*3.3. Overall Results Analysis*

It can be concluded that Bitcoin energy consumption (represented by the BECI LB) exhibits strong traces of long memory, with 90% of the feature (i.e., Hurst exponent) scoring over 0.85 with the same argument. Both the fractional integration parameter, d, and the measurement of long memory, H, provide enough evidence of true long memory with mean-reverting traits in the Bitcoin carbon footprint (as represented by BECI LB). Hence, Bitcoin's electricity consumption-led carbon footprint has an overall persistent pattern, with varying degrees across different window sizes. These findings complement the existing literature [36–39], and provide evidence for the suitability of applying permanent policy implications to address the carbon footprint of Bitcoin mining. The MFDFA findings were consistent with FMH and were found to be more realistic; they uncover a higher degree of long memory over FIGARCH (the traditional model in accordance with EMH).
