Energy technologies emitting differing proportions of methane (CH 4 ) and carbon dioxide (CO 2 ) vary significantly in their relative climate impacts over time, due to the distinct atmospheric lifetimes and radiative efficiencies of the two gases. Standard technology comparisons using the global warming potential (GWP) with a fixed time horizon do not account for the timing of emissions in relation to climate policy goals. Here we develop a portfolio optimization model that incorporates changes in technology impacts based on the temporal proximity of emissions to a radiative forcing (RF) stabilization target. An optimal portfolio, maximizing allowed energy consumption while meeting the RF target, is obtained by year-wise minimization of the marginal RF impact in an intended stabilization year. The optimal portfolio calls for using certain higher-CH 4 -emitting technologies prior to an optimal switching year, followed by CH 4 -light technologies as the stabilization year approaches. We apply the model to evaluate transportation technology pairs and find that accounting for dynamic emissions impacts, in place of using the static GWP, can result in CH 4 mitigation timelines and technology transitions that allow for significantly greater energy consumption while meeting a climate policy target. The results can inform the forward-looking evaluation of energy technologies by engineers, private investors, and policy makers.

The carbon intensity (CI) of travel is commonly used to evaluate transportation technologies. However, when travel demand is sensitive to price, CI alone does not fully capture the emissions impact of a technology. Here, we develop a metric to account for both CI and the demand response to price (DR) in technology evaluation, for use by distributed decision-makers in industry and government, who are becoming increasingly involved in climate change mitigation as the costs of lowercarbon technologies fall. We apply this adjusted carbon intensity (ACI) to evaluate ethanol-fueled, hybrid, and battery electric vehicles individually and against policy targets. We find that all of these technologies can be used to help meet a 2030 greenhouse gas emissions reduction target of up to 40% below 2005 levels and that decarbonized battery electric vehicles can meet a 2050 target of 80%, even when evaluated using the ACI instead of CI. Using the CI alone could lead to a substantial overshoot of emissions targets especially in markets with significant DR, including in rapidly growing economies with latent travel demand. The ACI can be used to adjust decarbonization transition plans to mitigate this risk. For example, in examining several transportation technologies, we find that accelerating low-carbon technology transitions by roughly 5−10 years would mitigate the risk associated with DR estimates. One particularly robust strategy is to remove carbon from fuels through faster decarbonization of electricity and vehicle electrification.

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