The Bitcoin Energy Consumption Index provides the latest estimate of the total energy consumption of the Bitcoin network.
NEW RELEASE: “The true costs of digital currencies”, noting that “the total Bitcoin carbon footprint exceeds the total GHG emission reductions of electric vehicles (51.9 Mt CO2 in 2020)” and urging for a more comprehensive view in assessing the externalities of cryptocurrencies (June 2021).
Annualized Total Bitcoin Footprints
62.12 Mt CO2
Comparable to the carbon footprint of Belarus.
Comparable to the power consumption of Argentina.
Comparable to the e-waste generation of Luxembourg.
Single Bitcoin Transaction Footprints
Equivalent to the carbon footprint of 1,668,626 VISA transactions or 125,479 hours of watching Youtube.
Equivalent to the power consumption of an average U.S. household over 54.33 days.
Equivalent to the weight of 1.57 'C'-size batteries or 2.22 golf balls. (Find more info on e-waste here.)
*The assumptions underlying this energy consumption estimate can be found here. Criticism and potential validation of the estimate is discussed here.
**The minimum is calculated from the total network hashrate, assuming the only machine used in the network is Bitmain’s Antminer S9 (drawing 1,500 watts each). On February 13, 2019, the minimum benchmark was changed to Bitmain’s Antminer S15 (with a rolling average of 180 days), followed by Bitmain’s Antminer S17e per November 7, 2019 and Bitmain’s Antminer S19 Pro per October 31, 2020.
***Note that the Index contained the aggregate of Bitcoin and Bitcoin Cash (other forks of the Bitcoin network have not been included). The latter has been removed per October 1, 2019.
Did you know Bitcoin runs on an energy-intensive network?
Ever since its inception Bitcoin’s trust-minimizing consensus has been enabled by its proof-of-work algorithm. The machines performing the “work” are consuming huge amounts of energy while doing so. Moreover, the energy used is primarily sourced from fossil fuels. The Bitcoin Energy Consumption Index was created to provide insight into these amounts, and raise awareness on the unsustainability of the proof-of-work algorithm.
A separate index was created for Ethereum, which can be found here.
What kind of work are miners performing?
New sets of transactions (blocks) are added to Bitcoin’s blockchain roughly every 10 minutes by so-called miners. While working on the blockchain these miners aren’t required to trust each other. The only thing miners have to trust is the code that runs Bitcoin. The code includes several rules to validate new transactions. For example, a transaction can only be valid if the sender actually owns the sent amount. Every miner individually confirms whether transactions adhere to these rules, eliminating the need to trust other miners.
The trick is to get all miners to agree on the same history of transactions. Every miner in the network is constantly tasked with preparing the next batch of transactions for the blockchain. Only one of these blocks will be randomly selected to become the latest block on the chain. Random selection in a distributed network isn’t easy, so this is where proof-of-work comes in. In proof-of-work, the next block comes from the first miner that produces a valid one. This is easier said than done, as the Bitcoin protocol makes it very difficult for miners to do so. In fact, the difficulty is regularly adjusted by the protocol to ensure that all miners in the network will only produce one valid block every 10 minutes on average. Once one of the miners finally manages to produce a valid block, it will inform the rest of the network. Other miners will accept this block once they confirm it adheres to all rules, and then discard whatever block they had been working on themselves. The lucky miner gets rewarded with a fixed amount of coins, along with the transaction fees belonging to the processed transactions in the new block. The cycle then starts again.
The process of producing a valid block is largely based on trial and error, where miners are making numerous attempts every second trying to find the right value for a block component called the “nonce“, and hoping the resulting completed block will match the requirements (as there is no way to predict the outcome). For this reason, mining is sometimes compared to a lottery where you can pick your own numbers. The number of attempts (hashes) per second is given by your mining equipment’s hashrate. This will typically be expressed in Gigahash per second (1 billion hashes per second).
The continuous block mining cycle incentivizes people all over the world to mine Bitcoin. As mining can provide a solid stream of revenue, people are very willing to run power-hungry machines to get a piece of it. Over the years this has caused the total energy consumption of the Bitcoin network to grow to epic proportions, as the price of the currency reached new highs. The entire Bitcoin network now consumes more energy than a number of countries. If Bitcoin was a country, it would rank as shown below.
Apart from the previous comparison, it also possible to compare Bitcoin’s energy consumption to some of the world’s biggest energy consuming nations. The result is shown hereafter.
Bitcoin’s biggest problem is perhaps not even its massive energy consumption, but the fact most mining facilties in Bitcoin’s network are located in regions (primarily in China) that rely heavily on coal-based power (either directly or for the purpose of load balancing). To put it simply: “coal is fueling Bitcoin” (Stoll, 2019).
Thinking about how to reduce CO2 emissions from a widespread Bitcoin implementation
— halfin (@halfin) 27 januari 2009
Determining the exact carbon impact of the Bitcoin network has been a challenge for years. Not only does one need to know the power requirement of the Bitcoin network, but one also need to know where this power is coming from. The location of miners is a key ingredient to know how dirty or how clean the power is that they are using.
Just like it’s not easy to find out what machines are active in the Bitcoin network, determining location isn’t an easy feat either. Initially the only information available to this end was the common belief that the majority of miners were located in China. Since we know the average emission factor of the Chinese grid (around 700 grams of carbon dioxide equivalent per kilowatt-hour), this can be used for a very rough approximation of the carbon intensity of the power used for Bitcoin mining. Assuming that 70% of Bitcoin mining is taking place in China, and that 30% of mining is completely clean, this yields a weighted average carbon intensity of 490 gCO2eq/kWh. This number can subsequently be applied to a power consumption estimate of the Bitcoin network to determine its carbon footprint.
A more detailed estimate
Later on, more granular information became available in the Global Cryptocurrency Benchmarking Study by Garrick Hileman and Michel Rauchs from 2017. In this study, they identified facilities representing roughly half of the entire Bitcoin hash rate, with a total (lower bound) consumption of 232 megawatts. Chinese mining facilities were responsible for about half of this, with a lower bound consumption of 111 megawatts. This information can be used to get a more accurate idea of the carbon emission factor in grams of carbon dioxide equivalent per kilowatt-hour (gCO2eq/kWh) that applies to the electricity used for mining.
The table below features a breakdown of the energy consumption of the mining facilities surveyed by Hileman and Rauchs. By applying the emission factors of the respective country’s grid, we find that the Bitcoin network had a weighted average carbon intensity of 475 gCO2eq per kWh consumed. (This number is currently applied to determine the carbon footprint of the Bitcoin network based on the Bitcoin Energy Consumption Index.)
|Location||Power consumption (megawatts)||% of surveyed facilities||Carbon intensity (gCO2eq/kWh)|
|Total / Weighed Average b>||233 b>||100.00 b>||475 b>|
Breakdown of regional carbon intensity
One can argue that specific locations in the listed countries may offer less carbon intense power. In 2018 Bitcoin company Coinshares suggested that the majority of Chinese mining facilities were located in Sichuan province, using cheap hydropower for mining Bitcoin. Subsequent studies have, however, never been able to support this claim and/or found the opposite. Confronted with this evidence, the lead author of the Coinshares paper had to admit “mistakes” were made.
The main challenge here is that the production of hydropower (or renewable energy in general) is far from constant. In Sichuan specifically the average power generation capacity during the wet season is three times that of the dry season. Because of these fluctuations in hydroelectricity generation, Bitcoin miners can only make use of cheap hydropower for a limited amount of time.
In a study titled “The Carbon Footprint of Bitcoin” (Stoll et al. 2019) properly account for these regional differences (while also introducing a new method to localize miners based on IP-addresses), but still find a weighted average carbon intensity of 480-500 gCO2eq per kWh for the entire Bitcoin network (in line with previous and more rough estimations).
Using a similar approach, Cambridge in 2020 provided a more detailed insight into the localization of Bitcoin miners over time. Charting this data, and adding colors based on the carbon intensity of the respective power grids, we can reveal significant mining activity in highly polluting regions of the world during the Chinese dry season (as shown below). On an annual basis, the average contribution of renewable energy sources therefore remains low. When Cambridge subsequently surveyed miners (also in 2020), respondents indicated only 39% of their total energy consumption actually came from renewables.
Key challenges for using renewables
It is important to realize that, while renewables are an intermittent source of energy, Bitcoin miners have a constant energy requirement. A Bitcoin ASIC miner will, once turned on, not be switched off until it either breaks down or becomes unable to mine Bitcoin at a profit. Because of this, Bitcoin miners increase the baseload demand on a grid. They don’t just consume energy when there is an excess of renewables, but still require power during production shortages. In the latter case Bitcoin miners have historically ended up using fossil fuel based power (which is generally a more steady source of energy).
Further substantiation on why Bitcoin and renewable energy make for the worst match can be found in the peer-reviewed academic article “Renewable Energy Will Not Solve Bitcoin’s Sustainability Problem” featured on Joule. With climate change pushing the volatility of hydropower production in places like Sichuan, this is unlikely to get any better in the future.
Comparing Bitcoin’s energy consumption to other payment systems
To put the energy consumed by the Bitcoin network into perspective we can compare it to another payment system like VISA for example. According to VISA, the company consumed a total amount of 740,000 Gigajoules of energy (from various sources) globally for all its operations. This means that VISA has an energy need equal to that of around 19,304 U.S. households. We also know VISA processed 138.3 billion transactions in 2019. With the help of these numbers, it is possible to compare both networks and show that Bitcoin is extremely more energy intensive per transaction than VISA. The difference in carbon intensity per transaction is even greater (see footprints), as the energy used by VISA is relatively “greener” than the energy used by the Bitcoin mining network. The carbon footprint per VISA transaction is only 0.45 grams CO2eq.
The number of VISA transactions that could be powered by the energy consumed for a single Bitcoin transaction on average (1584.99 kWh).
The number of VISA transactions with a carbon footprint equal to the footprint of a single Bitcoin transaction (752.87 kgCO2) after factoring in the respective energy mix.
Of course, VISA isn’t perfectly representative for the global financial system. But even a comparison with the average non-cash transaction in the regular financial system still reveals that an average Bitcoin transaction requires several thousands of times more energy.
It’s often argued that Bitcoin is more like “digital gold” than a payment system, as the network can process just around 5 transactions per second (whereas VISA can handle over 65,000 per second if needed). Hence we can also compare Bitcoin mining to gold mining instead. Every year, around 3,531 tonnes of gold are mined, with a total related emissions amounting to 81 million metric tonnes of CO2. When comparing this to the carbon intensity of mining Bitcoins, we can observe that the latter exceeds that of mining real gold (see below). Note that this includes mined fees, which has no comparison in mining for real gold (as we’d have to put previously mined gold back into the ground). Likewise, the comparison is also flawed because we can stop mining for real gold, whereas Bitcoin would simply stop existing without active mining.
15 tonnes CO2
The carbon footprint of one Bitcoin's worth of gold mined.
188 tonnes CO2
The carbon footprint of a single mined Bitcoin (inc. fees).
One could argue that this is simply the price of a transaction that doesn’t require a trusted third party, but this price doesn’t have to be so high as will be discussed hereafter.
Proof-of-work was the first consensus algorithm that managed to prove itself, but it isn’t the only consensus algorithm. More energy efficient algorithms, like proof-of-stake, have been in development over recent years. In proof-of-stake coin owners create blocks rather than miners, thus not requiring power hungry machines that produce as many hashes per second as possible. Because of this, the energy consumption of proof-of-stake is negligible compared to proof-of-work. Bitcoin could potentially switch to such an consensus algorithm, which would significantly improve environmental sustainability. The only downside is that there are many different versions of proof-of-stake, and none of these have fully proven themselves yet. Nevertheless the work on these algorithms offers good hope for the future.
Energy consumption model and key assumptions
Even though the total network hashrate can easily be calculated, it is impossible to tell what this means in terms of energy consumption as there is no central register with all active machines (and their exact power consumption). In the past, energy consumption estimates typically included an assumption on what machines were still active and how they were distributed, in order to arrive at a certain number of Watts consumed per Gigahash/sec (GH/s). A detailed examination of a real-world Bitcoin mine shows why such an approach will certainly lead to underestimating the network’s energy consumption, because it disregards relevant factors like machine-reliability, climate and cooling costs. This arbitrary approach has therefore led to a wide set of energy consumption estimates that strongly deviate from one another, sometimes with a disregard to the economic consequences of the chosen parameters. The Bitcoin Energy Consumption Index therefore proposes to turn the problem around, and approach energy consumption from an economic perspective.
The index is built on the premise that miner income and costs are related. Since electricity costs are a major component of the ongoing costs, it follows that the total electricity consumption of the Bitcoin network must be related to miner income as well. To put it simply, the higher mining revenues, the more energy-hungry machines can be supported. How the Bitcoin Energy Consumption Index uses miner income to arrive at an energy consumption estimate is explained in detail here (also in peer-reviewed academic literature here), and summarized in the following infographic:
Bitcoin miner earnings and (estimated) expenses are currenly as follows:
Total value of mining rewards (including fees) per year.
Assuming a fixed rate of 5 cents per kilowatt-hour.
Estimated ratio of electricity costs to total miner income.
Note that one may reach different conclusions on applying different assumptions (a calculator that allows for testing different assumptions has been made available here). The chosen assumptions have been chosen in such a way that they can be considered to be both intuitive and conservative, based on information of actual mining operations. In the end, the goal of the Index is not to produce a perfect estimate, but to produce an economically credible day-to-day estimate that is more accurate and robust than an estimate based on the efficiency of a selection of mining machines.