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The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO2 eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO2 equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers.

Solid sorbents based on silica and polyethyleneimine (PEI) are intensively investigated in the field of carbon capture and storage (CCS). Pyrolysis was proposed as a thermal process to recover the pure silica from exhausted sorbents and convert PEI into potentially useful products, such as alkylated pyrazines. A GC–MS method based on internal standardisation with 2-methoxypyrazine was developed and evaluated to determine the concentration of six pyrazines in the pyrolysis oils of exhausted silica-PEI sorbent pyrolysed at 400, 500, 600 and 650 °C. The most abundant pyrazines were 2-ethyl and 2,3-dimethyl, occurring at concentrations of 5–28 mg g–1, followed by pyrazine, 2-methyl, 2-ethyl-3-methyl and 2-propylpyrazine. The GC–MS results were compared to those from a HPLC-DAD method using the Welch's test. The 37 % discrepancy of concentrations was attributed to spectral interference in LC-DAD. GC was slightly less precise than HPLC, calibration errors were lower and enabled the identification of highly alkylated pyrazines. Both methods provided comparable values of total pyrazine yields (around 4–7 % by weight).