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    Deep decarbonisation of buildings energy services through demand and supply transformations in a 1.5°C scenario
    (Bristol : IOP Publ., 2021-5-12) Levesque, Antoine; Pietzcker, Robert C.; Baumstark, Lavinia; Luderer, Gunnar
    Buildings energy consumption is one of the most important contributors to greenhouse gas (GHG) emissions worldwide, responsible for 23% of energy-related CO2 emissions. Decarbonising the energy demand of buildings will require two types of strategies: first, an overall reduction in energy demand, which could, to some extent, be achieved at negative costs; and second through a reduction of the carbon content of energy via fuel switching and supply-side decarbonisation. This study assesses the contributions of each of these strategies for the decarbonisation of the buildings sector in line with a 1.5°C global warming. We show that in a 1.5°C scenario combining mitigation policies and a reduction of market failures in efficiency markets, 81% of the reductions in buildings emissions are achieved through the reduction of the carbon content of energy, while the remaining 19% are due to efficiency improvements which reduce energy demand by 31%. Without supply-side decarbonisation, efficiency improvements almost entirely suppress the doubling of emissions that would otherwise be expected, but fail to induce an absolute decline in emissions. Our modelling and scenarios show the impact of both climate change mitigation policies and of the alleviation of market failures pervading through energy efficiency markets. The results show that the reduction of the carbon content of energy through fuel switching and supply-side decarbonisation is of paramount importance for the decarbonisation of buildings.
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    Reducing greenhouse gas emissions in agriculture without compromising food security?
    (Bristol : IOP Publishing, 2017) Frank, Stefan; Havlík, Petr; Soussana, Jean-François; Levesque, Antoine; Wollenberg, Eva; Kleinwechter, Ulrich; Fricko, Oliver; Gusti, Mykola; Herrero, Mario; Smith, Pete; Hasegawa, Tomoko; Kraxner, Florian; Obersteiner, Michael
    To keep global warming possibly below 1.5 °C and mitigate adverse effects of climate change, agriculture, like all other sectors, will have to contribute to efforts in achieving net negative emissions by the end of the century. Cost-efficient distribution of mitigation across regions and economic sectors is typically calculated using a global uniform carbon price in climate stabilization scenarios. However, in reality such a carbon price would substantially affect food availability. Here, we assess the implications of climate change mitigation in the land use sector for agricultural production and food security using an integrated partial equilibrium modelling framework and explore ways of relaxing the competition between mitigation in agriculture and food availability. Using a scenario that limits global warming cost-efficiently across sectors to 1.5 °C, results indicate global food calorie losses ranging from 110–285 kcal per capita per day in 2050 depending on the applied demand elasticities. This could translate into a rise in undernourishment of 80–300 million people in 2050. Less ambitious greenhouse gas (GHG) mitigation in the land use sector reduces the associated food security impact significantly, however the 1.5 °C target would not be achieved without additional reductions outside the land use sector. Efficiency of GHG mitigation will also depend on the level of participation globally. Our results show that if non-Annex-I countries decide not to contribute to mitigation action while other parties pursue their mitigation efforts to reach the global climate target, food security impacts in these non-Annex-I countries will be higher than if they participate in a global agreement, as inefficient mitigation increases agricultural production costs and therefore food prices. Land-rich countries with a high proportion of emissions from land use change, such as Brazil, could reduce emissions with only a marginal effect on food availability. In contrast, agricultural mitigation in high population (density) countries, such as China and India, would lead to substantial food calorie loss without a major contribution to global GHG mitigation. Increasing soil carbon sequestration on agricultural land would allow reducing the implied calorie loss by 65% when sticking to the initially estimated land use mitigation requirements, thereby limiting the impact on undernourishment to 20–75 million people, and storing significant amounts of carbon in soils.
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    REMIND2.1: 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, Gunnar
    This 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.