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Fundur fyrir alla félagsmenn: The Social Cost of Carbon Dioxide - Mitigating Global Warming Whilst Avoiding Economic Collapse

Miðvikudaginn, 5. júlí 2017 - 16:45
stofu N-131 í Öskju, Sturlugötu 7, 101 Reykjavík

Næstkomandi miðvikudag, 5. júlí mun dr. Christopher Kellett halda erindið "The Social Cost of Carbon Dioxide - Mitigating Global Warming Whilst Avoiding Economic Collapse".

Að venju er boðið upp á kaffi og vínarbrauð í upphafi fundar og erindið byrjar kl. 17:00. Allir velkomnir!

Abstract: Many governments and international finance organizations use a carbon price in cost-benefit analyses, emissions trading schemes, quantification of energy subsidies, and modelling the impact of climate change on financial assets. The most commonly used value in this context is the social cost of carbon dioxide (SC-CO2). Users of the social cost of carbon dioxide include the US, UK, German, and other governments, as well as organizations such as the World Bank, the International Monetary Fund, and Citigroup. Consequently, the social cost of carbon dioxide is a key factor driving worldwide investment decisions worth many trillions of dollars.

The social cost of carbon dioxide is derived using integrated assessment models that combine simplified models of the climate and the economy. One of three dominant models used in the calculation of the social cost of carbon dioxide is the Dynamic Integrated model of Climate and the Economy, or DICE. DICE contains approximately 70 parameters as well as several "exogenous" driving signals such as population growth and a
measure of technological progress. Given the quantity of finance tied up in a figure derived from this simple highly parameterized model, understanding uncertainty in the model and capturing its effects on the social cost of carbon dioxide is of paramount importance. Indeed, in late January this year the US National Academies of Sciences, Engineering, and Medicine released a report calling for discussion on "the various types of uncertainty in the overall SC-CO2 estimation approach" and addressing "how different models used in SC-CO2 estimation capture uncertainty."

This talk, which focuses on the DICE model, essentially consists of two parts. In Part One, I will describe the social cost of carbon dioxide and the DICE model at a high-level, and will present some interesting preliminary results relating to uncertainty and the impact of realistic constraints on emissions mitigation efforts. Part one will be accessible to a broad audience and will not require any specific
technical background knowledge. In Part Two, I will provide a more
detailed description of the DICE model, describe precisely how the
social cost of carbon dioxide is calculated, and indicate ongoing
developments aimed at improving estimates of the social cost of carbon dioxide.

Biography: Christopher M. Kellett received the Bachelor of Science in Electrical Engineering and Mathematics from the University of
California, Riverside in 1997 and the Master of Science and Doctor of Philosophy in Electrical and Computer Engineering from the University of California, Santa Barbara in 2000 and 2002, respectively. He subsequently held research positions with the Centre Automatique et Systemes at Ecole des Mines de Paris (France), the Department of Electrical and Electronic Engineering at the University of Melbourne (Australia), and the Hamilton Institute at the National University of Ireland, Maynooth. Since 2006, Chris has been with the School of Electrical Engineering and Computing at the University of Newcastle, Australia, where he is currently an Associate Professor.

Chris is an Associate Editor for IEEE Transactions on Automatic Control, IEEE CSS Letters, the European Journal on Control, and Mathematics of Control, Signals and Systems, as well as a member of the IEEE Control Systems Society Conference Editorial Board. He has been the recipient of an Australian Research Council Future Fellowship (2011-2015), an Alexander von Humboldt Research Fellowship (2012-2013), and the 2012 IET Control Theory and its Applications Premium Award. Chris' research interests are broadly in the area of systems and control, with specific emphases on stability and robustness properties for nonlinear systems,
high speed model predictive control, applications in electricity
distribution networks, and applications in social systems such as carbon pricing and opinion dynamics.