CGE%20Greenhouse%20Gas%20Inventory%20Hands-on%20Training%20Workshop%20%20LAND-USE%20CHANGE%20AND%20FORESTRY%20SECTOR%20(LUCF)

1
CGEGreenhouse Gas Inventory Hands-on Training
WorkshopLAND-USE CHANGE ANDFORESTRY SECTOR
(LUCF)
2
Background

• COP adopted guidelines for preparation of initial
  National Communications at its second session
  (10/CP.2)
• IPCC guidelines used by 106 NAI Parties to
  prepare National Communications.
• New UNFCCC guidelines adopted at COP8 (17/CP.8)
• UNFCCC User Manual for the Guidelines on National
  Communications to assist NAI Parties in using
  latest UNFCCC guidelines
• Review and synthesis of NAI inventories
  highlighted several difficulties and limitations
  of using IPCC 1996GL (FCCC/SBSTA/2003/INF.10)
• GPG2000 and GPG2003 have addressed some of the
  limitations and provided guidance for reducing
  uncertainty

3
Purpose of the Presentation

• GHG inventory in biological sectors such as LUCF
  is characterized by
• methodological limitations
• lack of data or low reliability of existing data
• high uncertainty
• Presentation aims at assisting NAI Parties in
  preparing GHG inventories using the IPCC 1996GL,
  particularly in the context of UNFCCC decision
  17/CP.8, focusing on
• the need to shift to GPG2003 and higher
  tiers/methods to reduce uncertainty
• overview of the tools and methods
• review of AD and EF and options to reduce
  uncertainty
• use of IPCC inventory software and emission
  factor database (EFDB)

4
Problems Addressed and Approach

• The presentation addresses many of the problems
  encountered by NAI experts in using IPCC 1996GL
• Problems are reviewed and categorized into
  methodological issues, AD and EF/RF
• Approach adopted includes
• GPG2003 approach
• Strategies for improvement in methodology, AD and
  EF
• GPG2003 strategy for AD and EF/RF 3-Tier
  approach
• Sources of data for AD and EF/RF, including EFDB

5
Organization of the Presentation

• IPCC 1996GL and GPG2003 Approach and Steps
• Key source/sink category analysis and decision
  trees GPG2003
• Reporting framework for LUCF sector -IPCC
  1996GL-GPG2003
• Choice of methods Tier structure and Features
• Review of the problems encountered in using IPCC
  1996GL and how these are addressed in GPG2003
• Methodological issues
• Activity data (AD)
• Emission/removal factors (EF/RF)
• IPCC 1996GL category-wise assessment of problems
  and GPG2003 options to address them
• Review and assessment of AD and EF/RF data
  status and options
• Uncertainty estimation and reduction and EFDB

6
Background Resources

• Revised 1996 IPCC Guidelines for National
  Greenhouse Gas Inventories
• http//www.ipcc-nggip.iges.or.jp/public/gl/invs1.h
  tm
• GPG2000 Good Practice Guidance and Uncertainty
  Management in National Greenhouse Gas Inventories
• http//www.ipcc-nggip.iges.or.jp/public/gp/english
  /
• GPG2003 Good Practice Guidance for Land Use,
  Land-Use Change and Forestry
• http//www.ipcc-nggip.iges.or.jp/public/gpglulucf/
  gpglulucf.htm
• EFDB Emissions Factor Database
• http//www.ipcc-nggip.iges.or.jp/EFDB
• IPCC Inventory Software Revised 1996 IPCC
  Guidelines Software for the Workbook
• http//www.ipcc-nggip.iges.or.jp/public/gl/softwar
  e.htm
• Subsidiary Body for Implementation (SBI)
• http//maindb.unfccc.int/library
• Subsidiary Body for Scientific and Technological
  Advice (SBSTA)
• http//maindb.unfccc.int/library

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Definition of Key Terms

• LUCF (Land-Use Change and Forestry) Land use is
  the type of activity being carried out on a unit
  of land, such as forest land, cropland and
  grassland. The IPCC 1996GL refers to sources and
  sinks associated with GHG emissions/removals from
  human activities, which
• Change the way land is used (e.g., clearing of
  forest for agriculture, conversion of grassland
  to forest)
• Affect the amount of biomass in existing biomass
  stocks (e.g., forest, village trees, savanna) and
  soil carbon stocks
• LULUCF (Land Use, Land-Use Change and Forestry)
  This includes GHG emissions/removals resulting
  from managed land (involving no change in use,
  such as forest remaining forest land) and
  land-use changes (involving changes in land-use,
  such as grassland converted to forest land or
  forest land converted to cropland).

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Definitions

• Source Any process or activity that releases a
  GHG (such as CO2 and CH4) into the atmosphere. A
  carbon pool can be a source of carbon to the
  atmosphere if less carbon is flowing into it than
  is flowing out of it.
• Sink Any process, activity or mechanism that
  removes a GHG from the atmosphere. A given pool
  can be a sink for atmospheric carbon if during a
  given time interval more carbon is flowing into
  it than is flowing out of it.

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Definitions

• Activity data Data on the magnitude of human
  activity, resulting in emissions/removals taking
  place during a given period of time (e.g., data
  on land area, management systems, lime and
  fertilizer use).
• Emission factor A coefficient that relates the
  activity data to the amount of chemical compound,
  which is the source of later emissions.
  Emission/removal factors are often based on a
  sample of measurement data, averaged to develop a
  representative rate of emission or removal for a
  given activity level under a given set of
  operating conditions.
• Removal factor Rate at which carbon is taken up
  from the atmosphere by a terrestrial system and
  sequestered in biomass and soil.

10
Contribution and Role of LUCF sector to NAI GHG
emissions

• Examination of National Communications (examples)
  Argentina, Indonesia and Zimbabwe for 1994
• GHG inventories show that LUCF sector has a
  significant impact on national net CO2 equivalent
  emissions in developing countries
• Could be a significant source or sink of CO2
• LUCF sector is a net sink for Argentina and
  Zimbabwe
• Net source for Indonesia, which experienced
  forest land conversion of over one Mha
• Inclusion of LUCF sector in the inventory had the
  following impact on GHG emissions
• Argentina Emissions of 119 Tg CO2 when LUCF
  excluded, but 84 TgCO2 when LUCF included
• Zimbabwe Source of 17 Tg CO2 when LUCF excluded,
  but a net sink of 45 TgCO2 when LUCF included
• Indonesia Emissions of 189 Tg CO2 when LUCF
  excluded, but 344 Tg CO2 when LUCF included.

11
Revised 1996 IPCC Guidelines

• Fundamental basis for inventory methodology
  rests upon two linked themes
• Flux of CO2 to/from atmosphere assumed to be
  equal to changes in C-stocks in existing biomass
  and soils
• Changes in C-stocks can be estimated by
  establishing rates of change in land use and
  practices that bring about change in land use
• Estimating C-stocks in land-use categories
• that are not subjected to change
• that are changed

12
Default Categories in IPCC 1996GL

• 5A. Changes in forest and other woody biomass
  stocks due to
• commercial management
• harvest of industrial roundwood (logs) and
  fuelwood
• establishment and operation of forest plantations
• planting of trees in urban, village and
  non-forest locations
• 5B. Forest and grassland conversion
• the conversion of forests and grassland to
  pasture, cropland etc. can significantly change
  C-stocks in vegetation and soil
• 5C. Abandonment of cropland, pasture, plantation
  forests, or other managed lands
• 5D. CO2 emissions and removals from soils
• cultivation of mineral soils
• cultivation of organic soils
• liming of agricultural soils

13
Steps in Preparing Inventory Using IPCC 1996GL

• Step 1 IPCC 1996GL does not provide key category
  analysis approach. However, inventory experts are
  encouraged to conduct key category analysis using
  GPG2003 approach. Estimate the share of LUCF
  sector to national GHG inventory
• Step 2 Select the land-use categories
  (forest/plantations), vegetation types subjected
  to conversion (forest and grassland), changes in
  land-use/management systems (for soil carbon
  inventory)
• Step 3 Assemble required AD, depending on tier
  selected, from local, regional, national and
  global databases, including EFDB

14
Steps (IPCC 1996GL)

• Step 4 Collect EF/RF, depending on tier level
  selected, from local/regional/national/global
  databases, including EFDB
• Step 5 Estimate GHG emissions and removals
• Step 6 Estimate uncertainty involved
• Step 7 Report GHG emissions/removals
• Step 8 Report all procedures, equations and
  sources of data adopted for GHG inventory
  estimation

15
GPG2003 LULUCF Land-use Categories and Methods

• GPG2003 adopted two major advances overIPCC
  1996GL, namely
• Three hierarchical tiers of methods
• they range from use of default data and simple
  equations to use of country-specific data and
  models to accommodate national circumstances
• Land-use-category-based approach for organizing
  methodologies
• land-use categories Adopted six land categories
  to ensure consistent representation, covering all
  geographic areas of a country.
• Forest land, cropland, grassland, wetland,
  settlements and others
• Each land-use category is further disaggregated
  to reflect the past and the current land use
• Forest land remaining forest land
• Lands converted to forest land

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CO2 Pools, Non-CO2 Gases and Sources of Non-CO2
Gases

• CO2 and non-CO2 trace gases
• CO2 emissions and removal are estimated for all
  the C-pools namely
• Above-ground biomass
• Below-ground biomass
• Soil carbon
• Dead organic matter and woody litter
• Non-CO2 gases estimated include
• CH4, N2O, CO and NOx
• Sources of non-CO2 gases
• N2O and CH4 from forest fires
• N2O from managed (fertilized) forests
• N2O from drainage of forest soils
• N2O and CH4 from managed wetland
• Soil emissions of N2O from land-use conversion

17
Broad Approach and Steps in Adopting GPG2003
LULUCF

• Accounts for all land-use categories and
  sub-categories, all carbon pools and non-CO2
  gases, depending on key source/sink category
  analysis
• Select nationally adopted land-use classification
  system (categories and sub-categories) for
  inventory estimation. Each land category is
  further subdivided into
• land remaining in the same category (e.g. forest
  land remaining forest land)
• other land category converted to this land
  category (e.g. grassland converted to forest
  land)
• Select appropriate land classification system
  most relevant to country
• Conduct key source/sink category analysis to
  identify the key
• land categories and sub-categories
• non-CO2 gases
• carbon pools

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Steps to Adopting GPG

• Select appropriate tier level for key land
  categories and sub-categories, non-CO2 gases and
  carbon pools, based on key category analysis as
  well as resources available for the inventory
  process
• Assemble required AD, depending on tier selected,
  from regional, national and global databases
• Collect EF/RF, depending on tier selected, from
  regional, national and global databases, forest
  inventories, national greenhouse gas inventory
  studies, field experiments and surveys and use of
  EFDB
• Select method of estimation (equations), based on
  tier level selected, quantify emissions/removals
  for each land-use category, carbon pool and
  non-CO2 gas. Adopt default worksheet provided in
  GPG2003
• Estimate uncertainty
• Adopt QA/QC procedures and report results
• Report GHG emissions and removals using the
  reporting tables
• Document and archive all information used

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Features of Land Category Based Approach Forest
Land

• Estimates carbon stock changes and GHG
  emissions/removals associated with changes in
  biomass and soil organic carbon on forest land
  and lands converted to forest land
• Forest land remaining forest
• Land converted to forest
• Provides methodology for five carbon pools
• Links biomass and soil carbon pools for the same
  land areas (at higher tiers)

20
Features of Land Category Based Approach
Cropland

• Provides methods for estimating carbon stock
  changes in living biomass, mineral soils and in
  organic soils
• Provides methods for estimating annual N2O
  emissions from mineral soils due to addition of N
  (in the form of fertilizer, manure and crop
  residue) and N released by soil organic matter
  mineralization
• These categories are estimated and reported in
  agriculture sector in IPCC 1996GL

21
Features of Land Category Based Approach
Grassland

• Provides methodology for estimating carbon stock
  changes in living biomass and soils in grassland
  and lands converted to grassland
• Estimates annual change in carbon stocks in
  living biomass and soil carbon (mineral soils and
  cultivated organic soils) in grassland remaining
  grassland and lands converted to grassland
• Provides methodology for estimating non-CO2
  emissions from vegetation fires based on area of
  grassland burnt, mass of available fuel,
  combustion efficiency and emission factor for
  each GHG from grassland remaining grassland and
  land converted to grassland

22
Features of Land Category Based Approach
Wetlands

• The GHGs estimated include CO2, CH4 and N2O
• Methodology for estimating GHGs for wetlands
  remaining wetlands is given in the Appendix and
  for GHGs from lands converted to wetlands in
  the main text
• Estimates changes in carbon stocks in lands
  converted to wetlands due to peat extraction and
  land converted to flooded land
• Estimates N2O emissions from peatland drainage
  and flooded land and CH4 emissions from flooded
  land

23
Features of Land Category Based Approach
Settlements and Other Land

• Settlements
• Provides methodology for estimating CO2 emissions
  and removals for lands converted to settlements
  and methodology is given in Appendix for
  settlements remaining settlements
• Methods for estimating Annual change in carbon
  stocks in living biomass in forest lands
  converted to settlements based on area of land
  converted and carbon stock in living biomass
  immediately before and after conversion to
  settlements
•  Other land
• Changes in carbon stocks and non-CO2
  emissions/removals need not be assessed for
  category of other land remaining other land
• Methodology provided for estimating annual change
  in carbon stocks in land converted to other
  land based on estimates of change in carbon
  stocks in living biomass and SOC

24
Key Source/Sink Category Analysis

• One that is prioritized within national
  inventory system because its estimate has
  significant influence on a countrys total
  inventory of direct GHGs in terms of absolute
  level of emissions (removals), the trends in
  emissions (or removals), or both
• A land-use system or C-pool or non-CO2 gas is
  significant if its contribution to GHG
  emissions/removals is gt2530 of overall
  national inventory or overall LUCF sector
  inventory.
• The term key category is used to represent both
  sources and sinks
• Key category analysis helps a country to achieve
  highest possible levels of certainty while using
  the limited resources available for the inventory
  process efficiently

25
Key Source/Sink Category AnalysisGPG2003 Approach

• GPG2003 assists Parties in identifying the key
• land categories (e.g. forest land, cropland,
  etc.)
• gases (CO2, CH4 and N2O)
• carbon pools (living biomass, dead organic matter
  and soil organic carbon)
• The decision trees given in GPG2003 could be
  adopted
• Decision trees at two levels of disaggregation
• Land remaining in the same land-use category
  (e.g. forest land remaining forest land)
• Land converted to another land-use category (e.g.
  grassland converted to forest)

26
Tier Structure Selection and Criteria

• GPG2003 provides users with three methodological
  tiers for estimating GHG emissions/removal for
  each source.
• The three tiers defined in GPG2003 nearly
  correspond to the three levels of complexity
  given in IPCC 1996GL (not referred to as tiers)
• Tiers correspond to a progression from use of
  simple equations or methods with default data to
  country-specific data in more complex national
  systems
• Tiers implicitly progress from least to greatest
  levels of certainty in estimates as a function
  of
• Methodological complexity
• Regional specificity of model parameters
• Spatial resolution and extent of activity data

27
Combination of Tiers

• NAI experts could adopt multiple tiers in the GHG
  inventory for LULUCF sector
• for different land-use categories
• within a given land-use category for different
  carbon pools
• within a carbon pool, for activity data and
  emission factor
• Adopt higher tiers for key categories and
  wherever possible use country-specific, climatic
  region-specific emission/removal factors

28
Comparison Between IPCC 1996GL and GPG2003
29
Key Activity Data Required for GPG2003 and IPCC
1996GL
30
Key Emission Factors Required for GPG2003 and
IPCC 1996GL

• Number of emission factors common to both
• Above-ground biomass growth rate, biomass
  density
• Above-ground biomass stock, soil carbon density
• Fraction of biomass left to decay

31
Rationale for Adopting GPG2003
32
Reporting of GHG Inventory in the LUCF Sector
IPCC 1996GL
33
Reporting of GHG Inventory in the LUCF Sector
GPG2003
34
Mapping/Linkage BetweenIPCC 1996GL and GPG2003

• GPG2003 based on land-use category approach,
  provides a procedure to link inventory estimates
  of GPG2003 to IPCC 1996GL, based on Category 5A
  to 5D
• However, the inventory estimates obtained using
  IPCC 1996GL could be different from the estimates
  obtained using GPG2003 due to the following
  reasons
• Inclusion of additional land categories, e.g.
  agro-forestry, coconut, coffee, tea
• Inclusion of additional carbon pools
  below-ground biomass, dead organic matter, etc.
• Estimation of biomass increment and losses in
  each land category, sub-category
• Linking of biomass and soil carbon for each land
  category
• Use of improved default values

35
Methodological Issues/Problems in GHG Inventory
Using IPCC 1996GL

• Compatibility of IPCC 1996GL land categories to
  national classification
• High uncertainty of inventory, AD and EF
• Lack of disaggregated data, particularly on
  vegetation types
• Lack of clarity for reporting estimates of
  emissions/removal in managed natural forest
• Lack of consistency in estimating/reporting total
  biomass or only above-ground biomass
• Lack of methods for below-ground biomass and for
  incorporating non-forest areas, such as coffee,
  tea, coconut, cashew nut
• Difficulty in differentiating managed
  (anthropogenically impacted) and natural forests
• Ambiguity in terminology, e.g. forest,
  afforestation, reforestation, managed forest
• Complexity of the methodology

36
Methodological IssuesGPG2003 Approach and
Suggested Improvements
37

• Issue Lack of compatibility of IPCC land/forest
  category/vegetation types/systems/formats and
  national circumstances or classification of
  forests

38

• Issue High uncertainty in inventory estimation

39

• Issue Lack of consistency in estimating/reporting
  total biomass or only above-ground biomass

40

• Issue Methods for below-ground biomass not
  provided in default approach
• Issue Estimation (or differentiation) of managed
  (anthropogenically impacted) and natural forests

41

• Issue Lack of methods for savanna/grassland
• Issue Lack of methods for incorporating
  non-forest areas, such as coffee, tea, coconut,
  cashew nut, as well as ambiguity about
  agro-forestry

42

• Issue Absence of linkage between biomass and
  soil carbon
• In IPCC 1996GL changes in stocks of biomass and
  soil carbon are estimated in different worksheets
  and are not linked

43
Problems Relevant to Activity Data and Emission
Factors GPG2003 Approach and Suggested
Improvements
44
Examples of Problems Relevant to AD and EF
45
GPG2003 Approach

• To minimize the uncertainty involved in inventory
  estimation originating from activity data and
  emission factors, the GPG2003 has provided
  multiple approaches.
• Key source/sink category analysis enables
  focusing of inventory efforts on the identified
  key source/sink categories, incorporating AD and
  EF
• Three-tier approach for choice of AD and EF
• Additional default values for emission and
  removal factors
• Provision of improved sources of data, including
  EFDB

46
Improvements for the Future

• Non annex-I Parties may have to
• Initiate dedicated inventory programs
• Provide infrastructural and technical support for
  sustained inventory process
• This may involve
• Organizing periodic forest inventories
• Satellite or remote-sensing-based land-use maps
• Development of nationally relevant
  emission/removal factors
• Likely that many countries lack resources needed
  to initiate satellite-based monitoring
• Obtain satellite maps from institutions such as
  FAO, UNEP and NASA and undertake ground truthing

47
Changes in Forest and Other Woody Biomass Stocks

• Worksheet 5.1

48
Steps

• Step 1 Estimate total biomass carbon uptake by
  using area under different plantations/forests
  (AD) and annual biomass growth rate (removal
  factor)
• Step 2 Estimate total biomass consumption by
  adding commercial harvest, fuelwood consumption
  and other wood use
• Step 3 Estimate the net carbon uptake or release
  by deducting the consumption or loss from total
  biomass carbon uptake

49
Methodological Issues or Problems, Relevant to 5A
Category

• Lack of compatibility of IPCC land/forest
  category/vegetation types/systems/formats and
  national circumstances or classification of
  forests
• Lack of clarity for reporting estimates of
  emissions/removals in managed natural forest
• Lack of consistency in estimating/reporting total
  biomass or only above-ground biomass
• Methods for below-ground biomass not provided in
  default approach
• Estimation (or differentiation) of managed
  (anthropogenically impacted) and natural forests
• Lack of methods for incorporating non-forest
  areas, such as coffee, tea, coconut, cashew nut
• Carbon pools There are five carbon pools. The
  default method of IPCC 1996GL
• Estimates only the living biomass (above-ground
  biomass) because below-ground biomass stock is
  assumed to remain stable
• Assumes dead biomass stock to remain unchanged

50
Issues Relating to AD and EF, Relevant to 5A
Category

• Lack of availability of disaggregated data
• Lack of data on non-forest/fruit trees
• Lack of data on biomass/fuelwood/charcoal
  consumption data
• Lack of data on biomass growth rate for different
  vegetation types

51
Approach to Addressing Issues Relating to
Activity Data for LUCF Category 5A
52
Approach to Addressing Issues Relating to
Activity Data
53
Combining Tiers

• Inventory experts could adopt different tiers for
  different activity data
• Party could use Tier 2 for activity data on area
  of forest/plantations, while using Tier 1 for
  commercial harvest and traditional fuelwood with
  data from FAO Yearbook of Forest Products
• Inventory experts could use different tiers for
  activity data and emission factors
• Tier 2 for area of forest/plantations (AD) and
  Tier 1 for annual growth rate of above-ground
  biomass (EF)

54
Emission/Removal Factors

• The key emission/removal factors include
• annual biomass growth rate, carbon fraction of
  dry matter, biomass expansion ratio
• Biomass Expansion Ratios (BERs) as given in IPCC
  1996GL are required to convert commercial
  roundwood harvested biomass (in m3) to total
  above-ground biomass (in tonnes)
• Similarly, AGBBGB ratio is required to estimate
  BGB using data on AGB and the conversion ratio,
  according to GPG2003.
• Combining tiers Inventory experts could adopt
  different tiers for different emission factors

55
Approach to Addressing Issues Relating to
Emission/Removal Factors
56
Sources of AD
57
Sources of EF/RF
58
Assessment of Emission Factors and Strategy for
Improvement

• To reduce uncertainty, it is desirable to use
  nationally derived AD and EF at as disaggregated
  level as possible
• Example Annual growth rate (AGR) of biomass is
  mean annual above-ground biomass growth rate
  expressed in t/ha/year. AGR varies with
• Forest or vegetation or plantation types (e.g.
  evergreen/ deciduous/eucalyptus)
• Climatic region based on latitude and rainfall
  (e.g. humid, sub-humid, semi-arid, arid)
• Age of the forest or plantation stand
• Management system or silvicultural practice (e.g.
  thinning, fertilizer application, fire management)

59
Default Values Currently Available for AGR IPCC
1996GL

• AGR for natural regeneration
• Tropical and temperate
• By continent Africa, Asia and America
• Forest type Moist, seasonal and dry
• Age 0-20 and 20 to 100 years
• AGR for plantations
• Tropical Acacia, Eucalytpus, Tectona, Pinus,
  mixed hardwoods, mixed softwoods
• Temperate fir and pine
• Assessment
• Very few categories only 5 plantation types
• Single value for natural regeneration (e.g. 11
  t/ha/year for moist forests)
• Single value for plantations (e.g. eucalyptus
  14.5 t/ha/year for tropical region)
• The coarse categories and global AGR not likely
  to match national or sub-national circumstances
• High uncertainty likely

60
Default Values Currently Available for AGR
GPG2003

• AGR for natural regeneration
• Latitude tropical, temperate, boreal
• Continents Africa, Asia, America
• Age class lt 20 years and gt 20 years
• Rainfall range (mm/yr) gt2000, 100-2000, lt 1000
• AGR for plantations
• Continents Africa, Asia, America
• Species eucalyptus, pines and other for Africa,
  two categories for Asia and four categories for
  America
• Rainfall range class as above (four categories)
• Range and mean given
• Assessment
• AGR values are within a short range
• Multiple values are available only for eucalyptus
  and pine
• Very limited or absence of values for natural but
  managed forests, secondary forests, different
  forest types
• Values for eucalyptus range from 10 to 60
  m3/ha/year
• Generally default AGR values are all in the
  higher range

61
Short-term Strategy for Improving AGR Values

• Disaggregate the land use, forest or vegetation
  types occurring in the country at as fine a level
  as possible along the following lines or using
  other more nationally relevant stratification
• Different forest types / vegetation types /
  plantations
• Latitude tropical, temperate, boreal
• Rainfall zone (mm/yr) humid (gt2000), semiarid
  (500-1000), arid (lt500)
• Age of the stand 0-5 yr, 5 to 10 yr, 10-20 yr, gt
  20yr
• Management system naturally regenerated or
  planted
• Other category
• Allocate area of different forest
  types/plantations in the country, using forest
  map, rainfall zone map, soil map and other
  statistical information

62
Short-term Strategy

• Check IPCC 1996GL, GPG2003, EFDB and other global
  sources and select the closest default values
• Check if any national forest Inventory studies
  are available (many NAI Parties have them) and
  collect the growth rate data
• Review the national and international literature
  (web sites of FAO, CGIAR centers, universities,
  books and reports
• Compile all the default values available from
  national and international sources for the
  disaggregated or stratified forest/plantation
  types
• Select the most appropriate AGR for each stratum
  of the forest/plantation types

63
Long-term Strategy for Improving AGR Values

• Initiate national forest inventory studies
• Disaggregate/stratify the forest/plantation types
• Adopt sampling technique as explained in GPG2003
  (Chapter 3 and 4)
• Adopt permanent plots with proper boundaries
  marked for periodic revisits
• Refer to any text book on forest mensuration or
  web sites such as www.winrock.org, www.cifor.org,
  etc., for methods of measurement and estimation
• Estimate the standard deviation or variance

64
IPCC Inventory Software

• Provides a Microsoft Excel based approach where
  AD and EF/RF data can be input to obtain net
  annual carbon uptake/release 
• The key features or limitations in using the
  software are
• The names or type of forest/plantation category
  in a country may be different from the categories
  defined in the IPCC software
• The IPCC software can be changed to nationally
  relevant categories (e.g. Acacia spp. can be
  changed to other spp.)
• Names of categories, used in the column, are not
  included in the calculation procedure of the
  worksheets, and thus can be easily changed
• Forest/plantation categories Option exists for
  18 categories, which is a limitation if a country
  has more than 18 categories
• If the number of forest/plantation categories is
  more than provided
• Option 1 Insert additional rows only if the
  inventory expert has capacity to modify the
  macros
• Option 2 Merge smaller or homogeneous categories
  such that the total number of rows (or
  categories) is not gt18.

65
Illustration of Inventory Software IPCC 1996GL
66
Worksheet for Estimating Total Carbon Uptake
GPG2003
67
Forest and Grassland Conversion (5B)

• Worksheet 5.2

68
Steps for 5B

• Step 1 Estimate annual loss of biomass due to
  conversion
• Step 2 Estimate quantity of carbon released from
  fraction of biomass burnt on-site
• Step 3 Estimate quantity of carbon released from
  fraction of biomass burnt off-site
• Step 4 Estimate carbon released from decay of
  above-ground biomass
• Step 5 Estimate total annual CO2 release from
  burning and decay of biomass, resulting from
  forest and grassland conversion

69
Issues in Estimating CO2 Emissions from Biomass
Forest and Grassland Conversion

• Lack of compatibility between IPCC 1996GL
  vegetation types and national circumstances or
  classification
• Absence of forest and grassland conversion data
  for the inventory year as well as the 10-year
  average
• Lack of methods for savanna/grassland burning
• Lack of disaggregated activity data on biomass
  stock before and after conversion
• Lack of clarity on fraction of biomass burnt
  on-site, off-site and left to decay
• Biomass burnt for energy is reported in the
  energy sector

70
Approach for Addressing Issues Relating to
Activity Data
71
Approach for Addressing Issues Relating to
Emission Factors
72
Approach to Emission Factors
73
Sources of AD
74
Sources of EF
75
Abandonment of Managed Lands

• Worksheet 5C

76
Estimation Procedure

• Step 1 Estimate the annual carbon uptake in
  above-ground biomass, using the area abandoned
  (during the previous 20 years) and annual biomass
  growth
• Step 2 Estimate the total carbon uptake from
  area abandoned (during 20100 years) and annual
  growth rate
• Step 3 Estimate the total C-uptake from
  abandoned land (Step 1 Step 2)

77
Issues in Estimating CO2 Uptake from Abandonment
of Managed Lands

• Lack of compatibility between vegetation types
  given in IPCC 1996GL and national classification
  for abandoned land
• Lack of methods to identify managed land
  abandoned and regenerating
• according to different vegetation types
• for the past 20 years and 20100 years
• Absence of annual data for above-ground biomass
  growth for abandoned land
• according to different vegetation types
• for the past 20 years and 20100 years

78
Approach to Addressing Issues Relating to
Activity Data and Sources of Data
79
Approach to Addressing Issues Relating to Removal
Factor and Source of Data
80
CO2 Emissions and Removals from Soils

• 5D and Worksheet 5-5

81
Steps for 5D

• Step 1 Changes in soil carbon for mineral soils
• Step 2 Carbon emissions from intensively managed
  organic soils
• Step 3 Carbon emissions from liming of
  agricultural soils

82
Issues in Estimating CO2 Emissions/Removals from
Abandonment of Managed Lands

• Absence of linkage between biomass carbon and
  soil carbon for different land categories or
  vegetation types
• Ambiguity in classification of land-use and
  management systems, and soil types
• Absence of activity data on land area under
  different conditions
• land-use/management systems
• soil type
• for periods t (inventory year), and t-20
• intensively managed organic soils
• Absence of emission factors such as soil carbon
  in mineral soils and annual loss rate of carbon
  in managed organic soils

83
Approach to Addressing Issues Relating to
Activity Data
84
Approach to Addressing
85
Approach to Addressing Issues Relating to
Emission/Removal Factors
86
Approach to Addressing
87
Sources of Activity Data
88
Sources of Emission/Removal Factors
89
Other Categories

• Harvested wood products (HWP), wetlands and other
  sources/sinks
• Default assumption of IPCC 1996GL is that
• carbon removed in wood and other biomass from
  forests is oxidized in the year of harvest
• Countries may report on HWP pools, if they can
  document that existing stocks of forest products
  are in fact increasing
• GPG2003-Appendix provides guidance on
  methodological issues for accounting emissions
  and removals from HWP

90
Uncertainty Estimation and Reduction

• The good practice approach requires that
  estimates of GHG inventories be accurate
• They should neither be over- nor underestimated
  as far as can be judged
• Causes of uncertainty could include
• unidentified sources and sinks
• lack of data
• quality of data
• lack of transparency

91
Uncertainty Analysis

• Uncertainty analysis involves
• Identifying types of uncertainties
• measurement error, lack of data, sampling error,
  missing data, model limitations, etc.
• Methods for reducing uncertainties
• improving representativeness, using precise
  measurement methods, correct statistical
  sampling, etc.
• Quantifying uncertainties
• sources of data and information, techniques for
  quantifying uncertainty
• Methods to combine uncertainties (simple
  propagation of errors and Monte Carlo analysis)
• Estimates of C-stock changes, emissions and
  removals arising from LUCF activities have
  uncertainties associated with
• Area related and other activity data, biomass
  growth rates, expansion factors, biomass loss or
  consumption, soil carbon density, etc.

92
Methods of Estimating and Combining Uncertainties
GPG2003

• Two methods
• Simple propagation of errors (Tier 1)
• Monte Carlo analysis (Tier 2)
• Use of either Tier 1 or Tier 2 provides insight
  into how individual categories and GHGs
  contribute to uncertainty in total emissions in a
  given year
• Tier 1 and Tier 2 methods of assessment of
  uncertainty are different from methods or Tiers
  (1 to 3) of inventory estimation.
• Tier 1 methods
• Uncertainty associated is high as suitability of
  available default parameters to a countrys
  circumstances is not known
• Application of default data in a country or
  region that has different characteristics from
  those of the source of data leads to large
  systematic errors

93
Methods of Estimating (Tier 2)

• Country-specific data are used
• Data often only broadly defined
• with very little stratification according to
  climate/management/soil/land use
• Possible to assess uncertainties involved due to
  the national circumstances, based on a few
  national-level studies or direct measurements
• Uncertainty is moderate compared to Tier 1
• Statistical packages are readily available for
  adopting Monte Carlo algorithm

94
Quality Assurance and Quality Control

• Quality Control or QC is a system of routine
  technical activities to measure and control the
  quality of inventory as it is being developed
• It is designed to
• Provide routine and consistent checks to ensure
  data integrity, correctness and completeness
• Identify and address errors and omissions
• Document and archive inventory material and
  record all QC activities
• Quality Assurance or QA is a planned system of
  review procedures conducted by personnel not
  directly involved in the inventory
  compilation/development process

95
QC Tier 1

• Tier 1 general methods focus on processing,
  handling, documenting, archiving and reporting
  procedures
• QC procedure involves the following
• Check integrity of database files
• Confirm appropriate data processing steps are
  correctly represented in the database
• Confirm data relationships are correctly
  represented in the database
• Ensure that data fields are properly labeled and
  have correct design specifications
• Ensure adequate documentation of database and
  model structure

96
QC Tier 2

• Tier 2 procedures are directed at specific types
  of data used in the methods and require knowledge
  of
• source/sink category
• type of data available
• parameters associated with emissions/removals
• Tier 2 QC procedure focuses on the following
  checks
• Check that land areas are properly classified and
  that no double counting or omissions have
  occurred
• Ensure completeness of source/sink categories
• Check consistency of time series activity data
• Check sampling and extrapolation protocols
  adopted

97
QA Tier 1 and Tier 2

• Requires an expert review to assess the quality
  of inventory and identify areas where
  improvements are necessary
• Tier 1
• Involves basic expert peer review by inventory
  agencies
• Apply review process to all source/sink
  categories, particularly the key categories
• Tier 2
• Involves expert peer review, which includes
• review of calculations or assumptions
• identification if major models used have
  undergone peer review
• assessment of documentation of models, input data
  and other assumptions

98
Emission Factor Database

• EFDB is an online database
• It is continuously updated with data that are
  reviewed by a panel of experts
• It is menu driven and user friendly
• It requires use of Internet Explorer version 5.0
  or Netscape Navigator version 6.0 or higher
  coupled with Microsoft Office 97 for generating
  outputs in MS Word or Excel
• It has multiple options, such as
• Step-by-step search using IPCC source/sink
  category and gas
• Full text search using key words
• Find emission factor using unique ID
• Results are displayed along with the following
  details
• EF ID, gas, description, technologies/practices,
  parameters/conditions, region/regional
  conditions, abatement/control technologies, other
  properties, value, unit, data provider, source of
  data

99
Steps Involved in Using EFDB

• Step 1 Selection of the sector, e.g. LUCF (5)
• Step 2 Selection of gases, e.g. CO2, CH4
• Step 3 Display of the results
• Step 4 Set the filter giving the conditions,
  such as gas, parameter/condition, region, etc.

100
LUCF Status EFDB (2004 Aug.)

• The EFDB is an emerging database, initiated in
  2002
• EFDB expects all experts to contribute to the
  database
• Currently, limited information for LUCF sector
  emission factors.
• In future, with contribution from experts around
  the world, EFDB is likely to become a reliable
  source of data for emission/removal factors for
  GHG inventory

101
Conclusions and Strategy for the Future

• NAI experts and compilation and synthesis reports
  by UNFCCC have identified a number of issues and
  problems in using IPCC 1996GL, including
• Lack of clarity in the methods and inadequacies
  of the methods
• Lack of AD and EF
• Low quality or reliability of AD and EF
• High uncertainty of AD and EF, leading to
  uncertainty in inventory estimates
• Non-suitability

102
GPG2003 Approach

• GPG2003 meant to overcome some of the
  methodological issues/problems identified in
  using IPCC 1996GL
• Suggests methods to reduce uncertainty
• Suggests an improved land category and full
  carbon (and non-CO2 gases) estimation based
  approach and methods
• Adoption of GPG2003 approach will lead to
• full and consistent representation, consideration
  and reporting of all land categories
• full carbon (all 5 C-pools) estimation
• reduced uncertainty
• efficient use of limited inventory resources