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

2. Background IPCC 1996 Guideline
IPCC guidelines used by >131 NAI Parties to prepare National Communications.
New UNFCCC guidelines adopted at COP8 (17/CP.8)
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
IPCC, 2006 Guideline for GHG inventory has been accepted by IPCC Panel and COP will decide about its application
IPCC, 2006 for land-based sectors is based on GPG principles
COP – Conference of the Parties
IPCC – Intergovernmental Panel on Climate Change
NAI – Non-Annex I (NAI Parties are Parties not included in Annex I to the Convention)
1996GL – Revised 1996 IPPC Guidelines for National Greenhouse Gas Inventories
GPG – IPCC Good Practice Guidance

3. LUCF sector related issues for African region
LUCF sector is critical for most African countries, given low energy consumption
Many countries have large area under forests and grassland plus presence of Savannah
IPCC, 1996 GL; not consistent in representing Savannah land and other land categories
Large dependence on forests for fuelwood & charcoal
Occurrence of Forest conversion to cropland & other categories
Majority of countries having data limitations
Land use statistics / Activity Data
Emission / Removal factor

5. Forest Conversion/Loss in Africa (ha)
6 of the top 10 countries experiencing forest conversion/loss
are from Africa
Sudan
589,000
Zambia
445,000
Tanzania
412,000
Nigeria
410,000
Congo
319,000
Zimbabwe
313,000

6. GHG Emissions – Africa (Gg)

8. 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
GHG inventory is prepared for energy, industrial process, agriculture, LUCF and waste sectors. Inventory in the biological sectors, such as agriculture and LUCF, is likely to have higher uncertainty due to:
Inadequacy of the methods, high variation in the emission seq. factors (e.g., the growth rate of eucalyptus could vary from location to location)
Lack of activity data (e.g., the area under different forest types is not available for most countries) and it also varies from year to year due to deforestation and afforestation
Lack of EF/RF (e.g., the above-ground biomass growth rate of different forest types is not available for most countries and it varies with disturbance, management practices, age, etc.)
High uncertainty is a feature of biological systems, due to variation in the parameters linked to climate, soil, vegetation type and management practices.
IPCC methodology, particularly the default approach and methods, are provided to assist Parties in preparing comparable inventories. The main goal is to increase accuracy and reduce uncertainty by improving consistently in the methods as well as the data. The IPCC has prepared GPG to assist Parties in reducing uncertainty by providing multiple and improved methods.
In this presentation, an attempt is made to provide information to enable Parties to shift to GPG2003 in the LUCF sector. GPG2003 provides three tiers, where shifting from T-1 to T-3 reduces uncertainty. The NAI Parties are encouraged to gradually shift to higher tiers. An attempt is made to assist NAI Parties in using the emerging EFDB. The AD and EF are assessed for each IPCC 1996GL category and further, the sources of AD and EF are given for the default method. The key source category analysis from GPG2003 is introduced, though it is not directly relevant to the IPCC 1996GL categories

9. 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, EF/RF, uncertainty analysis
Consider African region related LUCF inventory issues
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
Over 100 NAI Parties have used the IPCC 1996GL and in the process, they have encountered several problems, relating to methods, AD and EF. In this presentation, an attempt is made to address problems faced by NAI Parties with respect to methods, AD and EF.
One of the most important approaches to reduce uncertainty is to adopt the GPG2003. However, GPG2003 will only contribute to reducing the methodological uncertainty.
Problems relating to AD and EF would remain. GPG2003 has attempted to give additional default data as well as some preliminary estimates of uncertainty. The approach adopted would involve the following
GPG2003 approach to overcome problems
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

10. 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
The presentation is organized along the following lines. The main aim is to assist NAI inventory experts to improve the GHG inventory in the LUCF sector. The organization of the presentation includes the following:
IPCC 1996GL and GPG2003 approach features and key steps are presented (Refer to respective guidelines for details)
The problems encountered by the NAI inventory experts are assessed and options to overcome them are presented
Issues relevant to AD and EF and potential sources of AD and EF (including EFDB) are presented.

11. Background Resources
Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
GPG2000 – Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
GPG2003 – Good Practice Guidance for Land Use, Land-Use Change and Forestry
EFDB – Emissions Factor Database
IPCC Inventory Software – Revised 1996 IPCC Guidelines; Software for the Workbook
Subsidiary Body for Implementation (SBI)
Subsidiary Body for Scientific and Technological Advice (SBSTA)
This presentation is based on multiple resources, namely the following:
Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
GPG2000 – Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
GPG2003 – Good Practice Guidance for Land Use, Land-Use Change and Forestry
EFDB – Emissions Factor Database
IPCC Inventory Software – Revised 1996 IPCC Guidelines; Software for the Workbook
Subsidiary Body for Implementation (SBI)
Subsidiary Body for Scientific and Technological Advice (SBSTA)

12. 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).
After definitions, the focus of LUCF guidelines is on forest land, grassland and agriculturally impacted soils. LULUCF is a broader term which according to GPG2003 covers all the six land-use categories – forest, grassland, cropland, wetland, settlement and others. The focus is on land remaining in the same category of land, as well as land that is subjected to change from one land use to another.

13. 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.
Source – Definition
- A unit of land becomes a source when it is subjected to any anthropogenic disturbance, such as land-use change, disturbance to soil, harvest of trees, fire, etc.
Sink – Definition
- A sink results when there is an increase in the C-density of biomass and/or soil resulting from growth.

14. 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.
Emission factor – Definition
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.
In the case of the LUCF sector, EF would include sequestration (removal factors) (e.g., AGB in t/ha), MAI or growth rate (t/ha/yr) as well as source (e.g., harvest, fire).
To obtain the emission of a GHG, AD is multiplied by the EF in the case of LUCF. If AD is multiplied by RF the estimate will give the carbon sink created.

15. Revised 1996 IPCC Guidelines

16. 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
5A – Estimates the CO2 emissions and removals resulting from growth and extraction. If the extraction is less than the growth in biomass stock, there will be net negative emissions, i.e. net removal. In this category, land areas subjected to land-use change are not included.
5B – In this category, CO2 emissions resulting from forest and grassland conversion are estimated. Non-CO2 emissions resulting from on-site burning of forests are also estimated.
5C – CO2 removals resulting from abandonment of managed land are estimated.
5D – CO2 emissions and removals from soils that are subjected to cultivation as well as liming practice are estimated.

17. 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
Step 1: Key category analysis
IPCC 1996GL does not provide key category analysis approach. However, inventory experts are encouraged to conduct key category analysis using GPG2003 approach.
Sector is compared to other source sectors, such as energy, agriculture, waste, etc.
Estimate share of LUCF sector to national GHG inventory
Key source/sink sector identification could be adopted by Parties that have already prepared initial National Communication or have GHG inventory estimates
Parties that have not prepared initial National Communication can use inventories prepared under other programs
Parties that have not prepared any inventory, may not be able to carry out the key source/sink sector analysis
Steps 2 to 4 are explained in later slides

18. 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
Steps 5 to 9 are explained in later slides

19. GPG2003 LULUCF Land-use Categories and Methods
GPG2003 adopted two major advances over IPCC 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
This slide explains the key advancements made in the GPG for LULUCF sector compared to the IPCC 1996GL.
The GPG also focuses on three tiers of methods. In the GPG, the methods are described for each land-use category and sub-categories.
GPG ensures inclusion of all geographical land area of a country. Each land category such as forest is further sub-divided into; forest land remaining forest land and land converted to forest. The default period for a land use to stay in the same category is 20 years. However, countries can adopt the most convenient land categorization approach relevant to that country.

20. CO2 Pools, Non-CO2 Gases and Sources of Non-CO2 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
This slide presents the CO2 pools and the non-CO2 gases for inventory as well as the sources of non-CO2 gases.
The selection of which CO2 pools and non-CO2 gases will depend on key source/sink category analysis.
The sources of non-CO2 gases are; forest fire, fertilizer application of forests, drainage of organic soils, management of wetlands and land-use conversion, that result in emissions.
It is important to note that all the carbon pools, and non-CO2 gases may not be relevant and need not be estimated for a country.

21. 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
In this and the following slide, steps for adopting GPG2003 LULUCF are presented.
GPG attempts to overcome some of the limitations of the IPCC 1996GL by accounting for all the land-use categories and sub-categories of a country as well as all the carbon pools relevant to the country.
The countries can use the nationally adopted land categorization approach, but it is necessary to account for all the land-use categories in the country.
Due to the limitations of time and resources the countries may have to adopt key source/sink category analysis so that the limited resources are focused on the identified key land categories, carbon pools and non-CO2 gases.

22. 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
This slide presents the steps to be adopted under the GPG, after identifying the key sources, carbon pool and non-CO2 gases. The next most critical step is to identify and adopt different tiers for different land categories, carbon pools, etc. Normally, higher tier (which is at a disaggregated level) is adopted for key land categories, carbon pools and non-CO2 gases. Adoption of higher tier requires nationally derived activity data and emission/removal factor as well as adoption of finer geographical scales
The activity data and emission/removal factors required, sources of data/factors, and the quality check are all explained in the later slides.

23. 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)
GPG2003 provides methods for estimating 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. It also provides methodology for five carbon pools and links biomass and soil carbon pools for same land areas at higher tiers.
Estimates annual increase in living biomass (AGB + BGB) carbon stocks, decrease in carbon stocks and net change in carbon stocks.
Estimates carbon stock change in deadwood, litter and net annual change in carbon stock in dead organic matter.
Estimates carbon stock change in mineral soils, organic soils and net annual change in carbon stock in soil.

24. 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
Provides methods for estimating carbon stock changes in cropland and N2O emissions from land-use conversions to cropland.
Estimates annual change in carbon stocks in living biomass based on: annual area of cropland with perennial woody biomass and annual growth rate of perennial woody biomass and deducting the harvest of biomass carbon.
Estimates annual change in carbon stocks in mineral soils based on: estimates of SOC stock at t year (default period is 20-years) and SOC in current inventory year.
Estimates annual change in carbon stocks in organic soils based on: estimates of land area under organic soils and emission factor for organic soils subjected to cultivation.
Estimates annual change in carbon stocks in living biomass, mineral soils and organic soils for different land categories converted to cropland.
Estimates annual emission of N2O from mineral soils due to addition of N (in the form of fertilizers, manures and crop residue) and N released by soil organic matter mineralization.

25. Features of Land Category Based Approach – Grassland / Savannah
Savannah / grassland are very critical for many African countries
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
Carbon stocks in grassland are influenced by human activities and natural disturbances, including harvesting of woody biomass, rangeland degradation, grazing, fires, rehabilitation, pasture management, etc. Below-ground biomass, including root biomass and soil organic matter, dominates the grasslands.
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.

26. 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
Includes land that is covered or saturated by water for all or part of the year, and that does not fall into forest and other categories. For GHG inventory, it is necessary to distinguish between managed and unmanaged 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 of GPG2003.
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 lands and CH4 emissions from flooded land.
Estimates annual change in carbon stocks in living biomass in lands converted to flooded land.

27. Features of Land Category Based Approach – Settlements and Other Land
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
GPG2003 provides preliminary methods for estimating CO2 and non-CO2 gases emissions/removals for settlements and other land.
Settlements
Includes all classes of urban tree formation and village trees.
Methods for estimating CO2 emissions and removals for “lands converted to settlements” are provided.
The methodology for estimating CO2 emissions for “settlements remaining settlements” is given in the Appendix.
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
Includes bare soil, rock, ice and all unmanaged land areas that do not fall into any other land-use categories.
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.
Changes in carbon stocks and non-CO2 emissions/removals need not be assessed for category of “other land remaining other land”.

28. Key Source/Sink Category Analysis
“One that is prioritized within national inventory system because its estimate has significant influence on a country’s 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 >25%–30% 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
According to GPG2000, a key source/sink category is “one that is prioritized within the national inventory system because its estimate has a significant influence on a country’s total inventory of direct GHGs in terms of absolute level of emissions (removals), the trends in emissions (or removals), or both”. Here the term key category is used to represent both the sources and sinks. Key category analysis helps a country to achieve highest possible levels of certainty while using limited resources for the inventory process. The decision about what tier to use and where to allocate resources for inventory improvement should take into account the key category analysis. Key category analysis is required to identify the following:
- Which land-use categories are critical
- Which sub-land category is significant
- Which carbon pools are significant
- Which non-CO2 gases are significant
A land-use system or a carbon pool or a non-CO2 gas is significant if its contribution to the GHG emissions/removals accounts for over 25% to 30% of overall national inventory or overall LUCF sector inventory. The key source/sink category analysis given in GPG2003 (which is land-use-category based) is not directly applicable to the categories used (5A to 5D) in IPCC 1996GL.
The key category analysis should be performed at the level of IPCC source or sink categories (i.e. at the level at which the IPCC methods are described).

29. Key Source/Sink Category Analysis GPG2003 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)
The key source category evaluation should be performed for each of the gases separately because the methods, emission factors and related uncertainties differ for each gas. For each key source category, the inventory agency should determine if certain sub-source categories are particularly significant (i.e. represent a significant share of the emissions). In the case of CO2 emissions/removals, a certain land category (say, land converted to forest land) and further a certain carbon pool (e.g. above-ground biomass) may contribute to a dominant share of net CO2 emissions/removals. A generic approach to key category analysis is given based on decision trees. Decision trees are given for selecting land, C-pools and non-CO2 among different land-use categories. As an illustration, decision trees are presented for:
Identification of appropriate tier level for land remaining in the same land-use category, e.g. forest land remaining forest land
Identify which land category is significant (forest land remaining forest land or grassland remaining grassland)
Which gas is significant (CO2 or CH4 or N2O)
Which carbon pool is significant (biomass or dead organic matter or soil carbon)
Identification of appropriate tier level for land converted to another land-use category, e.g. other land converted to forest land (same three categories as above: land category, gases and C-pools)

30. 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
IPCC 1996GL introduced 3 different levels of complexity and geographic scales at which national experts can work depending on importance of source/sink category and availability of data and other capabilities.
GPG2003 provides users with three methodological tiers for estimating GHG emissions/removals for each source. The three tiers defined by GPG2003 nearly correspond to three levels of complexity given in IPCC 1996GL (not referred to as ‘tier’).
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.
Regardless of tier level, countries need to document tiers used for various categories and carbon pools, EF and AD.
Countries with limited or no national level AD and EF tend to use Tier 1 methods where inventory estimation can be made using the default values.

31. 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
IPCC methodology provides options for using a single tier for different land categories, pools, etc. For example, a data-rich country can adopt the Tier 2 or Tier 3 approach. Further, IPCC methods also provide opportunity for adopting different tiers for different land categories, carbon pools and non-CO2 gases. Even within a pool, a Party can use Tier 2 for above-ground biomass and Tier 1 for below-ground biomass carbon. Similarly NAI experts could adopt Tier 2 for category 5A and Tier 1 for category 5B.
The general recommendation is to use higher tiers for key source/sink categories or carbon pools.
To reduce uncertainty, it is always desirable to use nationally derived AD and EF.

32. Comparison Between IPCC 1996GL and GPG2003
GPG2003 is an attempt to overcome the methodological limitations of IPCC1996GL. The basic approach is different from the IPCC 19996GL. The GPG approach aims at full and consistent estimation and reporting of all land areas and categories present in a country, particularly at higher tiers. Under this approach, it is possible to link biomass and soil carbon for each land-use category. In IPCC 1996GL, several land categories and land uses are not included in the default approach. GPG2003 is data intensive compared to IPCC 1996GL. GPG2003 provides methods for additional carbon pools as well as a three-tier approach to methods, AD and EF.

33. Reporting of GHG Inventory in the LUCF Sector – IPCC 1996GL
This is the Reporting Table for reporting GHG inventory in the LUCF sector according to IPCC 1996GL. Reporting is done according to the IPCC categories 5A and 5B. The CO2 emissions and removals are reported separately for the categories 5A to 5E. Only CO2 emissions are relevant to category 5B. Further, the trace gases are reported only for category 5B, where these gases are emitted during on-site burning of forests.

34. Reporting of GHG Inventory in the LUCF Sector – GPG2003
This tables provides the framework for reporting of GHG inventory for the LUCF sector, following the GPG2003 approach. Here, reporting is according to land categories and sub-categories and according to GHGs.
This table also attempts to provide linkage between reporting under GPG2003 and IPCC 1996GL. For example, row 5A.1 where CO2 emissions and removals are reported for forest land remaining forest land corresponds to category 5A of IPCC 1996GL.
It is important to note that there is no direct one-to-one correspondence between GPG2003 and IPCC 1996GL reporting categories.

35. Issues relevant to Ad & EF
IPCC 1996 guidelines
Categories 5A to 5b
Issues relevant to Ad & EF

36. Changes in Forest and Other Woody Biomass Stocks
Worksheet 5.1

37. 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
In this slide the key steps involved in estimating changes in forest and other woody biomass stocks are presented. Here forests and plantations, which are subjected to conversion or land-use change are not considered.
Step 1: Area under different and forest types from national sources or from FAO sources need to be obtained. The above-ground biomass growth rate for different forest and plantation types is needed. The area and biomass growth rate data are required at as disaggregated level as possible. Estimate the total growth in biomass for the inventory year.
Step 2: Loss of biomass due to extraction of biomass as commercial wood, fuelwood and other wood is estimated by using roundwood consumption data from national or FAO sources.
Step 3: Estimate the net carbon uptake by deducting loss or consumption of biomass from growth or increment in biomass. Convert biomass to carbon by multiplying with conversion factor (a default value of 0.5).

38. 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
This slide highlights the issues or problems faced by inventory experts in using category 5A. There are methodological as well as AD and EF problems.
Most countries have their own national classification of forests and plantations, which is often different from the IPCC categories.
Classification of managed forests is also a problem for many countries. Any forest is considered managed if subjected to any anthropogenic intervention.
There is lack of consistency on which biomass pools to be included; only above-ground biomass of commercial harvest or whole-tree biomass or inclusion of dead wood and below-ground biomass.
In many countries considerable area is under plantation crops, such as coffee, tea, coconut and cashew nut. Methodology for its inclusion is not given. Similarly, there is lack of clarity on inclusion of agro-forestry.

39. 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
Problems relevant to AD and EF are presented in this slide. The main problem relates to lack of AD as well as EF data.
Many Parties may not have data on area under different forest or plantation types. Data on non-forest trees are very limited. Further data may not be available for the inventory year. Often, data which is 10 or more years old are used.
Countries often use FAO data on roundwood consumption due to lack of detailed national sources.
Biomass growth rate data at a disaggregated level corresponding to each forest or plantation type are needed and may not be available.

40. Approach to Addressing Issues Relating to Activity Data for LUCF Category 5A
This slide presents approaches for addressing AD related problems under Tier 1, 2 and 3.
-         Tier 1: Refers to using, largely, default data from global data sources such as FAO
-         Tier 2: Refers to data largely from national sources
-         Tier 3: Refers to national sources at disaggregated and finer scale. Data may come from remote sensing.
The main source of AD for Tier 1 is FAO, which provides data on area under different forest and plantation types as well as on consumption or production of roundwood. Very often the area data available for a previous period may have to be extrapolated to the inventory year.

41. Approach to Addressing Issues Relating to Activity Data…
See explanation given for previous slide.

42. 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, AGB:BGB 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
The key emission factors for category 5-1 are listed in this slide. Biomass growth rate is the key EF. Growth rate data are required at as disaggregated level as possible.
BER or BEF is needed to convert commercial harvest, which includes only the main trunk and is expressed in m3. There is a need to convert the commercial harvest into whole tree volume, which includes tree crown, twigs, branches, etc. This volume (m3) has to be converted to tonnes using the density value.
Inventory experts could use different tiers for different EF, depending the importance of the EF and availability of data. It is always desirable to use higher tiers for as many EF as possible.

43. Approach to Addressing Issues Relating to Emission/Removal Factors
This slide presents approaches for obtaining different EF at Tier 1, 2 and 3. The Tier 1 approach involves depending largely on default data and global databases. Tier 3 involves sourcing EF values from forest inventory studies and other field studies.

44. Sources of AD
This slide provides sources for the AD for category 5A for different Tiers. Tier 1 is largely from global databases (such as FAO) and Tier 3 is from national remote sensing and land survey sources.

45. Sources of EF/RF
This slide presents the sources of EF/RF for category 5A for tiers 1 to 3. The data for Tier 1 are largely from IPCC 1996GL, GPG2003 and EFDB. Tier 3 values are obtained from periodic forest inventory studies.

47. Forest and Grassland Conversion (5B)
Worksheet 5.2

48. 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
In this slide, broad steps involved in estimating CO2 emissions from “forest and grassland conversion” are given. This worksheet estimates the total annual CO2 emissions from burning and decay of biomass, resulting from “forest and grassland conversion”. These steps reflect Worksheet 5.2 of IPCC 1996GL (see IPCC 1996GL for details).

49. 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
The problems and issues relevant to Worksheet 5.2 in estimating CO2 emissions from “forest and grassland conversion” are presented.
IPCC 1996GL provides a standard classification of vegetation types whereas countries have their own national systems of classification. Countries are welcome to change the names of vegetation types given in the Worksheet as well as in the inventory software.
A majority of the countries do not have data on area of different forest and grassland types converted during the inventory year. Very often, countries have to extrapolate data available for some previous time periods to the inventory year.
In many countries, savanna and grassland burning is a major activity leading to GHG emissions. The IPCC default methods are inadequate to estimate the emissions from savanna and grassland burning. There are inadequate data on the biomass stock before and after conversion for different land-use types.
There seems to be some confusion regarding the fraction of biomass burnt on-site and off-site and left to decay.

50. Approach for Addressing Issues Relating to Activity Data
This slide presents approaches for addressing each of the identified problems relating to key activity data. Methods and approaches for the identified AD are given separately for Tiers 1, 2 and 3.

51. Approach for Addressing Issues Relating to Emission Factors
This slide presents approaches and methods for addressing issues relating to the key emission factor – above-ground biomass before and after conversion for Tiers 1, 2 and 3.

52. Approach to Emission Factors…
This slide presents approaches and methods for addressing problems relating to some of the key emission factors. The methods and approaches for the identified EFs are given separately for Tiers 1, 2 and 3.

53. Sources of AD
In this slide, sources of activity data are given for area converted annually and average area converted over a 10-year period (10-year average). Very often countries do not have the area-converted data for the inventory year. Thus, the experts often use the data available for previous years.

54. Sources of EF
In this slide, the sources of data are given for the key emission factors. The fraction of biomass burnt on-site and off-site are not easily available for most Parties. These data may have to be generated indirectly by the inventory experts, based on the biomass extracted from forest areas subjected to conversion. Similarly, data may not be readily available on the fraction of biomass left to decay. A default value of 10 t/ha is given in IPCC 1996GL. These data will become available only through forest inventory studies.

55. Abandonment of Managed Lands
Worksheet 5C

56. 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 20–100 years) and annual growth rate
Step 3: Estimate the total C-uptake from abandoned land (Step 1 + Step 2)
This worksheet (5C) provides three steps for estimating CO2 removal from abandonment of managed lands.
First, there is a need to estimate the extent of managed lands abandoned during the two previous periods, namely, up to 20 years and 20–100 years. No default data are available for the area abandoned. Second, there is a need to estimate and use the biomass carbon uptake rates in the area abandoned during the above two periods. Third, the total carbon uptake from abandoned land is estimated using the area and the carbon uptake rates. Refer to IPCC 1996GL for details of the steps and procedures.

57. 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 20–100 years
Absence of annual data for above-ground biomass growth for abandoned land
This slide highlights some of the problems encountered in estimating CO2 uptake from abandonment of managed lands.
The first problem relates to incompatibility of land categories given in IPCC 1996GL with the land categories of countries doing inventory.
Second, many countries do not keep records of area abandoned and regenerating for different periods. There is no acceptable method for monitoring the area abandoned and regenerating for previous years.
Third, there is a lack of data on growth rates of above-ground biomass in managed land abandoned.

58. Approach to Addressing Issues Relating to Activity Data and Sources of Data
In this slide, approaches to address problems relating to activity data and sources of AD are presented.
For countries using Tier 1, limited data are likely to be available at the national level. Further, no default data are available at the global level. The experts may have to make a judgment based on data on degraded plantation, grassland and croplands that are left fallow or abandoned. In many countries, area abandoned for over 20 years may have already developed tree crown to qualify as forest.
In the long term, countries may have to initiate land surveys or satellite assessments, incorporating abandoned land.

59. Approach to Addressing Issues Relating to Removal Factor and Source of Data
The only parameter required for this worksheet is annual growth rate of above-ground biomass for abandoned lands for two time periods. IPCC 1996GL provides the default values that can be adopted in Tier 1. It is very important to obtain the annual growth rate for different vegetation types, climatic systems and soil types. Most countries will have to initiate new studies to monitor growth rate in abandoned land because routine forest inventory studies may not incorporate abandoned lands.

60. CO2 Emissions and Removals from Soils
5D and Worksheet 5-5

61. 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
In this Worksheet (5D), the three key steps for estimating CO2 emissions/removals from soils are presented.
The steps include: estimating changes in soil carbon stocks in mineral soils under different land-use/management systems and soil types; estimating the carbon emissions from intensively managed organic soils; estimating emissions resulting from application of lime in agriculture.
It is important to note here that under IPCC 1996GL, emissions/removals of CO2 from biomass and soil carbon are not linked and are estimated separately. Refer to IPCC 1996GL, Worksheets, for details of steps and procedures.

62. 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
IPCC 1996GL does not link CO2 emissions/removals from biomass and soils and they are estimated separately. GPG2003 links CO2 emissions/removals from biomass and soils for each land category.
Many countries seem to have difficulties in classifying the land-use systems according to management and soil categories given in IPCC 1996GL worksheets.
Classification of land and soil types in countries is likely to be different and countries may not maintain area data according to management system and soil type.
Further, data availability is also limited for managed organic soils.
Default data availability on area under different management systems and soil types is limited.
Default data is given only for soil carbon density in IPCC 1996GL.

63. Approach to Addressing Issues Relating to Activity Data
This and the following slide deal with approaches to addressing problems relating to activity data. The main problem relates to area under different land-use/management and soil types. Most countries are not likely to have detailed classifications. Further, default data on area at the country level are limited. Inventory experts may use the classification adopted in their countries. Default data availability is limited, particularly according to land-use, management and soil type.
The slide describes the methods for generating activity data under Tiers 2 and 3.

64. Approach to Addressing …
Many countries may not have data on area under managed organic soils. Default data on managed organic soils are limited. Countries may have to generate new data using land survey or satellite assessments. Similarly, data on quantity of lime applied is limited, as is the availability of default values.
Many countries do not report emissions from organic soils and lime application.
It is likely that the scale of these two activities is small in most countries.

65. Approach to Addressing Issues Relating to Emission/Removal Factors
The two critical emission factors are soil carbon density in mineral soils of different land-use systems and the annual rate of loss of carbon from managed organic soils.
Default values are given in IPCC 1996GL as well as GPG2003. Many countries may also have national-level scientific studies on soil carbon. FAO also provides soil maps at the global level.
Countries using Tiers 2 and 3 can generate soil carbon density data through field studies, if data do not exist for some land-use categories. Routine national forest inventory studies may not incorporate soil carbon data. Thus, forest inventory studies may have to be expanded to include soil organic carbon.

66. Approach to Addressing…
Most countries are likely to use IPCC 1996GL default values for the emission factors given in this slide.

67. Sources of Activity Data
Activity data on area under different land-use management systems during Year t and t-20 are critical for estimating carbon emissions/removals from soils. Countries may have their own land-use classification systems or may have to use the FAO database. There are limited default data on the area under managed organic soils. Many countries may not have estimates of carbon emissions from organic soils.

68. Sources of Emission/Removal Factors
IPCC 1996GL and GPG2003 provide default values for carbon density of soils. However, default soil carbon density data for the land-use systems prevalent in a country may not be available. Countries may adopt Tier 2 for many land-use and soil categories for which data may be available from national research studies. National forest inventory studies may have to be extended to incorporate soil organic carbon. Dedicated studies may be required to estimate the carbon density of organic soils.
Default data could be used for the carbon conversion factor from lime to carbon and base, tillage and input factors.

69. 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
Other categories include HWP, wetlands and other sources/sinks.
According to IPCC 1996GL, carbon removed in wood is assumed to be oxidized in the year of harvest.
It is unlikely that a majority of countries maintain data on the stock of wood products under different categories. Countries can report HWP only if they can demonstrate that HWP stock is increasing.
The appendix of GPG2003 contains a methodology for estimating HWP.

70. 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
GHG inventory in the LUCF sector is associated with large uncertainty due to limitations of methods and data.
The main goal in the long term should be to improve the methods as well as activity data and emission factors.
GPG2003 is an important approach to reduce uncertainty. According to GPG2003, GHG inventories should be accurate and they should neither be over- nor underestimated.
Uncertainty in GHG inventory using the IPCC 1996GL approach could result from: limitations of methods, non-inclusion of some of the sources/sinks of GHGs, non-availability or lack of quality of activity data and emission factors.

71. 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.
Uncertainty assessment involves identifying the sources and types of uncertainties, identifying methods for reducing uncertainty, quantification of uncertainty.
Currently, most countries are not making any assessment of the extent of uncertainty involved in GHG inventory due to lack of approaches and methods in the IPCC 1996GL.
Uncertainty in GHG inventory (particularly with regard to carbon stock changes) emissions/removals in the LUCF sector are associated with uncertainties resulting from the following key AD and EF: area related activity data, biomass growth rates, biomass stock, commercial and fuelwood consumption, soil carbon density, etc.

72. 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 country’s 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
GPG2003 provides approaches to estimate uncertainty as well as to minimize uncertainty. GPG2003 provides two methods, namely, simple propagation of errors (for Tier 1) and Monte Carlo analysis (for Tier 2). These two approaches could be adopted for assessment of uncertainty of inventories using Tier 1 to Tier 3 methods of estimation.
Countries predominantly using Tier 1 methods for inventory estimation are likely to have high uncertainty because they depend extensively on default values. The default values may not be suitable to the national circumstances. Use of default data in a country that has different characteristics from those of the source of activity data or emission factors increases uncertainty.

73. 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
Uncertainty is likely to be low in countries using Tier 2 and Tier 3 approaches of inventory estimation. However, the cost of GHG inventory is likely to be high when shifting from lower to higher tiers. Extensive use of nationally derived activity data and emission factors contributes significantly to reduction of uncertainty. Under Tiers 2 and 3, it is possible to assess the uncertainties involved due to knowledge of the national circumstances, methods, sampling, etc. Statistical packages are available for adopting the Monte Carlo method for analysis of uncertainty. Refer to GPG2003 for details of the methods, including Monte Carlo analysis.

74. 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
GPG2000 and GPG2003 provide definitions and guidelines for QA and QC, keeping in mind the need to enhance transparency and accuracy of the estimates of GHG inventory. In the following few slides, QA/QC procedures are briefly described. Refer to GPG2000 or GPG2003 for detailed descriptions of the procedures.
The QC procedure helps to identify and address errors and omissions and also increase the transparency of the inventory records and activities.
QA helps in assessing the quality of the inventory estimates and to identify areas where improvements are necessary. QA is normally carried out by experts who were not involved in the inventory process.
QA/QC procedures may not significantly add to the cost of the inventory process, but improve the quality and transparency of the inventory process and estimates.

75. 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
In this and the following slides, a summary of the key findings of the problems faced by the inventory experts in using IPCC 1996GL methods and default data as well as options for overcoming these problems, leading to improved GHG inventory, are presented. It is very important to note that the problems with regard to methods, AD and EF vary from country to country.
Over 100 NAI Parties have used IPCC 1996GL, and capacity-building has occurred in NAI countries with regard to using IPCC 1996GL. NAI experts as well as compilation and synthesis reports by UNFCCC have identified a number of issues and problems in using the IPCC 1996GL. Some broad issues identified are listed in this slide.

76. Region specific limitations
LUCF sector is very important for Africa
Many countries in Africa have serious limitations on availability and access to
AD and EF
Remote sensing and Satellite imagery data
There is a need for regional effort to address EF issues
Regional level forest or plantation type specific EF may need to be developed
West and Central Africa, North Africa, Eastern – Southern Africa, etc

77. 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
The GPG2003 for LUCF sector is meant to overcome the methodological problems identified in using IPCC 1996GL. GPG2003 adopted a land-category- and key-source/sink-category-based approach to reduce uncertainty. This slide presents the approaches adopted by GPG2003 to improve the inventory process and reduce uncertainty. One of the key strategies to improve the inventory estimates and to reduce uncertainty is through adoption of a key source/sink category analysis approach, which helps countries to focus their limited inventory resources on identified land categories, carbon pools and GHG gases.