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A Buyer’s Guide to Carbon Credit Data Quality

Introducing new tools for buyers to play an integral role in scaling a high-quality Voluntary Carbon Market
Building Buyer Confidence in the VCM

In recent years, the Voluntary Carbon Market (VCM) has emerged as an innovative carbon financing mechanism to complement direct decarbonization (i.e., a business taking action to reduce the emissions associated with its operations) because it provides an opportunity for private parties to buy, sell, and invest in carbon credits tied to avoided, reduced, or removed greenhouse gas (GHG) emissions. The VCM is a critical financing tool to enable critical climate action, such as scaling decarbonization technologies, rehabilitating or protecting critical ecosystems, and enabling a just transition and alternative livelihoods for Indigenous Peoples and Local Communities.

Buyers of carbon credits have been integral to the VCM’s rapid evolution, though many are asking for better guidance and clarity so they can be more confident in their credit purchases and buying strategies. A handful of large companies have embraced a leadership role in building an effective VCM by committing tens of millions in advanced purchase commitments to signal market demand for carbon removal and high-integrity nature-based credits. Other buyers have faced public criticism, or worse, based on allegations that the purchased credits have not delivered the climate impact that the buyers claimed. These dueling experiences can be seen in a rapid surge, and recent turbulence, in market activity (spiking from $320 million in 2019 to $2.1 billion in 2021; then dropping to $723 million in 2023). This turbulence can be attributed, in part, to the complexity, inefficiency and opacity of carbon crediting data in the VCM.

If buyers were entering a well-functioning market, they would be able to access granular, high-quality data about each crediting project’s real-world performance (i.e., emissions removed/reduced/avoided and potential community impact) and use that information to customize a credit portfolio that best fits their individual climate preferences, risk tolerance, and resource constraints. Such granular crediting data would help buyers build confidence in their ability to use high-quality carbon credits as a component of a broader decarbonization strategy.

Unfortunately, the VCM data landscape is fragmented, complicated, and opaque – making it difficult for market actors, including buyers, to quickly and confidently identify and value high-quality carbon credits (see RMI and Climate Collective’s VCM Landscape Guide for more on the current state of the market). This carries significant implications for current buyers: the fragmented data landscape increases the perceived riskiness of carbon market transactions and puts the onus on buyers to design and conduct their own rigorous due diligence into carbon crediting data (and thus carbon credit quality). This adds cost, time, and uncertainty at a time when we are short of all three.

Introducing RMI and Climate Collective’s Buyer’s Guide to Carbon Credit Data Quality

Launched on June 20, 2024, RMI and Climate Collective’s Buyer’s Guide to Carbon Credit Data Quality presents an actionable, analytical framework to help buyers think about how to find, compile, analyze, and test carbon crediting data in this complicated data landscape. The framework is designed to help buyers both understand how to identify the high-quality data that signals high-quality credits and gain their own familiarity and confidence in finding and testing high-quality data. This framework complements efforts from leading governing institutions, including the Integrity Council for Voluntary Carbon Markets (ICVCM), the Voluntary Carbon Market Integrity Initiative (VCMI), and the Biden Administration’s seven principles for high-integrity VCMs to clarify what counts as a “high-quality” carbon credit and how buyers can use, or claim, carbon credits. It can also operationalize the seven principles for high-integrity VCMs recently announced by the Biden Administration.

If you are a buyer at the critical “investigate” stage, when you are trying to discern which projects and credits will meet your sustainability strategy and quality goals, then this guide is for you. This guide focuses on carbon crediting data quality, which is a vital component of all high-integrity credits.

Exhibit 1: The six stages of the buyer’s purchasing journey

This guide helps buyers answer the technical and data-driven questions that inevitably shape credit purchasing decisions. Nearly all buyers want credits that are “additional” (meaning, projects that would not have happened without carbon finance or achieved GHG benefits without revenue from the sale of carbon credits), “durable” (have a lasting climate impact), and beneficial to local communities or ecosystems. But what information do buyers need to vet whether the credits have a verified additionality impact on emissions? Or that the credits will indeed perform, as expected, over time? They can do this by “looking under the hood” of the project’s crediting data (see Exhibit 2).

Building and Testing a Carbon Crediting Data Package

This Buyer’s Guide gives buyers an actionable, analytical framework to use to find, compile, analyze, and test carbon crediting data so that buyers can anchor their due diligence processes around processes around high-quality data and high-quality credits. This framework is anchored by building and testing a “carbon credit data package” (see Exhibit 2).

Exhibit  2: Building and testing a carbon crediting data package

Source: RMI & Climate Collective Buyer’s Guide to Carbon Crediting Data

A carbon crediting data package refers to all information within a project that indicates whether the credits are achieving their stated carbon and co-benefit impacts (i.e., verified emissions reduced, removed, or avoided, and social and ecosystem benefits achieved). The guide describes how to:

  • Build a data package: The guide describes the type of information that should be in a data package and provides specific guidance on which information to find in the registry databases, which to request directly from project developers, and which to consider purchasing from service providers in the market.
  • Test the trustworthiness of the data collected: Nearly half the guide is devoted to three testing tools that help buyers determine whether the crediting data they’ve collected is trustworthy (see Exhibit 3).

Exhibit 3: Testing tools to identify high-quality crediting data

Source: RMI & Climate Collective Buyer’s Guide to Crediting Data Quality

These testing tools walk buyers through which indicators, metrics, and questions indicate the desired project’s data credibility (whether the crediting data reliably captures the credits’ climate performance), data efficiency (whether the data can be efficiently shared with and analyzed by market actors)​, and project governance (whether the data can be independently verified and securely managed by the project’s operations).

  • Use the data package framework to identify high-quality credits: These tests are designed to be conducted separately but analyzed collectively. The guide helps buyers think about the perceived riskiness or quality of projects that struggle across all three tests or that perform well on some tests and poorly on others.
  • Stay updated on trends and innovations in carbon crediting data: The guide concludes with descriptions of the critical market dynamics and actors who are instrumental to shaping the carbon crediting landscape.

The Voluntary Carbon Market is undergoing a necessary but complicated transition. Market stakeholders are working to improve its ability to identify and value credits with a verifiable positive impact on combatting climate change and empowering local communities. With the tools presented in the Buyer’s Guide to Carbon Credit Data Quality, buyers can be empowered to play an integral role in shaping this transition and scaling a high-quality VCM.