Issues and Concepts in Projecting Baseline Emissions Leon Clarke Climate Change Expert Group Global Forum OECD Conference Center, Paris March 19-2, 213
The modeling community has produced many baseline scenarios Individual papers by individual modeling teams. Community exercises Asian Modeling Exercise (212) [Global, Asian Countries] EMF 22 (29) [Global, US, EU] AMPERE (213) [Global] LIMITS (213) [Global] EMF 27 (213) [Global] EMF 24 (213) [US] EMF 28 (213) [EU] RoSE (213) [Global] There is a lot of inertia in these baselines. There is often lock-in to particular underlying projections. Some studies specifically explore alternative baselines.
Some background for interpreting scenarios from the modeling community Interpretation of likelihood of different baselines is difficult Modelers are not necessarily trying to create best guesses, but their baselines are certainly informed by their perceptions of how the world might evolve. The treatment of policies in baseline scenarios is challenging The breadth of baseline policies can be quite difficult to represent. There are important questions about which policies should be in the baseline climate, climate-related, and non-climate. Scenarios do generally take into account some non-climate factors such as air pollution. Global modeling teams must produce baseline assumptions for all world regions, challenging the ability to get capture regional circumstances for individual countries or regions. Most global models have only limited regional detail that would be viable for developing country-level baselines.
Baseline uncertainty is not relevant only to rapidly developing regions. 12 1 GtCO2e/yr 8 6 Historic Emissions 287 4 2 ADAGE MRN-NEEM EPPA IGEM MERGE (opt) MiniCAM (base) 199 2 21 22 23 24 25 23 167 BM From: Fawcett, A., K. Calvin, F. de la Chesnaye, J. Reilly, J. Weyant, (29), Overview of EMF 22 U.S. transition scenarios, Energy Economics, 31: S198-S211
There is a long history of retrospective analysis of energy-related forecasts. From: Craig, P., A. Gadgil, and J. Koomey, (22) What can history teach us? A retrospective examination of longterm energy forecasts for the United States, Annual Review of Energy and the Environment, 27:83-118
There is a long history of retrospective analysis of energy-related forecasts. These projections could be further off: GDP projections were high, and energy intensity projections were low. From: O Neill, B., and M. Desai (25), Accuracy of past projections of US energy consumption, Energy Policy, 33:979-993
Baselines are the basis for assessments of mitigation options and costs. INDIA Reduction in Emissions Intensity in 22 Relative to 25 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Uncertainty in baselines is reflected in uncertainty in mitigation costs. INDIA Reduction in Emissions Intensity in 22 Relative to 25 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Baseline emissions influence, but do not define, the costs of meeting goals. INDIA Reduction in Emissions Intensity in 22 Relative to 25 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Baseline emissions influence, but do not define, the costs of meeting goals. UNITED STATES Emissions in 22 Relative to 25 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Baseline emissions influence, but do not define, the costs of meeting goals. EUROPEAN UNION Emissions in 22 Relative to 199 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Baseline emissions influence, but do not define, the costs of meeting goals. JAPAN Emissions in 22 Relative to 199 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Baseline emissions influence, but do not define, the costs of meeting goals. CHINA Reduction in Emissions Intensity in 22 Relative to 25 From: Calvin, K., A. Fawcett, K. Jiang, (212), Comparing model results to national climate policy goals: Results from the Asia modeling exercise, Energy Economics, 34: S36-S315
Modeling exercises are consistently used to help understand emissions pathways to long-term goals GtCO 2 /yr 4 3 2 1 CO2 Emissions in scenarios reaching 45 CO2-e by 21 ETSAP-TIAM FUN D GTEM IMAGE-BECS MESSAGE MESSAGE-N obecs MiniCAM-Base MiniCAM-LoTech There are a lot of pathways toward long-term goals. These pathways can be very different, for example Degree of overshoot. Degree of negative emissions. Nature of the goal (what is meant by 2 degrees?) -1-2 2 21 22 23 24 25 26 27 28 29 21 All of the new scenario exercises are producing these long-term scenarios, and they form the basis for the IPCC and other assessments. From: Clarke, L., J. Edmonds, V. Krey, R. Richels, S. Rose, M. Tavoni, 29, International Climate Policy Architectures: Overview of the EMF 22 International Scenarios, Energy Economics, 31 S64 S81.
How well do baselines reflect changing conditions? EJ/ yr 16 14 12 1 8 6 ADAGE Primary energy in the EMF 22 reference scenarios (k) Energy 16 Reduction (j) Total Non-Biomass 14 Renewable (i) Nuclear 12 (h) Bioenergy w/ccs 1 (g) Bioenergy w/o CCS Natural Gas 8 (f) Gas w/ccs EJ/ yr Coal (e) Gas w/o 6CCS MRN-NEEM (k) Energy 16 Reduction (j) Total Non-Biomass 14 Renewable (i) Nuclear 12 (h) Bioenergy w/ccs 1 (g) Bioenergy w/o CCS 8 (f) Gas w/ccs EJ/ yr (e) Gas w/o 6CCS EPPA (k) Energy Reduction (j) Total Non-Biomass Renewable (i) Nuclear (h) Bioenergy w/ccs (g) Bioenergy w/o CCS (f) Gas w/ccs (e) Gas w/o CCS 4 (d) Coal w/ccs 4 (d) Coal w/ccs 4 (d) Coal w/ccs 2 (c) Coal w/o CCS 2 (c) Coal w/o CCS 2 (c) Coal w/o CCS 2 21 22 23 24 25 (b) Oil w/ccs (a) Oil w/o CCS 2 21 22 23 24 25 (b) Oil w/ccs (a) Oil w/o CCS 2 21 22 23 24 25 (b) Oil w/ccs (a) Oil w/o CCS 16 IGEM (k) Energy 16 Reduction MERGE (opt) (k) Energy 16 Reduction MiniCAM (base) (k) Energy Reduction EJ/ yr 14 12 1 8 (j) Total Non-Biomass 14 Renewable (i) Nuclear 12 (h) Bioenergy w/ccs 1 (g) Bioenergy w/o CCS 8 (f) Gas w/ccs EJ/ yr (j) Total Non-Biomass 14 Renewable (i) Nuclear 12 (h) Bioenergy w/ccs 1 (g) Bioenergy w/o CCS (f) Gas w/ccs 8 EJ/ yr (j) Total Non-Biomass Renewable (i) Nuclear (h) Bioenergy w/ccs (g) Bioenergy w/o CCS (f) Gas w/ccs 6 (e) Gas w/o 6CCS (e) Gas w/o 6CCS (e) Gas w/o CCS 4 2 2 21 22 23 24 25 (d) Coal w/ccs 4 (c) Coal w/o CCS 2 (b) Oil w/ccs (a) Oil w/o CCS 2 21 22 23 24 25 (d) Coal w/ccs 4 (c) Coal w/o CCS 2 (b) Oil w/ccs (a) Oil w/o CCS 2 21 22 23 24 25 From: Fawcett, A., K. Calvin, F. de la Chesnaye, J. Reilly, J. Weyant, (29), Overview of EMF 22 U.S. transition scenarios, Energy Economics, 31: S198-S211 (d) Coal w/ccs (c) Coal w/o CCS (b) Oil w/ccs (a) Oil w/o CCS
Effect of Abundant Gas on Baseline Radiative Forcing: Countervailing Effects Natural gas emits less CO 2 than other fossil fuels; Inexpensive natural gas leads to both substitution for other energy carriers, and expanded use of total energy and power; Increased use of gas in power generation reduces the use of coal, which in turn reduces sulfur emissions. Sulfur aerosols also cool the Earth and therefore reduced emissions unmask some climate change; Natural gas use reduces non-sulfur air pollutants that are positive contributors to climate forcing; and The increase in gas use is potentially accompanied by greater losses from gas production and transport. That is, it increases methane emissions. ppm CO 2 equivalent Change Preliminary results not for citation or attribution 7 6 5 4 3 2 1-1 -2-3 -4 All Other Gases SO2 Other Kyoto Gases N2O CH4 CO2 Net change
What are some issues to keep in mind when considering baseline scenarios The modeling community has produced and will continue to produce many baselines. There is a great deal of uncertainty in these projections. This is unavoidable. There are ways to explore baselines to gain transparency (see the previous talk). There are challenges in defining what should be in a baseline. It is important to think about important unexpected changes (e.g., abundant gas). The modeling community is also producing a large set of scenarios that can help to define the range of pathways toward long-term goals and inform the costs of mitigation in different regions. Baselines are an important factor in developing these scenarios.