14 November 2016 - 16 November 2016
Atlantic Room, Blue Zone,
The twenty-second session of the annual climate negotiation conference COP 22, by the United Nations Framework Convention on Climate Change (UNFCCC) will be held in Bab Ighli, Marrakech, Morocco from 7-18 November 2016.
Michael Obersteiner and Florian Kraxner will participate in the three-day Low-Emissions Solutions Conference (LESC), aimed at problem solving, brainstorming, and global co-creation to inform nations about the latest technology developments. It will bring together technical experts and world-leading scientists, engineers and innovators from business, academia, and cities, to share knowledge, exchange information, identify bottlenecks, discuss best practices, and prioritize future research in order to set common technological trajectories for a decarbonized economy as well as the transformations necessary in each sector.
As part of the "Mitigation and Climate Smart Agriculture" session on the 16th November, Michael Obersteiner will give a presentation on the modeling perspective of "Deep climate mitigation through sustainable agriculture". The session will aim at highlighting the important role of agriculture in reducing GHG emissions and the role climate smart agriculture solutions can play in implementing INDCs. Furthermore, share the best practices in building resilience for smallholder farmers and introducing approaches to avoid deforestation. Finally, understanding how the contribution of CSA to reducing GHG emissions can be facilitated through enhanced monitoring, reporting and verifying tools.
Text adapted from official COP22 and LESC website
Last edited: 14 November 2016
Di Fulvio F, Forsell N, Korosuo A, Obersteiner M, & Hellweg S (2019). Spatially explicit LCA analysis of biodiversity losses due to different bioenergy policies in the European Union. Science of the Total Environment 651: 1505-1516. DOI:10.1016/j.scitotenv.2018.08.419.
Folberth C, Baklanov A, Balkovic J, Skalsky R, Khabarov N, & Obersteiner M (2019). Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning. Agricultural and Forest Meteorology 264: 1-15. DOI:10.1016/j.agrformet.2018.09.021.
Mesfun S, Leduc S, Patrizio P, Wetterlund E, Mendoza Ponce A, Lammens T, Staritsky I, Elbersen B, et al. (2018). Spatio-temporal assessment of integrating intermittent electricity in the EU and Western Balkans power sector under ambitious CO2 emission policies. Energy 164: 676-693. DOI:10.1016/j.energy.2018.09.034.
International Institute for Applied Systems Analysis (IIASA)
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