Oakland, California, USA
#00164
Case study of
#00169 Provide real-time, location- and time-specific grid carbon-intensity signals as the conversion factor
Implementer
WattTime (environmental non-profit; executive director Gavin McCormick)
Timeline
Since Jan 1, 2014
Location
Description
WattTime, founded in 2014 by UC Berkeley researchers and a subsidiary of Rocky Mountain Institute since 2017, provides Marginal Operating Emissions Rate (MOER, in pounds of CO₂ per MWh) via API in real-time, forecast, and historical form. Its Automated Emissions Reduction (AER) product uses these signals to shift flexible load (EV charging, smart thermostats, batteries) to lower-carbon moments. Partners include Microsoft, Apple, BMW, Toyota, Amazon, and Google Nest. In 2024 it completed an hourly marginal dataset covering 210 countries and territories; in 2025 it released a free global marginal dataset with REsurety. It co-developed the Green Software Foundation's Carbon Aware SDK with Microsoft, where load-shifting demonstrated roughly a 15% reduction in software-related carbon emissions.
Metrics
3Funding
Lessons learned
- Marginal signals (the emissions of the generator that responds to a change in load) are the correct basis for load-shifting decisions, even though average signals are what most regulatory reporting requires — teams building AER-style tools must choose which signal to optimise for.
- Embedding the signal into consumer devices and SDKs rather than dashboards is what scaled real-world emissions impact to over a billion devices; dashboard-only integrations did not achieve comparable reach.
- The average-versus-marginal methodological split is unresolved: at least one major competing provider dropped marginal signals entirely, so adopters should explicitly document and defend their signal choice to stakeholders.
Sources
3Documented Jul 13, 2026