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 14 th 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 of 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-CO 2 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 targeted to sectors covered by EU emissions tradings system, i.e. electric power and energy-intensive industries CO 2 price scenarios 2000 2005 2010 2015 2020 2025+ Stepwise CO 2 -eq 0 10 20 30 40 50 price 10 € per t CO 2 -eq 0 10 10 10 10 10 20 € per t CO 2 -eq 0 10 20 20 20 20 30 € per t CO 2 -eq 0 10 30 30 30 30 40 € per t CO 2 -eq 0 10 40 40 40 40 50 € per t CO 2 -eq 0 10 50 50 50 50

Non-CO 2 greenhouse gas emissions in Germany, 1995-2006 million ton CO 2 -eq 200 180 160 140 SF6 120 PFC 100 HFC N2O 80 CH4 60 40 20 0 Base 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 year

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

GHG emissions baseline 1,200 1,000 F-gas N2O CH4 800 million tons CO 2 -eq 600 CO2 400 200 0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

GHG emissions pathway: 50 € /t CO 2 -eq 1,200 1,000 F-gas 800 N2O CH4 2 -eq million tons CO 600 400 CO2 200 0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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 oil-fired Other industry gas-fired Rail and land transport coal-fired Other transport nuclear Agriculture hydro advanced technologies Services (everything else) Electricity distribution Gas distribution 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 CO 2 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 oil gas wind PC PCA PCAccs IGCC IGCCccs NGCC NGCCccs

SGM Results: baseline electricity generation TWh 700 600 wind subsidized wind 500 nuclear NGCC 400 IGCC 300 advanced coal (PCA) 200 coal (PC) 100 gas oil hydro&other ren 0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Electricity sector results – stepwise policy case TWh 700 Baseline 600 Policy scen. wind 500 nuclear subsidized wind NGCCccs 400 NGCC 300 IGCCccs IGCC 200 advanced coal PCAccs coal (PC) (PCA) 100 gas oil hydro & other ren 0 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Log-Mean Divisia (LMDI) Decomposition E C Q E �� � � � � ij ij i i C C Q ij Q Q E E i j i j i i ij C = total industrial CO 2 emissions C ij = emissions from fuel j in industry i Q = gross output across industrial sectors E i = total energy consumed in industry i E ij = 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 Q E C Q � � � � elec , k elec , k elec , k elec C C Q elec elec , k Q Q Q E k k elec elec , k elec , k C elec = CO 2 emissions from electricity generation C elec,k = emissions from electricity technology k Q = gross output across industrial sectors Q elec = gross output for electricity (GWh) Q elec,k = output for electricity technology k (GWh) E elec,k = energy consumption by electricity technology k

Decomposition of electricity sector CO 2 emissions over time, relative to model base year (1995), for the stepwise policy scenario 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 100 50 economic activity 0 cha nge in e m issions since 1 output share -50 generation mix -100 efficiency -150 emission factors (CCS) sum of components -200 -250 -300

Decomposition of industrial CO 2 emissions (excluding electricity) over time, relative to model base year (1995), for the stepwise policy scenario 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 250 200 150 100 change in emissions since 1995 economic activity 50 0 sum of components product mix -50 -100 energy efficiency -150 -200 -250

Simulated emissions reductions over a range of CO 2 prices, Germany 2040 60 2040 product econ energy emission factors (CCS) activity mix efficiency non-CO 2 GHGs fuel mix 50 CO 2 price ( € per tCO 2 -eq) 40 30 20 10 0 0 20 40 60 80 100 120 140 160 180 200 220 reduction in CO 2 emissions compared to baseline (million tons CO2-eq)

Decomposition of emissions reduction with a stepwise increasing CO 2 price fully and partially covering the economy 250 households non-CO2 GHGs reduction in CO 2 -eq emissions (million tCO 2 -eq) activity product mix 200 energy efficiency fuel mix emission factors (CCS) 150 100 50 0 full cov part cov full cov part cov full cov part cov full cov part cov 2010 2020 2030 2040

Conclusions One step toward providing more realistic scenarios of greenhouse gas mitigation options in Germany End-of-pipe character of non-CO 2 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