Sylvera works by applying machine learning to satellite data from a variety of sources
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Spotted: Carbon offsetting, essentially paying for others to reduce emissions or absorb CO2 to compensate for your own emissions, has gotten a bad rep. This is because it doesn’t really seem to work, except as a form of greenwashing. There are many reasons for this, but the main ones are that it is very difficult to measure the exact reductions of individual projects and the process often lacks transparency. A recently launched platform, Sylvera, hopes to change this with a process that makes offsetting more accurate and transparent.
Sylvera works by applying machine learning to satellite data from a variety of sources. The data is analysed to provide a more accurate analysis of carbon levels from different offsetting projects. The projects are then rated using a similar system as credit scoring, where scores are given from AAA (good) to D (bad). Scores are determined using the carbon performance of the project as well as the potential risks to the project. The platform also allows businesses to see ratings from a range of projects, to compare their relative efficiency.
Because Sylvera measures a variety of metrics, including raw carbon performance, additionality, permanence, co-benefits and risk, it offers a more effective and transparent model for measuring the levels of carbon that are actually offset. This is important because the carbon offset market may be on the brink of a major boom. According to the Taskforce on Scaling Voluntary Carbon Markets, the offsetting market is poised to grow 15-fold by 2030. This is likely why Sylvera raised $7.8 million in its recent seed round.
Sylvera co-founder Sam Gill became interested in the project after “accidentally” taking part in a carbon offsetting project and finding the process needlessly complex and vague. He pointed out that, in addition to complex documentation often stretching to hundreds of pages, “[Carbon offsetting performance] is …monitored using manual sampling techniques — which are often small sampling plots — and are extrapolated to represent the entire project.”
Many of the players in the sector agree that better data is vitally important to helping businesses make more environmentally friendly decisions. This explains why Springwise has seen a growth in innovations related to carbon capture, such as small, individual carbon capture devices and nature-backed financial instruments.
Written By: Lisa Magloff