This study attempts a numerical simulation of potential CCS (carbon dioxide capture and storage) use by using a modified version of the DICE (Dynamic Integrated model on Climate and Economy) model (Nordhaus, 1994; Nordhaus and Boyer, 2000). In DICE, CO2 emissions are controlled to the extent in which a hypothetical optimal carbon tax justifies CO2 reduction by firms: in our analysis, CCS is used when the optimal tax level is higher than the price of CCS. The analysis assesses the economic optimality of CCS use with a range of different assumptions. The simulation particularly focuses on the difference of results originating from two sets of general assumptions on climate change modeling, reflecting the current debate on the economics of climate change (see for example, Heal, 2008): (1) Parameterization of the standard DICE; (2) Alternative assumptions whose hints are drawn from Stern (2007). In the standard DICE cases, the model calculation shows that at the price level of $25/tCO2 ($92/tC), CCS is introduced around in the middle of the twenty-first century. With the alternative assumptions (e.g., near-zero discount rate), CCS begins to be utilized massively earlier in the century. The two sets of results lead to contrasting policy implications on the future CCS use; this is particularly problematic in the CCS context since its benefits are not always clear-cut (e.g., limitedness of secondary benefits besides CO2 reduction, uncertainties about the validity of technology itself). Settlement of the current intellectual debate on the economics of climate change would greatly benefit the debate on the role of CCS as well.
Carbon capture and storage (CCS) climate change energy integrated assessment models dynamic optimization