Bitcoin’s Carbon Footprint Revisited: Proof of Work Mining for Renewable Energy Expansion
Abstract
:1. Introduction
2. Background and Context
3. Bitcoin’s Environmental Impact
Approach | Description | Limitations |
---|---|---|
Per-transaction basis | “Taking all the emissions (or electricity consumption) in a given time frame and dividing them by the number of transactions in the period, to arrive at a carbon (or electricity consumption) per transaction metric” [22]. A variant of this considers the entire history of past transactions as secured with every new mining event, and not just the coinage of the latest coin. | Usually overlooks L2 transactions, overlooks that Bitcoin demand for transactions is a minor contributor to mining incentives, and thus is incorrectly used to imply that Bitcoin’s throughput can only grow at the cost of more energy consumption [5,16,22,26]. |
Per-dollar or per-coin settled basis | Considering that L2 solutions allow scaling without increasing energy usage, it focuses on value delivered per kWh [5]. | May incorrectly suggest that additional trading leads to a lower environmental impact. |
Per-dollar or per-coin mined basis | A novel short-run perspective assuming an “origin accounting” methodology [10]. | Neglects Bitcoin’s decreasing emission rate and presents impractical long-term implications, such as assuming that when the last Bitcoin is mined, Bitcoin’s emissions will be infinite, as well as that approximately 90% of Bitcoin’s climate damages have already occurred and the rest will be spread over an increasingly carbon-neutral energy grid. |
4. Bitcoin Mining and RE
4.1. Limitations of RE
4.2. Distinctive Characteristics of Proof of Work (PoW) Mining
4.3. Applications
4.4. Business Models
5. Potential Impact of Mining
6. Challenging Trends
7. Challenger Technologies: Alternative Load Resources
8. Empirical Support for Synergies between Bitcoin and RE
9. Discussion and Critical Analysis
9.1. Intermittency, Profitability and Increasing Fierceness of Competition
9.2. Bitcoin’s Potential: A Balanced Perspective
10. Limitations and Future Work
11. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Strategy | Description | Challenges |
---|---|---|
Transmission | Importing and exporting energy from areas with excess supply to areas with excess demand is an effective way to balance electricity markets [30,37]. | Transmission lines have limited capacity, experience congestion, struggle to keep up with electrification trends, suffer from energy losses proportional to their length, and require substantial initial investments [1,3,38]. “Stranded” energy cannot be transmitted. RE generation is often most efficient in remote locations. |
Capacity Expansion | Investing in excess RE infrastructure to meet demand during low supply periods. | Over-building or over-investing impacts the sector’s profitability, leading to low or negative prices during high supply periods and necessitating government subsidies [30] and curtailment, often intentionally built into capacity expansion projects [39]. |
Curtailment | When RE production infrastructure is built, excess energy is wasted to avoid issues such as overloading transmission capacity or negative pricing [12,35,40]. | Curtailment has an opportunity cost in terms of unsold energy, decreasing the profitability of VRE generation. Curtailment is projected to increase over time [34,41]. |
Storage | Storing energy during excess supply and using it during excess demand periods through batteries or other methods, such as pumped hydroelectric storage [14,30,42]. | Batteries and storage solutions are expensive [3,30,42] and have limited capacity, restricting their large-scale effectiveness. |
Demand-Response Programs | A form of sector coupling [43] and “power-to-X” solutions [15,44,45] where grid operators influence electricity demand patterns to match supply patterns, using flexible load response and compensating energy customers for not consuming electricity during peak events [30,32,38]. | Most loads are not flexible enough for large-scale implementation without significant costs or opportunity losses. |
Characteristic | Description |
---|---|
Flexibility of Load | Bitcoin miners can be activated or deactivated with sub-second responsiveness with little reaction costs (inertia, cooling, warming up). The load can furthermore be “available” in the long term, i.e., it can be reliably providing a stable load due to extended time-horizons and a cash-flow break-even level generally below the ROI break-even level [2,30,47,48,49]. |
Interruptibility | As mining relies on non-time-sensitive computation, it allows for immediate output switching, and interruptions result in no lost work. This high interruptibility, with the only nuances of difficulty adjustments and mining pool stability reward programs, can support grid stability [2,12,16,30,32,46,50]. |
Portability/Mobility | Bitcoin mining is location-agnostic, as it requires minimal investment in immovable assets, equipment is easily transportable, there is no need for a grid connection, there are modularised mining solutions, and there is an empirical track record of geographic flexibility under seasonal weather and country-wide bans [1,2,3,12,14,30,38,51,52]. |
Price Sensitivity | Bitcoin mining is one of the most price-sensitive industries due to its few inputs (mainly electricity) and outputs (primarily BTC, the prices of which are location-agnostic). This results in high OPEX sensitivity, particularly to electricity costs, making miners highly reactive to volatile energy prices. Furthermore, the different (and well known) profitability profiles of various ASIC models offer significant complementarities with multiple energy system niches and patterns [30,35]. |
Scale Agnosticity | Mining operations can adapt to a wide range of scales, from small home mining to large-scale industrial operations. This scalability makes the industry versatile in its role in the electrical grid [2,6,30]. |
Consumption-level Granularity | Energy-intensive ASICs with varying break-even points allow for precise adjustments in energy consumption levels, contrasting to binary consumption options, making Bitcoin mining a flexible participant in the energy market [30,41,47,50]. |
Non-rival Energy Consumption | Mining’s energy consumption does not necessarily result in increased energy generation or emissions. It can utilize otherwise wasted energy (already-generated energy) or harness emissions that would have been produced regardless, implying that miners may not compete directly with other energy consumers [2,12]. |
Diversification | The distinct and uncorrelated stochastic processes of global Bitcoin prices/hash rates and electricity prices enhance the value of switching outputs, offering a valuable source of income diversification and stability for RE sellers [46,53]. |
Waste Heat Utilization | The mining process generates significant waste heat, which can potentially be repurposed for various applications such as residential heating or commercial use [7,31]. |
Salient Characteristics of Bitcoin Mining | ||
---|---|---|
Category | Characteristic | Sub-Characteristics |
Flexibility of Load | Availability of Load | Stability of Load |
Reliability of Load | ||
Long Time Horizon | ||
Interruptibility | Quick Reaction Time | |
Consumption Granularity | ||
Price Sensitivity | Bitcoin Price Sensitivity | |
Cost Sensitivity | ||
Granularity | ||
Information Completeness | ||
Near-Zero Reaction Costs | ||
Scalability | Scale Agnosticity | Scalability |
Energy Intensity | ||
Portability | Location Agnosticity | Movable Goods |
Geography Independence | ||
Modularized Solutions | ||
Unnecessary Grid Connection | ||
Low Labor Intensity | ||
Transferability of Output | ||
Other Characteristics | Non-Rivalrousness | |
Non-Correlation | ||
Heat Output |
Category | Details |
---|---|
First or Last Resort Buyers | Mining can provide a primary demand source that pays more than selling to the grid, encouraging new plant installations. Bitcoin miners do not replace other consumers in first-resort scenarios caused by a connection queue. It can also provide last resort demand for periods of excess supply [1,46,53]. |
Uptime | Modern and efficient ASIC miners can run almost 24/7, suited for peak shaving. Older, less efficient miners become profitable during low energy prices only, with “ASIC retirement homes” absorbing excess supply as an ancillary service to stabilize the grid [2,3]. |
Miner Location | BTM mining reduces transmission costs by placing miners at renewable energy plants, whereas front-of-the-meter mining connects to the grid as a regular consumer [6,30,50]. |
Pricing Model | A PPA offers fixed prices to miners, facilitating external funding. It can include an option for the seller to switch off the buyer’s ASICs (in exchange for fixed compensation), leading to cost savings during off-peak times. However, regions with high renewable energy use or frequent severe weather may experience above-median PPA prices. PPAs can be used to integrate miners as emergency load resources for regulated ancillary service demand-response programs, as in Texas. Without PPAs (usually front-of-the-meter), a price-responsive model (usually BTM) is generally adopted, where the seller sells to the market if the market price is above the miners break-even point, and to the miner when it is below. This reduces cooling costs and may reduce prices as extreme price events do not affect the miner’s break even [30,41]. |
Relationship between Miner and RE Producer | Relationships range from mere proximity for efficiency gains to direct contracting for control over operations or vertical integration for full internalization of costs [1,3,6,30,35,46]. |
Gas Mining Models | Models include “pay for the gas”, where the miner pays for the gas used and keeps the mining proceeds, and “pay for the equipment”, where the miner provides a data center to the gas company, who keeps mining proceeds. Other models include “mobile market hubs” to alleviate pipeline constraints [59]. |
Operations and Portfolio Greening | Operations can be made greener through renewable energy certificates, guarantees of origin, carbon credits, or offsets. Investors may make their portfolio greener by investing in green hashrate (incentive offsets), purchasing sui generis green Bitcoin attributes. More controversial options include colored coin proposals to trace sustainably mined Bitcoin, which may break fungibility [3,7,15,17,22,35,66]. |
Technology | Potential for Decarbonization | Limitations |
---|---|---|
Water Desalination | Flexible and interruptible; can use nonrival energy sources; there are proposals for Bitcoin mining and water desalination as complementary infrastructures [69]. | Less portable due to infrastructure requirements (tanks, pumping) [69]. |
Green Hydrogen and Synthetic Methane | Flexible and interruptible; could potentially use nonrival energy sources [15,45,57]. | Electrolysis can be more expensive (e.g., requires storage infrastructure) and risky than mining; less flexible and less portable output; the business model is not battle-tested; a hydrogen economy would entail an energy consumption so large that curtailed energy could not meet it but in a fraction [3,12,15,30,54]. |
CO2 Removal | Potentially flexible and interruptible; could use nonrival energy sources. | Profitability is uncertain; public good subject to the tragedy of the commons without significant subsidies. |
Batteries | Can solve part of the daily intermittency problem by balancing load; are flexible and interruptible; their price is expected to continue falling; may complement Bitcoin mining in the “right mix” [2,3,33,35,42]. | Expensive and lower ROI in large scales due to physical limitations to the ability to store energy without dissipation; offer no additional profit other than flexibility itself; offer a smaller energy sink [2,30,33,42]. |
Other Flexible Data Centers | Other forms of non-time sensitive computation can have a net decarbonizing effect; can increase grid resiliency [14]. | Inferior to cryptocurrency mining facilities in terms of flexibility and efficiency; although there are leaders in the area, many players are lagging behind [38,47]. |
Other Load Resources (aluminum smelters, sector coupling, Power-to-X solutions, demand-response programs, load shedding, etc.) | Can provide alternative forms of load balancing [14,15,30]. | Power-to-X solutions require “a meaningful probability of occurrence to make it economically viable” [15] (p. 5734); inferior to cryptocurrency mining facilities in terms of flexibility and efficiency [14]. |
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Ibañez, J.I.; Freier, A. Bitcoin’s Carbon Footprint Revisited: Proof of Work Mining for Renewable Energy Expansion. Challenges 2023, 14, 35. https://doi.org/10.3390/challe14030035
Ibañez JI, Freier A. Bitcoin’s Carbon Footprint Revisited: Proof of Work Mining for Renewable Energy Expansion. Challenges. 2023; 14(3):35. https://doi.org/10.3390/challe14030035
Chicago/Turabian StyleIbañez, Juan Ignacio, and Alexander Freier. 2023. "Bitcoin’s Carbon Footprint Revisited: Proof of Work Mining for Renewable Energy Expansion" Challenges 14, no. 3: 35. https://doi.org/10.3390/challe14030035
APA StyleIbañez, J. I., & Freier, A. (2023). Bitcoin’s Carbon Footprint Revisited: Proof of Work Mining for Renewable Energy Expansion. Challenges, 14(3), 35. https://doi.org/10.3390/challe14030035