* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download MATCH - Status of research
Global warming hiatus wikipedia , lookup
Heaven and Earth (book) wikipedia , lookup
Climate resilience wikipedia , lookup
Climate change mitigation wikipedia , lookup
Low-carbon economy wikipedia , lookup
Climatic Research Unit email controversy wikipedia , lookup
Fred Singer wikipedia , lookup
Global warming controversy wikipedia , lookup
ExxonMobil climate change controversy wikipedia , lookup
Michael E. Mann wikipedia , lookup
Effects of global warming on human health wikipedia , lookup
Climate change denial wikipedia , lookup
Mitigation of global warming in Australia wikipedia , lookup
Soon and Baliunas controversy wikipedia , lookup
Climatic Research Unit documents wikipedia , lookup
Climate change adaptation wikipedia , lookup
Instrumental temperature record wikipedia , lookup
Economics of climate change mitigation wikipedia , lookup
Climate change in Tuvalu wikipedia , lookup
Global warming wikipedia , lookup
Climate change feedback wikipedia , lookup
United Nations Climate Change conference wikipedia , lookup
German Climate Action Plan 2050 wikipedia , lookup
Climate engineering wikipedia , lookup
Climate sensitivity wikipedia , lookup
2009 United Nations Climate Change Conference wikipedia , lookup
General circulation model wikipedia , lookup
Climate governance wikipedia , lookup
Effects of global warming wikipedia , lookup
Citizens' Climate Lobby wikipedia , lookup
Climate change in New Zealand wikipedia , lookup
Politics of global warming wikipedia , lookup
Economics of global warming wikipedia , lookup
Climate change and agriculture wikipedia , lookup
Solar radiation management wikipedia , lookup
Media coverage of global warming wikipedia , lookup
Attribution of recent climate change wikipedia , lookup
United Nations Framework Convention on Climate Change wikipedia , lookup
Effects of global warming on humans wikipedia , lookup
Public opinion on global warming wikipedia , lookup
Scientific opinion on climate change wikipedia , lookup
Climate change in Canada wikipedia , lookup
Climate change and poverty wikipedia , lookup
Climate change, industry and society wikipedia , lookup
Surveys of scientists' views on climate change wikipedia , lookup
Status of research SB-20 21 June 2004 Xiaosu Dai, Michel den Elzen, Niklas Höhne Overview 1. Introduction to the MATCH process Niklas Höhne / Xiaosu Dai 2. Introduction of first joint paper Michel den Elzen / Niklas Höhne Modelling and assessment of contributions to climate change SBSTA 17 (Oct 2002) • Work should be continued by the scientific community, in particular to improve the robustness of the preliminary results and to explore the uncertainty and sensitivity • Be of a standard consistent with the practices of peer-reviewed published science. • The process should be inclusive, open and transparent. • Capacity building: strongly encouraged Parties and institutions to facilitate capacity-building in developing countries, including by hosting scientists from developing countries • Invited the scientific community, including IGBP, WCRP, IHDP and IPCC to provide information on how they could contribute • Encouraged scientists to undertake further work, to make the results of their work publicly available and to report progress at SBSTA 20, June 2004 (side event). • SBSTA decided to review the progress at its 23rd session (Nov 2005). Modelling and assessment of contributions to climate change MATCH process UNFCCC process • • Two expert meetings Coordinated modelling exercise “ACCC” • • • Ad-hoc group Initiated by Brazil and UK Two expert meetings so far Modelling and assessment of contributions to climate change MATCH process Objective: • Assess methods for calculating the contribution of different emission sources (e.g. regional, national or sectoral) to climate change and its impacts, taking into account uncertainties, and the sensitivity of the calculations to the use of different methods, models and methodological choices. Outputs: • Provide clear guidance on the implications of the use of the different scientific methods, models, and methodological choices • Where scientific arguments allow, recommend one method/model/choice or several possible methods/models/choices for each step of the calculation of contributions to climate change, taking into account scientific robustness, practicality and data availability • Organization of expert meetings, workshops and a coordinated modelling exercise • Prepare papers to be published in peer reviewed scientific journals Modelling and assessment of contributions to climate change MATCH process Scientific Coordination Committee Xiaosu Dai National Climate Center, China Michel den Elzen RIVM, Netherlands Jan Fuglestvedt CICERO, Center for International Climate and Environmental Research - Oslo, Norway Jason Lowe Met Office, Hadley Centre for Climate Prediction and Research, UK Joyce Penner University of Michigan, USA Michael Prather (Chair) University of California at Irvine, USA Cathy Trudinger CSIRO Atmospheric Research, Australia Murari Lal IIT, India José Domingos Gonzalez Interministerial Committee on Global Climate Change, Miguez Brazil Niklas Höhne (Secretary) ECOFYS, Germany Modelling and assessment of contributions to climate change MATCH process Developing country participation: • Fund for travel costs of developing country experts sponsored by governments of Germany, Norway, UK (currently funds for further 15 developing country expert trips) Support unit: • Ecofys under contract to UK Defra Information: • http://www.match-info.net Modelling and assessment of contributions to climate change MATCH-info.net • Background • Organization • Papers • Expert meetings • File exchange • Discussion forum Modelling and assessment of contributions to climate change Participation at last meeting Atsushi Kurosawa Atul Jain Ben Matthews Cathy Trudinger Christiano Pires de Campos Fabian Wagner Gregory Bodeker Jan Fuglestvedt Jason Lowe Jesper Gundermann José Domingos Gonzalez Miguez Joyce Penner Maria Silvia Muylaert de Araujo Coppe Martin Weiss Michael Prather Michel den Elzen Murari Lal Niklas Höhne Rachel Warren Simone Ullrich Xiaosu Dai The Institute of Applied Energy Research and Development, Japan University of Illinois, USA Universite catholique de Louvain, Belgium CSIRO, Australia Federal University of Rio de Janeiro, Brazil IIASA, Germany NIWA, New Zealand CICERO, Norway Met Office, Hadley Centre, UK Danish Environmental Protection Agency Interministerial Committee on Global Climate Change, Brazil University of Michigan, USA Federal University of Rio de Janeiro, Brazil German Enironmntal Agency University of California at Irvine, USA RIVM, Netherlands University of the South Pacific, FIJI Ecofys, Germany UK DEFRA Ecofys GmbH National Climate Cente, China Modelling and assessment of contributions to climate change Individual scientific papers • • • • • • • Pinguelli & Kahn (2001): The present, past, and future contributions to global warming of CO2 emissions from fuels, Climatic Change den Elzen and Schaeffer (2002): Responsibility for past and future global warming: Uncertainties in attributing anthropogenic climate change, Climatic Change Trudinger & Enting (2004): Comparison of formalisms for attributing responsibility for climate change: Non-linearities in the Brazilian Proposal approach, Climatic Change Andronova and Schlesinger (2004): Importance of sulfate aerosol in evaluating the relative contributions of regional emissions to the historical global temperature change attribution methods, Mitigation and Adaptation Strategies for Global Change den Elzen, Schaeffer and Lucas (2004): Differentiating future commitments on the basis of countries' relative historical responsibility for climate change: uncertainties in the 'Brazilian Proposal' in the context of a policy implementation, Climatic Change Pinguelli, Kahn, Muylaert and Pires de Campos (2004): Comments on the Brazilian Proposal and contributions to global temperature increase with different climate responses—CO2 emissions due to fossil fuels, CO2 emissions due to land use change, Energy Policy Höhne and Harnisch (2004): Calculating historical contributions to climate change – discussing the ‘Brazilian Proposal’, Climatic Change Modelling and assessment of contributions to climate change Anticipated papers Paper #1 Analysing countries’ contribution to climate change: Scientific choices and methodological issues: status of the work and first results Paper #2 Demonstration of credible alternative scientific choices and their effect on the emissions, concentration and climate change Paper #3 Formal assessment of uncertainties and clarify parameter space Paper #4 Additional attribution calculations discussed in paper #1 by including the outputs from paper #2 and paper #3 Modelling and assessment of contributions to climate change Schedule Meeting September 2003: • Formation of the ad-hoc group MATCH • Agreement on terms of reference, scientific coordination committee, research questions Meeting May 2004: • Discussion of draft paper #1 • Discussion of development of further papers June 2004: SB 20 side event Meeting December 2004 (tentatively 2/3 December in Brazil): • Discussion of draft paper #2 • Discussion of development of further papers Meeting May 2005: Discussion of draft paper #3 Meeting September 2005: Discussion of draft paper #4 SB 23 November 2005: Presentation of results Modelling and assessment of contributions to climate change Remarks Challenges • New research • Resource requirements for contributing experts • Links to other organizations and programmes • Ambitious schedule Strong points of MATCH • Participation of leading experts on the topic • Joint research effort • Results are peer-reviewed publications Modelling and assessment of contributions to climate change 2. First joint paper Analysing countries’ contribution to climate change: Scientific choices and methodological issues Modelling and assessment of contributions to climate change Main objective of paper #1 • to summarise the studies and results so far (i.e. the contributions to the UNFCCC initiated process) • to present new attribution calculations with non-linear carbon cycle and climate models using non-linear attribution methodologies and updated historical emissions datasets • to investigate the effect of a range of scientific, methodological and policy-related choices on the attribution, but not the full range by all uncertainties. Modelling and assessment of contributions to climate change Policy choices • Policy choices refer: to parameters of which the values can not be based on objective ‘scientific’ arguments alone. For example, 100 year time horizon of GWPs. The choices have to be made largely within the policy context. • Policy choices analysed here: – Indicator – Timeframes – Emission scenarios – Mixture of Greenhouse gases – Attribution method Modelling and assessment of contributions to climate change Scientific uncertainties • Choice of the dataset on historical emissions • Choice of the representation of the climate system (different models) Modelling and assessment of contributions to climate change Models used Model Carbon cycle (CO2) Atmospheric chemistry (non-CO2) Sulphate aerosols Radiative forcing Temperature and sea level rise ACCC (default) CICERO - SCM IRF (Bern) fixed lifetimes Hadley IPCC-TAR IRFs (Hadley) IPCC-TAR IPCC-TAR ACCC EBC/UDO model (Schlesinger et al., 1992). ACCC Non-linear v ACCC or ACCC none ACCC v non-linear ACCC ACCC ACCC ACCC ECOFYS - ACCC ACCC* ACCC IPCC-TAR ACCC ACCC ACCC and other IRFS RIVM - ACCC Bern nonIPCC-TAR IPCC-TAR ACCC IPCC-TAR JCM - SCM linear ACCC ACCC ACCC ACCC ACCC IVIG - ACCC v * Same methodology used as in the ACCC model; The mixed layer response function of Joos et al. (1996); CSIRO - SCM Modelling and assessment of contributions to climate change Model show similar outcomes Source: UNFCCC Modelling and assessment of contributions to climate change Policy choices 1. Indicator 2. Timeframes 3. Attribution method 4. Mixture of greenhouse gases Modelling and assessment of contributions to climate change 1. Indicators Historical emissions Attribution end date Evaluation date Emissions Time Present Concentrations Increasing certainty Increasing relevance Time A B C Radiative forcing Time D Temperature change E Time F Source: Ecofys-ACCC Sea level rise Time Modelling and assessment of contributions to climate change 1. Indicators Name of indicator A Radiative forcing GWP-weighted B cumulative emissions Weighted C concentrations D Temperature increase Integrated E temperature increase F Sea level rise Backward discounting Forward looking X - - X X X * + + X - X X * X - + *: Also discounting most recent emissions +: Can be made forward looking, when evaluating at a date after attributed emissions end. In such case also a time horizon is required Modelling and assessment of contributions to climate change 1. Indicators 70% 50% 45% 40% 35% 30% 60% 50% 40% Radiative forcing GWP-weighted cumulative emissions Weighted concentrations Temperature increase Integrated temperature 25% 20% 15% 10% 5% 0% 30% 20% 10% 0% Fossil CO2 Forestry CO2 CH4 N2O OECD90 REF ASIA ALM Relative contributions using different indicators Modelling and assessment of contributions to climate change 1. Indicators Conclusions • Two main factors influence results • Whether a source emitted ‘early’ versus ‘late’ • The share of emissions of short-lived / long-lived gases. • Choosing the right indicator is ultimately a policy choice that also depends on the purpose of use of the results. • Temperate increase: use evaluation date after the attribution end date • ‘Backward discounting’ and ‘forward looking’: ‘weighted concentrations’ or ‘integrated temperature’ • Not ‘backward discounting’: GWP-weighted cumulative emissions could be an option, which is simple and approximately represents the integrated impact on temperature. Modelling and assessment of contributions to climate change 2. Timeframe Historical emissions • Start date emissions 1890, 1950 and 1990 Concentrations Time Increasing certainty • Evaluation date of attribution 2000, 2050, 2100, 2500 Time Present Increasing relevance • End date emissions 1990, 2000, 2050 and 2100 Attribution end date Evaluation date Emissions A B C Radiative forcing Time D Temperature change E Time F Sea level rise Time Modelling and assessment of contributions to climate change Start-date % Contribution to temperature incr ease in 2000 50 45 40 35 30 % 1765 1850 25 ref 20 Contribution to temperature incr ease in 2000 1950 1990 25 20 15 10 5 0 15 10 5 0 OECD90 EEUR & FSU As ia Africa & Latin America USA South Amer South. OECD Africa Europe FSU South Asia East Asia Source: RIVM-ACCC • Choosing a shorter time horizon (e.g. 1950 or 1990 instead of 1890) reduces the contributions of OECD90 countries ('early emitters') to temperature increase. Modelling and assessment of contributions to climate change End-date % Contribution to temperature incr ease in 2100 1990 2000 (ref ) 2050 2100 50 45 40 35 30 % Contribution to temperature incr ease in 2100 25 20 15 25 20 15 10 5 0 10 5 0 OECD90 EEUR&FSU Asia Afric a & Latin America USA South Amer South. OECD Africa Europe FSU South Asia East Asia Source: RIVM-ACCC • A late end-date increases non-Annex-I contributions, because it gives more weight to their larger future emissions. • Impact of emissions scenarios (error bars) can be large Modelling and assessment of contributions to climate change Evaluation-date % 50 Co ntr ibution to temperature in crease in : (end date 2000) % 45 40 2000 (r ef) 35 30 2100 2050 Co ntr ibution to temperature in crease in : (end date 2000) 25 20 15 25 20 10 15 10 5 5 0 0 OECD90 EEUR&FSU As ia ALM USA South Amer South. OECD Africa Europe FSU South Asia East Asia Source: RIVM-ACCC • A later evaluation-date raises OECD contributions due to: (1) their large share in historical CO2 emissions (long residence time) (2) and their small share of methane emissions (short residence time) Modelling and assessment of contributions to climate change 3. Attribution methods • Normalised marginal method - Attributes responsibility using total sensitivities determined "at the margin". • Residual (all-but-one) method - Attributes responsibility by leaving out the emissions of each region in turn. • Time-sliced - determines the effect of emissions from each time as if there were no subsequent emissions. Modelling and assessment of contributions to climate change 3. Attribution methods • The Residual method, although simple to implement and explain, can be rejected on scientific grounds (not additive). • The Normalised marginal and Timesliced methods are harder to implement and explain. These methods differ in how they treat early vs. late emissions. Modelling and assessment of contributions to climate change 3. Attribution methods % Contribution to temperature increase in 2000 45 % Contribution to temperature increase in 2000 25 40 N. Marg 35 30 T. Sliced N. Resid 25 N. Marg 20 T. Sliced N. Resid 15 20 10 15 10 5 5 0 0 OECD90 EEUR & FSU A sia A frica & Latin A merica USA Latin A mer A frica OECD Euro pe FSU India + So uth A sia East A sia Source: CSIRO-SCM • The differences between methods are fairly small compared to the effects of many of the other choices already considered. Modelling and assessment of contributions to climate change 3. Attribution methods % Contribution to temperature increase in 2100 40 35 N. Marg 30 T. Sliced 25 N. Resid % Contribution to temperature increase in 2100 25 N. Marg 20 T. Sliced N. Resid 15 20 10 15 10 5 5 0 0 OECD90 EEUR & FSU A sia A frica & Latin A merica USA Latin A mer A frica OECD Euro pe FSU India + So uth A sia East A sia • Differences between methods are greater Source: Source: CSIRO-SCM CSIRO-SCM for later evaluation date (2100) • In general, the results of the different methods vary most for regions with emissions that differ most from the average in terms of early versus late emissions, i.e. India and EU. Modelling and assessment of contributions to climate change 4. Greenhouse gas mixture Which gases are attributed to the regions? 1. Fossil CO2 2. All anthropogenic CO2 3. CO2, CH4, N2O 4. Kyoto basket (CO2, CH4, N2O, HFCs, PFCs, SF6) 5. Kyoto basket + more O3 precursors (NOx, CO and VOC) Modelling and assessment of contributions to climate change 4. Greenhouse gas mixture 60% Greenhouse gas mix, attribution period 1890-2000 CO2FF 2000 (dT=0.58) CO2ALL 2000 (dT=0.74) 50% Greenhouse gas mix, attribution period 1890-2000 30% CO2FF 2000 (dT=0.58) 25% CO2ALL 2000 (dT=0.74) KP3 2000 (dT=1.06) KP3 2000 (dT=1.06) 40% KP6 2000 (dT=1.07) 20% KP6 2000 (dT=1.07) KP6_O3P 2000 (dT=1.07) 30% 15% 20% 10% 10% 5% 0% KP6_O3P 2000 (dT=1.07) Am er ic a M id dl e Ea st Af ri c a La ti n IS Eu ro C pe hi na re gi on Ea st As ia So ut h As ia C Ea st er n Eu ro pe O ce an ia D SA Ja pa n EC O Source: CICERO-SCM ALM U ASIA C REF an ad a 0% OECD90 • Two main effects i) Going from fossil fuel CO2 emissions only to total anthropogenic CO2 emissions, ii) Inclusion of CH4 and N2O. • The effect is less pronounced on longer time scales (except for the shift from fossil CO2 to total CO2). Modelling and assessment of contributions to climate change Scientific uncertainties 1. 2. Choice of the dataset on historical emissions Choice of the representation of the climate system: carbon cycle and climate model and feedbacks Modelling and assessment of contributions to climate change 1. Historical datasets % Contribution to temperature incr ease in 2000 % Contribution to temperature incr ease in 2000 25 50 45 40 35 30 r ef CDIA C Hou ghton 25 20 15 10 5 0 ref 20 CDIA C Houghton 15 10 5 0 OECD90 EEUR & FSU As ia Africa & Latin America USA South Amer South. OECD Africa Europe FSU South Asia East Asia Source: RIVM-ACCC • Fossil CO2 emissions: small differences in relative attribution • CO2 emissions from land-use changes: differences in estimates leading to large differences. Data sets need to be compared and improved. • CH4 and N2O: Only one dataset is available (EDGAR) Modelling and assessment of contributions to climate change 2. Other scientific uncertainties • The influence of other climate model parameters (e.g. IRFs), based on simulation experiments with nine GCMs and climate models is limited • Including additional non-linearities in calculations of methane-concentrations (IPCC-TAR atmospheric chemistry model ) has a negligible effect on the relative contributions • ... Modelling and assessment of contributions to climate change Overall conclusions • First summary of the work undertaken to date. • Not a full assessment of the uncertainty range, but an evaluation of the influence of different policy-related and scientific choices. • The influence of scientific choices is notable. Therefore research is ongoing (see papers #2 and #3) • However, the current work suggests, that the impact of policy choices, such as time horizon of emissions, climate change indicator and greenhouse-gas mix is larger than the impact of scientific uncertainties • Impact of uncertainties on the relative contributions is smaller than impact of uncertainties on the absolute changes in temperature. • Research needs: Historical emission datasets Modelling and assessment of contributions to climate change Backup slides Policy choices Indicators Timeframes Attribution methods Attributed greenhouse gases (GHGs) Data Regions Radiative forcing, GWP-weighted cumulative emissions, weighted concentrations, temperature increase, integrated temperature, sea level rise Attribution start 1890, 1950 and 1990 dates Attribution end dates 1990, 2000, 2050 and 2100 Evaluation dates 2000, 2050, 2100, 2500 Normalized marginal, residual, time-sliced Fossil CO2, CO2, CO2, CH4, N2O, Kyoto-GHGs (including F-gases), all GHGs (including the other halocarbons (CFCs)) Historical emissions CDIAC database (fossil CO2, land-use CO2), EDGAR (all KP-GHGs), IEA (fossil CO2) Future emissions IPCC SRES B1, A2 and A1F emission scenario Four regions (Nakicenovic et al. 2000): OECD90; Eastern Europe and Former Soviet Union (REF); Asia (ASIA); Africa and Latin America (ALM), and 13 world regions: Canada, USA, Latin America, Africa, OECD Europe, Eastern Europe, Former USSR (FSU), Middle East, South Asia, East Asia, South East Asia, Oceania and Japan Modelling and assessment of contributions to climate change Models are calibrated Modelling and assessment of contributions to climate change E5 Gg CO2 - res idual Gg 10 1950 2000 2000 1950 2000 2050 1950 2000 2050 1950 2000 2050 0 -4 1900 x 10 4 2050 2 0 -4 1900 x 10 1 2050 °C 2050 2000 0.01 2050 1950 P uls e emis s ions of 1E5 Gg CO2 - proportional 5 W/m2 2000 4 0 1900 0.02 2050 ppm 2000 x 10 0.5 2000 0 1900 2050 1950 ars 2000 2050 Years =1 =0.6 1950 2000 2050 Table 3 No. Name of the indicator Radiative forcing due to increased A concentrations B GWP-weighted cumulative emissions C Weighted concentrations D Temperature increase E Integrated temperature F Sea level rise * CO2 CH4 N2O CO2 CH4 N2O CO2 CH4 N2O CO2 CH4 N2O CO2 CH4 N2O CO2 CH4 N2O 1900 1950 1990 2000 * 0.29 0.36 0.56 1 * 0.015 1.0 28 64 * 81 126 180 196 + 1 1 1 1 + 20 20 20 20 + 323 323 323 323 0.29 0.36 0.56 1 0.005 0.31 8.6 20 134 208 296 323 Max year 3.44 3.92 4.45 1 1983 9 33 262 64 1991 927 1290 1220 196 1976 0.90 0.93 1.03 1 1993 2.2 3.3 16 22 2000 189 260 327 324 1994 To be completed : Represent instantaneous GWPs. : Represent GWPs. Values slightly different to those of IPCC-TAR due to use of different parameters. + Contribution to radiative forcing Modelling and assessment of contributions to climate change Aerosol forcing Attributing SO2, attribution period 1890-2000 45% Attributing SO2, attribution period 1890-2000 30% KP3 2000 (dT=1.06) KP3 2000 (dT=1.06) 40% KP6_SO2 2000 (dT=0.51) 25% KP6_SO2 2000 (dT=0.51) 35% 20% 30% 25% 15% 20% 10% 15% 10% 5% 5% Am er ic a M id dl e Ea st Af ri c a La ti n IS Eu ro C pe hi na re gi on Ea st As ia So ut h As ia C Eu ro pe O ce an ia Ea st er n O EC D Ja pa n ALM SA ASIA U REF C OECD90 an ad a 0% 0% Source: CICERO-SCM • Inclusion of SO2 emissions reduces the contributions from ASIA and REF, but the effect disappear when there is a gap between attribution end date and evaluation date. • Again effect is less less pronounced on longer time scales Modelling and assessment of contributions to climate change A1b s non-li indic AOS start d EDG indic indic non-li evalu only indic only f defaul Canada 1.6 0.1 0.0 -0.1 0.0 0.0 -0.1 -0.1 0.1 0.0 0.0 0.0 0.0 -0.3 USA 17.9 3.1 2.0 1.1 0.7 0.5 0.3 0.1 -0.2 -0.9 -0.7 -0.8 -1.0 -2.7 Central America 2.9 -0.7 0.0 -0.3 -0.1 0.0 -0.3 -0.2 0.6 0.0 -0.1 0.0 -0.1 0.3 South America 7.3 -2.5 -0.1 -0.3 -0.2 0.0 -0.4 -0.1 0.1 0.1 -0.1 -0.1 0.0 0.8 Northern Africa 1.7 0.0 -0.4 -0.1 -0.1 -0.1 0.1 0.0 0.0 0.1 0.1 0.2 0.2 0.4 Western Africa 2.1 -1.2 -0.1 -0.6 -0.2 0.0 -0.6 -0.6 -0.2 0.1 -0.1 0.0 0.0 0.2 Eastern Africa 1.0 -0.7 0.0 -0.2 -0.1 0.0 -0.3 -0.2 -0.2 0.0 0.0 0.0 0.0 0.0 Southern Africa 1.8 -0.1 -0.2 -0.1 -0.1 0.0 -0.1 0.0 0.1 0.1 0.0 0.1 0.1 0.6 OECD Europe 11.2 2.5 2.0 1.0 0.7 0.5 0.1 0.0 0.2 -0.8 -0.7 -0.8 -1.0 -0.8 Eastern Europe 3.1 0.6 0.2 0.2 0.1 0.1 0.1 0.0 0.3 0.0 -0.1 -0.1 -0.1 -0.3 Former USSR 9.2 0.3 0.8 -0.1 -0.3 0.3 -0.6 -0.6 -0.6 0.2 -0.4 -0.3 -0.5 -0.8 Middle East 5.4 0.6 -1.3 0.1 -0.1 -0.3 0.6 0.5 -0.1 0.3 0.5 0.5 0.6 1.1 South Asia 10.1 -1.4 -0.9 -0.5 -0.3 -0.3 0.4 -1.0 -1.9 0.1 0.3 0.7 0.5 1.4 East Asia 14.4 1.3 -2.1 0.0 -0.1 -0.6 0.9 1.6 2.4 0.7 1.1 0.7 1.3 -0.2 South East Asia 5.9 -2.4 -0.3 -0.3 -0.3 -0.1 -0.2 0.2 -0.5 0.2 0.1 0.1 0.1 0.5 Oceania 1.2 0.0 0.0 -0.1 0.0 0.0 -0.1 -0.1 0.0 0.0 0.0 0.0 0.0 -0.1 Japan 3.1 0.5 0.1 0.4 0.2 0.0 0.2 0.4 -0.1 0.0 0.0 -0.1 -0.1 -0.2 Canada 1.6 0.1 0.0 0.0 0.0 0.1 0.0 -1.5 0.0 -1.8 0.0 -2.1 0.0 -0.3 OECD90 35.1 6.2 4.3 -0.1 2.3 1.6 1.0 -0.1 0.4 -0.1 0.4 0.1 -1.7 -4.1 USA 17.9 3.1 2.0 1.1 0.7 0.5 0.3 0.1 -0.2 -0.9 -0.7 -0.8 -1.0 EEUR & FSU 12.3 0.9 1.0 0.1 -0.2 0.3 -0.5 -0.6 -0.3 0.1 -0.4 -0.4 -0.6 -2.7 -1.1 Central 2.9 -0.7 0.0 -0.3 0.0 -0.3 0.6 0.0 0.0 0.3 Asia America 30.4 -2.5 -3.3 -0.8 -0.1 -0.6 -1.0 1.1 -0.2 0.8 -0.1 1.0 -0.1 1.4 1.5 -0.1 2.0 1.7 South America 7.3 -2.5 -0.1 -0.3 -0.2 0.0 -0.4 -0.1 0.1 0.1 -0.1 -0.1 0.0 0.8 Africa & Lam 22.3 -4.6 -2.0 -1.7 -0.8 -0.4 -1.0 -0.6 0.4 0.6 0.4 0.7 0.8 3.5 Northern Africa 1.7 0.0 -0.4 -0.1 -0.1 -0.1 0.1 0.0 0.0 0.1 0.1 0.2 0.2 0.4 Annex-I 47.3 7.1 5.3 2.4 1.4 1.4 -0.1 -0.2 -0.3 -1.6 -1.9 -2.2 -2.7 -5.2 Western Africa 2.1 -1.2 -0.1 -0.6 -0.2 0.0 -0.6 -0.6 -0.2 0.1 -0.1 0.0 0.0 0.2 non–Annex I 52.7 -7.1 -5.3 -2.4 -1.4 -1.4 0.1 0.2 0.3 1.6 1.9 2.2 2.7 5.2 Eastern Africa 1.0 -0.7 0.0 -0.2 -0.1 0.0 -0.3 -0.2 -0.2 0.0 0.0 0.0 0.0 0.0 Southern Africa 1.8 -0.1 -0.2 -0.1 -0.1 0.0 -0.1 0.0 0.1 0.1 0.0 0.1 0.1 0.6 OECD Europe 11.2 2.5 2.0 1.0 0.7 0.5 0.1 0.0 0.2 -0.8 -0.7 -0.8 -1.0 -0.8 increasing non-Annex I contribution decreasing non-Annex I contribution Eastern Europe 3.1 0.6 0.2 0.2 0.1 0.1 0.1 0.0 0.3 0.0 -0.1 -0.1 -0.1 -0.3 Formerdecrease USSR relative to default 9.2 contribution 0.3 0.8> 15% -0.1 -0.3 increase 0.3 relative -0.6 to -0.6 -0.6 0.2 -0.4 -0.3 -0.5 -0.8 default contribution > 15% -X.X X.X Middle East 5.4 0.6decrease -1.3 > 5%0.1 -X.X -0.1 increase -0.3 0.6 0.5 -0.1 0.3 0.5 0.5 0.6 1.1 > 5% X.X < 5% South Asia 10.1 -1.4decrease -0.9 < 5% -0.5 -X.X -0.3 increase -0.3 0.4 -1.0 -1.9 0.1 0.3 0.7 0.5 1.4 X.X East Asia 14.4 1.3 -2.1 0.0 -0.1 -0.6 0.9 1.6 2.4 0.7 1.1 0.7 1.3 -0.2 X.X is absolute change in contribution South East Asia 5.9 -2.4 -0.3 -0.3 -0.3 -0.1 -0.2 0.2 -0.5 0.2 0.1 0.1 0.1 0.5 Oceania 1.2 0.0 0.0 -0.1 0.0 0.0 -0.1 -0.1 0.0 0.0 0.0 0.0 0.0 -0.1 Japan 3.1 0.5 0.1 0.4 0.2 0.0 0.2 0.4 -0.1 0.0 0.0 -0.1 -0.1 -0.2 OECD90 35.1 6.2 4.3 2.3 1.6 1.0 0.4 0.4 0.1 -1.7 -1.5 -1.8 -2.1 -4.1 EEUR & FSU 12.3 0.9 1.0 0.1 -0.2 0.3 -0.5 -0.6 -0.3 0.1 -0.4 -0.4 -0.6 -1.1 Modelling contributions climate change Asia 30.4 -2.5 and -3.3 assessment -0.8 -0.6 -1.0 of1.1 0.8 -0.1 1.0 to 1.4 1.5 2.0 1.7 Africa & Lam 22.3 -4.6 -2.0 -1.7 -0.8 -0.4 -1.0 -0.6 0.4 0.6 0.4 0.7 0.8 3.5 Annex-I 47.3 7.1 5.3 2.4 1.4 1.4 -0.1 -0.2 -0.3 -1.6 -1.9 -2.2 -2.7 -5.2 A1b scenario non-lin. CO 2 concentration indicator forcing AOS C-cycle (w.r.t. NonLinConc) start date 1950 EDGAR indicator cumulative emissions indicator CO 2 concentrations non-lin. forcing evaludation date 2100 only CO 2 emissions indicator SLR only fossil CO 2 emissions default Policy choices vs. scientific choices Source: RIVM-ACCC • Policy choices (start-date, indicators) are more important than scientific uncertainties (attribution method, climate model)