Machine Learning the Carbon Footprint of Bitcoin Mining

Calvo-Pardo, H. ; Mancini, T. ; Olmo, J.

Resumen: Building on an economic model of rational Bitcoin mining, we measured the carbon footprint of Bitcoin mining power consumption using feed-forward neural networks. We found associated carbon footprints of 2.77, 16.08 and 14.99 MtCO2 e for 2017, 2018 and 2019 based on a novel bottom-up approach, which (i) conform with recent estimates, (ii) lie within the economic model bounds while (iii) delivering much narrower prediction intervals and yet (iv) raise alarming concerns, given recent evidence (e.g., from climate–weather integrated models). We demonstrate how machine learning methods can contribute to not-for-profit pressing societal issues, such as global warming, where data complexity and availability can be overcome.

Idioma: Inglés

DOI: 10.3390/jrfm15020071

Año: 2022

Publicado en: Journal of Risk and Financial Management 15, 2 (2022), 71 [30 pp.]
ISSN: 1911-8074

Factor impacto CITESCORE: 0.7 - Economics, Econometrics and Finance (Q4) - Business, Management and Accounting (Q4)

Factor impacto SCIMAGO: 0.258 - Accounting (Q3) - Finance (Q3) - Economics and Econometrics (Q3) - Business, Management and Accounting (miscellaneous) (Q3)

Tipo y forma: Artículo (Versión definitiva)