United States
Environmental Protection
Agency
Municipal Environmental Research
Laboratory
Cincinnati OH 45268
EPA-600/8-78-015
November 1978
Research and Development
&EPA
Energy
Conservation
Through Source
Reduction
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3, Ecological Research
4 Environmental Monitoring
5 Socioeconomic Environmental Studies
6 Scientific and Technical Assessment Reports (STAR)
7 Interagency Energy-Environment Research and Development
8 "Special" Reports
9 Miscellaneous Reports
This report has been assigned to the "SPECIAL" REPORTS series. This series is
reserved for reports targeted to meet the technical information needs of specific
user groups. The series includes problem-oriented reports, research application
reports, and executive summary documents. Examples include state-of-the-art
analyses, technology assessments, design manuals, user manuals, and reports
on the results of major research and development efforts
! his document is available to the public through the National Technical Informa-
tion ^Service Springfield, Virginia 22161.
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EPA-600/8-78-015
November 1978
ENERGY CONSERVATION THROUGH SOURCE REDUCTION
by
George W. Reid
Chan Hung Khuong
Bureau of Water and Environmental Resources Research
University of Oklahoma
Norman, Oklahoma 73019
Grant No. R804183
Project Officer
Oscar W. Albrecht
Solid and Hazardous Waste Research Division
Municipal Environmental Research Laboratory
Cincinnati, Ohio 45268
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
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DISCLAIMER
This report has been reviewed by the Municipal Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved for publica-
tion. Approval does not signify that the contents necessarily reflect the
views and policies of the U.S. Environmental Protection Agency; nor does men-
tion of trade names or commercial products constitute endorsement or recommen-
dation for use.
11
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FOREWORD
The Environmental Protection Agency was created because of increasing
public and government concern about the dangers of pollution to the health
and welfare of the American people. Noxious air, foul water, and spoiled
land are tragic testimony to the deterioration of our natural environment
and the interplay between its components require a concentrated and integrated
attack on the problem.
Research and development is that necessary first step in problem
solution and it involves defining the problem, measuring its impact, and
searching for solutions. The Municipal Environmental Research Laboratory
develops new and improved technology and systems for the prevention, treat-
ment, and management of wastewater and solid and hazardous waste pollutant
discharges from municipal and community sources, for the preservation and
treatment of public drinking water supplies, and to minimize the adverse
economic, social, health, and aesthetic effects of pollution. This publi-
cation is one of the products of that research; a most vital communications
link between the researcher and the user community.
As a result of energy shortages and rapidly rising prices for energy
sources, there has developed a strong interest in ways to conserve energy.
The investigation discussed in this report explored the potential for
energy conservation through source reduction, in the use of input materials
and the quantity of waste generated needing to be disposed of.
Francis T. Mayo
Director
Municipal Environmental Research Laboratory
111
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ABSTRACT
This report deals with energy conservation through reduction in
generation of post-consumer solid waste. The objective, scope, methodology
and summary of the report are presented in Section 1. Section 2 contains the
conclusions. Section 3 presents a review of output and input approaches to
estimate the quantity and composition of post-consumer solid waste. Compara-
tive notes on the two methods are included. Section 4 contains a compilation
of estimates of energy consumed in the manufacture of discarded materials and
in handling the solid waste. Section 5 studies potentials and possibilities
of reducing refuse and estimates corresponding energy savings. Twenty
examples of opportunities to reduce refuse at government, policy-maker,
manufacturer, and consumer levels are proposed. The energy intensiveness of
materials found in the waste stream, total energy residuals embedded in each
material, and possible candidates for reduction with greatest energy savings
are also presented.
This report was submitted in fulfillment of Grant No. R804183 by the
Bureau of Water and Environmental Resources Research, University of Oklahoma,
under the sponsorship of the U. S. Environmental Protection Agency.
IV
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CONTENTS
Foreword ill
Abstract iv
Figures . vi
Tables . vii
Metric Conversion Table .......... ix
Acknowledgment ..... x
1. Introduction . . . .1
2. Conclusions 7
3. Quantities and Composition of Solid Waste. .... .... 9
Quantities of solid waste .9
Composition of solid waste. . . 19
Comparative notes . . . .24
4. Solid Waste and Energy Consumption .28
Energy associated with the manufacture of products . .28
Energy associated with the handling of solid waste . .32
5. Reducing Refuse to Conserve Energy ........... 39
Energy conservation potentials . .39
Setting priorities for reducing refuse. ...... .43
Reduction in refuse: a joint initiative .43
Possible reductions and associated energy savings. . .45
References .53
Appendix . , . .57
v
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FIGURES
Numb er Page
1 Sources and classes of solid waste 1
2 Simplified municipal solid waste system . .34
3 Complete solid waste management system . 35
VI
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TABLES
Number Page
1. Energy consumption in the United States, 1950 to 1976 2
2. Contribution of major energy sources to total energy con-
sumption in the United States, 1950 to 1976 3
3. Supply and demand for all oils, United States 5
4. Average solid waste collected, 1967 11
5. Revised estimates of nationwide solid waste collection for
1967, based on the 1968 National Survey of community solid 11
waste practices 12
6. 1970 Nationwide solid waste collection estimates based on
private sector solid waste management survey 12
7. Refuse generation rates in six cities, 1958 - 68 12
8. Per capita solid waste collection: comparisons from two
recent studies 13
9. Post - consumer net solid waste disposed of, by material
and product categories, 1971 - 75 14
10. Material flow estimates of residential and commercial post -
consumer net solid waste disposed of, by material and
product categories, 1975 16
11. Post - consumer and commercial solid waste generated and
amount recycled, by product category, 1975 17
12. U.S. Baseline post - consumer solid waste generation
projections 18
13. Comparison of three studies of the quantity and composition
of post - consumer solid waste generated in 1971 19
14. Comparison of SEAS with Smith results for municipal waste,
1973 20
vii
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Number Page
15. Trends in material recovery from post - consumer munici-
pal waste, 1971 - 75 by type of material ........... 20
16. Composition of solid waste, output approach. .......... 22
17. Composition of average urban solid waste, output approach. ... 23
18. Composition of average solid waste, input approach ....... 23
19. Distribution of energy consumption by sector, 1971 ....... 29
20. Energy consumption in manufacturing four paper products. .... 30
21. Energy consumption in producing 1 metric ton of glass container. 30
22. Energy consumption in the manufacture of raw and finished steel. 31
23. Energy consumed in the manufacture of 1 metric ton of synthetic
fibers ............................ 32
24. Energy required to produce typical containers. ......... 33
25. Fuel consumed annually in the collection and land disposal
of solid waste ......................... 36
26. Energy consumed in manufacturing disposed of refuse, 1975. . , . 40
27. Energy consumed in manufacturing disposed of refuse, 1971 - 75 49
28. Total energy consumed in the solid waste management, 1971 - 75 41
29. U.S. Solid waste generation rates, 1971 - 75 42
30. Potentials of energy savings through source reduction, 1975. . . 42
31. Priorities for energy - intensive materials in the waste
stream ............................ 44
32. Priorities for materials in the waste stream based on total
energy 44
33. Possibilities for refuse reductions and energy savings, 1975 . . 52
VI11
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METRIC CONVERSION TABLE
Metric units to customary units.
1 liter
1 liter
1 liter
1 Kg
1 metric ton =
1 KWH
Customary units to metric units.
1 fluid ounce
1 gallon
1 barrel
1 Ib
1 short ton
1 BTU
33.814 fluid ounce
0.264 gallon
6.290 x 10 3 barrel
2.205 Ib
1.102 short ton
4,313 BTU
= 0.0296 liter
= 3.785
=158.983
= 0.454
= 0.907
liter
liter
Kg
metric ton
= 293 x 10~6 KWH
IX
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ACKNOWLEDGMENTS
The author gratefully acknowledges the valuable assistance of the fol-
lowing Environmental Protection Agency personnel during the course of this
study: Oscar W. Albrecht, H. Lanier Hickman, John A. Connolly, Frank A.
Smith, Fred L. Smith, Jr., Kenneth A. Shuster, and Stedman B. Noble. Thanks
are also due to Robert P. Stearns, SCS Engineer; Jack M. Betz, City of
Los Angeles; Joseph T. Swartzbaugh, Systems Technology Corporation; Mark S.
Bendersky, Resource Planning Associates; and Charles C. Humpstone, Marc
Narkus-Kramer, and Andrea L. Watson of the International Research & Technol-
ogy Corporation.
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SECTION I
INTRODUCTION
THE NEED TO CONSERVE ENERGY
Energy shortages and the need for energy conservation have been empha-
sized in recent years and are becoming universally recognized. The 1973
Arab oil embargo warned of future energy crises and political difficulties
that the United States will face if heavy dependence on foreign oil persists.
The impact of the severe natural gas shortage in the Northeastern States
during the winter of 1976 is illustrative of the problem. The importance
of conserving energy is reflected both in numerous Congressional hearings
and recommendations and in various measures undertaken by Federal and State
government. In the economic, scientific, and engineering communities, con-
siderable research on energy sources and policy is being conducted in the
public and private sectors at national, state, and local levels.
A review of energy consumption reveals that both total and per capita
energy consumption steadily increased between 1950 and 1976. Total consump-
tion more than doubled from 1950 to 1976 (or increased 3.1 percent annually),
and per capita consumption rose 49.8 percent (or 1.6 percent annually) during
the same period (Table 1).
Available energy resources are exhaustible. Indeed, today's only prac-
tical major energy sources are crude petroleum, natural gas, and coal. Less
important sources are hydropower and nuclear power. Contributions from other
energy sources (oil shale, tar sands, geothermal energy, and solar energy)
are insignificant. These statements are based on the contribution of each
energy source to total consumption from 1950 to 1976 (Table 2).
Recent data on all oil (the most important energy source) illustrate the
critical aspect of energy supply and demand (Table 3). From 1950 to 1975,
domestic demand grew 3.7 percent annually and decreased slightly from 1970 to
1975. Consequently oil imports increased at the rate of 8 percent annually
during the same period. Futhermore, total oil reserves (that portion of iden-
tified resources that can be extracted with current technology) in the United
States are estimated to be no more than 50 billion barrels, which, given the
present levels of consumption, is at the most a 9 year supply.2
A review of other energy sources (coal, natural gas, hydropower, nuclear
energy-, oil shale, geothermal energy, and solar energy) would yield similarly
discouraging results. Each energy source has its inconveniences and con-
straints, either quantitative (crude oil, natural gas, hydroelectric),
1
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TABLE 1.
Year
1950
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
ENERGY CONSUMPTION
Resident
population
(millions)
151.9
165.1
168.1
171.2
174.1
177.1
180.0
183.1
185.8
185.5
191.1
193.5
195.6
197.5
199.4
201.4
203.8
206.2
208.2
209.9
211.4
213.1
214.7
IN THE UNITED STATES,
Total
consumption
(trillions of KWH)
9.955
11.628
12.303
12.277
12.284
12.742
13.053
13.347
13.947
14.541
15.087
15.563
16.732
17.325
18.294
19.263
19.596
20.017
20.972
21.835
21.283
20.671
21.672
1950 TO 1976*
per capita
consumption
(thousands of KWH)
65.311
69.697
72.926
71.725
70.554
71.959
72.340
72.897
75.035
77.055
78.813
80.248
85.402
87.540
91.553
95.419
95.770
96.649
107.749
104.264
100.749
96.942
100.749
* Source: Reference 1.
technological (geothermal, tar sand, solar), economical (oil shale, solar,
nuclear), or environmental (coal, nuclear). It is logical to conclude, as did
the Energy Policy Project of the Ford Foundation, (Final report, A Time To
Choose, quoted by William, R. H. ), that the Nation's best approach to bal-
ancing its energy budget, safeguarding the environment, and protecting the
independence of its foreign policy, is to limit energy consumption through
policies that encourage more efficient use.
Objective and Scope
This study deals with the potential of energy conservation through re-
duction in the amount of refuse generated (source reduction). Refuse con-
tains residuals of energy. Decreasing the amount of refuse reduces (a) the
energy required in manufacture, (b) the energy imput necessary to collect,
transport, process and/or recycle the refuse, (c) the land necessary for
waste disposal, and (d) the environmental problems associated with management
of large amounts of refuse. Reduction of refuse entails conservation of
materials, since no matter how extensively recycling is carried out, sig-
nificant amounts of materials are still lost in incinerators or in land
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disposal sites.
Source reduction is of particular interest in the United States where
the waste generation rates are considerably higher than in other developed
countries. The annual solid waste generation rate in the United States
TABLE 2. CONTRIBUTION OF MAJOR ENERGY SOURCES TO TOTAL ENERGY
CONSUMPTION IN THE UNITED STATES, 1950 TO 1976*
Percent
Year
1950
1960
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
Coal
37.2
22.8
22.3
22.2
21.1
20.5
19.6
19.0
17.6
17.3
17.9
17.8
18.2
18.6
Petroleum
37.2
41.8
40.1
37.9
39.8
39.8
40.0
40.4
41.0
42.3
43.2
42.5
42.8
43.9
Natural
Gas
20.3
31.7
33.7
34.4
35.0
35.7
36.1
36.3
36.6
35.5
33.8
33.4
31.8
30.6
Electricity
(hydropower &
nuclear power)
NA
3.7
3.9
3.7
4.1
4.0
4.3
4.3
4.8
4.9
5.2
6.3
7.2
6.9
* Source: Reference 1.
is approximately 680 Kg per capita (or a daily rate of 1.863 Kg per capita).
By contrast, England generates 317; France, 272; the Netherlands, 206;
Germany, 349; Switzerland, 249; and Italy, 211 Kg per capita each year^-
These figures include household and commercial wastes.
Solid wastes fall into many categories (Figure 1), among which post-
consumer solid wastes, or combinations of household and commercial solid
wastes, are the most important. Results of the 1968 National Survey show
that of the daily average of 2.410 Kg per capita, 2.039 Kg originate from
households and commercial institutions^. This study deals with post-consumer
solid wastes.
The materials commonly found in the waste stream are paper, ferrous
metals, aluminum, other nonferrous metals, glass, plastics, rubber, textile,
leather, wood, food wastes, yard wastes, and miscellaneous inorganic wastes.
Only the first eight of these will be discussed, because they are highly
energy - intensive materials, based on the energy per ton of material and on
the total energy embedded in each material. The other components are not
considered, principally because of the unavailability of data. In addition,
the energy associated with yard wastes and miscellaneous inorganic wastes is
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agricul-
ture
indus-
tries
demonli-
tion
sites
construc-
tion
sites
sewage
treatment
plants
indus-
tries &
institu-
tions
Figure 1. Sources and Classes of Solid Waste
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assumed to be negligible. Reduction of food wastes is difficult and im-
practical, especially in an affluent society.
TABLE 3. SUPPLY AND DEMAND FOR ALL OILS, UNITED STATES.
(Millions of Barrels) * f
Supply
Demand
Year Import
Domestic Total Export Domestic
Total
1950
1955
1960
1965
1970
1971
1972
1973
1974
1975
310.2
455.7
664.1
900.7
1,248.1
1,432.9
1,735.2
2,263.6
2,231.0
2,198.9
2,155.7
2,766.3
2,915.8
3,290.1
4,129.6
4,077.8
4,102.1
3,998.5
3,831.8
3,661.7
2,466.0
3,211.9
3,579.5
4,190.9
5,377.7
5,510.7
5,837.3
6,262.0
6,062.7
5,860.6
111.3
134.2
73.9
68.3
94.5
81.8
81.5
84.2
80.5
76.4
2,375.1
3,087.8
3,535.8
4,125.5
5,237.7
5,417.6
5,848.1
6,297.3
6,078.2
5,946.2
2,486.4
3,222.0
3,609.7
4,193.7
5,332.2
5,499.4
5,929.6
6,381.7
6,158.7
6,022.6
* Source: Reference 9.
t Barrel is not a metric system unit but is internationally used in the oil
industry.
This report estimates the amount of energy embedded in the waste stream,
thus revealing the amount of energy that could be conserved if the quantity
of refuse were reduced. This work requires prior review of the quantity and
composition of solid waste and the energy associated with the manufacture and
handling of discarded materials. Possible reductions will be identified and
the associated energy savings will be estimated. Some incentives aimed at
refuse reduction will also be proposed.
Summary and Methodology
Section 3 is a literature review of quantities and composition of solid
waste generated across the country. Two methods are used for estimating
quantities of refuse, the output and the input approach. The output approach
directly measures the quantity of refuse. Refuse composition is also deter-
mined by sampling the refuse, classifying it and weighing each component.
The quantity of each component in the waste stream can then be determined by
multiplying its composition percentage with the refuse quantity. This ap-
proach is most appropriate to the study of a city waste stream but it can
also be applied at the national level by devising an average composition for
the national refuse. The imput approach estimates the quantity and composi-
tion of refuse by considering the flow of materials in the economy where con-
sumer products (with the exception of food) are discarded after use. Various
data relative to both output and input approach are compiled. Some compara-
tive notes and statistical tests of hypotheses about quantity and composition
of solid waste are incorporated in this section.
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Section A is a compilation of data on energy associated with the manu-
facture and handling of solid discarded products. Data on energy required
for the fabrication of products is not accounted for because they are not
available.
Section 5 provides estimates of energy consumed in the manufacture and
management of materials discarded in the national waste stream. The base
year chosen was 1975. Data on quantity and composition of refuse developed
by the Resource Recovery Division of the U. S. Environmental Protection
Agency (EPA) were used in the analysis. Potential reductions in refuse are
presented and estimates of associated energy savings are made. Also included
are proposed incentives for reducing refuse generation. These require the
cooperation of government, industry and the consumer.
In the appendix are presented computations details of statistical ana-
lyses made in Section 3.
Metric system units are used throughout the report, except when other-
wise indicated. However, for practical purposes, instead of using a certain
consistent unit system (e.g. CGS or MKS or MTS system), most familiar units
for various quantities are used. Thus, for example, both metric ton and kilo-
gram are used depending on the circumstances, also KWH is used as an energy
unit although it does not belong to any specific unit system. Conversion
factors given in the Metric Conversion Table are used except when otherwise
noted. Only those units used in this report are compiled in the Metric
Conversion Table.
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SECTION 2
CONCLUSIONS
Based on a sample of 24 compositions of solid waste at various geograph-
ical locations throughout the country, it was found that the solid waste was
statistically homogeneous. This means that the consuming and discarding hab-
its of the consumers do not change significantly nationwide. Therefore, it
would not be unreasonable to conceive common policies governing solid waste
management for all states.
Though the energy consumed in handling the refuse is far from being in-
significant (30,381 million KWH in 1975), it is very small compared with the
energy consumed in the manufacturing of discarded materials (767, 708 million
KWH in 1975) - about 4 percent of the latter. The efficient way to conserve
energy in solid waste management is then through source reduction rather than
through improvement of the collection, processing and disposal of the waste.
Material recycling is most beneficial in resource recovery but represents an
expensive route in energy conservation. Source reduction must be a joint ef-
fort among government policy makers, manufacturers, and consumers. Examples
of incentives to reduce refuse at these three levels were incorporated in the
report.
Total energy lost in the management of 123.5 million metric tons of solid
waste generated in the base year 1975 was 798,089 million KWH, or 3.86 percent
of the total national energy consumption (20.671 trillion KWH). This was a
conservative estimate in two ways. First, the quantity of solid waste was an
EPA material flow estimate (input approach), which yielded a-per capita gener-
ation rate significantly less than the population mean of generation rates
determined by the output approach. Second, the figure represented only the
energy consumed in handling the waste and in manufacturing the materials found
in the waste stream, but did not include the energy consumed in producing pro-
ducts. With the hypothetical reductions shown in Table 33, it would have been
possible to save at least 184 billion KWH-23.06 percent of the total energy
spent on managing the refuse, or 0.89 percent of the national energy consump-
tion. In terms of fuel conservation, the equivelent of 19.02 billion liters
of gasoline or 17.22 billion liters of diesel fuel would have been saved.
These figures are significant in light of the current energy dilemma, but
it is possible that even greater savings could be realized. The hypothetical
source reductions proposed here are only the most feasible. A more detailed
examination of the waste stream, the products currently available on the mar-
ket, and their packaging could uncover other possibilities.
Any reduction of refuse at its source implies conservation of our
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irreplaceable natural resources. Manpower Is also conserved and environmental
impacts of the waste is reduced. Significant source reduction cannot be ach-
ieved, however, without accompanying changes in industry, commerce, and life-
styles. It is hoped that cooperation among government agencies, industry,
and consumers will make any necessary inconveniences acceptable to the maj-
ority.
It was found herein that intensive materials are, in decreasing order,
aluminum, rubber, copper, plastics, textiles, ferrous metals, paper, glass.
Materials bearing greatest amounts of total residual energy are paper, fer-
rous metals, plastics, rubber, aluminum, glass, textiles, copper and other
nonferrous metals. This means that as far as energy savings in reducing one
unit weight of material is concerned, it is most advantageous to reduce al-
uminum, whereas paper is the material with greatest energy savings pot-
ential. In terms of consumer products, possible candidates for reduction
with greatest energy savings are major appliances, rubber tires, corrugated
paperboard, aluminum beverage cans, glass beverage containers, grocery paper
sacks. Other research topics in energy conservation might involve comparisons
between various activities, such as material recycling, energy recovery
through pyrolysis, using shredded refuse as fuel (RDF) etc.
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SECTION 3
QUANTITIES AND COMPOSITION OF SOLID WASTE
A knowledge of the quantities and composition of solid waste generated
is essential to its management, and particularly to any consideration of
energy conservation in the manufacturing and handling of solid waste. Esti-
mating quantities and composition of solid waste is difficult because of the
heterogeneous nature of the waste, which depends on the season, size, and
lifestyle of the community.
Various research groups have come up with many different results on the
quantities and composition of post consumer solid waste generated. Two basic
methods have been used: the output and the input approach. The output ap-
proach involves direct evaluation of solid waste quantities by weighing or by
other measures. The input approach, also called material flow approach, es-
timates quantities of materials involved in the manufacturing or marketing
of products that will ultimately go into the waste stream.
One major item of interest is the quantity of recycled materials from
the waste stream, especially since passage of the Resource Recovery Act by
Congress in 1970.
QUANTITIES OF SOLID WASTE
Output Approach
The output approach is usually based on questionnaire survey data ob-
tained from solid waste collection agencies (the sample size is generally too
large to be measured by a single investigator).
1968 National Survey of Community Solid Waste Practices—
This survey was designed by the Solid Wastes Programs, U. S. Department
of Health, Education and Welfare. Survey data available on July 1, 1968,
were presented in their basic forms-* and also in concise statistical format^.
All land disposal sites and facilities at which public and/or private col-
lectors deposited solid wastes were to be surveyed, regardless of the size of
community served by the site. Unauthorized dumpings at roadsides or in other
areas were not considered in this survey. In addition, private disposal
sites or facilities owned and operated by industrial, commercial, or insti-
tutional establishments solely for reduction or disposal of their own solid
waste were not surveyed. Onsite disposal facilities such as apartment house
incinerators and household garbage grinders were also excluded.
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A total of 6,259 communities were surveyed, representing an estimated
1967 population of 92.5 million persons, or approximately 46.3 percent of the
total population of the United States. On total population basis, the sample
is approximately 75 percent urban in nature.
Most of the data available were estimates; only a small portion was meas-
ured. From the survey data, it was estimated that 172 million metric tons of
solid waste were generated annually, corresponding to 2.410 Kg per capita
daily. These figures include reported demolition, construction, industrial,
and other municipal solid waste, in addition to household, commercial and
institutional refuse of all kinds. Of the daily 2.410 Kg per capita, 1.880
Kg was estimated as the household and commercial contribution to the nation-
wide average (Table 4).
A more rigorous evaluation of the complete returns from the 1968 survey
was subsequently conducted^. Figures based on estimates from a selected
sampling of the returns are shown in Table 5.
1971 Private Sector Collection Survey.
O
As part of a study of the private sector refuse collection industry0,
Applied Management Sciences, Inc. (AMS), developed national estimates of U.S.
per capita waste generation for 1970 based on quantities collected. Using
large samples from private waste haulers, scaled up to national totals on the
basis of estimated share of total customers covered by the private sector
survey, AMS was able to estimate residential, commercial, and industrial
solid waste. Private collectors play an important role in the collection of
household and commercial solid waste: 32 percent of household waste and 62
percent of commercial waste is collected by private collectors'^. The AMS
total national estimates and per capita generation rate are shown in Table 6.
Other Results.
The daily per capita generation rates for 12 cities in the United States
were compiled by the APWA in 1968 for 1957-58 . These cities had popula-
tions ranging from 4,500 to 8 million. The generation rates of six of these
12 cities from 1955 to 1968 are reported by APWA in Table 7.
The Quad - Cities New Jersey Solid Waste Project reports a daily genera-
tion rate in these cities of 1.241 Kg per capita for municipal waste during
1966-6811.
EPA has recently supported two independent residential collection stud-
ies. One set of data covering a number of residential collection routes in
each of 11 city or county jurisdictions was developed by ATC Systems, Inc.,
for a 12 month period during 1972-73 . The other set of data was made avail-
able by Applied Management Sciences, Inc., and involved analysis of more than
20 communities during the 1971-72 period''. Results of these two surveys are
shown in Table 8.
Input Approach
10
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TABLE 4. AVERAGE SOLID WASTE COLLECTED (Kg/PERSON DAILY), 1967*
Type of Solid Waste
Industrial
Demolition, construction
Street and Alley
Miscellaneous
Total
Urban
0.294
0.104
0.050
0.172
2.590
Source
Rural
0.168
0.009
0.014
0.036
1.781
National
Household
Commercial
Combined
0.571
0.208
1.191
0.326
0.050
1.178
0.516
0.172
1.192
0.267
0.082
0.041
0.140
2.410
* Source: Reference 4
TABLE 5. REVISED ESTIMATES OF NATIONWIDE SOLID WASTE COLLECTION FOR
1967, BASED ON THE 1968 NATIONAL SURVEY OF COMMUNITY SOLID WASTE PRACTICES*
Source
Total Solid Waste Collected
(millions of metric tons)
Daily Average Per
Person (Kg)
Residential
Commercial and institutional
subtotal
79.8
51.7
131.5
1.101
0.716
1.817
Other municipal
Demolition and construction
Industrial
Low
Estimate
5.4
4.5
30.8
High
Estimate
20.0
17.2
95.2
Low
Estimate
0.077
0.059
0.430
High
Estimate
0.276
0.240
1.314
* Source: Reference 7. Based on Environmental Protection Agency analyses of
final questionnaire returns received by the 1968 National Un-
published data, May 1970.
The input or material flow approach is based on industrial production
and/or trade statistics of all major materials and final products that become
solid waste after they are used.
EPA Material Flow Estimating Method—
Frank A. Smith and Fred L. Smith, Jr. of EPA developed the material flow
estimating method ' '-1- - This method is based principally on U. S. Govern-
ment and industrial trade association statistics and nationwide industrial
production, marketing, foreign trade and consumption of major raw materials
and final products. Using the principles of mass balances and a knowledge
11
-------
of the economy's material flow structure, the researchers adjusted the orig-
inal material product data where necessary for industrial scrap losses, prod-
uct lifetime, and material recycling to yield the final estimates of net
waste disposal for the manufactured goods component of solid waste.
TABLE 6. 1970 NATIONWIDE SOLID WASTE COLLECTION ESTIMATES BASED ON PRIVATE
SECTOR SOLID WASTE MANAGEMENT SURVEY.*
Source
Total Yearly Collection
(millions of metric tons)
Daily Average Per
Person (Kg)
Residential
Commercial
Subtotal
Demolition and other
Industrial
Grand total
116.1
52.6
168.7
10.9
59.9
239.5
1.567
0.711
2.278
0.145
0.784
3.207
* Source: Reference 7
The solid waste is divided into two categories, the non-food product
solid waste, and the food, yard and miscellaneous waste. Only the former
type (non-food product waste) is estimated directly using the actual material
flow approach. Food, yard and miscellaneous waste are estimated indirectly
from data on non-food product waste and from data on municipal waste composi-
tion developed by Niessen and Chansky-^. Estimates were adjusted to reflect
the moisture transfer occurring during storage and collection of waste com-
ponents, and the "as discarded" and "as disposed" moisture content of each
category was used.
TABLE 7. REFUSE GENERATION RATES IN SIX CITIES, 1958-68
(Kg PER CAPITA DAILY) *
City
1958
1965
1968
Cincinnati, Ohio
Garden City, N. Y.
Los Angeles, C. A.
New York N Y
Seattle, W. A.
Washington, D. C.
1.369
1.785
2.081
1 6AA
1.700
2.033
1.533
1.623
2.945
1 ftZil
1.872
1.917
1.694
1.805
3.147
1.776
2.158
* Source: Reference 6.
Estimates of net post-consumer solid waste for 1971 through 1975 are
shown in Table 9. Tables 10 and 11 show solid waste generation and resource
recovery for 1975.
Projections of post-consumer solid waste generation, resource recovery
and net waste disposal for 1980, 1985 and 1990 were also estimated and shown
in Table 12.
12
-------
TABLE 8. PER CAPITA SOLID WASTE COLLECTION:
RECENT STUDIES*
COMPARISONS FROM TWO
Item
Solid waste collected daily (Kg per capita)
ACT Systems, Inc. Applied Management
1972-73 Sciences, Inc. 1971-72
Unweighted arithmetic average
of individual community data
Median
Range of values
1.078
1.101
0.779 - 1.554
1.065
1.087
0.498 - 1.540
* Source: Reference 7.
URS Research Company Prediction Model—
URS Research Company, under contract with EPA, developed a prediction
model for residential and commercial solid waste. "» 1' The theory behind
the model is that waste generated by a community is derived primarily from the
goods and materials consumed there and that therefore waste quantities and
characteristics can be estimated from the data on the consumption habits of
the community. Quantitative results at the national level were not presented
in the URS's final report, but the computation methodology was explained
thoroughly.I?
International Research and Technology Corporation Forecasting Method—
Under contract with the EPA, the International Research and Technology
Corporation (IR & T) has developed a method of forcasting the composition
and weight of household solid wastes using input-output techniques. The
forecasting model uses data from the input-output table provided by the
Department of Commerce. Projections of input-output tables and of micro var-
iables in association with them are made by the Bureau of Labor Statistics.
The input-output table represents all accounting transactions in the
economy. Any row of the input-output table can be represented by an equation
of the following kind:
+ t. +
-
X,
where;£-- is the sales of sector^, to sector j , ^ is the sales by sector ^
that go to final uses, and x; is the total sales of sectorxL .
The input-output model is obtained by making the following assumption:
-t - ./X - =
-------
TABLE 9. POST-CONSUMER NET SOLID WASTE DISPOSED OF BY MATERIAL AND PRODUCT
CATEGORIES, 1971-75*
(As-generated wet weight, in millions of metric tons)
Materials and products
Material composition:
Paper
Glass
Metal
Ferrous
Aluminum
Other
Plastics
Rubber and leather
Textiles
Wood
Total nonfood product waste
Food waste
Total product waste
Yard waste
Miscellaneous inorganics
Total
Product composition:
Newspapers, books, magazines
Containers and packaging
Major household appliances
Furniture and furnishings
Clothing and footwear
Other products
Total nonfood product waste
Food waste
Total product waste
Add: Yard and misc. organics
Total
1971
35.5
10.0
10.7
(9.6)
(0.7)
(0.4)
3.8
3.0
1.6
4.2
69.7
20.0
89.7
21.9
1.6
113.2
9.3
37.8
1.9
2.9
1.1
16.7
69.7
20.0
89.7
23.5
113.2
1972
38.5
11.5
11.0
(9.8)
(.8)
(.4)
4.3
3.1
1.6
4.3
74.3
20.1
94.4
22.2
1.6
118.2
9.9
40.9
1.9
3.0
1.1
17.7
74.5
20.1
94.6
23.6
118.2
1973
40.1
12.0
11.2
(10.0)
(0.9)
(0.3)
4.5
3.3
1.7
4.5
77.3
20.3
97.6
22.7
1.7
122.0
10.2
42.4
1.9
3.1
1.2
18.5
77.3
20.3
97.6
24.4
122.0
1974
39.3
11.7
11.8
(10.4)
(0.9)
(0.3)
4.1
3.7
1.9
4.3
76.8
20.5
97.3
23.1
1.7
122.1
10.4
41.2
1.9
3.0
1.2
19.1
76.8
20.5
97.3
24.8
122.1
1975
33.7
12.1
11.0
(9.8)
(0.8)
(0.4)
4.0
3.0
2.0
4.5
70.3
20.7
91.0
23.6
1.7
116.3
9.0
37.8
2.1
3.1
1.2
17.1
70.3
20.7
91.0
25.3
116.3
* Office of Solid Waste, Resource Recovery Division, and Franklin Associates,
Ltd. Revised February 1977. This table is reproduced from Reference 15.
Then:
-, -,
In n °l
- a_ x. =X
2n n U2
-ax - a
nl 1 n2
- ---- +(l-a
14
)x =
n
-------
This is the set of simultaneous equations of the input-output model,
which in matrix form becomes:
(I -_A)X =6 or x= (I-A)"1^ =B^
where B = (I-A) is the inverse of the matrix (I-A).
Consider the following mass balance condition:
weight purchased - industrial waste=embodied waste
If the two following adjustments are made in the inverse matrix, the
latter can provide information that can be used to infer the amount and com-
position of post-consumer solid waste:
1. The effect of prices must be eliminated so that purchases of
inputs define the weight of inputs; and
2. The amount of industrial waste must be subtracted.
The purpose of this brief review of the input-output technique is only
to show the methodology. It is beyond the scope of the report to go into the
actual computation steps which are described in details by IR & T. ° The
computation steps require a number of assumptions and a series of adjust-
ments in the entries of the input-output table.
This technique has been used by IR & T in Table 13 to compute the com-
position of household and commercial solid waste generated for the base year
1971. The table also contains corresponding results developed by the Nation-
al Center for Resource Recovery (NCRR)21 and by EPA (Fred L. Smith, Jr.)-12
EPA Strategic Environmental Assessment System (SEAS)—
The Strategic Environmental Assessment System (SEAS) is an extensive
model developed by EPA that utilizes demographic, economic, and technological
projections to forecast environmental conditions to the year 1985. SEAS is
closely related to IR & T's input-output technique in a number of ways, par-
ticularly in its methodology and its use of data from INFORUM (The Inter-
industry Forecasting Model of the University of Maryland).
Let M . - (t) be the amount of material i, by weight, flowing into product
class j in year t. M . . (t) can be estimated through the input-output tech-
nique by a rather compVex formula. ^ Each of the entries in the M - - (t)
matrix represents commodities flowing into finished products. At some time
in the future, these commodities become waste. The model next projects the
quantity of material i embodied in product j, which is disposed of in year t.
This is calulated by timelagging the M - -matrix.
*-j
Some selected results of SEAS solid waste projections are presented in
Table 14.
Quantities Of Recycled Materials
EPA figures for materials recycled from the solid waste stream from 1971
to 1975 are shown in Table 15. Notice that these estimates are generally
smaller than both NCRR estimates2! and Midwest Research Institute esti-
mates22, because EPA excludes converting wastes and a number of special
15
-------
TABLE 10. MATERIAL FLOW ESTIMATES OF RESIDENTIAL AND COMMERCIAL POST-CONSUMER NET SOLID WASTE DISPOSED OF,
BY MATERIAL AND PRODUCT CATEGORIES, 1975*
Product category
(In millions of metric tons, as-generated wet weight)
Material category Newspapers,
books,
magazines
Paper 8.9
Glass
Metals
Ferrous -
Aluminum
Plastics
Rubber and Leather
Textiles
Wood
Total nonfood
product waste 8.9
Food waste
Total product
waste 8.9
Vard waste
Misc. inorganics
Grand total
Containers,
packaging
17.
11.
5.
(4.
(0.
2.
Tr
0.
1.
37.
_
37.
3
1
.It
.7)
6)
4
1
6
8
8
Major
household
appl lances
Tr
0.1
1.9
(1.6)
(0.1)
t n i\
0.1
Tr
Tr
Tr
2.1
_
2.1
Furniture ,
furnishings
Tr
Tr
0.1
(0.1)
Tr
0.1
Tr
0.5
2.3
3.1
_
3.1
Totals
As-generated
wet weight
Clothing, Food Other
footwear products prodi
7.
- 0.
3.
(3,
(0.
fr\
1,
0.6 - 2
0.5 - 0.
0
1.1 - 17
20.1
1.1 20.1 17
jets
6
9
,6
.3)
.1)
91
,4
.3
.8
.5
.1
.1
Million
tons
33.
12.
11.
(9.
(0.
CO
4.
3.
2,
4.
70.
20,
91
23
1
116
7
1
0
8)
8)
4)
0
0
0
5
.3
.7
.0
.6
.7
.3
Percent
29.0
10.4
9.6
(8.6)
(0.7)
(0 3)
3.4
2.6
1.6
3.8
60.5
17.8
78.3
20.2
1.5
100.0
As-disposed
wet weight
Million
Tons
40.7
12.2
11.4
4.5
3.1
2.0
4.5
78.4
17.3
95.7
19.0
1.8
116.5
Percent
34.9
10.5
9.8
3.8
2.6
1.7
3.8
67.3
14.9
82.2
16.3
1.6
100.0
* Office of Solid Waste, Recovery Division and Franklin Associates, Ltd., Revised January 1977.
This Table is reproduced from Reference 15.
-------
TABLE 11. POST-CONSUMER AND COMMERCIAL SOLID WASTE GENERATED AND AMOUNT RECYCLED, RY PRODUCT CATEGORY, 1975*
(AS-GENERATEI) WET WEIGHT, LN THOUSANDS OF METRIC TONS)
Ma Lr rial recycled
Product category
Durable gooJs:
Major appliances
Furniture, furnishings
Rubber tires
Miscellaneous durables
Nondurable goods, exc, food:
Newspapers
Books, Magazines
Office paper
Tissue paper, incl. towels
Paper plates, cups
Other nonpackaging paper
Clothing, footwear
Other misc. nondurables
Containers and packaging:
Glass containers:
finer, soft-drink
Wine, Liquor
Food and other
Steel cans:
Beer, soft-drink
Food
Other nonfood cans
Barrels, drums, pails, raise.
Aluminum:
Beer, soit-drink t
Other cans
Alu-inura foil
Paper, pjperboard:
Corrugated
Other paperboard
Paper packaging
Plastics:
Plastic containers
Other packaging
Wood packaging:
Other misc. packaging
Tutal nonfood product waste
Add: Food waste
Yard waste
Misc. Inorganic wastes
Toral
Gross
discards
13,369
2,204
3,057
1,623
6,485
21,895
8,027
2,789
4,725
2,027
440
948
1,134
1,805
42,221
11,356
5,755
1,624
3,977
5,011
1,215
2,898
689
209
698
462
23
213
20,983
11,356
4,961
4,666
2,390
381
2,009
1.633
150
77,485
20,666
23,591
1^723
123. V)5
Quantity
354
136
0
172
46
2,517
1,651
231
635
0
0
0
0
0
4,322
336
227
27
82
249
59
145
36
9
77
73
0
4
3,660
2,499
653
508
0
0
0
0
0
7,193
0
0
0
/^n
Percent
3
6
0
11
1
11
21
8
13
0
0
0
0
0
10
3
£4
2
2
5
5
5
5
5
11
16
0
2
18
22
13
11
0
0
0
0
0
9
0
0
0
6
Quantity
13,015
2,068
3,057
1,451
6,439
19,378
6,376
2,558
4,090
2,027
440
948
1,134
1,805
37,899
11,020
5,528
1,597
3,895
4,762
1,156
2,753
653
200
621
389
23
209
17,323
8,857
4,308
4,158
2,390
381
2,009
1,633
150
70,292
20,666
23,591
1,7?3
1J6.2/2
Net waste disposed of
% of total
waste
11
2
3
1
5
17
5
2
4
2
_
1
1
2
33
10
5
1
3
4
1
2
1
_
1
_
-
_
15
7
4
4
2
-
2
1
_
61
18
20
1
ion
% of nonfood
product waste
19
3
4
2
9
27
9
3
6
3
_
1
2
3
54
16
8
2
6
7
2
4
1
_
1
1
_
_
25
13
6
6
3
_
3
2
_
100
29
33
2
164
* Office of Solid Waste, Resource Recovery Division, and Franklin Associates, Ltd. Revised January 1977.
t Includes all-aluminum cans and aluminum ends frora nonaluminum cans.
^ This Table is reproduced from Reference 15.
-------
TABLE 12. U. S. BASELINE POST-CONSUMER SOLID WASTE GENERATION PROJECTIONS*
00
Estimated
1971 1973
Total gross discards
Millions of metric tons per year 121 131
Kg per person per day 1.595 1.699
Resource recovery
Millions of metric tons per year 7 8
Kg per person per day 0.095 0.104
Net waste disposal
Millions of metric tons per year 114 123
Kg per person per day 1.499 1.595
Projected
1980 1985
159 182
1.939 2.116
17 32
0.203 0.367
142 150
1.726 1.749
1990
204
2.265
53
0.584
151
1.681
^Source: Resource Recovery Division, Office of Solid Waste Programs,
U. S. EPA.
This Table is reproduced from Reference 23.
-------
TABLE 13. COMPARISON OF THREE STUDIES OF THE QUANTITY AND COMPOSITION
OF POST-CONSUMER SOLID WASTE GENERATED IN 1971
(IN MILLIONS OF METRIC TONS)*
IR & T
Materials
NCRR
Smith Household Commercial
Paper
Newsprint
Newspaper, books and magazines
Containers and packaging
Glass
Containers
Metals
Steel containers
Steel other
Aluminum containers
Aluminum other
Other metals
Plastics
Containers
Containers and film
Durables
Textiles
Wood
Containers
Furniture
Rubber
Rubber and leather
34.6
6.9
9.8
8.8
8.1
4.9
3.2
.23
.34
.41
2.0
1.7
.09
2.6
1.5
35.5
9.3
18.5
11.0
10.1
10.8
4.9
4.7
.5
.2
.2
2.9
2.3
1.6
4.2
1.6
2.1
2.9
26.8
9.6
11.7
14.8
9.4
8.2
11.28
4.9
5.3
.19
.39
.5
1.7
0.8
.14
3.8
7.7
.9
1.3
14.2
3.1
1.0
2.2
.5
* Source: Reference 18.
obsolete scrap sources.
(Table 14).
Two EPA estimates are, however, quite comparable
COMPOSITION OF SOLID WASTE
As in the study of quantities of solid waste, the composition of solid
waste can be estimated by either the sampling or the material flow approach.
The sampling approach (output approach) provides the composition of solid
waste generated by a certain community. Statistical analysis of a large
sample representing different areas of the country could yield the composi-
tion of an average national solid waste. Data obtained by the material flow
approach (input approach) represent the composition of an average solid waste
either at the national or community level, depending on the model used.
19
-------
TABI.K 14. CIWARfSdN OF SF.AS WTTII SMITH RF.S1I1.TS FOR MUNICIPAL WASTE, 1973 (MTU.TONS OF METRIC TONS)*
Gross
Solid Waste Component
P.ipcr
Glass
Plastics
Rubber
Aluminum
Other non-ferrous metals
Ferrous metals
Textiles
Wood
Leather
Total non-food products
Food, yard and miscellaneous
Total waste
Source: Reference 23
TABLE 15.
SEAS
48.
12.
5.
2.
0.
0.
13.
4.
7.
—
93.
49.
142.
TRENDS
0
0
0
0
9
4
?
2
8
-
5
3
8
IN
discards
Sm
AH
12
4
2
0
0
10
1
4
0
86
44
130
ith
. 1
.3
.5
.5
.9
.4
.2
.7
.5
.9
.0
.7
.7
MATERIAL
RECOVERY
Resource
SEAS
7.6
0.24
0.45
0.06
0.09
0.73
0.36
9.53
9.53
FROM POST-CONSUMER
recovery
Smith
7.92
0.25
0.36
0.04
0.36
8.93
8.93
MUNICIPAL WASTE,
1971-75 BY TYPE
Net
SEAS
40.36
11.8
5.0
1.5
0.6
0.3
12.5
3.8
7.8
83.7
130.6
OF MATERIAL*
waste
Smith
AO.l
12.0
4.6
2.4
0.9
0.4
10.0
1.7
4.5
0.9
77.5
44.7
122.2
(IN THOUSANDS OF METRIC TONS)
Paper and paperboard
% of gross paper and board discards
Aluminum
% of gross aluminum discards
Ferrous metals
% of gross ferrous discards
Glass
% of gross glass discards
Rubber (including tires and other)
% of gross rubber discards
Total materials
% of gross nonfood product waste
% of total post-consumer waste
1971
6,798
15.9
18
2.4
127
1 .3
200
1.8
233
8.9
7,376
9.5
6.1
1972
7,324
16.0
27
3.2
181
1.4
248
2.1
222
7.9
8,002
9.6
6.2
1973
7,918
16.5
32
3.4
272
2.4
277
2.3
198
6.8
8,697
10.1
6.7
1974
7,646
16.3
47
5.0
363
3.4
297
2.5
176
6.1
8,529
10.0
6.5
1975
6,176
15.5
79
8.7
433
4.4
334
2.7
171
6.9
7,193
9.3
5.9
* Source: Office of Solid Waste, Resource Recovery Division, and Franklin Associates, Ltd. This Table is reproduced from Reference 15.
-------
Sampling Approach (Output Approach)
Most existing estimates of solid waste composition were obtained by the
sampling approach which consists of sampling, manual sorting, separating, and
weighing refuse at the disposal site. A variation of the manual sorting tech-
nique is the photographic sorting technique, which was developed in 1974. The
sampling technique is the most simple and direct method for determining the
composition of solid waste.
In the Quad-City solid waste project , trucks to be sampled were sel-
ected on a random basis. The composition analysis was performed by hand pick-
ing the various types of material and placing them into corresponding con-
tainers. Eight containers were used, each with a description of the type of
material to be deposited in it. When the sorting was complete, each container
(55-gallon drum) was weighed to the nearest pound, and the tare weight of each
type of material, from which the composition of solid waste was computed.
Systems Technology Corporation (SYSTECH), Xenia, Ohio has conducted in
recent years several sampling analyses of solid wasted for the cities of
Cincinnati, Oakwood, and Franklin, Ohio, and Atlanta, Georgia, under various
projects with EPA (Personal communication, Joseph T. Swartzbaugh, SYSTECH,
Xenia, Ohio; and "Summary of Sort Procedures for Mixed Municipal Waste", 1975,
SYSTECH, unpublished). Special consideration was given to obtaining represen-
tative samples by using a random number generator to select the truck to be
monitored. The solid waste from the selected vehicles was then well mixed
by using a front-end leader before sampling. Furthermore, verticle samples
were taken to assure the homogeneity of the solid waste to be analyzed. Six
200-to-300-lb. samples were taken from each truck. Each sample was manually
sorted into 11 categories and weighed. Results are divided by the total
sample weight to yield the mass fraction of each material type. As an alter-
native to the direct sorting and weighing method, SYSTECH recommended the
photographic inversion procedure. This sorting method uses an area/mass com-
position inversion technique developed by metallurgists. This technique was
first applied to solid waste in mid-1974. This technique involves taking
35-mm color slides of solid waste, projecting the slides on a grid and read-
ing the composition of waste under each node. The summed node counts define
the area fraction of each waste component. If it is assumed that the area
composition remains the same regardless of the slice taken through the refuse
pile, the area distribution can be inverted into a mass distribution using
appropriate bulk densities. SYSTECH reported that there were no significant
differences in the results obtained by the classical manual sorting and
weighing method and this newly developed photographic sorting method.
Table 16 shows 24 sets of data on the composition of solid waste at var-
ious locations across the United States, including Quad-City project and
SYSTECH findings. The compositions of average urban refuse developed by
Bell and by Niessen^ are shown in Table 17.
Material Flow Approach (Input Approach)
The composition of solid waste estimated by the material flow approach
is derived from the studies of solid waste quantities under Input Approach.
21
-------
TABU; id. COMPOSITION OF sni.in WASTK. OUTPUT APPROACH (PF.KCHNT)
K)
hO
Rubber Food Yard
Location Paper Glass Plastics and leather Metals Textiles Woods Waste Waste Misc. Date
Johnson City, TN 45.5 10.9 1.7 1.0 10.8 1.3 0.3 25.9 1.6 1.0 1967
Johnson City, TN 34.9 9.0 3.4 2.4 10.4 2.0 0.8 34.6 2.3 0.2 1968
Memphis, TN 29.8 9.8 3.0 6.6 4.8 1.7 19.7 12.1 12.5 1968
Cincinnati, OH 42.0 7.5 1.6 1.0 8.7 1.4 2.7 28.0 6.4 0.7 1966
Cincinnati, OH 41.83 7.81 6.93 8.34 6.46 1.79 8.09 15.66 3.09 1974
Philadelphia, PA 54.4 9.1 0.2 1.5 8.4 2.6 2.4 5.0 16.0 0.0
Quad-Cities, NJ 43.87 6.44 2.66 9.44 4.52 2.96 8.3 13.3 8.96 1966
Hempstead, NY 42.6 9.6 4.0 8.5 3.1 3.2 10.9 17.6 0.5 1966
Alexandria, VA 55.3 7.5 3.1 8.2 3.7 1.7 7.5 9.5 3.4 1968
San Diego, CA 46.16 8.31 0.27 4.73 7.64 3.46 7.48 0.81 21.14 0.0 1966
Santa Clara, CA 47.5 12.7 1.0 1.0 7.6 1.2 1.0 2.3 23.8 1.9 1967
Berkeley, CA 44.6 11.3 1.9 0.3 8.7 1.1 0.0 12.0 13.1 7.1 1967
Los Angeles, CA 28.17 6.14 2.68 1.39 4.96 2.96 3.61 4.68 17.02 28.39 1973
Los Angeles, CA 23.57 6.15 3.42 1.38 5.6 3.28 6.26 4.31 17.26 28.77 1974
Los Angeles, CA 16.20 7.79 4.34 1.53 8.17 4.7 6.01 5.17 18.79 27.30 1975
Los Angeles, CA 15.61 8.11 3.43 1.4 6.54 4.04 6.74 4.53 20.41 29.19 1976
Chandler, AR 42.7 7.5 0.4 1.0 9.8 1.9 2.3 21.8 1.3 11.3
Atlanta, GA 49.1 14.0 7.4 11.6 4.2 0.6 6.9 1.2 5.0 1974
Tampa, FL 24.1 6.0 2.4 0.6 5.9 2.8 1.5 9.1 41.5 6.1
New Orleans, LA 44.9 9.5 3.5 8.1 3.2 3.1 11.0 9.6 6.9 1969
Reference
24
24
26
a
b
b
c
11
d
e
f
26
g
h
10
1
i
i
i
i
k
i
21
1
a. L'SPHS, Solid Wastes Program, Cincinnati, Ohio. Solid Wastes Study of a Residential Area. 1966 Quoted by Niessen26.
b. Private communication, Dr. Swartzbaugh, J. T. , Systems Technology Corporation (SYSTECH) , Xenia, Ohio. 1975.
c. Proceedings - Institute for Solid Waste - 1966. Quoted by Niessen26.
d. Kaiser, E. , C. D. Zlit, and J. B. McCoffery. Municipal Incinerator Refuse and Residues. Presented at the 1968 National Incinerator Conference, 1968.
Quoted by Niessen^*1.
e. Kaiser, E. R. Composition and Combustion of Refuse. In Proceedings; MECAR Symposium, New York, 1967.. Metropolitan Engineers Council on Air Resources,
1967. p. 1-9. Quoted by Darney .
I, USDHEW. The Solid Wastes Disposal Study, Genesee County, Michigan, 1968. Quoted by Niessen26
g. Hoffman, D. A., and R. A. Fitz. Batch Retort Research on Pyrolysis of Solid Municipal Refuse. Paper presented at Engineering Foundation Research
Conference, University School, Milwaukee, Wisconsin, 1967. Environmental Science & Technology, Nov. 1968. Quoted by Drobny"
h. FMC CoL-poL'aLiou. Systems Analysis Co;' Solid Waste Disposal by Incineration, 1968. Quoted by Niussc-n
i. Private communication, Mr. Jack M. Betz, Bureau of Sanitation, City of Los Angeles, 1976.
j. American Public Works Association. Municipal Refuse Disposal, Second Edition. Chicago, Public Administration Service, 1966. Quoted by Damay .
k. Bureau of Solid Waste Management, unpublished. Quoted by Darney .
1. Bureau of Solid Waste Management, unpublished. Quoted by Darney .
-------
U>
Researcher Note
Niessen, W. 9..^^ Un-seasonal state
Niessen, W. R.2° Semi-seasonal state
Niessen, W. R.2^ Seasonal state
Belli J- H-25 Composite
*AB - discarded basis
Researcher
Office of Solid Waste, U. S. EPA
Office of Solid Waste, U. S. EPA
Paper
32.6
35.1
38.2
42.0
TABLE 18.
Paper
37.8
34.9
Class
7.6
8.1
8.8
6.0
COMPOSITION
Class
10.0
10.5
PI as tics
1.0
1.1
1.1
0.7
OF AVERAGE SOLID
Plastics
3.8
3.8
Rubber
and leather Metals
1.3 7.5
1.4 8.1
1.5 8.7
0.9 8.0
WASTE, INPUT APPROACH
Rubber
and leather Metals
2.7 10.1
2.6 9.8
Textiles
1.8
1.9
2.0
0.6
(PERCENT)*
Textiles
1.6
1.7
Wood
2.3
2.4
2.7
2.4
Wood
3.7
3.8
Food
Was te
18.2
19.5
21.1
12.0
Food
Uaste
14.2
14.9
Yard
Waste
26.1
20.7
14.1
12.0
Yard
Waste
14.6
16.3
Kisc.
1.6
1.7
1.8
15.5
Misc.
1.5
1.6
Date
1968
1968
1968
1959-62
Date
1971
1975
* As - disposed oasis
-------
These compositions are shown in Table 18.
COMPARATIVE NOTES
One question now arises concerning which of the output and input ap-
proaches is the best method to estimate the quantity and composition of solid
waste generated in the United States. There is no direct and clear-cut an-
swer to this question.
Conceptually, the output approach should provide more accurate data for
a town or a city but it requires careful measuring and recording practices
and therefore is less convenient. At national level this approach has an
additional disadvantage that it must rely on results of survey questionnaires
and thus the investigator cannot control nor check the validity of the data
reported. It is also impossible to account for unrecorded and unreported
solid waste disposed of in rural areas or at unauthorized dumping sites.
The input approach is perhaps more convenient, but its major drawback is
that its validity cannot be guaranteed in principle, because the method is
based on assumptions that cannot be proved nor justified (one example is the
assumed lifetime of products). The URS Company method is more applicable at
community level than at national level while the EPA material flow method and
SEAS model can only be used at national level.
In the following paragraphs we will consider some applications of sta-
tistical techniques to test hypotheses about quantities and composition of
solid waste. This analysis would serve as a link between the input and out-
put approaches. The daily generation rate in Kg per capita per day is
thought of as an univariate random variable and the composition is thought
of as a p-dimension multivariate random vector; each of the p-elements of
the vector represents the percentage of one component of the solid waste
(paper, glass etc.). Notice that we will not include the percentage of misc-
ellaneous materials as a component of the vector composition because they are
of no importance with regard to energy.
Quantity
1. The daily generation rates Kg per capita per day of six cities in
the United States (Table 7) are reproduced below:
Group 1
1958
1.369
1.785
2.081
1.644
1.700
2.033
Group 2
1965
1.533
1.623
2.945
1.841
1.872
1.917
Group 3
1968
1.694
1.805
3.147
1.776
2.158
Total 10.612
11.731
10.580 32.923
An analysis of variance is carried out to test the hypothesis of equal
means between three groups.
24
-------
ss
MS
Between groups
Within groups
Total
0.332
3.098
3.425
2
14
16
0.166
0.221
0.751
F.95 (2, 14)=3.74
Since F< F.Q5 (2, 14), we conclude that at the level of significance
a=0.05 we cannot reject the null hypothesis HQ: y -j_=y 2=p 3. This means that
there is not enough evidence to reject the hypothesis that the generation
rates in 1958, 1965 and 1968 came from the same population with mean y un-
known at the 0.05 significance level. Details of the computation are pres-
ented in the Appendix.
2. The quantity of solid waste generated in 1971 computed by the EPA
material flow approach is 113.398 million metric tons . It was estimated
that the increase in solid waste from 1967 to 1971 was 11 percent , the
quantity of solid waste generated in 1967 is then 102.16 million metric tons,
or 1.417 Kg per capita per day. From data in Table 7 reproduced above, we
can compute:
sample mean x = 1.935
sample standard deviation s = 0.463
We now want to test the null hypothesis that the sample comes from a
population with mean
that y > y :
y •£ y
= 1.417, against the alternative hypothesis
o •
a:
1.935-1.417
= 4.613
S//n 0.463//17
Since t > t.g5 (16) = 1.746, the null hypothesis is rejected.
Composition
Consider the composition of solid waste as an
random vector (P=8):
1
C2
;•
X =
where: x^ is the percent of paper
X2 is the percent of glass
X3 is the percent of plastics, rubber and leather
X4 is the percent of metal
X5 is the percent of textile
X6 is the percent of wood
Xy is the percent of food waste
8-dimension multinormal
25
-------
Xg is the percent of yard waste
Also, consider a sample including the 24 values of X shown in Table 16.
Some inferences about the composition of solid waste can be made as follows.
1. To test for the homogeneity of solid waste, we divide arbitrarily
the data set into 2 groups. Group 1 is composed of data relative to the fol-
lowing states: Tennessee, Ohio, Pennsylvania, New Jersey, New York, Virginia,
and Michigan. Group 2 is composed of data relative to other states
We carry out a one-way multivariate analysis of variance to test the hy-
pothesis that the mean yj_ is equal to the mean y2 of group 2.
H0: yi=y2
HA:
where:
W12
^22
y2 =
The computer program BMD 12 V is used in this one-way MANOVA (Appendix) .
Since F (calculated) = 2.5802 is smaller than FQ.95 (8, 15) = 2.64, we can-
not reject the null hypothesis at an cc = 0.05 significance level.
2. We now test the hypothesis that the pooled sample (group 1 and group
2 pooled together) came from a population with mean y equal to the composi-
tion vector y0 determined by the material flow approach. The Retelling T
statistic is used in this test:
2 =
T = N (x -yo)
T -
(x -y0 )
where: N is the sample size
X is the vector sample mean
y0 is the vector population mean under null hypothesis (Table 18,
_1 year 1971)
S is the inverse of the sample covariance matrix S.
when the null hypothesis is true, the quantity
F =
N - p
p (N - 1)
T2
has the F distribution with degrees of freedom p and N - p. (In this
case the degrees of freedom are 8 and 16).
dix.
The computer program to compute S, T2 and F is presented in the Appen-
26
-------
Since the observed F = 27.3957 is in excess of F>95 (8, 16) = 2.59, the
null hypothesis is rejected. However, a follow-up analysis (Appendix) rev-
ealed that only the component plastics, rubber, and leather, and the compon-
ent wood (components X3 and Xg of the vector composition) contributed to the
rejection of the null hypothesis, the other six components do not.
We wish to note that the data used in the above statistical analyses
were unsophisticated in several ways. Many composition data belonged to the
years 1966-68; only a few data relative to recent years (1973-76) could be
obtained, and all data on generation rate belonged to the period 1958-68.
The number of data on generation rate was also very limited (the generation
rate was obtainable at only site cities). We did not consider the results of
the 1968 national survey in these analyses because most of them were estimat-
ed figures and thus their accuracy was questionable. If more data were av-
ailable, the reliability of the inferences would increase and some other sta-
tistical inferences would also become feasible. With this in mind, some con-
cluding comparative statements between input and output approach results can
be made as follows.
I/- The per capita generation rate does not change significantly during
the period from 1958 to 1968.
2/- At a significance level of a = 0.05, we can agree with the statement
that the daily generation rate is greater than 1.417 Kg per capita, which is
determined by the input approach. Therefore, as we will use input approach
estimates in subsequent sections, we will remain on the conservative side.
3/- As we cannot reject the null hypothesis that the means of the com-
position of solid waste of the two groups are equal, at a .05 significance
level, we cannot reject the null hypothesis that the solid waste (of the two
groups) is homogeneous.
4/- Although the null hypothesis that the mean of the compositions det-
ermined by the output approach is equal to the composition determined by the
input approach is rejected, only the component "plastic, rubber, and leath-
er", and the component "wood" contribute to the rejection. (the percentage
of plastics, rubber, and leather of the input approach is significantly
greater than that of the output approach).
27
-------
SECTION 4
SOLID WASTE AND ENERGY CONSUMPTION
Energy consumption is associated with post-consumer solid waste in two
ways: the manufacture of products and the handling of solid waste. Unless
otherwise noted, energy consumption refers to gross energy. When many data
are available for the same energy consumption, those values that are out of
line with most other data will be disregarded. Usually, the higher values or
their averages are selected.
ENERGY ASSOCIATED WITH THE MANUFACTURE OF PRODUCTS
Energy is consumed in the manufacture of products that enter the waste
stream after they are used. Table 19 shows that in 1971, the manufacturing
sector consumed 4.7 trillion KWH (net energy) or 27.9 percent of total U. S.
energy requirements. Conceptually, the direct and indirect energy use for a
given product could be derived by means of imput - output analysis, but an
input - output table with the necessary detail on energy use does not exist2".
The energy consumption reported in this paper represents only the energy req-
uired to manufacture each material. Energy needed to produce end products is
not included, except when otherwise indicated.
As reported in Section 3, the principal components of solid waste are paper,
glass, metals (ferrous, aluminum, and other nonferrous), plastics, rubber and
leather, textiles, wood, food waste, yard waste, and miscellaneous inorganics.
A review of energy consumed in the manufacture of each of these materials is
given in subsequent sections.
The Conference Board^o provides various estimates of total energy con-
sumed by the paper industry in 1971: American Paper Institute, 703.2 billion
KWH, Bureau of the Census, 556.7 billion KWH, and Conference Board, 615.3
billion KWH. Interagency Task Force on Energy Conservation29 presents ener-
gy data for 1972. In 1972, 694.4 billion KWH were utilized by some 750 pulp
and paper mills and some 5,000 converting plants; the product was 54.0 mil-
lion metric tons of paper and allied products in 1972 coresponding to 12.9
thousand KWH per metric ton of product. The paper industry is also the larg-
est consumer of oils in the manufacturing sector. In 1971, it used between
175,000 and 192,000 barrels of fuel oil per day29, more than 25 percent of
the total manufacturing consumption. In 1972, paper industry oil usage rose
to about 206,000 barrels per day.
28
-------
TABLE 19. DISTRIBUTION OF ENERGY CONSUMPTION BY SECTOR, 1971
(TRILLIONS OF KWH)*
Purchased fuels
Purchased Fuels plus electricityt
Sector
Household /commercial
Transportation
Industrial
Manufacturing
Non-manufacturings
Electrical generation
Total
KWH
4.184
4.973
5.945
(4.198)
(1.748)
. Ill
20.213
%
20.7
24.6
29,4
20,. 8
8.6
O C Q
Z j . J
100.0
KWH
5.110
4.978
6.629
4.713
1.916
16.717
%
30.6
29.8
39.6
(27.9)
(11.77
100.0
* Source: Reference 29.
t Purchased electricity at its thermal equivalence of 3,412 BTU/KWH.
Gordian Associates^ provides energy consumption per metric ton for four
major paper products (Table 20).
Glass
Glass accounted for 9.7 percent (13.3 million metric tons) of all post-
consumer solid waste in 1971. Of this amount, 12.2 million metric tons were
container and packaging glass12. The glass container industry consumed about
1 percent of the total energy used by the manufacturing sector in 1971. In
absolute terms, it consumed roughly 38.1 billion KWH of fuel and 3.2 billion
KWH of electricity .
The energy consumption per metric ton of glass container was estimated
separately by the Interagency Task Force on Energy Conservation , Gordian
Associates, and Makino and Berry31 and is shown in Table 21.
Steel
The steel industry consumed 19 percent of the total energy consumed by
the manufacturing sector in 197129. The energy consumed in the manufacture
of raw steel and finished steel is estimated variously as shown in Table 22.
Note that 1.516 tons of raw steel is necessary to produce 1 ton of finished
steel32.
Aluminum
29
-------
Total energy used by the aluminum industry in 1971 was 285.8 billion KWH.
This consumption approximated between 5.5 and 6 percent of total energy use
by manufacurings. Of the total energy estimated to have been used in the 2g
primary metals industries, aluminum accounted for approximately 28 percent.
Enery consumption per ton of aluminum was estimated as follows (KWH per
ton) :
U. S. Environmental Protection Agency 86,985
Interagency Task Force on Energy Conservation29 63,027
Gordian Associates3^ 55,956
Midwest Research Institute (quoted by Williams)32 85,597
Hannon (quoted by Williams32) 93,733
Atkins (quoted by Williams32) 73,263
Bravard (quoted by Williams32) 71,810
TABLE 20. ENERGY CONSUMPTION IN MANUFACTURING FOUR PAPER PRODUCTS
(KWH PER METRIC TON)
Item
Total net purchased energy
purchased fuels
purchased electricity
Total jjross purchased energyt
Newsprint
3,766
(2,334)
(1,432)
7,087
Writing
Paper
6,277
(5,579)
(698)
7,901
Corrugated
Container
6,709
(6,574)
(135)
7,020
Folding
Boxboard
6,256
(5,906)
(350)
7,071
* Source: Derived from Reference 30.
t Conversion of net electric energy into primary energy (gross energy) is det-
ailed in Reference 30.
TABLE 21. ENERGY CONSUMPTION IN PRODUCING 1 METRIC TON OF GLASS CONTAINER
(KWH)
Interagency Task Force Gordian
Makino on Energy Associates
and Berry* Conservation (1971) t (1971)^:
Total net purchased energy 5,715
Purchased fuels
Purchased electricity
Total gross purchased energy
4,043
(3,734)
(309)
4.665#
5,644
(5,389)
(255)
5 864
* Source: Reference 31.
t Source: Reference 29.
± Source: Reference 30.
* 3.0138 KWH of primary energy is needed to generate 1 KWH of net electric
energy3 .
Other Nonferrous Metals
30
-------
Copper is taken as representative of other nonferrous metals, all of
which account for only 0.3 percent of post-consumer solid waste. Energy con-
sumption for the production of copper is 32,816 KWH per ton.
TABLE 22. ENERGY CONSUMPTION IN THE MANUFACTURE OF RAW AND
FINISHED STEEL (KWH/METRIC TON).
Source
Gordian Associates-^0
Raw Steel
Finished Steel
Conference Board^°
Interagency Task Force
on Energy Conservation^"
5,631
7,325
Williams
32*
9,288
14,357
*Williams's estimate is the average of three other independent estimates.
Plastics
Energy consumption for production of the four following thermoplastics
are available: low-density polyethylene (LDPE), high-density polyethylene
(HDPE), polystyrene, and polyvinyl chloride (PVC). These thermoplastic
resins represent approximately 83 percent of the production of thermoplastics
and 64 percent of the total production of plastic materials over the period
1970-197230. Total gross energy consumed in producing LDPE, HDPE, polysteryne,
and PVC resins is, respectively, 27,393, 25,972, 34,404, and 24,296 KWH per
metric ton.30 The average figure is 28,016 KWH per metric ton of thermoplas-
tics .
Textiles
Major cellulosic fibers are rayon and acetate. Major non cellulosic,
organic fibers are polyester, nylon, acrylicmodacylic, and olefin fibers.
These fibers are used to manufacture apparel, carpets, blankets etc. that
are found in the waste stream after being used and discarded. Table 23
shows the energy consumed in producing 1 metric ton of these synthetic fibers
in 1973.
Containers
Table 24 shows the energy consumed in producing containers. These fig-
ures include the energy consumed in manufacturing the materials (steel,
glass etc.) and in producing end packaging products (steel cans, glass bottles
etc.)
31
-------
TABLE 23. ENERGY CONSUMED IN THE MANUFACTURE OF
1 METRIC TONE OF SYNTHETIC FIBERS, 1973*
Energy Consumed
Fiber (KWH per metric ton)
Rayon 32,547
Acetate 40,687
Polyester 11,172
Nylon 13,303
Acrylic modacrylic 28,027
Olefin 12,270
Average 23,001
* Source: Foster D. Snell, Inc. Industrial Energy Study of the Plastics and
Rubber Industries. Prepared for the Department of Commerce and the Federal
Energy Office, 1974. Quoted by Energy Task Force on Energy Conservation™.
ENERGY ASSOCIATED WITH THE HANDLING OF SOLID WASTE
The municipal solid waste management system consists of five groups of
unit processes (Figures 2 and 3):
Group 1. Storage and collection.
Group 2. Optional preparatory processes (transfer station, size red-
uction, baling).
Group 3. Transportation
Group 4. Alternative unit processes (composting, incineration, resource
recovery, energy recovery).
Group 5. Disposal methods (sanitary landfilling, millfilling, other
disposal methods).
The energy associated with the handling of solid waste includes the
energy consumed in these five groups of unit processes. Current major ener-
gy consuming functions are collection, transportation and disposal of solid
waste. Only limited and scattered information is available on the energy
consumption of solid waste processing systems (group 2 and 4), but they are
assumed to account for only a small percentage of total energy consumed.
However, as the potential for resource recovery increases because of the ec-
onomics of both material and energy resources, the energy used for recycl-
ing is likely to increase considerably.
Shuster^ has estimated that the total annual fuel consumption involved
in the collection and land disposal of solid waste in the United States is
2.3 billion liters (Table 25). In terms of KWH's the collection function
accounts for roughly 17.0 billion KWH, and the disposal function consumes
32
-------
TABLE 24. ENERGY REQUIRED TO PRODUCE TYPICAL CONTAINERS.*
Type of container KWH required/container
Internal packaging.
16 oz. (0.473 liter) coca cola reternable bottle (0.5 Kg) 2.85
16 oz. (0.473 liter) coca cola nonreturnable bottle (0.3 Kg) 1.71
Half gallon (1.893 liter) returnable milk bottle (1.8 Kg) 5.18
16 oz. (0.473 liter) vegetable jar (0.2 Kg) 1.19
12 oz. (0.355 liter) steel beverage can (0.051 Kg) 1.16
12 oz. (0.355 liter) aluminum beverage can (0.020 Kg) 1.91
Aluminum container (TV dinner) 1.74
16 oz. (0.473 liter) glass bottle (0.209 Kg) 1.16
1 qt. (0.946 liter) glass jar (0.318 Kg) 1.78
Folding box (medium, 0.057 Kg) 0.75
Folding box (large, 0.145 Kg) 1.92
Dept. store box (medium, 0.148 Kg) 2.18
Setup box, small 0.84
Half gallon (1.893 liter) sanitary container (0.064 Kg) 0.88
Molded pulp tray (size 6, 0.020 Kg) 0.45
Styrofoam tray (size 6, 0.068 Kg) 0.25
1 qt. (0.946 liter) polypropylene bottle 3.20
1 qt. (0.946 liter) PVC bottle 3.80
1 qt. (0.946 liter) PE bottle 2.90
Wooden berry basket 0.08
Hampers 1.63
Stove basket 1.59
12" x 12" x 8" appliance corrugated box (0.241 Kg) 3.12
Shipping containers.
12" x 16" x 20" corrugated box (0.863 Kg) 9.80
Wireband box (1.044 Kg) 2.30
Wooden crate (nailed) 10.00
* Source: Reference 31.
roughly 6.6 billion KWH. Shuster does not indicate the year for which these
estimates were provided, but because many of the data sources were dated in
1972 and 1973, it is assumed that these estimates can be applied to the year
1971. Energy consumption is then 150 KWH per metric ton for collection and
58 KWH per metric ton for land disposal, assuming that solid waste collected
and disposed of in 1971 is 113.2 million tons (Table 9).
The energy consumption for Los Angeles solid waste is 7.926 liters of
diesel fuel per metric ton of refuse (or 85 KWH/metric ton) for collection
and 0.303 liters of diesel fuel per metric ton of refuse (or 4 KWH/metric
ton) for disposal. (private communication. Jack M. Betz, Director, Bureau
of Sanitation, City of Los Angeles. 1976).
33
-------
OJ
T = Transportation
Preparatory
Processes
Storage
and
Collection
Alternative
Unit
Processes
Figure 2. Simplified Municipal Solid Waste System
-------
to
Ui
Figure 3. Complete Solid Waste Management System
-------
O "1
Makino and Berry made the following estimates of solid waste energy
requirements (for Chicago, Illionois):
Collection 82.7 KWH/metric ton
Incineration 26.1 KWH/metric ton
Transport and disposal at landfill 80.8 KWH/metric ton
Reinhardt and Ham^5 estimated the energy consumption in sanitary land-
filling of milled refuse as follows
Processor and end-loader 25.5 KWH/metric ton
Transport to landfill 77.1 KWH/metric ton
Maintain landfill 22.6 KWH/metric ton
Total 125.2 KWH/metric ton
TABLE 25. FUEL CONSUMED ANNUALLY IN THE COLLECTION AND LAND DISPOSAL OF
SOLID WASTE (LITERS /YEAR) *
Amount of fuel consumed
Type of fuel
Residential sector
Commercial sector
Subtotal
Collection
Diesel
Gasoline
219,983,254
244,155,210
390,850,493
840,841,005
610,833,747
1,084,996,215
Land disposal
Diesel
615,790,734
* Source: Reference 34.
Hannon36 estimated that the energy requirement to transport solid waste
to a sanitary landfill and to maintain the landfill is 145.5 KWH per metric
ton. The energy consumption of open dumping was estimated at 97 KWH per met-
ric ton.
The average energy consumption for three compost systems (Metro compost
system, International Disposal Corporation compost system and Fairfield-
Hardy compost system)- is as follows:
400 ton/day plant: 33,768 KWH/day or 93 KWH/metric ton
200 ton/day plant: 24,384 KWH/day or 134 KWH/metric ton
It seems reasonable, then, to estimate the average energy consumption of
all compost systems to be 114 KWH per ton.
o o
Williams^ provided information on energy consumed in recycling metals
from solid waste. The energy required to recycle steel, aluminum, and copper
is, respectively, 1,978, 2,784, and 1,963 KWH per metric ton.
Makino and Berry^l provided data on energy consumed in recycling pack-
aging materials. Paper that has been recycled consists of mixed waste paper
(largely clean commercial waste, 27 percent; used corrugated boxes, 26
36
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percent; and newspaper, including overruns, 20 percent). The estimated en-
ergy consumption for the entire process is as follows:
Truck collection and hauling 176 KWH
Baling and handling 264 KWH
Freight to mills 165 KWH
Pulping 463 KWH
Total per metric ton of recycled pulp 1,068 KWH
A similiar paperboard from virgin material would require 2,119 KWH to
produce-^.
Plastics are very difficult to recycle because of the task of separating
paper from plastics and different kinds of resins. However if the tech-
nology is ever developed to separate plastic resins in fairly homogeneous
states, recycling would be expected to cost 586 KWH per ton of plastic proc-
essed, compared with the 14,588 KWH per ton needed to produce plastic from
virgin materials^!.
The recycling of glass to use as cullet offers no energy savings over
using glass sand because glass making is primarily the melting of raw mater-
ials. Hannon concluded that, given present technology, recycling glass
from solid waste for bottle making would cost at least three times the energy
required to start from virgin resources. However, if glass containers are
voluntarily collected, the only costs are those for transportation (about 231
KWH per metric ton), melting, and forming the glass (4,996 KWH per metric
ton). There would be a savings of up to 485 KWH per ton in the material ac-
quisition. This would lower the overall cost of the finished bottle less
than 1 percental.
The average energy consumed to collect, transport, and dispose of 1 ton
of solid waste can be estimated as follows.
The energy required for collection can be estimated by taking the aver-
age of data for Los Angeles (85 KWH per metric ton) and Chicago (82.7 KWH per
metric ton), which is 83.9 KWH per metric ton.
The energy consumed at the incinerator (26.1 KWH per metric ton) and
later to transport the residue to the landfill and to maintain the landfill
(80.8 KWH per metric ton) is 106.9 KWH per metric ton. About 8 percent of
the total solid waste is incinerated yearly-5 .
The energy consumed for composting is 114 KWH per metric ton. Compost-
ing and hog feeding accounted for 2 percent of total solid waste^7. Another
data source showed that 18 composting plants in the United States processed
745,205 metric tons of solid waste in 196927. We can assume that composting
processes about 1 percent of the total solid waste yearly.
The energy consumed at a sanitary landfill is estimated to be an average
of 99.7 KWH per metric ton^S (excluding energy for reduction of refuse, 23.1
KWH per metric ton, which is strictly for mill filling), and 130.9 KWH per
37
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metric ton 36, or 115.3 KWH per metric ton. About 5 percent of the total
solid waste is disposed of in sanitary landfills
The energy for recycling is summarized as follows for 1971:
Millions of KWH/Year
Paper 6,798,000 ton/year x 1,068 KWH/ton= 7,260.3
Aluminum 20,000 ton/year x 2,645 KWH/ton- 47.6
Steel 127,000 ton/year x 1,978 KWH/ton= 251.2
Glass 275,000 ton/year x 5,227 KWH/ton= 1,045.4
Total 8,604.5
Total recycled material in 1971 is 7.376 million metric tons, or about 6
percent of total solid waste. The energy consumed to recycle is then 1,167
KWH per metric ton of recycled material.
Open dumping accounts for the remaining 80 percent of the total solid
waste collected. Energy consumed is 97 KWH per metric ton.
The national energy consumed to collect, process, transport and dispose
of 1 metric ton of solid waste is then:
KWH/ton
Collection and incineration (82.7 + 106.9) 8% = 15.168
Collection and composting (82.7 + 114.0) 1% = 1.967
Collection and recycling (82.7 + 1,167.0)6%= 74.982
Collection and sanitary land filling .(82.7 + 115.3) 5% = 9.900
Collection and open dumping (82.7 + 97.0) 80%= 143.760
Total average 245.777
In subsequent sections, the rounded figure of 246 KWH per metric ton will
be used.
38
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SECTION 5
REDUCING REFUSE TO CONSERVE ENERGY
PATHS OF ENERGY CONSERVATION IN SOLID WASTE MANAGEMENT
Any reduction in refuse generation implies savings of energy that would
otherwise be consumed in handling the waste, no matter how good the manage-
ment. Many recommendations have been made for improving solid waste manage-
ment practices to optimize the energy consumed. For example, Shuster pro-
posed 11 short-term steps and three long-term steps to conserve fuel in solid
waste management.
Part, but by no means all, of the residual energy in solid waste could
be recovered by material recycling. The Midwest Research Institute^2 estima-
ted that 85 percent of steel, 65 percent of aluminum, and 75 percent of cop-
per is potentially recycleable. Plastics are very difficult to recycle
and recycling of glass offers no energy savings 31,36^ Qn t^ie other hand, a
significant amount of energy is required to recycle and to process and dis-
pose of unrecovered materials; also, the energy consumed to produce con-
sumer's end products connot be recovered.
Energy recovery processes can likewise conserve only a portion of the
total energy associated with the waste.
The optional alternative, then, is to look for incentives aimed at
source reduction, which has a number of advantages for the national economy
and environment. In addition to energy conservation, source reduction helps
to conserve material, manpower, and land necessary for disposal and to al-
leviate the environmental impacts of handling a. large amount of refuse.
ENERGY CONSERVATION POTENTIALS
According to EPA (Table 11), the 1975 gross solid waste generated in
the United States was 123.5 million metric tons. Of this figure, 116.3 mil-
lion metric tons were disposed of and 7.2 million tons of material were re-
cycled. The energy associated with this quantity of refuse is the sum of
two categories: the energy consumed in the manufacture of 116.3 million
metric tons of disposed of materials, and the energy consumed in the handl-
ing of 123.5 million metric tons of generated refuse.
The energy consumed in manufacturing disposed of materials in 1975 is
estimated in Table 26. The energy required to produce consumer's end pro-
ducts is not included (except for glass containers) because of the unavail-
39
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ability of data. The energy embodied in each metric ton of disposed of ref-
TABLE 26. ENERGY CONSUMED IN MANUFACTURING DISPOSED OF REFUSE, 1975.
Energy consumed
Quantity
Material
Millions
(millions of metric tons)* KWH/metric ton of KWH
Paper
Glass
Ferrous metal
Aluminum
Other nonferrous metals
Plastics
Rubber
Textiles
T T^-i n J
wood
__, ,
rood waste
TT J
Yard waste
T J_l-
Leather
> , . _
Misc. Inorganic
Total
33.7
12.1
9.8
0.8
0.4
4.0
2.0
1.9
/. /.
4 . 4
on ~7
ZL) . /
o o £
Z J. 0
i n
_l_ . U
1—i
. /
116.3
7>270a
5,86430
14,35732
82,278b
32,81030
28,016C
38,27230
23,001d
1
un Known
-i
un ten own
-i . • "U 1
neg_LigiD_LB
-1 . . -t -t
negxigxD J.G
1 • * "U 1
negngi_D_i_e
244,999
70,954
140,699
65,622
13,124
112,064
76,544
43,702
767,708
* See Table 9. Assume the quantity of rubber is double that of leather.
a-Average of four types of paper products in Table 20.
b-Average of five estimates made by U.S. EPA, Midwest Research Institute,
Hannon, Atkins and Bravard (References 32, 33).
c-Average of 4 types of thermoplastics3^.
d-Average of 6 types of synthetic fibers (Table 23)
TABLE 27. ENERGY CONSUMED IN MANUFACTURING DISPOSED OF REFUSE, 1971-75.*t
Energy consumed (millions of KWH)
Material
Paper
Glass
Ferrous metals
Aluminum
1971
258,085
63,918
137,827
57,595
1972
279,895
67,436
140,699
65,822
1973
291,527
70,368
143,570
74,050
1974
285,711
68,609
149,313
74,050
1975
244,999
70,954
140,699
65,622
Other nonferrous
metals
Plastics
Rubber
Textiles
13,124
106,461
76,544
36,802
13,124
120,469
79,223
36,802
9,843
126,072
84,198
39,102
9,843
114,866
94,532
43,702
13,124
112,064
76,544
43,702
Total
KWH/metric ton
of refuse
750,356 803,470 838,730 840,626
767,708
6,629 6,798 6,875 6,885 6,601
Average energy consumed (1971-75) = 6,758 KWH/metric ton of refuse.
* For data on quantity of material, see Table 9.
t For data on energy consumed in manufacturing 1 metric ton of each material,
see Table 25.
use in 1975 is: 767,708 x 106/116.3 x 106=6,601 KWH/metric ton.
40
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TABLE 28 - TOfAL ENERGY CONSUMED IN THE SOLID WASTE MANAGEMENT, 1971-75.
Solid waste (millions of metric ton)
Year Gross gc
1971 120.
1972 126.
1973 130.
1974 130
1975 123
Derated* Net disposed of
6
, 2
,7
.6
.5
113.
118,
122,
122
116
.2
,2
.0
.1
.3
Energy
consumed yearly (millions of KWH/year)
Handling gross
generated solid waster
29
31
32
32
30
,668
,045
,152
,128
,381
Energy consumed per
Manufacturing net metric ton of generated refuse
disposed of materials// Total (KWH/metric ton)
750,
803,
838,
840,
767,
356
470
730
626
708
780,
834,
870,
872,
798,
024
515
882
754
089
6
6
6
6
6
,468
,613
,663
,683
,462
Sum of net disposed of refuse (Table 9) and recycled material (Table 15).
t Table 9.
f 246 KWH per metric ton (see Section 4)
It Table 26.
-------
TABLE 29. U.S. SOLID WASTE GENERATION RATES, 1971-75.* +
Year Kg/c.apita per year Kg/capita per day
1971
1972
1973
1974
1975
585
606
623
618
580
1.603
1.660
1.707
1.693
1.589
* The quantity of gross discards in the sum of net solid waste disposed of
(Table 9) and materials recycled (Table 15).
t The population is based on Table 1.
TABLE 30. POTENTIALS OF ENERGY SAVINGS THROUGH SOURCE REDUCTION, 1975.
Refuse reduction Energy savings
% Reduction (millions of metric ton)* (millions of KWH) t
10
20
30
39. 8 t
12.4
24.7
37.0
49.2
79,809
159,618
239,427
317,639
* Gross discards in 1975 is 213.5 million metric tons (Tables 9 and 15)
t Total energy consumed in solid waste management in 1975 is 798,089 million
KWH (Table 28).
t A refuse reduction of 39.8 percent would decrease the refuse generation
rate in the U.S. to that of West Germany (highest generation rate in West-
ern Europe).
By a similar computation method, the energy consumed in manufacturing
disposed of refuse from 1971 to 1974 was computed and shown in Table 27 along
with the results for 1975. The average energy residual (energy consumed in
manufacturing the components of solid waste) embodied in 1 metric ton of ref-
use, 1971-75, was computed to be 6,758 KWH/metric ton.
Average energy consumption required to collect, process, transport, and
dispose of 1 metric ton of gross discards was estimated earlier at 246 KWH.
The energy needed to handle the solid waste generated in 1971-1975 was es-
timated and shown on Table 28, along with the total energy required for the
solid waste management, which is the sum of the energy required for manufac-
turing and handling the waste.
Note that the total energy consumed in the management of solid waste in
1975 is 798,089 million KWH (Table 28), which is equivalent to 82.5 billion
liters of gasoline, or 74.7 billion liters of diesel fuel, or 3.86 percent of
total U.S. energy consumption in that year (20.671 trillion KWH1).
The United States generates more refuse than any other country in the
world. Following are the generation rates of Western countries3:
Kg/capita per year
Netherlands 206
Italy 211
Switzerland 249
France 272
42
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England 317
West Germany 349
The U.S. generation rates for 1971-74 are shown in Table 29. These fig-
ures are based on EPA material flow estimates, which are conservative esti-
mates, as we have indicated in Section 3. Suppose that American consumers
would reduce their refuse generation, the energy savings would be quite sig-
nificant. Table 30 shows the potentials of energy savings through reduction
in refuse. These figures represent hypothetical savings corresponding to
various levels of reduction. Note that a reduction of 39.8 percent would
bring the generation rate in the United States to that of West Germany, the
highest generation rate of Western Europe.
SETTING PRIORITIES FOR REDUCING REFUSE
The highest priority for refuse reduction should be attached to the most
energy intensive material. Table 31 thus establishes the list of high prior-
ity materials to be reduced in the waste stream.
On the other hand, if we consider the total disposed of refuse gener-
ated in 1975, the total amount of energy embodied in aluminum (65.6 billion
KWH) is less than the total amount of energy embodied in ferrous metal (140.7
billion KWH) even though aluminum is more energy intensive than ferrous met-
al. Thus, based on this total energy (instead of energy per metric ton of
material) we should consider the priority list found in Table 32.
REDUCTION IN REFUSE: A JOINT INITIATIVE
The consumers do not bear alone the responsibility for the high rate of
refuse generation in the United States. Indeed, from birth citizens have
learned from society luxurious habits of consuming and discarding goods.
Everyone believes that used products, especially packaging products, are man-
ufactured to be thrown away. Tossing things into trash cans is not only a
matter of course, but an inevitable decision, since that appears to be the
only way to get rid of most items.
On the other hand, manufacturers alone cannot be blamed for producing
material and energy-consuming products that are discarded after use, because,
in the business world, the production option that most benefits the company
will be chosen.
The effort to reduce refuse generation must be a joint one involving
government policy makers, manufacturers, and the consumers. Responsible pol-
icy makers can initiate wise practices governing the consumption of energy
and the production of consumer goods, including packaging products. Industry
can choose manufacturing and marketing alternatives that will best conserve
materials and energy. And finally, consumers can contribute through volun-
tary undertakings, such as source separation, reuse of products (paper and
plastic shopping bags etc.) and use of returnable beverage containers. Con-
sumers should particularly avoid generating unnecessary refuse for the sake
of convenience.
43
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TABLE 31. PRIORITIES FOR ENERGY - INTENSIVE MATERIALS IN THE WASTE STREAM.
Energy intensiveness
Priority
1
2
3
4
5
6
7
8
Material
Aluminum
Rubber
Copper
Plastics
Textiles
Ferrous metal
Paper
Glass
(KWH/metric
82,278
38,272
32,810
28,016
23,001
14,357
7,250
5,864
ton)*
* Sources: See Table 25.
TABLE 32. PRIORITIES FOR MATERIALS IN THE WASTE STREAM BASED ON TOTAL ENERGY
Priority
1
2
3
4
5
6
7
8
Material
Paper
Ferrous metal
Plastics
Rubber
Aluminum
Glass
Textiles
Copper and other
non ferrous metals
Total energy in the
stream* (million of
244,999
140,699
112,064
76,544
73,124
70,954
43,702
13,124
waste
KWH)
1975 (Table 26)
Examples of incentives to reduce refuse at the national policy level are
as follows:
1. Institute a tax on disposable products to discourage their use.
2. Institute a tax on new packaging products to promote their reuse.
3. Institute a tax to discourage high energy consuming products and
favor low energy consuming competitors.
4. Require a mandatory deposit and free repair policy during the life-
time of a durable product (household appliances, lawn mowers etc.).
Such requirement would be imposed on manufacturers or their local
agents, and the lifetime of a product would be determined by the
manufacturer. When the lifetime of a product is finished, it would
be returned to the manufacturer for complete overhauling or recycl-
ing, and the deposit would be returned to the consumer.
5. Require a mandatory deposit for reusable products such as beverage
containers.
6. Require mandatory source separation to facilitate reuse of products
and material recycling. For example, each household might have sev-
eral trash cans painted with different standard colors to differen-
tiate refuse components.
7. Establish product reuse centers and material recycling centers.
8. Increment pricing of solid waste collection and disposal.
44
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Examples of incentives to reduce refuse at the manufacturing level are:
9. Redesign products to reduce the amount of material per product (dur-
able goods, containers, and shipping packaging).
10. Increase lifetime of products.
11. Promote and facilitate reuse by fabricating both standard durable
goods and standard packaging products.
12. Reuse packaging products. Damaged packaging products, especially
those for shipping, can be repaired and reused.
13. Standarize products to promote reuse of undamaged components.
14. Reduce newspapers, magazine, and book overruns by careful surveys
and analyses of demand.
15. Reduce catalogs, directories, and commercial printing.
Examples of incentives to reduce refuse at the consumer level are:
16. Practice source separation to facilitate recycling and reuse.
17. Return discarded consumer and packaging products to local agents of
manufacturers or central collection warehouses to facilitate reuse
and/or recycling.
18. Cooperate with other government and/or manufacturer incentives to
reduce refuse.
19. Refrain from discarding products when they are still usable.
20. Carry out voluntary steps to reduce refuse generation; think of the
implications of refuse generation when purchasing products.
POSSIBLE REDUCTIONS AND ASSOCIATED ENERGY SAVINGS
The following suggestions are based on the post consumer solid waste of
1975 by detailed product category as shown in Table 11.
Durable Goods
Major Appliances and Miscellaneous Durable Goods—
Major appliances and miscellaneous durables account for 8,689,000 metric
tons of refuse (Table 11). Of this figure, 5,222,000 metric tons are ferrous
metals, 81,000 metric tons are aluminum, and 300,000 metric tons are other
nonferrous metals. Ferrous metal is the difference between total ferrous
metal (which is the sum of disposed of ferrous metal (Table 10) and recycled
ferrous metal (Table 15), and steel cans (Table 11).
Exact realizable refuse reduction and energy savings are unknown, but
energy savings associated with various assumed levels of reduction can be
estimated as follows.
10 - percent reduction (868,900 metric tons of refuse) Millions
of KWH
Ferrous metal. . . .522,200 metric tons x 14,357 KWH/metric ton=7,497.2
Aluminum 8,100 metric tons x 82,278 KWH/metric ton= 666.5
Other nonferrous . . 30,000 metric tons x 32,810 KWH/metric ton= 984.3
TOTAL energy savings 9,148.0
45
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Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
10 868,900 9,148
20 1,737,800 18,296
30 2,606,700 27,444
50 4,344,500 45,740
Rubber Tires—
Some 1.6 million metric tons (Table 11) of rubber tires were discarded
in 1975. There are three types of car tires: bias, belted bias and radial
ply. The most inexpensive type should provide satisfactory performance for
15,000 to 20,000 miles, and the most expensive type (radial) should last for
more than 40,000 miles. Estimates show that if all tires in original eq-
uipment were radial an annual 38 percent reduction in tire waste (616,740
metric tons) would result. If replacement tires were all radial, the total
on
waste reduction could be as high as 50 percent. y
Energy savings corresponding to various levels of reduction are as fol-
low (38,272 KWH/metric ton of rubber30).
Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
10 162,300 6,212
20 324,600 12,424
30 486,900 18,636
40 649,200 24,848
50 811,500 31,060
Nondurable Goods, Except Food
Newspapers—
Newspaper waste accounts for 8.0 million metric tons in 1975. The en-
ergy consumed in producing 1 metric ton of newsprint is 7,087 KWH/ metric ton
(Table 20) . If reduction could be made (one possibility is by reducing
overruns), energy savings would be achieved.
Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
5 401,350 2,844
10 802,700 5)689
15 1,204,050 8,533
Books, Magazines and Office Paper—
Some 2.8 million metric tons of books and magazines and 4.7 million
metric tons of office paper are generated annually. The energy consumed in
manufacutring writing paper is 7,901 KWH per metric ton. One possibility to
reduce this type of solid waste is by reducing overruns. Energy savings
46
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would be as follows.
% Reduction
5
10
15
Refuse reduction
(metric tons)
139,450
278,900
418,350
Energy savings
(millions of KWH)
1,102
2,204
3,306
Catalogs and directories are classified under this category of waste
paper. They include such items as telephone books, mail-order catalogs, and
business and professional directories. In 1973, catalogs and directories was
estimated at 861,650 metric tons . If we assume an annual increase of 1 per-
cent, the 1975 figure would be 878,882 metric tons. Such publications are of
transitory value and are usually replaced annually. Energy savings could be
realized if these periodical publications were completely replaced biennially,
or even every 3 years and updated by supplements every other year when nec-
essary. The resulting reduction could amount to 40 percent. Energy savings
associated with various levels of reduction are as follows.
% Reduction
10
20
30
40
Refuse reduction
(metric tons)
87,888
175,776
263,664
351,552
Energy savings
(millions of KWH)
694
1,389
2,083
2,778
Also classified under this category is the so-called commercial print-
ing, which includes direct-mail advertising, booklets, brochures, leaflets,
reports, promotional materials, forms, etc. In 1966, commercial printing ac-
counted for some 1.8 million metric tons of refuse—more than one third of
printing paper consumption for that year.^0 Commercial printing was estimated
at 2.6 million metric tons for 1973.^ With a 5 percent annual increase, the
1975 figure would be 2.9 million metric tons. Energy savings corresponding
to various levels of reduction in commercial printing ate as follows.
Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
30
50
70
90
Paper Plates, Cups—
870,000
1,450,000
2,030,000
2,610,000
6,874
11,456
16,039
20,622
1 provides comparative energy requirements for paper and reusable
plates. Paper plates (manufactured, used once, and discarded) require 1,641
KWH per 10,000 plates (or 16,2.73 KWH/metric ton). Reusable plates (manufac-
tured, used once, and washed once—each plate can be used and washed 6,000
times before being discarded) require 379 KWH per 10,000 plates. The energy
ratio (paper/reusable) is 4.340/1 and the weight ratio is 132/1. This ratio
is based on one use and is computed as follows. One paper plate weighs 0.010
Kg and can be used one time; one reusable plate weight 0.454 Kg and can be
47
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used 6,000 times. Therefore, the weight ratio (paper/reusable) corresponding
to one use is:
0.010 =
0.454/6,000
In 1975, paper plates and cups accounted for 440,000 metric tons of solid
waste. If these had been replaced by reusable ones, the energy savings and
reductions in refuse would have been as shown (16,273 KWH/metric ton of paper
plates).
Refuse reduction Energy savings
% Replacement (metric tons) (millions of KWH)
50 218,000 825
80 349,000 1,320
100 437,000 1,650
Tissue Paper—
In 1975, tissue paper amounted to some 2.0 metric tons (Table 11). Four
major categories of tissue paper are: toweling, table napkins, facial tissue,
and toilet tissue. The former three accounted for 55 percent and the latter
accounted for 42 percent of total tissue paper in 1966.^0 Assume these per-
centages held true in 1975, and assume the energy consumed to manufacture tis-
sue paper is equal to that for newsprint. If reduction of toweling, table
napkins, and facial tissue could be achieved, resulting energy savings would
be as shown.
^Reduction of % Reduction of Energy savings
three categories of total Refuse reduction (millions
tissue paper tissue paper (metric tons) of KWH)
20 11 222,970 1,580
40 22 445,940 3,160
Clothing—
Reduction in discarded clothing would result in energy savings as es-
timated in the following (Energy consumed to produce textile is 23,001 KWH
per metric ton).
Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
10 113,400 2,608
20 226,800 5,216
30 340,200 7,824
Containers and Packaging
48
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Glass Beverage Containers—
Based on 1972 data, refillable containers accounted for about 20 percent
of all glass beverage containers.^-*- If it is assumed that this proportion
held true in 1975, total refillable containers for that year would have ac-
counted for 1.2 million metric tons and the throw-away glass containers would
have accounted for 4.6 million metric tons. (Table 11 shows total beverage
glass container discards in 1975 to be some 5.8 million metric tons).
O £
Hannon-50 computed the energy ratio of the throw-away system to the ref-
illable system (15 refills) to be 4.6. A shift to 100 percent refillable bot-
tles would result in an energy savings of
4.604 x 106 x 5,864 x -f^ = 21,129 million KWH
4. 6
The average unit weight is 0.454 Kg (1.0 lb.) for the 0.473 liter (16 oz)
returnable bottle, and 0.298 Kg for the 0.473 liter throw-away bottle.36 One
returnable bottle can be used 15 times before being discarded. The refuse
reduction is then
4,604,000 - x'6298)/°454 = 4>136>°°° metric tons
The energy savings and refuse reduction corresponding to a usage level
of 50 percent for refillable bottles are estimated in the following:
Energy savings: 21,129 x 50% = 10,565 million KWH
Refuse reduction: 4,126,000 x 50% = 2,158,000 metric tons
Steel Beverage Cans—
The energy requirement per lb. of steel beverage cans is 37,640 BTU, or
25,318 KWH per metric ton. The energy associated with 1.2 million metric tons
of steel cans generated in 1975 is then
1.215 x 106 x 25,318 = 30,761 million KWH
The energy ratio of throw-away cans versus 15-trip refillable bottles
both 12 oz. (0.355 liter) was determined to be 2.9136. A shift from steel
cans to refillable bottles (both 12 oz.) would result in the following sav-
ings.
100-percent replacement
Energy savings: ,
30,761 - 30,761 x ^~- =20,190 million KWH
Refuse reduction:
(weight of 1 steel can is 0.05119 Kg; weight of 1 refillable bottle
is 0.45359 Kg)
1,215,000 - 15 x 0*05119/0.45359 = 497,266 metric tons
49
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Refuse reduction Energy savings
% Replacement (metric tons) (million KWH)
100 497,266 20,190
70 348,086 14,133
50 248,633 10,095
Aluminum Beverage Cans—
The all-aluminum cans are 33 percent more energy consuming than the steel
cans,36 therefore, the energy ratio of throw-away aluminum can versus 15-trip
refillable glass bottles (both 12 oz or 0.355 liter) is 3.88. A 100-percent
shift from aluminum cans to refillable glass bottles in 1975 would have resul-
ted in savings of
? Q Q
462,000 metric tons x 82,278 KWH/metric ton x y^ = 28,215 million KWH
Energy savings
% Replacement (millions of KWH)
100 28,215
80 22,572
50 14,108
Because one aluminum can weighs approximately 0.198 Kg, only a shift to
returnable glass bottles (1 Ib or 0.454 Kg) with at least a 25-trip life
would result in a reduction in refuse tonnage. But in any case, the reduc-
tion in refuse volume would be considerable.
Packaging Paper—
Packaging paper constitutes 53 percent of all containers and packaging
materials found in the waste stream. In 1975 discarded packaging paper ac-
counted for some 21.0 million metric tons of paper, which can be classified
as corrugated paperboard or containerboard (11.3 million metric tons), other
paperboard (5.0 million metric tons), and flexible packaging paper (4.7 mil-
lion metric tons).
Corrugated paperboard—Corrugated paperboard constitutes the most im-
portant fraction of all packaging paper. Almost all corrugated paperboard is
used for boxes or interior packings, and most of it is very suitable for
reuse, since usually it is not damaged during use. The energy savings cor-
responding to different levels of waste reduction are as follow.
Refuse reduction Energy savings
% Reduction (metric tons) (millions of KWH)
20 2,271,000 15,944
30 3,407,000 23,916
60 6,813,000 47,832
Paper milk containers—In 1975, some 1.4 million metric tons of paper
sanitary containers were discarded; of this figure milk cartons accounted for
41 percent 3 ' or 584,000 metric tons. Hannon36 computed the energy ratio
50
-------
for the throw-away paper versus the 33-trip glass returnable milk delivery
system to be 1.43. One half-gallon (1.892 liter) plastic coated paper con-
tainer weighs 0.127 Kg and one half-gallon glass returnable container weighs
0.908 Kg. A 100-percent shift from throw-away paper milk containers to ret-
urnable glass containers would result in an energy savings of (energy con-
sumed to produce paper containers is 13,183 KWH per metric ton)31
584,000 x 13,183 x
= 5,384 million KWH
The reduction in refuse tonnage is
584,000 - 584,000 x
°'9°8
~
X o o
= 457,000 metric tons
% Reduction
20
40
60
Refuse reduction
(metric tons)
91,000
183,000
274,000
Energy savings
(millions of KWH)
1,077
2,154
3,230
Grocery paper sacks — Paper sacks are made from unbleached kraft paper and
used as grocery bags. These sacks come in a variety of sizes, all of which
are used once and discarded although they are usually undamaged and look like
new. If these paper sacks were reused once or twice, considerable amounts of
energy and material could be saved. In 1966, bag paper accounted for 1.5 mil-
lion metric tons of refuse (of a total of 4.3 million metric tons of flex-
ible packaging paper). If a 4.1 percent annual increase is assumed^ , the
1975 figure is 2.2 million metric tons.
levels of reduction are as follow
Savings corresponding to different
% .Reduction
30
50
60
Refuse reduction
(metric tons)
660,000
1,100,000
1,320,000
Energy savings
(millions of KWH)
4,633
7,722
9,264
Shipping paper sacks — Shipping sacks are used to carry powder and gran-
ular products such as fertilizers, cement, carbon black, feeds, etc. Energy
savings effected by reduction in discards can be estimated in a manner simila:
to that for grocery sacks.
Quantity of shipping sacks in 1966: 900,000 metric tons
Quantity of shipping sacks in 1975 (2% increase): 1,075,000 metric tons
% Reduction
20
30
50
Refuse reduction
(metric tons)
215,000
323,000
538,000
Energy savings
(millions of KWH)
1,509
2,267
3,777
These possibilities for reducing refuse and saving energy are shown in
Table 33.
51
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TABLE 33. POSSIBILITIES FOR REFUSE REDUCTION AND ENERGY SAVINGS, 1975.
bo
Waste Source
Major appliances and misc. durable goods
Rubber tires
Newspaper
Books and magazines
Catalogs and directories
Commercial printing
Paper plates, cups
Tissue paper
Clothing
Glass beverage containers
Steel beverage cans
Aluminum beverage cans
Corrugated paperboard
Paper milk containers
Grocery paper sacks
Shipping paper sacks
Total
Plus energy saved in refuse handling
Grand total (rounded)
% Reduction
30
40
10
10
40
70
50
22
30
50
70
80
30
40
60
30
Refuse reduction
(metric tons)
2,606,700
649,200
802,700
278,900
351,552
2,610,000
218,000
445,940
340,200
2,158,000
348,086
negligible
3,407,000
183,000
1,320,000
323,000
16,042,278
16,000,000
Energy savings
(millions of KWH)
27,444
24,848
5,689
2,204
2,778
20,622
825
3,160
7,824
10,565
14,133
22,572
23,916
2,154
9,264
2,263
180,261
1 71 Q
j , / iy
184,000
-------
REFERENCES
1. U.S. Bureau of the Census, Department of Commerce. Statistical Abstract
of the United States, 1977 (98th edition). 1,048 pp.
2. The Science and Public Policy Program, University of Oklahoma. Energy
Alternatives: A Comparative Analysis. 1975. 627 pp.
3. Pavoni, J. L., J. E. Herr, Jr., and D. J. Hagerty. Handbook of Solid
Waste Disposal. Van Nostrand Reinhold Company, New York, 1975. 549 pp.
4. Black, R. J., A. J. Muhich, A. J. Klee, H. L. Hickman, Jr., and R. D.
Vaughan. The National Solid Waste Survey, an Interim Report. U. S.
Department of Health, Education and Welfare, 1968, Second printing 1970,
53 pp.
5. Muhich, A. J., A. J. Klee, and C. H. Hampel. 1968 National Survey of Com-
munity Solid Waste Practices. U. S. Department of Health, Education and
Welfare, Public Health Service Publication No. 1866, 1969.
6. Muhich, A. J., A. J. Klee, and P. W. Britton. Preliminary Data Analysis-
1968 National Survey of Community Solid Waste Practices. U. S. Department
of Health, Education, and Welfare, Public Health Service Publication No.
1867, 1968. 483 pp.
7. Smith, F. A. Comparative Estimates of Post-Consumer Solid Waste. EPA/530/
SW-148, U. S. Environmental Protection Agency, Cincinnati, Ohio, 1975.
18 pp.
8. Applied Management Sciences, Inc. The Private Sector in Solid Waste Man-
agement; A Profile of its Resources and Contribution to Collection and
Disposal .v.2. Analysis of Data. Environmental Protection Agency Publi-
cation SW-51 d.l. 1973.
9. U. S. Department of Commerce/Bureau of Economic Analysis. Survey of Cur-
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10. Institute for Solid Wastes of American Public Works Association. Munici-
pal Refuse Disposal. Public Administration Service, Third Edition 1970.
538 pp.
11. Ingram, W. T., et al. Quad-City Solid Wastes Project. U. S. Department of
Health, Education, and Welfare, Public Health Service, Cincinnati, Ohio,
1968. 175 pp.
53
-------
12. Smith, F. L. Jr., A Solid Waste Estimation Procedure: Material Flow
Approach. EPA/530/SW-147. U. S. Environmental Protection Agency, Cin-
cinnati, Ohio, 1975. 56 pp.
13. Smith, F. A. Quantity and Composition of Post-Consumer Solid Waste: Mat-
erial Estimates for 1973 and Baseline Future Projections. Waste Age
J., April 1976
14. Niessen, W. R., and S. H. Chansky. The Nature of Refuse. In: Proce-
edings of 1970 National Incinerator Conference, Cincinnati, 1970,
15. U. S. Environmental Protection Agency. Fourth Report. To Congress, Res-
ource Recovery and Waste Reduction. Environmental Protection Publication
SW-600, 1977. 142 pp.
16. Boyd, G. B., and M. B. Hawkins, URS Research Company, San Mateo, Califor-
nia. Methods of Predicting Solid Waste Characteristics. EPA Publication
SW-23c, 1971.
17. Black, R. H., R. R. Fielder, and M. B. Hawkins. A Planning Model for the
Prediction of Residential and Commercial Solid Wastes. Final Report to
the U. S. Environmental Protection Agency under contract No. CPE 70-117,
URS Research Company, San Mateo, California. 123 pp.
18. International Research and Technology Corporation (IR & T). Forecasting
The Composition and Weight of Household Solid Wastes Using Input-Output
Techniques. Arlington, Virginia, 1975. 179 pp.
19. Williams, R. H. The Energy Conservation Papers. Ballinger Publishing
Company. Cambridge, Mass., 1975. 377 pp.
20. Office of Research and Development, EPA. Solid Waste/Recycling Model of
Strategic Environmental Assessment System (SEAS). Unpublished.
21. National Center for Resource Recovery, Inc. Resource Recovery from Muni-
cipal Solid Waste. Lexington Books, Lexington, Massachusetts, 1974.
182 pp.
22. Darney, A., and W. E. Franklin, Midwest Research Institute. Salvage
Markets for Materials in Solid Wastes. U. S. Environmental Protection
Agency Publication SW-29e, 1972. 187 pp.
23. Ayres, R. U., M. N. Kramer, and A. L. Watson, The Analysis of Resource
Recovery and Waste Reduction using SEAS. International Research and
Technology Corporation (IR & T), Arlington, Virginia. 1976. 48 pp.
24. U. S. Department of Health, Education and Welfare. Comprehensive Solid
Waste Study, Johnson City, Tennessee. A Technical Service Report (SW-
ts), 1967. 336 pp.
-------
25. Bell, J. M. Characteristics of Municipal Refuse. Presented at National
Conference on Solid Waste Research, Chicago, 1963. American Public
Works Association, Special Report No. 29, p. 37.
26. Niessen, W. R., et al. Systems Study of Air Pollution from Municipal
Incineration. v.l. Arthur D. Little, Incorporated, Cambridge,
Massachusetts. 1970.
27. Drobny, N. L., H. E. Hull, and R. F. Testin. Recovery and Utilization
of Municipal Solid Waste. USEPA Publication SW-lOc. 1971. 118 pp.
28. The Conference Board. Energy Consumption in Manufacturing. Ballinger
Publishing Company. Cambridge, Massachusetts. 1974. 610 pp.
29. Interagency Task Force on Energy Conservation. Energy Conservation in
the Manufacturing Sector. Project Independence, v.3. Federal Energy
Administration. U. S. Government Printing Office. Washington, D. C.
1974. 438 pp.
30. Gordian Associates, Inc. New York, New York. The Data Base. The Po-
tential for Energy Conservation in Nine Selected Industries, v. 1-9
U. S. Government Printing Office, Washington D. C. 1975.
31. Makins, H., and R. S. Berry. Consumer goods. Illinois Institute for
Environmental Quality. Chicago, Illinois. U. S. Department of Com-
merce. National Technical Information Service publication PB-247-755.
1973. 175 pp.
32. Williams, R. H. The Energy Conservation Papers. Ballinger Publishing
Company. Cambridge, Massachusetts. 1975. 377 pp.
33. U. S. Environmental Protection Agency. Environmental Impacts of Virgin
and Recycled Steel and Aluminum. Publication SW-117 c. National Tech-
nical Information Service, U. S. Department of Commerce. 1976.
34. Shuster, K. A. Analysis of Fuel Consumption for Solid Waste Management.
U. S. Environmental Protection Agency. Unpublished, 1974.
35. Reinhardt, J. J., and R. K. Ham. Final Report on a Milling Project at
Madison, Wisconsin, between 1966 and 1972. USEPA. Washington, D. C.,
1973.
36. Hannon, B. M. System Energy and Recycling: A Study of Beverage In-
dustry. Center for Advanced Computation, University of Illinois,
Urbana, Illinois. 1972.
37. Canter, L. W. Chemical/Biological/Environmental Aspects of Solid Waste
Management. Lecture notes, University of Oklahoma, Norman, Oklahoma.
Unpublished.
38. Shuster, K. A. Fuel Conservation in Solid Waste Management. Office of
Solid Waste Management Programs, U. S. Environmental Protection Agency.
55
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39. Westerman, R. R. The Management of Waste Passenger Car Tires. Ph.D.
Thesis, University of Pennsylvania, Philadelphia, Pennsylvania, 1974.
40. Darnay, A., and W. E. Franklin. The Role of Nonpackaging Paper in Solid
Waste Management, 1966 to 1976. Midwest Research Institute. Public
Health Service Publication No. 2040. 1971. 76 pp.
41. U. S. Environmental Protection Agency. Resource Recovery and Source Re-
duction, Third Report to Congress. Publication No. SW-161, 1975. 96 pp.
42. Darnay, A., and W. E. Franklin. The Role of Packaging Paper in Solid
Waste Management. Midwest Research Institute. Public Health Service
Publication No. 1855. 1969. 205 pp.
43. Dixon, W. J., and F. J. Massey, Jr. Introduction to Statistical Analysis
McGraw-Hill Book Company. Third edition, 1969. 638 pp.
44. University of California at Los Angeles (UCLA). Biomedical (BMD) Com-
puter Programs. University of California Press, Berkeley, California.
Third edition, 1973.
45. Morrison, D. F. Multivariate Statistical Methods. McGraw-Hill Book Com-
pany. Second edition, 1976. 415 pp.
46. Barr, A. J. at el. A User's Guide to SAS 76. SAS Institute Inc. Ral-
eigh, North Carolina. 1976. 329 pp.
56
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APPENDIX
COMPUTATION DETAILS AND STATISTICAL INFERENCES ON THE QUANTITY AND THE
COMPOSITION OF SOLID WASTE (SEE SECTION 3)
TEST OF HYPOTHESIS OF EQUAL MEANS BETWEEN 3 GROUPS OF GENERATION RATES
This is an one-way univariate analysis of variance (see Reference 43).
HO: y-j_ = y2 = P3
Hy^: at least one inequality.
Group 1
1958
1.369
1.785
2.081
1.644
1.700
2.033
T =10.612
E Z X^y
*• j
Between groups.
OOO £
Group 2
1965
1.533
1.623
2.945
1.841
1.872
1.917
T2+=11.731
=32.923 ; IE
*• J
TXH_ 2 T++ 2
Group 3
1968
1.694
1.805
3.147
1.776
2.158
T =10.580
X^y2 = 67.185
=18.769 + 22.936 + 22.387 -63.760
=0.332
d^ = degrees of freedom = K-^l =3-1 =2
MS = Mean square = —n = —'—— =0.166
Within groups.
SS= Z Z X.-.-2 - Z
-t j -^j
-------
F.95 (2,14) = 3.74
Since F < F.95 (2» 14), we cannot reject the null hypothesis at an
a = .05 significance level.
TEST FOR THE HOMOGENEITY OF SOLID WASTE
Following is the preceded computer program BMD12V44 , which was used to
carry out the one-way multivariate analysis of variance (MANOVA) to test the
hypothesis of equal means between 2 groups of composition of solid waste.
H0: yx = y2
HA: y1 # y2
// EXEC BMD,PROG=BMD12V
//SYSIN DD *
PROBLMSLDWST 8281 1
INDEX 2 12
DESIGNIR $I,R(I).
(8(F5.2,1X))
24 data cards
SUBPR011111111
FINISH
The output of the program gave the approximate F statistic equal to
2.5802 with degrees of freedom 8 and 15. Since F
-------
has the F distribution with degrees of freedom p and N - p.
46
The following computer program computes F using SAS manual
PROC MATRIX;
X= 45.5 10.9 2.7 10.8 1.3 0.3 25.9 1.6/
34.9 9.0 5.8 10.4 2.0 0.8 34.6 2.3/
data cards
24.1 6.0 3.0 5.9 2.8 1.5 9.1 41.1;
PRINT X;
MU=37.8 10.0 6.5 10.1 1.6 3.7 14.2 14.6;
PRINT MU;
NOBS=NROW(X);
NVAR=NCOL(X);
SUM=J(1,NOBS)*X;
XBAR= SUM///NOBS; PRINT XBAR;
Y=X(*,1)-XBAR(1,1);
1=2;
LOOP1:IF I>NVAR THEN GO TO NEXT1;
YI=X(*,I)-XBAR(1,I);
Y=Y YI;
1=1+1;GO TO LOOP1;
NEXT1:PRINT Y;
I=1;A=J(NVAR,NVAR,0);
LOOP2:IF I>NOBS THEN GO TO NEXT2;
AI=Y(I,*)'*Y(I,*);
A=A+AI;1=1+1;GO TO LOOP2;
NEXT2:PRINT A;
S=A#/(NOBS-1);PRINT S;
B=XBAR-MU;
HOTELGT2=B*INV(S)*B'//NOBS;PRINT HOTELGT2;
F=HOTELGT2//(NOBS-NVAR)/// (NVAR*(NOBS-1) 1;
PRINT F;
Note that the vector MU is the composition of solid waste in 1971 det-
ermined by EPA material flow method as shown in Table 18.
o
The output gave a Hotelling T statistic equal to 315.05 and a value of
F equal to 27.3957- Since F is in excess of F.95 (8, 16) =2.59, the null hy-
pothesis is rejected. However, a follow-up analysis was done as follows and
revealed that only the component plastics, rubber, and leather, and the com-
ponent wood (components £3 dnd Xg of the vector composition) contribute to the
rejection of the null hypothesis, the other six components do not.
59
-------
Follow-up analysis (See Reference 45).
The values of the vectors X and y and of the covariance matrix S were
printed in the output of the above computer program as follows (y0 is the com-
position of solid waste shown in Table 18) .
X =
40.
9.
3.
8.
3.
2.
12.
12.
1379
08125
70667
43708
00917
63125
4329
5742
Covariant Matrix S
Column 1
137.859
9.06957
-5.22064
9.80475
-3.25675
-11.3855
7.11356
-54.4326
Column 2
9.
5.
-0.
2.
-1.
-2.
4.
-7.
06957
8872
115474
68753
15739
68809
09027
26733
Covariant Maxtrix S (continued)
Column 5
-3.25675
-1.15739
1.58952
-0.928972
2.19492
1.03911
-6.83241
2.47126
Column 6
-11.3855
-2.
0.
-1.
1.
4.
-9.
6.
68809
997213
91351
03911
32044
33224
63387
y =
Column 3
Column 7
-3
7.11356
4.09027
94292
9.3332
6.83241
9.33224
84.6885
49.7312
37.8
10.0
6.5
10.1
1.6
3.7
14.2
14.6
Column 4
5.22064
0.115474
2.70635
0.140132
1.58952
0.997213
•3.94292
•0.0490899
9.80475
2.68753
-0.140132
3.26069
-0.928972
-1.91351
9.3332
-11.3633
Column 8
-54.4326
-7.26733
-0.040899
-11.3633
2.47126
6.63387
-49.7312
88.6249
the 95 percent simultaneous confidence intervals of Roy and Bose are used
in this follow-up analysis (a =0.05).
,TC
a'X V N aTSa T a;P> N ~ P * a'y * a'X A/N aTsa Ta; P' N"P
Paper. aT=[lOOOOOOOJ; y(Paper) =37.8
1 x 137.869 = 2.397
aTx = 40.1379 ; ^ aTSa
Ta ; p, N-p =
-24-
-^£ Fa ; p,' N-p =\/^^ x 2.59 = 5.458
N-P ~~ ' r> " r y 16
40.1379 - 2.397 x 5.458 3 y (paper) ^40.1379 + 2.397 x 5.458
27.051 < y (paper) ^ 53.2207
Since this interval does not contain the value 37.8, paper does not con-
tribute to the rejection of the null hypothesis.
60
-------
Glass, a = 0100000 Oj ; y (Glass) =10.0
aTx = 9.08125 ;\ A aTSa~\L^ x 5.8872 = 0.49527
V N V24
9.08125 - 0.49527 x 5.458 :? y (Glass) <; 9.08125 + 0.49527 x 5.458
6.378 < y (Glass) $11.7844
Glass does not contribute to the rejection of the null hypothesis.
Plastics, rubber, and leather, y (Plastics, rubber and leather)=6.5
aTx = 3.70667 ;y- aSa =\ x 2.70635 = 0.3358
3.70667 - 0.3358 x 5.458 $y (Plastics, rubber and leather) ^
3.70667 + 0.3358 x 5.458
1.8738 < y (Plastics, rubber, and leather) cf5.58
Plastics, rubber, and leather does contribute to the rejection of the
null hypothesis
Metals. y (Metals) = 10.]
= 8.43708 - aTSa =/ * 3.26069 = 0.36959
N V 24
8.43708 - 0.36959 x 5.458 .< y (Metals) .$ 3.43708 + 0.36959 x 5.458
6.4198 $ y (Metals) <: 10.4543
Metals do not contribute to the rejection of the null hypothesis.
Textiles, y (Textiles) =1.6
aTx = 3.00917 ;y| aTSa =\A^ x 2.19492 = 0.302415
3.00917 - 0.302415 x 5.458< y(Textiles) ^ 3.00917 + 0.302415 x 5.458
1.35858 < y(Textiles) <4.36775
Textiles do not contribute to the rejection of the null hypothesis.
Wood, y (Wood) = 3.7
aTx = 2.63125 ; aSa-~ x 4.32044 = 0.424285
2.63125 - 0.424285 x 5.458
-------
12.5829 - 1.87848 x 5.458 ^p(Food) <12.5829 + 1.87848 x 5.458
2.330102 < y(Food) ^< 22.835698
Food waste does not contribute to the rejection of the null hypothesis.
Yard waste. y (Yard waste) = 14.6
aTx = 12,5742 ;\/|- a^Sa =\jr x 88.6249 = 1.92164
12.5742 - 1.92164 x 5.458 ^ y(Yard waste) <12.5742 + 1.92164 x 5.458
2.0858 < ij(Yard waste) ^ 23.0625
Yard waste does not contribute to the rejection of the null hypothesis.
62
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1 REPORT NO.
EPA-600/8-78-015
4, TITLE AND SUBTITLE
ENERGY CONSERVATION THROUGH SOURCE REDUCTION
3. RECIPIENT'S ACCESSION-NO.
5. REPORT DATE
November 1978
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
George W. Reid and Chan Hung Khuong
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Bureau of Water & Environmental Resources Research
University of Oklahoma
Norman, Oklahoma 73019
10. PROGRAM ELEMENT NO.
1DC618
11. CONTRACT/GRANT NO.
R804183
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research Laboratory—Cin.,OH
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
EPA/600/14
15. SUPPLEMENTARY NOTES
Project Officer: Oscar W. Albrecht 513/684-7886
16. ABSTRACT
This report deals with energy conservation through reduction in generation of
post-consumer solid waste. The objective, scope, methodology and summary of the
report are presented in Section 1. Section 2 contains the conclusions. Section 3
presents a review of output and input approaches to estimate the quantity and com-
position of post-consumer solid waste. Comparative notes on the two methods are
included. Section 4 contains a compilation of estimates of energy consumed in the
manufacture of discarded materials and in handling the solid waste. Section 5
studies potentials and possibilities of reducing refuse and estimates corresponding
energy savings. Twenty examples of opportunities to reduce refuse at government,
policy-maker, manufacturer, and consumer levels are proposed. The energy intensive-
ness of materials found in the waste stream, total energy residuals embedded in each
material, and possible candidates for reduction with greatest energy savings are also
presented.
This report was submitted in fulfillment of Grant No. R804183 by the Bureau of
Water and Environmental Resources Research, University of Oklahoma, under the sponsor-
ship of the U.S. Environmental Protection Agency.
17.
KE < WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Energy
Refuse disposal
b.IDENTIFIERS/OPEN ENDEDTERMS
Energy conservation
Source reduction
Solid waste
Solid wast quantity
COSATI Field/Group
97B
13. DISTRIBUTION STATEMENT
Release to Public
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
73
20. SECURITY CLASS {This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
63
OVERWENT PRINTING OFFICE- 1978 — 657-060/1528
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