Decomposition Analysis and Climate Policy in a General Equilibrium - - PowerPoint PPT Presentation

Decomposition Analysis and Climate Policy in a General Equilibrium Model of Germany

Ron Sands USA Katja Schumacher Germany 14th AIM International Workshop Tsukuba, Japan 15-16 February 2009

Acknowledgments

This presentation is a summary of the following journal article published in February 2009:

Sands, R.D., and K. Schumacher. (2009). “Economic comparison

• f greenhouse gas mitigation options in Germany,” Energy

Efficiency 2:17-36.

This paper was completed while the first author was employed at Pacific Northwest National Laboratory and the second author at the Institute for Applied Ecology in Berlin. This work was funded in part by the German Ministry for Education and Research (BMBF) within its socio- ecological research framework and also, in part, by the US Environmental Protection Agency. The views expressed by the authors do not necessarily reflect the views of the Institute for Applied Ecology (Öko-Institut e.V.), the German Government, Pacific Northwest National Laboratory, the US Government, or any agency thereof.

Introduction

Greenhouse gas mitigation options

Non-CO2 GHG emissions reduction Energy efficiency Fuel switching Carbon dioxide capture and storage (CCS)

Options vary by time and ability to represent them in economic analysis Objective of paper

provide balanced analysis of these options present results using a formal decomposition methodology

Use CGE model for Germany (SGM-Germany) Analyze costs of mitigating GHG emissions under different policy scenarios

Policy Scenarios

50 50 50 50 10 50 € per t CO2-eq 40 40 40 40 10 40 € per t CO2-eq 30 30 30 30 10 30 € per t CO2-eq 20 20 20 20 10 20 € per t CO2-eq 10 10 10 10 10 10 € per t CO2-eq 50 40 30 20 10 Stepwise CO2-eq price 2025+ 2020 2015 2010 2005 2000 CO2 price scenarios

targeted to sectors covered by EU emissions tradings system, i.e. electric power and energy-intensive industries

Non-CO2 greenhouse gas emissions in Germany, 1995-2006

20 40 60 80 100 120 140 160 180 200 Base year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 million ton CO2-eq SF6 PFC HFC N2O CH4

Magnesium 18 Electricity distribution 17 SF6 Semiconductor 16 Aluminum 15 PFCs Ozone depleting substances substitutes 14 HFCs Solvent use and other product use 13 Waste 12 Fossil fuels 11 Manure 10 Industrial processes 9 Agricultural soil 8 N2O Solid waste 7 Natural gas and oil systems 6 Enteric fermentation 5 Coal production 4 CH4 Coal combustion 3 Gas combustion 2 Oil combustion 1 CO2 Emissions Source Source # Gas

GHG emissions baseline

CO2 CH4 N2O F-gas 200 400 600 800 1,000 1,200 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

million tons CO2-eq

GHG emissions pathway: 50€/t CO2-eq

CO2 CH4 N2O F-gas 200 400 600 800 1,000 1,200 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

million tons CO

2-eq

Second Generation Model

Collection of computable-general-equilibrium (CGE) models for 14 world regions Regional models (e.g., Germany) can be run independently Dynamic recursive model Five-year time steps from 1995 through 2050 18 sectors, including 8 energy sectors

Production sectors in SGM-Germany

Crude oil production Pulp and paper Natural gas production Chemicals Coal production Non-metallic minerals Coke and coal products Primary metals Electricity generation Food Processing

• il-fired

Other industry gas-fired Rail and land transport coal-fired Other transport nuclear Agriculture hydro advanced technologies Electricity distribution Gas distribution Services (everything else) Oil refining

Technologies in SGM-Germany

Introduce bottom up technology information in energy economy model Keep richness of each set of information (macro-economic, energy, engineering) Focus on advanced electricity:

Advanced wind (offshore) IGCC (integrated coal gasification comb. cycle) PCA (advanced pulverized coal) NGCC (natural gas combined cycle) with and without CO2 capture and storage (CCS)

Availability:

IGCC, NGCC, PCA in 2015, Wind and CCS technology in 2020

Levelized costs of electricity production (COE):

COE = capital cost + labor cost + fuel cost + (capture + transport/storage cost)

Electricity sector in SGM Germany

All production sectors other than electricity represented by single CES production function Each electric generating technology represented by fixed-coefficient production function Electricity sector uses a nested logit structure to allocate new investment to generating technologies

electricity from fossil fuels and wind peaking base load

• il

NGCCccs NGCC IGCCccs gas wind PCA PCAccs IGCC PC

SGM Results: baseline electricity generation

hydro&other ren

• il

gas coal (PC) advanced coal (PCA) IGCC NGCC subsidized wind wind nuclear 100 200 300 400 500 600 700 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 TWh

Electricity sector results – stepwise policy case

hydro & other ren

• il

gas coal (PC)

advanced coal (PCA) PCAccs

IGCC IGCCccs NGCC

NGCCccs

subsidized wind wind nuclear Policy scen. Baseline 100 200 300 400 500 600 700 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 TWh

Log-Mean Divisia (LMDI) Decomposition

ij ij j i ij i i i i i j ij

E C E E Q E Q Q Q C C

• C = total industrial CO2 emissions

Cij = emissions from fuel j in industry i Q = gross output across industrial sectors Ei = total energy consumed in industry i Eij = energy consumed from fuel j in industry i

Source: Ang, B.W. (2005). “The LMDI approach to decomposition analysis: a practical guide.” Energy Policy 33: 867-871.

Variation of LMDI for Electricity

• k

k elec k elec k elec k elec elec k elec elec k k elec elec

E C Q E Q Q Q Q Q C C

, , , , , ,

Celec = CO2 emissions from electricity generation Celec,k = emissions from electricity technology k Q = gross output across industrial sectors Qelec = gross output for electricity (GWh) Qelec,k = output for electricity technology k (GWh) Eelec,k = energy consumption by electricity technology k

Decomposition of electricity sector CO2 emissions over time, relative to model base year (1995), for the stepwise policy scenario

economic activity

• utput share

generation mix efficiency emission factors (CCS) sum of components

• 300
• 250
• 200
• 150
• 100
• 50

50 100 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 cha nge in e m issions since 1

Decomposition of industrial CO2 emissions (excluding electricity) over time, relative to model base year (1995), for the stepwise policy scenario

economic activity product mix energy efficiency sum of components

• 250
• 200
• 150
• 100
• 50

50 100 150 200 250 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 change in emissions since 1995

Simulated emissions reductions over a range of CO2 prices, Germany 2040

10 20 30 40 50 60 20 40 60 80 100 120 140 160 180 200 220 reduction in CO2 emissions compared to baseline (million tons CO2-eq) CO2 price (€ per tCO2-eq)

econ activity emission factors (CCS)

2040

fuel mix non-CO2 GHGs product mix energy efficiency

Decomposition of emissions reduction with a stepwise increasing CO2 price fully and partially covering the economy

50 100 150 200 250 full cov part cov full cov part cov full cov part cov full cov part cov 2010 2020 2030 2040 reduction in CO2-eq emissions (million tCO2-eq) households non-CO2 GHGs activity product mix energy efficiency fuel mix emission factors (CCS)

Conclusions

One step toward providing more realistic scenarios of greenhouse gas mitigation options in Germany End-of-pipe character of non-CO2 greenhouse gas mitigation options means that they can be deployed relatively quickly on both new and existing capital equipment Rate that other greenhouse gas mitigation options can deploy is generally limited by the rate that existing capital stocks retire Limitation: Model only accounts for price signals (direct/indirect), not for other policies & measures Primary contribution: Formal decomposition of the energy efficiency component into production (energy) efficiency and output shift components