Summary. The Cambridge Centre for Carbon Credits is an initiative I started with Andrew Balmford, David Coomes, Srinivasan Keshav and Thomas Swinfield, aimed at issuing trusted and verifiable carbon credits towards the prevention of nature destruction due to anthropogenic actions. We are using a combination of large-scale data processing (satellite and and sensor networks) and decentralised Tezos smart contracts to build a carbon marketplace with verifiable transactions that link back to trusted primary observations.
In around 2019 Srinivasan Keshav joined the Cambridge Computer Lab from Waterloo, and we got chatting about ways that computer science could be applied to helping our colleagues in conservation with their quest to improve nature-based solutions (both deforestation and rewilding efforts). We wrote down our initial thoughts with some colleagues in How Computer Science Can Aid Forest Restoration and ran a summer UROP set of projects (writeups here) which had to be done remotely due to the 2020 lockdown.
Later during the pandemic, Srinivasan Keshav and I joined up with Andrew Balmford from Zoology and David A Coomes and Thomas Swinfield from Plant Sciences and the Cambridge Conservation Institute to establish a centre dedicated to combining classic topics from computer science (big data processing, reproducible computation and distributed consensus) to the pressing problem of issuing trusted and verifiable carbon credits towards the prevention of nature destruction due to anthropogenic actions. Our centre was announced later in 2021 officially.
Relevant Ideas
- Legal perspectives on integrity issues in forest carbon
by Sophie Chapman cosupervised with Eleanor Toye Scott in 2024 (Ongoing). - Meta Properties of Financial Smart Contracts
by Derek Sorensen cosupervised with Srinivasan Keshav in 2023 (Completed, PhD). - Making GPS accurate in dense forests using sensor fusion
by Keshav Sivakumar cosupervised with Srinivasan Keshav and David A Coomes in 2020 (Completed).
Relevant Papers
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[»] Mitigating risk of credit reversal in nature-based climate solutions by optimally anticipating carbon release |  |
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[»] PACT Tropical Moist Forest Accreditation Methodology v2.1 |  |
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[»] Nature-based credit markets at a crossroads |  |
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[»] LIFE: A metric for quantitatively mapping the impact of land-cover change on global extinctions |  |
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[»] Global, robust and comparable digital carbon assets |  |
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[»] Realizing the social value of impermanent carbon credits |  |
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[»] Credit credibility threatens forests |  |
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[»] How Computer Science Can Aid Forest Restoration |  |
Relevant Talks
Leveraging Scientific Innovation and AI to Scale Carbon Markets on 7th Mar 2023. On stage with Mantle Labs discussing carbon credits. Part of the Trusted Carbon Credits project.
Financing Forests: A Credible Approach towards Halting Tropical Deforestation on 16th Nov 2022. Cambridge Computer Lab Wednesday seminar on tropical deforestation. Part of the Trusted Carbon Credits project.
News Updates
» Discuss the NbS risks paper.
» Comment on nature-based credits published in Nature Sustainability / «» Discussion on the nature-based credits article / «» Tropical Moist Forest v2.1 specification released / «» Paper on ex-ante projection for nature-based solutions.» LIFE biodiversity paper accepted for publication later this year.» Preprint on forecasting nature based project risk.» Tropical Moist Forest v2.0 specification.» Preprint on new LIFE metric for global biodiversity / «» Paper on valuing impermanent carbon credits at Nature Climate Change, with cam.ac.uk coverage.» Preprint of paper on valuing impermanent carbon credits.» Published Tropical Moist Forest v1.0 specification.» Perspective in Science on carbon credits credibility.
» Discussion with Mantle Labs about carbon credits.» Wednesday seminar on financing forests using carbon credits.
» Quoted in Vox article on carbon credits.» Started maintaining (sporadically) a note on a forest preservation and restoration bibliography.» Preprint about our working notes on how CS might contribute to forest preservation.