🧮 Methodology

Our methodology is an extension of the approach pioneered by Cambridge, Marc Bevand, and others. We estimate the daily electricity consumption of cryptonetworks using a bottom-up technique based on commercially available mining equipment. Using electricity consumption, we estimate the carbon footprint of each network based on regional energy mix data. Lastly, we map network-level emissions to network participants via two mechanisms: average daily holdings and transactions. We currently support Bitcoin and Ethereum but intend to extend our methodology to encompass other protocols.

Key Assumption

The key assumption underpinning our model is that hash power is a public good for anyone using the network and all blockchain users benefit from miners maintaining the integrity of the network. Therefore, we believe it is incumbent upon any user to assume responsibility for a portion of the emissions generated by the network. In step 4, we talk about the assumptions that underlie this mapping.

Step 1. Determine the average efficiency of mining hardware

• We use an exhaustive list of commercially available mining equipment for each network
• For each piece of hardware, we check if running the machine is profitable given current market conditions
• We compute average hardware efficiency as the simple average of all profitable mining equipment for a given network on a given day

Step 2. Compute electricity load and consumption

• Using average hardware efficiency, we calculate electricity load, which is the power being used by crypto mining infrastructure at a given moment
• We compute daily electricity consumption of a given cryptonetwork by multiplying the hourly electricity load by 24

Step 3. Determine the weighted-average emissions factor

• Bitcoin:
  • We leverage research from Cambridge on the distribution of hash rate contribution across the world
  • Using IEA national-level carbon intensity data, we compute the weighted-average emissions factor for the Bitcoin network
• Ethereum:
  • We use the global distribution of nodes as a proxy for the distribution of mining power
  • Using IEA national-level carbon intensity data, we compute the weighted-average emissions factor for the Ethereum network

Step 4. Map carbon emissions to network participants

In general, Patch maps network-level emissions to individual market participants via two approaches: tokens and transactions. Both approaches assert different assumptions about distributing emissions responsibility. Before applying either approach, we compute daily emissions for each network by multiplying daily electricity consumption by the weighted-average emission factor.

Carbon emissions per token

In this approach, a token holder realizes carbon emissions each day commensurate to the proportion of the total circulating supply of the network that they hold. Patch uses a circulating supply that backs out provably lost coins and tokens held in accounts subject to escrow. To provide an example calculation:

Suppose CryptoCo holds 1 bitcoin for 30 days. Let the carbon footprint of the Bitcoin network equal 5,000,000 tonnes of CO2eq during this period. Finally, let the circulating supply of bitcoin be 14,000,000.

$$ \text{CryptoCo CO2e for the period} = \frac{1}{14000000} * 5000000\text{t} = 357 \text{kg} $$