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- ItemImplications of climate change mitigation strategies on international bioenergy trade(Dordrecht [u.a.] : Springer Science + Business Media B.V, 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).
- ItemThe shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500(Katlenburg-Lindau : Copernicus, 2020) Meinshausen, Malte; Nicholls, Zebedee R. J.; Lewis, Jared; Gidden, Matthew J.; Vogel, Elisabeth; Freund, Mandy; Beyerle, Urs; Gessner, Claudia; Nauels, Alexander; Bauer, Nico; Canadell, Josep G.; Daniel, John S.; John, Andrew; Krummel, Paul B.; Luderer, Gunnar; Meinshausen, Nicolai; Montzka, Stephen A.; Rayner, Peter J.; Reimann, Stefan; Smith, Steven J.; van den Berg, Marten; Velders, Guus J. M.; Vollmer, Martin K.; Wang, Ray H. J.Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other.
- ItemSpatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China([London] : Nature Publishing Group UK, 2021) Xing, Xiaofan; Wang, Rong; Bauer, Nico; Ciais, Philippe; Cao, Junji; Chen, Jianmin; Tang, Xu; Wang, Lin; Yang, Xin; Boucher, Olivier; Goll, Daniel; Peñuelas, Josep; Janssens, Ivan A.; Balkanski, Yves; Clark, James; Ma, Jianmin; Pan, Bo; Zhang, Shicheng; Ye, Xingnan; Wang, Yutao; Li, Qing; Luo, Gang; Shen, Guofeng; Li, Wei; Yang, Yechen; Xu, SiqingAs China ramped-up coal power capacities rapidly while CO2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China.
- ItemAlternative carbon price trajectories can avoid excessive carbon removal([London] : Nature Publishing Group UK, 2021) Strefler, Jessica; Kriegler, Elmar; Bauer, Nico; Luderer, Gunnar; Pietzcker, Robert C.; Giannousakis, Anastasis; Edenhofer, OttmarThe large majority of climate change mitigation scenarios that hold warming below 2 °C show high deployment of carbon dioxide removal (CDR), resulting in a peak-and-decline behavior in global temperature. This is driven by the assumption of an exponentially increasing carbon price trajectory which is perceived to be economically optimal for meeting a carbon budget. However, this optimality relies on the assumption that a finite carbon budget associated with a temperature target is filled up steadily over time. The availability of net carbon removals invalidates this assumption and therefore a different carbon price trajectory should be chosen. We show how the optimal carbon price path for remaining well below 2 °C limits CDR demand and analyze requirements for constructing alternatives, which may be easier to implement in reality. We show that warming can be held at well below 2 °C at much lower long-term economic effort and lower CDR deployment and therefore lower risks if carbon prices are high enough in the beginning to ensure target compliance, but increase at a lower rate after carbon neutrality has been reached.
- ItemCombining ambitious climate policies with efforts to eradicate poverty([London] : Nature Publishing Group UK, 2021) Soergel, Bjoern; Kriegler, Elmar; Bodirsky, Benjamin Leon; Bauer, Nico; Leimbach, Marian; Popp, AlexanderClimate change threatens to undermine efforts to eradicate extreme poverty. However, climate policies could impose a financial burden on the global poor through increased energy and food prices. Here, we project poverty rates until 2050 and assess how they are influenced by mitigation policies consistent with the 1.5 °C target. A continuation of historical trends will leave 350 million people globally in extreme poverty by 2030. Without progressive redistribution, climate policies would push an additional 50 million people into poverty. However, redistributing the national carbon pricing revenues domestically as an equal-per-capita climate dividend compensates this policy side effect, even leading to a small net reduction of the global poverty headcount (−6 million). An additional international climate finance scheme enables a substantial poverty reduction globally and also in Sub-Saharan Africa. Combining national redistribution with international climate finance thus provides an important entry point to climate policy in developing countries.
- ItemCarbon dioxide removal technologies are not born equal(Bristol : IOP Publ., 2021-7-1) Strefler, Jessica; Bauer, Nico; Humpenöder, Florian; Klein, David; Popp, Alexander; Kriegler, ElmarTechnologies for carbon dioxide removal (CDR) from the atmosphere have been recognized as an important part of limiting warming to well below 2 °C called for in the Paris Agreement. However, many scenarios so far rely on bioenergy in combination with carbon capture and storage as the only CDR technology. Various other options have been proposed, but have scarcely been taken up in an integrated assessment of mitigation pathways. In this study we analyze a comprehensive portfolio of CDR options in terms of their regional and temporal deployment patterns in climate change mitigation pathways and the resulting challenges. We show that any CDR option with sufficient potential can reduce the economic costs of achieving the 1.5 °C target substantially without increasing the temperature overshoot. CDR helps to reduce net CO2 emissions faster and achieve carbon neutrality earlier. The regional distribution of CDR deployment in cost-effective mitigation pathways depends on which options are available. If only enhanced weathering of rocks on croplands or re- and afforestation are available, Latin America and Asia cover nearly all of global CDR deployment. Besides fairness and sustainability concerns, such a regional concentration would require large international transfers and thus strong international institutions. In our study, the full portfolio scenario is the most balanced from a regional perspective. This indicates that different CDR options should be developed such that all regions can contribute according to their regional potentials.
- ItemBio-energy and CO2 emission reductions: an integrated land-use and energy sector perspective(Dordrecht [u.a.] : Springer Science + Business Media B.V, 2020) Bauer, Nico; Klein, David; Humpenöder, Florian; Kriegler, Elmar; Luderer, Gunnar; Popp, Alexander; Strefler, JessicaBiomass feedstocks can be used to substitute fossil fuels and effectively remove carbon from the atmosphere to offset residual CO2 emissions from fossil fuel combustion and other sectors. Both features make biomass valuable for climate change mitigation; therefore, CO2 emission mitigation leads to complex and dynamic interactions between the energy and the land-use sector via emission pricing policies and bioenergy markets. Projected bioenergy deployment depends on climate target stringency as well as assumptions about context variables such as technology development, energy and land markets as well as policies. This study investigates the intra- and intersectorial effects on physical quantities and prices by coupling models of the energy (REMIND) and land-use sector (MAgPIE) using an iterative soft-link approach. The model framework is used to investigate variations of a broad set of context variables, including the harmonized variations on bioenergy technologies of the 33rd model comparison study of the Stanford Energy Modeling Forum (EMF-33) on climate change mitigation and large scale bioenergy deployment. Results indicate that CO2 emission mitigation triggers strong decline of fossil fuel use and rapid growth of bioenergy deployment around midcentury (~ 150 EJ/year) reaching saturation towards end-of-century. Varying context variables leads to diverse changes on mid-century bioenergy markets and carbon pricing. For example, reducing the ability to exploit the carbon value of bioenergy increases bioenergy use to substitute fossil fuels, whereas limitations on bioenergy supply shift bioenergy use to conversion alternatives featuring higher carbon capture rates. Radical variations, like fully excluding all technologies that combine bioenergy use with carbon removal, lead to substantial intersectorial effects by increasing bioenergy demand and increased economic pressure on both sectors. More gradual variations like selective exclusion of advanced bioliquid technologies in the energy sector or changes in diets mostly lead to substantial intrasectorial reallocation effects. The results deepen our understanding of the land-energy nexus, and we discuss the importance of carefully choosing variations in sensitivity analyses to provide a balanced assessment. © 2020, The Author(s).
- ItemBioenergy technologies in long-run climate change mitigation: results from the EMF-33 study(Dordrecht [u.a.] : Springer Science + Business Media B.V, 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).
- ItemREMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits(Katlenburg-Lindau : Copernicus, 2021) Baumstark, Lavinia; Bauer, Nico; Benke, Falk; Bertram, Christoph; Bi, Stephen; Gong, Chen Chris; Dietrich, Jan Philipp; Dirnaichner, Alois; Giannousakis, Anastasis; Hilaire, Jerome; Klein, David; Koch, Johannes; Leimbach, Marian; Levesque, Antoine; Madeddu, Silvia; Malik, Aman; Merfort, Anne; Merfort, Leon; Odenweller, Adrian; Pehl, Michaja; Pietzcker, Robert C.; Piontek, Franziska; Rauner, Sebastian; Rodrigues, Renato; Rottoli, Marianna; Schreyer, Felix; Schultes, Anselm; Soergel, Bjoern; Soergel, Dominika; Strefler, Jessica; Ueckerdt, Falko; Kriegler, Elmar; Luderer, GunnarThis paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity.