Harnessing Systems Analytical Tools to develop Sustainable Energy Scenarios for the 21st Century

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Harnessing systems-

analytical tools to develop

sustainable energy scenarios for the 21 ^st century

David McCollum

Energy Program, IIASA

IIASA Systems Analysis 2015 Conference November 11-13, 2015 (Laxenburg, Austria)

Acknowledgements:

Keywan Riahi, Volker Krey, Peter Kolp, Manfred Strubegger, Joeri

Rogelj, Shilpa Rao, Markus Amann, Zig Klimont, Wolfgang Schoepp,

Shonali Pachauri, Arnulf Gruebler, Nebojsa Nakicenovic, Jessica Jewell,

Mathis Rogner, …

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Post-2015 Sustainable Development Goals (SDG)

Source: https://sustainabledevelopment.un.org/

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COP21: 2015 Paris Climate Conference

Goal is to achieve a legally binding and universal agreement on climate, with the aim of keeping global warming below 2°C.

Image sources: GIY(www.globalinstituteforyouth.org/2015/09/less-than-100-days-left-are-youth-ready-for-cop-21-paris/); COP21 (www.cop21paris.org/)

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Part I: Thinking about

energy as a system

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Graphics courtesy of Volker Krey (IIASA)

Energy Supply

Energy Demand

Transport Industry Buildings

Agriculture, economy, geo-politics,…

Climate,

environment

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Graphic courtesy of Volker Krey (IIASA)

IIASA Integrated Assessment Framework

Scenario Storyline

•demographic change

•economic development

•technological change

•policies

Population Economy

G4M

spatially explicit forest management

model

GLOBIOM

integrated agricultural, bioenergy and forestry model

MESSAGE

systems engineering model (all GHGs and all energy

sectors)

socio-economic drivers

consistency of land-cover changes (spatially explicit maps of agricultural, urban,

and forest land) carbon and

biomass price

agricultural and forest bioenergy

potentials, land-use emissions

and mitigation potential National level Projections

MAGICC

simple climate model

GAINS GHG and air

pollution mitigation

model

emissions

air pollution emission coefficients & abatement costs

demand response

iteration

MACRO

Aggregated macro-economic

model

energy service prices

socio-

economic

drivers

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‘Sustainable development’ means overcoming several energy challenges

Energy Security

Climate Change Air Pollution

Image sources: NASA, http://www.powernewsnetwork.com/white-house-releases-plan-to-cut-oil-imports-by-13-by-2025/1798/, http://wheresmyamerica.wordpress.com/2007/08/26/i-cant- see-my-america/, http://www.americanprogress.org/issues/green/report/2009/05/14/6142/energy-poverty-101/, http://today.uconn.edu/blog/2010/12/reclaiming-water-a-green-leap- forward/, http://te.wikipedia.org/wiki/%E0%B0%A6%E0%B0%B8%E0%B1%8D%E0%B0%A4%E0%B1%8D%E0%B0%B0%E0%B0%82:Forest_Osaka_Japan.jpg

Energy Poverty

Water Scarcity

Food Security &

Biodiversity

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Energy Security

Climate Change Air Pollution

2ºC warming

Increased diversity;

reduced imports

Air quality guidelines (e.g., PM2.5 35 µg/m

³

)

Affordability of $

Energy Services

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In c re a si n g s tr in g en c y

> 4

^o

C

3

^o

C 2

^o

C 1.5

^o

C

… … … In c re a si n g s tr in g en c y

Global warming

Business-as-usual Weak effort Moderate effort Stringent effort Energy imports and

diversity

No further improvement Current legislation Air pollution framework

(PM, SO

₂

, NO

_x

, BC, … )

Stringent legislation Maximum feasible

reduction

39 levels 4 levels 4 levels

Modeled policies of varying stringency

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>600 unique scenarios spanning the feasible scenario space

(energy-climate-pollution-security futures) Climate

Air Pollution

Security

Energy Security Climate Change

Air Pollution

A large scenario ensemble was generated

Ref: McCollum, D., V. Krey, K. Riahi et al., “Climate policies can help resolve energy security and air pollution challenges.”Climatic Change(2013).

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Synergies of energy efficiency and

decarbonization accrue in multiple dimensions

1. Co-benefits for air pollution and human health

→ improved air quality

(22-32 million fewer disability-adjusted life years globally in 2030)

2. Synergies for improved energy security

→ more dependable, resilient, and diversified energy portfolios

3. Cost savings and spillovers

→ up to $600 billion/yr globally in reduced pollution control and

energy security expenditures by 2030 (0.1-0.7% of world GDP)

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0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

To ta l G lo ba l P ol ic y C os ts (2 01 0- 20 30 ) Int egr at ed S ol ut ions

Only Climate Change

Only Air Pollution

Only Energy Security

G lo b al P o licy Co st s ( 2010 -2030, % o f G DP ) Ful l ra nge of s c e na ri os

Ful l ra nge of s c e na ri os Ful l ra nge of s c e na ri os

An integrated approach saves

>$5 trillion (~0.5% of GDP)

Ref: McCollum, D., V. Krey, K. Riahi et al., “Climate policies can help resolve energy security and air pollution challenges.”Climatic Change(2013).

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GEA Launch @ RIO+20, June 2012

Kandeh Yumkella, DG UNIDO, referred to the GEA report as the “energy bible”.

Josè Goldemberg, Yong Ha Kim, H.E. Nguyen Thien, L. Gomez-Echeverri, Pavel Kabat, Hasan Mahmud, Kuntoro Mangkusubroto

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Working Group III contribution to the IPCC Fifth Assessment Report

Low-carbon scenarios show reduced costs for achieving air quality and energy security objectives, with significant co ‐ benefits for human health, ecosystems, and energy

resource sufficiency and resilience.

(430-530 ppm CO₂eq, 2100) (430-530 ppm CO₂eq, 2100)

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Working Group III contribution to the IPCC Fifth Assessment Report

Low-carbon scenarios show reduced costs for achieving air quality and energy security objectives, with significant co ‐ benefits for human health, ecosystems, and energy

resource sufficiency and resilience.

(430-530 ppm CO₂eq, 2100)

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Part II: Integrating uncertainties for climate change mitigation

Acknowledgements: Joeri Rogelj

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Integrating uncertainties

for climate change mitigation

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Methodology: developing cost-risk distributions for climate protection

Graphics courtesy of Joeri Rogelj

MESSAGE

MAGICC

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Cost-risk framework for summarizing the importance of socio-political, technological, and geophysical uncertainties

2 ^o C

Ref: Rogelj J., D.L. McCollum, A. Reisinger, M. Meinshausen, K. Riahi, “Probabilistic cost estimates for climate change mitigation.”Nature (2013) .

+

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Cost-risk framework for summarizing the importance of socio-political, technological, and geophysical uncertainties

2 ^o C

+

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Technological uncertainties are large

2 ^o C

Cases based on:

Global Energy Assessment (Riahi et al. 2012) Reisinger et al. (2012), Beach et al. (2008), Van Vuuren et al. (2006)

Cost-risk distribution

No CCS Greater transport

electrification

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Social (energy demand) uncertainties are larger

2 ^o C

Cases based on:

Global Energy Assessment (Riahi et al. 2012)

Cost-risk

distribution

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Political (delayed action) uncertainties are largest

2 ^o C

Cost-risk distribution

Delay to 2030

Delay to 2025

Delay to 2020

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Systems analysis provides a lens through which complex interlinkages can be explored

Image sources: http://www.irunoninsulin.com/?attachment_id=1887

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Harnessing Systems Analytical Tools to develop Sustainable Energy Scenarios for the 21st Century