COMPREHENSIVE STUDIES OF
Third Annual Rf port

-------

-------

-------

-------

-------

-------
   COMPREHENSIVE  STUDIES  OF SOLID WASTE MANAGEMENT
                  Thi rd  Annual  Report
This interim report  (SW-lOrg)  on work performed under
            Research Grant No.  EC-00260
            (formerly Grant No.  UI-00547)
          to the University  of California
           was prepared by C.  G.  GOLUEKE
and has been reproduced as received from the grantee.
        U.S. ENVIRONMENTAL PROTECTION AGENCY
                       1971
               onn^rtcJ. r'r~tection Agency
          Lilr:ry, I '.-•-"> v
          1 Berth \7-x".:•.-• l-r^ve
          Chicago, Illinois  60606

-------
                               FOREWORD

     At the time of passage of the Solid Waste Disposal Act (PL 89-272)

in 1965, few, if any, studies of a truly comprehensive nature had been

undertaken to develop solutions to problems in all aspects of solid

waste management.  Although earlier research studies have made

invaluable contributions to knowledge in the field, they tended to

focus primarily upon discrete facets of the total solid waste problem.

     The present report represents the continuation of the first major

effort to examine the solid waste problem from the standpoint of systems

analysis.  An overall solid waste generation and evaluation model was

developed, demonstrating interrelationships between land use, technology,

economics, population, and other system elements.  Practical implications

were drawn from this model, as they relate to planning, public health,

and application of technology.

     A further example of the systems approach to solid waste management

is ^iven in the final report of a Solid Waste Management demonstration

project, A Systems Study of Sol-Id Waste Management in the Fresno Area

CPublic Health Service Publication No. 1959).
                                    --RICHARD D. VAUGHAN
                                      Assistant Surgeon^ General
                                iii

-------

-------
                               TABLE OF CONTENTS
Chapter                                                                       Pa6e

     T.   INTRODUCTION   	          1

            Weed for Study 	          1

            Objectives of Study 	          2

            Organization for Study	          3

            Authorship Credits	          3

            Acknowledgments	          3

   II.   PLANNING ABD ECONOMICS 	          ^

            Review of  Work to Date — Objectives and Rationale	          k

              Development of Structural Models for Studying
                the Existing Relationships Among Various
                Types  of Solid Wastes Generation and Relevant
                Economic, Demographic,  and Land-Use Information	          k
              Development of Procedures to Estimate Pertinent
                Quantities of the Various Types of Solid Wastes
                Generation Through Definition of Appropriate
                Sources of Wastes (Generator) and Corresponding
                Spatial and Functional Boundaries with Reference
                to a Selected Study Area	
              Development and Improvement of Solid Waste
                Multipliers and Their Composition "by Detailed
                Levels  of Economic Activity and Waste Sources.

              Survey of Engineering and Economic Aspects of
                Current Methods of Transfer and Disposal of
                Solid Wastes	
              Analysis  of Private and Public Expenditures in the
                Solid Wastes Industry — Theoretical and Empirical
                Issues  with Reference to a Metropolitan Region....
              Application of Network flow Model for Finding
                Short-term Solution Assuming Landfill as the
                Ultimate Disposal Method	
              Regional Economic Forecasts of Employment,  Income,
                Population,  and Land Use Through Input-Output and
                Other Related Studies	

-------
              TABLE OF CONTENTS (Continued)

                                                                  Page

  Technical Changes in Existing Methods and Consideration
     of Nev Methods of Transfer and Disposal for Future
     Management of Solid Wastes	          7
  A Systems Analysis Approach to Solid Wastes
     Management	
  Implementation of Proposed Regional Solution,
     Recognizing the Changes Caused by Increasing
     Demand for an Overall Solid Wastes Management
     Program, Jurisdictional Conflict, Efficiency and
     Equity Criteria Stemming from Different Pricing
     Mechanisms, and, Finally, Horizontal Integration
     With Other Similar Urban Services Under a Regional
     or Metropolitan Government	
Economic and Planning Aspects of Technology.
  Summary Description of Features of Conventional
     Technologies Pertinent to Economic Analyses	         12

    Landfill	         22

    Incineration	,	         12

    Composting	         15

  End Products of Conventional Disposal Methods	         16

    Sanitary Landfill	         l6

    Incineration	         16

    Composting	         18

  Comparative Costs of Conventional Disposal Methods	         18

    Landfill	         19

    Incineration	         19

    Composting	         20

  A Study of Variations in Landfill Costs	         20

    Theoretical Background	         20

    Empirical Study	,	         22

    Independent Variables	         22

  Choice of Conventional Method	,	         2^

  Marginal Cost	         25

  Summary Description of Experimental Technology	         25

    Compaction	         25

    Wet Oxidation	         25
                              vi

-------
              TABLE OF CONTENTS (Continued)


                                                                  Page

    Anaerobic Digestion	         26

    Biological Fractionation	         28

    Discussion	         28

Analysis of Private and Public Expenditures in the
   Solid Wastes Industry — Theoretical and Empirical
   Issues with Reference to a Metropolitan Region	         JO

  Need for Public Concern	         30

  Cost Study Involving the Oakland Metropolitan Area	         31

  Resources Diverted to the Solid Waste Industry	         31

  Cost Differences Between Public and Private Agencies
     and Among Collection Regions	         32

  Cost By Function	         32

  Costs by Quantity of Wastes Handled	         32

  Urban Planning Purposes	         32

  Expected Cost Accounting and Data Collection
     Problems	         32

  Some Economic Considerations	         33

  Tentative Data Collection Procedures	         36

    General Considerations	         36

    Data Collection for Franchised Firms	         37

    Data Collection for Firms and Individuals Transporting
      to Site	         39

  The Empirical Study of Oakland Metropolitan Region	         39

    Description of the Study Region	         hi

    Quantity of Wastes Generated in the Study Region	         ^5

A Method of Optimal Site Selection as Applied to
   Solid Waste Management	         55

  General Remarks	         55

  Introduction	         55

  Modifications of the Problem	         56

  Procedure	         58

  Application of the Modified Algorithm to Solid Waste	         59

    Selection of Disposal Sites and Waste Generating Points         59
                             vii

-------
                        TABLE OF CONTENTS (Continued)

lapter                                                                      Page

              The Cost Matrix,  C. .  	          60
                                •^ J
              Solid Wastes:   Generation points (i) and amounts
                generated (W. )	,	          60

              Remaining Capacity Vector	,	          62

              Discussion of  Results	          62

 III.   OPERATIONS RESEARCH IN  SOLID WASTES  	          66

          Model for Forecasting Waste Loads	          66

            The Leontief Model Augmented "by  the Solid Waste
               Disposal Service Industry	          66
            A First Approximation of Total Wastes.
            Ten-Year Forecast of Solid Wastes for the Nine-County
               San Francisco Bay Region	
            Extensions and Refinements	          71

          Optimal Strategies in Capacity Expansion	          72

            Cost Structure	          75

            First Part of Analysis-Infinite Horizon	          75

            Findings	          75

            Second Part of Analysis — Finite Planning Horizon	          77

  IV.  ANAEROBIC  DIGESTION 	          82

          Introduction	          82

          Objectives	          82

          The Investigation	          83

            Principles Involved	          83

              Kinetics of Solid Waste Digestion	          83

              Methods	          86

            General Materials and Methods	          87

              Preparation of Raw Materials	          87

              Animal Manures	          87

          First Experimental Series — Digestion of Newspaper	          88

            Procedure	          88

            Results	          89
                                      viii

-------
                      TABLE OF CONTENTS  (Continued)

ipter                                                                      Page

        Second Experimental Series — Digestion of Grass  Clippings..         95

          Procedure	         95

          Results	         95

        Third Experimental Series — Digestion of Animal  Manure	         99

          t^rocedure	         99

          Results	        100

        Fourth Experimental Series — Digestion of White  Fir Wood...        101

          Procedure	        107

          Results	        107

        Fifth Experimental Series — Digestion of Composite
            "Synthetic " Refuse	        110

          Formulating the Synthetic Refuse	        113

          Experimental Procedure	        11^

          Results	        115

          Kinetics of the Digestion Rate of the Cellulose in the
             "Synthetic" Refuse	        115

          Discussion	        121

          Solids Reduction	        123

          Efficiency of Digestion of the "Synthetic" Wastes	        123

        Discussion	        128

          Digestion of Urban Refuse	        128

          Kinetics of Digestion	        1J3

          Digestion of Organic Refuse and Animal Manure	        133

          Economics of Solid Waste Digestion	        13^

        General Conclusions	        ijk

 V.   BIOLOGICAL FRACTIONATION  OF SOLID WASTES  	        135

        Introduction	        135

        Experimental Studies in Enzyme Production	        135

          General Procedure	        135

          Experiment 1.  Glucose Substrate with pH Control	        136

          Experiment 2.  Cellulose Substrate Without pH  Control....        138
                                     ix

-------
                         TABLE OF CONTENTS (Continued)

                                                                             Page

             Experiment 3-   Cellulose Substrate with pH Control .......        l4l

             Experiment k.   Isolation of Cell Growth and Enzyme
                Production ............................................
             Summary of Experimental Results ..........................        2.k6

           Economic Analysis ..........................................        lM6

             Plant Design and Cost Analysis ...........................        1^6

             Description of the Process Design Basis ..................        IkJ

             General Process Description ..............................        1^7

             Cost Factors .............................................        114.9

VI .    INCINERATION — PYROLYSIS- COMBUSTION  ..........................        155

           Introduction ...............................................        155

             Rationale ................................................        155

             Ob j ecti ves ...............................................        156

           Pyrolysis- Combustion Experimental Unit .....................        156

             Pertinent Considerations in Construction of the
                Experimental Unit ........ . ............................        156

             Experimental Unit Construction ...........................        157

               First Stage ............................................        157

               Second Stage ........................... , ...............        l6l

           Research Program ...........................................        l6l

           Analytical Methods ................................ , ........        l6k

           Laboratory- Scale Pyrolysis of Solid Wastes .................        16^

VII.   WET OXIDATION OF ORGANIC  SOLID WASTE MATERIALS  ...............        165

           Introduction ...............................................        165

             Objectives ...............................................        165

             Rationale ................................................        165

           Research Program ...........................................        165

             Phase I — Determination of Basic Reaction Relationships..        165

             Phase II — Oxidation of Organic Solid Waste Materials....        168

             Phase III - Process Design ...............................        168

           Experimental Work ..........................................        168

-------
                         TABLE OF CONTENTS (Continued)

Chapter

 VIII.    SUMMARY	        17

           Introduction	        17^

           Planning and Economies	        17^

           Operations Research	        176

           Anaerobic Digestion	        176

           Biofractionation.	        177

           Pyrolysis-Combustion	        178

           Wet Oxidation	        178


APPENDICES

    A.   Application of Nigam's Algorithm	        l8l

    B.   Waste Generation in the Nine-County San Francisco Bay Area....        186

    C.   Remaining Capacity of Solid Waste Disposal Sites in the
          Nine-County San Francisco Bay Area	        195


REFERENCES	        199
                                       XI

-------
                                  LIST OF TABLES


Table                                  Title                                  Page

  1.    Composition and Analysis of an Average Municipal Refuse	    10

  2.    Analysis of Composite Refuse	    11

  5.    List of Equipment Required for Landfill	    15

  4.    List of Equipment for Continuous Incineration	    l4

  5 •    List of Equipment Required for Composting	    17

  6.    Summary of Data on Landfill Costs	    25

  7 •    List of Equipment for Wet Oxidation Process	    27

  8.    List of Equipment for Anaerobic Fermentation Process	    28

  9.    List of Equipment for Biological Fractionation Process	    29

 10.    Combinations of Cost Sources	    58

 11.    Format for Tabulation Collection and Transportation Expenditures....    ^0

 12.    Format for Tabulating Disposal Site Expenditures	    4l

 15.    Oakland-Berkeley Metropolitan Area — Population and Housing	    ^2

 1^.    Employment Data	    k-J

 15-    Agencies and their Functions	    kh

 l6.    Estimates of Wastes Received at the San Leandro Marina  Site	    4-5

 17 •    Site Estimates of Wastes	    h-6

 18.    Summary of Waste Types	    hi

 19«    Estimation Procedures and Estimates of Municipal Wastes	    1+9

 20.    Agricultural Wastes	    50

 21.    Alternate Estimates of Waste Generated by Commercial  Organizations
           and Services	    51

 22.    Alternate Estimates of Wastes Generated by Construction and
           Demolition	    52

 25.    Manufacturing Wastes	    53

 24.    Summary of all Wastes Generated in the Oakland Metropolitan Area....    5^

 25.    Transportation Times for Collection	    6l

 26.    Output of the Program Tinder the Condition that One  New  Site be  Opened
           for Each Existing Site Closed Down	    65
                                        XI1

-------
                            LIST OF TABLES (Continued)
Table                                  Title
 27-    Total Waste by Sector (28) — Nine-County San Francisco Bay Region,

28.
2Q.
30.
51.
32.
^4
35-
36.
37-
38.
39-
40.

1966 	
Aggregated Demand Vectors for Nine -County San Francisco Bay Region. .
Forecasted Output (Dollars) for the Nine -County San Francisco

Results of Multiple Regression Analysis of Cost Data on Incinerators

Optimal Policy for a 200-Period Problem with Demand Initially 1,200
Optimal Policy When the Demand Initially is 1,200 Tons Per Day and
Gas Production Per Pound of Volatile Solids Introduced in the
Efficiency of Newspaper Digestion Based on Comparison With Control..
Destruction of Newspaper Cellulose Based on Comparison With Control.
Composition of Gas From Cultures Receiving Newspaper and Sludge and
Summary of Results Pertaining to the Digestion of Newsrai>er 	
69
70
72
73
74
76
76
78
70
80
QO
91
91
94
06
 42.    Gas Production Per Unit of Volatile  Solids Added to  the Digester
           Receiving Grass Clippings	    99

 43.    Composition of Gas From the Digester Receiving Grass Clippings	   100

 44.    Summary of Results Obtained in the Experiments on the Digestibility
           of Grass Clippings	   101

 45.    Gas Production Per Unit of Volatile  Solids Added by  a Digester
           Receiving Steer Manure	   102

 46.    Solids Reduction in the Digestion of Animal Manure	   103

 47.    Acid-Base  Equilibria in the Digestion of Animal Manure	   104

 48.    Composition of Digester Gas in Experiments on the Digestion of
           Manure	   105

 49.    Summary of Results of  the  Experiments on Digestion of Manure	   106
                                      xiii

-------
                            LIST OF TABLES (Continued)


Table                                  Title

 50.    Apparent Destruction of Cellulose in the Digesters  Receiving Wood...    109

 51-    Daily Input of Cellulose to Digesters Receiving Wood ................    110

 52.    Summary of Real and Apparent Results of the  Experiments  on the
           Digestion of White Fir ........... , ................... , ...........    112

 53.    Estimating the Dry Weights of the Components of the "Synthetic"
           Refuse [[[    113

 514-.    Composition of Feed Mixture of "Synthetic" Refuse and Raw  Sewage
           Sludge [[[    11^
 55.    Loading to the Digester Receiving "Synthetic"  Refuse
 56.    Efficiency and Performance of the Digesters  Receiving "Synthetic"
           Refuse and Sewage Sludge .........................................    116

 57.    Acid-Base Equilibria in Digesters Receiving  "Synthetic"  Refuse ......    117

 58.    Composition of Gas From Digesters Receiving  "Synthetic"  Refuse  and
           Sewage Sludge [[[    118

 59.    Cellulose Destruction and Kinetic Data for the  Digestion of a
           Mixture of "Synthetic" Refuse and Sewage  Sludge ..................    119

 60.    Kinetic Constants for the Rate of Anaerobic  Decomposition of the
           Cellulose in Refuse ..............................................    122

 6l.    Percentage Reduction of Solids in the Digestion of  "Synthetic"
           Refuse [[[    125

 62.    Solids Concentration in the Effluent of Digesters Receiving a
           "Synthetic " Refuse and Sewage Sludge .............................    126

 63.    Efficiency of the Digestion of the "Synthetic"  Refuse ...............    127

 64.    Summary of the Results Pertaining to the Digestion  of the "Synthetic"
           Refuse [[[    129

 65.    Summary of Digester Efficiencies with Respect to Urban Organic  Solid
           Wastes [[[    130

 66.    Summary of Results of Studies on the Kinetics of Digestion ..........    131

 67-    Summary of Results of Studies on the Digestion  of Organic Refuse
           Component and Animal Manure Combinations .........................    132
 68 .    Enzyme Activity in Relation to Substrate and pH Control

-------
                            LIST OF TABLES (Continued)


Table                                  Title                                  Page

 71.   Costs for Medium on Which to Grow T. viride  on Commercial Scale	    152

 72.   Summary of Fixed Capital Costs  for a Ten-Ton Per Day  "Biofractionation"
          Plant	    152

 73-   Major Equipment for a Ten-Ton Per Day  "Biofractionation"  Plant	    153

 7^.   Cost Reductions From Process Improvements	    15^

 75.   Revised Material Balance for Wet Oxidation Reactions  of White Fir
          Wood	    170

 76.   Revised Oxygen Consumption and  Carbon  Dioxide —  Carton Monoxide
          Formation in Wet Oxidation Reactions  of White Fir  Wood	    171

 77-   Energy Balance for Wet Oxidation Reactions of White Fir Wood	    172

 78.   Organic Chemical Yields in Wet  Oxidation Reactions of White Fir Wood.    173
                                        XV

-------
                                  LIST OF FIGURES


Figure                                 Title

   1.    Relation Between Marginal Cost and Average Cost	    36

   2.    Efficiency of Newspaper Digestion	    92

   3.    Acid-Base Equilibria in Newspaper Digestion	    93

   k.    Efficiency of Grass Clippings Digestion	    97

   5.    Effect of Grass Clippings on Digester Acid-Base Equilibria	    98

   6.    Gas Production Efficiency Relative to Added Volatile Solids	   108

   7.    Acid-Base Equilibria in White Fir Digestion	   Ill

   8.    Growth Associated Plot	   123

   9.    Trichoderma viride Grown on Glucose Substrate and with pH Level
            Controlled	   137

  10.    Growth of T. viride on Glucose Substrate Without pH Control	   139

  11.    Growth of T. viride on Cellulose Substrate Without pH Control	   l40

  12.    Growth of T. viride on Cellulose Substrate With pH Control - Run 1..   1^2

  13.    Growth of T. viride on Cellulose Substrate With pH Control - Run 2..   1^3

  Ik.    Growth of T. viride on a Mixed Substrate of Cellulose and Glucose
            With pH Control - Run 1	   ihh
  15.    Growth of T. viride on a Mixed Substrate of Cellulose and Glucose
            With plfControl - Run 2
  16.    Process Flow Scheme for the Continuous Enzymatic Saccharif ication
            of Cellulose [[[   lit-8

  17 •    Pyrolysis -Combustion Unit ...........................................   158

  18.    Configuration of Pyrolysis -Combustion Unit When Processing Solid
            Wastes [[[   159

  19 .    First -Stage Pyrolys is Reactor .......................................   160

  20 .    Second -Stage Pyrolysis Reactor ......................................   162


-------
                                I.  INTRODUCTION


WEED FOR STUDY

        Need for comprehensive studies of solid waste management such as herein
reported is the natural outgrowth of a traditional American unconcern for the con-
servation of resources and an unconscious indifference to what is now called "the
environment."  The result, described in greater detail in the first of this series
of annual reports [4], was that each local jurisdiction called upon technology to
perform only the most rudimentary of tasks—pick up, haul, and deposit-until human
communities became so complex that even these simple tasks were all but impossible.
The collection system became uneconomical by any comparative standard, traffic and
transportation made hauling difficult, no plans for unloading inside the boundaries
of the jurisdiction had been made, and neighboring land areas faced the same unsolved
problems.  Moreover, the effect of urbanization of human society spilled over onto
land beyond the city's limits.  This led to attempts to control the environment by
zoning and limited piecemeal land-use management measures which constrained the
freedom of decision of private enterprises and so caused industrial, agricultural,
and commercial solid wastes to join municipal refuse as a matter of public concern
and responsibility.  Burning to reduce volume of wastes was found to be at best a
primitive process when concern for the air resource was thrust into the problem of
environmental quality.

        Within a rather brief period of time society became uneasy over the possible
consequences of resource exploitation and of the impact of man on his own environment.
It became painfully clear that in the matter of solid waste management no one really
knew how much of what is present in solid wastes or where it occurs in the community;
the resource potential of wastes had not been evaluated; technology had never been
asked to solve any of the emerging problems within an environmental or conservation
framework; society was organized to deal with regional problems only on a fragmented
local basis, and was institutionalized to deal with the quality of air, water,  and
land resources as discrete and essentially unrelated problems; systems had emerged
historically from sheer probability, or improbability; and the public, although
showing signs of concern for the environment or a high conceptual plane, had little
regard for their own solid waste nor applause for those who took care of it.  Clearly
there was a need for bringing together a team of planners, economists, health special-
ists, systems experts, engineers, and technologists to explore ways to overcome in
a systematic and organized fashion the consequences of overlong neglect of the problems
associated with "solid wastes."

        During the period covered by the report herein presented, several changes
occurred relative to the need for study.  For the most part they served only to
increase the urgency of the need, but in a few cases a change in emphasis emerged.
On the national scene citizens tended to group solid wastes with air and water
pollution problems in a single category of insult which defiles the "total environ-
ment."  Concern for the total environment led directly to concern for the ecosystem
of nature, and so the public came to ascribe to solid wastes a greater role than it
merits in damaging the "ecosystem."  This added to the problem of solid wastes an
aura of crisis,  the effect of which is not yet clearly evident.  It did, however,
heighten the concern of citizens for the effect of man on the environment.  Taking
a more realistic approach, most public agencies gave first priority to the effects
of environment on man.  In this context the aspects of the solid waste problem
outlined in preceding paragraphs came into sharp focus and raised the immediate
question of whether a need for study was secondary to a need for action.  This
question immediately generated another question:  "What are the attainable goals of
action?"  If technology is to be asked to do rudimentary things — pick up, transport,
and deposit — there is but limited progress that can be made by action toward solving
the solid waste problem in an environmental and resource context.  This self-evident
and unsatisfactory answer made more urgent a need for practical technological

-------
solutions of a more sophisticated nature.  The response was a rash of simplistic
solutions by 'far out1 new concepts which during the year herein reported lost much
of their luster when confronted with the complexities and realities of the solid
waste problem.   Thus was emphasized a need to discern more clearly what action is
necessary and to "be cognizant of research on new technologies.

        Both citizen and official objectives of resource conservation and environ-
mental control generate a need for recycling of resource value.  Thus there is still
a need at this  late hour to find out how much of what resource is being wasted; at
what point in time will wastage of one resource value cease in favor of wastage of
another; and when on a time scale will certain residues become valued as resources.
Associated with this question is that of the technology of recycle of some resource
values.  Here a need for study exists in the case of some materials and for action
in the case of others.  An overall need therefore exists for asking technology to
do more sophisticated things, and it can be argued that research on some of the
traditional techniques needs de-emphasis in favor of that related to resource recycle.
Here the need for study is urgent.

        In the realm of jurisdictional and institutional arrangements, the problems
are well recognized.  The need for action is clear, but how that action can be
brought about within existing political, social, and cultural constraints is still
in need of study.

        Based on the foregoing analysis and rationale it is concluded by the authors
of the report herein presented that the need for action resulting from neglect of
the problem of managing solid wastes until it reached crisis proportions, makes more
urgent, rather than redundant, a need for study of jurisdictional, planning, economic,
and systems managements as a blueprint for action; and generates a need for techno-
logical research along the road to recycling rather than destroying resource residues.


OBJECTIVES OF STUDY

        Pursuant to the rationale set forth in the Need For Study, the general
objective of the study was to make a significant contribution to a resolution of the
problems which created the need, through a multidiscipline research program.  Pursuant
to this general goal,  the research program herein reported was directed to several
more specific objectives.  As noted in the Second Annual Report [1] these included:

    1.  To bring the competence of people in the wide variety of disciplines
        involved in planning, financing, and administering a community into
        effective combination with that of engineers and environmental health
        specialists in seeking solutions to problems in solid wastes manage-
        ment which are technically sound, economically feasible, and politically
        and socially acceptable.

    2.  To bring the techniques of modern operations research to bear upon the
        organizational problems of managing solid wastes on an areawide or
        communitywide basis; and on the physical and logistic problems of
        collecting, transporting, and disposing of wastes.

    3-  To seek through experiments and other research techniques improve-
        ments in conventional methods of wastes disposal and the development
        of new  procedures for reclaiming or recycling fractions of the refuse
        mass.

    k.  To identify and seek answers to problems involving man's health and
        well-being that may be associated with solid wastes and related to
        his use of land, water, and air resources.

    5.  To develop, through participation in research, greater understanding
        and knowledge on the part of engineers, planners, administrators,
        economists, public health specialists, and others who are confronted
        with the problem of solid wastes management in the course of their
        professional service to the modern urban-industrial-agricultural
        community.

-------
    6.  To insure, through close coordination and effective  communication
        with public and private agencies, the pertinence of  research to
        real problems and the prompt availability of the results  of research
        to professional practitioners.


ORGANIZATION FOR STUDY

        Five faculty members, namely Professors P.  H. McGauhey, I. B. Tabershaw,
B. D. Tebbens, S. A. Hart, and W. J. Kaufman, representing the  Sanitary Engineering
Research Laboratory of the College of Engineering and School of Public Health  on
the Berkeley Campus and the Department of Agricultural Engineering on the Davis
Campus of the University of California, were initially responsible for the overall
management of the project.  However, on 1 July 1969 Professor P.  H. McGauhey retired
from the University and thereafter served only in an advisory capacity.  He was
replaced as Principal Investigator of the Project by Dr. Clarence G. Golueke,  Chief
Biologist of SERL and Coordinator of the study since its inception.  In the conduct
and coordination of the research program he was assisted by  additional faculty
members and professional research personnel who took responsibility for various
specific aspects, including:

                Professor C. R. Glassey, Operations Research
                Dr. S. A. Rao, Planning and Economics
                Dr. D. L. Brink, Forestry
                Professor C. R. Wilke, Chemical Engineering
                Professor P. B. Stewart, Mechanical Engineering

        Mr. Stephen A. Klein divided his time between assistance  to Dr. Golueke and
conduct of research on the anaerobic digestion of solid wastes.   In the 1969-1970
period a total of 18 graduate students participated in the program.


AUTHORSHIP CREDITS

        Authorship credit for individual chapters of the report is due the following
participants in the project:

        Need For Study - P. H. McGauhey

        Planning and Economics - S. A. Rao

        Operations Research - H. Stern, A. Nigam, E. Lofting, and C. R. Glassey

        Anaerobic Digestion - S. A. Klein and D. B. Chan

        Biological Fractionation - R. Rosenbluth, G. Mitra,  and C. R. Wilke

        Wet Oxidation - J. Bicho and D. L. Brink

        Pyrolysis-Combustion - D. L. Brink


ACKNOWLEDGMENTS

        This work was supported in part by Public Health Service  Grant No.  EC 00260-0^
from the Bureau of Solid Waste Management, U. S. Department  of  Health, Education,
and Welfare.

-------
                           II.  PLANNING AMD ECONOMICS


REVIEW OF WORK TO DATE-OBJECTIVES AND RATIONALE

        Since the writing  of the Second Annual Report [l],  the research work of the
Planning and Economics team has "been directed toward the achievement of substantive
progress in several phases of its intended activities.   Thus the primary goals and
specific objectives have been brought under sharper focus in the light of experience
gained in the past three years.  This, in turn, has made it possible to assess real-
istically the potential of laudable goals and of their implications in terms of
practical applications, and thereupon to identify various research aspects which
could be of benefit in attaining the goals of the project as a whole.

        After carefully examining the original plans, the major objectives discussed
in the succeeding paragraphs were formulated as a basis for evaluating progress made
thus far, as well as for setting up a definite plan of action for future research
into various economic and practical aspects which have hitherto received only periph-
eral treatment.


Development of Structural Models for Studying
the Existing Relationships Among Various
Types of Solid Wastes Generation and
Relevant Economic, Demographic, and
Land-Use Information

        Initially, the model formulation consisted of defining various types of solid
wastes and constructing the analytical framework for studying each type of waste in
relation to pertinent economic variables such as population, income, employment, and
land use.  The analytical framework was to be in the form of a multiple regression
in which solid waste volume would be treated as the dependent variable and be regressed
against the set of independent variables.  The model would then be able to specify
the structural relations between specific types of solid wastes and the generators
of wastes.   However, as the research progressed, it became clear that such an approach
was too idealistic, and that an alternative method had to "be developed.  The problems
responsible for the need to change the approach were mainly twofold:  l)  large
quantities of solid wastes (mostly industrial and commercial) were not accounted for,
primarily because they do not enter the regular disposal sites, and 2)  the estimates
of wastes received at the disposal sites could not be related to comparable sources
of wastes,  thus  precluding a thorough analysis of waste quantities coming into the
sites.  Subsequently, the limitations imposed by these two problems were delineated
and alternative approaches were developed to circumvent the limitations.  The results
obtained in this portion of the work were given in the Second Annual Report.

        Inasmuch as the development of a waste generation model is a continuous pro-
cess, refinement and expansion of the present model is  an ongoing part of the research.
The research procedure consists mainly of recognizing the interindustry details of
the study region, wherein it is possible to recognize waste management industry as
one of the producing and consuming sectors in the overall economic study of the region
in question.

-------
 Development  of Procedures  to Estimate  Pertinent
 Quantities  of  the  Various  Types of Solid Wastes
 Generation  Through Definition of Appropriate
 Sources  of  Wastes  (Generator) and Corres-
 ponding  Spatial and Functional Boundaries
 with  Reference to  a Selected Study Area

        The utility of the analytical framevork depends to a large extent on
availability of consistent and  comparable data on the volume of solid wastes generated
and on other related variables.  Inasmuch as the available body of data on solid
wastes could not be successfully related to  other variables, a beginning was made by
listing waste generators, estimating waste multipliers, and obtaining data on popula-
tion, employment, and land use  on a functionally comparable basis, while at the same
time avoiding duplications or omissions.  Work done along these lines in the present
research period was successful  in its outcome, and was reported in the Second Annual
Report.  It was possible to  identify more than JO different sources of wastes, making
it possible to develop adequate relationships between waste generation and generators
both for descriptive and forecasting purposes.  With the procedure established thus
far, it was possible to take  into account nearly all types of solid wastes (domestic,
commercial,  industrial, and  agricultural) generated in a community, and thereby arrive
at a realistic evaluation of the magnitude of the problem.  The research work done
in accomplishing this objective gave rise to the concept of "functional boundaries"
or "disposal service areas."  This concept was used extensively in setting up a much-
needed empirical data base for making the quantitative analyses needed in the work
concerned with the  study region (i.e.,  the nine-county San Francisco Bay Area).


Development and Improvement  of  Solid Waste Multipliers
and Their Composition by Detailed Levels of Economic
Activity and Waste  Sources

        The estimation procedures developed in the pursuit of the preceding objectives
led to a recognition of separate waste multipliers per unit of waste source in the
nine-county study region.  Though the concept of waste multipliers itself is not new,
a brief survey of existing literature indicated a conspicuous absence of useful
estimates of such multipliers for developing quantities of waste generation in a
given community.

        During the previous  years of the research much work was done in developing
waste multipliers on the basis  of available sample studies carried out in the study
region.  These multipliers were incorporated in estimates of waste generation in the
nine-county study region.  Present plans call for improving the quality of these
multipliers "by making a detailed examination of the physical and chemical composition
of the wastes, and by comparing these multipliers with those obtained in other regional
studies, such as the Des Moines Metropolitan Area Solid Wastes Study [2] and the
Fresno Area Solid Wastes Study  [3].  Such a study of waste multipliers can be used
to verify the accuracy and relevance of the quantitative estimates developed earlier
in this study and also to provide guidelines for other similar studies.  The sub-
stantive progress made in the study of waste multipliers was not complete at the
time of writing this report, and will be reported in a future presentation.


Survey of Engineering and Economic Aspects of
Current Methods of Transfer and Disposal
of Solid Wastes

        Progress already has been made in this direction and is reported in the
Second Annual Report.   The research reported in the Second Annual Report consisted
of discussions of each of the following technologies:  anaerobic digestion, composting,
wet oxidation, incineration-pyrolysis,  and biological fractionation.  A systematic
comparison of engineering aspects, cost considerations, economies of scale in the
operation of each of the above disposal methods and the trade-off between transfer
and disposal is considered for present and future work.  This phase of the research
will of necessity be preceded by work in other closely relevant areas such as cost

-------
 of transfer and transfer stations, cost of by-products of the processes  (whether
 positive  or negative), and  of  other related items.  The end product of this phase
 of work will be sufficiently complete and detailed to permit a listing of realistic
 alternative solutions  (or combinations of processes) for use in developing an overall
 systems analysis approach.

        A detailed approach to achieve the above objective will involve  an elaborate
 treatment of the subject in which will be defined appropriate production and related
 cost functions for each method of disposal or transfer.  It will also be necessary
 to identify those subprocesses within each listed process which are subject to
 differing variation in costs as the scale of operation increases.  The available
 body of information suggests that the multiple regression technique could be effec-
 tively used in some cases to estimate relevant parameters influencing the costs of
 disposal  and transfer.

        In the present report  a brief survey of existing and experimental techniques
 of disposal is attempted with  a view of establishing a framework for the study of
 the economic implications of each method on a comparative basis.  Conventional methods
 receiving attention are landfill, incineration, and composting.  Experimental methods
 to be considered are compaction, wet oxidation, anaerobic digestion, and biological
 fractionation.  Each method is discussed in terms of process, required equipment,
 possible  by-products,  and costs of operation.  In the case of landfill, a detailed
 account of the method  of estimating cost variation is given.  The experimental
 techniques are discussed summarily.


 Analysis  of Private and Public Expenditures in the
 Solid Wastes Industry—Theoretical and Empirical
 Issues with Reference  to a  Metropolitan Region

        An important element in formulating and implementing an effective wastes
 management system is the consideration of current expenditures on different segments
 of the waste management program, and the changes in expenditure suggested by proposed
 alternative management procedures.  Specifically, the expenditures are incurred by
 private households, industry,  commerce,  and agriculture as consumers using the waste
 disposal  facilities.   In addition to this, expenditures are incurred by public bodies
 as a part of supervision and administration of waste management programs.  Because
 of a variety of vays in which portions of solid wastes generated in the community
 are handled, there is a great need for establishing detailed accounting and estimation
 procedures by means of which it would be possible to estimate true costs of the
 several functions of waste management within the community.

        A detailed cost structure, as it currently exists,  should have many uses.
For example, it would be of value in comparing the efficiencies of various systems.
 With it,  one could estimate costs of alternative methods proposed for future imple-
mentation.  In a larger sense,  data available on expenditures by public and private
 agencies  should be sufficient as a basis for discussing the present distribution of
 costs,  efficiency,  and equity criteria.

        The initial phase of this objective was to recognize the different ways in
which wastes can be handled, e.g., wastes can be handled by any or all of 12 different
 combinations of agencies and functions,  viz.,  collection and hauling transportation,
and supervision and administration of disposal by private or public agencies.   Details
were given in the Second Annual Report.   Private agencies can be either franchised
 scavenger companies or commercial haulers.  Disposal site operations can be conducted
 either by private companies or by public agencies.   Each one of the various possible
 combinations of agencies and functions poses unique problems to be overcome in
arriving at estimates of the true cost structure of a subsystem.   Although some pro-
gress was made and was reported in the Second Annual Report, much analysis remains
to be carried out.   It is planned to discern the various difficulties inherent in
the estimating procedures and to develop reliable estimates with reference to smaller
 study regions.   At present,  the Oakland metropolitan area in California is considered
 as one such region.  It contains all of the complexities, and yet such a study could
be completed within a reasonable span of time.

-------
        A detailed report on the progress made to date on the study of theoretical
and empirical issues with reference to the Oakland metropolitan region is given
later in this report.


Application of Network flow Model for Finding
Short—Term Solution Assuming Landfill as the
Ultimate Disposal Method

        As mentioned previously, the planning and economics team is working with
the operations research team in providing empirical data for the overall model, and
in turn is using the submodels developed for feedback within the overall research
team.  An outgrowth of this joint venture is the development and application of a
network flow model for re-routing solid wastes from generation points to disposal
sites.  It is assumed that in the short run (i.e., a span of 5 years) the overriding
disposal method would still "be landfill, and the overall waste management problem
could be considered as one of finding new disposal sites when some of the current
sites are filled.

        The network flow model as developed by the operations research team was
reported in the Second Annual Report.  Since then the model has been subjected to
actual applications, and in the process, some revisions have been made.  The revised
model and the results of its application to the nine—county San Francisco Bay Area
are reported in a later section of this report.

        The preceding six objectives have been carefully scrutinized and the sub-
stantive progress achieved in varying degrees of completion is given in this report,
and was alluded to in earlier progress reports.

        The following objectives (objectives 7-10) are discussed only briefly because
they are still in the planning stage and will form the subject of future investigations.
These objectives represent a continuation of thought and are discussed briefly.  The
actual plans for their execution depend to a large extent on completing some of the
unfinished work reported earlier.


Regional Economic Forecasts of Employment, Income,
Population, and Land Use Through Input-Output and
Other Related Studies

        In the course of developing information for achieving earlier objectives, a
vast amount of spatial data on the economy was collected.  These data can be used in
projecting future waste quantities to be handled within the system.  The detailed
input-output model for forecasting the regional economy discussed in the First Annual
Report [h] will be enlarged to contain as many different economic sectors as possible
and at the same time be consistent with the waste generation model.  Such an expansion
will facilitate the projection of the regional economy and the utilization of the
waste multipliers which were estimated earlier, for the development of the necessary
forecasts of waste generation.

        Although it is proposed to develop forecasts of the regional economy and
the waste quantities within the model,  it will nevertheless be necessary to obtain
forecasts of income, land use,  and other allied forecasts from outside the model.
The latter pieces of information will be obtained from ongoing outside economic
studies of land use and population changes,  for example,  the Bay Area Simulation
Studies carried out by the University of California at Berkeley.


Technical Changes in Existing Methods_and Consideration
of Mew Methods of Transfer and Disposal for  Future
Management of Solid Wastes

        The development of the necessary research procedures for achieving this
objective depends to a large extent initially on the fulfillment of specific

-------
objective No. k viz., "Survey of existing methods of transfer and disposal," and
of specific objective Ho. 5 viz., "Analysis of expenditure by functions."  The
additional changes brought about by technological advances in the engineering methods
of transfer and disposal will be appraised fully, along with their implications on
the cost structure and management issues.  The end result of this objective will be
the provision of realistic, economic,  and meaningful alternatives of combinations of
various engineering methods for incorporation in the formulation of proposals for
optimization purposes.


A Systems Analysis Approach to Solid Wastes Management

        This penultimate objective involves various aspects,  among which are: a) the
development of comprehensive procedures to take into account the enormous detailed
information developed in the research  done thus far; t>) the recognition of the need
for spelling out in detail the subsystems of the overall management program; c) the
detailed listing of all feasible alternative combinations of engineering processes;
d) an estimation of corresponding direct and indirect costs;  and e) a study of the
implications of different combinations of all feasible solutions.  This item of work
will be pursued vigorously in the future, but the initial setting up of the various
subsystems and the various mathematical models developed in the study thus far is
expected to be completed during the year 1970-71-


Implementation of Proposed Regional Solution, Recognizing the Changes
Caused by Increasing Demand for an Overall Solid Wastes Management
Program, Jurisdictional Conflict, Efficiency and Equity Criteria
Stemming from Different Pricing Mechanisms, and, Finally,
Horizontal Integration with Other Similar Urban Services
Under a Regional or Metropolitan Government

        This ultimate objective is manifold, having several minor objectives each
with its own practical ramifications during its implementation.  The detailed nature
of the work involved in achieving this essential objective will depend to a large
extent upon the wealth of information  developed in the overall research program.
Especially important aspects of the management problem are the administrative and
sociological (or political), inasmuch  as together they constitute the sine qua non
so far as the implementation of any regional approach to management is concerned.

        The following items are listed as guidelines for developing the necessary
details for achieving this final objective:

    1.  A description of the regional  economic profile and the waste generation
        process.

    2.  Local vs. regional solution economies of scale of operations.

    J.  Jurisdictional questions in estimating the total quantity of demand and
        supply of the waste management industry.

    k.  Efficiency, equity and externalities, incidence and distribution of costs
        and benefits.

    5.  Private vs. public or semipublic participation in the waste management
        industry.

    6.  Alternative pricing mechanisms to bring about desired distribution and
        incidence of costs and benefits, taxation, subsidies, municipal bonds
        and user charges, need for developing incentives for regional management.

    7.  Proposal of alternative solutions with full implications and trade off
        between transport and disposal of solid wastes.

    8.  Horizontal aggregation with other similar urban services under a regional
        or metropolitan governing body - merits and demerits.

-------
        To recapitulate briefly, the rationale of the Planning and Economics phase
of the comprehensive research approach has been that "some fraction of the solid
wastes residue must be returned to the earth, at least in the foreseeable future,
even if efforts are made to compact, transport, treat,  and burn the solid wastes."
This has led to the recognition of landfill as the single most important method of
disposal — at least for the coming few years.  The recognition of landfill as the
important disposal method has serious implications for land-use planning, and there
is a great need to carry out some feed-back studies  between secular land-use planning
studies traditionally carried out by private and public planning bodies and the
waste management studies, such as those contemplated in this research program.

        On a different front, refuse disposal has already been recognized as one of
the major items for regional or metropolitan planning,  along with other urban ser-
vices such as air pollution control, regional parks, land transportation, and
regional planning in general.  This aspect has serious implications from the
administrative, regulative, and managerial points of view which in waste management
programs may in some instances be horizontally aggregated with other similar urban
services, chiefly to reduce unnecessary multiplicity and/or conflicts in governing
bodies.

        The interrelatedness of solid waste disposal and other urban services at the
local and regional levels makes it imperative that the final analysis of the imple-
mentation phase of the solid waste program effectively progress, and in turn
contribute to the overall process of planning for public services.


ECONOMIC AND PLANNING ASPECTS OF TECHNOLOGY

        Until quite recently, the disposal of solid wastes was for the most part
carried out in a somewhat haphazard fashion, with very little attention given to
planning beyond immediate needs.  Cities generally had little difficulty in finding
new and convenient disposal sites, and so could afford to postpone planning until
the existing dump capacity was nearly exhausted.  However, with the enormous rise
in waste generation during the past twenty-five years and the increasing scarcity of
open land within cities, random disposal has of necessity been replaced by attempts
at planning for future disposal needs.

        Along with planning in the prevention of environmental pollution comes the
question of which method or methods of disposal is most effective in terms of cost
per ton of waste disposed of, and at what point any given technology will cease to
be as efficient as some alternative.  To gain some information on these questions a
survey was made of conventional and of experimental methods of solid waste disposal,
and an analysis was made on the economic practicability of each in terms of present
and future needs and scarcities.  For example, the study considered what parameters
might cause incineration or any other method to become  more efficient than landfill.
Included in conventional technology are the disposal methods landfill,  incineration,
and composting.  Among the techniques which may be classified as experimental are
compaction at the disposal site, wet oxidation, anaerobic digestion,  and biological
fractionation. In the discussion to follow, each of the foregoing methods is discussed
in terms of the process and equipment required, possible by-products,  and costs.

        An idea of the nature of the material to be processed by a given disposal
method can be gained from a perusal of Tables 1 and 2.   Apparently,  approximately
64$ of the wastes is rubbish,  12$ food preparation residue (garbage),  and 2^$
noncombustibles.   In terms of the elemental composition that is expected of municipal
refuse,  about 2.8% may be carbon; 3-5$,  total hydrogen;  available hydrogen,  0.7$;
oxygen,  22%;  nitrogen,  0.33$;  and sulfur,  0.16$.   Such  a mixture would be about
4,917 Btu/lb.

-------
10
                                &^ -s
                      ,0
                      H

                      fc
                                 •rl M

                                  ft  ••
                                 « O
 LTNOOOLTNOOOOOO-d/OOO         OO          OOO
 LA  O   LT\  O   N~N  O   U"N   OOO   LT\  -j~    O   IT\   O         O   O          OOO
 OC—   OJVOr-ir—   OOVDOO-3-COOMDO         HO-          OOO


                                   HHHH             H              rHrH          H        H








 £•—  CO   t—  O-   t—  t—   CO   H  J-   KN  CO  C--  MD   KN   rO         CO   ^O                   _dr
                                   rH   rH   rH                                       rH




               t—   -dr        H   L/N  VO  -3-       -d;                         COOJ

 U"\LT\OJMDOJHONC—   n-Nr-VOOVQOO         i^   D—          H  _tf    O





 OOLT\rr\oooOOOOLr\OOO         O
 O  O   C—  KN   O   OJ   rH   O   OJ   r^"N  -d"  -dr    O   K^i   IT\         O   O          O   K>   CM

^D  i—I  ^O  CO   K"\  CO   OOO  ^-O   D—  OJ    lf\   OJ   CM         VD   O          ON   ON   O
                    H        HrHHiHOJ        OJ   t—  VO         H               ONONf-




 OL/NLr\irNLr\Lr\o                  OKNOHI/N         CM
 OJ  O   O  O   O   O   -dr   O    i     i   -^~  rH    OJ   O   O         LTN   O          '    '   U~N

 OOOOOOOOJ             OOOOO         OO                   6






 LT\L/NLT\OOOO             OOOJ-^-OlA         O
 OJrHtHOOOJO             OHVOrHLTvO         N~\O
  	II	          .               ill
 OOCMOJOJOO'lCMO-^-OOO         KNO          ill
                              H




 OJ  t—  CO  O   O   O   O        OOOOOOLTN         VOO               H
 K"NN"NVOOJO(HLrN       VD   OJ  t—  OJ    OJ   O   KN         O-OJ          CMHCO

-3"  CM   rH  rH   ON  LTN   iH    I    OJ   LTN  CO  rH   LA  _^-  CO         CO   rH          OOO
-=t~  -^t~  -3~  -^   fO  -^   rH        OJ        iH  KN  ^        OH         CQt—          OO-dr

 O  O   O  O   O   O   *vO   O  -d"   ON   N"N  OJOOJO         OJO          OOO
                                   rH                                                 rH








co  ON   o  ON   ^-O   ON   o   N~N   OJ  M3   F^N  VD   D~~-   ir\  -dr         -dr   iH          o   O   LT\

 LT\  LPi  v£)  LfN   LTN  LTN   CO   O   t~—   ON   UTN  MD   -cf   CM   OJ         ^3   OJ          OOO
                                   rH                                                 H








 rOOrOOJOOOt—   OVQcOU"\-drOMD         -drMD          OOCO




GOOD—  O-drOOCOOOOOOOQ         COO



                                        rHrHCM        OJ   E—  ^£>                          ONONVD
                                  I   0 .


                                 E§    O
                                                                                                                                                                           >

                                                                                                                                                                           •d
                ,
                   M  W

                   CO  03
                                                                                                                                  VO
                                                                                                                                                            CM
                     •O  .

                    ,  ^^
Volatile
Matter
                                                                                                            O^t-
                                                                                                            OLr\
                                                                                    KNll-^-d--J-O
                                                                                   CO            VDCOLTNCM
                                                                                                                                                  LT\^t-MD

                                                                                                                                                  OOOJ
                                                                                                                                                  888
                                                                                                                                                  m  CM   o
                          '»  3,
                          ) ^H
                                                 OJOJ-=J-rHHU"\OOOOOOroHO
                                                   -
                                                                                 o   o

                                                                                 O   OJ
o   q   q
CO   ^D   O
                                                                                                                                                                           H-    Pi
                                                                                                                                                                                        •g
                                                                                                                                                                                         0)
                                                                                                                                                                                         I
                                                                      atUXlCO
                                                                      -PrOtOCfl
                                                                      CUdcd^
                                                                                               ,
                                                                                                   flj
                                                                                               ^H
                                                            &-v
                                                            (U-P
                                                            (U^

-------
                                                           11
               TA.BIE 2

    ANALYSIS OF COMPOSITE REFUSE

Organic Analysis of Composite Refuse
Item
Moisture
Cellulose,, sugar , starch
Lipids (fats, oils, -waxes)
Protein, 6.25N
Other organic (plastics)
Ash, metal, glass, etc.
Percent
20.73
46.6J
4.50
2.06
1.15
24.93
                               100.00
   Analysis of Composite Refuse,
         as Received Basis
    Moisture

    Carbon

    Total Hydrogen

    Available Hydrogen

    Oxygen

    Nitrogen

    Sulfur

    Non-Comb.

    Ratio C:(H)

    Btu  per  lb
  20.73

  28.00

   3-50

  (0.71)

  22.35

   0-33

   0.16

  24.93

  39-4

4917

-------
12
Summary Description of Features of Conventional
Technologies Pertinent to Economic Analyses

        Landfill.  By far the most common method of waste disposal at present is
some form of landfill.  Three dimensions can be distinguished in classifying fill
operations.  First, a site may be called a sanitary landfill, modified landfill, or
open dump, according to whether the garbage is covered with soil at the end of each
day, covered periodically, or not covered at all.  Second,  a dump may be classed as
controlled or uncontrolled.  It is controlled if the manner of dumping, area of the
site to be used, and/or the type of refuse accepted is carefully designated.  Finally,
the landfill technique may be a trench fill or an area fill.

        Trench and area landfills are somewhat similar — the major distinction being
preparation of the earth before dumping.  The area method involves construction of
cells of refuse covered by compacted earth on flat or low-lying open spaces.  Since
no excavation is undertaken, cover material must be imported from outside the
landfill itself.  The trench method entails excavation of trenches several yards
wide followed by the discharge of solid wastes into the trench.  Both methods include
the dumping and compaction of garbage anywhere from 25/» to  kO% of its original volume;
and for a sanitary landfill, covering the refuse with two feet of earth (ideally).
The refuse usually is compacted in layers, or lifts, five to fifteen feet deep,
creating a cell-like effect.  Total depth of landfills vary widely, depending upon
the number of lifts [5].  Compaction is accomplished by the movement of earth movers,
bulldozers, and like equipment over the refuse.  In Table 3 is summarized the
equipment used in typical trench and area fill operations.

        In practice deep-hole landfill should be used with caution because of the
danger of water contamination connected with its use.  The  method is to excavate a
pit to a depth of fifty feet or more; or if one is at hand, to use an abandoned
quarry or open pit mine, and to fill the hole with compacted solid waste and earth.
With any landfill method, climatic, hydrologic, and geologic factors of an area
determine how deep a lift may be without danger of contamination.  Few locations
can safely accept a deep-hole landfill, though the method is used in parts of the
south and several sites in California [5].

        Canyon or gully landfill incorporates the most desirable elements of both
area and trench fill methods.  A canyon is filled with cells of refuse in much
the same way as an area fill.  However, cover material may be scraped from the
canyon sites to avoid the cost of importing earth.  A canyon fill results in
relatively level ground, while a trench fill raises the surface five to ten feet
above the original ground level [5]-

        The method of fill best suited to any operation is  largely dependent on the
characteristics of fill land.  Tidelands, marshes, and swamps, and other reclaimable
lands are amenable to area fill.  In the absences of such areas, trench, canyon, or
deep-hole fill must be used, depending on the terrain.

        Incineration.  Incineration of solid waste by modern techniques is a fairly
complex combination of subprocesses [6].  Collection trucks generally enter an
enclosed area (called a tipping floor) and discharge their contents into a deep,
box-like storage pit of watertight concrete construction.  Capacity of the pits
vary.  They should hold an amount approximately equal to a  twenty-four hour burning
capacity.  Usually, refuse is carried from the storage pit  to the furnace by a bridge-
type or monorail crane suspended from an I-beam and is discharged into a hopper
leading to the furnace.

        Actual incineration of the waste takes place in furnaces lined with
refractory and insulated brick designed to withstand extremely high temperatures
and equipped with agitating metal grates.  The residue of ashes, cans, and other
nonburnables is discharged into hoppers, quenched, and conveyed by truck to disposal
sites, usually landfills.  This residue varies from ten to twenty percent of the
original volume, and twenty to thirty-five percent of the original weight [6].

-------
                                                                                 13
                                      TABLE  3

                      LIST OF EQUIPMENT REQUIRED  FOR  LANDFILL
                  Method
                                                       Equipment
    I.   Area Method
        This method is  best suited to
        filling in low-lying areas such
        as tidelands, marshes,  and
        swamps.  The basic operations
        for vhich equipment must be
        provided includes :
        A.  Unloading fixed bed trucks.
        B-  Spreading and  compacting
            refuse.
        C-  Obtaining and  stockpiling
            cover material.
        D-  Placing and compacting cover
            on refuse fill.
        E.  Final grading  of finished
            landfill.
   II.   Trench Method
        The trench method  is most  often
        employed where  flat  or  gently
        sloping areas are  available.  It
        is adapted to use  on terrain
        which  can be trenched by normal
        earth-moving equipment.
    A "single crawler-type tractor"
equipped with a dozer blade (bull-
dozer) or a bullclam attachment
may perform all these operations.
For larger operations:
1•  Bulldozer.
2.  Compacting equipment.
3•  Water trucks.
4.  Earth movers.
(Note:  APWA's publication on munici-
pal refuse disposal suggests one
bulldozer of the 180 drawbar h.p.
class and ^700 Ib gross wt size to
handle about 250 tons of refuse
per day.)

    A single be It-propelled crawler
crane with a drag "bucket and a boom
serves satisfactorily for all the
operations.
        Exhaust gases given off by the combustion of the waste flow to the
combustion chamber, which may be simply an extension of the furnace,  where the gases
are burned along with any suspended particulate matter at l800°F.   Gases  then flow
to the subsidence chamber where the destruction of noxious gas and fine particulate
matter is completed, and any remaining particles are settled out to reduce pollution
of the atmosphere.  Finally, chimneys conduct the burned gases to the atmosphere
about 150 to 200 feet above ground level.  In Table k is listed the required equip-
ment for each stage of the process.
        Several types of pollution control devices can be included in the subsidence
chamber and/or the chimney.  The simplest of pollution control devices use water to
collect ash and dust particles either by moistening a system of baffles through
which the gas must pass, or by using a spray to capture and remove the particles

-------
                                TABUS
              LIST OF EQUIPMENT FOR  CONTINUOUS INCINERATION
          Process
                Equipment
l) Receiving of refuse.

2) Charging the incinerator
   furnace•
3) Incineration-
   Release of gases and
   ash.
5) Instruments and con-
   trols .
a) Storage pit.

a) Bridge crane-
b) Grab tucket.
c) Charging hopper with hopper gate.
d) Feeding and drying stoker.
e) Burning stoker.

a) Primary combustion chambers.
b) Secondary combustion chambers.

a) Gas cleaning chamber.
b) Flue.
c) Damper.
d) Chimney.
e) Ash hoppers.
f) Ash conveyors.

a) Indicating and recording pyrometers for
   temperature measurement.
b) Temperature alarms.
o) Draft gages at several points in the
   system.
d) Smoke meters and alarms•
e) Automatic gas-cooling vater controls.
f) CQs recorders .
g) Continuous chimney dust indicators.

-------
                                                                                 15
(e.g.,  "vet scrubber").  A wet scrubber removes dust particles by causing impinging
dust particles to be projected into a thoroughly dispersed scrubbing liquid.
Additionally, a spray chamber may be used to cool gases and moisten particles prior
to their removal by cyclone collectors.  The latter device is a cone-shaped cylinder
in which entering gases are forced into a spiraling, cyclone-like motion.  The
resulting centrifugal force directs particles to the outer wall of the collector
while the core of clean air is drawn out through the bottom.  The difficulty with
wet baffles, wet scrubbers, and cyclone techniques is their limited efficiency.
Though  these are virtually the only pollution control devices used with incinerators
in the  United States today, they cannot meet the standards set by the more discrim-
inating large metropolitan areas such as Los Angeles and San Francisco.

        Two far more efficient methods of removing particulate matter are the bag
filter  and the electrostatic precipitator [?]•  The former is in effect a reverse-
flow fiberglass unit mounted on a spider framework.  It works somewhat like the
bag filter in a vacuum cleaner.  One problem with this filter is that excessive heat
or air  pressure will cause it to fail.  Therefore, it is necessary to cool exhaust
gas in  a spray chamber or water-cooled furnace and to bring about a pressure drop
in the  flow of gas.  This is a fairly expensive but very effective procedure.  The
electrostatic precipitator [8] consists of small-diameter discharge wires and
collecting plates or tubes between which the gas and particles must pass.  Particles
passing through the precipitator are given a charge and thereby precipitated against
poles of opposite polarity in the precipitator.  The particles are then discharged
and removed from the wires and collecting surfaces.'  The precipitator, like the bag
filter, cannot function at high temperatures and high air pressure.  Consequently,
it too  requires some sort of cooling system, (e.g., a spray chamber or water-cooled
furnace) and a pressure drop.

        Composting.  Composting can be described as a process in which aerobic
bacteria break down organic wastes to a relatively stable, inoffensive humus under
controlled conditions.  The required bacteria are indigenous to garbage, so that
the process requires only that garbage be ground and suitably aerated, as well as
be maintained at a proper moisture content.  A compost of garbage and other refuse
can be  considered finished when the carbon-nitrogen ratio is below 20:1.  At that
ratio,  it may be safely used as a soil conditioner.  The required time to complete
the process is from 8 to 30 days depending upon the nature of the wastes and the
method  used.  Major factors in the composting process are particle size and moisture
content of the material, aeration, temperature, hydrogen-ion concentration,  and the
initial carbon-nitrogen ratio.  The smaller the particle, the more susceptible it
is to bacterial action because of the greater surface exposed per unit of volume.
Moisture content affects the metabolism of the organisms and changes the physical
structure of the material.  Aeration provides oxygen, which is essential for aerobic
bacteria in carrying on the stabilization process.  Microorganisms are sensitive to
temperature changes and generally metabolize more rapidly at the higher temperatures
within  the range in which they will grow.  Generally, bacteria thrive best at moderate
to low  hydrogen-ion concentration (alkaline) and fungi at moderate to high concen-
trations (acid).  Carbon serves as an energy source,  and nitrogen for use in building
protoplasm.

        Composting is, of course, only suitable for certain types of waste matter.
Of the  remaining the main noncompostables in municipal refuse are bottles and broken
glass,  11.7$j and tin cans, 9-8$.  As for the chemical composition, the average C:N
ratio of refuse ranges from 78 to 20.  The concentration of fertilizer elements are
rather  low, namely, nitrogen, 1.07$; phosphorus as Pa05, 1.16$;  and potassium as
K20, 0.83$.  Moisture content varies from 25$ to 70$.  It averages about 50$.  These
characteristics are reflected in the compost product.

        Two classes of composting may be distinguished as being possibly economical
and certainly adaptable to conditions in the United States.  They are mechanical
digestion and modified windrowing.  Both techniques involve the need for facilities
for storing and separating solid wastes into compostables and noncompostables,  as
well as for grinding or shredding the garbage.  In the separation step,  noncompostable
materials,  such as tin cans,  miscellaneous metals, glass and ceramic ware,  and rags
are removed from the incoming refuse.  Grinding or shredding reduces the particle

-------
16
size to a point at which the material is readily susceptible to bacterial attack.
The optimum particle size depends on the nature of the material.  Generally, it is
from 0.5 in. to 2 in. in cross-section.

        Mechanical digestion involves the use of enclosed devices of varying degrees
of complexity.  The devices include provisions for maintaining the composting mass
at a suitable moisture content, temperature, and degree of aeration.  No such
mechanical devices are used in windrow composting.  Instead, the shredded material
is stacked in windrows in the open.  Periodically, the material is turned to aerate
it.  A typical list of equipment is given in Table 5-


End Products of Conventional Disposal Methods

        Each of the conventional waste disposal methods leaves some residue or pro-
duces some product.   Though the existence of such products or residues may not affect
the physical or technical efficiency of a process, it certainly affects the economic
efficiency and social desirability of the process.  Since any discussion of disposal
costs must include implicit costs, positive or negative, a careful enumeration of
the by-products of each existing technique is indicated at this time.

        Sanitary Landfill.  Any sanitary landfill operation will result in a certain
amount of usable land after completion.  If the operation involves filling a swamp,
bay, or quarry, the end product will probably be a net addition to usable land.  If
useful land is filled, the result may only be some small degree of land improvement.
In evaluating the degree of land improvement, it should be borne in mind that the
property so treated has very little utility upon completion of the filling operation.
Its main use is as open space or for recreation, since the land will continue to
settle for years and methane gas will be generated in the completed fill for some
time.  Both of these effects would be detrimental to any major construction.  The
danger from the methane generation is that the gas (highly explosive when mixed with
air) may seep into the understructure of buildings constructed on the site,  and
thus give rise to an explosive hazard.

        Methane is not the only gaseous product in a landfill; carbon dioxide also
is formed.  When dissolved in water, the resulting carbonic acid can be corrosive,
and it also deteriorates the quality of groundwater permeated by it.  Leachates
containing biological and chemical contaminants constitute another type of product
which must receive attention.  Odor generation, leachate formation,  and water
contamination in general can be eliminated through the application of the sanitary
landfill method in its strictest application.  Settling can be lessened through
rigorous compaction.  Not much can be done about methane formation.

        Needless to state, open dumping has no place in modern waste management
practice.  In addition to being a blatant affront to even rudimentary aesthetics,
it has the additional disadvantage of producing a public health hazard and destroying
the land it occupies.  The cost of potential disease emanating from such sites
is difficult to measure, but would certainly constitute an important negative element.

        Incineration.  End products most commonly associated with incineration are
ash and the gaseous and particulate discharges which constitute air pollution.  The
damage resulting from such air pollution is too well known to warrant much further
discussion in this report.  The extent of air pollution is a function of incineration
design, operating procedure, completeness of combustion, and the refuse being fired.
Given sophisticated control devices such as the electrostatic precipitator,  inciner-
ation need not cause any appreciable pollution by present standards.  Toxic gases
and odors cannot presently be eliminated from incinerator exhaust, but may be reduced
by restricting the type of refuse to be burned, or by scrubbing devices yet to be
prefected.

        Inert ash and nonburnable objects constitute additional end products of
incineration.  Depending upon the efficiency of the incinerator, the volume and weight
of the ash should be from 10% to 30% of those of the incoming refuse.  Tin cans and
metallic objects make up the greater part of the noncombustibles.

-------
                                                                           17
                                TABLE 5

               LIST OF EQUIPMENT REQUIRED FOR COMPOSTING
             Process
             Equipment
                  a
Mechanical Method:
  l) Segregation of refuse, mag-
     netic and hand separation
     process.
  2) Grinding.



  3) Mixing with sewage sludge.
  k) Digestion process.

  5) Finishing process.

Windrow Method:
  l) Receiving of refuse.
  2) Segregation of refuse:
     Magnetic and hand separation
     process.
  3) Grinding of the refuse:
     Rough grinding.

  k) Glass and metal separation.
  5) Composting.
a) Magnetic separator to remove
   ferrous material.
"b) Suction blower to remove paper.
c) Conveyor belts.
a) Primary grinder.
b) Secondary grinder.
c) Final grinder.
a) Sewage sludge tank.°
a) Enclosed digester.
b) Air heater.
a) Dryer.


a) Hopper.


a) Magnetic separator.
a) Rasping machine,  hammermill,  or
   other type of grinder.
a) Ballistic separator.
 The equipment used by Metro Plant in Houston,  Texas.
 Optional.
°Sewage sludge is used.
 In Metro Composter only.
SThe equipment used by the  Tel Aviv Plant.

-------
18
        A somewhat less important characteristic of incineration is the necessity of
a smokestack, which breaks up the skyline and mars the little beauty that still exists
in modern cities.  A better cleaning of exhaust should permit a reduction in the
required height of an incinerator stack.

        On the more positive side, incineration generates a great amount of heat
which can be coupled with a cooling device to generate steam.  If properly designed
and some provision is made to contend with the traffic of refuse collection trucks
converging at the site, an incinerator could be located fairly close to the point of
waste generation.  If this could be done, obviously transport costs would be reduced.
The sale of the heat-steam product would necessitate a location near the market for
the steam.  One possible disadvangage along these same lines is the reluctance of the
city resident to accept an incinerator in his neighborhood.  If opposition is very
strong because of a popular and often true conception of an incinerator as a smoke-
belching monster, the facility may have to be located as far outside of populated
areas as would a landfill operation, and thereby eliminate the potential advantage
of reduction in transport costs.

        Since solid waste is not completely destroyed by incineration,  the principal
positive product of this process may be thought of in terms of reduced landfill
requirements.  Thus, if an incinerator reduces the compacted volume of wastes by
80$, the useful life of a landfill is extended correspondingly.  Since incineration
reduces the amount of land required for waste disposal,  land costs probably will be
one of the determinants in ascertaining whether or not incineration (or any other
process) is desirable.

        Composting.  At one time it was believed that compost would prove to be a
positively, or at least nonnegatively valued product, if not for its properties as
a fertilizer, which are minor, at least for its soil-conditioning qualities.  A
typical compost made from municipal refuse will have on a dry weight basis from 0-5$
to 1-5$ nitrogen, 0.75$ to 1.5$ phosphorus, and from 0.5$ to 1$ potash, in addition
to valuable trace elements required by growing plants.  Obviously, the addition of
animal manure, sewage sludge,  or slaughterhouse wastes to the refuse to be composted
will result in an increase in the final fertilizer values of the compost product.
Nevertheless, even though additives can enhance the fertilizer value of a municipal
compost, its best use will be as a soil conditioner.

        At present a large-scale market for the compost product is nonexistent.  One
reason is that the costs of hauling and spreading compost are prohibitive in com-
parison with those for synthetic fertilizers; and moreover, most farming areas already
have a plethora of readily available soil conditioners in the form of manure and
plant trimmings which they are paying to have hauled away [9].  In fact, unless some
great difficulty arises with other disposal methods, composting cannot be considered
a viable alternative.  The end product can rarely even be given away, and since the
volume is reduced by only 33$ at most, no large proportion of land is saved by its
use.

        A modified form of composting, termed low-cost biostabilization [l], has
been suggested as a possible means to circumvent the absence of a market for compost.
In this process the actual composting operation is kept to a minimum, i.e., only
enough to keep the processed refuse from posing an affront to the environment.
Another feature is that the land is "loaded," not in terms of soil amendment, but
solely in terms of acceptance up to (but not including) that level at which point
the land would be permanently damaged.  Unlike landfill, the capacity to absorb waste
is never completely exhausted.  Low-cost biostabilization probably still belongs
in the experimental class and is discussed in this section only because it is closely
related to the composting process.


Comparative Costs of Conventional Disposal Methods

        For all practical purposes—at least at the time of this writing—incineration
and some form of landfill seem to be the only feasible methods of waste disposal.
It should be possible, given the disposal process and by-products of the two techniques,
to form some basis upon which to compare costs to determine which is more efficient
in terms of economy.

-------
                                                                                 19


        Landfill.  The determination of land cost in a landfill operation presents
some quite complex economic questions.  Theoretically, the cost of land should be
the initial cost less the discounted value of land sales to "be realized at some
future date.  This total cost can then "be apportioned to find an annual rental figure.
The future date in this case is from 15 to 20 years, i.e., the time needed for land
to completely settle and waste matter to decay after the filling is completed.  In
the interim, however, the land may "be used for open space, parks, or other recreational
purposes.  If the latter are necessary facilities which vould have been provided in
the absence of landfill, the rental value of alternative open spaces should be
included as part of the gain to the providing government, analogous to sales revenue.

        Another question is whether or not a pure rent should be included in the
calculations.  Suppose, for example, that government takes a prime piece of land in
the center of the city, which will certainly appreciate in value at a rate of 10$
a year, and uses it for landfill.  Suppose, further, that the appropriate rate of
discount for public endeavors is 9$ per year.  At the end of twenty years, the
original calculations would show land cost to have been negative.  Would this be an
accurate measure of the cost to the economy of using the piece of land for waste
disposal?  It probably would not.  After all, the interest is not in the accounting
balances of a municipality or region, but in the real effect upon resource use.  For
a certain period of time, land was unavailable for alternative productive uses, and
this constitutes the real cost to the economy of the community in question.  It only
appears to be a negative cost because of a pecuniary (not real) change in land value.
Thus, the possibility of rental values.  (The point is whether an increase in the
rent earned by land should be considered to offset the real cost of land use.)

        Finally, how does one treat the value of land for which no market price
exists?  Such is the case with reclaimed land or municipally owned land with no direct
rental charge levied for use as a disposal site.  Possibly some rental value can be
imputed from surrounding properties for which a market does exist.

        If some acceptable method of evaluating rental costs could be formulated,
it would be fairly simple to form a cost function per ton of waste for landfill.
Costs, other than those for land, currently amount to from under fifty cents per
ton to over three dollars, depending on the site surveyed.  It should be possible
to use a regression technique to find a total or average cost function for landfill
in general.

        Another distinction between local and remote disposal site may be a different
quality of landfill operation.  Open dumping at the distant site may reduce explicit
costs, but it simultaneously leads to deterioration of the countryside,  or to the
building up of a health menace in the future.  This sort of cost is likely to be
completely external to the city doing the dumping.  It is analogous to a public good
in that it is a consequence of many cities' dumping, so that one city more or less
would make very little difference.


        Incineration.  Excluding adequate pollution control devices,  the explicit
costs of incineration ran from about four dollars to over twelve dollars per ton.
Adequate air pollution control features would add more than $2.00 per ton in the
case where no control apparatus is used, and could increase the cost  by a minimum
of $1.20 per ton where baffles or cyclone collectors are already installed.  As
with landfill, it should be possible to regress cost per ton incinerated on several
important variables such as air pollution equipment, age of the equipment,  and how
close the operation level is to capacity.

        Until the mid-1960's, relatively little attention was given in the United
States to the possibility of selling the heat and potential steam by-products of
incineration.  It has been suggested that the steam might be used to  heat city
buildings,  be sold commercially,  or used to generate electricity.   Whether or not
reclamation of the heat energy released in incineration would be economically feasible
depends upon the heating value of solid wastes,  the cost of alternative fuels in the
relevant area, the additional construction, operation, and maintenance costs incurred

-------
20
by using refuse as fuel, and the cost of alternative disposal methods.  Access
roads for trucks, scales, buildings, and equipment for storing arid loading refuse
into the furnaces, and residue disposal facilities will all act to raise capital,
operation, and maintenance costs.

        The sale of these products could be carried out either directly by the local
government or through the leasing of facilities for electrical generation to private
companies [10] .


        Composting.  Composting has never reached a stage in the United States at
which much data on cost of composting as a process could be obtained.  During its
brief operation, the demonstration plant at Gainesville, Florida, ran at a cost of
$6.25 per ton of waste processed.  This figure probably is conservative and gives
no idea of what could be expected from plants of larger size.  Although low- cost
biostabilization might at first sight seem a more acceptable method than conventional
composting, experimental results thus far indicate that as a technology, it needs
considerably further research before it can be accepted as a feasible waste- processing
method.  Preliminary figures indicate that for a city of 100,000, low-cost "biostabili-
zation might entail an expenditure of from $7 to $8.50 per ton of waste processed,
depending on the quality of compost.  This cost figure undoubtedly is somewhat higher
than what the actual costs would be.  However, it does indicate a rather high disposal
cost, even were no residue to remain when the process was completed.   It would seem,
then, that neither the conventional composting nor the low- cost biostabilization
processes would be likely choices for disposal technique in this country in the near
future, or at least in areas where either landfill or incineration are feasible.


A Study of Variations in Landfill Costs

        The complexities arising from the various factors influencing economics of
scale in landfill let to the present study of variations in landfill costs.   Currently,
landfill is the most commonly used method of disposal.  Reported costs of landfill
range from about $0-50 per ton for facilities operated in a haphazard manner to some
$2.00 per ton for those which qualify as true sanitary landfills.  According to
Black et al.[ll] and to Cannella [10],  the average cost for sanitary landfill is
about 1J51.13 per ton.

        The purpose of this particular study was to develop a cost function for
landfill from empirical data that would make it possible to identify those parameters
which most directly affect costs.  Such a cost function makes it possible to analyze
the efficiency of existing site operations and might lead to the formulation of
suggestions and cost estimates that will improve existing and future  operations.


        Theoretical Background.  Much of the theoretical background needed for the
study is contained in the general economic theory which assumes that  at any point
in time, output of any product bears a certain relationship to inputs in the pro-
duction process.  The most general form of the production function is given by
                             Y = f(xx,  x2,  . ..,  xn)


where Y represents output, and x.  represents  inputs to the production process.  The
functional form "f " can be estimated by minimizing the cost of production for any
level of output in a certain range of output.   Cost,  of course, is given by the
summation of products of prices and quantity  of inputs as in C:

                           C =


where C is total cost and P. is the price of  one unit of input i.

        It is possible to formulate a Lagrangian equation in order to derive first-
order conditions for cost minimization, given some level of production.

-------
                                                                                 21
Minimize C, where

        C = PO.X! + PsX2 +  ••• + P.*  - ;\  [f(x1, x2, . ..,x  )  - YJ
        »>  IS , p  - * |£  ,0  or  f  . X |£
           8x     n     Sx            n     5x
             n            n                   n


                    (xl7 xa,...,xn) + Y = 0  or  Y = f (xljX2, ... ,xn)   .


Thus, a system of n+1 equations in n+1 unknowns is developed.   Substituting the first
n equation into the last equation leads to the solution for input demand in terms of
prices and output.  That is,

                                    , Pi,P2,..., Pn)

                           x2 = g2(Y, P^Ps,..., Pn)
                                       l, P2,..., Pn)
Substituting into the original cost equation for x.


  C = PI  • gi(Y,Pi,..., Pn) + P2  • ga(*,Pi,..-, Pn) + ••• + Pn  • gn(Y,

                         /.  C = c(Y, Pi,Pa,..., Pn)  .


        This analysis raises some questions concerning the relevant inputs for the
production function of landfill.  Obviously, the process will use some amounts of
labor, land, and capital equipment both in the actual disposal  operations and in
their administration.  In addition, one would expect the use of capital improvements
on land such as fencing, diking, roads, structures, and cover material.

        These inputs are not homogeneous in character.  Labor, for example, may be
broken into sub-classes, e.g., clerical, supervisory, and operational or technical.
Technical labor, which actually performs the physical task of disposal may be
differentiated by levels of skill.  That is, labor skill is likely to range from
highly paid heavy-equipment operators to manual laborers.  Similarly, though equip-
ment is nominally fairly uniform,  some important variations may exist in size and
quality.  A site usually will involve the use of some combination of bulldozers,
graders, trucks, and cranes.  Furthermore, a classification such as "trucks" or
"bulldozers" may be differentiated in two dimensions according to horsepower and
capacity.   There is no set proportion in which equipment must be used.  The nonhomo-
geneity of inputs and output is a problem that is always encountered in economic
analysis.   A trade-off exists between operational usefulness and a completely
specified theoretical model.  The function of a model, in this case either a produc-
tion function or its concomitant cost function, is to succinctly enumerate the most

-------
22
important elements of a process.  Only then can the results of a change in process
be seen, and analysis and planning be possible.  It may not be desirable to enumerate
all sources of cost variation.  What is needed are the most significant sources and
some indication of their qualitative and quantitative impact.  The level of aggregation
of variable-labor, capital, or land, and the details obscured by such aggregation
becomes a matter of the researcher's judgment-given the data available and the purpose
of the model.

        The most important variables in a general landfill cost function are expected
to be labor, land rental, and capital equipment.  In addition, some qualitative
variables are expected to be important, e.g., lift depth, age of site, site location,
sanitary conditions at the site, and site capital improvements.

        The technique utilized to determine the sources of cost variation in landfill
is regression analysis.  Given data on a site's total and average costs, certain
elements of those costs and other variables (chosen to indicate qualitative character-
istics) are regressed against total and average costs.  The positive or negative
sign and the magnitude of each regression coefficient (in relation to its standard
deviation) will indicate those variables which most significantly influence costs.


        Bnpirical Study.  The data presented in Table 6 were gathered in 1968-69 by
questionnaire.  Only the data about which there is a reasonable level of accuracy
are reported.  Land is conspicuously absent.  Although some data on land exist; they
require further refinement.  Work is in progress on this and during the coming year
it should be possible to incorporate land rents into the model.  Until then it has
been excluded from all calculations.  Column 12 (Site Modifications) in the table
includes the capital costs necessary before raw land is ready to receive solid wastes.
In some cases this will consist of roads, fences, diking, and scales; in others only
one or two of these improvements may have to be made.  This type of investment is
essentially "lumpy" and fixed in nature.  If the site already is prepared,  that fact
may be reflected in higher land values.  On the other hand, if modification is yet
to be done, land thereby may be less expensive.  The manner of dealing with costs
of site modification must wait until land cost data are in workable form.  At that
time several approaches will be possible, namely, the cost of land and its  modification
can be treated as a single fixed cost and amortized over the expected life  of the
site, or each may be treated separately.

        The data on total wages, short-term depreciation, and equipment maintenance
and operating costs are complete for 31 sites.  Similarly the annual tonnage treated
at those sites is known.  Data on the number of lifts and their depth are incomplete,
thus reducing the sample size to 27 when those qualitative variables are used in
the regressions.   Work on the data array continues, as previously indicated, and will
be reported as they become available.

        When the data become available, there will be two basic equations,  total
cost and average cost, both to be run in linear and log-linear form to make a total
of four equations.  The nine independent variables will be run in a stepwise regres-
sion; i.e., all nine will be present in the first running, and they will be eliminated
as their explanatory significance dictates.  Complete specification of the model
follows:


        Independent Variables

        Y  = tons per year received at each site;

        X]_ = lift depth, i.e., number of feet deep each layer of refuse is
             before it is covered;

        X2 = total anniial wages paid;

        X3 = annual ammortized long-term capital, i.e., site modification;

-------
                    TABLE 6
or DMA oil LMTOFILL COSTS (OKJMSH> ™» sraw
No of
Obser-
vations
1
2
3
1>
5
6
7
8
9
10
11
12
15
111
15
16
17
18
19
20
21
22
23
2k
25
26
27
28
29
}0
31
32
33
54
35
56
37
38
59
lio
lil
Location of Disposal Site
Name
Palos Verdes
Spadra
Mission Canyon
School Canyon
Calabasas
Cannery St.
Coyote Canyon
Olinda
Forster Canyon
Santiago Canyon
Bishops Canyon
Taj igous
Sheldon Arleta
Toyon Canyon
Chollas
Otay
Miraraar
Arizona
Santa Maria (Airport)
Janacha
Tlerra Rejada
Wagon Wheel
Windsor
Sonoma
North Coast
Sycamore
Solvanp
San Elljo
Bonsall
Povay
Roblar
Palo Alto Muni.
Mountain Viev
Sunnyvale
Morgan Hill
Gilroy
Pacheco Pass
Guadalupe
Los Altos
Santa Clara Muni.
Nevby Island
County
Los Angeles
Los Angeles
Los Angeles
LOB Angeles
Los Angeles
Orange
Orange
Orange
Orange
Orange
Los Angeles
Santa Barbara
Los Angeles
Los Angeles
San Diego
San Diego
San Diego
San Diego
Santa Barbara
San Diego
Ventura
Ventura
Sonoma
Sonoraa
San Diego
San Diego
Santa Barbara
San Diego
San Diego
San Diego
Sonoma
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Santa Clara
Yearly
Waste
(tons)
1,550,000
142,500
1, 110,000
450,000
240,000
159,000
1,020,000
524,000
111,000
40,600
537,000
155,000
460,000
294,000
232,600
155,000
229,100
81,991
12,500
102,000
61,397
95,691
65,000
54,100
68,500
91,700
8,800
56,500
31,000
14,596
14,700
50,000
52,000
76,753
5,900
5,640
5,900
135,000
108,000
24,000
156,000
Lift
Depth
(ft)





40
60
60
50
50
10
20
10
10
15
15
15
15
25
15
11
15
6
6
15
15

15
15
15
6
18

28
4
5
10




Total
Wages
* 239,452
64,957
225,699
146,942
80,488
17, 527
178,057
150,871
36,744
26,455
89,000
4k, 782
115,000
124,000
58,682
62,600
65,046
22, 138
10,195
56,800
31,772
47,574
15,000
15,000
58,000
60,600
10, 026
43,700
47,000
35,100
15,000










Long Term
Cap. Expd.
(Site Modif.)
* 190,000
75,000
98,000
545,000
104,500
6,054
265,027
165,755
34,086
118, 562
55,000
20,691
125,000
100,000
9,000
54,594
9,000
6,000
-
12,200
25,000
41,200
41,000
27,500
8,700
70,201
-
97,676
54,100
2,600
22,000










Short Term
Cap Expd.
(Equip Depr.)
* 138,424
24,458
162,590
79,209
4o, 105
1,161
173,035
S6,670
22,266
18,535
14,000
6,251
45,000
34,000
55,267
23,949
55,409
19,864
1,08;
12,209
12, 754
14, 452
910
875
2,758
8,575
1,969
6,621
6,118
4,066
2,551










Maintenance
5 Equip. a
Oper. Costs
* 200,659
48,192
472,085
171,709
74,817
12,200
148,305
125,755
26,584
19,48i
16,000
6,656
46,000
36,000
98,956
55,651
109,655
56,927
748
38,091
25,027
47,917
49,430
18,150
40, 242
41,127
5,481
19,679
20,282
10, 654
57,154










Sanitary
Yes
Yes
Yee
Yes
Yes
Mo/Other
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
no/other
Bo/other
Ho/Other
No/Other
Yes
Yes
No/Other
Yes
Yes
Yes
No/Other
Ho/Other
No/Other
No/Other
Ho/Other
No/Other
Yes
Yes
No/Other
No/Other
No/Other
Site Location
Rural
Urban
Urban
Rural
Urban
Rural
Rural
Rural
Rural
Rural
Rural
Urban
Rural
Rural
Rural
Rural
Rural
Rural
Urban
Rural
Urban
Urban
Urban
Urban
Urban
Rural
Urban
Urban
Rural
Rural
Urban
Rural
Rural
Rura]
Urban
Urban
Urban
Urban
Rural
Rural
Rural

-------
         X4 = short-term capital,  i.e.,  equipment depreciation or rental;

         Xg = equipment maintenance and  operating cost;

         Xg = miscellaneous  costs;

         X7 = dummy variable,  equal to 1 if the  site qualifies as a
              sanitary landfill,  equal to 0 if it doesn't;

         X8 = dummy variable,  equal to 1 if site is  in urban area,  equal to 0
              if  it's  in rural area.

 Definitions are:            f,

         Total cost =  TC =

                            1=2
= )  —
         Average  Cost  =  AC

                            1=2

 The  regression equations  to be  run  are:

         1.    TC  =  tt!  +  a2Y + bjXi + b2X2 + b3X3  +  b4X4 + b5X5  + bgXg  + b7X7

         2.    AC  =  A!  +  A2Y -f- BjXj. + B2X2 + B3X3  +  34X4 + 85X5  + ^Xg  + 67X7  +  B8X8

         3.    In  TC =  ooj. + a2 In Y + p^ +...+pe In X8

         1* .    In  AC =  In ax + a2 In  Y +  BiXj. +. . .+  58  In Xe


 Choice  of  Conventional  Method

         The  decision  to be made at  the  present time seems to be one between
 incineration and landfill. More  specifically, incineration should replace landfill
 whenever the total net  cost per unit (ton) for incineration is less than  the total  net
cost  per unit for landfill and  other constraints  (e.g., environmental  quality)  are met.

 Represented  algebraically, then
where:
         T =  transport  costs per  unit  of  solid wastes

         M =  land  costs  per unit  of  solid waste

         p =  the coefficient of reduction of  incinerated wastes

         Z =  the net  value of  other  by-products  per  unit of waste  incinerated

         C =  costs per  unit of the actual disposal operation  including  capital,
             labor, and maintenance, but  excluding land cost

         1 =  designates  land fill

         i =  designates  incineration.

-------
        The total net cost of incineration includes a term, p (Ti + C1 + Mj_), which
represents the cost of landfill for residues of the incineration process.  In effect,
this formulation treats landfill as the means of disposal  with alternatives "becoming
feasible only when the savings in land and transportation costs offset the cost of
the new process.  Note that the value of land-saving depends on the price or rental
value of land.  It should also be noted that the key determinants of the optimal
method, given C± < C±, are land, transport costs, and distance.  These have "been
key factors in the decision of large cities to use incineration (e.g., New York).
Deriving an accurate measure of land cost, then, is quite important in the decision-
making process as to what disposal technique would be the most efficient.


Marginal Cost

        One important difficulty in the derivation of cost functions is that of
finding marginal costs.  Average cost, of course, does not give the true variation
which will occur upon changing from one technique to another.  If the average cost
of landfill is discovered to be $10 per ton while that of incineration is $9; the
question becomes one of whether or not it would be valid to deduct $1 for each ton
incinerated rather than buried.  The marginal cost of landfill may approach zero
while that of incineration may well be above $10.  It therefore is necessary to
estimate marginal as well as average cost figures in making comparisons between
alternative costs of disposal.


Summary Description of Experimental Technology

        A number of disposal methods as yet in the experimental or pilot stage have
been developed, which at some future time may replace or complement those currently
used.  The fact that these techniques are not widely used in this country limits
the analysis to be made at this time to hypothetical rather than actual costs.  In
such cases, cost estimates made by engineers generally are based on experimental
costs rather than on commercial scale-up of the experimental process.

        Compaction.  The experimental technique probably closest to immediate
commercial application in this country is compaction at the landfill site.   Compaction
should be considered a complement to landfill.  Befuse is fed into a compaction
device which reduces it to 1/10 to 1/20 of its original volume depending on whether
or not it has been ground.  This may be compared to the compaction of between 1/3 and
1/k of the original volume obtained with the conventional compaction brought about
by means of tractors.  Equipment required for the operation consists of the compaction
unit and a shredder (or pulverizer in operations in which compaction is preceded by
grinding).  Rrobably some on-site storage would have to be provided.

        The obvious by-product of compaction is more efficient land use.  Given the
above compaction ratios, a quantity of refuse might occupy as little as 1/5 the
space it would otherwise require.  Furthermore, some advantage may be realized if
landfill for compacted refuse of this type settled in a shorter time than regular
landfill.  Future receipts for usable land could be discounted over a shorter period
of time, assuming that the major constraint on the use of landfill product is settling
rather than gas emission.  This is another area in which more examination is needed
before its costs considerations are fully realized.

        Wet Oxidation.  The technical aspects of wet oxidation constitute the subject
of another section of this report.  The information given in this section is confined
to that needed to give perspective to the present discussion.  Hence some repetition
between this and the later section occurs.  Wet oxidation possibly could be used to
process a wide spectrum of organic waste found in the waste stream, as for example,
manures, tree trimmings, grass clippings, sewage sludge,  demolished lumber, and
waste paper.  The process requires facilities for storing and sorting waste materials
to remove metal, glass, masonry, and plastics.  The remaining organic waste must be
pulverized and then suspended in water.  The suspension is pressurized, mixed with
molecular or atmospheric oxygen, and heated by way of heat exchange in a stainless

-------
26
steel reactor at 220 to 320"C under 1,000 to 2,000 psi.  at about 200°C the mixture
reacts spontaneously.  The reactor products pass through the above-mentioned heat
exchanger to heat the incoming waste mixture and then are separated into gaseous
and liquid components.  The gases are used to drive an air compressor, and can be
used to generate electric power.  The heat from the liquid component is used to
heat the incoming material.  Steps of the process and the necessary equipment are
summarized in Table 7-

        End products of wet oxidation are a number of commercially useful acids,
such as acetic, formic, oxalic, and fumaric.  There is also some possibility that
the process could hydrolyze cellulose into glucose.  Another product is a nonfibrous
solid waste sludge which has a volume approximately 20% of the original material,
has a high BOD, and must be disposed of in a landfill.

        The economies of a 100 ton/day plant were extrapolated as in the Second
Annual Report [l] on the basis of cost figures on the West-Southwest Wet Oxidation
Plant of the Metropolitan Sanitary District of Chicago.  Using amortization of a
$3.82-million plant over 25 years with projected operating and maintenance costs,
it should cost around $8.78 to process a ton of solid wastes.  According to the
proponents of the process [l] for each 100 tons processed, some k-5 tons of organic
chemicals should be produced and about 10 tons of residue would have to be disposed
of by landfill.  Sales of chemicals produced in the process might bring in from $54
to $90 per ton of waste processed.

        A note of caution is called for in evaluating these cost figures.  They are
based upon experimental scale only, and consequently do not include any unforeseen
elements in moving from experimental to commercial size.  Also, no costs of separation,
storage, or sludge disposal are included.  Finally, once an operation goes beyond
the one-plant scale, very little may be assumed regarding price of the chemical by-
products.  Obviously, if every large city in the country were to turn out formic
acid in waste disposal plants, the price of that acid could be expected to fall,
possibly even to approach zero.

        Anaerobic Digestion.  A third, as yet experimental, disposal technique
(anaerobic digestion) has been incidentally used in this country for many years for
processing solid wastes in the form of garbage ground into the sewers by way of the
kitchen or restaurant garbage grinder.  Recent study has centered on the possibility
of including not only garbage, "but paper, wood, and glass as well.  The technical
aspects of this study are reported in another section of this report.

        In the process, refuse is sorted, ground, and again sorted by hand and by
magnet.  The sorted and pulverized wastes are passed through a "grit chamber," and
from there to an anaerobic digester.  Digested wastes are pumped to a drying bed.
The dried material can be used as a soil conditioner or as cover in a landfill.
Steps and equipment for the process are summarized in Table 8.

        Final products of anaerobic digestion are methane, carbon dioxide, and the
stabilized residue mentioned in the preceding paragraph.  Reduction in original volume
is about 50$-  The methane gas can be used as a fuel and thereby reduce the net cost
of the digestion procedure.  Again, if the system is proposed on a large scale, some
account should be taken of its impact on the market for gas before computing prices
and revenues from gas sales.  However, in view of the ever-increasing demand for
energy sources, there is little danger of a glut in the market for combustible gas.

        The costs of anaerobic digestion of garbage in general are based upon estimates,
and all the previous precautions concerning experimental vs. commercial scale apply
here.  The figures are strengthened by the fact that they are based on "off-the-shelf"
equipment and existing design.  Estimates range from $4 to $6 per ton [l].  However,
these appear to be based on only one scale of plant for cities of various sizes, and
in that respect are questionable.  Also, they do not include sorting costs.  Sales
of the methane gas can offset the gross cost somewhat, but costs still appear high
to obtain only a 50% reduction of landfill volume.

-------
                                 TABLE  7

               LIST OF EQUIPMENT FOR WET OXIDATION PROCESS
                                                                           27
               Process
           Equipment
 l) Pretreatment of the rav material.
    (This mainly consists of removal
    of metal,  glass, and masonry,
    followed by grinding of the  rav
    material to obtain required
    size of particle and solids
    concentration.)
 2) Storage.

 3) Pressurization.



 k) Treatment with air.

 5) Preheating.

 6) Oxidation process.

 7) Recovery of  heat.

 8) Phase separation.  (Nonconden-
    sable gases  from rest of the
    mixture•)
 9) Filtering of slurry.  (Solids
    portion used for landfill and
    liquid effluent has a fairly
    high BOD and so requires
    biological treatment.)

10) Recovery processes.
    a) Recovery from the  liquid
       portion of the organic
       chemicals.

    b) Recovery of carbon from the
       solid phase.

    c) Recovery of inorganic
       chemicals.
a) Magnetic separator.

b) Ballistic separator.

c) Grinding machine-

a) Storage tank.

a) High-pressure pump.
b) Heat exchangers.

a) Air compressor.

a) Heat exchangers.

a) Reactor.

a) Heat exchangers.
a) Expansion engine (only for a
   large-scale plant).
a) Filters.

-------
28
                                     TABLES

               LIST OF EQUIPMENT FOR ANAEROBIC FERMENTATION PROCESS
                  Process
                                                   Equipment
l) (a) Collection of garbage.
   (b) Transfer of garbage to
       grinding machine•
2) Removal of nongrindable material
   as cans, glass, bones, etc. by
   hand and magnetic separation.
3) Grinding of garbage and trans-
   ferring it to digesters.
k} Digestion process.
5) Auxiliary equipment.
                                           l)  Trucks
                                           2)  Conveyor belts


                                           l)  Magnetic separator
                                           l)  Garbage  grinding machine
                                           2)  Pumps
                                           l)  Primary  and secondary digesters
                                           1)  Pumps
                                           2)  Gas meters
                                           3)  Stirring system
                                           4)  Heating  system
                                           5)  Gas holder
                                           6)  Pipeline and valves
                                           7)  Automatic control system
        Biological Fractionation.  Biological fractionation of the organic content
of solid wastes is a process for recycling materials from the wastes stream to the
basic resources of the nation.  It differs in concept from anaerobic digestion in
that by-products of elevated economic values are produced, whereas digestion is
intended to reduce volume and yield a residue which may be disposed of to the land
with minimum insult to that resource.  Biological fractionation produces a solid
residue usable for animal feed, and glucose as an intermediate product.  In this it
parallels wet oxidation, the difference being that in wet oxidation the oxidation
or fractionation is physiochemical; whereas in biofractionation, it is biological.
The technical aspects of biofractionation are treated in a later section of this
report.

        In biological fractionation ground cellulosic wastes are hydrolyzed to
glucose, and the glucose in turn serves as a substrate for the production of a crop
of single-cell protein.  Protein and the cellulosic wastes not hydrolyzed can be
used as an animal feed or feed supplement.  The basic difficulty of the process at
present is that the cost, excluding land cost and taxes, and assuming a market for
the feed supplement, approaches $te per ton [l].  Of course, such a cost is prohibitive.
However, the process is as yet in the experimental stage, and the development of
additional by-products may offset the high costs to some degree.  Equipment needed
for the process is listed in Table 9-

        Discussion.  The summary given in the preceding paragraphs is not intended
to lead to any conclusion regarding the optimal method or combination of methods of
waste disposal, but merely to enumerate and briefly explain each process, and to
point out the relevant considerations in the study of disposal costs.  Indeed, it

-------
                                                                  29
                        TABLE 9




LIST OF EQUIPMENT FOR BIOLOGICAL FRACTIONATION PROCESS
Process
l) Biological fractionation process.








2) Recording of pH, temperature, and
RPM.
Equipment
a) 14 -litre culture flask fermenter
and bacterial culture •
b) Motors for stirring the contents of
the fermenter.
c) RPM control unit for motors.
d) Beckman pH analyzers and peristaltic
pump for control of pH.
e) Temperature control unit.
f) Anti-foam control unit.
a) Temperature, pH, and RPM recorders.

This listing is quite obviously incomplete in omitting the need for stor-
age, sorting and disposal facilities and equipment. It vas obtained from the
staff paper on "biofractionation. Another
Annual Report on page 77 and on page 78.

Equipment

1. Medium preparation vessel,
12,000 gal. capacity
2. Medium sterilizer, 12,000 gal
3. Fermenter, 60,000 gal capacity
4. Centrifuges, (2), 20 in. diam.
5- Hydrolysis vessel, 300,000
gallon capacity
6. Evaporator, 8,400 gal capacity
7. Crystallizers, (4), 3,600 gal
8. Agitated tank washer, 3,600 gal
9- Drum dryers, 50 sg ft area
10. Centrifugal pumps (6), 20 gal
per minute
11. Installation cost
12. Piping
13- Instrumentation
Ik • Insulation
15- Electrical auxiliaries
l6. Building
17- Land and improvements
18. Utilities (fixed capital
equipment)
19- Engineering and construction
20. Contractor's fee
21. Contingency
listing is available in the Second

Cost
1.
2.
3-
4.
5-

6.
7-
8.
9-
10.
-] -i
11 .
12.
13-
14.
15-
16.
17-
18.

19-
20.
21.
$ 14,500
14,800
115,000
43,000
119,000

22, 500
30,000
14,800
28,400
3,000
~i nv f^r\c\
ID [, pUU
155,000
64, 500
34, ooo
43,000
215,000
43,000
107, 500

300,000
75,000
150,000
Operating Costs Per Day


Item Cost
1. Labor $ 472
2. Raw Materials 60
3- Supervision 50
4. Maintenance 220
5. Plant Supplies 33
6. Utilities 34o
7- Overhead 260
8 . Laboratory 60
9. Packaging 100













-------
30
should "be obvious that no process will be universally ideal.  Rather, conditions
regarding land cost, transportation distances, and other factors will determine
•which process or combination should be used in any given circumstance.  The object
of study now ought to be to examine empirical data in order to formalize and quantify
the important relationships, and to devise solutions to some of the more complicated
theoretical problems, so that the foregoing analysis can be applied to actual
situations.
ANALYSIS OF PRIVATE AND PUBLIC EXPENDITURES IN THE
SOLID WASTES INDUSTRY-THEORETICAL AND EMPIRICAL
ISSUES WITH REFERENCE TO A METROPOLITAN REGION


Meed for Public Concern

        The solid wastes industry comprises a host of private and public agencies.
Essentially, the industry provides a service, namely, the collection, transportation,
and disposal of solid wastes.  The service is one whose benefits and costs cannot
always be exclusively confined to those deriving the benefits by paying for the
service.  Benefits from adequate levels of service include the absence of waste-borne
disease and of disease-carrying vectors, as well as the absence of littered streets,
polluted air, uncut lawns and untrimmed gardens, which together degrade the quality
of the environment.  The benefits of public health and environmental quality are
enjoyed by everyone in the community and they are not confined only to those bearing
the cost of the requisite service.  In fact they transcend private and political
boundaries, with the result that neighboring households, firms, cities, and counties
are essentially "together" in receiving the benefits of adequate disposal service;
or, in sharing the environmental decay in the absence of such service.

        The inability or inadvisability of confining the benefits of a service to
those directly paying for it constitutes a basic criterion for deeming it a public
good.  Hence efforts toward planning for current and future provisions of the service,
for establishing adequate levels of service, and of equitable methods of pricing must
explicitly take into account spillover costs and benefits to the public welfare.
These considerations of pervasive costs and benefits external to the industry render
the usual market mechanism itself inadequate.  Levels of output and methods of
organization and pricing optimal from the parochial viewpoint of private firms and
individuals are almost always suboptimal from the standpoint of society.  A decided
divergence exists between the social and the private costs and benefits that result
from the public nature of the service.  Broadly, the implications of this are
straightforward, i.e., decisions involving the service must take cognizance of its
spillover effects on public health and welfare.   However, it does not imply that the
service need be provided by a public agency, although the public's interest must
be borne in mind while making decisions as to levels of service, pricing, and methods
of organi zati ons.*

        Familiar to all social scientists are the immense problems involved in actually
implementing a mode of evaluating a public good.  Setting functional boundaries that
even approximate areas within which costs and benefits are commensurable is a
difficult venture.  Also attempting to assign costs to environmental quality and
the quality of life made possible by the absence of disease must ultimately involve
value judgment.  There are no inherently correct decisions.  There may be tools to
aid in the decision-making process, but ultimately someone's or one group's judgment
becomes essential.  So long as the value judgments are clearly stated, the socio-
political haggling over objectives can be separated from analysis of particular
choices; and the tools of analysis can be used to help recognize the full socio-
economic impact of each alternative course of action.
    •x-
     The problem Involved in finding eriteria for social optima constitute an on-going
and perhaps insoluble search.  For some approaches to the problem the interested
reader is referred to McKean's Public Spending,  McGraw-Hill,  1968.

-------
                                                                                  31
        Among the aids to decision making are program budgets, cost-benefit analysis,
systems analysis, and input-output analysis.  These aids can be used separately or
combined in a more comprehensive attempt to ascertain the magnitude of the spillovers
and alternative solutions to the problem.

        A final aspect of the solid wastes industry necessitating public concern
derives from its interrelatedness with other urban services, and its use of land
as a final repository for solid wastes residue.  Any plan for urban development or
redevelopment must incorporate the solid waste activity.  Urban planning must allocate
land for this purpose and decide upon modes of supervision in terms of long-term,
comprehensive urban needs.


Cost Study Involving the Oakland Metropolitan Area

        The need to explore problems in decision making regarding various aspects of
solid waste management as outlined in the preceding paragraphs, and to seek for
solutions, prompted a study the purpose of which was to establish a workable account-
ing framework and to develop operational procedures for data collection in the
Oakland (California) metropolitan region.  Ongoing studies in the region have brought
to light several difficulties in gathering needed data, and have enabled the research-
ers to come to grips with analytical details.  In the paragraphs to follow a brief
discussion is given of the need for such a cost study and of various accounting
procedures developed in the study, and report is made of progress made to data with
reference to the study area.

        For any study region, costs associated with the collection, transport,
disposal of solid wastes, and supervision of the solid wastes industry must be
determined so as to be able to arrive at the following items of information:

    1.  Amounts of the resources diverted to the solid waste industry;

    2.  Differences in cost between private and public agencies;

    3-  Differences in cost among areas;

    4.  Cost by function;

    5-  Costs by quantity of waste handled; and

    6.  Urban planning purposes.


Resources Diverted to the Solid Waste Industry

        ¥ith respect to resources diverted to the solid wastes industry, the interest
is in economic opportunity costs.  Such costs often go far beyond that which the
business community regards as "costs."  For example, a scavenger company may obtain
a franchise for refuse collection because it happens to own a parcel of land suitable
as a disposal site.  This land is "costed" by the company at the price paid for the
land; or if the company already owns the land, land costs may be ignored completely.
Yet, to arrive at opportunity costs, land must be considered and valued at its
current market prices - amortized of course — because this is the value of the
opportunities given up by using the land as a disposal site.  Similarly, costs of
labor, time,  and transportation to and from the disposal site must be estimated for
the occasional contract hauler and for individuals disposing of their own solid
wastes.  As can be seen,  true opportunity costs frequently are hidden.  Yet they
must be imputed in determining the total costs of the solid wastes industry.  It is
important that costs are complete and treated in this manner, because only then do
they yield a true picture of the resources diverted to the industry.

-------
 32
Cost Differences Between Public arid Private Agencies
and Among Collection Regions

        Ey ascertaining the differences in cost between public and private agencies,
it is possible to identify efficient methods for industrial organization.  Thus, it
mij,ht be more efficient for a local government to supply its own solid wastes services
or to franchise a private company to do so.*  Inherent differences among collection
regions — industrial, agricultural, commercial, suburb, deteriorating central city,
hilly, flat land —all affect the cost of service-  These different areas may require
different solutions as to service provision and pricing policies.


Cost By Function

        Cost by function comes into play in providing a socially acceptable level of
solid wastes service.  Tentatively, functional categories to take into consideration
are collection and transport to disposal site, the management of the disposal site
itself, and the overall public supervision of the quantity and quality of service.
The cost of the entire service depends on the efficiency of the methods used for each
functional task.  Although a single firm may provide all the functions comprising
the complete service, costs must be apportioned separately to each function.  Only
then can alternative methods be compared.


Costs by Quantity of Wastes Handled

        Preliminary investigation indicated the existence of economies of scale in
the industry, i.e., the more waste handled by a firm, the smaller is the per unit cost.
More evidence is needed to confirm or reject this hypothesis.  This subject was con-
sidered in the Second Annual Report [l], in which a regression model based on a
theoretical approach was developed.


Urban Planning Purposes

        In a rapidly growing urban area, both a long- and short-run plan for collection
and disposal of solid wastes are essential.  Regardless of the agencies and functional
methods used for disposal, some land must be set aside for this purpose.  The amount
and location of such land will depend on the projected growth both in magnitude and
nature of composition of the disposal service area.  A viable collection, transpor-
tation, and disposal system thus depends on several factors, viz., projections of kinds
of growth envisioned, nature of composition of wastes generated, and a true structure
of costs and their distribution.  The forecasts of supply and demand needed for sound
planning depend on a thorough understanding of the present system of waste generation,
and on the ability to ascertain the opportunity costs associated with each subfunction
in the solid wastes industry.

        Relevant cost data generated by this study will give a picture of present
performance in the solid wastes industry, and thereby help to decide as to "what
should be" for future management.


Expected Cost Accounting and Data Collection Problems

        Engaged in the collection, transportation,  disposal, and supervision of solid
wastes are a myriad firms which includes public agencies, private scavenger companies,
private commercial haulers, and small businesses and households.  Several combinations
of service are possible:  from private collection to public site, franchised collection
to franchised site, public collection to private site, and so on.  Some twelve such
combinations were identified in the Second Annual Report [l].
     This is a much debated area.  See Julius Margolis,   "The Demand for Urban
Services," in Issues in Urban Economies,  ed.  Perloff and Wingo,  Resources for the
Future, 1967; and for private industry's  point of view see "Efficient Disposal of
Solid Wastes versus Obsolete Municipal Boundries," Sanitation Industry Yearbook,
Refuse Removal Journal, 1969 •

-------
                                                                                  33
        One of the major problems of data gathering is identifying all of the  "firms"
engaged in each functional activity.  A second problem is in the difference in the
concept of cost from the viewpoint of the firm as opposed to that of cost as needed
in an economic analysis.  This difference may lead to some thorny problems of data
collection and interpretation.  A firm's  bookkeeping practices  may "be -wholly
inadequate from an economic point of view.  Economic analysis requires that costs
be apportioned by function.  A firm may give only total costs, and find it difficult,
if not impossible, to provide separate functional figures.  Furthermore, some cost
items may be omitted or are difficult to detect.  The design of a data collection
system should facilitate the recognition of total costs and their apportionment by
function.  A particular difficulty in tracing costs in a municipality's bookkeeping
stems from the fact that the engineering, personnel, and accounting departments are
each responsible for many services and activities.

        There appears to be a considerable amount of reticence on the part of
franch!sed scavenger firms in the Bay Area to divulge any information,  let alone cost
information.  This is a frequently-encountered problem in data collection, and should
not be surprising in the solid wastes industry due to its socio-legal and political
environment, fear of competition, of public disapproval of land use,  and of political
and legal review and control.

        Identifying all of the firms engaged in solid wastes collection and transpor-
tation may be difficult, since some of them conduct their business on a part-time
or contract basis.  In addition to those firms engaged in collection and transportation,
there are the private households and small businesses that provide this service for
themselves.  Hopefully, the quantity of refuse discharged by these groups may be
estimated on the basis of information obtained at the disposal site.   Costs will have
to be inputed in these cases.  Inputed costs will vary between households in high
and low income areas, as well as between households and small businesses.   Any
discrepancies should be reconciled.

        Once all the agencies involved in collection and disposal of wastes or in
supervision of the solid wastes industry have been identified and their costs
ascertained, double accounting must be avoided in estimating true total costs.  A
franchise fee will be reported as a cost to the franchise holder and a revenue to
the grantor.  Similarly, license fees, special taxes,  and disposal fees all present
an accounting problem which must be met.


Some Economic Considerations

        There are some purely economic aspects of the regional costs  study which
must be borne in mind.   In a competitive industry revenues can be treated as "being
equal to costs.   But a truly competitive industry is one wherein there  are many
producers of the service,  and no one individual can set the price of  the service
which must be charged by all of the producers;  nor can his output influence the
market price.  There must be free entry and exit from the industry,  and information
must be available to firms regarding opportunities.   Obviously the solid wastes
industry with its exclusive franchises for collection areas,  its regulated disposal
sites,  and its frequent cost-plus pricing is not competitive.   Therefore care  must
be taken in using the revenue and cost data that are obtained.

        In economic jargon,  the goal of a regional analysis is to arrive at a  "cost
function."  This presupposes that all possible  methods of accomplishing each functional
activity have been identified — in other words,  the production functions are known.
Each production function will require a certain variety and quantity  of inputs and
these will have  costs associated with their use.

        Economic efficiency criteria require choosing that method of  achieving a
given objective  which minimizes resource use.   Cost functions  yield the  minimum
resource cost for each production method.   Given this information,  decision makers
can choose the production method that minimizes costs.

-------
        The  relevant magnitude for decision making, as well as analysis, is marginal
or  incremental cost.  Heuristically, this is the cost of collecting, transporting, or
disposing of one additional unit.  Mathematically, it is the derivative of the cost
function, if it exists.  So long as the cost of collecting one more unit, where unit
is  properly  defined to fit the circumstances, is less than the marginal revenue
received for collection, then it pays to expand production.  Efficiency requires
that the marginal cost of a product be equal to its price - where marginal cost
measures the opportunity value of resources used and price the consumer's satisfac-
tion.*  However, because of the 'public good' nature of the solid wastes industry,
an  operational problem arises in descerning just what are true marginal costs and
prices.

        Producers do not pay all the costs connected with the service, — for instance,
for the noise, spilled litter, or unsightliness of the disposal site.  The consumer
receives the spillover benefits of the service regardless of his contribution, so
it  is to his advantage to understate the value of this true benefit [12-1^].  The
result is a  financing problem whose solution frequently necessitates a combination
of  price and tax policy.  It will suffice to explicitly identify this aspect of the
problem now.  It will come under further scrutiny later in the research.

        Production efficiency, the goal of the present research, can be viewed in
both a short-run and a long-run setting.  In the long run, all inputs are variable,
thus permitting any scale (size) of operation.  Long-run marginal cost normally
declines until the most efficient scale of operation is reached.  Thereafter it may
increase because of increasing cost —most often due to management inefficiencies.
Economies of scale refer to costs which depend solely on the size of the firm.  In
the extreme  case, the entire desired output of an industry will be less than that
which one firm could produce at maximum efficiency.  This is the case of a natural
monopoly.  There is no evidence that the solid wastes industry constitutes such a
monopoly, but there is preliminary evidence that economies of scale are present.

        The  scale of operation is unchangeable in the short run.  Most costs are
then fixed and do not enter into marginal cost analysis.  Generally, overhead expenses
must be paid regardless of the amount of business done,  but day-to-day variable
costs — especially labor — will be dependent upon the organization of production.
An efficient and incentive-orientated firm accomplishes more per laborer,  and thus
has lower per unit costs.  However, it is possible to overuse labor.  This can cause
costs to rise as accidents and other forms of carelessness take their toll.  The
trick is to  expand production up to the point where marginal costs begin to rise.
At that point further production is justified until price is equal to marginal
cost, but this will be a phenomenon only for the short run.  In the long run,  effi-
ciency criteria in the normal case dictate operation at the point of minimum marginal
cost.

        The nature of the solid wastes industry, with its external benefits and costs,
its mixture  of public and private firms, and the necessity of imputing large segments
of cost,  makes unsatisfactory the use of the usual efficiency criterion:  Marginal
cost equal marginal value of benefit (price)."

        In lieu of marginal valuations there are two possible criteria of efficiency:
l)  the rate of return on investment and 2)  the benefit/cost ratio,  (in their
publication, Northern California's Water Industry [I5l>  Bain et_ al. present a full
discussion of the preceding criteria.)  Because of the externalities problem the
benefit/cost ratios probably will not be used.  Instead, a rate of return test will
be tried.
    •K-
     Technically, the marginal rate of substitution in consumption must be equal
to the marginal rate of transformation in production.

-------
                                                                                35
        The rate of return on investment is a valid efficiency criterion, provided
the input market is sufficiently competitive to assume that the dollar cost of inputs
measures opportunity cost.  Assuming this, the average rate of return indicates the
relationship between marginal value and marginal cost.  Three cases can be distin-
guished:

    1.  If long-run marginal costs are constant, then the average rate
        of return should be the same as the applicable market rate
        (See a of Figure 1)

    2.  If long-run marginal costs are declining, the average rate of
        return should be lower than the prevailing market rate
        (See b of Figure 1)

    J.  If long-run marginal costs are rising, then the average rate
        of return should be greater than the market rate
        (See c of Figure 1).


Thus, if it can be ascertained that over the relevant range the average cost of
handling solid wastes is constant, then a rate of return equal to the average market
return for similar industries would indicate a correct allocation of resources to
solid wastes.

        Profits are properly considered an opportunity cost of production.  They are
the cost of retaining for the industry a set of resources, including entrepreneurial
ability.  The assumption is that resources will move to where they earn the highest
return.  This is perfectly valid in the long-run competitive economy and, furthermore,
it is desirable.  It should be pointed out that if the economy were perfectly com-
petitive, rates of return (profit) would be everywhere the same for similar resources
under similar conditions of risk.  Imperfections in the market from differing degrees
of uncertainty to barriers to entry result in varying rates of return.  Therefore,
the concept of a "normal profit" becomes ambiguous and laden with value judgment.
The best that can be done in an industry like solid wastes is to choose a rate of
return based on some clearly stated — and hopefully objective — criterion and call it
the normal profit for the industry.  Such a criterion might be what is earned by
other industries using similar types of capital and having similar capital/output or
capital/labor ratios.
                                                             _^_
        Economic profit (it) differs from accounting profit (it ) reported by business
mainly in that economic profit recognizes the opportunity cost of capital.  Thus
letting R = sales revenue, C = current cost, D = depreciation and amortization,
V = value of owner's equity, i = interest rate, and rt = profit, accounting profit
(n ) can be written:

                                K* = R - C - D  .

Economic profit takes account of the opportunity cost of capital and is written

                             * = R-C-D-iV  .

        Application of a rate of return criterion requires that the relevant para-
meters R, C, D, and V be identified.  This is frequently difficult to do since many
firms, and especially public agencies, do not always distinguish between current
and capital expenditures,  keep no depreciation records, and are merely guessing if
they set a value on their equity.  The tentative acceptance of a criterion does not
lessen the problem of data collection and manipulation.

        Value of land deserves consideration.  Land is a significant input in the
production function for disposal services.   It may be either privately or publicly
owned, and its user may or may not be its owner.  These considerations are immaterial
to a valuation criterion.   The opportunity cost of land, like any other resource,
is its value for its next best use.

-------
               (a)
              MC=AC
                    LRMC
                                               LRAC
                                           LRMC
                (c)
               MC>AC
                                                                         LRMC
                                                                           LRAC
                                       Quantity
     LRAC = Long-Run Average Cost
LRMC = Long-Run Marginal Cost
FIGURE   I.  RELATION  BETWEEN   MARGINAL   COST   AND  AVERAGE   COST
           Consider the process of sanitary landfill in the San Francisco  Bay  Area.
   Frequently this consists of Bay fill; i.e., actually creating land by extending
   shorelines.   Prior to landfill there was only potential value composed  of surpluses-
   rent  due to scarcity of land in the Bay Area and location rent because  usable  land
   contiguous to the water brings a market premium.  Alternatively,  land used  for disposal
   sites may be too vertical for development prior to fill.  In such cases the process
   of sanitary landfill creates usable land that immediately upon creation accrues
   surplus  value.  The net change in the value of space concomitant  with landfill must
   ultimately be a matter of value judgment.  The value of land, au  natural, in pre-
   serving  ecological balance must be weighed against its potential  use value.  Thus,
   a long-run view of land's opportunity cost might best be expressed as a benefit/cost
   ratio, where benefits are imputed as the value envisioned from a  fill project  and
   costs are the value of foregone benefits.  This approach to the problem has the
   advantage of yielding a criterion for choosing among alternative  sites,  viz.,  the sites
   with  highest benefit/cost ratios are chosen but this does not provide an immediate,
   operational method for "costing" land in the short run.  For this purpose the  cost
   of land  can best be taken to be its market rental price.  If this is not readily
   available,  it must be explicitly imputed from the market prices of similar  parcels.
   Tentative  Data Collection Procedures

           General  Considerations.  Any data collection procedure should progress  in
   two explicit  steps.  First, the purpose for which the data will be  used,  and by
   whom,  must be clearly recognized.  Second, the actual process  by which data will
   be  collected  must be designed with due regard for the type of  firm  being  considered.
   Firms  in a competitive market can be approached quite differently than those in
   monopolistic  markets.  The previous sections of this paper dealt with the underlying
   rationale  for data collection as well as some expected operational  difficulties and
   special economic considerations pertinent to both steps one and two.   In  this section
   are reviewed  some of these aspects while presenting some proposed data collection
   frameworks.

-------
                                                                                 37
        In the Second Annual Report three general categories of cost-sources for
the solid waste industry were identified.  They range from franchised scavenger
companies that operate both a collection-transport service and a disposal site to
individuals who provide self-service collection, transport, and disposal.  Some of
the possible combinations expected in the industry were listed in Table U of the
Second Annual Report.  A modification of the table is presented as Table 10 in this
report.

        Types of firms falling in category A operate regular collection services in
which wastes are picked up at the source and are transported to recognized disposal
sites.  The sites may be operated by the same company that provides the collection
service, or by another firm.  Firms may be private or public.  If private they are
franchised by a public agency—city, county, or special district—to operate in that
agency's jurisdictional area.  Thus, all firms in this category have some form of
public supervision and none of them operates in a competitive market.  These firms
are easy to identify, and in this case recognized public interest provides some
precedent for data requests.

        In category B "Firms and Individuals to Site," there are some special data
collection problems.  For the collection and transportation function two subgroups
can be identified, commercial contract haulers and self-service individuals.  The
latter's costs will probably need to be imputed since they are difficult to identify.
The former, if they can be identified, operate in a reasonably competitive market
making it possible to accept data on their revenues as equal to costs.  The decision
to identify and poll individual firms in this category will be made on a pragmatic
assessment of the expenses involved, budgetary limitations of the project, and benefits
of so doing.  If it is deemed too expensive, then these costs can also be imputed.
Costs for category B firms and individuals engaged in collection and transportation
can all be approached via data supplied from the sites they utilize.  Hopefully the
site operators will keep records on the quantity and composition of wastes deposited,
and these then can be utilized to develop cost estimates.   Regardless of the actual
approach taken, the costs associated with collection, transport,  and disposal for
this category can be obtained.

        Category C is conceptually vital and operationally complex.  It is vital
from a long-term viewpoint since some 60fo of solid wastes  generated does not go to
regular disposal sites.   During this phase of the study the entire category will be
held in abeyance while efforts are directed to developing cost functions for categories
A and B.  Attention again will be directed to wastes not going to site when later
objectives are incorporated in the study.


        Data Collection for Franchised Firms.  The main aspects considered in
designing the following data collection frameworks were the nonaompetitive nature
of the industry, the need to differentiate between public  and private firms, and
the need to obtain or apportion data along functional lines.

        From a bookkeeping point of view, expenditures (disbursements) must always
equal revenues (income).   The sum of all disbursements (costs of labor,  capital
including all equipment  and its maintenance, land and overhead,  plus taxes and
profits) must be a figure equal to the sum of all revenues, i.e.,  income from services
rendered plus loans or subsidies to cover any losses.  Thus,  it would seem that either
total revenue or total expenditure could be used to ascertain costs.  That this is
not true,  for true opportunity costs in the case of noncompetitive industries (or
firms), has already been discussed in the section on economic considerations.   There-
fore,  whenever possible  the Oakland metropolitan study will approach cost determina-
tion via a firm's expenditures.

        Operational exigencies can be expected to require  that in some cases revenue
data,  and in others,  expenditure data,  will actually be used.   This requires that
double accounting be carefully avoided.   If Scavenger Company A pays a disposal fee
to Company B,  that fee will be reported in the expenditures of A and it also will be
reported in the revenues  of B.  It must only be counted once  as a cost to the whole
industry.

-------
9
a
o
-p
oj

a
o

-p
•H
co

H
OJ
to
a
ra
n
13
1
•e
o
p<
B
jj
•d
B
0)
B
O
•H
•p
0
o
o









ra

oJ
O
W



«3*

O
o

cfl




*^H

O
U
1
B
p
oi
0
ra





^J Sj




P< O
0

o|
M 03
(U
S-t O
^ 
Oj -P
to ra


CM KA -d-




r*3
• o
0 B
O Q)
60
fc <•!
60 O
B 'ri
Q) i — 1



CO
O




















O O
-p P

 Eufi c~co cr\o foB r-i CM
H H r-{
m o

-------
                                                                                 39
        Firms must be differentiated as to type—public or private-to make sure that
their expenditures or revenues are comparable.  Public firms do not pay the franchise
fees and taxes paid by private firms, and their revenues commonly include tax sub-
sidies.  Further; it is often difficult to ascertain hov much of its resources a
public regulatory agency devotes to the supervision of the solid wastes industry
under its jurisdiction.  Frequently costs of this type are not explicitly considered
by public agencies; they are "hidden" in the bureaucratic structure.

        To meet all of the requirements listed in this and in the preceding paragraphs,
the data collection format lists detailed inputs to aid recognition of all costs.

        Tables 11 and 12 illustrate the format to be used in gathering data on the
expenditures made for the collection, transportation, and disposal of solid wastes.
The format, based on the program budget concept, allows expenditure? to be both
disaggregated among the inputs and allocated to functional outputs [ 17 & l8].  Each
row represents the expenditure made on an input, for example labor.  Each column
contains the expenditures made for functional output activities.  Thus the total
cost of labor is allocated to collection, transportation or supervision, and similarly
for all inputs.  Both rows and columns should add to the same figure, the total
expenditure for the activity in question.  Thus the bottom right-hand total when
added horizontally (rows) is the output expenditures and when added vertically
(columns) is the input expenditures.

        The format is designed to facilitate analysis.  It makes inter-firm com-
parisons of expenditures both by subfunction and by input costs relatively easy to
do.  However, to make the units comparable some common base is necessary.  Therefore,
data are needed on quantities of wastes handled as well as numbers of men and equip-
ment used in the operations.  These data can be requested on a separate form or
incorporated on the forms as shown in the tables.  In its ultimate form expenditures
should be expressed in terms of per ton of refuse processed.

        An alternative approach to arriving at costs for franchised firms is to
utilize revenue data.  The economic conditions that make this a less desirable
procedure than expenditures were discussed in the preceding paragraphs of this section.
Operationally this approach also is second-best, inasmuch as firms normally do not
keep revenues separately for collection and for transportation to site.  For analysis
these operations should be separate.  Moreover, revenue data would be aggregated
and do not permit inter-firm comparisons.  Thus expenditure data will be utilized
wherever possible.


        Data Collection for Firms and Individuals Transporting to Site.  Disposal
site operators in this category do not present problems different from those already
discussed.  Costing collection and transportation requires a new approach, however.
Since the market can be asserted to be competitive, firms engaged in contract hauling
can be polled to ascertain their revenues net of disposal fees, and these can be
taken as being equal to the opportunity costs of collection and transport to site.
Inasmuch as polling is a time consuming and expensive procedure when done accurately,
it probably would be more feasible in the study to impute these costs on the basis
of average distance to site and on average per mile haul cost for transport.
Collection cost can be reasonably imputed by using an average wage rate and collection
time.


The Empirical Study of Oakland Metropolitan Begion

        To formulate data collection procedures, identify problem areas, and generally
to provide an opportunity to test and refine the procedures, a pilot study of the
Oakland metropolitan region was initiated.  The empirical phase of the study of the
Oakland city portion is nearing completion.  Progress made to date consists of
defining the functional region, studying waste generation by types of wastes, and
identifying several public and private agencies involved in the various functions
of waste management.  In the present report a brief description is given of the
empirical study in its present state of progress.  The compilation of actual
expenditure data by function and agency within the region will be reported in a
later report.

-------
                            TABLE 11




FORMAT FOR TABULATION COLLECTION AND TRANSPORTATION EXPENDITURES




                      Firm 	(Name)	




                      Type (Public/Private)
^"^•-^^^ Outputs
^^•^^^
Inputs ^^^^^^
Labor -direct
route
maintenance
office
administrative
Labor -indirect
insurance
uniforms
fringes

Equipment rental cost
trucks
containers
Equipment operation
and maintenance
gas/oil
repair

Office
rent
supplies
telephone
equipment
Special Fees
license
franchise
taxes
professional
dumping fees
Total Output

Collection
































Transport
































Supervision
































Inputs Totals










Labor Sub -total







Equipment Sub -total











(Rows and Columns
add to total)

-------
                                      TABLE 12

                  FORMAT FOR TABULATING DISPOSAL SITE EXPENDITURES

                                Firm 	(Name)	

                                Type (Public/Private)
""•— -— ^____^ Outputs
Inputs ' _^_^
Land
Equipment :
Amortized Ccst
Operation and Maintenance
Labor:
Heavy Equipment Operators
Administrative
Other
Cover Material
Total Cost of Output
Disposal





Salvage





Supervision





Total Cost of
Inputs




Grand Total
Expenditures
        Description of the Study Region.  The study region is the Oakland metropolitan
region, a region which includes seven cities and peripheral unincorporated areas
functionally related to the waste disposal industry.  The area has a population of
slightly more than 800,000, and an area of nearly 129,000 acres with varying population
densities.  Nearly 351,000 people are employed in the region in various enterprises,
viz., government, services, manufacturing, and trade-  Agricultural employment is
insignificant, since the region is primarily urban in character.  The study repion
is described in detail in Tables 13 and ih.

        Apart from the seven city governments, a host of private and public agencies
are involved in one or more functions of the waste management industry.  A careful
identification of these agencies revealed that they are nearly 21 in number - some
private, some city, some special district, plus the county and state government.
All are engaged in one or more of five different functions, viz., l) franchised
collection of household wastes, 2) collection of commercial refuse, 3) collection of
special wastes, k) disposal site operation,  and 5) administration and regulation.
A list of these agencies by corresponding functions in which they are engaged is
given in Table 15-

        In addition to the major identifiable agencies given in Table 15,  there are
numerous contract haulers, industries,  and households that haul their own wastes
to sites.  In some cases,  the wastes do not even reach the disposal sites.  Instead,
they are disposed of by other methods,  e.g.,  agricultural wastes burned on the ground,
cannery wastes either hauled to sea or dumped into a sewage system, and industrial
and demolition wastes hauled to special sites not listed as disposal sites.  Thus,
identifiable agencies account for only a part of the total waste management industry.
Consequently,  there is a great need to supplement information by other sources.

-------
n
CO
s

•s



CO
•p
•H

i§
60
d
•H
a
r->
o
w
•d
(U
ft
3
O
O
O

0

id
rH
O

CO
ra
O
a


rH
d
-P
o
EH




>rl
O
CQ
1
CD
fl-l
O



d
CD
£


(H
O
>
-P
•H

0]
11
rl
<
H
rl
rH
CO
•Q"
EH


CD
H
ft
•p
H
I:



%
hO
•H
CQ

d
o
H
P
$
a
o
1,
d
o
H
3
~H
-^
O
li


ra
p
o
d
fj
iH
3 ^
ra o
fl d
S£













_=t- KN vo r— o t— ON vo
CMOVOVOLTNOOt—
LT\ CO VD O UN rH rH
KN VO rH

[— HN^l/Nt/NCMONH
f— ^t -=t D— C— H ONCO
rH H C— -3- rfNHVOO
HHKNCJN-3-VQK-NrH
-it- -d- -=i- CM H
H

ONKNOONHOC-LrN
CQ O\ -3- -d~ O K^ VQ H
OS ON ~3~ ON K\ ON ff~\
-cj- C"- OJ v£> OJ H
VO CM



CO CO KN VO -^f CM CV1 VO
CO-^fOCMt— COKAVO
HHKNLrNOHVQt—
VO S~\ rH CM CM -d- KN
C*- (A OJ CM rH





N-NCM ON C— CO ONCM KN
-3-OC^-N'NHO^-OO
ONCMCO O t>- t— rH CM
VO -j~ O ON -3~ rH H
N"N ' — 1 i — 1



oooooooo
LTNLrSocoOOOU'N
LrNU^ovo C— rH UNCO
[•— K"N.^t rHC^I>-rHCXJ
C- -Cf H ON -3- rH rH
rTN rH rH

CO H LT\ CO
CM VO VO .4- CM
^~ ^ ^ ^
±4 §§ S ra p pq M
O 1 1 1 1 < On
I VO <; ON CM ' '
rH-^t-HC\JC\]r-HC— VO
o^^^oSSS
ON KN CO t— t~- LTN CM rH
ON CM CM H


rd d)
d rl
0) >
d CD
CD OH
rl r( H > d > -P H
^d 'd CD d d -ri
d^lrHCUO^Op
H f ^ H-3 d "3 ff

hTN
O
ON
CM
H
KN
O
CO
0
co
CM

^j.
CO
ON
VO
0



ON
rH
CO
I—
H



ON

H
ON
CO
c-



o
ON
LA
0
CO





CVI
CO
H








d
(D
!H
<3j

H
d
CD

•P
O
d

rH
H
•H
3

ra
•P
o
a


o

CD
0)
R
CO
a
s
o
^H
0)
rl


O
HJ
tu
•N
O
rH

,0
rH
^
A


•H
^
fj
•H
J>
•H
•d

CQ

CD
H
rH
•H

CQ
•P
O
d
rl


•H
f—j

H
|
0
CJ
CD
•d

o
^
a
rl
O
fa


CO
d
K
cO

M
d
•H
d
d
d
H
ft
CD
ri
d

ra
d
CD

^<
o
•rH

»j

O
tsl
d

C.

•1

d
CO
to

ra

3
rH
o
d
•H
d •
CU TZJ
rl CD
^^
M rl
d o
•rl ft
d rl
d o
p [ -r-i
•d S
rl
d H
? H
Pa d

ra
•H
* cO
ts) (D
-H ^
P*  hD
co d

d d
<3
b>i r — I
CD
•H rH
rl rH
ft£

-d o
CD rl
-P H3
d CQ
rl CO
a°
ri
O •
o fd
d CD
•H -P
d 03
o
ra ft
3 ri
rH 0
p. 0
C
CQ 'H
CD d
•H 3
-p
•H ra
0 -rl

-------
3

a
H C
ff) O
0 M
EH d)
K
•d
•d HJ
r< rl 01 CO
d O X d)
1^1^
°-d 43
d FH t^^- rHLTNrH
C7\ cr\cO OJ H
rH \O OJ t— H Q5 C^
§OJ t^- D— -4" ^J- \O O
V£l CT\ OJ O\CO CTS O
r-HCO IA t— -* ^- O N^
OJ ^O H O H O t—
H H
88888888
OC^-VOLrNHrHC^OA
J- H LA CA H IT\ ITS
rH IA OJ IA H J- ^
OOOOOOOO
OOOOOOOO
-S--4-OCOOAON^OJ
OJ CO OJ CO OJ K> ON
rH OJ
[—
H O\ OA O\t— CT\^-
rH^'lMU^CO(?
OrHQAOOOOH
•NrH-* LAVO f- O\
LA
rH
on, Public Utilities
1 Estate
o
OJ
-=f
H
LT\
ro
O
OJ
vo
o
-^-
8
CO
(A
7$
§
c~
^0


           O  to   0)
           o -P   o
               o   c
            r- PH   cd

        M o -d   p
    c   c  -H  a   co
S>  O  -rl  -P  rji   S
^ Jl   fc!  S  ..  H     -P
                                               -p
                                               (J
                                               flOOtdDiD
                                               HoJpjwoo
ta
                                                                                            1
                                                                                             d
                                                                                            0
                                                                                            H
                                                                                            Pi
                                                                                            o
                                                                                           >
                                                                 ra

                                                                 •S
                                                                                                     cd     a
                                                                                                    r-l      cd
                                                                                                     .      rH
                                                                                                           "3
                                                                                                           'go
.H

!>
                                                                                                                         !§
                                                                                   •
                                                                             e>   i,
                                                                             -i-i  •3
                                                                             >
                                                                                                                         3
                                                                                                                         CO   FA
                                                                                                                        "i   0) HJ

                                                                                                                       -d  ^  g
                                                                                                                           ^    D -d
                                                                               M     tn
                                                                               ra ,

                                                                           o  -a3  h
                                                                          ^  p  01  t
                                                                           <8  -P  hD
                                                                          rH  w  eg
                                                                                                                           o      E

                                                                                                                          ^-r?g
                                                                                                                          O -H  HH
 O-H

    co
 tocn

-H  <

-------
W r-t
-P d
O S £3 W
o; o O ^i
rH ft -H ft
O QJ P-i
O (K
£
O
••-* d
"d 5
ft '-p
•p T3 oj
W C r3
•H CO 2
c 5
W CO
tfl tlQ 0
O (*H d 'a
CU O ? -H
W QJ W
•rl CO 0)
P Pi
H
w d
-P -H a
O O cq

rH CJ <£H


00
0
tn
W Tj
W rX C!
-P ft |

C D P-i c H
O H d «0
IS S5 I
i ^ ^
to
-p t>= ft

CJ ? -p
H isS
O -H uJ
o £ M
-p ft
CJ QJ (fl
QJ -P C
H -p d
H -H O

O

-P -P C
O QJ -H
QJ 0) PJ
H ft O
H -p a
O CO ^
0 CO
C
o
QJ -P
•p d
•H ft
CO 0)
O
QJ ft
W O
•H -p
i-d CJ
O QJ
§ H
rH °
&4 o











q
Q>
DO
•s

S5

















x x xx xxxx










X XX









X X XX XX






X X





X XX XX






x x x x xxx






XXX X XX






X XX X




3 O -H
-P fl O i>

ft £l .— J C fl
0 fi Cfi 0
a, o w -H ^
ft O O >> -P O 03
o o PJ c d ft •<-<
O r-H ftwdftTJ dcJ
>, H-POJ-HP.OS -3 ft
rHQj •(HdQOQBP'nJr^rt3QJO
C-HO ^Soj^oo^ddS-H
gj'y^ ftfO>ca O SHr^r-l

^Sm^aScop §fftcSffioeH°^1
eHeHf^[i_,iVHtJ(2w 8>O>)OO(4 HPOOO>) 43
£QJ aJKflJ -PQJtsO
>1cfl,>1HS>%'H -^H^^^g-P-H

Cj<|OPHOOOCoSp^OOOOCO



X








X XXX


X XX























































C
aj
-P -P
0 CH c- o
•H O O «H
ft -rl ft
-P -P -P -P
w >> c d -P w
•H -P Q) i> CJ -H
Q *H 6 ft C -H Q
H -P QJ O ft
^ -H ft W -iH -p >-,
ft -P d C CQ ID ft
d £> P- O w -H d
CM 3 E >5 C
gPi QJ d o ft d
•H 43 ^ m o d co
o o d -P -P
•H -H -P H O -P -H ^
tOC COaJOCCQJ
QJ P QJ [D QJ d H
u rH o P^ d
St^rl CO CO Qj^*
tfi dft ft-H COiH E
Fqpq+3 OH ftQj O O
w CH p h !> f-1! ft
4J 4^ .H -H IJ fl) -p
w WO'-fP-i S3O O w
W W O CO O O

-------
                                      TABLE 16

             ESTIMATES OF WASTES RECEIVED AT THE SAN LEANDRO MARINA SITE

                              Owned by San Leandro City
             Operated by Turk Island Co., 14222 E. l4th St., San Leandro
Haulers
Parley Batt from Berkeley Site
Other Commercial Haulers
S & R (Pranchised Collector)
Handy Can (Franchised Collector)
Mf g • Industry
Household Self -Haul
Demolition Companies
TOTAL
cu yd/yr
68,435
59,926
121,738
1,048
61,016
64,955
4i,948
4i9, 064
lb/cu yr
@ 400
@ 250
@ 250
@ 250
9 250
@ 250
@ 400

tons/yr
13,68?
7,^91
15,217
131
7,627
8,119
8,390
60,662
        Source: Turk Island Company.
        Quantity of Wastes Generated  in the Study Region.  The inability to identify
 all the waste generated  in the area presents a unique problem in determining the
 annual quantities of wastes actually  generated in the study region for planning
 purposes.  Quantities of wastes received at the disposal sites usually are under-
 estimated.  Among the reasons behind  the low estimates are methods of making estimates
 from  daily averages and  exclusion of  certain wastes if they are currently salvaged.
 Estimated quantities of  wastes from collectors represent only those from the franchised
 collection of wastes, and hence they  also are incomplete.

        Despite the difficulties listed in the preceding paragraph, an effort was
 made  to estimate quantities of waste  generation on the basis of information from
 disposal site operators  in the Oakland area.  Data obtained from the seven disposal
 site  operators in the area were usually incomplete, and frequently were of  dubious
 accuracy because the estimates were not based on any actual weighing of the material
 at  the sites.  Data obtained from the existing sites are given in Tables 16 and 17.
 Detailed data were available only for the San Leandro marina.  In all other cases
 the data on wastes received at the site were aggregated, and were reported in
 summary form as in Table 17-

        Judging from the data collected from the site reporters, a total of 5^-1,300
 tons/yr are produced.  Using this estimate it appears that waste generation in the
 study region is approximately 3-^ pounds per capita per day.  It should be noted
 the the figures on which the estimate is based are highly incomplete.  To arrive
 at  a  real number for per capita generation, and to make any meaningful analysis, other
 sources of waste generation and collection must be tapped.

        To develop a more complete and consistent set of data on waste generated in
 the study region,  a multiplier technique developed earlier was adopted (cf. Second
Annual Report).  For purposes of estimation, 51 types of wastes were defined ana are
 listed in Table 18.  The types can be broadly classified as household and related
 (municipal wastes), agricultural,  commercial and services, construction and demolition,
 and manufacturing.

-------
f-
rH
I
1

c3
      g
      H
£
C

-f


'c
E
a
•d
O

CD
3
&
rH
cd
•H
O
S
g
o
C)

rH
cd
•H

-p
3
rd
S3
H
id
CD
ra
-H
43
o
S3
cd

fe




ra
CD
-p
ra
cd


•d
•H
rH
O
ra
fH
cd
cu
>H




Cj
C]
Jf

CJ

a
c
C
C
a

P

)
^
3
I
H
1


rH
cd

1
H
£

3
cd
S3





SH
CU
rH
p!
g


O
•P
O
CD
H
H
O
O





3
o
-p







-d

o


CJ
J
>
H
3
H
j
0
3
1
r)
-1
3






cd



O
CM
C—


O
CM
H
rH





O
VO
H
CM~



0)
C
&




O
o

_-^
H









O CD
CM CO
-s O
in o
rH J








1
rH
<






cd



CO

-=t
a
H





l/N
r—
CO
o
CM






Q
0
CM
i-T
KN



tf\ O tf~\
rH O rH
M"\ CM LT\
H H CM
KN K"N VO


43 CD
co hO
•H cd
P P

K U

O cu
LTN ra
-, o
O 0
tr\ ,_)
CM ^





t-
cu
rH
cu
m



H
f«~N
ON
»\
rH
CM

C~
a\
CO
CT?






t-
C7\
00
CM"
rO






o
o
o
v6~
K^i
1-1


LT\ O ITV
CM O CM
f- O t-
f— VO K^
CO rA CM
rH CM

43 CD
ra bo
•H (3
rQ .Q
"§ h

--^
tA CU
K~N -P
ON O
- cd
K-N a,
f^ e
CM o
o

-P
cu
cu
-p
CO
CO
•H
cd
P


a
0
ON

•^
co


CJN
rH
H
CO

CO
c-
rH
H
CM





t—
CM
VO
c-^

cu
CO bD
-4- cd
*i 'fi

i — 1 *fZ U
^ —

,JJ
Ln t— CM
t — CO ^O
ON VO VO
vo ro o
-* rHNO








r~*
KN CU NA -p
vo to -* o
- o -. cd
O o co ft
1A|J VO fi
rA^-' o
O


o
•d

cd S3
CD -H
Cj !^
cS
ra






cd



rH
LTN
vo
^P
-4-





CM
ITN
__P
-=1-






c—
o\
vo
^p
LTN





_-j-
_^J-
H















S3
O
-p
S3
•H
-P
ra
CD
*



























vo



CD
g




O
O
O
VD
hO

















•d
Jn
cd
O
CU
fn
•H
fe



H
CM
KN
r^
O
KN

ITN
CM
CO
vo"
o\





ON
O
rr\
u \
vo
c—
rH





ITN
CM
c-^
hTN
CM


g
KA
rH
_-j-
LTN















K

s
1— 1 ^
IB


                                                                                                 CD
                                                                                                 rH
                                                                                                 CD

                                                                                                 !H CU
                                                                                                 CU -P
                                                                                                 pq -H
                                                                                                    co

                                                                                                 o cd
                                                                                                 -P fH

                                                                                                 o s
                                                                                                 •P S r.
                                                                                                 S3 O CU
                                                                                                 g O Wl


                                                                                                 •P $~* CU
                                                                                                 ^H CU t>
                                                                                                    EM cd
                                                                                                    a o
   cd id
ra o s3
,M ra cd
£H    i—I
O id -M
& S3 a)
   cd O
O rH
•H >i -d
rH Cd S3
P O Cfl
                                                                                                 Ei  -H  Cd
                                                                                                 ctj  B  ffl
                                                                                                       e -p
                                                                                                       o cd
                                                                                                       V -P
                                                                                                          ra

                                                                                                       d cd

                                                                                                       rT3
                                                                                                    CD ra
                                                                                                    O H
                                                                                                                -p
                                                                                                                o
                                                                                                                fl

                                                                                                                CD
                                                                                                                JH
                                                                                                                cu
                                                                                                                3

                                                                                                                CD
                                                                                                                -P
                                                                                                                ra
                                                                                                                cd


                                                                                                                c
                                                                                                                o
                                                                                                          CD  rj

                                                                                                          •3  cd

                                                                                                          CH
                                                                                                          O  rH



                                                                                                          |  5
1§
                                                                                                                CO
                                                                                                                  o
                                                                                                                  -p

                                                                                                                  cu

                                                                                                                  •H
                                                                                                                  ra


                                                                                                                  CD
                                                                                                                  rH
                                                                                                                  CD
                                                                                                                  CD
                                                                                                                  pq


                                                                                                                  o
                                                                                                                  CD
                                                                                                                  -P
                                                                                                                  O


                                                                                                                  •d
                                                                                                                  CD
                                                                                                                  •d



                                                                                                                  CD
                                                                                                                  CD
                                                                                                                  P
                                                                                                                        •d
                                                                                                                        od
                                                                                                                        rH
                                                                                                                        cd
                                                                                                                         CD


                                                                                                                         cd
                                                                                                                  ra
                                                                                                                  S3
                                                                                                                  o
                                                                                                                  -p

                                                                                                                  t-   P
                                                                                                                        S
                                                                                                          S3 £>
                                                                                                          i!
                                                                                                                H  fe
                                                                                                                s  «<
                                                                                                                aj i)
                                                                                                                rH  *"
                                                                                                                cu +3
                                                                                                                51 5
                                                                                                           "^  
-------
                              TABLE 18

                       SUMMARY OF WASTE TYPES
 1  Domestic garbage and rubbish — single unit
 2  Domestic garbage and rubbish — multiple unit
 3  Lawn clippings and prunings
 4  Septic tank residues
 5  Large appliances and furniture
 6  Street sweepings
 7  Tree trimmings of city streets
 8  Leaves
 9  Litter cans
10  Trash collected along highway right-of-way
11  Sewage treatment residue
12  Residue from incineration
13  Abandoned vehicles
14  Local parks and playgrounds
15  Regional parks
16  Dirt and rubble from excavating, e.g., from BART
17  Demolition waste from razing buildings v
18  Construction waste
19  Garbage from group eating facilities
20  Commercial refuse from stores, offices, public buildings, shopping
      centers, transportation terminals, etc.
21  Orchard prunings and dead trees
22  Crop wastes and residues
23  Manures
2k  Dead animals
25  Greenhouse and nursery wastes
26  Infectious material from hospitals and clinics
27  Hazardous radioactive materials
28  Other noxious wastes, as acids, insecticides, etc.

                        MANUFACTURING WASTES
29  Ordnance and accessories
30  Cannery wastes
31  Other foods
32  Tobacco
33  Textiles
34  Apparel and fabric products
35  Lumber and wood products
36  Furniture and fixtures
37  Paper and allied products
38  Printing, publishing
39  Chemicals
40  Semisolids from oil refineries
4l  Other petroleum manufacturers
42  Rubber and plastics
43  Leather
44  Stone, clay, glass, and concrete products
45  Primary metals
46  Fabricated metal products
4-7  Nonelectrical machinery
48  Electrical machinery
49  Transportation equipment
50  Instruments
51  Miscellaneous manufacturing

-------
        In  general, the estimation of vaste quantities (W.) is done by a simple
linear weighing system:
                                    W  = a.X.
                                     i    11
where
        W. = the total waste generated by source i

        a. = the appropriate waste multiplier; and

        X. = the source units of waste type i.  (i = 1, ..., 51) •


        For municipal wastes (households and related types), various source units
were used in making estimates.  Household wastes were estimated separately for
single-family and multiple-family units; wastes from city streets, sewage treatment
residue, and local and regional parks were estimated on a per capita basis, using
population as a factor.  Wastes from freeway and county roads were based on number
of miles.  In each case an appropriate waste multiplier was used.  The detailed
estimation procedure and the estimates are indicated in Table 19-

        The production of agriculture wastes is nominal in the study region, inasmuch
as the region is primarily urban in character.  However,  relevant estimates of
agricultural wastes were made on the basis of the land use (in acres) and appropriate
waste multipliers.  The resulting data are listed in Table 20.

        Amounts of wastes generated by commercial and service activities and by the
construction and demolition industries are difficult to ascertain under present
circumstances.  Much remains to be learned about the nature of waste generation by
these two types of industry; and the methods employed so far are as yet crude.  In
this study, waste from these two main types of sources were estimated by two methods.
The first method involved using employment in an industry; while the second used
size of city as the source unit.  In each case an appropriate multiplier was used.
Estimates based on employment were high and far from accurate.  Estimates based on
city size were more reasonable, and hence were used later in the study.  The detailed
calculations on wastes from commercial and service activities are given in Table 21;
and those on construction and demolition in Table 22.

        Manufacturing wastes were estimated by utilizing appropriate waste multipliers
and employment number in relevant industries are defined by Standard Industrial
Classifications.  The waste multipliers were developed and reported in an earlier
study  [l] .  Detailed calculations and the procedures used in this study are given
in Table 23.

        Those wastes having the highest multipliers are the ones generated by the
industries falling into one of the following three categories :  l) stone, clay,
glass, and concrete; 2) lumber and wood products; and 3)  furniture and fixtures.
As a result, these three categories apparently contribute nearly one-fourth of the
total manufacturing wastes even though their corresponding employment is slightly
less than 10$ of that in all of the manufacturing industries.  A significant portion
of these wastes currently do not go to public disposal sites.  It is also known that
most of the cannery wastes (seasonal foods) in the study region are taken by barge
for ocean disposal.  Moreover,  some of the wastes from paper and related industries
and from the metals industries  are are salvaged and recycled into the economy at
the source itself.  These facts influence the definition  of wastes and waste
multipliers, and it is possible to refine the multipliers further than has been
done in this study.  The problem is well recognized, and separate studies have
been started to improve the waste multipliers by source.   In the meantime, until
better multipliers become available, estimates developed thus far should be used
with caution in any actual implementation.

-------
                                        TABLE  19

                ESTIMATION PROCEDURES AND ESTIMATES OF MUNICIPAL WASTES
Waste Source
Household Garbage and Rubbish
Single Family Unit
Multiple Family Unit
City Streets: Leaves, Litter, Sweepings,
and Tree Trimmings
Refuse Collected Along Highway Right -of -Way
Freeway Refuse
County Roads Refuse
Sewage Treatment Residue
Local Parks and Playgrounds
Regional Parks
TOTAL WASTE
Multipliers

1.U2910 tons/unit/yeara
0.62755 tons/unit/yeara
U2-9 Ib/capita/year13

8.0 tons/mile/year0
3 • 3 tons /mi le/year
87-1 lb/capita/yeare
"P
5-4 Ib/capita/year


Source
Units

173,819s
106,98U8
758,230*

62 x
200d
805,930g
805,930g


Tons/year

2^8, 405
70,3^7
16,26^

496
660
35,098J
2,176
^15R
373,861
 Multiplier for household garbage and rubbish are from FMC Corporation Santa  Clara  Study,
 Systems Analysis for Solid Waste Disposal by Incineration (1968),  pages  22,2$.   Single
 family unit multiplier includes estimate of refuse hauled to disposal site by householder
 himself.

 FMC Corporation Santa Clara Study,  pages 52,53-   The multiplier is obtained  by  dividing
 total street sweepings and tree trimming wastes  (1,758 tons) by the population  (82,^82).

Multiplier for freeway refuse developed from weight and volume data from FMC study.

 Multiplier for county roads refuse  computed from information about mileage and  volume
 of refuse, which was supplied by Road Division of Alameda County.

eFMC Corporation Santa Clara S^udy,  page 51-
*f*
 FMC Corporation Santa Clflra Study,  pages 5^,55-

^Estimate of population and occupied housing units are from Alameda County Planning
 Department and are for July 1967-  The population of Castro  Valley, and  unincorporated
 area is excluded from this total.  Its street refuse is listed under county  roads  refuse-

"Excluding Castro Valley street sweepings.

''"Data on total freeway mileage in the county was  supplied by  State  of California
 Division of Highways, District k.  The study area's proportion of  the county total (57$) was
 determined by use of a contour meter.

 Including Castro Valley street sweepings.

 Mr. Lynch, Acting Chief of Maintenance Department,  East Bay  Regional Park District.

-------
50
                                     TABLE  20

                                ASaCULTURAL WASTES

Apricots
Cherries
Vegetables, terries, and
seed crops
Greenhouse and nursery
Feedlot cattle manure
TOTAL AGRICULTURAL WASTE
Source Units
310 acres
53 acres
3,61^ acres
125 acres
QkO head

Multiplier
1.5^20 tons /acre/year
lA265 tons /acre/year
3-0 tons /acre/year0
25-0 tons /acre/year
13.21 tons/head/year6

Tons /year
478
76
10,8^2
3,125
11,096
25,617
     Basic  crop acreage  and livestock  inventory  is from Alameda County
     Agriculture Commission Report  (1967)-  Data was allocated to subcounty
     areas  with help  of  Alameda County Agriculture Extension Office.

     Apricot  and cherry  orchard waste  multipliers determined by estimate of
     trees  per acre from University of California Agricultural Extension
     Service  and per  tree waste multipliers from FMC Corporation Santa Clara
     Study.

    cState  of California Department of Public Health, Status of Solid Waste
     Management in California, 1968.   We used an average of the five
     multipliers given for  field and row crops on page 111-17-

    Professor Harry  C.  Kohn, Department of Environmental Horticulture,
     Davis  Campus of  the University of California. (Verbal Communication).

    SThe  manure multiplier  for cattle  is from Taiganides, E. Paul, Table h-,
     Agricultural Solid  Wastes.  Three of the cattle manure multipliers in
     his  table averaged  to  72.4 Ib/day.

-------
                                                                                   51
                                      TABLE  21

        ALTERNATE ESTIMATES OF WASTE  GENERATED BY COMMERCIAL ORGANIZATIONS

                                   AND SERVICES8
Size of City Population
> 100,000
(l) 10,001 - 100,000
1,001 - 10,000

Waste
Multiplier
Ib/cap/day
3-5b
2.5*
2.0*

Applicable
Population
635,100
167,980
2,850
805,930
Waste
tons/yr
405,670
76,641
1,040
483,351
(2) 3.81011 tons /employee/year0 x 265,401 employment = 1,011,207
  Standard Industrial Classification 40  -94.


  Dept.  of Public Health,  State  of California,  Status  of  Solid Waste
  Management in California,  1968.

 Q
  Multiplier developed from employment data  from Dept.  of Employment
  and unpublished data from FMC  Corp. Santa  Clara Study.
        A summary of waste quantities by waste sources is given in Table 24.  On
the whole, the study region accounted for nearly 1.52 million tons of solid wastes,
or nearly 10.3 pounds per capita during the year 1967-68.

        To make further comparisons of waste generation as based on multipliers with
costs and quantity estimates obtained from agencies listed in Table 15, it was
necessary to disaggregate the regional totals (Table 24) by subregion.

        Eight subregional areas were recognized:  namely, the cities of Albany,
Berkeley, Oakland, Piedmont, Emeryville, and San Leandro, and the Castro Valley and
Hayward areas.  Efforts are being made to allocate wastes by source to each of these
subareas.  Neither Castro Valley nor Piedmont has any manufacturing industry,  and
Albany accounts for very little.  Most manufacturing is done in Oakland, San Leandro,
Hayward, and Emeryville, although Berkeley has some food processing, chemicals, metals,
machinery, and "miscellaneous" industries.

        A comparison of the estimates given "by site operators with those derived with
the use of statistical multipliers indicates that some 6-91 pounds per day per capita
currently were not going to disposal sites.  This amounts to 67$ of the generated
waste not going to the site — a significant figure to be considered in all future
management and control of disposal activities .

-------
                                     TABLE 22

              ALTERNATE ESTIMATES OF WASTES GENERATED BY CONSTRUCTION

                                  AND DEMOLITION8
Size of City Population
> 100,000
(l) 10,001 - 100,000
1,001 - 10,000

Waste
Multiplier
Ibs /capita /yr
500*
25013
100"

Applicable
Populat ion
635,100
167,980
2,850

805,930
Waste
tons/yr
158,775
20,997
1^2
179,91^
(rounded)
180,000
(2) ill. 25205 ton/employee/year0 x (19,262) employment = 79^,597
aStandard Industrial Classes 15, 16, 17-

bDept. of Public Health, State of California, Status of Solid Waste
 Management in California, 1968.

"^Multiplier developed from construction employment data from Dept.  of
 Employment and unpublished data from FMC Corp. Santa Clara Study.
       Given the present state of knowledge concerning the study region and solid
waste estimates, based on multipliers, the following considerations should be mentioned:

    1. Salvage operations need more investigation;

    2. Some types of waste are disposed of by other than landfill, i.e., such as
       products that are burnable, e.g., furniture;

    3- Demolition wastes are frequently used as base-fill;

    ^. Multipliers using population as a weight factor would probably benefit
       from further disaggregation based on incomes;

    5- Manufacturing estimates require further research.
       The above considerations will be borne in mind and remedied as far as possible
before further work on the analysis of private and public expenditure is continued.

-------
                                   •CABLE 23

                              MANUFACTURING WASTES
Industry
Seasonal Foods
Other Foods
Total Food Products
Paper, Printing, and Publishing
Chemicals
Textiles and Apparel
Rubber and Plastics
Leather
Total Other Nondurables
Stone, Clay, Glass, and Concrete
Primary and Fabricated Metals
Electrical and Nonelectrical Machinery
Lumber and Wood Products
Furniture and Fixtures
Transportation Equipment
Instruments
Total Cther Durables
Other Manufacturing
TOTAL MANUFACTURING EMPLOYMENT
Employment
July 1967
2,200
11,482
13,682
6,478
1,900
2,193
1,835
355
4,383
3,708
15,250
12,478
1,033
1,562
2,768
915
6,278
2,500
66,657
Multipliers13
tons/employee/year
5-56570
4.81655

12.87060
8.21075
•52575
1.54810
2.49365

18. 11425
6-7300
3 . 58o4o
21.68805
20.15545
3-39330
2 . 51700

2.49365

Waste
tons /year
12,245
55,304

83,376
15,600
1,153
2,84],
885

67,168
102,<'32
44,676
22,4o4
31,483
9,393
2,303

6,234
457, -97
Basic employment data is from the State of California Department of Employment
Community Labor Market Survey.  Data was adjusted to exclude Union City which is
not  in the study area.  Employment in the categories "Other Durables" and "Other
Hondurables" was distributed to the relevant SIC groups by using the same proportions
as existed in the 1965 employment data from ABAG.

Multipliers for the manufacturing industries were developed and reported in  Table  VI,
Comprehensive Studies of Solid Waste Management, Second Annual Report.  The multiplier
for  the category Paper, Printing and Publishing (SIC 26 and 27) is a simple average of
the  separate multipliers for SIC 26 and 27-  Also, the multiplier for the category
Electrical and Nonelectrical Machinery (SIC 35 and 36) is a simple average of the
separate multipliers for SIC 35 and SIC 36.

-------
                          TABLE 24




SUMMARY OF ALL WASTES GENERATED IN THE OAKLAND METROPOLITAN AREA
Waste Source
MUNICIPAL
Single Family Unit Housing
Multiple Family Unit Housing
Street Sweepings and Other Street Refuse
Sewage Treatment Residue
Local Parks and Playgrounds
Regional Parks
Refuse from Highway Right -of -Way

Construction and Demolition Waste
Commercial and Public Facilities
AGRICULTURAL
Orchard Primings
Crop Wastes and Residues
Manures
Greenhouse and Nursery Wastes

MANUFACTURING
Cannery Wastes
Other Foods
Textiles and Apparel
Lumber and Wood Products
Furniture and Fixtures
Paper, Printing, and Publishing
Chemicals
Rubber and Plastics
Leather
Stone, Clay, Glass, and Concrete Products
Primary and Fabricated Metals
Electrical and Nonelectrical Machinery
Transportation Equipment
Instruments
Miscellaneous Manufacturing

TOTAL

248,405
70,347
16, 924
35,098
2,176
415
496




554
10,842
11,096
3,125


12,245
55,304
1,153
22,4o4
31,483
83,376
15,600
2,84i
885
67, 168
102,632
44,676
9,393
2,303
6,234










373,861
180,000
^83,351





25,617
















457,697
1,520,526

-------
                                                                                 55
A METHOD OF OPTIMAL SITE SELECTION AS APPLIED
TO SOLID WASTE MANAGEMENT
General Remarks

       The problem of determining the optimal location of waste generating points
and disposal sites -was discussed in Chapter IV of the Second Annual Report [l].
The original formulations of the procedure for obtaining the optimum solution were
necessarily theoretical; and hence, certain assumptions were made to ensure that
the optimization procedure would not be unduly complicated.  These assumptions have
since been subjected to the realities of solid wastes management, and corresponding
improvements and variations of the original formulation have been made and were
issued in the form of special reports by El-Shaieb [19] and Stern [20].  In this
section, one variation of the network flov model is applied to the nine-county
San Francisco Bay area.  The area has 116 waste generating points and 60 disposal
sites.  The program developed and applied herein is still experimental in nature,
but it serves to illustrate the applicability of the mathematical model for a
practical situation.  The procedure described herein could be considered as a short-
run solution to a waste disposal situation in which landfill is the overriding method
of disposal and the transportation costs are of greater concern than those for
disposal.


Introduction

       The main problem considered by El-Shaieb [19] was as follows:  Given a set
of destinations n, their cartesian coordinates of locations (x.^, y^) (i = 1, ...,n)
and their requirements Wj_, the problem was to find 'm' disposal sites located at
(xj, y) j = 1,—, m, such that the cost function F(x,y) is minimized, where:
                             F(x,y) =  )   /a   w  £
                                       l—j  i—i  ij  i  ij
                                       i   J

 8ij = the distance; or unit cost, between destination i and source j and is taken as:
             [ 1 if the destination i is assigned to source j;  or 0 otherwise.
                     i    J

       Defining Cjj = v^-y, the problem is reduced to finding (aij),  such that
is minimized subject to the conditions on a-M • • -(i=l, • • -,n,  and j=l, ...,m).  When
'm1 is greater than one, the problem is usually referred to as "the multiple source
location problem" in operations research literature.

       El-Shaieb developed a branch and bound procedure that constructs source and
destination sets by adding one location at a time.  Once a feasible set has been
established, the objective is to reduce the number of feasible source  sets
constructed in order to reach the optimal solution.

       Before applying the El-Shaieb definition  and procedure to the present problem
in solid wastes, it should be noted that the usage of the terms "destinations" and
"sources" as conceived in operations research language is somewhat confusing to the
present  application.  The word "destination" is changed to mean the "waste generating
point" (or  simply the  "generating point") and the work "source" is changed to mean
"disposal site" (or simply, "site").

-------
56
 Modifications of the Problem

        The general network flow model as  described in the  preceding paragraphs
 considers all points as both potential generating point and disposal site.   This,
 of course, is unrealistic,  and obviously  there  is need to  modify  the original
 formulation.   Moreover, a distinction should be made  between existing disposal  sites
 and potential disposal sites .  The  potential sites may or  may not be selected by the
 procedure employed.  There is some  argument with respect to the fixed cost  of opening
 new disposal sites, and also to variation in the operating costs  by capacity of the
 existing sites.   These arguments are  not  emphasized in the present  formulation,  and
 will be considered in later studies.   The problem now is to recognize the existing
 disposal sites in operation and the set of potential  sites from which to choose and
 then to arrive at the optimal solution.

        The above factors lead to the  modification of  the original formulation.   The
 following model is now defined for  application:

 Let

        S = set of all existing disposal sites,  (= s)

        P = set of all potential locations where disposal sites could be
            established, (= p)

        D = set of waste generating  points,  (= n)

        m = set of additional (potential)  disposal sites to be located out of
            P.  (m is a criterion number specified outside  the model).


        The objective of the revised model is essentially that of  the previous model,
 i.e., to minimize the cost function F(a..)- An Important  difference, is that the
 optimization program will consider  all possible flows from all 'i1  to all  'j1 where
 (i=l, ...,n) and (j=l, • •-,s+p) and i not equal to j, inasmuch as a given location
 cannot be both generating point and disposal site. The change then is:

                   Minimize:
                                    n    s+p
                           F(a..) =  )    >  a.. C..
                              10    £_.   Z_,  !J  iJ
                                    i=l   j=l

                   Subject to:

                                  I 1 if generating point i  is assigned to site j
                           aij    JO otherwise.


        The various assumptions underlying the mathematical model, along with their
 implications  on the real world situation, are treated in the paragraphs which
 follow.  It is recognized at the outset that the assumptions are  more or less
 "enabling" and are fashioned to accommodate the present programming technique.   In
 future work,  each of these enabling assumptions will  be relaxed to  make the model
 more widely applicable.

        Assumption 1 — The unit transportation costs are independent of the  amount
                       shipped.  This  assumption is fairly  common  and any suitable
                       transportation  cost function can be  used.

        Assumption 2 — The optimal number  of disposal  sites (m) to be chosen from P
                       (the set of potential sites)  are given.This assumption  is
                       dictated by the nature of the algorithm used  rather than  by
                       any theoretical considerations.

-------
                                                                           57
 Assumption 3 ~~ Fixed cost of opening a new disposal site is negligible or
                zero-  This assumption is convenient;  but if it were true at all
                times,  then the question of which new disposal sites should be
                opened and at what time intervals becomes trivial.   The total
                transportation costs  will not be increased by nearly opening
                a site  as long as  there is no shipment to that site.  To
                circumvent this difficulty,  some schedule must be selected for
                the selection of new  sites,  m, during the designated time
                period.  In this study it is assumed that one new site is made
                operational each time the capacity of an existing site is
                exhausted.  This number could easily be two,  three,  or any
                number.  Although  this seems arbitrary it does have  the merit
                of practicality.  The fixed cost of opening sites could be
                considerable, and  only one new site can be opened by each city
                or public agency due  to budget restrictions.   It is  therefore
                realistic to assume that only a limited number of potential
                sites can be opened at a given time.

 Assumption k — The time  over which the optimum schedule is desired  is assumed
                to be 75  days.   The time horizon over which the optimum schedule
                is based  is one of expediency.  This target data could well have
                been five years if that were desired.   For the present,  75 days
                is used as an illustrative target date.   The  selection of a
                particular planning horizon does not influence the program
                itself.  If a large horizon like five  years were to  be chosen,
                then the  corresponding average waste generated during the
                period  would have  to  be used with similar changes in the
                transportation  costs  for each different  year,  month,  or  day,
                if desired.  This  can be easily accommodated  in the  program
                by causing a certain  elapsed time to trigger  the reading of the
                new set of data.  These trigger dates  can be  chosen  at random.
                Since the new set  of  data represents an  average over the  previous
                elapsed time,  it is strongly suspected that the optimum  solution
                obtained  may be a  qualified  one and may  vary  with the  time
                horizon chosen.

                     Another effect of a longer time horizon  would be  to
                require a more  elaborate cost matrix.  In the  present  problem
                quite a few distances  from generating  points  to sites  were
                chosen  as infinite, and thus  the  generating points were
                allocated to the few  nearby  sites.   This  is possible  in the
                short run where  the site capacity may  not be  exhausted.  Hovever,
                If a  longer time horizon,  such as  five years  were to be  chosen,
                then  the  number of possible  flows  would  increase enormously
                and a larger transportation  cost  matrix would be required.

                     Thus  the choice  of  time  horizon may affect the optimum
                solution  in two  ways:  l) by  necessitating different averages
                to be triggered  at  frequent  time  intervals; and 2)  by  increasing
                the number of possible network flows to be  examined.   The
                effects of planning horizons  are  stated as  possible hypotheses
                for future  experimentation.

Assumption 5 —  There are  no capacity restrictions on the disposal  sites.  This
                is one  of  the most  important  of the  assumptions.  To a great
                degree  it  determines the programming procedure used in this
                study.  Though the  disposal  site capacities are  in fact
                recognized at a  later stage  (when a  site  is filled) and
                rescheduling is  done,  the actual allocation of generating
               points to  sites  is   done  on an  instantaneous or minute-to-minute
               basis.  In other words, the program  developed and used in this
               study treats each disposal site as if it has Infinite capacity,
               up to the very moment it is exhausted.  This assumption of no
               capacity restriction does indeed give a qualified optimum
                (suboptimum).  Its   implications are  described in the next
               section (Procedure).

-------
Procedure

        With the mathematical program as developed in the present study,  locations of
disposal sites are chosen which should be made operational out of a given number of
possible potential sites.  The program does not provide for considerations of any
scheduling requirements on the transfer vehicles carrying solid wastes from the
generating points to the disposal sites.  It is assumed that enough transfer vehicles
are available for doing the job.  The program recognizes the already existing sites,
S, and then chooses the specified number, m, of new potential sites from a set of
given potential sites, P, such that the total transportation costs are minimized.
When the fixed capacity of the disposal sites is recognized, it may so happen that
some of the sites may be filled before the target date.  The program output specifies
when that eventuality will take place, which disposal site is closed, and how the
new allocation will affect the scheduling of wastes from generating points to new
disposal sites.

        The method of recognizing capacities of disposal sites described  in the
preceding paragraph raises a procedural question which is yet to be resolved.  The
allocation or scheduling of wastes to sites is done in this program on a  minute-to-
minute (or instantaneous) basis rather than on a realistic time horizon.   The program
treats each site as though it had infinite capacity up to the very moment it is
exhausted.

        The mathematical calculations involved a complete enumeration of  all possible
combinations of m out of P potential sites and corresponding allocation of flows to
take place.  As P increases, the number of necessary computations also increases
rather rapidly.  Accordingly, a branch and bound technique was employed.   The
technique reported herein is a modification of the earlier version given by El-Shaieb.
The object of this procedure is to reduce the number of feasible sets constructed
from P in order to reach the optimal solution.  After considering the various
combinations of potential sites and tacking them on to the existing set of sites,
only those sets were considered which met the feasibility requirements, i.e., select
m out of P.  Lower bounds were established to select the most promising of these,
and actual evaluations were then computed for them.  The set with the lowest actual
evaluation was then chosen as the current candidate.  The steps involved in arriving
at the evaluation are given in Appendix A.  All sets with a lower bound greater than
this evaluated value were dropped from further considerations.  The procedure was
repeated until there were no more sets with a lower bound less than the evaluated
actual value associated with the current candidate set.  Although at the  time of the
scheduling no explicit assumption of the site capacity was made, it was later introduced
to make it possible for the branch and bound technique to work.

        The method of treating the fixed capacity of sites as applied in this study
is perhaps the most serious limitation of the present approach.  The following
illustration emphasizes the consequences of such a procedure:  Suppose that two
waste generating points, A and B, both initially minimize transport costs by shipping
their respective wastes (Wi and Wa) to disposal site (l).  Assume, further, that the
capacity of site (l) will become exhausted halfway through the nominal planning
period, and that the cost differential between shipping to site (l) and shipping
to the next best alternative is for A, $2.00 per truckload; and , for B,  $5-00 per
truckload.  Assuming that the constraint on the second best alternative for A is
not effective, it is obvious that existing capacity in site (l) should be allocated
as much as possible to wastes coming from generating point B, leaving A only that
capacity which remains after B's requirements were satisfied at any given time.  The
program described earlier, in which the minute-to-minute scheduling horizon is used,
does not recognize the capacity constraint until it is reached, and so ships to site
(1) all wastes from A and B.  It then designates the next best route for both A and
B when the capacity of site (l) has been exhaused.

        The questions remaining for further investingation are the following:  Does
the planning horizon affect the optimum solution?  Similarly, does the definition
of the functional boundary to include or exclude a particular waste generating point

-------
                                                                                 59
also affect the optimum?  In other words, is the total transportation cost minimized
over the entire nominal planning period for any given functional "boundary?  Efforts
now are under way to investigate these questions and to lessen these limitations
in the future.  For the moment, a choice must 'be made "between using the method to
obtain a qualified suboptimum; or to experiment with a very large number of generating
points and sites and propose different definitions of planning horizons and functional
boundaries, and even so achieve perhaps only a marginal reduction in transportation
costs.

       To recapitulate, the present program assumes no fixed cost of opening new
disposal sites, sets up a hypothetical planning period for scheduling, and provides
a rough procedure for recognizing site capacity restrictions.  Some real world
situations will be introduced later in the research program, and thereby relax the
assumptions listed earlier.


Application of the Modified Algorithm to Solid Waste

       As is evident from the preceding formulation, to limit the size of the problem,
the application of the model requires data on location of waste generating points,
existing disposal sites, potential sites, quantities of wastes shipped to site,
transportation distances and unit costs, site capacities, and finally the target date.

       Selection of Disposal Sites and Waste Generating Points.  The present study
is being carried out with reference to the nine-county San Francisco Bay region, viz.,
Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano,
and Sonoma counties.

       Viewed in general framework, the problem of collecting solid wastes from each
and every home in a city is in itself a large and complex transportation and scheduling
problem.  For the purposes of this study, it was assumed instead that all wastes in
a city were generated at a central point (centroid) from which they were shipped to
a disposal site.  In the present study, this central point — representative of the
city — was usually taken as the downtown section.  Die only exception to this procedure
was with respect to the city and county of San Francisco, which was broken up into
12 different sectors and each sector treated as a city by itself.  Further refinement
is possible by treating larger cities like Oakland and San Jose as a cluster of
small cities —as was done in the case of San Francisco.  Hovever, this was not done,
because to have taken such a step would have resulted in making the problem unmanage-
able.

       As far as the disposal sites were concerned, no major assumptions were
involved.  The sites were also treated as points, but the extent of approximation
involved here is negligible when compared to assuming a city as a single generating
point.

       The entire San Francisco Bay Area region was thus broken up into 116
generating points.  For detailed discussion, see the Second Annual Report.  For the
existing sites the latest report put out by the California State Department of Public
Health [21] was used.  Since the reference period for the study reported herein was
chosen to be 1966-67, all sites with a remaining capacity of 10 acre-feet or less
at that time were neglected, because it was assumed that they would be used up by
the time this report was under way.  All special sites (which receive only special
wastes such as demolition wastes,  liquid industrial waste, etc.) were also ignored,
since they would not be relevant for the purposes of solid wastes considered in
this study.  In all,  the available, currently existing disposal sites were reduced
to 60 in number;  for which corresponding data on wastes, population, etc.,  were
developed.

       The potential sites were chosen from among the various  proposed general
sites pending approval from the local public health agencies.   Sites most likely
to be approved were chosen to serve as potential sites.   In addition,  some of the
currently existing cities,  whose capacities  could be easily increased by the
acquisition of land nearby,  were considered as potential sites.  Thus,  a total of
14 potential sites were selected.

-------
60
        The Cost Matrix, Cjj •  The cost matrix, GJ.J, gives the unit transportation
 cost of hauling wastes from generation point i to the disposal site j.  Though
 transportation cost -was expressed in terms of distance in the earlier formulation,
 the actual program was formulated in terms of travel time.  Therefore, the cost
 matrix Cij will be developed from a distance matrix %j, which is then translated
 into travel time •

        The waste generating points and disposal sites were plotted on the imp, and
 the distance &ij was chosen as the minimum distance over major roads leading from
 generating point i to disposal site j.  Freeways and major arterial routes were
 generally perf erred to minor roads because it was felt that distance saved on the
 latter would be more than offset by increased travel time-  Since 7^ x 116 measure-
 ments on the map would have been required to form the complete &^_* matrix, a simpl-
 ifying assumption was introduced.  Actual measurements were made only for a few
 sites nearest to the generation point under consideration, while distance was assumed
 to be forty miles for all other sites.  An average of seven or eight actual
 measurements were taken for each city.  The number varied from as low as three to
 as high as fifteen, depending on the amount of waste generated by that city.  For
 example, it was felt that a city like San Jose, which produces 1,272 tons of waste
 per day, should be given a wider range of choice regarding disposal sites than
 should be given to St. Helena, which produces only 6.9 tons per day.  If in the
 solutions a certain city had been alloted to one of the distant sites, more actual
 measurements would be included for that city and the program would be rerun.  It
 must be noted, however, that this procedure was followed only for convenience and
 to reduce unrealistic combinations.  It in no way affects the generality of the
 program itself.

        Once the distance matrix (&±j) was established, it was converted to transpor-
 tation time involved for the round trip by using a plot of the average haul speed
 vs. total haul distance as developed in SERL Bulletin 8 [5].  In Table 25 are given
 pertinent data excerpted from the Bulletin.  This process allows computation of
 travel time with a nonlinear relationship to distance.  The data compiled therein
 were obtained prior to 1952 and consequently the average speed figures used here
 probably are outdated.  However, because the purpose of the study is to demonstrate
 the application of an algorithm rather than to derive immediately useful results,
 the discrepancies are ignored as irrelevant for the moment.  It should be noted that
 the transportation time was developed for the round trip, inasmuch as the transfer
 vehicles and men would be tied up for this duration of time. To calculate the cost
 per ton of transporting solid wastes, the following formula developed by Dair [22]
 was used.  The cost is based on a standard 6 -ton truck with a 2 -person crew as
 follows :

       n  4.     4-        -4-    r$(2-55 + 0-325 s + 5.40L + 0.95) t 1
       Cost per ton per minute =  " — — -    (q\ ftn -   —


        Where ; t = travel time in hours, S = tonnage of solid wastes hauled, and L =
 labor (man-hours).  Using the above formula,  the cost/ton/minute is obtained as
 (0. 0^514 t), substituting S = 6 tons and L = 2 (man-hours).

        For any particular flow of solid wastes, i.e., from generating point i to site
 j, the total transportation cost is estimated by inserting the appropriate estimate
 for 't1 in the expression (0.0^51^ t).  The actual cost matrix, sometimes referred
 to as the distance matrix, as estimated in the present study consists of slightly more
 than 1,000 elements.  The elements are already undergoing revision for a later study
 and hence they are not included in this report.

        Solid Wastes:  Generation points (i) and amounts generated (WjJ.  The amount
 of solid wastes generated at the point 'i1 and transported to any of the disposal
 sites is represented as Wj_.  The generation point could be a complete city or a part
 of it, or an urban area not incorporated into a city.  The primary source for
 developing V± is the information tabulated in the Second Annual Report (cf . Table 2,
 page 19 of the report).  The procedure used in estimating Wi is given in the paragraphs
 which follow.

-------
                                                                          61
                               TABLE 25




                  TRANSPORTATION TIMES FOR COLLECTION
One Way
Haul
Distance
in
Miles
0.5
1.0
1-5
2.0
2-5
3-0
3-5
4.0
4-5
5-0
5-5
6.0
6-5
7.0
7-5
8.0
8-5
9-o
9-5
10.0
10.5
11.0
ii-5
12.0
12.5
13.0
13.5
14.0
14. 5
15-0
15-5
Average
Speed in
min/mile






4.10
3.60
3-35
3.22
3-15
3.09
3.01
2.96
2.90
2.84
2.78
2.72
2.66
2.60
2.54
2.48
2.42
2.36
2.JO
2.24
2.18
2.12
2.06
2.00
1.94
Adjusted
Travel
Time in
Minutes
Round Trip
18. £
20.5s
22. 5a
24. f
26.5s
27. 5*
28.5
29.0
30.0
32.0
3^-5
37-0
39-0
M-5
43.5
45-5
V7-5
49.0
50-5
52.0
53-5
5^-5
55-5
56-5
57-5
58.0
59-0
59-5
59-5
60.0
60.0
One Way-
Haul
Distance
in
Miles
16.0
16.5
17-0
17-5
18.0
18.5
19.0
19-5
20.0
20-5
21.0
21.5
22.0
22.5
23.0
23-5
24.0
24.5
25.0
25.5
26.0
26.5
27.0
27.5
28.0
28.5
29.0
30.0
40.0
50.0

Average
Speed in
rain/mile
1.88
1.82
1.76
1.70
1.64
1.58
1-53
1.48
1.44
l.4i
1-39
1.38
1.38
1-37
1-37
1.36
1.36
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35
1-35

Adjusted
Trave 1
Time in
Minutes
Round Trip
60.0
60.0
60.0
59-5
59-0
58.5
58.0
57-5
57-5
58.0
58.5
59-5
60.5
61.5
63.0
64.0
65-5
66.0
67-5
69.0
70.0
71-5
73-0
75-5
77-0
78.5
79-5
81.0
108.0
135-0

Represents extrapolated values.

-------
62
        In the earlier study of the nine-county San Francisco Bay area, the study
 region was divided into h2 functional boundaries, each of which was termed a "Disposal
 Service Area" (DSA).  The concept of DSA was very useful in compiling consistent
 and comparable information on wastes generated and the wastes generators.   This
 information was further broken down to estimate waste flows from each generating
 point.  In this study, the h2 DSA's have been broken down into 116 waste generating
 points (i=l,..., 116) and the waste data have been updated to correspond to a more
 recent year, namely, 1968.  The actual procedure is described below.

        Consider for example, the Oakland DSA (code No. 0102).  This DSA accounts
 for about 1,652 tons of solid wastes generated per day.  The wastes include mostly
 population-oriented wastes and some commercial wastes.  First, the waste figures
 were reduced to correspond only to household or population-oriented wastes; i.e.,
 the waste figure 1,652 was reduced to the 1,602 tons assumed to be generated by the
 population (692,000) within the DSA.  The DSA consists of 10 waste generating points,
 some complete cities such as Hayward, Piedmont, and Albany, other partial  cities
 such as Oakland and Berkeley, and other urban areas such as Castro Valley  and San
 Lorenzo which are not within city boundaries.  The total population of the DSA
 (692,000) was further broken down by these generating points.  These population
 figures were used to apportion the total wastes (l,602 tons/day) among the 10
 generating points.  Similarly, the other hi DSA's were broker, down,  with all 116
 waste generating points established within the nine-county San Francisco Bay area.
 All of the above calculations are summarized in Table B-l of Appendix B.   The
 waste data in the table pertain to 1966.   The waste figures were updated to 1968 on
 the basis of population growth and the updated numbers incorporated in Tables B-2
 and B-3 of Appendix B-

        Remaining Capacity Vector.  This represents the capacity remaining  to be
 used in the existing and potential disposal sites as of July 1968.   The original
 capacity referred to 1966.  These were updated again to reflect the  capacities
 remaining as of 1968 by using the rate at which they were receiving solid  wastes in
 1966.  For the potential sites this means the available capacity when that potential
 site becomes operational.  In the case of some of the potential sites,  where no
 capacity figure was available, the capacity was assumed to be very  large,  namely
 15,000 acre-feet.  The capacity data in acre-feet were converted to  tons,  using an
 average density of 600 cu yd per ton of solid wastes.  The detailed calculations
 are given in Appendix C .

        Discussion of Results.  The output of the program run under the  condition
 that one new site be opened for each existing site closed down is  listed in
 Table 26.  It can be seen from the results as listed in the table that  the program
 stipulates to which site  the generating points should ship their wastes when their
 existing flows cannot be  accommodated from the present site.   For example,  at the
 end of the first 15 days,  the disposal site coded 16 is filled to existing capacity,
 and a new site,  Ho.  J>}  should be opened.   At the end of 6l days,  site Ho.  hj is
 closed,  and a new site No. 7 is opened.  The various allocations of  waste  generating
 points,  closing down of particular sites  and opening of new sites, are  described
 in Schedules  1 through 5  until the target date of 75 days  is  reached.

        Since  it is stipulated that at least one new site be brought  into action  for
 every existing site  closed down,  limitation is placed upon the  practicability of the
 solution so obtained because it maintains at least as many sites operational as
 existed at the start.   This  may not be a  desirable situation,  and the reason for
 being forced into it concerns the limitation of the  theory employed  and hence the
 program.   It  should also be  noted that the theoretical model  does not mention the
 fixed costs  involved in opening up a new  site.   If fixed costs  are also taken into
 account,  then the added decision of whether to open a new site  and when  it should
 be opened can  be  built  into  the program itself.   Unfortunately,  very little  has  been
 done so  far in this  area to  include fixed costs  of a site  along with finite  capacity
 of the sources and make it operational for a large enough  study area.

-------
                              TABLE 26

OUTPUT OF THE EROORAM UMBER THE CONDITION THAT ONE NEW SITE BE OPENED
                 FOR EACH EXISTING SITE CLOSED DOWN
Generating Point
Nuniber

This schedule will
be in effect from
day 'a'
to
day Tt>'
This schedule
results in closing
of site number 	 *•
opening
of site number 	 »-
1
2
3
4
5
6
7
8
9
10
ll
12
13
14
15
16
17
18
19
20
21
22
23
2k
25
26
27
£8
29
30
31
32
33
34
35
36
37
38
39
40
1*1
42
43
kk
45
46
47
48
49
50
51
52
53
54
55
56
Wastes Should te Shipped to the Following Site Numbers
Schedule
One


0.00

15.21


16
3
66
63
64
64
65
62
68
33
32
31
31
70
69
70
74
74
70
72
72
71
71
71
72
22
24
24
24
26
26
26
26
26
26
23
65
26
26
16
62
15
27
27
27
15
15
28
29
29
29
29
29
29
29
29
29
29
Schedule
Two


15-21

61.21


43
7
66
63
64
64
65
62
68
33
32
31
31
70
69
74
74
74
70
72
72
71
71
71
72
22
24
24
24
26
26
26
26
26
26
23
65
26
7
15
62
15
27
27
27
15
15
28
29
29
29
29
29
29
29
29
29
29
Schedule
Three


61.21

67-00


29
6
_
_
.
_
-
_
.
-
-
-
-
-
-
.
_
-
73

-
73

-
73
6
_
-
_
_
_
-
-
-
-
-
_
_
.
-
-
.
_
.
_
.
_
_
_
_
-
_
-
-
-
-
-
-
Schedule
Four


67-00

73-95


73
9
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
72
-
-
-
_
.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
27
15
9
9
28
27
15
27
15
27
Schedule
Five


73-95

Target date


10 + — -
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
70
-
-
71
-
-
-
-
-
-
-
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
                                                                                  on day 'V

                                                                                  on day 'a'

-------
TABIE 26 (Continued)
Generating Point
Number
57
58
59
60
61
62
65
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
85
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
101+
105
106
107
108
109
110
ill
112
113
114
115
116
Wastes Should be Shipped to the Following Site Numbers
Schedule
One
15
16
16
16
16
17
17
18
19
19
20
21
21
23
22
^
33
kk
38
38
43
39
39
ho
4i
i+l
59
42
1+2
1+2
1+2
46
1+8
1+8
50
50
51
59
57
57
57
57
52
55
52
3
58
61
1+3
36
36
36
36
36
36
36
36
36
1+3
^3
Schedule
Two
15
15
15
15
15
17
17
18
19
19
20
21
21
23
22
43
33
1+4
38
38
*V
39
39
1+0
>+l
i+l
59
1+2
1+2
1+2
1+2
1+6
1+8
1+8
50
50
51
59
57
57
57
57
52
55
52
3
58
61
^3
36
36
36
36
36
36
36
36
36
43
43
Schedule
Three
_
-
-
-
-
-
_
_
-
-
-
-
-
-
-
44
_
-
-
_
38

-
_
_
_
_
_
-
_
-
_
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
.
36
-
-
-
-
-
-
-
-
-
44
44
Schedule
Four
_
-
-
-
-
-
r-
_
_
-
-
-
-
-
_
-
-
-
-
_
-
-
-
_
_
_
-
_
-
_
-
_
_
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
_
-
~
Schedule
Five
_
_
-
_
_
_
„
_
_
_
_
_
_
-
_
_
_
-
_
_
_
-
_
_
_
_
_
_
_
_
_
_
_
_
-
-
-
-
-
-
-
-
-
-
-
-
-
_
-
-
-
-
-
-
-
-
-
_
-
~

-------
                                                                                 65
       Another implicit assumption was that the variable costs of disposing of solid
wastes are linearly related to the amount of the solid wastes disposed of at the
site.  This cost is implicitly present in addition to the actual transfer of solid
wastes.  This assumption makes separate calculation unnecessary, inasmuch as the
cost of disposal is added in the same proportion, irrespective of the allocation.
The main reason the variable disposal cost cannot be treated as a function of the
volume of the wastes coming to the site is that disposal costs cannot be determined
until the allocation is known; and the allocation cannot be determined until the
variable costs are known.  This problem is not unsoluble; but in the  present state
of the art, no computationally feasible algorithm exists for a problem of this size.

       The solid wastes management field is one area in which the technique developed
herein could be effectively employed.  The problem facing most communities today —
both large and small — concerns not only the efficient use of existing disposal
sites, but also an efficient transfer of solid wastes.  The application of the type
of algorithm developed in this part of the study can be helpful in developing an
optimum solution toward selection of sites and transfer of solid wastes.  Although
capacity restriction on the sites does limit cost minimization somewhat and result
in sub-optimum solutions, it would at least help in ranking the potential sites on
the basis of costs.  Different variations of this algorithm to alleviate the existing
limitations are already under progress and will be reported in due course.

-------
                     III.  OPERATIONS RESEARCH IN SOLID WASTES


        The comprehensive solid wastes generation and disposal model described in
Chapter III of the First Annual Report [U] continued to provide the framework for
the activities of the operations research group since the publication of the Second
Annual Report [l].  During this time the emphasis shifted from models of optimal
flow patterns of waste and optimal operating policies for disposal plants (short-
planning horizon models) to the longer horizon problems of forcasting waste loads
and optimal dosposal plant expansion strategies.


MODEL FOR FORECASTING WASTE LOADS

        The basic rationale for the comprehensive solid wastes generation model
mentioned in the preceding paragraph was derived from the Leontief Input-Output
technique-  The objective was to forecast a solid waste profile for an arbitrary
geographical region and time period.  The mode of attack was to augment a basic N
by N interindustry Leontief model by M new indistries.   Each new industry representing
the service of disposing of waste of a particular type  such as garbage, radioactive
wastes, wrecked automobiles, etc.  In this section of the present report, this
approach is reviewed and an approximate procedure is developed to compensate for the
present difficulty in obtaining adequate data on the waste disposal service industries
themselves.  The method is then applied to the nine-county San Francisco Bay region
and forecasts for solid wastes generation in the region are proffered for a horizon
of ten years.


The Leontief Model Augmented by the Solid
Waste Disposal Service Industry

        The Leontief Input-Output model is essentially  a set of linear equations
relating the input and output of the industrial sectors of a particular region.  The
basic equation equates the production of each industrial sector to the amount
consumed by the consumption sector - the consumption sector being comprised of the
household, government, capital investment, and net exports.   The following is a
representation of the N-sector industrial region:
                                          y..;  1=1,2, ...,N                        (l)
where
        x. = the value in millions of dollars of goods or services  produced
             by industrial sector i in one year

       a.. = the value of goods or services of industrial sector i,  in
             millions of dollars, required in the production of one
             million dollars of goods or services by industrial sector
             j (referred to as technological coefficients)

        y. = the final yearly demand of goods or services of type i,  in
             millions of dollars, by the consumption sector

In matrix notation the following is obtained:

                                     X = AX + Y                                  (2)
                                         66

-------
                                                                                  67
                                    (I-A)X = Y                                   (3)


where

        I = the N by N identity matrix

        A = an W by N technological coefficient matrix

        X = an N-order column vector of total output production of goods or services

        Y = an N-order column vector of final demands for goods or services .


        Assuming the regional economy is viable, arjd therefore the inverse of (l-A)
exists, the production vector, X, may be found by:
        Kius, given a forecast of the final demand ^vector Y, the corresponding
levels of production (X) of each of the N industrial sectors may be found.

        These N equations may be augmented by the addition of M waste service
disposal industries.  Equation (l) becomes:
                Xi=Z,  VJ+Z,  al,n+kVk + yi;l=1'"->N                   (5>
                    \— "i         v—i
                    J—J-         -K.—J.

where

          x    = the number of tons of waste disposal service of type k utilized
           n+k   .
                 in one year

        a.     = the value of goods or services of industrial sector i, in millions
          '      of dollars, required for the disposal of one ton of waste of type k.


        Additionally M equations of type (5) are required to represent the waste
disposal service industries themselves.
where
                                     a.     x   y.j  i=N+1, ...,N+M                 (6)

                                 k=l
            x. = the number of tons of waste disposal service of type i performed
                 in one year by waste disposal industry i

           a.. = the number of tons of waste disposal service of type i required
            1J   in the production of one million dollars of goods or services
                 by industrial sector j

        a.    ,  = the number of tons of waste disposal service of type i required
          '      per ton of waste of type i,n+k serviced by waste disposal
                 industry k

            yi = the final yearly demand of waste disposal in tons of waste  of
                 type i by the consumption sector.

-------
68
         The resulting N+M equations  incorporate  the  interdependence  of the  M vaste
 disposal industries  of the region with  its basic N industrial sectors.  Of  interest
 here are the last M  industries,  in particular the quantities  x^+^^xjj+g, • • -.>XN+M>
 which represent the  amount of waste  processed "by the M waste  disposal industries .
 This then is equal to the amount of  waste generated  by the  industrial and household
 sectors  of the economy as reflected  in  (6),  assuming that the government sector is
 absorbed in the N basic sectors.
 A First Approximation of Total Wastes

         As a first approximation it was  decided to  drop the  intermediate  input
 requirements of the waste service industries  themselves.   Thus, Equation  (5)  reverts
 to Equation (l),  and the expressions for total  waste  (6) becomes:
                        i/ijji*            J * * * y                         \ i /
                           0=1

         It should be  noted that  the  production  levels for the If basic  industries  will
 be  underestimated due to the  exclusion  of  the required  inputs to the waste  industries
 themselves.  This in  conjunction with the  delineation of the M  terms in Equation  (6)
 causes  the forecast for total waste  to  be  underestimated.

         Hie procedure for finding the total waste  levels, x. ;i=N+l, .. .,N+M,  from
 Equations  (l) and (7) is as follows:

     1.   Estimate  the  final demands yi;i=l,...,N for  the N basic industries.

     2.   Find the  corresponding production  levels for these N industries from
         Equation  (l).

     3-   Using these production levels as the x^ in (7), coupled with estimates of
         the waste services demanded  by  the household sectors, yi;i=w+l, .. .,IW-M, and the
         waste coefficients, a^j,  compute the x-^ for  all the M waste disposal
         industries.


 Ten-Year Forecast of  Solid Wastes for the
 Mine-County San Francisco Bay Region

         The total waste for the  nine-county San Francisco Bay region was  forecasted
 for the years 1970, 1971*,  1978.   The model was  calibrated for the year 1966  from
 data obtained from the planning  portion of this study.  The method used in the
 forecast is that  described in the preceding section.  Due to difficulties obtaining
 data, all  types of waste were treated as one, reducing the set  of equations  in (7)
 to  one  of  the form,
                                      N

                                        a.x. +  y                                  (8)
 where
         x = the  total quantity  of  solid waste of all types,  in tons,  produced  in  one
             year

        a.  = tons of  solid waste of all  types per one million dollars  of output by
         J    industry j

         j  = the  total quantity  of  solid waste of all types,  in tons,  generated by
             the  household sector of the economy-

-------
                                                                             69
                               TABLE 27





TOTAL WASTE BY SECTOR (28) - NINE-COUNTY SAN FRANCISCO BAY REGION,  1966
Sector
j
1
2
3
k
5
6

1
8
9
10
11
12
13
Ik
15
16
17
18
19
20
21
22
23
24
25
26
27
28

Description
Livestock & Livestock
Products
Other Agricultural
Products
Forestry & Fishery
Products
Agric., Forestry &
Fishery Services
Metal Mining
Crude Petrol & Natural
Gas
Stone, Clay & Fertilizer
Mining
Construction &
Demolition
Ordnance & Accessories
Food & Kindred Products
Textiles & Apparel
Lumber & Wood Products
Furniture & Fixtures
Paper & Allied Products
Printing, Publishing &
Allied
Chemicals & Allied
Petrol. Refining
Rubber & Misc. Plastic
Leather & Allied
Stone, Glass & Clay
Primary Metals
Fabricated Metals
Non Elec. Machinery
Elec. Machinery
Trans . Equipment
Prof. & Scient. Instru.
Misc. Manuf.
Commercial & Public
Facilities
Output Level
Millions of
Dollars
x.
0
$ 170.32
232.69
1.59
18.79
9-01
121.84

3,676.22
957-45
3,680.55
222.75
122.26
376.83
492.93
653-72
1,545.72
75-22
19-39
377-58
459.11
736.14
654.99
1,035-21
789.14
112.38
276.75
2,030.95
413.87
$15,796.63

Waste Output
Tons
Va
1,386,460.
942,014.
0.
0.
0.
0.

0.
981,061.
15,053-
678,712.
5,751-
95,211.
115,329-
131,280.
335,450.
115,312.
151,692.
3,793-
165-
188,877.
95,141.
166,083.
92,901.
108, 702 .
62,080.
10,060.
4,183.
4,377,376.

Waste Coeff.
Tons/Millions of
Dollars
aj
$ 8, 140.32
4,048.36
0.0
0.0
0.0
0.0

0.0
1,024.66
4.09
3,046.97
47-04
252.66
233-93
200.82
217.02
1,532.99
7,823.21
10.05
0.36
256.58
145.26
160.43
117-73
967-27
224.32
4-95
10.11
$ 277.11


-------
                             TABLE 28




AGGREGATED DEMAND VECTORS FOR NINE-COUNTY SAN FRANCISCO  BAY REGION61
Sector
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
IT
18
19
20
21
22
23
2k
25
26
27
28
Y1966
68.55
119-58
.22
3.46
2.17
.08
3,525-41
825.19
3,517-35
214.29
93.43
103.70
458,10
44.83
1,206.97
28.71
10 . "C
66-78
334.33
269.21
16.54
49^.91
168.90
47-86
133.27
1,695-31
324 . 12
12,575-76
Y1970
82.26
143-50
.26
4.15
2.60
.10
4,230.49
990.49
4,220.82
257.15
112.12
124.44
549.72
53-80
1,448.56
34.45
12.92
8o.lt
401.19
323.05
19-85
593-89
202.68
57.43
159.92
2,034.37
388.94
15,090.91
Y1974
98.71
172.20
•32
4.08
3-12
.12
5,076.59
1,188.59
5,064.98
308.58
134.54
149.33
659.66
64.56
1,738.04
41.34
15-49
96.16
481.43
387.66
23.82
712.67
243.22
68.92
191.91
2,44i.25
466.73
18,109.09
Y1978
110.45
206.63
•38
5-93
3-75
.14
6,091.91
1,426.31
6,077.98
370.29
161.45
179-19
791.60
77-47
2,085.64
49.61
13.59
111-39
577-72
465-19
28.58
855.20
•291-85
82.70
230.29
2,929-50
560.08
21,730.91
      20$ grovth per four-year period.

-------
                                                                                  71
        No account was taken for technological change either in the technological
coefficients of the N basic industries or in the waste coefficients (aj).  The
technological coefficients  (&jj) used in Equation (l) were obtained from the multi-
regional input-output study conducted by the Economic Evaluation of Water Project at
the Sanitary Engineering Research Laboratory, University of California, Berkeley.
This was in the form of a 38 x 38 sector input-output table of technological
coefficients (ajj).  This matrix was aggregated into a 28 x 28 sector matrix of
coefficients.  The sector descriptions may be found in column 2 of Table 27-  Using
the final demand vector for the 28 basic sectors (shown in column 2 of Table 28)
for the year 1966, the vector of production levels, X, was computed (shown in
column 3 of Table 27).  The waste output for the base year, 1966, for each of the 28
industries was based on studies by the planning and economics team, and are tabulated
in column 4 of Table 27-  The waste coefficients required in Equation (8) are tabulated
in column 5 of Table 27 and were obtained by dividing the elements of column 4 by
those of column 5-

        The total waste produced by the household sector, y, was estimated from the
per family waste coefficients obtained from the city planning study.  These are:

                        h  = 1.43 tons/single-family unit
                         s
                        h  =0.66 tons/multiple-family unit-

The housing forecast for the nine-county San Francisco Bay region obtained from the
BASS Study is tabulated in Table 29.  The data for the year 1966 were found by
interpolation, and when multiplied by the per family waste coefficients, resulted
in a value of y = 1,800,000.  This amount is to be added to the total waste output
for the 28 industrial sectors found at the bottom of Table 1 in column 4.  The
resulting forecast in tons of solid waste, utilizing Equation (8), is

                     x = 9,8o4,86o + 1,800,000 = 11,604,860

        Using the same technological (a^j), industrial waste (a.), and household
waste (hs,hm) coefficients, a forecast was obtained for the years 1970, 1974, and
1978.  It was assumed that the gross regional product increased at a nominal rate
of 4.65 percent and that this was reflected in the growth of the final demand for
the region.  The final demand vectors, Y^, for the year t are shown in Table 28
and were obtained by the following relation for t equal to 1966 and n equal to
4, 8, and 12.

                                Yt = (1+0.046)^


        The production vectors XI^-JQ, xi974, and xj^yS given in Table 30 were computed
from Equation (l).  These values were in turn multiplied by the appropriate waste
coefficients, found in column 5 of Table 27, to obtain the total waste output for the
industrial part of the economy.  The total waste generated by the household sector
of the economy for each year of the forecast was obtained by multiplying the household
growth data of Table 29 by the household waste coefficients.  The total waste forecast
is summarized in Table Jl.

        The effect of the growth of the economy on the household waste coefficients
will be considered in future work.  This will be done by relating gross regional
product to average incoire of single- and multiple -family dwellings;  and in  turn,
relating average income to household waste production.  Regression techniques are
currently being employed for this purpose-


Extensions and Refineiasnts

        The assumption that all elements of the final demand vectors will increase
at the same rate as was made for convenience only.  The assumption leads to a
sequence of output forecasts and waste forecasts vectors that are multiples of the
1966 vectors.  An obvious refinement is to forecast the growth of final demands

-------
 72
                                     TABLE  29

           HOUSEHOLD FORECAST FOR THE NINE-COUNTY SAN FRANCISCO BAY AREA
Year
Type of Housing
Single -
Family
Dwelling
Multi-
Family
Dwelling
Waste of
Single
Dwellings
( tons )
Multiple
Dwellings
( tons )
Total Household
Waste (tons)
1965

91*2,633

1*1*5,167

1,3^7,965
293,810
1,61*1,715
1970

1,058,1*75

500,257

1,513,619
330,169
1,81*3,789
1971*

1, 172, 230

55^,913

1,676,289
366,21*3
2,01*2,531
1978

1,279,238

610, 532

1,829,310
1*02,951
2,232,261
independently for each sector.   Such a forecast may be constructed with the use of
national trends as a starting point, and then making modifications based on forecasts
of future exports from and imports into the region.  For example,  as more agricultural
land is committed to uses other than agriculture,  a corresponding  increase in agri-
cultural imports into the region would be expected.  This example  points out the
close connection between the economic forecasting model developed  in the preceding
paragraphs and the land-use model described in the First Annual Report.

        In attempting to evaluate the economic feasibilities of a  waste management
technology, the compositions of the waste is at least as important as total tonnage.
Since a great deal is known about the composition of the waste generator by each
economic sector, the composition of the total waste can be estimated.  Furthermore,
if changes in the mix of economic activity can be predicted, then  the corresponding
changes in composition can be estimated.  The ability to predict the impact of
future changes in the economic structure of the region on solid waste generation
(both total tonnage and composition) is perhaps the most significant feature of
this interindustry input-output model.
OPTIMAL STRATEGIES IN CAPACITY EXPANSION

        The method of solid waste disposal most widely practiced in the United States
today is the landfill method.  The type of fill may range from the simple open dump
to the truly sanitary landfill.  In terms of efficiency with respect to volume
reduction, the landfill method is the least efficient since only a limited amount of
volume reduction is accomplished in the operation of a landfill.  Following the same
criterion, incineration becomes a far more efficient method than landfill.  In
addition to the significant reduction in volume accomplished through incineration, a
biologically and chemically inactive residue or ash is produced.

-------
                   TABLE  30

FORECASTED OUTPUT (DOLLARS) FOR THE NINE-COUNTY
            SAN FRANCISCO BAY AREA
                                                                73
Sector
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
2k
25
26
27
28
Total
1966
170.31
232.67
1.60
19-78
9.00
121.85
3,676.22
957. 44
3,680.55
222.73
122.26
376.82
492.94
653-75
l,545-74
75-24
19-39
377-59
459.06
736-12
654-95
1,035-21
789.13
112.38
276.77
2,030.98
413.83
15,796.60
35,059.90
1970
204.38
279-21
1.92
22.53
10.80
146.23
1,149.19
1,149-19
4, 416.66
267-28
146.72
452.20
591-53
784.50
1,854.89
90.29
23.28
453.11
550.86
833-36
785-96
1,242.28
946-96
134.85
332-12
2,437.18
496.59
18,955-95
42,072.27
1974
245.25
335.06
2-31
27-04
12.95
175-47
1,379-03
1,379-03
5,299-99
320.73
176.05
542.64
709.83
94l.4i
2,225.87
108.34
27-92
543-72
661.03
1,060.03
943.16
1,490.74
1,136.36
161.83
398-55
2,924.62
595-91
22,747-14
50,486.75
1978
294.29
402.05
2.76
32.45
15-55
210 . 56
1,654.84
1,654.84
6,359-99
383-87
211.27
651.16
851.81
1,129.68
2,671-04
130.02
33-50
652.47
793-25
1,272.04
1,131-78
1,788.38
1,363-61
194 . 19
478.26
3,509-54
715-10
27,296.57
60,584.05

-------
74
                                     TABLE 31




               WASTE FORECAST FOR NOTE-COUNTY SAN FRANCISCO BAY AREA
Sector
1
2
3
4
5
6
7
8
9
10
ll
12
15
14
15
16
17
18
19
20
21
22
25
2k
25
26
27
28
Total Waste
Industrial
Household
Forecast
1966
1,586,599
941,9^5
0
0
0
0
0
981,050
15,055
678,649
6,750
95,207
115,314
131,285
555,^54
115,543
151,692
3,795
164
188,870
95,135
166,082
92,902
108,702
62,084
10,060
4,182
4,377,567
10,062,14-95
1,800,000
11,862,494
1970
1,665,684
1,150,553
0
0
0
0
0
1,117,529
18,063
814,386
6,901
Il4,2j4
138,577
157, 544
402, 544
158,4io
182,094
^,551
197
226,650
114,165
199,303
111,483
130,441
74, 500
12,072
4,019
5,252,850
12,075,378
1,845,789
15,919,168
1974
1,996,405
1,356,425
0
0
0
0
0
1,415,057
21,676
977,265
8,281
137,105
16^,052
189,055
485,055
166,091
218,405
5,^62
257
271,980
156,998
239, 165
135,780
156, 533
89, 402
14,486
6,022
6,305,419
14, 490,540
2,042,531
16,552,871
1978
2,395,649
1,627,664
0
0
0
0
0
1,695,646
26,011
1,172,697
9,957
164, 524
199, 264
226,865
579,664
199,513
262, 100
6,551+
285
326,375
164,597
286,997
160, 534
187,856
107,282
17,585
7,227
7,564,103
17,388,315
2,232,261
19,620,576

-------
                                                                                  75
        Because incineration is gaining increasingly wider acceptance as the disposal
method for at least the near future, it was the technology selected for consideration
in this section of the report.  The incinerator, as veil as any other types of
disposal facility, is faced with an increasing demand on its disposal capacity.  The
demands will increase until they exceed the capacity of existing facilities.  Because
of this inevitably increasing demand on incinerator capacity, the question becomes
one of how much should an existing plant be increased; and whether or not they
should be made operational such that, in a sense, they incur the minimum possible
cost in meeting the disposal needs.


Cost Structure
        The cost rate of processing wastes at an input rate P by an incinerator of
size K (KSP) was assumed to be W,

vhere

                               W = oK+7+(f-+5)P
                                             IV

        This cost structure is commonly used in accounting practice, and contains
a "variable" component which is directly preportional to the processing rate, and
a "fixed" component which is independent of the processing rate-  The concept of
economy of scale implies that the variable costs will decrease as plant size increases;
hence we assume the variable cost component is of the form (S + P/K)P-  The fixed
cost component, since it includes maintenance and the cost of the capital invested
in the plant, will certainly increase as plant size increases.  Thus we assume a
fixed cost component of the form 7 + oK.

        Values of the parameters a,p,y, and 6 were estimated by multiple regression
analysis of data collected on the costs of operating incinerator plants.  The results
of the analysis are listed in Table 32-  Since from a technological viewpoint, all
the parameters have to be positive, the range for the parameters was assumed in sub-
sequent work to be as listed in Table 33-  Whenever possible, the high and low values
in Table 33 were determined to be at the mean plus or minus standard error.


First Part of Analysis-Infinite Horizon

        An infinite planning horizon was assumed for the first part of the analysis.
Another assumption was that no lump sum cost is associated with the installation and
startup of a plant; and if there should be such a cost, it could be pro-rated over
time and included in the fixed-cost component with maintenance and upkeep costs.  The
latter alternative could be achieved in practice by floating a bond issue or other
similar step.  The capacity of a plant once installed was assumed to be nondepreciable
and nondisposable.  Time was taken as a continuous parameter and exponential dis-
counting was applied.

        Two situations were studied for each demand rate: l) one in which there is
an alternative, meeting all the demand for disposal capacity by installing incinerator
capacity (e.g., long haul to distant landfill); and 2) one in which no such
alternative exists.  Parameters of interest were the optimal size of the installed
plants.  These were determined on a theoretical basis for a number of demand-rate
situations, namely, constant future demand, linearly increasing future demand with
the present demand at zero, and linearly increasing future demand with the present
demand being positive.


Findings

        The most important theoretical result was that for any nondecreasing demand
rate,  there exists between any two build points (when additional plant capacities are
installed) a regeneration point at which the demand rate equals the cumulative capacity.
This result is comparable to that obtained in the simple back-order model in inventory
theory in which all positive or all negative inventory levels are nonoptimal.

-------
76
                                     TABLE 32

       RESULTS OP MULTIPLE REGRESSION ANALYSIS OF COST DATA ON INCINERATORS
Parameter
7
a
13
6
Units
$/day
$/ton
$/day
$/ton
Value
-135-90
1,308
317.88
0.7752
Standard
Error

0.7^99
786.66
1.9426
Student
t

l.TVuk
0.3980^
O.IK&IO
Significance
Level

0.101*72
0.69706
0.69271
Beta
Coefficient

0.60857
0.23097
0.13591
                                     TABLE 33

                        RANGE OF PARAMETERS FOR ANALYSIS OF
                                 INCINERATOR COSTS
Parameter
a
P
7
5
Low
0.5581
117.88
0.0
0.0
Mean
1.308
317.88
100.0
0.7732
High
2.0579
517-88
200.0
2.7158

-------
                                                                                 77
        Inasmuch as most of the equations involving optimal quantities turned out
to toe  implicit, and in order to obtain a greater insight into the nature of the
optimal policy, numerical results were obtained by the use of a digital computer.
Many different demand-rate situations were studied for different values of the
parameters a, (3, 7, and 8 and alternative cost c.

        The conditions and results of the analysis are summarized in Table jk.  In
the analysis, yearly interest rate was assumed to be 9$ per year (hence, 1+r =
1.000236 which represents the interest rate on a daily basis), and initial demand
to be  1,200 tons/day.  Moreover, m/r = 750, 1,500, 2,250, which correspond to a
linear growth of 60, 120, and ISO tons/day/year, respectively and represents the
increase in demand rate in a daily basis.  The optimal capacity to be installed
when the initial demand is zero is represented by K*, and W(K*) is the cost rate
associated with such an optimal policy-  KI* represents the optimal size of the first
plant  installed when the initial demand is d (<3 > 0).  Note that the second and
subsequent plant sizes will be of capacity K*.  The cost rate associated with this
optimal policy is represented by W(K*).  T0i* and TH* are the times (measured
after  a regeneration point) when the plants of size K* and KI* should be installed-

        From the analysis it can be seen that the following characteristics hold
in general:

    1.  Capacity and cost values are more sensitive to a and p.

    2.  Optimal capacity values are not affected by 5.

    3.  The smaller the alternative cost, the longer the installation time, and the
        smaller the incurred cost.

    k.  The capacity installed increases with decreasing a, increasing p, and
        increasing y.

        The case of linear probabilistic demand-rate also was analyzed and was found
to be  only slightly more complicated than the deterministic demand case.  Numerical
techniques were resorted to in this case, to obtain a better insight into the nature
of the results which were sought.


Second Part of Analysis —Finite Planning Horizon

        The second part of the analysis was based on the assumption of a finite
planning horizon.  Time was treated as being discrete in that this planning horizon
was assumed to consist of N periods, and that the decision to increase the plant
capacity could be made only at the beginning of a period.  The assumed plant model
was slightly different here.  It was as if a single plant existed, and all capacity
expansions resulted in an increased capacity of this single plant.  Demands were
assumed to be deterministic, and as before, disposal of capacity was assumed to be
prohibited.  In the most general case it was assumed that it costs a fixed amount,
xa, to order a capacity increase of any size, and that an alternative to increasing
the capacity of the plant exists which costs c per unit demand rate of disposal
capacity.

        It was shown that when the fixed cost to build was zero,  the optimal policy
had a very simple structure.  The problem, then, is effectively reduced to a one-
period planning horizon.  Hence the decision to build or not build at the beginning
of the period depends solely on the costs incurred during the period.  It was also
shown that it will always be optimal to add capacity at the "beginning of a period
to the demand level of the period and that alternative means are  never used at all.

        When the fixed cost to build,  x2,  is positive and when the alternative does
not exist (c is infinite),  the optimal policy is simple but somewhat more tedious
to calculate,  as is indicated by the following discussion.  If the decision is made

-------
78
                                                   TABLE 34




                                 NUMERICAL RESULTS OP OPTIMAL POLICY ANALYSIS
Units
$/ton
$/day
$/day
$/tcn
$/ton
tons /day 2
tons/day
$/day
tons/day
tons/flay
$/day
day
day
Case
a
&
y
6
c
m/k
K*
W(K*)
d
K!
W!(K?)
to!
txS
1
1.308
317-88
100.0
0.773
«,
1,500
886.55
4,520.0
1,200
2,063-9
7,061.8
0.0
0.0
2
1.308
317-88
100.0
0.773
CO
750
609-59
2,583-6
1,200
1,761.5
5,lV7.1
0.0
0.0
3
1.308
317.88
100.0
0.773
00
2,250
1,115.9
6,368.8
1,200
2,279.9
8,900.6
0.0
0.0
4
0.5581
317.88
100.0
0.773
00
1,500
1,337-9
2,950.6
1,200
2/95-9
4,598-3
0.0
0.0
5
2.0579
317.88
100.0
0.773
00
1,500
7^3.99
5,971-5
1,200
9,409.1
9,409.1
0.0
0.0
6
1.308
117.88
100.0
0.773
00
1,500
660.83
^,133-5
1,200
6,645.1
6,645.i
0.0
0.0
7
1.308
517.88
100.0
0.773
00
1,500
I,o4o.9
4,826.4
1,200
7,401.6
7,401.6
0.0
0.0
Case
a
3
7
8
c
m/k
K*
W(K*)
d
K?
Wi(Kt)
*
toi
txl
8
1.308
317-88
0.0
0.773
00
1,500
803.39
4,287.1
1,200
1,977-5
6,826-6
0.0
0.0
9
1.308
317.88
200.0
0.773
00
1,500
981.59
4,735-1
1,200
2,063.9
7,282.8
0.0
0.0
10
1-308
317-88
100.0
0.0
00
1,500
886.55
3,360.5
1,200
2,063.9
4,974.7
0.0
0.0
11
1.308
317.88
100-0
2.7158
.
1,500
886.55
7,434.2
1,200
2,063.9
12,307.0
0.0
0.0
12
1.308
317.88
100.0
0.773
5.0
1,500
1,088.0
4,200.2
1,200
1,920.0
6,873-3
1,093-4
0.0
13
1.308
317.88
100.0
0-773
10.0
1,500
979-39
4,382-7
1,200
1,992.0
6,983-3
438.22
0.0
14
1.308
317.88
100.0
0.773
20.0
1,500
932.81
4,456.0
1,200
2,063-9
7,025-9
197-46
0.0

-------
                                                                                  79
                                      TABLE 35

            OPTIMAL POLICY FOR A 200-PERIOD PROBLEM WITH DEMAND INITIALLY
              1200 TONS/DAY TO INCREASING LINEARLY AT 10 TONS/DAY/MONTH
Capacity Increased
at Beginning of
Period
1
15
29
43
57
71
84
97
110
123
136
149
162
175
188
Size of Capacity-
Increase
tons/day
1,330.0
140.0
140.0
140.0
140.0
130.0
130.0
130.0
130.0
130.0
130.0
130.0
130.0
130.0
130.0
Cumulative Capacity
Increased to Level
tons /day
1,330.0
1,470.0
1,610.0
1,750.0
1,890.0
2,020.0
2,150.0
2,150.0
2, 410.0
2,540.0
2,670.0
2,800.0
2,930.0
3,060.0
3,190.0
to build some capacity at the beginning of the period, then the optimal level to
which building takes place can "be any of the demand levels faced in the future.  Hence
for a given period, only & finite number of choices can be made.  A problem of this
sort can be solved by using the shortest path approach in a network.  However, that
approach was abandoned because it required too many calculations to obtain the optimal
policy.  To obtain numerical results, the problem was formulated as a dynamic program-
ming problem.  Special mathematical structuring of the problem helped reduce the
number of calculations required to only about 1/5 of the original value and the
scheme now is quite computationally efficient.

        The optimal policy was calculated for a 200-period problem (each period
corresponding to a month) in which the demand initially was 1,200 tons/day and
alternative costs were infinite; a) Vhen demand increases linearly at the rate of
10 tons/day per month (120 tons/day per year or 10$ a year) the optimal policy
is as shown in Table 35-  The demand for period j+1 can be expressed as

                        d    = d. + 10.0  with a  = 1,200.0   .
                         3 ^~    0               1
The parameter values were taken as :

            a = 1.308,  p = 317-88,
                                      = 100.0, 6 = 0.773, 72 = 1,000.0
b) When demand increases geometrically at the rate of 0.833$ a month (which roughly
corresponds to 10$ a year), the optimal policy is shown in Table 36.  The demand
for period j+1 can be expressed as
                      a
                           = d.  • 1.00833 with di = 1,200.0
                              J

-------
8o
                                      TABLE  36

            OPTIMAL POLICY WHEN THE DEMAND INITIALLY IS 1200 TONS PER DAY
                   AND INCREASES GEOMETRICALLY AT 0.835$ PER MONTH
Capacity Increased
at Beginning of
Period
1
111
26
38
^9
60
TO
80
89
98
106
lli+
122
130
137
11+1+
151
158
165
171
177
183
189
195
Size of Capacity
Increase
tons/day
1,325-66
138.81
153-35
151+. 63
169.1+2
168.03
182 . 57
177-78
191.56
182.72
195-26
208.66
222.99
207-63
220.00
233.22
21+7.16
261.95
236.96
21+9-06
261.77
275-11+
289.19
303-95
Cumulative Capacity
Increased to Level
tons/day
1,325-66
1,1+61+. 1+7
1,617.82
1,772.1+5
1,9^+1.87
2,109.90
2,292.1+7
2,1+70.25
2,66l.8i
2,8^.53
3,039-79
3,248.^5
3,1+71- l+i+
3,679-07
3,899.12
4,132. 31+
l+,379.50
l+,6l+l.i+5
i+, 878. l+i
5,127-1+7
5,389-21+
5,6611.38
5,953-57
6,257-52
The parameter values were taken as:

           a = 1.308, (3 = 317-88, 71 = 100.0, 5 = 0.773, 7s = 1,000.0
        The analysis showed that the frequency and the optimal size of capacity
increase depends much more strongly on the demand values and the rate of  increase  in
the near future than on the demand values in the distant future•  This certainly  is
a good omen as far as a real-life situation is concerned.

-------
                                                                                 81
        For the most general case, that is, when 72 is positive, and c finite but
positive, it was shown that the simple structure of the optimal policy no longer
holds, i.e., that the optimal policy corresponds to interior point solutions.
Although the shortest path method and dynamic programming approach can be used here
to obtain the optimal policy, it requires a far greater number of calculations than
in the previous cases.  The required number of calculations was reduced considerably
by developing an upper bound to which the capacity can be increased for any periods
and a  lower bound on existing capacity which triggers a build for that period.  A
new approach was developed in which attention was focused on the last period at which
the capacity was increased.  The latter approach was coded because it proved to be the
most efficient.  Thus optimal policies can be found for a finite planning horizon
and given demand sequence.

        General theoretical questions concerning the first part of the analysis were
investigated.  Thus, a study was made of the nature of the demand function which
would give rise to nondecreasing or nonincreasing capacity installations.  Some
sufficiency conditions for the demand function for nonincreasing capacity installations
were devised.  However, this analysis proved to be quite weak and of little practical
use.  A Markov renewal approach also was made to arrive at generalized cost functions
for maintenance and for upkeep costs and variable processing costs so as to obtain
stronger sufficiency conditions.  However, again the derived conditions were more
of theoretical interest than of practical value.

        Details of the mathematical derivations that support the results described
in the preceding paragraphs will be given in the soon-to-be published, University
of California, report "Optimal Strategies in Plant Expansion," by A. K. Nigam.

-------
                             IV.  ANAEROBIC DIQ3STION
INTRODUCTION
        The application of anaerobic digestion to materials other than sewage sludge
alone is not a new concept in municipal -wastes management.   Numerous communities
have practiced some degree of dual disposal of garbage and sewage for many years as
a result of the widespread use of the home garbage grinder.  This has resulted in
a significant reduction of the garbage fraction of domestic solid wastes without
disruption of the sewage treatment process.   The concept that other organic fractions
of the total refuse of a community might also be reduced in volume and stabilized in
this manner is, therefore, but one step beyond current practice.

        An integral and attractive aspect of this concept is the  use of hydraulic
transport.  Generally, existing sewer systems would be used with  the refuse being
ground into the sewers at points of origin or at central grinding stations.  Certain
materials such as metals, brick, and other high density inert materials would have
to be excluded, but the greater part of domestic, light commercial,  and agricultural
wastes could be transported in this manner.   Experiments conducted by the Los Angeles
County Sanitation Districts demonstrated the efficacy of refuse transport in sewers.
The major difficulty encountered in the Los  Angeles experiments resulted from the fact
that the sewage treatment plant was not designed to accept the added burden of solids
reaching it.  As one would expect, if refuse were to be transported by way of sewers,
existing treatment facilities would have to  be expanded in terms  of grit removal
chambers, primary sedimentation tanks, and increased digester capacity to cope with
the higher solids loading.

        Combining solid and liquid wastes to facilitate waste disposal is a possibility
that has several advantages.   Sorted ground  refuse can be transported from central
grinding stations through existing sewer systems, thus reducing hauling costs.  At the
treatment plant the combined solids can be stabilized and reduced in volume by
conventional anaerobic digestion.  The dewatered residue can be used as a soil
conditioner or as a cover for landfills.


OBJECTIVES

        Laboratory studies on the anaerobic  digestion of solid wastes were directed
toward the following specific objectives:

    1.  To determine the efficiency achieved by the process in terms of stabilization
        of volatile matter and weight reduction with respect to each major component
        of organic solid wastes.

    2.  To assess the effect  on the digestion process exerted by  a given waste
        material, i.e., possible retardation or toxic effects.

    3.  To investigate the feasibility of digestion of organic solid wastes and
        sewage sludge in terms of per capita generation of wastes.

    ^.  To determine proper loading proportions in terms of C:N ratio as applied
        either to the digestion of mixed refuse or to the digestion of selected
        components of solid wastes with sewage sludge.

    5-  To determine maximum permissible hydraulic and organic loading rates in
        dual disposal systems.

    6.  To investigate the utilization of animal manures as a nitrogen source in
        solid waste digestion, and to determine the reduction in  the bulk of the
        manures accomplished  by this process.
                                         82

-------
    7-  To consider the benefits of grinding to sewers for solid waste
        transport regardless of whether there is the added benefit of
        solids reduction by an accompanying digestion process.

    8.  To assess the economic feasibility of digestion of garbage only
        and of the digestion of total urban refuse with sewage sludge.


THE INVESTIGATION


Principles Involved

        Studies to date were confined to the use of laboratory-scale digesters of
1-gal capacity.  The apparatus and analytical methods which were employed were
described in the First and Second Annual Reports.  During the period encompassed by
the present report, several new techniques were adopted to evaluate the efficiency
of digestion.  These include a study of the kinetics of cellulose digestion, methods
for determining the efficiency of the digestion of the solid waste portion of the
feed, and of the efficiency of the destruction of the cellulose in the solid waste
portion of the feed.  A description of these techniques follows.


        Kinetics of Solid Waste Digestion.  The Michaelis-Menten kinetic model has
been employed by many investigators and has been found suitable for describing
anaerobic fermentation systems such as domestic sludge digestion.  Hence, it was used
in the present study to arrive at a quantitative kinetic description of the process
as applied to cellulose.  Since fundamental information regarding the kinetics of
refuse digestion permits an evaluation of operational parameters, the equations •which
follow were used to determine kinetic constants for the particular system reported
herein.

        To obtain a process materials balance, two factors must be considered—substrate
removal and cells produced.  In a continuously mixed reactor at steady state, the
substrate removal rate, q, may be expressed as the mass of substrate removal from the
waste stream per unit of mass of active organisms per unit of time, i.e.,


                                                                                (9)
                                        "•X ~

in which

        So = influent substrate concentration, mg/,0

        Si = digester substrate concentration, mg/,0

        Xi = cell concentration in the digester,

        9  = hydraulic residence time,  days

        In laboratory digester studies involving mixed refuse, the values required
to solve for q in Equation (y) were measured by assuming that the substrate concen-
tration equals the cellulose concentration,  and by estimating cell concentration on
the basis of the organic nitrogen concentration.  Although other methods of estimating
cell concentration such as volatile suspended solids and dehydrogenase activity were
tried, they proved unsuitable for use in this study because only very low correlation
coefficients were obtained.

        The maximum digestion rate of cellulose may be estimated by the Michaelis-
Menten enzyme catalyzed reaction model,  which expresses the relationship between the
rate of substrate utilization and the concentration of substrate.  The advantages of
the Michaelis-Menten model are that at, low concentrations  it is first order (continuous
function) and it approaches zero at high substrate concentrations.

-------
it is expressed as:
                                   1 =
                                            . S
                                        Ks + S
(10)
                              max
                                 Tnax
where

        q,    = substrate removal rate (digestion rate of cellulose)

        S    = cellulose concentration in digester,

        q_^   = an assumed constant denoting maximum hydrolysis rate of cellulose
               at infinite cellulose concentration

        K    = Michaelis-Menten constant, equal to -the cellulose concentration
               at one-half q   .
                            niax

The straight line form of the above plot provides a graphical solution of tne constants
q    and Kg.
                                    nax
                                         .    i
(11)
                     1
                     q

-------
        The substrate removal rate, q, can be transformed to cell growth rate,
by multiplying q by the yield coefficient, Y, as follows:
where
                                                                               (22)
        Y = is assumed to be constant in this study and yield in mass
            of cells produced per mass of substrate removed

        H = specific growth rate (r;  -TT- = ^)
                                  A  Qt

        Maximum growth rate may be determined from Monod's classic growth equation
relating organism growth to substrate concentration, in mathematical form identical
with the Michaelis-Menten equation (Equation 10).
                                        K  + S
                                         s
                                                                               (13)
where

        H    = specific growth rate, day"1

        u    = an assumed constant denoting maximum specific growth rate
               at infinite substrate concentration, day"1

        S    = substrate concentration, mg/£

        K    = substrate concentration at -| u   , mg/,0


        Assuming there are no incoming cells in the influent to the continuous flow
noncell digester recycling refuse, then the mean cell residence time, 9 ,
equals the hydraulic residence time, 9.  The net growth rate equals the specific
growth rate, ja, minus decay rate.  From Equation (12), ^ = Yq, it is apparent that
the net growth rate may be expressed as follows:
                                   ±  = Yq - kd
                                   9c
                                     = Yq - kd
                                                 slope = Y

-------
86
 where
         Q  = mean cell residence  time,  days

         7-  = net growth rate,  day'1
         C7
          c
         kd = decay rate,  day"1
         As expressed in Equations  (10) and (l4), the  cell washout time or  critical
 residence time,  l/#w,  is calculated from the  constants Y, qmax, and kd.  It  is
 hydraulically the minimum residence time at which a stable cell population can be
 maintained.  It  is represented as:
         The cell doubling time,  G,  may be  calculated  from the maximum growth  rate,
                                                                                (16)
         Methods .   Two new methods  for calculating efficiency were adopted to
 delineate the fate of the added solid waste  portion of the feed from the total
 digestion results.  The  first was  concerned  with the destruction of the solid
 wastes  in the feed; and  the second, with  the destruction of the cellulose in the
 solid wastes.

         The efficiency of solid wastes destruction was determined as follows:  For
 a  mixture of sludge plus an added  solid waste, the digestion efficiency of the
 solid waste component may be calculated by comparing the efficiency of a raw sewage
 sludge  digester  (control) to the test digester on the basis of cubic feet of gas
 produced per pound of volatile solids added.

         _,     ,  ,   .    . .     % solid waste  in feed - efficiency loss, % x 100
         Percent  destruction = * - 3 - 7-^3 - J — 3 — 3—* - 2—J- -
                                           f> solid waste in feed

         T,          „„.  .      ..      control, cu ft/lb -test, cu ft/lb
         Where the  efficiency loss  = - -* - - — <• -- ^ ,' - ' - x 100  .
                                             control, cu ft/lb

         Efficiency of destruction  of  cellulose was determined as follows:  Based on
 known inputs of  cellulose from the sewage sludge and from the solid wastes, and
 assuming that the  average cellulose destruction in the control is at the same rate
 as in the sludge portion of the test  digester, then the residual cellulose
 attributable to undigested sludge  may be  calculated.  Subtracting this value from
 that for total residual  cellulose  yields  the value for the quantity of undigested
 cellulose in the residue of the solid waste. The following is an example of the
 calculations :

         Given the  following conditions:  Feed mix — 10$ newspaper, 90$ sludge;
         loading  -0.077  Ib/cu ft digester =  3-70 g VS/day; sludge cellulose at 100$
         1-736 g/day input; newspaper  cellulose content — 88.5$; average cellulose
         destruction control = 87-9$ an
-------
                                                                                  87
        1.562 x  (100  - 0.379) =                 0.189 g

        Total residual cellulose =              0.336 g

        Sludge residual cellulose (-)           0.189 g

        Newspaper residual cellulose =          0.1^7 g

        and newspaper cellulose destruction =       h ^27*	  x 100^ =


General Materials and Methods
        Preparation of Raw Materials.  With the exception or newspaper, each solid
waste material was prepared in a sufficient quantity to satisfy the requirements of
all studies reported herein.  The newspapers were prepared in two batches.

        A synthetic refuse was used  in some of the experiments.  It consisted of a
mixture of grass clippings, green garbage, wood (white fir), Kraft paper, and
newsprint.  The grass clippings, garbage, and wood were mixed and stored separately
from the paper until the time of the experiments.  The grass, garbage, and wood
mixture was 48-3$ green garbage (air-dry total solids), 34.1$ grass clippings (air-
dry total solids), and 17-5$ white fir (air-dry total solids).  The computed moisture
content was 10.2$; computed volatile solids, 82.3%; cellulose content, 47-9$ (air-dry);
total carbon, 35-8$ (air-dry); and total nitrogen, 2.4$ (air-dry).  The mixture was
stored at 2PC until it was used.

        The Kraft paper was hammermilled to a fine powder.  The moisture content of
the powder was 6%; volatile solids on an air-dried basis were 93-6$ (99-6$ on. dry
weight basis); the fixed solids, 0.4$ (dry weight); cellulose, 97-3$ (dry weight);
total carbon, 38.1$ (air-dry); and total nitrogen, 0$.  The newspaper also was
hammermilled to a fine powder.  Its moisture content was 7$; volatile solids, 100$
(dry weight); cellulose, 97-3$ (dry weight); total carbon, 38.6$ (air-dry); and
total nitrogen 0.019$ (air-dry).

        Experiments also were conducted in which each of the components of the
"synthetic" refuse was studied separately.  The grass clippings were air-dried and
then were ground to a fine powder in a Wiley mill.  The powder was stored in
polyethylene bags at -2° C.  The moisture content of the powder was 24.8$; the
volatile solids, 87$ (dry weight); and the cellulose, 60-3$ (dry weight).  The
green garbage was obtained as vegetable trimmings from a loca] supermarket.  It
consisted of about 80$ lettuce, 10$ cabbage, and the remainder being corn husks,
parsley, and miscellaneous greens.  The material was dried to less than 1$ moisture,
and then was hammermilled.  The powder was stored in polyethylene bags at 2°C.  The
moisture content of the powder was less than 1$; volatile solids, 91.2$ (dry weight);
and cellulose content,  40.8$ (dry weight).

        The wood (white fir) was obtained in the form of chips .  The chips were
ground to a fine powder in a Wiley mill.  The powder was stored in sealed glass
containers at room temperature.  The moisture content of the powder was 9.3$; its
volatile solids, 99-5$ (dry weight); and its cellulose, 74.4$ (dry weight).

        When newsprint was studied on an individual basis, a different batch from
that used in the "synthetic" refuse served as the substrate, it was prepared by
blending with water in a Waring blender, then air drying overnight, and storing the
moisture material is polyethylene bags at 2eC.  This material served as substrate in
the runs with sewage sludge and chicken manure as the only other components of the
feed mixture.  The shredded newspaper contained on a dry weight basis 88.5$ cellulose,
97-1$ volatile solids,  40.6$ total carbon, 0.05$ total nitrogen, and its moisture
content after preparation was 70.8$.

        Animal Manures.  Chicken manure and steer manure were investigated individually
and in combination with sewage sludge and solid waste materials.  Chicken manure had
been used in previous  studies as a source of nitrogen in digesting nitrogen-deficient
wastes.   The nitrogen content of the manure was 3.2$ (dry weight); carbon 23-4$ (dry
weight); moisture content 9.8$; volatile solids content, 56.2$; and inorganic material,
43.8$ (dry weight).

-------
        Steer manure was obtained from a commercially packaged fertilizer product
containing no additives.  Its moisture content was ^5-7$; volatile solids, 68.5$ (dry
weight); total nitrogen, 1-35$ (dry weight); organic nitrogen, 1.22$ (dry weight);
NH3-N, 0.13$ (dry weight); and total carbon, 3^.1$ (dry weight).


FIRST EXPERIMENTAL SERIES - DIGESTION OF NEWSPAPER

        The fact that paper constitutes about one-half of domestic solid wastes and
nearly three-fourths of organic solid wastes demonstrates the significance of deter-
mining the degradability of this material in disposal processes.  Kraft paper, which
is wood-free, vas shown in previous studies to be readily destroyed by anaerobic
digestion (over 90$).  However, newspaper contains about 75$ ground wood pulp, and
thus may be expected to be much more resistant to biodegradation.  It is, therefore,
important to defferentiate between the quantity of waste paper that is essentially
wood-free and that amount which contains wood stock.  Recent figures indicate that
U. S- consumption of newsprint to be about 9 million tons annually, which is almost
20$ of the total 50 million tons of paper consumed.  This compares to about 10
million tons of Kraft apper consumption.  The remaining material consists of mixed
grades, some of which may be classified as wood-free and others containing wood
stock.  It is difficult to classify the latter material on the basis of wood content;
but based on recent figures an estimated 55$ of it is wood-free-

        Salvage of waste paper currently is approximately 20$ of that produced,
or about 10 million tons per year.  It is estimated from figures on secondary fiber
consumption supplied by the American Paper Institute that the ratio of wood to
wood-free stock in the salvaged paper is about 1:1.  The paper industry would like
to increase salvage and conserve paper stock, but current collection practices tend
to soil most of the waste paper through contact with garbage.  The Berkeley composition
study [k] showed that of the waste paper arriving at the disposal site 80$ was soiled.
This soiled paper constituted 3^-7$ of the total domestic wastes (wet basis), and
clean paper comprised 9-9$ of the total (wet basis).

        Clean paper separated from the main stream of solid wastes would not be
recommended for a conversion process such as anaerobic digestion even if there were
no salvage market, since paper is a compact material and the reduction in bulk afforded
by digestion or any other process probably would not be worth the effort.  Furthermore,
clean paper is inoffensive and may be readily disposed of in any manner without
creating nuisances.

        From the above considerations it seems likely that domestic solid wastes will
continue to contain upwards of 50$ waste paper intermingled with other wastes.
Disposal practices must therefore cope with this heterogenous mass of material,
including the 20$ to 25$ of paper from wood stock such as newspaper.  Because other
components of solid waste,  such as garbage and garden debris, contain a considerable
amount of moisture compared to paper, the paper content represents about 75$ °f the
total weight, in terms of quantity of dry-weight material comprising the organic portion
of municipal refuse.  It thus becomes apparent that the capability of a given process
for breaking down paper is of paramount importance in assessing the relative merits
of that process as a disposal technique.


Procedure
        One digester (unit l) served as the control and received only sewage sludge.
A second digester (unit 2) received sewage sludge and newspaper.  For unit 2 the
newspaper portion constituted 10$ of the volatile solids loading during the first
lj-0 days of the run.  During the next 80 days,  digester 2 received a newspaper loading
equal to 20$ of the total input.  In the final period (88 days), the loading to the
two digesters was 30$ newspaper.  The cultures in units 1 and 2 were mixed throughout
the experimental period by timer-operated magnetic stirrers on a schedule of 1-5
minutes each hour.  A third digester (unit 12) was not mixed.  It received a mixture

-------
of  50$  newspaper and  50$  chicken manure  for  a  period  Of  98  days.   The  culture
volume  in  the  three digesters was 3  liters per digester.  The  nominal  detention
period  of  the  cultures was  JO days,  and  the  loading was  0.077  Ib  volatile  solids/cu
ft  digester  capacity.


Results
         The  efficiency  of  the  three  digesters  is  shown  in Table  37  in terms of  gas
 production based on volatile solids  added and  volatile  solids  destroyed.  For some
 reason,  the  control (unit  l) decreased  in efficiency as the experiment progressed.
 However,  the values shown  in the  Table  are within the normal range  of fluctuations
 for  these parameters.   In  order to assess the  efficiency of newspaper digestion for
 comparison with that of digestion, the  impact  of  the added waste material must  be
 calculated.   This may be done  by  taking the  loss  in efficiency resulting from the
 percentage of waste material present in the  feed.  Such a procedure is relevant only
 to unit  2 which was fed sludge as well  as paper,  and may therefore  be compared  to
 the  sludge control.  On the basis of added volatile solids, the  data shown in
 Table  38 can be obtained on the basis of the average values listed  in Table 37-

         The  destruction of newspaper during  the initial period apparently was only
 8$ of  that introduced.   However,  with newspaper constituting only 10$ of the added
 material, experimental  errors  are magnified  by the calculations.  More accurate
 assessments  were possible  at the  20$ newspaper loading.  At this loading, the calculated
 destruction  of newspaper proved to be 53-5$-  At  30$ newspaper loading, the percent
 destruction  was 44.3$-   The average  of  these two  values, namely  ^8.9$; agrees very
 closely  with results in later  experiments in which cellulose destruction averaged
 V7-0$.

         Efficiency in terms of gas produced  per unit of volatile solids added rather
 than per unit of volatile  solids  destroyed is  much more meaningful  in solid waste
 digestion experiments.   If an  added  waste material is not destroyed at all, the
 efficiency in terms of  gas production per volatile solids destroyed is not affected
 in the slightest.  The  digester fed  paper and  manure (unit 12) is an example of
 this discrepancy.  On the basis of volatile  solids added, gas  production was 4.1 cu
 ft per Ib of volatile solids;  whereas in terms of volatile solids destroyed, it  was
 12.4 Ib  per  Ib volatile  solids.   Obviously the digestion efficiency of the culture
 receiving a  newspaper-chicken  manure mixture was  quite poor, but on a destroyed
 basis this would not be  apparent.  For  unit  2, the loss in efficiency on the basis
 of gas produced per pound  of volatile solids destroyed was only  about 10$ when
 compared to  the control.   This leads to the  erroneous conclusion that the digestion
 of newspaper proceeded  almost  as  efficiently as that of sewage sludge.

        A comprehensive  picture of the  valid parameters of efficiency in terms  of
 gas  production per unit  of volatile  solids added  is shown in Figure  2.  The poor
 overall  efficiency of unit 12  becomes evident  in the figure.   The magnitude of
 decrease  in  efficiency as the  newspaper loading to unit 2 is increased may be
 observed.  Volatile solids reduction was more affected than was total solids
 reduction.   Cellulose destruction decreased  to an even greater extent.  The average
 cellulose destruction in unit  2 during  each  period is shown in Table 39 together
 with the  calculated destruction of news pa per-de rived cellulose.

        A weighted average of  47-0$  newspaper cellulose destruction  was obtained on
 the basis of  the number  of determinations run  (at 55-0$, n = 5; V?.6$, n = 11; 4l-7$,
 n =  13)-  The  destruction of the  cellulose in newsprint was about one-half that  of
 Kraft paper  due to the resistance of lignin  to anaerobic decomposition.

        No serious adverse effects on acid-base parameters were noted, as is evident
 from Figure 3  in which pH,  volatile  acid concentration, and alkalinity are plotted.
As observed  in other experiments,  decreases  of the proportion of sludge in the feed
mixture resulted in a lower alkalinity and pH,  although the volatile acid content
 remained stable.  Despite the  poor digestion efficiency of the culture in unit 12
 (newspaper and manure)  the culture was  in quite good condition-

-------
90
TABLE 37
GAS PRODUCTION PER POUND OF VOLATIIE SOLIDS INTRODUCED IN THE DIGESTER RECEIVING NEWSPAPER AND SEWAGE SLUDGE
S>
a
a & 2
w
•p *e£-
•H O ^*-
B ^ R
^
w g 3
-P rH
.£ -g- CO
o ^ -g-
[•—
'ft
H !
•p H
•H CO
3
r-l
Destr.
Added
Destr.
Added
Destr.
Added
>v
&
COCO K\O\l^CO-*-=l- CM UM/NOM3
ONrH UA hO,_* rH H r-l LT\ U^-d- CM OJ
Hi-HnHHiHrH^rHHrHHrH
CO-VDvOCO CTN^t O O
rCv-d- J- -=f K> KN NA K>-4- -3" -3- -* ^t
D— O irvi^C~-_*VD^OC--OCO O\rr\
r-lr-IOJC\JC\J(AhA(Oi(AK\C\J lO^J-
HrHr-ir-lHHHHHi-li-Ii-IH
U^OONOOMDOOHr-lOrHVO
t~— D — t — CO F~~00 CO t — C t^ t^ C" — C*—
H OJU3rHt--OU3O fA-d- ON^O
OJ 1 rA KNJ- J-^-OJ(AOJOJK>Ot— -cfrHcn
OJ roroi^j- UM^VJDC-COCO ONOO
HrHHHHi-lrHr-liHHrHOJOJ
J-
OJ
rH
rH
-=f
-* OJ O
uMf\ tr\
rH rH i-H
OMX> IT\
ONCO t—
O OJ H MA
>-VD tA (A
rH r-H i-H rH
ONt— O O
O O> O\ O\
rH
• o oj o o
^^r^coaj
^rHS^3
(~1 rH

OJ /^ "^
r-l OH ,Q
-P ~^-
•rl 0 -BgL
rj ITS O
5 LfN
0
o) so
OJ PH "d
B 3
-P rH
•rl CO
fl -eP-
^ H "*"
W
5D
rd
"• 5
-p CO
•H
**
o
H
Destr.
-d
1
Destr.
Added
Destr.
Added
>>
&


O-* h^OJ CONOCO
V£)J-^t ITMTSLrN^Q LTN
rHHrHrHrHrHrHH
MD-=J--4-C~C~-OOO
O^CT\O\O\OCDp
rH ("H r- 1 (~i
OrOrHOOO-*CO
C7\VO \£) ^O ^ i>- C^- C~-
HrHHrHHHHrH
OJITNI^OOCM-*-^-
OJOOOOrHi-HH
HrHi-HrHrHHi-HH
OJ LT\ O\OJ \O ,^>-O O
H H H OJ CM rr\ |0!^t


^~&
£1
1 — 1
-rfa-co
°-g-
 f~ CJNVO OW""\NAOLP>OCOCOHO\r-OCOOOrH
LT\Lr\CM OJ^D1^-*-* K\O\ O\CO t— LP>-* 'vO VO |O, K> tA K> KN
HHHr-irHHTHHrHHHTyrHHrHrHHHrHHrH^H
\o \o o\ a\co coj--^- oo^--* HVOVDCJN 
-------
                                                                         91
                             TABLE 38
      EFFICIENCY OF NEWSPAPER DIGESTION BASED ON COMPARISON
           WITH CONTROL  (UNIT 1  - 100 PERCENT SLUDGE)


Efficiency


cu ft gas produced
Ib VS added
Efficiency loss, $
Calculated newspaper destruction, $a


Unit


1
2
2
2
Unit 2 (Fed with Newspaper
and Sludge Mixture)

10$ NP,
90 SL
10-9
9-9
9-2
8.0

20$ NP,
80$ SL
9-7
8.8
9-3
53-5

30$ NP,
70$ SL
9.0
7.5
16.7
Mt.5
Calculated Destruction,  $ = Waste  * "
                                                      X 10°
                             TABLE 39
            DESTRUCTION OF NEWSPAPER CELLULOSE BASED ON
                     COMPARISON WITH CONTROL
Parameter
Total Cellulose
Destruction, %
Calculated Newspaper
Cellulose
Destruction, $
Unit
1
2
2
Unit 2 (Fed Newspaper [NP] and
Sludge Mixture [SL] )
10$ NP,
90$ SL
87.9
82.8
55-0
20$ NP,
80$ SL
81.7
73-3
49.6
30$ NP,
70$ SL
79-9
63.0
41.7
     Calculations (see Materials and Methods section for
sample calculation).

-------
92
                                                                  S
                                                                 I-
                                                                 tn
                                                                 UJ
                                                                 rr
                                                                 UJ
                                                                 Q.
                                                                 
-------
                                                                                             93
                                                                                           o
a?

CJ
o


o
z

o
4
O
tr
UJ
a.

-------
94
        As onovn by the data in Table 40, the composition of gas produced by the
culture receiving newspaper and sludge was about the same as that from the culture
fed only sludge.  The methane content of gas from the former averaged 68.9$; and that
from the latter, 70.0$.
                                     TABLE  40

               COMPOSITION OF GAS FROM CULTURES RECEIVING NEWSPAPER
                           AND SLUDGE AND SLUDCS ONLY

Day

14
21
28
35
42
49
56
63
70
77
84
91
98
105
112
119
126
133
l4o
147
154
161
168
175
182
189
196
203
AVG.
Methane, $

Unit la
69.9
67-1
67-1
69.6
70.7
70.1
70.0
71.0
70.2
70.7
68.9
71.2
69.7
69.2
68.9
70.0
70.6
69.3
69.0
69-7
68.5
69.6
70.J
77-5
70.3
71-5
69-4
70.0
70.0
Unit 2
67.8
67-3
66.0
67.4
69.0
69-1
69-5
68.0
70.1
70.1
68.9
70.0
68.1
68.0
69.0
68.6
63.5
69.1
68.0
68.0
68.8
68.2
69-1
75-5
69.2
69.6
70.0
69-5
68.9
Unit 12














68.2
67-5
67.4
63.0
65.1
66.2
66.5
—
68.8
68.6
63.0
64.9
64.7
65.1
66.1
Carbon Dioxide, $

Unit 1
30.1
32.9
32.9
30.4
29-3
29-9
30.0
29.0
29-8
29.3
31-1
28.8
30.3
30.8
31.1
30.0
29.4
30.7
31.0
30-3
31-5
30.4
29.7
22.5
29-7
28.5
30.6
30.0
30.0
Unit 2
32.2
32.7
34.0
32.6
31.0
30.9
30.5
32.0
29-9
29-9
31.1
30.0
31.9
32.0
31.0
31.4
31-5
30-9
32.0
32.0
31-2
31.8
30-9
24.5
30.8
30.4
30.0
30.5
31.1
Unit 12














31.8
32-5
32.6
37.0
34.9
33.8
33-5
--
31.2
31.4
37.0
35-1
35-3
34.9
33-9
        Control  -  fed 100$ sludge

-------
                                                                                 95
        A summary of results pertaining to the digestion of newspaper is presented
in Table h-1.  The data are averages of weekly analyses for the test digesters.  The
averages may be compared to the average results obtained with the control (sludge
only) during the same experimental period.  Values for the control are in parentheses.


SECOND EXPERIMENTAL SERIES - DIGESTION OF GRASS CLIPPINGS

        The proportion :>f garden debris in urban solid wastes varies from one
community to another.  For example, it comprises 9$ of the total in Santa Clara,
and 5$ in Berkeley.  For the investigation of the digestibility of garden debris,
grass clippings were chosen as representative of the many types of vegetation which
fall into this general classification.


Procedure

        Three digesters were placed in operation at a sludge loading of 0.077 Ib/cu ft.
One digester served as a control (unit l).  It received only sewage sludge.   The
other two digesters were adapted to a feed containing 50% grass by increasing the
grass content of the feed mixture by 5$ increments over a 35-day period.  The second
digester (unit k-) was then fed 50$ grass and 50$ sludge throughout the experimental
period.  The third digester (unit 3) was converted to 50$ grass and 50$ chicken manure.
Subsequent to the acclimation period for both digesters, the duration of the experiment
was 65 days.

        Initially, an attempt was made to digest grass clippings without any form
of preliminary grinding or processing.  This proved unsatisfactory because the waxy
surface of grass prevented adequate wetting and access by bacteria.  Grinding
sufficiently to bruise the surface of the grass blades proved acceptable.  However,
because a hammermill was at hand, the grass clippings were ground to a powder in
the mill.


Results

        The grass proved readily digestible, combinations of grass and sludge digested
more readily than mixtures of grass and chicken manure.  The parameters of efficiency
as given in Figure k indicate that digestion of the grass-sludge mixture (unit k) was
almost identical to that of sludge alone in reduction of cellulose, volatile solids,
and total solids, although the gas yield was somewhat less.  Average gas production
per pound of volatiles added to the culture fed grass and sludge was 7-8 cu ft, as
is shown by the data in Table k-2.  Gas production by the control digester (sludge
only) was 9 cu ft/lb volatile solids introduced.  Gas production by the digester
fed grass and chicken manure averaged 5-9 cu ft, or 3^-5$ less than that by the
control.  A calculation based on the digestibility of sewage sludge showed that the
grass clippings were about 73$ digestible.  The average reduction in the cellulose
content of the grass-sludge mixture was 79-5$ (1-1$ less than the control).   The
calculated destruction of cellulose in the grass clippings averaged 78-5$-

        The acid-base parameters of the test units followed a pattern similar
to those of digesters fed garbage.  They were described in the First and Second
Annual Reports.  The continuous rise in alkalinity and pH which took place in
the culture is shown in Figure 5-  The rise indicates deamination of the grass feed.
As a result, an increase in ammonium carbonate concentration took place and the net
alkalinity increased.  The lowering of the C:N ratio brought about by the addition
of garden debris, green garbage, and chicken manure, apparently led to a high
degree of buffering capacity in the digester.

        As shown by the data in Table ^3 the gas composition for all three units
was virtually the same.  A summary of the results obtained in the experiment is
given in Table kk.

-------
96
                                             TABLE lt-1




                  SUMMARY OF RESULTS PERTAINING TO THE DIGESTION OF NEWSPAPER
Parameter
Efficiency of Newspaper
Digestion, $
cu ft Gas Produced
Ib VS Added
cu ft Gas Produced
Ib VS Destroyed
VS Reduction
*
TS Reduction
*
Cellulose Reduction
$
Efficiency of Newspaper
Cellulose Reduction, %
Methane
*
C02
%
pH
AJ-kalinity
mg/.e
Volatile Acids
mg/.e
Unit 2 - Newspaper Content in Sludge Feed
10$
8.0
9-9 n
(io.9)a
15 A
(17-0)
6k. k
(65.7)
53-1
(52.8)
82.8
(87.9)
55-0
67-1
(68.10
32.9
(31.6)
7.10
(7-17)
2620
(2^88)
38
(30)
20$
53-5
8.8
(9-7)
15.2
(16.2)
55A
(59A)
1A.3
(^5-7)
73-3
(81.7)
14.9.6
69.0
(70.0)
31.0
(30.0)
7-07
(7-21)
214-1*0
(30142)
29
(39)
30$
1A.3
7-5
(9-0)
13.0
(13.1)
58.0
(69A)
^7-5
(53-5)
63.0
(79-9)
1+1.7
69-5
(70-5)
30.5
(29-5)
6.98
(7-23)
2120
(3075)
18
(15)
Unit 12
50$ Chicken Manure
50$ Newspaper
— •
lt-,1
(9.0)
12.4
(13-3)
32 A
(68A)
23-1
(52.2)
46.7
(79-9)
~
66.1
(70.5)
33-9
(29-5)
7-11
(7-23)
2950
(3117)
2k
(18)
     Control - 100$ Sludge

-------
                                                                                97
CO
                   l~
                   \
1

_


—

~

-
_

-

— 1
r
/
;
i
i
I
1
I
1
i
i
I
1
/
/
< •
\
\
\
/
/


r

\
\
\
1 1


_


—

—

t-
_

-

-


—

—
-
-

—

          in
          u>
o
(O
o
10
o
ro
                                  % ''Na3d nos  101
                                                                          O
                                                                          •o
                                                                              O  2
                                                         CO
                                                         LJ
                                                         CD

                                                         Q

                                                         CO
                                                         Q_
                                                         Q_
                                                         IJ
                                                         O

                                                         cn
                                                         CD
                                                         <
                                                         CC
                                                         CD
                                                                          P   °
                                                                              >-
                                                                              O
                                                                              z
                                                                              LiJ
                                                                              o
                                                                              UJ
LU
o:
Z)
                              10A
                                          s A qi
                                                          SV9

-------

-------
                                      TABLE  42

                  GAS PRODUCTION PER UNIT uF VOLATILE SOLIDS ADDED
                     TO THE DIGESTER RECEIVING GRASS CLIPPINGS
                                                                                  99


2
9
16
23
30
37
44
51
58
65
AVG.
Unit 1
Added
9-6
10.1
10.1
9-6
8.6
8.6
8.4
8.3
8.6
8.5
9.0
Destr.
13.6
14.1
14.7
14.0
12.6
13.0
12.3
12.4
12.9
12.6
13-2
Unit 3
Added
5-6
5-5

5-9
6.0
5.8
5-7
5-9
6.1
6.2
5-9
Destr.
12.6
12.2
_
12.7
13.1
13.1
12.3
13.2
13-3
13-0
12.8
Unit 4
Added
7-7
8.6
8.6
6-9
8.0
7-7
7-4
7-7
7.8
7-4
7.8
Destr.
10.9
12.2
12.5
10.5
11.9
12.1
11.4
12.0
12.5
11.5
11.9
THIRD EXPERIMENTAL SERIES - DIGESTION OF ANIMAL MANURE

        In previous experiments, the possibility of disposal of animal manures
by anaerobic digestion was explored only incidentally, in that chicken manure was
used instead of sludge as a nitrogen source when studying the digestibility of other
solid waste materials.  In the present study, cow and chicken manure were digested
individually and in combination with each other.  In addition, steer manure was
combined with sludge and grass to determine the feasibility either of digesting
them along with sewage sludge in municipal digesters, or of using them as a
nitrogen source in digesters built especially for solid wastes.
Procedure

        The test digesters in this study had all been operated previously on other
solid wastes and were adapted over a two-week period to the following feed mixture:

                  Unit                        Feed
                   1          lOOjt Sludge
                   2          100$ Steer Manure
                   3           50% Steer Manure, 50$ Grass

                   4           50$ Steer Manure, 50% Chicken Manure

                   B          100# Chicken Manure
                   C           50$ Steer Manure, 5056 Sludge .

        Aside from the nature of the feed, other experimental conditions were the
same as in the previous experimental series, i.e., constant temperature of 37°C,
30-day detention time, digester liquid capacity of 3 liters, organic loading of
0.077 lb volatile solids per cu ft of digester capacity per day (3-70 g/day), and
mixing applied in units 1, 2, 3, and 4.

-------
100
                                      TABLE  43

                        COMPOSITION OF GAS FROM THE DIGESTER
                             RECEIVING  GRASS CLIPPINGS

Day
1*
11
18
25
39
k6
53
60
AVG.
Methane, "jo
Unit 1
69-7
68.5
69-6
70-3
70-3
71-5
69 A
70.0
69-9
Unit 3
68.8
69-7
68.1
67- b
67-3
68.1
67-5
—
68.1
Unit ^
69.1
67-9
69.0
70.1
70.0
70.0
69.6
70.0
69.5
Carbon Dioxide, 
Unit 1
30-3
31-5
30.4
29-7
29.7
28.5
30.6
30.0
30.1
Unit 3
31-2
30-3
31-9
32.6
32.7
31-9
32.5
--
31-9
Unit k
30-9
32.1
31.0
29-9
30.0
30.0
30. 1*.
30.0
30-5
 Results

         Very little gas was produced by the digester fed steer manure,  as  is
 shown by the data in Table k5.   The average production was  only lA cu  ft  per Ib
 of volatiles added.  When chicken manure was digested, the  yield was 5.0 cu ft per
 Ib.  The relative efficiency of the animals in utilizing the energy content of
 their diet is indicated by the  difference in gas production from the digestion of
 their wastes.  Thus, the energy content of steer wastes was much lower  than that
 of chicken wastes, hence steers apparently utilize their food more  efficiently
 than do chickens.

         Using as a basis, gas production per pound of added volatile sewage solids
 in a digester fed sewage sludge,  steer manure was lk.9% efficient and chicken
 manure 53.2$ efficient.  In terms of volatiles destroyed, the gas yield was higher
 from the digester-fed chicken manure than that from the sewage sludge digester.

         Although the animal manures were stabilized by digestion and rendered
 inoffensive, there was virtually no reduction in volume of  the material.   Destruction
 of total solids was less than 15$,  as is shown by the data  listed in Table ^6.

         Experimental results presented in Table Vj indicate that performance of
 digesters was not hampered by the presence of manures.  Regardless  of which
 combination of steer manure or  chicken manure with other solid waste was added, the
 pH of the culture remained higher than 7-2.  A significant  increase in  volatile
 acids was noted in all test units,  but average values were  not exceptionally high
 at steady state.  Apparently, the buffering capacity increased at a rate commensurate
 with the increase in acids.  The increase in alkalinity indicates that  a limited
 addition of manure would be helpful in stabilizing carbonaceous wastes.  Probably,
 the acid would result from the  lowering of the C:N ratio brought about  by the
 nitrogen content of the manure.

         According to the data given in Table ^8, the composition of the gas from
 the digester fed manure was comparable to that of the gas from the  sewage  sludge
 digester.  The methane content  of the manure (digester) was only slightly less
 than that from the sludge digester.  The maximum difference between the digester
 receiving only chicken manure and that fed sewage sludge are only k.h%. All of the
 results are summarized in Table ^9.

-------
                                                                                 101
                                       TABLE 1(4

                SUMMARY OF RESULTS OBTAINED IN THE EXPERIMENTS ON THE
                          DIGESTIBILITY OF (BASS CLIPPINGS
Parameter
a Efficiency of Grass
Digestion, %
Cu f L Gas Produced
Lb Vol. Sol. Added
Cu ft Gas Produced
Lb Vol. Sol. Destroyed
Vol. Sol. Reduction
Total Sol. Reduction
*
Cellulose Reduction
Efficiency of Grass
Cellulose Reduction, %
Methane
COS
PH
Alkalinity
mg/^
Volatile Acids
Unit 1
100$ Sludge
--
9-0
13-2
68.7
52-9
80.6
--
69.9
30.1
1.2k
3030
13
Unit 3
50$ Grass
50$ Ch. Man.
—
5-9
12.8
k5>5
31.1
70.5
--
68.1
31-9
7.4l
1*699
59
Unit k
50$ Grass
50$ Sludge
73-1
7-8
11.9
66.2
5^.3
79-5
78.5
69-5
30.5
7.3!*
3705
35
             Compared to Sludge
FOURTH EXPERIMENTAL SERIES - DIGESTION OF WHITE FIR WOOD

        As was stated in the Second Annual Report, the significance of wood as
a waste material to be processed in digesters derives from the possibility of
disposing of demolition rubble and of tree trimmings and garden debris by way
of sewerage systems.  The reasons for investigating the digestion of wood or any
other waste are manifold:  l)  The toxic potential of wood or any waste must be
evaluated to determine its suitability for contact with sensitive biological processes;

-------
102
                 CQ
                 O
                 a
CQ
8
S
!
                           OJ
                           -P     4^
                           i     w
                           a
                                      •d
                                      •d
                                             1   COCOOO   H
                                                                                                 C\H
                                                CO
                                                OJ
                                                CO
                                            O"\
                                                                               -*  f-UALPv^J-,^-
                                                                               LPU\LT\ir\_=t-_d-
                                                                               o   o
                                                                               i — 1   r— 1
                                                                                                 a\co
                                                                                                           o
                                                                                                           ON
                                                                                    as  c—  ^   >-co
                                                                                           fy

                                                                                          CO
                                            O  O   OJ  KN

                                            H  H   H  H
                                                      COC—  VDITN^-C—  rTNC—

                                                      rHHHi-lrHHHr-l
                                            OH   ITSCQCOCOCOCO
                                                                                            (0,  C—  O\
                                                                                                           OJ
                                                                                    lTv.3-
                                                                                    i-iH
                                            ~*.  ^7
                                            ON  CO
                                                                       ONO  O\O   ROCOCO
                                                                                                           O\
                                                                                                                 M3
                                                                                                                 ON
                                                                                       to

                                                                                      I
                                                                                       m
                                                                                       •p
                                                                                                 a

                                                                                                 S
                                                                                                 cd

                                                                                                 I
                                                                                                 -p
                                                                                                 to
                                                                                                                  cd
                                                                                                                  OJ   O\VD
                                                                                        C—  COCOON


-------
                                                                                                           103
      fe
      O

      B
      O
VD    |J
_4"    rn
      I
      i-^
      8

olf
p . A
•H -P CO
a co
^S tJ5.
t-J jf"
O tfN
IA
•
rt
«*
£6
B
rH
• •

•ri-P.fi
d co O
"SIS-
t/N LPv
.
a! ra
NA E d
•H -p
d W
S Tfr
O IA
ir\
•
d
«*
•H CO
r-H
Si
TJ
^^
•ri
!§•«*.
H
*
^
iS
rH
$
&
m
g
<-t
OS
s
*
^
rH
$
8
•
£
H
«s
e
.
£
H
£
S
•
£
rH
C— H
VO i/NLTvj- ir\ir\_d-^tJ- ir\LTvj-^i-
^OOJCO (OOO-* L/N^t r-H^t-d-K^lTv
1 1 U-NJ-OJ^OC— C— >>DK^J-t-C7\VDC\J
J-J-J- K>fAK>K\K>rArOvK>rAKN
i-l rH ONC7NVD HI^-^C— VOD— ^-
1 1 IOJr-HinM3COOHCOr-HJ-O\O
OJOJrHHHK-\t<^l/-\rHOOJC— l/NVOOJ
1 1 IOJHO\O\Ot— CO'OOt-OiVOf-
rn rH rH rH rH rH i"H (~H rH rH
K^-^C-C-OrAOJ^-^t-CVJChON^HOJ
lf\ t>- t— OOJrHVOC— iriLfNtA^DOl^^t
HrHrHOJCJWOJi-ICMOJOJOJrACMCM
l^COOONl/N-4-HoOC— LAt— OCQl^O
OxO HOJ (AK>VOO LPvirNJ-^OCOU^l^N
HHrHHHrHrHHHHrHHi-IH
^t O\O\O O C-t^VOJ-OOM3 NAN^OO H
OCOt— -4-|OvrHO\^Df-t-VOC7NO\t-t-
vo irvirsirNirvi^j-^j-j-^i-j-^j-j-^i-^d-
l/NK^^l- LT\r— t— O O\^Nt— CT\O O C— KA
V£) LTNJ- H O ONCO l^VOVO IACX300VDM3
J-^J--^--* (OKNtr\K\NArAfAN~\K^K\
t— l/NL/>O^>l^OJt— -^-(A-d-OMAf^^O
CO CT\J--d--=f-*t-ONONrHVO HtrxChrH
HrHrHHHHHWHOlOJHOJ
OLPvOVDOOCTNUAiOvOK^U^^D-^Crv
VDVjDOCTNOOrHrONAirNH-d-t— K>-*
rH rH I — I I — I I — I rH rH rH rH r~l rH rH
j-Hir\ooir\ou^Lr>^j-ovor-C7\-=i-
OONONOrHOCMONrHHOOHHrH
c— M3vo r-t— r-r-vo t— t— c— t— t— vo vo
CO^-Hir\NAC7\J-rArHCT\COK>C\l(?\^D
m^t ir\ir\M3 irvvo^j- LT\U\J- m^DO O
iALr\i/\ir\ir\irvi/\iAiALrNiAiAiAir\irv
HCOl^OJCTN^ffNOt— ^tC-CO-4-rHOO
HCMC\l^-3-lAlr>>\J>v-OC— COCOON
^f
H
LTl
O
CO
K>
O
VQ
01
VD
^
LTN
81
c^
ro
rH
rH
rH
lf\
NA
ON
MA
rH
c—
H
CO
rH
rH
-=t
ON
vo
CO
-4-
tr\
c5
5

-------
10k
       p=<
       O

       fa
       O

       B
       CO

  ^   8

  ?   B
       s
       H
       id
       g
       *

       a
       O
       
IS ^
° -^
-P -P CO
•H CO
£ •«-
OLfN
LT\

,
«
1 i
H

J3 &
**&
-p -p •
•H co si
B e
^8-
LTMA

J ™
S to
"^ . $
-p -P C5
•r4 CO
!§ ^
^, LT\
O
LT\

.
CM
•P -P
•H CO
,§ ^
H

Si
3 1
^ H
•P CO
£
O ~^v
O O
H

f
.a^
H -H-^
O O y)
> <; a
>=^
£i "M
< a
B

m
. r3 ^
r-l VH^^
O O bp
> <; a
. =s
A ~~ss
< s
%

.3-»
i-l -H^^
O O bD
><; s
. =s
^ >
< 3
B

CD
• rd ^
rH -H*^^
£3s
. «»
^ >
S

..!•*
rH 'H^^
O 0 bp
> < B
• ^
A ^
<1 R
S

.S-»
H -H^~^
g^g1
. "^
A ^
< B
B

>»
s
1 IJ-C\J^DoOJ-HC\JC\lJ-ONCJ\VOf-
c lOJCJrHhAt^C~K^OJa3^OCOt~-CT\
M3 H ^J- H
M
rHOOLTNOOOOJOOOOJO
I 1 l^-=i-00-S-OKNHa\^OCOHO-*
P IOOO\Oi-lrHOJrH^OJK>HH
K>K>C\J io\K>ror^rON^rAK\tAiA
^J-HCOrHL^hAU^CVJCVJH^I-CJONCU
i c\jN^oJc\icoroHOr-)j-s^-4-c\jaj
c— c— c— r-c— c— c— t-c— c— c— t— t— c—
MDOOU^ONM)HU)t— O\O^D
I I 1C— OOOOC\1OCJS^1-H
IllrHirvcOCOi-tH HH OJH
(A ro
OOOLTNl/NOOOOOOO
1 I irHt— C— OJH.4-J-CVJC— CO^OH
i i ia\o.-(K\t— CT\OOO\OCOO
N-\-=t-^--*J--^- ir\LfN^t- lA^- [^
OJ-ONh<-\COO\C\IS^OU3rHCOCOCK
1 OJOJO\COO\C\ILr\^|-l^j-^t_^-K>r^
C-C-VOVO\DC^t— t-C— D~-t-C— t-t-
SMOJt— LfNt— HS^l^^DVD\i)O[~-O
C— C— VO J- J- V£) J- UAJ-^t^t-VO a\K>
OOHOJOOOOOOOOOOO
^•VDt-ON^JDcOC^OtAVOl^aiCMCKH
r1OOJOJHOJC\JK\t<^(AM^K^K>i-l(M
-=f^t--=l--=|--4--=l--S--d--4--4--d--=J--4-J--=i-
tol^N^D CXJCO C— VO K>tAC— Lf\t— -4" C— CO
^t-h^K>^Mc\js^j- rr\K>tAC\jN^c\iaj
c-c—c-c— c-t-c-c— c-t— c-c-f-c— t-
OJO-4-^DO r^^|-^t-lAOHc\J-=f
N-NCTSJ-ONOHLrNOJcUOrHCOC— UAC—
HHH H H^HHH M
(OS-\CJOOOO\O^^OOOOO
CO^OONt— iHC— COON^OJ^D^tN^^i-N^
O^DC— M)iA_d-(AJ--*-=t-hr\rr\^tHhr\
irsj-^i-^t-*^)-^t-*-*-*Jt-*-*-*J-
VDOxrACO OSrHO H ONO\-^- t^co Ot—
^f K\-^- NACVJ NA-^--4- N^fO-^- N~\N^_4- OJ
t— t— t— C— C— C— C— t— C— C— t— t— C— t— t—
J-O-ii-OrO^OHO^UAMJCOC— ^QCT\
OJ^OCMC\J-^-rHtAhAOJr<^^t--=t-iH-d-tA
H OJ
COOOOOOHOLrNfArAt-VO H-3-VOOJ
tOirAtOOJHHOJOJOJOJOJOOOJOJOJ
f— c— t— t— t— t— t— c—r— t— t— f— c— c— c—
J-J-J-H^tC-OjasJ-HK^f-COt-O
OJOJCOHhAOJ-4- HOJC\JOJ-=tl^
OOst— O^NOOJlAI^NOlTvOJOOO
U^COrHOJU-NJ-VOCOOr— O\OLP>-=)-OJ
COC— C^CT\CT\CT\COCO O\COCO OC^COCO
OJOJOJOJOJOJOJOJOJto>C\lOJOJOJOJ
c— HLr\j-ocoLr\"^v-O^i'>'-lf—OJOJ
OJOJOJOJOJHOJOJOJOJOJOJK>r-lrH
C— t~-[— t— l>-t— C— t— C— C— t— f-C— C— t—
HOOU-\OJO\VDI^iOt— -*i-ICOl^OJCT\
MOJ OJ rA-=j- tr» IA vo ^ c— co o\o\
-cli
OJ
a\
•s
N^
\Q
OJ
t-
St
K-\
M
VD
[—
vo
-d-
ON
OJ
t—
s
03
LTN
OJ
^t
K~\
M^i
r-
H
rH
H
\D
a\
^t-
-J-
co
10
t-
TA
vo
K>
OJ
KN
LTN
OJ
t-
-ct
OJ
[-
co
CO
OJ
N-\
OJ
t-
cs
<:
                                                                                                                            t

                                                                                                                            !U

                                                                                                                            •P

                                                                                                                            W

-------
                                                                                 105
                                     TABLE 48
                 COMPOSITION51 OF DIGESTER GAS IN EXPERIMENTS ON THE
                                DIGESTION OF MANURE


19
26
33
40
47
54
61
68
75
82
89
AVG*
Control
C02
36-7
34.7
34.6
36-9
37-0
36.0
36.6
35-9
34.0
35-8
35-2
35-8
CH4
63-3
65-3
65.4
63.1
63.0
64.0
63.4
64.1
66.0
64.2
64.8
64.2
Unit 2
CO 2
31-5
33.^
32.2
31-9
33-6
34.7
37-2
37-1
36.8
38.6
35-7
34.8
CH4
68.5
66.6
67-8
68.1
66.4
65-3
62.8
62.9
63.2
61.4
64.3
65.3
Unit 3
CO 2
37-7
38.0
37-4
37-7
38.8
38.7
39-3
39-0
40.3
37-8
37-9
38.4
CH4
62.3
62.0
62.6
62.3
61.2
61.3
60.7
6l.o
59-7
62.2
62.1
61.6
Unit 4
CO 2
23.4
20.5
36.7
39-0
--
38.9
36.2
37-5
39-9
39-1
37-5
38.1
CH4
76.6
79-5
63-3
6l.O
--
6l.l
63.8
62.5
60.1
60.9
62.5
61.9
Unit B
CO 2
39-4
46.7
46.4
4i.9
37-5
35-2
36.3
38.4
39-3
38.6
42.1
40.2
CH4
60.6
53-3
53-6
58.1
62.5
64.8
63-7
61.6
60.7
6l.4
57-9
59-8
Unit C
CO 2
36.7
34.0
34.1
35-7
36.6
38.5
39-9
36.8
33-8
36.0
34.6
36.1
CH4
63-3
66.0
65.9
64.3
63.4
61.5
60.1
63.2
66.2
64.0
65.4
63.9
Normalized percent
At steady state

-------
106
                                                   "}
                                                   6
                                                                            O\
                                                                                  VO
                                                                                   tr\
                                                                               OA
                                                                               ^J-
                                                                               r-H
             OJ


             ir\
                                                                           CO
                                                                                   OJ
                                                                                          o\
                                                                                          OJ
                                                             VO
                                                             OJ
                            vo
                            r—
                            M3
                               OJ
VO
 •



rH
                                                             OJ
                                                             CM
                                                                CO
                                                                ro,
                            "rR
                             OJ
OJ
VD
K'vjJ


Is
                                                   O

                                                   a\
                                                                           vo
                                                                                          co
                                                         OJ



                                                         VD
                                                                                   CO
                                                                                          LTN

                                                                                          OJ
                                                                                                 VD
                                                                                                 rA
                                                                                                 OJ
                    I ^


                    1 CO
                                                                CO

                                                                ir\
                     fi
                                                      •d


                                                       s
                                                      HJ
             >> q
             O -H
             fl +?
             0) K>
                                O  60
                               •H -H
                                         -d
                                            •d
                                            s
tion
                                           •5


                                           &
§
•H
•P


1

s
                                                                     5
                                                          (U

                                                          cs
                                                                                    w
                                                                                   s
                                    •H

                                    -P


                                    rl
        CO

        $

        •d

        s
                                                                                              O

-------
                                                                                 10?
2)  the economic advantages of grinding to sewers and transport by the sewerage system
must be estimated; and 3)  a determination must be made of the benefits to be accrued
from reducing the bulk of a given waste by digestion.  Judging from experience of
the digestion of Monterey pine wood, very little reduction in the bulk of any material
containing wood would take place, probably because of the resistance of lignin to
anaerobic digestion.

        A fourth purpose evolved from the findings of the previous study, namely,
to determine the effect of a waste on the physical characteristics of sludge
effluent from the digester.  Monterey pine wood had a blanketing effect on the
sludge which interfered with circulation and mixing.  This was quite noticeable
when normal sampling procedures were practiced.  The subsidence of sludge took place
so rapidly following mixing that it was impossible to obtain representative examples
of the digester's solids content.

        Although Monterey pine could not be digested, it had no observable toxic
effect on the digestion process.  Monterey pine belongs to a group of conifers
characterized by a high content of pitch and resins.  These substances may be very
toxic to a digester culture.  Other conifers, of which white fir is an example,
have a low pitch and resin content, and hence should not affect the digestion
process adversely because of toxicity.  However, the wood may inhibit digestion in
other ways.  It could have the blanketing effect of rapid settling noted with
Monterey pine,  if so, the purposeful addition of a'woody material to a digester
would be undesirable because it would hasten the buildup of bottom sludges; which
in turn would necessitate more frequent shutdowns for the cumbersome task of a
clean-out.
Procedure
        Three digesters of $-£ capacity each were operated at a loading of 0.077 lb
volatile solids per cu ft of digester capacity per day.  Throughout the experimental
period of 107 days, the feed composition to the units was as follows:

        Unit 1 - 0# white fir, 100$ sludge

        Unit 3 - 10% white fir, 90% sludge

        Unit k - 60% white fir, k-0% sludge


        Mixing was accomplished by automatic mixing devices -which were activated
for 1.5 minutes each hour.  The units were maintained at 37°C throughout the study.


Results

        Gas production on the basis of volatile solids added is indicated "by the
curves in Figure 6-  Unit 1, the control (fed sewage sludge), averaged 10.1 cu ft/lb;
unit 3 (1056 white fir), averaged 9.3 cu ft/lb; and unit k (60% white fir), averaged
k.J cu ft/lb.  The digestion efficiencies of the digesters fed white fir calculated
by way of the formula given in Materials and Methods were found to be 20% for the
unit receiving 10% white fir, and k.k% for the one receiving 60% white fir.  The
results obtained with unit k probably are the more reliable than those from unit 3,
because the former received six times as much wood as did the latter, and consequently
any effect due to experimental error was correspondingly reduced.

        Other parameters of digestion efficiency, such as total and volatile solids
reduction and cellulose reduction, should not be taken at face value because the
rapid subsidence of the sludge precluded representative sampling of digester contents.
This can be readily demonstrated by the data on destruction of cellulose as presented
in Table 50.  If the values shown in the table were correct, then approximately 50%
of the cellulose input derived from white fir was destroyed in unit k.  This was cal-
culated from the cellulose inputs listed in Table 51 as follows:

-------
108
                                              f

                                            /
     4
    >
  i
 \

(
                                            \
   r
A
                                                      o
                                                      •o
                                                          05
                                                          Q
                                                          _l
                                                          O
                                                          cn

                                                          UJ
                                                          UJ
                                                          O
                                                          Q
                                                          UJ
                                                         UJ
                                                         tr ^
                                                         o u_
                                                         UJ Q
                                                            UJ
                                                         O
                   tr
                   UJ
           

                                                         UJ
                                                         o:
                           sonos
                         'Nouonaodd  svo

-------
                                                                               109
                                   TABLE 50
       APPARENT DESTRUCTION OF CELLULOSE IN THE  DIGESTERS RECEIVING WOOD
Day
4
11
18
25
32
39
46
53
60
67
74
8l
88
95
102
109
AVG.
1, 100$ Sludge
Residual
Cellulose
g/100 me
0.168
0.220
0.188
0.148
0.232
0.264
0.272
0.308
0.280
0.272
0.336
0.272
0.308
0.360
0.340
0.420
0.274
Destruction
*
90.3
87.5
89.2
91-5
86.6
84.8
84.3
82.2
83.9
84.3
80.7
84.3
82.2
79-2
80.4
75-8
84.2
3, 90% Sludge, 10$ WF
Residual
Cellulose
g/100 • m£
0.156
0.260
0.224
0.288
0.384
0.336
0.368
0.436
0.432
0.436
0.424
0.440
0.444
0.488
0.436
_.,
0.370
Destruction
*
91-5
85.9
87-9
84.4
79-2
81.8
80.0
76.3
76.5
76.3
77-0
76.1
75-9
73-5
76.3
,-
79-9
4, 40$ Sludge, 60$ WF
Residual
Cellulose
g/100 m«
0.196
0.320
0.568
0.972
0.788
0.880
0.632
1.136
0.884
0.992
1.J04
1.144
0.500
0.656
0.796
_-.
0.890a
Destruction
%
91-7
86.5
75-9
58.9
66.6
62.7
73-2
51.8
62.5
58.0
44.5
51-5
78.7
72.2
66.3
--
62.ia
Day 25 - 102 considered steady state.

-------
110
                                     TABLE 51

               DAILY  INPUT  OF  CELLULOSE TO DIGESTERS RECEIVING WOOD
To
Unit
1
3
k
Cellulose Added, grams
From Sludge Feed
1-736
1.560
0.700
From White Fir
0
0.370
1.650
Total
1.736
1.930
2.350
     1.   Control  (sewage sludge only) cellulose destruction equals &k.2%.

     2.   Unit k (10$ -white fir, 90$ sewage sludge) cellulose input from sludge
         equals 0.70 g/day.

     3.   Cellulose residual attributed to sewage sludge equals 0.70 x 0.158 equals
         0.111.

     k.   Average  cellulose residual equals 0.890 g.

     5.   Cellulose residual attributed to white fir equals 0.890 - 0.111 = 0.779 g-

     6.   Percent  destruction of white fir cellulose equals 1.65 - 0.779/1.65 x 100
         =  52.9-


         To have  a 50$ cellulose destruction without gas production could only mean
that either degradation proceeded only to the volatile acid stage of fermentation,
or that  nonrepresentative samples were taken.  Since the volatile acid content
remained constantly low as is shown by the curves in Figure 7, the former possibility
must be  rejected, and it must be concluded that the samples were not representative.
This leaves the  conclusion that the white fir was not degraded, and furthermore
that it  had the  same blanketing effect as did Monterey pine.  The results, real and
apparent,  are listed in Table 52.  (Results pertaining to volatile and total solids
destruction are  only apparent.  The reasons are the same as those applied to
cellulose  destruction.)

         The experiments indicate that the addition of small amounts of wood to a
digester would exert neither a chemically nor a physically adverse effect on the
culture.   Even with the addition of a high percentage of wood no adverse functional
effects  were noted.  Apparently, the main objection to adding wood to a digester
would be that it would settle out and cause a more rapid, than normal accumulation
of bottom  sediment.  There seems little likelihood than the problem of too much
wood in  the feed to a digester would occur under practical conditions.  For example,
a Santa  Clara study showed that the amount of wood in the city's refuse was only
2$ of the  total  refuse.
FIFTH EXPERIMENTAL SERIES - DIGESTION OF
COMPOSITE  ("SYNTHETIC") REFUSE
sludge,
In this series of experiments a "synthetic" refuse was digested with sewage
 The ratios of the two (refuse and sewage sludge) were based on the amounts

-------
                                                                    Ill
       \
                                                                      to
                      \
                                      H

              o
              o
              m
o
o
o
(0
o    o
O    o
10    o
CM    C\J
o
o
o
o
o
31IJLV10A

-------
112
                                     TABIB  52

            SUMMARY OF EEAL AMD APPARENT RESULTS OF THE EXPERIMENTS ON
                            THE DICSISTION OF WHITE FIR
Parameter
Efficiency of White Fir
Digestion, $
cu ft Gas Produced
lb Vol. Solids Added
cu ft Gas Produced
Ib Vol. Solids
Destroyed
Volatile Solids
Reduction, %
aTotal Solids
Reduction, $
aCellulose
Reduction, $
Methane $>
CQS %
pH (daily samples)
Alkalinity mg/Ji
as CaC03
Volatile Acids mg/£
as acetic
Unit 1
Control
100$ Sludge
--
10.1
16.6
60.7
«>
84.2
69.8
30.2
7-19
2823
37
Unit 3
10$ Wh. Fir
90$ Sludge
20.0
9-3
15-1
60.5
47.8
79-9
68.9
31.1
7.15
2500
kk
Unit k
60$ Wh. Fir
40$ Sludge
h.k
1-1
50. k
^
62.1
69.7
30.3
7.01
1390
33
        See text regarding sampling difficulties

-------
                                                                                 113
relative to each other generated per capita.  Therefore, the results obtained in
this series of experiments are those which one would expect were all organic
solid wastes digested in an existing sewage treatment system suitably expanded
to handle the additional loading.


Formulating the Synthetic Refuse

        The composition of the mixture was based primarily on the results of the
analysis made of Berkeley refuse in the first year of the overall project and
reported in the First Annual Report [I*-].  The analysis showed that about 25$ of
the domestic refuse processed at the site was garbage and garden debris; soiled
paper, 35$.! and clean paper, about 10$,  Of the garbage and garden debris mixture
about 80% was garbage.  Composition of the Berkeley refuse was quite similar to
that of refuse generated in Santa Clara County.  Garbage constituted about 12% of
the Santa Clara refuse; paper, 50$; wood, 2$; and garden wastes, 9$.

        Since the per capita production in the two areas was about 3-5 pounds "wet"
weight/day, this value was used in making up the feed.  To allow for wood wastes,
wood was included and constituted 2% of the "synthetic" refuse.  In setting up the
proportions of solid wastes to sewage sludge, the dry weights of the two classes
of wastes were used as the basis.  The dry weights of the various components of
the "synthetic" refuse were estimated as shown in Table 53-
                                     TABLE 53

                ESTIMATING THE DRY WEIGHTS OF THE COMPONENTS OF THE

                              "SYNTHETIC" REFUSE
Material
Garbage
Garden Debris (grass)
Paper (soiled)
Paper (clean)
Wood
% of Total
(Total = 3-5 lb)
20.0
5-1
3^-7
9-9
2.0
Wet
Weight
lb
0.700
0.178
1.210
0.3^6
0.070
Moisture
%
75-0
2k. 8
30.0
5-6
9-3
Dry
Weight
lb
0.175
0.089
0.850
0.326
0.063
        The paper fraction was further quantified on the basis of the relative
amounts of Kraft and newspaper to be encountered in refuse.  As mentioned previously
in the experiments on newspaper, the difference in digestibility between Kraft and
newsprint is considerable (Kraft is greater than 90$, newsprint equals ^8$),  and
a realistic estimate of their ratio in wastes must be made in setting up a represent-
ative "synthetic" waste.  Based on annual domestic consumption figures (196^) of
8,2^7,000 tons of newsprint and 9,900,000 tons of Kraft, the percentage of each in
paper wastes was calculated.  No adjustment was made for salvage, since a ratio of
1:1 (estimated by the American Paper Institute) is recycled.  Thus,  of the 1.176
pounds (dry weight) of paper consumed per person per day, 5^-6$ (0.6^2 pound) is Kraft,
and ^5.i$ (0.53^ pound) is newsprint.  Based on a loading of 0.077 pound/day
(3.70 g VS/day), the feed mixture had the composition shown in Table ^k.

-------
                                     TABLE 54

                 COMPOSITION OF FEED MIXTURE OF "SYNTHETIC" REFUSE

                               AND RAW SEWAGE SLUDGE

Material
Garbage
Grass
Newspaper
Kraft paper
White fir
Sludge
Total
Volatile
Solids
(g)
0.398
0.204
1.218
1.460
0.144
0.274
3.698
i of
Feed
Mixture
10.8
5-5
32.9
39-5
3-9
7.4
100.0
Experimental Procedure

        Four of the five digesters were operated at different loading rates.   Fifty
percent of the loading to the fifty digester (unit c)  was in the form of sewage
sludge, while the amount of "synthetic" refuse was reduced accordingly.   The  loading
to each of the units is listed in Table 55-   In summary,  the basic loading variables
were double loading at 3° days detention (unit 4), and single loading at 30,  20,
and 15 days.
                                    TABLE 55

              LOADING TO THE DIGESTER RECEIVING "SYNTHETIC" REFUSE
Detention
Time
(days)
30
20
15
30
30
Unit
2
1
3
4
c
Loading
g/day
3-70
5-50
7.4o
7.40
3-70
mj2/day
IOC
150
200
100
100

-------
                                                                                  115
        The duration of the experiment was 152 days for units 1 through 4, including
the acclimation period which varied for each unit.  The standard mixing procedure
was applied to the units, as well as standard measurements of performance parameters.
In addition, the theoretical maximum hydraulic loading was determined by deriving
kinetic constants for the rate of the hydrolysis of cellulose.  Unit C was operated
for 96 days.  Its results are reported separately from those of the other units.


Results

        The results obtained in the experimental run are summarized in Table 56.
In the digester receiving equal proportions of raw sewage sludge and "synthetic"
refuse, the alkalinity concentration stabilized above 1,700 mg/£ and the pH remained
constant at or near 7.0.  Solids reduction was only fair in the digester and reflected
the resistance of the newspaper portion of the feed mixture to biological degradation.
Total solids reduction averaged 43«8$j and volatile solids reduction, 51-9$'  Cellulose
reduction averaged 65-l$-  The calculated amount of destruction of the cellulose
in the solid waste was 54-8$.  Gas production by the digester was about 56$ of that
by digesters receiving raw sewage sludge (i.e., 56$ of 10 cu ft gas/lb volatile
solids added).

        Increasing the refuse portion of the mixture from 50$ to 92.6$, as was done
in units 1 to 4, altered the performance considerably.  Since the four units
received only 7-4$ sewage sludge, the nitrogen content of the feed was reduced to a
point at which the C:N ratio was 48.1.  Previous results (paper pulp digestion)
have indicated that the C:N ratio is the borderline at which a proper acid-base
relationship can be maintained.

        Alkalinity declined rapidly in each, unit, and corrective measures were
taken when volatile acids began to accummulate.  Alkalinity was increased by adding
lime or sodium bicarbonate.  In Table 57 are shown the amounts of lime or
added weekly to each unit to maintain an alkalinity above 2,000 mg/,0 (as
The quantities required for each unit were proportional to unit detention time.
The 30-day digesters (2 and k) required additions of approximately 500 mg/.2 per
week; the 20-day digester (unit l) required 750 mg/^ per week, while the 15-day
digester (unit 3) required almost 1,000 mg/,0 per week.

        The corrective measures were taken belatedly for unit 1, and as a consequence
the volatile acids concentration could not be effectively controlled for some time-
Several weeks were required to bring the concentration down from a peak of 4,975
mg/,0 to a stable operating level of approximately 300 mg/^.

        The composition of the gas from the various digesters is indicated in Table
58.  Apparently the detention period had some slight influence on the composition of
the gas.  The methane content declined from 58.1$ with the detention period at 30
days to 56-4$ at 20 days, and 55-8$ at 15 days.  Compared to that produced in
normal sludge digestion, the gas quality of these digesters was poor, in that it had
from 10$ to 15$ less methane content.  This again demonstrates the effect of a high
carbon to nitrogen ratio in the feed on the percentage of methane produced.


Kinetics of the Digestion Rate of the Cellulose
in the "Synthetic" Refuse

        The kinetics of refuse digestion were characterized by using the Machaelis-
Menten model and the cell continuity equation discussed in the section on theory
in the introductory portion of this section of the report.  Kinetic constants were
derived for the microbiological cultures used in this experiment.  Since in practice
mixed refuse contained over 80$ cellulose,  cellulose concentration was used to
represent substrate concentration.  The basic data required for this kind of
characterization are presented in Table 59-  Cellulose input and output data were

-------
116
      O

      B
      g
      CQ CQ


      S H
 LA   R
      fa
      O
      81
      I

      H
      O
      H

      £
      R
<
*
<
&


P<
CO
&


CO
1
3
rH
a)


^
---,
p
^
|-
&
to
6

,s
s
w
 ho
B
&
«!>
££>
$ *

@*

O^-
o
fH
we£-
a
H.l
(H bp
pq g
• «A
£<
d 60
M B
3 14
^. w
3S
^1
r^
j <;
4 •§
•o ^^-
O -P
^1 t|H
^ 0
O
.
o-e£-
>
H
S-yt
e
>>
a
HPJi-Hi-tH^-OHVDM3C— 1 r-loO
i-tOJPJHOJVDCMOJ K>OJ 1 t— |0\
OOOOOOOL^NOOOOOO
0\-d-CT\C—H- l>- C~ f- C— \Q \O t- &- t- C— C— C— C~-
^ OJ-d-OOCO-d- OJVD IO.N-NCOCO LTNC-
r-IOQOCOCT\OCOOJO\OCAONO
VOVO^S^JD LAl/\MD ITNMD l/"\V£) ir\LT\^o
M303VCiaJCV|VDCO-*C— C— OJ(MLO,to,
COChO\OirHOO\i-lt»-OO\OOON
^OlK^N^K^^t-^)- K\J- K>J- K>J--=J- N^
QOONQO OE— HHVQC-^O-NrHOCO
<>\M3D-v3vS
OOJOJO\OJMDH^l--*lAUArd-ir\
^DOCOHt-COCOU^W^l-rH-d-J- 1
ONOOO CM C-t-COVOC— f-t-C— t—
V£)VO\£l^QVOU3VO>^Q
cocococococoooaDoocococococo
^r^K^K^^^\K^K^«^K^^^^K^K^^<^^f^K^
cjojajcjojCJOJajaicMCMcMOJoj
\oir-ot~-aioc^coHO>Hoi-iaj
UAOVO L^LTNM3-rl- rOt— O\ITNVOU^IT\
HHHHHHHHH rHHrHH
CT\C— O\OVOl^VO-4--*t-OJ-^-OJO
t-LP>r-CO C— C— t- t— 00 Lr\cOcOCOcO
-^-K^MD-4-COt— OVDON^iOOJL^rH
^I-VOJ- L^NHHOJOa\U3l>-02VDUA
MD-=hVO VDVOM3VOVQMD-3"VOVO^VQ
oooooooooooooo
oooooooooooooo
lr\H*vD i-ICOJ- H CT\l^LA-d- H-^- pr\
OrACXHO\t-i-lrr\ONt^^t-CM^-H ONfAlAHOO IAKNVOH-
^J-^t^t-^t-^}- tO-4--d--4--=l--4--4--=J-3-
IACM (^VD K^OCO^t HCO IAOJ O\VO
H H C\J KA-=i--=J- lAVDVOt— OOOO O\
CO
OJ
IA
^
H
N^
O
t-
OJ
s
CO
o\
tr\
r-l
IA
^o
(A
10
CO
UD
CO
(O
OJ
t—
^
^D
t-
<-t
OJ

-------
117
1
a bo
o a
^t -H -H
fl a)
&•-
7
S

1
£
•P
s!

1
H

1
•H
g
H -H
-P
•H -P
P T)
™

7
•H
G
O
OJ -H
-P
^ §
g.8
1
rA

j
S
a
•H

r-}
w

•H
1

*
iS
fl

i?
fl
•H

H
fl

•rl
1
H
§
»

»j
P
p
l>
Si
•§ «
j|
H«_
^
W "^
i*

> a
a
ID "-•--.
tf w
P
•H~Q&

S nJ
d
QJ "~~^,
rd bp
-P M
••-I bD
O E
Si
» a

; •. ,s, , lii.aasassse.sss
CO rA O CO CO LT*1 fA M O r-H MD \D C — F~ ON CO CO U"\ CT\ LTS CO ^
!— -^----!— ^---^
i— t H O O O &\ O C3\OrHOOOOHOO CTN O ON O\ O
^f.^f.f-vot_voc-f_f-f.c_r-^f-f-VDr-vovof.
; , ,gejggS«S8i!iiJil>ii
LrxoOOL^OOOOOOLrvOOOOOOOOOO
KS^CMWCM^HHC.OJC.C.WC.CMWC.C.C.C.HCV,

^"^"^ HH r-1 H^
t— OJ lAOJ rA ON t— CO LPvOJ OJ (ACO «HJ- Q rAJ-t— CO l^Q
HHOOOCOCOCOOO OOONOOOO ONONONOO
i>-i>-^-r>-t-^D^DVD[r-ir-^-c-^)r>-t-i>.[~vovDvoi^i>-
HHHOJOJ H Hi-l
OOOtAOONQlAQOOOOOOOOOOOOO
\D-3- p— rH rA *-O IA f— t— i— 1 O\ N~\ 1A lA OCO i— 1 VO O^OJ N~\J-
,*fl«t»«*sfy§H^jii-f— C— t—
t— -3- HCO LPiOJ ON'vD rAO ^-i HCO lrN°j O\ 
-------
118
                                    TABLE  58

              COMPOSITION OF  GAS FROM DIGBSTBRS RECEIVING "SYNTHETIC"
                             REFUSE AND SEWAGE SLUDGE
Day
7
Ik
21
28
35
42
49
56
63
TO
77
84
91
98
105
112
119
126
133
140
147
AVG.
Methane, %
2
30 -day
59-3
69-0
63-6
--
--
54-5
55-7
67-9
51-6
48.7
58.7
56.5
66.7
56.0
55-9
--
55-9
57-2
55.8
55.8
57-3
58.1
1
20 -day
65-9
63-7
58.8
56.4
56.2
--
54.1
54.4
55.1
47.1
47-3
54.4
59-5
--
63.2
61.7
55-8
54.7
53-7
55-0
54.5
56.4
3
15 -Say
62.0
59-8
55.5
55-6
54.8
55-1
56-5
54.7
54.8
47-9
54.5
58.8
54.4
__
56.1
56.9
54.5
54.2
55-5
57.3
56-3
55-8
4
30-day
2x
58.1
60.9
57-5
52.7
55-3
55-3
56.4
55-4
56.5
56.7
55-5
57-1
55-9
55-7
--
56.2
54.9
57-1
56.3
55-5
54-9
56.2
Carbon Dioxide, %
2
30 -day
40.7
31.0
36.4
--
--
45-5
44.3
32.1
48.4
51-3
41.3
43-5
33.3
44.0
44.1
--
44.1
42.8
44.2
44.2
42.7
4l.9
1
20 -day
34.1
36-3
41.2
43.6
43.8
--
45.9
45.6
44.9
52.9
52.7
45.6
4o.5
—
36.8
38.3
44.2
45-3
46.3
45.0
45.5
45.6
3
15 -day
38.0
40.2
44.5
44.4
45.2
44.9
^3-5
45-3
45.2
52.1
^5-5
4l.2
45.6
--
43.9
43.1
45.5
45.8
44.5
42.7
43-7
44.2
4
30 -day
2x
4l.9
39-1
42.5
47.3
44.7
44.7
43.6
44.6
43-5
43-3
44.5
42.9
44.1
44.3
--
43.8
45-1
42.9
^3-7
44.5
45-1
43.8

-------
119






0
e
1
I
p=<
o
1
<:
0
S;
H S3
B R
CQ P
SJ
CQ
S „
R g
OP
PH ^
3$
O H
H ™
1
H
w

a
o
&
o
g

a
8






O
CD

g



LA
i-H
CD
-P




O
OJ
CD
H
-P
•rl
fl



O
CD
OJ
-P
§




">
™ S
™°>
.ag.
4


<=•*
ra ff
0^
^
4


H^x,
a
«t

•-< —
*§


H--X,
R
O — x.
"S
4
I
^^u-S^CKOJOXHl/X^C^J-CvjmoNrOO^
O\ C — LA N~N rH O\ rH O CVI CO NA OJ LA hA O\ CO <~l O
t~- [" — t — C~— C1 — VO C"" C~— C~ VO VO VJD VO VO LA LA VD ^O
tooooooooooooooooo
ooooooooooooooooo
-^- LAOCO 1ACO O\ -zt O OACO O H^t^J- t-~O
HHrHHHHMHHOJOJOJOJOJOJOJOJOJ
ooooooooooooo o o o o o
S££££B£S£®£®£®££©£
LA VO C^" C~— D-™ VO LA LA VO VO VO
C-O^CAOO^^^O>0-4-^00>fO fA OJ K\ -4" LA LT\ J- rA -4~ LA -zf _d"
HHHHHHiHHr-HHHHHi-lHHHi-1
ooo ooooooooooooooo

fO (H LA OJ CO rH C"~ CT\ O O OJ
ON.CO LArr\cO O H H t— rA OJ
-d-OJCOVOOJOOOOACO^tr-lcOrAOOOCO
S£^35S^^KK^^3!R^rt\RR
§00000000000000000
OOOOOOOOOOOOOOOOO
O O O i-HOJ H HHOJ-d'C— VOVDJ- LAlArA.-d'
HHHr-lr-lrHrHrHHi-HiHrHr-iHHHiHrH
Oo OOOOOOOOOOOOOOOO
-o^^^^ro^^f!,^^^^^^^^^
OJ hA O\ iH -d" OA CO ~h VO K^\ M~N
fO IO -cf -J" -^" -J" ^A fA fA if\ ff\
OJ LALr\CO-^-CO OJ IT— OJ D—iH LALAVO HCO-^" r-t
SJ&£d©tiS8®®tiS53^Svl?iS
oooooooooooooooooo
OJOOOJHOJOO\HrHOJOOHOJOJHOJ
oooooooooooooooooo
rO\ rA rO fo fr\ rA tA fO hA rA rA fA NA tO rA hA fA KA
O ON vo iH t— I vo vo o OJ c — -^l"
C^-H O O OJ O LAfAON-^-J-
fA--t^t-cj-^f-j- rArA.rA^A^A
VO rAO C^---t HCO LACJ CTvVO fAOC— -zf HCO tA
rA-^ LALAVOC^-L^-CO O\O\O H OJ OJ rr\ -^ -^ LA
r-HHHHHHHH
LA
VO
g
OJ
S
U3
H
^o
^o
O
A
LA
•3
1
£
OJ
CO
1^
S(
a
LA
o
NA
£
LA
S
S
H
o
rH
CM
CO
rA
a .
o














>
•V
C
bO
S
-P
3
CJ
H
S
0
CO
CO
Ti
LA § *
S I ^
W 0)
OJ 6 -H
O\ S *^ ^ CJ
cd JH S e CJH
T3  H
•\ CQ -P -P C
11) 1U C C O
+3 (ao CJ rH iH U
to q-i j -H -H (Up
TJ ta
a3 w C G a)
Jj H -H -H (5
M 4) 0) OJ a)
o w to m
05 3 3 3 3
rtf ,Q H H H
O aJ H «-H H
bO g 01 a) (p
H
U II II II II
<£ H OHM
nJ M CO CO

-------
120
used in  arriving at  removal rates and then to  cellulose destruction  efficiencies.
The range  of  efficiencies was from 63.5$ for a 30-day detention period to  52.5$
and 5^$  f°r periods  shorter than JO days.
         The  cellulose removal rate, q., for each unit was calculated with the use  of
Equation 1,
Average  removal rates proved to be as follows:

         Unit No.               'me cellulose^removed ^
                                  active  cells -daysy

           1                           2.092

           2                           1.753

           3                           2.979

           k                           2.027


        A significant comparison of removal rates may be made between units 3 and
k, which were loaded equally on an organic basis, but had differing hydraulic loadings.
It is evident from the comparison that the superior method for accelerating digestion
is by increasing hydraulic loading, rather than by stepping up organic loading
concentration.  This may be due to a difference in physiological condition of the
active  organism in the two digesters.  Judging from the results for units 1, 2, and
3, it would seem that improvement in removal rate occurs as residence time decreases.
However, the permissible increase in hydraulic loading rate does have a maximum limit.

        The decomposition rate of cellulose may be determined from Equations 9, 10,
and 11  given in the section on theoretical considerations, namely:


                         Tnax
                     11    K  + S
                           s

Therefore, by knowing the flow rate (F), the volume of the digester (v), the influent
cellulose concentration (So), the effluent cellulose concentration (S^, and the
cells concentration as represented by the organic nitrogen in the effluent sample
(Xi), the cellulose removal rate can be determined.  By plotting 1/q against 1/S,
Imax an!^ KS can be derived.

        The decay rate (kd), the maximum specific growth rate (|amax)j and the yield
constant (Y), may be estimated from the cell continuity equation, which is:

                                   1/9 = n - kd

or by Equation lA:

                                 1/9 = Y q - kd .


        In the present study, the kinetic constants Y, |imax> ^d> an(^ KS were calculated
from the basic data 0, Xit So, Sj. by means of a linear regression computer programming
instead of by using graphical solutions.  Steady state conditions were taken to be
from day 92 to day 155-  During this period the data pertaining to units 1 through
k were analized; unit k was excluded later because it introduced a second variable
to the variable detention period, namely, influent substrate concentration.

-------
                                                                                121
        The computed constants are shown in Table 60 and are as follows:

        Yield coefficient, Y = 0.01798 mg cells produced/mg cellulose removed;

        Maximum specific growth rate, ji    = 0.1204 day"1;

        Specific cell decay rate, k, = 0.0084 day ~1

        For practical purposes k, was small enough to "be taken as zero;

        Michaelis-Menten constant, K  = 28,353 mg cellulose/liter.
                                    s

Ks refers to the cellulose concentration in the digester at one-half the maximum
cellulose removal rate.

        Computing from nmax.> the maximum substrate removal rate (
-------
122
  S
      « !
•p
H O 4) to
> H A a s
CD CD CO -H rf
o ca EH i3
hO
a
rH -H flj W
O 2 EH T!
s
H • i1 
go I1
o •
rH TH
^ g_g,
rH •
cu HH
JH rH CVH
rH (U
o o
o o
>5 0) H
tJ cS p i
M 0 CO >j
cu
• ca n3
-p -d (5 cu
BO rH CO
>H n o M uo
O CJ
. 
H
l/N
aT
CM

CD
o
OJ
CO
CD
9

o
CD
CO
H

-------
                                                                                 123
        The Kb value was usually high, as compared to constants reported for other
biological systems.  However, it should "be pointed out only soluble substrates rather
than the particulate substrate reported herein were used in the reported systems.
The difference in nature of the substrate is an important distinction, since the
value of Ks is obtained in terms of the total concentration of linkages in the
substrate.  The fact that this was an enzyme-catalyzed system means that accessibility
of linkages to attack is a factor.  For a soluble substrate accessibility is no
problem, but for particulate matter only those linkages exposed to the enzyme would
influence the rate of formation of the enzyme-substrate complex.

        The statistical analysis indicates a satisfactory correlation for Y and
k(j regardless of whether or not the data from unit k are included.  However, only
the data from units 1, 2, and 3 meet the 5% test for level of significance for Ks
and Umax-  Although the correlation is not good, it may be considered acce^ ^able for
a system operated on a substrate containing a variable ingredient such as sewage
sludge.

        A comparison was made to determine whether or not this is a growth-associated
system.  In Figure 8 the net growth rate, 1/6, is plotted as a function of the
cellulose removal rate, q, and the gas production rate.  The fact that both gas
production and substrate removal increase as the net growth rate increases,  and
that the curves have similar slopes, indicates that this is indeed a growth-
associated process, as one would expect.


Solids Reduction

        The usual procedure for computing solids reduction gives misleading results
when applied to this study.  This is shown by the apparent magnitude of solids
reduction indicated in Table 6l.  The percentage removals declined as hydraulic
loading was increased.  However, percentage removals were calculated from organic
loading concentration, and do not account for improved efficiency from increases in
hydraulic loading.  For example, unit 3 received twice the hydraulic load of unit 2,
yet the influent solids concentration (g/m.0) was equal in both units.  On this
basis it is not surprising that the solids concentration in the effluent from unit 3
was somewhat greater than that from unit 2.  As shown in the preceding section on
kinetics, the removal rate was much greater in unit 3 than in unit 2.

        A more striking example of the impact of removal rate is given by the data
in Table 62, in which is given the residual solids concentration in each unit.  A
comparison of the data pertaining to unit 3 with those for unit k will show that
unit k- had a residual solids concentration nearly twice as great as did unit 3.
This underscores the difference in efficiency of the two units, even though they
appear to have equal percentage solids removals as indicated in Table 6l.

        The efficiency of the units in terms of gas produced per pound of volatilie
solids added or destroyed is shown by the data listed in Table 63-  The efficiency
of the cultures in units 2 and k, both on a 30-day detention period, were identical,
namely, 6.2$ on the basis of solids added.
        Of particular interest is the fact that the culture in unit 4 was about
more efficient that that in unit 3 when evaluated on the basis of the applied
measures of performance.  Yet in terms of solids removal, the reverse was true.
These two differences demonstrate that a longer detention time favors gas production,
while a shorter detention time favors substrate hydrolysis.


Efficiency of Digestion of the "Synthetic"
Wastes

        Only units 2 and k may be validly compared to the sludge (control) digester
with respect to efficiency since these were the only digesters operated on a 30-day
detention period.  The computed efficiency of both digesters was 60.6$.  The cellulose
destruction efficiency of the synthetic refuse component for unit 2 was 62.8$; and
that for unit k, 62.7$.

-------
    ID

    CM
 o
•o

^
o
r>  m
o  ^
o  -
tr
a.
    o
    m
    in
    (VI
                                                                                       o
                                                                                       q
                                                                                       10
                                                                                                          5


                                                                                                          £
                                                                                       m


                                                                                       CM
                                                                                           -o
                                                                                            a>

                                                                                            cS


                                                                                            a>
                                                                                           CC
                                                                                       m   3
                                                                                       CM  =
                                                                         o
                                                                        •o
                                                                         a>
                                                                        u

                                                                         v


                                                                         o
                                                                                       o
                                                                                       q
                                                                                       CVJ
                                                                                 o
                                                                                 LJ
                                                                                                        U
                                                                                                        O
                                                                                                        en
                                                                                                        in
                                                                                 O
                                                                                 a:
                                                                                 o

                                                                                 od

                                                                                 LJ
                                                                                 cc
                                                                                       m
                                                                 o
                                                                 m
        o
        6
CO
q

o
                                      m
                                      q

                                      o
q
d
if)
q
o
CM
q

o
                                        l-
                                          Aop '6/1

-------
                                                                          125
                              TABLE 61




FERCEWTAa; REDUCTION OF SOLIDS IN THE DICSSTION OF "SYNTHETIC" REFUSE
Day

19
26
33
40
47
54
61
68
75
82
89
96
103
110
117
124
131
138
145
152
AVG.
Unit 2
30 -day
detention time
Total
71-1
69.0
73-6
66.0
64.6
60.5
66.0
69.2
64.8
65-8
61.4
62.9
62.9
63-3
55.0
59-2
51-7
49-3
58.7
53-6
62.3
Volatile
77-0
74.5
79-8
71.2
69.6
65-1
71.2
75-0
70.0
71.0
66.1
67-9
67.8
68.4
59-1
63-9
55-5
52.6
63.2
57-5
67.3
Unit 1
20 -day
detention time
Total



58,7
52.1
49.8
65-1
66.2
71-9
70.8
70.5
70.5
65-7
59-9
56.1
56.1
55-7
48.9
52.5
56.8
60.4
Volatile



65-5
58.0
55-5
72.4
73-6
80.0
78.9
78.5
75-5
73-2
66.7
62.5
62.5
62.0
54.5
58.4
63-3
67-1
Unit 3
15 -day
detention time
Total



45-7
48.8
37.3
46.5
54.0
46.1
44.5
43.9
51-2
4l.2
50.0
37.1
44.5
41.3
48.5
^3-5
47.5
45-3
Volatile



64.0
54.0
41.4
65.0
60.0
51-1
62.8
48.8
56.8
45-7
55-5
41.3
49.4
45.8
53-7
48.1
52.6
52.7
Unit 4
30 -day
detention time
double loading
Total



74.8
62.2
55-8
61.2
68.3
54.3
55-0
53-5
50.0
52.2
50.0
44.5
48.3
43.0
29.1
39-0
40.2
51-8
Volatile



83.0
69.1
62.0
68.0
75-8
60.3
6l.o
59-5
55.5
58.0
55-5
49.4
53-7
47.8
32.3
43.2
44.7
57-6

-------
126
                                     TABLE  62

          SOLIDS CONCENTRATION IN THE EFFLUENT OF DIGESTERS RECEIVING A
                        "SYNTHETIC" REFUSE AND SEWAGE SLUDGE
Day
19
26
33
4o
47
54
61
68
75
82
89
96
103
110
117
124
131
138
145
152
AVG.
Unit 2
9 = 30
Total
3-07
2.89
2.63
2.56
2.42
2.38
2.37
2.42
2.14
2.19
2.05
2.00
2.09
2.15
2.09
2.24
2.27
2.25
2.19
2.14
2.20
Volatile
2.08
1-97
1.77
1.84
1-77
l.8o
1.70
1.68
1.56
1.59
1.54
1.48
1-57
1.59
1.64
1.72
1.8i
1.82
1.68
1.70
1.66
Unit 1
e = 20
Total
2.12
1.98
1.98
1.92
1.90
1.88
2.11
2.40
2.45
2.69
2.69
2.80
2.99
2.88
2.80
2.77
2.64
2-53
2.43
2.32
2.56
Volatile
1.40
1.40
1-37
1.46
1.50
1.50
1.50
1.69
1-57
1.76
1-77
1-93
2.12
2.16
2.16
2.14
2.04
2.03
1.92
1.78
1.87
Unit 3
0 = 15
Total
2.50
2.40
2.36
2.11
2.06
2.05
2.16
2.17
2.12
2.13
2.16
2.21
2.32
2.40
2.46
2.42
2.4?
2.47
2.32
2.30
2.28
Volatile
1.71
1.78
1.72
1.62
1.66
1.72
1.64
1.70
1-73
1.64
1.78
1.76
1-93
1.92
2.07
1.99
2.03
1.99
1.91
1.86
1.84
Unit 4
e = 30
Double Loading
Total
3.49
3-11
3.28
3.29
3.22
3-62
3-57
4.05
3-47
3.50
3.40
3-41
3.84
3-90
4.03
4.11
4.34
4.23
4.12
4.01
3.84
Volatile
1.90
1.98
2.15
2.31
2.38
2.80
2.64
2.77
2-67
2.73
2.66
2.74
3-06
3-12
3-30
3-31
3-57
3-64
3.44
3-34
3-05
  Steady  state average day  $4  - 152

-------
                                                                                               127
    a
rA   fe
VO   O

,-^
1
c a
.S3
^£8
•H 43 1
3$X
.£
j?g
•3 ^
o%"'
m


1
-p
§
•H
rr\ 43
a
•H -p
S3
If
LA
H


1
•p
1
M -P
.0 S
SJ5
£3
1
g


1
•H
-P
d
o
•H
OJ -P
.0 g
££
S3
1
O
rA

1
3 .
-•^ h
4-1 CO
g *
s
\ "d
£ ,S
^ s
g <
1
to — -.
5 ^>
3 Hn
2
o
5 •
\ h
^ m
g *
s
«• s
ri
i
to ~<^.
S+>
£H
3
CJ
s .
\ JH
CH in
3 &
O
A
^^ ti
+3  5
"*H ta
3 ,S
O
s
	 Ti
£ £
^ S
g <
1
W ^
5 C
g

IT\CO O\M3CO-* OJCO^£) C~-U^M3 CT\QO*^D tOrH
co a\ooo HOJ oocoooa\vo I-H c— j- vo

HC— C^-OJ C\J ON^\IAO\OC^OO C— V£> C— OJ C\J
t— MDVOC— CO\£>t^-MDmiA^-d- N^LfNiA^OC—
O m tA O -* O -HO P'AQ Q O^U>-^OV£) OO
ffxCUt^-U^GNOC— (AO4HuS^OJV£)t— QOJOJr-IC^
^OCO OSH O HrHrT\rHCVJ O Q\CQt~-£— \OQ\G\Q H
O O OrHrHr- IrHrHr^rHrHOOOOOOOr-lrH
oooooooooooooooooooo
m D— K> o O\H m 1-1 c— IA co t— ro c— ir\ roi H
OHLf\Q>ONrHcO HCO OC— Ir- t- H O\ H O
HrHH HHH r-J r-l H
V£) r^\roa\OA^-K>^d- OcO-4- OJ^)-* rHj-,^
\O \D \& i/\ir\i/\iALT\irv^t^t rorr\Lr\u\t/\irN
OQOfOOcOCOHOC\J-d-OlAO(T\HC— -^-C—hTs
I^gNyDC^fAOJU^voOJ^cO'-looH.-IO.tr-rrscoC-
00 5\H O OOQ\0>Q>cncOCO C— F-ir\l?>cocOc5co
O OHHrHHOOOOOO OOOOOOOO
OOOOOOOOOOOOOOOOOOOO
aj a3
OJ oco o\co rno f-ico o o%^co N~\LAO-^-
O«HHmc\joJ\ovou^v£>ir\vo-=t- o>Oooo
H H H «H H
a) aJ
C— J- \O ror-lco C— 00 -* -* O\roOcooO (>*^t
^ovnvo-d' c\j rH -4- j- -* J- ro-^- toLfNir\Lr\ir\
aj oj
t— O K>C— OQ CO rOCVJ^J" (-1 U^C^pp-3- OJOQ CU Lj-\OJ
LT\ C\J C— rH CO O CM LT\ OJ t— CO rOK>f— OJ^OO Oi-HLTN
ONco c— co t>-co moj cu ir\ tr\ IA ir\ Jb- tr\ ro ^- t»- t^ v£>
oooooooooooooooooooo
oooooooooooooooooooo
FA^t LjAH-4-MD O ^t O t^MD LAVOCOVO-* O C— J- O
CO O\t-O ONCOCO O»OCO CT*O\C7\CO O^O CM "-JCO ON
r-t i— i rH i— I rH
-^-OONHIAVOC— OOOJfA-4-lT\OrOHMDHrOH
\O [— LA C~- V£l 1/NIT\^— t~-VO1^OVOVOVO1s£)-^- ^DMD LTNlA
O O-^f OJO-*OJfOK^OJVO\O ONOJHOJ i-IOHO
OJ C-COCOfOlAVDt-!^c3 HCJ OJ ONHN^-=f ONACVJ
LAlTN-d- LT\lTS_d-_d- LAlTiUSlALALTN-^- irNK~\U"NLr\_4-_j-
OOOOOOOOOOOOOOOOOOOO
oooooooooooooooooooo
CTvVO fOOt— -^ HCO l/NOJ O\ \O rAOt-^1- HCO LACvJ
H OJ H-\-=J--*lA^Oi'Jjf-OOCO ONO HHCVI fT\f^\-d- LA
rHrHrHrHrHrHHrH
H
H

OJ
VD
cv
§
o
H
s
ro
IA
H
O
KN
D—
H
IA
•tR
«
0
LTN
01
a\
CVJ
\o
OJ
R
o
o
e
<

-------
128
        The results are summarized for each parameter In Table 6k.  A summary of the
kinetic constants derived for units 1, 2, and 3 is given at the "bottom of the ta"ble.


DISCUSSION

        The laboratory phase of the studies on the anaerobic digestion of solid
wastes was initiated over three years ago, and was completed about three months
prior to the writing of this report.  In this section of the report is given a
brief summary of results obtained to date, as well as a brief evaluation of their
relevance to the objectives of solid wastes management.

        The laboratory-scale investigations were divided into three categories;
namely, l) those concerned with the digestion of urban organic wastes in combination
with sewage sludge; 2) those dealing with the kinetics of solid waste digestion; and
3) those pertaining to the digestion of organic solid wastes in combination with
animal manures.  Major findings made in each of these categories of study are
summarized in Tables 65, 66, and 67, respectively.


Digestion of Urban Refuse

        The data in Table 65 emphasize the efficiency with which the destruction
of cellulose is accomplished in the digestion process.  As far as refuse is concerned,
cellulose is of primary importance, inasmuch as it constitutes approximately 80% of
the organic material (dry weight) in urban wastes.  It is significant that Kraft
paper, which constitutes about ^0$ of the organic urban wastes, also was the material
most readily destroyed in the digesters.  A clue to its ease of destruction is that
Kraft paper is about 97$ cellulose; and of this cellulose, 9^% is destroyed in the
digestion process.  The second largest component of the organic fraction of urban
solid wastes is newsprint.  It constitutes about 33% of the total organic urban
refuse, and of this amount about 50% is destroyed in the digestion process.  Thus,
paper, a component which accounts for nearly 75$ of the dry weight of the organic
fraction of urban wastes, can be destroyed to the extent of 82$ through anaerobic
digestion.

        Green garbage, which probably accounts for around 10$ of the organic urban
refuse in terms of weight, id digested readily.  In the experiments, the overall
digestion efficiency of digesters receiving nothing but green garbage was approximately
90$ that of the control digesters which received only raw sewage sludge.  Destruction
of the cellulose in this material probably was about 80$.  In terms of overall solids
and cellulose destruction, garden debris in the form of grass clippings was digested
with an efficiency about equal to that with raw sewage sludge.  However, gas
production efficiency was only about 73$ of that with sewage sludge.  Wood proved
to be almost immune to the digestion process.  On the other hand it does not exert
any inhibitory effect on the process.

        A combination of a composit ("synthetic") refuse consisting of the materials
discussed in the preceding paragraphs and of raw sewage sludge digested quite well,
provided the alkalinity was kept at an appropriate level.  The proportions of
refuse and sludge were those to be expected when organic refuse routinely ground
into the sewers and digested along with the sewage sludge.  Inasmuch as the nitrogen
content of this combination of refuse and sludge was less than optimum (C:N, ^8:1),
the pH of the culture had a tendency to be lower than desired.  This tendency was
corrected by increasing the alkalinity of the culture through the addition of
Ca(OH)3.

        Judging from the results obtained in the studies, any combination of sludge
and paper fed a digester should be at a maximum about 60$ paper.  In practice this
would mean that about 80$ of the paper in the waste stream could be digested.  The
remaining 20$ would have to be diverted.  However, in practice,  especially in the
not-too-distant future, it is highly unlikely that 80$ of the paper entering the
waste stream will be destined for destruction.  On the contrary, the increasing

-------
                                                                    129
                        TABLE  64

SUMMARY OF THE RESULTS PERTAINING TO THE DIGESTION OF THE
                   "SYNTHETIC" REFUSE
Parameter
cu ft Gas Produced
It Vol. Sol. Added
cu ft Gas Produced
lb Vol. Sol. Destroyed
Volatile Solids
Reduction, %
Total Solids
Reduction, $
Cellulose
Destruction, %
Methane, %
C02, %
PH
Volatile Acids
mg/i as acetic
Alia Unity
mg/,0 as CaC03
Alkalinity Added
mg/^/week
Unit 2
Q = JO days
6.2
9-3
67-3
62.3
63-5
58.1
4l.9
7-18
33
2696
567
Unit 1
9 = 20 days
5-1
7-3
67.1
60.4
52-5
56.4
43.6
7-07
339
2521
750
Unit 3
0 = 15 days
5-3
10.1
52.7
45-3
54.0
55.8
44.2
7-00
62
2281
978
Unit 4
Double Organic Loading
6 = 30 days
6.2
11.1
57.6
51.8
63-5
56.2
43.8
7.02
63
2764
513
Kinetic Constants for
Units 1, 2, 3
Yield Coefficient, Y =0.0
,,_Q mg cells produced
mg cellulose removed
Specific Cell Decay Rate, K = 0.008*! day"1
Correlation Coefficient, r = 82.50$
Michaelis -Menten Constant, K = 28353 rag cellulose per liter
s
Maximum Specific Growth Rate, u = 0.1204 day"1
Maximum Substrate Removal Rate, ci = 6-7
Q mg cellulose removed
mg active cells • day
Cell Doubling Time, G =5.8 days
Cell Washout Time, 9 = 7.8 days

-------
130





£>
a
d -H i— l
JL, ^ O 4J
to (U J3
$ *rl ^-^
+i
p
0) 0 0
to -H fl
O -P CO
i— 1 o -H ' — «
3 3 o-ejt
H -P SH^"

-------
                                                                                131
                                    TABLE 66



           SUMMARY OF RESULTS OF STUDIES ON THE KINETICS OF DIGESTION
Residence
Time,
e
(days)

30
20
15
Active
Cells
Cone . ,
(ng/-0

382
397
382
Cellulose
Concentration
Influent
So
(mgA)
31,640
31,640
31, 640
Effluent
Si
(ng/J)
11, 550
15,030
14,570
Efficiency
Cellulose
Destruction
(*)

63-5
52-5
54.0
Cellulose
Removal Rate, q
S Si
q = xi e

1-753
2.092
2.979
        Active cells measured as organic nitrogen concentration.




        Comprises over 80$ of substrate concentration.



                   Kinetic Constants Computed from Basic Data






      (From Michaelis -Menten, q. = •^ax. ' S and Cell Continuity, ~  = Yq-K )
                                   Ks + s                       6c       d





Yield Coefficient, Y = 0.0179^ MS sells produced per mg cellulose removed.




Specific Cell Decay Rate, Kd = 0.0081). day"1.



     Correlation Coefficient, r = 82.50$.




     Level of Significance, P = 0.01.





Michaelis -Menten Constant, K  = 28,353 mg cellulose per liter.
                            S


Maximum Specific Growth Rate, n    = 0.1204 day'1.
                               iflcix


     Correlation Coefficient, r = 36.80$.



     Level of Significance, P = 0.05.
                                 max
Maximum Substrate Removal Rate, q






Cell Doubling Time, G = =7^  = 5-8 days.

                           X


                            1
         = 6.70
                                                   "6 cellulose removed

                                                   mg active cells -day
Cell Washout Time 9
                   w  " Y
= 7-8 days,

-------
152
"o1
a*"*
,d 
H «
cS g
CS -P H
co d
* 1
Cellulose
Destruction
<*)
fl
o
hO -H
d -P
•H h>~ >
•d o-e^.
fM



^
s
o
&
o


CO O H
ON O vo
ITN VO VO

OJ IfN VO
ffN. Q LT\
IfN CO -*

O CO H
l/N C- -*

l^ CO K\
t— VO 1A
VO t— J-
t- VO H
t— ON ON
LA VO (A
<£ ^
1 H VO
ON -*
CO CU
O rAVO LTN 1A
r— 1
H
••
£
it
&
o
c a a
$ If 1^
S3 rt S 0 ft
AJ ,M fn X ft
O O O O CO
•rH -H ft -H ?
6 6 p2 6 si

H OJ i-l
CO IA rH
VO VO IA

IA ON t—
IA J- LTN
vo H .3-

ON -* rr\
IA H J1

H ON ON
r-l t- VO
VO OJ .d-
VO rH VO
• » •
0 OJ LTN
UN OJ fTN
1A
• 1 1
o
LT\ (T\ O LTN LT\
rH



ra ra
& S ^
p -H tt) 
-------
                                                                                133
demand  for secondary fibers will lend to a constantly increasing demand for
recycling paper.  More properly, digestion should be reserved for digesting the
garbage fraction of refuse and those other organic fractions not amenable to
processing for recycling or for which there is no demand.  Digestion as a disposal
process or step in the disposal process, would be especially compatible with a
system involving the hydraulic transport of solid wastes.


Kinetics of Digestion

        Results obtained in the kinetic studies on digestion are summarized in
Table 66.  The medium fed the digesters was the combination of "synthetic" refuse
and sewage sludge described in the preceding paragraphs.  In addition to learning
something about the kinetics of the process, the investigation was aimed at
determining the minimum hydraulic residence time at which a digester could be
maintained.  Detention times of 15, 20, and 3° days were tried.  Judging from the
results, the rate of removal of cellulose increased with a decrease in detention
time within the range of those periods applied in the experiments.

        Optimum conditions for operation were characterized by kinetic constants.
The constants were computed by means of a linear regression program based on the
Michaelis-Menten enzyme catalyzed model and the cell continuity equation.  On the
basis of the kinetic constants thus derived, the cell doubling time was computed
to be 5.8 days; and the cell washout time, 7-8 days.  The washout time is the
minimum residence time at which a stable bacterial population can be maintained.
Although a residence time of 7-8 days seems short in terms of conventional anaerobic
digestion practice, unquestionably, a much shorter residence time would be possible
under environmental conditions more favorable than those prevailing in the experiments.
For example, the "feed" mixture was far from ideal in that the C:N ratio was too
high for efficient cellulose destruction.  Thus, only 63-5$ of the cellulose was
destroyed in the experiments; whereas other experiments, in which conditions were
more favorable, showed that 80% of the incoming cellulose can be destroyed.
Obviously, increasing the rate of cellulose destruction will entail a change in the
kinetic description of digestion from that given in the present report.  Chan [23],
in his work on the kinetics of cellulose fermentation (using an artificial substrate),
found that the cell washout time could be as short as 2.86 days.   He worked with a
carefully formulated substrate consisting of finely divided cellulose powder and
soluble nutrients, and maintained his culture under optimum environmental conditions.


Digestion of Organic Refuse and Animal Manure

        The utilization of animal manure as a nitrogen source in the digestion
process proved to be effective — especially when chicken manure was used as the
source.  According to the data in Table 67> the efficiency of cultures digesting
chicken manure was equal to that of cultures digesting sewage sludge in terms of
solids reduction, and about 50% as efficient in terms of gas production.  Results
obtained in the digestion of combinations of chicken manure and components of
refuse lead to the following observations:  l) Chicken manure is  readily digested
in combination with Kraft paper pulp at C:N ratios as high as 70:1.  Solids
reduction is satisfactory and over 90% of the introduced cellulose is destroyed.
2)  In terms of cellulose destruction and gas production a 1:1 mixture of chicken
manure and newspaper could be digested at an efficiency approximately one-half
that at which sewage sludge normally is digested.   3) A mixture consisting of equal
portions of chicken manure and grass clippings will be digested with an accompanying
solids destruction nearly equal to that which takes place in sludge digestion.  Gas
production is about two-thirds that which takes place in the digestion of sewage
sludge.

        As others have found, steer manure remains relatively unchanged in the
digestion process,  in that only about 25% of the solids are destroyed.  Gas
production efficiency was only about 15% of that when sewage sludge was digested.
A mixture of equal parts of steer manure and grass clippings was  digested with a
resulting solids destruction about 40% that taking place in sludge digestion.   Gas
production from the digestion mixture was less than 5°$> of that from digesting
sewage sludge.

-------
Economics of Solid Waste Digestion

        According to the economic analysis described in the Second Annual Report, the
total per capita annual cost of separating, grinding, and digesting refuse would be
$2.18 (1968) for a city of 30,000, $1.27 for a city of 300,000,  and $0.75 for a city
of 1,000,000.  Total costs per ton of refuse digested for the above population levels
would be $^.00, $2.32, and $1-^2, respectively.  If only the garbage fraction of
refuse were digested, the per capita costs would be lower than those cited, but
higher on a per ton basis because of the lesser volumes involved.   A useful by-product
of refuse digestion would be the methane produced by the culture.


GENERAL CONCLUSIONS

    1.  The disposal of the organic fraction of the solid wastes by anaerobic
        digestion process would be economically feasible provided  the costs of
        dewatering the sludge were reasonable.

    2.  No inhibition or retardation of an anaerobic culture will  occur when solid
        wastes are combined with sewage sludge as a substrate for  digestion.  There
        is an important proviso, however,  namely that the nitrogen requirements of
        the culture are met.

    3.  A significant reduction in the bulk of the incoming material is accomplished.

    k.  The advantages inherent in the hydraulic transport of solid wastes may well
        justify the incorporation of digestion as a disposal method in areas so
        served.

-------
                   V.  BIOLOGICAL FRACTIONATION OF SOLID WASHES
INTRODUCTION
        The research effort of this phase of the technology investigation is concerned
with the enzymatic conversion of the cellulosic fraction of solid wastes to glucose
or other useful products by microbial action.  Previous work as described in the
First and Second Annual Reports involved  l) a literature survey of potentially
useful microorganisms;  2) a preliminary evaluation of the feasibility of using
certain organisms, particularly Sporocytophaga myxococcoides and Myrothecium
verrucaria, and  j) construction of a J-stage fermentation apparatus (14 liters per
stage) suitable for batch or continuous operation.

        Work during the past year was concerned primarily with two aspects of the
problem; namely, laboratory studies involving the fungus Trichoderma viride QM 6a
and directly toward improving the yield of the enzyme celluloase; and a process
design and economic evaluation of an enzymatic saccharification process based on
the fungus.


EXPERIMENTAL STUDIES ON ENZYME PRODUCTION


General Procedure

        The experiments were carried on with the use of 14-liter New Brunswick
microfermenter units modified to meel; the experimental conditions •  The internal
dimensions of the fermenters are 8.5 in. diameter and 17 in. in height.  Arranged
in the interior of each unit were four hollow baffles and numerous probes and
ports.  Each unit was equipped with two 4.625-in. four-blade turbine impellers, one
mounted directly above an air sponger; and the other, above the liquid level to aid
in breaking up foam.  A complete description of the apparatus is given in the Second
Annual Report.

        The organism used in the experiments was Trichoderma viride QM 6a.  The
temperature was maintained at 29°C.  Aeration was at 0.25 WM, i.e., at 2 4/min. for
the 8 liters of medium contained in each unit.  The impellers were rotated at 150
rpm.  The carbon source was either glucose, cellulose (Solka floe SW^O), or both as
specified.  All fermentations were performed batchwise•  The analytical techniques
used were as follows:

    1.  determination of dry weight of culture broth;

    2.  measurement of reducing sugar concentration;

    3-  measurement of cellulase enzyme activity; and

    k.  microscopic examination and contamination tests.


        For the dry weight determination, two 10-m,2 samples of culture broth were
centrifuged at 5,000 rpm for 5 minutes.  The supernatant was saved and the percipitate
was washed and recentrifuged.  The supernatant from the wash was poured off and the
percipitate was dried overnight in a 95°C oven and then weighed.  In runs where
cellulose was used as a substrate, the dry weight figures were a total of both the
cell material and the residual cellulose.
                                        135

-------
136
        The  concentration of glucose or total reducing sugars was measured according
to the denitrosalicylic acid (DNS) method  [25].  Three io0 of DNS reagent (see
reference for preparation) were added to one mi! of sample in a large test tube and
the resulting mixture was placed in a boiling water bath for exactly 5 minutes.  The
test tube was then placed in a running tap water cooling bath for approximately 5
minutes.  The liquid was then diluted to 25 m£ with distilled water and the test
tube was covered and inverted 4 to 5 times to mix.  Absorbance at 600 mn was measured
with the use of a Bechman DU-2 spectrophotometer.  Readings were corrected for appro-
priate reagent and substrate blanks.  The reducing sugar concentration measured as
glucose was  determined from a calibration curve based on glucose standards.

        Cellulase enzyme activity was measured by the ability of the enzyme to
hydrolyze Whatman No. 1 filter paper under standard conditions.  This form of
cellulose was chosen for several reasons .  It had been used previously by workers
 [4, 26, 2J], and thus would provide a common reference point for comparing results.
Secondly, Whatman No. 1 filter paper is readily available and is a highly standardized
form of cellulose.  Thirdly, and most importantly, its susceptibility to enzymatic
hydrolysis is about on a par with that of the forms of cellulose which would be handled
in a waste cellulose conversion process.  A filter paper (FP) activity unit is defined
as the number of milligrams of reducing sugar produced by 1 milliliter of cell-free
enzyme solution acting on 50 mg of Whatman No. 1 filter paper ( a 1 x 6 cm strip) in
1 m£ of 0.05 M pH 4.8 Na citrate buffer at 50°C for 1 hour.  At the end of 1 hour,
1 mi of this hydrolysate is tested for reducing sugar concentration by the DNS method.

        Before any of the analyses were performed, a small sample of the culture
broth was examined microscopically to detect any visible contaminants,  and also to
observe the  stage of growth of the culture.  Also at this time, plates  of glucose
nutrient agar and potato dextrose agar were streaked and incubated for about one
week as a further search for bacterial or fungal contaminants.


Kxperiment 1.  Glucose Substrate with pH Control

        An initial experiment was performed to determine the preliminary growth
characteristics of Trichoderma viride QM 6a on a glucose substrate.  The nutrient
medium was that developed by Mandels and Weber [28].  The composition was as possible:
KH2P04, 2 g/B; (NH4), S04, 4 g/&; urea, O.J &/&; MgSVTHaO, O.J g/4; CaCl2, 0-3 g/4;
FeS04'7H20,  5 mg/£; MnSCU-THaO,  1.56 m%/£; ZnS04-7HaO, 1.4 mg/£; and CoCl2,  2 mg/£.
Reagent grade glucose served as  the carbon source and was added at a concentration
of 10 g/£.  The glucose was sterilized separately to prevent the formation of
inhibitory products.  A silicone antifoam agent (Union Carbide SAG 471) was  added
in a concentration of 100 mg/,0.   Difco protease peptone No. 2 was added to boost
cellulase production [28].  To facilitate the measurement and addition  of trace
minerals, a  concentrated (200 x) solution was prepared with 950 m£ distilled water
and 50 m£ concentrated HC1.  Distilled water was used in all medium penetration.
The pH was adjusted to 5-0 prior to sterilization,  but it rose to 5-8 to 6.0 during
sterilization.  It was adjusted  to 5-0 after sterilization.

        The inoculum was 100 nU!  of Trichoderma viride from a J- to 4-day old shake
flash culture grown on a 1% glucose substrate having the same composition as that
of the medium used in the fermenters•

        A lag period of several  hours usually followed inoculation.  The lag was
characterized by a rise in pH — probably due to the deamination of the  amino acids
in the peptone.  Drop in glucose concentration and growth of the organism during the
first 80 hours are plotted in Figure 9-  As the figure indicates,  most  of the growth
occurred during a 10-hour period.  Active growth was accompanied by acid production.
However,  the pH was held at 5.0  by the automatic addition of 1.0 N NaOH.  Fifty-seven
percent of the glucose was converted into cellular material (dry weight).  The cells
began to autolyze after maximum growth had been reached.

-------
                                                   137
 6.0 f
FIGURE 9.  GROWTH OF  T.  viride ON  GLUCOSE
          SUBSTRATE  WITH pH  CONTROL
                                            SW 100

-------
158
         No  cellulase  activity was observed  in the experiments.  None was expected
 since  the medium contained no inducing agent.  Probably some constitutive cellulases
 were present,  but their concentrations were lower than the sensitivity of the
 analyses.


 Experiment  2.   Cellulose Substrate Without
 pH Control

         The next experiment was performed to determine the growth characteristics of
 Trichoderma viride QM 6a when grown on a cellulose substrate without pH control.
 The nutrient medium was basically the same  as that used in Experiment 1.  One
 modification was the  use of cellulose (Solka floe SW 40) instead of glucose as the
 carbon source.  The concentration of the cellulose was 10 g/£.  Another was that
 the inoculum was grown in 100-108 shaker flasks with a 1$ cellulose, 0.1$ glucose
 substrate.   The glucose was added to help promote growth of the spore suspension
 used for initial incoculation.

         Foam production was a very serious  problem in all experiments in which
 cellulose was  used as a substrate.  Attempts to eliminate foam by using a variety
 and combination of antifoam agents proved unsuccessful.  The most that could be
 achieved was a temporary reduction in the amount of foam.  To maintain the foam at
 an acceptable  level,  it was necessary to almost continuously add fresh antifoam
 agent.   Mandels and Weber [28] had the same problem in their work.  They eventually
 settled on  the procedure of adding small amounts (0.1$) of polyoxyethylene sorbitan
 monooleate  (Atlas Chemical Tween 80) to their medium.  Tween 80 is an emulsifying agent
 which  has the  effect  of "softening" foam and thereby making it more susceptible to
 the action  of  antifoam agents.  Their method was tried in the experiments described
 herein.  Although the foam problem was not eliminated, it was held to a workable level.
 Tween  80 (0«1$) was added to the medium in all runs in which cellulose was the
 substrate •

         Another serious problem encountered was that of the rise in pH during the
 initial period of growth.   This effect, caused by the deamination of amino acids,
 was also apparent in  runs  using a glucose substrate.  However, in runs in which
 glucose  was  the substrate,  the pH level began to drop when growth became very active-
 In runs  in  which cellulose  was the substrate, the rise in pH level had a much more
 serious  effect.   Growth almost ceased when the pH level reached 5.8 to 6.0.  It was
 necessary,  therefore,  during such runs to control the upper limit of pH at 5-0 by the
 automatic addition of acid.  Once active growth began, the pH dropped below 5.0
 and the  culture proceeded  to grow without any artificial control of pH.

         In Figures 10 and  11 are plotted change in pH, growth, and change in
 cellulose concentration during an 11- to 12-day period.  As the curves show, active
 growth  proceeded until the  pH dropped below 5-Oj  at which point the growth ceased
 and the  filter paper  activity* reached a maximum of 0.6 to 0.8 units.   The cessation
 of growth occurred after k-  to 5 days time.  In similar experiments, Mandels and
 Weber  [28] obtained a  filter paper activity of about 1.00 after 5-6 days.  However,
 they did not have  the  problem of growth inhibition during the initial pH rise,  and
 therefore did  not have  to add acid during this period.  From their data it seems
 that the pH  did  not drop below 3-0 until the 5"th or 6th day and filter paper activity
 had risen to its maximum.   The difference between the results obtained by them and
 these results  probably  was  a function of the difference in time before the pH dropped
below 3-0.    This difference in time was due to the fact that in the present experiments
 it  was necessary to add acid during the early period of cell growth.   The gradual
 decrease in total  dry weight of the cultures seems to be due mainly to autolysis
which occurred after growth ceased.   The effect of pH on enzyme activity was studied
by Mandels  and Weber  [28].  Their results show that the optimum pH is  4.8 and that
the enzyme  activity is  negligible at pH levels lower than 3-0.  It is  understandable,
    •1
      FP activity defined by Mandels and Weber [28] as the number of mg of reducing
sugar (as glucose) produced by 1 m? of cell-free culture liquid acting on 50 mg
(1x6 cm) strip of Whatman No. 1 filter paper in 1 ml of pH 4.8  0.05 M Na citrate
buffer at 50°C for 1 hour.

-------
                                                    139
     I   l    I   I    I   I   I    I   I    I   I   I    I
                     6       8
                     TIME, days
10      12
14
FIGURE 10.  GROWTH OF  I viride  ON GLUCOSE SUBSTRATE
           WITHOUT  pH CONTROL,RUN  1
                                              SW 101

-------
                     6      8      10


                    TIME,days
                                                14
FIGURE II.  GROWTH OF  T viride   WITHOUT  pH  CONTROL,


          RUN 2
                                              SW 102

-------
therefore, that growth of  T_. viride QM 6a would cease in a culture on a cellulose
substrate when the pH drops below 3-0.  The reason is that no carbohydrate source  is
available at pH levels lower than 3,  inasmuch as cellulose hydrolysis has come to
a standstill.


Experiment 3•  Cellulose Substrate with
pH Control

         The obvious question brought  out by the results obtained  in the previous
experiment is what would happen  if pH were controlled.  It is possible that with
the pH  controlled at the optimum for  enzyme activity, less enzyme would "be produced
because less would be needed inasmuch as it is at its maximum activity.  On the
other hand,  it is possible that  the rate of enzyme production is  related to growth
rate, and therefore more enzyme  will  be produced with the pH held at the optimum
for cellulase activity.  In this experiment, the aim was to determine the effect
of pH control on fungal growth and cellulase activity.  The pH of the fungal culture
was held at  5-0 by external control and automatic addition of acid and base.  Amount
of growth and change in cellulose concentration during the first  7 or 8 days are
shown in Figures 12 and 13•  As  would be expected, growth and cellulose degradation
both proceeded to a far greater  extent than in noncontrolled pH runs.  The most
interesting aspect, however, was the  level of enzyme activity achieved in the two
experimental runs.

         In run 1, the activity on filter paper reached a level of about 2.1 units
after 5 I/2 &&ys and then began  to drop off.  Plating of samples from the culture
indicated that a fungal contaminant had made its appearance•  It steadily increased
in number throughout the life of the  culture.  The enzyme activity level remained
constant at the maximum in all other  experimental runs, so it is highly probable
that this observed decrease was  due to the presence of the contaminating fungus in
the culture.

         Results obtained in run  2 were similar to those of run 1.  The only major
difference was that the activity on filter paper continued to rise after day 6
and reached a higher maximum level than that of run 1.  After 9 days the filter paper
activity reached a level of 2.86 units.

         These results indicate that the rate of enzype production tends to be growth
associated when T. viride QM 6a  is grown on a cellulose substrate.


Experiment k.  Isolation of Cell Growth
and Enzyme Production

         The previous results demonstrated that one of the limiting factors in the
rate of cellulase production by  T- viride QM 6a was the slow rate of growth of the
fungus  on cellulose substrates.  In the first and second runs of the fourth experiment
an attempt was made to increase the overall rate of enzyme production by accelerating
the initial growth stage of the fungus.  A comparison of the results obtained in the
first experiment with those of run 2 of the third experiment indicates the existence
of a major difference between the growth rate of a culture growing on glucose and
that of one growing on cellulose.  Growth was complete in JO hours when the fungus
was grown on glucose; whereas,  four or five days were required when the fungus was
cultured on a cellulose substrate.  (Cellulose substrate depletion was assumed
to have occurred when the total dry weight equaled 50$ of the original substrate
concentration.)  A major time advantage could be achieved if this difference in
growth  rate could be put to use.

        Runs 1 and 2 of the fourth experiment were carried out in the following
manner:  In the initial phase the fungus was cultured on glucose as in run 1.  At
the point at which glucose became depleted,  sterile cellulose (Solka floe  SW ^0)
was added aseptically to the culture liquid to bring the concentration of  cellulose
to about 1$.   At the same time,  a fresh supply of nutrients (in the same amounts as
supplied previously) was added to the culture to replace the depleted nutrients.
Dry weight and filter paper activity were then monitored periodically.  Throughout the
run the pH was held at 5-0-  The results are plotted in Figures l4 and 15.   In both

-------
1U2
       3.0
                                                - 14.0
                         4       6
                          TIME, days
10
         FIGURE 12. GROWTH  OF T. viride  ON CELLULOSE
                   SUBSTRATE WITH  pH CONTROL, RUN 1

                                                 SW 103

-------
                                                   143
3.0
                                         - 14.0
                  4       6
                  TIME,days
10
  FIGURE  13.  GROWTH  OF T. viride ON  CELLULOSE
             SUBSTRATE  WITH  pH  CONTROL, RUN  2
                                         SW 104

-------
%'NOIlVaiN30NOO  3500019
                                                      m
                                                 ID
                                                 a:
                                                 o
                                                 o:
                                                 o
                                                 o



                                                  Q.
                                                 t:

                                                 *


                                                 en
                                                 UJ

                                                 S3
                                                 a:

                                                 fc
                                                 QD

                                                 (/)


                                                 UJ
                                                 (/)

                                                 3

                                                 _i
                                                 _i
                                                 UJ
                                                 o

                                                 a

                                                 <

                                                 UJ
                                                 o>
                                                 o
                                                 o
                                                 o

                                                 o
                                                 UJ
                                                 a:
                                                 3
                                                 O

-------
'NOIlVdlN30NOD  3SOOfn9
q
cvi
                      u>
                      d
7uu/6uu'iH9l3/\A AdQ  1V101
                                               OJ
                                               o
                                               o:
                                               o
                                               o
                                               x
                                                a.

                                               I
                                               H
                                               UJ

                                               !5
                                               a:
                                               CD

                                               CO
                                               UJ
                                               en
                                               o
                                               UJ
                                               o

                                               a
                                               UJ
                                               co
                                               o
                                               o
                                               ID
                                               in

                                               UJ
                                               a:
                                               D
                                               O
                                               u.
                                                    (O

-------
runs two days passed "before signs of any cellulase activity appeared in the culture
liquid.  Following this  lag, the cellulase activity rose sharply to high levels.
During the 2-day lag period during which the culture was adapting to the cellulose
substrate, the carton source available to the culture was almost completely depleted.
It  is likely that autolysis of the fungal mycelium occurred to a significant extent
during this period, thus accounting for the decrease in total dry weight during the
lag period.  The advantage of rapid cell growth during the initial period was out-
weighed "by the added time used for the long lag period.


Summary of Experimental Results

        In table 68 are summarized the results obtained in the experimental work
thus far.  The results show that cellulase enzyme production is favored when the pH
level is at 5-0 (optimum pH for enzyme activity).  It is inhibited at the low pH
values (2.5 to 3-0) which occur in the latter stages of growth without pH control.
These results suggest that the production of enzyme by T. viride QM 6a is not related
to  the low pH but rather to the rate of growth of the fungus, which is best at pH
5-0.

        The results of the fifth experiment demonstrated that the cellulase enzyme
is  produced more effectively by first growing the fungus rapidly on glucose and
then adding cellulose to induce enzyme synthesis.  However, any advantage gained
is  offset by the long lag phase which takes place before cellulase begins to be
metabolized.  Therefore, some additional experiments should be done to explore
possible techniques to reduce the lag period.

        A comparison of this work with that of previous work of Mandels and Weber
[28] shows that the enzyme production rate may be increased 150$ through pH
control.  By incorporating pH control with pre-culture on glucose,  a very substantial
reduction in the plant investment and processing cost could be obtained.
ECONOMIC ANALYSIS
Plant Design and Cost Analysis

        To determine in a very general way the economic feasibility of a process
involving the hydrolysis of paper wastes to glucose and subsequent production of
fungal protein on the glucose, a cost estimate was made for a process such as that
diagrammed in Figure 16.  The estimate is based on data for growth and hydrolysis
rates reported for T. viride QM 6a as reported by Mandels  and Weber [28] and by
Ghose and Kostick [26, 27J.  Apparently the enzyme complex synthesized by T. viride
brings about the most rapid saccharification of paper cellulose of any of the enzyme
complexes synthesized by any other organism reported thus far.
                                     TABLE 68

              ENZYME ACTIVITY IN RELATION TO SUBSTRATE AND pH CONTROL
Culture Conditions
l) Cellulose, no pH control
2) Cellulose, pH control @ 5-0
3) Glucose, cellulose, pH control @ 5-°
4) Mandels and Weber [28], no pH control
Enzyme
Activity
At 5 days
0.8
2-5
2.0
1.0
(FP unitsa)
Maximum
0.8 @ 5 days
2.85 @ 9 days
3.12 tf I'd Jays
1.86 (semi-
contimious )
             As defined by Mandels and Weber [28].

-------
        The cost estimate was prepared with the additional intention of relating
the proportion of capital and operating costs to individual steps in the process.
The following evaluation was developed according to a method outlined by Newton and
Aries [29].


Description of the Process Design Basis

        The raw material for the process is waste cellulose, and the end products
are a 5-3% glucose syrup and a mixture of fungal protein and residual cellulose.
The glucose solution can be used directly in a secondary fermentation of commercial
value or it may be recovered as pure glucose in an additional recovery and purification
operation.  The protein-cellulose mixture is envisioned as being suited for use as
an animal feed or feed supplement.

        The basic plant size chosen for the study is based on a daily waste cellulose
feed of 10 tons.  The amounts of products are estimated to be 18,300 Ib of glucose
(as 5-3% syrup) and 7°° Ib/day of dry fungal mycelium-cellulose mixture (80% mycelium).
It is envisioned that a plant of this type would be located within a short distance
of the source of the waste material.  The refuse costs for transportation and rough
separation of the cellulosic waste material are not included.


General Process Description

        As illustrated in Figure 16, the process consists of the following main
steps:
    1.  Feed Preparation:  The nutrient medium is prepared in the medium
        supply tanks.

    2.  Cellulose Pretreatment:   The cellulose waste as received is reduced
        in size in a shredder, heat treated at 200°C, and then ground to
        approximately 50|a diameter particles.  The cellulose feed to the
        fermentor is taken off after the heating; the remainder is ground
        and fed to the hydrolysis vessel.

    3-  Microbial Growth and Enzyme Production:  In this major step of the
        process, the growth of T. viride QJ4 6a on cellulose takes place with
        the simultaneous production of high concentrations of enzyme induced
        by the presence of cellulose.

    ^.  Separation of Enzyme Solution:  In this step the effluent from the
        fermentor is sent to a rotary drum filter (filter l) where the fungal
        mycelium and residual celluose are filtered off from the culture liquid
        containing the enzyme.  The solid mixture is sent to a dryer.

    5-  Cellulose Hydrolysis (Saccharification):   This is the most important
        step of the process.  Here the cellulose  enzyme solution produced in
        step 3 comes in contact  with pretreated cellulose waste and a  hydrolysis
        to glucose occurs.   Conditions remain aseptic here and growth  of the
        fungus is prevented by the elevated temperature (50°C).   According
        to available data [28],  the residence time of the cellulose in this
        step would be  ^0 hours for an approximately ^0% conversion.

    6.  Separation of  Glucose Solution:  The glucose solution is separated
        from the unhydrolyzed cellulose by filtration (filter 2).  The glucose
        solution (5-3$ syrup) is suitable  for use in a secondary fermentation
        or recovery as a solid product in  an auxiliary purification operation
        (not included  here).  The residual cellulose is dried,  reground,  and
        returned to the hydrolysis vessel.

-------
IkQ
                                                                                                    2      o
                                                                                                    N
                                                                                                    Z
                                                                                                    UJ
                                                                                                    O
                                                                                                    z
                                                                                                    O
                                                                                                    O
                                                                                                    o:
                                                                                                    o
UJ
5
UJ
                                                                                                        UJ
                                                                                                        cn
                                                                                                        o
                                                                                                        o
                                                                                                    
-------
Cost Factors

        A capital cost summary for the 10 ton/day plant is presented in Table 69.
Table 70 presents a list of costs on 3 bases:  cost per day of operation, cost per
ton of cellulose treated, and cost per pound of glucose produced.  In Table 71 are
listed the medium requirements in raw materials as based on a preliminary defined
medium [28].  A summary of fixed capital costs is shown in Table 72; it is broken
down into the relative costs of four major segments of the process.  Major equipment
is listed and specified in Table 73.  In Table 7^ are listed costs for a 10 ton/day
plant and a plant capable of handling 100 tons of cellulose per day, based on two
methods of scale-up.  Also in Table 7^ are listed the possible savings from several
potential process improvements.  It serves to indicate areas of research which
should be investigated in order to improve the cost outlook.

        It is not surprising that the estimates lead to the conclusion that a 10
ton/day plant is too small for economic operation, due primarily to costs of fixed
capital and labor.  An increase of size to 100 tons/day capacity [scale-up basis
(b)] effects a marked reduction in unit cost and apparently glucose could be produced
with a small net gain based on present market value, which assumes a value of $1^6
for the glucose produced per ton of cellulose converted.

        A further reduction in product cost appears possible if certain process
improvements can be effected as summarized in part 2 of Table 73-  The most
important areas of improvement lie in the elimination of the cellulose recycle and
increase in fermentation rate or enzyme production rate.  Grinding costs do not
appear to be excessive.  Elimination of the recycle and doubling of the enzyme
production rate per unit volume of equipment together could result in a potential
savings of $30 per ton of cellulose treated, and a net cost of $79 per ton.  Assuming
a glucose value of $1^6 per ton of cellulose, there is a potential profit of $67
per ton.  A further potential saving of importance, not assessed in Table ik, is the
possibility of using a low cost technical grade simplified medium.  A further savings
of $10-20 per ton may be possible.  Although some savings could be effected by re-
duction of grinding costs, it does not seem likely that this would be probable.

        While it is recognized that the above cost analysis is subject to considerable
uncertainty, it may be concluded that processing along these lines appears sufficiently
promising to warrant further study.

        The increased rate of enzyme production realized during the described exper-
imental work greatly enhances the economic outlook of the proposed process.  With
pH control, a rate of enzyme production equal to 2.5 times that assumed in the process
design appears possible.   This suggests a 60(f0 reduction in the fixed capital costs
involved in enzyme production (which comprises 52.6% of the total fixed capital
costs, as noted in Table 72.  In a 100 ton/day plant (see Table 7M> this would mean
a cost reduction of from $13 to $2^ per ton of cellulose processed depending on the
method of scale-up.  This results in a corresponding net gain of from $17 to $50 per
ton of cellulose processed.

-------
150
                                    TABLE 69

                  CAPITAL COSTS FOR A TEN-TON CELLULOSE PER DAY
                             "BIOFRACTIONATION" PLANT


Purchased Equipment	    $   563,275

Equipment Installation  	        108,530

Piping  	        200,000

Instrumentation	,  .        22,900

Insulation  	        28,000

Electrical  	        38,000

Building  	        200,000

Land and Yard Improvements	        60,000

Utilities	        lj-1,500
    Physical Plant  Cost	     1,262,205

Engineering and Construction  	       316,000
    Direct Plant Cost	     1,578,205

Contractor's Fee 	        79,000

Contingency	        516,000
    Fixed Capital	    $1,973,205

-------
                         TABLE 70

       MANUFACTURING COSTS FOR A TEN-TON CELLULOSE PER
               DAY "BIOFRACTIONATION" PLANT
                                                                      151
Item
Raw materials (medium)
Labor
Supervision
Maintenance
Plant Supplies
Utilities
Direct Manufacturing Cost
Payroll Overhead
Laboratory
Plant Overhead
Indirect Manufacturing Cost
Depreciation
Property Taxes
Insurance
Fixed Manufacturing Cost
Total Manufacturing Cost
$/day
$ 246.
475-
70.
270.
41.
2JO.
$1352.
72.
72.
240.
$ 384.
550.
110.
55-
$ 715.
$2431.
%
10.1
19.4
2.9
11.1
1.7
9-5
54.7
3.0
3-0
9-9
15-9
22.6
4.5
2-3
29.4
100.0
$/ton of
Cellulose






$133-



$ 38.



$ 72.
$243.
$/lb of
Glucose






$0.073



$0.021



$0.039
$0.133
aSteam 65$,  electricity 31$,  other

-------
152
                                     TABLE 71

                  COSTS FOR MEDIUM ON WHICH TO GROW T.  viride ON
                          COMMERCIAL SCALE (10 TONS/DAY)
Item
KH2P04
(NH4)2SG4
Urea
MgS04-7H20
CaCl2
FeS04 7H20
MnS04 H20
ZnS03 7H20
Peptone
NaOH (pH control)
It /day
686
Wo
103
103
103
1.72
0.511
0.48
175
20
cents /it
10
10
4.7
2.9
29
10
59
5
20
28
$/day
69
48
5
3
50
—
__
--
35
6
Plus 25% shipping, handling, storage, etc.
Total Raw Material Costs 246.
for 10 tons cellulose per day
                                    TABLE 72

               SUMMARY OF FIXED CAPITAL COSTS FOR A TEN-TON PER DAY
                            "BIOFRACTIONATION" PLANT
Item
1.
2.
3-
k.
Cellulose Pretreatment
Shredding
Heating
Grinding
Enzyme Production
Fermentation
Air & Medium Sterilization
Medium Supply System
Cellulose Hydrolysis
Cellulose Recycle and
Product Recovery
Filtration
Drying
Total
$ Cost
$ 219,000.
1,036,000.
2^5,000.
470,000.
$1,970,000.
*
11.1
52.6
12.4
23-9
100.0

-------
                           TABLE 73




MAJOR EQUIPMENT FOR A TEN-TON PER DAY "BIOFRACTIONATION" PLANT
                                                                       153
Item
Fermenters (4)
Hydrolysis vessel
Filter 1
Filter 2
Air filter
Shredder
Heater
Grinder
Dryer 1
Dryer 2
Heat exchanger 1
Heat exchanger 2
Heat exchanger 3
Heat exchanger 4
Air compressor
Medium supply tanks (2)
Fermenter motors (4)
Hydrolysis unit motor
Medium supply motors (2 )
Solids feeder
Screw conveyors (2)
Centrifugal pumps (3)
Size/Capacity
52,000 gal
69,400 gal
2k sq ft surface
90 sq ft surface
465 SCFM
1,000 Ib/hr
1,000 Ib/hr
1,800 Ib/hr
150 sq ft surface
1,270 sq ft surface
85 sq ft
50 sq ft
200 sq ft
30 sq ft
500 SCFM
10,000 gal
10 hp
20 hp
5 hp
1,800 Ib/hr
1,000 Ib/hr
50 gal/min
Uninstalled
Cost
$240,000.
67,500.
21,000.
37,000.
3,000.
10,000.
ik, 600.
25,000.
12,200.
58,000.
3,000.
2,1+00,
If, 500.
1,800.
10,500.
32, too.
4,200.
1,500.
1,500.
750.
10,400.
2,025.
Installed
Cost
$276,000.
77,6oo.
27,000.
48,000.
4,000.
12,500.
18,600.
31,250.
14,700.
70,000.
3,300.
2,640.
4,950.
1,980.
13,500.
36,900.
8,4oo.
3,000.
3,000.
850.
11,400.
2,235-

-------
                                    TABLE Jk


                   COST REDUCTIONS FROM PROCESS IMPROVEMENTS



1.  Manufacturing Cost vs. Plant Size — $ per ton cellulose


                                   10 tons/day     100 tons/day3     100 tons/dayc


    Raw Materials                       2k              2.k                zk
    Utilities                           23              23                23
    Labor Based Costs                   92               9                 9
    Fixed Capital Based Costs          10k              jk                kl

                    Total              2^3             130                97

    Interest on Investment (6%}         33              23                12
    Annual Processing Cost             276             153               109
    Glucose Value at $Q.08/lb          jk6             146               146
                    Net Gain          -130              -7               +37


2.  Process Improvements — Cost Reduction — $ per ton of cellulose

    (l)  Elimination of Grinding        12              10                 7
         (6% of fixed capital,
          18$ of utilities)

    (2)  Elimination of Cellulose
         Recycle — (Reprocessing)       35              27                19
         (38/0 of utilities, 19%
          of fixed capital)

    (3)  Double Fermentation Rate       27              19                11
         (20fo of fixed capital)
    ^ermenters and hydrolysis vessels scaled-up directly, remainder of plant
scaled-up according to 0.6 power rule.  Fixed Capital Cost = $l4,000,QOO.

     Entire plant scaled-up according to 0.6 power rule.  Fixed Capital Cost =
$8,000,000.

-------
                  VI.  INCINERATION - FYROLYSIS-COMBUSTION
INTRODUCTION

        The pyrolysis of organic matter under conditions of temperature and time
sufficient to convert that matter to gaseous products and the subsequent combustion
of those products is a modified form of incineration that we have named pyrolysis-
combustion.  The important difference from conventional incineration is that the
processes of gaseous fuel formation and its combustion are separated in time and
space.  This permits a great deal more flexibility during the process of burning an
organic material even when the only objective is the disposal of a solid waste.
Moreover, the process can be designed to use the organic material for the production
of heat and power and for the production of chemicals of commercial value.  Solids,
suspensions, or solutions can be utilized as the raw material; therefore, a wide
range of domestic, industrial, agricultural, commercial, and special solid wastes
can be accommodated.

        As described in the Second Annual Report [l] on this project, the research
work which serves as a basis for the pyrolysis-combustion process was carried out
using a 50^ aqueous solution of the organic matter dissolved during the pulping of
wood with sodium hydroxide and sodium sulfide — known in the industry as kraft black
liquor.  However, it was recognized that the process should be generally applicable
to organic matter and specifically applicable to most forms of solid wastes.  The
research and initial phases of design of a demonstration unit to establish the
technical and economic feasibility for using the process in the recovery cycle of
the kraft pulping process had been carried out when the decision was made to direct
the incineration phase of this project into high-temperature pyrolysis-combustion.
The progress made during the past year is described in this report.


Rationale

        The rationale for developing the concept of pyrolysis-combustion for the
disposal or, more properly, utilization of solid wastes for the production of power
and ultimately for the production of chemicals was presented in the Second Annual
Report.  In order to achieve the maximum rates of gasification of the organic raw
material, the temperature used in pyrolysis should be the maximum that is practical.
As previously pointed out, this is particularly important in the steam-char reaction
in which carbon monoxide and hydrogen are produced.  For this reason the experimental
unit has "been designed to be operated at temperatures up to 1200°C in the pyrolysis
zone.  The maximum temperature that can be used will be limited by some factor such
as material from which the reactors are fabricated, the formation of a slag or smelt
that is undesirable, or, possibly, the occurrence of a reaction that would form an
undesirable end product.  To effect the heat transfer necessary for the evaporation
of water, a lower temperature pyrolysis zone was employed so that external heating
of a metal wall could "be used.  To attain the high final temperature specified, a
reactor using a high temperature, alkali-resistant ceramic has been designed and
constructed.  A gravity transfer system between these two units (a device for collec-
ting ash or slag if a smelting temperature is employed and a burner for flaming the
pyrolysis gases) has been provided.  Since solid wastes cover a spectrum of raw
materials and, indeed, as an area of study are considered to include the disposal
of solvents and solutions or suspensions of organic matter as well as solids, two
feed systems have been provided — one to accommodate pumpable fluids, the other for
conveyable solids.

        In the design of the pyrolysis-combustion process, particular attention has
been given to the avoidance of producing an air pollution problem which has plagued
conventional incineration processes.  The process has been specifically designed
with the objectives of eliminating the emission of malodorous products such as those
                                       155

-------
156
that have characterized modern kraft pulping recovery systems,  eliminating sulfur
dioxide emmission, or at least reducing it to a level well within the limit that is
contemplated as acceptable in the ambient air in the vicinity of the installation,
and eliminating emission of particulate material.  The gases produced will be used
to furnish the energy required to carry out the process;  excess can be converted to
power.  Chemical production can be an ultimate goal of the process which could be
of substantial importance in process economics.

        The experimental unit has been built to study the process on a continuous
basis and to obtain data to establish a reliable engineered system for processing
of organic solid wastes on a technically and economically feasible basis that will
satisfy the key considerations pertaining to public health and environmental impact.


Objectives

        The objectives of this study during the interim since the last report were
the major construction and shakedown of the experimental pyrolysis-combustion unit
in which the research and developmental work could be carried out to demonstrate the
process.  The objective in the next phase of the work is  to operate the unit to
demonstrate the technical feasibility of the process in the disposal of solid wastes.
Data obtained can then be used to provide information for design and economic evalua-
tion of the process.  As previously stated, the long-term objectives are the conversion
of organic matter to l)  usable energy, and 2)  commercially valuable products,  with
no organic residue, and with no or minimal (i.e., below established acceptable limits)
introduction of pollutants to air or water resulting from such processing.


PYROLYSIS -COMBUSTION EXEEEMEHTAL UNIT

        Construction of the pyrolys is-combustion experimental unit as an outdoor
structure has been completed as contemplated for initial operations.  Monitoring and
control equipment with a visual display indicating status of operating functions
have been installed on a panel which is housed in a control building.  Shakedown
procedures in which water has been introduced into the heated pyrolysis zones which
simulate the introduction of an aqueous solution or suspension have been carried
out to prove the reliability of the various pieces of equipment and to calibrate the
equipment with respect to temperature,  pressure, and flow parameters.  Testing and
calibration of the ancillary feeding, pyrolysis gas burning, air supply,  and control
equipment are proceeding satisfactorily and should be essentially completed in the
interim period covered by this report.


Pertinent Considerations in Construction
of the Experimental Unit

        In laboratory investigations of the pyrolysis of  solutions of organic material
having a high basic ash content, as, for example, draft black liquor, it was found
that temperatures on the order of 1,000°C should be maintained in order to  produce
simple fuels at maximum rates [30,31] with minimum concentrations of sulfur-containing
organic compounds.  However, at temperatures in excess of 750°C in the pyrolysis of
kraft black liquor, equipment fabricated from all but the most exotic alloys (corrosion
resistant) becomes prohibitively expensive.  Therefore, to supply the heat  required
for endothermic reactions and to vaporize water present in a wet feed,  indirect
heating by tr-° isfer through a metal wall was indicated.  Accordingly, to accommodate
these divergent needs for high rates of heat transfer and for high temperature under
highly corrosive conditions, it was concluded in early design considerations that at
least two stages should be used in the pyrolysis process  [32].

        In principle, the feed is dried in the first stage and pyrolysis is carried
out to the extent that a nonagglomerating, particulate solid is formed which can be
continuously fed to the second reactor.  Second-stage pyrolysis should be carried
out in a ceramic reactor that can be operated at temperatures up to 1,200°C.  Accord-
ingly, the second reactor was fabricated from a 3,^00°F,  high purity, 97$ tabular
alumina castable ceramic.  This material can withstand extreme temperature  conditions,

-------
                                                                                157


is resistant at elevated temperatures to an alkaline environment (specifically to
a smelt of sodium carbonate and sodium sulfide), and because of its very low iron
content, has a high resistance to carbon monoxide disintegration.  To minimize heat
losses in the second-stage reactor, two side walls are heated.  Since combustion of
pyrolysis gas would be used to provide the heat required in a full-scale application
of the process, it was decided to employ gas heating for all stages in the pilot
plant.  In initial studies, for reasons of uniformity in experimental design, natural
gas is being used.  However, by relatively simple modifications, the pyrolysis gas
could be used for this purpose.

        The low thermal conductivity of the ceramic materials used in the fabrica-
tion of the second reactor makes it impossible to reach the required high temperatures
by indirect heating.  Accordingly, it is planned to meter into the second-stage
reaction zone at the point of introduction of combustible gases and solids from the
first-stage reaction zone, an amount of air with which sufficient heat can be gen-
erated through exothermic reactions to maintain the temperature of the zone at the
desired level.  Since it is desirable to use a minimum amount of air to maintain
this temperature, an air preheater will be used.  In addition, a minor amount of
heat transfer through the heated ceramic wall will be provided by maintaining the
temperature of the heated side of the wall somewhat higher than the temperature in
the pyrolysis chamber.  It is anticipated that the oxygen in the admitted air will
be completely consumed within a restricted zone of the reactor.  Conditions beyond
this oxidation zone will again become reductive, and completion of the pyrolysis
reactions will take place.


Experimental Unit Construction

        The design of the experimental unit has been described in the Second Annual
Report and in Master's dissertation by Basu [33,3^]-  The unit consists of an outdoor
structure on a concrete pad.  A two-story, metal frame was erected on the pad to
support the first-stage pyrolysis unit and auxiliary equipment.  The accompanying
photograph (Figure 17) shows the unit completed as of April 1970-

        The major equipment items are the first- and second-stage pyrolysis reactors.
These may be considered as fixed pieces of equipment around which the auxiliary equip-
ment items can be arranged in various configurations to develop process designs most
suitable to the attainment of the objectives of this research.

        In initial studies, it is planned to use an equipment configuration in which
the feed can be either a solution pumped from a tank or a solid conveyed from a solid
wastes hopper.  The hopper is provided with an agitator to prevent bridging of material.
Solid feed will enter the bottom of the reactor just above the point at which pyrolysis
gas is recycled.  A schematic of the pyrolysis-combustion unit in the configuration
to be used initially in studying solid wastes is shown in Figure 18.


        First Stage.  The first-stage pyrolysis reactor (Figure 19), a cylindrical
vessel 8 in. in diameter and 6 ft in length, was fabricated from stainless steel
(type PH 15-7 MO) having high corrosion resistance to a reducing type environment
and a higher transition temperature than other types (3l6 or 321).   The top and
bottom of this reaction vessel are flanged and may be removed to accommodate various
feed and product removal configurations.   Five thermocouples were welded at equally-
spaced intervals from top to bottom of the reactor wall to measure reactor wall
temperatures.  The vessel is suspended in a gas-fired furnace built of two layers of
insulation brick and encased in a steel shell.  An annular heating space was provided
with two gas burners at the base to impart efficient cyclonic movement of the com-
bustion gases.  Thermocouples were placed in the annular space as sensors for the
temperature indicator — controllers which regulate the flow of gas to the two burners.
A stack is provided to discharge the combustion gases at a safe distance above the
top of the unit.

        In the present configuration,  pyrolysis gases and entrained solids are
removed from the top of the reactor and passed through a cyclone separator.   The gas
effluent from the top of the cyclone is fed to a hot-gas blower having specifications

-------
158
      I
                                                                                                              in
                                                                                                              en

CD
2
O
o
 I
CO
en


O
a:

a.
                                                                                                            UJ
                                                                                                            oc

-------
159
  (fl
  UJ
  o
  o
  (T
  Q.
  I
  Z
  D
  O
  I-
  cn
  ^
  03
  2
  O
  O
  I
  o
  cr

  a.

  u.
  o
  2 tO
  O UJ
     s
  o

  il 9
  2 _l
  o o
  O 
-------
l6o
          FIGURE 19.  FIRST-STAGE  PYROLYSIS  REACTOR

-------
for handling gases up to 1300°F.  The blower will discharge gas into the cone-shaped
bottom of the reactor through a tangential entry.  If solids build up in the reactor
and are not carried out in the top discharge, they can "be conveyed out of the "bottom
of the cone by way of a k in.-diameter pipe to a screw conveyor.  The screw conveyor
discharges to a vertical pipe which is common with the discharge from the cyclone
separator.


        Second Stage.  The gas stream containing the partially pyrolyzed solids is
charged to the top of the second-stage reactor (Figure 20).  This reactor was designed
to have a 6 ft vertical section joining a 6 ft horizontal section.  TTie vertical sec-
tion is 9 in. wide and 12 in. deep, whereas the horizontal section is 9 in. wide and
18 in. deep at the discharge end of the reactor.  The floor of the horizontal section
slopes approximately 1 in. per foot and in cross-section from either side to the center.
The discharge port in the floor of the furnace is a cast ceramic plug with a J in.-
"bore.  The side walls of the reactor are common to combustion chambers on either side
of the pyrolysls chamber.  The pyrolysis chamber was cast entirely of specially
selected alumina castable ceramic.  The other three walls of the combustion chambers
were constructed of a basic-chrome ceramic brick.  The top of the chambers and the
floors of the combustion chambers were cast, using the castable ceramic.  Two layers
of fire brick, a layer of insulating board, and lastly a steel housing completely
enclose these three chambers.  The reactor was built on a layer of fire tile which is
supported on a steel plate fastened to a combination concrete pier and steel stand.
An "ash collector" is provided to receive gases and solids or slag (smelt) discharged
from the port in the pyrolysis zone.

        Gas burners fire into the front end of each combustion chamber immediately
adjacent to the discharge end of the pyrolysis chamber.  The temperature of the com-
bustion chambers is controlled by the use of instrumentation identical to that used
for the first-stage pyrolysis reactor.  An interlocking system for supplying gas to
the burners, controlling temperature, and sensing the pilot flame of each burner has
been provided.

        Gases are discharged through the ash collector to a device for their combus-
tion.  A tank through which water can be recirculated and sprayed has been provided
for cooling the gas in order to study simple scrubbing operations.

        Appropriate sensing of temperatures, pressures, and gas flows is provided so
that accurate measurement of conditions in the unit can be made.  The instruments for
these controls, for control of gas and air to the gas burners, and switches for
energizing the blowers, pumps, and other electrical devices are assembled on a control
panel housed in an 8 ft x 12 ft building immediately adjacent to the unit.   Cabinets
have been supplied to house air blowers and the liquid feed system.


RESEARCH PROGRAM

        The plan for the study of pyrolysis-combustion involves the sequential
investigations of various types of solid wastes.  Thus, information gained in the
investigation of one type can be applied to and should facilitate the investigation
of each subsequent type selected for study.

        Since the ligno-carbohydrate type of material is the most abundant of all the
wastes in the solid wastes stream, the logical course of action is to select a typical
material from this category of wastes.  Secondly, the type of material selected for
the initial studies should pose no problems with respect to feeding it into the
reactor, since the development of a feeding device suitable for use with all types
of wastes is one of the continuing objectives of the research program.  Particulate
wood is a material which meets both of these criteria and it was selected for use in
the initial studies.   When satisfactory operation of the experimental unit is achieved
using wood the study of comminuted solid wastes supplied from a commercial operation
will be undertaken.

        Introduction of materials into the pyrolysis unit is considered a research
area to be investigated and will be given special attention.  Size, shape,  and
condition of particles will be an important aspect with regard to feeding and to
pyrolysis characteristics.

-------
162
       BLOCK INSULATION
       OREENCAST-97
       BASIC FIREBRICK
       6-26 INSULATING
       FIREBRICK
6-20 INSULATING
FIREBRICK
                                          INLET
                                          BLOCK v
DRY HESS HEAVY
DUTY FIREBRICK
                                                          BljOWOUT
                                                           DOORS
                      BLOWOUT DOOR
                         OBSERVATION      \  '
                           PORT     THERMOCOUPLE
                                       PORT
                                PYROLYSIS   CHAMBER

1
1
HH3"t-
sf ^
^ SMELT
SPOUT

                                               84"
                FIGURE  20.  SECOND-STAGE   PYROLYSIS  REACTOR

-------
                                                                               163
        The method of introduction of the rav material into the first pyrolysis zone
in initial studies will be in the nature of a bottom-feed type with material pneu-
matically conveyed in the reactor.  A simple change in this configuration can be
made by the addition of a stand-pipe of appropriate diameter and length, centrally
located in the reactor, and connected to the bottom outlet.  Then, as solids are
introduced and pyrolysis is effected, the partially pyrolyzed solids moving to the
top of the fluidized bed would overflow into the stand-pipe and be delivered to the
screw conveyor.  Gas would be removed from the top of the reactor to supply the
hot-gas blower.  That portion of the gas stream not recirculated by the blower, as
well as the separated solids, will be discharged from the cyclone and delivered with
the solids from the screw conveyor to the second pyrolysis stage.  A top,-feed con-
figuration could be provided by placing a baffle in the center of the reactor extending
a distance from the top.  One side of the reactor would then serve for introduction
of solids by free fall.  The bottom and other side of the reactor could be operated
to provide a moving-bed type pyrolysis with removal of gas taking place from the
reactor top and solids conveyed from the bottom.

        When solutions or light suspensions of solids are pumped into the reactor;
a top-feed, free-fall type of operation can be studied.  Furthermore, solutions or
suspensions can be introduced at the bottom or at an intermediate point in the reactor,
thus providing a fluidized, bed-type of pyrolysis.  Specialized equipment for handling
slurries would have to be provided.

        Ram feeding was considered as a technique which might be most generally
applicable and thus was incorporated in the original design.  This feeding mechanism
can be adapted to a screw feed or a belt feed simply by replacing the piston with
an appropriate device.  It also is possible that a gravity feed with entry through
a rotary feed located away from the high temperature zone of the reactor could be
devised.

        Clearly, a number of configurations of this equipment are possible.   As
experience is gained with the configuration initially used, needed changes will be
more clearly defined.  At appropriate times these changes can be made with relatively
minor rearrangements or additions to the basic equipment.

        The parameters to be studied in the operation of the experimental unit
include:

    1.  The physical condition (particle size, moisture content) of the feed.

    2.  The rate of feeding (ib/hr) which -will be a factor in establishing
        residence times in the two pyrolysis stages.

    J.  The mode of feeding.

    k.  The wall temperature of reactor 1 (initially 500°c).

    5.  The gas temperature in reactor 2 (initially 1000°C).

    6.  The rate of gas recycle.

    7-  The temperature of gas recycle.


        In planning the experimental program,  each of these variables will be
investigated systematically.

        Data will be obtained on composition of the pyrolysis products,  on heat
requirements,  and on the rates of pyrolysis.  Based upon the results, process designs
will be optimized and the most favorable operating conditions will be determined.
The optimized results will be verified.

        The experimental results can be used in developing the design of pilot- or
large-scale operations, and in making an economic analysis of the proposed process.

-------
        A specific part of the experimental program will invol/e the separation of
organic pyrolysis products on a scale large enough to permit a thorough investigation
of their chemical composition, of yield of major products of commercial significance,
and of processes that can be used for their purification.  Such a separation might
be effected following either the first- or second-stage pyrolysis.


ANALYTICAL MKTHODS

        Appropriate sampling of the pyrolysis products will be made at several
stations provided in the experimental unit.  In obtaining these samples the gases
will be cooled and condensable products will be collected.   The uncondensed gases
will be analyzed by the gas-solid chromatographic technique perfected in the labora-
tory studies  [31] in order to obtain the concentrations of components including:
hydrogen, carbon dioxide, carbon monoxide, ni'trogen, oxygen, methane, ethane,  ethylene,
propane, and propylene-  The condensed aqueous phase and any organic phase which is
separated will be analyzed by the system employing gas-liquid chromatography previously
described [52,35,36].  If sulfur compounds are present in either uncondensed gas or
condensed liquid phases these can be quantitatively analyzed for sulfur using this
system which involves dual detection of the stream eluting from the chromatograph
by fj-ame ioniaation and by microcoulometric titration.  This system using the latter
detector can also be used for the quantitative determination of chlorine in volatile
compounds.

        Instrumental methoas of analysis available to compliment gas chromatographic
analyses include infra-red, mass spectography, and nuclear magnetic resonance
spectrometry,  The chromatographic system used for preparing samples for IR and MS
analyses and various organic compounds identified in the pyrolysis products have
been described [35]-


LABORATORY-SCALE PYROLYSIS OF SOLID WASTES

        The laboratory apparatus employed in the pyrolysis of kraft black liquor [31]
has been modified to introduce a solid feed.  In order to simulate the continuous
pyrolysis of solid wastes with an appreciable moisture content, water can also be
introduced at a continuous rate.  This equipment can be heated to a temperature up
to 1200°C and thus can be used to study the "steady state" pyrolysis characteristics
of any given solid waste material that will be studied in the continuous pyrolysis-
combustion experimental unit.  Preliminary results using wood appear to be similar
to those obtained using kraft black liquor.  Because of the turbulence occurring
under the conditions used in this work, however, particulate carbon was not retained
in the reactor (pyrolysis temperature was 1000°C and the water feed rate, 3 m^/min).
Accordingly, complete gasification of the wood was not studied in the preliminary
work, and conditions of pyrolysis will be altered to achieve this end.  Even so,
approximately two liters of gas per gram of wood introduced was produced.

-------
              VII.  WET OXIDATION OF ORGANIC SOLID WASTE MATERIALS


INTRODUCTION

        Wet oxidation has teen applied to organic wastes to meet a variety of indus-
trial disposal objectives.  Under severe oxidative conditions these wastes have "been
degraded to inert gases and water and only thermal and mechanical energy and inorganic
chemicals have been recovered; under less severe conditions these materials have been
converted to a more convenient form for physical disposal or utilization as fuel.
The recovery of organic chemicals for their chemical value under these conditions
has largely been neglected, and the question 6f their potential production from such
waste materials left unanswered.


Objectives

        The objectives of this phase of the overall research was the reduction of
the solid wastes stream under conditions of wet oxidation and the coincident recycling
of such wastes "back, to basic resources such as thermal energy and organic chemicals
of commercial utility.


Rationale

        The overall promise of wet oxidation as currently "being utilized for the
disposal of waste materials and the potential of this reaction for the production
of organic chemicals, as indicated by studies at this and other laboratories, pro-
vides the justification for this approach.  Furthermore, the utilization of solid
wastes for the production of organic chemicals under these conditions involves a
unique application of wet oxidation.


RESEARCH PROGRAM

        The research program was divided into three experimental phases concerned
rfith l)  basic reaction relationships, 2)  oxidation of organic solid wastes, and
3)  process design.


Ehase I — Determination of Basic Reaction Relationships

        The initial stage of this phase was devoted to modification and to design
and fabrication of equipment needed to accommodate a batch type, laboratory-scale
wet oxidation process.  The process is diagrammed in Figure 21.  Reactions were
carried out with hammermilled, air-dried white fir wood to establish basic reaction
relationships and to relate their results to those of earlier studies.  Reaction
parameters under consideration included time,  temperature, total and partial pressures,
solids concentration, and agitation.  Oxygen consumption and carbon dioxide — carbon
monoxide formation were followed by gas-solid chromatography and pressure-volume
relationships.   Components of the reaction mixture were separated by vacuum filtration
and subjected to physical and chemical analyses to establish material and energy
balances.  Dissolved organic chemical yields were determined by gas-solid and gas-
liquid chromatography.  Computerized data reduction systems were developed for the
determination of material and energy balances, reaction gas consumption and formation,
and dissolved organic chemical yields.
                                       165

-------
166
                                                         	.r	"—00-- ---_—
                                                                       U3K  3i»SN30NOO ^^"H   I
                                                                                      f"1  ~
                                                                                  .<.  w
                                                                                                       Ul
                                                                                                       o
                                                                                                       0?
                                                                                                       g
                                                                                                       g
                                                                                                       h-
                                                                                                       UJ
I
00
                                                                                                       CD
                                                                                                       Q
                                                                                                       O
                                                                                                       |
                                                                                                       UJ
                                                                                                       O
                                                                                                       CO

                                                                                                       cvi
                                                                                                       UJ
                                                                                                       D

-------
                                                                                                                               167
 a
 o
•H

£
•H
 !H
 O
 10

«
separat
 O
 1
 
-------
168
Phase II — Oxidation of Organic Solid Waste Materials

        In this phase the experimental techniques and results of phase I were to "be
applied to additional organic waste materials such as municipal garbage, agricultural
residues, sewage sludge, industrial effluents,  and combinations of these and other
wastes.  Reaction conditions would be optimized for the production of a particular
organic chemical or group of chemicals; and, in the latter stage of this phase,  con-
tinuous operation would be simulated by periodic introduction of additional material.


Phase III — Process Design

        In this phase the results of the preceding phases would be used in developing
possible process designs for the production, isolation, and utilization of organic
chemicals and for the utilization of thermal and mechanical energy from wet oxidation
of solid waste materials.


EXPERIMENTAL WORK

        During the period covered by this report, the research team was primarily
involved with the completion of the analytical and data reduction aspects of phase
I of the research program and with the modification of the overall reaction system
in preparation for the investigative stage of phase II.

        Reaction mixtures from phase I were subjected to extensive chemical and
physical analyses.  Preliminary material balance and gas consumption-formation data
given in the Second Annual Report were completely revised.  The revised data are
shown in Tables 75 and 76.Energy balances for these reactions, presented in Table
77, were established by calorimetric analyses of the residual solids and nonvolatile
dissolved solids and by gas chromatographic analyses of the volatile dissolved solids
and off-gases.  Dissolved organic chemical yields, described in Table 78, were
determined by gas-solid chromatography of the volatile dissolved solids and by gas-
liquid chromatography of the nonvolatile dissolved solids following freeze drying
and silylation.  In addition, four FORTRAN IV computer programs were written for the
reduction of raw reaction and analytical data to the above material and energy
balance, gas consumption-formation, and organic chemical yield information.

        Upon completion of the phase I analytical activities some modifications of
the reaction system were made.  These included:  a)  installation of a Honeywell
pneumatic stem positioner on the back-pressure control valve to allow automatic
control of total reaction pressure; b)  installation of a third bank of air cylinders
to enlarge compressed air storage; c)  installation of a Foxboro 3-pen pressure re-
corder on the air storage system to provide continuous monitoring of air consumption;
d)  addition of a third turbine blade to the agitator to promote greater mixing
action; and, e)  installation of single stage regulator to provide constant input
air pressure to the reactor.

        As indicated previously, intermediate levels of degradation of waste materials
is a primary concern in this study because they control both the quality and quantity
of potential organic chemical production.  Results from phase I reactions indicate
that maximum dissolved solids yield, ~$6% of total carbon input, occurred at 200°C
and 2 cu ft/min air input.  Residual solids yields decreased and volatilized carbon
yields increased with temperature increase; dissolved solids yields increased with
temperature to maxima at l80c to 200°C and then decreased.

        Mechanistically these results suggest that there are two major steps in the
degradation reaction, namely hydrolysis and oxidation, and that oxidation is the
rate limiting step.  At l60°C, hydrolysis prevails as indicated by the low volatilized
carbon yields and oxygen consumption; at 220°C oxidation has substantially increased
as shown by the higher volatilized carbon yields and oxygen consumption and by the
lower dissolved solids yields.

-------
                                                                               169
        Individual organic chemical yields, primarily hydrolytic or oxidative
degradation products of the component pentose and hexose polymers of wood, show
varying trends.  Yields of aldose monomers, such as glucose, mannose, and xylose,
are high at 160° to l80°C but drop off sharply with further increase in temperature.
At 220°C yields of the low carbon number aliphatic acids, such as acetic and formic,
are dominant.  These results coupled with the residual solids and dissolved solids
yields indicates that the oxidation step involves the dissolved solids rather than
the residual.

        In short, organic chemical production under the conditions of phase I
reactions occurred at moderate temperatures, namely, l80° to 2008C.  Higher temper-
atures would undoubtedly increase total solids reduction and, in addition, cause
conversion of an increasingly larger amount of dissolved organic solids to acetic
acid and inert gases.

-------
170

fluent
H
d
0
•H
O
a





a
3
a

c




Volatilized
Solids
•d
cu co
r ^
rH -H
O H
M O
Kl W
P


1-3
•rH r-l
CO O


S
%

3
CO
ndition
0
o
g
•rH
•P
cd
Reaction
r-t^d
-p p M
£ s
Total
Carbon
g
,rO
(H CO
EH o
CO
H a
a o
-P ,Q bD
EH co
O
H M
£ o
CO
1-1 d
cd O
•P ,Q ho
8 Sj
H co
EH O
CO
•rH O C
<; r-l o
fn Cd
•H -H
Cd CO
•P hD
O -H
•P CO
I-
rH
CU
ojO-4- H ir\ co c— oo vo -=)-
C-yD rH H ITNVOCO rT\t~-VD
l^s OJ f^N HA K*X -^" ^O N^v
u"\ ON OJ ON ex) O •— 1 ^"N ^N -^}~
MD l^N rn -cj- ON C — C— *-O CO KN
^j- ^- L/N LT\ C\J LTV _zf KN CM N~N
[A-d-J- tr\ H (M^>^ r^-^-
ONONUA-* N~\-ct- H >- C— MD
H r-l r-l H H
V£>OOE~-COCO Hr— COCO-d-
OJKNHCMOCOHr-ICOOJ
rHHHr-li-l HH H
1£O SI 9*S 1
OJOJCMCMHi-ICMHr-ICM
OOOOOOJOOOO
C— C~[— t— C— C— C— C— t— C—
Hi-IHi-IHHHrHrHH
§OOOOOOOOO
OOOOOOOOO
^-^•J-^.J-J-J-J-^J-
OJHOJrHHOJrHHOJH
OOOOOOOOOO
LTN W\ tTX LT\ CO ^"^ ^^ LP* LTN LT\
HHHi-li-li-lHi-li-IH
C\J CVJCOCO ONVOMDC— t— C^-
S OOOOOOOOO
VOCOCOOOOCMOJCM
HHi-IHOJOJCVJOJCMCM
g
HHHHHHHHrHH
1 1 1 1 1 1 1 1 1 1
5S^^5>??SS
and vith
at tempera t
ho
                                                                                                              01
                                                                                                              0
                                                                                                              •d

                                                                                                              S
                                                                                                               o
                                                                                                              •H   •

                                                                                                              •P  S3

                                                                                                               o  o


                                                                                                               CD  -P


                                                                                                               *$

                                                                                                              H  -H

                                                                                                              pH  bO

                                                                                                              <  cd

                                                                                                             cd
                                                                                                                         co

                                                                                                                         01
                                                                                                                         o
                                                                                                                        •H

                                                                                                                        •a
                                                                                                                         s?
                                                                                                                        -p
                                                                                                                        In
 cu
-p

I
       CO

       o
       CO
       a
       o

       €
                                                                                                                         8      S
                                                                                                                                S-i

                                                                                                                               tH
 (U
-p
       3
       03
       O
      o
                                                                                                                                      §
                                                                                                                                      o

                                                                                                                                      •8
       x

       3
       •d

       0
       o

       •8
       OJ
       o


       a
 I

-------
                                                                                                                      171
X  «!„




1
•P
o
fe
to
a






a
o
•H
u
§
0
o
M
^




§
<§>£
O CS bD
~O"r-i
°£
a
0 M
°8
-5.^
o
o
O bD
O
a
bO O
Q P
O !H
>"
8^
CQ
•
w
C
O bD
9,0
O H
~"c\r~bD
8
w
0 bD

bD
8S
<£
w o
OH
«S
O
s
ft
o
a
o
H
o
w
0 hD
ft
O
3
ft M
o
Reaction
Number
O^O\C—HCT\,l/N(0,Lr\^J--^-
rOiOOJOJ-4-irNHVDt—
OOtOOJOJNAOJrOrACM
l/>
ONAhT\-=)-VD^DCOJ- HH
mN^-d-OD-4-^D ONl^N
C\J H Ot^ODJ- LA_* ir\M3
HHOJ-^-CQl/NCQHU'NCO
i-IOONrHOOJOlH
H rH H H H H rH
KAOC--^-C-HHKN^DCO
t-[~O^QCQMDHK>OJLPv
rH HVD-*l?\t-t-[r-ON^O
IT\^- t— O O.CO UAt^-^J-MD
M3H^DOJOJJ--^-OtAl^
OJCMOt^OJO\N^l^rAOJ
rH M H rH H OJ H
C— J- OJ K^-d- a\VQ-*CO-3-
_^- LA-^--d- CT\l^\l/NO t^l/N
HH^-^-L^VO'vO^DC— ^^
1/NrH t^O\C\JVO KN-*COCO
HcOOJU'Nr-OJ^Q^OJ^O
H i-H^-VDCO C— CO OO CO CO
ITNhOi^CO-^CO O H O ^
OJ ^T\CO-^-CO-^--d-VO Ln
OJHO\VDCMVOCJWCOO
H H H H H H
O\-4MDOJVDVD U^-d-VO OA
^t-VDOJ^-CMajN^LA^tH
OsO  LPk
                                                                                           P.H
                                                                                           O  M
                                                                                           O  S3

-------
172
















•g
i-rl
rH
H

.3
-p
o
(d












d
0
•H
•P
O
OJ














 O
rH
rH^rH
oj ""o cd cd
-P *H qj o
_Q w hij i
EH (U AS
K
M
M „ g
a gj H
•H 3--^.
HJ H H
cd cd cd
b I> o
X
i-H
c^ jd cd cd
e^'S^i
«
hfl
Mcd 8
•H p *~^^
+= rH H
cd ed cd
cu f> o
W i
rH
rH cd t-H
Cd -rH -P Cd
O *|H CJ '
EH d W AS
H



M
hDtd 8

V> H rH
cd cd cd
0) |> o

J3
*g
S
O rH N™\ -d" C*~ ^D J" OO CO O
i — 1 LfS f^ rH VO ^*O CM -^" CO OJ
rAVQVD-=J- H fO ON D— -sh ON
K~\CVJ fO\OJ LTvC^-_^'VO ONl/N

O rAVD H ir\rr\^}- ir\ ir\ c*-
rHNAU^OCO HCO O OJ
OJHOJt^OJOJ^OJ





O if\u~\ir\\f\u~\\s\ir\\r\ir\
-^ *4" -^" -^" -^~ -^* -4" *^J~ -^"
-^~ -3" -J" -^}~ -^d" -^J1 -^}~ -J" -^"


COCO H[— ONVOf'OvC— t^-Q
OJ N~\ ^t -^t -^ ~=t tc\ OJ f11 OJ



O^ O\ "^ t — rH O CO CO l-TS CO

i-HLT\OJ[>--d- H^OO-d-^O
vo H^O-^-ONOJ LTXCOC—
OjrrsOOJON^DOONVOO
rH rH rH rH i~i i — 1



CO CO -J" h<"\ VO O C^~ O*\ OJ LT\
VO l/\t>-ONO\COCOCOVO rH

rHrHrHrHrHrO\rArHrHrH
cocococococococococo







tAN^roroKN^^f^NM^N^rrx
S-C--C^t>-D^I>-C^t— C^- t-
-^t" -^" -^" -d" -d" r^~ -^" -^" -^" •^t"

i^ S
1 III 1 1 III 1
r-HHrHHHHrHrHi-IH
1 1 1 1 1 1 1 1 1 1
                                                                                                                        cd
                                                                                                                        •d
                                                                                                                        a)

                                                                                                                        3
                                                                                                                        ?!
                                                                                                                        o
                                                                                                                               £
                                                                                                                               o
                                                                                                                               •H

                                                                                                                               •a
                                                                                                                               •s
                                                                                                                                o
                                                                                                                               •H
                                                                                                                                fn
                                                                                                                               •P



                                                                                                                               I
       £
       ti
        0)
       •p
                                                                                                                                o
                                                                                                                               rH
                                                                                                                        cd      cd
                                                                                                                        O     O
                                                                                                                       cd     p
                                                                                                                                       Hi
                                                                                                                                       u
                                                                                                                                       cd
 w
 CD      w
 u      cd      o

S     M    3
 cd     id      PJ
        d      oj
        cd      K
               M


 ,      -     *


*      '       B

 h      M     "S

rH     H      W
 cd      cd      cd
 o      o      Eb
•d
 
-------
                                                                                                                                           173
CO
t—
3
      K
      t-\
      fn
       P5












-d
o
o
60
g
^
H
CO
•H
^








O

1
rH 60
A
OA
A 60
6
CO
H 60
3
KA
A 60
ci
OJ
A u
6
3
H
H 60
6
3

LTN
H 60
cS
-d-
A 60
6
1
H bQ
6
>0
r^ 60
i


r^J
f^
3
0
Pi
E
0
o



H -P
to i i

t- -p
UA | |
H
CO -P -p -P


f-i
OJ -P KA
H VO 1

rH OJ UA
rH

^
KA OJ -d- -P
H



UA OJ O
KA rH O 1
H H
3 ^ SI ,
H
OA VO CO -p
CO OJ VO

OJ -d" CU P
O OJ VO
H

TZ) CU


o o> <; ,3
-
OJ J- CU UA .d-


VO ON H VO VQ H
rH UA KA ^fS -d"



^
P H O UA O -d-
ON -d- -d- -d- u~\

^
P ON KA -d- CO OA
-d- KA CO -d- -d-

KA ON t— H C— H
H CM OJ H CO
rH
P UA CO P VO CO
OJ OJ rH VD
•d
•H

•H -H <£
O V
•a! H 
-------
                                  VIII.   SUMMARY


INTRODUCTION

        Progress is reported for the latter months of the third year and all of the
fourth year of the research project entitled "Comprehensive Studies of Solid Wastes
Management" being conducted as a multidisclplinary study of the planning, economics,
operations research, public health, and technological aspects of the solid wastes
problem.

        In the introduction it was pointed out that the need for studies such as
herein reported is the natural outgrowth of a traditional American unconcern for the
conservation of resources and an unconscious indifference to "the environment."
During the period covered by the report  herein presented, several changes occurred
relative to the need for study.  On the  national scene, citizens tended to group
solid wastes with air and water problems into a single category of insult which defiles
the total environment.  Because of the concern for the total environment, the tendency
was to ascribe to solid wastes a higher  degree of importance than it merited as far
as damage to the "ecosystem" is concerned.

        The distinction was brought out  between the two concepts effect of man on the
environment and the effects of the environment on man.  In one respect the distinction
is obvious from the titles.The practical implications of the two differ.  While
the public has become more concerned over the effect of man on the environment, most
public agencies have been more practical and have given first priority to the effect
of the environment on man.

        Based on the analysis and rationale given in the section Need For Study the
authors of the report herein presented came to the conclusion that the need for action
resulting from the failure to give the problem of solid wastes management the atten-
tion it warranted until it reached crisis proportions makes more urgent the need for
study of jurisdictional, planning, economic, and systems management as a plan for
action, and generates a need for technological research aimed at recycling rather
than destroying resource residue.


FLAMING AND ECONOMIES

        During the period since the writing of the Second Annual Report, activities
concerned with the planning and economic aspects of the overall research were con-
centrated on refining and expanding the  scope of work already underway and of that
remaining to be accomplished.  These activities are clarified in the present report
by including in it a reformulation of detailed objectives and specific aims, and a
description of the substantive progress  made to date in this phase of the research-
Plans also are discussed for developing  a final set of objectives as well as means
of implementing them.

        After carefully examining the original plans of the research (cf. First and
Second Annual Reports), the following ten objectives were defined:

    1.  Development of structural models for studying waste generation and
        its relationship to waste generators.

    2.  Empirical estimation of waste quantities and development of functional
        boundaries for regional analysis.

    3.  Development of waste multipliers in terms of quantity and composition
        by detailed economic activity.

-------
                                                                               175
    k.  Survey of engineering methods of disposal to acquire information
        for use in making economic analyses.

    5.  Analysis of private and public expenditure in the solid waste
        industry with reference to a metropolitan area.

    6.  Application of a mathematical model for arriving at short-run
        solutions based on disposal by sanitary landfill.

    7-  Regional economic forecasts and projections of solid wastes
        generation through the use of input-output studies.

    8.  Consideration of technical changes and new methods of transfer
        and disposal in terms of the management of solid wastes in the
        future.

    9-  Definition of a systems analysis approach to solid wastes manage-
        ment.

   10.  Implementation of an optimum solution, recognizing efficiency and
        equity criteria with reference to metropolitan or regional planning
        for urban services.


        In conducting the survey of current and proposed engineering methods (objec-
tive No. k in the preceding list), available systems of solid wastes disposal were
divided into "current" and "proposed" or "experimental."  A brief review was made of
the engineering aspects as a preliminary step leading to cost comparisons between
the systems.  As a part of this phase of the work, a detailed method for analyzing
costs of landfill was developed, which was based on the multiple regression technique.
Brief accounts were given of the experimental systems, compaction, wet oxidation,
anaerobic digestion,  and biological fractionation.  The purpose of the comparisons
and analyses was to obtain the information needed in arriving at alternative feasible
bases for selecting an optimum solution.

        Substantial progress has been made in fulfilling the objective "analysis of
private and public expenditures in a metropolitan region by the solid waste industry"
(item 5 in the list of objectives).  As a part of this objective, a procedure was
established for estimating waste generation in a given study region through use of
waste multipliers and waste sources (cf. Second Annual Report).  However, awaiting
detailed examination were questions on the composition of wastes, private and public
expenditures on various functions of waste management, and the implications of pro-
posed solutions for future management of wastes.  With a view to recognizing and
stipulating all of these planning and economic considerations, a workable study
region, namely, the Oakland metropolitan area, was defined on a functional basis for
the delineation of various issues and possible methods of analysis.  The Oakland
metropolitan area includes seven cities and nearby urban areas, and has a population
of about 800,000 people.  As reported herein,  the Oakland area study was started by
establishing a need for public concern, defining a functional boundary for cost
analysis and a need for cost data to emphasize private and public operations and the
economies of scale as well as other purely economic considerations.  The empirical
problems encountered in collecting data and setting up an accounting framework are
recounted.

        The application of the mathematical model for obtaining short-run solutions
based on a sanitary landfill reflects an application of the network flow model (cf.
Second Annual Report) developed to solve a part of the waste management problem.
Specifically, the nine-county San Francisco Bay area was chosen for the application
of the model.  The Bay area has about 116 points of waste generation and 7^- existing
and potential disposal sites.  The model uses  the branch-and-bound technique for
optimization.  As conceived and applied in the present study,  the model can be used
in choosing the locations of a specified number of sites to be made operational when
one or more of the existing sites is filled to capacity.  The problem of rerouting

-------
 176
the waste generating points to other sites is solved by the application of the network
flow model.  The application as described herein should be regarded as illustrative
of the uses and limitations of such mathematical models.  The results should not be
used at this stage for establishing policies.  Further refinement of the model by
way of relaxing the basic assumptions already is under way.

        To recapitulate briefly, the rationale of the planning and economics phase
of the comprehensive research is that some fraction of the solid wastes residue
must be returned to the earth.  This led to the recognition of landfill as constitu-
ting the single most important method of disposal, at least for the coming few years.
Recognizing landfill as the important disposal method has implications on land-use
planning.  Thus there is an urgent need to conduct feed-back studies between secular
land-use studies traditionally carried out by private and public planning bodies and
waste management studies of the type which constitute the subject of this report.
Moreover, refuse disposal already has been recognized as one of the major items for
regional or Metropolitan planning along with other urban services such as air pollu-
tion, regional parks, land transportation, and regional planning in general.  This
aspect has serious implications from the administrative, regulative, and managerial
points of view, which in waste management programs may in some instances be horizon-
tally aggregated with other similar urban services, chiefly to reduce unnecessary
multiplicity and/or conflicts in governing bodies.


OPERATIONS RESEARCH

        The work done by the Operations Research Group consisted of several aspects
including the following:  l)  development of a mathematical program to assist the
Planning and Economics Group in network flow analysis of the routing of solid wastes
in the nine-county San Francisco Bay area; 2)  development of a model for forecasting
solid waste loadings through the use of input-output technique for the nine-county
San Francisco Bay area; and 3)  development of optimal strategies in capacity ex-
pansion of disposal facilities under finite and infinite planning horizons.  The
first of the above three, viz. the development of a network flow model was fully
discussed in the section on Planning and Economics.  The remaining two are briefly
treated in the summary which follows:

        The input-output model developed for the nine-county San Francisco Bay area
consisted of 28 sectors.  The output forecasts were estimated for 1966, 1970, 197^,
and 1978 by these 28 sectors.  Utilizing the corresponding waste loadings by indi-
vidual sectors (estimated in the planning and economics studies), waste loading
forecasts were developed for the four time periods.  Although the original intention
was to augment the usual input-output model to include additional sectors corresponding
to waste industries, the augmentation of the industrial sectors was not complete
at this stage of the overall research; and consequently, the results of the model
are a first approximation.  Similarly, the forecasts of the exogenous sectors were
made for convenience and illustrative purposes and need further refinements.

        Development of optimal strategies in capacity expansion was discussed in
this report with reference to incineration facilities.  Assuming a given cost
structure that has two components, one corresponding to fixed cost, and the other a
variable cost component, the variation in incineration costs was studied under a
200-period finite planning horizon and an infinite planning horizon.  Since the
details of the mathematical derivations involved in the work were of purely theoretical
value, they were not included in this report.


ANAEROBIC DIGESTION

        Processing the garbage fraction of refuse through a conventional digester
has been practiced for years, in that a sizeable amount of kitchen garbage is ground
to the sewers each year by way of the home garbage disposal (grinder) unit.  The
concept that other organic fractions of refuse might also be reduced in volume and
stabilized in this manner is, therefore, but one step beyond current practice.  The
use of anaerobic digestion is especially attractive when considered as an adjunct to
the hydraulic transport of refuse.

-------
                                                                                177


        The laboratory studies herein reported were designed to:  l)  determine in
terms of reduction in volatile solids the efficiency of anaerobic digestion when
used to process the major individual organic constituents of the waste stream, namely
paper, wood, green garbage, and animal manure; 2)  ascertain the existence of any
inhibitory effects, if any, attending the digestion of the fractions named under the
preceding heading; 3)  arrive at practical levels for the key operating parameters;
and k)  assess the economic feasibility of the digestion of garbage alone and of the
entire organic component of refuse.  In the course of attaining these objectives,
the kinetics of solid waste digestion received special attention.
        In the experiments on the digestion of newspaper cellulose, 83$ of the total
cellulose in a mixture of 10$ newspaper and 90$ sewage sludge was destroyed with a
detention period of JO days.  About 55$ of the cellulose in the newspaper portion
of the mixture was digested.  With the proportion of newspapers stepped up to 20$,
73$ of "the total cellulose was destroyed, and 50$ of the newspaper cellulose.  In-
creasing the newspaper content of the mixture to 30$ resulted in a 63$ destruction
of the total cellulose, and 42$ of the newspaper cellulose.  The composition of the
gas from a digester receiving only raw sewage sludge was almost identical with that
of gas produced by digesters receiving newspaper cellulose.

        Grass clippings proved to be 73$ digestible.  The average destruction of
the cellulose in the grass clippings amounted to
        In experiments involving the digestion of manures, destruction of the volatile
solids in chicken manure was about three times that of the solids in steer manure.
Reduction in volume of the manures was minimal.  Destruction of manure total solids
was less than 15$.  The composition of gas produced in the digestion of manures was
quite like that of gas formed in the digestion of raw sewage sludge.

        The results of the experiments indicate that the addition of wood to a
digester would exert neither a chemically nor a physically adverse effect on the
culture.  Wood underwent very little decomposition in the digesters.  In essence,
the material acted as an inert material.  Perhaps the imposition of detention periods
longer than those applied in the present study might lead to the eventual decomposi-
tion of the wood.

        In experiments involving the digestion of a "synthetic" refuse (components
of the same nature and in same concentrations as found in municipal refuse), the
total solids reduction averaged 44$; and volatile solids reduction, 52$.   The
calculated amount of destruction of the cellulose in the "synthetic" refuse was 55$.
Gas production was about 56$ that of digester receiving raw sewage sludge.  No adverse
effects were noted with the C:N ratio adjusted to a high of 48:1.

        In a study on the kinetics of the destruction of cellulose in the "synthetic"
refuse,  minimum cell doubling time was calculated to be 5-8 days.  The "wash-out"
residence time for the digester cultures was found to be 7-8 days.


BIOFRACTIONATION

        ¥ork reported herein was concerned primarily with laboratory studies involving
the fungus Triehoderma viride QM 6a and directed toward improving the yield of the
enzyme cellulose, with a process design and economic evaluation of an enzymatic
saccharification process based on the fungus.  Laboratory results showed  that the
production of cellulose is favored when the pH level is at 5.0 and is inhibited at
pH levels of 2.5 to 3-0.  These results show that the rate of enzyme production is
a function of fungus growth.  The laboratory results also showed that cellulase
production is enhanced by first growing the fungus rapidly on glucose and then
introducing cellulose into the medium.

        In making an economic analysis of the process,  a basic plant and  process
design was drawn up.  The plant was based on a waste cellulose feed of 10-ton/day.
In the analysis, it was assumed that the material was delivered to the plant with
all necessary pretreatment having been accomplished.  Assigning a selling price of

-------
178
$0.08/lb for the glucose produced in the operation, the net cost of processing a
ton of cellulose in a 10-ton/day plant would be $!JOj and in a 100-ton/day plant,
from a cost of $7/ton to a profit of $57/ton, depending upon whether or not the
fermentors and hydrolysis vessel costs are scaled up directly with the remainder of
the plant scale up according to the 0.6 power rule, or the entire plant is scaled
up according to the 0.6 power rule.


HROLYSIS-COMBUSTION

        The construction phase of the Pyrolysis-Combustion portion of the overall
research program was completed during the past year.  Exploratory laboratory
experiments were run with the use of sawdust to obtain information needed to serve
as a guideline for experimentation involving the recently completed large-scale unit.
Parameters to be studied with the large-scale.unit are the physical condition of
the feed, rate of feeding, mode of feeding, temperature of the reactor wall, temper-
ature in the reactor, rate of gas recycle, and temperature of gas recycle,


WET OXIDATION

        In the studies on wet oxidation, the first phase of the research program
was completed.  It involved the determination of the basic reaction relationships
involved in the wet oxidation of raw white fir wood in the form of sawdust.  Hydrolysis
prevails when the process temperature is l60°C, as was indicated by the low volatilized
carbon yields and oxygen consumption.  At 220°C, oxidation substantially increased,
as was shown by the higher volatilized carbon yields and oxygen consumption and by
the lower dissolved solids yields.  Yields of aldose monomers (glucose, mannose,
xylose) were high at l608 to l80°C, but dropped off sharply with further increase
in temperature.  At 220*C, yields of the low carbon number aliphatic acids (e.g.,
acetic and formic acids) were dominant.  Results of the work indicate that the
oxidation step involves the dissolved rather than the residual solids.

-------
               APPENDICES
A.   Application  of Nigam's Algorithm

B.   Waste Generation in the Nine-County San Francisco
     Bay Area

C.   Remaining Capacity of Solid Waste Disposal Sites
     in the Nine-County San Francisco Bay Area
                   179

-------

-------
           APPENDIX A




APPLICATION OP NIGAM'S ALGORITHM
              181

-------

-------
                        APPLICATION OF HI GAM'S* ALGORITHM
        Let the current source set be  designated as K and the number of sources in
K be denoted by k.  Then K C P,  |K|  =  k, k  =g m <  |p| .  To start with K will be the
empty set and k = 0.  Let r = m-k.

    Step A.  The lower bound is  established for each of the remaining potential
             source locations by using the  formula
                               a

                       LB(h) =)   Min
                              '-'   ij&
                                        V h  e 7, h £ K
Step B.
             These lower bounds  are  then arranged in decreasing order as DL(.)
             along with the source location they correspond to, which is stored
             as JL(.).  The result is:
             Source Location
             Lower Bound
                           JL(1)
                           DL(1)   DL(2)
       JL(2)
          JL(P-R)

          DL(P-R)
    Step C.  Source location from the  list  in  (B) are cumulatively added to the
             set K to form new sets  IS(.) with their lower bounds VS(=) as follows:
      vs(.)
              K UJL(l)   K U JL(1)  UJL(2)
            DL(1)
DL(2)
KUJL(l) UJL(2)... (JJL(r-l)

           DL(r-l)
             Note that the set  IS(r-l)  consists of (m-l) potential source
             locations, and that the  lower bounds are still in decreasing
             order.

    Step D.  To find the rth column in  this IS(.) and VS(.) table, only one
             JL(.) source location is added at a time.  Now and then the set
             of established sources S is also added on and an actual evaluation
             of the costs involved is done — instead of just finding a lower
             bound.  Thus the sets considered for evaluation are:

                KllJL(l) UJL(2) U...  UJL(r-l)  UJL(r)  Us

                KUJL(l) UJL(2) U...  UjL(r-l)  UJL(r-l)  US
                K UJL(I)  UJL(2)  U...  UJL(r-i)  UJL(P-R)  Us

             In all these  sets the total number of sources is exactly as desired,
             and the intent  is to find an optimal solution rather than a feasible
             solution now.   The  source set having the lowest evaluation is chosen
             to fill the r*h column  in (C) and the evaluated value is used as
             the lower bound value.  This source set will be referred to as IIII
             and its evaluated value is VAL.
     A.  K.  Nigam,  Graduate Research Assistant in the Operations Research Group.
                                        185

-------
Step E.  For the sake of convenience,  the IS(.)  are rearranged so that they are
         now in increasing order,  and VAL is checked against the previous worst
         acceptable solution available.  The "previous worst acceptable solution"
        , refers to an upper bound such that any  source set with a higher
         evaluation is eliminated,  (in the previous goaround the worst solution
         for the source set is retained as IWOKDS(LY) with an evaluated value
         of VM).  In the first process of course,  there is no previous worst
         acceptable solution.  If VAL is less than VM then the present evaluation
         is better and therefore is kept.  If VAL  is greater than VM,  the
         previous worst acceptable solution is also regarded as the worst acceptable
         for this iteration, and is regarded as  IIII and VAL, respectively.

Step F.  All entries in IS(.) and VS(.) where the  VS(.) exceeds the best
         current evaluation VAL are dropped from consideration.

Step G.  The IS(.) and VS(.) are now fitted in their proper places in  the master
         storage map IWORDS(.) and VALUES(.), respectively.  The master storage
         map is kept so that VALUES(.) are in an increasing order.  In the first
         iteration this master storage map is empty and so IS(.) and VS(.) will
         be allowed to fill in the first available places.  In the later
         iterations they will be inserted at the proper places so that the increa-
         sing order of VALUES(.) is maintained.

Step H.  All VALUES(.) in the master storage map greater than VAL are  ignored so
         that the last entries in the map (indexed by LY) are IIII for the source
         set and VAL for the current evaluation.  These are taken as IWOKDS(LY)
         and VM for the next iteration as the worst possible cases from this
         iteration.

Step I.  If there is only one source set left in the master storage map then
         that is the answer being sought, and the  steps are terminated.  If
         there are more than one source sets, the  one with the greatest promise
         (and since they are arranged in increasing order it would be  the first
         one) is chosen to serve as K for the next iteration, beginning with step
         (A).

-------
                  APPENDIX B

WASTE GENERATION IN THE WINE-COUNTY SAN FRANCISCO
                   BAY AREA
                      185

-------

-------
                      APPENDIX B

Table B-l   Development of Waste Generating Points and
            Corresponding Waste Generation (1966)

Table B-2   Population Estimates for the Nine-County
            San Francisco Bay Area

Table B-3   Updating Solid Waste Data from 1966 to 1968
                          187

-------
188
                                                        TABLE B-l




                     DEVELOPMENT OF WASTE GENERATING POINTS AND CORRESPONDING WASTE  GENERATION (1966)
DSA Code
and Name
(1)
0101
Berkeley
0102
Oakland








0103
A lame da
0101*
Fremont

0105
Pleasanton

0106
Eastern
Alameda
0201
West Contra
Costa


















0202
Central
Contra Costa













020J
East
Contra Costa
0301
West Marin
Solid Wastes
Coming to
All Sites
in this DSA
(tons/day)
(2)
11*5

1,652









575

275


30


50


881




















1*32















215


9.6

Solid Wastes
Coming to
Effective
Sites in
this DSA
(tons/day)
(3)
95

1,602









225

275


30


50


881




















1+30















215


9-6

Population Section
in this DSA
(generating Point)
CO
Berkeley (part)
Oakland (part)
Oakland (part)
Albany
Emeryville
Piedmont
Hayward
San Leandro
Berkeley (part)
San Leandro Area
San Lorenzo
Castro Valley
Alameda

Fremont
Newark
Union City
Pleasanton
Upper Amador Valley
Pleasanton Area
Livermore
Livermore Area

El Cerrito
Hercules
Pinole
Richmond
San Pablo
Corte Madera
Belvedere
Tfburon
Mill Valley
Sausalito
Kensington

El Sobrante
San Quentin
Strawberry Alto


Homestead Valley


Marin City
Clayton
Concord
Martinez
Pleasant Hill
Walnut Creek
Port Chicago
West Pittsburgh
Lafayette
Pacheco
Alamo -Danville

Rodeo
Orinda
Moraga
Walnut Creek Area
Martinez Area
Antloch
Brentwood
Pittsburgh
Tamalpais Valley

Allocated
to
Generating
Point Code
Number
(5)
58
61
61
57
59
60
66
65
58
63
61*
65
62

69
68
67
70
70
70
71
71

>*5
1*0
1*1
1*1*
1*3
51
52
52
53
56
2/3 to 1»5
1/3 to 57
1*2
51*
1/3 to 51
1/5 to 55
1/3 to 55
2/3 to 53
1/6 to 51
1/6 to 55
55
27
51
29
52
55
28
26
56
50
1/2 to 5lt
1/2 to 55
59
38
57
53
29
25
2l*
26
1/2 to 1*8
1/2 to U6
Corresponding
Population
(6)
116,270
1,600
371*, 1*00
17,100
2,800
11,1*00
89,700
71,900
Moo
19,750
53,150
1*6,700
69,200

88,aoo
22,200
11,000
8,100
10,800
1,500
29,000
2,1*00

27,850
310
11,550
81,900
23,250
8,171
2,559
l*,978
11,783
6,1*11
6,1*50

21,000
1*,720
5,571


6,l*ll*


2, 111*
1,023
75,600
12,1*50
27,087
23,528
2,920
9,900
18,000
6,1*00
12,000

7,ll*0
ll*,850
9,800
29,772
6,670
25,050
2,1*15
20,900
3,200

Solid Wastes
Allocated
to this
Population
Section
(tons/day)
(7)
93-7
1-5
867-1
39.8
6.7
26.1*
207-7
166.0
11.3
1*5.8
123.0
108.2
225.0

199.8
50.1*
2l*.8
11-9
15-9
2.2
1*6.2
3-8

109 . 1+
1.2
1*5.5
520.7
90.8
32.1
10.0
19.5
1*6.2
25.0
16.9
8.1*
82.3
18.1*
7.3
7-3
7-5
16.7
l*.2
1*.2
8.2
1-7
126.3
20.8
1*5-5
38.8
4.8
16.5
30.5
10.7
10.1*
10.1*
12.1
21*. 7
16.5
1*9-7
11.0
106.9
11-5
96.8
1*.8
1*.8

-------
TABLE B-l (Continued)
                                                            189
DSA Code
and Name
(i)
0302
East Marin








01*01
Napa



0500
San Francisco











0601
Daly City


0602
South
San Francisco




0603
Pacific a
0601*
Central
San Mateo






0701
Palo Alto
0702
Mountain View
0703
Sunnyvale
0701*
Qilroy
0705
Los Qatos



Solid Wastes
Coming to
All Sites
in this DSA
(tons/day)
(2)
190. 1*









183




2,699












89



395






60

710








175

170

256

36

370




Solid Wastes
Coming to
Effective
Sites in
this DSA
(tons /day)
(3)
190.lt









183




2,580












89



395






60

7io








175

170

256

36

370




Population Section
in this DSA
CO
Fairfax
Larkspur
Novato
Ross
San Anselmo
San Rafael
Novato -Hamilton
North of San Rafael
Ross Valley-Kentfield

Calistoga
Napa
St. Helena
Yountville
Vallejo
Richmond
Marina -Pacific Heights
Central
South of Market
Western Addition
Twin Peaks -Buena Vista
South Van Ness
Potrero -Bayshore
Outer Mission
South Freeway -
Mt . Davidson
Lake Merced
Sunset
Daly City (part)
South San Francisco
(part)
Colma
South San Francisco
(part)
Daly City (part)
Brisbane
Milterae
San Bruno (part)
Burlingame (part)
Pacif ica
San Bruno ( part )
Burlingame (part)
Atherton
Belmont
Hillsborough
Half Moon Bay
Menlo Park
Redwood City
San Carlos
San Mateo
Palo Alto

Mountain View

Sunnyvale ( part )

Gilroy
Morgan Hill
Los Gatos (part)
Saratoga
Monte Sereno
Campbell (part)
San Jose (part)
Allocated
to
Generating
Point Code
Number
(5)
1*8
51
1*6
50
1*9
1*7
1*6
»*7
1/1* to 50
3/1* to 51
11
8
10
9
6
105
106
106
108
109
110
111
112
113
111*

115
116
72
76

73
76

72
75
78
77
79
74
77
79
81*
81
79
88
85
83
82
80
89

92

93

101*
103
97
95
96
98
100
Corresponding
Population
(6)
7,201
7,858
25,932
2,680
13,233
32,771
6,365
18,771*
10,956

1,895
30,231
3,1*82
2,372
65,826
90,51*0
67,100
93,295
28,260
52,815
63,025
^3,570
1*5,800
83,000
58,075

29,620
92,1*00
51*, 1*00
3,500

500
38,500

6,100
3,070
20,000
25,200
9,"*50
29,800
10,000
17,600
8,350
23,050
8,625
3,150
29,800
56,700
25,100
78,600
55,281*

!*8, 503

76,201

10,258
!*,566
ll*,289
21,91*1*
2,066
ll*,011
65,100
Solid Wastes
Allocated
to this
Population
Section
(tons/day)
(7)
10.9
11.0
39-3
i*.o
20.0
1*9.7
9-6
28.1*
1*.2
12-5
3-3
53-3
6.1
1*.2
116.1
312-5
831. 6
322.0
97-6
182.3
217-6
150.3
158.0
286.6
200.3

102.3
318.9
82.9
5-2

0-9
11*8.6

23-5
11.9
77-2
97-3
56. 5
1*1*. 9
15-1
1*9.8
23-7
61*. 7
21*. 5
9-0
81*. 1*
160.5
71.1
222.3
175-0

170.0

256.0

2l*.g
11.1
1*1*. 9
69.0
6.7
1*1*. 2
205.2

-------
190
                                                    TABLE B-l (Continued)
DSA Code
and Name
(1)
0706
Los Altos






0707
San Jose



0801
Vacaville
0802
Fairfield



0901
Healdstui-g

0902
Santa Rosa

3905
Western
Sonoma
090U
Southern
Sonoma



Solid Wastes
Coming to
All Sites
in this DSA
(tons/day)
(2)
570







1,005




78

127




65


181


1*70


140





Solid Wastes
Coming to
Effective
Sites in
this DSA
(tons/day)
(5)
570







1,005




78

122




65


179


1*6-5


140





Population Section
in this DSA
CO
Los Altos
Los Altos Hills
Cupertino
Santa Clara
San Jose (part)
Woods ids
Portola Valley
Alviso
San Jose (part)
Milpitas
Sunnyvale (part)
Los Gates (part)
Campbell (part)
Vacaville
Dixon
lairfield
Benlcia
Suisun City
Rio Vista
Cordelia
Healdsburg
Clove rdale
Geyserville
Santa Rosa
Fulton
Windsor
Jenner


Cotati
Petaluma
Rohnert Park
Sonoma
Sebastapol
Penngrove
Allocated
to
Generating
Point Code
Number
(5)
91
90
91*
99
100
86
87
101
100
102
95
97
98
2
1
5
5
5
7
k
20
22
21
17
18
19
25


15
12
15
15
16
14
Corresponding
Population
(6)
25,795
5,825
12,01*5
82,1*82
ll*,56l*
l*,156
5,570
1,512
280,158
19,85!*
8,625
1*,J12
7,210
15,21*5
5,71*8
25,007
6,612
5,861
5,168
602
5,280
5,260
500
1*1*, 010
500
500
767


1,1*00
20, 500
t*,l*90
5,725
5,260
502
Solid Wastes
Allocated
to this
Population
Section
(tons/day)
(7)
90.9
22.5
1*5-7
Jll*.9
51*. 8
15.8
20.5
5-1
879-5
62.5
27.0
15-5
22.7
62.6
15-1*
77-8
20.6
12.0
9-8
1.8
56.9
22.7
5-1*
175-0
2.0
2.0
1*6.5


5-8
81*. 8
18.5
15-5
15-5
2.1

-------
                      IABIE B-2
      POPULATION ESTIMATES FOR THE NINE-COUNTY
               SAN FRANCISCO BAY AREA
                                                                  191
County
Alameda
Contra Costs
Marin
Napa
San Francisco
San Mateo
Santa Clara
Solano
Sonoma
July 1966
Estimate61
1,045,000
528,400
195,300
76,800
737,300
539,300
925,000
162,600
182,900
July 1968
Estimate
1,150,000
604,998
231,999
87,000
759,909
600,000
1,033,000
180,003
222,002
Population
Ratio
(1968/1966)
1.10048
1.14496
1.18791
1.13281
1.03067
1.11255
1.11675
1.10701
1.21578
"California Population, 1967," Department of
Finance, State of California, Sacramento,
California, October 1967.


"Population and Labor Force Projections,"
Supplemental Report R & A-2; Association
of Bay Area Governments, Claremont Hotel,
Berkeley, California.

-------
192
                                          TABLE B-3




                         UPDATING SOLID WASOE DATA FROM 1966 TO 1968
Generating Point Name
(1)
Dixon
Vacaville
Fairfield and Suisun
Cordelia
Benicia
Vallejo
Rio Vista
Napa
Yountville
St. Helena
Calistoga
Petaluma
Sonoma
Penngrove
Cotati and Rohnert Park
Sebastapol
Santa Rosa
Fulton
East and West Windsor
Healdsburg
Geyserville
Cloverdale
Jenner
Brentwood
Antioch
Pittsburg
Clayton
Port Chicago
Martinez
Pacheco
Concord
Pleasant Hill
Walnut Creek
Alamo
Danville
Lafayette
Moraga
Orinda
Rodeo
Hercules
Pinole
El Sobrante
San Pablo
Richmond
El Cerrito
Novato
San Rafael
Fairfax
San Anselmo
Ross
Larks pur -Corte Madera
Tiburon -Belvedere
Mill Valley
San Quentin
Marln City
Sausalito
Albany
Berkeley
Emeryville
Generating
Point Code
Number
(2)
1
2
3
k
5
6
7
8
9
10
11
12
13
Ik
15
16
17
18
19
20
21
22
23
2k
25
26
27
28
29
30
31
32
33
5k
35
36
37
38
39
ko
41
42
1*3
kk
k5
k6
47
k8
k9
50
51
52
53
54
55
56
57
58
59
Solid Wastes
Produced
as of
July 66
(tons/day)
(3)
15 -k
62.6
89.8
1.8
20.6
116.1
9-8
53-3
4.2
6.1
3-3
84.8
15-3
2.1
24-3
13.5
175-0
2.0
2.0
36-9
3-4
22.7
46.3
11.3
106.9
113.3
1-7
4.8
31.8
10.7
126.3
45-3
88.5
10.4
10.4
30-3
16-5
24.7
12.1
1.2
^5-3
82.3
90.8
320-7
126.0
53-7
78.1
15-7
20.0
8.1
68.0
29-5
70.3
18.4
19-7
25.0
48.2
105.0
6-7
Ratio
CO
1.10701
1.10701
1-10701
1,10701
1.10701
1.10701
1.10701
1.13281
1.13281
1.13281
1.13281
1.21378
1.21378
1.21378
1.21378
1.21378
1.21378
1-21378
1.21378
1-21378
1.21378
1.21378
1.21378
1.14496
1-14496
1.14496
1-14496
1.14496
1-14496
1.14496
1 . 14496
1-14496
1.14496
1.14496
1 . 14496
1.14496
1.14496
1.14496
1.14496
1-14496
1.14496
1.14496
1 . l44g6
1.14496
1.14496
1.18791
1.18791
1.18791
1.18791
1.18791
1.18791
1.18791
1.18791
1-18791
1.18791
1.18791
1.10048
1.10048
1 . 10048
Solid Wastes
Produced
Estimated as
of July 68
(tons /day)
(5)
17-0
69-3
99.4
2.0
22.8
128.5
10-9
60.4
4.8
6-9
3-7
102.9
18.6
2-5
29-5
16.4
212.4
2.4
2.4
44.8
4.1
27-5
56.2
12.9
122.4
129-7
2.0
5-5
36.4
12.2
144.6
51-9
101.3
11-9
11-9
34-7
18.9
28.3
13-9
1.4
51-9
94.2
104.0
367-2
144-3
63-8
92.8
18.6
23-7
9-6
80.8
35-0
83-5
21-9
23-4
29-7
53-0
115-6
7-4

-------
                                                             193
TABLE B-3 (Continued)
Generating Point Name
(1)
Piedmont
Oakland
Alameda
San Leandro
San Lorenzo
Castro Valley
Hayward
Union City
Newark
Fremont
Pleasanton
Livermore
Daty City
Colma
Pacifica City
Brisbane
South San Francisco
San Bruno
Millbrae
Burlingame -Hillsborough
San Mateo
Be llmont
San Carlos
Redwood City
Atherton
Menlo Park
Woods ide
Portola Valley
Half Moon Bay
Palo Alto
Los Altos Hills
Los Altos
Mountain View
Sunnyvale
Cupertino
Sarato ga
Monte Sereno
Los OatoG
Campbell
Santa Clara
San Jose
Alviso
Milpitas
Morgan Hill
Gilroy
Richmond (SF)
Marina -Pacific Heights (SF)
Central (SF)
South of Market (SF)
Western Addition (SF)
Twin Peaks -Buena Vista (SF)
South Van Hess (SF)
Potrero -Bayshore (SF)
Outer Mission (SF)
South Freeway -Mt. Davidson (SF)
Lake Merced (SF)
Sunset (SF)
Generating
Point Code
Huniber
(2)
60
61
62
63
6k
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
Solid Wastes
Produced
as of
July 66
(tons/day)
(3)
26.4
868.4
225.0
211.8
123.0
108.2
207.7
24.8
50.4
199-8
JO.o
50.0
106.4
0.9
44.9
11.9
153-8
112.4
77-2
110.8
222.3
64.7
71.1
160.5
23.7
84.4
15.8
20.5
9-0
175-0
22.3
90.9
170.0
283.0
45-7
69.0
6-7
58.4
66.9
314-9
1139-5
5-1
62.3
11.1
24.9
312.5
231-6
322.0
97-6
182.3
217-6
150-3
158.0
286.6
200.3
102.3
318.9
Ratio
(4)
1.10048
1 . 10048
1.10048
1.10048
1.10048
1 . 10048
1 . 10048
1 . 10048
1 . 10048
1 . 10048
1 . 10048
1.10048
1.11255
1.11255
1.11255
1.11255
1.11255
1.11255
1.11255
1.11255
1-11255
1.11255
1-11255
1.11255
1.11255
1.11255
1.11255
1.11255
1.11255
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.11675
1.03067
1 . 03067
1.03067
1.03067
1.03067
1.03067
1.03067
1.03067
1.03067
1.03067
1.03067
1.03067
Solid Wastes
Produced
Estimated as
of July 68
(tons/day)
(5)
29-0
955-7
247-6
233-1
135-4
119-1
228.6
27-3
55-5
219-9
33-0
55-0
118.4
1.0
50.0
13-2
171-1
125.1
85-9
123-3
247-3
72.0
79-1
178-5
26.4
93-9
17-6
22.8
10.0
195-4
24.9
101-5
189.9
316.0
51.0
77-1
7-5
65.2
74.7
351-7
1272 . 5
5-7
69.6
12.4
27-8
322.1
238.7
331-9
100.6
187-9
224.3
154.9
162.9
295.4
206.4
105.4
328.8

-------

-------
                   APPENDIX C

REMAINING CAPACITY OF SOLID WASTE DISPOSAL SITES
    IN THE NINE-COUNTY SAN FRANCISCO BAY AREA
                       195

-------

-------
                                        TABIE C-l

           BKMAINING CAPACITY OF SOLID WASTE DISPOSAL SITES IN THE NINE-COUNTY
                                 SAN FRANCISCO BAY AREA
                                                                                               197
Site
Ho.
(1)
1

2
3
4

5

6

7
8

9
10
11

12
13
14
15
16

17
18
19
20
21
22
23
2k
25
26
27
28
29
30
31
32
33
34
35

36
37
38

39
40
41
42
43
44
45
46
47
48
49
Site Name and Identification
(2)
Ox Mountain Site EE in San Mateo
County
Benicia in Solano County
East of Milpitas -Customer Utility Site
Expansion of West Winton -Oakland
Scavenger Site (19)
Expansion of Durham Road-Oakland
Scavenger Site (21)
Expansion of Eastern Alameda County
Site (22)
Expansion of Acme Fill Site (26)
Expansion of West Contra Costa County
Site (27)
Expansion of Redwood Site (28)
Expansion of American Canyon Site (34)
Expansion of San Mateo Scavenger
Company Site (4l)
Expansion of Palo Alto Site (48)
Expansion of Newby Island Site (54)
Expansion of B and J Site (67)
Albany
Berkeley
Alameda
Davis Street -Oakland Scavenger Co.
San Leandro Marina
West Winton -Oakland Scavenger Co.
Turk Island Company
Durham Road -Oakland Scavenger Co-
Eastern Alameda County
Pleasanton
Pittsburg
Antioch
Acme Fill
West Contra Costa County
Redwood
San Quentin
Martinelli
Upper Valley
Yountville Veterans Home
Napa State Hospital
American Canyon
Del Santi
Islais Creek
Hunter's Point HSY
Leonetti
Sanitary Fill Co.
South San Francisco
Burlingame Rubbish
San Mateo Rubbish
San Mateo Scavenger Co.
South County Disposal District
Colma Rubbish
Daly City -Mussel Rock
Pacif ica
Half Moon Bay Rubbish
Pascedero
Palo Alto
Mountain View
Remaining
Capacity
as of 1966
(acre -feet)
(3)

-
-
-

-

-

-
-

-
-
-

-
-
-
-
1,550
120
100
4,300
670
i4,7oo
770
6,950
8,500
450
360
400
33,600
13,600
7,200
100
1,900
4oo
55
14
5,300
15
800
400
25
2,100
100
215
4oo
2,040
240
100
190
800
12
13
2,500
300
Average
Waste
Received
at Site
(tons/day)
CO

-
-
-

-

-

-
-

-
-
-

-
-
-
-
165
95
225
975
60
400
25
250
50
30
105
110
430
880
135
60
5
10
13
2
90
1
900
4o
10
1,600
280
100
100
400
200
15
79
60
3
5
175
90
Remaining
Capac ity
as of 1968
(acre -feet)
(5)

18, 500
15,000
1,000

15,000

15,000

15,000
15,000

15,000
15,000
15,000

15,000
15,000
15,000
15,000
1,383
24
-
3,311
609
14,295
745
6,696
8,449
420
254
288
33,164
12,708
7,063
39
1,895
390
42
12
5,209
14
-
359
15
479
-
114
299
1,635
37
85
110
739
9
8
2,323
209
NOTE:  Sites 1 through 14 are potential sites  vised in this  study.
       going to site at the moment.
As such there are no wastes

-------
198
                                     TAH£ C-l (Continued)
Site
No.
(1)
50
51
52

53
54


55

56
57
58
59
60
6l
62
63
64
65
66
67
68
69
70
71

72
73
74
Site Name and Identification
(2)
Sterlin Road Green Valley
Sunnyvale
Santa Clara
Edge water
Los Altos Ranch
Newby Island
Customer Utility
Story Road
Singleton Road
San Jose
Kastslde
Guadalupe
Morgan Hill
Moffett Field HAS
Pacheco Pass
Gilroy
Mare Island HSY
Travis AFB
Fairfield
Solano County
Dixon
B and J
Rio Vista
Sonoma
Petaluma
Clove rdale
Windsor
Guerneville
Occidental
Roblar
Remaining
Capacity
as of 1966
(acre-feet)
(3)
160
1,100
750
30
l,6oo
5,200
45
30
280
60
200
1,200
400
280
1,120
1,140
336
86
925
500
145
2,040
128
300
120
20
15
850
25
650
Average
Waste
Received
at Site
(tons/day)
(4)
80
250
70
200
300
500
55
160
4o
150
100
370
10
6
10
10
54
37
48
25
15
60
12
93
3
7
173
35
20
40
Remaining
Capacity
as of 1968
(acre -feet)
(5)
79
847
679
.
1,296
4,693

_
239

99
825
390
274
1,110
1,130
281
49
876
475
130
1,979
116
206
117
13
.
815
5
609

-------
                                    REFERENCES
 1.  Golueke, C. G. and P. H. McGauhey.  Comprehensive Studies  of  Solid Wastes
             Management.  Second Annual Report.SERL Report  No. 69-1-Berkeley:
             Sanit. Eng. Research Lab., Univ. of Calif.,  January 1969.

 2.  Peterson, R. J. and R. G. Glenn.  Report for the Des Moines Metropolitan
             Area — Collection and Disposal  of Solid Wastes.  Prepared by
             Hennington, Durham, and Richardson, Inc., and Engineering Firm of
             Veenstra and Kimm for Des Moines, Iowa.  May 19&9-

 3.  Calif. Dept. of Public Health.  A Systems Study of Solid Wastes Management
             in the Fresno Area.  California Integrated Solid Wastes Management
             Project.  Calif. State Dept. of Public Health, Berkeley, California.
             June 1968.

 4.  Golueke, C. G. and P. H. McGauhey.  Comprehensive Studies  of  Solid Wastes
             Management.  First Annual Report.SERL Report No. 67-7-Berkeley:
             Sanit. Eng. Research Lab., Univ. of Calif.,  May  1967.

 5.  An Analysis of Refuse Collection and Sanitary Landfill Disposal, SERL Bull.
             8^Berkeley:Sanit. Eng. Research Project, Univ. of Calif.,
             December 1952.

 6.  Committee on Municipal Refuse Practices.  "Municipal Incineration of Refuse."
             J. of the Sanitary Eng. Division, Proe. Am.  Soc. Civil Engrs.,  90
             (Part 1): 19, June 1964.

 7-  Fife and Boyer. "What Price Incineration Air Pollution Control," in
             Proceedings of the 1966 National Incinerator Conference, paper
             presented at the National Incinerator Conference,  New York,  N.  Y.,
             May 1-4, 1966.

 8.  Bump, R. L.  "The Use of Electrostatic  Precipitators for Incinerator Gas
             Cleaning in Europe," in Proceedings of the 1966  National Incinerator
             Conference, papers presented before the National Incinerator
             Conference, New York, N. Y., 1966.

 9.  Hawkes, G. R.  "Urban Compost Has No Future in Agriculture,"  Solid Wastes
             Management - Refuse Removal J., 12(5):22, May 19&9-

10.  Cannella, A. A.  "The Refuse Disposal Problem," Public Works,  92(2):ll6,
             February 1968.

11.  Black, R. J.  et.  al.   "The National Solid Wastes,  an Interim Report,"
             presented before the 1968 Annual Meeting of the  Institute for  Solid
             Wastes of the Am. Public Health Association, Miami Beach, Florida,
             October 1968.

12.  Samuelson, P. A.  "The Pure Theory of Public Expenditure," Review of
             Economics and Statistics, 36(4):387-389, November  1954.

13.  Head, J. H.  "Public Goods and Public Policy," Public Finances, _17(3):
             197-219, 1962.

14.  Musgrave, R. A.  The Theory of Public Finance, New York:   McGraw-Hill,  Co.,
             1959-
                                       199

-------
200
 References (Continued)


 15.   Baine,  J.  S.,  R.  E.  Caves,  and J.  Margolis.  Northern California's Water
              Industry, Resources for Future, Inc., Baltimore:  Johns Hopkins
              Press,  1966.

 16.   Ricardo, D.   The  Principles of Political Economy and Taxation, 1948.

 17.   McKean, R.  Public Spending, Hew York:  McGraw-Hill Co., 1968.

 18.   Novick, D.,  ed.  Program Budgeting, Cambridge, Mass.:  Harvard Univ.
              Press,  1965-

 19.   El-Shaieb, A.  M.   Optimal Activity Locations, Report No. 68-3-  Berkeley:
              Operations Research Center, Univ. of California, 1969.

 20.   Stern,  H.  L.  "Comprehensive Studies of Solid Wastes Management — Optimal
              Service Policy for Solid Waste Treatment Facility."  SERL Report
              No.  69-6.  Berkeley:  Sanit. Eng. Research Project, Univ. of
              California,  May 1969.

 21.   California State  Department of Public Health, "Status of Solid Waste
              Management," Vol. I, Interim Report, September 1968.

 22.   Dair, F. R.   "Time,  Crew Size, and Costs," Solid Wastes Management — Refuse
              Removal J.,  10(8):6-10, August 196?.

 2J.   Chan, D. B.   "Hydrolysis Rate of Cellulose in Anaerobic Fermentation."
              Doctoral Dissertation.  Berkeley:  Univ. of California, 1970.

 24.   Dubos,  R.  J.  "Influence of Environmental Conditions on the Activities of
              Cellulose Decomposition Bacteria in Soil."  Ecology, 9:12-12,
              September 1928.                                     ~

 25.   Sumner, J. B.  and G.  F. Somers.  Laboratory Experiments in Biological
              Chemistry.  New York:  Academic Press, 1949.

 2.6.   Ghose,  T.  K.  "Continuous Enzymatic Saccharification of Cellulose with
              Culture Filtrater of Trichoderma viride QM 6a," paper presented
              at the Third Inter. Ferment. Symposium, Rutgers University,
              3 September 1968.

 27.   Ghose,  T.  K. and J.  A. Kostick.  "Enzymatic Saccharification of Cellulose
              in Batch and Semi-continuous Agitated Systems," paper presented
              at the Cellulase Symposium, American Chemical Society Fall Meeting,
              Atlantic City, New Jersey, 11 September 1968.

 28.   Mandels, M.  and J. Weber.  "The Production of Cellulases for Specific
              Purposes," paper presented at the Cellulase Symposium, American
              Chemical Society Fall Meeting, Atlantic City, New Jersey,
              11 September 1968.

 29.   Newton, R. D.  and R. S. Aries.  Chemical Engineering Cost Estimation.
              New York:  McGraw-Hill Co., 1955-

 30.   Thomas, J. F., K. H. Jones, and D. L. Brink.  "A Mechanism to Explain
              the Production of Malodorous Product? in Kraft Recovery Furnaces,"
              Tapjji, 52(10):1873-1875, 1969.

 31.   Jones,  K. H.  "The Control of Malodors from Kraft Recovery Operations by
              Pyrolysis."  Ph.D. Dissertation.  Berkeley:  Univ. of California,
              February 1968.

-------
                                                                                                   201
                   References (Continued)
                   32.  Brink, D. L., J. F. Thomas, and K.  H. Jones.   "Malodorous  Products  from the
                                Combustion  of Kraft Black Liquor.  III.  A Rationale  for Controlling
                                Odors," Tappi, accepted for publication,  tentative,  May 1970.

                   33-  Basu, P. K.   "Development and Construction of  Pyrolysis-Combustion
                                Experimental Unit."  M.S. Dissertation.   Berkeley:   Univ. of
                                California, 5 September 1969.

                   3^.  Brink, D. L., P. K. Basu, and J. F. Thomas.  "Pyrolysis-Combustion  I.   A
                                New Type Recovery System,"  Preprint,  presented  at the  55th Annual
                                Meeting of  Tappi, February 15-19,  1970, New  York,  New York.

                   35-  Brink, D. L., A. A. Pohlman, and J. F. Thomas.  "Analysis  of Sulfur-
                                Containing  and Sulfur-Free Organic  Products  in Kraft Black  Liquor
                                Pyrolysis," Preprint, presented at  the 55th  Annual Meeting  of  Tappi.
                                February 15-19, 1970, New York, New York.

                   36.  Brink, D. L., J. F. Thomas, and D. L. Feuerstein.  "Malodorous  Products
                                From the Combustion of Kraft Black  Liquor. II.  Analytical Aspects,"
                                Tappi, _5_0(6):276-285.  June 1967.
4.
 r
           ya512

-------

-------