2020, Daioglou, Vassilis, Muratori, Matteo, Lamers, Patrick, Fujimori, Shinichiro, Kitous, Alban, Köberle, Alexandre C., Bauer, Nico, Junginger, Martin, Kato, Etsushi, Leblanc, Florian, Mima, Silvana, Wise, Marshal, van Vuuren, Detlef P.

Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade. © 2020, The Author(s).

2018, Krey, Volker, Guo, Fei, Kolp, Peter, Zhou, Wenji, Schaeffer, Roberto, Awasthy, Aayushi, Bertram, Christoph, de Boer, Harmen-Sytze, Fragkos, Panagiotis, Fujimori, Shinichiro, He, Chenmin, Iyer, Gokul, Keramidas, Kimon, Köberle, Alexandre C., Oshiro, Ken, Reis, Lara Aleluia, Shoai-Tehrani, Bianka, Vishwanathan, Saritha, Capros, Pantelis, Drouet, Laurent, Edmonds, James E., Garg, Amit, Gernaat, David E.H.J., Jiang, Kejun, Kannavou, Maria, Kitous, Alban, Kriegler, Elmar, Luderer, Gunnar, Mathur, Ritu, Muratori, Matteo, Sano, Fuminori, van Vuuren, Detlef P.

Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. © 2019 The Authors

2014, Kriegler, Elmar, Riahi, Keywan, Bauer, Nico, Schwanitz, Valeria Jana, Petermann, Nils, Bosetti, Valentina, Marcucci, Adriana, Otto, Sander, Paroussos, Leonidas, Rao, Shilpa, Currás, Tabaré Arroyo, Ashina, Shuichi, Bollen, Johannes, Eom, Jiyong, Hamdi-Cherif, Meriem, Longden, Thomas, Kitous, Alban, Méjean, Aurélie, Sano, Fuminori, Schaeffer, Michiel, Wada, Kenichi, Capros, Pantelis, van Vuuren, Detlef P., Edenhofer, Ottmar

This study explores a situation of staged accession to a global climate policy regime from the current situation of regionally fragmented and moderate climate action. The analysis is based on scenarios in which a front runner coalition – the EU or the EU and China – embarks on immediate ambitious climate action while the rest of the world makes a transition to a global climate regime between 2030 and 2050. We assume that the ensuing regime involves strong mitigation efforts but does not require late joiners to compensate for their initially higher emissions. Thus, climate targets are relaxed, and although staged accession can achieve significant reductions of global warming, the resulting climate outcome is unlikely to be consistent with the goal of limiting global warming to 2 degrees. The addition of China to the front runner coalition can reduce pre-2050 excess emissions by 20–30%, increasing the likelihood of staying below 2 degrees. Not accounting for potential co-benefits, the cost of front runner action is found to be lower for the EU than for China. Regions that delay their accession to the climate regime face a trade-off between reduced short term costs and higher transitional requirements due to larger carbon lock-ins and more rapidly increasing carbon prices during the accession period.

2018, Vrontisi, Zoi, Luderer, Gunnar, Saveyn, Bert, Keramidas, Kimon, Lara, Aleluia Reis, Baumstark, Lavinia, Bertram, Christoph, de Boer, Harmen Sytze, Drouet, Laurent, Fragkiadakis, Kostas, Fricko, Oliver, Fujimori, Shinichiro, Guivarch, Celine, Kitous, Alban, Krey, Volker, Kriegler, Elmar, Broin, Eoin Ó., Paroussos, Leonidas, van Vuuren, Detlef

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

2013, Bauer, Nico, Bosetti, Valentina, Hamdi-Cherif, Meriem, Kitous, Alban, McCollum, David, Méjean, Aurélie, Rao, Shilpa, Turton, Hal, Paroussos, Leonidas, Ashina, Shuichi, Calvin, Katherine, Wada, Kenichi, van Vuuren, Detlef

This paper explores a multi-model scenario ensemble to assess the impacts of idealized and non-idealized climate change stabilization policies on fossil fuel markets. Under idealized conditions climate policies significantly reduce coal use in the short- and long-term. Reductions in oil and gas use are much smaller, particularly until 2030, but revenues decrease much more because oil and gas prices are higher than coal prices. A first deviation from optimal transition pathways is delayed action that relaxes global emission targets until 2030 in accordance with the Copenhagen pledges. Fossil fuel markets revert back to the no-policy case: though coal use increases strongest, revenue gains are higher for oil and gas. To balance the carbon budget over the 21st century, the long-term reallocation of fossil fuels is significantly larger—twice and more—than the short-term distortion. This amplifying effect results from coal lock-in and inter-fuel substitution effects to balance the full-century carbon budget. The second deviation from the optimal transition pathway relaxes the global participation assumption. The result here is less clear-cut across models, as we find carbon leakage effects ranging from positive to negative because trade and substitution patterns of coal, oil, and gas differ across models. In summary, distortions of fossil fuel markets resulting from relaxed short-term global emission targets are more important and less uncertain than the issue of carbon leakage from early mover action.

2020, Daioglou, Vassilis, Rose, Steven K., Bauer, Nico, Kitous, Alban, Muratori, Matteo, Sano, Fuminori, Fujimori, Shinichiro, Gidden, Matthew J., Kato, Etsushi, Keramidas, Kimon, Klein, David, Leblanc, Florian, Tsutsui, Junichi, Wise, Marshal, van Vuuren, Detlef P.

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services. © 2020, The Author(s).

2014, Kriegler, Elmar, Petermann, Nils, Krey, Volker, Schwanitz, Valeria Jana, Luderer, Gunnar, Ashina, Shuichi, Bosetti, Valentina, Eom, Jiyong, Kitous, Alban, Méjean, Aurélie, Paroussos, Leonidas, Sano, Fuminori, Turton, Hal, Wilson, Charlie, Van Vuuren, Detlef P.

Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results.