status of research sb-20 21 june 2004 xiaosu dai, michel den elzen, niklas höhne

Status of researchSB-20

21 June 2004

Xiaosu Dai, Michel den Elzen, Niklas Höhne

Overview

1. Introduction to the MATCH processNiklas Höhne / Xiaosu Dai

2. Introduction of first joint paperMichel 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).


MATCH process


UNFCCC process

• Two expert meetings• Coordinated modelling

exercise “ACCC”

• Ad-hoc group• Initiated by Brazil and UK• Two expert meetings so far

MATCH processObjective:

• 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


MATCH processScientific 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 Miguez

Interministerial Committee on Global Climate Change, Brazil

Niklas Höhne (Secretary) ECOFYS, Germany

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


MATCH-info.net


• Background

• Organization

• Papers

• Expert meetings

• File exchange

• Discussion forum

Participation at last meeting


Atsushi Kurosawa The Institute of Applied Energy Research and Development, JapanAtul Jain University of Illinois, USABen Matthews Universite catholique de Louvain, BelgiumCathy Trudinger CSIRO, Australia Christiano Pires de Campos Federal University of Rio de Janeiro, BrazilFabian Wagner IIASA, GermanyGregory Bodeker NIWA, New ZealandJan Fuglestvedt CICERO, NorwayJason Lowe Met Office, Hadley Centre, UKJesper Gundermann Danish Environmental Protection AgencyJosé Domingos Gonzalez Miguez Interministerial Committee on Global Climate Change, BrazilJoyce Penner University of Michigan, USAMaria Silvia Muylaert de Araujo Coppe Federal University of Rio de Janeiro, BrazilMartin Weiss German Enironmntal AgencyMichael Prather University of California at Irvine, USA Michel den Elzen RIVM, NetherlandsMurari Lal University of the South Pacific, FIJINiklas Höhne Ecofys, GermanyRachel Warren UK DEFRASimone Ullrich Ecofys GmbHXiaosu Dai National Climate Cente, China

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


Anticipated papersPaper #1 Analysing countries’ contribution to climate change: Scientific choices and methodological issues: status of the work and first results

Paper #2Demonstration of credible alternative scientific choices and their effect on the emissions, concentration and climate change

Paper #3Formal 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


ScheduleMeeting 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

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


2. First joint paper

Analysing countries’ contribution to climate change: Scientific choices and methodological issues


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.


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


Scientific uncertainties

• Choice of the dataset on historical emissions• Choice of the representation of the climate system

(different models)


Models used


Model Carbon cycle (CO2)

Atmospheric chemistry (non-CO2)

Sulphate aerosols

Radiative forcing

Temperature and sea level rise

ACCC (default) IRF (Bern) fixed lifetimes Hadley IPCC-TAR IRFs (Hadley)

CICERO - SCM Non-linear v IPCC-TAR IPCC-TAR ACCC EBC/UDO model (Schlesinger et al., 1992).

CSIRO - SCM ACCC or non-linear v

ACCC none ACCC ACCC

ECOFYS - ACCC ACCC* ACCC ACCC ACCC ACCC RIVM - ACCC ACCC IPCC-TAR ACCC ACCC ACCC and other IRFS JCM - SCM Bern non-

linear IPCC-TAR IPCC-TAR ACCC IPCC-TAR

IVIG - ACCC ACCC ACCC ACCC ACCC ACCC

* Same methodology used as in the ACCC model; v The mixed layer response function of Joos et al. (1996);

Model show similar outcomes


Source: UNFCCC

Policy choices

1. Indicator

2. Timeframes

3. Attribution method

4. Mixture of greenhouse gases


1. Indicators


Source: Ecofys-ACCC

Historical emissions

Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations

Attribution end date

Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance


Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Time

AACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

1. Indicators


Name of indicator Backward discounting

Forward looking

A Radiative forcing X -+

B GWP-weighted cumulative emissions - X

C Weighted concentrations X X

D Temperature increase X* -

+

E Integrated temperature increase

X X

F Sea level rise 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

1. Indicators


0%

10%

20%

30%

40%

50%

60%

70%

Fossil CO2 Forestry CO2 CH4 N2O

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

OECD90 REF ASIA ALM

Radiative forcingGWP-weighted cumulative emissionsWeighted concentrationsTemperature increaseIntegrated temperature

Relative contributions using different indicators

Preliminary

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.

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



Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance


Time

ACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Time

AACB

Time

Time

Present

D

Emissions

Radiative forcing

Temperature change

E

Time

FSea level rise

Time

Concentrations


Evaluation date

Incr

easi

ng c

erta

inty

Incr

easi

ng r

elev

ance

Start-date


• Choosing a shorter time horizon (e.g. 1950 or 1990 instead of 1890) reduces the contributions of OECD90

countries ('early emitters') to temperature increase.

Contribution to temperature increase in 2000

05

10

1520

25

3035

40

4550

OECD90 EEUR & FSU Asia Africa & LatinAmerica

%

1765

1850

ref

1950

1990


0

5

10

15

20

25

USA SouthAmer

South.Africa

OECDEurope

FSU SouthAsia

EastAsia

%

Source: RIVM-ACCC

End-date


• 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


05

10

1520

25

3035

40

4550

OECD90 EEUR&FSU Asia Africa & LatinAmerica

%

19902000 (ref )20502100


0

5

10

15

20

25

USA SouthAmer

South.Africa

OECDEurope

FSU SouthAsia

EastAsia

%

Source: RIVM-ACCC

Evaluation-date


• 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)

Contr ibution to temperature increase in :(end date 2000)

0

5

10

15

2025

30

35

40

45

50

OECD90 EEUR&FSU Asia ALM

%

2000 (ref)

2050

2100

Contr ibution to temperature increase in:(end date 2000)

0

5

10

15

20

25

USA SouthAmer

South.Africa

OECDEurope

FSU SouthAsia

EastAsia

%

Source: RIVM-ACCC

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.



• The Residual method, although simple to implement and explain, can be rejected on scientific grounds (not additive).

• The Normalised marginal and Time-sliced methods are harder to implement and explain. These methods differ in how they treat early vs. late emissions.


• The differences between methods are fairly small compared to the effects of many of the other choices already considered.



0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU India +SouthAsia

EastAsia

%

N. Marg

T. Sliced

N. Resid


0

5

10

15

20

25

30

35

40

45


%

N. Marg

T. Sliced

N. Resid

Source: CSIRO-SCM


0

5

10

15

20

25

30

35

40


%

N. Marg

T. Sliced

N. Resid


0

5

10

15

20

25

USA LatinAmer

Africa OECDEurope

FSU India +SouthAsia

EastAsia

%

N. Marg

T. Sliced

N. Resid



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. Source: CSIRO-SCM

4. Greenhouse gas mixtureWhich 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)


Greenhouse gas mix, attribution period 1890-2000

0%

5%

10%

15%

20%

25%

30%

Canad

aUSA

Japa

n

OECD E

urop

e

Oce

ania CIS

Easte

rn E

urop

e

China

regio

n

East A

sia

South

Asia

Africa

Latin

Am

erica

Mid

dle E

ast

CO2FF 2000 (dT=0.58)

CO2ALL 2000 (dT=0.74)

KP3 2000 (dT=1.06)

KP6 2000 (dT=1.07)

KP6_O3P 2000 (dT=1.07)

4. Greenhouse gas mixture

• 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).


Source: CICERO-SCM

Greenhouse gas mix, attribution period 1890-2000

0%

10%

20%

30%

40%

50%

60%

OECD90 REF ASIA ALM

CO2FF 2000 (dT=0.58)

CO2ALL 2000 (dT=0.74)

KP3 2000 (dT=1.06)

KP6 2000 (dT=1.07)

KP6_O3P 2000 (dT=1.07)

Scientific uncertainties1. Choice of the dataset on historical emissions

2. Choice of the representation of the climate system: carbon cycle and climate model and feedbacks


1. Historical datasets

• 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)


Source: RIVM-ACCC


05

10

1520

25

3035

40

4550


%

ref

CDIAC

Houghton


0

5

10

15

20

25

USA SouthAmer

South.Africa

OECDEurope

FSU SouthAsia

EastAsia

%

ref

CDIAC

Houghton

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

• ...


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


Backup slides

Policy choices


Indicators Radiative forcing, GWP-weighted cumulative emissions, weighted concentrations,temperature increase, integrated temperature, sea level riseAttribution startdates

1890, 1950 and 1990Timeframes

Attribution end dates 1990, 2000, 2050 and 2100Evaluation dates 2000, 2050, 2100, 2500

Attributionmethods

Normalized marginal, residual, time-sliced

Attributedgreenhousegases (GHGs)

Fossil CO2, CO2, CO2, CH4, N2O, Kyoto-GHGs (including F-gases), all GHGs(including the other halocarbons (CFCs))

Data Historical emissions CDIAC database (fossil CO2, land-use CO2), EDGAR (allKP-GHGs), IEA (fossil CO2)

Future emissions IPCC SRES B1, A2 and A1F emission scenario

Regions Four regions (Nakicenovic et al. 2000): OECD90; Eastern Europe and Former SovietUnion (REF); Asia (ASIA); Africa and Latin America (ALM), and 13 world regions:Canada, USA, Latin America, Africa, OECD Europe, Eastern Europe, FormerUSSR (FSU), Middle East, South Asia, East Asia, South East Asia, Oceania andJapan

Models are calibrated


1900 1950 2000 20500

5

10x 10

4

Gg

P uls e emis s ions of 1E5 Gg CO2 - proportional

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4W

/m2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

1900 1950 2000 20500

5

10x 10

4

Gg

P uls e emis s ions of 1E5 Gg CO2 - res idual

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4

W/m

2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

1900 1950 2000 20500

5

10x 10

4

Gg

Pulse emissions of 1E5 Gg CO2 - proportional

1900 1950 2000 20500

0.01

0.02

ppm

1900 1950 2000 20500

2

4x 10

-4

W/m

2

1900 1950 2000 20500

0.5

1x 10

-4

°C

Years

=1

=0.6

Table 3

No. Name of the indicator 1900 1950 1990 2000 CO2 0.29 0.36 0.56 1* CH4 0.015 1.0 28 64* A Radiative forcing due to increased

concentrations N2O 81 126 180 196* CO2 1 1 1 1+ CH4 20 20 20 20+ B GWP-weighted cumulative

emissions N2O 323 323 323 323+ CO2 0.29 0.36 0.56 1 CH4 0.005 0.31 8.6 20 C Weighted concentrations N2O 134 208 296 323 Max year CO2 3.44 3.92 4.45 1 1983 CH4 9 33 262 64 1991 D Temperature increase N2O 927 1290 1220 196 1976 CO2 0.90 0.93 1.03 1 1993 CH4 2.2 3.3 16 22 2000 E Integrated temperature N2O 189 260 327 324 1994 CO2 To be completed CH4 F Sea level rise N2O

*: Represent instantaneous GWPs. +: Represent GWPs. Values slightly different to those of IPCC-TAR due to use of different parameters.

Contribution to radiative forcing


Aerosol forcing

• 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


Attributing SO2, attribution period 1890-2000

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

OECD90 REF ASIA ALM

KP3 2000 (dT=1.06)

KP6_SO2 2000 (dT=0.51)

Attributing SO2, attribution period 1890-2000

0%

5%

10%

15%

20%

25%

30%

Canad

aUSA

Japa

n

OECD E

urop

e

Oce

ania CIS

Easte

rn E

urop

e

China

regio

n

East A

sia

South

Asia

Africa

Latin

Am

erica

Mid

dle E

ast

KP3 2000 (dT=1.06)

KP6_SO2 2000 (dT=0.51)

Source: CICERO-SCM

decreasing non-Annex I contribution increasing non-Annex I contribution

decrease relative to default contribution > 15%decrease > 5%decrease < 5%

increase relative to default contribution > 15%increase > 5%increase < 5%

-X.X X.X-X.X X.X-X.X X.X

X.X is absolute change in contribution

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 -0.3USA 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 -2.7Central 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 0.3South 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 0.8Northern 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 0.4Western 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 0.2Eastern 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 0.0Southern 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 0.6OECD 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 -0.8Eastern 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 -0.3Former 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 -0.8Middle 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 1.1South 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 1.4East 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 -0.2South 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 0.5Oceania 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 -0.1Japan 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 -4.1EEUR & 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 -1.1Asia 30.4 -2.5 -3.3 -0.8 -0.6 -1.0 1.1 0.8 -0.1 1.0 1.4 1.5 2.0 1.7Africa & 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 -5.2non–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

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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 -0.3USA 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 -2.7Central 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 0.3South 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 0.8Northern 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 0.4Western 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 0.2Eastern 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 0.0Southern 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 0.6OECD 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 -0.8Eastern 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 -0.3Former 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 -0.8Middle 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 1.1South 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 1.4East 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 -0.2South 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 0.5Oceania 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 -0.1Japan 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 -4.1EEUR & 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 -1.1Asia 30.4 -2.5 -3.3 -0.8 -0.6 -1.0 1.1 0.8 -0.1 1.0 1.4 1.5 2.0 1.7Africa & 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 -5.2non–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

Policy choices vs. scientific choices

• Policy choices (start-date, indicators) are more important than scientific uncertainties (attribution method, climate model)


Source: RIVM-ACCC

status of research sb-20 21 june 2004 xiaosu dai, michel den elzen, niklas höhne

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