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1 MATCH paper 1: contributions to climate change SB-23 17 May 2006 Niklas Höhne 2 MATCH paper #1 Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices – – – – – – – – – Michel den Elzen (RIVM, Netherlands) Jan Fuglestvedt (CICERO, Norway) Niklas Höhne (Ecofys, Germany) Cathy Trudinger (CSIRO, Australia) Jason Lowe (Hadley, UK) Ben Matthews (UCL, Belgium) Bård Romstad (CICERO, Norway) Christiano Pires de Campos (Brazil) Natalia Andronova (UIUC, USA) M. den Elzen, J. Fuglestvedt, N. Höhne, C. Trudinger, J. Lowe, B. Matthews, B. Romstad, C. Pires de Campos, N. Andronova, 2005: “Analysing countries’ contribution to climate change: Scientific uncertainties and methodological choices”, Environmental Science and Policy, 8 (2005) 614–636 Modelling and assessment of contributions to climate change Cause-effect chain Emissions Region A Emissions Region B Emissions Region C Emissions Region D Concentrations Radiative forcing Global average temperature change Impact in Region A Impact in Region B Impact in Region C Impact in Region D Modelling and assessment of contributions to climate change 3 4 Attributed effects Temperature increase Total temperature increase Attributed temperature increase Region A Region B Region C Unattributed Region D Time Attribution start date, e.g. 1900 Attribution period Today 5 Choices • Policy choices (values can not be based on objective ‘scientific’ arguments) : – Indicator (e.g. temperature increase, radiative forcing, …) – Timeframes – Mixture of greenhouse gases – Attribution method • Scientific choices – 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 6 Main objective of paper #1 • Summarise the studies and results so far (i.e. the contributions to the UNFCCC initiated process) • Present new attribution calculations with non-linear carbon cycle and climate models using non-linear attribution methodologies and updated historical emissions datasets • 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 7 Models used Model Carbon cycle (CO2) Atmospheric chemistry (non-CO2) Sulphate aerosols Radiative forcing Temperature and sea level rise ACCC (default): ECOFYS-ACCC IVIG-ACCC UIUC-ACCC CSIRO-ACCC RIVM-ACCC UCL-ACCC CICERO-SCM UCL-JCM IRF (Bern) fixed lifetimes Hadley IPCC-TAR IRFs (Hadley) ACCC* ACCC ACCC Non-linear v Bern non-linear ACCC ACCC or IPCC-TAR ACCC IPCC-TAR IPCC-TAR No ACCC ACCC IPCC-TAR IPCC-TAR ACCC ACCC ACCC ACCC ACCC ACCC ACCC or IRFs UDEBv EBC/UDO model UDEBv Modelling and assessment of contributions to climate change Model show similar outcomes °C temperature increase 5.0 1 2 3,4 JCM-JCM (1) Hadley (2) 4.5 4.0 CICERO-SCM (3) CSIRO-ACCC (4) 3.5 5 6 7 8,9 RIVM-ACCC (5) 3.0 ECOFYS-ACCC (6) UCL-ACCC (7) 2.5 IVIG-ACCC (8) UIUC-ACCC (9) 2.0 1.5 1.0 0.5 0.0 -0.5 1900 1950 2000 2050 2100 Modelling and assessment of contributions to climate change 8 9 Models used Policy choices Indicators Timeframes Attribution methods Attributed greenhouse gases (GHGs) Scientific choices Historical emissions Representation of the climate system Radiative forcing, GWP-weighted cumulative emissions, weighted concentrations, temperature increase, integrated temperature, sea level rise Attribution start dates 1765, 1890, 1950 and 1990 Attribution end dates 1990, 2000, 2050 and 2100 Evaluation dates 2000, 2050, 2100, 2500 Normalised marginal, residual, time-sliced Fossil CO2, CO2, [CO2, CH4, N2O], Kyoto-gases (including F-gases, i.e. HFCs, PFCs and SF6), Kyoto gases and ozone precursors CDIAC database (fossil CO2a, land-use CO2b), EDGAR (Kyoto-gases and ozone precursors) c, IVIGd See table 2 1 Modelling and assessment of contributions to climate change Model show similar outcomes 100% 22.4 22.7 21.5 22.4 22.8 22.4 22.0 22.4 ASIA 80% OECD90 UCL-SCM CICERO-SCM UCL-ACCC RIVM-ACCC CSIRO-ACCC 0% EEUR&FSU 39.3 38.3 40.5 39.5 41.2 39.5 37.8 39.6 UIUC-ACCC 20% 14.8 15.3 13.2 14.7 14.9 14.3 14.4 14.3 IVIG-ACCC 40% 23.5 23.8 24.9 23.5 21.0 23.8 25.8 23.7 ECOFYS-ACCC 60% ALM Modelling and assessment of contributions to climate change 10 11 Policy choices 1. Indicator 2. Timeframes 3. Attribution method 4. Mixture of Greenhouse gases Modelling and assessment of contributions to climate change 12 1. Indicators Historical emissions Historicalemissions emissions Historical Emission pulse Emissions Emissions Emissions Attribution end date Evaluation date Time Present Present Present Concentrations Attribution end date Evaluation date Time Concentrations Concentrations forcing Temperature change Temperature change A Increasing certainty Increasing relevance Increasing certainty Increasing relevance Time Radiative forcing Radiative B C A B E Radiative forcing D D E Temperature change F Source: Ecofys-ACCC Time Time Time Time Time Time C Time Time Sea level rise Time E F Sea level rise Time Time Modelling and assessment of contributions to climate change 13 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 14 1. Indicators % 70 % 45 40 35 30 25 20 15 10 5 0 60 50 40 30 20 10 0 Fo ssil CO2 Fo restry CO2 CH4 N2O Radiative Forcing (100%=2.00 W/m2) GWP w eighted cummulative emissions (100%=160) Weighted concentrations (100%=67) Temperature increase (100%=1.19°C) Integrated Temperature increase (100%=84°Cy) Ocean Heat Content (100%=3.8E+9 J/m2) OECD90 EEUR&FSU A SIA A LM Radiative Forcing (100%=2.00 W/m2) GWP w eighted cummulative emissions (100%=160) Weighted concentrations (100%=67) Temperature increase (100%=1.19°C) Integrated Temperature increase (100%=84°Cy) Ocean Heat Content (100%=3.8E+9 J/m2) Relative contributions using different indicators Source: Ecofys-ACCC Modelling and assessment of contributions to climate change 1. Indicators Conclusions • Two main factors: • 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 temperatures’ • 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 15 16 2. Timeframe • Start date emissions 1890, 1950 and 1990 • End date emissions 1990, 2000, 2050 and 2100 • Evaluation date of attribution 2000, 2050, 2100, 2500 Temperature increase Total temperature increase Attributed temperature increase Region A Region B Region C Unattributed Region D Time Attribution start date, e.g. 1900 Attribution period Today Modelling and assessment of contributions to climate change 17 Start-date % Contribution to temperature increase in 2000 1765 (100% = 1.13) 1850 (100% = 1.04) 1890 (100% = 0.99) 1950 (100% = 0.78) 1990 (100% = 0.21) 45 40 35 30 % Contribution to temperature increase in 2000 25 20 15 25 20 10 15 10 5 5 0 0 OECD90 EEUR&FSU A SIA A LM USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia 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 18 End-date % 50 45 40 35 30 25 20 15 10 5 0 Contribution to temperature increase in 2100 1990 (100% = 0.43°C) 2000 (100% = 0.53°C) 2050 (100% = 1.54°C) 2100 (100% = 4.00°C) % Contribution to temperature increase in 2100 25 20 15 10 5 0 OECD90 EEUR&FSU A SIA A LM USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia 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 19 Evaluation-date % 50 45 40 35 30 25 20 15 10 5 0 Contribution to temperature increase in: (end date 2000) % 25 2000 (100% = 0.99°C) 2050 (100% = 0.68°C) 2100 (100% = 0.53°C) Contribution to temperature increase in: (end date 2000) 20 15 10 5 0 OECD90 EEUR&FSU A SIA A LM USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia 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 20 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 21 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 22 3. Attribution methods % Contribution to temperature increase in 2000 % Contribution to temperature increase in 2000 25 45 40 N. Marg (100% = 1.24°C) T. Sliced (100% = 1.24°C) N. Resid (100% = 1.24°C) 20 35 30 15 25 20 10 15 10 5 5 0 0 OECD90 EEUR & FSU A sia A LM USA Latin A mer A frica OECD Euro pe FSU 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 23 3. Attribution methods % Contribution to temperature increase in 2100 % Contribution to temperature increase in 2100 25 40 35 N. Marg (100% = 4.04°C) T. Sliced (100% = 4.04°C) N. Resid (100% = 4.04°C) 20 30 25 15 20 10 15 10 5 5 0 0 OECD90 EEUR & FSU A sia A LM USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia Source: CSIRO-SCM • Differences between methods are greater 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 24 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 25 4. Greenhouse gas mixture 60% 50% Contribution to temperature increase in 2000 Fossil CO2 (100% = 0.58°C) Anthropogenic CO2 (100% = 0.74°C) CO2, CH4 and N2O (100% = 1.06°C) Kyoto gases (100% = 1.07°C) Kyoto gases & precursors (100% = 1.07°C) 30% 25% 40% 20% 30% 15% 20% 10% 10% 5% 0% 0% OECD90 EEUR & FSU A SIA Source: CICERO-SCM A LM Contribution to temperature increase in 2000 USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia • Two main effects i) Going from fossil fuel CO2 emissions only to total anthropogenic CO2 emissions, ii) Inclusion of CH4 and N2O. Modelling and assessment of contributions to climate change 4. Greenhouse gas mixture 60% 50% 40% 26 Contribution to temperature increase in 2100 Fossil CO2 (100% = 3.11°C) Anthropogenic CO2 (100% = 3.26°C) CO2, CH4 and N2O (100% = 4.39°C) Kyoto gases (100% = 4.4°C) Kyoto gases & precursors (100% = 4.65°C) 30% 20% 10% Source: CICERO-SCM 0% OECD90 EEUR&FSU ASIA ALM • 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 27 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 28 1. Historical datasets % Contribution to temperature increase in 2000 50 45 40 35 30 25 20 15 10 5 0 FF+LUC:EDGAR (ref) (100% = 0.68°C) FF:CDIAC; LUC:EDGAR (100% =0.62°C) FF:EDGAR; LUC:Houg (100% =0.74°C) FF:EDGAR; LUC:IVIG (100% =0.69°C) • • Contribution to temperature increase in 2000 25 20 15 10 5 0 OECD90 • • % EEUR & FSU A sia A LM USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia 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) IVIG Dataset estimate is outside IPCC range; almost zero for DCs in 1980s! Modelling and assessment of contributions to climate change 29 2. Other scientific uncertainties % 40 35 Contribution to temperature increase in 2050 Hadley (ref) (100% = 2.30°C) CSIRO (100% = 2.04°C) ECHAM (100% = 1.68°C) GFDL (100% = 2.36°C) 30 25 20 15 10 5 0 OECD90 EEUR & FSU A sia A LM % Contribution to temperature increase in 2050 20 18 16 14 12 10 8 6 4 2 0 USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia Source: RIVM-ACCC • The influence of other climate model parameters (e.g. IRFs), based on simulation experiments with nine GCMs and climate models is limited Modelling and assessment of contributions to climate change 2. Other scientific uncertainties % 30 Contribution to temperature increase in 2100 40 1: UCL-ACCC (linear carbon cycle) (100% = 3.8°C) 2: 1 + non-linear carbon fertilisation (100% = 3.9°C) 3: 2 + nonlinear oceanic chemistry (100% = 4.3°C) 4: 3 + climate feedback ocean chemistry (100% = 4.4°C) 5: UCL-JCM (= 4 + atmospheric chemistry) (100% = 4.4°C) 6: 5 + soil respiration feedback (100% = 4.8°C) 7: 6 + high climate sensitivity (100% = 6.7°C) 8: 3 + high climate sensitivity (no feedbacks) (100% = 5.7°C) 9: 6 excl. F-gas, trop.O3, solar&volcano (100% = 4.9°C) 10 =4 + high carbon fertilisation (100% = 4.2°C) 11 =4 + fast ocean diffusivity (100% = 4.4°C) 35 30 25 20 15 10 5 0 OECD90 % EEUR & FSU A sia A LM Source: UCL-SCM Contribution to temperature increase in 2100 25 20 15 10 5 0 USA Latin A mer A frica OECD Euro pe FSU So uth A sia East A sia Modelling and assessment of contributions to climate change 31 Overall conclusions 20 percentage points • Policy choices (values can not be based on objective ‘scientific’ arguments) : – Indicator important – Timeframes important – Mixture of GHG important – Attribution method less important 25 15 10 Deviation from default calculations GWP w eighted cummulative emissions Ocean Heat Content Attribution start date 1990 Only fossil fuel CO2 All Kyoto gases and precursors All Kyoto gases and SO2 Other LUCF data: Houghton 5 0 -5 -10 -15 OECD • Scientific choices – Choice of the dataset on historical emissions important – Choice of the representation of the climate system (different models) less important for relative contr. EEUR&FSU ASIA Modelling and assessment of contributions to climate change ALM 32 Overall conclusions • First summary of the work undertaken so 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 paper #2) • 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 33 Backup slides 34 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 35 Models are calibrated Modelling and assessment of contributions to climate change 36 E5 Gg CO2 - res idual Gg 10 1950 2000 2000 2000 2050 1950 2000 2050 2050 1950 2000 2050 2 0 -4 1900 x 10 1 2050 °C 2050 1950 0 -4 1900 x 10 4 2050 1950 2000 0.01 W/m2 2000 P uls e emis s ions of 1E5 Gg CO2 - proportional 5 0 1900 0.02 2050 ppm 2000 x 10 4 0.5 2000 0 1900 2050 1950 ars 2000 2050 Years =1 =0.6 1950 2000 2050 37 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. + 38 Contribution to radiative forcing Modelling and assessment of contributions to climate change 39 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 40 Overall conclusions ECOFYS-ACCC RIVM - ACCC CSIRO - ACCC CICERO -SCM IVIG-ACCC Weighted concentrations Integrated Temperature increase Ocean Heat Content Defualt: Attribution start date 1890 Attribution start date 1990 Evaluation date 2100 Deafult: Normalized marginal Time sliced Deafult: all CO2, CH4, N2O Only fossil CO2 All Kyoto gases and precursors Default (all GHGs: EDGAR) Other LUCF data: Houghton Default: EDGAR IRF: GFDL Default: ACCC simplest Variant 7 (sect. 3.3.3): UCL-JCM 1.6 19.8 13.7 6.5 13.8 4.1 10.8 2.1 7.0 10.2 6.3 1.5 2.6 100.0 1.6 20.5 13.7 6.3 14.7 3.9 9.6 1.9 7.3 10.1 6.2 1.5 2.6 100.0 1.7 20.4 13.3 6.2 14.5 4.0 10.3 2.4 5.8 10.7 6.0 1.6 3.0 100.0 1.6 20.9 14.2 6.2 14.9 4.1 10.1 2.1 5.6 9.7 6.1 1.4 2.9 100.0 1.4 21.1 15.4 6.6 15.2 3.6 7.9 1.2 8.7 8.9 6.6 1.5 1.9 100.0 1.7 20.8 14.5 6.3 14.7 4.2 10.7 2.0 5.5 9.3 6.2 1.3 2.9 100.0 1.8 17.5 10.0 6.5 11.0 3.4 12.5 3.7 7.4 15.2 6.0 1.6 3.5 100.0 1.7 21.8 14.8 6.0 15.8 4.2 9.9 2.0 4.5 8.8 6.0 1.2 3.1 100.0 1.6 19.7 13.7 6.6 13.9 4.0 10.7 2.1 7.1 10.1 6.2 1.7 2.5 100.0 1.6 19.9 13.9 6.6 14.0 4.0 10.5 2.0 7.1 10.0 6.3 1.7 2.5 100.0 1.5 19.1 13.2 6.8 13.2 3.9 10.5 2.0 8.5 11.0 6.3 1.8 2.3 100.0 2.2 29.6 3.7 2.4 21.3 5.8 13.7 2.5 3.3 8.9 1.2 1.2 4.3 100.0 1.6 1.8 19.9 18.4 13.7 13.2 6.6 7.9 14.1 12.8 4.0 3.7 10.3 10.2 2.0 2.4 7.2 8.2 10.1 11.0 6.2 6.3 1.7 1.7 2.5 2.3 100.0 100.0 1.6 19.4 13.8 6.7 13.6 4.2 11.0 2.1 7.3 10.2 6.4 1.5 2.5 0.0 2.2 17.7 11.0 5.6 13.2 4.0 11.7 2.4 6.3 15.1 6.3 1.8 2.8 0.0 1.7 20.8 14.5 6.3 14.7 4.2 10.7 2.0 5.5 9.3 6.2 1.3 2.9 100.0 1.6 21.1 15.0 6.3 14.9 4.2 10.3 1.9 5.6 8.8 6.3 1.2 2.7 100.0 1.6 19.8 13.7 6.6 13.9 4.0 10.3 2.1 7.2 10.3 6.3 1.7 2.5 100.0 1.6 20.0 14.0 6.6 14.2 3.9 9.9 1.9 7.6 9.9 6.3 1.7 2.4 100.0 OECD EEUR&FSU ASIA ALM Total 39.3 14.8 23.5 22.4 100.0 40.9 13.5 23.6 21.9 100.0 41.3 14.4 22.5 21.9 100.0 41.8 14.2 21.4 22.5 100.0 41.1 11.6 24.2 23.2 100.0 41.2 14.9 21.0 22.8 100.0 35.3 15.9 28.6 20.1 100.0 43.6 14.1 19.4 22.9 100.0 39.5 14.7 23.5 22.4 100.0 39.6 14.5 23.3 22.5 100.0 37.8 14.4 25.8 22.0 100.0 58.6 19.5 13.4 8.5 100.0 39.8 37.0 14.3 13.9 23.6 25.6 22.3 23.5 100.0 100.0 38.6 15.1 23.8 22.5 100.0 37.7 15.7 27.6 19.0 100.0 41.2 14.9 21.0 22.8 100.0 41.6 14.5 20.7 23.2 100.0 39.5 14.3 23.8 22.4 100.0 39.9 13.8 23.9 22.5 100.0 1.2 160.4 3.8E+09 0.99 0.21 0.53 1.06 0.58 0.99 1.00 0.52 1.12 100% = ... °C 67.4 84°Cy Default with constant CH4 lifetime Region Canada USA Latin America Africa OECD Europe East Europe FSU Middle East South Asia (incl. India) East Asia (incl. China) South-East Asia Oceania Japan Total GWP weighted cummulative emissions JCM-SCM Default (temperature increase) RIVM -ACCC 1.04 1.07 = More than 10% higher than default = More than 10% lower than default Modelling and assessment of contributions to climate change