# The Environmental Stake of Bitcoin Mining: Present and Future Challenges
## 3 Results and Discussion  
### Carbon Emission Estimations  
The GWP estimated for the baseline scenario is 51.7 Mt CO\({}_{2}\) eq/year, an amount like the 2022 total carbon emissions of Singapore (53.25 Mt CO\({}_{2}\) eq) [67]. The values were derived as 98% from the USA (35.8%) and China (37.4%), which overcomes the USA despite the lower EffH, and Kazakhstan (24.8%). The estimated GWP emission can be compared with some important industrial chemical productions such as those for ammonia and methanol. By taking as a reference the GWP estimated for the baseline scenario 2022 (51.7 Mt CO\({}_{2}\) eq/year) and the carbon emissions of 1 kg of ammonia (Ammonia, anhydrous, liquid | RER\(|\) market for ammonia, anhydrous, liquid | APOS, U, 2.87 kg CO\({}_{2}\) eq/kg) and methanol (Methanol | RER\(|\) market for methanol | APOS, U, 0.96 kg CO\({}_{2}\) eq/kg) reported in the ecoinvent database [54], it is possible to estimate that, in 2022, the carbon emission predicted corresponds to the production of about 18 Mt of ammonia or 54 Mt of methanol, corresponding to the 12% and 49% of the worldwide production for 2022 of such chemicals, respectively [68; 69]. Concerning the electricity mix projected variations, assuming that in 2030 and 2050, the EffH of Bitcoin mining would remain the same as in 2022 (i.e., 95.53 TWh), GWP is estimated to reduce as follows: \(-\)17.5% (2030 BAD), \(-\)11.9% (2030 IRENA), \(-\)37.6% (2030 EMBER), \(-\)54.5% (2050 BAD) and \(-\)72.3% (2050 IRENA and EMBER). Figure 2(a) displays the GWP values (y axis) estimated according to future projections (x axis) and changes in EfH (z axis). Figure 2(b) depicts pie charts containing the same values presented in the histograms of Figure 2(a) but including the contribution of each country in the estimated values. The contribution of the country reflects both the amount of EfH consumed in the country and the electricity mix. Kazakhstan, the United States, and China emerge as the main GWP hotspots, contributing 24.8%, 35.8%, and 37.4% of the GWP\({}_{\text{tot}}\) in 2022, respectively. These countries were also characterized by the highest EfH scores. Moreover, according to our estimates, China and Kazakhstan were also characterized by the highest carbon intensities of national electricity, with 0.88 kg CO\({}_{2}\) eq/kWh and 0.93 kg CO\({}_{2}\) eq/kWh, respectively. By assuming that the EfH sharing will remain constant in the next few decades, the cumulative contribution of the remaining countries (i.e., Canada, Russia, Germany, Malaysia and Ireland) is expected to be \(<\)2% of GWP\({}_{\rm tot}\). Assuming maintenance of the same electricity mix, the GWP ranges from a minimum of 36.6 Mt CO\({}_{2}\) eq (\(-\)10% EffH) to a maximum of 127.2 Mt CO\({}_{2}\) eq (\(+\)100% EffH). In the 2030 BAD Scenario, the GWP ranges from a minimum of 24.7 Mt CO\({}_{2}\) eq (\(-\)10% EffH) to a maximum of 120.0 Mt CO\({}_{2}\) eq (\(+\)100% EffH) while, in the 2050 BAD scenario, the GWP ranges from a minimum of 12.4 Mt CO\({}_{2}\) eq (\(-\)10% EffH) to a maximum of 66.2 kg CO\({}_{2}\) eq (\(+\)100% EffH). The results are reported in Tables S4-S10 with a higher level of detail. On the other hand, considering the two estimated EfH values obtained by extrapolating the CBECI data to 2030 according to the two proposed models (linear model: 232 \(\pm\) 25 TWh; quadratic model: 334 \(\pm\) 19 TWh) described in Section 2.2.3, the BAD, IRENA, and EMBER scenarios for 2030 in terms of carbon emissions can be determined. Accounting for the increased values of EfH starting from 2022, the determined linear regression models within each of these scenarios are shown in Figure 4 (see Table S13 for the corresponding linear regression models). Their values range (predicted intervals) from 143 \(\pm\) 2 TWh and 226 \(\pm\) 3 TWh for the 2030 EMBER scenario to 154 \(\pm\) 1 and 234 \(\pm\) 1 TWh for 2030 IRENA, and this latter almost overlapped with the results for the BAD scenario (153 \(\pm\) 1 TWh and 236 \(\pm\) 2 TWh). These findings allow us to make some considerations:  
1.