Btc aquathlon

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The Bitcoin Energy Consumption Index provides the latest estimate of the total energy consumption of the Bitcoin network. NEW RELEASE: “The true costs of digital currencies”, noting that “the total Bitcoin carbon footprint exceeds the total GHG emission reductions of electric vehicles (51.9 Mt CO2 in 2020)” and urging for a more comprehensive view in assessing the externalities of cryptocurrencies (June 2021). Bitcoin’s biggest problem is perhaps not even its massive energy consumption, but the fact most mining facilties in Bitcoin’s network are located in regions (primarily in China) that rely heavily on coal-based power (either directly or for the purpose of load balancing). To put it simply: “coal is fueling Bitcoin” (Stoll, 2019). Determining the exact carbon impact of the Bitcoin network has been a challenge for years. Not only does one need to know the power requirement of the Bitcoin network, but one also need to know where this power is coming from. The location of miners is a key ingredient to know how dirty or how clean the power is that they are using. Just like it’s not easy to find out what machines are active in the Bitcoin network, determining location isn’t an easy feat either. Initially the only information available to this end was the common belief that the majority of miners were located in China. Since we know the average emission factor of the Chinese grid (around 700 grams of carbon dioxide equivalent per kilowatt-hour), this can be used for a very rough approximation of the carbon intensity of the power used for Bitcoin mining. Assuming that 70% of Bitcoin mining is taking place in China, and that 30% of mining is completely clean, this yields a weighted average carbon intensity of 490 g CO2eq/k Wh. This number can subsequently be applied to a power consumption estimate of the Bitcoin network to determine its carbon footprint. Later on, more granular information became available in the Global Cryptocurrency Benchmarking Study by Garrick Hileman and Michel Rauchs from 2017. In this study, they identified facilities representing roughly half of the entire Bitcoin hash rate, with a total (lower bound) consumption of 232 megawatts. Chinese mining facilities were responsible for about half of this, with a lower bound consumption of 111 megawatts. This information can be used to get a more accurate idea of the carbon emission factor in grams of carbon dioxide equivalent per kilowatt-hour (g CO2eq/k Wh) that applies to the electricity used for mining. The table below features a breakdown of the energy consumption of the mining facilities surveyed by Hileman and Rauchs. By applying the emission factors of the respective country’s grid, we find that the Bitcoin network had a weighted average carbon intensity of 475 g CO2eq per k Wh consumed. (This number is currently applied to determine the carbon footprint of the Bitcoin network based on the Bitcoin Energy Consumption Index.) One can argue that specific locations in the listed countries may offer less carbon intense power. In 2018 Bitcoin company Coinshares suggested that the majority of Chinese mining facilities were located in Sichuan province, using cheap hydropower for mining Bitcoin. Subsequent studies have, however, never been able to support this claim and/or found the opposite. Confronted with this evidence, the lead author of the Coinshares paper had to admit “mistakes” were made. The main challenge here is that the production of hydropower (or renewable energy in general) is far from constant. In Sichuan specifically the average power generation capacity during the wet season is three times that of the dry season. Because of these fluctuations in hydroelectricity generation, Bitcoin miners can only make use of cheap hydropower for a limited amount of time. In a study titled “The Carbon Footprint of Bitcoin” (Stoll et al. 2019) properly account for these regional differences (while also introducing a new method to localize miners based on IP-addresses), but still find a weighted average carbon intensity of 480-500 g CO2eq per k Wh for the entire Bitcoin network (in line with previous and more rough estimations). Using a similar approach, Cambridge in 2020 provided a more detailed insight into the localization of Bitcoin miners over time. Charting this data, and adding colors based on the carbon intensity of the respective power grids, we can reveal significant mining activity in highly polluting regions of the world during the Chinese dry season (as shown below). On an annual basis, the average contribution of renewable energy sources therefore remains low. When Cambridge subsequently surveyed miners (also in 2020), respondents indicated only 39% of their total energy consumption actually came from renewables. It is important to realize that, while renewables are an intermittent source of energy, Bitcoin miners have a constant energy requirement. A Bitcoin ASIC miner will, once turned on, not be switched off until it either breaks down or becomes unable to mine Bitcoin at a profit. Because of this, Bitcoin miners increase the baseload demand on a grid. They don’t just consume energy when there is an excess of renewables, but still require power during production shortages. In the latter case Bitcoin miners have historically ended up using fossil fuel based power (which is generally a more steady source of energy). Further substantiation on why Bitcoin and renewable energy make for the worst match can be found in the peer-reviewed academic article “Renewable Energy Will Not Solve Bitcoin’s Sustainability Problem” featured on Joule. With climate change pushing the volatility of hydropower production in places like Sichuan, this is unlikely to get any better in the future. To put the energy consumed by the Bitcoin network into perspective we can compare it to another payment system like VISA for example. According to VISA, the company consumed a total amount of 740,000 Gigajoules of energy (from various sources) globally for all its operations. We also know VISA processed 138.3 billion transactions in 2019. This means that VISA has an energy need equal to that of around 19,304 U. With the help of these numbers, it is possible to compare both networks and show that Bitcoin is extremely more energy intensive per transaction than VISA. The difference in carbon intensity per transaction is even greater (see footprints), as the energy used by VISA is relatively “greener” than the energy used by the Bitcoin mining network. The carbon footprint per VISA transaction is only 0.45 grams CO2eq. Of course, VISA isn’t perfectly representative for the global financial system. But even a comparison with the average non-cash transaction in the regular financial system still reveals that an average Bitcoin transaction requires several thousands of times more energy. One key reason why the CO2 emissions per Bitcoin transaction can be so extreme is that the underlying blockchain isn’t just built on an energy-demanding algorithm, but it’s also extremely limited in terms of transaction processing capacity. A block for Bitcoin’s blockchain can contain 1 megabyte of data. As a new block will be generated only once every 10 minutes on average, this data limit prevents the network from handling more than 7 transactions per second. In the most optimistic scenario Bitcoin could therefore theoretically handle around 220 million transactions annually. Meanwhile, the global financial system is handling more than 700 billion digital payments per year (and a payment provider like VISA can handle over 65,000 per second if needed). Bitcoin’s maximum transaction capacity represents only 0.03% of this (rapidly growing) number. This is less than the total number of electronic payments processed in a country like Hungary (more than 300 million per year), not even considering that cash still makes up for two thirds of all payment transactions here. With such an incredibly low limit, Bitcoin is simply incapable of achieving any form of mainstream adoption as a global currency and/or payment system. Unlike the network’s transaction limit, the energy consumption of the network isn’t capped. The price of Bitcoin is the main driver of the network’s environmental impact, and there’s no limit to how high this can go. Because of this, the Bitcoin network can consume several times as much electrical energy as the entire country of Hungary (which consumes 43 TWh annually). Unfortunately for Bitcoin, there’s no real solution for this scalability problem either. Proponents of the digital currency argue that so-called second layer solutions like the Lightning Network will help scaling Bitcoin, while dismissing that it is practically impossible to make such a solution work on a substantial scale. In order to move any amount of funds into the Lightning Network in the first place, a funding transaction on the main network is still required. It would take the Bitcoin network 35 years to process a single funding transaction for all 7.7 billion people (2021) on this planet, ignoring any other possible use of the main network and further population growth in the meanwhile. The only practical solution to Bitcoin’s scalability problem has, so far, been to make use of trusted third parties, as these can process transactions internally without the need to actually use the Bitcoin blockchain. The obvious problem with this is that it merely reinvents the system we already have in place. Because of the aforementioned scalability issues, it’s often argued that Bitcoin is more like “digital gold” than a payment system. Hence we can also compare Bitcoin mining to gold mining instead. Every year, around 3,531 tonnes of gold are mined, with a total related emissions amounting to 81 million metric tonnes of CO2. When comparing this to the carbon intensity of mining Bitcoins, we can observe that the latter exceeds that of mining real gold (see below). Note that this includes mined fees, which has no comparison in mining for real gold (as we’d have to put previously mined gold back into the ground). Likewise, the comparison is also flawed because we can stop mining for real gold, whereas Bitcoin would simply stop existing without active mining. One could argue that this is simply the price of a transaction that doesn’t require a trusted third party, but this price doesn’t have to be so high as will be discussed hereafter. Proof-of-work was the first consensus algorithm that managed to prove itself, but it isn’t the only consensus algorithm. More energy efficient algorithms, like proof-of-stake, have been in development over recent years. In proof-of-stake coin owners create blocks rather than miners, thus not requiring power hungry machines that produce as many hashes per second as possible. Because of this, the energy consumption of proof-of-stake is negligible compared to proof-of-work. Bitcoin could potentially switch to such an consensus algorithm, which would significantly improve environmental sustainability. It is estimated that a switch to proof-of-stake could save 99.95% of the energy currently required to run a proof-of-work based system. Even though the total network hashrate can easily be calculated, it is impossible to tell what this means in terms of energy consumption as there is no central register with all active machines (and their exact power consumption). In the past, energy consumption estimates typically included an assumption on what machines were still active and how they were distributed, in order to arrive at a certain number of Watts consumed per Gigahash/sec (GH/s). A detailed examination of a real-world Bitcoin mine shows why such an approach will certainly lead to underestimating the network’s energy consumption, because it disregards relevant factors like machine-reliability, climate and cooling costs. This arbitrary approach has therefore led to a wide set of energy consumption estimates that strongly deviate from one another, sometimes with a disregard to the economic consequences of the chosen parameters. The Bitcoin Energy Consumption Index therefore proposes to turn the problem around, and approach energy consumption from an economic perspective. The index is built on the premise that miner income and costs are related. Since electricity costs are a major component of the ongoing costs, it follows that the total electricity consumption of the Bitcoin network must be related to miner income as well. To put it simply, the higher mining revenues, the more energy-hungry machines can be supported. How the Bitcoin Energy Consumption Index uses miner income to arrive at an energy consumption estimate is explained in detail here (also in peer-reviewed academic literature here), and summarized in the following infographic: Bitcoin miner earnings and (estimated) expenses are currenly as follows: Note that one may reach different conclusions on applying different assumptions (a calculator that allows for testing different assumptions has been made available here). The chosen assumptions have been chosen in such a way that they can be considered to be both intuitive and conservative, based on information of actual mining operations. In the end, the goal of the Index is not to produce a perfect estimate, but to produce an economically credible day-to-day estimate that is more accurate and robust than an estimate based on the efficiency of a selection of mining machines. The Bitcoin Energy Consumption Index provides the latest estimate of the total energy consumption of the Bitcoin network. NEW RELEASE: “The true costs of digital currencies”, noting that “the total Bitcoin carbon footprint exceeds the total GHG emission reductions of electric vehicles (51.9 Mt CO2 in 2020)” and urging for a more comprehensive view in assessing the externalities of cryptocurrencies (June 2021). Bitcoin’s biggest problem is perhaps not even its massive energy consumption, but the fact most mining facilties in Bitcoin’s network are located in regions (primarily in China) that rely heavily on coal-based power (either directly or for the purpose of load balancing). To put it simply: “coal is fueling Bitcoin” (Stoll, 2019). Determining the exact carbon impact of the Bitcoin network has been a challenge for years. Not only does one need to know the power requirement of the Bitcoin network, but one also need to know where this power is coming from. The location of miners is a key ingredient to know how dirty or how clean the power is that they are using. Just like it’s not easy to find out what machines are active in the Bitcoin network, determining location isn’t an easy feat either. Initially the only information available to this end was the common belief that the majority of miners were located in China. Since we know the average emission factor of the Chinese grid (around 700 grams of carbon dioxide equivalent per kilowatt-hour), this can be used for a very rough approximation of the carbon intensity of the power used for Bitcoin mining. Assuming that 70% of Bitcoin mining is taking place in China, and that 30% of mining is completely clean, this yields a weighted average carbon intensity of 490 g CO2eq/k Wh. This number can subsequently be applied to a power consumption estimate of the Bitcoin network to determine its carbon footprint. Later on, more granular information became available in the Global Cryptocurrency Benchmarking Study by Garrick Hileman and Michel Rauchs from 2017. In this study, they identified facilities representing roughly half of the entire Bitcoin hash rate, with a total (lower bound) consumption of 232 megawatts. Chinese mining facilities were responsible for about half of this, with a lower bound consumption of 111 megawatts. This information can be used to get a more accurate idea of the carbon emission factor in grams of carbon dioxide equivalent per kilowatt-hour (g CO2eq/k Wh) that applies to the electricity used for mining. The table below features a breakdown of the energy consumption of the mining facilities surveyed by Hileman and Rauchs. By applying the emission factors of the respective country’s grid, we find that the Bitcoin network had a weighted average carbon intensity of 475 g CO2eq per k Wh consumed. (This number is currently applied to determine the carbon footprint of the Bitcoin network based on the Bitcoin Energy Consumption Index.) One can argue that specific locations in the listed countries may offer less carbon intense power. In 2018 Bitcoin company Coinshares suggested that the majority of Chinese mining facilities were located in Sichuan province, using cheap hydropower for mining Bitcoin. Subsequent studies have, however, never been able to support this claim and/or found the opposite. Confronted with this evidence, the lead author of the Coinshares paper had to admit “mistakes” were made. The main challenge here is that the production of hydropower (or renewable energy in general) is far from constant. In Sichuan specifically the average power generation capacity during the wet season is three times that of the dry season. Because of these fluctuations in hydroelectricity generation, Bitcoin miners can only make use of cheap hydropower for a limited amount of time. In a study titled “The Carbon Footprint of Bitcoin” (Stoll et al. 2019) properly account for these regional differences (while also introducing a new method to localize miners based on IP-addresses), but still find a weighted average carbon intensity of 480-500 g CO2eq per k Wh for the entire Bitcoin network (in line with previous and more rough estimations). Using a similar approach, Cambridge in 2020 provided a more detailed insight into the localization of Bitcoin miners over time. Charting this data, and adding colors based on the carbon intensity of the respective power grids, we can reveal significant mining activity in highly polluting regions of the world during the Chinese dry season (as shown below). On an annual basis, the average contribution of renewable energy sources therefore remains low. When Cambridge subsequently surveyed miners (also in 2020), respondents indicated only 39% of their total energy consumption actually came from renewables. It is important to realize that, while renewables are an intermittent source of energy, Bitcoin miners have a constant energy requirement. A Bitcoin ASIC miner will, once turned on, not be switched off until it either breaks down or becomes unable to mine Bitcoin at a profit. Because of this, Bitcoin miners increase the baseload demand on a grid. They don’t just consume energy when there is an excess of renewables, but still require power during production shortages. In the latter case Bitcoin miners have historically ended up using fossil fuel based power (which is generally a more steady source of energy). Further substantiation on why Bitcoin and renewable energy make for the worst match can be found in the peer-reviewed academic article “Renewable Energy Will Not Solve Bitcoin’s Sustainability Problem” featured on Joule. With climate change pushing the volatility of hydropower production in places like Sichuan, this is unlikely to get any better in the future. To put the energy consumed by the Bitcoin network into perspective we can compare it to another payment system like VISA for example. According to VISA, the company consumed a total amount of 740,000 Gigajoules of energy (from various sources) globally for all its operations. We also know VISA processed 138.3 billion transactions in 2019. This means that VISA has an energy need equal to that of around 19,304 U. With the help of these numbers, it is possible to compare both networks and show that Bitcoin is extremely more energy intensive per transaction than VISA. The difference in carbon intensity per transaction is even greater (see footprints), as the energy used by VISA is relatively “greener” than the energy used by the Bitcoin mining network. The carbon footprint per VISA transaction is only 0.45 grams CO2eq. Of course, VISA isn’t perfectly representative for the global financial system. But even a comparison with the average non-cash transaction in the regular financial system still reveals that an average Bitcoin transaction requires several thousands of times more energy. One key reason why the CO2 emissions per Bitcoin transaction can be so extreme is that the underlying blockchain isn’t just built on an energy-demanding algorithm, but it’s also extremely limited in terms of transaction processing capacity. A block for Bitcoin’s blockchain can contain 1 megabyte of data. As a new block will be generated only once every 10 minutes on average, this data limit prevents the network from handling more than 7 transactions per second. In the most optimistic scenario Bitcoin could therefore theoretically handle around 220 million transactions annually. Meanwhile, the global financial system is handling more than 700 billion digital payments per year (and a payment provider like VISA can handle over 65,000 per second if needed). Bitcoin’s maximum transaction capacity represents only 0.03% of this (rapidly growing) number. This is less than the total number of electronic payments processed in a country like Hungary (more than 300 million per year), not even considering that cash still makes up for two thirds of all payment transactions here. With such an incredibly low limit, Bitcoin is simply incapable of achieving any form of mainstream adoption as a global currency and/or payment system. Unlike the network’s transaction limit, the energy consumption of the network isn’t capped. The price of Bitcoin is the main driver of the network’s environmental impact, and there’s no limit to how high this can go. Because of this, the Bitcoin network can consume several times as much electrical energy as the entire country of Hungary (which consumes 43 TWh annually). Unfortunately for Bitcoin, there’s no real solution for this scalability problem either. Proponents of the digital currency argue that so-called second layer solutions like the Lightning Network will help scaling Bitcoin, while dismissing that it is practically impossible to make such a solution work on a substantial scale. In order to move any amount of funds into the Lightning Network in the first place, a funding transaction on the main network is still required. It would take the Bitcoin network 35 years to process a single funding transaction for all 7.7 billion people (2021) on this planet, ignoring any other possible use of the main network and further population growth in the meanwhile. The only practical solution to Bitcoin’s scalability problem has, so far, been to make use of trusted third parties, as these can process transactions internally without the need to actually use the Bitcoin blockchain. The obvious problem with this is that it merely reinvents the system we already have in place. Because of the aforementioned scalability issues, it’s often argued that Bitcoin is more like “digital gold” than a payment system. Hence we can also compare Bitcoin mining to gold mining instead. Every year, around 3,531 tonnes of gold are mined, with a total related emissions amounting to 81 million metric tonnes of CO2. When comparing this to the carbon intensity of mining Bitcoins, we can observe that the latter exceeds that of mining real gold (see below). Note that this includes mined fees, which has no comparison in mining for real gold (as we’d have to put previously mined gold back into the ground). Likewise, the comparison is also flawed because we can stop mining for real gold, whereas Bitcoin would simply stop existing without active mining. One could argue that this is simply the price of a transaction that doesn’t require a trusted third party, but this price doesn’t have to be so high as will be discussed hereafter. Proof-of-work was the first consensus algorithm that managed to prove itself, but it isn’t the only consensus algorithm. More energy efficient algorithms, like proof-of-stake, have been in development over recent years. In proof-of-stake coin owners create blocks rather than miners, thus not requiring power hungry machines that produce as many hashes per second as possible. Because of this, the energy consumption of proof-of-stake is negligible compared to proof-of-work. Bitcoin could potentially switch to such an consensus algorithm, which would significantly improve environmental sustainability. It is estimated that a switch to proof-of-stake could save 99.95% of the energy currently required to run a proof-of-work based system. Even though the total network hashrate can easily be calculated, it is impossible to tell what this means in terms of energy consumption as there is no central register with all active machines (and their exact power consumption). In the past, energy consumption estimates typically included an assumption on what machines were still active and how they were distributed, in order to arrive at a certain number of Watts consumed per Gigahash/sec (GH/s). A detailed examination of a real-world Bitcoin mine shows why such an approach will certainly lead to underestimating the network’s energy consumption, because it disregards relevant factors like machine-reliability, climate and cooling costs. This arbitrary approach has therefore led to a wide set of energy consumption estimates that strongly deviate from one another, sometimes with a disregard to the economic consequences of the chosen parameters. The Bitcoin Energy Consumption Index therefore proposes to turn the problem around, and approach energy consumption from an economic perspective. The index is built on the premise that miner income and costs are related. Since electricity costs are a major component of the ongoing costs, it follows that the total electricity consumption of the Bitcoin network must be related to miner income as well. To put it simply, the higher mining revenues, the more energy-hungry machines can be supported. How the Bitcoin Energy Consumption Index uses miner income to arrive at an energy consumption estimate is explained in detail here (also in peer-reviewed academic literature here), and summarized in the following infographic: Bitcoin miner earnings and (estimated) expenses are currenly as follows: Note that one may reach different conclusions on applying different assumptions (a calculator that allows for testing different assumptions has been made available here). The chosen assumptions have been chosen in such a way that they can be considered to be both intuitive and conservative, based on information of actual mining operations. In the end, the goal of the Index is not to produce a perfect estimate, but to produce an economically credible day-to-day estimate that is more accurate and robust than an estimate based on the efficiency of a selection of mining machines.

date: 02-May-2021 11:22next


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