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IAMC

Project

EEIST Project for the transition to a low carbon economy

The EEIST Project stands for The Economics of Energy Innovation and Systems Transition. It is a University of Exeter led project which develops cutting edge complexity based modelling solutions to support government decision making around low carbon innovation and technological change, and aims to facilitate a rapid transition to a

The EEIST Project stands for The Economics of Energy Innovation and Systems Transition. It is a University of Exeter led project which develops cutting edge complexity based modelling solutions to support government decision making around low carbon innovation and technological change, and aims to facilitate a rapid transition to a low carbon economy.

The aim of EEIST is to use cutting edge advanced methods, which exist in the sciences of complexity and economics, to support government decision making around facilitating a rapid low-carbon transition. By engaging with policy-makers in large emerging economies, this project will contribute to the economic development of emerging nations and support sustainable development globally.

The programme brings together world-leading expertise in complex systems modelling, economics and climate and environmental policy to better understand, and contribute to informing with rigorous science climate policy initiatives in China, Brazil, India, the UK and EU.

More projects

POLIZERO project final report

POLIZERO was funded by the Energy-Economy-Society research programme of the Swiss Federal Office of Energy. Led by the Energy Economics Group of the Laboraotry for Energy Systems Analysis at the Paul Scherrer Institute PSI and the Technoeconomics of energy systems laboratory of the University of Piraeus Research Center, it combined stakeholder input, energy modelling

Multiple pathways towards sustainable development goals and climate targets

The study presents three different sustainable development pathways, all of which avoid dangerous climate change and enable substantial progress towards the UN Sustainable Development Goals (SDGs). The scenarios were quantified by four different modelling teams participating in the SHAPE project, comprising two “full-system” integrated assessment models (REMIND-MAgPIE and IMAGE) and