Ethereum Emissions

Ethereum emits around 20 ktCO2/day, similar to 2–3 coal power plants. Estimated from hashrate, GPU efficiency, miner location, and more.

  • Hashrate. We can get this from Etherscan.
  • Hardware overhead (CPU, network card, fans)
  • Datacenter overhead (fans, lighting, networking infrastructure)
  • Grid loss. A significant portion of the electricity generated does not make it to the consumer (typically around 6%).
  • Hashing efficiency. How fast does the hardware hash at a given power?
  • Power supply efficiency. Most power supplies are only 80-90% efficient, losing a bunch of electricity as heat.
GPU power usage vs hashrate reported by users on MinerMonitoring, showing large variation across the same GPU models.
  1. We can look at HiveOS, which tracks some live statistics.
  2. We can check worker IDs on Nanopool where miners often name their workers based on the hardware they are using.
  3. We can assume that benchmark sites primarily benchmark hardware that is popular for mining, and that miners have followed the generally increasing trend in efficiency.
Plot of hardware hashing efficiency increasing over time, with hardware names drawn next to the median efficiency across multiple benchmarks.
Analysis of the hashrate distribution of around 70,000 active Nanopool workers per day over multiple days.
Ethereum network power in Gigawatts and equivalent annualized Terawatt hours per year, based on energy equation 1 and parameters. Shaded region shows the range between our lower and upper estimates.
Distribution of mining in different regions over time based on patterns in extraData indicating region, and mining pool region distributions. Dashed lines for the 2021–05–21 Chinese mining ban and 2021–09–23 Chinese crypto ban.
Regional emissions factor estimates, in gCO2/kWh.
Ethereum emissions in ktCO2/day and equivalent annualized MtCO2/year based on energy usage, block metadata, and regional emissions factors. Shaded region shows the range between our lower and upper estimates.
Ethereum electricity emissions factor gCO2/kWh, using data from regional emissions factors weighted by region estimated from block metadata.
  1. If the intra-year changes were fully accounted for, we would see a yearly “wobble” in the emissions factor as miners move between provinces in China. I haven’t been able to find that data in the blockchain yet. To the extent that this “wobble” lines up with price bubbles, it could make some bubbles worse than others. Right now the wobble is just “flattened out” across the whole year.
  2. With the 2021–05–21 Chinese mining ban, the amount of mining in China has nosedived. This should theoretically send the emissions factor higher, as many Chinese miners are moving to areas with more fossil fuels like Kazakhstan and Texas. That isn’t reflected in this analysis because I treat the “Asia” mining as automatically including some “China” mining. A better model would account for how the mixture of mining in “Asia” has changed over time.



Artist working with code.

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