2Printed on paper that contains at least 20 percent postconsumer fiber.

Greenhouse Gas Emissions

From Management of 

Selected Materials in

Municipal Solid Waste

United States 

Environmental Protection 

Agency

EPA530-R-98-013

September 1998

http://www.epa.gov

1EPA

Solid Waste

and Emergency Response

(5306W)
GREENHOUSE GAS EMISSIONS FROM

MANAGEMENT OF SELECTED MATERIALS IN

MUNICIPAL SOLID WASTE

FINAL REPORT

Prepared for the U.S. Environmental Protection Agency

under EPA Contract No. 68-W6-0029

September 1998
i

TABLE OF CONTENTS

EXECUTIVE SUMMARY: BACKGROUND AND FINDINGS..........................................................ES-1

ES.1 GREENHOUSE GASES AND CLIMATE CHANGE.................................................ES-1

ES.2 WHAT IS THE UNITED STATES DOING ABOUT CLIMATE CHANGE? ...........ES-2

ES.3 WHAT IS THE RELATIONSHIP OF MUNICIPAL SOLID WASTE TO

GREENHOUSE GAS EMISSIONS?............................................................................ES-3

ES.4 WHY EPA PREPARED THIS REPORT AND HOW IT WILL BE USED................ES-4

ES.5 HOW WE ANALYZED THE IMPACT OF MUNICIPAL SOLID WASTE

ON GREENHOUSE GAS EMISSIONS.......................................................................ES-5

ES.6 RESULTS OF THE ANALYSIS................................................................................ES-10

ES.7 LIMITATIONS OF THE ANALYSIS........................................................................ES-16

1. METHODOLOGY....................................................................................................................................1

1.1 INTRODUCTION...............................................................................................................1

1.2 THE OVERALL FRAMEWORK:

A STREAMLINED LIFE CYCLE INVENTORY .............................................................1

1.3 THE REVIEW PROCESS ..................................................................................................2

1.4 MSW MATERIALS CONSIDERED IN THE STREAMLINED LIFE CYCLE

INVENTORY .....................................................................................................................3

1.5 KEY INPUTS AND BASELINES FOR THE STREAMLINED

LIFE CYCLE INVENTORY ..............................................................................................4

1.6 HOW THESE INPUTS ARE TALLIED AND COMPARED ...........................................7

1.7 SUMMARY OF THE LIFE CYCLE STAGES..................................................................9

2. RAW MATERIALS ACQUISITION AND MANUFACTURING........................................................15

2.1 GHG EMISSIONS FROM ENERGY USE IN RAW MATERIALS

ACQUISITION AND MANUFACTURING....................................................................15

2.2 NON-ENERGY GHG EMISSIONS FROM MANUFACTURING

AND RAW MATERIALS ACQUISITION......................................................................20

2.3 RESULTS .........................................................................................................................20

2.4 LIMITATIONS OF THE ANALYSIS..............................................................................21

3. FOREST CARBON SEQUESTRATION...............................................................................................35

3.1 MODELING FRAMEWORK...........................................................................................38

3.2 THE NORTH AMERICAN PULP AND PAPER (NAPAP) MODEL ............................39

3.3 THE TIMBER ASSESSMENT MARKET MODEL (TAMM)

AND THE AGGREGATE TIMBERLAND ASSESSMENT SYSTEM (ATLAS) .........44

3.4 THE FOREST CARBON MODEL (FORCARB) ............................................................47

3.5 THE HARVESTED CARBON MODEL (HARVCARB)................................................49

3.6 RESULTS .........................................................................................................................52

3.7 LIMITATIONS OF THE ANALYSIS..............................................................................56

4. SOURCE REDUCTION AND RECYCLING........................................................................................61

4.1 GHG IMPLICATIONS OF SOURCE REDUCTION ......................................................61

4.2 GHG IMPLICATIONS OF RECYCLING .......................................................................63

4.3 SOURCE REDUCTION WITH MATERIAL SUBSTITUTION.....................................66

4.4 LIMITATIONS OF THE ANALYSIS..............................................................................67
ii

5. COMPOSTING.......................................................................................................................................71

5.1 POTENTIAL GREENHOUSE GAS EMISSIONS ..........................................................71

5.2 POTENTIAL CARBON SEQUESTRATION..................................................................72

5.3 NET GHG EMISSIONS FROM COMPOSTING ............................................................76

5.4 LIMITATIONS OF THE ANALYSIS..............................................................................76

6. COMBUSTION ......................................................................................................................................79

6.1 METHODOLOGY............................................................................................................81

6.2 RESULTS .........................................................................................................................89

6.3 LIMITATIONS OF THE ANALYSIS..............................................................................92

7. LANDFILLING ......................................................................................................................................95

7.1 EXPERIMENTAL VALUES FOR METHANE GENERATION

AND CARBON SEQUESTRATION...............................................................................96

7.2 FATES OF LANDFILL METHANE: CONVERSION TO CO2, EMISSIONS,

AND FLARING OR COMBUSTION WITH ENERGY RECOVERY ...........................99

7.3 NET GHG EMISSIONS FROM LANDFILLING..........................................................101

7.4 LIMITATIONS OF THE ANALYSIS............................................................................102

8. ACCOUNTING FOR EMISSION REDUCTIONS..............................................................................111

8.1 GHG EMISSIONS FOR EACH WASTE

MANAGEMENT OPTION ............................................................................................111

8.2 APPLYING EMISSION FACTORS ..............................................................................113

 BACKGROUND DOCUMENTS (Available in the docket in the RCRA Information Center)

DOCUMENT A - BACKGROUND DATA SUBMITTED BY FRANKLIN ASSOCIATES, Ltd.

ATTACHMENT 1 - A PARTIAL LIFE CYCLE INVENTORY OF PROCESS

AND TRANSPORTATION ENERGY FOR BOXBOARD AND PAPER

TOWELS

DOCUMENT B - BACKGROUND DATA SUBMITTED BY THE TELLUS INSTITUTE

DOCUMENT C - REVIEW PROCESS FOR THE REPORT

DOCUMENT D - COMMENT-RESPONSE DOCUMENT
iii

PREFACE

This document was prepared for the United States Environmental Protection Agency under

Contract No. 68-W2-0056. The work assignment was managed by Eugene Lee of the Office of Solid

Waste. Clare Lindsay and Henry Ferland of the Office of Solid Waste and Michael Podolsky and Brett

Van Akkeren of the Office of Policy provided substantive input and assistance.

Mr. Lee would like to thank the primary authors of this report, Randy Freed, William Driscoll,

and Sarah Stafford of ICF Incorporated. EPA also acknowledges the assistance of the following persons

in the development of this report:

Contributors

Frank Ackerman, Tufts University

Morton Barlaz, North Carolina State

 University

Terry Boguski, Franklin Associates

Bill Franklin, Franklin Associates

Marge Franklin, Franklin Associates

Melissa Huff, Franklin Associates

Clark Row, Row and Associates

John Stutz, Tellus Institute

Brian Zuckerman, Tellus Institute

Reviewers

Dana Arnold, EPA, OSW

Michael Cole, University of Illinois at Urbana-

 Champaign

Truett DeGeare, EPA OSW

Bob Dellinger, EPA, OSW

Richard Denison, Environmental Defense Fund

Linda Gaines, Argonne National Laboratory

George Garland, EPA, OSW

Terry Grist, EPA, OSW

Richard Haynes, USDA, Forest Service

Linda Heath, USDA, Forest Service

Kathleen Hogan, EPA, OAR

Bill Hohenstein, EPA, OPPE

Peter Ince, USDA, Forest Service

Cindy Jacobs, EPA, OAR

Rich Kashmanian, EPA, OPPE

Steve Levy, EPA, OSW

Reid Lifset, Yale University

Richard McClimans, State University of New

 York at Syracuse

William Seitz, H. John Heinz Center for

 Science, Economics and Environment

Frank Stodolsky, Argonne National Laboratory

Susan Thorneloe, EPA, ORD

Ralph Torrie, Torrie Smith Associates

Carleton Wiles, Natl. Renewable Energy Lab

Steven Winnett, EPA, OPPE
ES-1

EXECUTIVE SUMMARY: BACKGROUND AND FINDINGS

An important environmental challenge facing the United States (US) is management of

municipal solid waste (MSW). In 1996, the US generated 210 million tons of MSW;1

 per-capita

MSW generation rates have risen throughout most of the last decade. At the same time, the US

recognizes climate change as a potentially serious issue, and is embarking on a number of actions

to reduce the emissions of greenhouse gases (GHGs) that can cause it. This report examines how

the two issues – MSW management and climate change – are related, by presenting material–

specific GHG emission factors for various waste management options.

Among the efforts to slow the potential for climate change are measures to reduce

emissions of carbon dioxide from energy use, reduce methane emissions, and change forestry

practices to promote long-term storage of carbon in trees. Different management options for

MSW provide many opportunities to affect these same processes, directly or indirectly. This

report integrates, for the first time, a wealth of information on GHG implications of various

MSW management options for some of the most common materials in MSW and for mixed

MSW and mixed recyclables. The report's findings may be used to support voluntary reporting of

emission reductions from waste management practices.

ES.1 GREENHOUSE GASES AND CLIMATE CHANGE

Climate change is a serious international environmental concern and the subject of much

research and debate. Many, if not most, of the readers of this report will have a general

understanding of the greenhouse effect and climate change. However, for those who are not

familiar with the topic, a brief explanation follows.2

A naturally occurring shield of "greenhouse gases" (primarily water vapor, carbon

dioxide, methane, and nitrous oxide), comprising 1 to 2 percent of the Earth's atmosphere, traps

radiant heat from the Earth and helps warm the planet to a comfortable, livable temperature

range. Without this natural "greenhouse effect," the average temperature on Earth would be

approximately 5 degrees Fahrenheit, rather than the current 60 degrees Fahrenheit.3

 1

 U.S. EPA Office of Solid Waste, Characterization of Municipal Solid Waste in the United

States: 1997 Update, EPA 530-R-9-001, p. 26.

2

 For more detailed information on climate change, please see The Draft 1998 Inventory of US

Greenhouse Gas Emissions and Sinks: 1990-1996, (http://www.epa.gov/globalwarming/inventory/1998-

inv.html) (March 1998); and Climate Change 1995: The Science of Climate Change (J.T. Houghton, et al.,

eds.; Intergovernmental Panel on Climate Change [IPCC]; published by Cambridge University Press,

1996). To obtain a list of additional documents addressing climate change, call EPA's Climate Change

"FAX on Demand" at (202) 260-2860 or access EPA's global warming web site at

www.epa.gov/globalwarming.

3

Climate Change 1995: The Science of Climate Change (op. cit.), pp. 57-58.
ES-2

Many scientists, however, are alarmed by a significant increase in the concentration of

carbon dioxide and other GHGs in the atmosphere. Since the pre-industrial era, atmospheric

concentrations of carbon dioxide have increased by nearly 30 percent and methane

concentrations have more than doubled. There is a growing international scientific consensus that

this increase has been caused, at least in part, by human activity, primarily the burning of fossil

fuels (coal, oil, and natural gas) for such activities as generating electricity and driving cars.4

Moreover, there is a growing consensus in international scientific circles that the buildup

of carbon dioxide and other GHGs in the atmosphere will lead to major environmental changes

such as: (1) rising sea levels (that may flood coastal and river delta communities); (2) shrinking

mountain glaciers and reduced snow cover (that may diminish fresh water resources), (3) the

spread of infectious diseases and increased heat-related mortality, (4) impacts to ecosystems and

possible loss in biological diversity, and (5) agricultural shifts such as impacts on crop yields and

productivity. Although it is difficult to reliably detect trends in climate due to natural variability,

the best current predictions suggest that the rate of climate change attributable to GHGs will far

exceed any natural climate changes that have occurred during the last 10,000 years.5

Many of these changes appear to be occurring already. Global mean surface temperatures

have already increased by about 1 degree Fahrenheit over the past century. A reduction in the

Northern Hemisphere's snow cover, a decrease in Arctic sea ice, a rise in sea level, and an

increase in the frequency of extreme rainfall events have all been documented.6

Such important environmental changes pose potentially significant risks to humans,

social systems, and the natural world. Of course, many uncertainties remain regarding the precise

timing, magnitude, and regional patterns of climate change and the extent to which mankind and

nature can adapt to any changes. It is clear, however, that changes will not be easily reversed for

many decades or even centuries because of the long atmospheric lifetimes of the GHGs and the

inertia of the climate system.

ES.2 WHAT IS THE UNITED STATES DOING ABOUT CLIMATE CHANGE?

In 1992, world leaders and citizens from some 200 countries met in Rio de Janeiro,

Brazil to confront global ecological concerns. At this "Earth Summit," 154 nations, including the

United States, signed the Framework Convention on Climate Change, an international agreement

to address the danger of global climate change. The objective of the Convention is to stabilize

GHG concentrations in the atmosphere at a level, and over a time frame, that will minimize manmade climate disruptions.

By signing the Convention, countries make a voluntary commitment to reduce GHGs or

take other actions to stabilize emissions of GHGs at 1990 levels. All parties to the Convention

are also required to develop, and periodically update, national inventories of their GHG

emissions. The US ratified the Convention in October 1992. One year later, President Clinton

issued the US Climate Change Action Plan (CCAP), which called for cost-effective domestic

 4

Ibid., pp. 3-5.

5

Ibid., pp. 6, 29-30, 156, and 371-372.

6

Ibid., pp. 26, 29-30, 156, and 171.
ES-3

actions and voluntary cooperation with states, local governments, industry, and citizens to reduce

GHG emissions.

Countries that ratified the Framework Convention on Climate Change met in Kyoto,

Japan in December 1997, where they agreed to reduce global greenhouse gas emissions and set

binding targets for developed nations. (For example, the emissions target for the US would be 7

percent below 1990 levels.) As of the publication of this report, the Kyoto agreement remains to

be signed by the President and ratified by the US Senate; meanwhile, EPA continues to promote

voluntary measures to reduce GHG emissions begun under the CCAP. The countries that ratified

the Framework Convention will meet again in Buenos Aires in November, 1998, where the US

will attempt to secure meaningful participation by developing countries.

The CCAP outlines over 50 voluntary initiatives to reduce GHG emissions in the US.

One of the initiatives calls for accelerated source reduction and recycling of municipal solid

waste through combined efforts by EPA, the Department of Energy, and the Department of

Agriculture. Another waste related initiative is the Landfill Methane Outreach Program, which

aims to reduce landfill methane emissions by facilitating the development of landfill gas

utilization projects.7

ES.3 WHAT IS THE RELATIONSHIP OF MUNICIPAL SOLID WASTE TO

GREENHOUSE GAS EMISSIONS?

What does municipal solid waste have to do with rising sea levels, higher temperatures,

and GHG emissions? For many wastes, the materials that we dispose represent what is left over

after a long series of steps including: (1) extraction and processing of raw materials; (2)

manufacture of products; (3) transportation of materials and products to markets; (4) use by

consumers; and (5) waste management.

At virtually every step along this "life cycle," the potential exists for GHG impacts.

Waste management affects GHGs by affecting one or more of the following:

 (1) Energy consumption (specifically, combustion of fossil fuels) associated with

making, transporting, using, and disposing the product or material that becomes

a waste.

(2) Non-energy-related manufacturing emissions, such as the carbon dioxide

released when limestone is converted to lime (which is needed for aluminum and

steel manufacturing).

(3) Methane emissions from landfills where the waste is disposed.

(4) Carbon sequestration, which refers to natural or man-made processes that

remove carbon from the atmosphere and store it for long time periods or

permanently. A store of sequestered carbon (e.g., a forest or coal deposit) is

known as a carbon sink.

 7 The Landfill Methane Outreach Program is a voluntary partnership between the EPA, state

agencies, landfill gas-to-energy developers and energy users. The program has an Internet home page

(http://www.epa.gov/landfill.html), and can be reached via a toll-free hotline number (1-800-782-7937).
ES-4

The first three mechanisms add GHGs to the atmosphere and contribute to global

warming. The fourth - carbon sequestration - reduces GHG concentrations by removing carbon

dioxide from the atmosphere. Forests are one mechanism for sequestering carbon; if more wood

is grown than is removed (through harvest or decay), the amount of carbon stored in trees

increases, and thus carbon is sequestered.

Different wastes and waste management options have different implications for energy

consumption, methane emissions, and carbon sequestration. Source reduction and recycling of

paper products, for example, reduce energy consumption, decrease combustion and landfill

emissions, and increase forest carbon sequestration.

ES.4 WHY EPA PREPARED THIS REPORT AND HOW IT WILL BE USED

Recognizing the potential for source reduction and recycling of municipal solid waste to

reduce GHG emissions, EPA included a source reduction and recycling initiative in the original

1994 CCAP. At that time, EPA estimated that its portion of the source reduction and recycling

initiative could reduce annual GHG emissions by roughly 5.6 million metric tons of carbon

equivalent (MTCE) by the year 2000, or about 5 percent of the overall goal of the Action Plan.

To make these projections, EPA used limited data on energy consumption and forest carbon

sequestration to estimate how a 5 percent increase in both source reduction and recycling would

affect GHG emissions in 2000.

It was clear then that a rigorous analysis would be needed to more accurately gauge the

total GHG emission reductions achievable through source reduction and recycling. Moreover, it

was clear that all of the options for managing MSW should be considered. By addressing a

broader set of MSW management options, a more comprehensive picture of the GHG benefits of

voluntary actions in the waste sector could be determined and the relative GHG impacts of

various waste management approaches could be assessed. To this end, the Office of Policy and

the Office of Solid Waste launched a major research effort.

This research effort has been guided by contributions from many reviewers participating

in three review cycles (as described in Background Document C). The first draft report was

reviewed in 1995 by 20 EPA analysts from four offices (Air and Radiation; Policy; Research and

Development; and Solid Waste) as well as analysts from the US Department of Energy and US

Department of Agriculture, Forest Service. Comments resulting from these reviews were

incorporated into a second draft of the report, completed in May 1996.

The 1996 draft was distributed to four researchers with academic and consulting

backgrounds for a more intensive, external peer review. Based on their comments, another draft

of the report was completed in March of 1997.

In March, 1997, EPA published the draft research in a report entitled Greenhouse Gas

Emissions from Municipal Waste Management: Draft Working Paper (EPA530-R-97-010). As

described in an accompanying Federal Register notice, public comment was solicited on the draft

working paper.

This final report reflects comments from 23 individuals, representing trade associations,

universities, industry, state offices, EPA offices, and other entities. Among the groups that

provided detailed comments were:
ES-5

• The American Forest and Paper Association,

• The American Plastics Council,

• The Steel Recycling Institute,

• The Integrated Waste Services Association,

• The Minnesota Office of Environmental Assistance, and

• The Missouri Department of Natural Resources.

Each comment on the draft working paper is specifically discussed in a comment response

document, which is available in the public docket (F-97-GGEA-FFFFF). For each comment

received, the comment response document summarizes both the comment and EPA's response.

Among the changes made as a result of this review, EPA

• added two materials to the analysis – mixed paper and glass,

• revised system efficiencies for waste combustors, and provided a separate

characterization of refuse-derived fuel (RDF) as a category of combustion,

• based GHG reductions from displaced electricity on GHGs from fossil-fuel-fired

generation, rather than from the national average mix of fuels.

Each of these changes is discussed in more detail later in this report. In addition, this report

updates many of the inputs to the calculations (such as the global warming potential for various

greenhouse gases), and uses more recent information on waste composition and recycling rates.

The primary application of the GHG emission factors in this report is to support climate

change mitigation accounting for waste management practices. Organizations interested in

quantifying and voluntarily reporting GHG emission reductions associated with waste

management practices may use these emission factors for that purpose. In conjunction with the

Department of Energy, EPA has used these emission factors to develop guidance for voluntary

reporting of GHG reductions, as authorized by Congress in Section 1605 (b) of the Energy Policy

Act of 1992. EPA also plans to use these emission factors to evaluate its progress in reducing US

GHG emissions – by promoting source reduction and recycling through voluntary programs such

as WasteWi$e and Pay-as-You-Throw (PAYT) – as part of the US CCAP. The methodology

presented in this report may also assist other countries involved in developing GHG emissions

estimates for their solid waste streams.

8

ES.5 HOW WE ANALYZED THE IMPACT OF MUNICIPAL SOLID WASTE ON

GREENHOUSE GAS EMISSIONS

To measure the GHG impacts of municipal solid waste (MSW), one must first decide

which wastes to analyze. We surveyed the universe of materials and products found in MSW and

determined which were most likely to have the greatest impact on GHGs. These determinations

were based on (1) the quantity generated, (2) differences in energy use for manufacturing a

product from virgin versus recycled inputs, and (3) the potential contribution of materials to

methane generation in landfills. By this process, we limited the analysis to the following 11

items:

 8

 Note that waste composition and product life cycles vary significantly among countries. This

report may assist other countries by providing a methodologic framework and benchmark data for

developing GHG emission estimates for their solid waste streams.
ES-6

• newspaper,

• office paper,

• corrugated cardboard,

• aluminum cans,

• steel cans,

• glass containers,

• HDPE (high density polyethylene) plastic,

• LDPE (low density polyethylene) plastic,

• PET (polyethylene terephthalate) plastic,

• food scraps, and

• yard trimmings.

The foregoing materials constitute 55

percent, by weight, of municipal solid waste, as

shown in Exhibit ES-1.9 We also examined the

GHG implications of managing mixed MSW,

mixed recyclables, and mixed paper.

• Mixed MSW is comprised of the

waste material typically discarded by

households and collected by curbside

collection vehicles; it does not

include white goods or industrial

waste. This report analyzes mixed

MSW on an "as disposed" (rather

than "as generated") basis.

• Mixed recyclables are materials that

are typically recycled. As used in this

report, the term includes the items

listed in Exhibit ES-1, except food

scraps and yard trimmings. The

emission factors reported for mixed

recyclables represent the average

GHG emissions for these materials,

weighted by the tonnages at which

they are recycled.

• Mixed paper is recycled in large quantities, and is an important class of scrap

material in many recycling programs. However, it is difficult to present a single

definition of mixed paper because each mill using recovered paper defines its own

supply which varies with the availability and price of different grades of paper.

Therefore, for purposes of this report, we identified three different definitions for

 9 Note that these data are based on national averages. The composition of solid waste varies locally

and regionally; local or state-level data should be used when available. In recognition of the variability in

local conditions, EPA is developing the WAste Reduction Model (WARM), which may be used to estimate

the GHG emissions of MSW management actions on a local and state level. For more information on the

WARM model, contact the RCRA Hotline at 1-800-424-9346.

Exhibit ES-1

Percentage of 1996 US Generation of

MSW for Materials in This Report

Material

Percentage of

MSW Generation

(by Weight)

Newspaper 5.9%

Office paper 3.2%

Corrugated cardboard 13.8%

Aluminum cans 0.8%

Steel cans 1.3%

Glass containers 5.3%

HDPE plastic* 0.6%

LDPE plastic* 0.01%

PET plastic* 0.5%

Food scraps 10.4%

Yard trimmings 13.4%

TOTAL 55%

Source: Franklin Associates, Ltd.,

Characterization of Municipal Solid Waste in the

United States: 1997 Update. EPA 530-R-98-007

(May 1998)

* Based on blow-molded containers.
ES-7

mixed paper according to their dominant source – broad (general sources), office, and

residential.

Next, we developed a streamlined life cycle inventory for each of the selected materials.

Our analysis is streamlined in the sense that it examines GHG emissions only, and is not a more

comprehensive environmental analysis of all emissions from municipal solid waste management

options.10

We focused on those aspects of the life cycle that have the potential to emit GHGs as

materials change from their raw states, to products, to waste. Exhibit ES-2 shows the steps in the

life cycle at which GHGs are emitted, carbon sequestration is affected, and utility energy is

displaced. As shown, we examined the potential for these effects at the following points in a

product's life cycle:

• raw material acquisition (fossil fuel energy and other emissions, and change in forest

carbon sequestration);

• manufacturing (fossil fuel energy emissions); and

• waste management (carbon dioxide emissions associated with combustion and

methane emissions from landfills; these emissions are offset to some degree by

avoided utility fossil fuel use and carbon sequestration in landfills).

At each of these points, we also considered transportation-related energy emissions.

GHG emissions associated with electricity used in the raw materials acquisition and

manufacturing steps are estimated based on the current mix of energy sources, including fossil

fuels, hydropower, and nuclear power. However, estimates of GHG emission reductions

attributable to utility emissions avoided from waste management practices are based solely on the

reduction of fossil fuel use.11

We did not analyze the GHG emissions associated with consumer use of products

because energy use for the selected materials is small (or zero) at this point in the life cycle. In

addition, the energy consumed during use would be approximately the same whether the product

was made from virgin or recycled inputs.

To apply the GHG estimates developed in this report, one must compare a baseline

scenario with an alternative scenario, on a life-cycle basis. For example, one could compare a

baseline scenario, where 10 tons of office paper is manufactured, used, and landfilled, to an

alternative scenario, where 10 tons is manufactured, used, and recycled.

 10 EPA's Office of Research and Development (ORD) is performing a more extensive application

of life cycle assessment for various waste management options for MSW. ORD's analysis will inventory a

broader set of emissions (air, water, and waste) associated with these options. For more information on this

effort, go to their project website at http://www.epa.gov/docs/crb/apb/apb.htm.

11 We adopted this approach based on suggestions from several commenters who argued that fossil

fuels should be regarded as the marginal fuel displaced by waste-to-energy and landfill gas recovery

systems.
ES-8

In calculating emissions for the scenarios, two different reference points can be used:

• With a "raw material extraction" reference point (i.e., cradle-to-grave perspective),

one can start at the point of raw material acquisition as the "zero point" for

emissions, and add all emissions (and deduct sinks) from that point on through the

life cycle.

• With a "waste generation" reference point (solid waste manager's perspective), one

can begin accounting for GHG emissions at the point of waste generation. All

subsequent emissions and sinks from waste management practices are then

accounted for. Changes in emissions and sinks from raw material acquisition and

manufacturing processes are captured to the extent that certain waste management

practices (i.e., source reduction and recycling) impact these processes.

When developing an emission factor to account for GHG emissions from a waste management

activity, the key question to ask is "What is the baseline management practice?" Because it is the

difference in emissions between the baseline and alternate scenarios that is meaningful, using

raw material extraction or waste generation reference points yields the same results. The March

1997 Draft Working Paper used the raw material extraction reference point to display GHG

emissions because it is most consistent with standard life cycle inventory accounting techniques.

Several commenters pointed out that solid waste decision-makers tend to view raw materials

(captures process and transportation energy

associated with recycling)

CH4 emissions

-Uncontrolled

-Flared or recovered for energy (converted to CO2)

-Credit for avoided fossil fuel use

Credit for Carbon in long-term storage. 1

Note that source reduction affects all stages in the life cycle.

2

All life cycle stages analyzed include transportation energy-related emissions.
ES-9

acquisition and manufacturing as beyond their control, and suggested that a waste generation

GHG accounting approach would provide more clarity for evaluating waste management options.

Thus, this report uses the waste generation approach, and defines a standard raw material

acquisition and manufacturing step for each material as consisting of average GHG emissions

based on the current mix of virgin and recycled inputs. This standard raw material acquisition

and manufacturing step is used to estimate the upstream impacts of source reduction and

recycling.

Exhibit ES-3 shows how the GHG sources and sinks are affected by each waste

management strategy using the waste generation reference point. For example, the top row of the

exhibit shows that source reduction12 (1) reduces GHG emissions from raw materials acquisition

and manufacturing; (2) results in an increase in forest carbon sequestration; and (3) does not

result in GHG emissions from waste management. The sum of emissions (and sinks) across all

steps in the life cycle represents net emissions.

 12 In this analysis, the source reduction techniques we analyze involve using less of a given

product without using more of some other product - e.g., making aluminum cans with less aluminum

("lightweighting"); double-sided rather than single-sided photocopying; or reuse of a product. We did not

consider source reduction of one product that would be associated with substitution by another product -

e.g., substituting plastic boxes for corrugated paper boxes. Nor did we estimate the potential for source

reduction of chemical fertilizers and pesticides with increased production and use of compost. For a

discussion of source reduction with material substitution, please see section 4.3.
ES-10

Exhibit ES-3

Components of Net Emissions for Various Municipal Solid Waste Management Strategies

Greenhouse Gas Sources and Sinks

Municipal

 Solid Waste

Management

Strategy

Raw Materials Acquisition and

Manufacturing Change in Forest or Soil

Carbon Storage

Waste Management

Source Reduction Decrease in GHG emissions,

relative to the baseline of

manufacturing

Increase in forest carbon

storage

No emissions/sinks

Recycling Decrease in GHG emissions due to

lower energy requirements

(compared to manufacture from

virgin inputs) and avoided process

non-energy GHGs

Increase in forest carbon

storage

Process and transportation

emissions associated with

recycling are counted in the

manufacturing stage

Composting (food

scraps, yard

trimmings)

No emissions/sinks Increase in soil carbon

storage

Compost machinery emissions

and transportation emissions

Combustion No change No change Nonbiogenic CO2, N2O

emissions, avoided utility

emissions, and transportation

emissions

Landfilling No change No change Methane emissions, long-term

carbon storage, avoided utility

emissions, and transportation

emissions

ES.6 RESULTS OF THE ANALYSIS

Management of municipal solid waste presents many opportunities for GHG emission

reductions. Source reduction and recycling can reduce GHG emissions at the manufacturing

stage, increase forest carbon storage, and avoid landfill methane emissions. When waste is

combusted, energy recovery displaces fossil fuel-generated electricity from utilities (thus

reducing GHG emissions from the utility sector), and landfill methane emissions are avoided.

Landfill methane emissions can be reduced by using gas recovery systems and by diverting

organic materials from the landfill.

 In order to support a broad portfolio of climate change mitigation activities covering a

broad scope of greenhouse gases, many different emission estimation methodologies will need to

be employed. The primary result of this research is the development of material-specific GHG

emission factors which can be used to account for the climate change benefits of waste

management practices. A spreadsheet accounting tool, the Waste Reduction Model (WARM), is

being developed to allow for customizing of emission factors based on key variables which may

better reflect local conditions.

Exhibit ES-4 presents the GHG impacts of source reduction, recycling, composting,

combustion, and landfilling, on a per-ton managed basis, for the individual materials, mixed

waste, and mixed recyclables, using the waste generation reference point. For comparison,

Exhibit ES-5 shows the same results, using the raw material extraction reference point. In these
ES-11

tables, emissions for one ton of a given material are presented across different management

options.13 The life cycle GHG emissions for each of the first four waste management strategies -

source reduction, recycling, composting, and combustion - are compared to the GHG emissions

from landfilling in Exhibit ES-6. This exhibit shows the GHG values for each of the first four

management strategies, minus the GHG values for landfilling. With this exhibit, one may

compare the GHG emissions of changing management of one ton of each material from

landfilling (often viewed as the baseline waste management strategy) to one of the other waste

management options.

All values shown in Exhibit ES-4 through ES-6 are for national average conditions (e.g.,

average fuel mix for raw material acquisition and manufacturing using recycled inputs; typical

efficiency of a mass burn combustion unit; national average landfill gas collection rates). GHG

emissions are sensitive to some factors that vary on a local basis, and thus site-specific emissions

will differ from those summarized here.

Following is a discussion of the principal GHG emissions and sinks for each waste

management practice and effect they have on the emission factors:

• Source reduction, generally speaking, represents an opportunity to reduce GHG

emissions in a significant way.14 The reduction in energy-related CO2 emissions from

the raw material acquisition and manufacturing process, and the absence of

emissions from waste management, combine to reduce GHG emissions more than all

other options.

• Recycling generally has the second lowest GHG emissions. For most materials,

recycling reduces energy-related CO2 emissions in the manufacturing process

(although not as dramatically as source reduction) and avoids emissions from waste

management. Paper recycling increase storage of forest carbon.

 13 Note that the difference between any two values for a given material in Exhibit ES-4 (i.e.,

emissions for the same material in two waste management options) is the same as the difference between the

two corresponding values in Exhibit ES-5. 14 As noted above, the only source reduction strategy analyzed in this study is lightweighting.

Consequently, the results shown here do not directly apply to material substitution.
ES-12

Exhibit ES-4

Net GHG Emissions from Source Reduction and MSW Management Options

Emissions Counted from a Waste Generation Reference Point (MTCE/Ton)1

Source Recycling Composting3 Combustion4 Landfil

Material Reduction2

Newspaper -0.91 -0.86 NA -0.22 Office Paper -1.03 -0.82 NA -0.19 Corrugated Cardboard -0.78 -0.70 NA -0.19 Mixed Paper

 Broad Definition NA -0.67 NA -0.19  Residential Definition NA -0.67 NA -0.19  Office Paper Definition NA -0.84 NA -0.18 

Aluminum Cans -2.98 -3.88 NA 0.03 Steel Cans -0.84 -0.57 NA -0.48 Glass -0.14 -0.08 NA 0.02 HDPE -0.61 -0.37 NA 0.21 LDPE -0.89 -0.49 NA 0.21 PET -0.98 -0.62 NA 0.24 Food Scraps NA NA 0.00 -0.05 Yard Trimmings NA NA 0.00 -0.07 Mixed MSW as Disposed NA NA NA -0.04 Mixed Recyclables NA -0.76 NA -0.18 

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1MTCE/ton: Metric tons of carbon equivalent per short ton of material. Material tonnages are on an as-managed (wet weight2Source reduction assumes initial production using the current mix of virgin and recycled inputs.3There is considerable uncertainty in our estimate of net GHG emissions from composting; the values of zero are plausible v

based on assumptions and a bounding analysis. 

4Values are for mass burn facilities with national average rate of ferrous recovery.5Values reflect projected national average methane recovery in year 2000.
ES-13

Exhibit ES-5

Net GHG Emissions from Source Reduction and MSW Management Options

Emissions Counted from a Raw Materials Extraction Reference Point (MTCE/Ton)

Source

Material Reduction1 Recycling2 Composting2 Combustion2 Landf

Newspaper -0.43 -0.38 NA 0.26 Office Paper -0.50 -0.30 NA 0.34 Corrugated Cardboard -0.38 -0.30 NA 0.21 Mixed Paper Broad Definition NA -0.21 NA 0.26  Residential Definition NA -0.22 NA 0.26  Office Paper Definition NA -0.33 NA 0.33 Aluminum Cans 0.00 -0.90 NA 3.01 Steel Cans 0.00 0.26 NA 0.35 Glass 0.00 0.06 NA 0.17 HDPE 0.00 0.24 NA 0.81 LDPE 0.00 0.40 NA 1.10 PET 0.00 0.36 NA 1.21 Food Waste NA NA 0.00 -0.05 Yard Waste NA NA 0.00 -0.07 Mixed MSW as Disposed NA NA NA -0.04 Mixed Recyclables NA -0.26 NA 0.33 

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1Source reduction assumes initial production using the current mix of virgin and recycled inputs.2Includes emissions from the initial production of the material being managed, except for food waste, yard waste, and mixe
ES-14

Exhibit ES-6

Greenhouse Gas Emissions of MSW Management Options Compared to Landfilling1

(MTCE/Ton)

Source Reduction2 Recycling Net Emissions Composting3 Net C Combus

Net Emissions Minus Landfilling Minus Landfilling Min

Material Minus Landfilling Net Emissions Net Emissions Net Emissions N

Newspaper -0.68 -0.63 NA Office Paper -1.56 -1.35 NA Corrugated Cardboard -0.82 -0.74 NA Mixed Paper

 Broad Definition NA -0.73 NA  Residential Definition NA -0.69 NA  Office Paper Definition NA -0.95 NA 

Aluminum Cans -3.00 -3.89 NA Steel Cans -0.85 -0.58 NA Glass -0.15 -0.09 NA HDPE -0.62 -0.38 NA LDPE -0.90 -0.51 NA PET -0.99 -0.63 NA Food Scraps NA NA -0.15 Yard Trimmings NA NA 0.11 Mixed MSW as Disposed NA NA NA Mixed Recyclables NA -0.79 NA 

Note that totals may not add due to rounding and more digits may be displayed than are significant.

NA: Not applicable, or in the case of composting of paper, not analyzed.

1Values for landfilling reflect projected national average methane recovery in year 2000.2Source reduction assumes initial production using the current mix of virgin and recycled inputs.3Calculation is based on assuming zero net emissions for composting.4Values are for mass burn facilities with national average rate of ferrous recovery.
ES-15

• Composting is a management option for food scraps and yard trimmings. The net

GHG emissions from composting are lower than landfilling for food scraps

(composting avoids methane emissions), and higher than landfilling for yard

trimmings (landfilling is credited with the carbon storage that results from failure of

certain yard trimmings to degrade fully in landfills). Overall, given the uncertainty in

the analysis, the emission factors for composting or combusting these materials are

similar.

• The net GHG emissions from combustion and landfilling are similar for mixed

MSW. Because, in practice, combustors and landfills manage a mixed waste stream,

net emissions are determined more by technology factors (e.g., landfill gas collection

system efficiency, combustion energy conversion efficiency) than by material

specificity. Material-specific emissions for landfills and combustors provide a basis

for comparing these options with source reduction, recycling, and composting.

The ordering of combustion, landfilling, and composting is affected by (1) the GHG inventory

accounting methods, which do not count CO2 emissions from sustainable biogenic sources,15 but

do count emissions from sources such as plastics, and (2) a series of assumptions on

sequestration, future use of methane recovery systems, landfill gas recovery system efficiency,

ferrous metals recovery, and avoided utility fossil fuels. On a site-specific basis, the ordering of

results between a combustor and a landfill could be different from the ordering provided here,

which is based on national average results.

We conducted sensitivity analyses to examine the GHG emissions from landfilling under

varying assumptions about (1) the percentage of landfilled waste sent to landfills with gas

recovery and (2) methane oxidation rate and gas collection system efficiency. The sensitivity

analyses demonstrate that the results for landfills are very sensitive to these factors, which are

site-specific.16 Thus, using a national average value when making generalizations about

emissions from landfills masks some of the variability that exists from site to site.

The scope of this report is limited to developing emission factors that can be used to

evaluate GHG implications of solid waste decisions. We do not analyze policy options in this

report. Nevertheless, the differences in emission factors across various waste management

options are sufficiently large as to imply that GHG mitigation policies in the waste sector can

make a significant contribution to US emission reductions. A number of examples, using the

emission factors in this report, bear this out.

• At the firm level, targeted recycling programs can reduce GHGs. For example, a

commercial facility that shifts from a baseline practice of landfilling (in a landfill

with no gas collection system) to recycling 50 tons office paper and 2 tons of

aluminum cans can reduce GHG emissions by over 100 MTCE.

• At the community level, a city of 100,000 with average waste generation (4.3

lb/day per capita) and recycling (27 percent), and baseline disposal in a landfill

 15 Sustainable biogenic sources include paper and wood products from sustainably managed

forests; when these materials are burned or aerobically decomposed to CO2

, the CO2 emissions are not

counted. Our approach to measuring GHG emissions from biogenic sources is described in detail in

Chapter 1.

16 For details on the sensitivity analyses, see section 7.4 and Exhibits 7-7 and 7-8.
ES-16

with no gas collection system, could increase the recycling rate to 40 percent – for

example, by implementing a pay-as-you-throw program – and reduce emissions by

about 10,000 MTCE per year. (Note that further growth in recycling would be

possible; some communities are already exceeding recycling rates of 50 percent).

• A city of 1 million, disposing of 650,000 tons per year in a landfill without gas

collection, could reduce GHG emissions by 92,000 MTCE per year by managing

waste in a mass burn combustor unit.

• A town of 50,000 landfilling 30,000 tons per year could install a landfill gas

recovery system and reduce emissions by about 6,600 MTCE per year.

• At the national level, if the US attains the goal of a 35 percent recycling rate by

2005, emissions will be reduced by over 9 million MTCE per year compared to a

baseline where we maintain the current 27 percent recycling rate and use the

"national average" landfill for disposal.

ES.7 LIMITATIONS OF THE ANALYSIS

When conducting this analysis, we used a number of analytical approaches and

numerous data sources, each with its own limitations. In addition, we made and applied

assumptions throughout the analysis. Although these limitations would be troublesome if used in

the context of a regulatory framework, we believe that the results are sufficiently accurate to

support their use in voluntary programs. Some of the major limitations follow:

• The manufacturing GHG analysis is based on estimated industry averages for

energy usage, and in some cases the estimates are based on limited data.17 In

addition, we used values for the average GHG emissions per ton of material

produced, not the marginal emission rates per incremental ton produced. In some

cases, the marginal emission rates may be significantly different.

• The forest carbon sequestration analysis deals with a very complicated set of

interrelated ecological and economic processes. Although the models used

represent the state-of-the-art in forest resource planning, their geographic scope

is limited – because of the global market for forest products, the actual effects of

paper recycling would occur not only in the US but in Canada and other

countries. Other important limitations include: (1) the estimate does not include

changes in carbon storage in forest soils and forest floors, (2) the model assumes

that no forested lands will be converted to non-forest uses as a result of increased

paper recycling, and (3) we use a point estimate for forest carbon sequestration,

whereas the system of models predicts changing net sequestration over time.

• The composting analysis was limited by the lack of data on methane generation

and carbon sequestration resulting from composting; we relied on a theoretical

approach to estimate the values.

• The combustion analysis uses national average values for several parameters;

variability from site to site is not reflected in our estimate.

 17 When EPA published this report as a draft working paper, the Agency specifically requested that

commenters provide data on raw material acquisition and manufacturing. Although several commenters

agreed that updated information would be important, none provided such data.
ES-17

• The landfill analysis (1) incorporates considerable uncertainty on methane

generation and carbon sequestration, due to limited data availability, and (2) uses

as a baseline landfill methane recovery levels projected for the year 2000.

Finally, through most of the report we express analytical inputs and outputs as point

estimates. We recognize that a rigorous treatment of uncertainty and variability would be useful,

but in most cases the information needed to treat these in statistical terms is not available. The

report includes some sensitivity analyses to illustrate the importance of selected parameters, and

expresses ranges for a few other factors such as GHG emissions from manufacturing. We

welcome readers to provide better information where it is available; perhaps with additional

information, future versions of this report will be able to shed more light on uncertainty and

variability. Meanwhile, we caution that the emission factors reported here should be evaluated

and applied with an appreciation for the limitations in the data and methods, as described at the

end of each chapter.
1

1. METHODOLOGY

1.1 INTRODUCTION

This chapter provides an overview of the methodology we used to calculate the greenhouse gas

(GHG) emissions associated with various management strategies for municipal solid waste (MSW). The

chapter begins with a brief discussion of the life cycle framework used for the analysis. Next, it explains

how we selected the ten materials that were analyzed. We then describe the specific GHG emissions and

emission offsets considered in calculating the net emissions associated with particular waste management

options. Finally, the chapter discusses the life cycle stages that we studied to identify the GHG impacts

of MSW management options. Succeeding chapters will describe how we analyzed each step in the life

cycle.

1.2 THE OVERALL FRAMEWORK: A STREAMLINED LIFE CYCLE INVENTORY

Early in our analysis of the GHG benefits of specific waste management practices, it became clear

that there are opportunities to reduce GHG emissions from all waste management options, depending on

the particular circumstances. Although source reduction and recycling are often the most advantageous

waste management practices from a GHG perspective, it became clear that a material-specific

comparison of all available waste management options would clarify where the greatest GHG benefits

could be obtained for particular materials in MSW. This type of analysis is also intended to help

policymakers identify the best options for GHG reductions. We determined that a streamlined application

of life cycle assessment would be the best way to conduct such a comparative analysis.

A full life cycle assessment (LCA) is an analytical framework for understanding the material

inputs, energy inputs, and environmental releases associated with manufacturing, using, and disposing a

given material. A full LCA generally consists of four parts: (1) goal definition and scoping; (2) an

inventory of the materials and energy used in all stages in the life of a product or process, and an

inventory of environmental releases throughout the product lifecycle; (3) an impact assessment that

examines potential and actual human health effects related to the use of resources and environmental

releases; and (4) an assessment of the change that is needed to bring about environmental improvements

in the product or processes.

A full life cycle assessment is beyond the scope of this analysis. Rather, this report is a

streamlined application of a life cycle assessment that is limited to an inventory of the emissions and

other environmental impacts related to global warming; we did not assess air, water, or environmental

impacts that did not have a direct bearing on climate change. Moreover, we did not attempt, as part of

this analysis, to assess human health impacts or environmental improvements needed.1

 1

 EPA's Office of Research and Development (ORD) is performing a more extensive application of life

cycle assessment for various waste management options for MSW. ORD's analysis will inventory a broader set of

emissions (air, water, and waste) associated with these options. For more information on this effort, go to their

project website at http://www.epa.gov/docs/crb/apb/apb.htm.
2

1.3 THE REVIEW PROCESS

Prior drafts of this report were reviewed in three peer review cycles, the details of which

are provided in Background Document C. 2 The 1995 draft report was reviewed by 20 EPA analysts from

four offices (Air and Radiation; Policy, Planning and Evaluation; Research and Development; and Solid

Waste). In addition, the 1995 draft was reviewed by four analysts from the Department of Energy (DOE),

Argonne National Laboratory, and DOE’s National Renewable Energy Laboratory. Comments resulting

from these reviews were incorporated into a second draft of the report, completed in May of 1996.

The 1996 draft was distributed to four researchers with academic and consulting backgrounds for

a more intensive, external peer review. None of the researchers chosen was involved in the preparation of

the report. Based on the comments received from these reviewers, another draft of the report was

completed in March of 1997.

In March, 1997, EPA published the draft research in a report entitled Greenhouse Gas Emissions

from Municipal Waste Management: Draft Working Paper (EPA530-R-97-010). As described in an

accompanying Federal Register notice, public comment was solicited on the draft working paper.

Twenty-three individuals, representing trade associations, universities, industry, state offices, EPA

offices, and other entities provided comments. The most extensive comments were made by

• American Forest and Paper Association,

• American Plastics Council,

• Integrated Waste Services Association,

• Steel Recycling Institute,

• Minnesota Office of Environmental Assistance, and

• Missouri Department of Natural Resources.

Each comment pertaining to the 1997 draft, and an explanation of how the comment was taken into

account in this report, is specifically addressed in a comment response document (Background Document

D).

Among the changes made as a result of this review, EPA

• added two materials to the analysis—mixed paper and glass,

• revised system efficiencies for waste combustors, and provided a separate

characterization of refuse-derived fuel (RDF) as a category of combustion,

• based GHG reductions from displaced electricity on GHGs from fossil-fuel-fired

generation, rather than from the national average mix of fuels, and

• added a “waste generation” reference point for GHG accounting, where before only a

“raw material extraction” reference point was provided.

In addition, the revised working paper updates many of the inputs to the calculations (such as the global

warming potential for various greenhouse gases), and uses more recent information on waste composition

and recycling rates.

 2

 All background documents and supporting memoranda cited in this report are provided in the docket at the

Resource Conservation and Recovery Act (RCRA) Information Center.
3

1.4 MSW MATERIALS CONSIDERED IN THE STREAMLINED LIFE CYCLE

INVENTORY

Source reduction and recycling have been part of the President’s Climate Change Action Plan

since its inception. In 1993, we made initial rough estimates of the potential for source reduction and

recycling of MSW to reduce GHG emissions. However, it was clear that a more rigorous analysis would

be needed to determine the GHG emissions associated with source reduction and recycling and to

identify which materials in MSW were most likely to reduce GHG emissions if source reduced or

recycled.

Each material in MSW has different GHG impacts depending on how it is made and disposed. To

determine which materials in MSW had the greatest potential to reduce GHG emissions if source reduced

or recycled, we performed a screening analysis of 37 of the most common materials and products found

in MSW.3 The screening analysis compared: (1) the GHG emissions from manufacturing each of the 37

materials from virgin or recycled inputs (based on the process and transportation energy requirements,

and fuel mix for each material); and (2) the projected source reduction and recycling rates for each

material. The information on energy requirements, fuel mix, and recycling rates was estimated

independently by two groups with experience in MSW and life cycle assessment: Franklin Associates,

Ltd. and the Tellus Institute. The materials were ranked by their potential for GHG reductions. For each

material, we (1) averaged the two estimates for energy requirements and fuel mix, then (2) used those

averages, together with estimates of the GHG emissions per unit of fuel used, to estimate GHG

reductions per ton of material source reduced or recycled, and finally (3) used the estimated GHG

reductions per ton, together with the averaged estimates of the potential tonnage of source reduction and

recycling achievable for each material, to estimate the total GHG reduction potential for each material.4

While the screening analysis was general in nature and employed many assumptions, the

underlying data provided by Franklin Associates and the Tellus Institute pointed toward the same general

results. The energy and recycling data provided by both groups indicated that the same eight

manufactured materials had the greatest potential to reduce GHG emissions if they were source reduced

or recycled. We initially limited the life cycle assessment to these eight materials:

• newspaper,

• office paper,5

 3 Materials and products in the screening analysis included, in addition to the materials and products

covered in this report, the following: other paper materials (bags and sacks, other paper packaging, books, other

paperboard packaging, wrapping papers, paper plates and cups, folding cartons, other nonpackaging paper, and

tissue paper and towels), other plastic materials (plastic wraps, plastic bags and sacks, other plastic containers, and

other plastic packing), other metal materials (aluminum foil/closures, other steel packaging), and other miscellaneous

materials (miscellaneous durable goods, wood packaging, furniture and furnishings, carpet and rugs, and other

miscellaneous packaging).

4 Note that the comparative analysis among materials may vary for different units of measure. For example,

a comparison between two packaging materials based on the GHG impacts per thousand packages will differ from a

comparison based on the GHG impacts per ton of packaging material; the former comparison will account for the

different weights of different types of packages. However, we chose to compare materials on a per-ton basis because

this report’s analysis focuses on greenhouse gas impacts from waste management, and waste is typically measured in

tons.

5

 Office paper refers to the type of paper used in computer printers and photocopiers.
4

• corrugated cardboard,

• aluminum cans,

• steel cans,6 

• HDPE (high density polyethylene) plastic blow-molded containers,

• LDPE (low density polyethylene) plastic blow-molded containers, and

• PET (polyethylene terephthalate) plastic blow-molded containers.

We also examined the GHG implications of various management strategies for food scraps, yard

trimmings, mixed MSW, and mixed recyclables. Finally, in response to several public comments, we

later added mixed paper and glass containers to the analysis.

1.5 KEY INPUTS AND BASELINES FOR THE STREAMLINED LIFE CYCLE INVENTORY

Evaluating the GHG emissions of waste

management requires analysis of three factors:

1) GHG emissions throughout the life cycle of

the material (including the chosen disposal

option); 2) the extent to which carbon sinks are

affected by manufacturing and disposing the

material; and 3) the extent to which the

management option recovers energy that can be

used to replace electric utility energy, thus

reducing utility GHG emissions. In addition, to

provide a consistent basis for comparison, we

made several choices in our greenhouse gas

accounting framework in terms of timing and

levels of production. Each of these factors

warrants further discussion.

GHGs Emissions Relevant to Waste: The

most important GHGs for purposes of analyzing

MSW management options are carbon dioxide,

methane, nitrous oxide, and perfluorocarbons.

Of these, carbon dioxide (CO2) is by far the most

common GHG emitted in the US. Most carbon

dioxide emissions result from energy use,

particularly fossil fuel combustion. A great deal

of energy is consumed when a product is made

and then discarded. This energy is used in the

following stages: 1) extracting and processing

raw materials; 2) manufacturing products; 3) managing products at the end of their useful lives; and 4)

transporting materials and products between each stage of their life cycles. We estimated energy-related

GHG emissions at all of these stages, except for transportation of products to consumers (because GHG

emissions from transportation to consumers will vary little among the options considered). Much of this

report is devoted to explaining how we quantified the energy used - and the resulting carbon dioxide

emissions - at each stage in the life cycle of any given material in MSW. Energy consumed in connection

 6 Other steel materials may also be recycled, but we limited our analysis to steel cans from households.

Comparing GHGs

Carbon dioxide, methane, and nitrous oxide are

very different gases when it comes to their heat-trapping

potential. An international protocol has established carbon

dioxide as the reference gas for measurement of heattrapping potential (also known as global warming

potential or GWP). By definition, the GWP of one

kilogram (kg) of carbon dioxide is 1.

Methane has a GWP of 21. This means that one kg

of methane has the same heat-trapping potential as 21 kg

of CO2.

Nitrous oxide has a GWP of 310.

Perfluorocarbons are the most potent greenhouse gases

covered by this analysis; GWPs are 6,500 for CF4 and

9,200 for C2F6.

In this report, emissions of carbon dioxide,

methane, nitrous oxide, and perfluorocarbons have been

converted to their "carbon equivalents." Because CO2 is

12/44 carbon by weight, one metric ton of CO2 is equal to

12/44 or 0.27 metric tons of carbon equivalent (MTCE).

The MTCE value for one metric ton of each of the other

gases is determined by multiplying its GWP by a factor of

12/44. (All data provided here are from The

Intergovernmental Panel on Climate Change (IPCC),

Climate Change 1995: The Science of Climate Change,

1996, p. 121.)
5

with consumer use of products is not evaluated, because it is assumed that energy use for the selected

materials is small (or zero) at this point in the life cycle. In addition, the energy consumed during use

would be about the same whether the product was made from virgin or recycled inputs.

Methane (CH4), a more potent GHG, is produced when organic waste decomposes in an oxygenfree (anaerobic) environment, such as a landfill. Methane from landfills is the largest source of methane

in the US;7

 these emissions are addressed in Chapter 7. Methane is also emitted when natural gas is

released to the atmosphere during production of coal or oil, during production or use of natural gas, and

from agricultural activities.

Nitrous oxide (N2O) results from the use of commercial and organic fertilizers and fossil fuel

combustion, as well as other sources. For this analysis, we estimated nitrous oxide emissions from waste

combustion.

Perfluorocarbons (CF4 and C2F6) are emitted during the reduction of alumina to aluminum in the

primary smelting process. The source of fluorine for CF4 and C2F6 is the molten cryolite (Na3AlF6) in

which the reduction of alumina occurs. Perfluorocarbons are formed when the fluorine in cryolite reacts

with the carbon in the anode (a carbon mass of paste, coke briquettes, or prebaked carbon blocks), and in

the carbon lining that serves as the cathode. Although the quantities of perfluorocarbons emitted are

small, these gases are significant because of their high global warming potential.

Carbon Stocks and Carbon Sequestration Relevant to Waste: Carbon, like many other elements,

cycles throughout earth's air, water, land, and biota. A carbon stock (or sink) is a point in the carbon

cycle where carbon is stored. While the carbon is stored, it is not in the atmosphere contributing to the

"greenhouse effect" (i.e., the trapping of heat close to the earth's surface). Examples of carbon stocks are

forests, oceans, oil fields, and landfills.

"Carbon sequestration" is the opposite of GHG emissions. With carbon sequestration, carbon is

removed from the carbon cycle and added to a carbon stock. For example, when a forest removes carbon

from the atmosphere and converts it to wood at a faster pace than the trees are harvested (or decompose),

this is known as forest carbon sequestration. Likewise, if organic matter added to a landfill does not

decompose into methane or carbon dioxide, and enters into long-term storage, it is said to be

"sequestered."

The baseline against which changes in carbon stocks are measured is a projection by the US Forest

Service of forest growth, harvests, mortality, and removals under anticipated market conditions for forest

products. One of the assumptions on which the projections is based is that US forests will be harvested

on a sustainable basis (i.e., trees will be grown at a rate at least equal to the rate at which they are cut).8

Thus, we assume in the baseline that harvesting trees at current levels results in no diminution of the

forest carbon stock and no additional carbon dioxide in the atmosphere. On the other hand, forest carbon

sequestration increases as a result of source reduction or recycling of paper products because both source

 7

 US EPA, Draft Inventory of US Greenhouse Gas Emissions and Sinks: 1990-1996, April 1998.

8

 Assuming a sustainable harvest in the US is reasonable because from 1952 to 1992 US forest carbon

stocks steadily increased. In the early part of this period, the increases were mostly due to reversion of agricultural

land to forest land. More recently, improved forest management practices and the regeneration of previously cleared

forest areas have resulted in a net annual uptake (sequestration) of carbon. The steady increase in forest carbon

stocks implies sustainable harvests, and it is reasonable to assume that the trend of sustainable harvests will continue.
6

reduction and recycling cause annual tree harvests to drop below otherwise anticipated levels (resulting

in additional accumulation of carbon in forests). Consequently, source reduction and recycling "get

credit" for increasing the forest carbon stock, whereas other waste management options (composting,

combustion, and landfilling) do not.

Landfills are another means by which carbon is removed from the atmosphere. Landfill carbon

stocks increase over time because much of the organic matter placed in landfills does not decompose,

especially if the landfill is located in an arid area. However, not all carbon in landfills is counted in

determining the extent to which landfills are carbon stocks. For example, the analysis does not count

plastic in landfills toward carbon sequestration. Plastic in a landfill represents merely a transfer from one

carbon stock (the oil field containing the petroleum or natural gas from which the plastic was made) to

another carbon stock (the landfill); thus, there has been no change in the overall amount of carbon stored.

On the other hand, that portion of organic matter (such as yard trimmings) that does not decompose in a

landfill represents an addition to a carbon stock, because it would have largely decomposed into CO2 if

left to deteriorate on the ground.

While changes in fossil fuel carbon stocks (i.e., reductions in oil field stores that result from the

extraction and burning of oil resources) are not measured directly in this analysis, the reduction in fossil

fuel carbon stocks is indirectly captured by counting the CO2 emissions from fossil fuel combustion in

calculating GHG emissions.

Avoided Electric Utility GHG Emissions Relevant to Waste: When a waste is used to generate

electricity (either through waste combustion or recovery of methane from landfills), it displaces utility

fossil fuels that would otherwise be consumed. Fossil fuel combustion is the single largest source of

GHGs in the US. When waste is substituted for fossil fuel to generate electricity, the GHG emissions

from burning the waste are offset by the avoided electric utility GHG emissions.

Baseline Year: For most parts of the analysis, we selected as the baseline year the most recent year

for which data were available. However, for the landfill methane recovery rate, and system efficiency and

ferrous recovery rate at waste combustors, we used values projected for the year 2000. For paper

recovery, we made annual projections through 2010 that enabled us to develop an average value for the

period from 1996 through 2010.9

 In these cases, we developed future scenarios because some of the

underlying factors that affect GHG emissions are changing rapidly, and we are seeking to define

relationships (e.g., between tonnage of waste landfilled and methane emissions) that represent an average

over the next several years.

• In the case of landfill methane, there are three EPA programs that reduce methane

emissions: one that requires landfill gas recovery at large landfills; one that promotes

recovery of landfill methane on a voluntary basis at smaller landfills; and another that

promotes source reduction and recycling (which results in less methane-producing waste

being landfilled). In estimating the landfill methane emission reductions due to source

reduction and recycling, we needed to account for the planned increase in landfill methane

capture. Otherwise, EPA would count landfill methane emissions reductions twice: once for

capturing landfill methane, and once for avoiding methane production through source

reduction and recycling. Because the programs to regulate landfill gas and promote

 9

 The models we used simulated carbon sequestration through 2040, but we selected a value based on

average conditions through 2010.
7

voluntary methane recovery aim to become fully effective by 2000 (dramatically increasing

methane recovery), by using a baseline year of 2000 we avoided double counting.

• Although the current population of US municipal waste combustors includes a few small

facilities that do not recover energy, we assumed that these would be closed in the near

future. Thus, we represented all combustors as having energy recovery. We also used an

estimate provided by the combustion industry for anticipated levels of ferrous recovery.

• For paper recovery, earlier analyses had indicated that the marginal impact of increased

paper recovery on forest carbon sequestration changes over time; the impact also differs

depending on the initial paper recovery rate and how that rate changes over time. To

estimate the impact of increased paper recovery on forest carbon sequestration, we needed

to account for these influences. First, we developed a baseline projection for paper recovery

rates. We began with a projection, from the American Forest and Paper Association, that

paper recovery rates will continue to increase from about 35 percent in 1994 to 50 percent

by 2000. Then we developed a baseline scenario for paper recovery whose trajectory passes

through 50 percent in 2000, with continued modest increases in the following years.

Because we needed to estimate the effect of efforts (e.g., by EPA) to enhance recovery

beyond the baseline projected rates, we developed a plausible scenario for enhanced paper

recovery rates, and then compared the predicted forest carbon sequestration under the two

scenarios.10 (Our approach is fully described in chapter 3).

1.6 HOW THESE INPUTS ARE TALLIED AND COMPARED

Exhibit 1-1 shows the GHG sources and carbon sinks associated with the manufacture of various

materials, and the post-consumer management of these materials as wastes. As shown in the exhibit,

GHGs are emitted from: (1) the pre-consumer stages of raw materials acquisition and manufacturing; and

(2) the post-consumer stage of waste management. No GHG emissions are attributed to the consumer's

use of any product.

To calculate the net GHG implications of a waste management strategy for a given material, one must

first establish a baseline scenario and an alternative scenario. For example, one could compare a baseline

scenario, where 10 tons of office paper is manufactured, used, and landfilled, to an alternative scenario,

where 10 tons is manufactured, used, and recycled. Then, for each scenario, net GHG emissions are

estimated based on: (1) the GHG emissions associated with that material; and (2) any increases in carbon

stocks and/or displaced fossil fuel combustion that offset these emissions. The formula for net GHG

emissions is as follows:

Net GHG emissions = Gross GHG emissions - (increase in carbon stocks +

 avoided utility GHG emissions)

 10 Note that this estimate is necessary for analyzing the scenarios, however, it does not represent a plan of

action by EPA.
8

Exhibit 1-1

Comparing net GHG emissions for the two scenarios allows one to identify which has the lowest

net GHG emissions. For example, when a material is source reduced (i.e., some or all of it is not

produced), GHG emissions throughout the life cycle are avoided. In addition, when paper products are

source reduced, additional carbon may be sequestered in forests.

Similarly, when a material is recycled, the GHG emissions from making an equivalent amount of

material from virgin inputs are reduced. Generally, recycling reduces GHG emissions because, in most

cases, manufacturing a product from recycled inputs requires less fossil energy than making the product

from virgin inputs, and thus reduces energy-related GHG emissions. Another GHG issue in the case of

paper is that paper recycling results in additional carbon sequestration in forests.

If a waste is not source reduced or recycled, it may be either composted (if it is organic matter),

combusted, or landfilled. In any of these cases, there are GHG emissions associated with making the

material/product. These GHG emissions may be augmented by methane emissions from landfills (which

themselves may be offset to some degree by energy recovery at landfills or landfill carbon sequestration).

If the wastes are combusted, there may be an offset for avoided utility emissions.

(captures process and transportation energy

associated with recycling)

CH4 emissions

-Uncontrolled

-Flared or recovered for energy (converted to CO2)

-Credit for avoided fossil fuel use

Credit for Carbon in long-term storage. 1

Note that source reduction affects all stages in the life cycle.

2

All life cycle stages analyzed include transportation energy-related emissions.
9

In calculating emissions for the life cycle scenarios, two different reference points can be used:

• In a “raw material extraction” approach (i.e., cradle-to-grave perspective), one can start at the

point of raw material acquisition as the “zero point” for emissions, and add all emissions (and

deduct sinks) from that point on through the life cycle.

• In a “waste-generation” approach (solid waste manager’s perspective), one can begin

accounting for GHG emissions at the point of waste generation. All subsequent emissions and

sinks from waste management practices are then accounted for. Changes in emissions and

sinks from raw material acquisition and manufacturing processes are captured to the extent

that certain waste management practices (i.e., source reduction and recycling) impact these

processes.

Because it is the difference in emissions between the baseline and alternate scenarios that is

meaningful, using either of these reference points yields the same results. The March 1997 Draft

Working Paper used the cradle-to-grave method to display GHG emissions because it is most consistent

with standard life cycle inventory accounting techniques. Several commenters pointed out that solid

waste decision-makers tend to view raw materials acquisition and manufacturing as beyond their control,

and suggested that a waste generation GHG accounting approach would provide more clarity for

evaluating waste management options. Thus, this report uses the waste generation approach, and defines

the “standard” raw material acquisition and manufacturing step for each material as consisting of average

GHG emissions based on the current mix of virgin and recycled inputs.11

Exhibit 1-2 indicates how the GHG sources and sinks have been counted for each MSW

management strategy to estimate net GHG emissions using the post-consumer reference point. For

example, the top row of the exhibit shows that source reduction (1) reduces GHG emissions from raw

materials acquisition and manufacturing; (2) results in an increase in forest carbon sequestration; and (3)

does not result in GHG emissions from waste management. The sum of emissions (and sinks) across all

steps in the life cycle represents net emissions.

1.7 SUMMARY OF THE LIFE CYCLE STAGES

The following sections explain the life cycle diagram and components presented in Exhibits 1-1

and 1-2, and outline the GHG emissions and carbon sinks at each stage of the product life cycle. These

GHG emissions and carbon sinks are described in detail, and quantified for each material, in chapters 2

through 7.

 11 Changes in the mix of production (i.e., higher proportions of either virgin or recycled inputs) result in

incremental emissions (or reductions) with respect to this reference point.
10

Exhibit 1-2

Components of Net Emissions for Various Municipal Solid Waste Management Strategies

Municipal Greenhouse Gas Sources and Sinks

Solid Waste

Management

Strategy

Process and Transportation

GHGs from Raw Materials

Acquisition and Manufacturing

Change in Forest or Soil

Carbon Storage Waste Management GHGs

Source Reduction Decrease in GHG emissions,

relative to the baseline of

manufacturing

Increase in forest carbon

storage

No emissions/sinks

Recycling Decrease in GHG emissions due to

lower energy requirements

(compared to manufacture from

virgin inputs) and avoided process

non-energy GHGs

Increase in forest carbon

storage

Process and transportation

emissions are counted in the

manufacturing stage

Composting No emissions/sinks* No change Compost machinery

emissions and transportation

emissions

Combustion Baseline process and transportation

emissions due to manufacture from

the current mix of virgin and

recycled inputs

No change Nonbiogenic CO2, N2O

emissions, avoided utility

emissions, and

transportation emissions

Landfilling Baseline process and transportation

emissions due to manufacture from

the current mix of virgin and

recycled inputs

No change Methane emissions, longterm carbon storage,

avoided utility emissions,

and transportation emissions

* No manufacturing transportation GHG emissions are considered for composting of food scraps and yard trimmings

because these materials are not considered to be manufactured.

GHG Emissions and Carbon Sinks Associated With Raw Materials Acquisition and

Manufacturing

The top left of Exhibit 1-1 shows inputs for raw materials acquisition. These are virgin inputs used

to make various materials including ore used to make metal products, trees used to make paper products,

and petroleum or natural gas used to make plastic products. Fuel energy used to obtain or extract these

material inputs is also shown.

The inputs used in manufacturing are: (1) energy, and (2) either virgin raw materials or recycled

materials. In the exhibit these inputs are identified with arrows that point to the box labeled

"Manufacturing."

For source reduction, the “baseline” GHG emissions from raw materials acquisition and

manufacturing are avoided. This analysis thus estimates, for source reduction, the GHG reductions

(relative to a baseline of initial manufacture) at the raw materials acquisition and manufacturing stages.

Source reduction is assumed to entail more efficient use of a given material - for example,

"lightweighting," double-sided photocopying, or extension of a product's useful life. No other material

substitutions are assumed for source reduction; therefore, this report does not analyze any corresponding

increases in production and disposal of other materials (which could result in GHG emissions).12

 12 Although material substitution is not quantitatively addressed in the report, it is discussed from a

methodological standpoint in Chapter 2, and is also briefly discussed in Chapter 4, Section 4.3. Material substitution

is an important issue for future research.
11

The GHG emissions associated with raw materials acquisition and manufacturing are: (1) process

energy GHG emissions, (2) transportation energy GHG emissions, and (3) process non-energy GHG

emissions (for aluminum, steel, plastics, and office paper.) Each type of emission is described below.

Changes in carbon storage in forests are also associated with raw materials acquisition for paper

products.

Process Energy GHG Emissions: Process energy GHG emissions consist primarily of CO2

emissions from the combustion of fuels used in raw materials acquisition and manufacturing. CO2

emissions from combustion of biomass are not counted as GHG emissions (see box on CO2 Emissions

from Biogenic Sources, below).

The majority of process energy CO2 emissions are from combustion of fuels used directly, e.g., to

operate ore mining equipment or to fuel a blast furnace. Fuel is also needed to extract the oil or mine the

coal that is ultimately used to produce energy, and to transport these fuels to where they are used; thus

CO2 emissions from this "pre-combustion energy" are counted in this category as well. When electricity

generated by combustion of fossil fuels is used in manufacturing, the CO2 emissions from the fossil fuels

are also counted.

To estimate process energy GHG emissions, we first obtained estimates of both the total amount

of process energy used per ton of product (measured in British thermal units or BTUs), and the fuel mix

(e.g., diesel oil, natural gas, fuel oil). Next, we used emissions factors for each type of fuel to convert the

amount of each type of fuel used to the GHG emissions that are produced. As noted earlier, making a

material from recycled inputs generally requires less process energy (and uses a different fuel mix) than

making the material from virgin inputs.

Details of our methodology for estimating process energy GHG emissions are provided in

Chapter 2.

Transportation Energy GHG Emissions: Transportation energy GHG emissions consist of CO2

emissions from the combustion of fuels used to transport raw materials and intermediate products to the

final manufacturing or fabrication facility. We based our estimates of transportation energy emissions on:

1) the amounts of raw material inputs and intermediate products used in manufacturing one ton of each

material; 2) the average distance that each raw material input or intermediate product is transported; and

3) the transportation modes and fuels used. For the amounts of fuel used, we used data on the average

fuel consumption per ton-mile for each mode of transportation.13 Then we used an emission factor for

each type of fuel to convert the amount of each type of fuel consumed to the GHG emissions produced.

More detail on our methodology to estimate transportation energy GHG emissions is provided in

Chapter 2.

Process Non-Energy GHG Emissions: Some GHG emissions occur directly in the manufacture of

certain materials and are not associated with energy consumption. In this analysis, we refer to these

emissions as process non-energy emissions. For example, the production of steel or aluminum requires

lime (calcium oxide, or CaO), which is produced from limestone (calcium carbonate, or CaCO3); the

manufacture of lime results in CO2 emissions. Other process non-energy GHG emissions are associated

with production of plastics, office paper, and tissue paper. In some cases, process non-energy GHG

 13 These data are found in the Background Document A.
12

emissions are only associated with production using virgin inputs; in other cases, these emissions result

when either virgin or recycled inputs are used. These emissions are described in Chapter 2.

Carbon Sinks: The only carbon sink in the stages of raw materials acquisition and manufacturing

is the additional carbon sequestration in trees associated with source reduction or recycling of paper

products. Our methodology for estimating forest carbon sequestration is described in Chapter 3.

GHG Emissions and Carbon Sinks Associated With Waste Management

As shown at the bottom of Exhibit 1-1, there are, depending on the material, up to four postconsumer waste management options: recycling, composting, combustion, and landfilling. This section

describes the GHG emissions and carbon sinks associated with these four waste management options.

In this analysis, source reduction is measured by the amount of material that would otherwise be

produced but is not being produced because of a program promoting source reduction. Thus, with source

reduction there are no emissions from MSW management.

Recycling: When a material is recycled, it is used in place of virgin inputs in the manufacturing

process. Thus, the avoided GHG emissions from remanufacture using recycled inputs is calculated as the

difference between (1) the GHG emissions from manufacturing a material from 100 percent recycled

inputs, and (2) the GHG emissions from manufacturing an equivalent amount of the material (accounting

for loss rates) from 100 percent virgin inputs (including the process of collecting and transporting the

recyclables). There are no GHG emissions at the MSW management stage because the recycled material

is diverted from waste management facilities.14 (If the product made from the recycled material is later

composted, combusted, or landfilled, the GHG emissions at that point would be attributed to the product

that was made from the recycled material.) Chapter 4 details GHG emissions from recycling.

Most of the materials considered in this analysis are modeled as being recycled in a "closed loop"

(e.g., newspapers are recycled into new newspapers). However, office paper and corrugated boxes are

modeled as being recycled in an "open loop" (i.e., they are recycled into more than one product):

• Office paper is modeled as being recycled into either office paper or tissue paper; and

• Corrugated boxes are modeled as being recycled into either corrugated boxes or folding

boxes.

In addition, a variety of paper types are recycled under the general heading of “mixed paper.” Mixed

paper can be remanufactured, via an open loop, into boxboard or paper towels. We recognize that other

materials are recycled in open loop processes, but due to limited resources, we could not analyze all open

loop processes.15

Composting: When organic materials are composted, most of their organic mass quickly

decomposes to CO2. The materials that may be composted (e.g., leaves, brush, grass, food waste,

 14 We do not include GHG emissions from managing residues (e.g., wastewater treatment sludges) from the

manufacturing process for either virgin or recycled inputs.

15 For example, not all steel cans are recycled into more steel cans; not all aluminum cans are recycled into

more aluminum cans.
13

newspapers) are all originally produced by trees or other plants. As described in the text box above, the

CO2 emitted from these materials during composting is biogenic CO2, and thus is not counted in GHG

emissions.

There is some potential for the composting of yard trimmings to result in production of more

humic material (natural organic polymers, which degrade at a slow rate) than is produced when yard

trimmings are left to decompose in the yard. This process may act to enhance long-term carbon storage in

soils to which compost is applied.

Although composting may result in some production of methane (due to anaerobic decomposition

in the center of the compost pile) compost researchers believe that the methane is almost always oxidized

to CO2 before it escapes from the compost pile.

Because the CO2 emissions from composting are biogenic, and there are generally no methane

emissions, the only GHG emissions from composting result from transportation of compostable materials

CO2 Emissions from Biogenic Sources

The US and all other parties to the Framework Convention on Climate Change agreed to develop inventories

of GHGs for purposes of (1) developing mitigation strategies and (2) monitoring the progress of those strategies. The

Intergovernmental Panel on Climate Change (IPCC) developed a set of inventory methods to be used as the

international standard. (IPCC, IPCC Guidelines for National Greenhouse Gas Inventories (three volumes), 1997.)

In selecting the methodologies used in this report to evaluate emissions and sinks of GHGs, we attempted to be

consistent with IPCC's guidance.

One of the elements of the IPCC guidance that deserves special mention is the approach used to address CO2

emissions from biogenic sources. For many countries, the treatment of CO2 releases from biogenic sources is most

important when addressing releases from energy derived from biomass (e.g., burning wood), but this element is also

important when evaluating waste management emissions (for example, the decomposition or combustion of grass

clippings or paper). The carbon in paper and grass trimmings was originally removed from the atmosphere by

photosynthesis, and under natural conditions, it would eventually cycle back to the atmosphere as CO2 due to

degradation processes. The quantity of carbon that these natural processes cycle through the earth's atmosphere,

waters, soils, and biota is much greater than the quantity added by anthropogenic GHG sources. But the focus of the

Framework Convention on Climate Change is on anthropogenic emissions - emissions resulting from human

activities and subject to human control - because it is these emissions that have the potential to alter the climate by

disrupting the natural balances in carbon's biogeochemical cycle, and altering the atmosphere's heat-trapping ability.

Thus, for processes with CO2 emissions, if (a) the emissions are from biogenic materials and (b) the materials

are grown on a sustainable basis, then those emissions are considered to simply close the loop in the natural carbon

cycle -- that is, they return to the atmosphere CO2 which was originally removed by photosynthesis. In this case, the

CO2 emissions are not counted. (For purposes of this analysis, biogenic materials are paper, yard trimmings, and

food scraps.) On the other hand, CO2 emissions from burning fossil fuels are counted because these emissions

would not enter the cycle were it not for human activity. Likewise, CH4 emissions from landfills are counted - even

though the source of carbon is primarily biogenic, CH4 would not be emitted were it not for the human activity of

landfilling the waste, which creates anaerobic conditions conducive to CH4 formation.

Note that this approach does not distinguish between the timing of CO2 emissions, provided that they occur in

a reasonably short time scale relative to the speed of the processes that affect global climate change. In other words,

as long as the biogenic carbon would eventually be released as CO2, it does not matter whether it is released virtually

instantaneously (e.g., from combustion) or over a period of a few decades (e.g., decomposition on the forest floor).
14

to composting facilities, and mechanical turning of the compost piles. Carbon cycling in compost

operations is discussed in Chapter 5.

Combustion: When waste is combusted, two GHGs are emitted: CO2 and N2O. Non-biogenic CO2

emitted during combustion (i.e., CO2 from plastics) is counted toward the GHG emissions associated

with combustion, but biogenic CO2 is not. Because most waste combustors produce electricity that

substitutes for utility-generated electricity, the net GHG emissions are calculated by subtracting the

utility GHG emissions avoided from the gross GHG emissions. GHG emissions from combustion are

described in Chapter 6.

Landfilling: When organic matter is landfilled, some of this matter decomposes anaerobically and

releases methane, a GHG. Some of the organic matter never decomposes at all; instead it becomes

sequestered carbon. (Landfilling of metals and plastics does not result in either methane emissions or

carbon sequestration).

At some landfills, virtually all of the methane produced is released to the atmosphere. The gross

GHG emissions from these landfills consist of the methane emissions. At other landfills, methane is

captured for flaring or combustion with energy recovery (i.e., electricity production). Most of the

captured methane is converted to CO2, which is not counted as a GHG because it is biogenic. With

combustion of methane for energy recovery, credit is given for the electric utility GHG emissions

avoided. Regardless of the fate of methane, credit is given for the landfill carbon sequestration associated

with landfilling of some organic materials. GHG emissions and carbon sinks from landfilling are

described in Chapter 7.
15

2. RAW MATERIALS ACQUISITION AND MANUFACTURING

To estimate the GHG emissions and sinks for the full life cycle of MSW materials, we needed to

estimate the GHG emissions associated with raw materials acquisition and manufacturing. This chapter

describes how we estimated these emissions for ten materials: newspaper, office paper, corrugated boxes,

mixed paper, aluminum cans, steel cans, glass containers, and three types of plastic (LDPE, HDPE, and

PET).

In manufacturing, substantial amounts of energy are used in the acquisition of raw materials and in

the manufacturing process itself. In general, the majority of energy necessary for these activities comes

from fossil fuels. Combustion of fossil fuels results in emissions of CO2, a greenhouse gas, and trace

amounts of other GHGs that are not included in the analysis. In addition, manufacturing of some

materials also results in GHG emissions that are not associated with energy consumption. Section 2.1

addresses energy-related CO2 emissions, and section 2.2 covers non-energy GHGs.

2.1 GHG EMISSIONS FROM ENERGY USE IN RAW MATERIALS ACQUISITION AND

MANUFACTURING

To begin our analysis, we estimated the GHG emissions from fossil fuel combustion for both (1)

raw materials acquisition and manufacturing (referred to here as "process energy"), and (2) transportation

(referred to as "transportation energy").

In this analysis, process energy GHG emissions consist primarily of CO2.

1

 The majority of CO2

emissions are from combustion of fuels used directly, e.g., to operate mining equipment or to fuel a blast

furnace. Because fuel is also needed for "pre-combustion" activities (such as oil exploration and

extraction, coal mining and beneficiation, and natural gas production), CO2 emissions from "precombustion" activities are also counted in this category. When electricity is used in manufacturing, the

CO2 emissions from the fuels burned to produce the electricity are also counted. In general, making a

material from recycled inputs requires less process energy than making the material from virgin inputs.

Transportation energy GHG emissions consist of CO2 emissions from combustion of fuels used to

transport raw materials and intermediate products to the final manufacturing or fabrication facility. For

transportation of recycled inputs, this analysis considers transportation (1) from the curbside to the

materials recovery facility (MRF), (2) from the MRF to a broker, and (3) from a broker to the plant or

mill where the recycled inputs are used. The transportation values for recycled inputs also generally

include the energy used to process the inputs at a MRF. Transportation of finished manufactured goods

to consumers is not included in the analysis. We did not consider the global warming impacts of

 1

 Note, however, that CO2 emissions from combustion of biomass are not counted as GHG emissions (as

described in Chapter 1). For example, paper manufacturing uses biomass as a fuel.
16

transportation emissions of nitrogen oxides (NOx); such emissions contribute indirectly to climate

change.2

 This omission would tend to slightly understate the GHG impacts from transportation.

We also considered the methane emissions associated with producing, processing, and

transporting coal, oil, and natural gas. Methane is emitted during the various stages of fossil fuel

production because methane is trapped within coal and oil deposits, and because natural gas consists

largely of methane.

We developed separate estimates for GHG emissions from process and transportation energy for

virgin inputs and recycled inputs, generating a total of four separate GHG emissions estimates for each

material: (1) process energy with virgin inputs, (2) process energy with recycled inputs, (3) transportation

energy with virgin inputs, and (4) transportation energy with recycled inputs.

Methodology

We developed GHG emission estimates for each material based on two sets of data: (1) the

amount of each type of fuel used to make one ton of the material, and (2) the "carbon coefficient" for

each fuel (a factor that translates the energy value of fuel combusted into the mass of GHGs emitted).

Our methodology in using these two sets of data to estimate process and transportation energy

GHG emissions is best illustrated by an example. To estimate process energy GHG emissions from the

production of one ton of newspaper from virgin inputs, we multiplied the amount of each type of fuel

used (as measured in million British thermal units, or BTUs) times the carbon coefficient for that type of

fuel (as measured in metric tons of carbon equivalent, or MTCE, per million BTUs). Each of these

multiplications yielded an estimate, for one of the fuels used to make newspaper, of the amount of GHGs

emitted (in MTCE) from the combustion of that fuel when one ton of newspaper is made. The total

process energy GHG emissions from making one ton of newspaper are simply the sum of the GHG

estimates across the different fuels used. To estimate the GHG emissions when electricity is used, we

used the national average mix of fuels used to make electricity.

We estimated GHGs from the energy used to transport raw materials for making one ton of a given

product (e.g., newspaper) in the same way: the amount of each fuel used was multiplied by its carbon

coefficient, and the resulting values for each of the fuels were summed.

To count "pre-combustion" energy, we scaled up the amount of each fuel combusted during

manufacture by the amount of energy needed to produce that fuel.3

 In this approach, we used the

simplifying assumption that when oil is produced, oil is used as the energy source in oil production,

while natural gas is used for natural gas production, etc.

 2

 Because the Intergovernmental Panel on Climate Change (IPCC) has not established a method for

estimating the global warming implications of emissions of nitrogen oxides, we have not attempted such an

estimation.

3

 The proportion of precombustion energy, as a percent of total combustion energy, varies among fuels. The

following values represent the percentage of total combustion energy, for each source category, attributable to

precombustion energy. The precombustion energy equals 18.5 percent of the combustion energy for diesel, 20.5

percent for gasoline, 17.2 percent for residual fuel oil 18.5 percent for distillate fuel oil, 12.1 percent for natural gas,

and 2.4 to 2.7 percent for coal. Source, Franklin Associates, Ltd.
17

We developed GHG estimates for raw materials acquisition and manufacturing for each of the ten

manufactured materials considered in this report. We then developed GHG estimates for tissue paper and

folding boxes to enable us to estimate the GHG implications of increased recycling of office paper and

corrugated boxes, respectively, in an "open loop." We also developed GHG estimates for boxboard and

paper towels to enable us to estimate the GHG implications of recycling mixed paper in an “open loop.”4

Thus, the exhibits in this chapter show data not only for the ten materials of interest, but also for tissue

paper, folding boxes, boxboard, and paper towels. For steel cans, we developed GHG estimates for virgin

production using the basic oxygen furnace process,5

 and for recycled production using the electric arc

furnace process.6

For the amounts of each type of fuel used for process and transportation energy, we obtained two

independent sets of estimates from two consulting firms that have expertise in lifecycle analysis: Franklin

Associates Ltd. (FAL), and the Tellus Institute (Tellus). For carbon coefficients, we used data from the

Energy Information Administration of the US Department of Energy7

 for all fuels except diesel fuel and

electricity; for the latter fuels we used data from the American Council for an Energy-Efficient

Economy.8

 The carbon coefficient for electricity was based on the weighted average carbon coefficients

for all fuels used to generate electricity in the US.9

 4 Note that only Franklin Associates, Ltd. provided virgin and recycled manufacturing and transportation

data for boxboard and paper towels. For virgin boxboard, there is only one type of product manufactured, as shown

in Exhibits 2-3 and 2-4. For recycled boxboard, there are two types of products for which we obtained two different

sets of manufacturing and transportation data as shown in Exhibits 2-5 and 2-6. We have labeled the two types of

boxboard as boxboard “A” and boxboard “B.” These two products differ with respect to their recycled material

inputs only (i.e., the proportion of newsprint, corrugated cardboard, office paper, and coated paper used to

manufacture either boxboard “A” or boxboard “B”); both products share the same manufacturing and transportation

values for virgin inputs. In other words, there would be no reason to distinguish between boxboard “A” and

boxboard “B” if one considers virgin inputs only; in this case, there would only be one type of product—virgin

boxboard (as stated above).

5

 Note that the basic oxygen furnace process can utilize approximately 25 percent recycled inputs.

6

 Note that when recovered steel cans are used as inputs to an electric arc furnace, the resulting steel is not

suited for milling to the thinness of steel sheet needed for use in making new steel cans. Thus, a more precise

approach would have been to model recovery of steel cans as an open loop process, in which recovered steel cans

are made into some other steel product. By modeling recovery of steel cans as a closed loop process, we implicitly

assumed that each ton of steel produced from recovered steel cans in an electric arc furnace displaces a ton of steel

produced from virgin inputs in a basic oxygen furnace; we believe this is a reasonable assumption. (For the

fabrication energy required to make steel cans from steel, we used the values for fabrication of steel cans from steel

produced in a basic oxygen furnace.)

7

 Energy Information Administration, US Department of Energy, Draft Emissions of Greenhouse Gases in

the United States 1989-1994, DOE/EIA-0573-annual (Washington, D.C.: US Department of Energy), in press 1995,

cited in US Environmental Protection Agency, Draft Inventory of US Greenhouse Gas Emissions and Sinks: 1990-

1996 (Washington, D.C.: US EPA),April 1998.

8

 R. Neal Elliott, Carbon Reduction Potential from Recycling in Primary Materials Manufacturing,

(Berkeley, CA: American Council for an Energy-Efficient Economy), February 8, 1994, p. 14.

9

 FAL and Tellus reported the BTU value for electricity in terms of the BTUs of fuel combusted to generate

the electricity used at the factory, rather than the (much lower) BTU value of the electricity that is delivered to the

factory. Thus, FAL and Tellus had already accounted for the efficiency of converting fuels to electricity, and the
18

Because the carbon coefficients from these sources accounted for only the CO2 emissions from

combustion of each type of fuel, we added to these carbon coefficients (1) the average amount of

methane emitted during the production, processing, and transportation of fossil fuels, and (2) the average

CO2 emissions from oil production, due to the flaring of natural gas. We calculated the average GHG

emissions associated with US production of coal, oil, and natural gas. The resulting average estimates for

GHG emissions from fossil fuel production were 0.92 kilograms of carbon equivalent per million BTUs

(kg CE/million BTU) for coal, 0.10 kg CE/million BTU for oil, and 0.70 kg CE/million BTU for natural

gas.10

The carbon coefficients that reflect both CO2 and methane emissions are provided in Exhibit 2-1

(all exhibits are provided at the end of this chapter).

The process and transportation GHG values are shown in summary form in Exhibit 2-2. For each

product and each type of input (virgin or recycled), we summed the estimates for process and

transportation GHG emissions based on the FAL data, and then repeated the summation using the Tellus

data. Both sets of summed estimates are listed in Exhibit 2-2 in columns "b" (for virgin inputs) and "c"

(for recycled inputs).11 Although these estimates do not represent minimum or maximum values, we

believe that they do portray the variability in actual industry values for each material.

We also estimated the energy-related GHG emissions from manufacturing each material from the

current mix of virgin and recycled inputs. To do so, we averaged the two estimates for each material

based on FAL and Tellus data; the results are shown in column "e." (The remaining two columns of

Exhibit 2-2 are discussed later in this chapter.)

The FAL and Tellus values for energy use are provided in Exhibits 2-3 through 2-10. Exhibits 2-3

through 2-6 present the FAL data - providing, in turn, the data used to estimate energy-related GHG

emissions for products manufactured from virgin inputs, and then the data for energy-related GHG

emissions for products manufactured from recycled inputs.12 Exhibits 2-7 through 2-10 present the Tellus

data, which are organized in the same way.13

 

losses in transmission and distribution of electricity; and we did not need to account for these factors in the carbon

coefficient for electricity.

10 ICF Memorandum, "Fugitive Methane Emissions from Production of Coal, Natural Gas, and Oil," August

8, 1995, updated to use global warming potential for methane of 21.

11 Note that in Exhibit 2-2, only Franklin Associates, Ltd. provided virgin and recycled data for boxboard,

paper towels, and glass containers.

12 Note that when paper is made from virgin inputs, a substantial amount of biomass fuel (e.g., black liquor

from the digestion process and tree bark) is used. However, when paper is made from recycled inputs, no biomass

fuel is used.

13 Note that in Exhibits 2-7 and 2-9, Tellus included values for the energy content of steam used in

manufacturing. We translated these steam energy values into fuel inputs as follows: (1) we assumed that the energy

content of the fuels combusted was converted into steam energy at a conversion efficiency of 85 percent; (2) for

paper products, made from virgin or recycled inputs, we used a fuel mix for steam of 40 percent oil, 33 percent

biomass, 17 percent natural gas, and 10 percent coal; and (3) for non-paper products made from virgin or recycled

inputs, we used a fuel mix for steam of 50 percent natural gas, 25 percent coal, and 25 percent oil (based on ICF

professional judgment).
19

For most materials, both FAL and Tellus provided data for fuels used in manufacturing processes

that use (1) 100 percent virgin inputs and (2) 100 percent recycled inputs.14 To estimate the types and

amounts of fuels used for process and transportation energy, FAL and Tellus relied on published data

(such as engineering handbooks and published production data), and on personal contacts with industry

experts. FAL and Tellus counted all energy, no matter where it was used. For example, much aluminum

produced in the US is made from bauxite that is mined and processed into alumina in other countries.

The energy required for overseas bauxite mining and processing is counted in the analysis. In addition, it

does not matter where recycled inputs are made into remanufactured products. For example, if office

paper that is recovered in the US is remanufactured into paper products in Asia, the energy savings from

remanufacture using recycled rather than virgin inputs are counted.

Neither the FAL nor the Tellus transportation data reflect transportation of the finished

manufactured product to the retailer and consumer. This omission is only important in estimating the

GHG reductions associated with source reduction (i.e., source reduction reduces transportation energy).

It is not relevant in analyzing GHG implications of recycling compared to other post-consumer

management options, because the amount of transportation energy from the factory to the consumer is

about the same whether the product is manufactured from virgin inputs or recycled inputs. Even for the

source reduction analysis, we expect that the transportation energy from factory to consumer would

represent a very small fraction of the total process and transportation energy.

After FAL and Tellus had developed their initial estimates of process energy intensity and fuel

mix, we reviewed and verified the data by analyzing significant discrepancies between the estimates

provided by the two firms. Where discrepancies were found, we reviewed the most critical assumptions

and data elements that each firm used, and identified circumstances where it would be appropriate for

one firm to revise its assumptions or update its data sources.15 The effect of this process was to arrive at

estimates by the two firms that were closer to each other and, we expect, more accurately reflect the

energy used in raw materials acquisition and manufacturing of the materials considered. Nevertheless, we

recognize that different manufacturers making the same product use somewhat different processes with

different energy requirements and fuel mixes, and that there are limited data on the extent to which

various processes are used. Thus, our goal was to estimate as accurately as possible the national average

GHG emissions for the manufacture of each material from virgin and recycled inputs.

 14 The three exceptions were (1) the FAL data for corrugated boxes made from virgin inputs, for which

FAL provided data for manufacture from 90.2 percent virgin inputs and 9.8 percent recycled inputs, (2) the FAL

data for steel cans made from virgin inputs, for which FAL provided data for manufacture from 80 percent virgin

inputs and 20 percent recycled inputs, and (3) the Tellus data for steel cans made from virgin inputs, for which

Tellus provided data for manufacture from 90 percent virgin inputs and 10 percent recycled inputs. We extrapolated

from these data (and the corresponding values for production using 100 percent recycled inputs) to obtain estimates

of the energy inputs for manufacturing these materials from 100 percent virgin inputs.

15 For example, some of the data issues that we reviewed and decided on were (1) the fuel mix to assume

for electricity used to manufacture aluminum (the national average fuel mix for generating electricity was used,

because electricity generated from all types of fuel is sold as a single commodity through interconnected regional

grids meaning that, while aluminum is largely processed in the West where hydropower is abundant, aluminum

processing draws from the grid so all power sources are mixed), (2) whether to include the "pre-combustion" energy

for fossil fuels, i.e., the energy required to extract, refine, and deliver the fuels (pre-combustion energy was

counted), (3) whether to use data for use of recovered materials in "closed loop" or "open loop" processes (we used

a "closed loop" model for most materials), and (4) what loss rates should be used (we averaged the FAL and Tellus

loss rates).
20

In order to make the best use of all available data for each material, we averaged the FAL and

Tellus estimates of GHG emissions for manufacturing the material from (1) virgin inputs, and (2)

recycled inputs. These averaged values are used in all of the computations displayed in the executive

summary and in Chapter 8, which present overall results of the analysis.

Complete documentation of the FAL and Tellus data on the types and amounts of fuels used for

process and transportation energy, including data sources, is provided in Background Documents A and

B, available in the docket at the RCRA Information Center.

2.2 NON-ENERGY GHG EMISSIONS FROM MANUFACTURING AND RAW MATERIALS

ACQUISITION

We also accounted for three additional sources of GHGs in manufacturing processes that are not

related to energy use:

• When limestone (calcium carbonate, or CaCO3) is converted to lime (calcium oxide, or

CaO), CO2 is emitted. Significant quantities of lime are used in the production of steel,

aluminum, and, to a much lesser extent, office paper.

• Methane emissions from natural gas pipelines and processing of natural gas are associated

with the manufacture of plastic products.

• Perfluorocarbons (CF4 and C2F6) are emitted during aluminum smelting.

In most cases, process non-energy GHG emissions are only associated with production using

virgin inputs. In the case of steel, however, these emissions result when either virgin or recycled inputs

are used (because lime is used in the production of steel from recycled as well as virgin inputs).

The process non-energy GHGs for each material are shown in the second to last column of

Exhibits 2-3 and 2-5 (for manufacture from virgin inputs and recycled inputs, respectively), and are

repeated in column "f" of Exhibit 2-2. Our source for all these data, except the perfluorocarbon

emissions, is an appendix to a report prepared for the EPA Office of Policy, Planning, and Evaluation.16

Our source for the perfluorocarbon emissions is a memorandum prepared by ICF.17

2.3 RESULTS

Our estimates of the total GHG emissions from raw materials acquisition and manufacturing for

each material are shown in Exhibit 2-2, column "g." In order to obtain these estimates, we summed the

energy-related GHG emissions (column "e") and the non-energy GHG emissions (column "f").

 16 ICF Memorandum, "Detailed Analysis of Greenhouse Gas Emissions Reductions from Increased

Recycling and Source Reduction of Municipal Solid Waste," July 29, 1994, p. 48 of the Appendix prepared by

Franklin Associates, Ltd., dated July 14, 1994.

17 Memorandum from ICF to US EPA, "Perfluorocarbon Emissions from Aluminum Smelting," March 27,

1996. Memorandum from ICF to US EPA, "Perfluorocarbon Emissions from Aluminum Smelting," March 27,

1996.
21

The process energy and transportation GHG values that were developed as described earlier in this

chapter are shown in the third to last columns of Exhibits 2-3 and 2-5, and in the last columns of Exhibits

2-4 and 2-6 through 2-10 (the last columns of Exhibits 2-3 and 2-5 show the total process energy GHG

emissions).

Because we had two independent sets of data on the amounts of each type of fuel used in making

each product, we were able to develop both range estimates and point estimates of the energy-related

GHG values for manufacturing each material from virgin or recycled inputs, and from the current mix of

virgin and recycled inputs. In this report, for purposes of analyzing the GHG emissions associated with

the manufacturing stage of the product lifecycle, we are using the values in column "g" of Exhibit 2-2 for

total manufacturing GHG emissions (i.e., averages of point estimates). Depending on the inputs being

considered, the appropriate value for total GHG emissions is used (i.e., the value for manufacture from

virgin inputs, recycled inputs, or the current mix of virgin and recycled inputs).

2.4 LIMITATIONS OF THE ANALYSIS

There are several limitations to the analysis of the GHG emissions associated with raw materials

acquisition and manufacturing, as described below.

The approach used in this analysis provides values for the average GHG emission rates per ton of

material produced, not the marginal emission rates per incremental ton produced. In some cases, the

marginal emission rates may be significantly different. For example, reducing production of plastic

products from virgin inputs may not result in a proportional decrease in methane emissions from natural

gas pipelines and natural gas processing. Natural gas pipeline methane emissions are determined by the

operating pressure in natural gas pipelines, and the number and size of leaks in the pipeline.

Consequently, the amount of natural gas consumed at one end of the pipeline (e.g., to make plastic) does

not affect the level of pipeline methane emissions in a direct, linear way. As another example, long-term

reductions in electricity demand could selectively reduce demand for specific fuels, rather than reducing

demand for all fuels in proportion to their representation in the current average fuel mix. This analysis

estimates average carbon conversion rates largely because the marginal rates are much more difficult to

estimate. Nevertheless, we believe the average values provide a reasonable approximation of the GHG

emissions.

In addition, the analysis assumes that the GHG emissions from manufacturing a given product

change in a linear fashion as the percentage of recycled inputs moves from 0 percent to 100 percent. In

other words, the analysis assumes that both the energy intensity and the fuel mix change in linear paths

over this range. However, it could be that GHG emissions from manufacturing move in a non-linear path,

(e.g., some form of step function) when the percentage of recycled inputs changes, due to capacity limits

in manufacturing or due to the economics of manufacturing processes.

Although we developed two sets of energy data for most of the materials, we obtained only one set

(from Franklin Associates, Ltd.) for virgin and recycled energy use for boxboard, paper towels, and glass

containers. Similarly, very limited data were available for the typical proportions of virgin and recycled

inputs for tissue paper, folding boxes, boxboard, paper towels, and glass.

The transportation energy required for the final stage of transportation (to the consumer) was not

considered. Consequently, some carbon emissions reductions for "lightweighted" products for these

transportation stages were not considered; these savings are likely to be small.
22

The information used in this analysis represents the best available data from published and

unpublished industry sources, some dating back to the early 1980s. Therefore, the data do not

necessarily reflect recent trends in industrial energy efficiency or changes in the fuel mix. Although the

limitations in the energy data have been fully acknowledged in earlier versions of this report, and we

have specifically encouraged reviewers to provide updated or more complete data, no additional energy

data was brought to our attention as a result of the review process.

Finally, this static analysis does not consider potential future changes in energy usage per unit of

output or alternative energy (e.g., non-fossil) sources. Reductions in energy inputs, due to efficiency

improvements, could occur in either virgin input processes or recycled input processes. Efficiency

improvements and switching to alternative energy sources will result directly in GHG emissions

reductions, and may change the reductions possible through increased recycling or source reduction.
23

Exhibit 2-1

Carbon Coefficients

For Selected Fuels

Metric Tons of CO2 kg Carbon Equivalent (CE) Metric Tons of Fugitive kg CE from 

from Combustion per from Combustion Per Methane Emissions Per Methane E

Fuel Type Million BTUs Million BTUs Million BTUs Per MillioGasoline 0.07 19.54 0.00002 LPG 0.06 17.13 0.00002 

Distillate Fuel 0.07 20.06 0.00002 Residual Fuel 0.08 21.60 0.00002 

Diesel 0.08 20.91 0.00002 

Oil/Lubricants 0.07 20.35 0.00002 Steam (non-paper products) 0.07 18.73 0.00011 Steam (paper products) 0.05 13.16 0.00004 National Average Fuel Mix for Electric 16.21 0.00010 

0.06

National Average Fossil Fuel Mix for 0.09 24.14 0.00015 Coal Used for Electricity 0.09 25.71 0.00016 Coal Used by Industry (Non-Coking C 25.61 0.00016 

0.09

Natural Gas 0.05 14.47 0.00012 Other (Petroleum Coke) 0.10 27.96 0.00002 

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.
24

Explanatory notes: To estimate the GHG emissions from manufacturing, we first estimated the process and transportation GHG emissions when 100 percent virgin

inputs, or 100 percent recycled inputs, are used. For each product and each type of input (virgin or recycled), we first summed the estimates for process and transportation GHG

emissions based on the FAL data, and then repeated the summation using the Tellus data. These summed estimates are shown above in columns "b" (for virgin inputs) and "c" (for

recycled inputs). Two summed estimates are shown for each material in each column: the "FAL estimate" and the "Tellus estimate." However, for boxboard, paper towels, and

glass, we obtained data from FAL only.

Next we estimated the GHG emissions from manufacturing each material from the current mix of virgin and recycled inputs. We began with estimates of the percentage of

recycled inputs currently used in the manufacture of each material, as shown in column "d." We used these percentages to develop a weighted average value for the GHG

emissions associated with the manufacture of each material from the current mix of virgin and recycled inputs. Specifically, we used the FAL estimate of the percentage of recycled

inputs in the current mix, together with the FAL estimates for GHG emissions from manufacture using virgin or recycled inputs, to develop FAL estimates of GHG emissions from

manufacture using the current mix of virgin and recycled inputs (labeled "FAL estimate" in column "e"). We repeated the process using the Tellus data (labeled "Tellus estimate" in

Exhibit 2-2

Greenhouse Gas Emissions from the Manufacture of Selected Materials

(Metric Tons of Carbon Equivalent (MTCE) per Ton of Product)

(a) (b) (c) (d) (e) (f) (g)

Current Mix Combined

Virgin Input Combined Recycled Input Combined Process and Transportation Average Combined

Process and Transportation Process and Transportation Percent Recycled Energy Emissions Process Process and Transportation

Energy Emissions Energy Emissions Inputs in the Current (MTCE Per Ton of Product Non-Energy Energy and Process

(MTCE Per Ton of Product (MTCE Per Ton of Product Mix of Virgin and Made with the Current Mix of Emissions (MTCE Per Non-Energy Emissions

Made With Virgin Inputs) Made With Virgin Inputs) Recycled Inputs Virgin and Recycled Inputs) Ton of Product) (MTCE Per Ton of Product)

FAL Tellus FAL Tellus FAL Tellus FAL Tellus Virgin Recycled Current Virgin Recycled Current 

Type of Product Est. Est. Est. Est. Est. Est. Est. Est. Inputs Inputs Mix Inputs Inputs Mix

Newspaper 0.54 0.55 0.39 0.38 44% 39% 0.47 0.48 0.00 0.00 0.00 0.55 0.38 0.48

Office Paper 0.57 0.53 0.50 0.42 31% 32% 0.55 0.50 0.01 0.00 0.01 0.56 0.46 0.53

 Tissue Paper 0.66 0.51 0.59 0.36 NA NA 0.66 0.51 0.01 0.00 0.01 0.59 0.48 0.59

Corrugated Boxes 0.27 0.48 0.40 0.53 46% 51% 0.33 0.51 0.00 0.00 0.00 0.38 0.47 0.42

 Folding Boxes 0.42 0.51 0.45 0.56 NA NA 0.42 0.51 0.00 0.00 0.00 0.46 0.50 0.46

Mixed Paper

 Boxboard "A" * 0.33 NA 0.44 NA NA NA 0.33 NA 0.00 0.00 0.00 0.33 0.44 0.33

 Boxboard "B" * 0.33 NA 0.44 NA NA NA 0.33 NA 0.00 0.00 0.00 0.33 0.44 0.33

 Paper Towels 0.95 NA 0.78 NA NA NA 0.95 NA 0.00 0.00 0.00 0.95 0.78 0.95

Aluminum Cans 3.91 3.71 0.68 0.75 52% 51% 2.22 2.20 1.59 0.00 0.76 5.39 0.72 2.97

Steel Cans 0.79 0.97 0.28 0.30 45% 51% 0.56 0.63 0.24 0.24 0.24 1.12 0.53 0.83

Glass Containers 0.12 NA 0.07 NA 25% NA 0.11 NA 0.04 0.00 0.03 0.16 0.07 0.14

HDPE 0.51 0.79 0.25 0.32 24% 22% 0.45 0.68 0.05 0.00 0.04 0.70 0.28 0.61

LDPE 0.63 1.05 0.23 0.42 0% 0% 0.63 1.05 0.05 0.00 0.05 0.89 0.33 0.89

PET 0.98 1.29 0.40 0.50 27% 25% 0.82 1.09 0.03 0.00 0.02 1.16 0.45 0.98

Note that totals may not add due to rounding and more digits may be displayed than are significant.

NA: Not applicable, or in the case of composting of paper, not analyzed.

* For virgin Boxboard, there is one type of product manufactured for which we obtained manufacturing and transportation data. For recycled Boxboard, there are two types of products for which we obtained two 

different sets of manufacturing and transportation data. Boxboard "A" and Boxboard "B" differ with respect to their recycled material inputs only (i.e., the proportion of newsprint, corrugated boxes, office paper, and 

coated paper used to manufacture either Boxboard "A" or Boxboard "B"). If one does not consider the current mix of virgin and recycled inputs, then there is no reason to distinguish between Boxboard 

"A" and Boxboard "B"; in this case, there is only one product to consider--virgin Boxboard (as stated above).
25

Explanatory notes for Exhibit 2-2 (continued): column "e"). However, for tissue paper, folding boxes, boxboard “A”, boxboard “B”, paper towels, and glass, we were unable

to obtain estimates of the proportions of recycled and virgin inputs used in the current manufacturing mix.

Column "f" shows estimates of the process non-energy GHG emissions from manufacturing. First this column shows the process non-energy GHG emissions when virgin

inputs are used. Then it shows the emissions when recycled inputs are used (these values are simply copied from the final columns of Exhibits 2-3 and 2-5). Finally, column "f"

shows the process non-energy GHG emissions from manufacturing each product from the current mix of virgin and recycled inputs. The values for the current mix are the

weighted averages of the values for virgin and recycled inputs, based on the percentage of recycled inputs used in the current mix (as shown in column "d").

The total GHG emissions from manufacturing are shown in column "g." This column shows total GHG emissions when a product is manufactured from virgin or recycled

inputs, or from the current mix of virgin and recycled inputs. To obtain these values, we first developed two estimates of the GHG emissions for each material and each set of

inputs. One estimate is based on FAL data, and the other is based on Tellus data (these estimates included both energy-related GHG emissions and process non-energy GHG

emissions). The values in column "g" are the averages of the estimates based on FAL and Tellus data.
26

Exhibit 2-3 (Franklin Data)

GHG Emissions Per Ton of Product Manufactured from Virgin Inputs

Process GHGs Only

Process Energy Process Energy Proce

 (Million BTUs Per Average Fuel Mix (in Percent) Carbon Emissions Carb

Type of Product Ton of Product) Gasoline LPG Distillate Fuel Residual Fuel Biomass Diesel Electricity Coal Natural Gas Total (MTCE/Ton of Product) (MTCE

Newspaper 33.96 0.00 0.06 0.08 0.49 6.53 0.82 57.54 1.07 33.41 100.00 0.52 Office Paper 54.80 1.99 0.00 0.01 4.34 50.07 0.00 24.75 9.78 9.06 100.00 0.52 

 Tissue Paper 52.09 2.29 0.00 3.35 13.19 40.88 0.00 18.90 11.95 9.44 100.00 0.61 

Corrugated Boxes 30.01 0.00 0.00 0.01 1.62 56.06 1.21 19.67 8.75 12.68 100.00 0.24 

 Folding Boxes 40.12 2.79 0.00 1.44 5.88 47.87 0.00 18.22 10.29 13.52 100.00 0.40 

Boxboard 32.26 0.00 0.00 0.00 0.94 59.34 1.36 5.32 24.01 9.02 100.00 0.29 Paper Towels 73.44 0.00 0.00 0.01 1.80 24.89 0.45 28.15 2.93 41.78 100.00 0.91 Aluminum Cans 226.85 0.00 0.01 0.23 1.25 0.00 0.22 84.18 0.25 13.86 100.00 3.78 Steel Cans 31.58 0.21 0.00 5.06 0.35 0.00 0.00 21.02 53.90 19.45 100.00 0.69 Glass 6.62 0.54 0.00 1.40 0.45 0.27 0.00 10.65 7.52 79.15 100.00 0.11 HDPE 30.71 0.10 0.03 0.23 0.72 0.00 0.00 42.46 0.00 56.46 100.00 0.49 LDPE 37.68 0.08 0.03 0.19 0.58 0.00 0.00 51.11 0.00 48.01 100.00 0.60 PET 50.51 0.05 0.05 5.88 15.56 0.00 0.00 51.66 6.14 20.67 100.00 0.91 Note that totals may not add due to rounding and more digits may be displayed than are significant.
27

Exhibit 2-4 (Franklin Data)

GHG Emissions Per Ton of Product Manufactured from Virgin Inputs

Transportation GHGs Only

Transportation Energy Transportation E

 (Million BTUs Per Average Fuel Mix (in Percent) (Metric 

Type of Product Ton of Product) Diesel Residual Oil Natural Gas Electricity Total Equivalent P

Newspaper 0.77 98.59 1.14 0.17 0.10 100.00 Office Paper 2.46 99.43 0.43 0.11 0.03 100.00  Tissue Paper 2.46 99.43 0.43 0.11 0.03 100.00 Corrugated Boxes 1.43 99.79 0.18 0.02 0.01 100.00  Folding Boxes 1.01 99.19 0.59 0.20 0.02 100.00 

Boxboar 1.79 99.93 0.05 0.01 0.00 100.00 Paper 2.07 99.46 0.52 0.02 0.01 100.00 

Aluminum Cans 5.73 37.53 62.07 0.00 0.40 100.00 Steel Cans 4.60 98.24 1.76 0.00 0.00 100.00 Glass 0.58 88.96 2.64 6.51 1.90 100.00 HDPE 1.15 54.50 19.32 24.66 1.52 100.00 LDPE 1.15 54.50 19.32 24.66 1.52 100.00 PET 3.27 79.65 16.63 2.42 1.31 100.00 Note that totals may not add due to rounding and more digits may be displayed than are significant.
28

Process Energy Process Energy Pro

 (Million BTUs Per Average Fuel Mix (in Percent) Carbon Emissions Ca

Type of Product Ton of Product) Gasoline LPG Distillate Fuel Residual Fuel Biomass Diesel Electricity Coal Natural Gas Total (MTCE/Ton of Product)(MTC

Newspaper 23.01 0.00 0.22 0.12 0.05 0.00 0.00 59.65 0.95 39.02 100.00 0.37 Office Paper 26.46 0.00 0.00 14.29 13.26 0.00 0.00 48.64 0.00 23.81 100.00 0.46  Tissue Paper 26.46 0.00 0.00 14.29 13.26 0.00 0.00 48.64 0.00 23.81 100.00 0.46 Corrugated Boxes 15.95 0.00 0.13 0.01 1.29 0.00 0.66 44.81 30.08 23.00 100.00 0.31  Folding Boxes 18.90 0.00 0.00 0.00 3.22 0.00 0.00 36.23 22.45 38.10 100.00 0.35 

Boxboard* 22.53 0.00 0.03 0.02 0.36 0.00 0.49 67.46 24.36 7.25 99.98 0.43 Boxboard** 22.53 0.00 0.03 0.02 0.36 0.00 0.49 67.46 24.36 7.25 99.98 0.43 Paper Towels*** 51.69 0.00 0.00 0.00 0.45 6.94 0.15 36.32 0.98 55.14 99.99 0.77 

Aluminum Cans 40.34 0.00 0.00 0.00 3.10 0.00 0.00 39.96 0.00 56.94 100.00 0.65 Steel Cans 11.78 0.01 0.17 0.07 0.03 0.00 0.00 77.28 0.65 21.80 100.00 0.19 Glass 4.37 0.55 0.00 0.39 0.25 0.25 0.00 5.49 0.53 92.54 100.00 0.07 HDPE 12.68 0.00 0.21 0.00 0.00 0.00 0.00 99.79 0.00 0.00 100.00 0.21 LDPE 11.43 0.00 0.23 0.00 0.00 0.00 0.00 99.77 0.00 0.00 100.00 0.19 PET 21.87 0.00 0.12 0.00 0.00 0.00 0.00 99.88 0.00 0.00 100.00 0.37 Note that totals may not add due to rounding and more digits may be displayed than are significant.* Recycled boxboard using a "broad" definition of mixed paper comprised of 24 percent newsprint, 48 percent corrugated cardboard, 20 percent office paper, and 8 percent coa

** Recycled boxboard using a "residential" definition of mixed paper comprised of 23 percent newsprint, 53 percent corrugated cardboard, 14 percent office paper, and10 perce*** Recycled boxboard using an "office paper" definition of mixed paper comprised of 21 percent newsprint, 5 percent corrugated cardboard, 38 percent office paper, and 36 pe

Exhibit 2-5 (Franklin Data)

GHG Emissions Per Ton of Product Manufactured from Recycled Inputs

Process GHGs Only
29

Exhibit 2-6 (Franklin Data)

GHG Emissions Per Ton of Product Manufactured from Recycled Inputs

Transportation GHGs Only

Transportation Energy Transportation En

 (Million BTUS Per Average Fuel Mix (in Percent) (Metric T

Type of Product Ton of Product) Diesel Residual Oil Natural Gas Electricity Total Equivalent Pe

Newspaper 0.75 98.67 1.08 0.15 0.10 100 Office Paper 1.61 100.00 0.00 0.00 0.00 100  Tissue Paper 1.61 100.00 0.00 0.00 0.00 100 Corrugated Boxes 1.23 99.90 0.10 0.00 0.00 100  Folding Boxes 1.29 99.92 0.08 0.00 0.00 100 

Boxboard* 0.38 100.00 0.00 0.00 0.00 100 Boxboard** 0.38 100.00 0.00 0.00 0.00 100 Paper Towels*** 0.44 97.58 2.31 0.08 0.06 100 

Aluminum Cans 1.65 100.00 0.00 0.00 0.00 100 Steel Cans 4.03 99.99 0.01 0.00 0.00 100 Glass 0.34 88.61 2.61 6.53 1.95 100 HDPE 1.74 100.00 0.00 0.00 0.00 100 LDPE 1.74 100.00 0.00 0.00 0.00 100 PET 1.74 100.00 0.00 0.00 0.00 100 Note that totals may not add due to rounding and more digits may be displayed than are significant.* Recycled boxboard using a "broad" definition of mixed paper comprised of 24 percent newsprint, 48 percent corrugated cardboard, 20 percent ofand 8 percent coated paper.** Recycled boxboard using a "residential" definition of mixed paper comprised of 23 percent newsprint, 53 percent corrugated cardboard, 14 perceand10 percent coated paper.*** Recycled boxboard using an "office paper" definition of mixed paper comprised of 21 percent newsprint, 5 percent corrugated cardboard, 38 peand 36 percent coated paper.
30

Exhibit 2-7 (Tellus Data)

GHG Emissions Per Ton of Product Manufactured from Virgin Inputs

Process GHGs Only

Process Energy Proce

 (Million BTUs Per Average Mix of Energy Sources (percent) 

Type of Product Ton of Product) Gasoline Diesel Oil Steam Electricity Coal Natural Gas Other Fuels Total Equ

Newspaper 34.11 0.46 0.35 0.27 28.45 70.47 0.00 0.00 0.00 100.00 Office Paper 35.18 0.89 0.71 5.00 77.00 16.41 0.00 0.00 0.00 100.00  Tissue Paper 33.22 0.94 0.75 5.29 74.17 18.84 0.00 0.00 0.00 100.00 Corrugated Boxes 32.07 0.86 0.70 4.90 82.58 10.95 0.00 0.00 0.00 100.00  Folding Boxes 34.05 0.81 0.66 4.61 80.82 13.09 0.00 0.00 0.00 100.00 Aluminum Cans 216.24 0.00 0.00 1.93 1.08 72.01 1.25 23.68 0.05 100.00 Steel Cans 42.10 0.03 0.36 2.35 6.15 34.66 0.33 5.71 50.41 100.00 Glass 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 HDPE 37.29 0.00 8.10 0.00 1.69 23.09 0.00 42.27 24.85 100.00 LDPE 51.78 0.00 6.91 0.00 5.03 31.21 0.00 35.81 21.03 100.00 PET 62.51 0.00 5.61 0.00 27.37 34.99 0.00 10.89 21.14 100.00 Note that totals may not add due to rounding and more digits may be displayed than are significant.
31

Exhibit 2-8 (Tellus Data)

GHG Emissions Per Ton of Product Manufactured from Virgin Inputs

Transportation GHGs Only

Transportation Energy Transportation Energy Carbon Emission

 (Million BTUs Per Average Fuel Mix (in Percent) (Metric Tons of Carbon

Type of Product ton of Product) Diesel Natural Gas Total Equivalent Per Ton of Product)Newspaper 0.58 100.00 0.00 100.00 Office Paper 1.21 100.00 0.00 100.00  Tissue Paper 1.21 100.00 0.00 100.00 Corrugated Boxes 1.08 100.00 0.00 100.00  Folding Boxes 1.08 100.00 0.00 100.00 Aluminum Cans 5.29 100.00 0.00 100.00 Steel Cans 0.91 100.00 0.00 100.00 Glass 0.00 100.00 0.00 100.00 HDPE 3.72 53.25 46.75 100.00 LDPE 3.83 53.19 46.81 100.00 PET 2.48 57.44 42.56 100.00 Note that totals may not add due to rounding and more digits may be displayed than are significant.
32

Exhibit 2-9 (Tellus Data)

GHG Emissions Per Ton of Product Manufactured from Recycled Inputs

Process GHGs Only

Process Energy Pr

 (Million BTUs Per Average Mix of Energy Sources (percent) 

Type of Product Ton of Product) Gasoline Diesel Oil Steam Electricity Coal Natural Gas Other Fuels Total 

Newspaper 18.52 0.00 0.26 0.00 41.88 57.86 0.00 0.00 0.00 100.00 Office Paper 20.80 0.00 0.23 0.00 62.85 36.92 0.00 0.00 0.00 100.00  Tissue Paper 0.94 0.00 0.24 0.00 58.66 41.10 0.00 0.00 0.00 100.00 Corrugated Boxes 27.31 0.00 0.17 0.00 69.47 30.36 0.00 0.00 0.00 100.00  Folding Boxes 29.23 0.00 0.16 0.00 67.11 32.72 0.00 0.00 0.00 100.00 Aluminum Cans 46.04 0.00 0.10 2.57 0.00 35.51 0.00 61.82 0.00 100.00 Steel Cans 17.01 0.00 0.35 0.00 0.00 97.92 0.48 1.25 0.00 100.00 Glass 1.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 HDPE 17.85 0.00 0.27 0.00 0.00 99.73 0.00 0.00 0.00 100.00 LDPE 23.29 0.00 0.20 0.00 0.00 99.80 0.00 0.00 0.00 100.00 PET 27.84 0.00 0.17 0.00 0.00 99.83 0.00 0.00 0.00 100.00 Note that totals may not add due to rounding and more digits may be displayed than are significant.
33

Exhibit 2-10 (Tellus Data)

GHG Emissions Per Ton of Product Manufactured from Recycled Inputs

Transportation GHGs Only

Transportation Energy Transportation Energy Carbon Emissions

 (Million BTUs Per Average Fuel Mix (in Percent) (Metric Tons of Carbon

Type of Product Ton of Product) Diesel Natural Gas Total Equivalent Per Ton of Product)

Newspaper 2.13 100.00 0.00 100.00 0.04Office Paper 1.87 100.00 0.00 100.00 0.04 Tissue Paper 0.00 100.00 0.00 100.00 0.00Corrugated Boxes 1.33 100.00 0.00 100.00 0.03 Folding Boxes 0.83 100.00 0.00 100.00 0.02Aluminum Cans 0.90 100.00 0.00 100.00 0.02Steel Cans 0.82 100.00 0.00 100.00 0.02Glass 0.00 100.00 0.00 100.00 0.00HDPE 0.83 100.00 0.00 100.00 0.02LDPE 1.56 100.00 0.00 100.00 0.03PET 1.56 100.00 0.00 100.00 0.03Note that totals may not add due to rounding and more digits may be displayed than are significant.
34

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35

3. FOREST CARBON SEQUESTRATION

This chapter presents estimates of the forest carbon sequestration that result from recycling or

source reducing newspaper, office paper, and corrugated cardboard.

One of the large-scale processes that influences the cycling of carbon is the uptake or release of

carbon from forests. When trees are cleared for agriculture or other activities, carbon is released

(generally in the form of CO2). On the other hand, when forests are planted and allowed to continue

growing, they absorb atmospheric CO2 and store it in the form of cellulose and other materials. When the

rate of uptake exceeds the rate of release, carbon is said to be sequestered. In the US, uptake by forests

has exceeded release since about 1977, primarily due to forest management activities and the

reforestation of previously cleared areas. This net storage of carbon in forests represents a large and

important process – EPA estimates that the annual net CO 2 flux (i.e., the excess of uptake minus release)

in US forests was about 75 million metric tons of carbon equivalent (MMTCE) in 1996,1

 offsetting about

5 percent of US energy-related CO2 emissions. In addition, about 18 million metric tons of carbon was

stored in wood products.

When paper products are source reduced or recycled, trees that would otherwise be harvested are

left standing. In the short term, this results in a larger amount of carbon remaining sequestered, because

the standing trees continue to store carbon, whereas paper production and use tends to release carbon.2

 In

the long term, some of the short-term benefits disappear as market forces result in less planting of new

managed forests than there would otherwise be, so that there is comparatively less forest acreage in trees

that are growing rapidly (and thus sequestering carbon rapidly).3,4,5

 1 US EPA, Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-96, April 1998. Note that

the estimate cited includes only carbon storage in trees and understory; this report also includes estimates for forest

floor and soils.

2 The basic relation is that the forest carbon inventory in any year equals the carbon inventory the year

before, plus net growth, less harvests, less decay. Thus, when harvests are reduced the inventory increases. (However

when inventories become high relative to the carrying capacity of the land, the rate of growth decreases because net

growth [the rate at which growth exceeds decay] declines).

3

 Note also that when a ton of paper is source reduced or recycled, less timber is harvested to make new

paper. In general, as the demand for timber falls with increased source reduction and recycling, the price of timber

also falls. Consequently, increased harvesting for solid wood products (such as lumber or plywood used in

construction) may result.

4

 Note that some analysts project that in the long run, global demand for forest products will increase more

rapidly than global paper recovery rates, so that even with increased paper recovery, forested acreage is likely to

increase in the long run to meet increased demand.

5

 Some analysts have suggested that more efficient municipal waste combustors and increased paper

combustion rates, combined with more intensive tree planting, could result in reduced GHG emissions [Electric

Power Research Institute, "Paper Recycling: Impact on Electricity-Use, Electro-Technology Opportunities," Report

RP-3228-06 (1993), cited in Gaines, Linda L. and Frank Stodolsky, "Energy Implications of Recycling Packaging

Materials" (Argonne, IL: Argonne National Laboratory) 1994]. However, a comprehensive examination of the
36

Considering the importance of forest carbon sequestration as a process affecting net US GHG

emissions, and given the fact that paper products are a large and growing portion of the forest products

market, we recognized that a thorough examination of forest carbon sequestration was warranted for this

study. Moreover, the complexity and long time frame of carbon storage in forests, coupled with the

importance of market dynamics that determine land use behavior, dictated the use of best available

models to evaluate the effect of source reduction and recycling of paper products on forest carbon

sequestration. This chapter describes our method for applying models to estimate the effect of forest

carbon sequestration associated with paper source reduction and recovery for recycling. We used the

results from our analysis of paper recovery to estimate the effect of recycling and source reduction on

forest carbon sequestration.

We worked with the US Department of

Agriculture Forest Service (USDA-FS) to use a

system of models of the US forest sector to estimate

the amount of forest carbon sequestration per

incremental ton of newspaper, office paper, and

corrugated cardboard reduced and recycled. We

used the USDA-FS system of models because (1)

they are the best models available in modeling the

species composition, inventory, and growth of

forests, and (2) these models had been used

previously to analyze climate change mitigation

options for the Climate Change Action Plan.

Because the models did not allow us to separately

estimate the forest carbon sequestration associated

with recovery of each of the three types of paper,

we obtained a single estimate for the sequestration

from recovering any type of paper.

In brief, we found a relationship exists

between recycling rates and carbon sequestration,

and that recovering one ton of paper results in incremental forest carbon sequestration of 0.73 metric tons

of carbon equivalent (MTCE).6

 We converted this single estimate for recovering any type of paper into

separate estimates for source reducing each of three different types of paper. We developed separate

estimates for source reduction based on the inputs displaced by source reduction – either 100 percent

virgin inputs, or a mix of virgin and recycled inputs (this mix is different for each type of paper).

If one assumes that source reduction displaces 100 percent virgin inputs in paper manufacture,

forest carbon effects would be the same as for recycling, i.e., sequestration of 0.73 MTCE per ton. If

source reduction displaces the mix of virgin and recycled inputs currently used in manufacturing, the

benefits would be somewhat reduced—source reduction of one ton of newspaper, office paper, or

corrugated cardboard results in forest carbon sequestration of, respectively, 0.48, 0.56, and 0.44 MTCE.

 

interactions between combustion and forest dynamics was beyond the scope of this report. Likewise the use of

recovered paper for non-paper uses, such as molded pulp products and insulation, was not analyzed.

6

 Although a relationship exists, it is not directly measurable. Moreover, for the relationship to remain valid,

there must be continued investment in tree planting and growth. We believe this continued investment will occur,

because projections of forest product use consistently point to increases in demand.

Performance of the USDA-FS Forest Models

Researchers have never formally assessed the

accuracy of the USDA-FS models of the forest

sector. In analyses that compare the forest impacts

of a policy scenario to those of a baseline scenario

(such as the analysis described in this chapter), the

USDA-FS model results are probably reasonable.

This is because much of the uncertainty in the model

results is due to assumptions that apply to both the

baseline and policy scenarios – assumptions about

population growth, economic growth, tree growth,

and land use changes. Any error in these

assumptions would tend to bias the results in the

baseline and policy scenarios in the same direction.

Thus, when the outcomes of the baseline and policy

scenarios are compared, errors in the assumptions

tend to cancel each other out.
37

The remainder of this chapter is divided into seven parts. Section 3.1 provides an overview of the

linkages between the five models used in the analysis. Sections 3.2 through 3.5 describe the five models

in greater detail, and briefly discuss the inputs, assumptions, and outputs for each model. Section 3.6

presents the results of the analysis, and Section 3.7 discusses the limitations of individual models, and of

the analysis as a whole.
38

3.1 MODELING FRAMEWORK

Working with USDA-FS, we used five linked models of the forest sector to estimate the impacts

of increased recovery and source reduction of paper products on forest carbon sequestration.7 The first

model projects the decline in US pulpwood harvests when paper recovery increases. The second and

third models use the outputs of the first model, together with other inputs and assumptions, to estimate

the extent to which reduced pulpwood harvests due to paper recovery result in lower US timber harvests

and increased timber inventories. 8 The fourth and fifth models use the outputs of the second and third

models, and estimate how the increased timber inventories and decreased timber harvests due to paper

recovery translate into (1) increased forest carbon sequestration and (2) changes in carbon sequestration

in wood-in-use carbon sinks (e.g., wood used in home construction). Exhibit 3.1 shows how the models

are linked.

Our overall analysis proceeded as follows:

1) We developed two future recovery scenarios – a projected baseline paper recovery rate for the

year 2000 of 50 percent, and a hypothetical year 2000 paper recovery rate of 55 percent – as inputs

to the North American Pulp and Paper (NAPAP) model (the model is described in Section 3.2). A

50 percent recovery rate was used for the baseline scenario because the paper industry projects a

50 percent recovery rate by the year 2000 in the absence of further government policies to promote

recycling. We used a 55 percent recovery rate for the high recovery scenario because (1) we

considered this to be a plausible recovery rate with additional government programs to promote

recycling, and (2) this recovery rate corresponds to EPA's goal of increasing recovery of MSW in

the original (1993) Climate Change Action Plan. We assumed that EPA policies to promote source

reduction and recycling would end in 2000, and that over the next 15 years, the recovery rates

under both scenarios would continue to rise and would converge in the year 2016 at 57 percent.

(We assumed convergence so that we could isolate the long-term carbon sequestration effects that

might result from increasing paper recovery in the near term.) The paper recovery rates for both

scenarios were then projected to rise slowly from 57 percent in 2016 to 61 percent in 2040. This

adjustment to the model incorporated our assumption that the current trend of increasing paper

recovery rates would continue into the future.

The NAPAP model was then run to model the pulpwood harvests from 1985 to 2040 that would be

associated with (1) the baseline paper recovery rate and (2) the high paper recovery rate.

2) The outputs from NAPAP for projected pulpwood harvests in the two scenarios were used as

inputs to the Timber Assessment Market Model (TAMM), which projects US timber harvests, and

the Aggregate Timberland Assessment System (ATLAS) model, which projects timber growth and

changes in the US forest inventory (where inventory is a function of both growth and harvests).

The TAMM and ATLAS models are described more fully in Section 3.3. The TAMM and ATLAS

models were run, using the NAPAP inputs, to generate estimates of US harvest levels and forest

inventories for each year through 2040, for both the baseline and high recovery scenarios.

 7 The Forest Service models and data bases were last completely revised in 1987, and updated in 1993. The

Forest Service expects to publish a complete revision in December 1998.

8 The USDA-FS projections of forest product demand account for continued high demand for all types of

forest products.
39

3) The outputs from TAMM and ATLAS for forest harvest levels and forest inventories in the two

scenarios were used as inputs to the Forest Carbon (FORCARB) model, described in Section 3.4,

which projects forest carbon sequestration. The FORCARB model produced, as outputs, estimates

of US forest carbon sequestration for each year through 2040, for both the baseline and high

recovery scenarios.

4) FORCARB outputs were also used as inputs to the HARVCARB (Harvested Carbon) model,

which tracks the flow of carbon in wood products (see Section 3.5).

3.2 THE NORTH AMERICAN PULP AND PAPER (NAPAP) MODEL

The NAPAP model is a linear optimization model,9

 which uses forecasts of the US economy (e.g.,

growth in population and in the economy) to estimate the quantity of hardwood and softwood trees

harvested for pulpwood in North America each year.10 The model predicts the quantity of pulpwood

harvested each year based on estimated demand and supply curves; the quantity harvested is the quantity

at which these curves intersect.

Inputs to the NAPAP Model

Major inputs to the NAPAP model are:

• macroeconomic forecast data (e.g., estimates of US population growth, and growth in percapita gross domestic product),

• paper manufacturing capacity as of a baseline year,11

• manufacturing costs for each different paper manufacturing process, and

• assumed levels of future harvests from public forests.

 9 A linear optimization model begins with a set of constraints (e.g., profits = revenues–costs; costs = labor

costs + equipment costs + administrative costs + overhead costs) and an objective function (e.g., maximize profits).

The model uses principles of matrix algebra to find the solution (e.g., the total level of output) at which the objective

function is optimized (e.g., profits are maximized).

10 A number of analyses have been conducted using results from the NAPAP models. These include: (1)

USDA Forest Service, RPA Assessment of the Forest and Rangeland Situation in the United States – 1993 Update,

USDA Forest Service Forest Resource Report No. 27 (Washington, DC: USDA Forest Service) 1994, 75 pp.; (2)

Haynes, Richard W., Darius M. Adams, and John R. Mills, 1995, The 1993 RPA Timber Assessment Update, USDA

Forest Service General Technical Report RM-GTR-259 (Fort Collins, CO: Rocky Mountain Forest and Range

Experiment Station) 1995, 66 pp.; (3) Ince, Peter J., 1995, What Won't Get Harvested Where and When: The Effects

of Increased Paper Recycling on Timber Harvest, Yale School of Forestry and Environmental Studies Program on

Solid Waste Policy, Working Paper #3 (New Haven, CT: Yale University) 75 pp.; and (4) Environmental Defense

Fund, Paper Task Force Recommendations for Purchasing and Using Environmentally Preferable Paper: Final

Report of the Paper Task Force (New York, NY: Environmental Defense Fund) 1995, 245 pp.

11 The baseline year for paper manufacturing capacity is 1986. The model predicts how capacity for each

paper manufacturing process changes each year from 1986 onward. The model's predictions for paper manufacturing

capacity in 1995, based on the 1986 baseline as updated, were within five percent of actual 1995 paper

manufacturing capacity.
40

Equations and Assumptions Used in the NAPAP Model

The NAPAP model incorporates equations for the following functions and assumptions:

• estimated pulpwood supply functions (reflecting an increasing supply of pulpwood at

increasing market prices) for three regions in the US (west, south, and north) and two

regions in Canada,

• estimated supply functions for four principal categories of recovered paper – newspapers,

corrugated boxes, mixed papers, and the aggregate of pulp substitutes and high-grade deinking categories – in each supply region (the supply functions reflect an increasing supply

of recovered paper at increasing market prices),

• an unlimited supply of labor and energy at the market price in each supply region,

• a fixed-quantity supply function for residues from manufacture of solid wood products,

such as lumber and plywood, mostly in the form of “pulp chips”,

• demand functions12 for all thirteen principal categories of paper and paperboard products

produced in North America13 (the demand functions reflect increasing demand due to

population growth and growth in the gross domestic product, and decreasing demand at

increasing market prices),

• functions for changes in paper manufacturing capacity (including capacity for both virgin

and recycled inputs), assuming that when demand for paper increases, the investment in

paper manufacturing capacity that is needed to meet demand will be made in those types of

capacity where the ratio of profitability to capital cost is the highest, and

• the ratio of the weight of paper recovered to the weight of the fiber actually used in

manufacturing new paper, after accounting for discards during processing and losses during

manufacturing.

The major assumptions of the NAPAP model include basic assumptions of economic analysis – i.e.,

that markets are perfectly competitive and that paper manufacturers seek to maximize their profits.

Because owners of private forests may not always act to maximize their profits, NAPAP assumes that

they will continue historical patterns of economic behavior (which USDA-FS has modeled through

econometric methods). In addition, the model assumes (1) particular levels of harvests from public

forests, and (2) specific future technology options.14 Finally, the NAPAP pulpwood supply functions are

 12 Separate demand functions are incorporated for US domestic demand, Canadian domestic demand, and

demand from various trading regions for exported paper products from the US and Canada.

13 These paper grades include newsprint, coated and uncoated free sheet, coated and uncoated groundwood,

linerboard, and corrugating medium.

14 The model assumes that certain technologies that existed in 1995 but were not yet commercialized (e.g.,

two newsprint processes with higher yields) would enter the commercial marketplace in the period from 1995-2000.
41

the same for both the baseline and the high recycling scenario. In other words, the supply functions do

not incorporate market feedbacks to account for changes in the age structure of forests or the acreage of

forested land (the age structure of forests could change as increased paper recovery reduces tree harvests,

so that on average trees grow longer; forested acreage could change if higher paper recovery led to

decreased demand for pulpwood and lower pulpwood prices, leading some landowners to convert

forested land to farmland or ranchland).15

For this analysis, the USDA-FS simulated different recovery rates for the two scenarios—for the

year 2000, 50 percent in the baseline scenario, and 55 percent in the high recovery scenario. The

cumulative amounts of paper recovered under the baseline and high recovery scenarios are shown in

Exhibit 3-2.

NAPAP scenarios are generally specified in terms of recovered fiber utilization rates, which differ

somewhat from paper recovery rates. To assure that the model inputs for fiber utilization were consistent

with paper production, recovery, and consumption projections prepared by the American Forest and

Paper Association (AFPA), Franklin Associates, Ltd. (FAL) developed a set of conversion factors.

USDA-FS used these conversion factors to adjust the demand functions for paper products; the effect

was to increase the projections of paper demand and increase the estimates of the equilibrium quantity of

paper produced.16

Trade in forest products between the US and Canada was assumed to be fixed at levels projected

in recent USDA-FS studies. As a result, any change in North American pulpwood harvests due to

increased US paper recovery would be shown in the NAPAP outputs as a change in US pulpwood

harvests. Thus, the forest carbon effects of increased paper recovery in the US were modeled as if those

effects occur entirely in the US.

Outputs of the NAPAP Model

The principal outputs of the NAPAP model, for each of the two scenarios modeled, are annual US

pulpwood harvests from the present to the year 2040. These harvests are broken down into four

categories of pulpwood: (1) softwood roundwood, (2) softwood residues, (3) hardwood roundwood, and

(4) hardwood residues. The NAPAP estimates of pulpwood harvests for each scenario – for selected years

from 1995 to 2040 – are shown in Exhibit 3-3. As the exhibit shows, the NAPAP model projected that

higher paper recovery rates until the year 2016 would result in pulpwood harvests that would be

 15 The NAPAP pulpwood supply functions incorporate projections of timber inventories over time from a

prior run of the linked TAMM and ATLAS models. Ideally, the NAPAP portion of this analysis would have used

two separate projections of timber inventories over time: one projection based on the baseline paper recovery

scenario, and another based on the high paper recovery scenario. NAPAP has recently been revised so that it may

now be run iteratively with TAMM and ATLAS; however, NAPAP did not have that capability at the time this

analysis was conducted.

16 Specifically, the USDA-FS adjusted the NAPAP model by increasing the elasticity of demand for paper

products so that it reflected the historical relationship between (1) paper demand and (2) population and per capita

gross domestic product. "Elasticity of demand" is the extent to which a change in the price of a good will affect the

quantity of the good demanded, and is defined as the percentage change in quantity divided by the percentage change

in price that induced the change in quantity. For example, if the quantity demanded goes down by 2 percent when the

price goes up by one percent, the elasticity of demand is -2. (Specifically, this is the "own-price elasticity" of

demand – because it is measured with respect to the price of the good in question, as distinct from "cross-elasticity" of

demand – which would be measured with respect to the price of a different good.)
42

Exhibit 3-2

Cumulative Paper Recovery

Under the Baseline and High Recovery Scenarios

(Million Short Tons)

Year 2000 2010 2020 2030 2040

A. Baseline Scenario 536 1143 1893 2795 3808

B. High Recovery Scenario 556 1189 1975 2876 3890

C. Incremental Paper 

Recovery Under the High 

Recovery Scenario (B-A) 20 46 81 81 81

Cumulative Paper Recovery

Under the Baseline and High Recovery Scenarios

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

2000 2010 2020 2030 2040

Year

Cumulative Paper Recovery, Million Short Tons

Baseline Scenario

High Recovery Scenario
43

Exhibit 3-3

U.S. Pulpwood Harvests as Predicted by the NAPAP Model

for Selected Years (Million Cubic Feet)

Year 1995 2000 2010 2020 2030 2040

Baseline Scenario 7,152 7,230 7,328 7,808 7,989 8,173

High Paper Recovery 

Scenario 6,982 6,858 7,362 7,808 7,989 8,173

U.S. Pulpwood Harvests as Predicted by the NAPAP Model

6,000

6,500

7,000

7,500

8,000

8,500

9,000

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Year

Million Cubic Feet

Baseline Scenario

High Paper Recovery Scenario
44

substantially below the baseline from 1995 to 2000 (because of the recovered paper substitutes for pulp that would

otherwise be made from trees). From 2005 to 2010, the higher recovery scenario would result

in slightly higher pulpwood harvests than under the baseline,17 and from 2020 onward, annual pulpwood

harvests would be the same under the baseline and high recovery scenarios (because after 2016 the paper

recovery rates would be the same in both scenarios).

3.3 THE TIMBER ASSESSMENT MARKET MODEL (TAMM) AND THE AGGREGATE

TIMBERLAND ASSESSMENT SYSTEM (ATLAS)

TAMM and ATLAS are spatial equilibrium models.18 TAMM models US timber harvests through

2040, and ATLAS models changes in US forest growth, and inventory of growing stock volume, through

2040.19 The two models are interrelated, because timber harvests depend in part on timber inventory, and

timber inventory depends in part on prior harvest levels. (This interrelationship is shown graphically in

Exhibit 3-1 with arrows going in both directions between the two models.) To obtain consistency in the

projections of the two models, an iterative process is used. TAMM outputs for timber removals are used

as inputs to ATLAS, and the resulting ATLAS outputs for forest growth and inventory are used as inputs

to TAMM. This cycle is continued until the difference in projections between one cycle and the next has

been reduced to an acceptably small amount. Note that, to reduce the costs of modeling in this analysis,

no hand linkages were made to transfer price estimates from TAMM back to the Area Models (see

Exhibit 3-1), nor to transfer timberland area estimates from the Area Models back to ATLAS. Implicitly,

the forested area was modeled as being unaffected by increased paper recovery rates.

TAMM's estimates of timber harvests are based on four factors: (1) estimated demand for solid

forest products (such as softwood and hardwood lumber and panel products such as plywood) based on

projected macroeconomic data (e.g., growth in population and in the economy), (2) estimates of

 17 Pulpwood harvests are projected to be higher between 2005 and 2010 under the high recycling scenario

These harvests are expected to be higher due to the modeled consequences of reduced pulpwood harvests before

2005. Because pulpwood harvests before 2005 are projected to be lower under the high recycling scenario, more

pulpwood remains to be harvested in later years. The increasing supply of pulpwood ready for harvest reduces

pulpwood prices, leading to modeled increases in industry demand for non-paper uses. The increased industry

demand results in slightly higher pulpwood harvests after 2005. However, it is important to note that under the

baseline scenario, pulpwood harvests are projected to decline between 2000 and 2005. This is because the increase

in paper recycling during this period is projected to be greater than the increase in paper consumption.

18 A spatial equilibrium model is an optimization model (see footnote 9 in this chapter) that accounts for

costs of transportation of products from producing regions to consuming regions.

19 The descriptions of the TAMM and ATLAS models are drawn from Richard W. Haynes et al, Alternative

Simulations of Forestry Scenarios Involving Carbon Sequestration Options: Investigation of Impacts on Regional

and National Timber Markets, US Department of Agriculture Forest Service, Pacific Northwest Station, August 5,

1993. Two articles which give a more detailed description of the TAMM model are (1) Adams, D.M. and R.W.

Haynes, The 1980 Softwood Timber Assessment Market Model: Structure, Projections, and Policy Simulations,

Forest Science Monograph No. 22 (Washington, DC: USDA Forest Service) 1980, 62 pp., and (2) Adams, D.M. and

R.W. Haynes, A Spatial Equilibrium Model of US Forest Products Markets for Long-Range Projection and Policy

Analysis. In Andersson et al., eds., Systems Analysis in Forestry and Forest Industries, TIMS Studies in the

Management Sciences 21(1986)73-87. Two journal articles which describe analyses based on the TAMM model are

(1) Adams, D.M. and R.W. Haynes, Softwood Timber Supply and the Future of the Southern Forest Economy,

Southern Journal of Applied Forestry 15(1991):31-37, and (2) Adams, D.M and R.W. Haynes, 1991, Estimating the

Economic Impacts of Preserving Old-Growth on Public Lands in the Pacific Northwest, The Northwest

Environmental Journal 6(2):439-441.
45

pulpwood harvests from the NAPAP model, (3) estimates of fuelwood harvests (held constant at recent

levels), and (4) estimates of annual forest growth from ATLAS.

The ATLAS estimates of forest growth and inventory are based on (1) the previous year's

inventory, (2) timber harvests from TAMM, and (3) estimated forest growth parameters.

Inputs to the TAMM Model

Major inputs to the TAMM model are:20

• US pulpwood harvests, from the NAPAP model,

• US fuelwood harvests, from a fuelwood model,

• assumed levels of future timber harvests from public forests, from USDA-FS harvest plans,

• US net imports of forest products, from a trade model,

• changes in US forested acreage over time, from a prior run of forest area models,21

• growth in forest inventory, from the ATLAS model,

• macroeconomic forecast data, e.g., on US housing starts, housing repairs, and remodeling,

and

• installed capacity as of 1990 for producing timber products, such as lumber or plywood,

from harvested trees.

Equations and Assumptions Used in the TAMM Model

The TAMM model incorporates equations for the following:

• estimated timber product supply functions (reflecting an increasing supply of timber

products at increasing market prices) for eight regions in the US, and

• estimated demand functions for US demand for all major uses of lumber and plywood

(reflecting decreasing demand for such products at increasing market prices).

Also, changes in supply capacity for timber products are predicted by the model, based on anticipated

changes in relative regional profitability or rate of return from capital investment.22

 20 Inputs to the TAMM model are documented in Haynes, R.W., An Analysis of the Timber Situation in the

United States: 1989-2040, Gen. Tech. Rep. RM-199 (Ft. Collins, Colorado: USDA Forest Service, Rocky Mountain

Forest and Range Experiment Station) 1990, 286 pp.

21 Although in the NAPAP portion of this analysis, timber inventories over time were not affected by the

different paper recovery rates in the two different scenarios analyzed, in the TAMM and ATLAS models, timber

inventories were estimated independently for the two different scenarios.

22 Specifically, TAMM uses an assumption that changes in capital investment are a function of past changes
46

The major assumptions of the TAMM model include:23

• general assumptions of competitive markets, increasing demand for wood products with

increasing economic activity, profit maximization by owners of lumber and plywood mills,

and continued historical patterns of economic behavior by owners of forest land (these

behavior patterns may not be strictly profit maximizing), and

• specific assumptions regarding particular levels of public harvests, and projected changes in

technology.

In addition, TAMM and ATLAS assume (1) specified levels for net imports of softwood products, and

(2) no net imports of hardwood lumber.

Inputs to the ATLAS Model

Major inputs to the ATLAS model, for each simulation year, are:

• forest inventory at the beginning of the previous period, from a prior ATLAS model run,

• forest removals during the previous period, from the TAMM model,

• changes in forest acreage, from a prior run of a modified version of the Southern Area

Model, and

• state-by-state data on the number of forested acres, and the volume of timber per forested

acre (shown as "Forest Inventory Data" in Exhibit 3-1).

Equations and Assumptions of the ATLAS Model

The ATLAS model incorporates equations that allow the model to simulate shifts in forest

management intensities and consequent changes in yields. Projected shifts in forest management

intensities are based upon (1) the modeled prices of forest products, (2) the costs of various management

practices, and (3) the timber yields associated with each management practice.

The only major assumption in the ATLAS model is that owners of private forests manage their

forests at the level of intensity indicated by recent average forest planting rates. Otherwise, the model is

very simple, relying on a basic mathematical proposition that forest inventory in any period equals forest

inventory in the previous period, plus net growth, minus harvests. Net growth is gross growth less

mortality from fire, storm, insects, and disease.

 

in output (i.e., that manufacturers' expectations about the profitability of capital investment are based on past changes

in output).

23 Assumptions of the TAMM model are documented in the following two reports: (1) Haynes, R.W., An

Analysis of the Timber Situation in the United States: 1989-2040, Gen. Tech. Rep. RM-199. (Fort Collins, Colorado:

USDA Forest Service, Rocky Mountain Forest and Range Experiment Station) 1990, 286 pp.; and (2) Haynes, R.W.,

D.M. Adams, and J.R. Mills, The 1993 RPA Timber Assessment Update, Gen. Tech. Rep. RM-GTR-259 (Fort

Collins, Colorado: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station) 1995, 66 pp.
47

Outputs of the TAMM/ATLAS Models

The outputs of the linked TAMM and ATLAS models are projections, through 2040, of US

inventories of forest growing stock volumes (i.e., the volume of trees growing in forests), annual US

sawtimber harvests, and forest growth.

We used the TAMM/ATLAS data on forest growing stock inventories as inputs to FORCARB.

Exhibit 3-4 shows the growing stock inventories of privately owned forest lands in the US as projected

by the TAMM/ATLAS models. As the exhibit shows, forest growing stock inventories range from one to

two billion cubic feet higher under the high recovery scenario than under the baseline scenario for the

entire simulation period.

3.4 THE FOREST CARBON MODEL (FORCARB)

The Forest Carbon Model (FORCARB) projects US forest carbon storage (including soil, forest

floor, and understory carbon) each year through 2040, based on outputs from the TAMM/ATLAS linked

models.24

Inputs to the FORCARB Model

The major inputs to the FORCARB model are the following:

• forest growing stock inventories – by tree species, age, and region – from the linked

TAMM/ATLAS models, and

• the percentage carbon composition for different species of trees, as grown in different forest

regions.

Assumptions of the FORCARB Model

The Forest Service tracks information in TAMM/ATLAS in terms of growing stock volume, i.e.,

the merchantable portion of trees. Tree volume is larger than growing stock volume, due to additional

volume in non-merchantable portions of the tree such as roots and branches. The FORCARB model uses

the simplifying assumption that tree volume is a constant multiple of growing stock volume. Carbon in

the tree volume in the US forest industry is then estimated based on the percentage carbon content of

different species of trees.

When a tree is harvested, FORCARB no longer counts the carbon remaining in the nonmerchantable portion of the tree (e.g., tree roots) following harvest. In other words, FORCARB uses the

simplifying modeling assumption that the carbon in the non-merchantable portion of the tree is

immediately lost from storage, i.e., converted to CO2 emissions.

 24 The description of the FORCARB model here is drawn from Birdsey, Richard A., and Linda S. Heath,

Carbon Sequestration Impacts of Alternative Forestry Scenarios – Draft (Radnor, PA: US Department of Agriculture

Forest Service, Global Change Research Program), April 1993, pp. 47-51. A number of studies analyzing forest

issues using the FORCARB and HARVCARB models have been published in journal articles. Among these are three

which also explain the FORCARB and HARVCARB models. These three articles are: (1) Plantinga, A.J. and R.A.

Birdsey, 1993, "Carbon fluxes resulting from US private timberland management," Climatic Change 23:37-53; (2)

Heath, L.S. and R.A. Birdsey, 1993, "Carbon trends of productive temperate forests of the coterminous United

States," Water, Air, and Soil Pollution 70:279-293; and (3) Heath, L.S. and R.A. Birdsey, 1993, "Impacts of

alternative forest management policies on carbon sequestration on US timberlands," World Resource Review 5:171-

179.
48

Exhibit 3-4

Growing Stock Inventories of

Privately Owned Forest Lands in the US

As Projected by the TAMM/ATLAS Models

(Billion Cubic Feet)

Year 1995 2000 2010 2020 2030 2040

Baseline Scenario 478 488 515 532 541 545

High Paper Recovery 

Scenario 478 489 517 534 544 548

Growing Stock Inventories of Privately Owned Forest Lands in 

the US as Projected by the TAMM/ATLAS Models

470

480

490

500

510

520

530

540

550

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Year

Billion Cubic Feet

Baseline Scenario

High Paper Recovery Scenario
49

Outputs of the FORCARB Model

The FORCARB model produces as outputs estimates of total US forest carbon inventories, and

estimates of sawtimber and pulpwood harvests, for each year through 2040. The amount of forest carbon

sequestration in a given year equals the increase in forest carbon inventories during that year. If forest

carbon inventories decrease, there would be net emissions, i.e., negative forest carbon sequestration.

Exhibit 3-5 shows the projected carbon inventories of US forests, as predicted by the FORCARB

model, for the baseline and high paper recovery scenarios. The forest carbon inventories on which these

annual changes were based counted carbon in trees and understory (e.g., small trees), but not carbon in

the soil and forest floor. These carbon stocks were not included because of the high level of uncertainty

in estimating and modeling their carbon content.

Exhibit 3-6 shows the change in US forest carbon inventories, expressed as an annual average for

decades from 2000 to 2040. Inventories increase more quickly under the high recycling scenario than

under the baseline recycling scenario, through the decade ending 2010. After 2010, the rate of increase in

forest carbon inventories is essentially the same for both scenarios. This is because the paper recovery

rate is modeled as converging in 2016 to the same rate in both scenarios.

3.5 THE HARVESTED CARBON MODEL (HARVCARB)

The Harvested Carbon Model (HARVCARB) can be thought of as a spreadsheet model that

projects the disposition of harvested wood across four different potential fates, for 50 years into the

future.25 The spreadsheet would consist of estimates of the percentage of each of four types of wood that

will be found in each of four potential fates at ten-year intervals. The four potential fates are (1) products

(a "wood-in-use" sink), (2) landfills, (3) combustion for energy, and (4) aerobic decomposition. There is

some change in the fate of a wood product over time: wood products that are in use in the early years are

likely to be landfilled or combusted in later years. The four different types of wood considered in the

model are softwood and hardwood pulpwood, and softwood and hardwood sawtimber. The model has

separate fate estimates for three regions of the US – west, south, and north.

We combined the average annual sawtimber and pulpwood harvest estimates from FORCARB,

with the fate estimates in the HARVCARB spreadsheet, to obtain estimates of the amount of carbon from

harvested wood that would be found in each of the four potential fates for 50 years into the future.

Inputs to the HARVCARB Model

For this analysis the USDA-FS used, as the only input to the HARVCARB model, the annual

sawtimber and pulpwood harvests (from the FORCARB model).

 25 This Forest Service model is an adaptation of the HARVCARB model developed earlier (C. Row, and R.B.

Phelps , 1990, “Tracing the flow of carbon through the U.S. forest products sector”, Presentation at the 19th World

Congress, International Union of Forestry Organizations, 5-11 August 1190, Montreal, Quebec)., and described

more fully in Row and Phelps, 1996 “Wood Carbon Flows and Storage after Timber Harvest”, in Forests and Global

Change. Vol. 2, R. Neil Sampson and Dwight Hair, eds. American Forests, Washington, DC, p 27-58. This

description of the Forest Service’s implementation of the model is based on R.A. Birdsey and L.S. Heath, op cit, pp.

50-51.
50

Exhibit 3-5

US Forest Carbon Inventory, Trees, Understory, Soil, and Forest Floor

As Predicted by the FORCARB Model

(Million Metric Tons of Carbon)

Year 2000 2010 2020 2030 2040

A. Baseline Scenario 8,641 9,076 9,322 9,442 9,497 

B. High Paper Recovery Scenario 8,665 9,118 9,364 9,480 9,537 

C. Incremental Carbon Stored Under the 

High Paper Recovery Scenario (B-A) 42 24 42 38 40 

US Forest Carbon Inventory

As Predicted by the FORCARB Model

(Trees, Understory, Soil, and Forest Floor)

8,000

8,200

8,400

8,600

8,800

9,000

9,200

9,400

9,600

9,800

2000 2010 2020 2030 2040

Year

Million Metric Tons of Carbon

Baseline Scenario

High Paper Recovery

Scenario
51

Exhibit 3-6

Average Annual Change

In US Forest Carbon Inventories

As Predicted by the FORCARB Model

(Million Metric Tons of Carbon)

Decade Decade Decade Decade Decade

Time Period Ending Ending Ending Ending Ending

2000 2010 2020 2030 2040

A. Baseline Scenario 45.48 43.47 24.56 11.96 5.52

B. High Paper Recovery 

Scenario 47.89 45.25 24.59 11.70 5.74

C. Incremental Annual

Forest Carbon 

Sequestration in the 

High Paper Recovery 

Scenario [B-A] 2.40 1.79 0.03 -0.26 0.22

Average Annual Change in US Forest Carbon 

Inventories

0

10

20

30

40

50

60

2000 2010 2020 2030 2040

Decade Ending

Million Metric Tons of Carbon

Baseline Scenario

High Paper Recovery

Scenario
52

Assumptions of the HARVCARB Model

The HARVCARB model assumes that the disposition patterns for the four types of wood over a

50-year period do not change (e.g., it does not assume any change in the proportion of waste or disposed

wood burned for energy).

Outputs of the HARVCARB Model

In this analysis, HARVCARB provided outputs for the amount of carbon (1) retained in wood-inuse sinks, (2) landfilled, (3) combusted for energy, and (4) aerobically decomposed, for each year from

1995 to 2040. Because other parts of our analysis address landfills and combustion, and aerobic

decomposition has no GHG effects, we used only the estimates of the amount of carbon retained in

wood-in-use sinks (a form of carbon sequestration). We included this amount in our estimate of total

"forest carbon," even though this carbon is stored in locations outside of forests.

Exhibit 3-7 shows the wood-in-use sinks for the baseline and high recovery scenarios from 1990 to

2040, as predicted by the HARVCARB model. As shown in the exhibit, the wood-in-use sinks are

slightly less under the high recovery scenario than under the baseline scenario. The HARVCARB model

predicts this result because under the high recovery scenario, tree harvests are reduced; thus, under the

fixed proportions of the fates of wood assumed in HARVCARB, less wood is available for each of the

fates for wood products, including wood-in-use sinks. As noted above, HARVCARB uses fixed

proportions for the disposition of harvested wood (e.g., paper, housing, and furniture). With increased

paper recovery, wood prices would be expected to decline (due to reduced demand), and more wood

would probably be used for housing and furniture. Because HARVCARB does not account for any

change in the price of wood, and its impacts on wood-in-use sinks, the values in Exhibit 3-7 are probably

a slight underestimate of the amount of carbon in wood-in-use sinks under the high recovery scenario.

3.6 RESULTS

As noted in the introduction to this chapter, we first obtained estimates of the forest carbon

sequestration26 from recovery of paper, and then used those estimates to develop estimates of the forest

carbon sequestration from source reduction of paper.

We estimated the forest carbon sequestration per ton of paper recovered at various points in the

future by dividing the cumulative difference in forest carbon between the high recovery and baseline

scenarios by the cumulative difference in the amount of paper recovered between the two scenarios. To

estimate the forest carbon sequestration in each scenario, we summed the forest carbon sequestration

estimates generated by the FORCARB model and the wood-in-use sink estimates generated by the

HARVCARB model.

The USDA-FS projected forest carbon inventories under the baseline and high recovery scenarios

at several points in time (i.e., 2000, 2010, 2020, 2030, and 2040). The estimates of incremental forest

carbon sequestration per ton of paper recovered vary across time, as shown in Exhibit 3-8. Note that the

estimates of incremental forest carbon sequestration decline from 2000 to 2020, and then stabilize.

 26 As noted earlier, the term forest carbon sequestration is intended to include both the carbon stored in

forests and the carbon stored in wood-in-use sinks.
53

Exhibit 3-7

US Cumulative (Since 1990) Wood-in-Use Sinks

as Predicted by the HARVCARB Model

(Million Metric Tons of Carbon)

Year 2000 2010 2020 2030 2040

A. Baseline Scenario 733 1,216 1,634 2,028 2,381

B. High Paper Recovery Scenar 726 1,208 1,630 2,026 2,379

C. Change in Carbon Storage 

in Wood-in-Use Sinks [B-A] -7 -8 -4 -2 -2

2000 2010 2020 2030 2040

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

Million Metric Tons of Carbon

Change in Carbon Storage in Wood-in-Use Sinks 

Between the Baseline and High Paper Recovery Scenarios,

as Predicted by the HARVCARB Model

(Million Metric Tons of Carbon)
54

An important goal of this analysis is to develop "emission factors" or point estimates that enable

policymakers and the public to quantify and compare the GHG impacts from managing specific waste

materials in specific ways. Originally, these emission factors were intended to estimate progress made by

the US in meeting its commitment to reduce GHG emissions by the year 2000. However, in December

1997, the parties to the UN Framework Convention on Climate Change agreed to an historic Protocol on

climate change, the Kyoto protocol. The protocol establishes a US target of reducing GHG emissions to a

level 7 percent below 1990 emissions over a 5 year period from 2008 through 2012. If the US ratifies the

Kyoto protocol, these emissions factors may be used to help the US evaluate progress in meeting the

emission reductions set forth in the protocol. The emission factors developed here are also intended to

aid in the evaluation of voluntary programs, which, in a time of uncertain but inevitable reductions in

emissions, are especially important. Given the uncertainty of the analysis, the timeframes chosen for

developing emission factors are appropriate for the evaluation of voluntary programs.

In developing these estimates, we chose the forest carbon sequestration factor for the period

ending in 2010 as the best approximation of the forest carbon benefits from increasing source reduction

and recycling by the year 2000. This value – 0.73 MTCE per short ton of paper recovered – falls between

the higher value for 2000 and the lower values for later years in the simulation period. We selected this

value to approximate the short-term carbon sequestration benefits of source reduction and recycling

because it balances the following: (1) relatively high carbon sequestration benefits will be achievable by

the year 2000; (2) actions taken to bring about increases in source reduction and recycling by the year

2000 will have lingering effects beyond the year 2000; (3) forest carbon sequestration benefits drop

somewhat over time; and (4) there is more uncertainty associated with the long-term carbon sequestration

effects and market response (because model predictions far into the future are more uncertain than nearterm predictions). In sum, we believe that the value for the year 2010 strikes the best balance in capturing

the relatively higher short-term benefits of forest carbon sequestration, and recognizing that these

benefits decline over time.27 In addition, if the US ratifies the Kyoto protocol, 2010 fits well with the

proposed timeframe for achieving emission reductions.

As noted above, we did not consider in this analysis carbon sequestration in forest soils or the

forest floor. Research on forest soils is much more speculative than the characterization of the carbon in

trees. It seems more likely than not that some quantity of carbon is sequestered in forest soils (and should

be added to the forest carbon sequestration totals), but there are no reliable estimates of the actual

amounts.

Using the forest carbon sequestration estimate for paper recovery, we developed estimates for

forest carbon sequestration associated with source reduction, as shown in Exhibit 3-9. We estimated

source reduction values under two assumptions: that source reduction displaces only virgin inputs, and

that it displaces the current mix of virgin and recycled inputs.28 We estimated that forest carbon

sequestration for source reduction, assuming displacement of virgin inputs, is the same as for paper

 27 The impact of increased paper recycling and source reduction on forest growing stock inventories (3 billion

cubic feet in addition to the baseline scenario of 541 cubic feet in 2030, as shown in Exhibit 3-4) is only 0.5 percent.

This amount is less than the likely statistical error in measuring the inventories. Although the estimated effect is a

small proportion of the total inventory, the relationship between recycling and stocks is clear, and the magnitude of

the effect is plausible and is significant on a per-ton basis.

28 Source reduction may conceivably displace 100 percent virgin inputs if the quantity of paper recovered

does not change with source reduction, and all recovered paper is used to make new paper. In that case, if the

quantity of paper manufactured is reduced through source reduction, all of the reduction in inputs would come from

virgin inputs. It is more likely, however, that source reduction reduces both virgin and recycled inputs.
55

Exhibit 3-8

Increased Forest Carbon Storage Per Ton of Paper Recovered

Cumulative Change

Between the Baseline

and High Paper Recovery

Scenarios for: 2000 2010 2020 2030 2040

A. Forest Carbon Stocks* (million MTCE) 24.0 41.9 42.2 39.7 41.9

B. Wood-in-Use Stocks (million MTCE) -7.0 -8.0 -4.0 -2.0 -2.0

C. Incremental Carbon Stored (million MTCE) [A+B] 17.0 33.9 38.2 37.7 39.9

D. Incremental Paper Recovery (million short tons) 19.7 46.2 81.4 81.4 81.4

E. Incremental Carbon Sequestration (MTCE/ton) [C/D] 0.9 0.7 0.5 0.5 0.5

*Includes trees and understory.

Increased Forest Carbon Sequestration Per Ton of Paper Recovered

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

2000 2010 2020 2030 2040

Year

MTCE/ton of paper
56

recovery. Although this approach for estimating the effects of source reduction does not consider the loss

rates associated with paper recovery, we believe it is a reasonable first approximation. To estimate the

forest carbon sequestration for source reduction assuming displacement of the current mix of inputs, we

used an additional factor, i.e., the percentage of virgin inputs in the current mix of inputs. For this

calculation (column "d" in Exhibit 3-9), we account for the fact that displacement of recycled inputs does

not have any impact on forest carbon sequestration.

Exhibit 3-9

Forest Carbon Sequestration

Per Ton of Paper Recovered or Source Reduced

(a)

Material

(b)

Recycling,

Recovering

One

Incremental

Ton of Paper

(MTCE)

(c)

Source

Reduction,

Assuming

Displacement of

One Ton of Paper

Made from the

Virgin Inputs

(MTCE)

(d)

Percent

Virgin

Inputs in

the Current

Mix of

Inputs

(e)

(e = b * d)

Source Reduction,

Assuming

Displacement of One

Ton of Paper Made

from the Current

Mix of Virgin and

Recycled Inputs

(MTCE)

Newspaper 0.73 0.73 65% 0.48

Office Paper 0.73 0.73 76% 0.56

Corrugated

Cardboard

0.73 0.73 60% 0.44

3.7 LIMITATIONS OF THE ANALYSIS

Any analysis based on a complex system of models is subject to the limitations introduced by each

model in the system. The limitations of each component model derive from (1) the assumptions made in

developing the model, (2) the input equations used in the model, and (3) the potential impact of factors

not included in the model. Because of these limitations, the actual behavior of markets for paper and

other forest products (and the actual choices made by owners of private forest lands) could differ from

those predicted by the system of forest models. We believe that most of these limitations would tend to

bias estimates under the baseline and high recycling scenarios in the same direction – so that the estimated

differences between the two scenarios should be relatively accurate. However, some limitations could

result in unequal bias in the estimates, leading to biased estimates of the differences.

This section first discusses limitations associated with the geographic scope of the analysis.

Secondly, we discuss limitations that could bias the estimates. Limitations that could bias both scenarios

in the same direction are listed next. This section concludes with a brief discussion of the uncertainties

introduced by the choice of a time period over which incremental forest carbon sequestration is

estimated.
57

Limitations of Geographic Scope of Analysis and Results

Although the goal of this analysis is to estimate the impact of paper recycling and source reduction

on US GHG emissions, the actual effects would occur not only in the US but in Canada and other

countries.

• The Forest Service models treat forest product markets in the US and Canada as a single

integrated economic and biological system. But they do not treat Canadian forest inventories

in the same way and degree of detail as US forest inventories. The estimated impacts of

increases in recycling and source reduction were treated as impacts on U.S. forests. Because

much of the economically marginal paper production is from Canadian pulp sources, source

reduction, in particular, would lower demand for Canadian timber. In any case, the effects

would actually be shared by U.S. and Canadian forests.

• More than 20 percent of the paper currently recovered in the two countries is exported. Some

proportion of the increased amounts of recycled paper—probably more than 20 percent—

would undoubtedly be exported. Current exports comprise 43 percent of the world trade in

recovered paper. The major buyers of this paper are developing countries in Asia and Latin

America, with Korea, Taiwan, and Mexico being major destinations. The alternative sources

of fiber for the paper industry in these countries are pulp and fiber from non-forest sources

(agricultural refuse, hemp, bamboo, and rubber and palm oil trees). Very little comes from

forest harvests; however, forests in these countries are not necessarily managed on a

sustainable basis. It is difficult to determine which of these effects would dominate—

displacement of non-forest fiber (with no forest carbon impact) or displacement of

unsustainably managed forest fiber (with a benefit larger than that in US forests). 29

• NAPAP does not account for any effects of lower pulpwood prices (due to higher paper

recycling rates) on net exports of US pulpwood to non-Canadian markets. Lower pulpwood

prices would be expected to result in increased exports, and possibly changes in foreign timber

inventories. Though US pulpwood exports are currently less than one percent of US pulpwood

production, some virgin pulp fiber is now being exported from southern and western ports in

the form of pulp chips. The future potential for pulp chip exports is difficult to estimate.

• The competition to U.S. and Canadian exports of both recovered and newly manufactured

paper is likely to come from two sources. First, all other developed countries are also likely to

intensify recycling and source reduction programs, with additional recovery of paper fiber.

Second, a major developing source of fiber for paper is the establishment of intensive forest

plantations in tropical and southern hemisphere countries, particularly New Zealand,

Australia, Brazil, Chile, and South Africa, and Indonesia. The effect of additional world

sources of paper fiber from developed countries on these forest plantation programs is difficult

to estimate.

 29 A comprehensive description of the world paper industry, its fiber sources, and environmental concerns is

in IIED. 1996. Towards a Sustainable Paper Cycle. International Institute for Environment and Development.

London. 258 p. This study, prepared for the World Business Council for Sustainable Development, treats many of

the issues covered in this chapter, but on a global basis.
58

Limitations Expected to Bias the Results

Two limitations in the system of forest sector models could result in biased estimates of the

incremental forest carbon sequestration from increased paper recycling. They are as follows:

• The modeling system does not account for any conversion of US forest land to farmland or

rangeland that might occur in response to lower prices for pulpwood due to higher paper

recycling rates. The NAPAP model did not account for potential changes in timber

inventory in the near term (due to lower harvests associated with higher paper recovery),

nor potential changes in forest acreage in the longer term (if higher paper recovery

depresses pulpwood prices enough to induce landowners to convert forested acreage to

other uses). The TAMM and ATLAS models likewise did not allow for long-term changes

in forested acreage due to increased paper recovery. These effects, however, may be small.

Converting forest land to agriculture, or to industrial, commercial, or residential uses is far

more likely to result from much higher land values for crops or development, if the land is

suitable or in a favorable location.

• This analysis did not consider carbon sequestration in forest soils and forest floors, because

of the high level of uncertainty in projecting changes in carbon storage. Nonetheless,

projections of carbon storage in forest soils and floors under the baseline and high recycling

scenarios, as generated by the FORCARB model, suggest that incremental carbon storage

under the high recycling scenario could be slightly higher than shown here, if storage in

soils and the forest floor were included.

Limitations Not Expected to Bias the Results

We expect that several limitations in the system of forest models would bias – to about the same

extent – the estimates of forest carbon sequestration in the baseline and high recycling scenarios – and thus

would not result in significant bias in the estimate of the difference in forest carbon sequestration

between the two scenarios. These limitations are as follows:

• The macroeconomic forecasts used in the models (e.g., for population growth and growth in

per-capita gross domestic product) are simply forecasts, and may turn out to be inaccurate.

• The historical supply and demand functions used in the models may change in the future.

For example, (1) demand for newspapers may drop sharply due to competition from

electronic news media, or (2) improved technologies or tree diseases not anticipated in the

models may significantly change the cost of producing forest products.

• Future harvests from public forest lands may be different from those projected.

The Use of a Point Estimate for Forest Carbon Sequestration

As shown in Exhibit 3-8, estimates of forest carbon sequestration due to increased paper recycling

vary over time. As noted above, in choosing a single point estimate, we selected the time period that best

balances the competing criteria of (1) capturing the long-term forest carbon sequestration effects, and (2)

limiting the uncertainty inherent in projections made well into the future. The range of forest carbon

sequestration estimates over time, and the limitations of the analysis discussed above, indicate that there

is considerable uncertainty in the point estimate selected. In comparison to the estimates of other types of
59

GHG emissions and sinks developed in other parts of this analysis, the magnitude of forest carbon

sequestration is relatively high; based on these forest carbon sequestration estimates, source reduction

and recycling of paper are found to have substantial net GHG reductions. Because paper products

comprise the largest share of municipal waste generation (and the largest volumes of waste managed

through recycling, landfilling, and combustion), it is important to bear in mind the uncertainty in the

forest carbon sequestration values when evaluating the results of this report.
60

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61

4. SOURCE REDUCTION AND RECYCLING

This chapter presents estimates of GHG emission reductions and carbon sequestration resulting

from source reduction and recycling of ten materials: newspaper, office paper, corrugated boxes, mixed

paper, aluminum cans, steel cans, glass containers, and three types of plastic containers (LDPE, HDPE,

and PET).

To estimate GHG emissions associated with source reduction and recycling (and other MSW

management options), we used a baseline scenario in which the material is manufactured from the current

mix of virgin and recycled inputs, but has not yet been disposed or recycled. Thus, the baseline for each

material already incorporates some emissions from raw materials acquisition and manufacturing using

the current mix of virgin and recycled inputs.1

 Using this measurement convention, it follows that source

reduction2

 reduces GHG emissions from the raw material acquisition and manufacturing phase of the life

cycle for all materials. Moreover, source reduction of paper results in forest carbon sequestration (as

discussed in Chapter 3).

Manufacturing from recycled inputs generally requires less energy, and thus lower GHG

emissions, than manufacturing from virgin inputs. Our estimates of the GHG implications of recycling,

which are developed in this chapter, show that recycling reduces GHG emissions for each of the

materials studied.

4.1 GHG IMPLICATIONS OF SOURCE REDUCTION

When a material is source reduced (i.e., less of the material is made), the greenhouse gas

emissions associated with making the material and managing the post-consumer waste are avoided. In

addition, when paper products are source reduced, trees that would otherwise be harvested are left

standing and continue to grow, so that additional carbon is sequestered in forests. The modeled estimates

of forest carbon sequestration benefits are discussed in detail in Chapter 3. The additional carbon

sequestered due to source reduction is counted in the same way as a reduction in GHG emissions.

As discussed above, under the measurement convention used in this analysis, source reduction has

(1) negative raw material and manufacturing GHG emissions (i.e., it avoids baseline emissions

attributable to current production), (2) forest carbon sequestration benefits for paper products (also

treated as negative emissions, as estimated in Chapter 3), and (3) zero waste management GHG

emissions. Exhibit 4-1 presents the GHG implications of source reduction. The values for forest carbon

sequestration were copied from Exhibit 3-8.

 1

 There are no raw materials acquisition and manufacturing emissions attributable to food scraps and yard

trimmings in this analysis.

2

 In this analysis, the values reported for source reduction apply to material lightweighting or extension of a

product's useful life. We assume no substitution by another material or product, and thus we assume no offsetting

GHG emissions from another material or product. Thus, the data do not directly indicate GHG effects of source

reduction that involves material substitution. Considerations for estimating the GHG effects of material substitution

are presented in Section 4.3 below.
62

Exhibit 4-1

Greenhouse Gas Emissions for Source Reduction

(MTCE/Ton of Material Source Reduced)

Net Emissio

For Current For 100% For Current For 100% For Curren

Material Mix of Inputs Virgin Inputs Post-Consumer Mix of Inputs Virgin Inputs Mix of Inpu

Newspaper -0.48 -0.55 0.00 -0.43 -0.73 -0.Office Paper -0.52 -0.56 0.00 -0.50 -0.73 -1.Corrugated Cardboard -0.41 -0.38 0.00 -0.38 -0.73 -0.

Mixed Paper  Broad Definition NA NA NA NA NA N Residential Definition NA NA NA NA NA N

 Office Paper Definiti NA NA NA NA NA NAluminum Cans -2.98 -5.39 0.00 0.00 0.00 -2.Steel Cans -0.84 -1.12 0.00 0.00 0.00 -0.Glass -0.14 -0.16 0.00 0.00 0.00 -0.HDPE -0.61 -0.70 0.00 0.00 0.00 -0.LDPE -0.89 -0.89 0.00 0.00 0.00 -0.PET -0.98 -1.16 0.00 0.00 0.00 -0.Food Waste NA NA NA NA NA NYard Waste NA NA NA NA NA NMixed MSW NA NA NA NA NA N

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

Avoided GHG Emissions 

from Raw Materials 

Acquistion and Manufacturing

Change in Forest Carbon Storage 

(Minus sign indicates incremental 

carbon storage)
63

In order to compare source reduction to other solid waste management options, one compares the

GHG reductions from source reduction to the life cycle GHG emissions of the other solid waste

management option (e.g., landfilling). With this approach, policy makers can evaluate, on a per ton basis,

the overall difference in GHG emissions between (1) source reducing one ton of material and (2)

manufacturing and then managing (post-consumer) one ton of the same material. Such comparisons are

made in the executive summary chapter and in Chapter 8 of this report. Overall, source reduction has

lower GHG emissions than the other waste management options.

4.2 GHG IMPLICATIONS OF RECYCLING

When a material is recycled, it is used in place of virgin inputs in the manufacturing process,

rather than being disposed of and managed as waste. 3 As with source reduction of paper products,

recycling of paper also results in forest carbon sequestration.

Although most of the materials considered are modeled as being recycled in a "closed loop" (e.g.,

newspapers are recycled into new newspapers), two of the specific products considered – office paper and

corrugated boxes – are often recycled in an "open loop" (i.e., they are recycled into more than one

product). We modeled office paper as being recycled into either office paper or tissue paper, in

proportions of 45 percent and 55 percent, respectively. Corrugated boxes are modeled as being recycled

into either corrugated boxes (70 percent) or folding boxes (30 percent).4

In addition, several paper types are recycled under the general heading of “mixed paper.”5 Mixed

paper is included in this analysis because it is recycled in large quantities, and is an important class of

scrap material in many recycling programs. However, it is difficult to present a single definition of mixed

paper because each mill using recovered paper defines its own supply which varies with the availability

and price of different grades of paper. Therefore, for the purpose of this report, we identified three

different definitions for mixed paper—broad, office, and residential. The composition of each is

presented in Exhibit 4-2. The broad definition of mixed paper includes almost all printing-writing paper,

folding boxes, and most paper packaging. Mixed paper from offices includes copy and printer paper,

stationary and envelopes, and commercial printing. The typical mix of papers from residential curbside

pick-up includes high-grade office paper, magazines, catalogs, commercial printing, folding cartons, and

a small amount of old corrugated containers. Mixed paper as characterized by the broad and residential

definitions can be remanufactured via an open loop into recycled boxboard. Mixed paper from offices is

typically used to manufacture commercial paper towels.

Although our modeling approach addresses some of the most important open loops, it does not

fully reflect the prevalence and diversity of open loop recycling. For example, (1) office paper,

corrugated cardboard, and mixed paper are recycled into a variety of manufactured products, not just the

 3

 Note that when paper is manufactured from recycled inputs, the amount of paper sludge produced is

greater than when paper is made from virgin inputs. (This is because recycled paper has more short fibers, which

must be screened out.) We made a preliminary estimate of the GHG emissions from paper sludge managed in

landfills; our results indicated that net GHG emissions (i.e., methane emissions minus carbon sequestration) were

close to zero. Because the emissions are small and highly uncertain, no quantitative estimate is included in this

report.

4 These percentages were provided by Franklin Associates, Ltd. in working papers, October 1995.

5 This report also includes estimates for “mixed recyclables,” i.e., a mixture of the principal paper, metal,

and plastic materials that are recycled. Mixed recyclables are discussed in Chapter 8.
64

two products we selected for each, and (2) most of the other materials are also recycled to some degree in

open loops, which are typical outcomes of recycling. Resource limitations prevent an exhaustive analysis

of all the recycling possibilities for each of the materials analyzed.

Exhibit 4-2

SUMMARY OF MIXED PAPER SCENARIOS

(Composition as a percentage of total)

Paper Grade

All Paper and

Paperboard in

MSW (1)

Mixed Paper:

Broad Definition (2) Mixed Paper:

Offices (3)

Mixed Paper:

Single-Family

Residential (4)

Uncoated groundwood paper 4.9% 4.9% 7.9% 2.2%

Coated free sheet paper 5.0% 12.0% 13.9% 11.5%

Coated groundwood paper 4.3% 11.5% 30.7% 17.7%

Uncoated free sheet paper 14.3% 37.6% 41.6% 18.4%

Cotton fiber paper 0.1% 0.4% 1.8% 0.2%

Bleached bristols 1.5% 3.9% 4.1% 2.8%

Newsprint 13.3% 2.9% 2.9%

Virgin corrugated boxes 29.6% 12.2%

Recycled corrugated boxes 6.8% 2.8%

Unbleached kraft folding boxes 1.5% 5.7% 4.1%

Bleached kraft folding boxes 2.8% 5.7% 5.8%

Recycled folding boxes 3.0% 7.9% 8.0%

Bleached bags and sacks 0.4% 1.0% 1.6%

Unbleached bags and sacks 2.1% 5.6% 9.0%

Unbleached wrapping paper 0.1% 0.2%

Converting paper 0.3%

Special industrial paper 1.3%

Other paperboard 2.5%

Paper plates and cups 1.2%

Tissue, towels 3.9%

Set-up boxes 0.3% 0.7% 0.6%

Other paper packaging 0.8%

Totals 100.0% 100.0% 100.0% 100.0%

(1) All grades of paper and paperboard in MSW.

(2) Excludes newspapers, old corrugated containers, tissue produce, paper plates and cups, converting and special

industrial papers, nonpackaging paperboard such as album covers and posterboard, and paper labels.

(3) Includes the high-grade papers (ledger and computer printout) as well as stationery, mail, magazines, and

manila folders. Could be recovered as “File Stock.”

(4) Represents a typical collection of mixed paper from a single-family curbside program. Includes printingwriting papers, corrugated boxes, folding cartons, and bags and sacks.

Source: Working papers prepared by Franklin Associates. Ltd., October 1997.

For both open and closed loops, we assumed that increased recycling does not change overall

demand for products. In other words, we assumed that each incremental ton of recycled inputs would

displace virgin inputs in the manufacturing sector.

When any material is recovered for recycling, some portion of the recovered materials is

unsuitable for use as recycled inputs (these materials are discarded either in the recovery stage or in the

remanufacturing stage). Consequently, less than one ton of material is generally made from one ton of

recovered inputs. These losses may be expressed as "loss rates." Franklin Associates, Ltd. and the Tellus
65

Institute provided estimates of loss rates for each material; the averages of these values are shown in

Exhibit 4-3.

The avoided GHG emissions from remanufacture using recycled inputs is thus calculated as the

difference between (1) the GHG emissions from manufacturing a material from 100 percent recycled

inputs, and (2) the GHG emissions from manufacturing an equivalent amount of the material (accounting

for loss rates) from 100 percent virgin inputs.

Explanatory notes: The value in column "b" accounts for losses such as recovered newspapers that were

unsuitable for recycling because they were too wet. Column "c" reflects process waste losses at the

manufacturing plant or mill. Column "d" is the product of the values in columns "b" and "c."

Exhibit 4-4 shows the greenhouse gas implications of recycling each material. It sums, for each

material, the differences between manufacture from virgin and recycled inputs for (1) energy-related

greenhouse gas emissions (both in manufacturing processes and transportation), (2) process non-energyrelated greenhouse gas emissions, and (3) forest carbon sequestration. Our method of accounting for loss

rates yields estimates of GHG emissions on the basis of metric tons of carbon equivalent (MTCE) per

short ton of material collected for recycling (rather than emissions per ton of material made with recycled

inputs).

We recognize that some readers may find it more useful to evaluate recycling in terms of tons of

recyclables as marketed rather than tons of materials collected. To adjust the emission factors reported in

Exhibit 4-4 for that purpose, one would scale up the recycled input credits shown in Columns b and d of

that Exhibit by the ratio of manufacturing loss rate to total loss rate (i.e., Exhibit 4-3 Column “c” divided

by Column “d”).

Exhibit 4-3

Loss Rates For Recovered Materials

(a) (b) (c) (d)

(d = b * c)

Tons of

Percent of Product Made Tons of

Recovered Per Ton of Product Made

Materials Recycled Inputs Per Ton of

Retained in the in the Recovered

Material Recovery Stage Manufacturing Stage Materials

Newspaper 90 0.85 0.77

Office Paper 88 0.75 0.66

Corrugated Cardboard 92 0.84 0.77

Aluminum Cans 95 0.87 0.83

Steel Cans 98 1.00 0.97

Glass 90 0.98 0.88

HDPE 87 1.00 0.87

LDPE 87 1.00 0.87

PET 87 1.00 0.87
66

Another way that recycling projects can be measured is in terms of changes in recycled content of

products. To evaluate the effects of such projects, one could use the following algorithm6

:

Trecyc = Tprod*(RCp-RCi)/L, where

Trecyc = tons of material recycled, as collected

Tprod = tons of the product with recycled content

RCp = recycled content (in percent) after implementation of the project

RCI = recycled content (in percent) initially

L = loss rate (from Exhibit 4-3, column “d”).

Then, one could use the emission factors in this report directly with the tons of material recycled (as

collected) to estimate GHG emissions.

In order to compare GHG emissions from recycling to those attributable to another solid waste

management option such as landfilling, one compares the total GHG emissions from recycling the

material to the GHG emissions from managing the disposal of the same material under the other option.

The baseline for a given material (which includes GHG emissions from raw materials acquisition and

manufacturing for the current mix of virgin and recycled inputs) for both options is the same. Overall,

because recycling reduces the amount of energy required to manufacture materials (as compared to

manufacture with virgin inputs) and leads to avoided process non-energy GHG emissions, recycling has

lower GHG emissions than all other waste management options except for source reduction.

4.3 SOURCE REDUCTION WITH MATERIAL SUBSTITUTION

As noted above, our analysis of source reduction is based on an assumption that source reduction

is achieved by practices such as lightweighting, double-sided copying, and material reuse. However, it is

also possible to source reduce one type of material by substituting another material. Analyzing the GHG

impacts of this type of source reduction becomes more complicated. Essentially, one would need to

estimate the net GHG impacts of (1) source reduction of the original material, and (2) manufacture of the

substitute material and its disposal fate.

A quantitative analysis of source reduction with material substitution was beyond the scope of

this report because of the large number of materials that could be substituted for the materials analyzed in

this report (including composite materials, e.g., a composite of paper and plastic used in juice boxes), and

the need for application-specific data. However, where both the original material and the substitute

material are addressed in this report, the GHG impacts of source reduction with material substitution may

be estimated.

The estimate would be based on (1) the data provided in this report for the material that is source

reduced, (2) the mass substitution rate for the material that is substituted, and (3) data in this report for

the material substituted. The mass substitution rate is the number of tons of substitute material used per

ton of original material source reduced. Note, however, that in calculating the mass substitution rate, one

should account for any difference in the number of times that a product made from the original material

is used prior to waste management, compared to the number of times a product made from the substitute

material will be used prior to waste management.

 6

 This approach would apply only where the products with recycled content involve the same “recycling

loop” as the ones on which the values in this report are based (e.g., aluminum cans are recycled in a closed loop into

more aluminum cans).
67

To estimate the GHG impacts of source reduction with material substitution (per ton of material

source reduced), one should consider the following: a specific baseline scenario, including waste

management; an alternative scenario, involving the substitute material and a waste management method;

the number of tons of material used in each scenario, using the mass substitution rate;

the net GHG emissions for the baseline; the GHG impacts of source reduction of the original material;

the GHG impacts of manufacturing the substitute material; and the GHG impacts of waste management

for the substitute material. Among other factors, these considerations will allow for a comparison of net

GHG emissions from source reduction with material substitution to the baseline.

4.4 LIMITATIONS OF THE ANALYSIS

Because the data presented in this chapter were developed earlier in Chapters 2 and 3, the

limitations discussed in those chapters also apply to the values presented here. Four other limitations are

as follows:

• There may be GHG impacts from disposal of industrial wastes, particularly paper sludge at

paper mills. Because of the complexity of analyzing these second-order effects, and the lack

of data, we did not include them in our estimates. We did perform a screening analysis for

paper sludge, however, based on (1) data on sludge generation rates and sludge composition

(i.e., percentage of cellulose, hemicellulose, lignin, etc. in sludge),7

 and (2) professional

judgment on the methane generation rates for cellulose, etc. The screening analysis

indicated that net GHG emissions (methane emissions minus carbon sequestration) from

paper sludge are probably on the order of 0.00 MTCE per ton of paper made from virgin

inputs to 0.01 MTCE per ton for recycled inputs. Our worst case bounding assumptions

indicated maximum possible net GHG emissions ranging from 0.03 to 0.11 MTCE per ton

of paper (depending on the type of paper and whether virgin or recycled inputs are used).

• The recycling results are reported in terms of GHG emissions per ton of material collected

for recycling. Thus, the emission factors incorporate assumptions on loss of material

through collection, sorting, and remanufacturing. There is uncertainty in the loss rates –

some materials recovery facilities and manufacturing processes may recover or use recycled

materials more or less efficiently than estimated here.

• The models used to evaluate forest carbon sequestration and those used to evaluate energy

and non-energy emissions differ in their methods for accounting for loss rates. Although

one can directly adjust the emission factors reported here for process emissions, so that they

apply to tons of materials as marketed (rather than tons as collected), there is no

straightforward way to adjust the forest carbon estimate.

• We used a simple representation of recycling as mostly closed loop. We considered open

loop processes for only three products, and even there our open loop model was simplified –

we considered only two products that might be made from each original product.

 7

 ICF Memorandum to EPA Office of Solid Waste, Methane Generation from Paper Sludge, December

1996.
68

Explanatory notes for Exhibit 4-4: Columns "b" and "c" show the reduction in process energy GHGs and transportation making each material from recycled inputs, rather than virgin inputs. The values in columns "b" and "c" are based on (1) th

Exhibit 4-4 Greenhouse Gas Emissions for Recycling (MTCE/Ton of Material Recovered) (a) (b) (c) (d) (e) 

Recycled Input Recycled Input Recycled Input 

Credit*: Credit*: Credit*: 

Process Transportation Process Non- Forest Carbon 

Material Energy Energy Energy Sequestration 

Newspaper -0.14 0.01 0.00 -0.73 Office Paper -0.07 -0.01 0.00 -0.73 Corrugated Cardboard 0.03 0.00 0.00 -0.73 Mixed Paper Broad Definition 0.09 -0.02 0.00 -0.73  Residential Definition 0.09 -0.02 0.00 -0.73  Office Paper Definition -0.09 -0.02 0.00 -0.73 Aluminum Cans -2.49 -0.07 -1.32 0.00 Steel Cans -0.57 -0.01 0.00 0.00 Glass -0.04 0.00 -0.04 0.00 HDPE -0.30 -0.02 -0.05 0.00 LDPE -0.44 -0.01 -0.05 0.00 PET -0.58 -0.02 -0.03 0.00 

Note that totals may not add due to rounding and more digits may be displayed than are significant. NA: Not applicable, or in the case of composting of paper, not analyzed. *Material that is recycled after use is then substituted for virgin inputs in the production of new products. This credit represents the difference in emissions that results from using recycled inputs rather than virgin inputs. It accounts for loss rates in collection, processing, and remanufacturing. Recycling credit is based on weighted average of closed and open loop recycling for office paper, corrugated cardboard, and mixed paper. All other estimates are for closed loop recycling.
69

Explanatory notes continued: related GHG emissions between making one ton of the material from 100% virgin inputs ainputs, multiplied by (2) the estimated tons of material manufactured from one ton of material recovered, after accounting recovery and remanufacturing stages. We first estimated the values in columns "b" and "c" based on data provided by Fran(FAL), as shown in Exhibits 2-2 through 2-5. Then we estimated the same values based on data provided by the Tellus InsExhibits 2-6 through 2-9. Finally, we averaged the two sets of estimates to obtain the values shown in columns "b" and "c.corrugated cardboard and two of the mixed paper definitions, the process energy GHG emissions are higher when using rewhen using virgin inputs (as shown by positive values in column "b"). This is because the manufacture of corrugated cardbproduct of open loop recycling of these types of mixed paper) from virgin inputs uses a high proportion of biomass fuels—emissions are not counted as GHG emissions (see the discussion of biogenic CO2 emissions in Chapter 1). Still, because o

sequestration, the net GHG emissions from recycling corrugated cardboard and mixed paper are lower than the net GHG emanufacture of corrugated cardboard from virgin inputs.

For column "d," which presents the process non-energy GHG emissions from recycling, we used (1) data provided b

difference in process non-energy GHG emissions between making one ton of the material from 100% virgin inputs, and froinputs (as shown in the second to last column of Exhibits 2-2 and 2-4) multiplied by (2) the estimated amount of material mfrom one ton of material recovered, after accounting for loss rates in the recovery and remanufacturing steps.

Next, in column "e," the exhibit shows the estimated forest carbon sequestration from recycling of paper products, a

3. The last column (column "f") sums columns "b" through "e" to show the GHG implications of recycling each material
70

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71

5. COMPOSTING

This chapter presents estimates of greenhouse gas (GHG) emissions and carbon sequestration from

composting of yard trimmings and food scraps.1

Composting consists of the aerobic decomposition of organic materials. In controlled composting

operations, organic materials are typically placed in piles that have sufficient moisture and aeration for

aerobic microorganisms (e.g., bacteria) to decompose the materials. Aeration may be provided by turning

the piles; this prevents the development of low-oxygen conditions in the piles which could lead to

anaerobic decomposition, with its associated noxious odors and methane generation. Nitrogen may be

added to a compost pile to achieve a carbon/nitrogen ratio that is optimal for rapid composting.

As organic materials are composted, they are converted into a form of organic matter known as

humus. When the compost is added to soil, the humus decomposes further. At both stages of

decomposition, much of the carbon in the original material is released in the form of carbon dioxide.

Because this carbon dioxide is biogenic in origin, it is not counted as a greenhouse gas (as explained in

Section 1.7). However, it is conceivable that composting could result in (1) methane emissions from

anaerobic decomposition, or (2) long-term carbon sequestration in the form of undecomposed carbon

compounds. In addition, with centralized composting there are non-biogenic CO2 emissions from

collection and transportation of the organic materials to the central composting site, and from mechanical

turning of the compost pile.2

 Therefore, we investigated the extent to which composting might result in

(1) methane emissions, (2) carbon sequestration in soils to which compost is applied (for yard trimmings,

we considered the incremental carbon sequestration from composting, beyond the carbon sequestration

expected when yard trimmings are left in place on the ground) and (3) CO2 emissions from transportation

of compostable materials, and turning of the compost piles.

Our analysis suggests that composting, when properly done, does not result in methane generation,

and results in minimal carbon sequestration for yard trimmings. For centralized composting, slight GHG

emissions result from transportation of material to be composted and mechanical turning of the compost.

Overall, centralized composting of yard trimmings probably has no net GHG emissions (measured as

GHG emissions minus carbon sequestration). Similarly, backyard composting of food scraps is estimated

to have no net GHG emissions.

5.1 POTENTIAL GREENHOUSE GAS EMISSIONS

Two potential types of GHG emissions are associated with composting – (1) methane from

anaerobic decomposition, and (2) non-biogenic CO2 from transportation of compostable materials, and

turning of the compost piles.

 1

 Although paper and mixed MSW can be composted, we did not analyze the GHG implications of

composting them because of time and resource constraints.

2

 CO2 emissions from delivery of compost to its final destination were not counted, because (1) compost is a

marketable product and (2) CO2 emissions from transportation of other marketable, finished goods to consumers

have not been counted in other parts of this analysis.
72

Methane. To research the methane issue, we first conducted a literature search for articles on

methane generation from composting. We identified no relevant articles published between 1991 and

early 1995, and thus decided not to continue searching for earlier articles. Because the literature search

was unproductive, we contacted several researchers from universities and the US Department of

Agriculture to discuss the potential for methane generation, based on the nature of carbon flows during

composting. Our methane analysis was based on their expert opinions.

The researchers we contacted stated that well-managed compost operations usually do not

generate methane because they typically maintain an aerobic environment with proper moisture content

to encourage aerobic decomposition of the materials. They also said that even if methane is generated in

anaerobic pockets in the center of the compost pile, the methane is most likely oxidized when it reaches

the oxygen-rich surface of the pile. Several of the researchers commented that anaerobic pockets are most

likely to develop when too much water is added to the compost pile; however, they noted that this

problem rarely occurs because compost piles are much more likely to be watered too little, rather than too

much.

For backyard composting, the compost pile is rarely large enough to permit anaerobic conditions

to develop, even in the center of the pile (i.e., all parts of the pile are close enough to the surface to

remain oxygenated).

We concluded from the available information that methane generation from backyard and

centralized compost piles is negligible.

Carbon Dioxide from Transportation of Materials and Turning of Compost. Next, we estimated

the indirect carbon dioxide emissions associated with collecting and transporting yard trimmings to

centralized compost facilities, and turning the compost piles. We began with estimates developed by

Franklin Associates, Ltd. for the amount of diesel fuel required, for one ton of yard trimmings,3

 to (1)

collect and transport the yard trimmings to a central composting facility (363,000 BTUs), and (2) turn the

compost piles (221,000 BTUs).4

 We converted these estimates to units of metric tons of carbon

equivalent (MTCE) per ton of yard trimmings, based on a carbon coefficient of 0.0208 MTCE per

million BTUs of diesel fuel. This resulted in an estimate of 0.01 MTCE of indirect CO2 emissions per ton

of material composted in a centralized facility. There are no indirect CO2 emissions from backyard

composting, because there is no significant use of machinery to transport materials or to turn the compost

pile.

5.2 POTENTIAL CARBON SEQUESTRATION

We also evaluated the effect on soil carbon storage of composting yard trimmings and food scraps.

A number of long-term field experiments which directly controlled carbon inputs (through crop removal

and the readdition of specific amounts of organic matter) have generally shown a linear relationship

between carbon inputs and soil carbon levels. This relationship varies depending upon climatic and soil

 3

 Measured on a wet weight basis, as MSW is typically measured.

4

 Franklin Associates, Ltd., The Role of Recycling in Integrated Solid Waste Management to the Year 2000

(Stamford, CT: Keep America Beautiful), September 1994, pp. I-27, I-30, and I-31.
73

factors which affect decomposition rates in a particular location, as well as the length of the experiment.5

The relationship also depends on the chemical form of the carbon inputs. Our approach focuses on the

effect of composting on the persistence of carbon applied to soil.

Yard Trimmings. For yard trimmings, our analysis compared the amount of long-term soil carbon

storage when yard trimmings are composted (and subsequently applied to soil) to the amount of soil

carbon storage when the trimmings are left directly on the ground to decompose. Because we were

unable to find data allowing us to quantify incremental carbon storage, we used a bounding analysis to

estimate the upper and lower limits of the magnitude of this phenomenon.

During the process of decomposition, organic materials typically go through a series of steps

before finally being converted to CO2 (as well as water and other reaction products). The intermediate

compounds that are formed, and the lifetime of these compounds, can vary widely depending on the

chemical composition of the parent compound; the availability of oxygen and nutrients; the population of

microorganisms capable of degrading the compounds; temperature and moisture conditions; and many

other factors. To evaluate the potential of composting to enhance carbon storage, a useful simplification

is to view decomposition as a process consisting of two phases:

• a rapid degradation phase, lasting for a few months to a few years, where the readily

degradable materials are converted mostly to CO2, and to a much lesser extent to humic

materials, and

• a slow degradation phase, lasting much longer, where the humic materials are slowly

degraded to CO2.

Composting is designed to accelerate the pace of the first phase. It promotes rapid decomposition

of organics, thus reducing their volume. Some evidence suggests that composting produces a greater

proportion of humus than that typically formed when yard trimmings are left directly on the ground. The

conditions in the two phases are different – the heat generated within compost piles favors "thermophilic"

(heat-loving) bacteria, which tend to produce a greater proportion of stable, long-chain carbon

compounds than do bacteria that predominate at ambient surface temperatures. These long-chain carbon

compounds include lignin and humic materials (humic acids, fulvic acids, and humin).

For our analysis, we assumed that in soils where trimmings (i.e., grass clippings, leaves, and

branches) are left in place, there is no net accumulation of carbon in the soil. This assumption is

consistent with the observation that the quantity of carbon emitted from soils as carbon dioxide each year

is typically in equilibrium with the quantity of additional carbon introduced into the soil each year by

roots, leaf litter, and branches.6

 We used this scenario as our baseline against which to measure

incremental carbon storage attributable to composting.

The incremental storage is a function of three principal factors:

(1) The amount of carbon in each material (grass, leaves, branches),

 

5

 Paustian, K., H.P. Collins, and E.A. Paul, “Management Controls on Soil Carbon”, Soil Organic Matter in

Temperate Agroecosystems, (CRC Press: Boca Raton, FL), 1997, pp. 15-49.

6 Alexander, Martin, Introduction to Soil Microbiology, Second Edition (Malabar, Florida: Krieger

Publishing Company) 1991, p. 133.
74

(2) The additional proportion of carbon converted into humus when trimmings are composted,

rather than left in place, and

(3) The rate at which humus is degraded to CO2.

We obtained point estimates for the first factor from a series of experiments by Dr. Morton Barlaz,

which are described later in Chapter 7. As in other parts of the analysis, we assumed that yard trimmings

comprise 50 percent grass clippings, 25 percent leaves, and 25 percent branches, by weight.7

 We used

professional judgment to develop lower and upper bound estimates for the second and third factors, and

then combined the estimates in a bounding analysis.

As an upper bound on the incremental humus formation, we assumed that composting can result in

conversion of up to 25 percent more of the carbon to humus than the "baseline" conversion rate (i.e., if

residues were left on the ground).8

 (This upper bound implies, for example, that if 10 percent of the

carbon is in a relatively stable form following decomposition at ambient temperatures, then 35 percent of

the carbon would be relatively stable after composting.) For a lower bound, we used a value of 5 percent

as the incremental portion of carbon that is converted to stable carbon compounds.

We also developed a range for the half-life of stable carbon compounds in soil. Radiocarbon

dating of soils has shown that the long-chain carbon compounds in some soil samples can be hundreds or

thousands of years old.9

 As noted above, the decay rate of individual compounds is highly site- and

compound-specific; to account for this heterogeneity, we used wide bounds – from a half-life of 20 years

to a half-life of 2,000 years. We assumed that humus decomposition is a first-order decay process (i.e.,

the proportional decrease in concentration is constant over time).

Combining the two bounds for incremental humus formation (5 percent and 25 percent) and the

two bounds for half-lives (20 years and 2,000 years) resulted in four scenarios for the bounding analysis.

We estimated the incremental carbon storage implied by each scenario over a period of 100 years.

The results of our bounding analysis are shown graphically in Exhibit 5-1. The upper bound on the

incremental carbon storage from composting is about 0.05 MTCE per ton of yard trimmings (shown in

the top left of the graph); the lower bound is about 0.001 (shown in the bottom right of the graph). With

the rapid decomposition (20 year half-life) assumption, incremental storage is quite sensitive to the time

period over which carbon storage is considered – values at 20 years are sixteen times as high as values at

100 years. Under the slow decomposition assumption, there is little difference in incremental storage for

all periods up to 100 years.

 7 This professional judgment estimate for the percentage composition of yard trimmings (as a national

average) was provided by Franklin Associates, Ltd. (FAL) in a telephone conversation with ICF Incorporated,

November 14, 1995. Subsequently, FAL obtained and provided data showing a wide range of percentage

breakdowns for yard waste composition in different states; the percentage composition used here is within that range. 8

 Memorandum from Michael Cole, University of Illinois at Urbana-Champaign, U.S. EPA Office of Solid

Waste, February 1, 1996.

9 Allison, F.E., Soil Organic Matter and Its Role in Crop Production (Elsevier Scientific Publishing Co.)

1973, pp. 157-8.
75

Exhibit 5-1. Incremental Carbon Storage: 

Composting Yard Trimmings

MTCE/wet ton vs time 

0.0000.0100.0200.0300.0400.0500.060

0 20 40 60 80 100 

Time (years)

Incremental C Storage

(MTCE/ton)

Delta C as humus=5%; t1/2=200Delta C as humus=25%; t1/2=20Delta C as humus=5%; t1/2=20 yDelta C as humus=25%; t1/2=20 
76

Food Scraps. We also estimated the carbon storage from backyard composting of food scraps.

Data were not available on the amount of carbon sequestered in humus when food scraps are composted.

We assumed that backyard composting of food scraps converts all of the carbon in food scraps to CO2,

and that none of the carbon is sequestered in humus. To the extent that backyard composting of food

scraps may sequester carbon, our results would understate the net carbon sequestration resulting from

composting this material.

5.3 NET GHG EMISSIONS FROM COMPOSTING

Exhibit 5-2 presents the estimated net greenhouse gas emissions from composting. Our analysis

indicated that composting is a process that produces virtually no greenhouse gas emissions, and is not

likely to represent a significant carbon sink. For centralized yard trimmings composting, the

transportation emissions are probably balanced (and could well be exceeded) by additional carbon

storage. Given the large tonnage of yard trimmings composted annually, and the remaining uncertainties

in this analysis, this is an area that would benefit from further study. For backyard food waste

composting, we estimated no net GHG emissions.

Exhibit 5-2

Net Greenhouse Gas Emissions from Composting

(In Metric Tons of Carbon Equivalent Per Short Ton of Material Composted)

Material

Centralized Composting Backyard Composting

CH4

Transport

CO2 C seq Net C CH4

Transport

CO2 C seq Net C

Yard

Trimmings

0 0.01 -0.001

to

-0.05

0.009 to

-0.04

NA NA NA NA

Food

Scraps

NA NA NA NA 0 0 0 0

5.4 LIMITATIONS OF THE ANALYSIS

The analyses in this chapter are limited by the lack of data on methane generation and carbon

sequestration that result from composting. Because of inadequate data, we relied on a theoretical

approach to estimate the values (and in the case of carbon sequestration from composting of food scraps,

we assumed zero carbon sequestration).

Our analysis did not consider the GHG emissions that might be avoided if compost displaces some

chemical fertilizers (or peat moss, fungicides, pesticides, and other products applied to soil and plants).

The manufacture of chemical fertilizers requires energy, and thus is associated with some level of
77

energy-related GHG emissions. We also did not analyze the extent to which compost may reduce the

need for pesticides.10 For the most part, compost is applied for its soil amendment properties, rather than

for purposes of fertilization or pest control.

Moreover, we did not consider other environmental benefits of composting, and of using

compost as a soil amendment. For example, adding compost to soil increases the soil's capability to retain

moisture and nutrients. This helps to reduce storm runoff, thus preserving topsoil and reducing siltation

of streams and rivers. In the future, this may allow continued farming in areas that might have more

frequent droughts due to climate change. Adding compost to soil also improves soil tilth and reduces soil

density, i.e., it makes the soil easier to till, allows plant roots to go deeper, increases the likelihood that

new plantings become established, and helps plants to grow larger. Finally, we did not consider the value

of composting in reducing the amount of waste landfilled, and extending the useful lifetime of landfills.

 10 For example, the use of compost may eliminate the need for soil fumigation with methyl bromide (an

ozone-depleting substance) to kill plant pests and pathogens.
78

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79

6. COMBUSTION

This chapter presents estimates of the net GHG emissions from combustion of each of the

materials considered in this analysis and mixed MSW. Combustion of MSW results in emissions of CO2

(because nearly all of the carbon in MSW is converted to CO2) and N2O. Note that CO2 from burning

biomass sources (such as paper products and yard trimmings) is not counted as a GHG, because it is

biogenic (as explained in Section 1.7).

Combustion of MSW with energy recovery in a waste-to-energy (WTE) plant also results in

avoided CO2 emissions in two other industrial sectors. First, the electricity produced by a WTE plant

displaces electricity that would otherwise be provided by an electric utility power plant. Because most

utility power plants burn fossil fuels, and thus emit CO2, the electricity produced by a WTE plant reduces

utility CO2 emissions. These avoided GHG emissions must be subtracted from the GHG emissions

associated with combustion of MSW. Second, most MSW combusted with energy recovery in the US is

combusted in WTEs that recover ferrous metals (e.g., steel) and non-ferrous materials (e.g., non-ferrous

metals and glass).1

 The ferrous metals and non-ferrous materials that are recovered are then recycled.2 As

discussed in Chapter 4, processes using recycled inputs require less energy than processes using virgin

inputs. Thus, in measuring GHG implications of combustion, one must also account for the change in

energy use due to recycling associated with metals recovery.

WTE facilities can be divided into three categories: (1) mass burn, (2) modular, or (3) refusederived fuel (RDF). A mass burn facility generates electricity and/or steam from the combustion of mixed

MSW. In the US, there are approximately 90 mass burn facilities that process approximately 24 million

tons of MSW annually.

3 Modular WTE plants are similar to mass burn plants, but the modular units are

generally smaller plants prefabricated off-site and more quickly assembled where they are needed. Because

of their similarity to mass burn facilities, modular facilities are treated as part of the mass burn category for

the purposes of this analysis.

An RDF facility combusts MSW which has undergone varying degrees of processing, from simple

removal of bulky and noncombustible items to more complex processes (shredding and material recovery),

resulting in a finely divided fuel. Processing MSW into RDF yields a more uniform fuel that has a higher

 1

 We did not consider any recovery of materials from the MSW stream that may occur before MSW is

delivered to the combustor. We considered such prior recovery to be unrelated to the combustion operation – unlike

recovery of steel from combustor ash, an activity that is an integral part of the operation of many combustors.

2

 Note that material recovery at WTE facilities has increased in recent years, and this trend may continue as

more facilities install material recovery systems. According to the Integrated Waste Services Association,

approximately 775,000 tons of ferrous metal and 135,000 tons of non-ferrous material were recovered in 1996. Of

the non-ferrous material, approximately 34,000 tons consisted of non-ferrous metals. Letter received from Maria

Zannes, Integrated Waste Services Association, Washington, DC, August 25, 1997.

3

 Integrated Waste Services Association, The 1997-1998 IWSA Waste-To-Energy Directory of United States

Facilities, Table 1.
80

heating value.4 In the US, approximately 20 facilities process and combust RDF, 2 facilities combust RDF

using off-site processing, and 8 facilities process RDF for combustion off-site. These 30 facilities process

approximately 9 million tons of MSW annually.5

We analyzed the net GHG emissions from combustion of mixed MSW, and the following

individual materials at mass burn and RDF facilities:

• newspaper,

• office paper,

• corrugated cardboard,

• mixed paper,

• aluminum cans,

• steel cans,

• glass,

• HDPE plastic,

• LDPE plastic,

• PET plastic,

• food scraps, and

• yard trimmings.

Net emissions consist of (1) emissions of non-biogenic CO2 and N2O minus (2) avoided GHG emissions

from the electric utility sector and from processing with recycled inputs (e.g., steel produced from

recycled inputs requires less energy than steel from virgin inputs). There is some evidence that as

combustor ash ages, it absorbs CO2 from the atmosphere; however, we did not count CO2 absorbed

because we estimated the quantity absorbed to be less than 0.01 MTCE per ton of MSW combusted.6

Similarly, the residual waste from processing MSW into RDF is typically landfilled, and there is some

potential for the organic fraction of this residual waste to yield GHG emissions when landfilled;

however, we did not count these emissions because we estimate the quantity emitted to be less than 0.01

MTCE per ton of MSW processed into RDF.7

Our results showed that combustion of mixed MSW has small negative net GHG emissions (in

absolute terms). Combustion of paper products, food scraps, and yard trimmings results in negative net

GHG emissions. Processing steel cans at a combustor, followed by recycling the ferrous metal, likewise

results in negative net GHG emissions. Combustion of plastic produces positive net GHG emissions, and

 4 MSW processing into RDF involves both manual and mechanical separation to remove materials such as

glass and metals which have little or no fuel value.

5

 Integrated Waste Services Association, The 1997-1998 IWSA Waste-To-Energy Directory of United States

Facilities, Table 1.

6

 Based on data provided by Dr. Jurgen Vehlow of Karlsruhe, Germany's Institut fur Technische Chemie,

we estimated that the ash from one ton of MSW would absorb roughly 0.004 MTCE of CO2.

7

 Based on data provided by Karen Harrington, Principal Planner for the Minnesota Office of

Environmental Assistance, we estimated that landfilling the residual waste would emit roughly 0.003 MTCE of CO2

per ton of MSW processed into RDF. Facsimile from Karen Harrington, Minnesota Office of Environmental

Assistance to ICF, October 1997.
81

combustion of aluminum cans and glass results in small positive net GHG emissions. The reasons for

each of these results are discussed in the remainder of this chapter.8

6.1 METHODOLOGY

Our general approach was to estimate the (1) gross emissions of CO2 and N2O from MSW and

RDF combustion (including emissions from transportation of waste to the combustor, and ash from the

combustor to a landfill) and (2) CO2 emissions avoided due to displaced electric utility generation and

decreased energy requirements for production processes utilizing recycled inputs.9

 To obtain an estimate

of the net GHG emissions from MSW and RDF combustion, we subtracted the GHG emissions avoided

from the direct GHG emissions. We estimated the net GHG emissions from waste combustion per ton of

mixed MSW, and per ton of each selected material in MSW. The remainder of this section describes how

we developed these estimates.

Estimating Direct CO2 Emissions from MSW Combustion

The carbon in MSW has two distinct origins. Some of the carbon in MSW is derived from

sustainably harvested biomass (i.e., carbon in plant and animal matter that was converted from CO2 in the

atmosphere through photosynthesis). The remaining carbon in MSW is from non-biomass sources, e.g.,

plastic and synthetic rubber derived from petroleum.

We did not count the biogenic CO2 emissions from combustion of biomass, for reasons described

in Section 1.7. On the other hand, we did count CO2 emissions from combustion of non-biomass

components of MSW – plastic, textiles, and rubber. Overall, only a small portion of the total CO2

emissions from combustion are counted as GHG emissions.

For mixed MSW, we used the simplifying assumptions that (1) all carbon in textiles was nonbiomass carbon, i.e., petrochemical-based plastic fibers such as polyester (this is a worst-case

assumption), and (2) the category of "rubber and leather" in EPA's MSW characterization report10 was

composed almost entirely of rubber. Based on these assumptions, we estimated that there are 0.11 pounds

of non-biogenic carbon in the plastic, textiles, rubber, and leather contained in one pound of mixed

MSW. 11 We assumed that 98 percent of this carbon would be converted to CO2 when the waste was

combusted, with the balance going to the ash. Then, we converted the 0.11 pounds of non-biomass

carbon per pound of mixed MSW to units of metric tons of carbon equivalent (MTCE) per ton of mixed

 8

 Note that Exhibits 6-1, 6-2, and 6-5 show coated paper but not mixed paper; mixed paper is shown in the

summary exhibit (Exhibit 6-6). The summary values for mixed paper are based on the proportions of the four paper

types (newspaper, office paper, corrugated cardboard, and coated paper) that comprise the different “mixed paper”

definitions.

9 A comprehensive evaluation would also consider the fate of carbon remaining in combustor ash.

Depending on its chemical form, carbon may be aerobically degraded to CO2, anaerobically degraded to CH4, or

remain in a relatively inert form and be sequestered. Unless the ash carbon is converted to CH4 (which we considered

to be unlikely), the effect on the net GHG emissions would be very small.

10 US EPA, Office of Solid Waste and Emergency Response, Characterization of Municipal Solid Waste in

the United States: 1997 Update, May 1998.

11 ICF Incorporated, "Work Assignment 239, Task 2: Carbon Sequestration in Landfills," memorandum to

EPA, April 28, 1995, Exhibit 2-A, column "o."
82

MSW combusted. The resulting value for mixed MSW is 0.10 MTCE per ton of mixed MSW

combusted,12 as shown in Exhibit 6-1.

We estimated that HDPE and LDPE are 84 percent carbon, while PET is 57 percent carbon

(accounting for a moisture content of 2 percent). We assumed that 98 percent of the carbon in the plastic

is converted to CO2 during combustion. The values for CO2 emissions, converted to units of MTCE per

ton of plastic combusted, are shown in column "b" of Exhibit 6-1.

Estimating N2O Emissions from Combustion of Waste

Studies compiled by the Intergovernmental Panel on Climate Change (IPCC) show that MSW

combustion results in measurable emissions of N2O (nitrous oxide), a greenhouse gas with a high global

warming potential (GWP).13 The IPCC compiled reported ranges of N2O emissions, per metric ton of

waste combusted, from six classifications of MSW combustors. We averaged the midpoints of each range

and converted the units to MTCE of N2O per short ton of MSW; the resulting estimate is 0.01 MTCE of

N2O emissions per ton of mixed MSW combusted. Because the IPCC did not report N2O values for

combustion of individual components of MSW, we used the 0.01 value not only for mixed MSW, but

also as a proxy for all components of MSW, except for aluminum and steel cans.14

Estimating Indirect CO2 Emissions from Transportation of Waste to the WTE Plant

Next, we estimated the indirect CO2 emissions from the transportation of waste. For the indirect

CO2 emissions from transporting waste to the WTE plant, and ash from the WTE plant to a landfill, we

used an estimate for mixed MSW developed by Franklin Associates, Ltd. (FAL).15 We then converted the

FAL estimate from pounds of CO2 per ton of mixed MSW to MTCE per ton of mixed MSW. This

resulted in an estimate of 0.01 MTCE of CO2 emissions from transporting one ton of mixed MSW, and

the resulting ash. We assumed that transportation of any individual material in MSW would use the same

amount of energy as transportation of mixed MSW.

Estimating Gross Greenhouse Gas Emissions from Combustion

To estimate the gross GHG emissions per ton of waste combusted, we summed the values for

emissions from combustion CO2, combustion N2O, and transportation CO2. The gross GHG emissions

estimates, for mixed MSW and for each individual material, are shown in column "e" of Exhibit 6-1.

 12 Note that if we had used a best-case assumption for textiles, i.e., assuming they had no petrochemicalbased fibers, the resulting value for mixed MSW would have been 0.09 MTCE per ton of mixed MSW combusted.

13 Intergovernmental Panel on Climate Change, Greenhouse Gas Inventory Reference Manual, Volume 3,

(undated) p. 6-33. The GWP of N2O is 270 times that of CO2.

14 This exception was made because at the relatively low combustion temperatures found in MSW

combustors, most of the nitrogen in N2O emissions is derived from the waste, not from the combustion air. Because

aluminum and steel cans do not contain nitrogen, we concluded that running these metals through an MSW

combustor would not result in N2O emissions.

15 Franklin Associates, Ltd., The Role of Recycling in Integrated Solid Waste Management to the Year 2000

(Stamford, CT: Keep America Beautiful, Inc.) September 1994, p. I-24.
83

(a) (b) (c) (d) 

Combustion CO2 Combustion N2O Transportation CO2 (e = 

Emissions From Emissions Emissions Gr

Material Non-Biomass Per Per Ton Per Ton Emi

Combusted Ton Combusted Combusted Combusted Ton 

Newspaper 0.00 0.01 0.01 Office Paper 0.00 0.01 0.01 Corrugated Cardboard 0.00 0.01 0.01 Coated paper 0.00 0.01 0.01 Aluminum Cans 0.00 0.01 0.01 Steel Cans 0.00 0.01 0.01 Glass 0.00 0.01 0.01 HDPE 0.75 0.01 0.01 LDPE 0.75 0.01 0.01 PET 0.51 0.01 0.01 Food Scraps 0.00 0.01 0.01 Yard Trimmings 0.00 0.01 0.01 Mixed MSW 0.10 0.01 0.01 

Note that totals may not add due to rounding and more digits may be displayed than are significant.Note that Exhibits 6-1, 6-2, and 6-5 show coated paper but not mixed paper; mixed paper is shown in the summary eThe summary values for mixed paper are based on the proportions of the four paper types (newspaper, office papercardboard, and coated paper) that comprise the different "mixed paper" definitions.

Exhibit 6-1

Gross Emissions of Greenhouse Gases From MSW Combustion

(MTCE/Ton)
84

Estimating Utility CO2 Emissions Avoided

Most WTE plants in the US produce electricity. Only a few produce steam, and few cogenerate

electricity and steam. Thus, in our analysis, we assumed that the energy recovered with MSW

combustion would be in the form of electricity. Our analysis is shown in Exhibit 6-2. We used three data

elements to estimate the avoided electric utility CO2 emissions associated with combustion of waste in a

WTE plant: (1) the energy content of mixed MSW and of each separate waste material considered, (2)

the combustion system efficiency in converting energy in MSW to delivered electricity, and (3) the

electric utility CO2 emissions avoided per kilowatt-hour of electricity delivered by WTE plants.

Energy content. For the energy content of mixed MSW, we used a value of 5,000 BTUs per

pound of mixed MSW combusted, which is a value commonly used in the WTE industry.

16 This estimate

is within the range of values (4,500 to 6,500 BTUs per pound) reported by FAL,17 and is slightly higher

than the 4,800 BTUs per pound value reported in EPA's MSW Fact Book.

18 For the energy content of

RDF, we used a value of 5,700 BTUs per pound of RDF combusted.19 This estimate is within the range of

values (4,800 to 6,400 BTUs per pound) reported by the US Department of Energy’s National Renewable

Energy Laboratory (NREL).20 For the energy content of specific materials in MSW, we consulted three

sources: (1) EPA's MSW Fact Book (a compilation of data from primary sources), (2) a report by

Environment Canada,21 and (3) a report by Argonne National Laboratories.22 We assume that the energy

contents reported in the first two of these sources were for materials with moisture contents typically

found for the materials in MSW (the sources implied this, but did not explicitly state it). The Argonne

study reported energy content on a dry weight basis.

 16 Telephone conversation among representatives of Integrated Waste Services Association, American RefFuel, and ICF Incorporated, October 28, 1997.

17 Franklin Associates, Ltd., The Role of Recycling in Integrated Solid Waste Management to the Year

2000 (Stamford, CT: Keep America Beautiful, Inc.) September 1994, p. I-16.

18 US Environmental Protection Agency, Office of Solid Waste, MSW Fact Book, Version 2.0 (Washington,

D.C.: US Environmental Protection Agency) April 1995.

19 Note that this is a value reported by an RDF facility located in Newport, Minnesota; the data were

provided by the Minnesota Office of Environmental Assistance. Facsimile from Karen Harrington, Minnesota Office

of Environmental Assistance to ICF, October 1997.

20 US Department of Energy, National Renewable Energy Laboratory, Data Summary of Municipal Solid

Waste Management Alternatives Volume IV: Appendix B – RDF Technologies (Springfield, VA: National Technical

Information Service, NREL/TP-431-4988D) October 1992, p. B-5.

21 Procter and Redfern, Ltd. and ORTECH International, Estimation of the Effects of Various Municipal

Waste Management Strategies on Greenhouse Gas Emissions, Part II (Ottawa, Canada: Environment Canada, Solid

Waste Management Division, and Natural Resources Canada, Alternative Energy Division), September 1993.

22 Gaines, Linda, and Frank Stodolsky, "Mandated Recycling Rates: Impacts on Energy Consumption and

Municipal Solid Waste Volume" (Argonne, IL: Argonne National Laboratory) December 1993, pp. 11 and 85.
85

Exhibit 6-2

Avoided Utility GHG Emissions from Combustion at Mass Burn and RDF Facilities

(a) (b) (c) (d) (e) (f) (g) (h)

Material 

Combusted

Energy Content 

(BTUs per 

pound)

Energy 

Content 

(Million 

BTUs per 

ton)

Mass Burn 

Combustion 

System 

Efficiency 

(Percent)

RDF 

Combustion 

System 

Efficiency 

(Percent)

Emission 

Factor for 

UtilityGenerated 

Electricity 

(MTCE/

Million 

BTUs of 

electricity 

delivered)

(g = c * d * f) 

Avoided 

Utility CO2 

Per Ton 

Combusted 

at Mass 

Burn 

Facilities 

(MTCE)

(h = c * e * f)

Avoided 

Utility CO2 

Per Ton 

Combusted at 

RDF Facilities 

(MTCE)

Newspaper 7,950 a 15.9 17.8% 16.3% 0.083 0.24 0.22Office paper 6,800 a,b 13.6 17.8% 16.3% 0.083 0.20 0.18Corrugated cardboar a 14.1 17.8% 16.3% 0.083 7,043 0.21 0.19

Coated paper 5,258 c 10.5 17.8% 16.3% 0.083 0.16 0.14

Aluminum cans -335 d -0.7 17.8% 16.3% 0.083 -0.01 * -0.01 *Steel cans -210 d -0.4 17.8% 16.3% 0.083 -0.01 * -0.01 *Glass -235 d -0.5 17.8% 16.3% 0.083 -0.01 * -0.01 *HDPE 18,687 a 37.4 17.8% 16.3% 0.083 0.56 0.51

LDPE 18,687 a 37.4 17.8% 16.3% 0.083 0.56 0.51

PET 9,702 e,f 19.4 17.8% 16.3% 0.083 0.29 0.26

Yard trimmings 2,800 g 5.6 17.8% 16.3% 0.083 0.08 0.08

Food scraps 2,370 a 4.7 17.8% 16.3% 0.083 0.07 0.06

Mixed MSW** 5,000 h 10.0 17.8% 16.3% 0.083 0.15 0.14

Note that totals may not add due to rounding and more digits may be displayed than are significant.* The amount of energy absorbed by one ton of steel, aluminum cans, or glass in an MSW combustor would, if not absorbed, result in less than 0.01 MTCEof avoided utility CO2.** Mixed MSW represents the entire waste stream as disposed.a MSW Fact Book.b We used the MSW Fact Book's value for mixed paper as a proxy for the value for office paper.c We used Franklin Associates' value for magazines as a proxy for the value for coated paper.d We developed these estimates based on data on the specific heat of aluminum, steel, and glass and calculated the energy required to raise the temperature of  aluminum, steel, and glass from ambient temperature to the temperature found in a combustor (about 750° Celsius). We obtained the specific heat data from  Incropera, Frank P.and David P. DeWitt, Introduction to Heat Transfer, Second Edition (New York: John Wiley & Sons) 1990, pp. A3-A4.e Gaines and Stodolsky.f For PET plastic, we converted the value of 9,900 BTUs/pound dry weight, to 9,702 BTUs/pound wet weight, to account for a moisture content of 2 percent.g Procter and Redfern, Ltd. and ORTECH International.h Telephone conversation among IWSA, American Ref-Fuel, and ICF Inc., October 28, 1997.
86

Combustion system efficiency. To estimate the combustion system efficiency of mass burn

plants, we used with a net value of 550 kWh generated by mass burn plants per ton of mixed MSW

combusted.23 To estimate the combustion system efficiency of RDF plants, we evaluated three sources:

(1) data supplied by an RDF processing facility located in Newport, Minnesota, (2) the Integrated Waste

Services Association (IWSA) report Waste-to-Energy Directory: 1997-1998, and (3) DOE’s National

Renewable Energy Laboratory. We used the Newport Processing Facility’s reported net value of 572

kWh generated per ton of RDF for two reasons.24 First, this value is within the range of values reported

by the other sources. Second, the Newport Processing Facility provided a complete set of data from

which to evaluate the overall system efficiency of RDF plants.25

Next, we considered losses in transmission and distribution of electricity. Using a transmission

and distribution loss rate of 5 percent,26 we estimated that 523 kWh are delivered per ton of waste

combusted at mass burn facilities, and 544 kWh are delivered per ton of waste input at RDF facilities.

We then used the value for the delivered kWhs per ton of waste combusted to derive the implicit

combustion system efficiency (i.e., the percentage of energy in the waste that is ultimately delivered in

the form of electricity). To determine this efficiency, we first estimated the BTUs of MSW needed to

deliver one kWh of electricity. We divided the BTUs per ton of waste by the delivered kWh per ton of

waste to obtain the BTUs of waste per delivered kWh. The result is 19,200 BTUs per kWh for mass burn,

and 21,000 BTUs per kWh for RDF. Next we divided the physical constant for the energy in one kWh

(3,412 BTUs) by the BTUs of MSW and RDF needed to deliver one kWh, to estimate the total system

efficiency at 17.8 percent for mass burn and 16.3 percent for RDF (Exhibit 6-2, columns “d” and “e”).27

Electric utility carbon emissions avoided. To estimate the avoided utility CO2 from waste

combustion, we used the results in columns "c" and "d," together with a "carbon coefficient" of 0.083

MTCE emitted per million BTUs of utility-generated electricity (delivered), based on the national

average fossil fuel mix used by utilities28 as shown in Exhibits 6-3 and 6-4. This approach uses the

average fossil fuel mix as a proxy for the fuels displaced at the margin when utility-generated

 23 Note that this is the value reported by Integrated Waste Services Association in its comments to the draft

version of this report. This value is within the range of values reported by others in response to the draft version of

this report. Letter received from Maria Zannes, Integrated Waste Services Association, Washington, DC, August 25,

1997.

24 The net energy value reported accounts for the estimated energy required to process MSW into RDF and

the estimated energy consumed by the RDF combustion facility.

25 The data set included estimates on the composition and amount of MSW delivered to the processing

facility, as well as estimates for the heat value of RDF, the amount of energy required to process MSW into RDF,

and the amount of energy used to operate the RDF facility.

26 Telephone conversation among representatives of Integrated Waste Services Association, American RefFuel, and ICF Incorporated, October 28, 1997.

27 Note that the total system efficiency is the efficiency of translating the energy content of the fuel into the

energy content of delivered electricity. The estimated system efficiencies of 17.8 and 16.3 percent reflect losses in

(1) converting energy in the fuel into steam, (2) converting energy in steam into electricity, and (3) delivering

electricity. The losses in delivering electricity are the transmission and distribution losses, estimated at 5 percent.

28 Value estimated using data from the Energy Information Administration, Annual Energy Review 1996

(Washington, DC: US Government Printing Office, DOE/EIA-0384(96).) July, 1997.
87

Exhibit 6-3

Estimating the Emission Factor for Utility-Generated Electricity

Value Value Source

Electric Utility Consumption of Fossil Fuels to Generate ElectricityCoal (Quadrillion BTUs) 17.91 DOE, EIA, "Annual Energy Review: 1996," JNatural Gas (Quadrillion BTUs) 2.80 DOE, EIA, "Annual Energy Review: 1996," JPetroleum (Quadrillion BTUs) 0.73 DOE, EIA, "Annual Energy Review: 1996," JTotal (Quadrillion BTUs) 21.44 The sum of Coal, Natural Gas, and PetroleuEnergy Value of one Quadrillion BTUs 2.9E+11 DOE, EIA, "Form EIA 1605 (1997)," Append (measured in Kilowatt-hours)Total (Billion kWh) 6,279 (21.44 Quad BTUs) x (2.92875x1011 kWh/QNet Generation: Before Transmission and Distribution Losses (Fossil Fuels Only)Coal (Billion kWh) DOE, EIA, "Annual Energy Review: 1996," J

1,736

Natural Gas (Billion kWh) DOE, EIA, "Annual Energy Review: 1996," J

263

Petroleum (Billion kWh) DOE, EIA, "Annual Energy Review: 1996," J

68

Total (Billion kWh) The sum of Coal, Natural Gas, and Petroleu

2,067

Generation Efficiency (Fossil Fuels Only)Generation Output (Billion kWh) 2,067 Calculated above.Consumption (Billion kWh) 6,279 Calculated above.Efficiency (percent) 33% Generation Output / Consumption, i.e. 2,067 Efficiency of Energy Conversion From Fossil Fuels to Delivered ElectricityTransmission and Distribution Losses (TDL) (percent) 9% DOE, EIA, "Annual Energy Review: 1996," JDelivered Electricity Efficiency (percent) 91% Calculated as 100 percent (Deliverable ElecEfficiency of Energy Conversion and Delivery for Fossil Fuels (percent) 30% Generation Efficiency x Delivered Electricity Estimated Emission Factor for Delivered Electricity 

(MTCE/MBTU of Electricity Delivered)

Weighted Average Emission Factor of the US mix of fuels used to generate electricity All Fuels Fossil Fuels Only (kilograms of Carbon in CO2 per million BTU consumed) 16.80 25.01 Exhibit 6-4 of this report.

Weighted Average Emission Factor (MTCE/million BTU) 0.01680 0.02501 Converting kilograms of carbon (kg C) to me

Efficiency of Energy Conversion and Delivery (percent) 30% 30% Calculated above.Emission Factor for Delivered Electricity (MTCE/million BTU) 0.05607 0.08349 Weighted Average Emission Factor (MTCE/
88

Exhibit 6-4

Estimating the Weighted Average Carbon Coefficient of the 

US Average Mix of Fuels Used to Generate Electricity

(MTCE/Million BTU)

Fuel

Net 

Generation* 

(Billion kWh)

Percentage 

of 

Generation: 

All Fuels (%)

Percentage 

of 

Generation: 

Fossil Fuels 

(%)

Carbon Coefficents**

(Kg C in CO2 per 

Million BTU Consumed)

Coal 1,736 56.4% 84% 26.63Natural Gas 263 8.5% 13% 15.17Petroleum*** 68 2.2% 3% 21.70Nuclear 675 21.9% 0Hydroelectric 329 10.7% 0Other 7 0.2% 0Total 3,078 100.0% 100% NAWeighted Average - All Fuels 16.80Weighted Average - Fossil Fuels 25.01

Note that totals may not add due to rounding and more digits may be displayed than are significant.* Source: EIA's Annual Energy Review: 1996, "Table 8.3 Electricity Utility Net Generation of Electricity by Energy Source 

for 1996."** Values include fugitive methane emissions (weighted by the GWP of methane).*** The carbon coefficient for residual fuel is used as a proxy for petroleum.
89

electricity is displaced by electricity from WTE plants. In other words, we assume that nuclear,

hydropower, and other non-fossil sources generate electricity at essentially fixed rates; marginal demand

is met by fossil sources.29 The actual carbon reductions could vary depending on which type of fuel used

to generate electricity is displaced at the margin. The resulting estimates for utility carbon emissions

avoided for each material are shown in column "g" and “h” of Exhibit 6-2.

Approach to Estimating CO2 Emissions Avoided Due to Increased Steel Recycling

We next estimated the avoided CO2 emissions from increased steel recycling made possible by

steel recovery from WTE plants for (1) mixed MSW and (2) steel cans. Note that we did not credit

increased recycling of non-ferrous materials, because of a lack of data on the proportions of those

materials being recovered. This tends to overestimate net GHG emissions from combustion.

For mixed MSW, we estimated the amount of steel recovered per ton of mixed MSW combusted,

based on (1) the amount of MSW combusted in the US, and (2) the amount of steel recovered, postcombustion. Ferrous metals are recovered at approximately 79 WTE facilities in the US and at eight RDF

processing facilities that do not generate power on-site. These facilities account for approximately 90

percent of the 32 million tons of MSW combusted per year, and recovered a total of about 775,000 tons

per year of ferrous metals in 1997.30 By dividing 775,000 tons (total U.S. steel recovery at combustors)

by 32 million tons (total U.S. MSW combustion), we estimated that 0.02 tons of steel are recovered per

ton of mixed MSW combusted (as a national average).

For steel cans, we first estimated the national average proportion of steel cans entering WTE

plants that would be recovered. As noted above, approximately 90 percent of MSW destined for

combustion goes to facilities with a ferrous recovery system; at these plants, approximately 98 percent of

the steel cans would be recovered. We multiplied these percentages to estimate the weight of steel cans

recovered per ton of steel cans combusted – bout 0.88 tons per ton.

Finally, to estimate the avoided CO2 emissions due to increased recycling of steel, we multiplied

(1) the weight of steel recovered by (2) the avoided CO2 emissions per ton of steel recovered. Thus, we

estimated avoided CO2 emissions of approximately 0.51 MTCE per ton for steel cans, and 0.01 MTCE

per ton for mixed MSW, as shown in column "d" of Exhibit 6-5.

6.2 RESULTS

The results of our analysis are shown in Exhibit 6-6. The results from the last columns of

Exhibits 6-1, the last two columns of Exhibit 6-2, and the last column of Exhibit 6-3 are shown in

columns "b," through “e” in Exhibit 6-6. The net GHG emissions from combustion of each material at

mass burn and RDF facilities are shown in columns “f” and “g,” respectively. These net values represent

the gross GHG emissions (column "b"), minus the avoided GHG emissions (columns "c," “d,” and “e”).

As stated earlier, these net GHG emissions estimates are expressed for combustion in absolute terms;

 29 Non-fossil sources are expected to meet baseload energy requirements because of the financial incentive

for these energy sources to generate at capacity. In general, the marginal cost of producing more power from these

sources is minimal compared to the capital costs associated with establishing the facility.

30 Integrated Waste Services Association, The 1997-1998 IWSA Waste-To-Energy Directory Of United

States Facilities.
90

Exhibit 6-5

Avoided GHG Emissions Due to

Increased Steel Recovery from MSW at WTE Facilities

(a) (b) (c) (d)*

Material Combusted

Tons of Steel 

Recovered Per 

Ton of Waste 

Combusted 

(tons)

Avoided CO2 

Emissions Per 

Ton of Steel 

Recovered 

(MTCE/ton)

Avoided CO2 

Emissions Per 

Ton of Waste 

Combusted 

(MTCE/ton)

Newspaper NA NA NAOffice paper NA NA NACorrugated cardboard NA NA NACoated paper NA NA NAAluminum cans NA NA NASteel cans 0.88 0.57 0.51Glass NA NA NAHDPE NA NA NALDPE NA NA NAPET NA NA NAYard trimmings NA NA NAFood scraps NA NA NAMixed MSW 0.02 0.57 0.01

Note that totals may not add due to rounding and more digits may be displayed than are significant.*The value in column "d" is a national average, and is weighted to reflect 98 percent recovery at the90 percent of facilities that recover ferrous metals.
91

Exhibit 6-6

Net GHG Emissions from Combustion at WTE Facilities

(a) (b) (c) (d) (e) (f) (g)

(f = b - c - e) (g = b - d- e)

Material Combusted

Gross GHG 

Emissions Per 

Ton 

Combusted 

(MTCE/ton)

Avoided Utility 

CO2 Per Ton 

Combusted at 

Mass Burn 

Facilities 

(MTCE/ton)

Avoided Utility 

CO2 Per Ton 

Combusted at 

RDF Facilities 

(MTCE/ton)

Avoided CO2 

Emissions Per 

Ton 

Combusted 

Due to Steel 

Recovery 

(MTCE/ton)

Net GHG 

Emissions from 

Combustion at 

Mass Burn 

Facilities 

(MTCE/ton)

Net GHG 

Emissions from 

Combustion at 

RDF Facilities 

(MTCE/ton)

Newspaper 0.02 0.24 0.22 NA -0.22 -0.20Office paper 0.02 0.20 0.18 NA -0.19 -0.17Corrugated cardboard 0.02 0.21 0.19 NA -0.19 -0.17Coated paper 0.02 0.16 0.14 NA -0.14 -0.13Mixed paper

 Broad Definition 0.02 0.21 0.19 NA -0.19 -0.17 Residential Definition 0.02 0.21 0.19 NA -0.19 -0.17 Office paper Definition 0.02 0.19 0.18 NA -0.18 -0.16

Aluminum cans 0.02 -0.01 -0.01 NA 0.03 0.03Steel cans 0.02 -0.01 -0.01 0.51 -0.48 -0.48Glass 0.02 -0.01 -0.01 NA 0.02 0.02HDPE 0.76 0.56 0.51 NA 0.21 0.26LDPE 0.76 0.56 0.51 NA 0.21 0.26PET 0.52 0.29 0.26 NA 0.24 0.26Yard trimmings 0.02 0.08 0.08 NA -0.07 -0.06Food scraps 0.02 0.07 0.06 NA -0.05 -0.05Mixed MSW 0.12 0.15 0.14 0.01 -0.04 -0.03

Note that totals may not add due to rounding and more digits may be displayed than are significant.
92

they are not values relative to some other waste management option. They are expressed in terms of short

tons of waste input (i.e., tons of waste prior to processing).

We estimate that combustion of mixed MSW at mass burn and RDF facilities reduces net postconsumer GHG emissions to −0.04 and −0.03 MTCE per ton, respectively. Combustion of paper

products has negative net post-consumer GHG emissions ranging from −0.14 to −0.22 MTCE per ton at

mass burn facilities, and from −0.13 to −0.20 MTCE per ton at RDF facilities. Net GHG emissions are

negative because CO2 emissions from burning paper are not counted (because they are biogenic) and

fossil fuel burning by utilities (to generate electricity) is avoided. Combustion of food scraps and yard

trimmings (two other forms of biomass) also have negative net GHG emissions, but of a smaller

magnitude (-0.05 and −0.07 MTCE per ton of material, respectively, for mass burn and −0.05 and −0.06

MTCE per ton of material, respectively, for RDF).

Combustion of plastics results in substantial net GHG emissions estimated from 0.21 to 0.24

MTCE per ton of material combusted for mass burn facilities, and 0.26 MTCE per ton of material input

to RDF facilities. This is primarily because of the high content of non-biomass carbon in plastics. Also,

when combustion of plastic results in electricity generation, the utility carbon emissions avoided (due to

displaced utility fossil fuel combustion) are much less than the carbon emissions from the combustion of

plastic. This is largely due to the lower system efficiency of WTE plants, compared to electric utility

plants. Recovery of ferrous metals at combustors results in negative net GHG emissions, estimated at

−0.48 MTCE per ton of steel cans, due to the increased steel recycling made possible by ferrous metal

recovery at WTE plants. Combustion of aluminum cans and glass, on the other hand, results in slightly

positive net GHG emissions of 0.03 and 0.02 MTCE per ton of material, due to (1) some nitrous oxide

emissions during the combustion process (which we allocated to all materials), and (2) the energy used in

transporting these materials to the WTE plant.

6.3 LIMITATIONS OF THE ANALYSIS

The reliability of the analysis presented in this chapter is limited by the reliability of the various

data elements used. The most significant limitations are as follows:

• Combustion system efficiency of WTE plants may be improving. A survey of planned

WTE plants shows an expected efficiency improvement of 14 percent over current

plants.31 If efficiency improves, more utility CO2 will be displaced per ton of waste

combusted (assuming no change in utility emissions per kWh), and the net GHG

emissions from combustion of MSW will decrease.

• Data for the RDF analysis was provided by the Minnesota Office of Environmental

Assistance, and were obtained from a single RDF processing facility and a separate RDF

combustion facility. Research indicates that each RDF processing and combustion

facility is different. For example, some RDF combustion facilities may generate steam

for sale off-site, which can affect overall system efficiency. In addition, the amount of

energy required to process MSW into RDF and the amount of energy used to operate

RDF combustion facilities can be difficult to quantify and can vary among facilities on a

daily, seasonal, and annual basis. Thus, the values used for the RDF analysis should be

interpreted as approximate values.

 31 Berenyi and Gould, op cit, p. 46.
93

• The reported ranges for N2O emissions were broad; in some cases the high end of the

range was 10 times the low end of the range. Research has indicated that N2O emissions

vary with the type of waste burned. Thus, the average value used for mixed MSW and

for all MSW components should be interpreted as an approximate value.

• For mixed MSW, we assumed that all carbon in textiles is from synthetic fibers derived

from petrochemicals (whereas, in fact, some textiles are made from cotton, wool, and

other natural fibers). Because we assumed that all carbon in textiles is non-biogenic, we

counted all of the CO2 emissions from combustion of textiles as GHG emissions. This

assumption will slightly overstate the net GHG emissions from combustion of mixed

MSW, but the magnitude of the error is small because textiles represent only a small

fraction of the MSW stream. Similarly, the MSW category of "rubber and leather"

contains some biogenic carbon from leather. By not considering this small amount of

biogenic carbon, the analysis slightly overstates the GHG emissions from MSW

combustion.

• Because the makeup of a given community's mixed MSW may vary from the national

average, the energy content may also vary from the national average energy content that

we used in this analysis. For example, MSW from communities with a higher or lower

than average recycling rate may have a different energy content, and MSW with more

than the average proportion of dry leaves and branches will have a higher energy content.

• In our analysis, we used the national average recovery rate for steel. Where waste is sent

to a WTE plant with steel recovery, the net GHG emissions for steel cans will be slightly

lower (i.e., more negative). Where waste is sent to a WTE plant without steel recovery,

the net GHG emissions for steel cans will be the same as for aluminum cans (i.e., close

to zero). We did not credit increased recycling of non-ferrous materials, because of a

lack of information on the proportions of those materials. This tends to overstate net

GHG emissions from combustion.

• We used in this analysis the national average fossil fuel mix for electricity as the proxy

for fuel displaced at the margin when WTE plants displace utility electricity. If some

other fuel or mix of fuels is displaced at the margin (e.g., coal), the avoided utility CO2

would be different (e.g., for coal, the avoided utility CO2 would be about 0.01 MTCE per

ton higher for mixed MSW, and the net GHG emissions would be −0.05 MTCE instead

of −0.04 MTCE per ton).
94

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95

7. LANDFILLING

This chapter presents estimates of GHG emissions and carbon sequestration from landfilling of

each of the materials considered in this analysis and for mixed MSW. For this study, we estimated the

methane emissions, transportation-related carbon dioxide emissions, and carbon sequestration that will

result from landfilling each type of organic waste, and from landfilling mixed MSW.

• When food scraps, yard trimmings, and paper are landfilled, anaerobic bacteria degrade the

materials, producing methane and carbon dioxide. The carbon dioxide is not counted as a GHG

because it is biogenic, as explained in Section 1.7. Because metals do not contain carbon, they do

not generate methane when landfilled. Plastics do not biodegrade, and therefore do not generate

any methane.

• Transportation of waste materials to a landfill results in anthropogenic carbon dioxide emissions,

due to the combustion of fossil fuels in the vehicles used to haul the wastes.

• Because food scraps, yard trimmings, and paper are not completely decomposed by anaerobic

bacteria, some of the carbon in these materials is sequestered in the landfill. However, carbon in

plastic that remains in the landfill is not counted as sequestered carbon (as explained in Section

1.5).

We developed separate estimates of emissions for landfills without gas recovery systems, for

landfills that flare methane, for landfills that combust methane for energy recovery, and for the national

average mix of these three categories. Our national average emission estimate accounts for the extent to

which methane will be flared at some landfills, and will be combusted for energy recovery at others. In

both cases, our projected future landfill gas (LFG) recovery rates anticipate a significant increase in the

use of LFG recovery systems due to a recent EPA rule that requires gas recovery at large MSW landfills.1

From the standpoint of post-consumer GHG emissions, landfilling some materials, including

branches, newspaper, and leaves, results in net sequestration (i.e., carbon storage exceeds methane plus

transportation energy emissions) at all landfills, regardless of whether gas recovery is present. At the

other extreme, food scraps and office paper have net emissions even for landfills with gas recovery and

electricity generation. The remaining materials have net post-consumer emissions that are either very low

(aluminum cans, steel cans, and plastics have transportation-related emissions of 0.01 MTCE per ton,

regardless of whether gas collection is present) or that are borderline, depending on whether the landfill

has gas recovery (e.g., mixed MSW has net emissions at landfills without gas recovery, but net carbon

storage at landfills with gas recovery).

 1

 The rule requires a well-designed and well-operated landfill gas collection system at landfills that (1) have

a design capacity of at least 2.5 million metric tons, or 2.5 million cubic meters, (2) are calculated to emit more than

50 metric tons of nonmethane organic compounds per year, and (3) receive waste on or after November 11, 1987.

(Federal Register, Vol. 61, No. 49, p. 9905, March 12, 1996). It is anticipated that by 2000, some 54 percent of

landfill methane will be generated at landfills with landfill gas recovery systems subject to these requirements or

installed on a voluntary basis.
96

7.1 EXPERIMENTAL VALUES FOR METHANE GENERATION AND CARBON

SEQUESTRATION

To estimate methane emissions and carbon sequestration from landfilling of specific materials,

we used data from laboratory experiments conducted by Dr. Morton Barlaz.2

 The experiments provided

data on (1) the amount of methane generated by each type of organic material, when digested by bacteria

in anaerobic conditions simulating those in a landfill, and (2) the amount of carbon remaining,

undecomposed (i.e., sequestered) at the end of the experiment.

Experimental Design

Dr. Barlaz placed each type of organic waste and mixed MSW in separate reactor vessels, in

which he maintained anaerobic conditions similar to those in a landfill, but controlled to favor maximum

methane generation. Dr. Barlaz measured the amount of methane generated in each reactor, and the

amount of undecomposed carbon remaining in each reactor at the end of the experiment. Each material

was tested in four reactors, and the results from each were averaged. 3

At the start of the experiment, Dr. Barlaz dried a sample of each material, and analyzed the

amount of cellulose, hemicellulose, and lignin (and, for food scraps, protein) in each material. Cellulose,

hemicellulose, and protein partly decompose in a landfill, resulting in methane generation; lignin is

relatively stable and non-decomposable under anaerobic conditions.

Portions of each material were weighed, placed in two-liter plastic containers (i.e., reactors), and

allowed to decompose anaerobically under warm, moist conditions designed to accelerate decomposition.

The reactors were seeded with a small amount of well-decomposed refuse containing an active

population of methane-producing microorganisms (the "seed"), to ensure that methane generation was

not limited due to an insufficient population of microorganisms. To promote degradation, water was

cycled through each reactor. Nitrogen and phosphorus were then added so that methane generation would

not be limited by a lack of these nutrients.

The reactors were allowed to run for periods varying from three months to two years. The

experiment ended for each reactor when one of two conditions were met: (1) no measurable methane was

being emitted (i.e., any methane that was being emitted was below the detection limits of the analytical

equipment), or (2) a curve generated mathematically from an analysis of the reactor's prior methane

generation indicated that the reactor had produced at least 95 percent of the methane that it would

produce if allowed to run indefinitely.

Dr. Barlaz measured the amount of methane generated during the experimental period, and

subtracted the amount of methane attributable to the seed in order to obtain the amount of methane

generated by the material being tested. At the end of the experiment, he opened the reactors, drained the

leachate, dried and weighed the contents, and analyzed the percentage composition of cellulose,

hemicellulose, and lignin (and, for food scraps, protein) in the remaining contents. He then measured the

percentage of total volatile solids in the remaining contents. This amount included the cellulose,

hemicellulose, lignin, and protein, and any other carbon-containing components such as waxes and

tannins.

 2

 Barlaz, M.A., “Biodegradative Analysis of Municipal Solid Waste in Laboratory-Scale Landfills”, EPA

600/R-97-071, 1997. Dr. Barlaz's work was funded by EPA's Air and Energy Engineering Research Laboratory.

3

 Barlaz, op. cit.
97

The experimental results were then used to estimate the amount of each carbon-containing

component remaining that was attributable to the seed,4

 and to estimate the amount of carbon for each

material that remained. It was assumed that the experiment reflected actual landfill conditions, and that

organic carbon remaining undegraded in the reactors would also remain undegraded over the long term in

landfills, i.e., it would be sequestered.

As discussed in Section 4.2, we included three definitions of mixed paper among the materials

analyzed in this report, namely:

• Broadly defined mixed paper, which includes almost all printing-writing paper, folding

boxes, and most paper packaging;

• Residential mixed paper, which includes the typical mix of papers from residential

curbside pick-up (e.g., high-grade office paper, magazines, catalogs, commercial

printing, folding cartons, and a small amount of old corrugated containers); and

• Mixed paper from offices, which includes copy and printer paper, stationary and

envelopes, and commercial printing.

Dr. Barlaz’s experiment did not specifically test mixed paper as defined for recycling purposes,

but it did evaluate four specific grades of paper—newsprint, corrugated boxes, office paper, and coated

paper. To allow development of estimates of methane emissions and carbon sequestration for the three

categories of mixed paper, Franklin Associates started with their detailed characterization of mixed paper

(shown in Exhibit 4-2), and assigned analogs among the four paper grades tested by Dr. Barlaz. Exhibit

7-1 characterizes the composition of the two products made from mixed paper: boxboard (made using

either a broad or a residential mix of recycled paper) and paper towels (made from recycled office paper).

Emissions were calculated using the characterization of mixed paper in Exhibit 7-1 and the values

obtained from Dr. Barlaz’s experiment for newsprint, corrugated boxes, office paper, and coated paper. 5

Methane Generation: Experimental Data and Adjusted Values

The amount of methane generated by each type of organic material (after deducting the methane

attributable to the seed), is shown in column "b" of Exhibit 7-2.

As a check on his experimental results, Dr. Barlaz estimated the amount of methane that would

have been produced if all of the cellulose, hemicellulose, and protein from the waste material that was

decomposed during the experiment had been converted to equal parts of methane and carbon dioxide

(methane-producing microorganisms generate equal amounts, by volume, of methane and carbon dioxide

 4

 Dr. Barlaz tested seed alone to be able to control for the amount of methane generation and carbon

sequestration that was attributable to the seed.

5 Note that Exhibits 7-2 through 7-4 show coated paper but not mixed paper; mixed paper is shown in

Exhibits 7-6 through 7-8. Exhibits 7-2 through 7-8 appear at the end of the chapter.
98

Exhibit 7-1

Proxies for Composition Mixed Paper (percent)

Paper Grade

Broad Definition for

Mixed Paper5

Mixed Paper from

Residential Sources6

Mixed Paper from

Offices7

Newsprint1 24 23 21

Corrugated Boxes 2 48 53 5

Office Paper 3 20 14 38

Coated Paper 4 8 10 36

100 100 100

Explanatory Notes:

1 Includes newsprint, uncoated groundwood paper, recycled folding boxes, and set-up boxes.

2 Includes virgin and recycled corrugated boxes.

3 Includes uncoated free sheet paper, cotton fiber paper, bleached bristols, unbleached kraft folding boxes, bleached

kraft folding boxes, bleached bags and sacks, unbleached bags and sacks, and unbleached wrapping paper.

4 Includes coated free sheet paper and coated groundwood paper.

5

Mixed paper characterized by the broad definition can be remanufactured in an open loop system into recycled

boxboard.

6

Mixed paper characterized by the residential definition can be remanufactured in an open loop system into recycled

boxboard.

7

Mixed paper characterized by the office definition is typically used to manufacture paper towels.

gas).6 Dr. Barlaz referred to this amount as the material's "methane potential." He then calculated the

percentage of the methane potential for each material accounted for by the sum of (1) the measured

methane generation, and (2) the amount of methane that could be formed from the carbon in the leachate

that was removed from the reactor, and from the carbon in the refuse that remained in the reactor at the

end of the experiment.7

 The resulting percentages of the methane potential accounted for are shown in

column "c" of Exhibit 7-2. Methane potential not accounted for could be due to either (1) leaks of

methane, (2) measurement error, or (3) carbon in the cell mass of microorganisms (which was not

measured).

Methane recovery was below 85 percent of the "methane potential" for five materials: office

paper, coated paper, food scraps, leaves, and branches. In using Dr. Barlaz's data, we needed to make a

choice regarding how to allocate this missing carbon. We chose to assume that some of it had been

converted to microorganism cell mass, and the remainder had been degraded. Dr. Barlaz postulated a

higher methane yield based on assumptions that (1) five percent of the carbon in cellulose and

hemicellulose (and protein in the case of food scraps) that was degraded was converted into the cell mass

of the microbial population, and (2) 90 percent of the carbon-containing compounds that were degraded

but not converted to cell mass were converted to equal parts of methane and carbon dioxide. The

"corrected yields," based on these assumptions, are shown in column "d" of Exhibit 7-2.

 6

 Ibid. Lignin was not considered in this check because cellulose, hemicellulose, and protein account for

nearly all of the methane generated.

7

 Note that any carbon that was converted to cell mass in microorganisms was not considered in this

calculation.
99

We decided, in consultation with Dr. Barlaz, to use the "corrected yields" for leaves, branches,

and office paper because we believed that these values were more realistic than the measured yields.8

The methane values that we used for each material (either the measured yield, or the "corrected"

yield) are shown again in column "f" of Exhibit 7-2. In order to maintain consistent units with the other

parts of our analysis, we converted the units for methane generation from milliliters per dry gram of

waste, to metric tons of carbon equivalent (MTCE) per wet ton of waste.9

 The resulting values are shown

in column "g" of Exhibit 7-2. The value for yard trimmings is a weighted average of the values for grass,

leaves, and branches, based on an assumption that yard trimmings are composed of 50 percent grass, 25

percent leaves, and 25 percent branches (on a wet weight basis).

Carbon Sequestration: Experimental Data and Calculations

Carbon sequestration was estimated by calculating the amount of carbon remaining in each

reactor at the end of the experiment, and then subtracting the amount of carbon remaining that was

attributable to the seed. The difference between the two values is the amount of carbon from the waste

material that remained in the reactor, undecomposed, at the end of the experiment. Because the

conditions in the reactor simulated landfill conditions (favorable to optimized decomposition),

approximately this amount of carbon would be sequestered if the material were landfilled. Carbon

sequestration for each material is presented in Exhibit 7-3.10

7.2 FATES OF LANDFILL METHANE: CONVERSION TO CO2, EMISSIONS, AND

FLARING OR COMBUSTION WITH ENERGY RECOVERY

In this analysis, we accounted for (1) the conversion in the landfill of some portion of landfill

methane to CO2, and (2) the capture of methane, either for flaring or for combustion with energy

recovery (in either case, the captured methane is converted to CO2).11 Exhibit 7-4 presents this analysis.

The exhibit begins with the methane generation per wet ton of each material, which is shown in

column "b" (the values were simply copied from the last column of Exhibit 7-2). The next three sections

of the exhibit calculate net GHG emissions from methane generation for each of three categories of

landfills: (1) landfills without LFG recovery, (2) landfills with LFG recovery that flare LFG, and (3)

landfills with LFG recovery that generate electricity from the LFG. The second to last section of the

 8

 The corrected yield was not available for coated paper. For food scraps, even though the methane potential

recovery percentage was lower than 85 percent, we used the measured yield, as shown in column "b." We made this

choice for food scraps because the "corrected yield" for food scraps was greater than the maximum possible yield

(shown in column "e" of the exhibit). Dr. Barlaz had calculated the maximum possible yield for each material based

on the methane yield if all of the cellulose, hemicellulose, and protein in the material: (1) decomposed and (2) were

converted to equal parts of methane and carbon dioxide.

9

 To make the conversion, we used the ratio of dry weight to wet weight for each material and a global

warming potential of 21 for methane.

10 The approach for estimating carbon sequestration is more fully described in, Barlaz, Morton, “Carbon

Storage During Biodegradation of Municipal Solid Waste Components in Laboratory-Scale Landfills,” paper

submitted for publication, Department of Civil Engineering, North Carolina State University, Raleigh, NC, 1997.

11 The CO2 that is emitted is not counted as a GHG because it is biogenic in origin (as described in Section

1.6).
100

exhibit shows the expected percentage of landfills in each category in 2000. The final column shows the

weighted average GHG emissions from methane generation across all types of landfills in 2000.

To estimate MSW methane emissions from each category of landfill, we first needed to estimate

the percentage of landfill methane that is oxidized near the surface of the landfill. We estimated that 10

percent of the landfill methane that is generated is either chemically oxidized or converted by bacteria to

CO2,

 12 and that the remaining 90 percent is available for atmospheric methane emissions.13

To estimate MSW methane emissions from landfills with LFG recovery, we used the assumption

that these landfills will have an average LFG recovery efficiency of 75 percent by 2000.14 Further, to

estimate emissions for landfills that recover and then combust LFG to generate electricity, we estimated

the avoided utility GHG emissions per unit of methane combusted and then added the avoided emissions

to the net GHG emissions from methane generation (our calculations to develop this estimate are shown

in Exhibit 7-5).

We also projected the percentage of MSW disposed in each category of landfill in 2000. We

estimated that by the year 2000, when large landfills with substantial LFG emissions will be required to

recover LFG, 54 percent of all landfill methane will be generated at landfills with recovery systems, and

46 percent will be generated at landfills without LFG recovery.15 Of the 54 percent of all methane

generated at landfills with LFG recovery, 91 percent (or 49 percent of all methane) is expected to be

generated at landfills that use LFG to generate electricity, and 9 percent (or 5 percent of all methane) at

landfills that flare LFG.16, 17 By basing our analysis on projected LFG recovery by the year 2000 (and the

projected LFG recovery efficiency in 2000), we avoided double-counting of GHG reductions between

programs that reduce landfilling and programs that increase recovery of landfill methane.

 12 An oxidation rate of 10 percent is cited by Liptay, K., J. Chanton, P. Czepiel, and B. Mosher, Use of

stable isotopes to determine methane oxidation in landfill cover soils, Journal of Geophysical Research, April 1998,

103(D7), pp. 8243-8250; and Czepiel, P.M., B. Mosher, P.M. Crill, and R.C. Harriss, Quantifying the effects of

oxidation on landfill methane emissions, Journal of Geophysical Research, 1996, 101, pp. 16721-16729.

13 US EPA, Office of Air and Radiation, Anthropogenic Methane Emissions in the United States: Estimates

for 1990 (Washington, D.C.: US EPA) April 1993, page 4-20.

14 Several commenters on the draft version of this report suggested a range of values; 75 percent was most

often cited as a best estimate. Comments on the Draft Municipal Solid Waste Greenhouse Gas Report from Martin

Felker, Senior Environmental Engineer, Waste Management, dated July 28, 1997; Karen Harrington, Principal

Planner of the Minnesota Office of Environmental Assistance, dated July 28, 1997; Maria Zannes, President,

Integrated Waste Services Association, dated August 25, 1997 and October 15, 1997; and David Sussman, Poubelle

Associates, dated June 17, 1997.

15 Based on data on (1) year 2000 MSW landfill methane generation of 64.5 million MTCE, (2) year 2000

landfill methane recovery of 40.0 million MTCE, and (3) projected year 2000 landfill methane recovery efficiency of

85 percent (all from the memorandum from Cindy Jacobs, of the US EPA Atmospheric Pollution Prevention

Division to Michael Podolsky of the US EPA Office of Policy, Planning and Evaluation, July 25, 1995). EPA’s

current estimates of landfill methane generation and recovery differ from the values in this memo.

16 Memorandum from Cindy Jacobs, op cit.

17 The assumption that 91 percent of landfills recovering methane will use it to generate electricity is subject

to change over time based upon changes in the cost of recovery, and the potential payback. Additionally, new

technologies may arise that use recovered methane for purposes other than generating electricity.
101

Our results are shown in the final column of Exhibit 7-4. The materials with the highest rates of

net GHG emissions from methane generation – office paper and corrugated boxes – also have the highest

gross methane generation, as shown in column "b" of Exhibit 7-4. The recovery of methane at landfills

reduces the methane emissions for each material in proportionate amounts, but does not change the

ranking of materials by methane emissions. Leaves and branches have the lowest rates of net GHG

emissions from methane generation.

The three sections of the exhibit providing GHG emissions estimates for each category of landfill

(in columns "d," "g," and "j") may be used by local MSW planners to estimate GHG emissions from

MSW in a given community. For this purpose, one should add to the values in the appropriate column the

estimated transportation GHG emissions (the national average used in this study is 0.01 MTCE per ton),

and subtract estimated carbon sequestration (as shown for each material in Exhibit 7-3).

Anthropogenic Carbon Dioxide Emissions from Transportation of Wastes to a Landfill

We next estimated the anthropogenic carbon dioxide emissions from transporting waste materials

to a landfill. We began with estimates provided by Franklin Associates, Ltd. for the amount of diesel fuel

required per ton of waste material for (1) collecting and transporting the material to a landfill (297,000

BTUs), and (2) operating the landfill equipment (231,000 BTUs).18 We converted these estimates to units

of metric tons of carbon equivalent (MTCE) per short ton, based on a carbon coefficient of 0.0208

MTCE per million BTUs of diesel fuel. This resulted in an estimate of 0.01 MTCE of anthropogenic CO2

emissions per short ton of material landfilled.

7.3 NET GHG EMISSIONS FROM LANDFILLING

To determine the net GHG emissions from landfilling each material, we summed the net GHG

emissions from methane generation, carbon sequestration (treated as negative emissions), and

transportation CO2 emissions. The results are shown in Exhibit 7-6.

As the exhibit shows, the post-consumer results for organic materials vary widely. Landfilling

some materials, including branches, newspaper, and leaves, results in net sequestration (i.e., carbon

storage exceeds methane plus transportation energy emissions) at all landfills, regardless of whether gas

recovery is present. At the other extreme, food scraps and office paper have net emissions even for

landfills with gas recovery and electricity generation. The remaining materials have net emissions that

are either very low (aluminum cans, steel cans, and plastics have transportation-related emissions of 0.01

MTCE per ton, regardless of whether gas collection is present) or that are borderline, depending on

whether the landfill has gas recovery (e.g., mixed MSW has net emissions at landfills without gas

recovery, but net carbon storage at landfills with gas recovery). Based on projected rates of landfill gas

recovery in 2000, office paper, food scraps, mixed paper, and corrugated cardboard will, on average,

exhibit net emissions, and branches, newspaper, and leaves will exhibit net sequestration.

 18 Franklin Associates, Ltd., The Role of Recycling in Integrated Solid Waste Management to the Year 2000

(Stamford, CT: Keep America Beautiful), September 1994, p. I-5.
102

7.4 LIMITATIONS OF THE ANALYSIS

Perhaps the most important caveat to the analysis of GHG emissions and sequestration associated

with landfilling is that it is based on a single set of laboratory experiments, those conducted by Dr.

Morton Barlaz. While researchers other than Dr. Barlaz have conducted laboratory studies that track the

degradation of mixed MSW, his experiments were the only ones we identified that rigorously tested

materials on an individual basis. Dr. Barlaz is recognized as an expert on the degradation of different

fractions of MSW under anaerobic conditions, and his findings with respect to the methane potential of

mixed MSW are within the range used by landfill gas developers. Nevertheless, given the sensitivity of

the landfill results to estimated methane generation and carbon sequestration, we recognize that more

research is needed in this area.

Another important caveat relates to our estimate that 54 percent of MSW landfill methane

generated in the year 2000 will be generated at landfills with LFG recovery systems. This would be an

increase from the estimated 17 percent of landfill methane generated at landfills with LFG recovery in

1995. The net GHG emissions from landfilling each material are quite sensitive to the LFG recovery rate.

Because of the high global warming potential for methane, small changes in the LFG recovery rate by the

year 2000 could have a large effect on the net GHG impacts of landfilling each material, and on the

ranking of landfilling relative to other MSW management options. The effects of different rates of LFG

recovery by the year 2000 are shown in Exhibit 7-7. Column "b" of the exhibit shows net GHG emissions

at the 1995 recovery rate of 17 percent. The remaining columns show net GHG emissions at increasing

LFG recovery rates, up to a 60 percent recovery rate (exceeding 54 percent, the rate projected for 2000).

As the exhibit shows, the net post-consumer GHG emissions for landfilling mixed MSW are positive at

lower rates of recovery, and turn negative only when the LFG recovery rate exceeds 40 percent. At the

local level, the GHG emissions from landfilling MSW are quite different depending on whether the local

landfill has LFG recovery, as shown in Exhibits 7-4 and 7-6.

Because the national average estimate of emissions is based on LFG recovery levels expected by

the year 2000, there are several limitations associated with the use of this emission factor. First, landfill

methane emissions prior to 2000 will not be recovered at the year 2000 levels, thus, keeping organic

materials out of landfills prior to the year 2000 will have GHG benefits in excess of those estimated here.

Second, because landfill methane generation occurs over time and has significant timing delays (i.e.,

methane generation may not begin until a few years after the waste is deposited in the landfill and can

continue for many years after the landfill is closed), the values listed in this chapter represent total

methane generated, over time, per ton of waste landfilled. To the extent that LFG recovery rates shift

dramatically over time, these shifts are not reflected in the analysis. Third, landfills with LFG recovery

will be permitted, under EPA regulations, to remove the LFG recovery equipment when three conditions

are met: (1) the landfill is permanently closed, (2) LFG has been collected continuously for at least 15

years, and (3) the landfill emits less than 50 metric tons of nonmethane organic compounds per year.19

Although the removal of LFG recovery equipment will permit methane from closed landfills to escape

into the atmosphere, the amounts of methane emitted should be relatively small, because of the relatively

long time period required for LFG collection before LFG recovery equipment is removed.

Methane oxidation rate and landfill gas collection system efficiency are also important factors

driving results. We used values of 10 percent and 75 percent, respectively, as best estimates for these

factors. Commenters on the draft report and sources in the literature have reported estimates ranging

from about 5 percent to 40 percent for oxidation, and from about 60 to 95 percent for collection system

 19 Federal Register, Vol. 61, No. 49, p. 9907.
103

efficiency. We investigated the sensitivity of our results to these assumptions; our results are shown in

Exhibit 7-8. We portray the sensitivity as a bounding analysis, i.e., we use the combinations of variables

yielding the upper bound emission factor (5 percent oxidation, 60 percent collection efficiency) and the

lower bound (40 percent oxidation, 95 percent efficiency).20 As the exhibit shows, the materials most

sensitive to these variables are those with the highest methane generation potential, i.e., office paper,

mixed paper, and food scraps. Sensitivity varies—the difference between upper and lower bounds ranges

from 0.06 MTCE/ton for leaves and branches to 0.43 MTCE/ton for office paper. The post-consumer

emission factors of several materials – corrugated cardboard, mixed paper, grass, and mixed MSW –

change from having net sequestration under the lower bound to having net emissions under the upper

bound.

It is also likely that ongoing shifts in the use of landfill cover and liner systems could influence

the rate of methane generation and collection. As more landfills install effective covers and implement

controls to keep water and other liquids out, conditions will be less favorable for degradation of organic

wastes. Over the long term, it is possible that this will result in a decrease in methane generation and an

increase in carbon sequestration. Moreover, Dr. Barlaz believes that the methane yields from his

laboratory experiments are likely to be higher than methane yields in a landfill, because the laboratory

experiments were designed to generate the maximum amount of methane possible. If the methane yields

used in this analysis are higher than yields in a landfill, the net GHG emissions from landfilling organic

materials would be lower than estimated here.

We assumed that once wastes are disposed in a landfill, they are never removed. In other words,

we assumed that landfills are never "mined." (A number of communities have mined their landfills –

removing and combusting the waste – in order to create more space for continued disposal of waste in the

landfill.) To the extent that landfills are mined in the future, it is incorrect to assume that carbon

sequestered in a landfill will remain sequestered. For example, if landfilled wastes are later combusted,

the carbon that was sequestered in the landfill will be oxidized to CO2 in the combustor.

For landfilling of yard trimmings (and other organic materials), we assumed that all carbon

storage in a landfill environment is incremental to the storage that occurs in a non-landfill environment.

In other words, we assumed that in a baseline where yard trimmings are returned to the soil (i.e., in a

non-landfill environment), all of the carbon is decomposed relatively rapidly (i.e., within several years) to

CO2, and there is no long-term carbon storage. To the extent that long-term carbon storage occurs in the

baseline, the estimates of carbon sequestration reported here are overstated, and the net post-consumer

GHG emissions are understated.

Finally, our spreadsheet analysis is limited by the assumptions that were made at various steps in

the analysis, as described throughout this chapter. The key assumptions that have not already been

discussed as limitations are the assumptions used in developing "corrected" methane yields for organic

materials in MSW. Because of the high global warming potential of methane, a small difference between

estimated and actual methane generation values would have a large effect on the GHG impacts of

landfilling, and on the ranking of landfilling relative to other MSW management options.

 20 The table also reports two intermediate combinations, including the best estimate values.
104

Exhibit 7-2

Methane Yield for Solid Waste Components

(a) (b) (c) (d) (e) (f

Average Measured Percentage of "Corrected" Maximum Possible Selec

Methane Yield "Methane Potential" Methane Yield Methane Yield Methan

Material (ml per dry gm) Accounted For (ml per dry gram) (ml per dry gram) (ml per d

Newspaper 74.2 98.0 NA 239.4 Office Paper 217.3 55.5 346.0 398.2 Corrugated Boxes 152.3 87.7 NA 279.7 Coated Paper 84.4 83.7 NA NA Food Scraps 300.7 77.4 386.2 357.6 Grass 144.3 89.3 NA 153.2 Leaves 30.5 75.2 56.0 108.0 Branches 62.6 82.8 76.3 224.9 Yard Trimmings 

Mixed MSW 92.0 97.6 NA 157.6 

Note that totals may not add due to rounding and more digits may be displayed than are significant.Note that Exhibits 7-1 to 7-3 show coated paper but not mixed paper; mixed paper is shown in Exhibits 7-5 and 7-6. The values for the differetypes of mixed paper are based on the proportion of the four paper types (newspaper, office paper, corrugated cardboard, and coated paperthat comprise the different "mixed paper" definitions.
105

Explanatory Notes for Exhibit 7-3:(1) Because MSW is typically measured in terms of its wet weight, we needed to convert the ratios for carbon sequestered as a fraction sequestered as a fraction of wet weight. To do this, we used the estimated ratio of dry weight to wet weight for each material. These rati“c” of the exhibit. For most of the materials, we used data from an engineering handbook.21 For grass, leaves, and branches, we used dat

(2) For consistency with the overall analysis, we converted the carbon sequestration values for each material to units of metric tons of casequestered per short ton of waste material landfilled. The resulting values are shown in column “e” of the exhibit.

21 Tchobanoglous, George, Hilary Theisen, and Rolf Eliassen, Solid Wastes: Engineering Principles and Management Issues (

Book Co.) 1977, pp. 58 and 60.

Exhibit 7-3

Carbon Sequestration for Solid Waste Components

(a) (b) (c) (d) (e)

(d = b * c)

Ratio of Carbon Ratio of Carbon Amount of

Sequestration Ratio of Dry Sequestration Carbon

to Dry Weight Weight to to Wet Weight Sequestered

Material (gm C/dry gm) Wet Weight (gm C/wet gm) (MTCE per Wet Ton)

Newspaper 0.42 0.94 0.39 0.36Office Paper 0.05 0.94 0.05 0.04Corrugated boxes 0.26 0.95 0.25 0.22Coated Paper 0.34 0.94 0.32 0.29Food Scraps 0.08 0.30 0.02 0.02Grass 0.32 0.40 0.13 0.12Leaves 0.54 0.80 0.43 0.39Branches 0.38 0.60 0.23 0.21Yard Trimmings 0.23 0.21Mixed MSW 0.22 0.80 0.18 0.16

Note that more digits may be displayed than are significant.
106

Exhibit 7-4

Net GHG Emissions from Methane Generation

Methane from Landfills Without Percenta

Methane Recovery Flaring Each Ty

(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) 

(g+i)

Net GHG Percentage of Percentage of Net GHG Utility CO2 Utility Net GHG Percentage of 

Percentage Emissions Methane Not Methane Not Emissions Emissions CO2 Emissions Methane From 

CH4 Of Methane from CH4 Recovered Recovered From CH4 Avoided Per Emissions From CH4 Landfills Without 

Generation Not Generation (100 % Minus That is Not Generation MTCE CH4 Avoided Generation LFG 

(MTCE/ Oxidized (MTCE/ LFG Collection Oxidized (MTCE/ Combusted (MTCE/ (MTCE/ Recovery 

Material Wet Ton) to CO2 Wet Ton) System Efficiency) to CO2 Wet Ton) (MTCE) Wet Ton) Wet Ton) in 2000 

Newspaper 0.259 90% 0.23 25% 90% 0.06 -0.18 -0.04 0.02 46% Office Paper 1.207 90% 1.09 25% 90% 0.27 -0.18 -0.16 0.11 46% Corr. Boxes 0.537 90% 0.48 25% 90% 0.12 -0.18 -0.07 0.05 46% Coated Paper 0.294 90% 0.26 25% 90% 0.07 -0.18 -0.04 0.03 46% Food Scraps 0.335 90% 0.30 25% 90% 0.08 -0.18 -0.05 0.03 46% Grass 0.214 90% 0.19 25% 90% 0.05 -0.18 -0.03 0.02 46% Leaves 0.166 90% 0.15 25% 90% 0.04 -0.18 -0.02 0.01 46% Branches 0.170 90% 0.15 25% 90% 0.04 -0.18 -0.02 0.02 46% Yard Trimmings 0.191 90% 0.17 25% 90% 0.04 -0.18 -0.03 0.02 46% Mixed MSW 0.273 90% 0.25 25% 90% 0.06 -0.18 -0.04 0.02 46% 

Note that totals may not add due to rounding and more digits may be displayed than are significant.

Electricity Generation

Methane from Landfills With LFG Recovery and:
107

Exhibit 7-5

Calculation to Estimate Utility GHGs Avoided

Through Combustion of Landfill Methane

Step Value Source

Metric tons CH4/MTCE CH4 0.17 1/((12/44)*Global warming potential of CH4)

Grams CH4/metric ton CH4 1.00E+06 Physical constant

Cubic ft. CH4/gram CH4 0.05 1/20: 20 grams per cubic foot of methane at standard temperature and pressure

BTUs/cubic ft. CH4 1,000 "Opportunity for LF Gas Energy Recovery in Kentucky," USEPA/OAR September 97, p. 2-12kWh electricity generated/BTU 0.00008 1/13,000: from "Opportunity" report p. 2-11, assumes use of internal combustion engineskWh electricity delivered/kWh electricity generated 0.95 U.S. DOE, EIA, "Annual Energy Review 1993 (Washington, DC: DOE/EIA) July 1994, p. 252

BTUs/kWh electricity delivered 3,412 Physical constantKg. utility C avoided/BTU delivered electricity 8.349E-05 0.08349 MTCE/mmBTU delivered electricity, from Exhibit 6-3. This assumes that LFG energy recovery 

Metric Tons avoided utility C/kg utility C 0.001 1000 kg per metric tonRatio of MTCE avoided utility C per MTCE CH4 0.18 Product from multiplying all factors
108

Exhibit 7-6

Net GHG Emissions from Landfilling

(a) (b) (c) (d) (e) (e = b + c + d

Net GHG Emissions from CH4 Generation GHG Net GHG Emissions from 

(MTCE/Wet Ton) Net Emissions (MTCE/Wet Ton

Landfills Landfills With Landfills With Projected Carbon from Landfills Landfills With La

Without LFG LFG Recovery LFG Recovery and National Sequestration Transportation Without LFG LFG Recovery LFG 

Material Recovery and Flaring Electric Generation Average (MTCE/Wet Ton) (MTCE/Wet Ton) Recovery and Flaring Elec

Newspaper 0.23 0.06 0.02 0.12 -0.36 0.01 -0.11 -0.29 Office Paper 1.09 0.27 0.11 0.56 -0.04 0.01 1.05 0.24 Corrugated Cardboard 0.48 0.12 0.05 0.25 -0.22 0.01 0.27 -0.09 Coated Paper 0.26 0.07 0.03 0.14 -0.29 0.01 -0.01 -0.21 Mixed Paper Broad Definition 0.53 0.13 0.05 0.27 -0.23 0.01 0.31 -0.08  Residential Definition 0.49 0.12 0.05 0.25 -0.24 0.01 0.26 -0.10  Office Paper Definition 0.58 0.15 0.06 0.30 -0.21 0.01 0.39 -0.05 Aluminum Cans 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 Steel Cans 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 Glass 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 HDPE 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 LDPE 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 PET 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 Food Scraps 0.30 0.08 0.03 0.16 -0.02 0.01 0.29 0.06 Grass 0.19 0.05 0.02 0.10 -0.12 0.01 0.09 -0.06 Leaves 0.15 0.04 0.01 0.08 -0.39 0.01 -0.23 -0.34 Branches 0.15 0.04 0.02 0.08 -0.21 0.01 -0.04 -0.16 Yard Trimmings 0.17 0.04 0.02 0.09 -0.21 0.01 -0.02 -0.15 Mixed MSW 0.25 0.06 0.02 0.13 -0.16 0.01 0.10 -0.09 Note that totals may not add due to rounding and more digits may be displayed than are significant.
109

Exhibit 7-7

Net GHG Emissions from Landfilling

Sensitivity Analysis: Varying the Percentage of Waste Disposed

at Landfills with Methane Recovery

(a) (b) (c) (d) (e) 

17% 30% 46% 50% 

of waste disposed of waste disposed of waste disposed of waste disposed 

at landfills with at landfills with at landfills with at landfills with 

Material LFG recovery LFG recovery LFG recovery LFG recovery 

Newspaper -0.15 -0.18 -0.21 -0.22 Office Paper 0.89 0.77 0.61 0.57 Corrugated Cardbd 0.20 0.14 0.07 0.06 Coated Paper -0.05 -0.08 -0.12 -0.13 Mixed Paper 

 Broad Def'n. 0.23 0.17 0.10 0.08  Residential Def'n. 0.19 0.13 0.06 0.05  Office Paper Def'n. 0.30 0.23 0.15 0.13 

Food Scraps 0.25 0.21 0.17 0.16 Grass 0.06 0.04 0.01 0.00 Leaves -0.25 -0.27 -0.29 -0.30 Branches -0.07 -0.08 -0.11 -0.11 Yard Trimmings -0.05 -0.07 -0.09 -0.10 Mixed MSW 0.06 0.03 0.00 -0.01 

Note that totals may not add due to rounding and more digits may be displayed than are significant.Note: Of the methane that is captured, we assumed that 9% is flared and 91% is recovered for energy.
110

Exhibit 7-8

Net GHG Emissions from Landfilling

Sensitivity Analysis: Varying Oxidation and 

Gas Collection Efficiency Rates. Based on projected

national mix of landfill gas recovery systems for 2000.

Oxidation Rate: 40% 10% 5%

Collection 

Efficiency: 95% 75% 60%

Lower bound Best estimate Upper bound

Material emissions emissions

Newspaper -0.29 -0.23 -0.20Office Paper 0.23 0.53 0.66Corrugated Cardbd -0.10 0.04 0.10Coated Paper -0.22 -0.14 -0.11Mixed Paper 

 Broad Def'n. -0.09 0.06 0.12 Residential Def'n. -0.11 0.03 0.09 Office Paper Def'n. -0.06 0.11 0.18

Food Scraps 0.06 0.15 0.18Grass -0.06 -0.01 0.02Leaves -0.35 -0.30 -0.29Branches -0.16 -0.12 -0.10Yard Trimmings -0.16 -0.11 -0.09Mixed MSW -0.09 -0.02 0.01

Note that totals may not add due to rounding and more digits may be displayed than are significant.
111

8. ACCOUNTING FOR EMISSION REDUCTIONS

Earlier chapters of this report examined the GHG emissions from (1) raw materials acquisition

and manufacturing (and forest carbon sequestration for paper products) and (2) waste management. This

chapter combines information from the earlier chapters to present a picture of the life cycle GHG

emissions associated with raw materials acquisition, manufacturing, and then managing as waste, each of

the materials considered in this analysis.

Management of municipal solid waste presents many opportunities for GHG emission

reductions. Source reduction and recycling can reduce GHG emissions at the raw materials acquisition

and manufacturing stage, increase forest carbon storage, and avoid landfill methane emissions. When

waste is combusted, energy recovery displaces fossil fuel-generated electricity from utilities (thus

reducing GHG emissions from the utility sector), and landfill methane emissions are avoided. Landfill

methane emissions can be reduced by using gas recovery systems and by diverting organic materials

away from the landfill.

In order to support a broad portfolio of climate change mitigation activities covering a broad

scope of greenhouse gases, many different emission estimation methodologies will need to be employed.

The primary result of this research is the development of material-specific GHG emission factors which

can be used to account for the climate change benefits of waste management practices. 1 These emission

factors are summarized in the following pages.

In the discussion that follows, we focus on national average conditions. For example, we

represent landfills as having the national average landfill gas collection efficiency, and represent

combustors based on mass burn units with national average collection efficiency of ferrous metal. As

shown in the previous chapters, the GHG emission factors are sensitive to many variables, including

several that are site-specific; thus, at specific locations, the emission factors can differ from those

described below. A spreadsheet accounting tool, the Waste Reduction Model (WARM), is being

developed to allow for customizing of emission factors based on key variables (e.g., landfill gas

collection, electric utility fuel mix, transportation distances) which may better reflect local conditions.

8.1 GHG EMISSIONS FOR EACH WASTE MANAGEMENT OPTION

This section presents the life cycle GHG emissions for each waste management option, for each

material considered. These emissions are shown in five exhibits that recapitulate the GHG emissions and

sinks analyzed in detail in earlier chapters.2

 As mentioned in Chapter 1, we used a waste generation

reference point for measuring GHG emissions. That is, one can begin accounting for GHG emissions at

the point of waste generation. All subsequent emissions and sinks from waste management practices are

 1

 Note that the exhibits presented in this chapter are intended to present the GHG impacts of the different

MSW management options for the specific materials examined and are not intended to compare materials.

2

 We did not provide an exhibit for composting. As described in Chapter 5, we performed a bounding

analysis and concluded that net GHG emissions from composting are zero or close to zero.
112

then counted. Changes in emissions and sinks from raw material acquisition and manufacturing processes

are captured to the extent that certain waste management practices (i.e., source reduction and recycling)

impact these processes (for reference, GHG emissions from raw materials acquisition and manufacturing

are shown in the first column of several exhibits in this chapter). Negative emission factors indicate that

from the point of waste generation, some MSW management options can reduce GHG emissions.

Exhibit 8-1 shows the life cycle GHG reductions associated with source reduction. In brief, the

exhibit shows that, for all of the manufactured materials evaluated, source reduction results in GHG

emission reductions. On a per-ton basis, the metals (aluminum cans and steel cans) have greatest

emission reduction potential, due primarily to reductions in energy use in the raw material acquisition

and manufacturing step.

Exhibit 8-2 shows the life cycle GHG emissions associated with recycling materials. The third

through fifth columns in this exhibit show the GHG reductions associated with using recycled inputs in

place of virgin inputs when the material is remanufactured. As the final column in the exhibit indicates,

recycling generally results in negative emissions (measured from the point of waste generation).

Emission reductions associated with recycling are due to several factors, including avoided waste

management emissions and reduced process energy emissions.3

 In addition, emission reductions from

recycling paper products (when measured at the point of waste generation) are due in part to the forest

carbon sequestration benefits of recycling paper.

Exhibit 8-3 presents the life cycle GHG emissions from combusting each of the materials

considered. This exhibit shows emissions for mass burn facilities with the national average rate of

ferrous recovery; results for RDF facilities are similar. As the exhibit shows, mixed MSW combustion

has net emissions of –0.04 MTCE/ton. Net GHG emissions are positive for plastic and negative for paper

products, steel cans, food scraps, and yard trimmings.

GHG emissions from landfilling each of the materials is shown in Exhibit 8-4. The values in the

final column indicate that net GHG emissions from landfilling mixed MSW, under anticipated national

average conditions in 2000, are slightly negative. Among individual materials, emissions are lowest for

newspaper and yard trimmings, and highest for office paper and food scraps. For the other materials, the

net emissions are close to zero, ranging from 0.01 MTCE/ton for steel, aluminum, glass, and plastics to

0.10 MTCE/ton for mixed paper (from office sources).

As discussed in Chapter 7 and shown in Exhibit 7-6, the results for landfills are very sensitive to

site-specific factors. Landfill gas collection practices significantly influence the net GHG emissions from

landfilling the organic materials. For mixed MSW, net emissions are 0.10 MTCE/ton in landfills without

landfill gas collection, and -0.12 MTCE/ton in landfills with landfill gas collection and energy recovery.

The largest differences attributable to landfill gas recovery are for office paper (range of almost 1

MTCE/ton), corrugated cardboard, and mixed paper. The methane oxidation rate and gas collection

system efficiency also have a strong influence on the estimated net emissions for mixed waste and the

organic materials.

Exhibit 8-5 displays the net emissions for each of the management options. In addition, it adds a

row for “Mixed Recyclables,” and provides estimates for recycling, combustion, and landfilling this

category of materials. We developed the emission factors for mixed recyclables by calculating the

 3

 Corrugated cardboard and mixed paper (broad and residential definitions) recycling actually have higher

energy GHG emissions, because production with recycled inputs uses fossil fuel-derived energy, while production

from virgin inputs uses high proportions of biomass fuel (CO2 from such fuel is not counted in GHG inventories).
113

average emission factor (weighted by tons recycled in 19964) for newspaper, office paper, corrugated

cardboard, aluminum cans, steel cans, HDPE containers, LDPE containers, and PET containers. The

exhibit provides a summary of the emission factors, in terms of national average emissions for each

management option and each material. When reviewing the emission factors, it is important to recall

caveats that appear throughout this report. In particular, these estimates do not reflect site-specific

variability, and they are not intended to compare one material to another. A brief recap of how to apply

the emission factors appears in the following section.

8.2 APPLYING EMISSION FACTORS

The net GHG emission estimates presented in Exhibits 8-1 through 8-5 (and the more detailed

estimates in the preceding chapters) provide emission factors that may be used by organizations

interested in quantifying and voluntarily reporting emissions reductions associated with waste

management practices. In conjunction with the Department of Energy, EPA has used these estimates as

the basis for developing guidance for voluntary reporting of GHG reductions, as authorized by Congress

in Section 1605(b) of the Energy Policy Act of 1992. Other potential applications include evaluating the

progress of voluntary programs aimed at source reduction and recycling, such as EPA’s WasteWi$e, Payas-You-Throw, and other Climate Change Action Plan programs.

In order to apply the emission factors presented in this report, one must first establish two

scenarios: a baseline scenario that represents current management practices (e.g., disposing 10 tons per

year of office paper in a landfill without LFG collection); and an alternative scenario that represents the

alternative management practice (e.g., recycling the same 10 tons of office paper).5, 6

 The emission factors

developed in this report can then be used to calculate emissions under both the baseline and the

alternative management practices. Once emissions for the two scenarios have been determined, one

calculates the difference between the alternative scenario and the baseline scenario. The result represents

the GHG emission reductions or increases attributable to the alternative waste management practice.

Exhibit 8-6 illustrates the results of this procedure in a scenario where the baseline management

scenario is disposal in a landfill with national average conditions (i.e., the weighted average in terms of

landfill gas recovery practice). Alternative scenarios involve source reduction, recycling, composting, or

combustion. The values in the cells of the matrix represent the incremental change in GHG emissions.

For example, recycling one ton of office paper, rather than landfilling it, reduces GHG emissions by 1.35

MTCE (this is the second value in the “Recycling” column of the exhibit). Continuing the example from

the previous paragraph, if a business implements an office paper recycling program, and annually diverts

10 tons of office paper (that would otherwise be landfilled) to recycling, the GHG emission reductions

are: 10 tons/yr * 1.35 MTCE/ton = 13.5 MTCE/yr.

 4

 Characterization of Municipal Solid Waste in the United States: 1997 Update, US EPA, Office of Solid Waste and

Emergency Response, (May 1998).

5

 In calculating emissions for the scenarios, two different reference points can be used. These reference

points are described in detail in Section ES.5. Because the desired information is the difference in emissions between

the baseline and alternative scenarios, either reference point yields the same result.

6 The emission factors are expressed in terms of GHG emissions per ton of material managed. In the case of

recycling, we define 1 ton of material managed as 1 ton collected for recycling. As discussed in Chapter 4, the

emission factors can be adjusted to calculate GHG emissions in terms of tons of recycled materials as marketed

(reflecting losses in collection and sorting processes), or changes in the recycled content of products.
114

(MTCE/Ton of Material Source Reduced)

Emissions Measured from a Waste Generation Reference Point1

(b) Forest Carbon Sequestration 

(c)

Source Reduction Source Source Reduction Source Source ReducDisplaces Current Reduction Displaces Current Reduction Waste Displaces Cur

Mix of Virgin and Displaces Virgin Mix of Virgin and Displaces Virgin Management Mix of Virgin 

Material Recycled Inputs Inputs Recycled Inputs Inputs Emissions Recycled Inp

Newspaper -0.48 -0.55 -0.43 -0.73 0.00 Office Paper -0.52 -0.56 -0.50 -0.73 0.00 Corrugated Cardboard -0.41 -0.38 -0.38 -0.73 0.00 Mixed Paper Broad Definition NA NA NA NA NA  Residential Definition NA NA NA NA NA  Office Paper Definition NA NA NA NA NA Aluminum Cans -2.98 -5.39 0.00 0.00 0.00 Steel Cans -0.84 -1.12 0.00 0.00 0.00 Glass -0.14 -0.16 0.00 0.00 0.00 HDPE Containers -0.61 -0.70 0.00 0.00 0.00 LDPE Containers -0.89 -0.89 0.00 0.00 0.00 PET Containers -0.98 -1.16 0.00 0.00 0.00 Food Scraps NA NA NA NA NA Yard Trimmings NA NA NA NA NA Mixed MSW (as disposed) NA NA NA NA NA Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1 Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has already undergone the raw

materials acquisition and manufacturing phase).

and Manufacturing

(a) Raw Materials Acquisition

(d) 

Exhibit 8-1

Greenhouse Gas Emissions for Source Reduction
115

Emissions Measured from a Waste Generation Reference Point1

(a) 

RMAM Emissions (b) (f) 

Not Included in Waste (c) (d) (e) Forest 

Baseline3 (current Generation Process Transportation Process Carbon M

Material mix of inputs) Baseline Energy Energy Non-Energy Sequestration 

Newspaper 0.48 0.00 -0.14 0.01 0.00 -0.73 

Office Paper 0.52 0.00 -0.07 -0.01 0.00 -0.73 Corrugated Cardboard 0.41 0.00 0.03 0.00 0.00 -0.73 Mixed Paper Broad Definition 0.38 0.00 0.09 -0.02 0.00 -0.73  Residential Definition 0.38 0.00 0.09 -0.02 0.00 -0.73  Office Paper Definition 0.89 0.00 -0.09 -0.02 0.00 -0.73 Aluminum Cans 2.98 0.00 -2.49 -0.07 -1.32 0.00 Steel Cans 0.84 0.00 -0.57 -0.01 0.00 0.00 Glass 0.14 0.00 -0.04 0.00 -0.04 0.00 

HDPE Containers 0.61 0.00 -0.30 -0.02 -0.05 0.00 LDPE Containers 0.89 0.00 -0.44 -0.01 -0.05 0.00 PET Containers 0.98 0.00 -0.58 -0.02 -0.03 0.00 

Food Scraps NA 0.00 NA NA NA NA 

Yard Trimmings NA 0.00 NA NA NA NA Mixed MSW (as disposed) 0.49 0.00 NA NA NA NA 

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1 Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has already undergone 

 and manufacturing phase).

2Material that is recycled after use is then substituted for virgin inputs in the production of new products. This credit represents the difference in emissions that result

rather than virgin inputs. It accounts for loss rates in collection, processing, and remanufacturing. Recycling credit is based on weighted average of closed and openloop recycling for office paper, corrugated cardboard, and mixed paper. All other estimates are for closed loop recycling.

3The value for mixed MSW is the weighted average of the RMAM emissions for those materials we studied. 

Exhibit 8-2

Recycling 

(GHG Emissions in MTCE/Ton)

Raw Materials Acquisition and 

Manufacturing Recycled Input Credit2
116

(a) (b) (f) 

RMAM Emissions Waste (c) (d) (e) Avoided 

Not Included in Generation Transportation CO2 from N2O from Utility 

Material Baseline2 Baseline to Combustion Combustion Combustion Emissions 

Newspaper 0.48 0.00 0.01 0.00 0.01 -0.24 

Office Paper 0.52 0.00 0.01 0.00 0.01 -0.20 Corrugated Cardboard 0.41 0.00 0.01 0.00 0.01 -0.21 Mixed Paper Broad Definition 0.38 0.00 0.01 0.00 0.01 -0.21  Residential Definition 0.38 0.00 0.01 0.00 0.01 -0.21  Office Paper Definition 0.89 0.00 0.01 0.00 0.01 -0.19 Aluminum Cans 2.98 0.00 0.01 0.00 0.01 0.01 Steel Cans 0.84 0.00 0.01 0.00 0.01 0.01 Glass 0.14 0.00 0.01 0.00 0.01 0.01 HDPE Containers 0.61 0.00 0.01 0.75 0.01 -0.56 LDPE Containers 0.89 0.00 0.01 0.75 0.01 -0.56 PET Containers 0.98 0.00 0.01 0.51 0.01 -0.29 Food Waste NA 0.00 0.01 0.00 0.01 -0.07 Yard Waste NA 0.00 0.01 0.00 0.01 -0.08 Mixed MSW (as disposed) 0.49 0.00 0.01 0.10 0.01 -0.15 

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1 Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has already undergone th

and manufacturing phase).

2 The value for mixed MSW is the weighted average of the RMAM emissions for those materials we studied. 

Exhibit 8-3

Combustion

(GHG Emissions in MTCE/Ton)

Values are for mass burn facilities with national average rate of ferrous recovery.

Raw Materials Acquisition and 

Manufacturing

Emissions Measured from a Waste Generation Reference Point1
117

(a) (b) (d) (e) (f)

RMAM Emissions Waste (c) Net Landfill (f=b+c+d+e)

Not Included in Generation Transportation Landfill Carbon Net

Material Baseline2 Baseline to Landfill CH4 Sequestration Emissions

Newspaper 0.48 0.00 0.01 0.12 -0.36 -0.23

Office Paper 0.52 0.00 0.01 0.56 -0.04 0.53

Corrugated Cardboard 0.41 0.00 0.01 0.25 -0.22 0.04

Mixed Paper

 Broad Definition 0.38 0.00 0.01 0.27 -0.23 0.06

 Residential Definition 0.38 0.00 0.01 0.25 -0.24 0.03

 Office Paper Definition 0.89 0.00 0.01 0.30 -0.21 0.10

Aluminum Cans 2.98 0.00 0.01 0.00 0.00 0.01

Steel Cans 0.84 0.00 0.01 0.00 0.00 0.01

Glass 0.14 0.00 0.01 0.00 0.00 0.01

HDPE Containers 0.61 0.00 0.01 0.00 0.00 0.01

LDPE Containers 0.89 0.00 0.01 0.00 0.00 0.01

PET Containers 0.98 0.00 0.01 0.00 0.00 0.01

Food Scrap NA 0.00 0.01 0.16 -0.02 0.15

Yard Trimmings NA 0.00 0.01 0.09 -0.21 -0.11

Mixed MSW (as disposed) 0.49 0.00 0.01 0.13 -0.16 -0.02

Note that totals may not add due to rounding and more digits may be displayed than are significant.

NA: Not applicable, or in the case of composting of paper, not analyzed. 1

 Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has already undergone the raw

materials acquisition and manufacturing phase). 2

The value for mixed MSW is the weighted average of the RMAM emissions for those materials we studied. 

Exhibit 8-4

Landfilling 

(GHG Emissions in MTCE/Ton)

Emissions Measured from a Waste Generation Reference Point1

Values for landfill methane and net emissions reflect projected 

national average methane recovery in year 2000.

Raw Materials Acquisition and 

Manufacturing
118

Source Recycling Composting3 Combustion4 Landfilling5

Material Reduction2

Newspaper -0.91 -0.86 NA -0.22 -0.2Office Paper -1.03 -0.82 NA -0.19 0.5Corrugated Cardboard -0.78 -0.70 NA -0.19 0.0Mixed Paper Broad Definition NA -0.67 NA -0.19 0.0 Residential Definition NA -0.67 NA -0.19 0.0 Office Paper Definition NA -0.84 NA -0.18 0.1Aluminum Cans -2.98 -3.88 NA 0.03 0.0Steel Cans -0.84 -0.57 NA -0.48 0.0Glass -0.14 -0.08 NA 0.02 0.0HDPE Containers -0.61 -0.37 NA 0.21 0.0LDPE Containers -0.89 -0.49 NA 0.21 0.0PET Containers -0.98 -0.62 NA 0.24 0.0Food Scraps NA NA 0.00 -0.05 0.1Yard Trimmings NA NA 0.00 -0.07 -0.1Mixed MSW (as disposed) NA NA NA -0.04 -0.0Mixed Recyclables NA -0.76 NA -0.18 0.0

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1 Under the accounting convention used in this analysis, emissions are quantified from a waste generation reference point (once the material has 

already undergone the raw materials acquisition and manufacturing phase).

2 Source reduction assumes displacement of current mix of virgin and recycled inputs.3 There is considerable uncertainty in our estimate of net GHG emissions from composting; the values of zero are plausible values based on 

assumptions and a bounding analysis.

4 Values are for mass burn facilities with national average rate of ferrous recovery.5 Values reflect projected national average methane recovery in year 2000.

Exhibit 8-5

Emissions Measured from a Waste Generation Reference Point1

Net GHG Emissions from Source Reduction and MSW Management Options

(MTCE/Ton)
119

Net GHG Emissions of MSW Management Options Compared to Landfilling1

Source Reduction Recycling Composting2 Combustion3

Net Emissions Net Emissions Net Emissions Net Emissions

Minus Landfilling Net Emissions Minus Landfilling Minus Landfilling Minus Landfilling

Material Current Mix of Inputs 100% Virgin Inputs Net Emissions Net Emissions Net Emissions

Newspaper -0.68 -1.05 -0.63 NA 0.01Office Paper -1.56 -1.82 -1.35 NA -0.72Corrugated Cardboard -0.82 -1.15 -0.74 NA -0.23Mixed Paper Broad Definition NA NA -0.73 NA -0.25 Residential Definition NA NA -0.69 NA -0.22 Office Paper Definition NA NA -0.95 NA -0.28Aluminum Cans -3.00 -5.40 -3.89 NA 0.02Steel Cans -0.85 -1.13 -0.58 NA -0.49Glass -0.15 -0.17 -0.09 NA 0.01HDPE Containers -0.62 -0.71 -0.38 NA 0.20LDPE Containers -0.90 -0.90 -0.51 NA 0.20PET Containers -0.99 -1.17 -0.63 NA 0.22Food Scrap NA NA NA -0.15 -0.20Yard Trimmings NA NA NA 0.11 0.04Mixed MSW (as disposed) NA NA NA NA -0.02Mixed Recyclables NA NA -0.79 NA -0.20

Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.

1 Values for landfilling reflect projected national average methane recovery in year 2000.2 Calculation is based on assuming zero net emissions for composting.3 Values are for mass burn facilities with national average rate of ferrous recovery.

Exhibit 8-6

Negative values indicate emission reductions.

(MTCE/Ton)
120

All of the exhibits presented so far in this report have expressed GHG emissions in units of

metric tons of carbon equivalent (MTCE), calculated as the sum of the individual gases (CO2, CH4, N2O,

and PFCs) weighted by their global warming potential. In the Voluntary Reporting of Greenhouse Gases

Program, established by the Department of Energy’s Energy Information Administration (DOE/EIA),

reporters are asked to provide emission reductions for each of the individual gases. DOE/EIA is using

this approach because GWPs change as new scientific information becomes available, and at some point

in the future, the reported data may be used to develop a baseline of emission reductions. If the GWPs

change in the future, and if the weighted contributions of all gases were aggregated in the voluntary

reports, it would be difficult (and in many cases impossible) to adjust the estimated emission reductions

for the new GWPs.

For purposes of supporting participants in the DOE/EIA’s Voluntary Reporting of Greenhouse

Gases Program, we developed a set of emission factors, by gas. These provide incremental emissions for

a baseline of landfilling, and alternative scenarios of source reduction (Exhibit 8-7) and recycling

(Exhibit 8-8). The emission factors for CO2 and CH4 are specified in terms of three possible landfilling

baselines: no LFG recovery, LFG recovery with energy recovery, and national average landfill. The

exhibits are set up such that one obtains the appropriate factor for the material being source reduced or

recycled, and multiplies it by the tons that are diverted from landfilling to yield the emission reductions

for each gas. DOE/EIA provides detailed reporting instructions and forms, including a step-by-step

description of how to use the factors, on their web site at http://www.eia.doe.gov/oiaf/1605/forms.html.

** ***

We close with a final note about the limitations of the GHG emission estimates in this report. We

based our analysis on what we believed to be the best available data; where necessary, we made

assumptions that we believe are reasonable. However, the accuracy of the estimates is limited by the use

of these assumptions and by limitations in the data sources, as discussed throughout this report. Where

possible, the emission factors reported here can be improved by substituting process- or site-specific data

to increase the accuracy of the estimates (for example, a commercial firm with a large aluminum

recycling program may have better data on the specific fuel mix of its source of aluminum, and could

thus calculate a more exact value for the emission factor). Despite the uncertainty in the emission factors,

they provide a reasonable first approximation of the effects, from a GHG perspective, of solid waste

management, and we believe that they provide a sound basis for evaluating voluntary actions to reduce

GHG emissions in the waste management arena.
121

Exhibit 8-7

GHG Emission Reductions, by Gas, of Source Reduction

Relative to Landfilling*

(Metric Tons (MT) of Gas Per Short Ton of Product Source Reduced)

CO2 Emissions 

(MT/Ton of Product)

CH4 Emissions

(MT/Ton of Product)

Waste Component

Relative to (a) 

Landfills Without 

LFG Recovery 

or (b) Landfills 

With LFG 

Recovery and 

Flaring

Relative to 

Landfills With 

LFG Recovery 

and Electricity 

Generation

Relative to 

the National 

Average 

Landfill

Relative to 

Landfills 

Without LFG 

Recovery

Relative to (a) 

Landfills With 

LFG Recovery 

and Flaring or 

(b) Landfills 

With LFG 

Recovery and 

Electricity 

Generation

Relative to the 

National 

Average 

Landfill

CF4

Emissions

(MT/Ton of 

Product)

Newspaper -1.99 -1.86 -1.93 -0.043 -0.013 -0.027 0.000 

Office Paper -3.60 -3.00 -3.30 -0.192 -0.050 -0.115 0.000 Corrugated Cardboard -2.02 -1.75 -1.89 -0.086 -0.023 -0.052 0.000 Mixed Paper (Broad) NA NA NA NA NA NA NA Aluminum Cans -8.53 -8.53 -8.53 -0.014 -0.014 -0.014 -0.0003 Steel Cans -3.05 -3.05 -3.05 -0.002 -0.002 -0.002 0.000 Glass -0.54 -0.54 -0.54 -0.001 -0.001 -0.001 0.000 HDPE Containers -2.05 -2.05 -2.05 -0.010 -0.010 -0.010 0.000 LDPE Containers -3.03 -3.03 -3.03 -0.014 -0.014 -0.014 0.000 PET Containers -3.46 -3.46 -3.46 -0.008 -0.008 -0.008 0.000 Note that totals may not add due to rounding and more digits may be displayed than are significant.NA: Not applicable, or in the case of composting of paper, not analyzed.*Assuming Source Reduction displaces the current mix of virgin and recycled inputs in the manufacture of the material.
122

Exhibit 8-8

GHG Emission Reductions, by Gas, of Recycling 

Relative to Landfilling 

(Metric Tons (MT) of Gas Per Short Ton of Product Recycled)

CO2 Emissions 

(MT/Ton of Product)

CH4 Emissions

(MT/Ton of Product)

Waste Component

Relative to 

(a) Landfills 

Without LFG 

Recovery or 

(b) Landfills 

With LFG Recovery 

and Flaring

Relative to 

Landfills With 

LFG 

Recovery 

and 

Electricity 

Generation

Relative to 

the National 

Average 

Landfill

Relative to 

Landfills 

Without LFG 

Recovery

Relative to (a) 

Landfills With 

LFG 

Recovery and 

Flaring or (b) 

Landfills With 

LFG 

Recovery and 

Electricity 

Generation

Relative to 

the National 

Average 

Landfill

CF4

Emissions

(MT/Ton of 

Product)

Em

(M

P

Newspaper -1.86 -1.73 -1.79 -0.041 -0.011 -0.025 0.000 

Office Paper -2.89 -2.29 -2.59 -0.190 -0.048 -0.113 0.000 Corrugated Cardboard -1.80 -1.53 -1.67 -0.084 -0.020 -0.047 0.000 Mixed Paper (Broad) -1.67 -1.38 -1.67 -0.091 -0.022 -0.049 0.000 Aluminum Cans -10.26 -10.26 -10.26 -0.015 -0.015 -0.015 0.000 Steel Cans -2.10 -2.10 -2.10 -0.002 -0.002 -0.002 0.000 Glass -0.33 -0.33 -0.33 0.000 0.000 0.000 0.000 HDPE Containers -1.18 -1.18 -1.18 -0.010 -0.010 -0.010 0.000 LDPE Containers -1.64 -1.64 -1.64 -0.010 -0.010 -0.010 0.000 PET Containers -2.18 -2.18 -2.18 -0.007 -0.007 -0.007 0.000 Note that totals may not add due to rounding and more digits may be displayed than are significant.