Historical Transitions in Transport Systems iTEAM4 Workshop, IIASA - PowerPoint PPT Presentation

Historical Transitions in Transport Systems iTEAM4 Workshop, IIASA October 30, 2018 Arnulf Grubler

Technological/Infrastructural Transitions: Main Messages • End-use innovation driven (people!) • Involves Hardware + Software + Orgware • Important complementarities (infrastructures, society) • Fractal nature of transition speeds from fast (end-use) to slow (infrastructures) • Implications for modeling: Explicit representation of: -- actors and interactions -- technologies (“which”) and techniques (“how used”) -- time and space (“when, where”) -- interdependencies

France – Growth in Motorized Mobility 10 2 100,000 All modes 10 1 10,000 Buses + cars Meter/day-cap Rail Km/day-cap 1,000 10 0 2-Wheelers Horses TGV 10 -1 100 Air Railways Waterways 10 -2 10 1800 1850 1900 1950 2000 Source: A. Grubler, The Rise and Fall of Infrastructures, Physica, 1990

Disruptive, Rapid Change Darum geht zu allen Völkern […] und lehrt sie alles zu befolgen was ich Euch geboten habe. Seid gewiss: Ich bin bei euch alle Tage bis ans Ende der Welt. Source: Campanale, Carbontracker

USA – Substitution of Horses by Automobiles Saturation density: 1 vehicle/person ? Source: N. Nakicenovic, 1986, The Automobile Road to Technological Change, Technological Forecasting & Social Change 29 (4):309-340.

Ford Model T Learning by Doing-1: Fordism Learning by Doing-2: Users aka interpretative flexibility R. Kline and T. Pinch, 1996, Users as Agents of Technological Change: The Social Construction of the Automobile in the Rural Unites States , Technology and Culture 4(October):763-795.

Social Change: Change in Car Driving Licenses Held by Young Trends: near-term: <50%, long-term: ~0? Location year a year b age group % of age group with Location year a year b age group % of age group with drivers license change drivers license change year a year b %-points year a year b %-points Austria 2 2010 2015 17-18 39 28 -11 Austria 1 2006 2010 17-18 32 39 7 Germany 2008 2017 18-24 71 66 -5 Finland 1983 2008 18-19 37 68 31 Great Britain 1995 2008 17-20 43 36 -7 Finland 1983 2008 20-29 51 82 31 Great Britain 1995 2008 21-29 74 63 -11 Israel 1 1983 2008 19-24 42 64 22 Israel 2 2005 2015 17-18 34 30 -4 Israel 1 1983 2008 25-34 62 78 16 Israel 2 2009 2016 19-24 65 64 -1 Netherlands 1985 2008 18-19 25 45 20 Japan 2001 2009 16-19 19 17 -2 Netherlands 1985 2008 20-24 64 64 0 Japan 2001 2009 20-24 79 75 -4 Spain 1999 2009 15-24 37 50 13 Norway 1991 2009 19 74 55 -19 Norway 1991 2009 20-24 85 67 -18 Sweden 1983 2008 19 70 49 -21 Sweden 1983 2008 20-24 78 63 -15 Switzerland 1994 2015 18-24 71 61 -10 USA 1983 2014 18 80 60 -20 USA 1983 2014 19 86 69 -17 USA 1983 2014 20-24 91 77 -14 Note in particular much larger prevalence of declining driving license ownership and shift from growth to decline trends in Austria and Israel around 2008/2010 (for Finland, Netherlands, Spain no more recent data are available to uncover similar trend breaks) Data sources: Sivak & Schottle, 2011; Delbosc & Currie, 2013; Nat.Stats, 2017 for Austria, Germany, Israel, Switzerland

Resource Impacts of Digital Convergence 1706 449 kWh Watts 5 Watts 75 kWh Embodied energy Power 2.5 Watts 0.1 kg 26 kg 72 Watts Stand-by Weight energy use Updated ( Malmodin & Lundén, 2018; Bento, 2016) from Grubler et al, 2018. Pictorial representation based on Tupy, 2012.

France - Transport and Communication Volume Index 1985 = 100 10 2 100 10 1 10 Communication 10 0 1 Transport 10 -1 0.1 10 -2 0.01 1800 1825 1850 1875 1900 1925 1950 1975 2000 Source: A. Grubler, The Rise and Fall of Infrastructures, Physica, 1990

The Pitfalls of Supply-side Only: Failed Innovations, ex. Palmer 1828 monorails using sails Example today: Hyperloop with integrated PV ??

Explaining Fast vs. Slow Transitions slow transitions fast transitions discrete technologies systemic novel concepts, market-ready formative phases substitutes granular technologies lumpy technologies & social networks & infrastructures late adopting markets early adopting markets weak adopter benefits strong adopter benefits, (mainly less externalities) high relative advantage strong co-ordination co-ordination problems, vested and policy direction interests Grubler, A., Wilson, C., Nemet, G., 2016, Apples, oranges and consistent comparison of the temporal dynamics of energy transitions, Energy Research and Social Science 22 :18-25.

2 Modeled Transitions – World Transport Energy Use (EJ) GEA Supply vs. LED 150 150 100 100 oil products synliquids 50 50 electricity 0 0 2010 2040 2020 2030 2050 2010 2040 2020 2030 2050 GEA Supply (2012) LED (2018) Conventional Transport Shared urban mobility Low asset utilization (efficiency of use) High asset utilization (efficiency of use) IC with oil+substitutes Electrification+H2 Source: Grubler et al., 2018 , Nature Energy. Source: Riahi et al., 2012, GEA Chapter 17.

Implications for Modeling • Represent actors and their interactions (e.g. ABM) • Move from technology choice only to include also technology use • Time and space: consider interactions (e.g. Haegerstrand) and constraints (beyond Zahavi, e.g. urban size and densities) • Model systems rather than sectors/activities (takebacks, interdependencies, synergies)

Access to Technologies & Services (Lorenz Curves) 100 Cumulative percent of global access/owenership Granularity Equity 80 cell phones 2014 radios 2000 60 bicycles 2014 0.77 automobiles 2013 0.43 40 piped water 2012 piped water 2012 0.21 2014 electricity 2005 electricity 2005 GDP 20 0.89 PPP & MER 0.17 broadband 2014 broadband 2014 0.88 0.58 0.11 2000 0 Technologies & 0 20 40 60 80 100 Infrastructures Cumulative percent of global population/households Source: Zimm & Grubler (in preparation)

Global Access to Technologies (Lorenz Curves) Development & Technology Gaps 100 equity line Cumulative percent of global consumption GDP MER 80 GDP PPP 60 radios 2000 bicycles 2014 40 mobile phones 2000 20 mobile phones 2014 automobiles 2013 0 0 20 40 60 80 100 internet Cumulative percent of global population Data source: World Bank WDI 2016 and PEW Survey 2016

Global Access to Technologies (Lorenz Curves) Development & Technology Gaps 100 equity line Cumulative percent of global consumption GDP MER 80 GDP PPP 60 radios 2000 bicycles 2014 40 mobile phones 2000 20 mobile phones 2014 automobiles 2013 0 0 20 40 60 80 100 internet Cumulative percent of global population Data source: World Bank WDI 2016 and PEW Survey 2016

lumpy large unit size high unit cost Indivisible high risk Technology Unit Size granular small unit size low unit cost modular low risk

Granularity Benefits 2: Higher Learning smaller units heat pumps -> more units -> more opportunities to experiment -> more learning nuclear 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.

Energy Efficiency (%) and Emissions (g/km) for Horses, and Early and Contemporary Automobiles Horses Cars Cars (ca. 1920) (1995) Engine efficiency, % 4 10 20 Wastes Solid 400 – – Liquid 200 – – Gaseous, including Carbon (CO 2 ) d 170 120 70 Carbon (CO) – 90 2 Nitrogen (NO x ) – 4 0.2 Hydrocarbons 2 e 15 0.2 d Total carbon content of fuel e Methane Source: A. Grubler, 1998. Technology and Global Change , Cambridge University Press.

Diffusion as Epidemiological Temporal/Spatial Process Temporal distribution of adopters (countries introducing postage stamps) Source: Pemberton, 1936 Spatial distribution of car adopters Distribution of adopters by mean in region of Southern Sweden. adoption rate (K/2). Rogers, 1962 Source: Haegerstrand, 1968

ABM Example – Adoption of “green” Products • Representation of producers and adopters of technologies (agents) and policy maker (principal) micro-level interactions yield aggregate macro-level outcomes • Heterogeneous products (performance, price,…,…, environment) • Heterogeneous agents (producers: technological capability, R&D strategy; consumers: preferences and preference weights) • Agent interaction 1: producers-consumers • Agent interaction 2: consumers-consumers (“small world network” Watts- Strogatz-1998 model) depending on: -- nature and size of social network -- peer effect • Agent interaction 3: policy makers – producers – consumers policy options: education, C-tax, R&D subsidy • Illustrative results from exploratory (!) modeling

Results ABM - Network Effects: Network size (critical threshold level) >> peer effect > # of neighbors and their distance Grubler et al., 2014

Results ABM Policy Leverages: ∆ consumer preferences >> C -tax > R&D subsidy Grubler et al., 2014

Car Diffusion: Catch-up at Lower Levels Source: A. Grubler, 1998. Technology and Global Change , Cambridge University Press.