Dynamic environmental impacts of technologies

The impacts of technologies depend on various factors, including the background state of the environment. Here we explore how the intensity and decay of impacts influences the relative attractiveness of technologies. We focus on comparing the impacts of various greenhouse gases, and develop new models to evaluate technologies.

Papers in progress focus on the development of new metrics to compare the impacts of greenhouse gases and technologies to one another. We are also investigating how technology portfolios can optimally adapt to a changing background environmental state.

New metric development: We are working on revised CO2-equivalency metrics that take into account how close in time a technology is used to when critical climate thresholds are expected to be reached. This work focuses on comparing methane and carbon dioxide emissions across various transportation fuels and electricity generation options (Figure 1).

  • Edwards MR, Trancik JE, Climate impacts of energy technologies depend on emissions timing, Nature Climate Change, 2014, Vol. 4, pp. 347-352.

Figure 1. Assessments of the climate benefits of alternative fuels depend on the time horizon over which impacts are evaluated, for example 100 years (A) or 20 years (B). Alternative fuels emit multiple gases during their life cycle – including methane, which has a high initial climate impact but relatively short atmospheric lifetime (C).  As a result, the impacts of methane-heavy fuels like natural gas are initially high but decay more quickly than those of methane-light fuels like gasoline (D).

Portfolio optimization: In this work we formulate dynamic technology choice as a simplified forward-looking multi-period portfolio optimization problem, maximizing energy consumption over a planning horizon in the presence of a policy constraint. Optimal portfolios require switching from relatively methane-heavy technologies to methane-light ones as the policy target approaches. The benefit of this method is numerically quantified using various transportation technology pairs (Figure 2). The optimal results are compared to choices relying on the standard GWP-based method which does not allow for dynamic technology selection (Figure 2C-D). .

  • Roy M, Edwards MR, Trancik JE, Methane mitigation timelines to inform energy technology evaluation, Environmental Research Letters, 2015, Vol. 10, 114024


Figure 2. Greenhouse gas emission intensities of alternative transportation technologies and the benefit of using dynamic portfolio choice method in the presence of a policy constraint. Emission intensities of carbon dioxide (A), methane and nitrous oxide (B). Energy consumption allowed using individual technologies, their optimal switching portfolios and the optimal GWP-based portfolio (C). Gain in energy consumption using the optimal switching portfolio and GWP100 over the methane-light (D) and methane-heavy (E) technology in each pair.