The researchers behind the famous Cambridge Bitcoin Electricity Consumption Index (CBEC) officially revised its calculation methodology for the first time since its launch in 2019 to improve the accuracy and reliability of the index’s estimates.
Launched in July 2019, CBECI aims to provide solid data-driven insights into questions about the energy-intensive nature of Bitcoin mining and the associated environmental impacts.
Speaking exclusively to Cointelegraph ahead of announcing the revisions, lead researcher Alexander Neumueller explained the index’s role in providing a relatively accurate estimate of the Bitcoin (BTC) network’s power consumption and contextualizing the data in a way that ordinary people can easily understand. .
Key takeaways from the revised methodology include focusing on recent developments in Bitcoin mining hardware and hashrate, and whether CBECI accurately reflects the changing landscape. The researchers delved into the issue of the massive increase in hash rate that has occurred in recent years as newer mining equipment surpassed older models in computing power.
Related: Nuclear and Natural Gas Are Fastest-Growing Energy Sources for Bitcoin Mining: Data
Neumueller and his fellow researchers note that the scarcity of hardware-related data poses a major challenge because it limits CBECI’s ability to accurately assess the type of hardware miners are using and how common it is.
This led the researchers to previously create a method for simulating everyday hardware distribution based on performance and power consumption data from real hardware. Neumeuller noted that the backbone of the previous CBECI methodology assumed that every profitable hardware model released five years ago contributed equally to the total network hash rate.
This in turn results in a “disproportionately large” amount of old mining hardware compared to the newer models in the hardware distribution during the unusually profitable mining period that the method assumes.
RELATED: Iris Energy Buys 248 $10M Nvidia GPUs to Generate AI and Bitcoin Mining
The researchers then found that recently released devices appeared to be underrepresented, while devices nearing the end of their life cycle were overrepresented. This prompted a change in the CBECI methodology.
Neumeller then explained how his team began comparing hashrate growth to U.S. import data that reflects recent deliveries of bitcoin mining hardware. This was combined with an examination of public sales data from mining hardware manufacturer Canaan.
The analysis considered a number of in-depth factors and was used to test the hypothesis that the increase in the network’s hash rate can be attributed to recently released mining hardware.
“This assumption is based on U.S. import data, and we seek more evidence to verify it. If Canaan’s sales data is industry-representative, it confirms the statement.”
Neumueller highlighted the divide in opinion, with critics arguing that bitcoin “harms environmental progress and could exacerbate climate change,” while proponents argue that mining can combat climate change and provide other social benefits.
“However, the complexities of the industry and the lack of information are often underappreciated, leaving room for curated data points and biased viewpoints.”
CBECI includes a wealth of data points and visualizations, including the index’s Bitcoin network electricity demand, a mining map reflecting the geographic distribution of Bitcoin mining hashrate, and a greenhouse gas emissions index.
CBECI and the GHG Emissions Index provide three different estimates for these two sectors, providing ranges of assumptions for these specific indicators.
Bookmark this article as an NFT Preserve this moment in history and show your support for independent journalism in the cryptocurrency space.
Magazine: Recursive Inscription: Bitcoin ‘Supercomputer’ and BTC DeFi Coming Soon
Svlook
