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INSTITUTO DE INVESTIGACIÓN TECNOLÓGICA - IIT
Potential options for mitigation of climate change from the energy and transport sectors
Pedro Linares
BC3 Summer School
San Sebastián, July 10th 2013
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Global GHG emissions
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Spain and the US, 2011
Avance Emisiones GEI 2011 con datos a 3 de mayo de 2012 página 6
Figura 5.1.- Distribución de las emisiones GEI por grupos SNAP en 2010
DISTRIBUCIÓN DE LAS EMISIONES GEI POR GRUPOS SNAP
AÑO 2010Combustión en la
producción y
transformación de
energía
20,1%
Combustión no industrial
8,6%
Combustión industrial
16,9%
Extracción y distribución
de combustibles fósiles
0,3%
Transporte por carretera
23,6%
Otros modos de
transporte
5,5%
Tratamiento y
eliminación de residuos
4,7%
Agricultura
11,2%
Procesos industriales sin
combustión
6,1%
Uso de disolventes y
otros productos
3,0%
Figura 5.2.- Distribución de las emisiones GEI por grupos SNAP en 2011
DISTRIBUCIÓN DE LAS EMISIONES GEI POR GRUPOS SNAP
AÑO 2011
Combustión en la
producción y
transformación de
energía
23,7%
Combustión no industrial
7,9%
Combustión industrial
15,8%
Extracción y distribución
de combustibles fósiles
0,3%
Transporte por carretera
22,4%
Otros modos de
transporte
5,5%
Tratamiento y
eliminación de residuos
4,9%
Agricultura
10,9%
Procesos industriales sin
combustión
5,5%
Uso de disolventes y
otros productos
3,1%
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Mitigation options
Source: IEA World Energy Outlook 2012
Behavioral vs Technological
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Potentials and carbon prices
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Assessing costs and potentials
• It is easy to overestimate potentials and underestimate costs
• Counterfactual scenarios
• Public vs Private perspectives
– Discount rates
– Taxes
• Interactions between options
• Rebound effect
• Bottom-up vs. Top-down
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The McKinsey curve
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The Economics for Energy curve
• Expert-based
• Only technological changes
• Interaction between options
• Private and public perspectives
• 80% of energy consumption in Spain
• How to translate energy into GHG mitigation?
– Electricity: 0.3 tCO2/MWh
– Transport: 0.25 tCO2/MWh
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Counterfactual scenario
Efficient vehicles Boilers
Lighting
Wind Heat pump
Insulation
26% savings compared to BAU
2% less than 2010
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“Strong policy” scenario
Efficient vehicles and modal change
Wind Heat pumps
Insulation
19% additional savings
50% negative cost
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“Advanced technology” scenario
Wind
Hybrid / Electric V.
Solar HW Solar TE
Insulation
Lighting
Heat pump
15% additional savings
40% negative cost
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Why don’t we use negative cost measures?
• The energy-efficiency paradox
• Non-monetary barriers
–Hidden or transaction costs
– Lack of awareness
– Inertia
– Risk premium
– The problem is not economic: subsidies may be useless
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Why do some measures look so expensive?
• Lack of the right information
–Very difficult to get reliable data (non-ETS)
–Data aggregation: there may be niches
• Multiple objectives (e.g., buildings)
–How to allocate the costs?
• Interaction between measures
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Priority options
• Efficient / Hybrid vehicles
• Efficient lighting
• Modal change in transport
• Efficient heating & cooling
• Solar water
• Heat pump results are questionable
– Other studies get much better results
• Rehabilitation of buildings might be interesting if other factors are considered (and also its great potential for reduction)
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Conclusions
• Large abatement potential in the energy and transport sector
– Technology change has a limited range
– We need behavioral changes
• The cost may be very low, even negative
• In other cases, the cost is very high
– But other factors can be considered
• Results depend very much on fuel prices
• General lack of data for these analyses