&EPA
United States
Environmental Protection
Agency
Municipal Environmental Research
Laboratory
Cincinnati OH 45268
EPA-600/5-80-001
May 1980
Research and Development
Forecasts of the
Quantity and
Composition of
Solid Waste
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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 SOCIOECONOMIC ENVIRONMENTAL
STUDIES series. This series includes research on environmental management,
economic analysis, ecological impacts, comprehensive planning and fore-
casting, and analysis methodologies. Included are tools for determining varying
impacts of alternative policies; analyses of environmental planning techniques
at the regional, state, and local levels; and approaches to measuring environ-
mental quality perceptions, as well as analysis of ecological and economic im-
pacts of environmental protection measures. Such topics as urban form, industrial
mix, growth policies, control, and organizational structure are discussed in terms
of optimal environmental performance. These interdisciplinary studies and sys-
tems analyses are presented in forms varying from quantitative relational analyses
to management and policy-oriented reports.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/5-80-001
May 1980
FORECASTS OF THE QUANTITY AND COMPOSITION
OF SOLID WASTE
- hy
Ralph M. Doggett
Mary K. O'Farrell
Andrea L. Watson
International Research and Technology Corporation
McLean, Virginia 22102
Contract No. 68-03-2649
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 publication.
Approval does not signify that the contents necessarily reflect the views and
policies of the U.S. Environmental Protection Agency, nor does mention of
trade names or commercial products constitute endorsement or recommendation
for use.
ii
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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.
The complexity of that 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.
Increasing quantities coupled with rising costs are of great concern
to those charged with efficient management of solid waste. Policymakers
need adequate data and reliable projections on which to develop strategies
for achieving their objectives and goals. This report describes the various
approaches available for estimating residential and commercial solid waste
quantities and composition. It furnishes predictions to 1990, using an
economic input-output model to reflect the impact of both economic growth
and structural changes in the economy on the quantity and composition of the
solid waste stream. The research project is one of the special studies man-
dated under Section 8002 of the Resource Conservation and Recovery Act of
1976 (PL94-580).
Francis T. Mayo
Director
Municipal Environmental Research
Laboratory
iii
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ABSTRACT
This research program was initiated with the overall objective of esti-
mating the future quantity and composition of solid waste discards. A data
base was compiled and a methodology was developed to evaluate the effects of
a number of variables (including the extent of resource recovery initiatives,
average product lifetimes, materials and process substitutions, and economic
growth) on the quantity and composition of discards to the year 1990. The
methodology employs an interindustry forecasting model of the United States
economy, which allows for the specification of alternative values for criti-
cal variables.
Solid waste discards and recycling of fourteen materials in twenty-one
product categories are estimated under five different sets of assumptions,
or scenarios. Results of the scenarios are analyzed and compared with esti-
mates from other studies, notably the EPA annual Reports to Congress on
Resource Recovery and Waste Reduction, and projections by Midwest Research
Institute in Base Line Forecasts of Resource Recovery, 1972-1990 prepared
for EPA. The results of the scenario suggest that the quantity of solid
waste is likely to increase at a rate slower than that of the economy, due
to substitutions away from heavy materials such as steel and glass, to
lighter materials such as aluminum, plastics and paper. The results also
suggest that the quantity and composition of future solid waste discards
will be substantially determined by average product lifetimes, recycling
rates, and technology change.
This report was submitted in fulfillment of Contract Number 68-03-2649
by International Research and Technology Corporation under the sponsorship
of the U.S. Environmental Protection Agency. Computer support was provided
by Control Data Corporation under Subcontract to IR&T. This report covers
the period December 8, 1977 to December 23, 1978, and work was completed as
of March 23, 1979.
iv
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CONTENTS
Foreword ill
Abstract iv
Figures vi
Tables viii
Acknowledgments xi
j " O
1. Overview 1
Review of Previous Studies . 1
Methodology and Scope 7
Summary and Conclusions 22
2'. The Forecasts, 24
The Reference Scenario 24
Impacts of Technology Change and
Materials Substitution 36
The Effects of Product Life 48
The Impacts of Recycling 48
3. Comparison of Estimates and Forecasts of the
Quantity and Composition of Solid Wastes 52
4. Methodology 61
Data Development 61
Linkage to the Economic Forecasting Model 67
Estimating Future Solid Waste 70
Limitations 73
5. Recommendations 75
References 77
Appendix
Introduction 87
Materials Data Base and Flow Diagrams 87
Material Flows Selected for This Study 128
Product Lifetime Assumptions 145
Recycling Assumptions 150
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FIGURES
Number Page
1 Conceptual flow diagram of the IR&T solid waste/recycling
model 16
2 Material flows in the IR&T solid waste/recycling model ... 18
3 Material flow diagram of aluminum in 1971 (thousands of
metric tons) 21
4 Material flow paths (chains) selected for textiles 72
A-l Material flow diagram of aluminum in 1971 91
A-2 Material flow diagram of copper in 1971 95
A-3 Material flow diagram of ferrous metals in 1971 99
A-4 Material flow diagram of glass in 1971 102
A-5 Material flow diagram of lead in 1971 104
A-6 Material flow diagram of leather in 1971 106
A-7 Material flow diagram of paper in 1971 Ill
A-8 Material flow diagram of paperboard in 1971 112
A-9 Material flow diagram of plastics in 1971 116
A-10 Material flow diagram of rubber in 1971 118
A-ll Material flow diagram of textiles in 1971 122
A-12 Material flow diagram of wood in 1971 124
A-13 Material flow diagram of zinc for 1971 127
A-14 Material flow paths selected for this study: aluminum .... 129
A-15 Material flow paths selected for this study: concrete .... 130
vi
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FIGURES (continued)
Number Page
A-16 Material flow paths selected for this study: copper 131
A-17 Material flow paths selected for this study: ferrous metals . 133
A-18 Material flow paths selected for this study: glass 135
A-19 Material flow paths selected for this study: lead 136
A-20 Material flow paths selected for this study: leather .... 137
A-21 Material flow paths selected for this study: paper 138
A-22 Material flow paths selected for this study: paperboard . . . 139
A-23 Material flow paths selected for this study: plastics .... 140
A-24 Material flow paths selected fo'r this study: rubber 142
A-25 Material flow paths selected for this study: textiles .... 144
A-26 Material flow paths selected for this study: wood 145
A-27 Material flow paths selected for this study: zinc 146
vii
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TABLES
Number Page
1 Material, Product, and Disposal Categories Used in
this Study 9
2 Definition of Product Categories 10
3 Description of Solid Waste Source Categories Used in
this Report 15
4 Material/Product Matrix for 1971 . . . 19
5 Reference Scenario Gross National Product Summary 25
6 Reference Scenario Trends of Final Demand in Selected
Material Inputs Per Dollar, 1971-1990 26
7 Reference Scenario Outputs of Selected Industries 27
8 Reference Scenario. Assumptions for New Scrap and
New Scrap Recycled 28
9 Solid Waste Recycling Model Reference Scenario. Prompt
Scrap Generation By Product Category for Selected Materials 29
10 Reference Scenario. Post-Consumer Recycling Assumptions,
1971 and 1990 30
11 Product Lifetime Assumptions for Each Scenario 31
12 Reference Scenario Projections of Net Solid Waste Disposal
By Material, 1971-1990 32
13 Reference Scenario Projections of Net Solid Waste Disposal
By Product Category, 1971-1990 33
14 Reference Scenario Projections of Net Solid Waste Generation
By Material and Sector 34
15 Reference Scenario Projections of Recycled Solid Waste
By Material, 1971-1990 37
viii
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TABLES (continued)
Number Page
16 Reference Scenario Projections of Recycled Solid Waste
by Product Category, 1971-1990 38
17 Reference Scenario Summary of Net Solid Waste Per Capita
and Per Dollar of GNP, 1971-1990 39
18
19
20
21
22
23
24
25
Comparison of 1980 Net Solid Waste Projections by Material. .
Comparison of 1980 Net Solid Waste Projections by Product
Comparison of 1980 Recycling Projections by Material ....
Comparison of 1980 Recycling Projections by Product Category.
Comparison of 1990 Net Solid Waste Projections by Material. .
Comparison of 1990 Net Solid Waste Projections by Product
Comparison of 1990 Recycling Projections by Material ....
Comparison of 1990 Recycling Projections by Product Category.
40
41
42
43
44
45
46
47
26 Recycling Assumptions of Each Scenario for 1990 (Old Scrap
Post-Consumer) 49
27 Comparison of Post-Consumer Net Residential and Commercial
Solid Waste by Material 53
28 Comparison of Post-Consumer Net Residential and Commercial
Solid Waste by Product Category 54
29 Estimates of Transportation, Industrial, Demolition and
Construction Wastes for the Year 1971 55
30 Comparison of Post-Consumer Estimates and Projections of
Per Capita Waste Generation 57
31 Comparison of Post-Consumer Estimates and Projections .... 58
32 Path Products by Material for Various Thresholds 71
33 SEAS Projections of Solid Waste by Category 1975-1990 .... 76
A-l Reference Scenario. Historical Time Series Production
Data for Aluminum 90
A-2 Reference Scenario. Historical Time Series Production
Data for Concrete 92
ix
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XT , TABLES (continued)
Number Page
A-3 Reference Scenario. Historical Time Series Production
Data for Copper 94
A-4 Reference Scenario. Historical Time Series Production
Data for Ferrous Metals 98
A-5 Reference Scenario. Historical Time Series Production
Data for Glass 101
A-6 Reference Scenario. Historical Time Series Production
Data for Lead 103
A-7 Reference Scenario. Historical Time Series Production
Data for Leather . 105
A-8 Paper and Paperboard Product Category Allocation
Assumptions 108
A-9 Reference Scenario. Historical Time Series Production
Data for Paper 109
A-10 Reference Scenario. Historical Time Series Production
Data for Paperboard 110
A-ll Comparison of Plastic Sales Data for 1972 114
A-12 Reference Scenario. Historical Time Series Production
Data for Plastics 115
A-13 Reference Scenario. Historical Time Series Production
Data for Rubber 117
A-14 Reference Scenario. Historical Time Series Production
Data for Textiles 121
A-15 Reference Scenario. Historical Time Series Production
Data for Wood 123
A-16 Reference Scenario. Historical Time Series Production
Data for Zinc 126
A-17 Recycling Scenario. Sources of Average Product Lifetime
Assumptions 148
A-18 Recycling Rates for Material Product Categories 151
A-19 New Scrap Factors and New Scrap Recycling-Rates 152
A-20 New Scrap and Old Scrap Recycling and Diversion
Assumptions for Paper and Paperboard Wastes 155
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ACKNOWLEDGMENTS
The cooperation and assistance of Mr. Oscar Albrecht, the EPA
project officer for this study, is gratefully acknowledged. Comments
and suggestions by EPA consultant, Stedman Noble, proved valuable in
the preparation of the final report. We would also like to thank
Dr. Frank Smith of EPA's Office of Solid Waste Management Programs
for his continued interest and assistance in this project. We are
indebted to Mr. Raj Shah, Ms. Carol Metzger and Ms. Laura Beck of
Control Data Corporation for programming support.
xi
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SECTION 1
OVERVIEW
The quantities and composition of solid waste disposed of in our land-
fills, incinerators, and dumps are largely determined by initiatives for
waste reduction and resource recovery. The thrust of the Resource Conserva-
tion and Recovery Act of 1976, and of numerous state and local initiatives
over the past several years has been to focus attention for the purpose of al-
leviating a growing national problem.* There are a number of promising pro-
grams in progress, including research and development in the area of mixed-
waste processing technology, economic incentives for materials separation at
the point of disposal, and the establishment of guidelines for returnable
beverage containers. When evaluating the efficacy of these programs, it is
important to recognize trends in the factors that determine the composition
of solid waste. These include overall economic growth - an indication of the
continuing increase in the demand for goods and services that ultimately gen-
erate waste - and within the economic growth context, the extent of materials
substitution, technology change and recycling, and the average useful life of
products produced. By quantifying these factors and by estimating their im-
pacts on current and future waste loads, policy makers, solid waste managers,
producers and consumers can more readily evaluate economic incentives, re-
source recovery programs, emerging technologies, and personal attitudes.
The purpose of this study was to compile a data base and develop a meth-
odology to estimate the current and future quantity and composition of solid
waste discards. Using the methodology, future solid waste loads can be es-
timated under alternative assumptions regarding recycling rates, product
life, materials composition, technology change and general economic growth.
REVIEW OF PREVIOUS STUDIES**
This is by no means the first study to analyze the flow of materials
through the economy for the purpose of estimating the characteristics of
* See, for example, the annual reports to Congress on Resource Recovery and
Waste Reduction, prepared by the U.S. Environmental Protection Agency.
** Much of this review of solid waste studies originally appeared in a pre-
vious IR&T report, Forecasting the Composition and Weight of Household
Solid Waste Using Input-Output Techniques, Final Report, U.S. Environ-
mental Protection Agency, November 1975, NTIS (PB 257499/AS), Vol. I,
and NTIS (PB 257500/AS), Vol. II.
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solid waste. Indeed, much of the data and design concepts for the
methodology presented here have been derived from previous studies. None-
theless, this study is unique in that it combines different approaches that
have been used in previous studies.
The previous studies vary greatly in their scope and objectives, but
they can be generally classified by the approach used. The more common
approach, called the output approach, is to analyze the materials contained
in the waste stream after disposal. This approach is a sampling approach
that requires the separation and weighing of materials at the disposal site.
Sampling surveys for estimating the quantity of solid waste were first
encouraged through legislative action. In enacting the Solid Waste Disposal
Act of 1965, Congress provided for grants to state and interstate agencies
of up to 50 percent of the costs of conducting surveys of solid waste
disposal practices and problems. By 1968, 38 states, the District of
Columbia, Puerto Rico, and three interstate agencies have received planning
grants, and had started or completed solid waste surveys following a study
design and reporting format established and coordinated by the U.S. Public
Health Service. Data available on July 1, 1968, were published in their
basic form (1), followed by a second publication in a more concise statis-
tical format (2). Although widely distributed in this form, the final
results of the completed survey were never formally evaluated or published.
However, final figures have been analyzed and informally reported (3).
Although the survey requested responses based on actual weights or measure-
ments in cubic yards, most of the participating communities furnished only
estimates of the waste loads they handled. Within the survey group, house-
hold and commercial solid wastes were found to be generated at an average
rate of 4.15 pounds per capita per day. Adding demolition, construction,
industrial, yard trash and other municipal solid wastes, this figure was
raised to 5.32 pounds per day. Placing the survey data within a broader
context, the informal final 1968 data analysis arrived at a somewhat lower
figure of 4.01 pounds per capita per day for the residential, commercial,
and institutional total. Subsequent critical analysis showed that the
relatively few communities that made actual measurements to comply with the
national survey requirements arrived at lower totals than those communities
that reported estimates (4,5). It was then pointed out that the amount of
paper waste estimated from samples for the 1968 survey would be greater
than the estimates of paper entering the waste stream that are based on
paper production data - even though the production-based data were in dry
weights and the 1968 survey estimates would include varying amounts of
water (6). Subsequent evaluation by F.A. Smith of EPA's Office of Solid
Waste Management Programs recognized these shortcomings and suggested that,
although the 1968'survey results may have overstated waste flows, the
ensuing analytical efforts have not yielded information on which to base
a more accurate estimate (7).
A less comprehensive survey conducted for the National Solid Waste
Management Association in 1971 used volume data from major private waste
collection organizations as a basis for estimating the weights of waste
collected per capita (8). In general, the range of values estimated for
commercial, demolition, industrial and other non-residential waste
categories coincided with the range in EPA's final analysis of the 1968 survey
results, but for residential waste it was approximately 30 percent higher.
2
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The single, most significant drawback of the survey data, considered
as a base from which to forecast future amounts of municipal wastes, is
that regardless of the degree of accuracy of particular surveys, differen-
ces in samples, estimation techniques, and assumptions are likely to ac-
count for differences among the results to a greater degree than differ-
ences in actual household waste generation. For this reason, although
the studies may relate to various years (i.e., 1967, 1970, and 1971), they
cannot be treated as a time series. Standing alone, unlike a time series
of production or consumption data, these surveys do not permit trend ex-
trapolation in order to anticipate future waste levels. If the assump-
tion is made that per capita solid waste output is a fixed value that is
unaffected by such variables as changes in per capita income, packaging
technology, or family size, then a value taken from these survey results
could be multiplied by future population levels to arrive at an estimate
of the weight of 1985 wastes. Because it has not been established whether
these and other variables will not have a major effect on amounts of waste
generated, these output or sampling surveys have not been used extensively
to provide long-range estimates of amounts of wastes generated.
Both before and since the 1968 survey, there have also been a large
number of analyses of the composition of household or municipal solid
wastes. Representative examples include Oceanside, New York (9); Atlan-
ta, Georgia (10); Cincinnati, Ohio (10); Flint, Michigan (10); Johnson
City, Tennessee (10); San Diego, California (10); Berkeley, California
(11); Raleight, North Carolina (12); Santa Clara County, California (13);
New Orleans, Louisiana (14); and Madison, Wisconsin (15). Also, there
have been several efforts to synthesize average or national composition
figures from the many available samplings (16, 19). These studies cust-
omarily use composition categories such as food, yard wastes, glass, metal
(sometimes disaggregated into ferrous and non-ferrous), paper, plastics,
textiles, wood, leather and rubber. Variations among the recorded figures
indicate that "average" composition may be a misnomer and that wide fluc-
tuations in daily composition, varying by day of the week and month of the
year, as well as by geographic location, are the norm.
The composition studies have been very helpful in previous estima-
tion work aimed at identifying the resource potential implicit in national
waste flows (7, 20). However, to an even greater degree than the surveys,
each of the composition studies must be considered one point in its own
discrete time series. Data from different places, collected over a short
period of time and under conditions suggesting major seasonal and even
weekly changes in composition, cannot be used as a base from which to
extrapolate long-term change. In a study for the Energy Research and
Development Administration, Resource Planning Associates made similar con-
clusions after a review of recent waste composition surveys (21).
The need for greater predictive capabilities, as well as other factors
Csuch as the possibility that extrapolations from survey results may lead
to unreliable results because of the difficulty of handling such variables
as moisture content) have led to the use of industrial production statistics
as a source of data from which to estimate the amounts and composition of
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household wastes. The approach has been called "input" estimation, to dis-
tinguish it from collection-based "output" oriented surveys.
The best known of the early input studies were the studies of packaging
materials and non-packaging paper by Darnay and Franklin (22,23) of Midwest
Research Institute (MRI). They have been followed by successor MRI studies
on salvage markets, paper recycling and baseline forecasts of solid wastes
by material and product category (24,26). Resource Planning Associates, Inc.,
has also started from industrial production data to arrive at waste genera-
tion estimates (4). Comprehensive Reviews and evaluations of the earlier
work were prepared by Frank A. Smith and Fred L. Smith, Jr., of EPA's Office
of Solid Waste Programs, in 1974 and 1975 (7,27). Estimates of national
totals and per capita daily average waste production and waste composition
have been updated several times (-7,27,28). In each study using the input
approach, bulk production data on materials are corrected for imports and
exports to yield an estimate of apparent domestic consumption. This estimate
is corrected for process losses and for imports and exports of the relevant
finished goods. The consumption estimates are then allocated by end-use to
determine the quantities of materials "by product category which potentially
enter the relevant waste stream. This step, for example, determines what
fraction of paperboard will end up as household waste. Allocated consumption
data, thus obtained, are lagged to account for the durability of each cate-
gory of end-use product. In each of these final use categories, the amount
of material recovered is subtracted to yield an estimate of solid waste for
that category. This development by Smith has resulted in the compilation of
a six-year time series of solid waste estimates, the only one of its kind.
There are several difficulties implicit in this form of analysis.
Time lag estimation is a difficulty that is also common to the other classes
of analyses discussed below. There are actually two sets of time lags.
The first is the lag between production and consumption, during which a
product is in the distribution system. The second is the lag between pur-
chase and discard. Although rational methods for developing time lag assump-
tions for both kinds of lags can be developed and defended, they will neces-
sarily rely in large part upon intuitive processes. It may be reasonably
safe to assume that all packaging materials used in packaging consumer pro-
ducts enter the waste stream within a year of their production. It may be
less safe to assume that small appliances enter the waste stream at a rate
equivalent to the production output of a part year (selected by consulting
product life expectancy data), or that the rate of disposal for all textiles
used in clothing can be assigned a single "average" lag rate.
A second, more fundamental difficulty- with the production data or input
approach is the need to know not only how much of a given material is pro-
duced, but also for what it is used. Polyester fiber may be used in cord-
age, automobile upholstery and electric cable insulation, as well as in
textiles incorporated into clothing. The nature of the use will determine
whether a material ends up in automobile scrap, demolition waste, or house-
hold waste. It will also determine the lag time, which varies widely with
different end-uses.
For every major -component of the waste stream, it is necessary to de-
termine the weight of material sold by its producers to all manufacturers
4
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of products or materials destined for sales to consumers. For some mater-
ials, such as glass bottles, data are readily available; for others, they
are not.
Waste estimation based on production data has a significant advantage
over survey-based estimates in that time series data are available on which
to base a forecasting procedure. While such time series will be use-
ful for short-range forecasts, they cannot be used for long-range esti-
mation. Extrapolation from past production will not be a reliable indica-
tion of probable future concentrations of tinned steel, aluminum, or bi-
metal cans, metal foil, glass, paper, or plastic containers in the packaging
of consumer products. To develop such an indication requires an independent
reconciliation of the competing claims for materials that can be substituted
for one another.
Studies employing econometric techniques have focused on analyzing
consumer expenditure data and other economic and social variables. R.A.
Richardson and J. Havlicek have published papers which suggest that such
variables as household income and age structure and size of households
appear to be important factors affecting the quantity and composition of
solid waste, based on an analysis of data samples in Indianapolis, Indiana
(29). However, the authors conclude that further research appears neces-
sary to disaggregate waste materials and relate their quantities directly
to household consumption patterns.
A detailed analysis of consumer spending patterns was carried out by
URS Research Company to permit the analysis of waste generation (30-j31).
Two models were developed; one for the prediction of residential solid waste
generation, and the other for the prediction of commercial solid waste gen-
eration. For the residential model, total retail expenditures were collect-
ed for a regional data bank that shows the 1960-61 distribution of household
spending on over 700 items. Analysis of this data shows the amount spent by
households on each consumer item during the period of time sampled (usually
one week). The number of items purchased was then derived from the price
per unit for each consumer item. From the number of items purchased and a
listing of the physical weight and composition of each item, an inventory
of waste materials was generated.
The commercial model is similar insofar as it used the sales of merchan-
dise (prorated to the specific items) and the unit price per item to deter-
mine the number of items sold. It then estimates total commercial (retail
activity) waste assuming a standard waste composition for each item. It has
identified discarded shipping containers as a major component of commercial
waste.
This model, as ultimately developed, was oriented toward a rapid through-
put of materials. Standing by itself, it would not project future solid
waste generation. The interim report on the project described the procedures
for dealing with projections using such variables as retail expenditures,
distribution of household expenditures, price-per-unit by item, and physical
description of each item. An endogenous estimate for each variable was
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required in order for the model to produce a projection. The interim report
also recommended the development of separate models to segregate those pro-
ducts associated with short versus long periods of resistance.
Other attempts to use forecasts of the future consumer environment to
project the amounts and composition of household packaging wastes have been
made by the Research Triangle Institute (32). One study used a straight-
forward method to estimate future packaging waste. The weight of consumer
packaging per dollar of consumer expenditure (for each of 30 categories of
consumer products) was determined for 1958-1970 and extrapolated linearly to
1980. Econometric projections of personal consumption expenditures were
made to determine the 1980 expenditures for each product category. From the
1980 weight of packaging per dollar and estimates of 1980 expenditures, a
value for the total weight of 1980 packaging was determined. This value and
an estimate of the materials distribution in packaging yield the amounts of
materials used in packaging in 1980 for each product category, assuming that
packaging materials become solid waste within a year.
Consumer forecast-based studies constitute an important conceptual ad-
vance over the industry production studies because they take advantage of
an internally consistent set of forecasts about future levels of consumption
and production, and, in general, these forecasts are based upon an adequate
body of time series data. However, the consumer forecast-based studies are
conceptually deficient in their handling of product consumption, whether in
fixed product composition estimates or in linear extrapolation of product
composition change from past composition trends. Similar to the production
data studies described earlier, these studies fail to deal adequately with
the lag times between purchase and disposal.
An International Research and Technology Corporation study undertook to
apply all of these methods to the task of forecasting the amounts, composi-
tion, and location of future (through 1980) loads of combustible wastes from
all sources (20). Livestock wastes were estimated by utilizing data on
manure production per animal and forecasts of future animal populations
based on future consumer expenditure forecasts. Crop waste estimates were
derived from data on regional crop production and on waste generation and
disposition by crop. Industrial combustible wastes were forecast based on
an input-output model, which customarily describes flows of materials and
products in terms of dollar sales. These were converted, using price data,
into flows of physical quantities. The literature was surveyed to obtain
estimates of the amounts and composition of process waste and plant trash
(mostly miscellaneous packaging waste) generated per pound of output, and of
waste generation trends. These data were converted into waste coefficients
and applied to the model's forecasts of future outputs in order to yield
forecasts of industrial process wastes. The analysis was also regionalized,
using data on industry locations.
Because of the lack of regional consumer purchase forecasts, no input-
output analysis of household waste was attempted. Instead, household
waste generation forecasts were estimated by using per capita waste produc-
tion figures derived from the 1968 survey and future population distribution
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figures. While stopping short of applying input-output analysis to house-
hold waste prediction, this study nevertheless marked the first formulation
of input-output analysis as a tool for the development of waste management
policy.
Under the auspices of EPA's Municipal Environmental Research Laboratory
in Cincinnati, IR&T developed a methodology using input-output techniques to
estimate and forecast industry-by-industry material consumption (33). Eco-
nomic input-output analysis was used to trace the flows of physical materials
through analysis of purchases by every sector in the economy, adjusting them
to estimate flows to the household sector. From such a base, a dynamic model
was developed to show the levels of future purchases, sector by sector. By
converting the values of purchases into the weights of basic material inputs,
the kinds and quantities of materials embodied in the products discarded by
households was inferred. The quantity and composition of household waste
was forecast to 1985 using the "corrected" structure of the economy (i.e.,
the economy as described in terms of materials embodied in products purchased
by households) as a baseline, and employing extrapolations of interindustry
coefficients.
In a recent study for the Office of Solid Waste, Research Triangle In-
stitute (RTI) used input-output techniques to estimate and forecast the
weight of material required for 478 categories of consumer expenditure (34).
Production data by end-use was related to the inverse matrix of the 1967 De-
partment of Commerce input-output table which was used to develop coeffic-
ients as reasonable first approximations of future material flows and exo-
genous projections of personal consumption expenditures from the Bureau of
Labor Statistics.
This study departs from previous efforts in its attempt to be more com-
prehensive in its scope, taking into account not only material flows poten-
tially entering the household and commercial waste stream, but also flows
into other disposal sites (e.g., demolition sites and junk yards). Second,
this study attempts to combine the best features of materials-flow estima-
tion procedures and input-output techniques, to provide forecasts of mater-
ials-flow in tons that are consistent with an economic model, and thereby
reflect both economic growth and structural changes in the economy that have
an impact on the composition of the solid waste stream (e.g., materials sub-
stitution and technological changes).
METHODOLOGY AND SCOPE
The methodology presented here combines features of the production data
or materials flow estimation procedures developed by William Franklin, Fred
Smith, and Frank Smith, and the input-output analysis and forecasting tech-
niques developed by Stedman B. Noble in the IR&T household waste study for
EPA, briefly described above (33). While an overview of the methodology is
presented here, a more detailed description is presented in a later section.
-------
The approach used in this study differs from the solid waste estima-
tion procedures developed by Stedman Noble, although they also explore the
economic relationships suggested by the input-output table to estimate and
forecast material flows. For this study, production data was related to
flows of materials to product categories defined by the sectors of an inter-
industry forecasting model, in order to derive estimates of material use
by product category. The model was then used to forecast future material
use. The need for adjustments made in the Noble study to account for price
differentials in the use of materials and aggregation errors was diminished.
Other adjustments to the model required in the earlier study were avoided
by carefully selecting only the significant flows of materials to product?
for the purpose of forecasting solid waste.
Although the recent RTI study also uses a combination of input-output
procedures and materials-flow analysis to estimate solid waste, it does not
make the detailed analysis of the economy required to adequately differen-
tiate among the various components of the waste stream. The inverse term
does indicate the direct and indirect material requirements per dollar of
final demand, but it does not adequately deal with the problems of aggrega-
tion and non-embodied material flows that are enmeshed in the coefficients
of the inverse tables. Furthermore, the RTI study uses static input-output
coefficients, and consequently fails to take structural changes in the
economy into account. Also, since projections of consumer demand are made
exogenously, forecasts of the waste stream are not internally consistent
with the economic data base.
This study has the advantage of providing an internally consistent set
of forecasts of consumption and production that take future trends in tech-
nological developments and materials substitution into account. The meth-
odology does not entirely solve the problems related to using the production
data and time lag estimation techniques, although the time lags were derived
from published estimates. Normal distributions and step functions were
applied to selected material product categories in order to estimate the
quantities of materials entering the waste stream.
In this study, the flows of 14 materials to 21 product categories were
analyzed for the years 1960 to 1990. The materials and products included
are listed in Table 1. Each of the 21 products are categorized by their
Standard Industrial Classification (SIC) as shown in Table 2. The industry
sector numbers refer to the interindustry model used in making the projec-
tions, and are described later. The flows of materials and their disposi-
tion have been traced from primary manufacture, through fabrication of final
products, to consumers, and finally, to the point of disposal. Estimates
account for new and old scrap, amounts of new and old scrap recycled, and for
diversions (i.e., "disappearance") of materials from the waste flow. Attempts
were made to estimate waste generation by source as well (e.g., residential/
commercial, industrial, etc.). For this purpose, waste disposals by product
or material were assigned to sectors as described in Table 3. Note that
some process wastes, such as sludge, slag, ash, and agricultural and mining
wastes, were not included in this analysis.
-------
TABLE 1. MATERIAL, PRODUCT, AND DISPOSAL CATEGORIES USED IN THIS STUDY
Material.Categories Product Categories
Disposal
Categories
Paper
Paperboard
Plastics
Glass
Aluminum
Zinc
Copper
Lead
Ferrous Metals
Wood
Textiles
Rubber
Leather
Concrete
Newspaper
Books, Periodicals and Other
Printing Paper
Writing and Other Fine Paper
Disposable Products
Beverage Containers
Other Packaging and Containers
Consumer and Institutional
Products
Furniture and Furnishings
Apparel
Footwear
Household Durables
Electrical and Electronic
Products
Machinery and Other Industrial
Equipment
Automobiles
Other Transportation Vehicles
Tires and Inner Tubes
Batteries
Buildings and Structures
Ordnance
Other Industrial Applications
Miscellaneous
Other Components of Waste
Stream
- Food Waste
- Yard Waste
Residential
Commercial
Industrial
Transport
Construction
Demolition
The methodology is displayed diagramatically in Figure 1. The procedure
for estimating the quantity and composition of solid waste begins with esti-
mates of economic activity generated by an adapted version of the Interin-
dustry Forecasting Model of the University of Maryland.* The INFORUM Model
makes macroeconomic projections of Gross National Product and its components
- Personal Consumption Expenditures, Producers' Durable Equipment Investment,
Construction Expenditures, Government Expenditures, Exports and Imports -
year by year from 1971 to 1990. These final demand estimates are provided
for each of the 185 product categories, encompassing agriculture, mining, man-
ufacturing and services. Final demand projections are run through an input-
output table where they are combined with interindustry (or intermediate)
demands to estimate the total outputs of the 185 categories, or sectors. The
coefficients of the input-output table are dynamic so that the effects of
A detailed description of INFORUM is contained in 1985: Interindustry
Forecasts of the American Economy, Clopper Almon, et al., Lexington
Books, Lexington, Massachusetts, 1974.
-------
TABLE 2. DEFINITION OF PRODUCT CATEGORIES
NAME INDUSTRY SECTOR
Newspaper
Books, Periodicals and
Other Printing Paper
Writing and Other Fine
Paper
Disposal Products
Beverage Containers
Other Packaging/
Containers
52
53
54
57
58
49
56
49
78
92
44
49
51
74
78
92
93
SIC CODE
2711
2721
2731
2741
2642
2649
2645
2761
2782
2647
3221
3411
244
2646
265
3079
3221
3411
3491
DESCRIPTION
Newspaper
Periodicals : Publishing
Books : Publishing
Miscellaneous Publishing
Envelopes
Converted Paper and Paperboard Products,
NEC (i.e., stationery, notebooks,
writing tablets)
Die-Cut Paper and Paperboard and
Carboard
Manifold Business Forms
Blankbooks , Loose Leaf Binders and
Devices
Sanitary Paper Products
Glass Containers
Metal Cans
Wooden Containers
Pressed and Molded Pulp Goods
Paperboard Containers and Boxes
Miscellaneous Plastic Products
Glass Containers
Metal Cans
Metal Shipping Barrels , Drums ,
Kegs and Pails
(continued)
-------
TABLE 2 (continued)
NAME
INDUSTRY SECTOR
SIC CODE
DESCRIPTION
Other Packaging/
Containers (continued)
Other Consumer/Institutional
Products
Furniture and Furnishings
101
73
74
77
78
83
87
97
98
124
126
143
144
145
146
147
148
149
150
36
3499
3069
3079
3172
3229,3231
3321
3361
3461
3421
3423
3425
3429
364
3652
3831
384
3861
387
391
2941-2-3
3931
3949
395
399,396
227
Miscellaneous Fabricated Metal Products,
NEC (i.e., foil, tube)
Fabricated Rubber Products
Miscellaneous Plastic Products
Personal Leather Goods
Glassware
Cooking Utensils, Cast Iron
Cooking Utensils, Cast Aluminum
Metal Stampings
Cutlery
Hand and Edge Tools
Hand Saws and Saw Blades
Hardware, NEC
Electric Lighting and Wiring Equipment
(Light Bulbs)
Phonograph Records
Optical Instruments and Lenses
Surgical Medical and Dental Instruments
and Supplies
Cameras, Photographic Equipment
Watches, Clocks and Parts
Jewelry, Silverware and Plated Metal
Toys
Musical Instruments
Amusement, Sporting and Athletic Goods
Office Supplies
Miscellaneous Manufacturing: Costume
Jewelry and Novelties
Floor Coverings
(continued)
-------
TABLE 2 (continued)
NAME INDUSTRY SECTOR SIC CODE
Furniture and Furnishings
(continued)
Apparel
Footwear
Household Durables
Electrical/Electronics
Machinery and Industrial
Equipment
40
45
46
39
73
76
103
116
123
125
80
118
119
120
121
122
124
127
128
130
131
102
103
239
251
252
23
302
314
3522
3585
363
365
3264
3611
3612-3
3621
3622
3623-4-9
364
366
367
3694
3693,3699
351
352
DESCRIPTION
Household Textiles
Household Furniture
Office Furniture
Apparel
Rubber Footwear
Footwear , Exc . Rubber
Lawnmowers
Air Conditioning Equipment
Household Appliances
Radio and T.V. Receiving
Porcelain Electrical Supplies
Electrical Measuring Instruments
Transformers and Switchgear
Motors and Generators
Industrial Controls
Welding Apparatus and Graphic
Products
Electric Lighting and Wiring
Equipment
Communication Equipment
Electronic Components
Engine Electrical Equipment
X-Ray Equipment and Electronic
Equipment
Engines and Turbines
Farm Machinery
(continued)
-------
TABLE 2 (continued)
OJ
NAME
Machinery and Industrial
Equipment (continued)
Automobiles
Other Transportation
Tires and Inner Tubes
Batteries
INDUSTRY SECTOR
104
105
106
107
108
109
110
111
112
113
114
115
116
117
133
132
134
137
138
139
140
72
129
SIC CODE
3531-2-3
3534-5-6-7
3541
3542
3544-5-8
355
3561-4
3562
3566
3565-7-9
3571-3-4
3572-6-9
358
359
3711
3712
3714
3713
3715
372
373
374
375
3791
3011
3691
3692
DESCRIPTION
Construction, Mining and Oilfield
Materials Handling Machinery
Machine Tools, Metal Cutting
Machine Tools, Metal Forming
Other Metal Working Machinery
Special Industrial Machinery
Pumps, Compressors, Blowers, Fans
Ball and Roller Bearings
Power Transmission Equipment
Industrial Patterns
Computers and Related Machines
Other Office Machinery
Service Industry Machinery
Machine Shop Products
Motor Vehicles
Passenger Car Bodies
MV Parts and Accessories
Truck and Bus Bodies
Truck Trailers
Aircraft
Ship and Boat Building
Railroad Equipment
Cycles and Parts
Trailer Coaches
Tires and Inner Tubes
Storage Batteries
Primary Batteries
(continued)
-------
TABLE 2 (continued)
NAME
INDUSTRY SECTOR
SIC CODE
DESCRIPTION
Buildings and Structures
Ordnance
41
42
43
78
79
80
94
95
100
101
20
21
22
241,242
2432
2433
3211
325
3261
343
3441
3494
3498
1925
1929,1961
1931-41-51-11-99
Lumber and Wood Products
Veneer and Plywood
Millwork and Wood Products
Flat Glass for Windows
Structural Clay Products
Plumbing Fixtures and Bathroom
Accessories
Heating Apparatus and Plumbing
Fabricated Structural Steel
Pipes, Valves, Fittings
Complete Guided Missile
Ammunition
Other Ordnance
Other Industrial"
Applications
Miscellaneous
Materials Consumed in Other Materials
Other Product End Uses, Not Elsewhere
Classified
Source: Office of Management and Budget, 1972 Standard Industrial Classifications, and Clopper
Almon, et al., 1985: Interindustry Forecasts of the American Economy, Lexington Books,
Lexington, Massachusetts, 1974. Compiled by International Research and Technology
Corporation.
-------
TABLE 3. DESCRIPTION OF SOLID WASTE SOURCE CATEGORIES USED IN THIS REPORT
Post-Consumer Residential Wastes -
This category includes product wastes originating in private
households, including bulky items such as household appliances,
as well as tires. The term "post-consumer" refers to old or
obsolete final products or user discards as distinct from the
processing residuals of industrial refining or manufacturing
activities.
Post-Consumer Commercial Wastes -
This category includes wastes emanating from office buildings,
restaurants, hospitals, and all other commercial trade and
service establishments. This category also includes bulky
items (e.g., appliances) and tires from the commercial/insti-
tutional sector. Post-consumer refers to old or obsolete final
products as distinguished from industrial process wastes.
Transport Sector Wastes -
This category includes product category wastes (except tires)
from automobiles and all other modes of transportation, i.e.,
trucks, ships, airplanes, railroad, and transport equipment)
as well as batteries from all modes of transportation.
Industrial Wastes -
This category includes two distinct types of solid waste:
obsolete and current. Obsolete waste includes plant, machinery
and other equipment previously used in the manufacture of products.
Prompt scrap or new scrap is material waste generated during the
fabrication process and is usually marketed or sometimes recycled
within the plant.* Prompt scrap is forecast separately from the
total scrap material created during the fabrication process.
The total industrial waste category includes only the material
generated during the manufacture of products and does not
include sludge, ash, mining or agriculture wastes.
Construction Wastes -
This category includes all wastes from various materials
during the construction of buildings and structures.
Demolition Wastes -
This category includes all wastes generated during the
destruction of various buildings and structures.
* Scrap recycled within a plant is usually referred to as home scrap
(in-house) or mill revert.
15
-------
INFORUM
MACROECONOMIC
PROJECTIONS
- GNP
- DISPOSABLE INCOME
- PQPT1LATTOH
NEW SCRAP (TONS)
RECYCLED
OLD SCRAP (TONS)
RECYCLED
INFORUM
INDUSTRY SECTOR
OUTPUTS; INTER-
INDUSTRY SALES
ANNUAL DOLLAR
INPUT OF MATER-
IALS TO PRODUC-
TION OF PRODUCTS
ANNUAL INPUT OF
MATERIAL TO
PRODUCTION IN
TONS
OUTPUT BY
PRODUCT CATEGORY
(TONS)
DOMESTIC
PURCHASE OF
PRODUCTS
Time Lag
DISCARDED
PRODUCTS
(TONS)
NET SOLID WASTE
DISPOSAL (TONS)
COMMERCIAL
.TRANSPORT
DEMOLITION
Figure 1. Conceptual flow diagram of the IR&T Solid Waste/Recycling Model.
Source: International Research and Technology Corporation.
16
-------
trends in technological innovation, materials substitution, relative prices
and tastes are accounted for in the model itself.
From the INFORUM projection, the inputs of materials to product cate-
gories in constant dollar terms over time are extracted for use in estimating
solid waste generation. The dollar flows are translated into physical flows
on the basis of historical data (from 1960 to 1971) described in the appendix
to this report. The physical flows by material type are then adjusted to
account for new scrap generation (recycled amounts are returned to the input
mode, unrecycled new scrap is included in the industrial waste category) and
exports of products, to estimate the amount of material embodied in products
produced domestically. Imports of products are included to estimate apparent
domestic consumption by product. Diversions of products from the waste stream
are removed at this point.
Each product has an associated average product life assumption. After
appropriate time lags (estimated by normal distribution or step functions),
products are disposed of in the relevant waste stream. Old scrap that is
salvaged is returned to the material input mode, and the remainder constitutes
net solid waste. This component is disaggregated to the consuming sectors,
as described previously. Note, however, that construction wastes, as the
diagram is presented, are included in the new scrap recycled and new scrap
waste modes, since structures are considered as an end-use product.
Figure 2 depicts the flow of materials through the economy, as concep-
tualized in the IR&T model. Primary, secondary and imported materials are
combined to produce finished materials. The secondary materials included in
this stage are obtained from old scrap and recycled new scrap. Finished mat-
erials are used in the production of products, and the scrap from production
is discarded or recycled. Imported finished products are included (exports
are removed, as are diversions from the solid waste stream) and the products
are purchased by consumers. After a time lag, products are discarded. Some
materials from these products are recycled; the remainder, along with new
scrap waste, constitutes total net waste disposal.
The mathematical formulation uses a materials/product history file as
input. This file provides estimates of the use of each material in the manu-
facture of products, from 1960 to 1971, maintained in matrix form. All his-
torical materials/product data used by the model are provided in an appendix
to this report. However, the data for 1971 are displayed in Table 4 as an
example. The data is manipulated through the model, using estimates of the
fraction of each material flowing to each product category that is new scrap,
and adjustments to account for product imports and exports, to arrive at
estimates of net material consumption by product category. For example, the
flows of aluminum to each product category and adjustments for 1971 are dis-
played in Figure 3. Data for all material flows in 1971 are provided in the
aforementioned appendix. Other assumptions regarding average product life,
the disposition of wastes by consuming sector, and the extent of recycling by
material and product, are then used to estimate net solid waste generation.
In forecast years, alternative assumptions regarding overall economic
growth, trends in materials substitution and trends in technology change are
17
-------
FINISHED
MATERIAL
PRODUCTION
CONSUMPTION 03
MATERIAL BY
PRODUCT CATEGORY
PURCHASE OF
PRODUCT BY
CONSUMER
Time Lag
DISCARD OF
PRODUCT
NET
WASTE
DISPOSAL
DIVERSIONS FROM
SOLID WASTE
STREAM
Figure 2. Material flows in the IR&T -Solid Waste/Recycling Model.
Source: International Research and Technology Corporation.
18
-------
TABLE 4. MATERIAL/PRODUCT MATRIX FOR 1971 (Thousand Metric Tons)
Material
Aluminum
Copper
Ferrous Metals
Lead
Zinc
Glass
Leather
Plastics
Rubber
Textiles
Hood
Paper
Paperboard
Newspaper
0
0
0
0
0
0
0
0
0
0
0
9103
0
Books &
Periodicals
0
0
0
0
0
0
0
0
0
0
0
6702
42
Writing
Paper
0
0
0
0
0
0
0
0
0
0
0
3518
0
P R 0 D U
Disposables
0
0
0
0
0
0
0
0
0
12
0
3307
0
C T C A
Beverage
Containers
417
0
1404
0
0
5775
0
0
0
0
0
0
0
T E G 0 R I
Other
Packaging
279
0
6546
56
0
4336
0
2214
0
0
6512
4710
20237
E S
Consumer/
Insti-
tutional
Products
245
135
1698
24
151
2159
87
1135
37
473
1102
321
347
Furniture
67
0
1993
0
0
0
13
422
28
1515
4871
0
0
Apparel
0
0
0
0
0
0
38
0
52
2126
0
0
0
Footwear
0
0
0
0
0
0
367
0
157
30
0
0
40
Household
Durables
134
71
3691
0
29
268
0
257
169
0
0
0
0
(continued
Source: International Research and Technology Corporation, September 1978
-------
TABLE 4 (continued)
to
o
Material
Aluminum
Copper
Ferrous Metals
Lead
Zinc
Glass
Leather
Plastics
Rubber
Textiles
Wood
Paper
Paperboard
Electronics
654
1385
6301
51
122
664
0
540
20
12
0
23
18
Machinery
297
314
13393
67
81
0
1
205
180
39
798
0
0
P
Automobiles
407
190
25557
24
233
992
0
438
248
24
0
0
52
R 0 D U C T
Other
Transpor-
tation
417
59
5994
4
114
102
0
183
34
20
440
0
0
C A
Tires
6
0
0
0
0
0
0
0
1796
283
0
0
0
T E G 0 R I
Batteries
0
0
0
688
0
0
0
0
0
0
0
0
0
E S
Construction
1282
457
35910
102
429
1256
0
1609
0
0
45187
0
5648
Ordnance
0
89
950
89
0
0
0
0
0
0
0
0
0
Other
Industrial
Appli-
cations
335
0
0
349
0
0
0
1016
0
168
0
0
0
Miscellaneous
0
0
4419
0
0
0
0
98
0
0
0
0
0
Source: International Research and Technology Corporation, September 1978.
-------
APPARENT DOMESTIC CONSUMPTION:
ALUMINUM
4534
1
I \
V V '
f if \
MATERIAL CONSUMPTION BY PRODUCT
BEVERAGE
CONTAIN-
ERS
417
OTHER
PACKAGING
279
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
245
FURNITURE
67
HOUSE-
HOLD
DURABLES
134
ELECTRICAL
ELECTRONIC
PRODUCTS
654
1 1
1 \l '
CATEGORY:
MACHINERY
297
AUTO-
MOBILES
407
OTHER
TRANSPORT
417
1
BUILD-
INGS &
STRUC-
TURES
1282
OTHER
INDUSTRIAL
APPLI-
CATIONS
335
NEW SCRAP ADJUSTMENT:
-65
-44
-38
-10
-21
-102
-46
-63
-65
-200
-52
FOREIGN TRADE ADJUSTMENT:
- 8
- 1
- 3
-16
-25
12
-24
-15
15
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
352
\
235
\
i \
199
56
110
1
1
1
1 V . Y V
536
226
TIME LAG
r * ^
356
' \
328
1067
1
1
r v \
298
1
1
1
1 V
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure 3. Material flow diagram of aluminum in 1971 (thousand metric tons).
-------
made within the economic forecasting model. These assumptions dictate the
growth in demand for products and their material composition. The starting
point for the analysis of the impact of all of these factors on the quantity
and composition of solid waste is the establishment of a Reference Scenario,
or set of assumptions, that can then be adjusted in alternative scenarios to
perform sensitivity analyses. Five scenarios were developed for this study,
as described in the next section.
SUMMARY AND CONCLUSIONS
The five scenarios suggest that waste reduction and resource recovery
can be significantly enhanced by encouraging certain technological changes,
materials substitution, increased product life, and recycling. The trends
in materials use, and the mix of forecasted product demands, indicate that
the composition of solid waste may change dramatically. Most notable are
the declining shares of steel and glass, and the increasing shares of alum-
inum and plastics. Despite expected trends in materials substitution and
resource recovery initiatives, the per capita waste load is expected to con-
tinue to increase nationally.
The economic model projects especially high rates of growth for indus-
tries supplying plastics, concrete, and aluminum. A review of past and
current trends in the use of these materials suggests that the projected
growth is reasonable. For two of the materials, plastics and concrete,
little or no recycling has been assumed. Consequently, the share of these
materials in the net solid waste load increases substantially. Aside from
these materials, however, the bulk of the waste load continues to be com-
prised of steel, paper and paperboard, glass and wood.
The national trends suggested by the scenarios must be viewed with
caution by regional solid waste managers and policy analysts. Past and pro-
jected regional consumption patterns and materials usage must be taken into
consideration in the design and implementation of waste reduction and re-
source recovery techniques. Nonetheless, the national trends do provide in-
dicators of the types and directions of regional trends that might be expect-
ed. National trends and known effects of state and local initiatives to
reduce waste and promote recovery, can be used in evaluating proposed pro-
grams. For example, the assumptions regarding trends in recovery of mater-
ials from beverage containers nationally, can be adjusted to account for
state and local initiatives, such as those in Vermont, Oregon, and Fairfax
County, Virginia.
The five scenarios presented in the next section depict a range of
plausible future solid waste loads. The estimates of new wastes in 1990
vary from a total of 295 million metric tons assuming increased product
lifetimes, to 341 million metric tons assuming no technology change or
materials substitution. The projected trends in post-consumer recycling can
reduce the 1990 net waste load by five percent. A modest increase in these
initiatives can reduce the load by an additional one percent, for a total
reduction of 20 million metric tons by 1990. It is clear that the extent of
technology change and materials substitution, the effectiveness of recycling
initiatives, and the average lifetimes of future products, can substantially
22
-------
affect the quantity and composition of the waste generated by our society.
The estimates presented in this study are substantiated to a great extent
by estimates derived in previous studies. Comparisons of these estimates,
presented in Section 3, indicate areas in which this study provides signi-
ficant improvements in the data base and methodologies used to manipulate
solid waste data.
23
-------
SECTION 2
THE FORECASTS
Five scenarios, or sets of assumptions, were developed to estimate the
impacts of technology change and materials substitution, recycling initia-
tives, and average product lifetimes on the future quantity and composition
of solid waste. The first scenario, called the Reference Scenario, provides
a basis for performing this analysis. The assumptions of the Reference Sce-
nario depict a future in which past and current trends in economic growth,
materials substitution, and recycling rates are extrapolated in a more or
less business-as-usual context. In four alternate scenarios, one or more of
the categories of assumptions are either relaxed or emphasized. A Constant
Technology Scenario employs the economic growth assumptions of the Reference
Scenario, but assumes no change from the mix of technologies and materials
used to manufacture products in 1971. The impact of recycling is addressed
in two scenarios; one in which the recycling rates for 1977 are held constant
through 1990, and another in which the assumed recycling rates are increased
ten percent over Reference Scenario assumptions for each material and product
category and each forecast year. Finally, a fifth scenario was developed in
which the average product life assumptions of the Reference Scenario were in-
creased ten percent. Herewith are more detailed descriptions of the
scenarios, and their results.
THE REFERENCE SCENARIO
The projections of solid waste flows are based on estimates of future
economic activity generated by the INFORUM model. The model provides highly
detailed estimates of interindustry transactions in response to purchases of
particular end-use products. These final demand purchases are estimated on
the basis of assumptions regarding growth in income and population, interest
rates, and relative prices. Estimates of aggregate final demand - or Gross
National Product - and its components are shown in Table 5.
As can be seen, Gross National Product is assumed to grow at its long-
term average rate of 3.4 percent per year, supported by continued moderate
increases in productivity. This productivity growth results in part from
the farily rapid growth in producers' durable equipment investment. The
combination of growth in productivity and slowing growth in the size of the
labor force yields a declining unemployment rate.
Nearly two-thirds of GNP is comprised of personal consumption expendi-
tures, as has generally been the case over the past thirty years. It is
24
-------
TABLE 5. REFERENCE SCENARIO GROSS NATIONAL PRODUCT SUMMARY
(Billions of 1971 Dollars Except as Noted)
ro
Components of GNP and
Exogenous Assumptions
Gross National Product
Personal Consumption Expenditures
Durable Goods
Non-Durable Goods
Services
Gross Private Domestic Investment
Structures
Producers' Durable Equipment
Net Exports
Exports
Imports
Government Purchases
Productivity ($1000 Per Employee)
Employed Persons (Millions)
Disposable Per Capita Income (58$)*
Population (Millions)*
Labor Force (Millions)*
Civilian Unemployment Rate (%)*
1971
1063.4
668.2
63.3
148.9
281.0
160.0
87.9
65.7
1.6
65.6
- 64.0
233.7
13.0
81.7
2566.0
207.1
86.9
5.9
1980
1387.0
869.0
82.3
176.0
393.0
212.8
97.9
105.3
23.0
112.7
- 89.7
282.2
14.4
96.6
3307.7
222.8
101.8
5.6
Average Annual
Percentage Growth
1990 1971-1990
2021.4
1328.8
128.1
236.8
641.9
318.1
139.1
161.7
22.6
166.5
- 143.9
352.0
18.3
110.6
4790.6
245.9
118.7
4.7
3.4
3.7
3.8
2.5
4.4
3.7
2.4
4.9
15.0
5.0
4.4
2.2
1.8
1.6
3.3
.9
1.7
-1.2
* Exogenous Assumptions
Source: Compiled by International Research and Technology Corporation from Modified INFORUM Projections.
-------
intersting to note, however, that consumer spending is expected to shift
away from non-durable goods in favor of durables and, especially services.
This shift is likely to have significant impacts on the quantity and compo-
sition of solid waste. The economic model provides disaggregate forecasts
for each component of GNP, which are then used to estimate the output levels
for each of 185 industries. Projected outputs for selected industries are
shown in Table 7. As can be seen, relatively rapid growth is forecast for
the new and maintenance construction industries, which draw on the outputs
of some supplying industries shown, notable cement, concrete and gypsum.
Very rapid growth is projected for the plastic materials and resins industry,
as plastics are increasingly used in place of metals, glass, and paper in
numerous products. Growth in the output of pulp mills is also rapid, spurred
by continued substitution of paper in packaging and increased use of paper
and paperboard in structural applications. Sluggish growth is forecast for
the steel industry, due in large part to substitutions of aluminum in auto-
mobiles and beverage containers.
To indicate the types of material substitutions occurring in the
Reference Scenario, Table 6 displays trends in selected input-output co-
efficients for two industries: motor vehicles and household furniture. In
a number of cases, large rates of substitution are assumed, such as plastics
and aluminum in place of steel in automobiles, and plastics and aluminum in
place of steel and wood in furniture.
TABLE 6. REFERENCE SCENARIO TRENDS OF FINAL DEMAND IN SELECTED
MATERIAL INPUTS PER DOLLAR. 1971-1990.* (1971 = 1.00)
Buying Sector: Motor Vehicles
Selling Sector 1990 Index Value
Plastic Materials and Resins 2.35
Steel .40
Aluminum 2.00
Buying Sector: Household Furniture
Selling Sector 1990 Index Value
Lumber and Wood Products .75
Plastic Materials and Resins 1.44
Glass 1.00
Steel .79
Aluminum 1.22
* Based on the inverse of the Input-Output Matrix.
Source: Compiled by International Research and Technology Corporation from
outputs of a modified INFORUM Model.
The economic projections are combined with the historical materials-flow
data and assumptions regarding new scrap fractions, recycling rates and aver-
26
-------
TABLE 7. REFERENCE SCENARIO OUTPUTS
(Millions of 1971 Dollars)
OF SELECTED INDUSTRIES
N>
-vl
Industry Number and Name
8
11
12
13
16
18
19
41
47
62
73
75
78
81
83
84
85
86
87
92
133
Forestry and Fishery Products
Iron Ore
Copper Ore
Other Nonferrous Ores
Stove and Clay Mining
New Construction
Maintenance Construction
Lumber and Wood Products
Pulp Mills
Plastic Materials and Resins
Rubber Products
Leather Products
Glass
Cement, Concrete, Gypsum
Steel
Copper
Lead
Zinc
Aluminum
Metal Cans
Motor Vehicles
1971
2255
1349
1471
1005
2426
45192
16994
9403
1123
3768T
3665
956
5120
8243
31263
6873
536
420
6751
3888
60163
1980
2971
2128
1826
1237
3864
66422
23522
11427
1786
7644
5692
1068
7005
16870
40046
8971
595
610
11459
4783
75865
Average Annual
Percentage Growth
1990 1971-1990
3974
2536
2319
1833
5649
90123
35484
15727
2746
13521
7749
1298
9458
29210
45996
11650
915
806
19510
6643
111380
3.0
3.4
2.4
3.2
4.5
3.7
4.0
2.7
4.8
7.0
4.0
1.6
3.3
6.9
2.1
2.8
2.9
3.5
5.7
3.3
Source: Compiled by International Research and Technology Corporation from modified INFORUM projections.
-------
age product life, as described in Section 1. The new scrap fractions and
recycling rates assumed for the Reference Scenario are summarized in Tables
8 and 9. For cases in which data exist, separate new scrap fractions have
been employed. In other cases, the same fraction was used for all product
categories. High recycling rates are assumed for inos-t new scrap materials;
exceptions include rubber and leather.
TABLE 8. REFERENCE SCENARIO. ASSUMPTIONS FOR NEW
SCRAP AND NEW SCRAP RECYCLED
Material
Paper
Paperboard
Plastics
Glass
Aluminum
Zinc
Copper
Lead
Ferrous Metals
Wood
Textiles
Rubber
Concrete
Leather
New Scrap
Fraction^-
*
*
.049
*
.156
.146
.310
*
*
*
*
*
.000
.150
Fraction of
New Scrap
Recycled^
.870
.870
.580
1.00
.840
.680
.995
.990
1.00
.740
.600
.250
1.00
.000
* See Table 9.
Fraction of total in-house scrap.
Fraction of in-house scrap that is recycled for re-use.
Source: Compiled by International Research and Technology Corporation. See
Appendix for detailed source listing.
Recycling rates for old scrap by material and product category are pre-
sented in detail in the appendix. However, a summary of the assumed recycl-
ing rates, based on outputs of the model, is provided in Table 10. The table
shows the percent of all materials recovered from both new and old scrap. As
can be seen, the rates are fairly high. By 1990, 29 percent of all paper, 58
percent of the aluminum, and 62 percent of the steel entering the waste
stream is recycled. The high amounts of aluminum and steel are recovered
primarily from automobiles.
28
-------
TABLE 9. SOLID WASTE RECYCLING MODEL REFERENCE SCENARIO, NEW SCRAP
GENERATION BY PRODUCT CATEGORY FOR SELECTED MATERIALS
MATERIAL
Fer-
Paper- Tex- Rub- rous
Product Category Paper board Glass Wood tiles ber Metals Lead
Newspapers .025
Books & Periodicals .150 .170
Writing Paper .061
Disposables .050 .050
Bev. Containers .047 .120
Other Packaging .050 .136 .047 .235 .120 .100
Cons/Inst. Prod. .050 .170 .068 .600 .050 .050 .200 .100
Furniture .600 .050 .050 .200
Apparel .100 .050
Footwear .170 .050 .050
Household Durables .080 .050 .200
Elect/Electronics .050 .170 .068 .050 .050 .200 .100
Machinery .300 .050 .050 .200 .100
Automobiles .170 .133 .050 .050 .200 .100
Other Transportation .133 .100 .050 .050 .200 .100
Tires .050 .030
Batteries .100
Construction .065 .138 .100 .200 .100
Ordnance .200 .100
Other Indust. Appl. .050 .000 .000
Miscellaneous .200
Source: Compiled by International Research and Technology Corporation.
See Appendix for detailed source listing.
29
-------
TABLE 10. REFERENCE SCENARIO, POST-CONSUMER RECYCLING ASSUMPTIONS*
1971 AND 1990
Percent Recovered
Material 1971 1990
Paper and Paperboard
Glass
Metal
Ferrous
Aluminum
Other
Plastics
Rubber and Leather
Textiles
Wood
Concrete
Total Non-Food
Food Waste
Total Product Waste
Yard Waste
TOTAL
23.2
9.9
52.5
52.8
44.8
51.1
6.7
5.0
56.7
18.8
0.0
27.7
0.0
25.6
0.0
23.7
29.0
12.3
61.1
61.8
57.6
61.3
5.9
9.5
54.3
21.2
0.0
28.3
0.0
26.7
0.0
24.9
* The figures presented here are composites for materials recovered from
21 different product categories.
Source: Compiled by International Research and Technology Corporation.
Product lifetime assumptions for all scenarios are shown in Table 11.
Six of the product categories have an average life of under one year, in-
cluding all paper products and beverage containers. In the Reference Scenario
an average life of fifty years is assumed for buildings and structures, while
automobiles, furniture, and household durables have ten-year average life-
times. As with the new scrap fractions and recycling assumptions, the pro-
duct lifetime assumptions can be changed to develop alternative solid waste
scenarios.
Net solid waste projections of the Reference Scenario are shown in
Tables 12, 13, and 14. As can be seen, the total waste load is projected to
grow at a rate of 2.42 percent per year, considerably slower than GNP, but
faster than population. As would be expected, the highest growth rates are
projected for materials with low recycling potential, namely concrete, plas-
tics, rubber and textiles. Continued increases in the use of aluminum in
place of other materials results in fairly rapid growth in the amount of alum-
inum in the waste load. Conversely, the quantity of ferrous metals in the
waste load grows very slowly as a result of substitutions and high resource
recovery rates. Shares of paper and paperboard in the waste load decline
30
-------
TABLE 11. PRODUCT LIFETIME ASSUMPTIONS FOR EACH SCENARIO FOR 1990
Reference
and
Other
Product Category Scenarios
Newspaper
Books, Periodicals & Other
Printing Paper
Writing & Other Fine Paper
Disposable Products
Beverage Containers
Other Packaging & Containers
Consumer & Institutional Products
Furniture & Furnishings
Apparel
Footwear
Household Durables
Electrical & Electronic Products
Machinery & Other Industrial
Equipment
Automobiles
Other Transportation Vehicles
Tires
Batteries
Buildings & Structures
Ordnance
Other Industrial Applications
Miscellaneous
< 1
< 1
< 1
< 1
< 1
< 1
7
10
4
2
10
15
20
10
20
5
3
50
5
2
5
Increased
Product
Lifetime
Scenario*
< 1
< 1
< 1
< 1
< 1
< 1
7.7
11
4.4
2.2
11
16.5
22
11
22
5.5
3.3
55
5.5
2.2
5.5
Source: Compiled by International Research and Technology Corporation.
Detailed references are provided in the Appendix.
* Average product lifetime assumed to be 10% longer than in Reference
Scenario, except for products with assumed lifetimes of one year or
less.
31
-------
TABLE 12. REFERENCE SCENARIO PROJECTIONS OF NET SOLID WASTE
DISPOSAL BY MATERIAL, 1971-1990 (Million Metric Tons)
Material
Aluminum
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Paperboard
TOTAL NON-FOOD RECOVERY
Food Waste
TOTAL PRODUCT RECOVERY
Yard Waste
TOTAL
1971
1.17
43.02
1.06
35.02
10.98
.32
.55
18.70
3.22
1.73
1.38
31.69
.69
16.40
165.93
18.67
184.60
20.37
204.97
1976
1.73
53.87
1.11
37.60
12.98
.38
.61
18.47
4.36
2.21
1.99
32.89
.82
16.71
185.73
19.42
205.15
23.02
228.17
1980
1.94
64.50
1.22
37.91
14.67
.31
.59
20.90
5.94
2.46
2.20
34.79
.81
18.54
206.78
20.09
226.87
25.12
251.99
Avge . Annual
% Growth
1990 1971-1990
2.39
101.15
1.38
36.87
18.54
.33
.84
28.50
10.27
4.29
3.48
37.32
.87
24.59
270.82
22.10
292.92
29.84
322.76
3.83
4.60
1.40
.27
2.80
.16
2.25
2.24
6.29
4.90
4.99
.86
1.23
2.15
2.61
.89
2.46
2.03
2.42
Note: Totals for material and product categories may not be the same due
to rounding.
Source: International Research and Technology Corporation, January 1979.
32
-------
TABLE 13. REFERENCE SCENARIO PROJECTIONS OF NET SOLID WASTE DISPOSAL
BY PRODUCT CATEGORY, 1971-1990 (Million Metric Tons)
Product Categories
Newspapers
Books , Periodicals
Writing/Other Fine Paper
Disposable Products
Beverage Containers
Other Packaging
Consumer/ Inst. Products
Furniture & Furnishings
Apparel
Footwear
Household Durables
Electrical/Electronic Prod.
Machinery/ Indus t. Equip.
Automobiles
Other Transportation
Tires & Inner Tubes
Batteries
Buildings & Structures
Ordnance
Other Industrial Appl.
Miscellaneous
New Scrap
TOTAL NON-FOOD RECOVERY
Food Waste
TOTAL PRODUCT RECOVERY
Yard Waste
TOTAL
1971
6.62
4.43
2.40
.78
6.81
35.08
4.16
3.27
.67
.53
2.28
4.10
8.05
3.29
1.13
1.12
.13
74.09
.38
2.72
3.86
165.90
18.67
184.57
20.37
204.94
1976
6.23
4.36
2.70
.74
8.03
34.94
5.68
3.84
.82
.71
3.02
4.68
8.35
4.42
1.17
1.63
.17
86.31
.53
3.53
3.89
185.75
19.42
205.17
23.02
228.19
1980
6.47
5.25
3.52
.93
7.84
38.18
7.14
4.15
.87
.64
3.44
6.10
8.57
4.00
1.07
1.73
.11
97.96
.34
3.72
4.75
206.78
20.09
226.87
25.12
251.99
Avge . Annual
% Growth
1990 1971-1990
9.11
6.96
5.71
1.32
7.03
45.11
10.52
4.78
1.51
.98
4.75
6.74
9.55
4.13
1.10
3.10
.12
137.58
.30
4.33
6.08
270.81
22.10
292.91
29.84
322.75
1.69
2.41
4.67
2.81
.17
1.33
5.00
2.02
4.37
3.29
3.94
2.65
.90
1.20
-.14
5.50
-.42
3.31
-1.24
2.48
2.42
2.61
.89
2.46
2.03
2.42
Note: Totals for material and product categories may not be the same due
to rounding.
Source: International Research and Technology Corporation.
33
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TABLE 14. REFERENCE SCENARIO PROJECTIONS OF NET SOLID WASTE
GENERATION BY MATERIAL AND SECTOR (Million Metric Tons)
Material and Source
Aluminum
Res /Com
Industrial
Transportation
Demolition
Concrete, Masonry
Demolition
Copper
Res /Com
Industrial
Transportation
Demolition
Ferrous Metals
Res /Com
Industrial
Transportation
Demolition
Glass
Res /Com
Industrial
Transportation
Demolition
Lead
Res /Com
Industrial
Transportation
Demolition
Leather
Res /Com
Industrial
Paper
Res /Com
Industrial
1971
1.17
.77
.17
.19
.04
43.02
43.02
1.06
.45
.22
.13
.27
35.02
16.91
7.61
2.82
7.69
10.98
10.26
.56
.16
.32
.06
.03
.14
.10
.55 .
.47
.08
18.70
18.46
.24
1976
1.73
1.15
.21
.32
.05
53.87
53.87
1.11
.52
.20
.13
.26
37.60
18.07
8.00
3.43
8.10
12.98
12.10
.69
.19
.38
.07
.04
.19
.09
.61
.54
.07
18.47
18.20
.27
1980
1.94
1.24
.28
.35
.07
64.50
64.50
1.22
.65
.18
.14
.25
37.91
19.25
7.93
2.40
8.33
14.67
13.59
.86
.22
.31
.04
.04
.13
.09
.59
.50
.09
20.90
20.60
.30
1990
2.39
1.42
.45
.41
.11
101.15
101.15
1.38
.75
.17
.23
.23
36.87
18.28
8.54
.97
9.08
18.54
16.94
1.28
.32
.33"
.03
.07
.14
.09
.84
.72
.12
28.50
28.09
.41
(continued)
34
-------
TABLE 14 (Continued)
Material and Source
Plastics
Res /Com
Industrial
Transportation
Demolition
Rubber
Res /Com
Industrial
Transportation
Textiles
Res /Com
Industrial
Transportation
Wood
Res /Com
Industrial
Transportation
Demolition
Zinc
Res /Com
Industrial
Transportation
Demolition
Paperboard & Construction
Res /Com
Industrial
Transportation
Demolition
Total, All Materials
Res /Com
Industrial
Transportation
Demolition
1971
3.22
2.95
.18
.08
.01
1.73
1.42
.17
.14
1.38
1.21
.15
.02
31.69
6.77
2.93
.32
21.67
.69
.20
.10
.12
.27
16.40
15.07
.42
.03
.89
165.97
75.00
12.30
4.55
74.12
1976
4.36
3.90
.23
.22
.00
2.21
1.84
.19
.18
1.99
1.81
.15
.03
32.89
7.25
2.85
.35
22.44
.82
.28
.12
.18
.25
16.71
15.19
.44
.04
1.04
185.74
80.92
12.77
5.76
86.29
1980
5.94
5.20
.32
.42
.00
2.46
1.98
.25
.24
2.20
1.95
.21
.03
34.79
7.93
3.42
.36
23.08
.81
.24
.14
.21
.22
18.54
16.81
.49
.04
1.19
206.76
89.98
13.65
5.18
97.95
1990
10.27
8.36
.63
1.25
.03
4.29
3.58
.35
.36
3.48
3.13
.31
.04
37.32
8.20
4.01
.36
24.75
.87
.27
.19
.26
.15
24.59
22.20
.69
.05
1.66
270.83
111.97
15.94
5.35
137.57
Note: Totals for materials may not be the same due to rounding.
Source: International Research and Technology Corporation.
35
-------
only slightly over the forecast period.
Demolition activities are the source of a large fraction of the solid
waste generated in the projections. This sector accounts for all of the con-
crete, almost 25 percent of the steel, and two-thirds of the wood in the 1990
net solid waste load. The residential and commercial sector is the next
largest contributor, accounting for 60 percent of the aluminum, more than
half of the steel and copper, and almost all of the glass, paper, textiles,
and paperboard. High resource recovery from scrap motor vehicles results in
relatively small contributions by the transportation sector.
Projections of the quantities of materials recycled are displayed in
Tables 15 and 16. Over half of the total quantity of recycled materials is
accounted for by recovered ferrous metals. Recycled aluminum triples over
the forecast horizon, while recycling of most other materials more than
doubles. No recycling is assumed for concrete, leather, food and yard wastes.
Most of the recovered materials are from new scrap (49 percent) and auto-
mobiles (14 percent).
The Reference Scenario suggests that total net solid waste per capita
will continue to increase as a result of continued growth by the economy.
However, because of materials substitution and resource recovery initiatives
the growth in solid waste will be significantly lower than growth in GNP.
These indicators are displayed in Table 17. Solid waste per dollar of GNP is
projected to decline at a rate of 0.9 percent per year, and slow rates of
growth are estimated for solid waste per capita.
The Reference Scenario provides an analytical framework for addressing
the impacts of factors affecting the quantity and composition of solid waste.
The impacts of technology change, materials substitution, recycling rates,
and average product lifetime are estimated in four alternative scenarios,
presented below.
IMPACTS OF TECHNOLOGY CHANGE AND MATERIALS SUBSTITUTION
The results of the Reference Scenario indicate that much of the re-
duction in future net solid waste per unit of final demand can be attributed
to the substitution of lighter materials in the manufacture of final products,
and to the changing pattern of final demands. The latter is demonstrated by
higher growth in consumer spending on services, primarily at the expense of
spending on nondurable goods. To analyze the impacts of materials substi-
tution and technology change on solid waste, a scenario called Constant
Technology was formulated. For this scenario, the economic framework and the
new scrap, recycling, and product-life assumptions of the Reference Scenario
were employed, but no changes in the mix of materials and processes used in
the manufacture of products were assumed from 1971 on. That is, the input-
output coefficients of the economic model were held constant at their 1971
values. Comparisons of the net solid waste and recycled materials projections
of each scenario for 1980 and 1990 are given in Tables 18 through 25.
36
-------
TABLE 15. REFERENCE SCENARIO PROJECTIONS OF RECYCLED SOLID WASTE
BY MATERIAL, 1971-1990 (Million Metric Tons)
Material
Aluminum
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Paperboard
TOTAL NON-FOOD RECOVERY
Food Waste
TOTAL PRODUCT RECOVERY
Yard Waste
TOTAL
1971
.95
0
1.35
39.21
1.20
.53
0
4.89
.23
.12
1.81
7.34
.28
5.71
63.62
0
63.62
0
63.62
1976
1.23
0
1.37
42.32
1.40
.73
0
4.95
.28
.18
2.31
7.13
.31
6.66
68.87
0
68.87
0
68.87
1980
1.78
0
1.68
50.00
1.69
.67
0
5.70
.37
.20
2.59
8.66
.37
7.45
81.16
0
81.16
0
81.16
1990
3.24
0
2.18
59.69
2.59
1.39
0
9.86
.65
.54
4.15
10.04
.52
11.89
106.74
0
106.74
0
106.74
Note: Totals for material and product categories may not be the same due
to rounding.
Source: International Research and Technology Corporation.
37
-------
TABLE 16. REFERENCE SCENARIO PROJECTIONS OF RECYCLED SOLID WASTE
BY PRODUCT CATEGORY, 1971-1990 (Million Metric Tons)
Product Category
Newspapers
Books, Periodicals
Writing & Other Fine Paper
Disposable Products
Beverage Containers
Other Packaging & Containers
Consumer & Institutional
Products
Furniture & Furnishings
Apparel
Footwear
Household Durables
Electrical & Electronic Products
Machinery & Industrial Equipment
Automobiles
Other Transportation
Tires & Inner Tubes
Batteries
Buildings & Structures
Ordnance
Other Industrial Applications
Miscellaneous
New Scrap
TOTAL NON-FOOD RECOVERY
Food Waste
TOTAL PRODUCT RECOVERY
Yard Waste
TOTAL
1971
1.98
.55
.30
0
.27
4.07
.09
.52
1.10
0
.12
.46
.51
12.79
3.36
.10
.34
1.11
.03
0
.14
35.79
63.63
0
63.63
0
63.63
1976
1.86
.54
.33
0
.45
5.03
.11
.71
1.42
0
.17
.49
.52
16.56
3.13
.16
.52
1.69
.04
0
.18
34.98
68.89
0
68.89
0
68.89
1980
2.16
.65
.43
0
.56
5.84
.16
.92
1.48
0
.34
.69
.99
18.51
3.40
.16
.46
2.36
.04
0
.40
41.60
81.15
0
81.15
0
81.15
1990
3.91
1.33
1.09
0
1.20
11.50
.56
1.42
2.61
0
1.13
1.52
2.24
14.56
4.72
.48
1.05
4.22
.08
0
1.06
52.10
106.78
0
106.78
0
106.78
Note: Totals for material and product categories may not be the same due
to rounding.
Source: International Research and Technology Corporation.
38
-------
TABLE 17. REFERENCE SCENARIO SUMMARY OF NET SOLID WASTE PER CAPITA
AND PER DOLLAR OF GNP, 1971-1990
Average
Annual
Percentage
Growth
1971 1980 1990 1971- 1990
Sector/Description
All Sectors:
Net Solid Waste Per Capita (Tons) .91 1.13 1.31 1.49
Kilos per capita per day 2.71 3.10 3.60 1.49
Net Solid Waste Per $1000 GNP (Tons) .19 .18 .16 -0.90
Residential/Commercial Sector:
Net Solid Waste Per Capita (Tons) .55 .61 .67 1.04
Kilos per capita per day 1.51 1.66 1.83 1.04
Source: International Research and Technology Corporation.
As would be expected, the projected amounts of paper, glass, steel, and
wood in the waste load are greater in the Constant Technology Scenario,
while the amounts of aluminum and plastic are less. Food and yard waste
projections are the same for all scenarios, since these components are
estimated as a function of projected population and residential housing
demand, respectively, both of which are the same in each scenario. The
concrete waste estimates are also the same since this component emanates
from buildings and structures erected prior to 1971. The effect of the
Constant Technology Scenario assumptions on the total net solid waste pro-
jection is an additional 18 million tons by 1990, an increase of 5.5 percent
over the Reference Scenario projection. However, the Constant Technology
Scenario projects substantially higher amounts of recycled materials,
especially steel, glass, and wood, resulting in a total recycled material
estimate for 1990 that is 34 million tons greater than that of the Reference
Scenario, reflecting a difference of 32 percent. A large part of this
difference can be attributed to the continued reliance on steel in the
manufacture of automobiles and other products, as assumed in the Constant
Technology Scenario (combined with the relatively higher recycling rate
for this material), as well as to the continued reliance on the use of
glass in beverage containers, which is also assumed. The projections show
substantially lower amounts of aluminum and plastics recovered or disposed
of as waste, as a result. Substantial differences are also shown for wood
and leather, materials that are substituted for at fairly high rates in the
Reference Scenario.
39
-------
TABLE 18. COMPARISON OF 1980 NET SOLID WASTE PROJECTIONS
BY MATERIAL (Million Metric Tons)
Material
Aluminum
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Paperboard
TOTAL -NON-FOOD
Food Waste
TOTAL PRODUCT
Yard Waste
TOTAL
Increased
Constant Product
Reference?- Technology^ Lifetime^
1.94
64.50
1.22
37.91
14.67
.31
.59
20.90
5.94
2.46
2.20
34.79
.81
18.54
206.78
20.09
226.87
25.12
251.99
1.64
64.50
1.22
40.06
16.21
.34
.65
22.22
5.37
2.43
2.24
- 35.85
.83
19.76
213.32
20.09
233.41
25.12
258.53
1.86
51.50
1.16
32.57
14.40
.18
.59
20.89
5.63
2.46
2.17
33.88
.81
18.35
186.45
20.09
206.54
25.12
231.66
Constant Increased
Recycling* Recycl ing5
2.05
64.50
1.23
40.86
14.71
.34
.59
21.08
5.94
2.46
2.20
34.79
.83
18.54
210.12
20.09
230.21
25.12
255.33
1.87
64.50
1.16
35.24
14.63
.25
.59
20.53
5.94
2.45
1.97
34.79
.72
18.13
202.77
20.09
222.86
25.12
247.98
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
o
Scenario assumes no change in technology or mix of materials
use in forecast period.
Scenario assumes average lifetime of products to increase 10 %.
Scenario assumes no change in post-consumer recycling rates
during forecast period.
5Scenario assumes 10% increase in postTConsumer recycling rates
over reference case assumptions.
40
-------
TABLE 19. COMPARISON OF 1980 NET SOLID WASTE PROJECTIONS
BY PRODUCT CATEGORY (Million Metric Tons)
Increased
Constant Product Constant Increased
Product Category Reference1- Technology2 Lifetime3 Recycling^ Recycling5
Newspapers 6.47
Books, Periodicals 5.25
Writing/Other Fine Paper 3.52
Disposable Products .93
Beverage Containers 7.84
Other Packaging 38.18
Consumer /Inst. Products 7.14
Furniture & Furnishings 4.15
Apparel . 87
Footwear . 64
Household Durables 3.44
Electric/Electron. Prod. 6.10
Machinery / Indus t. Equip. 8.57
Automobiles 4.00
Other Transportation 1.07
Tires & Inner Tubes 1.73
Batteries . 11
Buildings & Structures 97.96
Ordnance . 34
Mis cellaneous 3.72
New Scrap 4. 75
TOTAL NON-FOOD 206.78
Food Waste 20.09
TOTAL PRODUCT 226.87
Yard Waste 25.12
TOTAL 251.99
6.86
5.50
3.67
1.00
8.04
43.14
7.16
4.18
.87
.67
3.45
6.10
8.57
3.98
1.07
1.74
.13
97.96
.36
3.71
5.15
213.31
20.09
233.40
25.12
258.52
6.47
5.25
3.52
.93
7.84
38.18
6.90
4.08
.86
.64
3.29
5.53
8.18
3.83
1.01
1.78
0
83.08
.35
0
4.75
186.47
20.09
206.56
25.12
231.68
6.64
5.25
3.52
.93
7.96
38.48
7.20
4.21
.87
.64
3.60
6.11
9.00
5.05
1.27
1.73
.14
98.50
.36
3.92
4.75
210.13
20.09
230.22
25.12
255.34
6.26
5.19
3.47
.93
7.78
37.60
7.05
4.05
.72
.64
3.41
6.05
8.47
2.15
.73
1.72
.07
97.72
.33
3.68
4.75
202.77
20.09
222.86
25.12
247.98
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
o
Scenario assumes average lifetime of products to increase 10%.
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling
rates over reference case assumptions.
41
-------
TABLE 20. COMPARISON OF 1980 RECYCLING PROJECTIONS BY
MATERIAL (Million Metric Tons)
Material
Aluminum
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Faperboard
TOTAL NON-FOOD
Food Waste
TOTAL PRODUCT
Yard Waste
TOTAL
Reference
1.78
0
1.68
50.00
1.69
.67
0
5.70
.37
.20
2.59
8.66
.37
7.45
81.16
0
81.16
0
81.16
Increased
Constant Product
Technology2 Lifetime3
1.55
0
1.71
56.34
1.80
.78
0
6.08
.32
.20
2.62
9.73
.39
8.05
89.57
0
89.57
0
89.57
1.70
0
1.65
49.06
1.69
.22
0
5.70
.37
.21
2.55
8.66
.37
7.45
79.63
0
79.63
0
79.63
Constant
Recycling4
1.66
0
1.66
47.04
1.64
.63
0
5.53
.37
.21
2.59
8.66
.35
7.45
77.79
0
77.79
0
77.79
Increased,
Recycling1
1.85
0
1.74
52.67
1.72
.73
0
6.07
.37
.22
2.82
8.66
.47
7.86
85.18
0
85.18
0
85.18
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
Scenario assumes average lifetime of products to increase 10%.
4 -
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario, assumes 10% increase in post-consumer recycling rates
over reference case assumptions.
42
-------
TABLE 21. COMPARISON OF 1980 RECYCLING PROJECTIONS BY
PRODUCT CATEGORY (Million Metric Tons)
Increased
Constant Product
Product Category Reference1 Technology Lifetime3
Newspapers
Books, Periodicals
2.16
.65
Writing/Other Fine Paper .43
Disposable Products
Beverage Containers
Other Packaging
Consumer /lost. Products
Furniture & Furnishings
Apparel
Footwear
Household Durables
Electric/Electron. Prod.
Machinery /Ind us t. Equip.
Automobiles
Other Transportation
Tires & Inner Tubes
Batteries
Buildings & Structures
Ordnance
Other Industrial Appl.
Miscellaneous
New Scrap
TOTAL NON-FOOD
Food Waste
TOTAL PRODUCT
Yard Waste
TOTAL
0
.56
5.84
.16
.92
1.48
0
.34
.69
.99
18.51
3.40
.16
.46
2.36
.04
0
.40
41.60
81.15
_0
81.15
0
81.15
2.29
.68
.45
0
.57
6.67
.16
.92
1.48
0
.34
.69
.99
18.55
3.40
.16
.53
2.36
.05
0
.40
48.86
89.55
0
89.55
0
89.55
2.16
.65
.43
0
.56
5.84
.16
.89
1.47
0
.33
.61
.95
18.29
3.31
.17
0
2.15
.05
0
0
41.60
79.62
0
79.62
0
79.62
Constant Increased,.
Recycling Recycling^
2.00
.65
.43
0
.44
5.55
.10
.85
1.48
0
.19
.68
.56
17.46
3.20
.17
.43
1.82
.03
0
.20
41.60
77.84
0
77.84
0
77.84
2.37
.71
.48
0
.61
6.43
.25
1.01
1.63
0
.37
.74
1.09
20.36
3.74
.18
.50
2.60
.05
0
.44
41.60
85.15
0
85.15
0
85.15
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
3
Scenario assumes average lifetime of products to increase 10%.
A
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling
rates over reference case assumptions.
43
-------
TABLE 22. COMPARISON OF 1990 NET SOLID WASTE PROJECTIONS
BY MATERIAL (Million Metric Tons)
Material
Al imfiT^nn
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Paperboard
TOTAL NON-FOOD
Food Waste
TOTAL PRODUCT
Yard Waste
TOTAL
Increased
Constant Product
Reference1 Technology2 Lifetime3
2.39
101.15
1.38
36.87
18.54
.33
.84
28.50
10.27
4.29
3.48
37.32
.87
24.59
270.82
22.10
292.92
29.84
322.76
2.03
101.15
1.39
41.74
23.53
.39
1.02
32.54
8.01
3.78
3.68
40.53
.92'
27.92
288.63
22.10
310.73
29.84
340.57
2.30
80.77
1.39
31.50
18.18
.22
.84
28.48
9.80
4.17
3.39
36.35
.87
24.32
242.58
22.10
264.68
29.84
294.52
Constant Increased
Recycling* Recycling5
2.96
101.15
1.42
47.64
18.97
.55
.84
30.43
10.27
4.44
3.48
37.32
.95
26.06
286.48
22.10
308.58
_29.fl4
338.42
2.24
101.15
1.31
34.61
18.46
.21
.84
27.79
10.27
4.24
3.11
37.32
.74
23.86
266.15
22.10
288.25
29.84
318.09
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
3
Scenario assumes average lifetime of products to increase 10%.
4
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling
rates over reference case assumptions.
44
-------
TABLE 23. COMPARISON OF 1990 NET SOLID WASTE PROJECTIONS
BY PRODUCT CATEGORY (Million Metric Tons)
Increased
Constant Product
Product Category Reference1 Technology2 Lifetime3
Newspaper 9.11
Books, Periodicals 6.96
Writing/ Other Fine Paper 5.71
Disposable Products 1.32
Beverage Containers 7.03
Other Packagin 45.11
Constmer/Inst. Products 10.52
Furniture & Furnishings 4.78
Apparel 1.51
Footwear . 98
Household Durables 4.75
Electric/Electron. Prod. 6.74
Machinery/ Indus t. Equip. 9.55
Automobiles 4.13
Other Transportation 1.10
Tires & Inner Tubes 3.10
Batteries .12
Building & Structures 137.58
Ordnance . 30
Other Industrial Appl. 0
Miscellaneous 4.33
New Scrap 6.08
TOTAL NON-FOOD 270.81
Food Waste 22.10
TOTAL PRODUCT 292.91
Yard Waste 29.84
TOTAL 322.75
10.35
7.82
6.38
1.51
9.62
54.85
11.02
5.43
1.55
1.07
5.01
6.91
9.68
3.93
1.10
2.77
.13
137.58
.36
0
4.32
7.22
288.61
22.10
310.71
29.84
340.55
9.11
6.96
5.71
1.32
7.03
45. 11
10.19
4.58
1.49
.99
4.43
6.69
9.56
3.86
1.07
3.01
0
115.07
.30
0
0
6.08
242.56
22.10
264.66
29.84
294.50
Constant Increased
Recycling* Recycling?
10.02
7.38
6.05
1.32
7.76
49.19
10.94
5.05
1.51
.98
5.61
7.31
11.12
5.81
1.68
3.25
.29
139.61
.36
0
5.13
6.08
286.45
22.10
308.55
29.84
338.39
8.72
6.83
5.60
1.32
6.91
43.96
10.36
4.63
1.25
.98
4.63
6.61
9.33
3.34
.84
3.05
.01
137.16
.29
0
4.23
6.08
266.13
22.10
288.23
29.84
318.07
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during .the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
3
Scenario assumes average lifetime of products to increase 10%.
A
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling rates
over reference case assumptions.
45
-------
TABLE 24. COMPARISON OF 1990 RECYCLING PROJECTIONS BY
MATERIAL (Million Metric Tons)
Material
Aluminum
Concrete, Masonry
Copper
Ferrous Metals
Glass
Lead
Leather
Paper
Plastics
Rubber
Textiles
Wood
Zinc
Paperboard
TOTAL NON-rFOOD
Food Waste
TOTAL PRODUCT
Yard Waste
TOTAL
Increased
Constant Product
Reference1 Technology2 Lifetime3
3.24
0
2.18
59.69
2.59
1.39
0
9.86
.65
.54
4.15
10.04
.52
11.89
106.75
0
106.75
0
106.75
2.65
0
2.38
86.80
3.16
1.65
0
11.27
.47
.47
4.32
13.25
.53
13.77
140.72
0
140.72
0
140.72
3.17
0
2.19
58.31
2.59
.34
0
9.86
.65
.53
4.05
10.04
.53
11.89
104,15
0
104.15
0
104.15
Constant Increased
2.67
0
2.14
48.92
2.17
1.18
0
7.94
.65
.39
4.15
10.04
.44
10.42
91.11
0
91.11
0
91.11
3.39
0
2.26
61.95
2.67
1.51
0
10.57
.65
.59
4.52
10.04
.65
12.62
111.42
0
111.42
0
111.42
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
3
Scenario assumes average lifetime of products to increase 10%.
4
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling rates
over reference case assumptions.
46
-------
TABLE 25. COMPARISON OF 1990 RECYCLING PROJECTIONS BY
PRODUCT CATEGORY (Million Metric Tons)
Increased
Constant Product
Produce Category Reference1Technology2Lifetiine3
Newspapers 3. 91
Books, Periodicals 1.33
Writing/Other Fine Paper 1.09
Disposable Products 0
Beverage Containers 1.20
Other Packaging 11.30
Consumer/lost. Products .56
Furniture & Furnishings 1.42
Apparel 2.61
Footwear 0
Household Durables 1.13
Electric/Electron. Prod. 1.52
Machinery/ Indus t. Equip. 2.24
Automobiles 14.56
Other Transportation 4.72
tires & Inner Tubes .48
Batteries 1.05
Buildings & Structures 4.22
Ordnance . 08
Other Industrial Appl. 0
Miscellaneous 1.06
New Scrap 52.10
TOTAL NON-FOOD 106.75
Food Waste 0
TOTAL PRODUCT 106.75
Yard Waste 0
TOTAL 106.75
4.44
1.49
1.22
0
1.69
15.36
.64
1.60
2.67
0
1.27
1.54
2.27
24.47
4.77
.41
1.20
4.22
.11
0
1.06
70.27
140.70
0
140. 70
Q
140. 70
3.91
1.33
1.09
0
1.20
11.50
.54
1.35
2.57
0
1.06
1.50
2.24
14.70
4.69
.46
0
3.82
.08
0
0
52.10
104.14
0
104.14
0
104.14
Constant Increased
Recycling Recycling^
2.99
.91
.75
0
.47
7.42
.14
1.14
2.61
0
.27
.94
.67
12.88
4.14
.33
.87
2.20
.02
0
.27
52.10
91.12
0
91.12
0
91.12
4.30
1.46
1.20
0
1.32
12.65
.71
1.57
2.87
0
1.25
1.64
2.46
15.35
4.98
.53
1.15
4.65
.09
0
1.17
52.10
111.45
0
111.45
0
111.45
Note: Totals for material and product categories may not
be the same due to rounding.
Source: International Research and Technology Corporation,
January, 1979.
Scenario assumes moderate change in technology, materials
substitution and recycling rates during the forecast period.
2
Scenario assumes no change in technology or mix of materials
use in forecast period.
3
Scenario assumes average lifetime of products to increase 10%.
4
Scenario assumes no change in post-consumer recycling rates
during forecast period.
Scenario assumes 10% increase in post-consumer recycling
rates over reference case assumptions.
47
-------
The Constant Technology Scenario shows that-in the absence of materials
substitution and technology change, the quantity of solid waste that will
have to be managed in future years may be slightly greater if past and
current trends in substitution were to cease. Alternatively, the scenario
suggests that substantially higher quantities of the materials that are
relatively easy to recycle can be recovered, since the projected net waste
load of the Constant Technology Scenario in 1990 is only 5.5 percent higher
than that of the Reference Scenario, while the estimate of total recycled
material is 31.8 percent higher.
THE EFFECTS OF PRODUCT LIFE
The lowest net solid waste projection is found in the Increased Product
Lifetime Scenario. For this projection, the assumed average product lifetime
was increased 10 percent over Reference Scenario values for all products
with average lifetimes over 1 year. All other assumptions of the Reference
Scenario were maintained, including the new scrap factors and recycling rates
for new and old scrap.
The impacts of the assumptions are greatest on the projections for
steel and concrete, materials that are typically used in products with
relatively long average lifetimes - household durables, automobiles, and
particularly, buildings and structures. The differences in the projections
for these two materials alone account for over 90 percent of the total
difference between scenarios. For all other materials, the differences are
less than 5 percent, since they are typically incorporated in products with
relatively short average lifetimes. The projected total net solid waste
load for 1990 in the Increased Product Lifetime Scenario is over 28 million
metric tons lower (8.7 percent) than that of the Reference Scenario, while
the quantity of materials recycled is less than 3 million metric tons lower
(2.4 percent).
THE IMPACTS OF RECYCLING
For two of the alternate scenarios, variations in the recycling assump-
tions of the Reference Scenario were examined. Both of these alternate
scenarios employ the technology change, materials substitution, new scrap,
and product life assumptions of the Reference Scenario. One scenario, called
Constant Recycling, assumes no change in the recycling rates for old scrap
from 1976 on, and the other, called Increased Recycling, reflects an assumed
10 percent increase in the Reference Scenario recycling rates, for all
materials in all products, for all forecast years. These recycling assump-
tions were applied at the point of disposal; the new scrap and other
diversion rates assumed in the Reference Scenario were not changed. The old
scrap recycling rates assumed for 1990 in each scenario are shown in Table 26.
The results suggest that the greatest post-consumer resource recovery
potential lies with metals. The amount of unrecycled metal in the 1990
48
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TABLE 26. RECYCLING ASSUMPTIONS OF EACH SCENARIO FOR 1990 (OLD SCRAPPOST-CONSUMER)*
PRODUCT CATEGORY
Newspapers
Books & Periodicals
Writing Paper
Disposables
Beverage Containers
Other Packaging
Consumer & Institutional Products
Furniture
Apparel
Household Durables
Electrical/Electronics
Machinery & Industrial Equipment
Automobiles
Other Transportation
Tires
Batteries
Construction
Ordnance
Other Industrial
Miscellaneous
PAPER
R
.30
.16
.16
.15
CR
.23
.11
.11
.10
IR
.33
.18
.18
.17
PAPERBOARD
R
.16
.25
.15
CR
.11
.20
.10
IR
.18
.28
.17
GLASS
R
.06
.06
CR
.03
.03
IR
.07
.07
ALUMINUM
R
.30
.10
.20
.20
.25
.95
.30
.60
.60
.20
.20
CR
.15
0
.09
.09
.15
.93
.25
.30
.30
.13
.09
IR
.33
.11
.22
.22
.28
1.00
.33
.66
.66
.22
.22
ZINC
R
.06
.10
.29
.10
.20
.20
.52
CR
.06
.10
.23
.10
.20
.20
.30
IR
.07
.11
.31
.11
.22
.22
.57
VO
(continued)
-------
Ul
o
TABLE 26 (continued)
PRODUCT CATEGORY
Newspapers
Books & Periodicals
Writing t>aper
Disposables
Beverage Containers
Other Packaging
Consumer & Institutional Products
Furniture
Apparel
Household Durables
Electrical/Electronics
Machinery & Industrial Equipment
Automobiles
Other Transportation
Tires
Batteries
Construction
Ordnance
Other Industrial
Miscellaneous
COPPER
R
.19
.38
.38
.40
.33
.33
.30
.19
CR
.18
.36
.36
.37
.31
.31
.29
.18
IR
.21
.42
.42
.44
.36
.36
.33
.21
LEAD
R
.80
.50
.90
.90
.30
.50
CR
.65
.20
.40
.75
.30
.20
IR
.88
.55
.99
.99
.33
.55
FERROUS METALS
R
.50
.50
.20
.20
.25
.10
.20
.95
.95
.30
.20
.20
.20
CR
.15
.15
.01
.01
.05
.00
.05
.85
.85
.15
.05
.05
.05
IR
.55
.55
.22
.22
.28
.11
.22
1.00
1.00
.33
.22
.22
.22
TEXTILES
R
.66
.66
CR
.66
.66
IR
.73
.73
RUBBER
R
.15
CR
.10
IR
.17
*Figures indicate the fraction of total old (post-consumer) scrap assumed to be available for recycling
for reuse.
Note: R denotes Reference and other scenarios.
CR denotes Constant Recycling
IR denotes Increased Recycling
For materials and products not shown, the recycling rate
is assumed to be zero (plastics, wood, leather and
concrete recycling rates are zero).
Source: Compiled by International Research
and Technology Corporation. For more
information on sources of information,
see Appendix.
-------
waste load is more than 11 million metric tons higher in the Constant
Recycling Scenario than in the Reference Scenario, reflecting a difference
of 28 percent. Household durables and transportation equipment account for
the bulk of the difference. The fraction of aluminum recovered from junked
automobiles is assumed to double in the Reference Scenario, from 30 percent
in 1971 to 60 percent in 1990, in contrast to the Constant Recycling Scenario,
in which only 30 percent of the aluminum from automobiles scrapped in 1990
is recovered. Similarly, 85 percent of the steel in automobiles scrapped
in 1971 was recovered, and this fraction increases to 95 percent in the
Reference Scenario. In the Constant Recycling Scenario, the fraction remains
at 85 percent throughout the forecast. The impact on the total net waste
load is a projection that is 15.7 million metric tons greater than that of
the Reference Scenario; a difference of 4.9 percent.
In the Increased Recycling Scenario, the change is less dramatic, but
still significant. The difference between the two scenarios regarding the
net waste load projection for 1990 is only 1.4 percent, but the amounts of
steel, aluminum, other metals and textiles are 6 to 12 percent lower than
the amounts in the Reference Scenario.
51
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SECTION 3
COMPARISON OF ESTIMATES AND FORECASTS OF THE
QUANTITY AND COMPOSITION OF SOLID WASTE
Previous studies reporting estimates of solid waste and its composition
vary in scope and, to some extent, in definitions of product categories
analyzed. In the forecast years, estimates vary primarily due to differences
in basic assumptions. In this section, comparisons are made between estimates
provided by this study with estimates used by EPA, and estimates from other
studies.
Sources of solid waste are usually categorized as either residential,
commercial/institutional, or municipal. The latter is roughly a consol-
idation of the residential and commercial categories. In the IR&T study, the
residential and commercial contributions to the total solid waste load are
estimated on the basis of aggregating specific product categories assumed to
emanate from these sectors. Comparisons of post-consumer residential and
commercial solid waste estimates by IR&T and EPA (7,36) are provided in Tables
27 and 28. Estimates of total waste differ by only 0.7 percent in 1971, and
by 7.4 percent in 1975. Although the estimates of total waste from these
sectors are quite similar, there are some fairly large differences between
estimates for specific materials and product categories. In order to clarify
the reasons for these discrepancies, EPA's descriptions of solid waste cate-
gories and methodologies are briefly discussed.
The EPA estimates exclude agricultural, mining, and industrial process-
ing waste; construction and demolition residuals; street sweepings (except
packaging material); heavy or bulky tree and landscape waste (except normal
yard waste); sewage sludge; and residuals from automobiles and trucks (except
tires). These items have similarly been excluded from the IR&T estimates
of residential and commercial waste. IR&T's estimates of transportation
equipment, industrial and demolition wastes are included in Table 29, only
to emphasize the scope of the present study on solid waste.
It would appear from the table that the discrepancies between estimates
for individual material and product categories are not due to differences
in materials or product categories. Differences in the description of some
product end-use markets and methodologies employed may explain some of the
variations, although the approach used by both IR&T and EPA was to analyze
the flow of materials from production through consumption to disposal. Both
studies use production data for each material and both include net exports
to obtain estimates of apparent domestic consumption. Nevertheless, discrep-
52
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TABLE 27. COMPARISON OF POST-CONSUMER NET RESIDENTIAL AND COMMERCIAL
SOLID WASTE BY MATERIAL (Million Metric Tons)
Material
Paper
Glass
Metal
Ferrous
Aluminum
Other
Plastics
Rubber & Leather
Textiles
Wood
TOTAL NON-FOOD
PRODUCT WASTE
Food Waste
TOTAL PRODUCT
WASTE
Yard Waste
Misc. Inorganics
TOTAL
IR&T
33.5
10.3
18.4
(16.9)
( .8)
( -7)
3.0
1.9
1.2
6.8
75.1
18.7
93.8
20.4
114.2
1971
EPA
33.5
10.9
10.7
( 9.6)
( .7)
( .4)
3.8
3.0
1.6
4.2
69.9
20.0
89.9
21.9
1.6
113.4
Percent
Diff.*
- 5.6
- 5.5
72.0
(76.0)
(14.3)
(75.0)
-21.1
-36.7
-25.0
61.9
7.4
- 6.5
4.3
- 6.9
.7
IR&T
34.0
12.9
20.0
(18.2)
( 1-0)
( -8)
4.0
2.3
1.7
8.4
83.3
19.3
102.6
22.5
125.1
1975
EPA
33.8
12.1
11.1
( 9.8)
( -8)
( .4)
4.0
3.0
1.9
4.5
70.5
20.7
91.2
23.6
1.7
116.5
Percent
Diff.*
.6
6.6
80.2
(85.7)
(25.0)
(100.0)
0.0
-23.3
-10.5
86.7
18.2
- 6.8
12.5
- 4.7
7.4
Note: Totals may not add due to rounding. Parentheses indicate estimates
for subcomponents of the metals category.
* Percent difference is calculated using the formula: [(IR&T/EPA)-!] x 100
Source: International Research and Technology Corporation.
Frank A. Smith, "Comparative Estimates of Post-Consumer Solid
Waste," Resource Recovery Division, Office of Solid Waste Manage-
ment Programs, U.S. Environmental Protection Agency, May 1975;
and, Resource Recovery and Waste Reduction. Fourth Report to
Congress, SW-600, Office of Solid Waste, U.S. Environmental
Protection Agency, 1977.
ancies between material data used in each analysis may be in part due to
differences in conversion factors used to change reported units of bulk
consumption into tonnage data (e.g., lumber feet into tons of wood, or
number of glass containers into tons of glass, etc.). In addition, vari-
ations in other adjustments to the data, such as diversions and time lags,
may help explain differences in the material estimates of solid waste.
It should be noted that the estimates of total residential and commercial
waste are virtually identical in 1971, and fairly close in 1975.
53
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TABLE 28. COMPARISON OF POST-CONSUMER NET RESIDENTIAL AND COMMERCIAL
SOLID WASTE BY PRODUCT CATEGORY (Million Metric Tons)
Product
Newspapers , Books ,
Magazines
Containers/Packaging
Major Household Appl.
Furniture/Furnishings
Clothing & Footwear
Other Products
TOTAL NON-FOOD
PRODUCT WASTE
Fook Waste
TOTAL PRODUCT
WASTE
Yard/Misc . Organics
TOTAL
IR&T
13.5
41.9
2.3
3.3
1.2
12.9
75.1
18.7
93.8
20.4
114.2
1971
EPA
9.4
37.9
1.9
2.9
1.1
16.7
69.9
20.0
89.9
23.5
113.4
Percent
Diff.*
43.6
10.6
21.1
13.8
9.1
-22.8
7.4
- 6.5
4.3
-13.2
.7
IR&T
15.0
45.0
2.9
3.7
1.4
15.4
83.4
19.3
102.7
22.5
125.2
1975
EPA
8.9
37.9
2.1
3.1
1.2
17.2
70.5
20.7
91.2
25.4
116.5
Percent
Diff.*
68.5
18.7
38.1
19.4
16.7
-10.5
18.2
- 6.8
12.5
-11.4
7.5
Note: Totals may not add due to rounding.
* Percent difference is calculated using the formula: [(IR&T/EPA) - l] x 100
Source: International Research and Technology Corporation.
Frank A. Smith, "Comparative Estimates of Post-Consumer Solid
Waste," Resource Recovery Division, Office of Solid Waste
Management Programs, U.S. Environmental Protection Agency, May
1975; and, Resource Recovery and Waste Reduction. Fourth Report
to Congress, SW-600, Office of Solid Waste, U.S. Environmental
Protection Agency, 1977.
implying that the-major differences for specific materials are due to the
manner in which each study chose to allocate materials to product categories.
The largest percentage difference between estimates for 1971 lies with
metals. The EPA-estimates of ferrous metals in net solid waste are based on
a study by W.J. Regan, et al., (37), while IR&T used a time series on steel
shipments by detailed product category from the American Iron and Steel Insti-
tute (38,39). Regan, who uses estimates provided by Battelle Memorial Insti-
tute (40), reports that the determination of obsolescent or post-consumer
scrap is a "complex, imprecise calculation." Regan also indicates that the
Battelle steel estimates are provided only as a "rough approximation of magni-
tude." Consequently, it would appear that the American Iron and Steel Insti-
54
-------
TABLE 29. ESTIMATES OF TRANSPORTATION, INDUSTRIAL, DEMOLITION AND
CONSTRUCTION WASTES FOR THE YEAR 1971 (Million Metric Tons)
Solid Waste Source Sector and Product Category
Transportation 4.4
Automobiles 3.3
Batteries .1
Other Transportation 1.0
Industrial 12.7
Machinery & Equipment 8.0
Ordnance . 8
New Scrap 3.9
Demolition 74.1
Construction 1.4
Source: International Research and Technology Corporation.
tute time series data used by IR&T in conjunction with materials-flow analysis
and input-output techniques, may provide more reliable estimates of the amount
of steel in the solid waste load.
IR&T data for aluminum, copper, lead, and zinc are based on time series
published in government sources as outlined in the appendix. EPA suggests
that their estimation procedure was adjusted for nonferrous metals and plas-
tics due to a lack of detailed knowledge for these materials. IR&T's esti-
mate for the "other" metal category is much larger than that of EPA's, due
to the inclusion by IR&T of specific zinc, lead and copper estimates; the
EPA emphasis is on copper and lead in the waste stream.
Estimates of the amount of plastic in the 1971 residential and commer-
cial waste are much closer, and for 1975, they are identical. The different
estimates for 1971 may be explained by differences in data sources used. EPA
uses estimates for major resins only; their estimates are derived from two
data sources that provide statistics for the "big-five" polymers: low density
polyethylene, high density polyethylene, polystyrene, polyvinyl chloride,
and polypropylene. To estimate total use of plastics, EPA assumes that these
five materials comprise 88 percent of all plastics used in packaging, and 67
percent (a 1970 estimate) of all plastics used in major appliances, furniture,
apparel, footwear, and other products. However, IR&T uses time series data
from Modern Plastios (41) by resin and product category, so that adjustments
to obtain control totals were not necessary.
Large discrepancies also exist between the EPA and IR&T estimates of
wood in residential and commercial waste, although both studies employed
time series data from the Forest Service (42). EPA, however, states that
55
-------
wood packing and shipping materials discarded by the shipping end-use category
are used solely in industrial applications, while IR&T assumes that this
category should be included in the commercial waste stream. Consequently, the
IR&T wood waste estimate is substantially higher than EPA's.
Definitional differences are the primary cause for discrepancies between
estimates by product category. IR&T includes writing and other fine paper with
newspapers, books and magazines. As stated previously, IR&T includes wooden
packaging and containers with commercial wastes while EPA delegates this
category to industrial waste. Also, EPA assumes that most of the other
nonferrous metals category is comprised of copper and lead. EPA did not trace
materials-flows, but instead obtained data on copper waste from Battelle (40)
and estimates of tin and lead consumed in tin can manufacture from another
EPA study (45). An arbitrary figure of 0.1 million tons was used to estimate
all other nonferrous metals, which seems to be the major explanation for the
difference between IR&T and EPA. IR&T's estimates for copper, lead, and
zinc are based on time series data from the Bureau of Mines (44). Zinc used
in household durables, commercial and institutional products, and electrical/
electronic products amounted to 302 thousand metric tons - over a quarter of
total zinc use in 1971.
IR&T and EPA projections of post-consumer solid waste are compared in
Table 30. The EPA projections are based on product end-use analyses for
all major categories by Midwest Research Institute (26). The table compares
estimates of gross discards (total waste generation before recycling),
material recovery (diversions from post-consumer discards), and net waste
disposal (final residual wastes remaining after material recovery). EPA's
projections are referred to as "base line" by EPA and by Midwest Research
Institute, since the projections assume no new intervention by the federal
government with regard to resource recovery or waste reduction incentive
programs; no new regulations on non-hazardous waste disposal; and no other
new programs in the solid waste management field.
As can be seen in Table 30, estimates by IR&T and EPA of total net solid
waste disposal in 1971 are identical. Slight absolute variations are found
between estimates of gross discards and resource recovery. Projections of
gross discards are comparable, differing by just 6.3 percent in 1990. The
large differences between projected resource recovery estimates and projec-
tions of net waste disposal are due to different recycling rates assumed.
The EPA projections suggest rather rapid increases in the fraction of
gross discards recycled, from about 6 percent in 1971 to about 26 percent
in 1990. Such a dramatic increase seems to contradict the fundamental
base line assumption of no new initiatives. EPA states that the projections
are indeed hypothetical, yet the large increases in resource recovery imply
the existence of large-scale waste processing installations. Without
incentive programs or substantial increases in the demand for secondary
materials, the EPA projections of resource recovery appear unrealistic.
The IR&T projections, on the-other hand, seem more reasonable, as the
fraction of gross discards recovered increases from 8.1 percent in 1971
to 14.6 percent in 1990.
56
-------
TABLE 30. COMPARISON OF POST-CONSUMER ESTIMATES AND PROJECTIONS OF PER CAPITA WASTE GENERATION
(Million Metric Tons)
Ul
Category /Des cript i on
Total Gross Discards
Million Tons /Year
Kilos/Person/Day*
Less: Resource Recovery
Million Tons /Year
Kilos/Person/ Day*
Equals: Net Waste
Disposal
Million Tons /Year
Kilos /Person/ Day*
IRT
124
1.64
10
.13
114
1.51
1971
EPA
121
1.60
7
.09
114
1.51
% Diff.
2.5
2.5
42.9
42.9
0.0
0.0
IRT
149
1.83
14
.17
135
1.66
1980
EPA % Diff.
159
1.96
17
.21
142
1.75
-6.3
-6.3
-17.7
-17.7
-4.9
-4.9
IRT
192
2.15
28
.31
164
1.83
1990
EPA % Diff.
205
2.29
53
.59
152
1.70
-6.3
-6.3
-47.2
-47.2
7.9
7.9
Average
Annual
Percentage
Growth
1971 - 1990
IRT EPA
2.33
1.44
5.57
4.68
1.93
1.02
2.81
1.91
11.24
10.40
1.53
.63
* Per capita solid waste figures were based on U.S. Census population estimates assuming a 365-day
year. The population figures used were: 1971: 207.05 million; 1980: 222.80 million;
1990: 245.08 .million.
Source: International Research and Technology Corporation, January 1979. Frank A. Smith, "Quantity
and Composition of Post-Consumer Solid Waste: Material Flow Estimates for 1973 and Baseline
Future Projections," Waste Age3 April 1976.
-------
TABLE 31. COMPARISON OF POST-CONSUMER ESTIMATES AND PROJECTIONS (Million Metric Tons)
Material
Paper
Glass
Metsla
Ferrous
Alunlnun
Other Non-Ferrous
Plastics
Wood
Food Wastes
Yard Wastes
Miscellaneous Organlcs
TOTAL
Kilos/Person/Day**
1971
*
IR&T MR I Diff.*
33.5 35.5 - 5.6
10.3 11.0 - 6.4
18.4 10.8 70.4
(16-9) ( 9.7) 74.2
( .8) ( .7) 14.3
( .7) ( .4) 75.0
3.0 3.8 -21.1
6.8 4.2 61.9
18.7 20.0 - 6.5
20.4 21.9 - 6.9
1.7
114.2 113.6 .5
1.51 1.50 .5
1975
Z
IR&T MRI Diff.*
34.0 38.3 -11.2
12.9 13.2 - 2.3
20.0 12.1 65.3
(18.2) (10.6) 71.7
( 1.0) ( 1.1) - 9.1
( .8) ( .4) 100.0
4.0 5.2 -23.2
8.4 4.6 82.6
19.3 20.9 - 7.7
22.5 23.9 - 5.9
1.9
125.1 125.4 - .2
1.60 1.61 - ,2
1980
X
IR&T MRI Diff.*
37.4 46.0 -18.7
13.6 14.9 - 8.7
21.4 13.7 56.2
(19.3) (11.9) 62.12
( 1.2) ( 1.4) -14.3
( .9) ( .5) 80.0
5.2 7.6 -31.6
7.9 5.2 51.9
20.1 22.3 - 9.9
25.1 26.6 - 5.6
2.3
135.2 144.7 - 6.6
1.66 1.78 - 6.6
1990
Z
IR&T MRI Diff.*
50.3 61.1 -17.7
16.9 15.4 9.7
20.7 17.6 17.6
(18.3) (14.9) 22.8
( 1.4) ( 2.1) -33.3
( 1.1) ( .6) 83.3
8.4 12.0 -30.0
8.2 6.7 22.4
22.1 25.2 -12.3
29.8 33.1 -10.0
3.0
169.9 182.5 -10.2
1.83 2.04 -10.2
Average Annual
Percentage Growth
1971 - 1990
IR&T MRI .
2.16 2.90
2.64 1.79
.62 2.60
.42 2.28
2.99 5.95
2.41 2.16
5.57 6.24
.99 2.49
.88 1.22
2.01 2.20
3.03
1.92 2.53
1.02 1.63
Ul
00
Note: Totals may not add due to rounding.
* Percent difference is calculated using the formula: [(IR&T/EPA) - l] x 100
** Per capita solid waste figures were based on U.S. Census population estimates assuming a 365 day
year. The population figures used were 1971: 207.05 million; 1975: 213.60 million; 1980: 222.80
million; 1990: 245.05 million.
Source: International Research and Technology Corporation.
Midwest Research Institute, Base Line Forecasts of Resource Recovery, 1972 to 1990, Final
Report, U.S. Environmental Protection Agency, 1975.
-------
MRI's projections by material category are compared with IR&T's
projections in Table 31. The starting point for the MRI projections is
the set of 1971 values developed by EPA. The MRI and IR&T total solid
waste estimates in 1971 and 1975 are nearly identical, but show varia-
tions in 1980 and 1990; however, large discrepancies are found between
estimates for specific materials. Although the MRI approach is based on
a materials-flow analysis (i.e., input approach), in which the flow of
materials through production and consumption stages.are traced, for a
number of materials (notably glass, ferrous metals and plastics) esti-
mates were arbitrarily adjusted based on judgement. The major discrep-
ancies are found in comparing estimates for metals and wood. A detailed
analysis of aluminum waste was conducted by MRI, but estimates for other
nonferrous metals are based on EPA data for 1971 that were discussed pre-
viously. MRI increased EPA estimates for nonferrous metals in 1980,
1985, and 1990 by 0.1 million tons arbitrarily. In contrast, IR&T per-
formed materials-flow analyses for aluminum, copper, zinc, and lead, us-
ing historical data published by various government sources. To project
wood wastes, MRI extrapolated EPA's 1971 estimate using an assumed aver-
age annual percentage growth rate of 2.5. Using IR&T's materials-flow
approach coupled with input-output techniques, wood wastes are projected
to increase less than 1.0 percent per year.
Similarly, the MRI textile waste projection is based on EPA's es-
timate for 1971 and an assumed growth rate of 3.7 percent per year. A
much higher growth in textile wastes is projected using the IR&T mater-
ials-flow methodology. MRI projections of rubber and leather waste are
presented together, although different methodologies were used for the
two materials. In the analysis of the rubber end-use market, MRI assum-
ed that 75 percent of all rubber waste is comprised of discarded tires
and inner tubes. The balance is comprised of rubber from other uses, of
which half is assumed to be discarded in the residential and commercial
waste stream. MRI projects leather waste based on EPA's data for 1971,
and an assumed average annual growth rate of 3.0 percent. IR&T's analy-
sis yields a projected growth rate of 4.4 percent per year for rubber
and leather, based on time series of production data for both materials.
In the MRI study, six materials were analyzed in detail: ferrous
metals, aluminum, glass, plastics, rubber and paper. The analysis in-
cluded demand forecasts for each industry producing these materials,
estimates of the generation of waste by source, and estimates of the
quantities of recoverable materials. With the exception of ferrous
metals, differences in the forecasts for the six materials are due
largely to different recycling assumptions employed or to differences in
the delineation of source categories. For the other materials, the IR&T
projections are not based on growth rates assumed outright, but on
materials-flow analysis and on input-output techniques that take mater-
ials substitution and technology change into account. The MRI baseline
forecasts are in the process of being updated, but this work will not
be available until later this year. A comparison at that time may
clarify the reasons for discrepancies discussed in this section.
59
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A comparison of demolition waste estimates was also made. The
Massachusetts Institute of Technology (MIT) conducted a study (45) of
demolition wastes, based on a survey of Boston, Atlanta, and Los Angeles
debris. An estimate for the nation was derived on the basis of 0.327
metric tons per person, an average for the three cities. IR&T's anal-
ysis of demolition wastes, based on estimates of the total amount of
materials used in construction over the past fifty years, resulted in
an estimate of 0.357 tons per capita in 1971, a difference of 9.2 per-
cent. It should be noted that IR&T does employ the MIT time series as
the source for the quantity of concrete that goes to the buildings and
structures end-use market annually. The difference in demolition waste
estimates is due to different study approaches as well as different
waste sources of data for the other materials flowing to the construc-
tion end-use (e.g., ferrous metals, plastics, glass, lead, copper, alum-
inum, and wood). In addition, the MIT study indicates that brick and
clay products constitute a fairly large proportion of demolition wastes;
the inclusion of these materials in the IR&T analysis could significant-
ly improve estimates of total demolition debris in the solid waste
stream.
60
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SECTION 4
METHODOLOGY
The methodology used to forecast the quantity and composition of
solid waste combines estimation procedures using production data (i.e.,
materials-flow analysis) with input-output forecasting techniques. The
methodology requires historical data on materials use by product manu-
facturers, and a linkage of this data to the economic forecasting model.
As discussed briefly in Section 1, historical data on physical flows are
maintained in materials/product matrices for the years 1960 to 1971.
The 1971 physical data is linked to specific 1971 dollar flows in the
economic model in order to estimate future physical flows on the basis
of projected dollar flows. To estimate the makeup of future solid waste
flows, the projected gross physical flows are adjusted to account for
new scrap, imports and exports, time lags from production through con-
sumption to disposal, and recycling of old (post-consumer) scrap.
DATA DEVELOPMENT
As described briefly in Section 1, the estimation of the quantity
and composition of solid waste involves the use of production data and
materials-flow analysis with input-output forecasting techniques. Pro-
duction data by material and product category end-use were obtained
through a literature search. The historical material data files for the
years 1960-1971 for each material and the material flow diagrams for
each material for the year 1971 are presented in the appendix.
The physical flows of materials, measured in tons, were obtained
from data published by government agencies and trade associations. Con-
sistency with data published by the Census (46) was established wherever
possible. In the historical time series data, many of the product end-
use categories were in general terms, such as "containers and packaging"
or "transportation." An effort was made to disaggregate these large
categories into their components, in order to forecast the composition
of the solid waste stream in greater detail. For example, containers
and packaging tonnage data were divided into beverage containers and
other packaging and containers for the appropriate material history file,
and transportation data for a particular material were divided into por-
tions used in automobiles and other transportation. The production data
for larger categories were adjusted and allocated to more specific end-
uses using data from the input-output table of the economic model. For
some of the material history files, it was not necessary to disaggregate
the general categories to the specific end-uses, due to the fact
61
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that the detailed categories were specified (e.g., aluminum end-use cate-
gories) or that very detailed categories were compiled to meet the specific
end-uses (e.g., plastics and textiles end-use categories). In addition to
the present data on residential and commercial sources of solid waste, pro-
duction data were also found for the buildings and structures sector and
transportation equipment. This data made it possible to forecast the quan-
tity of solid waste from transportation equipment, and from construction and
demolition.
It should be noted that the number of material categories examined in
this study is larger, and therefore more comprehensive, than that of previous
studies. For example, specific data on nonferrous metals were obtained
from government sources, while, with the exception of aluminum, the quantity
of lead, zinc, and copper entering the solid waste stream has been grouped
under the heading "nonferrous" in other studies. The product end-use category
allocations for each material are valuable in predicting trends in recycling,
materials substitution, and future demand-supply relationships in secondary
materials markets. The addition of concrete to the list of materials pro-
vided the data base necessary for forecasting the bulk of demolition and
construction wastes .
The following is a description of the sources of history production
data by material. Time series for each material from 1960 to 1971, further
information on data sources, product categories, major adjustments to the data,
and sources for recycling assumptions are provided in the appendix.
The time series in the two Bureau of Mines publications, Mineral Foots
and Problems (44) and Mineral Commodity Profiles Aluminum 197? (47) were
selected to update and expand the aluminum data. The source of most of the
figures on the end-use demand patterns included in these government publi-
cations is the Aluminum Associations ' s Statistical Review (48). The trade
association's figures are based on shipments of finished products and semi-
fabricated products as reported in industry questionnaires. The Bureau of
Mines publications use the distribution of aluminum among product categories
to allocate total aluminum figures to final end-use products.
Concrete
Consumption of concrete was assumed to be entirely for buildings and
structures. The data were taken from the MIT study, The Investigation of
the Potential for Resource Recovery from Demolition Wastes (45) published
in 1976.
Copper
Data from the Bureau of Mines Mineral Facts and Problems (44) and Mineral
Commodity Profiles in Copper 1977 (49) were used in the model. The source of
the end-use data in the two Bureau of Mines publications is Copper Develop-
ment Association (50) data as well as the Mineral Yearbook (51) data on total
annual demand for copper, which served as a control total. The Copper Develop
62
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merit Association's source of data is industry reports on brass mill products,
Current Industrial Reports (52,53) on insulated wire and cable, and estimates
of castings and powder by the trade association's research department. The
end-use data on copper were derived from company reports of shipments of
sheet, strip, and plumbing, etc., to the various end-use markets.
Ferrous Metals
The methodology to derive product category estimates for iron and steel
included data not previously available, as well as end-uses not previously
specified in the economic model. The product category estimates are now
available from the Bureau of Mines Mineral Foots and Problems (44). The
government compiles data on steel mill shipments from the American Iron and
Steel Institute's Annual Statistical Report (38,39) and data on foundry
shipments from the Department of Commerce's Current Industrial Report (54).
The data on steel mill shipments are gathered from industry questionnaires.
Glass
No comprehensive source of data was found for glass production in tonnage.
Estimates for glass containers, pressed and blown glass, and flat glass were
derived from separate sources. Apparent domestic consumption in tonnage for
glass containers was derived from the Glass Container Manufacturer's Institute
(GCMI) and the Glass Packaging Institute (55,56). In 1976, the Bureau of the
Census in Current Industrial Reports (57) published for the first time tonnage
estimates for glass container production by type of container. The ton-per-
container ratio assumed by the Census was used to allocate glass container
shipments between beverage and other containers for this study.
Apparent domestic consumption estimates in tonnage for pressed and blown
glass products and flat glass were not available until recently when the
Federal Energy Administration (now the Department of Energy) began to collect
data on industrial energy usage based on a BTU-per-ton of production from
representative industries. Estimates of tonnage were derived from raw mater-
ials consumed in tonnage for glass, sand, soda ash, and cullet from the Census
of Manufacture's (57) "Materials Consumed by Kind" table for the pressed and blown
glass industry, SIC 3229 and the flat glass industry, SIC 3211. A comparison
of estimates obtained by this methodology with the DOE estimates indicates
substantial agreement considering DOE accounted for only 60% of the output
from the pressed and blown glass industry. End-use allocations for pressed,
blown and flat glass were derived from the Census of Manufactures and from the
INFORUM Model. Glass fiber for textiles was excluded from this study because
of its inclusion in textiles.
A comparison of the IR&T glass materials-flow estimation procedure with
the Smith/Franklin methodology indicated that both used the GCMI data for
glass containers. No documentation of other glass estimates was available.
However, in A Solid Waste Estimation Procedure: Materials-Flow Approach (27).
EPA used an MRI estimate that employed a similar methodology to that used in
this study.
63
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Lead
The data from the time series in two Bureau of Mines publications,
Mineral Facts and Problems (44) and Mineral Commodity Profiles Lead 1977
(58), were selected for the IR&T time series. As a result of informative
conversations with the lead commodity specialists at the Bureau of Mines,
the methodology used to group the various lead products from the Minerals
Yearbook categories into the Mineral Facts and Problems major end-use markets
was altered. Batteries were segregated from the transportation end-use cate-
gory and the electrical and electronic products category. Batteries, specifi-
cally storage batteries, which include batteries, grids and posts, and battery
oxides, are primarily used in automobiles. They are also used to some extent
in the electrical and electronic products category for standby power and
emergency lighting. The time series totals for batteries were derived from
the Minerals Yearbook (51) storage battery figures. The residual transporta-
tion end-use figure included the use of lead in bearings, solder, and weights
and ballast in wheels and keels, respectively. The residual direct use of
lead in transportation was allocated between automobiles and other transpor-
tation end-use based on estimates from INFORUM. The residual direct use of
lead in the electrical and electronics-end-use market includes the use of
lead in cable coverings, solder, and brass and bronze.
The data for the ordnance and buildings and structures end-use cate-
gories were taken directly from the Bureau of Mines time series because des-
criptions of the markets correspond to end-use categories in the IR&T Model.
Lead is used in pipes, traps and beds, sheet lead, calking lead, and solder
in the buildings and structures market. In the ordnance end-use market,
lead is used in the manufacture of ammunition.
Leather
No published estimates of material consumption in tonnage were found.
IR&T derived estimates of leather consumption by product end-use from ton-
per-dollar ratios in the Census of Manufactures (46) and from the dollar
flows in the INFORUM Model.
Paper and Paperboard
Tonnage estimates of apparent consumption from the Current Industrial
Report, Pulpj Paper and Board (59) provided the basis for the material history
report for paper and paperboard. These data were compared to data in the
American Paper Institute's annual report, Statistics of Paper and Paperboard
(60). There is general agreement between Census estimates and those provided
by API; however, small variations of up to 4% may exist in any given year
between the sources. In this study, data directly from the Bureau of the
Census is considered to be the best available source because it provides the
underlying economic data of the input-output model used in this study.
Estimates for paper and paperboard employed in this study are comparable
to those used in other materials-flow studies, including those by William
Franklin for EPA's Office of Solid Waste and the Midwest Research Institute.
64
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There are small differences in this procedure due to variations in defin-
itions of product categories.
Plastics
An investigation of data sources indicated that no comprehensive
source for apparent domestic consumption estimates exists for plastics
by product category. Two major sources of estimates of apparent domes-
tic consumption are the U.S. International Trade (formerly Tariff)
Commission's annual publication Synthetic Organic Chemicals (61) and the
Society of the Plastic Industry's (SPI) Facts and. Figures of the Plastics
Industry (62). A third source is McGraw-Hill's publication Modern
Plastics (41), which uses SPI totals and allocates plastic tonnage
to major market end-uses. According to an editor of Modern Plastics^
SPI obtained estimates of plastics production and sales in 1970 from
the U.S. Tariff Commission. The plastics industry considers the Tariff
estimates to be unreliable because they include production data on
textiles using plastic products and exclude other specific plastics
categories. SPI, on the other hand, derives its estimates from a plant
survey.
Due to the desire to maintain consistency between total consumption
and market end-use allocations as well as expressed industry misgivings
with the Tariff Commission estimates, the data from Modern Plastics were
selected. Specific major market end-use data were derived from Modern
Plastics. Unfortunately, a portion of plastic usage was left unaccounted
for by this source, and data were only available from 1967. To fill in
the gaps, an analysis of Modern Plastics detailed end-use estimates by
resin was made to account for consumer and institutional products, i.e.,
luggage, medical products, records, optical goods, tools, and recreation-
al products, machinery and other industrial equipment. Trends in plastic
usage, published in Markets for Plastics (63) , were used to fill in data
gaps for earlier years. A miscellaneous category was used for plastics
in agricultural applications. The other industrial applications category
was used for the remaining plastics, assuming that the residual was used
in adhesives, coatings and other applications that are consumed in the
production of other finished materials (e.g., textiles, paints).
Although the methodology selected has shortcomings given the lack
of data and the ubiquitous nature of plastics usage, these estimates are
the best available. Comparing this methodology to that of William
Franklin's projections for EPA's Office of Solid Waste, differences were
noted. Franklin did employ Modern Plastics data for packaging; however,
other uses were derived from a secondary source: A.D. Little's Incen-
tives for Recycling and Reuse of Plastics (64). An examination of these
estimates indicated that this source originally utilized Modern Plastics
data for its estimates. The EPA estimates seem to be out of date given
the fact that the study was published in 1972 and plastics usage has
changed considerably in recent years.
65
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Rubber
The only available source of apparent domestic consumption of rubber
is the Rubber Manufacturers Association's publication (65). The data is di-
vided into tire and non-tire products and the problem is to allocate rubber
among non-tire market end-uses. Rubber Age (66) has published estimates of
rubber use for footwear, mechanical goods, wire and cable, latex foam pro-
ducts, and other; however, there is no corresponding tonnage data available
for the market end-use categories in this study. Consequently, estimates
were derived from Census of Manufactures (46) data for the Fabricated Rubber
Products, NEC Industry, SIC 3069.
A comparison of this methodology with William Franklin's approach for
EPA indicated that although RMA data was also used, it appeared that no
attempt was made to allocate non-tire rubber usage to more precise end-use
categories.
Textiles
The total annual consumption figures for textiles were taken from the
time series in the Textile Economics Bureau publication, Textile Organon (67).
Textile Organon specifies many market end-uses for textiles, so the various
end-uses were grouped and calculated according to market end-uses currently
in the IR&T Model.
Wood
Estimates of total apparent domestic consumption of wood by product
category end-uses were derived from the U.S. Forest Service's annual report
The Demand and Price Situation for Forest Products (68) and another publica-
tion, The Outlook for Timber in the United States (42). The estimates do not
include woodpulp. The product category allocations for buildings and struc-
tures, including mobile homes, furniture, consumer products, machinery and
other transportation were derived from the latter source. Mobile homes are
classified as buildings and structures, in order to be consistent with the
revised 1972 SIC definitions. The IR&T data is based on 1973-1974 data
because the Forest Service will not be updating its end-use survey until later
this year. Although Forest Service data were also used by EPA, tonnage esti-
mates were made through the use of conversion ratios. Thus, some differences
can be noted in materials end-use estimates.
Zinc
The time series in two Bureau of Mines publications, Mineral Foots and
Problems (44) and Mineral Commodity Profiles Zino 1977 (69), were selected for
the zinc time series. The source of the brass and bronze end-use data for
zinc in the government publications is the Copper Development Association's
publication Annual Data 1976: Copper Supply and Consumption 1956-1975 (50).
The source of the government figures for the use of zinc in galvanizing is the
American Iron and Steel Institute's Annual Statistical Report (38, 39). The
trade association data is based on industry questionnaires.
66
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LINKAGE TO THE ECONOMIC FORECASTING MODEL
The most difficult part of the methodology involves the linkage of
physical material flows data to dollar flows in the economic model.
The input-output model used in this study provides considerable variety
with its 185 sector scheme. However, as with an industry-based input-
output model, the estimates of dollar flows between industries are not
directly related to the analysis of flows by specific materials to spe-
cific products. To illustrate the problem, flows of aluminum in an in-
terindustry model are considered. The aluminum industry sells some al-
uminum directly to the motor vehicles industry and some indirectly
through the metal stampings industry. The metal stampings industry
sells aluminum metal stampings (e.g., fenders, hoods, trunk lids, etc.)
to the motor vehicles industry and also to consumers (e.g., aluminum
pots and pans). Part of the sales by the metal stampings industry to
the motor vehicles industry includes stampings made from steel and
other metals. It is clear from this example that it would be difficult
to distinguish material-specific flows between industries from industry-
specific dollar flows for the purpose of estimating the amounts of spe-
cific materials used to manufacture final products. To do so would
require a very detailed, commodity-specific input-output table, and no
such table of the U.S. economy exists in a form readily available for
this study. Consequently, for the purpose of mapping physical material
flows to interindustry transactions, a very basic assumption is made.
It is assumed that interindustry transactions in dollar terms provide
reasonable indicators of physical material flows, and that the relation-
ships between the dollar flows and physical flows hold over time.
The proportionality assumption in itself does not solve the problem
of distinguishing the amount of aluminum in metal stampings sold to
automobiles from the amount of steel, since the relative amounts of al-
uminum and steel in the metal stampings sold to the motor vehicles in-
dustry can change over time. To account for this aspect, the relation-
ship between the physical flow of aluminum used in the manufacture of
motor vehicles, to the dollar transactions between the metal stampings
and motor vehicles industry, is determined by a set of transactions:
the sales by the aluminum industry directly to the motor vehicles in-
dustry, sales of aluminum to metal stampings, and sales of metal stamp-
ings to the motor vehicles industry. This approach, called the "path
products" or "chain" approach, was developed for the purpose of estima-
ting solid waste flows in the earlier work by IR&T for EPA, and is dis-
cussed in detail in the final report for that study (33).
The chain approach makes use of the interindustry sales (input-
output) coefficients of the economic forecasting model. In the model,
the dollar output of each of the 185 sectors is estimated by summing
sales to other industries (i.e., intermediate demands) and sales of
finished goods (i.e., final demands). Consequently, the sales by an
industry i, X,, can be shown mathematically as:
67
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185
where a denotes the dollar input requirement of industry i per dollar
-1 output of industry j (X.), and
F. denotes the final demand for outputs of industry i.
Alternatively, the sales by each industry can be shown in matrix
form, as follows:
X
X
185
'1,1
X2
'2,2
X3
'2,3
1,185
a!85,l E185,2 S185,3 al85,185
imes X + F
X
Xl
X2
_X185
+
"Fl
F2
_V_
Here, X and F are vectors of outputs and final demands, respectively,
and A is a matrix of dollar-input-per-dollar-output coefficients. In
solving for the outputs of each industry, the final demand vector and
'A' matrix are given, so that
X = (I - A)
-1
where (I - A) is the inverse of the identity matrix minus the A matrix.
This relationship is derived algebraically from the earlier relation-
ship, A = AX + F.
The terms of the inverse matrix suggest the amount by which the out-
put of an industry is affected by the final demand for each industry's
output. If we call the inverse matrix B, we can show the relationship
as:
XI
'2,1
Lb185,l
X2
'2,2
'1,3
'2,3
b!85,2 b!85,3 '
1,185
'2,185
J185,185_
"185
Hence, the output of aluminum is determined as the sum of the products
of the inverse terms for the aluminum industry times the final demands
for the output of each industry, i.e., X = BF. Within this formula-
tion, the product of the inverse term for the aluminum industry times
final demand for motor vehicles, reflects not just the aluminum used
68
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in the manufacture of motor vehicles (including the aluminum in metal
stampings purchased by the motor vehicles industry), but all indirect
impacts of motor vehicles sales to final demand on aluminum industry
outputs. To illustrate, the motor vehicles industry requires a number
of aluminum products to provide support for the manufacture of motor
vehicles (e.g., light bulbs, tools, and other equipment). Such articles
or tools are not incorporated in the final products, but are extended
during the production process. The inverse terms also indicate impacts
on the aluminum industry that are completely removed from motor vehicle
manufacturing. The motor vehicles industry buys products from indus-
tries that require products made of aluminum in their own productive
processes, and these impacts are also reflected in the aluminum to motor
vehicles inverse term.
A simplified approach for relating physical materials flows to
dollar flows would be to associate the material flows with the products
of the inverse terms times final demands. For this purpose, the amount
of aluminum actually incorporated in the motor vehicle is assumed to be
proportional to the relationship of the inverse term to output over
time. This is the apporach used in the study by Research Triangle In-
stitute, described in Section 1 (32). The limitations of the approach
are primarily concerned with the problem of differentiating, the amount
of materials incorporated in final products, from materials incorpor-
ated in other products expended during their manufacture, the propor-
tions of which are likely to change over time.
However, the differentiation can be made using the uninverted
input coefficients, since the inverse is a formal power series expan-
sion of the input coefficients. That is:
B = (I - A)"1
= I + AB
= I + A + A B
Written algebraically, we have:
bij - 1 + aij + £ aikVj + 5 ?
Since all of the coefficients are less than or equal to 1.0, the
products of the coefficients times other coefficients get successively
smaller as the expansion moves to the right in this equation. Hence,
an approximation of the inverse can be obtained after summing several
of the elements of the series. Furthermore, through disaggregating the
inverse terms into components comprised of individual A matrix coeffic-
ients, the dollar flows that are the best indicators of physical mater-
ial flows to particular products can be identified. By isolating these
"chains," the sequences of dollar flows that reflect the flows of mat-
erials that are not incorporated in a subject final product, can be re-
moved. These include input requirements of industries supplying raw
materials (e.g., purchases by the mining and agriculture sectors),
service costs (e.g., transportation, repairs, and insurance), and over-
69
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head and manufacturing costs (e.g., office supplies, machine tools,
electricity and other fuels).
The selection of specific chains also avoids the prorating and
aggregation errors inherent in input-output analysis. Such problems
occur when the flow of material from one industry to another continues
on to third and fourth industries which purchase intermediate products
from the second industry that contains different proportions of the
material. For example, the proportion of aluminum metal stampings to
steel metal stampings used by the motor vehicles industry is different
than the proportions used in the manufacture of pots and pans.
The selection of chains to be used as indicators of materials-
flows is necessarily based on judgment. It is desirable, however, to
tighten the causal connection between final product use and material
composition, by eliminating as many spurious chains as possible. Be-
cause of the enormous number of chains contained in a 185-sector input-
output table, it is not possible to examine every chain in a material
flow. Consequently, for this study only major direct and indirect
flows for each material to each product category were selected.
The selection procedure has theoretical foundations that are dis-
cussed at length in the previous IR&T study (33). The report for that
study demonstrates methods for adjusting flows in the input-output
model to estimate solid waste emanating from households. For this
study, the major chains relating materials to all product end-uses were
selected.
In the household waste study, it was shown that the economy, as
represented by an input-output table, appears to consist of a relative-
ly small number of major dependencies and a very large number of dis-
tant effects. This is demonstrated in Table 32, which shows that re-
latively few chains are required to account for most of the output of
sectors producing the materials relevant to this study. The number of
chains required to account for all flows greater than half of one per-
cent of output is considerably larger, but still manageable. By nearly
doubling the number of chains considered, all flows accounting for more
than two-tenths of a percent of total output would be included, but
this addition would add little to the accuracy as evidenced by the small
difference in coverage at the two thresholds.
The chains selected for use in the study are presented in detail
in the appendix; however, an example for one material, textiles, is
shown in Figure'4. The numbers in this diagram refer to sectors of the
input-output model.
ESTIMATING FUTURE SOLID WASTE
The chains selected for each material flowing to each end-use pro-
duct are used to estimate future material flows. As the structure of
the economy changes with materials substitution and technology innova-
70
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tions, the input-output coefficients take on new values affecting the
values of the chains. The input-output coefficients change over time
according to logistics curves estimated on the basis of historical
trends. These changes are adjusted in some cases on the basis of engin-
eering data and opinions of industry experts. The relative change in
the values of the chains are used to estimate implied changes in mater-
ials used for the manufacture of each end-use product.
TABLE 32. PATH PRODUCTS BY MATERIAL FOR VARIOUS THRESHOLDS*
INFORUM Sector
Number and Name
41 Lumber
48 Paper & Paperboard
Mills
50 Building Paper Mills
62 Plastic Materials &
Resins
63 Synthetic Rubber
75 Leather Tanning/ Indus-
trial Leather Goods
78 Glass
83 Steel
84 Copper
85 Lead
86 Zinc
87 Aluminum
TOTAL
Number
Accounting
for
75% of
Output
5
14
7
35
4
2
5
13
21
20
35
18
179
of Chains
Threshold
.005
of
Output
23
82
19
96
38
14
39
58
48
84
99
57
657
.002
of
Output
40
125
37
180
75
22
65
92
78
177
209
103
1,203
Difference
in
Coverage
Between
.005
and .002
.005
.014
.005
.025
.011
.003
.008
.011
.009
.029
.034
.015
* Calculated using input coefficients of the input-output table, which
represent the amount of sales of an industrial sector to other indus-
tries per dollar of selling industry output.
Source: International Research and Technology Corporation.
Adjustments are then made to account for processing losses (i.e.,
new scrap) using technological data, and for the import and export of
finished products on the basis of import and export estimates from the
economic forecasting model. In most cases, it is assumed that the mat-
erials composition of imports is comparable to that of products pro-
71
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"FINISHED MATERIAL"
TEXTILES
035 -
Broad and
Narrow Fabrics
IAL":
Market End-Use
DISPOSABLE PRODUCTS
CONSUMER & INSTITUTIONAL PRODUCTS
rt-i-»
FURNITURE & FURNISHINGS
APPAREL
FOOTWEAR
1**3
1A7
149
L- 150
ELECTRICAL & ELECTRONIC PRODUCTS
i?n
MACHINERY & INDUSTRIAL EQUIPMENT
AUTOMOBILES
OTHER TRANSPORTATION
TIRES
OTHER INDUSTRIAL APPLICATIONS
n fi
nfi?
07i
- Paper Products, NEC
Other Leather Products
Optical & Ophthalmic Goods
Toys, Sporting Goods and
Musical Instruments
Musical & Surgical
Instruments
Jewelry & Silverware
Office Supplies
Misc. Manufacturing, NEC
Floor Coverings
Household Textiles
Household Furniture
Other Furniture
- Apparel
- Footwear (Except Rubber)
Non-Ferrous Wire-Drawings
Motors & Generators
Electric Lighting & Wire
Equipment
Special Industrial Machinery
Service Industry Machinery
- Motor Vehicles
Aircraft
Aircraft Equipment, NEC
- Tires & Inner Tubes
Paper & Paperboard Mills
Plastic Materials & Resins
Misc. Plastic Products
Source: International Research and Technology Corporation.
Figure 4. Material flow paths (chains) selected for textiles.
72
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duced domestically. For some products, including automobiles, it was
possible to modify this assumption on the basis of published data. In
these cases, domestic trends in materials use were applied to estimate
future compositions.
Solid waste generation by material product category is then esti-
mated. Estimates are derived through the application of two adjustment
factors: one to estimate the amount of material lost by wear or other
dissipative processes before its final disposal as solid waste (the
"disappearing" fraction), and the other to estimate scrappage as a func-
tion of product age. Diversions from the material flows include the
permanent storage of books in libraries and tissue paper disposed of in
municipal sewer systems. Time lags between purchase and disposal of
products are estimated using averages, normal probability distributions,
or step functions.
The solid waste estimates are adjusted to account for assumed re-
cycling levels, based on analyses of technological and economic trends.
The quantity of waste material that is recycled is comprised of two com-
ponents: new and old scrap. New scrap constitutes materials discarded
during the manufacturing process, while old scrap stems from post-con-
sumer waste. Both are computed on the basis of assumed recycling rates
for each material and product category.
Net solid waste disposals are the unrecycled residuals from dis-
cards. These quantities are distinguished by disposal sector according
to product category. For example, newspapers are included in residen-
tial and commercial wastes, scrap automobiles are included in trans-
portation wastes, and scrap machinery is an industrial waste.
LIMITATIONS
A major limitation of the methodology is that materials-flow in
the economic model is not sensitive to assumptions regarding recycling
rates and product lifetimes. The methodology deals with solid waste
generation, disposal, and recycling in a partial equilibrium framework,
taking neither the direct impact of recycling on the demand for virgin
materials, nor the input requirements, including labor, of the recycling
(i.e., secondary materials) industry into account. This limitation
could be partially corrected by making the change in some input-output
coefficients a function of recycling rates. The result would affect
outputs of key industries, including forestry products, ferrous ore
mining, and energy. The economic model would automatically account for
impacts on other economic activities, including employment. However,
the problem is compounded due to the aggregation of primary and second-
ary production for a number of sectors in the economic model, notably
the steel and other metals industries. In these cases, economic sectors
would have to be disaggregated through the inclusion of additional rows
and columns in the input-output table. This would be a difficult task,
but has the advantage of providing additional detail for estimating im-
73
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pacts of recycling and impacts of other assumptions.
A second limitation of the approach is that it provides national
estimates only. To assist solid waste managers and policy planners,
it would be desirable to estimate regional and municipal solid waste
loads. Regional projections reflecting economic and social variables,
and technological change factors could assist in the design and implem-
entation of resource recovery incentives and facilities.
74
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SECTION 5
RECOMMENDATIONS
For the purpose of estimating specific regional trends, it would
be possible to expand to some extent on the methodology presented here.
For example, the Consumer Expenditure Surveys conducted by the Bureau
of Labor Statistics (35) provides estimates of spending on specific pro-
duct categories, with regional detail by Standard Metropolitan Statis-
tical Area. These data, collected every ten or twelve years since 1888,
could provide a starting point for regional analyses if supplemented
with information regarding resource recovery at the regional level.
In the analysis presented here, an attempt has been made to expand
on the number of materials and product categories considered, and to in-
clude estimates of waste emanating not just from the residential, com-
merical and institutional sectors of the economy, but also those from
industrial and construction activities, and from demolition and scrapped
transportation equipment. It has been shown that while the residential
and commercial waste load is quite substantial, the wastes emanating
from demolition activities are equally so. Certainly, large components
of residential and commercial wastes can be recovered more readily than
those from demolition, since the bulk of the latter is composed of re-
latively unrecyclable concrete. In considering the extent of future
disposal site requirements, the growth in replacement construction is
an important element.
To complement the analysis of wastes from these sectors, it is im-
portant to recognize the potential growth in wastes emanating from acti-
vities that were not considered in this study. These include mining and
agricultural wastes, and the sludges and ash collected in attempts to
reduce pollution from industrial sources. The latter is likely to be-
come a major factor given the timetables for compliance with more strin-
gent standards in a number of areas. Disposal of hazardous wastes is a
particularly significant area of concern, given the recent Love Canal
and "Valley of the Drums" incidents.
Gross estimates of the quantities of some of these waste categor-
ies are currently generated by the Strategic Environmental Assessment
System (SEAS), which includes the same economic model used in the IR&T
analysis of solid waste. Using the economic assumptions of the IR&T
Reference Scenario, along with assumptions regarding compliance with
pollution abatement standards and penetrations of new energy conversion
75
-------
technologies, the SEAS model produced estimates of future solid waste
shown in Table 33. Large portions of the projected waste loads stem
from surface oil shale mining, uranium extraction, gasification and
liquefaction of coal, and dry scrubbing for the abatement of sulfur ox-
ide emissions from electric utilities. It is clear that the emergence
of these energy technologies is going to compound the solid waste pro-
blem.
Municipal solid waste managers will not, of course, be concerned
with most of these solid waste categories, except to the extent that
competing demands for landfill areas develop. Of more interest, per-
haps, are the projected trends in combustible versus non-combustible
solid waste. The growth in the combustible portion is comparable in
all five scenarios; about two percent per year. By 1990, these wastes
may provide an alternative through the use of energy recovery systems,
to high priced fossil fuels and landfills. Reductions in the non-com-
bustible portion, either through resource recovery or increased product
life, would provide similar energy saving opportunities given the re-
latively larger energy requirements for the fabrication of primary
materials. Increasing costs of land -for the disposal of these wastes
may add extra incentives for resource recovery.
To estimate the impacts of rising costs in land, fossil fuels,
and primary materials on the extent of future recycling would require a
detailed economic analysis that takes the costs of resource recovery
and the relative prices of primary and secondary materials into account.
Such a methodology could be developed to expand on the analysis present-
ed here. The need to specify future recycling rates as assumptions
could be diminished, and better analysis of interindustry transactions
and their effects on output, employment, and investment activities
could be achieved.
TABLE 33. SEAS PROJECTIONS OF SOLID WASTE BY CATEGORY, 1975-1990
(Million Metric Tons)
Avg. Annual
Category 1975 1990 % Growth
Combustible Biomass 0.0 6.9
Non-Combustible Waste From Pollu-
tion Abatement and Energy Conver-
sion
Mining Wastes
Industrial Sludge
Sewage Sludge
80.6
66.6
8.3
2.8
439.9
200.6
58.5
4.5
12.0
7.6
13.9
3.1
Source: Technology Assessment Modeling Project, U.S. Environmental
Protection Agency.
76
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Press, Baltimore, Maryland, and London, England, 1974. 141 pp.
Shilepsky, A., and R.A. Lowe. Resource Recovery Plan Implementation:
Guides for Municipal Officials- Planning and Overview. Environmental
Protection Agency Pub. No. SW-157.1, U.S. Environmental Protection
Agency, Washington B.C., 1976. 33 pp.
Smith, F.A. Technical Possibilities for Solid Waste Reduction and
Resource Recovery: Prospects to 1985. Office of Solid Waste Management
Programs, U.S. Environmental Protection Agency, December 1974. 18 pp.
U.S. Bureau of Mines. Minerals in the U.S. Economy: Ten-Year Supply-
Deamnd Profiles for Mineral and Fuel Commodities (1965-1974). U.S.
Department of Interior, Washington, D.C., 1975. 99 pp.
U.S. Environmental Protection Agency. Resource Recovery and Source
Reduction. First, Second, and Third Annual Reports to Congress. Pub.
Nos. SW-118, SW-122, and SW-161. Office of Solid Waste Management,
U.S. Environmental Protection Agency, Washington, D.C., 1974, 1975,
1976. 61 pp., 112 pp., 96 pp.
U.S. Environmental Protection Agency. Current Recommended Readings on
Resource Recovery and Waste Reduction. Report No. SW-536. Office of
Solid Waste Management Programs, Resource Recovery Division, U.S.
Environmental Protection Agency, Washington, D.C., 1976. 23 pp.
86
-------
APPENDIX
INTRODUCTION
The Appendix contains four sections that describe the base line data
inputs used in the Reference Scenario for this study. The first section
describes the sources of data for each material, adjustments made to the
data, historical time series tables, and material flow diagrams from the
production stage to the consumption stage. The second section provides a
series of diagrams that display the interindustry flows of materials by
product category end-use. The third section briefly describes the sources
of the product lifetime assumptions and the fourth section provides an
account of the Recycling Assumptions and their data sources.
MATERIALS DATA BASE AND FLOW DIAGRAMS
For each of the materials analyzed in this study, historical pro-
duction data in tonnage were obtained from government and industry sources.
The production data provide the basis for the materials-flow analysis in
which materials are traced through the stages of production, consumption
and finally, disposal. The production data by material are adjusted for
exports and imports to estimate apparent domestic consumption. The
apparent consumption of each material is then divided among the appropriate
product end-use categories to determine the quantities of materials that
eventually enter the waste stream. These material allocations were derived
from the same government and industry sources, although in some cases
allocations were derived using the input-output table of the economic model.
The time series data is presented in tabular form, showing control totals
for each year. For the ferrous and nonferrous metals data, adjustments
were made to include new (prompt) scrap, since the methodology separates
new scrap from each material. The historical time series input data,
listed in short tons, is converted into metric tons to conform with EPA
specifications for reporting. Since the input-output model uses 1971 as
the base year, time series for the years 1960-1971 are displayed. However,
some production data for later years (1972-1976) are included for selected
materials and product end-use categories (e.g., beverage containers and
automobiles) when relevant.
For each material, a diagram depicting the flows of materials from
production to consumption in the year 1971 is included. Each diagram
shows the apparent domestic consumption estimate and allocations to various
product categories; new scrap adjustments; foreign trade adjustments; and
net material consumption by product category. Hence, the materials-flow
diagrams outline the methodology for the year 1971 based on historical data.
87
-------
It should be noted, however, that this methodology is also used for forecast
years. Projections of the material flows are made on the basis on inter-
industry sales coefficients in the input-output model, thus accounting for
structural relationships within the economy, materials substitution, tech-
nological change, and economic growth within a consistent forecasting frame-
work. The following is a discussion of the derivation of production data
and allocations to market end-use as defined by sectors of the input-output
model.
Aluminum
Time series data for aluminum were available from two Bureau of Mines
publications, Mineral Facts and Problems (44) and Mineral Commodity Profiles
Aluminum 1977 (47). The figures in the government time series on the end-
use pattern were similar to those published in the Aluminum Association's
Statistical Review (48).
After examination of the Bureau of Mines definitions of end-use
categories, ten end-use categories were chosen for aluminum including
beverage containers, other packaging and containers, household durables,
furniture, consumer and institutional products, machinery and industrial
equipment, electrical and electronic products, buildings and structures,
automobiles and other transportation.
The Bureau of Mines definition of the packaging and container end-use
included the use of aluminum in flexible packaging, semi-rigid food contain-
ers, foil, cap and closures, metal cans, tabs and ends, and composite cans.
This total figure was allocated between the two end-use categories, beverage
containers and other packaging and containers. The source of the figures
for the aluminum beverage containers was the Aluminum Association's
Statistical Review (48). The residual aluminum after segregating the
beverage container end-use was allocated to the other packaging and contain-
er category.
The consumer durables product category as defined by the Bureau of
Mines, included the use of aluminum in refrigerators, air conditioners,
washing machines, furniture, cooking utensils, small appliances, and per-
sonal and recreational products. Thus, the end-use category included three
end-use categories specified in this study. The total was allocated to
household durables, furniture and consumer and institutional products based
on investigation of the 1972 and 1967 Census of Manufactures (46), the
INFORUM model, and product category estimates in the Aluminum Association's
Statistical Review (48).
The Bureau of Mines transportation end-use described the use of alum-
inum in automobiles, including pistons, automatic transmission parts, trim,
air conditioning, electrical uses, body, brakes, steering and metallic paint.
The high strength-to-weight ratio of aluminum makes it valuable in any car-
rier, and this factor has been important in the manufacture of aircraft
parts. Trucks, buses, trailers, and semi-trailers account for a significant
portion of aluminum sheet and extrusions in this end-use. Aluminum is also
used in commercial and naval marine, rail, motor scooters, air cushion
88
-------
vehicles and cargo containers. The Aluminum Association's Statistical Review
reported data on the use of aluminum in automobiles was employed for this end-
use and the residual of the Bureau of Mines total transportation category was
the other transportation end-use category figure.
The other Bureau of Mines product categories included items that are
consistent with product categories specfied in this study. In the buildings
and structures end-use category, the category includes the use of aluminum in
residential siding, doors and windows, roofing, awnings, canopies, heating
and ventilation applications, curtain walls, screen frames and screening,
bridge rails and guard rails, pre-engineered structures, and other bridge,
street and highway uses. The electrical and communication end-use includes
steel, reinforced aluminum cable that has replaced the use of copper in high
transmission lines, and power transmission and distribution towers that
account for a large portion of aluminum shipped to the communications market.
Electrical use also includes base and insulated wire and cable, rigid conduit
and electrical metallic tubing, telephone cable, electrical machinery, and
equipment, lighting fixtures and electric lamps. In the last end-use cate-
gory, machinery and industrial equipment, aluminum is used in special indus-
trial and agricultural machinery, materials handling equipment, irrigation
pipe, and chemical and metallurgical industries.
The material history for aluminum is presented in Table A-l by product
category. The time series is relatively short for beverage containers and
other packaging and containers due to the short product lifetimes. The second
reason for the short time series is the lack of specific data on these product
categories. The estimates in the table by product category also include new
scrap. Figure A-l depicts the material flow of aluminum from production to
final waste stream, including new scrap and net import adjustments to the data.
Concrete
Consumption of all concrete is attributed to the buildings and struct-
ures product end-use category. The source of data is the MIT study, An
Investigation of the Potential for Resource Recovery from Demolition Waste
(45). The historical time series data are presented in Table A-2. A material
flow diagram is not presented for concrete because of the sole product end-
use, buildings and structures.
Copper
The Mineral Facts and Problems (44) and Copper 1977 (49) , both published
by Bureau of Mines, are sources of the material history time series data. The
source of the government end-use time series data is the Copper Development
Association's Annual Data 1976: Copper Supply and Consumption, 1956-1975 (50)
and the Minerals Yearbook (51) data on specific copper products, such as in-
sulated wire and cable.
Eight product categories were selected after an investigation of the
Bureau of Mines definitions, used to verify the correspondence of source end-
use categories to end-use categories in the economic model. The eight pro-
duct categories include electrical and electronic products, household durables,
89
-------
VO
o
TABLE A-l. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR ALUMINUM
(Thousand Short Tons)
Product Category
Beverage Containers
Other Packaging & Containers
Consumer/Institutional Prod.
Furniture & Furnishings
Household Durables
Electrical/Electronic Prod.
Machinery /Indus trial Equip.
Automobiles
Other Transportation
Buildings & Structures
Other Industrial Appl.
TOTAL
1960
0
0
137
37
74
269
166
191
286
560
0
1,720
1961
0
0
164
44
89
320
197
228
340
666
0
2,048
1962
0
0
192
53
104
372
230
277
417
791
0
2,436
1963-
0
0
167
45
92
326
212
262
393
732
0
2,229
1964
0
0
206
57
112
411
247
295
442
862
0
2,632
1965
0
0
230
63
126
527
281
348
523
933
0
3,031
1966
0
0
259
70
141
671
338
403
603
1,024
468
3,977
1967
0
0
231
63
127
632
313
361
540
975
514
3,756
1968
261
258
266
74
149
663
342
437
561
1,136
555
4,702
1969
314
275
287
78
158
703
346
421
557
1,171
530
4,840
1970
436
293
255
70
139
676
301
354
412
1,117
393
4,445
1971
460
308
271
74
148
721
327
449
460
1,414
369
5,001
Source: Mineral Facts and Problems, 1970 and 1975 editions, Bureau of Mines, U.S. Depart-
ment of Interior.
Aluminum 1977, Mineral Commodity Profiles, U.S. Department of Interior, 1977.
Aluminum Statistical Review, Aluminum Association, Annual Publication (1974-1976).
-------
APPARENT DOMESTIC CONSUMPTION:
ALUMINUM
4534
MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
BEVERAGE
CONTAIN-
ERS
OTHER
PACKAGING
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
FURNITURE
HOUSE-
HOLD
DURABLES
ELECTRICAL
ELECTRONIC
PRODUCTS
MACHINERY
AUTO-
MOBILES
OTHER
TRANSPORT
BUILD-
INGS &
STRUC-
TURES
OTHER
INDUSTRIAL
APPLI-
CATIONS
417
279
245
67
134
654
297
407
417
1282
335
NEW SCRAP ADJUSTMENT:
-65
-44
-38
-10
-21
-102
-46
-63
-65
-200
-52
FOREIGN TRADE ADJUSTMENT:
- 8
- 1
- 3
-16
-25
12
-24
-15
15
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
352
~T~
I
I
235
199
56
110
536
226
1 1
(TIME LAG
I I
J J
356
328
1067
298
I
I
JL
1
1
V
I
I
JL
I
JL
I
I
JL
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation
3
Figure A-l. Material flow diagram of aluminum in 1971 (10 metric tons)
-------
TABLE A-2. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR CONCRETE
(Thousand Short Tons)
Product
Category 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971
if) Buildings &
N> Structures 282,210 288,777 300,426 314,450 329,256 338,000 343,977 336,948 359,052 372,031 357,464 378,139
Source: An- Investigation of the Potential for Resource Recovery from Demolition Wastes,
Massachusetts Institute of Technology, Cambridge, Massachusetts, 1976.
-------
buildings and structures, machinery and industrial equipment, automobiles,
other transportation, ordnance, and consumer and institutional products. In
two instances, the general product categories (electrical and electronic
products and transportation), defined by the Bureau of Mines included more
specific end-use than specified by the economic model.
The Bureau of Mines electrical and electronics end-use category includes
the use of copper in electrical apparatus, such as electric motors, power gen-
erators, motor generator sets, dynamotors, fans, blowers and industrial con-
trols. Copper is also a component in electrical transmission, distribution
equipment, lighting and wiring equipment, electronic navigation and communi-
cations, including electronics, telephone and telegraph wires and cables.
The electrical category also includes household appliances, knives, hairdry-
ers, toasters, blenders, coffeemakers, and frying pans. Thus, the electrical
and electronics market end-use includes the various electrical uses of copper
as well as the specific use of copper in household durables. Estimates of
the household durables product category and the electrical and electronic
product category were derived by allocating the total electrical figure among
the two end-uses according to the INFORUM model.
The Bureau of Mines figures on machinery and industrial equipment,
buildings and structures, ordnance, and consumer and institutional products
did not require adjustment because the definitions of the product categories
corresponded to the solid waste end-use categories. Buildings and structures
included the use of copper in building, construction, roofing, brass, and
bronze decorations, and utilitarian items for public buildings and private
homes. According to the Bureau of Mines, the end-use category machinery and
industrial equipment includes the use of copper in household and commercial
air conditioning, farm machinery, and components in sea water desalination
distillation plants and pollution control equipment. The ordnance end-use
category description includes the use of copper in the manufacture of muni-
tions and armaments. The consumer and institutional products, as specified
by the Bureau of Mines, includes the use of copper in coinage, chemical pig-
ments and jewelry. Copper is also used extensively in watches, clocks,
microscopes, projectors and many types of gauges.
The last category defined by the Bureau of Mines is the transportation
category which includes the numerous applications of copper in the automobile
industry, railroad transportation, airplane manufacture, and in marine appli-
cations . The use of copper, especially in automobiles, results from the trend
toward greater convenience and comfort such as power windows, seats, brakes,
steering, and air conditioning, and also from more utilitarian uses in radia-
tors, heaters and defrosters, bearings, brushings, carburetors, oil lines and
wiring. The Bureau of Mines transportation category includes the use of
copper in automobiles and other modes of transportation, two end-use categor-
ies specified in the solid waste model. The automobile and other transporta-
tion estimates were derived by allocating the total figure between the two
end-uses based on the INFORUM economic data.
The complete time series data are presented in Table A-3. The estimates
include new scrap, although government sources do not include new scrap.
It is necessary to include new scrap due to the methodology which adjusts
93
-------
TABLE.A-3. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR COPPER
(Thousand Short Tons)
Product Category
Consumer/Institutional Prod.
Household Durables
Electrical/Electronic Prod.
Machinery /Industrial Equip.
Automobiles
Other Transportation
Buildings & Structures
Ordnance
TOTAL
1960
46
51
955
365
188
62
480
136
2,283
1961
50
52
997
382
197
65
500
142
2,365
1962
51
56
1,071
410
211
70
538
154
2,561
1963
41
58
1,107
440
229
76
565
159
2,675
1964
37
69
1,295
452
242
80
608
174
2,957
1965
154
74
1,416
442
247
83
602
65
3,083
1966
176
85
1,622
458
247
81
594
263
3,526
1967
146
81
1,532
301
158
52
402
272
2,944
1968
149
75
1,440
346
210
70
458
238
2,986
1969
164
87
1,641
368
216
71
494
249
3,290
1970
150
80
1,515
364
188
62
476
173
3,008
1971
150
81
1,532
352
209
70
509
100
3,003
Source: Copper 1977, Mineral Commodity Profiles, U.S. Department of Interior, 1977.
Mineral Facts and Problems3 1970 and 1975 editions, Bureau of Mines, U.S.
Department of Interior.
Annual Data 1976: Copper Supply and Consumption; 1956-19753 Copper Development
Association, 1976.
-------
VO
Ln
\
> !
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
135
APPARENT DOMESTIC CONSUMPTION:
COPPER
2700
\
MATERIAL
HOUSE-
HOLD
DURABLES
71
\
\
r
\
\
\
V
ADJUSTMENT BY PRODUCT CATEGORY:
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
1385
MACHINERY
314
AUTO-
MOBILES
190
OTHER
TRANSPOR-
TATION
59
BUILD-
INGS &
STRUC-
TURES
457
ORDNANCE
89
NEW SCRAP ADJUSTMENT:
-42
-22
-429
-97
FOREIGN TRADE
- 4
-21
NET MATERIAL
93
45
1
1
1
V \
-59
-19
-144
-28
ADJUSTMENT:
10
- 3
- 5
CONSUMPTION BY PRODUCT CATEGORY:
935
197
1
1 T I
r
r v v
141
ME L
1 ^
DISPOSAL, REUSE, AND DIVERSIONS FROM
40
A G
1 \
310
1 \l
56
SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure A-2. Material flow diagram of copper in 1971 (in 10 metric tons)
-------
material flows to exclude new scrap. Figure A-2 shows the new scrap adjust-
ment as well as the other adjustments such as foreign trade or conversion loss
adjustments in the methodology during the flow of material from production to
consumption to disposal.
Ferrous Metals
The total consumption estimates for iron and steel allocated by product
category are now available in the Bureau of Mines publication Mineral Faots
and Problems (44). These estimates are based on the American Iron and Steel
Institute's data on steel mill shipments and the Department of Commerce data
on foundry shipments (38, 39, 54).
After examining the American Iron and Steel Institute's data on markets
for steel mill shipments and the Bureau of Mines definitions of product cate-
gories, a methodology was derived to include twelve end-use markets in the
time series. The twelve product categories are buildings and structures,
machinery, electrical and electronic products, household durables, furniture
and furnishings, consumer and institutional products, automobiles, other
transportation, beverage containers, other packaging and containers, ordnance
and miscellaneous.
The Bureau of Mines categories of transportation, cans and containers,
and others, were disaggregated to reflect other end-uses. The transportation
end-use category includes iron and steel used in automobiles, trailers, van-
type vehicles, van coaches, truck trailer parts and accessories. The auto-
mobile and other transportation end-use categories were segregated from the
general transportation category using the data in the American Iron and Steel
Institute's (AISI) Annual Statistical Report (38,39).
The cans and containers end-use category was specified in the American
Iron and Steel Institute's report and Mineral Faots and Problems. Using two
Department of Commerce publications, the Current Industrial Report (70) and
Containers and Packaging (71) on beverage containers, steel beverage contain-
ers were segregated from the general category and the remaining containers
were allocated to the other packaging and container end-use market. The other
packaging and container category includes the use of steel in sanitary and
general lined cans, crowns, caps, and other closures, steel barrels and drums,
shipping pails for paint and petroleum, compressed gas cylinders, bailing,
blending, strapping and tying strips, and miscellaneous boxes and containers.
The appliances and equipment end-use category includes the use of iron
and steel in furniture, office furniture, business machines, restaurant cook-
ing and dish-washing equipment, soda fountain equipment, floor and wall clean-
ing equipment, commercial dry cleaning equipment, hospital and surgical equ;Lp-
ment, professional and scientific equipment,'sporting goods, toys, signs and
ordnance. These uses were accordingly assigned to the consumer and institu-
tional products, furniture, and household durables categories using AISI data.
The Bureau of Mines definitions for the product categories, buildings
and structures, machinery, and electrical and electronic products were
96
-------
consistent with the end-use markets in this study. The data were taken
directly from the Bureau of Mines publication. A brief description of
the categories will be given to show the consistencies between the sources
and the end-uses defined in the study.
The buildings and structures end-use category of iron and steel in-
cludes the use of these metals in apartment buildings, dormitories, hotels,
industrial buildings, commercial warehouses, offices, lofts, department
stores, restaurants, government buildings, schools, hospitals, churches,
and bus and air terminals. The steel mill shipments are also used in dams,
reservoirs, bridges, tunnels, guard rails, transmission towers, water works,
power plants and electric light structures.
The machinery end-use category includes the use of steel mill pro-
ducts in agricultural machinery (e.g. combines, pickers, and plows) and
industrial machinery (e.g. industrial trailers, tractors, boilers, indus-
trial engines, conveyors, escalators, cranes, elevators, and fork lifts).
Iron and steel are also used in ball bearings, roller, plain and tapered
bearings, mechanical power transmission equipment, and attrition mills and
valves. Pipes, tubes and equipment used in oil and gas industries are also
accounted for in this enduse market.
In the electrical end-use category, iron and steel data include use
of material in turbo-generators, generator type steam turbines, motor
powered generators, electric lighting equipment, flashlights, floodlights
and traffic lights.
The household durables end-use category includes the use of iron and steel
in cooking and space heating stoves, refrigerators, freezers, room air
conditioners, household laundry equipment, dishwashers, enamelware (i.e.,
pots, pans, pails and tinware), galvanized ware, cutlery and table flatware.
Miscellaneous uses of steel were calculated to be the residual.
Table A-4 shows the historical time series production data of ferrous
metals including appropriate adjustments to general categories to disaggre-
gate them into detailed end-uses. It should be noted that the government
and trade association data excludes new scrap. New scrap is included in
the data inputs from Table A-4. Figure A-3 follows this table and shows
the flow of the ferrous metals from production to consumption for the year
1971.
Glass
No historical time series data in tonnage was available for glass by
product category. Apparent domestic consumption data in tonnage for glass
containers were derived from the Glass Container Manufacturer's Institute
and the Glass Packaging Institute time series (55,56). The Bureau of the
Census Current Industrial Report (57) provided tonnage estimates for glass
containers (1976) by type of container and Census ton-per-container ratios
were used to allocate glass container shipments between beverage and other
packaging and containers.
97
-------
VO
oo
TABLE A-4. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR FERROUS METALS
(Thousand Short Tons)
Product Category
Beverage Containers
Other Packaging & Containers
Consumer/Institutional Prod.
Furniture & Furnishings
Household Durables
Electrical/Electronic Prod.
Machinery/Industrial Equip.
Automobiles
Other Transportation
Construction
Ordnance
Miscellaneous
TOTAL
1960
0
0
1,597
2,044
2,746
4,986
11,098
20,644
4,532
28,321
173
2.980
79,121
1961
0
0
1,520
1,884
2,675
4.865
10,339
18,245
3.475
27,433
191
2.747
73,374
1962
0
0
1,604
1,989
2,823
5,289
11,239
21,047
4,311
28,291
264
2.868
79,725
1963
0
0
1,706
1,979
3,138
5,759
12,237
23,211
5,445
30,556
310
3,083
87,424
1964
0
0
1,907
2,212
3,509
6,496
14,460
26,026
6,507
33,968
231
3.404
98,720
1965
0
0
2,069
2,482
3,723
7,547
16,036
29,419
7,355
38,603
322
4.042
111,598
1966
0
0
2,133
2,474
3,925
7,699
16,359
27,146
8,109
38,249
769
4.039
110,902
1967
0
0
1,966
2,359
3,538
7,119
14.455
25,039
6,656
35,990
1,847
3.708
102,677
1968
0
0
2,078
2.511
4,070
7,796
15,827
30,142
6,616
40,422
2,430
3.991
115,883
1969
1,572
6,701
2.049
2,390
4,098
7,378
16,422
28,755
6,745
39,525
2,036
4.235
121,906
1970
1,980
7,020
1,960
2,205
4,001
7.030
14,938
23,526
6,636
39,126
1,414
4.835
114,671
1971
1,930
6,843
1,872
2,197
4,069
6,948
14,766
28,177
6,609
39.592
1,047
4.872
118,922
Source: Mineral Facts and Problems, 1970 and 1975 editions, Bureau of Mines, U.S.
Department of Interior.
Annual Statistical Report (1960, 1970, 1976), American Iron and Steel Institute.
Containers and Packaging, Quarterly Annual Report, Bureau of Domestic Commerce,
U.S. Department of Commerce.
Current Industrial Reports, Series M34Dj Metal Cans, Summary for 1976, Bureau
of the Census, U.S. Department of Commerce.
-------
APPARENT DOMESTIC CONSUMPTION:
FERROUS METALS
107,864
VO
VO
\
< \
' \
V \
f \
I
1 \
\
\
\
f \
' V
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
BEVER-
AGE
CONTAIN-
ERS
1404
OTHER
PACKAG-
ING
6546
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
1698
FURNI-
TURE
1993
HOUSE-
HOLD
DURABLES
3691
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
6301
MACHIN-
ERY
13393
AUTO-
MOBILES
25557
OTHER
TRANSPORT
5994
BUILD-
INGS &
STRUC-
TURES
35910
ORD-
NANCE
950
MISCEL-
LANEOUS
4419
NEW SCRAP ADJUSTMENT:
-168
-786
-340
-399
-738
51
185
FO]
-149
-1260
REIGN
-2679
-5111
-1199
-7182
-190
-884
TRADE ADJUSTMENT:
-15
-1054
345
80
-309
-71
268
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
1236
5760
1
1
1
ff \
1409
1 1
1409
2804
1
1
*
5026
1 T I
* \
9660
ME L 1
* \
21718
^ G
r i
4875
1
If \
28417
I \
. DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
689
1 \
3808
If *
Source: International Research and Technology Corporation.
Figure A-3. Material flow diagram of ferrous metals in 1971 (in 10 metric tons).
-------
Estimates of tonnage for pressed and blown glass products and flat
glass were derived from tonnage figures of raw materials consumed (i.e.,
glass, sand, soda ash and cullet) provided by the Census of Manufactures
"Materials Consumed by Kind," tables in the 1963, 1967 and 1972 publica-
tions (2,6). Product category end-use allocations for pressed, blown
and flat glass were derived from the Census of Manufactures and
INFORUM input-output model. Similar to the other material history
descriptions, Table A-5 shows the historical time series tonnage data
and Figure A-4 shows the material flow of glass from the production to
consumption stage.
There are relatively few data for the glass beverage containers
and other packaging and container end-use markets in the earlier years
of the time series. The assumed product lifetimes are less than one
year for both product end-uses; and thus, the lack of a complete time
series will not affect the results of the study. The relatively few
data for product end-use categories with assumed lifetimes of less than
one year is apparent in quite a few of the historical time series.
Lead
The data from Mineral Facts and Problems (44) and Lead 1977(58),
two Bureau of Mines publications, were selected as the basis of the
material history time series. Estimates were adjusted, however, to
specify more product category end-uses. The methodology used to group
various lead products listed in the Minerals Yearbook (51) into end-
uses in the other sources was altered. Batteries tonnage estimates
were isolated from the transportation and electrical electronics
products end-use category. The source of the time series for batteries
was the Minerals Yearbook, and the residual tonnage figure, after the
adjustment, included the use of lead in bearings and solder, and weights
and ballast in wheels and keels, respectively in the transportation
category. This residual figure depicting direct use in the transporta-
tion category was then allocated between the detailed end-use categories,
automobiles and other transportation based on estimates' from INFORUM.
The residual figure, after adjustment for batteries, also depicts
direct use in the electrical and electronics products category where
lead is used in cable coveraings, solder, brass and bronze. The
ordnance and buildings and structures end-use categories are taken
directly from the Bureau of Mines time series. The historical time
series is shown in Table A-6 and these estimates include new scrap.
The material flow diagram for lead is presented in Figure A-5.
Leather
In the literature search, no publisned estimates of apparent
consumption were found by product end-use. IR&T derived estimates by
product end-use, employing ton-per-dollar ratios from the Census of
Manufactures (46) and the input-output model's product end-use
allocations. A well defined time series does not exist for leather.
The estimated historical time series is presented in Table A-7 and the
material flow diagram for leather is displayed in Figure A-6.
100
-------
TABLE A-5. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR GLASS
(Thousand Short Tons)
Product Category
Beverage Containers
Other Packaging & Containers
Consumer/Institutional Prod,
Household Durables
Electrical/Electronic Prod.
Automobile
Other Transportation
Buildings & Structures
TOTAL
1960
0
0
499
91
171
662
69
912
2,404
1961
0
0
562
99
193
675
70
930
2,529
1962
0
0
625
106
215
689
72
947
2,654
1963
0
0
691
113
235
704
73
963
2,779
1964
0
0
792
127
268
744
78
1,016
3,025
1965
0
0
893
140
301
803
83
1,050
3,270
1966
0
0
995
151
335
845
87
1,103
3,516
1967
0
0
1,097
165
367
906
93
1,134
3,762
1968
0
0
1,412
196
463
915
95
1,133
4,214
1969
5,761
4,633
1,730
231
556
991
102
1,218
15,222
1970
6,921
4,370
2,054
257
644
910
94
1,146
16,396
1971
6,366
4,783
2,380
.295
732
1,094
113
1,385
17,148
Source: Current Industrial Reports, Series M32G3 Glass Containers, Bureau of the Census,
U.S. Department of Commerce.
Census of Manufactures (19633 19673 1972), Bureau of the Census, U.S. Depart-
ment of Commerce.
Glass Containers 1973-19?43 Glass Container Manufacturer's Institute.
Glass Packaging Institute 1977s Glass Packaging Institute.
-------
o
to
r \
APPARENT DOMESTIC CONSUMPTION:
GLASS
15551
i 1 \
\
J
1
i
BEVERAGE
CON-
TAINERS
5775
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
OTHER
PACKAGING
4336
' CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
2159
HOUSE-
HOLD
DURABLES
268
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
664
AUTO-
MOBILES
992
OTHER
TRANSPORT
102
CONSTRUC-
TION
1256
NEW SCRAP ADJUSTMENT:
-271
-204
-147
-21
-45
-132
-14
-173
FOREIGN TRADE ADJUSTMENT:
78
60
-22
69
- 1
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
5503
4132
2090
307
597
929
87
- 8
1075
1 1
T I M E L A G 1
II 1 1 1
V V Y V V V V *
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure A-4. Material flow diagram of glass in 1971 (in 10 metric tons)
-------
TABLE A-6. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR LEAD
(Thousand Short Tons)
Product Category
Other Packaging & Containers
Consumer/Institutional Prod.
Electrical/Electronic Prod.
Machinery/Industrial Equip.
Automobiles
Other Transportation
Batteries
Buildings & Structures
Ordnance
Other Industrial Appl.
TOTAL
1960
55
26
39
68
11
1
394
149
49
0
792
1961
52
22
37
59
12
1
410
151
51
0
795
1962
62
19
39
51
13
2
468
165
54
0
873
1963
66
18
41
47
13
2
494
168
54
0
903
1964
69
20
23
55
11
2
478
164
62
0
884
1965
74
35
21
94
13
2
507
153
64
0
963
1966
72
36
20
98
16
2
526
147
87
0
1,004
1967
65
38
10
104
16
2
521
134
88
0
978
1968
67
62
9
169
17
3
573
130
91
0
1,121
1969
69
49
11
132
19
3
650
133
88
0
1,154
1970
65
21
22
57
21
3
661
135
81
421
1,487
1971
62
27
56
74
26
4
758
112
98
385
1,602
Source: Minerals Yearbook, Annual Publication (1960-1974), Bureau of Mines, U.S.
Department of Interior.
Lead 1977, Mineral Commodity Profiles, Bureau of Mines, U.S. Department
of Interior, 1977.
Mineral Facts and Problems, 1970 and 1975 editions, Bureau of Mines, U.S.
Department of Interior.
-------
o
-p-
\
APPARENT DOMESTIC CONSUMPTION:
LEAD
1454
i
V V V V V V V \
V
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
OTHER
PACKAGING
56
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
24
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
51
MACHINERY
67
AUTO-
MOBILES
24
OTHER
TRANSPORT
4
BATTERIES
688
BUILDINGS
& STRUC-
TURES
102
ORDNANCE
89
OTHER
INDUSTRIAL
APPLI-
CATIONS
349
NEW SCRAP ADJUSTMENT:
- 6
- 2
- 5
- 7
- 2
-69
-10
- 9
FOREIGN TRADE ADJUSTMENT:
- 2
- 4
- 5
-
- 1
- 2
- 4
- 6
-16
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
50
20
42
55
23
3
617
88
74
1 1 1 1 | 1
| 1 T I M E L A G 1
III 1
V V V V Mf ^ V * ^
333
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
3
Figure A-5. Material flow diagram of lead in 1971 (in 10 metric tons)
-------
o
Ui
TABLE A-7. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR LEATHER
(Thousand Short Tons)
Product Category
Consumer/Institutional Prod.
Furniture & Furnishings
Apparel
Footwear
Machinery/Industrial Equip.
TOTAL
1960
116
19
51
488
6
680
1961
109
18
48
459
6
640
1962
109
18
48
460
6
641
1963
110
18
48
461
6
643
1964
113
19
49
472
6
659
1965
117
19
51
489
6
682
1966
112
19
49
470
6
656
1967
114
19
50
478
6
667
1968
113
19
49
473
6
660
1969
103
17
45
430
6
601
1970
95
16
41
400
5
557
1971
97
16
42
405
5
565
Source: Census of Manufactures (1967 and 1972), Bureau of Census, U.S. Department
of Commerce.
-------
o
a*
APPARENT DOMESTIC CONSUMPTION:
LEATHER
506
V
\ V I1 V 1
M
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
87
[ATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
FURNITURE
13
APPAREL
38
FOOTWEAR
367
MACHINERY
1
NEW SCRAP ADJUSTMENT:
-13
- 2
FOREIGN
13
NET MA
87
o
-55
TRADE ADJUSTMENT:
3
58
TERIAL CONSUMPTION BY PRODUCT CATEGORY:
11
35
370
1
1
TIME LAG 1
1
V V * V V
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLIDWASTE STREAM
Source: International Research and Technology Corporation.
Figure A-6. Material flow diagram of leather in 1971
3
in 10 metric tons).
-------
Paper and Paperboard
The Bureau of the Census (59) estimates of apparent consumption in
tons was used to establish the material history for paper and paperboard.
The American Paper Institute (API) estimates, published in Statistics
of Paper and Paperboard (60), were also investigated as a possible data
source. There is general agreement between the Census and API, although
there are variations in data for some years. The data from the Bureau
of the Census were chosen since these estimates are more likely to be
consistent with the underlying economic data of the input-output model
used in this study. Product category allocations were primarily derived
from Bureau of the Census data.
Allocations among the product end-use categories are given in
Table A-8. If the Census definitions by grade of paper did not
coincide with the product categories outlined in this study, other data
were employed. These data were obtained primarily from API. In
addition, Kline's Marketing Guide to the Paper and Paperboard Industry
(72) and the Midwest Research Institute's The Role of Non-Packaging
in Solid Waste Management (23) was also examined. The historical time
series production data and material flow diagram for paper and paper-
board are presented in Tables A-9 and A-10, and in Figures A-7 and A-8.
Plastics
Total apparent consumption estimates and market end-use data were
derived primarily from McGraw-Hill's publication Modern Plastics (41).
Modern Plastics uses control totals published by the Society of the
Plastic Industry (SPI) in Facts and Figures of the Plastics Industry
(62), and then allocates these totals among market end-use categories.
A large portion of plastic consumption was omitted by this source and
time series data by product category were only available for the years
1967 through 1971. To obtain appropriate estimates by end-use product
categories as defined in this study, Modern Plastics detailed end-use
estimates by resin were used for the consumer and institutional products
category (i.e., luggage, medical products, records, optical goods,
tools, and recreational products) and machinery and industrial equip-
ment category. Data for the earlier years of the time series were
derived from the product end-use estimates and trends in plastic usage
published in Markets for Plastics (63). These estimates were compared
with data published in Modern Plastics for the earlier years wherever
possible. A miscellaneous category was used for plastics employed in
agricultural applications; plastics used in the production of textiles
and paints were included in the "other industrial applications" category.
The methodology used to develop data for this material is rather
complicated. The data was adjusted to control totals in the historical
time series. An investigation of data sources showed that Modern
Plastics makes the most comprehensive survey of the industry's produc-
tion figures, and the U.S. International Trade (formerly Tariff)
Commission's annual publication Synthetic Organic Chemicals (61)
107
-------
TABLE A-8. PAPER AND PAPERBOARD PRODUCT CATEGORY
ALLOCATION ASSUMPTIONS
Material/Product Category
Grade
PAPER:
Newspaper
Books, Periodicals & Other
Printing Paper
Writing & Other Fine Paper
Disposable Products
Other Packaging & Containers
Consumer & Institutional
Products
Electrical & Electronic
Products
PAPERBOARD:
Books, Periodicals & Other
Printing Paper
Other Packaging Containers
Consumer & Institutional
Products
Footwear
Electrical & Electronic
Products
Automobiles
Buildings & Structures
Newsprint
Groundwood
Coated Printing
Book Paper
Writing Paper
Bleached Bristol
Sanitary Paper
Tissue Paper
Unbleached Kraft Packaging
Packaging & Industrial
Converting
Special Industrial
(other grades)
Special Industrial
(electrical & cable paper)
Wet Machine Board (according
to Kline's Marketing Guide")
Corrugated Paper
Non-Corrugated Liner Board
Bleached Packaging & Converting
(according to API)
Combination Board-Bending
Special Combination (fiber
cans, drums, tubes & boards)
Special Combination (Other)
Bleached Packaging & Converting
(according to API)
Wet Machine Board (according
to Kline's Marketing Guide)
Wet Machine Board (shoeboard)
Wet Machine Board (according
to Kline's Marketing Guide)
Special Combination (panelboard)
Wet Machine Board (according
to Kline's Marketing Guide)
Construction Paper
Construction Board
Source: James Rauch. Kline Guide to the Paper and
Pulp Industry, 3rd'Edition, Charles H. Kline
& Company, Fairfield, New Jersey, 1976.
108
-------
o
VO
TABLE A-9. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR PAPER
(Thousand Short Tons)
Product Category
Newspaper
Books, Periodicals & Other
Writing 6, Other Fine Paper
Disposable Products
Other Packaging & Containers
Consumer/Institutional Prod.
Electrical/Electronic Prod.
TOTAL
1960
0
0
0
0
0
200
33
233
1961
7,336
4,695
0
0
0
235
36
12,302
1962
7,473
4,938
0
2,174
0
231
35
14,851
1963
7,508
5,244
0
2,335
0
228
34
15,349
1964
8,086
5,600
2,827
2,498
0
252
37
19,300
1965
8,419
6,023
3,132
2,632
0
266
38
20,510
1966
9,238
6,710
3,437
2,835
0
294
38
22,552
1967
9,108
6,662
3,459
2,943
0
298
34
22,504
1968
9,289
7,007
3,689
3,141
0
336
34
23,496
1969
9,915
7,376
3,967
3,324
5,231
356
33
30,202
1970
9,836
7,353
3,859
3,531
5,160
338
33
30,110
1971
10,036
7,389
3,880
3,646
5,193
358
28
30,530
Source: Statist-Los of Paper and Paperboard, 19763 American Paper Institute.
Current Industrial Reports, Series M26A, Pulp, Paper and Boards Bureau of
the Census, U.S. Department of Commerce.
-------
TABLE A-10. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR PAPERBOARD
(Thousand Short Tons)
Product Category
Books , Periodicals
Other Packaging & Containers
Consumer/Institutional Prod.
Footwear
Electrical/Electronic Prod.
Automobiles
Buildings & Structures
TOTAL
1960
53
0
0
59
22
46
__0
180
1961
54
0
607
59
17
42
4.008
4,787
1962
58
0
579
61
19
41
4,256
5,014
1963
55
0
631
58
11
39
4,506
5,300
1964
59
0
685
61
13
53
4.796
5,667
1965
59
0
708
60
11
60
4.933
5,831
1966
65
0
667
59
10
54
4,637
5,492
1967
59
0
466
52
11
53
4,640
5,281
1968
53
0
565
49
20
60
5,277
6,024
1969
50
22,633
511
46
20
53
5,499
28,812
1970
48
22,140
355
44
19
51
5,279
27,936
1971
46
22,311
383
44
20
57
6,127
29,088
Source: Statistics of Paper and Paperboard, 19763 American Paper Institute.
Current Industrial Reports, Series M26A3 Pulp, Paper and Board, Bureau of
the Census, U.S. Department of Commerce.
-------
\
APPARENT DOMESTIC CONSUMPTION:
PAPER
27684
V \
M
NEWS-
PAPER
9103
BOOKS
AND PERI-
ODICALS
6702
\
1
\
\
WERIAL ADJUSTMENT BY PRODUCT CATEGORY:
WRITING
& OTHER
FINE
PAPER
3518
DISPOS-
ABLE
PRODUCTS
3307
OTHER
PACKAGING
4710
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
321
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
23
NEW SCRAP ADJUSTMENT:
-228
-1005
-211
-165
-236
- 16
- 1
FOREIGN TRADE ADJUSTMENT:
5
- 32
31
- 30
16
- 4
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
8880
5668
3324
1
1
1
V v
DISPOSAL, REUSE,
3112
4474
320
1
TIME LAG
1
t y V ,
18
1 V
AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
3
Figure A-7. Material flow diagram of paper in 1971 (in 10 metric tons)
-------
NJ
APPARENT DOMESTIC CONSUMPTION:
PAPERBOARD
26384
Jt
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
BOOKS &
PERIODI-
CALS
42
OTHER
PACKAGING
20237
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
347
FOOTWEAR
40
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
18
AUTO-
MOBILES
52
BUILD-
INGS &
STRUC-
TURES
5648
NEW SCRAP ADJUSTMENT:
- 7
-2752
-59
- 7
- 3
- 9
-367
FOREIGN TRADE ADJUSTMENT:
- 1
-66
- 2
-26
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
34
17419
293
39
13
46
5255
I
JL
I
V
1
TIME! LAG I
I I
V V
I
I
JL
I
i
JL
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure A-8. Material flow diagram of paperboard in 1971
(in 10 metric tons).
-------
includes some plastic categories while excluding others, making their
estimates less reliable. (A comparison of Modern Plastics, SPI, and
the U.S. Tariff Comission's plastic sales data is given in Table A-ll).
It was also noted that although there are differences between the IR&T
and Franklin plastic estimates for EPA's Office of Solid Waste, Franklin
also employs Modern Plastics figures in his methodology. In addition,
the original source of A.D. Little's estimates in Incentives for
Recycling and Reuse of Plastics (64), which was used in the Franklin
analysis, was the Modern Plastics data. Thus, the Modern Plastics
data used in this study provide reliable and comprehensive time series
data. Data from 1972 to 1976 were included in the analysis, especially
plastics packaging data, because usage has changed considerably in more
recent years. The historical time series production data is presented
in Table A-12 and the flow of plastics for 1971 from production to
consumption is presented in Figure A-9.
Table A-12 provides the breakdown of plastics by product end-use
category for 1960-1971. It should be noted that, due to the recent
trend of substituting plastics for glass or metal beverage containers,
1971 is the first year that beverage containers are included as an end-use
category. Changes to material flows are included as inputs for the later
years, 1972-1976. The fact that beverage containers have an assumed
product lifetime of less than one year means that the lack of a complete
time series will not greatly affect the reliability of forecasts of
tonnage figures. In addition, the other industrial applications
category and miscellaneous category have fairly short time series from
1967 to 1971 due to the fact that residuals of plastic tonnage have
only been identifiable in recent years when the product category end-
use data were more detailed.
Rubber
The Rubber Manufacturers Asscociation's publication (65) is the
only available source of apparent domestic consumption data. The data
in this publication are divided into tire and non-tire products and the
rubber had to be allocated among the non-tire market end-uses according
to the IR&T descriptions of product category market end-uses. Rubber
Age (66) has published estimates of rubber use for footwear, mechanical
goods, wire and cable, latex foam products, and others but there is no
breakdown in tonnage available for market end-use categories in this
study. Consequently, estimates were derived from the Census of Manufac-
tures (46) data for the Fabricated Rubber Products SIC 3069.
The historical time series tonnage data are presented in Table A-13
and the flow of rubber from production to consumption is represented in
Figure A-10.
Textiles
The Textile Economics Bureau publication Textile Organon (67) is
the primary source of the total annual consumption figures for textiles.
113
-------
TABLE A-11. COMPARISON OF PLASTICS SALES DATA FOR 1972 (in 106 Ibs.)
Material
Acrylic
Cellulosics
Epoxy
Nylon
Phenolic
Polyester
HOPE
LDPE
Polyacetal
Polycarbonate
Modern
Plastics
459
165
183
148
1435
917
2342
5230
58
56
Society of
the Plastics
Industry
NA
NA
183
151
1431
906
2387
5263
NC
NC
U.S. Tariff
Commission
627
252
179
119
1227
889
2054
4877
NC
NC
Polypropylene
Polystyrene &
co-polymers
Polystyrene
ABS
SAN
Other
Polyvinyl Chloride &
co-polymers
Urea & Melamine
/
Urethane Foam
Other
GRAND TOTAL
Exports
1689
4654
3429
787
101
337
4355
906
1088
23685
664
1705
4049
3162
785
102
4354
897
1190
22516
663
1685
4557
3646
810
101
4435
780
NC
21681
663
Source: Modern Plastics, McGraw-Hill Publication.
Facts and Figures of the Plastics Industry: 1977 Edition,
Society of the Plastics Industry, September 1977.
Synthetic Organic Chemicals, U.S. International Trade Commission.
114
-------
TABLE A-12. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR PLASTICS
(Thousand Short Tons)
Product Category
Beverage Containers
Other Packaging & Containers
Consumer/Institutional Prod.
Furniture & Furnishings
Household Durables
Electrical/Electronic Prod.
Machinery/Industrial Equip.
Automobiles
Other Transportation
Buildings & Structures
Other Industrial Appl.
Miscellaneous
TOTAL
1960
0
300
309
200
90
235
53
59
41
403
0
0
1,690
1961
0
500
350
205
92
246
63
93
45
460
0
0
2,054
1962
0
650
428
215
93
260
78
124
51
546
0
0
2,445
1963
0
750
468
250
98
283
93
150
58
632
0
0
2,782
1964
0
900
513
260
115
311
110
183
65
718
0
0
3,175
1965
0
977
563
290
150
339
130
215
70
832
0
0
3,566
1966
0
1,100
668
350
190
368
148
246
125
975
0
0
4,170
1967
0
1,300
773
344
198
396
155
282
144
1,065
0
75
4,732
1968
0
1,507
904
306
234
488
178
301
172
1,149
0
85
5,324
1969
0
1,893
1,080
398
267
580
196
426
228
1,284
0
95
6,447
1970
0
2,298
1,134
394
285
617
230
462
197
1,478
1,184
99
8,378
1971
20
2,450
1,259
467
285
599
230
483
206
1,775
1,124
110
9,008
Source: Facts and Figures of the Plastics Industry: 1977 edition, Society of the
Plastics Industry, New York.
Modern Plastics, McGraw-Hill publications, New York.
Markets for Plastics, D.V. Rosato, W.,. Fallen, Van Nostrand Reinhold
Company, New York, 1969.
-------
APPARENT DOMESTIC CONSUMPTION:
PLASTICS
8117
_V
\
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
OTHER
PACKAGING
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
FURNITURE
HOUSE-
HOLD
DURABLES
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
MACHINERY
AUTO-
MOBILES
TRANSPORT
STRUC-
TURES
MISCEL-
LANEOUS
OTHER
INDUSTRIAL
APPLI-
CATIONS
2214
1135
422
257
540
205
438
183
1609
98
1016
NEW SCRAP ADJUSTMENT:
-109
-56
-21
-13
-26
-10
-21
- 9
-79
- 5
-50
FOREIGN TRADE ADJUSTMENT:
66
13
32
-12
10
32
-12
- 9
26
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
2105
1145
414
276
502
185
449
162
1530
84
992
I
I
JL
I
I
JL
I
TIME
I
JL
I
LAG
I
V
T
I
JL
I
I
V
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure A-9. Material flow diagram of plastics in 1971 (in 10 metric tons).
-------
TABLE A-13. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR RUBBER
(Thousand Short Tons)
Product Category
Consumer/Institutional Prod.
Furniture & Furnishings
Apparel
Footwear
Household Durables
Electrical/Electronic Prod.
Machinery/ Industrial Equip.
Automobiles
Other Transportation
Tires & Inner Tubes
TOTAL
1960
25
19
57
107
90
14
157
143
21
1,114
1,747
1961
25
20
58
109
90
14
159
145
21
1.073
1,714
1962
29
22
66
124
104
16
179
166
24
1,195
1,925
1963
31
23
69
130
109
17
187
175
24
1,211
1,976
1964
33
24
75
140
118
17
202
188
26
1,342
2,165
1965
35
24
76
143
120
18
205
191
27
1,463
2,302
1966
36
27
81
152
128
19
221
203
29
1,581
2,477
1967
36
26
80
151
126
19
217
202
29
r.485
2,371
1968
39
29
89
166
138
20
239
224
32
1,799
2,775
1969
39
29
79
169
160
21
231
246
34
1,929
2,937
1970
41
30
77
171
160
21
227
246
34
1,767
2,774
1971
41
31
57
173
186
22
199
273
38
1.980
3,000
Source: Census of Manufactures' (1967 and 1972),, Bureau of the Census, U.S. Depart-
ment of Commerce.
Rubber Industry Facts, Rubber Manufacturers Association, New York.
Rubber Age, Palmerton Publishing Company, New York.
-------
APPARENT DOMESTIC CONSUMPTION:
RUBBER
2721
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
FURNITURE
APPAREL
FOOTWEAR
HOUSE-
HOLD
DURABLES
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
MACHINERY
AUTO-
MOBILES
OTHER
TRANSPORT
TIRES
37
28
52
157
169
20
180
248
34
1796
NEW SCRAP ADJUSTMENT:
- 2
- 1
- 3
- 8
- 8
- 1
- 9
-12
- 2
-54
00
FOREIGN TRADE ADJUSTMENT:
- 3
28
- 6
-27
18
- 5
64
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY;
35
24
54
177
162
13
144
254
27
1806
I
I
I
JL
\
I
I
JL
I
TIME
LAG
I
I
I
JL
I
JL
I
JL
I
I
I
JL
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
Figure A-10. Material flow diagram of rubber in 1971 (in 10 metric tons).
-------
Man-Made Fibers Source Book (73) was also examined to confirm man-made
fibers data. Textile Ovganon specifies many market end-uses for textiles
which were aggregated into eleven product categories according to the
market end-uses in the IR&T model. These categories are apparel, foot-
wear, furniture and furnishings, automobiles, other transportation,
electrical and electronic products, tires and inner tubes, consumer
and institutional products, machinery and industrial equipment, other
industrial applications, and disposables.
The apparel end-use category includes sheer hosiery, anklets and
socks, sweaters and related accessories, craft and handwork yarns,
underwear and nightwear, robes and loungewear, pile fabrics, lining-
type fabrics, apparel lace, retail piece goods, narrow woven apparel,
and other apparel and accessories (e.g., handkerchiefs, ties, mittens,
and scarves.) Shoes and slippers comprise the footwear end-use category.
Manmade fibers and cottons used in boots, tennis shoes, and mesh tops
for summer shoes are accounted for in this end-use category.
The furniture and furnishings category includes manmade fibers,
cotton and wool used in bedspreads, quilts, blankets, and blanketing,
sheets, and other bedding. The category also includes carpets, rugs,
face yarn, backing, curtains, drapery and upholstery, and miscellaneous
articles, (e.g., woven and lace napery, tablecloths, doilies, shower
curtains, and embroidered goods).
The transportation end-use category includes auto seat upholstery,
slipcovers, sidewall, headlining and sheeting. Knit and woven fabric
used as backing for vinyl sheeting, convertible automobile tops are
included in the end-use as well as upholstery used in different modes
of transportation (e.g., railroad cars, airplanes, subways, and buses.)
The INFORUM model was used to segregate automobile and other transpor-
tation for textiles.
The electric applications end-use category includes electric wire
insulation and covering of all kinds plus friction tape and cable wrap,
stuffing and identification.
The tires end-use category includes all types of tires (e.g.,
automobile, truck, tractor, off-road, and bicycle), tire cord and
tire cord fabric, chafer and other tire components (e.g., flipper
fabric, breaker strips, and bead wraps).
The consumer and institutional products end-use category includes
medical, surgical and sanitary goods (e.g., bandages, gauzes, adhesive
tapes and plasters, cotton diapers, surgical gowns and packs, and non-
woven wiping cloths). The end-use category also includes felts, sewing
threads, rope, cordage, fishline, bags, sports equipment and hand
umbrellas, manmade stuffing and filling materials. The machinery
and industrial equipment end-use category includes hoses (fire, chemical
and fuel), belting (e.g., conveyor belts) transmission belts and V-belts.
119
-------
The other industrial applications end-use category includes reinforced
plastics, paper and tape reinforcing, and non-woven bonded structures for
paper and tape reinforcing.
The disposable end-use category includes textiles used for filtra-
tion. This includes woven and non-woven fibers for wet and dry filtration,
including tea bags.
The material time series data for textiles are presented in Table
A-14. It should be noted that for a few product category end-uses, such
as other industrial applications, tires, footwear, and disposables, the
time series data are relatively limited. The fewer number of available
estimates for these end-uses will not affect the forecasts because the
product lifetime assumptions for these end-uses are relatively short.
A material flow diagram is presented for textiles in Figure A-ll.
Wood
Apparent domestic consumption data for wood is provided by two
sources, The Demand and Price Situation for Forest Products (Table 5)
(68) and The Outlook for Timber in the United States (42). Product
category allocations were derived from The Outlook for Timber in the
United States where data on buildings and structures are presented
in Table 136, p. 181, data on furniture, consumer products and machinery
in Table 128, p. 169; and data on other transportation data on p. 166.
It was not possible to obtain the most recent data from the Forest Service
because the update of survey data will take place later this year. The
historical time series data are presented in Table A-15 and the flow
of wood in 1971 from production to consumption is depicted in Figure A-12.
Zinc
Similar to the other nonferrous metals, the time series for zinc
estimates was taken from Bureau of Mines Mineral Facts and Problems (44)
and Mineral Commodity Profiles Zinc 1977 (69). The source of the brass
and bronze end-use data in the government publications is the Copper
Development Association's annual publication Annual Data 1976: Copper
Supply and Consumption, 1956-1975 (50), and the source of data for the
use of zinc in galvanizing is the American Iron and Steel Institute's
Annual Report (38, 39). Based on the definitions of the categories in
the Mineral Facts and Problems, the use of zinc was allocated to seven
product categories; buildings and structures, household durables,
electrical and electronic products, automobiles, other transportation,
machinery, and consumer and institutional products.
The Bureau of Mines definition of electrical and electronic
products included the use of zinc in household durables. According to
the electrical and electronic end-use description, zinc is mainly
employed in the manufacture of household cooking equipment, household
refrigerators and freezers, household laundry equipment, electric
housewares and fans, household vacuum cleaners, sewing machines, and
120
-------
NJ
TABLE A-14. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR TEXTILES
(Thousand Short Tons)
Product Category
Disposables
Consumer/Institutional Prod.
Furniture & Furnishings
Apparel
Footwear
Electrical/Electronic Prod.
Machinery/ Indus tr-al Equip.
Automobiles
Other Transportation
Tires & Inner Tubes
Other Industrial Appl.
TOTAL
1960
0
330
834
1,628
0
8
27
17
14
0
0
2,850
1961
0
326
851
1,662
0
8
29
18
15
0
0
2,909
1962
0
343
945
1,764
0
8
31
19
15
0
0
3,125
1963
0
346
1,024
1,820
0
9
33
19
15
0
0
3,266
1964
0
382
1,133
1,900
0
9
35
21
17
0
0
3,497
1965
0
424
1,243
1,978
0
10
37
23
19
0
0
3,734
1966
0
478
1,289
2,021
0
10
38
25
20
0
0
3,881
1967
0
472
1,308
2,042
0
11
39
24
20
285
0
4,201
1968
0
523
1,478
2,197
29
11
40
25
21
291
0
4,615
1969
0
530
1,521
2,140
30
12
41
27
22
295
0
4,618
1970
12
481
1,476
2,174
32
12
42
26
22
286
171
4,722
1971
13
522
1,670
2,344
33
13
45
26
22
312
185
5,185
Source: Text-lie Ovganon, Annual November Issue, Textile Economics Bureau, Inc., New York.
Man-Made Fibers Source Book3 Man-Made Fibers Producers Association, Inc., 1978.
-------
ro
\
\
FURNITURE
AND
FURNISH-
INGS
1515
\
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
473
' \
FOOTWEAR
30
APPARENT DOMESTIC CONSUMPTION:
TEXTILES
4704
\
' \ \
r
' V \
\
\
\>
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
APPAREL
2126
MACHINERY
41
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
12
TIRES
283
AUTO-
MOBILES
24
OTHER
TRANSPORT
20
DISPOS-
ABLE
PRODUCTS
12
OTHER
INDUSTRIAL
APPLI-
CATIONS
168
NEW SCRAP ADJUSTMENT:
-76
-24
- 2
-213
- 2
- 1
-14
-1
- 1
- 1
- 8
FOREIGN TRADE ADJUSTMENT:
-24
4
1463
\
6
453
*
1
179
NET
34
i
* \
- 5
- 4
9
1
- 8
3
MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
2092
^
r \i
DISPOSAL
34
7
1
I TIME
1 V \
278
24
LAG
( w V
11
y
11
1 )
163
, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
3
Figure A-ll. Material flow diagram of textiles in 1971 (in 10 metric tons).
-------
ISJ
TABLE A-15. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR WOOD
(Thousand Short Tons)
Product Category
Other Packaging & Containers
Consumer/Institutional Prod.
Furniture & Furnishings
Machinery/Industrial Equip.
Other Transportation
Buildings & Structures
TOTAL
1960
5,400
1,247
3,600
530
453
35^350
46,580
1961
5,250
1,215
3,640
550
445
35,400
46,500
1962
5,450
1,247
3,830
620
468
38,025
49,640
1963
5,600
1,255
3,900
650
485
40,810
52,700
1964
5,800
1,215
4,100
700
485
43,500
55,800
1965
5,770
891
4,410
800
424
44.650
56,945
1966
6,300
891
4,500
800
409
44.600
57,500
1967
5,950
891
4,400
800
399
42,760
55,200
1968
6.650
1,012
4.700
800
438
46*300
59,900
1969
6,600
1,093
4,800
800
477
46,130
59,900
1970
6,620
1,150
4,810
810
470
11,970
58,830
1971
7,180
1.215
5,370
880
485
49,820
64,950
Source: The Demand and Prioe Situation for Forest Products, 1973-1974, U.S. Department of
Agriculture, Forest Service, September 1974.
Outlook for Timber in the United States, U.S. Department of Agriculture,
Forest Service, October 1973.
-------
NJ
APPARENT DOMESTIC CONSUMPTION:
WOOD
58910
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
OTHER
PACKAGING
6512
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
1102
FURNITURE
4871
MACHINERY
798
OTHER
TRANSPORT
440
BUILD-
INGS &
STRUC-
TURES
45187
NEW SCRAP ADJUSTMENT:
-1530
-661
-2923
-239
-4519
FOREIGN TRADE ADJUSTMENT:
13
54
61
-59
-22
2180
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
4995
495
2009
500
374
42848
I
I
JL
T I M E
LAG
I
I
I
JL
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technblogy Corporation.
Figure A-12. Material flow diagram of wood in 1971
3
(in 10 metric tons).
-------
other household applicances. Zinc is also used in electric trans-
mission equipment, pumps, mechanical transmission, and control rods.
The total figure specified in the Minerals Facts and Problems was
allocated between the two end-use categories, household durables and
electrical and electronic products based on economic data in the
INFORUM model.
The consumer and institutional products end-use category includes
the use of zinc (brass) in costume jewelry, statuary and decorative
applications, zippers, instrument bezels, and gasoline lawnmowers.
The Bureau of Mines transportation end-use includes zinc used in
motor vehicles and equipment, such as passenger car, truck and bus
bodies and motor vehicle parts (carburetors, grilles and trim) and
accessories. This product category also .'.includes aircraft and parts
(engines, propellers, and equipment), ship and boat building, railroad
and miscellaneous modes of transportation, (e.g., motorcycles, bicycles
and trailer coaches.) The INFORUM model was used to allocate
the general product category data to automobile end-use and other
transportation end-use product categories.
The other Bureau of Mines product categories, buildings and
structures, and machinery, included the use of zinc in product end-use
markets that were consistent with the IR&T model categories. Thus,
the data for these end-uses were taken directly from the source. In
the buildings and structures end-use category, zinc is used in metal
sanitary ware, plumbing, fitting and brass goods, and heating equipment.
Zinc is also used in fabricated structural steel, sash and trim on
metal doors, fabricated platework, and architectural and miscellaneous
metal work. In galvanizing, zinc is used to protect steel beams,
girders, and fasteners, such as nuts and bolts to protect steel roofing
and siding.
The machinery end-use category includes the use of zinc in engines,
turbines and farm machinery, construction, mining and metal working
machinery, and office, computing, and accounting machines. Zinc is
also used in brass bearings, bushings and tubing, galvanized sheet,
fittings, fasteners, diecast parts, and fixtures.
The historical time series data by product category are presented
in Table A-16; the adjusted data include new scrap. The zinc material
flow diagram for 1971 is displayed in Figure A-13.
125
-------
10
TABLE A-16. REFERENCE SCENARIO. HISTORICAL TIME SERIES PRODUCTION DATA FOR ZINC
(Thousand Short Tons)
Product Category
Consumer/Institutional Prod.
Household Durables
Electrical/Electronic Prod.
Machinery/ Industrial Equip.
Automobiles
Other Transportation
Buildings & Structures
TOTAL
1960
122
25
108
99
94
45
365
858
1961
130
26
115
107
182
89
388
1,037
1962
167
34
149
138
235
116
503
1,342
1963
144
29
127
118
211
104
446
1,179
1964
144
29
129
120
213
105
450
1,190
1965
176
36
156
144
258
127
547
1,444
1966
250
47
203
141
284
140
504
1,569
1967
239
45
194
127
245
122
438
1,410
1968
250
47
203
133
257
127
458
1,475
1969
253
47
204
126
306
150
488
1,574
1970
228
37
162
107
224
110
469
1,337
1971
166
32
134
89
257
126
473
1,277
Source: Zinc, Mineral Commodity Profiles, Bureau of Mines, U.S. Department of Interior.
Mineral Foots and Problems, 1970 and 1975 editions, Bureau of Mines, U.S.
Department of Interior.
Annual Data 1976: Copper -Supply and Consumption 1956-1975, Copper Development
Association.
Annual Statistical Report, 1976, American Iron and Steel Institute.
-------
APPARENT DOMESTIC CONSUMPTION:
ZINC
1159
1
V V V V ^ V \
MATERIAL ADJUSTMENT BY PRODUCT CATEGORY:
CONSUMER
& INSTI-
TUTIONAL
PRODUCTS
151
HOUSE-
HOLD
DURABLES
29
ELECTRICAL
AND
ELECTRONIC
PRODUCTS
122
MACHINERY
81
AUTO-
MOBILES
233
OTHER
TRANSPORT
114
BUILD-
INGS &
STRUC-
TURES
429
NEW SCRAP ADJUSTMENT:
-22
- 4
-18
-12
-34
-17
-63
FOREIGN TRADE ADJUSTMENT:
- 2
_ Q
- 1
-15
-10
NET MATERIAL CONSUMPTION BY PRODUCT CATEGORY:
129
25
102
60
200
82
356
1 1 II
1 1 T I M E L A G 1 1
1 1 II
* * V * « V V
DISPOSAL, REUSE, AND DIVERSIONS FROM SOLID WASTE STREAM
Source: International Research and Technology Corporation.
3
Figure A-13. Material flow diagram of zinc in 1971 (in 10 metric tons),
-------
MATERIAL FLOWS SELECTED FOR THIS STUDY
The methodology used in this study is based'to a large extent on the
selection of "path-products" or "chains" to represent the material flows
through the economy. The chains are selected for the so-called fourteen
categories of "finished materials," that is those materials which do not
become embodied in other materials. Because of the numerous number of
"chains" in a large input-output table, it was necessary to select only
those major chains that represent material flows through the successive
stages of production and consumption. The selection procedure for this
study has theoretical foundations in the previous IR&T study on household
waste.*
The following Figures A-14 through A-27 show the chains selected for
each material by product category end-use for inclusion in the material
flow analysis. The particular economic sectors specified by taxonomic codes
are included in each flow in order to thoroughly explain the methodology
used in the chain selection procedure.
* Forecasting the Composition and Weights of Household Solid Wastes Using
Input-Output Techniques, IR&T 372-R, November 1975.
128
-------
"FINISHED MATERIAL"
ALUMINUM
087 - ALUMINUM
Market End-Use:
BEVERAGE CONTAINERS
092 - Metal Cans
_r 030 - Alcoholic Beverages
' 031 Soft Drinks & Flavorings
OTHER PACKAGING & CONTAINERS
092 - Metal Cans
101 - Other Fabricated
Metal Products
023 - Meat Products
024 Dairy Products
026 - Grain Mill Products
032 - Fats & Oils
033 - Misc. Food Products
_[ 025 - Canned & Frozen Foods
029 - Confectionery Products
066 Drugs
067 - Cleaning & Toilet Products
093 Metal Barrels & Drums
CONSUMER & INSTITUTIONAL PRODUCTS
FURNITURE
& FURNISHINGS
HOUSEHOLD
DURABLES
ELECTRICAL & ELECTRONIC PRODUCTS
MACHINERY & INDUSTRIAL EQUIPMENT
097 - Metal Stampings
098 - Cutlery, Hand Tools,
Hardware
143 - Optical & Surgical
Instruments
144 - Medical & Surgical
Instruments
145 - Photographic Equipment
148 Toys, Sporting Goods,
Musical Instruments
150 Misc. Manufacturing, NEC
045 Household Furniture
046 - Other Furniture
103 - Farm Machinery
116 - Service Industry Machinery
123 - Household Appliances
125 - Radio & TV Receiving
118 - Electric Measuring
Instruments
119 - Transformers & Switchgear
120 Motors & Generators
124 Electric Lighting & Wiring
Equipment
127 Communication Equipment
128 Electronic Components
102 - Engines & Turbines
107 - Machine Tools, Metal
Formings
108 - Other Metal Working
Machinery
109 - Special Industrial
Machinery
110 - Pumps, Compressors, Blowers
113 - Industrial Patterns
115 - Other Office Machinery
117 Machine Shop Products
142 - Mechanical Measuring Devices
Figure A-14.
(continued)
Material flow paths selected for this study:
aluminum.
129
-------
AUTOMOBILES
u»/ - rieudx jL
-------
"FINISHED MATERIAL":
COPPER
084 - COPPER
Market End-Use:
CONSUMER & INSTITUTIONAL PRODUCTS
097 - Metal Stampings
098 - Cutlery, Hand Tools,
Hardware
147 - Jewelry and Silverware
148 - Toys, Sport, Musical
Instruments
150 - Misc. Manufacturing, SEC
HOUSEHOLD DURABLES
128 - Electronic Components
ELECTRICAL & ELECTRONIC PRODUCTS
090 - Non-Ferrous Wire
Drawings
MACHINERY & INDUSTRIAL EQUIPMENT
AUTOMOBILES
Machine Products
Hardware
. OTHER TRANSPORTATION VEHICLES
ML*
1 12
136
137
138
139
116 - Service Industry Machinery
123 - Household Appliances
125 - Radio & TV Receiving
118 - Electrical Measuring
Instruments
124 - Electric Lighting & Wiring
Equipment
127 - Communication Equipment
119 - Transformers & Swtichgear
122 - Welding Apparatus &
Graphite Products
128 - Electronic Components
131 - X-Ray, Elect. Equipment, NEC
102 - Engines & Turbines
103 - Farm Machinery
105 - Materials Handling
Machinery
109 - Special Industrial
Machinery
Pumps, Compressors,
Blowers
Power Transmission Equip.
Industrial Patterns
Machine Shop Products
Mechanical Measuring Devices
- Motor Vehicles
Truck, Bus, Trailer Bodies
Aircraft Equipment, NEC
Ship & Boat Building
Railroad Equipment
Cycles, Trans Equipment, NEC
(continued)
Figure A-16. Material flow paths selected for this study: copper.
131
-------
BUILDINGS & STRUCTURES
019 - Maintenance Construction
090 - Non-Ferrous Wire Drawings
094 - Plumbing & Heating Equip.
095 - Structural Metal Products
096 - Screw Machine Products
100 - Pipes, Valves, Fittings
140 - Trailer Coaches
167 - Owner-Occupied Dwellings
ORDNANCE
021 - Ammunition
022 - Other Ordnance
Source: International Research and Technology Corporation.
Figure A-16. (continued)
132
-------
"FINISHED MATERIAL":
FERROUS METALS
083 - STEEL
Market End-Use
BEVERAGE CONTAINERS
092 - Metal Cans
r 030
" 031
OTHER PACKAGING & CONTAINERS
092 - Metal Cans
097 - Metal Stampings
023
024
025
026
029
032
033
034
066
1 067
093
CONSUMER & INSTITUTIONAL PRODUCTS
i 098
143
144
145
146
147
148
149
L 150
Alcoholic Beverages
Soft Drinks & Flavorings
Meat Products
Dairy Products
Canned & Frozen Foods
Grain Mill Products
Confectionery Products
Fats & Oils
Miscellaneous Food Products
Tobacco Products
Drugs
Cleaning & Toilet Products
Metal Barrels & Drums
Cutlery, Hand Tools,
Hardware
Misc. Fabricated Wire
Products
Optical & Ophthalmic Goods
Medical & Surgical
Instruments
Photographic Equipment
Watches & Clocks
Jewelry & Silverware
Toys, Sport, Musical
Instruments
Office Supplies
Misc. Manufacturing, NEC
FURNITURE & FURNISHINGS
098 - Cutlery, Hand Tools,-
Hardware
099 - Misc. Fabricated
Wire Products
HOUSEHOLD DURABLES
096 - Screw Machine Products
097 - Metal Stampings
099 - Misc. Fabricated
Wire Products
120 - Motors & Generators
045 - Household Furniture
046 - Other Furniture
116 - Service Industry Machinery
t!23 - Household Appliances
125 - Radio & TV Receiving
ELECTRICAL & ELECTRONIC PRODUCTS
F119 - Transformers & Switchgear
120 - Motors & Generators
- Industrial Controls
1-121
\ 122
096 - Screw Machine Products
- Welding App.
Products
Graphite
127 - Communication Equipment
128 - Electronic Components
131 - X-Ray, Electric Equipment,
NEC
124 - Electric Lighting & Wiring
Equipment
(continued)
Figure A-17. Material flow paths selected for this study: ferrous metals.
133
-------
MACHINERY & INDUSTRIAL EQUIPMENT
102
103
104
105
106
107
108
109
110
Ill
112
113
115
117
142
Engines & Turbines
Farm Machinery
Construction, Mining,
Oil, Field Machinery
Materials Handling
Machinery
Machine Tools, Metal
Cuttings
Machine Tools, Metal
Formings
Other Metal Working
Machinery
Special Industrial
Machinery
Pumps, Compressors,
Blowers
Ball & Roller Bearings
Power Transmission
Equipment
Industrial Patterns
Other Office Machinery
Machine Shop Products
Mechanical Measuring
Devices
AUTOMOBILES
096 - Screw Machine Products -
097 - Metal Stampings
098 - Cutlery, Hand Tools,
Hardware
099 - Misc. Fabricated
Wire Products
OTHER TRANSPORTATION VEHICLES
133 - Motor Vehicles
BUILDINGS & STRUCTURES
I 132 - Truck, Bus, Trailer
Bodies
135 - Aircraft Engines
137 - Ship & Boat Building
138 - Railroad Equipment
139 - Cycles, Trans Equipment,
NEC
I 094 - Plumbing & Heating
Equipment
095 - Structural Metal Products
096 - Screw Machine Products
100 - Pipes, Valves, Fittings
101 - Other Fabricated Metal
Products
1 140 - Trailer Coaches
ORDNANCE
E
020 - Complete Guided Missiles
021 - Ammunition
022 - Other Ordnance
MISCELLANEOUS
083 - Steel
Source: International Research and Technology Corporation.
Figure A-17. (continued)
134
-------
"FINISHED MATERIAL":
GLASS
078 - GLASS
Market End-Use:
BEVERAGE CONTAINERS
030 - Alcoholic Beverages
031 - Soft Drinks & Flavorings
OTHER PACKAGING & CONTAINERS
024 - Dairy Products
025 - Canned & Frozed Foods
032 - Fats & Oils
033 - Misc. Food Products
066 Drugs
067 Cleaning & Toilet Products
CONSDMER & INSTITUTIONAL PRODUCTS
HOUSEHOLD DURABLES
124 - Electric Lighting &
Wiring
128 - Electronic
Components
ELECTRICAL & ELECTRONIC PRODUCTS
AUTOMOBILES
OTHER TRANSPORTATION VEHICLES
BUILDINGS & STRUCTURES
098 - Cutlery, Hand Tools,
Hardware
124 - Electric Lighting & Wiring
Equipment
143 - Optical & Ophthalmic Goods
144 - Medical & Surgical
Instruments
145 - Photographic Equipment
146 - Watches & Clocks
148 - Toys, Sporting Goods,
Musical Instruments
150 - Misc. Manufacturing, NEC
123 - Household Appliances
125 - Radio & TV Receiving
118 - Electric Measuring
Instruments
124 - Electric Lighting & Wiring
Equipment
127 - Communication Equipment
128 - Electronic Components
133 - Motor Vehicles
132 - Truck, Bus, Trailer Bodies
137 - Ship & Boat Building
019 - Maintenance Construction
095 - Structural Metal Products
167 - Owner-Occupied Dwellings
168 - Real Estate
Source: International Research and Technology Corporation.
Figure A-18. Material flow paths selected for this study: glass.
135
-------
"FINISHED MATERIAL":
LEAD
085 LEAD ~
Market End-Use:
OTHER PACKAGING & CONTAINERS
| 025
Metal Products ' 067
CONSUMER & INSTITUTIONAL PRODUCTS
Roll & Draw
144
145
146
1 147
ELECTRICAL & ELECTRONIC PRODUCTS
Drawings
Roll & Draw
i 119
122
MACHINERY & INDUSTRIAL EQUIPMENT
AUTOMOBILE
OTHER TRANSPORTATION
BATTERIES
BUILDINGS & STRUCTURES
ORDNANCE
OTHER INDUSTRIAL APPLICATIONS
nni
06S
Canned & Frozen Foods
Bakery Products
Cleaning & Toilet Products
Medical & Surgical
Instruments
Photographic Equipment
Watches & Clocks
Jewelry & Silverware
Toys, Sporting Goods,
Musical Instruments
Transformers & Switchgear
Motors & Generators
Welding & Graphite Products
X-Ray, Electric Equipment,
NEC
Other Metal Working
Machinery
Special Industrial
Machinery
- Motor Vehicles
- Ship & Boat Building
- Batteries
Structural Metal Products
Pipes, Valves, Fittings
- Ammunition
Industrial Chemicals
Paints
Source: International Research and Technology Corporation.
Figure A-19. Material flow paths selected'for this study: lead.
136
-------
"FINISHED MATERIAL":
LEATHER
075 - LEATHER
Market End-Use:
CONSUMER & INSTITUTIONAL PRODUCTS
077 - Other Leather Products
148 - Toys, Sporting Goods,
Musical Instruments
FURNITURE & FURNISHINGS
APPAREL
FOOTWEAR
040 - Household Textiles
045 - Household Furniture
046 - Other Furniture
039 - Apparel
076 - Footwear (Except Rubber)
MACHINERY & INDUSTRIAL EQUIPMENT
102 - Engines & Turbines
109 - Special Industrial
Machinery
110 - Pumps, Compressors, Blowers
113 - Industrial Patterns
116 - Service Industry
Machinery
Source: International Research and Technology Corporation.
Figure A-20. Material flow paths selected for this study: leather.
137
-------
"FINISHED MATERIAL":
PAPER
048 -
PAPER &
PAPERBOARD MILLS
Market End-Use:
NEWSPAPERS
049 - Paper Products, SEC
057 - Commercial Printing
052 - Newspapers
BOOKS, PERIODICALS & OTHER PRINTING PAPER
049 - Paper Products, NEC
057 - Commercial Printing
049 - Paper Products, NEC
058 - Other Printing,
Publishing
WRITING & OTHER FINE PAPER
049 - Paper Products, NEC
DISPOSABLE PRODUCTS
OTHER PACKAGING & CONTAINERS
053 - Books
054 - Periodicals
056 - Business Forma, Blank
Books
149 - Office Supplies
049 - Paper Products, SEC
049 - Paper Products, NEC
023 - Meat Products
024 - Dairy Products
025 - Canned & Frozen Foods
027 - Bakery Products
028 - Sugar
029 - Confectionery Products
033 - Misc. Food Products
034 - Tobacco Products
067 - Cleaning & Toilet Products
CONSUMER i INSTITUTIONAL PRODUCTS
049 - Paper Products, NEC
144 - Medical & Surgical In
Instruments
145 - Photographic Equipment
148 - Toys, Sporting Goods,
Musical Instruments
150 - Misc. Manufacturing, NEC
ELECTRICAL & ELECTRONIC PRODUCTS
119 - Transformers & Switchgear
122 - Welding & Graphite Products
128 - Electronic Components
049 - Paper Products, NEC
Source:. International Research and Technology Corporation.
Figure A-21. Material flow paths selected.for .this study: paper.
138
-------
"FINISHED MATERIAL":
PAPERBOARD
048 -
PAPER & PAPERBOARD
MILLS
Market End-Use:
BOOKS, PERIODICALS & OTHER PRINTING PAPER
054 - Books
OTHER PACKAGING & CONTAINERS
051 - Paperboard Containers
CONSUMER & INSTITUTIONAL PRODUCTS
I 144 - Medical & Surgical
Instruments
145 - Photographic Equipment
148 - Toys, Sporting Goods,
Musical Instruments
149 - Office Supplies
1 150 - Misc. Manufacturing, NEC
FOOTWEAR
076 - Footvear
ELECTRICAL & ELECTRONIC PRODUCTS
AUTOMOBILES
049 - Paper Products, NEC
BUILDINGS & STRUCTURES
> 119 - Transformers & Switchgear
122 - Welding Apparatus & Graphic
Products
128 - Electronic Components
133 - Motor Vehicles & Parts
I 019 - Maintenance Construction
050 - Wall & Building Paper 071 - Paving & Asphalt
1 140 - House Trailers
Source: International,Research and Technology Corporation.
Figure A-22. Material flow paths selected for this study: paperboard..
139
-------
"FINISHED MATERIAL":
PLASTICS
062 -
PLASTIC MATERIALS
AND RESINS
Market End-Use:
BEVERAGE CONTAINERS
074 - Misc. Plastic Products f~
OTHER PACKAGING & CONTAINERS
030 - Alcoholic Beverages
031 - Soft Drinks & Flavorings
074 - Misc. Plastic Products
074 - Misc. Plastic Products
023 - Meat Products
024 - Dairy Products
025 - Canned & Frozen Foods
027 - Bakery Products
029 - Confectionery Products
033 - Misc. Food Products
034 - Tobacco Products
067 - Cleaning & Toilet Products
066 - Drugs
CONSUMER & INSTITUTIONAL PRODUCTS
074 - Misc. Plastic Products
074 - Misc. Plastic Products
FURNITURE & FURNISHINGS
-c
077 - Other Leather Products
097 - Metal Stampings
126 - Phonograph Records
143 - Optical & Ophthalmic Goods
144 - Medical & Surgical
Instruments
145 - Photographic Equipment
146 - Watches & Clocks
148 - Toys, Sporting Goods,
Musical Instruments
149 - Office Supplies
150 - Misc. Manufacturing, NEC
098 - Cutlery, Hand Tools,
Hardware
147 - Jewelry & Silverware
074 - Misc. Plastic Products
HOUSEHOLD DURABLES
074 - Misc. Plastic Pro
="128 - Electronic >
Components
ELECTRICAL & ELECTRONIC PRODUCTS
090 - Non-Ferrous Wire Dwgs-
074 - Misc. Plastic_Prj
""128 - Electric
Components
MACHINERY & INDUSTRIAL EQUIPMENT
r 108
-074 - Misc. Plastic Products
E' 112
114
045 - Household Furniture
046 - Other Furniture
Household Durables
Radio & TV Receiving
- Transformers & Switchgear
- Electrical Measuring Devices
- X-Ray, Electric Equipment,
NEC
- Communication Equipment
- Electric Lighting & Wiring
Equipment
Other Metal Working
Machinery
Industrial Patterns
Power Transmission Equipment
Computers & Related
Machinery
Other Office Machinery
115 -
(continued)
Figure A-23. ' Material flow paths selected for this study: plastics.
140
-------
AUTOMOBILES
074 - Misc. Plastic Products -J~~ 133 " tfocor Vehicles
OTHER TRANSPORTATION VEHICLES
074 - Misc. Plastic Products T
BUILDINGS & STRUCTURES
074 - Misc. Plastic Products j
OTHER INDUSTRIAL APPLICATIONS
132 - Truck, Bus, Trailer Bodies
134 - Aircraft
135 - Aircraft Engines
137 - Ship & Boat Building
138 - Railroad Equipment
019 - Maintenance Construction
095 - Structural Metal Products
099 - Misc. Fabricated Wire
Products
100 - Pipes, Valves, Fittings
101 - Other Fabricated Metal
Products
1
074 - Misc. Plastic Products T^
MISCELLANEOUS
074 - Misc. Plastic Products
037 - Misc. Textiles
040 - Household Textiles
049 - Paper Products, NEC
073 - Rubber Products
Grains
Tobacco
Source: International Research and Technology Corporation.
Figure A-23. (continued)
141
-------
"FINISHED MATERIAL":
RUBBER
063 -
STOTHETIC RUBBER
Market End-Use:
CONSUMER & INSTITUTIONAL PRODUCTS
073 - Fabricated Rubber
Produces
FURNITURE & FURNISHINGS
073 - Fabricated Rubber
Products
APPAREL
073 - Fabricated Rubber
Products
FOOTWEAR
073 - Fabricated Rubber
Products
HOUSEHOLD DURABLES
073 - Fabricated Rubber^
Product
-128 - Electronic
Components
144 - Medical & Surgical
Instruments
145 - Photographic Equipment
147 - Jewelry & Silverware
149 - Office Supplies
150 - Misc. Manufacturing, SEC
036 - Floor Coverings
045 - Household Furniture
046 - Other Furniture
039 - Apparel
076 - Footwear (Except Rubber)
116 - Service Industry
Machinery
123 - Household Durables
ELECTRICAL & ELECTRONIC PRODUCTS
073 - Fabricated Rubber
Products
073 - Fabricated Rubber
Products
090 - Non-Ferrous »ire -
Drawings
125 - Radio & TV Receiving
118 - Electrical Measuring
Instruments
127 - Communications Equipment
128 - Electronic Components
119 - Transformers & Switehgear
120 - Motors & Generators
124 - Electric Lighting & Wiring
Equipment
131 - X-Ray, Electrical Equipment,
NEC
I (continued)
Figure A-24. Material flow paths selected for this study: rubber.
142
-------
MACHINERY & INDUSTRIAL EQUIPMENT
073 - Fabricated Rubber
Products
AUTOMOBILES
073 - Fabricated Rubber
Products
OTHER TRANSPORTATION VEHICLES
073 - Fabricated Rubber
Products
TIRES
103 -
104 -
105 -
106 -
113 -
114 -
115 -
141 -
142 -
Farm Machinery
Construction, Mining, Oil
Field Machinery
Materials Handling
Machinery
Machine Tools, Metal
Cutting
Industrial Patterns
Computers & Related
Machinery
Other Office Machinery
Engineering & Scientific
Instruments
Mechanical Measuring Devices
133 - Motor Vehicles & Parts
132 - Truck, Bus, Trailer Bodies
134 - Aircraft
_ 136 - Aircraft Equipment, NEC
137 - Ship & Boat Building
138 - Railroad Equipment
139 - Cycles, Trans Equipment,
NEC
076 - Tires & Inner Tubes
Source: International Research and Technology Corporation
Figure A-24. (continued)
143
-------
"FINISHED MATERIAL":
TEXTILES
035 -
Broad and
Narrow Fabrics
IAL":
DISPOSABLE PRODUCTS
CONSUMER & INSTITUTIONAL PRODU
FURNITURE & FURNISHINGS
APPAREL
FOOTWEAR
A/,0
CTS
i 077
14 .5
1 Aft
149
150
HAH
n-tf
ELECTRICAL & ELECTRONIC PRODUCTS
nr\n
i ?n
___ 1 1A
MACHINERY & INDUSTRIAL EQUIPMENT
AUTOMOBILES
OTHER TRANSPORTATION
TIRES
OTHER INDUSTRIAL APPLICATIONS
1 1 fi
, 1 11
1 1A
1 Ifi
07?
/\*o
. _ . -. rm
Source: International Research and Technology
Figure A-25. Material flow paths selected for
- Paper Products, NEC
Other Leather Products
Optical & Ophthalmic Goods
Toys, Sporting Goods and
Musical Instruments
Musical & Surgical
Instruments
Jewelry & Silverware
Office Supplies
Misc. Manufacturing, NEC
Floor Coverings
Household Textiles
Household Furniture
Other Furniture
- Apparel
- Footwear (Except Rubber)
Non-Ferrous Wire Drawings
Motors & Generators
Electric Lighting & Wire
Equipment
Special Industrial Machinery
Service Industry Machinery
- Motor Vehicles
Aircraft
Aircraft Equipment, NEC
- Tires & Inner Tubes
- Paper & Paperboard Mills
- Plastic Materials & Resins
- Misc. Plastic Products
Corporation.
this study: textiles.
144
-------
"FINISHED MATERIAL":
WOOD
041 -
LUMBER & LUMBER
PRODUCTS
Market End-Use:
OTHER PACKAGING & CONTAINERS
CONSUMER & INSTITUTIONAL PRODUCTS
FURNITURE & FURNISHINGS
. flAfi
Products
MACHINERY & INDUSTRIAL EQUIPMENT
OTHER TRANSPORTATION
Products
BUILDINGS & STRUCTURES
1 ^fl
nAi
iin
1 fi7
168
- Wooden Containers
Other Leather Products
Toys, Sporting Goods,
Musical Instruments
Misc. Manufacturing, NEC
Household Furniture.
Office Furniture
Farm Machinery
Construction, Mining, Oil
Field Machinery
Special Industrial
Machinery
Pumps, Compressors, Blowers
Ball & Roller Bearings
Industrial Patterns
Ship & Boat Building
Railroad Equipment
Maintenance Construction
Veneer & Plywood
Millwork & Wood Products
Structural Metal Products
Trailer Coaches
Owner-Occupied Dwellings
Real Estate
Source: International Research and Technology Corporation.
Figure A-26. Material flow paths selected for this study: wood.
145
-------
"FINISHED MATERIAL":
ZINC
086 - ZINC
Market End-Use:
CONSUMER & INSTITUTIONAL PRODUCTS
HOUSEHOLD DURABLES
091 - Non-Ferrous Casting
& Forging
ELECTRICAL & ELECTRONIC PRODUCTS
091 - Non-Ferrous Casting
& Forging
MACHINERY & INDUSTRIAL EQUIPMENT
091 - Non-Ferrous Casting
4 Forging
AUTOMOBILE
091 - Non-Ferrous Casting
& Forging
097 - Metal Stampings
097 - Metal Stamping
098 - Cutlery, Hand Tools,
Hardware
123 - Household Appliances
Transformers & Swltchgear
Electric Lighting & Wiring
Equipment
102 - Engines & Turbines
105 - Materials Handling
Machinery
110 - Pumps, Compressors, Blowers
112 - Power Transmission
Equipment
130 - Engine Electrical
Equipment
OTHER TRANSPORTATION VEHICLES
091 - Non-Ferroua Casting
& Forging
BUILDINGS & STRUCTURES
133 - Motor Vehicles
134 - Aircraft
135 - Aircraft Engines
136 - Aircraft Equipment, NEC
138 - Railroad Equipment
095 - Structural Metal Products
096 - Screw Machine Products
099 - Misc. Fabricated Wire
Products
100 - Pipes, Valves, Fittings
140 - House Trailers
Source: International Research and Technology Corporation.
Figure A-27. Material flow paths selected for this study: zinc.
146
-------
PRODUCT LIFETIME ASSUMPTIONS
One of the major parameters affecting solid waste generation is
average product lifetimes. The estimates used in this study were derived
from a review of the literature; the lifetime assumptions and sources
of information are presented in Table A-17. Note that for some products,
no source giving average product life was available. For those products,
average lifetime assumptions were made on the basis of judgment.
147
-------
TABLE A-17. SOLID WASTE RECYCLING MODEL REFERENCE SCENARIO. SOURCES OF
AVERAGE PRODUCT LIFETIME ASSUMPTIONS (Percent Discarded by
Age) ___^__
Product
Lifetime*
Source
Newspaper
Books & Periodicals and
Other Printing Paper
Disposables
Beverage Containers
Other Packaging &
Containers
Consumer & Institutional
Products
Furniture
Apparel
Footwear
Household Durables
Electrical & Electronic
Products
Machinery and Industrial
Equipment
Automobiles
Other Transportation
Tires
Batteries
Buildings and Structures
Ordnance
94.0% - 1st year
5.0% - 1-5 years
1.0% - 5-10 years
70.0% - 1st year
17.0% - 1-5 years
13.0% - 5-10 years
100% - 1st year
100% - 1st year
100% - 1st year
7 year average
10 year average
4 year average
2 year average
10 year average
15 year average
20 year average
10 year average
20 year average
5 year average
3 year average
50 year average
5 year average
MRI
MRI
API
API
A.D. Little
A.D. Little
A.D. Little
IR&T
MIT
(continued)
148
-------
TABLE A-17. (continued)
Product Lifetime* Source
Other Industrial 2 year average
Applications
Miscellaneous 2 year average
Source: Compiled by International Research and Technology Corporation.
* Disposal of a product for which an average lifetime is listed (i.e.,
all but the first six categories) is distributed over time using a
frequency distribution whose graph is bell-shaped and symetrical.
Thus, for products with an average life of seven years, half are
disposed of between 0 and 7 years in increasing amounts annually,
and half are disposed of after seven years in decreasing amounts
annually.
149
-------
RECYCLING ASSUMPTIONS
Introduction
The recycling rates used in this study are assumed levels based on
technological trends discussed in various sources. Table A-18 shows the old
scrap recycling rates for material product categories in 1971 and 1990.
These old scrap or post-consumer rates are the exogenous variables that were
changed in two scenarios, Constant Recycling and Increased Recycling. In the
Increased Recycling Scenario, the recycling rates assumed for material in
each product category was increased by ten percent, with the exception of
those material product categories that have no recycling. Table A-19 shows
the estimated current and assumed future new (prompt) scrap factors for each
material product category and the percentage of new scrap which is recycled
by marketing the material or recycling within the plant. The new scrap rate
is the ratio of material discarded during the manufacture of a product to the
material consumed in the fabrication of that product. The new scrap factors
and the new scrap recycling rates were not changed from scenario to scenario.
Aluminum
Bureau of Mines provides data on aluminum new scrap factors which are
presented in Table A-19. Present recycling levels for aluminum were obtained
from estimates in A Study to Identify Opportunities for Increased Solid Waste
Utilization^ Volume II (40), by Battelle Memorial Institute. Recycled values
for 1969 are presented in Table 13, page 45, for old scrap (obsolete) re-
cyclables. Data on recycling levels for aluminum cans were derived from the
Aluminum Association (48).
The maximum recycling levels of aluminum for 1990 are based on esti-
mates and trends from Base Line Forecasts of Resource Recovery3 1972-1990
(26) by Midwest Research Institute (MRI), 1977, and IR&T. The main increase
in the recycling of obsolete aluminum will be due to the large increase in
packaging and container recycling, the result of the increased efficiency of
waste recovery systems for separating aluminum from other wastes.
Concrete
No recycling of concrete products is assumed.
Copper
New (prompt) scrap factors, shown in Table A-19 were derived from
Bureau of Mines data. Values for the current copper recycling rates (1970)
were derived from their data presented in the Recovery of Secondary
Copper and Zinc in the United States (74) published in 1974. Levels of
recycling were derived by calculating the ratio of the amounts of copper
recovered from obsolete sources by product category in 1970 to amounts
of obsolete copper available (recovered plus unrecovered) in 1970 by
150
-------
TABLE A-18. RECYCLING RATES FOR MATERIAL PRODUCT CATEGORIES (1971 and 1990)*
(Old Scrap Post Consumer)
MATERIAL
Product
Category
Newspapers
Books/Periodicals
Writing Paper
Disposables
Bev. Containers
Other Packaging
Cons/Inst. Products
Furniture
Apparel
Footwear
Household Durables
Elect. /Electronics
Machinery
Automobiles
Other Transp.
Tires
Batteries
Construction
Ordnance
Other Indus. Appl.
Miscellaneous
Paper
71/90
.23 .30
.11 .16
.11 .16
.00 .00
.10 .15
.00 .00
.00 .00
Paper-
Board
71/90
.11 .16
.17 .25
.10 .15
.00 .00
.00 .00
.00 .00
.00 .00
Plas-
tics
71/90
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
Glass
71/90
.02 .06
.02 .06
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
Alu-
minum
71/90
.08 .30
.00 .10
.09 .20
.09 .20
.13 .25
.93 .95
.25 .30
.30 .60
.30 .60
.13 .20
.09 .20
Zinc
71/90
.06 .06
.10 .10
.23 .29
.10 .10
.20 .20
.20 .20
.27 .52
Copper
71/90
.18 .19
.36 .38
.36 .38
.37 .40
.31 .33
.31 .33
.29 .30
.18 .19
Lead
71/90
.62 .80
.14 .50
.25 .90
.00 .00
.00 .00
.00 .00
.72 .90
.29 .30
.14 .50
.00 .00
Ferrous
Metals
71/90
.11 .50
.11 .50
.01 .20
.01 .20
.05 .25
.00 .10
.05 .20
.85 .95
.85 .95
.10 .30
.05 .20
.05 .20
.05 .20
Wood
71/90
.00 .00
.00 .00
.00 .00
'.00 .00
.00 .00
Tex-
tiles
71/90
.00 .00
.00 .00
.66 .66
.66 .66
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
Rub-
ber
71/90
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
.08 .15
Lea-
ther
71/90
.00 .00
.00 .00
.00 .00
.00 .00
.00 .00
Con-
crete
71/90
.00 .00
* Old scrap is scrap generated after consumption of products and their discard by consumers.
Old scrap recycling rates have been rounded.
Source: Compiled by International Research and Technology Corporation.
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TABLE A-19. NEW SCRAP FACTORS AND NEW SCRAP RECYCLING RATES*
MATERIAL
Product
Category
Newspapers
Books/Periodicals
Writing Paper
Disposables
Bev. Containers
Other Packaging
Cons/ Ins t. Products
Furniture
Apparel
Footwear
Household Durables
Elect. /Electronics
Machinery
Automobiles
Other Transportation
Tires
Batteries
Construction
Ordnance
Other Indus. Appl.
Miscellaneous
Paper
NS/RF
,03 .87
.15 .87
.06 .87
.05 .87
.05 .87
.05 .87
.05 .87
Paper
Board
NS/RF
.17 .87
.14 .87
.17 .87
.17 .87
.17 .87
.17 .87
.07 .87
Plas-
tics
NS/RF
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
.05 .58
Glass
NS/RF
.05 1.0
.05 1.0
.07 1.0
.08 1.0
.07 1.0
.13 1.0
.13 1.0
.14 1.0
Alu-
minum
NS/RF
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
.16 .84
Zinc
NS/RF
.15 .68
.15 .68
.15 .68
.15 .68
.15 .68
.15 .68
.15 .68
Copper
NS/RF
.31 1.0
.31 1.0
.31 1.0
.31 1.0
.31 1.0
.31 1.0
.31 1.0
Lead
NS/RF
.10 .99
.10 .99
.10 .99
.10 .99
.10 .99
.10 .99
.10 .99
.10 .99
.10 .99
.00 1.0
ferrous
Metals
NS/RF
.12 1.0
.12 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
.20 1.0
00 1.0
.20 1.0
Wood
NS/RF
.24 .74
.60 .74
.60 .74
.30 .74
.10 .74
10 .74
Tex-
tiles
NS/RF
.05 .60
.05 .60
.05 .60
.10 .60
.05 .60
.05 .60
.05 .60
.05 .60
.05 .60
.05 .60
.05 .60
Rub-
ber
NS/RF
.05 .25
.05 .25
.05 .25
.05 .25
.05 .25
.05 .25
.05 .25
.05 .25
.05 .25
.03 .25
Lea-
ther
NS/RF
.15 .00
.15 .00
.15 .00
.15 .00
.15 .00
Con-
crete
NS/RF
.00 1.0
*The new scrap factor (NS) reflects the fraction of material throughput contributing to new
scrap. The new scrap recycling rate (RF) reflects the fraction of new scrap re-used inhouse
or elsewhere. These assumptions are held constant over time. New scrap rates have been
rounded.
Source: Compiled by International Research and Technology Corporation.
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product end-use category. In mathematical terms,
CR1970
CR1970 + CU1970
where CR is copper recovered form obsolete sources, and
CU is copper unrecovered from obsolete sources.
Projections of copper recycling rates for 1990 are based on a
ratio of the amount of copper expected to be recovered in 1990, to the
amount of copper expected to be available (recovered plus unrecovered).
This data is also available in the Bureau of Mines report.
Ferrous Metals
EPA's Office of Solid Waste provided data on new scrap factors for
ferrous metals as shown in Table A-19. Recycling level estimates (1970)
of ferrous metals were derived from estimates in two reports sponsored
by EPA, Economic and Technological Impediments to Recycling Obsolete
Ferrous Solid Waste (75) by the National Environmental Research Center
(NERC), 1973, Base Line Forecasts of Resource Recovery, 1972-1990 (26)
by MRI, 1975, and IR&T estimates.
Packaging and container recycling levels were derived from the data
shown in the Appendix (obsolete scrap supply from steel products) of the
NERC report. Discussion on pages 33-35 of this report projects increased
container recycling due to the use of tin-free steel. Values for house-
hold durables are based on the discussion on pages 37-39 in the NERC
publication. Problems of contaminants, porcelain coating, and low
yield of steel per article shredded reduce the desireability of recycling
household products. Automotive and transportaion levels are based on
NERC's estimate of present car recycling (85%). Values for "Other
Consumer Goods" are derived from the MRI report (pp. 79,90), assuming
that container ferrous scrap in municipal waste is from "Other Consumer
Products." Construction recycling of ferrous metals are based on
discussion of building and industrial plant demolition (pp. 222-224) in
Identification of Opportunities for Increased Recycling of Ferrous
Solid Waste, (37). Other recycling assumptions for machinery, electronics,
and other metal products are IR&T estimates.
Glass
New scrap generation factors are derived from Census data on
cullet consumption (57). Adjustments for assumed recycling levels of
glass containers are derived from the Glass Packaging Institute's
data (56).
Lead
New (prompt) scrap factors for lead are derived from Bureau of
Mines data. Estimates for lead recovery are based on A Study to
153
-------
Identify Opportunities for Increased Solid Waste Utilization, Volume IV
(40) by Battelle Memorial Institute, and IR&T estimates. It is assumed
that estimates of recycling rates for lead products applies to product
end-use categories in the study. For instance, recycling rate estimates
for cable sheathing applies to the electrical and electronics product
category, foil applies to other packaging and containers, pipe fittings
and sheet to buildings and structures, and ammunition, solders and
beaming lead to other metal products.
Projections of recycling rates for 1990 are based on estimates in
the Battelle-Columbus report. Large increases are projected for lead
recovery due to the phasing out of tetra-ethyl lead in gasoline. Large
savings are expected in cable recycling by the year 1990. The other
trend in lead recovery is a marked increase in the recycling rate of
batteries by 1990, as shown in Table A-18.
Leather
A new (prompt) scrap factor of 15% is assumed in this study. No
recycling of post-consumer leather is assumed.
Paper and Paperboard
A summary of the recycling assumptions made for new scrap and old
scrap for paper is presented in Table A<-20. The source of most of the
assumptions is the American Paper Institute's report, 1976-1979 Capacity:
Paper3 Paperboard3 Woodpulp (76) and William Franklin's estimates for
the EPA's Office of Solid Waste annual Report to Congress (36).
Plastics
As shown in Table A-18, no recycling of obsolete plastic scrap is
assumed for the years 1971 through 1990. The A.D. Little study,
Incentives for Eecycling and Reuse of Plastics (64) indicates that all
sources of industrial plastics from manufacture to distribution are
included in these estimates. New scrap in this study includes scrap
conversion of the material and fabrication of the product. The new
scrap estimates were reduced from a previous estimate of 6.1% to 4.9%
as indicated in Table A-19. The recycling of the new scrap, generally
by marketing the material, is assumed to be 58% of the new scrap
generation.
Rubber
New (prompt) scrap estimates were taken from the EPA report A Solid
Waste Estimation Procedure: Materials Flow Approach (27), 1975. Estimates
of rubber tire recycling of 8.3 percent in 1971 were taken from the Rubber
Manufacturers Association (65) data on reclaimed rubber usage. Rubber
tire recycling is projected to increase to 15% in 1990. Rubber use
diverted from tread is assumed to be 10 percent from the Markiewcz and
Gransky study Solid Waste Management and Rubber Reuse Potential in the
Rubber Industry: Waste Rubber and Its Use, 1968 (77).
154
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TABLE A-20. NEW SCRAP AND OLD SCRAP RECYCLING AND DIVERSION
ASSUMPTIONS FOR PAPER AND PAPERBOARD WASTES
Percent
Recycled
Source
PAPER
Newspaper
New Scrap
% Recycled
Diversion
Old Scrap
Base (1971)
Projected (1990)
2.5%
87.0%
.5%
23.0%
30.0%
MRI/Franklin/API
EPA
MRI
API
IR&T
Other Printing Paper
New Scrap 15.0%
% Recycled 87.0%
% Diverted 7.0%
Old Scrap
Base (1971) 11.0%
Projected (1990) 16.0%
Writing & Other Fine Paper
New Scrap 6.1%
% Recycled 87.0%
% Diverted 6.0%
Old Scrap
Base (1971) 11.0%
Projected (1990) 16.0%
Disposable Paper
New Scrap 5.0%
% Recycled 87.0%
% Diverted 31.0%
Old Scrap
Base (1971) 0.0%
Projected (1990) 0.0%
Electrical & Electronic
Products
New Scrap 5.0%
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 0.0%
Projected (1990) 0.0%
MRI
MRI
API
IR&T
MRI
EPA
MRI
API
IR&T
MRI
EPA
MRI
API
EPA
EPA
(continued)
155
-------
TABLE A-20. (continued)
Percent
Recycled
Source
Other Packaging &
Containers
New Scrap 5.0%
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 10.0%
Projected (1990) 15.0%
Consumer & Institutional
Products
New Scrap 5.0%
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 0.0%
Projected (1990) 0.0%
PAPERBOARD
Other Packaging &
Containers
New Scrap 13.6%
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 16.5%
Projected (1990) 25.0%
Books, Periodicals and
Other Printing Paper
New Scrap
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 11.0%
Projected (1990) 16.0%
Consumer & Institutional
Products
New Scrap 17.0%
% Recycled 87.0%
% Diverted 0.0%
Old Scrap
Base (1971) 10.0%
Projected (1990) 15.0%
MRI
EPA
API
IR&T
MRI
EPA
EPA
API
IR&T
EPA
EPA
API
IR&T (continued)
156
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TABLE A-20. (continued)
Footwear
New Scrap
% Recycled
% Diverted
Old Scrap
Base (1971)
Projected (1990)
Electrical & Electronic
Products
New Scrap
% Recycled
% Diverted
Old Scrap
Base (1971)
Projected (1990)
Automobiles
New Scrap
% Recycled
% Diverted
Old Scrap
Base (1971)
Projected (1990)
Buildings & Structures
New Scrap
% Recycled
% Diverted
Old Scrap
Base (1971)
Projected (1990)
Percent
Recycled
17.0%
87.0%
0.0%
0.0%
0.0%
17.0%
87.0%
0.0%
0.0%
0.0%
17.0%
87.0%
0.0%
0.0%
0.0%
6.5%
87.0%
0.0%
0.0%
0.0%
Source
EPA
EPA
EPA
EPA
Source: API, Peeper, Paperboard, Woodpulp Capacity, annual report, "Waste
Paper in Paper and Paperboard Manufacture."
Franklin, estimates for EPA's Office of Solid Waste's Annual
Report to Congress.
EPA, Office of Solid Waste, A Solid Waste Estimation Procedure:
Materials Flow Approach, EPA/530/SW-147, 1975.
A.D. Little, Incentives for Recycling and Reuse of Plastics, Study
for EPA, PB 214045, 1972, Table 35, p. 111-40.
157
-------
New scrap factors and recycling estimates were derived from the
Battelle study, A Study to Identify Opportunities for Increased Solid
Waste Utilisation (40).
Wood
Estimates for new scrap and recycling rates were taken from EPA's
Office of Solid Waste. No recycling of post-consumer (old scrap) wood
products is assumed in this study.
Zinc
The source of the zinc new scrap factors is data from the Bureau
of Mines. Current zinc recycling rates (1970) are derived from data in
the Recovery of Secondary Copper and Zinc in the United States (74)
published by the Bureau of Mines in 1974. Zinc recycling levels were
derived by calculating the ratio of the amounts of zinc recovered from
obsolete sources by each product category in 1970 to the amounts of
zinc available (recovered plus unrecovered) from obsolete recovery in
1970 by product end-use category. As discussed previously in the
section on copper recycling, the ratio calculated to obtain zinc
recycling by product category is the same ratio calculated to obtain
copper recycling by end-use. In mathematical terms,
ZR1970
ZR1970 + ZU1970
where ZR is zinc recovered from obsolete sources, and
ZU is zinc unrecovered from obsolete sources.
Projections of the percentage of zinc expected to be recycled in
1990 are based on a ratio of the amount of zinc projected to be recovered
in 1990, to the amount of zinc available (recovered and unrecovered).
This data was also available in the Bureau of Mines report.
Categories were coupled for both 1970 and 1990 estimates as follows:
Product Category Bureau of Mines Categories
Construction Agricultural, Mining and Construction
Equipment, Roofing and Construction
Electrical Electronic Equipment, Rod and Wire
Automobiles Automotive
Other Transportation Other Transportation
Machinery Machinery and Tools, Office
Equipment
Other All Other Categories Listed
158
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/5-80-001
3. flECIPIENTS ACCESSIOWNO.
4. TITLE AND SUBTITLE
Forecasts of the Quantity and Composition of Solid
Waste
5. REPORT DATE
May 1980 (Issuing Date)
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO
Ralph M. Doggett, Mary K. 0'Parrel!,
and Andrea L. Watson
9. PERFORMING ORGANIZATION NAME AND ADDRESS
International Research and Technology Corporation
7655 Old Springhouse Road
McLean, Virginia 22102
10. PROGRAM ELEMENT NO.
1DC818
11. CONTRACT/GRANT NO.
68-03-2649
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research LaboratoryCin.,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 513/684-7881
he overall' objective was to develop a methodology and predict the future
quantities and composition of solid waste. A data base was compiled and a methodology
developed to evaluate the effects of selected variables, including the extent of
resource recovery, product lifetime, material and process substitutions, and economic
growth. The methodology employs an interindustry forecasting model of the United
States, which allows for specification of alternative values for critical variables.
Projections of the quantity and composition of solid waste involving 14 materials
in 21 product categories are made to 1990 under five different scenarios. Results of
the scenarios are compared with other studies, including the EPA Annual Reports to
Congress on Resource Recovery and Waste Reduction, and projections by Midwest Research
Institute in Base Line Forecasts of Resource Recovery, 1972-1990, prepared for EPA.
Results of the scenarios suggest that the quantity of solid waste is likely to increase
at a slower rate than the economy due to substitutions of heavy materials such as stee
and glass by lighter materials such as aluminum, plastics and paper. The results also
suggest that the future solid waste stream is strongly influenced by product lifetime,
recycling rates, and technolgical changes.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Wastes
Refuse disposal
Scrap
Solid waste
Forecasts
Quantity
Composition
68C
18. DISTRIBUTION STATEMENT
Unlimited
19. SECURITY CLASS (ThisReport)
not classified
21. NO. OF PAGES
171
20. SECURITY CLASS (Thispage)
not classified
22. PRICE
EPA Form 2220-1 (9-73)
159
«US GOttWUENT HUNTING OFFICE 1SSO-657-146/S692
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