Combating Climate Change by Measuring Carbon Emissions Correctly

The briefing explains that measuring electricity emissions through average factors often misrepresents the actual environmental impact of energy use. By adopting technology that tracks marginal emissions—the rate at which emissions change with a small change in load—consumers and corporations can optimize the timing and location of electricity use to maximize carbon reductions. The author highlights that harnessing end-use flexibility can make devices run 15 percent cleaner on average without cost or quality impacts. Practical applications include timing electric vehicle charging to avoid peaking plants and valuing renewable energy projects based on their specific carbon reduction potential rather than treating all megawatt-hours as equal.

• Harnessing the flexibility of end-use devices—adjusting the timing of electricity use without impacting service quality—can result in devices running 15 percent cleaner on average compared to non-flexible devices, with no cost or quality impact to the user.
• There is a significant difference between average emissions factors (total emissions divided by total energy) and marginal emissions factors (the rate of change in emissions relative to a change in load). Relying on average factors can lead to incorrect decisions; for example, in the U.S. Pacific Northwest, while the average emissions factor is low due to hydropower, the marginal resource is often natural gas, meaning new electricity demand increases emissions at the rate of natural gas (840 lbs. CO2 per MWh).
• The marginal resource on the electricity grid changes every five to 15 minutes, meaning the optimal time for carbon-intensive activities varies by region and time of day. In the Midwest, charging electric vehicles during the day is cleaner because utilities primarily burn coal at night, whereas in California, charging in the evening is preferable due to more efficient gas plants being on the margin at night.
• Correctly accounting for carbon emissions enables several optimization opportunities: adjusting the timing of energy use via Internet-connected devices, siting generation and consumption based on location-specific impacts (e.g., wind farms in West Virginia reduce more carbon per MWh than those in California), valuing energy conservation based on the specific fuel displaced, and pricing carbon markets and RECs based on actual rather than average impacts.

APA

McCormick, G. (2016). Combating Climate Change by Measuring Carbon Emissions Correctly. RMI. https://rmi.org/resources/combating-climate-change-measuring-carbon-emissions-correctly/

Chicago

McCormick, Gavin. Combating Climate Change by Measuring Carbon Emissions Correctly. RMI, 2016. https://rmi.org/resources/combating-climate-change-measuring-carbon-emissions-correctly/.

Wikipedia

{{cite report |last1=McCormick |first1=Gavin |title=Combating Climate Change by Measuring Carbon Emissions Correctly |publisher=RMI |date=30 November 2016 |url=https://rmi.org/resources/combating-climate-change-measuring-carbon-emissions-correctly/ |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{mccormick2016combating, author = {McCormick, Gavin}, title = {{Combating Climate Change by Measuring Carbon Emissions Correctly}}, institution = {RMI}, year = {2016}, month = nov, url = {https://rmi.org/resources/combating-climate-change-measuring-carbon-emissions-correctly/}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }