The environmental impacts of blockchain technology in the context of international trade; Determining the relationship between Bitcoin and carbon footprint using the Bayesian method

The present study was intended to explore blockchain technology regarding relevant application areas and environmental impacts within international trade. We traced the ecological impacts of the mentioned technology through the data of carbon dioxide (CO2) emission data pertinent to Bitcoin (BTC) mining-related variables that ensure the addition of new blocks to the blockchain as well as its security: miner efficiency (eff), miner revenues (rev), the total number of BTC mined daily in circulation (tran), difficulty as a measure of the effort to validate a block in blockchain technology (difficulty), and estimated hash rate by the BTC network (hash rate). Our estimation findings of the Bayesian Vector Autoregression (BVAR) model showed that BTC itself and difficulty significantly affect BTC CO2 emissions but that the other mentioned variables did not significantly predict the emission values. The devices deployed in mining activities and the number of miners with the system contribute to the difficulty value. Given that most BTC miners rely on fossil fuels as energy sources, an inflated difficulty is thought to lead miners to deplete more energy and, thus, increase CO2 emissions. Overall, deploying more efficient mining devices with novel algorithms and methods is more likely to bring energy savings for environmental concerns. In addition, the widespread utilization of lower-cost, renewable, and clean energy sources (e.g., solar and wind energy) in blockchain technology may be an alternative approach that will help reduce the detrimental environmental impacts of fossil fuels.