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Slide1: 

Definitions of renewable and non-renewable biomass for CDM projects Ingmar Juergens Climate Change and Bioenergy Unit Food and Agriculture Organization of the United Nations (FAO) Rome, Italy Side Event, UNFCCC SB-26 May 16, 2007 Bonn, Germany

Outline : 

Outline Some developing country context How to measure the baseline case of non-renewable biomass? Relevance of this project type Related activities

Developing country context: 

Developing country context

ER through biomass: 

ER through biomass Source: Juergens and Mueller, based on data from Kaltschmitt, 2002

Slide5: 

CDM and developing countries Biomass energy projects that displace the use of fossil fuel are eligible Many developing countries do not have Big opportunities for fossil-fuel reductions Most do have either: High LULUCF emissions Big LULUCF opportunities Large share of (unsustainable) biomass in primary energy > 80% of global bioenergy is traditional biomass No fossil-fuel baseline, GHG benefits in land use sector 10% of world primary energy excluded from CDM / Kyoto Main categories: cooking and heating

Slide6: 

Source: FAO FRA 2005

The concept: 

The concept

Slide11: 

Renewable energy in the CDM that replace fossil fuels Time Cumulative C Emissions Baseline: emissions from fossil fuels (in Annex A) Zero emissions renewable technology Credit Source: Schlamadinger and Juergens, 2004

Slide12: 

More efficient biomass energy Time Cumulative C Emissions Baseline emissions from land use (not in Annex A) Reduced emissions or enhanced stocks Not eligible as credit Source: Schlamadinger and Juergens, 2004

Renewable and non-renewable biomass: 

Renewable and non-renewable biomass

Renewable biomass (EB decision) : 

Renewable biomass (EB decision) Woody biomass from forests or croplands / grasslands where Land remains forests Levels of stocks not decreasing systematically Forestry / conservation regulations are adhered with Non-woody biomass (conditions apply) Biomass residues Non-fossil fraction of waste

Discussion of some recent submissions proposing methodologies for replacing non-renewable biomass: 

Discussion of some recent submissions proposing methodologies for replacing non-renewable biomass Principles: Biomass consumption in baseline non-renewable Emission reductions can only be claimed in proportion to the reduction of non-renewable biomass Qualitative or quantitative proof, depending on data available Sources: IETA, IEA Bioenergy Task 40, Joanneum Research, Oekoinstitut, Ecosecurities

Different types of non-renewable biomass: 

Different types of non-renewable biomass Woody biomass from forests and woodland Woody Biomass from croplands and/or grasslands Biomass residues and any non-fossil fraction of industrial or municipal waste should be considered 100% renewable. Non-woody biomass should be assessed using an alternative method, since this methodology deals only with woody biomass.

Principles: 

Principles Biomass consumption in baseline non-renewable Emission reductions can only be claimed in proportion to the reduction of non-renewable biomass Qualitative or quantitative proof, depending on data available

Quantitative vs. qualitative approach to determining non-renewable character of biomass in the baseline: 

Quantitative vs. qualitative approach to determining non-renewable character of biomass in the baseline Data available: quantitative approach collection of household consumption data and data on forest size and growth. When it can be proven that over the same time span the consumption of biomass by households is larger than the growth in biomass, the biomass has to be considered non-renewable. No data available: qualitative approach Proof against a number of indicators demonstrating non-sustainable character of biomass system.

Indicators for determining non-renewable biomass in the baseline: 

Indicators for determining non-renewable biomass in the baseline Such indicators could include: Deforestation rates Forest degradation rates Time spent by households/distance travelled in order to collect fuel wood  Survey data? Bias? Cost? Significant up-ward trends in fuel wood price  Works for where there are formal markets; what is significant? (Trends in) type of biomass collected by users, e.g. (a switch from wood to) lower quality biofuels (dung, small branches and twigs, etc.)  Survey data?

Six Steps for establishing the non-renewable character of biomass used in the baseline case: 

Six Steps for establishing the non-renewable character of biomass used in the baseline case

Step 1: identify a “woody biomass production area”: 

Step 1: identify a “woody biomass production area” Reflects spatial variability of carbon stock (changes) Easier for commercial enterprises, such as charcoal production or agro- and forest SMEs, where maximum radius around conversion/use of biomass is determined by the logistics (costs of transportation)

Step 2: estimate the average annual wood fuel increment (I): 

Step 2: estimate the average annual wood fuel increment (I) For the area estimated in step 1, estimate the average annual wood fuel increment (I) which could be harvested, consistent with the definition of “renewable biomass”; maximum sustainable yield;

Step 3: estimate the average removals of fuelwood from this area (H): 

Step 3: estimate the average removals of fuelwood from this area (H) Other non-fuelwood removals have to be considered Consider import and export out of the region.

Step 4: calculate the shortage of woody biomass in the area: S = H – I.: 

Step 4: calculate the shortage of woody biomass in the area: S = H – I. In the reachable harvesting area, does the consumption of woody biomass exceed the sustainable forest growth? If S (shortage) negative: removal < MSY  biomass renewable If S (shortage) positive: removal > MSY  biomass non-renewable

Step 5: Demonstrate that the amount of woody biomass used in the project baseline, at time zero, is less than S. If this is not the case, set the amount of woody biomass that can be included in the baseline to S. : 

Step 5: Demonstrate that the amount of woody biomass used in the project baseline, at time zero, is less than S. If this is not the case, set the amount of woody biomass that can be included in the baseline to S. Splitting the renewable and the non-renewable fraction Allocation procedure of non-renewable and renewable biomass between the different wood removals Reminder: S = H – I

Step 6: Baseline biomass equivalent to significant share of total removal in project area?: 

Step 6: Baseline biomass equivalent to significant share of total removal in project area? Demonstrate that the type of wood-based biomass occurring in the baseline (e.g., cooking fuel) is a significant share of H in the area analysed. The project can demonstrate that a particular user type (e.g. households) has a significant share if it meets one of the following criteria (note, the word ‘household’ here could be replaced by other user types e.g. ‘industrial users’): - (Household) woody biomass consumption > Annual Increment (A) - (Household) woody biomass consumption is the largest woody biomass consumption sector; - Share of (household) woody biomass consumption as a proportion of total woody biomass consumption (C) is greater than 20% or 30%

DATA: 

DATA

Data needs and monitoring methods: 

Data needs and monitoring methods Extent of forest - change over time: deforestation rate  METHOD: remote sensing and field inventories Change in carbon stock - above ground biomass - below ground biomass - dead wood - litter - soil  METHOD: field inventories

Data availability: 

Data availability Forest area change?  Yes...but quality varies Deforestation?  Only in a few countries Carbon stocks? Limited data, particularly on soil and litter, Weak trend data FRA Working Paper: Analysis of the carbon stock  Data provided by countries

Situation in non-Annex 1 countries: 

Situation in non-Annex 1 countries National forest inventories and repeated field measurements are essential for good trend estimates, but: Most countries do not have national forest inventories (long enough in place) to make trend estimates Therefore, most countries rely on estimates of forest area change over time that are incompatible Most countries have little or no data on deadwood, litter and soil carbon: they rely on use of conversion factors and default values

FAO’s efforts to improve data: 

FAO’s efforts to improve data Support establishment and improvement of national forest inventory systems Capacity strengthening in NFI, including remote sensing Global data set and monitoring system Standardized land cover classification

LCCS: some basic concepts: 

LCCS: some basic concepts Comprehensive methodology for description, characterization, classification and comparison of most land cover features identified anywhere in the world, at any scale or level of detail Created in response to a need for A harmonized and standardized collection and reporting on the status of land cover Availability of land cover data for a wide range of applications and users Comparison and correlation of land cover classes between different systems/approaches

LCCS Operational Context: 

LCCS Operational Context

GLCN: 

GLCN World Land Cover Scale 1:5-2,000,000 - raster based IGBP 1991 Global Land Cover 2000- JRC at Scale 1:1,000,000 - raster based GLC 2000 Globcover 2005/6 – MERIS 1:500,000 raster based Georeferenced Land Cover Initiatives -Africover/Asiacover - National Scale: 1:250,000-1:100,000 - vector based Member States Catchment Information System at Scale 1:50,000 - vector based Regions Local Soil Information System at Scale 1:20,000 - vector based Local Applications using LCCS: e.g GLC 2000, Global map Africover, Asiacover, S. C. America, ME, SADC, Sahel many country initiatives GOFC/GOLD (LCCS acceptance)

WISDOM: 

WISDOM

Wood energy in Eastern and Central Africa: 

Wood energy in Eastern and Central Africa Extreme relevance of wood energy in tropical Africa Wood consumption for energy is the major contributor to total wood removals in Africa. (> 90 percent of total African wood consumption, FAO 1999). In project countries: Woodfuel production in total roundwood in 2000: 88-100 percent The contribution of woodfuels to total primary energy consumption in the countries of East Sahelian Africa, Central Africa and Tropical Southern Africa: 75% to 86% (FAO 1999). Source: FAO, Drigo and Trossero, 2006

Key characteristics of woodfuel and related analysis: 

Key characteristics of woodfuel and related analysis Geographic specificity. The patterns of woodfuel production and consumption, and their associated social, economic and environmental impacts, are site specific [Mahapatra and Mitchell, 1999; RWEDP, 1997; Masera, Drigo and Trossero, 2003]. Broad generalizations about the woodfuel situation and impacts across regions, or even within the same country, have often resulted in misleading conclusions, poor planning and ineffective implementation. Heterogeneity of woodfuel supply sources. Forests are not the sole sources of woody biomass used for energy. Other natural landscapes such as shrublands as well as other land uses such as farmlands, orchards and agricultural plantations, agro-forestry, tree lines, hedges, trees outside forest, etc. contribute substantially in terms of fuelwood and, to a lower extent, of raw material for charcoal production. Users’ adaptability. Demand and supply patterns influence each other and tend to adapt to varying supply patterns and resource availability. This means that quantitative estimations of the impacts that a given demand pattern has on the environment are very uncertain and should be avoided [Leach and Mearns, 1988; Arnold et al., 2003]. Source: FAO, Drigo and Trossero, 2006

Slide38: 

Source: FAO, Drigo and Trossero, 2006

Slide39: 

Source: FAO, Drigo and Trossero, 2006

CONCLUSIONS: 

CONCLUSIONS

Questions: 

Questions High share of fuelwood in total wood removals Share of unsustainable bioenergy systems in developing countries’ energy supply is massive Deforestation or reduction of forest stocks is massive Can we relate reduction of carbon stocks to biomass for energy use? Does reduction of biomass for energy use reduce pressure on forest stocks? CERs as incentives for introducing more sustainable energy systems A measurable link to avoided deforestation Sector wide approaches, programmes;

FAO, data, analysis: 

FAO, data, analysis Data mostly available on national level Case studies on sub-national level Careful review of available data with a view to its role in non-renewable biomass baseline setting and CDM project development more broadly is necessary FAO is open to discuss collaboration, particularly on analytical, data and methodological issues related to biomass and related carbon stocks and flows Contact information: Forests and climate change: Susan.Braatz@fao.org and Heiner.vonLuepke@fao.org LCCS, GLCN et al.: John.Latham@fao.org Wood energy: Miguel.Trossero@fao.org Bioenergy and climate change: Ingmar.Juergens@fao.org and many more... .

The Economist, April 23rd 2005: 

The Economist, April 23rd 2005 “The valuation of ecosystem services is not without its difficulties. Nevertheless, the fact that there is a growing consensus about how and where it is appropriate is an important step forward for economists and environmentalists.”