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New Carbon At Risk Framework Aims To Standardize Permanence Risk Across CDR Technologies

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New Carbon At Risk Framework Aims To Standardize Permanence Risk Across CDR Technologies

A group of researchers from established organizations has released a new framework that aims to standardize the measuring of permanence risks across different carbon dioxide removal (CDR) technologies. 

Inspired by “Value at Risk” in financial markets, the researchers called the framework Carbon at Risk (CaR), presenting a new asset that can be helpful to CDR buyers, investors, and regulators. 

As explained by the authors, the framework is a probabilistic measure of the shortfall between contracted removals and realised storage at a given confidence level and time horizon.

Identifying a lack of a standardized, quantitative measure of permanence risk in today’s carbon markets, the researchers joined forces to create a toll that will address exactly this issue. 

The resulting CaR methodology provides a technology-agnostic basis for risk-calibrated buffer sizing, insurance pricing, and reserve-fund design, over both policy- and climate-relevant scopes. 

The researchers behind this work share that carbon removal markets currently lack a well-understood and continuous probabilistic metric that can anchor risk management across regulators, buyers, insurers, and investors. 

Instead, the authors explain, CDR projects are conventionally sorted using qualitative labels such as permanent versus nonpermanent or nature-based versus engineered, sometimes supplemented by buffer-pool approaches whose sizing is only weakly linked to quantified risk.

“These heuristics can be useful for first-pass screening, but they do not quantify the probability, magnitude, or timing of under-performance. The result is distorted capital allocation,” CaR creators say.

Relevant: Relae, Microsoft Publish New High-Quality CDR Criteria, Addressing Delivery Risk For The First Time

Developed through a series of workshops between academics and industry stakeholders, the methodology is defined as a probabilistic measure of downside risk for promised storage: the risk that realised storage falls short of what was contracted.


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