Nature-tech company Revalue has secured the highest Sylvera assessment score for its new model for carbon credits generated through avoided deforestation.
This milestone promises a brighter future for avoided deforestation carbon credits, which have experienced a drop in confidence and market price following scrutiny and questions around their overall effectiveness.
Revalue’s new system, called Model R, implements various sophisticated components to ensure integrity and carbon measurement accuracy in avoided deforestation activities.
Following a standard independent evaluation process by carbon data company Sylvera, Model R received the highest assessment score of any other avoided deforestation models so far, ranking among the best removal approaches out there.
Avoided deforestation refers to activities that prevent the loss of existing forests that clean the air of CO2 pollution. To provide a more in-depth and precise measurement of the carbon credits generated by it, Revalue employed a set of comprehensive tools.
Its Model R replaces static deforestation prognoses with dynamic baselines built on more frequently updated, real-world data. The model establishes control forest plots, where it uses machine learning, satellite imagery, and field insights to measure the project impact.
Powered by LiDAR laser scanning, the model builds 3D maps of forests that allow for better biomass measurements, making sure every tonne of CO2 removed is backed by verifiable data.
It combines machine learning with earth observation data to evaluate the deforestation risk, taking into account factors like new roads or land-use pressure.
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With each batch of issued credits, the model reassesses the project effect, ensuring ongoing monitoring and proof of impact. Model R also tracks the ecosystem changes through environmental DNA (eDNA) and bioacoustics, detecting species that might otherwise go unnoticed.
When it comes to local communities, Revalue’s approach conducts surveys with robust sampling and analysis methods, gaining a better grasp on the project’s social outcomes.
Lastly, the Model R deforestation avoidance carbon credit approach has a climate impact buffer, where each credit targets more than 1 ton of avoided CO2, creating a protective guard against over-crediting.
