Topic 5 mitigation options

Public Economics 2013-‐2014 Manon Cuylits

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Topic 5 : Mitigation options “Reaching 80% to 95% GHG emissions reduction [...] is possible. Nevertheless, reaching this target is very challenging, will imply large reductions in all sectors and a thorough understanding of the various interconnected dimensions is key.” Pestiaux et al. (2013), Scenarios for a low carbon Belgium by 2050, Forthcoming

1. Introduction Objective of this topic: analyse what can be done to reduce GHG emissions and analyse economic impacts of these actions Models are used to:

• Assess the emission reduction possibilities at the level of a sector/country/region/world

• Assess the impacts of emission reductions on several indicators such as costs, employment, air pollution, etc...

This requires to begin with a clear view on:

• Possible technological levers • Possible behavioural levers • Their combination

2. Case-‐study on Belgium : OPEERA accounting model

2.1. Overall approach

• Establish historical GHG emissions per sector (starting point, e.g. 2010) • Establish a mid-‐term or long-‐term “business-‐as-‐usual” scenario (e.g. up to 2020

or 2050), i.e. under no additional policies/measures/actions, to be used as a benchmark/reference against which the impact of targets/policies/ actions (levers) are to be assessed;

• In each (sub)sector, identify emission reduction levers and possible ambition levels for each lever:

o Possible technologies aimed at reducing GHG emissions, with due attention to the level of deployment (existing, in demonstration phase, in R&D phase, ...)

o Activity levels, such as travel demand per person or industrial production

• Build scenarios, i.e. coherent set of assumptions and levers leading to required level of total emission reductions in 2050

• Analyse the impacts of each scenario on e.g. energy security, final energy demand, costs, etc...

Source: Pestiaux et al. (2013)


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Main question: how to reduce emissions by 80 to 95% by 2050 wrt 1990 and what are the main impacts of such large reductions?

Historical GHG emissions Belgium has reduced its emissions by ~8% since 1990

Historical distribution of emissions Emissions in 2010 are relatively equally distributed between power, industry, buildings and transport


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Methodology Based on open and transparent tool OPE2RA developed by CLIMACT and VITO on the basis of DECC (UK) pathways calculator

Building scenarios

2.2. Sectoral analysis

2.2.1. Transport Observations:

1. Transport represents about a quarter of the overall energy consumption in Belgium

2. The Belgian motorized transport is somewhat less car-‐based than the European average

3. The density of the Belgian highway network is far above European average 4. The overall distances covered by passengers since 1990 increased by 30%,

cars represent ~80% 5. Between 1990 and 2008, cars lost some share to buses and rail transport 6. The CO2 emissions of new vehicles have been decreasing in recent years


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7. Urbanization levels and land planning play a crucial role in GHG mitigation policies

8. The availability of public transport influences the choice of transport modes 9. The Belgian modal split for goods is somewhat less road-‐oriented than the

European average 10. Road transport represents the bulk of energy consumption across passenger

and goods, and across transport modes

Levers for domestic passenger transport (ambition levels 1 and 4)


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Visualisation of the different levels of technology distribution for cars

Costs : capital (CAPEX) and operational (OPEX) expenditures in 2010 and 2050 – Passenger cars


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Levers for freight transport (ambition levels 1 and 4)

2.2.2. Buildings Levers in residential buildings include:

• for heating: compactness of buildings (flats vs houses), heating comfort level, thermal efficiency, electrification level, innovative heating technologies;

• for lighting and appliances: demand/efficiency, electrification


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2.2.3. Agriculture Levers include: number of animals and meat consumption, emissions intensity per animal (enteric fermentation + manure management), evolution of soil emissions

2.2.4. Industry


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2.2.5. Energy production (Energy supply) Levers include biomass, geothermal, wind (onshore and offshore), solar PV, solar thermal, Carbon capture and sequestration (CCS), imports of electricity

2.3. Scenarios

GHG Emissions

Main indicators in 2050


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2.4. Costs of mitigation scenarios Undiscounted costs => does not assess ‘private profitability’ of investments

With discounting of 10% (thus rather high rate):

More on discounting è See topic 8


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2.5. Build and assess your own low carbon scenario

• UK: http://2050-‐calculator-‐tool.decc.gov.uk • BE: forthcoming on www.climatechange.be/2050 • Walloon region: http://www.wbc2050.be • China: http://2050pathway-‐en.chinaenergyoutlook.org • Others ...

3. Various approaches

3.1. Modelling approaches

Accounting models (e.g. OPE2RA, SAVER-‐LEAP, EPM, Anonymous model of FPB)

• Central modelling logic: to guarantee consistency in energy accounting. • Defining activity drivers and pathways for energy efficiency or carbon

intensity improvements at the sectoral levels are the core elements of the methodology.

• Technologies are implicit (no ‘production function’) and costs are often considered in an ex-‐post calculation.

• The particular strength of accounting models is: o Their transparency and flexibility in presenting energy analysis concepts

whilst guaranteeing consistency in energy accounting. o They can be useful to explore possible pathways and provide more

quantitative analysis on the required targets to be reached by the underlying hypothesis at sectoral levels

o Can be useful to explore the social acceptance of the transition as well as its contours by stakeholder consultation as they provide powerful reporting capabilities.

Macro-‐economic models: General equilibrium macro-‐economic model, econometric macro-‐economic models (e.g. GEM-‐E3, HERMES, NEMESIS)

• Macroeconomic models represent the whole economy and include feedback mechanisms from and to the energy system.

• These models are based on the same type of behavioural assumptions for the economic agents but they differ regarding

o the market equilibrium assumptions and o the dynamic path modelling.

• Econometric models are more oriented towards the adjustment path in the short to medium term allowing market disequilibrium; basis is : Y = C +I+G+X-‐M

• General equilibrium model are medium to long term oriented evaluating the impact of a policy when the full effect are accounted for; based on maximisation of Utility functions.

Partial equilibrium models of the energy system (e.g. TIMES and PRIMES)

• Have a detailed representation of technologies in a consistent framework • Partial equilibrium means that the energy demand (curve) is fixed (which is

NOT the case in macroeconomic models) • PRIMES and TIMES differ in their mathematical formulations:


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o PRIMES models the economic agent’s behaviour (describing what would happen if); this takes place through, a.o. high discount rates for consumers reflecting some form of information failure (private discount rate => see topic 8)

o TIMES is more normative from the point of view of the public authority (prescribing what optimally should happen) through, a.o. low discount rates (close to social discount rate => see topic 8)

• Example: on blackboard

Trade-‐offs

3.2. What do we mean by « costs » ? Macroeconomic models: GDP and/or welfare:

• Macroeconom(étr)ic models and some CGE models, i.e. required feedback of, typically, changes in energy system on the whole economy, including public sector (taxes, revenues, ...)

• Thus level of economic activity (GDP), also per sector, employment effects, possibly competitiveness, ...

• Computable general equilibrium (CGE) models, i.e. based on utility function, thus relative change in Utility (%) is computed

Partial equilibrium models: energy system including loss of consumer surplus:

• Costs of technologies • Possibly, loss of consumer surplus

Accounting models: energy system costs: Capex – Opex – Fuel Other important costs (or benefits) are usually not included in models and must be computed separately: health effects of changes in emissions, energy security, traffic congestion, ...


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4. Appendix

A.1 Global GHG emissions and their distribution

GHG emissions by sector in 2010 (cfr. Topic 1)

Shares of GHG emissions per sector in 2010 (selection of countries)


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A.2 What are negative emissions?

Negative emissions IPCC scenarios to keep temperature rise below 2°C indicate that it might be required to reduce emissions below 0 (i.e. net absorption of carbon dioxide). What are negative emissions? IEA (2013), Box 1.1, p.17:

Readings

• Pestiaux, J., Cornet, M., Duerinck, J., Laes, E., Lodewijks, P., Meynaerts, E., Renders, N. and Vermeulen, P. (2013), Scenarios for a low carbon Belgium by 2050, Final Report, Study performed for the Climate Change Section of the Federal Public Service Health, Food Chain Saftey and Environment, forthcoming (www.climatechange.be/2050)

• IEA (2013), Redrawing the energy-‐climate map, World Energy Outlook Special Report. • Duerinck, J. (2012), Transition towards a low carbon society in 2050: Status of long term

modelling in Belgium, Mimeo (forthcoming on www.climatechange.be/2050)

Economy & Finance

Topic 5 mitigation options