Plattsburgh, NY made headlines this week by banning cryptocurrency mining. But what is it, and why would an entire town ban it?
Bit Mining, or cryptocurrency mining, is a form of transaction validation that is conducted by independent sources. Individuals and businesses have created cryptocurrency mining “farms” where high-powered computers solve mathematical equations within the transaction. The main appeal of cryptocurrencies is that they are decentralized, and mining adds another layer of security because the these validations ensure the same token is not fraudulently spent.
Validation of these transactions (called blocks) has become very popular because miners receive “block rewards” in the form of digital token payments, and those rewards can be very lucrative. Currently, the reward for solving a bitcoin block is 12.5 bitcoin, a value of $119,000.
However, mining comes at a high price that many local cities and governments did not expect – electricity usage.
The power required to solve these mathematical equations and validate the transactions is enormous. The strain it has been placing on the local power grid is the reason Plattsburgh made a move to ban the activity for the next 18 months while they evaluate the problem. The processing power required was using 10% of the city’s power supply and driving up their costs astronomically.
And they are not alone.
Chelan, Washington banned mining activity in residence for six months. China has been actively ridding itself of Bitcoin miners, which has already dramatically affected the currency. Quebec, however, has encouraged cryptocurrency miners because they have enough power to handle the job. How other cities and nations handle this emerging problem will define the future of cryptocurrency.
For reference, it is estimated that cryptocurrency miners will use 54 terawatts of energy per year as they validate these digital transactions. The nation of Israel uses 56 terawatts of energy per year. The power required is staggering, and it’s an unexpected pitfall of cryptocurrency mining.