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UNEP WMO
Greenhouse as Inventory
Reference Manual
First Draft
IPCC/OECD
Joint Programme
IPCC Draft Guidelines for National
Greenhouse Gas Inventories
•
!
i Volume 3
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IMPORTANT NOTICE
The material contained in this document is in draft, and is sent to you
for comment as part of the IPCC review process. The document has
not yet been approved by the IPCC and must not be published or cited
as an official IPCC report.
As a result of the review process this draft is expected to undergo
amendment and correction before being presented for approval by
IPCC WGI in September 1994 and by IPCC plenary in November
1994.
Material contained in this draft may be copied in whole or in part for
review by others, but a copy of this notice should be attached to all
such copies.
Recycled/Recyclable
Printed with Soy/Canofa Ink on paper that
contains at toast 50% recycled liber
Printing support provided by the U.S. Environmental Protection Agency
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ACKNOWLEDGEMENTS
The IPCC/OECD Programme on the Development of a Methodology for National
Inventories of Net Greenhouse Gas Emissions would like to thank those governments,
international organizations, and individuals whose contributions have made the
development of this methodology possible.
Financial support for the programme has been provided by the United Nations
Environment Programme, the Global Environment Facility, the Organization for Economic
Co-operation and Development Environment Directorate, the International Energy
Agency, the European Community, and the governments of the United States, the United
Kingdom, Switzerland, Italy, Norway, Sweden, and the Netherlands, Germany, France,
Canada, and Australia. Significant (non-financial) contributions and resources in kind came
from the United Nations Environment Programme, the United States, the Netherlands,
the United Kingdom, Japan, the Organization for Economic Cooperation and
Development, and the International Energy Agency.
Many individuals have contributed in various ways to the programme. Those who have
drafted, commented, and advised in the direct support of the production of these
documents include: Jane Ellis, Tim Simmons, and Karen Treanton, of the International
Energy Agency; Craig Ebert and Barbara Braatz of ICF Inc.; Karl jorss of the Federal
Environment Agency in Germany; Gordon Mclnnes of the CEC/European Environment
Agency Task Force & UNECE Task Force on Emission Inventories; James Penman of the
UK Department of the Environment; Andre van Amstel of the National Institute for Public
Health and Environmental Protection (RIVM) in the Netherlands; Jan Feenstra, Ella
Lammers, and Pier Vellinga, of the Institute for Environmental Studies in the Netherlands;
Berrien Moore of the University of New Hampshire; Gerald Leach, Jack Siebert, Susan
Subak, and Paul Raskin, of the Stockholm Environment Institute; Lucy Butterwick, Martin
Parry, and Martin Price, of the University of Oxford;; Michael Short and Peter Usher of the
United Nations Environment Programme; N Sundararaman of the IPCC Secretariat; Bert
Bolin, Chairman of the Intergovernmental Panel on Climate Change; Tim Weston, Peter
Bolter and Austin Pearce of TMS Computer Authors Ltd.; Sir John Houghton, Bruce
Callander, Buruhani Nyenzi and Kathy Maskell of the IPCC Working Group I Secretariat;
Paul Schwengels, Jan Corfee-Morlot, Jim McKenna, Scott Lurding, and Hans Sperling, of the
OECD Environment Directorate.
The IPCC/OECD Programme would like to thank all the participants in the expert groups
and in the various regional workshops, especially the coordinators and co-chairs of expert
groups process to provide improvements in technical methods; L Gylvan Meira Filho of
the National Institute for Space Research, Brazil; Berrien Moore of the University of New
Hampshire; Paul Crutzen of the Max Planck Institute for Chemistry; Elaine Matthews of
NASA; A P Mitra, of the National Physics Laboratory in India; Nigel Roulet of York
ACKNOWLEDGEMENTS. I
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ACKNOWLEDGEMENTS
University in Canada; K Minami of the National Institute for Agro-Environmental Sciences
in Japan; M A K Khalil of the Oregon Graduate Institute; Alan Williams of the University of
Leeds; Dina Kruger, Susan Thornloe, and Lee Beck, of the US Environmental Protection
Agency; Audun Rosland of the State Pollution Control Authority in Norway; Frank
Shephard of British Gas pic; Richard Grant of the E&P Forum; Michael Gibbs and Jonathan
Woodbury of ICF Inc.; Lis Aitchison of the Energy Technology Support Unit; Ron Lerig of
the University of New England in Australia; Mark Howden of the Bureau of Resource
Sciences, Australia; T Ramasami of the Central Leather Institute in India; Robert Delmas of
the Universite Paul Sabatier; Dilip Ahuja of the Bruce Company; Chris Veldt and Jan
Berdowski of the National Organisation for Applied Scientific Research (TNO-IMW) in
the Netherlands; and Jos Olivier of the RIVM.
National case studies were contributed by: Audun Rosland of the State Pollution Control
Authority in Norway, Peter Cheng of the Department of Arts, Sport, the Environment,
and Territories in Australia, Jane Legget of the US Environmental Protection Agency, Art
Jacques of Environment Canada, Sture Bostrom of Finland, and Karl Jorss of the Federal
Environment Agency in Germany, Simon Eggleston of Warren Spring Laboratory in die
United Kingdom, Andre van Amstel of the National Institute for Public Health and
Environmental Protection (RIVM) in the Netherlands! I B Obioh of Obafemi Awolowo
University Nigeria, P A Ratnasiri of the Ceylon Institute of Scientific and Industrial
Research, Gordon Mclnnes of the CEC/European Environment Agency Task Force &
UNECE Task Force on Emission Inventories, Anne Niederberger-Arquit of the Federal
Office of Environment, Forests and Landscape in Switzerland, and Kendaro Doi of the
Japan Environment Agency.
A very large number of experts have participated in IPCC/OECD expert groups and
workshops. All of these contributors have played contructive roles in shaping methods
presented here. These efforts reflect an important contribution to the implementation of
the Framework Convention on Climate Change, and are greatly appreciated.
ACKNOWLEDGEMENTS.!
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PREFACE
The signature of the UN Framework Convention on Climate Change (UNFCCC) by
around 150 countries in Rio de Janeiro in June 1992 indicated widespread recognition that
climate change is a potentially major threat to the world's environment and economic
development. Human activities have substantially increased atmospheric concentrations of
greenhouse gases, thus perturbing the earth's radiative balance. According to projections
from climate models, a global rise of temperature is a likely consequence. The potential
impacts of climate change such as sea level rises and changes in local climate conditions -
such as temperatures and precipitation patterns - could have important negative impacts
on the socio-economic development of many countries.
The ultimate objective of the Convention is the stabilisation of greenhouse gas
concentrations in the atmosphere at a level that would prevent dangerous anthropogenic
interference with the climate system. Such a level is to be achieved within a time frame
sufficient to allow ecosystems to adapt naturally to climate change.. The Convention also
calls for all Parties to the Conference to commit themselves to three objectives:
• To develop, update periodically, publish, and make available to the Conference of the
Parties their national inventories of anthropogenic emissions of all greenhouse gases
not controlled by the Montreal Protocol.
• To use comparable methodologies for inventories of greenhouse gas emissions and
removals, to be agreed upon by the Conference of the Parties.
• To formulate, implement, publish and update regularly national programmes
containing measures to mitigate climate change by addressing anthropogenic
emissions.
By the time of the Second World Climate Conference in Geneva in October - November
1990, the need for a standard methodology for compiling national emission inventories
was obvious. Under the auspices of the Organisation for Economic Cooperation and
Development (OECD) and the International Energy Agency (IEA), with support from the
USA, the UK and Norway, an initial compendium of methods (covering all gases except
chlorofluorocarbons (CFCs) which were already accounted for under the Montreal
Protocol). This document was discussed in detail by a meeting of experts (including many
representatives of non-OECD countries) in Paris in February 1991. It was then adopted in
a slightly modified form at the fifth session of the Intergovernmental Panel on Climate
Change (IPCC) in March 1991 as the starting point for a set of IPCC guidelines to be used
by countries drawing up national inventories of greenhouse gas emissions.
The IPCC Guidelines for National Greenhouse Gas Inventories consists of three volumes: the
Greenhouse Gas Inventory Reporting Instructions, the Greenhouse Gas Inventory Workbook and
PREFACE.I
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PREFACE
the Greenhouse Gas Inventory Reference Manual. The Guidelines are being distributed world-
wide to national experts for review before adoption.
Further development of the methodology has been undertaken by the Scientific
Assessment Working Group (WGI) of the IPCC, working in close collaboration with the
OECD and the IEA under the IPCC/OECD programme on emissions inventories. The
objectives of the programme are:
• Development and refinement of an internationally agreed methodology and software
for calculation and reporting of national net emissions.
• Efforts to encourage widespread use of the methodology by countries participating in
the IPCC and Parties to the UN Framework Convention on Climate Change.
• Establishment of procedures and a data management system for collection, review and
reporting of national data.
In the Guidelines, default methods and assumptions have been developed for
characterising the major sources and sinks of greenhouse gases. Countries have the option
of using the various methods depending on their own needs and capabilities. Other more
detailed methods are also discussed. However, the IPCC/OECD programme is developing
a common reporting and documentation framework for all inventories. This will provide
for comparison of these methodologically diverse national estimates. It is essential that
guidelines for this methodology are internationally agreed upon, and this will be achieved
through workshops and expert groups with a broad geographical base.
Additionally, the IPCC/OECD programme is charged with continuing to improve the
methodology. This is being achieved through:
• expert groups which review and recommend changes to the method
• results from country studies
• comments and preliminary inventories from countries
• feedback from technical workshops held in Asia, Africa, Latin America and Central and
Eastern Europe
About thirty five countries from all over the world have submitted their preliminary
inventory data on anthropogenic greenhouse gas emissions and removals from different
sources, using a range of approaches including the IPCC methodology. The results of all
the above activities have been considered in developing the current Guidelines.
The IPCC/OECD programme gives technical support to the greenhouse gas inventory
components of country study projects sponsored by UNEP, Asian Development Bank,
individual countries etc.. Countries participating in these projects are developing national
emission inventories. These country studies will contribute to:
• development of national capacity and capability (including improving baseline data)
• promulgation of the methodology
• realistic testing of the methodology and its guidelines in order to identify strengths
and weaknesses
Over thirty countries are currently working on country studies with support from various
sponsors.
PREFACE.2
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CONTENTS
-.K f
Introduction..
Conclusion....
References ....
I Using the IPCC Guidelines
Before you start. . ™ .
UVIWI *•» ^WM UkU> M» ................................................. ...i
General Notes on the Guidelines...... „....
ivIJgSJfc?.',
Chapter I Emissions From Energy
I. I Introduction
| .2 Emission Factor Data............... „ _
1.3 Enerev Activity Data..............................
O/ ««•*»"•/ .^.-•w..... [[[
1.4 Carbon Dioxide Emissions from Energy
1.5 Greenhouse Gas Emissions from Stationary Combustion
1.6 Burning Traditional Biomass Fuels
1.7 Greenhouse Gas Emissions from Mobile Combustion.—
1.8 Fugitive Emissions from Coal Mining, Handling and Utilization....
1.9 Fugitive Emissions From Oil And Natural Gas Systems
1-5
1-6
1-7
1-10
1-40
1-61
1-66
1-89
. 1-105
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CONTENTS
2 Industrial Processes
2.1 Overview --------- ..... [[[ 2-3
2.2 Carbon Dioxide Emissions From Industrial Processes .................................................. 2-4
23 References [[[ [[[ 2-13
3 Solvent Use
3.2 NMVOC Emissions from Solvent Use [[[ 3-3
3.3 References [[[ 3-5
4 Emissions From Agriculture
4.| Overview [[[ 4-3
4.2 Methane Emission From Domestic Livestock Enteric Fermentation
And Manure Management [[[ 4-5
4.11 References [[[ 4-23
Appendix A
Data Underlying Default Emission Factors for Enteric Fermentation .................... 4-32
Appendix B
Data Underlying Default Emission Factors for Manure Management ..................... 4-39
Appendix C
Derivation of Tier 2 Enteric Fermentation Equations .................................................. 4-48
4.3 Methane Emissions from Flooded Rice Fields [[[ 4-52
4.4 Agricultural Burning [[[ 4-69
4.5 Nitrous Oxide Emissions from Agricultural Soils [[[ 4-85
5 Emissions From Land Use Change And Forestry
5.2 Basic Calculations [[[ 5-10
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CONTENTS
6 Methane Emissions From Waste
6.1 Methane Emissions From Landfills. ............... ................... ....................... 6-5
6.2 Methane Emissions From Wastewater Treatment 6-21
6.3 Emissions From Waste Incineration............ ........................ ._...„.... .....6-33
6.4 References 6-35
CONTENTS.3
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PART I
INTRODUCING THE
REFERENCE MANUAL
PART I
INTRODUCTION.I
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INTRODUCTION
INTRODUCTION
This Reference Manual is one of three volumes of the IPCC Draft Guidelines for
National GHG Inventories. It provides a compendium of information on the
various human activities which cause greenhouse gas emissions to or
removals from the atmosphere. It builds on work carried out in preparation
of the OECD Report: Estimation of Greenhouse Gas Emissions and Sinks, Final
Report From the OECD Experts Meeting, 18-21 February 1991, (OECD, 1991).
In August 1991, the IPCC/OECD joint programme distributed this
document as a starting point for development of guidelines for national
inventories of greenhouse gases. In some sections for which no recent
methodologies are available, it incorporates text with very little change from
that document. In some areas, detail presented in the earlier report is
summarized here. The OECD (1991) document remains a valuable
reference document for national experts and others interested in the
development of the IPCC National GHG Inventory Methods. In particular,
detailed discussions of the reasoning behind some of the technical decisions
made early in the IPCC/OECD programme can be found there.
Another major published resource document heavily used in the preparation
of this Manual is the Proceedings of an International IPCC Workshop on Methane
and Nitrous Oxide, Amersfoort, NL, 3-5 February 1993 (van Amstel, 1993). To
provide technical information for improvement of the early methods known
to be weak, the IPCC/OECD programme established informal expert groups
to work toward reaching international agreement on proposed revisions to
the guidelines. A major landmark in this effort was the Amersfoort
workshop sponsored by the Dutch government and hosted by the
Netherlands National Institute of Public Health and Environmental
Protection (RIVM). National experts presented their findings at the
workshop and then discussions were held in working group sessions. The
conclusions and recommendations have been drawn upon in the preparation
of the Guidelines.
In preparing this document, the IPCC/OECD has also received valuable
technical input from a number of other international workshops. The overall
purpose of these workshops was to provide a forum for experts to discuss
ways to improve the methodologies and reporting procedures and to ensure
widespread participation in the development process. Many of the
recommendations received have been incorporated into this revised Manual.
In general, the basic approach to estimating national emissions is similar
across the various gases and human activities which are sources or sinks.
Fundamentally, emissions are a product of activity data and emission factors.
Activity data are some quantitative measures of the level of the relevant
human activity which occurs in the country (or region) of interest, during
the inventory year. Activity data range from fuel combustion and industrial
production statistics to numbers of domesticated animals of various types,
to hectares of forest land converted to other uses.
Emission Factors are average relationships between a level of activity and the
expected level of emissions which would result. Ideally they are derived
from a number of data points of monitored emission levels from a single
type of activity or technology being used in different places under different
conditions.
PART I
INTRODUCTION.3
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INTRODUCTION
In reality, these calculations are often more complicated than this would
indicate, with several steps being involved in the calculation of each of the
general terms - activity data and emission factors. But it is useful to keep this
general structure in mind as it provides an organizing framework for all of
the calculations and a means of evaluation and comparison.
The Reference Manual frequently provides a number of different possible
methodologies or variations for calculating a given emission. In most cases
these represent calculations of the same form but the differences are in the
level of detail at which the original calculations are carried out. Wherever
possible the methodology provides a "tiered" structure of calculations which
describes and connects the various levels of detail at which national experts
can work depending on the importance of the source category, availability of
data, and other capabilities. All national experts are encouraged to work at
the most detailed level which is possible and appropriate for their situation.
The tiered structure ensures that estimates calculated at a very detailed
level can be aggregated up to a common minimum level of detail for
comparison with all other reporting countries.
The methodology is by necessity broken down into segments and presented
category by category. It is important to recognize some key linkages and
interactions among components. For example, calculations in land use
change and forestry methods (chapter 5), energy (chapter I) and agriculture
(chapter 4) are connected with one another through the calculation of
emissions from biomass as fuel. Several sub-categories within the energy
chapter make use of common data elements which must be consistent.
There are many other such examples which are noted in the appropriate
sections of the Manual.
Reviewers and users of this document will recognize that a full scale final
editing has not yet been completed. There are significant inconsistencies in
formats and styles among the various chapters and sometimes even within
chapters. For example while most of the document uses footnotes, there
are a few sections which provide notes at the end of the chapter or page.
These editing problems will be corrected during the review process. The
IPCC/OECD programme elected to place emphasis on completing the
technical update and to produce a review draft quickly rather than
correcting all of the appearance problems at the draft stage.
Another known problem of a more technical nature is the inconsistency in
treatment of full molecular weight of nitrogen oxides (NOX). Nitrogen
oxides as emitted consist of NO and NO2. The convention among engineers
working with emissions from industrial combustion is to assume that all of
the N is emitted as NO2. However, experts on emissions from biomass
burning have generally adopted a different convention, assuming that all of
the N is emitted as NO. In the document, both conventions are used in
different sections, and noted in each case. The programme recognizes that
this is an unsatisfactory compromise, as a particular term or formula must
have only one meaning in order to ensure comparability. This problem will
be corrected in the final IPCC Guidelines.
INTRODUCTIONS
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INTRODUCTION
Conclusion
This Guidelines document draws on the input of expert groups and national
experts from around the world. The methodologies presemted offer a
recommended process for estimating and tracking national emissions
inventories. Along with offering the best current methodologies for
developing consistent national inventories, these Guidelines discuss
weaknesses in the existing methodologies and identify technical areas where
additional work is needed to develop better methods in the future.
The chapters are divided by subject areas and correspond to the same
subject chapters in the Workbook. This document should be used by national
experts as a reference tool to accompany the Workbook and the Reporting
Instructions when constructing and reporting national inventories of GHG
emissions and removals.
References
OECD (1991) Estimation of Greenhouse Cos Emissions and Sinks, Final Report
from the OECD Experts Meeting, 18-21 February 1991. The Organization for
Economic Cooperation and Development, Paris. Revised August 1991.
van Amstel, A.R., (ed.) 1993. Methane and Nitrous Oxide: Methods in National
Emissions Inventories and Options for Control. Proceedings of an International IPCC
Workshop, Amersfoort, NL 3-5 February 1993. RIVM Report no. 481507003.
Bilthoven, NL. July.
PART I
INTRODUCTION.5
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INTRODUCTION
I USING THE IPCC GUIDELINES
This document is one volume of the IPCC Guidelines for National
Greenhouse Gas Inventories. The series consists of three books:
• THE GREENHOUSE GAS INVENTORY REPORTING INSTRUCTIONS
• THE GREENHOUSE GAS INVENTORY WORKBOOK
• THE GREENHOUSE GAS INVENTORY REFERENCE MANUAL
These books together provide the range of information needed to plan,
carry out and report results of a national inventory using the IPCC system.
The Reporting Instructions (Volume I) provide step-by-step directions for
assembling, documenting and transmitting completed national inventory data
consistently, regardless of the method used to produce the estimates. These
instructions are intended for all users of the IPCC Guidelines and provide
the primary means of ensuring that all reports are consistent and
comparable.
The Workbook (Volume 2) contains suggestions about planning and getting
started on a national inventory for participants who do not have a national
inventory available already and are not experienced in producing such
inventories. It also contains step-by-step instructions for calculating
emissions of carbon dioxide (CO2) and methane (CH4) (also some other
trace gases) from six major emission source categories. It is intended to
help experts in as many countries as possible to start developing inventories
and become active participants in the IPCC/OECD programme.
The Reference Manual (Volume 3) provides a compendium of information on
methods for estimation of emissions for a broader range of greenhouse
gases and a complete list of source types for each. It summarizes a range of
possible methods for many source types. It also provides summaries of the
scientific basis for the inventory methods recommended and gives extensive
references to the technical literature. It is intended to help participants at all
levels of experience to understand the processes which cause greenhouse
gas emissions and the estimation methods used in compiling inventories.
The three books are designed to be used together and include these
features:
• all three volumes use an identical arrangement and numbering by source
category for ease of cross reference
• all the books have a common index which allows you to follow up all
references to a topic
(The common index will be included in the final, approved version but
not in the February 1994 review draft.)
• icons in the margin of each book indicate the source category
• colour coding on the page indicates source category.
(Colour will be included in the final, approved version but not in the
February 1994 review draft.)
INTRODUCTIONS
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INTRODUCTION
Before you start...
This diagram explains the stages needed to make a national inventory which
meets IPCC standards.
Do you have a detailed
National inventory?
Yes
Aggregate/transform
data and put into
standard format
Do you want to use
IPCC Computer Software?
Reporting
recommendations
- documentation
- verification
- uncertainty
Ref. manual
Final National Inventory
PART I
INTRODUCTION.7
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INTRODUCTION
The stages are:
Question I
Do you have a detailed national inventory?
Answer: Yes
If your country already has a complete national inventory, you should
transform the data it contains into a form suitable for use by IPCC. This
means transforming it into a standard format. In order to do this, use
Volume I of the IPCC Guidelines, Reporting Instructions. This gives details of the
way in which data should be reported and documented.
Answer: No
You should start to plan your inventory and assemble the data you will need
to complete the Worksheets in this book. Refer to the Getting Started
section of this Workbook.
Question 2
Do you want to use the IPCC computer software?
Answer: Yes
If you want to use the IPCC software, you will still follow the instructions
are included in the Workbook to assemble the data you have collected into
an inventory (see margin box). You will use the software instead of the
printed worksheets to enter data.
Answer: No
If you do not use the IPCC software, use the Workbook and the Worksheets
it contains to assemble the data you have collected into an inventory.
Finally...
Inventory data should be returned to IPCC in the form recommended in the
Reporting Instructions. It is important that, where you have used a
methodology other than the IPCC Default Methodology, it is properly
documented. This will ensure that national inventories can be aggregated
and compared in a systematic way in order to produce a coherent regional
and global picture.
General Notes on the Guidelines
I The flow diagram above is intended as a simple schematic to illustrate
the different types of users (working at different levels of inventory
detail) and how they should be able to use the various volumes of the
Guidelines. You should recognise that reality is more complex than this
simplest explanatory chart. Many countries may have some parts of the
inventory complete at a high level of detail but may only be getting
started on other parts. It is quite likely that some users will need to do
several iterations of the thinking process reflected in the diagram with
regard to different parts of their inventory.
2 Throughout the Guidelines there is an intentional double-counting of
carbon released from human activities. On one hand, CC>2 is calculated
based on the assumption that all of the carbon in original fuel, biomass,
INTRODUCTIONS
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INTRODUCTION
soils etc. which oxidizes produces CC>2. For combustion sources,
however, methods are also provided to estimate portions of the original
carbon which are released as CH^ and CO. The prima.ry reason for
double counting this is that carbon is that carbon released as CH4 or
CO is eventually converted to COj in the atmosphere. This occurs in
less than IS years, which is short relative to the 100+ years lifetime of
CO2 in the atmosphere. Therefore carbon emitted as CH4 and CO can
have two effects. First, in the form initially emitted, and, second, as part
of long term COj accumulation in the atmosphere. In order to have a
very precise estimate of the actual emissions of carbon species for a
given year (i.e. as input to a complex atmospheric model) you should
subtract carbon in reported CH^ and CO from CO2 to get net annual
emissions.
Many of the categories of greenhouse gas emissions and removals can
only be estimated with large ranges of uncertainty. Quite naturally,
some national experts have -developed methods which are designed to
produce ranges of estimates rather than point estimates for highly
uncertain categories.. The IPCC Guidelines, however, require that users
provide a single point estimate for each gas and emissions/removal
category. This is simply to make the task of compilation, comparison
and evaluation of national reports manageable. Users are encouraged to
provide uncertainty ranges or other statements of confidence or quality
along with the point estimates. The procedures for reporting
uncertainty information are discussed in the Greenhouse Gas Inventory
Reporting Instructions.
PART I
INTRODUCTIONS
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PART 2
SECTORS
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CHAPTER I
EMISSIONS FROM ENERGY
ENERGY
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EMISSIONS FROM ENERGY
CHAPTER I EMISSIONS FROM ENERGY
I.I Introduction
This chapter discusses inventory methods for the energy sources of greenhouse gases,
which include CO2, CH4, N2O, NOX, NMVOC and CO. Energy systems are extremely
complex and pervasive components of national economies. The full range of greenhouse
gases are emitted from a wide variety of different aspects of energy production,
transformation handling and consumption activities. The various emissions from energy
systems are organized in two main categories - I) emissions from combustion, and 2) non-
combustion, or "fugitive" emissions.
In dealing with fuel combustion emissions, CO2 is discussed in a separate section because
it can be calculated accurately at a highly aggregate level, unlike other gases. CO2 emissions
are primarily dependent on fuel properties. The IPCC reference method for CO2
emissions from fuel combustion is a simple, accurate and internationally transparent
approach which takes advantage of this fact. Non-CO2 greenhouse gases are more related
to technology and combustion conditions, and hence, must be estimated from detailed
sectoral energy activity data.
CO2 from energy activities can be estimated on a mass balance basis using information on
the amount and carbon content of the fuels consumed. Primary energy data, with a few
adjustments such as for non-oxidized products, serve as the basis of the inventory
calculation. Energy data on all commercial fuels are widely available from internationally-
validated data bases for individual countries of the world. These data provide an accurate
starting point for the estimation of CO2 inventories. However, since fuel qualities vary by
region, so will emission factors. For global or regional estimations of CO2, these variations
are slight enough that they will not significantly affect inventories. However, wide variation
among the types of fuels consumed within the primary fuel categories from one nation to
another will affect the accuracy of each national inventory. For example, certain countries
may depend on lignite, whereas others will use only bituminous coals. As discussed later,
the variation in emission factors within fuel categories can be as high as 10%. As a result,
national energy data and appropriate emission factors should reflect the actual mix of fuel
types within each country.
Unlike CO2, national inventories of CH4, N2O, NOX, CO and NMVOCs all require more
detailed information. This is due to the dependence of non-CO2 emissions on several
interrelated factors, including combustion conditions, technology, and control policies, as
well as fuel characteristics. These other gases cannot be estimated on the same mass
balance basis as used for CO2, as the use of average emission factors for broad emission
categories will introduce high levels of uncertainty. Average emission factors can represent
a wide distribution of values even across a single source" category or sub-category. CO2
emissions can also be calculated at the more detailed level required for other gases. When
national experts calculate other GHG emissions from energy combustion at a detailed
level, they should use the same data to estimate CO2 at the more detailed level as well.
Comparison and reconciliation of the aggregate and detailed CO2 emissions calculations
can serve as a valuable verification process. Procedures for estimating CO2 at both levels
of detail are discussed in this chapter. For all emissions estimates, the range of uncertainty
should be stated to the extent feasible. Volume I: Reporting Instructions discusses
approaches for estimating and expressing uncertainty.
The non-CO2 gases from energy are discussed according to two major combustion source
categories: stationary sources and mobile sources. The us;e of these two main categories
PART 2
1.5
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EMISSIONS FROM ENERGY
is the most common method for the initial disaggregation of energy combustion activities. These
two categories also best represent differences in the types of service, which also captures
technology differences. A special section on traditional biomass fuels is included because they
may need to be treated with a somewhat different approach from other stationary combustion
sources. This is due to their dispersed nature and scarcity of data on this category.
Fugitive emissions are essentially intentional or unintentional releases of greenhouse gases
during production including from venting and flaring, processing transmission and storage of
fuels. The most significant greenhouse gas emissions in this category are methane emissions
from coal mining and from oil and gas systems. There are also emissions of other gases, such as
CO2 and NMVOC as fugitive or by-product emissions from energy systems.
I.I.I Organization of the Chapter
In addition to this introduction, this chapter is organized into six separate energy sections:
• CO2 emissions from fossil fuels: CO2 emissions from all combustion sources are
estimated using an aggregate carbon balance approach to account for all carbon
across all energy categories.
• Non-CO2 emissions from stationary sources: Separated by common type of
service sector, and further by technology, estimation of non-CO2 emissions from
stationary source activities focuses on large facilities for NOX and on the commercial
and residential sectors for CO and VOC.
• Non-COz emissions from burning of traditional biomass fuels: A simplified
approach is provided because data are often inadequate for estimating emissions
from this category based on technology-specific emission factors. This approach is
designed to be used with data obtainable in developing countries where traditional
fuels make up a large fraction of total energy use.
• Non-CO2 emissions from mobile sources: Mobile source activities are divided
by transport mode, vehicle type and size to characterize a diverse range of engine
types and their respective emission characteristics.
• Fugitive emissions from coal production and handling activities: Emissions
are generated as a result of the production and handling of coal, primarily methane
emissions from coal mining. Other emissions of GHG from coal mine and waste fires,
are briefly discussed.
• Fugitive emissions from oil and gas systems: Methane emissions from natural
gas flaring and venting, and from natural gas production, transmission and distribution
are the most important for this category. COZ emissions from venting and flaring are
included as are NMVOC emissions from production, processing and distribution of
oil and oil products.
1.2 Emission Factor Data
Emissions of GHGs from fuel combustion and fuel supply activities are calculated by
multiplying levels of activity by emission factors. Emission factors are usually presented in
the form of mass of pollutant per unit of activity (e.g., g N2O/GJ). The most commonly
used activity measure for energy-related emissions is the amount of fuel combustion or,
where fugitive emissions are concerned, the amount of fuel produced or distributed. In
some cases other measures of activity are used, most notably in calculating emissions from
the transport sector.
1.6
-------
EMISSIONS FROM ENERGY
For CO2 emission factors are a function of fuel quality, but for all other gases emission
factors are also related to other factors (e.g., combustion technology, combustion
conditions, control technology). A number of international and national sources of energy
and industry emission factors exist largely as a result of international and national analyses
of alternative control policies for SOX, NOX and NMVOC, A few sources have also
recently emerged on various other GHGs. The more detailed factors (for gases other than
CO2) do not relate directly to national energy activity data described below, but require
some additional information. The sources of emission factor data and procedures for
making these linkages are discussed in the context of specific gases and source types, in
the relevant sections which follow.
1.3 Energy Activity Data
Subject to the requirements outlined below and intended to ensure the comparability of
country inventories, the IPCC approach to the calculation of emission inventories
encourages the use of fuel statistics collected by an officially recognised, national body as
this is usually the most appropriate and accessible activity data. In some countries,
however, those charged with the task of compiling inventory information may not have
ready access to the entire range of data available within their country and may wish to use
data specially provided by their country to the international organisations whose policy
functions require knowledge of energy supply and use in the world.
There are, currently, two main sources of international energy statistics: the International
Energy Agency of the Organization for Economic Cooperation and Development
(OECD/IEA), and the United Nations (UN). The primary energy data sources cited in this
report include:
• From the OECD/IEA: Energy Statistics and Balances for Non-OECD Countries
(OECD/IEA, I993a); Energy Balances of OECD Countries (OECD/IEA, I993b); and
Energy Statistics (OECD/IEA, I993c).
• From the United Nations: Energy Statistics Yearbook (UN, 1993).
There is a substantial amount of overlap among these two systems. The UN uses data
supplied by the IEA for the countries of the OECD, and the IEA starts with the UN data
for non-OECD countries when preparing its world energy data publication. While the UN
data set starts with IEA data for OECD countries, in its book-form publications it reports
slightly more detail by fuel. This is simply a preference for1 reporting, since all data points
exist in the original IEA source and are available in machine-readable format (i.e., magnetic
tape or computer diskette).
Another issue is the "official" nature of the statistics reported by each source. The UN
data source represents the official energy profile of both OECD countries (via the IEA
source) and the rest of the world, via their own national data collection and review
procedures. Alternatively, the IEA begins with the UN data for non-OECD countries,
compiles it in their format, and augments it with information not available to the UN, e.g.,
data from oil companies and other energy industries provided to the IEA. These additions
to the basic UN data are checked for internal consistency and against other sources of
data for the country, and when discrepancies exist, experts are contacted in the country
PART 2
1.7
-------
EMISSIONS FROM ENERGY
for an opinion as to which data to use. Coverage of the nations of the world in the IEA
data is not complete.1
1.3.1 Comparability of Reporting
In order to meet the objectives of the IPCC/OECD programme, inventories submitted by
parties to the agreement must be readily comparable. This requires a large measure of
commonality of definitions of activities and fuel product groups and the use of a reporting
discipline which makes evident the construction of the inventory from the activity data.
Specific guidelines for reporting have been prepared. In order to reduce the uncertainty
created by possibly different definitions, the IPCC methodology recommends the use of
those utilised by the IEA for the regular collection of energy data from OECD member
countries. The active cooperation between the UN Statistical Division (Mew York), the
'JNECE (Geneva), Eurostat and the IEA has ensured that there are now very few
differences between the definitions employed by these organisations for the collection of
their energy data. The IEA definitions may be found in Energy Balances of OECD Countries
1990-91.
The paragraphs above make clear that the reporting country, when constructing the
inventory, is entitled to use national data from local sources or the national data as
reported to the international organisations. If local data are used, this should be stated,
identified and the reasons for preferring it to those provided to the international
organisations discussed in the documentation accompanying the submission. The activity
data used should also be reported.
A group of experts convened recently to discuss in detail the existing internationally
compiled energy data bases and their use in estimating GHGs, primarily carbon dioxide.
This group included representatives of the two major data collection activities (UN and
IEA), the IPCC/OECD programme and a number of experts who have used or currently
are using these data for the purposes of estimating GHG emissions. The experts in this
meeting confirmed that, of existing data sources, "the data bases of the UN Statistical
Division in New York and of the IEA are the most comprehensive and provide the basis
for others. There is good consistency between the UN data base, the IEA data base and
other data bases such as those of the UN-ECE and CEC (EUROSTAT data set)."
An important result of the experts' meeting, which led to the IPCC methodology, was to
highlight the importance of careful and comprehensive reporting of national energy data in
relation to its use in GHG emissions estimation and analysis. Experts recommended that
every effort be made to communicate to national agencies who provide energy data that
this data plays a crucial role in international evaluation of national GHG emissions. It is
hoped that this awareness will provide an additional motivation for national energy data
sources to allocate adequate effort to the development and reporting of energy data so
that comprehensive and high quality information will be available as input to GHG
assessments. This recommendation is being conveyed through traditional channels to
energy statistics sources and also reinforced through environmental channels such as the
IPCC and INC.
1 Approximately 120 countries (of about 170 UN Member countries) are included in
the IEA data, but the countries it includes account for about 98% of worldwide energy
consumption and nearly all energy production.
2 This meeting was convened by the International Atomic Energy Agency (IAEA), and
detailed results are described in IAEA. 1993.
1.8
-------
EMISSIONS FROM ENERGY
Inconsistent reporting standards among both national and international energy data sets
can lead to differences that hinder comparison and comparable inventory development. At
least five aspects of energy data reporting need to be checked prior to using data for
greenhouse gas inventories:
• Are energy data reported in terms of lower heat values (LHV) or higher heat values
(HHV)?3 Since most of the world uses lower heat values, the IPCC Guidelines use
lower heating values.
• Are waste or waste-derived fuels included if combusted for energy production?
These fuels should be accounted for in the IPCC methodology, but are included with
biomass fuels.
• Is non-energy fuel usage (if non-oxidized) accounted for?4
• How are international bunker fuels for air and ship transport treated?5
• Are non-commercial fuels, including wood and other biomass fuels, included?6
Given responses to these questions, several adjustments may need to be made to the
energy data being used in order to formulate a complete inventory of greenhouse gases. If
published IEA data are being used the following corrections must be made:
I Bunker fuels and vegetal fuels (both commercially-traded and traditional or non-
commercial biomass fuels) need to be added to each country of origin. The IEA has
some data on commercially-traded vegetal fuels, but traditional biofuels consumption,
e.g., wood collected for cooking by individuals, is typically not included in official
energy statistics.
2 Non-energy fuel use needs to be estimated and deducted from apparent energy
consumption.7 Adjustments also need to be made for the portion of non-energy
uses that do not oxidize.
3 Vegetal fuels should be separated and added as a separate fuel group.
The IEA generally reports data in lower heat values. The; difference between the lower
and the higher heating value of a fuel is the heat of condensation of moisture in the fuel during
combustion. The lower heating value excludes this. The IEA assumes that lower heating values
are 5% lower than higher heating values for oil and coal and 10% lower for natural gas.
4 This is normally reported in primary energy requirements but is not combusted and
therefore does not contribute directly to greenhouse gas emissions.
5 Bunker fuels are combusted at sea and by airplanes and therefore should be included
in greenhouse gas estimations. The question is how to allocate emissions among nations or
regions. As discussed later, the Paris workshop recommended that emissions from bunker
fuels be estimated as a separate category under energy-related emissions, and that the
issue of how to allocate these emissions be addressed and agreed upon internationally in
follow-up efforts. Okken and Tiemersma (1984) provide an example of the contribution of
shipping bunker fuels to the Netherlands' CO2 budget.
While some of these fuels (such as wood) may be included in national or
international data sets, it is likely that they are underestimated due to poor record keeping
and lack of statistical information for non-commercial fuels..
7 IEA data on bunker fuels and non-energy fuel use represent only a partial accounting of
these activities and would need to be supplemented with outside information. Specifically, non-
energy natural gas products and aviation bunker fuels are not separated in the IEA statistics.
PART 2
1.9
-------
EMISSIONS FROM ENERGY
These adjustments can be quite significant to the energy balance and hence to the
calculation of greenhouse gases. For example, in 1987 international bunker fuels for
shipping represented about 3 per cent of the global oil requirement, but in some countries
accounted for a much higher share. Non-commercial vegetal fuels in 1 987 are estimated to
represent less than 4% of total primary energy requirements (TPER) in the OECD and
CPE, but nearly 22% for Developing Countries. Non-energy use of fuel products
represented about 10% of the world oil TPER in I987.8
1.4 Carbon Dioxide Emissions from Energy
In this section methodology for estimating CO2 emissions from energy is discussed.
Carbon dioxide (CO^ is the most common greenhouse gas produced by anthropogenic
activities, accounting for about 60% of the increase in radiative forcing since pre-industrial
times. (IPCC, 1 992) By far the largest source of CO2 emissions is from the oxidation of
carbon when fossil fuels are burned, which accounts for 70-90% of total anthropogenic
COj emissions. When fuels are burned, most carbon is emitted as CO2 immediately
during the combustion process. Some carbon is released as CO, CH4, or non-methane
hydrocarbons, which oxidize to CO2 in the atmosphere within a period from a few days to
10-11 years. The IPCC methodology accounts for all of the carbon from these emissions
in the total for CO2 emissions. The other carbon-containing gases are also estimated and
reported separately (see following sections for methodologies for estimating CH4, CO,
and non-methane VOCs).9
Fuel combustion is widely dispersed throughout most activities in national economies, and
assembly of a complete record of the quantities of each fuel type consumed in each "end
use" activity is a considerable task, which some countries have not yet completed.
Fortunately, it is possible to obtain an accurate estimate of national CO2 emissions by
accounting for the carbon in fuels supplied to the economy. The supply of fuels is simple
to record and is more likely to be available in many countries, than detailed end use
consumption statistics. For this reason, the IPCC Reference Approach for estimating
emissions of CO2 from fossil fuels is somewhat different than the approach used for other
greenhouse gases. For CO2 emissions depend mostly on the basic fuel characteristics
rather than on technology or emission controls (as with gases such as NOX or CO).
The Reference Approach requires a careful accounting of fossil fuel production by energy
type, carbon content of fossil fuels consumed, fossil fuel consumption by type, and
production of products with long term carbon storage. In this respect the methodology
for estimating CO2 emissions represents more of a "top-down" approach compared to the
"bottom-up" approach recommended for the other gases. This does not mean that a
"bottom-up" approach used for other gases cannot also be followed for estimating CO2
8 Also combustion of non-energy oil products, such as plastics or refuse-derived fuel,
may not be consistently counted in the energy statistics compared to other solid fuels, nor
would they be included in the base energy statistics if combusted without energy recovery.
No global estimate of their significance is available.
9 It is important to note, as discussed in the introduction to this document, that there
is an intentional double counting of carbon emitted from combustion. This format treats
the non-CO2 gases as a subset of CO2 emissions and ensures that the CO2 emission
estimates reported by each country represent the entire amount of carbon that would
eventually be present in the atmosphere as CO2. The reasons for this double counting are
discussed in the introduction.
1.10
-------
EMISSIONS FROM ENERGY
emissions. A method for estimating emissions with a "bottom-up" approach is briefly discussed
later in this section. It is recommended that national experts who do detailed estimates of
emissions of non-CO2 gases, should also apply CO2 emission factors at this detailed level. In all
cases, experts should estimate CO2 emissions from fuel combustion using the IPCC reference
method also. This method provides the basis for international comparison, and all national
estimates should be reconciled with the results of this approach.
For all calculations of CO2 emissions from fuel combustion, emissions are directly
related to the amount of fuel consumed and the carbon content of the fuel. Coal
contains close to twice the carbon of natural gas and roughly 25 per cent more than
crude oil per unit of useful energy. A number of complicating factors need to be
considered carefully:
• Common Energy Units: There is considerable variation in the energy content by
weight of some fuels, especially coals. For comparison all energy data must first be
converted to common energy units (e.g., gigajoules) before emission factors (or
coefficients) are applied.
• Variations in Fuel Carbon: For a given fuel type, even when quantified in energy
units, the carbon per unit of useful energy varies. For example, not all coal types
contain the same proportion of carbon. Generally speaking, the lower the quality of
the coal (such as sub-bituminous coal and lignite), the higher the carbon emission
factor (i.e., carbon per unit of energy).10 There are similar carbon differences among
the different types of liquids and gases.
• Unoxidized Carbon: When energy is consumed not all of the carbon in the fuel
oxidizes to CO2. Incomplete oxidation occurs due to inefficiencies in the combustion
process that leave some of the carbon unburned or partially oxidized as soot or ash.
• Stored Carbon: Not all fuel supplied to an economy is burned for heat energy.
Some is used as a raw material (or feedstock) for manufacture of products such as
plastics, fertilizer, or in a non-energy use (e.g. bitumen for road construction,
lubricants). In some cases, as in fertilizer production, the carbon from the fuels is
oxidized quickly to CO2 once applied and exposed to air. In other cases, as in road
construction, the carbon is stored (or sequestered) in the product, sometimes for as
long as centuries. The amounts stored for long periods are called stored carbon (or
sequestered carbon), and should be deducted from the carbon emissions calculation.
Estimation of stored carbon requires data on fuel used as feedstock and/or quantities
of non-fuel energy products produced. The calculations are discussed within each of
the alternative approaches presented in this section.
• Bunker Fuels: Bunker fuels refer to quantities of fuels used for international marine or
aviation purposes. The IPCC methodology accounts for these fuels as part of the energy
balance of the country in which they were delivered to ships or aircraft Thus the CO2
emissions from combustion of those fuels would also appear in the country of delivery,
even though most of the actual emissions occur outside its boundaries. This is done to
ensure that all fuel use is accounted for in the methodology. However, for informational
purposes, the quantities and types of fuels delivered for international bunker purposes
should be separately subtotaled.
10 The major exception to this relationship is anthracite or very hard coal, which
typically has a higher carbon emission coefficient than bituminous coal.
PART 2
.1 I
-------
EMISSIONS FROM ENERGY
• Biomass Fuels: Biomass fuels are included in the national energy and emissions
accounts for completeness, as an information item. These emissions should not be
included in the summation of national CO2 emissions from energy. If biomass is being
regrown at roughly the same rate as it is being harvested on an annual basis, die net
flux of CO2 to the atmosphere is zero. If energy use, or any other factor, is causing a
long term decline in the total carbon embodied in standing biomass (e.g. forests), this
net release of carbon should be evident in the calculation of CO2 emissions described
in the Land Use Change and Forestry chapter.
All of the above issues are addressed within each of the alternative approaches presented
in the remainder of this section.
1.4.1 Approaches For Estimating CO2 Emissions
The conceptual approach for estimating CO2 emissions from energy consumption is well-
known and straightforward. The basic calculations can be characterized as six fundamental
steps that explicitly identify all of the factors necessary to measure CO2 emissions from
energy consumption:
Estimating consumption of fuels by fuel product type.
Converting fuel data to energy units (if necessary).
Selecting carbon emission factors for each fuel product type and total carbon
potentially released from use of the fuels.
Estimating the amount of carbon stored in products for long periods of time.
Accounting for carbon not oxidized during combustion.
Converting emissions as carbon to full molecular weight of CO2.
I
2
3
4
5
6
There are three basic approaches for estimating CO2 emissions discussed in this document
that vary primarily according to the level of detail at which these six steps are carried out.
The methods are: . .
I The IPCC Reference Approach: Detailed Fuels. The Detailed Fuels approach is
the basic methodology recommended by the IPCC and requires information on
several different types of energy products. This approach is sometimes referred to as
"top-down" estimation since a country only needs information on the quantities of
fuels produced domestically, and flowing into and out of the country. Accounting for
actual consumption of fuels at the sectoral or sub-national level is not required.
2 Detailed Technology Based Calculation: "Bottom-Up" Method. Most
countries would ultimately like more detail on emissions of CO2 by energy using sub-
sector than provided in the reference approach. This information is clearly necessary
for evaluating policy options for reducing GHG emissions. In addition, if national
experts are calculating emissions of non-CO2 GHGs from energy combustion, they
are very likely working at a much finer level of energy use and technology detail. It is
desirable to estimate CO2 emissions and other gases at the same levels of detail for
consistency purposes. The basic calculations to estimate CO2 can be applied a very
detailed level, including by sector and fuel types consumed in specific end-uses. This
level of calculation is called "bottom-up" because it is very data-intensive, requiring a
substantial amount of information about national energy consumption patterns in
each sector of a nation's economy. Some of the additional complexities which must
be addressed at this level are discussed briefly at the end of this section. If national
experts use this approach, it is recommended that they also use the IPCC reference
1.12
-------
EMISSIONS FROM ENERGY
approach and reconcile any differences between results at the two levels of detail.
This can be a very useful verification exercise.
Aggregate Fuel Approach. The aggregate fuel approach only requires information
on the generic types of fossil fuels consumed in each country, specifically the
quantities of solid, liquid, and gaseous fossil fuels consumed, and the amount of
biomass consumed. No further detail on fuel product types is used in this approach.
Since most countries have access to energy data that iis more detailed than these
general categories, this overly simplified approach is not recommended by the IPCC
unless the reference approach cannot be implemented. Discussion of this aggregate
fuels approach can be found in Annex A. As an alternative to the IPCC reference
approach, this level of detail still allows a country to estimate CO2 emitted, due to
consumption of various types of fossil fuels, but at a very aggregate, and less accurate
level.
1.4.2 IPCC Reference Approach:: Detailed Fuels
The Reference Approach is based on an accounting of the carbon in fuels supplied to the
economy. It involves the careful estimation of each country's production of fuels, imports
of fuels and refined products, exports of fuels and refined products, and changes in the
stock levels for these fuels and products within the country. It makes use of a simple
assumption: once carbon is brought into a national economy in fuel, it is either saved in
some way (e.g., in increases if fuel stocks, stored in products, left unoxidized in ash) or it
must be released to the atmosphere. It is not necessary to know exactly how the fuel was
used or what intermediate transformations it underwent in order to calculate the carbon
released.
Carbon accounting is based mainly on the totahsupply of primary fuels and the net
quantities of secondary fuels brought into a country. Using these values apparent
consumption (i.e., energy supply) can be estimated Once apparent consumption is
estimated, subsequent steps account for carbon emission factors and other adjustments
for the stored carbon, fraction oxidized, and other complications discussed in the
introduction to this section.
The first step of the IPCC Reference Approach is to estimate apparent consumption of
fuels within the country. This requires a balance of primary fuels produced, plus imports,
minus exports, and net changes in stocks, stock change." In this way carbon is
"transferred" into the country from energy production and imports (adjusted for stock
changes) and transferred out of the country through exports. In this accounting system for
fuels supplied it is important to distinguish between primary fuels (i.e., fuels which are found
in nature such as coal, crude oil, natural gas), and secondary fuels or fuel products, such as
gasoline and lubricants, which are derived from primary fuels.
This approach is similar to, but not as detailed as, standard energy balance
accounting. Energy balances, by their nature, are an attempt to reconcile supply (apparent
consumption) with observed consumption where all the end-use sectors are separately
identified. The Reference Approach includes only the data necessary to account for carbon
flows into and out of a country. Therefore, the level of detail needed for this approach to
CO2 emissions estimation is not as great as for a complete national energy balance.
PART 2
1.13
-------
EMISSIONS FROM ENERGY
To calculate the supply of fuels to the country, the following data are required for each
fuel and inventory yean
• the amounts of primary fuels produced (production of secondary fuels and fuel
products is excluded)
• the amounts of primary and secondary fuels and fuel products imported
• the amounts of primary and secondary fuels and fuel products exported
• the net increases or decreases in stocks of fuels
Production data would be provided for the primary (untreated) fuels, including crude oil,
natural gas liquids (NGL), coking coal, steam coal, sub bituminous coal, lignite (brown
coal), peat, and natural gas. These production data would define the initial amount of
carbon available for consumption in a country from which CO2 emissions are generated.
To determine the net amount of carbon consumed, i.e., apparent consumption, any
exports of these fuels would be subtracted and any imports added. Adjustments for stock
changes are also needed. The apparent consumption of primary fuels is, therefore,
calculated as:
Production + Imports - Exports - Stock Change.
An increase in stocks is a positive stock change. As this is subtracted in the equation, a
positive stock change results in a decrease in apparent consumption. A stock reduction is
a negative stock change which, when subtracted in the equation, causes an increase in
apparent consumption.
Flows of secondary fuels should be added to primary apparent consumption. The
production (or manufacture) of secondary fuels should be ignored in the calculations of
apparent consumption since the carbon in these fuels will already have been accounted for
in the supply of primary fuels from which they were derived (e.g.. the estimate for
apparent consumption of crude oil already contains the carbon from which gasoline would
be refined). However, information on production of some secondary fuel products is
required in a later step to adjust carbon stored in these products. Flows of secondary fuels
are calculated as:
Imports - Exports - Stock Change.
Note that this calculation can result in negative numbers for Apparent Consumption. This
is a perfectly acceptable result for the purposes of this calculation since it indicates a net
export or stock increase in the country when domestic Production is not considered.
This procedure, in effect, calculates the supply of primary fuels to a country, with
adjustments for net imports (imports-exports) and stock changes in secondary fuels.
Since carbon content typically varies by fuel type, data should be reported for detailed
categories of fuel and product types as shown in Table I-I. The table also illustrates the
inputs and calculations recommended for the IPCC Reference Approach. The data are
specified in the form available in the OECD/IEA Energy Statistics (1993). As discussed
above, biomass fuels and bunker fuels have been included in the emission inventory
calculations for information only. These subtotals are not added to the totals calculated for
fuels above the line.
1.14
-------
EMISSIONS FROM ENERGY
TABLE l-l
IPCC REFERENCE APPROACH
ENTRIES AND CALCULATIONS FOR STEPS (I) AND (2)
Fuel
A) Liquid Fossil
Primary Fuels
1) Crude Oil
2) N.Gas Liquids
Secondary Fuels/Products
3) Gasoline
4) Kerosene
5) Jet Fuel NA
6) Gas/Diesel Oil
7) Residual Fuel Oil
8)LPG
9) Naphtha NA
10) Bitumen
1 1) Lubricants
12) Petroleum Coke
13) Refinery F-stocks
14) Other Oil
B) Solid Fossil
Primary Fuels
15) Coking Coal
16) Steam Coal
17) Lignite input
18) Sub-bit. Coal
19) Peat
Secondary Fuels
20) BKB & Patent Fuel
21) Coke
C) Gaseous Fossil
22) Nat. Gas(Dry)
Total
(1)
Produc
tion
input
input
NA
NA
input
NA
NA
NA
input
NA
NA
NA
NA
NA
input
input
input
input
input
NA
NA
input
(2)
Imports
input
input
Input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
(3)
Exports
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
input
(4)
Stock
Change
input
input
input
input
calc
input
input
input
calc
input
input
input
input
input
input
input
calc
input
input
input
input
sumQ
input
(5)
Apparent
Cons.1
sumO2
calc
calc
calc
calc
input
calc .
calc
calc
input
calc
calc
calc
calc
calc
sumO
calc
calc
input4
calc
calc
calc
calc
calc
sumQ1
(6)
Conver.
Factor
input
input
input
input
calc
input
input
input
calc
input
input
input
input
input
input4
input4
calc
input4
input
input
input
surr>0
input
(7)
Apparent
Cons,
(GJ=IO*)
sumQ
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
sumQ
calc
calc
calc
calc
calc
calc
calc
sum()
Information Entries (Not Summed!
Biomass
23) Solid Biomass
24) Liquid Biomass
input
input
input
input
input
input
input
input
sumO
calc
calc
input
input
sumO
calc
calc
Bunkers - (Fuel Used for International Transport)
Total'
Jet Fuel Bunkers
Gas/Diesel Oil Bunkers
Resid. Fuel Oil Bunkers
"Other Oil" Bunkers
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
surnQ
input
input
input
input
input
input
input
input
sum()
calc
calc
calc
calc
PART 2
1.15
-------
EMISSIONS FROM ENERGY
TABLE l-l (CONTINUED)
IPCC REFERENCE APPROACH
ENTRIES AND CALCULATIONS FOR STEPS (3) - (6)
Eusl
A) Liquid Fossil
Primary Fuels
1) Crude Oil
2) N. Gas Liquids
Secondary Fuels/Products
3) Gasoline
4) Kerosene
S) Jet Fuel calc
6) Gas/Diesel Oil
7) Residual Fuel Oil
8)LPG
9) Naphtha
10) Bitumen
1 1) Lubricants
12) Petroleum Coke
13) Refinery F-stocks
14) Other Oil
B) Solid Fossil
Primary Fuels
IS) Coking Coal
16) Steam Coal
17) Ugnite
I8)Subbic.Coal
19) Peat
Secondary Fuels/Products
20) BKB & Pat. FueJ
21) Coke
Q Gaseous Fossil
22) Natural Gas (Dry)
Total7
Information Entries (Not S
Biomass Total
23) Solid Biomass
24) Liquid Biomass
(7)
Apparen
Cons
(GJ)
sumO
calc
calc
calc
calc
19.5
calc
calc
calc
calc
calc
calc
calc
calc
calc
sumQ
calc
calc
calc
calc
calc
calc
calc
sumO
calc
sumQ
ummed)
sum()
calc
calc
(8)
Carbon
Emission
Factor5
IK.% acn
20.0
15.2
18.9
19.5
calc
20.2
21.1
17.2
NA(20.0)
22.0
NA(20.0)
27.5
NA(20.0)
NA(20.0)
sumO
25.8
25.8
27.6
26.2
28.9
NA(25.8)
29.5
15.3
a«=t-.o
NA(20.0)
(9)
Potential
Emissions6
(GgQ
sumO
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
sumQ
calc
calc
calc
calc
calc
calc
calc
sumO
calc
sum()
sumQ
calc
calc
(10) (II)
Net
Carbon Carbon
Stored Emissions
(GgQ (Gg CV
sumQ sumQ
calc
calc
calc
calc
calc calc
calc
calc
Table 1-4 calc
Table 1-4 calc
Table 1-4 calc
Table 1-4 rale
calc
calc
calc
sum() sum()
Table 1-4 calc
calc
calc
calc
calc
calc
calc
sumQ sum()
Table 1-4 calc
sum() sum()
sumQ
calc
calc
(12)
Adjusted
Carbon
Emissions
(Sg^
i;um()
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
sum()
calc
calc
calc
calc
calc
calc
calc
sum()
calc
sum()
sum()
calc
calc
Bunkers - (Fuel Use in international Transport)
Total
Jet Fuel Bunkers
Gas/Diesel Oil Bunkers
Resid. Fuel Oil Bunkers
Other Oil Bunkers
sumQ
calc
calc
calc
calc
19.5
20.2
21.1
NA(20.0)
sumO
calc
calc
calc
calc
sumQ
calc
calc
calc
calc
sumQ
calc
calc
calc
calc
(13)
CO2
Emissions
(Gg CO21
sumO
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
calc
sumQ
calc
sum()
sumO
calc
calc
5>o
-------
EMISSIONS FROM ENERGY
TABLE l-l (CONTINUED)
EXPLANATORY NOTES
calc = value to be calculated, NA = not applicable
1 Apparent Consumption equals production plus imports minus exports minus stock changes. Apparent
Consumption includes energy use for bunkers, although the subset of each category consumed as bunker fuels
should be calculated separately to allow for differential treatment at a later date.
2 Apparent Consumption for the aggregate categories of Liquid Fossil, Solid Fossil, Gaseous Fossil, and Biomass
Fuels equal the sum of Apparent Consumption over the fuel types within the appropriate categories.
3 Total should include Liquid, Solid, and Gaseous Fossil Fuel subtotals only. Biomass and Bunkers subtotals are
for informational purposes only, and should not be included in the totals,
4 If data is in lO'mt. separate conversion factors are available for Production, Imports, Exports, and Stock
Changes in Table 1-2. Each of these entries should be multiplied by the appropriate conversion factor. Then,
the results should be summed to find Apparent Consumption in GJ (Col. 7).
5 NA = Carbon Emission Factor (CEF) not available; value in parenthesis is a default value until a fuel-specific
CEF is determined. For oil products the default value is the emission for crude oil; for coal products the default
value is die emission factor for steam coal. All values taken from Grubb (1989), except LPG, which was taken
from Marland and Pippin (in press), and subbicuminous coal which was tsiken from Bowling (1989).
calc = calculation to be made by respondent; in this case, Consumption (column I) is multiplied by the
Carbon Emission Factor (column 2) and converted to Gg.
7 Total includes Liquid Fossil, Solid Fossil, and Gaseous Fossil subtotals only. Biomass emissions are not
considered "net" emissions, and bunker data is already included in the totals for the fuel types from which it is
derived. Separate biomass and bunker fuel totals are provided for information only.
Fuel statistics are needed on an energy basis (preferably in gigajoules; I gigajoule = I09 joules) for
accurate estimation of CO2 emissions. In the OECD/IEA Energy Statistics, and in many other
energy data compilations, production and consumption of solid and liquid fuels are specified in
IO3 metric tons (I O3 mt). To convert metric tons to gigajoules, conversion factors must be
applied. For unrefined fuels, energy content per tonne of fuel can vary widely from country to
country. Default conversion factors for a number of countries based on IEA energy data. These
values to convert from I O3 metric tons to gigajoules are in Tattle I -2. Note that in many cases
different conversion factors are given for production, imports and exports in a given country.
These can be used to convert each of these categories separately in die calculation of apparent
consumption. For stock changes national experts can use a weighted average of the different
conversion (actors, or use die one which represents die largest quantity of total apparent
consumption for that coal type. For refined products die conversion factors from I O3 metric
tons to gigajoules do not normally vary by country and global default values are provided in
Table 1-3.'*
National experts may use more detailed locally available conversion factors. In this case, die
conversion factors used should also be reported and documented. If original data are expressed
in odier energy units such as British thermal units (Btu's), million tons of oil equivalent (Mtoe),
diey should be converted to gigajoules using standard conversion factors. If energy data are
already available in gigajoules, no conversion is necessary and column 6 of Table l-l can be
ignored.
12 The IEA has agreed to provide die relevant energy statistics data, along with die
appropriate conversion {actors, to any interested countries ufion request The IEA will provide
data combining die fuel product detail found in die Energy Statistics (OECD/IEA, 1993)
publication with die common energy unit format found in die Energy Balances publication.
PART 2
1.17
-------
EMISSIONS FROM ENERGY
TABLE 1-2
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Albania Algeria Angola Argen- Arme- Azer- Bahrain Bangla- Bela- Benin
Cabinda tina nia baijan desh russia.
Bolivia
Oil
Crude OH
41.45
43.29 42.75 42.29
42.08 42.71
42.16
42.08 42.S8 43.33
NGL
43.29
4Z50
42.71
42.71
43.33
Coal
Hard Coal
Production
25.75
24.70
Imports
27.21
25.75
30.14 18.58 18.58
20.93
25.54
Exports
24.70 18.58 18.58
25.54
Brown Coal and Sub-Bituminous Coal
Production
9.84
Imports
14.65 14.65
14.65
Exports
9.84
14.65
14.65
14.65
Coal Products
Patent Fuel/BKB
29.31
29.31
29.31
Coke
27.21
27.21
28.46 25.12 25.12
25.12
Brazil Brunei Bulgaria Came- Chile China Colo-
roon mbia
Congo
Cuba Cyprus Czech
Republic
Oil
Crude Oil
4ZS4
42.75 42.62 42.45 42.91 42.62 42.24
42.91
41.16 42.48 41.78
NGL
45.22
42.75
42.87
41.87
Coal
Hard Coal
Production
18.42
24.70
28.43 20.52 27.21
24.40
Imports
30.56
24.70
28.43 20.52
25.75 25.75 23.92
Exports
20.52 27.21
27.98
Brown Coal and Sub-Bituminous Coal
Production
7.03
17.17
12.26
Imports
Exports
15.26
Coal Products
Patent Fuel/BKB
20.10
21.28
Coke
28.30
27.21
28.43 28.47 20.10
27.21
27.01
Crude oil conversion factors are based on weighted average production data.
The conversion factors are those used by the IEA In the construction of energy balances.
Source: OECD/IEA, 1993.
1.18
-------
EMISSIONS FROM ENERGY
TABLE I-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Ecuador Egypt Estonia Ethiopia Gabon Georgia Ghana
Guate- Hong Hungary India
mala Kong
Oil
Crude Oil
42.45 42.54
42.62 42.62 42.08 42.62 42.45
40.36 42.79
NGL
42.45
42.54
45.18 43.00
Coal
Hard Coal
Production
18.58
16.42 19.98
Imports
25.75
18.58
18.58 25.75
25.75 26.33 25.75
Exports
18.58
18.58
24.15 19.98
Brown Coal and Sub-Bituminous Coal
Production
14.65
10.55 9.80
Imports
14.65
14.65
9.91
Exports
14.65
14.65
Coal Products
Patent Fuel/BKB
20.10
29.31
21.44 20.10
Coke
27.21
25.12
25.12
27.21 30.11
Indonesia Iran
Iraq
Israel Ivory Jamaica Jordan
Coast
Kazakh-
stan
Kenya Kuwait Kyrgy-
zstan
Oil
Crude Oil
42.66
42.66 42.83 42.54 42.62 42.16 42.58 42.08
42.08 42.54 42.08
NGL
42.77 42.54
42.83
42.62
Coal
Hard Coal
Production
25.75 25.75
18.58
18.58
Imports
25.75
25.75
26.63
25.75
18.58
25.75
18.58
Exports
25.75
18.58
18.58
Brown Coal and Sub-Bituminous Coal
Production
14.65
14.65
Imports
14.65
14.65
Exports
14.65
14.65
Coal Products
Patent Fuel/BKB
29.31
29.31
Coke
27.21
25.12
25.12
Crude oil conversion factors are based on weighted average production data.
The conversion factors are those used by the IEA in the construction of energy balances.
Source: OECD/IEA. 1993.
PART 2
1.19
-------
EMISSIONS FROM ENERGY
TABLE I-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Latvia
Leb-
anon
Libya
Lithu- Malaysia Malta Mexico Moldava
ania
Mor- Mozam-
occo bique
Myan-
mar
Oil
Crude Oil
42.16 43.00 42.08 42.71
42.35
43.00
42.24
NGU
43.12
46.81
42.71
Coal
Hard Coal
Production
25.75
24.72
23.45 25.75
25.75
Imports
18.58
18.59
25.75 25.75 30.18
13.58
27.63 25.75
25.75
Exports
18.58
18.59 25.75
22.41
13.58
Brown Coal and
Sub-Bituminous Coal
Production
8.37
Imports
14.65
14.65
14.65
Exports
14.65
14.65
14.65
Coal Products
Patent Fuel/BKB
29.31
29.31
29.31
Coke
25.12
Nepal
-
Neth.
Antilles
-
Neutral
Zone
25.12
Nigeria
27.21
North Oman
Korea
27.96
Paki-
stan
25.12
Panama
27.21
Para-
guay
27.21
Peru Philip-
pines
Oil
Crude Oil
42.16 42.12 42.75 42.16 42.71 42.87 42.16 42.54 42.75
42.58
NGL
42.75
Coal
Hard Coal
Production
25.75 25.75
18.73
29.31
20.10
Imports
25.12
25.75
27.54 25.75
29.31
20.52
Exports
25.75 25.75
Brown Coal and Sub-Bituminous Coal
Production
17.58
8.37
Imports
Exports
Coal Products
Patent Fuel/BKB
Coke
27.21
27.21
27.21
27.21
Crude oil conversion factors are based on weighted average production data.
The conversion (actors are those used by the IEA in the construction of energy balances.
Source: OECD/IEA. 1993.
1.20
-------
EMISSIONS FROM ENERGY
TABLE 1-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Poland Qatar
Romania Russia Saudi Senegal Sing- South South Slovak Sri
Arabia apore Africa Korea Republic Lanka
Oil
Crude Oil
NGL
41.27 42.87
43.00
40.65 42.08 42.54 42.62 42.71 44.13 42.71 41.78 42.16
42.62 ... ...
Coal
Hard Coal
Production
Imports
Exports
Brown Coal and
Production
Imports
Exports
22.95
29.41
25.09
Sub-Bituminous Coal
8.36
-
9.00
16.33 18.58 - - - 25.09 19.26
25.12 18.58 - 27.21 23.92 25.75
18.58 - - - 25.09
7.24 14.65 ..... 12.26
7.24 14.65 .... ...
14.65 ..... 15.26
Coal Products
Patent Fuel/BKB
Coke
20.93
27.76
14.65 29.31 ..... 21.28
20.81 25.12 - - 27.21 - - 27.01
Sudan Syria Taiwan Tajik- Tanz- Thai- Trini- Tunisia
istan ania land dad /
Tobago
Turk- Ukraine Utd
meni- Arab
stan Emir-
ates
Oil
Crude Oil
42.62
42.04 41.41
42.08 42.62 42.62 42.24
43.12
42.08 42.08 42.62
NGL
46.85
43.12
Coal
Hard Coal
Production
25.96
18.58 25.75
21.59
Imports
27.42
18.58
26.38
25.75
18.58 25.54
Exports
18.58
18.58 21.59
Brown Coal and Sub-Bituminous Coal
Production
12.14
14.65
Imports
14.65
14.65
14.65
Exports
14.65
14.65
14.65
Coal Products
Patent Fuel/BKB
29.31
29.31
29.31
Coke
25.12 27.21 27.21
27.21
25.12 25.12
Crude oil conversion factors are based on weighted average production data.
The conversion factors are those used by the IEA in the construction of energy balances.
Source: OECD/IEA, 1993.
PART 2
1.21
-------
EMISSIONS FROM ENERGY
TABLE 1-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Uruguay Uzbek- Vcnez-
istan uela
Viet Yemen Former Zaire
Nam Yugo-
slavia
Zambia
Zim-
babwe
Oil
Crude OH
42.71
42.08 42.06 42.61 43.00 42.75 42.16 42.16
NGL
41.99
Coal
Hard Coal
Production
18.58 25.75
20.91
23.55 25.23 24.71
25.75
Imports
18.58
30.69 25.23
25.75
Exports
18.58 25.75
20.91
24.71
25.75
Brown Coal and Sub-Bituminous Coal
Production
8.89
Imports
14.65
16.91
Exports
14.65
16.90
Coal Products
Patent Fuel/BKB
29.31
20.10 29.31
Coke
25.12 27.21
27.21
26.90 27.21
27.21
Crude oil conversion factors are based on weighted average production data.
The conversion factors are those used by the IEA in the construction of energy balances.
Source: OECD/IEA. 1993.
1.22
-------
EMISSIONS FROM ENERGY
TABLE I-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Australia Austria Belgium
Canada
Den- Finland France
mark
Ger-
many
Greece Iceland Ireland Italy
Oil
Crude Oil
NGL
Refinery Feedst.
43.21 42.75 42.75
45.22 45.22
42.50 42.50 42.50
42.79
45.22
42.50
42.71 42.66 42,75
45.22
42.50 42.50 42.50
42.75
-
42.50
42.75 - 42.83 42.75
45.22 - - 45.22
42.50 - 42.50 42.50
Coal
Coking Coal
Production
Imports
Exports
28.34
28.00 29.31
28.21
28.78
27.55
28.78
28.91
34.33 30,50
-
28.96
28.96
28.96
.
27.44 29.10 30.97
.
Bituminous Coal and Anthracite
Production
Imports
Exports
24.39 - 25.00
28.00 25.00
25.65 - 25.00
28.78
27.55
28.78
26.71
26.09 26.38 25,52
26.09 - 26.43
24.96 ,
26.52
31.71
26.13 26.16
27.21 25,85 29.98 26.16
26.13
Sub-Bituminous Coal
Production
17.87 - 18.06
17.38
.
-
-
Imports - ........ ....
Exports
18.20
-
.
-
.
Brown Coal
Production
Imports
Exports
9.31 10.90
10.90 21.56
10.90
14.25
-
14.25
17.94
17.94
.
8.41
14.88
8.40
5.74 - - 10.47
19.82 10.47
.
Coal Products
Patent Fuel/BKB
Coke
21.00 19.30 23.81
25.65 28.20 29.31
-
27.39
18.27 - 28.80
31.84 28.89 28.71
20.64
28.65
15.28 - 20.98
29.30 26.65 32.66 29.30
The conversion factors for oil and coal are those used by the IEA in the construction of energy balances.
The conversion factors for coal product groupings listed are calculated from the conversion factors of their
constituents.
Source: OECD/IEA, 1993.
PART 2
1.23
-------
EMISSIONS FROM ENERGY
TABLE 1-2 (CONTINUED)
1990 COUNTRY-SPECIFIC CONVERSION FACTORS
(Gigajoule per metric ton)
Japan
Luxem- Ncther-
bourg lands
NZ Norway Port- Spain Sweden Switzerl Turkey
ugal and
UK
USA
Oil
Crude Oil 42.62
NGL. 46.05
Refinery Feedjt. 4Z50
42.71
45.22
42.50
43.12 42.96 42.71 42.66 42.75 42.96 42.79
46.05 45.22 - 45.22
44.80 42.50 42.50 42.50 42.50 42.50 42.50
42.83
46.89
42.50
42.71
45.22
42.50
Coal
Coking Coal
Production 30.63
Imports 30.23
Exports
-
29.30
-
28.00 - - 29.16 - - 33.49
28.00 - 29.30 30.14 30.00 - 33.49
28.00 .... - -
29.27
30.07
29.27
29.68
:
29.68
Bituminous Coal and
Anthracite
Production 23.07
Imports 24.66
Exports
-
29.30 29.30
29.30
26.00 28.10 - 21.07 14.24 - 29.30
28.10 26.59 25.54 26.98 28.05 27.21
28.10 - 23.00 26.98 28.05
24.11
26.31
27.53
26.66
27.69
28.09
Sub-Bituminous Coal
Production
Imports
-
-
21.30 - 17.16 11.35
11.35
-
-
19.43
-
Exports • ~ ~ ~ "•"
Brown Coal
Production
Imports
Exports
-
20.03 20.00
20.00
14.10 - - 7.84 - - 9.63
8.37 - 12.56
-
-
-
-
14.19
-
14.19
Coal Products
Patent Futl/BKB 27.05
Coke 28.64
20.10 23.53
28.50 28.50
20.31 20.10 21.76 20.93
28.50 28.05 30.14 28.05 28.05 29.28
26.26
26.54
-
27.47
The conversion factors for coal product groupings listed are calculated from the conversion factors of their
constituents.
Source: OECD/IEA, 1993.
1.24
-------
EMISSIONS FROM ENERGY
TABLE 1-3
CONVERSION FACTORS FOR OTHER
PRODUCTS
Factors (GJ/IO tonnes)
'Refined Petroleum Products
Gasoline (aviation and auto)
Kerosene
Jet Fuel
Gas/Diesel Oil
Residual Fuel Oil
LPG
Naphtha
Bitumen
Lubricants
Petroleum Coke
Refinery Feedstocks
Other Oil Products
44800
447SO
44590
43330
40190
47310
45010
40190
40190
40190
44800
40190
Other Products
Coal Oils and Tars
derived from Coking Coal
28000
Source: OECD/IEA, Paris. 1993.
CO2 emission estimates also need to consider that the amount of carbon per unit of
energy varies considerably both among and within primary fuel types:
• For natural gas, the carbon emission factor depends on the composition of the gas
which, in its delivered state, is primarily methane, but can include small quantities of
ethane, propane, butane, and heavier hydrocarbons. Natural Gas flared at the
production site will usually be "wet", i.e. containing far larger amounte of non-
methane hydrocarbons. The carbon emission factor will be correspondingly different
• For crude oil, Marland and Rotty (1984) suggest that the API gravity acts as an
indicator of the carbon/hydrogen ratio. Carbon content per unit of energy is usually
less for light refined products such as gasoline than for heavier products such as
residual fuel oil.
• For coal, carbon emissions per ton vary considerably depending on the coal's
composition of carbon, hydrogen, sulfur, ash, oxygen, and nitrogen. While variability
of carbon emissions on a mass basis can be considerable, carbon emissions per unit
of energy (e.g., per gigajoule) vary much less (with lower ranked coals such as
subbituminous and lignites usually containing slightly more carbon than higher-ranked
coals; anthracite is an exception since it typically contains more carbon than
bituminous coal).
PART 2
1.25
-------
EMISSIONS FROM ENERGY
TABLE 1-4
CARBON EMISSION COEFFICIENTS FOR FUELS FROM DIFFERENT STUDIES
(kg C/gigajoule,"net" heating value basis)
Study
Marland &Rotty (1984)
Marland &Rppin( 1990)
Grubb (1989)
OECD (1991)
Study
Anthracite Bit. Coal Sub-Bit.
Coal
25.5'
25.4'
26.8' 25.8'
25.8'
Crude Oil Gasoline Kerosene Diesel/Gas-
Lignite Peat
27.6' 28.9'
Fuel Oils NaturalGas
Oil
Marland&Rotty(l984)
Marland & Pippin (1990)
Grubb (1989)
OECD (1991)
2I.01
2I.01 I9.41
20.0 ' I8.91
20.0
IS.21
I9.41 I9.91 21.1 W I5.31
I9.51 20.01 21.1 ' IS.31
15.3
assuming a 5% difference in heating value for coal and oil, and 10% for natural gas. These percentage
adjustments are the IEA assumptions on how to convert from gross to net heating values.
Z Average value for all coal: sub-bituminous through anthracite.
3 Midpoint of range from 20.7 for light fuel oil (#4 fuel oil) to 21.6 for residual fuel oil (#6 fuel oil).
Estimates of carbon emission factors for fuels from several studies are summarized in
Table 1-4. The largest differences in emission factors between the studies occur with
bituminous coal and oil, although these differences are relatively minor.
One approach'for estimating the carbon emission factors was presented in Marland and
Rotty (1984). For natural gas, the carbon emission factor was based on die actual
composition of dry natural gas. They estimated the composition for natural gas from 19
countries based on sampling data and then calculated a weighted average global gas
composition, breaking the gas out into methane, ethane, propane, other hydrocarbons,
CO2, and other gases. The composition of the gas then determined both the heating value
of the gas and the carbon content. The carbon emission factor of the gas (kg C/gigajoule,
using gross "calorific" units13) was expressed using the following relationship:
Cg = 13.708 + (0.0828 X IO'3) X (Hv - 37.234)
where C{ is the carbon emission factor of the gas in kg C/gigajoule (GJ) and Hv is the
heating value of the gas (heating value in "gross" calorific units, see OECD/IEA, I990b) in
kj/meter3. The coefficients of the equation (13.708.0.0828 X IO"3. and 37,234) were
estimated using regression analysis based on data from the 19 countries. The carbon
content of oil was estimated to be a function of the API gravity: using an estimate of
world average API gravity of 32.5° ± 2°, they estimated a composition of 85% ± 1% carbon.
13 Two ways are used to express the energy content of fuels: gross calorific value and
net calorific value, sometimes expressed as high heating value and low heating value. The
IPCC methodology requires that all energy data be expressed using net calorific (or lower
heating) value.
1.26
-------
EMISSIONS FROM ENERGY
Converting this to units of carbon per gigajoule yielded an estimate of 21.0 kg C/GJ on a
net heating value basis (assuming 42.62 gigajoules per tonne, higher heating value, as
reported in Marland & Rotty, 1984). For coal, the literature suggested that the carbon
content of coal was predominantly a function of the energy content and that the carbon
content on a per ton coal-equivalent basis was around 74.6% + 2% (Marland and Rotty
1984). The carbon emission factor was estimated to be 25.5 kg C/GJ.
The approach used by M.J.Grubb (1989) to estimate carbon emission factors is very similar
but based on more recent research. All carbon emission factors were originally reported
on a "gross" heating value basis, but are converted here to a net heating value basis. He
provides carbon factors for methane, ethane, propane, and butane and using data from
Marland and Rotty (1984), he estimates an average emission factor for natural gas of 15.3
kg C/Gj ± 1%. For oil and some refined petroleum products the estimates are based on
data from the literature, as summarized in Table 1-4. The carbon emission factor of coal,
excluding anthracite, was defined as:
Cc = 32.15- (0.234 X Hv)
where Cc is the carbon emission factor in kg C/GJ and H¥ is the heating value of the coal
("gross" calorific value) when the heating value is from 31 to 37 GJ/ton on a dry mineral
matter free (dmf) basis. Anthracites fall outside this range and are estimated using a value
of 26.8 kg C/GJ.
Since the publication of the original OECD Background Document (OECD 1991),
additional information has been made available on carbon emission factors. Key points
from this new information are summarized below (all factors are in lower heating value):
• At an (PCC-sponsored workshop in October 1992 (IPCC/OECD, 1993), experts
recommended several revised emission factors based on national inventory
submissions to the OECD:
Oven or Gas Coke
Natural Gas Liquids
Petroleum Coke
Refinery Gases
29.5 kg C/GJ
15.2 kg C/GJ
27.5 kg C/GJ
!8.2kgC/Gj
Wood
Blast Furnace Gas
Coke Oven Gas
Bitumen
14
29.9 kg C/GJ
66 kg C/GJ
13 kg C/GJ
22 kg C/GJ
Of the country submissions received by the IPCC/OIECD programme to date only
Canada has reported a specific emission factor for subbituminous coals. This was a
value of 27.1 kg C/GJ ()aques, 1992). Detailed analysis conducted in the United
States reported an average value of 26.2 kg C/GJ (USDOE/EIA, 1992). Based on these
two results, it appears that the value previously recommended in OECD (1991)
should be lowered. Because the U.S. analysis is documented in a detailed report, and
14 This emission factor would only be necessary if a bottom-up methodology were
being used (e.g., see Approach #3).
15 This is the mid-point of a range of values.
PART 2
1.27
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EMISSIONS FROM ENERGY
U.S. production of subbituminous coals is much higher than in Canada, the new
recommended default value is 26.2 kg C/GJ.
• A number of countries have provided emission factors for jet fuel including those
reported in IPCC/OECD (1993) and more recent reports. Based on a weighted
average of these values the recommended emission factor for jet fuel is 19.5 kg; C/GJ.
The IPCC Reference Approach relies primarily on the emission factors from Grubb
(1989), with additions from other studies as discussed above, to estimate total potential
carbon. The suggested carbon emission factors are listed in Step 3 of Table l-l, Column 8.
Table l-l. Step 3, also provides the calculations needed to estimate the total carbon that
could potentially be released from the use of fuels. The basic methodology is:
Total Carbon (Gg C) =
Apparent Energy Consumption (by fuel type in GJ)
X Carbon emission factor (by fuel type in kg C/GJ), added across all fuel
types
Apparent consumption of the fuels is estimated in Step 2 of Table l-l (Column 7). The
carbon emission factors for the fuels are average values based on net calorific value (lower
heating value). As noted, this approach relies on carbon emission factors from Grubb
(1989), adjusted for net calorific value, plus factors recently available from other studies.
This approach has been recommended by the IPCC because it explicitly treats each major
fuel type differently according to its carbon emission factor. However, while carbon
emission factors are available for most fuel types, some gaps in the data still remain. It is
also possible that the default values provided here are not as accurate as country-specific
factors that may be available. To the extent that other assumptions are used, countries
should note the differences with the default values and provide documentation supporting
the values used in the national inventory calculations.
ESTIMATE CARBON STORED liji pVoDUCTS f ~*
*' ' NVw < t'^« ' *t$t , ~* rt-'n w, s, • *? •
After estimating the total carbon contained in the fuels, the next step is to estimate the
amount of carbon from these fuels that is stored (or sequestered) in non-energy products
and the portion of this carbon expected to oxidize over a long time period (e.g., greater
than 20 years). All of the fossil fuels are used for non-energy purposes to some degree.
Natural gas is used for ammonia production. LPGs are used for a number of purposes,
including production of solvents and synthetic rubber. A wide variety of products are
produced from oil refineries, including asphalt, naphthas, and lubricants. Coal is used to
produce coke; two by-products of the coking process include crude light oil and crude tar,
which are used in the chemical industry.
Not all non-energy uses of fossil fuels, however, result in the sequestering of carbon. For
example, the carbon from natural gas used in ammonia production is oxidized quickly.
Many products from the chemical and refining industries are burned or decompose within
a few years, while the carbon in coke is oxidized when used. Several approaches for
estimating the portion of carbon stored in products are reviewed in Box 2-1.
1.28
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EMISSIONS FROM ENERGY
Box 2-1
Approaches for Estimating Carbon Stored in Products
The approach used by Marland and Rotty (1984) relied on historical data for determining
non-energy applications and varied depending on fossil fuel -type. For natural gas they
assume that close to I /3 of the carbon used for non-energy purposes (equivalent to I % of
total carbon from natural gas production) does not oxidize over long periods of time. For
oil products they assume that some portion of LPG, ethane, naphthas, asphalt, and
lubricants do not oxidize quickly. Specifically, they assume that about 50% of LPG and
ethane from gas processing plants is sold for chemical and industrial uses and that 80% of
this amount, or 40% of all LPG and ethane, goes into products that sequester the carbon.
About 80% of the carbon in naphthas is assumed to end up in products such as plastics,
tires, and fabrics and oxidize slowly. All of the carbon in asphalt is assumed to remain
unoxidized for long periods, while about 50% of the carbon in lubricants is assumed to
remained unoxidized. For coal they assume that on average 5.91% of coal going to coke
plants ends up as light oil and crude tar, with 75% of the carbon in these products
remaining unoxidized for long periods.
M.J.Grubb (1989) basically uses the Marland and Rotty (1984) approach, but suggests
several changes, including higher estimates of methane losses during production and
transportation of natural gas to market and a wide range of estimates concerning the
fraction of carbon in refinery products that remain unoxidized. He does use Marland and
Rotty's estimate of the amount of carbon in coal that does not oxidize, but also quantifies
the amount of carbon emissions from SO2 scrubbing (in which CO2 is released during the
chemical interactions in the desulfurization process) using the formula: (% sulfur by
weight) X (coal consumption) X 12/32.
Okken and Kram (1990) introduce the concept of actual and potential emissions of CO2
where potential emissions are defined as carbon that is stored in products from non-
energy uses or by-products from combustion and actual emissions as all carbon from fuels
that are emitted immediately or within a short period of time. Actual emissions plus
potential emissions equal total carbon in the fuels. They assume that carbon from the
following non-energy uses of fossil fuels oxidizes quickly: fertilizer production (ammonia),
lubricants, detergents, volatile organic solvents, etc. Carbon from the following non-energy
uses of fossil fuels remains stored for long periods of time (in some cases, hundreds of
years): plastics, rubber, asphalt, bitumen, formaldehyde, and silicium carbide.
For the IPCC Reference Approach, the suggested formula for estimating carbon stored in
products for each country is:
Total Carbon Stored =
(Non-energy Use, I03 mt) x (Conversion Factor, GJ/IO3 mt) x (Emission
Factor, kg C/GJ) x
(% Stored), by product type
This approach is slightly revised from the original methodology in OECD (1991). The main
changes are converting all values to gigajoules rather than leaving all values in metric
tonnes and using an emission factor rather than an assumption for percent carbon
content. The resulting carbon estimates from non-energy uses would be considered
"potential" emissions, and are assigned to the country that produces the products. Most of
the suggested categories conform to those used by Marland and Rotty (1984) and include
naphthas, bitumen (asphalt), lubricants, LPG, and crude lighi: oil and crude tar. The data
available from the UN reports (e.g., 1990) correspond to these categories, with the
exception of crude light oil and tar, which is not reported.
PART 2
1.29
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EMISSIONS FROM ENERGY
In addition, recent information has suggested some other modifications to the approach
originally proposed in OECD (1991). These recommended modifications include:
• Naphtha will be stored when used as a feedstock in the petrochemical industry.
However, in many countries naphtha is not always used as a feedstock. As the
original methodology was based on total consumption of naphtha and not just that
portion intended for use as a feedstock, it has been recommended that the
methodology be changed to include only naphtha used as a feedstock. Furthermore,
available evidence from Western European countries indicates that approximately
75% of naphtha used as feedstock is transformed into intermediate products in the
petrochemical industry. The value of 75% is slightly lower than the 80% value
originally assumed, which was based on U.S. information only.
• Gas/Diesel oil may also be used as a feedstock. This category was not included
originally in the methodology, but is added here. Evidence from Western European
countries indicates that about 50% of gas/diesel oil used as feedstock is transformed
into intermediate products in the petrochemical industry.
The assumptions of 75% for naphtha as a feedstock and 50% for gas/diesel oil as a
feedstock should be viewed as potential overestimates since not all of the carbon from the
intermediate products will be stored. For example, carbon emissions may occur due to
losses in the production of final products or incineration of final products. At this time
these percentages can be used as the upper bound when determining stored carbon.
This suggested approach for estimating carbon stored in products is illustrated in Table I-
5. Whenever possible, countries should substitute assumptions that are more
representative of practices within their own countries and provide documentation for
these assumptions. The resulting estimates from Table I -5 (Column 7) should be
subtracted from potential emissions to determine net emissions of carbon that could be
oxidized. This calculation is done by entering the values from Table 1-5 (Column 7) for the
relevant fuels/products into Table I-I (Column 11). In Table I-1, carbon stored in
products is subtracted from total carbon in the fuels to get net carbon emissions.
1.30
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EMISSIONS FROM ENERGY
TABLE 1-5
ESTIMATION OF CARBON STORED IN PRODUCTS
I 234567
Estimated Conversion Fuel Emission Estimated Potential Percent
Fuel Factor Quantities Coefficient Carbon Carbon Carbon
Quantities Stored Stored Stored
Product/Fuel
Lubricants
Bitumen
Coal Oils and Tars from
Coking Coal
Naphtha as Feedstock
Gas/Diesel Oil
(Original
Units)
catc2
ca!c
calc
calc
calc
GJ/Units
Table 1-3
Table 1-3
Table 1-3
Table 1-3
Table 1-3
(GJ)
calc3
calc
calc
calc
calc
(Kg/GJ)
Table l-l
Table l-l
Table l-l6
Table l-l
Table l-l
(Gg)
calc4
calc
calc
calc
calc
(%)
50%
100
75
75
50
(Gg)
calc5
calc
calc
calc
calc
as Feedstock
Gas as Feedstock
LPG as Feedstock
calc
calc
Table 1-3
Table 1-3
calc
calc
Table l-l
Table l-l
calc
calc
33
80
calc
calc
This is only a partial list of products/fuels which accounts for the majority of carbon stored. Where data is
available for other fuels, the estimation of stored carbon is strongly encouraged.
Production plus Imports minus Exports minus Stock Change, or Feedstock Use.
Apparent Consumption (Col. 3) equals Apparent Consumption (Col. I) times a Conversion Factor (Col. 2).
4 Potential Carbon Stored (Col. 5) equals Apparent Consumption (Col. 3) times an Emission Coefficient (Col. 4).
4 Carbon Stored (Cot. 7) equals Potential Carbon Stored (Col. 5) times Actual Percent Carbon Stored (Col. 6).
6 Use the emission coefficient for coking coal (25.8 Kg C/GJ)
ESTIMATE CARBON OXIDIZED FROM ENERGY USES
As described earlier, not all carbon is oxidized during the combustion of fossil fuels. The
amount of carbon that fells into this category is usually a small fraction of total carbon, and
a large portion of this carbon oxidizes in the atmosphere shortly after combustion. Based
on work by Marland and Rotty (1984), the IPCC has been recommending that 1% of the
carbon in fossil fuels would remain unoxidized. This assumption was based on the
following findings from Marland and Rotty for the amount unoxidized:
• For natural gas less than 1% of the carbon in natural gas is unoxidized during
combustion and remains as soot in the burner, stack, or in the environment.
• For oil 1.5% ±1% passes through the burners and is deposited in the environment
without being oxidized. This estimate is based on 1976 U.S. statistics of emissions of
hydrocarbons and total suspended particulates.
• For coal 1% ±1% of carbon supplied to furnaces is discharged unoxidized, primarily in
the ash.
However, several countries have commented that the amount of carbon remaining
unoxidized is more variable than indicated by the 1% assumption across all fuels. For
example, it has been noted that the amount of unburnt carbon varies depending on several
factors, including type of fuel consumed, type of combustion technology, age of the
equipment, and operation and maintenance practices, among other factors.
PART 2
1.31
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EMISSIONS FROM ENERGY
Information submitted by the Coal Industry Advisory Board of the OECD (Summers
1993), provided the following observations for coal combustion technologies:
• Unoxidized carbon from electric power stations in Australia averaged about 1%. Test
results from stoker-fired industrial boilers, however, were higher, with unoxidized
carbon amounting to 1% to 12% of total carbon with coals containing from 8-23%
ash. As average values, 2% carbon loss was suggested for best practices, 5% carbon
loss for average practices, and 10% carbon loss for worst practices. In those cases
when coal is used in the commercial or residential sectors, carbon losses would be
on the order of 5-10% (Summers, 1993).
• In related work British Coal has provided information on the percentage of unburnt
carbon for different coal combustion technologies:
Pulverised Coal
Travelling Grate Stoker
Underfeed Stoker
Domestic Open Fire
Shallow Bed AFBC
PFBC/CFBC
1.6%
2.7-5.4%
4.0-6.6%
0.6-1.2%
Up to 4.0%
3.0%
• Evaluations at natural gas-fired boiler installations indicate that combustion efficiency
is often 99.9% at units reasonably well-maintained.
It is clear from the available information that a single global default assumption of I %
unoxidized carbon is not always accurate. While some additional information is available to
refine the assumptions for this portion of the methodology, most of the new information
requires some level of detail on the type of technology in which the fuel is combusted or
information on which sector is consuming the fuel. For this approach, the methodology
only requires data on the amount of fuels consumed in a country, not data by technology
type or sector'of the economy. As a result, based on the information available at this
point, the default values presented in Table 1-6 are recommended for the percentage of
unoxidized during combustion by fuel. It should be recognized that the value for coal is
highly variable based .on fuel quality and technology types. National experts are encouraged
to vary this assumption if they have data on these factors which indicates that different
average values for their countries are appropriate. It is clear from the information available
at this time that additional research should be conducted on this topic.
TABLE 1-6
CARBON OXIDIZED DURING
COMBUSTION
RECOMMENDED DEFAULT
ASSUMPTIONS
percent
Liquid Fuels
99%
Solid Fuels
Gaseous Fuels
98%
99.5%
1.32
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EMISSIONS FROM ENERGY
Net carbon emissions (column 12 in Table I-1) are then multiplied by the fraction of
carbon oxidized (column 13 of Table I-I), and then summed across all fuel types, to
determine the total amount of carbon oxidized from the combustion of the fuel. Next, to
express the results as Carbon Dioxide (CO2), there is one more step. Total carbon
oxidized should be multiplied by the molecular weight ratio of CO2 to C (44112) to find
total carbon dioxide emitted from fuel combustion.
1.4.3 Detailed Technology Based Calculations
This section briefly discusses procedures already used by some countries for estimating
CO2 emissions from fuel consumption at a more detailed and data-intensive level. This is a
"bottom-up" approach in that emissions are estimated by sector of economic activity
and/or by type of technology in which the fuel is consumed. The results for a wide range
of "end-uses" and transformation activities must be summed to arrive at total national
emissions. This discussion does not represent step by step guidance, but rather an initial
conceptual discussion, that raises some issues which should be considered.
A greater level of detail than is provided by the IPCC Reference Approach may ultimately
be needed by most, if not all, countries participating in international climate change
discussions. Such detail is important for analysis of policy options for reducing emissions,
which are frequently related to specific end uses rather than aggregate fuel use. As
discussed in the next three sections, a more detailed approach is needed to credibly
estimate emissions of several non-CO2 greenhouse gases from energy combustion.
Countries which have developed detailed energy and technology data for calculating
emissions of NOX, CO, etc., will very likely want to ensure that CO2 emissions estimates
are consistent and comparable. For this reason many countries may wish to utilize a
detailed approach for CO2 along with their detailed calculations for other GHG's from
energy. This current discussion is intended to assist those\countries which are trying to
build CO2 estimates into their existing detailed calculation procedures by indentifying
some of the calculation issues which will have to be'resolved.
This very detailed technology based approach does not provide a completely satisfactory
result for two reasons. First it is extremely data intensive and may not be possible for the
full range of IPCC countries in a reasonable time horizon. Second, even the most detailed
technology based estimates produced in some countries, do not always carry with them
the data necessary to conect emissions with economic subsectors of interest. In the
future, the IPCC/OECD programme plans to provide more detailed guidance on practical
application of a more detailed sectoral approach which will be less detailed than the
technology based estimates but will still provide emissions broken down by economic
sectors and sub-sectors of concern.
The detailed technology based calculations should be essentially the same as those carried
out in the Reference Approach, but should be carried out at a finer level of resolution.
PART 2
1.33
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EMISSIONS FROM ENERGY
The formula is:
fuel consumption (actual now rather than apparent) expressed in energy
units (GJ) at the level of transformation or end use sub-sector and possibly
by specific technology/process
x carbon emission factor
x fraction oxidized
Stored carbon would be calculated as is done in the reference approach although this, too,
may be done at a finer level of product/process detail.
These steps are also conceptually quite similar to the calculations used to estimate
emissions other than CO2 from stationary and mobile source combustion. The
methodologies for estimating emissions from these sources are discussed in detail in the
following three sections. The Reference Approach for CO2 only requires data by fuel type
at the national level, but for the detailed calculations, national experts would be required
to provide data on energy consumption patterns at a much greater level of detail. Once
countries have obtained the activity data required for estimating detailed "bottom-up"
inventories of NOX, CO, etc., from combustion in stationary and mobile sources (i.e., fuel
consumption data by sector by technology type), CO2 emissions can also be estimated as
part of the inventory estimates for these other gases. The amount of fuel consumed for
each disaggregated category can be multiplied by an appropriate emissions factor to
determine potential carbon emissions from fuel combustion. The fraction oxidized must
also be accounted for each category.
There are some important complexities which must be recognized in working from the
"bottom-up". Theoretically, it should make no difference in a country's total CO2 emission
estimate if the Detailed Technology Based Approach or the Reference Approach is applied
since the amount of fuel consumed, and hence the amount of carbon oxidized, should be
the same with both approaches. Differences may result, however, if the source activity
data or emission factor data are not the same between the two approaches. These
differences could be the result oft
• Actual differences may be due to better estimation methods with one approach (e.g.,
a country may choose alternative emission coefficients using the Detailed Technology
Based Approach that are thought to more closely represent fuel qualities for a
particular application)
• Statistical inconsistencies may exist between two different data sets (e.g., estimates of
national coal consumption do not match).
• A special problem may be in accurately accounting for losses of carbon in
transformation processes (as discussed below).
• Stored carbon (or non-fuel use) should be accounted for in much the same way as in
the reference approach. However, this may produce somewhat different results if
carried out at a finer level of detail.
The most important value of the Reference Approach is that it provides a simple,
transparent and verifiable means of accounting for all of the carbon in fuels which could
potentially be emitted to the atmosphere. Because of all of the above complexities, and
others, it may not always be the case that adding up the fuel used from detailed data sets
will account for all of the carbon in original fuels. For this reason, countries calculating
their emissions at the Detailed Technology Based level should cross-check their emission
estimates by also using the Reference Approach for verification, and reconcile any major
differences.
1.34
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EMISSIONS FROM ENERGY
Some of these difficulties at the detailed technology based level are discussed conceptually
below related to specific aspects of the calculations. If national experts have or are
developing detailed inventories of other gases they are encouraged to incorporate CO2
estimates in this process as well. Experts should read through the stationary combustion
and mobile combustion sections and should incorporate as much of the CO2 estimation as
possible in the same calculations. The emission factors necessary to apply the Detailed
Technology Based Approach for COZ emissions are repeated in the relevant sections.
In this approach countries would estimate fuel consumption for at least the same fuel
categories specified for the Reference Approach. A few additional fuel types such as Blast
Furnace Gas and Refinery Gas may need to be added to account for all of the fuels in the
form of their end use. The concept of "apparent consumption" used in the Reference
Approach allows users to ignore some of the details in fuel transformations. For example,
while we know that in fact crude oil is not actually consumed as an end use fuel, we also
know that all the carbon in the original crude oil is emitted to the atmosphere unless a) it
is converted to a non-fuel product (stored carbon), or b) it is incompletely oxidized and
remains as ash at a combustion or transformation step.
When working at the detailed level, countries would estimate actual fuel consumption for
these fuel categories rather than apparent consumption. Moreover, rather than
determining total national fuel consumption for these categories, a country would need to
determine the amount of fuel consumed in each sector in order to estimate emissions for
each sector of the economy. It may be necessary to account for actual consumption of
specific fuels in various end use subcategories, further broken down by specific processes
and technologies. Then one needs to work backwards to arrive at the total amounts of
fuel carbon supplied to an economy.
A major area of difficulty in this process is accounting for the carbon released in
transformation of energy from one form to another. The largest emissions from the
energy transformation sub-sector are associated with electric power generation, in which
fossil fuels are converted into electricity. These emissions are treated exactly like end use
fuel combustion emissions in most detailed inventories so this component should be
relatively straightforward.
Other transformations such as the refining of crude oil into oil products and the
production of coke from coal can be more complicated and may be difficult to fully
account for in the "bottom-up" approach. A simple input-output analysis may be helpful in
accounting for the carbon releases during transformation si:eps. For example, a refinery
(or for all refineries of a specific type) is a complex set of processes, but can be considered
as a single box. Total carbon in the form of crude oil (and possibly other input energy
forms) can be estimated. Total carbon out of the box in the form of secondary fuels or
fuel products can be estimated. Any carbon disposed of in die form of wastes (such as
ash), which represent stable long term storage, can be estimated. Any carbon not
accounted for in one of these output forms must be assumed to have oxidized as a result
of the transformation process.
Primary fuels that are not combusted directly, would thus not appear in end use
combustion, although they may be considered as input to the input-output analysis of
transformation Steps. In both transformation and in some end use applications, the
detailed technology based level will require explicit accounting of some intermediate
products -e.g., blast furnace gas, refinery gas - which can be ignored in the Reference
PART 2
1.35
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EMISSIONS FROM ENERGY
Approach. At a minimum it is recommended that countries using the Detailed Technology
Based Approach report emissions by the major fuel-consuming sectors defined in Volume
/: Reporting Instruction.
•Energy and Transformation Industries
—*r
• Industry
• Transport
• Commercial/Institutional
• Residential
• Agriculture/Forestry
• Other
• Biomass Burned for Energy (Unallocated to any of the other sectors listed
above)
Within each consuming sector emission estimates could also be developed according to
the technology type in which the fuel was consumed. The following sections on stationary
and mobile source combustion list possible technology source categories that could be
estimated. Additional work needs to be done to further define a comprehensive set of
appropriate categories.
This is handled exactly as in the Reference Approach. Wherever detailed fuel consumption
data are collected in original physical units such as I03 mt or other energy units such as
tons of oil equivalent (toe), they should be converted to gigajoules (GJ) using the same
conversion procedures discussed in the Reference Approach.
l»aKs»PTA:x;H'-'':/:%, j,,;yv.v;^J.%5Ssa^a|3M^^^ •,•-•'•.•-iS(j:,v*is-«;»,T:
|^lft£&&,Nl;.!£jM;iy5;§^
Once fuel consumption data are provided in GJ for the relevant sectors and/or technology
types, these consumption estimates can be multiplied by the appropriate carbon emission
factors to determine potential carbon emissions in kilograms (kg). The default carbon
factors are the same as those used in the Reference Approach since the carbon content of
specific fuel types does not change by sector or technology application. For example, if
bituminous coal is used in an industrial boiler, a country could use the same emission
factor for bituminous coal it would select under the Reference Approach. This does not
mean that a country may not vary the emission factor from one application to another if it
has reason to believe that the fuel qualities may differ. For example, if it is known that
bituminous coal consumed in the industrial sector has significantly different fuel qualities
than the average bituminous coal consumed in the country, then a country may wish to
specify an alternative emission factor. Unless such information is available, however, the
default emission factors used in the Reference Approach are acceptable.
These factors are provided again in the following sections on stationary and mobile source
combustion. In some cases the factors are also converted to different forms (e.g. kg total
COj/GJ, g CO2/km) where these are more appropriate for specific end uses. Countries
using alternative emission factors should note these differences and report the reasons for
using an alternative factor.
As in the IPCC Reference Approach, bunker fuel and biomass fuel and CO2 subtotals are
for informational purposes only, and should not be added to overall totals. They should be
shown as separate information totals when reporting.
1.36
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EMISSIONS FROM ENERGY
As discussed above under the Reference Approach, the amount of carbon that may remain
unoxidized from combustion activities can vary for many reasons, including type of fuel
consumed, type of combustion technology, age of the equipment, and operation and
maintenance practices, among other factors. Since the Detailed Technology Based
Approach relies on fuel consumption data on a more disaggregated level, it is possible to
specify the assumptions for unoxidized carbon by application. Unless other data are
available, as default values countries should use the assumptions recommended in the
Reference Approach: 2% of carbon in fuel consumed is unoxidized for coal, 1% for oil-
derived fuels and 0.5% for natural gas. In addition, the following assumptions (from
Summers, 1993) are recommended:
• For stoker-fired industrial boilers an average value for carbon unoxidized is 5%. If
countries believe that their operation and maintenance procedures achieve maximum
efficiency, a 2% carbon loss is suggested. If these procedures are believed to lead to
very poor efficiency, then a 10% carbon loss is recommended.
• In those cases when coal is used in the commercial or residential sectors, the
assumption for unoxidized carbon should be 5%.
Clearly, much additional research needs to be done in this area. These adjustments are
suggested as initial default values. As more work is done, countries are encouraged to
report any additional information they may have to refine understanding of the amount of
carbon unoxidized in various applications.
Calculations of stored carbon for countries choosing to use a detailed technology based
approach should be more straightforward since the counti-y would already be collecting
fuel consumption data, at a disaggregated level. The methodology for calculating stored
carbon (non-fuel uses) is the same as the procedures used in the Reference Approach.
That is, fuel quantities for which carbon may be stored should be estimated, then
converted to GJ, multiplied by the carbon emission factor to determine potential
emissions, and then multiplied by the actual share of carbon stored to determine the
carbon stored for each fuel. It may be that national experts working at a detailed
technology based level may account for non-fuel uses for a more detailed level of products
and processes. In this case, default factors may not apply, and fractions of carbon actually
stored and in some cases carbon emission factors will have to be supplied by the national
experts.
The adjustments for stored carbon (deductions of Gg CO2 stored) would have to be made
to the appropriate sector for which emissions are being estimated. In most cases, these
adjustments are made to emission estimates from the industrial sector since most uses for
which potential storage of carbon have been identified are from this sector. Countries
should explicitly identify the sectoral category to which they have assigned the estimates of
stored carbon.
PART 2
1.37
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EMISSIONS FROM ENERGY
This is also similar to the Reference Approach. For some end use categories emission
factors may be provided directly as kg CO2/Gj. Wherever emissions have been calculated
as carbon, the must be expressed as Carbon Dioxide (COj). To convert to CO* total
carbon oxidized should be multiplied by the molecular weight ratio of CO2 to C (44/12) to
find total carbon dioxide emitted from fuel combustion.
1.38
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EMISSIONS FROM ENERGY
1.5 Greenhouse Gas Emissions from Stationary
Combustion
1.5.1 Overview
This section discusses greenhouse gas emissions (CO2, NOX, N2O, CO, CH4, and
NMVOCs) from energy consumption in stationary sources. This section focuses on
emissions from commercial fuel consumption, which includes virtually all fossil fuel
combustion, but also includes the portion of biomass fuels traded commercially and used
in large scale technology applications. These biomass emissions are estimated in exactly
the same manner as fossil fuel combustion emissions, except for CO2 emissions 6. A large
share of total global biomass fuel consumption, however, is not accounted for in
commercial energy statistics. GHG emissions from this "traditional" biomass fuel use,
primarily in developing countries, are calculated differently and discussed in the next
section of this chapter.
Emissions of non-CO2 greenhouse gases across activities (sectors, sub-sectors) will
depend upon fuel, technology type, and pollution control policies. Emissions will also vary
more specifically with size and vintage of the combustion technology, its maintenance, and
its operation. As discussed in the previous section, CO2 emissions are not technology-
dependent, although these emissions can be estimated by technology using a "bottom-up"
approach, as described in this section.
In addition to CO2, stationary fuel combustion is a major component of total NOX
emissions in most countries. As defined here (i.e., excluding; "traditional" biomass), this
category generally contributes a smaller but still significant share of national emissions of
CO and NMVOC. With the exclusion of "traditional" biomass, the stationary combustion
category is generally a small contributor to total N2O and CH4, but these two gases are
nonetheless discussed in some detail because of their priority status within the
IPCC/OECD programme.
Organization of this section
The next sub-section provides a general discussion of the emissions calculation method
common to the estimation of all GHGs from detailed fuel combustion data. This includes
discussion of data needed including extensions required based on energy data discussed
earlier, and highlights the importance of fuel and technology specific emission factors in
this approach. The following sub-section provides a series of tables of representative
emission factors which illustrate the range of technologies of concern and the variations of
emission rates across these technologies.
16 CO2 emissions resulting from biomass fuel consumption should not be included in a
national energy emission totals to avoid double counting CO2. This double-counting would
occur either because: (I) biomass fuels may have been produced on a sustainable basis,
particularly for commercial consumers, such that no net increase in CO2 occurs, or (2)
production of CO2 from due to extraction of biomass fuels from existing stocks on a non-
sustainable basis would be captured as part of emissions which are calculated as described
in the Land Use Change and Forestry chapter in this manual. The IPCC method
recommends that countries estimate CO2 emissions from biomass fuel consumption and
report this as an information item.
r*ART 2
1.39
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EMISSIONS FROM ENERGY
Two additional sub-sections, discuss each of the relevant gases of interest is discussed
briefly. This discussion is presented in two parts - dealing with direct GHGs (CO2, N2O
and CH.,), and indirect GHGs (NOX, CO, and NMVOC) respectively. The priority area of
work for the IPCC/OECD programme in the initial stages was methodologies for direct
GHGs. Thus, improvements in methods for these gases are discussed in some detail. For
CO2 some additional discussion is provided to assist national experts who wish to do
these calculations at a "bottom-up" level of detail. N2O and CH4 from stationary
combustion are relatively minor as shares of total emissions. Nonetheless, as priority
gases, a review of recent research results is included for each.
For indirect gases, the IPCC/OECD programme has not carried out any original methods
development work. However, these gases are traditional air pollutants, as well as indirect
GHGs, and have been the focus of a great deal of ongoing work outside the IPCC/OECD
programme. The discussion of these gases, is primarily oriented toward identification of
comprehensive, up-to-date references which have been published by other inventor)'
programmes, including CORINAIR, and programmes of individual countries.
Finally, the last subsection discusses some priorities for future work.
1.5.2 Recommended Methodology
General Method
Estimation of emissions from stationary sources can be described using the following basic
formula:
Emissions = £ (EFabc x Activityab(.)
1
where:
EF = Emission Factor (g/GJ);
Activity = Energy Input (GJ);
a = Fuel type;
b = Sector-activity; and
c = Technology type.
Total emissions for a particular nation is the sum across activities, technologies and fuels of
the individual estimates.
Emission estimation is based on at least three distinct sets of assumptions or data: I)
emission factors; 2) energy activities; and 3) relative share of technologies in each of the
main energy activities. Sources of the emission factors and energy activities data that are
relevant internationally are described briefly below and suggestions on appropriate use of
such data are made.
Technology share or technology splits for each of the various energy activities are needed
at least on a national level for non-CO2 greenhouse gas estimation since emission levels
are affected by the technology type. Unfortunately, there are no complete international
sources of data on technology splits and, as a result, each nation will need to develop its
own technology splits for each energy activity.
1.40
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EMISSIONS FROM ENERGY
The main steps in the inventory method can be summarized as follows:
I Determine source of, and the form of, the best available, internationally verifiable,
national (or sub-national) energy activity data;
2 Based on a survey of national energy activities, determine the main categories of
emission factors;
3 Compile best available emission factor data for the country, preferably from national
sources. If no national source is available, select from the options described here.
Selection among the options should be based on an assessment of the similarity of
the country to the source of original measurements for types of technology and
operating conditions across main energy activities. The selection should also consider
the extent to which control technologies may be in place and the ability to clearly
separate and understand control policy assumptions that may be embedded in the
emission factor data.
4 Based on the form of the selected emission factor data, develop assumptions
regarding the technology categories to be used in the national inventory;17
5 Using these assumptions on technology categories, develop estimates, main activity
by main activity, of each of the greenhouse gases.
6 Sum the individual activity estimates to arrive at the national inventory total for the
greenhouse gases.
Data Needs
A considerable amount of detailed and specialized data is required to construct a national
inventory of GHGs from stationary fuel combustion. At minimum, the following types of
data are needed:
• Energy Activity Data:
Energy data sources are discussed in the introduction. The same basic energy information
is needed in estimating other GHGs from fuel combustion.
International sources or locally available sources of energy activity data can be used,
provided that the definitions and formats specified in the IPCC methodology are used to
ensure comparability and transparency. However, national sources will be needed for
activity data relating to specific technologies. It should be noted, that in many countries,
energy consumption data may be available in truly "bottom-up" data collection efforts,
associated with major programmes to develop detailed emissions. That is, energy
consumption data may be collected, along with technology information on a source by
source, region by region, or other disaggregated level. It is, of course, highly desirable to
have actual data on fuel use by technology type, rather than having to allocate down from
national statistics. It is important, however, in this situation, to carefully reconcile total
national energy accounts with "bottom-up" fuel use data to ensure that all fuel combustion
is being accounted for and none is double counted.
• Technology Splits for Energy Data
National data or assumptions on the technology shares of each of the main source sector
categories that have been identified as important in each country are necessary to create
the linkage between national energy balances and the emission factors. Again, this may be
bases on "bottom-up" data collection at as detailed a level as individual sources, or it may
17 This may also require assumptions about the control technologies in place.
PART 2
1.41
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EMISSIONS FROM ENERGY
be more of a top down allocation based on statistical sampling, or engineering judgement
The objective is to match up fuel use, by fuel type, with specific technologies or classes of
technologies, for which credible emission factors for non-COi gases can be provided.
• Emission Factor Data
Emission factors represent the average emission performance of a population of similar
technologies. Emission factors for all non-CO2 greenhouse gases from combustion
activities vary to lesser or greater degrees with:
• fuel type;
« technology;
• operating conditions; and
• maintenance and vintage of technology.
Good emission factors for gases other than COj are therefore usually technology specific,
but may still represent a wide distribution of possible values. In addition to technology
type, the impacts of equipment vintage, operating conditions, maintenance conditions, and
pollution control also affect emission factors. When available, the standard deviation of the
emission factor should be used to show the range of possible emissions factors, and hence
emissions, for each particular energy activity.18
There already exists a considerable body of literature and other data bases on emission
factors, particularly for the indirect GHGs (NOX, CO, and NMVOC) which are of great
interest as local and regional air pollutants, in addition to their affect on global radiative
forcing of the atmosphere. In addition to the basic emissions for specific technology types,
in some cases adjustments for control technologies may be needed. Accounting for
controls is particularly critical to estimation of emissions from large stationary sources in
OECD countries, but probably has a minor effect on emission estimates for the rest of the
world since control technologies are not typically used in these countries (See OECD/IEA,
1991).
Some tables of representative emission factors by main technology and fuel types were
presented in the previous preliminary methodology manual (OECD, 1991) distributed by
the IPCC. This information is still useful in illustrating the range and variation of sources
and emission rates, and is reproduced in the next section. More detail on current emission
factors and references is presented in the gas-by-gas discussions which follow after the
next section.
18 Unfortunately, the standard deviation of emission factors is rarely reported with
emission factor data. One study shows that when considered, variation of emissions
factors within an energy activity vary widely, from 20 to more than 50 per cent (Eggleston
andMclnnes, 1987).
1.42
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EMISSIONS FROM ENERGY
1.5.3 Illustrative Emission Factor Data
Some tables of representative emission factors for NOX", CO, CH4, N2O, and NMVOCs
by main technology and fuel types (based on Radian, 1990) were presented in the previous
preliminary methodology manual (OECD, 1991) distributed by the IPCC. This information
is still useful in illustrating the range and variation of sources and emission rates, and is
reproduced in Tables 2-8 to 2-12 for the major sectoral categories.20 All factors are
expressed on a grams per gigajoule of energy input basis (unless stated otherwise) and are
stated on a full molecular weight basis assuming that all NOX emissions are emitted as
NO2. These data are taken from Radian (1990) and show uncontrolled emission factors
for each of the technologies indicated. These emission factor data therefore do not include
the level of control technology that might be in place in some countries. For instance, for
use in countries where control policies have significantly influenced the emission profile,
either the individual factors or the final estimate will need to be adjusted.
It may be necessary to make adjustments to "raw" emission estimates to account for
control technologies, in place. Alternative control technologies, with representative
percentage reductions, are shown in Tables 2-13 to 2-16 (Radian, 1990) for the main
control technologies applicable to each sector. These lists reflect technologies in use for
large stationary sources in OECD countries. Preliminary indications are that, in the rest of
the world, control technologies are not typically used (See OECD/IEA, 1991). These data
should be used in combination with the uncontrolled emission factors to develop a "net"
representative emission factor for each of the technologies to be characterized in the
national emission profile; alternatively, the total emission estimate could be adjusted
downward according to the indicated percentage reduction.
Table 1-17 provides the fuel property assumptions upon which the Radian data are based.
The emission factor data in these tables is provided primarily for illustrative purposes.
These factors could be used as a starting point or for comparison by national experts
working on detailed "bottom-up" inventories. However, much more detailed data are
available and should also be consulted in this process. More detail on current emission
factors and references is presented in the gas-by-gas discussions in the next two sections.
The convention in this document is that NOX emissions from fossil fuel combustion
are expressed on a full molecular basis assuming that all NOX emissions are emitted as
NO2. It should be noted that this is inconsistent with the convention reflected in the
methods on NOX emissions from traditional biomass burning, which are expressed on a
full molecular weight basis assuming the emissions are all in the form of NO. This is a
convention common in literature on biomass burning. This inconsistency should be
reconciled in future versions of the methodology.
20 Little reliable information on N2O and NMVOCs emission factors was available at the
time these tables were developed. Some more recent information is presented or
reference later in this section.
PART 2
1.43
-------
EMISSIONS FROM ENERGY
TABLE 1-7
UTILITY BOILER SOURCE PERFORMANCE
Source
Natural Gas - Boilers
Gas Turbine Combined Cycle
Gas Turbine Simple Cycle
Residual Oil Boilers
Distillate Oil Boilers
Shale Oil Boilers
MSW - Mass Feed2
Coal - Spreader Stoker
Coal - Fluidized Bed Combined Cycle
Coal - Fluidized Bed
Coal - Pulverized Coal
Coal - Tangentially Fired
Coal - Pulverized Coal Wall Fired
Wood-Fired Boilers2
CO
19
32
32
15
IS
15
98
121
N/A
N/A
14
14
14
1,473
Emissions
CH4
O.I
6.1
5.9
0.7
0.03
0.7
N/A
0.7
0.6
0.6
0.6
0.6
0.6
18
Factors (g/GJ energy input)
NOX
267
187
188
201
68
201
140
326
N/A
255
857
330
461
112
N2O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
0.8
N/A
N/A
0.8
0.8
0.8
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
1 Values were originally based on "gross" (or higher) heating value; they were converted to "net" (or lower) heating value by
assuming that net heating values were 5% lower than gross heating values for coal and oil, and 10% lower for natural gas.
These percentage adjustments are the OECD/IEA assumption on how to convert from gross to net heating values.
1 Emission factors were adjusted to lower heating value assuming a 5% difference in energy content between lower heating
value and higher heating value.
Source: Radian, 1990.
TABLE 1-8
INDUSTRIAL BOILER PERFORMANCE
Emissions Factors (g/GJ energy input)1
Source
Coal-Fired Boilers
Residual Oil-Fired Boilers
Natural Gas-Fired Boilers
Wood-Fired Boilers2
Bagasse/Agricultural Waste-Fired
Boilers2
MSW - Mass burn2
MSW - Small Modular2
CO
93
15
17
1,504
1,706
96
19
CH4
2.4
2.9
1.4
15
N/A
N/A
N/A
NOX
329
161
67
115
88
140
139
N2O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
' Values were originally based on "gross" (or higher) heating value; they were converted to "net" (or lower) heating
value by assuming that net heating values were 5% lower than gross heating values for coal and oil, and 10% lower
for natural gas. These percentage adjustments are the OECD/IEA assumption on how to convert from gross to net
heating values.
2 Emission factors were adjusted to lower heating value assuming a 5% difference in energy content between lower
heating value and higher heating value.
Source: Radian, 1990.
1.44
-------
EMISSIONS FROM ENERGY
TABLE 1-9
KILNS, OVENS, AND DRYERS SOURCE PERFORMANCE
Emissions Factors (g/Gj energy input)1
Industry
Cement, Lime
Cement, Lime
Cement, Lime
Coking, Steel
Source
Kilns - Natural Gas
Kilns - Oil
Kilns - Coal
Coke Oven
CO
83
79
79
211
CH4
I.I
1.0
1.0
1
NOX
1,111
527
527
N/A
N20
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
Chemical Processes, Wood, Asphalt, Dryer - Natural Gas
Copper, Phosphate
64
N/A
N/A
Chemical Processes, Wood, Asphalt, Dryer - Oil
Copper, Phosphate
16
1.0
168
N/A
N/A
Chemical Processes, Wood, Asphalt, Dryer - Coal
Copper, Phosphate
179
1.0
226
N/A
N/A
Values were originally based on "gross" (or higher) heating value; they were converted to "net" (or lower) heating value by
assuming that net heating values were 5% lower than gross heating values for coal and oil, and 10% lower for natural gas.
These percentage adjustments are the OECD/IEA assumption on how to convert from gross to net heating values.
Source: Radian, 1990.
TABLE 1-10
RESIDENTIAL SOURCE PERFORMANCE
Emissions Factors (g/GJ energy input)
Source
Wood Pits2
Wood Fireplaces
Wood Stoves
Propane/Butane Furnaces
Coal Hot Water Heaters
Coal Furnaces
Coal Stoves
Distillate Oil Furnaces
Gas Heaters
CO
4,949
6,002
18,533
10
18
484
3,580
13
10
CH4
200
N/A
74
I.I
N/A
N/A
N/A
5
1
NOX
147
116
200
47
158
232
179
51
47
N2O
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Values were originally based on "gross" (or higher) heating value; they were converted to "net" (or
lower) heating value by assuming that net heating values were 5% lower than gross heating values for
coal and oil, and 10% lower for natural gas. These percentage adjustments are the OECD/IEA
assumption on how to convert from gross to net heating values.
Emission factors were adjusted to lower heating value assuming a 5% difference in energy content
between lower heating value and higher heating value.
Source: Radian, 1990.
PART 2
1.45
-------
EMISSIONS FROM ENERGY
TABLE Ml
COMMERCIAL SOURCE PERFORMANCE
Emissions Factors (g/GJ energy input)
Source
Wood Boilers'
Gas Boilers
Residual Oil Boilers
Distillate Oil Boilers
MSW Boilers''
Coal Boilers
Shale Oil Boilers
Open Burning - MSW
Open Burning - Agriculture
Incineration - high efficiency
Incineration - low efficiency
CO
199
9.6
17
16
19
195
17
42 kg/Mg
58 kg/Mg
5 kg/Mg
10 kg/Mg
CH4
15
1.2
1.6
0.6
N/A
10
1.6
6.5 kg/Mg
9 kg/Mg
N/A
N/A
NOX
33
48
155
64
463
236
186
3 kg/Mg
N/A
1.5 kg/Mg
1 kg/Mg
N2O
4.3
2.4
46.5
15.7
N/A
59.1
46.5
N/A
N/A
N/A
N/A
NMVOCs
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
' Values were originally based on "gr°ss" (or higher) heating value; they were converted to "net" (or
lower) heating value by assuming that net heating values were 5% lower than gross heating values for coal
and oil. and 10% lower for natural gas. These percentage adjustments are the OECD/IEA assumption on
how to convert from gross to net heating values.
Emission factors were adjusted to lower heating value assuming a 5% difference in energy content
between lower heating value and higher heating value.
Source: Radian, 1990.
1.46
-------
EMISSIONS FROM ENERGY
TABLE 1-12
UTILITY EMISSION CONTROLS PERFORMANCE
Efficiency CO
CH4
NOX
N20
NMVOCs
Date
Technology
Loss Reduction Reduction Reduction Reduction Reduction Available2
Low Excess Air (LEA)
Overfire Air (OFA) - Coal
OFA - Gas
OFA - Oil
Low NOX Burner (LNB) - Coal
LNB - Tangent. Fired
LNB - Oil
LNB - Gas
Cyclone Combustion Modification
Ammonia Injection
-0.5
0.5
1.25
0.5
0.25
0.25
0.25
0.25
0.5
0.5
+ +
+ +
+ +
+ +
+ +
+ +
+ 4-
+ +
N/A N/A
+ +
IS
25
40
30
35
35
35
50
40
60
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
1970
1970
1970
1970
1980
1980
1980
1980
1990
1985
Selective Catalytic Reduction
(SCR) - Coal
80
N/A
N/A
1985
SCR - Oil, AFBC
80
N/A
N/A
1985
SCR - Gas
80
60
N/A
1985
Water Injection - Gas Turbine
Simple Cycle
70
N/A
N/A
1975
SCR - Gas Turbine
CO2 Scrubbing - Coal
CO2 Scrubbing - Oil
CO2 Scrubbing - Gas
Retrofit LEA
Retrofit OFA - Coal
Retrofit OFA - Gas
Retrofit OFA - Oil
Retrofit LNB - Coal
Retrofit LNB - Oil
Retrofit LNB - Gas
Burners Out of Service
1 8
22.5 N/A
16.0 N/A
11.3 N/A
-0.5 +
0.5 +
1.25 +
0.5 +
0.25 +
0.25 +
0.25 +
0.5 +
+• 80
N/A N/A
N/A N/A
N/A N/A
+ IS
+ 25
+ 40
* 30
+ 35
+ 35
+ 50
+ 30
60
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
1985
2000
2000
2000
1970
1970
1970
1970
1980
1980
1980
1975
Efficiency loss as a percent of end-user energy conversion efficiency (ratio of energy output to energy input for each
technology) due to the addition of an emission control technology. Negative loss indicates an efficiency improvement.
Date technology is assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
PART 2
1.47
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EMISSIONS FROM ENERGY
TABLE 1-13
INDUSTRIAL BOILER EMISSION CONTROLS PERFORMANCE
Efficiency
CO
CH4
NOX
NMVOCs
Date
Technology
Loss1 Reduction Reduction Reduction Reduction Reduction Available^
Low Excess Air (LEA)
Overfire Air (OFA) - Coal
OFA -Gas
OFA -Oil
Low NOX Burner (LNB) - Coal
LNB -Oil
LNB - Gas
Flue Gas Recirculation
Ammonia Injection
Selective Catalytic Reduction
(SCR) - Coal
SCR-Oil.AFBC
SCR - Gas
Retrofit LEA
Retrofit OFA - Coal
Retrofit OFA - Gas
Retrofit OFA -Oil
Retrofit LNB - Coal
Retrofit LNB -Oil
Retrofit LNB - Gas
-0.5 + H
0.5 + •>
1.25 + •>
0.5 + H
0.25 +•
0.25 +
0.25 +
0.5 +
0.5 +
1 8
1 8
1 8
-0.5 +
0.5 +
1.25 +
0.5 +
0.25 +
0.25 +
0.25 +
r 15
^ 25
^ 40
H 30
H 35
^ 35
^ 50
^ 40
4- 60
<- 80
+ 80
+ 80
+ 15
+ 25
+ 40
+ 30
+ 35
+ 35
+ 50
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
60
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
1970
1970
1970
1970
1980
1980
1980
1975
1985
1985
1985
1985
1970
1970
1970
1970
1980
1980
1980
' Efficiency loss as a percent of end-user energy conversion efficiency (ratio of energy output to energy input for each
technology) due to the addition of an emission control technology. Negative loss indicates an efficiency improvement.
^Date technology is assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
1.48
-------
EMISSIONS FROM ENERGY
TABLE 1-14
KILN, OVENS, AND DRYERS EMISSION CONTROLS PERFORMANCE
Technology
LEA - Kilns, Dryers
LNB - Kilns, Dryers
SCR - Coke Oven
Nitrogen Injection
Fuel Staging
Efficiency
Loss1
-6.4
0
1.0
N/A
N/A
CO
Reduction
•f
+
8
N/A
N/A
CH4 NO'X
Reduction Reduction
+ 14
+ 35
+ 80
N/A 30
N/A 50
N20
Reduction
N/A
N/A
60
N/A
N/A
NMVOCs
Reduction
N/A
N/A
N/A
N/A
N/A
Date
Available2
1980
1985
1979
1990
1995
' Efficiency loss as a percent of end-user energy conversion efficiency (ratio of energy output to energy input for each
technology) due to the addition of an emission control technology. Negative loss indicates an efficiency improvement
2Date technology is assumed to be commercially available.
Note: A"+" indicates negligible reduction.
Source: Radian, 1990.
PART 2
1.49
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EMISSIONS FROM ENERGY
TABLE 1-15
RESIDENTIAL AND COMMERCIAL EMISSION CONTROLS PERFORMANCE
Technology
Catalytic Woodstove
Non-Catalytic Modified
Combustion Stove
Flame Ret. Burn. Hd.
Heed. Mix. Burn. Hd.
Integr. Furn. Syst
Blueray BurnVFurn.
MAN. Burner
Radiant Screens
Secondary Air Baffle
Surface Comb. Burner
Amana HTM
Modulating Furnace
Pulse Combuster
Catalytic Combuster
Replace Worn Units
Tuning, Seasonal Maintenance
Red. Excess. Firing
Red fir with new ret b
Pos. Chimney Dampers
Inc. thermal anticip.
Night therm, cutback
Low Excess Air
Hue Gas Recirculation
Over-fire Air
Over-fire Air
Low NOx Burners
Low NOX Burners
Efficiency
Loss1
(%)
-44
-30
-9
-7
-12
-12
-13
-7
N/A
N/A
-21
-7
-36
-29
N/A
-2
-19
-40
-8
-1
-IS
-0.8
0.6
1
1
0.6
0.6
CO
Reduction
(%)
90
15
28
43
13
74
N/A
62
16
55
-55
N/A
N/A
N/A
65
16
14
14
II
43
17
N/A
N/A
N/A
N/A
N/A
N/A
CH4
Reduction
(%)
90
50
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NOX
Reduction
(%)
-27
-5
N/A
44
69
84
71
55
40
79
79
32
47
86
N/A
N/A
N/A
N/A
N/A
N/A
N/A
15
50
20
30
40
50
N20
Reduction
(%) :
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
NMVOCs
Reduction
(%)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Date
Available2
1985
1985
1980
1970
1975
1970
1970
1980
1980
'Efficiency loss as a percent of end-user energy conversion efficiency (ratio of energy output to energy input
for each technology) due to the addition of an emission control technology. Negative loss indicates an
efficiency improvement.
2Date technology is assumed to be commercially available.
Note: A "+" indicates negligible reduction.
Source: Radian, 1990.
1.50
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EMISSIONS FROM ENERGY
TABLE 1-16
FUEL PROPERTIES'
Fuel
GAS
Butane/Propane
Coke Oven Gas
Methane (pure)
Natural Gas
Process Gas
LIQUID
Crude Shale Oil
Diesel/Distillate
Gasoline
Jet A
Methanol
Residual Oil
SOLID
Bagasse/ Agriculture
Charcoal
Coal
MSW
Wood
Heating Value
(GJ/tonne)2
45.7
36.7
45.0
46.0
48.6
40.9
42.9
H6.9MJ/gal
41.0
56.1 MJ/gal
40.9
8.6
27.6
22.0
10.7
10.1
Carbon
(wt percent)
82.0
56.1
75.0
70.6
70.6
84.5
87.2
85.7
86.1
37.5
85.6
22.6
87.0
65.0
26.7
27.0
Values were originally based on "gross" (or higher) heating value; they were converted to "net" (or
lower) heating value by assuming that net heating values were 5% lower than gross heating values for
coal and oil, and 10% lower for natural gas. These percentage adjustments are the OECD/1EA
assumption on how to convert from gross to net heating values.
2 Unless otherwise indicated.
Source: Radian, 1990.
1.5.4 Discussion Of Direct GHGs
In the initial stages of the IPCC/OECD programme it was recognized that work on both
methods development and national inventories needed to be prioritized, as it was not
possible to deal with all of the gases and sources simultaneously. The direct greenhouse
gases were established as the priority, with priority within this category in the following
order CO2, methane and nitrous oxides (IPCC/OECD, 1991). CO2from fuel
combustion has been discussed in detail in the previous section. It is discussed again here
briefly to emphasize the possible linkage of detailed CO2 calculations with the detailed
approach required for estimation of other GHGs from combustion.
Methods for estimating emissions of methane and nitrous oxide are not yet well
established, but are evolving rapidly based on a great deal of research underway within the
global change research community and elsewhere. For this reason, expert groups have
been established to recommend improvements in estimation methods for a variety of
source categories - including fuel combustion - which produce these gases. Information
developed by these groups provides some improvements in emission estimation methods
as described below.
PART 2
1.51
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EMISSIONS FROM ENERGY
Carbon Dioxide (CO2): The IPCC Reference Approach to estimation of CO2 emissions
from fuel combustion is described in the previous section. This method is designated as a
reference method because it is transparent, easy to implement, and produces very reliable
and comparable estimates for all IPCC countries. It is also clear that more detailed
information on CO2 emissions by source type can be useful to most countries. Countries
which have detailed data bases for estimating emissions of non-CO2 gases are encouraged
to also estimate CO2 emissions at a "bottom-up" level of detail based on the data
developed to estimate non-CO2 emissions.
Specifically, in order to estimate non-CO2 emissions using the emission factors provided in
Tables 2-9 to 2-13, countries will need to determine the amount of energy consumed by
sector, technology type, and fuel type. Since the fuel type is known, the carbon emission
coefficients provided in Table I-1 by fuel type could, in theory, be applied to the total
amount of input energy for each fuel/technology type by sector to determine total carbon
consumed for that category. To determine total CO2 emissions, one would sum across all
technology/fuel combinations and all sectors, and then follow the steps outlined in die
CO2 section including adjusting for any carbon unoxidized during combustion (see Table I -
7). It would also be necessary to account for non-energy uses emitting carbon (see Table
1-6), in order to ensure that total carbon in fuels is covered.
As noted in the previous section, there may be some variations in the carbon emission
factors (due to variations in fuel quality), and very likely will be differences in fraction
oxidized for different technologies. If more detailed factors are available based on local
conditions and measurements, these should be used (and documented). In addition, as
discussed in the previous section, there are a number of complex accounting problems
which can be ignored at the "top-down" level, but have to be addressed at a "bottorn-up"
level of detail. These are especially difficult in accounting for all of the carbon released
during transformation of energy from one form to another (e.g., refining of crude oil). The
IPCC Guidelines do not yet provide detailed guidance for dealing with these complexities.
Rather, it is recommended that national experts currently working at the detailed use
their own judgement to deal with the detailed questions which must be answered at the
"bottom-up" level. It is also strongly recommended that all countries also prepare
estimates using the IPCC Reference Approach and reconcile the results. This will help
identify any carbon in original fuels (e.g., transformation losses) which may not have been
accounted for in the detailed "bottom-up" accounts.
Methane (CH«): CH4 is produced from fuel combustion in small quantities due to
incomplete combustion of hydrocarbons in fuel. In large, efficient combustion facilities, the
emission rate is very low. In smaller combustion sources, emissions rates can be higher,
particularly where smoldering combustion conditions occur. In global terms, total
emissions from this source category (here defined to exclude "traditional" biomass burning
discussed in the next section) are believed to be small relative to other anthropogenic
source categories. Nevertheless, because of the importance of this gas, these emissions
are being studied carefully.
In a background paper prepared for the informal experts group, Berdowski, et al., (1993)
summarized the average emission rates for fuel combustion within broad subsectors. The
highest rates of methane emissions from fuel combustion are reported for residential
applications, where coal and "traditional" biomass fuels are used in small stoves for cooking
and heating. Emissions from "traditional" fuels such and fuelwood and agricultural residues
are discussed in the next section. Emissions from coal use in residential stoves can also be
quite high relative to other combustion applications, as shown in Table 1-18. This table
gives average emission factors for broad classes of combustion. It is clear that actual
emissions would vary within each category by technology type, fuel quality, and operating
conditions. However, the very aggregated information presented is sufficient to show that
1.52
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EMISSIONS FROM ENERGY
methane emissions from fossil fuel combustion in large scale utility and industrial
applications are low, with utility emission rates being less than I % of average rates for
residential coal combustion.
Based on the average emission factors in the above table, Berdowski, et al., (1993) estimate
global emissions from residential coal use to be in the range of 2.5-5.0 Tg/year, despite the fact
that residential coal use is common in only a few countries. The total emissions from utility and
industrial coal use and all other fossil fuel use was estimated to be less than 1.5 Tg/year. Despite
the fact that large amounts of fuel are used in these latter applications, the very low average
emission rates result in very small contributions to total emissions.
TABLE 1-17
GLOBAL EMISSION FACTORS AND EMISSIONS OF METHANE FROM COMBUSTION OF SOLID FUELS.
Fuel (type)
Coal
Residual oil
Distil, oils
Natural gas, LPG
Utilities
1
3
-
1
Emission factor (g/GJ)
Industry
10
3
1
4
Residential
300 (range 200-400)
-
7
3
Table adapted for Berdowski, et al., 1993
References: For residential coal use, USEPA, 1985; Zeedijk, 1986. All other categories from Veldt, 1991.
Nitrous Oxide (N2O): N2O is produced from combustion of fuels, although this source
category (stationary combustion, excluding "traditional" biomass burning) is presently
considered to be minor, relative to other anthropogenic source categories. The
mechanisms that cause the formation of N2O during the combustion of fossil fuel are now
fairly well understood (see De Soete, 1993). The basic knowledge on both gas phase and
heterogeneous N2O chemistry is well able to explain and to forecast at least in a
qualitative manner N2O emissions from different combustion sources and flue gas
treatment techniques.
Nitrous oxide (N2O) is produced directly from the combustion of fossil fuels. Gas phase
N2O chemistry is relatively well understood as it is part of NO kinetics and N2O appears
as a by-product of the so-called fuel-NO mechanism. For combustion temperatures well
below 1000 K or above 1200 K the emission factor for N2O is almost zero or negligible; in
the temperature range between about 800 and 1100 K N2O emissions are reaching the
highest levels with a maximum around 1000 K. Increasing the oxygen concentration or the
pressure tends to increase the emissions.
Fundamental studies of non-catalytic heterogeneous reactions on the formation and
destruction of N2O only started in recent years, so the available experimental data is still
rather scarce. The main mechanisms for the N2O chemistry appear to be: destruction of
N2O on bound carbon atoms, the formation of N2O from char bound nitrogen atoms, and
the formation of N2O from NO and reduced sulfates. Catalytic N2O chemistry may play a
role in the following cases:
• at overall reducing conditions (catalysts in spark ignition cars and trucks),
• at overall oxidizing conditions (de-NOx-techniques such as Selective Catalytic
Reduction [SCR], emission abatement of diesel engines and lean-burn spark ignition
engines), and
• catalytic formation and destruction (e.g. during fluidized bed combustion caused by
the presence of CaO).
PART 2
1.53
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EMISSIONS FROM ENERGY
Recent re-evaluation of available emission factor data from fuel combustion showed that in
measurements before July 1988 often a so-called artefact appeared stemming from the
presence of NOX and SO2 in samples, which resulted in erroneous emission factors whjch
were much too high, thereby highly overestimating the importance of this source category
(Muzio and Kramlich, 1988). Since the recognition of this artefact in June 1988 new
measurements have lead to new reliable emission factors from different conventional
stationary combustion sources (De Soete, 1993).
Emission factors can be limited to one value per fuel type for all applications, since relevant
knowledge is now readily available, (see De Soete (1993) and references therein)
Advanced (Pressurized) Fluidized Bed Combustion [(P)FBC] emissions are dependent on
the rank of the coal: brown coal produces less emissions than bituminous coal. The
emission factors for waste combustion and especially for sludge incineration are very high,
with a tendency to increase when FBC technology is applied.
Combustors with application of catalytic reduction techniques for emission abatement (e.g.
SCR or Non-Catalytic Selective Reduction [NCSR] of NO,,) also have estimated emission
factors. NCSR experiments suggest that the application of this control technology
increases the emission factor for N2O; for SCR no differences are observed. In the case of
NCSR the N2O emissions are higher from urea or cyanuric acid injection than in the case
of ammonia injection. These control technologies may not only be applied on large scale
facilities exploited by utilities or industry, but may also be applied in modern woodstoves.
Due to the uncertainty for the last categories at present an uncertainty range for these
sources is most appropriate. Default uncertainty ranges still have to be determined, but a
preliminary range is presented in this report.
Default emission factors and uncertainty ranges are shown in Table 1-19. When a country
has its own locally determined emission factors, these are of course preferred above the
default factors reported here. However, care should be taken that no artefact data were
used in deriving the factors.
Reliable emission factors for non-commercial fuel combustion in particular fuelwood and
charcoal are currently not yet available because of lack of data on emission measurements
for these combustion technologies. This refers amongst others to fuelwood, charcoal
(production and use in residential, commercial and industrial sectors), crop residues and
dung. Published data are scarce and the representativeness for global application is
questionable. Also, in the preparation of national inventories care should be taken to avoid
double counting, since emissions of fuelwood use may also be included in the category of
biomass burning. (Olivier, 1993)
1.54
-------
EMISSIONS FROM ENERGY
TABLE 1-18
ESTIMATED DEFAULT EMISSION FACTORS FOR STATIONARY
COMBUSTION FACILITIES.
Technology
Emission factors
(S N2O/GJ energy
input)
(or g NjO/ton waste)
Uncertainty range
(ibidem)
Conventional facilities, uncontrolled
Coal
1.4
0-10
Oil
0.6
0-2.8
Gas
0.1
0-1.1
Conventional facilities, controlled
Selective catalytic
reduction (SCR) of NOx
see uncontrolled
see uncontrolled
NCSR
NA
10-100
**5T
Other combustion facilities:
Fluidized bed com-
bustion - hard coal
NA
10-95
FBC - brown coal, peat,
wood
NA
10-30
Gas turbines - oil, gas
NA
0-5'
N.B.
NA = Not Available
If the combustion temperature exceeds 1000 °C one may use
a range of 0-10.
Preliminary estimate with NH3 injection at lower end and
with urea injection at higher end of range.
Source: De Soete (1993) and references therein.
1.5.5 Discussion Of Indirect GHGs
The IPCC/OECD programme has not yet addressed the indirect GHGs in detail. This is
consistent with the initial priorities within the IPCC/OECD programme. As noted above,
fuel combustion is a major source for all of these gases. Because they are important
contributors to a range of local and regional, as well as global atmospheric pollution
problems, NOX, CO and NMVOC have been widely studies and reported. The Radian data
cited above reflect estimates of performance ranges of main combustion technologies in
place worldwide, as of 1990. They are still considered to be reasonably representative.
However, since in most instances the data are based on measurement samples taken from
the United States, they represent averages of operating conditions, sizes and vintages of
units found there. In all cases they are averages over a range of technologies, fuel qualities,
and operating conditions.
More detailed alternative emission factor source data representative of the precise
technologies and other conditions in a particular country would always be desirable.
National experts working on detailed emission of non-CO^ GHGs (particularly the
indirect gases) should consult the extensive literature on emission factors and other
estimation procedures which has been developed by other inventory programmes outside
of the framework of the IPCC/OECD programme. As distinguished from the Radian
emission factors, these data generally contain more technology detail, and are further
detailed by sizes of the various technologies. There is also a slight difference in the
PART 2
1.55
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EMISSIONS FROM ENERGY
technology representation, but this may be more a terminology than a technical difference.
The specific nature of these control assumptions should be known and carefully matched
with actual conditions in the specific country in selecting the specific factors to be used.
Some key examples of data sources are:
• The CORINAIR Inventory: Default Emission Factors Handbook (Bouscaren, 1992);
• U.S. EPA's Compilation of Air Pollutant Emissions Factors (AP-42), 4th Edition 1985,
(U.S. EPA, 1985), and Supplement F, (U.S. EPA, 1993);
• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory
(Stockton and Stelling, 1987)
• Proceedings of the TNO/EURASAP Workshop (TNO Inst of Environmental
Sciences, 1993)
J Emissions Inventory Guidebook (European Environment Agency, forthcoming)
• EMEP and CORINAIR Emission Factors and Species Profiles for Organic Compounds.
(Veldt, 1991);
• Other National Compilations of Emission Factors Include
Netherlands
Norway
Germany
Walbeck, et al., 1988
Japan
United Kingdom
Bakkum, et al., 1987, Okken, 1989
Statens forurensningstilsyn, 1990
Brieda, 1989, Fritsche, 1989, Rentz et al., 1988,
JAERI, 1988
Essleston and Mclnnes, 1987
Nitrogen Oxides (NOX): Electricity generation and industrial fuel combustion activities
are similar in that they provide combustion conditions conducive to NOX formation. NOX
emissions depend in part on the nitrogen contained in the fuel (this may be especially
important for coal), but more importantly on the firing configuration of the technology.
Excess air and .high temperatures contribute to high NOX emissions. Such conditions are
highly variable by type of boiler; for instance, for oil-fired plants, tangential burner
configurations generally have lower emission coefficients than horizontally opposed units.
Also, the size of the boiler will affect the NOX emission rate due to the lower
temperatures of smaller units.
Usage of the technology can also significantly alter the pattern of NOX emissions.
Measurements of emissions show a 0.5% to 1.0% decrease in NOX emission rates for
every 1.0% decrease in load from full load operation. That is, as the usage rate increases,
so does the emission rate associated with the facility.
Finally, control policies and related technological changes to meet emission limits directly
influence NOX emissions. Emissions from large facilities can be reduced by up to 60% by
straightforward adjustments to the burner technology.2' These adjustments are often
standard in new facilities, but may not exist in older facilities in many OECD countries and
may be especially rare in non-OECD countries. NOX controls may also increase the rate
of CO emissions. Information on the stock of combustion facilities, their vintage, and level
of control are therefore necessary to accurately estimate emissions from large combustion
facilities.
21 This can be done, for example, by limiting the excess air in combustion or by
staging the combustion process.
1.56
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EMISSIONS FROM ENERGY
NOX emissions from small combustion facilities (small industry, commercial and residential)
tend to be much less significant than for large facilities due to lower combustion
temperatures. Nevertheless, emissions will depend on the specific combustion conditions
of the activity in question, and an effort should be made to carefully characterize the type
of activity, on average, in order to select appropriate emission factors.
For many years, NOX has been the target of environmental policies for its role in forming
ozone (O3), as well as for its direct acidification effects. As a result, NOX emission
inventories and related data such as emission factors are more widely available than those
for the other non-CO2 greenhouse gases considered here. The sources listed above
provide a large number of emission factors depending on technology, fuel characteristics,
operating conditions, size, vintage, etc.
Carbon Monoxide (CO): By comparison to NOX, combustion conditions in large
facilities are less conducive to formation and release of CO emissions. CO is an unburnt
gaseous combustible that is emitted in small quantities due to incomplete combustion. It
have also been the target of emission control policies in some countries and hence must
be estimated with these controls in mind. It is directly influenced by usage patterns,
technology type and size, vintage, maintenance and operation of the technology. Emissions
can vary by several orders of magnitude, for example, for facilities that are improperly
maintained or poorly operated, such as may be the case for many older units. Similarly,
during periods of start-up, combustion efficiency is lowest, and CO emissions are higher
than during periods of full operation.
Size of the unit may indicate that combustion is less controlled and hence the CO
emission coefficients for smaller units are likely to be higher than for large plants. Also
wood stoves, due to their largely inefficient combustion of the fuel, have particularly high
emission rates of CO. For these reasons, an understanding of commercial and residential
activities are key to the estimation of CO from stationary sources, particularly in non-
OECD countries where residential consumption of wood and other vegetal fuels is
commonly high.
CO emissions from stationary sources are estimated in the same way as for NOX
emissions. Detailed energy data provide the basis for estimation, but there may be
significant variation in the precise size and type of combustion technologies in place. A
main combustion source of CO is the residential sector, where there is great variation in
technology by geographic region due to a variety of manufacturers as well as
unconventional combustion modes that may be found throughout the world. This may be
especially the case for wood fuel use22 — an area where data are weak both on total
energy consumption and characterization of the range of technologies in use in different
regions of the world.
With these notes of caution in mind, another data source for CO emission factors from
stationary sources is provided in {.'Office Federal de la Protection de [.'Environment, Bern,
Switzerland (OFPE, 1987). This source is based on other European sources; it does
22Some wood fuel use which is covered in commercial energy statistics and for which
technology and emission factor data are known, may be included in the calculation
described in this section. For developing countries, however, there is frequently a large
share of "traditional" biomass use, which is generally not included in commercial energy
statistics, and data on the mix of specific technologies used is lacking. For these countries
an optional simpler method of calculating emissions from "traditional" biomass fuel use is
provided in the next section. National experts must take care to ensure that there is not
double counting, if more than one method is used.
PART 2
1.57
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EMISSIONS FROM ENERGY
provide a range for each of the activity categories for CO emission factors when combined
with the Radian factors above.
Non-Methane Volatile Organic Compounds (NMVOC): As with CO, combustion
conditions in large facilities are less conducive to formation and release of NMVOC
emissions. VOCs are also unburnt gaseous combustibles that are emitted in small
quantities due to incomplete combustion. They have also been the target of emission
control policies in some countries and hence must be estimated with these controls in
mind. They are directly influenced by usage patterns, technology type and size, vintage,
maintenance and operation of the technology. Emissions can vary by several orders of
magnitude, for example, for facilities that are improperly maintained or poorly operated,
such as may be the case for many older units. Similarly, during periods of start-up,
combustion efficiency is lowest, and NMVOC emissions are higher than during periods of
full operation.
Size of the unit may indicate that combustion is less controlled and hence the NMVOC
emission coefficients for smaller units are likely to be higher than for large plants. Also
wood stoves, due to their largely inefficient combustion of the fuel, have particularly high
emission rates of VOCs. For these reasons, an understanding of commercial and
residential activities are key to the estimation of these greenhouse gases, particularly in
non-OECD countries where residential consumption of wood and other vegetal fuels is
commonly high.
Extensive emission factor data for non-methane volatile organic compounds (NMVOCs)
from energy combustion sources are available from most of the sources listed above. In
some older sources total volatile organic compounds, including methane have been
considered together. The recent work of the CORINAIR programme, the U.S. EPA
sources cited above, and most other more current sources distinguish both NMVOC and
methane in emission factors and emission estimates. Analysts should be careful to
understand the exact category of pollutant being specified when selecting emission factor
data. There is considerable uncertainty in most available information on NMVOC
emissions as is the case for methane.
The CORINAIR and U.S. EPA factors show rough agreement on most categories of fuel
combustion, though both acknowledge considerable uncertainty. These data highlight the
importance of small combustion facilities as the main energy-related source of emissions,
but emission factor data for small facilities is also particularly unreliable. In any case, a
review of the literature confirms that NMVOCs from energy combustion (excluding
traditional biomass fuels) is a relatively minor source of the total NMVOC emissions in any
given country or region.
1.5.6 Priorities For Future Work
Data for Non-OECD Regions of the World
A high priority for follow-up work is to develop representative energy technology and
emission factor data for developing countries and other non-OECD regions of the world.
Emission factor data are likely to differ significantly among OECD and non-OECD regions
due to differences in types of fuels, combustion technologies, their vintage, their size and
operating conditions.
Uncertainty in Emission Factor Data
Emission factor data are normally presented as single point estimates. In fact, emission
factors are characterized by a great deal of variation around these point estimates.
1.58
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EMISSIONS FROM ENERGY
Therefore, it would be preferable to have emission factor data presented with appropriate
ranges, as well as with accompanying statistics such as representative operating conditions.
These statistics should help relate the range of emission factors to the associated
operating conditions.
Priorities by Gas
Emission factor data are particularly weak for N2O, CH4, NMVOC and CO. Monitoring
and measurement studies for these gases to improve the base emission factor data would
further the development of complete greenhouse gas inventories. The extent to which it
is necessary to fill data gaps depends upon the importance of these greenhouse gases in
national inventories.
However, CH4 and N2O emissions from stationary combustion sources (excluding
"traditional" biomass fuel burning) are a small share of total emissions, although a few
specific technologies appear to have higher emission rates and may warrant extensive
study.
Similarly, NMVOC and CO can be quite significant in areas where wood or vegetal fuels
make up a major share of total energy consumption. Again, these are areas with substantial
"traditional" biomass fuel consumption, discussed in the next section.
Development of Simplified Workbook Methods
As noted several times in this chapter, the non-CO2 gases do not lend themselves to
simple "top-down" aggregate emissions estimation. Nonetheless, the IPCC and parties to
the Framework Convention on Climate Change are committed to providing methods
which are both comprehensive over all GHGs and accessible to all participating countries.
Further work is needed to define default methods for estimating the non-CO2 gases from
fuel combustion. This may require development of a "mid-level" approach which
incorporates more detail than the national top down CO2 approach, but provides an
intermediate level of detail which can capture the most important variations by technology
without going directly to the most detailed level of technology information which may be
difficult for some countries to obtain.
Reconciling Energy and ISIC Categories with Engineering-Technology
Category Definitions
A priority for those countries where extensive emission data bases are being developed is
a means of relating categories used in IEA energy statistics, a:> well as more detailed ISIC
categories to standard engineering-technology or process category definitions. One key
example is the ongoing effort to reconcile the proposed IPCC source category structure
with the engineering/technology based structure in CORINAIR. This is discussed in Volume
I: Reporting Instructions.
PART 2
1.59
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EMISSIONS FROM ENERGY
1.6 Burning Traditional Biomass Fuels
1.6.1 Overview
For all burning of biomass fuels, the IPCC methodology requires that net: CO2 emissions
are treated as zero in the energy sector. Some biomass fuels are sustainably produced, in
which case the actual net emissions are zero. However, even if all or part of the biomass
fuel burned is extracted unsustainably from existing biomass stocks (e.g., forests), it would
be difficult to determine, at the point of combustion, what fraction actually represents net
emissions. Therefore, net CO2 emissions, which are reflected in reductions in biomass
stocks, are accounted for in the Land Use Change and Forestry section of the
methodology.23 However, other (non-CO2) gases are emitted from burning of biomass
fuels. Emissions of these gases (e.g., methane - CH4, carbon monoxide - CO, nitrous oxide
- N2O, and oxides of nitrogen - NOX) are net emissions and are accounted for as energy
emissions. This section provides a method for calculating emissions of these non-CO2
gases from burning of traditional biomass fuels.
Burning of "traditional biomass" is intended to include all traditional, small-scale use of
biomass fuels, such as cook stoves and open fires. It also includes the production as well as
consumption of charcoal in small scale traditional processes. In these conditions, emissions
can be estimated using emission ratios of CH4 and other gases to total carbon oxidized in
the biomass, as is done in the various non-energy types of open burning. Non-CO2 trace
gas emissions from commercial use of biomass in large-scale combustion facilities or other
technologies for converting energy, are treated elsewhere in the energy combustion
chapter. This is because the recommended methods for calculating emissions for these
source types are different from this proposed method for traditional, small-scale bioenergy
use. Emissions from large-scale facilities are very much a function of the particular
technology used and are treated very much like emissions from stationary fossil fuel
combustion -- with specific emission factors for each technology/fuel combination.
Emissions from traditional biomass fuel use also vary significantly based on technology,
operating conditions, etc. However, available data often does not support a technology
specific approach for traditional biomass fuel use. Therefore, the emission ratios approach
is provided as a common method for crude estimation which can be used by all national
experts.
This separation between commercial and traditional biomass does introduce the possibility
of double counting some biomass energy use. Care should be taken to ensure that the
"commercial" component of bioenergy use is carefully defined and deducted from total
bioenergy consumed before doing the calculations of emissions from traditional biomass
fuel use described in this section. It should also be noted that other possibilities for double
counting of emissions from biomass fuels exist in the methodology. Agricultural residues
and dung are two of the traditional fuels included in this section. Both are also sources of
23 For policy analysis purposes in the energy sector, it may be very important to
consider the net CO2 emissions from biomass fuel burning as an energy related emission.
This can facilitate the comparison of biomass fuel combustion with other energy options
on the basis of CO2 or total GHG emissions. It is possible to reallocate the implied CO2
emissions to biomass burning for such analytic purposes. However, it is essential, for
consistency, that all national inventories be reported as specified in the IPCC Guidelines,
that is, no net CO2 emissions are counted for biomass burning.
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emissions calculated in the agriculture section. Some portion of agricultural residues may
be burned in the fields and produce the same set of trace gases in that situation. Dung is
treated as a potential source of methane emissions from anaerobic decomposition in the
calculation of emissions from animal wastes. In both cases it is the responsibility of users of
this methodology to ensure that these materials are allocated to their different uses and
not counted in both places.
For traditional biomass fuels, the approach is essentially the same as that used for non-
CO2 trace gases from all burning of unprocessed biomass, such as field burning of
agricultural residues and savanna burning (Chapter 4: Agriculture) and open burning of
cleared forests (Land use change and forestry, Chapter 6). For all these activities there is a
common approach in the proposed methodology, in that crude estimates of non-CO2
trace gas emissions can be based on ratios to the total carbon released. The carbon trace
gas releases (CH4 and CO) are treated as direct ratios to total carbon released. To handle
nitrogen trace gases ratios of nitrogen to carbon in biomass fuels are first used to derive
total nitrogen released. Then emissions of N2O and NOX are based on ratios to total
nitrogen released. Default values for non-CO2 trace gas emission ratios are provided,
including ranges which emphasize their uncertainty. However, the basic calculation
methodology requires that users select a best estimate value.24
1.6.2 Recommended Methodology
Calculations: There are two basic components to the calculation. First, it is necessary to
estimate the amount of carbon released to the atmosphere from biomass fuel burning.
These carbon releases are not net emissions, but are needed to derive non-CO2 trace gas
emissions which are net emissions. The activity data required are the annual consumption
of the various types of biomass fuels. Box I provides some suggestions for developing
these data. Based on the type of fuel burned, the amount of carbon released can be
calculated (a reflection of carbon content and combustion efficiencies, see Table A). The
second component is the same as for other biomass burning categories -- emission ratios
are applied to estimate the amount of non-CO2 trace gas released based on the amount of
carbon released (Box 2)
Part I: Total Carbon Released. First, for combustion by fuel, the mass of fuel as dry
matter is converted to carbon units, and second, an efficiency of burn is assigned. The
general equation for estimating CO2 emissions is:
Emissions from Biomass Fuel (by type) = Total Fuel Consumed (10 mt dm)
X Carbon Fraction X Fraction Oxidized (combustion efficiency)
For emissions from charcoal production a single factor is applied based on total carbon
released in charcoal production. One estimate indicates that the amount of carbon
released during charcoal production roughly equals the carbon in charcoal consumed. In
other words, roughly half of the original carbon in the wood is lost during charcoal
Emissions inventory developers are encouraged to provide estimates of uncertainty
along with these best estimate values where possible, or to provide some expression of
the level of confidence associated with various point estimates provided in the inventory.
Procedures for reporting this uncertainty or confidence information are discussed in
Volume I: Reporting Instructions.
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manufacture.25 Therefore, to account for this release, as a default value, one could simply
use the estimated release of carbon from charcoal burning as the estimate of carbon
released from charcoal production.
Part 2: Non-CO2 Trace Gas Emissions. Once the carbon released from biomass fuel
burning has been estimated, the emissions of CH4, CO, N2O, and NOX can be calculated
as follows.26 The amount of carbon released due to burning is multiplied by the emission
ratios of CH« and CO relative to total carbon emissions to yield total emissions of CH4
and CO (each expressed in units of C). The emissions of CH, and CO are multiplied by
16/12 and 28/12, respectively, to convert to full molecular weights.
Box I
FUEL CONSUMPTION ACCOUNTING
For traditional biomass fuel use, direct consumption statistics are often incomplete or
unavailable. Large amounts of traditional fuels used may not be traded through normal
commercial fuel markets. Instead they may be traded in the informal sector or directly
gathered by consumers. In this situation, it is often considered more accurate to base fuel
consumption estimates on surveys of household and small commercial fuel use patterns. In
many countries, such surveys have produced rules of thumb concerning per capita use of
traditional fuels (charcoal, fuelwood, dung, etc.). Survey results may be available as national
averages, or broken down between rural and urban populations, or by region within
countries. Users of this methodology may determine this to be the most reliable approach
for all or part of biomass fuel consumption. In that case, available values for per capita
consumption of biomass fuels should be documented and multiplied by population to
obtain total consumption values by fuel type.
To calculate emissions of N2O and NOX, first the total carbon released is multiplied by the
estimated N/C ratio of the fuel by weight (default values for biomass fuels are provided in
table A) to yield the total amount of nitrogen (N) released. The total N released is then
multiplied by the ratios of emissions of N2O and NOX relative to the N content of the fuel
to yield emissions of N2O and NOX (expressed in units of N). To convert to full molecular
weights, the emissions of N2O and NOX are multiplied by 44/28 and 30/14, respectively.27
75 Delmas, 1993. Based on measurements indicating that 26% by weight of input
fuelwood (dm) was produced as charcoal, with 87% carbon. This results in about 1/2 the
carbon in original biomass remaining in charcoal, with 1/2 released during charcoal
production. Hall (1993) suggests much different values assuming that only 12.5% of dry
biomass in original wood is produced as charcoal and that carbon content of traditionally
produced charcoal ranges from 60-80%. This would indicate that less than 25% of carbon
in original dry biomass is incorporated into charcoal produced. Thus, 75+% of carbon is
released in production. Additional work is needed to resolve these differences.
26
From Crutzen and Andreae, 1990.
27 There is an inconsistancy in the methodology in the treatment of the full molecular
weight of NO*. In fossil energy and industry discussions NOX is expressed as though all of
the N were in the form of NOj. In biomass burning literature, (e.g., Crutzen and Andreae,
1990) NOX is often discussed as though the emissions were in the form of NO.
Therefore, the biomass burning discussions in these Guidelines convert NOX-N to full
weight using the conversion factor (30/14) for NO. All other references to NOX are
based on the full weight of NO2 (i.e., the conversion factor from NOX-N would be 46/14).
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The non-CO2 trace gas emissions from burning calculation is summarized as follows:
CH4 Emissions = (carbon released) x (emission ratio) x 16/12
CO Emissions = (carbon released) x (emission rai:io) x 28/12
N2O Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 44/28
NOX Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 30/14
TABLE 1-19
BIOMASS FUELS DEFAULT DATA
Fuel Type
Fuelwood
Charcoal Consumption
Charcoal Production
Dung
Agricultural Residues
Carbon Fraction
0.45-0.5
0.87
0.45-0.5
0.36-0.42
0.4-0.48
Nitrogen-Carbon (N/C)
Ratioz
0.01
}
0.01
)
0.01-0.02
Combustion Efficiency
87
88
30
85
88
Sources: Delmas and Ahuja, 1993; 2 Crutzen and Andreae, 1990."' Delmas, I993b
These are general default values for crop residues. Specific carbon fraction and N/C ration data for
residues from individual crops are provided in the agricultural burning discussion in chapter 4. If
consumption data on biomass fuels are specific by crop type, these crop specific values can be used.
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Box 2
TRACE GAS EMISSIONS RATIOS
Emissions of CHt, CO, N2O and NOX from burning of traditional biomass fuels (and other types of
blomass burning associated with forest clearing and agriculture) are generally estimated by first
calculating the total carbon emitted (mostly as CO2) from combustion and applying a series of ratios.
First, a ratio of nitrogen to carbon in fuel is applied to estimate total nitrogen released. Then specific
ratios of CH< and CO to total carbon, and N2O and NOX to total nitrogen are used to estimate
these trace gas emissions. Crutzen and Andreae (1990) provided a range of values considered
representative of biomass burning generally.
Compound Ratios
CH< 0.01 (0.007-0.013)
CO 0.10 (0.075-O.I25)
N2O 0.007 (0.005 - 0.009)
NO* 0.121 (0.094-0.148)
Source: Crutzen and Andreae. 1990
More recently, Lacaux et al.(!993) have suggested a lower emissions ratio range for CO: 0.06 (0.04-
0.08).
Delmas (I993a) and Delmas and Ahuja (1993) have developed more specific ratios for CH, from
different types of biomass burning, including values for specific biomass fuels and open burning from
forest clearing and agriculture. Delmas and Ahuja, 1993, also provide a ratio for estimating methane
from the charcoal production process. This value is much higher than the Crutzen and Andreae
range for relatively open burning, and should be used to estimate what could be a significant
methane source in many countries. Fuel values are shown below.
Fuel Type
Fuelwood
Ratio - C-CH^total C
0.012 (0.009-0.015)
0.005 (0.003-0.007)
0.017
0.005 (0.0014-0.0085)
0.063 (0.04-0.09)
Agricultural Residues
Dung
Charcoal combustion
Charcoal production
These more recent values are considered more accurate than the Crutzen and Andreae ranges
where available for individual components of biomass burning.
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1.7 Greenhouse Gas Emissions from Mobile
Combustion
I .7. I Overview
This section discusses emissions of greenhouse gases from mobile sources, including
carbon dioxide (CC>2), carbon monoxide (CO), nitrogen oxides (NOX), methane (CH4),
nitrous oxide (N2O), and non-methane volatile organic compounds (NMVOCs). Emissions
from mobile sources are most easily estimated by major transport activity, i.e., road, air,
rail, and ships. Several major fuel types need to be considered, including gasoline, diesel, jet
fuel, aviation fuel, natural gas, liquified petroleum gas, and residual fuel oil. Road transport
accounts for the majority of mobile source fuel consumption (e.g., 82% in 1988 for the
OECD), followed by air transport (about 13%). This suggests that the primary emphasis in
developing emission inventories should be placed on road vehicles, followed by aircraft.
As a one of the major energy consuming sectors, globally and in most countries, transport
is a significant source of CO2 emissions. As discussed previously, these emissions should
be accounted for in the "top-down" IPCC Reference Approach to CO2 from fuel
combustion described earlier. However, it is also useful to develop more detailed
information about the role of specific end use activities, such as mobile sources, in causing
CO2 emissions. National experts are therefore encourage to also calculate CO2 emissions
at a more detailed level (as described in this section for transport) and to aggregated these
estimates up for comparison with the Reference Method. Therefore, the discussion in this
section includes information needed to estimate CO2 emissions as well as other gases at a
detailed level.
Motor vehicles release a large portion of total anthropogenic NOX emissions. These
emissions are related to air-fuel mixes and combustion temperatures, as well as pollution
control equipment. For uncontrolled vehicles, NOX emissions from diesel-fueled vehicles
are generally lower than from gasoline-fueled vehicles and lower from heavy duty vehicles
(HDV) on an emissions per ton/kilometer basis than light duty vehicles (LDV). HDV still
contribute significant emissions and are more difficult to control than light duty vehicles.
The majority of CO emissions from fuel combustion comes from motor vehicles. CO
emissions are a function of the efficiency of combustion and post-combustion emission
controls. Emissions are highest when air-fuel mixtures are "rich," with less oxygen than
required for complete combustion. This occurs especially in idle, low speed, and cold start
conditions in spark ignition engines.
CH4 and NMVOC emissions are a function of the methane content of the motor fuel, the
amount of hydrocarbons passing unburnt through the engine, and any post-combustion
control of hydrocarbon emissions, such as use of catalytic converters. In uncontrolled
engines, emissions of unburned HC, including CH4, are lowest when the combustion
conditions (quantity of hydrogen, carbon, and oxygen present) are exactly right for
complete combustion. They are generally highest in low speed and engine idle conditions.
Poorly tuned engines (typical of many developing countries) may have particularly high
output of total HC, including CH4. Emissions are also dependent on engine type, emission
controls and the fuel combusted.
N2O emissions from vehicles have only recently been studied in detail. Emissions from this
source are still thought to be small relative to total anthropogenic emissions. Emission
rates are, however, substantially higher when some emission control technology
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(especially catalysts on road vehicles) are used, and this could cause the total emissions to
grow in the future.
Emission control policies adopted in many OECD member countries, will substantially
reduce CO, NMVOC, CH4, and NOX emissions per automobile in these countries, but
may cause N2O emissions to increase.
Organization of this section
The next sub-section provides a discussion of the basic inventory methodology
recommended for this mobile source emissions. Following illustrative information on
emission factors is provided. This is summarized from a 1991 document, but useful in
illustrating the range of mobile source types of concern and rates of emissions of various
gases. Subsequently, some more recent information, developed by expert advisory groups
to the IPCC/OECD programme, is provided on two direct GHGs - N2O and CH4. A short
subsection discusses indirect GHGs - NOX, CO and NMVOC. No new work has been
done within the IPCC/OECD programme on these gases, but considerable detailed
information is available from other national and international emissions inventory
programmes. Some key references to this body of technical work are provided. A final
sub-section suggests some priorities for future work on GHG emissions from mobile
sources.
1.7.2 Basic Inventory Method:
Emissions
Mobile Source
Estimation of mobile source emissions is a very complex undertaking that requires
consideration of many parameters, including information on such factors as:
• transport class
• fuel consumed
• operating characteristics
• emission controls
• maintenance procedures
• fleet age
• other factors
The need for data on several parameters and the wide variety of conditions that can affect
the performance of each category of mobile sources makes it very difficult to generalize
the emission characteristics in this area. This area is so complex that is difficult even for
countries with extensive experience to develop highly-precise emission inventories.
Nevertheless, a basic emission estimation methodology was developed and included in the
in the report of the OECD Experts Meeting in which was circulated to IPCC national
experts as a starting point for the methods development programme (OiECD, 1991). This
basic discussion is still useful and repeated with few changes in this section. The method is
consistent with the calculations carried out in those countries which already have detailed
mobile source emissions inventory data bases. It is presented in a somewhat simplified,
aggregate form to assist countries, with limited experience estimating emissions from
mobile sources, in getting started.
In order to develop estimates for greenhouse gas emissions from mobile sources, basic
information is required on the types of fuels consumed in the transport sector, the
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combustion technologies that are used to consume the fuels, operating conditions during
combustion, and the extent of emission control technologies employed during and after
combustion. The basic calculation for estimating these emissions can be expressed as:
Emissions = £ (EFab<: x Activityabc)
where: EF = emissions factor
Activity = amount of energy consumed or distance traveled for a given mobile
source activity
a = fuel type (diesel, gasoline, LPG, bunker, etc.)
b = vehicle type (e.g., passenger, light duty or heavy duty for road vehicles)
c = emission control
Based on this formula, the following basic steps are required to estimate mobile source
emissions:
• Determine the amount of energy consumed by fuel type for all mobile sources using
national data or, as an alternative, IEA or UN international data sources (all values
should be reported in gigajoules).
• For each fuel type, determine the amount of energy that is consumed by each vehicle
type, e.g., light-duty gasoline vehicles, etc. (all units are in gigajoules). If distance
traveled is the basis, determine the total distance traveled by each vehicle type. In
this case; the energy consumption associated with these distance travelled figures
should be calculated and aggregated by fuel for comparison with national energy
balance figures. If necessary, further subdivide each vehicle type into uncontrolled and
key classes of emission control technology.
• Multiply the amount of energy consumed, or the distance traveled, by each vehicle,
or vehicle/control technology, category by the appropriate emission factor for that
category. Data presented in the next section (Illustrative Emission Factors) can be
used as a starting point. However, national experts are encouraged to consult other
data sources referenced in this chapter and locally available before determining
appropriate factors for a particular country.
• Emissions can be -summed across all fuel and technology type categories, including for
all levels of emission control, to determine total emissions from mobile source-
related activities.
Regardless of the specific methodology that is used to determine emissions, it is important
to remember that there is a substantial amount of uncertainty surrounding the estimation
of emissions from mobile sources. National experts are encouraged to provide indications
of uncertainty in their estimates as described in Volume I: Reporting Instructions.
Data Sources
Emission factors (such as those in Tables 2-20 through 2-31) can only be used if energy
consumption can be adequately characterized by the fuel and vehicle/control technology
categories. For example, for transportation needs, information is required on the
percentage of light-duty versus heavy-duty vehicles by fuel type (gasoline- versus diesel-
fueled) and the extent of emission controls for each category. There is no single data
source that comprehensively provides all relevant information. There are several sources,
however, that can help to determine this information.
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For example, activity data on vehicle fleet characteristics will be needed. There are two
main international sources of data available on transport, both of which are recommended
to be used as the international point of reference. For road transport, both the UNECE
(Annual Bulletin of Transport Statistics for Europe, e.g., 1989, Geneva) and the International
Road Federation (World Road Statistics, e.g., 1990, Washington, D.C.) provide annual data
on various aspects of vehicle fleets and traffic conditions. While the former is more
detailed for the various modes of transport, it is available for Europe only. The latter is
worldwide in coverage but provides only a few key statistics. These include data on
vehicles in use, road traffic, motor fuels, and data on the flows of vehicles produced and
sold (imports and exports) among countries. Individual regional and national data sources
can also be used and may in fact be more disaggregate and up-to-date than these
international data sources.
Information on energy consumption in the transport sector is also needed to determine
emissions. As discussed earlier, the most reliable sources for international energy statistics
are the International Energy Agency and the UN Statistical Division, where data on
transport activities are detailed by fuel type and basic transport mode. These data are
available for most mobile source energy consumption in the world. National energy data
sources may be preferable to these international sources but the reporting definitions and
conventions of the IEA energy balance should be used to summarise these energy data.
This provides a check for internal consistency of the energy assumptions used to estimate
emissions from mobile source combustion.
1.7.3 Illustrative Emission Factors
This section summarizes results of a detailed analysis of mobile source emission factors for
gases contributing to global warming which was carried out in 1991. A more detailed
discussion of the methods and assumptions used can be found in OECD 1991. It has not
been possible, in the preparation of this Reference Manual, to update this earlier analysis in
a systematic way. The results are still useful in illustrating the range of emission rates from
different types of vehicles and how those rates vary by vintage and control technology. It is
also very useful in providing side by side expressions of the same emission factors in three
different forms. Therefore, the results are summarized in this section, as originally
presented, for illustrative purposes.
However, for actual calculations of national emissions, users are encouraged to also
consult a range of more recent and more detailed information sources. Particularly for
indirect GHGs, more comprehensive and up-to-data sources as well are available based on
programmes outside the GHG emissions area. More recent data on some gases, and
references to other detailed data sources are provided in the gas by gas subsections later
in this section.
Emission factor estimates are presented for CO2, CO, NOX, N2O, methane, and non-
methane VOCs for several classes of highway vehicles, railway locomotives, ships and
boats, farm and construction equipment, and aircraft. All emission factor data are stated
on the basis of full molecular weight of the respective pollutant; NOX factors are stated as
NOZ.
Road Vehicles - Conventional Fuels
Technical Approach
The emissions estimates for NOX, CO, methane, and NMVOC from highway vehicles are
based on the U.S. EPA's MOBILE4 model (EPA, 1989). MOBILE4 calculates exhaust
emission factors for U.S. vehicles using gasoline and diesel fuel, based on the year in which
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they were manufactured. For gasoline vehicles, it also calculates VOC emissions due to
evaporative, running, and refueling losses (VOC emissions from diesel vehicles due to
these causes are negligible).
Assumptions
Specific U.S. model years were used to represent the different possible control
technologies. Emissions were calculated for a five year old vehicle of each type (approxi-
mately halfway through their useful lives). Similarly, emissions estimates for advanced-
technology vehicles were based on 1990 model vehicles, calculated in 1995. Table 1-20
shows the correspondence between technology types and the U.S. model years used to
represent them in the model. The conditions chosen for the modeling were "typical"
values of 75 °F, with a diurnal range from 60 to 85 °F (24±8 °C), and Reid vapor pressure
of gasoline at 9.0 PSI (62 kPa). Average speed was taken as the MOBILE4 default of 31.4
km/hr, typical of uncongested urban driving. An effective inspection/ maintenance and anti-
tampering program, was assumed to be in place.
Since MOBILE4 does not estimate N2O or CO2 emissions, these were estimated
separately. CO2 emissions were calculated from typical fuel economy data for U.S. vehicles
for representative model years in which the technology was used together with the
average carbon content for each type of fuel.28 Fuel economy estimates for heavy-duty
gasoline and diesel trucks, are from Machiele, (1988), and from Weaver and Turner (1991)
for other vehicle classes. The specific fuel economy value assumed for U.S. vehicles in each
case is shown in the tables. The estimated vehicle fuel economies were also used to
calculate fuel-specific (g/kg fuel) and energy-specific (g/MJ)2' emission factors for all of the
pollutants. The CO2 factors on an energy input (g/MJ) wen; taken from Grubb (1989); all
other emission factors are from Turner and Weaver (1991). Since emissions and fuel con-
sumption tend to vary in parallel (vehicles and operating modes causing high emission rates
also tend to result in high fuel consumption, and vice versa), these energy-specific emission
factors are expected to be more generally applicable than the factors in grams/km.
N2O emissions factors were developed based on the limited available test data. Prigent and
Soete (1989), Dasch (1991), Ford (1989-1991), and Warner-Selph and Smith (1991) gave
N2O emissions for light-duty gasoline vehicles which were divided into four groups of
technologies: uncontrolled, oxidation catalyst, early three-way catalyst, and modern three-
way catalyst technologies. For light-duty gasoline trucks and motorcycles, fuel-specific N2O
emissions were assumed to be the same as for the corresponding passenger car
technology. No data on N2O emissions from heavy-duty gasoline trucks were available, but
they were assumed to emit at the same rate per unit of fuel burned as passenger cars
having similar technology. However, since these trucks undergo a heavier duty cycle, and
experience fewer cold-starts, it was considered more appropriate to use N2O emission
factors based on the U.S. highway fuel economy test (HFFf) rather than the cold-start FTP
procedure. Fuel-specific N2O emissions for passenger cars in the HFET procedure were
obtained from the same data sources listed above. Dietzmann, Parness, and Bradow (1980)
reported N2O emission factors for heavy-duty diesel vehicles. No N2O emissions data
28As is the convention throughout these Guidelines, CO2 emissions are calculated to
include the carbon emitted as CO and as VOC. The rationale for this approach is
explained in the Introduction.
29 MJ=megajoule=l06 joules. Energy-specific emission factors were based on the lower
heating value of the fuel in each case.
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were available for light-duty diesel vehicles, but they were assumed to have the same fuel-
specific emission rates as for diesel passenger cars.
Results of this analysis are presented by categories defined by the U.S. EPA as listed below:
Table 1-21: Light-duty gasoline passenger cars - vehicles with rated gross weight less
than 8,500 Ib (3,855 kg) designed primarily to carry 12 or fewer passengers. Five levels of
gasoline-vehicle control technology are shown:
I Uncontrolled (still typical of most vehicles around the world)
2 Non-catalyst emission controls - including modifications to ignition timing and air-fuel
ratio to reduce emissions, exhaust gas recirculation (EGR), and air injection into the
exhaust manifold.
3 Oxidation catalyst systems normally including many of the same techniques, plus a
two-way catalytic converter to oxidize HC and CO.
4 "Early" three-way catalyst results representative of vehicles sold in the U.S. in the
early to mid '80s, which were mostly equipped with carburetors having electronic
"trim".
5 "Advanced" three-way catalyst values based on current U.S. technology vehicles, using
electronic fuel injection under computer control.
Table 1-22: Light-duty gasoline trucks - vehicles having rated gross vehicle weight less
than 8,500 Ib (3,855 kg), and which are designed primarily for transportation of cargo or
more than 11 passengers at a time, or which are equipped with special features for off-
road operation. They include most pickup trucks, passenger and cargo vans, four-wheel
drive vehicles, and derivatives of these. The technology classifications used are the same as
those for gasoline passenger vehicles.
Table 1-23: Heavy-duty gasoline vehicles - manufacturer's gross vehicle weight rating
exceeding 8,500 Ib (3,855 kg). This includes large pickups, vans and specialized trucks using
pickup and van chassis, as well as the larger "true" heavy-duty trucks, which have gross
vehicle weights of eight short tons or more. In the U.S., the large pickups and vans in this
category greatly outnumber the heavier trucks, so that the emission factors calculated by
MOBILE4, and fuel economy estimates, are more representative of these vehicles. Three
levels of emission control technology are shown:
I Uncontrolled.
2 Non-catalyst emission controls, including control of ignition timing and air-fuel ratio
to minimize emissions, EGR, and air injection into the exhaust manifold to reduce
HC and CO emissions.
3 Three-way catalyst technology presently used in the U.S. includes electronically-
controlled fuel injection, EGR, air injection, and electronic control of ignition timing,
as well as the catalyst itself.
Table 1-24: Light-duty diesel passenger cars - a diesel passenger car designed primarily
to carry fewer than 12 passengers, with gross vehicle weight less than 8,500 Ib (3,855 kg).
Three levels of emission control technology are shown:
I Uncontrolled
2 Moderate emissions control (achieved by changes in injection timing and combustion
system design).
3 Advanced emissions control utilizing modern electronic control of the fuel injection
system, and exhaust gas recirculation.
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Table I-2S: Light-duty diesel trucks - light-duty diesel trucks defined like their gasoline
counterparts, including weight, utility, and off-road operation features. The technology
classifications are the same as those for diesel passenger car's.
Table 1-26: Heavy-duty diesel vehicles - the classification for heavy-duty diesel vehicles
is the same as for gasoline vehicles, but the characteristics of the U.S. vehicle fleets are
different. Heavy-duty diesel vehicles are primarily large trucks, with gross vehicle weight
ratings of 10 to 40 tons. Therefore, the MOBILE4 emission factors are more
representative of large trucks (and buses) than the smaller pickup and van-type vehicles,
and this is reflected in the fuel economy estimates. Three levels of control are presented:
I Uncontrolled.
2 Moderate control (typical of 1 983 U.S. engines).
3 Advanced control (for engines meeting U.S. 1 99 1 emissions standards)
Table 1-27: Motorcycles - The MOBILE4 emission factors for these vehicles are based
on the U.S. motorcycle population, which probably reflects higher average power ratings
and fuel consumption than for many developing countries. The factors for uncontrolled
motorcycles include a mixture of two-stroke and four-stroke engines, with the VOC
emissions due primarily to the two-strokes, and the NOX to the four-stroke engines. The
factors for motorcycles with non-catalyst emission controls reflect four-stroke engines
only, as U.S. emission control regulations have essentially eliminated two-stroke engines
from the market.
Emission factors for certain greenhouse gas emissions from road vehicles can be
developed using the MOBILE4 computer model.' This model was the basis for most of
the emission factors presented in Tables 2-2 1 to 2-27, and can be used to calculate
average emission rates for any selected calendar year (from 1 960 to 2020) essentially by
aging the fleet and weighting the emission factors by the shares of distance travelled by
vehicles of various ages. The emission factors are estimated as a function of several
parameters, including: vehicle type; model year (technology); vehicle age and accumulated
mileage; percent of driving in cold start, hot start or stabilized conditions;
average speed; ambient temperatures; fuel volatility; and tampering rates with emission
control systems. Since *these variables can be manipulated by the user, the conditions can
be altered to reflect conditions in a variety of geographic regions and regulatory situations.
MOBILE4 calculates emission factors for total and non-methane hydrocarbons (HC and
NMHC), NOX and CO, and two fuels (gasoline and diesel). The emissions performance in
MOBILE4 for vehicles under various conditions is estimated based on years of extensive
testing of vehicles in use in the United States. The user can specify input data for the
particular region or country, and emission factors that are tailored to that particular
region will be estimated.
Several notes of caution need to be given on the use of MOBILE4 for development of
greenhouse gas emission factors. First, the pollutant coverage is incomplete (including only
NOX, CO, VOC, and NMVOCs with methane as a calculated result of the difference
between NMVOC and VOC).
Second, alternative fuel vehicles are not yet incorporated into the model. Supplementary
information must therefore be used to develop these factors should the fuel mix in
transport activities require them. Any assumptions used to build these factors should be as
comparable as possible with those for conventional motor fuels.
PART 2
1.71
-------
EMISSIONS FROM ENERGY
Third, special attention must be given to the definition of MOBILE4 fleet assumptions to
include two-stroke engines in order to make the results useful to many non-OECD
nations. A substantial portion of the automobile fleets in countries of Eastern Europe and
perhaps in other parts of the non-OECD world are two-stroke engines. These engine
types have a substantially different emission profile than the standard (Otto) gasoline or
four-stroke engine which is predominant in the OECD. Fleet data on two-stroke engine
vehicle stocks will therefore be a first priority in understanding the necessary
modifications to MOBILE4 emission factor estimates, which have been largely developed
for OECD countries and regions.
1 The MOBILE4 Model and its User's Guide can be obtained from the U.S. National Technical
Information Service, U.S. Department of Commerce, Springfield, Virginia, 22161, United States.
TABLE 1-20
EMISSION CONTROL TECHNOLOGY TYPES AND U.S. VEHICLE MODEL
YEARS USED To REPRESENT THEM
Technology
Model Year
Gasoline Passenger Cars and Light Trucks
Uncontrolled
Non-catalyst controls
Oxidation catalyst
Early three-way catalyst
Advanced three-way catalyst
1963
1972
1978
1983
1990
Heavy-Duty Gasoline Vehicles
Uncontrolled
Non-catalyst control
Three-way catalyst
1968
1983
1991
Diesel Passenger Cars and Light Trucks
Uncontrolled
Moderate control
Advanced control
1978
1983
1990
Heavy Duty Diesel Vehicles
Uncontrolled
Moderate Control
Advanced control
1968
1983
1991
Motorcycles
Uncontrolled
Non-catalyst controls
1972
1990
1.72
-------
EMISSIONS FROM ENERGY
TABLE 1-21
ESTIMATED EMISSIONS FACTORS FOR GASOLINE PASSENGER CARS
EMISSIONS
NOx
CH4
NMVOC
CO
N20
C02
Advanced Three- Way Catalyst Control; Assumed Fuel Economy: 1 1.9 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
0.50
0.50
7.94
0.18
0.020
0.020
0.32
0.0072
0.66
0.26
0.11
0.15
0.14
10.48
0.24
3.14
3.14
49.87
1.13
0.019
0.019
0.30
0.0069
200
200
3172
69.3
Early Three-Way Catalyst; Assumed Fuel Economy: 9.4 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
0.52
0.52
6.49
0.15
0.04
0.04
0
0
0
0.50
0.0113
0.67
0.25
0.12
0.16
0.14
8.36
0.19
3.12
3.12
38.93
0.88
0.046
0.046
0.57
0.0130
254
254
3172
69.3
Oxidation Catalyst; Assumed Fuel Economy: 6.0 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
1.59
1.59
12.63
0.29
0.09
0.09
0
0
0
0.71
0.0162
1.75
1.13
0.19
0.21
0.22
13.90
0.32
12.98
12.98
103.07
2.34
0.027
0.027
0.21
0.0049
399
399
3172
69.3
Non-Catalyst Control; Assumed Fuel Economy: 6.0 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
1.97
1.97
15.64
0.36
0.174
0.174
0
0
0
1.38
0.0314
3.15
2.14
0.45
0.29
0.27
25.01
0.57
23.8
23.8
188.99
4.30
0.005
0.005
0.04
0.0009
399
399
3172
69.3
Uncontrolled; Assumed Fuel Economy: 6.0 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
2.14
2.14
16.99
0.39
0.174
0.174
0
0
0
1.38
0.0314
6.33
4.36
1.37
0.28
0.32
50.27
1.14
40.62
40.62
322.56
7.33
0.005
0.005
0.04
0.0009
399
399
3172
69.3
PART 2
1.73
-------
EMISSIONS FROM ENERGY
TABLE 1-22
ESTIMATED EMISSION FACTORS FOR LIGHT-DUTY GASOLINE TRUCKS.
EMISSIONS
NOx
CH4
NMVOC
CO
N2O
Advanced Three-Way Catalyst Control; Assumed Fuel Economy: 9.4 km/I
otal - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
0.67
0.67
8.36
0.19
0.04
0.04
0
0.50
0.0113
0.75
0.4
O.I
0.2
0.04
9.36
0.21
4.68
4.68
58.40
1.33
0.024
0.024
0.30
0.0068
C02
254
254
3172
69.3
Early Three-Way Catalyst; Assumed Fuel Economy: 6.8 krn/l
"otal - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
1.00
1.00
9.08
0.21
Oaa.07
0.07
0
0
0
0.64
0.0144
1.17
0.78
0.13
0.21
0.04
10.62
0.24
9.23
9.23
83.76
1.90
0.063
0.063
0.57
0.0130
350
350
3172
69.3
Oxidation Catalyst; Assumed Fuel Economy: 5.1 km/I
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
Non-Catalyst; Assumed
Fuel Economy: 5.1 km/I
1.62
1.62
11.03
0.25
Total - g/km
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g/MJ
Uncontrolled; Assumed
Fuel Economy: 5.1 km/I
2.82
2.82
19.19
0.44
0.09
0.09
0
0
0
0.61
0.0139
1.95
1.22
0.22
0.29
0.22
13.27
0.30
12.15
12.15
82.70
1.88
0.031
0.031
0.21
0.0048
466
466
3172
69.3
0.174
0.174
0
0
0
1.18
0.0269
Total
Exhaust
Evaporative
Refueling
Running loss
g/kg fuel
g>MJ
2.63
2.63
17.90
0.41
0.174
0.174
0
0
0
1.18
0.0269
4.55
3.01
0.9
0.34
0.29
30.97
0.70
28.81
28.81
196.09
4.46
0.006
0.006
0.04
0.0009
466
466
3172
69.3
8.54
4.98
2.92
0.32
0.32
58.13
1.32
44.55
44.55
303.23
6.89
0.006
0.006
0.04
0.0009
466
466
3172
69.3
1.74
-------
EMISSIONS FROM ENERGY
TABLE 1-23
ESTIMATED EMISSION FACTORS FOR HEAVY-DUTY GASOLINE VEHICLES
EMISSIONS
NOx
CH4 | NMVOC
CO
N2
-------
EMISSIONS FROM ENERGY
TABLE 1-24
ESTIMATED EMISSION FACTORS FOR DIESEL PASSENGER CARS
EMISSIONS
NOx
CH4
NMVOC
CO
N20
C02
Advanced Control; Assumed Fuel Economy: 1 0.6 km/I
Total - g/km
g/kg fuel
g/MJ
0.65
8.04
0.19
0.01
0.12
0.003
0.29
3.59
0.084
0.86
10.64
0.25
0.007
0.08
0.0019
258
3188
73.3
Moderate Control; Assumed Fuel Economy: 6.8 km/I *
Total - g/km
g/kg fuel
g/MJ
0.93
7.36
0.17
0.01
0.08
0.002
0.29
2.30
0.054
0.86
6.81
0.16
0.010
0.08
0.0019
403
3188
73.3
Uncontrolled; Assumed Fuel Economy: 5.1 km/I
Total - g/km
g/kg fuel
g/MJ
1.02
6.05
0.14
0.01
0.06
0.001
0.52
3.09
0.073
1.06
6.29
0.15
0.014
0.08
0.0019
537
3188
73.3
TABLE 1-25
ESTIMATED EMISSION FACTORS FOR LIGHT-DUTY DIESEL TRUCKS
EMISSIONS
NOx
CH4
NMVOC
CO
N2O
C02
Advanced Control; Assumed Fuel Economy: 7.7 km/I
Total - g/km
g/kg fuel
g/MJ
0.76
6.77
0.16
0.01
0.09
0.0021
0.42
3.74
0.09
0.98
8.73
0.21
0.009
0.08
0.0019
358
3188
73.3.
Moderate Control; Assumed Fuel Economy: 5. 1 km/I
Total - g/km
g/kg fuel
g/MJ
1.04
6.17
0.15
0.01
0.06
0.0014
0.42
2.49
0.06
0.98
5.82
0.14
0.014
0.08
0.0019
537
3188
73.3
Uncontrolled; Assumed Fuel Economy: 4.3 km/I
Total - g/km
g/kg fuel
g/MJ
I.4S
7.17
0.17
0.02
0.10
0.00
0.83
4.11
0.10
1.61
7.96
0.19
0.017
0.08
0.0019
559
3188
73.3
1.76
-------
EMISSIONS FROM ENERGY
TABLE 1-26
ESTIMATED EMISSION FACTORS FOR HEAVY DUTY DIESEL VEHICLES
EMISSIONS
NOx
CH4
NMVOC
CO
N2O
C02
Advanced Control; Assumed Fuel Economy: 2.8 km/I
Total - g/km
g/kg fuel
g/MJ
Total - g/km
g/kg fuel
g/MJ
5.01
16.27
0.38
0.06
0.19
0.005
1.26
4.09
0.10
6.8
22.09
0.52
0.025
0.08
0.0019
982
3188
73.3
Moderate Control; Assumed Fuel Economy: 2.8 km/I
11.94
38.41
0.90
0.07
0.23
0.01
1.7
5.47
0.13
8.28
26.64
0.63
0.025
0.08
0.0019
991
3188
73.3
Uncontrolled; Assumed Fuel Economy: 2.2 km/I
Total - g/km
g/kg fuel
g/MJ
16.79
42.86
1.01
O.I
0.26
0.01
2.99
7.63
0.18
8.54
21.80
0.51
0.031
0.08
0.0019
1249
3188
73.3
TABLE 1-27
ESTIMATED EMISSION FACTORS FOR MOTORCYCLES
EMISSIONS
NOx
CH4
NMVOC
CO
N2O
C02
Non-catalytic Control; Assumed Fuel Economy: 1 4.9 km/I
Total - g/km
g/kg fuel
g/MJ
0.53
10.52
0.24
0.15
2.98
0.07
2.2
42.9
0.97
13.2
261
5.9
0.002
0.04
0.0009
160
3188
69.3
Uncontrolled; Assumed Fuel Economy: 1 2.8 km/I
Total - g/km
g/kg fuel
g/MJ
0.19
3.23
0.07
0.329
5.60
0.13
6.5
III
2.5
23.8
405
9.2
0.002
0.04
0.0009
186
3172
69.3
Road Vehicles - Alternative Fuels
Alternative motor vehicle fuels such as natural gas, LP gas, methanol, and ethanol are
presently being used in a limited way, and are the subjects of a great deal of research and
development effort aimed at increasing their usage in the future. This section presents
some preliminary estimates of the emissions to be expected from vehicles using these
fuels, based on fuel properties and the limited emissions data available.30
Natural gas
Because natural gas is mostly methane, natural gas vehicles (NGVs) have lower exhaust
NMVOC emissions than gasoline vehicles, but higher emissions of methane. There are no
evaporative or running-loss emissions, refueling emissions and cold-start emissions are
Actual emission levels from these vehicles may be very different, and further testing is
needed to confirm these estimates.
PART 2
1.77
-------
EMISSIONS FROM ENERGY
low, and have leaner fuel-air ratios. These conditions reduces both NMVOC and CO
emissions relative to gasoline vehicles. CO2 emissions from NGVs will be lower than for
gasoline vehicles, since natural gas has a lower carbon content per unit of energy. It
possible to attain increased efficiency by increasing the compression ratio. Optimized
heavy-duty NGV engines can approach diesel efficiency levels. NOX emissions from
uncontrolled NGVs may be higher or lower than comparable gasoline vehicles, depending
on the engine technology. NGV NOX emissions are more difficult to control using three-
way catalysts. N2O emissions from NGVs were not included.
Table 1-28 shows three types of NGVs: passenger cars, gasoline-type heavy-duty vehicles,
and diesel-type heavy-duty vehicles.31 Two sets of emission factors are ishown for each:
uncontrolled (typical of a simple natural gas conversion, without catalytic converter or
optimization for emissions) and advanced control (reflecting an engine and catalytic
converter factory-produced and optimized for natural gas). The estimates for the
passenger car and gasoline-type heavy duty vehicle are based on a gasoline-type engine,
converted to use natural gas. For the uncontrolled vehicles, no changes in the engine are
assumed beyond the fitting of a natural gas mixer and modified spark timing such that the
efficiency would be the same. For the vehicles with advanced control, a higher
compression ratio is assumed to give 15% better fuel efficiency.
For the diesel-type heavy-duty vehicles, the engine assumed is a diesel-type engine,
converted to lean. Otto-cycle operation using natural gas. The uncontrolled case reflects
no further optimization beyond the conversion, while the controlled case includes
extensive combustion optimization for NOX control and an oxidation catalytic converter.
LPgas
LPG is primarily propane (or a propane/butane mixture) rather than methane which
affects the composition of exhaust VOC emissions, but otherwise it similar to NG.
Evaporative and refueling emissions are virtually zero, and CO and exhaust NMVOC
emissions are usually lower than gasoline vehicles. The CO2 emissions should be
somewhat lower than gasoline, due to the lower carbon-energy ratio, and the higher
octane allows some increase in efficiency, although less than for natural gas. NOX
emissions from LPG vehicles tend to be higher than for gasoline, but can also be
controlled using three-way catalysts. N2O emissions were not included.
Table 1-29 shows four categories of LPG vehicles. The engines and technologies
considered are the same as those for natural gas, except that the lean, diesel-derived
natural gas engine with propane is not considered.
Methanol and ethanol. The two alcohols have similar properties, and are discussed together.
Development efforts have focussed primarily on mixtures of alcohols with gasoline, in
flexible fuel vehicles, capable of running on any combination of gasoline and up to 85%
methanol or ethanol. Engines and emission control systems are similar to those for
advanced-technology gasoline vehicles, and the overall energy efficiency and emissions
properties are similar. Table 2-30 shows estimated emissions for a vehicle of this type
using M85 (85% methanol/15% gasoline) fuel. Also shown are some rough emissions
estimates for heavy-duty vehicles equipped with methanol or ethanol engines.
3lThe emissions considered are only those of the vehicle itself-additional emissions due
to, e.g., compression or liquefaction of gas for storage on the vehicle, leakage from
pipelines, etc. are not included, nor are the potential emissions credits due to, e.g.
production of methane from biomass. This is consistent with the trezitment of emissions
from vehicles using oil based fuels.
1.78
-------
EMISSIONS FROM ENERGY
TABLE 1 -28
ESTIMATED EMISSION FACTORS FOR LIGHT- AND HEAVY-DUTY NATURAL CAS VEHICLES
EMISSIONS
| NOx
CH4
NMVOC
CO
N2O
C02
Passenger Car
Advanced Control; Assumed Fuel Economy: I4.9km/Mj
g/km
g/kgfuel
g/MJ
0.5
10.3
0.21
0.7
14.5
0.29
O.OS
1.0
0.0?.
0.3
6.2
0.12
N/A
N/A
N/A
Uncontrolled; Assumed Fuel Economy: 6.5 km/MJ
g/km
g/kg fuel
g/MJ
2.1
19.0
0.38
3.5
31.6
0.63
0.5
4.5
0.09
4.0
36.1
0.72
N/A
N/A
N/A
133
2750
56.1
305
2750
56.1
Heavy-Duty Vehicles: Stoichiometrlc Engine (compare with gasoline)
Advanced Control; Assumed Fuel Eiconomy: 3.6 km/MJ
g/km
g/kgfuel
g/MJ .
2.6
13.0
0.26
3.0
15.0
0.30
0.20
1.0
0.02
1.0
5.0
0.10
N/A
N/A
N/A
550
2750
56.1
Uncontrolled; Assumed Fuel Economy: 2.2 km/MJ
g/km
g/kg fuel
g/MJ
5.7
17.4
0.35
10.0
30.6
0.61
1.4
4.3
0.09
12.0
36.7
0.73
N/A
N/A
N/A
900
2750
56.1
Heavy-Duty Vehicles: Lean Burn Engine (compare with diesel)
Advanced Control; Assumed Fuel Economy: 2.4 km/M 3
g/km
g/kg fuel
g/MJ
4.0
13.3
0.27
4.0
13.3
0.27
0.40
1.3
0.03
1.5
5.0
0.10
N/A
N/A
N/A
825
2750
56.1
Uncontrolled; Assumed Fuel Economy: 2.0 km/MJ
g/km
g/kg fuel
g/MJ
23.0
63.9
1.28
10.0
27.8
0.56
2.0
5.<>
0.11
8.0
22.2
0.44
N/A
N/A
N/A
990
2750
56.1
PART 2
1.79
-------
EMISSIONS FROM ENERGY
TABLE 1-29
ESTIMATED EMISSION FACTORS FOR LIGHT- AND HEAVY-DUTY LP GAS VEHICLES.
EMISSIONS
NOx
CH4
NMVOC
CO
N2O
C02
Passenger Car
Advanced Control
g/km
I/kg fuel
g/MJ
0.5
8.8
0.19
0.02
0.4
0.01
0.25
4.4
0.10
0.3
5.3
0.11
N/A
N/A
N/A
170
3000
63.1
Uncontrolled
g/km
g/kgfuel
g/MJ
2.1
17.7
0.38
0.18
1.5
0.03
3.5
29.S
0.64
8.0
67.5
1.45
N/A
N/A
N/A
356
3000
63.1
Heavy-Duty Vehicles: Stoichiometric Engine (compare with gasoline)
Advanced Control
g/km
g/kgfuel
g/MJ
2.6
11.2
0.24
0.1
0.4
0.01
0.70
3.0
0.07
1.0
4.3
0.09
N/A
N/A
N/A
695
3000
63.1
Uncontrolled
g/km
g/kgfuel
g/MJ
S.7
16.8
0.36
0.4
1.2
0.03
8.0
23.5
0.51
24.0
70.6
1.52
N/A
N/A
N/A
1020
3000
63.1
1.80
-------
EMISSIONS FROM ENERGY
TABLE 1-30
ESTIMATED EMISSION FACTORS FOR LIGHT- AND HEAVY-OUTY METHANOL VEHICLES
EMISSIONS
NOx
CH4
NMVOC
CO
NiO
C02
Passenger Car (M85 Fuel)
Advanced Control
g/km
g/kg fuel
g/MJ
0.5
4.5
0.19
0.02
0.2
0.01
0.66
5.9
0.25
3.14
28.0
1.19
N/A
N/A
N/A
183
1632
69.7
Heavy-Duty Vehicle -Methanol-Diesel Engine- M 100 Fuel
Advanced Control
g/km
g/kg fuel
g/MJ
4.0
6.1
0.30
O.I
0.2
0.01
1.50
2.3
0.11
4.0
6.1
0.30
N/A
N/A
N/A
908
1375
68.8
Non-Rood Mobile Sources
Emission factors are provided for major non-road vehicle source categories including farm
and construction equipment, railway locomotives, boats, and ships (all primarily equipped
with diesel engines), jet aircraft, and gasoline-fueled piston aircraft in Table 1-31.
Emission factors for diesel engines used in railway locomotives, farm equipment such as
tractors and harvesters, construction equipment such as bulldozers and cranes, and diesel
boats, are from Weaver (1988). These estimates are specilk to the U.S., may be applicable
to other regions as well. N2O emission factors for off-road diesels are assumed to be the
same as those for heavy-duty on-highway diesel engines.
Large ocean-going cargo ships are driven primarily by large, slow-speed and medium-speed
diesel engines, and occasionally by steam turbines and gas nurbines (the latter in high pow-
er-weight ratio vessels such as fast ferries and warships). The number of vessels equipped
with steam or gas-turbine propulsion is small, however, since these vessels are unable to
compete with the more efficient diesels in most applications. The results shown for NOX
and CO are from Hadler (I990)32. N2O emissions for these engines were assumed to be
the same, on a fuel-specific basis, as those for other heavy-duty diesels, and VOC
emissions from these large diesels are probably negligible.
32Other sources consulted for comparison are Melhus (1990), Bremnes (1990),
Alexandersson (1990)
PART 2
1.81
-------
EMISSIONS FROM ENERGY
TABLE 1-3!
ESTIMATED EMISSION FACTORS FOR NON-HIGHWAY MOBILE SOURCES
UNCONTROLLED EMISSIONS
NOx
CH4
NMVOC
CO
N2O
C02
OCEAN GOING SHIPS
g/kgfuei
g/MJ
87
2.1
n/a
n/a
n/a
n/a
1.9
0.046
0.08
0.002
3212
77.4
BOATS
g/kg fuel
g/MJ
67.5
1.6
0.23
0.005
4.9
0.11
21.3
0.50
0.08
0.002
LOCOMOTIVES
g/kg fuel
g/MJ
74.3
1.8
0.25
0.006
5.5
0.13
26.1
0.61
0.08
0.002
3188
73.3
3188
73.3
FARM EQUIPMENT
g/kg fuel
g/MJ
63.5
1.5
0.45
0.01 1
9.6
0.23
25.4
0.60
0.08
0.002
3188
73.3
CONSTRUCTION AND INDUSTRIAL EQUIPMENT
g/kg fuel
g/MJ
50.2
1.2
0.18
0.004
3.9
0.09
16.3
0.38
0.08
0.002
3188
73.3
JET AND TURBOPROP AIRCRAFT
g/kg fuel
g/MJ
12.5
0.29
0.087
0.002
0.78
0.018
5.2
0.12
n/a
n/a
3149
71.5
GASOLINE (PISTON) AIRCRAFT
g/kg fuel
g/MJ
3.52
0.08
2.64
0.06
24
0.54
1034
24
0.04
0.0009
3172
69.3
Data on emissions from aircraft are limited or presented in forms which are difficult to
compare. The factors shown for aircraft were developed by Radian (1990) - for jet
(turbine) emissions based on a Pratt and Whitney JT-17 engine (one of the most
commonly used types), and for small gasoline-fueled piston aircraft based on a Cessna
engine. These are considered very approximate. For the gasoline piston engines, fuel-
specific N2O emissions were assumed to be similar to those for uncontrolled passenger
cars.
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1.7.4 Recent Information Updates
Methane
As background for an expert group meeting to advise the IPCC/OECD programme,
Berdowski, Olivier and Veldt (1993) provided some updated emission factors for methane,
in general derived from total VOC factors and studies on VOC profiles. In Table I -32 the
emission factor estimate for each fuel and vehicle type is summarized. Some of these
factors are presented in a somewhat different format, but aire generally very similar to
those presented in the previous section, where they overlap. Some factors, notably for
uncontrolled gasoline road vehicles are somewhat higher in the more recent material. The
expert group in its report (Berdowski, et al., 1993) emphasized that uncertainties in all
CH4 estimates to date are large, and that no fully satisfactory set of emission factors is
currently available for use in national inventory development.
Highest emission factors for CH4 appear for (uncontrolled) gasoline vehicles (cars, light
and heavy duty vehicles), and for consumption of aviation gasoline (avgas) which is
generally used by general aviation aircraft (e.g. business aircraft). All factors are averages
including all transport modes of a specific vehicle (e.g. city (traffic, highways; cruise flights,
take-off, landing, etc.). Uncertainty ranges are difficult to specify, since factors are derived
by taking a fraction of total VOC emission factors, both introducing uncertainties. In
addition, estimating global averages of total VOC, and thus methane, factors is an other
cause of uncertainty. Mobile sources, in particular gasoline consumption, are a source
category which is of some importance, and the uncertainty' of which may be quite large.
PART 2
1.83
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TABLE 1-32
GLOBAL METHANE EMISSION FACTORS FOR MOBILE SOURCES
Modofveh tele type * Y ,"*",
-~"~ „ t) T * ,
Cars/ 4-stroke, uncontr.
LDV-Freighc
2-stroke, uncontr.
4-stroke, 3-way cat.
3-way cat
HDV (Freight)
Rail, water
Aircraft
Fuel type
gasoline
gasoline
gasoline
diesel
LPG
natural gas
alcohol
gasoline
diesel
diesel, res. oil
coal
biomass
jetfuel
avgas
Emission factor****} »
*)
Olivier, 1991
Radian 1990***)
*)
*)
*)**)
*)**)
*)**)
Olivier, 1991
Radian, 1990
Radian, 1990
Notes:
LDV = Light Duty Vehicle (car. van); HDV = Heavy Duty Vehicle (trucks)
*) Emission factors derived from VOC factors and studies on VOC profiles.
**) Emission factor derived from boiler emissions.
***) Emission factor for methanol.
****) Emission factor all mode average (including all transport phases e.g. highways,
city traffic; cruise flight, take-off etc.). Original factors are in g/kg [marked *)].
Nitrous Oxide
An expert group convened to advise the IPCC/OECD programme on N2O from
combustion concluded that the basic estimation methodology previously recommended by
the OECD (1991) was generally still appropriate, though future imporvements should be
considered in characterizing catalyst equipped road vehicles. (Olivier, 1993) This is
especially important as vehicles equipped with new catalysts have emission factors which
are 4 to 5 times higher than those of uncontrolled vehicles (De Soete, 1993); and emission
factors of vehicles with medium aged catalysts (about 25 000 km) are 10 to 16 times higher
than uncontrolled vehicles (De Soete, 1993; Baas, 1991). In principle, an improved
methodology for estimating N2O emissions from catalyst controlled gasoline cars would
be a further distinction between:
(a) cars equipped with a new catalyst (e.g. < 15 000 km)
(b) cars equipped with aged catalysts (e.g. > 15 000 km).
(c) cars with malfunctioning catalysts.
However, since in practice the fraction of catalyst equipped cars which has a "new" catalyst
will be quite small, these refinement will likely result in a minor correction of the factors
used for category (b) to be used as average figures for the whole fleet including all vintages
1.84
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EMISSIONS FROM ENERGY
of catalyst equipped cars of a specific type as defined under category 2. Also the fraction of
the catalyst car fleet with malfunctioning catalysts will generally not be known as are the
appropriate N2O emission factors for this category. Some countries may improve the
calculations by distinguishing between various types of catalysts or between different parts
of the driving cycle - when activity data are available of course.
For non-catalyst equipped vehicles the estimated emission factors for gasoline and diesel
cars reported in the Revised IPCC/OECD Report of August 1991 are in line with the
ranges reported in the evaluation by De Soete (1993) and Baas (1991). For other fuels
such as LPG, natural gas, and biofuels (e.g. ethanol and methanol) default emission factors -
expressed as g/GJ -for different types of road vehicles still have to be determined. In Table
1-33 the estimated emission factors and uncertainty ranges are shown for a number of
types of road vehicles, where the figures in the column "emission factor" are preliminary
estimates for the vehicle fleet in the USA. For default emission factors of catalyst equipped
cars it is recommended to use a value within the uncertainly range shown in the table.
For non-road vehicles (ships, locomotives and off-road vehicles e.g. for farming and
construction) emission factors have been assumed to be the same as for heavy duty diesel
trucks. For gasoline piston aircraft fuel-specific emission factors were assumed to be
similar to those for uncontrolled gasoline passenger cars; for jet aircraft no N2O estimated
emission factors are available. Table 1-34 shows the estimated emission factors for these
categories.
Indirect Greenhouse Gases
The IPCC/OECD programme has not yet addressed the indirect GHGs in detail. This is
consistent with the initial priorities within the programme. As noted above, mobile source
combustion is a major contributor to all of these gases. Because they are important
contributors to a range of local and regional, as well as global atmospheric pollution
problems, NOX, CO and NMVOC have been widely studies and reported. The illustrative
data cited above reflect estimates of average emission rates for main transport sub-
categories worldwide, as of 1991. They are still considered to be reasonably
representative. However, the data are based on analyses done for the United States
vehicle fleets, and they may be less representative elswhere. In all cases they are averages
over a range of vehicle and control technologies, and operating conditions.
PART 2
1.85
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EMISSIONS FROM ENERGY
TABLE 1-33
ESTIMATED EMISSION FACTORS AND UNCERTAINTY RANGES FOR ROAD VEHICLES.
Vehicle type
Gasoline car
Gasoline car. 2 stroke engine
Diesel car
LPGcar
Natural gas (CNG) car
Motor cycle
Blofuel car (echanol, methanol)
Passenger, controlled:
Non-catalytic controlled gasoline car
Oxidation catalyst gasoline car
Early 3-way catalyst gasoline car
Advanced 3-way catalyst gasoline car
Aged catalyst gasoline car
Moderate controlled diesel car
Advanced controlled diesel car
Catalyst equipped LPG car
Catalyst equipped methanol car
Non-catalytic controlled motor cycle
Freight, uncontrolled:
Low-duty gasoline vehicles
Low-duty diesel vehicles
Low-duty LPG vehicles
Low-duty CNG vehicles
Heavy-duty gasoline vehicles
Heavy-duty diesel vehicles
Heavy-duty LPG vehicles
Heavy-duty CNG vehicles
Freight, controlled:
Non-catalyst LD gasoline truck
Oxidation catalyst LD gasoline truck
Early 3-way catalyst LD gasoline truck
Advanced 3-way catalyst LD gasoline truck
Moderate controlled LD diesel truck
Advanced controlled LD diesel truck
Catalyst equipped LD LPG truck
Non-catalyst controlled HD gasoline truck
Oxidation catalyst HD gasoline truck
3-way catalyst HD gasoline truck
Moderate controlled HD diesel truck
Advanced controlled HD diesel truck
Emission factors* (g N2O/km)
(g N2O/GJ energy input)
NA/0.005
NA
NA/0.014
N/A
NA
NA/0.002
NA
NA/0.005
NA/0.027
NA/0.(M6
N A/0.0 19
NA
N A/0.01
NA/0.007
NA
NA
NA/0.002
NA/0.006
N A/0.0 17
NA
NA
NA/0.009
NA/0.031
NA
NA
NA/0.006
NA/0.031
NA/0.063
NA/0.024
NA/0.014
NA/0.009
NA
NA/0.006
NA
NA/0.006
NA/0.025
NA/0.025
NA/0.9
NA
NA/1.9
NA
NA
NA/0.9
NA
NA/0.9
NA/4.9
NA/13.0
NA/6.9
NA
NA/1.9
NA/1.9
NA
NA
NA/0.9
NA/0.9
NA/1.9
NA
NA
NA/0.5
NA/1.9
NA
NA
NA/0.9
NA/4.8
NA/13.0
NA/6.8
NA/1.9
NA/1.9
NA
NA/0.5
NA
NA/0.5
NA/1.9
NA/1.9
Uncertainty range4*"
(g N20/kmXg N.20/GJ energy)
0.004-0.06
NA
0.02-0.06
NA
NA
NA
NA
NA
NA
NA
NA
0.05-0.32
• NA
NA
NA
NA/0.002-0.004
NA
0.004-0.06
0.02-0.06
NA
NA
NA
NA
NA
NA
NA
0.03-0.084
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
1.5-22
NA
8-25
NA
NA
NA
NA
NA
NA
NA
NA
18-120
NA
NA
NA
NA/0.2-0.4*"™
NA
1.5-22
8-25
NA
NA
NA
NA
NA
NA
NA
12-35
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
N.B. NA = Not Available
Preliminary estimate for US vehicles.
^^
Assumed fuel economy. 12 km/I gasoline; 15 km/I diesel.
Preliminary estimate for Japanese vehicles.
source: emission factor estimates for US vehicles: EPA (1989); Prigent and De Soete (1989); Dasch (1990); Ford
(1989-1991); Warner-Selph and Smith (1991);
uncertainty range: De Soete (1993), Baas (1991)
controlled methanol cars: Iwasaki et of. (1990), Susuki et al. (1992).
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TABLE 1-34
ESTIMATED DEFAULT EMISSION FACTORS AND UNCERTAINTY RANGES FOR NON-ROAD
TRANSPORT.
Activity
Sea ships (diesel)
Ships (int. nav.)(diesel)
Locomotives (diesel)
Off-road vehicles" (diesel)
Aircraft (jet fuel)
Aircraft (aviation gasoline)
Emission factor
(gN20/kg)
2*
2*
2*
2*
NA
0.9'
Uncertainty range
(gN20/kg)
NA
NA
NA
NA
NA
NA
N.B. NA = Not Available
* Preliminary estimate (assumed to be similar to HD dieseil vehicles and uncontrolled gasoline
passenger cars).
e.g. farm and construction equipment.
source: See note ^____
More detailed alternative emission factor source data representative of the precise vehicle
types, control technologies and other conditions in a particular country would always be
desirable. National experts working on detailed emissions of non-CO2 GHGs (particularly
the indirect gases) should consult the extensive literature on emission factors and
estimation procedures which has been developed by other inventory programmes outside
of the framework of the IPCC/OECD programme. As distinguished from the illustrative
emission factors, these data generally contain more vehicle and control technology detail,
and are further detailed by operating conditions (e.g., catalyst vintages, driving cycles). The
specific nature of these assumptions should be known and carefully matched with actual
conditions in the specific country in selecting the specific factors to be used.
Some key examples of data sources are:
• The CORINAIR Inventory: Default Emission Factors Handbook (Bouscaren, 1992);
• CORINAIR Working Group on Emission Factors for Calculating 1990 Emissions
from Road Traffic, Volume I: Methodology and Emission Factors (Eggleston, et al.,
1992)
• CORINAIR Working Group on Emission Factors for Calculating 1990 Emissions
from Road Traffic, Volume 2: COPERT Model, Users Mannuel (Andrias, etal., 19.92)
• Emissions Inventory Guidebook (European Environment Agency, forthcoming)
• U.S. EPA's Compilation of Air Pollutant Emissions Factors: Highway Mobile Vehicles
(AP-42), 4th Edition 1985, (U.S. EPA, 1985);
• U.S. EPA's Mobile4 Model and User's Guide. U.S. NTIS (1991)
• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory
(Stockton and Stelling, 1987)
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1.87
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EMISSIONS FROM ENERGY
1.7.5 Priorities For Future Work
Access to Exisiting Data: There is a significant amount of past and on-going work in the
area of mobile source emissions estimation that could be very useful for all countries. ,
Major references are cited in the previous section. However, at this time there is no
simple mechanism for published information, and especially underlying data bases be
disseminated it to other interested countries. The IPCC/OECD Programme should
address information exchange more explicitly, in conjunction with other interested
organizations and programmes, possibly resulting in a clearinghouse or some other
mechanism to improve access to such information.
Data for Non-OECD Regions of the World: Most of the information which does
exist on emissions performance of vehicles, is based on data collected in the OECD
countires. A critical need is for measurement data to determine the characteristics of
vehicle fleets in non-OECD countries and to develop adjusted emission factors if
necessary.
Key Emission Factor Uncertainties: At this moment there are some key areas for
which available emission factors are not adequate for to support national inventory
development. Expert groups have identified several specific categories for priority work:
CH« uncontrolled gasoline road vehicles particularly as affected by age and
maintenance
N2O - biofuels for all applications
ships, aircraft and rail
gasoline and diesel vehicles (with and .without catalyst control)
LPG, natural gas and biofuels used for road transport (with and without catalyst
control)
1.8 Fugitive Emissions from Coal Mining,
Handling and Utilization
1.8.1 Overview
This section covers "fugitive" emissions of greenhouse gases (GHGs) from production,
processing, handling and utilization of coal. Conceptually, this includes all emissions from
coal-related activities which are not the result of combustion of coal as a fuel. Thus,
intentional or unintentional releases of gases such as methane in mining are included here,
as are emissions from inadvertent combustion of coal in coal mine fires. By far the most
important component of this sub-category is methane (CH4) emissions from coal mining
and handling. The bulk of this section, deals with these emissions. Two other fugitive
emission sources are discussed briefly at the end of the section. These are CO2 from
burning coal mines and waste piles, and CO2 from SO2 scrubbing. There are very likely
other fugitive emissions associated with the coal fuel cycle. If important sources are
identified, these will be considered for inclusion in future editions of the Guidelines.
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1.8.2 CH< From Coal Mining And Handling
The process of coal formation, commonly called coalification, inherently generates
methane and other byproducts. The formation of coal is a complex physio-chemical
process occurring over millions of years. The degree of coalification (defined by the rank
of the coal) determines the quantity of methane generated and, once generated, the
amount of methane stored in the coal is controlled by the pressure and temperature of
the coal seam and other, less well-defined characteristics of the coal. The methane will
remain stored in the coal until the pressure on the coal is reduced, which can occur
through the erosion of overlying strata or the process of coal mining. Once the methane
has been released, it flows through the coal toward a pressure sink (such as a coal mine)
and into the atmosphere (Boyer, 1990). Methane emissions: from coal mining in 1990
contributed an estimated 23 to 39 Tg of methane (USEPA, I993a; CIAB, 1992; Airuni,
1992).
The amount of CH4 generated during coal mining is primarily a function of coal rank and
depth, gas content, and mining methods, as well as other factors such as moisture. Coal
rank represents the differences in the stages of coal formation and is dependent on
pressure and temperature of the coal seam; high coal ranks;, such as bituminous, contain
more CH4 than low coal ranks, such as lignite. Depth is important because it affects the
pressure and temperature of the coal seam, which in turn determines how much CH4 is
generated during coal formation. If two coal seams have the same rank, the deeper seam
will hold larger amounts of CH4 because the pressure is greater at lower depths, all other
things being equal. As a result, the methane emission factor's for surface mined coal are
assumed to be lower than for underground mining.
In most underground mines, methane is removed by ventilating large quantities of air
through the mine and exhausting this air (typically containing a concentration of I percent
methane or less) into the atmosphere. In some mines, however, more advanced methane
recovery systems may be used to supplement the ventilation systems and ensure mine
safety. These recovery systems typically produce a higher concentration product, ranging
from 35% to 95% methane. In some countries, some of thiis recovered methane is used as
an energy source, while other countries vent it to the atmosphere. Recent technological
innovations are increasing the amount of medium- or high-quality methane that can be
recovered during coal mining and the options available to use it. Thus, methane emissions
could be reduced from this source in the future.
In surface mines, exposed coal faces and surfaces, as well as areas of coal rubble created by
blasting operations, are believed to be the major sources of methane. As in underground
mines, however, emissions may come from the overburden (in limited cases where these
strata contain gas), which is rubblized during the mining process, and underlying strata,
which may be fractured and destressed due to removal of the overburden. Because
surface mined coals are generally lower rank and less deeply buried, they do not tend to
contain as much methane as underground mined coals. Thus, emissions per ton of coal
mined are generally much lower for .surface mines. Research is underway in the United
States and elsewhere to increase the understanding of CH,, emissions from surface mines
(Kirchgessner, I992;USGS, 1993).
A portion of the CH4 emitted from coal mining comes from post-mining activities such as
coal processing, transportation, and utilization. Coal processing involves the breaking,
crushing, and thermal drying of coal, making it acceptable for sale. Methane is released
mainly because the increased surface area allows more CH4 to desorb from the coal.
Transportation of the coal contributes to CH4 emissions, because CH4 desorbs directly
from the coal to the atmosphere while in transit (e.g., in railroad cars). Utilization of
metallurgical coal also emits, methane. For instance, in metallurgical coke production, coal
PART 2
1.89
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EMISSIONS FROM ENERGY
is crushed to a particle size of less than 5 mm, vastly increasing the surface area of the coal
and allowing more CH4 to desorb. During coking process, methane, carbon dioxide, and
other volatile gases are released. In modern coke ovens, this gas is typically collected and
utilized as a fuel source, but in older coke ovens, particularly those used in less developed
regions, coke gas is vented to the atmosphere (Boyer, 1990; coke production is covered in
Chapter 3).
Some methane is also released from coal waste piles and abandoned mines. Coal waste
piles are comprised of rock and small amounts of coal that are produced during mining
along with marketable coal. There are currently no emission measurements for this
source. Emissions are believed to be low, however, because much of the methane would
likely be emitted in the mine and the waste rock would have a low gas content compared
to the coal being mined. Emissions from abandoned mines may come from unsealed shafts
and from vents installed to prevent the buildup of methane in mines. There is very little
information on the number of abandoned mines, and data are currently unavailable on
emissions from these mines. Most available evidence indicates that methane flow rates
decay rapidly once deep mine coal production ceases (Williams and Mitchell, 1992;
Creedy, 1991). In some abandoned mines, however, methane can continue to be released
from surrounding strata for many years. In Belgium, France, and Germany, for example,
several abandoned mines are currently being used as a source of methane which can be
added to the gas system (Smith and Sloss, 1992; KfA, 1993). Due to the absence of
measurement data for both coal waste piles and abandoned mines, no emissions estimates
have been developed for these sources.
Review of Previous Methane Emission Estimation Studies
Over the years, a variety of methane emissions estimates have been developed for coal
mining, as shown in Table I. As the table shows, the variation in estimates has been quite
large, although more recent studies are showing more similar results. Many of the
emission studies conducted to date have confronted difficulties in developing estimation
methodologies that have resulted in the widely varying estimates and large uncertainties.
These difficulties include:
• Absence of data on which to base estimates: Many methane emission estimation
studies were developed without access to detailed data on methane emissions
associated with various components of the coal cycle. For certain sources such as
surface mines and post-mining activities, moreover, reliable emissions measurements
are still lacking.
• Use of national data to develop global estimates: Some studies have relied on data
from a single country to estimate global methane emissions from coal mining. This
approach can introduce large errors into the estimates due to the difficulty of
generalizing from one country's coal and mining conditions to other countries. Mining
experience has shown that there are frequently significant differences in methane
emission factors within countries, coal basins, and even coal mines for a variety of
geologic and other reasons.
• Failure to include all possible emission sources: Some studies prepared to date have
only estimated underground coal mining emissions from ventilation systems and have
not included degasification system emissions or post-mining emissions. In addition,
many estimates have assumed emissions from surface mines to be negligible and have
not included this source. At this point, moreover, there are still potential emission
sources such as abandoned mines for which emissions cannot be estimated due to
the absence of necessary data.
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• Overreliance on statistical estimation methodologies: Several studies have attempted
to estimate global emission factors using statistical models that relate methane
emissions to various coal properties. For the most part, these models have proven
unreliable when estimates are compared to those developed using more detailed
country-specific information. The principal problem with using statistical
methodologies is the number of variables that can affect methane emissions. Mining
experience has shown that a complete understanding of methane emissions requires
detailed examination of coal and geological characteristics and that methane
emissions can be highly variable within mines, basins and countries. Collecting
comprehensive data and developing statistical models of methane emissions that can
reliably predict methane emissions on a global basis is thus extremely difficult.
In general, the results of the more recent country-specific and global methane emission
studies are likely to be more reliable than previous efforts. For several of the mafor coal
producing countries, for example, detailed data on methane; emissions from underground
mine ventilation and degasification systems are reported to central institutes and are
publicly available. More recent studies have been able to use this available data from
several countries in preparing and validating their estimates of methane emissions from
underground mines. Data is still lacking on emissions from surface mines and post-mining
activities, however, and thus even the emission estimates from more recent studies should
be considered uncertain.
Suggested Emission Estimation Methods
Methane emission estimates should be developed for the three principal sources of
methane emissions: underground mines, surface mines, and post-mining activities. To
assist in developing these estimates, the IPCC recommends use of a "tiered" approach for
estimating emissions. For each source, two or more approaches (or "tiers") are presented
for estimating emissions, with the first tier requiring basic and readily available data and
higher tiers requiring additional data. The selection among iJie tiers will depend upon the
quality of the data available in the country.
Underground Mining
Methane emissions from underground mines should include! estimated emissions from
ventilation systems and from degasification systems, if any of a country's mines use
degasification systems to supplement ventilation. In the approaches outlined below,
methods of estimating emissions from both of these sourceis are presented.
Three possible methodological approaches are suggested by the IPCC, with the choice
among them depending upon the availability of data and the degree to which coal mining is
considered a significant source of emissions by particular countries. For those countries
with comparatively large methane emissions from coal mining, the use of more detailed
estimation methodologies may be warranted. In smaller coal producing countries,
however, the most simple approach may provide a reasonably accurate first approximation
of CH4 emissions from underground mines.
PART 2
1.91
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EMISSIONS FROM ENERGY
TABLE 1-35
SUMMARY OF EMISSIONS ESTIMATES FROM SELECTED STUDIES
Study Author
Koyama (1963)
Hitchcock & Wechsler (1972)
Seller (1984)
Crutzen(l987)
Okkcn & Kram (1989)
Zimmcrmcyor (1989)
Seltzer &Zittel( 1990)
Barns & Edmonds. USDOE (1990)
Boyer.USEPA(l990)
Margraves (1990)
Airuni(l992)
C1AB(I992)
USEPA(l993a)
Emissions
Estimate
(Tg)
20
8-28
30
34
15-45
24
23
25
33-64
29
28
24
23-39
Year of Estimate
I960
1967
1975
n/a
n/a
n/a
n/a
1986
1988
n/a
1990
1990
1990
Methodological Issues
Hard coal only; no emissions estimates for
surface mining or pose-mining activities. 1 960
coal production data.
Post-mining not included; Source of emission
factors, particularly low end, unspecified. 1 967
coal production data.
Based on Koyama, with 1 975 coal production
data.
Source of emission factors unclear. Hard coal
only; no emissions estimates for surface mining
or post-mining activities.
Source of emission factors unclear. Hard coal
only; no emissions estimates for surface mines or
post-mining activities.
Only underground mining considered; no
emissions estimates for surface mines or post-
mining activities.
Adjusted Zimmermeyer by: ( 1 ) including surface
mines; (2) assuming that 1 5 percent of
underground mining emissions (3.6 Tg) not
emitted to the atmosphere due to methane
utilization.
Assumed mathematical relationship between coal
rank and depth and that in-situ methane content
was equal to the mining emission factor.
Statistical approach related methane emissions to
in situ methane content. Correlation based on
U.S. data only. Large uncertainty in application of
results for global estimates.
Method based on current methane production
rates due to continued coalification.
Methodology unspecified.
Country specific data used where available for
underground mines. Surface and post-mining
emissions developed using low emission
assumptions. No uncertainty analysis.
Country specific data used where available for
underground mines. Global average emission
factors for rest of countries for underground
mines and for all surface mining and post-mining
emissions.
The first tier approach—called the Global Average Method—uses a pre-determined range
of emission factors (based on experience in a number of countries) to estimate emissions.
The most complex, third tier, approach—called the Mine Specific Method—develops
emissions estimates using detailed emission data for most, if not all, of a country's
underground coal mines. In between these two methods is an intermediate, second tier,
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approach-called the Basin or Country Average Method-in which more limited
information, including either measurements from a subset of mines or geological and other
data, can be used to refine the range of possible emission factors presented in the Global
Average Method. Each of these approaches is described in more detail below.
Tier I: Global Average Method
The simplest method for estimating methane emissions is to multiply underground coal
production by a factor or range of factors representing global average emissions from
underground mining, including both ventilation and degasification system emissions. This
method may be selected in cases where total coal production from underground mines is
available but more detailed data on mining emissions, geological conditions, coal
characteristics, and the like are not. The emission estimates generated using this method
should be presented as a range to reflect the high degree of uncertainty associated with it.
The Tier I Equation is shown below.
EQUATION I
TIER I: GLOBAL AVERAGE METHOD - UNDERGROUND MINES
Low CH.4 Emissions = Low CH4 Emission Factor
(tonnes)
(m3 CH4/tonne of coal mined)
High CH4 Emissions =
(tonnes)
x Underground Coal Production
(tonnes)
x Conversion Factor
High CH4 Emission Factor
(m3 CH4/tonne of coal mined)
x Underground Coal Production
(tonnes)
x Conversion Factor
Where:
• Low CH4 Emission Factor = 10 m3/tonne
• High CH4 Emission Factor = 25 m3/tonne
• Conversion Factor converts the volume of CH4 to a weight measure based
on the density of methane at 20C and I atm, which is:
1.49 x I09 m3 per I million metric tons
In the original IPCC methodology, a single emission factor of 27.1 m3 of methane per
tonne of coal mined was recommended for all underground mining. This factor included
both emissions from mining and from post-mining emissions associated with underground
coal production.33
33 Due to a mistake in OECD (1991), it appeared that this factor did not
include emissions from mine degasification systems and post-mining activities. In
fact, however, this emission factor did include these two additional emission
sources.
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Based on more recent studies and additional country-specific emission data, the IPCC
recommends revising this emission factor to reflect some additional issues. First, use of a
range of emission factors is suggested to reflect the large variation possible in methane
emissions from underground mines in different coal basins and countries. Second, this
emission factor should represent only those emissions associated with underground
mining (ventilation and degasification systems); post-mining emissions should be handled
separately.
The IPCC recommends revised global average emission factors of 10 to 25 m /tonne of
coal mined (not including post-mining activities). This range reflects the findings of various
country studies, as shown in Table 1-36. As more detailed emissions data are published by
various countries, the factors can be further revised, if necessary.
Tier 2: Country or Basin Average Method
The suggested Tier 2 approach-called the "Country or Basin Average Method"~can be
used to refine the range of emission factors used for underground mining by incorporating
some additional country or basin-specific information. Basically, this method enables a
country with limited available data to determine a more appropriate and most likely
narrower range of emission factors for their underground mines. For many countries, it is
expected that this range will fall within the global average emission factor range of 10 to
25 mVtonne. The range of possible emission factors is not constrained under the Tier 2
approach, however, and some countries may find that their underground mining emission
factors lie outside the global average emission factor range.
To implement the Tier 2 approach, national experts must examine measurement data
from at least a limited number of underground coal mines in their country or region. Using
this data, either statistical analysis or expert judgement should be applied to develop a
reasonable range of emission factors for the country or region.34 Making this estimate will
require judgment on the part of the estimator regarding the adequacy of the available data
and its uncertainty. If sufficient expertise is not available to make such judgments, it is
recommended that the Tier I approach (the Global Average Method) be used to prepare
emissions estimates.
TABLE i-36
ESTIMATED UNDERGROUND EMISSION FACTORS FOR SELECTED COUNTRIES
Country
Former Soviet Union
United States
Germany (East & West)
United Kingdom
Poland
Czechoslovakia
Emissions Factors (mJ/ton)
17.8-22.2
11.0- 15.3
22.4
15.3
6.8- 12.0
23.9
15.6
Source
USEPA, I993a
USEPA, 19936
Zimmermeyer, 1989
BCTSRE, 1992
Richer, 1991
Elibler, 1992
Lama, 1992
34 If measurement data is available for most or all or a country's underground
coal mines, the Tier 3 approach-called the "Mine Specific Method"--should be
used to estimate emissions.
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In some cases, measurement data on emissions from mines may be unavailable but a
country will still seek to develop a narrower estimate based on other types of available
data. In such cases, a country may seek to develop a simple emissions model based on
physical principals or make judgments based on an evaluation of available data. Among the
key types of data that should be considered in such a model or evaluation are:
• the gas content of the coal, which contributes to the total amount of methane
available for emission during mining;
• the frequency of coal within the strata above and below the mined coal seam, which
also contributes to the total amount of methane available for emission during mining;
and,
• the method of mining, which determines the amount of ground that is disturbed by
mining the coal and the extent to which the methane contained in the mined coal
seam and the coal seams in the surrounding strata is liberated during mining.
It should be noted that while the Tier 2 approach can provide some additional information
about methane emissions in a particular country or coal basin, the estimates will still be
quite uncertain because of the absence of comprehensive and reliable emissions data. This
approach should thus be used only in cases where there is a strong need to make an
estimate that is narrower than the Tier I (Global Average Method) and not enough data
are available to prepare an estimate using the Tier 3 (Mine Specific Method) described in
the next section. It should further be noted that these narrower estimates will not
necessarily be more accurate than those developed under Tier I because they have not
been developed or verified with comprehensive measurement data.
In all cases where the Tier 2 approach is used, a detailed discussion of the types of data
available and the manner in which it was used to determine the refined range of emission
factors should be presented, so as to allow for the independent verification of estimates
and ensure comparability with estimates being prepared by other countries.
Tier 3: Mine Specific Method
Because methane is a serious safety hazard in underground mines, many countries have
collected data on methane emissions from mine ventilation systems, and some also collect
data on methane emissions from mine degasification systems. Where such data are
• available, the more detailed Tier 3 approach-called the "Mine Specific Method"-should
provide the most accurate estimate of methane emissions from underground mines. Since
these data have been collected for safety, not environmental reasons, however, it is
necessary to ensure that they account for total emissions from coal mines. The key issues
that should be considered when using mine safety data, as well as the recommendations of
the IPCC for resolving them, are shown in Table 1-37.
Treatment of Methane Utilization
All of the methods described above, with the possible exception of the Mine Specific
Method, assume that all of the methane liberated by mining will be emitted to the
atmosphere. In many countries, however, some of the methane recovered by mine
degasification systems is used as fuel instead of being emitted. Wherever possible, the
emission estimates should be corrected for the amount of methane that is used as fuel, by
subtracting this amount from total estimated emissions.
In several countries, data on the disposition of methane recovered by degasification
systems (i.e., whether it is used or emitted to the atmosphere) can be obtained from the
coal industry or energy ministries. Poland, for example, reports that its mine degasification
systems recovered 286 million m3 of methane in 1989, of which 201 million m3 was used
and the remaining 85 million m3 was emitted to the atmosphere (Polish Central Mining
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EMISSIONS FROM ENERGY
Institute, 1990). Regardless of the method used to develop the emissions estimates, the
Polish emission estimate should be adjusted to reflect the use of methane by subtracting
201 m3 from total emissions.
In some countries, data on the disposition of methane recovered by degasification systems
may not be reported, but it may still be possible to estimate utilisation amounts. In some
cases, for example, it may be possible to collect utilization data from end-users of the
methane if such data are unavailable from the mining industry. It may also be possible to
estimate utilization amounts based on information about the specific utilization options
being employed (i.e.. if the methane is being used to fuel a gas turbine of a specific size).
TABLE 1-37
KEY ISSUES FOR CONSIDERATION WHEN USINGTIER 3 ~ MINE SPECIFIC METHOD
ISSUE
DESCRIPTION
RECOMMENDATION
Where and how are ventilation system
emissions monitored?
When used to develop overall methane
emission estimates, the optimal location for
ventilation air monitors is at the point
where ventilation air exhausts to the
atmosphere.
If ventilation emissions are not monitored
at the point of exhaust, emission data
should be corrected based on estimated
additional methane emissions between the
point of measurement and the point of
exhaust to the atmosphere.
Arc ventilation system emissions
monitored and/or reported for all mines?
In some countries, emissions are only
reported for "gassy mines".
Estimates should be developed for non-
gassy mines as well. Estimates can be
prepared using information about the
definitions of gassy and non-gassy mines
and data on the total number of mines and
the coal production at these mines.
Are methane emissions from degasification
systems reported?
Some countries collect and report methane
emissions from ventilation and
degasification systems, while others only
report ventilation system emissions. Both
emission sources must be included in
emissions estimates.
If degasification system emissions are not
included, those mines with degasification
systems should be identified and estimates
prepared on emissions from their
degasification systems. Emissions estimates
can be based on knowledge about the
efficiency of the degasification system in use
at the mine or the average efficiency of
degasification in the country.
The data sources for any adjustments to emissions that are made to reflect the utilization
of methane should be clearly specified to ensure the independent verification of the
emissions estimates developed. If data are unavailable, no adjustment for utilization should
be made.
Surface Mining
Two possible approaches for estimating methane emissions from surface mining are
suggested by the IPCC. For the most part, these approaches resemble those developed
for underground mining, but the results will be much more uncertain due to the absence
of emissions data. If emissions measurements are developed in the future, it should be
possible to refine these estimation methodologies.
Tier I: Global Average Method
As for underground mining, the simplest Tier I approach for surface mines-called the
"Global Average Method"-is to multiply surface coal production by a range of emission
factors representing global average emissions, as shown in the equation below.
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EQUATION 2
TIER I: GLOBAL AVERAGE METHOD — SURFACE MINES
Low CH4 Emissions =
(tonnes)
High CH4 Emissions =
(tonnes)
Low CH4 Emission Factor
(m3 CH^/tonne of coal mined)
x Surface Coal Production
(tonnes)
x Conversion Factor
High CH4 Emission Factor
(m3 CH^tonne of coal mined)
x Surface Coal Production
(tonnes)
x Conversion Factor
Where:
• Low CK4 Emission Factor = 0.3 m3/tonne
• High CH4 Emission Factor = 2.0 m3/tonne
• Conversion Factor converts the volume of CH4 to a weight measure based on
the density of methane at 20C and I atm, which is:
1.49 x I09 m3 per I million metric tons
In the original 1PCC methodology, an average emission factor of 2.5 m /tonne was
recommended (OECD, 1991), based on the results of Boyer (I990).35 Based on more
recent analyses and additional studies, a revised emission factor range of 0.3 to 2.0
m3/tonne is recommended by the IPCC, not including post-mining emissions (USEPA,
!993a;CIAB, I992;BCTSRE, I992;CMRC, 1992; Kirchgessner, 1992).
Given the lack of information and measurements on methane emissions from surface
mines, this range must be considered extremely uncertain, and it should be refined in the
future as more data become available.
Tier 2: Country or Basin Specific Method
A second tier estimation of methane emissions—called the "Country or Basin Specific
Method"--can be used if additional information is available on in-situ methane content and
other characteristics of a country's surface mined coals. This approach enables a country
to develop emission factors that better reflect specific conditions in their countries.
Depending on the degree of detail desired, emissions can be estimated for specific coal
basins or countries, using the equation below.
35 In OECD (1991), it mistakenly appears that the surface mining emission factor does
not include emissions from post-mining activities; In fact, i:he factor of 2.5 m3/ton includes
both direct emissions from surface mining and those from post-mining activities.
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EQUATION 3
TIER 2: COUNTRY OR BASIN SPECIFIC METHOD - SURFACE MINES
CH^ Emissions = [ In-Situ Gas Content
(tonnes) (m3 CH4/tonne)
x Surface Coal Production
(tonnes)
x Conversion Factor ]
+ [Assumed Emission Factor for Surrounding Strata
(m3/tonne)
x Surface Coal Production
(tonnes)
x Conversion Factor ]
Where:
n In-Situ Gas Content and Assumed Emission Factor for Surrounding
Strata are described in the text.
n Conversion Factor converts the volume of CH4 to a weight measure
based on the density of methane at 20C and I atm, which is:
1.49 x IO9 m3 per I million metric tons
In Equation 3, In-Situ Gas Content represents the methane actually contained in the coal
being mined, as determined by measuring the gas content of coal samples. Average values
for a coal mine, coal basin or country could be developed, depending on the level of detail
in the estimate. For surface mines, unlike underground mines, it is frequently assumed that
all of the methane contained in the coal is released during mining and that post-mining
emissions from surface mined coals are effectively zero (BTSCRE, 1992; CIAB, 1992;
CMRC, 1992). Some countries may choose to modify this assumption based on their
specific conditions. Care should be taken, however, to ensure that estimates of any
emissions assumed to occur during post-mining activities are subsequently prepared.
Assumed Emission Factor for Surrounding Strata represents the possibility that more
methane will be emitted during surface mining than is contained in the coal itself because
of emissions from the strata below (or in limited cases, above) the coal seam. Some
countries have assumed that there are not emissions from surrounding strata associated
with surface mined coals (BTSCRE, 1992; CMRC, 1992). If available information indicates
that there are gas bearing strata surrounding the mined coal seam and that these strata are
emitting their gas in conjunction with the mining, however, countries should include these
emissions in their estimates.
Emission factors for the surrounding strata can be developed using one of two
approaches. Ideally, the assumed emission factor should be based on an evaluation of the
gas content of the surrounding strata and verified by measurements. If such data are
unavailable, an alternative method of developing an emission factor is to assume that some
multiple of the gas content of the mined coal is emitted by the surrounding strata. It
should be noted that the alternative approach is highly speculative, however, given the lack
of data upon which to base such assumptions.
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Post-Mining Activities
Like surface mining emissions, there are currently few measurements of methane
emissions from post-mining activities. In fact, many past studies have overlooked this
emission source, while others have developed only rudimentary estimation methodologies.
Two possible approaches for estimating emissions from post-mining activities are
recommended by the IPCC.
Tier I: Global Average Method
For the most simple estimates, a global average emission factor can be multiplied by coal
production for underground and surface mining, as shown in the equation below. It is
important to distinguish between underground and surface: mined coals because the gas
contents are likely to be very different and hence emissions could vary significantly.
High CH4 Emissions =
(tonnes)
EQUATION 4
TIER I: GLOBAL AVERAGE METHOD - POST-HINING ACTIVITIES
Low CH4 Emissions = Low CH4 Emission Factor
(tonnes) (m3 CH4/tonne of coal mined)
x Underground Coal Production
(tonnes)
x Conversion Factor
High CH4 Emission Factor
(m3 CH4/tonne of coal mined)
x Surface Coal Production
(tonnes)
x Conversion Factor
Where:
• Underground Low CH4 Emission Factor = 0.9 m3/tonne
• Underground High CH4 Emission Factor = 4.0 m3/tonne
• Surface Low CH4 Emission Factor = 0 nrVtonne
• Surface High CH4 Emission Factor = 0.2 m3/tonne
• Conversion Factor converts the volume of CH4 to a weight measure
based on the density of methane at 20C and I atm, which is:
1.49 x I09 m3 per I million metric tons
Underground Mined Coals: The IPCC recommends emission factors of 0.9 to 4 m /ton
for underground mined coal, based on recent studies (CIAB, 1992; BCTSRE, 1992; USEPA,
I993a).
Surface Mined Coals: Emission factors of 0 to 0.2 m3/ton are recommended by the IPCC
for post-mining activities involving surface mined coal (GAB, 1992; CMRC, 1990; USEPA,
I993a).
Tier 2: Country or Basin Specific Method
Emissions estimates can be refined if additional data are available on coal characteristics.
This method may be preferable if higher tier methods have been used to estimate
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EQUATION 5
TIER 2: COUNTRY OR BASIN SPECIFIC METHOD POST-MINING ACTIVITIES
a) Underground CH4 = In-Situ Gas Content
Emissions (tonnes) (m3 CH4/tonne)
Activities (%)
When Necessary:
b) Surface CH<
Emissions (tonnes)
Activities (%)
Where:
x Fraction of Gas Released During Post-Mining
x Underground Coal Production (tonnes)
x Conversion Factor
= In-Situ Gas Content
(m3 CH^/tonne)
x Fraction of Gas Released During Post-Mining
x Surface Coal Production (tonnes)
x Conversion Factor
In-Situ Gas Content and Fraction of Gas Released During Mining are
described in the text
Conversion Factor converts the volume of CH4 to a weight measure
based on the density of methane at 20C and I atm, which is:
1.49 x IO9 m3 per I million metric tons
In-Sltu Gas Content represents the methane actually contained in the coal being mined, as
determined by measuring gas contents in coal samples. Average values for a coal mine, coal
basin or country could be developed, depending on the level of detail in the estimate.
Fraction of Gas Released During Post-Mining Activities represents the percentage of the
in-sicu gas content that is assumed to be emitted during post-mining activities. There are
three key issues related to the development of this fraction:
• For Surface Mined Coal: In most cases, if the Tier 2 approach is used to estimate
methane emissions from surface mines, post-mining emissions from surface mined
coals are assumed to be zero. In these cases, the use of Equation 5(b) is unnecessary
and countries should be careful to avoid double-counting. If a country has not
assumed that all of the methane contained in surface mined coal is released during
mining, however, Equation 5(b) should be used to estimate post-mining emissions and
the value selected for "Fraction of Gas Released During Post-Mining Activities"
should be consistent with the previous assumption used.
• For Underground Mined Coal: The assumed fractions for underground mining will
be based on information about coal permeability, desorption rates, mining methods
and other factors. Recent studies have assumed that 25 to 40 percent of the in-situ
CH< content of underground mined coal is emitted during post-mining activities
(USEPA. I993b; BCTSRE, 1992).
• Potential Fraction of Methane Not Emitted: It is currently assumed that all of the
CH| contained in mined coal will be emitted to the atmosphere, although it is
possible that a fraction could remain in the coal until the point of combustion and be
burned instead of emitted. At this time, estimates of the extent to which this may be
the case have not been developed. If countries have such information, however, they
could further incorporate this factor into Equation 5.
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Total Emissions from Coal Mining Activities
Total methane releases as a result of coal mining activities will be the summation of
emissions from underground mining (ventilation and degasilkation systems), surface
mining, and post mining activities. The IPCC recommends that emissions be estimated for
each of these categories, in tonnes of CH4, then aggregated to determine total national
methane releases. To the extent that methane is recovered and used that would
otherwise have been released to the atmosphere during coal mining, the recovered
quantity should be subtracted from the .emission total.
Availability and Quality of Activity Data
Data are readily available to develop general emissions estimates using the Tier I
approach-die Global Average Methods for underground, surface and post-mining
activities. For these estimates, the only required data are country statistics on
underground and surface coal production, which are available from domestic sources, such
as energy ministries, or from the OECD/IEA, which publishes Coal Information (e.g.,
I990a) and Coal Statistics (e.g.. I990b). These data are thought to be reliable.
The IPCC recommends that countries involve their coal mining personnel in the
development of emissions estimates as much as possible, because of the improved
accuracy of emissions estimates prepared with more detailed coal and mining data. The
availability and quality of data collected by mining personnel for mine safety purposes
should be assessed on a case-by-case basis, however, to ensure that it can be appropriately
used for preparing emissions estimates.
The IPCC further recommends that future efforts attempc to better characterize the
factors affecting methane emissions from coal mining for tiliose countries and emission
sources with limited data, so as to develop more refined emission factors. Specific
activities should include:
• Obtaining more data on coal and geologic characteristics in selected coal-producing
countries;
• Monitoring emissions from surface mines and post-mining activities; and,
• Monitoring emissions from closed or inactive mining operations, and some other
potential methane sources, such as mine water.
1.8.3 CO2 Emissions From Burning Coal
Deposits And Waste Piles
Marland and Rotty (1984) estimated that burning of coal in coal deposits is less than 0.3%
of total coal produced and that burning of all coal in waste banks in the US. over a ten
year period would represent less than 1% of U.S. coal consumption. Subsequently, they
chose to ignore these emissions.
If these sources are estimated, the amount of coal burned in waste piles and coal deposits
must be specified along with an emission coefficient that (represents the percentage of coal
that is carbon times the percentage of carbon oxidized. We suggest an arbitrary value of
50% of the carbon present in the coal to represent this emission coefficient; this value
would be highly variable from one country to another and one site to another. This
assumption of 50% for an emission coefficient should be evaluated to determine its
validity. The formula for calculating these emissions would be:
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Emissions from Coal Burning (I03 mt C) = (Quantity of Coal Burning; I03
mt)
X Emission Coefficient
(i.e., Percentage of Carbon in Coal X Percentage of Carbon Oxidized;
default value is 50%)
Note that other GHG's such as N2O, CO, NOX, etc. are also emitted from combustion of
coal wastes
1.8.4 CO2 Emissions From SO2 Scrubbing
When SO2 scrubbing (or flue gas desulfuization) technology is used in conjunction with
combustion of coal, the process which removes sulfur dioxide from the Hue gas also
releases CO2 from the chemical interactions during the process. This can be considered a
fugitive emission resulting from coal utilization, since the emissions are emitted only as a
result of the combustion process. Typically calcium carbonate reacts with sulfur oxides in
flue gas to produce calcium sulfate and release carbon dioxide. Marland and Rotty (1984)
suggest that CO2 emissions from SO2 scrubbing are small enough to be ignored in global
calculations. However, for completeness, some national experts may wish to included this
subcategory.
To estimate carbon emissions from SO2 scrubbing, the approach is derived from Grubb
(1989) with slight modifications. In Grubb's approach, carbon emissions would equal the
total amount of coal scrubbed times the fraction of sulfur by weight in the coal, adjusted
for the differences in molecular weight between carbon and sulfur (12/32). Since this
procedure assumes that all of the sulfur is removed, it should be adjusted by the sulfur
removal efficiency of die desulfurization process (an average removal efficiency of 90% is
suggested). The formula for calculating these emissions would be:
Emissions from SO2 Scrubbing (I03 mt C) = (Total Coal Consumption; I03
mt)
X Fraction Scrubbed (%)
X Average Sulfur Content of Coal Scrubbed (%)
X Sulfur Removal Efficiency (default value is 90%)
X 12/32 (i.e., the Carbon/Sulfur Ratio)
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1.9 Fugitive Emissions From Oil And Natural
Gas Systems
1.9.1 Overview
This section covers "fugitive" emissions of greenhouse gases- (GHGs) from oil and natural
gas systems. This category includes all emissions from production, processing handling and
transport of oil and natural gas, and their derivative products, which are not the result of
combustion of these oil, gas or other products as fuel. It excludes use of oil and gas of
derived fuel products to provide energy for internal use in energy production processing
and transport The latter are considered fuel combustion and treated in earlier section of
this chapter.
By far the most important components of this sub-category are methane emissions from
oil and gas production, and from all aspects of natural gas systems. The bulk of this section
identifies and describes different methane emission sources from oil and gas systems and
presents a default methodology to estimate these emissions, on a national level. The basis
for estimating methane emissions from oil and gas systems is, however, weak for most
regions at this time. Only a few detailed studies of emissions rates have been performed.
Better emissions data that take into account region- and country-specific factors are
needed. Currently available information indicates that gas production and transportation in
the former USSR and Eastern Europe are by far the most important sources, accounting
for perhaps 50 percent of global CH4 emissions from oil and gas systems. Because the data
are so limited at present, global and regional estimates of CH4 emissions from this source
category, should be considered highly uncertain.
Oil and gas systems are also responsible for significant fugitive emissions of CO2, NOX, and
especially NMVOC during production from venting and flaring; and from leakages at all
stages. No original work has been done on CO^ NOX, and NMVOC emission from oil and
natural gas systems, within the IPCC/OECD programme, consistent with the programmes
priorities for the first phase. Considerable information has been developed in other
national and international emissions inventory programmes,, however, because of the
importance of these gases for local and regional (as well as global) pollution. This is
especially the case
for NMVOC as fugitive emissions from production, processing and distribution of oil and
oil products is a major source of this gas. References to some of the available sources of
emission factor data and other information for calculating emissions from this category are
provided in the last sub-section of this section.
1.9.2 Fugitive Methane Emissions
Background
Fugitive emissions from oil and gas systems are an important source of methane, probably
accounting for about 30 to 60 Tg per year of emissions. Meithane is emitted during Oil and
gas production, processing, storage, transportation and distribution. "Fugitive" sources of
emissions within oil and gas systems include: releases during normal operation, such as
emissions associated with venting and flaring during oil and gas production, chronic leaks
or discharges from process vents; emissions during routine maintenance, such as pipeline
repair; and emissions during system upsets and accidents.
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Oil and Natural Gas System Overview: Oil and gas systems are divided into three
main parts, for this discussion:
I Oil and Gas Production: Oil and gas are withdrawn from underground formations
using on-shore and off-shore wells. Oil and gas are frequently withdrawn
simultaneously from the same geologic formation, and then separated. Gathering lines
are generally used to bring the crude oil and raw gas streams to one or more
collection point(s) within a production field. Because methane is the major
component of natural gas, leaks or venting from these systems result in methane
emissions. Oil and/or gas are produced in approximately 186 countries worldwide.
2 Crude Oil Transportation and Refining: Crude oil is transported by pipelines
and tankers to refineries. Often, the crude oil is stored in tanks for a period of time.
Methane is usually found in the crude oil stream, and leaks or venting of vapours
from these facilities result in methane emissions, particularly from crude oil tankering.
Methane emissions from crude oil streams are strongly dependent on the original
methane content of the crude oil and its preparation for transport.
Refineries process crude oil into a variety of hydrocarbon products such as gasoline
and kerosene. During the refining process, methane and other hydrocarbons are
separated and methane may be leaked or vented in some processes;. Refinery
outputs, referred to as "refined products," generally contain negligible amounts of
methane. Consequently, methane emissions are not estimated for transporting and
distributing refined products. Refineries are operated in 102 countries.
3 Natural Gas Processing, Transportation, and Distribution: Natural gas is
processed to recover heavier hydrocarbons, such as ethane, propane and butane, and
to prepare the dried gas for transporting to consumers. Most gas is transported
through transmission and distribution pipelines. A small amount of gas is shipped by
tanker as liquefied natural gas (LNG). Because only a small portion of gas is
transported as LNG, emissions from LNG facilities are not included in default
emission methods.
The following are the main processing, transportation, and distribution activities:
• Gas processing plane Natural gas is usually processed in gas plants to produce
products with specific characteristics. Depending on the composition of the
'unprocessed gas, it is dried and a variety of processes may be used to remove
most of the heavier hydrocarbons, or condensate, from the gits. The processed
gas is then injected into the natural gas transmission system and the heavier
hydrocarbons are marketed separately. Unintentional leaks of methane occur
during natural gas processing.
• Transmission pipelines: Transmission facilities are high pressure lines that
transport gas from production fields, processing plants, storage facilities, and
other sources of supply over long distances to distribution centres, or large
volume customers. Although transmission lines are usually buried, a variety of
above ground facilities support the overall system including metering stations,
maintenance facilities, and compressor stations located along the pipeline
routes.
Compressor stations, which maintain the pressure in the pipeline, generally include
upstream scrubbers where the incoming gas is cleaned of particles and liquids before
entering the compressors. Reciprocating engines and turbines are used to drive the
compressors. Compressor stations normally use pipeline gas to fuel the
compressors. They also use the gas to fuel electric power generators to meet the
station's electricity requirements. ,
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• Distribution systems: Distribution pipelines are extensive networks of generally
small diameter, low pressure pipelines. Gas enters distribution networks from
transmission systems at "gate stations" where the pressure is reduced for
distribution within cities or towns.
Sources of Methane Emissions in the Oil and Natural Gas Systems: Emissions
from oil and gas systems can be categorized into: (I) emissions during normal operations;
(2) routine maintenance; and (3) system upsets and accidents. In Table 1-38 these emission
types are linked to the different stages in oil and gas systems. Typically the majority of
emissions are from normal operations.
I Normal Operations: Normal operations are the day-to-day operations of a facility
absent the occurrence of abnormal conditions. Emissions from normal operations
can be divided into two main source categories: (I) venting and flaring and (2)
discharges from process vents, chronic leaks, etc.
Venting and Flaring - Venting and flaring refers to the disposal of gas that cannot be
contained or otherwise handled. Such venting and flaring activities are associated with
combined oil and gas production and take place in production areas where gas
pipeline infrastructure is incomplete and the natural jps is not injected into reservoirs
(Emissions from process vents are not included here - see next sub-section).
Venting activities release methane because the vented gas typically has a high
methane content If the excess gas is burned in flares the emissions of methane will
depend on how efficient the burning processes are. Generally the combustion
efficiency for flare sources are assumed to be between 95 and 100%. However a new
study based upon measurements carried out by Norwegian Oil Industry Association -
OLF (Forthcoming) indicates very small amounts of unburned methane from flares,
less than 0.1% of the gas burned. To estimate the methane emissions from venting
and flaring activities satisfactorily it is required to know the flare efficiency rates and
the distributed quantity of gas vented and gas flared.
The combined quantity of gas vented and flared is reported by countries that produce
oil and gas (Barns et al., 1990). A few countries also are able to report the
distribution between gas vented and gas flared. The reliability of the data is
questionable in many cases because vented and flared amounts normally are not
metered and are often an "accounting balance" whereby withdrawal totals are set
equal to disposition totals by putting any discrepancies in the estimates in the
category of vented and flared.
Discharges from Process Vents. Chronic Leaks etc. - Methane emissions will also
occur when gas pipelines infrastructure is available and the market for natural gas is
well developed. Oil and gas production, gas processing, oil and gas transportation and
gas distribution facilities emit methane due to a wide variety of operating practices
and factors, including:
• Emissions from pneumatic devices (gas-operated controls such as valves and
actuators). These emissions depend on the size, type, and age of the devices,
the frequency of their operation, and the quality of their maintenance.
• Leaks from system components. These emissions are unintentional and usually
continuous releases associated with leaks from the failure of a seal or the
development of a flaw, crack or hole in a component designed to contain or
convey oil or gas. Connections, valves, flanges, instruments, and compressor
shafts can develop leaks from flawed or worn seals, while pipelines and storage
tanks can develop leaks from cracks or from corrosion.
• Emissions from process vents, such as vents on glycol dehydrators and vents on
crude oil tankers and storage tanks. Vapours, including methane, are emitted
PART 2
1.105
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EMISSIONS FROM ENERGY
from the vents as part of the normal operation of the facilities. However such
process vents are minor methane sources in most gas production facilities.
• Emissions from starting and stopping reciprocating engines and turbines.
• Emission during drilling activities, e.g., gas migration from reservoirs through
wells.
2 Routine Maintenance: Routine maintenance includes regular and periodic activities
performed in the operation of the facility. These activities may be conducted
frequently, such as launching and receiving scrapers (pigs) in a pipeline, or
infrequently, such as evacuation of pipes ("blowdown") for periodic testing or repair.
In each case, the required procedures release gas from the affected equipment.
Releases also occur during maintenance of wells ("well workovers") and during
replacement or maintenance of fittings.
3 System Upsets and Accidents: System upsets are unplanned events in the
system, the most common of which is a sudden pressure surge resulting from the
failure of a pressure regulator. The potential for unplanned pressure surges is
considered during facility design, and facilities are provided with pressure relief
systems to protect the equipment from damage due to the increased pressure.
Relief systems vary in design. In some cases, gases released through relief valves
may be collected and transported to a flare for combustion or re-compressed and
re-injected into the system. In these cases, methane emissions associated with
pressure relief events will be small. In older facilities, relief systems may vent gases
directly into the atmosphere or may send gases to flare systems where complete
combustion may not be achieved.
The frequency of system upsets varies with the facility design and operating practices.
In particular, facilities operating well below capacity are less likely to experience
system upsets and related emissions. Emissions associated with accidents are also
included under the category of upsets. Occasionally, gas transmission and distribution
pipelines are accidentally ruptured by construction equipment or other activities.
These ruptures not only result in methane emissions, but they can be extremely
hazardous as well.
Table 1-38 lists those emissions types that are the most important: sources within
each segment of the oil and gas industry. Based on available information, the sources
listed as "major" account for the majority of emissions from each segment Because
•data are limited and there is considerable diversity among oil and gas systems
throughout the world, other potential sources are also listed which may, in some
cases, be important contributors to emissions.
Available Emissions Data: Only very limited data are available that describe methane
emissions from natural gas and oil systems. Estimating the types of emissions defined above
is complicated by the fact that emissions rates from similar systems in various regions and
countries are influenced by differences in the industry's supporting infrastructure,
operating and maintenance practices, and level of technology used. Because natural gas and
oil systems are comprised of a complex set of facilities, simple relationships between
emissions and gross descriptors of the systems are not easily defined.
1.106
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EMISSIONS FROM ENERGY
TABLE 1-38
EMISSIONS FROM OIL AND NATURAL GAS SYSTEMS
Segment
Oil and Gas Production
Oil and Gas Wells
Gathering lines
Treatment facilities
Grade oil transportation and
Refining
Pipelines
Tankers
Storage tanks
Refineries
Natural Gas Processing,
Transportation, and
Distribution
Gas Plants
Underground storage
reservoirs
Transmission Pipelines
Distribution Pipelines
Major Emission Sources
Venting
Normal operations: fugitive
emissions; deliberate releases from
pneumatic devices and process vents
Normal operations: fugitive
emissions; deliberate releases frortii
process vents at refineries, during
loading and unloading of tankers arid
storage tanks
Normal operations: fugitive
emissions; deliberate releases from
pneumatic devices and process vents
Other Potential Emission
Sources
Flare and combustion in e.g. gas
turbines, 1C engines.
Routine maintenance
System upsets and Accidents
Combustion in e.g. gas turbines, 1C
engines.
Routine maintenance
System upsets and Accidents
Combustion in e.g. gas turbines, 1C
engines
Routine maintenance
System upsets and Accidents
To estimate emissions, the available published data were reviewed to identify emissions
estimates that include: a detailed consideration of the physical attributes of oil and gas
systems; theoperation and maintenance characteristics of key facilities; and country- or
region-specific factors that may influence emissions rates. The following data were
identified:
• Surveys: Several studies have surveyed system operators to estimate emissions as a
portion of production or throughput. These studies include Alphatania (1989), AGA
(1989), and INGAA (1989). While these studies provide a basis for identifying the
portions of the systems that operators believe are likdy to be major sources of
emissions, they are not based on detailed assessments of emissions rates.
Consequently, these studies do not provide a quantitative basis for making estimates
of methane emissions from oil and natural gas systems;.
• Estimates Based on Reported Unaccounted For Gas: Several studies, such as
Hitchcock and Wechsler (1972), Abrahamson (1989) and Cicerone and Oremland
(1988), have assumed that emissions can be approximated by reported amounts of
"unaccounted for" gas. Unaccounted for gas is defined as the difference between gas
production and gas consumption on an annual basis. Like estimates of venting and
flaring, unaccounted for gas often is used as an accounting convenience to balance
company or national production and consumption estimates.
• The applicability of unaccounted for gas estimates is very limited because factors
other than emissions account for the majority of the gas listed as unaccounted
for, including: meter inaccuracies, use of gas within the system itself, theft of gas
(PG&E, 1990), variations in temperature and pressure and differences in billing
cycles and accounting procedures between companies receiving and delivering
the gas (INGAA, 1989). Furthermore, because known releases of gas are not
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1.107
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EMISSIONS FROM ENERGY
reflected in unaccounted for gas estimates, such as emissions from compressor
exhaust, the unaccounted for gas estimates cannot unambiguously be
considered an upper or lower bound on emissions.
Engineering Studies and Measurements: A small number of studies are based on
detailed engineering and/or field measurement analyses. Several
engineering analyses have considered the manner in which actual or
model facilities are built and operated, andextrapolate facility emissions
to a system-wide basis. Several measurement studies have measured
emissions from operating facilities or identified actual leaks and
extrapolated these measurements to estimate system-wide emissions.
TABLE 1-39.
SUMMARY OF EMISSION FACTORS
Data source!
EPA (1992)
All emissions have been
scaled down to 1988 energy
consumption or production
levels
Study methodology
Compilation of estimates
from detailed engineering
analyses and field
measurement studies
Emission factors
Applicability
Oil and Gas Production:
290 - 4670 kg/PJ of oil produced
39590- 104220 kg/PJ of gas
produced
2870 - 13920 kg/PJ of total oil and
gas produced
Emissions from non-gas
producing oil wells including
fugitive emissions and routine
maintenance emissions in the
US.
Emissions from gas production,
including fugitive emissions,
dehydrator venting, bleeding
from pneumatic devices, routine
maintenance, and systems upsets
in the U.S.
Venting and flaring emissions
from oil and gas production and
fugitive emissions from gas
producing oil wells in the U.S.
Crude Oil Transportation and Refining:
110- 1666 kg/PJ of oil refined
Emissions from oil refining and
related oil storage tanks in the
U.S.
Natural Gas Processing, Transmission acid Distribution:
59660- II 66 10 kg/PJ of gas
consumed
Emissions from gas processing,
transmission and distribution
including fugitive emissions,
dehydrator venting, bleeding
from pneumatic devices, routine
maintenance, and system upsets
in the U.S.
Generally, data from engineering studies and measurements are the preferred
basis for making estimates. Unfortunately, only several of these types of studies
have been performed, which limits the ability to estimate emissions nationally,
regionally and globally from oil and gas systems. Table 1-39 lists the studies
identified and the information they contain. The emissions estimates from the
1.1 08
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EMISSIONS FROM ENERGY
studies in the table have been converted to common units of kilograms of
emissions per petajoule of energy (kg/PJ). A total of 5 studies are listed, with
emissions estimates for portions of North America (EPA, 1992), Eastern Europe
(Rabchuk et al.. 1991), and Western Europe (Schneider-Fresenius et al.. 1989,
TABLE 1-39
CONTINUED): SUMMARY OF EMISSION FACTORS
Data source
Rabchuk etal. (1991)
Schneider-Fresenius et al.
(1989)
Barns etal. (1990)
Study Methodology
Compilation of estimates from
previous measurement studies
and from official data for 1 989
Compilation of results from the
Batelle study's 1988 literature
survey
Compilation of official reports
and projections on
international emissions
Emission Factors
Applicability
Oil and Gas Production:
218000 - 567600 kg/P) of gas
produced
Emissions from leakages at gas wells
including routine equipment venting
in the former USSR
Natural Gas Processing, Transmission and Distribution:
340000 - 715800 kg/PJ of gas
consumed
Emissions from leakages at
underground storage facilities,
compressor stations, linear part of
main pipelines and distribution
networks in the former USSR
Oil and Gas Production:
14800 - 27000 kg/PJ of gas produced
Emissions from gas production and
treatment facilities in Germany
Natural Gas Processing, Transmission and Distribution:
58000 - 1 1 1000 kg/PJ of gas consumed
Emissions from transportation,
distribution and storage of gas in
Germany
Oil and Gas Production:
96000 kg/PJ of natural gas production
6300- 1019000 kg/PJ of gas
production
Emissions from gas production and
separation facilities in the world
Emissions from venting and flaring
activity by region of the world
Norwegian SPCA, 1992 and Norwegian Oil Industry Association, 1993 in prep.).
Additionally, Barns etal. (1990) present estimates based on a global assessment. Additional
studies of this type are needed to improve the basis for making emissions estimates.
1.9.3 Methodology For Estimatiing Emissions
A three tiered approach is presented for estimating CH4 emissions from oil and gas
systems. The specific tiers are listed below in the order of increasing sophistication, data
requirements, and accuracy:
• Tier I - Production Based Average Emissions Factors,
• Tier 2 - Mass Balance, and
• Tier 3 - Rigorous Source-specific Evaluations
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1.109
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TABLE 1-39 (CONTINUED)
SUMMARY OF EMISSION FACTORS
Data Source
Norwegian SPCA (1992)
Norwegian Oil Industry
Association (OLF), 1993 (in
prep.)
Study Methodology
Summary of emissions
estimates for 1989 based on
nformation and measurements
collected from oil companies
and industry associations
Summary of emission estimates
based on information and
measurements collected from
oil associations
Emission Factors
Applicability
Oil and Gas Production:
12800 kg/PJ of gas produced
3200 kg/Pj of gas produced
200 kg/PJ of gas produced
Emissions from cold vents and
Fugitive emissions
Flare and gas turbines
Pre-production emissions (Well
testing)
Crude oil transportation:
2500 kg/PJ oil tankered
Emissions from offshore loading of
crude oil
Natural gas processing:
1800 kg/PJ of gas processed
Emissions from one Norwegian gas
processing terminal
Oil and Gas Production:
3000 - 7500 kg/PJ of gas produced
1 00 - 400 kg/Pj of gas produced
Emissions from cold vents and
fugitive emissions
Pre-production emissions
The intent is to allow countries to select an approach or combination of approaches that
may be most suited to their circumstances. Some important considerations may include
the relative cohtribution of oil and gas systems to total CH4 emissions for the country, the
available information and resources, and the complexity of the local oil and gas industry.
Regardless of the method that is used, the results must be aggregated back to a Tier I
format to provide a consistent basis for comparison. Moreover, CH4 emissions due to
incomplete combustion by flares and other process combustion equipment are excluded
from these calculations; they are accounted for separately in the section on CH4 emissions
from combustion and industry.
Tier I - Production Based Average Emission Factors
This is the simplest approach for estimating CH4 emission from oil and gas systems, and is
the only one that does not require any direct interaction with the oil and gas industry and
associated regulatory agencies. Accordingly, it is the least reliable of the methods.
The required activity data may be easily referenced from a published documents of the IEA
or the United Nations Statistical Division, and the necessary emission factors are provided
in this document. The production based average emission factors approach can be used as
a starting point for any country, and may be all that is needed where the emissions from a
country's oil and gas industry are comparatively small and/or where data or resources are
not available to pursue a more rigorous approach.
I.I 10
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EMISSIONS FROM ENERGY
Production Base: To estimate emissions, the following steps are recommended as a
default estimation procedure:
I Global oil and gas systems have been divided into regions with the objective of each
region having relatively homogeneous oil and gas system characteristics. Each country
should decide which system characterisation best fits its own oil and gas system(s).
2 For each region, representative emissions factors for ea.ch emissions type within each
segment have been selected with the objective of taking into account the various
system designs and operating practices found in each region.
3 For each country, country-specific activity levels must be obtained and multiplied by
the appropriate emissions factor. Emissions factor for countries should be selected
from those corresponding to the appropriate region.
As more data become available for oil and gas producing activities within different
countries, the default methodology described above (including activity data and emission
factors) should be refined. Each step is discussed below in more detail.
Regional Definitions: Regions have been defined considering the limitations in data on
emissions factors and activity levels, but also recognizing the key differences in oil and gas
systems that are found globally. The following 5 regions are recommended at this time:
• U.S. and Canada: The U.S is a large producer and importer of oil and is a large
producer of gas. Detailed emissions estimates are available for the U.S.
• Former USSR and Eastern Europe: Indications are that emissions rates from this
region are much higher than emissions rates from other regions, in particular for the
gas system. This region includes the former USSR (which is by far the largest oil and
gas producer in the region), Albania, Bulgaria, Czech & Slovak Republics, Hungary,
Poland, Romania, and the former Yugoslavia.
• Western Europe: This region is a net importer of oil and gas, and mainly produces
oil and gas off shore. This region includes: Austria, Belgium, Denmark, Faroe Islands,
Finland, France, Germany, Gibraltar, Greece, Iceland, Ireland, Italy, Luxembourg,
Malta, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and UK.
• Other Oil Exporting Countries: This region includes the world's other major oil
producing countries: the 13 OPEC members (Algeria, Gabon, Libya, Nigeria, Ecuador,
Venezuela, Indonesia, Iran, Iraq, Kuwait, Qatar, Saudi Arabia and the United Arab
Emirates) and Mexico. Generally, these countries produce large quantities of oil and
have limited markets for gas.
• Rest of the World: This region includes the remaining countries of Asia, Africa,
Middle East, Oceania and Latin America.
In defining these regions, countries were aggregated with relatively similar oil and gas
systems. Additional investigation would likely improve the definition of the regions.
Emissions Factors: As discussed above, the basis for selecting emissions factors is weak
because very few detailed studies of emissions have been performed. Using the
information summarized in Table 1-39, emissions factors should be selected by industry
segment and emissions type for each of the regions. In some cases data from the U.S. were
used when region-specific information was not available.
Tables 2-42 through 2-46 list suggested emissions factors for each region. Emissions
factors from EPA (1992) were used for the U.S. Key emissions factors for Eastern Europe
and the Former USSR were taken from Rabchuk et al. and EJarns et al. Estimates were
used for emissions factors for venting and flaring for the several regions, including Eastern
Europe.
PART 2
I. I I I
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EMISSIONS FROM ENERGY
Studies by Schneider-Fresenius et al. and Norwegian SPCA were adopted as
representative of emissions factors for Western European gas production and venting and
flaring. No region-specific data were available for the Other Oil Exporting countries and
the Rest of the World. Emissions factors in these regions are expected to fall between the
relatively low rates found in North America and Western Europe and tine relatively high
rates found in Eastern Europe. Consequently, a range of emissions factors is suggested for
these regions unless more information can be obtained.
Activity Levels: Data on the quantity of oil and gas produced, refined, and consumed can
be obtained from the IEA or the U.N. Statistical Division. Sources are described in the
introduction to this chapter. Data on oil refining capacity can be used to approximate oil
refined. Data on oil tankered were not available by region. It is important for national
experts to ensure that production figures used in calculation of apparent consumption for
CO2 emissions estimates (described in section B of this Chapter) are consistent with
those used in this section.
Tier 2 - Mass Balance
The mass balance approach employs standard, generally easy-to-obtain, oil and gas data
(i.e., production volumes, gas-to oil ratios (GORs), and gas compositions) to estimate the
maximum amount of methane that could potentially be available for emissions to the
atmosphere by different sectors of the oil and gas industry. These amounts are then
adjusted to reflect actual emissions by applying appropriate system adjustment and loss
factors. The system adjustment factors account for the amount of gas that is disposed by
control devices, consumed by combustion equipment, conserved, or reinjected. Loss
factors account for specific losses from these control/utilization systems.
A particular advantage of conducting a mass balance analysis is that it helps avoid any
double counting of emissions. This may be most important in the crude oil transportation
and refining sector where the methane fraction is difficult to track.
The basic procedures for performing the mass balance calculations are delineated below
by sector of the oil and gas industry. Total CH4 emissions is the sum of emissions for each
of these sectors. Default data and factors are provided where possible.
Oil and Associated Gas Production: Emissions from oil and associated gas production
may be estimated using the relation,
M,
'STP
where
Eoil =
Qoil =
GOR =
YAGCH4=
MCH4 =
gc
rnass (Tg) of CH4 emitted to the atmosphere due to oil and associated gas production,
volume of oil produced (mj /y),
gas to oil ratio (mj /mj ),
average mole fraction of CH4 in the associated gas (dimensionless),
molecular weight of CH4
16,043.
volume (m* ) of I kmole of gas at reference temperature and pressure of the GOR factor
(e.g., 23.645 mj at 15 C and 101.325 kPa),
system adjustment factor which accounts for any gas utilization, conservation and disposal
schemes and their effectiveness (dimensionless).
constant of proportionality,
IO"7.
I.I 12
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EMISSIONS FROM ENERGY
The value of the system adjustment factor is determined using the equation presented
below.
KO« =
p
L+(
fared
where,
QAG = volume of associated gas disposed by control devices (e.g., flare
systems), consumed (burned as fuel) or conserved (reinjected or sold)
and therefore unavailable for emission to the atmosphere (nT3 ), and
L = loss factors that account for emissions from the gas control and
utilization systems (e.g., losses due to fugitive equipment leaks,
blowdown activities, and use of natural gas as the supply medium for
gas-operated devices). (Note: Emissions due to incomplete combustion
are accounted for in the section on CH4 from combustion and
industry.)
If none of the associated gas is controlled or utilized (i.e., L< = I for all x), then the system
adjustment factor (K) is equal to one. This situation occurs when it is not economical to
conserve or reinject the gas (e.g., there is no local market for the gas and the volumes are
relatively small) and when venting of the gas is preferable to disposal by flaring. It is not
necessary to evaluate the different paths by which CH4 emissions may occur (e.g., fugitive
equipment leaks, process venting, system upsets, etc.) in these cases since the end effect is
the same: essentially all the CH4 produced is emitted to the atmosphere.
If all of the associated gas is controlled or utilized (i.e., none is vented), then the value of
the system adjustment factor will be nearly equal to zero. The difference from zero is due
to fugitive leaks, blowdown activities and other system losses.
Crude Oil Transportation and Refining: The crude oil from production facilities will
initially contain a certain amount of gas in solution. This gas, particularly the CH4 fraction,
evaporates quickly as this oil progresses through the storage and transportation systems
enroute to the refinery. When the oil reaches the refinery, it is usually fully weathered and
essentially free of any CH4 .
Accordingly, the basic mass balance relation for oil transportation and refining activities
may be expressed as follows:
A
CH.
where,
FSG =
YSGCH4
gc
solution gas factor (m3 /m3 ),
mole fraction of CH4 in the solution gas (dimensionless),
system adjustment factor to account for the amount of vapour collected
and subsequently flared, incinerated or recovered, and
constant of proportionality,
10-9.
PART 2
I.! 13
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EMISSIONS FROM ENERGY
The value of the solution gas factor and the corresponding mole fraction of methane is
determined by the type of crude oil (light, medium, heavy, or crude bitumen), the
composition of the associated gas, and the initial vapour pressure of the crude oil when it
is placed in the storage tanks or compartments at the production site. Typically, the initial
vapour pressure will be equal to the operating pressure of the first vessel upstream of the
storage facilities.
Table I -40 presents some estimated values for these two parameters at onshore and
offshore facilities. Better estimates may be determined by performing site specific process
simulations.
The value of the system adjustment factor is determined using the equation below:
K_ I
-'"
T^oil
In the absence of any data regarding the volume of CH4 collected, the value of system
adjustment factor should be set to a default value of one.
Exploration and Drilling Losses
Total CHH emissions from the exploration and drilling sector will usually be small
compared to the amount emitted by other sectors of the oil and gas industry.
Consequently, a simple Tier I approach is perhaps most appropriate for use here.
The basic relation is shown below:
ED — Nw(,i|. . Fn
where.
ED = total CH4 emissions (Tg) from drilling and testing of oil and gas wells,
Nwcits = number of wells drilled and tested, and
FD = average amount of CH4 emitted per well (Tg/well).
Gas Systems - Production, Processing and Transmission: Methane emissions from
gas systems may be estimated by applying appropriate loss factors to the total volume of
gas that passes through the different stages of the system, and by adding to this value
emissions do to accidental releases (e.g., pipeline ruptures and well blowouts). This latter
component can be quite significant for gas systems in developing countries.
TABLE 1-40 SOLUTION GAS FACTORS AND CORRESPONDING CH4 MODE FRACTIONS FOR DIFFERENT TYPES
OF CRUDE OIL PRODUCTION AT ON SHORE AND OFFSHORE FACILITIES
Type of Crude Oil
Light
Medium
Heavy (Primary)
Heavy (Thermal)
Onshore Facilities
FSG
3.3 to 5.0
3.2 to S.O
1.0
8.3
YCH4
0.5642
0.1001
0.8723
0.6666
Offshore Facilities
FSG
n.a.
n.a.
n.a.
n.a.
YCH4
n.a.
n.a.
n.a.
n.a.
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EMISSIONS FROM ENERGY
The resulting mass balance relation for gas systems is as follows:
gas Logos'\gasG gasp gasj ^accidents-' gasCH' CHJ/'°c
where,
Egas
Qgas
Lgas_
total CH4 emissions (Tg) from gas systems,
total volume of natural gas produced into the gas system (possibly including some
associated gas) (1113),
loss factors for the gathering/production (G), processing (P) and transmission (T) stages
of the system (dimensionless),
Qaccidents = total volume of unburned natural gas released into the atmosphere due to major
accidents such as pipeline ruptures and well blowouts (mj), and
gc
average mole fraction of CH4 in the produced gas dimensionless),
constant of proportionality,
ID'7
The loss factor for a given stage "i" of the gas system may be estimated using a relation,
0, +0
Meats, ^venting.
gas~ Q
1 ^as
volume of gas lost to the atmosphere due: to fugitive equipment leaks (mj ), and
where,
Qleaksi
Qventingi = volume of gas lost to the atmosphere duei to process venting and use of natural gas as
the supply medium for gas operated devices (m3).
Table 1-41 presents some default values for the different loss factors.
TABLE 1-41
DEFAULT LOSS FACTORS FOR DIFFERENT STAGES OF ONSHORE AND OFFSHORE NATURAL GAS
SYSTEMS.
Stage
Gathering/Production
Processing
Transmission
Onshore
0.2 to 1.0
0.04 to 0.10
0,03 to ?
Offshore
n.a.
n.a.
n.a.
Tier 3 - Rigorous Source-specific Evaluations
Rigorous source-specific evaluations will generally involve compiling the following types of
information and may require significant interaction with industry and associated regulatory
agencies:
• detailed inventories of the amount and types of process infrastructure (e.g., wells,
minor field installations, a major production and processing facilities),
PART 2
I.I 15
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EMISSIONS FROM ENERGY
• production disposition analyses (e.g., oil and gas production; vented, flared and
reinjected volumes of gas; and fuel gas consumption),
• accidental releases (i.e., well blow-outs and pipeline ruptures),
• typical design and operating practices and their impact on the overall level of
emission control.
The amount of emissions is then assessed by applying appropriate emission factors,
empirical correlations, process simulation results, and field measurements to these data.
Some examples of detailed emission inventories that have been developed in this manner
are listed below:
• U.S. Environmental Protection Agency (U.S. EPA). Anthropogenic Methane Emissions
in the United States. Estimates for 1990: Report to the Congress. October 1992.
• Picard, D.J., B.D. Ross, and D.W.H. Koon. A Detailed Inventory of CH4 and VOC
Emissions from Upstream Oil and Gas Operations in Alberta. Clearstone
Engineerineg Ltd., for the Canadian Petroleum Association, Mars 1992.
• UK Offshore Operators Association Ltd. Methane Emissions From Offshore Oil &
Gas Exploration & Production Activities. Submitted to The Watt Committee on
Energy. 1993.
• Norwegian Oil Industry Association - OLF. Report from OLF Environmental
Programme - Phase 2. Will be available Mars 1993.
1.9.4 Uncertainty
Because relatively few detailed emissions studies have been conducted, the emissions
estimates resulting from application of these methodologies must be considered very
uncertain. The overall magnitude of the emissions that will be obtained for some countries
is driven by two key studies:
• Rabchuk et al. report that emissions from gas production and transportation in the
former USSR is very high, about 3 to 7 percent of total gas production. Recent visits
to this region indicate that system construction, maintenance, and operations may be
consistent with high emissions rates (Craig, 1992). However, a better quantitative
evaluation is needed to validate the current emissions estimates.
• Barns et al. report emissions from venting and flaring by region. The emissions
estimates for the OPEC countries are relatively high, and account for most of the
emissions from this category! The safety concerns associated with venting, and the
value of re-injecting gas into oil reservoirs to maintain reservoir pressures, would
tend to question the high emissions estimates. Improved data are needed to resolve
this question.
The adoption of emissions factor estimates from EPA (1992) for various regions also adds
uncertainty to the overall estimates. U.S. oil and gas production facilities and refineries are
subject to emission control requirements. The U.S. emissions factors, particularly for
refining, may under-estimate emissions in other regions. Nevertheless, this may not be a
significant uncertainty since, if the emissions factors for oil production and oil refining
were increased by a factor of 10 for the entire world, the estimate of total global
emissions would only increase by about I to 6 Tg for 1988.
I.I 16
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EMISSIONS FROM ENERGY
TABLE 1-42
U.S AND CANADA - EMISSIONS FACTORS
Emissions Type
Oil and Gas Production
Oil
Gas
Oil & Gas
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
Natural Gas Processing, Transport, and
Distribution
Gas Processing
Gas Pipelines
Gas Distribution
Emissions Factor
kg/PetajouIe
290 - 4,670 of Oil Production
39,590 - 104,220 of Gas Production
2,870 - 1 3,920 of Oil & Gas Prod.
745 of Oil Tankered
90 - 1 ,400 of Oil Refined
20 -260 of Oil Refined
59,660 - 1 16,610 of Gas Consumption
Source
EPA (1992)
EPA (1992)
EPA (1992)
API (1987)
EPA (1992)
EPA (1992)
EPA (1992)
TABLE 1-43
EASTERN EUROPE AND FORMER USSR - EMISSIONS FACTORS
Emissions Type
Oil and Gas Production
Oil
Gas
Oil & Gas
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
Natural Gas Processing, Transport, and
Distribution
Gas Processing
Gas Pipelines
Gas Distribution
Emissions Factor
kg/Petajoule
290 - 4,670 of Oil Produced
218,000 - 567,600 of Gas Produced
6,300 - 29,700 of Gas Produced
745 of Oil Tankered
90- 1,400 of Oil Refined
20 -260 of Oil Refined
340,000 - 715,800 of Gas Consumption
Source
EPA (1992)
Rabchukeial. (I9?l)
Barns etal. (19901
API (1987)
EPA (1992)
EPA (1992)
Rabchuk etal. (1991)
PART 2
I.I 17
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EMISSIONS FROM ENERGY
TABLE 1-44
WESTERN EUROPE - EMISSIONS FACTORS
Emissions Type
Emissions Factor
kg/Petajoule
Source
Oil and Gas Production
Oil
Gas
Oil & Gas
290 - 4,670 of Oil Produced
14,800 - 27,000 of Gas Produced
13,000-16,000 of Gas Produced
3,000-8,000 of Gas Produced
EPA (1992)
Schneider-Fresenius
etaUI989)
Norwegian SPCA( 1992)
OLF in prep. (1993)
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
745ofOilTankered
2,500 of Oil Tankered
90- 1,400 of Oil Refined
20 - 260 of Oil Refined
API (1987)
Norwegian SPCA( 1992)
EPA (1992)
EPA (1992)
Natural Gas Processing, Transport, and
Distribution
Gas Processing
Gas Pipelines
Gas Distribution
58,000 - 111,000 of Gas Consumption
1,800 of Gas Processed
Schneider-Fresenius
etal. (1989)
Norwegian SPCA (1992)
TABLE 1-45
OTHER OIL EXPORTING COUNTRIES - EMISSIONS FACTORS
Emissions Type
Oil and Gas Production
Oil
Gas
Oil & Gas
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
Natural Gas Processing, Transport, and
Distribution
Gas Processing
Gas Pipelines
Gas Distribution
Emissions Factor
kg/Petajoule
290 - 4,670 of Oil Produced
39,590 - 96,000 of Gas Produced
739,470 - 1,019,220 of Gas Produced
745 of Oil Tankered
90- 1,400 of Oil Refined
20 -260 of Oil Refined
1 16,610 - 340,000 of Gas Consumption
Source
EPA (1992)
EPA (1992) and Barns
etal. (1990)
Barns etal. (1990)
API (1978)
EPA (1992)
EPA (1992)
EPA (1992 and
Rabchuk etal. (1991)
1.1 18
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EMISSIONS FROM ENERGY
TABLE 1-46
REST OF THE WORLD - EMISSIONS FACTORS
Emissions Type
Oil and Gas Production
Oil
Gas
Oil & Gas
Crude Oil Transportation and Refining
Transportation
Refining
Storage Tanks
Natural Gas Processing, Transport, and
Distribution
Gas Processing
Gas Pipelines
Gas Distribution
Emissions Factor
kg/Petajoule
290 - 4,670 of Oil Produced
39,590 - 96,000 of Gas Produced
170,000 - 209,000 of Gas Produced
745 of Oil Tankered
90- 1,400 of Oil Refined
20-260 of Oil Refined
116,610-340,00 of Gas Consumption
Source
EPA (1992)
EPA (1992) and Barns etal.
(1990)
Barns etal. (1990)
API (1987)
EPA (1992)
EPA (1992)
EPA (1992 and
Rabchuketal. (1991)
Recent Revisions to Emission Factors
The above methodology and emission factors are based on the report of an expert group
convened to advise the IPCC/OECD programme on methods and data in this specific area
(Ebert, et al., 1993). Since that group delivered its report in mid 1993, a more recent
analysis (U.S. EPA, in press) has provided a somewhat different interpretation of some
emission factors. While this very detailed analysis endorses the basic tiered methodology
included in this manual, its evaluation of emission factors differs somewhat. This evaluation
was based on essentially the same set of measurement data cited herein, but draws
somewhat different results from the limited available data. The results of the recent EPA
analysis are summarized in Table I -47. The most significant differences are in natural gas
processing, transportation and distribution, where a somewhat more detailed set of
emission factor ranges are recommended for non-OECD countries. These factors include
some which are based on production of natural gas and some which are based on
consumption of natural gas (which is the case for all of the factors provided above).
Where emission factors are provided for more than one sub-category, they are intended
to be additive, and would result in somewhat higher total emissions estimates. Other
differences in this U.S. EPA analysis are that venting and flaring emissions for Western
Europe are based on oil rather than gas production, and there are minor revisions to
some factors for fugitive and other emissions from gas production.
These differences are significant, even given the overall uncertainty in this category, and
should be considered carefully by national experts in regions where emissions from this
source category are significant. It is hoped that the differences can be resolved of
explained in more detail in the final version of these Guidelines.
PART 2
I.I 19
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EMISSIONS FROM ENERGY
1.9.5 Fugitive Emissions Of Other GHGs
Methane is by far the most important greenhouse gas emitted on a "fugitive" basis from oil
and gas systems. However, other GHG's are clearly emitted from this source category and
should be included in a comprehensive national inventory. There is one type of
combustion - flaring of natural gas during production, which is consider a "fugitive"
emission.36 From this combustion, CO2 and NOX are certainly produced and other
combustion related gases - N2O, CO, and NMVOC may be emitted at least in small
quantities.
However, after methane, the most significant fugitive emissions from oil and gas
production, processing transport and distribution are of non-methane volatile organic
compounds (NMVOC). Oil and gas are largely composed of organic compounds, and
releases through evaporation or leakages are likely at all stages wherever the fuels or their
products contact the atmosphere. Fugitive emissions from refining, transport and
distribution of oil products is a major component of national NMVOC emissions in many
countries.
The IPCC/OECD programme has not yet addressed the indirect GHG's (including
NMVOC) in detail. This is consistent with the initial priorities within the programme - .
which focused on the direct greenhouse gases, CO2, CH4, and N2O. However, because
these gases are important contributors to a range of local and regional (as well as global)
atmospheric pollution problems, they have been widely studied and repotted elsewhere.
National experts interested including the other fugitive emissions of GHG's from oil and
natural gas systems should consult the existing literature which provides detailed emissions
factors and procedures for calculating emisions. Some key examples are:
• The CORINAIR Inventory: Default Emission Factors Handbook (Bouscaren, 1992);
• Proceedings of the TNO/EURASAP Workshop (TNO Inst of Environmental
Sciences, 1993)
• Emissions' Inventory Guidebook (European Environment Agency, forthcoming)
• EMEP and CORINAIR Emission Factors and Species Profiles for Organic Compounds.
(Veldt, 1991);
• U.S. EPA's Compilation of Air Pollutant Emissions Factors (AP-42), 4th Edition 1985,
(U.S. EPA, 1985), and Supplement F, (U.S. EPA, 1993);
• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory
(Stockton and Stelling, 1987)
36This is because the combustion is not for energy purposes and takes place
before gas produced is included in national energy accounts.
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EMISSIONS FROM ENERGY
TABLE 1-47
REVISED REGIONAL EMISSION FACTORS FOR METHANE FROM OIL AND GAS SYSTEMS (Kc/Pj)
Source Type
Basis
Western Europe
US & Canada
Former USSR,
Central & Eastern
Europe
Other Oil Exporting
Countries
Rest of the World
OIL & GAS PRODUCTION
Fugitive and Other
Routine Maintenance
•missions from Oil
Production
:ugitive and Other
Routine Maintenance
•missions from Gas
'reduction
Venting & Flaring from
Oil and Gas Production
Oil Produced
Gas Produced
Oil & Gas Produced1
Oil Produced
Gas Produced
300 - 5,000
15,000-27,000
1,000-3,000
-
300 - 5,000
46,000 - 84,000
3,000- 14,000
-
-
300 - 5,000
140,000-314.000
-
6,000 - 30,000
300 - 5,000
46,000 - 96,000
-
758,000- 1.046,000
300 - 5,000
46,000 - 96,000
1
175,000-209,000
CRUDE OIL TRANSPORTATION, STORAGE AND REFINING
Transportation
Refining
Storage Tanks
Oil Tankered
Oil Refined
Oil Refined
745
90-1,400
20 - 250
745
90-1,400
20 - 250
745
90- 1,400
20 - 250
745
90- 1,400
20 - 250
745
90- 1,400
20 - 250
NATURAL GAS PROCESSING, TRANSPORT AND DISTRIBUTION
Emissions from
'recessing, Distribution
and Transmission
Leekage at industrial
slants and power
stations
Leekage in the
residential and
commercial sectors
Gas Produced
Gas Consumed
Non-Residential Gas
Consumed
Residential Gas
Consumed
~
72,000- 133,000
-
-
~
57,000- 118,000
-
-
288,000 - 628,000
-
175,000 - 384,000
87,000- 192,000
288,000 (high)2
II 8,000 (low)3
0- 175,000
0 - 87,000
288,000 (high)2
II 8,000 (low)3
0-175,000
0 - 87,000
1. In the US and Canada, the emissions are based on total production of both oil and gas produced.
2. The emissions factor of 288,000 kg/Pj of gas produced is used only for the high emissions estimate.
3. The emissions factor of 1 1 8,000 kg/Pj of gas consumed is used only for the low emissions estimate.
4. Gas consumption by utilities and industries.
5. Gas consumption by the residential and commercial sectors.
PART 2
1.121
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EMISSIONS FROM ENERGY
1.9.6 References
Introduction
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OECD/IEA. I993b. Energy Balances of OECD Countries, 1990-1991. International Energy
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OECD/IEA. I993c. Energy Statistics for OECD Countries, 1990-1991. International Energy
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OECD/IEA. 1991. Greenhouse Gas Emissions: The Energy Dimension. OECD, Paris.
UN (United Nations). 1993. 1991 Energy Statistics Yearbook. United Nations, New York.
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Grubb, M.J. 1989. On Coefficients for Determining Greenhouse Gas Emissions From Fossil Fuel
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Agency, OECD, Paris.
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Department of Environmental Technology, Apeldoorn, Netherlands.
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IPCC/OECD Programme on National GHG Inventories. 1991. Proceedings of a Workshop
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PART 2
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EMISSIONS FROM ENERGY
Emissions From Coal Mining, Handling And Utilization
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Procedure for Estimation and Results for 1950-1982. TeHus 36b:232-261.
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EMISSIONS FROM ENERGY
OECD/IEA (1990b), Coal Statistics. Paris, France.
OECD (1991), Estimation of Greenhouse Gas Emissions and Sinks. Final Report from the
OECD Experts Meeting, Paris, France, 18-21 February 1991.
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Foundation.
Pilcher, R.C., et al. (1991), Assessment of the Potential for Economic Development and
Utilization of Coalbed Methane in Poland. EPA/400/1-91/032, U.S. Environmental
Protection Agency, Washington, D.C.
Polish Central Mining Institute (1990), Official Polish Methane Emissions Data for 1989.
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the U.S. Congress. U.S. Environmental Protection Agency, Office of Policy, Planning and
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USEPA (1993b), Anthropogenic Methane Emissions in the United States: Estimates for
1990. Report to the U.S. Congress. U.S. Environmental Protection Agency, Office of Air
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USGS (1993), personal communication.
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Essen, Germany, Gesamtverband des deutschen Steinkohlenbergbaus, personal
communication.
Emissions From Oil And Gas Systems
Abrahamson D. 1989. "Relative Greenhouse Effect of Fossil Fuels and the Critical
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Alphatania. 1989. Methane Leakage from Natural Gas Operations. The Alphatania Group.
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Barns, D.W. andJ.A. Edmonds. 1990. "An Evaluation of the Relationship Between the
Production and Use of Energy and Atmospheric Methane Emissions," prepared for the
Office of Energy Research, U.S. Department of Energy, Washington, D.C.
Cicerone, R.J. and R.S. Oremland. 1988. "Biogeochemical Aspects of Atmospheric
Methane," Global Biogeochemical Cycles, Vol. 2, No. 4, Dec. 1988, pp. 299 - 327.
Craig, Bruce. 1991. Personal communication. U.S. Environmental Protection Agency,
Global Change Division, Washington, D.C.
Ebert, C, D. Picard, P. Pope, and A. Roslund. 1993. Methane Emissions from Oil and
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(ed.). Proceedings of an International IPCC Workshop: Methane and Nitrous Oxides, Methods in
National Emissions Inventories and Options for Control, 3-5 February 1993, Amersfoort, NL RIVM
Report no. 481507003, Bilthoven, NL, July.
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Soviet Natural Gas Supply System," prepared for the Battelle Pacific Northwest
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in the Natural Gas Supply System of the Federal Republic of Germany - Contribution of
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the United States - Report to Congress," prepared by Global Change Division, Office of
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profiles for emissions of organic compounds. IMET-TNO report 91-299.
PART 2
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CHAPTER 2
INDUSTRIAL PROCESSES
PART 2
2.1
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INDUSTRIAL PROCESSES
2.1 Overview
Greenhouse gas emissions are produced from a variety of non-energy related industrial
activities. The main emission sources are industrial production processes which chemically
or physically transform materials from one state to another. During these production
processes, many different greenhouse gases (CO2, CH4, N2O, CO) can be released.
Cement production is perhaps the most notable example of such an industrial
(transformation) process that releases a significant amount of CO2.
In some instances industrial process emissions are produced in combination with energy
combustion emissions. To the extent that these emissions are the direct result of the fuel
combustion, they are included as energy emissions not industrial process emissions. This
will avoid double-counting since these emissions should be estimated as a result of energy
consumption activities (see the Energy Chapter). Also, all emissions, including evaporative
emissions which occur in energy transformation activities (e.g., petroleum refining) are
discussed in the Energy Chapter. Other evaporative emissions, primarily of NMVOC, are
not included in the Industrial Processes Chapter. These sources, also referred to as "area
sources" are now treated separately in the Solvent Use Chapter. Refer to Volume I,
Greenhouse Gas Inventory Reporting Instructions for further discussion of source category
definitions and reporting issues.
At this time, cement production is the only process for which a detailed methodology is
proposed for emissions estimation. However, it has been recommended that all processes
generating emissions be identified, the level of emissions from these processes evaluated,
and appropriate emission estimation methodologies developed. Some preliminary
information is provided for CO2, CH4 and N2O emissions estimation from industrial
processes. Experts have suggested general additions to the range of source activities to be
addressed in this Guidelines document. Some of these are listed in Table 2-1 of this
chapter. This is not intended to be a definitive list, but rather to be a working list which
will evolve over time as methods improve.
2.1.1 Chapter Organization
The remainder of the chapter is organized by gases of concern. The next section discusses
CO2 emissions from industrial processes including cement manufacturing. The next two
sections summarize available preliminary information on industrial process sources of CH4
and N2O respectively. The final section discusses sources of other GHGs from industrial
processes. The IPCC/OECD programme has not yet addressed these gases in detail.
Instead, this section identifies some of the major information sources already available
from other international and national emissions inventory programs. The sections in this
chapter dealing with industrial process emissions give background information on the
sources and uncertainties associated with estimating emissions for the most important
gases and source categories. This is consistent with the initial priorities under the
IPCC/OECD programme. National experts are encouraged to report any other relevant
data, along with documentation of methods and assumptions used. This will greatly assist
in the development of more complete methods for future editions of the IPCC Guidelines.
PART 2
2.3
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INDUSTRY
2.2 Carbon Dioxide Emissions From Industrial
Processes
2.2.1 Cement Manufacturing
Carbon dioxide emitted during the cement production process represents the most
important non-energy industrial process source of global carbon dioxide emissions.
Cement production accounts for about 2.4 percent of total global industrial and energy
CO2 emissions (Marland et at., 1989). Carbon dioxide is produced during the production
of clinker, an intermediate product from which cement is made. High temperatures in
cement kilns chemically change raw materials into cement clinker (grayish-black pellets
about the size of ^-inch-diameter marbles). Specifically, calcium carbonate (CaCO3) from
limestone, chalk, or other calcium-rich materials is heated, forming lime (calcium oxide or
CaO) and carbon dioxide in a process called calcination or calcining:
CaCO3 + Heat -> CaO + CO2
This lime combines with silica-containing materials, provided to the kiln as clays or shales,
to form dicalcium or tricalcium silicates, two of the four major compounds in cement
clinker (Griffin, 1987). The clinker is then removed from the kiln, cooled, and pulverized
into an extremely fine gray powder. During this operation a small amount of gypsum is
added to regulate the setting time of the cement. The finished product is called "portland"
cement.
Most of the cement currently produced in the world is portland cement type, which
contains 60 to 67 percent lime by weight. Other speciality cements are lower in lime, but
are typically used in small quantities. Research is underway on cement formulations that
have similar structural properties to portland cement, but require less lime (Tresouthick
and Mishulovich, 1990). Carbon dioxide emissions from cement production are essentially
directly proportional to lime content, so production of cements lower in lime yield less
CO2.
Because carbon dioxide is emitted during clinker production (rather than cement
production itself), emission estimates should be based on the lime content and production
of clinker. Estimating emissions based on the lime content and production of finished cement
ignores the consideration that some domestic cement may be made from imported
clinker, or that some finished cement may use additional lime that is not accounted for in
the cement calculations. Clinker statistics, however, may not be readily available in some
countries. If this is the case, cement statistics can be used. The differences between the
lime content and production of clinker and cement, in most countries, are not significant
enough to affect the emission estimates.
Estimating CO2 Emissions from Cement
Estimation of CO2 emissions from cement production is accomplished by applying an
emission factor, in tonnes of CO2 released per tonne of clinker produced, to the annual
clinker output.1 The emission factor is the product of the fraction of lime used in the
cement clinker and a constant reflecting the mass of CO2 released per unit lime:
1 Note that the estimation of CO2 from energy use during cement production is
explained in the energy chapter; these emissions should be reported under Energy-fuel
combustion activities.
2.4
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INDUSTRY
= Fraction CaO x (44 g/mole CO2 / 56.08 g/hnole CaO)
or
EFdinker = Fraction CaO x 0.785
There are two methods for calculating this emission factor. The first is to assume an
average CaO fraction in clinker. Since clinker is mixed with gypsum, which contains less
lime per unit, to make cement, clinker has a higher lime percentage than finished cement.
The average clinker lime percentage was found to be 64.6%2. This number was multiplied
by the molecular weight ratio of CO2/CaO (0.785) to achieve a clinker emissions factor of
0.5071 tonnes of CO2/tonne of clinker produced.
EFd,-nker = 0.646 * 0.785 = 0.5071
A second method is to assemble country or regional data on clinker production by type
and clinker CaO content by type, then calculate a weighted average for cement lime
content in the country. In most countries, the difference in the results of these two
methods is likely to be small; any error in the lime content assumption is likely to be
smaller than the uncertainty in clinker and cement production figures (Griffin, 1987).
If information on clinker production is not readily available, an emissions factor in tonnes
of CO2 released per tonne of cement produced can be applied to annual cement
production instead. This approach has been followed by Marland et al. (1989), who took
the average CaO content of cement to be 63.5%, yielding an emission factor of 0.4985
COj/cement (0.136 te CO2 as C/te cement).
EFcement = 0.635* 0.785
0.4985
Additional research indicates that "masonry cement", as opposed to "portland cement"
requires additional lime, over and above the lime used in its clinker. The following formula
can be used to account for this activity:
a x (All Cement Production) x ((I -(I /1 +b) x c) x 0.785 = tonnes CO2 from
CaO added to masonry cement
where:
a = fraction of all cement produced that is masonry cement (e.g. O.I, 0.2)
b = fraction of weight added to masonry cement by non-plasticizer additives such as
lime, slag, and shale (e.g. .03, .05)
c = fraction of weight of non-plasticizer additives that is lime (e.g. 0.6, 0.8)
a x (All Cement Production) = Masonry Cement Production
((l-l/l +b) x c) = fraction of lime in masonry cement not attributable to clinker
((I -1 /1 +b) x c) x 0.785 = an emissions factor of CO2 from masonry cement additives
1 - Gregg Marland, ORNL, Personal communication.
PART 2
2.5
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INDUSTRY
Data Sources
International cement production data are available from the United Nations (1988) and
from the U.S. Bureau of Mines (1988). In some countries, national data may be available
from appropriate government ministries. There is substantial overlap between the U.S.
Bureau of Mines and the UN data sets, but the former is more complete. Published
information is also available from the European Cement Association (CEMBUREAU,
1990).
Recommended Method
The recommended method for estimating CO2 emissions from cement production is to
multiply the most reliable figures available for tonnes of clinker produced by an emission
factor of 0.5071 CO7/clinker. Alternatively, cement production can be multiplied by an
emission factor of 0.4985 COi/cement.
2.2.2 Other Industrial Processes
There are many other processes which may be significant sources of CO2 for some
countries. In the national inventories collected by the IPCC/OECD joint programme, CO2
emissions from the following processes have been reported:
Production: coke, iron, steel, aluminum, ferro alloys, carbon carbide,
fertilizers, limestone, lime, dolomite, bricks, glass, paper, pulp, and
print.
Consumption: limestone
In estimating emissions from these sources, it is expected that most categories will use the
following simple method:
Physical units of production (e.g. tonnes) x Emission Factor = Emissions
(e.g. tonnes CO7/tonne
product)
As more national data is collected and evaluated in this area, we expect to be able to
develop and provide formulae and default emissions for additional categories (IPCC, 1993).
Methane Emissions From Industrial Processes
Most global methane budget estimates do not included a large and diverse group of minor
industrial sources which emit methane into the atmosphere. This source class deals with
non-combustion processes in industry, which excludes methane emitted from fuel
combustion in the production process. Individually, these sources emit minor quantities of
methane, but collectively their contribution to the global budget may be significant.
Non-combustion processes include the following:
• primary metals production and associated processes (coke, sinter, pig iron, steel);
• chemical manufacturing processes; production of a variety of chemicals like carbon
black, ethylene, dichloro-ethylene, styrene and methanol.
Table 2.2 summarizes estimated global methane emissions from some specific non-
combustion industrial processes. These processes include: production of iron/steel (coke
included); oil refining; production of carbon black, ethylene, dichloroethylene, styrene and
methanol.
2.6
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INDUSTRY
Iron & steel production, appearing as the major source in this category, may be further
subdivided in coke, sinter and pig iron production as sources of process emissions. The
other processes that have been analyzed for process emissions of methane are of minor
importance due to low estimated production level and/or emission. (Berdowski et al.,
I993b)
Uncertainties
Further study and clarification of the sources included in this category and their global
average emission factors are required in order to arrive at final conclusions with respect
to the importance of this source category in total global methane emissions. Table 2.3
presents the estimated global total methane emissions from non-combustion industrial
processes along with estimated ranges. The estimated range presented in the table
illustrates the uncertainty of point estimates. Wide ranges, such as those presented, imply
the need for further examination of the data used, particularly for iron and steel industries
and oil refineries.
Methane from industrial processes is estimated to be only 3% of all fossil fuel related CH4
emissions, and hence seems negligible on a global scale. However, it is recommended that
national experts make a critical review of all possible sources in this category because
their inclusion may be quite relevant in some national inventories.
N2O Emissions From Industrial Processes
Non-combustion industry processes resulting in N2O emissions are recognized as
important anthropogenic contributors to global nitrous oxide emissions. It is estimated
that this source category represents 10 to 50% of anthropogenic N2O emissions and 3 to
20% of all global emissions of N2O emissions. (IPCC, 1992) Three sources of N2O
emissions have been identified within this category: adipic acid production, nitric acid
production, and other chemicals production.
Adipic acid
Adipic acid is a raw material primarily used for the manufacturing of 6,6 nylon and is
generally produced from cyclohexane. Cyclohexane is used to produce so-called "KA",
which is subsequently oxidized with nitric acid to produce adipic acid. This oxidation step
unavoidably produces nitrous oxide as a side-product with an associated emission factor
(for unabated emissions) of 300 g N2O/kg adipic acid produced. (Thiemens and Trogler,
1991)
Figures for global adipic acid production are estimated to be 1.8 Tg, with associated
emissions of 0.37 Tg N2O or 0.24 Tg N2O-N. This emissions estimate assumes a total of
0.55 Tg of N2O initially produced during the adipic acid production process with an
average abatement of about 32%. (Reimer et al., 1992) The abatement of N2O results
from the treatment of the off-gases in a reductive furnace. A number of adipic acid
producers treat the off-gases with the aim of reducing NOX emissions, but the treatment
also coincidentally destroys nitrous oxide. (Reimer et al., 1992, and McCulIoch, 1993).
Nitric acid
Nitric acid (HNO3)is a raw material used mainly as a feedstock in fertilizer production. As
mentioned above, nitric acid is also a component in the production process of adipic acid.
Of the 50 to 65 Tg nitric acid globally produced annually, about 1.6 Tg is used by the adipic
acid industry. (Reimer et al., 1992) Off-gas measurements at. DuPont showed emission
factors ranging from 2-9 g N2O/kg HNO3 or 7-27 g N2O-N/l
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INDUSTRY
Although no abatement techniques are specifically directed at removing nitrous oxide, the
emission factors presented include any effect of other abatement systems that may be
applied. (McCulioch, 1993) The generation of N2O in this production process is likely to
be accidental, not unavoidable. The representativity of the DuPont nitric acid production
process or of the derived emission factor for N2O for the global production of nitric acid
is not known. (Olivier, 1993a)
Emissions calculation methodology
Estimation of N2O emissions from adipic acid and nitric acid production requires four
distinct assumptions or type of data: I) production data on adipic acid and nitric acid,
respectively; 2) default emission factors (without specific N2O abatement); 3) applicable
abatement factors for N2O; and 4) the part of the activity level for which a specific
abatement factor applies.
The recommended calculation scheme is described by the following basic formula:
N2O Emissions = 2 (Activity,, x
where:
Activity
EF,
= production level (tonne of product annually produced)
= Effective Emission Factor (kg/tonne product)
= Emission Factor EF, x abatement factor;
i = Total Activity of type i
j = Part of activities of type i with a specific applicable abatement factor
Abatement factor = I - percentage abated / 100
Total emissions for a country is the sum across activities and sub-activities with distinct
abatement levels. In the absence of information on the abatement factor one may either
chose to disregard it or instead use a range for this factor. When production figures are
not available, instead production capacity figures of national production facilities can be
used to estimate associated emissions. (Olivier, 1993b) Table 2.4 lists the emission factors
and level of abatement discussed in the adipic acid and nitric acid sections.
In general, emission abatement also needs to be considered when estimating emissions
from industrial sources. Technical options for reducing the N2O emissions have been
developed. Table 2.5 lists some of these options. Some of the options may not be
technically or economically feasible at the current time, but further research should
improve the possibilities.
Other chemicals production
The industrial production of other chemical compounds has been identified as a source of
nitrous oxide. There has not been enough study to determine whether this represents a
significant global source of N2O. Emissions reported in the Netherlands in the chemical
industry showed an emission of about 1.7 Gg N2O in 1990 from the production of
chemicals other than adipic acid or nitric acid. (Project Emission Registration, 1990)
The precise nature and location of the processes that produce these emissions are not
known. Suggested sources are related to either a process using a N-compound or a
catalytic reduction step. Although global N2O emissions from this source category will
probably be small as compared to emissions associated with adipic acid and nitric acid
production, further investigation is recommended. It is possible that other industrial
sources make significant contributions at a national level. The Netherlands reports about
2.8
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INDUSTRY
25% of the total energy related emissions of national N2O in 1988-1990, or about 6.6 kton
N2O/yr. (Van den Born et al., 1991) The study suggests thai: any process in which a
nitrogen compound is used or catalytic reduction is applied can be a source of N2O
emissions. (Olivier, 1993a)
Emissions calculation methodo/ogy
It is recommended that national inventories include the adipic acid and nitric acid
production processes at this time, adipic acid and nitric acid manufacture should be
included as source categories in national inventories. Other industrial processes can be
included if the national experts have data on relevant processes. It is likely that these
figures will be highly country specific, since both process conditions and application of
abatement technology of some kind may be very different for different countries.
It is recommended that further research on industrial processes focus on N2O emissions
in measurements of the off-gases and other emissions. A more comprehensive study of
industrial processes and N2O emission measurements at production sites may reveal more
processes in which nitrous oxide is released. More representative measurements will
further reduce the uncertainty in the current estimate of global emissions from this source
category. (Olivier, 1993b)
Other GHGs From Industrial Processes
Although the major GHG emissions have been dealt with above, there are other GHG
emissions from these processes. These may be significant sources for some countries. The
following simple method can be used to estimate these GHGs:
Physical units of production
(e.g. tonnes)
x Emission Factor
(e.g. tonnes CO2/
tonne product)
= Emissions
The IPCC/OECD documents do not provide specific examples of emissions factors for
other GHGs. For information on emissions factors and estimation procedures for GHGs
which are currently not provided in this chapter, experts should consult extensive existing
literature developed by other emissions inventory programmes. Some key examples are:
• CORINAIR. Default Emissions Handbook (Bouscaren, 1992);
• U.S. EPA's Compilation of Air Pollutant Emissions Factors (AP-42) (US EPA, 1985)
and Supplement F (AP-42) (US EPA, 1993);
• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory
(Stockton and Stelling, 1985).
• Proceedings of the TNO/EURASAP Workshop (TNO Inst. of Environmental
Sciences, 1993).
• Emission Inventory Guidebook (European Environmental Agency, 1994).
2.2.3 Conclusion
There is not much information available on national emission factors and levels of
abatement for emissions of GHG from industrial processes. This chapter describes basic
methods and global mean values for emission factors for the following GHG sources:
• CO2 from cement production;
• N2O from adipic acid production;
PART 2
2.9
-------
INDUSTRY
• NZO nitric acid production.
In addition, the chapter discusses possible sources and basic approaches to estimate CO2,
CH,,, and N2O from other industrial processes. National experts are encouraged to report
any relevant emissions for which data are available, along with documentation of methods
used. This will greatly assist in the development of more complete methods for future
editions of IPCC guidelines.
2.10
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INDUSTRY
TABLE 2.1
EMISSIONS FROM PRODUCTION PROCESSES
PROCESS
Cement Production
Limestone Production
Agricultural Liming
Aluminum Production
Ferro-alloy Production
Silisium Carbide Production
Coke Production
Nitric Acid Production
Nitrogen Fertilizer Production
Steel Plant (electric, BOF, etc.)
Ammonia Production
Sodium Carbonate
Urea Production
Carbon Black
Titanium Dioxide
Ethylene Production
Propylene Production
1 ,2 Dichlorothane Production
Vinylchloride Production
Polyethylene Low Density
Production
Polyethylene High Density
Production
Polyvinylchloride Production
Polypropylene Production
Styrene Butadiene
ABS Resins
Ethylene Oxide
Formaldehyde Production
Ethylbenzene Production
Styrene Butadiene Latex
Styrene Butadiene Rubber
Phtalic Anhydride Production
Acrylonitrile Production
Chipboard Production
Paper Pulp Production
Bread Production
Wine Production
Beer Production
Spirits Production
Nitrate Production
POLLUTANTS
NOX
X
X
X
X
X
NMVO
C
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
CH4
X
X
X
CO
X
X
X
X
C02
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
N2O
X
X
X
PART 2
2.1
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INDUSTRY
TABLE 2.2
GLOBAL EMISSION FACTORS AND EMISSIONS OF METHANE FROM INDUSTRIAL MANUFACTURING PROCESSES
EXCLUDING COMBUSTION EMISSIONS MENTIONED IN TABLE 4.
Manufacturing process •*•••-' ..;.
Integrated iron & steel plant
of which: Coke production
Sinter production
Pig iron production
Carbon black
Ethylene
Dichloroethylene
Styrene
Methanol
Production *)
(T?i ;
750
400
650
550
5
40
20
15
15
Emission factor
(g/kg).
<3
0.5
0.5
0.9
II
1
0.4
4
2
Emission
OB)'
<2
0.2
0.3
0.5
0.06
0.04
0.01
0.06
0.03
References
emission factor.
[1-6] ,
[1,5.6]
[3.4,6]
P]
[3], [7]
[3], [7]
[3], [7]
[3], [7]
[3], [7]
Note:
*) Production data are estimated from various data sources (UN a.o.).
Source: Berdowski et at., I993b
[1] Schade, H. (1980)
P] Stallings.R.L(l984)
[3] Shareef, G.S., WA Buder, LA. Bravo and M.B. Stockton (1988)
[4] Stoehr,R^.(l982)
[5] Prefect Emission registration.
[6] Barnard. W.R. (1990)
[7] Stockton. M.B. and J.H.E Stelling (1987)
TABLE 2.3
ESTIMATED GLOBAL METHANE EMISSIONS FROM INDUSTRIAL PROCESSES (Tg CH4 PER YEAR)
Source
category
Emission
estimate
Estimate
range
Industrial processes
> Iron & steel
0.4- 4
> Chemical manufacturing
0.2
O.I - 2
1 Miscellaneous
0.6
0.6
Total
3.3
1.6 - 9.5
Source: Berdowski et al.,!993a
2.12
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INDUSTRY
TABLE 2.4
ESTIMATED EMISSION FACTORS AND ABATEMENT FACTORS FOR INDUSTRIAL SOURCES OF t*iO
Activity
Adipic acid production
Nitric acid production
Emission factor
(gN20/kg)
300
NA
Emission factor range
(gN20/kg)
-
2-9
Percentage
abated
32
0
Global average value for total AA industry; global value for Du Pont: 5.3%; national uncertainty range not available.
** (7-27 g N2O-N/HNO3-N)
**"* At present no specific N2O abatement techniques are in use.
Source: (Olivier, I993b) and references therein (Thiemens and Trogler, 1991); (McCulioch, 1993).
TABLE 2.5
OVERVIEW OF TECHNICAL OPTIONS FOR N2<3 REDUCTION
Source
Global strength
(Tg N20-N/yr)
Options
Industry
I. adipic acid
0.4-0.6
Incineration (technically and economically
feasible); research programme
On long term:
• alternative production process for
adipic acid
• alternatives for applications of 6,6-
nylon
2. nitric acid
0.1-0.3
On long term:
• alternative production process for
nitric acid
• alternatives for applications of 6-nyIon
• modify/optimize production processes
Source: (Olivier, I993b)
2.3 References
Barnard, W.R. (1990). Emission factors for iron and steel sources - criteria and toxic
pollutants. EPA-600/2-90-024 (PB 90-242314).
Berdowski, J., J. Olivier, C. Veldt. (1993)a. Methane from Fuel Combustion and Industrial
Processes. In A.R. van Amstel (ed.), Proceeding of an International IPCC Workshop on
Methane and Nitrous Oxide: Methods in National Emissions Inventories and Options for
Control. RIVM Report no. 481507003, Bilthoven, The Netherlands.
Berdowski, J.J.M., L Beck, S. Piccot, J.G.J. Olivier, & C. Veldt (1993)b. Working Group
Report; Methane Emissions from Fuel Combustion and Industrial Processes. In A.R. van
Amstel (ed.), Proceeding of an International IPCC Workshop on Methane and Nitrous
Oxide: Methods in National Emissions Inventories and Options for Control. RIVM Report
no. 481507003, Bilthoven, The Netherlands.
PART 2
2.13
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INDUSTRY
Bouscaren R. (1992). CORINAIR Inventory, Default Emissions Handbook, 2nd ed., 12: 1-3.
Published by CITEPA.
CEMBUREAU. 1990. World Cement Market in Figures and World Statistics Review.
European Environmental Agency. 1994. Emissions Inventory Guidebook.
Griffin, R.C. 1987. CO2 release from cement production, 1950-1985. In Marland, G., T.A.
Boden, R.C. Griffin, S.F. Huang, P. Kanciruk, and T.R. Nelson. Estimates of CO2 Emissions
from Fossil Fuel Burning and Cement Manufacturing, Based on the United Nations Energy
Statistics and the U.S. Bureau of Mines Cement Manufacturing Data. Report #ORNL/CDIAC-
25, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak
Ridge, Tennessee. May 1989. 643-680.
IPCC, 1992. Climate Change 1992. The Supplementary Report to the IPCC Scientific
Assessment Published for The Intergovernmental Panel on Climate Change (IPCC),
World Meteorological Organization/United Nations Environment Programme. Cambridge
University Press. Edited by J.T. Houghton, G.J. Jenkins, and j.J. Ephraums.
IPCC parts I & II, 1993. National GHG Inventories: Transparency in Estimation and
Reporting, p. 11. Prepared by The Intergovernmental Panel on Climate Change (IPCC) and
Organization for Economic Co-operation and Development, World Meteorological
Organization/United Nations Environment Programme.
Marland, G., T.A. Boden, R.C. Griffin, S.F. Huang, P. Kanciruk, and T.R. Nelson. 1989.
Estimates of C02 Emissions from Fossil Fuel Burning and Cement Manufacturing, Based on the
United Nations Energy Statistics and the U.S. Bureau of Mines Cement Manufacturing Data.
Report #ORNL/CDIAC-25, Carbon Dioxide Information Analysis Center, Oak Ridge
National Laboratory, Oak Ridge, Tennessee. May.
McCulloch, A. [ICI] (1993). Personal communication 21-1-93.
Olivier,]. (I993)a. Nitrous Oxide Emissions from Industrial Processes. In A.R. van Amstel
(ed.). Proceeding of an International IPCC Workshop on Methane and Nitrous Oxide:
Methods in National Emissions Inventories and Options for Control. RIVM Report no.
481507003, Bilthoven, The Netherlands.
Olivier,]. (I993)b. Working Group Report: Nitrous Oxide Emissions from Fuel
Combustion and Industrial Processes. In A.R. van Amstel (ed.), Proceeding of an
International IPCC Workshop on Methane and Nitrous Oxide: Methods in National
Emissions Inventories and Options for Control. RIVM Report no. 481507003, Bilthoven,
The Netherlands.
Project Emission registration. Ministry of Housing, Physical Planning and the Environment
(Mln. VROM), The Hague, The Netherlands.
Reimer, R.A., R.A. Parrett and C.S. Slaten (1992). Abatement of N2O emission produced in
adipic acid. Proc. of 5th Int. Workshop on Nitrous Oxide emissions, Tsukuba (JP), July I-3,
1992.
Schade, H. (1980). Die Schadstoffemissionen der Eisen- und Stahlindustrie in den
Belastungsgebieten Ruhrgebiet-West und Ruhrgebiet-Ost Schriftenr. d. Landesanstalt fur
Immissionsschutz des Landes N.W. 52 55-62.
Selzer, H. (1989). Energiebedingte Methanemissionen. Ludwig-Bolkow-Systemtechnik
GmbH, quoting Frische, Emissions-Matrix 1989 (without further reference).
Shareef, G.S., W.A. Butler, L.A. Bravo and M.B. Stockton (1988). Air emissions species
manual Vol. I, Volatile organic Compounds (VOC) Species profiles. EPA-450/2-88-003a (PB
88-215792); Addendum (1989), EPA-450/2-88-003c (PB 90-146416).
2.14
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INDUSTRY
Stallings, R.L (1984). Metallurgical industries: compilation of emission factors and control
technologies. EPA-600/2-84-003 (PB 84-141548).
Stockton M.B., and J.H.E. Stelling. 1987. Criteria Pollutant Emission Factors for the 1985
NAPAP Emissions Inventory. U.S. EPA Washington, Ouverage, EPA-600/7-87-015 XV-211.
Stoehr, R.A. (1982). Organic emissions from iron ore sinter-ing plants. EPA-600/2-82-091
(PB 83-116897).
Thiemens, M.H. and W.C Trogler (1991). Nylon production: an unknown source of
atmospheric nitrous oxide. Science 251 932-934.
TNO Institute of Environmental Sciences. 1993. Proceedings of the TNO/EURASAP
Workshop on the Reliability of VOC Emission Databases. Edited by H.P. Baars, P.J.H.
Builtjes, M.P.J. Pulles, C. Veldt. IMW-TNO Publication P 93/040. Delft, The Netherlands.
Tresouthick, S.W., and A. Mishulovich. 1990. Energy and environment considerations for
the cement industry. In conference proceedings Energy and Environment in the 21st Century.
Massachusetts Institute of Technology, Cambridge, Massachusetts. March 26-28, 1990. B-
IIOtoB-123
United Nations, 1988. United Nations Statistical Yearbook. United Nations, New York.
U.S. Bureau of the Mines. 1988. Cement Minerals Yearbook, authored by Wilton Johnson.
U.S. Bureau of the Mines, U.S. Department of the Interior, Washington, D.C.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. 1985.
Compilation of Air Pollutant Emission Factors (Fourth Edition), Volume I: Stationary Point
and Area Sources. EPA-AP-42 (GPO 055-000-00251-7), Research Triangle Park.
U.S. Environmental Protection Agency. 1993. Office of Air Quality Planning and Standards.
1985. Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and Area
Sources. EPA-AP-42, Supplement F.
Van den Born, G.J., A.F. Bouwman, J.G.J. Olivier and R.J. Swart (1991). The emission of
greenhouse gases in the Netherlands. RIVM, Bilthoven, July 1991. RIVM report 222 901
003.
PART 2
2.15
-------
-------
CHAPTER 3
SOLVENT USE
PART 2
3.1
-------
-------
SOLVENTS
SOLVENT USE
3.1 Overview
Solvents and related compounds are important for greenhouse gas (GHG) and other
emission inventories because they are a significant source of emissions of non-methane '
volatile organic compounds (NMVOC). No other GHGs are emitted in significant amounts
from this category, which includes chemical cleaning substances used in dry cleaning,
printing, metal degreasing, and a variety of industrial applications as well as household use.
Also included in this category are paints, lacquers, thinners and related materials used in
coatings in a variety of industrial, commercial and household applications. Table 3.1 lists
some of the potentially important subcategories included under this source category.
All of the substances included here contain significant amounts of NMVOC. Emissions are
produced through evaporation of the volatile chemicals when these products are exposed
to air. Non-methane volatile organic compounds (NMVOC) are often emitted in significant
quantities from evaporation during the variety of dispersed activities discussed above.
These emissions are sometimes referred to as "area" sources because they occur in large
numbers of small dispersed applications, rather than from lairge centralized industrial
processes (or "point sources").
Solvent use is treated as a separate category in detailed inventory procedures (e.g.,
CORINAIR) because the nature of this area source requires a somewhat different
approach to emissions estimation than that used for calculating other emissions categories.
The draft IPCC Guidelines treats the category separately for this reason.
3.2 NMVOC Emissions from Solvent Use
NMVOC emissions estimates are characterized by high uncertainty. This is especially true
for the solvent use source category on a global scale. The contribution of this source
category is believed to be quite significant. A preliminary analysis estimated total global
NMVOC release from solvent use to be about 11 percent of total NMVOC emissions.
(Watson, et al., 1991)
Based on national GHG emissions inventories, NMVOC emissions from solvent use can
represent a much larger share of the total NMVOC emissions for some countries.
NMVOC from solvent use represents 31% of the total NMVOC emissions for both Italy
and Denmark. (ENEA, 1991, Fenger etal., 1990) The Netherlands estimates solvent use
to account for 25%, and both Finland and the United States estimate emissions to be 24%
of their total NMVOC emissions, (van den Born et al., 1991, Bostrom et al., 1992, US EPA,
1991) By contrast, emissions from solvent use in Nigeria were only 3% of the total
NMVOC. (Obioh etal., 1992)
3.2.1 Estimating Emissions
The wide variations in national emissions from solvent use highlight the differences in
solvent use in countries and some of the difficulties associated with accurately estimating
emissions from this source category.
PART 2
3.3
-------
SOLVENTS
There are two basic approaches to estimation of emissions from Solvent: Use, which
depend of the availability of data on the activities producing emissions and the emission
factors.
I Production based - In some cases, solvent or coating use is associated with
centralized industrial production activities, such as automobile and ship production,
textile manufacture, paper coating, chemical products manufacture, etc. In these
cases it is generally possible to develop NMVOC emission factors based on unit of
product output. These are based on the amount of paint, solvents, or other
chemically volatile products consumed per unit of production of the final products.
Once reasonable factors are developed it is straightforward to estimate annual
emissions based on production data which is generally available on an annual basis for
most countries. Industrial production data is also compiled and published by
international organizations (e.g., United Nations, 1992) and these data can be used to
supplement locally available data.
2 Consumption based - In many applications of paints, solvents and similar products,
the end uses are too small-scale, diverse, and dispersed to be tracked directly.
Therefore emissions estimates are generally based on total consumption (i.e., sales)
of the solvents, paints, etc. used in these applications. The assumption is that once
these products are sold to end users, they are applied and emissions produced
relatively rapidly. For most surface coating and general solvent use, this approach is
used. Emission factors are developed based on the likely ultimate release of NMVOC
to the atmosphere per unit of product consumed. These emission factors can then
be applied to sales data for the specific solvent or paint products.
The IPCC/OECD joint programme has not produced any original work on estimation of
NMVOC from solvent use. This is for two reasons. First, NMVOC is a greenhouse gas
(actually a class of gases) covered under the programme, but it has been assigned a lower
priority for national experts just initiating greenhouse gas inventory work. Most methods
development work within the IPCC/OECD programme has focused on providing methods
and default information for the first priority gases - CO2, CH4, and N2O, which are direct
greenhouse gases. Second, NMVOC is one of the gases already under heavy scrutiny in
national and international inventory programmes because of its role as a local and regional
air pollutant Hence there is a large and growing body of literature containing guidance on
estimation procedures and emission factors for NMVOC from solvent use and other
source categories. National experts who are already familiar with these procedures and
have emissions data available or under development, should report these data to the
IPCC/OECD programme, as discussed in Volume I: Reporting Instructions. Other experts
needing information should consult the existing major references such as:
• CORINAIR Default Emissions Handbook (Bouscaren, 1992);
• U.S. EPA's Compilation of Air Pollutant Emissions Factors (AP-42) (US EPA, 1985)
and Supplement F (AP-42) (US EPA, 1993);
• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory
(Stockton and Stelling, 1985).
• Proceedings of the TNO/EURASAP Workshop (TNO Inst. of Environmental
Sciences, 1993).
• Emission Inventory Guidebook (European Environmental Agency, 1994).
3.4
-------
3.2.2 Uncertainties
Because NMVOC emission controls vary widely throughout; the world, it is important for
national experts to account for the level of emission control application in their country.
Also, there may be significant differences among countries regarding the processes and
equipment used. These differences can affect the level of NMVOC emissions. Finally,
because estimates based on commodities data provide only an approximation of the
activities associated with the manufacture of all products wichin a particular subcategory,
there is a degree of uncertainty in the estimates. (Watson, eital., 1991)
SOLVENTS
TABLE 3.1
POTENTIALLY IMPORTANT SUBCATEGORIES INCLUDED UNDER SOLVENT USE
Surface coating (e.g., painting) operations
Paper coating operations
Printing and Publishing
General Solvent Use
Production of Automobiles and Trucks
Ship building -
Chemical Products Manufacture and Processing
Applications of paints, lacquer, enamel and primer to cans, wood
products, metal parts, buildings, etc. Use of thinning solvents.
Coating operations, mixing and use of thinning solvents.
Press operations, lithography, use of thinning solvents.
Vapor degreasing;, dry cleaning, textile manufacture, household
solvent use.
Surface coating, deaning/degreasing operations.
Surface coating, deaning/degreasing operations.
Solvents are used in a variety of applications in the manufacturing of
chemicals and chemical products.
3.3 References
Bostrom, S., R. Backman, M. Hupa. 1992. Greenhouse Gas Emissions in Finland 1988 and
1990, Energy, Industrial, and Transport Activities. Published by Innsinooritoimisto
Prosessikemia.
Bouscaren R. 1992. CORINAIR Inventory, Default Emissions Handbook, 2nd ed., 12: 1-3.
Published by CITEPA.
ENEA. 1991. National Emission Inventories of SOX, NOX, NMVOCs, CO, TSP, NH3, CH4,
CO2, N20 in Italy, 1985-1989.
European Environmental Agency. 1994. Emissions Inventory Guidebook.
Fenger, J., j. Fenhann, N. Kilde. 1990. Danish Budget for Greienhouse Gases. Nordic
Council of Ministers, Copenhagen. Nord 1990:97.
Obioh, I.B., A.F. Oluwole, F.A. Akeredolu. 1992. The Methodology and Status of
Greenhouse Gases (GHG) Inventory In Nigeria: 1988 Inventory Results. Paper presented
at the IPCC/OECD Workshop on National Inventories of CiHGs, Hadley Centre,
Bracknell, UK.
Stockton M.B., and J.H.E. Stelling. 1987. Criteria Pollutant Emission Factors for the 1985
NAPAP Emissions Inventory. U.S. EPA Washington, Ouverage, EPA-600/7-87-015 XV-211.
TNO Institute of Environmental Sciences. 1993. Proceedings of the TNO/EURASAP
Workshop on the Reliability of VOC Emission Databases. Edited by H.P. Baars, P.J.H.
Builtjes, M.P.j. Pulles, C. Veldt IMW-TNO Publication P 93/1340. Delft, The Netherlands.
United Nations. 1992. United Nations Statistical Yearbook. United Nations Statistical Office,
New York.
PART 2
3.5
-------
SOLVENTS
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. 1985.
Compilation of Air Pollutant Emission Factors (Fourth Edition), Volume I: Stationary Point
and Area Sources. EPA-AP-42 (GPO 055-000-00251 -7), Research Triangle Park.
U S Environmental Protection Agency, Office of Air Quality Planning and Standards. 1991.
National Air Pollutant Emission Estimates 1940-1989. EPA-450/4-91-004, Research
Triangle Park.
U.S. Environmental Protection Agency. 1993. Office of Air Quality Planning and Standards.
1985. Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and Area
Sources. EPA-AP-42, Supplement F.
van den Born. G.J., A.F. Bouwman, J.G.J. Olivier, and R.J. Swart. 1991. The Emission of
Greeenhouse Gases in the Netherlands (Report no. 222901003). National Institute of
Public Health and Environmental Protection, The Netherland.
Watson. J.J., J.A. Probert and S.D. Picot. 1991. Global Inventory of Volatile Organic Compound
Emissions from Anthropogenic Sources. Prepared for the Office of Research and
Development, USEPA. Washington, D.C.
3.6
-------
CHAPTER 4
EMISSIONS FROM AGRICULTURE
PART 2
4.1
-------
-------
AGRICULTURE
EMISSIONS FROM AGRICULTURE
4.1 Overview
Agricultural activities contribute directly to emissions of greenhouse gases through a
variety of different processes. This chapter discusses four greenhouse gas-emitting
activities:
• CH4 emissions from animals and animal wastes
— CH4 emissions from enteric fermentation in domestic animals
Methane is produced in herbivores as a by-product of enteric fermentation, a
digestive process by which carbohydrates are broken down by microorganisms
into simple molecules for absorption into the bloodstream. Both ruminant
animals (e.g., cattle, sheep) and some non-ruminant animals (e.g., pigs, horses)
produce CH4, although ruminants are the largest source since they are able to
digest cellulose due to the presence of specific microorganisms in their digestive
tracts. The amount of CH4 that is released depends on the type, age, and weight
of the animal, the quality and quantity of the feed, and the energy expenditure of
the animal.
— CH4 emissions from anaerobic decomposition of animal wastes
CH4 is produced from the decomposition of manure under anaerobic
conditions. These conditions often occur when large numbers of animals are
managed in a confined area (e.g., dairy farms, beef feedlots, and swine and
poultry farms), where manure is typically stored in large piles or disposed of in
lagoons.
• CH4 emissions from rice cultivation
Anaerobic decomposition of organic material in flooded rice fields produces
methane, which escapes to the atmosphere primarily by transport through the
rice plants. The amount emitted is believed to be & function of rice species,
number and duration of harvests, soil type and temperature, irrigation practices,
and fertilizer use.
• CH4, CO, N2O, and NOX emissions from agricultural burning:
C/-/4, CO, N2O, and NOX emissions from the prescribed burning of savannas
The burning of savannas — areas in tropical and sub-tropical formations with
continuous grass coverage — results in the instantaneous emissions of carbon
dioxide. But because the vegetation regrows between burning cycles, the
carbon dioxide released into the atmosphere is reabsorbed during the next
vegetation growth period. CO2 emissions are therefore assumed to be zero.
But savanna burning also releases gases other tha.n CO2, including methane,
carbon monoxide, nitrous oxide and oxides of nitrogen. Unlike CO2 emissions,
these are net emissions.
PART 2
4.3
-------
AGRICULTURE
CHj, CO, N20, and NOX emissions from the prescribed burning of agricultural wastes
Crop residues burning is not thought to be a net source of carbon dioxide
because the carbon released to the atmosphere is reabsorbed during the next
growing season. However crop residue burning is a significant source of
emissions of methane, carbon monoxide, nitrous oxide, and nitrogen oxides. It
is important to note that some crop residues are removed from the fields and
burned as a source of energy, especially in developing countries. Emissions from
this type of burning are dealt with in the Energy module of this manual. Crop
residue burning must be properly allocated to these two components in order
to avoid double counting.
N2O emissions from agricultural soils
Emissions of N2O from agricultural soils are primarily due to the microbial
processes of nitrification and denitrification in the soil. Increases in the amount of
N added to the soil generally result in higher N2O emissions (Bouwman, 1990).
Increases in the input of N to the soil may result from (I) atmospheric
deposition, (2) commercial fertilizer, (3) animal manures and plant residues, (4)
biological N fixation, and (5) soil organic matter mineralization.
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4.2 Methane Emission From Domestic
Livestock Enteric Fermentation And
Manure Management
4.2.1 Overview Of Methane Emissions From
Livestock
This section covers methane emissions from enteric fermentation and manure of domestic
livestock. Cattle are the most important source of methane from enteric fermentation in
most countries because of their high numbers, large size, arid ruminant digestive system.
Methane emissions from manure management are usually smaller than enteric
fermentation emissions, and are principally associated with confined animal management
facilities where manure is handled as a liquid. This section presents a brief overview of the
key factors affecting methane emissions from these sources.. The methods for estimating
these emissions are then presented.
Enteric Fermentation
Methane is produced during the normal digestive processes; of animals. The amount of
methane produced and excreted by an individual animal is dependent primarily on the
following:
• Digestive System
The type of digestive system has a significant influence on the rate of methane
emission. Ruminant animals have the highest emissions because a significant amount of
methane-producing fermentation occurs within the rumen. The main ruminant
animals are cattle, buffalo, goats, sheep, and camels. Pseudo-ruminant animals (horses,
mules, asses) and monogastric animals (swine) have relatively lower methane emissions
because much less methane-producing fermentation tikes place in their digestive
systems.
• Feed Intake
Methane is produced by the fermentation of feed within the animal's digestive system.
Generally, the higher the feed intake, the higher the methane emission. Feed intake is
positively related to animal size, growth rate, and production (e.g., milk production,
wool growth, or pregnancy).
The amount of methane emitted by a population of animals is calculated by multiplying the
emission rate per animal by the number of animals. To reflect the variation in emission
rates among animal types, the population of animals is divided into subgroups, and an
emission rate per animal is estimated for each subgroup. Population subgroups are
recommended in the method1. ' . • • .
'Countries are encouraged to carry out emissions inventory calculations at a finer level
of detail if possible. Many countries have available more detailed information than was
used in constructing default values here. Countries may wish to calculate emissions
estimates at a finer level of detail by sub-category — further disaggregating recommended
activity categories and sub-categories — or they may choose to subdivide the categories on
some other basis which they feel is appropriate to their particular national circumstances.
Working at finer levels of disaggregation does not change the basic nature of the
PART 2
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Manure Management
Livestock manure is principally composed of organic material. When this organic material
decomposes in an anaerobic environment (i.e., in the absence of oxygen) it produces
methane. Methanogenic bacteria produce the methane as part of an interrelated
population of microorganisms.
The principal factors affecting methane emission from animal manure are the amount of
manure produced and the portion of the manure that decomposes anaerobically. The
amount of manure that is produced is dependent on the amount produced per animal and
the number of animals. The portion of the manure that decomposes anaerobically depends
on how the manure is managed. When manure is stored or treated as a liquid (e.g., in
lagoons, ponds, tanks, or pits), it tends to decompose anaerobically and produce a
significant quantity of methane. When manure is handled as a solid (e.g., in stacks or pits)
or when it is deposited on pastures and rangelands, it tends to decompose aerobically and
little or no methane is produced.
To estimate methane emission, the animal population must be divided into subgroups to
reflect the varying amounts of manure produced per animal, and the manner in which the
manure is handled. Population subgroups are recommended in the method.
4.2.2 Inventory Method
Overview
The method for estimating methane emission from enteric fermentation and manure
management requires three basic steps:
Step I: Divide the livestock population into subgroups and characterize each subgroup.
Step 2: Estimate emission factors for each subgroup in terms of kilograms of methane per
animal per year — separate emission factors are required for enteric fermentation and
manure.
Step 3: Multiply the subgroup emission factors by the subgroup populations to estimate
subgroup emission, and sum across the subgroups to estimate total emission.
These three steps can be performed at varying levels of detail and complexity. This
chapter presents the following two approaches:
• Tier I
A simplified approach that relies on default emission factors drawn from previous
studies. The Tier I approach is likely to be sufficient for most animal types in most
countries.
• Tier 2
A more complex approach that requires country-specific information on livestock
characteristics and manure management practices. The Tier 2 approach is
calculations. Once emissions have been calculated at whatever is determined by the
national experts to be the most appropriate level of detail, results should also be
aggregated up to the minimum standard level of information requested in the IPCC
proposed methodology. This will allow for comparability of results among all participating
countries. The data and assumptions used for finer levels of detail should also be reported
to the IPCC to ensure transparency and replicability of methods. Volume I: Reporting
Instructions discusses these issues in more detail.
4.6
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AGRICULTURE
recommended when the data used to develop the default values do not correspond
well with the country's livestock and manure management conditions. Because cattle
characteristics vary significantly by country, it is recommended that countries with
large cattle populations consider using the Tier 2 approach for estimating methane
emissions from cattle and cattle manure. Similarly, because buffalo and swine manure
management practices vary significantly by country, it is recommended that countries
with large buffalo and swine populations consider using the Tier 2 approach for
estimating methane emissions from buffalo and swine manure.
Some countries for which livestock emissions are particularly important may wish to go
beyond the Tier 2 method and incorporate additional country-specific information in their
estimates. Although countries are encouraged to go beyond the Tier 2 approach
presented below when data are available, these more complex analyses are only briefly
discussed here. Table 4-1 summarizes the recommended approaches for the livestock
emissions included in this inventory.
Tier I Approach
This Tier I method is simplified so that only readily-available animal population data are
needed to estimate emissions. Default emission factors are presented for each of the
recommended population subgroups. Each step is discussed in turn.
The average annual population of animals is required for each of the livestock categories
listed in Table 4-1. In some cases the population fluctuates during the year. For example, a
census done before calving will give a much smaller number than a census done after
calving. A representative average of the population is therefore needed. In the case of
poultry and swirie, the number of animals produced each year exceeds the annual average
population because the animals live for less than 12 month:;. The population data can be
obtained from the FAO Production Yearbook (FAO, 1990) or similar country-specific
livestock census reports.
The dairy cow population is estimated separately from other cattle (see Table 4-2). Dairy
cows are defined in this method as mature cows that are producing milk in commercial
quantities for human consumption. This definition corresponds to the dairy cow
population reported in the FAO Production Yearbook.
In some countries the dairy cow population is comprised of two well-defined segments:
high-producing "improved" breeds in commercial operations; and low-producing cows
managed with traditional methods. These two segments can be combined, or can be
evaluated separately by defining two dairy cow categories. However, the dairy cow
category does not include cows kept principally to produce calves or to provide draft
power. Low productivity multi-purpose cows should be considered as other cattle (non-
dairy).
Data on the average milk production of dairy cattle is also required. These data are
expressed in terms of kilograms of whole fresh milk produced per year per dairy cow, and
can be obtained from the FAO Production Yearbook or similar country-specific reports. If
two or more dairy cow categories are defined, the average milk production per cow is
required for each category.
Finally, the livestock populations must be described in terms of warm, temperate, or cool
climates for purposes of estimating emissions from livestock manure. Data on the annual
PART 2
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AGRICULTURE
average temperature of the regions where livestock are managed should be used as
follows:
• Areas with annual average temperatures less than 15°C are defined as cool.
• Areas with annual average temperatures greater than 15°C and less than 25°C are
defined as temperate.
• Areas with annual average temperatures greater than 25°C are defined as warm.
For each animal population, the fraction in each climate should be estimated. These data
can be developed from country-specific climate maps and livestock census reports. To the
extent possible, the temperature data should reflect the locations where the livestock are
managed. If necessary, data from nearby cities can be used. Table4-2 summarizes the
animal population data that must be collected in Step I.
TIER lYsxEP 2* -- EMISSION "FACTORS!
.;* -^ ^ i V '•'^ - r"«r*> V -'" ""J>*4» *"-M* .
The purpose of this step is to select emission factors that are most appropriate for the
country's livestock characteristics. Default emission factors for enteric fermentation and
manure management have been drawn from previous studies, and are organized by region
for ease of use. The basis for the emission factors, described more fully under Tier 2,
includes the following:
• Enteric Fermentation:
- Feed Intake: Feed intake is estimated based on the energy intake required by the
animal for maintenance (the basic metabolic functions needed to stay alive) and
production (growth, lactation, work, and gestation). The animal characteristics
required to estimate feed intake are taken from regional and country-specific
studies and include: population structure (portion of adults and young); weight;
rate of weight gain; amount of work performed; portion of cows giving birth
each'year; and milk production per cow.
- Conversion of Feed Energy to Methane: The rate at which feed energy is converted
to methane is estimated based on the quality of the feed consumed - low
quality feed has a slightly higher methane conversion rate. Feed quality is
assessed in terms of digestibility on a regional basis.
• Manure Management
— Manure Production: Manure production is estimated based on feed intake and
digestibility, both of which are used to develop the enteric fermentation
emission factors.
- Methane Producing Potential: Methane producing potential (referred to as B0) is
the maximum amount of methane that can be produced from a given quantity of
manure. The methane producing potential varies by animal type and the quality
of the feed consumed. Reported measurements for selected animals are used.
- Methane Conversion Factor (MCF): The MCF defines the portion of the methane
producing potential (B0) that is achieved. The MCF varies with the manner in
which the manure is managed and the climate, and can theoretically range from
0 to 100 percent Manure managed as a liquid under hot conditions promotes
methane formation and emissions. These manure management conditions have
high MCFs, of 65 to 90 percent. Manure managed as dry material in cold
climates does not readily produce methane, and consequently has an MCF of
about I percent. Laboratory measurements were used to estimate MCFs for
the major manure management techniques.
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- Manure Management Practices: Regional assessments of manure management
practices are used estimate the portion of the manure that is handled with each
manure management technique.
The data used to estimate the default emission factors for enteric fermentation and
manure management are presented in Appendix A and Appendix B respectively.
Table 4-3 shows the enteric fermentation emission factors for each of the animal types
except cattle. As shown in the table, emission factors for sheep and swine vary for
developed and developing countries. The differences in the emission factors are driven by
differences in feed intake and feed characteristic assumptions (see Appendix A). Although
point estimates are given for the emission factors, an uncertainty of about +20 percent
exists due to variations in animal management and feeding. Deviations from the emission
factors can be larger than 20 percent under specialized feeding or management conditions.
Table 4-4 presents the enteric fermentation emission factors for cattle. A range of
emission factors is shown for typical regional conditions. As. shown in the table, the
emission factors vary by over a factor of four on a per head basis.
While the default emission factors shown in Table 4-4 are broadly representative of the
emission rates within each of the regions described, emission factors vary among countries
within regions. Also, as with the emission factors shown in Table 4-3, an uncertainty of
about ±20 percent exists due to variations in animal management and feeding. Animal size
and milk production are important determinants of emission rates for dairy cows.
Relatively smaller dairy cows with low levels of production are found in Asia, Africa, and
the Indian subcontinent. Relatively larger dairy cows with high levels of production are
found in North America and Western Europe.
Animal size and population structure are important determinants of emission rates for
non-dairy cattle. Relatively smaller non-dairy cattle are found in Asia, Africa, and the Indian
subcontinent. Also, many of the non-dairy cattle in these regions are young. Non-dairy
cattle in North America, Western Europe and Oceania are larger, and young cattle
constitute a smaller portion of the population2.
Select emission factors from Tables 4-2 and 4-3 by identifying the region most applicable
to the country being evaluated. The data collected on the average annual milk production
by dairy cows should be used to help select a dairy cow emission factor. If necessary,
interpolate between dairy cow emission factors shown in tine table using the data collected
on average annual milk production per head.
Table 4-5 shows the default manure management emission factors for each animal type
except cattle, buffalo, and swine. Separate emission factors are shown for developed and
developing countries, reflecting the general differences in feed intake and feed
characteristics of the animals in the two regions. These emission factors reflect the fact
that virtually all the manure from these animals is managed in dry manure management
systems, including pastures and ranges, drylots, and daily spreading on fields (Woodbury
and Hashimoto, 1993).
2 One method which has been suggested to account for animal growth (increase in
weight) over time is to use the mean live weight for a given animal category over the year
of the inventory. A weight correction factor (integrator) equal to the ratio of the
averaged annual weight and the projected end weight (which is derived from statistics) is
multiplied by the number of animals in a category to get the live weight of animals in that
category.
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AGRICULTURE
The ranges of values shown in Table 4-5 reflect the range of MCF values of I to 2 percent.
The higher value is appropriate for manure managed in warm climates, while the lower
value is appropriate for manure managed in cooler and dryer climates. A middle value is
assigned to temperate conditions. The uncertainty in the emission factors remains
substantial, however, because field measurements are required to validate the laboratory
measurements that form the basis for the MCFs used in the analysis. Appendix B
summarizes the data used to estimate the emission factors shown in Table 4-6.
The climate data collected in Step I is used to select the emission factors from Table 4-6.
A weighted average emission factor for each animal type is computed by multiplying the
percentages of the animal populations in each climate region by the emission factor for
each climate region. For example, if sheep in a developing country were 25 percent in a
temperate region and 75 percent in a warm region, the emission factor for sheep would
be estimated at about 0.2 kg/head/yr as follows:
Emission Factor = (25% x 0.16) + (75% x 0.21) = 0.1975 kg/head/yr.
An alternative way of handling these calculations is to sub-divide the category of sheep into
two populations: one in warm and one in temperate region. Calculations could then be
done separately and summed.
Because the manure from cattle, buffalo, and swine is managed in a variety of ways, •
including both dry and liquid systems, the variations in manure management practices
among regions and countries must be considered to develop emission factors for these
animals. Table 4-6 presents emission factors based on regional manure management
practices described in Safley et al. (1992).
As shown in the table, the emission factors for dairy cattle range between 81 kg/head/year
in warm parts of Western Europe to 0 kg/head/year in cool parts of Latin America. The
emission factors for non-dairy cattle range between 38 kg/head/yr in warm parts of
Western Europe to I kg/head/year in cool parts of North America and Latin America. In
addition to climate, the range of emission factors is due to the manure management
practices used in each region. For example, the emission factors for North American dairy
cattle manure and European dairy and non-dairy cattle manure are relatively high because
the manure is often managed using liquid systems that promote methane production. The
emission factors for North American non-dairy cattle and for all animals in Africa and the
Middle East are relatively low because their manure is generally managed using dry systems
that do not promote methane production.
To select emission factors from Table 4-6, first identify the appropriate region, such as
Latin America. Within that region, identify the animal type of interest. For that animal type
three values are given for the three climate regions. Compute a weighted average emission
factor for the animal type by multiplying the percentages of the animal population in each
climate region by the emission factor for each climate region. Appendix B summarizes the
estimates of manure management system usage and MCFs that underlie the emission
factors in Table 4-6.
As with the other manure management emission factors, there is substantial uncertainty in
the estimates shown in Table 4-6 because field measurements are required to validate the
laboratory measurements that form the basis for the MCFs used in the analysis, and
because there is uncertainty and variability in the manner in which manure is managed in
each region.
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4
AGRICULTURE
To estimate total emission the selected emission factors are multiplied by the associated
animal population and summed. The emission estimates should be reported in gigagrams
(Gg).3 Because the emission factors are reported in kilograms per head per year, the total
emissions in Gg is estimated as follows for each animal category:
emission factor (leg/head) x population (head) / 10* kg/Gg - emissions in Gg.
As a point of reference, in 1990 total annual global methane emissions from domestic
livestock enteric fermentation were on the order of .060 to . 100 Gg (Gibbs and Johnson,
1993). Enteric fermentation emissions from countries with large populations of livestock
may be on the order of .001 to .005 Gg per year. Countries with smaller populations of
livestock would likely have emissions of less than .001 Gg per year.
In 1.990 total annual global methane emissions from manure management was on the order
of .010 to .018 Gg (Woodbury and Hashimoto, 1993). Manure management emissions
from countries where manure is managed in liquid-based systems may be on the order of
.001 to .002 Gg per year. Countries where manure is not managed in liquid-based systems
would likely have emissions of much less than .001 Gg per year.
Tier 2 Approach For Enteric Fermentation Emissions
The Tier 2 approach is recommended for estimating methane emissions from enteric
fermentation from cattle for those countries with large cattle populations. As contrasted
with the Tier I method, this approach requires much more detailed information on the
cattle population. Using this detailed information, more precise estimates of the cattle
emission factors are developed. When the Tier 2 method is used the default emission
factors listed in Tier I for cattle are not used.
This Tier 2 approach is similar to the August 1991 OECD method (OECD, 1991), with
some modifications:
• The Blaxter and Clapperton (1965) equation is replaced with a recommended set of
methane conversion rate "rules of thumb."
• Feed energy intake requirements for pregnancy have been added.
• The energy requirements required for grazing have been reduced based on newly
available data from AAC (1990).
• The equations used to relate gross energy intake to net energy used by the animal
have been made more general to accommodate a wider variety of feed conditions.
The three steps outlined for Tier I are also used here.
To develop precise estimates of emissions, cattle should be divided into categories of
relatively homogeneous groups. For each category a representative animal is chosen and
characterized for purposes of estimating an emission factor. Table 4-7 presents a set of
recommended representative animal types for cattle. Three main categories, Mature Dairy
3 I Tg = I012 grams = I09 kilograms = I06 metric tons.
PART 2
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AGRICULTURE
Cows, Mature Non-Dairy Cattle, and Young Cattle, are recommended as the minimum set
of representative types. The sub-categories listed should be used when data are available.
In particular, the sub-population of cows providing milk to calves should be identified
among non-dairy cattle because the feed intake necessary to support milk production can
be substantial. In some countries the feedlot category is needed so that the implications of
the high-grain diets can be incorporated.
For each of the representative animal types defined, the following information is required:
• annual average population (number of head);
• average daily feed intake (megajoules (MJ) per day and kg per day of dry matter); and
• methane conversion rate (percentage of feed energy converted to methane).
Generally, data on average daily feed intake are not available, particularly for grazing
animals. Consequently, the following data should be collected for estimating the feed
intake for each representative animal type:
• weight (kg);
• average weight gain per day (kg);4
• feeding situation: confined animals; animals grazing good quality pasture; and animals
grazing over very large areas;
• milk production per day (kg/day);5
• average amount of work performed per day (hours/day);
• percent of cows that give birth in a year;6 and
• feed digestibility (%).7
These data should be obtained from country-specific cattle evaluations. Some data, such as
weight, weight gain, and milk production, may be available from production statistics. Care
should be taken to use the live cattle weights, as contrasted with slaughter weights.
Appendix B lists the data used to develop the default emission factors presented in Tier I.
Individual country data can be compared to the data presented in Appendix A to ensure
that the data collected are reasonable.
Data on methane conversion rates are also not generally available. The following rules of
thumb are recommended for the methane conversion rates:
• Developed Countries. A 6% conversion rate (±0.5%) is recommended for all cattle in
developed countries except feedlot cattle consuming diets with a large quantity of
grain. For feedlot cattle on high grain diets a rate of 4% (±0.5%) is recommended. In
circumstances where good feed resources are available (i.e., high digestibility and high
* This may be assumed to be zero for mature animals.
5 Milk production is required for dairy cows and non-dairy cows providing milk to
calves.
6 This is only relevant for mature female cows.
1 Feed digestibility is defined as the proportion of energy in the feed that is not
jxcreted in the feces. Digestibility is commonly expressed as a percentage (%). Common
ranges for feed digestibility for cattle are 50% to 60% for crop by-products and rangelands;
60% to 70% for good pastures, good preserved forages, and grain-supplemented forage-
based diets; and 75% to 85% for grain-based diets fed in feedlots.
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energy value) the lower bounds of these ranges can be used. When poorer feed
resources are available, the higher bounds are more appropriate.
• Developing Countries. Several recommendations are made for different animal
management situations in developing countries:
- All dairy cows and young cattle are recommended to have a conversion rate of
6.0% (±0.5%). These cattle are generally the best-fed cattle in these regions.
- All non-dairy, non-young stall-fed animals consuming low-quality crop by-
products are recommended to have a conversion rate of 7.0% (±0.5%) because
feed resources are particularly poor in many cases in these regions.
— Grazing cattle are recommended to have a conversion rate of 6.0% (±0.5%),
except for grazing cattle in Africa, which are recommended to have a rate of
7.0% (±0.5%) because of the forage characteristic; found in many portions of
tropical Africa.
These rules of thumb are a rough guide based on the general feed characteristics and
production practices found in many developed and developing countries. Country-specific
exceptions to these general rules of thumb should be taken into consideration as
necessary based on detailed data from cattle experts.
The emission factors for each category of cattle are estimated based on the feed intake
and methane conversion rate for the category. Feed intake is estimated based on the feed
energy requirements of the representative animals, subject to feed-intake limitations. The
net energy system described in NRC (1984 and 1989) is recommended as the starting
point for the estimates. Because the NRC system was developed for feeding conditions in
temperate regions, several adjustments were made to avoid potential biases when applied
to evaluate feed-energy intakes for tropical cattle (see Appendix C). Comparisons with
alternative feeding systems (e.g., ARC, 1980) indicate that the emissions estimates are not
sensitive to the feeding system used as the basis for making the estimates.
The net energy system specifies the amount of feed energy required for the physiological
functions of cattle, including maintenance, growth, and lactation. Feed energy requirements
for work have also been estimated, and are included in this analysis for the draft animals in
developing countries. Energy requirements for pregnancy have also been added for the
portion of cows that give birth in each year. The following information is required to
estimate feed energy intakes:
• Maintenance
Maintenance refers to the apparent feed energy required to keep the animal in
energy equilibrium, i.e., there is no gain or loss of energy in the body tissues (Jurgens,
1988). For cattle, net energy for maintenance (NEm) has been estimated to be a
function of the weight of the animal raised to the 0.75 power (NRC, 1984):
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EQUATION I
NEm (Mj/day) = 0.322 x (weight in kg)075
NRC (1989) recommends that lactating dairy cows be allowed a slightly
higher maintenance allowance:
NEm (MJ/day) = 0.335 x (weight in kg)075 {dairy cows}
Additional energy is required for animals to obtain their food. Grazing animals
require more energy for this activity than do stall-fed animals. The following energy
requirements are added for this activity based on their feeding situation:8
- Confined animals (pens and stalls): no additional NEm;
- Animals grazing good quality pasture: 17% of NEm; and
— Animals grazing over very large areas: 37% of NEm.
Growth
The energy requirements for growth can be estimated as a function of the weight of
the animal and the rate of weight gain. NRC (1989) presents formulae for large- and
small-frame males and females, the estimates from which vary by about ±25%. The
equation for large-frame females is recommended, which is about the average for the
four types:
EQUATION 2
NEg (MJ/day) = 4.18 x (0.035 W075 x WG1
WG) (2)
animal weight in kilograms (kg); and
weight gain in kg per day.
where:
W
WG
The relationships for NEg were developed for temperate agriculture conditions, and
may over-estimate energy requirements for tropical conditions, particularly for draft
animals that may have a lower fat content in their weight gain (Graham, 1985).
However, no data are available for improving the estimates at this time.
Lactation
Net energy for lactation has been expressed as a function of the amount of milk
produced and its fat content (NRC, 1989):
EQUATION 3
NE, (MJ/day) = kg of milk/day x (1.47 + 0.40 x Fat %)
At 4.0% fat, the NE, in MJ/day is about 3.1 x kg of milk per day.
Draft Power
Various authors have summarized the energy intake requirements for providing draft
power (e.g., Lawrence, 1985; Bamualim and Kartiarso, 1985; and Ibrahim, 1985). The
strenuousness of the work performed by the animal influences the energy
requirements, and consequently a wide range of energy requirements have been
estimated. The values by Bamualim and Kartiarso show that about 10% of NEm
8 The original OECD method recommended slightly higher energy additions. These
revised figures are based on newly-published information in AAC (1990).
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AGRICULTURE
requirements are required per hour of typical work for draft animals. This value is
used as follows:
EQUATION 4
NEdraft (MJ/day) = 0.10 x NEm x hours of work per day
Pregnancy
Daily energy requirements for pregnancy are presented in NRC (1984). Integrating
these requirements over a 281-day gestation period yields the following equation:
EQUATION 5
(MJ/281 -day period) = 28 x calf birth weight in kg
The following equation can be used to estimate the approximate calf birth weight as a
function of the cow's weight:9
EQUATION 6
Calf birth weight (kg) = 0.266 x (cow weight in kg)079
Manipulating Equations 5 and 6, in conjunction with Equation I, shows that the NE
required for pregnancy is about 7.5% of NEm for the range of cow sizes considered in
this analysis. Therefore, a factor of 7.5% of NEm is added to account for the energy
required for pregnancy for the portion of cows giving birth each year.
Based on these equations, each of the net energy components for each of the cattle
categories can be estimated from the data collected in Step I: weight in kilograms; feeding
situation; weight gain per day in kilograms; milk production in kilograms of 4% fat-
corrected milk; number of hours of work performed per day; and portion that give birth.
These net energy requirements must be translated into gross energy intakes. Also, by
estimating the gross energy intake, the net energy estimates can be checked for
reasonableness against expected ranges of feed intake as a percentage of animal weight. To
estimate gross energy intake, the relationship between the net energy values and gross
energy values of different feeds must be considered. This relationship can be summarized
briefly as follows:
Digestible Energy = Gross Energy - Fecal Losses
Metabolizable Energy = Digestible Energy - Urinary and Combustible Gas Losses
Net Energy = Metabolizable Energy - Heat Increment
Net Energy = Gross Energy - Fecal Losses - Urinary and Combustible
Gas Losses - Heat Increment
The quantitative relationship among these energy values varies among feed types.
Additionally, the values depend on how the feeds are prepared and fed, and the level at
which they are fed. For purposes of this method, simplifying assumptions are used to
derive a relationship between net energy and digestible energy that is reasonably
9 This species-specific equation from Robbins and Robbins (1979) was adjusted to the
mean cow and calf weight of a typical beef breed of cattle. This adjustment increases the
coefficient in the equation from 0.214 to 0.266.
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AGRICULTURE
representative for the range of diets typically fed to cattle. Gross energy intake is then
estimated using this relationship and the digestibility data collected in Step I.
Given the digestibility of the feed (defined in Step I), a general relationship between
digestible energy and metabolizable energy can be used as follows (NRC, 1984):
EQUATION 7
Metabolizable Energy (ME) = 0.82 x Digestible Energy (DE)
Equation 7 is a simplified relationship; larger (smaller) methane conversion rates would
tend to reduce (increase) the coefficient to values below (above) 0.82.
NRC (1984) presents separate quantitative relationships between metabolizable energy
and net energy used for growth versus net energy used for other functions. Using
Equation 7, the NRC relationships can be re-arranged to quantify the ratio of NE to DE, as
follows:
NE/DE
EQUATION 8
= 1. 123 - 4.092 x 10J x DE% + 1. 126 x I O's x (DE%)2 - 25.4/DE%
EQUATION 9
NEj/DE = 1. 164 - 5.160 x IO'3 x DE% + 1.308 x IO'5 x (DE%)2 - 37.4/DE%
where:
NE/DE = the ratio of net energy consumed for maintenance, lactation,
work and pregnancy to digestible energy consumed;
NEg/DE = the ratio of net energy consumed for growth to digestible
energy consumed; and
DE% = digestible energy as percentage of gross energy, expressed in
percent (e.g., 65%).
Because the NRC (1984) relationships were developed based on diets with relatively high
digestibilities (generally above 65%), they may not be appropriate for the relatively low
digestibility diets that are commonly found in tropical livestock systems. In particular, the
non-linear nature of the relationships could bias the estimates of feed intake upward for
low-digestibility feeds. An upward bias in feed intake would lead to an upward bias in
emissions estimates.
Based on a review of other energy systems (e.g., ARC, 1980), a linear relationship between
digestible energy and net energy was derived for digestibilities below 65% as follows (see
Appendix C):
NE/DE
EQUATION 10
= 0.298 + 0.00335 x DE%
4.16
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AGRICULTURE
EQUATION 11
= -0.036 + 0.00535 x DE%
Given the estimates for feed digestibility (from Step I) and equations 8 through 11, the
gross energy intake (GE in MJ/day) can be estimated as follows:
EQUATION 12
GE = [(NEm+NEfMd+NEl+NEw+NEp) / {NE/DE}
(DE%/IOO)
(NEg / {NE/DE})] /
where:
{NE/DE} is computed from equation 8 for digestibility greater than 65% and from
equation 1 0 for digestibility less than or equal to 65%;
is computed from equation 9 for digestibility greater than 65% and from
equation 1 1 for digestibility less than or equal to 65%; and
DE% is digestibility in percent (e.g., 60%).
To check the estimate of daily gross energy intake from equation 1 2, the estimate can be
converted in daily intake in kilograms by dividing by 1 8.45 MJ/kg. This estimate of intake in
kilograms should generally be between 1 .5% and 3.0% of the animal's weight.
Using Equation 12 and the cattle data summarized in Appendix A, Gibbs and Johnson
(1993) found that the intake estimates are consistent with expected intakes as a percent
of body weight and previously published values. For example, the intake estimate for Indian
cattle is the equivalent of about 1 0,000 MJ per year of metabolizable energy (ME).
Winrock (1978) estimates the average ME requirements for Indian cattle at 10,600 MJ per
year. Similarly, the ME values implied for U.S. dairy and beef cows are 58,000 MJ and
3 1 ,000 MJ per year, respectively, which are similar to estimates of 62,000 MJ and 3 1 ,700
MJ derived in U.S. EPA (1993). Consequently, for a diverse set of conditions, the intake
estimates correspond to reasonably expected ranges from previously published estimates.
To estimate the emission factor for each cattle type, the feed intake is multiplied by the
methane conversion rate (from Step I ) as follows:
EQUATION 13
Emissions (kg/yr) = Intake (MJ/day) x Ym x 365 days / 55.65 MJ/kg of methane
where Ym is the methane conversion rate expressed in decimal form (such as 0.06 for 6%).
The result of this step of the method is an emission factor for each cattle type defined in
Step I.
L*ei"< t£f,f t
io,FE,RMEN;r/moN TI^R 2: STEP 3 -- TOTAL
Hf^** * \ *f A. s*. Jt. ^
-• *
To estimate total emissions the selected emission factors are multiplied by the associated
animal population and summed. As described above under Tier I, the emissions estimates
should be reported in gigagrams (Gg).
PART 2
4.17
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AGRICULTURE
Tier 2 Approach For Manure Management Emissions
The Tier 2 approach provides a more detailed method for estimating methane emissions
from manure management systems. The Tier 2 approach is recommended for countries
with large cattle, buffalo and swine populations managed under confined conditions.
Compared to the Tier I approach, this method requires additional detailed information on
animal characteristics and the manner in which manure is managed. Using this additional
detailed information, emission factors are estimated that are specific to the conditions of
the country, and the default emission factors from Tier I are not used.
The Tier 2 approach is similar to the original OECD method described in OECD (1991).
Improvements to the method have been made to incorporate more recent figures on
methane conversion factors and to link the method more closely to the animal
characteristic data collected for estimating enteric fermentation.
MANURE MANAGEMENT T
LIV ESTO C K P C> P'U LATi O N Sl
2: STEP
•---•-••• •
To develop precise estimates of emissions, the animals should be divided into categories of
relatively homogeneous groups. For each category a representative animal is chosen and
characterized for purposes of estimating an emission factor. Suggested categories for cattle
are discussed above under the enteric fermentation Tier 2 method and are summarized in
Table 4-7. Similar categories can be used for buffalo. Categories for swine could include
sows, boars, and growing animals (farrows to finishers). For each of the representative
animal types defined, the following information is required:
• annual average population (number of head) by climate region (cool, temperate, and
warm);
• average daily manure volatile solids (VS) excretion (kg per day of dry matter);10
• methane producing potential (B0) of the manure (cubic meters (m3) of methane per
kgofVS);
• manure management system usage (percentage of manure managed with each
manure management system).
Population data are generally available from country-specific livestock census reports. As
described above under Tier I, the portion of each animal population in cool, temperate,
and warm climate regions is required.
Often, data on average daily VS excretion are not available. Consequently, the VS values
may need to be estimated from feed intake levels. The enteric fermentation Tier 2 method
should be used to estimate feed intake levels for cattle and buffalo.'' For swine, country-
specific swine production data may be required to estimate feed intake. To develop the
default emission factors for swine presented in Tier I, average feed intake estimates for
swine in developed and developing countries were used from Crutzen et al. (1986) (see
Appendix B).
10 Volatile solids (VS) are the degradable organic material in livestock manure.
11 By using the enteric fermentation Tier 2 method to estimate feed intake,
consistency is assured in the data underlying the emissions estimates for both enteric
fermentation and manure management.
4.18
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AGRICULTURE
Once feed intake is estimated, the VS excretion rate is estimated as:12
EQUATION 14
VS (kg/day dry) = Intake (MJ/day) * (I kg/18.45 MJ) * (I - DE%/IOO) * (I-
ASH%/IOO)
where:
VS = VS excretion per day on a dry weight basis;
Intake = the estimated daily average feed intake in MJ/day;
DE% = the digestibility of the feed in percent (e.g., 60%);
ASH% = the ash content of the manure in percent (e.g., 8%).
For cattle, the DE% value used should be the same value used to implement Tier 2 for
enteric fermentation. The ash content of cattle and buffalo manure is generally around 8%.
For swine, the default emission factors were estimated using 75% and 50% digestibility for
developed and developed countries, respectively, and an ash content of 2% and 4% for
developed and developed countries, respectively. Appendix B summarizes the data used to
estimate the VS excretion rates for cattle, buffalo, and swim;.
The maximum methane-producing capacity for the manure (B0) varies by species and diet.
Country specific data should be used where feasible. A range of representative B0 values
for cattle, buffalo, and swine populations were used to develop the default emission factors
as follows (see Appendix B):
• Dairy Cattle
Developed Countries: 0.24 m3/kg VS
- Developing Countries: 0.13 m3/kg VS
• Non-Dairy Cattle
Developed Countries: 0.17 m3/kg VS
Developing Countries: 0.10 m3/kg VS
• Buffalo in all regions: 0.10 m3/kg VS
• Swine
Developed Countries: 0.45 rrvVkg VS
Developing Countries: 0.29 m3/kg VS
The portion of manure managed in each manure management system must also be
collected for each representative animal type. Table 4-8 summarizes the main types of
manure management systems. The first four types in the table, pasture, daily spread, solid
storage, and drylot are all dry manure management systems. These systems produce little
or no methane. The wet manure management systems, liquid/slurry, anaerobic lagoon, and
pit storage are the primary sources of manure methane emissions. To implement this
Tier 2 method, at a minimum the proportion of manure managed in wet and dry systems
must be estimated.
The default emission factors presented in Tier I are based on manure management system
usage data collected by Safley et al. (1992). Appendix B presents these data by region for
cattle, buffalo, and swine. Although the data in Appendix B can be used as defaults,
12 The energy density of feed is about 18.45 MJ per kg of dry matter. This value is
relatively constant across a wide range of forage and grain-based feeds commonly
consumed by livestock.
PART 2
4.19
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AGRICULTURE
country-specific data, e.g., obtained through a survey, would improve the basis for
implementing the Tier 2 method. The resulting estimates must show the portion of
manure from each animal type managed within each management system, by climate
region.
Emission factors are estimated for each animal type based using the daia collected in
Step I and the methane conversion factors (MCFs) for each manure management system.
The MCF defines the portion of the methane producing potential (B0) that is achieved. The
MCF varies by manure management system and climate and can range between 0 and 100
percent. Table 4-8 presents the latest available MCF estimates for the major manure
managements systems that have been developed.
To calculate the emission factor for each animal type, a weighted average methane
conversion factor (MCF) is calculated using the estimates of the manure managed by waste
system within each climate region. The average MCF is then multiplied by the VS excretion
rate and the B0 for the animal type. In equation form, the estimate is as follows:
EQUATION 15
where:
EF,
VS,
Bo,
and
annual emission factor (kg) for animal type i (e.g., dairy cows);
daily VS excreted (kg) for ariimal type i;
maximum methane producing capacity (m3/kg of VS) for manure
produced by animal type /;
methane conversion factors for each manure management
system; by climate region k;
fraction of animal type fs manure handled using manure system j
in climate region k.
To estimate total emissions the selected emission factors are multiplied by the associated
animal population and summed. As described above under Tier I, the emissions estimates
should be reported in gigagrams (Gg).
Beyond Tier 2
The default values used in the Tier I and 2 methods were derived from available livestock
and manure management data and are generally representative of regional conditions.
Because livestock and manure management conditions can vary significantly across and
within countries, the default values may not reflect adequately the conditions in a given
country. Additionally, the variability of conditions has not been well characterized to date.
4.20
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AGRICULTURE
The emissions estimates can be improved by going beyond (the Tier 2 default data and
collecting key country- or region-specific data. Data elements that would benefit from data
collection initiatives (such as targeted surveys of major livestock types) include the
following:
• Cattle weight
In many regions the weights of cattle are not well quantified.
• Feed intake
Field data on feed intake would be valuable for validating the feed intake estimates
made under Tier 2 for cattle.
• Manure production
Field data on manure production by livestock would be valuable for validating the
manure production estimates made under Tier 2.
• Manure management
Field data on manure management system usage would improve the basis for making
the estimates. Considerations of seasonal management practices could be
incorporated into the data.
In addition to these data collection initiatives, measurement: programs can be used to
improve the basis for making the estimates. In particular, measuring emissions from
manure management systems under field conditions is needed. Techniques for making
these measurements are described in IAEA (1992). Additionally, measurements of the
maximum methane producing ability of manure (B0) from livestock in tropical regions is
needed.
Additionally, new techniques are being deployed to measure emissions from cattle under
field conditions (Johnson et al., 1993). Using these techniques, coefficients used in Tier 2
can be verified (such as the methane conversion rate) and che emissions estimates can be
validated. Targeted assessments of tropical cattle populations would be most valuable.
PART 2
4.21
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AGRICULTURE
4.2.1 References
AAC (Australian Agricultural Council) (1990), Feed Standards for Australian Livestock.
Ruminants, Commonwealth Scientific and Industrial Research Organization (CSIRO)
Publications, East Melbourne, Victoria, Australia.
ARC (Agriculture Research Council) (1980), The Nutrient Requirements of Ruminant
Livestock, Commonwealth Agricultural Bureaux, The Lavenham Press Ltd., the United
Kingdom.
Bamualim, A., and Kartiarso (1985). "Nutrition of draught animals with special reference to
Indonesia," in Copland, J.W., ed. Drought Animal Power for Production, Australian Centre for
International Agricultural Research (ACIAR) Proceedings Series No. 10. ACIAR, Canberra.
A.C.T., Australia.
Blaxter, K.L, and J.L Clapperton (1965), "Prediction of the amount of methane produced
by ruminants," British Journal of Nutrition 19:511-522.
Crutzen, P.J.. I. Aselmann, and W. Seiler (1986), "Methane Production by Domestic
Animals, Wild Ruminants, Other Herbivorous Fauna, and Humans," Teffus 386:271-284
FAO (Food and Agriculture Organization) (1990), Yearbook - Production Vol. 44, FAO,
United Nations, Rome, Italy.
Gibbs, M.J. and D.E.Johnson (1993). "Livestock Emissions," in International Methane
Emissions, U.S. Environmental Protection Agency, Climate Change Division, Washington,
D.C. (in press).
Graham, N.M. (1985), "Relevance of the British metabolisable energy system to the feeding
of draught animals," in Copland, J.W., ed. Drought Animal Power for Production, ACIAR
(Australian Centre for International Agricultural Research) Proceedings Series No. 10.
ACIAR, Canberra, A.C.T., Australia.
Hashimoto, A. and J. Steed (1993). Methane Emissions from Typical U.S. Livestock Manure
Management Systems, Draft report prepared for ICF Incorporated under contract to the
Global Change Division of the Office of Air and Radiation, U.S. Environmental Protection
Agency, Washington, D.C.
IAEA (International Atomic Energy Agency) (1992), Mam/of on measurement of methane and
nitrous oxide emissions from agricu/ture, International Atomic Energy Agency Publication
IAEA-TECDOC-674, Vienna. Austria.
Ibrahim, M.N.M. (1985), "Nutritional status of draught animals in Sri Lanka," in Copland,
J.W., ed. Draught Animal Power for Production, ACIAR (Australian Centre for International
Agricultural Research) Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia.
Johnson, KA, H. Westberg, M. Hyler, and B. Lamb (1993), Cattle Methane Measurement
Techniques Workshop, August 9-12, 1993, Washington State University, Pullman, WA,
sponsored by the Global Change Division, Office of Air and Radiation, U.S. Environmental
Protection Agency, Washington, D.C.
jurgens, M.H. (1988), Animal Feeding and Nutrition, Sixth Edition, Kendall/Hunt Publishing
Company, Dubuque, Iowa.
Lawrence, P.R. (1985), "A review of nutrient requirements of draught oxen," in Copland,
J.W., ed. Draught Animal Power for Production, ACIAR (Australian Centre for International
Agricultural Research) Proceedings Series No. 10. ACIAR, Canberra, A.C.T., Australia.
4.22
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AGRICULTURE
Lichtman, R. J. (1983), Biogos Systems in India, Volunteers In Technical Assistance (VITA),
Arlington, Virginia.
NRC (National Research Council) (1984), Nutrient Requirements of Beef Cattle, National
Academy Press, Washington, D.C.
NRC (National Research Council) (1989), Nutrient Requirements of Dairy Cattle, National
Academy Press, Washington, D.C.
OECD (Organization for Economic Cooperation and Development) (1991), Estimation of
Greenhouse Gas Emissions and Sinks: Final Report from the OECD Experts Meeting, 18-21
February 199 /, OECD, Paris, France.
Robbins, C.T., and D.L Robbins (1979), "Fetal and neonatal growth patterns and maternal
reproductive effqrt in ungulates and sub-ungulates," Amer. Naturalist 114:101.
Safley, L.M., M.E. Casada, J.W. Woodbury, and K.F. Roos (1992). Global Methane Emissions
from Livestock and Poultry Manure. U.S. Environmental Protection Agency, Global Change
Division. Washington, D.C., February 1992, EPA/400/1091 /048.
Safley, LM. Jr., and P.W. Westerman, (1992), "Performance! of a low temperature lagoon
digester," Bioresource Technology 41:167-175.
Stuckey, D.C. (1984), "Biogas: a global perspective," in EI-Halwagi, MM., ed. Biogos
Technology, Transfer and Diffusion, Elsevier, New York, pages 18-44.
U.S. EPA (U.S. Environmental Protection Agency) (1993), Anthropogenic Methane Emissions
in the United States, Global Change Division, Office of Air and Radiation, Washington, D.C.
Winrock (Winrock International) (1978), The Role of Ruminants in Support of Man, Winrock
International, Morrilton, Arkansas.
Woodbury, J.W. and A. Hashimoto (1993). "Methane Emissions from Livestock Manure,"
in International Methane Emissions, U.S. Environmental Protection Agency, Climate Change
Division, Washington, D.C. (in press).
Yancun, C, H. Cong, and Liang Pusen (1985), "Development of a new energy village -
Xinbu, China," in El Mahgary, Y., and A.K. Biswas, eds. integrated Rural Energy Planning,
Butter-worths Publishing, Guildsford, England, pages 99-108.
PART 2
4.23
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AGRICULTURE
TABLE 4-1
DOMESTIC LIVESTOCK INCLUDED IN THE METHODS
Livestock
Recommended Emissions Inventory Methods
Enteric Fermentation
Manure Management
Dairy Cows
Cattle Other than Dairy Cows
Buffalo
Sheep
Goats
Camels
Horses and Mules
Swine
Poultry
Tier I
Tier I
Tier I
Tier I
Tier I
(Not Estimated)
Tier I
Tier I
Tier I
Tier I
Tier24
T
fieri
a The Tier 2 approach is recommended for countries with large livestock populations. Implementing the Tier 2 approach for additional
Kvdtock subgroups may be desirable when the subgroup emissions are a large portion of total methane emissions for the country.
4.24
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AGRICULTURE
TABLE 4-2
ANIMAL POPULATION DATA COLLECTED IN TIER 1 STEP 1
Livestock
Dairy Cows
Cattle Other than Dairy
Cows
Buffalo
Sheep
Goats
Camels
Horses and Mules
Swine
Poultry
Data Collected
Population
(# head)
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Average Annual
Population
Milk Production
(kg/head/yr)
Milk Production per
Head
Not Applicable (NA)
(NA)
(NA)
(NA)
(NA)
(NA)
(NA)
(NA)
Population By Climate (%)
Cool Temperate
% Cool % Temp.
%Cool %Temp.
% Cool % Temp.
%Cool %Temp.
% Cool % Temp.
% Cool % Temp.
% Cool % Temp.
% Cool % Temp.
Warm
%Warm
%Warm
%Warm
%Warm
%Warm
%Warm
%Warm
%Warm
Data can be obtained from the FAO Production Yearbook and country-specific livestock census reports. Climates are defined in terms ot
average annual temperature as follows: Cool = less than 1 5°O Temperate = greater than 1 S°C and less than 2S°C; Warm = greater than
25°C.
TABLE 4-3
ENTERIC FERMENTATION EMISSION FACTORS
(kg per head per year)
Livestock
Buffalo
Sheep
Goats
Camels
Horses
Mules and Asses
Swine
Poultry
All estimates are ±20 percent
Developed Countries
55
8
5
46
18
10
1.5
Not Estimated
55
5
5
46
18
10
1.0
Sources: Emission factors for buffalo and camels from Gibbs and Johnson (1993). Emission factors for other livestock from Crutzen et al.
(1986).
^ %,..,....,£...£.£... £„.£. ,^s.=^sss;.,^&V,^^^mS!^y!X!l^f!Sff!mi^/yl^f^im^t^!&
PART 2
4.25
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AGRICULTURE
TABLE 4-4
ENTERIC FERMENTATION EMISSION FACTORS FOR CATTLE
Regional Characteristics
North America: Highly productive commercialized dairy sector
Feeding high quality forage and grain. Separate beef cow herd,
primarily grazing with feed supplements seasonally. Fast-growing
beef steers/heifers finished in feedlots on grain. Dairy cows are a
small pan of the population.
Western Europe: Highly productive commercialized dairy
sector feeding high quality forage and grain. Dairy cows also
used for beef calf production. Very small dedicated beef cow
tent Minor amount of feedlot feeding with grains.
Eastern Europe: Commercialized dairy sector feeding mostly
forages. Separate beef cow herd, primarily grazing. Minor
amount of feedlot feeding with grains.
Oceania: Commercialized dairy sector based on grazing.
Separate beef cow herd, primarily grazing rangelands of widely
varying quality. Growing amount of feedlot feeding with grains.
Dairy cows are a small part of the population.
Latin America-. Commercialized dairy sector based on grazing.
Separate beef cow herd grazing pastures and rangelands. Minor
amount of feedlot feeding with grains. Growing beef catde
comprise a large portion of the population.
Asia-. Small commercialized dairy sector. Most catde are multi-
purpose, providing draft power and some milk within farming
regions. Small grazing population. Cade of all types are smaller
than those (bund in most other regions.
Africa and Middle East: Commercialized dairy sector based
on grazing with low production per cow. Most catde are multi-
xirpose, providing draft power and some milk within farming
regions. Some cattle graze over very large areas. Catde of all
types arc smaller than those found in most other regions.
ndlan Subcontinent: Commercialized dairy sector based on
crop byproduct feeding with low production per cow. Most
Hillocks provide draft power and cows provide some milk in
farming regions. Small grazing population. Catde in this region
are die smallest compared to catde found in all omer regions.
Animal Type
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Dairy Cows
Non-Dairy Catde
Emission Factor
(kg/head/yr)
118
47
100
48
81
56
68
S3
57
49
56
44
36
32
46
25
Comments
Average milk production of 6,700 kg/yr
Includes beef cows, bulls, calves, growing
steers/heifers, and feedlot cattle
Average milk production of 4,200 kg/yr
Includes bulls, calves, and growing
steers/heifers
Average milk production of 2,550 kg/yr
Includes beef cows, bulls, and young.
Average milk production of 1 ,700 kg/yr
Includes beef cows, bulls, and young.
Average milk production of 800 kg/yr
Includes beef cows, bulls, and young.
Average milk production of 1,650 kg/yr
ncludes multi-purpose cows, bulls, and
young.
Average milk production of 475 kg/yr
ncludes multi-purpose cows, bulls, and
young.
Average milk production of 900 kg/yr
ncludes cows, bulls, and young. Young
comprise a large portion of the
jopulation.
4.26
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AGRICULTURE
TABLE 4-5
MANURE MANAGEMENT EMISSION FACTORS
(kg per head per year)
Livestock
Developed Countries
Developing Countries
Cool
Temp.a
Warm
Cool
Temp.a
Warm
Sheep
0.19
0.28
0.37
0.10
0.16
0.21
Goats
0.12
0.18
O.B
O.I I
0.17
0.22
Camels
1.6
2.4
3.2
1.3
1.9
2.6
Horses
1.4
2.1
2.8
1.6
2.2
Mules and Asses
0.76
1.14
1.51
0.60
0.90
1.2
Poultry
0.078
0.117
O.I 57
0.012
0.018
0.023
The range of estimates reflects cool to warm climates. Climate regions are defined in terms of annual average temperature as follows:
Cool = less than IS°C; Temperate = IS°C to 25°C; and Warm = greater than 25°C Trie Cool. Temperate and Warm regions are
estimated using MCFs of I %, 1.5% and 2%. respectively.
a Temp. = Temperate climate region.
b Chickens, ducks, and turkeys.
All estimates are ±20 percent.
Sources: Emission factors developed from: feed intake values and feed digestibilities used to develop the enteric fermentation emission
factors (see Appendix A); MCF, and Bo values reported in Woodbury and Hashimoto (1993). All manure is assumed to be managed in dry
systems, which is consistent with the manure management system usage reported in Woodbury and Hashimoto (1993).
PART 2
4.27
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AGRICULTURE
TABLE 4-6
MANURE MANAGEMENT EMISSION FACTORS FOR CATTLE, SWINE AND BUFFALO
Regional Characteristics Animal Type
North America: Liquid-based systems are common!/ used for
dairy and swine manure. Non-dairy manure is usually managed
as a solid and deposited on pastures or ranges.
Western Europe: Liquid/slurry and pit storage systems are
commonly used for cattle and swine manure. Limited cropland
is available for spreading manure.
Eastern Europe: Solid based systems are used for the
majority of manure. About one-third of livestock manure is
managed in liquid-based systems.
Oceania: Virtually all livestock manure is managed as a solid
on pastures and ranges. About half of the swine manure is
managed in anaerobic lagoons.
Latin America: Almost all livestock manure is managed as a
solid on pastures and ranges. Buffalo manure is deposited on
pastures and ranges.
Africa: Almost all livestock manure is managed as a solid on
pastures and ranges.
Middle Ease Over two-thirds of cattle manure is deposited on
pastures and ranges. About one-third of swine manure is
managed in liquid-based systems. Buffalo manure is burned for
fuel or managed as a solid.
Asia: About half of catde manure is used for fuel with the
remainder managed In dry systems. Almost forty percent of
swine manure is managed as a liquid. Buffalo manure is
managed in drylots and deposited in pastures and ranges.
Indian Subcontinent: About half of cattle and buffalo manure
is used for fuel with the remainder managed in dry systems.
About one-third of swine manure is managed as a liquid.
a Cool climates have an average temperature below IS°C; tern]
warm climates have an average temperature above 25°C. All clin
example, there are no significant warm areas in Eastern or West
Middle East. See Appendix B for the derivation of these emission
Mote: Significant buffalo populations do not exist in North Amer
Dairy Cows
Non-Dairy Cows
Swine
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
Dairy Cows
Non-Dairy Cows
Swine
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
Dairy Cows
Non-Dairy Cows
Swine
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
Dairy Cows
Non-Dairy Cows
Swine
Buffalo
erate climates have an ave
late categories are not nee
ern Europe. Similarly, then
factors.
ica, Oceania, or Africa.
Emission Factor by Climate Region3
(kg/head/year)
Cool
36
1
10
14
6
3
3
6
4
4
3
31
5
19
0
1
1
1
1
0
0
1
1
1
4
7
1
1
1
Temperate
54
2
14
44
20
II
8
19
13
7
9
32
6
19
1
2
2
3
5
16
1
4
2
Warm
76
3
18
81
38
20
17
33
23
II
16
33
7
20
2
1
3
2
1
1
2
2
1
6
5
27
2
7
3
556
222
346
455
•age temperature between I5°C and 25°C;
essarily represented within every region. For
: are no significant cool areas in Africa and the
4.28
-------
AGRICULTURE
TABLE 4-7
RECOMMENDED REPRESENTATIVE CATTLIE TYPES
Main Categories
Mature Dairy Cows
Mature Non-Dairy Cattle
Young Cattle
Sub-Categories
Used principally for commercial milk production
Mature Females:
• Beef Cows: used principally for producing beef steers and heifers
• Multiple-Use Cows: used for milk production, draft power, and other uses
Mature Males:
• Breeding Bulls: used principally for breeding purposes
• Draft Bullocks: used principally for draft power
Pre-Weaned Calves
Growing Heifers, Steers/Bullocks and Bulls
Feedlot-Fed Steers and Heifers on High-Grain Diets
PART 2
4.29
-------
AGRICULTURE
TABLE 4-8
MANURE MANAGEMENT SYSTEMS AND METHANE CONVERSION FACTORS (MCFs)
System
Pasture/Range/Paddoclc The manure from pasture and range grazing animals
is allowed Co lie as is, and is not managed.
Daily Spread Manure is collected in solid form by some means such as scraping.
The collected manure is applied to fields regularly (usually daily).
Solid Storage: Manure is collected as in the daily spread system, but is stored in
bulk for a long period of time (months) before any disposal.
Drylot In dry climates animals may be kept on unpaved feedlots where the
manure Is allowed to dry until it is periodically removed. Upon removal the
manure may be spread on fields.
Liquid/Slurry These systems are characterized by large concrete lined tanks
built into the ground. Manure is stored in the tank for six or more months until it
can be applied to fields. To facilitate handling as a liquid, water may be added to
the manure.
Anaerobic Lagoon Anaerobic lagoon systems are characterized by flush
systems that use water to transport manure to lagoons. The manure resides in
the lagoon for periods from 30 days to over 200 days. The water from the lagoon
may be recycled as flush water or used to irrigate and fertilize fields.
Pit Storage Liquid swine manure may be stored In a pit while < 30 Days
awaiting final disposal. The length of storage time varies, and for
this analysis is divided into two categories: less than one month
or greater than one month.
> 30 Days
Anaerobic Digester The manure, in liquid or slurry form, is anae-robically
digested to produce methane gas for energy. Emissions are from leakage and vary
with the type of digester.
Burned for Fuel Manure is collected and dried In cakes and burned for heating
or cooking. Emissions occur while the manure is stored before it is burned.
Methane emission associated with the combustion of the manure are not
considered here. Combustion-related emissions are estimated in the Traditional
Btomass Fuels section of the Energy chapter.
MCF by Climate3
Cool , , Temperate Warm
1% 1.5% 2%
0.1% 0.5% 1.0%
1% 1.5% 2%
1% 1.5% 5%
10% 35% 65%
90% 90% 90%
5% 18% 33%
10% 35% 65%
5-15% 5-15% 5-15%
5-10% 5-10% 5-10%
Source
b
b
b
b
b
c
b
b
d
e
a Cool climates have an average temperature below I5°C; temperate climates have an average temperature between I5°C and 25°C;
warm climates have an average temperature above 25°C.
b Hashimoto and Steed (1993).
c Safley ec al., (1992) and Safley and Westerman (1992).
d Yancun et al. (1985), Stuckey (1984) and Uchtman (1983).
e Safleyetal. (1992).
4.30
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AGRICULTURE
Appendix A
Data Underlying Default Emission Factors
for Enteric Fermentation
This appendix presents the data used to develop the default emission factors for methane
emissions from enteric fermentation. The detailed information presented for cattle and
buffalo was developed in Gibbs and Johnson (1993). The Tier 2 method was implemented
with these data to estimate the default emission factors for cattle and buffalo. Also
presented are the summary data from Crutzen et al. (1986) that were used to estimate
the emission factors for the other species.
PART 2
4.31
-------
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-------
AGRICULTURE
Appendix B Data Underlying Default Emission
Factors for Manure Management
This appendix presents the data used to develop the default emission factors for methane
emissions from manure management The detailed information presented for cattle and
buffalo were developed in Gibbs and Johnson (1993). The swine feed intake data are from
Crutzen et al. (1986). The manure management system usage data and B0 estimates are
from Safley et al. (1992). The methane conversion factor (MCF) data are from Woodbury
and Hashimoto (1993). The Tier 2 method was implemented with these data to estimate
the default emission factors for cattle, buffalo, and swine. Also presented are the summary
feed intake data from Crutzen et al. (1986) and the manure-related data from Safley et al.
(1992) and Woodbury and Hashimoto (1993) that were used to estimate the emission
factors for the other species.
PART 2
4.37
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AGRICULTURE
Appendix C Derivation of Tier 2 Enteric
Fermentation Equations
This appendix summarizes the derivation of the relationship between net energy (NE) and
digestible energy (DE) that is used to estimate total feed-intake requirements for cattle.
This derivation is drawn from Gibbs and Johnson (1993).
As described in the main text, the relationship among the energy values of feed consumed
by cattle can be summarized as follows:
Digestible Energy =
Metabolizable Energy =
Losses
Net Energy =
Gross Energy - Fecal Losses
Digestible Energy - Urinary and Combustible Gas
Metabolizable Energy - Heat Increment
Net Energy = Gross Energy - Fecal Losses -
Urinary and Combustible Gas Losses - Heat Increment
NRC (1984) presents the following quantitative relationships among these energy values:
ME = 0.82 xDE (C.I)
NEm = 1.37 x ME-0.138 x ME2+ 0.0105 x ME3-1.12 (C.2)
NE£ = 1.42 x ME - 0.174 x ME2 + 0.0122 x ME3 - 1.65 (C.3)
where:
DE = digestible energy in Meal/kg (dry matter basis);
ME = metabolizable energy in Meal/kg (dry matter basis);
NEm = net energy for maintenance in Meal/kg (dry matter basis); and
NEg = net energy for growth in Meal/kg (dry matter basis).
Using these relationships, the ratio of NEm and NEg to ME or DE can be derived as
follows:
NE/DE = I.I23-4.092X W3xDE% + I.l26x I0'sx (DE%)2- 25.4/DE% (C.4)
NEj/DE = 1.164 - 5.160 x IO'3 x DE% + 1.308 x IO'5 x (DE%)2 - 37.4/DE% (C.5)
where:
NE/DE = the ratio of net energy consumed for maintenance, lactation, work
and pregnancy to digestible energy consumed;
NEg/DE = the ratio of net energy consumed for growth to digestible energy
consumed; and
DE% = digestible energy as percentage of gross energy, expressed in percent
(e.g., 65%).
Graph C-l shows the relationships in graphical form. As shown in the graph, the ratio of
NE to DE is non-linear, with an increasing slope with decreasing DE. These relationships
imply that at lower values of DE, cattle are able to recover a decreasing portion of the
energy to use for maintenance or growth.
4.46
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AGRICULTURE
For purposes of estimating methane emissions from cattle, applying these relationships to
cattle consuming relatively low-quality feeds (such as cattle in many tropical countries) may
be inappropriate because the relationships were developed based on analyses of the
higher-quality feeds typically found in the U.S. temperate agriculture system. Consequently,
the experimental basis for extrapolating the non-linear relationships to low levels of DE is
not very strong.
In examining other energy systems, it is seen that they also indicate that the rate of net
energy retention declines at lower values of digestible energy. Unlike the NRC system,
however, many imply a linear relationship between NE and DE. The U.K. energy system
(ARC, 1980), which is typical of the energy systems used in Europe, has a slope for the
linear NEm:DE relationship that is similar to the slope of the non-linear NRC relationship
in the range of 65%-70% digestibility. Similarly, the slope of the U.K. NE^DE relationship is
similar to the slope of the non-linear NRC relationship in the range of 60%-65%
digestibility.
To avoid possible biases in estimating feed-intake requirements in this study, the
relationships were extrapolated linearly for DE values below 65% using the average slopes
of the NRC relationships between 60% and 70% DE. The derived equations are as follows:
NE/DE = 0.298 + 0.00335 x DE% (C.6)
NEg/DE = -0.036 + 0.00535 x DE% (C.7)
Graph C-2 shows the extrapolated linear relationships along with the non-linear estimates.
As expected, the linear extrapolations fall above the original non-linear estimates.
The implication of making this adjustment to the N RC (1984) relationship for the global
emissions estimate is relatively minor. Gibbs and Johnson (1993) report that using the
non-linear relationship to estimate global emissions from cattle increases the 1990
emissions estimate by .001 Gg, from .0581 Gg to .0591 Gg. Considering the wide range of
factors that contribute to uncertainty in the estimates, including characterization of animal
populations, this adjustment has a minor influence on the estimates.
PART 2
4.47
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AGRICULTURE
Graph C-l: NRC NE:DE Relationship
HE to DE Ratio by DE
Derived from NRC (1984)
Ratio
48
52 56 60 64
Digestible Energy (%)
68
72
76
NEm
NEf
4.48
-------
AGRICULTURE
Graph C-2: Linear Extrapolation Of The NRC NE:IOE Relationship
NE to DE Ratio by DE
0.54
0.52
0.50
0.48
0.46
0.44
0.42
0.40
0.38
RatiO 0.36
0.34
0.32
0.30
0.28
0.26
0.24
0.22
0.20
0.18
44
48
r '
72
76
Digestible Energy (%)
NETO Linear Extrapolation
NE( Linear Extrapolation
PART 2
4.49
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AGRICULTURE
4.3 Methane Emissions from Flooded Rice
Fields
4.3.1 Overview
Anaerobic decomposition of organic material in flooded rice fields produces methane
(CH4). which escapes to the atmosphere primarily by diffusive transport through the rice
plants during the growing season. Upland rice fields, which are not flooded and therefore
do not produce significant quantities of CH4, account for approximately 10% of the global
rice production and about 15% of the global rice area under cultivation. The remaining
area is wetland rice, consisting of irrigated, rainfed, and deepwater rice. The global wetland
rice area harvested annually in the early 1980s was about 123.2 million hectares, over 90%
of which was in Asia (Neue et al., 1990).'3
Of the wide variety of sources for the atmospheric CH/}, rice paddy fields are considered
one of the most important sources. The Intergovernmental Panel on Climate Change
(Watson et al, 1992) estimated the global emission rate from paddy fields to be ranging
from 20 to I SO Tg/yr, averaged 60 Tg/yr. This is about 5-30% of the total emission from all
sources. This figure is mainly based on field measurements of CH4 fluxes from paddy fields
in the United States, Spain, Italy, China, India, Australia and Japan.
The measurements at various locations of the world show that there are large temporal
variations of CH4 fluxes and that the flux differs markedly with soil type, application of
organic matter and mineral fertilizer. The wide variations in CH4 fluxes also indicate that
the flux is critically dependent upon several factors including climate, characteristics of
soils and paddy, and agricultural practices. On the other hand, about 90% of the world's
harvested area of rice fields is located in Asia. Of the total harvested area in Asia, about
60% is located in India and China.
Methane production processes
The major pathways of CH4 production in flooded soils are the reduction of CO2 with
H2, with fatty acids or alcohols as hydrogen donor, and the transmethylation of acetic acid
or methyl alcohol by methane producing bacteria (Takai 1970; Conrad 1989). In paddy
fields, the kinetics of the reduction processes are strongly affected by the composition and
texture of soil and its content of inorganic electron acceptors. The period between
flooding of the soil and the onset of methanogenesis can apparently be different for the
various soils. However, it is unclear if soil type also affects the rates of methanogenesis and
CH4 emission when steady state conditions have been reached (Conrad 1,989).
13 The term "harvested area" has a different meaning than "cultivated area" in that the
former accounts for double and triple cropping. For example, if a country has 10 million
hectares of land under rice cultivation, all of which are double-cropped (i.e.,, two crops of
rice are grown on each hectare each year), then this country has 20 million hectares of
rice area harvested annually.
4.50
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AGRICULTURE
14
The redox potential is the most important factor for production of CH4 in soils. The Eh
of the soil gradually decreases after flooding. This is due to a decrease in the activity of the
oxidized phase and increased activity of the reduced phase. Takai etal. (1956)
demonstrated that the redox potential of a soil must be below -200 mv in order to have
CH4 production. Yamane and Sato (1964) also showed that: the evolution of CH4 from
flooded paddy soils did not commence until the Eh fell below -200 mv. There is a
correlation between the soil redox potential and methane emission (Patrick et al. 1981;
Cicerone et al. 1983; Yagi and Minami 1990).
Substrate and nutrient availability is also an important factor. Application of rice straw to
paddy fields significantly increase CH4 emission rate compared with application of
compost prepared from rice straw or chemical fertilizer.
Soil temperature is known to be an important factor in affecting the activity of soil
microorganisms. This is to a certain extent related to the soil moisture content because
both the heat capacity and the heat conductivity are lower for a dry soil than for a wet
soil. Yamane and Sato (1961) have already found that CH4 formation reached a maximum
at 40°C in waterlogged alluvial soils. Above 40°C, CH4 formation decreased and stopped
at 60°C. The formation was very small below 20°C.
It is generally recognized that CH4 formation is only efficient in a very narrow range
around neutrality (pH from 6.4 to 7.8). Flooding will have an increasing effect on pH in
acid soil, while it will decrease the pH in alkaline soil. The increase of pH in acid soils is
mainly due to the reduction of acidic Fe to Fe .
Growing plants on soils may also affect the emission of gaseous CH4. At later growth
stages' of rice, more nitrogen gas and less CH4 were found in wetlands soils planted to rice
than in an unplanted rice field (Yoshida 1978). Yamane and Sato (1963) found that flooded
soils planted with rice frequently evolve less CH4 than the corresponding uncropped sites.
The addition of sulfate as chemical fertilizer to flooded soils also influences the production
of CH4 because of its effect on raising the redox potential and of the toxic effect of its
reduction product. Also, the addition of sulfate increases the activities of sulfate-reducing
bacteria, which outcompete methanogens for the substrate. Sulfate must be reduced
before CH4 is formed in paddy soils (Takai 1980).
The addition of nitrate as chemical fertilizer to flooded soils; may also suppress the
production of CH4. Because nitrate acts as a terminal electron acceptor in the absence of
molecular oxygen for anaerobic respiration and it poises the redox potential of soils at
values such that the activity of strict anaerobes is prevented.
There are three processes of CH4 release into the atmosphere from rice paddies.
Methane loss as bubbles from paddy soils is a common and significant mechanism. Diffusion
loss of CH4 across the water surface is another process. The third, CH4 transport
through rice plants, which has been reported (Seiler et al. 1984; Cicerone et al. 1983;
Minami and Yagi 1988; Nouchi et al. 1990), as the most important phenomenon.
Many researchers reported that more than 90% of the total CH4 released from rice
paddies is diffusive transport through the aerenchym system of the rice plants and not
through diffusion or escape of bubbles across the air-water interface. Emission through
plants may be expected to show great seasonal variations tied to environmental changes in
soil conditions and variations in plant growth stage, respiration and photosynthesis rates.
14 Redox refers to oxidation-reduction, two processes that take place simultaneously.
Oxidation is the loss of an electron by an atom, and reduction is the gain of an electron by
an atom.
PART 2
4.51
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AGRICULTURE
Although CH4 flux rates are revealed to be a function of the total amount of CH4 in the
soil, there is a possibility that the gas may be consumed in the thin oxidized layer close to
the soil surface and in deep flooding water. It is known that soil methanogenic bacteria can
grow with CH4 as their sole energy source, and other soil bacteria, Nitrosomonas species
consume CH4 (Seller and Conrad 1987). Methane is also leached to ground water as a
small part is dissolved in water.
Global emissions from rice paddies
The area harvested of paddy rice has increased from 86 x IO6 ha in 1935 to 144 x IO6 ha
in 1985, which means an annual average increase of 1.05%. The average annual increase has
been 1.23% between 1959 and 1985. However, in the last few years, the expansion of the
total acreage of paddy is decreasing. (Minami, 1993)
About 90% of the world's harvested area of rice paddies is located in Asia. Of the total
harvested area in Asia, about 60% is located in India and China. Although we had no
detailed data available for the estimation of CH4 flux from India and China in 1990,
recently some data are published for Asian countries as shown in Table 2.
4.52
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AGRICULTURE
TABLE 2
METHANE EMISSION FROM RICE PADDY FIELDS IN VARIOUS LOCATIONS OF THE WORLD
China (Hangzhou)
Early rice
Late rice
Single rice
China (Tuzu)
India
Italy
Japan
Ryugasaki (Peat soil)
Ryugasaki (Gley soil)
Tsukuba (Andosol)
Spain
Thailand
Suphan Buri
Khlong Luang
Chai Nat
USA
California
Texas
.Louisiana
0.19
0.69
0.44
1.39
0.04-0.46
0.10-0.68
0.39
0.07-0.37
-------
AGRICULTURE
TABLES
GLOBAL ANNUAL METHANE EMISSION FROM RICE CULTIVATION AS ESTIMATED BY
DIFFERENT AUTHORS
Koyama (1964)
Ehhalc and Schmidt (1978)
Cicerone and Shetter (1981)
KhalilandRasmussen(l983)
Seller etal (1984)
Blake (1984)
Crutzen (1985)
Holzapfel-Psdiorn and Seller (1986)
Cicerone and Oremland (1988)
Schutzetal. (1989)
Aselman and Crutzen (1989)
Schutz and Seller (1989)
Wang etal. (1990)
Ncucctal. (1990)
Bouwman (1990)
YagiandMlnami(l990)
IPCC(I990)
IPCC (1992)
MinamiandYagi(l993)
190
280
59
95
35-59
142-190
120-200
70-170
60-170
50-150
30-75
60-140
70-170
60-120
25-60
53-114
22-73
25-170
20-100
12-113
4.3.2 Methods For Estimating Emissions15
Emissions of methane from rice fields can be represented as follows:
FC = compXE (I)
where Fc is the estimated emission of methane from a country (c) in Tg/yr, comp is the
"composite emission factor" (Tg/hectare/yr) representative of the conditions in a country,
and E is the "extrapolant" (hectare-years). The composite emission factor is evaluated
from direct field measurements of methane fluxes, and the extrapolant consists of the
product of the rice area harvested per year and the fraction of the year the fields are used
for growing rice: E = A (hectares) x T (years). The extrapolant is obtained from
geographical and agricultural archives.
In practice it is simpler to calculate the total annual emissions from a country as a sum of
the emissions over a number of conditions. The emissions differ under each condition and
.... Ttffc... (2)
lsFrom Kalil, 1993, reporting recommendations of the expert group.
4.54
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AGRICULTURE
represent the effect of the biological, chemical, and physical factors that control methane
emissions from rice fields.
where ijk... are categories under which methane emissions from rice fields may vary. For
instance, i may represent water levels in the rice fields such as fields inundated for the
duration of the growing season (flooded regime) or fields under water only intermittently,
either from managed irrigation when water is not readily available or when rains do not
maintain flooded conditions throughout the growing season (intermittent regime) or
highland rice when the fields are seldom flooded during the growing season (dry regime), j
may represent fertilization regimes under each of the conditions represented by the index
i, and so on. As more factors are identified, more categories need to be included. Inclusion
of additional factors does not, however, lead to an automatic improvement of the total
emissions since errors propagate and may create large uncertainties. Similarly, using
extremely simplified methods for calculating the representative flux (
-------
AGRICULTURE
Default Methodologies
In many cases, especially in the beginning of the process, there will be important rice
growing areas for which specific fluxes or details of extrapolants will not be available. In
such cases the recommended methodology is to adopt the emission factors from the
nearest region where data are available or the most similar climatic zone from which data
are available. If data on irrigation practices are not available, it should be taken as the
flooded regime.
4.3.3 Summary Of Recommended Method
I Base years: 1990 as averaged over 1989-1991.
2 Use:
Area of rice agriculture under flooded regime = A (flooded) in m .
Emission factor for flooded conditions, over the three years for emissions from
nearby region or similar climatic zone = (Tg/m /day).
Number of days under cultivation when flooded = T (days/yr)
Calculate Flux(flooded) = A(flooded) x ({((flooded) x T(flooded) for each of the
three base years and take average.
Correct flux for temperature effect:
multiplyby [Q10
a
b
c
d
where Q|Q is the ratio of the flux at temperature IO°C above the base
temperature.
f Repeat steps a)-e) for intermittently flooded rice agriculture:
Flux(intermittent).
g Repeat steps a)-e) for dryland rice: Flux(dry).
h Average annual country flux is F(country) = Flux(flooded) + Flux(intermittent) +
Flux(dry).
3 Where data are available on fertilizer type, it may be incorporated into the
calculations.
Calculate each of the three factors in h) as follows:
i Flux(flooded) = Flux(flooded|organic) + Flux(flooded|chemical)
where Flux(flooded|organic) is calculated according to steps a)-e) using the
emission factors, areas, time of flooding, and temperatures applicable to the
amount of rice grown under flooded conditions using organic fertilizers.
Flux(flooded|chemical) is calculated analogously.
j Calculate Flux(intermittent) and Flux(dry) analogously to i)
4 Each additional factor may be incorporated in the same manner by further subdividing
each category in 3).
The procedure is described by the following general formulae:
Base: F=Z((>.A.Tt
(3)
i represents water management regimes - flooded, intermittent, dry.
4.56
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AGRICULTURE
Adding fertilizer effecc
(4)
where j represents different fertilizer types. Each component if (3) is calculated by (4).
Additional factors: soil type, for example:
(5)
where k represents different soil types. Each component of (4) is calculated from (5) and
then each component of (3) is calculated from (4).
The process may be continued for more factors.
Default Data.
Tables 4-6 and 4-7 present regional and country specific information regarding rice
production and emissions.
In Table 4-6 the area information is based on statistics from the FAO
Yearbook, China Agricultural Yearbook, and World Rice Statistics from IRRI. The crop
calendars of Matthews et al. (1991) were modified to reflect the period in which a
particular crop was grown, rather than the total possible period in which a crop can be
grown. Using the length of the season calculated from the crop calendar leads to an
overestimate of the methane emission season. The two exceptions to this are Louisiana,
where two crops are being grown, and Italy, which has a longer growing season for rice
than the crop calendars suggest. The Matthews et al. tables were the basis for estimating
season length and then were reduced by 10 to 45 days depending on the crop calendar
season length. In Table 4-6, "Season Length" is the weighted average of all growing seasons
after they have been adjusted for the crop calendar length.
Table 4-7 provides default emission factors for intermittently flooded and flooded rice fields. If
countries have local measurements data available to develop country-specific emission
factors, these should be used and documented. Default values in Table 4-7 can be used for
initial calculations where local measurements are not adequate. A "modal" average seasonal
flux for Asian countries was estimated to be 20 (+/-5) mg/m2 nr, Q10 = 1.8, with a base
temperature of (Tb) = 23 *C. The base temperature is representative of average seasonal
temperatures in the areas of Asia where flux measurements are available (20-25 *C). These
flux values are representative of flooded rice fields where organic amendments are used,
which is common in rice growing countries where measurements are not available. Dryland
rice was assigned a flux of 0 and shallow rainfed rice was used as a proxy for intermittently
flooded rice fields.
Based on the work of Chen et al. (1993) and Sass et al. (1992) intermittently flooded rice was
assumed to have a flux rate that is 60% of flooded rice fields. Currently there are no data
readily available on intermittently flooded rice. The current estimating procedure probably
underestimates the flux of methane from this category, since it assumes that there is one
drought episode in every crop of shallow rainfed rice fields worldwide.
PART 2
4.57
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AGRICULTURE
TABLE 4-6
DEFAULT ACTIVITY DATA- HARVESTED RICE
Country
1990 Area
1 OOOs ha
Season Length
(days)
Continuously
Flooded
(%)
Dry
(%)
Intermittently Flooded
(%)
AMERICAS
USA
Belize
Costa Rica
Cuba
Dominican Rep
El Salvador
Guatemala
Haiti
Honduras
lamalca
Mexico
Nicaragua
Manama
Puerto Rico
Trinidad & Tobago
Argentina
Bolivia
Brazil
Chile
Columbia
•quador
Guyana
Paraguay
'era
Surinam
Jruguay
Venezuela
1114
2
S3
ISO
93
IS
IS
52
19
0
123
48
92
0
S
103
110
4450
35
453
266
68
34
185
58
108
119
123
139
103
139
103
123
139
123
123
123
130
123
103
123
103
121
101
101
121
124
100
123
101
167
123
138
103
100
10
10
100
98
10
10
40
10
40
41
10
5
75
45
100
25
18
79
53
40
95
50
84
100
100
90
0
90
90
0
2
90
90
60
90
60
59
90
95
25
55
0
75
76
21
47
10
5
SO
16
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
50
0
0
0
0
0
0
4.58
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AGRICULTURE
TABLE 4-6 (CONTINUED)
DEFAULT ACTIVITY DATA - HARVESTED RICE
Country
1990 Area
1 OOOs ha
Season Length
(days)
Continuously
Flooded
(%)
Dry
(%)
Intermittently Flooded
<*»
ASIA
Jrunei
Hong Kong
Syria
Turkey
India
Pakistan
Bangladesh
Surma
Nepal
Afghanistan
Bhutan
China
Indonesia
Iran
Iraq
Japan
Malaysia
Philippines
Sri Lanka
Taiwan
Thailand
Kampuchea
Laos
Vietnam
N Korea
S Korea
1
0
0
52
42321
103
10303
4774
1440
173
25
33265
10403
570
78
2073
2073
3413
793
700
9878
1800
625
6069
673
1237
82
123
123
123
107
103
132
139
90
103
169
115
110
103
123
123
123
98
122
119
123
134
123
119
103
103
79
100
100
too
53
100
14
42
29
100
21
93
78
100
100
96
96
54
65
97
22
34
II
65
67
91
21
0
0
0
IS
0
I*
15
4
0
is
2
IS
0
0
4
4
-12
7
3
12
27
49
7
13
1
0
0
, 0 ,
0
32
0
72
43
67
0
64
5
7
0
0
0
0
34
28
0
66
39
40
28
20
8
PART 2
4.59
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AGRICULTURE
TABLE 4-6 (CONTINUED)
DEFAULT ACTIVITY DATA - HARVESTED RICE
Country
1990 Area
1 OOOs ha
Season Length
(days)
Continuously
Flooded
(%)
Dry
(%)
EUROPE
Albania
Bulgaria
'ranee
Greece
•lungary
Italy
'ortugal
Romania
Spain
winer USSR
tanner Yugoslavia
2
II
20
15
II
208
33
37
81
624
8
123
103
139
103
123
102
123
123
103
103
123
100
100
100
100
100
100
100
100
100
100
100
0
0
0
0
0
0
0
0
0
0
0
Intermittently Flooded
(%)
0
0
0
0
0
0
0
0
0
0
0
PACIFIC
Australia
Rji
Solomon Islands
"apua/New Guinea
97
13
0
0
128
81
102
102
100
50
38
38
0
0
0
0
0
0
0
0
AFRICA
Algeria
Angola
Jenin
iurklna Faso
Surundi
Cameroon
C African Rep
Chad
Comoros
Congo
Egypt
Gabon
Gambia
Ghana
Guinea Bissau
Guinea
Ivory Coast
Kenya
Liberia
Madagascar
1
18
7
19
12
15
10
39
13
4
427
0
14
85
57
608
583
15
168
1135
138
121
123
123
167
103
123
123
100
121
123
121
123
139
123
123
123
139
123
167
100
100
10
89
25
25
25
25
100
25
100
25
90
24
25
8
6
25
0
35
0
0
90
II
75
75
75
75
0
75
0
75
10
76
75
47
87
75
94
19
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
45
7
0
6
46
4.60
-------
4
AGRICULTURE
TABLE 4-6 (CONTINUED)
DEFAULT ACTIVITY DATA- HARVESTED RICE
Country
Malawi
Mali
Mauritania
Morocco
Mozambique
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zaire
Zambia
Zimbabwe
1990 Area
1 OOOs ha
29
222
14
6
109
29
1567
3
73
339
5
1
1
0
375
21
37
393
II
0
Season Length
(days)
137
123
123
138
121
102
103
167
103
139
103
167
103
167
137
139
137
101
121
121
Continuously
Flooded
(%)
25
25
100
100
25
35
28
25
25
1
50
100
50
25
10
4
25
5
25
25
Dry
(%)
75
75
0
0
75
65
55
75
75
67
SO
0
SO
75
26
96
75
90
75
75
Intermittently Flooded
(%)
0
0
0
0
0
0
17
0
0
32
0
0
0
0
64
0
0
5
0
0
Source: Khalil (1993), personal communication.
PART 2
4.61
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AGRICULTURE
TABLE 4-7
SEASONAL AVERAGE EMISSION FACTORS CORRECTEDFOR AVERAGE TEMPERATURE
Growing Season
Average Temperature
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Emission Factor
kg/ha/day
Continuously Flooded
2.91
3.09
3.28
3.48
3.68
3.91
4.14
4.39
4.66
4.94
5.24
5.56
5.90
6.25
6.63
7.03
7.46
7.91
8.39
8.90
9.44
Intermittently Flooded
1.75
1.85
1.97
2.09
2.21
2.34
2.94
2.64
2.80
2.97
3.15
3.34
3.54
3.75
3.98
4.22
4.48
4.75
5.03
5.34
5.66
Source: Khalil (1993), personal communication
4.62
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AGRICULTURE
4.3.4 References
Aselmann, I. and P.J. Crutzen 1989: The global distribution of natural freshwater wetlands
and rice paddies, their net primary productivity, seasonality and possible methane
emission. J. Atm. Chem., 8, 307-358.
Bingemer, H.G. and P.J. Crutzen 1987: The production of methane from solid wastes. J.
Geophys. Res., 92(D), 2181-2187.
Blake, D.R. and F.S. Rowland 1988: Continuing worldwide increase in tropospheric
methane, 1978 to 1987. Science, 239, 1129-1131.
Bouwman, A.F. 1990: Exchange of greenhouse gases between terrestrial ecosystems and
the atmosphere. Ed. A.F. Bouwman, In Soil and the greenhouse Effect. John Wiley and
Sons, 62-127.
Bremner, J.M. and A.M. Blackmer 1982: Composition of soil atmospheres, In Methods of
soil analysis, Part 2, Chemical and Microbiological Properties, Agronomy Monograph No.
9,873-901.
Chen, Z., D. Li, K. Shao, and B. Wang 1983: Features of CH4 emission from rice paddy
fields in Beijing and Nanjing, China. Chemosphere, 26( I -4):239-246.
China Agricultural Yearbook, 1990. Agribookstore, Hampton, VA.
Cicerone, R.J., J.D. Shetter and C.C. Delwiche 1983: Seasonal variation of methane flux
from a California rice paddy. J. Geophys. Res., 88, 7203-7209.
Cicerone, R.J. and R.S. Oremland 1988: Biogeochemical aspects of atmospheric methane.
Global Biogeochem. Cycles, 2, 299-327.
Conrad, R. 1989: Control of methane production in terrestrial ecosystems, In Exchange of
Trace Gases between Terrestrial Ecosystems and the Atmosphere, eds. M.O. Andreae and
D.S. Schimel, 39-58.
Ehhalt, D.H. and U. Schmidt 1978: Sources and sinks of atmospheric methane. Pure Appl.
Geophys., .16,452-464.
Graedel, T.E. and J.E. McRae 1980: On the possible increase of the atmospheric methane
and carbon monoxide concentrations during the last decade. Geophys. Res. Lett, 7,977-
979.
Grist, D.H. 1986: Rice. Longman, Inc., New York, U.S.A. 6th edition.
Holzapfel-Pschorn, A., R. Conrad, and W. Seller 1985: Production, oxidation, and emission
of methane in rice paddies. FEMS Microbiology Ecology, 31, 343-351.
Holzapfel-Pschorn, A., and W. Seller 1986: Methane emission during a cultivation period
from an Italian rice paddy. J. Geophys. Res., 91, 11803-1181.4.
Huke, R.F. 1982: Rice area by type of culture; south, southeast and east Asia. International
Rice Research Inst, IRRI, Los Banos, Los Banos, Philippines.
IRRI, 1991: World Rice Statistics 1990. International Rice Research Inst., Los Banos,
Laguna, Philippines.
Khalil, M.A.K. 1993: Working Group Report: Methane Emissions from Rice Fields. In A.R.
van Amstel (ed.), Proceeding of an International IPCC Workshop on Methane and Nitrous
Oxide: Methods in National Emissions Inventories and Options for Control. RIVM Report
no. 481507003, Bilthoven, The Netherlands, pp. 239-244.
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AGRICULTURE
Khalil, MAK., RA Rasmussen, M.X. Wang, and LRen 1991: Methane emission from rice
fields in China; Environ. Sci. Tech., 25:979-981.
Lai, S., S. Venkataramani, and B.H. Subbaraya 1993: Methane flux measurements from
paddy fields in the tropical Indian region; Atmos. Environ., 27A:I69I-I694.
Undau, C.W., and P.K. Bollich 1993: Methane emissions from Louisiana first and ratoon
rice crop; Soil Science, 156:42-48.
Matthews, E., I. Fung, and J. Lerner 1991: Methane emission from rice cultivation;
Geographic and seasonal distribution of cultivated areas and emissions. Global
Biogeochem. Cycles, 5, 3-24.
Minami, K. 1993: Methane Emissions from Rice Production. In A.R. van Amstel (ed.),
Proceeding of an International IPCC Workshop on Methane and Nitrous Oxide: Methods
in National Emissions Inventories and Options for Control. RIVM Report no. 481507003,
Bilthoven, The Netherlands, pp. 143-162.
Minami, K., and K. Yagi 1988: Method for measuring methane flux from rice paddies. Jpn. J.
Soil Sci. Plant Nutr., 59, 458-463 (in Japanese).
Minami, K., K. Kumagai, K. Yagi, and H. Tsuruta 1992: unpublished.
Neue, H.U., P. Becker-Heidmann and H.W. Scharpenseel. 1990: Organic matter dynamics,
soil properties and cultural practices in rice lands and their relationship to methane
production. Ed. A.F. Bouwman, In Soils and the Greenhouse Effect. John Wiley and Sons,
457-466
Nouchi, I., S. Mariko, and K. Aoki 1990: Mechanisms of methane transport from the
rhizosphere to the atmosphere through rice plant. Plant physiology, 94, 59-66.
Nozaki, M. 1989: Rice cultivation in Tropical Africa. Trop. Agr. Rec. Center. (In Japanese).
Patrick, W.H. Jr. 1981: The role of inorganic redox systems in controlling reduction in
paddy soils. In Proc. Symp. Paddy Soil, 107-117, Science Press, Beijing, Spring Verlag.
Ponnamperuma, F.N. 1972: The chemistry of submerged soils, Adv. Agron., 24, 29-69.
Rasmussen, RA, and MAK. Khalil 1981: Increase in the concentration of atmospheric
methane. Atmos. Environ., 15,883-886.
Rasmussen. RA., and M.A.K. Khalil 1984: Atmospheric methane in the recent and ancient
atmospheres: concentrations, trends, and interhemispheric gradient J. Geophys. Res.,
89(D), 11599-11605.
Rowland, F.S. 1991: Stratospheric ozone in the 21st century, The chlorofluorocarbon
problem, Environ. Sci. Technol., 25, 622-628.
Sass, R.L, F.M. Fisher, P.A. Harcombe, and FT. Turner 1991 a: Mitigation of methane
emissions from rice fields: possible adverse effects of incorporated rice straw. Global
Biogeochemical Cycles, 5(3): 275-287.
Sass, R.L, F.M. Fisher. Y.B. Yang, FT. Turner, and M.F. Jund 1992: Methane emissions from
rice fields: the effect of flood water management Global Biogeochemical Cycles, 6(3): 249-
262.
Seller, W., A. Holzapfel-Pschorn, R. Conrad, and D. Scharffe 1984: Methane emissions
from rice paddies. J. Atmos. Chem., I, 241-268.
Seller, W., and R. Conrad 1987: Contribution of tropical ecosystems to the global budgets
of trace gases, especially CH4, H2, CO and N2O, In R.E. Dickinson (Ed.), Geophysiology
of Amazonia. Vegetation and Climate Interactions, 133-160, Wiley and Sons, New York.
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Sheppard, J.C., H. Westberg, J.F. Hopper, K. Ganesan, and IP. Zimmerman 1982: Inventory
of global methane sources and their production rates.]. Geophys. Res., 87(C), 1305-1312.
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continuous record on the influence of daytime, season, and! fertilizer treatment on
methane emission rates from an Italian rice paddy. J. Geophys. Res., 94, 16405-16416.
Steele, L.P., E.J. Dlugokencky, P.M. Lang, P.P. Tans, R.C. Maitin, and K.A. Masarie 1992:
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Yamane, I., and K. Sato 1963: Decomposition of plant constituents and gas formation in
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AGRICULTURE
4.4 Agricultural Burning
4.4.1 Introduction
Where there is open burning associated with agricultural practices, a number of
greenhouse gases (GHG) are emitted from combustion. All burning of biomass produces
substantial CO2 emissions. However, in agricultural burning, the CO2 released is not
considered to be net emission. The biomass burned is generally replaced by regrowth
over the subsequent year. An equivalent amount of carbon is removed from the
atmosphere during this regrowth, to offset the total carbon released from combustion.
Therefore the long term net emissions of CO2 are considered to be zero. Agricultural
burning releases other gases in addition to CO2 which are by-products of incomplete
combustion: methane, carbon monoxide, nitrous oxide, and oxides of nitrogen, among
others. These non-CO2 trace gas emissions from biomass burning are net transfers from
the biosphere to the atmosphere. It is important to estimate the emissions in national
inventories.
There are two major types of agricultural burning addressed in this section — savanna
burning and field burning of crop residues. The approach is essentially the same as that
used for non-CO2 trace gases for all burning of unprocessed biomass, including traditional
biomass fuels and open burning of cleared forests. For all these activities, there is a
common approach in the proposed methodology, in that crude estimates of non-CO2
trace gas emissions can be based on ratios to the total carbon released. The carbon trace
gas releases (CH4 and CO) are treated as direct ratios to total carbon released. To handle
nitrogen trace gases, nitrogen to carbon ratios are used to derive total nitrogen released
and then emissions of N2O and NOX are estimated based on ratios of these gases to total
nitrogen released. Tables B and C provide suggested default values for non-CO2 trace gas
emission ratios. These are presented with ranges, which emphasize their uncertainty.
However, the basic calculation methodology requires that users select a best estimate
value.2
The calculation of immediate trace gas emissions, based on the default emission ratios
provided in Tables B and C, produces relatively crude estimates with substantial
uncertainties. Use of specific emission ratios which vary by 'type of burning, region, etc.
may allow for more precise calculations. The calculations described here ignore the
contemporary fluxes associated with past burning activities. These delayed releases are
known to exist, but are poorly understood at present. This and other possible
refinements are discussed at the end of this section.
4.4.2 Prescribed Burning: Savannas
Background
The term savanna refers to tropical and subtropical vegetation formations with a
predominantly continuous grass cover, occasionally interrupted by trees and shrubs.4
These formations exist in Africa, Latin America, Asia, and Australia. The growth of
vegetation in savannas is controlled by alternating wet and dry seasons: most of the
growth occurs during the wet season; man-made and/or natural fires are frequent and
generally occur during the dry season. The global area of sava.nnas is uncertain, in part due
to lack of data and in part due to differing ecosystem classifications. Estimates of the areal
extent of savannas range from 1300-1900 million hectares worldwide, about 60% of which
PART 2
4.67
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AGRICULTURE
are humid savannas (annual rainfall of 700 mm or more) and 40% are arid savannas (annual
rainfall of less than 700 mm).5 Large-scale burning takes place primarily in the humid
savannas because the arid savannas lack a sufficient grass cover to sustain fire. Humid
savannas are burned every one to four years on average with the highest frequency in the
humid savannas of Africa.
Savannas are intentionally burned during the dry season primarily for agricultural purposes
such as ridding the grassland of weeds and pests, promoting nutrient cycling, and
encouraging growth of new grasses for animal grazing. Savanna burning may be
distinguished from other biomass burning activities like open forest clearing because there
is little net change in the ecosystem biomass in the savanna after the vegetation regrows
during the wet season. Consequently, while savanna burning results in instantaneous gross
emissions of CO2, it is reasonable to assume that the net carbon dioxide released to the
atmosphere is essentially zero because the vegetation typically regrows between burning
cycles. Savanna burning does release several other important trace gases: methane (CH4),
carbon monoxide (CO), nitrous oxide (N2O), and oxides of nitrogen (NOX, i.e., NO +
NO,).
Estimates of global emissions of these gases due to savanna burning have been based on
estimates of the annual instantaneous gross release of carbon from this activity and ratios
of the other trace gases released from burning to total carbon released by burning.
Estimates of the annual instantaneous gross release of carbon from savanna burning are
highly uncertain because of lack of data on the aboveground biomass density of different
savannas, the savanna area burned annually, the fraction of aboveground biomass which
actually burns, and the fractions which oxidizes (i.e., combustion efficiency). The
methodology that is proposed in the next section although conceptually quite simple,
takes these factors into account. The approach allows for estimation of non-CO2 trace
gases released by savanna burning based on default data sets and assumptions from average
literature values for various regions and types of savannas. It also allows for more accurate
national estimates if data and assumptions can be developed to reflect national average
conditions accurately. Nonetheless, a wide variety of technical details and open scientific
issues remain important research topics.
Calculations
There are two basic components to the calculation. First, it is necessary to estimate the
total amount of carbon released to the atmosphere from savanna burning. These are not
considered net emissions, but are needed to derive non-CO2 trace gas emissions which
are net emissions. What is required is the annual area burned for the various types of
savannas, where type is based primarily upon above and below ground biomass, and
perhaps climatological conditions and nutrient status. If data are not directly available,
estimates can be derived based on total savanna area8 and average percentages of savanna
burned annually, as shown in Table A. Based on the area and type of savanna burned, the
amount of carbon released can be calculated (a reflection of biomass densities, fractions
burned, carbon contents and combustion efficiencies). The second component of the
calculation is the same as for other biomass burning categories -- emission ratios are
applied to estimate the amount of trace gas released based on the amount of carbon
released (Table B provides default emission ratios).
The approach formally recognizes that countries generally possess more than one savanna
type, each with different characteristics, such as vegetative cover, that would affect trace
gas emissions from burning. Also, the savanna area within a country may not be burned all
at once, but rather in stages over the course of the dry season. Since the amount and
nature (e.g., moisture content) of the vegetation changes during the year, factors such as
biomass exposed to burning and burning efficiency will vary among the savanna areas
4.68
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AGRICULTURE
burned at different times. The data requested by this methodology focus upon country-
specific types of savannas and the country-specific rate of burning for each type.
It is also recognized that national and regional estimates of the percent of savanna area
burned annually are highly uncertain. An example selection of regional estimates is
included in Table A. Though regional variability is great, the methodology, by focusing upon
a simple classification of savanna type and the burning by type, can be implemented using
data that are available to most countries. The methodology is intended to be flexible to
allow users to define the savanna types and/or geographic subregions for calculations.
National experts are encouraged to carry out the calculations at the finest levels of detail
for which credible data can be obtained. Finally, by varying che rate and/or type of savannas
burned, national experts can easily test to the sensitivity of the calculated emissions to
the uncertainties in the data.
Part I: Total Carbon Released From Savanna Burning
In order to calculate the carbon released to the atmosphere from savanna burning, these
data are required:
• Area of savanna;
• Fraction of savanna area burned annually;
• Average aboveground biomass density (tonnes dry matter/hectare) of savannas;
• Fraction of aboveground biomass which actually burns;
• Fraction of aboveground biomass that is living;
• Fraction of living and of dead aboveground biomass oxidized, (i.e., combustion
efficiency of living and dead biomass); and
• Fraction of carbon in living and dead biomass.
Not all of these data must be provided by the user. Initially one could pool the living and
dead biomass if data are not available. More importantly, Table A provides much of the
basic default data that only need to be refined for country-specific relevance. Given the
data, the steps to calculate emissions are not overly difficult One simply calculates from
the area burned the total carbon released based upon the factors listed above. In addition
to the data in Table A, other recommended default values are included in the step-by-step
discussion below.
The following equations summarize the calculations to estimate the total carbon released
due to the burning of savannas:
EQUATION I
Area of Savanna Burned Annually (ha)
Total Area of Savanna (ha) x Fraction Burned Annually
PART 2
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EQUATION 2
Biomass Burned (t dm)
Area of Savanna Burned Annually (ha) x Aboveground Biomass Density (t
dm/ha) x Fraction Actually Burned
EQUATION 3
Carbon Released from Live Biomass (t C)
Biomass Burned (t dm) x Fraction that is Live x Combustion Efficiency x
Carbon Content of Live Biomass (t C/t dm)
EQUATION 4
Carbon Released from DeadBiomass (t C)
Biomass Burned (t dm) x Fraction that is Dead x Combustion Efficiency x
Carbon Content of Dead Biomass (t C/t dm)
EQUATION 5
Total Carbon Released (t C)
C Released from Live Material (t C) + C Released from Dead Material (t C)
In the first equation, the savanna area in the country is multiplied by the percentage of the
savanna area that is burned annually, if statistics on area burned annually are not directly
available. If national experts have data on the area burned annually they should use this and
begin with equation 2. In the second, area burned is multiplied by aboveground dry
biomass per hectare (ha) on the savanna at the time of burning and the fraction of biomass
which actually burns. Regional estimates of rates of savanna burning and biomass densities
are presented in Table A. The fraction actually burned accounts for the fact that when
savannas are burned, not all of the biomass on each hectare is actually exposed to flame. If
detailed information is not available, a general default value in the range of 0.8-0.85 is
recommended.
The aboveground biomass density before burning is a function of the type of savanna being
burned and the time of year in which burning occurs.1 The values for West African
savannas provided in Table A correspond to mid-season fires, except for those of the
Sahel where burning occurs early. If statistics on maximum biomass density and fraction of
maximum biomass density present at the time of burning are not available, countries can
use an average biomass density instead. According to this analysis, average savanna biomass
densities are lowest in tropical Asia, at about 5 tons per hectare (t/ha),1 average around
6.6 t/ha in tropical Africa and tropical America,14 and range between 2 and 6 t/ha in
Australia.15 These estimates have an uncertainty of ±30% based on field measurements.16
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As mentioned, these regional average densities are presented in Table A and can be used
as default values if average biomass density for a specific country or savanna type is not
known.
In the third and fourth equations, the living and the dead portions of aboveground biomass
burned are multiplied by their respective combustion efficiencies and carbon contents.
Estimates of the fraction of aboveground biomass that is living for West African savannas
range from 20 to 55% (Table A). Data suggest that the live portion burns with a
combustion efficiency that ranges between 65 and 95% and the dead portion with
essentially 100% efficiency.17 If combustion efficiencies are not available, 80% and 100% for
the living and dead portions, respectively, can be used. If country or ecosystem values are
not available, then the values 0.45 t C/t dry biomass and 0.40 t C/t dry biomass can be
used as default values for the carbon contents of the living and dead portions,
. , 18
respectively .
The total carbon released from savanna burning (Equation 5) is estimated by summing the
carbon released from the living and the dead biomass fractions, calculated in Equations 3
and 4.
Part 2: Non-CO2 Trace Gas Emissions
Once the carbon released from savanna burning has been estimated, the emissions of CH4,
CO, N2O, and NOX can be calculated using emission ratios. (Default values are presented
in Table B.)19 The amount of carbon released due to burning is multiplied by the emission
ratios of CH4 and CO relative to total carbon released to yield emissions of CH4 and CO
(each expressed in units of C). The emissions of CH4 and CO are multiplied by 16/12 and
28/12, respectively, to convert to full molecular weights.
To calculate emissions of N2O and NOX, first the carbon released is multiplied by the
estimated ratio of nitrogen to carbon (N/C ratio) in savanna biomass by weight (0.006 is a
general default value for savanna biomass burning ). This yields the total amount of
nitrogen (N) released from the biomass burned. The total N released is then multiplied by
the ratios of emissions of N2O and NOX relative to the N released to yield emissions of
N2O and NOX (expressed in units of N). To convert to full molecular weights, the
emissions of N2O and NOX are multiplied by 44/28 and 30/14, respectively.
The non-CO2 trace gas emissions calculations from burning are summarized as follows:
CH4 Emissions = (carbon released) x (emission ratio) x 16/12
CO Emissions = (carbon released) x (emission ratio) x 28/12
N2O Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 44/28
NOX Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 30/14
PART 2
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TABLE A
REGIONAL SAVANNA STATISTICS
Region
Tropical America
Tropical Asia
Tropical Africa
Sahel zone
North Sudan zone
South Sudan zone
Guinea zone
Australia
Fraction of
Area Burnt
Annually to
Total Savanna
0.50
0.50
0.75
0.05-0. 15a
0.25-0.50a
0.25-0.50a
0.60-0.80a
5-70
Aboveground
Biomass Density
(t dm/ha)
6.6 ±1.8
4.9
6.611.6
0.5-2.S3
2-4a
3-6a
4-8a
2.1-6
Fraction of
Biomass
Actually
Burned
0.95
0.85
0.85
0.9-1.0
Fraction of
Aboveground
Biomass that is
Living
0.20
0.45
0.45
0.55
Sources: Hao et al., 1990, except where noted. These figures are growing season average biomass values, considered
most appropriate for general default values
a Menaut et al. (1991) These figures are maximum biomass values. For these arid sub-regions, maximums are
considered the most appropriate default values.
Note: Biomass density is in tonnes of dry matter (dm) per hectare (ha).
TABLE B
EMISSION RATIOS FOR SAVANNA BURNING CALCULATIONS
Compound
ov
CO '
N203
NOX3
0.004
0.06
0.007
0.121
Ratios
(0.002 - 0.006)
(0.04 - 0.08)
(6.005 - 0.009)
(0.094-0.148)
Sources: ' Delmas, 1993
2 Lacaux, et al., 1993
3 Crutzen and Andreae, 1990
Note: Ratios for carbon compounds, i.e., CH4 and CO, are mass of
carbon compound released (in units of C) relative to mass of total
carbon released from burning (in units of C); those for the nitrogen
compounds are expressed as the ratios of emission relative to total
nitrogen released from the fuel.
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4.4.3 Prescribed Burning: Agricultural Crop
Wastes
Background
Large quantities of agricultural wastes are produced, from farming systems worldwide, in
the form of crop residue.22 Burning of crop residues, like the burning of savannas, is not
thought to be a net source of carbon dioxide (COj) because the carbon released to the
atmosphere during burning is reabsorbed during the next growing season. However, crop
residue burning is a significant net source of CH4, CO, NOX, and N2O. This section
accounts for emissions of these non-CO2 gases from field burning of agricultural crop
residues (Burning of agricultural crop residues as an energy source is covered in the Energy
chapter, in the section entitled Traditional Biomass Fuels).
The amount of agricultural wastes produced varies by country, crop, and management ^
system. Cereal crops produce between 0.6 and 2.5 tonnes of straw per tonne of grain.
For example, wetland rice cultivated under a moderate level of management in the
Philippines was found to produce between 0.6 and 0.9 tonnes of straw per tonne of
grain. Approximately 3.1 billion tonnes of crop residue are produced each year^with
about 60% originating in the developing world, and 40% in the developed world.
Burning of agricultural wastes in the fields is a common practice in the developing world. It
is used primarily to clear remaining straw and stubble after harvest and to prepare the
field for the next cropping cycle. In Southeast Asia, burning is the major disposal method
for rice straw,26 which accounts for about 31% of the agricultural waste in the developing
world. Sugar cane residues, which make up about 11% of the world's agricultural waste.
are primarily disposed of by burning.27 It has been estimated that as much as 40% of the
residues produced in developing countries may be burned in fields, while the percentage is
lower in developed countries. Estimates suggest that approximately 425 Tg dry matter
agricultural wastes (-200 Tg C) are burned in the fields in developing countries and that
about one-tenth as much is burned in developed countries.
Calculations
The methodology for estimating greenhouse gas emissions from burning of agricultural
wastes is based, as in savanna burning, on I) total carbon released, which is a function of
the amount and efficiency of biomass burned, the carbon content of the biomass, and 2)
the application of emission ratios of CH4 and CO to total carbon released, and Np and
NOX to total nitrogen released from biomass fires which lire available from the scientific
literature on biomass burning. Default values are provided in Table C.
Part I: Total Carbon Released from Burning Agricultural Residues
Data required, for each crop type, to calculate the amount of carbon burned in agricultural
wastes are listed below:
• Amount of crops produced with residues that are commonly burned,
• Ratio of residue to crop product
• Fraction of residue burned
• Dry matter content of residue
• Fraction oxidized in burning (combustion efficiency
• Carbon content of the residue
PART 2
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There are standard default or literature values available for many of these data. Table D
provides a summary of available default data. The most important data for users to provide
are the actual amount of crops produced (by type) with residues that are commonly
burned. Annual crop production statistics by country for most of the crops from which
residues are burned may be found in the FAO Production Yearbooks.30 Crop-specific data
for each country on ratios of residue to crop, fraction of residue burned, dry matter
content of residue, and carbon content of residue can be incorporated at any time to
replace the default values. The essential data needed from the countries are the actual
amount of crops with residues that are commonly burned. A potentially very valuable data
source is the recent study the BUN/UNCED study by Professor D. Hall (and others) of
Kings College, London.
From production data one can estimate the actual material (in carbon units) that is
burned. One simple procedure is shown below:
Total carbon released =
annual production data (tonnes of biomass per year) for each crop,
x the ratio of residue to crop product (fraction),
x the average dry matter fraction (tonnes of dry matter / tonnes of
biomass),
x the fraction actually burned in the field,
x the combustion efficiency (fraction),
x the carbon fraction (tonnes of carbon / tonnes dry matter)
It is highly desirable to use country specific data for these values wherever possible.
Example estimates of residue/crop product ratios, average dry matter fraction and carbon
fraction for certain crops are presented in Table D.32 If no other data are available, the
following assumptions regarding the percentage of crop residue burned in the field can be
used as very crude default factors: for developing countries 0.25, and for developed
countries a much smaller share possibly 0.10 or less.33 A default value of 0.90 can be used
to account for the approximate 10% of the carbon that remains on the ground
(combustion efficiency).34
Part 2: Non-CO2 Trace Gas Emissions
Once the carbon released from field burning of agricultural resides has been estimated, the
emissions of CH4, CO, N2O, and NOX can be calculated based on emission ratios (default
values are provided in Table C).35 The amount of carbon released due to burning is
multiplied by the emission ratios of CH4 and CO relative to total carbon to yield
emissions of CH4 and CO (each expressed in units of C). The emissions of CH4 and CO
are multiplied by 16112 and 28/12, respectively, to convert to full molecular weights.
To calculate emissions of N2O and NOX, first the total carbon released is multiplied by the
estimated N/C ratio of the fuel by weight to yield the total amount of nitrogen (N)
released. Some crop specific values are given in Table D and 0.015 is a general default
value for crop residues.36 The total N released is then multiplied by the ratios of
emissions of N2O and NOX relative to the N content of the fuel to yield emissions of N2O
and NOX (expressed in units of N). To convert to full molecular weights, the emissions of
N2O and NOX are multiplied by 44/28 and 30/14, respectively.37
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The calculation for trace gas emissions from burning is summarized as follows:
CH4 Emissions = Carbon Released x (emission ratio) x 16/12
CO Emissions = Carbon Released x (emission ratio) x 28/12
N2O Emissions = Carbon Released x (N/C ratio) x (emission ratio) x 44/28
NOX Emissions = Carbon Released x (N/C ratio) x (emission ratio) x 30/14
TABLE C
EMISSION RATIOS FOR AGRICULTURAL RESIDUE BURNING
CALCULATIONS
Compound
Ratios
CH4'
CO2
NjO3
NOX3
0.005 Range 0.003 - 0.007
0.06 Range 0.04 - 0.08
0.007 IHange O.OOS - 0.009
0.121 Range 0.094-O.M8
Sources:
1 Delmas, 1993
2 Lacaux, et al.. 1993
Crutzen and Andreae. 1990
Note: Ratios for carbon compounds, i.e., CH4 and CO, are mass of carbon compound released
(in units of C) relative to mass of total carbon released from burning (in units of C); those for the
nitrogen compounds are expressed as the ratios of emission relative to total nitrogen released
from the fuel.
TABLE D
SELECTED CROP RESIDUE STATISTICS
Product
Residue/Crop Product
Dry Matter Content Carbon Content
(%) (%dm)
Nitrogen-Carbon
(N/C) Ratio
Wheat
Barley
Maize
Oats
Rye
Rice
Millet
Sorghum
1.3
1.2
1
1.3
1.6
1.4
1.4
1.4
78-88 48.53
78-88 45.67
30-50 47.09
78-88 41.44
0.012
0.02
0.014
0.0)6
0.02
Pulse
Pea
Bean
Soya
Potatoes
Feedbeet
Sugarbeet
Jerusalem artichoke
Peanut
1.5
2.1
2.1
0.4
0.3
0.2
0.8
1
30-60 42.26
10-20 ' 40.72'
10-20 ' 40.72'
0.05
Sources: Strehler and Stutzle, 1 987
Sugarbeet data from Ryan and Openshaw, 1991
Nitrogen content from Barnard and Kristoferson, 1 985
Note: ' These statistics are for beet leaves.
PART 2
4.75
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Possible refinements of the basic calculations
The basic calculations presented above address the immediate release of non-CO2 trace
gases when savannas or crops are burned. This is believed to be the most important effect
of biomass burning on GHG emissions and the best characterized at present. However,
there are other issues not treated in these calculations. The effect of past burning on
current emissions is one such issue. The longer-term release or uptake of these gases
following burning is an important research issue and may eventually be included in
refinements of the calculations. In particular, grassland fires (savanna burning) may perturb
the soils sufficiently to release additional N2O and NOX. Little is known about the
magnitude of this flux so these emissions may not be included in the first application of the
methodology. It is less likely that such delayed releases are significant after field burning of
agricultural residues, but this may also require further study.
Long term changes in soil carbon are certainly possible as a result of agricultural practices.
In the land use change and forestry chapter, there is A general default assumption that soil
carbon is gradually lost from agricultural lands over many years after forests are cleared. In
fact, depending on the specific agricultural and soil management practices (including
burning) which are used, there may be a variety of impacts on soil carbon. For example,
repeated burning of savannas and crop residues in fields may create a store of carbon as
charcoal which increases over time. This is an area which requires further research and
may lead to more detailed emissions estimation methods in the future.
In addition, agricultural practices (e.g. overgrazing) which degrade the productivity of
grasslands or other agricultural lands reduce the amount of aboveground biomass which
regrows and could be considered a gradual emissions source for carbon dioxide. This
situation is not included in the basic calculations, but could be included in more refined
calculations. National experts should determine whether or not this is important for their
country, and whether or not they are able to provide input data.
4.4.4 References: Agricultural Burning
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global dimate. Paper presented at the Chapman Conference on Global Biomass Burning:
Atmospheric, Climatic, and Biospheric Implications, 19-23 March 1990, Williamsburg,
Virginia.
Barnard, G.W. 1990. Use of agricultural residues as fuel. In: Pasztor, J., and LA.
Kristoferson (eds.). Bioenergy and the Environment. Westview Press, Boulder, Colorado, pp.
85-112.
Barnard, G.W., and LA. Kristoferson. 1985. Agricultural Residues as Fuel in the Third World.
Technical Report No. 5. Earthscan, London.
Bolin, B., ET. Degens, P. Duvigneaud, and S. Kempe. 1979. The global biogeochemical
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Carbon Cycle. SCOPE 13. Wiley, Chichester. pp. 1-56.
Bouliere, F., and M. Hadley. 1970. The ecology of tropical savannas. Annual Review of
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Bucher, E.H. 1982. Chaco and Caatinga-South American arid savannas, woodlands and
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Studies 42). Springer-Verlag, Berlin, pp. 48-79.
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Coutinho, LM. 1982. Ecological effects of fire in Brazilian cerrado. In: Huntley, B.J., and
B.H. Walker (eds.). Ecology of Tropical Savannas. (Ecological Situdies 42). Springer-Verlag,
Berlin, pp. 273-291.
Crutzen, P.J., M.O. Andreae. 1990. Biomass burning in the Tropics: Impact on atmospheric
chemistry and biogeochemical cycles. Science 250:1669-1678.
Crutzen, P.j. 1983. Atmospheric interactions — Homogenous gas reactions of C, N, and S
containing compounds. In: Bolin, B., and R.B. Cook (eds.). 7'he Major Biogeochemical Cycles
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Delmas, R. 1993. An Overview of Present Knowledge on Methane Emission from Biomass
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February 1993, Amersfoort, NL RIVM Report no. 481507003, Bilthoven, NLJuly.
Delmas, R.A. and D. Ahuja. 1993. Estimating National Methane Emissions from
Anthropogenic Biomass Burning. Working Group Report: Methane Emissions from
Biomass Burning, in A.R. van Amstel (ed.), Proceedings of an International IPCC Workshop:
Methane and Nitrous Oxides, Methods in National Emissions Inventories and Options for Control,
3-5 February 1993, Amersfoort, NL RIVM Report no. 481507003, Bilthoven, NU July.
FAO/UNEP (Food and Agriculture Organization of the United Nations/United Nations
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Galbally, I.E. 1985. The emission of nitrogen to the remote atmosphere: Background
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pp. 27-53.
Gonzalez-Jimenez, E. 1979. Primary and secondary productivity in flooded savannas. In:
UNESCO/UNEP/FAO (ed.). Tropical grazing land ecosystems of Venezuela. Nat Resour.
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Haggar, R.J. 1970. Seasonal production of Andropogon gayanus, I. Seasonal changes in field
components and chemical composition. Journal of Agricultural Science 74:487-494.
Hao, W.M., M.H. Liu, and P.J. Crutzen. 1990. Estimates of annual and regional releases of
CO2 and other trace gases to the atmosphere from fires in the tropics, based on the FAO
statistics for the period 1975-1980. In: Goldammer, J.G. (ed.). fire in the Tropical Biota,
Ecosystem Processes and Global Challenges. Springer-Verlag, Berlin, pp. 440-462.
Harris, D.R. 1980. Tropical savanna environments: Definition, distribution, diversity, and
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Hopkins, B. 1965. Observations on savanna burning in the Olokemeji Forest Reserve,
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Howden, S.M., G.M. McKeon, J.C. Scanlan, J.O. Carter, and D.H. White. Methods for
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Huntley, B.J. 1982. South African savannas. In: Huntley, B.J., and B.H. Walker (eds.).
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PART 2
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Huntley B.J., andJ.W. Morris. 1982. Structure of Nylsvley savanna. In: Huntley, B.J., and
B.H. Walker (eds.) Ecology of Tropical Savannas. (Ecological Studies 42). Springer-Verlag,
Berlin, pp. 433-455.
Johansson, T.B., H. Kelly, A.K.N. Reddy, and R.H. Williams. 1992. Renewable Energy: Sources
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Lacaux.J.P., H. Cachierand R. Delmas. 1993. Biomass Burning in Africa: An Overview of
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Environment: The Ecological, Atmospheric and Climatic Importance of Vegetation Fires. J. Wiley &
Sons Ltd.
Lacey, C.J., J. Walker, and I.R. Nolde. 1982. Fire in Australian tropical savannas. In:
Huntley, B.J., and B.H. Walker (eds.). Ecology of Tropical Savannas. (Ecological Studies 42).
Springer-Verlag, Berlin, pp. 246-272.
Lanly.J.P. 1982. Tropical Forest Resources. Food and Agriculture Organization of the United
Nations (FAO) Paper 30. FAO, Rome.
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Levine, J.S. (ed.). 1990. Global Biomass Burning: Atmospheric, Climatic and Biospheric
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Lieth, H. 1978. Patterns of Primary Productivity in the Biosphere. Hutchinson Ross,
Stroudsberg.
Lobert, J.M., D.H. Scharffe, W.M. Hao, and P.J. Crutzen. 1990. Importance of biomass
burning in the atmospheric budgets of nitrogen-containing gases. Nature 346:552-554.
Menaut, J.C., L Abbadie, F. Lavenu, Ph. Loudjani, and A. Podaire. 1991. Biomass burning in
West African savannas. In: Levine, J. (ed.). Global Biomass Burning. MIT Press, Cambridge, in
press.
Menaut, J.C., and J. Cesar. 1982. The structure and dynamics of a West African savanna. In:
Huntley, B.J., and B.H. Walker (eds.). Ecology of Tropical Savannas. (Ecological Studies 42).
Springer-Verlag, Berlin, pp. 8-100.
Menaut, J.C. 1990. B/omoss burning in West African savannas. Presentation given at the
Chapman Conference on Global Biomass Burning. Williamsburg, Virginia, March 19-23.
Proceedings forthcoming: MIT Press, Cambridge, Massachusetts.
Ponnamperuma, F.N. 1984. Straw as a source of nutrients for wetland rice. In: Organic
Matter and Rice. International Rice Research Institute, Los Banos. pp. 117-135.
San Jose, J.J., and E. Medina. 1976. Organic matter production in the Trachypogon savannas
in Venezuela. Tropical Ecology 17:113-124.
Seiler, W., and P.J. Crutzen. 1980. Estimates of gross and net fluxes of carbon between the
biosphere and the atmosphere from biomass burning. Climatic Change 2:207-247.
Singh, K.P., and R. Misra. 1978. Structure and Functioning of Natural, Modified and Silvicultural
Ecosystems of Eastern Utter Pradesh. Technical Report MAB Research Project, Banaras
Hindu University, Varanasi.
Strehler, A., and W. Stiitzle. 1987. Biomass residues. In: Hall, D.O., and R.P. Overend
(eds.). Biomass: Regenerab/e Energy. John Wiley, Chichester. pp. 75-102.
U.S. HEW (U.S. Department of Health, Education, and Welfare). 1970. Air Quality Criteria
for Carbon Monoxide. U.S. HEW, Washington, D.C.
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Whittaker, R.H., and G.E. Likens. 1975. The biosphere and Man. In: Lieth, H., and R.H.
4.4.5 Endnotes
I It is important to note, as discussed in the introduction to this document, that
there is an intentional double counting of carbon emitted from combustion. First,
CO2 is calculated based on the assumption that all carbon in fuel is emitted as
CO2. Methods are provided to then estimate portions of total carbon which are
emitted as CH4 and CO. The reasons for this double counting are discussed in
the introduction. For biomass combustion, CO2 emissions are frequently not
considered net emissions, and this is the cases for agricultural burning. One could
argue, in such cases, that this burning could be considered a short term sink of
CO2. That is, a portion of carbon in biomass is being released as net emissions of
CH4 and CO, while regrowth is removing the full aimount of the original carbon
from the atmosphere in the next cycle. Each year plants take up a certain amount
of carbon from the atmosphere. When they are burned some of that carbon is
converted to CO, and CH4, so that some amount less than the total CO2 taken
up by the plants is re-emitted as CO2. See Howden et al. (in press), for a more
detailed discussion of this proposal. Treating emissions of CO and CH4 to the
atmosphere, as a sink for atmospheric CO2, however, is inconsistent with the
proposed IPCC emissions methodology, for the same reasons that some of the
carbon emissions from fossil fuel are double counted. Most importantly, the
other carbon compounds emitted are converted back into CO2 in the
atmosphere over periods of days up to a decade or so. Thus, over the time
horizons of interest for CO2, (i.e. more than 100 years) there is no sink of CO2.
2 Emissions inventory developers are encouraged to provide estimates of
uncertainty along with these best estimate values where possible or to provide
some expression of the level of confidence associated with various point
estimates provided in the inventory. Procedures for reporting this uncertainty or
confidence information are discussed in Volume I: Reporting Instructions.
3 Emission ratios used in this section are derived from Crutzen and Andreae
(1990), Delmas (1993), Delmas and Ahuja (1993) and Lacaux, etal. (1993) as
presented in tables. They are based on measurements in a wide variety of fires,
including forest and savanna fires in the tropics and laboratory fires using grasses
and agricultural wastes as fuel. In many cases these ratios are general averages for
all biomass burning. Research will need to be conducted in the future to
determine if more specific emission ratios, e.g., speicific to the type of biomass and
burning conditions, can be obtained. Also, emission ratios vary significantly
between the flaming and smoldering phases of a fire. CO2, N2O, and NOX are
mainly emitted in the flaming stage, while CH4 and CO are mainly emitted during
the smoldering stage (Lobert et al., 1990). The relsitive importance of these two
stages will vary between fires in different ecosystems and under different climatic
conditions, and so the emission ratios will vary. As inventory methodologies are
refined, emission ratios should be chosen to represent as closely as possible the
ecosystem type being burned, as well as the characteristics of the fire.
4 Bouliere and Hadley, 1970
5 Bolin etal. (1979), Whittaker and Likens (1975), Lanly (1982), Laceyetal.
(1982), and Hao etal. (1990).
6 Harris, 1980; Bucher, 1982; Huntley, 1982; all as cited in Hao et al., 1990
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10
II.
12
If grazing pressure coupled with burning too often reduces biornass (i.e., degrades
the quality of savannas), then this needs to be considered as a carbon dioxide
source. This is not assumed in the basic calculations but could be included as a
refinement if considered important.
Most countries with significant savanna area should have national statistics on the
total area, but FAO publications (e.g. FAO, 1993) also provide country specific
estimates.
If the area of savanna is not readily available, then the area of "open, broadleaved
forests," including open, broadleaved, fallow areas, as defined by the U.N. Food
and Agriculture Organization in FAO (1993) can be used as an estimate. This land
area, corresponds to "mixed broadleaved forest-grassland tree formations with a
continuous dense grass layer in which the [woody vegetation covers] more than
10% [of the area]" (Lanly, 1982). FAO (1993) provides 1990 estimates of this
area, by country, for tropical America, Asia, and Africa. Hao et al. (1990) provide
an estimate of the humid savanna area in Australia, based on work by Lacey et al.
(1982).
It is hoped that individual countries have this information since it is needed to
execute the proposed methodology. Regional estimates of these statistics are
provided by Menaut (1990) and Hao et al. (1990) and reproduced in a table. More
country-specific research is clearly needed on this issue before accurate
inventories can be developed. This research should include data on savanna area
burned annually, savanna biomass densities, live fractions of biomass, burning
efficiencies, and carbon contents of savanna biomass. In the meantime, default
values can be used.
Delmas and Ahuja, 1993.
Menaut et al. (1991) calculate this number by multiplying the maximum biomass
density of the savanna (which generally is reached at the end of the growing
season) by a coefficient that declines as the burning occurs later in the dry
13 Singh and Misra, 1978.
14 . San Jose and Medina, 1976; Gonzalez-Jimenez, 1979; Coutinho, 1982; Hopkins,
1965; Haggar, 1970; Menaut and Cesar, 1982; and Huntley and Morris, 1982.
IS Lacey etal., 1982.
16 Hao etal., 1990.
17 Menaut etal., 1991.
18 Menaut etal., 1991.
19 This approach is adapted from Crutzen and Andreae, 1990, with some values
updated based on more recent studies by Delmas (1993), Delmas and Ahuja
(1993) and Lacaux et al. (1993).
20 from Crutzen and Andreae, 1990.
21 There is an inconsistency in the methodology in the treatment of the full
molecular weight of NOX. In fossil energy and industry discussions NOX is
expressed as though all of the N were in the form of NO2. In biomass burning
literature, (e.g., Crutzen and Andreae,'l990) NOX is often discussed as though
most of the emissions were in the form of NO. Therefore, the biomass burning
discussions in these Guidelines convert NOX-N to full weight using the
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conversion factor (30/14) for NO. All other references to NOX are based on the
full weight of NO2 (i.e., the conversion factor from NOX-N would be 46/14).
22 Barnard (1990) outlines several broad categories of crop residue: woody crop
residues (coconut shells, jute sticks, etc.), cereal residues (rice and wheat straw,
maize stalks, etc.), green crop residues (groundnut straw, soybean tops, etc.), and
crop processing residues (bagasse, rice husks, etc.).
23 Barnard, 1990; Ponnamperuma, 1984.
24 Ponnamperuma, 1984
25 Strehler and Stutzle, 1987
26 Ponnamperuma, 1984
27 Crutzenand Andreae, 1990
28 Barnard and Kristoferson, 1985.
29 I Tg dm = 10 Grams of Dry Matter, estimates are from Crutzen and Andreae
(1990)
30 See also United Nations World Trade Yearbooks.
31 In this context, one should also note the book Renewable Energy: Sources for Fuels
and Electricity edited by Johansson et al. (1992).
32 Dry matter (dm), or dry biomass, refers to biomass in a dehydrated state.
According to Elgin (1991), the moisture content of crop residue varies depending
on the type of crop residue, climatic conditions (i.e., in a humid environment the
residue will retain more moisture than in an arid einvironment), and the length of
time between harvesting and burning of the residue. From a simple perspective,
one can use the dry matter content values in Table D to convert from total crop
residue to dry matter. For example, if 200 tonnes of crop residue with a moisture
content of 10%, would have a dry matter content of 90%, equal to 180 tonnes of
dry matter. To convert from dry matter to carbon content, an average value of
0.45 t C/t dm can be used in the cases where cropi specific data are not available.
The terms dry matter and dry biomass are used interchangeably in this text.
33 Crutzen and Andreae, 1990. The estimates are very speculative and should be
used with caution. The actual percentage burned varies substantially by country
and crop type. This is an area where locally developed, country specific data are
highly desirable. As this issue is studied further, it may be possible to incorporate
more accurate, country-and crop-specific percentages into future editions of the
Guidelines.
34 To account for charcoal formation and other aspects of incomplete combustion.
See Seller and Crutzen (1980) and Crutzen and Andreae (1990).
35 This approach is adapted from Crutzen and Andreae, 1990, with some values
updated based on more recent studies by Delmas (1993), and Delmas and Ahuja
(1993).
36 Crop specific values are generally in the range of 0.01 -0.02, from Crutzen and
Andreae, 1990, so that 0.015 can be used as a generally representative value if no
other information is available.
37 There is an inconsistency in the methodology in the treatment of the full
molecular weight of NOX. In fossil energy and industry discussions NOX is
expressed as though all of the N were in the form of NO2. In biomass burning
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literature, (e.g., Crutzen and Andreae, 1990) NOX is often discussed as though
the emissions were in the form of NO. Therefore, the biomass burning
discussions in these Guidelines convert NOX-N to full weight using the
conversion factor (30/14) for NO. All other references to NOX are based on the
full weight of NO2 (i.e., the conversion factor from NOX-N would be 46/14).
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4.5 Nitrous Oxide Emissions from
Agricultural Soils
4.5.1 Introduction
This chapter covers emissions of nitrous oxide (N20) from agricultural soils. Estimates of
N2O emissions from the biosphere into the atmosphere are: highly uncertain, but it is
believed that about 70% originate from soils (Bouwman, 1990; Houghton et al., 1992). It
seems reasonable then, to assume that changes in N cycling in soil systems have influenced
the increases in atmospheric N2O during the past century and will help dictate future
changes in atmospheric N2O. A direct effect, that can be quantified, is the increase in N
input into the soil systems. This increase in N input is derived from atmospheric
deposition, which ranges from about 0.5 g N m"2 y'1 in the central U.S. to 6 g N m"2 y"1 in
western Europe (Andreae and Schimel, 1989), N fertilization with mineral N sources or
animal manures and biological N fixation. Nitrogen fertilizer use and biological N-fixation
are projected to continue to increase during the next 100 years (Hammond, 1990).
To determine N2O emissions from agricultural soils for various parts of the earth, we
must predict how much N2O is produced from each unit of fixed N (chemically or
biologically) that is added to the soil. To make this prediction we first must understand
how and where N2O is produced in the biosphere, what sinks exist for the gas, and how
the gas moves from where it is produced into the atmosphere. Research during the past
several decades provides an understanding of how N2O is produced, factors that control
it's production, source/sink relationships, and gas movement: processes. However, even
with this large amount of knowledge, we are not yet able to reliably predict the fate of a
unit of N that is applied or deposited on a specific agricultural field. Studies of emissions of
N2O from presumably "similar" agricultural systems show highly variable results in both
time and space. It is the complex interaction of the physical and biological processes
involved that must be understood before appropriate predictive capability can be
developed.
It is surprising that during the last few years, with the renewed interest in climate change
and the role of radiatively active trace gases, little new information concerning emissions
of N2O from agricultural fields has been published. Many recent review papers and
inventory assessments have all relied on published gas flux measurements from studies
conducted, primarily, during the late 1970's and early 1980's. The number of flux
measurements and the variety of soil conditions examined are limited. Therefore, the data
from which these reviews and inventories have been drawn are also limited and because of
the limitations, inappropriate conclusions may have been drawn.
As noted in the OECD/OCDE (1991) report, we know that N2O is produced primarily
from the microbial processes, nitrification and denitrification in the soil. In well aerated
conditions, where soil moisture content is low enough not to limit aeration, N2O
emissions from nitrification of ammonium based fertilizers can be substantial (Bremner and
Blackmer, 1978; Duxbury and McConnaughey, 1986). Other work suggests that N2O
release is a byproduct of nitrification (Yoshida and Alexander, 1970) and may occur by
denitrification of nitrite by nitrifying organisms under oxygen stress (Poth and Focht,
1985). Recent evidence indicates that in well aerated, porous soils, little N2O may evolve
but much larger amounts of NO may be emitted during nitrification (Williams et al., 1993).
In wet soils where aeration is restricted, denitrification is generally the source of N2O
(Smith, 1990). Under these conditions both the rate of denitrification and the N2O/(N2 +
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N2O) ratio must be known to evaluate N2O emissions through denitrification. According
to Smith (1990), soil structure and water content, affecting the balance between diffusive
escape of N2O and its further reduction to N2 are important among the factors
determining the proportions of the two gases.
Research has also shown us that a number of individual factors are controllers of
nitrification and denitrification. Such factors as soil water content, which regulates oxygen
supply; temperature, most organisms have a temperature range over which reaction rates
are optimal; nitrate or ammonium concentration, substrates may individually regulate
reaction rates and in the case of denitrification regulate the N2O/N2 ratio; available organic
carbon, denitrifiers require a usable organic carbon source and microbial respiration of
organic carbon may also regulate oxygen supply; and pH, is a controller of both
nitrification and denitrification and the N2O/N2 ratio in denitrification.
Increases in the amount of N added to the soil generally increases N2O emissions from
the soil (Bouwman, 1990). The temporal pattern of N2O emissions following fertilization is
generally that of a large efflux of N2O occurring for a short time (about six weeks). After
this time, emission rates are reduced to fluctuate around a low base-line level independent
of the amount of fertilizer applied (Hosier et al., 1983). Some studies indicate that N2O
emission rates are higher for ammonium-based fertilizers than for nitrate (Eichner, 1990).
For example, Bremner etal. (1981) found a much higher proportion of N2O released from
anhydrous ammonia than from urea or ammonium sulfate. Bouwman's (1990) review,
however, suggested no particular trend in N2O emissions related to fertilizer type. Byrnes
etal. (1990) suggest that N2O emissions from the nitrification of fertilizers may be more
closely related to soil properties than to the N source that is supplied. Mineral N
applications along with organic matter amendments generally increase total denitrification
and N2O production.
As discussed in more detail by Hosier (1989), N2O emissions from the soil can vary by
orders of magnitude from a location both spatially and temporally. These heterogeneities
in both space and time in measured gas fluxes and in the microbial activity which produces
the gases make predictions highly uncertain.
External factors also perturb "normal" soil N cycling and thus increase N2O emissions.
Land use conversion has been a primary factor in the past (Houghton and Scole, 1990),
and conversion of forests and grasslands to croplands accelerated C and N cycling and
increased N2O emissions from the soil. Globally, land use conversion is important now
only in tropical areas. Most of the conversions of forests and grasslands in the northern
hemisphere occurred 50 to 200 years ago (Hammond, 1990). Global changes may impart
changes in soil temperature and moisture which will directly influence N cycling.
4.5.2 1991 OECD NjO Emission Methodology
The first OECD/OCDE (1991) methodology for calculating N2O emissions from nitrogen
fertilizers was based on the amount of each type of commercial fertilizer nitrogen
consumed (in mass units of N), an emission coefficient for the fraction of applied N that is
released as N2O-N for each fertilizer type, and a factor used to convert the emission from
N2O-N to N2O. Emissions of N2O-N are estimated from each fertilizer type, summed
over all types, and then converted to units of N2O:
(I) N2O-N Emissions (tonnes N2O-N) = £(F,x Ef)
where:
F = Fertilizer Consumption (tonnes N)
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E = Emission Coefficient (Tonnes N2O-N released/tonne N applied)
f = Fertilizer type
N2O Emissions (tonnes N2O) = N2O-N Emissions (tonnes N2O-N) x 44/28.
The Working Group suggested dropping the attempt to calculate N2O emissions based on
the type of commercial fertilizer N applied. Considering the number of agricultural
systems that exist world wide and the number of sources of N available for use, the data
set available for these analyses are quite small. As a result, single studies at single locations
can dominate, and possibly skew the analysis. Another point is that since most of the data
cited were from studies conducted only during the cropping season, or part of the
cropping season, little is known about N emissions following crop harvest and before
planting in the spring. Recent research (Sommerfeld et al., 1993) indicates that appreciable
N2O emissions can occur from snow covered soils and Goodroad and Keeney (1984)
noted large fluxes of N2O during winter thaw periods. The Expert Group concluded that
there is no justification for including fertilizer type in the equation, as existing data shows
wide, overlapping ranges of emission factors for each commercial fertilizer type. Many
studies show that field variables such as the interaction of soil type, soil water content, and
substrate availability regulate N2O emissions rather than N source.
The second OECD/OCDE (1991) methodology includes the fertilizer source variable
discussed in section A and also includes the crop type to which the fertilizer is applied.
The approach is the same as section A except that emissions of N2O-N are summed over
all fertilizer and crop types, instead of just over all fertilizer types.
(2)
N2O-N Emissions (tonnes N2O-N) =Z (Ffc x E fc)
where F = Fertilizer Consumption (tonnes N)
E = Emission Coefficient (tonnes N2O-N released/tonne N applied)
f = Fertilizer Type
c = Crop Type
N2O Emissions (tonnes N2O) = N2O-N Emissions (tonnes iN2O-N) x 44/28
Including crop type in the calculation seems reasonable since the type of crop tends to
regulate soil water content, the timing of mineral N uptake, and the release of
mineralizable carbon into the soil. All of these factors are regulators of N2O-forming
processes. But as noted in OECD/OCDE (1991) there is not enough information to
calculate the necessary coefficients for each crop type. This calculation is therefore no
longer recommended.
4.5.3 Suggested N2O emission calculation
method
As the data available from which to calculate N2O emission coefficients from either N
fertilizer source or crop type are not adequate to make such calculations, and it is unlikely
that within the next few years sufficient studies will be conducted to make adequate
coefficient calculations, the following, simplified calculation is recommended for estimating
N2O emission from agricultural soils:
(3) N2O-N Emission (tonnes N2O-N) =2 F x 0.01
where F = Fertilizer Consumption (tonnes N)
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where F = Fertilizer Consumption (tonnes N)
N2O Emissions (tonnes N2O) = N2O-N Emission (tonnes N2O-N) x 44/28
Because of the limitations of the data available and the scope of the data, a value of
1%/year of fertilizer (both mineral and organic) N direct emission from agricultural fields
does not seem unreasonable. The literature on field N2O flux are adequate to provide the
order of magnitude of the multiplication coefficient, greater than 0.001 and less than O.I'
(CAST, 1992).
There is certainly room for arguing the validity of this suggestion. For example in a flooded
rice field, when fertilizer N is added immediately before flooding, little N2O is emitted
(Freney et al., 1981). We do not know, however, how much N2O evolves from the field
when the water is drained for harvest or during the intercrop dry period. Some evidence
indicates that appreciable N2O is evolved from a rice field during the first few days after
the field is flooded (Byrnes et al., 1993). A simple equation relating soil mineral N content
and soil % water-filled pore space to N2O emissions integrated through the entire year
may represent N2O emissions reasonably well. There is, unfortunately, no possibility to
link this to national inventory calculations.
The second major point discussed by the Expert Group was that the OECD (1991)
method only addressed direct N2O emissions from cultivated agricultural soils that had
been fertilized with commercial fertilizer N. The consensus of the group was that this
narrow concept is not appropriate since N from (I) atmospheric deposition, (2)
commercial fertilizer, (3) animal manures and plant residues, (4) biological N fixation, and
(5) soil organic matter mineralization should all be considered in the equation. World-
wide, the amount of N input into agricultural systems from animal manures and biological
N fixation is roughly the same as the input from commercial fertilizer N (about 80 Tg in
1990). Nitrogen input from atmospheric deposition varies globally from about I to 50 kg
N ha"1 y"1 while N from mineralization of soil organic matter may vary from 10 to 200 kg
N ha y , both are site dependent.
Based upon information that is considered to be available in most countries, the following
N2O emission calculation method is suggested:
a) Low Estimate
N20 Emission = 2 (Fmn + Fon + Fbnf) * C0,
b. High Estimate
N20 Emission = £ (F^ + Fon + Fbnf) * C0,
c. Median Estimate
•0.0005
1.039
N20 Emission = 2 (Fmn + Fon + Fbnf) * COM3t
Where Fmn = amount of mineral N applied
FO,, = amount of organic N applied (animal manure or crop residue)
F^ = amount of biological N fixation
CD 0005 = low end of emission coefficient range
C0039 = high end of emission coefficient range
C0,oo3« = median emission coefficient
Units are in Tg of N for input and Tg N2O-N x 44/28 for total N2O emission. The
emission coefficients are those used by OECD (1991) on page 5-51 based on total
commercial fertilizer N consumed and N2O emission based on these low, high, and median
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emission factors. These numbers should span the range of most measured N2O emissions.
It was felt that because the range of measured N2O emissions from different agricultural
systems is so large, the whole range must be considered to convey the uncertainty in using
these estimates.
Most of the information to calculate N2O emissions are avsiilable for many countries, but
part may not be readily available for others:
a) N from commercial fertilizer. Total N consumption as v/ell as mean N-application level
(in kg/ha of arable land) is available for all countries in the FAO Fertilizer Yearbooks (e.g.
FAO, I990a).
b) N from animal manure. Animal population data is available from the FAO Production
Yearbooks (e.g. FAO, 1990b). The amount of N in the excreta and the volatilization of
ammonia are well known for most parts of the world. Whesre such data are not available,
estimates can be made based on animal diet. Further data required are: the portion of the
year that animals are grazed and confined, and the portion of the manure collected in the
stables and the portion applied to the soil.
The working group on NH3 of the Global Emission Inventories Activity (GEIA), a core
project of the International Global Atmospheric Chemistry Program (IGAC) will develop a
methodology to estimate the above parameters. For countries having difficulties to obtain
the data, these GEIA-estimates could be used as default values.
c) N from biological N-fixation. Data on the areas cropped to leguminous crops, such
alfalfa, pulses, soy beans, are readily available from FAO Production Yearbooks (e.g. FAO,
I990b). Commonly, leguminous crops are not fertilized with commercial N, or are
fertilized only a small amount of starter N. It is difficult to estimate the amount of N fixed
by the crop if we do not know the amount of soil N before sowing and after harvest, as
well as the yield and % N in the crop.
4.5.4 For the Future
The OECD Expert Group made the following suggestions for improving the methodology
for estimating N2O emissions from agricultural soils:
I The assumption that N2O emissions directly from fertilizers are relatively small
should be reviewed. A critical look at the reviews of Eichner (1990), Bouwman
(1990) and CAST (1992) indicate that a conservative estimate of direct emission of
N2O from mineral fertilizer over a full year are in the range of I % of the N applied,
currently about I Tg, or about 10% of current global emissions. This estimate does
not include either organic N fertilizer from human and farm animal excreta or N
fixed by biological N fixation. Limited data suggest that N2O emissions from these N
sources are generally greater than from mineral N application (Bouwman, 1990).
Assuming that N emissions from all sources are equal, the direct emissions from all
three N sources could total 3 Tg annually.
2 Although the individual factors that regulate N2O production are known, we cannot
predict how these factors interact under field conditions to produce measured fluxes
(OECD/OCDE, 1991). Both nitrification and denitrification and the regulators of
N2O/N2 ratios from denitrification have their own set: of optimum conditions. As a
result, one process may be the primary N2O producer in one set of field conditions,
but as soil conditions change, another process may predominate. The complexity of
the interactive factors important to the different processes obviously make a simple
description of N2O production difficult (Hosier et al., 1983). Complex models such
as that described by Li et al. (1992) may be the only way that N2O fluxes may be
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predicted. Simpler, mechanistic models such as that described by Parton et al. (1988)
may, however, play a role in simplifying estimation of N2O emission. To accurately
inventory N2O emissions from agricultural soils we must be able to predict N2O
emissions based on N application, soil, crop and management.
It is also likely that N2O production resulting from fertilizer and increased use of
biological nitrogen fixation is underestimated because the effect of a nitrogen input is
usually only partially traced through the environment. In an example taken from
Duxbury et al. (1993), 50 of the 100 kg ha'1 of N applied as fertilizer on a typical
dairy farm are harvested in the crop, and 50 are lost by the combination of leaching
(25), surface run-off (5), and volatilization (20, primarily denitrification). If N2O
comprises 10% of the volatilized N, 2 kg N2O-N would be generated in the primary
cycle. Assessments of fertilizer effects on N2O emissions usually stop at this point
even though only 20 of the 100 kg N have been returned to the atmosphere and it
can be reasonably assumed that almost all would be returned within a few years.
Secondary flows include feeding of the 50 kg of harvested N to animals, which
generate 45 kg of manure N. The manure is returned to cropland to fertilize a
second crop, however about half of this N is volatilized as NH3 prior to or during
manure application. Volatilized NH3 is aerially dispersed and subsequently returned
to and cycled through both natural ecosystems and cropland. Ammonia volatilization
from agricultural systems is globally important (Isermann, 1992) but its impact on
N2O emissions have not been explicitly addressed. To provide some perspective, it
should be noted that the quantities of fertilizer N used and animal manure N
generated by USA agriculture are equal (Bouldin et al., 1984). On a global basis, about
30 of the 80 Tg fertilizer N used each year are volatilized as NH3.
Similarly, the amount of N2O arising from leached nitrate, which may average 20-25%
of applied N (Meisinger and Randall, 1991), is not known but much may be denitrified
in riparian zones or cycled through wetland or aquatic vegetation. A complete
accounting of fertilizer N, biologically fixed N, and N mineralized from soil organic
matter is-difficultto achieve, but needed if we are to accurately assess the impact of
increased use of N in agricultural ecosystems on terrestrial N2O emissions (Duxbury
etal., 1993).
The Working Group felt that considering only N2O emissions from cultivated
agricultural soils was too narrow a view. The whole picture of anthropogenic effects
of N2O emissions should include the indirect fertilization of grasslands, forests and
wetlands from agricultural and industrial sources. Since cultivated lands represent
only about 13% of the global land surface it does not seem appropriate to consider
only those areas when estimating global N2O emissions.
Calculations of N additions and N cycling within all of these ecosystems must include
N from atmospheric deposition and N from soil organic matter mineralization. The
entire calendar year should be considered, not just the cropping season.
Improving methodology for estimating N2O emissions may evolve in a series of steps,
beginning with the above equations and ending with development of process based
models which are used to develop regional and larger scale emission models. With
these models, if a relatively simple set of input information can be developed, then
detailed emission calculations may be made. Because of the inherent spatial and
temporal variability associated with N2O production and emissions from soils, it
appears that very simple approaches will not provide realistic emission estimates.
To support the development of the steps for improved methodology for calculating
country-wide N2O emissions, a number of unknowns were identified. Better
understanding of these issues should improve methodologies.
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AGRICULTURE
a Research needs specifically for agricultural systems include:
i Improve management strategies to optimize N use efficiency and match
plant N input needs.
ii Facilitate integration of animal and crop production systems within the
agricultural industry.
iii Develop mitigation strategies at the farm level.
iv Perform measurements in important tropical agricultural systems.
v Develop strategy to provide farmers with options and knowledge about N
use to limit N leakage.
b General recommendations:
i Estimate anthropogenic N input into "natural systems" and amount
processed into N2O.
ii Develop process level models, based on field research measurements,
refine and test the models and use these models as basis for developing
regional and larger scale emission models.
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4.5.5 References
Andreae, M.O. and D.S. Schimel (eds.). 1989. Exchange of Trace Gases between
Terrestrial Ecosystems and the Atmosphere. John Wiley & Sons. 346 p.
Bouldin, D.R., S.D. Klausneer and W.S. Reid. 1984. Use of nitrogen from manure. In R.D.
Hauck (ed.). Nitrogen in Crop Production. Amer. Soc. Agron. Madison, Wl. pp. 221-245.
Bouwman, A.F. 1990. Exchange of greenhouse gases between terrestrial ecosystems and
the atmosphere. In A.F. Bouwman (ed.). Soils and the Greenhouse Effect. John Wiley &
Sons. New York. pp. 61-127.
Bremner, J.M. and A.M. Blackmer. 1978. Nitrous oxide: emissions from soil during
nitrification of fertilizer nitrogen. Science. 199:295-296.
Bremner, J.M., G.A. Breitenbeck and A.M. Blackmer. 1981. Effect of nitrapyrin on emission
of nitrous oxide from soil fertilized with anhydrous ammonia. Geophys. Res. Lett. 8:353-
356.
Byrnes, B.H., L S. Holt and E.R. Austin. 1993. The emission of nitrous oxide upon wetting
a rice soil following a dry season fallow. J. Geophys. Res. (In Press).
Byrnes, B.H., C.B. Christiansen, LS. Holt and E.R. Austin. 1990. Nitrous oxide emissions
from the nitrification of nitrogen fertilizers. In A.F. Bouwman(ed.). Soils and the
Greenhouse Effect. ChichestenWiley. pp. 484-495.
CAST. 1992. Preparing U.S. Agriculture for Global Climate Change. Task Force Report
No. 119. P.E Waggoner, Chair. Council for Agricultural Science and Technology. Ames,
IA. 96 pp.
Duxbury, J.M. and P.K. McConnaughey. 1986. Effect of fertilizer source on denitrification
and nitrous oxide emission in a maize field. Soil Sci. Soc. Am. J. 50:644-648.
Duxbury, J.M., LA. Harper and A.R. Mosier. 1993. Contributions of agroecosystems to
global climate change, in Agricultural Ecosystem Effects on Trace Gases and Global
Climate Change. LA. Harper, A.R. Mosier, J.M. Duxbury and D.E. Rolston (eds.). ASA
Special Pub. No. 55 Amer. Soc. Agron. Madison, Wl. pp. 1-18.
Eichner, M.J. 1990. Nitrous oxide emissions from fertilized soils: summary of available
data.J. Env. Qual. 19:272-280.
FAO. I990a. Fertilizer Yearbook. Volume 39, pp. 127. FAO statistics series No. 95. Food
and Agricultural Organization of the United Nations. Rome.
FAO. I990b. Production Yearbook. Volume 43. FAO statistics series No. 94. Food and
Agricultural Organization of the United Nations.me.ns. Rome.
Freney, J.R., O.T. Denmead, I. Watanabe and E.T. Craswell. 1981. Ammonia and nitrous
oxide losses following applications of ammonium sulfate to flooded rice. Aust. J. Agric. Res.
32:37-44.
Goodroad, LL and D.R. Keeney. 1984. Nitrous oxide emissions from soils during thawing.
Can. J. Soil Sci. 64:187-194.
Hammond, A.L 1990. World Resources 1990-91. A report by The World Resources
Institute, Oxford University Press. Oxford, UK. 383 pp.
Houghton, R.A. and D.L Skole. 1990. Changes in the global carbon cycle between 1700
and 1985. in B.L Turner (ed.). The Earth Transformed by Human Action. Cambridge
University Press.
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Houghton, J.T., B.A. Cailander and S.K. Varney (eds.). 1992. Climate Change 1992. The
Supplementary Report to the IPCC Scientific Assessment. Intergovernmental Panel on
Climate Change. Cambridge University Press. 200 pp.
Hynes, R.K. and R. Knowles. 1978. Inhibition of acetylene of ammonia oxidation by
Nitrosomas europea. FEMS Microbiol. Lett. 4:319-321.
Iserman, K. 1992. Territorial, Continental and Global Aspects of C, N, P and S Emissions
from Agricultural Ecosystems. In NATO Advanced Research Workshop (ARW) on
Interactions of C, N, P and S Biochemical Cycles. Springer-Verlag, Heidelberg (In Press).
Li, C., S. Frolking and T.A. Frolking. 1992. A model of nitrous oxide evolution from soil
driven by rainfall events: I. Model Structure and Sensistivity. j. Geophys. Res. (In Press).
Meisinger, J.J. and G.W. Randall. 1991. Estimating nitrogen budgets for soil-crop systems. In
Managing Nitrogen for Ground Water Quality and Perm Profitability. R.F. Follett, D.R.
Keeney and R.M. Cruse (eds.). Soil Sci. Soc. Am. Inc. Madison, Wl. pp. 85-124.
Mosier, A.R. 1989. Chamber and isotope techniques. In M.O. Andreae and D.S. Schimel
(eds.). Exchange of Trace Gaes between Terrestrial Ecosystems and the Atmosphere.
Chichester:Wiley. pp. 175-187.
Mosier, A.R., W.J. Parton and G.L Hutchinson. 1983. Modelling nitrous oxide evolution
from cropped and native soils. R. Hallberg (ed.). Ecol. Bull (Stockholm). 35:229-241.
OECD/OCDE. 1991. Estimation of Greenhouse Gas Emissions and Sinks. Final report
from the OECD Experts Meeting, 18-21 February, 1991. Prepared for Intergovernmental
Panel on Climate Change. Revised August, 1991.
Parton, W.J., A.R. Mosier and D.S. Schimel. 1988. Rates and pathways of nitrous oxide
production in a shortgrass steppe. Biogeochemistry. 6:45-58.
Poth, M. and D.D. Focht. 1985. I5N kinetic analysis of N2O production by Nitrosomas
europea: an examination of nitrifier denitrification. Applied. Env. Microbiol. 49:1 134-1 141.
Smith, K.A. 1990. Greenhouse gas fluxes between land surfaces and the atmosphere.
Progress in Physical Geography. 14:349-372.
Sommerfeld, R.A., A.R. Mosier and R.C. Musselman. 1993. CO2> CH.,, and N2O flux
through a Wyoming snowpack and implication for global budgets. Nature. 361:140-142.
_ Williams, E.J., G.L. Hutchinson and F.C. Fehsenfeld. 1993. NOX and N2O emissions from
soil. Global Biogeochem. Cycles. (In Press).
Yoshida, R. and M. Alexander. 1970. Nitrous oxide formation by Nitrosomas europea and
heterotrophic microorganisms. Soil Sci. Soc. Am. Proc. 34:880-882.
PART 2
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4.92
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CHAPTER 5
LAND USE CHANGE
& FORESTRY
PART 2
5.1
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LAND USE CHANGE & FORESTRY
5.2
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LAND USE CHANGE & FORESTRY
EMISSIONS FROM LAND USE CHANGE
AND FORESTRY
5.1 Overview
This chapter summarizes methods for calculating greenhouse gas (GHG) emissions from
human activities which:
I change the wayland is used (e.g., clearing of forests for agricultural use, including
open burning of cleared biomass), or
2 affect the amount of biomass in existing forests (e.g., logging, fuelwood harvesting).
The biosphere is a strong determinant of the chemical composition of the atmosphere.
This has been true since the existence of the biosphere, and hence well before the
presence of humans. A rich variety of carbon, nitrogen, and sulfur gases are emitted and
absorbed by the biosphere. There is, however, strong evidence, that the expanding human
use and alteration of the biosphere for essential food, fuel and fiber is contributing to the
increasing concentrations of greenhouse gases. The dominant gas of concern in this source
category is carbon dioxide (CO2), and much of the methodology discussion in this chapter
is specific to CO2. Other important direct greenhouse gase:;', including methane (CH4)
and nitrous oxide (N2O), and indirect greenhouse gases, including carbon monoxide (CO),
and oxides of nitrogen (NOX, i.e., NO + NOj) are also produced from land use change
and forest management activities, particularly where burning is involved.
Estimates of greenhouse gas emissions due to land use change vary considerably. Estimates
of emissions resulting from changes in the use of forests and of forest area vary due to
uncertainties in annual forest clearing rates, the fate of the land that is cleared, the
amounts of biomass (and hence carbon) contained in different ecosystems, the fate of the
biomass removed, and the amounts of CH4, CO, N2O, and NOX released when biomass is
burned and soils are disturbed. The 1990 IPCC Scientific Assessment estimated the flux in
1980 to be 0.6-2.5 Pg CO2-C, and estimated the average annual emissions for the decade
1980-1989 to be I.6±I.O Pg CO2-C.2 Subsequently, the IPCC (1992) reviewed more
recent but still inconclusive information, and could find no basis for changing the earlier
estimate. Carbon sequestration by tropical tree plantations 'was not explicitly included in
these estimates but is thought to be relatively small: in 1980 these plantations were
estimated to absorb only 0.03-0.11 Pg CO2-C.3 At the time of the IPCC 1990
Assessment estimates in the literature indicated the net release or uptake of CO2 due to
land use change in the temperate and boreal regions in the 1980s to be small with CO2
emissions from deforestation in these regions almost balanced by CO2 uptake from the
regrowth of forests. More recently, several analyses have suggested that growth of
existing forests in temperate and boreal regions may be a significant carbon sink,
potentially as much as 1.0 Pg-C annually. Analysts have suggested a number of
complementary factors which could be causing these sinks, including regrowth of
historically cleared forests, CO2 fertilization, and nitrogen fertilization due to atmospheric
deposition.5 The precise mix of causes and magnitude of these sinks is still a subject of
research and debate.
Gross emissions of non-CO2 trace gases (CH4, CO, N2O, and NOJ due to biomass
burning are also net emissions and are generally produced immediately, while gross
emissions of CO2 due to reductions in forest area may or may not be balanced by uptake
of CO2 and may occur over immediate or delayed time frames.6 Similarly, increases in
forest area or in the biomass density of existing forests will result in CO2 uptake at varying
PART 2
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LAND USE CHANGE & FORESTRY
rates and over delayed time frames. Only about 50-60% of the carbon estimated to have
been released in 1980 was a result of deforestation in that year. The remainder was a
release due to oxidation of biomass cleared in previous years. Other land use changes,
such as land flooding, result in continuous greenhouse gas emissions for as long as the land
remains in its altered state.
5.1.1 Background - biomass stocks and carbon
fluxes
Vegetation withdraws carbon dioxide from the atmosphere through the process of
photosynthesis. Carbon dioxide is returned to the atmosphere by the (autotrophic)
respiration of the vegetation and the decay (heterotrophic respiration) of organic matter
in soils and litter. The gross fluxes are large; roughly a seventh of the total atmospheric
carbon dioxide passes into vegetation each year (on the order of 100 Pg COrC per year),
and in the absence of significant human disturbance, this large flux of CO2 from the
atmosphere to the terrestrial biosphere is balanced by the return respiration fluxes. This
remarkable balance is clearly expressed by the relative constancy, which can be inferred
from the ice core records, of the concentration of atmospheric CO2 between 10 and
18* century.
Land use change and the use of forests •directly alters these fluxes (and their balance) and
consequently the amount of carbon stored in living vegetation, litter, and soils. For
example, forest clearing for agriculture by burning greatly increases the return
(respiration) flux of CO2 and decreases for a while the photosynthetic flux. Burning is,
after all, simply a rapid form of oxidation or decay. Subsequently, the balance on the
cleared area will return: the photosynthesis associated with the agricultural production
being balanced by the respiration of the vegetation, the decay of on-site organic material,
and the oxidation of the agricultural product when it is consumed, perhaps off site.
However, the total amount of carbon stored in the terrestrial system will have been
reduced because a forest contains more carbon than does a corn field, and the removed
carbon (i.e., the forest) was not put into long term storage pools. An obvious
consequence is that the activity resulted in a net flux of CO2 from the biosphere to the
atmosphere. A natural first order assumption is that the net reduction in carbon stocks is
equal to the net CO2 flux from the cleared area.
Forest harvest does not necessarily result in a net flux to the atmosphere. It can produce
a complex pattern of net fluxes that change direction over time. For instance, suppose
that a forest is harvested producing wood products and leaving some slash and debris.
Initially, the CO2 flux from the wood products that decay rapidly plus the increased
respiration flux of CO2 associated with the oxidation of the slash (in effect the litter pool
has been increased and hence so has the respiration flux associated with this pool) could
be greater than the flux from the atmosphere due to the photosynthesis and the resulting
carbon storage in the regrowing forest. Consequently, there is a net flux of CO2 from the
biosphere to the atmosphere. This would also be reflected in a carbon accounting: the
amount of carbon in the original living vegetation, the litter, and the soils would be greater
than the amount of carbon in the young regrowing forests, litter, soils and forest products
pool. However, if some of the forest products are very long-lived, and if the forest
regrows to its original level, then the integrated net flux must have been from the
atmosphere to the terrestrial biosphere since the resulting total terrestrial carbon stocks
(vegetation, litter, soils, and wood products) would be greater than before the forest
harvest.
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LAND USE CHANGE & FORESTRY
Box I
ILLUSTRATIVE CALCULATIONS OF CAREION FLUXES
Consider the example of forest clearing for agriculture which results in a net
flux to the atmosphere. For descriptive purposes we consider the following
assumptions: I) a 20 year time frame (e.g., 1970 to 1990), 2) one hectare is
cleared each year (so that over the 20 year period, 20 hectares are cleared),
3) cleared land is used as pasture, which is established the year following the
clearing, 4) after three years cleared land is abandoned and it regrows
linearly to 75% its original biomass in 15 years but no further, 5) all of the
vegetation is completely burned at the time of clearing and there are
essentially no soil or litter pools, 6) there are 200 tonnes of carbon per
hectare in the forest biomass and 5 tonnes carbon per hectare in the
pasture.
In the first year, there is a 200 tonne net flux of carbon as CO2 to the
atmosphere. In the second there is a 195 tonne net flux; the clearing of the
second hectare is partially balanced by the establishment of the first pasture.
In the third, there is a net flux again of 195; the clearing of the third hectare
is again partially balanced by the establishment of the second pasture;
however, the first pasture is now again in a steady state (as a pasture). The
fourth year the pattern is again the same, but in the fifth year the net annual
flux drops to 185 as the first pasture is now abandoned and begins to
recover to a secondary forest In the sixth year, the flux drops to 175 as
two hectares are recovering to a secondary forest. In this example, in 1989
one hectare would be converted to pasture (200 tonne flux of carbon to the
atmosphere), one hectare would have become a pasture (5 tonne flux to the
terrestrial biosphere), two hectares would be in steady state as pasture, and
15 hectares would be recovering to secondary forest with one hectare in its
final year of recovery (150 tonne flux to the terrestrial biosphere). The 1989
gross flux of carbon from land clearing in 1989 would still be 200 tonnes to
the atmosphere, but the net flux to the atmosphere in 1989 associated with
land clearing would be 45 tonnes of carbon as CO2- The 1990 flux would be
the same since now the original one hectare of pasture would have reached
a new steady state as a secondary forest
Many variations on this example can be devised: e.g., conversion of some
vegetation to charcoal, varying deforestation and regrowth rates. For
instance, if the land clearing rates declined over the time period, the 1990
net flux could easily be from the atmosphere to the biosphere even though
the net integral flux over the time period was to the atmosphere.
There are other complexities such as the variety of land-use practices,
varying assumptions about biomass densities, recovery rates, the dynamics of
the associated litter and soil pools, and so forth. However, the net flux to or
from a particular site will always be reflected in the change of carbon stocks
on site and/or in the products pools associated with the site. Thus, a
methodology that determines carbon stock changes, also provides estimates
of the net fluxes of CO2-
PART 2
5.5
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LAND USE CHANGE & FORESTRY
This characteristic that changes in land use activity today affects both present and future
CO2 fluxes associated with that specific land use activity is one feature of CO2 emissions
analysis that distinguishes land use from fossil fuel consumption. Consequently, when one
considers the issue of CO2 flux associated with land use today or in a ba'se year, one must
consider past land use activities and their effects upon current fluxes of CO2. Box I
provides some illustrative numerical examples of carbon fluxes associated with land use
change over a series of years.
5.1.2 The Proposed Approach
The fundamental basis for the methodology rests upon two linked themes: i) the flux of
CO2 to or from the atmosphere are assumed to be equal to changes in carbon stocks in
existing biomass and soils, and ii) changes in carbon stocks can be estimated by first
establishing rates of change in land use and then applying simple assumptions about the
biological response to a given land use. As noted above, there are large uncertainties in all
current methods for estimating fluxes of CO2 from forestry and land use change. Direct
measurements of changes in carbon stocks are extremely difficult since one must confront
the difficulty of determining small differences in large numbers as well as the inherent
heterogeneity of terrestrial systems. A more practical first order approach in many
countries is to make simple assumptions about the effects of land use change on carbon
stocks and the biological response and to use these assumptions to calculate carbon stock
changes and hence the CO2 flux. This observation is at the heart of the proposed g
approach. It is also central to more complex terrestrial carbon accounting models.
Rates of change of land use are also difficult to establish. However, on a practical basis it is
possible since there are a variety of data on which to base land use change estimates. The
Technical Appendix to this chapter reviews sources of data on rates of tropical
deforestation, the land use change which currently makes the largest contribution to CO2
flux. Finally, the assumptions regarding the response of vegetation and soils to different
land uses and land use change can be expressed in uncomplicated terms which can be
altered for particular differences for different countries.
The methodology is designed to allow calculations based on such assumptions.which cover
each of the main categories, and which are feasible for all participating countries. It can be
implemented at several different levels of complexity and geographic scale, depending on
the needs and capabilities of national experts in different countries.
I A simple, first order approach can be based on very aggregate default data and
assumptions, derived from the technical literature, and provided throughout the
text. Methods are presented in the context of national level aggregate calculations
for a limited set of subcategories which can be supported by these default values.
2 A more accurate level can be achieved simply by substituting country-specific valued
for general defaults provided in the methodlogy. If appropriate and possible, locally
available data can be used to carry out calculations at a more detailed geographic
and/or sub-category level. Alternative levels of detail are discussed more fully in the
next section. National experts are strongly encouraged to substitute more
appropriate (i.e., country or region-specific) and more detailed input data wherever
this is available.
3 Forest inventory data can also be used with this methodlogy. It is important to note
that some countries with highly developed forestry industries do in fact keep track
of existing commercial forests through periodic detailed surveys. In these countries
it is generally the ongoing management of existing forests rather than land use
changes which has the greatest impact on GHG emissions or removals. National
5.6
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LAND USE CHANGE & FORESTRY
experts who have very detailed, inventory based data, can reformat this data to
create equivalent average responses (e.g., annual biomass growth rates by ecosystem
type) which can be aggregated up to categories matching the simple approach
outlined here. This procedure is discussed in more detail in the managed forests
section below.
The intent is to provide a calculation and reporting framework which can accommodate
users with vastly different levels of data available, yet allow them all to place the results on
a comparable basis.
5.1.3 Priority Categories
In estimating the effects of land use and land use changes on the concentration of
greenhouse gases, it is reasonable to stage the calculation methods so that the most
important components can be addressed first, and complexities and subtleties of the
relationship of forestry and land use change to fluxes of CO2 and other gases can be
incorporated in a consistent manner into subsequent calculations as knowledge advances
and data improve. The methodology presented in this chapter focuses initially on a simple,
practical, and fair procedure for determining the carbon dioxide flux directly attributed to
forest management and land use change activities. This procedure must account for the
influence of past land use changes upon the contemporary flux. The method also
accounts for trace gas emissions from biomass burning where this occurs in conjunction
with land use change.
On a global scale, the most important land use changes thai: result in CO2 emissions and
removals are:
• forest clearing - the conversion of forests to non-forests (e.g., to pasture or
cropland)10
• grassland conversion - the conversion of natural grasslands to cultivated (tilled) or
pasture lands
• abandonment of managed lands which regrow into grasslands or forests
• managed forests - the most important effects of human interactions with existing
forests are considered in a single broad category , which includes logging for forest
products, the harvest of fuel wood, and establihment and operation of forest
plantations.
The method also addresses the immediate release of non-CO2 trace gases (CH4, CO,
N2O and NOx) from the open burning of biomass from forest clearing. The approach is
essentially the same as that used for non-CO2 trace gases from all burning of unprocessed
biomass, such as burning of traditional biomass fuels (Chapter I: Energy), and burning of
agricultural residues and savanna burning (Chapter 4: Agriculture). These calculations are
similar to fossil fuel emission calculations, in that they do not include time lags and all
emissions are net emissions.
5.1.4 Relationships Among Categories
It is important to recognize some key linkages and interactions among components of the
land use change and forestry methods and with other calculations discussed in other
chapters. Figure I illustrates a number of complicated relationships among these
categories and also with biomass fuel combustion which is covered in the energy source
category. Key linkages which should be understood are:
PART 2
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LAND USE CHANGE & FORESTRY
I To estimate CO2 emissions from burning or cleared forests, it is only necessary to
know the total amount of biomass which is burned in the inventor/ year.
2 However, it is necessary to divide this burning into on-site and off-site (fuelwood)
portions for other reasons:
First, the type of burning affects the emissions of non-CO2 trace gases such as
methane so that different emission factors may be applied to open burning on-site
and to fuelwood use off-site.
Secondly, the amount of fuelwood removed from cleared forests must be deducted
from total fuelwood consumed for the nation or region to determine the residual
amount of fuelwood which must have been harvested from managed forests (as
broadly defined in this chapter). This is only an issue for those countries which must
infer some or all of forest harvest from wood consumption surveys. If some of the
fuelwood consumed has already been accounted for once in calculations of forest
clearing, this amount must be take out of the amount attributed to managed forests.
3 Fuelwood Consumption Information. Countries which have accurate and complete
statistics on direct harvesting of all types of wood from managed forests, and all uses
of biomass for fuel, should use locally available data. Many countries, however, have
significant amounts of wood removed from forests, primarily for domestic fuel use,
which is not accounted for in commercial harvest statistics. For these countries, an
optional Fuelwood Consumption Accounting approach is provided. This approach is
based on household and other fuel consumption surveys, scaled to population to
estimate total annual demand for fuelwood and other fuels. This information can then
be used instead of, or in combination with, commercial harvest and sales statistics.
Fuelwood consumption information is used in two ways:
— for estimating trace gas emissions from biomass fuel combustion (in the Energy
section of the methodology); and
— total wood consumption, corrected to deduct any wood which has come from
forest clearing (for which CO2 is already accounted) is also a key input to the
calculations of net CO2 emissions or removals by managed forests.
5.8
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LAND USE CHANGE & FORESTRY
FIGURE I: Relationships Among Categories
L
A
N
D
U
S
E
C
H
A
N
G
E
F
O
R
E
S
T
R
Y
E
N
E
R
G
Y
Forest Clearing
immediate Release from Burning
Delayed Release from Decay (10 yrs)
Delayed Release from Soils (25 yrs)
Total
C
On-site burning
Off-site (field)
Trace Gas Emissions
from Open Burning
7
Abandoned Land Regrowing
Grassland Conversion
Total
Fuelwood
Demand
Fuelwood Consumption
Accounting (Optional)
^, CO2 N2O and NO* Emissions
CO Emissions
Removals
Quantity of
->-CO2 Emissions
Minus Quantity from
Cleared Forests
Net CC>2 Emissions or Removals
Trace Gas Emissions from
Biomass Fuel Combustion
Emissions
5.1.5 Chapter Organization
The remainder of this chapter presents methods for calcubting greenhouse gases from •
land use change and forestry in two stages. The next section, Bask Calculations, presents
initial simple calculations for each of the four key land uses and changes in land use
identified above. These categories also correspond directly to the subsections of the Land
Use Change and Forestry Module of Volume 2: Workbook.
The second stage, Refinements in Calculations, discusses a range of complexities and
refinements which ideally could be included in such calculations, as data and understanding
permit, in order to improve accuracy and completeness. These possible refinements
include more detailed treatment of some aspects of the basic categories of land uses and
land use changes, as well as additional categories, which cam affect carbon stocks and are
potentially important for other greenhouse gases. Issues discussed include the delayed
releases (or uptake) of non-CO2 trace gases after burning of forests (either as a
prescribed forest management tool or as a means of land-clearing), forest degradation,
traditional shifting cultivation, and conversion of wetlands to other land uses or the
reverse. These activities and other refinements can be incorporated in more detailed
versions of the calculations.
A Technical Appendix, as mentioned, is also provided, which deals with sources of
information on rates of land use change, a critical activity data input for calculating GHG
emissions.
PART 2
5.9
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LAND USE CHANGE & FORESTRY
5.2 Basic Calculations
5.2.1 Introduction
The basic calculations focus primarily on the flux of CO2 and the land use changes and land
use activities that result in the largest, potential flux of CO2 to the atmosphere or have
the largest potential for sequestering carbon.
Three categories of land use change are considered:
• forest clearing
• conversion of grasslands to agricultural lands
• abandonment of managed lands
In contrast to other aspects of the greenhouse gas emissions methodology, the estimation
of CO2 from land use change requires the consideration of historic time horizons. When
forests are cleared or agricultural lands abandoned, the biological responses result in
"commitments" of fluxes of carbon to or from the atmosphere for many years after the
land use change. This methodology is designed to produce an emissions estimate that is
comparable to other elements of the inventory, fossil fuel emissions, for example. That is,
it attempts to quantify the flux to or from the atmosphere in the inventory year. To do this,
it is necessary to obtain estimates of land use change activities for many years prior to the
inventory year, and estimate the effects of these activities on the current year fluxes. The
three selected categories are considered to be the most important land use changes
affecting CO2 fluxes, but are not a comprehensive set. Many relevant land use changes are
excluded from the basic calculations. These are discussed in the last section of this
chapter.
Relevant forestry (ongoing land use) activity is combined in one very broad category,
managed forests, which is defined here to include potentially a wide variety of land use
practices. Key examples are establishing and harvesting plantations, commercial forest
management and harvesting, and fuelwood gathering. Conceptually, this category is
intended to account for all significant human interactions with forests which affect CO2
fluxes to and from the atmosphere. It is intended to account, at least on a crude level, for
all existing forests, with two exceptions.
I Natural, undisturbed forests, are not considered to be either an anthropogenic
source or sink, and are excluded from the calculations entirely.
2 Forests regrowing naturally on abandoned lands are a net carbon sink attributable to
past human activities and are accounted for separately. "Abandoned" lands are by
definition assumed not to be subject to ongoing human intervention (of significance
to carbon stocks) after abandonment
Several simplifying assumptions are made in the basic calculation methodology. A number
of refinements and removals of simplifying assumptions are possible to improve on the
basic calculation. One important option is to implement the basic calculations at a more
detailed level of subcategories or spatial detail. National experts are strongly encouraged
to do so if data are available. Box 2 discusses possibilities for adapting the methodology to
various levels of detail, depending on the capabilities and data available to the user, and the
relative importance of various components to the individual country.
Other possibilities for improving the accuracy and completeness of the basic calculations
are possible. For example, the fate and amount of belowground biomass (roots, etc.) is
currently ignored in the calculation. The section titled: Refinements to Calculations, later
in this chapter, reviews a number of possible additions and refinements.
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Box 2
ALTERNATIVE LEVELS OF DETAIL
For simplicity and clarity, this chapter discusses calculation of emissions from
at a national level and for a relatively few sub-categories within each
category of land use changes and forestry. The level of detail in the sub-
categories is designed to match the available sources of default input data,
carbon contents and other assumptions. It is important, however, for users
of these emissions methodology guidelines to understand that they are not
only permitted but encouraged to carry out the GHG emissions inventory
calculations at a finer level of detail, if possible. Many countries have more
detailed information available about land use change, forests and agriculture,
than was used in constructing default values here. It may be important in
such countries to carry out emissions calculations at finer levels in two ways:
I Geographic detail finer than the nation as a whole
If data are available, experts may find that GHG! estimation for various
regions within a country are necessary to capture important geographic
variations in ecosystem types, biomass densities, agricultural practices,
rates of burning, etc.
2 Finer detail by sub-category
If data are available, experts may subdivide the recommended activity
categories and sub-categories to reflect important differences in
ecology or species, land use or agricultural practices, bioenergy
consumption patterns, etc.
In all cases, working at finer levels of disaggregation, does not change the
basic nature of the calculations, although, additional data and assumptions
will generally be required beyond the defaults provided in the chapter. Once
GHG emissions have been calculated at whatever is determined by the
national experts to be the most appropriate level of detail, results should
also be aggregated up to the national level and the standard categories
requested in the IPCC proposed methodology. This will allow for
comparability of results among all participating countries. Generally, the data
and assumptions used for finer levels of detail should also be reported to the
IPCC to ensure transparency and replicability of methods. Volume I:
Reporting Instructions discusses these issues in more detail.
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LAND USE CHANGE & FORESTRY
5.2.2 Forest Clearing: CO2 Release
Background
The calculation of carbon fluxes due to forest clearing is in many ways the most complex
of the emissions inventory components. Because of the delayed responses of biological
systems, it is necessary to consider forest clearing activity over three different historic
time horizons and to sum the results to estimate the total flux in the current year. Also, as
with all categories of forest management and land use change activity, it is necessary to
determine net C02 flux.
Forests can be cleared to convert land to a wide variety of other uses, including
agriculture, highways, urban development, etc. In all cases there is a net carbon release
to the atmosphere which should be accounted for in this calculation. The predominant
current cause of forest clearing is conversion to pasture and cropland in the tropics. This
is accomplished by an initial cutting of undergrowth and felling of trees. The biomass may
then be combusted in a series of on-site burns or taken off site to be burned as fuel, or
perhaps used for forest products. A portion of the biomass remaining on site as slash is
not actually combusted and remains on the ground where it decays slowly. Some of the
decay of remaining carbon left on the ground is probably accomplished by termites, which
produce both CO2 and CH4.14 However, the methane release from cleared, unburned
biomass is very difficult to quantify and ignored for purposes of the basic calculation,
where all of the carbon in biomass which decays is assumed to be released as CO2. Of the
portion burned on site, a small fraction of the carbon remains as charcoal, which resists
decay for well over 100 years or more; the remainder is released instantaneously to the
atmosphere.16 For biomass removed for fuelwood, the fate is very similar. A small fraction
of the carbon remains in ash which effectively provides long term storage, while the
majority of the carbon is released to the atmosphere.
Forest conversion also results in CO2 emissions through soil disturbance, particularly
when the conversion is to cultivated or tilled lands. When forests are converted to
croplands, a fraction17 of the soil carbon may be released as CO2, primarily through
oxidation of organic matter. This can be a long term process which continues for many
years after the land use change occurs. The basic calculations allow for estimation of loss
in soil carbon due to forest clearing. Because of the uncertainty in current understanding
of this component, and the difficult historic data requirements, the users are encouraged
to exercise their own judgement as to whether or not to include this calculation in the
basic estimates.
Calculations
Emissions of CO2 due to forest clearing are calculated through a sequence of easy steps
treating:
• the net change in aboveground biomass carbon
• the portion of this change that is burned in the first year versus the amount left to
decay over a longer time period
• for the burned portion, loss to the atmosphere versus long term storage in ash
• current emissions from decay of biomass cleared over the previous decade
• if estimated, current releases of carbon from soils due to clearing over the previous
25 years
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LAND USE CHANGE & FORESTRY
18 .
Net change in aboveground biomass
First, the amount of biomass affected by clearing in the emissions inventory year"' is
calculated by multiplying the annual forest area converted to pasture or cropland or other
land uses by the net change in aboveground biomass. This calculation is carried out for
each relevant forest type and, if appropriate, by region within a country. The net change
is the difference between the density (t dm/ha) of aboveground biomass on that forest
land prior to conversion, and the density of aboveground living biomass (t dm/ha)
remaining as living vegetation, after clearing. The after clearing value includes the biomass
that regrows on the land in the year after clearing and any original biomass which was not
completely cleared.
Tables I and 2 provide a range of values for aboveground biomass in forests prior to
clearing, which can be used as default data if more appropriate and accurate data are not
available in a given country. For aboveground biomass after clearing, it is necessary to
account for any vegetation (i.e., crops or pasture) that replaces the vegetation that was
cleared. A reasonable figure for crops or grasslands is 10 tonnes of dry biomass per
hectare.21 The recommended default assumption is that all of the original aboveground
biomass is destroyed during clearing. If locally available data indicate that some fraction of
the original biomass is left living after clearing, this should be added to the after clearing
value.
To arrive at net change, one reduces the gross release from land clearing in a given base
year by 10 tonnes dry biomass (or some other value if more accurate information is
available) for each hectare cleared. The total affected biomsiss for a given year can be
calculated from the total area cleared (by region and type) and multiplied by the net
change in living on site biomass (including regrowth). This provides an estimate of the total
affected biomass for the time period in question.
Immediate emissions from burning
The biomass that is cleared has one of three immediate fates:
I a portion may be burned on site;
2 a portion may be removed from the cleared site and used as fuelwood, or for
products;
3 a portion is converted to slash and decays on site to carbon dioxide over a decade or
so. Some estimates in the literature suggest that a global average of about 50% of the
cleared forests are burned in the first year with the remaining 50% left to decay.
This value could be used as a default for first order calculations if the user does not
have access to more appropriate local information. It is important to recognize that
this average is dominated by practices in Latin America which has the largest current
rates of deforestation. There are certainly wide variations in burning practices in
different regions. To calculate the gross amount of carbon released in the current
year to the atmosphere it is necessary to consider the: burned portions and the
decaying portion over different time horizons.
To estimate the CO2 released by the burning of cleared aboveground vegetation, estimate
a) the fraction of the affected biomass that is subjected to burning (on and off site - the
remaining, disturbed biomass is slash) and b) the fraction of the burned biomass that is
oxidized. The fraction of burned biomass which does not oxidize remains as charcoal.
The amount of biomass oxidized is converted to carbon units to estimate the carbon
dioxide flux from burning.24 A reasonable average for converting from dry biomass to
carbon content is to multiply dry biomass by 0.45. Of the portion of cleared biomass
which is burned, some of this may be burned in the field to- facilitate clearing, and some
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LAND USE CHANGE & FORESTRY
may be removed and used as fuel. The portion which is burned in the field is used
subsequently for calculating the trace gas emissions from open burning of cleared forests,
in the next section. The amount removed for fuel is important for calculations of fuel
wood extracted from managed forests in the last component of these basic calculations.
Emissions from decay
The aboveground biomass which remained on site but was not burned will oxidize in
roughly a decade, and this historical release associated with land clearing must be
considered. The 10 year period is a recommended default value, as a reasonable historical
horizon in light of the twin realities of data availability and biological dynamics. This can
be varied if the user has data or a strong rationale to suggest that a longer or shorter
average decay time is more representative of local conditions. The "committed" flux
calculation simply accounts for the current oxidizing of material left unburned during the
specified historic decay period.
The decay phenomenon can be simply characterized for emissions estimation purposes.
Each year, some portion of the cleared aboveground biomass is left as slash, and we
assume that 10% of this decomposes each year. Therefore, the total carbon being released
to the atmosphere in the inventory year is a function of the land clearing rate for each of
the past 10 years, and the portion of the aboveground carbon remaining on site but not
combusted each year. The current year emissions from decay of biomass cleared in a
historic year would be 10% of the total decay. The total current emissions from decay of
historically cleared biomass would then be the sum of the current estimated emissions
from biomass cleared in each of the ten historic years.
For practical purposes, the methodology recommends working with decadal average
values for the land clearing and portion left to decay which can then simplify the
calculation. Working with average values, one would in theory divide the total emissions
from decay by 10 to get the contribution of one "average" historic year's clearing to
current emissions, then multiply by 10 to account for ten historic years' clearing which
could be expected to affect current emissions. Obviously the division by 10 and
multiplication by 10 cancel each other and can be ignored. Therefore, the flux in the
inventory year from historic land clearing of the aboveground vegetation is simply is
expressed in Equation 5.1.
EQUATION 5.1
average annual land clearing over the period
x the average quantity of aboveground biomass per hectare remaining on
site as slash but not burned (either oxidized or converted to charcoal)
x carbon content of dry biomass
flux in the inventory year from historic land clearing of the aboveground
vegetation
Soil carbon release
For calculating the annual CO2 flux associated with the loss of soil carbon following forest
clearing, the methodology is essentially the same as the approach for treating the historic
flux from slash. The time horizon suggested is twenty five years. The historic release from
soils is simply the average annual land clearing times the change in carbon stock in soil
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LAND USE CHANGE & FORESTRY
between the original forest and a twenty five year old pasture or crop land. For simplicity,
it is assumed that the soil carbon release is linear over the 2ij year period.
The annual rate of soil carbon loss would be total change in soil carbon from before
clearing levels to the final level divided by 25. Some evidence exists that roughly 50% of
soil carbon is lost over twenty-five years after temperate and boreal forest are converted
to cultivated soil.28 This value, although highly uncertain, could be used as a default for
initial calculations, if more accurate information or measurements are not available to
users. This would imply that the annual rate of soil carbon los would be 2% (50%/25
years).
The contemporary flux associated with past land use could be calculated by multiplying the
number of hectares of land converted in each of the previous 25 years by the annual per
hectare loss in soil carbon and summing. Alternatively, the average annual historic
conversion rate over a twenty-five year period could be multiplied by the annual loss rate
times twenty-five. The average rate of conversion is simply the total hectares converted
over the period divided by 25 years.
It is an open question if the conversion of tropical forests to pasture results in loss of soil
carbon as CO2.29 Pending resolution of the scientific debate on this issue, it is left to the
judgement of users whether or not to include this component in the calculations, and
what values to use for the portion of carbon lost. Tables 3 and 4 provide average values
for soil carbon in undisturbed tropical, temperate, and boreal systems.
As with emissions from decay of aboveground biomass, the recommendation is to use
average values for the rate of land clearing, soil carbon content and portion of soil carbon
lost over time. Again, for the same reason, the theoretical requirement to multiply and
divide by 25 cancel. The calculation of current emissions (from soils in forest cleared over
25 years) is expressed in Equation 5.2.
EQUATION 5.2
the average annual clearing rate over the last 25 years
x change in soil carbon between a forest system and a 25 year old pasture
or crop land.
current emissions (from soils in forest cleared over 25 years)
The estimate of the total carbon released in the inventory year from current and historic
clearing is calculated by summing the current year release of carbon due to burning - on
site or as fuelwood, the average long-term annual release of carbon from decay of biomass
cleared over the base decade, and, if estimated, the current year release of soil carbon due
to land clearing over the previous 25 years.
Burning of Cleared Forests: Non-CO2 Trace gases
Where there is open burning associated with forest clearing;, it is important to estimate
the emissions of methane (CH4), carbon monoxide (CO), nitrous oxide (N2O), and oxides
of nitrogen (NOX, i.e., NO + NO2). The approach is essentially the same as that used for
non-CO2 trace gases for all burning of unprocessed biomass, including traditional biomass
fuels, savanna burning and field burning of crop residues. For all these activities there is a
common approach in the proposed methodology in that crude estimates of trace gas
emissions can be based on ratios to the total carbon released by burning. The carbon
trace gas releases (CH4 and CO) are treated as direct ratio;; to total carbon released. To
handle nitrogen trace gases, ratios of nitrogen to carbon in biomass are used to derive
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LAND USE CHANGE & FORESTRY
total nitrogen released from burning, and then emissions of N2O and NOX are based on
ratios to total nitrogen release. Table 7 provides suggested default values for trace gas
emission ratios.30 These are presented with ranges which emphasize their uncertainty.
However, the basic calculation methodology requires that users select a best estimate
value.31
In sum, clearing by burning releases other gases in addition to CO2 which are by-products
of incomplete combustion: methane, carbon monoxide, nitrous oxide, and oxides of
nitrogen, among others. Unlike CO2 emissions from land clearing, which may or may not
imply a net release of CO2 to the atmosphere (depending on whether or not the
vegetation is allowed to regrow), emissions of these other gases from biomass burning are
net transfers from the biosphere to the atmosphere. The calculations described here
ignore the contemporary releases associated with past burning events. These delayed
releases are known to exist, but are sufficiently uncertain that they should be ignored at
present. This and other possible refinements to the calculations are discussed in the last
section.
All of the crude biomass burning calculations have two components: I) estimating total
carbon released, and 2) applying emission ratios to estimate emissions of the non-CO2
trace gases. In the case of burning of cleared forests, part I has been carried out in the
previous section which included the estimation of carbon emissions from the portion of
cleared forests which is burned on site in inventory year. The total carbon release from
this on site burning (not including any carbon released from decay or soils) provides the
basis for the inventory year release of non-CO2 trace gases. To complete the calculations,
it is necessary only to add part 2 of the calculation — the release of non-CO2 trace gases
from current burning.
Once the total carbon released from on site burning of cleared forests has been
estimated, the emissions of CH4, CO, N2O, and NOX can be calculated.32 The total carbon
released due to burning is multiplied by the emission ratios of CH4 and CO relative to
emissions of total carbon to yield total emissions of CH, and CO (each expressed in units
of C). The emissions of CH4 and CO are multiplied by 16112 and 28/12, respectively, to
convert to full molecular weights.
To calculate emissions of N2O and NOX, first the total carbon released is multiplied by the
estimated N/C ratio of the fuel by weight (0.01 is a general default value for this category
of fuel33) to yield the total amount of nitrogen (N) released. The total N released is then
multiplied by the ratios of emissions of N2O and NOX relative to the total N released of
the fuel to yield emissions of N2O and NOX (expressed in units of N). To convert to full
molecular weights, the emissions of N2O and NOX are multiplied by 44/28 and 30/14,
respectively.
The trace gas emissions from burning calculation are summarized as follows:
• CH, Emissions = (carbon released) x (emission ratio) x 16/12
• CO Emissions = (carbon released) x (emission ratio) x 28/12
• N2O Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 44/28
• NOX Emissions = (carbon released) x (N/C ratio) x (emission ratio) x 30/14
Conversion of Grasslands to Cultivated or Pasture Lands
Conversion of a grassland to cultivated land could result in net CO2 emissions to die
atmosphere due to soil disturbance and resultant oxidation of soil carbon even if there is
no net reduction in standing biomass. The carbon density in the aboveground vegetation in
grasslands is approximately the same as the annual average aboveground biomass in crops
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LAND USE CHANGE & FORESTRY
or pasture, and therefore any change in this aboveground pool due to the land use change
is generally small in comparison to other changes in carbon stocks in terrestrial systems.
Consequently, changes in aboveground biomass are ignored in the basic calculation. Thus,
this calculation focuses on the change of carbon in soils. The currently available
information relates primarily to the temperate zone, where there is evidence that perhaps
50% of the soil carbon in the active layer (roughly the top one meter) has been lost over
roughly a SO year period, with most of this loss occurring in the first 25 years. The loss
tends to be exponential. In some agricultural systems, there has been an accumulation of
carbon rather than a loss. The actual rate of soil carbon loss in a specific area of
agricultural land, is a function of the specific agricultural use and management practices as
discussed in the refinements section of this chapter. There is evidence that, in some cases,
the conversion of grasslands to cultivated lands has actually increased carbon stocks in
certain systems. However, data and scientific understanding are not sufficient to include a
simple methodology for characterizing these relationships in the current basic calculations.
Data on changes in soil carbon in tropical systems are sparse. Therefore, no default
assumptions can be provided for this region. In the initial application of basic calculations,
grassland conversion can be ignored for tropical countries unless the user has access to
data on the rate of soil carbon loss (or accumulation) after this land use change. This is an
important research issue, as discussed in the refinements section of this chapter. As a
result, in the initial application of the basic calculations to the land use change of
converting grasslands to cultivated lands, default values are recommended only for changes
in the soil carbon pool in temperate grassland systems. The simple calculation structure
would be the same for tropical systems but the use of available default assumptions and
values (based on temperate systems) is not recommended.
For calculating the carbon flux from this land use change, a twenty-five year time horizon
is suggested. The annual rate of soil carbon loss would be total change in soil carbon from
before conversion levels to the final level divided by 25. Soil carbon contents of natural
grasslands are highly variable and should be evaluated based on locally available data if
possible. Very crude general default values are 60 tonnes/ha for tropical systems and 70
tonnes/ha for temperate systems. As noted above, there is some evidence that 50% of
soil carbon is lost over twenty-five years after temperate grasslands are converted to
cultivated soil. This value could be used as a default for initial calculations, if more
accurate information or measurements are not available to users. This would imply that
the annual rate of soil carbon loss would be 2% (50%/25 yeairs).
As with soil carbon emissions from forest clearing above, the recommendation is to use
average values for the rate of land conversion, soil carbon content and portion of soil
carbon lost over time. Again, for the same reason, the theoretical requirement to multiply
and divide by 25 cancel. Therefore the calculation is expressed in Equation 5.3.
EQUATION 5.3
average annual land conversion rate over the last 25 years
x change in soil carbon between a grassland system and a 25 year old
pasture or crop land.
carbon flux from conversion of grasslands to cultivated or pasture Lands
For emissions from grasslands used for pasture one needs before and after estimates of
biomass and soil carbon applied in the above methodology. This category may prove to be
important in certain grasslands that are being grazed heavily or burned often.
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LAND USE CHANGE & FORESTRY
Abandonment of Managed Lands
If managed lands, e.g., croplands and pastures, are abandoned, carbon may re-accumulate
on the land and in the soil. The response of these converted systems to abandonment
depends upon a complex suite of issues including soil type, length of time in pasture or
cultivation, and the type of original ecosystem. It may be that some of the abandoned
agricultural lands are too infertile, saline, or eroded for regrowth to occur. In this case,
either the land remains in its current state or it may further degrade and lose additional
organic material (i.e., carbon in the biomass and the soils). Therefore, to calculate changes
in carbon flux from this activity, the area abandoned should first be split into parts: lands
that re-accumulate carbon naturally, and those that do not or perhaps even continue to
degrade.
In the basic calculation, only those that begin to return to an approximation of their
previous natural state are considered. Those that remain constant with respect to carbon
"ox can be ignored. Likewise, the CO2 flux to the atmosphere for those lands that
continue to degrade is likely to be small and hence can also be ignored in the initial
application of basic calculations. In any event, the issue could be considered in a more
refined calculation.
Abandoned lands must be evaluated in the context of the various natural ecosystems
originally occupying them. In addition, the effect of previous patterns of abandonment
should be considered while recognizing the desire for simplicity and practicality. The
process of recovery of aboveground biomass generally is slower than the human-induced
oxidation of biomass. With this in mind and in consideration of possible data sources it is
recommended that abandoned lands be evaluated in two time horizons. A twenty year
historical time horizon is suggested to capture the more rapid growth expected after
abandonment. A second time period - 20 years after abandonment up to roughly 100
years — may be considered if data are available.
The calculation, by original ecosystem (e.g., closed broadleaf forest, open forest, grassland)
is straightforward.
The total area abandoned (total over the previous 20 years including the inventory year) is
multiplied by
I the average annual uptake of carbon in the aboveground biomass, and
2 the average annual uptake of carbon in the soils.
Results of these two calculations are summed to yield the current uptake of carbon due to
abandonment over the previous 20 years of managed lands that are naturally regenerating
to forests or grasslands.
If land use data are available to support calculations over a longer time horizon, national
experts may want to consider adding a pool of forests and grasslands that are regrowing
from abandonment that occurred more than 20 years ago. The growth rates of
aboveground biomass in these forests would be slower than that of forests regrowing
from abandonment that occurred less than 20 years ago. The same calculations can be
repeated for lands abandoned more for than 20 years and up to about 100 years prior to
the inventory year.
Table 5 presents estimates of average annual aboveground biomass accumulation in
vegetation in various regrowing forest ecosystems following abandonment of cultivated
land or pasture.38 These general growth rates, averaged over large regions and many
specific ecosystem types, should be considered crude approximations as applied to the
particular lands regrowing in a given region or country. If more accurate data on these
growth rates are locally available, they should be used. Accumulation of aboveground dry
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LAND USE CHANGE & FORESTRY
biomass can be converted to carbon using a general default conversion value for live
biomass — 0.45 t-C/t dm.
If lands are regenerating to grassland, then only the soil pool needs to be considered.
Default rates of soil carbon uptake for both forests and grasslands can be derived from the
expected sbil carbon values for fully restored natural systems and some simple
assumptions. In temperate and boreal systems it can be assumed that soil carbon
accumulates linearly from some base value (e.g., 50-75% of original stocks) Table 4
provides default soil carbon values for temperate systems. Values for tropical systems are
provided in Table 3, and crude defaults for grasslands were provided in the previous
section (60 t-C/ha tropical, 70 t-C/has temperate). Soil carbon changes in tropical systems
are poorly understood and can be included or ignored in basic calculations at the
discretion of national experts.
The base value at the start of the reaccumulation process in soils would depend on the
average amount of time that cleared lands had been used for agricultural purposes (and
the management practices utilized during the agricultural period) before abandonment.
Based on the simple default assumptions for soil carbon losses from forest clearing one
could calculate the level to which soil carbon would have fa.llen during the agricultural use
period. The default assumption was that after 25 years, soil carbon would have fallen to
50% of the pre-clearing value (i.e., 2% per year linear average change). For example, if the
average agricultural use period was 10 years before abandonment, it could be assumed
that the base value in soils would be 80% of original values. It could be assumed that soil
carbon is restored at roughly the same rate at which it is lost under cultivation. Available
evidence is that the recovery is not this fast in reality. In this forest clearing calculations the
default assumption is that soil carbon might be lost at an average rate of 2 percent of the
original carbon content per year. If no detailed information is available, a default
assumption could be that the soil accumulation occurs linearly roughly one-half this rate
after abandonment. This procedure was used to derive the values presented in the
Workbook. The values given are 1.3 tonnes C/year for temperate evergreen and deciduous
forest soils and 2.0 tonnes C/year for boreal forests. These are one percent of the values
from table 4 for soil carbon in primary forests. This is an important area for further
research.
Managed Forests
The category managed forests as used in these basic calculations is very broad, potentially
including a wide variety of land use practices. A basic organizing concept in this chapter is
that all existing forests can be allocated into one of three categories.
I Natural, undisturbed forests, where they still exist are in balance and should not be
considered either an anthropogenic source or sink. They are therefore excluded
form national inventory calculations.
2 Forests regrowing naturally on abandoned lands are a net carbon sink attributable to
past human activities and are accounted for as discussed in the previous section.
While the current regrowth is considered a response to past anthropogenic activity,
"abandoned" lands are by definition assumed not to be subject to ongoing human
intervention (of significance to carbon stocks) after abandonment.
3 Managed Forests are considered to include all other types of forest That is any forest
which experiences periodic or on-going human interventions that affect carbon
stocks would ideally be included here. In the basic calculations, the chapter focuses
primarily on a few types of human interactions with forests which are believed to
result in the most significant fluxes of carbon. National experts are encouraged,
however, to estimate emissions for any activity related to managed forests which is
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LAND USE CHANGE & FORESTRY
considered to result in significant carbon emissions or removals, and for which
necessary data are available. Any such activities falling within our broad definition of
managed forests should be included in this category and reported to the IPCC as
discussed in Volume I: Reporting Instructions.
Some of the activities in the managed forests category which can potentially produce
significant carbon fluxes are:
• management of commercial forests - including logging, restocking, selective thinning,
etc., as practiced by commercial forest products industries
• establishment and management of commercial plantations
• other afforestation, and reforestation programmes
• informal fuelwood gathering
Based on comments from the land use and forestry experts, the managed forests category
has been broadened to include sub-categories of trees which may not traditionally have
been considered "forests". It can include village and farm trees if these are important for
biomass and biofuel accounting in some developing countries. It could also include urban
trees, trees planted along highways, aircraft runways, etc., if these are considered
significant for a particular country's biomass calculations. These dispersed trees do not
contribute greatly to carbon fluxes to or from biomass on a global scale. However, in
some countries, they may be important in accounting for the total amount of wood used
for fuel. Also, they may be of interest to some countries because of their potential use in
response strategies. For these reasons, they have been included in the basic calculation
methods so that national experts who feel they are important, and have necessary locally
available data, can include them.
As illustrated in the above list, the managed forests category also includes some tree
planting activities which, strictly speaking, are land use changes. Plantation establishment
and other afforestation/reforestation programmes are examples. It is recognized that this
is conceptually inconsistent as the category is intended to account for ongoing interactions
with existing forest. However, from a pragmatic perspective, including these activities
within the category can simplify the calculations. These sub-categories are land-use
changes which create new managed forests. As soon as the land use change occurs (i.e.,
the tree planting), new land use becomes part of the managed forests category which is
accounted for on an annual incremental basis. Although it would be possible, it is not
necessary to estimate the lagged effects of this change as is done with other land use
changes. While including such a range of tree-related activities in one category may
introduce some confusion, the calculation procedure is basically the same for all sub-
categories, and this allows the simplest possible set of emissions calculations.
As discussed in the Overview, the methodology is designed to accommodate users at
several levels of detail. This is especially important in the managed forests category.
Possible levels include:
I A simple first order approach, covering the main sub-categories, with calculations
based on simple default assumptions and default data provided.
2 Calculations at the same level of detail but substituting more appropriate data and
assumptions from local sources.
3 Calculations following the same structure, but broken down to finer levels of detail
to improve accuracy and utility of estimates, where locally available data can support
this.
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LAND USE CHANGE & FORESTRY
4 Estimates derived from much more detailed and precise inventory-based forest
accounting methods. These results can be reformatted and presented in the form of
calculations comparable to those used by the other national experts operating with
less detailed data.
It is highly desirable that the methodology be relevant for countries which have access to
much more detailed data on managed forests. Some countries with highly developed
forestry industries, do in fact keep track of existing commercial forests through periodic
detailed surveys. For such countries, it is possible to derive from survey results aggregate
values comparable to the data and assumptions used in the simple approach, and present
them in this common format. This will assist all interested parties in evaluating various
national estimates on a comparable basis, and will thus be necessary to comply with
requirements of Volume I: Reporting Instructions. Box 3 provides some further
discussion of these procedures.
Box 3
ADAPTING DETAILED FOREST INVENTORY DATA To THE IPCC FORMAT
A number of countries with highly developed commercial forestry industries
routinely collect forest biomass data at a detailed inventory level which
allows for relatively precise and direct assessment of the changes in biomass
stocks, and equivalent carbon fluxes. National experts working with data of
this kind, should be able to derive from it values equivalent to those used in
calculating emissions with the IPCC methodology.
Regardless of how detailed the data base used, the results will be ultimately
presented in units (e.g. Gg) of carbon and CO2 emitted or removed in a
given average responses (e.g., annual biomass growth rates by ecosystem
type) which year. Similarly, the number of hectares of forest in various types
can be aggregated up to categories matching the simple approach outlined
here. The amount of biomass removed as commercial harvest or for other
reasons, should also be relatively well established in such inventories. With
these data, it should be
possible to, in effect, work backwards to the derive the necessary input
assumptions and aggregate values. For example, national experts might start
with a change in total biomass for specified forest types (and/or regions)
over a specified time period. Then they could add the amounts of biomass
removed through commercial harvest or for other reasons (e.g., thinning),
to get the total growth of biomass over the period. This could then be
divided by the number of kilo-hectares in the category (and the number of
years, if a multi-year period) to get average annual growth rates by category.
This would then provide all the values needed to reconstruct the
calculations in a comparable form to those from countries with minimal data.
The national emission/removal estimates presented in this form would then
be easily understood and compared by all other parties involved in the
international climate change discussions. The intent is to provide a
calculation and reporting framework which can accommodate users with
vastly different levels of data available, yet allow them to place the results on
a comparable basis.
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LAND USE CHANGE & FORESTRY
Managed forests (which are harvested for forest products including fuel wood) may be
either a source or a sink for carbon dioxide. The simplest way to determine which is by
comparing the annual regrowth versus annual harvest, including the decay of forest
products and slash left during harvest. Decay of biomass damaged or killed during logging
results in short-term release of CO2. For the purposes of the basic calculations, the
recommended default assumption is that all carbon removed in wood and other biomass
from forests is oxidized in the year of removal. This is clearly not strictly accurate in the
case of some forest products, but is considered a legitimate, conservative assumption for
initial calculations. Box 4 provides some further discussion of this issue.
Box 4
THE FATE OF HARVESTED WOOD
Harvested wood releases its carbon at rates dependent upon its end-use:
waste wood is usually burned immediately or within a couple of years, paper
usually decays in up to 5 years (although landfilling of paper can result in
longer-term storage of the carbon and eventual release as methane or CO),
and lumber decays in up to 100 or more years. Because of this latter fact,
forest harvest (with other forms of forest management) could result in a net
uptake of carbon if the wood that is harvested is used for long-term
products such as building lumber, and the regrowth is relatively rapid. This
may in fact become a response strategy.
For the initial calculations of CO2 emissions from managed forests, however,
the recommended default assumption is that all carbon in biomass harvested
is oxidized in the removal year. This is based on the perception that stocks
of forest products in most countries are not increasing significantly on an
annual basis. It is the net change in stocks of forest products which should
be the best indicator of a net removal of carbon from the atmosphere,
rather than the gross amount of forest products produced in a given year.
New products with long lifetimes from current harvests frequently replace
existing product stocks, which are in turn discarded and oxidized. The
proposed method recommends that storage of carbon in forest products be
included in a national inventory only in the case where a country can
document that existing stocks of long term forest products are in fact
increasing.
If data permits, one could add a pool to Equation 5.4 (I) in the managed
forests calculation to account for increases in the pool of forest products.
This information would, of course, require careful documentation, including
accounting for imports and exports of forest products during the inventory
period.
The net regrowth of the forest (and re-accumulation of carbon) depends on the type of
forest logged and the intensity of logging or other harvesting. Well managed commercial
forests, replacing natural forests, would over the long term be expected to be close to
zero net emissions. In many cases, where historically cleared areas are regrowing under
commercial management, with limited logging, the forest areas are currently a net sink. If
forests (or parts of forests) are logged or harvested at a rate which exceeds regrowth,
then there is a net loss of carbon.
Establishment of plantations and other tree planting activities result in absorption of CO2
from the atmosphere and storage of this carbon until the vegetation is burned or decays.
Restocking of managed forests, planting of urban, village and farm trees, and establishing
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LAND USE CHANGE & FORESTRY
plantations on unforested lands, therefore, result in an uptake of carbon from the
atmosphere, at least until the biomass is harvested and enters a decay pool, or the system
reaches maturity. The effect of plantation establishment can be to create a net sink for
carbon even if the plantation is harvested for products that are rapidly oxidized (e.g.,
fuelwood). If the plantations are harvested so that there is no net loss of biomass over
time (i.e., harvested in a sustainable fashion), then the rate of carbon accumulation on land
is positive (or at least non-negative) and tied directly to changes in the area of plantations
and their average biomass.
The conversion of natural forests to plantations may result in an initial loss of biomass
carbon due to an initial reduction in standing biomass. If plantations are established by first
clearing existing forests, the initial loss should appear under forest clearing above.
Reaccumulation of biomass in these plantations in subsequent years would be accounted
for here under managed forests. The approach accounts for all plantations in operation in
a given year, including both previously planted and newly established plantations.
The method for calculating the affected forest harvest, afforestation, and reforestation on
carbon stocks is shown in Equation 5.4.
EQUATION 5.4
I
Hectares of land in a particular category (e.g., plantations)
x Average annual growth per hectare in biomass
Gross annual growth increment.
Total biomass increment is the sum of all relevant categories.
2
Total Harvest by category
x Expansion factor to treat slash
Gross annual biomass loss.
Total harvest and other biomass loss is the sum of all relevant categories of harvest
3
Total gross annual growth increment -
Total gross annual biomass loss
Net annual biomass change (positive or negative).
The recommended unit of calculation is dry biomass, and it is necessary to convert to
carbon for emissions estimation. A general default value of 0.45 tonnes-C/tonne dry
biomass is recommended for all biomass calculations. If more accurate conversion values
are available for the particular system, these should of course be used.
Growth Increments
Estimates of average annual accumulation of dry matter as biomass per hectare are
presented for in forests naturally regrowing by broad category in Table 5. These values
can be used as default values for growth rates in similar managed forest categories if no
other information is available. Fore forests which are more intensely managed (e.g., with
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LAND USE CHANGE & FORESTRY
periodic thinning, restocking, etc.) annual growth increments could be somewhat different
In countries where such practices result in significantly different average growth rates,
locally available data should be used instead of Table 5 values. Values for some typical
plantation species are presented in Table 6, can be used as default values.
Biomass Loss
Two approaches can be used to estimate biomass harvest and other losses from managed
forests.
Commercial Harvest Statistics The first, and obvious, approach is to use statistics on
amounts of biomass actually removed from forests. In countries where commercial
harvests of various kinds make up a large majority of total biomass losses, and statistics are
well maintained, this may be the only approach needed. Country specific estimates of
commercial harvest statistics are provided in annual FAO Forests Products Yearbooks
(I993b). and periodic Assessments (e.g., FAO, I993a), and are also generally available from
national governments.
In using commercial harvest statistics, users must pay careful attention to the units
involved. Commercial harvest statistics are often provided for the commercial portion of
biomass only, in cubic meters (m3) of roundwood. If this is the case, values will need to be
converted to tons of dry biomass. and total biomass removed including slash. Some
general default values for converting volume data to tons are 0.65 t dm/m3 for deciduous
and 0.45 t dm/m3 for conifers. To account for the biomass lost beyond the commercial
wood portion expansion factors can be applied. Some general default values from the
literature are 1.75 for undisturbed forests and 1.90 for logged forests. There is
considerable variability in these conversion values and expansion factors, so use of more
specific locally available data is highly desirable. Also, some commercial harvest data may
be reported as equivalent total biomass (i.e., expansion factors already applied). It is
important to check carefully the information in the original harvest data to ensure that
expansion factors are used only where appropriate.
Fuelwood Consumption Accounting In many countries, however, commercial statistics will
give only a partial account of wood removals and may need to be supplemented with an
alternative approach. Significant amounts of biomass may removed from forests on an
informal basis (i.e., they are never accounted for in commercial statistics). This is generally
true where "traditional" biomass fuels make up a major share of total fuel used in
residences and small commercial enterprises.
The alternative approach, Fuelwood Consumption Accounting, first estimates fuelwood
consumed based on per capita consumption data and population statistics. This accounting
should also consider charcoal consumption, and "back out" an estimate of the wood which
must have been consumed in traditional charcoal manufacture. The Fuelwood
Consumption Accounting approach is discussed in more detail in the Energy chapter, in
the section on emissions from traditional biomass fuels. Results from this type of
accounting can be used in managed forest calculations to account for removals of carbon.
Any wood which was extracted from cleared forests and used for fuel, will already have
been accounted for in the forest clearing calculations above. This amount should be
subtracted from total wood consumed, directly for fuel and for traditional charcoal
making, to determine the amount which must have come from remaining managed forests.
The result of this calculation can then be combined with any commercial harvest amounts
to produce a total amount of biomass lost from managed forests.
There is an implicit assumption that slash is not accumulating. The instantaneous release of
CO2 from the current year's slash that is explicit in Equation 5.4 (2) is a simple
mathematical device to treat slash oxidation from previous years under the assumption
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LAND USE CHANGE & FORESTRY
that the slash pool is not changing. The expansion factor for slash in Equation 5.4 (2) could
be modified to address the destruction of below ground biomass left after harvest
Finally, although plantation establishment usually results in an accumulation of soil carbon,
conversion of natural forests to plantations could cause a net loss of carbon from the
soil. Because of the uncertainty about the magnitude and direction of the soil carbon
change in plantation systems, this is ignored in the basic calculations. This issue is discussed
in the Refinements section.
5.3 Refinements In Calculations
5.3.1 Issues and Possible Methodologies
There are a number of areas in which the basic calculations, could be improved at least
theoretically. Simplifying assumptions have been made in many places in order to produce
methods consistent with data likely to be available in many countries. The basic
calculations focus only on the most important categories for emissions of CO2 within a
much larger set of land use and forest management activities having some impact on GHG
emission fluxes. Some activities are known to result in GHG fluxes, but cannot be
quantified based on the available scientific research results. Many of these issues are
summarized below to assist users in considering which, if any, of these possible
refinements could be included in national inventories, currently, or in the future as
scientific understanding improves.
The first section deals with the subcategories already discussed in the basic calculations,
but highlights a number of ways in which these calculations could be augmented. The
second section discusses additional categories of land use change or forest management
which could be added to the categories in the basic calculations.
5.3.2 Possible Refinements or Additions to Basic
Categories
Cleared Forests
Forest clearing is a very complex and diverse set of activities which can have many
interactions with biospheric fluxes of greenhouse gases over long periods of time. The
components of this set of interactions which are included in the previous section are
those on which there is general agreement among experts of their importance and simple
estimation procedures. A number of other possible elements have been discussed in the
scientific literature, but are controversial or difficult to calculate at present.
• Emissions from Burning of Cleared Forests
A number of aspects of emissions due to burning could be treated in more detail.
a Subsequent burns in years after clearing. In some cises, where forests are cleared
for agricultural purposes, the land may be partially burned in the year of
clearing, but may also be burned again in later years. Fearnside (I990b) indicates
that pastures in the Brazilian Amazon are typically burned two or three times
over about a ten year period. This would cause a larger fraction of carbon in
cleared biomass to be released to the atmosphere sooner than the approach
now included in the basic calculations, and would certainly increase emissions of
non-CO2 trace gases from biomass burning.
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LAND USE CHANGE & FORESTRY
b Non-CO2 trace gases re/eased after burning. Basic calculations address the main
issues in trace gas production by burning, however, they do not treat all issues.
For instance, the effect of past burning, particularly of forests, on trace gas
exchanges must eventually be considered. Specifically, the instantaneous release
of non-CO2 trace gases when forests are burned is included in Land Clearing
calculations. However, the longer-term release or uptake of these gases
following forest burning is an important research issue and should eventually be
included in refinements of calculations. The issue of the contemporary release
of non-CO2 trace gases associated with past burning is complex. For example,
clearing by burning may stimulate soil nutrient loss. Measurements in temperate
ecosystems44 indicate that surface biomass burning enhances emissions of N2O
and NOX from the soils for up to 6 months following the burn; however, in
other studies measurements of N2O emissions at a cleared and burned tropical
forest site in Brazil, begun five months after the burn and continuing for a year,
were not significantly different, however, from those taken from a nearby intact
forest site. The "historic" issue is obviously complex and further research is
needed before an adequate methodology for emissions calculations can be
proposed.
• Delayed release of non-CO2 trace gases after land disturbance.
Even when no burning is involved there may still be a release of trace gases. An
experiment in a temperate forest in the northeast United States found that
clearcutting resulted in enhanced N2O flux to the atmosphere via dissolution of N2O
in the soil water, transport to surface waters, and degassing from solution. An
experiment in Brazil found that N2O emissions from newly clearcut tropical forests
were about three times greater than those from adjacent undisturbed forests.
Conversion of tropical forests to pasture also has been found to result in elevated
N2O emissions relative to the intact forest soils.48 Another example involves the
loss of a sink for methane which, in effect, adds to the atmospheric burden of CH4.
Specifically, the loss of forest area (tropical or temperate) may also result in
increased net CH4 emissions to the atmosphere. Soils are a natural sink of CH4 (i.e.,
soils absorb atmospheric CH4), and various experiments indicate that conversion of
forests to agricultural lands diminishes this absorptive capacity of soils.
• Methane from termites attributable to biomass left to decay
When forests are cleared, a portion of the cleared biomass may be left to decay on
the ground. Frequently some of the biomass decay is accomplished by termites which
emit both methane and carbon dioxide during this process. Fearnside (I990b)
estimates that 75% of the unburned carbon is decomposed by termites, and of this
75%, 99.8% is released as CO2 and 0.2% is released as CH4. Fearnside suggests that
forest clearing results in increased termite populations and thereby enhances natural
termite CH4 emissions. However, as discussed by Collins and Wood (1984), data
from Malaysia, Nigeria, and Japan indicate that clearing and cultivation in some forests
reduces termite populations. The only incidence of termite abundance increase
following clearing cited by Collins and Wood was entirely due to a fungus-growing
termite, a type of termite which is unlikely to produce methane. Because of the
uncertainty of the effect of clearing on termite populations and associated CH4
release, no guidance on calculation of this component is included in the methodology.
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LAND USE CHANGE & FORESTRY
• Soil carbon loss in tropical systems
The basic calculations allow but do not encourage estimation of soil carbon loss after
clearing of tropical forests. There are research results which indicate that conversion
of tropical forests to pasture may or may not result in loss of soil carbon. Because
of the uncertainty no recommendation is made in the basic method concerning
whether .and how to estimate this component. Further research appears needed to
resolve this issue.
• Fate of roots in cleared forests
The basic calculation ignores the fate of living belowground woody biomass (roots,
etc.) after forest clearing. The amount of belowground biomass affected, and its fate,
need to be considered as work continues beyond the basic calculations. This
belowground biomass could be treated as slash but with perhaps a longer decay time.
The issue merits research.
• Aboveground biomass after conversion
In the basic calculation, a single default value (10 tonnes dm/ha) is recommended for
aboveground biomass which regrows after forests are cleared for conversion to
crops or pastures. This may be somewhat variable depending on the type of crop or
other vegetation which regrows. National experts carrying out more detailed
assessments may wish to account more precisely for this variability.
Conversion of Grasslands to Cultivated Lands:
Non-CO2 Trace Gases
Conversion of natural grasslands to managed grasslands and to cultivated lands may affect
not only the net emission of CO2 but CH4, N2O, and CO emissions as well. For instance,
the conversion of natural grasslands to cultivated lands has been found in the semi-arid
temperate zone to also decrease CH4 uptake by the soils. It is not clear what the effect
on N2O would be, unless of course nitrogen fertilization occurs. The effect of conversion
of natural grasslands to managed grasslands on trace gas emissions has not been evaluated
in the field, except for the effect of associated nitrogen fertilization on N2O emissions.
Nitrogen fertilization on managed fields may increase carbon accumulation on land, relative
to the unfertilized system, and grazing by domestic animals may also affect trace gas fluxes.
CO fluxes may be affected due to changes in soil temperature and moisture. These effects
on trace gas fluxes, however, are highly speculative and remain a research issue.
Abandoned Lands
The basic calculations account only for the portion of abandoned lands which regrow
toward a natural state. There may be additional releases of carbon from abandoned lands
which continue to degrade. Where data are available, analysts doing detailed assessments
may wish to account for this phenomenon.
Managed Forests
Prescribed Burning of Forests: Non-C02 Trace Gases
The issue of prescribed forest burning is complex because of two issues. First, there is the
question of the rate of change that humans have induced and second, there is the question
of releases of trace gas several years after the burning. Prescribed burning is a method of
forest management by which forests are intentionally set; on fire in order to reduce the
accumulation of combustible plant debris and thereby prevent forest fires, which could
possibly be even more destructive. This activity is primarily limited to North America and
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5.27
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LAND USE CHANGE & FORESTRY
Australia. Because carbon is allowed to re-accumulate on the land after burning no net
COj emissions occur over time,'
from the biomass combustion.
S3
although emissions of CH4, CO, N2O, and NOX result
Some of the issues associated with prescribed forest burning, particularly in the temperate
world, remain important research topics. Some have suggested that prescribed forest
burning may be increasing carbon stocks in forests and hence serving as a CO2 sink, but at
the same time adding other radiatively important non-CO2 trace gases to the
atmosphere. An important issue is the change in burning rate because of human activity. Is
prescribed burning, and its consequent emissions, just a man-made replacement for what
would have occurred naturally? What is the rate change? If we assume that this question,
the rate of change, can be answered, then the issue of trace gas release for prescribed
burning is similar to trace gas emissions following forest clearing deforestation.
The second complicating issue which should be considered is the release of non-CO2
trace gases in years after burning. This is also discussed under "Cleared Forests" above.
The same uncertainties apply here, although this may be a less important area for
prescribed burning, because the forests will be regrowing quickly, and possibly overcoming
the conditions which could cause longer term trace gas emissions.
Soil carbon and establishment of plantations
In the basic calculations, no soil carbon accumulation is assumed plantations are
establishing (or other tree planting activities occur) on previously non-forest lands. If
plantations are established where natural or managed forests previously existed, then the
carbon content of soils may not change significantly. However, it is possible that the
establishment of plantations on previously non-forest lands could result in accumulation of
soil carbon over time. Further investigation may be useful to determine whether this is a
significant enough effect to warrant addition to the calculations.
5.3.3 Other Possible Categories of Activity
Several other land use activities affect the flux of carbon dioxide and other trace gases
between the terrestrial biosphere and the atmosphere. Shifting cultivation may now be
reducing the storage of carbon in forests, because of shorter fallow periods, and thereby
becoming a net source of CO2 to the atmosphere. The changing areas and distribution of
wetlands may be adding to or reducing the methane burden of the atmosphere. These
issues are complex; often the sign of the flux is not even known, and simple models may
not give reasonable results. In this section, some of the issues and possible methodological
approaches are recorded; however, an agreed-upon methodology is not yet at hand.
Shifting Cultivation
Shifting cultivation, or slash-and-burn agriculture, is a common agricultural practice in the
tropics in which short periods of cultivation (usually about 3 to 5 years) alternate with
longer periods of fallow (about 10 to 50 years). Clearing occurs by initial cutting and
felling, followed by a series of burns. When practiced in the traditional manner, shifting
cultivation produces essentially no net CO2 emissions because the forest is allowed to
return to its original biomass density during the fallow period.5 However, increasing
population pressure has reduced the lengths of fallow periods so that currently much of
the fallow land is not allowed to recover and net CO2 emissions are believed to result.55
Loss of soil carbon also may occur during shifting cultivation, although the loss is certainly
far less than for permanent cultivation.
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LAND USE CHANGE & FORESTRY
Calculation of net emissions due to shifting cultivation requires calculation of average
annual emissions due to clearing of forests for cultivation and calculation of average annual
uptake due to abandonment of cultivated lands in the fallow period of the shifting
cultivation cycle. This involves a rather complex pattern of land cohorts and probably
requires a model to do the book keeping.
The basic concepts are not difficult. The carbon calculations would proceed almost exactly
like the deforestation and abandonment terms in the basic: methodology; however, the
difficulty is that the abandonment period may be shorter, and this may only be apparent by
using a cohort-based model and a finite stock of forest. In other words the increasing rate
of shifting cultivation (the likely data) will force a shorter fallow period and hence less
regrowth, and this dynamic may only become apparent when one models the shifting
cultivation cycle within a specific area of available forest
One intermediate simple approach is to split the calculation into the two logical
components. The deforestation component which would be treated similarly to the basic
calculations; namely, convert the above ground dry biomass to carbon (multiply by 0.45)
and assume 90% of this material is released as CO2 less the amount taken upon by the
replacing crops (default value of 5 tonnes of carbon per hectare). In this intermediate step
one ignores soil carbon and history since the abandonment period follows so quickly upon
deforestation. To calculate the uptake of carbon by the regrowing forest during the fallow
cycle, simply estimate the amount of land in abandonment, (but not yet in steady-state) and
the average rate of carbon accumulation per unit area in these fallow lands. The difference
would be the net flux of CO2 associated with shifting cultivation.
Flooding and Wetland Drainage
Land Flooding
Flooding of lands due to construction of hydroelectric dams, or other activities, results in
emissions of CH4 due to anaerobic decomposition of the vegetation and soil carbon that
was present when the land was flooded, as well as of organic material that grows in the
floodwater, dies, and accumulates on the bottom. The methane emissions from this source
are highly variable and are dependent on the ecosystem "icype", and the status of the
ecosystem, that is flooded (i.e., above- and below-ground carbon, plant types, whether any
pre-flooding clearing occurred, etc.) and on the depth and length of flooding (some regions
may only be flooded for part of a year). Rates of methane emissions from freshwater
wetlands are also strongly dependent on temperature, and therefore vary seasonally, as
well as daily. Net emissions of N2O and CO also may be affected by this activity, although
these fluxes are not well determined.
A straight-forward methane flux calculation can be based on the area of land flooded, due
to hydroelectric production or other manmade causes, an average daily CH4 emission
coefficient, and the number of days in the year that the area is flooded. Since
measurements of CH4 emissions from freshwater wetlands are so variable, both spatially
and temporally, the area should be divided into groups based on characteristics such as
length of flooding, vegetation type, and latitude. Then appropriate emission coefficients can
be chosen for each group, rather than choosing one emission coefficient for the entire
area of flooding. Table 8 presents average daily CH4 emission rates for natural wetlands,
derived from measured emission rates in field experiments, and average CH4 production
periods based on data on monthly mean temperatures and inundation lengths. These rates
and production periods can be used if countries do not have more appropriate estimates.
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LAND USE CHANGE & FORESTRY
Wetland Drainage
Freshwater wetlands are a natural source of CH4, estimated to release 100-200 Tg CH4
(75-150 Tg CH4-C) per year due to anaerobic decomposition of organic material in the
wetland soils (Note: Tg = teragrams, I Tg = IO12 grams = I06 tonnes).57 Destruction of
freshwater wetlands, through drainage or filling, would result in a reduction of CH4
emissions, and an increase in CO2 emissions due to increased oxidation of soil organic
material.58 The magnitude of these effects is largely a function of soil temperature and the
extent of drainage (i.e., the water content of the soil). Also, since dryland soils are a sink
of CH4, drainage and drying of a wetland could eventually result in the wetland area
changing from a source to a sink of CH4.
Loss of wetland area could also affect net N2O and CO fluxes, although both the direction
and magnitude of the effect is highly uncertain. Natural dryland soils are a source of N2O,
believed to emit 9-28 Tg N2O (3-9 Tg N2O-N) annually as a result of nitrification and
denitrification processes.60 This emission estimate is highly uncertain, however, as
emission measurements vary both temporally and spatially by up to an order of magnitude.
Moreover, the measurements are not consistently correlated with what are believed to be
controlling variables such as soil temperature, moisture, and composition, and vegetation
type. Dryland soils both produce and consume CO. Carbon monoxide production,
estimated at 2-32 Tg CO (1-14 Tg CO-C) per year, is an abiotic process due to chemical
oxidation of humus material.61 It is strongly dependent on soil temperature, moisture, and
pH. Destruction of CO is a biological process believed to be due to microorganisms
present in the soil. Carbon monoxide destruction (250-530 Tg CO/yr, or 107-227 Tg CO-
C/yr) increases with increasing temperature, although it is independent of soil surface
temperature (indicating that the process is more active in deeper soil layers) and requires
a minimum soil moisture.62 Desert soils have always been found to be a net source of CO,
as have savanna soils, at least during the hottest parts of the day. CO destruction
outweighs production in humid temperate soils; humid tropical soils are believed to also
be a net sink of CO because of their higher soil moisture and lower soil temperature than
deserts and savannas.
To calculate the reduction of CH4 emissions due to wetland drainage, the area drained is
multiplied by the difference in the average daily CH4 emission rate before and after
draining, and is multiplied by the number of days in a year that the wetland was emitting
CH4 prior to drainage. The number of days of CH4 emissions prior to drainage can be
approximated by using the number of days in the year that the wetland was flooded. To
calculate the increase in CO2 emissions due to this activity, the area drained is multiplied
by the difference in the average annual CO2 emission rate before and after draining. This
assumes that the elevation in CO2 emissions due to drainage continue throughout the
year. However, the length of time over which the elevated CO2 emissions continue is
uncertain — it could be less than a yean it could be greater than a year. The net release
would also depend on the degree to which there was regrowing vegetation, a CO2 sink.
In summary, the difference in CH4 and CO2 emissions before and after drainage will vary
depending on factors such as soil temperature, extent of drainage, and wetland type. Very
little data are available on this subject. A laboratory experiment with materials
representing a fen, a bog, and a swamp found that the reduction in CH4 emissions
increased with increasing drainage, although the magnitude of the reduction varied
between the three types of materials. CH4 emissions from the fen decreased from about
21 mg CH4-C/m2/day (with the water level about 10 cm above the surface) to about 0.8
CH4-C/m2/day (with the water table about 70 cm below the surface); CH4 emissions from
the swamp decreased from about 9 to about 0.6 CH4-C/m2/day; and CH4 emissions from
the bog decreased only slightly, from about 0.7 to about 0.6 mg CH4-C/m /day. CO2
emissions from all three materials were about 0.08 mg CO2-C/m /day (with the water
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LAND USE CHANGE & FORESTRY
level about 10 cm above the surface), and increased to about 2 mg CO2-C/m /day (with
the water table about 70 cm below the surface.
The direction and magnitude of the effects on these gases are highly uncertain and
significant advances in our understanding of the biological processes as well as
determination of the areal extent of the activities will be required before these
calculations can be adequately accomplished. It may be possible to include methane
calculations associated with land flooding in early refinements of the calculations, but the
N2O and CO calculations are more difficult and as yet of uncertain importance.
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5.4 Tables
TABLE 5-1
DRY MATTER IN ABOVEGROUND BIOMASS IN TROPICAL FORESTS
(tons dm/hectare)
Closed Forests
Open Forests
Broadleaf
Conifer
Undisturbed Logged Unproductive Undisturbed Logged Unproductive Productive Unproductive
America
230
190
ISO
ISO
60
60
60
Africa
Asia
300
300
240
ISO
185
230
130
160
60
135
no
130
36
61
16
20
Volume-based estimates derived from a variety of sources. Recent revised estimates for aboveground biomass in undisturbed closed
broadleaf forests were taken from Brown and Lugo (1992) for Tropical America, Brown et al. (in press) for Asia and Brown (1993) for
Africa. Corresponding values for logged and unproductive forests were derived on the basis of the ratios of these biomass densities to the
rfomass density for undisturbed forests as reported in Brown et al. (1989). For closed conifer forests, stemwood biomass/hectare was taken
rom Brown and Lugo (1984) and multiplied by more recent expansion factors for undisturbed, logged and unproductive categories (1.75,
1.90. and 2.0 respectively) from Brown et al. (1989). Values for open forests were taken from Brown and Lugo (1984) and multiplied by
).77 to obtain the aboveground portion only.
iNOlC.
Estimates based on destructive sampling involve direct measurements (weighing) of biomass harvested from an experimental site. Volume-
iased estimates are generally somewhat lower than those based on destructive sampling, and are derived from FAO data on commercial
wood volumes that are converted to mass units based on average wood densities and ratios of aboveground biomass to commercial biomass
[i.e., expansion factors). There is considerable uncertainty in all regional estimates of biomass densities of tropical forests. Researchers
agree that there Is a great deal of variability from stand to stand and among subreglons within large regions. For example, Brown and Lugo
(1992) report biomass estimates ranging from 166 to 3321 dm/ha for dense Amazonian forests.
There are also some differences in the way different experts interpret the available data to produce averages. Fearnside (1993) has
produced somewhat higher average estimates of aboveground biomass for the Brazilian Amazon than those of Brown and Lugo (1992) His
estimates are for:
Average for Brazilian
Amazon
(t dm/ha)
Forests Actually Cleared in
1990 in Brazilian Amazon
(t dm/ha)
Undisturbed forests
308
291
Logged forests
271
Fearnside (1992) and Brown and Lugo (1992) discuss in detail a number possible explanations for the differences in results.
TABLE 5-2
DRY MATTER IN ABOVEGROUND BIOMASS IN TEMPERATE AND BOREAL FORESTS
(tons dm/hectare)
Primary
Secondary
Temperate Forests
Evergreen
295
220
Deciduous
250
175
Boreal Forests
165
120
5.32
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LAND USE CHANGE & FORESTRY
Source
Primary forest estimates from Whittaker and Likens (1973); secondary forest estimates from Houghton et al.
(1983). Total biomass estimates were converted to aboyeground biomass by multiplying by 0.83 (Leith and
Whittaker, 1975). Alternate estimates of aboveground biomass per hectare, by country, for coniferous
species and non-coniferous species, can be derived using statistics provided in ECE/FAO (1985). Data are
provided for 22 countries.
TABLE 5-3
CARBON IN SOILS IN TROPICAL FORESTS
(tons carbon/hectare)
America
Africa
Asia
Moist
115
115
115
Seasonal
100
100
100
Source:
Post, W.M., et al., 1982.
Note:
The forest categories presented here are different from those presented in Tables
the values for moist and seasonal forests presented above can be used for both clo
(broadleaved and coniferous); the values for dry forests presented above can be us
Dry
60
60
60
and 2. The average of
set) forest types
ed for open forests.
TABLE 5-4
CARBON IN SOILS IN TEMPERATE AND BOREAL FORESTS
(tons carbon/hectare)
Primary
Secondary
Temperate Forests
.Evergreen
134
120
Deciduous
134
120
Boreal Forests
206
185
Source: Schlesinger, 1977, as cited in Houghton etal., 1983; and Houghton et al., 1987.
Note: Alternate values for soil carbon in tropical, temperate, and borjial forests, by continent, are available
in Zinke et al. (1984). However, care must be taken when choosing appropriate soil carbon values in Zinke
et al. (1984). Ecosystem types in this reference may not match the ecosystem types for which clearing data
and biomass estimates are available.
PART 2
5.33
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LAND USE CHANGE & FORESTRY
TABLE 5-5
ANNUAL AVERAGE ABOVEGROUND BIOMASS UPTAKE BY NATURAL REGENERATION
c dm/ha
Region
Tropical
Temperate
Boreal
America
Africa
Asia
Evergreen
Deciduous
Forest Types
Closed Forests
0-20 Years
8.0
II
II
0-20 Years
7.5
S.S
4.0
20- 100 Years
0.9
1.0
1.0
1.8
1.4
I.I
Open Forests
4.0
4.0
4.0
{?<&:;*'&?$"?' l'WC^-'.;--',
£•$&&• '"«!;¥&
'•;<•, W.'-ft*??*.1 'fe-ifjV'"
20- 100 Years
0.25
0.25
0.25
Note Growth rates are derived by assuming that tropical forests regrow to 70% of undisturbed forest biomass ana temperate ana
boreal forests regrow to S0% of undisturbed forest biomass in the first twenty years. All forests are assumed to regrow to 100% of
undisturbed forest biomass in 100 years. Undisturbed forest biomass values are from Tables 1 and 2. For tropical forests, assumptions
on the rates of growth in different time periods are derived from Brown and Lugo, 1990. Assumptions for temperate and boreal
forests are based on Houghton et al.. 1983. and Houghton et al., 1987.
5.34
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LAND USE CHANGE & FORESTRY
TABLE 5-6
AVERAGE ANNUAL ACCUMULATION OF DRY MATTER AS
BIOMASS IN PLANTATIONS
Forest Type
Annual Increment in Biomass
(tons dm/hectare/year)
Tropical
Acacia spp.
Eucalyptus spp.
Tectono grandis
Pinus spp.
Pinus caribaea
Mixed Hardwoods
Mixed Fast-Growing Hardwoods
Mixed Softwoods
15.0
14.5
8.0
11.5
10.0
6.8
12.5
14.5
Temperate
Douglas fir
Loblolly pine
6.0
4.0
Sources: Derived from Brown et al., 1986.
Farnum etal., 1983
Note:
These are average accumulation rates over expected plantation lifetimes:
actual rates will vary depending on the age of the plantation. The data for
the temperate species are based on measurements in the U.S. Data on
other species, and from other regions, should be supplied by individual
countries (as available). Additional temperate estimates by species and by
country can be derived from data in ECE/FAO (1985), assuming that
country averages of net annual increment for managed and unmanaged
stands are reasonable approximations for plantations.
TABLE S-7
EMISSION RATIOS FOR OPEN BURNING OF CLEARED
FORESTS
Compound
Ratios
CH4
CO
N20
NOX
0.012 (0X109-0.015) '
0.06 (0.04-0.08) 2
0.007 (0.005 - 0.009) •
0.121 (0.094-0.148)'
Sources: ' Delmas, 1993
2Lacaux, 1993
3 Crutzen and Andreae, 1990
Note:
Ratios for carbon compounds, i.e., CH4 and CO, are mass of carbon
compound released (in units of C) relative to mass of total carbon
released from burning. Those for the nitrogen compounds are
expressed as the ratios of emission (in units of N) relative to total
nitrogen released from the fuel.
PART 2
5.35
-------
LAND USE CHANGE & FORESTRY
TABLE 5-8
AVERAGE METHANE EMISSIONS AND PODUCTION PERIODS OF NATURAL WETLANDS
Wetland Categories
Bogs
Fens
Swamps
Marshes
Floodplains
Lakes
Emission Rate
(mg CH^C/rnVday)
II
(1-38)
60
(21-162)
63
(43-84)
189
(103-299)
75
(37-150)
32
(13-67)
Production Period
(days)
178
169
274
249
122
365
Source: Aselmann and Crutzen, 1989.
Noter Average daily emission rates are derived from measured emission rates in field experiments
(the range in measured emission rates is in parentheses after the average), and average production
periods are based on monthly mean temperature data and lengths of inundation.
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Whittaker, R.H., and G.E. Likens. 1973. Carbon in the biota. In: Woodwell, G.M., and E.V.
Pecan (eds.). Carbon and the Biosphere. U.S. Atomic Energy Commission, Symposium Series
30. National Technical Information Service, Springfield, VA, USA. pp. 281-302.
Whittaker, R.H., and G.E. Likens. 1975. The biosphere and Man. In: Lieth, H., and R.H.
Whittaker (eds.). Primary Productivity of the Biosphere. Springer-Verlag, New York. pp. 305-
328.
Whittaker, R.H. 1975. Communities and Ecosystems. Macmillan, New York.
Zinke, P.J., A.G. Stangenberger, W.M. Post, W.R. Emanuel, and J.S. Olson. 1984. Worldwide
Organic Soil Carbon and Nitrogen Data. ORNUTM-8857. Oak Ridge National Laboratory,
Oak Ridge, Tennessee.
5.6 Endnotes
I. "Indirect" greenhouse gases here refers to gases which contribute to the chemical
formation or destruction of ozone (O3) in the atmosphere. As O3 is an important
greenhouse gas, the gases which create or destroy it affect the radiative forcing of the
atmosphere indirectly.
2. IPCC (1990). Note fluxes of CO2 are generally expressed in scientific literature as mass
of carbon per year. The mass is in I015 grams carbon as CO2 (pg COrC).
3. Brown et al., 1986
4. Houghton etal, 1987; Melillo etal., 1988
5. See, for example, Tans et al., 1990, IPCC, 1992 and Kauppi et al., 1992.
6. Delayed releases of non-CO2 trace gases are an important research issue. These
releases may be important, but are currently too uncertain to be included in calculations.
7. Houghton, 1991
8. For example, see Moore etal., 1981, Houghton etal.. 1983, Houghton etal., 1986,
Mellilo et al., 1988, and Emanuel et al., in press.
9. Similarly, current land-use will affect future fluxes of carbon dioxide.
10. This is what the term "deforestation" should mean and it is frequently accompanied by
burning.
11. Abandonned lands which are regrowing naturally may be cleared again. In this case,
they should shift again to cleared lands, probably with a lower value for preclearing
biomass density.
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12. Conversion of tropical forests to pasture and cropland accounts for the largest share
of global forest clearing and resulting CO2 emissions, the discussion and default
information focus on this case, as it is most important that national inventories account for
the largest contributions to emissions first. Forest clearing for other purposes (e.g., urban
development) should also be accounted for to the extent possible, as less default
information is provided for these cases, this will require national experts to provide input
data.
13. For instance, see Houghton, 1991; Crutzen and Andreae, 1990. The decay rates
generally depend on several factors including humidity, temperature, and litter quality.
14. This issue is discussed in the section on possible refinements to the methodology.
15. The portion of burned carbon that remains on the ground as charcoal is highly
uncertain. Measurements following burning of a forest for conversion to pasture indicate
that 2.6% of the pre-burn aboveground carbon, or 8.5% of the burned carbon, is
converted to charcoal (Fearnside et al., I990a). according to Fearnside (I990b), pastures
are typically burned two to three times over about a 10-year period. Under such a
scenario, the latter burns probably result in combustion of some of the charcoal formed
during the first burn and formation of additional charcoal. Fearnside (I990b) estimates that
about 4.6% of the pre-burn aboveground carbon, or 10.1% of the burned carbon, is
converted to charcoal under this scenario. Based on results of observations in the
Brazilian Amazon (Fearnside, I990a) and in a Florida pine forest (Comery, 1981), Crutzen
and Andreae (1990) adopt charcoal values of 5% of the pre-burn aboveground carbon and
10% of the burned carbon for clearing in the tropics.
16. It is important to note, as discussed in the introduction to this document, that there is
an intentional double counting of carbon emitted from combustion. CO2 is calculated
based on the assumption that all carbon in fuel is emitted as CO2. however, methods are
also provided to estimate portions of total carbon which are emitted as CH4 and CO. the
reasons for this double counting are discussed in the introduction.
17. On average about-25-50% of the soil carbon, as discussed in Houghton etal., 1983.
18. For simplicity of explanation, the discussion refers to the inventory year as though data
for a single year were the desired input. However, as noted in the overview, for land use
and forestry emissions estimates, it is recommended that data averaged over three years
be used in place of annual data.
19. Defining regions will require balancing data availability, biological and land-use
heterogeneity, and practical considerations such as the available time and effort.
furthermore, developing adequate land-use and land-use change data is a central issue. In
the case of land-clearing, this data would likely be obtained from a combination of
departments of land management, agriculture, and forestry, this data will come at a variety
of scales in time and space, and producing consistent records will be a challenging task to
all countries, in time, new internationally-based remote sensing programs could greatly
facilitate this task; this is discussed in the technical appendix.
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20. As in the case of land-use data, developing appropriate biomass data is a challenging
task, in theory, it can be obtained directly by destructive sampling but this is unrealistic for
adequate coverage for even small countries, an alternative approach is to use inventory or
production data where one exploits volumetric data on marketable timber and uses a
sequence of expansion factors to convert this to total stemwood, total above ground
biomass volume, and total biomass volume, see the references to Tables I and 2.
21. Houghton et al., 1987.
22. For instance, see Houghton, 1991; Crutzen and Andreae, 1990.
23. Note also that the smoldering that produces charcoal and ash also forms other
important greenhouse gases such as CH4 and N2O. for instance, see Fearnside et al.,
I990a and Crutzen and Andreae, 1990.
24. We are also ignoring the carbon flux associated with CO formation during combustion
which accounts for about 8% of the burned carbon.
25. The range most cited is (0.43 - 0.58) hence some suggest that 0.5 as a more
appropriate default assumption.
26. See Houghton 1991; Crutzen and Andreae 1990 for discussion of this issue.
27. In temperate systems, in fact, most of the soil carbon is released in the first 5 years
after clearing; the rest is released over the next 20 years, see Houghton, 1991.
28. See Houghton et al., 1983.
29. The issue of soil carbon change following land-clearing in the tropics is an important
research topic, there is evidence that there is a rapid soil carbon loss follow by soil carbon
accumulation depending upon the type of grasses that are used in pasture, (e.g., Fearnside,
I960, 1986; Buschbacher, 1984; Cerri etal., 1988; and Lugo etal., 1986); and clear cutting
of tropical forests does not appear to release soil carbon (Keller et al., !986).The current
status of the science, however, may not provide an adequate basis for recommending
values for inclusion of this aspect of the carbon cycle in emissions calculations at this time.
further research needs to be done.
30. The emission ratios used in this section are derived from Crutzen and Andreae (1990),
and Delmas, 1993, as presented in the table, they are based on measurements in a wide
variety of fires, including forest and savanna fires in the tropics and laboratory fires using
grasses and agricultural wastes as fuel. Research will need to be conducted in the future to
determine if more specific emission ratios, e.g., specific to forest fires, can be obtained.
also, emission ratios vary significantly between the flaming and smoldering phases of a fire.
coj, n2o, and nox are mainly emitted in the flaming stage, while CH4 and CO are mainly
emitted during the smoldering stage (lobert et al., 1990). The relative importance of these
two stages will vary between fires in different ecosystems and under different climatic
conditions, and so the emission ratios will vary. As inventory methodologies are refined,
emission ratios should be chosen to represent as closely as possible the ecosystem type
being burned, as well as the characteristics of the fire.
31. Emissions inventory developers are encouraged to provide estimates of uncertainty
along with these best estimate values where possible, or to provide some expression of
the level of confidence associated with various point estimates provided in the inventory.
procedures for reporting this uncertainty or confidence information are discussed in
Volume 1: Reporting Instructions.
32. Crutzen and Andreae, 1990.
33. From Crutzen and Andreae, 1990.
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34. There is an inconsistency in the methodology in the treatment of the full molecular
weight of NOX. In fossil energy and industry discussions NOX is expressed as though all of
the N were in the form of NO2. In biomass burning literature, (e.g., Crutzen and Andreae,
1990) NOX is often discussed as though the emissions were in the form of NO. Therefore,
the biomass burning discussions in these guidelines convert NOX-N to full weight using the
conversion factor (30/14) for no. all other references to NOX are based on the full weight
of NO2 (i.e., the conversion factor from NOX-N would be 46/14).
35. See Houghton et al., 1983.
36. Post, etal., 1982.
37. See Houghton et al., 1983.
38. Values given in Table 5 assume linear regrowth of aboveground biomass in each of the
two time periods (0-20 years and 21-100 years). In reality, as shown in Brown and Lugo
1990, the regrowth is closer to an exponential function, the calculation could be improved
by breaking the 20 year period into finer segments, assuming availability of data, to
determine a weighted average.
39. The re-accumulation of carbon in soils is not linear. Generally accumulation occurs
quickly in initial stages of regrowth and slows as regrowth slows.
40. Plantations are forest stands that have been established artificially, to produce a forest
product "crop". They are either on lands that previously have not supported forests for
more than SO years (afforestation), or on lands that have supported forests within the last
50 years and where the original crop has been replaced with a different one
(reforestation) (Brown et al., 1986).
41. There is one omission in this accounting which may be important for some countries.
If plantations are established on previously non-forest lands, there may be a long term
accumulation of carbon in the soil as a result of the land use change, this would not
normally be picked up in the simple managed forest calculations. It could be added if
national experts have-detailed data on the pre-plantation land uses, The soil carbon
contents and rates of accumulation, etc.
42. In addition, logging provides access to previously unaccessible forests, thereby
facilitating degradation of forests by activities such as fuelwood collection, habitation, and
agricultural activity.
43. Volume to mass conversions and expansion factors are taken from Brown et al., 1989
which reports on tropical forests, however, The values are in the range of those reported
by ECE/FAO, 1985, for temperate forests.
43. Holt and Spain, 1986
44. e.g. Anderson et al., 1988 and Levine et al., 1988
45. Luizao etal., 1989
46. Bowden and Bormann, 1986
47. Keller et al., 1986
48. Luizao etal., 1989and Matson etal., 1990
49. Keller et al., 1990; Scharffe et al., 1990.
50. See, for example, Fearnside, 1980, 1986; Bushbacher, 1984; Cerri et al., 1988; and
Lugo et al., 1986. Keller et al. (1986) indicate that clearcucting of tropical forests does not
appear to release soil carbon.
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S[. Hosier etal. 1991
52. Seller and CrutzenK 1980
53. In fact, prescribed burning may actually result in a net accumulation of carbon when
the natural ffre that would have occurred (had prescribed burning not taken place) is
included in the accounting of emissions.
54. Actually, following the first clearing (Le., clearing of primary forests), the forest hiomass
may not recover fully to its original density during the fallow period, but instead reaches a
slTgjhtly reduced leve), referred to as a secondary forest, after this point, however, clearing
(of a secondary forest) is balanced by recovery (to a secondary forest), and netCOj
emissions over time are zero.
55, See Myers (1989) and Houghton {1991)
56, Generally, shifting cultivation is practiced in fallow forests, since the least dense and
most accessible forest areas are most susceptible co this form of clearing. Abaveground
biomass density estimates for fallow forests are highly uncertain, and vary significantly both
within and among countries because of varying ecosystem types as well as varying intervals
between clearings. As a rough estimate* 50% the biomass estimates fjor unproductive
forests can be used (see Table 6-1 for regional estimates In. units of carjbptvper hectare),
Biomass carbon densities for other forest types, e^j., undisturbed forests, should of course
be used if more appropriate in specific cases.
57. Cicerone and Greenland, 1988 .,'.'.'.'
58. Moore and Knowles, 1989 ~ '.'",'
59, For example, see Harriss et a!., 1982
SO. Seiler and Conrad, 1987 ~' \_ _
6L Seller and Conrad, 1987 " ; ' = =-
62, Seifer and Conrad, 1987 '
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T5 TECHNICAL APPENDIX:
DEFORESTATION DATA
Data on rates of deforestation1 are essential for calculating the fluxes of carbon dioxide
and other trace gases between terrestrial systems and the atmosphere. When arranged on
a country-by-country basis, these data provide the forcing function for computation of
country-specific emissions from forest clearing. Recogni::ing that such data sets are not yet
available for many countries with the accuracy needed for these computations, this
technical appendix provides suggestions for utilizing the available global and national
sources of data, while bringing new or better sources of information into the calculations
when and where they are available.
T5.I Food and Agriculture Organization (FAO)
Published Data
Currently, the most comprehensive international source1 of data on rates of deforestation
broken down to the country level is maintained by the FAO in the following forms:
I Source data, preferably in the form of a time series, collected in cooperation with
member countries (i.e., without standardization) including data on: forest cover,
ecofloristic zone and sub-national boundaries, biomass, plantations and conservation,
collected and compiled in the form of a geographic information system.
2 Standardized estimates of forest cover, rate of deforestation, afforestation, and
biomass/ha at the country level. Standardization is done by FAO because of variations
from country to country in:
• -the definitions of "forest", "deforestation" and "afforestation"; and
• -the reference years for forest cover and deforestation measurements.
The standardization is intended to bring country data to common definitions of
forest cover and reference data, and to make the country information useful for
regional and global studies. The basis for standardization is adjustment functions by
ecological zones based on time-series data on forest cover of countries.
3 Data from a global sample survey of forest cover slate and change during 1980 and
1990 based on a limited sample of high resolution satellite images using common
definitions and measurement techniques. The main aim of this survey is to calibrate
regional and global estimates and provide comprehensive information on various
types of on-going forest cover changes, in the form of change matrices (1980 and
1990). It should be noted that the sample survey is not intended to check or replace
country estimates, but only to provide reliable estimates (i.e., with standard error) of
forests cover and rate of change at regional/global fevels. This is being done taking
into account the inherent limitations of aggregating heterogeneous country data at
regional/global levels.
This appendix is limited to discussion of current and future international sources
of data on rates of deforestation at the national level. It is understood, however, that
other types of input data are also key sources of uncertainty in calculation and are also the
subject of a great deal of ongoing activity. This includes other types of land use change and
land cover data as well as more detailed information on growth rates and biomass
densities for different types of forests and other ecosystems.
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The results of these data collection and analysis efforts are provided in a series of
publications produced by the FAO. These data can be used to construct national input
data for calculating COj from deforestation. This should be useful to many countries at
least as a point of comparison with locally available data sources, and may be used to
provide a first order estimate of national emissions if desired by national experts.
The FAO Forest Assessment produced in the early 1980s (FAO/UNEP 1981, Lanly r982)
provides a first-order estimate of deforestation rates worldwide. These data produced on
a country basts can be used as a baseline land use rate. An interim assessment (FAO 1988)
provided deforestation rates by country for the period 1981-85. A 1990 assessment has
been recently published (FAO I993)» which provides estimates of deforestation rates by
country for the period 1981-1990. Thus, some estimates of current and historic rates of
deforestation on a country basis can be obtained from these published reports. More
detailed information, including sub-national data, can be obtained by contacting the FAO
dtrecdy,
It should be noted, however, that there have been controversies and disagreements
regarding FAO estimates of national deforestation rates at times. In some cases where
national experts have developed significantly more detailed approaches for their own
countries, results have been found to be significantly different than die published FAO
estimates. (See, for example, Fearnside, et al, f990b for Brazil). Any internationally
provided data should be reviewed carefully by national experts if they are used as a basis
for emissions Inventory estimates.
Some countries have well-developed estimates of deforestation, based on very good
measurements, which provide more detail than is available from the FAO assessments
(eg,, Arbhabhirama et al. 1987,1NPE 1992). Where detailed national studies exist for die
earty 1990s they may be a preferred data source for experts preparing national
Inventories. FAO data may nonetheless be useful for comparison purposes. The choice of
input data Is always ultimately a decision of the national experts.
Lack of consistent time-series data at national level is considered by FAO staff to be die
most critical problem in estimating die deforestation rate. Variation in definitions and
measurement techniques from country to country is another problem in making regional
and global estimates. FAO has initiated a comprehensive programme for capacity building
to forest resources assessment by mobilizing technical and economic cooperation among
member countries and among concerned regional and global agencies as follow-up to
recommendations of UNCED Agenda 21: Programme Area D.
T5.2 Ongoing Data Efforts
The lack of a comprehensive data set on deforestation rates is a critical problem. The
development of such data sets remains one of the priorities for the 1PCC process in the
coming years (IPCC 1992). Methods using high resolution remote sensing rn conjunction
wldt geographic information systems appear most promising. The International
Geosphere-Biosphere Programme's Data Information System 0GBP-DIS) is serving as a
central focal point to collect and disseminate information about the various ongoing
activities and data sets dealing with land use and changes in land cover. The IGBP-DIS is
located in Paris, France (Tel: 33-1-4427-6168, Fax: 33-1-4427-6171).
Experts from around the world have begun to build the scientific, technical, and
procedural underpinnings of such a system. The World Forest Watch Meeting held in Sao
Jose dos Campos, Brazil (June 1992) provided a high-level international forum for the
assessment of current approaches to satellite-based forest monitoring. This meeting also
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served as a basis for forwarding recommendations from the technical and scientific
communities to the policy makers and government leaden; at UNCED*
A variety of international participants were represented at the World Forest Watch
Conference. The conference concluded that significant technical and methodological
advancements have been made in recent years, and they are now sufficient for proceeding
with an observation system which could satisfy both scientific and national-level forest
management requirements. A priority action now is to establish a fully functional,
permanent monitoring system. The system would support national forest management,
global change science, and international policy information needs, such as those of the
IPCC.
The current research and development being carried out in laboratories and research
centers around the world has shown that it is now feasible; to acquire repetitive satellite
data sets over very large areas, and that the information derived from such data sets can
form the core of a global forest monitoring program. The International Space Year World
Forest Watch Conference has recently provided illustrations that space observation
technology and the community of users are ready for regional and global applications.
Progress made on two forest monitoring projects is worth noting in this respect.
I The National Institute for Space Research (INPE) of i:he Secretariat of Science and
Technology of the Presidency of the Republic of Bra2:il has made surveys of the entire
Legal Amazon (about 5 million square kilometers) using LandSat images. This survey
was first conducted in 1978 (with 1977 and 1979 being used to cover areas covered
by clouds in the 1978 imagery. The studies were repeated in 1988, 1989, 1990 and
1991. These space-based surveys mapped the extent of gross deforestation (i.e.,
without accounting for forest regeneration or the establishment of plantations) in the
portion of the Legal Amazon covered by forest. The ecosystems ranged from dense
tropical forest to thick savannas (cerradao) with a total surface area between 3.9 and
4 million square kilometers. The 1978 survey used 232 Land Sat MSS black and white
images based on channels 5 and 7 at a scale of 1:250,000. The more recent studies
used 229 LandSat TM images annually in a color composite of channels 3,4 and 5 at a
scale of 1:250,000.
2 In 1990 NASA, in conjunction with the United States Environmental Protection
Agency and the U.S. Geological Survey, began a prototype procedure for using large
amounts of high resolution satellite imagery to map the rate of tropical deforestation.
This activity, the LandSat Pathfinder Project, builds on experience gained during a
proof-of-concept exercise as part of NASA's contribution to the International Space
Year/World Forest Watch Project. It focused initially on the Brazilian Amazon, and
has now been expanded as part of NASA's Earth Observing System activities to
cover other regions of the humid tropical forests.
This project has succeeded in demonstrating how to develop wall-to-wall maps of
forest conversion and re-growth. The project is now in the process of extending its
initial proof-of-concept to a large-area experiment across Central Africa, Southeast
Asia and the entire Amazon Basin. The project is acquiring several thousand LandSat
scenes at three points in time — mid 1970s, mid 1980s, and mid 1990s — to compile a
comprehensive inventory of deforestation and secondary growth (regrowth of
forests on land cleared and subsequently abandoned) to support global carbon cycle
models. Methodology and procedures have been identified. Although this exercise is
being implemented for most of the tropics, it is not an operational global program. In
principle it will provide an initial large-scale prototype of an operation program.
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The use of geographic information system technology is crucial to die project, as it
provides the overall framework upon which the raw satellite data can be synthesized
with other cartographic, numerical, and geographical data for scientific research and
national forestry management As its name implies, this project is exploratory, but it
could readily be expanded to form the nucleus of a global scale operational program.
These two projects demonstrate the feasibility of developing a global tropical forest
information system to support an operational tropical forest monitoring program. High
resolution satellite data from LandSat or Spot satellites are being used to provide digital
maps of deforestation.
High resolution data from the LandSat series of earth observation satellites can be
employed to make regular measurements of deforestation. Urge amounts of these data
exist in national and foreign archives, dating back approximately 20 years. This satellite
data system has been perfected over years of development (5 satellites have been
launched) and it is expected to be an operational system into the next century (LandSat 6
is ready for launch, 7 and 8 are being designed). This system is complemented by the
French SPOT satellites. Thus, a continuous and consistent source of data is available upon
which a high resolution, fine-scale (1:250,000 scale mapping) information system could be
developed.
An operational forest monitoring using high resolution data such as that provided by
LandSat and SPOT could provide wall-to-wall mapping for the entire tropical zone. The
approach would be as follows:
• An initial mapping effort would define where and how much deforestation exists in
die tropical forests (a baseline assessment). The stratification of forest types and
critical regions could be enhanced by the use of coarse resolution information from
AVHRR.
• Acquisition of LandSat and/or SPOT imagery can be coordinated regularly ever/ 3-5
years to obtain cloud-free coverage systematically throughout the tropics. The best
way to achieve tfiis is to rely heavily on the foreign ground stations. For example,
from die LandSat routine and complete coverage for die Amazon Basin and
Southeast Asia is possible from several foreign ground receiving stations in these
regions. As a rule diese stations regularly collect data from every orbital pass within
the line-of-sight radius of their antenna. For regions, such as central Africa where no
ground station exits, programmed acquisitions from die satellite are possible.
» The imagery are analyzed for deforestation using a methodology analogous to that
developed by die LandSat Pathfinder Project, where a simple delineation of the
boundary between intact forest and cleared areas is recorded into a geographic
information system. Areas of secondary growth would also be delineated. Subsequent
years are compared to die baseline and die increment of new deforestation and
secondary growth is recorded. The resulting data set provides a 1:250,000 to
1:500,000 scale map of deforestation at a regular repeat interval, and from diis a rate
of deforestation is derived.
• These geographically-referenced measurements can directly support the
implementation of die (PCC national inventory methodology, which requires a time
series of historic forest clearing data, and would require updating at periodic
intervals. The proposed accurate and precise deforestation data set would be an
important asset to national experts working to implement the IPCC methodology for
national emissions and removals from land use change.
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An accuracy assessment effort will need to be put into place to define and track the
measurement variance and error. This component will need to determine accuracy
with respect to: (a) variance due to positional accuracy (i.e., the mapping precision)
and (b) the variance associated with image interpretation.
An effort focused on establishing in-country cooperation will be necessary. Such
cooperation fulfills several ancillary but vital objectives: (a) it builds a process of
national acceptance of the methods and results through active involvement, (b) it
provides a mechanism for technology transfer and training for eventual
implementation of remotely sensed-based national inventories, (c) it facilitates
logistical coordination of the field component, (d) it provides direct cooperation at
various foreign ground stations, and (e) it enables cooperation with national and
regional experts in the interpretation of imagery.
T5.3 Summary
Tropical deforestation and carbon emissions are important: components of both science
and policy. Yet, in spite of the growing need for precise estimates of deforestation to
support both international policy and basic research, an operational program of
measurement, monitoring and mapping has yet to be developed. Comprehensive and
systematic information on the extent of forest and forest loss is not available on a global
basis. The latest IPCC Assessment Report, for example, considers the rate of tropical
deforestation to be one of the key unknowns in global climate change assessment. Any
lasting and effective implementation of a global system of national emission inventories to
support the IPCC and other international processes will require a new, concerted effort
to measure and map tropical deforestation, and develop the database necessary for other
important components of the calculations. These measurements of deforestation from
high resolution satellite remote sensing can also support the UN/FAO Forest Assessment
by providing quantitative and spatially comprehensive measures of changes in forest cover
for the tropics.
This Technical Appendix summarizes the most comprehensive current data source for
tropical deforestation information, and discusses ongoing efforts to improve on this data
via analysis of remote sensing images. Ideally, each country would like to have data on their
land use changes and associated trace gas emissions and uptake over the past 40 to 50
years so that their estimates of current annual net emissions would include delayed and
continuous emissions and uptake due to activities that occurred in prior years. Since this is
not the case for many countries, the methodology described has made simplifying
assumptions in order to treat the effects of past land use activities on current emissions.
This appendix provides some perspective on the available international sources for dealing
with one key data gap — data on rates of forest clearing over time.
In future editions of the Guidelines, it may be possible to include more information on data
available to assist national experts as a result of some of the ongoing efforts described in
this version. It may also be possible and desirable to provide similar discussion of a range
of other international data collection efforts which may assist national experts in refining
other key data driven uncertainties in the national estimate:; of emissions and removals
from land use change and forestry.
In the meantime, it is recommended that countries continue efforts to collect historical
records of land use change and develop systems of tracking land use through time so that
as the methodology is further refined, the land use change time series needed to account
better for emissions and uptake of carbon dioxide and other trace gases are available.
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CHAPTER 6
METHANE EMISSIONS
FROM WASTE
PART 2
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WASTfc
6 METHANE EMISSIONS FROM WASTE
Disposal and treatment of industrial and municipal wastes can produce emissions of most
of the important greenhouse gases (GHG). Solid wastes ca,n be disposed of through
landfilling, recycling, incineration, or waste to energy. GHG emissions from waste to
energy, where waste material is used directly as fuel or converted into a fuel, should be
calculated and reported under Energy - Chapter 2. Liquid wastes can be dealt with
through various forms of wastewater treatment. In addition, sludge from wastewater can
be incinerated. This chapter will deal with emissions resulting from landfilling of solid
waste, treatment of liquid wastes, and waste incineration.
The most important gas produced in this source category is methane. Significant amounts
of the annual global methane produced and released into the atmosphere are a by-product
of the anaerobic decomposition of man-made waste. Two major sources of this type of
methane production are landfills and wastewater treatment. In each case, the
methanogenic bacteria break down organic matter in the waste to produce methane.
These sources are treated in detail in later sections of this chapter.
Landfilling of solid waste represents the major form of solid waste disposal in the
industrialized world. (OECD, 1993) In addition to CH4, landfills also can produce
substantial amounts of CO2 and non-methane volatile organic compounds (NMVOCs).
CO2 is primarily from decomposition of organic material derived from biomass sources
(e.g. crops, forests) which are regrown on an annual basis. Hence, these are not treated as
net emissions from waste in the IPCC methodology. If biomass raw materials are being
unsustainably produced, the net CO2 release should be calculated and reported under the
Agriculture or Land Use Change and Forestry sections.
The process of wastewater treatment produces NMVOCs as well as CH4. (Bouscaren,
1992) Wastewater treatment is also now being studied as a source of N2O. Norway
(IPCC, 1993) and Japan (Kyosai and Mizuochi, 1993) have documented N2O production
from their sewage treatment processes. Future evaluation of ongoing research will give an
indication of the importance of this source.
Waste incineration, like all combustion, can produce CO2, CH4, CO, NOX, N2O and
NMVOCs. No detailed methodologies are provided for this source category. Instead, the
section on waste incineration later in this chapter provide:; references to other major
methods documents already available for some gases. For CH4 and N2O it is only possible
to report preliminary estimates and research results at this time. Further studies are
needed to give more information about GHG emissions from this source category.
The sections in this chapter dealing with landfills and wastewater treatment give
background information on the source, a description of the methodology to estimate
methane production only, and uncertainties associated with estimating emissions. This is
consistent with the initial priorities under the IPCC methodology programme. National
experts are encouraged to report any other relevant emissions for which data are
available, along with documentation of methods used. This will greatly assist in the
development of more complete methods for future editions of IPCC guidelines. For
information on estimation procedures and emissions factors for other GHGs which are
currently not provided in this chapter, experts should consult extensive existing literature
developed by other emissions inventory programmes. Some key examples are:
• CORINAIR Default Emissions Handbook (Bouscaren, 1992);
• U.S. EPA's Compilation of Air Pollutant Emissions Factors (AP-42) (US EPA, 1985)
and Supplement F (AP-42) (US EPA, I993a);
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Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions inventory
(Stockton and Steiiing, 1985);
Air Emissions from Municipal Solid Waste Landfills - Background Information for
Proposed Standards and Guidelines (US EPA, 1991 a).
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6.1 METHANE EMISSIONS FROM
LANDFILLS
6.1.1 Introduction
Since the early 1980s, it has been recognized that the methane component of landfill gas
can be a local environmental hazard if precautions are not taken to prevent uncontrolled
emissions or migration into surrounding land. Gas can migrate from the landfill either
laterally or by venting to atmosphere, and this can cause vegetation damage and unpleasant
odours at low concentrations, while at higher concentrations the gas may form explosive
mixtures.
More recently, increasing attention has focused on the role of methane in global
atmospheric change. Methane from landfills contributes a significant proportion of annual
global methane emissions, although the estimation is subject to a great deal of uncertainty.
Estimates of global methane emissions from landfills range from 20 to 70 Tg/yr, global
anthropogenic sources emit about 360 Tg/yr, which suggests that landfills may account for
6 to 20% of the total. (IPCC, 1992)
This section will describe the processes that result in landfill gas generation and the factors
which affect the amount of methane produced within landfills. It will then describe
methodologies for estimating methane emissions from landfills. One of these methods is
proposed as a default base method with which all countries can comply. Other methods
are also described as well as some examples from various countries that have applied
them. The section also discusses sources of uncertainty associated with any estimates of
methane emissions from landfills, in particular the availability and quality of data required.
6.1.2 Landfill gas generation
Organic waste within landfills is broken down by bacterial action in a series of stages that
result in the formation of methane, carbon dioxide and further bacterial biomass. In the
initial phase of degradation, organic matter is broken down to small soluble molecules
including a variety of sugars. These are then broken down further to hydrogen, carbon
dioxide, and a range of acids. These acids are then converted to acetic acid which,
together with hydrogen and carbon dioxide, forms the substrate for growth of
methanogenic bacteria.
Landfills are by nature heterogeneous, and all microbiological investigations into landfill
characteristics have shown that there are considerable differences between different
landfills and even different regions within the same landfill (Westlake, 1990). This makes it
very difficult to extrapolate from observations on single landfills to predictions of global
methane emissions. Nevertheless, there are a number of significant factors which influence
the generation of methane and its emission from landfills. A better understanding of these
factors can reduce the uncertainty associated with emissions estimates.
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6.1.3 Factors influencing methane production in
landfills
The factors which influence methane production within landfills have been reviewed
comprehensively elsewhere (eg. Peer el a!., 1993; US EPA, 1992; US EPA, 1991 b; US EPA,
1991 c; Lawson and Alston, 1990; Augenstein and Pacey, 1991), therefore this section will
only provide a brief summary of the most significant factors relating to methane emissions.
Waste management practices
The two main types of waste management practices of concern for CH4 emissions are
open dumping, which is generally practiced in developing regions, and sanitary landfilling,
generally practiced in developed countries and urban areas of developing countries. Both
of these types of waste management can result in- methane production if the waste
contains organic matter.
In open dumping, wastes are disposed of in shallow, open piles, generally only loosely
compacted, and with no provision for control of any pollutants generated, either gas or
leachate. Scavenging by animals and humans can remove much of the biodegradable wastes
therefore reducing substrate availability.
Wastes in open dumps generally decompose aerobically, producing carbon dioxide.
However, there is anecdotal evidence that some methane production can occur
(Thorneloe et al., 1991), but this has not been quantified. Methane from open dumping is
therefore not included in any methodology considerations for global inventories. Bhide et
al (1990) reported biogas recovery from two uncontrolled landfills in Nagpur, India. The
CH4 content of the biogas from one site was 3Q to 40%. This suggests that open dumps
are a source of CH4.
Thorneloe et al. use the same methodology to calculate CH, emissions from open
dumping in non-industrialized countries as from sanitary landfills in industrialized regions.
However, total CH4 emissions are reduced by 50% to account for the differences between
CH, production potential from open dumping and sanitary landfilling. The choice of 50% is
arbitrary and should be updated when additional data are available. This procedure can be
used by national experts at their discretion. Uncertainty due to this source is discussed
later.
Sanitary landfills are designed specifically to receive wastes. Landfill design and
management is becoming increasingly sophisticated in many countries, as the serious
environmental consequences of uncontrolled landfilling are becoming understood. New
landfill design standards in many countries are ensuring that landfills are lined before
receiving waste, and also that there are adequate provisions for the safe control, and
removal where appropriate, of gas and leachate generated. Good waste management
practices ensure that the waste is compacted to minimise use of void space, also that it is
covered both with intermediate daily cover and with an effective cap when final
restoration takes place. The costs associated with these management practices are
encouraging the development of larger landfills to economise on scale, taking in greater
quantities of waste. All of these factors can encourage the rapid development and
maintenance of anaerobic conditions within the landfill, and hence ensure continued
methane production.
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Waste composition
The composition of waste is one of the main factors influencing both the amount and the
extent of methane production within landfills. Municipal solid waste (MSW) contains
significant quantities of degradable organic matter. This can decompose to form acetate
and carbon dioxide as intermediate decomposition products, which are the main
substrates for methanogenic bacteria. Different countries and regions are known to have
MSW with widely differing compositions: wastes from developing countries generally have
a high putrescible content, whereas developed countries, especially in North America,
have very high paper and card content in their MSW. Thus landfills in developing countries
will tend to stabilise within 10-15 years because putrescible material decomposes rapidly,
whereas landfills with a high paper and card content will tend to produce methane for 20
years, or more at a lower rate.
Physical factors
The moisture content of the landfill environment is one of the principal physical factors
influencing landfill gas production. Moisture is essential for cell growth and metabolism,
also for transport of nutrients and bacteria within the landfill. The moisture content of a
landfill will depend on the initial moisture content of the waste, the extent of infiltration
from surface and groundwater sources, and on the amount of water produced during the
decomposition processes.
Temperature will affect the growth rate of the bacteria. Under anaerobic conditions,
landfill temperatures are generally between 25-40°C. These temperatures can be
maintained within the core of the landfill independent of the external temperatures.
Outside of these temperatures, methane production is reduced or can cease altogether.
Optimal pH for methane production is between 6.8 and 7,2. Nutrients that are important
for efficient bacterial growth include sulphur, phosphorous, sodium and calcium. CH4
production rates decrease sharply with pH values "Below-about 6.5 (Zehnder, 1982). When
refuse is buried in landfills, there is often a rapid accumulation of carboxyte acids^thjs
results in a pH decrease and a long time lapse between refuse burial and the onset of CH4
production ranging from months to years.
"The lapsed time preceding the onset of CH4 production in landfills is an important aspect
when considering the management of individual landfills for biogas recovery or emissions
mitigation. The age at which landfills and uncontrolled dumps begin to produce CH4 is of
lesser importance when evaluating global CH4 emissions from MSW management systems.
For estimating global emissions, it is the total CH4 production potential that is more
critical." (Thorneloe, 1993a)
The importance of these physical factors to methane generation can be demonstrated
within controlled laboratory conditions, but the heterogeneity of landfills makes definitive
research very hard under field conditions, and there are limited data available. Therefore
until better global data become available, none of these factors can be taken into
consideration when estimating national or global methane emissions.
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6.1.4Methodologies to estimate methane
emissions from landfills
A number of methods have been used to estimate methane emissions from landfills. These
methods vary widely, not only in the assumptions that they make, but also in their
complexity, and in the amount of data they require for the determinations.
This chapter will deal only with those methods that can be applied to whole regions or
countries. There are some very complex models that are concerned with movement of
methane and other gases through individual landfills; however these models cannot be
applied to landfill populations and therefore will not be considered further here.
Mass balance and theoretical gas yields
methodologies
This is the simplest method for calculating methane emissions from landfills. It is based on
a mass balance approach, and does not incorporate any time factors into the methodology.
The calculation assumes that an instantaneous release of methane takes place from refuse
during the same year that the refuse is landfilled.
Using empirical formulae
At its simplest level, an empirical formula for refuse can be used as the starting point for
estimating yields from waste. If a complete breakdown to carbon, hydrogen and oxygen is
considered, this gives very high and unrealistic levels of methane generation, therefore
some adjustments are necessary because complete breakdown is known not to take place.
EMCON Associates (1981) modified this by using an extended Buswell equation, which
takes other elements into account, and estimated that 53% of the carbon content of
refuse is converted to methane. If microbial biomass as an end product is also taken into
account, then this further reduces the methane generation potential. Polytechnic of East
London (1992) have predicted that this results in the production of 234 m3 of methane
per tonne of wet MSW.
Default methodology: using degradable organic carbon content
A more useful approach is to consider the degradable organic carbon (DOC) content of
MSW, i.e. the organic carbon that is accessible to biochemical decomposition, and to use
this value to calculate the amount of methane released from the MSW. This is the
approach taken by Bingemer and Crutzen (1987), who segregated the world into four
economic regions, and applied different values of DOC to the waste generated within each
of these regions. As a simple and robust method, this is currently the most widely
accessible default methodology for calculating country-specific emissions of methane from
landfills, since it requires the least amount of data to perform the calculations, and it can
be modified and refined as the amount of data available for each country increases.
The four regions derived by Bingemer and Crutzen (1987) were: US, Canada and
Australia; other OECD; USSR and Eastern Europe; and developing countries. In their
assessment, they determined how much MSW was produced for each region, and how
much of that MSW was degradable organic carbon.
The percent degradable organic content (DOC) is based on the composition of waste.
The percent of DOC can be calculated from a weighted average of the carbon content of
various components of the waste stream. Bingemer and Crutzen (1987) collected data for
the various global regions considered in the study. No data were available for the USSR or
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Eastern Europe or for some developing countries, so these values had to be
approximated. These data were updated by OECD (1991) using more recent data from
OECD (1989) where available. The data presented to OECD (1991) are summarized in
Table 6-1. It is highly recommended, however, for countries where the composition of the
fractions in the waste stream are known, that these be combined with a knowledge of the
carbon content of these various fractions to produce a country-specific value for DOC.
The determination of annual methane emissions for each country or region can then be
calculated from Equation 6.1
EQUATION 6.1
Total MSW generated (Gg/yr) x Fraction MSW landfilled x Fraction DOC in
MSW x Fraction Dissimilated DOC x 0.5 g C as CH4/g C as biogas x
Conversion factor (16/12) - Recovered CH4 (Gg/yr)
Methane emission
Total MSW generated can be calculated from Population (thousand persons) x Annual MSW
generation rate (Gg/thousand persons/yr).
In developing countries only urban populations are considered, since the rural populations
are assumed to dispose of their waste in very small open clumps, where significant
methane generation is assumed not to occur.
Fraction dissimilated carbon: This is the portion of carbon in substrates that is converted to
landfill gas. The assimilated fraction is the remainder of carbon that is used to produce
new microbial cell material. To date, estimates of how much carbon may be dissimilated
have relied on a theoretical model that varies only with the temperature in the anaerobic
zone of a landfill: 0.014T + 0.28, where T = temperature (Tabasaran, 1981). The
temperature in the anaerobic zone of a landfill is thought to remain constant at about
35°C, regardless of ambient temperature (Bingemer and Crutzen, 1987). Therefore
applications of the Bingemer and Crutzen (1987) method use a figure of 0.77 dissimilated
DOC.
No allowance was made for any reduction in methane emissions from methane oxidation,
also it was assumed that all waste decomposed anaerobically within the landfill rather than
aerobically. •
Using the data that they had collected, Bingemer and Crutzen (1987) estimated that global
emissions of methane from landfills ranged between 30 - 70 Mt per year.
As an example, an estimate for the US can be derived as follows (based on values provided
by the US EPA):
Assumptions:
Waste generated:
% waste landfilled:
% DOC:
% DOC dissimilated:
Recovered methane:
about 235 Tg/yr to landfills
up to 80
21
77
I-5 Tg/yr
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These assumptions yield an estimate of:
((235 Tg/yr x 0.80 x 0.21 DOC x 0.77 Dissimilated DOC x 0.5 kg C as
CH.,/kg C as biogas x 16/12) - 1.5 Tg/yr) = 19 Tg/yr
OECD (1991) also cites a study by Piccot et al. {1990) who surveyed 31 countries through
literature review and personal communication, resulting in country-specific factors of
MSW generation rates per capita, waste composition and percentages of waste landfilled.
These values are given in Table 4.2 of OECD (1991); however they have been subject to
criticism from some countries and some OECD Workshop participants who were
concerned that the data may not be very representative of their countries or regions.
It is proposed that the methodology of Bingemer and Crutzen (1987) remains as the
methodology that can be used by all countries to calculate methane emissions estimates
from their landfills. The Workbook provides a detailed step-by-step version of this
methodology as well as default values (as discussed above) for factors to be used where
they are not already available from within each country.
Limitations to this methodology
However, there are limitations to this methodology which have resulted in criticism from
researchers who have tried to apply it in their own countries. Some of these factors have
already been highlighted above. The principal factors which cause these concerns are:
• there is no time factor involved in the calculations; also
• there is a high level of carbon converted to methane because there are no
considerations of methane oxidation.
In addition, die assumption that a constant fraction (0.77) of the DOC is dissimilated,
under any ambient conditions, is open to discussion. Ranges of values for dissimilated
DOC may therefore be more appropriate where local information is available.
Two further factors should be incorporated into the methodology of Bingemer and
Crutzen (1987) to account for concerns relating to time factors and to methane oxidation.
Both of these factors and suggested modifications to account for them are now discussed
further. They may be incorporated into the Workbook calculations in future versions.
Accounting for delayed release of methane: There is a lag time between placement
of the waste and the beginning of methanogenesis, after which generation increases until it
reaches a plateau. In the later stages of methanogenesis, gas production trails off and
eventually ceases. The actual timing of the various stages of methane generation depend
on the type of waste and the conditions prevalent in the landfill.
If waste of roughly the same composition were deposited at the same frequency for the
number of years that it takes for the majority of carbon in that waste to decay, the
assumptions of instantaneous release would not lead to an overestimation of emissions -
current emissions from all the waste deposited during those years should equal the
eventual emissions from the waste deposited in the current year, as calculated by
Bingemer and Crutzen's equation. If however the rate of disposal has increased over time,
the uncorrected Bingemer and Crutzen method will overstate the current year's
emissions. (US EPA, 1991 a)
In most cases, the amount of waste disposed of to landfills is increasing, it should be
possible to develop correction factors based on the average annual growth rate of landfill
waste disposal, and the average amount of time the waste produces methane. Some initial
research in this area has been done recently. (ICF, 1993) Results of this work and other
related research will be reviewed and considered for possible updating of the
methodology in the future.
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Accounting for oxidation: Methane migrating through aerobic soil or waste can be
oxidised by microorganisms, whilst sulphate-reducing bacteria may oxidise methane in
anaerobic soil or waste. However, very little is known about the extent of methane
oxidation that takes place within landfills, or of the factors which influence methane
oxidation (Bogner and Spokas, 1993), and there is no widely accepted estimate for the
rate at which methane is oxidised after it has been generated within landfills. Factors
affecting methane oxidation are known to be' related to the microbiological conditions
within the site, as well as the depth of the si|e, its permeability, etc. In addition, site
management is likely to be important, including the characteristics of the site cap and any
venting or control measures that are installed.
More sophisticated models of methane emissions include a factor related to methane
oxidation. However, the factors chosen differ widely: Orlich (1990) chooses 40 - 50%; UK
Department of the Environment (1993) uses range between 0 - 40%; van Amstel et al
(1993) assume 20%; US EPA (1993) use a factor of 10%. A better understanding of
methane oxidation is needed to provide a more reliable factor for inclusion in future
models.
Based on these models, it is suggested that the estimate of methane emissions from
landfills derived using the Bingemer and Crutzen methodology be reduced by 10% to
account for oxidation. Some consideration of the variation associated with this value may
also be appropriate.
Thus by incorporating these two modifying factors, the underlying Bingemer and Crutzen
approach can be adjusted to reflect more accurately landfill conditions and country-specific
data. It has the added advantage that the Bingemer and Crutzen approach is very simple
and easy to use, and with these additional modifications, it can provide the best model for
estimating emissions in many countries.
Other approaches used
For countries where more comprehensive data are available, different and more
sophisticated methods may be applied to arrive at estimates of methane emissions from
landfills. There have been various refinements made to Bingemer and Crutzen's approach;
these are described in the next section.
Ahuja (1990) used the same approach as Bingemer and Crutzen (1987), but included a
further factor in the equation, namely the percentage of MSW that is dry refuse. Methane
emissions were calculated according to Equation 6.2.
EQUATION 6.2
Total MSW generated (Gg/yr) x Fraction MSW landfilled x Fraction DOC in
MSW x Fraction Dry refuse x Fraction Dissimilatecl DOC x 0.5 g C as CH4/g
C as biogas x Conversion factor (16/12) - Recovered CH4 (Gg/yr)
Methane emission
Again however, this approach requires application of regional factors which are subject to
much uncertainty, also the value for the Fraction Dry refuse can be open to much dispute
even within a single country, let alone worldwide.
Another empirical approach'was taken by Orlich (1990), who applied factors for waste
generation rates per capita and for methane generation rates per tonne of waste for both
developed and developing countries. These two factors were 1.0 kg or 0.5 kg per capita
per day, and 180 m3 or 60 m3 methane per tonne for developed and developing countries
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respectively. Orlich ((990) also excluded any waste disposal outside of urban areas in
developing countries. This method of calculation gave a global estimate of 32.9 M tonnes
of methane emissions from landfills in developed and developing countries in 1990. UN
population statistics were also used to estimate future emissions up to 2030.
Richards (1989) used gross domestic product (GDP) as an indicator of waste generation
rates, which in turn were used to estimate methane emissions from landfills as an energy
resource. Using figures of world GDP, he estimated a world waste generation value of 490
million tonnes per annum, of which about 80% would be landfilled, yielding about 100 m3
of landfill gas per tonne of refuse over about 10 years. This analysis yielded a value of
global methane emissions from landfills of 9.8-18.3 Mt/yr.
Theoretical first order kinetics methodologies
More complex methods for estimating methane emissions from landfills acknowledge the
fact that methane is emitted over a long period of time rather than instantaneously as in
the former methodologies. A kinetic approach therefore needs to take into account the
various factors which influence the rate and extent of methane generation and release
from landfills. This approach has generally been used to calculate emissions from individual
landfills, for example in the estimation of the potential of a site to generate economic
quantities of landfill gas,:but it can also be applied in a more general way to entire regions
or countries.
Early attempts to calculate emissions using a kinetic approach were discussed by EMCON
Associates (1981), the most well known and used of which is referred to as the Scholl
Canyon Model. This approach modelled the "average" landfill within the region or country,
and then scaled the results to take into account the total waste landfilled within the whole
region or country.
A number of factors need to be taken into account in any kinetic modelling of landfill
methane generation. The main factors to consider are those of waste generation and
composition, environmental variables such as moisture content, pH, temperature and
available nutrients, as well as information on the age, type and time since closure of the
landfill (Thorneloe and Peer, 1990).
The model equation and variables included in the Scholl Canyon model are given as
follows:
Q CH4 s LO R (expfkc) - exp(-kt)}
where:
QCH«
LS
R
k
c
t
methane generation rate at year t (rrrVyr)
DOC available for methane generation (nrrVt of refuse)
quantity of waste landfilled (t)
methane generation rate constant (yr'1)
time since landfill closure (yr)
time since initial refuse placement (yr)
Practical applications of kinetic models
A number of countries have applied this or similar modelling approaches to their own
situation;
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A recent study in the United Kingdom (Department of the Environment, 1993) has used
the same modelling rationale but with two different approaches to the problem of scaling
the modelling to include all wastes within the UK:
(i) UK landfilled waste was treated as if it were disposed of to a single site. Model
parameters were selected to represent nationally weighted average values, and an
estimate of methane production from a unit of waste was made. The results were
then extrapolated to arisings for the whole of the UK..
(ii) Data were collated for sites where information was available, the yield of methane
was calculated for these sites, and the results were then extrapolated to waste
arisings for the whole of the UK. Average parameteb values were used as above. It
was necessary to assume that the sites covered contained waste types in proportions
representative of all UK sites to ensure that the extrapolation was valid.
This study drew on extensive data available on the typical composition of waste arisings
from different sources (domestic, civic amenity, commercial, industrial and inert), and used
this information to divide the degradable carbon pool into three categories, each with a
different decomposition rate constant, representing material that decomposes at different
rates. This is a similar approach to that taken by Pacey and Augenstein (1990) and Manley
etal (1990). Further modifications to the model predictions included a one year time lag
before the start of methane generation, as well as modifications for aerobic
decomposition, microbial biomass, leachate generation and methane oxidation. Each of the
factors was included in the model as a percentage decrease in methane emissions.
The results from this study provided estimates of the range of methane production per
tonne of waste over all time. These were then either compiled with waste arisings
statistics, or were incorporated into sites with known data and then extrapolated to
national levels, to provide estimates of methane production from MSW in the UK. The
results showed a wide range of values for the amount of methane produced from MSW,
between 0.6 and 5.3 Mt per year, as well as a best estimate of about 2 Mt per year. These
figures have already taken reductions from gas flaring or use into account. The study
emphasised that the uncertainty associated with the estimate reflected the lack of
confidence in the modelling parameters.
The Netherlands have carried out a national estimate of methane emissions using a first
order kinetic model applied to the whole country (Van Amstel et al., 1993). The estimate
used detailed information on landfilling that has been collected for the country since 1945,
a degradation rate coefficient of 0.1 per year (based on measurements of actual methane
emissions at three landfills), and a degradable organic fraction of 18% before 1986, and
17% between 1986 and 1995. After 1995 this fraction is predicted to decrease because of
recycling and separation initiatives that are aimed at reducing the organic content of waste
to landfills. The calculation also assumed an oxidation percentage in the soil cover of 20%
and a methane concentration of 50% of the landfill gas. This approach has provided an
estimate of methane emissions from landfills in the Netherlands of 377 kt methane per
year (range 178-576), with 25% recovery.
In Canada, emissions from landfills have also been calculated using the Scholl Canyon
model (Environment Canada, 1992). The approach used population statistics and waste
generation rates per capita, as well as collecting as much information as possible on major
landfills such as the date opened and closed, waste quantities landfilled, and gas collected.
The default value for methane generation used was 232 mVt, whilst the rate constant k
was determined for specific landfill sites. Using these factors, a value of 1405 kt methane
was obtained for methane emissions from Canadian landfills in 1990 (excluding any
methane reductions from flaring or use). Environment Canada (1992) estimate that this
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value is about 22% lower than one derived using the Bingemer and Crutzen (1987)
methodology.
In the United States, emission from landfills have been calculated using an adaptation of
the Scholl Canyon model (US EPA, 1991 b) by EPA's Office of Air Quality Planning and
Standards of the Office of Air and Radiation. Data was collected from a stratified sample of
630 US landfills (US EPA, 1988) indicating that 334 teragrams per year of waste are
tandfilled annually. This data was used to develop inputs for the first-order decomposition
model and estimates were generated to consider potential regulations for MSW landfill atr
emissions. The baseline estimate for the U.S. for active municipal solid waste landfills is 18
teragrams in 2000 and 20 teragrams in 2010. This estimate does not include methane
emissions from industrial landfills. Extensive modelling of potential emissions for different
regulatory strategies has been conducted. This has been published in a background
information document. (U.S. EPA, 1991 a)
Other methodologies used
In the United States, EPA's Air and Energy Engineering Research Laboratory (AEERL) of
die Office of Research and Development has taken a different approach to calculating
methane emissions from US landfills. (EPA, 1991 b; EPA, 1992; EPA, I993b) Due to the
concern with the inaccuracy of predicting degradable organic content and the occurrence
of over-prediction of gas quantities using first-order decomposition rate equations, AEERL
gathered data from 112 landfills including landfill gas recovery rates and welled waste (i.e.,
quantity of waste from which landfill gas is extracted through the recovery wells). The data
went through extensive quality assurance including site visits to over 30 facilities and
scrutiny by industry and academia exports.
An empirical model was developed relating flow rates to welled waste through statistical
and regression analyses. (EPA, I99(band 1992; Thorneloe, 1992.) The objective was to
Set statistical criteria dictate the shape and position of the regression curve. A regression
model with three different linear segments was the result where each segment applies to a
distinct landfill size class. The emission factors that were developed from this approach are
believed to represent the actual gas recovery rates as opposed to model predictions based
on assumed values for degradable organic content. The results of this research are being
published in two EPA reports.
. Estimate of Global Methane Emissions from Landfills and Open Dumps, to be
published 1/94.
• Estimate of Methane Emissions from U.S. Landfills, to be published 119.4.
The findings from this modelling approach indicate that U.S. methane: emissions account
for 11 to 23 tg/yr (with an average of 17) and that global emissions account for 27 to 58
ts/yr (with an average of 43) in 1992. The amount of methane being utilised or flared was
excluded from this estimate. Using Bingemer and Crutzen's (1987) approach and similar
inputs for these different approaches, an average for U.S. emission was 25 tg/yr and the
average for global emissions was 61. This suggests that Bingemer and Crutzen's approach
results in an estimate approximately 30% greater than the estimates obtained by AEERL.
(Thorneloe, 1993a)
The Global Change Division (GCD) of the Office of Air and Radiation has adopted a
similar statistical modelling approach. Data were collected from 85 landfills that were
considered to be representative of those US landfills that contain the majority of the
waste in place in the US. A statistical model was then developed from the verified database
that established the relationship between the quantity of waste in place and the methane
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production from the landfill. Their estimate for the US suggests that landfills contribute 8.1
to 12 tg/yr for 1990, with a central estimate of 9.9 tg/yr. The major reason for the
difference between the AEERL and GCD model results is believed to be the difference in
the waste quantity used. It is recognised that there is uncertainty with estimates available
for the quantity of waste being landfilled. In fact, this is considered one of the largest
uncertainties with estimating methane emissions from landfills.
A regression approach such as those used by AEERL and GCD may be appropriate to use
in other countries outside of the US. However, regression coefficients may vary
considerably between different countries because of the many factors that differ between
landfills in the US and in other countries. In particular, the landfills included in the US
analyses were generally some of the largest landfills in the world. Few other countries have
as many landfills as large as this. Other factors which will influence the value of the
regression coefficient include the waste composition, site management techniques, and the
climate. Other countries are conducting studies to see if similar results are found. The
United Kingdom's Department of the Environment is obtaining gas extraction data from
landfills and will explore a similar modelling approach.
6. I .5 Sources of uncertainty
Several sources of uncertainty in estimating emissions of CH4 from landfills exist, these
include:
• The quantity of CH4 that is actually produced from the waste in the landfill;
• The quantity and composition of landfilled waste;
• The quantity of CH4 that is actually emitted to the atmosphere.
Emissions of methane from open dumps and
from older small sites
Most methods of estimating methane-emissions from landfills exclude both these
categories, on the grounds that emissions from these sources are very insignificant.
However, as discussed above, there is anecdotal evidence to indicate that "open" landfills
may generate significant quantities of methane, even though they are not managed
according to high standards of landfilling techniques. The waste contains high levels of
readily degradable organic material, and therefore degrades very rapidly and completely
over a period of up to 10 years. National experts may use their own discretion as to
whether or not to include these estimates. Obviously this increases the overall range of
uncertainty in national estimates.
For old or small landfill sites, US EPA's (I993b) calculations have excluded any
consideration of these sites contributing to methane emissions. However, there are
thought to be about 30,000 older closed landfills in the US (Thorneloe, 1992), and field
measurements of urban methane concentrations indicate that older closed landfills are
often significant sources of emissions in the urban environment (Kolb et al. 1992).
Omission of older closed landfills from this analysis therefore biases the estimates of
methane emissions downwards, contributing to the overall uncertainty in the estimate.
PART 2
6.15
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Waste quantities and composition
The most significant factor that determines the accuracy of estimates of methane
production from landfills is an accurate knowledge of the quantity and composition of
wastes disposed of to landfill. This includes the quantity of waste already in place, plus data
relating to annual waste disposal to landfills.
Many developed countries now have effective means for statistical collection of the
quantity of waste being disposed of to landfills, and are also improving their understanding
of die composition of various waste categories.
Historical knowledge of waste disposal is often less accurate: waste statistics for the UK,
for example, are of very limited quality before 1974 - prior to that date, responsibility for
waste disposal was at a local level, and was not nationally co-ordinated (Department of the
Environment, 1993).
Similarly, many countries have poor records on numbers of landfills, especially of older
closed sites. US EPA (I993b) estimates that in the US, approximately 3,000 small landfills
closed during the 1980s, additionally that there may be tens of thousands of landfills that
closed prior to this. In many countries, the existence of older closed sites may be known
but no records of waste types or quantities are available.
For most countries, limitations on funds available will prevent extensive investigations of
these older closed sites, except for those that are still causing local environmental
concern. It is therefore more cost-effective to concentrate efforts into improving the
quality of data being collected on existing landfilling operations, including on the total
waste to landfill plus more detailed site-specific landfill data. Detailed site investigations, for
example in connection with a gas exploitation scheme, may give additional support to
emissions predictions, or can be used to support predictive methodologies as with the US
EPA's (1993) method.
Composition of waste is very important in determining the amount of methane generated.
The degradable organic content (DOC) of waste is an essential component in all
calculations of methane emissions, and small variations in the assumed values for DOC can
result in large variations in the overall estimate of methane emissions. As further
information becomes available about the composition of a country's waste, so it can be
categorised into fractions with varying decomposition half lives, for incorporation into
kinetic models.
Different countries have widely differing MSW compositions: developing countries have
solid waste that is of a higher putrescible fraction compared with developed countries,
where waste has a much higher paper and card content. These factors influence both the
rate and the extent of degradation of the various waste fractions, and need to be taken
into account where data are available. Future changes in waste management practices will
change the composition of waste to landfill considerably, resulting in different methane
emissions levels.
The amount of municipal waste landfilled in the U.S. is estimated at approximately 334 Tg
(U.S. EPA, Office of Solid Waste [OSW], 1988). This figure represents one of the largest
uncertainties in the current estimates. Paper was the largest single component of the
degradable organic carbon (DOC) fraction in both the U.S.and Canada.Per capita MSW
generation was in the range of 1.7 to 1.8 kg/person/day for both the U.S. and Canada (U.S.
EPA, 1990; El Rayes and Edwards, 1991). The average MSW generation rate in other
OECD countries is 1.1 kg/person/day. MSW in these countries has a DOC content of
approximately 15.3% (Davis et al., 1992). The value used for the U.S. is for MSW only; an
additional 15 Tg/yr of biodegradable industrial solid waste is also landfilled, (U.S. EPA,
6.16
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1987). This industrial solid waste is unaccounted for in the initial estimates of landfill
methane.
In most cases, country-specific information does not state specifically whether industrial
waste is co-disposed with MSW.
Information on the amount of MSW generated and landfilled in the European countries
that are not OECD members and the former Soviet Union is limited. Average MSW
generation for Greece, the former Soviet Union, and Eastern Europe is approximately 0.6
kg/person/day (Frantzis, 1988; Papachristou, 1988; Peterson and Perlmutter, 1989 and
Bingemer and Crutzen, 1987), and the available data indicate that putrescibles make up a
large portion of the MSW (estimates range from 32 to 60%). This MSW contains
approximately 15% DOC (Frantzis, 1988; Papachristou, 1988; Peterson and Perlmutter,
1989; Bingemer and Crutzen, 1987; Zsuzsa, 1990).
For most Asian countries, estimates of MSW generation were identified for one or two
major cities, but not for the entire country. National per capita MSW generation estimates
were identified for Indonesia, Sri Lanka, the Philippines, Singapore, Taiwan, and Pakistan.
These estimates range from 0.4 kg/person/day for the Philippines to 1.0 kg/person/day for
Singapore. The average per capita MSW generation for these countries is estimated to be
0.6 kg/person/day (Davis et al., 1992). t,
If
Few data are available on MSW production and management in Central America, South
America, the Caribbean Islands, and Mexico. Most of the available information is only for
the larger cities. The average per capita MSW generation rate in Costa Rica, and Mexico
and six South American countries (Brazil, Colombia, Chile, Paraguay, Peru, and Venezuela)
is estimated to be 0.8 kg/person/day. The components are mainly vegetable and
putrescible waste paper and cardboard. The average DOC for the mentioned countries is
!7%(Davisetal., 1992).
Information on MSW generation and disposal for African and Middle Eastern countries is
very limited. In Africa, it-appears that toxic and hazardous industrial and commercial
wastes are purposely or inadvertently disposed of with the MSW stream. Some
information pertaining to generation rates for African countries was located; but
information for only two Middle Eastern countries, Israel and Yemen, was obtained. Based
on the very limited information for these two continents, it: is estimated that per capita
generation rates range from 0.3 to I. I kg/person/day, and the DOC content ranges from 3
to 20%. (Thorneloe, I993a)
Landfill and waste management practices also have significant effects on methane
generation, for example the degree and type of landfill cover, the method of landfilling, the
water management practices etc.
Flaring and gas recovery schemes
Both of these factors will reduce the amount of uncontrolled methane emissions from
landfills. Utilisation and/or flaring of landfill gas as an energy source is one of the most
successful methods for reducing uncontrolled methane emissions from landfills (see
"Options for controlling methane emissions from landfill sites" for further details).
Gas flaring generally occurs where it is necessary to ensure local site safety, but it is now
recognized as a valuable method for reducing the extent of methane emissions to
atmosphere.
Any national inventory of methane emissions from landfills therefore needs to take into
account the reductions achieved by these two factors. For gas use, numbers of schemes
PART 2
6.17
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are generally well known and documented, therefore an accurate estimate can be made of
the amount of methane being used in the schemes. Information on landfill gas schemes
around the world is available from a variety of sources, eg. Governmental Advisory
Associates (1991) for the US; Landfill Gas TRENDS (1993) for the UK; Gendebien et al.
(1992) for the European Community; Lawson (1991) for countries participating in the
International Energy Agency's Bioenergy Agreement; Richards (1989) for world statistics,
etc. Most of these sources update their information regularly as more schemes are
commissioned.
Estimates of the extent of flaring are more difficult to achieve with accuracy, and generally
have to be estimated from a knowledge of the state of landfill management within the
country. For many countries, new legislation will ensure that most future landfills will be
obliged to have gas control equipment installed; therefore in the future this will result in
reductions in uncontrolled emissions as well as better quality data on this factor.
6.l.6Availability and quality of data
Waste management data
The quality of methane emissions estimates are directly related to the quality of the waste
management data used to derive these estimates, i.e. data on MSW generation rates, and
on quantities of MSW disposed of to landfill. Most developed countries have these data
available, and they should be used wherever possible. These data are often lacking
however for developing countries and for the former Communist bloc countries.
Some global compilations of data have been made that can be used where local data are
not available:
• Thorneloe et al. (In Press) has compiled data on waste management activities;
• World Resources Institute (1990) summarised waste generation rates for some
countries, including Eastern European countries;
• Piccot et al, (1990) collected waste generation data;
• Bingemer and Crutzen (1987) compiled regional data;
• Carra and Cossu (1990) compiled data from 15 countries;
• OECD (1989) compiled country-specific data;
• U.S. EPA (forthcoming) compiled data on global waste management activities;
• U.S. EPA (forthcoming 4/94) compiled data on waste management activities;
• U.S. EPA in the forthcoming Report to Congress on Global Anthropogenic Emissions
of Methane have compiled a list of over 50 references on global waste generation
data.
Historical data on the amount of MSW disposed of to landfill are usually of limited value or
quality. Extrapolation to future waste management scenarios is usually easier, especially
since many countries are modifying their waste management policies, in particular to
promote waste reduction and recycling, and so are required to review and monitor total
MSW generation rates and disposal routes to provide current and future waste disposal
scenarios (eg. Van Amstel et al. (1993) for the Netherlands, US EPA (1993) for the US).
6.18
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Waste composition data
The composition of waste directly determines its DOC value. Default factors provided by
Bingemer and Crutzen (1987) should be used where no country-specific factors are
known.
As with 6.1 above, many countries are improving the quality of data held on waste
composition, because of changes to waste management policies that are encouraging
reduction and recycling.
Gas flaring and use
Accurate statistics are available in most of the countries where landfill gas use is practiced.
However, the extent of gas flaring is often less well documented. Improvements to waste
management practices should see an improvement in the collection of regular statistics
which monitor the numbers of sites where gas is flared or used.
6.1.7 Conclusion
A methodology is presented here that allows simple calculation of methane emissions
from landfills globally, and can be used by all countries. Some of the assumptions used in
the method are open to criticism however, therefore countries are encouraged to
progress to using a more sophisticated method with more country-specific data when
more data become available.
PART 2
6.19
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TABLE 6,1
REGIONAL WASTE DISPOSAL, COMPOSITION, AND WASTE GENERATION DATA
Region
USJCanada/AustraKa
US.
Canada
Australia
Other OECD
Japan
New Zealand
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Ireland
Italy
Luxembourg
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
UK
USSR/E.Europe
Developing Countries
% MSW Landfilled
91
62
93
98
71
28
95
57
50
63
87
47
69
100
100
35
27
55
78
24
76
42
18
NA
85
80
% DOC of MSW
22
NA
NA
NA
19
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
17.5
15
Waste Generation
(kg/cap/day)
1.8
2.0
1.7
1.9
0.8
0.9
1.8
0.6
0.9
1.2
I.I
0.7
0.9
0.7
0.9
0.7
1.0
1.2
1.3
0.6
0.8
0.9
1.0
1.0
0.6
0.5
Sources: Bingemer and Crutzen (1987) for regional data and OECD (1989) for individual countries.
6.20
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6.2 METHANE EMISSIONS FROM
WASTEWATER TREATMENT
6.2.1 introduction
Methane (CH4) production from wastewater treatment (WWT) under anaerobic
conditions is estimated to range from 30 to 40 teragrams, per year (Tg/yr). This represents
8 to 11 percent of the total global anthropogenic methane emissions, estimated at 360
Tg/yr (IPCC, 1992). Industrial WWT sources are estimated to be the major contributor
to WWT emissions, accounting for 26 to 40 Tg/yr. Municipal WWT is estimated to emit
approximately 2 Tg/yr, with Asia accounting for 65 percent. Uncertainty in these estimates
result from a lack of data characterizing wastewater management practices, the quantities
of wastewater that are anaerobically treated, data on the extent that CH4 produced is
flared or otherwise utilized, and field data on the CH4 potential of wastewater treatment
lagoons. (Thorneloe, 1993b)
Wastewater can produce methane if it is treated anaerobically and if the methane
produced is released to the atmosphere. Anaerobic methods are used to treat wastewater
from municipal sewage and from food processing and other industrial facilities, particularly
in developing countries. In contrast, developed countries typically use aerobic processes
for municipal wastewater treatment or anaerobic processes in enclosed systems where
methane is recovered and utilized.
This section provides an explanation of the default methodology for estimating CH4
emissions from WWT. A discussion of the uncertainty involved with these calculations is
included.
6.2.2 Background
Highly organic waste streams including municipal wastewater and wastewater from
industries such as food processing and pulp and paper plants have a high potential for CH4
emissions. These waste streams quickly deplete available oxygen as their organic matter
decomposes. The organic content or "loading" of wastewater is expressed in terms of
biochemical oxygen demand (BOD), which is the principal factor determining methane
generation potential of wastewater. BOD represents the amount of oxygen consumed by
the organic material in the wastewater during decomposition (expressed in milligrams per
liter - mg/l). A standardized measurement of BOD is the "5-day test" denoted as BODS.
The maximum, or ultimate BOD is denoted as BODU. Untreated municipal waste streams
typically have a BOD5 ranging from 110 to 400 mg/l. Food processing facilities, such as
fruit, sugar and meat processing plants, creameries, and breweries can produce untreated
wastewater with a BOD5 as high as 10.000 to 100.000 mg/l. (Thorneloe, I993b) Most
other industrial wastewater has a low BOD content.
Under the same conditions, wastewater with higher BOD concentrations will yield more
CH4 than wastewater with relatively lower BOD concentrations. Because of its influence
in CH4, BOD is a commonly measured parameter and data is available on BOD loading
rates. Table 6.2 shows BOD values for municipal wastewater by region, while Table 6.5
includes BOD values for the wastewater of key industries.
Five-day BOD can range from 0.023 - 0.091 kg/capita/day for municipal wastewater. Per
capita municipal wastewater BODS has been reported from 0.023 - 0.045 kg/day in
PART 2
6.21
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developing countries and from 0.024 - 0.059 kg/day in developed countries; (the lower
value was reported for rural France) (Mara, 1976). The BOb increases when substantial
amounts of kitchen wastes are discharged to sewers, for instance as the result of using
sink disposals. (Thorneloe, I993b)
Treatment of wastewater and its residual solids byproduct (sludge) under anaerobic
conditions results in CH4 emissions. Wastewater treatment in developed countries
typically occurs aerobically using aerated impoundments. Digesters are also often used and
the gas is either flared or utilized. Wastewater in these countries is not expected to be a
major source of CH4. However, facultative and anaerobic lagoons are often used for
storage and treatment. EPA estimated to 1987 that there are approximately 5.500
municipal waste stabilization lagoons in the United States which treat 5.2 x 10 m /day of
wastewater from 8 percent of die population served by municipal treatment systems
(Office of Municipal Pollution Control, 1987). The CH4 potential from these lagoons is not
well understood and little field data are available. Industrial and commercial wastewater
processes also use lagoons for treatment and storage.
Methane production varies depending upon temperature, retention time, BOD loading,
and lagoon maintenance. Facultative lagoons, the most common type, treat wastewater by
both anaerobic fermentation and aerobic processes. At the bottom of the lagoon, where
an anaerobic environment exists, organic matter is digested to CH4 and CO2. As these
gases bubble to the surface, much of the CO2 is adsorbed by algae and is used, along with
nutrients liberated during digestion, to produce algal biornass (University of California,
1984). Aerobic conditions, supported by algae growth, are maintained near the surface.
Between 20 and 30 percent of the BOD loading to a facultative pond is anaerobicaliy
metabolized. As BOD loading increases and natural surface aeration diminishes, facultative
lagoons proceed to a more anaerobic state. This results in higher CH4 production, provi-
ding that the temperature is higher than 15°C. Under these conditions, a facultative lagoon
may act more as an anaerobic pond, with possibly 95 percent of the lagoon volume
functioning anaerobicaliy. Fermentation and thus CH4 production, is negligible at
temperatures below about I5°C, at which point the lagoon serves principally as a
sedimentation tank (Gloyna, 1971).
The depth of the lagoon is also an important factor in CH4 production. Shallow lagoons,
one meter or less in depth, are not expected to produce large quantities of CH4 because
the intake of oxygen from the surface, as well as the production of oxygen due to
photosynthesis, prevent the formation of a significant anaerobic zone. Facultative lagoons
are typically 1.2 to 2.5 meters in depth; lagoons greater than 2.5 meters in depth are
typically referred to as anaerobic lagoons. The last important factor influencing the
production of CH4 is the retention time. (Thorneloe, I993b)
6.2.3 Methodology for Estimating Emissions
from Wastewater Treatment
Methane emissions from wastewater treatment should be calculated for two different
wastewater types:
I Municipal wastewater
2 Industrial wastewater
For each category, a simple methodology for calculating methane emissions from
wastewater treatment is based on BOD loading and relies on available country-specific
data. In each category a more detailed approach is also discussed. The more detailed
6.22
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approaches would produce more accurate results if input data are available. These data are
not readily available now for many countries, but they may be in the future as research
continues.
Estimate methane emissions from municipal
wastewater treatment
Steps for Method A (simplified approach)1
Data needed are:
I Kg BODS per capita-day (default values are shown in Table 6.2 for different regions.)
2 Country Population (developing countries may choose to estimate
wastewatertreatment emissions based only on the urban population of the country if
wastes produced in rural areas decompose in an aerobic environment - see Table
6.3 for list of anaerobic and aerobic treatment methods).
3 Estimate fraction of total wastewater that is treated anaerobically. Wastewater
treatment methods that may result in anaerobic decomposition of waste are listed in
Table 6.3. Because published data on the fraction of wastewater that is anaerobically
treated in different countries are scarce, countries are encouraged to provide their
own estimate based on their available data. Table 6.4, however, contains default
values for the fraction of total wastewater that is treated anaerobically in certain
regions — these values may be used in the absence of country-specific estimates.
4 Subtract the amount of methane, if any, that is recovered and thus not emitted to the
atmosphere. This would include any methane recovered and either flared or used for
energy as part of wastewater treatment. If no national data are readily available, the
default assumption is that this amount is zero.
Equation 6.3 summarizes the methane emissions calculation.
EQUATION 6.3
[Population] x [kg BODs/capita-day] x [365 days/year] x
[0.22 kg CtVkg BOD5] x [Fraction Treated Anaerobically]
- Methane Recovered
kg CrVyear
Steps for Method B (detailed approach)
A more precise estimate of methane emissions from wastewater treatment for a given
country is possible if the following additional data are available: I) The different treatment
methods that are used in each country and the total portion of wastewater that is treated
using each of these methods; and, 2) the methane conversion factor (MCF) for each of
these treatment methods (the MCF represents the extent to which the maximum
methane producing capacity of the wastewater is realized for a given wastewater
treatment system).
1 This method is based on the approach developed for the Wastewater Treatment
Chapter of EPA (forthcoming) and is described in Thonneloe (I993b).
PART 2
6.23
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Unfortunately, many countries are not likely to have data on the portion of wastewater
treated using different methods. This is likely to be the case for many developing
countries, which are of particular importance because of their reliance on anaerobic
treatment methods. Additionally, at this time, complete information on MCFs for different
wastewater treatment systems is not available. Countries which have more detailed
Information on specific treatment methods and their MCFs are encouraged to use this
information in preparing national emissions estimates and to report these results to the
IPCC. Through review of such estimates and results of ongoing research, a more
comprehensive database of MCFs for specific treatment methods may be developed in the
future.
Where these data are available, the following approach would be used to estimate
methane emissions from wastewater treatment:
Data Needed are:
I Country Population
2 Kg BOD5 per capita-day
3 Fraction of total wastewater treated using different treatment methods. Some
common methods are listed in Table 6.3.
4 The MCF (methane conversion factor) of each wastewater treatment method.
Equation 6.4 summarizes the calculation of methane emissions from each wastewater
treatment system using the more detailed approach. Total emissions are die sum of
emissions from all systems.
EQUATION 6.4
[Population] x [kg BODsfcapita-day] x [365 days/year] x
[0.22 kg CH^/kg BODS] x [Fraction Wastewater Treated using Method,]
x Methane Conversion Factor (MCF) for Methodj
- Methane Recovered
kg QVyear
Estimate methane emissions from industrial
wastewater treatment
Methane emissions from wastewater produced in a few key industries are estimated to
account for a very large portion of total methane emissions from wastewater treatment.
(Thorneloe I993b) Table 6.5 lists industries which are believed to be responsible for
most of the emissions. National experts should estimate emissions for these industries, if
applicable, and any others which can be estimated to have significant emissions, based on
locally available data.
6.24
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Steps for Method A (Simplified Approach)
I Determine the relevant industries for a given country. The methane emissions from
industrial wastewater treatment are based on wastewater outflow by industry. Table
6.5 lists industries which produce wastewater containing concentrations of organic
material likely to produce significant CH4 emissions.
2 Wastewater outflow by industry must be estimated. If these data are not directly
available, they may be estimated based on production by industry, and waste
consumed per unit of product. Typical water consumption rates for some key
industries are presented in Table 6.6.
3 Then, the BOD content of the wastewater for each product must be estimated.
Default SOD values are provided in Table 6.5.
4 Estimate the fraction of wastewater from each industry that is treated anaerobically.
Unfortunately, default values are not available by industry. If no information is locally
available, the default values shown in Table 6.4 could be used as an initial
approximation.
5 If anaerobic treatment with methane recovery is employed, the amount of methane
that is recovered should be subtracted from total emissions.
Equation 6.5 summarizes the emissions calculation for industrial wastewater treatment
Emissions should be estimated for each industry; total emissions from industrial
wastewater treatment are the sum of emissions from each industry.
EQUATION 6.5
Wastewater outflow by industry (kl) x
[kg BODS/I] x [0.22 kg CHH/kg BODS] x [Fraction Wastewater Treated
Anaerobically]
- CH, Recovered
kg CH4/year
Method B (detailed approach)
As with estimating methane emissions from municipal wastewater treatment, more precise
estimates of methane emissions from industrial wastewater treatment can be made if
specific methods used to treat wastewater from each industry are known and the MCFs
for each method have been estimated.
If this information is available. Equation 6.6 can be used to calculate emissions from
industrial wastewater treatment. Total emissions for each industry are the sum of
emissions from each wastewater treatment system. Total emissions from industrial
wastewater treatment are the sum of emissions from each industry.
PART 2
6.25
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EQUATION 6.6
Wastewater outflow by industry (kl) x
[kg BODj/l] x [0.22 kg CH
-------
WASTE
Wastewater Treatment Facility Efficiency and
Output
Wastewater supposedly treated aerobically by treatment plants may still be subject to
anaerobic conditions, due to poorly functioning facilities. In addition, adjustments should
be made for (I) the amount of CH4 that is controlled through utilization or flaring and (2)
the amount of CH4 that is oxidized prior to atmospheric release. However, the specific
data needed are often not available.
Research in Japan has produced data on high levels of methane production resulting from a
wastewater treatment process that includes aeration and is essentially operated under
aerobic conditions. (Kyosai and Mizuochi, 1993) This is result represents an area that
should be studied in more detail in the future.
Current estimates from wastewater treatment lagoons are relatively uncertain due to the
limited available data. The US EPA's Office of Research and Development's Global Climate
Change Engineering Research Program is conducting field measurements of wastewater
treatment lagoons, both anaerobic and facultative, to develop emission factors from these
sources.
Physical and Chemical Data
Data on physicochemical wastewater characteristics are limited, especially for country-
specific wastewater volumes. For industrial wastewater emission estimates, the BOD
values reported for the source categories are averages of BOD values given for several
process wastewater streams. The estimate could be improved if data were obtained on
the chemical characteristics and volumes of process wastewater streams and the fraction
of these wastewater streams anaerobically degraded. Furthermore, the emission
methodology does not account for factors, such as temperature, pH and retention time,
that influence the rate and extent of anaerobic decomposition, and consequently, the
potential for CH4 production.
6.2.7 Conclusion
The methodology presented in this section gives a simple calculation of methane emissions
from wastewater globally, and can be used by all countries. Some of the assumptions used
in the method are open to criticism. Therefore countries are encouraged to progress to
using a more sophisticated method with more country-specific data, when more data
become available.
TABLE 6.2
ESTIMATED BOD5 VALUES IN MUNICIPAL WASTEWATER BY
REGION (KG/CAPITA/DAY)
Region
Africa:
Asia, Middle East, Latin America:
N. America, Europe, Former USSR, Oceania:
BOD5 Value
0.037
0.04
0.05
Source: EPA (forthcoming)
PART 2
6.27
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TABLE 6.3
ANAEROBIC AND AEROBIC METHODS OF
WASTEWATER TREATMENT
Treatment Method
Aerobic (low MCF) methods:
Developing Countries
• Open Pits/Latrines
• Aerobic (shallow) ponds
• Ocean Dumping
• River Dumping
Developed Countries
• Sewer systems with aerobic treatment
Anaerobic (high MCF) methods:
Developing Countries
• Anaerobic (deep) ponds
• Sewer systems with aerobic treatment.
Developed and Developing Countries
• Septic Tanks
Anaerobic Methods with Methane Recovery
Primarily Developed Countries
TABLE 6.4
ESTIMATED TOTAL (URBAN) WASTEWATER FRACTION
ANAEROBICALLY TREATED
Country/Region
Fraction Treated
Africa
N/A
Asia and Oceania
15%
Latin America
7% to 10%
North America and Europe
15%
Latin America
10%
Source: EPA (forthcoming)
Note: For many developing countries, industrial wastewater is often
discharged with domestic wastewater.
6.28
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TABLE 6.5
BIOCHEMICAL OXYGEN DEMAND (BOD) ESTIMATES FOR VARIOUS INDUSTRIAL
WASTEWATERS
Industry* "
->> *"*$> «. •*&
Iron and Steel
Non-ferrous
metals
Fertilizer
Food & Beverages
Fruits/vegetables
Cereals
Meats
Butter
Cheese
Cane Sugar
Beet Sugar
Wine
Beer
Other Beverages
Pulp and Paper
Petroleum Refining
(Petrochemical)
Textiles
Rubber
Miscellaneous11
BOD5*
0^0
0.00 lb
0.00 lb
0.00 lb
0.035
0.003
0.00 lc
0.02°
0.003C
0.003°
0.002b
0.0 lb
0.135°
0.085°
0.083°
0.004b
0.004°
0.00 lb
0.00 lb
0.002
References and Notes -^ <• ^ , ^
. f " >- i f- t
J, " i - * T" *,/«•.
No references for BOD were obtained. Used the value for BOD in textile
wastewaters, p.67, Carmichael and Strzepek (1987) since it was the lowest
value obtained for industrial sources.
No references for BOD were obtained. Used the value for BOD in textile
wastewaters, p.67, Carmichael and Strzepek (1987) since it was the lowest
value obtained for industrial sources.
No references for BOD were obtained. Used the value for BOD in textile
wastewaters, p.67, Carmichael and Strzepek (1987) since it was the lowest
value obtained for industrial sources.
This value is an average of the following categories of the fruit & beverage
Industry.
Barnes etal. (1984), p. 213
EPA(l974a), p. 39,40
EPA (1975), p. 58, 60; EPA (I974c), p. 39, 41
EPA (I974b), p. 59; Barnes et al. (1984). p. 316
EPA (I974b), p. 59; barnes et al. (1984), p. 316
Barnes etal. (1984), p. 20
Barnes et al. (1984), p. 12; EPA (I974d)
Barnes etal. (1984), p. 73
Barnes etal. (1984), p. 73
Barnes etal. (1984), p. 73
Carmichael and Strzepek (1987), p. 4? and Hall et al. (1988) as cited in
Torpy(l988), p. 20
Average of values reported in Carmichael and Strzepek ( 1 987), pp. 33, 36
Carmichael and Strzepek (1987), p. 67
No references for BOD were obtained. Used the value for BOD in textile
wastewaters, p.67, Carmichael and Strzepek (1987) since it was the lowest
value obtained for industrial sources.
No BOD values obtained. Used BOD reported for the pharmaceutical
Industry in Carmichael and Strzepek (1987), p. 85
' Industries presented here are taken from table 47, pp 116, 117 in Carmichael and Strzepek ( 1 987).
b Reported as BOD. This is assumed to be ultimate BOD.
° Reported as BODs.
d Industries in this group were undefined.
Source: Thorneloe, I993b.
PART 2
6.29
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WASTE
TABLE 6.6
WATER CONSUMPTION PER UNIT OF PRODUCT FOR PAPER AND FOOD PROCESSING
FACILITIES
Process
Canneries
- Green beans
- Peaches and pears
- Other fruits and vegetables
:ood and Beverage Industry
-Beer
- Wine
- Meat packing
- Dairy products
- Sugar
3ulp and Paper
-Pulp
- Paper
Textiles
- Bleaching
- Dyeing
Water Consumption
(liters/metric ton)
80,000
22,000
8,000-40,000
60,000
20,000 liters/ton live weight
16,00-20,000
344,000-966,000
200,000 liters
300,000-400,000 liters/ton cotton
40,000-80,000 liters/ton cotton
Sources:
aMetcalfandEddy(l972).
b EPA (forthcoming).
* These were reported as BOD and are assumed to be ultimate BOD, as opposed to 6005. These
values, however, should still be used as the default assumptions, as other data are not available.
These water consumption factors are approximate, and in some cases, the water used in the process
may not all become wastewater.
6.30
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WASTE
TABLE 6.7
ESTIMATE OF GLOBAL AND COUNTRY-SPECIFIC METHANE
EMISSIONS FROM THE TREATMENT OF DOMESTIC
WASTEWATER -
I990(TG/YR)
Country
Emissions
Africa3
Egypt
0.02
Kenya
0.01
Morocco
0.01
Nigeria
0.04
South Africa
0.01
Sudan
0.01
Tanzania
0.01
Uganda
0.01
Other Africa
0.09
Total Africa
0.21
Asia0
China
0.54
Korea, N.
0.01
Vietnam
0.03
Other Asia
0.92
Total Asia
1.50
South America3
Argentina
0.01
Brazil
0.05
Colombia
0.01
Mexico
0.03
Venezuela
0.01
Other So. America
0.02
Total South America
0.13
^iorth America
Canada
0.02
United States
0.15
Other No. America
0.04
Total North America
0.21
Europe
France
0.01
German Democratic 0.01
Republic
Italy
0.01
United Kingdom
0.01
Total Europe
0.04
Former
USSRb
O.I (I
Oceania0
Australia
0.01
Total Oceania
0.01
World Total
2.30
a. Ten percent of BODS is assumed to be anaerobically degraded.
b. Fifteen percent of BODS is assumed to be ariaerobically
degraded.
PART 2
6.31
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WASTE
TABLE 6.8
ESTIMATE OF GLOBAL METHANE EMISSIONS FROM INDUSTRIAL
WASTE WATER TREATMENT 1990
(TG/YR)
Industry
con & Steel
^on-Ferrous
Meals
^ertiliier
foodSt
Beverages
Pulp* Paper
Petroleum
Refming
Textile
Rubber
MisceJ-
laneous*
TOTAL
Developed Countries
Endu stria!
Waste-
water
Outflow*
(Millions
m'/vr)
168,000
26.400 '
H.300
7,700
33,300
54.700
34.600
6.800
9.50G
3S5.500
BODS
W)
0.001
0.001
0.001
0.035
0.004
0.004
0.001
0.001
0.002
Percent of
BOD,
Anaerobicallv
Degraded
10%
15%
Emissions
4
1
0
6
3
5
1
0
0
20
6
1
I
9
4
7
1
0
1
30
Developing Countries
Industrial
Waste-
water
Outflow*
(Millions
mV)
56.000
8.850
4.SOO
2.600
11.100
(8.200
11,450
2.300
3.200
1 18.200
BOD'S
W>
0.00 1
0.001
0.001
0.035
0.004
0.004
0.001
0.001
0.002
Percent of
BODs
Anaeroblcallx
Degraded
10%
15%
Emissions
I
0
0
2
1
2
0
0
0
6
2
0
0
3
2
2
1
0
0
10
Worldwide
Industrial
Wastewate
r Outflow*
(Millions
mVyr)
224.300
35,000
19.000
10.300
44.400
73.200
46.100
9.100
12.700
474.100
BOD's
(M)
o.ooi
0.001
0.00)
0.035
0,004
0.004
0.001
O.OOI
0.002
10%
15%
Emissions
5
1
0
8
4
6
1
0
1
26
7
1
I
12
6
10
2
0
1
40
a. This group was undefined in Carmichael & Strzepec ( 1987).
b, Carmichjel & Strzepec (1987).
c. Sources of BOD values are given In Table 6.5.
6.32
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WASTE
6.3 EMISSIONS FROM WASTE
INCINERATION
6.3.1 Introduction
Waste incineration like other types of combustion, is a source of many GHGs. Very few
data have been compiled on the global emissions from waste incineration. Preliminary
indicators are that this source represents a small percentage of the total GHG output
from the waste source category.
6.3.2 Emissions
Certainly waste incineration produces CO2, but it is difficult to identify the portion which
should be considered net emissions. A large fraction of the carbon in waste combusted
(e.g. paper, food waste) is derived from biomass raw materials which are replaced by
regrowth on an annual basis. These emissions should not be considered net CO2 in the
IPCC methodology. If the agricultural or forestry sources are not being sustainably
managed, net CO2 emissions (equivalent to reductions in biomass stocks) should be
accounted for in those source categories. On the other hand, some carbon in waste is in
the form of plastics or other fossil fuel based products. Combustion of these materials,
like fossil fuel combustion, releases net CO2 emissions.
Other relevant gases released from combustion are net GHG emissions. Methane
emissions from waste incineration are highly uncertain. An expert working group
recognised waste incineration as a source of methane production, but was not able to give
global estimates or default emissions factors. Although this source is considered to be
relatively small compared to the other CH4 sources in waste, it was recognised as an area
for further research in the future. (Berdowski et al., 1993)
Recent studies have also shown that N2O may be an important GHG produced from
incineration. Table 6-8 provides data from studies of several incineration plants and the
N2O produced from the waste incineration, (de Soete, 1993) Studies in Belgium (IPCC,
1993), Japan (Tanaka et al., 1992) and Norway (Rosland, 1993) have estimated N2O
production from their waste incineration processes. It has also been found that the
emission level depends on the nature of the waste burned. Research in Japan has noted
that while all types of incineration produce N2O, sludge incinerators produce the highest
emissions rates. (Tanaka et al., 1992)
Traditional air pollutants from combustion - NOX, CO, NMVOC - are characterized in
existing emissions inventory systems. The IPCC does not provide a new methodology for
these gases, but recommends that national experts use existing published methods. Some
key examples of the current literature providing methods are: CORINAIR Default
Emissions Handbook (Bouscaren, 1992), as well as the U.S. EPA's Compilation of Air
Pollutant Emissions Factors (AP-42) (US EPA, 1985) and Criteria Pollutant Emission
Factors for the 1985 NAPAP Emissions Inventory (Stockton and Stelling, 1985).
PART 2
6.33
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WASTE
TABLE 6.9
NITROUS OXIDE EMISSIONS FROM WASTE INCINERATION
Nature of Waste
reference)
(65) Municipal
refuse
(£6) Municipal
refuse
[67) Municipal solid
waste
[65) Sewage- sludge
(66) Sludge
Facility
10 furnaces
{65-300 tons/day)
Stepgrate
Stepgrate
Ftuid.bed
5 stokers
20-400 t/d
3 fluid.bed
rotktln
120 t/d
4 incin.
150-300 t/d
Rotary grate
Fiuid.bed
"
••
"
T°C
780-880
780-980
830-850
750
770-812
838-854
834-844
853-887
mm.
1.2
0.8
4
6.7
3
5.6
10.2
57
270
135
100
45
>pmv
aver-
age
8
7
9.8
II. 1
87
50.7
NjO emission
max
18
4.9
24
10.5
12
17.1
12.1
125
600
292
320
145
at
02(%)
10
8-14
13-15
gN70
ton waste
11-43
40-220
14-123
26*270
97-293
135-165
227
580-1528
684-1508
275-886
101-307
Source; deSoete, 1993.
6.34
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WASTE
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