Emissions Scenarios: SRES, Emissions Scenarios: SRES, post- -SRES, - - PowerPoint PPT Presentation

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Emissions Scenarios: SRES, Emissions Scenarios: SRES, post post-

• SRES, MA,

SRES, MA, UNEP/GEO, and LCA UNEP/GEO, and LCA

National Institute for Environmental Studies National Institute for Environmental Studies

http://www-iam.nies.go.jp/aim/

Mikiko Kainuma Mikiko Kainuma

Expert Meeting on Expert Meeting on “ “Developing visions for a Low Developing visions for a Low-

• Carbon Society through sustainable development

Carbon Society through sustainable development” ” Tokyo, 14 Tokyo, 14-

• 16 June 2005

16 June 2005

Scenarios Scenarios

• Provide a framework for decision making

Provide a framework for decision making which illuminates the impact associated which illuminates the impact associated with alternative courses of action with alternative courses of action

• Facilitate the interpretation of possible

Facilitate the interpretation of possible future states future states

• Include elements that cannot be formally

Include elements that cannot be formally modeled modeled

• Aimed at challenging prevailing mind sets

Aimed at challenging prevailing mind sets

Source: Source: Nakicenovic Nakicenovic, 2005 , 2005

Previous developed and used scenarios by IPCC

INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)

1990 1992

Six IS92 scenarios

1995

Evaluation Scenarios

1996

Panel decision new scenarios

2000

Special Report Emissions Scenarios (SRES)

2001

TAR

2004

Start writing AR4 Based on SRES

????

Start writing AR5 Based on ??????? Four SA90 scenarios Start reviewing post-SRES scenarios and updating database

Purposes of Emissions Purposes of Emissions Scenarios Scenarios

• Purpose 1: Evaluate the environmental and climatic

Purpose 1: Evaluate the environmental and climatic consequences of consequences of “ “non non-

• intervention

intervention” ” futures futures

• Purpose 2: Evaluate the environmental and climatic

Purpose 2: Evaluate the environmental and climatic consequences of consequences of “ “intervention intervention” ” futures futures

• Purpose 3: Examine the feasibility and costs of

Purpose 3: Examine the feasibility and costs of mitigating mitigating GHGs GHGs from different regions and sectors from different regions and sectors

• Purpose 4: Negotiate possible emissions reductions

Purpose 4: Negotiate possible emissions reductions for different countries and regions for different countries and regions

Source: IPCC, 1995 Source: IPCC, 1995

Source: Source: Nakicenovic Nakicenovic, 2005 , 2005

No (?) No (?) No No No No Yes Yes SRES SRES No (?) No (?) No (?) No (?) No (?) No (?) Purpose 4 Purpose 4 "Negotiation" "Negotiation" Yes (?) Yes (?) No No No No Purpose 3 Purpose 3 feasibility and costs feasibility and costs from different regions from different regions and sectors and sectors Yes Yes No No Yes Yes Purpose 2 Purpose 2 “ “intervention intervention” ” No No Yes Yes Yes Yes Purpose 1 Purpose 1 “ “non non-

• intervention

intervention” ” TAR TAR IS92 IS92 SA90 SA90

Purposes of Emissions Scenarios Purposes of Emissions Scenarios

(Together with Climate Projections) (Together with Climate Projections)

Source: IPCC SRES, 2000 Source: IPCC SRES, 2000

Alternative Scenario Formulations Alternative Scenario Formulations

Models Stories Scenarios

Quantitative Qualitative

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SRES: Socioeconomic development scenarios for climate change prediction

economy environment regionalism globalism

A2 A2 B1 B2

Population Economic growth Technology Energy Agriculture(land use)

Driving Forces

A1

A1FI A1FI A1T A1T A1B A1B

Source: IPCC SRES

Global Population Projections Global Population Projections

World Population (SRES, n=40) (pre SRES, n=62) 1940 1960 1980 2000 2020 2040 2060 2080 2100

billion

5 10 15 20 pre SRES range SRES pre SRES

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Global Population Projections Global Population Projections

World Population (post SRES, n=168) (pre SRES, n=62) 1940 1960 1980 2000 2020 2040 2060 2080 2100

billion

5 10 15 20 pre SRES range post SRES pre SRES

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Global Population Projections Global Population Projections

World Population (post SRES, non intervention, n=64) 1940 1960 1980 2000 2020 2040 2060 2080 2100

billion

5 10 15 20 post SRES, non intervention range Median pre SRES range post SRES pre SRES

Gross World Product Gross World Product

Range Across Emissions Scenarios Range Across Emissions Scenarios

World GDP (SRES, n=40) (pre SRES, n=151) 1940 1960 1980 2000 2020 2040 2060 2080 2100

trillion 1990$

100 200 300 400 500 600 700 800 pre SRES range SRES pre SRES

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Gross World Product Gross World Product

Range Across Emissions Scenarios Range Across Emissions Scenarios

World GDP (post SRES, n=194) (pre SRES, n=151) 1940 1960 1980 2000 2020 2040 2060 2080 2100

trillion 1990$

100 200 300 400 500 600 700 800 pre SRES range post SRES pre SRES

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Gross World Product Gross World Product

Range Across Emissions Scenarios Range Across Emissions Scenarios

World GDP (pre SRES, non intervention, n=113) 1940 1960 1980 2000 2020 2040 2060 2080 2100

trillion 1990$

100 200 300 400 500 600 700 800 pre SRES non intervention post SRES non intervention pre SRES range post SRES range

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

Carbon Emissions Carbon Emissions

Range Across Emissions Scenarios Range Across Emissions Scenarios

World CO2 emissions (pre SRES, non intervention, n=199) 1940 1960 1980 2000 2020 2040 2060 2080 2100

Gt C

10 20 30 40 50 60 70 80 pre SRES non intervention

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

World CO2 emissions (tar, intervention, n=80) (SRES, n=40) 1940 1960 1980 2000 2020 2040 2060 2080 2100

Gt C

10 20 30 40 50 60 70 80 SRES range

Carbon Emissions Carbon Emissions

TAR Intervention Scenarios TAR Intervention Scenarios

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

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A1B

450 450 550 550 650 650

Baseline

10 20 30 40 2000 2050 2100

AIFI

450 450 550 550 650 650 750 750

Baseline

2000 2050 2100 10 20 30 40

A1T

Baseline

450 450 550 550 650 650 2000 2050 2100 10 20 30 40

A2

550 550 750 750 2000 2050 2100

Baseline

10 20 30 40

B1

450 450 550 550

Baseline

2000 2050 2100 10 20 30 40

B2

450 450 550 550 650 650

Baseline

2000 2050 2100 10 20 30 40

CO2 emission (GtC)

Difficulty of CO2 reduction depends on Difficulty of CO2 reduction depends on development path for future world development path for future world

A1FI and A2 require much larger reduction than A1T and B1

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Major findings of Post-SRES

• Different development paths require different

technology/ policy measures and show different costs of mitigation to stabilize atmospheric CO2 concentrations

• A portfolio of measures required for timely development,

adoption and diffusion of mitigation options; Policy integration across an array of technologies, sectors and regions is the key to successful climate policies

• However, associated socio-economic and institutional

changes are required to realize the potential for the above stabilization in practice

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Issues after Post-SRES

• Greater need for the linkage of emission and impact

analysis

– Appropriate criteria of stabilization targets (ex. GHG concentration, radiative forcing, temperature change, rate

• f temperature change, sea level rise, rate of sea level rise)

– Timing of mitigation (early vs. late)

• Uncertainty in future technological advances (risks of

mitigation in later stage)

• Specific mitigation implementation strategies for

achieving targets of 550 ppmv, 450 ppmv, etc.

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Recent Stabilization Scenarios

• Global level studies

– e.g. MA, UNEP/GEO, EMF21, IEA/Energy to 2050,

• Country level studies

– Each country focusing on its own mitigation targets and ways to achieve them

• Sector focused analysis

– e.g. OECD/Environmentally Sustainable Transport

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Framework of MA Framework of MA (Millennium ecosystem assessment) (Millennium ecosystem assessment)

• !

" # $ % $&'(')' ')% $'%

• #

*

!

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Globally Connected Regional Focus Proactive Reactive

Approach to environmental management Institutions Technogarden Focus: Environmental technology Global Orchestration Focus: Social policy Adapting Mosaic Focus: Active learning Order from Strength Focus: Self interest

Frame of MA Scenarios

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Global Orchestration (GO) Order from Strength (OS) TechnoGarden(TG) Adaptive Mosaic (AM)

2000 2100

0 20 40 60 80 100 ～ ～ ～ ～ (%) 1 5 10 0 20 40 60 80 100 ～ ～ ～ ～ (%) 1 5 10

• In general, the order of stress is OS > AM >

GO > TG Withdrawal: driven by socio-economic factors Water resource: driven by climate factors General trend of stress index change can be explained by demand side.

• Middle East and North Africa

High drought risk ← ← ← ← water demand increase derived from population increase and economic development. Mitigated in TG ← ← ← ← high efficiency of water use.

• East Europe

High draught risk inGO ← ← ← ←high rate increase of industrial water withdrawal which cannot be compensated with the water use efficiency improvement.

• "###

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UNEP/GEO4 Meeting 2005

• The UNEP GEO project was initiated in response to
• Environmental reporting requirements of Agenda 21
• UNEP governing council decision of May 1995
• The coordinated global network of collaborating centers (CCs) is

at the core of the GEO process

• Reports are produced using regional and participatory approach

UNEP/GEO4 Meeting 2005

• The Outlook
• The extent and direction of opportunities (actions) would

determine different out looks for the future.

• GEO 4 will explore possible futures
• Markets first, Policy first, Security first, Sustainability

first

• Regional differentiation and regional and global implications

to be explored

• Implications of decisions made today

UNEP/GEO4 Meeting 2005

• !"

Proposed Purpose and Key Questions

• Where does each scenario stand in relation to specific goals?
• What are intermediate and long-term implications of current

(and already taken) actions?

• What are the contrasting ‘costs’ (in a broad sense) for

achieving particular sustainability goals under the scenarios?

• How, and how well, can different actors/regions respond to a

future shock/disturbance/new insight/concern under the different scenarios?

Asia Pacific Integrated Modeling Team #$%

• 100%
• 50%

0% 50% 100% 150% 200% 250% 300% MF PO SC SU MF PO SC SU MF PO SC SU MF PO SC SU MF PO SC SU Afghanistan Bangladesh Bhutan India Iran Maldives Nepal Pakistan Sri Lanka Brunei Cambodia Indonesia Lao Malaysia Myanmar Philippines Singapore Thailand Vietnam China Korea,Dem Japan Korea,Rep Mongolia Taiwan Kazakhstan Kyrgyz Republic Tajikistan Turkmenistan Uzbekistan Australia New Zealand Fiji Kiribati Nauru Palau Papua New Guinea French Polynesia Tonga Vanuatu Samoa Solomon Islands

South East Asia South Asia East Asia Central Asia ANZ and South Pacific

MF: market first, PO: policy first, SC: security first, SU: sustainability first

Change in energy-related SO2 emissions by 2032 relative to 2002 (%)

Focus on regional environmental changes

Asia Pacific Integrated Modeling Team &'()*(+,-

Request for Storyline Millennium Development Goals 7, Target 10: Halve by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation ►►► Timing of MDG achievement ►►► Quality of safe water/sanitation technologies or investment cost Quantification Consistency check between access to safe water/sanitation by technology, investment costs and MDG achievement Potential mortality of diarrhea

Focus on Short-term (2015) and Medium-term (2050)

Asia Pacific Integrated Modeling Team ()./01./1/

20 40 60 80 100 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability Australia and New Zealand Central Asia North West Pacific and East Asia South Asia South East Asia South Pacific Access to safe water (%)

2015

2015

PF scenario in every sub-region except South Pacific achieves MDG due to fully investment cost and

SuF scenario achieves MDG in some sub-regions. MF only achieves MDG in Northwest Pacific and East Asia and SeF scenario fail to achieve MDG. Austria and New Zealand already have 100% access to safe water.

2050

In Northwest Pacific and East Asia, four scenario almost achieve 100% access to safe water based

• n rapid economic growth

In other sub-regions, growth of access to safe water coverage stagnates because of rapid population growth, investment cost limitation and rise of investment cost for household connection

20 40 60 80 100 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability 2000 Markets Policy Security Sustainability Australia and New Zealand Central Asia North West Pacific and East Asia South Asia South East Asia South Pacific Access to safe water (%)

2050

Millennium Development Goal (MDG), Goal 7, Target 10: Halve by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation

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How much speed of technological How much speed of technological How much speed of technological How much speed of technological change should be required to achieve change should be required to achieve change should be required to achieve change should be required to achieve Low Carbon Society? Low Carbon Society? Low Carbon Society? Low Carbon Society?

E : Primary energy use, E/GDP: Energy intensity E : Primary energy use, E/GDP: Energy intensity E : Primary energy use, E/GDP: Energy intensity E : Primary energy use, E/GDP: Energy intensity CO2/E : Carbon intensity CO2/E : Carbon intensity CO2/E : Carbon intensity CO2/E : Carbon intensity

CO2 = (CO2/E) x (E/GDP) x GDP

• Comparison of scenarios -

CO2 emission disaggregation by Kaya identity

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–3 –2 –1 –3 –2 –1 Carbon intensity (%/y) Energy intensity (%/y)

Germany

5 % r e d u c t i

• n

6 % r e d u c t i

• n

7 % r e d u c t i

• n

8 % r e d u c t i

• n

9 % r e d u c t i

• n

(1990–2000) Japan(1960–2000) France UK (1960–2000) (1960–2000)

Source: kawase et al., 2006

Rates of change of aggregated energy intensity and carbon intensity

Dotted isoquant lines show the estimated CO2 reduction over 50years assuming annual GDP growth rate of 1% for each country; It must be noted that reduction levels shown here are not the same as those reported by each country’s scenarios because they assume different GDP growth rate

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–3 –2 –1 –3 –2 –1 Carbon intensity (%/y) Energy intensity (%/y)

Germany

5 % r e d u c t i

• n

6 % r e d u c t i

• n

7 % r e d u c t i

• n

8 % r e d u c t i

• n

9 % r e d u c t i

• n

Japan(1960–2000) France UK (1960–2000) (1960–2000)

Source: kawase et al., 2006

Dotted isoquant lines show the estimated CO2 reduction over 50yrs assuming annual GDP growth rate of 1% for each country; It must be noted that reduction levels shown here are not the same as those reported by each country’s scenarios because they assume different GDP growth rate

Change in carbon intensity with CCS Change in carbon intensity excluding carbon capture and storage (CCS)

Rates of change of aggregated energy intensity and carbon intensity

(1990–2000)

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• To achieve ambitious target of a 50-90% CO2

emission reduction, the pace of aggregated energy intensity improvement and carbon intensity decrease must be 2-3 times greater than the 40-year historical change, while the change rates should be maintained for 50 years.

• We need ‘trend-braking’ intervention. What and

How?

• Scenarios can help to foresee the future world and

provide lessons from the future.

Summary

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Thank you for your attention!

World CO2 emissions (SRES, n=40) (is92, n=6) 1940 1960 1980 2000 2020 2040 2060 2080 2100

Gt C

10 20 30 40 50 60 70 80 IS92 range

Carbon Emissions Carbon Emissions

SRES Range of Scenarios SRES Range of Scenarios

Source: Source: Nakicenovic Nakicenovic et al., 2006 et al., 2006

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• " $

" $

Wheat Maize

• Generally, the degree of potential productivity change coincides with the speed of temperature

increase; FW > EO > LL >TG. Potential productivity will increase in high-latitude regions, and decrease in low-latitude regions. In mid-latitude regions, effect of climate change depends on the variety of crops.

• FSU: productivities of wheat and maize increase very rapidly by global warming under any scenarios.
• Latin America: As global warming progresses, the potential productivity will decrease.
• OECD: the potential productivity of wheat will decrease, while that of maize will increase because of

global warming. Generally, the most suitable temperature for maize growth is higher than that for wheat growth.

OECD

• 15
• 12
• 9
• 6
• 3

2000 2050 2100 Year Wheat [%] L-America

• 50
• 40
• 30
• 20
• 10

2000 2050 2100 Year

Wheat [%]

FSU

10 20 30 40 2000 2050 2100 Year Wheat [%]

OECD 2 4 6 8 10 2000 2050 2100 Year

Maize [%]

FSU 20 40 60 80 100 120 2000 2050 2100 Year Maize [%] L-America

• 10
• 8
• 6
• 4
• 2

2000 2050 2100 Year Maize [%]

UNEP/GEO4 Meeting 2005

• !"

Starting point

• The GEO-3 scenarios will act as the first draft scenarios for

GEO-4.

• The focus of the work will be on the global and regional

levels with some differentiation, as appropriate, on a sub- regional level. Temporal Specification

• Time horizon for narratives and quantification will be 2050
• Reporting of indicators in 2015 (short-term)
• Certain environmental indicators to 2100 (long-term)

UNEP/GEO4 Meeting 2005

• !"

Content Elements

• Specific priority, cross-cutting, and emerging issues
• Trends in key drivers, e.g. population, consumption,

production, and technology

• Trends in key environmental indicators, e.g. pollutant levels,

land cover, and biodiversity

• Progress toward specific goals and targets, e.g. MDGs
• Global story with regional elements, separate regional stories

for each of the scenarios, (sub-)regions free to elaborate on issues that are important to them

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MiniCAM A1FI 450 500 1000 1500 2000 2500 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Other Renewables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing

BaU Energy Consumption Stabilization Case

How to achieve stabilization targets differs among models

ASF A2 550 200 400 600 800 1000 1200 1400 1600 1800 2000 1 9 9 2 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 1 Other Renweables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing

A!M A1FI 550 500 1000 1500 2000 2500 3000 1 9 9 2 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 1 Other Renweables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing

LDNE A1G 550

• 1500
• 1000
• 500

500 1000 1500 2000 2500 3000 3500 1 9 9 2 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 1 Other Renweables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing MARIA A1B 550

• 1000
• 500

500 1000 1500 2000 1 9 9 2 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 1 Other Renweables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing

MESSAGE A1C 450

• 4000
• 3000
• 2000
• 1000

1000 2000 3000 4000 1 9 9 2 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 1 Other renewables Biomass Nuclear Gas Oil Coal Demand reduction PE with Carbon scrubbing

EJ EJ EJ EJ EJ EJ

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Framework of MA Framework of MA (Millennium ecosystem assessment) (Millennium ecosystem assessment)

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! " # $ % $&'(')' ')% $'%

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Cultural Services Supporting Services

Ecosystem Services

Products obtained from Ecosystems

• Food
• Fresh water
• Fuelwood
• Fiber
• Biochemicals
• Genetic resources

Benefits obtained from regulation of ecosystem Processes

• Climate regulation
• Disease regulation
• Water regulation
• Water purification
• Pollination

Nonmaterial benefits

• btained from

Ecosystem

• Spiritual religious
• Recreation and

ecotourism

• Aesthetic
• Inspirational
• Educational
• Sense of place
• Cultural heritage

Services necessary for the production of all other ecosystem services

• Soil formation
• Nutrient cycling
• Primary production

Regulating Services Provisioning Services