Policy assessments for the carbon emission flows and sustainability of Bitcoin blockchain operation in China

The increasing popularity of blockchain technology, driven by Bitcoin's success, has raised concerns about its significant energy consumption and associated carbon emissions. This paper focuses on quantifying the current and future carbon emission patterns of Bitcoin blockchain operations in China under various carbon policies. The study leverages a system dynamics (SD) based model, the Bitcoin blockchain carbon emission model (BBCE), which offers advantages in capturing the complex, endogenous dynamics of the system and evaluating policy effectiveness. The BBCE model is built upon the theory of carbon footprint, considering three interacting subsystems: Bitcoin blockchain mining and transaction, energy consumption, and carbon emission. The model incorporates factors like network hash rate, power usage efficiency (PUE), electricity price, miner profit rate, and the Bitcoin reward halving mechanism. Understanding the carbon footprint of Bitcoin mining in China is particularly crucial given China's significant role in Bitcoin mining (accounting for over 75% of global hashing power) and its commitment to emission reduction targets under the Paris Agreement. The research aims to assess the impact of different policies on mitigating the environmental impact of Bitcoin mining in China.

Existing literature highlights the significant energy consumption of the Bitcoin blockchain, comparing its annual energy usage to that of small to medium-sized countries. Studies have estimated considerable CO2 emissions linked to Bitcoin mining, though estimates vary. The growing energy consumption and environmental impact pose a challenge, particularly for China, a major energy consumer and signatory to the Paris Agreement. Previous research has utilized system dynamics (SD) modeling for carbon emission flow estimation in various sectors, appreciating its ability to capture complex system dynamics and evaluate policy impacts. This study builds upon this approach to model the specific case of Bitcoin mining in China.

The study develops a Bitcoin blockchain carbon emission model (BBCE) using system dynamics modeling. The model consists of three interconnected subsystems: Bitcoin mining and transactions, energy consumption, and carbon emissions. The model incorporates various factors such as network hash rate, power usage efficiency, electricity prices, miner profit rates, the Bitcoin reward halving mechanism, and the location of mining operations (coal-based vs. hydro-based regions). Four scenarios are simulated: a benchmark scenario with minimal policy intervention, and three policy scenarios: market access restrictions, site regulation (encouraging relocation to hydro-rich areas), and increased carbon tax. The model considers the interplay of various factors, including the competitive nature of Bitcoin mining (Proof-of-Work), miner profitability, investment decisions, and the impact of different energy sources on carbon emissions. The model is parameterized using data from various sources including btc.com (for network hash rate, block size, transaction fees, and difficulty), the World Bank (for energy costs and carbon taxation), and the China Emission Accounts & Datasets (CEADS) for domestic emission data. The model simulations run from 2014 to 2030, allowing for an assessment of the long-term impacts of various policies.

The benchmark scenario projects a peak annual energy consumption of 296.59 Twh and 130.50 million metric tons of carbon emissions in 2024. This surpasses the energy consumption of countries like Italy and Saudi Arabia and the annual greenhouse gas emissions of countries such as the Czech Republic and Qatar. Domestically, the emissions would rank among the top 10 emitters in China. The carbon tax scenario shows only a limited reduction in energy demand and emissions. The market access scenario, while aiming to improve efficiency by restricting low-efficiency miners, surprisingly leads to an increase in emissions due to increased competition among remaining miners. Conversely, the site regulation scenario, which encourages miners to relocate to hydro-rich areas, demonstrates significant reductions in carbon emissions, despite a slightly higher energy consumption. The analysis also shows that the carbon emission per GDP of Bitcoin mining far exceeds the average industrial carbon intensity of China, highlighting its high carbon-intensive nature. The peak carbon emission per GDP is estimated at 10.77 kg/USD in the benchmark scenario, significantly higher than in other scenarios. The study emphasizes the need for separate accounting for Bitcoin industry emissions to improve policy management.

The findings highlight the ineffectiveness of solely relying on carbon taxation to address the environmental impact of Bitcoin mining. The market access policy demonstrates unintended consequences, showing that improving miner efficiency alone may not reduce overall emissions due to increased competition. In contrast, the site regulation policy proves to be the most effective strategy, illustrating the importance of considering energy source and geographic location in emission reduction efforts. The study underscores the high carbon intensity of Bitcoin mining, exceeding the average industrial carbon intensity in China. This necessitates specific policy interventions tailored to the unique characteristics of the Bitcoin industry. The high energy consumption and emission levels indicate a trade-off between the advantages of blockchain technology and its environmental impact, demanding further research on more sustainable consensus mechanisms. The paper concludes that the current Proof-of-Work consensus algorithm used in Bitcoin presents a significant environmental challenge and needs to be addressed for the technology to be sustainable.

This research provides a comprehensive analysis of Bitcoin's carbon footprint in China under different policy scenarios. The results demonstrate that site regulation, which influences the energy mix used in mining, is a more effective strategy compared to carbon taxation or market access controls. The high carbon intensity of Bitcoin mining, even under policy interventions, highlights the urgency of developing more sustainable blockchain technologies. Future research should explore alternative consensus mechanisms and the incorporation of more detailed economic factors into the model.

The study's projections rely on several assumptions, including a linear increase in Bitcoin price based on the halving mechanism, and the absence of relocation costs for miners. Furthermore, the model doesn't incorporate potential future changes in China's energy mix, which may shift towards more renewable sources. These assumptions could influence the accuracy of the long-term projections. The model also assumes full investment intensity by miners while in operation, which may not always be the case in reality.