Emissions projections for US utilities through 2050

Abstract

Abstract Decarbonization is an urgent global policy priority, with increasing movement towards zero-carbon targets in the United States and elsewhere. Given the joint decarbonization strategies of electrifying fossil fuel-based energy uses and decarbonizing the electricity supply, understanding how electricity emissions might change over time is of particular value in evaluating policy sequencing strategies. For example, is the electricity system likely to decarbonize quickly enough to motivate electrification even on relatively carbon-intensive systems? Although electricity sector decarbonization has been widely studied, limited research has focused on evaluating emissions factors at the utility level, which is where the impact of electrification strategies is operationalized. Given the existing fleet of electricity generators, ownership structures, and generator lifespans, committed emissions can be modeled at the utility level. Generator lifespans are modeled using capacity-weighted mean age-on-retirement for similar units over the last two decades, a simple empirical outcome variable reflecting the length of time the unit might reasonably be expected to operate. By also evaluating generators in wholesale power markets and designing scenarios for new-build generation, first-order annual average emissions factors can be projected forward on a multidecadal time scale at the utility level. This letter presents a new model of utility-specific annual average emissions projections (greenhouse gases and air pollutants) through 2050 for the United States, using a 2019 base year to define existing asset characteristics. Enabling the creation and evaluation of scenario-based projections for dynamic environmental intensity metrics in a decarbonizing electricity sector can inform life cycle and other environmental assessment studies that evaluate impact over time, in addition to highlighting particular opportunities and risks associated with the timing and location of long-lived capital investments as the fossil fuel electricity generator fleet turns over. Model results can also be used to contextualize utilities’ decarbonization commitments and timelines against their asset bases.