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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