Introduction to the AMPERE model intercomparison studies on the economics of climate stabilization

Kriegler, Elmar; Riahi, Keywan; Bosetti, Valentina; Capros, Pantélis; Petermann, Nils; Vuuren, Detlef van; Weyant, John P.; Edenhofer, Ottmar

doi:10.1016/j.techfore.2014.10.012

Cited by 22 publications

(13 citation statements)

References 20 publications

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“…It is particularly current and comprehensive for coal-fired power generators, the most carbon-intensive assets. 3 We use three additional sources to calculate committed emissions: (1) current and historic heat rates from the U.S. Energy Information Agency (EIA) and the U.S. Environmental Protection Agency (EPA) (EPA, 2009; EIA, 2017); 4 (2) emission factors for individual fuels from the EIA (EIA, 2016); 5 and (3) global technology specific utilization rates for power generators from the International Energy Agency, IEA's World Energy Outlooks (WEO) 2005-15.…”

Section: Databases and Sourcesmentioning

confidence: 99%

“…To improve on the previous estimates of the currently remaining generation-only carbon budget we use all scenarios, assessed by the Intergovernmental Panel on Climate Change (IPCC) for its 5 th Assessment Report (AR5) (IPCC, 2013; IIASA, 2014b) combined with the results from a further climate modelling effort from a recent cross-comparison IAM 15 study: AMPERE 16 (IIASA, 2014a; Kriegler et al, 2015). The analysis of the scenario outputs from these two databases suggests that the median remaining carbon budget available in 2005 for a good chance for 1.5-2C warming (430-480 ppm scenarios), was 1,333 GtCO2.…”

Section: Compatibility Of the Capital Stock With Remaining Carbon Budmentioning

confidence: 99%

See 1 more Smart Citation

Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required to Meet the Paris Agreement

Pfeiffer¹,

Hepburn²,

Vogt-Schilb³

et al. 2018

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Section: Databases and Sourcesmentioning

confidence: 99%

Section: Compatibility Of the Capital Stock With Remaining Carbon Budmentioning

confidence: 99%

Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required to Meet the Paris Agreement

Pfeiffer¹,

Hepburn²,

Vogt-Schilb³

et al. 2018

View full text Add to dashboard Cite

show abstract

“…At the same time, the range of targets that can be achieved at a given cost, with a given level of mitigation risks, and with a given probability of success will be increasingly narrowed over time if emissions are only moderately reduced in the near term [16][17][18][19] . The window of options is rapidly closing [20][21][22] .…”

Section: The Origin -Not Only the Magnitude -Of Uncertainty Matters Fmentioning

confidence: 99%

“…Specifically, emission reductions at the low end of the 2050 range consistent with the 2 o C target (e.g., around 40%) create a commitment to climate policies with more rapid reductions -and larger negative emissions -beyond 2050. Defining the level of near-term action that is sufficient to achieve a given target depends on what is deemed realistic over the long-term 16 . Defining what is possible or realistic is not straightforward, as it depends less on technical or economic feasibility than on political and social acceptability 20 .…”

Section: A Long-term Climate Goal Implies a Limit On Cumulative Co2 Ementioning

confidence: 99%

Mapping the climate change challenge

et al. 2016

Self Cite

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The recent negotiations on climate change in Paris have left partly open the discussion on a long-term global goal, in the form of an upper limit to warming. Agreement on such a limit is a political decision that need to be informed by scientific knowledge through a mapping that systematically explores the consequences of different policy choices. Such a multi-disciplinary effort, based on the analysis of a set of scenarios, helped structure the IPCC AR5 Synthesis Report. This Perspective summarizes this approach and its results, reviews its strengths and limitations, and discusses how decision-makers can use these results in practice. It also identifies research needs to facilitate integrated analysis of the climate change problem and to help better inform policy-makers and the public.

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“…The Assessment of Climate Change Mitigation Pathways and Evaluation of the Robustness of Mitigation Cost Estimates (AMPERE) project, funded by the European Union, analyzed the effects of delayed international action to address climate change on the achievability of long-term climate policy goals (Kriegler et al, 2015a). Several studies in this project evaluated the effects of near-term policy choices on energy transitions throughout this century.…”

Section: Energy Technology Assessmentsmentioning

confidence: 99%

Representing spatial technology diffusion in an energy system optimization model

Leibowicz

Krey

Grübler

2016

Technological Forecasting and Social Change

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In this study, we develop a series of technology diffusion formulations that endogenously represent empirically observed spatial diffusion patterns. We implement these formulations in the energy system optimization model MESSAGE to assess their implications for the market penetration of low-carbon electricity generation technologies. In our formulations, capacity growth is constrained by a technology's knowledge stock, which is an accumulating and depreciating account of prior capacity additions. Diffusion from an innovative core to less technologically adept regions occurs through knowledge spillover effects (international spillover effect). Within a cluster of closely related technologies, knowledge gained through deployment of one technology spills over to other technologies in the cluster (technology spillover effect). Parameters are estimated using historical data on the expansion of extant electricity technologies. Based on our results, if diffusion in developing regions relies heavily on earlier deployment in advanced regions, projections for certain technologies (e.g., bioenergy with carbon capture and storage) should be tempered. Our model illustrates that it can be globally optimal when innovative economies deploy some low-carbon technologies more than is locally optimal as it helps to accelerate diffusion (and learning effects) elsewhere. More generally, we demonstrate that by implementing a more empirically consistent diffusion formulation in an energy system optimization model, the traditionally crude-or nonexistent-representation of technology diffusion in energy-climate policy models can be significantly improved. This methodological improvement has important implications for the market adoption of low-carbon technologies.

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Introduction to the AMPERE model intercomparison studies on the economics of climate stabilization

Cited by 22 publications

References 20 publications

Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required to Meet the Paris Agreement

Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required to Meet the Paris Agreement

Mapping the climate change challenge

Representing spatial technology diffusion in an energy system optimization model

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