MESSAGE-MACRO (IIASA) Volker Krey, Shilpa Rao, Keywan Riahi, - - PowerPoint PPT Presentation

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MESSAGE-MACRO (IIASA) Volker Krey, Shilpa Rao, Keywan Riahi, - - PowerPoint PPT Presentation

Jan 09, 2023 728 likes •972 views

MESSAGE-MACRO (IIASA) Volker Krey, Shilpa Rao, Keywan Riahi, Shonali Pachauri September 17, 2009 Tsukuba, Japan Key Design Characteristics Participating Model: MESSAGE-MACRO Model Type: Coupled Systems Engineering and Macroeconomic

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MESSAGE-MACRO (IIASA)

Volker Krey, Shilpa Rao, Keywan Riahi, Shonali Pachauri September 17, 2009 Tsukuba, Japan

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  • Participating Model: MESSAGE-MACRO
  • Model Type: Coupled Systems Engineering and

Macroeconomic model

  • Participating Modelers: Volker Krey, Shilpa Rao,

Keywan Riahi

  • Time Step: 10 years (annual for access modeling)
  • Time Frame: 2000-2100
  • Solution Type: Inter-temporal optimization (cost

minimization)

  • Equilibrium Type: Partial Equilibrium
  • Underlying Computing Framework: MESSAGE (C,

Cplex) and MACRO (GAMS)

Key Design Characteristics

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SLIDE 3

Inputs and Outputs

  • Key inputs

– Demographics: Population, Income cohorts (access) – Economic: reference GDP, household budgets (access) – Resources: Conventional & unconventional fossil fuels, renewable potentials (solar, wind, biomass, geothermal) – Technology: full energy chain (extraction all the way to consumer services)

  • Key outputs

– Economic: GDP, prices (fuels, GHG emissions), investments – Energy: technology specific capacity and activity pathways for all sectors – Agriculture: commodity, price and land-use change (linked to BLS/AEZ and Dima models) – Emissions: All GHGs and raditively active substances – Climate: alternative implementations (GHG concentrations, forcings, temperature)

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SLIDE 4

CCT

The Reference Energy System The Reference Energy System MESSAGE MESSAGE

gas well

Extraction Treatment Conversion Technologies Distribution Technologies Final Energy End-Use Technologies Energy Services

coal mine

  • il

well agro- forestry gas coal bio- mass

  • il

power plant refin- ery grid/ truck grid truck gas elect- ricity kero- sene

air craft, light bulb, furnace, air conditioner, oven, automobile etc.

synfuel plant grid/truck synthetic fuel sun- light hydrogen plant hydrogen grid/

  • n site

Energy Conversion Sector

Primary Sources

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SLIDE 5

IIASA Modeling Framework IIASA Modeling Framework

Scenario Storyline

Economic development Demographic change Technological change Policies

Population Projections Economic Projections DIMA

Forest Management Model

AEZ-BLS

Agricultural Modeling Framework

Downscaling Tools

Spatially explicit (and national) projections of economic and demographic growth

MESSAGE-MACRO

Systems Engineering / Macro-Economic Modeling Framework (all GHGs and all sectors) Regional population & economic projections

Endogenous Climate Model

National, regional & spatially explicit socio-economic drivers Spatially explicit socio-economic drivers Consistency of land-cover changes (spatially explicit maps of agricultural, urban, and forest land)

Potential and costs of forest bioenergy and sinks Carbon and biomass price

Feedbacks

Agricultural bioenergy potentials and costs Drivers for land-use related non-CO2 emissions

Feedbacks

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SLIDE 6

Regional Scope & Other Detail

  • Regional Details:

– Regional Scope: Global – Number of Sub-Regions: 11 – Asian Regions: Pacific OECD (PAO), Centrally Planned Asia (CPA), South Asia (SAS), Pacific Asia (PAS)

NAM PAO WEU EEU FSU MEA AFR LAM SAS PAS CPA 1 NAM North America 2 LAM Latin America & The Caribbean 3 WEU Western Europe 4 EEU Central & Eastern Europe 5 FSU Former Soviet Union 6 MEA Middle East & North Africa 7 AFR Sub-Saharan Africa 8 CPA Centrally Planned Asia & China 9 SAS South Asia 10 PAS Other Pacific Asia 11 PAO Pacific OECD OECD REFS ALM ASIA

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SLIDE 7

Spatial modeling of Land-use

Dynamic GDP maps (to 2100) Dynamic population density (to 2100) Development of bioenergy potentials “bottom-up” assessment Consistency of land-price, urban areas, net primary productivity, biomass potentials (spatially explicit)

“Top-down” Downscaling

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SLIDE 8

A2 Baseline: A2 Baseline: Population, Urbanization, GDP Population, Urbanization, GDP

500 1000 1500 2000 2500 3000 3500 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Million CPA PAO PAS SAS 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Share CPA PAO PAS SAS 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Trillion $2005 CPA PAO PAS SAS

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SLIDE 9

10 20 30 40 50 60 70 80 90 100 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Primary Energy [EJ]

  • 10

40 90 140 190 240 290 340 390 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Primary Energy [EJ] Renewables Biomass Nuclear Gas Oil Coal Synfuel Trade 50 100 150 200 250 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Primary Energy [EJ]

  • 5

5 10 15 20 25 30 35 40 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Primary Energy [EJ]

A2 Baseline: Primary Energy A2 Baseline: Primary Energy CPA CPA PAS PAS PAO PAO SAS SAS

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A2 Baseline: GHG Emissions A2 Baseline: GHG Emissions

1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC] 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC]

  • 400
  • 200

200 400 600 800 1000 1200 1400 1600 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC] 100 200 300 400 500 600 700 800 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC]

CPA CPA PAS PAS PAO PAO SAS SAS

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SLIDE 11

A2 550 A2 550 ppmv ppmv: : Sectoral Sectoral Mitigation Mitigation

1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC]

Electricity & Heat Other Conversion Industry Residential/Commercial Transport Other (LULUCF, F-gases, etc)

500 1000 1500 2000 2500 3000 3500 4000 4500 5000 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC]

  • 400
  • 200

200 400 600 800 1000 1200 1400 1600 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC] 100 200 300 400 500 600 700 800 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 CO2-equiv. [MtC]

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The Nature of the Energy Transition will The Nature of the Energy Transition will Depend on the Ranking of (Subjective) Depend on the Ranking of (Subjective) Policy Priorities Policy Priorities

Mid-term GHG/pollutant emissions levels (2050) Aspiration Level Reservation Level Regional energy trade (share of PE) Diversity of trade (index) 5% 70% 100% X trill 5% 1 Y trill Energy system cost

More preferable, but more difficult 12

+80%

  • 80%

Long-term climate target (prob. of 2C)

Environment Energy Security Economy

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SLIDE 13

More than 600 scenarios!

System Costs vs. Probability of Staying Below 2 degree (alternative security targets)

0% 2% 4% 6% 8% 10% 12% 14% 0% 10% 20% 30% 40% 50% 60%

Probability of Staying Below 2 degrees Centigrade Total Discounted System Costs Relative Change from Baseline (2000‐2050)

5% Max Import Share 10% Max Import Share 15% Max Import Share 20% Max Import Share 25% Max Import Share 30% Max Import Share No Max Import Share

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System Costs vs. Probability of Staying Below 2 degree (alternative security targets)

0% 2% 4% 6% 8% 10% 12% 14% 0% 10% 20% 30% 40% 50% 60%

Probability of Staying Below 2 degrees Centigrade Total Discounted System Costs Relative Change from Baseline (2000‐2050)

5% Max Import Share 10% Max Import Share 15% Max Import Share 20% Max Import Share 25% Max Import Share 30% Max Import Share No Max Import Share

More than 600 scenarios! Stringency of the climate target

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SLIDE 15

System Costs vs. Probability of Staying Below 2 degree (alternative security targets)

0% 2% 4% 6% 8% 10% 12% 14% 0% 10% 20% 30% 40% 50% 60%

Probability of Staying Below 2 degrees Centigrade Total Discounted System Costs Relative Change from Baseline (2000‐2050)

5% Max Import Share 10% Max Import Share 15% Max Import Share 20% Max Import Share 25% Max Import Share 30% Max Import Share No Max Import Share

More than 600 scenarios! Effect of the trade constraint

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SLIDE 16

System Costs vs. Probability of Staying Below 2 degree (alternative security targets)

0% 2% 4% 6% 8% 10% 12% 14% 0% 10% 20% 30% 40% 50% 60%

Probability of Staying Below 2 degrees Centigrade Total Discounted System Costs Relative Change from Baseline (2000‐2050)

5% Max Import Share 10% Max Import Share 15% Max Import Share 20% Max Import Share 25% Max Import Share 30% Max Import Share No Max Import Share

More than 600 scenarios!

high security better climate

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SLIDE 17

0.00 1000.00 2000.00 3000.00 4000.00 5000.00 6000.00 0-20 % 20-40 % 40-60 % 60-80 % 80-100 % 0.00 1000.00 2000.00 3000.00 4000.00 5000.00 6000.00 0-20 % 20-40 % 40-60 % 60-80 % 80-100 % Electricity Coal LPG Kerosene Dung Firew ood

Income vs. energy consumption in India (MJ/cap/a, 2000)

Urban: Rural:

Income quintiles Income quintiles Most polluting and least efficient

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SLIDE 18

Methodology

  • Simple energy model of the

residential/commercial sector of India

– Linear programming, cost optimization (MESSAGE)

  • 10 consumer groups

– Urban/rural – Five income categories

  • Main factor affecting fuel choice

– Price of energy fuels & appliances – Financial (budget) constraints – Consumer’s rate of time preference (planning horizon & implicit discount rate) – “Inconvenience costs” of low quality fuels (biomass and coal) – Policy instruments: fuel subsidy and/or micro-financing

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Urban and rural fuel use (cooking) No policy in addition to present ones

Rural in 2000

200 400 600 800 1000 1200 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Urban in 2000

100 200 300 400 500 600 700 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Rural in 2020

200 400 600 800 1000 1200 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Urban in 2020

100 200 300 400 500 600 700 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Biomass use -30% Biomass use +18%

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Urban and rural fuel use (cooking) Two policy cases

Biomass use -30% Biomass use +18%

Rural in 2020 with -30% LPG Price Policy

200 400 600 800 1000 1200 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Urban in 2020 with -30% LPG Price Policy

100 200 300 400 500 600 700 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Rural in 2020 with Price Policy and Microfinancing

200 400 600 800 1000 1200 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Urban in 2020 with Price Policy and Microfinancing

100 200 300 400 500 600 700 0-20% 20-40% 40-60% 60-80% 80-100% Income Quintiles Electricity LPG Kerosene Coal Biomass

Biomass use -100% Biomass use -100% Biomass use -100% Biomass use -28%

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People without Access

(modern cooking fuels only)

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90

2000 No policy (2020) Subsidy only (2020) Subsidy and Microfinancing (2020)

billion

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5000 10000 15000 20000 25000 30000 LPG subsidy micro financing + LPG subsidy Million US 2000$

Policy Costs and Efficiency

(cumulative 2010-2020)

  • 33% subsidy assumes reducing LPG prices from 6.4 $/GJ to 4.2 $/GJ
  • Values do not include present costs to keep prices at 6.4 $/GJ

Access for 200 mill people Access for 700 mill people

4$ per person annually 9$ per person annually

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SLIDE 23

CO2 Emissions in India

Effect of cooking fuel policy

50 100 150 200 250 300 350 400 2000 2020 MtonC

Increment by Microfinancing Increment by LPG subsidy Total w /o Access Policy