Bitcoin mining represents 0.1% of global greenhouse gas emissions, study finds

THE BLOCKPublished on 2022-09-27Last updated on 2022-09-27

Abstract

Bitcoin mining accounts for roughly 0.10% of global greenhouse gas emissions, a new report from the Cambridge Centre for Alternative Finance (CCAF) found.

Bitcoin mining accounts for roughly 0.10% of global greenhouse gas emissions, a new report from the Cambridge Centre for Alternative Finance (CCAF) found.
That figure amounts to 48.35 million tons of carbon dioxide annually, per the report. The institute also estimated that 37.6% of the energy used by the industry comes from sustainable sources, according to the data published Tuesday.
The numbers are based on the geographical distribution of bitcoin mining in January. CCAF took its most recent data and combined it with public information on how electricity is being generated in different regions.
It's important to note that the numbers don't capture "activities that might be expected to reduce emissions," like the use of flare gas, energy produced behind the meter, and waste heat recovery.
"We're simply lacking the data to capture that," said Alexander Neumueller, Cambridge Bitcoin Electricity Consumption Index's project lead and author of the report.
CCAF's estimate on the percentage of sustainable energy use contrasts with the 59.5% that the Bitcoin Mining Council came up with in reference to the second quarter of 2022 after surveying mining companies.
The report addressed the discrepancy between those who believe bitcoin will undo environmental progress and those who, on the contrary, think it might help combat climate change.
"Observing the arguments of both sides, some claims seem rather far-fetched and based on over-simplifications, while others are based on scant information," the report says. "Interest groups on both sides are vying for interpretive authority to sway public opinion in their favour (sic) and persuade policymakers as to the necessity of regulations."
A White House report on crypto assets and climate published earlier this month encouraged regulators to work towards reducing greenhouse gas emissions and stated that the administration or Congress might consider restrictions down the line if all else fails. On the other hand, it suggested that certain types of energy used to power bitcoin mines could have a positive impact on emissions.
In response to the White House report, Marathon CEO Fred Thiel said that U.S. regulators should create incentives for bitcoin miners to use renewable energy and disincentives for fossil fuel-based sources.
Emission decrease
The current annual estimate of greenhouse gas emissions from bitcoin mining (as of Sept. 21) is 14.1% lower than in 2021, according to CCAF's findings.
"A significant decrease in mining profitability led to a decline in electricity consumption despite substantial increases in hashrate," the report says.
It points towards a possible increase in the efficiency of mining hardware, as the revenue decline encourages miners to retire older and less efficient hardware.
"Even if the hashrate is increasing, this does not necessarily translate into increased demand of electricity consumption if the efficiency of the devices is increasing," Neumueller said. "Miners are rational economic agents. They would not run something just for running. They would turn off machines that are not profitable and then continue with the more profitable ones."

Related Reads

Beyond the Model Lies the Harness: Deepseek Enters the Arena, Why Has the Main Battlefield of China's AI Competition Shifted?

In mid-to-late May 2026, Deepseek internally established a new Harness team focused on code agent products, internally benchmarked against Anthropic's Claude Code. This move, marked by the formula "Model + Harness = Agent" in their job postings, signals a major shift in China's AI competition: the main battlefield is transitioning from developing large models to building toolchains and achieving workplace integration. Deepseek's direct involvement in Harness development aims to secure control over interface design and training data feedback loops, moving beyond open-sourcing powerful models. Harness, the runtime infrastructure for AI agents, handles everything beyond model reasoning—task orchestration, tool calling, context management, safety checks, and error recovery. It is crucial because agent products are not just outputs of model capability but also training grounds for it. Real-world task failures recorded by Harness can feed back into model training, creating a flywheel effect. Engineering Harness is more critical than optimizing prompts, as poor context management or error handling can drastically reduce agent success rates in multi-step, real-world scenarios. This shift is not isolated. Other major Chinese tech companies are also pursuing differentiated toolchain strategies. Tencent leverages its enterprise ecosystem (WeChat Work, Tencent Cloud) to build connectors for organizational-level AI collaboration and complex task delivery. Alibaba focuses on lowering automation barriers on the web with a front-end, browser-based GUI Agent framework, PageAgent. This diversification shows the industry recognizes that success lies not in a perfect general agent, but in vertically focused solutions built with robust engineering. The trend is validated by overseas success, such as Poland's Viktor, an AI coworker on Slack achieving $20M ARR by autonomously executing complex, multi-step tasks. This proves a shift in enterprise willingness to pay—from "AI-assisted generation" to "AI-autonomous execution." As Harness matures to provide safety guards and reliability, AI transitions from a human-supervised intern to an independent outsourcer. The competition now faces key engineering challenges: preventing "token explosion" through intelligent context compression, and building "thick frameworks" with features like sandbox isolation and checkpoint recovery for enterprise-grade stability. Geopolitical restrictions on tools like Claude Code further create a significant market vacuum for domestic solutions like Deepseek's Harness. For enterprises and developers, the focus must shift from comparing model benchmarks to evaluating a vendor's engineering capabilities, error recovery mechanisms, context management, and ecosystem compatibility when choosing AI products and platforms.

marsbit36m ago

Beyond the Model Lies the Harness: Deepseek Enters the Arena, Why Has the Main Battlefield of China's AI Competition Shifted?

marsbit36m ago

Soaring Export Data for Memory Chips, Market Is Redefining the Valuation Anchor for Memory Stocks

Korean storage export data for the first 20 days of June shows substantial year-on-year increases in both value and price-per-kilogram for categories like DRAM, NAND, and SSDs. This signals a potential shift beyond simple demand recovery, indicating rising prices and a product mix shift towards higher-value items, possibly influenced by AI infrastructure needs. A key point is that the surge in price-per-kilogram is not simply a uniform chip price hike. It reflects a combination of actual price increases and, more importantly, an export structure increasingly dominated by high-value-density products like HBM (High-Bandwidth Memory) and advanced DRAM, which are critical for AI servers. This suggests AI-driven demand may be spilling over from just HBM into broader memory markets. SK Hynix stands to benefit directly due to its leading HBM position. For Samsung and Micron, the implication is potential for greater margin elasticity if the tightness in high-end memory spreads to enterprise SSD and NAND prices. However, the storage sector remains cyclical. Risks include supply expansion, inventory changes, and potential slowdowns in broader AI capital expenditure. Ultimately, while the strong export data supports upward revisions for storage company earnings and fuels discussion of an "AI infrastructure bottleneck premium," a definitive valuation shift from a cyclical to a structural story depends on upcoming quarterly reports. Investors need confirmation from SK Hynix, Samsung, and Micron that improvements in average selling prices, product mix, and, crucially,毛利率 are sustained over multiple quarters.

marsbit2h ago

Soaring Export Data for Memory Chips, Market Is Redefining the Valuation Anchor for Memory Stocks

marsbit2h ago

Trading

Spot
Futures
活动图片