Exploring Relationships among Bitcoin’s Market Price, Energy Consumption and Carbon Dioxide Emissions: A Machine Learning Approach

The cryptocurrency boom has resulted in a substantial rise in energy usage and carbon emissions. The mining process of Bitcoin is notorious for its energy intensive process because it requires huge computational power. The carbon footprint of Bitcoin mining is a growing concern that’s why we have to analyze the number of CO2 emissions resulting from the mining procedure. In this study, we have utilized machine learning techniques to examine the number of CO2 emissions generated by Bitcoin mining, analyzed the correlations between Bitcoin price, electricity consumption, and CO2 emissions, and pinpoint the factors during the process of Bitcoin mining that leads to CO2 emissions. We gathered global data set on Bitcoin electricity consumption, prices, and CO2 emissions. We trained supervised machine learning model (Regression) in Python to analyze and investigate the data. Our research findings have great implications for policymakers and researchers worried about the impact of the latest technologies on the environment, and in future Bitcoin policies and practices; they should prioritize sustainability and reduce the carbon footprint of mining operations. In the end, our research will provide valuable insights into the environmental impact of Bitcoin mining, highlight the factors that cause CO2 emissions and underscored the need for further research and action to reduce the carbon footprint of cryptocurrencies.