Potential of Carbon Finance to Protect the Amazon and Mitigate Climate Change

Transcription

1 C A R B O N C R E D I T S O R I G I N A T I O N T O C O M M E R C I A L I S A T I O N Potential of Carbon Finance to Protect the Amazon and Mitigate Climate Change Johannes Ebeling Climate Change and the Fate of the Amazon 22 March EcoSecurities Group plc Overview Background on Avoided Deforestation (AD) and Compensated Reductions The Amazon in the context of AD Challenges and potentials for effective AD mechanism Carbon market impacts Deforestation baselines, incentives, and hot air Non-permanence risk Forest degradation Co-benefits: biodiversity and local development Linking international incentives to local governance Outlook and To Do s 1

2 Deforestation & Climate Change Land-use change in tropics accounts for 20 % of global GHG emissions and is main driver of biodiversity loss 13 million ha of tropical forests lost per year Largest source of emissions in developing world 2 nd largest source globally after fossil-fuel use! Not included in current climate regime - Kyoto Protocol (UNFCCC) does not address tropical deforestation (yet!) No emission targets for developing countries Clean Development Mechanism (CDM) is limited to reforestation Avoided Deforestation The Proposal Incentives for reducing emissions from deforestation Host country receives compensation based on lowering deforestation on national level Note: crediting at national level, unlike project-based CDM, to counter leakage risk 2

3 The Amazon in the Context of Avoided Deforestation Source: JRC / ACTO 2005 Amazon biogeographical & political definition (8 member States of ACTO) The Amazon in the Context of Avoided Deforestation Amazon countries responsible for around 30 % of global deforestation and > 30 % of related emissions Country Bolivia Brazil Columbia Ecuador Guyana Peru Suriname Venezuela Annually deforested area ( ) -270,000 ha -0.5% -3,103,000 ha -0.6% - 47,000 ha -0.1% -198,000 ha -1.7% (0 ha) (0.0%) - 94,000 ha -0.1% (0 ha) (0.0%) -288,000 ha -0.6% 3

4 Avoided Deforestation and Carbon Markets Potential emission reductions and income from carbon trading at... Carbon price of 18/tC ( 5/tCO 2 ) and... Carbon price of 55/tC ( 15/tCO 2 ) and... Carbon price of 110/tC ( 30/tCO 2 ) and % in - 20 % deforestation deforestation - 50 % - 10 % in deforestation - 20 % deforestation deforestation - 50 % - 10 % in deforestation - 20 % deforestation deforestation - 50 % deforestation Reduced emissions (Mt C) Reduced emissions (Mt CO 2 ) , , , Total market volume / income from AD credits (Mt ( million) CO 2 / million) 1, , , , , , , , , Limitation: No one knows opportunity costs of reducing deforestation globally (exception: Daniel N.?) Will above potential be realised? How attractive will carbon finance be for landholders / govt s? P - Marginal abatement costs Market flooding and crowding out of other investments? 2) Hypothetical post-2012 target & cost (incorporating AD) P1 P2 P2* Crowded out of other mitigation investment 1) Current ER target & cost (only fossil fuel Fossil fuel ER only AD only Both abatement options combined Q - Quantity of abated emissions Q2 Q1 Additional abatement at no extra cost Total cost of reaching (1) with fossil fuel ER only (blue area) Total cost of reaching (2) using both abatement options (black area, same as blue area, i.e. no additional cost) 4

5 Avoided Deforestation and Carbon Markets Scale of expected emission reductions? Unpredictable market and price impacts? Annually deforestated area (1000 ha) 3,500 3,000 2,500 2,000 1,500 1, Inter-annual variability in deforestation rate (percent) Deforestation in Brazilian Amazon (Amazônia Legal) National baselines (carbon stocks) Difficulty of predicting the future (Business as usual) Historical baselines may not be representative of future Risk of hot air if BAU deforestation is lower than assumed Leaves out countries with historical good performance (A) and countries past forest transition (C) Examples A) Guyana, Suriname B) Brazil, Ecuador C) Chile, Uruguay PES = Payments for Environmental Baselines for carbon crediting Services, e.g. carbon storage 5

6 Non-permanence of emission reductions Effect of a possible end of mitigation measures on atmospheric GHG concentrations The case of delaying deforestation Non-permanence Risk Anthropogenic risk: Rebound after temporary deforestation prevention Climatic risk: Feedbacks and tipping points - droughts, fires, 6

7 Emissions from forest degradation Deforestation: Lowering of crown cover below defined threshold value Kyoto Protocol: % FAO: 10 % CO % crown cover 30 % crown cover Emissions from forest degradation Large-scale degradation threatens biodiversity, soils (& climate) Widespread selective logging, etc. - Affects up to 24 M ha/yr (2x deforestation) Typically adds 2 25 % to emissions from deforestation Problem: measuring specific carbon content of forest with RS Currently only area proxy is feasible and economical Solutions: Discounting carbon value of forest with signs of intervention 7

8 Co-benefits of Avoided Deforestation Hope: Carbon finance for reducing deforestation will bring additional benefits for biodiversity, rural livelihoods etc. Challenge: Payments from carbon markets would be based on carbon! (reduced emissions) Carbon contents of forests vary widely Brazil: average 104 t C/ha Sudan: average 6 t C/ha Similar in-country variations, e.g. lowland Amazon vs. cerrados Potential finance from AD varies proportionally Income variation does not necessarily match highest biodiversity threat, human dev. needs, etc.! Co-benefits: Biodiversity Cons. Similar variations within countries, e.g. lowland Amazon vs. Cerrados Great variations in biodiversity richness and threat between and within countries 8

9 Co-benefits: Biodiversity Conservation Mixed relationship between finance potential from AD and threat to biodiversity on a national (and local) level Possible solutions? Rewards for AD not exclusively based on carbon Co-financing from non-carbon funds Biodiversity richness (NBI) Co-benefits: Enhancing rural livelihoods Will AD benefit human development? Hope: Govt. uses carbon finance to enhance rural livelihoods Challenges: Implementation tools: e.g. law enforcement vs. direct payments Drivers of deforestation: e.g. small-scale vs. industrial agriculture Income potential from AD per capita vs. funding needs for human development Corruption 9

10 Co-benefits: Enhancing rural livelihoods Health index Potential income p.c. - Prevalence of certain diseases - Child mortality The governance challenge Good governance WBI governance Indonesia Brazil Mongolia Zambia Myanmar How realistic is it to realise the theoretical income & mitigation potential? Some of the countries with the highest potential carbon income have severe governance issues Zimbabwe Solomon Guinea Liberia Deficiencies (corruption, capacity, ) Bolivia Congo, DR Potential income / GDP 10

11 The governance challenge? WBI governance indicators (aggregate) Within-country variation. (poor data) Governance at the forest frontier? Outlook Political process: post-kyoto negotiations, regional climate mitigation agreements Voluntary carbon markets evolving in parallel Needs to engage with political process: Develop credible and acceptable baselines Quantify and manage risk of Amazon die-back Incorporate degradation pragmatically in LUC monitoring Ensure and enhance AD co-benefits through Efficient frameworks for co-financing? Non-carbon criteria for payments (see CDM)? Address governance challenge 11

12 Thank you!! 12

13 Country (Non-Annex I, net deforestation) Potential annual income at.. 10 % defor. red., 15 / tco2 ( million) Potential annual income as share of GDP at % defor. red., 15 /tco2 (percent) WBI governance indicators Mean of 2 indicators Potential winners of trading approach (Top 30) Off the chart: Brazil with 1, 632 M (!) = 0.26 % of GDP Sudan with M = 0.09 % of GDP 1 Liberia Congo, DR Solomon Islands Thailand Zambia Togo Bolivia Myanmar Zimbabwe Mongolia Nicaragua Benin Central African Rep Madagascar Honduras Malawi Sierra Leone Cambodia Burundi Papua New Guinea Cameroon Guinea Paraguay Nepal Ghana Ethiopia Indonesia Ecuador Enhancing rural livelihoods Health index Predicted income - Prevalence of certain diseases - Child mortality 13

14 Deforestation Baselines Forest area Forest cover Annual change Annual change A - Dominican Republic A - Gabon B - Papua New Guinea B/C - Costa Rica C - Vietnam (1000 ha) 1,376 21,775 29,437 2,391 12,931 (Percent of land area) (1000 ha) / (Percent) / Baselines for carbon crediting Risk of creating hot air getting countries on board which halted or reversed deforestation have not (yet) deforested have lost most forest all of these have low historical baselines to credit against - There are trade-offs between economic / political attractiveness, fairness & environmental effectiveness! Gabon Thailand 14

15 Carbon content of forests varies widely Potential rewards from RED vary proportionally R D C ,000, 000 P D Criteria for RED - Emission Reductions Sudan: 19.5 M/yr at 10% and 15 / t CO 2 DR Congo: M/yr I.e. some countries / areas would gain almost nothing Country Deforested area (1000 ha/y, average ) Brazil 2,822 Indonesia 1,872 Sudan 589 Myanmar 467 DR Congo 461 Zambia 445 Tanzania 412 Nigeria 410 Zimbabwe 313 Venezuela 288 Other 68 countries 3,257? Trend to Carbon Leakage International leakage Market leakage and activity shifting, e.g. soy and timber production Same problem as for any mitigation action with significant scale Likelihood for leakage depends on drivers for deforestation Markets would find areas with low opportunity costs Ultimate goal is inclusion of all deforesting countries Project crediting (modified CDM, alternative option) Problem: Leakage up to 100% for conservation projects Leakage = displacement of emissions /deforestation EU and most NGOs oppose CDM option Shadows of history ( Don t sink Kyoto! ) 15

16 Basin-wide water deficit caused by the recent Amazonian droughts WD year WD mean = WD difference Aragão et al. (2007) 16