Optimal reductions in CO2 emissions.

Current optimizing climate-economy models use CO2 uptake functions that greatly underestimate both peak atmospheric CO2 concentrations and the time horizon of elevated CO2. As a result these models underestimate potential global warming damages. Here, a more realistic, but practical, carbon cycle parameterization is developed that can be incorporated within an optimizing climate-economy model framework. This method is utilized in conjunction with the DICE model (Nordhaus, 1994) to estimate optimal reductions in CO2 emissions. The results are shown to be extremely sensitive to the pore rate of time preference, rho. For rho=3% (Nordhaus' preferred value), our model predicts an optimal CO2 emission reduction of 13% by the year 2045, as compared to 11% in the original DICE model. But, for rho=0% the optimal emissions reduction rises to 79% in the year 2045 and to 97% by the year 2200. We argue that energy policy should be guided by the rho=0% results for both economic and ethical reasons. A steady-state analysis performed using the DICE model supports the argument that large fractional reductions in CO2 emissions should be undertaken.