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Poster
in
Workshop: Tackling Climate Change with Machine Learning

Critical misalignments between climate action and sustainable development goals revealed

Francesca Larosa · Sergio Hoyas · Fermin Mallor Franco · J. Alberto Conejero · Javier GarcĂ­a-Martinez · Francesco Fuso Nerini · Ricardo Vinuesa


Abstract:

A mere 12 percent of the Sustainable Development Goals (SDGs) is currently on track to meet the 2030 deadline in a world under climate change. Since their launch in 2015, the 2030 Agenda for Sustainable Development and the Paris Agreement have suffered persistent mismatches, which limit the potential for mutual gains. We use Artificial Intelligence (AI) to assess the degree and type of alignment between the Nationally Determined Contributions (NDCs) and the SDGs. While high income countries tackle the energy-infrastructure-community nexus in term of opportunity, lower income countries make climate impacts more explicit and center their trade-offs around the water-energy-food nexus. These two approaches mark different development trajectories and have non-negligible implications on international financial flow architecture and climate governance.

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