Jan. 20, , was the first time the Bitcoin network saw a block that was over 2MB, when block came in at MB, and similar to block , the block had a relatively low number of transactions compared to an average block on the Bitcoin network. Block only contained transactions — about 15 percent of the usual amount of. rows · timberlandschuheherren.de Monitor Health provides key metrics for the system performance and . 2 days ago · Current Fee Estimates API Call API Docs High Priority ( blocks) Medium Priority ( blocks) Low Priority (7+ blocks) BTC/KB BTC/KB BTC/KB Fee estimates are based on a rolling, weighted average. You can also embed data into the Bitcoin blockchain.
Current bitcoin network statusBitcoin Block Explorer | BlockCypher
Denmark Iran, Islamic Republic of Indonesia Bahrain Greece Turkey Thailand Estonia Moldova, Republic of Latvia Iceland Belarus 9. Croatia 9. Kazakhstan 7. Colombia 6. Luxembourg 6. Venezuela 4. Philippines 4. United Arab Emirates 4. Vietnam 4. Gibraltar 3. Ecuador 3. Saudi Arabia 3. Bermuda 2. Costa Rica 2.
Kyrgyzstan 2. Cambodia 2. Andorra 2. Virgin Islands, U. Bosnia and Herzegovina 1. Bolivia 1. Reunion 1. Guatemala 1. Paraguay 1. Montenegro 1. Uruguay 1. Uzbekistan 1. Isle of Man 1. Faroe Islands 1. Seychelles 1. Dominican Republic 1. Algeria 1. Saint Lucia 1. Liechtenstein 1.
Armenia 1. Aland Islands 1. 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 Bitcoin company Coinshares suggested that the majority of Chinese mining facilities were located in Sichuan province, using cheap hydropower for mining Bitcoin. 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. Using a similar approach, Cambridge in 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.
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. In the latter case Bitcoin miners have historically ended up using fossil fuel based power which is generally a more steady source of energy.
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 , Gigajoules of energy from various sources globally for all its operations. We also know VISA processed 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 note that the chart below compares a single Bitcoin transaction to , VISA transactions.
The carbon footprint per VISA transaction is only 0. 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.
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. The only downside is that there are many different versions of proof-of-stake, and none of these have fully proven themselves yet. Nevertheless the work on these algorithms offers good hope for the future.
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.
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.
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 latter index was based on the alternative methodology provided by Bevand which is strongly advocated by Koomey , but failed to produce significantly different estimates. Apart from the energy consumption estimates, the resulting environmental impact in the form of carbon footprint has also been strongly contested by critics like Robert Sharratt and the company Coinshares. Specifically, Sharratt used the Coinshares mining report to argue that the network has limited environmental impact.
This is an important omission, as it ignores that the carbon intensity of electricity bought in Sichuan China , where miners are primarily located according to Coinshares, is nowhere near as low as one might expect. Of course, the Bitcoin Energy Consumption Index is also very much a prediction model for future Bitcoin energy consumption unlike hashrate-based estimates that have no predictive properties.
At the moment January , miners are spending a lot more on electricity. This can happen after a significant drop in mining revenues where mining becomes generally unprofitable. In this situation machines are removed from rather than added to the network. Annualized Total Footprints Carbon Footprint. Electrical Energy.