Why marginal CO₂emissions are not decreasing for US electricity: Estimates and implications for climate policy

Abstract

Marginal emissions of CO2 from the electricity sector are critical for evaluating climate policies that rely on shifts in electricity demand or supply. This paper provides estimates of marginal CO2 emissions from US electricity generation using the most recently available and comprehensive data. The estimates vary by region, hour of the day, and year to year over the last decade. We identify an important and somewhat counterintuitive finding: While average emissions have decreased substantially over the last decade (28% nationally), marginal emissions have increased (7% nationally). We show that underlying these trends is primarily a shift toward greater reliance on coal to satisfy marginal electricity use. We apply our estimates to an analysis of the Biden administration’s target of having electric vehicles (EVs) make up 50% of new vehicle purchases by 2030. We find that, without significant and concurrent changes to the electricity sector, the increase in electricity emissions is likely to offset more than half of the emission reductions from having fewer gasoline-powered vehicles on the road. Moreover, using average rather than marginal emissions to predict the impacts significantly overestimates the emission benefits. Overall, we find that the promise of EVs for reducing emissions depends, to a large degree, on complementary policies that decarbonize both average and marginal emissions in the electricity sector.

Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

“…10 and 11). Though average emissions have been decreasing, marginal emissions have been increasing in the United States over the past decade 64 . The control used average emissions as a fixed objective throughout the year.…”

Plug‐in hybrid electric vehicles are better than battery electric vehicles to reduce CO 2 emissions until 2030

“…29 Thus, a high round trip efficiency for recovering and reusing the braking energy of about 85% permits drastically reducing the net energy required to cover the cycle by 1 /4. Thus, the transition from MVs to HEVs and PHEVs has a huge immediate advantage of reducing the energy requirement by 1 Figure 2B presents the scheme of a much simpler series hybrid HC ICE/lithium-ion batteries propulsion system for a passenger car. In this case, the evolution of a BEV is pursued through the addition of a range extender engine, a high-efficiency small ICE is continuously operated at a constant speed and load as soon as the SOC of the battery falls below a threshold to recharge the battery.…”

“…Holland et al 1 recently analyzed the Biden administration's target of having battery electric vehicles (BEVs) making up 50% of new vehicle purchases by 2030. They found more than half the emission reductions from having fewer gasoline-powered vehicles, without significant changes to the electricity sector, are offset by the increase in electricity emissions.…”

Estimation of Emission Factors from Purchased Electricity for European Countries: Impacts on Emission Reduction of Electricity Storage

“…Many studies have shown that AEFs would seriously erroneously calculate the emissions related to the intervention. Some studies pointed out that AEFs had around 20–50% errors due to the difference in the end-use of electricity and the level of emission reduction. ,, Opposite trends have been found in the U.S. electricity AEFs and MEFs due to the increased dependence on coal for marginal electricity demand . Therefore, MEFs were usually used to calculate the carbon emission impact of energy storage systems.…”

“…14,18,19 Opposite trends have been found in the U.S. electricity AEFs and MEFs due to the increased dependence on coal for marginal electricity demand. 20 Therefore, MEFs were usually used to calculate the carbon emission impact of energy storage systems. The existing short-run MEF calculation methods were mainly divided into economic dispatch models and comprehensive statistical models.…”