Download MATCH - Status of research

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)
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Af
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La
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Eu
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C
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O
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an
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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
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O
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Ea
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er
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O
EC
D
Ja
pa
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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)