Carbon Potential of Forests of MP and CDM Opportunities through

- Afforestation and Reforestation Projects

Dr. Rajiv PandeyScientist – Statistics

ICFRE

Workshop on Carbon Trading and CDM Opportunities in MP

Bhopal, 29-1-2010

• Forests and Ecosystem Services - Introduction• Forests and Carbon – Some Pertinent Issues• Carbon Estimation Procedures• Carbon in India’s Forests• Carbon in MP’s Forests – Preliminary Estimates• CDM and Afforestation and Reforrestation – Some Facts

OUTLINE

Forest, Ecosystem Services With Special Reference to Carbon

(A issue with future concerned)

• Global forests cover around 30% of earth’s surface, spread

over about 4 billion hectares of land mass.

• Latest deforestation rates are estimated around 13 million

hectares per year.

• Global forest vegetation stores 283 billion tonnes of carbon,

• 38 billion tonnes in dead wood and 317 billion tonnes in soil.

• Total carbon in Forest ecosystems is 638 billion tonnes.

Forests: Global ScenarioForests: Global Scenario

FAO, 2006

Countries with Largest Forest Cover(Million ha)

808

478310

303

197

164

13488 69 68

Russian Fedeartion

Brazil

Canada

US

China

Australia

DR Congo

Indonesia

Peru

India

Opportunities: Forestry Sector

• Ecosystem goods and services utilized locally, regionally and globally

• Encashment – goods……….yes– services……..possible (who pays?????)

• Crucial element: balance between goods and services

Co-benefits of Forests

• Ecosystem services:

– Benefits people obtain from ecosystems orThe “services of nature”

• Cultural (e.g. traditional values): Local• Provisioning (e.g. food, freshwater): Regional• Supporting (e.g. nutrient cycling): Regional• Regulating (e.g. climate, disease): Global

Ecosystem Services (Anthropogenic Perspective)

Provisioning Regulating Cultural

Goods produced or provided by ecosystems

•Food•Fresh water•Fuel wood•Fiber•Biochemicals•Genetic resources

Benefits obtained from regulation of ecosystem processes

•Climate regulation•Disease regulation•Flood regulation

Non-material benefits obtained from ecosystems

•Spiritual•Recreational•Aesthetic•Inspirational•Educational•Communal•Symbolic

Services necessary for production of other ecosystem services

•Soil formation•Nutrient cycling•Primary production

SupportingCarbon

Ecological Services

Ecosystem Services: Local

• People rely on cultural/provisioning ES:

• 60 million indigenous people almost wholly dependent on forests

• >1.4 bn of the world’s poorest people rely on forests for some part of their livelihoods/food security out of 6.8 bn people

• Often rely on biodiversity during climatic shocks• Forests help to provide clean water

Value of Forests – Fodder Value in Uttarakhand

Livestock feed proportion (Quantity) in hills

• 58% from forests, • 39% from other than forests land, and• 3% from markets

Vlaue proportion• 40-41% for forest; • 40-41% for other than forest land and• 18% from market

The annual livestock fodder value from forest is Rs 4810 crore and Rs 5210 crore in different scenarios.

Pandey, 2009

Ecosystem services: Local - Regional

• Supporting/regulating ES

• Canopy: local cooling effect through evaporation• Roots: prevention of erosion/mudslides/flooding• Flooding costs about $100bn/year• Flood frequency linked to deforestation

Ecosystem Services: Regional- Global

• Hydrology

Water vapour from oceans

Some rain water recycled

Drainage to rivers

Evaporation and cooling

effect

Extraction of soil water

by roots

Rain

Ecosystem Services: Global

• Carbon sequestration– Forests absorbing and storing Carbon

– Vegetation and soils containing microbial and invertebrate communities, sequester CO2 directly from the atmosphere.

– Approximate MITIGATION value of $43 billion/year

– Causes?

• Forest responses to changing atmosphere

Uttarakhand total Forest cover: 2.44 m ha

Uttarakhand forests are rich in Soil Organic carbon.

Carbon density > 120 t/ha in Deodar, fir and spruce

>60 t/ha in sal, pine and miscellaneous forest

Assuming on an average 100t/ha of SOC and 80 t/ha of biomass carbon in Uttarakhand Forests, Uttarakhand forest stores about 450 million tonnes of carbon (A conservative estimate)

Sinks of Carbon in Uttarakhand- Forests

Per Unit Carbon (in million tonnes) Change in Various Major Forest Types of Uttarakhand from 1995 - 2005

S. N.

Forest Types (Symbol) Carbon 1995

Carbon 2005

Decadal Increment

Carbon/ 000, ha 1995

Carbon/ 000, ha 2005

Per 000, Unit Increment

1 Himalayan Dry Temperate Forests

1.8851 1.9703 0.0853 0.0608 0.0616 0.0008

2 Himalayan Moist Temperate Forest

306.5313 331.5177 24.9864 0.1375 0.1355 -0.0020

3 Sub Alpine and Alpine Forest

226.4590 234.8060 8.3470 0.1121 0.1136 0.0015

4 Sub-Tropical Dry Evergreen Forests

119.0389 123.1936 4.1547 0.0973 0.0987 0.0014

5 Sub-Tropical Pine Forests 386.7450 406.2947 19.5497 0.0849 0.0857 0.0008

Sub- Alpine, Moist Alpine Scrub and Dry Alpine Scrub is merged due to less area and named as Sub Alpine and Alpine Forest (SAAF)The total carbon is derived from the technical paper of Kishwan et. al., 2009.

Pandey, 2009

• Value of C-sequestration annually by Uttarakhand forests: Rs 3.28 billion (37.5 billion/year for Himalayan states) (@ US$ 13/ t C).

• Himalayan forests worth Rs. 1,000.00 billion annually.

Valuation of Ecosystem ServicesCase Study - Himalayan States….

Source: Singh, S.P. 2008

Sources of Carbon from Forests– Domestic Energy in Uttarakhand

• 2.7 mt forest biomass extracted for domestic energy

• Leads to 3.87 mt of CO2 emissions annually

• Cost wise - Rs 534 million to Rs 890 million @ $ 3 – 5 per tonne CO2

• Shifting requires 0.295 mt of LPG

• Leads to release of 0.885 mt CO2 e worth Rs 120 million to Rs 210 million.

• Economics of shift to LPG (@ Rs. 400 with transportation to hills) requires the total expenditure of Rs 4153 million with one cylinder for rural population of state (Conservative estimate)

• Additionally – Better quality of life Pandey, 2009

Carbon Potential of Forests Carbon Potential of Forests CDM ProjectsCDM Projects

Conflict AvoidanceConflict Avoidance

Carbon TradingCarbon Trading

Comparative AnalysisComparative Analysis

Impact of Climate Change -Impact of Climate Change -EEmissions Removal Capability

Under Forestry & Logging sectorUnder Forestry & Logging sector

•Forestry – planting & conservation of forests, gathering of forest products, charcoal burning carried out in forests

•Logging – felling & rough cutting of trees,

•Farmyard wood

Green AccountingGreen Accounting

Incorporation in National AccountsIncorporation in National Accounts

MDGs are the world's time-bound and eight quantified targets for addressing basic human rights

3. Promote gender equality and empower women

MDG7 Indicators

25. Proportion of land area covered by forest

26. Ratio of area protected to maintain biological diversity to surface area

27. Carbon dioxide emissions per capita and consumption of ozone-depleting CFCs

Global requirementsGlobal requirements

Role in Millennium Development Goals (MDGs)Role in Millennium Development Goals (MDGs)

Ecosystem Services and its LinkagesEcosystem Services and its Linkages

• Provide array of goods and services.

• Debate on ecosystem stresses and shocks with reduction in the diversity

• Imbalancing the system• No effect on systemNo effect on system

• Reduction of global emissions revolves mainly around forests.

• Therefore, assessment of carbon potential of forests.

Strategy

Forests & Climate Change Mitigation

COP7, 2001: Bonn Marrakesh Accord

COP13, 2007: Bali Road Map

Carbon ForestryCarbon Forestry

Brown, et.al., 1996

Carbon PotentialIn

India’s Forestsand

Madhya Pradesh’s Forests

Carbon Pool in Forest Ecosystem

• Five pools of carbon –Above-ground biomass, –Below-ground biomass, –Litter, –Dead wood, and –Organic carbon in soil.

Carbon Estimation - Procedure

Mathematically,

= Total available carbon in the

forest, i.e., in the vegetation and in soil = Total available carbon in the above

and below ground biomass of all forest vegetation

= Total available soil organic carbon (SOC) up to 30cm depth in forest

SoilBiomassCarbon CCC

CarbonC

BiomassC

SoilC

Soil Organic Carbon Stock

Soil organic carbon stock Qi (Mg m-2) in a soil layer or sampling level i with a depth of Ei (m) depends on the carbon content Ci (g C g-1), bulk density Di (Mg m-3) and on the volume fraction of coarse elements Gi, given by the formula (Batjes 1996)

)1(11

iiii

k

i

k

iitsoil GEDCQQC

Biomass Carbon

Biomass (B) of the Forest x (1 - mcdb) x Proportion of Carbon Content

B = x MD = Total forest growing stock (Mm3)

B = Biomass (Mt)

MD = Mean wood density

mcdb = Moisture Content on dry basis (ranges between 10 – 20 %)

Proportion of Carbon Content (ranges between 40 – 50%)

BiomassC

TotalGS

TotalGS

Growing Stock of Forest

VegetaionOtherTreeTotal GSGSGS .

TotalGS Total growing stock in forest

TreeGS Growing stock of tree component

VegetaionOtherGS . Growing stock of other vegetation on forest floor

Growing Stock Tree

GroundBelowGroundAboveTree VVGS ..

GroundAboveV . = Above ground volume

GroundBelowV . = Below ground volume

GroundAboveV . = CommercialGS x Expansion factor

CommercialGS = Growing stock of tree bole up to 10 cm diameter

Expansion factor = adjusted mean biomass (volume) expansion factor for the country

GroundBelowV . = GroundAboveV . x Ratio

Ratio = adjusted mean ratio between below and above ground

biomass (volume)

Growing Stock Other Vegetation

VegetaionOtherGS . TreeGS X Ra

Ra = Ratio of other forest floor biomass to growing stock of tree component

VegetaionOtherTreeTotal GSGSGS .

Forest Cover Map of India 2007

(FSI, 2009)

Assessment of Carbon in India’s Forests

Trends in Land Use in India(Million Ha)

0

25

50

75

100

125

150

1880 1900 1920 1940 1960 1980

Are

a (

Mil

l h

a)

Agriculture

Forest

Forest Biomass Carbon in India (million tonnes)

Item with symbolic description Factor 1995 2005Growing Stock of Country in Mm3 - GS 5842.320 6218.282Mean Biomass Expansion Factor - EF 1.575 Ratio (Below to Above Ground Biomass) - RBA 0.266 Above Ground Biomass (Volume) - AGB = GS X EF 9201.654 9793.794Below Ground Biomass (Volume) - BGB = AGB X RBA 2447.640 2605.149Total Biomass (Volume) – TB = AGB + BGB 11649.294 12398.943

Mean Density - MD 0.7116 Biomass in Mt = Growing Stock (Mm3) x Mean Density (MD) 8289.638 8823.088Ratio (Other Forest Floor Biomass except tree to Tree Biomass) 0.015

Biomass in Mt (Trees + Shrubs + Herbs) - TFB 8413.982 8955.434Dry Weight in Mt (80% of TFB) - DW 6731.186 7164.348Carbon in Mt (40 % of DW) 2692.474 2865.739

Factors for various items were derived from mainly Kaul, et.al., 2009; Ray and Ravan, 1996 and Singh and Singh, 1985.

Soil Organic Carbon Pool Estimates (0 - 30 cm) in India’s Forests

Forest Type (Group) Area, 000 ha 1995

Area, 000, ha 2005

Soil Carbon (t)/ha

Total SOC (000, t) 1995

Total SOC (000,t) 2005

Himalayan dry temperate forest 31 32 36.198 1122.144 1158.343Himalayan moist temperate forest 2230 2447 71.577 159616.937 175149.168Littoral and swamp forest 383 481 71.062 27216.904 34181.021Montane wet temperate forest 2583 2593 115.460 298233.293 299387.893Sub alpine and alpine forest 2021 2067 74.071 149698.375 153105.661Sub tropical broad leaved hill forest 260 303 86.611 22518.833 26243.102Sub tropical dry evergreen forest 1223 1248 65.279 79836.780 81468.766Sub tropical pine forest 4556 4743 50.270 229031.601 238432.151Tropical dry deciduous forest 18233 19156 34.195 623475.447 655037.332Tropical dry evergreen forest 134 165 52.398 7021.363 8645.709Tropical moist deciduous forest 23091 24284 55.009 1270222.177 1335848.398Tropical semi evergreen forest 2573 2946 54.625 140549.907 160925.000Tropical thorn forest 1604 1827 20.375 32681.741 37225.399Tropical wet evergreen forest 5040 5414 101.404 511078.124 549003.366

Total 63962 67706 3552303.628 3755811.310

Component-wise Carbon in India’s Forests in 1995 and 2005 (million tonnes)

Carbon 1995 2005 Incremental Change

In Biomass 2692.474 2865.739 173.265

In Soil 3552.304 3755.811 203.507

Total 6244.778 6621.55 376.772

Source: Kishwan, et al., 2009

Trends in Carbon stock estimates: Indian Forests (million tonnes)

Source: 1880 and 1980 Richards and Flint (1994); 1986 Ravindranath et al (1997);1986 Chabra and Dadwal (2004);1994 Haripriya 2003,;2005 FAO (2005)

Forest Cover Map of Madhya Pradesh (FSI, 2009)

Carbon in Madhya Pradesh Forests (million tonnes)

State/UT Madhya Pradesh 2005

Madhya Pradesh 1995

Total Growing Stock 298.780255 280.9148Mean Biomass Exp. Factor 1.59 1.59Mean wood Density 0.75 0.75Ratio Below to Above Biomass 0.26 0.26Above Ground Biomass 475.0606055 446.654587Below Ground Biomass 123.5157574 116.1301926Total (Above + Below) 598.576363 562.7847796Weight (Volume * W density) 448.9322722 422.0885847All Biomass on forest 455.6662563 428.4199135Dry weight (80%) 364.533005 342.7359308Biomass Carbon 145.813202 137.0943723Soil Carbon 2005 180.7186478 170.9264857Total Carbon 2005 326.5318498 308.0208581

Component-wise Carbon in MP’s Forests in 1995 and 2005 (million tonnes)

Carbon 1995 2005 Incremental

Change

In Biomass 137.0943723 145.813202 8.7188297

In Soil 170.9264857 180.7186478 9.7921621

Total 308.0208581 326.5318498 18.5109918

5 % for India’s Carbon Increment

Source: Own estimate

Per Unit Carbon (in million tonnes) in Various Forest Types of MP and Adjoining Regions from 1995 - 2005

Forest Types Carbon 1995

Carbon 2005

Decadal Increment

Carbon/ 000, ha 1995

Carbon/ 000, ha 2005

Increment

Tropical Dry Deciduous Forests (TDDF)

977.3823 1031.7186 54.3364 0.0536 0.0539 + ve

Tropical Dry Evergreen Forests (TDEF)

10.0408 11.8595 1.8187 0.0749 0.0719 - Ve

Tropical Moist Deciduous Forests (TMDF)

2397.7747 2535.9607 138.1860 0.1038 0.1044 + Ve

Tropical Semi-Evergreen Forests (TSEF)

286.4960 316.2629 29.7670 0.1113 0.1074 -Ve

Tropical Thorn Forests (TTF)

49.1030 54.7033 5.6004 0.0306 0.0299 - Ve

Source: Own estimate

Assumptions

• Soil Carbon of respective year is based on the product of total soil carbon in India’s forest with the proportion of growing stock (Total State GS/Total Country GS).

• Biomass expansion factor is based on Kaul, et al., 2009; and Kishwan et al., 2009.

• Ratio Below to Above Biomass was based on secondary literature Ray and Ravan, 1996 and Kishwan et al., 2009.

• Mean wood density is based on the Rajput et al., 1996 study for major tree species in MP forests.

• In general, other forest floor biomass accounts for less than 2 percent of total biomass of closed forest formations (Ogawa, et al., 1965; Rai, 1981; Brown and Lugo, 1984).

• This study uses the conservative value of 40% carbon content keeping in view the fact that it deals with mixed biomass comprising timber, fuelwood, leaves, twigs, roots, etc.

• The study also assumes the presence of an average moisture content of 20% mcdb (moisture content on dry basis) in dry wood and other biomass (Hall et al., 1994) with consideration that good amount of water still remains in wood even after proper drying (Ludwig et al., 2003).

• Conservative values of carbon content and mcdb have been adopted to have realistic estimates in view of the errors that are generally associated with use of such values and factors in computation of total growing stock, wood densities, expansion and conversion factor, etc.

Afforestation & Reforestation

in CDM

Legal background: A/R CDM UNFCCC

The Kyoto Protocol

Article 12: The clean development Mechanism

Decision 16/CMP.1Land Use, Land use Change and Forestry

Decision 5/CMP.1Modalities and Procedures for afforestation and reforestation project activities

underthe CDM in the first commitment period of the Kyoto Protocol

Decision 6/CMP.1Simplified modalities and procedures for small-scale afforestation and

reforestation Project activities under the CDM in the first commitment period of the Kyoto Protocol

• The mechanism aims at reducing GHG emissions or

enhancing carbon sinks in developing countries and in

turn assists Annex I Parties or Industrial countries in

meeting their GHG emission reduction commitments,

promoting sustainable development in developing

countries by encouraging investments.

• Developed countries will receive credit against their

targets for emissions avoided by these Projects

The Clean Development Mechanism (CDM)

Industrialized countries (Annex I)

Developing countries (Non-Annex I)

CDM project activity

To assist in achieving sustainable development

To assist in meeting their emission limitation commitments

Project participantsInvestors

(private business, governments, NGOs)

(private business, governments, NGOs)

What is the CDM

Demonstration of CDM ability

Land Use land use Change and Forestry (LULUC F) under Kyoto Protocol

• LULUCF activities included in the seventh COP for the first Commitment period 2008 – 2012

• These are limited to Afforestation and Reforestation Projects for CDM

• Non Annex 1 host country shall select a value for forest for purpose of CDM

Definition of Forests for the purpose of CDM and LULUCF A/R Projects

Forest Threshold to be set by Designated National Authority (DNA) that also grants Host Country Approval

(a) “Forest” is a minimum area of land of 0.05 –

1.0 hectares with tree crown cover of more

than 10 – 30 per cent with trees with the

potential to reach a minimum height of 2 – 5

meters at maturity in situ

‘Forest’ as defined by Indian DNA

(b) “Afforestation” is the direct human-

induced conversion of land that has

not been forested for a period of at

least 50 years to forested land

through planting, seeding and / or

the human-induced promotion of

natural seed sources

Procedures to demonstrate eligibility of land (EB35, Annex 18)

Non forest at project start

Non forest for 50 years before project start

Non forest

Afforestation

Land use change from non forest to forest (defined through tree crown cover, tree height and land area)

(c) “Reforestation” is the direct human-induced

conversion of non-forested land to forested land through planting, seeding and / or the human-induced promotion of natural seed sources, on land that was forested but that has been converted to non-forested land. For the first commitment period, reforestation activities will be limited to reforestation occurring on those lands that did not contain forest on 31 December 1989

Time31/12/1989

Reforestation: CDM eligible lands

31/12/1989

Reforestation: not CDM eligible lands

EB-35 Annex 18Project participants shall provide information that reliably

discriminates between forest and non-forest land according to the particular thresholds adopted by the host country, inter alia:

(a) Aerial photographs or satellite imagery complemented by ground reference data; or

(b) Land use or land cover information from maps or digital spatial datasets; or

(c) Ground based surveys (land use or land cover information from permits, plans, or information from local registers such as cadastre, owners registers, or other land registers).

If options (a), (b), and (c) are not available/applicable, project participants shall submit a written testimony which was produced by following a Participatory Rural Appraisal (PRA) methodology or a standard Participatory Rural Appraisal (PRA) as practised in the host country.

Planning of Projects

Each projects should be managed so as to be real and measurable and permanent. It should demonstrate co-benefits, be transparent and credible and should have clear and prior consent of owners.

Accounting

• Credits issued on the basis of achieved “Net anthropogenic greenhouse

gas removals by sinks” • To calculate them:

– Actual net greenhouse gas removals by sinks (AR): removals minus emissions of GHG due to project;

– Baseline net greenhouse gas removals by sinks (BL): changes in carbon stocks in the baseline

– Leakage (L): emissions outside the project boundary that are the result of the project.

• 5 pools: Above-ground biomass, Below-ground biomass, Soil organic carbon, litter and Dead organic carbon

Outside the project boundary,

“attributable” and “measurable”Within the project boundary

Removals minus emissions of GHG due to project

Carbon benefits of A/R CDM project activitiesCarbon benefits of A/R CDM project activities

Project scenario

(changes in the carbon

stocks in the carbon pools)

Baseline scenario

(changes in the carbon

stocks in the carbon pools)

(decrease in the carbon

stocks in the carbon pools)

increase in

emissions

=

“Net an

thro

po

gen

ic GH

G

remo

val by sin

ks”=Leakage

=“Actual net GHG removal by sinks”

=“Baseline net

GHG removal by sinks”

Nearby the Project AreaProject Area

Leakage = Increased GHG emissions outside the project boundary attributable to the project activity (e.g. induced land use/cover change,

increased consumption of fossil fuels) and measurable.

Leakage Leakage

2005 2005

2005+XCO2

2005+X

C

C

The method to be used to assess leakage is part of the “baseline” methodology.

Additionality

A project activity is “additional” or “not additional”. Accordingly it gets 100% or 0% of the carbon credits.

Under the Kyoto Protocol “additionality” is a “yes” or “no” judgment.

Key differences relevant to carbon inventory at different project phase

Project phase Carbon mitigation projectsConceptualization Primary focus: carbon mitigation and carbon credits-global

environmental benefit Secondary focus: soil and biodiversity conservation

Proposal development

Clear historical records of the past vegetation and soil carbon status needed

Project boundary impacted by project activities needs clear definition

Estimation of baseline carbon stock is critical Intensive plan needed for monitoring carbon stock changes

Project review and appraisal

Baseline and project scenario carbon monitoring methods and arrangements very critical

Implementation Activities aimed at maximizing carbon benefits, followed by other co-benefits

Monitoring and evaluation

Approved methodologies Additionality of carbon stock gain critical All the five carbon pools need to be considered Large transaction cost likely for carbon inventory and monitoring

Implications of different methodological issues (Use of approved methodology is mandatory)

Issue Carbon mitigation projectsBaseline Very critical for estimating net carbon benefits

Requires periodic monitoring of relevant carbon pools for dynamic stock

Additionality Estimation of additional carbon stock gains over the baseline carbon stock change is necessary

Periodic monitoring of carbon pools and baseline scenario is necessary

Multiple carbon pools are relevantLeakage Estimation of leakage of carbon benefits outside the area subjected

to direct project activities necessary for estimating net carbon benefits

Permanence Estimation of reversal or loss of carbon benefits required Carbon stock-Difference method estimates any loss due to reversal

of carbonProject boundary

Includes area directly subjected to project activities as well as areas not directly subjected to project activities but where carbon stocks will be impacted

Scale Has implications for carbon inventory methods and cost of monitoring

• Small Scale A & R project activities

- Threshold limit of net anthropogenic GHG removals by

sinks of 16 kilotonnes CO2 per year (revised from 8 kt

CO2 by decision /CMP.3, Bali)

-Implemented by low income communities

• Large Scale A & R project activities

- No threshold limit of net anthropogenic GHG removals by sinks

Types of A/R activities

Potential CDM Projects in A/R

Forest Sector Opportunity Project Examples

Afforestation & reforestation

Short rotation fuel wood Fuel wood supply for rural people

Agro-forestry Farm income/ Joint Forestry Mgmt

Carbon SequestrationShort rotation industrial

woodPulp etc. to industries

Forest Produce Methane Avoidance Aerobic Composting of forest litter

Development of oils Biodiesel from Jatropha

Green Energy

Short rotation energy Biomass feedstock to power generators Energy efficient

ConstructionBuilding energy efficient buildings like

Jungle Resorts/ Forest LodgesTapping renewable

energy sources available in natural habitats

Solar Photovoltaics along side afforestation activities

Wind power projects in farmlands (e.g. Gujarat)

Mitigation Activities and Carbon Inventory

Land-use Mitigation Activity Projects Items in Carbon InventoryForest Land Afforestation •Community Woodlands

•Community Plantations•Fruit Orchards

•Estimation in changes of carbon stocks in biomass and soil•Production of fuelwood, timber

Reforestation •Natural Regeneration•Plantation in Degraded Lands

•Estimation in changes of carbon stocks in biomass and soil•Production of roundwood

Cropland Agroforestry •Row-intercropping•Shelterbelts•Watershed Management

•Estimation in changes of carbon stocks in soil•Increase in perennial crop biomass production

Grassland Improved Management •Grazing Management•Improved Grassland Practices

•Increase in grass production and Soil organic carbon

List of approved CDM Afforestation and Reforestation (A/R) methodologies

Sl.No. Meth No. Details

1 AR- AM 0001

“Reforestation of degraded land”This methodology is based on the draft CDM-AR-PDD “Facilitating Reforestation for Guangxi Watershed Management in Pearl River Basin, China

2 AR- AM 0002

“Restoration of degraded lands through afforestation/reforestation”This methodology is based on the draft CDM-AR-PDD “Moldova Soil Conservation Project”

3 AR- AM 0003

“Afforestation and reforestation of degraded land through tree planting, assisted natural regeneration and control of animal grazing”This methodology is based on the draft CDM-AR-PDD “Assisted Natural Regeneration on Degraded Land in Albania”, (Withdrawn)

4 AR – AM 0004

Reforestation or afforestation of land currently under agricultural use”This methodology is based on the draft CDM-AR-PDD “Reforestation around Pico Bonito National Park, Honduras”,

5 AR – AM 0005

“Reforestation or afforestation of land currently under agricultural use”This methodology is based on the draft CDM-AR-PDD “Reforestation as Renewable Source of Wood Supplies for Industrial Use in Brazil”

6 AR – AM 0006

“Afforestation/Reforestation with Trees Supported by Shrubs on Degraded Land”This methodology is based on the draft CDM-AR-PDD “Afforestation for Combating Desertification in Aohan County, Northern China

List of Approved CDM Methodologies for A/R

Number Title Above Ground Biomass

Below Ground Biomass

Dead Wood

Litter Soil Organic Carbon

AR - AM 0001

“Reforestation of degraded land”

Yes Yes No No No

AR - AM 0002

Restoration of degraded lands through afforestation/reforestation

Yes Yes Yes Yes Yes

AR - AM 0003

Afforestation and reforestation of degraded land through tree planting, assisted natural regeneration and control of animal grazing

Yes Yes No No No

AR - AM 0004

Reforestation or afforestation of land currently under agricultural use

Yes Yes No No No

Sl. No. Project Title Methodologies Reductions* Comments

1 Reforestation of severely degraded landmass in Khammam District of Andhra Pradesh, India under ITC Social Forestry Project.

AR-AM0001 ver. 1 49,484 Registered on 5 June 2009

2 Bagepalli CDM Reforestation Programme AR-AM0001 ver. 2 346,701

3 Reforestation Project at Shree Panchavati Panjrapole (SNPP),

AR-AM0001 ver. 2 10,590

4 Reforestation of degraded land in AR-AM0001 ver. 2 3,555

5 Bagepalli CDM Reforestation Programme Small Scale Cooperative AR-AM0001 ver. 2 155,852

6 Afforestation CDM Pilot Project Activity on Private Lands Affected by Shifting Sand Dunes in Sirsa, Haryana

AR-AMS0001 ver. 4 11,591 Registered on 23 March 2009

7 The International Small Group and Tree Planting Program (TIST), Tamil Nadu AR-AMS0001 ver. 4 7,367 Registration in Process

8 Reforestation of degraded land by MTPL in India

AR-AC 001 ver.2M 137,018 Submitted in 2009

9 Improving Rural Livelihoods Through Carbon Sequestration By Adopting Environment Friendly Technology based Agroforestry practices

AR-AM 004 ver.3 324269 Submitted in 2009

10 India: Himachal Pradesh Reforestation Project – Improving Livelihoods and Watersheds

AR-ACM 001 ver.2 252,905 Submitted in 2009

11 Rehabilitation of Degraded Wastelands at Deramandi in Southern District of National Capital Territory of Delhi through Reforestation

AR-AMS 001 ver.5 15058 Submitted in 2009

A/R CDM Projects from India submitted to CDM EB

Carbon Potential of Fast Growing Species

• A fast growing tree species (Eucalyptus) under intensive management can assimilate more than 15 m3 ha-1y-1 of wood during its rotation (10 years), which is significantly higher than the observed assimilation potential of traditional timber trees such as teak (Tectona grandis) and Sal (Shorea robusta).

• D.sissoo and Prosopis juliflora produced biomass 114/dry t/ha at three years of age (Kimothi, 1984).

• In dry tropical region, the E.tereticornis biomass varies from 5.65 t/ha at 5 years to 112.5t/ha at 8 years (Rawat and Kishwan, 2007.

• Therefore, plantations of quick growing species QGS with a mean annual increment (MAI) have a potential to sequester 5 t of carbon  ha-1 y-1 or about 18.35 t CO2e ha-1 y-1.  

Biomass Energy Plantations

• A/R projects may generate CERs through bioenergy plantations (biodiesel, fuelwood) for displacing fossil fuels in power and industrial applications.

• Large no. of methodologies for biomass energy, e.g. AM007, AM0026, AM0027, AM0036, AM0042, AM0047, AM0057, ACM 0002, ACM0006.

• Biomass energy does not have the restrictions on use of CERs (Certified Emission Reductions) under Marrakesh accord.

Registered Bioenergy Projects

• Biomass Energy: Just one Meth: AM0007 has >100 registered projects (a project may use > 1 meth)!

• India had approved >200 renewable biomass energy projects.

• These facts suggest that A/R for renewable biomass energy can also be used for CDM credits.

Acknowledgments

• ICFRE, Dehradun• Mr Jagdish Kishwan • Dr Mukesh Gupta, Soil Expert• Dr Vijay Rawat, Ecology

Thanks to

• EPCO• Mr Alok Srivastava, Principal Secretary• Mr Lokendra Thakkar and EPCO team

ThanksThanks

Contact Address

Dr Rajiv PandeyScientist EIA DivisionIndian Council of Forestry Research & Education (ICFRE)Dehradun, India

Phone: +91 0 9412918634Email: rajivfri@yahoo.com