LFG Learnings Report: Digital Asset Computing Is an Economically Viable Approach to Reducing Landfill Methane Emissions
Abstract
In this study, we reveal that it is not only feasible but economically viable and environmentally beneficial to use landfill gas (LFG) for digital asset compute (e.g., Bitcoin mining). To support this theory, Marathon partnered with Nodal Power to harness excess capacity from their project, which is exclusively powered by landfill methane gas. This partnership, leveraging Nodal’s patented technology, successfully utilized methane from a landfill, converted it into electricity, and used it to power the on-site data center. This process proved to be consistently reliable, with high uptime and emerged financially beneficial for Marathon and Nodal. The cost of electricity was substantially lower than the industry average, and the landfill generated revenue from a previously untapped resource that would otherwise have been wasted. Additionally, powering compute with landfill gas efficiently reduced methane emissions. In scenarios where the landfill would have resorted to flaring the methane, digital asset compute proved to be more effective in mitigating emissions.
This pilot project was Marathon’s first successful test run of “energy harvesting,” which includes initiatives dedicated to converting waste into energy, methane gas recapture, stabilizing energy grids by utilizing stranded or excess energy, and reusing heat generated by data centers for industrial and commercial purposes.
Click HERE to download a PDF of the full report
Introduction
Methane is a potent greenhouse gas with a global warming potential 80 times greater than carbon dioxide over a 20-year period. According to the Global Methane Assessment, “achieving methane emissions reductions in the next decade will keep the planet significantly cooler than attempts to cut carbon dioxide emissions alone.” In our Cashing in on Trash report, we cited that landfills are responsible for 11% of global methane emissions, with recent studies suggesting that these emissions might be 1.4 to 2.6 times higher than previously estimated.
Recognizing that landfills are major emitters of methane, we believed there was an opportunity to make landfills more sustainable with our digital asset compute technologies. Large landfills capable of producing sufficient quantities of methane have the option to economically reduce their emissions through waste-to-energy conversion technologies. These sites can convert captured methane into two forms of sustainable energy: 1) electricity, which can be sold to the grid, and 2) renewable natural gas (RNG), which can be distributed through pipelines. Unfortunately, traditional waste-to-energy conversion methods are often not feasible or economical for smaller or more remote landfills. In our report, we proposed a more viable, win-win solution that we believed was feasible today for smaller landfills: capture methane from landfills, convert it into electricity, and power digital asset data centers to economically reduce methane emissions.
To test our theory, Marathon launched a pilot project by joining Nodal’s off-grid digital asset compute facility to power a Bitcoin data center with 100% renewable, off-grid energy from a landfill.
Pilot Details
Location: Utah, USALaunch Date: September 27, 2023Pilot Status: On-goingDuration: 240+ daysCapacity: 270 kWComputing Equipment: 83 S19J ProsOperational Hash Rate (computing power): 8.3 PH/s
Figure 1: Marathon’s and Nodal’s Project
Source: Nodal Power
Source: Nodal Power
The results from this pilot supported our initial theory. Marathon and Nodal utilized methane from the landfill and converted it into electricity to power a digital asset data center. The landfill successfully reduced its methane emissions while generating a revenue stream it otherwise could not have earned. Marathon and Nodal realized an energy cost significantly below the industry average and maintained an above-average operational uptime. Additionally, this was Marathon’s first successful trial of “energy harvesting,” marking a significant milestone in our development of sustainable and inclusive energy projects. These projects include converting waste into energy, methane gas recapture, stabilizing the energy grid by utilizing stranded or excess energy, and reusing heat generated by mining systems for industrial and commercial processes.
Definitions and Calculations of Key Metrics
During our pilot project, we tracked various metrics to evaluate the effectiveness and impact of our operations. The following are the key metrics used in this report, each outlined with its definition and calculation method.
Average Operational Hash Rate
The average hash rate or computing power that was generated during a specific time period from all operational digital asset computing devices, measured in petahashes per second (PH/s).
Pool reported hash rate per day / Total days
Operational Uptime
The percentage of time that the computing devices were functional and actively operating.
Operational uptime = Minutes with pool reported hash rate / Total minutes
Methane Utilized
The volume of methane gas (CH4) that was harnessed for generation, measured in Standard Cubic Feet (SCF).
CH4 utilized (SCF) = Average petahash (PH/s) × Methane utilization rate (SCF/PH/s/Day) × Days
Carbon Dioxide Equivalent Emissions (C02e)
CO2e quantifies the global warming impact of various greenhouse gases, like methane, by comparing their effect to that of an equivalent amount of carbon dioxide. This comparison is based on each gas’s Global Warming Potential (GWP), a factor that represents the comparative warming effect of a unit of the gas relative to the same unit of CO2 over a specific time frame. We used a GWP timeline of 20 years (factor: 84) and 100 years (factor: 28).
C02e = CH4 pounds utilized * GWP factor
Note: We assumed one SCF of CH4 equals 0.045 pounds at one atmosphere and 80 degrees Fahrenheit.
Average Fuel Cost per Kilowatt-hour (kWh)
The average cost of electricity per kWh includes operational and maintenance expenses.
Average Fuel Cost per kWh =
(SCF × 0.001002 dekatherms per SCF × methane content percentage × rate per dekatherm / kwh) + (operations and maintenance cost / kWh)
Results
The results presented in this section reflect the first 240 days of the pilot project, spanning from September 27, 2023, to May 24, 2024. It is important to note that these findings do not encompass the entire duration of the project but focus specifically on this period.
Methane Utilized
Over the course of 240 days, we utilized approximately 16.1 million SCF of methane. This figure was estimated from the daily utilization rate, which was approximately 8,400 SCF of methane for each petahash operational.
Had we not harnessed this methane, the landfill would have flared it. While flaring does reduce the global warming potential of methane by converting it into carbon dioxide, it is only about 92% efficient. On average, 8% of flared methane still escapes into the atmosphere. By redirecting the methane to power a reciprocating engine to produce electricity for Nodal’s data center, we achieved a near 100% mitigation efficiency. This approach resulted in us mitigating an additional 672 SCF of methane daily per petahash, which would otherwise not have been mitigated by flaring. In the span of 240 days, we prevented the release of approximately 1.3 million SCF of methane into the atmosphere.
Figure 2: Methane Utilized by Marathon’s and Nodal’s LFG Pilot Project (240 Day Duration)
Source: Nodal Power
Carbon Dioxide Equivalent Impact
To contextualize the environmental impact of our pilot project, we calculated its methane utilization in its carbon dioxide equivalent using a GWP timeline of 20 years and 100 years.
Of the total 16.1 million SCF of methane we utilized, our findings indicate that we helped prevent the release of approximately 60.9 million pounds of C02e using a 20-year GWP timeline and 20.3 million pounds of CO2e using the 100-year GWP timeline.
According to the Environmental Protection Agency (EPA), an average gas-powered passenger car emits about 9,200 pounds of C02 annually. Thus, over the course of 240 days, our project mitigated the equivalent of 6,627 gas-powered passenger cars using the 20-year GWP timeline and 2,209 gas-powered passenger cars using the 100-year GWP timeline.
If we only consider the additional 1.2 million SCF of methane mitigated in addition to flaring, we prevented the release of approximately 4.8 million pounds of C02e using a 20-year GWP timeline and approximately 1.6 million pounds of CO2e using the 100-year GWP timeline. Thus, over the course of 240 days, our project mitigated the equivalent of the yearly emissions from 530 gas-powered passenger cars using the 20-year GWP timeline and 177 gas-powered passenger cars using the 100-year GWP timeline.
Figure 3: Carbon Dioxide Equivalent Methane Utilized by Marathon’s and Nodal’s LFG Pilot Project (240 Day Duration)
Source: Nodal Power
Operational Efficiency and Uptime
We used a reciprocating engine on-site to convert the methane into electricity. This engine produced up to 10,000 BTU per kWh, equating to a conversion efficiency of approximately 34%. Compared to the average coal and existing nuclear power plants, which operate at an efficiency of around 32% and 33%, respectively, Nodal’s generator operated at a slightly higher efficiency.
Figure 4: Efficiency of the Average Natural Gas Power Plants, Existing Nuclear Power Plants, and Coal Power Plants Versus Nodal’s On-Site Reciprocating Generator
Source: Nodal Power, EIA
Figure 5: On-Site Reciprocating Generator and Data Center
Source: Nodal Power
Moreover, to effectively harness the methane for generator use, it underwent treatment through a gas compression and conditioning skid. This crucial step refined and pressurized the methane to meet necessary standards. The extent of treatment depends on the gas quality, directly influenced by the landfill’s organic matter composition. In this particular case, the landfill gas contained approximately 50% methane, resulting in a comparatively lower level of treatment requirement.
Figure 6: Gas Compression and Conditioning Skid
Source: Nodal Power
A key aspect of the project’s success was the landfill’s ability to generate a consistent stream of methane due to its favorable waste composition and volume. Going into the project, we expected an operational uptime of 85%, which is approximately on par with the industry average. However, our pilot exceeded expectations, achieving an uptime of 92%. Downtimes were primarily due to maintenance purposes and were not due to a lack of gas availability.
Figure 7: Average Operational Uptime of Marathon’s and Nodal’s Pilot Project
Source: Nodal Power, TheMinerMag
*The average uptime of digital asset compute providers is based on the average Bitcoin hash rate realization rate. These providers include Iris Energy, Bitdeer Technologies Group, Hive Digital Technologies, Bit Digital, CleanSpark, TeraWulf, Core Scientific, Cipher Mining Technologies, Riot Platforms, Marathon Digital Holdings, Argo Blockchain, Hut 8, and Digihost Technology. The data was accessed on May 28, 2024, and may have changed since then.
Financial Benefits for Marathon, Nodal, and the Landfill
Nodal’s Power Plant generates electricity at a rate of $0.03 per kWh, which includes operational and maintenance costs. This rate is less than half the average $0.08 per kWh paid by the industrial sector.
Figure 8: Average Fuel Costs Including Electricity, Operational, and Maintenance Costs of Marathon’s and Nodal’s LFG Pilot Project
Source: Nodal Power, Hashrate Index
Our pilot project was not eligible for carbon credits or renewable energy credits (RECs), benefits that many similar sites often receive. If we had qualified for these incentives, our computing expenses would have been significantly lower.
Over the 240 days, Marathon and Nodal utilized approximately 1.4 million kWh of electricity, which the landfill was able to generate revenue from. Without Marathon’s and Nodal’s pilot project, the landfill would have flared the excess methane, yielding no additional financial benefit. Faced with limited options, the landfill could either flare the methane without any financial gain or harness it to power an on-site data center. The latter option, as evidenced by the pilot project, not only prevented waste but also turned a previously unprofitable byproduct into a source of revenue.
Conclusion
The results from our pilot project successfully validated our initial theory. Digital asset compute is not only possible but also an economically viable option to reduce methane emissions from landfills. Marathon and Nodal successfully captured methane from a landfill, converted it into electricity, and used it to power Nodal’s data center. For data center operators like Marathon and Nodal, the project was financially advantageous, as we realized a lower-than-industry average cost for computing with reliably high uptime. For the landfill, which previously did not have an incentive to put the methane gas into productive use, digital asset compute provided a catalyst to reduce emissions more effectively by creating a new income stream that otherwise could not have been generated. This project was, indeed, a win-win for all parties involved.
Furthermore, we believe the techniques and insights gained from this project open the door to new opportunities at landfill sites and other industries where we can leverage our energy harvesting technologies to tap underutilized or wasted energy sources and turn them into productive, more sustainable assets.
Click HERE to download a PDF of the full report
Disclaimer: This report is provided for general informational purposes only. The opinions expressed in the report may differ from those expressed by Marathon Digital Holdings (“MDH”), its officers, employees, directors or advisors or their affiliates. The information on this report does not constitute investment, legal, accounting or other advice or information by MDH or its officers, employees, directors or advisors or their affiliates. Information has been obtained from sources believed to be reliable, but MDH or its affiliates do not warrant its completeness or accuracy. Outlooks and past performance are not guarantees of future results. The information in the report may be changed without notice and is not guaranteed to be complete, correct or up-to-date, and may not reflect the most current developments.
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