Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

Details Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

Dec 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008agufmgc31a0718h&link_type=abstract

American Geophysical Union, Fall Meeting 2008, abstract #GC31A-0718

Physics

1626 Global Climate Models (3337, 4928), 1630 Impacts Of Global Change (1225), 1699 General Or Miscellaneous, 6309 Decision Making Under Uncertainty, 6349 General Or Miscellaneous

Scientific paper

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

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