a clear, concise statement concerning the objective(s)
of solid waste management. Is the objective to move refuse from a generation
source where the presence of refuse is objectionable to some other location;
to eliminate the health hazards associated with refuse; to collect and dispose
of refuse at minimum cost; to maximize the utilization of all resources
associated with solid waste handling; to ; to ; etc. The highlighting
of this deficiency or problem is not done for the purpose of beclouding the
real-world planning and operating solid waste problems but rather to suggest
that unless the objectives of solid waste handling are specified it is difficult
to perform management decision-making. To reiterate a concept included in
Section 2, the objective(s) selected must be related to the level at which the
problem is being examined. That is, utilizing solid waste handling objectives
which have been selected at the National-level would, in most instances, be
highly irrelevant at the local (village, town) levels. Thus, any attempt at
precise problem definitions and system requirements must be coupled to the
objectives of the system -- what explicitly is desired to be accomplished?
The growing interest in solid waste handling within the Buffalo SMSA
is the recognition that the methods and techniques being employed cannot or
should not be maintained at the current levels of performance in order to meet the
projected demands. In some instances these approaches are infeasible (not suffi-
cient available land to all municipalities for continued disposal) and in other
instances there is an appreciation that there are better ways to provide refuse
handling at either the same or reduced cost. Among the most significant factors
nhich are responsible for the developing solid waste handling problems are the
following:
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(a) Shifting population patterns in Region - As described in
Appendix A, the population shifts being experienced are from the urban centers
to the rural areas which are taking on many of the attributes of the suburban
» . . . - •
areas. In most instances the suburban communities which are adjacent to
the urban centers have become stabilized in terms of population and thus, based
on natural birth and death rates, are experiencing a net out-migration. The
impact of this population shift on solid waste is twofold:
(1) The rural communities require an expanded capacity of
current services to meet the needs of their rapidly
growing populations, and
(2) The population moving into these new areas are demanding
a higher level of solid waste handling services than had
previously been afforded to the rural inhabitants.
Additionally, in some instances some of the solid waste
handling practices which had been performed previously are being
objected to by these new inhabitants and in some cases
have been terminated.
If the previous patterns of local solid waste handling are to continue, land
use plans are required which include adequate land reserves for the growing
population and which are compatible with the levels of service that the incoming
population are demanding. On the presumption that a regionalization scheme
will be adopted, planning must be performed to provide an adequate tax base
to finance this increased level of service.
(b) Limited available and accessible land - As the population
relocates from the densely populated urban areas to the suburban and rural
areas of the region, the land utilized per capita increases. The movement of
population has the effects of reducing the available lands available for solid
waste handling purposes in terms of the actual amount of land being directly
utilized by this population and the further requirement for larger buffer
zones between the residential areas and the processing plant or disposal site.
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Kith the growth of suburbanization, around the urban centers of the Buffalo
SMSA, the problem of accessible land to the high quantity generators of solid
waste becomes more acute. In addition to the direct problem of greater
transportation costs is the political jurisdictional factor which exists in the
region composed of autonomous, locally-operated solid waste handling systems.
Municipalities are unwilling to have other municipalities' solid waste
disposed of within their jurisdiction unless there is a direct economic benefit
to them with virtually no deleterious effects. There are instances where, given
the economic gains and the absence of penalties, the local communities are unwilling
to cooperate.
The impact of this limited available and accessible land, whether
actual or jurisdictional, is to reduce the option spectrum available to local
decision makers. On a regional-basis, with the opportunities of large-scale
operations, the problem of land availability is reduced and the determination
of accessible land is modified because of the opportunities to achieve economies
of scale which then enlarges the accessible land region.
(c) Improved 1 eyej^ of operation standards - Over the past five or
»ore years, the New York State Health Department and the County Health Departments
have promoted legislation to both improve the standards of operation of solid
waste handling systems and to increase their abilities to monitor and enforce
conformance to these improved standards of operation. These standards are
related to air pollution, with respect to particulate matter emission, constituent
gases such as sulfur dioxide, oxides of nitrogen, hydrocarbons; vermin and insect
control; ground water contamination; as well as odors and aesthetic consideration.
The enforcement of these more stringent standards has resulted in the
termination of operations at certain facilities. (For example, the shutdown of
the village dump of Akron, New York, which resulted in the elimination of all
village-owned and operated disposal services.) Another impact of these stand-
ards on small communities has been the imposition of higher tax levels to
finance the modification and improvement of the operating standards to existing
facilities. A third effect of these standards is to eliminate certain options
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for solid waste handling previously available to local communities because of
the significant increase in cost required to meet these standards.
In recognition of the implication of these more rigid standards of
operation and the prospects of even greater controls, the local communities
should be making projections of their solid waste handling requirements and
deciding whether the options available to each of them are technically and
economically feasible, and then comparing their most suitable options with those
available to them through a consolidation of refuse handling services on a regional
basis.
D.2 Currently Planned and Considered Technological and Management Options
On a National basis, one current approach to meet the aforementioned
problems is the establishment of solid waste handling districts — a form of
regionalization. In Erie County, after several years of study and deliberation,
a gross plan has been formulated which, although modest in scope, permits an
assessment of cooperative solid waste handling facilities, and meets some of the
current problems of participating municipalities. The plan, based on a
voluntary concept, would establish one or several truck transfer stations and
provide the required transportation capabilities to a county-owned or licensed
landfill site. Because of the preliminary nature of the planning effort and
the lack of specific and binding commitments on the part of individual villages,
towns or cities, the number and locations of the transfer stations have not been
established and the selection of the disposal site has not been made. Therefore,
at this time, it is not possible to describe the details of the plan, to estimate
the cost of implementation (capital and operating costs), and to evaluate the
decisions made. The nature of the plan can be described as a demonstration
project rather than one whose purpose it is to handle the current problems; to
anticipate future difficulties and provide for their orderly solution.
D-4
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D.2.1 The City of Buffalo Activity
Within the Buffalo SMSA, a number of actions are being taken and
are under consideration for alleviating portions of the solid waste handling
problem. Before summarizing some of these actions, it should be stated that
none of them is being formulated and evaluated from a total system point of view
but rather each is being investigated in terms of a specific portion of solid
waste handling. There is no attempt to formulate an optimum solid waste handling
system.
The City of Buffalo's solid waste represents approximately 45 percent
of the total of Erie County and its population is approximately 45 percent
of the County. In view of the fact that its area is only four percent of the
County total, the City is confronted with a solid waste handling crisis. To meet
this crisis, the following actions are being pursued at the present time.
(a) Over the past year and a half, the Buffalo West Side Incinerator
Plant has been undergoing a major rehabilitation and expansion, which should be
conpleted sometime in 1969. As part of the expansion, a continuous feed grate
furnace of 200 tons per day is being installed as well as a bulky-refuse burner
of 60 tons per day. Based on the 1966 daily burning rate of approximately
307 tons per day, the total capacity of the plant will become 567 tons per day;
or an expansion of 85 percent. A significant benefit to be derived from the
bulky-refuse burner is the processing of currently oversized objects which are
disposed of at the landfill with the accompanying penalty in scarce landfill
capacity. A significant aspect of the modernization program is the addition
of air pollution control equipment to the existing and additional furnaces
Aich, it is predicted, would allow the incinerator to perform in conformance with
the new State and County air pollution control regulations.
The second incinerator within the City of Buffalo -- the East Side
Incinerator is approximately 40 years old, in need of major overhaul and
•odernization and not capable of conforming to the current air pollution control
standards. The City of Buffalo is considering a number of options to meet this
D-5
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present deficiency. The alternatives being pursued are (a) a new 600 ton per day
incinerator which can be expanded to 900 tons per day, and possibly to 1200 tons
per day; (b) a 200 ton per day truck transfer station which would be obtained
through the conversion of the existing incineration station; (c) a 400 ton per
day composting plant; and (d) a 200-600 tons per day sanitary land fill operation.,
tach of these alternatives would be put out for competitive bidding so as to derive
a sounder basis for selecting the type of facilities to be selected. Whereas
the expansion of the West Side Incinerator is a project which is well under
way and thus rather well defined, the efforts associated with the East Side
Incinerator, or more specifically the area within the City serviced by this
incinerator, characterize an earlier stage of the planning process.
D.2.2 A Demonstration Within Niagara County
A demonstration project has been undertaken by Niagara County to
establish the application and merits of a specialized piece of equipment to
be used in sanitary landfill operations. In principle, the machine receives
refuse from a collection truck and then proceeds to shear, crush and extrude
the refuse from a press into the trench which is being excavated by the trencher
wheel. The excavated earth is subsequently replaced in the trench and is compacted.
It is estimated that the "D and J Press" Refuse Disposal Machine is
capable of performing the above operations within approximately five minutes
while handling 15 cubic yards of refuse per cycle.
D.2.3 Town of West Seneca - An Example of Facility Conversion
With the advent of the new Erie County air pollution standards and
the rapidly increasing quantity of refuse generated in the Town of West Seneca,
the Town decision makers were faced with the options of either modernizing and en-
larging their 60 tons per day rated capacity incinerator or select some other alter-
native for solid waste processing. It was decided to construct a truck transfer
station for a variety of reasons among which were: (a) the minimization of air
pollution problems associated with a well-operated transfer station, and (b)
the many characteristics and facilities of the existing incinerator plant
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lend themselves to relatively simple modification and economic conversion for
re-use as a transfer station. The transport equipment for hauling refuse from
the transfer station to the landfill site consists of two 70-75 cubic yard
capacity trailers and one tractor. Based on three to four round trips per tractor
trailer per day, the refuse disposal capacity of the system is approximately
240 cubic yards. The addition of a second tractor will increase the refuse
handling capacity to about 480 cubic yards per day.
It is planned that future increased capacity can be obtained by the
installation of an additional hoppers,stationary ram packer units, and transfer-
trailer stalls.
Based on a capacity estimate of 60 tons per day and a landfill disposal
&!rge of 30 cents per cubic yard, it is estimated that the total cost (including
lirect labor, maintenance, supplies, fuel and utilities, landfill charges and
uortization) is $4.90 per ton. For a 100 ton per day operation, the total cost
is $3.90 per ton. Although these charges are fairly high for truck transfer
jpcrations, they are heavily dependent on the limited size of the operation.
D.2.4 Carborundum Company Uni-Melt. A Technological
Innovation being Examined
In recognition of such problems as (1) air pollution, (2) the rela-
tively large volume of residue (15-20%) from conventional incineration, and (3)
the low temperatures of conventional incinerators which thus require that many
types of refuse be sent directly to disposal sites and thereby inefficiently
tilize this scarce resource, the Carborundum Company has developed a processing
sncept called Uni-Melt. Basically, the Uni-Melt concept is built around the pyro-
IfSis process which is conducted in the neighborhood of 3000°F. At this temperature,
4e processing facility is capable of handling virtually all types of solid waste
ad it is estimated that the resulting inert residue should be approximately 5
«rcent by volume of the solid waste charged. The principal components of
te Uni-Melt consists of a (a) hot blast heater which furnishes preheated
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air at temperatures in the vicinity of 1800-2000°F; (b) a gasifier into which
the refuse is charged and is then volatilized; (c) an igniter within which the
incomplete products of combustion are completely combusted; (d) and (e) spray
tower and bag filter to reduce and virtually eliminate any particulate matter.
The residue obtained from the Uni-Melt process is a slag-like substance which
may have application in the construction industry as well as a road construction
material. Because of the high temperatures maintained in the gasifier, it can
be expected that the residue will be quite uniform and thus require no preheating
before it is utilized.
Since no pilot plant has been constructed and operated, it is not
possible at this time to assess the technical and/or operating problems which
may be encountered. A demonstration project is being contemplated which includes
the construction and operation of a Uni-Melt facility having a capacity of 75
tons per day. If the process proves technically and economically feasible and
reliable, and if, as recommended, the facility is located near the town lines
of Boston, Concord and North Collins in Erie County, it should be capable of
meeting the total refuse processing needs of this portion of the region.
D.3 Feasible Technological and Management Options
With the rapidly growing concern with the solid waste handling problems
throughout the world, very considerable amounts of research and development
efforts are being expended in the areas of collection, processing and disposal.
To a degree, the applicability of the research and innovations is dependent
on such local factors as the types and amount of waste being generated, the
availability and cost of land and labor, the attitudes and legislative restrictions
imposed on solid waste managers, and the financial capabilities of the region
to acquire and operate the specific facilities.
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No attempt will be made to enumerate and describe all the various
research approaches and innovations which are being investigated; only a sampling
of these efforts is described below. Furthermore the sampling incorporates
some processes which have been utilized successfully in other parts of the
United States and/or in other countries, but not in the Buffalo SMSA. For
example, the inclusion of a vacuum refuse system within the collection category
is made with recognition of its employment in Sundeberg, Sweden. A second
example is the inclusion of the Tezuka-Kasan "garbage block" system within the
processing category. This system could also be viewed as a value-adding waste
handling process. Thus, the options included are those which have not been
seriously considered by the refuse managers in the Buffalo SMSA and are illus-
trative of the broader spectrum of choices which are available for meeting some
aspects of the regionalized refuse problem.
Since the collection function constitutes roughly two-thirds to
three-quarters of the cost of solid waste handling, a considerable amount of
effort is being expended in this area and to reduce the quantity or volume of
refuse being collected. In general the "advances" have been rather straight-
forward in concept; that is, attempting to apply existing technology in a more
economic manner. Prime examples of these efforts are train-type collection
vehicles, various forms of on-site compaction units and improved on-site incin-
erators. Two examples of significant innovations related to collection and
transport are:
(a) Sweden's vacuum collection system which is
a pneumatic refuse transportation system, and
(b) Zandi's hydraulic collection system which is
a collection-transportation system within which
solid waste is transformed into a slurry and
transported within water carrying pipes (this
research is being supported by the Solid Wastes Program)
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(c) , Conveyor systems for collection and transport
of solid wastes to one of several destinations
e.g. a centralized collection pickup point; to a
processing plant; directly to the final disposal
site.
Each of the above developments reduces the manpower requirement, and
eliminates the amount of moving vehicle needs (with their associated deleterious
effects) but entails large capital expenditures.
The second largest cost component in solid waste handling is related
to the processing function. Beyond the direct costs associated with such pro-
cessing alternatives as incineration and composting are the indirect social
costs which if significantly reduced would increase the direct cost of pro-
cessing. In general most of the research and development in the area of pro-
cessing can be categorized in the following manner: (Ref. 11).
(a) Chemical Oxidation Combustion
Central Municipal Incineration
Centralized Incineration
Wet Air Oxidation
Pyrolysis, Distillation and Other Oxidation Processes
Cb) Biochemical Oxidation
Composting
Anaerobic Processes
(c) Physical Size Reduction
Commercial, Institutional, and Industrial Grinders
Central Garbage Grinding Stations
Central Pulverization Plants
Compaction
Pulping
Dewatering
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(d) Salvaging - Reclamation - Reuse - Physical Separation
In general, category (a) Chemical Oxidation Combustion has been viewed
primarily as a means of achieving volume reduction and rendering the solid
vaste chemically inert. With the fairly recent development of high temperature
incineration (Melt-Zit process of the American Development Design Corp.) and
the pyrolysis process (Uni-Melt of the Carborundum Company), the residue resulting
from these processes are being considered as commercially-useful materials there-
by eliminating much of the need for subsequent disposal of the process residue.
A similar point of view has been held relative to category (c) Physical Size
Reductions, that is processing the solid waste so as to alleviate the require-
rents for subsequent solid waste disposal operations. The very high pressure
compaction (Tezuka-Kasan)process of solid waste and the cladding of refuse block
with either concrete or iron results in a product which may have considerable
commercial value for such purposes as bulkhead, retainer wall and foundation
construction.
Categories (b) Biochemical Oxidation and (d) Salvaging - Reclamation
- Reuse - Physical Separation have traditionally been thought of as value-
adding processes. Unless value-adding can be viewed from an over-all national
resources conservation position, they have not in the recent past proven to be
of significant and continuous economic benefit as a method of processing the
solid waste of a municipality or region. In specialized instances, such as
the salvaging of paper and raps, from industrial waste or because of special
locational factors (the shipping of tin cans from Chicago to the Copper smelters
in the Southwest) there have been some successful operations.
Developments directly associated with the disposal function have been
rather traditional which may be explained partially by the facts that this
function is the least costly of the three major solid waste handling functions
md the greater emphasis on various processing and associated transport opera-
tions which directly affect disposal. But as has been repeatedly stressed through-
wit this report, much of the National interest and urban concern relative to
solid waste stems from the limitation of accessible and available land needed
for the disposal function.
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Beyond the broadening of perspectives of accessible disposal sites
which involves the development of most cost-effective transport systems, most
of the disposal entails open dumping on land, and a variety of sanitary land-
fill operations. Furthermore as a means of deriving "greater" capacity from
disposal sites, obtaining greater public acceptance and enhancing the utility
of the sites being utilized, more comprehensive planning is being given to the
ultimate uses of the completed site. For example, as a means of increasing the
capacity of the site and obtaining public acceptance such end-uses as coaster hills
and ski slopes are being developed from the disposal operation.
Thus as mentioned earlier, the number of technological options avail-
able to the regional solid waste planner are fairly extensive. The major factors
limiting the scope of the options available to a specific region are (i) the
vision and willingness of the planners to try something different; (ii) the
ability of the region to support the associated costs of the operations and
facilities; and (iii) finally, the solid waste operating standards which are
being demanded by the population.
In addition to the aforementioned technological options available
to the region, another spectrum of options which can provide a major assist to
solving the regional problems is the application of sound management practices.
Whereas some urban areas of the United States, notably Los Angeles and New York,
have recognized the benefits of applying scientific management techniques and
management information systems to solid waste handling operations and planning,
the majority of the Country has for a variety of reasons not availed themselves
of this capability. In part, this is a function of the cost of acquiring and
maintaining the capability, the limitations of the people currently operating
and planning solid waste systems, and the fairly low status that solid waste
handling has in local governmental organizations.
As illustrative of the contributions that can be derived from the
application of management science techniques two examples are offered - the
first relative to operations and the second relative to planning. Within
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an urban area, there are continuous shifts in land-use patterns and population
densities which thus influence the types and amounts of solid waste being
produced. Since little or none of these movements are explicitly known or fully
appreciated by the solid waste manager (usually the Commissioner of Sanitation and
his staff) the utilization and scheduling of men and collection equipment are
not modified accordingly. It is apparent that the operations could be improved
significantly if the scheduling were done on a dynamic-basis based on the avail-
ability of current and projected data which could be stored and processed within
a solid waste management information system. Such improvements as greater
productivity per man-hour or equipment-hour within the collection function (the
most expensive portion of solid waste handling); reduction in waiting times of
vehicles at processing plants and disposal sites; improved reliability of equip-
nent through proper maintenance scheduling should be achievable.
Within the area of planning much of this activity is currently per-
formed at a point of impending crisis when the major thrust of the planning
is to find solutions to meet the immediate problems and, in passing, to give
some rather general considerations to the longer-range problems. This planning
also has the characteristic of being "one-shot" efforts in that once a plan is
formulated, parts are implemented and the planning activity is then minimized
until the next crisis period. The effective application of planning for solid
waste is to maintain a continuous information gathering activity concerning
changes in types and quantities of refuse, the location of refuse generation
(these are similar to the information required for operations), future land-use
plans, and technological changes in collection, processing and disposal functions.
With information of this nature, plans can be made and actions taken to avoid
the crisis-to-crisis mode of planning and to establish a well-conceived integrated
and coordinated regional solid waste handling system. The two main activities
in this form of planning are continuous information gathering and processing,
and the development, review, and assessment of plans for future actions.
These two brief examples are simply illustrative of the variety of
applications of sound management science technology to the current and long-
range problems of solid waste management.
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APPENDIX E CONCEPTUAL SCREEN AND SCREENING PROCEDURE FOR PRELIMINARY
ASSESSMENT OF SOLID WASTE OPERATIONS* AND SYSTEMS
LI Introduction
In the evaluation and selection of solid waste operations and
systems, the decision-makers with the aid of their analysts are confronted
nth a broad spectrum of alternative choices. As an integral part of the
system planning procedure, detailed study of these alternatives is required
so as to determine whether the operation or system meets the solid waste
landling requirements of the region in such terms as the types, quantities
of refuse, costs, physical limitations, etc. Beyond meeting handling requirements,
the system should be evaluated relative to various performance standards
Did associated acceptance levels, as specified by the numerous interests
dthin the region.
Within the context of this Appendix, the term handling requirements
of the region refers to those operation or system properties which are
related to: (a) the characteristics of the refuse to be processed and/or
disposed; (b) the quantity of refuse to be handled; (c) the rate at which
the refuse is to be processed and/or disposed; and (d) those properties
ihich are related to the capability of the operation or system to handle
the region's refuse within the required reliability and adaptability constraints.
Hie second category of operation or system properties, referred to as standards,
ire those factors which are associated with the health, aesthetic, environmental,
political, land-use variables, and for which performance levels have been
specified for or desired by the population of the region. Certain of these
standards may be classified as subjective since they reflect, to a high
iegree, the type of environmental quality that the population specifies
md is willing to support financially. In many of these instances, there are
io direct monetary trade-offs between the benefits accrued by changing
the acceptance level associated with a given standard (e.g. noise level) and
An operation is defined as any major stage within the solid waste handling
system functions of collection, transportation, processing and disposal.
E-l
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the cost of achieving this modified level. For these variables, the body
politic selects levels (usually through a rather cumbersome and sometimes
mysterious procedure) to be met by a solid waste system and thereafter,
any acceptable alternative (operation and/or system) is required to perform
within these levels. Even in those instances where it is possible to demonstrate
the monetary trade-off relationships between the benefit derived by the
region for acquiring an operation or system capable of operating at a
specified level with respect to a given standard, and the additional operation
or system cost to achieve this level, it certainly does not follow that
the acceptance level selected by the region is the optimum benefit-cost
point. The decision concerning the specified level is based on the criterion
established by the regional decision-making bodies (including in some instances
the citizens) and the availability and/or willingness to commit the necessary
resources.
Fig. E.I depicts the general relationships of costs and benefits
(described in terms of cost) to a region for levels of particulate matter
associated with a given operation such as an incinerator. Whereas the
minimum total cost (C*T) to the region may be achieved by selecting the
particulate matter level of L*, the cost of illness (C*x) related to this
level of particulate matter (some combination of number of illness and
severity of illness) may be objectionably high to the population. Thus,
from a health standpoint alone, the region may select particulate matter
level Lj which would significantly reduce CL but would increase both the
cost of procuring the particulate matter abatement measures (C.) and the
f\
total cost (Op).
The establishment of objective acceptance levels for given standards
is exceedingly difficult for at least the following reasons:
(a) The quantitative relationships between the standards, within the
domains of health, aesthetics, environment, etc., and objective
measurements associated with the standards are extremely
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difficult to establish. In most cases these relationships
are virtually impossible to determine on any statistically
significant basis with the current state-of-knowledge.
COST
*
ci
,
ABATEMENT I
MEASURE (c.) j
COST OF ILLNESS
RELATED TO PARTICULATE
MATTER C
PARTICULATE MATTER LEVELS
Figure E.I RELATIONSHIPS OF COSTS AND PARTICULATE MATTER LEVELS
(b) Assuming that the relationships can be established, there
remains the problem of describing the dependent variables
in some common unit. The unit most commonly utilized is a
monetary one since the decision to be made usually requires an
expenditure of funds and therefore some "trade-off" between
funds expended and monetary benefits derived.
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E .2 Formulation of a Screen and Screening Procedure
The effort required for examining and evaluating a candidate solid
waste operation or system, or synthesizing systems from screened operations
can be reduced considerably if a screening procedure is employed initially.
The formulation of a screen, and screening procedure starts with the condition
that a set of standards and their associated acceptance levels have been
specified. It is assumed that these standards and acceptance levels have
been derived based on both an assessment of what is desired and some gross
estimation of their implications in terms of the technical opportunities
available for achieving the acceptance levels.
The screen and associated screening procedure consists of a series
of tests and comparisons of the operation or system to determine whether
all the acceptance levels can be met by the candidate being tested. Given
that a system passes through the screen successfully, it is now an acceptable
candidate for the more extensive evaluation procedure, as outlined within the
Regional Solid Waste Handling Evaluation Model described in Section 3. This
subsequent evaluation considers the system's refuse processing and/or disposal
capabilities, its performance and associated costs over the planning horizon
or the system's useful life, whichever is shorter. The evaluation model
requires inputs concerning the system's physical characteristics, operational
performance, initial and operating costs, material reclamation and salvaging
properties (if any) and its impact on other aspects of the regional planning
(e.g. the need for roadways or road characteristics).
The remainder of this Appendix is a description of the screen and
screening procedure. The description should be viewed as conceptual since
the details of the individual screen stages as well as the number of stages
requires precise definition, and the screening procedure (including the process
or system modification operations) could be made more efficient. For example,
whereas the screening process calls for a modification step at each stage within
the screen, it may be more efficient to permit the candidate operation or
system to be evaluated at all screen stages and only initiate the required
E-4
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•edifications after the "screening" has been completed. Additionally,
whereas the screen and screening procedure appears to have broad utility,
the specific measures and acceptance levels must be specified to meet the
objectives and requirements of individual regions.
In essence, the screen consists of a number of individual stages
each of which is related directly to a specific standard (S.) and its
associated level of acceptance (L^). The stages are categorized into three
•ain classes:
(a) Immutable
(b) Conditional
(c) Negotiable
The immutable class includes those standards and levels whose
deleterious effects are well understood and,because of externally imposed
regulations, no deviations from the acceptable (specified) levels are tolerated
(e.g. location of open dumps relative to streams, rivers, or other bodies of
rater). Within Fig. those standards are shown as S., S., and S^. The
second class, referred to as conditional, includes standards having acceptable
levels which have been locally established and are specified as a range
rather than a single value. Here there is a less precise understanding of
the relationship between the levels of the standard and the deleterious effect
than those included within the first class of standards. An example of a
standard within this second class, as shown on Fig. E.2 , is the average
rermin population density. Finally, in the third class, negotiable, are standards
mich are related to highly subjective factors and for which the relationships
lith the associated deleterious effects are almost entirely established by
individual or group preference. Thus, based on the importance and/or severity
if the deleterious effects, the screen stages are ordered accordingly.
As shown in Fig.E.£ an operation or system, with those characteristics,
mich are relevant to the standards, is entered into the screen at stage S
E-5
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PAGE NOT
AVAILABLE
DIGITALLY
-------
It should be noted at this point that since the screen is being designed
for any solid waste handling system, the number of screen stages (relating
to specific standards) would be greater than is required for any individual
operation or system. Within this stage, for example, a comparison is made of
the paniculate emission characteristics, operation or system and the
acceptable particulate emission level. Given that either the operation
or system does not emit particulate matter, or the acceptance level is
not exceeded, the operation or system is advanced to the next stage. If the
candidate does not perform within the particulate matter limit, an assessment
is made (outside the screen structure) to determine whether appropriate
lodifications can be made. At this point, if the results of the technical
assessment indicates that the modification cannot be made so as to enable
the candidate to operate within the acceptable level, the candidate is immediately
rejected. In many instances, it can be expected that the modification can be
appropriately achieved by utilizing several different approaches. If the
approaches are significantly different, their introduction to the inclusion of
operation or system can be thought of as generating additional candidates. Thus,
another function of the screen and screening procedure is to assist in the
formulation of additional alternative operations or systems from the original
set of candidates. When appropriate modifications are made, the operation or
system is passed on to the following screen stage, S-.
At the second screen stage (within the immutable class of stages), the
operation or system is subjected to a similar comparison. For the example shown
inFig.E.2, the second stage is associated with the gaseous emission (NOX» S0x»
vt hydrocarbon) standard.* Here again, if appropriate modification can not
be made, the candidate is discarded. Given that the modification is required
»nd is accomplished, the operation or system is now examined further. At
Although the gaseous emission standard is depicted as a single stage, each
of the constituents would be assessed individually within successive screen
stages; the operation or system could be rejected if the level is not
let or appropriate modifications could not be accomplished at each stage.
E-7
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this point an assessment must be made to establish whether the type or
extent of the modification made has changed its characteristics in a manner
which relates to the previous screen stages. Thus at screen stage S,.
after the modification has been performed, a question is posed as to whether
the operation or system particulate emission characteristics has been
altered. If no alteration has been made to the characteristics related to
the standard, or if the particulate matter acceptance level has not been
violated the operation or system is passed through to the S. . stage, or
in this case, S_.
At the third screen stage, solids in water output standard, the
screening procedure is similar to that described for the S2 screen stage with
the one major exception being that, given a modification to the operation
or system, the consequences of the modification must be examined relative
to all preceding stages. As a result of a modification at this stage or
any stage i which has an associative effect relative to a previous standard,
it is possible that the candidate is now rejected because of an inability
to meet both acceptable levels concurrently.
The second class of stages, conditional, is located within the
screen directly after the immutable stages. Since the conditional class
consists of standards whose acceptance levels are locally-derived and whose
impacts are not precisely understood, the screening process for this class
would have the following properties:
(1) As in the immutable class, the operation or system is
compared with the acceptance level at stage j. If its
appropriate characteristics performance is within the
level, the candidate is passed through to the next stage.
(2) Under the condition that the acceptance level is not met,
a measurement is made of the difference between the can-
didate performance and the acceptance level. Depending
on the specific standard and the amount of uncertainty
E-8
-------
regarding the relationship of the level and the "deleterious"
effect(s) the candidate is either passed through or the
modification procedure is utilized.
(3) In the event that the candidate must be modified for
acceptance at the specific stage, the same process is
employed as had been described earlier.
As indicated, the significant difference in screening between the conditional
class and the immutable class is the introduction of a step which allows for
judgment to be exercised as to the altering of the acceptance level for
individual candidates. An example of this class of measure and the screening
process is shown in Fig.E-2 as stage S': vermin limit.
The third and last class of stages, negotiable, operates in a
similar manner to the above with the major difference being that the acceptance
level may be altered significantly, if it appears desirable. In the Figure,
the example shown refers to an odor standard. Whereas initially it may
have been decided to require that odors be restricted to the building or
buildings housing an operation, for certain types of odors it may be
acceptable to restrict the odor to the total area occupied by the operation;
that is, within the boundaries of the facility. Therefore, instead of
rejecting the operation or system since it did not pass the acceptance
level and no modification could be made, a question is posed as to whether
or not the acceptance level should be altered. If the response to the question
is negative, the process or system is discarded,whereas, if the response
is positive, a new acceptance level is established and the candidate is
passed to the next stage of screening. This procedure is shown on Fig. E.2
as the S", screen stage.
Upon passing through the final screen stage, a determination is made
as to whether the alternative being screened is an operation or a solid waste
handling system. If the candidate is a system, it is now considered an
appropriate alternative for main evaluation and is introduced into the Solid
E-9
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Waste System Evaluation Model. In the case that the candidate is an operation,
the accepted operation is now considered for systems synthesis and subsequent
reinsertion into the screen as part of a candidate system. The synthesized
system is subject to the identical screening procedure as outlined above.
E. 3 Summary
The screen and screening procedure is a systematic approach to the
examination of operations and systems to determine whether they meet the
acceptance levels associated with the standards prescribed by and/or imposed
on the region. The screening/modification procedure of each candidate is
useful in rejecting alternatives which cannot meet these standards prior to
the more extensive and.expensive procedure of system evaluation as described
in Section 3, and assisting in the formulation of additional alternatives
resulting from the modification step. Given these attributes of the screen
and screening procedure, the further development of an efficient, operational
screen and screening procedure would provide a useful capability for evaluating
large numbers of alternative solid wastes operations and systems.
E-10
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APPENDIX F INTRODUCING PRIVATE SOLID WASTE HANDLING INTO REGIONAL SOLID
WASTE MANAGEMENT PLANNING
F.I Introduction
A review of numerous county and regional solid waste handling studies
has revealed that:
(a) The collection of refuse is being performed by individual
municipalities and/or private collectors and recommendations
or conclusions are made that collection should not be
performed on an integrated country-wide or regional basis.
That is, the current organizations and their responsibilities
for refuse collection should not be modified.
(b) In recognition of significant increases in population and
economic activity, and increases in solid waste generated
per capita, it is concluded that available and accessible (near
sources of refuse generation) landfill sites are rapidly
disappearing.
(c) Data and estimates pertaining to household refuse generation
rates, municipal collection, processing and disposal functions
are presented and analyzed in considerable detail. Very little,
if any, information concerning refuse generated by sources not
serviced by municipal systems, and private collection proces-
sing and disposal practices, is included.
(d) The conclusions and recommendations made refer to the "public
sector" with little or no regard to the current and/or
potential interactions between this sector and the private
sector with respect to processing and disposal operations.
Whereas the severity of the municipal problems are described,
and short as well as long-term solutions recommended, the
implications left by these studies are that the problems
F-l
-------
of the private sector are not severe or that many alternative
solutions to their problems are available. In addition, it
can be inferred that there is little or no need to consider
the interactions between these two sectors, and the mutual
benefits of coordinated processing and disposal functions.
It is this dichotomization of the regional solid waste management
problem which bears further study to determine whether or not these sectors
should be treated dependently and if so, in what manner. It is recognized
that both sectors compete for the available capacity of "close-in" landfill
sites and although their objectives may differ somewhat, there appears to be
various bases for cooperation which can be arrived at by quantitative study.
The material presented in this Appendix is a discussion of the objectives of
the individual sectors; a description of an aspect of mutual cooperation;
and a presentation of an illustrative example which highlights, in economic
and land use terms, the advantages which each sector could accrue on a short-
term as well as a long-term basis through cooperation. It should not be
inferred that the identical solution will be applicable to all regions since
there are obvious differences in refuse generated rates, location and availabil-
ity of landfill sites, ordinances prohibiting certain forms of refuse proces-
sing, etc. The main purpose of this preliminary look at this question is to
explore the implications of cooperation between the private and public refuse
handling systems.
F.2 Common and Diverse Objectives of Public and Private Solid Waste
Management
The study of solid waste handling problems in urban areas, metropoli-
tan districts, county and regional levels involves projections of population,
economic activity and land-use developments over a period of 25 to 35 years.
Utilizing these projections, gross estimates can then be made of the residential,
commercial and industrial solid waste quantities to be generated, the locations
of refuse generation, and the available land for refuse processing and disposal
operations, for these future periods. A cost analysis of alternative processing
F-2
-------
and disposal operations can be performed and finally, recommendations can be
derived which are predicated on fulfilling some long-term objectives in an
orderly, time phased plan of action.
A commonly used form of objective function is the minimization of
direct cost over some specified time period subject to a number of qualitative
constraints such as health standards, aesthetic considerations, political
realities, public reaction, etc. A major attribute of the public sector solid
waste handling system objective should be, and often is, the long time period
being planned for rather than solutions which are derived for year to year, or
short-term system operation. Two aspects of the problem which have introduced
the need for examining solid waste management on a long-term basis are (i) the
requirement for large capitalization systems (amortized over 20 or more years)
and ii) the dwindling supply of land which is available and suitable for solid
waste processing and disposal. The scarcity of land is referred to consistently
when conclusions and recommendations for refuse handling are made.
In considering the objectives and operations of the private solid
waste collector and his waste handling problems, it becomes apparent that this
economic activity is organized and performed in a manner which is similar to
that of many profit-making organizations. Depending on the size of the
individual private solid waste collector's organization, the objectives and
operations are designed primarily to maximize profits over relatively short-
time periods - on a month to month or year to year basis. Thus, ways and
means for reducing costs or conversely, increasing profits, independent of
the mid-range or long-term community or regional objectives, are sought and
readily adopted by the private sector. In view of the relatively fast amortiza-
tion periods used for their equipment, and the relatively small investment
made on fixed facilities, these organizations can be properly characterized as
"foot-loose". This is not to say that they are established for short-terra
service but rather, their commitments to performing the refuse collection and
disposal functions are entirely dependent on the economic factors which govern
their profit structure.
F-3
-------
With these two seemingly opposed objectives, it may be questionable
as to whether these two sectors - public and private - could cooperate in Beet-
ing the total solid waste handling needs of a city, district, county or region,
and still enable each sector to achieve its objectives, at least in part.
In addition to the differences in objectives, an area of competition
between the two sectors is the demand for a scarce resource - land. For the
private sector, this scarce resource can be thought of in terms of the cost
entailed in hauling refuse to disposal sites which will be located further and
further away from the points of collection. The public sector is also confronted
with this same consideration and in addition, the political reality of the
uncertainties when utilizing land outside their jurisdictions. This uncertainty
stems from the difficulties of obtaining acceptance of another political entity
to allow it to utilize their land for disposal purposes on a long-term,
uninterrupted basis.
Assuming for the time being that one can view the collection function
as being relatively independent of the processing and disposal functions, it is
evident that the existence of private collection organizations is bene-
ficial because one result of their activity is reduction of the require-
ment for the general community to provide this service. In some communities
where all the refuse is collected by private organizations, the individual
household and other refuse producers pay directly for the performance
of this service. Another mode of payment for collection services
provided by the private sector is to have the community enter into a
contractual arrangement with the refuse collecting organization, and
incorporate these costs into the overall community budget. In other communities,
the households are serviced by the public sector, and commercial and industrial
organizations are handled by the private sector. This latter arrangement
normally results in a service designed to be more responsive to the specific
needs of the individual commercial and industrial organization being serviced.
F-4
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When considering the processing and disposal functions, it is not
ipparent that similar arguments for decentralization are valid. In general,
processing requires rather large, expensive, fixed installations which are
either beyond the fiscal resources of the individual private collector or are
not in consonance with their individual objectives. The processing facilities
io not dispose of the refuse but rather modify the weight, volume or chemical
properties of the input. Unless one can establish that this processing function
results in a net profit to the private organization, there are few, if any,
economic incentives for the private sector to process the refuse. To date,
except for refuse-compaction processing, and a limited number of highly local
situations, the processing operations in the United States have not been
justified on the basis of a "profit" being derived by the operator of the facility,
towever, it has been shown that as the volume or tonnage of refuse being processed
ty a facility increases, the unit cost of processing is reduced substantially.
A significant advantage derived from refuse processing is the con-
servation of the available sanitary landfill capacity. This advantage is of
mtual benefit to both sectors and thus serves as a basis for an investigation of
the conditions and means required to bring about this cooperative action. With-
in any investigation of cooperative actions, explicit attention must be given
to the objectives of each sector over its respective time span of interest. A
preliminary model and an illustrative example is presented to highlight some
rf the points made and to provide further insights for examining the hypothesis
that cooperation between the public and private sectors would result in mutual
tenefits. Thus, given a range of regional and technological inputs, the
todel should assist regional planning in examining ways and means for achieving ;
Ritual cooperation between the private and public sectors in the processing
nd disposal of solid waste.
F-5
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F.3 Preliminary Model
A preliminary model is presented for examining the question of
cooperation. The model is exercised under two conditions — cooperative and
noncooperative operations -- and results are derived upon which comparisons
can be made. Briefly described the two systems to be examined are:
(1) A waste management system (including processing and
disposal only) within which the public sector operates
independently of the private sector. Within this system
both sectors utilize the same disposal facilities but only
the public sector processes its refuse.
(2) A waste management system within which all the refuse is
processed and then disposed of at the same disposal facilities.
Each of these systems is formulated in terms of the direct costs
to the public and private sectors and results are derived relative to land
requirements as a function of elapsed time of system operation. So as to
allow for a preliminary assessment of the systems to be made, the following
assumptions are utilized within the model.
(a) The publicly -controlled or operated (municipal or region)
and privately-operated collection function are performed
independently
(b) The collection costs are not included within the determination
. of refuse handling
(c) The cost components included in establishing the refuse
handling cost include (i) processing costs; (ii) round-
trip transportation costs to the disposal site; and
(iii) disposal costs.
F-6
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(d) Within System (1), the publically-constructed and
operated processing plant maintains a three-shift, five day
per week schedule and has a capacity which is sufficient to
handle the total quantity of public sector refuse. When
the private sector utilizes the same processing facilities
as the public sector (System 2), the plant capacity can
be increased to accommodate the additional refuse within
a three shift, five day per week schedule.
(e) Refuse (processed or unprocessed) is hauled to the
nearest disposal site until such time as the site capacity
is exhausted. Each sector's refuse is handled at the
disposal sites on a first come - first served basis; that
is, no preferential treatment is given to either sector
in terms of site capacity allocation and reservation, or
cost per load disposed.
(f) Refuse generation sources are distributed in such a manner
that there is no significant difference in transportation
costs between hauling refuse to the processing plant or
directly to the disposal site.
§
v*.
[Note: Although the disposal sites are all shown located along a
straight line, they are located, more appropriately, within
a two-dimensional space.]
Figure F.I LOCATION OF DISPOSAL SITES RELATIVE TO SINGLE PROCESSING PLANT
F-7
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F.3.1 Processing Plant Parameters
a = reduction ratio of process; for municipally or
cooperatively - operated processing plant, (initial
weight of solid waste is that within collection vehicle
at time of delivery to processing plant)
p1 = reduction ratio of processing plant (employing
a different process than above) operated by private
sector (e.g., compaction associated with transfer station)
c = cost/ton of municipally-operated processing plant of
capacity C (C = R ) ($/ton)
P P M
c1 = cost/ton of cooperatively-operated processing plant of
capacity C1 (C1 = R., + R ) ($/ton)
P P " P
c" = cost/ton of privately-operated processing plant of
capacity C" (C" = R ) ($/ton)
F.3.2 Refuse Collected Parameters
IL '- municipally collected, or privately-collected,
municipal solid waste (tons/day)
R = commercial and industrial refuse collected by
private sector (tons/day)
density of refuse (in vehicle) collected by public
and private sectors delivered to processing plant.
In the general case, the average density (D) of
refuse collected by the public sector is different
than that of the private sector (Ibs/cu. yd)
F-8
-------
,3.3 Transportation Parameters
capacity of municipal vehicles used for transporting
processed refuse (yd /truck )
C' = capacity of private vehicles used for transporting
3
processed or unprocessed refuse (yd /truck )
c = cost/mile of municipal vehicles for transporting
processed refuse ($/mile )
c1 = cost/mile of private vehicle for transporting
processed or unprocessed refuse ($/mile )
3.4 Disposal Site Parameters
7
C = capacity of site i (yd )
c = cost of disposing of truck load (capacity C ) ($/ truck load)
c' = cost of disposing of truck load (capacity C')($/truck load)
d. = distance of disposal site i from processing plant
(miles)
3.5 Life of Disposal Site i
Case 1 - Site receives processed municipal refuse and
unprocessed private sector refuse
s.
F-9
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Case 2
Site receives municipal refuse and private
sector refuse - all refuse processed in
identical fashion
DC,
L»,=
5.
Case 3
Site receives processed municipal refuse and
private sector refuse - each sector employs
different process
s •
L. =
F.3.6 System (1)
Municipal Solid Waste Processed and Disposed
Private Waste Disposed Directly
TCM = Total Cost to Public Sector Over Life of Disposal Sites
TC = Total Cost to Private Sector Over Life of Disposal Sites
— -~_ _ . ___ .
C P
S*>
Y^R^R-
- i
Subject to condition:
J_
D
F-10
-------
F.3.7 System (2) - Both Municipal and Private Solid Waste Processed Within
Cooperative Processing Facility and Then Disposed
Total Cost to Public Sector Over Life of Disposal Sites
TC
M
DC,
' _ c. /? ^
' ^? j_
•« **..* '
V
Total Cost to Private Sector Over Life of Disposal Sites
DC.
z»c;
Z
's DCj
r
DC.
^^;
System (2A) - Both Municipal and Private Solid Waste Processed Within
Different Processing Facilities and Then Disposed
Total Cost to Public Sector Over Life of Disposal Sites
Y * L ,
t-^ f>%~ + P t
z
Z
DC.
F-ll
-------
*«
-» /?*»**/
/ r Ft I
DC.
TC
Total Cost to Private Sector Over Life of Disposal Sites
Sf?p
i
T
DC, d.
<
DC,.
F.3.8 Illustrative Example
R a 1000 tons/day
R * 1000 tons/day
D = 400 lbs/yd3 « .2 tons/yd3
P »
c =
p
c»
*%
.2
$5/ton
$4/ton
200,000 yd
400,000 yd
800,000 yd
1,600,000 yd
3,200,000 yd*
d
Sl
d «
S2
d
S3
d
S4
d
5 miles
10 miles
15 miles
20 miles
25 miles
s
F-12
-------
40 yd3/load
C'T « 40 yd3/load
ct * $l/mile
c' » $l/mile
$10/load « $10 per 40 yd3 of residue
c' = $10/load = $10 per 40 yd of residue or refuse
F.4 Results and Conclusions
A number of conclusions can be drawn based on the results derived
within the illustrative example but in all instances these conclusions
should be viewed as trends or directions rather than as estimates of the
savings in total system cost if a cooperative system is adopted. As
another note of caution, it is important that the initial assumptions
utilized be kept in rr.ind as well as the parameters employed within the
illustrative example when assessing the results and attempting to utilize
them within a specific region.
An examination of Table F.I and Figs. F.2, F.3 and F.4 , reveals
the fact that if the planning for a regional solid waste system is predicated
on a long-term basis, and if there is a relative scarcity of close-in and
available land for refuse disposal, it appears advantageous to introduce a
processing function which is utilized by all sectors which perform refuse
disposal. This advantage (shown on Fig.F.4), in terms of direct costs, is
immediately experienced by the public sector and, within a short time, by the
private sector. Within the illustrative example, the costs associated with
System (1) rise steeply, especially for the private sector, as the disposal
operation shifted from Site 4 to Site 5, whereas the costs associated with
F-13
-------
•n
SYSTEM (1) Non-cooperative Operations
Table F.I
PUBLIC AND PRIVATE REFUSE SYSTEM COSTS
Disposal
Site (j)
1
2
3
4
5
SYSTEM (2)
1
2
3
4
5
Life of
Disposal Site Elapsed Time
( Days ) ( Days )
33
67
133
267
534
Cooperative
100
200
400
800
1600
33
100
233
500
1034
Operations
100
300
700
1500
3100
Public
Total Cost*
$ 181,500
(5500)
566,700
(8460)
1,364,700
(10,260)
3,023.500
(11,320)
6,494,500
(12,160)
$ 450.000
(4500)
950,000
(4750)
2,000,000
(5000)
4,200,000
(5250)
8,800,000
(5500)
Private
Total Cost**
5 82,500
(2500)
333,700
(4980)
998,700
(7510)
2,627.500
(9840)
6,632,500
(12,420)
$ 450,000
(4500)
950,000
(4750)
2,000,000
(5000)
4,200,000
(5250)
8,800.000
(5500)
Public
Ace. Total
Cost
$ 181,500
(5500)
748,200
(7480)
1,931,400
(8290)
4,954.900
(9910)
11,349,400
(10,980)
$ 450,000
(4500)
1,400,000
(4670)
3,400.000
(4860)
7,600,000
(5070)
16,400,000
(5290)
Private
Ace. Total
Cost
$ 82,500
(2500)
416,200
(4100)
1,332,400
(5720)
3,959,900
(7920)
10,292,400
(9950)
$ 450,000
(4500)
1,400,000
(4670)
3,400,000
(4860)
7,600,000
(5070)
16,400,000
(5290)
Public I Priv,
Ace. Total
Cost
$ 264,000
(8000)
900,400
(11,640)
3,263,800
(14,010)
8,914,800
(17,830)
21,641,800
(20,930)
$ 900,000
(9000)
2.800,000
(9340)
6,800,000
(9720)
15,200,000
(10,140)
32.800,000
(10,580)
( ) Refer to Daily Costs
System (1) and (2) Cost of Processing and Disposal.
System (1) Cost of Disposal and System (2) Cost of Processing and Disposal.
-------
ta
PUBLIC SECTOR PROCESSES 4 DISPOSES
PRIVATE SECTOR DISPOSES ONLY
PUBLIC & PRIVATE SECTOR PROCESSES
AND DISPOSES (CURVE IS IDENTICAL
FOR BOTH SECTORS)
~s
•»««_»• ••*»•••*> J* ^»^-——- -
J"
... (ol).-
SYSTEM
^- +
i
......j.........j
i
r"
V -r r -t-
i - 1
^. -,
•{- + *• -h -<• •••
i I I I
200 100 600 800 1000
1200 UOO 1600 1800
ELAPSED TIME (DAYS)
2000 2200 2WO 2600 2800 3000
Figure F.2 CUMULATIVE COST FOR PUBLIC AND PRIVATE SECTORS VS ELAPSED TIME
-------
-------
11000
10000
9000
8000
7000
6000
S 5000
1000
3000
2000
1000
SYSTEM (1) PUBLIC
100 200 300
400 500 600 700
ELAPSED TIME (DAYS)
800 900 1000 1100
Figure F.H COST PER DAY FOR PUBLIC AND PRIVATE REFUSE HANDLING SYSTEMS
F-17
-------
System (2), although increasing, increased at a much slower rate. These
findings are shown more directly on Fig. F.2.
Depicted on Figs.F.2 and F-3 is a time history of the utilization
of the disposal sites under the two systems. Although this time history is
related to the total amount of refuse collected, the amount which is
processed and the process reduction coefficient, p , the impact of the
different utilization rates of the available land fill capacity is made
evident by these illustrative results. Here again, it is not significant
to note the specific values on the abscissa scale but rather to note the
relative capacity utilization rates of the disposal sites.
In conclusion, there are indications that a regional processing
and disposal plan, which includes the public and private sectors should
result in savings for both sectors, and in more effective utilization of the
available land fill capacity.
F-18
-------
APPENDIX G ESTIMATION OF OPERATING COSTS FOR REFUSE TRANSPORTATION
IN THE CITY OF BUFFALO
G.1 Summary
Records kept by the City of Buffalo do not contain odometer
readings on serial-numbered refuse trucks, nor are cost records kept in suffi-
cient detail on collection truck fleet operations to allow for determining the
cost of transporting refuse. Nevertheless a rough estimate of transportation
costs per mile was derived by means of estimating total operating costs and the
total number of miles required to perform typical weekly operations. The estimate
of cost per mile for transporting refuse does not include the amortized cost
of the truck or the labor cost of a crew or driver; these costs are approxi-
mately 65 cents per mile during the year 1966. When amortization and labor costs
are included, the cost of transportation while performing the transport(exclu-
sive of direct refuse collection) function is approximately 89 cents per mile.
G.2 Method of Estimation
Approximately two-thirds of the "Servicing Auto Equipment" account,
which amounts to $1.05 million in the City of Buffalo Department of Streets and
Sanitation budget for 1966, is attributable to collection and transport. The
remainder of the funds within the "Servicing Auto Equipment" account is
attributable to an assortment of functions including snow-removal, dog pound
operation, and street-cleaning. Thus the weekly cost of operation of trucks for
collection and disposal purposes is approximately (2/3) (1.05/52)million
dollars, or $13,462 per week. This cost is divided by an estimate of the number
of miles covered in one week by the entire truck fleet to obtain an operating
cost per mile. The estimate of the weekly miles traveled is derived by the method
whose description follows.
G-l
-------
All calculations are based on a truck fleet of 106 trucks; an average
of 99 trucks are in operation at any one time. It was estimated that six to
eight trucks are usually under repair or maintenance. The 99 operating trucks
make the following trips during an average week:
(a) All streets in Buffalo are traversed twice, once
for the regular refuse collection and once for the
trash collection.
(b) Each truck travels to its assigned district every day.
(c) Each truck makes several round trips to its
assigned incinerator, or one of the two landfills.
(d) Each truck makes a final one-way trip, assumed to be
to one of the landfills.
(e) Each truck returns to the garage after discharging its final
load of the day.
(f) The residue from the East Side Incinerator is hauled to
the Squaw Island Landfill. Since the Squaw Island Landfill
is adjacent to the West Side Incinerator, only negligible
mileage is involved in hauling West Side Incinerator residue.
This breakdown of all distances traversed by the truck fleet into "trip types"
enables the weekly total miles to be estimated as follows:
AVERAGE MILES PER WEEK = M. + M. + M. + M. + Mc + M,
123456
where :
2 [TOTAL NO. OF MILES OF STREETS IN BUFFALO]
G-2
-------
M2 = C5) C99) [AV. DISTANCE FROM GARAGE TO COLLECTION DISTRICT]
M3 = 2 [AV. NO. OF TRUCKLOADS TO INCINERATORS PER WEEK] [AV. DISTANCE
FROM COLLECTION DISTRICT TO INCINERATOR]
M4 = (5) (2 [AV.NO. OF TRUCKLOADS TO LANDFILLS PER DAY] - 1) [AV. DIS-
TANCE FROM DISTRICT TO LANDFILL]
M5 = (5) (99) [AV. DISTANCE FROM LANDFILL TO GARAGE]
Mfi = 2 [AV. NO. OF TRUCKLOADS OF RESIDUE FROM EAST SIDE INCINERATOR PER
WEEK] [DISTANCE FROM EAST SIDE INCINERATOR TO SQUAW ISLAND
LANDFILL]
*
All quantities in brackets were estimated by means of map measurements and by
use of data obtained from the City of Buffalo on truckload deliveries to the
various facilities, and on truckload quantities originating in the various
collection districts during 1966.
Distance and location data which are basic to the various calculations
are given in Table G.I. The approximate centroid of each collection district
was located (by visual estimation ) with respect to an arbitrary coordinate
system, as were the locations of the incinerators, landfills, and the garage.
Given these locations, straight line distances from the districts to the
facilities, and among the facilities, could be calculated; these are the figures
appearing in Table G.I. As will be seen, after all mileage calculations are
completed on a straight line basis, the actual miles traveled (as the trucks
are constrained to the street network) were obtained by multiplying the straight
line distances by the factor 1.3. This correction factor was obtained empirically
by a series of map exercises. It is by no means well-established, but is pre-
sented as the best estimate currently available for adjusting straight line
distances to the distances actually traveled within a city street grid network.
G-3
-------
Table G.I
LOCATION AND DISTANCE INFORMATION,
REFUSE COLLECTION DISTRICTS AND FACILITIES, CITY OF BUFFALO
COLLECTION
DISTRICT
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
E.S. INCINERATOR
SQUAW ISLAND
LASALLE L.F.
GARAGE
COORDINATES
2.5, 4.7
2.0t 5.4
2.5, 6.7
1.4, 6.1
1.4, 7.0
2.0, 8.0
1.0, 9.4
2.2, 9.1
3.5, 8.7
3.5, 9.8
4.7, 9.3
4.1, 7.8
5.0, 7.7
4.2, 6.6
3.2, 6.0
3.2, 5.0
4.0, 4.5
4.5, 5.7
3.2, 3.5
5.0, 2.2
6.0, 2.6
6.3, 4.7
5.4, 4.5
5.4, 6.4
6.2, 6.8
6.1, 8.0
5.9, 9.3
6.5, 4.5
1.1, 8.1
5.2, 9.3
3.0, 4.9
ASSIGNED
INCINERATOR
W
W
W
W
W
W
W
W
W
W
W
W
E
E
W
E
E
E
E
E
E
E
E
E
E
E
E
DISTANCE TO
INCINERATOR
4.08
3.25
2.38
2.42
1.54
1.51
2.00
1.89
2.87
3.34
4.19
3.41
3.53
3.11
3.37
3.34
2.50
2.33
3.44
2.75
1.96
1.20
1.60
2.15
2.32
3.52
4.84
"ASSIGNED"
LANDFILL
S
S
S
S
S
S
S
S
L
L
L
L
L
S
S
S
S
S
S
S
S
L
S
L
L
L
L
S
DISTANCE TO
LANDFILL
4.03
3.25
2.38
2.42
1.54
1.51
2.00
1.89
1.80
1.77
0.50
1.86
1.61
3.44
3.37
3.74
4.62
4.16
5.07
7.07
7.36
4.73
5.61
2.92
2.69
1.58
0.90
6.89
DISTANCE TO
GARAGE
0.53
1.30
1.87
2.00
2.64
3.26
4.92
4.67
3.83
4.92
4.72
3.10
3. 44
2.08
1.30
0.50
1.08
1.70
1.60
3.36
3.78
3.31
2.43
2.92
3.72
3.10
5.27
3.52
3.83
3.81
G-4
-------
Other basic data utilized consist of the tonnage figures transported
to the incinerators, which are identified by originating district, and the
cubic yardage delivered to the landfills, which are similarly identified. The
1966 totals over all districts and over the entire year yield the following
averages:
Av. Truckload to Incinerator = 2.6 tons
Av. Truckload to Landfill =14.2 cu. yd.
Checks on data sets which are restricted geographically and in time revealed
that these relationships remain sufficiently stable to be of use as conversion
factors. With this information, all quantity data could be stated in terms of
numbers of truckloads. Having performed this conversion on all quantity data,
it was possible to give the following for each collection district i,
1 » i • 27:
U. = the total number of truckloads from i delivered to incinerators
i
V. » the total number of truckloads from i delivered to landfills
i
W. = the total number of truckloads originating in i
This quantity data is given in Table G.2. In order to aggregate the total
number of truckloads, the following definitions are employed:
U = £u. as the total number of truckloads delivered to incinerators
£V. as the total number of truckloads delivered to landfills
£W. as the total number of truckloads of refuse
G-S
-------
Table G.2
REFUSE QUANTITY INFORMATION, CITY OF BUFFALO, 1966
NUMBER OF TRUCKLOADS GENERATED DURING THE YEAR
COLLECTION
DISTRICT
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
TOTALS
INCINERATED
• i» v I n fc*\M i bw
1993
2370
2023
2367
2679
1962
3254
1989
1815
1963
1945
2548
1665
2666
2835
2295
2925
3644
1645
3537
3142
2343
2312
1965
1795
2272
2177
64126
DISPOSED AT
LANDFILLS
1170
1221
1541
698
682
753
556
706
316
595
758
774
700
728
536
1504
788
725
562,
781
770
516
630
702
727
655
765
20860
TOTAL
TRUCKLOADS
3163
3591
3564
3065
3361
2715
3810
2695
2131
2558
2703
3322
2365
3394
3371
3799
3713
4369
2207
4318
3912
2859
2942
2667
2522
2927
2942
84986
WEIGHTS
U j
0.0311
0.0370
0.0315
0.0369
0.0418
0.0306
0.0507
0.0310
0.0283
0.0306
0.0303
0.0397
0.0260
0.0416
0.0442
0.0358
0.0456
0.0568
0.0257
0.0552
0.0490
0.0365
0.0361
0.0306
0.0280
0.0354
0.0339
1 .0000
vi
0.0561
0.0585
0.0739
0.0335
0.0327
0.0361
0.0267
0.0338
0.0151
0.0285
0.0363
0.0371
0.0336
0.0349
0.0257
0.0721
0.0378
0.0348
0.0269
0.0374
0.0369
0.0247
0.0302
0.0337
0.0349
0.0314
0.0367
1.0000
wi
0.0372
0.0423
0.0419
0.0361
0.0395
0.0319
0.0448
0.0317
0.0251
0.0301
0.0318
0.0391
0.0278
0.0399
0.0397
0.0447
0.0437
0.0514
0.0260
0.0508
0.0460
0.0336
0.0346
0.0314
0.0297
0.0344
0.0346
1.0000
G-6
-------
Weighting factors, i^ = IL/U, vi = Vi/V, wi - HL/W, are now computed which
are of use in establishing average distances for the various trip types. These
weighting factors are included in Table G.2 in the last three columns.
Specifically, if d| is the distance given in Table G.I from the
garage to the centroid of district i, then:
Av. distance from garage to collection district = D2 = £w.d!
This distance is 2.777 mi.
The refuse from each district is transported to one of the two incin-
erators based on the 1966 practices of the city of Buffalo. The fact that in
emergencies the alternative incinerator is sometimes used is ignored. An
examination of the records indicate that this does not occur often enough to
exert a significant influence on the outcome. Therefore it is possible to
assign to each collection district i, a distance dV to the appropriate incinerator.
The "assigned" incinerator and the distances to it appear in Table G.I. With
these inputs, the average distance from the collection district to the assigned
incinerator is:
Av. distance from collection district to assigned incinerator = D^ sEu^dV
This average distance is 2.721 mi.
No explicit assignment of collection districts to the two landfills
was in existence. However, the total cubic yardages delivered to the two sites
during the year was known. Using these totals, an assignment could be arti-
ficialized in which the collection districts closest to the LaSalle landfill
Vere assigned to that facility until the total of the Vj figures associated
with those districts approximated as nearly as possible the actual total delivered
to the LaSalle landfill. This "assignmenf'is indicated in Table G.I for
each collection district, along with the distance dV1 to that landfill. Then:
G-7
-------
Av. distance from collection district to landfills = D = £v.d'."
This average distance is 3.146 mi.
With these three averages computed, calculation of the mileage
estimates, M ,...M6> defined previously, and hence the per mile cost estimate,
can be made.
G.3 Calculation of the M-Quantities and the Cost Estimate
Since the number of miles of streets in the City of Buffalo is
620 miles, Mj = 2 x 620 = 1240 miles/wk. The distance traveled from the garage
to the collection districts, is M2 « 5 x 99 x 2.777 » 1375 miles/wk, using the
average distance D_ = 2.777 miles.
To compute M_, one needs to know the average number of truckloads
delivered to the incinerators per week. This is given by (U/52) = (64126/52)=
1233.2 truckloads/wk. Using the'average distance D_ = 2.721 miles, given pre-
viously, M3 = 2 x 1233.2 x 2.721 = 6711 miles/wk.
To compute M., one needs the quantity D. = 3.146 miles from the
previous section and also the average number of truckloads delivered to the
landfills per day. Based on a 260 day year, the latter quantity is given by
(V/260) = (20,860/260) = 80.23 truckloads/da. Then M4 = 5[2(80.23) - 1] x 3.146
[10(80.23) - 5] x 3.146 » 797.3 x 3.146 - 2508 miles/wk.
Computation of M_ in the present case is simplified by the fact
that the distances from the garage to the two landfills are just about equal,
that is, 3.82 miles for each. Thus Mg » 5x99x3.82 - 1891 miles/wk.
To compute M,, the average number of truckloads of residue hauled
per week from the East Side incinerator is known. This figure, which does not
appear in either of the tables, is 169 truckloads per week. Since the distance
from the East Side incinerator to the Squaw Island landfill is 6.9 miles, the
estimate Mg - 2 x 169 x 6.9 • 2332 miles/wk.
G-8
-------
The sum MX + ... + Mfi = 16,057 miles/wk. which represents the
straight line distance estimation. As discussed previously, this figure is
multiplied by 1.3 to account for the fact that the actual truck travel is
constrained to the road network. On that basis, the average is 16,057 x 1.3 =
20,874 miles/wk. This results in an average operating cost of ($13,462/20,874):
$.645 per mile. This estimate does not include any portion of the cost of
the vehicle, nor does it include labor costs for a driver or crew.
G.4 Other Cost Components
Depending on the application, there may be need to add other cost
components to the vehicle operating cost alone. For considering use of the
vehicle within the transport function (i.e. separating the round trips to the
incinerators and landfills apart from the collection function) it probably
makes sense to include the cost of the vehicle amortized over all miles
covered by the vehicle. Assuming the seven-year amortization period used by
the City of Buffalo, the average number of miles covered is
20.874 mi/wk x 52 wks/yr x 7 yr _ _.
106 vehicles * 71'681 miles
per vehicle. Assuming an approximate $12,000 per vehicle, this increases the
cost by an additional 16.8 cents per mile.
For the same application, if only the driver's labor cost is
relevant, and that is assumed to be $3 per hour including fringe benefits,
then, assuming an average speed of twenty miles per hour, there is an
additional labor cost associated with each vehicle of 15 cents per mile.
Including these additional costs (and assuming seven year life for
each vehicle) the per mile cost of transportation for the transport function is
estimated to be 64.5 + 16.8 * 15.0 = 96 cents per mile for the year 1966.
G-9
-------
APPENDIX H: A COMPUTER PROGRAM FOR GENERATING AND LISTING ALL V
COMBINATIONS
Let C^ represent the number of combinations of the N consecutive
integers 1, 2, 3, . . ., N taken K at a time. SUBROUTINE COMB which was
developed from Ref.26,is a Fortran computer program which can be used to
M
generate any of the 2 -1 possible combinations. The flow chart (SUBROUTINE
COMB) for the generation of all the possible combinations is shown on
Fig. H.I. The Fortran listing associated with the flow chart is included
on Fig. H.2.
A sample computer output for N=10 is given in Figure H.3 where all
the combinations for K=l, 2, 3 and 4 are shown. It is emphasized that
a call to SUBROUTINE COMB with a particular choice for N and K returns to
u
the user a single combination out of the total CKcombinations available.
The input parameters required for using the subroutine are defined
as follows:
N - the number of integers over which the combinations
are to be taken
K - the length of the combinations where K can take on
any of the values 1, 2, 3, . . ., N
JIN - the N consecutive integers representing the input
over which combinations are to be taken are stored
in the dimensioned variable JIN where JIN(1)=1,
JIN(2)=2, . . ., JIN(N)=N and N±20
JOUT - the output is stored in the dimensioned variable
JOUT representing one of the C^total number of
combinations. If the generated combination is of
length K then the first number is stored in JOUT(l),
the second in JOUT(2), .... and finally the Kth
H-l
-------
number in the combination is stored in JOUT(K)
where K^N
ITST - a call to SUBROUTINE COMB results in the generation
i4
of one of the C combinations which is subsequently
T^
stored in the output parameter [JOUT(I), 1=1,
2, . . ., K]. However, in calling COMB one is faced
^
with the problem of when all C have been generated.
IN
The user should test ITST after each call to COMB.
If ITST is 0, then further calls to the subroutine
|A
are required. If ITST=1, then all C combinations
i^
have been generated previously and a new K should
be specified. It should be emphasized that ITST
must be initialized to 1 by the user in the call
program at the start of the program, with SUBROUTINE
COMB modifying ITST whenever necessary.
H-2
-------
( ITST=0?
^\ YES
J
INO
Not all of the NCK
combinations have
been generated
GO TO 13
Return to call program with
the generated combination in
JOUT(l), JOUT(2), . . . JOUT(K)
All C., combinations were
accounted for on the last call
to subroutine. Return to call
program with ITST having been
set to 1
Input: ITST, N, K [JIN(I), 1*1, 2, . . ,,N]
Output: ITST, [JOUT(J), J-l, 2, . . .K]
Figure H.I FLOW CHART FOR SUBROUTINE COMB
H-3
-------
SUBROUTINE COMB
COMMON/BOB/ ITST,N,K,JIN(20),JOUT(50),JOUTT(50),
1 ITAB(SO), DISTPD(20,20), DISTSF(200,20)
IF(ITST .EQ.O) GO TO 13
2 IT=1
3 ITAB(1)=1
4 J= ITAB(IT)
5 JOUT(IT) = JIN(J)
6 IF( IT.EQ. K ) GO TO 7
8 ITAB( IT+1) = ITAB(IT) + 1
9 IF(ITAB(n>l).EQ.N+l) go to 10
11 IT=IT+1
GO TO 4
10 IT=IT-1
12 IF(IT.EQ.O) GO TO 20
13 ITAB(IT)= ITAB(IT)+1
15 IF ( ITAB(IT).EQ.N+1) GO TO 10
GO TO 4
7 ITST=0
RETURN
20 ITST=1
RETURN
END
Figure H.2 FORTRAN LISTING FOR SUBROUTINE COMB
H-4
-------
1
2
3
4
5
6
7
8
9
10
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
7
7
7
8
8
K=2
2
3
4
5
6
7
8
9
10
3
4
5
6
7
8
9
10
4
5
6
7
8
9
10
5
6
7
8
9
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
K=3
10
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
~ 2
2
2
2
2
2
2
2
2
2
' 2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
3
3
3
3
3
3
3
4
4
4
4
4
4
5
5
5
5
5
6
6
3
4
5
6
7
8
9
10
4
5
6
7
8
9
10
5
6
7
8
9
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
10
4
5
6
7
8
9
10
5
6
7
8
9
10
6
7
8
9
10
1
8
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=l, 2, 3 AND
H-5
-------
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
7
7
7
8
8
9
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
6
6
6
6
7
7
7
8
8
9
7
7
7
9
10
8
9
10
9
10
10
5
6
7
8
9
10
6
7
8
9
10
7
8
9
1U
8
9
10
9
10
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
10
7
8
9
10
8
9
10
9
10
10
8
9
10
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=l, 2, 3 AND ¥ (Cont.)
H-6
-------
6
6
6
7
7
7
8
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
8
8
9
8
8
9
9
K-4
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
9
10
10
9
10
10
10
3
3
3
3
3
3
3
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
. 7
7
7
8
8
9
5
5
5
4
5
6
7
8
9
10
5
6
7 ~
8
3
10
6
7
8
9
id
7
8
9
10
8
9
10
9
10
io
5
6
7
8
9
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
10
6
7
8
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=l, 2, 3 AND 4 (Cont.)
H-7
-------
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
7
7
7
8
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
5
5
6
6
6
6
7
7
7
8
8
9
6
6
6
6
7
7
7
8
8
9
7
7
7
8
8
9
8
8
9
9
4
4
4
4
4
4
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
5
9
10
7
8
9
10
8
9
10
9
10
10
7
8
9
10
8
9
10
9
10
10
8
9
10
9
10
10
9
10
10
10
5
6
7
8
9
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
10
6
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=l, 2, 3 AND M- (Cont.)
H-8
-------
2
2
^
2
2
2
^
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
p
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
7
7
7
8
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
6
6
6
6
7
7
7
8
8
9
6
6
6
6
7
7
7
8
8
9
7
7
7
8
8
9
8
8
9
9
5
5
5
S
5
6
6
6
6
7
7
7
8
8
9
6
6
6
8
9
10
7
8
9
10
8
9
10
9
10
10
7
8
9
10
8
9
10
9
10
10
8
9
10
9
10
10
9
10
10
10
6
7
8
9
10
7
8
9
10
8
9
10
9
10
10
7
8
9
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=l, 2, 3 AND 4 (Cont.)
H-9
-------
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
6
6
6
7
5
5
5
5
5
5
5
6
6
6
6
6
6
7
7
7
8
5
5
5
S
5
5
5
5
5
5
6
6
6
6
6
6
7
7
7
8
6
6
6
6
6
6
7
7
7
8
7
7
7
8
8
6
7
7
7
8
8
9
7
7
7
8
8
9
8
8
9
9
6
6
6
6
7
7
7
8
8
9
7
7
7
8
8
9
8
8
9
9
7
7
7
8
8
9
8
8
9
9
8
8
9
9
9
10
8
9
10
9
10
10
8
9
10
9
10
10
9
10
10
10
7
8
9
10
8
9
10
9
10
10
8
9
10
9
10
10
9
10
10
10
8
9
10
9
10
10
9
10
10
10
9
10
10
10
10
Figure H.3 SAMPLE COMPUTER OUTPUT OF 10CK FOR K=1, 2, 3 AND M- (Cont.)
H-10
-------
APPENDIX I: LISTING AND SAMPLE OUTPUT OF THE FACILITY SELECTION MODEL
This Appendix contains a FORTRAN listing of the facility selection
model described in Section 4.3. The listing appears in Fig. I.I.
A DO loop is set up so that a number NCASE of runs can be input
at the same time. In the particular setup pictured in Fig. I.I, the sources
are the same in all runs, as are the facility types and their locations.
The only thing which changes from run to run are the specific parametric
descriptors of the facilities.
The input deck for a series of runs of this type is as follows:
CARD 1: NCASE = number of cases
CARD 2: NS = number of sources
CARDS 3A.-3A.r_. : (Q(I)) » source quantities [NS of them]
1 H.-5J
eight to a card
CARDS 4Aj-4AL(4) (XS(I), YS(I)) = source locations [NS pairs]
four pairs to a card
CARD 5: N = number of facilities
NPP = number of processing plants
NDS = number of disposal sites
CARD 6: JIN(J) * facility names [N of them]
eight to a card
(Usually the first N integers are used)
CARDS 7A.-7A.,.,,: (XF(J), YF(J)) = facility locations [N of them]
1 LI/ j
four pairs to a card.
This is followed by a set of N cards for each run, making NCASE x N cards in all
For each run, one card is required to describe each facility. Each processing
plant card includes:
1-1
-------
PFC = the A. of the text
PCIN = the a. of the text
PPC = the cp of the text
PCOMP = the p. of the text
PCTO = the c' of the text
PCTTPP = the CT of the text
Each disposal site card includes
DFC « the A. of the text
DCIN = the a. of the text
DDC = the CD of the text
DCOMP = a constant similar to p., not used in the text
DCTTDS = the c_, of the text
For specific formats, see the listing.
In Fig. 1.2 is a portion of the output of one run of the program. In
this run, five facilities were on trial, and what is shown is the minimum cost
selection, namely all except Facility 5. The long list within the output gives
the service area assignments for each of the 110 sources. The string of zeros
in the other column indicates that there are no ties among possible facility
assignments for any of the sources.
1-2
-------
Figure 1.1 FORTRAN LISTING OF FACILITY SELECTION MODEL
0001
0002
0003
0004
0005
0006
0007
0008
0009
CC1C
0011
0012
0013
0014
0015
0016
C017
0018
0019
CC2C
0021
C022
0023
0024
0025
CC26
0027
0028
CC2<3
C03C
COMMON/806/ ITST,N,K,JINf20>,JOUT(50),JOUTT(5C),
1 ITAB<50), OISTPD(20,20), CISTSFt200,20 )
COMMON/COST/ PFC120),PC IN(20),PPC(20),PCQ*P(20I,PCTO(20) . PCTTPPC20
1 )tCFC(20),DFCIN<20),CDC(20),DCOMP(201,OCTTOS(2C)
2 ,C<20),Qi200),JEQUAL(200),JPRE0(200)
3 ,XS(200),YS(2CO),XF(2C),YF(20),AK(2CO,20I
4 ,JTFMP(200),JPRINT<200)
EPSL=.OOCC1
NCASE
NS
( XS( I ),YS(1ItI =
0 )
NtNPPtNDS
(JIN(l),I-i,N)
J
( XF( I),YF( 11,1-1,
1
REAO(5,5100)
READI5t5100)
51CO FORMAT*I1C)
REAO(5,IOC1)
RFAD(5,lOCil
1001 FORMAT ( 8F 10
READ(5,100C)
READ(5,ICOC)
1000 FORMAT( 8I1C
REAO(5,1001) ( XF( I),YF(11,1-1, N )
KNDS1= NDS +
00 5000 ICASE=ltNCASE
IF(NPP.EQ.O) GO TO 2000
REAO(5,2001I fPFCUItPCINdlf PPC( I) , PCOMP (I) , PCTOC I ) , PCTTPP (I)
1 I=KNDS1,N )
2 CCO READ (5, 2002) (OFC( Il.DFCIM I),OOC (I) ,CCOMP( I) , DCTTDS (I ), I = l,NCS
2001 FORMAT(6F10.0)
2002 FCRMAT(5F10.0)
DC 600 11=1,50
600 JOUTTlII)=C
DC 601 1=1,200
JTEMP(I)= C
6C1 JPRINTU)= 0
KCUT =0
URITE(6,5001)
5001 FORMATdHi )
V»RITE(6 ,5002) ICASE
5002 FORMAT(25X,«CASE NUMBER»,I 3,/////)
-------
Figure I.I FORTRAN LISTING OF FACILITY SELECTION MODEL (Cont.)
CC31
0032
0033
0034
0035
0036
0037
0038
OC39
0040
0041
C042
0043
0044
0045
0046
CC47
0048
0049
0050
0051
0052
0053
0054
0055
CC56
CC57
C058
0059
006C
C061
0062
00*3
WRITE(6,3000) ! JIM I), I-i ,N I
3000 FORMAT! • FACILITIES* / 10110 I
MUTE!6,3C01> !Q!I ),I*1VNS>
3001 FORMAT! • QUANTITIES* / (8E12.5I)
WRITE!6,1CC2I NS,N,NPP,NDS
1002 FORMAT!* NOS OF SOURCES AND FACILITIES*, 4110,///»
WRITE!6,IC03I !XS
-------
Figure I.I FORTRAN LISTING OF FACILITY SELECTION MODEL (Cont.)
t/i
0064
CC65
CC66
C067
0068
CC6<5
0070
CC71
0072
CC73
0074
OC75
0076
CC77
0078
0079
0080
CC81
CC82
CC83
0084
0085
0086
0087
CC88
0089
0090
0091
CC92
0093
CC94
CC95
C096
CC97
C098
13
200
201
202
203
2C5
2C6
2C7
208
212
209
211
210
14
301
3CO
15
4C1
905
402
J*l
JJ*0
Jl- JOUT(J)
IF( Jl.GT. NDSJ
JJ»JJ * 1
BJ = DCOHPU1 I *
CCJl) = DFCIN(Jl)
IFU.GE.K } GC TC
J=JM
GO TO 200
J2=l
BJ= 10**20
J22^ JOUT(J2)
TEMP= PCTC(Ji)*OISTPD
-------
Figure I.I FORTRAN LISTING OF FACILITY SELECTION MODEL (Cont.)
CC99
0100
0101
0102
0103
0104
0105
0106
0107
0108
CIC9
0110
0111
0112
0113
0114
C115
0116
0117
0116
0119
0120
0121
0122
0123
0124
C125
0126
0127
C128
0129
0130
0131
0132
4C3 J=l
AKMIN=10**2C
404 IFfAKU,J).LT.AKMIN- EPSL) GO TO 405
406 IF(J.GE.K ) GO TO 408
4C7 J=J*1
GC TO 404
4C5 AKMIN = AKIItJI
JTEMP(I )= JOUT(J)
JIND=J
GO TO 406
408 TMP *. AKMIN* CII) * TMP
J3= JIND+1
IFU3.GT.K) GO TO 4C9
903 TT= ABSI AK(I,J3) - AKMIN)
IF( TT.LT. EPSL) JEQUAL(I) = 1
IF(J3.GE.K) GO TO 409
J3- J3+1
GO TO 903
409 IFtI.GE.NS) GO TO 411
410 1=1+1
GO TO 4C3
C MIN AK(I.J) COMPUTED AND IS LOCATED IN TMP
411 AMP=0
00 500 1 = 1,K
Jl= JOUTtI)
IFt Ji.GT. NDS) GC TC 501
AMP= AMP-i- DFC(Jl)
GO TO 500
5CI AMP=AMP <• PFCtJl)
500 CONTINUE
C SUP AJ CCMPLETEC ANC IS IN AMP
TEMP = AMP + TMP
16 IFITEMP.GT.tAMIN+EPSLl) GO TO 4
WPITE(6t5001J
9990 FORHAT(//« THE FACILITIES BEING CONSIDERED ARE «t2CI4)
-------
Figure I.I FORTRAN LISTING OF FACILITY SELECTION MODEL (Cont.)
0133
C134
0135
C136
C137
0138
C139
0140
C141
Cl«2
0143
0144
0145
0146
0147
0148
C149
0150
0151
0152
0153
0154
0155
0156
C157
0158
0159
0160
0161
0162
0163
0164
0165
0166
C167
DO 602 1 = 1 ,NS
JPREQU)* JEGUALII)
602 JPRINT( I)= JTEHPUl
17 A*IN= TEMP
KOUT = K
DC 700 J=1,K
700 JOUTT!J>* JCUT!J)
JJ=0
J=l
8CI Jl* JOUTTIJ)
8C2 IF! Jl.GT. NDS) GO TC 8C7
803 JJ = JJ + 1
804 MUTE(6,850I Jl
850 FORMAT! • DISPOSAL SITE NUMBER =•, 13 )
805 IF(J.GE.K) GO TG 853
8C6 J=J+1
GO TO 801
807 J2*l
808 BJJ =10**20
8C9 J22 » JOUTTU2)
810 TEMP= PCTO!J1)* D ISTPD
811 IFUFMP.LT.8JJ-EPSL) GC TC 812
813 IFIJ2.GE. JJ) GO TO 815
814 J2« J2* 1
GO TO 809
812 JOUMP » J22
BJJ=TEMP
GO TO 813
815 WRITE(6,851) Jl.JDUMP
851 FORMAT! • PROCESSING PLANT NO.
INSERT BLOCK A
900 J2= JDUMP + I
902 IFIJ2.GT.JJ) GC TC 805
J22= JOUTTIJ2)
TEMP= PCTO!JU* DISTPD! Jl,J22) * DDC1J22)
TMBJ= ABS< TE*-P - BJJ )
DFCIN!J22)
•,13,5X,"DISPOSAL SITE NO. =«,I3 I
OFCIN!J22)
-------
Figure I.I FORTRAN LISTING OF FACILITY SELECTION MODEL (Cont.)
00
0168
0169
017C
0171
C172
0173
0174
0175
0176
0177
0178
0179
0180
0181
0182
0183
0184
0185
C186
0187
C188
IF( TMBJ.LT.EPSL) HRlTEC6f85ll J1.J22
IF( J2.GE.JJ) GO TO 805
J2= J2 * 1
GO TO 902
853 kRITE(6,904l AM IN
9C4 FORMAT!• MINIMUM COST =•, E12.6//)
WRITE! 6,8 52) ( I, JPRINTU ) f JPREQC 1I ,1-l * NSI
852 FCRMATUOX,'SOURCE KG. FACILITY ASSIGNMENT
*TEST»/(115,I2C,125)1
GO TO 4
4141 IF(K.GE.N) GO TO 10
9 KsK+1
GO TO 5
10 WRITE(6 ,5001»
WRITE(6t9970)
9970 FORMAT (60X f« COMPLETE COST MATRIXS///)
00 9981 I*lfNS
9981 URITE(6,9S62) ( I ,J,AK(I,J),J=I,N)
9982 FCRMAT(/,5(2X,I4,2X,I4,2X,E11.5))
5000 CONTINUE
STOP
END
EQUALITY
-------
Figure 1.2 SAMPLE OUTPUT OF FACILITY SELECTION MODEL
THE FACILITIES BEING
DISPOSAL SITE NUMBER
DISPOSAL SITE NUMBER
DISPOSAL SITE WJMBFR
PROCESSING PLANT NO.
CONSIDERED ARE
= 1
= 2
= 3
= A CISPCSAL
MINIMUM COST =0.385A22E 07
SITE NO. =
SOURCE NO.
I
2
3
A
5
6
7
8
9
10
11
12
13
IA
15
16
17
18
19
7Q
21
22
23
?A
2*5
26
?7
2fl
?9
30
31
32
33
3A
35
36
37
3*
FACILITY
A
A
A
A
A
A
A
A
1
1
1
A
A
A
A
A
A
1
1
A
A
1
1
1
I
1
1
1
1
1
I
1
1
I
1
1
1
1
ASSIGNMENT
EQUALITY
0
C
0
0
0
C
0
C
0
0
0
C
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C
0
0
0
0
0
0
0
0
C
0
0
TFST
1-9
-------
Figure 1.2 SAMPLE OUTPUT OF FACILITY SELECTION MODEL (Cont.)
39 I 0
40 1 0
41 I 0
42 I 0
43 1 0
44 1 0
45 1 0
46 1 0
47 1 C
48 1 C
49 1 r
50 1 0
51 1 0
52 1 0
53 1 0
54 1 0
55 1 ' 0
56 I 0
57 1 C
58 1 C
59 I 0
60 1 0
(SI 1 0
62 1 0
63 1 0
64 1 0
65 1 C
66 I 0
67 1 0
68 I C
69 I C
70 1 0
71 1 C
7? I 0
73 3 C
74 3 0
75 2 0
76 3 0
77 ? C
78 I 0
79 I 0
80 2 0
81 ? 0
82 1 C
83 1 0
84 1 C
85 1 C
1-10
-------
Figure 1.2 SAMPLE OUTPUT OF FACILITY SELECTION MODEL (Cont.)
36 1 0
87 1 0
88 i 0
89 1 0
90 1 0
91 1 0
92 1 0
9? 1 C
94 I 0
95 1 °
96 2 0
97 2 c
98 2 0
99 2 0
100 2 °
101 3 °
102 3 0
103 3 *
104 3 C
105 3 0
106 2 0
107 2 0
108 3 0
109 3 0
110 3 0
1-11
-------
APPENDIX J ANALYSIS FOR FACILITY SELECTION OVER TIME
J.I
1.
2.
3.
4.
Assumptions
All initial introduction and subsequent expansion of processing
plant capacity is maintained indefinitely into the future.
Both processing plant and disposal site costs are dichotomized into
fixed and rate-dependent (or so-called "operating") costs.
For processing plants, fixed costs include mainly: initial
capital outlay (if any), debt retirement, maintenance, and
periodic major overhaul. Each capacity increment introduced
at a time interval t will contribute a specified fixed cost
schedule into the future which might appear as in Fig. J.I.
For disposal sites, fixed costs include initial capital
outlay (if any) and debt retirement - these will be dependent
on the specific site - initial capacity, location, etc. -
and will be scheduled from time of initial activation of the site.
COST
INITIAL
CAPITAL
OUTLAY
MAINTENANCE + OVERHAUL
LO V1 V2-
Figure J.I PROJECTED FIXED COST SCHEDULE
TIME INTERVAL
J-l
-------
5. For both processing plants and disposal sites, operating
costs will be assumed to be proportional to current rate of
operation.
6. Transportation costs are assumed to be proportional to
quantity transported.
7. All dollars are adjusted to present levels, i.e., inflation
is neglected; this seems to be the reasonable approach when
combining costs over an extended time period.
8. Each processing plant has associated with it a specific, time-
invariant volume reduction factor.
i
9. Each disposal site has associated with it two specific, time-
invariant reduction factors, for unprocessed and processed
material, respectively.
10. As in the static model, the quantity from any source area
or the output from any processing plant is not permitted to be
subdivided and goes to a single destination during each elemental
time interval.
J.2 Input Parameters and Definitions
1. Total time period consists of T elemental intervals, each T years
in duration, and designated by variable t = 1,2,...,T.
2. There are I source areas designated by i = !,...,!,
with projected output q. at time interval t. (All mater
are measured as cumulative total for a 7"-year interval.)
J-2
-------
3. There are N possible processing plants designated by j=l,...,N,
each with:
processing capacity: Q • t = 1-M, 2-M,..., T*
actual processing level: q • t = 1,...,!
reduction factor: r. (0
-------
operating: q£t * dk /irfct; t = 1,...,T
(V^ V^t, irkt measured in units after reduction.)
Transportation costs from i source to j destination
(j*l,...,N+K) per unit load: S..,
from j* processed plant (j = l,...,N) to kth disposal site (k*l,...,K)
per unit load: T...
jk
Allocation variables (representing control variables for optimization):
0;i source not sent to j p.p. or d.s. at time t [ i=l,...M
X. = . (
l;i source sent to " " " " " " "J j = l,.. .N+K
-,.^
jkt
fO;jth p.p. not sent to kth d.s. at time t 1 j=l,...,N
l;jth p.p. sent » " " ' J k=l,...,K
7. Projected population of region under service:
Pt ; t=l,...,T
8. Derived quantities:
Actual processing level at j p.p. at time t:
Actual operating level at k site at time t
Time of activation of k disposal site
t. = min -S.; t such that
J-4
-------
Total fixed cost at time t:
f
Total operating cost at time t
rJ K x rl+K
*
sij "it *ijt
J.3 Conditions for Solution
1. Constraints for Step 2 optimization (sequentially for each t » 1.....T)
N+K
X
; i « 1,. ...
Z yikt 2 i
k*l J
; j = I,...,N
-
it '
Jt j = 1.....N
= V - v
k,t+l kt kt
V ^ v
vkt - vkt
= L f • » • j Jv
2. Objective function for Step 2 optimization;
Minimize Ht over £ x^, yjkt, Q^ } sequentially for each
t = 1,2,...,T subject to the above constraints
J-5
-------
3. Objective function for Step ^ optimization
T
h = Z [ H / P ]
t-i l l
Minimize h over all permissible variations (subject to above Q and V
constraints) in the times of destination changes for source area
quantities and processing plant outputs, maintaining these times of
destination changes in original semi-strict order corresponding to
the Step 2 optimum solution. In this process x.. and y..
XJ * J Kt
follow automatically and continue to satisfy constraints;
Q. will likely require readjustment.
J'6
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