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


1
CGE Greenhouse Gas Inventory Hands-on Training
Workshop LAND-USE CHANGE AND FORESTRY 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

7
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).

8
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.

9
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 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

16
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

18
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

19
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 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)

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 Between IPCC 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 Issues GPG2003 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
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