Product

2022 Wrapped: A Year In Product

December 6, 2022

As 2022 comes to a close, here at Sylvera we’ve been reflecting on the incredible year we’ve had and the people that have made it possible, from our team to our partners and customers. The start of the year marked the close of our Series A round, where we secured $32 million from organizations who believed in our mission to be a source of truth for carbon markets. Other key developments included increasing our ratings coverage and building new, rigorous methodologies for ARR, IFM and renewables carbon projects, which will give carbon credit buyers much-need transparency and insights into the voluntary carbon markets (VCMs).

More ratings and more project types

For every project category, we create individual frameworks to assess carbon credit quality. It takes a lot of time, testing and refinement, but is absolutely worth it in order to produce the most accurate ratings. Currently, the largest category of carbon credits is nature-based solutions (NBS), which account for 45% of the voluntary carbon markets (VCMs). Compared to technology-based solutions (TBS), NBS come at a lower cost and already exist at scale. This is why Sylvera started rating these project types first, specifically starting with REDD+ in 2021. We’ve now scaled to cover ARR, IFM and also Renewables credits. We’ve also expanded the registries that we cover in our platform to include Verra, Gold Standard, Climate Action Reserve and the American Carbon Registry.

Spotlight on benefit sharing: Sustainable Development Goals (SDGs) and accreditations 

At the start of the year, we enriched the commentary we provide for every rated project. This enabled customers to view both a summary of the overall rating and subscores, as well as an in-depth project analysis complete with relevant data visualizations, animations and interactive maps. 

For every project we rate, we now include the associated primary and secondary SDGs in the project assessment. Why does this matter? In addition to understanding the true carbon impact of a particular project, buyers are increasingly interested in understanding the co-benefits - mainly the impact on communities and biodiversity - to ensure their investments align with their broader climate strategies. These co-benefits are especially relevant to nature-based solutions (NBS). When NBS are well designed and maintained, they can bring many positives beyond the primary metric of storing and sequestering carbon. However, a poorly designed project can have a large negative impact on local communities and biodiversity. It is encouraging that more and more buyers value and seek out projects with legitimate co-benefits.  

We recognize that many organizations also use various accreditations as a benchmark for investing in credits. In our platform, we tag two accreditations from Verra: the Sustainable Development Verified Impact Standard (SD VISta) and the Climate, Community & Biodiversity (CCB) Standard

By surfacing this information alongside the assessment of quality, we’re helping buyers more easily identify high-integrity projects with strong co-benefits, which is critical to mitigating both climate change and the biodiversity crisis we’re facing.

Machine learning meets interactive maps

When analyzing carbon projects, Sylvera utilizes machine learning (ML) and multiple types of satellite data to identify specific features of forests and land cover. Utilizing ML allows us to see what is occurring within project areas (PA) at scale. Rather than manually sampling small areas within a project – which is time-consuming and less precise – we can assess whole project areas, located anywhere in the world. In order to have the most accurate output from our ML models, we train proprietary models in specific biomes and geographies, which are used for different carbon project types.

For example, if we are trying to assess forest growth in an afforestation, reforestation and revegetation (ARR) project, we will use ML to estimate the canopy height of trees in the project area (PA). To do this, we train a model to identify forest canopy height by feeding it tens of thousands of labeled data points. Then we run our models on the PA to estimate the canopy height. By running the model over the same area with data from multiple years, we can see changes over time in the forest area.

We customize our map widget to showcase our ML output for every project, so users are able to see how canopy height or forest coverage has changed over time.

Layering in IBAT data

We have enhanced our map functionality to include biodiversity data provided by IBAT (Integrated Biodiversity Assessment Tool), the world's most authoritative biodiversity dataset, which covers 271,088 protected areas and 16,356 key biodiversity areas (KBA). Key Biodiversity Areas (KBA) are sites that contribute significantly to the global persistence of biodiversity in terrestrial, freshwater and marine ecosystems. Sylvera users are able to see how a project relates to protected areas and key biodiversity areas.

Price and quality comparisons side-by-side

Earlier this year, through our partnership with Xpansiv CBL – the world’s largest carbon credit exchange – we launched the ability to view pricing of carbon credit projects. Up until this point, buyers and traders of carbon credits couldn’t easily compare the price and quality of carbon credits in one place. This made it difficult to know the true value of their investments, and whether or not they were driving capital toward high-quality carbon projects. 

So, what does our price vs. quality comparison reveal at the moment? Currently, there’s little correlation between carbon credit quality and carbon credit price in the VCMs. There are also large variations in carbon credit prices. But we believe in time with better data and more transparency into carbon project integrity, prices will begin to align with quality. 

Incorporating N-GEO Pricing

N-GEO is one of the most frequently traded futures contracts on the Xpansiv platform. This allows buyers to access standardized offset credits through the cleared futures market. 

The N-GEO contract tracks AFOLU (Agriculture, Forestry & Other Land Use) projects from the Verra Registry with the CCB (Climate, Community and Biodiversity) accreditation. Issuance vintages 2016 to 2022 are currently eligible for delivery into the N-GEO contract. The price reflects the 10-day volume weighted average price for trading data from the previous 10 days. 

Looking ahead to 2023

We have an ambitious roadmap that extends through next year, which will expand our ratings coverage and platform functionality. For example, we’re in the process of building unique frameworks for Direct Air Capture, Biochar, Cookstoves and Jurisdictional REDD projects, which we aim to launch early in 2023. We’re also developing exciting partnerships that will help us enrich our data and insights, and most importantly, amplify our impact by helping organizations better align their carbon reduction strategies and offsetting activities while ensuring the quality and integrity of carbon credits.

We anticipate a lot of developments and possibly even a few curve balls in the carbon markets in the year ahead. Hopefully, this time next year we’ll be on our way out of the wild west and into a more stable environment. One thing we can promise is that Sylvera will continue to keep you informed and up-to-date with all these changes through our newsletter: “Unlocking Carbon.” Sign up below to stay in the know.

Get up to speed with "Unlocking Carbon"
Subscribe to our newsletter to get fresh insights and news on all things carbon markets.
Thank you!
Oops! Something went wrong while submitting the form.

Get up to speed with "Unlocking Carbon"

Sign up to our newsletter for the latest carbon insights.

Thank you!
Oops! Something went wrong while submitting the form.
About the author
Senior Product Manager

Rani Shah is a Senior Product Manager at Sylvera. She has 5+ years of experience of product management in financial services (Barclays) and telecoms (BT) working in data, API and innovation teams both in London and South Africa. She studied Economics at the London School of Economics.

Connect