Cambridge study: Ethereum low on PoS energy intensity
Cambridge Centre for Alternative Finance estimates Ethereum uses about 7.87 GWh a year and roughly 33 kWh per $1 million of market value, near the lower end among proof-of-stake networks.
The Cambridge Centre for Alternative Finance placed Ethereum near the lower end of energy intensity among major proof-of-stake blockchains, estimating the network consumes about 7.87 gigawatt-hours annually and about 33 kilowatt-hours per $1 million of market value. In the study’s ranking, Ethereum was second-lowest by energy intensity, behind BNB Chain, though it used more electricity in total than most other PoS chains analyzed.
Researchers measured electricity draw at the wall across 20 combinations of Ethereum’s main software clients. They recorded a typical home node drawing about 18 watts and a more powerful workstation at roughly 153 watts. Using a mix of residential and professionally hosted nodes, the study calculated an average draw of about 105 watts per node.
The study identified around 8,522 discoverable full nodes on Ethereum, with roughly 64% running in cloud or enterprise facilities and 36% on residential connections. The node measurements were scaled to the network level and adjusted for market value to produce energy-intensity comparisons across chains.
By that metric, Solana had the highest energy intensity among the PoS networks measured, at about 13.48 GWh annually and roughly 283 kWh per $1 million of market value, about 8.5 times Ethereum’s intensity. The networks included in the comparison together consumed about 38 GWh per year.
The report notes that after Ethereum’s transition from proof-of-work to proof-of-stake in September 2022, electricity use associated with mining fell by more than 99.9%. Remaining electricity consumption and emissions now come mainly from the power sources that supply validator and full-node computers.
The study estimated that roughly 56.4% of the electricity used by Ethereum nodes came from renewable and nuclear sources, while about 43.6% came from fossil fuels. Researchers combined the wall-power measurements, node counts and hosting patterns to estimate total consumption and compare networks on an energy-intensity basis.
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