I wrote the Blockchain vs Climate Change series of articles to achieve the following:
- Explore applications of DLT to reduce GHG emissions and therefore their impact on climate change
- Educate on the commercial and social opportunities presented by these applications
- Spark conversation and debate around these and adjacent ideas
- Inspire readers to experiment with the proposed applications to ultimately realise the described benefits
Throughout the series I have covered 15 applications where I believe blockchain has a valid value proposition that, if correctly applied, will more likely than not result in a reduction in GHG emissions in the area described. These have covered a broad range of applications across transport, power, land use, cities and industry, and I hope that as a reader you have extracted value and relevance from at least a handful of these use cases.
One of the common themes across these applications is the incentivisation of data sharing that can be enabled by a blockchain-based system. High availability of data is crucial for enabling many of the ML-based models described in the inspiration of this series — Tackling Climate Change with Machine Learning. It should be noted that Google recently announced its Dataset Search which is the beginning of common data sharing in addition to the widespread practice adopted by academia for decades. An acceleration of this behaviour will be critical in realising the benefits of ML applications to reduce the impact of climate change.
Despite listing many applications as Short Term time horizon implementations, blockchain still has a long way to go before it can be implemented at widespread production scale. I covered this topic in a recent article which ties in well with another publication written by the team at Vakt which is well worth a read. It will take time but the technology is well on its way to making some of these applications, and the described benefits, a reality.
Use the links below to navigate to the other sections of the series: