Future costs of low-carbon technology options are a key factor in determining the challenges of reducing greenhouse gases and therefore the nature of lower emissions scenarios such as the RCP 2.6 and RCP 4.5 used in the CMIP process. To explore the implications of uncertainty about future technology costs researchers, including a Department of Energy scientist working at Pacific Northwest National Laboratory’s Joint Global Change Research Institute, acquired the output of multiple expert elicitation surveys on the future cost of key low-carbon technologies and used it as input for three integrated assessment models. They found that the future emission trajectory is most responsive to the capital cost of nuclear power plants. Under the climate-constrained scenarios they found that the cost of biofuel processing also has a large impact, especially when coupled with carbon capture and storage to produce negative emissions.

Their large set of simulations using the Global Change Assessment Model (GCAM), Market Allocation Model of the U.S. energy system (MARKAL_US) and the World Induced Technical Change Hybrid model (WITCH) enabled them to assess the implications of technology performance probability distributions over key model outputs. They were able to detect what sources of technology uncertainty are more influential, how this differs across models, and whether and how results are affected by the time horizon, the metric considered, or the stringency of the climate mitigation. This effort is important for improving understanding of uncertainty in emissions scenarios and improving the usability of models to inform technology research and development. The research is also important for model evaluation, to better understand what is driving the results of the complex models, and as a consequence, focus modeling and calibration efforts on a more crucial area of model responses.