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An Analysis of Energy Consumption and Carbon Footprints of Cryptocurrencies and Possible Solutions

Varun Kohli, Sombuddha Chakravarty, Vinay Chamola, Kuldip Singh Sangwan, Sherali Zeadally

arXiv:2203.03717v1cs.CY

TL;DR

The review addresses high energy use and carbon emissions associated with Proof of Work cryptocurrencies. It synthesizes comparisons and identifies contributing issues and possible solutions, finding that Bitcoin and Ethereum’s consumption and emissions approach those of some countries while Visa is more efficient per transaction.

  • Problem

    Proof of Work cryptocurrencies have high energy consumption and carbon emissions, while estimating energy sources and mining-related impacts is uncertain.

    Source: A. Consensus Mechanism: Proof of Work · p. 6, D. Sources of Energy · p. 8

  • Method

    The review compares Bitcoin and Ethereum with countries and Visa, identifies four contributing factors, and discusses possible solutions and two work-in-progress case studies.

    Source: §I · p. 2

  • Results

    Bitcoin and Ethereum consumed nearly as much energy as Sweden and Romania, respectively, while their CO2 emissions were close to Greece and Tunisia; Visa was more energy-efficient and had a lower per-transaction carbon footprint.

    Source: §VI · p. 13

  • Takeaways & Limitations

    Because Proof of Work consensus is identified as the largest contributor to energy consumption among the issues discussed, exploring more energy-efficient consensus mechanisms is one viable option.

    Source: A. Alternative Consensus Mechanisms · p. 8

Abstract

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There is an urgent need to control global warming caused by humans to achieve a sustainable future. $CO_2$ levels are rising steadily and while countries worldwide are actively moving toward the sustainability goals proposed during the Paris Agreement in 2015, we are still a long way to go from achieving a sustainable mode of global operation. The increased popularity of cryptocurrencies since the introduction of Bitcoin in 2009 has been accompanied by an increasing trend in greenhouse gas emissions and high electrical energy consumption. Popular energy tracking studies (e.g., Digiconomist and the Cambridge Bitcoin Energy Consumption Index (CBECI)) have estimated energy consumption ranges of 29.96 TWh to 135.12 TWh and 26.41 TWh to 176.98 TWh respectively for Bitcoin as of July 2021, which are equivalent to the energy consumption of countries such as Sweden and Thailand. The latest estimate by Digiconomist on carbon footprints shows a 64.18 Mt$CO_2$ emission by Bitcoin as of July 2021, close to the emissions by Greece and Oman. This review compiles estimates made by various studies from 2018 to 2021. We compare with the energy consumption and carbon footprints of these cryptocurrencies with countries around the world, and centralized transaction methods such as Visa. We identify the problems associated with cryptocurrencies, and propose solutions that can help reduce their energy usage and carbon footprints. Finally, we present case studies on cryptocurrency networks namely, Ethereum 2.0 and Pi Network, with a discussion on how they solve some of the challenges we have identified.

I. INTRODUCTION

The review frames cryptocurrency energy use and carbon emissions as a sustainability concern, then compares Bitcoin and Ethereum with countries and Visa. It identifies four contributing factors and discusses possible solutions, including two work-in-progress case studies.

I. INTRODUCTION

  • The review links cryptocurrency growth to climate concerns amid rising greenhouse-gas levels and reports that energy use is disproportionate to technical performance.It notes that global average temperatures are expected to rise by 3–5°C by 2100.Source: §I · p. 1
  • Bitcoin energy estimates vary widely: 2.5–7.67 GW, 1.3–14.8 GW, 15.47–50.24 TWh, and 22–105 TWh were reported for 2018.Later estimates include 69.63 TWh from CBECI and 135.12 TWh from Digiconomist in July 2021.Source: §I · pp. 1–2
  • The review notes uncertainty in energy estimates because mining equipment and energy sources vary, complicating comparisons of consumption and carbon footprints.It also reports estimates of renewable energy shares in Proof of Work mining ranging from 39% to 78%.Source: §I · pp. 1–2
  • Bitcoin’s carbon footprint was estimated at 63 MtCO2 in 2018, 55 MtCO2 in 2019, and 64.18 MtCO2 in early 2021.Digiconomist also estimated Ethereum’s July 2021 footprint at 26.13 MtCO2.Source: §I · p. 2
  • The review compares Bitcoin and Ethereum’s energy consumption and carbon emissions with countries and Visa, then identifies four contributing factors and discusses solutions and two work-in-progress case studies.Its proposed solutions address the factors associated with high energy use and emissions.Source: §I · p. 2

II. BACKGROUND

This background introduces blockchain and cryptocurrency networks, then situates Bitcoin and Ethereum in comparisons of energy consumption and carbon emissions with countries and Visa.

II. BACKGROUND

  • The background describes comparisons of Bitcoin and Ethereum’s annual energy consumption and carbon footprints with country rankings as of July 2021.The supplied table captions identify the ranking scopes but do not provide cell values.Source: §II · p. 2, Table I · p. 3, Table II · p. 4

A. Blockchain, Bitcoin and Cryptocurrencies

  • Blockchain stores information chronologically in linked blocks, with hashes used to detect changes and copies of the ledger held across network nodes.The described benefits include continued network function when some nodes fail and peer-to-peer trust maintained through consensus.Source: A. Blockchain, Bitcoin and… · pp. 2–3
  • Bitcoin miners compete to solve resource-intensive cryptographic problems under Proof of Work to add blocks, with the puzzle difficulty adjusted to maintain roughly 10-minute block times.Block rewards halve every 210,000 blocks; the stated reward was 6.25 BTC after the May 2020 halving.Source: A. Blockchain, Bitcoin and… · p. 3
  • Ethereum introduced a programmable network and smart contracts, but its Proof of Work basis associates it with energy-consumption and carbon-footprint issues also found in Bitcoin.Ethereum 2.0 is proposed to address most of these issues.Source: A. Blockchain, Bitcoin and… · p. 4

B. A Global Perspective: Energy Consumption and CO2 Emissions

Bitcoin and Ethereum consume substantial shares of global electricity and rank alongside countries in energy use and CO2 emissions. Together, their energy consumption and emissions are comparable to those of Thailand and Belgium, respectively.

B. A Global Perspective: Energy Consumption and CO2 Emissions

  • Bitcoin and Ethereum consumed 135.12 TWh and 55.01 TWh, respectively, corresponding to global electrical energy shares of 0.58% and 0.23%; they ranked 28th and 50th, respectively.The University of Cambridge also arrived at a close estimate.Source: B. A Global Perspective: Energy… · p. 4
  • Together, Bitcoin and Ethereum use 190.13 TWh annually (0.81% of world energy), ranking 23rd and matching Thailand’s 185.85 TWh (0.79%).Bitcoin consumes 135.12 TWh (0.58%) and Ethereum 55.01 TWh (0.23%).Source: B. A Global Perspective: Energy… · p. 4
  • Together, Bitcoin and Ethereum emit 90.31 MtCO2 (0.24% of the global share), ranking 41st and nearly matching Belgium’s 91.2 MtCO2 (0.24%).Bitcoin emits 64.18 MtCO2 (0.17%), while Ethereum emits 26.13 MtCO2 (0.07%).Source: B. A Global Perspective: Energy… · p. 4

C. Comparison with Visa

The review compares Bitcoin, Ethereum, and Visa using annual totals and per-transaction energy and emissions. Its break-even comparison shows that one cryptocurrency transaction can match the energy use or carbon footprint of many Visa transactions.

C. Comparison with Visa

  • Table III compares annual energy consumption and emissions for Bitcoin, Ethereum, and Visa, including all Visa consumption sources.The review also presents per-transaction energy and emissions comparisons in Table IV and Figure 3.Source: C. Comparison with Visa · p. 4, Table III · p. 5, Table IV · p. 5
  • Bitcoin and Ethereum account for 0.08% and 0.25% of Visa’s 500 million daily transactions, while their daily transaction counts are 0.4 million and 1.25 million.Visa’s total metrics include office and server electricity and commuting; the per-transaction comparison considers computational costs.Source: C. Comparison with Visa · p. 5, Table IV · p. 5
  • 1,195,657 Visa transactions use the same electrical energy as one Bitcoin transaction; 83,574 Visa transactions match its carbon footprint.For Ethereum, the corresponding break-even counts are 83,574 Visa transactions for energy and 132,334 for carbon footprint.Source: C. Comparison with Visa · p. 5, Table V · p. 5

III. PROBLEMS

The review identifies four drivers of cryptocurrency energy use and emissions, with Proof of Work (PoW) the dominant energy contributor among the mechanisms discussed. PoW requires miners to repeatedly search for a valid hash, imposing substantial computational demand.

III. PROBLEMS

  • The review identifies PoW, operational and traffic redundancy, mining devices, and energy sources as four major drivers of cryptocurrency energy consumption and emissions.Source: §III · p. 5

A. Consensus Mechanism: Proof of Work

  • PoW mining has high computational needs that limit the continuous use and scalability of cryptocurrencies; transactions themselves consume less energy than the PoW process.A cited 2021 study predicted that PoW mining in China alone would consume nearly 300 TWh and generate 130 MtCO2 by 2024.Source: A. Consensus Mechanism: Proof of Work · p. 6
  • Bitcoin miners repeatedly change the Merkle root or nonce and recalculate the hash until it falls below a difficulty-adjusted target; the block interval is set to 10 minutes.Each proposed block's hash uses the previous block's hash, the nonce, and the Merkle root.Source: A. Consensus Mechanism: Proof of Work · p. 6
  • Finding a nonce is computationally expensive, and the search cannot be accelerated by parallelization or alternative algorithms, creating an arms race as mining difficulty rises.A miner's share of the reward can be equated to its share of network computational power.Source: A. Consensus Mechanism: Proof of Work · p. 6

B. Redundancy in Traffic and Operation

Operational and traffic redundancy increases energy use, while mining-device efficiency varies substantially. ASICs are the most efficient device class described, but their computational advantage can concentrate mining power; ASIC-resistant algorithms instead lead miners toward less efficient general-purpose devices.

B. Redundancy in Traffic and Operation

  • Redundancy arises because every node stores the complete ledger, independently performs transaction-related operations, and contributes additional network traffic, increasing energy use and reducing system efficacy.Source: B. Redundancy in Traffic and Operation · p. 6
  • Over 98% of Bitcoin network traffic was redundant; every 1,000 nodes increased effective traffic by 0.3 GB and total traffic by 24 GB, leaving 23.7 GB redundant.The cited simulation found a positive correlation between routing-path length and traffic redundancy, with shorter paths associated with less redundancy.Source: B. Redundancy in Traffic and Operation · p. 6

C. Mining Devices

  • ASIC devices provide 44,000 GH/s at 0.05 J/GH, while CPUs provide 0.01 GH/s at 9000 J/GH; ASICs are the most efficient, but their advantage creates centralization concerns.ASICs provide 40,000 to 200,000 times the computational power of GPUs; ASIC-resistant algorithms can force miners to use GPUs, which consume disproportionate energy.Source: Figure 5 · p. 6, C. Mining Devices · p. 7
  • The device study assessed 269 hardware devices—111 CPUs, 111 GPUs, 4 FPGAs, and 43 ASICs—and defined minimum and maximum energy consumption using the most and least efficient devices relative to context.Its estimated minimum and maximum power demands across devices were 2 GW and 6 GW, respectively.Source: C. Mining Devices · p. 7

D. Sources of Energy

Cryptocurrency emissions depend on energy sources even though these sources do not drive PoW's disproportionate electricity consumption. The review identifies difficulty estimating mining energy mixes and recommends alternative mechanisms and renewable energy as routes to reduce emissions.

D. Sources of Energy

  • Bitcoin estimates of up to 90 MtCO2 and 64.18 MtCO2, and Ethereum's 26.13 MtCO2, are compared with Oman at 68.8 MtCO2 and aluminium mining at 90 MtCO2.The authors characterize nation- and industry-level emissions from these transaction systems as alarming.Source: D. Sources of Energy · p. 7
  • Non-renewable energy sources lead to high carbon footprints in PoW blockchains, although the energy source itself does not cause their disproportionate electricity consumption.Source: D. Sources of Energy · pp. 7–8
  • Estimates of cryptocurrency mining's energy mix differ: some studies report nearly 80% renewable energy, while the 3rd GCBS reports 61% reliance on non-renewable sources.The passage also reports a 58% hydro-energy and 42% coal-heavy generation split for mining in China.Source: D. Sources of Energy · p. 8
  • Distributed networks make it difficult to estimate renewable and non-renewable energy shares accurately, and mining-device choices add further uncertainty.Source: D. Sources of Energy · p. 8

IV. SOLUTIONS

  • The review recommends exploring alternative consensus mechanisms and reducing redundancy, and examines efficient mining devices and renewable energy in major mining areas as possible solutions.Source: §IV · p. 8

A. Alternative Consensus Mechanisms

The review presents alternatives to PoW that reduce reliance on computational work, including stake-based, voting, trust-based, and storage-based approaches. It also describes useful-work mining and trusted-hardware mining as ways to redirect or limit mining computation.

A. Alternative Consensus Mechanisms

  • Proof of Stake derives proof from miners' blockchain stakes rather than computational power, removing PoW's computational race and reducing mining energy consumption and CO2 emissions.It was first used in Peercoin and has been proposed for Ethereum 2.0.Source: A. Alternative Consensus Mechanisms · p. 8
  • Proof of Activity reduces network communication and storage requirements without compromising security, while Proof of Burn uses burned coins rather than computational power to determine mining power.Proof of Burn is described as low-energy and is implemented in SlimCoin.Source: A. Alternative Consensus Mechanisms · p. 8
  • Hashgraph, Fast Probabilistic Consensus, and XRP Consensus avoid high computational power and consume substantially less energy than PoW.Hashgraph uses collaborative gossip history, FPC uses binary voting, and XRP Consensus reaches agreement without requiring complete consensus among all network members.Source: A. Alternative Consensus Mechanisms · p. 8
  • Proof of SpaceTime uses stored data over time as proof, allowing difficulty to change through storage duration rather than computational capacity; Proof of Space requires little computation and can use free disk space.The passage also describes Proof of Retrievability as a distributed-storage-based consensus mechanism.Source: A. Alternative Consensus Mechanisms · p. 8
  • Useful Proofs of Work allocate verifiable computational tasks to miners, while Resource Efficient Mining uses SGX enclaves to select tasks that can yield valid block proofs.The cited SGX-blockchain implementation had computational overhead of 5–15%.Source: A. Alternative Consensus Mechanisms · p. 9

B. Redundancy Reduction Techniques

The review describes approaches to reduce blockchain redundancy and compares mining-device energy use. Among the listed devices, AvalonMiner 1246 is reported as most efficient, while Antminer S7 is least efficient.

B. Redundancy Reduction Techniques

  • Sharding divides a blockchain into shards that update transactions within their own bounds, though PoW makes division difficult.The passage says sharding can be based on stake proportions in PoS and storage proportions in PoSpace.Source: B. Redundancy Reduction Techniques · p. 9
  • ElasticChain stores only part of the complete ledger at each node, improving storage scalability while maintaining reported stability, security, and fault tolerance.Semantic Differential Transaction captures BIM changes as contracts at 0.02% of IFC size, while a Bitcoin traffic study recommends shorter average routing paths.Source: B. Redundancy Reduction Techniques · p. 10
  • Zero Knowledge Proofs can improve privacy, security, scalability, and throughput without complex encryption, making networks more energy-efficient.One cited method uses ZKP to reduce the time needed to prove and verify large sequential computations compared with other current ZKP implementations.Source: B. Redundancy Reduction Techniques · p. 10

C. Choice of Mining Device

  • ASIC devices use the least energy per hash and provide the highest computational power, with a reported hash rate of 40,000 GH/s at 0.05 J/GH.A study of the KnCMiner facility in Boden, Sweden estimated ASIC use could reduce worldwide annual mining energy consumption to 1.46 TWh.Source: C. Choice of Mining Device · p. 10
  • Among five popular ASIC devices, AvalonMiner 1246 is reported as most efficient at 38 J/TH, while Antminer S7 is least efficient at 273.36 J/TH.The other four devices have comparable maximum annual consumption, ranging from 29.32 GWh to 29.95 GWh.Source: C. Choice of Mining Device · p. 10

D. Renewable Sources of Energy

The review assesses whether renewable capacity in major Bitcoin-mining regions could match mining energy consumption. It finds relatively high renewable capacity in Germany, Canada, China, and the U.S.A., and lower capacity in several other regions.

D. Renewable Sources of Energy

  • The review recommends renewable energy for PoW mining, identifying wind and solar as the best energy alternatives in one cited study.The cited discussion also identifies legal criteria, continuity of supply, and electricity cost as important factors in mining-location decisions.Source: D. Renewable Sources of Energy · p. 10
  • China's estimated Bitcoin mining consumption is 62.15 TWh, comparable to Switzerland's 56.35 TWh of electricity consumption.The review says major mining regions should focus on measures to minimize environmental degradation and global warming from PoW mining.Source: D. Renewable Sources of Energy · p. 10
  • Maximum Energy Generation estimates the highest possible annual output from installed renewable capacity, and RCR compares that generation with mining energy consumption.Figure 9 presents the Renewable Capacity Ratio for major Bitcoin mining regions.Source: D. Renewable Sources of Energy · pp. 10–11
  • Germany, Canada, China, and the U.S.A. have high renewable capacity relative to Bitcoin mining consumption, unlike Kazakhstan, Ireland, Malaysia, Iran, and Russia.The Renewable Capacity Ratio expresses renewable energy available per TWh of Bitcoin mining consumption; the table presents estimated consumption, maximum generation, and RCR for major mining regions.Source: D. Renewable Sources of Energy · p. 11, Table VIII · p. 11

V. CASE STUDIES

The case studies discuss Ethereum 2.0 as a network aiming to address sustainability and scalability. Its proposed changes combine a shift to PoS with sharding to reduce energy use and network redundancy.

V. CASE STUDIES

  • The case studies examine Ethereum 2.0 and Pi Network as networks adapting proposed solutions to cryptocurrency energy consumption and carbon-footprint problems.The review presents them as examples of active development that may inform future research directions.Source: §V · pp. 11–12

A. Ethereum 2.0

  • Ethereum 2.0 plans to shift from PoW to PoS, which is expected to consume less than 99% of current PoW energy consumption.The passage attributes PoS's lower energy use to fewer mathematical calculations and lower computational requirements.Source: A. Ethereum 2.0 · p. 12
  • Ethereum 2.0 plans a Beacon Chain with 64 additional chains, distributing transaction validation so more transactions can be processed in parallel.The passage says this sharding approach reduces redundancy, congestion, and energy consumption by requiring transaction details to be shared with only a fraction of nodes.Source: A. Ethereum 2.0 · p. 12

B. Pi Network

The Pi Network uses a modified Stellar Consensus Protocol rather than PoW and allows mobile-phone users to mine without ASIC devices. The review concludes that Pi Network and Ethereum 2.0 plan to use alternative consensus and load-distribution approaches to reduce energy consumption and carbon footprints.

B. Pi Network

  • The Pi Network uses a modified Stellar Consensus Protocol instead of PoW, with significantly lower energy requirements despite the possibility of congestion from multiple consensus exchanges.The passage describes this approach as addressing Bitcoin's high energy consumption and miner centralization.Source: B. Pi Network · p. 12
  • The Pi Network lets any user with a mobile phone mine without expensive ASIC devices, making mining inexpensive and more widely accessible.The passage contrasts this with Bitcoin, where around 87% of BTCs are owned by 1% of nodes.Source: B. Pi Network · p. 13

VI. CONCLUSION

  • The review concludes that Ethereum 2.0 and Pi Network plan to use PoS, SCP, and sharding to reduce network energy consumption and carbon footprints.The networks are still under development, but the review presents them as efforts to address cryptocurrency energy and CO2 issues.Source: §VI · p. 13
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