Penn State -Cornell Integrated Assessment Model
AbstractIn the past decade dynamic geoeconomic climate modelling has been successful in integrating basic relations in macroeconomic growth and climatology. Now physical scientists and economists at The Penn State University and Cornell University propose to link transient annual climate modelling with the greenhouse gas emissions resulting from a macroeconomic-energy model. In climatological terminology, this is a 3-dimensional General Circulation Model with detailed time and geographic data at the 4.5 degree latitude by 7.5 degree longitude level. The integrated model analysis may proceed up to periods with 10-15 times today's CO2 equivalent concentration level. Feedback effects include space heating and cooling energy demand, and natural ecosystem relationships such as CO2 fertilization and terrestrial CH4 release. In the macroeconomic submodel, an augmented Hotelling analysis incorporates long-term depletion with short-term rising market equilibrium values which reflect growing populations and income. Energy demand is explicitly represented by demand functions, as is the possibility of renewable energy, conservation, or nuclear substitution for fossil fuel, as well as the substitution of coal-based energy services for those now provided by petroleum and natural gas. On a detailed regionally disaggregated level, climate change interactions would be studied for agriculture, morbidity and mortality, sea level rise, and income levels. The Framework Convention on Climate Change charges policy makers to find stable greenhouse gas concentrations "at a level that would prevent dangerous anthropogenic interference with the climate system." The Penn State-Cornell Integrated Assessment Model would assist in defining those concentration levels, and the national and international policy pathways such as marketable permits or taxation.
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Bibliographic InfoPaper provided by Cornell University, Department of Applied Economics and Management in its series Working Papers with number 127929.
Date of creation: Dec 1996
Date of revision:
Research Methods/ Statistical Methods;
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