a low energy demand scenario for meeting the 1.5 °c target
TRANSCRIPT
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 (<250 EJ FE by 2050) in
published scenario literature• End-use transformations (efficiency, electrification) drive
upstream decarbonization• Stays below 1.5°C without negative emission
technologies• Significant SDG synergies (assessed for six SDGs)
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: <50%, long-term: ~0?
Note in particular much larger prevalence of declining driving license ownershipand shift from growth to decline trends in Austria and Israel around 2008/2010(for Finland, Netherlands, Spain no more recent data available to uncover similar trend breaks)
Location year a year b age group % of age group withdrivers license changeyear a year b %‐points
Austria 2 2010 2015 17‐18 39 28 ‐11Germany 2008 2017 18‐24 71 66 ‐5Great Britain 1995 2008 17‐20 43 36 ‐7Great Britain 1995 2008 21‐29 74 63 ‐11Israel 2 2005 2015 17‐18 34 30 ‐4Israel 2 2009 2016 19‐24 65 64 ‐1Japan 2001 2009 16‐19 19 17 ‐2Japan 2001 2009 20‐24 79 75 ‐4Norway 1991 2009 19 74 55 ‐19Norway 1991 2009 20‐24 85 67 ‐18Sweden 1983 2008 19 70 49 ‐21Sweden 1983 2008 20‐24 78 63 ‐15Switzerland 1994 2015 18‐24 71 61 ‐10USA 1983 2014 18 80 60 ‐20USA 1983 2014 19 86 69 ‐17USA 1983 2014 20‐24 91 77 ‐14
Location year a year b age group % of age group withdrivers license changeyear a year b %‐points
Austria 1 2006 2010 17‐18 32 39 7Finland 1983 2008 18‐19 37 68 31Finland 1983 2008 20‐29 51 82 31Israel 1 1983 2008 19‐24 42 64 22Israel 1 1983 2008 25‐34 62 78 16Netherlands 1985 2008 18‐19 25 45 20Netherlands 1985 2008 20‐24 64 64 0Spain 1999 2009 15‐24 37 50 13
Data sources: Sivak & Schottle, 2011; Delbosc & Currie, 2013; National Statistics, 2017 for Austria, Germany, Israel, Switzerland
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 upstreamPROCESS
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
