The platform is based on Hyperledger Fabric, an open-source blockchain-based carbon management application developed for enterprises.
IBM says its product, a joint effort with Chinese company Energy-Blockchain Labs, will facilitate carbon asset development, also known as CER (carbon emission reduction) quota issuing, intended to encourage enterprises to decrease emissions and use low carbon emission technology.
“It is estimated that the platform will significantly shorten the carbon assets development cycle and reduce the cost of carbon assets development by 20 to 30 percent, enabling cost-effective development of a large number of carbon assets,” said Cao Yin, chief strategy officer of Energy-Blockchain Labs, in a statement. “Blockchain technology is expected to become an important means for effective control of carbon emissions, which is of great significance to China, the world’s largest source of carbon emissions.”
The two companies completed a proof of concept in late 2016 and will release a beta version of the carbon asset management platform on blockchain in May. Energy-Blockchain Labs and IBM say they intend to commercially offer this platform later this year, in line with China’s unified national carbon market opening.
IBM is positioning blockchain technology as a solution to reduce enterprises’ carbon emissions, Cryptocoins News reports.
Smart contracts-enabled digital collaboration over a common ledger will push to improve the efficiency of carbon assets development and management. Just as significantly, blockchain’s core characteristic as an immutable ledger will bring credibility to the carbon emission reduction market, IBM contends. Increased transparency and straightforward auditability that will sit well with regulators are yet more reasons to use blockchain technology in the carbon market.
The project, in partnership with the Dublin City University (DCU) Water Institute, will leverage Internet of Things technologies for environmental monitoring and management. It will deploy DCU sensors with IBM’s machine learning and cognitive IoT technologies and aims to help protect and conserve natural resources while addressing environmental management issues such as water quality for both freshwater and marine environments.