Alternative Strategies
for Sustainable Development and Deep Decarbonization.
Renewed Focus on End-use, Efficiency,
Granularity, and Digitalization
1.5˚C
Arnulf Grubler IIASA, Laxenburg, Austria

ALPS Symposium, Tokyo, February 19. 2019

2 Perspectives on Meeting 1.5 °C
GHG Emissions Profiles
Overshoot as
supply-side options
scale slowly, but need massive
long-term deployment
for high demand scenarios

Inertia in policy,social & technology
changeNegative emissions, e.g. BECCS

Conventional wisdom 1.5 IAM model run

Rapid Transformation
driven by end-use changes(efficiency & behavior)Granular, distributed supply side
options lead the way for scalingother mitigation options, rapid change
under low demand“Grand Restoration”
sink enhancement via
returning land to nature
LED Scenario narrative and IAM run

Why Focus on End-use?
• Most direct link to SDGs: human welfare• Changing societal preferences(emerging “tectonic shifts”)• Least efficient part of resource systems(eff. = technology x behavior x business models)• Improvements translate into
vast upstream leverage effects (x <10!!)• Dominance of granular technologies• Rapid transitions possible

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(Society 5.0)
• Rapid innovation and cost reductions
in granular technologies
and integrated digital services

Social Change:
Change in Car Driving Licenses Held by Young
Trends: near-term: <50%, long-term: ~0?
Location

Austria 2
Germany
Great Britain
Great Britain
Israel 2
Israel 2
JapanJapan
NorwayNorwaySwedenSwedenSwitzerland
USAUSAUSA

year ayear b2010
2008
1995
1995
2005
2009
2001
2001
1991
1991
1983
1983
1994
1983
1983
1983

2015
2017
2008
2008
2015
2016
2009
20092009
2009
2008
2008
2015
2014
2014
2014

age group % of age group withdrivers licensechangeyear ayear b %-points
17-18
39
28
-11
18-24
71
66
-5
17-20
43
36
-7
21-29
74
63
-11
17-18
34
30
-4
19-24
65
64
-1
16-19
19
17-2
20-24
79
75
-4
1974
55
-19
20-24
85
67
-18
1970
49
-21
20-24
78
63
-15
18-24
71
61
-10
18
80
60
-20
19
86
69
-17
20-24
91
77
-14

Location

Austria 1
FinlandFinlandIsrael 1
Israel 1Netherlands
Netherlands
Spainyear ayear b

2006
1983
1983
1983
1983
1985
1985
1999

2010
2008
2008
2008200820082008
2009

age group % of age group withdrivers licensechangeyear ayear b%-points
17-18
32
39
7
18-19
3768
31
20-2951
82
31
19-24
42
64
22
25-34
62
78
16
18-1925
45
20
20-24
64
64
0
15-24
3750
13

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)
Data sources: Sivak & Schottle, 2011; Delbosc & Currie, 2013; Nat.Stats, 2017 for Austria, Germany, Israel, Switzerland

End-use and Supply Efficiencies andUpstream Leverage Effect of Savings at Service Level
Energy (all services)
aggr. eff.: 14%
1 EJ saved =7 EJ primary energy
Water (ex. irrigation)
aggr. eff.: 17%
1 m3 saved =6 m3 water withdrawn
Materials (ex. steel)
aggr. eff.: 13%
1 ton saved =8 tons ore minedlumpy
large unit size
high unit costindivisiblehigh risk

TechnologyUnit Sizegranularsmall unit size
low unit cost
modularlow risk

Source: Grubler
ESA class material

Granularity Benefits

Higher Learning with Smaller Unit Scale After Accounting for Economies of Scale

geothermalsmaller units-> more units-> moreopportunities toexperiment

nuclear-> more learning

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.

the Low Energy Demand(LED) Scenario

qualityof life

urbanisation
granularity

decentralised
serviceprovisionnovelenergy
servicesouter circle =observable driversof long-term change

use value
fromservices

LEDscenario

digitalisationof daily life

rapidtransformation

information
innovation

end-userroles

inner circle =additional elements inscenario narrativeLED Highlights• Higher levels of energy services
than even GEA High• 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) ever published• End-use transformations (efficiency, electrification) drive
upstream decarbonization• Stays below 1.5 with no negative emission technologies• Significant SDG synergies (>6 SDGs)

LED - Per Capita Energy Services in the Global South
Food - kcal/day/capita
3200

Thermal comfort - m2/capita
North2020

North2020

30

3000

252800Decent Standards of Living

2600
2400

2015

Decent Standards of Living

1022002000

35

5LED2020

LED2050

0LED2020

Consumer goods - items/capita
30

North2020

25

Mobility - passenger-km/year/capita
North2020

12000
10000

20800015600010Decent Standards of Living

50LED2050

Decent Standards of Living

4000
2000

LED2020

LED2050

0LED2020

LED2050

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 Global:
More services & amenities: Less resource inputs

Example Households: Consumer Goods& Upstream Impact on Industry

X 2.4==0.1 kg of materials
0.3
6.1 GJ embodied energy

÷ 2.0

26 kg of materials
6.1 GJ embodied energy
0.3“upstream (industry) energy: ÷ 23

LED Global (compared to 2020) Thermal Comfort:
Activity x 1.5, Intensity ÷ 6.3, Energy ÷ 6.3
Mexico: NAMA
low energy social housing projects

Netherlands: Energiesprong
prefabricated thermal retrofits, net-zero housing

Austria: RaiffeisenFirst Passivhausstandard office tower retrofit

The “Sharing Economy”: Mobility Case Studies
Reductions (%) in shared mobility
scenario compared to status quovehicle
con- mobility
CO2fleet gestion
costs emissions
AucklandDublinHelsinki
Lisbon-95%-98%-96%-97%

-49%
-43%
-37%
-30%

-43%
-50%
-43%
-50%

-54%
> -31% *> -34% *-62%* IC vehicle fleets, no electrification

LED Global (compared to 2020) Mobility:
Activity x 1.9, Intensity ÷ 4.6, Energy ÷ 2.5

17

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 91%/yr historically, 15% (2020-2030)<5% (>2050)• With no CCS, BECCS, or geoengineering• Outperforming all other scenarios on 7 SDG dimensions

LED EJ Final Energy

LED EJ Final Energy

LED EJ Primary EnergyLED: Global Mean Temperature Change
Probabilistic MAGICC Results

SDG 2, 3, 7, 13, 14, 15 Implications

LED vs IPCC SSPs (SSP1-3Ref & 1.9) Scenarios
SSP3 2.6~600
SSP1,2 2.6

Scenario
Comparison
2050

Conclusion• Demand (technological and service efficiency)
key for SDGs and 1.5• Transition acceleration possible withend-use & granularity focus• First global scenario quantification (LED), informed by recent
trends and advances in transition modeling• Implications for Policy Makers: Deemphasizet global climate
policy architecture, actor coalitions with urban citizens andfarmers, challenge: systemic incentives (land-use, transport,infrastructure)• Implications for Business: New opportunities with serviceoriented business models, building efficiency, granular enduse technology innovation

ありがとう