A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies

Volker Krey

IAMC Annual Meeting 2018, Seville, 13-15 November 2018

A people-centredapproach to limiting global warming to 1.5°C

Volker Krey

IAMC Annual Meeting 2018, Seville, 13-15 November 2018

Credits

https://doi.org/10.1038/s41560‐018‐0172‐6

Illustrative Model Pathways to 1.5°C

Source: IPCC SR1.5, Figure SPM.3b

P3: “Conventional wisdom”P1: LED Scenario

SSP2‐based

2 Perspectives on Meeting 1.5°CGHG Emissions Profiles

Overshoot assupply‐side optionsscale slowly, but need massivelong‐term deploymentfor high demand scenarios

Negative emissions, e.g. BECCS

Rapid Transformationdriven by end‐use changes(efficiency & behavior)

“Grand Restoration”sink enhancement viareturning land to nature

Granular, distributed supply sideoptions lead the way for scalingother mitigation options, rapid changeunder low demand

Inertia in policy,social & technologychange

“Conventional wisdom” 1.5°C IAM model run LED Scenario narrative and IAM run

LED Highlights

• High levels of energy services• Assuring “decent standards of living” for all (well above

access and poverty thresholds)• (technological & service) efficiency driven “Peak” Energy• Lowest demand scenario (

New Trends in Social and Technological Change

• Changing consumer preferences (e.g. diets)• Generational change in materialism

(service rather than ownership)• New business models

(sharing & circular economy)• Pervasive digitalization and ICT

convergence• Rapid innovation in granular technologies

and integrated digital services

Social Change: Change in Car Driving Licenses held by YoungTrends: near-term:

Mobility: 'usership‘ vs. ownership

lumpylarge unit sizehigh unit costindivisiblehigh risk

granularsmall unit sizelow unit costmodularlow risk

TechnologyUnit Size

Source: Grubler,ESA class material

y = ‐0.02ln(x) + 0.0822 R² = 0.33179

‐40%

‐30%

‐20%

‐10%

0%

10%

20%

30%

40%

1.E‐04 1.E‐03 1.E‐02 1.E‐01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04

De‐scaled

Learning Ra

te (C

umula

ve Num

ber o

f Units)

Average Unit Size (MW)

'De‐scaled' Learning Rates (per doubling of cumula ve numbers of units)

Healey, S. (2015). Separating Economies of Scale and Learning Effects in Technology Cost Improvements. IR-15-009.International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.

smaller units

‐> more units

‐> more opportunities to experiment

‐> more learning

geothermal

nuclear

Granularity Benefits: faster learningHigher Learning with Smaller Unit Scale after Accounting for Economies of Scale

2000

2200

2400

2600

2800

3000

3200

LED2020 LED2050

Food ‐ kcal/day/capita

0

5

10

15

20

25

30

35

LED2020 LED2050

Thermal comfort ‐ m2/capita

0

5

10

15

20

25

30

LED2020 LED2050

Consumer goods ‐ items/capita

North2020

Decent Standards of Living

0

2000

4000

6000

8000

10000

12000

LED2020 LED2050

Mobility ‐ passenger‐km/year/capitaNorth2020

Decent Standards of Living

North2020

Decent Standards of Living

North2020

Decent Standards of Living

Granularity Benefits: equal distribution per capita energy services in the global South

Updated (Malmodin & Lundén, 2018; Bento, 2016) from Grubler et al, 2018. Pictorial representation based on Tupy, 2012.

Resource Impacts of Digital Convergence

449 Watts

72 Watts

Power

Stand-byenergy use

1706 kWh

26 kg

Embodied energy

Weight

scenario narrative

drivers of change

food

mobility

thermalcomfort

consumer goods industry & 

manufacturing

freighttransport

commercial buildings

bottom‐up quantification of activity and energy intensity

integrated modelling of system consequences

MESSAGEix(energy-

system model)

GLOBIOM (land-use

model)

MAGICC (climate)

energy supply & land‐use

climate& health

GAINS (air pollution)

‐ activity levels ‐‐ energy intensities ‐

‐ global North vs South ‐

‐ discount rate ‐‐ technology costs ‐‐ CCS constraints –

‐ cum. emission budget ‐

downstream … then upstreamPRO

CESS

METHOD & TOOLS

ASSU

MPT

IONS

‐ probabilistic climate

sensitivity ‐‐mortality ‐

‐ digitalisation ‐‐ end‐use diversity ‐

‐ efficiency standards ‐

LEDFinal Energy DemandCompared for 2050:

Scenarios with comparable climate outcomes:

IPCC Shared Socioeconomic Pathway 2 (SSP2)max. 1.9 W/m2 radiative forcing

Global Energy Assessment (GEA) Efficiency scenario

International Energy Agency (IEA)Below 2 Degrees Scenario (B2DS)

Greenpeace A[R]evolution scenario

LED: Factors of Change 2050/2020 GlobalMore services & amenities: Less resource inputs

LED Global Thermal Comfort (rel. to 2020): Activity x 1.5, Intensity ÷ 6.3, Energy ÷ 4.3

Netherlands: Energiesprongprefabricated thermal retrofits, net‐zero housing

Mexico: NAMAlow energy social housing projects

Austria: RaiffeisenFirst Passivhausstandard office tower & retrofit

Structure of demand remains stable

Rapid electrification and decarbonization

Rapid diffusion of renewable energy

Main Characteristics of Transitions• Scaled-down demand allows faster

systems transitions:– faster electrification– higher market share of renewables:

8% (2020), 32% (2030), 60% (2050)– with lower rates of absolute capacity additions

up to 20-50%/yr historically, 15% (2020-2030), 5-10% (>2040)

• Outperforming other scenarios on most SDG dimensions

Integration of SDGs via Goal 12 addresses 12 SDGs

LED

Pre-mature Deaths from Air Pollution

0

1

2

3

4

5

2015 2015 with2050's agestructure

SSP2 1.5°C LED LED with MFR only naturalPM sources

Million pe

ople / year

1.4 Million deaths/year avoided

MFR= maximum feasible emissions reductions (near‐term technology) Source: GAINS model

Conclusion• Demand (technological and service efficiency)

key for SDGs and 1.5°C• Transition acceleration possible with end-use &

granularity focus• Global scenario quantification informed by recent

trends and advances in transition modeling• Implications for Policy Makers: Forget global climate

policy architecture, actor coalitions with urban citizens and farmers, challenge: systemic incentives (land-use, transport, infrastructure)

• Implications for Business: New opportunities with service-oriented business models, building efficiency, granular end-use technology innovation

Thank You!

Volker KreyIIASA Energy Programhttp://www.iiasa.ac.at 

krey@iiasa.ac.at