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Center for Global Change Science

Research and Teaching Output of the MIT Community

Center for Global Change Science


The Center for Global Change Science (CGCS) seeks to better understand the fundamental processes and mechanisms controlling the global environment. The interdisciplinary Center, founded in January, 1990, utilizes theory and observations of oceanic, atmospheric, and terrestrial systems, to improve the ability to accurately predict global environmental change. Two major activities of the CGCS are the Climate Modeling Initiative, and the Joint Program on the Science and Policy of Global Change. Visit the CGCS website for more information.

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Recent Submissions

  • Zhang, Xiaohan; Qi, Tianyu; Zhang, Xiliang (2015-12-28)
    Carbon capture and storage (CCS) from coal combustion is widely viewed as an important approach for China’s carbon dioxide (CO2) emission mitigation, but the pace of its development is still fairly slow. In addition to the ...
  • Lanz, B.; Dietz, S.; Swanson, T. (MIT Joint Program on the Science and Policy of Global Change, 2015-10)
    We structurally estimate a two-sector Schumpeterian growth model with endogenous population and finite land reserves to study the long run evolution of global population, technological progress and the demand for food. The ...
  • Paltsev, S.; Chen, Y.-H.H.; Karplus, V.; Kishimoto, P.; Reilly, J. (MIT Joint Program on the Science and Policy of Global Change, 2015-05)
    CO2 emissions mandates for new light-duty passenger vehicles have recently been adopted in the European Union (EU), which require steady reductions to 95 g CO2/km in 2021. Using a computable general equilibrium (CGE) model, ...
  • Strzepek, K.; Fant, C.; Gebretsadik, Y.; Lickley, M.; Boehlert, B.; Chapra, S.; Adams, E.; Strzepek, A.; Schlosser, C.A. (MIT Joint Program on the Science and Policy of Global Change, 2015-05)
    We develop and test a physically based semi-Lagrangian water body temperature model to apply climatological data and thermal pollution from river-based power plants to historical river flow data in order to better understand ...
  • Zhang, Da; Karplus, V.; Rausch, S. (2015-10-20)
    Top-down energy-economic modeling approaches often use deliberately simple techniques to represent heterogeneous resource inputs to production. We show that for some policies, such as feed-in tariffs (FIT) for renewable ...